 |
|
Newsletter of HoloGenomics
|
|
|
|
Newsletter of HoloGenomics
|
Genomics, Epigenomics integrated into Informatics:
HoloGenomics
HoloGenomics for a Song (read Lyrics of Regulatin' Genes)
view YouTube-s
Regulatin' Genes YouTube
NOW BEYOND 150,000 VIEWS
Skip to HoloGenomics Table of Contents
For HoloGenomics News articles before 2010 see Archive here.
Archives before Hologenomics (before mid-2008) are listed in Archives, bottom here.
 |
Eric Lander (Science Adviser to the President and Director of Broad Institute) et al. delivered the message
on Science Magazine cover (Oct. 9, 2009) to the effect:
 |
For archived HoloGenomics News articles before 2010 click here.
Articles before Hologenomics (before mid-2008) are listed in Archives, bottom here.
Genome Informatics, Globalized; - USA - China - Korea - India
Francis Collins (in Bangalore)
How much does the US spend on medical research?
Typically, the NIH invests $30 billion every year. But I should say the budget's been about there for almost eight years. We're having difficulties in fiscal deficit, so medical research may not grow much in the near future. Thoughtful decisions have to be taken on what we want to do.
What strengths do you see in Indian institutions? How are they compared to China?
India's great strength now is its IT and computational capacity. Biology is now more a computational science. To understand diseases like diabetes and cancer, we need computational strategies to sift through vast datasets. India can provide that asset.
India is on right track for biomedical research, says NIH director
Date:2011-12-05houhaizhen
Bangalore, Dec 05, 2011: Currently on a tour of India to improve collaborations between research institutes in India and the NIH, Dr Francis Collins, director, NIH, USA, spoke about the impact NIH funding has had on research in India and how it intends expand its presence in India.
National Centre for Biological Sciences (Bangalore)
Francis Collins in Bangalore
--
Andras Pellionisz, Board of Advisors to ELOGIC Technologies in Bangalore, tours Bangalore, Hyderabad, Trivandrum
China excels in Genome Informatics by running in BGI (Shenzhen) the World's largest capacity of Genome Sequencing Machines (all USA-made), and employing up to 4,000 computer scientists, with an every age of 27, with access to the World's fastest supercomputers (a hybrid of Intel serial chips and NVIDIA graphics parallel chips, all USA-made). Korea announced by Sept. 1, 2011 that SAMSUNG started to provide a Global Genome Analytics Service.
India's strengths, as Francis Collins pointed out in Bangalore, to deploy her massive IT and mathematics expertise towards personalized therapy against cancer, combined with clinical trials.
Andras Pellionisz, his science presentation featured above in Hyderabad, builds collaborations of Silicon Valley of California with "Silicon Valley of India"; Bangalore.
UNESCO’s Memorial Year Honours János Szentágothai
[János Szentágothai - AJP]
As decided by the general assembly of UNESCO, the year 2012 is to be dedicated to honour the 100th birthday of János Szentágothai, a formal president of the Hungarian Academy of Sciences and a groundbreaker in his field. According to Ambassador Katalin Bogyay, the memorial year provides a unique opportunity to showcase the achievements of Hungarian science and Hungarian culture in general to a wider audience through the legacy of the great Hungarian scientist.
UNESCO has long been taking part in commemorating the anniversaries of historical events and outstanding personalities. The national committees of the organisation may make such proposals each year. Headed by member of HAS József Hámori, the Hungarian National Committee initiated a Szentágothai Memorial Year, a proposal supported by the Jury of Experts and the Executional Council and finally was accepted by UNESCO's General Assembly.
"According to my plans, an exhibition and conference are going to be organised commemorating the greatness of János Szentágothai in the centre of UNESCO in Paris. Through introducing his life to an international audience, we are to bring the achievements of Hungarian science into the forefront, while also drawing attention to the responsibility of science and to the connection between science and art", Katalin Bogyay said. "As a Christian thinker and music teacher Franz Liszt had been an ambassador of Hungarian culture in his age, so was János Szentágothai committed to both science and art, a true renaissance man of Hungarian intellectual life."
"János Szentágothai was a real founder of a school of thought. We, today's Hungarian brain researchers, are all standing on his shoulders", former student József Hámori said. Member of HAS and President of the Hungarian UNESCO Committee, professor Hámori started his career at the Department of Anatomy of Pécs University in 1955 where János Szentágothai had established a research community whose members not only improved in expertise but also had the chance to enrich the spiritual-cultural aspects of their personalities. "We worked from 9 am. until late evening every day, but were not doing science exclusively", József Hámori recalls. "The art of painting, baroque music was just as often the topic of our discussions as was poetry." However it was his findings in brain research that had earned him world fame. Among these were his results on the functions of the spinal cord, the cerebellum, and the structure of the neocortex, making him a Nobel-prize nominee several times.
Besides being an avid researcher, János Szentágothai had great affection for teaching and always encouraged his students to pass on their knowledge. He considered education as a crucial aspect of science, not only for the sake of the next generation, but also because he believed it's the perfect way for teachers to keep their knowledge up-to-date. Professor Szentágothai authored Functional Anatomy and the Atlas of Human Anatomy with Miklós Réthelyi and Ferenc Kiss respectively.
János Szentágothai was the President of the Hungarian Academy of Sciences between 1977 and 1985. Besides holding several national awards, he was also a member of many international organisations, such as the Royal Society, and the Papal Academy of the Vatican. He was an honorary doctor at several universities, among them the University of Oxford. Professor Szentágothai also played a significant role in the public life of Hungary. He was a representative of science in the Hungarian Parliament until his death in 1994.
[Why was Prof. Szentágothai passed over for Nobel Prize? - AJP]
The simple answer is that the Nobel Committee did not vote him in. At what rate and why not, is only guesswork, since the Minutes of the Committee are classified for 50 years.
As a pupil of the “Szentágothai school” since 1967, my belief is that the reason might be that the “Grand Old Man” thought and acted in terms of “Schools of Science”, not limited to that of his own. For the Nobel Committee, however, it is much easier to award the Prize to focused efforts, especially since the Science Prizes are to be awarded to living persons, divided at a maximum to three people.
Prof. Szentágothai built his school of science to a large degree on that of the schools of “vestibulo-ocular cerebellar systems” of Drs. Bárány, Hőgyes and Lenhossék – wherein Dr. Bárány was already some time ago awarded by the Nobel Prize. In itself, this could not be a major problem, as both Drs. Kornberg and his son were awarded. In Szentágothai’s school, like in all schools of excellence, there was more than a single eminent course.
There seems to be no doubt that the legacy of Hungarian schools of science, and the international schools of science that Prof. Szentágothai built a solid alliance with, made the cerebellar sensory-motor system a pre-eminent focus of his ouvre – with the cerebellum making up to 1/3 of the brain with birds top make them capable of coordinated flight.
By 1967 János Szentágothai was about ready with the proof of their Springer book, co-authored with the leading British-Australian-American Sir John (Eccles) Nobel Laureate and Japanese Masao Ito. The title was “The Cerebellum as a Neural Machine”. This splendid accomplishment could have been the reason for János Szentágothai NOT having been awarded by a Nobel. Why? The bestseller book, according to Google Scholar under “Eccles” was cited 2,117 times – that is far more than any citation of Szentágothai’s own publications (highest is 472, often in different fields). Thus, it could be difficult to award a Nobel for the authors of the book, divided to the maximal three allotted recipients who might share the Prize. For one issue, this would have been the second Nobel to Sir John (Eccles). Not impossible, for the precedents of double Laureates. However, the electrophysiology of the cerebellum, comprised in the book, was the result of cardinal collaborative effort with Rodolfo Llinás and other colleagues, and similarly the electronmicroscopy laid out in the book was performed largely by József Hámori. Third, the contribution to the book by the Japanese Masao Ito was his flabbergasting discovery that the sole output of the cerebellum, from the Purkinje neurons, are inhibitory (as opposed to the expected excitatory action). The book on the “Neural Machine” simply could not interpret this experimental result. As a conclusion, on the very last page of the book (pp. 177.) the main three authors, altogether at least five individuals, over the limit of maximal three for any Nobel, confessed in effect that “we know everything about the neural networks of the cerebellum, except how it works as a Neural Machine”. The Nobel Committee could have wondered about the best stance towards a book that verbatim predicted by the last sentence of the book that “It is essential to be guided by the insights that can be achieved by communication theorists and cyberneticists who have devoted themselves to a detailed study of cerebellar structure and function. We are confident that the enlightened discourse between such theorists on the one hand and neurobiologists on the other will lead to the development of revolutionary hypotheses of the way in which the cerebellum functions as a neuronal machine and it can be predicted that these hypotheses will lead to revolutionary developments in experimental investigation”. Pondering over such a mesmerising conclusion, perhaps they thought that “there are too many authors now and the conclusion still awaits some time” and decided to reconsider any award for the function of the cerebellum later.
It is noteworthy that Szentágothai was ahead of his time far further than he could have ever envisioned. Springer is just proofing their handbook “The Cerebellum and Cerebellar Diseases”, in which a Chapter on Recursive Genome Function of Cerebellum: Geometric Unification of Neuroscience and Genomics” reveals that the mathematical “trick” of the cerebellum (a topic of neuroscience) is also found, in an even more profound manner, in genomics. The function of the cerebellum as a neuronal machine is to turn the independent, sensory-type motor intentions (that are mathematically covariant) into physically properly assembled motor-execution components (that are mathematically contravariant). This “invention” by mother Nature for the cerebellum is fairly recent in evolution – it only goes back to about 400 million years, when the sharks, equipped with the emerging cerebellum could outswim less coordinated competitors.
Szentágothai, who passed away in 1994, could not have known about “RNA interference” (discovered by Fire and Mello 4 years later, in 1998, to be awarded by Nobel in 2006). “The RNA system acting as a genomic cerebellum” (by both contravariant, cRNA and covariant ncRNA, by their interference comprising the metric of coordinated genome function) is a far more ancient invention about 530 million years ago by mother Nature; it resulted in the so-called “Cambrian explosion” in evolution, by enabling coordinated genome function of multi-cellular organisms.
Our beloved “Grand Old Man” (Prof. Szentágothai) would get truly excited, since he was the epitomy of scientific curiosity and its ultimate reward (understanding) - regardless of the destination of Prizes of any kind, if at all.
János Szentágothai, prof. of Semmelweis University Medical School, Budapest [at right], and András Pellionisz, prof. of New York University Medical School, New York [at left]]
Power in Numbers [math must grab genomics, beneath neuroscience – AJP]
[Eric Lander is right, again. In the video above, essentially he says: For genomics, the homework is to explain cerebellar brain function by its intrinsic math. This is exactly the strategy Tensor Network Theory (applied to Recursive Function of Cerebellar Neural Nets) and its Unification with the Fractal Approach to Genome Function followed. Lander skipped, for a number of reasons, the few decades I invested in “geometrization of neuroscience”– and Lander zoomed right into mathematization of genome (as it is “informatics”). While as a Science Adviser to the President, the US might follow his advice (“Mr. President, the Genome is Fractal!”) because of the inertia of the medical establishment countries with smaller legacy but faster growth in their GDP, plus mobilizing their mathematics-physics-engineering formerly honed to create their own nuclear industry, might even overtake the US in certain segments of “Industrialization of Genomics”. Fortunately, Dr. Lander is also schooled in economics – thus along with fellow Havard Professor economist Dr. Juan Enriquez (see his decade-old-bestseller “As the Future Catches You”) the US can maintain leadership in “Genome Based Economy”. – AJP]
“I took random classes in Harvard about the brain… To know about the brain, you have to learn about cell biology… to know about cell biology you have to learn about molecular biology… I have to know about genetics! “
“I began to appreciate that the career of mathematics is rather monastic,” Dr. Lander said. “Even though mathematics was beautiful and I loved it, I wasn’t a very good monk.” He craved a more social environment, more interactions.
“I found an old professor of mine and said, ‘What can I do that makes some use of my talents?’ ” He ended up at Harvard Business School, teaching managerial economics.
He had never studied the subject, he confesses, but taught himself as he went along. “I learned it faster than the students did,” Dr. Lander said.
Yet at 23, he was growing restless, craving something more challenging. Managerial economics, he recalled, “wasn’t deep enough.”
He spoke to his brother, Arthur, a neurobiologist, who sent him mathematical models of how the cerebellum worked."...
Paired Ends, Lee Hood, Andras Pellionisz - 2012 a Year of Turing and Year of Turning
January 1st, 2012
[Genomeweb - AJP]
Genomeweb paired us prompted by our respective press releases, signaling the general trend of new global alliances that bridge the USA to Asia. However, as 2012 begins, the Centennary Year of Alan Turing (born in 1912), some deeper analysis may be warranted. This Centennary year closes a decade of fierce struggle. It starting by the passing of Ohno (“Junk DNA” since 1972) in 2000, and Crick in 2004 (“Central Dogma” since 1956), ENCODE’s belated admission in 2007 that “Junk DNA is anything but”, and the Principle of Recursive Genome Function (paper and YouTube in 2008, Unification of Neuroscience and Genomics in print 2012).
This year may become another turning point in mathematical theory of genome function, with great advances in deciphering cancer, see the potential of Full DNA Sequencing (and Analytics) in cancer diagnosis and personalized therapy e.g. in this YouTube by Matthew Ellis (University of Washington in St. Louis).
A Decade ago (2002) both Dr. Hood and I went on our respective records with the notion that “Biology is an Informational Science”; see Lee Hood and Andras Pellionisz.
LeRoy Hood (2002), in his Commemorative Lecture acceptance speech of the Kyoto Prize in Advanced Technologies announced that he was writing a book on “The Living Code: Biology As An Informational Science” assuming Bertalanffy’s “General Systems Theory” (1956, Dover, New York) as his intellectual foundation.
Andras Pellionisz (2002) , for better or worse, specifically pointed out the mathematics intrinsic to genomes with his FractoGene (2002). The “Fractal Approach to DNA” – after the magical 7 years of silencing – is now boosted by the group of Eric Lander (Science Advisor to the President, featuring fractal folding of DNA on Science magazine cover issue, Oct. 2009 based on decades-old pioneering by Alexander Grosberg). Further, a Boston group of four (MIT/Broad/Harvard/Dana-Farber), with Leonid Mirny in both the 2009 paper and now, found in 2011 that “fractal defect” (in their case, a Copy Number Variation, CNV) blocked the see-through transparency of 3D Hilbert-curve, becoming the root cause of cancer.
My personal FractoGene (interlaced with Tensor Network Theory) is a lineage from relativistic tensor geometry brought into a synthesis of the quantum-theory-inspired-Schroedinger school of thought; Schroedinger, “What is Life?”, 1944). I was intellectually imprinted for life by the Hungarian Edition of John von Neumann “The Computer and the Brain” (1958), where on the last page von Neumann posthumously made a visionary statement. Von Neumann was tragically short-lived 1903-1957, quite possibly exposed to nuclear radiation while participating in the Manhattan-project, died of bone cancer. His statement was that whatever the intrinsic mathematics Nature uses in biological systems (notably in brain function) is certainly not the mathematics we know and that he used to create computers.
Perhaps the most revealing article is by Alan Turing, born a Century ago, who published a seminal article well over half a Century ago (1952), before the Double Helix was ever discovered, in 1952 (in Phil. Trans. R. Soc. Lond. B.)
“The Chemical Basis of Morphogenesis”. Its Chapter 13. was entitled “Non-linear theory. Use of Digital Computers”. Aptly, he wrote: “Most of an organism, most of the time, is developing from one pattern into another, rather than from homogeneity into a pattern. One would like to be able to follow this more general process mathematically also. The difficulties are, however, that one cannot hope to have any very embracing theory of such process, beyond the statement of the equations. It might be possible, however, to treat a few particular cases in detail with the aid of a digital computer”.
Neither Ludwig von Bertalanffy (1956), nor John von Neumann (1958) had time enough to specify the math intrinsic to coordinated genome regulation, in spite of early pioneering by Schroedinger (1944) predicting in his essay “What is Life?” that covalent Hydrogen-bondings over an aperiodical crystal (later to be found as DNA Double Helix in 1953), along with other pioneering by Norbert Wiener’s Cybernetics (1949) and the departure from war-time, having deciphered cryptography, to biology by Alan Turing (1952).
In view of the above, it would be grossly unfair to take the credit of a single decade of (2002-2012), despite all turf-protecting-below-the-belt-strikes by the few mathematically unseasoned, for the now prevailing notion that the sine qua non of progress is the software enabling intrinsic algorithm of genome informatics.
I was lucky enough to be exposed at the level of a personal friend to Edward Teller in his late years. Teller was Heisenberg’s Ph.D. student, with relativistic and quantum physics in his weaponry – and I was also inspired by Benoit Mandelbrot’s fractals - Mandelbrot was a Ph.D. student of John von Neumann.
Is the fact that the lineage of concepts of genome informatics has a clear parallel to war-time efforts of Relativity (published in final form in 1916) and quantum theory that made both peaceful (Leo Szilard) and strategic applications of nuclear industry possible (Heisenberg on one side and Turing, Teller, von Neumann, Wiener on the other)?
War-time efforts drained the best minds to lay down the exact (“bullet-proof”) intellectual infrastructure, as if developing an armor capable of deflating all flak, friendly or not. Mathematicians, physicists and nuclear engineers, having served their respective countries, moved in droves from physics to biology.
In 1971, Nixon declared his “War on Cancer”. Now, those whose experise leaves no question that the disease of the genome (with Genomics=Informatics) can only be won with mathematicians, information theorists and most of all, by computers deployed the bolster the infantry of traditional medicine will make sure that the “New War on Cancer”, forty years after the first, will have the needed weaponry developed and ready to use.
The genetic code, 8-dimensional hypercomplex numbers and dyadic shifts
[Excerpts]
Sergey V. Petoukhov
Head of Laboratory of Biomechanical System, Mechanical Engineering Research
Institute of the Russian Academy of Sciences, Moscow
spetoukhov@gmail.com, petoukhov@imash.ru,
http://symmetry.hu/isabm/petoukhov.html, http://petoukhov.com/
Abstract: Matrix forms of the representation of the multi-level system of molecular-genetic alphabets have revealed algebraic properties of this system. Families of genetic (4*4)- and (8*8)- matrices show an unexpected connections of the genetic system with functions by Rademacher and Walsh and with Hadamard matrices which are well-known in theory of noise-immunity coding and digital communication. Dyadic-shift decompositions of such genetic matrices lead to sets of sparse matrices. Each of these sets is closed in relation to multiplication and defines relevant algebra of hypercomplex numbers. It is shown that genetic Hadamard matrices are identical to matrix representations of Hamilton quaternions and its complexification in the case of unit coordinates. The diversity of known dialects of the genetic code is analyzed from the viewpoint of the genetic algebras. An algebraic analogy with Punnett squares for inherited traits is shown. Our results are discussed taking into account the important role of dyadic shifts, Hadamard matrices, fourth roots of unity, Hamilton quaternions and other hypercomplex numbers in mathematics, informatics, physics, etc. These results testify that living matter possesses a profound algebraic essence. They show new promising ways to develop algebraic biology.
1. Introduction
Science has led to a new understanding of life itself: «Life is a partnership between genes
and mathematics» [Stewart, 1999]. But what kind of mathematics is a partner with the genetic code? Trying to find such mathematics, we have turned to study the multi-level system of interrelated molecular-genetic alphabets. On this way we were surprised to find connections of this genetic system with well-known formalisms of the engineering theory of noise-immunity coding: Kronecker products of matrices; orthogonal systems of functions by Rademacher and Walsh; Hadamard matrices; a group of dyadic shifts; hypercomplex number systems, etc. This article is devoted to some of our results of such studing of the phenomenologic system of interrelated genetic alphabets….
Genetic information is transferred by means of discrete elements. General theory of signal processing utilizes the encoding of discrete signals by means of special mathematical matrices and spectral representations of signals to increase reliability and efficiency of information ... A typical example of such matrices is the family of Hadamard matrices. Rows of Hadamard matrices form an orthogonal system of Walsh functions which is used for the spectral representation and transfer of discrete signals… An investigation of structural analogies between digital informatics and genetic informatics is one of the important tasks of modern science in connection with the development of DNA-computers and bioinformatics. The author investigates molecular structures of the system of genetic alphabets by means of matrix methods of discrete signal processing [Petoukhov, 2001, 2005a,b, 2008a-c; Petoukhov, He, 2010, etc.].
The article describes author’s results about relations of matrix forms of representation of the system of genetic alphabets with special systems of 8-dimensional hypercomplex numbers (they differ from the Cayley’s octonions). The discovery of these relationships is significant from some viewpoints. For example, it is interesting because systems of 8-dimensional hypercomplex numbers (first of all, Cayley’s octonions and split-octonions) are one of key objects of mathematical natural sciences today. They relate to a number of exceptional structures in mathematics, among them the exceptional Lie groups; they have applications in many fields such as string theory, special relativity, the supersymmetric quantum mechanics, quantum logic, etc. … The term “octet” is also used frequently in phenomenologic laws of science: the Eightfold way by M.Gell-Mann and Y.Ne’eman (1964) in physics; the octet rule in chemistry… In view of these facts one can think that genetic systems of 8-dimensional numbers will become one of the interesting parts of mathematical natural sciences.
In addition, hypercomplex numbers are widely used in digital signal processing… Formalisms of multi-dimensional vector spaces are one of basic formalisms in digital communication technologies, systems of artificial intelligence, pattern recognition, training of robots, detection of errors in the transmission of information, etc.
Revealed genetic types of hypercomplex numbers can be useful to answer many questions of bioinformatics and to develop new kinds of genetic algorithms. Hadamard matrices and orthogonal systems of Walsh functions are among the most used tools for error-correcting coding information, and for many other applications in digital signal processing …. As noted in the article [Seberry, et al., 2005], many tens of thousands of works are devoted to diverse applications of Hadamard matrices for signal processing. Our discovery of relations of the system of genetic alphabets with the special systems of 4-dimensional and 8-dimensional hypercomplex numbers and with special Hadamard matrices helps to establish the kind of mathematics which is a partner of the molecular-genetic system. Hypercomplex numbers, first of all, Hamilton quaternions and their complexification (biquaternions) are widely applied in theoretical physics. The author shows that matrix genetics reveals a special connection of the system of genetic alphabets with Hamilton quaternions and their complexification. These results give new promising ways to build a bridge between theoretical physics and mathematical biology. They can be considered as a new step to knowledge of a mathematical unity of the nature….
As Hamilton quaternions describe the properties of three-dimensional physical space, the discovery of the connection of the genetic system with Hamilton quaternions attracts our attention to some fundamental questions. It is, for example, the question about innate spatial representations in humans and animals [Russell, 1956; Petoukhov, 1981]. Or the question about a development of physical theories, in which the concept of space is not primary, but derived from more fundamental concepts of special mathematical systems [Kulakov, 2004; Vladimirov, 1998]. The described effectiveness of the algorithm of hidden parameters allows thinking about the systems of hidden parameters as about a possible base for additional development of these theories.
Molecular biology and bioinformatics possess their own problems where Hamilton quaternions and their complexification can be used. For example some approaches are known about algorithmic constructions of fractal patterns in biological structures including fractals in genetic molecules (see [Pellionisz et al, 2011; web]). A development of geometric algorithms for such approaches needs those geometrical operations inside physical 3D-space which are connected with the molecular-genetic system and which can be used as a basis of these geometric algorithms. Hamilton quaternions and their complexifications, which are connected with the system of genetic alphabets and which correspond to geometric properties of our physical space, seem to be promising candidates for this purpose.
Our article shows that now Hamilton quaternions and their complexifications are connected not only with theoretical physics but also with molecular genetics and bioinformatics. The discovery of the relation between the system of molecular-genetic alphabets and Hamilton quaternions together with their complexification provides a bridge between theoretical physics and biology for their mutual enrichment. It can be considered as a next step to discover the mathematical unity of nature.
[Physicists pick up from where Schroedinger left Genome Informatics in 1943 in his essay "What is Life?" - AJP]
Biophysicists Discover Four New [Fractal - AJP] Rules of DNA 'Grammar'
MIT Technology, December 10, 2010
... Today, Michel Yamagishi at the Applied Bioinformatics Laboratory in Brazil and Roberto Herai at Unicamp in Sao Paulo, say they've discovered several new patterns that significantly broaden the grammar of DNA.
Their approach is straightforward. These guys use set theory to show that Chargaff's existing rules imply the existence of other, higher order patterns.
Here's how. One way to think about the patterns in DNA is to divide up a DNA sequence into words of specific length, k. Chargaff's rules apply to words where k=1, in other words, to single nucleotides.
But what of words with k=2 (eg AA, AC, AG, AT and so on) or k=3 (AAA, AAG, AAC, AAT and so on)? Biochemists call these words oligonucleotides. Set theory implies that the entire sets of these k-words must also obey certain fractal-like patterns.
Yamagishi and Herai distil them into four equations.
Of course, it's only possible to see these patterns in huge DNA datasets. Sure enough, Yamagishi and Herai have number-crunched the DNA sequences of 32 species looking for these new fractal patterns. And they've found them.
They say the patterns show up with great precision in 30 of these species, including humans, e coli and the plant arabidopsis. Only human immunodeficiency virus (HIV) and Xylella fastidiosa 9a5c, a bug that attacks peaches, do not conform.
"These new rules show for the first time that oligonucleotide frequencies do have invariant properties across a large set of genomes," they say.
That could turn out to be extremely useful for assessing the performance of new technologies for sequencing entire genomes at high speed.
One problem with these techniques is knowing how accurately they work. Yamagishi and Herai suggest that a simple test would be to check whether the newly sequenced genomes contain these invariant patterns. If not, then that's a sign the technology may be introducing some kind of bias.
This is a bit like a checksum test for spotting accidental errors in blocks of data and a neat piece of science to boot.
Ref: arxiv.org/abs/1112.1528: Chargaff's "Grammar of Biology": New Fractal-like Rules
Chargaff's "Grammar of Biology": New Fractal-like Rules
Michel Eduardo Beleza Yamagishi, Roberto H. Herai
(Submitted on 7 Dec 2011)
Chargaff once said that "I saw before me in dark contours the beginning of a grammar of Biology". In linguistics, "grammar" is the set of natural language rules, but we do not know for sure what Chargaff meant by "grammar" of Biology. Nevertheless, assuming the metaphor, Chargaff himself started a "grammar of Biology" discovering the so called Chargaff's rules. In this work, we further develop his grammar. Using new concepts, we were able to discovery new genomic rules that seem to be invariant across a large set of organisms, and show a fractal-like property, since no matter the scale, the same pattern is observed (self-similarity). We hope that these new invariant genomic rules may be used in different contexts since short read data bias detection to genome assembly quality assessment.
http://arxiv.org/ftp/arxiv/papers/1112/1112.1528.pdf
ABSTRACT
Chargaff once said that “I saw before me in dark contours the beginning of a grammar of
Biology”. In linguistics, “grammar” is the set of natural language rules, but we do not know for
sure what Chargaff meant by "grammar” of Biology. Nevertheless, assuming the metaphor,
Chargaff himself started a “grammar of Biology” discovering the so called Chargaff’s rules. In
this work, we further develop his grammar. Using new concepts, we were able to discovery new
genomic rules that seem to be invariant across a large set of organisms, and show a fractal-like
property, since no matter the scale, the same pattern is observed (self-similarity). We hope that
these new invariant genomic rules may be used in different contexts since short read data bias
detection to genome assembly quality assessment.
[We are soon approaching the phase when everyone will say "Of course, the Genome is Fractal! Why should it be an exception to everything else in Nature?" The invited Springer Handbook Chapter "Recursive Genome Function of the Cerebellum: Unification of Neuroscience and Genomics" (In Press) reviews that looking at the genome as a kind of a "language" (with grammar) goes back to a couple of decades - but could not break through in part because full DNA sequences were not available, and also since the double barrier of the "Central Dogma" and "Junk DNA" misnomer blocked progress for over half a Century. With The Principle of Recursive Genome Function recursive fractal iteration was established as the fundamental algorithm of genome function, and in the "Unification" publication not only the Genomic-Epigenomic (HoloGenomic) system was put in a coherent mathematical framework, but also the "RNA System Serves as the Genomic Cerebellum" concept was put forward. The genome is not only fractal, but the "Coordinated Genome Function" uses the dual (covariant and contravariant) representations of protein production. This entry can be discussed in the FaceBook page of Andras Pellionisz]
Francis Collins [Head of NIH of the USA in Bangalore, India -AJP].
This US scientist is the director of the National Institute of Health, the country's leading health research establishment. He's in Bangalore to meet top Indian scientists on Saturday and Sunday and shares his outlook on life in this exclusive interview.
What strengths do you see in Indian institutions? How are they compared to China?
India's great strength now is its IT and computational capacity. Biology is now more a computational science. To understand diseases like diabetes and cancer, we need computational strategies to sift through vast datasets. India can provide that asset.
China has strengths too - a long history of genomics research and was into the human genome project earlier than India. India is catching up. But we need the collaboration of all countries on health because everyone everywhere in the world has health problems. Like Louis Pasteur said, science belongs to no one country.
Tell us more about your Bangalore visit...
It's been very exciting. I've been to the National Centre for Biological Sciences, St John's Medical Research College and IISc. At St Johns, I visited the hospital and clinical facilities to get a grasp of research there.
At NCBS, I spoke to students and faculty. The experience was wonderful. The students are bright and inquisitive and we discussed issues ranging from neuroscience to genomics. Clearly, Bangalore is a city that has a thoughtful generation of youngsters out to prove themselves in science. I see a spark in the young people here.
What collaborations are you looking at with institutions here?
We have a collaboration on cancer with India. India is concentrating on mouth cancer as that occurs at a higher frequency here. Then, there's diabetes - a worldwide concern. At St John's, we talked about diabetes and cardiovascular research and the implications for heart disease arising out of diabetes. We're also looking at vaccines, HIV, vision and brain research and technologies we need to develop to tackle these and other chronic diseases.
Paired Ends: Lee Hood, Andras Pellionisz
Genomeweb, In Sequence
December 06, 2011
a "leader in the field of genome informatics." Pellionisz holds PhD degrees in computer engineering...
People In The News
GenomeWeb Daily News - Dec 2, 2011
Elogic Technologies has named Andras Pellionisz to serve on its advisory board. An expert in genome informatics who established the International ...
People In The News
GenomeWeb Daily News - 1 day ago
PrimeraDx this week announced that it has appointed Leroy Hood to its scientific advisory board. Hood has helped found several research and commercial ...
[Genomeweb elected to disclose full contents only to subscribers or registered readers. This entry can be discussed on the FaceBook page of Andras Pellionisz]
ELOGIC Technologies (Bangalore) to launch Genome Analytics Service (See Binet - Genome)
ELOGIC Technologies is proud to present, for the very first time in India, IT Infrastructure Services in Next Generation Sequence (NGS) Analysis and Management on the Cloud Environment, through its BINET (Biological Internet) Division.
ET partners with leading IT MNC’s as a preferred alliance partner in India, to cater to the needs of Genome Informatics for a gradually burgeoning global clientele. ET’s partnership with these MNC’s goes back a decade for providing a range of services and products.
ET is foraying into Life Sciences sector as a whole and will pursue its interests at present in Genome Informatics as a focus area.
Being a forerunner in the arena of Genome Informatics and Data Analysis for NGS on the Cloud, ET is building a team comprising Board of Advisors, experienced Genomics experts, Biology Scientists, Mathematicians and IT Professionals, to provide an array of services in this field as a one-stop-shop for its customers. ET is aiming at providing services in the entire Life-Sciences sector per se, which implies developing software products and algorithms for NGS Analysis.
TD Prakash, Managing Director, ET says – “ET understands the Genome Informatics Landscape in all its entirety and interdisciplinary nature of Biological Sciences, which has occupied the foreground now, with the emergence of new areas in Bio research, such as Genomics, Proteomics and System Biology.
We envision value in building Life Science services with cutting edge technologies and will forge collaboration with global players in NGS area, with the objective of serving the global Life Science industry and related Academia.
In order to ensure that we provide services with complete knowledge and understanding of the field, extra proficiency and authority, ET has engaged with Dr. Andras Pellionisz, a global leader in Genome Informatics from USA, to be a part of our Board of Advisors and we welcome him with much delight on board our advisory team”.
Dr. Pellionisz is the President of HolGenTech, Inc. in Silicon Valley, California, USA and is a thought leader in Fractal Genomics and Hologenomics and will be undertaking the role of the guiding force for ET in this field. He has convinced himself of ET’s domain knowledge, capabilities, business model and growth plans prior to being a part of our Board of Advisors. For more information on our collaboration, please read here a Press Release held in California USA on the 30th November, 2011.
Equipped with the very best of high-end IT know-how and technical expertise, Bangalore is emerging as the epicentre of Biotech - a hub for Genomics and Genome Informatics and is therefore in a unique position to deliver to a world-wide audience, quality services and products in the field of Genome Informatics.
ET is poised to deliver its services to the market by the first quarter of 2012 and will, as a first step, start with executing pilot projects with the Academia. ET will offer services in IT infrastructure to begin with, in Compute Power and Storage followed by NGS Data Analysis Services.
Headquartered in Bangalore, ET has its office in Mumbai and operations in Dubai United Arab Emirates and UK too. Its immediate expansion plans include establishing offices in Chennai and Delhi in India, followed by an office in the Silicon Valley of USA.
With its knowledge of Genomics and its strategic location, ET has at its disposal the means and wherewithal to achieving Data Analysis of Next Generation Sequencing on Cloud.
DNA Sequencing Caught in Deluge of Data
New York Times, By ANDREW POLLACK
Published: November 30, 2011
[Added by Pellionisz: In 2008 I warned against this problem in my YouTube. Today, 3 years and 12,744 views later, the NYT describes precisely what was predicted and warned against. The lessons are not analyzed by general media - see my proof of the presently unsustainable path of Genome Sequencing Industry - without the rapid matching of Genome Analytics Industry (stock charts appended). This will emerge (in the USA or elsewhere) once Genome Analytics will be able to tap the vast market of Global Consumers and Global Health Care - this entry can be discussed in the FaceBook of Andras Pellionisz]
BGI, based in China, is the world’s largest genomics research institute, with 167 DNA sequencers producing the equivalent of 2,000 human genomes a day.
BGI churns out so much data that it often cannot transmit its results to clients or collaborators over the Internet or other communications lines because that would take weeks. Instead, it sends computer disks containing the data, via FedEx....
The field of genomics is caught in a data deluge. DNA sequencing is becoming faster and cheaper at a pace far outstripping Moore’s law, which describes the rate at which computing gets faster and cheaper.
The result is that the ability to determine DNA sequences is starting to outrun the ability of researchers to store, transmit and especially to analyze the data.
“Data handling is now the bottleneck,” said David Haussler, director of the center for biomolecular science and engineering at the University of California, Santa Cruz. “It costs more to analyze a genome than to sequence a genome.”
...
That could delay the day when DNA sequencing is routinely used in medicine. In only a year or two, the cost of determining a person’s complete DNA blueprint is expected to fall below $1,000. But that long-awaited threshold excludes the cost of making sense of that data, which is becoming a bigger part of the total cost as sequencing costs themselves decline.
...
But the data challenges are also creating opportunities. There is demand for people trained in bioinformatics, the convergence of biology and computing. Numerous bioinformatics companies, like SoftGenetics, DNAStar, DNAnexus and NextBio, have sprung up to offer software and services to help analyze the data. EMC, a maker of data storage equipment, has found life sciences a fertile market for products that handle large amounts of information. BGI is starting a journal, GigaScience, to publish data-heavy life science papers.
“We believe the field of bioinformatics for genetic analysis will be one of the biggest areas of disruptive innovation in life science tools over the next few years,” Isaac Ro, an analyst at Goldman Sachs, wrote in a recent report.
...
There will probably be 30,000 human genomes sequenced by the end of this year, up from a handful a few years ago, according to the journal Nature. And that number will rise to millions in a few years.
In a few cases, human genomes are being sequenced to help diagnose mysterious rare diseases and treat patients. But most are being sequenced as part of studies. The federally financed Cancer Genome Atlas, for instance, is sequencing the genomes of thousands of tumors and of healthy tissue from the same people, looking for genetic causes of cancer.
One near victim of the data explosion has been a federal online archive of raw sequencing data. The amount stored has more than tripled just since the beginning of the year, reaching 300 trillion DNA bases and taking up nearly 700 trillion bytes of computer memory.
Straining under the load and facing budget constraints, federal officials talked earlier this year about shutting the archive, to the dismay of researchers. It will remain open, but certain big sequencing projects will now have to pay to store their data there.....
“In the life sciences, anyone can produce so much data, and it’s happening in thousands of different labs throughout the world,” he said.
Moreover, DNA is just part of the story. To truly understand biology, researchers are gathering data on the RNA, proteins and chemicals in cells. That data can be even more voluminous than data on genes. And those different types of data have to be integrated. [See an entirely new approach to the "RNA System Acting as a Genomic Cerebellum" In Press - AJP]
...
Researchers are increasingly turning to cloud computing so they do not have to buy so many of their own computers and disk drives.
Google might help as well.
“Google has enough capacity to do all of genomics in a day,” said Dr. Schatz of Cold Spring Harbor, who is trying to apply Google’s techniques to genomics data. Prodded by Senator Charles E. Schumer, Democrat of New York, Google is exploring cooperation with Cold Spring Harbor.
Google’s venture capital arm recently invested in DNAnexus, a bioinformatics company. DNAnexus and Google plan to host their own copy of the federal sequence archive that had once looked as if it might be closed.
...
[Stock charts of the dramatic drop of valuation over the last six monts of the four leading DNA Sequencing companies. (Illumina and Life dropped less, since they are NOT "pure play sequencers"). This evidence of the presently unsustainable path of Genome Sequencing - without the rapid ramp-up in the USA or by SAMSUNG (announced Sept. 1. 2011) and/or other global players - has long been directly communicated, and non-standard solutions are emerging - these additions to the NYT description of the mesmerizing symptoms can be discussed on FaceBook of Andras Pellionisz]
The FDA’s confusing stance on companies that interpret genetic tests is terrible for consumers.
Tell Me What’s in My Genome!
SLATE - By Christopher Mims|Posted Friday, Nov. 25, 2011, at 12:20 AM ET
Right now, for about the same price as a conventional medical test that reveals just a handful of genes, you could learn the entire contents of your genome. Sure, it’s a "research" scan, which means it will contain mistakes, and your insurance won’t cover the $4,000-$5,000 bill. But it won't be more than a few years before a complete and virtually error-free version of your genome will be within financial reach. Wouldn’t you like to unlock your complete instruction set, with all the medical and ancestry data it contains?
Enticing as that may be, it won’t be easy get those keys if the FDA has its way. Last summer, the agency indicated that it wants to classify the work of any company that helps you decipher your genome as a medical test that must be regulated accordingly. But over the last year, the agency’s lack of continued communication has left companies that would interpret genetic information—which are simply offering information—confused as to where they stand. This lack of clarity and direction could ultimately mean ceding leadership in this field to overseas competitors who are not similarly constrained.
The FDA has indicated through its public statements that it will put regulatory barriers in the path of companies that want to help us interpret genomes. In June 2010 the agency sent a series of letters to providers like 23andMe, warning them that they were selling what amounted to medical tests that were not vetted by the FDA, and so were in violation of the law. The FDA’s letter to consumer genetics testing company 23andMe is a good example of the tack the agency is now taking. “23andMe has never submitted information on the analytical or clinical validity of its tests to FDA for clearance or approval. ... Consumers may make medical decisions in reliance on this [genetic] information [provided by 23andMe].”
Since then, the FDA has continued to send out letters of a similar tone—23 in total, all to different companies—but has offered no other guidance to providers of direct-to-consumer genetic tests, leaving these companies, and their investors, in the dark about the ultimate direction of regulation in this area. Frustrated by the delay, in recent months many of these companies have made their responses to the FDA public on their websites, in part to protest the climate of ongoing regulatory uncertainty that the agency’s actions have created. Others have pre-emptively eliminated medically significant interpretations from their tests, even if the genes they return still contain that information.
Rather than protect consumers, the FDA’s move has left the genetic information industry in limbo—and it seems a matter of time before it moves overseas. Can’t get your full genome scan interpreted by software hosted on servers in the United States, owned by a U.S. company? Within a decade, a company in a country not subject to our laws will almost certainly be happy to accommodate you. That’s if you don’t take the do-it-yourself route first, plumbing your genome with free and open-source software linked to Wikipedia-style databases maintained by volunteers (which, because they aren’t sold, aren’t subject to FDA regulation).
It’s difficult, if not impossible, to find legal or medical scholars in the United States who are against patient access to full genome sequences. So where does the FDA’s reticence come from? In part, it’s the long shadow of “genetic exceptionalism”—the idea that “genetic information is inherently unique and should be treated differently in law than other forms of personal or medical information,” as Alan Dow, vice president and legal counsel at Complete Genomics, put it.
Other Western governments, too, have fallen into the genetic exceptionalism trap. In 1997, the European Union’s member states even signed a treaty, the Convention on Human Rights and Biomedicine, which mandates that all signatories apply the precautionary principle when handling biomedical advances like genetic sequencing. This means it’s incumbent upon the advocates of these technologies to prove they won’t do any harm. So, for example, Germany has instituted a law so broad that it basically prevents anyone from getting her own genes sequenced without a doctor’s permission. If the genome-interpreting industry is forced by regulatory limbo to seek shelter outside the United States, we may see developing countries like India compete to fill the market gap.
Based on how we've (mis)used other medical technologies, it’s understandable that governmental bodies are at least a little concerned about the advent of whole-genome sequencing. For example, full-body MRI scans have fed into hypochondria-type fears by flagging benign abnormalities that then have to be further examined. Wouldn't a full-genome scan, with the many disease-contributing genes it turns up, do the same? And won't patients who discover, for example, an elevated chance of an incurable disease have their quality of life adversely affected? We'll get to the details later, but the short answer is no.
Genetic data have to be interpreted in a way that the public might not be accustomed to. But it is elitism of the highest order to imagine that most of us are simpletons who can’t grasp the concept that a gene might contribute to a disease condition, but in no way guarantees it. The fear is that every new study associating a gene with a particular disorder will send patients running to their doctors to ask whether they should be worried. But that seems to be a short-term concern: Most patients will understand the reality after their first (or maybe second) panicked trip to the doctor. The physician will tell them that these studies are always preliminary and that even if they’re borne out by subsequent research, the vast majority of these genes have only a marginal effect on our health.
Studies suggest that even patients who find out they have an elevated risk for a disease with a strong genetic component but no cure—like Alzheimer’s—handle the news quite well. In light of this, it seems like the worst-case scenario for a full genome scan is that a patient might be inspired to actually talk to their doctor about their health. If having genes that suggest an elevated chance of heart disease inspire someone to at least be conscientious about their other risk factors for the disease, great! Preliminary research suggests that results of genetic tests change consumers’ intention to do something about their health, if not their actual behavior. (Consumers’ options about what to do with this information often come down to common lifestyle changes like diet and exercise, which are difficult to get patients to implement under any circumstances.)
The only thing worse than the paternalism keeping genetic data and its implications from consumers is the failure of imagination this represents, in terms of the potential upside of the coming genomic revolution. The more full-genome scans we have, and the cheaper they become, the more useful information patients will have. Widespread genotyping will help us understand our own ancestry, but perhaps more importantly will lead to a new kind of engagement with our health and biology. For this new technology to transform American health—and to cultivate a new, high-tech, high-promise industry within the United States—the FDA needs to provide clarity and guidance. The alternative is that the FDA becomes something like the recording industry at the dawn of the MP3 age: a body trying to lock down immaterial assets that consumers are going to get their hands on, one way or another.
[No Comment - Andras Pellionisz]
ELOGIC Technologies Private Limited Bangalore, India [Pellionisz unites Silicon Valley-s of USA/India - AJP]
PRWeb, November 30, 2011
Bangalore, India - Genome informatics leader Dr. Andras Pellionisz joins the BoA of the global IT Company to break into Industrialization of Genomics
ELOGIC Technologies Private Limited is a Company Certified for ISO 9001:2008 by BVQI and ISO 27001:2005 for Security by BSI for years now and is in the process of obtaining an ISO: 50001 Certification for Energy Management System. In the business of Secure Information Management and IT Infrastructure Services Delivery, the Company aims at maintaining an uncompromising level of integrity and character to serve its customers, partners, employees and community, building a network of trust along the way. The company is now foraying into Genome Informatics and Next Gen Seq Data Analysis on the public and private clouds.
ELOGIC Technologies announces that Dr. Andras Pellionisz has accepted invitation to join the Advisory Board of ELOGIC Technologies. Dr. Pellionisz is an internationally renowned leader in the field of genome informatics specializing in the geometric unification of neuroscience and genomics. Founder and President of Silicon Valley-based HolGenTech, Inc. in California, he exemplifies the model Andy Grove, senior adviser to Intel, by putting innovation within goal-oriented corporation structure. In his major paper in Springer Handbook (in Press, accepted Nov. 1st 2011) he pairs breakthrough algorithmic development with a blueprint for industrial deployment at a crucial time when the Human Genome Project already impacted the economy by $796 Bn.
“We are delighted to welcome Dr. Andras Pellionisz into our Advisory Board. He brings a wealth of leading edge understanding and global contacts in genome informatics that will be invaluable to ELOGIC Technologies as we edge into this major emerging market,” says TD Prakash, Managing Director and Chairman of the Board of ELOGIC Technologies. "This is the formative decision in the long-term co-operation between USA-Silicon valley HolGenTech, Inc. and ELOGIC Technologies from Bangalore, Silicon valley of India, in the emerging field of genome analytics”, both Dr Pellionisz and Mr. TD Prakash concurred.
“Dr. Pellionisz will be our guiding force for foraying into Data Analysis of Next Gen Sequencing and Management, which we are offering to global clientele by early 2012”, added MV Ramanujam, VP of BINET Division, ELOGIC Technologies.
As a domain expert in Genome Informatics, Dr. Pellionisz is a cross-disciplinary scientist and technologist. With Ph.D.-s in Computer Engineering, Biology and Physics, he has 45 years of experience in Informatics of Neural and Genomic Systems spanning Academia, Government and Silicon Valley Industry. He played a leading role in the shift from artificial intelligence to neural nets, including the establishment of the International Neural Network Society. In 2005, he combined interdisciplinary communities of Genomics and Information Technology when he established the International HoloGenomics Society (IHGS).
Based on sound genome informatics, his work sets forth new mathematical principles for proceeding with full exploration of the whole genome. Dr. Pellionisz’ fractal approach to genome analysis is corroborated by recently published findings about fractal folding of DNA structure by Presidential Science Adviser Eric Lander.
“I am very pleased to join the ELOGIC Technologies Advisory Board. I am convinced that they have the foundation essential for edging into genome informatics. As one who served the “Internet Boom” as Chief Software architect of several Silicon Valley companies, I see and publicly expressed already in 2008 two major differences in the coming much larger boom of Industrialization of Genomics. First, while Internet companies could charge ahead without scientific innovation as packet-switching technology is both man-made and is utterly simple, industrialization of genomics (like nuclear industry) would not only be naive but utterly dangerous without science leadership. Second, while the Internet Boom was essentially centered on Silicon Valley of California, the Genome Boom is already global. I not only realize the cardinal importance of an alliance of Silicon Valley of California with Bangalore, the Silicon Valley of India, but will enjoy building a spectacular success based on global alliance,” says Dr. Pellionisz.
In 1973 Dr. Pellionisz was awarded a Stanford Post Doctoral Fellowship, subsequently he served as Research Professor of Biophysics at New York University Medical Center. Later at NASA Ames Research Center, as a Senior Research Associate of the National Academy. From 1994, he served as Chief Software Architect to several Silicon Valley companies.
About ELOGIC Technologies
ELOGIC Technologies is an IT Enabled Services Company serving a clientele of major multi- national and Government organisations seeking collaboration in the areas of Genome Informatics & Life Sciences, E-Security Services, Productivity Enhancement Solutions, Banking Solutions, Engineering Services and Professional Services Consultancy.
Established in the year 2002, they aim at providing high quality, products and services to achieve customer satisfaction and to be an innovating Company in leading edge technologies.
Contact
MV RAMANUJAM
ELOGIC Technologies Pvt Ltd
BANGALORE, INDIA
Phone : 0091 80 41210 892
Email : mvramanujam(at)elogic(dot)co.in
URL : http://www.elogic.co.in
[Dr. Pellionisz, as Founder and President of his HolGenTech, Inc. in Silicon Valley, California, with his new Board of Adviser role to Elogic Technologies of India's Silicon Valley in Bangalore, builds a global alliance. Dr. Pellionisz also serves as Board of Adviser to DRCcomputer - a hybrid serial/parallel processing hardware integrator of California's Silicon Valley. While the terms of an emerging global alliance are not disclosed, in view of the Boston team just having provided "proof of concept" (see full preview and Nature article two items below in this column, and popular coverage here) to the long-held thesis of Dr. Pellionisz that "fractal defects are root causes of a slew of hereditary syndromes, most notably of cancer" (see at min. 30 of his Google Tech Talk YouTube, 2008), Dr. Pellionisz' major peer-reviewed paper In Press provides hints of a global agenda) - This entry can be discussed on the FaceBook page of Andras Pellionisz]
Genomeweb
November 2011
By Christie Rizk
The creation of new drugs is a vital part of the health-care system. Researchers in academia and in industry are always searching for new ways to combat disease — more efficiently, with fewer toxicities, and less chance of rejection. Until recently, most medicines have been limited to the classic formulation of a small molecule targeting a protein to disrupt its function. But there are many targets and formulations that have yet to be fully exploited, particularly those involving RNAs.
Small interfering RNAs and microRNAs can be used both as targets for drugs and as compounds in drug formulations to disrupt the function of certain genes. By taking advantage of RNA interference, miRNAs and siRNAs can bind to specific messenger RNAs and either increase or decrease their expression to affect how much or how little a given target gene functions. "There are really quite a lot of different methods and cellular pathways that are exploited. In some of them the field is quite old, so you might consider antisense technology a form of RNA therapeutics," says the University of Massachusetts Medical School's Phillip Zamore, who co-directs the school's RNA Therapeutics Institute. "There are people who are engineering different kinds of cellular RNAs to alter splicing or to degrade messages. Most of those involve re-engineering longer RNA, and probably can be delivered as drugs."
But the real promise shown by RNA in the therapeutics field comes from small RNAs, he adds. "The new small RNA therapeutics are really the first time that RNA has shown some promise as a drug," Zamore says. "The secret is that they're small, they're generally double-stranded, and they need relatively little — although they need some — chemical modification to make them stable. The real advance has been the discovery of chemical formulations that allow them to be retained in the body instead of filtered out by the kidneys and delivered to cells. And those drugs, which generally take the form of siRNA, are now being tested in early-stage clinical trials." [SiRNA, a tiny start-up to deploy small interfering RNA-s was acquired by Merck 5 years ago for $1.1 Billion - just to be shut down this summer. Why? See comment... AJP]
Most miRNA-based drugs use RNAi pathways to bind argonaute proteins — the protein complexes responsible for RNAi — and, together, the combination of siRNA or miRNA and argonaute protein bind the target complementary mRNA and destroy it. "My lab has for the last 12 years studied the basic mechanisms of siRNAs and microRNAs," Zamore says. "We work in a variety of organisms including flies and mice, and out of our basic research efforts, we've been able to understand new ways in which one can use siRNAs to target genes that differ by as little as a single nucleotide. And in that case it would be a question of targeting a mutant versus a normal gene."
Treating disease
Zamore's primary focus is Huntington's disease, which has been shown to be caused by a mutated gene with an extended CAG repeat. "There has not been much success by any lab targeting the extended repeat," Zamore says. "But as we showed a couple of years ago, there's a polymorphism — a neutral base change — that is commonly associated with the disease gene. And because it creates a single nucleotide difference between the disease gene and the wild-type gene, one can target that and not the normal gene." Zamore's work on Huntington's disease is still in the preclinical stages, but he's hopeful that it will eventually make it to clinical trials.
The list of diseases that are potentially treatable with RNA drugs is long. "There are certainly clinical trials using siRNAs for cancer, and the kinds of targets that people are interested in are molecules, proteins, that normally would be considered non-druggable," Zamore says. "The pharmaceutical industry has a very short list of the types of proteins that they suspect will be amenable to inhibition by classical small-molecule drugs. Any gene that doesn't fall on that list — whose expression or over-expression contributes to a disease — would be a good candidate for RNA interference. So basically, if you can reduce the expression of the protein and do some good, it's a good target for RNAi."
Merck is one of the companies moving into RNA therapeutics. The company acquired San Francisco-based biotechnology company Sirna Therapeutics — which specialized in the development of siRNA drugs — in a 2006 deal worth $1.1 billion, because it believed RNA could "open up a whole new class of medications to treat patients with unmet medical needs," says Jeremy Caldwell, head of Merck's RNA therapeutics division. Caldwell says Merck is working to apply RNA drugs to the treatment of cancer as well as cardiovascular and respiratory diseases. He adds that he's "cautiously optimistic" that the company will be starting clinical trials on some therapeutics in the near future. "RNA is really going to be the modality that takes advantage of all the high-throughput sequencing and genomic information that identify potential drug targets, many of which are not druggable with classic approaches like small molecules," Caldwell says. "Classic small molecule targets are receptors and enzymes because they have a hydrophobic pocket that the small molecule can insert itself into and block the activity of the target. Biologics are similar, but only work on cell surface. What siRNA will be able to do is address both small molecule targets and biologic targets, but also targets such as adaptor proteins that regulate a catalytic intracellular event, for example." He says there are practically no diseases that cannot be targeted by RNA therapeutics.
There are some problems that must be resolved, however. For one thing, most RNA therapeutics are currently limited by their routes of administration — such as intravenous or subcutaneous approaches, Caldwell says. And since there are already plenty of drugs that can be administered orally, it's unlikely they would be replaced by comparable RNA therapeutics unless those, too, could be administered by mouth or were a significant improvement upon the standard treatments.
In addition, researchers are struggling with how to deliver these drugs to their intended targets once they're administered. Many companies developing RNA drugs, including Merck, are taking a route through the liver, which is generally quite efficient, but limits the number of diseases that can be treated with these drugs.
Special delivery
Silence Therapeutics, which specializes in the delivery of targeted RNAi therapeutics, aims to solve this problem with its new delivery system called AtuPlex — a lipid delivery technology that targets the vascular endothelium of different organs. "For the whole field, the biggest hurdle is the delivery. There are different ways to use RNAis or even antisense molecules, but I think in the last three or four years, most companies shifted to formulations — they realized you need delivery technologies for the nucleic acids," says Jörg Kaufmann, Silence's vice president of research. "Our delivery technology, AtuPlex, is a liposomal formulation complexed with nucleic formulations, and the difference is that our formulation targets the vascular endothelium of different organs, including the tumor vasculature." While some companies target the tumor cells themselves, Silence's method allows the therapeutic to directly enter the tumor, and to alter the vasculature of target organs in order to prevent secondary metastasis, Kaufmann adds.
The company's most advanced RNAi therapeutic, a compound called Atu027, has been shown to prevent metastasis to the lungs by modulating the organs' blood vessels, Kaufmann says. "Basically, if the cancer cells are in a solid tumor, at one point they will go into the bloodstream to start growing in different organs. Our system delivers the nucleic acids to the endothelium or the vasculature," he says. Then, the system works to change it enough to prevent cancer cells from taking hold and metastasizing. This approach differs from that of Silence's competitors — companies like Alnylam, which UMass's Zamore co-founded, or Tekmira — which generally target the liver, liver metastases or cancer in the liver, whereas Silence is attempting to target metastases throughout the body, Kaufmann says.
Currently, the company is at the end of Phase I testing on Atu027 and will start Phase II trials by the end of this year or in early 2012. Phase III trials are likely six to 10 years away, Kaufmann says, but he is optimistic about the drug's chances of making it to market. So far, the company is still escalating the dose, and is aiming to show Atu027 can be used as a monotherapy in Phase II testing. "After that, we will combine it, and I personally envision it that it will be used in combination with chemotherapy or maybe as an adjuvant therapy," Kaufmann says. "After the chemotherapy has taken care of the primary tumor, this would prevent metastasis."
RNA in the crosshairs
At the University of Michigan, chemistry and biophysics professor Hashim Al-Hashimi is taking a different approach: instead of using RNAi to create drugs, he's creating ways to target the RNAs themselves. "Antibiotics that bind RNA in the ribosome are really the only example of a bona fide drug that we have on the market that we know functions by binding RNA," says Al-Hashimi, who co-founded a company that specializes in RNA targeting, called Nymirum. "There may be more drugs out there that function by binding RNA that we don't know about, but the drugs that are currently known to bind RNA and have an effect are very few, and the ones that are known are the antibiotics, and those compounds tend to be positively charged. That presents a problem in general, for various reasons — they can be toxic, they can be difficult to take up by cells — but certainly these are compounds that demonstrate the proof of principle that one should be able to target RNA."
However, part of the challenge in finding compounds that bind RNAs is developing assays or technologies that will allow researchers to measure the exact effect of a compound on its target. "Most small molecule drugs target proteins and take advantage of the fact that many proteins are enzymatic," Al-Hashimi says. "When a molecule is enzymatic, you can have an enzymatic assay to read the effect of a drug, so you can screen to assess the inhibitory activity of small molecules by simply asking, 'How well does this enzyme do what it's supposed to do in the absence or presence of a small molecule?'" The challenge with RNA, however, is that the majority of RNA targets are not enzymatic, so there isn't an easy way to create a high-throughput assay to measure a compound's effect on the target RNA.
There are methods that involve tagging RNA with modified compounds like fluorescent tags, Al-Hashimi says. "But because RNA is very fickle and flexible — a very delicate structure — having these large tags attached to it can cause problems in terms of perturbing the RNA," he adds. "Also, with these techniques that rely on tagging the RNA, often what happens is that the molecules that you would like to test have features or optical properties that make them ill-suited to these types of experiments because they happen to absorb light at the same wavelengths as the tag does. So there's quite of a bit of limitation as to the types of molecules you can test with these types of approaches."
RNA, camera, action
To address this challenge, Al-Hashimi and his group have developed a new technology to test molecules and see if they will bind RNA. In a perfect world, this would be done with a computer program, Al-Hashimi says, but he notes that most computer programs assume that RNA is a rigid molecule when it is a mobile, flexible structure that's "wriggling and dancing around, and assumes many different shapes." Instead of taking static images of RNA and then asking a computer program to predict which compounds will bind to it, Al-Hashimi records videos of RNA to capture the structure's fluctuations.
"What we do is we take different frames from our movie, highlighting the lock in different shapes, and then ... we test keys," Al-Hashimi says. "We test them not just against one frame, but against all of the different frames we have, and that gives us more shots on target. So we will not, for example, miss the key that can specifically bind to an unusual shape of the lock. With this new technology we can find these keys, and screen them more effectively."
Using NMR spectroscopy coupled with computational techniques that can predict which agents will bind RNA, Al-Hashimi can visualize RNA in motion and screen for existing compounds that could target the RNA to treat disease. He's already successfully identified one compound — netilmicin — which inhibits HIV replication, and continues to screen existing compound libraries to see whether any of the molecules there could be used to target RNAs. "We know a lot about proteins — we know a lot about what molecules they like to bind — so we have a history that we've accumulated over many, many years," Al-Hashimi says. "With RNA, it's just an open field — we really don't know the kind of keys that RNA is going to like, and it might be keys that we have never synthesized. ... The advantage of this computational approach is that we can test molecules that don't even exist, and see if there's a class of molecules that we ought to spend some effort making, because they could be the next generation of small molecules targeting RNA."
Too soon to tell?
Of course, as with the development of any drug, there are questions as to how the body will react, whether there will be toxic side effects, and whether there is potential for the disease to become resistant to the treatment. Al-Hashimi says that it's still too early to tell whether drugs targeting RNA will create adverse reactions or treatment resistance, but says there is evidence indicating that RNA-targeting compounds may escape resistance more effectively than traditional drugs. "Because of the sheer amount of RNA that one has, there are more goals to shoot at," he says. "So the chance that you have one RNA that has more favorable properties might be quite large, simply because of the potential different ways you could attack a disease through targeting RNA."
And, he adds, the potential for beating resistance with combination therapies is high with an RNA targeting approach. "I think the sheer number of targets that are out there and the different strategies one can go about inhibiting a given disease, you can imagine cocktail strategies where you have drugs that bind not one but multiple elements and that could probably really help with the resistance issue, because you're hitting the disease from so many different ends. It's hard for a mutant to occur that can defeat all of them simultaneously," Al-Hashimi says.
Suppressing toxicities would be a matter of making sure the compound has "exquisite selectivity" for its target, so that it affects one specific target RNA and not similar RNAs as well, he adds.
When it comes to RNAi, Merck's Caldwell says that, although it's likely some diseases will evolve resistance to certain RNA therapeutics, the advantage of RNAi drugs is that it's easier to identify potential resistance mutations in the pre-clinical testing stages and be ready with a backup against the mutated version of the disease.
Overall, researchers say that there is a great deal of potential in RNA therapeutics. "The connection of RNA to diseases is literally unfolding as we speak," Al-Hashimi says. "We really have many decades to go to figure out RNAs and develop the technology needed, but now that the interest is there, we'll definitely be able to learn more and figure out how things work."
[Everyone agrees that the RNA system is most likely the clue to "Coordinated Genome Function" and thus has an enormous potential. Presently, as documented by Merck having shut down its $1.1 Bn SiRNA-wing, the field experiences several difficulties. 1) RNA drugs will be difficult to get approved by FDA. 2) RNA drugs are difficult to deliver to the genome. 3) It is not well understood at all, how the RNA system works to yield "Coordinated Genome Function". Regarding the theoretical foundation of RNA system (how contravariant cRNA functors by means of interference with covariant ncRNA functors comprise the functional geometry by their eigendyads, see "The Recursive Genome Function of the Cerebellum: Geometric Unification of Neuroscience and Genomics". Announcement below, pre-publication here, and Abstract, References and Essential Geometric Concepts here - AJP]
High order chromatin architecture shapes the landscape of chromosomal alterations in cancer ["Fractal Defects" as root causes of cancer -AJP]
Geoff Fudenberg, Gad Getz, Matthew Meyerson & Leonid A Mirny
Nature Biotechnology (2011) doi:10.1038/nbt.2049
Received 09 September 2011 Accepted 21 October 2011 Published online 20 November 2011
ABSTRACT - The accumulation of data on structural variation in cancer genomes provides an opportunity to better understand the mechanisms of genomic alterations and the forces of selection that act upon these alterations in cancer. Here we test evidence supporting the influence of two major forces, spatial chromosome structure and purifying (or negative) selection, on the landscape of somatic copy-number alterations (SCNAs) in cancer1. Using a maximum likelihood approach, we compare SCNA maps and three-dimensional genome architecture as determined by genome-wide chromosome conformation capture (HiC) and described by the proposed fractal-globule model2, 3. This analysis suggests that the distribution of chromosomal alterations in cancer is spatially related to three-dimensional genomic architecture and that purifying selection, as well as positive selection, influences SCNAs during somatic evolution of cancer cells.
[Consistent with copyright principles that authors retain their intellectual property, the above Nature publication (other than the Abstract) is "for fee", a pre-publication .pdf can be found, with full text and full-size Figures, see Fig. above and text-excerpts below - AJP]
...Here, we ask whether the “landscape” of SCNAs across cancers can be understood with respect to spatial contacts in a 3D chromatin architecture as determined by the recently developed HiC method for high-throughput chromosome conformation capture or described theoretically via the fractal globule (FG) model ...Specifically, we investigate the model presented in Figure 1A, and test whether distant genomic loci that are brought spatially close by 3D chromatin architecture during interphase are more likely to undergo structural alterations and become end-points for amplifications or deletions observed in cancer...
[Some may have been wondering how aberrations of fractal properties of the genome (e.g. its "fractal folding", shown by the rotating 3D Hilbert curve in the header of this site) could lead to genomic pathology. The presented overall "fractal defect" (altering the "optimal functional closeness") is a major finding; leading researchers directly to root-causes of cancer. This article is to be compared to the pre-publication copy of the collective work of authors Pellionisz et al. 2011 (In Press), below - AJP]
Recursive Genome Function of the Cerebellum: Geometric Unification of Neuroscience and Genomics
Andras J. Pellionisz, Roy Graham, Peter A. Pellionisz, Jean-Claude Perez
Chapter in Press: The Cerebellum, Handbook by Springer (Ed. M. Manto). Submitted 20th of October, Accepted 1st of November, 2011
Contact: holgentech_at_gmail_dot_com
Abstract
Recursive Fractal Genome Function in the geometric mind frame of Tensor Network Theory (TNT) leads through FractoGene to a mathematical unification of physiological and pathological development of neural structure and function as governed by the genome. The cerebellum serves as the best platform for unification of neuroscience and genomics. The matrix of massively parallel neural nets of fractal Purkinje brain cells explains the sensorimotor, multidimensional non-Euclidean coordination by the cerebellum acting as a space-time metric tensor. In TNT, the recursion of covariant sensory vectors into contravariant motor executions converges into Eigenstates composing the cerebellar metric as a Moore-Penrose Pseudo-Inverse.
The Principle of Recursion is generalized to genomic systems with the realization that the assembly of proteins from nucleic acids as governed by regulation of coding RNA (cRNA) is a contravariant multi-component functor, where in turn the quantum states of resulting protein structures both in intergenic and intronic sequences are measured in a covariant manner by non-coding RNA (ncRNA) arising as a result of proteins binding with ncDNA modulated by transcription factors. Thus, cRNA and ncRNA vectors by their interference constitute a genomic metric. Recursion through massively parallel neural network and genomic systems raises the question if it obeys the Weyl law of Fractal Quantum Eigenstates, or when derailed, pathologically results in aberrant methylation or chromatin modulation; the root cause of cancerous growth. The growth of fractal Purkinje neurons of the cerebellum is governed by the aperiodical discrete quantum system of sequences of DNA bases, codons and motifs. The full genome is fractal; the discrete quantum system of pyknon-like elements follows the Zipf-Mandelbrot Parabolic Fractal Distribution curve.
The Fractal Approach to Recursive Iteration has been used to identify fractal defects causing a cerebellar disease, the Friedreich Spinocerebellar Ataxia – in this case as runs disrupting a fractal regulatory sequence. Massive deployment starts by an open domain collaborative definition of a standard for fractal genome dimension in the embedding spaces of the genome-epigenome-methylome to optimally diagnose cancerous hologenome in the nucleotide, codon or motif-hyperspaces. Recursion is parallelized both by open domain algorithms, and also by proprietary FractoGene algorithms on high performance computing platforms, for genome analytics on accelerated private hybrid clouds with PDA personal interfaces, becoming the mainstay of clinical genomic measures prior and post cancer intervention in hospitals and serve consumers at large as Personal Genome Assistants.
[This preview of the Abstract, with References and further material to be provided elsewhere, outlines the Non-Euclidean Geometrical Unification of Neuroscience with Genomics, since the authors state at the outset that "Our understanding of both the genome and the brain will remain partial and disjointed until we reach a unification of the intrinsic mathematics of structuro-functional geometry of both – as the first is without question a foundation of the second". The paper features the RNA System as a "Genomic Cerebellum", based on the dual valences (covariant and contravariant) of biological entities that represent invariants, such as movements in sensorimotor coordination in case of the cerebellar neural networks, and physically additive protein-synthesis with the use of RNA from "coding DNA" as well as measures of built proteins by RNA emanating from binding of proteins to "non-coding DNA", where their interference acts as the metric of the functional geometry of coordinated genome function. Based on conceptual breakthrough, the paper lays down an Agenda for a unification of Neuroscience and Genomics both in R&D and in the Industrialization of Genomics. As discussed in the FaceBook page of Andras Pellionisz, this paper is cited even before its appearance, and in view of an accelerated surge of both the demand and technology development (see Nature publication of a Korean school of scientists and technologists below), will lead to rapid advances both in our conceptual breakthrough from "frighteningly unsophisticated" notions of coordinated genome function (called "genome regulation") as well as massive deployment in health-care R&D and Industry, such as fractal diagnosis of cancer ]
Altered branching patterns of Purkinje cells in mouse model for cortical development disorder
Nature, Scientific Reports 1, Article number: 122 doi:10.1038/srep00122
[Purkinje neuron Fractal Dimension is a measure of disease - AJP]
Disrupted cortical cytoarchitecture in cerebellum is a typical pathology in reeler. Particularly interesting are structural problems at the cellular level: dendritic morphology has important functional implication in signal processing. Here we describe a combinatorial imaging method of synchrotron X-ray microtomography with Golgi staining, which can deliver 3-dimensional(3-D) micro-architectures of Purkinje cell(PC) dendrites, and give access to quantitative information in 3-D geometry. In reeler, we visualized in 3-D geometry the shape alterations of planar PC dendrites (i.e., abnormal 3-D arborization). Despite these alterations, the 3-D quantitative analysis of the branching patterns showed no significant changes of the 77 ± 8° branch angle, whereas the branch segment length strongly increased with large fluctuations, comparing to control. The 3-D fractal dimension of the PCs decreased from 1.723 to 1.254, indicating a significant reduction of dendritic complexity. This study provides insights into etiologies and further potential treatment options for lissencephaly and various neurodevelopmental disorders.
The formation of cellular layers and dendritic architectures is essential in the development of cortical structures in the mammalian brain1. Alterations in cortical structures are related to epilepsy, mental retardation, deficits in learning and memory, autism, and schizophrenia2, 3, 4. The alteration patterns of cortical structures are often studied using neurological mutation reeler5, which is characterized by ataxia, tremors, imbalance, and a reeling gait6, 7, 8, 9. In the reeler cerebellum, the cytoarchitecture of neural networks and neurons becomes gradually defective during the developmental process10, 11. The Purkinje cells (PCs) are not arranged in a regular plane but clustered in subcortical areas at early stages of corticogenesis. As a consequence of the ectopic location of such cells, an aberrant laminar organization occurs12, 13.
...3-D Fractal Dimension
This parameter reflects the degree of geometric complexity31 of the PC branching systems. Previous estimates from 2-D data varied among different authors31, 32, 33, 34. We extracted our values using instead 3-D data with the box counting method. The results for normal and reeler PCs were 1.71 ± 0.03 and 1.25 ± 0.02 (Table 2). Our fractal dimension for normal cells is consistent with previous results31, 32, 34, whereas for reeler cells it is significantly smaller, indicating a reduced geometric complexity. The lower geometric complexity is also consistent with the data of Figure 5 and could reflect reduced synaptic connections with other neurons.
...Fractal dimension
To estimate the fractal dimension of the PCs, we used the box-counting method. First, we embedded the data points of the PCs in the 3-D space. This space was divided in a grid of boxes with size r and we counted the number of boxes N(r) that contain at least one data point. A log-log plot of r versus N(r) could be fitted by a straight line with slope -D, where D is the fractal dimension (supplemental Fig. 1). A linear least square regression was performed to accurately evaluate this slope. To determine the scaling region and the slope, two end-points of the size giving the best linear fits were selected.
[It only took less than a quarter of a Century since the Fractal Model of the Purkinje Neuron for Korea to deploy 21 Century high-tech to actually measure in 3D the Fractal Dimension, to be used as a measure of disease. While this technology does not show how the growth of fractal physical geometry is governed by the fractal genome, FractoGene (2002) does. At the point when Samsung already announced by September 1, 2011 a genome analytics service for the World, Geometric Unification by Pellionisz of Neuroscience and Genomics (see announcement below and accelerated exposure above) is expected to result in a breakthrough. This comment can be discussed in the FaceBook page of Andras Pellionisz]
Geometric Unification of Neuroscience and Genomics
October 31, 2011
[Invited Chapter accepted to Springer, with the Editor's comment "A Decade Ahead" by Pellionisz et al. (submitted Oct. 20, 2011). Section "Future Directions" lays down a specific Agenda for Industrialization of Genomics. Inquiries to holgentech_at_gmail_dot_com]
...Initially Jobs sought alternatives to surgery
By Joseph Menn in San Francisco
Financial Times
October 21, 2011 2:44 am
[Section on Apple/Google omitted] ...
[Jobs' cancerous DNA analyzed too early, too late - AJP]
Jobs’ core beliefs are at a more emotional level, involving ideas, where the legal outcomes are less predictable, according to the book.
The 630-page book by Walter Isaacson, simply titled Steve Jobs, gives new details on many other areas of the secretive man’s professional and personal life, including his health and his romances.
It is based on dozens of interviews with Jobs that continued until just weeks before his death from cancer this month, as well as talks with family members and friends.
Some of the biggest revelations involve Jobs’ decisions on his medical treatment, where it appears that a man widely hailed as a genius made the poorest decisions possible.
It had been reported by Fortune magazine in 2008 that Jobs had delayed surgery for what he knew was a highly treatable form of cancer in his pancreas while he pursued alternatives. It emerges that Jobs resisted entreaties by his wife, a cancer survivor, former Intel chief Andy Grove and others close to him to have the small tumour removed because he did not want his body to be “violated”, Mr Isaacson told the CBS television show 60 Minutes.
After Jobs finally gave in, it may have been too late. Doctors discovered that the disease had spread to neighbouring tissue, Mr Isaacson said, and Jobs “regretted” his initial reluctance. The news programme posted an excerpt of its interview with Mr Isaacson on Thursday ahead of its full broadcast on Sunday night.
After Jobs accepted a traditional medical approach to his illness, he mastered it in detail and made the final decisions on all treatment, according to an account of the book in the New York Times. That included approving the sequencing of his own genes, which allowed for hand-tailored treatments, a pioneering approach that Jobs believed was key to the future of medicine. But not all that Jobs wrought, at Apple or in his personal life, was a success.
[Steve's cancerous DNA (compared to DNA of healthy tissues) was analyzed when his condition was too advanced, and the science was too early. Thus, we lost not only a giant, but a dear friend. Bill Gates had been asked if he wanted his DNA fully sequenced. After some hesitation, he said no ... but perhaps if I had cancer, I would. Now both Intel Founders Andy Grove and Gordon Moore should know that the genomics hinges on ... Informatics. (Gordon Moore had been sequenced twice, not for disease, but to compare Life Technologies' two very different sequencing platforms). Time is ripe for Informatics Giants to help programs, such as laid out in the invited Chapter submitted October 20th "Geometric Unification of Neuroscience and Genomics" (by Pellionisz et al.). This entry can be discussed in the FaceBook page of Andras Pellionisz]
Savoring an NGS Software Smorgasbord
In the latest crop of analysis tools for NGS data, functionality and ease-of-use are twin priorities.
By Allison Proffitt
September-October issue of Bio-IT World, 2011 | ‘Scaling to bigger and better hardware doesn’t help if your data is [sic] growing in size faster than your hardware,” says Titus Brown at Michigan State University. He and others in the NGS community are calling for software solutions to their NGS data woes instead of massive storage options. In an August post on his blog, “Daily Life in an Ivory Basement,” Brown wrote: “The bottom line is this: when your data cost is decreasing faster than your hardware cost, the long-term solution cannot be to buy, rent, borrow, beg, or steal more hardware. The solution must lie in software and algorithms.”
Thankfully, the options for both are expanding. Familiar names such as CLC bio, Geospiza, DNAnexus, GenomeQuest (see, p. 24), Omicia (see, p. 48) and others (see, “Next-Gen Sequencing Software: The Present and the Future,” Bio•IT World, Sept 2010) are being joined by a new batch of friendly competitors. For the most part, these offerings—from aligners to niche analytics—support the Illumina, 454, and SOLiD platforms, with some including Ion Torrent, Pacific Biosciences, and Complete Genomics data as well.
The software landscape for NGS analysis is broad and varied partly because “analysis” isn’t a cut and dried term, says Knome’s Nathaniel Pearson, director of research. “We’ve managed, as a community, to make people understand that analysis is as important as sequencing in the end… But now we have to tease out upstream and downstream analysis.”
Pearson defines “upstream analysis” as that closest to the sequencing machines, where the first work was done: base calling, variant calling, variant assessment, etc. “Now we’re seeing a focus moving toward downstream analysis, toward understanding many genomes at a time. As the stream of sequencing data from one machine comes together in a river with the streams coming from other machines, we need to make sense of that tide of data.”
Swimming Upstream
Knome’s area of interest can be summarized as “service with software,” says Pearson. kGAP—Knome’s Genome Analysis Platform—is the analysis software Knome uses to “richly annotate genomes and compare them to each other thoroughly,” says Pearson.
Knome’s sequencing and genome analysis service was launched in 2007. “Knome cut its teeth analyzing whole genomes for consumers. Given how costly whole genome sequencing remains, most of those consumers are still either healthy and wealthy aficionados of science and technology, or physician-aided families with urgent health problems—fairly small markets,” says Pearson.
“We do foresee that the consumer market will eventually democratize, as sequencing gets cheaper and insights for small numbers of relatively healthy genomes—especially in family settings—become more precise and useful,” he says.
Until then, Knome plans to keep refining its analysis pipeline and end-user software Today more than 95% of the firm’s customer base is researchers, about half from academia and half from industry, users that Pearson says can best understand diseases of widespread public interest.
When these customers receive Knome’s analysis they also receive software tools like KDK Site Finder, a simple query interface that lets clients find interesting sites in one or a set of genomes by “sensibly chosen criteria: allele frequency, call quality, novelty, zygosity—the usual suspects—as well as a rich archive of gene- and site-associated phenotype data from the literature.”
The current version of kGAP runs in the Cloud, which has greatly increased its throughput. But Pearson doesn’t expect analysis costs to fall at the rate of sequencing costs. “They’re going to drop slower than sequencing costs overall because we’re more tied to computational costs—which is more of a Moore’s Law scale,” he says. “Some software will fall quickly; it’ll get commoditized. But the very best software will always be costing a bit more because it will entail evermore complex underlying calculations to make the bottom line look much simpler to use.”
He believes future analysis options will do for sequencing what Photoshop did for photography. “I think we’ll see software for the end user for understanding genomes [in which] a lot of the underlying calculations will be done very swiftly and very cleverly under the hood. And the user’s experience will be very easy and very fast, but that’s going to cost a bit.”
The team at Real Time Genomics might disagree. The company’s “single and only intent is to provide the world’s best genomic analysis software,” says CEO Phillip Whalen. And they’re giving it away for free.
The venture-funded company based in San Francisco unveiled its website only a few months ago, but the technical team has been working on this problem for seven or eight years.
“The decision we made when we basically took the wrappers off,” says Whalen, “was that for organizations we wanted to charge a license fee, but if [researchers are] working on a project and they decide, ‘I’d like a really tight, easy to use pipeline,’ absolutely the use of our software by an individual investigator is unrestricted.”
RTG Investigator is made up of two such pipelines: one geared for variant detection and one for metagenomics. The software runs from a command line interface and is geared toward research teams that include both bioinformaticians and biological investigators. “Our customers wring the last bit of information out of their datasets, and the tension of discovery demands a collaborative effort,” says Stewart Noyce, RTG’s director of product marketing.
“Right at the core is this extremely fast and sensitive searching technology,” says Graham Gaylard, RTG’s founder. “When I say sensitive, we actually can search with mismatches in the search pattern right at the very start. “The variant detection pipeline does all of the alignment—it’s a fully gapped aligner—so it does full read matching assembly and also processing right through to variant calls such as SNPs, complex calls, indels, CNVs [copy number variations] and structural variations,” says Gaylard. “It handles paired ends natively, not as an add-on. That gives us far superior efficiency. We’re as accurate as all of them, but we’re faster than the BWA/GATK pipeline by 10x.”
And the numbers are even better for metagenomics. “One of the functions our search technology replaces is BLASTX, a translated nucleotide search of protein databases. We’re 1,000x faster than that.” The Genome Institute at Washington University acquired some of the early licenses for the product a couple of years ago and RTG has worked closely with them on the Human Metabolome Project. Gaylard says RTG has turned a 10-year compute task on their cluster into a three-month problem. “That has a big impact on how you do things,” he says.
The software is designed to make maximum use of the computing resources allocated to it, and will run on a laptop or cluster or can be pushed to the Cloud. Everything is proprietary—new algorithms, a new approach, and patent protected (or pending). “We have not gone out and taken something open source and tweaked it,” says Whalen. “We have attacked the problems from a computer science point of view with new ways of doing things. We’ve done that from scratch and come up with some results that our customers say are pretty compelling.”
Betting on Biologists
Though some users are happy at a command line, Enlis Genomics and others are betting that many biologists would like to dig into their data without also learning bioinformatics. Enlis’ “point-and-click genomics” software was designed by biologists, says founder Devon Jensen.
The software caught Illumina’s eye in July, winning the commercial category in the iDEA Challenge (see, “Illumina Showcases New Visions in Genomic Interpretation,” Bio•IT World, July 2011; part of the prize was a one year co-promotion marketing agreement with Illumina. Jensen says the details of that agreement are still being finalized).
This isn’t variant calling though. The software addresses the biologist’s question: After you have sequenced, assembled, and called variants, what do you do next? Tools like the Variation Filter and the Genome Difference tool let users query the genome and compare up to 100 genomes. “The focus of our software is making it easy to find what is biologically relevant in the sequence data of a patient, individual or research animal,” says Jensen.
The Enlis software comes with an import/annotation tool that creates a .genome file format encapsulating all the different types of genomic data into a single file to improve the process of handling and storing the data for the researcher. The focus is on speed and ease. “The software contains very fast algorithms for filtering variations and finding differences between whole genomes,” says Jensen. “We have organized all of the information in a way that allows a researcher to quickly assess whether a particular feature of a genome is important.”
SoftGenetics’ NextGENe product is also aimed at the individual biologist or clinician, says John Fosnacht, the company’s co-founder and vice president. “It’s a Windows-based program that’s easy to use. It has a lot of tools in it that [users] can use on multiple applications. It’s doesn’t require any kind of bioinformatics support.”
Fosnacht says the company has several groups of customers, including core labs that don’t have huge bioinformatics resources. The Mayo Clinic, for example, is using a networked version of the software. The software will process a whole human genome in ten hours, Fosnacht says.
In a partnership with the rare disease group at NIH, SoftGenetics developed a variant comparison tool as a module in NextGENe to identify which of thousands of variants are most likely to be causative mutations in rare genetic disorders. The software takes the total number of variants (more than 275,000 variants in a family of 6 in one example) and filters out silent variants, known mutations in dbSNP, and other parameters. The NIH researchers were left with a very manageable six candidate mutations.
“The filtering and prediction part takes less than half a day. That allows the molecular geneticist and researcher, instead of trying to do the impossible and look at 280,000 variants, to focus on relatively few,” says Fosnacht.
The software uses a modified Burrows-Wheeler transform method, and excels in indel discovery and somatic mutations. NextGENe was able to find a 55-basepair deletion in a 50-bp read. “This is a patented functionality in the software, that can elongate short reads,” says Fosnacht. “In reality it is a localized assembly. Once the reads are elongated the software can detect an indel up to 33% of the elongated length. The same process can be used to actually merge paired reads into one long read. When employed this process can produce Sanger quality reads from short reads.”
These types of projects make the most of what Fosnacht calls tertiary analysis tools. “We want to provide the third level of tools to the actual users to speed up the whole process. Unlike many “freeware” or other programs that just give you a list—an Excel spreadsheet basically—of all the variants that were found, you can actually see them in our browser… A lot of people like to touch and feel, you might say, their data.”
DNASTAR agrees. “There just aren’t enough bioinformaticians out there to handle the data deluge,” says Tom Schwei, DNASTAR’s VP and general manager. “And they don’t want to wait in line for a week or two weeks for that bioinformatics core group. We believe that the end user, the person who is sponsoring the experiment, knows best their research objectives and their data and is in the best position to do the analysis… You shouldn’t have to be a bioinformatician to parse through the data and understand what you see.”
The company views the NGS market as simply an extension of what their customers are already doing. As such, DNASTAR recently moved their next-gen data products under the Lasergene umbrella, a 15-year old brand name that also includes primer design software and cloning resources. SeqMan
NGen is the GUI-based assembler, SeqMan Pro the data analysis module. They are designed to work together, although they can be purchased separately.
Schwei says that the new Lasergene offerings are designed to be intuitive, fast, and easy to use. Users can easily compare their variants to dbSNP and the reference genome.
“SeqMan Pro’s strength is really the analysis of any number of samples. It can handle individual assemblies quite well, and it can handle multiple assemblies.” The software can manage 100 samples of a certain region, says Schwei. “We will do separation of the tags if people are running multiple samples in one lane on the assembly side. We’ll then report on those samples on the analysis side.”
The software is also affordable. “For less than $10,000, scientists can get all the software they need—and the computer to run it on—to do any next-gen assembly and analysis project they need to do,” he says, thanks to proprietary assembly algorithms. “Basically, it no longer relies on the amount of memory you have on your computer,” Schwei says. “There’s no correlation between the amount of RAM and the size of the genome you have to assemble.”
Avadis NGS by Strand Scientific Intelligence enables “NGS analysis for the rest of us,” says Thon de Boer, director of product management, software. With a strong focus on visualization, Avadis NGS has three major workflows: DNA-seq, CHIP-seq, and RNA-seq. De Boer says Strand is focusing on “the individual researcher with their individual [sequencer] and their individual piece of software.” The desktop software manages analysis after alignment, the “backend” analysis, de Boer calls it, and he says that Strand has been able to “sell to places that already have the Genomics Workbench from CLC bio, for instance, because people really like our visualization.”
“We have special never-seen-before visualizations around splicing—very informative alternative splicing analysis visualization. And the same goes for SNP analysis, what we call the variant supporter view, which is just a better way to look at all of the supporting reads for a particular SNP without being overwhelmed with the amount of data you have to look through.”
Strand has also had success partnering in the field. Ion Torrent is a reseller of Avadis NGS, and Strand recently announced a partnership with German-based BIOBASE to give all Avadis NGS users one-click access to BIOBASE’s Genome Trax curated biological database. “We bundle a lot of our software with publicly available data,” says de Boer, and the partnership with BIOBASE will expand the available data pool and “make it easy for customers to get all the information that they need right from our servers.”
Partek’s Genomics Suite is a complete start-to-end solution,” says Hsiufen Chua, Partek’s regional manager in Singapore. “Just one package off the shelf and you can use all the genomics data analysis you need in the lab.”
Partek’s product integrates sequencing data with microarray data or real time PCR because, as Chua points out, most labs have several types of data. “[Customers] would like to bring together two sets of data because they would have samples that have been run on different platforms.” Genomics Suite allows users to compare the results in the same platform.
“From the point that [researchers] obtain the reads from the next-gen sequencer, we take care of them. We have solutions to help them align the reads down to the point where they can do quality control to see if the data they have is good enough to proceed for further analysis. If so, then we have the tools for them to do the statistical analysis—all the statistics. Following that, we also have the same tools to do the biological interpretation.”
Service Segment
But if a do-it-all platform is not what a researcher wants, the analysis-as-a-service segment of the market is expanding. While BGI (see, p 31) and Complete Genomics will do sequencing and analysis, Samsung just launched beta testing of an analysis-only service.
Samsung’s Genome Analysis Service will provide analysis for whole-genome sequencing and RNASeq for Life Technologies and Illumina data, says SungKwon Kim, director of the bioinformatics lab at Samsung SDS, with support for the Ion Torrent sequencer ready by the end of 2011.
The algorithms that Samsung SDS is using are a combination of open-source and vendor-provided software with Samsung’s own proprietary “tweaks,” says Kim. Samsung has built its own genome browser, but all of the data are available for download if the customer prefers another option.
Samsung is offering analysis on its own Cloud infrastructure in Korea, which Kim expects it to be extremely efficient, safe, and fast. “I think our analysis job is much faster than other competitors,” he says. “Our whole genome analysis will take five days; our RNA analysis will take 3 days.”
He also cites Samsung’s reputation for enterprise-level IT. “We’ve been working with system innovation with banks, high-profile Fortune 500 companies, so when it comes to data security—I don’t think any other vendor companies should be able to match our capabilities in security and recovery handling.”
Kim says Samsung has been eyeing the NGS space for three years. “This [industry] is mainly driven by academics and research institutions who have some of the IT infrastructure and who have their own sequencers… but when the read price drops below $1,000, then I don’t think any research institute or academia will be able to handle [both] their own sequencing jobs and their own analysis jobs.”
With so many options, they shouldn’t have to. •
This article also appeared in the 2011 September-October issue of Bio-IT World magazine.
Foundations of XXI Century Industrialization of Genomics
We're at a frighteningly unsophisticated level of genome interpretation
http://www.signonsandiego.com/news/2011/sep/20/venter-institute-breaking-ground-35-million-center/
Venter Institute breaking ground on $35 million center
While the institute has borrowed money to launch the work, its leaders are hoping to pay for some of the project's cost with donations from local philanthropists.
''It's now easy with the new technology to generate a lot of different data, but there are very few groups or scientists generating knowledge out of this data. We're at a frighteningly unsophisticated level of genome interpretation.''
Read more: http://www.smh.com.au/world/genome-research-little-bang-for-buck-scientists-20100401-ri2t.html#ixzz1YztapdeV
http://www.sisbq.org/uploads/5/6/8/7/5687930/qbtherapy.pdf
Stagnaro, S. and Caramel, S. (2011) Italy
"...human bodies are a continuum of biological systems whose dynamics follow the laws of deterministic chaos (Lorenz 1963, Ruelle 1991, Cramer 1994, Stagnaro et al. 1996), which can be measured by means of nonlinear statistical invariants. Furthermore, there is the recent discovery that energy information and communication between DNA and bio-systems are strictly linked with quantum behavior."
As more and more people's genomes are decoded, we need better ways to share and understand the data.
FRIDAY, SEPTEMBER 23, 2011BY DAVID EWING DUNCAN
If the Internet cloud were actually airborne, it would be crashing down right now under the sheer weight of a quintillion bytes of biological data.This year, the world's DNA-sequencing machines are expected to churn out 30,000 entire human genomes, according to estimates in Nature magazine. That is up from 2,700 last year and a few dozen in 2009. Recall that merely a decade ago, before the completion of the Human Genome Project, the number was zero. At this exponential pace, by 2020 it may be feasible—mathematically, at least—to decode the DNA of every member of humanity in a single 12-month stretch.
The vast increase in DNA data is occurring because of dazzling advances in sequencing technology. What cost hundreds of millions of dollars a decade ago now costs a mere $10,000. In a few years, decoding a person's DNA might cost $100 or even less.
But what's missing, say a growing chorus of researchers, is a way to make sense of what these endless strings of As, Gs, Cs, and Ts mean to individuals and their health. "We are really good at sequencing people, but our ability to interpret all of this data is lagging behind," says Eric Schadt, director of the Mount Sinai Institute for Genomics and Multiscale Biology and chief scientific officer at California-based Pacific Biosciences, which sells sequencing machines.
Scientists don't yet know what all our DNA does—how each difference in genetic code might influence disease or the color of your hair. Nor have studies confirmed that all the genetic markers linked to, say, heart disease and most cancers actually increase a person's risk for these illnesses. Just as significant, the thousands of genomes being cranked out right now can't easily be compared. There is no standard format for storing DNA data and no consistent way to analyze or present it. Even nomenclature varies from lab to lab.
The industry is working to address these problems. ["Industry" will never solve a problem that is SCIENTIFIC - AJP]. Earlier this summer, at a meeting of geneticists and other experts that I attended in San Francisco, Clifford Reid, the CEO of Bay Area-based Complete Genomics, called for a consortium of gene companies to develop sorely needed standards for everything from consent procedures for DNA donors to methods of collecting, storing, and analyzing DNA specimens. Reid says the ultimate purpose is to "aggregate multiple data sets, providing broad access to data sets that are today in silos and largely unavailable to the broader scientific community."
The payoff from "interoperable" genomes will be faster research on the links between DNA and disease, scientists say. Researchers will be able to validate suspected links between genetic makeup and drug reactions or overall health by conducting much larger studies in which many people's genomes are compared. And physicians and individuals will be able to use standardized methods of reporting a person's genetic risks and advantages. That will matter as more and more ordinary people have their DNA decoded.
Another major initiative comes from Sage Bionetworks, a Seattle-based nonprofit cofounded by Schadt and Sage director Stephen Friend, formerly the leader of Merck's advanced technologies and oncology groups. Sage has raised $20 million to support a movement among biologists, computer scientists, patient advocacy groups, and businesses to standardize DNA databases that have sprung up over the years. "This won't happen overnight," says Schadt. "But it will be huge, like the Internet."
At some companies, efforts are under way to build an IT infrastructure capable of pooling and interpreting whole genomes on a larger scale. Jorge Conde, the CEO of Knome, a company in Cambridge, Massachusetts, that sells whole-genome sequencing as a service and uses a team of PhDs in India to analyze the results, says more drug companies now want to use full genomes to understand why drugs work or have side effects in some people and not others. "As the price has dropped, we are getting more interest from pharma and biotech companies," says Conde. Knome's price for its sequencing and analytical service has dropped from $350,000 in 2007 to under $10,000 today.
One of Knome's more recent ideas, still at an early stage, is to get drug companies to share genomes they have had decoded. The company has launched a cloud-based service called kGAP that would let customers process several hundred genomes at one time, studying them for the presence of 200,000 known links between DNA markers and genotypes for disease and other traits. The technology is still oriented toward facilitating big research projects, but eventually such engines might be used to compare an individual's genome with thousands of others and spit out personalized health tips and diagnoses. "The big play is when this information is available to be used by health-care providers and patients," says Conde. "But that's still several years away."
[The colossal threat of unsustainability of Industrialization of Genomics; a hyper-escalating number of available full DNA sequences glutting the supply-side, and an almost total lack of the "demand side", of overall theoretical understanding of how The Recursive Genome Function arises (in the form of iterative fractal recursion) from the Fractal DNA) I disseminated as early as it was possible once the US government admitted in 2007 in their ENCODE results, that the underlying assumptions have been false for over half a Century. The peer-reviewed science publication was The Principle of Recursive Genome Function, and the now outrageously evident facts were popularized in a Google Tech Talk YouTube (both in 2008), making the trivial point that Information TECHNOLOGY is more than ready, but Information THEORY of genome function is not. With the software-enabling recursive algorithms of FractoGene, HolGenTech, Inc. in Silicon Valley, working with global strategic partners, is ready to come to the rescue. This entry can be discussed at the FaceBook page of Andras Pellionisz]
Sam Waksal, Pfizer Venture Investments, and More: Moderator Looks Forward to All-Star Chat at New York Life Sciences 2031
Arlene Weintraub 9/6/11
Les Funtleyder, manager of the Miller Tabak Health Care Transformation Fund (MTHFX), recently told Xconomy that in a few years, investors are going to look back and wish they had invested more in healthcare today. That forward-thinking attitude prompted Xconomy to invite Funtleyder to moderate our first public New York event, Life Sciences 2031, a panel discussion that will take place October 13 at the Alexandria Center for Life Science.
Funtleyder, who is also author of the book Health Care Investing (McGraw Hill 2009), spends his days contemplating what the future will hold for pharmaceuticals, biotechnology, and health care—and searching for the companies that are best poised to capitalize on those trends. So he’s excited by the prospect of polling the event’s four panelists on current trends in those industries and what they portend for the next 20 years. “The level of expertise on this panel will give the current era some context,” Funtleyder says.
The panelists bring a wide range of experience to bear on what’s sure to be a lively discussion. Sam Waksal was the founder and CEO of ImClone Systems and now serves as CEO of Kadmon, a New York-based biotech startup working on drugs to treat cancer, autoimmune diseases, and infectious diseases. Barbara Dalton is a scientist-turned-investor—a Ph.D. trained in virology and immunology who is now VP of venture capital for Pfizer. Sam Isaly, founder of OrbiMed Advisors, manages the popular Eaton Vance Worldwide Health Sciences Fund. And Eric Schadt is a genomics expert who serves as the chief scientific officer of Pacific Biosciences, as well as the director of the New York-based Mount Sinai Institute for Genomics and Multiscale Biology.
Funtleyder expects all the panelists to weigh in on one of the top questions on everyone’s mind: What are the next areas of growth in research? “The fact that they’ve all been around a while will allow them to bring to the table some ideas about how we can increase R&D productivity in the industry,” Funtleyder says.
For his part, Funtleyder believes R&D has reached an inflection point. “We had Genomics Part 1—the sequencing of the human genome,” he says. “Now there’s Genomics Part 2. The cost of sequencing a genome has come down from $3 million to $1,000 and the speed has gone up. Is this going to lead us into better drug discovery in the next decade? Or are we having another fad and nothing will ever come from it? That will be an interesting question to discuss.”
Personalized medicine is one of the goals of genomics research, Funtleyder points out, and will no doubt be part of the discussion at New York Life Sciences 2031. “Personalized medicine is the holy grail. But are we there yet? I don’t know. It seems like it’s inevitable. But what’s the timing? It could be a while,” he says.
Pfizer’s Barbara Dalton will bring valuable perspective as someone from Big Pharma’s ranks, Funtleyder predicts. “What’s the business model of the future?” he wonders. “Pfizer is setting up campuses all over, in Massachusetts, New York, California. Is that the new model—hiring universities, basically, to do research for you?” Funtleyder is also interested in how Pfizer’s acquisition choices might impact the rest of the industry. “The old saying is ‘If Pfizer sneezes, the industry catches a cold,’” he says. “What Pfizer does will guide what other companies do, and it will also affect the decision making by small and mid-cap biotechs. They want to make themselves attractive to Big Pharma.”
Funtleyder also wonders what the future holds for small biotechs. Some promising startups are getting snapped up by Pfizer and other large companies, he notes. But what about the legions of small biotechs that need years of research to bring their ideas to fruition—and the capital to support those projects? He’s particularly interested in what “Sam and Sam” will have to say about that, seeing as Waksal is running a startup, and Isaly’s firm has a venture arm. “It seems like private equity and venture capitalists are taking less risky bets,” Funtleyder says. “Is this setting us up to no longer have a small biotech industry in the middle of the decade? The good ones will get acquired, the bad ones will go out of business, and we’re not seeing too many public offerings.”
The biggest macro-risk for the future of the industry, Funtleyder believes, is government spending. “We’re having cost problems in the U.S.—that’s not going to go away,” he says. “We’re going to have health care reform. How are we going to grapple with it over the next decade?” Funtleyder hopes to gather perspectives and advice on that issue from all four panelists.
This being a New York event, there will, no doubt, be plenty of discussion about what needs to happen for the city to become a biotech hotbed—long the goal of Mayor Michael Bloomberg and other politicians. “This has been a knock on Manhattan forever,” Funtleyder says. “We have eight research institutions and more people than Boston or San Francisco. It’s always been a mystery to me why we don’t have a thriving biotech industry.”
The four panelists should have some creative ideas for fostering growth in the city’s life sciences sector, Funtleyder believes. “This is a great industry from an economic-development point of view,” he says. “Having life sciences as a growth engine in this town would create other growth engines.”
Funtleyder won’t be the only one firing questions at our panelists, as we will leave plenty of time for audience Q&A. So please join us at Xconomy Forum: New York Life Sciences 2031 by registering here.
[Having spent 14 years as Professor of New York University Medical School, originating a tensor- and now fractal geometrical approach to identify the intrinsic mathematics of living systems (both in Neuroscience and Genomics, unifying the two) I have plenty observations and suggestions to share. This comment can be discussed in the FaceBook page of Andras Pellionisz]
Lost In Translation? Andy Grove blasts "Change the System!" in his Anti-Medical School Course at UC Berkeley
California Institute for Quantitative Biosciences
published by Adam Mann on Thu, 09/01/2011 - 16:57
In QB3’s Anti-Medical School course, UC Berkeley and UCSF bioengineering students try to solve real-world problems that doctors face in the clinic.
Wednesday night, QB3 hosted a talk at Byers Auditorium in Genentech Hall entitled “Translational Medicine: Key to Progress or Bridge to Nowhere.” Speaking at the lecture was Andy Grove, co-founder and former CEO of the semiconductor giant Intel.
Grove spoke about the problems currently facing drug development. In terms of time and investment, he said the closest equivalent process in history to the creation of a single drug is the construction of a single pyramid in ancient Egypt. According to his estimates, a pyramid cost the equivalent of $1.5 billion US dollars and took 20 years to construct—similar to the average drug development cost and time in the US since the early 90s.
Things are only set to get worse. Grove pointed out that modern science is currently facing a new age of genetic- and cellular-based personalized medicine. The complexity of delivering such individualized drugs repeatedly and effectively will require a new way of thinking about medicine. Researchers will need to rely heavily on integrative technology and collaboration. Grove cited the implantable artificial kidney under development in the lab of Shuvo Roy at UCSF as one such approach to overcoming such problems.
But other difficulties loom. Because of the extraordinary complexity of personalized medicine, researchers have a hard time telling the truly relevant effects from everything else, said Grove. [Algorithm of Fractal Recursive Iteration has "parameters" - keeping fractality intact, resulting in harmless human diversity, whereas "syntax fractal defects" breach the fractal integrity - a revolutionary way to tell chaff from needles in a haystack - AJP]. This unsettles investors, who consider biotech a “risky business at risk.” Currently, potential biotechnology seed investments are diverted to Silicon Valley social networking sites, he said.
And then he delivered the bad news.
According to Grove, the industry is not primed for the overwhelming change it will face in the coming decades. Transformation is needed, he said repeatedly. This revolution will only come if people can lower the resistance to flow of knowledge from labs and research organizations to pharmaceutical companies.
Ideally, Grove said, knowledge flows from a medical center to industry and dollars flow back. Biotech startups are the perfect transitional step between such institutions. Unfortunately, due to difficulties in integration and regulation, nothing flows either way, said Grove.
The solution for him is to do science and early research inside the industry. Grove cited his work at Intel, where he got rid of the R&D department and placed it entirely inside manufacturing, streamlining the process. Perhaps such a model could be a boon to clinical medicine, he suggested.
Regulation has also become a barrier to companies trying to develop new medicine, said Grove. Because it is so easy to file, the US patent office is overwhelmed with trivial and obvious inventions. This is threatening and kills innovation, he said. Furthermore, the agency has been slow to upgrade from paper-based technology to computers, which would greatly reduce waste and increase speed, he said. [A good illustration is that the USPTO requires, in its latest twist of an ardous struggle, more than 9 years of the priority date of submission in 2002 August a re-writing of FractoGene core-patent, incorporating attachments already submitted. The expense of this (and claiming extension for 9 years lost) forces a "shotgun marriage" with a giant that can handle this imposed burden - while benefitting a lucky US IT global leader, determined to edge into Genome Analytics 50/50 from the now incredibly precious early priority-date - AJP]
In addition, the FDA, while trying to help, has also slowed innovation. Every year, 800,000 scientific papers related to new drugs appear in the literature, said Grove. From these, 6,000 new drugs make it to phase 3 FDA trials. But because of stringent standards, only 20 new drugs come to market each year.
Still, Grove’s talk was not all about gloom and doom. He urged scientists and doctors to get involved in trying to change the system. Ultimately, researchers need to look into doing science that’s not just for itself, Grove said. They need to produce products that help people.
Comment on the Article by Pellionisz:
Happy Birthday, dear Andy! It speaks volumes that a truly great man celebrates his landmark birthday-eve by looking ahead to swim across rough waters of the future of human kind. The absolute need of "new ways to think about medicine" [and biology at large] recalls perhaps just two outstanding precedents. John von Neumann turned to an informatics-based biology having accomplished so much for the first serial computer architecture. Neumann looked ahead to times when "the von Neumann bottleneck" will halt what later became "Moore's Law". Gordon Moore's genome fully sequenced twice just recently most likely makes also Andy Grove think in overdrive how to put genome analytics code on a chip, as the future device capable to match the data-flow parallel processing by the genome itself. Prior to von Neumann, Nobelist Schrödinger addressed in "What's Life" the quantal hereditary code-script as information by aperiodical covalent bondings of hydrogen. Without turning the vision into reality of giants of thinker-architects of strategies for a better future human kind will do poorly. [This comment can be discussed at the Lost in the Translation original website, as well as in the FaceBook page of Andras Pellionisz]
[A particularly crass example of "scientists" who never produced anything to help people suffering from "Junk DNA diseases", but on the contrary as a detractor excelled only in badmouthing pioneers of genome informatics is a Canadian Academic in semi-retirement. With his blog "Revisiting the Central Dogma in the 21st Century", while 11 years late even with his calendar and unable to produce mathematically properly rounded percentage-numbers, the topic fetched to date an astronomical, close to 500 comments, the vast majority is totally off-topic cyber-sewage and cyber-libel. One trying to focus on the issue asked "what if Crick was dead wrong with his Dogma?" and an answer pointed out that even Crick considered that as a "game changer". Nonetheless, an avalanche of superficial comments from people who admitted their incompetence in science matters, produced an utterly worthless "papering over" of the issue itself, by digressing into a flabbergasting array of meaningless tangentials. Perhaps out of his embarrassment (over becoming infamous for his libelious badmouthing) the blog-owner (while still uphelding the legally faulty policy making him liable of letting "anonymous" postings) now openly censors out attempts to steer attention to the paradigm-shift necessitated by historical failures of the two mistaken dogmas of Old School Genomics - AJP]
W.M. Keck Foundation awards Jefferson scientists with $1M medical research grant [Rigoutsos - AJP]
Published on August 4, 2011 at 2:23 AM
Scientists at Thomas Jefferson University have been awarded a $1 million medical research grant from the W.M. Keck Foundation for an ambitious project looking at the little explored 98 percent of the human genome and what role it may play in the onset and progression of diseases.
The multidisciplinary team, led by Computational Medicine Center at Jefferson director Isidore Rigoutsos, Ph.D., will soon begin studying a particular group of DNA motifs-genomic combinations of letters that repeat more frequently than expected by chance-called pyknons. Researchers and physicians will be looking at what function they serve in the context of several types of cancers, platelet aggregation properties, two autoimmune disorders, and type-1 diabetes.
Dr. Rigoutsos, a world-renowned computational biologist, originally discovered pyknons in 2005 using computational analyses. In the time since their discovery, evidence has been slowly accumulating that these pyknon motifs mark transcribed, non-coding RNA sequences with potential functional relevance in human disease.
"This is very exciting. The grant comes on the heels of six years of research," said Dr. Rigoutsos. "It will help us get to the bottom of this story: an unexplored territory that we strongly suspect has something important to reveal about human disease. There is disconnected evidence, and we want to assemble all the pieces."
For many years, Rigoutsos, who came to Jefferson in 2010 following a nearly 18-year tenure at IBM's Research Division, focused on generating conspicuous tidbits of evidence computationally, the result of his not having access to experimental facilities. All of this has, of course, changed at his new home: the Computational Medicine Center, which he founded at Jefferson last year.
Now, he said, he can cast a wider and deeper net by studying pyknons using samples from a diverse collection of human conditions: prostate, colon and pancreatic cancer, chronic lymphocytic leukemia, type-1 diabetes, hyper- and hypo-reactivity in platelets, multiple sclerosis, and systemic sclerosis. Dr. Rigoutsos is also a member of the Kimmel Cancer Center at Jefferson.
The goal is to investigate the presence of pyknon-marked non-coding RNAs in these conditions and determine the rules governing the biogenesis, processing, and mechanisms of regulatory action of these transcripts. The planned research activity will involve a combination of computational analyses and modern experimental techniques.
The winning team comprises researchers and physicians from the Computational Medicine Center and several Departments of Thomas Jefferson University and Hospital, the Children's Hospital of Philadelphia, the University of North Carolina at Chapel Hill, and the University of Texas' MD Anderson Cancer Research Center.
"It is a great honor to be recognized by the W.M. Keck Foundation, which has a long history of supporting innovative and pioneering medical research," said Mark L. Tykocinski, M.D., Dean of Jefferson Medical College and Senior Vice President of Thomas Jefferson University. "This is a unique award for a unique area of human genome research that, with our multidisciplinary approach, will undoubtedly pave the way for breakthrough discoveries to help better treat and prevent diverse diseases."
[Nobel Prizes in Genomics will be awarded in Physics, for biophysicists, picking up the trail left by Erwin Schroedinger (What is Life? - 1944) who predicted that non-periodical covalent bondings of hydrogen encode life by a mathematics unknown to him - and the rest of the World. After the "Big Genome Letdown" decade since Full Human DNA sequencing (revealing the sequence of bondings, but absolutely not "cracking the code" how life is encrypted in a sequence, a new era started with biophysicists (often, with degrees in pure math, bioinformatics, computer science, etc) - who have been traditionally sidetracked as "rebels". Now, "rebels are becoming leaders". Isidore Rigoutsos is in the same rank as Eric Schadt or Eric Lander (soon, Francis Collins will also be widely known to have had quantum mechanics before his full M.D./Ph.D...). There will be no Nobel Prize for "the gene of cancer, schizophrenia, autism, diabetes etc. - since with the failed "gene discovery" is extremly unlikely to come up with (almost for sure, non-existent) "genes for complex hereditary syndromes". (This is not to deny, that about 2,800 so-called "Mendelian diseases" are already on record, since even a single letter of A,C,T,G can turn by mutation an amino-acid producing codon e.g. into a "premature termination codon" - thus resulting in truncated thus disfunctional or even toxic protein and thus dreadful disease. However, "Genome Regulation Diseases" will not be so "easy" to map - an entirely new science is needed to mathematically understand "Recursive Genome Function" - though as yet still a minority of leading scientists are fully aware of the game-changer of discarding an "open loop" obsolete axiom and carting in the "recursive, e.g. fractal iteration" algorithms. Eric Lander already joined the fray of the "fractal nature of DNA" - grabbing Grosberg's 20+ year old seminal concept of fractal folding of the 2m long "noodle" of DNA into the 6 micron radius nucleus of a cell. Lander commands the $600 M Broad Institute (by grace of Eli & Edythe Broad). Eric Schadt, a "rebel" who told off one of the biggest of Big Pharma that they'd have to become a "genome informatics company" was dismissed as an outright "rebel" - but now Eric Schadt, in addition to CSO of PacBio, assumed Directorship of the $100 M Mount Sinai Institute of Genomics and Multi-Scale Biology ("multi-scale" rhymes with "scale-free"...). Another mathematician, Isidore Rigoutsos, while enjoying the comfort of IBM Watson Center for almost 2 decades, graced the somewhat unwilling World by his "pyknon"-s (short repetitive segments of DNA snippets that appear throughout genes and "Junk" with frequency far exceeding non-significant repetitions. It took a year to get his work published - yet another "rebel" trampling on the no man's land of "Junk" considered undesirable - but now he has his own Institute to lead progress. While Isidore did not focus his immediate attention to the distribution-curve of pyknon-like elements of a full DNA, in my Cold Spring Harbor Laboratory presentation (2009), upon invitation by George Church I provided evidence that they follow the Zipf-Mandelbrot Fractal Parabolic Distribution Curve (see Figs. 11-14). It may be, that Academic Institutes like the above are needed before Industrialization of Genomics will make Sequencing Industry sustainable by matching Analytics Industry - or history will show that the next quantum-leap is a better solution, turning paradigm-shift science into an IT-led "New Pharma" based on "Genome Computing Business" (the latter already a fact accomplished by SAMSUNG). - This entry can be discussed in the FaceBook page of Andras Pellionisz]
Samsung Launches Genome Analysis Service, Offers Free Genome
Bio-IT World
By Allison Proffitt
August 23, 2011
Samsung SDS is launching beta testing of its new next generation sequencing data analysis service beginning September 1. The Samsung SDS Genome Data Analysis Service will provide analysis services for whole genome sequencing and RNASeq for both Life Technologies and Illumina sequencers. The service will be in beta testing mode from September to November and will be offering free genome analysis (one genome per researcher) during the testing phase.
The service will be Cloud-based, with all analysis being done on the Samsung cloud in Korea. Users can either upload their data, or send a hard drive. “The customer will be actually going to our website and filling out the order form… [to get] their whole genome analyzed and their RNA analyzed,” SungKwon Kim, director of the Bioinformatics Lab, told Bio-IT World. Results are returned to the user online via Samsung’s own genome browser. “User should be able to easily navigate their genomic analysis with our web browser once we finish the genomic analysis.”
The algorithms that Samsung SDS is using for analysis are a combination of open source and vendor provide softwares with Samsung’s own proprietary “tweaks”.
Bioinformatics is a newer area for Samsung, but Kim expects it to be a growth area for the company in the years to come. “We are known for the enterprise-level IT business. When I say enterprise level, we’ve been working with system innovation with banks, high profile, Fortune 500 companies, so when it comes to data security… I don’t think any other vendor companies should be able to match with our capabilities in security, recovery handling, those kinds of things.”
Kim also believes that Samsung will offer faster genome analysis than its competitors or in house options. He expects the final service to take 5 days for whole genome analysis and 3 days for RNA analysis.
Interested parties can sign up for beta test beginning on September 1 on the Samsung Genome website http://www.samsunggenome.com.
[I predicted in 2004 that the formative event, as far as technology and business are concerned, would be when the "tectonic plates" of IT and Genomics will pile up, resulting in the "earthquake" in Industrialization of Genomics. I would never guess that it would be Korea (Samsung) beating the World to the punch, including IBM (Rigoutsos just left...), Intel (pioneering investment into sequencing, but Schadt has just left for most of his activities from Silicon Valley to New York City), Microsoft, Google, Oracle or even Dell or HP not really engaged into Genome Analytics in earnest, and even Sony, Fujitsu or Japan only explored the option but now are beaten in the all-important, indeed crucial "rush to market". One wonders if the world will rush to ship their full genomes to Korea (with the dubious claim that their security beats everyone...), and - as pointed out in my YouTube (2008) Genome IT means not one, but two things. Genome Information Technology is the relatively "easy" part (with Samsung now in the lead), but Genome Information Theory (intrinsic algorithms of recursive genome function) are much harder. HolGenTech, Inc. in Silicon Valley put IP since 2002 into the focus Genome Information Theory - and is now ready to beat the "combination of open source and vendor provide softwares with Samsung’s own proprietary “tweaks”" - This entry can be discussed on the Facebook page of Andras Pellionisz]
Comment by Andras J. Pellionisz to New York Times "Cancer's Secrets coming into Sharper Focus"
The following (unpublished) comment is better suited to this more specialized audience:
It is a pleasure to see in the superb coverage of NYT that both mistaken and very seriously stated axioms are finally discarded; Crick's over half-a-Century "Central Dogma", held from 1956 to his passing in 2004, and Ohno's "So much "Junk" DNA in our genome" erroneous theory published in 1972 and held until his death in 2000. The establishment acknowledged first in 2007 when the NIH-organized ENCODE project revealed that the human DNA is "pervasively transcribed", and now that entirely new conceptual basis is available to mathematically formulate genome regulation in terms of advanced (software-enabling) algorithms of fractal iterative recursion, as well as explaining how aberrant methylation and chromatin modulation of regulatory sequencing leads to uncontrolled (cancerous) growth. The peer-reviewed science paper is The Principle of Recursive Genome Function (2008) and the misregulation by aberrant methylation and chromatin modulation leading to cancer is specifically demonstrated at min. 30:00 of the Google Tech Talk YouTube (2008) and subsequent Cold Spring Harbor Presentation invited by George Church (2009). Indeed, present NIH Head Dr. Collins called upon conclusion of ENCODE in 2007 that "the community of scientists have to re-think long-held beliefs". A lucky few did not have to "re-think" old dogmas, since they never believed in them in the first place, for reasons of cross-disciplinary domain expertise of informatics-essentials of biophysics - but publication of formerly "lucid heresy" (on both counts, since iterative fractal recursion "violated" both the Central Dogma and Junk DNA rules of the establishment) was only possible floated in the self-edited Cambridge University Press book-chapter Neural Geometry: Towards a Fractal Model of Neurons (1989). The NIH Grant Proposal -duly acknowledged in the book chapter- was rejected, and an ongoing NIH Grant was discontinued. Nearly ¼ Century later, since “our concepts of genome regulation are frighteningly unsophisticated”, the immediately utility of advanced algorithmic (software enabling) approaches is now palpable. This post can be discussed in the FaceBook page of Andras Pellionisz.
Everything Scientists Thought They Knew About Cancer Might Be Totally Wrong
A 2000 study called The Hallmarks of Cancer is the most-referenced paper in the journal Cell, one of the most influential journals in the world. Turns out that paper might be wrong.
And that might partly explain why cancer death rates are falling slowly.
The theory, which is illustrated in the video above, basically says that sometimes cells lose their ability to regulate growth and go crazy, creating cancer tumors. The New York Times reports that at the recent annual meeting of the American Association for Cancer Research in Orlando, Florida, scientists had a whole lot of other theories up their sleeves.
One states that microbes, which include tiny creatures like bacteria and make up 90 percent of the cells in our body, sometimes turn against us to cause cancer.
Another theory is that what scientists used to think was "junk DNA" and makes up 98 percent of our DNA (only two percent is the kind that actually instructs genes) is not junk at all but a mechanism for causing cancer, among other things.
Lastly, micoRNAs might be the culprit. Until recently scientists thought they didn't do much, but now they're starting to think that microRNAs might intercept or block messages from DNA to messenger RNA.
If all of that seems crazy-complicated, check out this pretty awesome video the New York Times created for you.
Of course, cancer ain't talkin' so these theories might be totally wrong too. But one thing's for certain: smoking is still bad. Damn.
---
Cancer’s secrets are coming into sharper focus
By George Johnson / New York Times News Service
Published: August 16. 2011 4:00AM PST
For the last decade cancer research has been guided by a common vision of how a single cell, outcompeting its neighbors, evolves into a malignant tumor. Now recent discoveries are providing new details. Cancer appears to be even more willful and calculating than previously imagined.
Through a series of random mutations, genes that encourage cellular division are pushed into overdrive, while genes that normally send growth-restraining signals are taken offline.
With the accelerator floored and the brake lines cut, the cell and its progeny are free to rapidly multiply.
More mutations accumulate, allowing the cancer cells to elude other safeguards and to invade neighboring tissue and metastasize.
These basic principles — laid out 11 years ago in a landmark paper, “The Hallmarks of Cancer,” by Douglas Hanahan and Robert Weinberg, and revisited in a follow-up article this year — still serve as the reigning paradigm, a kind of Big Bang theory for the field.
But recent discoveries have been complicating the picture with tangles of new detail.
Most DNA, for example, was long considered junk — a netherworld of detritus that had no important role in cancer or anything else. Only about 2 percent of the human genome carries the code for making enzymes and other proteins, the cogs and scaffolding of the machinery that a cancer cell turns to its own devices.
These days “junk” DNA is referred to more respectfully as “noncoding” DNA, and researchers are finding clues that “pseudogenes” lurking within this dark region may play a role in cancer.
“We’ve been obsessively focusing our attention on 2 percent of the genome,” said Dr. Pier Paolo Pandolfi, a professor of medicine and pathology at Harvard Medical School. This spring, at the annual meeting of the American Association for Cancer Research in Orlando, Fla., he described a new “biological dimension” in which signals coming from both regions of the genome participate in the delicate balance between normal cellular behavior and malignancy.
As they look beyond the genome, cancer researchers are also awakening to the fact that some 90 percent of the protein-encoding cells in our body are microbes. We evolved with them in a symbiotic relationship, which raises the question of just who is occupying whom.
“We are massively outnumbered,” said Jeremy Nicholson, chairman of biological chemistry and head of the department of surgery and cancer at Imperial College London. Altogether, he said, 99 percent of the functional genes in the body are microbial.
In Orlando, he and other researchers described how genes in this microbiome — exchanging messages with genes inside human cells — may be involved with cancers of the colon, stomach, esophagus and other organs.
These shifts in perspective, occurring throughout cellular biology, can seem as dizzying as what happened in cosmology with the discovery that dark matter and dark energy make up most of the universe: Background suddenly becomes foreground and issues once thought settled are up in the air. In cosmology the Big Bang theory emerged from the confusion in a stronger but more convoluted form. The same may be happening with the science of cancer.
Exotic players
According to the central dogma of molecular biology, information encoded in the DNA of the genome is copied by messenger RNA and then carried to subcellular structures called ribosomes, where the instructions are used to assemble proteins. Lurking behind the scenes, snippets called microRNAs once seemed like little more than molecular noise. But they have been appearing with increasing prominence in theories about cancer.
By binding to a gene’s messenger RNA, microRNA can prevent the instructions from reaching their target — essentially silencing the gene — and may also modulate the signal in other ways. One presentation after another at the Orlando meeting explored how microRNAs are involved in the fine-tuning that distinguishes a healthy cell from a malignant one.
Ratcheting the complexity a notch higher, Pandolfi, the Harvard Medical School researcher, laid out an elaborate theory involving microRNAs and pseudogenes. For every pseudogene there is a regular, protein-encoding gene. (Both are believed to be derived from a common ancestral gene, the pseudogene shunted aside in the evolutionary past when it became dysfunctional.) While normal genes express their will by sending signals of messenger RNA, the damaged pseudogenes either are mute or speak in gibberish.
Or so it was generally believed. Little is wasted by evolution, and Pandolfi hypothesizes that RNA signals from both genes and pseudogenes interact through a language involving microRNAs. (These signals are called ceRNAs, pronounced “sernas,” meaning “competing endogenous RNAs.”)
His lab at Beth Israel Deaconess Medical Center in Boston is studying how this arcane back channel is used by genes called PTEN and KRAS, commonly implicated in cancer, to confer with their pseudotwins. The hypothesis is laid out in more detail this month in an essay in the journal Cell.
In their original “hallmarks” paper — the most cited in the history of Cell — Hanahan and Weinberg gathered a bonanza of emerging research and synthesized it into six characteristics. All of them, they proposed, are shared by most and maybe all human cancers. They went on to predict that in 20 years the circuitry of a cancer cell would be mapped and understood as thoroughly as the transistors on a computer chip, making cancer biology more like chemistry or physics — sciences governed by precise, predictable rules.
Now there appear to be transistors inside the transistors. “I still think that the wiring diagram, or at least its outlines, may be laid out within a decade,” Weinberg said in an email. “MicroRNAs may be more like minitransistors or amplifiers, but however one depicts them, they still must be soldered into the circuit in one way or another.”
In their follow-up paper, “Hallmarks of Cancer: The Next Generation,” he and Hanahan cited two “emerging hallmarks” that future research may show to be crucial to malignancy — the ability of an aberrant cell to reprogram its metabolism to feed its wildfire growth and to evade destruction by the immune system.
Unwitting allies
Even if all the lines and boxes for the schematic of the cancer cell can be sketched in, huge complications will remain. Research is increasingly focused on the fact that a tumor is not a homogeneous mass of cancer cells. It also contains healthy cells that have been conscripted into the cause.
Cells called fibroblasts collaborate by secreting proteins the tumor needs to build its supportive scaffolding and expand into surrounding tissues. Immune system cells, maneuvered into behaving as if they were healing a wound, emit growth factors that embolden the tumor and stimulate angiogenesis, the generation of new blood vessels. Endothelial cells, which form the lining of the circulatory system, are also enlisted in the construction of the tumor’s own blood supply.
All these processes are so tightly intertwined that it is difficult to tell where one leaves off and another begins. With so much internal machinery, malignant tumors are now being compared to renegade organs sprouting inside the body.
As the various cells are colluding, they may also be trading information with cells in another realm — the micro-organisms in the mouth, skin, respiratory system, urogenital tract, stomach and digestive system. Each microbe has its own set of genes, which can interact with those in the human body by exchanging molecular signals.
“The signaling these microbes do is dramatically complex,” Nicholson said in an interview at Imperial College. “They send metabolic signals to each other — and they are sending chemicals out constantly that are stimulating our biological processes.
“It’s astonishing, really. There they are, sitting around and doing stuff, and most of it we don’t really know or understand.”
People in different geographical locales can harbor different microbial ecosystems. Last year scientists reported evidence that the Japanese microbiome has acquired a gene for a seaweed-digesting enzyme from a marine bacteria. The gene, not found in the guts of North Americans, may aid in the digestion of sushi wrappers. The idea that people in different regions of the world have co-evolved with different microbial ecosystems may be a factor — along with diet, lifestyle and other environmental agents — in explaining why they are often subject to different cancers.
The composition of the microbiome changes not only geographically but also over time. With improved hygiene, dietary changes and the rising use of antibiotics, levels of the microbe Helicobacter pylori in the human gut have been decreasing in developing countries, and so has stomach cancer. At the same time, however, esophageal cancer has been increasing, leading to speculation that H. pylori provides some kind of protective effect.
At the Orlando meeting, Dr. Zhiheng Pei of New York University suggested that the situation is more complex. Two different types of microbial ecosystems have been identified in the human esophagus. Pei’s lab has found that people with an inflamed esophagus or with a precancerous condition called Barrett’s esophagus are more likely to harbor what he called the Type II microbiome.
“At present, it is unclear whether the Type II microbiome causes esophageal diseases or gastro-esophageal reflux changes the microbiome from Type I to II,” Pei wrote in an email. “Either way, chronic exposure of the esophagus to an abnormal microbiome could be an essential step in esophageal damage and, ultimately, cancer.”
Unseen enemies
At a session in Orlando on the future of cancer research, Dr. Harold Varmus, the director of the National Cancer Institute, described the Provocative Questions initiative, a new effort to seek out mysteries and paradoxes that may be vulnerable to solution.
“In our rush to do the things that are really obvious to do, we’re forgetting to pay attention to many unexplained phenomena,” he said.
Why, for example, does the Epstein-Barr virus cause different cancers in different populations? Why do patients with certain neurological diseases like Parkinson’s, Huntington’s, Alzheimer’s and Fragile X seem to be at a lower risk for most cancers? Why are some tissues more prone than others to developing tumors? Why do some mutations evoke cancerous effects in one type of cell but not in others?
With so many phenomena in search of a biological explanation, “Hallmarks of Cancer: The Next Generation” may conceivably be followed by a second sequel — with twists as unexpected as those in the old “Star Trek” shows. The enemy inside us is every bit as formidable as imagined invaders from beyond. Learning to outwit it is leading science deep into the universe of the living cell.
[The Cancer Establishment "threw in the towel" - giving up on the old axiom of looking for "cancer gene". Now they bank on more sophisticated approaches, where the two mistaken axioms ("Junk DNA" and "Central Dogma") are given up. Good time for the "Jim Clark"-s of Postmodern Genomics to jump on the fractal bandwagon of HolGenTech, Inc.! - This post can be discussed on the FaceBook page of Andras Pellionisz]
Author(s): Dinsa Sachan
Issue: Aug 15, 2011
Down to Earth (India)
Personal genomics makes individualised healthcare possible; but experts remain wary.
SOUMYA Swaminathan’s 16-year-old son, Sudarshan, loves sports, and is training to be a footballer. Two years ago, he was confused which sport to train in. “He would come home and say he wants to play cricket. Next week it would be football,” says Swaminathan. Then she heard about the sports DNA test offered by Super Religare Laboratories (SRL). The Mumbai-based firm had just launched the test, which would examine DNA from your saliva sample for variants of a gene linked with sporting prowess. It turned out that Sudarshan had a genetic predilection for power sports. “So we decided to focus on football and basketball,” she adds.
Gene testing is no longer restricted to paternity testing and DNA fingerprinting for criminal cases. It has varied avenues from giving details about what diseases you are likely to contract to which sports are suited for you. Experts say the personal genomics is the future of science. All you have to do is give saliva or blood sample and within days a comprehensive feedback on your health, which includes what diseases you are more or less likely to develop over your lifetime, is handed over to you.
“Personalised medicine means different things to different people. Some see it as targeted genomics where changes in specific genes predict responses to specific therapies,” says John Tomaszewski, president, American Society for Clinical Pathology. Others might see it as cellular engineering where one’s own cells are removed, re-engineered to treat a specific disease, and then re-infused into the patient, he adds. Both of these strategies are in limited use today, but hold hope for individualised healthcare.
Beginning and future
The seeds of personalised genomics were first sown in 1990 when the Human Genome Project (HGP) was conceived by a team of scientists in the US. The project, which lasted 13 years, identified and mapped the entire human genome—approximately 30,000 genes.
The Personal Genome Project (PGP), pioneered by George Church, one of HGP’s founders, is the next step. HGP mapped the genome of an anonymous person, while the PGP, when completed, will have genetic information of several individuals as well as their phenotypic information. Through this researchers can study the connections between gene functions and physical traits. The project is in process gathering genotypical information for 100,000 participants.
Rush to capitalise on science
Besides the research-based projects like PGP, the more visible side of the personal genomics industry are commercial enterprises like 23andme, Navigenics and Knome that offer different genetic tests to people. Companies like the California-based 23andme, which was floated in 2006, take a saliva sample of the customer and predict susceptibility to 199 genomic conditions including cancer and diabetes. It also has a research division, 23andWe, which published its first paper in June 2011 pinpointing genetic origins of the Parkinson’s disease.
23andme, along with ventures like Navigenics, belongs to the direct-to-consumer bracket that rely on SNP (single nucleotide polymorphism) genotyping. SNPs are particular point-locations in human DNA showing errors. Some SNP’s influence traits like physical appearance and susceptibility to diseases.
23andme sequences only a portion of one’s genome. Other players like Knome and Illumina, whose technology is used by a number of projects, offer whole genome sequencing services, which list every minute detail of your genetic fingerprint. Knome’s DNA analytics service is priced at US $4,998. When it was launched, 23andme charged US $999 for its sequencing service. The cost was slashed to US $399 two years later. Now, the company offers a package for USD $99, which includes a year’s mandatory subscription for US $9 per month in which participants are informed about any new updates from their single saliva sample.
“The price to sequence bases has fallen a million times from when HGP started with three billion ,” says Richard Resnick, CEO of GenomeQuest, a genome sequence management company. He adds that the cost will drop to as low as US $1,000 till next year.
Where India stands
Although companies like 23andme have not yet arrived in India, the country has been making strides in the field of personal genomics. Institute of Genomics and Integrative Biology (IGIB) in New Delhi mapped the first human genome in 2009. “Though India started slow in the field we are catching up,” says Rajesh Gokhale, Director, IGIB.
On the commercial side, only SRL [Super Religare Laboratories] has set its shop in the country. It takes a cheek swab and tests it for variations within the gene (ACTN3) associated with athletic performance in numerous studies. SRL tests children for two variants of the gene. According to B R Das, research and development chief at SRL, individual having the R variant of the gene have a possibility of excelling in sports that require short, powerful bursts of energy. The other variant, X, may be more useful in endurance sports like cricket. The test has been taken by 3,000 people across India. It costs Rs 2,000.
Binay Panda, head of Ganit Labs, Institute of Bioinformatics and Biotechnology in Bengaluru, believes India should develop its genomic potential in the direction which can benefit population at large. He sees a potential in medicine. His lab is trying to pin down the genetic causes of cancer. “This can help us devise specific diagnostic and prognostic techniques that would detect cancer at an early stage,” he adds.
In doubt
But experts remain critical about the disease assessments made by companies. “As far as sequencing some parts of genome and making predictions is concerned, we do know a fair amount about specific diseases and mutations associated with them,” says Kevin Rosenblatt, director, Center for Clinical Proteomics at The University of Texas Medical School at Houston. But when we consider the whole genome and the vast number of mutations that each of us carries in our DNA, science is not that well developed, he adds.
Gil Atzmon, assistant professor of genetics and medicine, Albert Einstein College of Medicine in the US, says, “Risk is not necessarily illness, and the probability of getting a disease is dependent on many factors, especially when epigenetics—response of gen ome to stress, diet, toxins and much more—is introduced to the equation.” He adds that two people can have the same genetic blueprint but are vulnerable to different diseases based on the environment they interact with. Andras Pellionisz, head of HolGenTech Inc, which makes genome analysing software, believes analysing genomes presents various challenges which current technology is not adequately prepared to meet. “The biggest challenge is interpretation. Genome is a changing repository of information because mutations and actual sequence alterations happen throughout life.”
Indian researchers are also wary of such endeavors. “The test by SRL measures one factor of energy metabolism. Will you become a sportsperson or not depends on other factors like environment also,” says Gokhale. Panda dubs the tests as “recreational genomics”.
Ethical and legal issues
When genomics companies were sprouting, the debate revolved aro und ethical issues and these still continue to haunt it. Critics question the repercussions of telling people what diseases they are vulnerable to. There are also concerns that health insurance companies might exploit the information and not insure one based on the probability of having a specific disease. Though US has a law— The Genetic Information Nondiscrimination Act—that protects US citizens from “genetic discrimination” no other country has such a legislation.
[I made a technical comment on "biological information" to the Article (click on the headline-link to view). Additionally, I attribute the biggest significance to this news that it amounts to yet another entry to the "DTC becames global" trend, with Mumbai-based Super Religare Laboratories. This comment can be discussed at the FaceBook page of Andras Pellionisz]
Researchers uncover a new method of checking for skin cancer
01 July 2011 @ 11:41 am EDT
Medical Daily
[Skin Cancer? There is an app for it ... AJP]
Skin Scan, a Romanian startup, claims it has found a way to measure the amount of risk a mole represents using a proprietary algorithm combined with an iPhone image of the mole which it says can measure the likelihood of it representing skin cancer.
The app raises awareness of a particularly aggressive disease which kills when people aren't aware of the serious nature of a mole that might have developed from over-exposure to harmful sunlight.
"It is accepted that human tissues have a fractal-like structure." says P.hD Mircea Olteanu, brains behind the app, "Consequently, during the last decades scientists tried to classify different types of tumors by computing their fractal dimension and numerical characteristics... Skin Scan is a skin cancer prevention tool which tells users when to look for a professional medical investigation."
Commonly found in Caucassions 1:80, the disease is largely preventable by precautionary measures and Skin Scan hopes to take that a step forward by getting people to check for their mole's more regularly - with an iPhone.
The app measures the mole's size and uses various characteristics, such as it's fractal nature - smoothness, colour and other irregularies to keep an eye on more serious ones.
If the app detects a change in the mole, it sends them to the doctor.
"Skin Scan is a skin cancer prevention tool which tells users when to look for a professional medical investigation...Our team encourages the use of this modern technology that alerts users to seek medical help in time." continued Mircea Olteanu.
The team is run by Mihai Mafteianu of Cronian Labs in Romania. It’s headed up by CEO Victor Anastasiu, co-founder of Romanian seed fund SeedMoney.
The team secured $50,000 dollars of startup and costs $6.50 on the iPhone app store.
Download the Skin Scan app: http://itunes.apple.com/us/app/skin-scan/id434196122?mt=8&ls=1
Access the company's website: http://www.skinscanapp.com/index_3
[Both the utility of mobile devices and fractality of tissues (as well as fractality of the genome has been pioneered since 2002, see FractoGene and Barcode Shopping App YouTube). Fractals are eminently recursive algorithms, however, and thus FractoGene used to be a "lucid heresy" violating Crick's "Central Dogma" (while Crick was still alive, forbidding protein-to-DNA recursion) as well as Ohno's "Junk DNA" dogma (that Ohno actually meant seriously in 1972 such that any recursion to the "Junk" would be pointless - his 4.5 page meeting abstract deteriorated into a ludicrious misnomer now "seriously" upheld only by an occasional lonely moron, who is unable to produce a properly rounded percentage number, let alone understand advanced mathematics of postmodern genome informatics). Obsolete dogmas had to be demolished once Crick was gone, and the ENCODE results were published (2007), clearing the path towards The Principle of Recursive Genome Function (see peer-reviewed science paper and popularization by Google Tech Talk YouTube, both in 2008). The YouTube shows at min. 31 how aberrant methylation of perused auxiliary information (from the "Junk") results in uncontrolled fractal growth - the genome misregulation diseases a.k.a. cancer. Today, there is a veritable groundswell of observations, papers, and "the tip of the iceberg", an already deployed $6.50 tool as an app to help prevent cancer - based on the realization that the "double lucid heresy" was crazy, and actually was crazy enough to be true! (Paraphrasing Niels Bohr's theory, when the Copenhagen Group heard Bohr's thesis, and concluded "We all agree that your theory is crazy - the only question we have if it is crazy enough to be true"). HolGenTech, Inc. now focuses on cancer where the fractal genome, because of its "fractal defects" violates the genome's own mathematical rules, and thus genome misregulation results in clearly fractal, uncontrolled cancerous growth. In addition to several papers covered in this column, below is a list of recent observations and findings substantiating the case:
http://www.ncbi.nlm.nih.gov/pubmed/21319994
http://www.ncbi.nlm.nih.gov/pubmed/21514387
http://lambda.qsensei.com/content/1pmhrw
http://www.biomedcentral.com/1471-2407/10/260
http://www.cancertherapyblog.com/cancer-news/fractal-dimension-analysis-helps-breast-cancer-prognosis/
This entry can be discussed on the FaceBook page of Andras Pellionisz]
How accurate is the new Ion Torrent genome, really?
Genetic Future
By Daniel MacArthur July 21, 2011
New sequencing technology Ion Torrent has made a splash with a paper in today’s issue of Nature. There’s no question the high-impact publication is a massive boost for the young platform, now nestled within the embrace of the giant Life Technologies (who acquired the startup for a surprisingly large price last August) and bracing for the impending launch of its most serious competitor, Illumina’s MiSeq.
The paper jumps the new platform through the standard hoops: some basic kicking-the-wheels, a test run on three bacterial genomes (Vibrio fisheri, Escherichia coli, and Rhodopseudomanas palustris), and then the traditional main event: the sequencing of a complete human genome. The genome in question is that of Intel co-founder Gordon Moore, the eponymous originator of Moore’s Law. There’s some pleasing symmetry here: Moore’s Law is frequently cited in the context of the massive decline in the costs of DNA sequencing; in addition, the Ion Torrent technology is based on the same kind of semiconductor technology pioneered by Moore. Refreshingly, the paper refers to Moore by name, which is a pleasant change from the rather affected pseudo-anonymity of other published genomes (e.g. Patient Zero).
Anyway I’m not going to comment at all here on the technical and bacterial work, which I have no doubt will be covered in detail by my esteemed colleagues Keith Robison and Nick Loman. My main interest in this paper is what it tells us about the ability of Ion Torrent as a potential platform for large-scale sequencing of human genomes, and a rival to current sequencing market leader Illumina. I also want to spend some time berating the authors of the paper for a thoroughly misleading piece of statistical sleight-of-hand that makes their accuracy numbers sound far better than they actually are.
What did they do?
The company sequenced Moore’s genome using their technology to an average coverage of 10.6x. This just means that on average each base in the genome was covered by 10.6 separate Ion Torrent reads, albeit with substantial variation: some bases had lots more reads, and some had fewer. You can see the distribution of read counts per base (in red), compared with the ideal distribution (a Poisson distribution, in green) in Figure 4b of the paper – I’ve copied a thumbnail to the right. It’s clear that there are plenty of positions in the genome with substantially less than 10 reads.
Let’s be very clear about this up front: by modern standards, this is a poor-quality genome. An average coverage of 10x means that most positions in the genome will be covered by at least one read – 99.21%, in this case – but in many of those locations, the number of reads will be too low to have any chance of accurately calling a heterozygous SNP (a base change where both different versions are present, one on the maternal and one on the paternal chromosome). This isn’t a function of the raw data quality – it’s simply a statistical consequence of sampling error at small sample sizes, that can only be overcome by additional sequencing.
It’s also an extremely expensive genome: even at this low coverage the sequencing burned through around 1,000 Ion Torrent chips, and in an NY Times piece yesterday sequencing guru George Church estimated the total cost of this project at around $2 million. That would be substantially lower at today’s prices, but still north of $200,000 for a poor-quality genome compared to less than $5,000 for a high-quality sequence from Complete Genomics. The yield of the Ion platform (in terms of bases per dollar) is of course going up rapidly, but I think it’s important to emphasise that Ion Torrent is not yet a remotely competitive technology for affordable whole human genome sequencing.
So how accurate is the genome sequence, really?
The authors attempted to explicitly estimate their error rate by sequencing Moore’s genome a second time using an independent technology: in this case, Life Technologies’ SOLiD platform, to a total coverage of around 15x. (The higher depth of the SOLiD sequencing understates the far higher yield from that platform compared to Ion Torrent; for this paper the authors ran over 1,000 chips on the Ion Torrent, whereas the SOLiD coverage was presumably achieved in a single run.) 15x coverage isn’t much better than 10x, so the SOLiD sequence would be expected to be missing plenty of heterozygous sites as well.
So, the authors have two separate low-coverage genomes, both of which would be expected to be missing plenty of SNPs – that means we would expect to see plenty of sites that differ between the two sequences (reflecting changes that by chance were detected by one platform but missed by the other). Yet the paper appears to cite a “validation rate” for the SNPs called by the Ion Torrent that is implausibly high:
To confirm the accuracy of our analysis, we also sequenced the G. Moore genome using ABI SOLiD Sequencing43 to 15-fold coverage and validated 99.95% of the heterozygous and 99.97% of the homozygous genotypes (Supplementary Tables 1 and 2). [my emphasis]
There’s absolutely no conceivable way that a comparison between a 10x genome sequence and a 15x genome sequence could possibly result in a “validation rate” of 99.95% for heterozygous sites, at least not for any reasonable definition of the term “validation rate”. It takes some digging in the supplementary data to figure out what’s going on here. This is the definition of the term in the legend of Table S2, where the metric is referred to as the “percent same genotype”:
In cases where both datasets call the same type of SNP (heterozygote or homozygous variant) the proportion for which the genotype call is the same
The only way I can parse that sensibly is as follows: for sites that are called as heterozygous in both the Ion Torrent and SOLiD data, the “validation rate” is the proportion where the same two alleles are present. In other words, non-validated sites would only be sites where both platforms called a heterozyous SNP, but one platform said it was an A/G SNP while the other said it was an A/C SNP.
This is a near-useless metric, and does not correspond to any meaningful definition of the term “validation rate”. It gives us no information about what we actually want to know about, the proportion of sites where a SNP is called by one platform but not by the other – those are simply excluded from the comparison entirely. This is simply a measure of the platform’s ability to call the correct non-reference base at sites that are genuinely polymorphic, something that would be extremely high for virtually any half-decent sequencing technology. The only useful thing this metric does is provide a percentage with lots of convincing nines in it, which I’m sure the investors love, but I’m seriously perplexed that it managed to sneak past the manuscript reviewers.
Let’s take a more sensible definition of the term “validated”: for instance, let’s say it’s the proportion of sites called as heterozygous by Ion Torrent that also show some evidence of variation in SOLiD (we’ll generously say that the variant can be either homozygous or heterozygous in the SOLiD calls). Using this more plausible definition, the validation rate for Ion Torrent SNPs is just 88.0% at homozygous sites and 84.4% at heterozygous sites.
Ion Torrent could no doubt argue that this calculation is unfair to them: in many (probably most) cases, a discrepancy between Ion Torrent and SOLiD will be due to SNPs that were missed by the SOLiD technology, and thus aren’t really errors made by Ion Torrent. This is absolutely true, and in response I say: so do a proper job of validating your variants. Being a part of Life Technologies, one might imagine, should give the chaps at Ion Torrent a decent amount of access to SOLiD machines, and one more run of Moore’s genome on a SOLiD 4 would have given a far cleaner genome sequence for comparison. LIFE might even have one or two of those old capillary sequencing machines around that they used to sell: just 100-200 targeted capillary reactions around sites discrepant between the Ion Torrent sequence and a high-quality SOLiD sequence would have given plenty of data for an accurate estimation of the platforms real false positive and false negative rates.
Lack of proper validation is even more of an issue for larger structural variants. Here the authors steer clear of attempting to discover new variants, focusing instead on figuring out whether Moore carries any of the known structural variants called by the 1000 Genomes pilot project (PDF). Of 7,565 large deletions and inversions found by 1000 Genomes, the authors find evidence for 3,413 of them in Moore’s genome. That seems like a surprisingly large proportion to me, and it’s unclear how many of these calls are real: the authors report the results of a simulation using random genomic regions to estimate that 99.94% of their called events are real, but this number is not particularly meaningful as true deletion breakpoints are not well-represented by random chunks of the genome. And here there is absolutely no experimental evidence brought to bear – for instance, as far as I can tell no attempt was made to see how many of these apparent deletions also showed support in the SOLiD data, and certainly no attempt to independently validate the variants using a simple PCR assay.
All in all, a disappointing showing. This clearly isn’t a great genome sequence – it simply can’t be at 10x coverage, no matter how good the raw accuracy is – but the authors haven’t done enough experimental work to get a good sense of how accurate it really is. That means there’s very little we can say about the utility of Ion Torrent for whole human genome sequencing, apart from the fact that it’s currently too expensive to be practical.
What does Moore’s genome tell us about him?
Not much. The authors make a fairly cursory attempt at genome interpretation, pulling annotations from 23andMe’s database and OMIM, but their results aren’t particularly useful. That’s not a criticism, by the way: the point of this paper was demonstrating a sequencing technology, not a functional annotation pipeline. (Incidentally, 23andMe’s database was apparently used without any formal collaboration with the company, suggesting the researchers simply scraped the information from the company’s website: it’s intriguing to see one of the companies attacked by the FDA and Congress as “snake oil” being used as the go-to source for functional annotation.)
However, I note that the indefatigable Mike Cariaso has already run Moore’s genome through his interpretation pipeline Promethease – you can get the results here. It appears Moore has an increased risk of baldness (check), altered responses to various drugs, and a potentially highly elevated risk of age-related macular degeneration. However, nothing that he couldn’t have learnt from a 23andMe test, at less than 0.1% of the cost.
Where to next for Ion Torrent genomes?
This has been a pretty negative post, because I’ve focused solely on a section of the paper that – I’ll be frank – was done pretty badly. It’s not intended to be a critique of the Ion Torrent technology as a whole, and I’ll leave an evaluation of the technical merits of the platform to others who know it far better than I.
Still, I can’t help but wonder if Torrent made a mistake in including a human genome in this paper at all. I mean, I know it’s traditional, and sequencing Moore makes for some easy headlines, but the Torrent platform simply isn’t currently suited to whole-genome sequencing and won’t be until its yield improves substantially (there are clear signs in the paper that this is happening, albeit perhaps a little slower than we were promised). In sequencing a human genome with this early-stage, low-yield technology, Ion Torrent was forced into a dilemma of its own making: either spend an obscene amount of money to generate a high-quality sequence, or spend a simply lewd amount of cash to generate a crappy sequence. In the end they opted for the second approach, and I suspect they would have been better off simply leaving Moore’s genome out of the paper entirely.
In any case, I should emphasise that given the slow pace of publishing, this is a genome that was put together using the technology of maybe 12 months ago. There’s no question that Torrent technology has been improving over that time, and while it’s still not at the stage of competing with Illumina on cost right now, it’s certainly possible that this will be more viable in 12 months’ time. Hopefully the next genome sequence published using this technology comes complete with sufficient validation data to get a real impression of its quality.
[With TWO Former Intel Presidents (legendary Andy Grove and "Moore's Law" Gordon Moore) personally involved, with their own genomes, in "Genome Informatics" one may assume there is much talk at Intel about the future. As for the "present perfect", the Battelle Study (avilable on the web free full text) already assessed the economic impact of The Human Genome Project at $796 Bn in the USA alone - with Intel taking a vital part in the investments into quick and affordable full DNA sequencing by Pacific Biosciences since July 14, 2008 (first $100 M - a formative event in the history of "Genomics becoming Informatics"). It is unclear from the coverage from this article and the one below, why Gordon Moore got fully sequenced (once by Ion Torrents new platform, another time by the well-established SOLiD platform of the same company (Life Technologies) - and why is it that Andy Grove is not on public record of having been fully sequenced by any platform (thus missing from the approximately 2,700 individual humans whose DNA has been fully sequenced to date). From the viewpoint of Intel as a company and lead investor, it certainly makes a lot of sense to cross-compare the existing and emerging "full DNA sequencer technologies" for e.g. accuracy, costs, speed - and e.g. clinical applications (for instance with PacBio's capability of calling not only nucleotides, but also the methylation-status). It follows, that we might expect e.g. IT celebs with genomic conditions (cancer, Parkinsons', Alzheimers' - already a list of about 30 serious hereditary conditions that remained unpublished by Newsweek) - if I were Steve Jobs or Andy Grove could probably afford and be extremely keen on including a "Full DNA Sequencing" in my "Annual Physical" - but presently costing about $5k and needing only a blood sample, I would absolutely kindly but firmly demand a "before and after" full DNA sequencing for any therapy (say, chemo) with a propensity or requirement that it should do something about my diseased genome (at the very least monitoring its methylation-pattern, if full DNA sequencing would be deemed too costly, by the inexpensive Illumina methylation-interrogation by their microarrays). If I were a former leader of a major IT company with my opinion heavy as gold, I would probably not advise to have some other country to grab, beyond a point of no return, the software development of modern genome informatics (ask me why). This entry can be discussed in the FaceBook page of Andras Pellionisz]
[Former Intel President] Grove Backs an Engineer’s Approach to Medicine
(see also similar coverage by Kristen Bole)
May 17, 2010, 4:52 PM
New York Times
By ANDREW POLLACK
Andrew S. Grove, the former chief executive of Intel, is taking the next step in his quest to infuse the engineering discipline of Silicon Valley into the development of new medical treatments.
Mr. Grove has pledged $1.5 million so that the University of California campuses in San Francisco and Berkeley can start a joint master’s degree program aimed at so-called translational medicine — the process of turning biological discoveries into drugs and medical devices that can help patients.
The idea is to expose students to both the engineering prowess of Berkeley and the medical research of San Francisco to train a new breed of medical innovator.
“What we have learned from decades of rapid development of information technology is that the key is relentless focus on ‘better, faster, cheaper’ — in everything,’’ Mr. Grove said in a statement. “The best results are achieved through the cooperative efforts of different disciplines, all aimed at the same objective.”
Mr. Grove first broached the idea of the joint-campus program in November.
Mr. Grove’s views reflect in part his personal frustrations with waiting for better treatments for prostate cancer, which he had, and Parkinson’s disease, which he has now.
“I have my own decade-plus experience with a number of diseases that have dozens of ways of curing mice if mice have them and don’t progress toward clinical implementation,’’ Mr. Grove said in an interview.
Translational medicine is indeed a big buzzword these days. Everyone seems to recognize that there is a gap in getting from “bench to bedside.’’ Various programs are being set up to try to speed the process. Interdisciplinary work is another buzzword and trend among medical researchers.
Clearly, medical innovation can stand to be improved. Spending by big pharmaceutical companies on research and development has roughly doubled in the last decade, without any increase in the number of new drugs getting to market.
Yet whether Mr. Grove has the right prescription is open to debate. Some medical researchers have ridiculed his criticisms of their work, saying it is simply not possible to apply the techniques of the electronics business to the far greater complexity of human biology. ["Is Andy Grove a Kook?" - some old schooler biochemists who can't even produce properly rounded percentages, let alone come near to understanding a (now old) Itanium CPU, consisting of 2 Billion transistors, would probably put Andy Grove into the same category of ridicule as they did Barbara McClintock - to get her Nobel four decades delayed - AJP]
“Mr. Grove, you can print out the technical specs for your chips,’’ Derek Lowe, a pharmaceutical industry chemist, wrote in 2007. “We don’t have them for cells.’’
--
Comment (Pellionisz)
Harvard Medical School medicine was successfully united with MIT engineering to have created the Broad Institute. With $600 M charitable contribution from Eli and Edythe Broad – since a hereditary and “incurable” (!) syndrome, appeared in the family - a single frustrated venture philantrophist family provided the wherewithal to put Informatics and Genomics together. Broad is under directorship of Dr. Lander, with first degree in mathematics, now a Science Advisor to the President. Lander et al. 2009 Science cover article amounted to the outry “Mr. President, the Genome is Fractal!”. Andy Grove certainly is one the Worlds best experts how to wrestle the 500 pound gorilla of Informatics – but seems to be frustrated by old school medicine to handle his serious hereditary syndromes (prostate cancer and Parkinsons’). Mr. Grove is forcefully vocal both about his conditions and even more so about the need and extreme timeliness to seek entirely new avenues. Now the Battelle Study (assessing that the Human Genome Project had a $796 Bn impact on the US economy alone) rests on the pillar that “Genomics turned into Informatics”. It would take just minutes for Andy Grove to verify that the genome is a code of Informatics how to (mis)regulate genome function of a massively parallel 2-bit dataflow-“machine” – totally impossible without massive deployment of the best defense-computers. Assembling full human DNA has proven this thesis, BTW a trivial note for Silicon Valley movers and shakers, over a decade ago. More in my Google Tech Talk YouTube under “Pellionisz”.]
Loophole found in genetic traffic laws [Death Certificate of Crick Central Dogma - AJP]
Altered molecule causes protein-making machinery to run stop signs
By Tina Hesman Saey July 16th, 2011; Vol.180 #2 (p. 8)
Science News
Biology’s rules may be full of exceptions, but a new discovery has uncovered a violation in a rule so fundamental that geneticists call it the central dogma.
The molecular equivalent of writing one RNA letter in a different font can change the way a cell’s protein-building machinery interprets the genetic code, Yitao Yu and John Karijolich of the University of Rochester in New York report in the June 16 Nature. They found that occasional conversions of a genetic letter found in RNA into a slightly different form can cause a cell’s protein-building machinery to roll right through a stop sign.
That might seem like a run-of-the-mill molecular traffic violation, but it results in an entirely different protein than the one encoded by DNA — a clear violation of the central dogma.
The central dogma holds that DNA is the repository for all genetic instructions in a cell. The tenet declares that those instructions are carefully transcribed into multiple messenger RNA, or mRNA, copies, which are then read in three-letter chunks called codons by cellular machinery called ribosomes. Ribosomes then convert the mRNA instructions into proteins.
Yu and Karijolich studied pseudouridine, a slightly different version of the RNA component uridine. The enzymes that copy DNA to RNA and vice versa can’t tell the difference between the two components, but the subtle chemical tweak — akin to writing a letter in a hard-to-read, byzantine font — gives an entirely different meaning for the ribosome, the researchers suggest.
The result is “groundbreaking,” says Nina Papavasiliou, a molecular biologist at Rockefeller University in New York City. “It says that we don’t fully understand how ribosomes decode RNAs.”
That discovery could also mean that genes contain more information than scientists have realized, Papavasiliou says.
Pseudouridine is already known to be important for the function of many types of RNA in cells. Yu and Karijolich engineered a system to discover whether mRNAs containing the modified letter might also have a slightly different function than those with plain old uridine. The researchers created a flawed copper-detoxifying gene called CUP1 that contained an early signal to stop making protein. The team also created a system that would cause yeast cells to edit the mRNA, replacing the uridine in the stop codon with pseudouridine. If pseudouridine behaved just like uridine, then cells would prematurely halt production of the detoxifying protein and wouldn’t be able to grow in the presence of copper.
Yeast cells that replaced uridine in the stop sign with pseudouridine could grow on copper, the researchers found. Looking more closely, the team found that instead of reading the stop sign as stop, ribosomes interpreted the pseudouridine-containing codon as an instruction to insert the amino acids serine, threonine, phenylalanine or tyrosine into the protein.
That choice of amino acids by the ribosome has biologists reeling, because those aren’t even the amino acids usually chosen when the protein factories do occasionally run stop signs.
“When you know the literature, you would expect other [amino acids],” says Henri Grosjean, a biochemist and geneticist at the University of Paris-South.
Apparently ribosomes haven’t read those papers.
Whether pseudouridine plays a part in changing the genetic code in nature remains to be seen, but researchers are betting that it does. The implications for health and disease could be great, says Juan Alfonzo, a molecular biologist at the Ohio State University. Pseudouridines may be required to make some proteins correctly, but “misplacing a pseudouridine could make things a physiological mess,” he says, causing some proteins to have flaws, even fatal ones.
And Yu and Karijolich’s technique might be used to fix genetic errors, too. Introducing stop sign–busting pseudouridine into an RNA may one day help people with rare genetic diseases in which one of their genes contains an early stop codon, Alfonzo says.
[Here you go, again. Crick' infamous "Central Dogma of Molecular Biology", totally falsely pontificating that sequence information NEVER recurses from proteins and RNA to DNA, was immediately laughed about by Nobelists Jacobs and Monod as far back as half a Century ago (1961). "Facts don't kill theories", however - some lonely morons (who can not produce properly rounded numbers!) could still dismiss this experimental discovery as "not fitting into their ideology"). Obsolete theories are killed by superior theories - in this case The Principle of Recursive Genome Function peer reviewed paper and its popularization in Google Tech Talk YouTube. - This entry can be discussed in the FaceBook page of Andras Pellionisz]
Editing the genome - Scientists unveil new tools for rewriting the code of life
BOSTON, MA (July 14, 2011) — The power to edit genes is as revolutionary, immediately useful and unlimited in its potential as was Johannes Gutenberg's printing press. And like Gutenberg's invention, most DNA editing tools are slow, expensive, and hard to use—a brilliant technology in its infancy. Now, Harvard researchers developing genome-scale editing tools as fast and easy as word processing have rewritten the genome of living cells using the genetic equivalent of search and replace—and combined those rewrites in novel cell strains, strikingly different from their forebears.
"The payoff doesn't really come from making a copy of something that already exists," said George Church, a professor of genetics at Harvard Medical School who led the research effort in collaboration with Joe Jacobson, an associate professor at the Media Lab at the Massachusetts Institute of Technology. "You have to change it—functionally and radically."
Such change, Church said, serves three goals. The first is to add functionality to a cell by encoding for useful new amino acids. The second is to introduce safeguards that prevent cross-contamination between modified organisms and the wild. A third, related aim, is to establish multi-viral resistance by rewriting code hijacked by viruses. In industries that cultivate bacteria, including pharmaceuticals and energy, such viruses affect up to 20 percent of cultures. A notable example afflicted the biotech company Genzyme, where estimates of losses due to viral contamination range from a few hundred million dollars to more than $1 billion.
In a paper scheduled for publication July 15 in Science, the researchers describe how they replaced instances of a codon — a DNA "word" of three nucleotide letters — in 32 strains of E. coli, and then coaxed those partially-edited strains along an evolutionary path toward a single cell line in which all 314 instances of the codon had been replaced. That many edits surpasses current methods by two orders of magnitude, said Harris Wang, a research fellow in Church's lab at the Wyss Institute for Biologically Inspired Engineering who shares lead-author credit on the paper with Farren Isaacs, an assistant professor of molecular, cellular and developmental biology at Yale University and former Harvard research fellow, and Peter Carr, a research scientist at the MIT Media Lab.
In the genetic code, most codons specify an amino acid, a protein building block. But a few codons tell the cell when to stop adding amino acids to a protein chain, and it was one of these "stop" codons that the Harvard researchers targeted. With just 314 occurrences, the TAG stop codon is the rarest word in the E. coli genome, making it a prime target for replacement. Using a platform called multiplex automated genome engineering, or MAGE, the team replaced instances of the TAG codon with another stop codon, TAA, in living E. coli cells. (Unveiled by the team in 2009, the MAGE process has been called an evolution machine for its ability to accelerate targeted genetic change in living cells.)
While MAGE, a small-scale engineering process, yielded cells in which TAA codons replaced some but not all TAG codons, the team constructed 32 strains that, taken together, included every possible TAA replacement. Then, using bacteria's innate ability to trade genes through a process called conjugation, the researchers induced the cells to transfer genes containing TAA codons at increasingly larger scales. The new method, called conjugative assembly genome engineering, or CAGE, resembles a playoff bracket—a hierarchy that winnows 16 pairs to eight to four to two to one—with each round's winner possessing more TAA codons and fewer TAG, explains Isaacs, who invokes "March Madness."
"We're testing decades-old theories on the conservation of the genetic code," Isaacs said. "And we're showing on a genome-wide scale that we're able to make these changes."
Eager to share their enabling technology, the team published their results as CAGE reached the semifinal round. Results suggested that the final four strains were healthy, even as the team assembled four groups of 80 engineered alterations into stretches of the chromosome surpassing 1 million DNA base pairs. "We encountered a great deal of skepticism early on that we could make so many changes and preserve the health of these cells," Carr said. "But that's what we've seen."
The researchers are confident that they will create a single strain in which TAG codons are completely eliminated. The next step, they say, is to delete the cell's machinery that reads the TAG gene — freeing up the codon for a completely new purpose, such as encoding a novel amino acid.
"We're trying to challenge people," Wang said, "to think about the genome as something that's highly malleable, highly editable."
[Starting from the conclusion of the authors' Press Release, the philosophical message is: "The Genome is NOT your Destiny". This drastically altered world-view, introduced by Genome Informatics, is similar in scope to the Heisenberg "Principle of Uncertainty" - that forever changed the former deterministic physics to probabilistic physics. As emphasized in the 2088 Google Tech Talk YouTube, the radically different new philosophy instills scientific reason for hope ("The Principle of Recursive Genome Function" presented as "The Circle of Hope"), replacing the gloomy former attitude that "Your Genome was Your Destiny" - both a reason for gloom and doom, as well as avoiding any genome testing, in the (mistaken) belief that "there is nothing one can do about it". Beyond philosophical world-view and attitude of the masses, the paradigm-shift practical application is also evaluated (by some interesting metaphors) in various leading Journals (New York Times, Los Angeles Times, Forbes, etc, etc.). Let's just start with the metaphors used in the authors' Press Release. Is the new breakthrough like "Gutenberg' Press", or "The Word Processor (software)"? In terms of "Synthetic Biology", entirely new "texts" can be composed of the A,C,T,G letters. Most exciting! In terms of "The Principle of Recursive Genome Function", however, (see one follower below), an even more immediate - and patently useful - "word processing" could e.g. be made in time in vivo for humans - by the "replace" function of e.g. the "fractal defects" of the genome with snippets that do obey the genome's own fractal mathematics - thus fractal iterative recursion function of genome regulation no longer "hicks up" on the glitches! Those familiar with (man-made) software know, that the instructions are first run through a "Syntax Checker"; to see if all instructions fully conform with the formal requirements. Suppose an instruction is found to have a "structral variant" (gibberish), the coder uses "global replace" throughout the code to straighten out all such glitches. (Those familiar with code also know, that impeccable syntax is a necessary but not sufficient condition for any software to run - but actual compilation could never take place before all instructions obey the rules). The articles below, to "replace" codons (or even just a single nucleotide in case of Progeria...) show the enormous potential power of the breakthroughs for IT-led "New Pharma". The issue can be debated in Andras Pellionisz' FaceBook page. - AJP]
An Explanation of Molecular Polymorphisms and Why Many Molecular Structures Can Be Preserved Although They Are Not Predominant
DNA AND CELL BIOLOGY
Volume 29, Number 10, 2010
Mary Ann Liebert, Inc.
Pp. 571-576
DOI: 10.1089/dna.2009.094
Borros M. Arneth
Institute of Clinical Chemistry and Laboratory Medicine, Johannes Gutenberg University, Mainz, Germany
The existence of many processes that regulate RNA expression poses a challenge to the idea that the cell is the culmination of a highly efficient interplay of individual proteins, each with specific, highly specialized functions.
It will be demonstrated here the extent to which the cell may undergo evolutionary processes that also occur in the macrocosmos, specifically with reference to the rules of mutation and preservation. These molecular evolutionary processes could facilitate a better understanding of the development of molecular structures and the functioning of the cell and could give an explanation of the molecular polymorphisms and also explain why many molecular structures can be preserved although they are not predominant...
Pellionisz (2008) describes the principle of recursive genome function and how DNA is affected by this recursion through proteins.
[See the 2008 paper in full here - AJP]
Clue to kids' early aging disease found [The Colossal Paradigm-Shift - AJP]
By Madison Park, CNN
July 1, 2011 12:08 p.m. EDT
[Dr. Francis Collins wrote the book on the colossal paradigm shift; Personalized (Genomic) Medicine - AJP]
(CNN) -- Her name was Meg, 23, featherweight and feisty.
Standing 3 feet tall, Meg didn't look like her peers. Bald and skinny, her body was aging rapidly because she had a rare genetic disease called Hutchinson-Gilford progeria syndrome.
People with progeria wrinkle and develop the same circulation and joint ailments as the elderly -- except most of them die by age 13.
Progeria affects 200-250 children worldwide, but research into the disease could offer clues on cellular function and how it affects human aging and other age-related diseases.
This week, a study about a possible treatment was published in Science Translational Medicine. Dr. Francis Collins, director of the National Institutes of Health, is one of the authors.
About 30 years ago, Collins, then a young Yale University doctor, met Meg. He realized there was little he could do for his patient, but he couldn't look away.
"It was compelling to try to understand why someone's body is melting away in the ravages of age," he said. "You couldn't be involved without marveling at it and wanting to do something to understand the situation."
Collins offered his concern and compassion, but there was no treatment for her disease.
Despite her grave prospects and appearance, Meg did not shy away from the public eye. Instead, she became an outspoken advocate for disabled people in Milford, Connecticut.
Long before it became customary to do so, "She got that town to become friendly to the disabled," Collins said. "She made it happen."
Just because she was diminutive, it didn't mean people could step all over her. Meg could also "curse like a sailor" in her birdlike voice, he said.
Meg Casey died in 1985, but she never faded from the doctor's memory.
Collins' role as a geneticist is to decode the most complex puzzles of human life. He is best known as a leader of the Human Genome Project that mapped and sequenced the human DNA.
The mystery of progeria remained one of his interests. Collins and seven others are authors of a study that found an immune suppressing drug, called rapamycin, could possibly treat progeria.
There have been no approved drugs or treatment to slow the course of the disease.
Children with this rare genetic condition lose their hair as infants, while they're learning to talk. Their minds develop normally, but their bodies age rapidly.
As toddlers, their skin begins to wrinkle and sag. Most of them die of age-related causes, like heart disease, heart attack or stroke, before they start high school.
Clues found in mysterious childhood aging disease
The cause: A single letter in a progeria patient's genome is out of place. This genetic defect causes the child to accumulate too much of a toxic protein called progerin and the cells can't get rid of it. [The single letter clue was actually found in 2003 by Vastag B 2003 Cause of progeria's premature aging found: expected to provide insight into normal aging process. JAMA 289:2481-2482 - AJP]
"Cells have a normal way of removing byproducts," said Dr. Dimitri Krainc, an author in the study. "You accumulate trash and you take it out. That's what happens in cells. As they work, they start accumulating byproducts. There has to be a system to remove those byproducts."
Progerin is seen in small amounts in healthy people's cells as they begin to age. The difference is that healthy cells can get rid of the damaged molecules and unneeded proteins.
The researchers chose to test rapamycin on cells from progeria patients because research suggested its effectiveness in extending the lives of mice. Rapamycin is an immune-suppressing drug given to transplant recipients to prevent organ rejection.
Krainc, an associate professor of medicine at Harvard University, said cells from progeria patients look "very sick."
"When you treat them with rapamycin, it looks normal," he said. The drug appeared to activate a cellular system that removes the waste.
"Rapamycin or similar drugs of that same class are capable of revving up that cleanup system," Collins said.
But the drug comes with major risks because it raises cholesterol levels and suppresses the immune system, making patients more vulnerable to infections. Rapamycin was derived from bacteria found in the soil of Easter Island in the 1960s.
The results of the progeria study triggered discussions about a potential human clinical trial.
"I can't say what the drug will do before clinical trial," Krainc said. "We're very hopeful, because of the dramatic effect (in cells) was replicated."
The protein buildup in cells is seen in other diseases, such as Alzheimer's and Parkinson's disease. Alzheimer's patients have tau protein tangles and another protein called the beta amyloid plaques in their brains. Parkinson's patients have a buildup of a protein called alpha-synuclein.
Some scientists hypothesize that the cell's inability to dispose of unnecessary protein as humans age is what could lead to severe illnesses.
"This is a fundamentally important pathway by which cells maintain their own health," Collins said. "Yet as we age, we don't do it quite as well and the buildup starts to happen."
The Progeria Research Foundation, a nonprofit that supports affected families and promotes scientific research on the disease, supplied tissue and cell samples for the study.
Dr. Leslie Gordon, the foundation's medical director and a mother of a boy with progeria, said scientists are considering the use of RAD001, a modified version of rapamycin that has fewer side effects in a potential human trial.
"Nothing is in place," she said. "These things take instructional and federal scrutiny. We're considering this based on this very study."
For years, progeria research languished as another orphan disease. Rare diseases struggle to attract attention and research dollars because they affect very few people.
Drug development favors common diseases that could lead to blockbuster medications. This leaves patients and families of orphan diseases with little support or medical options.
"The first thing that we discovered after my son was diagnosed was there was nothing out there to help researchers to do research -- no cells or tissue, no clinical information bank, no outreach for families," said Gordon. "There was nothing to work with."
The foundation established a cell and tissue bank and started efforts to identify more progeria patients. It is involved in a different clinical trial involving a three-drug cocktail to treat progeria.
It hasn't been easy trying to bring attention and resources to a rare disease, Gordon said.
"For all the times people could not help, there are people like Francis (Collins) who say yes," Gordon said. "When we approached him, it was the fact that he cared and the fact that it bothered him that we didn't have the answer."
"He's not only interested in science, he's interested in people."
Collins has met her young son, Sam.
Patients with progeria are enthusiastic, precocious and embrace life, Collins said.
"They're taking what most of us look at as a really discouraging situation and saying, 'No, darn it. I'm going to make the most of it. If I have a shortened time being here, I'm not going to waste it feeling sorry for myself.
"I'm going to make the most of it.'"
[Given a single-letter glitch in the DNA (that, in the wrong place, could make the codon produce inappropriate and/or toxic protein), as elaborated in e.g. Dr. Collins' book can be theoretically dealt with in two entirely different manner. One is to CURE the DNA by patching the erroneous code (see early animal research results of e.g. Dr. George Church' lab in the news below). The traditional ways and means of Big Pharma aim at THERAPY by means of compounds (that, as Dr. Collins elaborates in his book) may or may not work in individual cases - plus could have serious side-effects in SOME, causing FDA to withhold or pull a compound such that it might never become an approved drug (as FDA is mandated by a generation-old legislation to apply a "one drug fits all" - scientifically clearly obsolete - criteria. The paradigm-shift towards "New Pharma" (led by genome informatics, to understand how the genome malfunctions and/or misregulated e.g. in the case of cancer, and how to measure the efficacy in genomic (not often too late protein) results, as well as how to modify the genome such that "The Genome is NOT your Destiny") is, indeed, colossal. The issue can be debated in Andras Pellionisz' FaceBook page. - AJP]
Researchers Use Genome Editing Methods to Swap Stop Codons in Living Bacteria
July 14, 2011
Genomeweb
By Andrea Anderson
NEW YORK (GenomeWeb News) – In Science today, an international research group led by investigators at Harvard University and the Massachusetts Institute of Technology reported that they have advanced their genome editing technology, using these tools to develop Escherichia coli strains in which one stop codon has been replaced by another.
"We're able to, at a genome-wide scale, make codon replacements for an entire codon across the whole genome," co-first author Farren Isaacs, who performed the research as a post-doctoral researcher at Harvard University and is currently a researcher at Yale University, told GenomeWeb Daily News. "Basically we use living cells as a template and we make changes within the living cells."
To do this, the team split the E. coli genome into dozens of pieces and then used a method called multiplex automated genome engineering, or MAGE, to introduce codon changes to each region in differents E. coli cultures, trading the guanine nucleotide in the TAG stop codon for an adenine to make the synonymous stop codon TAA. From there, they came up with a hierarchical "conjugative assembly genome engineering" (CAGE) strategy to amalgamate these changes so that increasingly large stretches of the genome were recoded in each intermediate strain.
At the moment, the team has four E. coli strains that they plan to use to generate a single strain in which every TAG has been converted to TAA.
"These four strains, which contain up to 80 modifications per genome, can be combined to complete the assembly of a fully recoded strain containing all 314 TAG-to-TAA codon conversions," the study authors wrote.
The long-term objectives of such experiments are to develop the technology to make large-scale changes to genomes and introduce new functions into organisms, Isaacs explained, and, eventually, to create organisms with new genetic codes, including those capable of producing proteins from amino acids not currently found in nature.
"That could lead to entirely new classes of drugs, industrial enzymes, biopolymers that could be used to make new types of materials, and so on," he said, noting that similar strategies could also be used to genetically isolate organisms, thwarting potential viral pathogens, and to contain genetically engineered organisms within restricted environments.
Members of the team previously used MAGE to reprogram a biosynthesis pathway in E. coli cells leading to enhanced production of the compound lycopene — work that they reported in Nature in 2009.
Now, researchers have shown that they can build on this method, putting together pieces of the genome containing MAGE-induced changes to produce bacterial strains with specific codon changes across larger and larger swaths of the genome.
The 20 amino acids and "stop" signal are encoded by 64 triplet nucleotide sequences, meaning there are more than three times as many codons as there are functions for which they code.
The researchers were able to exploit this redundancy in the genetic code, Isaacs explained, trading the stop codon TAG, which usually appears 314 times in the E. coli genome, for another stop codon, TAA, that's recognized by a different release factor during translation.
The team first introduced targeted alterations into 32 E. coli cultures by MAGE using oligonucleotides containing the desired changes, Isaacs said, gauging the functional consequences, if any, along the way.
"We decided to pursue a strategy whereby we would divide up the strains and quickly introduce all of these changes to small pools to, one, verify that they're viable and, two, be able to detect and quantify phenotypes," he explained. "It was important to be able to obtain enough resolution on the changes that we're making to see if any of them led to any sort of strange phenotype."
They then merged the MAGE-produced alterations into their final four intermediate strains using CAGE. Coupled with selection, this hierarchical genome engineering method let the researchers transplant well-defined stretches of DNA from one genome to another without introducing unintended changes to the recipient genome.
The researchers are now continuing to use CAGE to take the E. coli strains with the most extensive recoding to the next stage — assembling a strain in which every TAG in the genome has been converted to TAA.
In the future, they also plan to try trading out other codons, including those coding for amino acids. The team will likely attempt to use their codon replacement strategy in other bacterial species, Isaacs noted, and, perhaps, in eukaryotic cells as well.
"Our methods treat the chromosome as both an editable and an evolvable template," the researchers wrote, "permitting the exploration of vast genetic landscapes."
[Look for a piece of news that appeared a few minutes after this one. (Should be shown here ASAP). Putting 1+1 together, you'll see crystal clear why and how we are facing the biggest paradigm-shift of science & technology of all times. The issue will be up for debate in Andras Pellionisz' FaceBook page. - AJP]
The Mathematics of DNA [is Fractal - says Dr. Perez]
The number of triplets that begin with a T is precisely the same as the number of triplets that begin with A (to within 0.1%).
The number of triplets that begin with a C is precisely the same as the number of triplets that begin with G.
The genetic code table is fractal - the same pattern repeats itself at every level. The micro scale controls conversion of triplets to amino acids, and it’s in every biology book. The macro scale, newly discovered by Dr. Perez, checks the integrity of the entire organism.
Perez is also discovering additional patterns within the pattern.
I am only giving you the tip of the iceberg. There are other rules and layers of detail that I’m omitting for simplicity. Perez presses forward with his research; more papers are in the works, and if you’re able to read French, I recommend his book “Codex Biogenesis” and his French website. Here is his English paper.
(By the way, he found some of his most interesting data in what used to be called “Junk DNA.” It turns out to not be junk at all.)
OK, so what does all this mean?
Copying errors cannot be the source of evolutionary progress, because if that were true, eventually all the letters would be equally probable.
This proves that useful evolutionary mutations are not random. Instead, they are controlled by a precise Evolutionary Matrix to within 0.1%
When organisms exchange DNA with each other through Horizontal Gene Transfer, the end result still obeys specific mathematical patterns
DNA is able to re-create destroyed data by computing checksums in reverse - like calculating the missing contents of a page ripped out of a novel.
No man-made language has this kind of precise mathematical structure. DNA is a tightly woven, highly efficient language that follows extremely specific rules. Its alphabet, grammar and overall structure are ordered by a beautiful set of mathematical functions.
More interesting factoids:
The most common pair of letters (TTT and AAA) appears exactly 1/13X as often as all the letters combined – consistently, the genomes of humans and chimpanzees.
If you put the 32 most common triplets in Group 1 and the 32 least common triplets in Group 2, the ratio of letters in Group1:Group2 is exactly 2:1. And since triplet counts occur in symmetrical pairs (TTT-AAA, TAT-ATA, etc), you can group them into four groups of 16.
When you put those four triplet populations on a graph, you get the peace symbol:
Does this precise set of rules and symmetries appear random or accidental to you?
My friend, this is how it is possible for DNA to be a code that is self-repairing, self-correcting, self-re-writing and self-evolving. It reveals a level of engineering and sophistication that human engineers could only dream of. Most of all, it’s elegant.
Cancer has sometimes been described as “evolution run amok.” Dr. Perez has noted interesting distortions of this matrix in cancer cells. I strongly suspect that new breakthroughs in cancer research are hidden in this matrix.
I submit to you that the most productive research that can possibly be conducted in medicine and computer science is intensive study of the DNA Evolution Matrix. Like I said, this is just the tip of the iceberg.
There is so much more here to discover!
When we develop computer languages based on DNA language, they will be capable of extreme data compression, error correction, and yes, self-evolution. Imagine: Computer programs that add features and improve with time. All by themselves.
What would that be like?
Perry Marshall
P.S.: Dr. Perez and I are friends. Perez worked on HIV research with the man who originally discovered HIV, Luc Montagnier. Perez also worked in biomathematics and Artificial Intelligence at IBM. I’m familiar with this work because last spring I had the privilege of helping him translate his groundbreaking research paper about this into English. [See link above - AJP]
In the 1940′s, the eminent scientist Barbara McClintock damaged parts of the DNA in corn maize. To her amazement, the plants could reconstruct the damaged section. They did so by copying other parts of the DNA strand, then pasting them into the damaged area.
This is a lot like ripping an entire page out of a mystery novel and somehow being able to re-construct the missing text, even though the page is destroyed.
This discovery was so radical at the time, hardly anyone believed McClintock’s reports. [To the contrary, her pioneering was opposed at every step of the way, ignorant detractors called Barbara McClintock a "Kook" - she got her Nobel several decades after her "lucid heresy"]
And we still wonder: How does a tiny cell possibly know how to do…. that???
A French HIV researcher and computer scientist has now found part of the answer. Hint: The instructions in DNA are not only linguistic, they’re beautifully mathematical.
Imagine that someone gives you a mystery novel with an entire page ripped out.
And let’s suppose someone else comes up with a computer program that reconstructs the missing page, by assembling sentences and paragraphs lifted from other places in the book.
Imagine that this computer program does such a beautiful job that most people can’t tell the page was ever missing.
DNA does that.
In the 1940′s, the eminent scientist Barbara McClintock damaged parts of the DNA in corn maize. To her amazement, the plants could reconstruct the damaged section. They did so by copying other parts of the DNA strand, then pasting them into the damaged area.
This discovery was so radical at the time, hardly anyone believed her reports. (40 years later she won the Nobel Prize for this work.)
A French HIV researcher and computer scientist has now found part of the answer. Hint: The instructions in DNA are not only linguistic, they’re beautifully mathematical. There is an Evolutionary Matrix that governs the structure of DNA.
Computers use something called a “checksum” to detect data errors. It turns out DNA uses checksums too. But DNA’s checksum is not only able to detect missing data; sometimes it can even calculate what’s missing. Here’s how it works.
In English, the letter E appears 12.7% of the time. The letter Z appears 0.7% of the time. The other letters fall somewhere in between. So it’s possible to detect data errors in English just by counting letters.
In DNA, some letters also appear a lot more often (like E in English) and some much less often. But… unlike English, how often each letters appears in DNA is controlled by an exact mathematical formula that is hidden within the genetic code table.
When cells replicate, they count the total number of letters in the DNA strand of the daughter cell. If the letter counts don’t match certain exact ratios, the cell knows that an error has been made. So it abandons the operation and kills the new cell.
Failure of this checksum mechanism causes birth defects and cancer.
Dr. Jean-Claude Perez started counting letters in DNA. He discovered that these ratios are highly mathematical and based on “Phi”, the Golden Ratio 1.618. This is a very special number, sort of like Pi. Perez’ discovery was published in the scientific journal Interdisciplinary Sciences / Computational Life Sciences in September 2010.
Before I tell you about it, allow me to explain just a little bit about the genetic code.
DNA has four symbols, T, C, A and G. These symbols are grouped into letters made from combinations of 3 symbols, called triplets. There are 4x4x4=64 possible combinations.
So the genetic alphabet has 64 letters. The 64 letters are used to write the instructions that make amino acids and proteins.
Perez somehow figured out that if he arranged the letters in DNA according to a T-C-A-G table, an interesting pattern appeared when he counted the letters.
He divided the table in half as you see below. He took single stranded DNA of the human genome, which has 1 billion triplets. He counted the population of each triplet in the DNA and put the total in each slot:
When he added up the letters, the ratio of total white letters to black letters was 1:1. And this turned out to not just be roughly true. It was exactly true, to better than one part in one thousand, i.e. 1.000:1.000.
Then Perez divided the table this way:
Perez discovered that the ratio of white letters to black letters is exactly 0.690983, which is (3-Phi)/2. Phi is the number 1.618, the “Golden Ratio.”
He also discovered the exact same ratio, 0.690983, when he divided the table the following two alternative ways:
Again, the total number of white letters divided by the total number of black letters is 0.6909, to a precision of better than one part in 1,000.
[We will never know fractal computer languages of DNA without appropriate (and potentially eminently lucrative) funding. Dr. Perez is an independent scientist in France, who cited his motivated to write his papers by publications of Pellionisz (2008) The Principle of Recursive Genome Function, Pellionisz, A. (2009) From the Principle of Recursive Genome Function to Interpretation of HoloGenome Regulation by Personal Genome Computers. Cold Spring Harbor Laboratory; Personal Genomes, Sept. 14-17, 2009 and Lander et al. (2009 October 9th Science cover article). While Dr. Lander is Science Advisor to the US President and thus could help ensure that the USA emerges in her race with China, Japan, Korea, India - and even Russia, the US government is out of funds - fractal clues to e.g. cancer (as voiced in the Google Tech Talk YouTube by Dr. Pellionisz, 2008), may come from "Venture philantrophists" like Dr. Lander's own Broad Institute (Eli and Edythe Broad) - AJP].
Cell Surface as a Fractal: Normal and Cancerous Cervical Cells Demonstrate: Different Fractal Behavior of Surface Adhesion Maps at the Nanoscale
M. E. Dokukin,1 N.V. Guz,1 R. M. Gaikwad,1 C. D. Woodworth,2 and I. Sokolov1,3,* 1Department of Physics, Clarkson University, Potsdam, New York 13699-5820, USA 2Department of Biology, Clarkson University, Potsdam, New York 13699-5820, USA 3Nanoengineering and Biotechnology Laboratories Center (NABLAB), Clarkson University, Potsdam, New York 13699-5820, USA
(published 8 July 2011)
Here we show that the surface of human cervical epithelial cells demonstrates substantially different fractal behavior when the cell becomes cancerous. Analyzing the adhesion maps of individual cervical cells, which were obtained using the atomic force microscopy operating in the HarmoniX mode, we found that cancerous cells demonstrate simple fractal behavior, whereas normal cells can only be approximated at best as multifractal. Tested on 300 cells collected from 12 humans, the fractal dimensionality of cancerous cells is found to be unambiguously higher than that for normal cells.
DOI: 10.1103/PhysRevLett.107.028101
China genomics institute outpaces the world
(Xinhua)
Updated: 2011-06-14 17:19
SHENZHEN - Many people were surprised when BGI (formerly Beijing Genomics Institute), a Chinese genomics institute, sequenced a strain of E. coli bacterium responsible for the outbreak in Germany that killed at least 18 people earlier this month.
But it was no surprise for Qin Junjie, deputy head of BGI's microorganism genomics researcher center, whose team sequenced the bacterium in three days. "We have the greatest output of genomics data and the best team to analyze it," Qin said.
BGI is more like a factory than a lab, according to Qin. The BGI facility, a converted shoe factory in Shenzhen city, now houses 137 top-of-the-line genome-sequencing machines and high-speed computers.
BGI pumped out 500 Tb of genomics data in 2010 - ten times the amount of data the US National Center for Biology Information (NCBI) produced in the past twenty years. BGI expects to produce 100 Pb of data in 2011, Qin said [That will be two hundred times, in a single year, of NCBI output in the past twenty years - meanwhile, NCBI closes some of its data-services, due to lack of continued government support - AJP] .
In addition, BGI used Ion Torrent, a newly-developed sequencing machine that is much quicker. "Even half an hour counts in the fight against epidemics," said Yang Bicheng, spokeswoman for BGI.
To cope with the vast amount of data, BGI needs a robust, young staff. The institute has 3,000 scientists who are younger than 25 on average. At 29, Qin is one of the oldest.
Li Yingrui was just a college student and an intern of BGI when he published his first paper in Nature Journal in 2007. Now, Li, 24, directs the bioinformatics department and its 1,500 computer scientists. He has become one of BGI's leading scientists with five papers published in Science Magazine and Nature Journal.
In BGI, college, or even high school students, lead cutting-edge projects and publish papers in top science journals. Yet despite the impressive work of these young scientists, their pay isn't so world-class. A recent college graduate gets about 3,000 yuan ($462) per month. The average monthly salary in Shenzhen is more than 4,000 yuan.
Having an army of scientists at a comparatively low cost contributes to BGI's competitiveness, Yang said.
At BGI, young people can work with world's leading scientists and participate in international projects," Yang said. "They also have the opportunity to lead research in new areas, and such motivation is more powerful than anything else."
The growing fame of BGI in the world shows China's efforts in promoting scientific advancement is starting to pay off, said Wang Jian, BGI's director.
"The scientific outlook on development is a key policy of China, and it requires the government to focus on supporting research facilities like BGI," Wang said.
In addition, China has been striving for progress in medical reform, agriculture and environmental protection, which in turn boosts bioscience research, he added.
In a visit to BGI on June 4, two days after it completed the sequencing of the bacterium, Xu Qin, mayor of Shenzhen, said the city will give all-out support to boost the leap-frog development of BGI.
Shenzhen, a boomtown near Hong Kong, is the base of some of China's most innovative companies such as ZTE and Huawei.
[It is not that in the USA there is nothing done. There is a lot of competition, for instance. The E. coli German strain has also been sequenced by Pacific Biosciences SMRT molecular sequencer - while China favored Life Technologies' Ion Torrents sequencer (that is way over ten times cheaper as a machine). Illumina is also in the race - and of course for full human DNA sequencing there is Complete Genomics. All US companies develop their separate (and largely incompatible) software for the "sequencing" part (assembly), as well as for the crucial "analytics" part (interpretation). This is exactly where China differs; and appears to develop a 200x lead over US government (in a single year, beating the two decades worth of US government support). In "assembly", China (BGI) already announced a GPU-assisted software cloud tool kit. Unless the US entrepreneurship wakes up (it will take either a miracle, or some movers & shakers getting sick with cancer, or just getting sick of the feeling of a mortal dependence...) the US will find Genome Informatics going the same way as the entire consumer electronics did ("Invented and designed in the USA - made in China" - with the "tiny" difference that consumer electronics is mostly for fun, but Genome Informatics is a life or death issue). - This entry can be discussed on the FaceBook of Andras Pellionisz]
Searching For Fractals May Help Cancer Cell Testing
Researchers use a new tool to determine that cancerous cells have different geometries than healthy cells.
Jul 5, 2011
By Phillip F. Schewe
Inside Science News Service
[The above figure shows a cell imaged by SEM (scanning electron microscope) and AFM (atomic force microscope).- excerpt from the Sokolov paper - AJP]
(ISNS) -- Scientists have long known that healthy cells looked and behaved differently from cancer cells. For instance, the nuclei of healthy cells -- the inner part of the cells where the chromosomes are stored -- tend to have a rounder surface than the nuclei in cancerous cells.
A new experiment looks at the shapes of healthy and cancerous cells taken from the human cervix and has attempted to quantify the geometrical differences between them. The research, carried out at Clarkson University in Potsdam, N.Y. finds that the cancerous cells show more fractal behavior than healthy cells.
Fractal is the name used for heavily indented curves or shapes that look very similar over a variety of size scales. For example, the edge of a snowflake, when observed with a microscope, has a lacelike structure that looks the same whether at the level of a millimeter, or a tenth of a millimeter, or even a thousandth of a millimeter. The position of galaxy clusters in the sky seems to be fractal. So does the snaking geometry of streams in a river valley, or the foliage of leaves on a tree. The shape of coastlines and clouds reveals a fractal, "self-similar" geometry. Even the "drip" paintings of Jackson Pollack are fractal.
Fractal geometry apparently also appears in the human body. The pattern of heartbeats over long intervals looks fractal. How about the geometry of cells? And could the observation of fractal geometry be used to identify cancer cells?
Igor Sokolov and his Clarkson colleagues used an atomic force microscope to view cells down to the level of one nanometer, or a billionth of a meter (one-millionth of a millimeter). Just as the needle on a record player rides over the groove of a rotating vinyl record to read out the music stored on the record's surface, so the sharp needle forming the heart of an atomic force microscope rides above a sample reading out the contours of matter just below at nearly atomic resolution.
Previous studies of cells at the microscopic level produced two-dimensional maps of the cells' surface. The new study produces not only three-dimensional surface maps of geometry. But with their atomic force microscope device the Clarkson scientists can also map properties such as the rigidity of the cells at various points on its surface or a cell's adhesion, its ability to cling to a nearby object, such as the needle probe of the atomic force microscope itself.
The Clarkson measurements show that cancerous cells feature a consistent fractal geometry, while healthy cells show some fractal properties but in an ambiguous way. The fact that the adhesive map is fractal for cancerous cells but not for healthy cells was not known before.
Being able to differentiate clearly between healthy and cancerous cells would be important step toward a definitive diagnosis of cancer. Can a fractal measurement of cells serve as such a test for malignancy?
Sokolov believes it can.
"The existing cytological screening tests for cervical cancer, like Pap smear, and liquid-based cytology, are effective and non-invasive, but are insufficiently accurate," said Sokolov.
These tests determine the presence of suspicious abnormal cells with sensitivity levels ranging from 80 percent all the way down to 30 percent, for an average of 47 percent.
The fractal criterion used in the Clarkson work was 100 percent accurate in identifying the cancerous nature of 300 cells derived from 12 human subjects, Sokolov said. He intends now to undertake a much wider test.
"We expect that the methodology based on our finding will substantially increase the accuracy of early non-invasive detection of cervical cancer using cytological tests," Sokolov said.
Sokolov asserts that physics-based methods, such as his atomic force microscope maps of cells, will complement or even exceed in detection ability the more traditional biochemical analysis carried out at the single cell level.
"We also plan to study how fractal behavior changes during cancerous transformation, when a normal cell turns into a fully developed malignant cell, one with a high degree of invasiveness and the ability to reproduce itself uncontrollably," Sokolov added.
Robert Austin, an expert on biological physics at Princeton University in N.J., believes it is important to learn more about the properties that make cancer cells lethal, such as their ability to metastasize, to invade new parts of the body. About the Clarkson paper, which is appearing in the journal Physical Review Letters, [This column will excerpt the Letter, to appear on July 8th by courtesy of Prof. Sokolov - AJP] Austin said "Perhaps this is a step in the direction of connecting physical aspects of cancer cells with the biological reality that their proliferation and invasiveness is what makes them deadly."
[FractoGene (2002, web) and The Principle of Recursive Genome Function (2008, YouTube from 30:00 minutes) are rapidly closing on cancer. While the Fractal Recursive Iteration (developing fractal brain cells was shown as early as in 1989, the "lucid heresy", running head-to-head with both of the (totally wrong) axioms of Old School Genomics ("Junk DNA" and "Central Dogma") met with violent opposition at every step of the long way (including some detractor, alas with inaptitude in math not only to - admittedly - grasp advanced tensor and fractal geometry, but unable to produce a properly rounded number!). Today, a massive evidence is shown below to substantiate the Principle of Recursive Genome Function, where methylation of perused auxiliary (intergenic and intronic) genomic information is of the essence to keep fractal growth bounded (properly regulated). While Prof. Sokolov does not seem to connect the enhanced fractality of cancerous cells with genomic shifts (e.g. in methylation), it is clear that fractal geometry has an immediate utility e.g. for diagnosis by measuring significant difference in fractal dimension of already developed cancerous cells. Imagine how important it is to conduct a targeted search for "fractal defects" of the genome BEFORE the uncontrolled protein-production is spotted from the very early signs of genomic shifts e.g. in methylation! History will not be kind to those whose tardiness contributes to hundreds of millions of people dying of "Junk DNA diseases" (such as cancers), while those smart enough to advance (also in mathematics, in algorithmic - software enabling) to PostModern analytics of genome function will be richly rewarded - This entry can be discussed on the FaceBook of Andras Pellionisz]
A quest for better genetics [from Moscow...]
The Moscow News
By Oleg Nikishenkov at 27/06/2011 21:56
Genetics, advanced mathematics and new online solutions can help humans quantify their behavior with the ultimate goal of living longer.
That’s the message from Esther Dyson, a top-50 global IT investor and Skolkovo advisor who is promoting a new project in genome analysis designed to fulfill the goal.
“Biology becomes more and more information processing, and you have some of the best mathematicians and algorithm people here in Russia,” Dyson told The Moscow News on the sidelines of RIA Novosti’s Future Media Forum in Moscow last week.
The process of getting personal genetic analysis is fairly simple, despite its scientific complexity. All you have to do is deposit saliva into a test tube and send your sample to the lab. But it has geographical and even political restrictions. If you are in Russia, you need a special permission to send a sample of your saliva to the US, where the 23andMe (equal to the number of human chromosomes) labs are. And some US states prohibit the purchase of genetic data by private individuals on the assumption of reaction to this knowledge could be unpredictable. “We keep the information very secure but if you fear more than fear of death, we won’t get you genus [genomic] test done,” Dyson said.
Nikolai Mityushin, head of investments of the ABRT venture fund, said such projects are quite promising, as they deal with real needs like healthcare.
“On the other hand, the specifics of the project attribute it to the biotech industry, which has its own regulation,” he said.
Dyson said some Russian businesspeople she knows have already sent samples of their saliva to the project.
The higher math and strong computer systems required to analyze SNPs (Single Nucleotide Polymorphism), which are variations each our gene has.
“What we look for is specific little correlations of data, which come in different varieties,” Dyson said. They occur once in every 300 nucleotides on average, which means there are roughly 10 million SNPs in the human genome.
Currently genetic labs can analyze 1 million SNPs, but “in two years it will probably be 3 million and in a few years the entire genome will be collected,” Dyson said. That might help predict an individual’s reaction to certain drugs and the risk of some diseases, including heart failure, diabetes and cancer.
But so far the genetic testing only gives “hints” on how to change your behavior.
“The remainder of the proof is left as an exercise for the reader,” said Dyson quoting popular math professors’ saying. She explained that the next trend is user-generated data for research, as opposed to user-generated content. “And this research is about ourselves,” she said.
Pavel Gitelman, who coordinates the Red Quest project, said that in Russia such an innovation could be well received by wealthy clients. “We still have quite a huge category of people who mistrust genetics, but fully believe in all kinds of fortune tellers,” he said.
[Some of the World's best algorithm-creators, like Sergey Brin and Larry Page originate from Russia (Sergey was born in Moscow) - now running the World's most powerful IT company (Google, Inc.). Shura Grosberg published - while in Moscow, in the early 90-s - the seminal concept of the fractal folding structure of the DNA-strand (to become the foundation of Lander et. al. 2009 Oct 9 Science Cover article "Mr. President, the Genome is Fractal!"). As I mention towards the end of my 2008 Google Tech Talk YouTube , for those who know that the Internet itself is fractal (and depends on "recursion", moreover putting "cookies" to perused pages...) it should be obvious that the genome functions based on The Principle of Recursive Genome Function (Pellionisz, 2008, see the seminal Fractal Model of brain cell 1989). Interestingly, as shown below (a Figure from Pellionisz' 2009 presentation in Cold Spring Harbor Laboratories, upon invitation by Harvard Professor of Genetics George Church, even Esther Dyson's father (physicist Freeman Dyson) suspected that the origin of life may be fractal by showing the Mandelbrot fractal set on the cover of his book - though neither the index mentions "fractal", nor citation is not made to "Mandelbrot". Some of such "near misses" may be even more likely where the gap between "biologist" Lisenko and outstanding mathematicians let to some mistrust of genetics. To the advantage of the European Schools, the two mistaken dogmas of Genomics (the "Junk DNA" misnomer, rendered obsolete by Pellionisz' Symposium in Budapest, 2006, and Nobelist Crick's huge mistake "Central Dogma") have never been entrenched to such a degree in Europe than in America. In the USA, the establishment till the end of ENCODE 2007 and some detractor individual of Toronto, without the elementary competence in mathematics if a number was rounded correctly or not (!) inflicted severe damage on the development of PostModern Genomics. Huge downloads (much more from the Ukraine compared from Russia) from this website show a torrent of interest now in PostModern Genome Informatics. This entry can be discussed on the FaceBook of Andras Pellionisz]
Study Suggests Widespread Loss of Epigenetic Regulation in Cancer Genomes
June 27, 2011
By Andrea Anderson
Genomeweb
[Figure from Nature Genetics - by courtesy of Dr. Feinberg ]
NEW YORK (GenomeWeb News) - Cancer coincides with a widespread loss of epigenetic regulation affecting large chunks of DNA in the genome, according to a study in the early, online version of Nature Genetics yesterday. ["We suggest a model for cancer involving loss of epigenetic stability of well-defined genomic domains that underlies increased methylation variability in cancer that may contribute to tumor heterogeneity."].
Using custom microarrays, American researchers assessed methylation patterns in five types of cancer, focusing on regions of the genome that were shown to be differentially methylated in cancer in the past. The team found that cancer genomes show dramatically different methylation patterns compared to corresponding normal tissues, including a lack of defined methylation boundaries around so-called CpG islands where cytosine and guanine nucleotides frequently neighbor one another.
In addition, they reported, the cancers showed dramatic variability in their methylation levels, along with changes in some parts of the genome that are known to be differentially methylated in other tissue types or in undifferentiated cells.
Moreover, their bisulfite sequencing studies of colon cancer, pre-cancerous polyps, and normal colon tissue uncovered large stretches of DNA that were differentially methylated in the cancer samples, leading to altered expression of some cell cycle and cell matrix-related genes in these regions.
"Epigenetics, specifically DNA methylation, is losing its regulation in cancer and we think that that's helping cancer thrive," co-first author Winston Timp, a post-doctoral fellow in Andrew Feinberg's lab at Johns Hopkins University's Center for Epigenetics, told GenomeWeb Daily News.
"It may be a very early event which acts in conjunction with mutations to cause cancer," he added. "And it seems to happen in all types of cancer."
In 2009, Feinberg, Johns Hopkins biostatistics and epigenetics researcher Rafael Irizarry, and colleagues published a Nature Genetics study describing methylation differences in colon cancers compared to normal colon tissue. In particular, they found cancer-specific differences not necessarily within CpG islands, but more often on the "shores" of these islands.
In addition, many of the same regions that were differentially methylated in the colon cancers correspond to those that tend to be differentially methylated in various tissue types or in undifferentiated cells.
Consequently, the team decided to look at several cancer types in the current study, Timp explained. "If these differences seem to control differentiation state, so to speak, maybe they'll show differences in other cancers too."
Using Illumina custom bead arrays, the team first tested 122 colon, lung, breast, and thyroid cancers and Wilms' tumors, a childhood kidney cancer. They also tested 30 pre-malignant samples, along with 141 matched control samples, focusing on 384 sites in 151 cancer-specific differentially DNA-methylated regions detected in colon cancer in the past
Indeed, researchers reported, cancer and normal samples from each tissue type had very distinct methylation patterns. While both normal tissues and cancers tended to fall in distinct clusters based on their methylation patterns, methylation in the cancer samples was far more variable.
"This seems to show a loss of control - a loss of regulation - of methylation in cancer compared to [matched normal tissue]," Timp said. "The five different normal tissues also cluster out very well from each other … but all the cancers are much more variable."
To explore the methylation patterns across the genome in cancer cells, meanwhile, the researchers did shotgun, whole-genome bisulfite sequencing of three colorectal tumor samples — along with matched normal colon tissue and two pre-cancerous adenomatous polyp samples — using the ABI SOLiD platform.
From this sequence data, the team found altered methylation in large chunks of the cancer genomes. These blocks frequently had lower methylation levels than normal colon tissue, though, again, methylation patterns were far more variable in the cancer samples.
Consistent with these methylation changes, the expression of genes within these hypo-methylated blocks of the cancer genomes typically showed higher but more variable expression.
"We think that what's happening is a loss of [methylation] control rather than a concerted shift," Timp explained.
In addition, he noted, some of these differentially methylated regions in cancer appear to coincide with regions previously reported to be partially methylated in stem cells or other tissue types, while others overlapped with regions known to have chromatin alteration or epigenetic marks related to lamina function.
"We can say with some certainty that these areas are important for both differentiation and cancer," Timp said. "We would propose that maybe there's a link here and maybe cancer is losing regulation of these areas and reverting to a more primitive or less controlled state."
Although more research is needed to determine whether that is the case or whether there is some other explanation for the importance of the areas in both cancer and tissue development or differentiation, those involved in the study argue that their findings may ultimately lead to improved tests or treatments for cancer.
"Maybe the big lesson learned from our observation of this universal [epigenetic] chaos is that we may need to think not so much about just killing cancer cells, but also about ways of helping cancer cells figure out how to be what they're supposed to be, and re-educate them so they can stay truer to their normal identities," Feinberg said in a statement.
[This landmark experimentation substantiates the prediction of The Principle of Recursive Genome Function (also popularized in the YouTube, both in 2008) by Pellionisz. Fractal Iterative Recursion, to grow organelles, organs and organisms (FractoGene) requires not only a recursion to intergenic and intronic regions of the DNA to pick up auxiliary information to maintain growth, but also the auxiliary information must be cancelled (e.g. by methylation) to prevent uncontrolled use, resulting in cancerous protein production. The two snapshots from YouTube show normal methylation (at 31:04 of YouTube, while at 31:50 of the YouTube the epigenomic control by methylation is shown to be defective, leading to unduly repeated perusal of "non-coding" information. This entry can be discussed in the FaceBook page of Andras Pellionisz]
A surge of top-quality papers pointing into "methylation-defects" as predicted by FractoGene as culprits for cancer
Scientists Report that Methylation Chaos in Cancer Contributes to Cell Adaptability
http://www.genengnews.com/gen-news-highlights/scientists-claim-methylation-chaos-in-cancer-contributes-to-cell-adaptability/81245352/
Scientists claim cancer cells have lost the ordered patterns of methylation demonstrated by normal tissues and demonstrate chaotic methylation across the genome that could help them adapt to changing environments in growing tumors and facilitate metastasis. Research by aJohns Hopkins University-led team has found that in contrast to normal tissues that demonstrate specific patterns of methylation at CpG islands or in large blocks of DNA, cells from a range of different tumor types showed vastly differing methylation patterns at the same sites, which they termed differentially-methylated regions (cDMRs).
In colon cancer this was evidenced by loss of methylation stability both at the boundaries of CpG islands and the presence of blocks of hypomethylation affecting over half the genome, which together led to significant variability in gene expression. Andrew P. Feinberg, M.D., professor of molecular medicine and director of the Center for Epigenetics at the Johns Hopkins University School of Medicine’s Institute for Basic Biomedical Sciences, and colleagues, report their findings in Nature Genetics. In their paper, titled “Increased methylation variation in epigenetic domains across cancer types,” the authors point out that their findings could indicate that the use of nonspecific DNA methylation inhibitors as cancer therapy could have unwanted effects by activating tumor-promoting genes in hypomethylated blocks.
Work by Dr. Feinberg’s team has previously demonstrated that colon cancers exhibit changes in the degree of methylation at regions of lower CpG density near CpG islands. These cDMRs corresponded in the main to the same regions that show DNA methylation variation in normal spleen, liver, and brain tissues, or tissue-specific DMRs (tDMRs), suggesting their involvement in cell differentiation in normal tissues.
To investigate cancer-related changes in global methylation further, the researchers designed an array to analyze over 151 cDMRs that were consistently altered across colon cancer, and compared methylation within these regions in another 290 samples including matched normal and cancer samples from colon, breast, lung, thyroid, and Wilms’ tumor. They found that almost all of the cDMRs were altered across all cancers tested. “Specifically, the cDMRs showed increased stochastic variation in methylation level within each tumor type, suggesting a generalized disruption of the integrity of the cancer epigenome,” the team suggests.
To look further at this phenomenon, the team carried out genome-scale bisulfite sequencing of three colorectal cancers, matched normal colonic mucosa and two adenomatous polyps. The study was designed to obtain methylation estimates with enough precision to detect differences of 20% methylation. The results demonstrated a significant loss of methylation stability in colon cancer, which involved CpG islands and their boundary regions (shores), and also identified large blocks (5010 kb) of hypomethylation. “Remarkably, these hypomethylated blocks in cancer corresponded to more than half of the genome, even after accounting for the number of CpG sites within the blocks,” the authors note.
Over 5,800 hypermethylated and 4,300 hypomethylated small DMRs (less than 5 kb) were also identified. Interestingly, the research comfirmed previous findings that hypermethylated cDMRs are enriched in CpG islands, whereas hypomethylated cDMRs are enriched at CpG island shores. The thousands of small DMRs frequently involved loss of boundaries of DNA methylation at the edge of CpG islands, shifting of DNA methylation boundaries, or the creation of novel hypomethylated regions in CG-dense regions that are not normally recognized as islands. The knock-in effect of this variability in cancer cell methylation was both an increase in gene silencing and a substantial enrichment of genes with increased expression variability in the methylated blocks, Dr. Feinberg and colleagues state.
These data underscore the importance of hypomethylated CpG island shores in cancer, the authors note: “Shores associated with hypomethylation and gene overexpression in cancer are enriched for cell cycle related genes, suggesting a role in the unregulated growth that characterizes cancer.” Regions of altered methylation in cancer were also found to match those in normal tissues associated with controlling cell differentiation into specific cell types. “Targeting those regions might help the cells become more normal,” suggests Rafael Irazarry, Ph.D., professor of biostatistics at the Johns Hopkins University Bloomberg School of Public Health and lead author of the Nature Genetics paper.
From the cancer perspective, methylation chaos is helpful because it means tumors can turn genes on and off in an uncontrolled way, increasing their adaptability, Dr. Feinberg adds. This indicates that increased epigenetic heterogeneity in cancer at cDMRs may play a role in the ability of cancer cells to adapt rapidly to changing tissue environments, such as increased oxygen in regions of neovascularisation, then decreased oxygen with necrosis, or metastasis to a new intercellular milieu.
Current efforts to exploit DNA methylation for cancer screening have focused on identifying narrowly defined cancer-specific profiles. However, the Johns Hopkins research suggests broader evaluation of the cancer epigenome may be more relevant. “Given the importance of boundary regions for both small DMRs and large blocks identified in this study, it will be important to focus future epigenetic investigations on the boundaries of blocks and CpG islands (shores) and on genetic or epigenetic changes in genes encoding factors that interact with them,” the authors conclude.
Measuring DNA Methylation
http://asweetlife.org/a-sweet-life-staff/featured/dna-methylation-the-coolest-new-technology-at-the-ada-scientific-sessions/17772/
What is this promising new technology? A means of “Using Differentially Methylated Circulating DNA for In Vivo Detection of Beta-Cell Death in Diabetes,” as presented by Dr. Eitan Akirav.
Come again? Using differentially methy-what?
Okay, I admit the technology is not very consumer-friendly, but it’s really cool, so bear with me, and we’ll start from the beginning.
Beta-cell death is a problem in both type 1 and type 2 diabetes; in the former, cell death is induced as cells react to their increasingly toxic, auto-reactive environment, and in the latter, cell death is induced as cells become over-stressed. Currently, beta-cell death is very hard to measure. The best way is to look directly at tissue in the pancreas—but that’s not possible if you want to keep your human patient or mouse models alive. Without tissue samples, imaging of a living pancreas would be useful, but that proves difficult and inaccurate because of the location and nature of the pancreas. So, researchers will usually quantify beta-cell death using proxies like C-peptide (as an indicator of how much insulin is being secreted).
These proxies, though, are not reliable or accurate; ideally, if we want to understand exactly what causes beta-cell death and what we can do to manipulate the process, we should be able to measure the degree of beta-cell death while the subject is still living, and without too much indirection.
This sort of problem is not unique to diabetes; researchers face a similar issue with, for example, diagnosing cancers. Many cancers come with tangible symptoms or lumps, but how can you test for internal cancers in asymptomatic patients before it’s too late? Much research has been done to identify unique biological signatures, called biomarkers, for tumors. People started by looking for specific proteins or RNA sequences, but these have not proved reliable indicators of many tumors. More recently, though, a promising new biomarker is being tested—the methylation of DNA fragments circulated freely in the blood [1].
Relationship exists between mutations in tumors and methylation patterns found in their genomes
http://triplehelixblog.com/2011/07/methylation-the-cause-of-brain-tumor/
Methylation: The Cause of Brain Tumor?
When one thinks of the word “cancer” breast cancer, lung cancer, and skin cancer are among the various types that first come to mind. One type of cancer that is often neglected is Brain Tumor. According to the National Tumor Society, more than 500 people per day are diagnosed with primary or metastatic brain tumor and what’s worse is that the mortality rates for those diagnosed with brain and nervous system tumors haven’t improved over the past decade. The desperate need for new treatments and therapies for brain tumor is evident and it is the hope of many people whose loved one have suffered the wrath of this incurable disease that 2011 will bring new treatments and bring the path to the cure closer than ever before [1].
Neuroscience is an area of science that has faced its fair share of failures, yet that doesn’t mean scientists should give up on the field itself. Recently, researchers at the Alpert Medical School made an important discovery that may change the face of brain tumor treatments and diagnosis forever.
This new discovery is developed from the hypothesis that a relationship exists between mutations in tumors and methylation patterns found in their genomes (2). Chemically speaking, methylation is the addition of a methyl group to a substrate or the substitution of an atom or group by a methyl group. When DNA is methylated, gene silencing often occurs which could be the cause of the tumor. Gene silencing is a process of gene regulation which “switches off” a gene through a mechanism. Researchers and neuroscientists speculate that the methylated regions mark the genes involved in metabolic processes which explain the abnormal behavior of tumor cells [2]
New Method Used by Cells to Reverse Silenced Genes Discovered
New Method Used by Cells to Reverse Silenced Genes Discovered http://www.medindia.net/news/New-Method-Used-by-Cells-to-Reverse-Silenced-Genes-Discovered-87312-1.htm#ixzz1ScKlWBcS
Novel mechanism used by body cells to turn on the silenced genes has been identified by researchers at Fox Chase Cancer Center. This process is critical in preventing the development of cancer suggesting the possibility of new therapies that might target the specific changes underlying the disease. The findings will be published online in the journal Cell.
Read more: New Method Used by Cells to Reverse Silenced Genes Discovered http://www.medindia.net/news/New-Method-Used-by-Cells-to-Reverse-Silenced-Genes-Discovered-87312-1.htm#ixzz1ScL7s4vP
The process investigated by Alfonso Bellacosa, M.D., Ph.D., Associate Professor at Fox Chase, and his colleagues, is called methylation, in which the cell chemically tags genes to turn them off. More specifically, the cell silences a gene by adding a chemical compound known as a methyl group; without that methyl group, the gene remains active.
Read more: New Method Used by Cells to Reverse Silenced Genes Discovered http://www.medindia.net/news/New-Method-Used-by-Cells-to-Reverse-Silenced-Genes-Discovered-87312-1.htm#ixzz1ScLKxrKH
"So What?" - if you separate Fractal Defects from Structural Variants of Human Diversity? - In Vivo Genome Editing!
[Zinc Finger Nucleases inserted into intron ("Junk"...) fix Hemophilia in Mouse - AJP]
Genome editing, a next step in genetic therapy, corrects hemophilia in animals.
Using an innovative gene therapy technique called genome editing that hones in on the precise location of mutated DNA, scientists have treated the blood clotting disorder hemophilia in mice. This is the first time that genome editing, which precisely targets and repairs a genetic defect, has been done in a living animal and achieved clinically meaningful results. As such, it represents an important step forward in the decades-long scientific progression of gene therapy -- developing treatments by correcting a disease-causing DNA sequence.
In this new study, researchers used two versions of a genetically engineered virus (adeno-associated virus, or AAV) -- one carrying enzymes that cut DNA in an exact spot and one carrying a replacement gene to be copied into the DNA sequence. All of this occurred in the liver cells of living mice. "Our research raises the possibility that genome editing can correct a genetic defect at a clinically meaningful level after in vivo delivery of the zinc finger nucleases," said the study leader, Katherine A. High, M.D., a hematologist and gene therapy expert at The Children's Hospital of Philadelphia. High, a Howard Hughes Medical Institute Investigator, directs the Center for Cellular and Molecular Therapeutics at Children's Hospital, and has investigated gene therapy for hemophilia for more than a decade.
The study appeared online today in Nature.
High's research, a collaboration with scientists at Sangamo BioSciences, Inc., makes use of genetically engineered enzymes called zinc finger nucleases (ZFNs) that act as molecular word processors, editing mutated sequences of DNA. Scientists have learned how to design ZFNs custom-matched to a specific gene location. ZFNs specific for the factor 9 gene (F9) were designed and used in conjunction with a DNA sequence that restored normal gene function lost in hemophilia. By precisely targeting a specific site along a chromosome, ZFNs have an advantage over conventional gene therapy techniques that may randomly deliver a replacement gene into an unfavorable location, bypassing normal biological regulatory components controlling the gene. This imprecise targeting carries a risk of "insertional mutagenesis," in which the corrective gene causes an unexpected alteration, such as triggering leukemia.
In hemophilia, an inherited single-gene mutation impairs a patient's ability to produce a blood-clotting protein, leading to spontaneous, sometimes life-threatening bleeding episodes. The two major forms of the disease, which occurs almost solely in males, are hemophilia A and hemophilia B, caused respectively by a lack of clotting factor VIII and clotting factor IX. Patients are treated with frequent infusions of clotting proteins, which are expensive and sometimes stimulate the body to produce antibodies that negate the benefits of treatment. In the current study, the researchers used genetic engineering to produce mice with hemophilia B, modeling the disease in people. Before treatment, the mice had no detectable levels of clotting factor IX. Previous studies by other researchers had shown that ZFNs could accomplish genome editing in cultured stem cells that were then injected into mice to treat sickle cell disease. However, this ex vivo approach is not feasible for many human genetic diseases, which affect whole organ systems. Therefore the current study tested whether genome editing was effective when directly performed in vivo (in a living animal). High and colleagues designed two versions of a vector, or gene delivery vehicle, using adeno-associated "Genome editing, a next step in genetic therapy, corrects hemophilia in animals." PHYSorg.com. 26 Jun 2011. http://www.physorg.com/news/2011-06-genome-genetic-therapy-hemophilia-animals.html Page 1/2 virus (AAV). One AAV vector carried ZFNs to perform the editing, the other delivered a correctly functioning version of the F9 gene. Because different mutations in the same gene may cause hemophilia, the process replaced seven different coding sequences, covering 95 percent of the disease-carrying mutations in hemophilia B.
The researchers injected mice with the gene therapy vector, which was designed to travel to the liver—where clotting factors are produced. The mice that received the ZFN/gene combination then produced enough clotting factor to reduce blood clotting times to nearly normal levels. Control mice receiving vectors lacking the ZFNs or the F9 minigene had no significant improvements in circulating factor or in clotting times. The improvements persisted over the eight months of the study, and showed no toxic effects on growth, weight gain or liver function, clues that the treatment was well-tolerated. "We established a proof of concept that we can perform genome editing in vivo, to produce stable and clinically meaningful results," said High. "We need to perform further studies to translate this finding into safe, effective treatments for hemophilia and other single-gene diseases in humans, but this is a promising strategy for gene therapy." She continued, "The clinical translation of genetic therapies from mouse models to humans has been a lengthy process, nearly two decades, but we are now seeing positive results in a range of diseases from inherited retinal disorders to hemophilia. In vivo genome editing will require time to mature as a therapeutic, but it represents the next goal in the development of genetic therapies."
[The Nature paper concludes:
Studies showing that ZFNs can mediate gene correction efficiently through the introduction of site-specific DSBs, and can induceHDRin cultured cells, have provided important proof-of-concept results for the clinical application of engineered nucleases for diseases affecting cells that can be removed and returned to the patient. However, the necessity to isolate and manipulate cells ex vivo limits the application of this technology to a subset of genetic diseases. Our results show that AAV-mediated delivery of a donor template and ZFNs in vivo induces gene targeting, resulting in measurable circulating levels of factor IX.
This therapeutic strategy is sufficient to restore haemostasis in a mouse model of haemophilia B, thus demonstrating genome editing in an animal model of a disease. Clinical translation of these results will require optimization of correction efficiency and a thorough analysis of off-target effects in the human genome, an issue that we have begun to monitor. Together, these data show that AAV-mediated delivery of ZFNs and a donor template gives rise to persistent and clinically meaningful levels of genome editing in vivo, and thus can be an effective strategy for targeted gene disruption or in situ correction of genetic disease in vivo.]
[When presenting paradigm-shifts, the most American question is "so what?". To be able to separate Fractal Defects (wherein the genome violates its own mathematics) from at least 4 million Structural Variants that only reflect "Human Diversity" (with the fractality intact) is nice. However, in the not-so-distant future when Big Pharma delivers drops of liquid containing a harmless virus that carries a "patch" to fix genomic glitches, not unlike when your computer updates lethal Windows defects by simply patching them, will make a similar, but multiple quantum leaps like when Polyo was rendered harmless - this entry can be discussed in FaceBook of Andras Pellionisz]
23andMe-Led Team Reports on Findings from Web-Based Parkinson's GWAS
June 24, 2011
By a GenomeWeb staff reporter
NEW YORK (GenomeWeb News) - In a paper appearing online last night in PLoS Genetics [See Excerpts and link below - AJP], researchers from the personal genetics firm 23andMe and the Parkinson's Institute in California reported that they have identified two new loci contributing to Parkinson's disease risk.
The team's web-based genome-wide association study approach involved 3,426 individuals with Parkinson's disease - enrolled over the span of a year-and-a-half through a collaboration between 23andMe, the Michael J. Fox Foundation, the National Parkinson Foundation, and the Parkinson's Institute and Clinical Center - and 29,624 unaffected control individuals who enrolled as customers of 23andMe's personal genome services.
Using custom Illumina HumanHap 550+ arrays to genotype these individuals, researchers not only verified 20 Parkinson's associations identified previously, but also detected two new risk loci - one SNP falling near the lysosomal integral membrane protein type 2 coding gene SCARB2 and another in the vicinity of the SREBF1 and RAI1 genes. Two other variants - in and around the RIT2 gene and the USP25 gene - fell just shy of significantly associating with the disease.
"Not only are these new genetic findings significant, but we've also shown that the data collected by 23andMe support discovery of new associations as well as replication of previously known associations," lead author Chuong Do, a research scientist at 23andMe, said in a statement.
"This study is a rigorous 'proof of principle,'" he added, "and clearly demonstrates that web-based phenotyping works for a disease of real public health significance."
Based on their findings so far, the team estimated that at least a quarter of Parkinson's disease risk can be attributed to genetic factors. Consequently, they say, additional studies are needed to further tease apart the genetic environmental contributors to the disease.
23andMe's Parkinson's disease cohort now consists of more than 5,000 individuals with the condition, the company said. Meanwhile, some 76,000 individuals who use the 23andMe database have reportedly consented to participate in the Parkinson's disease or similar 23andMe research projects.
For instance, the company is currently using a similar web-based approach to study sarcoma, using a cohort that includes more than 500 individuals with that disease.
"We believe this paper proves the potential of our approach of combining genetic information with web-based data about specific conditions to make novel research discoveries," Anne Wojcicki, president and CEO of 23andMe, said in a statement. "This approach has the potential to be used in many other conditions."
[Excerpts and Link of the PLOS paper - AJP]
Chuong B. Do1*, Joyce Y. Tung1, Elizabeth Dorfman1, Amy K. Kiefer1, Emily M. Drabant1, Uta Francke1, Joanna L. Mountain1, Samuel M. Goldman2, Caroline M. Tanner2, J. William Langston2, Anne Wojcicki1, Nicholas Eriksson1*
We conducted a large genome-wide association study (GWAS) of Parkinson's disease (PD) with over 3,400 cases and 29,000 controls (the largest single PD GWAS cohort to date). We report two novel genetic associations and replicate a total of twenty previously described associations, showing that there are now many solid genetic factors underlying PD. We also estimate that genetic factors explain at least one-fourth of the variation in PD liability, of which currently discovered factors only explain a small fraction (6%-7%). Together, these results expand the set of genetic factors discovered to date and imply that many more associations remain to be found. Unlike traditional studies, participation in this study took place completely online, using a collection of cases recruited primarily via PD mailing lists and controls derived from the customer base of the personal genetics company 23andMe. Our study thus illustrates the ability of web-based methods for enrollment and data collection to yield new scientific insights into the etiology of disease, and it demonstrates the power and reliability of self-reported data for studying the genetics of Parkinson's disease.
We found two novel associations at a genome-wide level of significance near SCARB2 (rs6812193) and SREBF1/RAI1 (rs11868035), both of which were replicated in data from [23]. We also report two novel associations (near RIT2 and USP25) just under the level of significance, one of which (RIT2) was also replicated. While it is difficult to pinpoint any causal genes from a GWAS, there are a few biologically plausible candidates worthy of discussion.
The PD-associated SNP rs6812193 lies in an intron of the FAM47E gene, which gives rise to multiple alternatively spliced transcripts, many of which are protein-coding; the functions of these hypothetical proteins are unknown. A more attractive candidate, located kb centromeric to the SNP, is SCARB2 (scavenger receptor class B, member 2), which encodes the lysosomal integral membrane protein type 2 (LIMP-2). LIMP-2 deficiency causes the autosomal-recessive disorder Action Myoclonus-Renal Failure syndrome (AMRF), which combines renal glomerulosclerosis with progressive myoclonus epilepsy associated with storage material in the brain [34]. LIMP-2 is involved in directing -glucocerebrosidase to the lysosome where it hydrolyzes the -glycosyl linkage of glucosylceramide [35]. Deficiency of this enzyme due to mutations in its gene (GBA) causes the most common lysosomal storage disorder, Gaucher's disease. Recently, mutations in GBA have also been identified in PD [36], pointing to a possible functional link between the newly identified candidate gene SCARB2 and PD.
rs11868035 appears in an intron of the alternatively spliced gene, SREBF1 (sterol regulatory element-binding transcription factor 1), within the Smith-Magenis syndrome (SMS) deletion region on 17p11.2. SREBF1 encodes SREBP-1 (sterol regulatory element-binding protein 1), a transcriptional activator required for lipid homeostasis, which regulates cholesterol synthesis and its cellular uptake from plasma LDL [37]. Studies of neuronal cell cultures have implicated SREBP-1 as a mediator of NMDA-induced excitotoxicity [38]. rs11868035 is directly adjacent to the acceptor splice site for the C-terminal exon of the SREBP-1c isoform of the protein [39], suggesting that the effect of the polymorphism may be specifically related to the splicing machinery for this protein. The mutation is also in strong LD with rs11649804, a nonsynonymous variant in the nearby gene RAI1 (retinoic acid-induced protein 1), which regulates transcription by remodeling chromatin and interacting with the basic transcriptional machinery. Heterozygous mutations in RAI1 reproduce the major symptoms of SMS, such as developmental and growth delay, self-injurious behaviors, sleep disturbance, and distinct craniofacial and skeletal anomalies [40]. Future work is needed to identify the functionally important variant(s) responsible for this association.
The SNP rs4130047, slightly below the genome-wide significance threshold, lies in an intron of the RIT2 (Ras-like without CAAX 2) gene that encodes Rit2, a member of the Ras superfamily of small GTPases. Though we do not claim this SNP as a confirmed replication, there are a number of reasons to suspect that this association may also be real. Rit2 binds calmodulin in a calcium-dependent manner, and is thought to regulate signaling pathways and cellular processes distinct from those controlled by Ras [41]. It localizes to both the nucleus and the cytoplasm. Independent of our study, RIT2 was previously proposed as a candidate gene for PD, based on the possibility that dopaminergic neurons may be especially vulnerable to high intracellular calcium levels, perhaps through an interaction with -synuclein [42]. The PD-associated region contains another biologically plausible candidate gene, SYT4 (synaptotagmin IV), which encodes synaptotagmin-4, an integral membrane protein of synaptic vesicles thought to serve as sensor in the process of vesicular trafficking and exocytosis. It is expressed widely in the brain but not in extraneural tissues [43]. Homozygous Syt4−/− mouse mutants have impaired motor coordination [44]. SYT4 is particularly interesting as a SNP near SYT11 (synaptotagmin XI) has been associated with PD in [22], and the encoded protein, synaptotagmin-11, is known to interact with parkin [45].
The suggestively associated SNP rs28233572 lies in a gene-poor region with only one candidate gene downstream, USP25, encoding ubiquitin specific peptidase 25, which regulates intracellular protein breakdown by disassembly of the polyubiquitin chains. Other ubiquitin-specific proteases (USP24, USP40) have been proposed as candidate genes for PD [46] (although USP24 fails to replicate here, see Table 3).
Our heritability estimates, which suggest that genetic factors account for at least one-fourth of the total variation in liability to PD, represent the tightest confidence bounds determined for the heritability of PD to date. These estimates, which rely on observed genetic sharing rather than predicted relationship coefficients, avoid confounding from shared environmental covariance by restricting attention to very distantly related individuals. Furthermore, they complement estimates of heritability from twin studies by considering large numbers of individuals with low amounts of genetic sharing, rather than small numbers of twin pairs with large amounts of genetic sharing.
These estimates should only be interpreted as lower bounds on the actual heritability of liability of PD for two reasons. First, they only reflect phenotypic variation due to causal variants in LD with SNPs on the genotyping platform. Second, they only capture the contribution to additive variance that arises from a polygenic model of many SNPs of small effect, but do not include the variance arising from known specific associations. This limitation is most apparent in our estimate of heritability based on only early-onset cases (), which is considerably lower than reported in prior twin studies (e.g., in [10]). In early-onset PD, mutations in six specific genes (SNCA, PRKN, PINK1, DJ1, LRRK2, and GBA) have been reported to account for 16% of cases [47]; these specific mutations are not directly accounted for in our estimate, which is based on a polygenic model. We note that a similar effect may explain the low heritability estimate for early-onset PD in [48]. Thus, the actual heritability of PD, and the corresponding true upper bound on discriminative accuracy achievable through genetic factors, may be even higher than the estimates we provide.
Our estimates also indicate a substantial genetic component for late-onset PD (), for which previous estimates of heritability have been inconclusive due to the lack of statistical power (e.g., 0.068 in [10] and 0.453 in [48]). One might ask, if late-onset PD is indeed so heritable, why do cases frequently appear sporadically in the general population? Following the analysis of [49], if one were to assume a heritability of and an average of three children per family, then the proportion of sporadic cases (i.e., no parent, child, sibling, grandparent, aunt or uncle, or first cousin with PD) among all PD cases would be 64% for a prevalence of ; in the 23andMe cohort, 69% of PD cases would be considered sporadic by this definition based on self-reported family history. Similarly, the expected proportion of PD cases with no affected parent or sibling would be 88% under the same assumptions, compared with 84% as reported in [50], or 89% based on the cohort in [51]. These examples illustrate the fact that the presence or absence of a familial pattern cannot always be used to determine pathogenesis, especially for diseases that are rare and have a complex etiology.
Overall, our risk prediction results are consistent with a measured AUC of roughly 0.6. The cross-validated AUCs presented here should be distinguished from more usual measurements of AUC in genome-wide association studies, which are typically only estimated on the development set, and which rely on weighted combinations of SNPs with independently estimated odds ratios. In some cases, the bias resulting from lack of proper external validation can be quite large. For example, a simple genetic profile score based on multiplying together odds ratios for the SNPs in Table 2 appears to achieve an AUC of in the 23andMe data (or if no covariate adjustment is performed) making it appear competitive with some of the best models described in Table 5. However, when the same model is evaluated in the NINDS data, the AUC drops to , exhibiting a drop in performance characteristic of models that have been overfit to their training data. In contrast, the consistency between the internal and external validation results in the models shown in Table 5 demonstrate not only the predictiveness of our models within the 23andMe cohort but also their ability to generalize to other populations.
Our empirical demonstration that including SNPs beyond the genome-wide significant level provides improved discriminative power mirrors the recent results of [32], which also studied the performance of sparse regression methods in a risk prediction setting. In an applied setting where the goal is to achieve the best predictive accuracy rather than to isolate the contribution of individual genetic factors, however, even higher discriminative accuracies may be possible if one were to incorporate these covariates as part of the predictive models. Even without these, however, significant improvements in risk prediction are likely still possible, with our heritability analyses indicating asymptotic target AUCs above 0.8.
Our AUCs are generally conservative for a number of reasons. In the internal experiments, they were obtained by training on only 80% of the data. In the external experiments, the models included only the SNPs in common between the 23andMe and NINDS datasets and thus excluded several SNPs with large effects in LRRK2 and GBA that may add a percent or more to the AUC if included. Furthermore, our analyses adjusted for confounding from population structure and other covariates so as to ensure that the discriminative accuracies we reported were specifically due to genetic effects.
Finally, we note that data for the 23andMe cohort used in this study were acquired in a novel manner, using genotype and survey data acquired through a commercial online personal genetic testing service. The use of self-reported phenotype data raised some unique challenges. For example, our cohort was not a true population sample for a number of reasons, such as the general bias toward higher socioeconomic status, as typical of 23andMe customers. In general, however, we would not expect these ascertainment biases to substantially affect our conclusions unless their effects varied differentially between the case and control sets.
As another example, in compiling the cohort, we used participants with varying levels of completeness in their self-reported data (see Materials and Methods). Out of the 3,426 cases in the 23andMe cohort, though most cases reported having PD in a questionnaire, 482 affirmatively stated they had PD upon entry to the research study but did not fill out any PD-related questionnaire during the study. However, we did not see a large difference between those answering questions and not. Among the 11 associations presented in Table 2, only the association with MAPT showed a significant difference between the cohort who answered a questionnaire and those who did not (see Table S7). Also, approximately 84% of the cases filled out a questionnaire, and of them, over 96% reported a PD diagnosis. Even if a larger fraction (say 10–15%) of those who did not take a questionnaire did not have PD, the gain in power from the additional cases would more than offset the loss of power from having some 50 more false positive cases.
Despite the challenges associated with using self-reported data collected through online surveys, ultimately, our results lend credibility to the accuracy of this novel research design. For example, the agreement between our study and previous studies in terms of the ORs estimated for the 19 associations replicated in Table 3 strongly suggests that our cohort is similar to those used in other PD studies. Similarly, the consistency of AUCs and heritability estimates across our cohort and the NINDS cohort both suggest a limited role of bias in our study.
Importantly, our mode of data collection also provided a number of clear benefits. The use of internet-based techniques enabled rapid recruitment of a large patient community. The 3,426 cases in this study were enrolled in about 18 months, with over half joining in the first month of the study. Also adding significantly to the power and robustness of this study was the availability of a large cohort of controls derived from the 23andMe customer base. By using a non-traditional recruitment approach, we thus were able to attain good power for our study through large sample sizes. To our knowledge, this study represents the largest genome-wide association study of Parkinson's disease conducted on a single cohort to date, with only a recent meta-analysis achieving a larger number of cases [22]. We suggest that this methodology for study design may prove advantageous for other conditions where the advantage of having a large cohort is paramount for detecting subtle genetic effects.
...
In summary, we have for the first time used a rapid, web-based enrollment method to assemble a large population for a genome-wide association study of PD. We have replicated results from numerous previous studies, providing support for the utility of our study design. We have also identified two new associations, both in genes related to pathways that have been previously implicated in the pathogenesis of PD. Using cross-validation, we have provided evidence that many suggestive associations in our data may also play an important role. Using recently developed analytic approaches developed for GWAS that take into account the ascertainment bias inherent in a case-control population, we have estimated the genetic contribution to PD in this sample. These findings confirm the hypothesis that PD is a complex disorder, with both genetic and environmental determinants. Future investigations, expanded to include environmental as well as genetic factors, will likely further refine our understanding of the pathogensis of PD, and, ultimately, lead to new approaches to treatment.
Researchers Develop Methylation-Based Model for Predicting Age from Spit DNA
June 23, 2011
By a GenomeWeb staff reporter
NEW YORK (GenomeWeb News) – In a study appearing online last night in PLoS ONE, a University of California at Los Angeles research team demonstrated that it's possible topredict a person's age from saliva samples using DNA methylation patterns.
Those involved in the study say the findings could have both forensic applications and medical implications, particularly for finding individuals whose biological age differs from their chronological age.
The researchers used microarrays to look at DNA methylation patterns in spit samples from nearly three-dozen male twin pairs between the ages of 21 and 55 years old, tracking down nearly 90 sites where methylation coincides with age. From follow-up experiments involving another group of men and women between the ages of 18 and 70 years old, the team was able to come up with a model that predicts an individual's age to within an average of five years based on methylation status at two sites in the genome.
"Our approach supplies one answer to the enduring quest for reliable markers of aging," senior author Eric Vilain, a professor of human genetics at the University of California at Los Angeles who is also affiliated with the school's Center for Society and Genetics, said in a statement. "With just a saliva sample, we can accurately predict a person's age without knowing anything else about them."
DNA modifications change with tissue development, differentiation, and age, Vilain and his co-authors explained. For the current study, they looked at whether it was possible to exploit these shifts to find age markers, focusing on methylation at cytosine residues — first in identical twins and then in unrelated individuals from the general population.
"While certain methylation changes are genetically controlled, environmental exposure and stochastic processes can lead to a change in methylation patterns," they explained. "In this context, identical twins can be considered replicates of the same developmental and aging experiment."
Using Illumina HumanMethylation27 arrays, the researchers assessed methylation patterns at nearly 16,100 CpG sites in the genomes of 34 pairs of identical male twins between the ages of 21 and 55 years old.
When they sifted through the data for the twins using an analytical approach known as weighted correlation network analysis, the team found five methylation modules containing loci with comparable methylation patterns.
Within the modules, researchers narrowed in on 88 loci at which cytosine methylation status depended on an individual's age, including 69 showing positive correlation and 19 showing negative correlation. The sites fell in and around 80 different genes, they noted, including several genes that have been implicated in cardiovascular, neurological, and other conditions.
Because methylation at three sites in the promoter regions of the EDARADD, TOM1L1, and NPTX2 genes were particularly well correlated with age, the team used either targeted bisulfite sequencing or Sequenom MassArrays to evaluate CpG methylation profiles for these three genes in DNA from saliva samples from 22 of the twins and from another 31 men and 29 women who were between 18 and 70 years old.
Although methylation status for all three genes corresponded to age in the DNA from the male saliva samples, the researchers reported, methylation profiles for just two of these — EDARADD and TOM1L1 — coincided with age in the females.
Meanwhile, the team's predictive model, based on methylation profiles for cytosine residues near the EDARADD and NPTX2 genes, explained some 73 percent of the age variance and could predict age to within a 5.2 year window based on average.
"[O]ur ability to predict an individual's age to an average accuracy of 5.2 years could be used by forensic scientists to estimate a person's age based on a biological sample alone, once the model has been tested in various biological tissues," the study authors wrote.
And, they say, such predictive models may find favor for diagnosing and treating some age-related diseases and for finding situations in which an individual's biological age differs from their age in years.
"Doctors could predict your medical risk for a particular disease and customize treatment based on your DNA's true biological age, as opposed to how old you are," Vilain said in a statement.
Epigenetic Predictor of Age [Full free text of PLOS]
Bocklandt S, Lin W, Sehl ME, Sánchez FJ, Sinsheimer JS, et al. (2011) Epigenetic Predictor of Age. PLoS ONE 6(6): e14821. doi:10.1371/journal.pone.0014821
Published: June 22, 2011
Abstract
From the moment of conception, we begin to age. A decay of cellular structures, gene regulation, and DNA sequence ages cells and organisms. DNA methylation patterns change with increasing age and contribute to age related disease. Here we identify 88 sites in or near 80 genes for which the degree of cytosine methylation is significantly correlated with age in saliva of 34 male identical twin pairs between 21 and 55 years of age. Furthermore, we validated sites in the promoters of three genes and replicated our results in a general population sample of 31 males and 29 females between 18 and 70 years of age. The methylation of three sites—in the promoters of the EDARADD, TOM1L1, and NPTX2 genes—is linear with age over a range of five decades. Using just two cytosines from these loci, we built a regression model that explained 73% of the variance in age, and is able to predict the age of an individual with an average accuracy of 5.2 years. In forensic science, such a model could estimate the age of a person, based on a biological sample alone. Furthermore, a measurement of relevant sites in the genome could be a tool in routine medical screening to predict the risk of age-related diseases and to tailor interventions based on the epigenetic bio-age instead of the chronological age.
Introduction
Throughout development, cells and tissues differentiate and change as the organism ages. This includes alterations to telomeres, accumulation of DNA mutations, decay of cellular and organ structures, and changes in gene expression [1]. Both differentiation of tissues, and ageing effects are at least partially caused by chemical modifications of the genome, such as DNA methylation.
Monozygotic (MZ) twins form an attractive model to study methylation changes with age. At the time of separation both embryos have nearly identical methylation patterns. While certain methylation changes are genetically controlled, environmental exposure and stochastic processes can lead to a change in methylation patterns. In this context, identical twins can be considered replicates of the same developmental and ageing experiment.
Several studies have investigated the epigenetic state of a small number of selected genes or CpG islands in subjects of varying age [2] or have measured the global changes in DNA methylation with increasing age [3]. Recently, unbiased genomewide studies have documented age effects on DNA methylation in cultured cells [4], mice [5], and humans [6], [7], [8]. Most of these reports' subjects were of a limited age range, and the continuity of the age related changes has been unclear. Therefore, estimating the age of a biological sample based on methylation values has not been possible.
[This paper, reporting results that the authors bumped into something quite different that they were looking for, stands out in significance far beyond what the authors claim in their PLOS paper. Their claim is focused on the predictability of "biological age". This is very noteworthy, but pales in comparison with the modern and now clinched fact that the genome is NOT "static", but changes (as its function is regulated in a recursive manner, see book below and references to two reversed axioms of genome informatics). Monitoring the "aging process" - that is rendering auxiliary information unreadable upon perusal in recursion, is a physiological process; now proven by this experimental finding. However, the pattern of change of methylation, as e.g. shown in Google Tech YouTube can also be pathological (e.g. cancerous) - thus the Genome (mis)Regulation by Fractal Iterative Recursion, a technology IP of HolGenTech, Inc. is now even firmer on experimentally verified ground. This entry can be discussed on the FaceBook page of Andras Pellionisz]
What the new field of epigenetics reveals about how DNA really works.
By Christine Kenneally
Posted Monday, June 20, 2011, at 9:52 AM ET
There are almost as many metaphors for genes as there are genes. One of the most familiar, and the hardest to let go of, is the tidy blueprint, at once reassuringly clear and oppressively deterministic: Our genome is the architectural plan for who we are. It tells our body how to build itself, setting our height, our health, and even our moods since before we are born. Small wonder that we imagine if we can read our genome, we will discover not just the truth of ourselves but perhaps our future, too. Remember the high hopes that spurred on the Human Genome Project in the 1990s? Though the genetic catalog is now largely complete, we still await many of the anticipated insights, and in Epigenetics: The Ultimate Mystery of Inheritance, Richard Francis, a writer with a biology Ph.D., traces the emergence of a different genetic paradigm. Our DNA shapes who we are, Francis reports from the research forefront, but it is far from a static plan or an inflexible oracle; DNA gets shaped, too. For good or ill, the forces that determine our fate can't be captured by anything so neat as a blueprint.
Francis's primer introduces a new field, whose roots predate the rise of pure genetic determinism. How is DNA itself shaped? The search for answers begins in the late-19th-century work of scientists such as Hans Driesch, whose study of sea urchin embryos revealed that the cell plays a key administrative role in an organism's development. He discovered that if you take cells from one location in the embryo—the area that will become, say, the spines--and plant them in another—the mouth area--their function changes: You don't get spines growing out of the mouth, you get a normal mouth. A cell's identity doesn't arise from a preordained genetic recipe inside it. Crucially, it is the cues that a cell gets from neighboring cells that affect how the genes inside it behave.
Epigenetics has taken its cue from this process, and sets out to explore not just how cells control the genes inside them but also how altered genes are passed on when cells reproduce—both within an organism's lifetime and, more fantastically, across generations. If you detect another historical antecedent, you're right. Looming over this new field is the once-derided Lamarck, who proposed in the 18th century that if a giraffe, for example, consistently stretches its neck to reach leaves, its children will be born with longer necks. Lamarck's ideas about how traits are acquired and passed down were mostly wrong. But the basic notion that an event in a parent's life can sculpt fundamental traits in a child, once consigned to the dustbin of biology, has been revived. The epigenetic quest is to discover how chemical attachments to genes shape the fate of an animal by altering the genes' long-term expression.
If cellular regulation of genetic expression sounds complicated, it is, which is one reason—aside from our allegiance to the idea of some foreordained pattern to our lives—the epigenetic field has been slow to develop. The research that has been accumulating for decades upends the conception of "controller" genes that are either "on" or "off." Francis is a thorough guide to the many ways in which personality and health can play out through our genes but not be coded for in DNA. He proceeds step-by-step. After all, this is unsettling terrain: The notion of environmental forces that can be genetically determining does not fit our deeply etched nature vs. nurture categories. Francis begins by explaining what he calls "garden variety," or short term—rather than epigenetic—gene regulation, by way of androgens, like testosterone. This happens in normal development, but also in abnormal situations, such as when athletes abuse steroids. Where normal testosterone changes gene expression, extra testosterone causes a frantically altered gene expression, which leads to strong muscles, shrunken testes, and out-of-control aggression. The changes are direct. You take the steroids, they affect some of the cells in your body, the gene activity inside those cells changes, and then your body changes. The changes in garden-variety gene regulation end with the affected cells, and with you. When cells divide they do not pass along the abnormal genetic activation. The children of a steroid abuser inherit their parent's genes, but they do not inherit the synthetic steroid-induced changes to gene expression.
But gene expression doesn't change merely when you put chemicals in your body. The connections between people may shape it, too. In the 1990s, scientists began to explore how social status can influence biology. In one kind of African cichlid fish, for example, the males are either "territory-owning" tough guys who have vividly bright colors, huge testes, larger neurons, and lots of testosterone. Or they are nonterritorial and much less striking. The low-testosterone males do not get to breed. Scientists discovered they could manipulate the social status of fish, their testosterone level and all the hoopla that accompanies it, by changing only the fish's "friends." If they put big, territorial fish in a tank with much bigger, territorial males, the former-breeders lost color, their testes and neurons shrank, and they literally transformed into nondominant fish. When they put nonterritorial wallflowers in a tank with females and smaller males, they too were transformed, but in the other direction. As Francis points out, we obviously can't run this kind of experiment with humans. It nevertheless shows how context can change the way genes work.
Changes that arise from normal gene regulation happen in the short term, but epigenetic changes alter the way that genes react to the world for a very long time—even when the original cause has vanished. It is this rather shocking long-term influence that makes epigenetics one of most alluring—and terrifying—shifts in how we think about our genes. Epigenetic changes can occur in adulthood, in childhood, even in utero (a phenomenon explained in Origins by Annie Murphy Paul), with the consequence that an event you experienced as a child could dictate the ways your genes behave in a different situation as an adult. It may have been simple-minded to assume that we are programmed by our genes, but there was a weird egalitarianism in that: Even if we get different genes to begin with, we are under their sway in the same way. Epigenetic change means that not only do we start out as unwitting participants in a genetic lottery, but environmental forces we cannot see or control can mess with our genetic hardware and change our destiny. At the level of DNA, epigenetic change occurs when particular chemicals become attached to the gene, and stay there, altering how the gene behaves. The first of these attachments to be discovered, and still the best known, is from the methyl group. In 1980, it was shown that different degrees of methylation can alter gene expression in different ways. Demethylation can cause problems, too. Depending on the genes involved, one consequence can be unconstrained cell division, otherwise known as cancer.
The causes of epigenetic attachments are various, and the evidence so far indicates they range from pollution to stressful social interactions. Studies on the long-term effects of a pregnant woman's poor nutrition suggest that the food our mothers eat while we are in the womb can shape our gene expression. So, too, the food they don't eat. The best data on long-term genetic change come from the terrible Dutch famine of 1944, when the Nazis blockaded food supplies, disrupted transport, and flooded farmlands in western Holland. It has emerged as the classic case study in the field, thanks to the exemplary record-keeping of the Dutch, which gives researchers solid longitudinal data on the famine's many far-reaching effects. For children who were in utero at the time of the famine, the consequences include a higher risk of schizophrenia, antisocial personality disorder and other psychological disturbances, and even 50 years down the road, a greater likelihood of becoming obese. At first glance it may seem that the legacy is poor health in general. But that's not how it works. The impact depends on exactly when the fetus was exposed to the famine, Francis reports. Women whose mothers suffered the famine in the first trimester have a higher risk of breast cancer. Those whose mothers suffered in the second trimester have problems with lungs and kidneys.
The first person to realize what a data trove the Dutch records were was Clement Smith, a U.S. doctor who was flown to the Netherlands in 1945 to help. He found that children born during the famine were much smaller than those born before. Numerous teams have revisited the data, which have been updated during the decades since, and they have discovered many ways the famine is still playing out in the lives of Dutch people, even those who weren't born at the time. The studies became epigenetic 20 years ago, when scientists began to look for altered genes in famine survivors to see whether changed DNA explains the ways in which the survivors differ.
In 2009, one team unearthed a tantalizing result: Examining the blood cells of adults who were in the womb at the time of the famine, researchers discovered unusual epigenetic attachments on the gene that codes for a hormone called insulin-like growth factor 2. The hormone is crucial for growth, particularly in fetuses. It turns out the IGF2 gene of the famine group is methylated to a different degree than the same gene in a non-famine group. Even though scientists haven't yet traced the specific causal chain between the epigenetic attachments, the genes, and people's lives, those attachments are a smoking gun for epigenetic change in the womb, and health issues many decades later.
Even more fascinating, and unnerving, it appears that the consequences of epigenetic change may stretch over several lifetimes. In one Swedish village, which also has records of crop harvests that go back hundreds of years, the paternal grandsons of men who experienced famine were less likely to have cardiovascular disease than their peers whose paternal grandfathers did not experience famine. But, wait, conventional wisdom says only genes are supposed to be passed on to the next generation. Most epigenetic attachments are stripped away from genes in the creation of sperm and egg cells. Yet it seems that a record of some epigenetic attachments is passed on and then recreated in the genome of the embryo, too. That means that an event in your parent's life that occurred before you were conceived could affect how your genes work today. In other words, the sins of the fathers may be visited on the deoxyribose nucleic acids of the sons. How malleable are our sons and daughters? The mechanisms involved are extraordinarily subtle. Researchers are now only beginning to understand how and why this happens.
It's almost enough to make one nostalgic for the simplicity of old-style genetic determinism, which at least offered the sense that the genetic hand you were dealt at birth was the same one you would play your whole life—except that epigeneticists hold out the promise that the blessings of a single life, too, can be passed on. Disease researchers, Francis reports, have hopes that the effects of abnormal epigenesis may be reversed. For example, it's possible that the damage caused by many cancers is epigenetic. If those epigenetic attachments can be altered, then it's possible the cancer can be stopped. Still, even if we are discovering that an extraordinary range of conditions may be epigenetic, not all of them are. There are still specific diseases that follow a deterministic path. If you are unlucky enough to draw the Huntington's mutation in the genetic shuffle, you will develop the disease. Francis rightly emphasizes the wonder of epigenetics and the molecular rigor it brings to the idea that life is a creative process not preordained by our genome any more than it is preordained by God. Yet even as epigenetic research invites dreams of mastery—self-creation through environmental manipulation—it also underscores our malleability. There is no easy metaphor for this combination. But if we must have one, we should at least start with the cell, not the gene. The genome is no blueprint, but maybe the cell is a construction site, dynamic, changeable, and complicated. Genes are building materials that are shaped by the cell, and they in turn create materials used in the cell. Because the action at the site is ongoing, a small aberration can have a small effect, or it can cascade through the system, which may get stuck. Recall that your body is a moving collection of these building sites, piled in a relatively orderly way on top of another. Malleability? It's an ongoing dance with chaos, but, incredibly, it works.
[Epigenomics, working together with Genomics [hence called HoloGenomics] was exposed in the peer-reviewed science paper The Principle of Recursive Genome Function , invoking "fractal iterative recursion" that is called by Francis "cascading through the system", "dance with chaos" - which nonlinear dynamics (chaos and fractals being the two sides of the same coin) are demonstrably working in complex systems of biology. The concept by reversing two mistaken axioms that blocked progress for over half a Century were also popularized in Google Tech Talk YouTube, both in 2008. - This entry may be discussed in the FaceBook page of Andras Pellionisz]
Cells may stray from 'central dogma'
Published online 19 May 2011 | Nature | doi:10.1038/news.2011.304
Erika Check Hayden
The ability to edit RNA to produce 'new' protein-coding sequences could be widespread in human cells.
[Crick's own handwritten "Dogma" ruled 1956-2008 - see website, peer-reviewed science paper, Google Tech Talk YouTube - AJP]
All science students learn the 'central dogma' of molecular biology: that the sequence of bases encoded in DNA determines the sequence of amino acids that makes up the corresponding proteins. But now researchers suggest that human cells may complicate this tidy picture by making many proteins that do not match their underlying DNA sequences.
In work published today in Science1, Vivian Cheung at the University of Pennsylvania in Philadelphia and her team report that they have found more than 10,000 places where the base (A, C, G or U) in a cell's RNA messages is not the one expected from the DNA sequences used to make the RNA read-out. When some of these 'mismatched' RNAs were subsequently translated into proteins, the latter reflected the 'incorrect' RNA sequences rather than that of the underlying DNA.
It was already known that some cells 'edit' RNA after it has been produced to give a new coding sequence, but the new work suggests that such editing occurs much more often in human cells than anyone had realized, and that hitherto unknown editing mechanisms must be involved to produce some of the changes observed. If the finding is confirmed by other investigators — and some scientists already say they see the same phenomenon in their own data — it could change biologists' understanding of the cell and alter the way researchers study genetic contribution to disease.
Editing the central dogma
"The central dogma says that there is faithful transcription of DNA into RNA. This challenges that idea on a much larger scale than was known," says Chris Gunter, director of research affairs at the HudsonAlpha Institute for Biotechnology in Huntsville, Alabama.
The work suggests that RNA editing is providing a previously unappreciated source of human genetic diversity that could affect, for instance, how vulnerable different people are to disease.
Cheung does not know whether there are heritable changes, passed down from parent to child, that affect how much RNA editing occurs in different people. But scientists already know of a handful of RNA editing proteins that play a role in human health, such as the APOBEC enzymes, some of which have antiviral activity. Researchers investigating the connection between genetics and disease have been stymied by their inability to find strong connections between genetic variation and risk for most common diseases, leading researchers to wonder where the 'missing heritability' is hiding. The new study at least provides one place to look.
"These events could explain some of the 'missing heritability' because they are not present in everyone and therefore introduce a source of genetic variation which was previously unaccounted for," says Gunter.
Living with error
But because they do not know what mechanism might be responsible, most scientists contacted by Nature remained cautious about the significance of the finding and its possible impact on biology. Some say it is possible that technical errors could have caused the results. For instance, high-throughput sequencing machines can make systematic errors in DNA and RNA sequencing experiments.
And even if the findings hold up, it is still too early to know whether 'mismatching' plays an important role in human biology or not.
"The devil is in the details — to determine if the results are caused by some unintended technical or computational flaw or are correctly describing a biological phenomenon," says Thomas Gingeras at the Cold Spring Harbor Laboratory in New York. "Assuming the latter, I would be encouraged to look at our own large data sets to see if we see similar phenomenona."
Other researchers, such as Manolis Dermitzakis at the University of Geneva in Switzerland, say they are seeing the phenomenon in their data. Indeed, Cheung's team drew in part on data generated by the 1000 Genomes project, of which Dermitzakis is a member. However, Dermitzakis says it is still unclear how important the phenomenon is for disease susceptibility.
Cheung's group attempts to address many of these concerns, some of which were raised when the preliminary work was presented last November (see 'DNA sequence may be lost in translation') at the annual meeting of the American Society for Human Genetics, in Washington DC. Since then, the team has been looking for possible errors that could have caused the results.
For example, the researchers first observed DNA–RNA 'mismatches' in data generated by next-generation sequencing technologies in the International HapMap Project and the 1000 Genomes project. They have now confirmed some of the putative DNA-to-RNA changes using traditional Sanger sequencing, and have found the same changes in different people, across different cell types, and reflected in proteins.
Cheung says that at first "we truly did not believe it". But after performing the additional experiments "we cannot explain this by any obvious technical errors, so we are pretty convinced that this is real," she says.
Researchers who study RNA editing, which up to now was known mostly from plants and some unicellular human parasites, are intrigued by the new finding.
Kazuko Nishikura of the Wistar institute in Philadelphia says she was sceptical at first, because some of the base changes could not be explained by previously identified mechanisms. But she was convinced once she saw Cheung's data.
"It's really exciting, because this study reports a different variety of RNA editing that is much more widespread than existing mechanisms," Nishikura says.
Comment: (Andras Pellionisz)
It is a pitiful fact that “All science students learn the ‘central dogma’ of molecular biology” as if science were based on “Dogma”. To the contrary, science is based on facts explained not by negative pontification but by predictive theories that can be experimentally verified or refuted, and updated as required by new facts. Certain particularly crass pseudo-scientists (hiding their heads in the sandbox of “Dogmatic Ideologies”), when confronted with a new theory, like “The Principle of Recursive Genome Function” (peer-reviewed science paper, popularized by the “Google Tech Talk YouTube”, both in 2008) claim ignorance of the cardinal issues, behind their shield of incompetence in information theory. It is too bad (for them), since the “Battelle Study”: identified old school biochemistry-based Genomics turned into new school information-theory based Genomics. Indeed, an $796 Bn economical impact just in the USA is unsustainable without software-enabling algorithmic approaches to genome function, particularly of genome (mis)regulation. Regarding both “Junk DNA” the historical challenge is not the endurance-game of some provincial ideologies but the vital need to stop ignoring the informatics of “Junk DNA diseases”, most notably cancers. Regarding “Central Dogma” it must be superseded by the science of e.g. fractal iterative recursion, where every event is, by definition, a function of preceding events. As Ms. Hayden so aptly pointed out elsewhere, the result appears complex, but its underlying mathematics (when understood) is lucid; “There is nothing simpler than a problem solved” – Faraday. The Battelle Study also identifies our times as the most important scientific-technological paradigm-shifts, ever. Therefore, those whom the Study refers to as “retards”, in any “lucid heresy” they only note the latter part – new understanding does not illuminate them, rather, it irritates their die-hard habits.
The fractal globule as a model of chromatin architecture in the cell
Leonid A. Mirny
Harvard-MIT Division of Health Sciences and Technology, and Department of Physics, Massachusetts Institute of Technology, Cambridge, MA USA
Chromosome Res. 2011 January; 19(1): 37-51.
Published online 2011 January 28. doi: 10.1007/s10577-010-9177-0.
The fractal globule is a compact polymer state that emerges during polymer condensation as a result of topological constraints which prevent one region of the chain from passing across another one. This long-lived intermediate state was introduced in 1988 (Grosberg et al. 1988) and has not been observed in experiments or simulations until recently (Lieberman-Aiden et al. 2009). Recent characterization of human chromatin using a novel chromosome conformational capture technique brought the fractal globule into the spotlight as a structural model of human chromosome on the scale of up to 10 Mb (Lieberman-Aiden et al. 2009). Here, we present the concept of the fractal globule, comparing it to other states of a polymer and focusing on its properties relevant for the biophysics of chromatin. We then discuss properties of the fractal globule that make it an attractive model for chromatin organization inside a cell. Next, we connect the fractal globule to recent studies that emphasize topological constraints as a primary factor driving formation of chromosomal territories. We discuss how theoretical predictions, made on the basis of the fractal globule model, can be tested experimentally. Finally, we discuss whether fractal globule architecture can be relevant for chromatin packing in other organisms such as yeast and bacteria.
The Principle of Recursive Genome Function: Quantum Biophysical Semeiotics clinical and experimental evidences
Sergio Stagnaro and Simone Caramel
May 8th, 2011
Conclusions: In this paper we have shown that Quantum Biophysical Semeiotics clinical and experimental evidences are consistent with and fully confirm the Principle of Recursive Genome Function. We can argue that the genetic alteration of the mit-DNA is reversible, generally not for a lack or impairment of genes, but for qualitative information imperfections in genes networking which lead to the activation of inappropriate genes or to inefficient configurations, defective or missing in some cases. Similarly, in microvessels there are communication obstructions which slow down the communication itself (blood flow) from structural and functional point of view. In parallel, it may be assumed that the alteration of the mit-DNA is reversible, during lifetime, and not just in overlapping generations, not for the fact that we create new genes from scratch, or because we are able to repair single genes in some way in a patient (as in genetic determinism), but because we intervene holistically on the whole, .. so that a proper and customized release of 'information' gives resonance to a virtuous feedback mechanism between DNA, RNA and downstream structures (tissues, cells, proteins, mithocondria,..) and vice versa, restoring physiological DNA dynamics...
The Myth of Junk DNA - an issue fallen from science in 2006 to a rejected ideology for the masses to chew on as an Amazon bestseller
This review is from: The Myth of Junk DNA (Paperback)
In recent years, a number of leading boosters of Neo-Darwinism have claimed that much of our genome is filled with functionless "junk DNA… But what if so-called "junk DNA" is not junk at all? In this meticulously documented book, molecular biologist Jonathan Wells … presents a growing flood of research that is showing the widespread functionality of DNA previously dismissed by leading Darwinists as little more than genetic garbage. For non-scientists, some of the detail provided here may be tough-sledding. But Wells does his best to make things clear even for those who may not have a detailed understanding of modern genetics, and his book includes a helpful glossary of key terms as well as 17 black and white illustrations. Chapter 9 provides a useful (and understandable!) summary of the case for functionality in "junk DNA." For scientifically-inclined readers, Wells' careful distillation in Chapters 3-8 of hundreds of recent journal articles documenting various functions for so-called "junk DNA" will be extremely valuable.
This review is from: The Myth of Junk DNA (Paperback)
… this book is a gold mine for anyone interested in the junk DNA issue and, indeed, the whole genetics field. The references (page 114 to page 159) alone are worth the price of the 173 page book (I paid 9.95 from Amazon). This readable well-documented tome included a glossary for those not in the field to insure that the book was assessable to every educated adult. In the last decade more and more research has supported the conclusion that much, if not most, of the so-called junk DNA has an important, if not a critical, function and I predict that this trend will continue for some time. Darwinism turned out to be a science stopper in this case. Instead of concluding the DNA that has no known function is junk, as was common, researchers should have been asking what does it do, the same question that would have saved us a lot of grief when Darwinists labeled organs that it was not known what their function was as vestigial (meaning then that they were evolutionary leftovers from the past without a function)
This review is from: The Myth of Junk DNA (Paperback)
As exploration began to reveal the full extent of the human genome in the 1970s, it was discovered, much to the shock of early researchers, that only a small portion of our DNA served explicitly to fold proteins. What did the rest of it do? More than a few researchers proposed that most of our genome was "junk," relics of an evolutionary past that served no current function. Despite the caution of some geneticists, who wisely suggested that junk DNA was merely a category representing the limits of our understanding, several self proclaimed spokesmen for science pounced on the idea that junk DNA was in fact proof that popular alternatives to Darwinian evolution were simply wrong… Much of what was originally thought to be "junk" in fact serves a purpose.
The bulk of Well's latest book is a summation of hundreds of articles dealing with the non protein coding portions of DNA. Indeed, the small print endnotes to the book make up more than a quarter of its total pages. But in general, Wells finds two lines of evidence that these DNA sequences are indeed functional. The first is that these sequences are ultra conserved, both in humans and other animals. If they were truly non-functional, we would expect that they would gradually deteriorate and be subject to a greater number of mutations than the DNA which we know to be functional. But in fact, this is not the case. This line of evidence, of course, is indirect. But a more direct line of evidence is found in the number of positive functions that have been uncovered. Apparently repetitive sequences of DNA, for example, serve to deactivate one of the two X chromosomes in female mammals to promote healthy development. Other functions, including RNA coding, are common.
Taken as a whole, this book is a useful summary of the current literature…. But there is another sense in which the story of "Junk DNA" (or rather, the story of how it was widely accepted and then gradually rejected) is in fact devastating to the Darwinian paradigm. Junk DNA was an important "proof" for many defenders of "science" that evolution was "true." And yet, one of the main arguments against the whole concept of junk DNA is that it is not compatible with what we know of natural selection. In other words, Darwinian evolution is at once proved both by the presence and absence of junk DNA. And given that is the case, falsifying Darwinian evolution is nearly inconceivable. In the final analysis, real science can be falsified, but ideologies cannot.
This review is from: The Myth of Junk DNA (Paperback)
This is a scholarly and impeccable book that takes a cogent case against the contemporary Darwinian story of intergenic sequences and conveys it on a level for the general peruser.
["So much 'Junk DNA' in our Genome" (see full facsimile of the 4.5 page science talk by Dr. Ohno, 1972) intended not as a metphor but a fully serious science issue was branded as "a suspect way to arrive at 1% figures of structural utility to 99% junk" (see first person Boyer to rise immediately after the utterance of the nonsense - ibid). The misnomer was discarded as a science issue by the first international organization of scientists, International PostGenetics Society in 2006, October 16, eight months before the US government released the devastating ENCODE results in 2007). Simply put, those who know anything about informatics realize that 1.3% of "about half the information of Windows 7" (indeed, a fraction of it, as amino-acid-coding exons are a small part of what used to be "genes") is simply an insufficient amount of information to build e.g. a human (a stamp-sized gif picture contains about that tiny amount of information). View Google Tech Talk YouTube of the triple Ph.D. Pellionisz or read his peer-reviewed science paper The Principle of Recursive Genome Function (both in 2008, laying down fractal iterative recursion as truly cracking the compressed code of full DNA, once proponents of "Junk DNA" and "Central Dogma" passed away, and even the US Government released the public admission ENCODE results in 2007). Contrary to earlier quotes, as of today all leading scientists, (Let us just list 7) Drs. Watson, Venter, Hood, Lander, Collins, Church, Schadt all agree that the classic notions are not only "frighteningly unsophisticated" (Venter), but have been outright "wrong" (see Lander telling NIH with all leaders present at the 10th Anniversary of the Human Genome Project, the Science Advisor to the President endorsing fractal approach). Others, notably name-caller ideologues, of course, can carry on with their pseudo-scientific propaganda forever, one full of junk just having been congratulated on his birthday of retirement-age as an epitome of a generation of ideologues "who led science nowhere". - This entry can be discussed on the FaceBook page of Andras Pellionisz]
Eric Schadt Joins Mount Sinai Medical School [Dir. of Inst. of Genomics AND Multiscale Biology]
May 16, 2011, 10:03 AM
Schadt Joins Mount Sinai Medical School
By ANDREW POLLACK
[Schadt' "The New Biology" is fractal-like "Multiscale" - AJP]
With his boundless energy and unvarying outfit of shorts, sandals and a white polo shirt, Eric E. Schadt, the chief scientific officer of DNA sequencer manufacturer Pacific Biosciences, is considered a brilliant rebel in the field of genomics.
Now Dr. Schadt is about to take on a new role – as chairman of genetics at the Mount Sinai School of Medicine in New York as well as chief of an institute there designed to study complex biology and apply it to medical treatments.
Dr. Schadt will retain his position at Pacific Biosciences, which is based in Menlo Park, Calif., but will clearly be spending less time there now.
Pacific Biosciences said it would collaborate with Mt. Sinai on the institute that Dr. Schadt will run, known as the Institute for Genomics and Multiscale Biology.
Dr. Dennis S. Charney, dean of the school of medicine, said in an interview that Dr. Schadt could make Mt. Sinai, “among the leaders in making genetics a key part of the way medicine is practiced.’’
The collaboration with Pacific Biosciences is “a value added,’’ Dr. Charney said. He said the genomics institute would receive about $100 million over five to six years.
Under the collaboration, Pacific Biosciences will supply the institute with two prototype machines that can be used for DNA sequencing as well as for analysis of other biological molecules, such as RNA. Mt. Sinai is also expected to buy at least one of the standard $695,000 DNA sequencers that Pacific Biosciences has just started shipping.
Dr. Schadt said the new effort will allow him and Pacific Biosciences to be “embedded’’ in a medical institution to apply sequencing findings to medicine. “They have clinical data that can be provided instantly’’ from patient medical records, he said.
Hugh Martin, chief executive of Pacific Biosciences, said the company had been looking for a big academic collaboration.
Dr. Schadt is a leading proponent of the view that focusing on individual genes might not be the way to treat diseases or discover drugs. Rather, researchers should focus on complex networks of interactions between genes and other parts of an organism. Such complex networks can be understood best by simulating them on computers.
He spent much of his career at Rosetta Inpharmatics, a genomics company acquired by Merck. He is also co-founder of Sage Bionetworks, a nonprofit organization that seeks to apply the complex network philosophy to understanding diseases. He has been profiled, among other places, in The New York Times and in Esquire.
May 16, 2011
Genomeweb
As our sister publication GenomeWeb Daily News reports, Pacific Biosciences' Chief Scientific Officer Eric Schadt will lead the Mount Sinai Institute of Genomics and Multiscale Biology. As part of the collaboration between PacBio and Mount Sinai, GWDN continues, "a Single Molecule Real Time Biology User Facility will be established within the institute, which is the hub of genomics research at Mount Sinai and collaborates with 13 other disease-oriented and core technology-based institutes at Mount Sinai." Luke Timmerman at Xconomy San Francisco adds that the "union of PacBio and [Mount] Sinai is a high-profile effort to bridge the traditional divide between lab research and clinical treatment of patients," saying that both parties are likely to benefit:
For Mt. Sinai, hiring a star like Schadt means it will likely attract more donations, and be able to recruit many more bright young physicians and scientists interested in genomic-based personalized medicine. For PacBio, it hopes to learn how to best position its instrument with customers around the world, after hearing from Schadt how it works in the trenches.
Timmerman also says that, by joining Mount Sinai, "Schadt and PacBio are walking away from a potential partnership with UC-San Francisco, which had been wooing Schadt for months," and that this move raises questions as to the future of the New York Genome Center, "a fledgling effort to bring together a number of New York's top biomedical research centers to create a shared world-class genomics research facility," which, he adds, is still its planning phases.
COMMENTS:
Submitted by andras on Tue, 05/17/2011 - 01:24.
Kudos to Eric, who is now also the Chairman of the Mount Sinai Institute of Genomics AND Multiscale Biology. The CSO of sequencer PacBio, he is a brilliant rebel, a proponent that focusing on individual genes is not the way to treat diseases or discover drugs. In the paradigm shift of the "genome revolution" documented by the Battelle Study as the most disruptive economic singularity of science and technology ever, already the size of beyond the GDP of Brazil, about the same as the GDP of Russia and just slightly smaller than the GDP of India, rebels are becoming acknowledged leaders. "Multiscale" is a quantum leap towards "scale free" fractals. It is particularly nice to see that "New York's gain is NOT Silicon Valley's loss! - Andras Pellionisz
[It is remarkable that though Eric's "The New Biology" video, from which the illustration is clipped, was uploaded by PacBio as "Systems Biology" (that is clearly not new, Ludwig von Bertalanffy used the term first in 1928). In order to better define the unquestionable mathematical system lurking behind the "complexity" ("complexity is in the eye of the bewildered") Eric Schadt's new $100 M institute is called "Multiscale Biology" - a quantum leep towards the Fractal Approach such as FractoGene (2002), identifying the intrinsic mathematics of the genome-epigenome (hologenome) system, and thus emerging as algorithmic genome interpretation, where e.g. the "before and after" cancer therapy structural variants can be neatly separated to (harmless) "human diversity" parametric differences, and (harmful) "fractal defects" that are syntax-errors, the genome violating its own mathematical rules, leading to disregulated (cancerous) growth; see Principle of Recursive Genome Function science paper and its popularization Google Tech Talk YouTube, 2008. This entry can be commented in the FaceBook page of Andras Pellionisz]
Battelle Study: The $796 Bn Economic Impact of the Human Genome Project
[.pdf of full 58-page Battelle Study - AJP]
[First an idea what $796 Bn is. It is larger than the 2010 GDP - Gross Domestic Product - of the Continent-size Brazil. It is about the same as the GDP of Russia, and just a little bit smaller than the full GDP of India - AJP]
Excerpts [AJP]
Introduction
The sequencing of the human genome represented the largest single undertaking in the history of biological science and stands as a signature scientific achievement. All of history in the making, human DNA took just 13 years to sequence under the Human Genome Project (HGP), an international public project led by the United States, and a complementary private program.[Myth #1 may be, that "the government did it all" - as we know, it was an official "tie" between the government and public sector; by now at both ends of Sequencing Companies and Genome Computers the USA private sector rules - AJP]. Sequencing the human genome—determining the complete sequence of the 3 billion DNA base pairs and identifying each human gene—required advanced technology development and the assembly of an interdisciplinary team of biologists, physicists, chemists, computer scientists, mathematicians and engineers... the knowledge of genome structure, and the data resulting from the HGP as the foundation for fundamental advancements in medicine and science with the goals of preventing, diagnosing, and treating human disease. Also, while foundational to the understanding of human biological systems, the knowledge and advancements embodied in the human genome sequencing, and the sequencing of model organisms, are useful beyond human biomedical sciences.
The resulting “genomic revolution” is influencing renewable energy development, industrial biotechnology, agricultural biosciences, veterinary sciences, environmental science, forensic science and homeland security, and advanced studies in zoology, ecology, anthropology and other disciplines.
In the ten years since the first sequences were published, much has been written about the scientific consequences of mapping the genome but little analysis has been done of the economic significance of the achievement. [Myth #2 may be, that the Battelle Study is about the Science of PostGenetics. It is NOT. It fills the void of a comprehensive ECONOMIC study of its impact, already a historical turning-point, and "just the beginning" - AJP]
The technologies that have empowered genome sequencing range from the gene sequencers themselves, to sample preparation technologies, sample amplification technologies, and a range of analytical tools and technologies. An industry has grown up to supply the scientific research community in the private sector, government and academia with the equipment, supplies and services required to conduct genomics research and development (R&D) and associated product development. This industry, of course, generates additional economic impacts.
To evaluate these genomics-enabled industry impacts in the U.S., Battelle constructed a “from the ground-up” database of individual companies engaged within the sector. The employment of this industry base was used as the foundation for an input/output analysis to quantify the total impacts of these firms (in terms of direct and indirect output and employment and their multiplier effect). The results of the analysis show that—spurred by the original investment and technological development impetus of the human genome sequencing projects—a substantial economic sector has developed thereby benefiting the U.S. economy in terms of business volume, jobs, and personal income supporting American families. [Myth #3 may be, that the Battelle Study introduced "Genome-Based Economy". As the website of Genome Based Economy and the 2009 Churchill Club YouTube indicate, the First Chapter opened by the Nobel Prize in 1970 to Norman Borlaug for his "Green Revolution" - AJP]...
• Non-coding DNA, previously termed “junk DNA” because it was thought to be a relic of evolution with little biological function, was instead confirmed to have specific functionality in transcription and translational regulation of protein-coding—i.e., most of it is not junk at all, it is central to life functions. This finding alone supports the vision of undertaking whole genome sequencing, since prior to the HGP some detractors argued that the budget would be better spent simply studying known protein coding genes and ignoring the rest. Eric Lander points out that “it has reshaped our view of genome physiology, including the role of proteins-coding genes, non-coding RNAs and regulatory sequences. [Myth #4 may be, that the Battelle Study proved that "Junk DNA is anything but Junk". No, the "Junk DNA" misnomer and "Central Dogma" obsolete axioms have long died of a thousand wounds, and only lingered because "facts don't kill theories, only a better theory kills an obsolete one"; as the Gene/Junk "frighteningly unsophisticated" notion was superseded by The Principle of Recursive Genome Function, 2008. What the Batelle Study did prove, however, that "detractors" not only inflicted half a Century of delay in the progress of Genomics/Epigenomics (HoloGenomics) science (and documentable harm to scientists) - but also were directly responsible to huge economic losses; e.g. pursuing for decades "gene discovery" (of non-existent genes) at horrendous expense. The end result is a continuous decrease of the "predicted" 4 million, 140,000, 40,000, 30,000, 19,000 "genes", concluding that the very old-fashioned definition of "gene" became extinct - yielding room for FractoGene (2002) - AJP]
A. Basic Science and Knowledge Expansion Impacts
The sequencing of the human genome has resulted in a distinct paradigm shift in our understanding of the biology of humans, and indeed all organisms. As such, ipso facto the decoding of the human genome stands among the preeminent findings in the history of science.
[Myth #5 may be, that the Battelle Study is impeccable from a science viewpoint. It is NOT. Few leading scientists would disagree with the rock-solid statement that "by revealing - sequencing - of the genome, it was NOT "DECODED". Indeed, the Battelle Study is a rock-solid basis of a horrific scenario; that without an actual (mathematical) decoding of the meaning of revealed sequences a Russia-sized economic Titanic may hit an iceberg. The Battelle Study does provide a very strong hint, as follows: - AJP]
Sequencing the human genome made clear information sciences, mathematics and biological investigation are now inexorably intertwined. The sequencing of the genome was as much a mathematical and computational achievement as it was a biological one and has helped to give rise to new fields of biological science in “computational biology” and “systems biology”. It has been noted that “The revolutions that have been generated by the first draft of the Human Genome Project have barely been felt, but there is one profound change that has already occurred, and that is the realization that biology is fundamentally an information science.”
[Myth #6 may be, that the Battelle Study equates the new axiom that "genomics (not biology in general) is fundamentally an information science" with the improper statement that sequencing of the genome gave rise to "systems biology". The term Systems Biology was first used by Ludwig von Bertalanffy in 1928 and even his General System Theory book appeared in 1936, decades before HGP. While there is no question in anyone's mind that the Genome/Epigenome (HoloGenome) complex interactions constitute a "system", the absolutely critical challenge is the mathematical identification of what "system" do we face; how its complexity is reduced to the size of about half of Microsoft Windows 7. The Principle of Recursive Genome Function peer-reviewed paper and its popularization as Google Tech Talk YouTube (2008) defines the "system" mathematically as fractal iterative recursion; the name of the game is to come up with a more befitting algorithmic (software enabling) system-definition - AJP]
... Most common diseases, such as cancers, heart disease and psychiatric disorders are not homogeneous diseases, but differ dramatically across individual genomes from patient to patient...
[The profound implications of this simple sentence (on cancers, to be analyzed in detail separately), can be best documented by the Battelle Study directly quoting Thomas Kuhn, see below - AJP]
Thomas Kuhn first coined the term “paradigm shift” which is, by definition, a rather radical upheaval—a major movement of scientific knowledge and understanding to a new platform. Such movement occurs rarely and research leading to a paradigm shift should, therefore, be viewed as a momentous scientific achievement.
Thomas S. Kuhn. 1962. “The Structure of Scientific Revolutions.”
[Since this is my third paradigm-shift, I can make some comparisons of the Battelle Study with watershed events of the publication of two earlier Studies. I took part in pioneering the transition from ill-defined "Artificial Intelligence" (mistakenly claiming that we can create machine intelligence without the benefit of understanding the real, biological one). In that breakthrough the US defense-agency DARPA made the crucial difference by their DARPA-Study assessing the potential in Neural Nets - the science and technology providing "reverse engineering" e.g. how flying of birds with their cerebellum can be used to automatically land an F15 fighter on one wing. In my second paradigm-shift (when the tiny R&D defense project of connecting computers by email of system administrators became a Private Industry in 1994 by Jim Clark's Netscape and the ensuing Internet-boom exploded bigger and quicker than anyone imagined, the US Government's "Blue Book on Internet future" ("High Performance Computing & Communications: Toward a National Information Infrastructure" multi-agency report, completed in 1994) served as the key Study for the breakthrough. Now, with the Battelle Study on $796 Bn Genomics of the USA (developed from the seed of $3.8 Bn government investment with competing private investments) is the "eye opener" that literally overnight generates now a ripple-effect through all media. Genome-based Economy is the Next Big Thing already. This entry can be commented in the FaceBook page of Andras Pellionisz]
In an improbable corner of China, young scientists are rewriting the book on genome research [Newsweek]
Newsweek 2011/04/24
high-quality-dna
The world’s largest genome-mapping facility is in an unlikely corner of China. Hidden away in a gritty neighborhood in Shenzhen’s Yantian district, surrounded by truck-repair shops and scrap yards prowled by chickens, Beijing’s most ambitious biomedical project is housed in a former shoe factory.
But the modest gray exterior belies the state-of-the-art research inside. In immaculate, glass-walled and neon-lit rooms resembling intensive care units, rows of identical machines emit a busy hum. The Illumina HiSeq 2000 is a top-of-the-line genome-sequencing machine that carries a price tag of $500,000. There are 128 of them here, flanked by rows of similar high-tech equipment, making it possible for the Beijing Genomics Institute (BGI) to churn out more high quality DNA-sequence data than all U.S. academic facilities put together.
“Genes build the future,” announces a poster on the wall, and there is no doubt that China has set its eye on that future. This year, Forbes magazine estimated that the genomics market will reach $100 billion over the next decade, with scientists analyzing vast quantities of data to offer new ways to fight disease, feed the world, and harness microbes for industrial purposes. “The situation in genomics resembles the early days of the Internet,” says Harvard geneticist George Church, who advises BGI and a number of American genomics companies. “No one knows what will turn out to be the killer apps.” Companies such as Microsoft, Google, IBM, and Intel have already invested in genomics, seeing the field as an extension of their own businesses—data handling and management. “The big realization is that biology has become an information science,” says Dr. Yang Huanming, cofounder and president of BGI. “If we accept that [genomics] builds on the digitalization of life, then all kinds of genetic information potentially holds value.”
BGI didn’t always seem destined for success—or even survival. “The crazy guys” was how Chinese colleagues initially referred to the two founders, Huanming and director Wang Jian. Refused government support, they muscled their way into the international Human Genome Project, mapping out 1 percent of that celebrated first full sequence before tackling the rice-plant genome on their own, beating a well-funded international consortium, and suddenly finding political leverage. Yang and Wang used it to set up the research center, which is nominally nonprofit but carries out commercial activities in support of the research. With an annual grant of $3 million from the local government in exchange for moving to the shoe factory in 2007, BGI first grew modestly, generating income from fee-for-service sequencing and conducting molecular diagnostic tests for hospitals. A $1.5 billion loan from the Chinese Development Bank in 2009 allowed the company to catapult into a different league, and its combination of sequencing power and advanced DNA data-management solutions for the pharma industry are now drawing international attention. Last year, pharmaceutical giant Merck announced plans for a research collaboration with BGI, as the Chinese company’s revenue hit $150 million—revenue projected to triple this year. “I admire their passion and the willingness to take risks,” says Steven Hsu, a physicist at the University of Oregon, adding that “it permeates the organization.”
Others would like to see deeper scientific reflection tempering the monumental ambition. “A more philosophical and conceptual rather than just a technical approach to the genome is needed to foster great discovery,” says long-time collaborator Oluf Borbye Pedersen of the University of Copenhagen.
While other well-known genomics centers such as Boston’s Broad Institute concentrate more narrowly on human health, the Shenzhen scientists cover a broad biological spectrum. In one shiny lab, thousands of microbes are being scanned for genes that might serve useful industrial purposes, while in another human stem cells are being developed for clinical applications. Scientists have mapped the genomes of everything from cucumbers and 40 different strains of silk worms to the giant panda. They have also cataloged tens of thousands of genes of bacteria living in the human gut, and pieced together the genomic puzzle of an ancient human—an extinct paleo-Eskimo who lived in Greenland 4,500 years ago. While such academic prestige projects are geared toward publication in scientific journals, real-world experimentation is going on at a nearby farm where pigs are cloned to serve as disease models. And in Laos, scientists are testing genetically enhanced plants to feed China’s growing population. The institute has already amassed almost 250 potentially lucrative patents covering agricultural, industrial, and medical applications.
Satellite research centers have been set up or are underway in the U.S., Europe, Hong Kong, and four other locations in China, and the number of researchers at the main headquarters in Shenzhen has more than doubled during the past year and a half. The institute now employs almost 4,000 scientists and technicians—and is still expanding.
“I’ve seen it happen but sometimes even I can’t believe how fast we are moving,” says Luo Ruibang, a bioinformaticist, who at 23, fits perfectly within the company’s core demographic. The average age of the research staff is 26.
Li Yingrui, 24, directs the bioinformatics department and its 1,500 computer scientists. Having dropped out of college because it didn’t present enough of an intellectual challenge, he firmly believes in motivating young employees with wide-ranging freedom and responsibility. “They grow with the task and develop faster,” he says. One of his researchers is 18-year-old Zhao Bowen. While still in high school, Zhao joined the bioinformatics team for a summer project and blew everyone away with his problem-solving skills. After consulting with his parents, he took a full-time job as a researcher and finished school during his downtime. Fittingly, he now manages a project on the genetic basis of high IQ. His team is sampling 1,000 Chinese adults with an IQ higher than 145, comparing their genomes with those of an equal number of randomly picked control subjects. Zhao acknowledges that such projects linking intelligence with genes may be controversial but “more so elsewhere than in China,” he says, adding that several U.S. research groups have contacted him for collaboration. “Everybody is interested in intelligence,” he says.
A shoe factory becoming a genomics center, scientists replacing blue-collar workers—the Shenzhen research facility embodies the country’s economic and social ambitions. According to a 2010 report from Monitor Group, a management consulting firm based in Boston, China is “poised to become the global leader in life-science discovery and innovation within the next decade.”
The Chinese government will, by next year, have spent $124 billion since 2009 building hospitals and health-care centers. Such strategic investments have lured Chinese scientists back to China. So far, at least 80,000 Western-trained Ph.D.s have returned, the vast majority in the past five years. With the country on track to become the second-largest pharmaceuticals market next year, and the U.S. failing behind, afflicted by weak—and declining—government funding of basic science as well as anemic collaboration between private and public sectors, China could take the lead. As George Baeder, vice president of Monitor Group Asia, says, China “has the potential to create a more efficient model for discovering and developing new drugs,” a prediction echoed by Caroline Wagner, a science-policy specialist and professor at Pennsylvania State University, who argues in a forthcoming paper that the days of American leadership will soon be gone. “After more than half a century at the top spot, the U.S. will become one big player among several,” she says.
But, Wagner adds, “science is not a zero-sum game,” and as the pie gets bigger, so will the opportunities for collaboration. Yang, for his part, puts it simply: “Genomics is international,” he says. “We must collaborate to survive and develop.” Certainly, the scientists at his Shenzhen headquarters have their view on the world. The latest shipment of high-tech toys sits, still unpacked, on the floor; the stamp on the sides of the crates proclaiming: Made in the USA.
[This posting can be debated at the FaceBook site of Dr. Pellionisz. Suffice to note here, that the same Newsweek that in 2007 elected to publish in all its editions - except in the American edition - a brilliant article on the "Genome Revolution" ensuing publication of US-lead ENCODE, now laments on the fact that 80,000 returned to China with the best ideas and equipment and the US 4 years later is about to slip into the traditional role of "followership" that formerly China practiced, not us. I posted the article, and took steps to secure precious intellectual property. It may well be that the manpower will be provided by China, India, Korea and Japan. It is hard to resist meetings like Bio-IT in Shenzen, China, timed for former US "Independence Day", 4th of July, 2011]
Systems Biology 'Makes Sense of Life'
Genomeweb,
April 27, 2011
Systems Biology needs System Identification [e.g. Fractal System - AJP]
Researchers have made great strides in understanding biology by taking a reductionist approach and studying little bits of the "complex tapestry of life" at a time, says Scientific American's Christine Gorman. And until now, that's worked just fine, she says. But researchers increasingly find themselves butting up against the limits of this traditional approach, eventually realizing that they must embrace the complexity of life in order to really understand it, Gorman adds. Institute for Systems Biology co-founder Alan Aderem says a systems biology approach could allow researchers to produce vaccines that have been otherwise unachievable to date. In this video from Virginia Commonwealth University, researchers explain the systems biology approach and how it can be used to study disease.
Submitted by lermanmi on Wed, 04/27/2011 - 15:09.
Systems Biology was invented following the "omics revolution" and is a tool in the war for monies. No more. Like the omics it's totally devoid of ideas and is illusory and mystical. It is so "new" that I have not seen a textbook describing its principles and fundamental findings for students. However there are a lot of new paper and digital magazines titled with the word Systems...... (e.g. Systems Urology etc) Michael Lerman
Submitted by andras on Thu, 04/28/2011 - 03:27.
Nature can only be understood as interactive systems. Trajectories of planets, from a reductionist view focusing on the Earth, look needlessly overcomplicated - while a Galilean view of the planetary system (planets elliptically orbiting around the Sun) instantly reduces a seemingly maddening "complexity". We know by now that Genomics just would not work if viewed from a "frighteningly unsophisticated" perspective of "Genes/Junk". Rather, a holistic approach of uniting Genomics with Epigenomics, expressed in Informatics; HoloGenomics is needed to mathematically identify the (fractal) "system" that we face. FractoGene and The Principle of Recursive Genome Function, identifying the system as fractal iteration is not a vague "systems biology" approach, but is an algorithmic (and thus software-enabling) specification of fractal genome function, arising from the demonstrably fractal nature of the genomic code. All this was laid out in peer-reviwed science paper and popularized by Google Tech Talk YouTube in 2008 - and within the very short window of a mere three years have become the algorithmic inroad to beat - Pellionisz
["Systems theory is the transdisciplinary study of systems in general, with the goal of elucidating principles that can be applied to all types of systems in all fields of research. The term does not yet have a well-established, precise meaning, but systems theory can reasonably be considered a specialization of systems thinking and a generalization of systems science. The term originates from Bertalanffy's General System Theory (GST), 1968." (Wikipedia). As I commented to Genomeweb (above) the fashionable "New Frontier; Systems Biology" is highly welcome to the club of holistic approaches (see HoloGenomics, once the mistaken half a Century of old reductionalist Dogmas of JunkDNA/Genes/Central Dogma is finally written off). Dr. LeRoy Hood would probably not consider Systems Biology all that new, however, as he has pursued it at least since 2002 - about the same time when FractoGene arose in 2002, and we might add that "The term systems biology is thought to have been created by (my fellow Hungarian nobleman) Ludwig von Bertalanffy in 1928" (Wiki). With Systems Theory, the axiomatic challenge has always been the mathematical identification of what system do we face. From the viewpoint of Academics, one can argue back and forth, forever, but the crucial need to identify the system will not vanish. From the viewpoint of those suffering from genomic diseases (e.g. The Genome Disease, a.k.a. Cancer) this is question of extreme urgency - just as it was for another Hungarian, John von Neuman, to architect computers for the computing needs of World War II. For the present, War on Cancer, II. (the first waged by Nixon, $30 Bn - without the modern weaponry), now we have both practically any number of fully sequenced genomes (in repeat customer mode...) - and can leverage defense-validated High-Performance-Computers - assuming that e.g. a Fractal System Identification (or competing approaches) are algorithmic, i.e. software-enabling. - Pellionisz]
Virginia Tech partners with NVIDIA to “Compute the Cure” for Cancer
Virginia Tech professors have received research backing from the NVIDIA Foundation in the Silicon Valley to develop an analysis program that will help researchers identify cancer mutations. Here is a press release from Tech:
Virginia Tech researchers Wu Feng and David Mittelman have won the first worldwide research award from the NVIDIA Foundation, as part of its “Compute the Cure” program.
The award will enable them to develop a faster genome analysis platform that will make it easier for genomics researchers to identify mutations that are relevant to cancer.
This program is a pilot effort started by the NVIDIA Foundation, the philanthropic arm of the Silicon Valley-based technology firm NVIDIA. The company specializes in programmable graphics processing units (GPUs), which are used in everything from super phones to supercomputers. The Compute the Cure program has a strategic mission to leverage GPUs to support cancer researchers in the search for a cure, as well as promote cancer awareness and prevention initiatives for the greater good.
“Compute the Cure seeks to revolutionize the way that cancer biologists conduct their science by delivering a framework and toolkit of personal desktop supercomputing solutions for the analysis of genome changes from next-generation sequencing data, as a first step toward seeking a cure for cancer,” said Feng, associate professor in the Department of Computer Science and Bradley Department of Electrical and Computer Engineering in the College of Engineering at Virginia Tech. He is principal investigator on the project.
Co-investigator David Mittelman is an associate professor with the Virginia Bioinformatics Institute and the Department of Biological Sciences, part of the College of Science at Virginia Tech. Mittelman previously worked at the Human Genome Sequencing Center at Baylor College of Medicine in Houston. As the domain expert, Mittelman’s research program has explored the molecular basis for genome instability in mammalian systems and its role in diseases such as cancer. His lab also has developed sensitive methods for characterizing genome instability using next-generation whole-genome sequencing.
Using GPU-accelerated alignment and mapping software in combination with sensitive mutation detection methods, Feng and Mittelman will use the $100,000 Compute the Cure award to deliver an optimized and powerful solution for genome analysis to the research community that other investigators can build upon, to collaboratively advance the field of cancer genomics.
Feng first worked with NVIDIA in 2009, when he was one of 38 recipients worldwide to receive an NVIDIA Professor Partnership Award, designed to accelerate exploration at the frontiers of visual, parallel, and mobile computing. Feng’s Professor Partnership Award spurred his research in the parallelization and optimization of different algorithms in pairwise sequence alignment and short-read mapping onto the GPU. These are critical tasks towards understanding how genomes change during cancer.
Tonie Hansen, the director of the NVIDIA Foundation, said the tech firm’s interest in medical research always has been strong.
“NVIDIA’s Compute the Cure program combines our company’s technical focus and our people’s personal priorities,” she said. “Medical researchers the world over use GPU technology to accelerate the pace of their research. And NVIDIA employees donate generously each year to cancer research organizations, in support of a friend or family member who is fighting the disease. Compute the Cure combines these objectives into one comprehensive program.”
Breast cancer prognosis goes high tech [Fractal - AJP]
[Fractal lilly - even laypeople are aware of the fractality of cancer tumors - AJP]
Published: Monday, April 18, 2011 - 09:04 in Health & Medicine
Cancer researchers at the University of Calgary are investigating a new tool to use for the prognosis of breast cancer in patients. This new digital tool will help give patients a more accurate assessment of how abnormal and aggressive their cancer is and help doctors recommend the best treatment options. Currently, a useful factor for deciding the best treatment strategy for early-stage breast cancer is tumour grade, a score assigned by a pathologist based on how abnormal cancer cells from a patient tissue sample look under the microscope. However, tumour grade is somewhat subjective and can vary between pathologists. Hence, there is a need for more objective methods to assess cancer tissue, which could improve risk assessment and therapeutic decisions.
Using a mathematical computer program developed at the U of C , Mauro Tamabsco, PhD, and his team used fractal dimension analysis to quantitatively assess the degree of abnormality and aggressiveness of breast cancer tumours obtained through biopsy. Fractal analysis of images of breast tissue specimens provides a numeric description of tumour growth patterns as a continuous number between 1 and 2. This number, the fractal dimension, is an objective and reproducible measure of the complexity of the tissue architecture of the biopsy specimen. The higher the number, the more abnormal the tissue is.
According to the team's published study, this novel method of analysis is more accurate and objective than pathological grade. "This new technology is not meant to replace pathologists, but is just a new digital tool for them to use" says Tambasco, a medical physicist at the University of Calgary Faculty of Medicine and the Tom Baker Cancer Center.
Researchers say they will continue to study this new digital method and hope in the next few years that it could become another tool used in the clinical setting.
The retrospective study analysed tissue specimens from 379 breast cancer patients and the findings were published in the January 2011 edition of the Journal of Translational Medicine.
FractoGene (2002) and Fractal Frenzy set off by The Principle of Recursive Genome Function, YouTube (2008) [AJP]
[FractoGene 2002, (also USPTO, 2002 Aug. 1.) Pellionisz in CSHL 2009 September, Lander et al. 2009 October, Stein 2011]
“There is a growing gap between the generation of massively parallel sequencing output and the ability to process and analyze the resulting data” McPherson [Ontario Institute of Cancer Research]
“Chanock [See quotation from Article below, National Cancer Institute], also a medical doctor, cautions that the community should be realistic with regard to ... all this structural variation data to facilitate improvements in the clinic… "The plausibility and the meaning of this discovery is complex: each one of these regions requires its own study and it's still a work in progress to reach the level of confidence and validity that's needed to incorporate that into our clinical workflow. We have to be careful with all the ballyhooing about 'The genomic age is going to turn everything into Star Trek medicine,' because I find this dangerously naïve”
As seen above, YouTube Is IT Ready for the Dreaded DNA Data Deluge? 2008 clearly predicted both that "Information Technology will be all right" as well as that Information Theory of Genome Function needed not a cosmetic, but profound reform.
Now, three years later - there is a crisis in Cancer Research without Algorithmic breakthrough.
Conventional medicine has lost ground without algorithmic, software-enabling theory
It is also increasingly recognized by leaders, that Brute Force must be augmented by Genome Theory to resolve crisis:
Francis Collins; Scientists have to re-think long-held beliefs
Craig Venter: Our level of understanding the genome is frighteningly unsophisticated
George Church: Zero dollar sequencing and one million dollar interpretation
Eric Lander: Fundamental assumptions were all wrong
John Mattick: Dogmas are obsolete
Eric Schadt: Considers the fractal approach of AP [HolGenTech] “truly revolutionary”
From the Figs. quoted above, a "Fractal Frenzy" is evident since 2008, especially afer the Fractal Approach was also presented in Cold Spring Harbor (2009 September). Lander et al. published their Science cover article in 2009 October - and now a CSHL leader (though not on record with fractal papers) placates fractals as the ZeitGeist. The acceleration is also evident from the escalation of viewership of the 2008 YouTube, see above.
The Structural Struggle - [vs. Fractal Algorithmic Elegance - AJP]
Genomeweb
April 2011
By Matthew Dublin
The diverse world of structural genomic variation research — which includes investigations into copy number variation and mapping myriad inserted, deleted, inverted, and translocated genes — is undoubtedly providing investigators with an exciting and promising source of data on human diversity and disease susceptibility. [But the Ten Million Dollar question is the algorithm that sets the "human diversity" and "disease susceptibility" structural variations apart - AJP]. But if a Nature paper published by the 1,000 Genomes Project's Structural Variant group in February is any indication, eureka moments in this field may be a bit further off than researchers originally hoped. The report — which represents the culmination of roughly two years' work involving more than 50 investigators from across the world — describes the group's construction of a CNV map based on whole-genome sequencing data from 185 human genomes. It encompasses roughly 22,000 deletions and 6,000 insertions and tandem duplications. Using a genotyping approach that examined several partial- and whole-gene deletions, the researchers reported a depletion of gene disruptions among high-frequency deletions as well as differences in the size spectra of structural variants.
While the team produced a robust resource for future sequencing-based association studies, Charles Lee, the group's co-chair and director of Harvard Medical School's Molecular Genetic Research Unit, says the take-home message is that considerable barriers must still be overcome before the field can move forward. "We found that we needed new algorithms to identify structural variants and we ended up creating 19 different computer programs. No one program was sufficient — we had to combine multiple programs to maximize the amount of structural variation we are picking up," Lee says. "But at the end of the day ... even at high coverage, we are picking up probably about 82 percent of known deletions, about 15 to 18 percent of known duplications, and essentially no inversions or translocations that we can verify at this stage — so we have a long way to go. If that's where we're at with over 50 investigators, 19 algorithms, and two years of work, we have a long ways to go."
Stephen Chanock, chief of translational genomics at the National Cancer Institute, says that while the generation of resources like the 1,000 Genomes Project are important to better explore genomic structural variation, the need for analytical accuracy will be the pinch that wakes the dreamers up to face reality. "The excitement of having more and more tools always bring us back to the very important question of having to validate or replicate, and I worry that that's getting lost as everyone gets so excited about the next really cool tool. Those are all in silico observations; you still have to go back and make sure that variant is stable and matches what you think you've seen when you actually sequence a genotype," Chanock says. "CNVs, I think, are very interesting for rare or less-common diseases, although the common disease, common variant hypothesis for CNVs has been not quite as exciting as everyone had hoped. It didn't have the drama that everyone thought was there, unlike [in] the common SNP world. ... Ultimately, the technologies are making it easier and we may be going after uncommon and rare variants if whole-genome sequencing kicks in, or at least much denser chips become available."
Better tools
While there are many tools available to identify structural variants, the question of determining which reported variants are actually valid remains a large challenge that bioinformatics tools alone cannot deal with. "I'm not saying any one study is bad, but there is an under-appreciation for the amount of false-positives in the structural variation data that we're generating as a scientific community from next-generation sequencing data," Harvard's Lee says. "My advice to people who are analyzing next-generation sequence data in structural variants — especially for whole genome analyses — is to use as many technologies to complement their analysis as possible. For example, if you're whole-genome sequencing a given individual, maybe use different insert-sized libraries complemented with arrayCGH data. And, by all means, perform a significant amount of validation so you can minimize the amount of false-positive data."
The limitations to productivity Lee and his colleagues face when using multi-color probes to look at the structure of repeated genes using the fiber FISH technique is just one area in need of improvement. "It's just not high-throughput enough, so if someone could come up with a high-throughput method, that would be an excellent way to genotype some of the more copy number variable regions," he says. "I think also the arrays themselves are continually being improved in terms of what probes are being placed on there to genotype specific CNVs, but there needs to be more effort put into the technology for accurate genotyping of CNVs." For now, Lee says, the only work-around is putting in hours of labor to get the job done. [This is called "the brute force approach" in industry - AJP]
The most significant development with genotyping and CNVs over the last few years is the development of high-resolution array comparative genomic hybridization. This technique enabled the very first studies that mapped structural variation genome-wide in 2003 and 2004. Since then, advancements in high-throughput paired-end mapping, read depth of coverage analysis, split read analysis, and assembly have all seriously ramped up research efforts. "We consider massive paired-end mapping a key technique to identify structural variation and genomic rearrangements," says Jan Korbel, group leader at the European Molecular Biology Laboratory. Korbel and his colleagues at Yale University and 454 Life Sciences developed an approach for massively parallel paired-end sequencing that is helping the team to identify germ-line structural rearrangements in connection with the 1,000 Genomes Project and the International Cancer Genome Consortium. "The key advantage of paired-end mapping [is that] it allows a fairly deep and quick and cheap sequencing structural aberrations in the genome by recognizing ends of long fragments and mapping them," Korbel says.
Some newer genotyping tools show particular promise, he adds. These include the SUN genotyping method, developed by Evan Eichler's group at the University of Washington, which identifies "singly unique nucleotide" positions to genotype the copy and content of specific paralogs within gene families that are highly duplicated, and the analytical software framework Genome-STRiP, developed by Harvard University's Steve McCarroll for characterizing genome structural polymorphisms using multiple types of next-generation sequencing data including read depth, read pairs, and split reads.
Korbel's own group has designed a novel computational method to analyze the depth of coverage of high-throughput DNA sequencing reads, called CopySeq. This tool can infer locus copy number genotypes by integrating paired-end and break point junction analyses based on CNV-analysis approaches such as arrayCGH and FISH. In November, Korbel demonstrated CopySeq in a PLoS Computational Biology paper in which the team used it to genotype 500 chromosome 1 CNV regions in 150 genomes sequenced at low-coverage and to analyze gene regions enriched for segmental duplications by comprehensively inferring copy number genotypes in the CNV-enriched olfactory receptor human gene and pseudogene -loci. Using CopySeq, they found that for several olfactory receptor loci, the reference genome appears to represent a minor-frequency variant — a finding that could inform future functional studies.
As far as discovery methods are concerned, Korbel says he is waiting for a technique that can identify unique CNVs, irrespective of their sizes, as well as those in segmental duplications. "There are still regions in the genome that are very poorly understood and are hard to compare between individuals and with current technologies. We are unable to correctly resolve for these regions. ... Some of them are relevant for medicine, so that's a huge challenge," he says. "The data is good and so much is being generating by newer techniques, but we're still not fully exploring all the benefits of this data yet because we're still developing suitable methodologies that combine all types of signature signals in the data. We're obviously trying to improve this, but there's still a challenge there."
Recently, a team of researchers from Yale and Stanford University developed a method for genotyping and CNV discovery from read-depth analysis of personal genome sequencing. In February, they published a paper in Genome Research describing a method called CNVnator, which is based on a combination of the established mean-shifting approach with multiple-bandwidth partitioning and GC correction. The team used 1,000 Genomes Project validation data sets to calibrate CNVnator so it could be applied to CNV discovery, population-based genotyping, and the characterization of de novo and multi-allelic events. The team also reported its identification of six de novo CNVs in two family trios.
"The technology has sort of changed incrementally over the last decade, but the large data sets that we accumulated really made all the difference and allowed groups to start definitively identifying genetic factors that contribute to autism and schizophrenia," says Jonathan Sebat, an assistant professor at the University of California, San Diego.
"In 2011, the biggest game-changer is the short read sequence data, and shortly on its heels, the long-read, third-generation sequence data. The methods for detection of variants and the spectrum of potential disease alleles that you can find now is enormous, so that's a complete game-changer there."
'Game-changer'
In February, Sebat published a paper in Nature describing a large, two-stage genome-wide scan of rare CNVs that associated copy number gains at chromosome 7q36.3 with schizophrenia. Their findings implicate altered vasoactive intestinal peptide signaling receptor gene VIPR2 in the pathogenesis of schizophrenia and indicate the VPAC2 receptor as a potential target for future antipsychotic drug development. "What's new and interesting about that is that the structural variants that we're finding contrast [with] the large microdeletion syndromes that we knew about from the early CNV studies. We're now honing in on the smaller CNVs, not the big, non-allelic homologous recombination-mediated deletions that we used to see," Sebat says. "We're now seeing structural variants that are mediated by other types of mutational mechanisms. The break points are not the same in different patients — they're overlapping, but very different risk alleles. When we get our disease association, we end up finding many different rare mutations in the same gene, often with the same functional impact." He adds that down the road, new CNV findings will not only be used to pinpoint specific genes but identify neurobiological processes in diseases as well.
The University of Washington's Joshua Akey and his colleagues are refining approaches to explore patterns of genomic variation using exome sequencing, as it allows them to use data from thousands of individuals rather than from the mere handful they'd afford using whole-genome sequencing. "It's really striking to be able to look at a data set of 2,000 individuals because you have such deep insight into patterns of variation and you get a real appreciation for the structure of rare variation that you can't get when you only have 20 or 40 individuals," Akey says. "One of the most interesting things that we'll be able to do with thousands of individuals is make very detailed inferences into recent human history. You can't do that unless you have thousands of individuals. For the first time, we can see these dramatic expansions in human population sizes that have occurred in the [past] couple thousand years."
Akey is involved in several structural variation research projects, including one study that looks at the genetic basis of adverse drug responses across dog breeds. He is working, in collaboration with his colleague Evan Eichler and Washington State University's Katrina Mealy, to characterize the distribution of segmental duplications and CNVs across 20 dog breeds with arrayCGH, as it functions at a higher resolution than chromosome-based comparative genomic hybridization.
Coming up
Later this year, Akey and his colleagues plan to publish what he describes as one of the largest and most comprehensive studies into patterns of human genetic variations using high-quality data from roughly 2,000 exomes. Although the rise of exome sequencing has undoubtedly caused excitement and heightened expectations within the structural variation research community, he cautions that the real insights are only going to come from taking a step back and determining how to interpret and compare those sequences from that many individuals. "There's a critical need for further methodological development to be able to fully extract all of the information in these complex data sets and the challenge is that there are so many challenges," he says. "Let's assume that the genotypes we have are accurate: what do we do with that data in terms of making inferences about human history and about disease susceptibility? What's the best way to test for association between rare variants and disease? What's the best way to look for natural selection? There are challenges from the very beginning of the process to the very end of the process. A lot of theoretical work needs to be developed to fully exploit the information that CNVs have. [Lest anyone think that "theoretical work" is free, let us correct the perception. Superior theory is the most expensive part of research - except for all those funds wasted on "garbage in - garbage out"; done with "frighteningly unsophistaced" (most often disarmingly naive) "theoretical background" - AJP]
While the literature contains a growing number of studies that demonstrate associations of common simple CNVs with specific disease susceptibilities, forming a substantial collection of common CNVs, the issue of resolution still hinders researchers who aim to study rare CNVs. "I think we have a very nice catalog of common copy number variants and we have methodologies to pick up the rare CNVs, although not as high resolution as I'd like to see, but it's the cost effective way of doing it," Harvard's Lee says. "We have 18 to 20 of these very clear associations — these are deletions that increase your susceptibility with more common disease — and I think there are more to come. But the issue we have right now is that we don't have a catalog for the rare variants and the smaller ones. Once we start to develop those catalogs, we can start to improve on our arrays, or whatever method we use to detect CNVs in the disease association studies, to see if any of those rare, smaller CNVs are associated with other diseases."
NCI's Chanock, who is also a physician, cautions that the community should be realistic with regard to the potential for all this structural variation data to facilitate improvements in the clinic. "We've started to make very important steps, and when we look at the age of CNVs and a good part of the sequencing that's going on, the discovery element is spectacular — -almost unprecedented," he says. "The plausibility and the meaning of this discovery is complex: each one of these regions requires its own study and it's still a work in progress to reach the level of confidence and validity that's needed to incorporate that into our clinical workflow. We have to be careful with all the ballyhooing about 'The genomic age is going to turn everything into Star Trek medicine,' because I find this dangerously naïve."
[Would anybody with a sane mind fund a nuclear accelerator to smash an atom into myriads of pieces - if nuclear physics was not enough developed to see where the predicted trajectories differ from the actually measued data? More or less the same is happening now, when the "frighteningly naive" (and totally discredited "Gene/Junk" notion, see Dr. Mattick's article in this column) is far too often the only "theory" that experimentalist can use as an alibi. Let's us face it - the non-targeted hunt for "structural variants" could cost cancer patients (literally) and arm and a leg (let alone other even more precious body parts to surgery) - yeat an amassed "Library" of "structural variants", will yield only an extraordinary knowledge at an exorbitant price of what "structural variants" there are - but (as Thomas Kuhn predicted, the knowledge would never automatically translate into "understanding"). The better way is to go for a Fractal Recursive Genome Function Algorithic Approach, that is software enabling. The algorithmic fractal approach would tell you immediately that changing the "c" constant in a Mandelbrot Set would retain the fractality (such structural variants only affecting human diversity), while the ways how the Genome does not obey its own fractal rules would pinpoint fractal defects that violate the fractal rules of the Genome - thereby associated with pathology of phenotypes. This entry can be commented on the FaceBook page of Andras Pellionisz]
Cancer center builds Texas-sized cloud [Private cloud!]
Computerworld
Beth Schultz
04.04.2011 kl 04:32 | Network World (US)
As researchers at The University of Texas MD Anderson Cancer Center work at "making cancer history," they're doing so with the help of compute power and storage capacity from a private cloud.
But this is no ordinary cloud.
After all, when you're researching something as complex as the human genome you tend to think big, and MD Anderson's cloud reflects that type of ambition and scale. We're talking 8,000 processors and a half-dozen shared "large memory machines" with hundreds of terabytes of data storage attached, says Lynn Vogel, vice president and CIO of MD Anderson, in Houston.
A different path
And while MD Anderson's general server infrastructure uses virtualization, the typical foundational technology for cloud, this specialized research environment doesn't. Rather, the organization uses an AMD-based HP high-performance computing (HPC) cluster to underpin the research cloud.
"We're currently implementing the largest high-performance computing environment in the world devoted exclusively to cancer," says Vogel, who was recently named Premier 100 IT Leader honoree by our sister publication, Computerworld.
The data and processing capacity are available to the MD Anderson cancer researchers as needed, whether they're sequencing human genomes or investigating radiation physics, epidemiology, dosing calculations for radiation therapy or running simulations for clinical trial activities. About three dozen principal investigators, who each have anywhere from two to 10 assistants, regularly tap into the research cloud, Vogel says.
To access the cloud, they use a service oriented architecture-based Web portal called ResearchStation.
"When you look at the classic definition of cloud computing as enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released, that's in fact how we're approaching our environment," Vogel says.
Enterprise Cloud Services: The agenda
However, he notes, the MD Anderson cloud doesn't currently have a chargeback mechanism - an oft-cited but, at this point, little used cloud attribute. "We don't require a chargeback mechanism because we manage demand largely by a peer review process. The actual determination of priority for using resources is driven by clinicians and researchers themselves, not by IT people," Vogel says.
What this means, he adds, is that he never needs to plead a case for, say, more storage. "They're the ones going to executive management, saying, 'You really have to increase the capacity of this capability or that capability for us to continue to do our work and maintain our rating as one of the top cancer centers in the world," Vogel explains.
More, more, more
In addition, MD Anderson doesn't experience the typical up and down spikes in usage that other enterprises might encounter.
"We find that both the clinicians and researchers in the field of medicine have what I would label 'an insatiable demand' for computing resources, and the demand curve just keeps going up," Vogel says.
He notes that the 8,000-processor HPC sitting at the heart of the private cloud already operates at 80% to 90% capacity, as did its predecessor, a mere 1,100-processor machine. Memory-intensive applications rely on six 512-GHz, 32-CPU servers.
The cloud build-out at MD Anderson dovetails with the organization's expansion into a third data center, due to open this summer.
This will be the second new data center the organization has opened in a four-year period - and these are good-sized operations, with 12,000 to 15,000 square feet of raised floor in each, Vogel says. "We thought our second data center would last us four to five years, but it was full within 18 to 20 months. We had to turn our disaster recovery site into a production data center as we built another one," he adds.
The MD Anderson data centers house roughly 3 petabytes of data, a "somewhat surprising amount," Vogel says, since the cancer center is primarily a 500-bed hospital. But the volume of research data, at about 1.4 PB, now exceeds the amount of clinical data at MD Anderson.
"Anybody who looks at genomic medicine and the sequencing of human genomes begins to realize that there's a tsunami of data coming out of those processes," he notes. "So, ironically, today at MD Anderson we have more data storage capacity devoted to research than we do for clinical care, and that includes all of our images. We're being hit by extraordinary amounts of data that needs to be managed and stored." [See YouTube below, that predicted today's conditions 3 years ago - AJP]
To handle the cloud's storage requirements, MD Anderson uses an HP-Ibrix system that supports extreme scale-out. It chose the Ibrix system because of its reliability and its ability to present storage seamlessly over Ethernet or InfiniBand, using CICS, FTP, HTTP, the Linux client, NFS and other technologies, Vogel says. "This capability also enables us to do data tiering through the cluster," he adds.
Manageability also has been a boon. "Having HP as the end-to-end vendor ensures that all parts will fit together and fit into our monitoring system without any clashes," Vogel says.
While MD Anderson uses HP Storage Essentials and CIM to manage each storage unit, it relies on the Ibrix management server, Fusion Manager, for a top-level view. Each server also reports into Fusion Manager, Vogel says.
"As an added bonus, and very much a consideration in a constrained healthcare personnel environment, is the ability to operate our entire cloud configuration with minimal personnel involvement - just two people," Vogel says.
Public cloud: Not on your life
Vogel says he's talked to some public cloud providers who would love to host those MRIs, CT Scans and other clinical images - more than 1 billion of them - within their infrastructures. But no can do, he says.
"We've looked into this, but quite honestly, we've found on performance, access and in the management of that data, going to a public cloud is more risky than we're willing to entertain," Vogel says. "This goes directly to the point that this is identifiable patient data ... and we're just not comfortable with the cloud given the actionable capability of a patient should there be a breach."
What's more, public cloud providers simply can't provide the level of business knowledge that MD Anderson's IT staffers can, some of whom are PhD scientists themselves, Vogel says.
"When you're in the business of biology, which we are, it's a different ballgame in terms of understanding the structures of data, the kinds of access and models used, and the applications that need to be available," Vogel says. "As much as public cloud providers would like us all to believe, this is not just about dumping data into a big bucket and letting somebody else manage it."
Cancer as Defective Fractal Recursive Genome Function (Pellionisz and Lander et. al trigger escalation of fractal approach)
[Google Tech Talk YouTube, The Principle of Recursive Genome Function, 2008]
[The "double lucid heresy" of brain cell growth programmed by an iterative fractal recursive genome function from proteins to DNA - surpassing both mistaken axioms ruling for half a Century; the "Central Dogma" AND the "Junk DNA" misnomer - are traced back to the fractal model of a Purkinje brain cell (Pellionisz, 1989, see page 461 Fig. and point 3.1.3. "repeated access to genetic code", see also acknowledgement on pp. 462 reference to the NIHM grant application - denied because of double heresy, and renewal of ongoing NIH grant to AJP also denied). Based on the core-concept, FractoGene (fractal DNA governing growth of fractal organelles, organs and organisms, Pellionisz, 2002) could only be established in a stealth-mode (USPTO, 2002), till the results of NIH "ENCODE" concluded (2007) that "the community of scientists would have to re-think long-held beliefs (Collins, 2007). Upon this clearance, both the peer-reviewed The Principle of Recursive Genome Function and the Google Tech Talk YouTube could be swiftly disseminated (click above, 2008).
The "fractal approach to DNA" ("The Principle") received a major impetus (mark B) when, within 6 months of its publications was explicitely cited by about 15 authors (see e.g. Shapshak et al, 2008 and Chiappelli et al, 2008, and the fractal approach to recursive genome function was also presented (invited by Prof. George Church) in Cold Spring Harbor, Personal Genomes, Pellionisz, 2009, September (see escalation from Mark A).
As the manuscript was handed over to Dr. Lander prior to its publication, along with a dozen of co-workers a Science cover article appeared (Lieberman et al. 2009, October), showing a fractal folding structure of the DNA. The article with Eric Lander, Science Advisor, amounted to convey the message "Mr. President, the DNA is fractal! Although the Lander et al. paper (2009) reached back by direct citation to the seminal idea of fractal folding by Grosberg et al. (1993) - similarly as Pellionisz' The Principle of Recursive Genome Function (2008) reached back by direct citation to the seminal idea of fractal neural growth by Pellionisz (1989), the mutually reinfocing papers by Pellionisz (2008) and Lieberman et al. (2009) created the flood of viewership of Pellionisz' YouTube (2008).
Thus, with Pellionisz (2002), Collins (2007), Church (2009), Lander (2009), Schadt (2010), Mattick (see article below, prized in 2011) there is a slew of leaders calling for new axioms, some implicitely or explicitely referring to the fractal nature of DNA, setting of a new school in Genomics (HoloGenomics). Some further representatives of the followership include:
Jean-Claude Perez (2010) Codon Populations in Single-stranded Whole Human Genome DNA Are Fractal and Fine-tuned by the Golden Ratio 1.618 Interdiscip Sci Comput Life Sci 2: 228–240. DOI: 10.1007/s12539-010-0022-0
“Since the PHYSICAL structure was found fractal (providing enormous amount of untangled compression), it is reasonable that the LOGICAL sequence and function of the genome are also fractal.” (Pellionisz, A., 2009, personal communication: From the Principle of Recursive Genome Function to Interpretation of HoloGenome Regulation by Personal Genome Computers.Cold Spring Harbor Laboratory. Personal Genomes Conference, Sept. 14–17, 2009).
For several years, ...researchers like A. Pellionisz advocated ways to analyze and detect fractal defects within whole genomes. This is based on recursive fractal exploration methods and artificial neural network technologies (Pellionisz, 2008).
Simone Caramel and Sergio Stagnaro (2011) in their "Quantum Biophysical Semeiotics and mit-Genome's fractal dimension" attempt make generalizations from fractal dimension to chaotic, thermodynamical and quantum-states of the genome.
Alexei Kurakin (2011) "The self-organizing fractal theory as a universal discovery method: the phenomenon of life" attempts to make generalizations from fractal theory to non-equilibrium thermodynamics in genomics, expanding the horizon to life sciences.
The PostModern era of Genomics, HoloGenomics that unites Genomics and Epigenomics in terms of Informatics is upon us. It is a new science- and since it is at the same time a new industry to save lifes as urgently as possible, science results can be immediately verified (or falsified) - and if they are algorithmic (software enabling) can be put into use at once.
The Trouble with Genes [Article Gets prize - Mattick joins leaders to admit that basic premises were all wrong - AJP]
Cosmos
by Elizabeth Finkel
'Junk DNA' research inspires Higher Education Journalist of the Year
3 March 2011
The article, "The Trouble with Genes", was published in Issue 31 of Cosmos in February 2010 and details Professor's Mattick theory that so-called 'junk DNA' actually helps regulate our development. [Why does a year-old article get Prize? Because the message looms greater and greater as the "Big Genome Letdown" sours - AJP]
This research runs counter to the traditional scientific dogma that the only useful genetic material is genes, which contain the instructions to make proteins, and everything else in the genome is 'junk'. Dr Finkel, who herself has training as a geneticist, said Professor Mattick's view "puts him way ahead of the curve".
"We know he is leading the scientific world with his ideas and we really ought to be writing about them but it is difficult to understand what he has discovered - one seems to require degrees in both computing and genetics," Dr Finkel said. [This is a reason why AJP, originator of FractoGene, can excel - with Ph.D. in computer technology, Ph.D. in biology and Ph.D. in physics - AJP]
The Higher Edcuation Awards, conducted in conjunction with the National Press Club, are judged in two categories, each with awards for print and broadcast. The Journalist of the Year is selected from the category winners and is awarded a $10,000 study tour funded by Universities Australia. Dr Finkel's category win was for excellence in communicating research and innovation, teaching and learning, equity and access, social inclusion or Indigenous education issues in print.
National Press Club President and Chair of the judging panel, Laurie Wilson, said, "Elizabeth's story displayed all the hallmarks of outstanding journalism - she tackled an extremely complex topic, translated it into layman's language and turned it into a great story."
The other judges were: Dr Matthew Ricketson, author and former journalist who is now Professor of Journalism at the University of Canberra; Mischa Schubert, NPC Vice-President and political reporter for The Age; and Malcolm Colless, journalist, media consultant and former Director of News Ltd.
---
Junk DNA was once thought to be little more than gibberish. But it may actually be the software that controls a complex organism.
"WHAT'S A GENE, DAD?" I'd like to be there when the nine-year-old son of iconoclastic geneticist John Mattick pops the question. It used to be simple - a gene coded for a protein.
But when I put that question to Mattick, based at the University of Queensland, his response was as disturbing as it was confusing.
"Genetic information is multilayered and a gene can convey lots of different information into the system. It's almost like we've moved into hyperspace in terms of information coding and transfer."
Mattick's cutting-edge theories about gene regulation have been published in the British journal Nature and even appeared in the New York Times. Yet, even though I was once a geneticist, I couldn't fathom his answer.
It seemed my fears had been realised and I'd been left behind by the genetics revolution. In a desperate ploy to catch up, I asked how he would explain a gene to his young son.
"I would just tell him, 'it's an old-fashioned concept', and then explain about information networks. He's a child of the digital generation - he won't have any trouble with it." [This is a reminder that presently "gene" has ZERO universally accepted definition. You get as many fragmented definitions, as may experts you ask - the algorithmic (software enabling) definition is FractoGene - AJP]
IT'S NOT JUST ME who's confused. I checked the 2008 edition of my favourite text book, Molecular Biology of the Cell.
The traditional definition is still there in the opening chapter. But as you read on, you sense the textbook struggling, trying to wrestle the gene back into the box of a definition.
Mattick prefers not to try. And a lot of other geneticists are starting to think this way too. As Ed Weiss at the University of Pennsylvania told me, "the concept of a gene is shredding". [It is not really shredding - it is becoming fractal - AJP].
The genomics revolution is largely to blame. Scientists were shocked when they found out how few 'old-fashioned' genes we actually have - about the same number as the humble nematode worm (Caenorhabditis elegans).
In fact, almost all multicellular creatures with the complexity of a worm or greater have about 20,000 genes. But for Mattick, the death knell of the traditional concept of the gene was triggered by another revolution altogether - that of the digital information age.
Scientists have always understood biology in terms of the technology of the day. The brain, for instance, was considered by the Ancient Greeks and Romans to be an aqueduct for pumping blood; inhabitants of the 19th century likened it to a telephone exchange; those of the 20th century likened it a personal computer. Now scientists compare the brain to chaos and distributed functions of the Internet. [Indeed, those who actually know nonlinear dynamics, with chaos/fractals the two sides of the same coin, declared FractoGene as soon as ENCODE invalidated the premises of the old school; see peer-reviewed science paper (about 10,000 downloads) and Google Tech YouTube (now at some 10,300 views) in 2008 - AJP].
WHEN IT COMES to the gene, Mattick likes to point out that scientists cracked its code in the 1950s, when the world was purely analogue [This perhaps the only major science mistake of the brilliant science writer. The code was never "cracked" - only "revealed". Those in WWII intercepting coded messages of the Japanese and German forces know exactly the difference between "intercepting" the exact transmission - and "cracking the code, to reveal its meaning - AJP].
We had vinyl records, slide rules and mechanical cars. We were primed to recognise the gene as a recipe for an analogue device - such as a protein, for instance.
Proteins are the analogue devices that operate the chemistry of life: the enzymes that metabolise food; the mortar and bricks of tissues; the motors of muscles; the hormones that transmit signals; and the ferries that carry oxygen through blood. We recognised a gene as being the recipe for a protein.
Today, iPods store the equivalent of many thousands of vinyl records. Microprocessors in cars can control everything from the engine to the stereo.
The digital revolution has succeeded in taking vast amounts of information and compressing it. Mattick believes something very similar happened to the gene. In the course of evolution, it went digital. [Dr. Mattick may not be on firms grounds when it comes to information theory - or the science writer may have misunderstood his statement. The DNA has always been digital throughout the evolution - only human interpretation did not seem to recognize this fact for far too long - AJP]
In 1953 we got our first inkling of how genes work. Scientists knew that genetic information was carried by the threadlike molecule DNA - a polymer of four repeating molecules adenine, thymine, cytosine and guanine or A, T, C and G. But how did this thread carry genetic information? Perhaps a picture would reveal its secret.
BRITISH CRYSTALLOGRAPHERS Rosalind Franklin and Maurice Wilkins bombarded crystals of DNA with X-rays and observed an enigmatic regular structure.
The University of Cambridge's James Watson and Francis Crick figured out what it was. Like the elegant spiral staircase of the Louvre in Paris, it was a double helix. And the moment they figured out the structure, the secret of life was revealed. [No, it wasn not. Reproduction (copy mechanisms) of the DNA was, indeed, discovered, but how the fractal DNA governs the growth of fractal organelles, organs and organisms were not at all revealed. Certainly never understood by Dr. Crick (because of his adherence to his "Central Dogma" till the end of his life, and the jury is still out on Dr. Watson - AJP]
Life copied itself by splitting the helical ladder down the middle. Each half then became a template for generating a new copy because each DNA letter on the split rung specified what its partner must be: A only paired with T; C would link only with G.
Watson and Crick had figured out how the code of life copies itself. Some five years later, Marshall Nirenberg, Har Gobind Khorana and Robert Holley in the U.S. figured out what the code means.
The letters of DNA spelt words that coded for amino acids - the building blocks of proteins. Until then scientists had been kids pulling Tinkertoys apart, but now they had the instructions for assembling them. Mankind had discovered the awe-inspiring logic of life.
Genes were made up of a string of DNA, and DNA coded for proteins. DNA happened to have a go-between, a disposable working copy called 'messenger RNA'.
RNA was chemically similar to DNA, but flimsier. Just as an architect will run off copies of a blueprint, so messenger RNA was the working copy used on the protein construction site.
HAVING CRACKED THE SECRET of life, these scientists now started calling themselves molecular biologists (biologists who studied living molecules). And they became rather sanguine, so sanguine they started talking about dogmas.
"We had two central dogmas that were regarded as universal truths in the '60s," said geneticist Bob Williamson, now an emeritus professor at the University of Melbourne.
"The first was 'DNA made RNA made protein'. The second was that the genetic code was universal: what was true for E. coli would be true for an elephant".
The shock to the system came in 1977. Researchers by now were quite au fait with genetic code. Thanks to its universality, they could insert the predicted DNA code for a human gene into a bacterium and out would pop the correct protein.
Yet no-one had ever glimpsed the 'mother code' of a human gene. It was packaged in a chromosome within the dark nucleus of the cell, like a hallowed tome in the crypt of the Vatican library.
IN 1977, RESEARCHERS decided to fish out the mother code for the gene that makes globin (a component of haemoglobin). But no-one was prepared for its size - the globin gene was way larger than it ought to have been.
Williamson, whose group at St Mary's Hospital in London were the first to put the human globin gene into bacteria, remarked in a Nature editorial: "Once again we are surprised".
The explanation was bizarre. The mother gene did indeed carry the predicted code for globin, but it was strangely interspersed with gibberish.
Imagine that the predicted DNA code for globin was written with the English letters: G-L-O-B-I-N.
The mother code appeared as:
G-L-z-z-z-q-q-O-B-s-r-m-b-I-N.
Researchers panicked. What was this gibberish? Was the genetic code not universal after all?
But the panic soon subsided. Whatever gibberish had infiltrated the mother code, it disappeared from the working copy - the messenger RNA - by the time it got to the factory floor.
Like an edited home video, the internal junk had been clipped out and the good bits spliced back together again. Indeed the process was dubbed 'splicing'. The bits that were spliced together were named 'exons'; the internal junk, 'introns'.
With everything neatly named and explained, "the world collectively breathed a sigh of relief," says Mattick. The hallowed central dogma had been saved.
THERE WERE LOTS OF justifications for dismissing junk DNA as 'junk'. Not only did it lack code words for amino acids; it turned out 50% of the junk was comprised of inane repetition.
These repetitious tracts seemed meaningless. But researchers had a good notion of what many of them were. Most of the repeats were 'transposons' or 'jumping genes'.
Jumping genes, which may have originated from invading viruses, have the ability to copy themselves independently of the rest of the genome and then become inserted randomly throughout the genome.
Then there was another reason to suspect that much of the DNA of a species was junk. The total amount of DNA seemed to bear very little relationship to the complexity of the organism.
An amoeba for instance, had a thousand times more DNA than a human. Sometimes it seemed cells multiplied, but forgot to divide, ending up with vast amounts of DNA. It seemed as though DNA just liked to go along for the ride.
NOT EVERYONE DISMISSED junk DNA. Physicists such as Eugene Stanley at Boston University looked for patterns in junk DNA and found long-range interactions more typical of language than gibberish.
Malcolm Simons, a Melbourne immunologist, stumbled upon junk DNA in the course of testing people's tissue types. Tissue compatibility depends on MHC genes, as do some aspects of immunity.
Yet he found the pattern of junk DNA surrounding the genes was a better predictor of the tissue type. For him, junk turned to treasure.
Mattick's departure from the dogma seems to have been driven more by instinct than evidence. Blame it on his genes: "I've got a natural tendency to challenge everything because of my Irish background," he says.
Mattick recalls sitting in a pub in 1977 during his postdoctoral stint at the Baylor College of Medicine in Houston, Texas, and thinking "Maybe this is telling us something?" But for 16 years, while he built his career as a bacterial geneticist, the problem of junk remained an "intellectual hobby".
In 1993, Mattick felt he deserved a break. He'd completed the Herculean task of setting up an entire new institute from scratch - the Institute of Molecular Biosciences at the University of Queensland in Brisbane. What better reward than to spend a sabbatical at the University of Cambridge scratching his intellectual itch?
He had slowly been building a theory in which RNA was central. The current dogma said that most of the RNA made by the genome, the RNA from introns, was bound for the scrap heap. But Mattick thought otherwise.
Simple organisms such as bacteria do not carry introns, but complex creatures do. Mattick wondered if the scrap RNA was part and parcel of that complexity. After all, RNA has amazing versatility: it is a code-carrying molecule that can recognise matching codes on both DNA and other bits of RNA. And it can also form extraordinary three-dimensional structures to mesh with proteins.
IN MATTICK'S THEORY, the scrap RNA or 'non-coding' RNA as it became called, was not flotsam and jetsam floating off a sea of junk DNA. Rather this scrap was more akin to the optical fibres of a modern high-rise building.
An 18th century time traveller, spying these cables, might pass them off as scrap compared to the recognisable analogue components of the building like bathrooms, kitchens and bedrooms. Yet, just as the cables are crucial for the building's communications and controls, so scrap RNA was crucial to the communications and control of a multicellular organism.
The major problem with his theory was that there was no experiment to prove it right or wrong. So Mattick decided to spend his sabbatical in the library looking for "circumstantial evidence".
What he searched for with the most alacrity was evidence to prove him wrong. "The critical observations were the ones that would show it was bunk. Then I could just return to my lab and forget about all this stuff".
TWO BITS OF EVIDENCE threatened to abruptly end to his quest. One was fugu - the pufferfish (Diodon). Fugu is famous for the tetrodotoxin, which kills dozens of Japanese diners each year and for its tiny genome - about an eighth the size of our own.
Nobel Prize winner Sydney Brenner, then at the British Medical Research Council's Laboratory of Molecular Biology in Cambridge, was in the process of reading fugu's DNA sequence. Rumour was the fish had barely any introns, and if a complex vertebrate such as fugu had no introns, then Mattick's theory about regulatory RNA must be wrong.
He paid a visit to Brenner to discover the terrible truth. It turned out that while most of fugu's introns were very small, some were really big. Mattick's theory survived.
The next mortal threat was a publication reporting that introns, once clipped out of the messenger RNA, were destroyed within seconds. If introns were as ephemeral as a puff of smoke, how could they perform any function?
Mattick scrutinised the report closely. It showed that introns were edited out of the main message within seconds. But as to how long they persisted before being shredded, no-one knew. Perhaps, he speculated, it was long enough to do something.
Mattick, of course, was also on the lookout for evidence that would support his theory. He found some. The fruit fly possessed a set of genes that were responsible for its body plan, known as the bithorax complex. It turned out that a crucial stretch of this DNA produced RNA that did not code for protein. What other function might this RNA have?
MATTICK RETURNED to the University of Queensland with his theory intact. He started writing papers articulating his theory that non-coding RNA (shorthand for non-protein coding RNA) was the high-level coding language of complex organisms.
His approach remained one of gathering circumstantial evidence. Together with co-workers in mathematics and computer science, he amassed some compelling observations.
For instance, as more and more species became the darlings of DNA sequencing projects, Mattick noticed a delectable relationship: there was no link between the complexity of the critter and its total amount of DNA.
But there was a clear relationship between the proportions of junk and protein-coding DNA: as the complexity of the organism increased, so did the relative amount of junk.
And then genome sequencing delivered the pièce de résistance: making a human being required no more old-fashioned genes than making a worm or fly.
Clearly complexity was encoded elsewhere, and according to Mattick and a growing number of converts, it was in non-coding RNA.
Mattick's genetic programming theory, outlined in a recent edition of the Annals of the New York Academy of Science, started to assume its current form. In simple terms it goes like this: bacteria could make do with using analogue devices - proteins.
But even these single-celled critters devoted a large portion of their genetic information to the task of control. If organisms were going to get more complex and coordinate decisions between trillions of cells, they needed to develop a more compact regulatory language.
Just as engineers turned to digital coding to move from LPs to iPods, biological systems turned to RNA to evolve from bacteria to people. According to Mattick, RNA, like DNA, carries coded digital information in four letters that can rapidly interact with other parts of the code, much like the self-modifying or feed-forward routines of some computer programs.
As Mattick was building the framework of his model, the rest of the world started providing the bricks and mortar. Big time.
SINCE 1993, THERE has been an avalanche of evidence on the surprising roles of non-coding RNA.
Most of our DNA may well have originated as 'junk' but that junk has been put to work. One of its most common jobs is to produce tiny bits of RNA known as 'microRNA' that targets other RNA for destruction. MicroRNA has been shown to shut down the activity of protein-coding RNA in everything from petunias to people.
Junk DNA also plays another crucial function: it guards the DNA code from invasion by retroviruses or so-called jumping genes, which can hop about in the genome causing dangerous mutations.
Junk DNA is itself largely composed of former interlopers but, like a patriotic immigrant, it does its best to prevent any further invasions.
The RNA transcripts that run off junk DNA are still a close match to live viruses or active jumping genes, and if these junk transcripts meet up with their relatives, they inactivate them.
JUNK DNA MAY play an even more profound role in the workings of multicellular animals. A crucial part of being multicellular is that different cells do different things - they are not all reading from the same page of the genome hymn book.
The first step toward specialisation is folding down those pages that are not to be read, and it seems junk DNA guides the folding process. For instance, females carry two X chromosomes, but only read the contents of one.
During embryonic development, one of the X chromosomes is folded away, a process initiated by a large string of non-coding RNA called 'Xist'.
While most tissues of the body want to keep jumping genes from jumping, the brain might have other ideas.
Fred Gage's lab at the Salk Institute for Biological Studies in La Jolla, California, found evidence that jumping genes known as 'LINE-1' or 'L1', which are permanently deactivated in other cells, become active during development of the human brain.
The L1 genes replicate and insert randomly, sometimes creating as many as 100 extra copies per cell. This variation among neurons in our brains could be the basis for individual differences in neural circuitry and may open up a new way of looking at neurological disorders.
Junk may also have played a crucial role in our evolution. At the DNA level, one of the things that distinguishes primates from other mammals is the invasion of a million copies of a jumping gene that goes by the name of 'alu'. It now occupies 10.5% of the human genome.
JUNK RNA MAY also account for some of the difference between humans and chimps. Our DNA is 99% similar, but one of the regions that differs is the so-called 'HAR1', or human accelerated region 1.
It turns out HAR1 produces a 118-letter non-coding RNA, which is highly active in the brain.
In 2005, Mattick resigned as director of his institute and went back to work in the lab. Tools to explore the function of non-coding RNA had arrived in the form of heavy-duty sequencing machines.
In just one week a 'next generation' sequencing machine can read three billion letters - the equivalent of an entire human genome. Not long ago, that task took the combined forces of the Human Genome Project 14 years to complete.
Mattick and University of Queensland colleague Sean Grimmond have been in collaboration with like-minds at Japan's RIKEN institute. They have been scouring the output of mouse and human genomes, trying to put together a comprehensive catalogue of their RNA output. The database called 'Fantom' (functional annotation of mammalian genomes) now contains millions of transcripts.
THE LATEST DATA is mind boggling. As Grimmond tells me: "Each gene is capable of seven different transcripts, some of these code for proteins and some don't."
Trying to make sense of this deluge is the challenge. "[But] we're getting good at asking questions about ludicrous amounts of data," he says.
For Mattick, the human genome is an RNA machine. But is his theory well and truly vindicated? Not yet. [Why not? One may ask. A possible explanation is that Dr. Mattick's theory is not algorithmic; thus not "software enabling" - AJP] Though it would be hard to find anyone today who blithely dismisses junk DNA, few are willing to go as far as he is and say that the RNA read from junk code is the software that controls a complex organism.
For example, Claude Desplan at New York University has studied fruit fly development for 25 years and argues that complex genomes, in flies or people, are still fundamentally controlled by proteins. While acknowledging that some junk has a role he says, "most of junk DNA is still junk".
Mattick, though, is convinced that our genome is way ahead of anything that IT designers have yet imagined. "The genome is so sophisticated, that there are lessons in information storage and transmission that will be really useful," once we figure it out, he tells me. "The human genome is a similar size to Microsoft Word, but it makes a human that walks and talks."
Notwithstanding the deluge of papers he has authored in top journals, Mattick still seems to be on the fringe. And you get the impression that's just where he likes it.
Adventures in Extreme Science [Eric Schadt and other kooks - AJP]
Esquire
March 22, 2011, 12:24 PM
From Crick and Watson through J. Craig Venter, we had all our eggs in one basket — molecular biology, gene mapping, whatever you want to call it. It failed. And now we're counting on this guy.
By Tom Junod
There may be another scientist in the world as smart as Eric Schadt. After all, scientists are a pretty smart lot, even though you'd be surprised at how few want to change the world, and how many of them have the trudging souls of brilliant, dutiful clerks. There may even be another scientist in the world as popular, as in demand as Eric Schadt, even though Eric works hard at everything he does, including his popularity, and is engaged, at any given time, in at least ten collaborations with other top scientists, not to mention the production — just last year — of a profligate thirty-five scientific papers, not to mention the delivery, year in and year out, of about forty talks and presentations after receiving invitations to deliver two or three hundred. (You'd also be surprised by how social a lot of scientists are, and how many parties they go to.) But if you're looking for a scientist whose great popularity rests in tirelessly writing papers and delivering speeches whose implicit and sometimes explicit message to the most eminent minds in his field is that they're wrong, that they've failed, and that the best way for them to stop wasting their lives is to follow him in a scientific revolution that he admits might not even work: Well, then you'd probably have to narrow your search a little bit. It takes a pretty smart guy to tell the smartest people in the world that all their success, all their hard-won knowledge has led them to a dead end ... that the approach they've taken has been a little, um, simplistic. It takes Eric Schadt to say that — and then to make the damned sale.
What's he selling? Well, the first way to answer that is to say what he's not selling. He's not selling molecular biology. He's not selling the last big revolution in biology, the revolution that made biology the dominant science of our time and was supposed to save us. The Human Genome Project, which at a cost of about $3 billion mapped the twenty-three thousand or so genes that are said to encode all of human existence? That's molecular biology, man — its signal triumph, its apotheosis, the culmination of an effort that began with the elucidation of the structure of the DNA molecule, picked up speed and funding with the War on Cancer, and then, well, figured everything out for us, from the causes of cancer to the roots of belief. (Hint: They're both in the genes, which govern our biology by the proteins they express.) And so we believed. We believed that in our genes was the code for not just our proteins but our fates; we believed what we read in the newspapers and heard on television, that a gene for this had been found, or a gene for that; and we believed above all that if a cause for a certain disease had been discovered, then a cure had to be on the way. Indeed, without quite knowing it, we believed in the logic of molecular biology, its inexorable momentum, which we equated with scientific progress itself. The logic was this: one gene at a time. One gene at a time, we'd triumph over disease, and if we figured out the right gene, the right protein, and the right pathway between genes and proteins, maybe we'd even triumph over death itself. How triumphant was molecular biology? It was so triumphant that we believed in it (and still believe in it) even when it has gone a long way toward bankrupting the pharmaceutical industry with drugs like the painkiller Vioxx and the diabetes medication Avandia — drugs that hit their molecular targets but also cause catastrophic side effects by hitting other unforeseen targets as well — or drugs that never come close to making it to market at all. We still believe in it even when nearly ten years after the mapping of the genome, it has radically increased the cost of drug development while delivering next to nothing in return.
That's right: nothing. Oh, sure, knowledge, yes. Humans know more about the workings of individual genes, proteins, pathways, and kinds of cells than we ever have. We know so much that surely all we need is time. Because one gene at a time takes time. And drug discovery takes time. And FDA approval takes time, gobs of time, epochal engines of time ... and now here comes Eric Schadt saying, Don't hold your breath. Here comes Eric Schadt saying that time isn't the problem with molecular biology — molecular biology is. Reductionism is. Willful oversimplification is. The very idea that humanity can enlist the aid of grunting lab-coated Sherpas and march toward pharmaceutical nirvana one gene at a time is. Here comes Eric Schadt saying, "All right, so the idea was that understanding individual proteins and their missions could open up our understanding of the complexity of living systems. That's failed. That's turned out not to be true. And that was the dream, right? So it's a crisis. We understand simple processes, but we have no idea how simple processes fit into larger processes." You get that? Molecular biology — the great scientific god of our age, not just the answer to but the explanation for our prayers — in crisis! Not true! A failure! Dead wrong! No wonder that a few years ago, Schadt gave one of his talks at Columbia and five minutes into the speech, a gray biological eminence stood up and said (in Eric's telling), "How dare you dismiss all the biology that has made us so successful today? My recommendation to everyone in this audience is not to listen to what this man has to say."
The gentleman then turned and walked out, in front of a few hundred people. But here's the deal: Everybody else stayed. And listened. Because you see, at the time, Eric Schadt was working for Merck and was already getting a reputation as the guy who was remaking Merck from the inside out. And because Schadt's not just (or even) a critic, not some apocalyptic scold. He's funny. He's a real character. He's the life of the party, with a line of bullshit he likes to call bullshit, a mad motormouthed charisma that he combines with a mad cackling awareness of the absurdity of all intellectual endeavor, especially his own. He has a shtick, a pitch, but he also has a vision, and that's what he's selling, with evangelical fervor. And the vision, basically, is this:
Okay, so focusing on one gene at a time doesn't work, doesn't explain what causes disease, indeed falsifies the causes of disease and makes it nearly impossible to develop the drugs we need to cure it. So how about focusing on thousands of genes at a time? How about focusing on thousands of genes and thousands of proteins with some enzymes and environmental factors thrown in for good measure? How about getting bigger instead of getting smaller? How about going for complexity instead of simplicity? How about implicating not single genes and single pathways of proteins in disease but whole vast networks of genes and proteins — networks that have been invisible to us until now? How about taking advantage of the technology and the data that's become available over the past ten years and using it to create models of the living world that are nearly as complex as the living world itself and by God nearly as large? Oh, sure, it sounds impossible. Maybe it is impossible. But that's why Eric Schadt wants not just to remake the underpinnings of biological science but rather to remake science itself — the way it's done. Okay, so the complexity of living systems — and the amount of data they generate — turns out to be too much for even the most heroic of individual scientists to master. All right then: Biologists have to form networks that mimic the biological networks they're studying. The networks between genes and proteins turn out to be organized socially, like human networks, and so human social networks will be required to understand them ... with Eric Schadt at their center/
Basically, most anecdotes about Eric Schadt involve the two things that have enabled him to be both highly connected and a revolutionary — smarts and salesmanship. For example, here's how he met his wife. He was a graduate student at UC Davis, going for his Ph.D. in pure mathematics. Pure math is the hardest, most abstract and conceptually demanding discipline you can find, which is why Eric was studying it, and why a young woman named Jennifer Harkness one night gave him a call. She was a freshman with nothing to do, and she and her friends were making prank phone calls. The phone rang, Eric picked it up, and he heard a voice say, "Hi, this is Jenny." He said instantly, "Hi, Jenny — is this a prank phone call?" Jenny and her friends started screaming; they couldn't figure how he'd figured out what they were doing. He explained that he was an inveterate prank caller himself — he liked calling seismologists and telling them that he was feeling tremors — and when Jennifer stayed on the line, he found out that she was, like him, from Michigan, and they had some things in common... .
He made the sale, in other words, and now he and Jennifer live in Palo Alto, California, with their five blond kids, the big sprawling brood that inevitably causes other scientists to remark, "Oh, you're an optimist!" when he tells them about it and also prompts him to articulate an elemental personal philosophy when he's sitting at his big dining-room table one morning, trying to finish another of his groundbreaking papers while bouncing his five-year-old daughter in his lap and at the same time checking his oldest son's math homework — "I can never do too much of anything. Bring it on, baby." He's forty-six years old, and he has the moonfaced swagger of a former child star, albeit one who grew up to be a football blocking back. He's stocky and strong, with a knobby nose and an imposingly lumpy brow and a disheveled head of brown hair spit-curled to his forehead by the sweat induced by his Herculean labors. Think Jack Black in a white lab coat and you get the picture ... except that he doesn't wear a lab coat. He's developed his own standardized scientific uniform — a white tennis shirt with a dark-blue Polo insignia and a pair of hiking shorts — and he wears it as faithfully as Steve Jobs wears blue jeans and a black mock turtleneck. He wears it when you see him in the morning and he wears it when you see him at night, so that you don't really know if he's ever gone to sleep or ever changed, and he even wears it when he takes his motorcycle to work, though the motorcycle is to motorcycles exactly what Eric Schadt is to biology — a baroque exaggeration of normal capabilities that either promises deliverance or threatens obliteration. But let Eric, who's something of a gearhead in both the civilian and scientific aspects of his life, describe the specifications of the BMW S 1000 RR:
"Four hundred pounds, 200 horsepower, the fastest thing out there, zero to 60 in 2.9 seconds, the first superbike." Well, at least he wears a helmet — and not just a helmet but a big black-visored one with a video camera rigged on top so that he can record the sublime experience of riding his superbike or the inevitably annihilating experience of being run off the road and crashing it. "People don't like being passed," he worries, but of course he passes them anyway on the way to work, hitting 100 miles per hour on the street and 120 miles per hour at the office park and popping the occasional celebratory wheelie in nothing but the white shirt, the short pants, and the mitered black helmet that makes him look like some kind of postmodern grenadier, sporting technological plumage.
And then, when he gets to work, three miles from his house, he gets to ride something that goes even faster.
He's one of those guys with a coveted brain, so he's one of those guys with a lot of gigs. He's cofounder of a nonprofit organization called Sage Bionetworks, which is dedicated to facilitating biological research through an open-source sharing of data. He's been trying to start his own institute — the catchily titled Institute for Multi Scale Biology — at the University of California, San Francisco, though he's constantly getting wooed, and it seems inevitable that he'll wind up with a big academic appointment somewhere, along with what's known as "massive institutional support" — i.e., a lot of money. There's a lot of money in biology, and Schadt, like a lot of other brilliant minds for hire, spends a lot of his time chasing it, making his pitch to the venture capitalists in and around the Bay Area or else going up to Seattle and making his pitch to the Gates Foundation and to Microsoft cofounder Paul Allen. "I think I must amuse Paul," Schadt says. "He keeps on inviting me up there, and he never gives me any money."
He does, however, have a regular job, with somewhat regular hours, and that's his job as chief scientific officer of a seven-year-old biotech company called Pacific Biosciences. It's a pretty interesting job, because basically Pacific Biosciences hired him the way a big-time Nascar team hires a driver — that is, because it has this miraculous machine, and it wants someone to drive it really, really fast. Schadt had just left Merck and could have gone almost anywhere he wanted — Yale wanted him to start a systems-biology department, and Genentech wanted him as its head of genetic research, a story that harkens once again to the constants of smarts and salesmanship: "When I was interviewing for that job, the head of the company's research department said, 'You're either completely full of shit or the smartest person on earth. We're not smart enough to know. But we're willing to bet that you're the smartest person on earth.' "
He wound up going to PacBio instead, even though it was essentially a start-up whose fortunes were and are tied to a machine called the RS, which stands for "real-time sequencer" but which is really an homage to "Rally Sport" and a nod to the fact that the people who run the company are really into California car culture. Schadt had heard of the RS when he was at Merck — he had heard that a scientist at Cornell named Stephen Turner had created a technology that could look at individual molecules of DNA in real time and was trying to take it into production. Schadt never thought he'd pull it off but realized that if he did ... well, the technology would be to some enterprising biologist what the telescope was to Galileo — a chance to corroborate what was a mathematical inference, a chance to see "changes in DNA causing changes in cellular networks causing changes in tissue networks going up to the whole organism." And then, in 2008, PacBio gave him a call. Turner's technology was now the RS, a $260 million triumph of engineering, design, and the kind of precautionary prophylaxis that's usually implemented around Level 4 biohazards. Would Schadt like to take it for a spin? Oh, hell yes — it was a job offer that satisfied the gearhead in him, the daredevil, the biologist who thinks like an astronomer, and, not incidentally, the salesman. Indeed, in his job as PacBio's top scientist, Schadt is a cross between Galileo, a paid thinker at someplace like the Santa Fe Institute, and a guy hawking ultra-high-end copiers. Yes, he's already glimpsed some things with the PacBio RS — he's looking to prove that instead of four bases making up the DNA molecule, there are actually so many modifications of the four that the real number could be more than twenty. (It's a perfect Eric Schadt breakthrough, because not only would it be a "game changer," it would also complicate the practice of biology beyond human capability.) But Schadt's also on the road a lot and on the phone a lot, because PacBio hired him not only to figure out the best experimental applications for the RS but also to "work your collaborations like you've been doing" — because it was his collaborative nature, his connectivity, that was at the heart of his attempt to remake the scientific culture at Merck. And that's where he's happiest. He's not the solitary scientist heroically thinking big thoughts. What he does at PacBio is his "vision of the perfect life" precisely because he's hardly ever alone, precisely because after "thinking of the things I want to think about," he gets to "travel around and talk them over with the most interesting people in the world."
He's all about the network, you see. He's helped identify it as the fundamental organizing principle of biological systems, and he sees very little difference between biological networks and social ones. When you look at biological networks comprised of thousands of genes, you'll see that they are just like social ones, with a few "highly connected" genes showing up again and again as "hub nodes" and others acting as spokes and outliers. Well, Schadt's ambition is to be a hub node. And PacBio allows him to realize his ambition because now not only is he Eric Fricking Schadt, but he's also got the machine that nobody else in the world has — the telescope, the souped-up gene sequencer, the RS. People call him out of the blue. He picks up the phone. And if their interest sounds interesting enough, he says yes, even when — hell, especially when — he already has too many projects to handle. Bring it on, baby. So now he's got collaborations going on with people at Harvard, Stanford, Columbia, Northwestern, UCLA, UC San Diego, UC San Francisco, the University of Washington, the University of Colorado, and the University of God Knows Where Else. He's got collaborations going that are intended to target the relevant biological networks behind cancer, heart disease, aging, diabetes, and sleeping problems. He's even collaborating with a scientist who's trying to extract energy from bacteria. And back in November, he got a call from a team at Harvard that was trying to figure out the strain of cholera that was ripping the guts out of Haiti almost a year after the earthquake. They'd heard about him. Could he help? Moreover, could the PacBio RS help? So here's what happened: They sent him the cholera strain from the cell culture, and he ran it through the RS. And four weeks after he received the samples, The New England Journal of Medicine published his paper with the results. A month, man. That's instantaneous in the world of biology. That's unprecedented. Turns out the strain of cholera originated in South Asia, and that information now makes a mass-vaccination plan feasible.
But this is also part of Schadt's vision — part of his pitch, part of what he's selling. He's worked at two big drug companies, Roche and Merck, and he knows what they're good at and knows what they're bad at. What they're good at: making drugs. What they're bad at: sharing. Unfortunately, what they're bad at sharing is the information that would help them make better drugs. But Eric Schadt is the strange rebel who happens to play well with others. He's the strange outlier who wants nothing more than to be a hub node. If anything, he overshares, and so what he wants to do is convince biologists to share for those who can't. In all his collaborations, he says, "we don't have as clear a path in getting drugs developed as in a pharmaceutical setting," so what he and his collaborators are doing is "publishing papers so that anyone can pursue them for whatever reason" — i.e., so that drug companies can use the ideas in them to make better drugs. And this is the idea that really gets Schadt going. Eric Schadt's the biggest thinker in biology, but meeting him sometimes feels like meeting Einstein and finding out that what he really liked about physics was the parties, like meeting Niels Bohr and having to look at his autograph collection. But that's why this is Schadt's moment: because he is out to erase the distinctions between intellectual force, technological force, and social force. Because as the Age of Information inexorably morphs into the Age of Information Overload, he's figured out that social force is the key to science's survival. And because when you ask him his grandest aim, his most cherished ambition, what he really wants to be, he answers, without hesitation, is a "master of information."
He never mentions the word science at all.
He wasn't supposed to be a scientist, anyway. Literally. It was, like, forbidden. It was ungodly. He grew up in Stevensville, Michigan, a town of a thousand people one mile square. His family was hardcore evangelical. His stepfather was a hard man, a believer, and a beautician, in roughly that order. Was Eric Schadt a believer? "Of course I was. I had no choice." Education was suspect — "I had no education to speak of." And so although he went to high school, what he calls the "greatest compliment I ever received" came when a teacher pronounced him "untamable," and as soon as he graduated, he was gone. He joined the Air Force, only to realize that instead of escaping the social and intellectual poverty of his background, he had planted himself "on the lowest rung of an organization that people in society already regarded as the lowest rung." His answer: step one, "I became profoundly depressed." Step two: He did the hardest thing he could think of doing, which was joining Special Operations. Parachute rescue. But he blew out his shoulder rappelling down a cliff, so he washed out. The Air Force looked to salvage its investment by giving him a battery of aptitude tests. When the results came back, he was asked if math had come easily to him in high school.
"Yeah, I guess so," he said. "Well, look at your scores," the Air Force said, and sent him to Cal Poly on a military scholarship.
He studied computer science and applied math at Cal Poly, and it was like taking a drug. Education itself blew a mind hungry for expansion. It wasn't just math. It was ... enlightenment. He came home, started talking about logic and philosophy, started posing "thought experiments" to his brothers and sisters. His stepfather kicked him out of the house. What he said, in Eric's recollection: "You are of the devil. Leave and never come back." Eric's answer, of course, was to do the hardest thing he could think of doing, even after his mother called a year and a half later and invited him back into the fold. He went to UC Davis to get a doctorate in pure math. Pure math: a purely conceptual exercise that takes place in purely abstract space. That's why they call it pure. But he kept learning real-world things from it. The first was how to sell something intellectually ambitious, even impossible: "People don't understand, but if you can make them think you understand, your story wins." The second was what he wanted to do with his life. He was still a Christian in orientation, if not in practice, and pure math, after a while, started feeling, well, "a little empty," even ungodly. It wasn't going to help anyone. So he passed his Ph.D. candidacy tests but never wrote his dissertation and instead enrolled in UCLA's biomathematics Ph.D. program. He had the math for it, certainly, but since he hadn't taken a biology course since high school, he had to learn Ph.D.-level biology "from scratch." To catch up, he began reading through the basic textbooks in genetics and molecular biology on his own. Sounds hard. It wasn't. Pure math was hard. Biology? "It was so easy, it was like a vacation. After pure math it was so refreshing and conceptually simple that my mind just locked onto it."
Indeed, biology was so simple that he began to suspect that what was in the textbooks was simplified, even simplistic. He began to suspect there was something wrong with it, molecular biology in particular. As a former creationist, he immediately saw the insufficiency of a biology of broken pieces, and as a man of broken faith he wondered whether he could put it back together again.
There's a famous book, written by Thomas S. Kuhn and published in 1962, called The Structure of Scientific Revolutions. Well, maybe it's not so famous — but it's hugely influential. It introduced the term "paradigm shift" into the language. A promiscuous term, as it turns out, used to describe everything from the emergence of smartphones to the omnipresence of the spread offense in college football. But in Kuhn's book it describes something specific to science. According to Kuhn, scientific progress is not a peaceful process, characterized by the gradual accumulation of knowledge. Rather, it's a nearly political one, characterized by acts of intellectual violence. A paradigm is like a king — it's the body of knowledge and practice that coheres around a theory or a discovery, and in periods of stability everybody serves it by practicing what Kuhn calls "normal science." Eventually, though, it becomes insufficient to its own ends and enters a period of crisis, during which it comes under attack by those practicing "extraordinary science." At last, the king is overthrown, and that's a paradigm shift.
Has Schadt read Kuhn's book? "I remember the exact month, almost the exact day I started reading that. It was when I first started graduate school in 1993." And of course, he knew what kind of science he wanted to practice even before he knew what king he wanted to kill. A paradigm shift requires not only scientists practicing extraordinary science; it requires "attackers" and "persuaders" willing to declaim the end of the old order and announce the dawn of the new. Schadt has turned out to be both. He's very aware that biology is in the middle of a paradigm shift and very aware of his role in both the murder of molecular biology — the king is dead! — and the establishment of its successor. He's even produced a documentary film entitled The New Biology, which heralds the arrival of a biology that's "more like physics" and "more quantitative in nature" than biology has ever been. Not incidentally, it's also a whole lot harder.
He was doing New Biology even before he got his Ph.D. from UCLA in 1999. Big Pharma, in the form of Roche, had recruited him. He was thirty-three years old, just another brilliant nobody, but he started improving the algorithms on the "gene chips" Roche used for gene detection and sharing them publicly. That gave him a name; it also got him investigated by the U. S. Attorney's office under suspicion of stealing trade secrets, because nobody could believe that he was picking the lock on proprietary algorithms without resorting to illegal means. He was cleared when investigators found out that, well, as a matter of fact, he could. Still, it was the start of his career, and he'd already seen "the amount of energy devoted to keeping you from breaking out of accepted paradigms. It was an extraordinary amount of energy. But the cool thing about the human spirit is its ability to push and persist if it thinks it's on the right path. And the path I was on was the right path from which to change biology."
Yes, that's right: The guy who wants to change biology now wanted to change biology even then, and eventually his ambition brought him to the attention of Stephen Friend and Leland Hartwell of Rosetta Inpharmatics. They were molecular biologists. To be more precise, they had made history as molecular biologists, Friend becoming the first scientist to clone a human gene associated with inherited tumors and Hartwell winning the damned Nobel Prize. That's all. But they'd thought deeply about molecular biology and had started Rosetta in part to address its inherent limitations, in particular its failure to deliver drugs to the marketplace. They were looking for the future. And so when Stephen Friend met Eric Schadt, he saw a scientist with "almost Mozart-like qualities — insights that are not always logical, but they're correct. You talked to Eric and you said to yourself, Oh, my God, I can see what's going to come."
Schadt went to Rosetta, and then, when Merck bought Rosetta, he went with Friend and a team of fifty nascent New Biologists to Merck. At the time, Merck was a molecular-biology company. It was using the basic techniques of molecular biology to figure what proteins to target and what drugs to develop. The main technique is called a "knockout study." A scientist interested in the function of a specific gene "knocks out" the gene in mice bred for the purpose, to see what happens. Schadt and Friend thought the strategy was hopeless. Not only are there twenty-three thousand genes to be knocked out one gene at a time, there are also catastrophic side effects when the drug you develop to hit a single protein encoded by a single gene instead hits a network of genes and proteins all working together in mysterious and invisible concert.
The idea of networks was not original to Schadt. What was original to Schadt, however, was a method for finding them and proving their existence. How could he find something that was not only invisible but indescribably vast, involving thousands of genes and thousands of proteins? Well, the sky is vast, and astronomers can't see the planets orbiting distant stars, either. But they prove their existence by measuring the changes in starlight and subjecting the data to statistical analysis. They never see the new planets — the whole new solar systems — they're exploring. They just know they're out there, in the numberless flickerings of the stars.
And that's how Schadt proved the existence of biological networks. He developed algorithms to mine Merck's massive troves of biological data, and he began finding genetic networks through statistical correlations. Were the networks merely theoretical? To the contrary: They were "highly predictive" experimentally — that is, they could predict the success or failure of therapeutic interventions. And so in 2003, he started publishing the papers that, in the words of a Merck spokesman, "changed the way people looked at disease," and at the same time became the foundations of the New Biology. What's more, he and his team began using the networks they were finding to figure out which genes Merck should target, until they were responsible for "half the drugs" in Merck's pipeline. What's more, long before GlaxoSmithKline ran into problems with Avandia, Schadt predicted that a similar drug Merck was developing would fail for the same reasons — because it would lower the risk of diabetes but increase the risk for cardiovascular problems — and therefore proved that the New Biology could save pharmaceutical companies billions of dollars. And then, of course, he and Friend tried to turn Merck into a New Biology company, by which they meant a company that would share its data with networks of outside scientists and that would develop drugs that targeted networks instead of single genes. The problem with that: Merck was still an old biology company. The drugs in its pipeline — including the drugs informed by Schadt's networks — targeted single genes. And so when Schadt and Friend made their presentation, this was Merck's response: "We're not an information company." And when, in 2009, Schadt published a paper in Nature entitled "A Network View of Disease and Compound Screening" — a paper that implied that drugs targeting single genes were doomed to failure — "well, that was the paper that got me kicked out of Merck."
He likes to do his supercomputing on planes now, because that's the one place where he's alone. He had access to a supercomputer at Merck, but he and Friend left Merck in 2009 after negotiating an agreement to take the New Biology component with them — including the millions of dollars' worth of data necessary to continue their work — and turn it into Sage Bionetworks. He still needs the capacity of a supercomputer, however, because the amount of data generated by the networks he's exploring is inordinate, overwhelming. There's terabytes of data, petabytes of data. Fortunately, he has the same access to supercomputers that every other American with an Internet connection and a credit card has. He waits till the plane climbs to a cruising altitude, waits for the pilot to allow electronic devices, and then uses the plane's WiFi to get on Amazon. Amazon sells a lot of stuff — books, washing machines, whatever the hell you want. What it sells Schadt is super-computing on the cheap. You see, companies like Amazon have a lot of computing power available, and now it's gotten in the business of selling some of that to guys like Schadt and whoever else might want it. A guy like Schadt doesn't have to work for a company like Merck anymore, because he has as much computing power available to him on an airplane as a scientist at Merck does on the company's multimillion-dollar supercomputer. More even. On cross-country flights he tells Amazon what data to crunch after takeoff, and for a few hundred bucks the job's done by the time he lands.
He likes to talk about this kind of stuff, because it's one of the ways he makes his sale. A lot of people are afraid of the Age of Information. They think things are getting too big and too complicated, and going too fast. You think scientists are immune? You think biologists are immune? No, they're especially anxious, because biology has turned out to be even more complex than they thought, indeed precisely as complex as the world in general. And so what Schadt has done is not only give biologists the tools to deal with the problem of increasing complexity; he's also sold complexity and has gotten biologists to relax and embrace it, in the words of Stephen Friend. "And it's a good thing, because the complexity is just going to get worse. But Eric gets you to understand that it's out of complexity that a pattern derives. That complexity is not the enemy but the vehicle of understanding, and embracing it is how you get there. You talk to him and he makes you think, Oh, this might turn out all right after all."
Schadt has sold the New Biology by making biologists feel that if they change biology, they can change the world. But he also makes it clear that as the world changes, it will change biology, whether biologists like it or not — whether we like it or not. For instance, he has this idea for what he calls a "disease weather map" that will inform people what kind of pathogens are on the handrails of the escalators, say, at the San Francisco Airport, or for that matter in the bathrooms. The idea would have been laughable just a few years ago, but Schadt is not only thinking about it — he's doing it, with the PacBio RS. He's sending out technicians, getting samples, and sequencing them more or less instantly. This is an extension of Schadt's vision to expand the network model of human disease into tracking the forces of infection in the population at large; the network is not just genes, it's also germs. He's able to do the same with sewage outflows, which has led him to a vision of monitoring the pathogens that pour out of individual households — a vision of helpful technicians knowing what's coming out of your toilets, and calling you if they think you need to eat more yogurt.
Does anybody want a world of pathogen surveillance and transparent effluvia? Well, DARPA does, Schadt says — they're very interested. And he's not overly concerned about everybody else. He's a revolutionary, and what he knows about revolutions — scientific and otherwise — is that "it's best to be one of the drivers of the revolution, and then it will work itself out." What he knows about revolutions is that "there's always this outcry, but the revolution marches on. And I would rather be part of the revolution than on the outside figuring out what it all means."
And that's what Eric Schadt's really all about — why he wants to be a "master of information" instead of simply a scientist. The New Biology is the New World, and he wants to be part of both. He wants to be one of the people who help other people figure out that information overload is not the enemy, if you know how to read it (and have supercomputer access). He wants to be part of what he calls "a revolution in human intelligence." He wants to make the sale, even if what he's selling is what so many fear. The world is getting too big? Make it bigger. The world is getting too fast? Make it faster. The world is getting complex to the point of impossibility? Bring it on, baby.
Bring it on.
Read more: http://www.esquire.com/features/eric-schadt-profile-0411-3#ixzz1HpNA1mta
[One left - but all others stayed. Genes/Junk failed Genomics, by now Mattick, Simons, Pellionisz, Collins, Lander and Schadt are in unisone. See my 2008 Google Tech Talk YouTube currently with 10,138 views - some mediocre minds dismissing anybody with a paradigm-shift as a "kook". (Giordano Bruno was torched, and his ashes thrown into the Tiberis - with the Vatican correcting the course some 300 years later. In modern times, Barbara McClintock had to reach the age 83 to get her Nobel, decades after her discovery). This entry can be commented on the FaceBook page of Andras Pellionisz]
Global Scaling Institute of Germany Explores Roots of Fractals with Euler
Leonhard Euler was one of the greatest mathematicians of all times. He developed the basics of the modern theory of numbers and algebra, the topology, the probability calculus and combinatorics, the integral calculus, the theory of the diffenrential equation and the differential geometry, the variational calculus and he discovered the coherence between trigonometrical functions and exponential functions. Leonard Euler developed the hydrodynamics and fluidic, he made the bases for the theory of the gyroscope. He was a brilliant natural scientist, an excellent teacher and mentor.It was on April 24th, 1727 when on invitation of the Russian czarina Katharina I the 19-year-old master Leonhard Euler left his home town of Basel and set off for a brillant scientific career at the Academy of the Sciences of Russia. The brothers Bernoulli (Nikolai and Daniel), Christian Goldbach and other excellent European scientist already worked there.Peter I engaged the philosopher and mathematician Christian Wolf from Marburg shortly before his death to unite the best heads of Europe under the seal of Academy of the Sciences of St. Petersburg.
In May 1771 an enormous blaze raged through St. Petersburg. Hundreds of buildings burned down, among others the house of the graduate Leonard Euler. But the basler craftsman Peter Grimm succeeded in saving the 64-year-old blind mathematician from death by burning. Thanks to his courageous intervention almost all manuscripts of the greatest mathematician of all times remained for the posterity. Among others also the work “About continued fractions” (1737) and “About the vibrations of a string” (1748). In these papers Euler formulated theses whose solution would keep mathematics busy for 200 years to come. Eulers work made it possible 250 years later to air one of the most fundamental secrets of nature – the free vibrations of the universe.
Euler examined already free vibrations of an elastic thread with no mass occupied with pearls. In connection with this task d’Alembert developed his integration method for a system of linear differential equations. Starting out from there Daniel Bernoulli put forward his famous theorem that the solution for the problem of a free vibrating string can be portrayed as a trigonometrical series, which lead to a discussion between Euler, d’Alembert and D. Bernoulli which spread over few decades. Later on Langarne pointed out more correctly, how one can come to a solution of the problem of swinging string of beads to the solution of the problem of the vibrating of a homogeneous string by breaching the limit. Only in 1822 J. B. Fourier in solved this formulation completely for the first time.
Meanwhile, nearly insurmoutable problems still arose with pearls of various mass and irregular distribution. This task leads to functions with gaps. According to a letter of Charles Hermite of May 20th, 1893, which called to “reject the lamentable plague of the functions without derivations in fright and fear “, T. Stieltjes examined functions with discontinuities and found an integration method of such functions, which led to continued fractions.
Meanwhile, Euler already recognized that complicated vibrating systems can contain also such solutions (integrals) which aren't differentiating everywhere and left to the mathematically talented posterity an analytic monster – the so called non-analytic functions (this term was chosen by himself). Non-analytic functions have ensured a lot of work up until the 20th century, even after the identity crisis of the mathematics seemed to be already overcome.
The crisis started, as E. du Bois Reymond 1875 reported for the first time about a steady, but not subtly differentiable function designed by Weierstrass, and lasted approximately till 1925. Their dominant players were Cantor, Peano, Lebesgue and Hausdorff. As result a new branch of the mathematics was given a birth – the fractal geometry.
Fractal comes from the Latin fractus and means as much as “in pieces broken” and “irregular”. [We already know since 2002 that Gene/Junk is scientifically incorrect; thus FractoGene, with its self-similar repetitions - AJP]. So fractal are really incomplete, spiteful mathematical objects. The mathematics of the 19th century took these objects for exceptions and therefore looked at regular, steady and smooth structures or tried to put down fractal phenomenons to such structures.
The theory of the fractal quantities made it possible to examine strictly “not analytic” creased, granulous or incomplete forms qualitatively. Soon it turnes out that fractal structures aren't that rare at all. In nature one discovered more fractal objects than suspected till now. More, it seemed so as if suddenly the universe was fractal by nature.
Especially the works of Mandelbrot placed the geometry finally in a position capable of describing correctly fractal mathematical objects: incomplete crystal lattices, the Brown’s movement of the gas molecules, sinuous polymer giant molecules, irregular star clusters, Cirrus clouds, the saturn rings, the distribution of the lunar craters, turbulences within liquids, bizarre shorelines, winding river courses, folded mountain ranges, branched forms of growth of most different plant sorts, areas of islands and seas, rock formations, geological depositions, the spatial distribution of raw material occurrences and so on and so on.
The Leningrad mathematicians F. R. Gantmacher and M. G. Krein looked 1950 at the deflection line of a vibrating string with pearls as partitioned line. Just this attempt made it possible for them to view the problem in a fractal way without being conscious of it (Mandelbrot’s classic “Le Objets Fractals” appeared 1975, his first works from 50’s fell into the linguistics school). Only the fractal view put them to the position to completely solve (also for the most general case) the 200 years old Euler’s problem of the vibrating string of beads for pearls of various masses and irregular distribution. In their work “Oscillation-Matrixes, Oscillation-Cores and Small Vibrations of Mechanical Systems” they proved, that all free vibrations form a finite string of beads or string a finite or infinite Stieltjes-continued fraction. The masses of the pearls and the separations between them are identical with the part denominators of the continued fraction.
1955 V. P. Terskich generalized the (as regards content fractal) continued fraction method on vibrations of complicated branched chain systems. The classic work of T. N. Thiele, A. A. Markov, A. J. Chintchin, O. Perron, J. A. Murphy, M. R. O'Donohoe, A. N. Chovansky, H. S. Wall, D. I. Bodnar, C. I. Kucminskaja, V. J. Skorobogat'ko and others helped to get the definite breakthrough for the continued fraction method and made the development of efficient algorithms possible for the addition and multiplication of continued fractions up till 1981.
Mathematical models of vibrating fractal chain systems are used with great success in the most different scientific fields today. Their popularity reached a highlight already in the sixties in the electrotechnical engineering. The fast development of the computer branch during the last decades have to be put down to the efficiency of such models in the solid state physics. One discovered vibrating fractal chain systems also in neural networks, our genome and eco-systems.
The complete universe is a vibrating fractal chain system, what can be compared mathematically with the free vibrations of a Euler’s string of beads of gigantic proportion. The natural oscillations of matter influence not only the temporal course of all physical, chemical, biological and social processes, but it is also a global morphogenetical factor and cause for a global selection process. Their frequency spectrum is logarithmic fractal.
Leonard Euler left about 900 scientific work, among others:
Mechanica 1736)
Über Kettenbrüche (1737)
Tentamen novae musicae (1739)
Theorie der Planetenbewegung (1744)
Neue Grundsätze der Artillerie (1745)
Nova theoria lucis et colorum (1746)
Über die Schwingungen einer Saite (1748)
Introductio in analysin infinitorum (1748)
Theorie des Schiffbaues (1749)
Institutiones calculi differentialis (1755)
Institutiones calculi integralis (1770)
Vollständige Anleitung zur Algebra (1770)
Lettres · une princesse d'Allemagne sur quelques sujets de Phsique et Philosophie (1772)
Dioptrica (1771)
[Genomics will yield to FractoGene Mathematical Theory and its immediate applications of how the fractal genome violates its own mathematical rules - triggering hereditary syndromes. Understanding of the scaling (identification of the System as a seemingly complex fractal hierarchy) enables targeted search for "fractal defects" - rather than searching in a haystack for something that we can't even define as a needle. Soon, Institutes will spring up to devote the type of attention this paradigm-shift has the power of yielding, by software-enabling algorithms, deployed by defense-, financial-, graphics-, seismic-, meteorological-, cryptographical-, etc. already validated HPC appliations to Genomics (the busines of HolGenTech, Inc.). This entry can be commented on the FaceBook page of Andras Pellionisz]
Avesthagen launches Whole Genome Scanning
IBNlive
PTI | 04:03 PM,Mar 22,2011
Bangalore, Mar 22 (PTI) Bangalore-headquartered Avesthagen Limited launched its Whole Genome Scanning (WGS) service in India today, which will provide an individual a list of the diseases to which the person is predisposed, such as cancer, diabetes and Alzheimer's, in return for a payment.
A whole genome scan of an individual would provide information to understand his/her own genetic make-up that would lead to an increased awareness about the predisposition to the disease(s), the company said in a statement.
The diseases that would be covered by the scan include major types of cancer, cardiovascular diseases, diabetes, schizophrenia, Alzheimer's, asthma and arthritis, it said.
The total cost of the WGS would be Rs 45,000 [about $1,000 - AJP] which is subject to revision based on volume, the company said. The scan would be carried out on DNA extracted from saliva/buccal swab provided by the individual, the company said.
The report would consist of a list of the various diseases to which the person is predisposed, and risk ratio of the disease occurrence and the association of the disease to the mutation, it added. "The technology platform at Avesthagen is able to interrogate the genetic markers (SNPs and CNVs) across an individual's genome to decipher the association of the markers to the diseases", it said. "By employing a streamlined sample collection and delivery system, Indian customers will now have access to personalised genomics services, which until now were only available in the developed markets", the company said. Avesthagen said it would leverage its expertise in genomics technology and state-of-the-art high throughput facilities for carrying out genomic analysis. The facility can process 200 samples per month, the statement said. Explaining about DNA, the company said every organism, including humans, has a genome encoded by deoxyribonucleic acid (DNA) that contains the biological information needed to build and maintain a living example of that organism. DNA is essentially made of four kinds of molecules, called bases, it said. The bases are arranged in a sequential order to form a unit known as gene. The triplet of bases in the gene encode for amino acids that are building blocks of proteins that carry out most of the cellular activities, it said. A change/mutation in the base-pair sequence of the gene(s) could indicate that either certain proteins are not formed or are processed differently, which may result in disease, it said. Measuring the mutation in the genes could tell us the risk (predisposition) of getting a particular disease in his/her lifetime, it said, adding disease risk is one way of describing the likelihood of a person developing a particular disease.
Renaissance Herbs was founded in 1990 by Alex Moffett. In 1994, the Company formed a wholly owned subsidiary, Dhanvantari Botanicals, Pvt., Ltd and built a 50,000 square foot state-of-the-art manufacturing and research and development facility in Bangalore, India. This fully certified cGMP facility has won numerous Nutrition Business Journal awards and is one the very first factories of its type in the world to achieve ISO 22000-2005 and “Certified Organic” processing certification.
Avesthagen Ltd, Bangalore, India purchased all outstanding shares of Renaissance Herbs company stock in 2007. The merger and acquisition of Renaissance Herbs supports the fulfillment of Avesthagen’s bionutritional business strategy through vertical integration and significant scientific competencies.
With the acquisition of California-based Renaissance Herbs and their wholly owned Bangalore subsidiary, Dhanvantari Botanicals, Avesthagen has gained a state-of-the-art, 50,000 square foot, nutriceutical manufacturing complex.
In Renaissance, Avesthagen found an industry colleague whose products were based on a blending of the bountiful traditions of Ayurveda with superior modern production and QC methods. They also discovered that they shared a similar corporate spirit that understood sustainability from all perspectives, from the customer, the company employee, and the planet.
[While the description is rather incomplete (e.g. it is unknown if the analysis is based on true full DNA sequencing, or partial interrogation of the full genome by microarray technology), "the genie is out of the bottle" with this news - since the "Silicon Valley" of Bangalore (India) is entirely outside of the jurisdiction of the USA. Thus, hindrances imposed by FDA and other US requlator fervor will not set back DTC as it was entirely banned for some weeks in California, or severely set back by FDA/Congressional hindrance. Another "Sputnik moment" to the US - we either change the ways and means of our investment and operation, or will no longer stay on top of the use of postmodern genomics. This entry can be commented on the FaceBook page of Andras Pellionisz]
Complementing Private Domain Genome Sequencing Industry - the Birth of Genome Analytics Industry
[The three news items on the venerable Partek, Inc. (1993) and two Silicon Valley new companies of HolGenTech, Inc. (linked from the title) and DNAnexus, Inc. signal the birth of the Private Domain Genome Analytics Industry - not totally unlike the venerable IBM and the new start-ups of Microsoft and Apple of the "home computer era". This entry can be commented on the FaceBook page of Andras Pellionisz]
--
Partek Expands Global Operations
March 14, 2011 08:30 AM Eastern Daylight Time
Software Manufacturer Increases Staff in Europe and Asia
Sees Continued Strong Renewal Rate of its Flagship Product, Partek® Genomics Suite™
ST. LOUIS--(BUSINESS WIRE)--Partek Incorporated, a global leader in bioinformatics software, today announced the expansion of its business development and support staff to keep pace with continued demand for its core product offering, Partek Genomics Suite. The company now has personnel throughout Europe — United Kingdom, France, Germany, Spain and Croatia — and a wholly owned subsidiary in Singapore servicing Asia, Australia and New Zealand.
Complementing a strong US-based support team, Partek’s regional managers have extensive expertise in biology and statistics, and are strategically positioned to assist scientists around the globe with analyzing their microarray and next-generation sequencing (NGS) studies. In addition to its direct operations, Partek also maintains partnerships with local distributors in more than a dozen countries, and worldwide reseller agreements with genomics device manufacturers Life Technologies Corporation and Affymetrix, Inc.
“It’s an exciting time at Partek, as rapid advances in genomics technology are fueling worldwide demand for software that simplifies and accelerates the data analysis process,” said Tom Downey, President of Partek Incorporated. “We are continuing to see a 95+ percent renewal rate among current Partek Genomics Suite licensees, and significant growth in new markets where NGS adoption is increasing. Our dedication to training and individual user-level support helps further differentiate our offering, and it is opening new doors to researchers seeking both the best-quality software and a knowledgeable team that stands behind it.”
Partek Genomics Suite is a comprehensive solution for the analysis, comparison and integration of massive amounts of genomic data. Used by thousands of scientists worldwide, Partek Genomics Suite was cited in more than 440 peer-reviewed publications in 2010. It is unique in its ability to support all microarray and NGS [Next-Generation Sequencing - AJP] technologies for RNA-, DNA- and gene regulation applications in a single software package, allowing also for the integration of multiple applications in a user-friendly way. Embedded tools for alignment, quality control analysis, robust statistics, clustering, biological interpretation and pathways helps scientists identify biomarkers and patterns in the data with confidence.
About Partek
Partek Incorporated (www.partek.com) develops and globally markets quality software for life sciences research. Its flagship product, Partek® Genomics Suite™, provides innovative solutions for integrated genomics. Partek Genomics Suite is unique in supporting all major microarray and next-generation sequencing platforms. Workflows offer streamlined analysis for: Gene Expression, miRNA Expression, Exon, Copy Number, Allele-Specific Copy Number, LOH, Association, Trio analysis, Tiling, ChIP-Seq, RNA-Seq, DNA-Seq, DNA Methylation and qPCR. Since 1993, Partek, headquartered in St. Louis, Missouri USA, has been turning data into discovery®.
---
Complete Genomics and DNAnexus Work Together to Provide a Scalable Solution for Complete Genomics Data Storage, Visualization and Query
MOUNTAIN VIEW, Calif. and PALO ALTO, Calif., March 14, 2011 (GLOBE NEWSWIRE) -- Complete Genomics Inc. (Nasdaq:GNOM) announced today that its customers can now choose to store and visualize their human genome sequencing data within the cloud-based DNAnexus platform. Furthermore, DNAnexus Inc. will host the publicly available Complete Genomics human genome public datasets and make them available as reference data to all its customers.
Through the DNAnexus platform, Complete Genomics' customers will have access to a suite of powerful and easy-to-use informatics tools, which will allow them to visualize and query multiple complete human genomes and focus on relevant findings. For example, structural variations, copy number variations and small variants detected by Complete Genomics can be simultaneously visualized in the DNAnexus Genome Browser allowing researchers to gain further insights from these important genomic elements. This new workflow has been extremely well-received by Complete Genomics customers who gained early access to the cloud-based solution as part of a beta-testing program.
"As we continue to refine our genome sequencing service, we want to make sure that our customers have access to the best tools available to interpret the rich datasets that we provide," said Mark Sutherland, senior vice president of business development at Complete Genomics. "We have worked closely with DNAnexus to ensure that its informatics platform will support our detailed sequence data and thus allow our customers to capitalize on its visualization capabilities."
Built on the robust Amazon Web Services, DNAnexus is a universal platform for analyzing, managing and storing DNA sequencing data. DNAnexus acquires computational and storage resources on demand from Amazon, on behalf of each user, to provide scalability and pricing that mirrors usage, whether a user is investigating one or thousands of genomes.
"Like Complete Genomics, DNAnexus was founded to relieve scientists of the operational, computational and capital purchase burdens associated with advanced sequencing technologies," said Andreas Sundquist, Ph.D., CEO of DNAnexus. "By enabling its customers to access their data via our easy-to-use, Web-based research environment, Complete Genomics is allowing them to expand their compute and storage infrastructure on demand and streamline access to the sophisticated informatics necessary to quickly access and interpret their sequencing data."
Moving forward, DNAnexus will integrate Complete Genomics Analysis Tools (CGA™ Tools) functionality into DNAnexus, further enabling customers to interrogate their data. The integration of the CGA Tools, an open source software project that provides solutions for downstream analysis of data produced by Complete Genomics, will allow researchers to take on complex multigenome comparisons.
Additional product information and details on how to upload, store and visualize Complete Genomics data within DNAnexus are available at http://www.completegenomics.com/customer-support/partners/DNAnexus.
About Complete Genomics
Complete Genomics is a complete human genome sequencing company that has developed and commercialized an innovative DNA sequencing platform. The Complete Genomics Analysis Platform (CGA™ Platform) combines Complete Genomics' proprietary human genome sequencing technology with our advanced informatics and data management software. We offer this solution as an innovative, end-to-end, outsourced service, CGA™ Service, and provide customers with data that is immediately ready to be used for genome-based research. Additional information can be found at http://www.completegenomics.com.
The Complete Genomics logo is available at http://www.globenewswire.com/newsroom/prs/?pkgid=8216
About DNAnexus Inc.
DNAnexus combines a cloud computing infrastructure with scalable systems design and advanced bioinformatics to address the data storage, management, analysis and visualization challenges inherent in next-generation DNA sequencing. By leveraging the cloud, the company has created a flexible platform that evolves with emerging sequencing technologies and research applications and scales to support the computational infrastructure needs of researchers and sequencing service providers alike. For more information please visit https://dnanexus.com.
[The emerging Industrialization of Genomics by the private domain already generated a slew of Genome Sequencing Companies (Illumina, 454/Roche, Life Technologies (now with Ion Torrents) - all in the USA, plus e.g. Oxford Nanopore in the UK - altogether several dollar billions of private investments, e.g. by Intel Capital, etc.). Indeed, the Industrialization of Genomics would become unsustainable if Genome Analytics, based on our entirely novel understanding of (Holo)Genome function (c.f. The Principle of Recursive Genome Function), could not match the "demand-side" of the already existing "supply side" (of DNA sequences). Not unlike in the "home computer era", existing venerable companies (IBM) opened a new branch for "PC" - but found a stiff competition from Silicon Valley start-ups with paradigm-shifts put into action. Now, e.g. Partek (1993) opens its new branch from statistical analysis in Life Sciences to HoloGenome Analysis - while DNAnexus start-up is built on the (unsecurable) Cloud Computing (by Amazon Cloud Services) for Genome Analytics for those who forgo privacy in the interest of research. It is noteworthy that the proprietary and open source software systems are likely to be in some conflict. HolGenTech, Inc. leverages defense-validated High-Performance-Computing (e.g. DRCcomputer) to ensure the convergence of three fundamental requirements. (1) All Genome Analytics software must be based on axioms that make a clean break from the half-a-Century-old misunderstanding of the Gene/Junk obsolete views, (2) Just like with defense and financial computing, safeguarding fiercely proprietary algorithms and software is essential for geopolitical, Big Pharma and Private Genome Research reasons, (3) The "Holy Grail" of postmodern genomics is deployment in hospitals of HIPPA-compliant and patient-required privacy of genome-based diagnosis, therapy and up to cure, combined with the vitally important "time critical" speed. These requirements are highly parallel with proven solutions in both defense and financial computing. This entry can be commented on the FaceBook page of Andras Pellionisz]
Scientists need new metaphor for human genome [or better yet, industrialization of the new paradigm - AJP]
The National
Robert Matthews
Last Updated: Mar 13, 2011
The science of genetics has particular importance for Arab populations, [a reference to the ongoing World Conference in Dubai - AJP] among whom inherited conditions are relatively common.
Historically, one major reason for this has been the prevalence of marriages between cousins. Less well-known is the fact that some genetic conditions were once beneficial for those living in this part of the world - notably the blood disorder sickle cell anaemia, which confers protection against malaria.
Once upon a time, those attending meetings like this four-day event would tell anyone who would listen that victory against such lethal conditions was now in sight. Such optimism flowed from one of the most trumpeted scientific breakthroughs of the past half-century: the unveiling in 2000 of the first rough draft of the human genome.
The genome is often described as the "genetic book of human life". Decoding it was predicted to lead to a host of advances, from "personalised" medical treatment to the discovery of genetic risk factors for diseases like cancer - and cures for some genetic diseases.
A decade on, however, the mood of geneticists is far more downbeat, although the quest remains as inspiring as ever. There's no doubt that medicine would be transformed if doctors could tailor drugs and dosage to each individual.
For example, many hundreds of people die each year in the UAE because of adverse drug reactions.
The assumption has been that the root cause of such reactions lies in each person's genes, and the dream has been that one day doctors would simply check a patient's genome and reach for precisely the right drug, confident there would be no side effects.
Yet with very few exceptions, the dream seems more like a mirage. To date, only a small minority of women with invasive breast cancer have benefited from anything close to personalised medicine.
These women carry an overactive gene called Her2/neu, and research has shown that about half of them can benefit from a drug called Herceptin. But this drug has itself been found to increase the risk of heart dysfunction, for reasons unknown.
Genetic researchers have fared little better trying to link genes to common ailments such as heart disease and cancer.
Grand "genome-wide association" (GWA) projects have been set up, with the aim of trawling the genomes of thousands of people. But in return, researchers have been rewarded with a baffling melee of faint trails and dead ends.
The GWA technique first made headlines in 2007, when several different teams unveiled the existence of 12 genetic quirks apparently linked to coronary artery disease, the clogging up of arteries.
The disease has long been linked to factors such as high cholesterol. Yet only a handful of the genetic quirks were linked to these factors; the role of all the others remains a total mystery.
More baffling still, the 12 are all but useless at predicting who will suffer the condition - suggesting that even when their role is tracked down, the information will be of little help.
Just last week the journal Nature Genetics reported the discovery by three independent teams of 18 more genetic quirks linked to coronary artery disease. Even when combined with those previously known, however, experts estimate these genes will explain only about 10 per cent of the risk.
Nowhere is the schism between genome hype and reality starker than in the treatment of inherited diseases.
The quest for a cure began long before the human genome project, with scientists focusing on the simplest disorders, caused by faults in single genes. In 1989, a team at the Hospital for Sick Children in Toronto identified the gene for cystic fibrosis, one of the most common of all genetic diseases.
For years afterwards, geneticists talked of curing this fatal disease simply by replacing the faulty gene, like car mechanics fixing an engine by replacing the spark plugs.
Yet to this day, not a single patient has been cured of cystic fibrosis, or indeed any other common genetic disorder. Their life expectancy has certainly improved - in the case of cystic fibrosis patients, by 10 years or more - but credit for that goes to conventional medicine, not genomic research.
The common thread in this litany of disappointment is the simplistic idea of genes being "for" specific traits.
Researchers who should have known better - including a few Nobel Prize winners - cheerfully foisted this view of genes on the public, the media and worst of all, themselves. Ironically, the best evidence against it has come from the genome project itself.
One of the first discoveries from the project was the amazingly low number of genes in the human genome. Before the project began, most geneticists expected to find at least 100,000 genes.
We now know the true figure is about 23,000 - far fewer than for many parasites. The implications are clear: there is no simple relationship between genes and the living organism they supposedly define. Genes aren't at all like the "words" in a "genetic book of human life".
Metaphor plays a key role in science, defining how entire generations of researchers view their subjects. Physicists once thought of gravity as being some kind of invisible "elastic" between masses, light as made of waves, and electrons as subatomic bullets.
All these metaphors have their uses, but they also have their limits - and the success of physicists owes much to their ability to choose the right metaphor for the job.
For decades, geneticists have tried to emulate the success of physicists, and have taken a reductionist, [Newtonian - AJP] mechanistic view of genes. Their lack of progress in understanding the genome suggests they should spend some time at this week's meeting finding a better metaphor for genes. Lives depend on it.
Robert Matthews is Visiting Reader in Science at Aston University, Birmingham, England.
[Metaphors are fine - but they are no substitutes for new science axioms. "FractoGene" (Pellionisz, 2002) could be understood as a "metaphor" (as the basic materials for buildings) - while the design of what architecture you create from essentially the same set of basic materials resides in the vast majority (in human, 98.7%) of "non-directly coding", formerly "Junk" DNA. Both the fractured (non-contiguous) DNA-structure of directly protein-coding sequences replaced "genes" (that have no universally accepted definition today, other than in terms of FractoGene). Also, the algorithmical (software-enabling) fractal approach to regulation of building fractal hierarchies of organelles (such as brain cells), organs (such as lungs, kidneys), and organisms (e.g. cauliflower Romanesca) can be handled by the mathematical grip of fractal theory - rendering "metaphors" to high-school audience. The huge problem is, of course, that almost a decade after FractoGene, there is no major World Conference where a giant of postmodern Genomics would not raise the cardinal point of obsolete axioms, I did it in Cold Spring Harbor, 2009), Lander did it in 2011 to tell the entire top leadership of NIH that "all basic assumptions were wrong" and the DNA structure was fractal, and now in Dubai Dr. Mattick told the World Organization of HUGO the same, but e.g. the Director of HUGO, who was well aware of FractoGene since the 50th Anniversary of the Double Helix (Monterey, 2003), could only confront e.g. Dr. Mattick with a new descriptive outlook with Dr. Brenner's view of still sticking with the "Junk DNA" (for convenience) - it takes an organizer like George Church to invite directly the innovator(s). Thus, real progress (much beyond "metaphors") is left for China (the BGI commanding 3,000+ informatics & programming specialists with the avery age of 27, thus not affected by Old Obsolete Axioms), India (where engineering dovetails much easier with biology due to tens of thousands of software specialists e.g. in "Silicon Valley of Bangalore). The geopolitical race is well reflected by the 10010+ views of my 2008 "Google Tech YouTube" This entry can be commented on the FaceBook page of Andras Pellionisz]
RNA regulation of human development, cognition and disease (Mattick in Dubai)
It appears that the genetic basis of the programming of human development and cognitive capacity has been misunderstood for the past 50 years, because of the assumption that most genetic information is transacted by proteins. Contrary to the derived assumption that most of the human genome is comprised of evolutionary debris (introns, integenic 'deserts', retrotransposon-derived sequences), it is now evident that essentially the entire genome is dynamically transcribed to produce enormous numbers of regulatory RNAs that control gene expression at various levels, including the site-specificity of the chromatin-modifying complexes that underpin developmental trajectories and cognitive function. Increasing numbers of these regulatory RNAs are being shown to be dysregulated in cancer and other complex diseases. It is also becoming evident that the system has evolved extraordinary plasticity via RNA editing, and that this is the molecular basis of environment-epigenome interactions underpinning brain function and influencing the progression of diseases such as type 2 diabetes. Retrotransposons also appear to contribute to genomic, epigenomic and transcriptomic plasticity, and somatic mosaicism, especially in the brain. Thus, apart from the fact that some genes encode proteins, it appears most orthodox assumptions about human genetic information have been incorrect, and that what was dismissed as 'junk' because it was not understood will hold the key to understanding human evolution, development, variation, cognition and disease.
[Dr. Mattick has long been on record to say that "Junk DNA" was "anything but". The significance of his talk is not that he put forward any mathematical theory for Recursive Genome Function (like others did e.g. in 2008 paper and YouTube (now over 10010 views) - but that following Eric Lander (Science Advisor to US Prez) he told the World Conference in their face that "most othodox assumptions ... have been incorrect". This entry can be commented on the FaceBook page of Andras Pellionisz]
Hamdan Bin Rashid to inaugurate HGM 2011 Monday
Mar 13, 2011 - 04:09 -
WAM DUBAI: H.H Sheikh Hamdan Bin Rashid Al Maktoum, Deputy Ruler of Dubai, UAE Minister of Finance and the Patron of the Sheikh Hamdan Bin Rashid Al Maktoum Award for Medical Sciences (SHAMS), will open the 15th Human Genome Meeting in conjunction with the 4th Pan Arab Human Genetics Conference at Maktoum Hall in Dubai World Trade Centre.
The conference is organized by SHAMS in collaboration with the Human Genome Organisation (HUGO).
Dr. Mahmoud Taleb Al Ali, the Director of the Award's Centre for Arab Genomic Studies and a member of the HGM's Scientific and Organizing Committees praised the unlimited support for the largest gathering of geneticists worldwide by HH Sheikh Hamdan Bin Rashid Al Maktoum.
He said that the eyes of all countries of the world will be tomorrow on UAE, which is the first Arab country to host the HGM through more than two decades, the age of HUGO, whose international headquarter is in Singapore.
"The prestigious status of UAE among world countries has allowed this major scientific event to be held here in Dubai", he added.
He said that 1200 geneticists are expected to participate in the 4-day HGM 2011, during which 480 research papers by 1700 researchers from 66 countries around the world will be discussed.
He also noted that the preparation for this big event has taken considerable time and efforts, to be held at the appropriate level.
He added that he is proud of the participation of distinctive top geneticists in HGM 2011, led by Prof. Edison T Liu, the president of HUGO and the Executive Director of the Genome Institute of Singapore, a biomedical research institute of the Agency for science, technology and research.
Also participating in the HGM 2011 is Professor Sydney Brenner, Chairman of the Okinawa Institute of Science and Technology in Singapore and the Nobel laureate for Medicine in 2002.
Dr. Mahmoud Taleb Al Ali said that HGM 2011 will discuss the next generation of genome technologies and their impact on heritable disorders, stem cell therapy, and genetic diseases such as cancers, metabolic diseases, deafness and neurological disorders in terms of diagnosis and treatment.
The conference will also discuss the global economic effects of genome applications and their related ethical and legislative challenges. Among the discussed subjects is the use of developed algorithms to read human genome maps and allow the discovery of disease-related loci.
During the conference, the HUGO Council will conduct several closed meetings to discuss its future strategic plans; the details of the forthcoming HGMs; its publications, in particular, The HUGO Journal; and the goals and directions for its various sub-committees.
The Executive Board and Arab Council of CAGS will also hold a number of important meetings to evaluate their achievements during the past years and discuss future projects.
[The "Arab genome" is one of the largest, fairly homogeneous genome of the Global population (the Chinese Hun tribe, over 1Bn people aside). For strategic planning and hereditary diseases, e.g. due to frequent in-breeding in leading Arab circles, there are very considerable funds mobilized for this next challenge. This meeting in Dubai, under some international umbrella, well serves the Arab interests. In view of Dr. Mattick of Sidney, telling yet another World Conference in their face that most of their basic assumptions were wrong for 50 years, the Fractal Recursive Iteration approach by Dr. Pellionisz, which was duly submitted to his home country for "first refusal" in 2006, becomes of interest to the USA, China and the Arab World. This entry can be commented on the FaceBook page of Andras Pellionisz]
DRC Computer Invites Dr. Andras Pellionisz to Advisory Board
Distinguished expert in genomics to advise DRC on technology and market plan
SUNNYVALE, CA (MMD Newswire) March 2, 2011 -- DRC Computer Corporation (DRC), the leading innovator of dynamically reconfigurable processors, announces that Dr. Andras Pellionisz is joining DRC's Advisory Board. Dr. Pellionisz is a recognized expert in the field of genome informatics specializing in the geometrization of biology, which he applied first in neuroscience to produce industrial neural net applications and later in genomics, manifesting today in applications for personal genomes.
"I am delighted to welcome Andras to our Advisory Board. He brings a wealth of knowledge and contacts in genomics that will be valuable to DRC as we continue to build presence in this major market segment," said Larry Laurich, DRC President.
As a domain expert in Genome Informatics, Andras Pellionisz is an interdisciplinary scientist and technologist. With Ph.D.'s in Computer Engineering, Biology and Physics, he has 45 years of experience in Informatics of Neural and Genomic Systems spanning Academia, Government and Silicon Valley Industry. Dr. Pellionisz played a leading role in the shift from artificial intelligence to neural nets, including the establishment of the International Neural Network Society. In 2005, he combined interdisciplinary communities of Genomics and Information Technology when he established the International HoloGenomics Society (IHGS).
Based on sound genome informatics, his work sets forth new mathematical principles for proceeding with full exploration of the whole genome. Dr. Pellionisz' fractal approach to genome analysis is corroborated by recently published findings about fractal folding of DNA structure by Presidential Science Adviser Eric Lander.
"I am very pleased to be joining the DRC Advisory Board. I am convinced that DRC has the foundation for the genome computer with their leading edge accelerator technology, and I will enjoy assisting them in developing the market for this," said Dr. Andras Pellionisz.
In 2008, his breakthrough research: "The Principle of Recursive Genome Function", superseded the misnomer "Junk DNA". "Junk DNA", a term widely used for 30+ years to define intergenetic material, was as widely misunderstood and dismissed until HoloGenomics. It is now acknowledged as critical to understanding DNA.
In 1973 Dr. Pellionisz was awarded a Stanford Post Doctoral Fellowship, subsequently he served as Research Professor of Biophysics at New York University Medical Center. Later at NASA Ames Research Center, as a Senior Research Associate of the National Academy. From 1994, he served as Chief Software Architect to several Silicon Valley companies.
About DRC Computer Corporation
DRC Computer Corporation is the leading innovator of dynamically reconfigurable processors, addressing the needs of time-critical, data-intense applications in the defense and finance industries, security environments, web companies, and biomedical markets. Recently DRC announced a world performance record in bioinformatics achieving 9.4 trillion cell updates per second using the Smith-Waterman technique. Also this was achieved at a price/performance 5 times better than previous records. DRC's Accelium™ processors deliver ultra-high performance with very low energy usage (typically less than 25 watts) and minimal space requirements, producing actionable intelligence much faster (100x and more) and at significantly lower cost (90% lower) than traditional computer technologies. DRC is a wholly owned subsidiary of Security First Corp., an emerging industry leader in information assurance, data security, privacy, integrity, and high availability.
[Ever since LeRoy Hood (2002) identified the genome as a system for information processing, computer companies started to swirl around Genome Informatics - but they typically lack the multiple domain expertise the subject requires. IBM was the "grand old lady" of Big IT with several decades of interest in Life Science, under the inspiration and leadership of Carolyn Kovach (whose group has migrated to Dell Computer, led by Jamie Coffin). As I outline in my 2008 Google Tech Talk YouTube now approaching 10,000 views Intel's $100 M investment into Pacific Biosciences' nanotechnology-based DNA sequencing was an important turning point by July, 2008. Since then, chip companies like serial CPU manufacturers Intel, AMD, parallel chip manufacturers like Xilinx, Altera, and integrators into high-performance computing by FPGA and/or GPU (DRCcomputer in Silicon Valley holding the speed/price world record, NVIDIA, XtremeData, Convey, Pico, Nallatech) along with the major league of Big IT, Microsoft, Google, Oracle, HP, Sony, Hitachi, Fujitsu, Samsung have all joined the fray of approaching (some already deploying) the genome-based Personalized Medicine and Commerce market, forecast on February, 17, 2011 by $148 Bn market of genome-driven “Personalized Medicine” by 2015, forecast by Businesswire on February 17, 2011 by BusinessWire reaching by 2015 the significant emerging market of maybe several hundreds of Billions range. The challenge for trans-disciplinary experts is the fusion of almost diametrically opposite cultures of old school Genomics of medical doctors with Computer Science and Mathematics-based Genome Informatics specialists. This is the conclusion, see the Feb. 11, 2011 talk, and his answer to the single question, by Eric Lander, the President's Science Advisor. This entry can be discussed on FaceBook of Andras Pellionisz]
NHGRI Celebrates Tenth Anniversary of Human Genome Sequence [what went wrong - Green]
Jacquelyn K. Beals, PhD
Medscape Today
February 18, 2011
Twenty years ago, the Human Genome Project was just getting underway — 10 years later, investigators had a draft sequence of the human genome.
To celebrate these landmark events, and to publicize its vision for the future, on February 11 the National Human Genome Research Institute (NHGRI) held a symposium on "A Decade with the Human Genome Sequence: Charting a Course for Genomic Medicine," on the campus of the National Institutes of Health (NIH). The same week, NHGRI unveiled its vision in Nature....
....Vision for the Future
...NHGRI also marked the celebration by presenting its vision for the future in the February 10 issue ofNature. Dr. Green was lead author of a perspectives piece highlighting 5 research domains for NHGRI "from base pairs to bedside": understanding the structure of genomes, understanding the biology of genomes, understanding the biology of disease, advancing the science of medicine, and improving the effectiveness of healthcare.
A schematic in the article shows that most genomics research accomplishments from 2004 to 2010 dealt with the structure or biology of genomes. The period from 2011 to 2020 is projected as a time of intensifying research on the biology of disease. Beyond 2020, the research focus is expected to advance into the science of medicine and improving the effectiveness of healthcare.
The article repeatedly refers to the "importance of non-coding variants in human disease" or "illuminating the fundamental biology of non-coding sequence variation and its phenotypic implications."
A Lot More to Learn
Medscape Medical News asked Dr. Green to elaborate on this topic, which goes far beyond the familiar formula of "DNA to RNA to protein."
"Study of the human genome, since the end of the human genome project, has revealed that the minority of the functional parts of the human genome are protein-coding regions, which really are the regions we understand the best," said Dr. Green.
"Once upon a time we thought that most of the action, where the functional parts of our genome are going to be, was in the genes, the stuff that made information for coding proteins.
"What has been revealed, since the end of the genome project, is that's really important stuff — something like 21,000 genes or so — but in fact, that only represents about a third of the functional sequences in our genome," he added.
The remaining two thirds of the functional sequences do not code for protein, but have other functions.
"We have a lot to learn. We barely have scratched the surface in studying that part of the genome," said Dr. Green.
Some elements in this noncoding DNA regulate where and when and how much genes are turned on or off; Dr. Green refers to them as "dimmer switches" that can switch on, or switch off, or modulate how much a gene is expressed. That constitutes a whole circuitry of noncoding DNA that is very important.
"The more we study it, the more we realize how complicated it is. We are learning that these genetically complex diseases, which are diseases responsible for filling hospitals and clinics around the world — diabetes, cardiovascular disease, mental illness, some forms of cancer — that these disorders are complicated because they involve multiple different genetic changes that confer risk for disease. The majority of times, the noncoding DNA elements are the ones that contain variants conferring risk for these complex diseases," explained Dr. Green.
"So the reason [noncoding DNA elements] are so medically important is: number 1, it's probably where a lot of the variation is that confers risk for human disease. And number 2, we don't understand that very well. And yet we have to, because it's medically important," he added.
[Open "confession" that the establishment of Genetics missed the boat by not recognizing the misnomer "JunkDNA" early enough, and even a hint that the DNA-RNA-PROTEIN "arrow model" (based on Crick's Central Dogma) might be wrong. These are great news from the establishment. However, do we want to waste yet another decade (with billions of dollars) by waiting to deploy applications, STARTING TO PLAN FOR HEALTH-CARE IMPACT BY 2020 (!), that is possible today (see YouTube "Shop for your Life"? With the USA a superpower NOT having a "National Genome Program" (NASA style) we are facing a colossal dilemma of slipping in the global race - letting applications, possible today, to drift off-shore. Maybe it is time to bring some captains with proven telescopes aboard a streamlined ship, instead of loading up already sinking ships, or planning decades for a turn-around of huge old-built freighter ships drifting sideways. This entry can be debated at the FaceBook of Andras Pellionisz]
Initial impact of the sequencing of the human genome [What went wrong according to Eric Lander]
Eric S. Lander
Nature
doi:10.1038/nature09792
...The view from 2000
Our knowledge of the contents of the human genome in 2000 was surprisingly limited. The estimated count of protein-coding genes fluctuated wildly. Protein-coding information was thought to far outweigh regulatory information, with the latter consisting largely of a few promoters and enhancers per gene. The role of non-coding RNAs was largely confined to a few classical cellular processes. And, the transposable elements were largely regarded as genomic parasites. [This is a very diplomatic but factual rejection of the "JunkDNA misnomer - AJP]
"Mr. President, the basic assumptions were all wrong!" (Lander video at 9:43, Exhibit A)
A decade later, we know that all of these statements are false. [It follows that a new set of fundamental assumptions have to be made - totally consistent with Francis Collins' statement at the publication of the ENCODE results, showing that "the genome is pervasively transcribed", "now the scientific community will have to re-think long-held beliefs"] The genome is far more complex than imagined, but ultimately more comprehensible because the new insights help us to imagine how the genome could evolve and function...
...The road ahead
The ultimate goal is to understand all of the functional elements encoded in the human genome. Over the next decade, there are two key challenges.
"Mr. President, 'Junk DNA' is dead as a doornail (Lander video at 11:29; blue (genic) area is shrinking, red (formerly Junk DNA) area is already five times bigger and is exploding. The "Junk" is evolutionarily conserved five times more than "genes" (1.2% - but most of them are non-coding "introns", anyway, Exhibit B)
The first will be to create comprehensive catalogues across a wide range of cell types and conditions of (1) all protein-coding and non-coding transcripts; (2) all long-range genomic interactions; (3) all epigenomic modifications; and (4) all interactions among proteins, RNA and DNA. [Yes, "all interactions" does include the DNA-to-PROTEIN interaction; this is a very diplomatic rejection of Crick's "Central Dogma" (that Protein information "never" goes back to DNA sequence information - today even high-schoolers know that proteins methylating DNA modulate the accessibility of DNA sequence information - AJP]
Some efforts, such as the ENCODE and Epigenomics Roadmap projects, are already underway
Among other things, these catalogues should help researchers to infer the biological functions of elements; for example, by correlating the chromatin states of enhancers with the transcriptional activity of nearby genes across cell types and conditions.
... The second and harder challenge is to learn the underlying grammar of regulatory interactions; that is, how genomic elements such as promoters and enhancers act as ‘processors’ that integrate diverse signals.
"Mr. President, the DNA is Fractal! Lander video shows fractal structure at 16:38 and utters the word "fractal" at 41:20 (exhibit C)
Large-scale observational data will not be enough. We will need to engage in large-scale design, using synthetic biology to create, test and iteratively refine regulatory elements. Only when we can write regulatory elements de novo will we truly understand how they work. ...
[This somewhat belated but top-level rejection of both mistaken dogmas (Junk DNA and Central Dogma) will lead a scientist, like Eric Lander, a mathematician by training, into learning NOT the "grammar", but the "algorithm" of genome regulation; as e.g. laid out by The Principle of Recursive Genome Function peer-reviewed paper (2008) and its popular rendering in Google Tech Talk YouTube (2008). The road-map when, how and who took the wrong turn towards the over half of a Century dead-end of (Holo)Genomics, blocking the path to understand fractal iterative recursion as the core of genome regulation, (and how to hunt, in a targeted fashion, for fractal defects causing genome regulatory diseases) will be summed up shortly - This entry can be debated at the FaceBook of Andras Pellionisz.
Dr. Lander's extremely revealing video (look up the very end of his YouTube) makes a further dramatic turn AFTER he wraps up his speech. Below is a transcript of a single question, answered only by Dr. Lander, with no comment by Dr. Green at all:
41:55 Eric Lander finishes “and thank you for the invitation”. [Applause by NIH audience in the NIH Auditorium]
41:06 NIHGR Chief, Dr. Eric Green, Session Chair takes over: “We have time for one quick question, if anybody would be bold enough” [Calls out a short haired lady, about 40 years of age clad in green from the audience]
42:14 “That was a great talk! Uhm.. but you, Eric [Lander] and Francis [Collins] all got up and talked about the diminishing cost of sequencing, which I think was great. But what I would really like you to comment on what the increasing cost of analysis has done because the two are really tied in hand in hand, and now you are talking about a million genome and we don’t really want to update the reference, because people really don’t want to analyze a million genome. So could you please comment on where to go get the analysis faster, better and more reproducible?”
42:44 [Dr. Lander answers, standing on the podium with Dr. Green together with a truly baffled face] “This is a great question. There is really there are three parts of the costs of what we have to be going ahead. There is … actually, four parts … collecting samples, preparing samples, sequencing samples and analyzing data. The sequencing part of continuing to drop that’s very good. With every other part we’re gonna have to put a tremendous amount of attention to sample prep, which will, in the next year or so, begin to match the cost of sequencing of all exomes. We got to nail that down. Collecting the samples [pats Dr. Green’s shoulder] is also a non-trivial expense, [smiles] and yes, with analyzing the data, right now data storage alone (used to be a trivial sliver of the pie) is now a visible part of the pie and if you calculate another five-fold decrease of [sequencing] costs, just storage alone will become significant part of the pie – a big problem of running faster than Moore’s Law is you no longer have Moore’s Law of keep decreasing the storage at the rate you need. And so one is gonna need to store only parts of it, one would have to have to use reduced representation by compression techniques, one is gonna say I’have seen this genome a million times before; the salient features I need to store are the following. [AJP: Thus, the 3 easier parts are toi be covered, but... ] We are going to need tremendous input from informatics folks, from computer scientists to think about this kind of reduced representations, about efficient computing but this is in the spirit of the Genome Project that has always been to reaching out to different fields and Lord knows at this point we are going to need help from a lot of fields to bring all those costs down in parallel to really deliver on his [Lander points at Dr. Green, who is leading the Genome Institute of the Dr. Collins-led NIH] “Million Genomes” project.” [One wonders about the algorithmic understanding-project, that can e.g. be found already outlined in The Principle of Recursive Genome Function - AJP]
44:18 [Dr. Green, Chairman of the Celebration makes no comment at all, but moves on] “Right. I know that there is a lot, but we have to move on…”
[video abruptly ends]
Primates' Unique Gene Regulation Mechanism: Little-Understood DNA Elements Serve Important Purpose
ScienceDaily (Feb. 9, 2011)
[Realizing the importance of Genome Regulation needs not much higher IQ than found in most primates; see 150,000+ views of rap "Regulatin' Genes" and elaborate Google Tech Talk YouTube of 2008, approaching 10,000 views - AJP]
Scientists have discovered a new way genes are regulated that is unique to primates, including humans and monkeys.
Though the human genome -- all the genes that an individual possesses -- was sequenced 10 years ago, greater understanding of how genes function and are regulated is needed to make advances in medicine, including changing the way we diagnose, treat and prevent a wide range of diseases.
"It's extremely valuable that we've sequenced a large bulk of the human genome, but sequence without function doesn't get us very far, which is why our finding is so important," said Lynne E. Maquat, Ph.D., lead author of the new study published February 9 in the journal Nature.
When our genes go awry, many diseases, such as cancer, Alzheimer's and cystic fibrosis can result. The study introduces a unique regulatory mechanism that could prove to be a valuable treatment target as researchers seek to manipulate gene expression -- the conversion of genetic information into proteins that make up the body and perform most life functions -- to improve human health.
The newly identified mechanism involves Alu elements, repetitive DNA elements that spread throughout the genome as primates evolved. While scientists have known about the existence of Alu elements for many years, their function, if any, was largely unknown.
Maquat discovered that Alu elements team up with molecules called long noncoding RNAs (lncRNAs) to regulate protein production. They do this by ensuring messenger RNAs (mRNAs), which take genetic instructions from DNA and use it to create proteins, stay on track and create the right number of proteins. If left unchecked, protein production can spiral out of control, leading to the proliferation or multiplication of cells, which is characteristic of diseases such as cancer.
"Previously, no one knew what Alu elements and long noncoding RNAs did, whether they were junk or if they had any purpose. Now, we've shown that they actually have important roles in regulating protein production," said Maquat, the J. Lowell Orbison Chair, professor of Biochemistry and Biophysics and director of the Center for RNA Biology at the University of Rochester Medical Center.
The expression of genes that call for the development of proteins involves numerous steps, all of which are required to occur in a precise order to achieve the appropriate timing and amount of protein production. Each of these steps is regulated, and the pathway discovered is one of only a few pathways known to regulate mRNAs directly in the midst of the protein production process.
Regulating mRNAs is one of several ways cells control gene expression, and researchers from institutions and companies around the world are honing in on this regulatory landscape in search of new ways to manage and treat disease.
According to Maquat, "This new mechanism is really a surprise. We continue to be amazed by all the different ways mRNAs can be regulated."
Maquat and the study's first author, Chenguang Gong, a graduate student in the Department of Biochemistry and Biophysics at the Medical Center, found that long noncoding RNAs and Alu elements work together to trigger a process known as SMD (Staufen 1-mediated mRNA decay). SMD conditionally destroys mRNAs after they orchestrate the production of a certain amount of proteins, preventing the creation of excessive, unwanted proteins in the body that can disrupt normal processes and initiate disease.
Specifically, long noncoding RNAs and Alu elements recruit the protein Staufen-1 to bind to numerous mRNAs. Once an mRNA finishes directing a round of protein production, Staufen-1 works with another regulatory protein previously identified by Maquat, UPF1, to initiate the degradation or decay of the mRNA so that it cannot create any more proteins.
While the research fills in a piece of the puzzle as to how our genes operate, it also accentuates the overwhelming complexity of how our DNA shapes us and the many known and unknown players involved. Maquat and Gong plan on exploring the newly identified pathway in future research.
This research was supported by a grant from the General Medical Sciences Division of the National Institutes of Health and an Elon Huntington Hooker Graduate Student Fellowship.
[Full paper is at Chenguang Gong, Lynne E. Maquat. lncRNAs transactivate STAU1-mediated mRNA decay by duplexing with 3′ UTRs via Alu elements. Nature, 2011; 470 (7333): 284 DOI: 10.1038/nature09701 ]
[With the evidence in ~1 Million of ALU's in human genome mounting, how is that some Lonely Central Moron can continue claiming ignorance? See below - AJP]
[Seed paper 1989, FractoGene early general coverage 2002, and The Principle of Recursive Genome Function 2008 - AJP]
[Oh, yes. How about "the Fractal Defect in an ALU" disrupting a FractoSet, causing Friedreich Spinocerebellar Ataxia; Figure and Cold Spring Harbor presentation, 2009 - Entry can be discussed at FaceBook of Andras Pellionisz]
Genomes: Know Your Genes ... Fast
Personal computing transported the technology out of large machines to the comfort of a room in the form of desktop, laptop and palmtop computers. A similar revolution is now underway with human genome analysers where the concept of expensive DNA decoding is gradually moving out of large medical facilities and onto researchers’ tables and, ultimately, to common people.
One such example is the Personal Genome Machine (PGM) which is presently being used for research purposes only and is a size of a desktop printer. The idea is to input a sample of DNA and receive the results within hours. Since it’s a research-based device, the genetic sequencing revealed cannot be used for medical diagnostic or therapeutic purposes as yet, but it has still achieved what other machines could not do: use a technology similar to computers, which is parallel semiconductor-based sensors measuring hydrogen ions generated by DNA replication.
This real-time processing is the key to speed, using which genetic information is transformed into digital information for the end-user’s consumption. This machine, which weighs around 30kgs, comes with iPod and iPhone dock and sports a touchscreen interface.
One may wonder whether there is a real need to invest time and money in creating smaller and faster DNA and genome sequencing machines and then making it public. The answer is simple: the research in DNA sequencing is the key to understanding basic physical features of human beings and is instrumental in preventing and providing cure for diseases linked to genetic composition.
Additionally, a personal gene sequence can help determine mutations that can predict which drugs will work best in a given condition. Earlier, complete human gene sequencing had been a daunting task, but the Human Genome Project undertook it successfully and it helped determine the exact order of the three billion chemical building blocks making up the DNA of 24 chromosomes found in the human DNA.
Based on these rapid advancements, companies like HolGenTech.com have taken the genome application to the next level by introducing a smartphone Personal Genome Assistant (PGA). This is a unique handset application that reads bar code off a product wrapping to identify ingredients and matches the data with data generated by service providers like 23andMe and Navigenics.
The former is a retail DNA testing service (DTS) that allows interested users to purchase a kit from its online store, provide saliva sample in a test tube present in the kit and ship it to the lab. After a few weeks, results are available online. According to the service, it provides users with details on personal traits from baldness to muscle performance, risk factors for 94 diseases, predicted response to drugs and even ancestral origins. Navigenics also work in a similar way using saliva sample.
The smartphone application also takes into account users’ personal health data stored in database services like Google health and Microsoft health vault. This integrated, matched view provides a recommendation score to allow the consumers to make a choice when purchasing a particular product. The idea is to make consumers aware of any risks associated with the use of product with a known genetic or medical condition.
Upcoming devices
Scientists at Imperial College, London, are researching on workable and quick ways of sequencing the entire genetic makeup. Since each human genome consists of around three billion bases, this at present takes about 3.5 days to sequence them.
Compared to this, the new device will sequence an entire human genome in about five minutes. The methods available at present can sequence genes at a rate of 10 bases/second approximately. However, it’s expected that with the success of the researches, the genome devices will be able to read around 10 million bases/second.
The latest genome device functions on the fact that each base protein has its unique electrical signal. Each strand of DNA is passed through a 50 nanopore openings in a silicon chip. As it goes through the tiny gap, a tunnelling electrode junction on the other side reads each base’s distinct electrical signal. And even though using electrical signatures to read DNA is not a new idea, the problem was that no one was able create a small enough electrode junction until now.
However, the team at Imperial College have successfully constructed a prototype with a small enough gap to read DNA bases. After this they will work on calibrating the device to identify the individual bases. The scientists working on this project are optimistic that their method will be in wide use within the next 10 years.
[Read carefully what the article mentions about HolGenTech' Personal Genome Assistant "smart phone". Neither 23andMe, nor Navigenics establishes diagnosis - and HolGenTech does not even touch anything "medical". Instead, it focuses on Genome-based Product Recommendations, where diagnosis may come from Google Health and/or Microsoft Healthvault data-bases, made to be interoperable with genomic markers how one product (supplement, vitamin, cosmetics, etc, etc, could be better for your genome than another. This entry is open to comments at FaceBook of Andras Pellionisz]
Computing in the Age of the $1,000 Genome
Xconomy, Seattle
Luke Timmerman 12/27/10
Speakers from Isilon, Arch Join Stellar Lineup
The quest to sequence entire human genomes for $1,000 or less is one of the stories that many predict will change healthcare in the 21st century. It’s an enormously complex puzzle that requires some of the brightest minds in both IT and life sciences to put their heads together. And quite a few of them are working to make this happen right here in Seattle.
So that’s why I’m pleased to announce we’re adding a couple more great speakers to our next event, “Computing in the Age of the $1,000 Genome” on February 7th in Seattle. The first is Paul Rutherford, the chief technology officer of Seattle-based Isilon Systems, which has now officially been acquired by EMC for $2.2 billion. The second is Bob Nelsen, the managing director of Arch Venture Partners, an early investor in Illumina, the leading maker of DNA sequencing instruments that are creating this massive data pile-up.
Rutherford is a natural fit for this event because he has spearheaded Isilon’s work in providing the immense data storage capability that biologists need when they run DNA sequencers that spit out billions of data points. Isilon has gotten some early traction in this market, having signed up A-list customers like The Broad Institute of MIT and Harvard, Johns Hopkins University, Merck, & Genentech.
Rutherford will offer his perspective during a panel at this event alongside Deepak Singh of Amazon Web Services, and Jim Karkanias of Microsoft Health Solutions. Each comes at the genomic data challenge from a slightly different angle—Amazon is focused on flexible cloud computing approaches for storage and analysis, Microsoft has an open-source software platform it is pushing along with bioinformatics software to crunch the data, while Isilon offers hard core centralized servers to store and access the data at places that pump out vast amounts of DNA sequences every day.
I’ve asked Tim Hunkapiller, one of the founding fathers of bioinformatics from the early 1980s at Caltech, to moderate this panel. Hunkapiller has a long history as an academic scientist, and these days has his finger on the pulse of what’s new in DNA sequencing instruments, partly through his work as a consultant to one of the industry leaders, Carlsbad, CA-based Life Technologies (NASDAQ: LIFE).
Nelsen, who’s never afraid to stir the pot, will join this event for a closing fireside chat with biotech pioneer Leroy Hood.
So, here’s the updated list of speakers:
—Leroy Hood, the co-founder and president of the Institute for Systems Biology, Seattle
—Cliff Reid, co-founder and CEO, Mountain View, CA-based Complete Genomics
—Eric Schadt, chief scientific officer, Menlo Park, CA-based Pacific Biosciences
—Jim Karkanias, senior director, applied research and technology, Microsoft Health Solutions, Redmond, WA
—Deepak Singh, senior business development manager, Amazon Web Services, Seattle
—Rowan Chapman, partner, Menlo Park, CA-based Mohr Davidow Ventures
—Andreas Sundquist, co-founder and CEO, Palo Alto, CA-based DNANexus
—Ilya Kupershmidt, co-founder and VP of products, Cupertino, CA-based NextBio
—Rob Arnold, president, Seattle-based Geospiza
—Tim Hunkapiller, Seattle-based consultant, Life Technologies
—Paul Rutherford, chief technology officer, Isilon Systems, Seattle
—Bob Nelsen, managing director, Arch Venture Partners, Seattle
Tickets have been going fast for this event, and at the current pace I wouldn’t be surprised if this event sells out a couple weeks in advance. So check your calendars for the afternoon of February 7, and join us for a thoughtful conversation about how computer scientists can work with biologists in a way that will ultimately shake up medicine as we know it.
Luke Timmerman is the National Biotech Editor of Xconomy, and the Editor of Xconomy Seattle. You can e-mail him at ltimmerman@xconomy.com, or follow him at twitter.com/ldtimmerman.
[The Dreaded DNA Data Deluge (see YouTube, 2008) has long been expected. Now, not only "Big IT" (Microsoft, Amazon Cloud Services etc) take it deadly seriously, but also biological systems (lung, kidney, brain cell - and even the genome and the organelles, organs, and organisms it grows) are targeted in the intrinsic mathematical language - fractal geometry. FractoGene (Pellionisz, 2002) had no chance of becoming published in 2002 as it ran dead-against the two prevailing (obsolete) axioms, the Central Dogma (with Crick still alive), and the JunkDNA misnomer that was officially put to rest only by ENCODE in 2007 (though Dr. Pellionisz put together an International PostGenetics Society with an European Inaugural International conference, to speed up publication of ENCODE by 8 months). Thus, FractoGene was entered to USPTO not in the interest of seeking undue monetary gains, but to secure the intellectual priority-date of the concept, that reaches back to his Cambridge University Press publication of "The Fractal Geometry of Purkinje Neurons", 1989. With the ENCODE results published, Dr. Pellionisz could publish in a peer-reviewed research journal The Principle of Recursive Genome Function in 2008, and present his Google Tech Talk YouTube, 2008 with genome computing architectures (YouTube, 2009, 2010).
[See here]
[See here]
-[FractoGene, 2002]
This entry can be debated on the FaceBook of Andras Pellionisz]
The State of Science [What was Obama's Sputnik? What should be his Apollo? - AJP]
January 26, 2011
Genomeweb
The theme of US President Barack Obama's State of the Union address yesterday evening was on how Americans could "win the future" despite increased competition from countries including China and India. Obama noted that China has the largest private solar research facility as well as the world's fastest computer — which Top500 says is at the National Supercomputer Center in Tianjin. "We need to out-innovate, out-educate, and out-build the rest of the world," Obama said.
Obama then called for an increased federal investment in science as well as for training 100,000 more science, technology, engineering, and math teachers. "This is our generation's Sputnik moment," he said, echoing remarks he made at Forsyth Tech in Winston-Salem, NC, in December....
William Talman, the president of the Federation of American Societies for Experimental Biology, said he was pleased to hear Obama say that he wants to make biomedical research investment a 2012 budget priority. "This will promote innovation, create new technologies, improve health, and revitalize the economy," Talman said in a statement. "It is also gratifying to the thousands of young Americans who have dedicated themselves to pursuit of careers in science and engineering, and this will inspire others to follow their lead."
[The President correctly identified his "Sputnik moment" - when China turned on the world's fastest supercomputer (move over USA, October 28, 2010). However - just as with Sputnik - the proper answer was NOT to launch a "bigger, better Sputnik"; but to escalate the competition onto a new dimension (in that case, producing the Apollo Moon Shot). In this column, referring by name to the "Sputnik analogy", I argued on August 15, 2010, that the truly vital challenge is the solving of the science problem of mathematical understanding of genome regulation, such that "Industrialization of Genomics" could be complete with not only sequencing the DNA - but also to interpret its Recursive Genome Function (Fractal Recursive Iteration). When China first sequenced the Han (Chinese) genome, they stressed in the brief announcement that their knowledge of the genome of the largest homogeneous population of the World (Han) is not only vital for their health care, but it is also of strategic priority (so mentioned "national strategy" the Russians when sequenced the first Russian genome). - This entry can be debated on the FaceBook of Andras Pellionisz]
Like Life Itself, Sustainable Development is Fractal
By Sustainable Land Development Initiative | January 7th, 2011
By Terry Mock and Tony Wernke, SLDI Co-founders
Follow Terry and Tony on Twitter: Terry @SustainLandDev; Tony @Sustainable4U
Watch the full episode. See more NOVA.
A new understanding of the world is revolutionizing how scientists and other professionals of all disciplines are solving important problems today, and this understanding also has the potential to significantly impact how we think about and work to achieve a sustainable world.In just the last couple decades, we have learned that fractal geometry – and its related field of chaos theory – forms the very basis of science. “Chaos,” as its name implies, is the study of processes that appear so random that they do not seem to be governed by any known laws or principles, but which actually have an underlying order. We now know that the physical, biological, social and even the economic universe is not random, and we’re beginning to determine just what that underlying “code” is.
Scientists are learning that everything natural is created by the immutable laws of fractal geometry. This includes static elements as well as energy flows, living things, and their behavior patterns. They are all built on self-similar patterns that replicate each other on increasing and decreasing scales, sort of like Russian nesting dolls. The various levels of scale are not all exactly alike, but they are all self-similar and build one on top of the other based upon a fundamental “code” that reproduces itself on different scales. In both the metaphysical and practical sense, the entire universe is built by fractal geometry.
While it’s a relatively simple concept to understand and the general idea isn’t new, we have barely begun to realize the full importance and usefulness of fractal geometry. We are now beginning to learn how to dissect these “codes” and fractal geometry is now being used in many different ways. It is being used to better understand and impact economic trends, computerized image/data compression, human behavior, natural systems, molecular biology, cosmology, and much, much more.
Brief History
Throughout history, scientists have formed scientific principles in one discipline based on those from another. In ancient China, irrigation science formed the basis for the healer’s model of Chi, the life-force energy that flows through meridians like aqueducts. In psychology, Freud’s conceptualization of emotion used a scientific model of a hydraulic steam engine. More recently, laser technology and holography have prompted the neurological investigation and understanding of memory. The interrelationships go on and on, and now our recent understanding of fractal geometry goes to the heart of it all.
Benoit Mandelbrot, a financial analyst who worked at IBM, discovered the computer’s ability to visually display what had previously been abstract mathematical equations, such as the mathematics of recursive loops. He coined the term “fractal geometry” to describe his efforts to portray the complexity of nonlinear systems in visual form, admitting his fascination for the beauty of many fractal forms. In such an equation, the formula is typically simple, consisting of a single equation, the output of which is fed back into the equation as its next input, forming an infinite loop. Although the idea of recursive loop equations have been around a long time, it is only with the advent of computers that enough iterations to approximate infinity – in both inward (high number of decimal places) and outward (high number of digits) directions – can be produced.
The following video introduces the concepts of fractal geometry and the capacity it has to enhance our understanding of our world. It is a fascinating view.
The Fractal Nature of Life Itself
Fractal geometry has dramatically expanded our scientific understanding in the field of biology. If you understand how a cell works, you understand how a human works biologically. A human is nothing more than a collection of about 50 trillion cells, each with the same structure and basic functionality, replicated and then adapted to work together to achieve the success of the community – the human being. All the functions of the human body are already present in every living cell that comprises it. Each cell has its own intelligence and all the functions of the whole human being. They know how to grow, reproduce, digest food, respirate, defecate, communicate, etc. Everything humans can do, each cell in our body already does individually. After all, humans were programmed by and patterned after the cells themselves. [See FractoGene (Pellionisz, 2002), Fractal DNA governs fractal growth of organelles, organs and organisms, peer-reviewed science paper The Principle of Recursive Genome Function (2008) and Google Tech YouTube 2008)]
Similarly, humanity is comprised of a population of self-similar humans, each made up of trillions of cells. As cells evolve, as people evolve, so does humanity. Biologically speaking, the entire population of the world is akin to a cell. It has the same functions and needs. It’s a self-similar pattern of increasing scale. The old axiom, “As it is above, so it is below,” becomes the geometry of life and the laws of humanity. The similarities of function and need are scientifically inescapable.
As is true with all things that are fractal, understanding the inner-workings of one level of the structure offers insight into all other levels of the structure. Humans tend to think of ourselves as a singularity, but by scientific definition each human is a community of cells, all working together harmoniously toward one end, the sustainability of the whole. If you understand the dynamics of how 50 trillion cells can live in the smallest environment in harmony, all the rules are there for a few billion people to live on the planet – in harmony. But this knowledge must be applied, as it is in the human body.
The following video introduces the laws of fractal geometry to our understanding of biology.
The Environment
One of the largest fractal relationships in real-life is the self-similarity of objects in nature. Clouds, trees, ferns, snowflakes, crystals, mountain ranges, lightning, river networks, coastlines, and much, much more can be produced remarkably accurately within a computer using relatively simple fractal geometric equations. It is the way nature produces itself.
The Human Body
The brain, nervous system, respiratory system, circulatory system, and everything else in the human body, is a product of fractal geometry at work. Significant advances in medicine are currently being developed using fractal geometry that are directly attributable to our new understanding of the body.
Psychology
Scientists are learning that not only is human physiology fractal, but so is human behavior. In fact, fractal geometry has immense consequences on our mental and physical quality of life. Individual behavior, while often seemingly random, actually follows predictable patterns based on the “code” of instructions that are built into an individual’s psyche. Behavior, over time, reflects self-similarity and predictability. In fact, psychologists are beginning to define individual identity based on the patterns of self-similarity embodied in behavior. With the human psyche, just as with fractals, the closer you look, the more there is to see. Psychologists can start with any detail about a person, no matter how trivial it may seem, and the more it is explored, the more richness and complexity is revealed, but it also can be traced back to the “code” of instructions that are embedded within the psyche of that individual person. In true fractal-like fashion, any part of behavior one examines reflects and is intimately connected to the whole. Through the exploration and understanding of this code, psychologists can begin to heal mentally sick patients.
Psychologists are learning that human creativity takes on fractal characteristics. Human creativity has an underlying process that selectively amplifies small fluctuations of mental stimulus and molds them into coherent mental states experienced as thought.
Fractal patterns of mental activity in sleep and wakefulness have been evaluated from EEG recordings. This has important implications for the proposal that dreams result from the brain’s attempt to bring meaning to the images evoked by a stimulation of the brain’s visual and motor centers during rapid eye movement sleep.
Other researchers are beginning to suggest that fractal geometry and chaos theory might help bring some order to the potpourri of provocative findings in parapsychology. For over a century, parapsychologists have investigated such purported phenomena as extrasensory perception and psychokinesis using old linear models from natural science. There is now some optimism that fractal models may begin to provide some breakthroughs.
Our understanding of fractal geometry has enabled scientists to make breakthroughs in social psychology and welfare. We’re learning that our ethical perspectives and the functioning of community are based on fractal geometric relationships. The forms of these community fractal relationships extend to national and even global physiology. For example, to this day George Washington is considered to be the “Father of Our Country” by setting the example for American democracy which now is playing out internationally, albeit with some unintended consequences due to some alterations in his original philosophy.
Economics
Fractal geometry has significant ramifications in economics and finance. Countless economic and financial “behaviors” are fractal in nature. In a nutshell, understanding fractal geometry enables organizations to improve their profitability and opens up entire new economic opportunities that simply did not exist previously.
In the 1930s, Ralph Elliott proposed that market prices unfold in specific patterns, which we now call fractal patterns.
The Elliott Wave Principle says that just as naturally-occurring fractals often expand and grow more complex over time, so does collective human psychology. This is manifested in buying and selling decisions reflected in market prices. The principle has become popularized by Robert Prechter, a noted stock market analyst who realized through reading many of Elliott’s lost works that mass psychology is what the markets are all about, and mass psychology is governed by fractal geometry. Elliott Wave practitioner John Casti said in New Scientist in 2002,
It’s as though we are somehow programmed by mathematics. Seashell, galaxy, snowflake or human: we’re all bound by the same order.
In the 1970’s, Mandelbrot found other economic variables that followed similar patterns. His research suggested that markets of many different kinds exhibited a complex behavior that could be broken into smaller and smaller self-same bits. Price fluctuations could be described by fractal functions. He eventually wrote a book on the subject, The (Mis)behavior of Markets.
Today, economics and finance remains one of the hottest topics in the application of fractal geometry. Fractal geometry is being used to accurately model financial market risk. This understanding has led to the evolution of a new economic discipline called, “econophysics” where the study of fractals is chief among the many topics of study. Another aspect of the real world tackled by fractal finance is that markets keep the “memory” of past moves, particularly of volatile days, and act according to such memory. Volatility breeds volatility; it comes in clusters and lumps according to the laws of fractal geometry.
Sustainable Development and Fractal Geometry
We know that human health and behavior (people) are driven by the laws of fractal geometry. We also know that our natural environment (planet) functions according to the laws of fractal geometry. And we know that the world of finance and economics (profit) follows the laws of fractal geometry. So if the individual people, planet and profit components of triple-bottom-line sustainability are bound by the laws of fractal geometry, it follows that their combination will be self-similar as well. A closer examination reveals that to be the case.
By following a set of instructions, or “code,” designed to define our sustainable condition on earth, all human endeavors, regardless of their size, scope and scale, can produce sustainable results by following a set of instructions, or “code.” It is this universal code which we must model in order to produce replicable and scalable results. Whether we’re interested in land development, food production, or healthy living, the same basic set of instructions apply if sustainable results are desired.
Functioning like life itself, the SLDI Code™ is the world’s first and only model that graphically and conceptually identifies the instructions to achieve sustainable results, regardless of application.
It is represented as a three-sided fractal geometric figure called Sierpinski’s (equilateral) Triangle. It begins with the whole and penetrates deeper and deeper into project decision-making, replicating itself throughout all of the various areas, aspects and phases of the project development process from planning through finance, design, construction, maintenance and back to planning again.
It was not developed as a prescriptive checklist to specify a narrowly defined set of products or practices to achieve an outcome. Such systems almost always prove inappropriate on some level because of the unlimited variability of specific project types and circumstances at any point in time. The SLDI Code provides the basic instructions upon which any sustainable project may be achieved.
Any useful system requires the ability to adapt decisions to specific circumstances. As such, the SLDI Code is equally applicable regardless of project type, scale, terrain, climatic zone, etc. It allows for the consideration of all the unique characteristics and constraints of any project, all of which ultimately produce completely unique outcomes. In other words, rather than prescribing how to design a project, the SLDI Code provides the “code” or programming that provides the user with the tools to enhance the quality of their work by combining and balancing virtually unlimited possibilities into a sustainable end result.
In fact, the SLDI Code, like many computer programs, is applicable on projects of any type, regardless of industry. The principles embedded in its top few orders of magnitude are so universal that they apply to all applications of its use, much like a word processing, spreadsheet or graphic design program may be applied broadly across industries and disciplinary endeavors.
The code enhances the quality of outcomes, however diverse they may be, toward greater sustainability from a holistic people, planet and profit perspective. Using the constructs of fractal geometry, the SLDI Code uses the practical methods of how our world, and in fact the universe itself, has been constructed, to perpetuate life in the universe in the most effective manner possible.
In the pass-it-forward spirit, SLDI is now offering this fractal geometric model, including the instructions, to all those willing to collaborate for the collective benefit of people, planet and profit – today and in the future. It’s high time for us to apply the scientific laws of nature to our hope for sustainable civilization.
[See and debate the above in the FaceBook page of Andras Pellionisz -
The outcry in the first minutes of the NOVA movie is "Oh My God! Of course! It is obvious!" - in retrospect...
Not entirely surprisingly, we are approaching the long-awaited singularity. Just days ago I was told that "there is a universal agreement that the genome-epigenome system is fractal" as if they did not oppose me so vehemently in every step of my way! With such pieces of evidence for the scale invariance (an intrinsic property of fractals) found in neuronal activity, what was yesterday's "lucid heresy" becomes "of course, we knew it all along".
The hard part for "me too copycats" will be the next phase of inevitable hypocrisy "actually I new it before you did", since one would have to pull peer-reviewed paper dated prior to my Cambridge University Press piece published in 1989 on the fractal development of Purkinje neurons, as governed by a recursive genome function. It will be hard for San Francisco Chronicle to explain why they pulled an article already out in 2002 http://www.junkdna.com/plotkin.htm and for the Hungarian "Origo" to explain why they pulled the article already out in 2006 http://junkdna.com/origo/ playing up the Budapest host [Dr. F.A. Semmelweis University] on the expense of my science such that he became the "regular" Member of the Hungarian Academy of Science, while my work already done went unpaid with their unilateral breach of contract, see both in the Hungarian and in the English language at http://junkdna.com/contract_pellionisz.htm
Today, the "name of the game" is to profit on the software that delineates structural variants of the genome that reflect "parametric human diversity" from those that are "syntax-glitches where the genome deviates from its own intrinsic structural and functional geometry" - and thus we can provide diagnosis, therapy and up a to a cure for hereditary conditions.
It is one thing to talk about it - and a totally different ball game to turn major investment into Industrialization of Genome Informatics.
Now, approaching the genome with monstrous expense with no utilization of understanding already gathered and at hand is becoming a major scientific/economic embarrassment.]
EU Funds Development of Gene Regulation Software Suite
January 13, 2011
Genomeweb Staff Writer
NEW YORK (GenomeWeb News) – CLC Bio said today that it is leading a consortium funded by the European Union to develop a software suite that will enable gene regulation analysis of a large number of genomes.
CLC Bio, Decode Genetics, Biobase, the University of Oxford, Hungary’s Alfred Renyi Institute of Mathematics, and Russia’s BioRainbow will use €1.6 million ($2.1 million) in EU funding to support the Comparative Genomics and Next Generation Sequencing, or COGANGS, project.
The COGANGS partners plan to develop a software suite that will enable the analysis of up to one thousand genomes at the same time.
“We will apply both the initial prototype and the final software package for the analysis of regions that have been identified to have strong disease associations in the human genome,” Gisli Masson, Decode’s director of bioinformatics, said in a statement.
Masson explained that the software suite could enable scientists to “unlock a lot of information in the vast collection of human DNA samples we already have, once this project enables us to do large-scale comparative genomics analyses.”
[Comment in FaceBook of Andras Pellionisz - The sum is laughable ($2.1 M) for participants from 6 European countries. In addition, the construction is highly debatable. The news is, that orders of magnitude bigger and healthy funding became a "must".
The EU has never been famous for sound and fair science & technology policies. For this petty sum, two industrial players (one is not even in the EU as yet!) will be permitted to rake in, for free, the largely unprotected intellectual power of an Institute of Mathematics of the Hungarian Academy of Sciences, plus the vast potential of Russia (unlikely to become an EU-member anytime soon). Still, the news speaks highly about the EU initiatives, as the needed, at least two-three orders of magnitude larger USA equivalent program (that should be headed by NSF or DARPA) is not even on the horizon yet.
Unless US "Big IT" moves to target with God' speed, China is likely to win this one - the rest will be history.]
Biotech’s Biggest Winner [according to Forbes, it is Illumina - AJP]
Forbes
Matthew Herper
Jan. 3 2011
To most people, including biotechnology investors, the human genome project was a bust that led to no new drugs, no medical breakthroughs, and no real profits. So as I start a series of posts that I’m calling Gene Week, let’s take a step back and look at the best-performing stocks in all of medicine, not just in biotech, but in medical devices and drugs, too. Five companies delivered total returns – a measure of how much you’d make if you’d held the stock and reinvested any dividends — of more than 300%.
The winner, hands down, is Illumina, the leading maker of DNA sequencing equipment, which has delivered a total return to investors of nearly 800% since late 2005. That annualizes to an amazing 50% return ever year, buoyed by sales that have grown twelve-fold from $73 million in 2005 to a projected $879 million. Goldman Sachs projects that earnings of $72 million will triple by 2012.
How did a company that makes machines for decoding DNA wind up at the top of biotech’s heap, beating every drug maker? Illumina has led a revolution with these machines. Five years ago reading out all six billion letters of a person’s genetic code cost $1 million. Now, it costs something like $10,000, and the accuracy has improved. That’s a drop in price and increase in speed that rivals that seen with microprocessors. In the current issue of Forbes, I argue that DNA sequencing could become the foundation for a $100 billion business.
Illumina’s success is largely attributable to the strategic acumen of its chief executive, Jay Flatley, who may well be the best CEO in biotech. Illumina started making DNA chips, an early technology for detecting mutations. At the time, it trailed Affymetrix, which had created the market; Illumina overtook Affy, but, more impressively, Flatley convinced his board to make a big bet on DNA sequencing by purchasing a company called Solexa for $600 million in 2006. Machines like these, still sold almost entirely to researchers, have become a $1 billion market in which Illumina has 70% market share. “The data really is beautiful stuff,” says blogger and genetic researcher Daniel Macarthur. “It’s just stunning it’s so clean.”
Plenty of companies are gunning for Illumina’s crown in sequencing – I focus on one entrant, Life Technologies’ Ion Torrent division, in my Forbes cover story. Illumina shares currently trade for a whopping 84 times trailing earnings. Goldman still rates the company a buy, saying it stands a good chance of holding on to its leadership in the sequencing space.
The rest of this list – this elite top five of health care companies that sport market capitalizations of more than $4 billion – actually bolsters my feeling that the time is ripe for DNA sequencing to push its way out of the research market and into medicine. Look at what other companies have rivaled Illumina’s five-year return: Alexion, which makes a rare disease drug that costs $500,000 per patient per year; Dendreon, a high-risk drug developer that hit pay dirt after years of desperate work on prostate cancer treatment; Perrigo, the Michigan maker of generic over-the-counter drugs; and Novo Nordisk, the diabetes-focused drug giant.
What do these other companies have to do with DNA sequencing? The argument for this technology has been that it will be cheap enough to become ubiquitous – that’s the idea behind the genoscenti’s favorite catchphrase, “The $1,000 genome.” But it doesn’t need to become cheap – it just needs to become useful. Alexion can charge half a million dollars for a rare disease drug, and Dendreon’s Provenge costs $93,000 a year. The cost of a genome doesn’t need to come down for doctors to start adopting DNA sequencing, the usefulness needs to go up and regulatory and insurance barriers need to come down. The kinds of successes that will drive that – like a case in which sequencing may have allowed doctors to identify the right treatment for a very sick five-year-old – are already happening.
Medicine may be ready for the next technological leap. It’s just going to be a matter of making it happen.
[Well ... almost. Matthew Herper's analysis is very compelling, but some deeper background and essentials for the future may be warranted. With the case of Illumina, while Jay Flatley is without question an outstanding CEO, much credit is also due to the revolutionary microarray-technology that enabled Illumina to grow on the turf of Affymetrix. Also, regarding microarrays, it is noteworthy that the so-called DTC (Direct-to-Customers) Genome Testing is also grabbing a lead-role with the Illumina arrays (e.g. by 23andMe, that has just catapulted its marketing model with the help of a more potent array by Illumina). As for the statement "Medicine may be ready for the next technological leap. It's going to be a matter of making it happen" - one could happily agree, if the prescription for "making it happen" would be just a little bit clearer in scientific terms. The analysis may leave the reader with the impression that success in (personalized) genomic medicine is just a matter of time/money - as it used to be believed, mistakenly as we know now - with the "War on Cancer" some forty years ago. "Just Sequencing" may be the equivalent of "Just Surgery", in case of cancer, whereas success of both Genomic Medicine and Cancer Treatment and Cure need a breakthrough in understanding the software-enabling (algorithmic) regulation of recursive genome function. This entry can be debated on the FaceBook-page of Andras Pellionisz]
The Next $100 Billion Technology Business
Forbes
Matthew Herper
Dec. 30 2010
That headline is the cover language from the current issue of Forbes magazine – for a story I wrote about DNA sequencing and, particularly, about Jonathan Rothberg and his new Personal Genome Machine.
What we are declaring in this story is that DNA sequencing, the technology by which individual letters of genetic code can be read out, could be the basis for a $100 billion market that encompasses not only medicine, where sequencing is already being evaluated to help cancer patients, but also other fields like materials science, biofuels that replace petroleum, and better-bred crops and farm animals. There are even synthetic biologists who are talking about using biology to make buildings and furniture based on the idea that this will be better for the environment than current plastic and concrete.
Rothberg’s machine is important because it is the first attempt to lower the cost of DNA sequencing machines to bring them to a far wider audience. The cost of sequencing DNA has been dropping at a rate that rivals – and may surpass – the increases in speed seen with the microchip, but the machines used to do it cost $500,000 or more. The PGM is far less powerful, but it cost only $50,000, although you need other equipment to get it running. It is being made and sold by Life Technologies, the laboratory equipment firm that bought Rothberg’s company earlier this year.
We’re likening the PGM to the Apple Computer, which changed the world, but it could be more like the Altair, which fizzled. Right now, Illumina of San Diego holds the lead in the newer, faster segment of the DNA sequencing market, and it could very well keep it. There are also other new players, such as Pacific Biosciences, which can sequence a single molecule of DNA, and Complete Genomics, which is taking a factory-like approach to bring down cost. That adds to the excitement. Of course, as with all things biotech, this could all fall apart.
Starting on Monday – earlier if I can’t help myself — I’m going to be posting as much material as I can about the new science of genetics, looking at the companies, the science, the potential and the pitfalls. I’ll show you that there is already been a business revolution driven by genomics, even though you might have missed it. I’ll tell you what I think this means for privacy, for drug development, and for medicine, and tell you what books and blogs are good sources of information about the coming DNA wave. It will be Gene Week on The Medicine Show – sort of like Shark Week, but with alleles and sequencing by synthesis instead of sharp teeth and small brains.
And as I do that, I’d like to hear from you. After you’ve read my story, please tell me what you think and share your questions and criticisms in the comments or via email. I’ll publish the best commentaries I receive – and I promise not to hold back if they are critical of my work. I’ll try to answer questions, or to find sources who can. I think we’re on the cusp of a really big technological change. What about you?
[Pellionisz, called-out comment] Forbes has been pioneering the coverage of the first Decade of “Genome Revolution”, and apparently the second Decade, the “Industrialization of Genomics”. It is imperative to point out what went wrong in the first Decade (since 2001) and what is the sound basis of ramping up now from 2011 a “$100 Billion Technology” – especially in view of the admission that “Of course, as with all things biotech, this could all fall apart”. In my opinion, an interesting historical parallel is the blow-up of Newtonian Physics with Nuclear Physics facing the challenge that the old axioms (i.e. that the atom would not split, elements can not be changed – even the philosophical foundation of determinisms) had to create quantum mechanics first, before plunging into peaceful and not so peaceful applications in nuclear industry. The Decade of “Genome Revolution” (officially, with ENCODE, 2007) revealed that the axioms of Central Dogma, JunkDNA, genomic determinism were false – and instead of an introspection Genomics turned towards an “Industrialization” starting with the necessary but not sufficient need of full genome sequencing made affordable. We may be in for the brutal scene of “Sequencing-based industrialization” falling apart, if the “Dreaded DNA Data Deluge” (that e.g. I featured in YouTube, 2008) is not matched by our ability to interpret by software-enabling theory (based on sound informatics of The Principle of Recursive Genome Function). We must bear in mind that the very sustainability of the Industrialization of Genomics is at stake if it is (wrongly) assumed to be just “Technology”, without the software-enabling (algorithmic) understanding of the genome-epigenome (hologenome). Sequences will be worth nothing, and their huge glut will destroy the ecosystem of investments in and industrialization of genomics without the emergence of mathematical understanding of the complex system of hologenome. As always, analytics of complex systems must start with the identification of what the system is. The principle of recursive genome function holds that the system is fractal. Should there be a better idea, let’s hear about it.
[I entered my 2 cents to Matthew's blog - and will insert a pointer in my FaceBook page. The entry ccould thus be debated in Matthew's blog as well as in FaceBook of Andras Pellionisz]
23andMe lowers price from $499 to $199 permanently
[With the Holiday sale of $99 gone, 23andMe made its change of business model permanent. Under the new model they provide a low-cost entry ($199 plus S&H), but charge a monthly pittance of $5, and the buyer of the kit must enroll for the monthly updates for at least 12 months. Or, with a one-time payment ($499) there is no monthly fee for the updates (looks like on a permanent basis). This new marketing will certainly generate a sizable enlargement of their pool of "before sales" 50,000 or so (the official count is not public). This entry can be debated in FaceBook of Andras Pellionisz]
Genetic Tests Debate: Is Too Much Info Bad for Your Health?
Dec 19, 2010 | 8:31 AM ET |
By Samantha Murphy
My Health News
Hoping to find any disease susceptibilities lurking in her genes, 21-year-old Lee — who goes by the nickname "Zlyoga" on YouTube — spit into a container and posted a video of her salivary sampling on the popular site in December 2008.
"I think this is the coolest thing in the entire universe," she giddily said to the camera. "This is one of the best gifts I ever received — so much better than the bike I was going ask for."
Lee's parents had given her a mail-in genetic test. She completed the forms in the kit — then priced at a few hundred dollars — from California genetic-testing company 23andMe, enclosed the sample of her saliva, and sent it on its way.
Direct-to-consumer genetic tests have become increasingly popular since they first hit the market several years ago — in fact, 23andMe alone boasts of having more than 50,000 customers. Although the company does not release statistics about its actual growth, a spokewoman told MyHealthNewsDaily that "our database has grown steadily."
But there's been much debate over whether knowing the results is beneficial or harmful — and if they even give an accurate picture of a person's risk for certain diseases.
Not the whole picture
When Lee received her results, she took to YouTube once again: "In some ways, reading the results felt like a horoscope," she said, sounding half-satisfied.
The test revealed she indeed has blue eyes and, like both of her parents, has a low-tolerance for statin drugs, which are used to treat people with high cholesterol levels. However, she was surprised to learn a few diseases that run in her family posed little to no risk for her.
"I know [genetic testing] is still in its infancy, but how do I know any of this legitimate?" she said.
Others who have completed the 23andMe test have expressed similar concerns on YouTube: "It's all so vague; what does [higher risk] even mean?" asked "MelissaMich," after receiving her 23andMe results.
Not only may the results seem vague, they are just a snapshot of someone's genetic makeup, called single-nucleotide polymorphisms (or SNPs).
"Imagine that the genome is a huge jigsaw puzzle, with many more pieces than we have ever seen in a puzzle before," said Dr. Andras Pellionisz, founder of HolGenTech, a genome interpretation software company. "Now, suppose someone gives you only 10 percent of the pieces."
By knowing your SNPs, you may "get lucky" and precisely learn your risk of some diseases, said Pellionisz, who thinks the tests are a good idea. But, he said, the genetic picture is incomplete.
For example, the results don't factor in lifestyle choices. A person might be told he has a low risk of developing lung cancer, but if he smokes two packs a day, his chances of getting the disease increase.
Indeed, 23andMe is upfront about this on its site, stating that it provides genetic information and "not the sequence of your entire genome," nor does it perform predictive or diagnostic tests. The company acknowledges SNP information is difficult to interpret.
The uncertainty factor
UCLA sociology professor Stefan Timmermans, who studies the genetic testing of newborns, said that knowing too much puts stress on those who've taken the tests. In a recent study, Timmermans revealed how the newly mandated genetic screening of newborns for rare diseases is creating unexpected upheaval for families whose infants test positive for risk factors but show no immediate signs of any diseases.
"Although newborn screening undoubtedly saves lives, some families are thrown on a journey of great uncertainty," Timmermans said. "Rather than providing clear-cut diagnoses, screening of an entire population has created ambiguity about whether infants truly have a disease — and even what the disease is."
"Basically you're telling families of a newborn, 'Congratulations, but your child may have a rare genetic condition. We just don't know, and we don't know when we'll know,'" Timmermans said.
His study paints a picture of families caught in limbo as they wait months for conclusive evidence that their children are out of the woods for various conditions. In many cases, however, the test results never come, the study found. Instead, the children slowly outgrow their known risk factors for dozens of metabolic, endocrine or blood conditions But the effects linger.
"Years after, everything appears to be fine, parents are still very worried," Timmermans said.
Some families are so traumatized that they follow unwarranted and complicated treatment regimens, including waking their children up in the middle of the night, enforcing restrictive diets and limiting their contact with other people for years.
And the same lasting worries come with direct-to-consumer testing, Timmermans told MyHealthNewsDaily.
"Those types of tests are planting seeds in people's minds for something there isn't a lot of firm data about. The genetic information provided by direct-to-consumer tests by itself isn't enough; they also have to look at family history and what has actually developed."
Understanding the results
Mike Spear, a 56-year-old communications director from Calgary, Alberta, didn't know exactly what to make of his results. He found he had a high risk of age-related macular degeneration, which causes vision loss in old age, and became very concerned.
"When I saw my results on paper, it seemed impossible to distance myself from the fact that it was just an experiment," said Spear, who works for Genome Alberta, a not-for-profit genetics research funding organization.
Spear contacted a genetic counselor to gain more insight into the results' meaning.
"The counselor explained that just because I'm at risk for certain conditions, it doesn't mean it's going to turn into anything," Spear told MyHealthNewsDaily. "I also started to be proactive and go to the eye doctor more."
The company 23andMe offers counseling services and gives customers access to its online community, where people can chat about their results, for an additional fee.
But not everyone who participates in the tests reaches out to genetic counselors who can help explain the results, said Dr. Christopher Tsai, director of clinical informatics of Generation Health, a genetic-testing benefits firm. And this is another place problems rise.
Further interpretation
The interpretation of the results is an increasingly central challenge to genetic testing, Tsai said, and the power to analyze the genome has outpaced the ability to interpret the results.
"Even trained geneticists disagree on how results should be interpreted and used to guide care," Tsai said. "The results can certainly be empowering if they lead to concrete actions that the patient can take. Even in terms of lifestyle, there is some evidence that genetics influence people's response to diet and exercise, and this information can guide their lifestyle changes."
According to a 2009 survey conducted by the National Institutes of Health, about 78 percent of respondents said they would change their diet and exercise habits if their results showed a higher risk of cardiovascular disease.
However, some diagnoses seem to only bring bad news, Tsai warned.
For example, a test can predict if someone will develop Huntington's disease — a devastating neurological condition with no cure. It's common for people to develop depression when given such results. [That is why 23andMe does not even check for this condition - such that they have no idea - even if you'd click "I *DO* want to know" -AJP].
"Understanding the value of genetic tests, and when [and] where to use them in the health care system, is becoming an increasing focus of the health care industry," Tsai said.
FDA crackdown
It is for this reason the Food and Drug Administration is increasingly scrutinizing direct-to-consumer genetic-testing companies, Tsai said.
Critics of the tests worry about the safety of consumers who base important lifestyle or medical decisions on inaccurate or misunderstood test results.
"The risk is what people may do in response to the tests — some may suffer psychological harm or feel dread about their future health risks," said Barbara J. Evans, co-director of the Health Law & Policy Institute at the University of Houston Law Center.
"People sometimes pursue ill-advised medical interventions that may actually cause them harm. They may be unaware that these tests can produce false positives and false negatives, and even when people do have a 'bad' gene that does not necessarily imply that the gene will ultimately make them sick. People's futures depend on many, many factors other than their genes," Evans said.
Evans said the solution will require studies to be done before tests enter the market, and ongoing evaluations to see how well they perform once they are in use.
About 90 percent of genetic tests available in the United States have never been through a regulatory review of how safe they are or how much they improve health, she said. Most experts agree such review is needed, but solutions have been mired in the controversies surrounding the tests.
There are practical barriers to forcing all genetic tests to undergo the same sort of review the FDA requires for other medical products, such as drugs. The obstacles include lack of data, the short commercial lives of test products and the difficulty of assessing products that make long-term predictions.
Evans said making genetic tests as safe and effective as they can be will require close coordination among the FDA, state agencies, professional groups and other private-sector overseers.
"Resolving the lingering unknowns about genetic tests will require more data, and getting more data will require a commitment of resources," Evans said. "And make no mistake, having better data about genetic tests will only improve the public's health if the data are communicated in a timely and understandable way to the public."
[Bottom line: GO FOR IT TILL IT LASTS (sale ends December, 25) - the best gift you can ever give for the Holidays! Checks for 179 conditions, for 50 cents you can save the lives of loved ones (up to ten kits per order). This entry can be debated in FaceBook of Andras Pellionisz]
Key information about breast cancer risk and development is found in 'junk' DNA
EurekaAlert
December 16, 2010
A new genetic biomarker that indicates an increased risk for developing breast cancer can be found in an individual's "junk" (non-coding) DNA, according to a new study featuring work from researchers at the Virginia Bioinformatics Institute (VBI) at Virginia Tech and their colleagues.
The multidisciplinary team found that longer DNA sequences of a repetitive microsatellite were much more likely to be present in breast cancer patients than healthy volunteers. The particular repeated DNA sequence in the control (promoter) region of the estrogen-related receptor gamma (ERR-γ) gene – AAAG – contains between five and 21 copies and the team found that patients who have more than 13 copies of this repeat have a cancer susceptibility rate that is three times higher than those who do not. They also discovered that this repeat doesn't change the actual protein being reproduced, but likely changes the amount.
The researchers from VBI's Medical Informatics and Systems Division (https://www.vbi.vt.edu/vbi_faculty/vbi_research_group/personal_research_group_page?groupId=6), the University of Texas Southwestern Medical Center and the University of Liverpool, United Kingdom, report their findings in an upcoming edition of the journal Breast Cancer Research and Treatment. The study is currently available online. The group sequenced a specific region of the ERR-γ gene in approximately 500 patient and volunteer samples. While the gene has previously been shown to play a role in breast cancer susceptibility, its mechanism was unknown.
"Creating robust biomarkers to detect disease in their early stages requires access to a large number of clinical samples for analysis. The success of this work hinged on collaborations with clinicians with available samples, as well as researchers with expertise in a variety of areas and access to the latest technology," explained Harold "Skip" Garner, VBI executive director who leads the institute's Medical Informatics and Systems Division. "We are now working to translate this biomarker into the clinical setting as a way to inform doctors and patients about breast cancer susceptibility, development, and progression. Akin to the major breast cancer biomarkers BRCA1 and BRCA2, this will be of particular benefit to those high-risk patients with a history of cancer in their family."
The majority of DNA is non-coding, meaning its not transcribed into protein. The largest amount of this type of DNA consists of these microsatellites – specific repeated sequences of one to six nucleotides within the genome. There are over two million microsatellites in the human genome, yet only a small number of these repetitive sequences have previously been linked to disease, particularly neurological disorders and cancer.
"We've become increasingly aware that non-coded DNA has an important function related to human disease," said Michael Skinner, M.D., professor of pediatric surgery at the University of Texas Southwestern Medical Center and collaborator on the project. "Replication of this study in another set of patients is needed, but the results indicate that that this particular gene is an important one in breast cancer and they reveal more details about the expression of the gene. This kind of work could eventually result in the creation of a drug that would specifically interact with this gene to return expression levels to a normal range."
"Ninety percent of all the breast cancer patients we see aren't considered high risk patients, which means there wasn't any indication that they would be susceptible to breast cancer," said Dr. James Mullet, a radiologist at Carilion Clinic's Breast Care Center. "This compels us to screen everyone in some way. If we had a better test – one that is more robust and sensitive, but also specific – we could make sure the women with most risk are getting properly screened for breast cancer."
"One practical clinical application of this research is to have a test available that would allow us to tailor our screening better," Mullet said. "For example, we could lessen patients' time, expense, and worry if we could better determine which patients would need only a mammogram, as opposed to additional tests like ultrasound or screening breast MRI. This work may also give us genetic insight into the cause of the breast cancer that may develop in those 90 percent of patients who are not currently identified as high risk."
According to Garner, "There is a big gap between what is suspected and what is known about the genetics of cancer. While more work is needed to better understand how these changes play a role in cancer, these results can be used now as a new test for breast cancer susceptibility and, as our data suggests, for colon cancer susceptibility and possibly other types of cancer. We think this is just the beginning of what there is to be found in our junk DNA."
--
[Excerpts from the paper in the journal of Breast Cancer, "Discussion" - AJP]
There are at least five possible explanations for our results: (1) direct transcriptional influence of ERR-c based on the length of the repeat, (2) linkage of an ancestral ‘‘lengthening’’ mutation with a cancer causing mutation in/ around ERR-c, (3) the repeat resides in an uncharacterized biologically active RNA which is affected by the length of the repeat, (4) misregulation of splicing due to overexpansion of the polymorphic repeat, or (5) a spurious association due to various sampling errors or population issues (albeit unlikely).
["Runs" in intronic and intergenic regions (in the "Junk") have been associated with heredetitary syndromes - but his is one of the papers that pins the main "genome regulation disease" (cancer) on them. Thus, Crick's fear that collapse of his "Central Dogma" (in 1972 rescued by Ohno's nonsense "Junk DNA" theory) will necessitate "putting genomics on an entirely new intellectual foundation" (see The Principle of Recursive Genome Function), is now becoming an active field of identification of glitches in the recursion, leading to a collapse of genome regulation. It has been presented in Cold Spring Harbor, that e.g. the GAA repeat-run in Friedreich' Spinocerebellar Ataxia is a "fractal defect" that disrupts a FractoSet in the middle of an intronic fractal structure. This entry can be debated in FaceBook of Andras Pellionisz]
DIY DNA on a Chip: Introducing the Personal Genome Machine
Fast Company
BY ARIEL SCHWARTZ
Wed Dec 8, 2010
[Life/Ion Torrent Desktop Sequencer, $49k - AJP]
DNA sequencing technology isn't exactly accessible; a typical sequencing machine can easily cost $500,000. A startup called Ion Torrent aims to change that with a desktop sequencing machine for just $50,000--cheap enough for well-funded research projects to afford.
The key to Ion Torrent's Personal Genome Machine is a semiconductor chip that holds 1.5 million sensors, each of which can hold a single strand DNA fragment. The chip electronically detects the DNA sequence, unlike other sequencing machines that optically detect DNA with pricey lasers, microscopes, and cameras. It can sequence a DNA sample in a few hours, while other machines can take at least a week. And it can scale up fast. The company explains:
Because Ion Torrent produces its proprietary semiconductor chips in standard CMOS factories, we leverage the $1 trillion dollar investment that has been made in the semiconductor industry over the past 40 years. This industry's huge manufacturing infrastructure enables Ion Torrent to meet any demand for our chips.
There are some caveats. Each $250 chip can only be used once. The chip also reads a small amount of DNA; 10 to 20 million bases per run, out of the 3 billion base pairs in the human genome. But that's enough for genetic diagnostic tests, according to Technology Review.
Ion Torrent's machine goes on sale this month. Soon enough, these semiconductor sequencing chips may start popping up in cash-endowed hospitals around the world. Could consumer DNA sequencing machines be far behind?
[Life Technologies bought Jonathan Rothberg's Ion Torrent for $725 M just a few months ago - for an extremely strong reason; "Democratization of Genome Sequencing" (beyond Industrialization of Genomics, also making it available like Ford T auto models, for the masses). Without question, "Leveraging the Semiconductor Industry" for Genomics is a formidable economic driver. However, since the one-time use of the $250 chip (run on the $49k) machine is a "bridge" from the present microarray-technology (that is NOT a sequencer but is suitable only to interrogate up to about 1.6 M single-letter "structural variants") to "full sequencing of all 6.2 Bn A,C,T,G letters of a human genome" (like Roche' 454, Illumina Genome Analyzer and Life's own SOLiD, with Complete Genomics in production and Pacific Biosciences in beta-production), the "Personal Genome Machine" by Life/Ion Torrent is to cater for a very precious segment of the market. The "fractal defects" (peek at the Cold Spring Harbor presentation by Pellionisz) are much-much larger "structural variants" compared to single-letter SNP-s (typically, they are 150-350 letter oligos) - precisely in the range of the capabilities of the PGM. Moreover, IP-owner of "The Fractal Approach", HolGenTech, Inc. is based on the dovetailing economic driver, "Leveraging High Performance Computer Industry" for Genomics - by focusing on pure-play Genome Analytics software. Note, that the Personal Genome Machine is a "Sequencer" - that sorely needs another box (like a washer needs a dryer), that takes the raw data of sequences and provides Analytics and Interpretation; such as either "diagnosis" in hospital settings (FDA permitting), or "Genome-based Product Advertisements" (see YouTube "Shop for your Life") that require no clearance from the medical establishment - yet accomplishes the kind of "democratization" and turning PGM into real "Consumer Sequencing Machines", completed by enabling consumers to use genomic information in their daily life. This entry can be debated in FaceBook of Andras Pellionisz]
Break Out: Pacific Biosciences Team Identifies Asian Origin for Haitian Cholera Bug
By Kevin Davies
December 9, 2010
In a dramatic piece of ultra-quick genetic detective work, next-generation sequencing company Pacific Biosciences has decoded the sequence of the strain of bacteria responsible for the deadly cholera outbreak in Haiti. The findings, which confirm the putative Asian origin for the devastating disease, are published online in the New England Journal of Medicine today.
The project was led by physician scientists at Harvard Medical School and Massachusetts General Hospital (MGH), including Matthew Waldor, John Mekalanos, Stephen Calderwood and Morton Swartz. “This understanding has important public health policy implications for preventing cholera outbreaks in the future,” says Mekalanos.
Cholera was first detected in Haiti in mid October, spreading across the country and into the Dominican Republic. Nearly 2,000 people have died from the outbreak, with no end in sight. Shortly after the outbreak, Waldor contacted the Centers for Disease Control and Prevention (CDC) and offered to sequence the bacterial strain using Illumina’s technology. Waldor says the CDC initially said he could have the strain, but five days later, changed their mind (citing political reasons) and said they were going to do it themselves. “At that point, I thought we were out of the game,” says Waldor.
CDC subsequently announced that using pulse-field gel electrophoresis fingerprinting technology, the strain was consistent with a south Asian origin. “But from a pure scientific point-of-view, that’s heresay,” Waldor, who is professor of medicine at Harvard Medical School and an investigator with the Howard Hughes Medical Institute, told Bio-IT World. “What are their controls? Pulse-field gel electrophoresis has nothing like the depth of a full genome sequence.”
But by then, Waldor and colleagues were already putting the finishing touches to their manuscript. Two weeks earlier, two MGH physicians -- pediatrician Jason Harris and Richelle Charles – returned from Haiti with samples they’d collected from a hospital. But who would do the sequencing?
That Was the Week
Two days earlier, on Saturday November 6, Waldor emailed a speculative inquiry to the PacBio website. “I knew they had some exciting technology, my understanding was it was very useful for resequencing bacterial genomes.” While he was fishing around on the PacBio Web site, Waldor noticed that one of his colleagues at the Brigham & Women’s Hospital – Joseph Bonventre – was on the PacBio advisory board.
“So I called him up,” Waldor continues. “He was in his office that Saturday, just like me, I told him the story, and he said, ‘let me make a phone call.’ Literally five minutes later, the CEO of PacBio, Hugh Martin, called me up, and said, ‘that sounds very interesting. Let me talk to Eric Schadt and my team.’ We got the strains on Monday November 8. Eric and the CTO called me that day and said they’d be interested in collaborating.”
“We’re going all in!” Waldor recalls Schadt telling him. “They went all in, I must say.”
Waldor’s team grew up the Vibrio cholerae strains on November 8, and the DNA samples arrived at PacBio in California on Wednesday, November 10. “We got a good idea of the [identity of the] two Haitian strains on the evening of November 12. We sent three other strains for comparison, including a true resequencing of the canonical strain.”
Each of the five strains took about one day to sequence to about 60X coverage. “They did an outstanding job in the analysis,” says Waldor. “Most of the credit for this project goes to Eric and his team.”
“The rapidity and depth of the sequence using this 3rd-generation sequencing technology has enormous potential to transform how we can analyze outbreaks of infectious disease and even the prediction of future outbreaks because of the power of their technology.”
According to PacBio, the five cholera genomes were sequenced on November 12 to 12-15X coverage in less than two hours. [This is the kind of speed I predicted in my 2008 Google Tech Talk YouTube as vital for deploying sequencing in real-life emergencies - AJP]. Further runs bumped up the coverage to 60X over the course of the day. Over the next three days, the sequence data were subjected to in-depth analysis, including genome assembly, annotation, and sequence comparisons, including comparisons to nearly two dozen published cholera genomes.
Subsequent bioinformatic analysis confirmed earlier hints matching the Haitian cholera outbreak to a variant of the “El Tor O1” variant from South Asia. This strain has never been documented in the Caribbean or Latin America, suggesting that a recent visitor to the island, possibly a volunteer or a United Nations peacekeeper helping relief efforts after the earthquake, could have inadvertently carried the bacteria to Haiti from outside Latin America.
“Our data strongly suggest that the Haitian epidemic began with the introduction into Haiti of a cholera strain from a distant geographic source by human activity,” is how Waldor puts it. The results disprove another possibility, namely that the strain arose from the local aquatic environment.
The identification of the Haitian strain has important implications regarding vaccination, says Waldor. “By showing this strain is closely related to a south Asian strain, and not close to Latin American isolates, it shows that human activities – food or water brought from South Asia, led to this epidemic and not from transfer from Latin America. That’s a conclusion that allows us to alter our policies in the future to prevent such a thing. For instance, relief workers or security forces should be deployed where there is no domestic or endemic cholera. Otherwise, workers should be screened and/or vaccinated, so they can’t bring it in.”
Speed of analysis is crucial in such situations, says Jason Harris, requiring a technology “that could immediately provide comprehensive genomic information about this virulent strain and quickly get it into the hands of the global health and research community. In the initial stages of a major epidemic, real time is the speed we need to be working in order to have the greatest impact on saving lives.”
From PacBio’s perspective, Schadt says that “real-time monitoring” of pathogens opens the door to using his firm’s technology as “a routine surveillance method, for public health protection in addition to pandemic prevention and response.”
Warning Sign
Just last month, Waldor and colleagues published a perspective the New England Journal advocating the establishment of a cholera vaccine stockpile in the United States to be used to counter outbreaks such as the one in Haiti. There are an estimated 3-5 million cases of cholera each year resulting in about 100,000 deaths.
“The resistance to vaccination is truly baffling,” Waldor said at the time. The Harvard/PacBio results raise another troubling possibility: expansion of the epidemic with the replacement of the currently endemic strains with much more threatening variants. “That would be a deeply troubling outcome,” says Mekalanos. “A cholera vaccination campaign might not only control the disease but also minimize the dissemination beyond the shores of Hispaniola,”
The scientific manuscript was drafted over a few days and submitted to NEJM on November 19. The paper was formally accepted on December 1 and published December 9. “That’s like my record,” says Waldor.
Further Reading: Chin, C-S. et al. “The origin of the Haitian cholera outbreak strain.”New England Journal of Medicine December 9, 2010.
[PacBio [PACB] stocks shot up by about 10% upon the news of this historical landmark in applying rapid genome sequencing for control of Pandemics. This is the first major example how "time critical" sequencing could make a global difference. This entry can be debated in FaceBook of Andras Pellionisz]
Which Is a Better Buy: Complete Genomics or Pacific Biosciences?
By Brian Orelli | More Articles
November 29, 2010
Today's battle pits recent DNA sequencing IPOs Complete Genomics (Nasdaq: GNOM) against Pacific Biosciences of California (Nasdaq: PACB). Which one is the better buy? Let's have a closer look.
What they do
Technically, Complete Genomics and PacBio aren't direct competitors, but they're close enough. Complete Genomics specializes in sequencing DNA for researchers; PacBio sells DNA sequencing equipment for researchers. It comes down to whether researchers will outsource their sequencing or do it themselves, so the two end up directly competing with the funds researchers have to carry out experiments.
And the two have plenty of additional competition. Illumina (Nasdaq: ILMN), Life Technologies (Nasdaq: LIFE), and Roche have been selling DNA sequencers for a while. Illumina also offers a sequencing service direct to patients.
Both Complete Genomics and PacBio are still in the ramping-up stage. Neither is turning a profit nor should you expect one soon. Fortunately, they have an influx of cash from their IPOs to keep things going for a while.
As of the end of September, Complete Genomics had sequenced 400 genomes to date, 300 of which were completed in the third quarter. At the time, the company had a backlog of more than 800 genomes.
PacBio had sold seven of its limited production models as of the middle of September and had orders for four more that were scheduled to ship by the end of the year. We should get an update on the commercial launch of its machine when PacBio has its earnings conference call tomorrow after the stock market closes.
What investors think
One of the things David Gardner looks for when picking stocks for the Motley Fool Rule Breakers newsletter is strong past price appreciation. This isn't technical analysis mumbo jumbo, but there's something to be said for a company that other investors have confidence in.
Complete Genomics and PacBio don't have a very long history, but so far their ability to catch the fancy of investors has been fairly limited.
Company
Expected IPO rang
Actual IPO price
Price Close Nov. 26
Complete Genomics $12-$14 $9 $7.76
PacBio $15-$17 $16 $11.53
What this Fool thinks
Investors are rightfully timid about the DNA sequencing hype. Remember how the Human Genome Project was going to save the world? Human Genome Sciences (Nasdaq: HGSI) was worth more than $100 on a split-adjusted basis in early 2000. Ten years later, with the company on the verge of getting its first drug approved, the stock is trading at only $25.
Famous last words or not, I think this time it's different. We know a lot more about what genes do now than we did 10 years ago, and the price of sequencing has come down considerably. At some point, getting a DNA sequence will be a routine part of a newborn's first checkup, and everyone who is already alive is going to have to catch up. There's a lot of DNA to be sequenced and therefore a lot of money to be made.
But investors do need to be careful. The market may be huge, but there's a diminishing size as more people get their genomes sequenced since your genome doesn't really change.
That's different than say the software market, where the potential customers remain constant since Microsoft can convince current customers to upgrade to newer software.
The best long-term hope for Complete Genomics and PacBio is probably to expand into other markets, just as Intuitive Surgical (Nasdaq: ISRG) has expanded the use of its robotic surgery machines into additional surgical procedures. Tumors often have genetic mutations, so they'll likely get sequenced to determine the best drugs to treat the cancer. And you could use DNA sequencing to identify viruses and bacteria.
Still, I think this is ultimately a boom-bust industry, albeit with the bust still many years away.
Which one?
If you're interested in trying to catch the boom and get out before the bust, both Complete Genomics and PacBio look like a good choice to benefit from an exponential increase in DNA sequencing.
It's too early to make a definitive call, but of the two, I like PacBio better because I'm not fond of the low-cost, high-volume business model. Sure, it's worked for Costco and Wal-Mart, but I like PacBio's razor and blade model -- sell the machine once and then continue to supply reagents year after year -- a little better.
Which one is your pick? Take the poll and let us know your reason in the comment box below.
[Actually, both in practice and in theory the answer is rather easy to tell. In practice, if one is limited to the price of a stock (an astonishingly narrow-minded approach), the cheapest stock is that of Complete Genomics. In theory, it is also easy to pick the winner from all entrants of the "Sequencing" technology companies. Since sequences alone are absolutely worthless without interpretation, the winner will be that secures the key to the algorithmic (thus software-enabling) theoretical high ground. Which will it be out of the five listed (and further runner-up) companies? It may be one of them, some sharing key IP - or perhaps another company that is not even listed above. This entry can be debated in FaceBook of Andras Pellionisz]
The discoverer of the double-helix says the disease can be cured in his lifetime. He's 82.
By ALLYSIA FINLEY
The Wall Stree Journa
November 27, 2010
'We should cure cancer," James Watson declares in a huff, and "we should have the courage to say that we can really do it." He adds a warning: "If we say we can't do it, we will create an atmosphere where we just let the FDA keep testing going so pitifully."
The man who discovered the double helix and gave birth to the field of modern genetics is now 82 years old. But he's not close to done with his life's work. He wants to win "the war on cancer," and thinks it can be won a whole lot faster than most cancer researchers or bureaucrats believe is possible.
Call it the last crusade of one of the nation's most indefatigable and productive scientists. In a long career, Dr. Watson was awarded the Nobel Prize in Physiology or Medicine (1962), garnered 36 honorary degrees and wrote 11 books, including the bestseller "The Double Helix" (1968), which recounts his dramatic quest with Francis Crick to determine the structure of DNA. He spent the early 1990s helping spearhead and direct the Human Genome Project to identify all human genes. And there's the 40 years he's devoted to transforming the Cold Spring Harbor Laboratory in Long Island, N.Y., from a ramshackle ruin into the elite cancer research institute it is today.
To hear Dr. Watson tell it, this determination began—at least formally—in Hyde Park at the age of 15. "The University of Chicago always used to be ranked in the U.S. News and World Report as the third most unpleasant college to go to in the United States," he chuckles. "It was a place that was knocking you down and expecting you to get up by yourself. Nobody was picking you up."
He says he's the better for it because it taught him how to be a leader, something he thinks there are too few of nowadays. "The United States is suffering from a massive lack of leadership. There are some very exceptional, good leaders. I'm not saying they don't exist, but to be a good leader you generally have to ruffle feathers," which Dr. Watson believes most people aren't willing to do.
He certainly is. Throughout his career, Dr. Watson has been a lightning rod for controversy, beginning with his unflattering portrayal of some fellow scientists as awkward and hostile in "The Double Helix." He later butted heads with fellow genetic researcher and founder of Celera Genomics, Craig Venter, over the commercialization of the human genome. Dr. Venter wanted to turn a buck for his firm by selling access to the human genome sequence. Dr. Watson thought the human genome database should be free to the public.
In 2003, Dr. Watson stirred up another academic kerfuffle when he joked that genetic engineering could be used to make all women beautiful and, more seriously, that gene therapy could one day cure stupidity. His 2007 book "Avoid Boring People: Lessons from a Life in Science" used the following words to describe former Harvard colleagues: "dinosaurs," "vapid," "mediocre" and "deadbeats."
But these days, Dr. Watson is sparring with the bureaucratic behemoth known as the FDA.
"The FDA has so many regulations," Dr. Watson says. "They don't want you to try a new thing if there's an old thing that might work. . . . So you take the old thing, but we know cancer changes over time and we would really like to get it whacked early, and not late. But the regulations are saying you can't do these things until we give you a lot of s— drugs," he snorts. "Shouldn't this be the patient's choice to say I would rather beat the odds with a total cure rather than just to know that I am going to have all my hair fall out and then after a year I'm dead? . . . Why should [FDA commissioner] Margaret Hamburg hold things up? There's the cynical answer it gives employment to lawyers."
Ah, the lawyers. "Right now America is being destroyed by its lawyers! Most of the people in Congress just want work for lawyers." He quickly adds: "I was born an Irish Democrat, so I wasn't born into a family which instinctively says these things. But my desire is to cure cancer. That's my only desire."
Dr. Watson may have been born an Irish Democrat, but he's more of a libertarian when it comes to scientific regulation. In his view, freer research enables greater innovation. "I do think one success of Northern Europe, which the United States came from, was its willingness to accept innovation in business practices like Adam Smith and the whole Enlightenment. It essentially made the merchant class free instead of controlled by the king and aristocracy. That was essential."
Another impediment to innovation today is funding. Dr. Watson thinks money is being spread around too much and not enough is going to the best brains. "Great wealth could make an enormous difference over the next decade if they sensibly support the scientific elite. Just the elite. Because the elite makes most of the progress," he says. "You should worry about people who produce really novel inventions, not pedantic hacks."
He also complains that too often government and private money help support scientists rather than cutting-edge science. "That's not the aim of our money—job research, job security. It should be job insecurity. Or hospital insecurity. Empty the breast cancer ward."
Dr. Watson's commitment to innovation is why most scientists at Cold Spring Harbor don't have tenure. Instead, they have security for five years. "We can't decide at the age of 40 that you're going to have a job for 30 years even though you're not producing much science."
Although Dr. Watson says leaders should think in the long term, he is critical of those who say we might find a cure for cancer in another 10 to 20 years. "If you say we can get somewhere in 10 to 20 years, there's no reason you shouldn't be saying 20 to 40, except then people would just give up hope. So 10 to 20 still maintains hope, but why not five to 10?" He adds that there's no reason we shouldn't know all of the genetic causes of major cancers in another few years.
"I want to see cancer cured in my lifetime. It might be. I would define cancer cured as instead of only 100,000 being saved by what we do today, only 100,000 people die. We shift the balance." Alas, modern research has merely reduced cancer mortality in the United States from about 700,000 per year to about 600,000. "We've still got 600,000, which is what the problem is."
The challenge now—at least by Dr. Watson's lights—is killing the mesenchymal cells that cause terminal cancer and figuring out why those cells have become chemotherapy-resistant. He says scientists and doctors are reluctant to tackle terminal cancer because there's so much that remains uncertain about its causes.
The treatment of early-stage cancer, however, is more certain since scientists have already pinpointed many of the genes that are associated with specific cancers. But they still don't know exactly which gene or gene mutations lead to terminal cancer [one reason they still don't know may be that NO GENE OR GENE MUTATION may be the cause of cancer - but HoloGenome Regulation derailed - AJP].
Dr. Watson points out that scientists are correctly looking at DNA before they treat early-stage cancer, since different drugs work on different genes. "If I had cancer I'd certainly want them to look at the DNA to see if there's a Ras gene or change in the Ras gene," which signals cell growth and proliferation.
He points to lung cancer as a case in point. Right now Dr. Watson says there are two types of treatments. The first is a new drug that treats cancers linked with the specific gene ALK, which has proven effective in trials. "I have no idea if it works beyond the first six months, but most drugs don't work in the first six months, so that's very good."
Then there's Tarceva and Iressa, two drugs that inhibit the epidermal growth factor receptor that causes cancer cells to divide. But "they only work on about 10% of people," who have specific mutations in their tumors. "And they work for about a year, and then you become resistant. And we don't have anything to treat the resistant cancer with."
So this is where we now stand in the war against cancer: at our own 20-yard line with a playbook full of untested, complicated plays. But Dr. Watson is optimistic that there could be a Hail Mary: a single drug that will work on all of the deadly mesenchymal cells. All of these cells, he notes, secrete a protein—interleukin-6—and in lab experiments, adding interleukin-6 to lung cancer cells that had been controlled by anti-cancer drugs made them resistant to the treatments.
Thus the key to curing cancer may be finding a drug that blocks interleukin-6. "While this would be wonderful if it turns out to be true," he says, he doesn't know if it is and he concedes, "it's not conventional wisdom."
Despite his crusade, it's not cancer that personally scares Dr. Watson. It's Alzheimer's disease. When he had his genome sequenced and published in 2007, he specifically asked that the doctors not reveal whether he had a gene that would make it virtually certain he would develop Alzheimer's. The mentally debilitating disease would make it impossible for him to continue his research—not to mention that it would estrange him from his family.
I ask Dr. Watson about the double-edged sword of DNA testing and its proliferation. As prices fall due to improved technology, the market for testing grows. Now companies like 23andMe are selling personal DNA tests for roughly $500. Simply spit in a tube, send it in, and in a few weeks you'll get back everything you've ever wanted to know about your genetic inheritance—and some stuff you'd probably rather not.
While such information might encourage some people to adopt healthier lifestyles or get more frequent check-ups, it could also cause undue anxiety. For example, what do you do when you learn at the age of 20 that you have a gene that makes you susceptible to Parkinson's disease—something that you can't do anything about?
To this question, Dr. Watson says that DNA testing "has to involve a lot of acquired common sense." But he doesn't think that common sense should come from government agencies. "I don't see how regulations can do it." Banning it because of potential negative repercussions would be futile.
Futile—now that's a word you won't often hear Dr. Watson use. "I'm going to look optimistically and of course sometimes it doesn't work," he says. But "you move forward through knowledge. You prevail through knowledge. I love the word prevail. Prevail!"
Ms. Finley is assistant editor of OpinionJournal.com.
[I am not going to mince words here - time for a blunt talk, in order for Dr. Watson to renounce Crick's "Central Dogma" (That Dr. Watson actually never subscribed for). Jim Watson is a friend and a hero (I have chosen my FaceBook icon standing next to him and his Double Helix at Cold Spring Harbor) - when I was invited to present a "breakthrough idea" - ditching both JunkDNA and Central Dogma obsolete axioms to be superseded by The Principle of Recursive Genome Function. Jim Watson is far too clever, and he never subscribed to e.g. Crick's "Central Dogma" - Jim just stated the truth (DNA>RNA>PROTEIN), never saying that "the information never recourses to DNA". However, now we need his leadership (not only to do away with FDA obsolete legal mandate of 1976), but more importantly for science to make a clean break to say with full force that cancers (the explosion of genome regulation) will never be "cured" unless we target it as it is; a derailment of Recursive Genome Function. Dear Jim, renounce Crick's "Central Dogma", "break down that wall"! Just look at cancerous, uncontrolled growth; some can be seen by the naked eye to be the result of Fractal Iterative Recursion went out of control. This entry can be debated in FaceBook of Andras Pellionisz]
News from 23andMe: a bigger chip, a new subscription model and another discount drive
[GRAB IT NOW - $99 Offer Extended till December 25, or when supply runs out - AJP]
[$99 plus a monthly $5 covers 175 conditions - click on 23andMe website to see the video testimonials how a $99 gift may save the life of a loved one - AJP]
Category: 23andme • personal genomics
Posted on: November 24, 2010 8:45 AM, by Daniel MacArthur
Personal genomics company 23andMe has made some fairly major announcements this week: a brand new chip, a new product strategy (including a monthly subscription fee), and yet another discount push. What do these changes mean for existing and new customers?
The new chip
23andMe's new v3 chip is a substantial improvement over the v2 chip that most current customers were run on (the v2 was introduced back in September 2008). Firstly, the v3 chip includes nearly double the number of markers across the genome, meaning that it is able to "tag" a larger fraction of common genetic variants ("tagging" means that a marker on the chip is sufficiently highly correlated with other markers that it can be used to make a reasonable guess about someone's sequence at those other markers). Secondly, the chip now includes additional custom markers targeting specific variants that the company thinks will be of interest to its customers.
The technical details: the v3 chip is based on Illumina's HumanOmniExpress platform, which includes 733,202 genome-wide markers. The company has also added around 200,000 custom markers to the chip (vs ~30,000 on the v2 chip). We don't yet have full details on what those custom markers are, but there's a summary of the improvements over the v2 chip in the press release:
Increased coverage of drug metabolizing enzymes and transporters (DMET) as well as other genes associated with response to various drugs.
Increased coverage of gene markers associated with Cystic Fibrosis and other Mendelian diseases such as Tay-Sachs.
Denser coverage of the Human Leukocyte Antigen region, which contains genes related to many autoimmune conditions.
Deeper coverage of the HLA is particularly welcome - variants in this region are very strongly associated with many different complex human diseases (including virtually every auto-immune disease), and the v2 chip was missing several crucial markers.
The addition of more rare variants associated with Mendelian diseases like cystic fibrosis is entirely unsurprising, but the devil will be in the details: in the arena of carrier testing 23andMe is up against the extremely thorough and experimentally validated platform offered by pre-conception screening company Counsyl. It will be very interesting to see the degree to which 23andMe focuses on the carrier testing angle in their marketing of the v3.
More power for imputation
From the perspective of those of us simply interested in squeezing as much information as possible out of our genetic data, the v3 chip is a welcome arrival. The additional markers present on the chip will substantially improve the power of genotype imputation - that is, making a "best guess" of our sequence at markers not present on the chip using information from tagging variants.
The HumanOmniExpress platform has some decent power here: in European and East Asian populations, 60-70% of all of the SNPs with a frequency above 5% found in the 1000 Genomes pilot project are tagged by a marker on the chip (in this context, "tagged" means "has a correlation of 80% or greater"). In effect, that means that being analysed at the one million markers on this chip allows you to make a decent inference of your sequence at around another 4.5 million other positions in your genome.
At the recent American Society of Human Genetics meeting, 23andMe presenter David Hinds suggested that the medium-term future for 23andMe rested not in moving to sequencing, but rather on expanding the role of genotype imputation. The new chip will certainly help with that. However, it's worth emphasising that imputation is not a replacement for sequencing: it is only accurate for markers that are reasonably common in the population, meaning that it will miss most of the rare genetic variants present in your genome.
However, improved imputation with the extra markers on the v3 chip will mean that 23andMe should be able to do a decent job of predicting customer genotypes at the positions we currently know the most about - those arising from genome-wide association studies of common, complex diseases. I expect that many customers will see changes to their disease risk profiles as a result of the move to the new chip.
Over at Genomes Unzipped, we've already been looking at various approaches to imputation from our 23andMe v2 data, and we'll put a post together soon looking at how this will improve with content from the v3 chip.
The new product strategy
There are two interesting things that 23andMe has done with the new product line: firstly, it has reversed the transient division of its products into separate Health and Ancestry components; and it has introduced a subscription model in which customers pay $5/month for updates to their account as new research findings become available (previously, customers paid a flat purchase fee and were then entitled to free updates).
The recombining of the Health and Ancestry products into a single Complete package is an extremely interesting move. As Dan Vorhaus notes, the previous separation of the two product lines was plausibly interpreted as a way for the company to pre-empt the possibility of a regulatory crackdown by the FDA: if regulators hammered the company's ability to offer health-relevant tests directly to consumers, 23andMe could easily switch to its Ancestry product to maintain a revenue stream.
In the currently uncertain regulatory environment, the decision to reverse this division is an unexpected one. It certainly appears that 23andMe - flush with cash following a successful $22M funding round - is somewhat more confident than I am about the regulatory future for health-relevant genetic tests; I hope that confidence turns out to be warranted. [I am much more of an optimist; since 23andMe could easily outsource their services to Asia or even Central Europe - AJP]
Subscription fees: good for customers
The decision to add a subscription fee may prove unpopular with customers (and has already received a qualified thumbs down from blogger Dienekes, albeit for perfectly sensible reasons). However, a business model based on providing continuous product updates that customers don't pay for has never really looked like a viable long-term business model.
I personally see a subscription model as a positive move: it provides a steadier revenue stream for personal genomics companies, which means less focus on splashy discount drives. It also provides more of a financial incentive for the company to improve the ongoing experience of customers: under the current deal customers are locked in for the first 12 months, but after that 23andMe will need to convince them that it's worth continuing to pay for additional content and features.
Other personal genomics companies (e.g. Navigenics) have long relied on some form of a subscription model, but typically at a higher cost. I think 23andMe is hitting a pretty reasonable price point here: I suspect $60/year would be seen by most customers as a fair price.
OMG discount!
That doesn't mean that 23andMe has abandoned the discount drive approach just yet, of course: they're currently offering v3 kits for just $99 (vs the retail price of $499), which must be purchased along with the previously mentioned 12-month subscription fee of $60. Non-US customers can also expect a ~$70 postage fee, based on comments on Twitter.
Anyone who missed out on the DNA Day sale and is keen to take advantage of the v3 content would be well-advised to get in quickly. The discount code is B84YAG.
[Terrific Holiday Gift - grab it TODAY (offer is still good till November 29, or when the supplies run out)! This entry can be debated in FaceBook of Andras Pellionisz]
This Recent IPO Could Soar [as money for "Analytics" makes "Sequencing" sustainable - AJP]
[This double IPO could soar? - Yes, when funds start pouring into "Analytics", to make "Sequencing" business sustainable - AJP]
Tuesday, November 16, 2010
Street Authority
The initial public offering (IPO) market continues to heat up with deals coming this week for GM (NYSE: GM), Booz Allen (NYSE: BAH), Caesars Entertainment (NYSE: CZR) and a half dozen other firms. The flurry of deals puts us on track for the most robust quarter for IPOs in more than two years. And looking at the pipeline of new deal registrations, the first quarter of 2011 may be even hotter.
I recently looked at a strategy that uses analyst research to find stocks about to pop. [See: "The Secret Way to Play IPOs"]
Yet that's not the only way to look for upside among recent new deals. You can also scan lists for "broken IPOs," which are firms that have been public for a short while and are drifting lower while investors focus on more established companies.
Last month, I took a look at top-performing IPOs, as I wrote back then, "many new IPOs take time to find their sea legs and only take off well after their debuts. In fact, every single stock [mentioned in that piece] came out of the gate with a whimper and only started rising many weeks or months after their debut."
The stocks in the table below are all broken IPOs, each is trading off at least -15% from its IPO offering price. I've pored through the list and found the best rebound candidate.
Complete Genomics (Nasdaq: GNOM)
Any company that struggles to fetch a desired IPO price is a conundrum for investors. On the one hand, a lower-than-expected price is a sign that investor demand just isn't there. On the other hand, you've got a chance to buy a stock at a cheaper price than investment bankers have recently assessed. Case in point, Complete Genomics, which hoped to sell shares for $12 to $14, had to settle for a $9 offering price last Friday, and the stock is now down to $7. That's just half the high end of the expected range of pricing. The weak demand may be due to the fact that rival Pacific Biosciences (Nasdaq: PACB) had just pulled off an IPO weeks earlier, snatching the attention of any fund managers that buy these kinds of companies.
Complete Genomics is involved in DNA sequencing. While other firms like Illumina (Nasdaq: ILMN) and Pacific Biosciences sell equipment to scientists, Complete Genomics acts as a service bureau, performing third-party DNA sequencing services.
Why the tepid IPO reception? Complete Genomics is just starting to generate sales and investors fear that quarterly losses will continue for the next year or two, setting the stage for another round of capital-raising. Ideally, the company would have waited until sales started building and losses started shrinking, but its backers likely balked at putting any more money into the company.
Yet this stock has all the makings of an IPO rebounder, as the firm's underwriters, led by Jefferies, get set to publish initial reports on the company in early December. You can expect to see bullish forecasts of projected sales growth rates, and if you look out far enough, fast-rising profits.
Analysts are likely to note that Complete Genomics' DNA sequencing approach may prove to be very cost-effective and capable of high market share. Industry leader Illumina can analyze an entire sequence of DNA strands for around $10,000 in materials. Complete Genomics thinks it can do it for just $4,500. And over time, prices could drop well below that level, making DNA sequencing for the masses more feasible.
Action to Take --> Keep an eye on new IPOs. They often stumble out of the gate, giving the false impression that they are unworthy investment candidates. Of the recent crop of IPO laggards, Complete Genomics appears to have the greatest potential upside.
With a broken IPO and scant revenues, investors will need to focus on the company's technology value. Complete Genomics is valued at less than $150 million, roughly $20 million less than the money spent developing its technology platform. The revenue profile tells you that this is a risky as a biotech stock. But if the company can make headway in the space, investors may start to make comparisons to Illumina, which is valued at $7.2 billion -- 50 times more than Complete Genomics.
-- David Sterman
[While a mere $10 M of Round A or M/A (with IP) into "pure-play DNA Analytics Company", like HolGenTech, Inc. (that leverages HPC for Genomics) could yield a decisive advantage to a "Sequencer" Company (if such deal would be exclusive), the compelling argument above that the two fresh "Pure-Play" Sequencer Companies are grossly undervalued (by a factor as much as 50x), thereby providing a historical investment-opportunity, David assumes that long-public genome companies (Roche/454, Illumina, Life Technologies/Ion Torrents) might not try to take the high ground of "Analytics" - and thus even force (as an auditor of Complete Genomics warned its investors) to go out of business before it could take off. This assumption may be mistaken - as the belief that a key "pure-play DNA Analytics Company" would do an "exclusive" - rather than go for the easily $10 B opportunity if its Genome Computers cater for all Sequencers in a non-exclusive basis (see below the explosive global market of Sequencers humming with an eye on $1,000 sequences - but in dire need of $1 M interpretation). This entry can be debated in FaceBook of Andras Pellionisz]
BGI – China’s Genomics Center Has A Hand in Everything
Singularity Hub
November 11th, 2010 by Aaron Saenz
[See interactive (zooming) World Map of Sequencers here - AJP]
When it comes to genomics, China seems a little like the proverbial kid in the candy store – she wants a taste of everything. Of course, unlike the child, China might be making a bid to own the candy store outright as well. The Beijing Genomics Institute (BGI), now located in Shenzhen, is the leading genomics facility in China, and all of Asia. BGI has striven to make a name for itself in every major international genome sequencing project of the last decade. The International Human Genome Project, the International Human HapMap Project, sequencing SARS, the Sino-British Chicken Genome Project, etc. It was also responsible for completely sequencing the rice genome, the silkworm genome, the giant panda genome…the list goes on an on. By the end of this year BGI will have 128 of Illumina’s HiSeq 2000 platforms, 27 of AB’s SOLiD 4 systems, and many other sequencing devices. At full capacity this means they will be capable of the equivalent of 10,000+ human genomes per year. And they are still growing. BGI may not be the largest genomics facility in the world, but it is has phenomenal support from its government, ambition to expand quickly, and a hand in dozens of major sequencing projects. You can’t talk about the future of genetics without talking about China.
In late 1999 the Beijing Genomics Institute started to build China into a world leader of genetic research. In the decade that’s elapsed since, they’ve put their name on some major developments...
Since its inception, BGI has had a very ambitious attitude when it came to participating in world genomics. Every time they were presented with a new project, they basically said, sure, we’ll be a part of that. They contributed 1% to the Human Genome Project’s reference genome, and 10% to the Human HapMap Project. It was like they never met a sequencing project they didn’t like.
That attitude hasn’t seemed to wane at all. BGI is spearheading efforts that will sequence a wide variety of organisms. There’s the 1000Genomes Project aimed at producing a wide database of human genomes from people all over the world. They are also working to sequence 1000 plants and animals, and have already completed 14+ of the former and around 50 of the latter. In 2009, BGI launched its effort to map the genomes of 10,000 microbes – they’ve managed 800 bacteria, 100 fungi, and 100 viruses so far, with more finished every day. They are looking for collaborators to sequence 1000 Mendelian Disorders in humans. Completion of large genetic databases like these will be part of what could empower genetic research to finally make the discoveries the public has been waiting for since the first human genome was sequenced a decade ago.
Even while BGI is a testament to Chinese ambitions in genomics, it also speaks to the prominence of the US in that field. BGI relies heavily, almost exclusively, on sequencing technology rooted in California. Illumina’s HiSeq2000 and Applied Biosystems SOLiD 4 form the bulk of BGI’s machine workforce. To be fair, most of the world has focused on using these systems as well, and BGI is working to expand its hardware horizons, collaborating with OpGen on new optical sequencing methods. Still, when one sees BGI’s successes in genomics one also has to acknowledge that such capabilities weren’t developed in a vacuum. China’s sequencing projects, like every nation’s sequencing projects, have worked as part of a larger global effort.
The only real question, then, is how much will China simply be a part of that worldwide phenomenon, and how much will it lead? Even if the hardware is largely developed by California companies, those companies themselves are international entities [suffice to point out that Life Technologies' just announced 5500 SOLiD sequencers are co-produced with Hitachi - AJP]. BGI is officially part of the sequencing club, recognized by Illumina as one of its associated world class facilities. BGI isn’t some second tier group working its way to the top, it’s already at the top, sharing space with the other lead genomics institutions around the world. If BGI and China continue to dedicate money, labor, and insight into genomics, they’ll be able to set the agenda for many sequencing projects around the globe. Actually, they’re already doing this with their various sequencing projects for microorganisms, plants, animals, and humans.
I know that many of us will view BGI’s growing importance through the lens of competitive national spirit. Yet no matter your feelings about China, you have to view BGI’s accomplishments as wonderful gifts to the global scientific community. Every genomics center around the world is going to have different specialties (Complete Genomics is dedicated to bringing down the costs of human whole genome sequencing, for instance) and it’s only through combining these disparate efforts that we’ll create the general understanding we need to move the field of genetics forward. It’s a team effort. Yay China, Yay us.
[If one would have to point out an outstanding difference of the BGI from much older schools of the UK and USA is Genome Informatics. While it is true that both Illumina and Life Technologies' Sequencers are based on biochemistry-technology of the USA, in BGI in Shenzehen (in the backyard of Hong-Kong) 3,000 Genome Informatics specialists are working busily, with the average age of 27 (thus by definition none of them can be "old schoolers". Hong-Kong and Seoul has some of the very best Neural Network specialists of the World. Once they devote full attention to "The Principle of Recursive Genome Function", China will set PostModern Genomics into an entirely new trajectory of hypergrowth. - This entry can be debated in FaceBook of Andras Pellionisz - AJP.]
Most doctors are behind the learning curve on genetic tests - the $1,000 sequence and $1 M interpretation
Updated 10/24/2010 8:37 PM
USA Today
By Rita Rubin, USA TODAY
GREENWICH, Conn. — It's ironic that Steven Murphy's medical practice is located in this town's Putnam Hill historic district.
His Maple Avenue building, the Dr. Hyde House, is a cozy hodgepodge of architectural styles, with stone and stucco walls, a double bay corner window and orange clay roof tiles. It has housed doctors' offices for a century.
Although Murphy's surroundings may be old-fashioned, his practice is not. Murphy, a board-certified internist who writes a blog called The Gene Sherpa, is one of a small minority of doctors who use genetic tests to help manage their patients' care.
"The majority of people we see have a very strong family history of X, Y or Z disease," says Murphy, who'll be 34 this week. He doesn't bring up genetic testing until after taking a detailed personal and family medical history and assessing such risk factors as cholesterol and blood pressure. "I tell them there are lots of ways to dig deeper. Then I also tell them the limitations."
Other patients show up with the results of personal genome tests, costing upward of $1,000, they had ordered online from companies such as 23andMe and Navigenics. They want to know what it all means. "We like to call it the thousand-dollar genome with the million-dollar interpretation," Murphy says.
Having trained in genetics as well as in internal medicine, he's much further on the learning curve than most doctors.
Since the Human Genome Project was completed in 2003, the introduction of new genetic tests has far outpaced the ability of doctors — who typically have little training in genetics — to figure out what to do with them. Some tests are marketed to help predict disease risk, others to determine how patients might respond to certain medications.
"This is going to become a very big part of mainstream medicine, and we really aren't ready for it," says human geneticist Michael Christman, president and CEO of the Coriell Institute for Medical Research, a non-profit research center in Camden, N.J.
A deluge of data
Eric Topol, director of the Scripps Translational Science Institute in La Jolla, Calif., cites what he calls "a really great paradox."
"Ask patients 'whom do you trust with your genomic data?' and 90% say their physicians," Topol, a cardiologist, says. Yet, when Medco Health Solutions, the pharmacy benefit manager, and the American Medical Association surveyed more than 10,000 doctors, only 10% said they felt adequately informed and trained to use genetic testing in making choices about medications.
That physician survey was conducted two years ago, but Topol, Christman and others in the field doubt much has changed.
Take the blockbuster drug Plavix. In March, the Food and Drug Administration added the strongest type of warning, a black box, to the label of Plavix, which is taken by millions of Americans who have had stents inserted to keep their coronary arteries open. Plavix is supposed to reduce the risk of blood clots in those stents, but, as the boxed warning notes, some patients might not effectively convert the drug to its active form in the body.
The warning points out that a genetic test can identify those patients, who might need a higher dose of Plavix or a different drug. Yet, Christman says, "even in tertiary academic medical centers, you don't have routine testing for Plavix efficacy."
On the other hand, Topol says, doctors have ordered 250,000 $100 tests for a gene called KIF6, tests that were aggressively marketed. One KIF6 variation was thought to raise heart disease risk by up to 55%, but, Topol says, a study this month in the Journal of the American College of Cardiology shot that down.
Considering that there are thousands of genetic tests, doctors might be forgiven for feeling overwhelmed, especially because so many questions remain.
"We have way more data than we have knowledge," says Clay Marsh, a lung and critical-care doctor who directs the Center for Personalized Health Care at The Ohio State University College of Medicine in Columbus. "The biology is struggling to keep up with the technology."
Though some diseases, such as sickle cell and cystic fibrosis, are caused by mutations in a single gene, many common conditions arise from the interplay of a variety of genes and lifestyle and environmental factors, not all of which have been identified.
"Having a family history of heart disease increases your risk of heart disease more than some of these (genetic) markers they test for," Murphy says. "Then, just because you have that marker doesn't mean that's what caused the heart disease in your family. That's one thing I teach residents: No gene is an island."
Right test for one patient
Murphy's first patient on a sunny fall afternoon sat in her home nearly 1,000 miles away, in the village of Niantic, Ill., smack dab in the middle of that state.
Wanda Conner, 72, never met a medication that agreed with her. She heard about the Genelex test for five genes involved in drug sensitivity from her dental hygienist and figured it might provide some answers. So she swabbed some cells from her cheek and mailed them to the company's lab in Seattle.
Besides seeing his own patients, Murphy reviews test results by phone for Genelex customers. He scrolled through Conner's on his computer. Turns out that she carried variations in three of the genes for which she was tested that could affect her response to certain medications.
Murphy touched on types of drugs that Conner wouldn't process normally if taken. He advised her to stay away from SSRIs, or selective serotonin reuptake inhibitors, a class of antidepressants, and cautioned her that she might experience side effects if she took beta-blockers, a heart medication. He promised to fax his report to her doctors.
"They're fascinated with this," Conner says of her doctors in Illinois, "but they don't know much about it. In fact, I probably know more than they do."
Christman's and Topol's organizations hope to change that. "The purpose of our study ... is to determine the best practices, from soup to nuts, in using personal genome information in clinical care," Christman says. "What are the best information technology systems to deliver this?"
For example, he says, when it comes to genetic factors affecting drug response, it probably makes more sense for pharmacists, not genetics counselors, to advise doctors or patients.
The Coriell Personalized Medicine Collaborative is halfway toward its goal of enrolling 10,000 people. Many are doctors. "We're measuring a lot of genetic information about them," Christman says. Genetics counselors explain the results, usually by e-mail or phone, which participants seem to prefer over a face-to-face visit.
The next 5,000 participants will have already been diagnosed with breast or prostate cancer or heart disease. The cancer patients will be recruited through Fox Chase Cancer Center in Philadelphia, the heart disease patients through Ohio State.
Coriell is sharing only results that patients or their doctors can do something about. Expert committees meet twice a year to review the latest findings about different genetic markers. "If somebody came out with an effective cure for Alzheimer's," Christman explains, "then we would report Alzheimer's risk."
In a related study, Coriell is investigating how best to educate doctors about genetic testing and how that affects what they do with results.
Meanwhile, Scripps plans to launch the College of Genomic Medicine, a free online physician training and accreditation program, early next year, Topol says. To become accredited, he says, doctors will spend five to eight hours reviewing materials developed by an international group of leaders in the field and then take a "highly interactive" test.
The genomic medicine college was born at last year's TEDMED, an annual medical technology and health care conference. There, Topol says, both he and Gregory Lucier, CEO of the San Diego-based Life Technologies, a leading supplier of gene-sequencing equipment to academic laboratories, delivered talks about the need to get the medical community up to speed.
As a result, the Life Sciences Foundation, the company's philanthropic arm, awarded Scripps a $600,000 grant to develop the genomic medicine college.
Topol expects interest in the program will be high.
"Consumers are coming into their physician with their genomic data," he says. "Physicians don't want to be trumped in their knowledge by the patient they're looking after. Instead of playing catch-up, they need to be in the leading front of knowledge."
[Whom are we kidding? Doctors spending "five to eight hours" will be equipped to catch up with e.g. 3,000 full-time Genome Informatics specialists' output, just in one place of the globe, the Beijing Genome Institute??? This task is simply nonsense without Doctors' use of results prepared by High Performance Genome Computers. At your annual check-up, does your doctor conduct your actual blood test? Nonsense! The sample is sent to the lab, where super-sophisticated machines conduct the tests, and deliver only the results. The doctor does not even have to look at those "within range". This entry can be debated in FaceBook of Andras Pellionisz - AJP.]
Forget About a Second Genomics Bubble: Complete Genomics Tumbles on IPO First Day
Xconomy
Luke Timmerman 11/11/10
Super-fast, super-cheap DNA sequencing technologies have made big news in biotech the last couple years. But the early returns have made it clear that investors haven’t gone ga-ga for genomics like they did a decade ago.
The latest data point arrived today in the form of Complete Genomics (NASDAQ: GNOM). This Mountain View, CA-based company, which aspires to lead the way in the quest to sequence entire human genomes for as little as $1,000, got a ho-hum reception from IPO investors this week. The company pared back its forecasted price from a range of $12 to $14, ultimately settling for an initial price of $9 per share. And in its first day of trading as a public company—on an overall down day for the markets—Complete Genomics stock fell 11 percent, closing at $8.03.
The deal still provides Complete Genomics with a much-needed shot of $54 million in fresh capital, which it plans to use to pitch its commercial sequencing service to researchers. But the company was originally hoping to raise as much as $86 million, so Complete Genomics is going to have to pursue this market on a leaner budget.
One of Complete Genomics’ archrivals—Menlo Park, CA-based Pacific Biosciences (NASDAQ: PACB) has also seen some wind come out of its sails. PacBio broke out with a $200 million IPO late last month, commanding a hefty $800 million market valuation at an initial price of $16 a share. Investors initially bid up PacBio’s shares to as high as $17.47, but the stock has since been on a downward slide, closing today at $12.51.
It’s nothing like the hype-driven period of 2000, in which first-generation genomics companies like Human Genome Sciences, Celera Genomics, Incyte, and Millennium saw their stocks enter triple-digit territory on notions that the genome would lead to new cures and personalized medicine, right around the corner. It didn’t happen, and for a nice little retrospective, check out this piece from Nature last March.
This will be a fascinating story to watch over the coming months and years, to see whether PacBio and Complete Genomics, as well as established players like San Diego-based Illumina (NASDAQ: ILMN) and Carlsbad, CA-based Life Technologies (NASDAQ: LIFE), will truly make gene sequencing so cheap and convenient that it’s really accessible to the average biologist and changes the way they think about running experiments. But it now looks clear that the two intriguing new entrants into the market will have to tap into this emerging arena without the luxury of being able to raise more cash at the snap of a finger.
[Some of us have warned against the unsustainability of the "Industrialization of Genomics" without proper "supply chain management". First, the Genome Based Economy is NOT about "running experiments" - but "Sequencing" must match "Analytics by Genome Computers", such that results can be useful for the ultimate markets of the ecosystem: Consumers should be directly involved for their own P4 Health Care. Hospitals must be provided with both Sequencers and matching Genome Computers in order to be useful in diagnosis and personalized therapy, up to personalized cure. Biodefense, Agriculture and Synthetic Genomics are all branches of the "Genome Industry" - but (similar to Nuclear Industry) it can not be achieved based on demonstrably false axioms of the underlying science. (Nuclear reactors or nuclear weapons were simply unthinkable based on the obsolete axiom that "the atom does not split nor fuses"). The predicted crash happened much earlier than projected; with the President's Science Advisor (Eric Lander) admitting to the hordes of workers at ASHG convention in Washington, D.C. that the underlying axioms have been false (and both himself and I went on record with the understanding of genome structure and function in the mathematical and thus software enabling terms of fractals). Just as outlined in YouTube-s "Pellionisz" (2008, 2009, 2010) and in the peer-reviewed science paper "The Principle of Recursive Genome Function, 2008", industries (both Sequencing industry and Big IT now involving Intel, Google, Microsoft, IBM, HP, Xilinx, Altera, Hitachi, Samsung, etc) are ready to take off - as well as major Consumer Companies (Procter and Gamble, Johnson and Johnson, Nestle, etc.) are ready - and so are Big Pharma and Big Agriculture Firms, (such as Roche, Merck, Pfizer or Monsanto, etc). However, without sound mathematical (thus software enabling) genome informatics on one hand, to first understand how the hologenome functions, before plunging into handling its malfunctions, and without an industrial-strength supply chain management on the other, how supply of sequences will not glut our ability to process them, Industrialization of Genomics will remain inherently wasteful and unable to bring out its tremendous potential. This entry can be debated in FaceBook of Andras Pellionisz - AJP.]
The Daily Start-Up: Gene Tests Attracting Money & Scrutiny [23andMe C round with J&J]
NOVEMBER 10, 2010, 10:56 AM ET
The Wall Street Journal
By Scott Austin
This morning’s roundup of the latest venture capital news and analysis across the Web:
The [hollowed by the change of politics in the Congress, making it extremely unlikely that FDA might have an updated mandate from its 1976 legislation anytime soon - AJP] threat by the Food and Drug Administration to regulate direct-to-consumer genetic tests didn’t stop Johnson & Johnson and two venture firms from investing more than $22 million in 23andMe, whose services are designed to help consumers better understand what their genetic information says about their ancestry and disease risk. In July a Government Accountability Office [deeply flawed, admittedly non-scientific analysis of science] report raised questions about the accuracy of these services’ results, and the FDA is moving to regulate them. Besides 23andMe, whose investors include Google Ventures and New Enterprise Associates, other venture-backed companies developing the genetic tests include deCODE Genetics, Navigenics and Pathway Genomics.
GroupMe is only a few months old, but the start-up that lets users send group text messages on their cellphones is already worth about $35 million, according to All Things Digital. That high valuation, set upon GroupMe’s $9 million Series B round led by Khosla Ventures, resulted from a bidding war among prominent venture firms, Business Insider previously reported, and reportedly acquisition interest from Twitter.
Two Groupon co-founders are sinking $1 million in a start-up that helps small businesses manage social-media tools like Twitter and Facebook, The Wall Street Journal reports. The money for Sprout Social comes from Lightbank, a seed fund managed by Eric Lefkofsky and Brad Keywell. Lightbank previously invested in Betterfly.com, which helps users find professional services, and Where I’ve Been, a Facebook application that lets people share travel information.
Rhode Island’s general treasurer-elect, Gina Raimondo, is officially cutting ties with Point Judith Capital, the firm she co-founded. The Providence Journal reports she will no longer make investments, and will set up a blind trust to manage her investment in the firm. Raimondo, who invested in health-care companies, resigned from her boards, which included GetWellNetwork, NABsys, Novare Surgical and Spirus Medical.
“The Deal Professor” explains why entrepreneurs should be sure to maintain control of their companies after raising venture capital. “The key for entrepreneurs in negotiations is to make sure that when they do raise V.C. money, they have options,” writes Steven M. Davidoff, a former corporate attorney who is now a professor at the University of Connecticut School of Law. “If they can get multiple term sheet offers, then they can negotiate to sell the smallest part of their company on the most lenient terms. If you only have one term sheet, you are not going to fare well.”
[This entry can be debated in FaceBook of Andras Pellionisz - AJP.]
NIH Chief Readies the Chopping Block
MedPage Today
Published: November 07, 2010
WASHINGTON -- The National Institutes of Health is considering ways to cut research grant funding in anticipation of possible budget restrictions, NIH Director Francis Collins, MD, PhD, said here Saturday.
"One area we have to look at more is whether our workforce is properly planned for," Collins said in a keynote address at the American Society of Human Genetics meeting.
"I don't think it's reasonable to assume that NIH is going to have another doubling [of its budget] anytime soon, and yet, we never tried to model what the workforce should look like in such [an economically difficult] environment."
One idea that has been raised is whether university faculty members receiving NIH grants should continue to have their salaries largely supported by those grants.
"One might make the case that it would be better for those funds perhaps to be available for other investigators," he said. "We at NIH are committed to looking at this in a careful way, and we're going to have a discussion about this at the NIH Institute Directors Leadership Forum coming up in three weeks."
He elaborated at a press conference after his address. "NIH is supporting an awful lot of salaries, and that seems fair to the degree that they are spending that amount of time on the research. Universities have also discovered that's a great way to build programs... but it may be in the long run that this may not be the best way... for research to be supported."
Despite his worries about the agency's future budget, Collins said he was excited by some of the new research opportunities at NIH. One example is the NIH's new Therapeutics for Rare and Neglected Diseases program, a collaboration among various NIH laboratories to take research findings and develop them to a point where private companies would be interested in getting the products to market.
The program currently has a budget of $24 million, but it is expected to soon grow to $50 million, Collins said. Diseases currently being worked on under the program include schistosomiasis/hookworm, Niemann-Pick Type C disease, hereditary inclusion body myopathy, sickle cell disease, and chronic lymphocytic leukemia.
One interesting compound being studied in the sickle cell project is 5-hydroxymethyl-2-furfural, which binds to the sickled hemoglobin and increases its oxygen affinity, thus allowing blood cells to hold onto oxygen. The work on this compound is now in the late pre-clinical stage, Collins said. "It's something fairly bold for a disease that hasn't attracted much private sector investment."
In general, the NIH has been sheltered from the winds of shifting political opinion, Collins said during the press conference. "For the most part people, regardless of their political party, are concerned about human health -- about themselves, their families, and their constituents. If one can pull medical research aside from hot-button issues like stem cells, most people regardless of political persuasion say 'Yeah, it's a good thing.'"
He acknowledged that the controversy surrounding human embryonic stem cell (hESC) research has been a problem for NIH. The agency is fighting litigation by medical researchers who allege that NIH's recent support of such research violates federal law and hurts adult stem cell research.
At the press conference, Collins noted that the controversy has put a damper on the NIH's efforts to hire a director for its new Center for Regenerative Medicine.
"We were hoping to recruit a world-renowned expert in stem cells to come and direct it [but] with the cloud over the whole field, it is difficult," Collins said. "It has been a factor in slowing down the process of trying to search for that director."
He added that his institution spends nearly three times as much money on adult stem cell research as it does on studies with hESCs -- in fiscal year 2009, the ratio was $397 million to $143 million.
Overall, Collins said, the NIH needs to do a better job of selling itself.
"Whether there is a general understanding that the government has been the main driver of medical research in the last five decades, I'm not sure," he said. "We have not done a good job of getting our brand name appreciated for what it does."
[It is certainly a fact that medical research was driven by the government for half a Century - just like Internet was ramped up from nothing by the initial support coming entirely from the government (defense). Now time has come for Genomics to be integrated with Epigenomics, in terms of Informatics (HoloGenomics) - which will take off driven by private industries worldwide. When Intel, AMD, Xilinx, Altera, Hitachi, IBM, Samsung, Illumina, Life Technologies, Roche, Merck (and fresh IPO-s by Pacific Biosciences two weeks ago, and Complete Genomics tomorrow) - the landscape will change forever. - AJP.]
Next Generation Sequencing
BioCompare
Monday November 01, 2010
by Jeffrey M. Perkel
If you want to get a sense of the current state of the high-throughput sequencing market, look no further than this month's news.
First, the US Department of Energy's Joint Genome Institute mothballed the last of its fleet of Sanger chemistry-based sequencers, completing the transition to newer, faster, next-gen sequencers that has been in the works for several years.
"With these new sequencers incorporated into the production line over the last two years, our productivity has risen to 1 terabase in FY09; 5 Tb in FY10 and to a projected over 25 Tb in FY11," GenomeWeb quotes JGI Spokesman David Gilbert as saying. [1] "To put this in perspective, our total commitment to DOE in FY98 was 20 megabases, which we do now in a few minutes."
The second item was the initial data release from the 1000 Genomes Project Consortium, an effort to sequence the genomes of 1,000 humans and thereby get a handle on human sequence variation. In a report in the journal Nature, the Consortium detailed the sequencing and analysis of nearly 900 individual genomes (179 full genomes and 697 partial exomes), as part of the project's "pilot phase," using a blend of next-gen sequencers from Illumina, 454 (a Roche company), and Life Technologies. [2]
Remarkable as that achievement is, it represents just a fraction of next-gen sequencing output to date. According to an infographic accompanying the article, "at least 2,700 human genomes will have been completed by the end of this month [October 2010], and [the] total will rise to more than 30,000 by the end of 2011." [3]
The final news item: One of those 2,700 genomes belongs to none other than rocker Ozzy Osbourne, of MTV's The Osbournes and biting-the-head-off-a-live-bat fame, who wrote of the experience in the October 24 Sunday Times of London. According to Scientific American, [4]:
"I was curious," he wrote in his column. "Given the swimming pools of booze I've guzzled over the years—not to mention all of the cocaine, morphine, sleeping pills, cough syrup, LSD, Rohypnol…you name it—there's really no plausible medical reason why I should still be alive. Maybe my DNA could say why."
If the JGI announcement and 1000 Genomes Project data release speaks the fact that sequencing whole genomes is, as Jay Therrien, vice president of commercial operations for next-gen sequencing at Life Technologies, puts it, "basically routine," the Osbourne sequencing project attests to how far there still is to go.
"We're in this era at the moment of celebrity genomics," says Daniel MacArthur, a UK-based postdoctoral fellow who blogs [5] and tweets [6] extensively about the next-gen sequencing industry. "That will persist for a while until the cost goes down enough that ordinary people can actually afford to do it. And I guess that's when it will get really interesting."
Of course, from a technology point-of-view, the next-gen sequencing arena has been interesting for years—Harvard geneticist George Church estimates the industry cost has plummeted about 10-fold per year for each of the past five years—and even if that pace is slowing a bit (Church estimates this year's improvement at between three and five fold) it continues to be so.
To wit: the rise of "personal" next-gen platforms. All three of the major sequencing companies, Life Technologies, Roche/454, and Illumina, have announced such devices, which provide a lower-cost, lower-throughput alternative for those researchers who would like to take advantage of next-gen sequencing, but have neither the resources nor the need for the industrial-scale equipment that previously was their only option.
"To keep the latest generation of Illumina fully loaded, you need to have a 400-gigabase-pair project. Most people don't have a 400-Gbp project," says Church, who is a scientific advisor for some 18 next-gen firms, including all six with commercial products (Dover Systems, Roche/454, Life Technologies, Illumina, Complete Genomics, and Helicos).
First out of the gate was Roche/454, which announced its GS Junior system late in 2009. Priced at around $100,000 (as compared to $500,000 for the company's top-of-the-line GS FLX), the GS Junior runs the same pyrosequencing chemistry as the GS FLX, but at a lower throughput: 100,000 parallel reactions, compared to one million on the GS FLX.
"It's a scaled down version of our big system," says Katie Montgomery, marketing communications manager at 454 Life Sciences.
At about 400 bases apiece, those reads currently lead the industry in terms of length. But in 2011, the company plans an upgrade to about a kilobase, says Montgomery, adding that this will be available to existing users as "a small hardware upgrade to accommodate the increased reagent volumes."
On Oct. 26, Illumina announced a new member of its sequencer line, as well. The HiSeq 1000 "is designed for researchers who want the ease of use, industry-leading cost per gigabase (Gb) and data rate of the HiSeq 2000 but do not currently require its throughput," the company said in a press release (Illumina was unavailable to comment for this article). [7]
This "single flow cell version" of the HiSeq 2000 "will deliver in excess of 100 Gb of data per run using paired 100 base pair reads, easily enabling the sequencing of a complete human genome in a single run," according to the release.
Finally, at the American Society of Human Genetics annual meeting this week, Life Technologies announced two new additions to its line of SOLiD sequencers. On the high end, the company is launching the SOLiD 5500xl. Built in collaboration with Hitachi, the 5500xl will generate twice the data of SOLiD 4 (200 Gbp per run) at half the cost ($6,000 per run) and in half the time (5-6 days vs 10-12), Therrien says.
"You can sequence an entire human genome at 30x coverage at a price of $3,000, which was unheard of just a year ago," says Therrien.
At the same time, the company also announced a personal option. Priced at $299,000 (vs $595,000 for the 5500xl), the SOLiD 5500 base system is essentially a single flow-cell version of the 5500xl.
Life Technologies is also gearing up to commercialize an entirely new sequencing technology this November. Based on its recent acquisition of Ion Torrent Systems for some $725 million, the Personal Gene Machine (PGM) will provide up to 10 Megabases worth of 100-base reads in just two hours for about $500, according to Therrien. (An upgrade to 100 Mbp per run is planned for release "early next year," he adds.)
That, Church notes, is 1,600 times more expensive per-base than the SOLiD 4. But the company, says Therrien, is positioning it as mid-way between a Sanger capillary electrophoresis-based instrument and the SOLiD, for applications such as bacterial and viral genomics and targeted amplicon sequencing. "What that gets you is a radical reduction in turnaround time for really what is a very large amount of sequence data," he says.
The Ion Torrent consumable "is a computer chip that's been modified so we can flow biologics into it," Therrien says. Amplified DNA templates on silicon beads are flowed into that flow cell, where they sit in tiny wells. At the bottom of those wells is basically "the smallest pH meter in the world." As nucleotides are flowed into the reaction chamber one by one and added to the growing DNA chain by DNA polymerase, they release protons, causing a pH drop that registers as a change in voltage.
It's a design that requires no optics, no fluorescence, and no imaging; "We call it 'post-light sequencing,’" Therrien says. It is also, for that reason, considerably less expensive than other next-gen platforms, costing just $52,000 for the hardware.
"It's a clever system," says MacArthur. "I think it's really quite elegant, but how well it actually works in the field will be the big test."
(In related news, Roche/454 announced Monday a partnership with DNA Electronics "for the development of a low-cost, high-throughput DNA sequencing system," according to a press release. Details are sketchy, but the described system bears certain similarities to Ion Torrent's technology. According to the release, the system will use "inexpensive, highly scalable electrochemical detection"—as opposed to optical detection—and "leverages 454 Life Sciences' long read sequencing chemistry with DNA Electronics' unique knowledge of semiconductor design and expertise in pH-mediated detection of nucleotide insertions, to produce a long read, high density sequencing platform.")
Of course, not all sequencing will be done on these platforms. Sanger sequencing remains a powerful force in the industry. "If you just want to check one fact in 24 hours, as biologists often do, it's $2 for a 700 bp run," Church says. "And that's a no-brainer."
At the same time, sequencing firms are also pursuing the "next-next" generation of instruments.
One such technology is Project Starlight, which Life Technologies discussed at the Advances in Genome Biology and Technology meeting in February. Project Starlight is a sequencing approach based on single-molecule fluorescence resonance energy transfer (FRET) between a FRET donor-bearing DNA polymerase and FRET acceptor bearing nucleotide triphosphates.
Unlike most commercial sequencing systems, which amplify a template prior to sequencing it, Starlight sequences individual molecules directly. (Helicos BioScience's HeliScope commercial sequencer is also a single-molecule technology, as is Pacific Biosciences' in-development SMRT technology.) According to Therrien, the company is "currently targeting a commercial release in mid-2011," with 1-kb read lengths—about twice as long as any current next-gen technology—at launch.
Such long reads are sorely needed, MacArthur says. Short reads (such as the products of the SOLiD and Illumina chemistries) make it difficult to assemble a genome without a reference scaffold (that is, de novo), especially if the genome contains repetitive sequences. A few long reads could go a long way towards overcoming that problem, he says.
"Once you start pushing beyond about a kilobase or so, that starts giving you some real power," MacArthur says. "If you can sprinkle even a few of these kind of longer reads into a sequencing project that's already generating lots and lots of short reads, then that potentially can make a big difference to how well you can put the genome together."
Another next-next-gen technology in development is nanopore-based sequencing, in which DNA is "read" as it passes through nanometer-scale holes. Oxford Nanopore has been pursuing that approach for several years now. More recently, Roche/454, in partnership with IBM, entered the fray.
According to a press release [8] announcing the latter collaboration, IBM's in-development approach is based on the company's “DNA Transistor” technology. "The novel technology, developed by IBM Research, offers true single molecule sequencing by decoding molecules of DNA as they are threaded through a nanometer-sized pore in a silicon chip," the release explains.
"It's still an early-stage research project at this point, but Roche is very interested in the future of sequencing," says Montgomery. "I think there's still a lot yet on the horizon to come."
For the next-generation sequencing market overall, that surely is the case.
["Sequencing" became industrialized. Now is the turn towards industrialization of the "Genome Computing" - HolGenTech does this by leveraging defense computing for genomics. - AJP.]
Experts Discuss Consumer Views of DTC Genetic Testing at ASHG, Washington
GenomeWeb
November 08, 2010
By Andrea Anderson
WASHINGTON (GenomeWeb News) – Researchers are sifting through survey and other data that may eventually help discern consumers' attitudes about direct-to-consumer genetic tests and inform future oversight of such tests, experts explained at the American Society of Human Genetics meeting here today.
The ASHG's existing recommendations for DTC genetic testing call for transparency and evaluation of DTC tests by health and/or consumer organizations such as the US Food and Drug Administration or the Federal Trade Commission, along with education about the tests for consumers and healthcare providers and studies of consumers' views on and use of such tests, ASHG President-elect Lynn Jorde, chair of human genetics at the University of Utah, told reporters during a press briefing.
Jorde moderated a panel of experts who weighed in on DTC tests and outlined findings from their own studies of consumer attitudes toward DTC tests.
For instance, David Kaufman, director of research and statistics at Johns Hopkins University's Genetics and Public Policy Center, described results from a survey of more than 1,000 individuals that was designed to get at individuals' motivation for using DTC genetic testing services offered by 23andMe, Decode Genetics, and Navigenics — and their experiences and level of satisfaction with these tests.
Kaufman and his colleagues surveyed 1,048 DTC genetic test customers who had been tested by 23andMe, Decode Genetics, or Navigenics and received their test results between June 2009 and the following March.
In general, they found that the earliest DTC genetic test adopters tended to be well educated and had significantly higher incomes than the average American. Most participants said they were motivated by factors such as general curiosity and an interest in assessing their ancestry and/or disease risk, Kaufman noted, though many also cited an interest in improving their health as a motivator for testing.
Although some 70 percent of consumers surveyed supported oversight by a consumer agency that would hold testing companies to their scientific claims, Kaufman and his team found that roughly two-thirds of those surveyed believe DTC tests should be available to the public without government oversight.
The researchers also gained insights into everything from participants' understanding of test results to their overall satisfaction with the tests.
Nevertheless, Kaufman cautioned, though the survey provided information on how DTC test results are interpreted by customers, it did not address the scientific rigor of the tests themselves or the clinical validity or utility of the test results.
Meanwhile, Barbara Bernhardt, co-director of the University of Pennsylvania's Center for the Integration of Genetic Health Care Technologies, and her co-workers surveyed 60 individuals who had been tested for risk variants associated with eight conditions through the Coriell Personalized Medicine Collaborative.
Again, the team found that participants tended to be well educated and motivated by factors such as curiosity and interest in improving their health.
While most of the individuals surveyed understood their general results — often interpreting them within the context of their own family history — they did not necessarily have a deep understanding of the relative risk information provided to them, Bernhardt explained. Though some were told they were at a heightened risk certain diseases, the researchers found that none of the participants reported being very concerned about this increased risk.
Even so, Bernhardt said, nearly a third had at least somewhat changed their behavior or lifestyle based on their test results. And half had discussed their test results with their doctor.
Finally, Andrew Faucett, director of genomics and public health at Emory University School of Medicine, outlined some questions that consumers and clinicians should keep in mind when selecting, evaluating, and interpreting DTC genetic tests and results.
For example, Faucett said, consumers need to consider what they hope to learn by taking the test. For clinicians, meanwhile, issues such as treatment implications of genetic findings are important, Faucett noted, as are an understanding the population(s) in which a particular test has been evaluated.
Faucett also drew a distinction between DTC genetic tests that are regularly used in the clinic and those that aren't, explaining that while testing labs in general are doing a good job with test analyses, much less is known about the clinical validity and utility of some tests.
[During the week of ASHG in Washington, the American people have spoken - and the legislative lame-duck remainder of the mid-term and ensuing division of Congressional Legislature make it an impossibility that the 1976 mandate of the FDA will be updated anytime soon. There is enough consumerism around, most people think, to give advice to consumers to make their free choices. The more choice, the better. - AJP.]
Complete Genomics plans Tuesday initial public offering of stock
Associated Press
11/05/10 5:11 PM EDT
INDIANAPOLIS — Complete Genomics Inc. expects to raise about $69.3 million in an initial public offering of 6 million shares Tuesday to help fund improvements and expansion of its DNA sequencing strategy.
The Mountain View, Calif., company said proceeds could rise to about $80.2 million if underwriters exercise an overallotment option for 900,000 shares. The company expects the stock price to range between $12 and $14 per share.
It plans to use the money to expand the sequencing and computing capacity at its Mountain View and Santa Clara locations, to fund more development of its technology and for sales and marketing and working capital, according to a registration statement filed with the Securities and Exchange Commission.
The company said it has developed and commercialized an innovative DNA sequencing platform and aims to "become the preferred solution for complete human genome sequencing and analysis," according to the statement. Complete Genomics believes its products will offer academic and biopharmaceutical researchers complete analysis without requiring them to invest in equipment like in-house sequencing instruments and high-performance computing resources.
"By removing these constraints and broadly enabling researchers to conduct large-scale complete human genome studies, we believe that our solution has the potential to revolutionize medical research and expand understanding of the basis, treatment and prevention of complex diseases," the company said.
Complete Genomics started operations in March 2006 and spent its first three years focused on research and developing its sequencing technology. It has piled up a $108.1 million deficit during its development stage.
The company plans to list its stock on the NASDAQ Global Market under the ticker symbol "GNOM."
[In the five-way horse race for Genome Sequences with 3 public companies (Roche, Life Sciences and Illumina) and 2 fresh IPO-s (Pacific Biosciences and now two weeks later Complete Genomics) the crucial question, surprising as it is, will not be "Sequencing" - but "Analytics" - based on entirely new paradigms, since the Decade since the finish of "Human Genome Project" "was all wrong" (confessed publicly the President's Science Advisor, Eric Lander, November 2nd, 2010). In the horse race "leveraging" is expected to play a major role. For instance, while PacBio leverages Big IT (IntelVC), Life Technologies leverages Big IT (Hitachi) in their new high-end SOLiD 5500 sequencer (announced at ASHG for next Spring). At the same time, for their "low end" ($49k) Ion Torrent sequencer Jonathan Rothberg, now part of Life Technologies, leverages the entire $1 Trillion semiconductor industry for the sequencer chip. As for "Analytics", HolGenTech leverages "Defense Computing" (with their High Performance Computing Hybrid Platforms), combined with Pellionisz' Fractal Approach to Recursive Genome Function - AJP.]
Today, we know all that was completely wrong - Lander's Keynote at ASHG, Washington
Lander’s Lessons Ten Years after the Human Genome Project
Bio-IT World
November 3, 2010
Kevin Davies
By Kevin Davies
November 3, 2010 | WASHINGTON, DC – If anyone was capable of distilling the lessons learned in the ten years since the first draft of the Human Genome Project (HGP) in 2000, it was Broad Institute director Eric Lander.[Also, Science Advisor to the President - AJP]
Opening the annual American Society of Human Genetics (ASHG) convention in Washington, D.C., Tuesday evening, Lander tried to meet the organizers’ challenge to sum up “what’s come of it?”
From a technical perspective, the HGP produced “a scaffold onto which information can be put,” said Lander, including cancer genes, epigenomics, evolutionary selection, disease association, 3-D folding maps, and much more. As for intellectual advances, Lander made a series of startling comparisons of geneticists’ knowledge around the time of the HGP in 2000 and today.
In 2000, for example, only four eukaryotic genomes (yeast fly, worm, and Arabidopsis) had been sequenced, as well as a few dozen bacteria. Today, those numbers stand at 250 eukaryotic genomes, 4,000 bacteria and viruses, metagenomic projects and many hundreds of human genomes. By the end of this year, Lander expects the Broad Institute to have generated 100,000 Gigabases (Gb) of sequence.
“The cost [of sequencing] has fallen 100,000 fold in past decade, vastly faster than Moore’s Law,” said Lander. But the question remained: “How will this get used in clinical medicine? The costs need to drop to $1,000 and then $100,” said Lander.
“I no longer think these things are crazy.”
In 2000, Lander and his HGP consortium colleagues estimated there were about 35,000 protein-coding genes, with a few classical non-coding RNAs. Repetitive DNA elements called transposons were just parasites and junk.
“Today, we know all that was completely wrong,” said Lander.
Studying patterns of evolutionary conservation in some 40 sequenced vertebrates, the human gene count is “21,000, give or take 1,000,” said Lander. “There are many fewer genes than we thought. Much more information is non-coding than we thought . . . 75% of the information that evolution cares about is non-coding information.”
The study of 29 mammalian genomes shows some 3 million conserved non-coding elements in the genome, covering about 4.7% of the genome. Some of these have regulatory functions, he said. Another exciting area was the generation of genome-wide 3-D maps, which has revealed that the genome resides in ‘open’ and ‘closed’ compartments. There was much more work to be done in the coming decade, but with new next-generation sequencing tools, “it will happen.”
Mendel Redux
In 2000, the genes for about 1,300 Mendelian genetic disorders had been identified. Today, that number is about 2,900, leaving “another 1,800 Mendelian disorders to go,” said Lander. He noted the success of some whole-genome sequencing projects in identifying rare Mendelian disease genes, although the approach was not trivial. “We all have about 150 rare coding variants,” he said, in other words glitches in about 1% of a person’s genes. Those have to be carefully vetted and filtered, but in the case of recessive genes or a small number of patients, the whole-genome approach was very powerful.
Lander also broached the progress in genome-wide association studies (GWAS) for common inherited disease, where Lander says “an entire village came together” to develop the array tools, haplotype maps, and a catalogue of more than 20 million single nucleotide polymorphisms (SNPs). “The vast majority of common variation is known,” said Lander. The numbers are 1,100 loci associated with 165 common diseases/traits. For diseases such as inflammatory bowel disease and Crohn’s disease, 70-100 loci have been mapped, a pattern that Lander showed exists for lipid disorders, type 2 diabetes, height, and many other conditions.
Lander addressed the oft-publicized disappointment and criticisms expressed by some prominent geneticists, including ASHG president-elect Mary-Claire King, in the “missing heritability” and the net value extracted from GWAS papers. One widely voiced concern is that the effect size of individual GWAS “hits” is small. “I think that’s nonsense,” said Lander. “Effect size has nothing to do with biological or medical utility.” He pointed out that a drug acting on a target can have much bigger effect that the effect of the common allele.
Some geneticists believe that the “missing heritability” so far untapped by GWAS must be explained by rare DNA variants. Not so fast, said Lander. For one thing, the proportion of heritability explained in disorders such as Crohn’s and diabetes is increasing. Population genetics theory suggests that for many common diseases, rare variants will explain less than common variants.
Lander also said that geneticists must take into account epistasis, the effects of modifier genes. Such effects cannot be found statistically in GWAS, he argued. Rather than moving from mapped loci to explaining heritability to understanding biology, Lander said we must understand biology first, and then explain the models of heritability.
Cancer Conclusion
In 2000, Lander said some 80 cancer-related genes were known. The tally is now 240 genes, with genome sequencing studies revealing mutational hotspots in colon, lung, and skin cancers with therapeutic implications. As an example, Lander said his Broad Institute colleague Todd Golub, studying multilple myeloma tumors, had discovered mutations in four well known cancer genes, but more excitingly, implicated a handful of new biological pathways, including protein synthesis and an extrinsic coagulation pathway.
The battle against cancer needed more sequencing. “We’ll need the equivalent of the 1 million genomes project. We better start thinking how to engage patients,” said Lander, suggesting social networking and other ideas had to be leveraged to get patients involved.
Lander concluded by presenting what he called “the path to the promise.” If the HGP provided the raw tools, scientists were still translating basic genome discoveries into more medically directed research. That’s how far we’ve progressed in ten years. But that still leaves the daunting tasks of clinical interventions, clinical testing, regulatory approval and widespread adoption.
[This public confession of the Science Advisor to the President that the last ten years of Genomics (derailed by Crick in 1956) was on a completely wrong track even for the last decade since HGP, may still be stunning for a part of the huge crowd, though such a message was heralded in peer-reviewed paper and widely disseminated YouTube in 2008. Still, there were even companies at the ASHG convention that attempt to sell analytics with validity only for "genes" - when nobody can even know the number of genes (protein-coding exons amounting to far less than 1% of human DNA), since at this point there isn't even a scientifically valid commonly accepted definition of what a "gene" is. Thus, ASHG conference in Washington, 2010 November became the "Eye of the Cyclone". Along with his notion to turn the "upside down" approach to "right side up" ("we must understand biology first, and then explain the models of hereditability"), Dr. Lender published in Science a year ago that the structure of DNA was fractal. Meanwhile, Pellionisz gained a decade with his "Fractal Approach to Recursive Genome Function using Fractal Iteration", on record since 2002, reaching back to his seminal 1989 publication. Those who only see the "tip of the iceberg" of Pellionisz' Fractal Approach in publications are into huge suprises now that all (formerly fierce) opposition has been wiped out from the top. Look for more coming here and also on Pellionisz FaceBook and pellionisz_at_junkdna.com - AJP.]
1,000 Genomes Project Maps 16 Million DNA Variants: Why?
CBS News
October 28, 2010 11:47 AM
Remember the race to map the human genome? Science crossed that finish line in 2003. But it turns out that was just the beginning.
Scientists are now focusing on the small differences in our genomes, hoping to find fresh clues to the origins of many diseases.
The effort is called the 1000 Genomes Project and already it claims to have found 16 million previously unknown variations in human DNA, about 95 percent of all variations in our species. That's just from the 800 people who are part of the pilot study. The group hopes to catalog DNA from 2,500 people before they are done. [How do we know that after 16 M only 5% will be found? If 95% is already found from 800 people, why does the "1,000 Genomes" project plan for 2,500 Genomes? - AJP]
Why does it matter?
"What really excites me about this project is the focus on identifying variants in the protein-coding genes that have functional consequences," said Dr. Richard Gibbs, director of the Human Genome Sequencing Center at the Baylor College of Medicine, in a statement. "These will be extremely useful for studies of disease and evolution."
That's geek speak for finding cures to diseases that have genetic components, such as Alzheimer's, mental illness, cystic fibrosis and Huntington's Disease. The work may eventually also help certain cancers that are genetically linked such as breast and prostate.
The research is being done at government, academic and corporate facilities around the world including the National Institutes of Health in America and is made possible by new high speed techniques for mapping genetic material.
The pilot results were published in Nature and are being shared freely to speed research.
[The Nature (hard core science) paper concludes "The 1000 Genomes Project represents a step towards a complete description of human DNA plymorphism". With all due regard to the very distinguished line-up of the Consortium IMHO a "complete description of human DNA polymorphism (if completion of such a "brute force aproach" is possible at all) may not be the best and most scientific approach. At the conception of the 1,000 Genomes Project e.g. Francis Collins and George Church critized the project' planning in a Nature article in 2008. Will there be reconsideration of the design in view of the initial results? (Looks like 1,000 is already changed to 2,500). The crucial question seems to be that no two genomes may be identical - yet chances are that those differences that are responsible for "human diversity" might hugely outnumber those structural variants that are the root causes of hereditary diseases. Some algorithmic approaches can tell the "parametric" and "syntactic" variants apart. This might a burning question at the 60th meeting of the Amercian Society of Human Genetics this week in Washington, D.C. - AJP.]
Parody of Public’s Attitude Toward DTC Genetics
October 27, 2010
Genomeweb
Daily Scan’s inbox has been teeming with announcements for various talks and workshops to be held at the upcoming American Society of Human Genetics annual meeting in Washington, D.C., though none have read quite like Blaine Bettinger’s at the Genetic Genealogist blog. Bettinger has posted a parody of a press release for a talk in which “a group of the nation’s top geneticists and ethicists” showed data that analyzed the public’s awareness of direct-to-consumer genetic testing services and their regulation. “The researchers, funded in large part by federal grants, interviewed over 10 people randomly chosen at the entrance to the nearest grocery store and asked them whether they were familiar with one or more of the five DTC genetic testing companies included in the study,” whether they had – or had ever considered – taking a DTC gene test, and whether they felt the public should be allowed access to their genetic information, the blogger writes in his satire. “Finally, to gauge the participant’s understanding of the basic principles of genetics, each was asked to briefly describe in 100 words or less the role of the replication fork in DNA replication,” Bettinger adds
---new
I'm getting a 404 error when
Submitted by sarahemily on Wed, 10/27/2010 - 13:24.
I'm getting a 404 error when I click the link to the parody and can't find it anywhere else on the site. I would love to read it - can you supply a new link?
• reply
---new
Here is the text: New Study
Submitted by Jeff.Rosner on Wed, 10/27/2010 - 14:01.
Here is the text:
New Study Analyzing DTC Genetic Testing Released Today
October 26th, 2010 in Genealogy |
I received this news release yesterday via email. I’m probably breaking the embargo by publishing this, but I think it’s too important not to get it out there. Please be sure to read ALL the way to the bottom.
Nation’s Top Geneticists and Ethicists Release New Study of Consumer Perceptions of Direct-to-Consumer Genetic Testing and Announce New DTC Testing Guidelines
Leading up to the American Society of Human Genetics 60th Annual Meeting, which will be held November 2-6, 2010 in Washington, D.C., a group of the nation’s top geneticists and ethicists today released the results of a new study analyzing the public’s awareness and use of so-called “direct-to-consumer” genetic testing by companies such as 23andMe, deCODEme, and Pathway Genomics.
The researchers, funded in large part by federal grants, interviewed over 10 people randomly chosen at the entrance to the nearest grocery store and asked them whether they were familiar with one or more of the five DTC genetic testing companies included in the study. The participants were then asked if they had participated in DTC genetic testing, and whether they might be interested in doing so in the future. The participants were also asked whether they believed that members of the general public should be allowed to access their own genetic data without the assistance of a physician or genetic counselor. Finally, to gauge the participant’s understanding of the basic principles of genetics, each was asked to briefly describe in 100 words or less the role of the replication fork in DNA replication.
The results of the study indicate that 100% of the study participants were completely unfamiliar with these DTC testing companies, and none had any experience with DTC testing. The study also showed that while none were currently interested in performing testing on their own DNA, 90% believed that Americans should be allowed to access their genetic data without the assistance of a physician or genetic counselor. The results also showed that none of the participants in the study were able to competently explain even the basics of the DNA replication fork.
“Our study shows for the first time that the vast majority of the American public is completely unaware of even the most popular DTC testing companies,” reported Dr. David N. Anderssen, lead geneticist in the study. “Additionally, the inability of every single one of the study participants to explain one of the most basic aspects of genetics was, quite frankly, very disappointing, again suggesting that people are not equipped to handle genetic information.”
“While 90% of the participants stated that they should be able to access their own genetic information without a physician or geneticist’s assistance, we completely disagree with their opinions and took this opportunity to explain to each one of them just how dangerous their genetic information can be. We also explained to them that their erroneous opinions and beliefs don’t really matter anyway, since it is the role of certified geneticists and ethicists to determine for America exactly who should access genetic information.”
In light of the findings, Dr. Anderssen noted the group’s newly-issued guidelines on DTC testing: “We’re recommending that all DTC genetic testing companies immediately close up shop, or, alternatively, hire a staff of 25 or more genetic counselors. We also recommend that Congress immediately make it illegal to even look at an ‘A,’ ‘T,’ ‘G,’ or ‘C’ without a physician or genetic counselor within at least 5 feet; the danger of privacy violations and/or the misunderstanding DTC genetic testing results is just too great to ignore.”
“Indeed, the majority of the group [of ten people - AJP] believes that there is no role for genetics in health care, disease risk, genealogy, or anthropology, among other endeavors; the old-fashioned – but always informative – family history is really the only way to go here,” reported the geneticist. “However, since most of us need these jobs, we decided to approve the use of genetics for disease assessment in the new guidelines.”
Dr. Anderssen noted that the group is continuing to study this emerging area of genetics, and plans to expand the study to 25 more participants from the nearby gas station in the near future.
____________________________________
(This post is a parody only, meant as criticism of some of the glaring deficiencies in recent studies analyzing DTC claims. A reasonable person would not interpret this post to contain factual claims, and is within my First Amendment rights (isn’t it sad that I have to write this?)).
• reply
new
Hi Sarah, the post appears to
Submitted by tvence on Wed, 10/27/2010 - 14:51.
Hi Sarah, the post appears to have been removed from the site. We'll provide an updated link when -- and if -- it becomes available.
Jeff: Thanks for pasting the full text in the meantime.
[This is really a parody of an infamous, and explicitely "non-scientific" study of the science of DTC by some genomically illiterate lame-duck politician, having already announced his retirement - AJP.]
UPDATE: Pacific Biosciences IPO Rises While First Wind Cuts Price
Wall Street Journal
By Lynn Cowan, Tess Stynes And Christopher Zinsli
Of DOW JONES NEWSWIRES
OCTOBER 27, 2010, 4:30 P.M. ET
A genetics technology company on Wednesday became the first U.S. life sciences initial public offering this year to both price well and trade higher, while a wind farm operator cut its asking price ahead of its offering.
Pacific Biosciences of California Inc. (PACB), which has created an instrument platform to help scientists observe nucleotides being added to DNA in real time, offered up a strong data point for the initial public offering market, while First Wind Holdings Inc. showed that green energy companies continue to be a hard sell in America.
Pacific Biosciences closed at $16.44 a share on the Nasdaq, up 2.8% from its initial public offering price of $16. It sold 12.5 million shares at the midpoint of its $15 to $17 price range.
...
Even though it hasn't commercially released its DNA sequencing platform or generated any revenues from it, Pacific Biosciences has more going on than the typical early-stage life science IPO hopeful. It plans to begin commercial delivery in the beginning of next year, has an order backlog of $15 million, and could see recurring revenue from the consumable components that need to be re-ordered.
The platform is a new generation of DNA sequencing technology, one that allows longer nuceotide chains to be read in less time than existing systems, according to the company's prospectus.
"It's a disruptive technology," said Steve Brozak, a biotech and medical-devices analyst who is president of WBB Securities LLC. "It could be a building block for future innovation."
Not every deal this week seems destined for easy pricing and trading. Wind-farm developer First Wind Holdings Inc. on Wednesday cut the estimated price range of its 12-million share IPO to $18 and $20 each, $6 below the $24 to $26 that it had originally planned. The company, which is supposed to begin trading on the Nasdaq Thursday under the symbol WIND, operates 504 megawatts of wind farms in the Northeastern and Western U.S.
...
[While market conditions are still shaky, "Genome Informatics" is "IN", while "Green Tech" may be fading OUT, according to investors - AJP.]
Tue Oct 26, 2010 7:22pm EDT
* Prices at $16 vs $15-$17 range-underwriter
* Sells 12.5 mln shares, raises about $200 mln-underwriter
* To trade on Nasdaq under symbol "PACB"
NEW YORK, Oct 26 (Reuters) - Pacific Biosciences of California Inc (PACB.O), which designs machines to speed up DNA sequencing in labs, priced shares in its initial public offering at the midpoint of the expected range on Tuesday, according to an underwriter.
The company sold 12.5 million shares for $16 each, raising about $200 million. It had planned to sell shares for $15 to $17 each.
Menlo Park, California-based Pacific Biosciences sells equipment that can be used for clinical, agricultural and drug research, food safety, biofuels and biosecurity applications.
The company has never been profitable and all of its revenue to date has come from government grants. Pacific Biosciences posted a net loss of $63.04 million on revenue of $1.17 million in the six months ended June 30.
Pacific Biosciences said it had a backlog of orders worth $15 million as of June 30. The U.S. Department of Energy Joint Genome Institute and Monsanto Co (MON.N) are among those that have ordered Pacific Biosciences equipment.
Underwriters were led by JPMorgan, Morgan Stanley, Deutsche Bank Securities and Piper Jaffray. The shares are expected to begin trading on the Nasdaq on Wednesday under the symbol "PACB."
[The Industrialization of PostModern Genomics has begun - AJP.]
Complete Genomics Sets IPO Price Range
XConomy
Luke Timmerman 10/26/10
Complete Genomics, the low-cost gene sequencing company in Mountain View, CA, has set a goal of pricing 6 million shares in its initial public offering at a price of $12 to $14, according to a filing today with the Securities and Exchange Commission. If the company can find demand from investors at the top of its range, and its underwriters buy an extra 900,000 shares, then the deal could bring in as much as $96.6 million. The company is scheduled to set the actual IPO price the week of Nov. 8, according to Renaissance Capital. Complete Genomics’ existing roster of investors includes OrbiMed Advisors, Essex Woodland Health Ventures, San Diego-based Enterprise Partners Venture Capital, Kirkland, WA-based OVP Venture Partners, and Palo Alto, CA-based Prospect Venture Partners. The company plans to begin trading under the symbol (NASDAQ: GNOM).
[As heralded since YouTube in 2008 (based on peer reviewed science paper of The Principle of Recursive Genome Function) the key is Analytics, not only for the public investors, but for the sustainability of the Industrialization of Genome revolution of Genome Revolution. The paradigm-shift has been available since 2002 - a year before the START of ENCODE - AJP.]
IPO Preview: Pacific Biosciences [this week; a huge surge for Fractal Analytics - AJP]
Bloomberg BusinessWeek
October 22, 2010
Pacific Biosciences expects to offer up to $212.5 million in common stock in an IPO next week.
The company said it expects to price 12.5 million shares between $15 and $17 apiece. It is also offering underwriters 1,875,000 shares to cover overallotments. If all options are exercised, the company could have gross proceeds of just under $244.4 million.
The company, based in Menlo Park, Calif., makes genetic analysis technology focused on helping researchers investigating biochemical processes. Its initial focus is in the DNA sequencing market, with customers including research institutions and commercial companies focusing on agricultural research, drug discovery and development, biosecurity and bio-fuels.
The company said there are a significant number of competitors in the market, including Illumina Inc., Life Technologies Corp. and Roche Applied Science. Many of its competitors already have established manufacturing and marketing capabilities.
"We expect the competition to intensify within this market as there are also several companies in the process of developing new technologies, products and services," Pacific Biosciences said in its prospectus.
Those emerging competitors could include Complete Genomics Inc., Oxford Nanopore Technologies Ltd. and Ion Torrent Systems Inc., which is in the process of buying Life Technologies [for $735 M in cash and stocks - AJP].
Pacific Biosciences said it had $135 million in revenue in 2009. The fledgling company has yet to turn a profit.
The company said it expects net proceeds of about $210.4 million, after costs, depending on how the stock prices within the range and overallotment options. It said it would invest between $60 million and $70 million in current and future applications of its SMRT technologies [The $60-70 M looks most like the investment in Analytics - AJP], use $40 million to $60 million to fund anticipated future working capital needs, and use $20 million to $30 million to fund planned capital expenses. It would use between $40 million and $60 million for other general corporate purposes.
Underwriters in the offering include J.P. Morgan, Morgan Stanley, Deutsche Bank Securities, and Piper Jaffray.
The company plans to trade under the "PACB" symbol on the Nasdaq Global Market.
--
Among "Investment Risks" disclosed by PacBio on their S1 filing:
Adoption of our products by customers may depend on the availability of informatics tools, some of which may be developed by third parties.
Our commercial success may depend in part upon the development of software and informatics tools by third parties for use with our products. We cannot guarantee that third parties will develop tools that will be useful with our products or be viewed as useful by our customers or potential customers. A lack of additional available complementary informatics tools may impede the adoption of our products and may adversely impact our business.
[As the PacBio IPO will happen in the coming week, there will be a huge surge for the Fractal Approach to Analytics:
a) If the IPO will be successful, there will be monies to make good on what PacBio claims to be; a DNA "analysis" company - "at the first step" with the focus on sequencing". Smart Public Investors are keenly aware that analytics is missing - and would be a huge (Silicon Genetics type, 2000) mistake investing in Analytics based on totally wrong ancient axioms of Genome Informatics (Central Dogma and Junk DNA), at a time when the superseding replacement paradigm "The Principle of Recursive Genome Function" is available. The "proof of concept" that the genome (structure) is fractal was provided now over a year ago by Science Advisor to President Eric Lander et al.
b) If the PacBio IPO will be less than successful (e.g. should the $15-17 stock list price drop upon IPO to lower levels), it will have to be the bitter lesson to all Sequencing Companies that smart enough public investors are as aware of the "Dreaded DNA Data Deluge" - as I presented it in 2008 (Google YouTube, which by the way rises relentlessly, now over 9,000 views from all Continents) - and would be reluctant to invest in Genomics where a potential glut of sequences that can not be adequately analyzed may threaten sustainability. Many investors are aware of the present DTC "unsustainability" - though that is caused by the US government, rather than supply-chain-management initial difficulties in the Industrialization of Genomics by the Private Sector, banking on public investment. Sequencing companies would have to do something rather quickly to embrace Fractal Analytics. AJP.]
Benoît B Mandelbrot: the man who made geometry an art [censored -reinstated - AJP]
Guardian.co.uk
October 19, 2010
[Excerpts - see full article linked to title - AJP]
Few recent thinkers have woven such a beautiful braid of art and science as Benoît B Mandelbrot, who has died aged 85 in Cambridge, Massachusetts. (The B apparently doesn't stand for anything. He just felt like adding it.) Mandelbrot was a provocative mathematician, a subversive geometer. He left a beautiful legacy in visual art, for Mandelbrot was the man who named and explained fractals – those complex, apparently chaotic yet geometrically ordered shapes that delight the eye and fascinate the mind. They are icons of modern understanding of the universe's complexity.
The Mandelbrot set, one of the most famous fractal designs, is named after him. With its fizzing fringe of crystal-like microforms blossoming out of a conjunction of black circles, this fractal pattern looks crazy but is the outcome of geometrical calculations.
.... Mandelbrot was not the first, but with his startling fractals concept he created a visual manifesto for a non-Euclidean universe.
Fractals – and I'd be delighted if mathematicians can give a better explanation below– are shapes that are irregular but repeat themselves at every scale: they contain themselves in themselves. Mandelbrot used the example of a cauliflower which, like a fern, is a fractal found in nature; if you look at the smallest sections of these vegetable forms, you see them mirroring the whole....
Artists have been fascinated by geometry for as long as mathematicians have. The studies of Euclid are reflected in the regularities of classical and Renaissance architecture, from the Pantheon in Rome to the duomo in Florence. But artists and architects were also thinking centuries ago about non-regular, curving geometries. You could argue that fractals give us the mathematics of the Baroque – they were anticipated by Borromini and Bach. I have a facsimile, given away by an Italian newspaper, of part of Leonardo da Vinci's Atlantic Codex, which contains page after page of his attempts to analyse the geometry of twisted, curving shapes.
Mandelbrot was a modern Leonardo, a man who showed the beauty in nature...
---
Comments [partial list - AJP]
singo111
19 October 2010 2:22PM
As others have already pointed out...
The beauty is not the 'pretty pattern' fractal. The beauty is in the fact that a dry and simple mathematical function can give rise to a fractal output of such complexity. That's what blows my mind anyway.
And as for:
Mandelbrot was not the first, but with his startling fractals concept he created a visual manifesto for a non-Euclidean universe - there isn't anything necessarily Non-Euclidean (as a mathematician would understand the term) about it at all.
Why isn't a science correspondent writing this?
RIP Benoit - you deserved better than this article.
---
Pellionisz
19 October 2010 6:36PM
This comment has been removed by a moderator. Replies may also be deleted.
Pellionisz
21 October 2010 4:33PM
Comment reinstated (see contents below).
--- [ end of excerpts from the Guardian - AJP] ---
[The comment by Pellionisz that was censored out - AJP]
19 October 2010 6:36PM
Mandelbrot defined himself by his book "Fractal Geometry of Nature" (B. B. Mandelbrot. W. H. Freeman, 1982) as his creative job title was "mathematical scientist". Though a highly artistic soul, Benoit left "the art part" to colleagues; e.g. The Beauty of Fractals (H. O. Peitgen and P. H. Richter, Springer 1986). His oeuvre is profoundly seminal, with a significance way over visual arts only. Suffice to mention his well-known fractal understanding of stock market prices.
Further, to illustrate how "seminal" his geometrical understanding of Nature became, I quote FractoGene (Pellionisz, 2002), The Principle of Recursive Genome Function where the fractal DNA governs growth via fractal recursive iteration of fractal organelles (e.g. brain cells, cardiac coronaries), organs (e.g. lung, kidney) and organisms (e.g. cauliflower romanesca). For those preferring over peer-reviewed science papers, a Google Tech Talk YouTube is available.
One might argue that (fractal) universe, lunar surfaces, mountain ranges etc. had been around for time measured by mega-millions of years, Mandelbrot did not invent fractality of lifeless and living Nature (just like Newton did not invent gravity) - but discovered their mathematical principles. While he realized (2004) that the genome is fractal, testing his uncanny ability to tell with high precision the fractal dimension of roughness I asked in public at Stanford "what do you think the fractal dimension of the genome might be?" his honest answer was "I do not know" (implying that understanding the fractal nature of the genome structure and function will dominate genomics of the 21st Century). Just as John von Neumann could have arrived at the intrinsic mathematics of brain function (that he stated in his posthumus book "The Computer and the Brain" as certainly different from logical calculus), had beloved Benoit lived a decade more, his expressed interest in the most seminal biology (genomics) could have contributed with breakthroughs beyond his realization of the challenge.
Pellionisz_at_JunkDNA.com
---
[Mandelbrot and Pellionisz at Stanford, 2004]
[Labeling Mandelbrot as an artist by an admittedly non-mathematician is like celebrating Picasso as a mathematician; a flat journalistic mistake that censorship will not hide (comment reinstated in 48 hours) - AJP, FaceBook and Pellionisz_at_JunkDNA.com]
'Fractalist' Benoît Mandelbrot dies
New Scientist
Valerie Jamieson, chief features editor
21:08 18 October 2010
[View his last major presentation at TED, 2010 - AJP]
Benoît Mandelbrot, who died a month shy of his 86th birthday on Thursday, wanted to be remembered as the founding father of fractal geometry – the branch of mathematics that perceives the hidden order in nature.
He became a household name, thanks to the psychedelic swirls and spikes of the most famous fractal equation, Mandelbrot set. (Recently, a 3D version of the set was discovered, called theMandelbulb.)
Fractals are everywhere, from cauliflowers to our blood vessels. No matter how you divide a fractal nor how closely or distantly you zoom in, its shape stays the same. They have helped model the weather, measure online traffic, compress computer files, analyse seismic tremors and the distribution of galaxies. And they became an essential tool in the 1980s for studying the hidden order in the seemingly disordered world of chaotic systems.
By his own admission, Mandelbrot spent his career trawling the litter cans of science for fractal patterns and found them in the most unusual places. His job title at Yale University in New Haven, Conneticut, was deliberately chosen with this diversity in mind. "I'm a mathematical scientist," he told me. "It's a very ambiguous term."
I met Mandelbrot in 2004 when he was promoting The (Mis)behaviour of Markets, the book he'd written with financial journalist Richard L Hudson. After a long detour through other fields of science, Mandelbrot turned the tools of fractal geometry to financial data and had a stark warning for economists. "We have been mismeasuring risk," he said. "Brokers who ask why we should even think about 'wild events' where one bad event in the stockmarket can wipe out everything are misleading themselves."
Mandelbrot's hope was that by thinking about markets as scientific systems, we might eventually build a stronger financial industry and a better system of regulation. He also challenged Alan Greenspan, chairman of the Federal Reserve, and other financiers to set aside $20 million for fundamental research into market dynamics.
He called himself a maverick because he spent his life doing only what he felt was right and never belonging to a particular scientific community. And he enjoyed the reputation of someone who was happy to disturb ideas.
Back in 2004, Mandelbrot showed few signs of slowing down. He was writing his memoir – The Fractalist: Memoir of a Geometer – which was set to be published in 2012.
He worked every day except Sunday and enjoyed going to conferences (watch his talk at the 2010 TED conference ...). This year, he even co-authored two papers in the Annals of Applied Probability. "What motivates me is the feeling that these ideas may be lost if I don't push them any further," he told me of his desire to continue his research.
Mandelbrot may be gone. But the beauty of his fractals live on. You only have to look around you to be reminded of his insights. In his own words: "Clouds are not spheres, mountains are not cones, coastlines are not circles, bark is not smooth, nor does lightning travel in a straight line." [and the Genome is not contiguous snippets of Gene-sequences in the vast see of Junk DNA - but FractoGene, AJP]
Benoît Mandelbrot, Novel Mathematician, Dies at 85
By JASCHA HOFFMAN
New York Times
Published: October 16, 2010
[All this visual complexity is compressed into the Z=Z^2+C equation - AJP]
Benoît B. Mandelbrot, a maverick mathematician who developed the field of fractal geometry and applied it to physics, biology, finance and many other fields, died on Thursday [Oct. 14, 2010 – five weeks before turning 86 - AJP] in Cambridge, Mass. He was 85.
The cause was pancreatic cancer, his wife, Aliette, said. He had lived in Cambridge.
Dr. Mandelbrot coined the term “fractal” to refer to a new class of mathematical shapes whose uneven contours could mimic the irregularities found in nature.
“Applied mathematics had been concentrating for a century on phenomena which were smooth, but many things were not like that: the more you blew them up with a microscope the more complexity you found,” said David Mumford, a professor of mathematics at Brown University. “He was one of the primary people who realized these were legitimate objects of study.”
In a seminal book, “The Fractal Geometry of Nature,” published in 1982, Dr. Mandelbrot defended mathematical objects that he said others had dismissed as “monstrous” and “pathological.” Using fractal geometry, he argued, the complex outlines of clouds and coastlines, once considered unmeasurable, could now “be approached in rigorous and vigorous quantitative fashion.”
For most of his career, Dr. Mandelbrot had a reputation as an outsider to the mathematical establishment [Received tenure from Yale University in 1999, at the age of 75 - AJP]. From his perch as a researcher for I.B.M. in New York, where he worked for decades before accepting a position at Yale University, he noticed patterns that other researchers may have overlooked in their own data, then often swooped in to collaborate.
“He knew everybody, with interests going off in every possible direction,” Professor Mumford said. “Every time he gave a talk, it was about something different.”
Dr. Mandelbrot traced his work on fractals to a question he first encountered as a young researcher: how long is the coast of Britain? The answer, he was surprised to discover, depends on how closely one looks [How many "Genes" the human DNA has? It depends how closely one looks - AJP]. On a map an island may appear smooth, but zooming in will reveal jagged edges that add up to a longer coast. Zooming in further will reveal even more coastline.
“Here is a question, a staple of grade-school geometry that, if you think about it, is impossible,” Dr. Mandelbrot told The New York Times earlier this year in an interview. “The length of the coastline, in a sense, is infinite.”
In the 1950s, Dr. Mandelbrot proposed a simple but radical way to quantify the crookedness of such an object by assigning it a “fractal dimension,” an insight that has proved useful well beyond the field of cartography.
Over nearly seven decades, working with dozens of scientists, Dr. Mandelbrot contributed to the fields of geology, medicine, cosmology and engineering. He used the geometry of fractals to explain how galaxies cluster, how wheat prices change over time and how mammalian brains fold as they grow, among other phenomena.
His influence has also been felt within the field of geometry, where he was one of the first to use computer graphics to study mathematical objects like the Mandelbrot set, which was named in his honor.
“I decided to go into fields where mathematicians would never go because the problems were badly stated,” Dr. Mandelbrot said. “I have played a strange role that none of my students dare to take.”
Benoît B. Mandelbrot (he added the middle initial himself, though it does not stand for a middle name) was born on Nov. 20, 1924, to a Lithuanian Jewish family in Warsaw. In 1936 his family fled the Nazis, first to Paris and then to the south of France, where he tended horses and fixed tools.
After the war he enrolled in the École Polytechnique in Paris, where his sharp eye compensated for a lack of conventional education. His career soon spanned the Atlantic. He earned a master’s degree in aeronautics at the California Institute of Technology, returned to Paris for his doctorate in mathematics in 1952, then went on to the Institute for Advanced Study in Princeton, N.J., for a postdoctoral degree under the mathematician John von Neumann.
After several years spent largely at the Centre National de la Recherche Scientifique in Paris, Dr. Mandelbrot was hired by I.B.M. in 1958 to work at the Thomas J. Watson Research Center in Yorktown Heights, N.Y. Although he worked frequently with academic researchers and served as a visiting professor at Harvard and the Massachusetts Institute of Technology, it was not until 1987 that he began to teach at Yale, where he earned tenure in 1999.
Dr. Mandelbrot received more than 15 honorary doctorates and served on the board of many scientific journals, as well as the Mandelbrot Foundation for Fractals. Instead of rigorously proving his insights in each field, he said he preferred to “stimulate the field by making bold and crazy conjectures” — and then move on before his claims had been verified. This habit earned him some skepticism in mathematical circles.
“He doesn’t spend months or years proving what he has observed,” said Heinz-Otto Peitgen, a professor of mathematics and biomedical sciences at the University of Bremen. And for that, he said, Dr. Mandelbrot “has received quite a bit of criticism.”
“But if we talk about impact inside mathematics, and applications in the sciences,” Professor Peitgen said, “he is one of the most important figures of the last 50 years.”
Besides his wife, Dr. Mandelbrot is survived by two sons, Laurent, of Paris, and Didier, of Newton, Mass., and three grandchildren.
When asked to look back on his career, Dr. Mandelbrot compared his own trajectory to the rough outlines of clouds and coastlines that drew him into the study of fractals in the 1950s.
“If you take the beginning and the end, I have had a conventional career,” he said, referring to his prestigious appointments in Paris and at Yale. “But it was not a straight line between the beginning and the end. It was a very crooked line.”
[How mammalian brains fold in a fractal way, was followed up (after the initial ideas of Grosberg 20 years ago) almost exactly a year ago by Dr. Lender et al., for the fractal folding of the DNA; "Mr. President, the Genome is Fractal!". The primary concept of FractoGene (2002 by Pellionisz, reaches back to the Fractal Geometry of Cerebellar Purkinje Cells, 1989, based on a musing of Mandelbrot in his "Fractal Geometry of Nature" classic book - AJP]
Genomeweb
October 14, 2010
BioMed Central's Beyond the Genome conference in Boston this week — which was held in conjunction with Genome Biology's 10th anniversary — showcased the work of several researchers whose ideas go beyond just sequencing.
The University of Maryland's Steven Salzberg kicked off the conference with a keynote speech about the work he and others are doing to try and accurately estimate exactly how many genes a person has. In 1964, F. Vogel wrote a letter to Nature estimating that humans have 6.7 million genes. He was way off, Salzberg said, but it hasn't gotten any easier over the years to make the estimate more accurate. In the mid-1990s, three different papers estimated the count to be 50,000 to 100,000, 64,000, and 80,000. Even after the draft genome was published, the estimates widely varied. The public consortium estimated the count to be between 30,000 and 40,000, while Celera and its private partners estimated 26,588, with 12,000 other additional "likely" genes. So far, the most accurate estimate is 22,333 human genes, Salzberg said, but there is still much of the human genome that not much is known about, and RNA-seq is still revealing a lot of new genes that may have previously been overlooked. In the end, Salzberg said, it's not as important to know how many genes there are as to know what they are and what they do.
George Church emphasized how important it is to continue to read the genome. About 2,000 genes are highly predictive and medically actionable, he said, and as the price of sequencing continues to drop, researchers will be able to find more genes they can work with to the benefit of human health. Church also stressed the importance of open-access data, and said there is a need for an open database that researchers can use to analyze each others' data.
Elaine Mardis spoke about her work with cancer genomics, and said that, in researching the way tumors work, validating tumor variants is important especially for dissemination of the information to the wider scientific community for further analysis. The speed of data generation is both challenging and enabling, she added.
The University of Washington's Jay Shendure talked about his lab's work with exome sequencing in autism studies. At least some percentage of autism is caused by coding mutations, and exome sequencing is useful in studies of the disorder because the technique can be used to focus in on a single gene instead of an entire region of the genome, Shendure said. He described a trio-based exome study done in his lab, where 60 exomes — from 20 autistic children and both of their parents — were sequenced, and then analyzed to identify Mendelian errors. The researchers found 16 de novo SNPs validated by Sanger from the 20 autism trios, and found two genes — GRIN2B and FOXP1 — which they think could be causative in autism.
The University of Colorado's Rob Knight and BGI's Jun Wang discussed their respective labs' work with microbes. Knight talked about the research he has done with obese and lean mice, and trying to elucidate the relationship between an organism's weight and its gut microbes. Wang talked about some of the studies BGI has done with diabetic patients, and said one study of Chinese type II diabetes patients discovered more than 500,000 novel bacterial genes and found 1,306 bacterial genes associated with diabetic patients, though whether the genes were the cause or the effect of diabetes is not yet known.
Comments:
Submitted by S. Pelech - Kinexus on Thu, 10/14/2010 - 14:08.
It is intriguing that despite the complete sequencing of the human genome for many years now, it is still unresolved exactly how many human genes actually exist. Mass spectrometry studies have revealed several protein sequences that were not originally described in gene databases. In my own experience, with the assignment of over 90,000 phospho-sites in predicted human proteins for PhosphoNET (www.phosphonet.ca), I have noticed several hundred proteins that were originally documented in UniProt (www.uniprot.org) that have had the entries deleted without any replacements. Since these phosphoproteins were identified from cell lysates by mass spectrometry, obviously the encoding genes actually exist. Since Uniprot has just over 21,000 distinct human proteins currently listed, perhaps 4 to 5 percent of human proteins are still not tracked in the best repository that we have information about our proteins. How well the 22,333 figure for the total number of human genes accounts for these anomalies identified by mass spectrometry analysis of proteins is also unclear.
reply
Submitted by andras on Thu, 10/14/2010 - 19:47.
A better title would be: "FractoGene Recurses to the Genome". Both "Going beyond the Genome" and "Counting the Exact Number of Genes in Human DNA" are exercises in futility - unless going beyond the genome is tracked through its full recourse from intrinsic and extrinsic proteins back to the DNA>RNA>PROTEINS> and on, as well as contiguous sequences, formerly defined as "genes" yield to facts of their "alternative splicing" (one gene acting as many different genes when spliced in various different ways), as well as to the newly found facts that given contiguous sequences constitutes functional units with sequences very far downstream or upstream, totally outside of the boundaries of the (now obsolete) "gene" definition. The Principle of Recursive Genome Function peer reviewed science paper and Google Tech TalkYouTube of our Genome Revolution defines not just one trip to go "beyond Genome" (akin to the Russians in the early days of Space Age, blasting a dog into space and leave it there to perish), but more like "Sending a Man on the Moon - and taking him safely back to Earth" (and do it repeatedly, again and again). It is within the context of recursive algorithms, such as fractal iterative recursion, that seemingly scattered elements of genes, FractoGene governs growth of fractal organelles (such as brain cells), organs (such as the lung) and organisms (such as the cauliflower romanesca) as guided by the demonstrably fractal genome, recursing through epigenomic channels back to the DNA. Pellionisz_at_JunkDNA.com (reprint requests to holgentech_at_gmail.com).
Cold Spring Harbor Lab Says Benefits of ARRA Funding Will Outlast Stimulus Program
October 08, 2010
By Alex Philippidis
NEW YORK (GenomeWeb News) - Cold Spring Harbor Laboratory says it expects to benefit from the stimulus funding it received through from the American Recovery and Reinvestment Act of 2009, well past the program's end next year.
"For CSHL, the injection of ARRA funds has been very positive and will have an impact past the two years of the funding in that it is generating new data that will lead to new projects and new opportunities to pursue grant funding from public and private sources," a laboratory spokeswoman, Dagnia Zeidlickis, told GenomeWeb Daily News this week.
CSHL secured $23.4 million of stimulus funding in 19 awards. The largest award, at more than $4.7 million over two years from the National Cancer Institute, funded the creation of a Molecular Target Discovery and Development Center, with the goal of determining which of the hundreds of genes that are altered in cancer actually play a role in causing the disease.
The center - part of a network of five such centers established nationwide - is evaluating the torrent of data from recent human cancer genome projects, as well as validating candidate genes in mouse models. The center hopes that information can help in discovering and validating new cancer drugs targeting molecular changes in the disease seen in patients. Scott Powers, an associate professor, is the project's principal investigator.
Next largest, at just over $2.5 million over two years from the National Heart, Lung, and Blood Institute, is a study of the epigenetic dynamics of developing germ cells and early mouse embryos. Gregory Hannon, professor and Howard Hughes Medical Institute investigator, served as PI for the study, part of which compares epigenetic profiles in early embryos derived from normal mice to those of early embryos in hormone-treated, super-ovulated mice, since hormone treatments are believed to alter the epigenetic state of some genes.
The research is designed to help understand hormone-assisted attempts at conception undergone by up to 1 million women each year.
CSHL also used almost $1.3 million of ARRA funds over two years from the National Institute of Mental Health to hire a developmental neurobiologist with expertise in neural circuit development and plasticity. Zeidlickis said the laboratory won't disclose the faculty member's identity until the appointment is finalized.
That person will join CSHL's current 50-member faculty, which includes professors, associate professors, assistant professors, and fellows.
A less costly project, using $497,423 in ARRA funds from the National Science Foundation, consisted of renovations of the greenhouse at CSHL's Uplands Farm Research Field Station, which supports research into Arabidopsis and crop plants as well as the plant genetics teaching programs of CSHL's Dolan DNA Learning Center.
In an abstract of its grant application, CSHL concluded: "These facilities are inadequate to meet the demands of current genome driven plant biology research. The infrastructural improvements will provide appropriate growing conditions for a greater diversity of plant species and will increase the energy efficiency of the facilities."
"With new research project funding, upgraded infrastructure, and a new faculty position, CSHL will be able to continue to pursue the kind of innovative research that we are best known for," Zeidlickis said. "This research should lead to new opportunities for funding from Federal programs that are increasingly recognizing innovation and transformative research - like the TRO1 and Challenge Grants that we have been successful in securing - in addition to ARRA."
ARRA is the $814 billion measure signed into law by President Obama last year with the intent of stimulating the nation's economy. The law required NIH to spend, or commit to spend, all $10 billion available to the agency under the legislation by Sept. 30, 2010 - though ARRA money doesn't have to be in the hands of grant winners, generally, until Sept. 29, 2011.
New Research Buildings Open at Cold Spring Harbor Laboratory
Research at the $100 million Hillside Laboratories will address “grand challenges” facing science and society
Cold Spring Harbor, NY – Cold Spring Harbor Laboratory (CSHL) cut the ribbon on six new research buildings, collectively called the Hillside Laboratories, at a dedication ceremony on June 12. The $100 million complex represents the largest expansion in CSHL’s 119-year history and increases active research space by 40%. When fully occupied the buildings will house approximately 200 new research-related personnel, which will mark a 20% increase in employment at CSHL.
At the dedication ceremony, CSHL President Bruce Stillman said, “This expansion will allow Cold Spring Harbor Laboratory to do more of what it has always done best: perform pioneering research at the leading edge of biological science, particularly in the areas of cancer and neuroscience, but also in the emerging field of quantitative biology.” Dr. Stillman spoke before a distinguished audience of CSHL staff and supporters from the research, business, philanthropic and government communities, including Nobel laureate Philip Sharp.
In his dedication remarks, Dr. Sharp, perhaps best known as the co-discoverer of gene splicing, suggested how research to be performed in the Hillside buildings “will help humanity surmount some of the great challenges of our time.” He recalled that the first public announcement calling for a national effort to sequence the human genome was made at the dedication of a new research building at CSHL in 1985. He then issued his own implicit challenge to the scientists who will occupy the gleaming new Hillside buildings. Sharp envisioned a future in which data collected in millions of patient electronic medical records will be merged with genome scans of the same individuals. This would serve as the basis for profound insights into cancer and mental illness, two of the foci of work in the new Hillside Laboratories. Such an effort, he said, might also help usher in an era of personalized medicine.
CSHL’s President Stillman in his remarks thanked gathered guests for their support of the expansion project, saying, “Such a significant addition to our research space was made possible by the generous contributions of private donors, philanthropic foundations and the New York State ‘Gen*NY*sis’ initiative, which provided a grant of $20 million. They had the foresight to understand the significance of this expansion to the Laboratory’s long-term mission to advance our ability to diagnose and develop more effective ways of treating cancers, neurological diseases and other major causes of human suffering.”
A capital campaign raised over $200 million to support the construction of the new research buildings, recruitment of new investigators, equipment for new research projects and endowment for research and graduate education. The project was also supported by a bond issued with the Nassau County Industrial Development Authority.
The Hillside Laboratories
Called the “Hillside Laboratories,” the six new research buildings total 100,000 square feet and include:
The Donald Everett Axinn Laboratory, for research on the neurobiological roots of mental illness;
the Nancy and Frederick DeMatteis Laboratory, for research on the genetic basis of human diseases, including autism, cancer, and schizophrenia;
the David H. Koch Laboratory, home to a newly established Center for Quantitative Biology, where an interdisciplinary team of top mathematicians, physicists, and computer scientists will develop mathematical approaches to interpret and understand complex biological data sets;
the William L. and Marjorie A. Matheson Laboratory, for research on the tumor microenvironment and metastasis;
the Leslie and Jean Quick Laboratory, for research on new therapeutic strategies for treating cancer; and
the Wendt Family Laboratory, for research on neurodevelopment and the wiring of complex circuits in the brain.
Designed to foster the progress of scientific discovery
Speaking at the opening ceremony, CSHL Board Chairman Eduardo Mestre said, “An important goal for the design of the Hillside Laboratories was to encourage collaboration among scientists and foster the progress of scientific discovery, while preserving the historic appeal of CSHL’s picturesque campus. Looking at this beautiful complex I believe we have succeeded brilliantly.”
The six new buildings are actually outcroppings of a single interconnected structure with an infrastructure that is integrated beneath ground level. Each of the laboratories rises from the ground in a different place, giving the appearance of six discrete buildings. Nestled into the hillside, the buildings are connected at various elevations and share a common utility grid that will make them 30% more energy-efficient than prevailing standards for laboratory facilities.
In order to preserve the idyllic nature and existing environment of the 115-acre campus, the Hillside Laboratories have been designed to complement rather than overpower CSHL’s smaller, historic buildings along the western shoreline of Cold Spring Harbor. In addition to the six research buildings, the new complex features the Laurie and Leo Guthart Discovery Tower, the tallest structure in the group, which serves to vent heat from the six buildings while providing an aesthetic “cap” for the ensemble.
Other unique features of the complex include a water element that threads like a mountain stream through its center; a 200-foot-long bridge; an award-winning storm water management system; meticulous landscape design; and spectacular new vantage points for viewing Cold Spring Harbor.
The Hillside Laboratories were designed by Centerbrook Architects and Planners LLP, which was selected for this project based on its history of award-winning designs of earlier CSHL buildings and its commitment to creating unique and uplifting designs that fulfill program and budget objectives while enriching the natural surroundings.
In the construction phase of the project CSHL emphasized the hiring of local Long Island craftsmen and -women. It is estimated that the project provided as many as 250 construction industry jobs on Long Island during the course of its nine-year planning and construction phases.
Hillside Laboratory Facts
The construction project is the largest ever undertaken by CSHL and will increase research space by 40%.
The expansion at CSHL will create 200 new high-paying, high-tech jobs on Long Island.
More than 250 project contractors, consultants, and craftsmen who worked on the project were from local Long Island companies.
Construction costs on the new 100,000-square-foot building complex totaled $100 million.
The laboratory buildings are designed to be 30% more energy-efficient than standards set for laboratories by ASHRAE (American Society of Heating, Refrigerating, and Air-Conditioning Engineers).
An innovative environmental design for storm-water management uses newly-created wetlands, rain gardens, and bio-swales to filter storm water runoff from the hillside before it makes its way into the harbor. This system has a capacity of 254,000 gallons, and was awarded the 2007 Project of the Year by the Nassau County Society of Professional Engineers.
Nearly 700 trees have been planted to reforest the approximately 11 acres of forest that were cleared to make way for construction.
All organic material from the site was retained for reuse. Trees were chipped and mulched for site restoration, and topsoil was scraped away from the building site, retained onsite, and reapplied during site restoration.
Approximately 200,000 cubic yards of excess earth was removed from the site. A sand mining operation was set up on-site, screening out rock, gravel, fine sand and other high-quality construction material before being removed from site. Sale of the construction material reduced the cost of excavation from $4 million to $2 million.
William H. Grover, FAIA, and James C. Childress, FAIA, are Centerbrook Architects’ Partners-in-Charge of the Hillside complex. Todd E. Andrews, AIA, is the Project Manager. Visit www.centerbrook.com for more information.
Art Brings is the Vice President, Chief Facilities Officer in charge of the project.
Cold Spring Harbor Laboratory is a private, nonprofit research and education institution dedicated to exploring molecular biology and genetics in order to advance the understanding and ability to diagnose and treat cancers, neurological diseases and other causes of human suffering.
What to Do with All That Data?
October 07, 2010
By Alex Philippidis
Recent technological advances in genomics have caused something both "terrifying" and "exciting," Mike the Mad Biologist says - "a massive amount of data." Mike says that genome sequencing is already fast and cheap, but it will become faster and cheaper; the problem is evolving from how to sequence genomes to get informative data to how best to use the information we already have. "We are entering an era where the time and money costs won't be focused on raw sequence generation, but on the informatics needed to build high-quality genomes with those data," Mike says. While it's great to be able to contemplate a $100 genome, the costs of storing and using the data could be upwards of $2,500. Researchers must find ways to store the data and analyze everything that's already been sequenced. "You have eleventy gajillion genomes. Now what? Many of the analytical methods use 'N-squared' algorithms: that is, a 10-fold increase in data requires a 100-fold increase in computation. And that's optimistic," he says.
Submitted by Stephen.Craig.J... on Thu, 10/07/2010 - 16:47.
I am thinking there needs to a an independent organization, comprised of experts, which continually analyzes and interprets the new information and translates it into a usable form for clinicians and other end users.
• reply
Submitted by S. Pelech - Kinexus on Thu, 10/07/2010 - 18:41.
Unless there is a well funded parallel program of biomedical research that can make sense of the genomics data from a proteomics perspective, the genome sequencing efforts will yield primarily correlative data that will offer limited risk assessment at best. In view of the complexities of cellular regulation and metabolism, it will not provide conclusive data about the actual cause and progression of an individual's disease and how best to treat it. Unfortunately, much of the currently efforts to understand the roles and regulation of proteins are undertaken in simple animal models that are attractive primarily because of their ease of genetic manipulation. However, such studies have little relevance to the human condition. Without a better understanding of how mutations in genes affect protein function and protein interactions in a human context, genome-based diagnostics will in most situations probably not be much more beneficial than phrenology.
Phrenology is an ancient practice that was extremely popular about 200 years ago. It was based on the idea that formation of an individual's skull and bumps on their head could reveal information about their conduct and intellectual capacities. Phrenological thinking was influential in 19th-century psychiatry and modern neuroscience. While this practice is pretty much completely ridiculed now, it is amazing how many people still use astrology, I Ching, Tarot cards, biorhythms and other questionable practices to guide their lives, including medical decisions. I fear that an even wider portion of the general population will put their faith into whole genome-based analyses, especially with the strong encouragement of companies that could realize huge profits from offering such services. The most likely consequences, apart from yet another way for the sick to be parted from their money, is a lot more anxiety in the healthy population as well.
While I am sure that many of my colleagues may view my comparison of gene sequencing with obvious pseudo-sciences as inappropriate, the pace at which such genomics services are becoming offered to the general population warrants such consideration. We know much too little about the consequences of some 15 million mutations and other polymorphisms in the human genome to make sensible predictions about health risks. For only a few dozen human genes, primarily affected in cancer, do we have sufficient data to make reasonable pronouncements about the cause of a disease and the means to do something effective about it in the way of targeted therapy.
While it is easy to become exuberant about the power and potential of genomic analyses, the limitations of this type of technology alone to improve human health will soon become painfully obvious. Ultimately, economics will be the main driver of whether it is truly worthwhile to pursue whole genomic sequencing on mass. This will not be dictated simply by the cost of whole genome sequencing, but as pointed out by others, the costs of storing and analyzing the data, and whether significant improvement outcomes in health care delivery actually materialize.
I am much less optimistic about the prospects of this. When I grew up in the 1960's, there was excitement about human colonies on the moon and manned missions to Mars before the turn of the 20th century. Nuclear power, including fusion, was going to solve our energy problems by this time. I believe in 30 years when we look back at current plans to sequence tens to hundreds of thousands of human genomes, we will be amazed at the naivety of proponents for this undertaking.
Pacific Biosciences Targeting $15-$17 Share Price for IPO
October 05, 2010
By a GenomeWeb staff reporter
NEW YORK (GenomeWeb News) – Pacific Biosciences will make 12.5 million shares available at a price between $15 and $17 per share for its initial public offering, the company said in an amended preliminary prospectus filed with the US Securities Exchanged Commission today.
Today's amended S-1 document follows a similar filing last week with the SEC in which the company disclosed it had done a 1-for-2 reverse stock split in September and increased the amount it expects to raise from its IPO to $230 million from the $200 million originally targeted when the company announced its proposed IPO in August.
The Menlo Park, Calif.-based single-molecule sequencing firm also said in today's filing that it is making about 1.9 million shares available to its underwriters to purchase to cover over-allotments
At the midpoint of its share price range, $16, PacBio's net proceeds from the offering would be about $182.5 million or $210.4 million if the underwriters fully exercise their option to purchase additional shares, the company said.
The underwriters on the offering are JP Morgan, Morgan Stanley, Deutsche Bank Securities, and Piper Jaffray.
PacBio previously had stated that through the first half of 2010, it had recorded almost $1.2 million in revenues, all from government grants, and a net loss of $63 million, or $99.58 per share. In H1 2009, it had no revenues, and a net loss of $35.1 million, $75.39 per share.
The company had cash and cash equivalents of $90.1 million as of June 30, it said.
[There is hardly any question that with the stock market easing back to 11,000 three possible successful IPO-s could clinch the return of a definite recovery. It is widely rumored that the social Internet media sector FaceBook is poised for one. The other two could be guestimated for Affordable DNA Sequencing by Complete Genomics (Mountain View) and almost simultaneously filed by Pacific Biosciences (Menlo Park). Thus the remaining crucial question is "when", "which one first", and "which will be more successful than the other"? Answers to these heretofore open questions might harbor some very good news for Silicon Valley - and for the US Economy, as heralded in YouTube "Personal Genome Computing" panel by Churchill Club in early 2009. (FaceBook) / Pellionisz_at_JunkDNA.com]
Bio-IT World, September 28, 2010
SPECIAL REPORT
The term next-generation sequencing (NGS) has been around for so long it has become almost meaningless. We use “NGS” to describe platforms that are so well established they are almost institutions, and future (3rd-, 4th-, or whatever) generations promising to do for terrestrial triage what Mr Spock’s Tricorder did for intergalactic health care. But as the costs of consumables keep falling, turning the data-generation aspect of NGS increasingly into a commodity, the all-important problems of data analysis, storage, and medical interpretation loom ever larger.
“There is a growing gap between the generation of massively parallel sequencing output and the ability to process and analyze the resulting data,” says Canadian cancer research John McPherson, feeling the pain of NGS neophytes left to negotiate “a bewildering maze of base calling, alignment, assembly, and analysis tools with often incomplete documentation and no idea how to compare and validate their outputs. Bridging this gap is essential, or the coveted $1,000 genome will come with a $20,000 analysis price tag.”
“The cost of DNA sequencing might not matter in a few years,” says the Broad Institute’s Chad Nusbaum. “People are saying they’ll be able to sequence the human genome for $100 or less. That’s lovely, but it still could cost you $2,500 to store the data, so the cost of storage ultimately becomes the limiting factor, not the cost of sequencing. We can quibble about the dollars and cents, but you can’t argue about the trends at all.”
But these issues look relatively trivial compared to the challenge of mining a personal genome sequence for medically actionable benefit. Stanford’s chair of bioengineering, Russ Altman, points out that not only is the cost of sequencing “essentially free,” but the computational cost of dealing with the data is also trivial. “I mean, we might need a big computer, but big computers exist, they can be amortized, and it’s not a big deal. But the interpretation of the data will be keeping us busy for the next 50 years.”
Or as Bruce Korf, the president of the American College of Medical Genetics, puts it: “We are close to having a $1,000 genome sequence, but this may be accompanied by a $1,000,000 interpretation.”
Arbimagical Goal
The “$1,000 genome” is, in the view of Infinity Pharmaceuticals’ Keith Robison, an “arbimagical goal”—an arbitrary target that has nevertheless obtained a magical notoriety through repetition. The catchphrase was first coined in 2001, although by whom isn’t entirely clear. The University of Wisconsin’s David Schwartz insists he proposed the term during a National Human Genome Research Institute (NHGRI) retreat in 2001. During a breakout session, he said that NHGRI needed a new technology to complete a human genome sequence in a day. Asked to price that, Schwartz paused: “I thought for a moment and responded, ‘$1,000.’” However, NHGRI officials say they had already coined the term.
The $1,000 genome caught on a year later, when Craig Venter and Gerry Rubin hosted a major symposium in Boston (see, “Wanted: The $1000 Genome,” Bio•IT World, Nov 2002). Venter invited George Church and five other hopefuls to present new sequencing technologies, none more riveting than U.S. Genomics founder Eugene Chan, who described an ingenious technology to unfurl DNA molecules that would soon sequence a human genome in an hour. (The company abandoned its sequencing program a year later.)
Another of those hopefuls was 454 Life Sciences, which in 2007 made Jim Watson the first personal genome using NGS, at a cost of about $1 million. Since then, the cost of sequencing has plummeted to less than $10,000 in 2010. Much of that has been fueled by the competition between Illumina and Applied Biosystems (ABI). When Illumina said its HiSeq 2000 could sequence a human genome for $10,000, ABI countered with a $6,000 genome dropping to $3,000 at 99.99% accuracy.
Earlier this year, Complete Genomics reported its first full human genomes in Science. One of those belonged to George Church, whose genome was sequenced for about $1,500. CEO Cliff Reid told us earlier this year that Complete Genomics now routinely sequenced human genomes at 30x coverage for less than $1,000 in reagent costs.
The ever-quotable Clive Brown, formerly a central figure at Solexa and now VP development and informatics for Oxford Nanopore, a 3rd-generation sequencing company says: “I like to think of the Gen 2 systems as giant fighting dinosaurs, ‘[gigabases] per run—grr—arggh’ etc., a volcano of data spewing behind them in a Jurassic landscape—Sequanosaurus Rex. Meanwhile, in the undergrowth, the Gen 3 ‘mammals’ are quietly getting on with evolving and adapting to the imminent climate change... smaller, faster, more agile, and more intelligent.”
Nearly all the 2nd-generation platforms have placed bets on 3rd-gen technologies. Illumina has partnered with Oxford Nanopore; Life Technologies has countered by acquiring Ion Torrent Systems; and Roche is teaming up with IBM. PacBio has talked about a “15-minute” genome by 2014, Halcyon Molecular promises a “$100 genome,” while a Harvard start-up called GnuBio has placed a bet on a mere $30 genome.
David Dooling of The Genome Center at Washington University, points out the widely debated cost of the Human Genome Project included everything—the instruments, personnel, overhead, consumables, and IT. But the $1,000 genome—or in 2010 numbers, the $10,000 genome—only refers to flow cells and reagents. Clearly, the true cost of a genome sequence is much higher (see, “The Grand Illusion”). In fact, Dooling estimates the true cost of a “$10,000 genome” as closer to $30,000, by the time one has considered instrument depreciation and sample prep, personnel and IT, informatics and validation, management and overheads.
“If you are just costing reagents, most of the vendors could claim a $1,000 genome right now,” says Brown. “A more interesting question is: ‘$1,000 genome—so what?’ It’s an odd goal because the closer you get to it the less relevant it becomes.”
Special Interests
This special issue of Bio•IT World contains a series of stories and essays that provide some useful perspectives on the march to the $1,000 genome, which some regard as a medical imperative and others a grand illusion.
We get an up-close look at sequencing operations at the Broad Institute, which has been the U.S. flagship genome center for a decade (see page 30). We also meet the leaders of BGI Americas, which aims to provide sequencing capacity and analysis for labs big and small, while managing editor Allison Proffitt gleefully visits BGI’s prized new sequencing center under construction in Hong Kong (page 42).
We look at the genesis of Solexa, the British company that provided the raw technology for Illumina, the best-selling NGS platform to date (page 52). We meet Kevin Ulmer, a man who has spent more than three decades trying to develop the killer app for the $1,000 genome (page 64). And we meet NABsys, a 3rd-generation technology taking aim at the myriad clinical applications of NGS (page 61).
Given that the costs of data analysis and storage will increasingly dominate the NGS equation, Alissa Poh reviews some of the latest software solutions on offer (page 58), while Allison Proffitt appraises some of the latest data storage technologies (page 38).
Finally, we meet some of the organizations—from bioinformaticians and medical geneticists to pathologists and software engineers—who are developing new ideas and resources for clinical genomic interpretation (page 48). And we profile Hugh Rienhoff, physician and founder of My Daughter’s DNA.org, and follow his inspirational quest to solve his daughter’s mystery condition (page 34).
Also in this report are invited commentaries from genomics experts at two big pharma—Amgen’s Sasha Kamb and Novartis’ Keith Johnson and colleagues—discussing the potential applications and adoption hurdles to NGS in pharma. We also have our regular columns, including BioTeam’s Michele Clamp and our colleague Eric Glazer on social media and a preview of an exciting online community called NGS Leaders.
We hope you enjoy this special report on the road to the $1,000 genome as much as we have enjoyed reporting and preparing it.
—Kevin Davies, Mark Gabrenya and Allison Proffitt
[George Church has been talking about "the zero dollar DNA sequence" for years by now. The "Great Inflection" from emphasis on Sequencing to emphasis on Analytics of Data was looming for at least since YouTube "Is IT ready for the Dreaded DNA Data Deluge?" 2 years ago. We almost agree with Stanford' Russ Altman that The Principle of Recursive Genome Function will us preoccupied for 50 years (I think 500 is more likely...). (FaceBook) / Pellionisz_at_JunkDNA.com]
Revolution [was] Postponed [for too long, over Half a Century - AJP]
Scientific American
By Stephen S. Hall
October 18, 2010
[The full 8-page article is to be purchased for $5.99 at Scientific American]
The Human Genome Project has failed so far to produce the medical miracles that scientists promised. Biologists are now divided over what, if anything, went wrong—and what needs to happen next
In Brief:
In the year 2000 leaders of the Human Genome Project announced completion of the first rough draft of the human genome. They predicted that follow-up research could pave the way to personalized medicine within as few as 10 years.
So far the work has yielded few medical applications, although the insights have revolutionized biology research.
Some leading geneticists argue that a key strategy for seeking medical insights into complex common diseases— known as the “common variant” hypothesis— is fundamentally flawed. Others say the strategy is valid, but more time is needed to achieve the expected payoffs.
Next-generation methods for studying the genome should soon help resolve the controversy and advance research into the genetic roots of major diseases.
---
Comment #3
Yehuda Elyada
06:26 PM 10/1/10
The complexity of the concept of a gene requires analytic tools far more sophisticated than the naive assumption that there exist a one-to-one correspondence rule between gene variation and phenotype traits. The DNA is not a "blueprint" in the simple metaphor borrowed from engineering drawings. A more fitting metaphor is a musical score, defining the timing and amplitudes of notes series expression by various organs in the assemblage. Each musical instrument produces different waveforms due to its unique note expression mechanism, but music is made when all are controlled by a single set of notes and playing instructions and synchronized by the conductor. The waveforms combine to generate something "higher" than just more complex waveforms - just as life is more than metabolism.) The musical metaphor suggests how to analyze the relationship between DNA and phenotype.
The "holistic" approach to appreciation of music is based on subjective, human-centric psychological response to various harmonics, note sequences, tempo, emphasis, etc. No "reductionist" approach can grasp the essence of what make music a different experience from noise. However, we do not possess a similar mental capacity to analyze DNA expression, so we have to develop a reductionist approach to enable analysis based on mathematical rigor. This is where physics can point the way.
From the point of view of physics, music is a time varying complex waveform that can be broken into its simple components. By doing so, you move from the complex world of waveforms into the linear, "orthogonal" world of frequencies. You pay for this transformation by losing the ability to grasp the wholeness of the musical experience - a heavenly symphony become just flickering bars on your spectrum analyzer - but the technique of Fourier transform is essencial when you want the zero-in on an acoustic trait of a music instrument.
It is somewhat naive to assume that the same transformation that proved so useful and central in physics (not just in acoustics. Where would quantum mechanics be without the Fourier transformation) will unlock the genotype-phenotype conundrum. But it's a promising first step in injecting some more sophisticated mathematics into genomics. To gain insight into the rules of the game you have to start with an overarching paradigm: our aim is to uncover a many-to-many transformation (perhaps expressed as a matrix) between two complementary world-views, the genome (the vector of DNA bases) and the phenotype (the vector whose components are traits).
[The Scientific American article (though for copyright reasons we can not reveal contents in full) blows open for the public the core problem of "PostModern Genomics"- that scientists are split in the middle, some would not even admit that anything was deadly wrong with the "frighteningly unsophisticated" (and mathematically void) "theory" of (holo)genome function, oversimplified to "genes" (1.3% and Junk DNA 998.7%) with both intronic and intergenic, as well as epigenomic pathways not only neglected, but their research discouraged by withdrawing ongoing government grants. As commenter #3 points out, the article is fundamentally flawed, since if one does not consider overarching new paradigms (such as e.g. the "Recursive Genome Function - AJP) and sophisticated mathematics (such as e.g. the "Fractal approach - AJP), in princple one can not tell if anything based on obsolete axioms is valid or not.
For a preview of this message, see YouTube "Is IT ready for the Dreaded DNA Data Deluge?" 2 years ago . Also, see The Principle of Recursive Genome Function (FaceBook) / Pellionisz_at_JunkDNA.com]
The $1,000,000 Genome Interpretation
Bio-IT World
By Kevin Davies
October 1, 2010
Groups of clinicians, academics, and some savvy software companies are crafting the tools and ecosystem to make medical sense of the sequence.
It is doubtful that the scientists and physicians who first started talking about the $1,000 genome in 2001 could have imagined that we would be on the verge of that achievement within the decade. As the cost of sequencing continues to freefall, the challenge of solving the data analysis and storage problems becomes more pressing. But those issues are nothing compared to the challenge facing the clinical community who are seeking to mine the genome for clinically actionable information—what one respected clinical geneticist calls “the $1 million interpretation.” From the first handful of published human genome sequences, the size of that task is immense.
Although early days, a number of groups are making progress in creating new pipelines and educational programs to prepare a medical ecosystem that is ill-equipped to cope with the imminent flood of personal genome sequencing.
Pathologists’ Clearing House
The pathology department at one of Boston’s most storied hospitals isn’t necessarily the place where one might expect to find the stirrings of a medical genomics revolution, but that’s what’s happening at Beth Israel Deaconess Medical Center (BIDMC) under the auspices of department chairman Jeffrey Saffitz.
“I see this as ground-breaking change in pathology and in medicine,” he says.
Together with Mark Boguski and colleagues, Saffitz has introduced a genomic medicine module for his residents (see “Training Day”). And under the stewardship of applied mathematician Peter Tonellato, he is building an open-source genome annotation pipeline that might pave the way for routine medical inspection once whole-genome sequencing crosses the $1,000 genome threshold.
All well and good: but why pathology? [In my 25 years in University Medical Schools I find it quite unheard of to teach Pathology first, followed by Physiology. For Pathology, taking Physiology is a prerequisite - AJP] “We are the stewards of tissue and we perform all the clinical laboratory testing. This has been our function historically for many years. But we have a sense that the landscape is changing,” says Saffitz. Genetic testing, he argues, must be conducted under the same type of quality assessment, regulatory oversight, and CLIA certification as provided by the College of American Pathologists (CAP), “and should be done by physicians who are specifically trained to do this. That’s us!”
“The brilliance of that,” says Boguski, a pathologist by training, “is that it removes a lot of the mysticism surrounding genomics and makes it just another laboratory test.” There’s really nothing magical or different about DNA, insists Saffitz. “We regard a file of sequence data as a specimen that you send to the lab, just like a urine specimen!”
BIDMC is a medium-sized hospital that conducts 7 million tests a year. Arriving in Boston five years ago, Saffitz began recruiting visionaries to shape “the future of molecular diagnostics” and help the discipline of pathology become a clearinghouse for genomic medicine in a way that is “going to revolutionize the way we do medicine.”
Boguski is best known as a bioinformatician who spent a decade at the National Center for Biotechnology Information (NCBI). He sums up the genomic medicine informatics challenge thus: “You have 3 billion pieces of information that have to be reduced to six bytes of clinically actionable information. That’s what pathologists do! They take in samples—body fluids and tissues—and we give either a yes/no answer or a very small range of values that allow those clinicians to make a decision.”
Increasingly, he says, pathology will become a discipline that depends on high-performance computing to extract clinically actionable information from genome data. That frightens many physicians, but Boguski cites a precedent. “Modern imaging technology would not be possible were it not for high-performance computing, but it’s built into the machine!” he says. “Most practicing radiologists don’t think about the algorithms for reconstructing images from the X-rays. Most pathologists in the future won’t think about that stuff either—it will just be part and parcel of their trade. Nevertheless, we have to invent those technologies.”
Math Lab
Mathematician Peter Tonellato has a deep interest in software systems for the clinic, and formulated the idea of a whole-genome clinical clearinghouse within pathology. “We have to start thinking about genetics as just another component of data information and knowledge that has to be integrated into the electronic health record. Stop labeling genetics as something different and new and completely outside the mainstream medical establishment and move it back into the fundamental foundational effort of medical activity.”
Come the $1,000 genome, it will simply make sense to sequence everyone’s tumor, he says. Just as pathologists study tissue biopsies under a microscope, “we’re going to be sequencing it in parallel and figuring out which pathways and targets are pertinent to that person’s condition.” Simply doing more specialized tests isn’t the solution. “How many tens of millions of dollars and how many years has it taken to validate [the warfarin] test?” asks Boguski. “Multiply that by 10,000 other genes and it simply doesn’t scale. We’re going to have to look at this in a whole new way.”
Tonellato has been funded by Siemens and Partners HealthCare to construct an open-source, whole-genome analysis pipeline. Although not commercially released, the pipeline is built and being used for some pilot projects. He is also partnering with companies—including GenomeQuest—who want to do the sequencing analysis in a best-of-breed competition to establish the most refined NGS mapping utilities and annotation tools. The goal is to annotate those variants in a clinically actionable way down to Boguski’s six bytes of information and the drug response recommendation. “We think we’re as far forward in terms of doing that in an innovative and pragmatic way as anyone,” says Tonellato.
Using the cloud (Amazon Web Services), his team has lowered the cost of whole-genome annotation to less than $2,000. “Everybody talks about the $1,000 genome, but they don’t talk about the $2,000 mapping problem behind the $1,000 genome,” he says. It takes Tonellato’s group about one week using five nodes for the resequencing, mapping and variant calling, while the medical annotation takes three people about a month. High-quality computer scientists have to be paid too, he says. “You can’t just talk about the sequencing costs.”
Of course, it is most unlikely that hospitals will start running massive NGS and compute centers. “We envision a day where every clinical laboratory in every hospital in this country can do this testing,” says Saffitz. “They’re not going to do the sequencing, but there’ll be a machine where they can basically acquire the data, analyze it, and send a report to the doctor saying, ‘This is what we found, this is what it means, this is what you do.’” Where the sequencing is done isn’t of great concern. “We actually treat sequencing as a black box,” says Boguski. What’s important is that the hospital’s cost requirements and quality standards (and those of the FDA) are met. But Tonellato reckons it would be “very odd to have U.S. samples sent abroad for sequencing to Hong Kong or India... and then sit around and wait for the CLIA-certified, clinically accurate results to come back to us. That may happen in the future, but we have to get our own house in order first.”
Another problem is the current state of the gene variant databases, which Boguski calls “completely inadequate” in terms of clinical grade annotation. Where such a resource belongs is open to debate but Boguski is certain it does not belong with the government. “The government is not a health care delivery organization. Whatever that database is, it needs to operate under the same CLIA standards as the actual tests.”
Pathologists have traditionally interacted with patients when they are sick. “But more and more,” says Saffitz, “we’re going to be analyzing the genomes of people who are well, and I hope assuming a very prominent role in the preservation of health and preempting disease.”
Quake Aftershocks
The most comprehensive clinical genome analysis to date was reported in May 2010 in the Lancet. Stanford cardiologist Euan Ashley and colleagues, including Atul Butte and Russ Altman, Stanford’s chair of bioengineering, appraised the genome of Stephen Quake (see, “A Single Man,” Bio•IT World, Sept 2009). “This really needs to be done for a clinical audience to show them what the future is going to be like,” says Altman, who is also director of the biomedical informatics program and chief architect of the PharmGKB pharmacogenomics knowledgebase. The task of interpreting Quake’s genome involved more than 20 collaborators, including bioethicist Hank Greeley and genetic counselor, Kelly Ormond. When discussions turned to the risk of sudden cardiac arrest (Quake’s family has a history of heart disease), Ormond would invite Quake to leave the room until a consensus was reached.
Altman’s own group was able to predict Quake’s response to about 100 drugs. Some of it was imprecise, but he realized that, “especially for the pharmacogenomics, we are much closer [to clinical relevance] than I realized.” He said he would “bet the house” on the results dealing with statin myopathy, warfarin and clopidogrel dosing. The Stanford team also tried linking environmental and disease risk, but Altman admits that is farther from clinical practice. The Lancet study drew high praise from the BIDMC team. “As good as it gets,” is Tonellato’s verdict. “But go down to some town in the middle of America and say, ‘What are you going to do with this genome dataset for your patient?’... Is medicine ready for genetics yet or not? There is a long way to go.”
Since the publication, Altman has received inquiries from companies interested in doing similar “genomic markups” and licensing his group’s annotations. Altman intends to hire an M.D. curator to complement his Ph.D. curators, someone who can highlight the clinical significance of research data. Altman says he would be happy to have PharmGKB data included “in any and all pipelines. Meanwhile, Ashley is leading a Stanford program to make a computer pipeline to reproduce the Quake analysis on a larger scale.
In a rational world, Altman says, it seems logical to sequence human genomes at birth and put the data in a secure database, querying it only when you know what you’re going to do with the results. That’s in an ideal world. In the United States, he notes dryly, some people do not trust governmental databases. “I could imagine if it’s cheap enough, that people will actually resequence the genome on a need-to-know basis, simply so they don’t have to store it. I think that’s a little bit silly, but in order to get genomic medicine effected, I’m not going to lose the fight over the database.”
Whoever ends up doing clinical genomic sequencing in the future, Altman says they will have to document high-quality data with a rapid turnaround. “We will then put [the data] through the pipeline—hopefully the Stanford pipeline or whatever pipeline seems to be winning—and then we will query it as needed and as requested by the physicians on a need-to-know basis.”
1,500 Mutations
Genome Commons was established by Berkeley computational biologist Steve Brenner to foster the creation of public tools and resources for personal genome interpretation. He wants to build an open access Genome Commons Database and the Genome Commons Navigator. He is also launching a community experiment called CAGI (The Critical Assessment of Genome Interpretation) to evaluate computational methods for predicting phenotypes from genome variation data (http://genomeinterpretation.org).
One notable private effort in clinical genome annotation is that of Omicia, a San Francisco-based software company founded by Martin Reese in 2002.
Omicia is taking genome data and extracting clinical meaning, focusing on DNA variation, rather than gene expression or pathways. “We have one of the best systems for interpreting the genome clinically,” claims Reese. He started with Victor McKusick’s classic Mendelian Inheritance in Man catalogue, which now lives online as OMIM, mapping a “golden set” of disease mutations to the reference genome. Omicia is also developing algorithms to predict the effect of protein-coding variants to better understand which mutations are medically relevant.
Reese sums up the goal: “You have 21,000 protein coding mutations compared to the reference genome. 10,000 of them are non-synonymous. We have 3,500 in disease genes. That’s roughly 15%. So 15% of 10,000 is 1,500 protein coding mutations. The goal is to interpret 1,500 mutations.”
For the time being, Omicia is offering its services through collaborations. Reese has a three-year collaboration with Applied Biosystems, and was a co-author on the first NGS human genome paper using the SOLiD platform in 2009. Then there is the Life Alliance, a cancer genome alliance, featuring various medical centers and Life Technologies. “We’re doing their interpretation of these cancer genomes for 100 untreatable cancers,” says Reese.
Presenting the data for a physician is a challenge, says Kiruluta, but not as bad as the scant amount of time a physician has to see a patient. “The reporting is to help a physician make a decision quickly—green light, red light. Then there’s a much more detailed interface behind the scenes,” where other medical professionals can study the patient’s data in more detail.
Reese sees advantages to the commercial approach for genome software compared to academic solutions. “This will be a big play in next few years as people make clinical decisions. So the quality of the software, the QC of the assembly, how transparent you are, the annotation, is critical. It will be a big problem for academia to do that—you know how it is when a postdoc writes something!” [Yes, I do. Government Software does not measure up, because it is not in touch with any real market. University Software does not mesure up, since when a postdoc writes a code - and graduates - the University Software either takes a new life in Industry if the postdoc leaves there - or quite simply dies without maintenance. For Genome Informatics software the only way to go is through "Industrialization of Genomics" - AJP]
Reese has also been spearheading the effort to develop a new Genome Variation Format with Mark Yandell (University of Utah) and others, which was recently published in Genome Biology.
DNA Partners
The challenge facing the affable Samuel (Sandy) Aronson, executive director for IT at the Partners HealthCare Center for Personalized Genetic Medicine (PCPGM) and PCPGM’s clinical laboratory director, Heidi Rehm, is to deliver clinically actionable information to physicians in the Partners HealthCare network. “This challenge cannot be entirely solved by a single institution,” Aronson notes. “It takes a network of institutions working together.”
Rehm maintains a knowledge base of 95 genes that are routinely curated by the PCPGM’s Laboratory of Molecular Medicine and supplies information to physicians on the status of those genes in their patients in real time. The PCPGM’s GeneInsight suite, developed by Aronson’s team, has been in use for about seven years. There are two components—one for the laboratory, the other for the clinician. The lab section consists of a knowledgebase—the tests, genes, variants, drug dosing, etc—as well as an infrastructure to generate reports via the Genome Variant Interpretation Engine (GVIE).
On the clinical side is a new entity, the Patient Genome Explorer (PGE), which allows clinicians to receive test results from an affiliated lab and query patient records. “The PGE, without a doubt, is one of its kind,” says Rehm. “There’s no other system out there. There’s a lot of excitement about it. Labs are choosing us for testing because we offer that service.” When an update is made to the PCPGM knowledgebase on a variant that is clinically significant, the PGE proactively notifies the clinicians caring for patients with that variant. If there are 100 clinics with 10 patients each, and Rehm updates the knowledgebase, then 1,000 patient updates are dispatched automatically.
For inherited disease testing, the alert changes the variant from one of five categories to another: 1) pathogenic 2) likely pathogenic 3) unknown 4) likely benign, or 5) benign. The PGE made its debut last summer in the Brigham and Women’s Hospital Department of Cardiology. When the system launched, a dozen “high alerts” (meaning a variant has shifted from one major category to another) were immediately dispatched. The physicians’ response has been really positive, says Aronson. “There’s a significant disconnect between the level of quality of data being used for clinical purposes and the quality of data in the research environment,” says Rehm. “Our hope with the distribution of this infrastructure is to get more data validated for clinical use.”
Core Challenges
The Partners effort is a worthy start, but the larger goal is to build a network where labs with expertise in other genetic disorders such as cystic fibrosis contribute their data, perhaps by offering attribution or a nominal transaction fee. “We can’t maintain data on every gene, but we’re willing to establish nodes of expertise,” says Rehm. As for the IT infrastructure, Aronson hopes to enable organizations to create a node on the network, link to the PGEs, and then operate under their own business models—whatever it takes to make the data accessible. The first external partner that linked to GeneInsight was Intermountain Healthcare (IHC) in Utah. “We believe this is the first transfer of fully structured genetic results between institutions so that they got into IHC’s electronic health record and are now available for decision support,” says Aronson.
Aronson anticipates a day where whole-genome sequencing for patients will be a clinical reality. “It’s very much on our radar,” he says, but doesn’t appear unduly concerned. After all, he says, the PGE is designed to store highly validated clinical information, and he doesn’t expect the millions of variants in a whole genome to contain enough clinically actionable variants to overwhelm the database. The challenge will come in understanding complex/low-penetrance diseases, “where we’re more algorithmically dependent. That will require new infrastructure.”
A bigger problem is facilitating the business models that will solve personalized medicine challenges. “Our goal is to expand networking, adding labs, PGEs and going after a network effect,” says Aronson. “We have a structure that could present an answer to how do you—in a true patient-specific, clinically actionable way that clinicians can use in their workflow—help interpret the data?
[Comment (1)
Kevin has pointed to a most important development if genomics is to deliver on long-awaited promises. An available, affordable personal genome has little value without analysis and interpretation delivered in consumable application.
Our "Genome Revolution" often invites analogy with the Space Age, e.g. comparing the Genome Project to the Moon Project.
The comparison is unfair to the Moon Project unless genomics delivers the full ride.
The Moon Project promised “to put a man on the Moon, and bring him safely back”. If we sequence the entire human DNA and fail to deliver the harder half of interpreting the sequence, the comparison is more akin to the Russians blasting a dog into space and leaving him there.
The ambitious approaches noted in this article all seem to be charting new territory and struggling to break from long-held erroneous beliefs. Trying to fix hereditary diseases without solid principles of recursive genome function as explained by (holo)genome physiology and biophysics is like trying to fix a broken television set without understanding how it works in the first place.
Thank you, Kevin, for addressing the key topic for our critical time.
---
For a preview of this message, see YouTube "Is IT ready for the Dreaded DNA Data Deluge?" 2 years ago . Also, see The Principle of Recursive Genome Function (FaceBook) / Pellionisz_at_JunkDNA.com]
Mastering Information for Personal Medicine
Pathway
Sept. 27, 2010
Eric E. Schadt, Chief Scientific Officer of Pacific Biosciences
To make the most of new technologies, medicine must come to grips with the mountains of data it will produce.
Sometimes, mastery over the raging influx of information all around us has life and death consequences. Consider national security agencies charged with ensuring our safety by detecting the next big terrorist threat. Presented with worldwide email traffic, phone conversations, credit card purchase histories, video images from pervasive surveillance cameras and intelligence reports, the challenge for these agencies is to integrate all this abundant, disparate information and to present it to analysts in ways that help to identify significant threats more quickly.
Soon we will all be faced with a similar challenge that could have a dramatic impact on our well-being. In the not-too-distant future, average Americans will have access to detailed information about their genetic makeup, the molecular states of cells and tissues in their bodies, longitudinal collections of readings on their weight, blood pressure, glucose and insulin measurements, and myriad other clinical traits informative about disease, disease risk and drug response. Whereas classic molecular biology and clinical medicine offered only simple links between molecular entities and disease (for example, relating insulin levels and glucose levels to risks of diabetes), new technologies will provide comprehensive snapshots of living systems at a hierarchy of levels, enabling a more holistic view of human systems and the molecular states underlying disease physiologies. All this data—once appropriately integrated and presented—will allow us and our doctors to make the best possible informed decisions about our risks for disease; it will also help us to tailor treatment strategies to our particular disease subtypes and to our individual genetic and environmental backgrounds.
Powerful examples of how this new era of personalized medicine will change diagnosis and treatment are already available. A now-routine genetic test can indicate whether breast cancer patients will respond to treatment with the drug Herceptin, and testing for certain changes in DNA that affect blood-clotting can help doctors decide what dose of the anticoagulant warfarin would be safest for certain patients.
However, unlike the doctor of today, armed with a stethoscope and thermometer, tomorrow’s doctors will have access to a multitude of biosensor chips and imaging technologies capable of monitoring variations in our DNA and in the activities of genes and proteins that drive all cellular functions. They will be able to order scans with singlecell resolution for any organ in our bodies. How will such data be managed? How will it be analyzed and contrasted with similar types of data collected from populations so that the totality of these data help us to better understand our specific condition? How will the complex models derived from such data be interpreted and then applied to us as individuals by our doctors? Is the medical community prepared—and are individuals ready—for this revolution?
Managing Mountains of Data
The biomedical and life sciences are not the first to encounter this type of big data deluge. Google, which is among the most sophisticated handlers of big data on the planet, aims for no less than “organizing the world’s information” by employing high performance, large-scale computing to manage the petabytes of data available on the Internet. (A petabyte is one million gigabytes. By one estimate, 50 petabytes could store every written work in every language on earth since the beginning of recorded history.)
Companies such as Microsoft, Google, Amazon and Facebook have become proficient at distributing petabytes of data over massively parallel computer architectures (think hundreds of thousands of sophisticated, highly interconnected computers all working in concert to solve common sets of problems). Their technologies grab bits of those data on the fly, link them together and present them to users on request in fractions of a second.
However, the problems those companies have solved thus far are much simpler than understanding how the millions of variations in DNA distinguish us as individuals, the activity levels of genes and proteins in all the cell types and tissues in our bodies, and the physiological states associated with disease. The data revolution in the biomedical and life sciences is powered by technologies that provide insights into the operation of living systems, the most complex machines on the planet. But achieving such understanding will require that we tame the burgeoning information those technologies generate.
Within the next five to 10 years, for example, companies like Pacific Biosciences will deliver new singlemolecule, real-time sequencing technologies that will enable scans of a person’s entire genome (DNA), transcriptome (RN A) and chemical “epigenetic” modifications of the genome in a matter of minutes and for less than $100. For a single individual, hundreds of gigabytes of this information could be gathered from many tissue and cell types, at multiple time points and under varying environmental stresses. Layer on top of it more data from imaging technologies, other sensing technologies and personal medical records, and one might possibly produce terabytes (trillions of bytes) of data per individual, and well into the petabyte range and beyond for populations of individuals. Hidden in those collective data sets will be answers relating to the causes of disease and the best treatments for disease at the individual level.
Integrating such data and constructing predictive models will require approaches more akin to those now employed by physicists, climatologists and workers in other strongly quantitative disciplines. Biomedical investigators and information specialists will need to develop tools and software platforms that can integrate the large-scale, diverse data into complex models; experimental researchers will need to be able to use these models and refine them iteratively to improve their ability to assess the risk and progression of disease and the best treatment strategies. In the end, these models will need to be able to move into clinical settings where doctors can employ them effectively to improve patients’ conditions without necessarily having to understand all of the underlying complexities that produced the models.
Only by marrying information technology to the life sciences and biotechnology can we realize the astonishing potential of the vast amounts of biological data that new generations of devices can gather and share. Such data, if properly integrated and analyzed, will enable personalized medicine strategies that could lead to everyone making better choices, not only on treating disease, but preventing it altogether.
Eric E. Schadt is chief scientific officer at Pacific Biosciences in Menlo Park, Calif. and co-founder and a director of Sage Bionetworks in Seattle, Wash.
[For a preview of this message, see YouTube "Is IT ready for the Dreaded DNA Data Deluge?" 2 years ago - (FaceBook) / Pellionisz_at_JunkDNA.com]
Cacao Genome Database Promises Long Term Sustainability
Chocolate-based Economy? (Potato, too... ) - AJP
Triple Pundit
September 20, 2010
by Leon Kaye
It is one of the oldest foods and is the subject of ancient texts and myths. One of the top ten most traded commodities in the world, this plant is a huge part of the economies of countries ranging from Cote d’Ivoire to Ecuador to Papau New Guinea. The finished product props up some of the world’s best known brands, and it exudes luxury while also contributing to a brutal way of life for some of the world’s poorest people—including hundreds of thousands of children. The cacao tree is also the subject of science, from botanists, agronomists, and now, geneticists.
Now scientists have decoded 92% of the cacao tree’s genome. Funded by MARS with the support of the US Department of Agriculture, IBM, and several universities, the Cacao Genome Database project is three years ahead of schedule. With the sequenced genotype, Matina 1-6, the project promises to solve such problems as pests and diseases that often plague cacao farmers, and in the long run, could improve both the production and sustainability of the cacao industry.
With this genome sequencing, cacao will join other commodities including rice, corn, and wheat, all of which have already gone through the process. Promises are aplenty: improved crop yields, heartier cacao beans, and improved production within the entire supply chain from farmers to chocolatiers. The project also tackles the long term sustainability of what some would call big chocolate: the demands of giants including Hershey, MARS, Cadbury, Nestle, Kraft, and Lindt. Over the past quarter-century, the growing global appetite for cacao has caused its global production to double, but the increase has come through more land use, not improved yields.
So will we all nosh on Matina Bars or Matina Kisses in the near future? It definitely could boost demand for organic and fair trade chocolate brands, as plenty of customers will add chocolate to the “non-GMO” shopping list. Large cacao farming operations stand to benefit as well. The environment possibly could be a winner, with a reduction in the use of pesticides and other chemicals. Plenty of long term questions, however, remain. Will less common varietals of cacao trees survive? What about smaller farmers, who could find themselves squeezed by the price of coveted pods and seedlings?
Or is this just the reality farmers, producers, and consumers must face in order for an industry to survive? The global cacao industry lost $US700 million the past 15 years from a trio of fungal diseases alone. Such losses do not only affect the bottom line of companies like Nestle & Hershey: the livelihoods of many people who have limited economic opportunities may hang in the balance as well.
[As detailed on "Genome Based Economy", the present "Genome Revolution" is not at all the first chapter in entirely changing the global economy. Norman Borlaug (Nobel Prize, 1970) started the "Green Revolution" - that with the help of Genomics at that time, saved billions of people from starvation (and by removing the reality of dying of hunger, turned India and China into global powers, as they are now). With the global population exploding over 7 billion, there is universal agreement that a "Second Green Revolution" is needed. By means of full DNA sequencing, PostModern Genomics delivers (no wonder that Product and Food Companies, such as NESTLE, KRAFT pitch in with very substantial funds, as well as agricultural giants like Monsanto are in the first 10 on the Pacific Bioscience' "short list" that already bought in cash the PacBio SMRT sequencer. Another aspect of this news is, that the already existing "Personalized Chocolate, best fitting to your Genome" (with technology shown here) will reach masses of consumers. (Without and way before full DNA sequencing, diabetics already have sugar-free chocolate...). Some might say "chocolate is insignificant" (which it isn't). Potato certainly is one of the main sources of global nutrients (and look what the US did with rice for India in the First Green Revolution...). Now high-protein potato is claimed to have been developed by India, for themselves and perhaps to the World. - (FaceBook) / Pellionisz_at_JunkDNA.com]
US clinics quietly embrace whole-genome sequencing
Published online 14 September 2010 | Nature | doi:10.1038/news.2010.465
It may be small-scale and without fanfare, but genomic medicine has clearly arrived in the United States. A handful of physicians have quietly begun using whole-genome sequencing in attempts to diagnose patients whose conditions defy other available tools.
As hospitals and insurers battle over coverage for single-gene diagnostic tests, and the US Food and Drug Administration cracks down on the products of personal genomics companies, a growing number of doctors are relying on the sequencing of either the whole genome or of the coding region, known as the exome. [No, the FDA did not "crack down" on personal genomics - if anything, they blew their case with an incompetent (admittedly non-scientific "analysis" of a science) and malicious and deplorable "From Gulf oil to Snake oil" soundbite of a lame-duck politician]
"If one hospital is doing it, you can be sure others will start, because patients will vote with their feet," Elizabeth Worthey, a genomics specialist at the Human and Molecular Genetics Center (HMGC) of the Medical College of Wisconsin in Milwaukee, said at the Personal Genome meeting at Cold Spring Harbor Laboratory in New York last weekend.
In May 2009, the genetic-technology provider Illumina, based in San Diego, California, launched its Clinical Services programme with two of its high-throughput genome analysers. The company now has 15 such devices dedicated to this programme.
Illumina provides the raw sequence data attained from a patient's DNA sample to a physician, who passes it on to a bioinformatics team, which works to crack the patient's condition. However, Illumina is working to develop tools to help physicians navigate genomes and identify genes already associated with diseases, as well as novel ones.
So far, the company has sequenced more than 24 genomes from patients with rare diseases or atypical cancers at the request of physicians at academic medical centres. The standard US$19,500 price tag is typically covered by the patient, by means of a research grant, or with the help of private foundations, although one patient is currently applying for insurance reimbursement.
Steering treatments
Such efforts are having a direct effect on treatment decisions. For three years, physicians at the Children's Hospital of Wisconsin in Milwaukee had struggled to treat a child whose intestines had become swollen and riddled with abscesses. At the age of 3, he had more than 100 separate surgeries and his colon was later removed, but his doctors were stumped.
They called on Worthey and her colleagues at the HMGC. The team obtained a completed exome sequence for the child and used in-house tools to identify the disease culprit as the protein XIAP, which inhibits a programmed-cell-death pathway called apoptosis. XIAP has a role in the immune system and is conserved across organisms including primates, flies and frogs.
The hospital's lab was then able to show that the child's cells were more sensitive than normal to apoptosis, and the gene is known to play a role in the immune system. On the basis of this diagnosis, the physician recommended a bone-marrow transplant in June 2010. By mid-July, the child was eating his first meal.
Such work demands substantial resources. That child's case took a team of 30, says Worthey, and included a 12-person bioinformatics team, three sequencing technicians, five physicians, two genetic counsellors and two ethicists. The hospital is already working on a handful of other whole-genome sequences, and plans to be analysing 90 per year by 2014.
During the past year, familial whole-genome and exome sequencing has identified gene variants with a role in disease at a rate of two to three per month. One major programme, the Undiagnosed Diseases Program at the National Institutes of Health in Bethesda, Maryland, has received more than 3,000 enquiries and reviewed 1,192 medical records, diagnosing 15% of the cases they have accepted. As of this month, the programme has also completed 59 exomes from 15 families. Thomas Markello, a geneticist and paediatrician on the project, says that the team has confirmed one genetic cause for a disease, and has a dozen new candidates to be validated.
Whole-genome sequencing is also affecting treatment choices for atypical cancers. Richard Wilson, director of the Genome Sequencing Center at Washington University in St. Louis, Missouri, spoke at the meeting of a 39-year-old woman who was thought, from a bone-marrow biopsy, to have acute promyelocytic leukaemia (APL).
However, when she was given the standard diagnostic test for the disease, this failed to demonstrate the expected exchange of a large piece of chromosomes 15 and 17, which causes two genes to fuse together.
But when Wilson and his colleagues sequenced and analysed cancerous tissue in the bone marrow, they found that a small chunk of chromosome 15 had popped out and been inserted into chromosome 17, fusing the two affected genes in a novel way. As a result, the woman was prescribed a drug known to improve survival in patients with APL. "We were able to assist oncologists in making an effective diagnosis and treatment, which — not trying to hype it at all — saved the patient's life," Wilson said.
Tim Aitman, a molecular geneticist at the UK Medical Research Centre's Clinical Science Centre in London, says that cases in which whole-genome sequencing has directly benefited the patients involved are still rare. "The view is these are anecdotes and one-off occasions," he says, "but it is inescapable that within the next 10 and 20 years that will become much more routine."
[It is not up to FDA or any red-tape, if We The People (who, by the way) pay for the FDA "non-scientific experts" by their tax dollars, decide to go to the genomic culprits of deadly diseases. - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
The Broad's Approach to Genome Sequencing (Part II)
Bio-IT World | September 17, 2010
Since 2001, computer scientist Toby Bloom has been the head of informatics for the production sequencing group at the Broad Institute. Her team is the one that has to cope with the “data deluge” [see my 2008 YouTube "Is IT ready for the Dreaded DNA Data Deluge - AJP] brought about by next-generation sequencing. Kevin Davies spoke with Bloom about her team’s operation, successes and ongoing challenges.
BIO-IT WORLD: What’s the mission of your team?
TOBY BLOOM: Our goal is to be able to track everything that’s going into the lab from the time samples enter the building, through all standard processing of the data. My team is responsible for managing the sample inventory, keeping track of the projects, the LIMS (Laboratory Information Management System), which tracks processing events in the lab, the analysis pipeline, which at this point includes the standard vendor software, then alignment, various quality checks, generating metrics, and we do SNP [single nucleotide polymorphism] calling for fingerprinting. We have a data repository – a content management system that makes all that sequence data available to the researchers when it gets handed over to their side for further analysis.
Did your team build the LIMS?
We did, many times! We have a couple of times in the past looked at what’s on the market, but not recently. Because of the scale we’re at and how fast we change things, we usually find that any one product that’s out there is aimed at one of the things we do, but not all of them. We’ve had our own LIMS since before I got here, nine years ago, but for next-gen sequencing, we’ve had to rebuild much of that. We’re far enough ahead of the curve on most of this stuff that most of the LIMS out there wouldn’t be ready in time.
How big is your team and what is its chief expertise?
There are about 25 people. The vast majority is software engineers, but I have a couple of people in data management, and a couple deal with the databases. Everybody else is writing code, mostly Java programmers.
What brought you to the Broad, or the Whitehead Genome Center as it was then?
I was just fascinated with what was going on! It was clear from as far back as ’95 they were bringing in computer scientists to deal with the data challenges. I didn’t get here until ’01. I was looking to change positions, and it’s just a fascinating place to be. I didn’t know a lot about the biology but it’s exciting to be a part of what Broad is doing.
What do you do in terms of downstream processing?
We do a number of things in the software. We handle a variety of different technologies. We built a pipeline manager that allows us to specify the workflows that should be used for various types of analyses or sequencing. So if we’re doing RNA-sequencing for example, we’re doing something a little different than whole-genome shotgun or targeted sequencing. It [the pipeline manager] lets us handle many pipelines at once. It lets us pull in information from our instruments, our LIMS, and our sample repository to decide what to do on the fly. All of those pieces are integrated.
We’re doing 0.5-1 Terabases a day. We’re doing a lot of processing! There’s a focus on high throughput and automation. Having it under our own control and being able to change rapidly is important.
Within the pipeline manager, we run the Illumina vendor software. What part runs off instrument changes over time. We started out doing the image processing off the instrument, but it got to the point where [Illumina] could do the image processing reliably enough on–instrument that we could use that. Then we started pulling the intensities from the instrument, instead of images. I hope that with the HiSeq 2000s, we soon get to the point where they do the base calling on the instrument. We’re still doing all the base calling in the pipeline right now, but maybe we’ll soon get to the point where we can take the base calls off the instrument and just do the downstream processing – creating BAM files, recalibration, alignment, deduplication, quality analysis, SNP calling, etc.
Are you able to distribute Broad Institute resources such as the pipeline manager to the community?
We’re not proprietary about it, but because all our pieces are integrated, it’s sometimes hard to release pieces of code because they depend on our databases or other internal metadata. We’ve released some of our BAM file processing tools, the Picard tools, publicly. I’ve been trying to see if we could make our pipeline manager run in the Cloud, to make it available to other people. We’ve done some work to isolate our actual pipeline management from our database and internal structures, but it’s not ready to do that yet . . . The goal is to be able to flexibly create and change workflows, and run many at once. It’s focused on massively high throughput and very automated processing. We want to make sure that if something fails -- because we’re running 2,000 compute cores at a time, things will fail, servers will drop out – it can track where everything is, what’s failed, what’s stuck and hasn’t turned up. Our goal is to be able to restart from the last step automatically without a lot of human intervention. In some ways we do that better than others but we’re always working on it. The goal is to push all of this stuff through without a lot of people.
Do you function at all like a core lab?
We don’t’ function as a core informatics facility, in other words we don’t provide a service for building custom software, but we will do specialized things for certain projects. We’re not here as a service, we’re here to support production, but we do get requests. We’re very much a production system, so we’re not [writing] research algorithms [This is very interesting. Although Eric Lander et. al. have been exploring in the cover article that "Mr. President, the DNA is Fractal ! (see top diagram of this column), HolGenTech, Inc. is let to spearhead algorithmic approaches of DNA function - in part because of my trail of IP protection since 2002. Algorithms and Software for "Recursive Genome Function" [presently, at 269,000 hits on Google] is to emerge from the intellectual resource and facility of HolGenTech, Inc. in Silicon Valley - not from Broad - AJP]. We do take research algorithms when they’re working well enough and optimize them to make them more robust to run in a pipeline. There are specialized cases where [Broad] research groups will come to us and say, we need specialized processing of the data in the pipeline. So we have to do something different, e.g. for epigenetics or RNA-seq, things like that. Sometimes they’ll ask us to write specialized code, and we can sometimes, but we don’t always have the bandwidth.
We often hear about the “data deluge.” [See above YouTube - AJP]. What’s it like facing the brunt of that?
From the informatics side, we were all prepared to see the data volume go up. We were ready for the hardware choices … same for the software. The big surprise wasn’t that or the amount of data coming off the machines. What had us playing catch up was the impact on the lab and the LIMS. It was more the change in the number of libraries we were making, the number of samples in the lab at once, than the actual amount of data – from my point of view. I’m not saying it was easy to scale the data, but we weren’t predicting the whole lab process would have to change so much because of the volume of samples. When we were doing large genomes on the [ABI] 3730s, a library would last a month or more. We didn’t have to worry about 1,000 samples in the same step in the lab at the same time and having to track them to make sure they didn’t get mixed up or lost. We built many layers of tracking in the LIMS that weren’t needed before. That’s been a major change.
Other parts of the Broad’s sequencing operation borrow from proven factory automation methods. Can you apply any of those methods on the informatics side?
Well it’s not quite the same -- you can’t put tape on your screen! It’s more of focus on how do we do rapid iterations reliably. Things change in the lab very quickly. Your standard engineering software practices – gathering requirements and writing careful specifications and then doing careful design and building – isn’t a process that works in this environment, because by the time you get through all those steps, you’re building the wrong thing. We need to move rapidly, whereas that model is made for building software for processes that are well established and you’re automating them.
We are building software often ahead of the process. We’re trying to get enough working that they can function and get the data they need, before they really know what they need from us. They’re doing ongoing process improvement . . . We have to focus on how we can identify what they need most, and how to change along with their process changes. We need to build it in small pieces and then add to it without rebuilding what you already did. In many ways, it’s agile software development. It’s as close to agile as anything else, but it doesn’t follow a (typical) agile process.
How much are you involved in the decision to put machines or new platforms into production?
We’re definitely part of that. It’s not just that we have to be satisfied that it’s ready to go, it’s that “we’ve got the software changes in that you need.” The Illumina software that runs in our pipeline has changed several times. We had to get that software into production too. When there are changes in data types and metrics, we have to change all that in our system.
Do you communicate much with the vendors on the software?
We often take beta versions of their software before it’s out. We’re expected to find their bugs! We can’t wait for their official release. We’re the first ones to get the instruments often, so yes, there’s a very definite interaction on the informatics side as well.
We have weekly calls with [Illumina] about the informatics. On the HiSeqs, we don’t want to pull the intensity data if we don’t have to. We’re just validating we can get the same results using their on-instrument base-calling; we need to understand the failure modes in the integration so we can make sure we’re not going to lose data.
What impact will the third-generation sequencing technologies such as PacBio and Ion Torrent have on your team? [Note, that the Broad Institute is on the short-list to receive shipment of PacBio' SMRT sequencer... -AJP]
The long reads will help with a number of kinds of analyses downstream, but they don’t affect the production software I build as much. We’re looking forward to having long reads.
I try to make sure I know what all of the things are on the horizon that might show up and what the informatics implications are. Sometimes it matters, sometimes we don’t have to do much to prepare. We initially thought the biggest difference might be the size of the data, the bytes/base might be different on different instruments. On the HiSeq, Illumina has gotten down to essentially one byte/base, so that difference -- where you didn’t have to pull images -- has gone away. There are some that have much higher volumes of data than others.
The differences in the [sample] prep process matter to us, because it matters what our LIMS can handle. We watch but we don’t jump into active building until we have a machine in house and we think it’s time to ramp up.
What have you been doing in the Cloud?
There are a couple of reasons for exploring the Cloud. One is small centers that don’t have the IT infrastructure to be able to handle the volumes of data and the complexity of the processing. That’s not an issue for us but it is for small centers. The other side is the big collaborative projects, where you have many, many centers sharing data -- many centers producing data, and many centers that are then processing the data, e.g. 1000 Genomes or TCGA. (TCGA we can’t yet put on the Cloud because of security concerns.)
For some of the groups that want to do analysis, getting the data back and forth from NCBI or other centers is a burden. If the data could be put in one place and everyone could move the compute to the data . . . When you get to these very big projects, moving the compute to the data seems very much more efficient than having to keep moving the data every time you want to compute. So that’s the model: can we put the data in one place and move the compute to the data as needed?
That’s the experiment. I’m not saying we’ve gotten there. Very different from some of the Grid models, who provide the compute, and essentially, if you don’t have the compute you need, you can just borrow it, but you have to get your data there. … This is very much, let’s not move the data—the data is the problem. I have a grant to experiment with my pipeline. One of the experiments is: Could we put a pipeline manager up there [Amazon EC2] with a lot of the standard analysis steps, let people go to the Cloud and figure out how to use it, for their own pipelines and workflows? I don’t’ think we’re there yet. This only works if it’s easy to get the data in the Cloud. It’s clearly not the kind of application that was targeted originally by the public Cloud vendors.
Are putting the data and running the pipeline in the Cloud two separate issues?
They are. We all submit these data to NCBI or EBI, and those two data repositories are already putting some of their data up on the Cloud to make it more available. Whether it goes on a public Cloud or not is not the question. If we’re already sending data to NCBI and EBI, and those guys exchange and replicate all the data anyway, could that be the foundation for the data already being there? NCBI isn’t about to provide all the compute for the world. But the notion is we already have a central repository, if that were part of a Cloud-like infrastructure -- whether on the Amazon Cloud or another commercial Cloud, or a private Cloud -- is that kind of architecture useful?
The jury is still out on the Cloud and how to do it. Is the Cloud model a helpful model for the community? We won’t know that until we can run things enough to test it. Can we make it work on the existing Cloud infrastructure? The jury is still out on that one also.
[What has happened/is happening at Broad appears to be a major validation of the YouTube-s "Pellionisz", with HolGenTech, Inc. (not everything is on the website...) slated to be for the role of the kind of advanced algorithm- and software developments that is suitable for the (near) future of "Private Clouds" for DNA Analytics in Hospitals' basement, next to their "traditional data labs" - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
Pellionisz Principle; "Recursive Genome Function" gets well over a quarter of a Million hits (261,000)
"Facts don't kill theories - only a better theory can surpass obsolete dogmas [AJP]". The "Death of Central Dogma" used to be a monthly event for some significant time by now, but Nobelist Crick's obsolete theory only became dead as a doornail by Pellionisz Principle of "Recursive Genome Function" actually replacing BOTH Crick's arbitrary "dogma" (that was quite laughable from its first utterance in 1956 e.g. by Nobelist Francois Jacobs) and Ohno's also doubted "Junk DNA" fatal mistake (1972).
"Recursive Genome Function" gets not only more hits (today, 261,000 on Google) than the two other COMBINED, but now is consistently well over quarter of a Million hits.
It may be particularly noteworthy that this is the second time when Pellionisz' biophysics came out ahead of Crick's failed efforts addressing solid intrinsic mathematics of living systems. Crick started from modest physics (B.Sc.) and invoked Erwin Schroedinger's essay "What is Life?" - where it was crystal clear to the physicist Schroedinger as early as in 1944 that the ultimate secrets of "Life" could, therefore must be cracked by the power of mathematics. Yet, Francis Crick, gotten lucky by Rosalind Franklin's revealing chrystallography of the double helix (not triple, as Linus Pauling almost got it right) Rose's photos cleverly obtained by and Francis and so skillfully co-publicised the structure of the DNA scaffold with Jim Watson - Francis Crick failed to deploy any advanced biophysics to the actual coding of Schroedinger's predicted "covalent bondings". Instead, itchy because he was still not getting the Nobel, in 1956 Francis Crick scribbled his Central Dogma longhand, and published and laudly promoted till the end of his life in 2004 (c.f. "I have never seen Francis in a modest mood" - a famous saying by Jim Watson). A setback of Genome Informatics ensued for over half a Century by his "Dogma" (later he confessed that he did not know what the Latin word "Dogma" meant - believable since he had failed to gain his intended place at a Cambridge college, probably through failing their requirement for Latin).
The half a Century setback setback never bothered Crick much, since upon getting his Prize he changed fields - realizing that the sugar double helix was a mere scaffolding, he ventured into proteomics - only to realize that it was too difficult. Soon after the "Central Dogma" almost collapsed (though Ohno made in 1972 an all-out effort with his "Junk DNA" silly notion to argue that even if there is a protein-to-DNA recursion, it would only find "Junk", devoid of information), by the Nobel to Baltimore et al. (1975) Crick elected to change fields from Genomics to Neural Networks. (The paradigm shift that instead of AI, creating intelligent systems without and before understanding what intrinsic mathematical language actual neural networks are using to produce brain functions). My earlier victory over Crick on the turf of Neural Nets was easy - as a Neural Net pioneer I explained the function of cerebellar function of actual neural nets of cerebella (spacetime coordination) in crisp terms of tensor geometry by Tensor Network Theory- whereas Crick was aiming at "consciousness", largely devoid of mathematics. A direct comparision of my Tensor Network Theory (verified by independent experimentalist on basic sensorimotor systems) is provided by the same Pat Churchland, who collaborated with Crick to solve higher order brain functions (consciousness) at the level of philosophy. Devoid of mathematics, it is clearly a futile exercise.
Let no one believe that I have any personal grudge against Francis Crick. I never-ever met him (even my Google Tech Talk YouTube in 2008 when I claimed that "there was no Emperor", Crick was gone already for 4 years).
My pure interest with destroying roadblocks and thus getting us on the open road again is to focus at this crucial time of "inflection from data-overaboundance and theory-void Genomics" to "Industrialization of Genomics". Let's get back to the solid biophysics-path laid down by Schroedinger, since the very sustainability of "Industrialization of Genomics" is at stake at its upswing as long as Genome Informatics is deadlocked by evidently mistaken paradigms. The road has been cleared at least by the overwhelmingly acknowledged "recursive genome function" in a peer-reviewed publication in 2008 June, and popularized by YouTube in 2008 October.
Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
Victory Day of Recursion over Junk DNA and Central Dogma COMBINED
In a mere two years since its publication in "The Principle of Recursive Genome Function" 2008 (presented in Google Tech YouTube 2008, the almost a full hour long presentation viewed 8,639 times) "Recursive Genome Function" clearly surpassed (with 238,000 Google hits) the "Junk DNA" and the "Central Dogma" obsolete paradigms COMBINED (together 234,000 Google hits). Half a Century of Genome Informatics retarded by two demonstrably false paradigms is finally OVER.
Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
Complete Genomics to Sequence 100 Genomes for National Cancer Institute Pediatric Cancer Study
Bradenton.com
Tuesday, Sep. 07, 2010
Complete Genomics Inc., a life sciences company focused on human genome sequencing, today announced a collaboration to identify and validate somatic mutations from 50 pediatric cancer cases from multiple research centers across the United States.
SAIC-Frederick, on behalf of the National Cancer Institute (NCI), will be using Complete Genomics’ sequencing, bioinformatics and scientific services to sequence and analyze 50 tumor-normal pairs. This analysis could enable researchers to identify patterns of tumorigenesis and ultimately lead to improved diagnosis and treatment of pediatric cancers.
SAIC-Frederick is the prime contractor for the NCI’s R&D facility in Frederick, Md. This project, which is being undertaken by Complete Genomics forms part of the NCI’s Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Initiative. TARGET seeks to use genomics technologies to rapidly identify valid therapeutic targets in childhood cancers so that new, more effective treatments can be developed. It is currently focusing on five childhood cancers: acute lymphoblastic leukemia, acute myeloid leukemia, neuroblastoma, osteosarcoma, and Wilms tumor.
Complete Genomics will seek to identify and validate mutations found in the pediatric tumor genomes. These could include somatic single nucleotide polymorphisms, insertion/deletions, copy number variations, and somatic variations. The sequenced data, as well as the assembled and validated data sets are expected to be submitted to the National Center for Biotechnology Information’s Sequence Read Archive database, as well as the TARGET Database.
Complete Genomics will be paid $1.1 million for completing this project, which is funded by the American Recovery and Reinvestment Act (ARRA) of 2009.
Upon success of this project, the contract contains an option for SAIC, on behalf of the NCI, to sequence more than 500 additional NCI cancer cases (more than 1,000 genomes) over an 18-month period with Complete Genomics.
[This very interesting news item signals a turmoil of the (private domain) "sequencing industry" to find the sustainable business model - such that the ecosystem does not crash because of a glut of unprocessed (not fully interpreted) DNA sequences. While formerly (see my quotation of Complete Genomics in my Google Tech YouTube, 2008) they promised not just sequencing but also a "Google-type Data Center" for Analytics. Later, CG declared itself (similar to PacBio) a "pure-play genome sequencing company" - with an uncertain market that is capable of taking up the raw sequences, threatening with a "Dreaded DNA Data Deluge". Price of a full DNA sequence was heralded to sink just under $5,000. Now, the new twist more than doubled the price to $11,000 per pop, to include some sorts of (certainly less than full) Analytics - with all the financial burden shouldered by the taxpayers (the government's National Cancer Institute) - also meaning that both the sequences and the partial analytics are "public domain" for the entire World. This appears to be a transitional business model that makes US taxpayers blindly finance the New Chapter of Genomics for the entire World, where the direction is governed by the Government's experts - who contributed to the over half a Century of setback that Genomics could not get rid of the obsolete axioms of "Junk DNA" and "Central Dogma". With the US government funds dwindling (ARRA is running out...) this business model is unlikely to be either fair to the US taxpayers or sustainable in the long run. From science viewpoint, cancer clearly seems to have to do with defective methylation in "recursive genome function" (Google hits today: 238,000). While this wide acceptance (that is within 10% of beating COMBINED hits of "Junk DNA" (132,000) plus "Central Dogma"!(128,000) signals an essentially completed paradigm-shift, it is still questionable how and when (not if) e.g. the NCI will embrace the new paradigm to accelerate (and make less expensive by competitive private sector...) those long-promised medical breakthroughs (that did not happen in the First Decade after the Human Genome Project) accomplished in the NEXT decade - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
Junk DNA can rise from the dead and haunt you [Comments]
By Boonsri Dickinson | Aug 20, 2010 |
[98.7% of her DNA don't look like "zombie genes" at all... - AJP]
Scientists have found that junk DNA can come back to life and can cause disease.
As it turns out, a region of the genome — that is hundreds of thousands of years old, mind you — can bring on trouble.
Soon after the zombie gene wakes up, people can no longer smile and their upper body muscles begin to waste away.
Those victims suffer from facioscapulohumeral muscular dystrophy (FSHD), one of the more common forms of the genetic disease.
1 in 20,000 people suffer from FSHD — what makes it different than diseases like diabetes is that inheriting the gene means the person will one day get the genetic disease.
While scientists knew genetics was to blame, they didn’t exactly know why and how it caused disease. Now they know, zombies are to blame.
The researchers published their results in Science.
There’s a certain rhythm to this madness. To cause disease, the gene needs to be repeated a number of times and has to have the right sequence. The trouble gene is found on chromosome 4 (which is a region scientists eyed for several decades).
If the zombie gene is repeated more than 10 times, the person will not develop FSHD. Researchers believe the surplus copies change the structure of the chromosome so the zombie gene can’t attack. Otherwise, the gene (DUX4) is allowed to be made and becomes toxic to the muscle cells.
This finding fundamentally changes how geneticists think about simple genetic diseases. It’s clear that even though FSHD was thought to be a simple disease because having the gene meant the person would definitely get the disease, it’s actually much more complex than that.
In the future, researchers could knock out this dead gene and develop new treatments.
Scientists believe they will discover that other diseases will have similar causes.
Geneticist Dr. Francis Collins told The New York Times, “the first law of the genome is that anything that can go wrong, will.”
Comments--
1
Pellionisz
08/20/10
The "Junk DNA" misnomer was put forward as a "theory" (though totally wrong, and suspect after its first utterance) by Susumu Ohno (1972), an otherwise serious scientist; see "So much 'Junk' DNA in our genome" (full text in my junkdna.com domain). He mistakenly argued that the non-genic sequences are in the genome "for the importance of doing nothing" (p. 367).
It was only later that this catastrophic misnomer became widely accepted at face value - as an excuse for the establishment to (BTW negligently) ignore 98.7% of (human) DNA - while millions if not hundreds of millions were (and still are) dying of "Junk DNA diseases".
"The Principle of Recursive Genome Function" (2008), by retiring both the "Junk DNA" and "Central Dogma" obsolete axioms became the first full genome (hologenome) theory based on sound genome informatics, sweeping away science-nonsense that retarded genomics for over half a Century (starting from Crick's notion in 1956, that he dared to call "Central Dogma", that information "never" recurses from either RNA or from
PROTEINS to DNA).
Upon conclusion of ENCODE (2007) Francis Collins was the one to issue a public call "the scientific community will have to re-think long-held beliefs". Some lucky few did not have to re-think as they never believed the two false axioms in the first place - but now we have (really, not the first...) experimental evidence as a de facto basis to discard wrong assumptions that were totally absurd from the viewpoint of genome informatics. 1.3% of human DNA (in fact, much less since "genes" may contain a big majority of non-coding introns) is simply not enough information to govern growth of as complex organisms as humans.
FractoGene (2002) clinched it in one year after it was established that the expected 140-300,000 "genes" were nowhere to be found by The Human Genome Project. Today, "recursive genome function" prevails with close to 200,000 hits in Google...
"Fractal defects" such as reported, with the recursion derailed and/or not supported with enough auxiliary information by sufficient number of recursion not only "have been expected", but theoretically predicted. - Pellionisz_at_JunkDNA.com
2
IMWeira
08/23/10
Dear Pellionisz; excellent post. I have not heard it put quite that way but some of us borderline science junkies have not accepted the junk dna designation nor could we understand why anyone would accept it.
I will mention your site to some of my friends and see you there.
3
JohnMcGrew@...
08/23/10
Interesting.
@Pellionisz, thanks for that info. Very interesting reading.
4
wizoddg
08/23/10
What Pellionisz said... Is far better put than I've heard before.
But it is a symptom of the way we do research on nearly everything--if it's not seen to be part of the current problem, we discard it...only later finding that it is causing other problems or preventing them.
Part of this in medicine is the practice of studying diseases (disorders) while ignoring the study of properly functioning systems.
We've spend many many decades studying disorders to find cause and cures--at the expense of ignoring the 'benign' organisms...many of which, once examined, turned out to be essential for our health--not merely not causing problems.
We finance medical research by popularity--rather than spending our time and energy where we as a society will get the most return for the effort, we routinely spend money based upon the ability to raise funding--filling the world with images of dying children and causing the public to mis-perceive the actual risk/benefit ratios.
Investing by emotion rather than analysis, while extremely human, is counter-productive.We end up spending money to treat 'horrific' problems, rather than the problems which kill or disable the most people.
The number one killer in the world today is heart disease and related circulatory issues--yet I routinely receive pleas for funding for many other conditions which affect far fewer people, and far too often those making the appeal believe that they are actually working to find a cure for something which is kills "the most."
Much unexpressed DNA is like that in the article--old ills piggyback ridding upon our genes.
Another large group are genes which are expressed only under certain circumstances
In the past couple decades we've learned that such gene expression can continue generations after the triggering circumstance has disappeared from the environment.
With the discovery of what crystallized DNA looks like decades ago, the public assumed that it meant we understood DNA. This has happened anew with each new advance.
The latest, the mapping of the genome is seen by the public as an end--that mapping means understanding.
In fact, each major step we make is merely the beginning of understanding--often forcing us to toss out our favorite theories of how things work.
In a world where understanding changes rapidly, it is every bit as valuable to be able to 'unlearn' and let go of previously loved theories as new data arises.
The one advantage that the scientific method has over the dogmatic methods of our more distant past, is the recognition that knowledge [better said, "understanding", since knowledge constantly advances, but understanding leaps with paradigm-shifts -AJP] is not static.
[It is a delight to see that the public is far ahead of some of the ossified parts of the establishment in understanding that Genetics-Genomics-HoloGenomics experiences far more profound "paradigm-shift" than previously imagined. We have to bring attention that by "What is Life?" Schroedinger questioned (1944) none of the "diseases" but the informatics-axioms of how Life is encoded (he predicted that covalent H-bindings of an aperiodical crystal encode life - later acknowledged by Crick the pioneering vision of Schroedinger, when Watson, Crick, Wilkinson and Franklin realized (1953) that the DNA crystal is aperiodical in the nucleotides, though is periodical (helical) in the physical arrangement of the aperiodical bases. Crick attempted to provide a further axiomatic basis of Life (not diseases...) by putting forward in 1956 (the unfortunately totally mistaken, and brazenly called "Central Dogma of Molecular Biology") that "information never recourses from Proteins to DNA". This wrong axiom (shored up by Ohno's "Junk DNA" second fatal axiom, 1972) set modern Genomics back by more than half a Century - which is relatively a short time comparing to the setback that the suppression of dismissal-attempt of "Geocentric" mistaken axiom inflicted upon our understanding of the surrounding universe. The Vatican admitted some 300 years after Giordano Bruno was torched to death alive and his ashes were thrown to the Tiberis, that actually his paradigm-shift was correct. No wonder that bringing a "lucid heresy on two counts"; dismissal of both mistaken axioms have proven to take such toll in the process of bringing it to the status of the presently prevailing leading paradigm. The blogger is "right on the money" that US Congress finances its Agencies based on "popularity" (meaning, votes) - and (mostly through NIH) e.g. The Human Genome Project deteriorated into a "gene discovery" - where the surprisingly few genes were (largely mistakenly) associated with particular diseases. Now, this horrendously expensive detour (yielding not much, if anything say the very leaders...) seems finally over. Mostly, not because a rigorous scientific rationale necessarily results in automatic victory (see Giordano Bruno...). Two non-scientific factors appear actually more important. One is (proven by this blog...) that the general public (who are not only voters, but actual taxpayers) realizes in massive droves that Agencies put on an auto-pilot of a mushrooming bureaucracy are heading into the void of a wrong direction, and thus look at some Agencies in a different way than before (and may cast their votes differently, how to spend their own hard-earned tax-dollars). Most important, however, it seems that postmodern Genomics is already deep into its "Industrialization" (i.e. a massive migration from government-led R&D to businesses of the Global Private Sector), where "popularity" drops into the important, but not so essential "marketing department" - while the primary drivers are the validated science, technology, performance, cost-efficacy, proper supply-chain management, etc., etc. The first segment where the transition from government R&D to Private Industry is practically complete is "Affordable Full Human DNA Sequencing". The dollar billions already invested into sequencing industry, however, will relentlessly drive postmodern Genomics away from "popularity of Sick-Care", into the direction of valid science-based predictive, participatory and personalized prevention; a new paradigm not only in Genomics, but genome-based Health Care. To maintain health, we must first understand how the healthy hologenome functions - and not in less than exact biological terms, but in terms of software-enabling algorithmic explanations, like "recursive genome function". Thus, sequencing industry will become a driver, since their only product (DNA sequences) are virtually worthless without interpreting their function by means of intrinsic algorithms, turned into potent software - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
Pacific Biosciences Denies Helicos' Infringement Claims
September 01, 2010
By a GenomeWeb staff reporter
NEW YORK (GenomeWeb News) – Pacific Biosciences today said that it believes the patent infringement claims brought against the company last week by Helicos Biosciences are without merit and that it intends to vigorously defend against the claims.
Helicos filed the suit Friday in the US District Court for the District of Delaware. It claims that Pacific Biosciences is infringing claims in four of its US Patents: Nos. 7,645,596; 7,037,687; 7,169,560; and 7,767,400.
Those patents cover Helicos' methods for sequencing a single strand of DNA by synthesizing a complementary strand of DNA using labeled nucleotide bases. This sequencing-by-synthesis method underlies Helicos' single-molecule sequencing platform.
"Helicos' patents are directed to methods used in their second generation 'flush and scan' system, and even at that, do not represent the earliest publication of those concepts," Hugh Martin, Pacific Biosciences' chairman and CEO, said in a statement. "Our third generation SMRT technology observes single molecules in real time, a fundamentally different approach."
Menlo Park, Calif.-based PacBio is gearing up for a commercial launch in early 2012 of its RS sequencing instrument. Among customers who have placed orders for the system are Baylor College of Medicine, the Broad Institute, Cold Spring Harbor Laboratory, the US Department of Energy Joint Genome Institute, The Genome Center at Washington University, Monsanto, the National Cancer Institute, the National Center for Genome Resources, the Ontario Institute for Cancer Research, Stanford University, and the Wellcome Trust Sanger Institute.
[Molecular Sequencing Industry is thriving - IPO-positioning, major M/A, IP lawsuits are all clear signs of an Industry coming alive. The question is not if, but when, who and (most importantly) "what is in it for me?" by everyone. One important reminder: NOTHING is in mere sequencing for anybody (except patent attorneys, but what else is new?) until and after the algorithmic understanding of "recursive genome function" will have been achieved, even partially, and software-enabling algorithms, now with the escalating "cloud solutions" are properly wrapped into the game - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
Will Fractals Revolutionize Physics, Biology and Other Sciences?
[Look at Romanesca also in The Principle of Recursive Genome Function - AJP]
A new discovery, reported in the latest Nature, hints at higher universal laws of the physical world, as well as new ways to approach and understand life in general. Even though the European discovery actually dealt with superconductors, it has an interesting twist with implications for the life sciences [predicted by FractoGene by Pellionisz, 2002 - AJP].
A group of physicists from London Centre for Nanotechnology at UCL and their collaborators at Sapienza University of Rome and European Synchrotron Radiation Facility in Grenoble, France were studying properties of so-called high-transition-temperature (high-Tc) copper oxide superconductors. They were looking at the microstructures that these superconductors form as they are cooled down. To the surprise of investigators, they discovered that microstructures, exhibited by oxygen atoms, seemed to organize into self-repeating fractals. Moreover, these fractal shapes, some extending almost to the millimeter scale, were correlating to superconductivity. In fact, larger fractals correlated with higher superconductivity temps.
What does it have to do with life? We think, plenty. Fractals, known for their geometric morphologies that are made up of patterns that repeat themselves at smaller scales infinitely, were first discovered by mathematician Benoit Mandelbrot in 1960s. Since then, they took the world of natural sciences by storm. As mathematicians and physicists discovered more and more interesting properties of these unique constructs, people started to notice fractals' ubiquitous presence in nature. Whether in the living world or in inorganic one, they seem to pop up in unexpected places. Somehow, there are laws of physics that favor these structures for whatever reason.
To us, the discovery of fractal function is eerily reminiscent of polarization in pre-quantum mechanical physics. Not until Niels Bohr, Albert Einstein and others laid the foundations of quantum mechanics, polarization of light has remained a mystery. Now we have a new puzzle to answer. Fractals are ubiquitous in the physical and living world for some unknown reason, and there is a function to them.
Paper in Nature: Scale-free structural organization of oxygen interstitials in La2CuO4+y
UCL press release: Fractals make better superconductors ...
More from Wired: Inexplicable Superconductor Fractals Hint at Higher Universal Laws...
Wired
Inexplicable Superconductor Fractals Hint at Higher Universal Laws
Wired
By Brandon Keim
August 11, 2010
What seemed to be flaws in the structure of a mystery metal may have given physicists a glimpse into as-yet-undiscovered laws of the universe.
The qualities of a high-temperature superconductor — a compound in which electrons obey the spooky laws of quantum physics, and flow in perfect synchrony, without friction — appear linked to the fractal arrangements of seemingly random oxygen atoms.
...
“Everyone was looking at these materials as ordered and homogeneous,” said Bianconi. That is not the case — but neither, he found, was the position of oxygen atoms truly random. Instead, they assumed complex geometries, possessing a fractal form: A small part of the pattern resembles a larger part, which in turn resembles a larger part, and so on.
“Such fractals are ubiquitous elsewhere in nature,” wrote Leiden University theoretical physicist Jan Zaanen in an accompanying commentary, but “it comes as a complete surprise that crystal defects can accomplish this feat.”
If what Zaanen described as “surprisingly beautiful” patterns were all Bianconi found, the results would have been striking enough. But they appear to have a function.
...
However, while the arrangement of oxygen atoms appears to influence the quantum behaviors of electrons, neither Bianconi nor Zaanen have any idea how that could be. That fractal arrangements are seen in so many other systems — from leaf patterns to stock market fluctuations to the frequency of earthquakes — suggests some sort of common underlying laws, but these remain speculative.
According to Zaanen, the closest mathematical description of superconductive behavior comes from something called “Anti de Sitter space / Conformal Field Theory correspondence,” a subset of string theory that attempts to describe the physics of black holes.
That’s a dramatic connection. But as Zaanen wrote, “This fractal defect structure is astonishing, and there is nothing in the textbooks even hinting at an explanation.”
[FractoGene (Pellionisz, 2002) attributes efficacy to the fractal coding of organelles, organs and organisms by means of fractal DNA. The "frighteningly unsophisticated" (quoting Venter) "Genes and Junk" primitive notion of genome function would have you believe the idiocy that the exon-fractions of 1.3% of the non-Junk DNA (information of a stamp-sized digital picture...) would suffice to generate e.g. a human body and brain. The second decade of Genome Revolution (now with Fractal Revolution...) is to rectify that historical insult. - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
Reanimated ‘Junk’ DNA Is Found to Cause Disease
New York Times
By GINA KOLATA
August 19, 2010
The human genome is riddled with dead genes, fossils of a sort, dating back hundreds of thousands of years — the genome’s equivalent of an attic full of broken and useless junk.Some of those genes, surprised geneticists reported Thursday, can rise from the dead like zombies, waking up to cause one of the most common forms of muscular dystrophy. This is the first time, geneticists say, that they have seen a dead gene come back to life and cause a disease.
“If we were thinking of a collection of the genome’s greatest hits, this would go on the list,” said Dr. Francis Collins, a human geneticist and director of the National Institutes of Health.
The disease, facioscapulohumeral muscular dystrophy, known as FSHD, is one of the most common forms of muscular dystrophy. It was known to be inherited in a simple pattern. But before this paper, published online Thursday in Science by a group of researchers, its cause was poorly understood.
The culprit gene is part of what has been called junk DNA, regions whose function, if any, is largely unknown. In this case, the dead genes had seemed permanently disabled. But, said Dr. Collins, “the first law of the genome is that anything that can go wrong, will.” David Housman, a geneticist at M.I.T., said scientists will now be looking for other diseases with similar causes, and they expect to find them.
“As soon as you understand something that was staring you in the face and leaving you clueless, the first thing you ask is, ‘Where else is this happening?’ ” Dr. Housman said.
But, he added, in a way FSHD was the easy case — it is a disease that affects every single person who inherits the genetic defect. Other diseases are more subtle, affecting some people more than others, causing a range of symptoms. The trick, he said, is to be “astute enough to pick out the patterns that connect you to the DNA.”
FSHD affects about 1 in 20,000 people, causing a progressive weakening of muscles in the upper arms, around the shoulder blades and in the face — people who have the disease cannot smile. It is a dominant genetic disease. If a parent has the gene mutation that causes it, each child has a 50 percent chance of getting it too. And anyone who inherits the gene is absolutely certain to get the disease.
About two decades ago, geneticists zeroed in on the region of the genome that seemed to be the culprit: the tip of the longer arm of chromosome 4, which was made up of a long chain of repeated copies of a dead gene. The dead gene was also repeated on chromosome 10, but that area of repeats seemed innocuous, unrelated to the disease. Only chromosome 4 was a problem.
“It was a repeated element,” said Dr. Kenneth Fischbeck, chief of the neurogenetics branch at the National Institute of Neurological Disorders and Stroke. “An ancient gene stuck on the tip of chromosome 4. It was a dead gene; there was no evidence that it was expressed.”
And the more they looked at that region of chromosome 4, the more puzzling it was. No one whose dead gene was repeated more than 10 times ever got FSHD. But only some people with fewer than 10 copies got the disease.
A group of researchers in the Netherlands and the United States had a meeting about five years ago to try to figure it out, and began collaborating. “We kept meeting here, year after year,” said Dr. Stephen J. Tapscott, a neurology professor at the University of Washington.
As they studied the repeated, but dead, gene, Dr. Tapscott and his colleagues realized that it was not completely inactive. It is always transcribed — copied by the cell as a first step to making a protein. But the transcriptions were faulty, disintegrating right away. They were missing a crucial section, called a poly (A) sequence, needed to stabilize them.
When the dead gene had this sequence, it came back to life. “It’s an if and only if,” Dr. Housman said. “You have to have 10 copies or fewer. And you have to have poly (A). Either one is not enough.”
But why would people be protected if they have more than 10 copies of the dead gene? Researchers say that those extra copies change the chromosome’s structure, shutting off the whole region so it cannot be used.
Why the reactivated gene affects only muscles of the face, shoulders and arms remains a mystery. The only clue is that the gene is similar to ones that are important in development.
In the meantime, says Dr. Housman, who was not involved in the research but is chairman of the scientific advisory board of the FSHD Society, an advocacy group led by patients, the work reveals a way to search for treatments.
“It has made it clear what the target is,” he said. “Turning off that dead gene. I am certain you can hit it.”
The bigger lesson, Dr. Collins said, is that diseases can arise in very complicated ways. Scientists used to think the genetic basis for medical disorders, like dominantly inherited diseases, would be straightforward. Only complex diseases, like diabetes, would have complex genetic origins.
“Well, my gosh,” Dr. Collins said. “Here’s a simple disease with an incredibly elaborate mechanism.”
“To come up with this sort of mechanism for a disease to arise — I don’t think we expected that,” Dr. Collins said.
[Susumu Ohno (1972), an otherwise serious scientist, put forward his (totally wrong) theory, see in junkdna.com full text free, that the non-genes are in the human genome "for the importance of doing nothing". It was only later that this catastrophic misnomer became widely accepted at face value - as an excuse such that the establishment could feel free to ignore 98.7% of (human) DNA - while millions if not hundreds of millions were (and still are) dying of "Junk DNA diseases". "The Principle of Recursive Genome Function" (2008), by retiring both the "Junk DNA" and "Central Dogma" obsolete axioms became the first full genome (hologenome) theory based on sound genome informatics, sweeping away science nonsense that retarded genomics for over half a Century (starting from Crick's notion in 1956, that he dared to call "Central Dogma" that information "never" recurses from either RNA or from PROTEINS to DNA). Upon conclusion of ENCODE (2007) Francis Collins was the one to issue a public call "the scientific community will have to re-think long-held beliefs". Some lucky few did not have to re-think as they never believed the two false axioms in the first place - but now we have (really, not the first...) factual evidence to discard wrong assumptions that were totally absurd from the viewpoint of genome informatics. 1.3% of human DNA (in fact, much less since most of the "genes" are non-coding introns) is simply not enough information to govern growth of as complex organisms as humans. FractoGene (2002) clinched it in one year after it was established that the expected 140-300 thousand "genes" were nowhere to be found by The Human Genome Project. Today, "recursive genome function" prevails with close to 200,000 hits in Google.... - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
Life Technologies inks $725M deal for Ion Torrent
August 18, 2010 — 11:23am ET | By John Carroll
FierceBiotech
Arming itself for a looming showdown with Illumina over the booming market for second-generation gene sequencing technologies, Life Technologies struck a deal to buy Ion Torrent for $375 million in cash and stock with $350 million more on the line based on a series of milestones.
The deal gives Life Technologies a shot at introducing a gene sequencing device later this year that will be sold for less than $100,000, according to the San Diego Union-Tribune. A variety of companies have been angling for the fast track in the race to market new, faster and far cheaper sequencing technologies.
"We believe Ion Torrent's technology will represent a profound change for the life sciences industry," said Gregory Lucier, chairman and chief executive of Life Technologies. "This technology will usher in a new era in science, one in which DNA sequencing can be done easier, faster and more cost effectively than ever before."
- check out the San Diego Union-Tribune story [below]
- here's the Life Technologies release [below]
SingOn San Diego
Life Technologies of Carlsbad said Tuesday it will acquire Ion Torrent, a Guilford, Conn., company that has developed a new way of sequencing genes, in a deal worth as much as $725 million.
The move is Life Technologies’ latest effort to boost its position in the increasingly competitive and potentially lucrative genomic sequencing technology business.
It also intensifies the rivalry between Life Technologies and Illumina, another San Diego genetic sequencing technology company, said Daniel MacArthur, a genetic researcher at the Wellcome Trust Sanger Institute in Cambridge, England.
“Life Technologies already owns a second-generation sequencing platform [SOLiD - AJP], but has been struggling to compete against the current market-dominating technology from Illumina [with their Genome Analyzer - AJP],” MacArthur wrote Tuesday on his blog, Genetic Future.
Life Technologies is paying $375 million in cash and stock for Ion Torrent, a privately held company created in August 2007 by high-speed DNA sequencing developer Jonathan Rothberg. The sellers will receive up to $350 million in additional cash and stock if certain milestones are reached by 2012.
“We believe Ion Torrent’s technology will represent a profound change for the life sciences industry,” said Gregory T. Lucier, chairman and chief executive of Life Technologies. “This technology will usher in a new era in science, one in which DNA sequencing can be done easier, faster and more cost effectively than ever before.”
Standard DNA sequencing devices use a chemical process to attach fluorescent tags to individual pieces of DNA, which are then illuminated by lasers and photographed with a high-tech camera. Super computers interpret the light signals and convert them into usable genetic data. The process is time consuming and costly.
With the technology developed by Ion Torrent, tiny pH meters measure the change in acidity that occurs in a solution when DNA base pairs are formed. Those pH changes are then translated into the alphabet code that identifies genetic strands.
Life Technologies will launch the Personal Genome Machine, the first commercial sequencing device to use Ion Torrent’s process, later this year at a cost of less than $100,000, the San Diego company said. [Life Technologies, with its SOLiD, may not be known as best in "on rig software" - thus, this business move opened the "Big Four" (PacBio, Complete Genomics, Oxford Nanopore and Ion Torrent) to the vulnerability of software, especially algorithmic IP, as the critical factor for users - AJP]
Life Technologies announced the purchase after stock markets closed Tuesday.
In after-hours trading, the company’s shares were up 36 cents, or nearly 1 percent, to $45.31.
[Business Wire - Company Release]
CARLSBAD, Calif. & GUILFORD, Conn., Aug 17, 2010 (BUSINESS WIRE) -- --Complements Existing Sequencing Solutions Portfolio
Life Technologies Corporation, a provider of innovative life science solutions, today announced a definitive agreement to acquire Ion Torrent for $375 million in cash and stock.
The sellers are entitled to additional consideration of $350 million in cash and stock upon the achievement of certain technical and time-based milestones through 2012. Life Technologies' Board of Directors has approved an additional share repurchase program in order to repurchase its shares associated with the stock portion of the consideration. The impact on total share count is expected to be neutral.
Formed by life sciences pioneer Dr. Jonathan Rothberg, founder of CuraGen, 454 Life Sciences and co-founder of Raindance Technologies, Ion Torrent has revolutionized DNA sequencing by enabling a direct connection between chemical and digital information through the use of proven semiconductor technology. Ion Torrent's proprietary chip-based sequencing represents a new paradigm in DNA sequencing by using PostLight(TM) sequencing technology, the first of its kind to eliminate the cost and complexity associated with the extended optical detection currently used in all other sequencing platforms.
The first product using this technology will be the Personal Genome Machine (PGM), an easy-to-use, highly-accurate benchtop instrument optimal for mid-scale sequencing projects, such as targeted and microbial sequencing. The instrument is currently available through an early access program and will be launched later this year at an entry cost of less than $100,000. Subsequent products will benefit from cutting edge semiconductor fabrication technologies that can expand throughput at an accelerated pace, thereby dramatically lowering the cost to sequence a genome.
Gregory T. Lucier, Chairman and Chief Executive Officer of Life Technologies, said, "We believe Ion Torrent's technology will represent a profound change for the life sciences industry, as fundamental as the one we saw with the introduction of qPCR. This technology will usher in a new era in science, one in which DNA sequencing can be done easier, faster and more cost effectively than ever before.
"By leveraging the cumulative $1 trillion already invested in semiconductor research and development, we believe that Ion Torrent will drive unprecedented scalability, delivering the solution required for future generations of sequencing," Lucier continued. "With a heritage of more than 25 years as a leader in sequencing, Life Technologies is perfectly suited to bring such an innovative technological breakthrough to market."
Mark Stevenson, Life Technologies' President and Chief Operating Officer, said, "This transaction enhances our strategy of providing a complete sequencing offering to our customers across the research and applied markets. Ion Torrent's technologies are highly complementary to our existing portfolio of sequencing CE and SOLiD platforms."
Dr. Rothberg said, "The entire Ion Torrent team is excited to be joining the talented people at Life Technologies. Our products and mission make this an ideal and logical strategic fit for both companies. Both Ion Torrent and Life Technologies share rich cultures of innovation and excellence, and I firmly believe that Life Technologies is the right partner to bring such revolutionary technology in the sequencing arena to market."
Dr. Rothberg will continue to lead Ion Torrent with the support of the Ion Torrent leadership team. Life Technologies intends to retain Ion Torrent's presence in Guilford, CT and South San Francisco, CA where it has established R&D centers of excellence.
Life Technologies will finance the transaction with cash on hand, available lines of credit, and stock. Including the impact of specific cost saving initiatives, the transaction is expected to be 2 cents dilutive to Life Technologies' earnings per share in 2010, neutral in 2011, and accretive in 2012 and beyond. Earnings per share guidance for 2010 remains unchanged at $3.35 to $3.50. Life Technologies expects to deliver double-digit earnings-per-share growth in 2011 including the impact of this transaction. Upon closing, Life Technologies expects to benefit from synergies created by combining Ion Torrent's proprietary technologies, product pipeline and R&D capabilities with Life Technologies' commercial channel, sample preparation, sequencing automation, informatics, and reagent expertise.
Life Technologies remains committed to a strategy of balanced capital deployment, including the execution of the previously announced $350 million share repurchase. In addition, Life Technologies reaffirms its goal of reaching 10% ROIC by 2012.
The transaction, which is expected to close in the fourth quarter, is subject to customary closing conditions, including regulatory approval.
About Life Technologies
Life Technologies is a global biotechnology tools company dedicated to improving the human condition. Our systems, consumables and services enable researchers to accelerate scientific exploration, driving to discoveries and developments that make life even better. Life Technologies customers do their work across the biological spectrum, working to advance personalized medicine, regenerative science, molecular diagnostics, agricultural and environmental research, and 21st century forensics. Life Technologies had sales of $3.3 billion in 2009, employs approximately 9,000 people, has a presence in approximately 160 countries, and possesses a rapidly growing intellectual property estate of approximately 3,900 patents and exclusive licenses. Life Technologies was created by the combination of Invitrogen Corporation and Applied Biosystems Inc., and manufactures both in-vitro diagnostic products and research use only-labeled products. For more information on how we are making a difference, please visit our website: http://www.lifetechnologies.com.
About Ion Torrent
Ion Torrent has developed a DNA sequencing system that directly translates chemical signals (A, C, G, T) into digital information (0, 1) on a semiconductor chip. The result is a sequencing system that is simpler, faster, less expensive and more scalable than any other technology available. Because Ion Torrent produces its proprietary semiconductor chips in standard CMOS factories, it leverages the $1 trillion investment that has been made in the semiconductor industry. Ion Torrent uniquely and directly benefits from four decades of exponential improvement in semiconductor technology, expressed as Moore's Law. Ion Torrent will launch the Ion Personal Genome Machine sequencer in 2010. Ion Torrent was founded in August 2007 by Dr. Jonathan M. Rothberg, who pioneered high-speed, massively parallel DNA sequencing. Ion Torrent is based in Guilford, Connecticut, with an office in South San Francisco. For more information about Ion Torrent, visit www.iontorrent.com.
[Molecular DNA sequencing is at full swing with the Life Technologies' deal with Ion Torrents (grand total $725 M). Illumina invested into Oxford Nanopore, and both Complete Genomics and Pacific Biosciences filed for IPO. Quite a foursome! The net result is that sequencing technology is in a "home run" - thus the emphasis shifted to Intellectual Property in Full DNA Analytics and Consumerism of the results (a HolGenTech profile). An interesting question is why Jonathan Rothberg "gave away" his company Ion Torrent for under a $ Billion? An answer may be "bis dat qui cito dat" - Jonathan's R&D is to be kept both in CT and in CA (San Francisco) ... instead of going through an agonizing public scrutiny of IPO (e.g. full disclosure of all their "risk factors", such as IP) he can plunge into his third major venture (actually his sixth, after 454 sold to Roche, and Ion Torrent sold to Life Technologies, and also including CuraGen, Clarifi and Raindance). Brilliant technologies, brilliant business moves ... - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
PacBio files for $200 million IPO
FierceBiotech
August 16, 2010 — 10:39am ET | By Maureen Martino
Money-raising machine Pacific Biosciences--a 2009 Fierce 15 winner--has decided to take its act public. The company has filed a $200 million IPO, the proceeds of which will help the company fund R&D of its products and SMRT technology, which uses nanofabrication, biochemistry, molecular biology, surface chemistry and optics to enable real-time analysis of biomolecules.
Just last month, PacBio closed a $109 million Series F, bringing its total haul to $370 million, and in June landed a PacBio gets $50 million investment from Gen-Probe. In addition to R&D expenses, PacBio will boost its sales and marketing in advance of commercial launch, increase its manufacturing operations, and for general corporate purposes. PacBio added in its filing that it may be in the market to acquire complementary technology or businesses that would boost its own operations, but that no acquisitions were planned at this time.
In the short term, PacBio will focus its technology on clinical, basic and agricultural research. It hopes to expand into molecular diagnostics, drug discovery and development, food safety, forensics, biosecurity and bio-fuels. "We believe that our SMRT platform represents a new paradigm in biological science...that has the potential to significantly impact a number of areas critical to humankind, including the diagnosis and treatment of disease as well as efforts to improve the world's food and energy supply," the company boasts in its SEC filing.
----
PacBio's SEC filing stipulates (verbatim quote):
RISK FACTORS
Investing in our common stock involves a high degree of risk. You should consider carefully the risks and uncertainties described below, together with all of the other information in this prospectus, including our financial statements and related notes, before deciding whether to purchase shares of our common stock. If any of the following risks is realized, our business, financial condition, results of operations and prospects could be materially and adversely affected. In that event, the price of our common stock could decline, and you could lose part or all of your investment.
Risks Related to Our Business
We are a development stage company with limited operating history.
We may never achieve commercial success and have not yet commercially launched our first product. We have no historical financial data upon which we may base our projected revenue. We have limited historical financial data upon which we may base our planned operating expense or upon which you may evaluate us and our prospects. Based on our limited experience in developing and marketing new products, we may not be able to effectively:
• drive adoption of our products;
• attract and retain customers for our products;
• comply with evolving regulatory requirements applicable to our products;
• anticipate and adapt to changes in our market;
• focus our research and development efforts in areas that generate returns on these efforts;
• maintain and develop strategic relationships with vendors and manufacturers to acquire necessary materials for the production of our products;
• implement an effective marketing strategy to promote awareness of our products;
• scale our manufacturing activities to meet potential demand at a reasonable cost;
• avoid infringement and misappropriation of third-party intellectual property;
• obtain licenses on commercially reasonable terms to third-party intellectual property;
• obtain valid and enforceable patents that give us a competitive advantage;
• protect our proprietary technology;
• provide appropriate levels of customer training and support for our products;
• protect our products from any equipment or software-related system failures; and
• attract, retain and motivate qualified personnel.
In addition, a high percentage of our expenses is and will continue to be fixed. Accordingly, if we do not generate revenue as and when anticipated, our losses may be greater than expected and our operating results will suffer. You should consider the risks and difficulties frequently encountered by companies like ours in new and rapidly evolving markets when making a decision to invest in our common stock.
[About two weeks after Complete Genomics filed for IPO, almost overnight challenged by Illumina intellectual property infringement lawsuit, PacBio decided to deny the uniqueness of Complete Genomics to capture public funds. This move will no doubt re-vamp the competitive landscape - perhaps most critically in intellectual property matters - Pellionisz_at_JunkDNA.com or Andras Pellionisz at FaceBook]
How Can the US Lead Industrialization of Global Genomics? [AJP]
[Francis Collins, Head of NIH, USA (left) and BGI co-founder Wang Jian (right) - AJP]
There is no question that a Global Industrialization of Genomics is taking place - in which the USA is hard pressed to (maintain to) lead with its somewhat antiquated and fragmented R&D system. As we recall, the shock of Soviet Satellite "Sputnik" (1957 - over half a Century ago...) triggered a successfull re-vamping of the entire US education and R&D system. Hruschev' Soviet Union was provocative and arrogant - while (as the brilliant write-up by Kevin Davis, shows below) - China deliberately underplays their cards. Nonetheless, a somewhat similar re-adjustment at every half a Century might be needed if the US is to maintain her lead - this time in the Global Industrialization of Genomics. I illustrate this thesis by a contrasting triad of write-ups . One is from Nature on NIH, the other is in Bio-IT World, and the third is my conclusion that "Industrialization of Genomics is not possible either by the brute force of government administration of orthodox Biochemistry Research or massive deployment of the shere force of Big Information Technology (their converge I predicted since 2004, and disseminated in YouTube 2008 - by now viewed over 8,500 times) - without a theoretical understanding of recursive genome function" - Pellionisz_at_JunkDNA.com or Andras Pellionisz on FaceBook.
Francis Collins: One year at the helm [US government over the cliff in Genomics - AJP]
Nature 466, 808-810 (2010) | doi:10.1038/466808a
Published online 11 August 2010 |
Meredith Wadman
Having taken on the biggest job in biomedicine - leading the US National Institutes of Health - Francis Collins must now help his agency over a funding cliff. Meredith Wadman looks at his record so far, and his plans to cushion the fall.
There were three scans of Francis Collins's genome, and all showed the same thing: the geneticist and physician has an increased risk of developing type 2 diabetes. After Collins received the results from the genetic-testing companies in the spring of 2009, shortly before he became director of the US National Institutes of Health (NIH), he hired a personal trainer and began working out three times a week. He jettisoned his favourite junk food - honey buns and oversized muffins - in exchange for yoghurt, granola bars and broccoli. The 60-year-old now dead lifts 48 kilograms, chest presses 43, and has lost more than 11 kilograms himself. [So much for some bureaucrats who consider DTC "useless"; if it did change the lifestyle of one of the most knowledgeable man, perhaps its relatively small impact is because others are not yet at his level - AJP] "It has helped me a lot in terms of being able to take on the intensity of the job," he says.
That salubrious slimming is nothing compared with the crash diet that Collins's US$31-billion-a-year agency is about to go on. Collins took control of the NIH - the world's largest biomedical-research funder - in the middle of a feast: a $10.4-billion, two-year boon delivered in 2009 by the American Recovery and Reinvestment Act, as part of the US government's effort to revive a moribund economy. Next month, the last of that money will go out of the door, and its recipients will have spent the bulk of it by September 2011. "The Recovery Act provided an enormously timely and appropriate stimulus for the community after five years of flat funding," Collins said in an interview with Nature at the NIH's Bethesda, Maryland, campus last month. "But now we face this potential of falling off a cliff. That's the biggest challenge" of his job, he says.
Collins comes equipped for challenges, intellectually and temperamentally. From his co-discovery of the gene for cystic fibrosis 21 years ago, to his 15 years of leadership of the NIH'sNational Human Genome Research Institute - and, with it, the Human Genome Project - he has proved that he combines serious scientific know-how with a leader's vision (see 'Francis Collins: in sequence'). With his boy-scout manners and folk-guitar habit, he is also a decided contrast to his immediate predecessor, the sharp-suited Elias Zerhouni, a radiologist whom many bench investigators viewed warily for not being a scientist's scientist.
Collins's exceptional self-discipline extends well beyond dieting. By the time he started the job, he had already formulated a 'pocket list' of 22 goals for his first year in office, from hosting a visit to the NIH by President Barack Obama to hiring a new cancer-institute director. Now, he proudly hands over the list of mostly ticked-off accomplishments: Obama visited the NIH last September, and Harold Varmus, a former NIH director, took the reins of the National Cancer Institute in July. "He's in a hurry," says Susan Shurin, the acting director of the NIH's National Heart, Lung and Blood Institute (NHLBI). "He moves fast and he likes to be surrounded by people who are going to make things happen."
Collins has detractors as well as fans. When he was appointed, some scientists voiced loud scepticism that he could separate his very public Christian faith from his policy decisions. There were also fears that his roots heading the Human Genome Project would lead him to favour NIH-initiated mega-projects over proposals by individual scientists. Others scolded him - and still do - for what they call his perennial overpromising on the fruits of the genomic revolution. "He is still leading people to believe that genetics is the key to everything," says Neil Greenspan, an immunologist at the Case Western Reserve University School of Medicine in Cleveland, Ohio. If, five or ten years from now, only a handful of therapies emerge as a direct result of the genome project, "you could end up with a lot of people [in Congress] getting upset and cutting the NIH because they are not producing what they claimed".
Such concerns do not worry a lean, list-checking Collins. "My job it seems to me is not to spend my time apologizing for being optimistic. But rather to try to take that optimism and turn it into reality," he says.
Morning to night
On a sultry morning in mid-July, Collins straps on his black motorcycle helmet and rides his Harley-Davidson the 15 minutes from his suburban Maryland home to the NIH campus. Collins had grabbed his usual, abbreviated night of sleep, after recording an interview for the Charlie Rose Show, marking the tenth anniversary of the draft sequencing of the human genome, and then staying up until nearly midnight to watch the popular talk-show air. In between, he had participated in a conference call with senior government officials, discussing how to enrol 20,000 subjects in a long-term study of the health effects on workers cleaning up the Gulf of Mexico oil spill. Having risen at his usual time of 5:00 a.m. - "that is a protected time, before all hell breaks loose, when I can actually try to think and plan," he says he is now on his way to a 7:45 a.m. interview with a candidate to head the NHLBI.
Collins wasted no time on his first day as NIH director either, when he announced five 'themes' - areas of what he calls "exceptional opportunity" - that would receive special priority during his tenure (see Nature 460, 939; 2009). Collins targeted translational medicine, health-care reform, global health and "empowering and energizing the research community". And he said he wanted to apply high-throughput technologies including genomics and proteomics to answer, as he puts it, questions with 'all' in them, such as "what are all of the major pathways for signal transduction in the cell?"
He also had to deal with some of the issues left over from Zerhouni's watch. He was faced with the delicate job of making new human embryonic stem-cell lines available for federal funding fast enough to suit a community that was hankering for them after eight years of drought - without any missteps that would provide ammunition to opponents of the research. Between December and June, the agency approved 75 new stem-cell lines. (Collins points to the approvals as evidence that he "will not allow my own personal spiritual beliefs to interfere with decision-making or priority setting".) But the agency has also drawn criticism for rejecting scores of disease-specific cell lines because of the broad legal language used in patient-consent forms (see Nature 465, 852; 2010).
Collins also faced the aftermath of several scandals in which NIH-supported academics had flouted reporting rules by failing to disclose five- and six-figure sums that they had collected from drug companies. In May, the NIH published proposed changes that would tighten the rules governing financial-interest reporting by its grantees.
Still, nothing Collins has faced so far comes close to the budget straits that the agency now confronts as the government struggles to control ballooning deficits, fight two wars and deal with the detritus of a major economic crisis. As NIH director, "what happens to you is going to depend on things beyond your control", says Anthony Fauci, director of the National Institute of Allergy and Infectious Disease since 1984. "I hope that circumstances beyond his control start leaning towards helping him rather than hindering him."
Slim chances
Already, this year, success rates for scientists applying for the agency's research-project grants have dipped to an estimated 19%, down from 21% in 2009 and far lower than the comfortable 32% of a decade earlier (see 'Grant applications to the NIH'). The worsened odds partly reflect an increase of about 10% in the number of applications, many of which are recycled from failed stimulus grant proposals. In 2011 and 2012, the grant success rates are expected to fall further as stimulus funding runs out and its recipients attempt to extend support for their projects.
The NIH's baseline budget is also approaching dangerous waters. Although agency supporters were heartened last month when key subcommittees of the Senate and House of Representatives approved Obama's request for a 3.2%, $1-billion boost that would bring the budget to $32 billion in 2011, the increase is not guaranteed to survive final congressional wrangling this autumn or winter. And it does no more than match the government's predicted biomedical inflation rate. Things could be even bleaker in 2012: this June, Collins, like every other federal agency director, was asked by the White House's Office of Management and Budget, as part of its planning process for the 2012 US budget, to identify cuttable programmes amounting to 5% of the agency's budget. This is hardly a calamity compared with the deep research cuts occurring in some European countries, but still a shock to the NIH, which has faced only one absolute funding cut since 1970, and that only a 0.1% shave (see 'NIH budget'). Late last month, Collins collected from the directors of the NIH's 27 institutes and centres a list of targeted programmes, constituting 7% of their budgets - the 7% giving him some flexibility to cut less here and more there. The final list is due to the White House in mid-September.
The initial response of the institute directors to his request was "full of angst", says Collins. "But there has also been a sense of 'We need to look hard at everything we are doing at a time like this'." He remains hopeful that given Obama's emphasis on science, "when the dust all settles and they [the White House] decide exactly what to do, we will be at some level a bit protected, but we don't know that".
All or none
All this has been a growing cloud on the horizon even as Collins has been fleshing out his five themes. He has emphasized translational research, throwing his weight behind a programme aimed at speeding treatments for rare and neglected diseases towards human trials. He has embraced health reforms by overseeing the spending of $400 million in Recovery Act money earmarked for research into the 'comparative effectiveness' of medical treatments. And he has promoted his global health priority with initiatives such as a collaboration involving Britain's Wellcome Trust medical charity, in which the NIH will contribute $25 million over five years to study the genetic and environmental underpinnings of chronic diseases in sub-Saharan Africa.
Collins has also been launching high-tech assaults on the 'all' questions, committing $175 million in Recovery Act money to accelerate The Cancer Genome Atlas - a five-year-old effort to develop a detailed catalogue of all of the mutations associated with 20 common cancers. [Results of these programs will, or course, be available for the World, for free - AJP]. Collins's emphasis on these types of ambitious projects has led some to question his commitment to the individual investigator and the mainstay, multi-year 'R01' grants that fund many such scientists. But his defenders say there is no evidence that Collins is advancing the first at the expense of the second. "Francis fully gets the importance of funding some of the larger efforts that can be so transforming. But I think he's also paying very close attention to maintaining a vigorous pipeline of R01-funded research," says Levi Garraway, a cancer biologist at Harvard Medical School and Dana-Farber Cancer Institute in Boston, Massachusetts, who holds investigator-initiated NIH grants and also participates in The Cancer Genome Atlas project.
Collins says that big-team science is the only way to produce some tools that greatly benefit individual investigators. [Craig Venter, who single-handed matched at least to a tie the $3 Bn "Human Genome Project" is likely to question the rationale of this statement - AJP]. But he says that the individual lab "is where almost all of the discoveries of the present and the future are going to come from". [It is interesting that Dr. Collins uses the term "individual lab" as the source of advancement of science. Albert Einstein, who never ran any lab of physics, might question the rationale of this statement, since advancements of science have come in the past from "individual brain" of Newton, Heisenberg, Planck, Schrodinger, Einstein, etc - AJP], And these labs are at the centre of his push to "energize and empower" the research community by addressing peer review, training and other workforce issues. Anaemic success rates for research-project grant applicants have created "a terribly stressful circumstance, particularly for early-stage investigators", says Collins, noting that the average age for winning a first R01 award has now crept above 42 years old. As a partial response to this, he has been planning the launch in 2011 of an award that will allow promising young investigators to skip postdoc positions entirely, giving them five-year funding to launch independent labs.
As for the immediate concerns of thousands of NIH grantees edging towards the funding cliff, Collins says that the agency will be "sympathetic" in allowing Recovery Act-funded grantees to spend their money over more than two years, "making it more of a ramp instead of a cliff". [Does it matter if US leadership slides or falls into demise? - AJP] "We will be doing other things which may assist the ability to give new grants, but hurt the people who already have them," he adds. Those will include cutting individual grant budgets "as we have to, in order to keep as many researchers going as possible".
These measures bring cold comfort for many in postdoc purgatory with little prospect of securing independent funding. "I didn't think it would be some Glory Hallelujah moment when Collins was appointed," says one 35-year-old scientist in his second postdoc, who asked to remain anonymous. He would like Collins to make it possible for those more than five years beyond their PhDs to secure transition funding such as a coveted 'K99' award, which supports postdocs in the shift to independent positions. "To be brutally honest, I haven't noticed any difference in his tenure after the first year compared to Zerhouni," he says.
But if Collins hasn't impressed some struggling bench scientists, his skill as a public communicator may nonetheless help to improve the NIH's prospects — or at least lessen its immediate peril. William Talman, president of the Federation of American Societies for Experimental Biology, attributes the White House's request for a $1-billion boost for the NIH - even in a stark funding climate - to Collins's persuasive powers. "He has been a superb advocate for the NIH with the administration and with Congress." Collins has the rare gift of being able to translate complex concepts into simple language, leaving his audiences - including all-important congressional audiences - feeling brilliant about their grasp of his material. (In one typical analogy he describes a haplotype, a group of genetic markers that are inherited together, as being like a neighbourhood of houses that moves together - with a causative mutation residing at one street address.)
"The most important thing he has done really is his public outreach," says Shurin, who recalls as typical Collins's May guitar performance for patient advocacy groups affiliated with her institute. Set to the tune of Del Shannon's hitRunaway, his lyrics described the anxieties raised by confronting a readout of one's own genome "I'm a walking through the genes/Don't know what all this means/Oh what can the meaning be?/Behind that G and T?/And I wonder …" He received a standing ovation. [Others worked their butts off to focus not on a song but on a breakthrough theory.. - AJP]
Collins is going to need all of that support and more to help those funded by the agency over the cliff - or down the ramp - ahead. "I don't have any magic here," says Collins. "I wish I did." [For believers in God, there is always a hope for a miracle ...]
[NIH got $40 Bn "for a song" - as in 2007 when DECODE was wrapped up - Genomics confessed in science papers - as well as by public whining - "Don't know what it all means". We simply can't make it without "theory of genome function" - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
BGI Americas [and BGI Europe] Offers Sequencing the Chinese Way
By Kevin Davies
Bio-IT World
August 11, 2010
25 years ago, Shenzhen was a tiny fishing village in southwest China, just one hour north of Hong Kong. Today, [Shenzhen] is the country’s second largest port after Shanghai, a booming technology haven and since 2007, home to BGI, formerly known as the Beijing Genomics Institute.
With 3,000 employees currently rising to an expected 5,000 by the end of this year, and a fleet of more than 150 Illumina and Life Technologies next-generation sequencing instruments, most of which are being installed in a former printing press in Hong Kong, BGI is poised (if it isn’t already) to become the world’s largest genome sequencing center. And it wants to share its extraordinary resources and expertise with, well, everybody.
Last April, BGI Americas was officially incorporated in Delaware as the official interface for BGI in North America. BGI Europe followed suit the next month (see “European Union”). From a small office in an incubator space overlooking Boston’s Charles River, a stone’s throw from the Broad Institute, the husband-and-wife team of Paul Tu (president) and Julia Dan (CEO) are reaching out to potential academic and commercial partners and customers. By the end of 2010, BGI Americas will have as many as 20 sales representatives spanning the continent in search of partners who wish to avail themselves of BGI’s prodigious sequencing capacity.
“We’re an interface representing BGI to collaborators in America and to promote the BGI brand,” says Tu. “That means finding collaborators working on different interesting projects, or fee-for-service projects, to support our operations.” He smiles: “3,000 people need to eat!” [American scientists need to eat, too - AJP]
Tu graduated from MIT’s Sloan School of Management and worked in venture capital for ten years before meeting BGI co-founder Wang Jian and “drinking the Kool-Aid”. Indeed, Tu and Dan abandoned their own start-up plans in China to sign on with BGI Americas. Tu’s wife is also his boss: Dan previously worked in corporate development for Genzyme. She lets Tu do most of the talking, but corrects him occasionally, just like any happily married couple.
Lucky Numbers
The growth and data output at BGI is nothing short of astonishing. The institute currently employees 3,000 staff in Shenzhen, including 1,500 working in bioinformatics, including programmers and IT staff. As of July 2010, BGI had 40 Illumina HiSeq 2000 instruments installed in its new facility in Hong Kong (a former printing press), growing to 100 by the end of 2010. When Illumina introduced its new state-of-the-art sequencer in January 2010, BGI immediately ordered a total of 128 machines -Tu explains that 128 is a lucky number in Chinese. (The number eight sounds like ‘wealth.’)
“God forbid it was 124,” he adds dryly. “Four would sound like ‘death!’ ” [2, 6, 8 or 9 are also "lucky numbers" in China; why do they need two orders of magnitude bigger numbers? - AJP]
The new facility in Hong Kong will greatly facilitate the shipment of samples from the rest of the world. [Yes, it is "lucky"... AJP]. “It’s a British system: one China, two systems,” says Dan about Hong Kong. “It’s the same thing with BGI.” For investigators leery of sending samples to Hong Kong, Dan hopes to give them the option of shipping to a sample receiving lab attached to BGI Americas headquarters in Boston, which will then handle the paperwork and shipment. That could be ready as early as September 2010.
By the time the Hong Kong facility is fully operational at the end of 2010, BGI will have a total sequencing output of 5 Terabytes/day—the equivalent of 1500x human genome/day. The data center now boasts 50,000 CPUs, 200 Terabytes of RAM and will reach a whopping 1,000 Petabytes—1 Exabyte—of data storage by year’s end. “It’s an awesome machine to play games on,” jokes Tu.
Such infrastructure comes at a price. BGI spends an estimated $10 million on electricity annually. “We cannot be a non-profit organization without any external support,” says Tu.
That is where BGI Americas and BGI Europe come in. “We’d love to work with [principal investigators] around the world, not just the U.S., on any interesting projects,” says Tu. Back in China, a committee of animal, plant and disease experts will select which projects BGI takes on. “BGI can be flexible—give us the samples, we can fund everything, and then we co-author the publication,” says Tu. A variant of that model would have BGI split everything—the costs, authorship and IP—with its partners.
“Not everyone can offer that. We don’t just do human, we do animals, plants, bacteria, complex diseases,” says Tu. “That’s the non-profit aspect. We want to sequence 1,000 plants and animals and have set aside $100 million for this initiative… It’s all about the science.”
But BGI is also offering a fee-for-service option. “We are a contractor,” says Tu. “Every single profit generated by the fee-for-service division will be returned to BGI to support the non-profit research agenda.” As a contractor, BGI will take any specs and deliver what the client wants. “If you want your data via FTP, or hard disk, we’ll do that. We give you a report, annotation, mapping, analysis. Not just sequencing, we also do all the back end as well,” says Tu.
Cost and Competition
Tu turns very diplomatic when asked about potential competition to BGI’s sequence service plans. “Personally, and throughout the organization, we don’t view anybody as our competitor. This field is extremely nascent. In science, what we know today may be only 2-5% of what it will be later. The science keeps advancing, we keep discovering new things.” As an example, he cites the recent UC Berkeley/BGI publication in Science that described a highly selected gene variant associated with altitude adaptation.
Dan says that, unlike a commercial service provider such as Complete Genomics, BGI’s value proposition is the flexibility to offer a pure fee-for-service as well as a collaborative model. “We don’t want to be restricted by funding for which research we can do. That’s the reason we do fee-for-service, and we love to do collaborations. We spend a lot on the collaboration side.”
Diplomacy turns to downright evasion when the subject is cost. “It depends,” says Dan not unpredictably, “on coverage, analysis, volume, and so on.”
“All these players—Complete Genomics, Broad Institute, etc.—are just collaborators for us,” says Tu. “When it comes to fee-for-service, we’re at the mercy of what Illumina charges us for reagent costs. We have gigantic overheads… We’ll eat some of the overhead, but the variables, somebody has to cover.”
“Can we compete head-to-head with Illumina and Complete Genomics, where this is all they do? They don’t even do exomes, they only do whole genome humans? They make their own machines and reagents, how can we compete with that?”
Tu marvels at the drop in sequencing prices over the past 12-24 months. “I’ve never seen such price erosion! This is like, Whoosh!... We’re a service provider, how can we compete with that? We compete with the back end, our bioinformatics. That’s where we’re good. Who else has 1,500 staff?” BGI already makes its popular software SOAP (Short Oligonucleotide Alignment Program) freely available (See http://SOAP.genomics.org.cn). Any data or tools built for the SOAP platform (using C++) are being donated to the public sector [This may not apply on everything beyond SOAP... AJP]
The average age of the BGI staff is just 24.7. [Compare this to the average age of US researchers getting their FIRST RO1 NIH grant - at the tender age of 42]. Tu calls the legions of bioinformatics workers “the young and the brightest,” drawn from the top tiers of mathematicians and scientists from the top universities around the country, supplemented with operations people who have worked abroad. “They work around the clock,” he continues. “If they come to BGI, they get to work on real projects. Plus you get to program all day, with these toys in the background! It’s like a video game, they love it!” New recruits cannot rest on their laurels however: every month for the first six months, there’s a test. Fail it, and it’s bye-bye BGI.
Tu and Dan have only been on the job a few months, but they too are working pretty much around the clock. Inquiries are already flooding in—mosquito genomes from Brazil, palm oil from Costa Rica, ancient DNA from the University of Massachusetts Medical Center. Tu was preparing to visit researchers at the Children’s Hospital of Philadelphia, and is already discussing projects with partners and clients at the Dana Farber Cancer Institute, Harvard Medical School, and the Broad Institute. He hasn’t had time to speak to all of the U.S. genome centers yet.
“We want to be a trusted scientific partner and research collaborator,” stresses Tu, speaking on behalf of 3,000 BGI scientists and counting.
European Union
BGI Europe was registered in Copenhagen, Denmark, in May 2010, and officially launched in June at the European Society of Human Genetics. The plan is to invest $10 million and to recruit 20 local staff in the organization’s first year alone. The CEO of BGI Europe is Mason Mak, who joined BGI earlier this year, although he is based primarily in Shenzhen.
Given BGI’s historic ties with Denmark, it is no surprise that BGI Europe headquarters is at the University of Copenhagen, Faculty of Life Sciences. The president of BGI, Yang Huanming, obtained his PhD from the University of Copenhagen in 1988. BGI’s director, Wang Jun, is a visiting professor at the University of Copenhagen and Aarhus University.
A new Copenhagen research institute on metabolic diseases, funded by a $170-million donation from Novo Nordisk, will strengthen an ongoing collaboration with BGI, led by diabetes researcher Oluf Pedersen. He says the alliance with BGI will create “an international powerhouse in the field of medical genetics.” (Diabetes and obesity are a growing health concern in China.) “Genomics cannot be done alone,” says BGI director Wang Jun. He says the Sino-Danish collaboration harnesses the superb medical infrastructure in Denmark with “Chinese genomics muscle” in the study of type 2 diabetes and obesity.
According to BGI Europe’s business development director, Danish-educated Wang Xuegang (he prefers to go by the name ‘Greg’), BGI Europe will offer European clients two models—collaboration or fee-for-service—just like its American counterparts. BGI Europe has six sales people already, but will be recruiting additional staff specializing in different fields such as agriculture, pharmaceutical, and biotech, spread across key regions including the UK, Germany, and Scandinavia.
As for what BGI’s key selling point is, Wang Xuegang says it is not necessarily the cost of sequencing. “Price is not what we sell on,” he says. A bigger selling point is BGI’s “very strong bioinformatics team,” with its immense experience in genome data analysis and de novo sequencing.
BGI Europe has an even more ambitious agenda than its American counterparts. The current plan is to establish a sequencing facility, probably in Copenhagen, within a couple of years, while growing the local staff to around 100 people. It would be futile for BGI Americas to set up a sequencing operation in the Broad Institute’s backyard, but BGI Europe may see an advantage to establishing a local production base in Copenhagen.
“Our vision is to make BGI Europe to be one of largest centers of sequencing services and bioinformatics,” says BGI Europe’s Xuan Min. “We’re trying to set up a sequencing lab in Copenhagen,” adds Wang Xuegang, likely in collaboration with a biotech partner or partners. The availability of a local facility might appease some potential biotech clients worried about data security and privacy. “We can set up a pipeline where everything is under control by the customer,” says Wang.
[Hope that this masterful interview by Kevin Davies will ring some bells - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
Junk DNA: Does it Hold More than what Appears?
Junk DNA: The secret key
What is the mystery behind so called “junk DNA” afterall? Is it really “junk” just because pretty little has been done to reveal its’ exact function? But, their codons have in them all! This particular variety of the “junk DNA” regulates the behavior of the normal coding genes. Presently, researchers [except the FractoGene explanation of Recursive Genome Function by Pellionisz] are unable to say anything with certainty about the supposed functions of these “non-coding” genes.
It is the same reason why scientists abhor from the usual practice of inserting foreign genes in the normal gene sequence. They fear that it could start the production of hitherto unknown proteins due to its uncontrollable spread. But, numerous possibilities exist due to the striking resemblance of these to the normal genes. [That is, synthetic genomics will not really take off, until regulation of recursive genome function is mathematically understood - AJP]
The future
The possibilities are endless. In fact, scientists do speculate that these genes could contain some kind of coded information for the future. Even if they ascribe the reasons of dreaded diseases like cancer to the “junk DNA”, others like Haig H. Kazazian, chairman of the University of Pennsylvania, has linked them evolution of the new species.
A June 2004 Harvard Medical School report while working on a “junk DNA” gene in the yeast, quotes an evidence regarding a new find, gene SRG1. It is believed that it physically blocks the transcription of the adjacent normal “coding” gene, SER3. Studies done elsewhere say that the non-functional DNA, aids in the gene expression regulation during development.
Over 700 studies done in this arena prove the role of “junk DNA” as an enhancer for the transcription of proximal genes. While around 60 studies in the same, have again proved that the non-coding DNA acts as a silencer during the suppression of transcription of “proximal” genes. Apart from that yet others talk about the function of the non-coding DNA in the regulation of the translation of proteins.
The twist in the tale
Russian researchers like Gariaev suggest the possible mediation of the non-coding genes at the quantum level. The studies done by the above and group confirm about the chromosomal ability “to gyrate the polarization plane of its own radiated and occluded photons”.
The very idea that about 98% of the DNA belongs to the junk category is a misnomer now. Biologists have long since ignored the fact that majority of the biological species — complete energy entities in themselves – function on the principle of minimal energy expenditure. This therefore, means that it is completely against the norm of energy saving feature of these organisms to include in their biological mechanism, the “non-coding DNA”.
It is but a reality that the unused DNA does have a function according to the researchers now. But, what that is can be anybody’s hard guess as of now.
The mathematical link
What is appearing now is the new branch of genomics itself supported by the likes of Andras Pellionisz, a biophysicist [formerly] at the New York University. He has some done ground-breaking work in the field of biological neural networks, based on the fractal geometry of cellular development addressing the decisive role of recursive genome function [both at the level of peer-reviewed science publication and having secured IP, widely distributed the concept of "Recursive Genome Function" in Google Tech Youtube (presently fetching 181,000 hits on a regular day, see below, with occasional peaks close to a million). The FractoGene concept was also embraced in the Churchill Club YouTube, as well as upon inviation of George Church (a BoA of holgentech.com), in Cold Spring Harbor, 2009] According to him, protein structures act back upon their genetic code, which is supported by many an observation and analysis of the genome sequences.
This, in fact, is undoubtedly a vast subject. But, amazing strides made in the recent times have left everyone dumbfounded as one upon another, information unlocks itself. The above principles could find their usage in the customization of the foods, drugs, cosmetics, chemicals; materials etc. which could then be matched with our genome. Of course, this will prevent the diseases from occurring, or maybe even halt the adverse conditions from developing further in their lethality.
[Algorithmic approach by A. Pellionisz, HolGenTech, Inc.]
[Cloud-solutions (this is by DNAnexus - in addition to the slew of such services) rushing to the market created by the "Dreaded DNA Data Deluge" need algorithms, e.g. for targetable structural variants (fractal defects) - AJP]
Biotech is back [in Korea - AJP]
JoonAng Daily
Korea
August 11, 2010
The [Korean - AJP] nation’s biotechnology and life sciences industries are hitting one milestone after another. Many of the biological and genetic experiments undertaken in laboratories more than a decade ago are finally ready to see daylight and hit drug store shelves.
According to the Korea Food and Drug Administration, a local biotechnology enterprise has completed clinical safety testing of a drug aimed at treating acute myocardial infarction - or heart attacks - and has filed for approval with health authorities. If it passes the screening, the company will be able to release the world’s first legitimate drug derived from stem cell technology.
Other biotechnology companies are also actively involved in developing disease-specific stem cells into drugs to treat and repair knee cartilage and spinal cord injuries. These companies may open the door to entirely new medical treatments and prop up the health care industry by releasing blockbuster drugs using human embryonic stem cells.
News of breakthroughs in the local bioengineering industry is coming from many areas. Single-gene malady treatment using an individual’s DNA genome is ready for commercialization. Thanks to advances in genome analysis and technology, the cost of having a hospital study your gene sequence is expected to fall to $1,000 within two to three years. We may not be far away from the days when we’ll commonly receive accurate diagnosis of ailments and individually tailored treatments based on our genetic makeup.
Competition in the area of low-cost generic products marketed after the expiration of patents is also getting fierce. Large business groups like Samsung, LG, Hanwha and CJ are jumping into the fray to sell drugs with similar properties to biotech drugs whose patents are about to expire.
The local biotechnology industry has groped its way through a dark tunnel over the last 10 years. The gold hunt in the Kosdaq market and controversy over scientist Hwang Woo-suk’s fabrication of his stem-cell research also scarred and crippled the industry.
But news of technological headway is triggering excessive competition and reckless scouting of scientists and bioengineers. Authorities must now step in to redefine the industry and revisit the nation’s strategy for biotechnology.
The industry is a high-end market that can fuel the country’s future growth. The government should administer state projects in key areas and promote strategic alliances among companies. A new business model can be created by fostering partnerships between large corporate giants and upstart biotech companies.
[Wishing for some specifics - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
CLC bio [of Denmark] and PSSC Labs [California] Deliver Turnkey Solution for Full-Genome Data Analysis
Business Wire
Aug 12, 2010
AARHUS, Denmark, Aug 12, 2010 (BUSINESS WIRE) -- Today, CLC bio and PSSC Labs announced a new turnkey solution, CLC Genomics Factory, for assembly, read mapping, and subsequent downstream analysis of very large amounts of high-throughput DNA and RNA sequencing data. Built as a high-performance bioinformatics appliance, CLC Genomics Factory comes in three different sizes with varying numbers of compute nodes, capable of processing the data output from up to 10 Illumina HiSeq2000 or 7 Life Technologies SOLiD 4 systems.
Vice President Bioinformatics Solutions at PSSC Labs, Alex Lesser, states, "As we're already working with the leading instrument providers such as Roche 454, Life Technologies, and Illumina, it was a natural step for us to partner with the leading software provider within high-throughput sequencing data analysis, CLC bio. Based around their enterprise platform, we have tailored an extremely powerful turnkey solution for analyzing the vast amounts of data coming off all the different high-throughput sequencing instruments, including upcoming technologies such as Ion Torrent and Pacific Biosciences."
CEO at CLC bio, Thomas Knudsen, continues, "It was obvious for us to combine our expertise on high-performance bioinformatics algorithms and user-friendly software, with PSSC Labs' extensive experience in cluster solutions for the life science industry. We now provide the first and only turnkey solution for full-genome analysis of data from all types of high-throughput sequencing instruments. Our customers don't have to invest in a new cluster for each technology they wish to adopt: CLC Genomics Factory handles them all - now and in the future!"
CLC Genomics Factory is built around CLC bio's enterprise platform, including the award-winning CLC Genomics Server, as well as all of CLC bio's accelerated algorithms for full-genome assembly and analysis. Multiple licenses for CLC Genomics Workbench enable users to interface with the server software through either a user-friendly graphical user interface or, optionally, a command line interface. CLC Genomics Factory includes also support for CLC bio's Software Developer Kit, for those wishing to integrate 3rd party systems and software.
CLC Genomics Factory includes a master node, multiple job nodes, as well as varying amount of storage. Read more about CLC Genomics Factory including full technical specifications at http://www.clcfactory.com [The specs reveal that in complete configuration the system can analyze 32 full human genomes per week ~ 5 hours per individual genome - about an order of magnitude more than will be required in biopsy-sequencing AND analysis - AJP]
CLC Genomics Factory is sold by CLC bio and CLC bio resellers. The computer hardware is assembled, tested, distributed, and supported by PSSC Labs who have great experience in delivering complex computer setups, with more than 1000 running installations of their clusters across 35 countries around the world. CLC bio handles the support on the software.
[The California-based hardware manufacturer, because of competitive funding requirement, is again forced to be quite specific, but we don't learn a lot here about the software created in Denmark - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
GenomeQuest and SGI Announce Whole-Genome Analysis Architecture
PRWeb
August 4, 2010
Immediate Availability of World's First Whole Genome Analysis Services for Researchers
Westborough, MA and Fremont, CA (Vocus) August 4, 2010
GenomeQuest and SGI (NASDAQ: SGI) today announced the immediate availability of the world’s first whole-genome analysis (WGA) services for researchers. As a result, pharmaceutical companies, core labs, biotechs, government agencies, and clinics now have direct access to whole-genome processing previously found only inside genome centers combined with comprehensive, self-serve analysis.
The WGA services allow whole-genome/exome research teams to:
Store, manage, and compare their sequences and annotations
Assemble and align sequences from any instrument
Interactively query and analyze their runs and projects
Merge and re-analyze with findings from colleagues and public studies
Use standard workflows, including Variant Detection, RNA-Seq, and ChIP-Seq
Build and query enterprise-wide variant archives
"Data analysis is recognized as the bottleneck of whole-genome research. Traditionally, researchers receive static reports for their sequence runs which, at today's volumes, are impossible to analyze and increasingly siloed,” said Jean-Jacques Codani, GenomeQuest Chief Scientific Officer. “From its inception, the GQ Engine has provided researchers with rich, interactive reports and the ability to integrate and re-analyze with other work. Now, with SGI's longstanding experience in high-performance computing, we have found the bow that best fits our arrow for WGA-scale services.”
GenomeQuest and SGI co-developed a software and hardware architecture that is optimized for next generation sequencing and enables whole-genome scale and performance. Based on this architecture, the WGA services are available through the just-upgraded GenomeQuest data center or deployed directly into a customer data center, as may be required by larger accounts, core labs, and clinics.
“Clearly, the storage and computational needs of WGA are massive and unique,” said Dr. Eng Lim Goh, senior vice president and chief technology officer at SGI. “Given the complexity of the algorithms and the scale of the data, success in this area requires a careful factoring then optimization across four key parts of the system -- software, computational and I/O capabilities, and burstability. We are very excited about the new GenomeQuest center, and applying this enabling blueprint for life science organizations.”
The GenomeQuest center was upgraded on May 18, 2010. A major investment, it radically improved the user experience and performance for over 2000 existing commercial and academic users.
“We have observed a radical change in the use of GenomeQuest since the opening of the new center,” comments Ron Ranauro, GenomeQuest CEO. "Our personalized medicine research application is processing thousands of exomes per month and will soon scale to over 1000 full-human genomes at deep-coverage.”
The SGI-based upgrade includes:
Multiple, load-balanced head nodes to service high-volume user requests and interactions
Rackable XE, server stack of high-performance compute nodes to service highly-parallelized, sequence database comparisons
Storage solution featuring high-performance I/O subsystem scalable to Petabytes
Housed in a Type II SAS 70 compliant data center with fully redundant hardware and software for 24/7 availability
In related recent news at BIO-IT WORLD, GenomeQuest also announced GQ-PMR, the world’s first genomic reference system for personalized medicine-based research. With GQ-PMR, pharmaceutical companies can integrate raw data from public whole genome studies, such as the 1000 Genome Project, directly into their private research. The combination allows research organizations to massively expand sample sizes at virtually no cost and accelerate their transition to molecular-based personalized medicine.
As background, in a July 8, 2010, feature story in USA Today titled "The human genome: Big advances, many questions", Vivien Bonazzi, head of computational biology for National Human Genome Research Institute at the National Institutes of Health, comments, "We're really crying out for the ability to analyze this (output of genome sequencing machines) efficiently and effectively."
[By this illustration of a US (MA-based) software company (Genomequest), working with the Silicon Valley based company SGI (California), the point is to contrast the transparency of USA technologies (also applying to HolGenTech' "Genome Computing Architecture" that - having filed for IP protection - has even been broadcast on YouTube-s). Such dangerous transparency is necessitated in the USA because of competitive funding pressures - and is contrasted by the largely elusive (at times evasive) nature of certain Asian comparable efforts - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
Pacific Biosciences Expands into European Union
Pacific Biosciences - release
August 3, 2010
Terry Pizzie Appointed Vice President, Europe
UK-based Wellcome Trust Sanger Institute Becomes Early Access Customer Menlo Park, Calif. – August 3, 2010
Pacific Biosciences, a private company developing a disruptive technology platform for real-time detection of biological events at single molecule resolution, today announced it has expanded its operations into the European Union with the appointment of Terry Pizzie as Vice President, Europe and with its first European customer, the Wellcome Trust Sanger Institute. Mr. Pizzie has more than 20 years experience in a broad range of international commercial life sciences industry management positions. Previous to joining Pacific Biosciences he was Director of Global Commercial Operations (a board position) for Genetix (now part of the Leica Division of Danaher Corp.) Prior to joining Genetix in 2007 he was Senior Vice President of Commercial Operations from 2005-2007 at Biacore (now part of GE Healthcare), a market leader in protein interaction analysis in research, drug discovery development and manufacturing. Before joining Biacore, he was Vice President Europe of Applied Biosystems (now part of Life Technologies Corp.) from 2002-2004 with responsibility for all European commercial operations including strategy, performance and operational efficiency. He joined Applied Biosystems in 1988 as a sales engineer and advanced through the organization in increasingly responsible positions including Vice President of Sales and Marketing for Europe from 2000-2002. Mr. Pizzie holds a degree in Physiology and Biochemistry from the University of Reading. “Terry has an exceptional track record of strategically managing the commercial success of leading life science organizations in Europe, and we are delighted that he will lead the establishment of our European operations,”said Hugh Martin, Chairman and Chief Executive Officer of Pacific Biosciences.
Pacific Biosciences also announced that the Wellcome Trust Sanger Institute has purchased a PacBio RS 3rd generation sequencing system as part of the company’s early access program. Earlier this year, Pacific Biosciences announced the first 10 customers as part of its North American early access program. These sites, which represent genome centers, cancer research institutions, commercial organizations, and universities, have begun receiving their instruments.
Today’s announcement reflects the company’s expansion of its early access program to a limited number of sites outside of North America.
[While PacBio already made Full DNA Genome Analytics GLOBAL by establishing Partnership with Canadian and Danish developers (see DevNet below) - the actual physical delivery of the now "lead-technology" nanosequencer equipment (by PacBio) into foreign land, starting with the UK, completes the globalization of the spread of sequencing machines (and, therefore, puts the produced full human DNA sequences outside the jurisdiction of the USA). For the previous generation of machines (Illumina Genome Analyzer, Roche/454 and Life Technologies' SOLiD the global spread, especially to China, has alredy been a fact for quite a while - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
Pacific Biosciences launches PacBio DevNet at ISMB 2010
9. July 2010 08:29
The Medical News
As part of its commitment to introducing third generation DNA sequencing technology to the market, Pacific Biosciences today announced the launch of a software developer's network - the PacBio DevNet - at the Eighteenth International Conference on Intelligent Systems for Molecular Biology (ISMB 2010).
“We look forward to contributing to a robust analytical ecosystem that allows more scientists to exploit the new possibilities enabled by this technology.”
Throughout the development of the company's Single Molecule Real Time (SMRT™) technology platform, Pacific Biosciences has been working closely with members of the informatics community to develop and define standards for working with single molecule sequence data. Now, as the company prepares for the commercial launch of the PacBio RS, it is launching a more formal program to support the needs of the informatics community.
The PacBio DevNet was created to support the ecosystem of academic informatics developers, life scientists, and independent software vendors interested in creating tools to work with PacBio's third generation sequencing data. Interested parties can sign up for the PacBio DevNet at www.pacbiodevnet.com, a hub for data sets, source code for algorithms, application programming interfaces (APIs), conversion tools to industry standard formats, and documentation related to SMRT sequencing.
Eric Schadt, Ph.D., Chief Scientific Officer for Pacific Biosciences commented: "Single Molecule Real Time sequencing introduces entirely new dimensions to data, such as a time component, that are unlike anything the bioinformatics community has encountered to this point. Therefore, in addition to a strong internal focus on informatics development, we are committed to supporting third-party software development and facilitating the rapid adoption of this new data type into the scientific community where the really exciting 'big science' can begin [already begun in 2002 - AJP] to happen."
At the ISMB conference, PacBio scientists and collaborators will present results from some of their informatics development efforts to date, including new algorithms tailored to the unique characteristics of the SMRT data such as its long reads. Pacific Biosciences has also developed a suite of data management and analysis software tools that mimic the granularity, scalability and functionality of the PacBio RS. These informatics solutions are designed to efficiently integrate with the user's LIMS system, making them accessible not only to high-end informatics researchers, but also to biologists and clinical researchers.
"The release of PacBio's tools under an open source license and the launch of its Developer's Network will foster the creation of tools that maximize the value of SMRT sequencing," said Reece Hart, Chief Scientist, Genome Commons. "We look forward to contributing to a robust analytical ecosystem that allows more scientists to exploit the new possibilities enabled by this technology."
[The key to "industrialization of genome analytics" is precisely how some "open source license" system could be brought into a productive synthesis with "professional (and for profit) private entrepreneurs". Our "Internet Boom" in Silicon Valley provided some very important lessons; e.g. the Internet browser started with Jim Clark founding Netscape - but having failed to develop a secured business model around it, reverted into Mozilla (open source) - while Microsoft and now Google ran away with the software profit. (With Cisco to be mentioned as the winner in Internet hardware). PacBio' DevNet requires registration, accepting their terms & conditions, but even the public interface reveals their "Partnership" with Amazon Web Services, BioTeam, CLCbio, GenoLogics, GenomeQuest and Geospiza - yet none of them are the Silicon Valley HQ-d "genome informatics pure-play" with proprietary algorithmic approach to Recursive Genome Function, like HolGenTech, Inc. - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
Illumina Inc. et al. v. Complete Genomics Inc.
1:10-cv-00649; filed August 3, 2010 in the District Court of Delaware
• Plaintiffs: Illumina Inc.; Solexa Inc.
• Defendant: Complete Genomics Inc.
Infringement of U.S. Patent Nos. 6,306,597 ("DNA Sequencing by Parallel Oligonucleotide Extensions," issued October 23, 2001), 7,232,656 ("Arrayed Biomolecules and Their Use in Sequencing," issued June 19, 2007), and 7,598,035 ("Method and Compositions for Ordering Restriction Fragments," issued October 6, 2009) based on defendant's manufacture and sale of its Complete Genomics Analysis Platform products and services. View the complaint here.
[This lawsuit, aimed at core technologies, is an obvious setback not only to Complete Genomics, but the entire "Full DNA sequencing" industry. Immediately, it may adversely affect Complete Genomics' determination to go public at this time, since in some investors' eye a relatively novel company that is sued by one of the leading and well-established companies (Illumina) at the least would lessen the financial success of a Complete Genomics IPO. A quick settlement looks unlikely as Complete Genomics is capital hungry, and Illumina by demanding "jury trial" looms large, possibly inflicting a multi-year and expensive process. This three-pronged lawsuit is also a set-back to the entire "Full Human DNA Sequencing" industry - and given that Complete Genomics altered twice the expectations (first as quoted in my YouTube 2008 October, promising a "Google-type Data Analytics Center", and secondly the service seems to be open to batches of 100-s of sequences, in a whole-sale mode to R&D, rather than to the public) - Illumina (and Life Science) may stay longer as an established provider with their "pre-nanosequencing technology" (the Genome Analyzer by Illumina and SOLiD by Life Science). This altered dynamics is likely to trigger a ripple of business decisions - Andras Pellionisz (FaceBook) / Pellionisz_at_JunkDNA.com]
At the Churchill Club event "Personal Genome Computing: Breakthroughs, Risks and Opportunities on January 22, 2009 in the Q&A period the question was asked when would the first genome computer game appear. I said "In Two Years". I was wrong. In exactly One Year (January 22, 2010, that is precisely half the time predicted) the following paper was submitted to Nature (accepted June 30, 2010):
Predicting protein structures with a multiplayer online game
Seth Cooper, Firas Khatib, Adrien Treuille, Janos Barbero, Jeehyung Lee, Michael Beenen, Andrew Leaver-Fay, David Baker, Zoran Popović & Foldit players
Nature 466, 756–760 (05 August 2010) doi:10.1038/nature09304
Received 22 January 2010 Accepted 30 June 2010
People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully ‘crowd-sourced’ through games1, 2, 3, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology4, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.
"Recursive Genome Function" - winner takes it all
 |
[Screenshots of Google, Aug.4, 2010 - AJP]
The astonishing fact overnight is not that "Recursive Genome Function" inched forward from 160,000 by two thousand hits.
"The Winner Takes It All" is shown by the obsolete axioms dropped overnight by almost thirty thousand hits (combined). An almost 10% daily drop of the stock market index halts trading. A more common example: You never want to take away toys, even old ones, from those (not scientists) playing in a sandwalk. They scream from the top of their lungs. The thing to do is to offer a new (and better) toy. The obsolete ones are quietly dropped by those grabbing the novelty, while those who drop the old but fail to grasp the new show all the signs of hard times - FaceBook: Andras Pellionisz, or email Pellionisz_at_JunkDNA.com
Pellionisz' "Recursive Genome Function" supersedes both obsolete axioms of "Central Dogma" AND "Junk DNA"
 |
At the tenth Anniversary of The Human Genome Project, there is a unanimous agreement of scientists worldwide that there is tremendous intellectual void between our ability of reading the Full Human DNA (all 6.2 Bn A,C,T,G-s of a diploid human genome) on one hand, and our (limited) ability of writing new sequences, on the other hand. It is not the greatest problem that both our reading (e.g. precision) and synthesis (size) needs improvements. E.g. synthetic sequences presently must be small enough in size and in difference from existing forms of life to remain "stealth" to Genome Regulation, such that they can be synthesized and even started to function (nobody knows through how many generations, since they have been put into a freezer...).
By far the most critical void is the present almost complete lack of professional theoretical foundation of genome informatics. This coming intellectual void was actually predicted by Francis Crick when he attempted to temporarily shore up his collapsing "Central Dogma" (upheld since his promulgation in 1956 till his passing in 2004); "If it were shown that information could flow from proteins to nucleic acids, he said, then such a finding would 'shake the whole intellectual basis of molecular biology' "(Crick, 1970). Although Ohno (1972) rushed to save the establishment with his misnomer that even if there were such recursion, it would only find "Junk DNA" in the 98.7% non-genic part of the genome, which is there, he falsely claimed, for "the importance of doing nothing" (p.367), by now the "genes-Junk" primitive and obsolete school is what Venter calls flatly: "we have a frighteningly unsophisticated view of genome function". What happened to Dr. Collins' call upon concluding ENCODE in 2007 that "the scientific community has to re-think long-held beliefs"?
A lucky few did not have to re-think "Central Dogma" and "Junk DNA" - since they never believed them in the first place. Thus I had a decade-long lead to build The Principle of Recursive Genome Function (2008) - that elaborates my FractoGene concept (2002). Nobody seems to raise "no, the genome function is not recursive" - that would be pretty foolish. If some think "yes, it is recursive, but not fractal", one would recommend the recent Science cover issue (Oct. 9, 2009) "Mr. President, the Genome is Fractal!" (Lander et al., 2009) Though Pellionisz Principle was quoted by a dozen or so authors within 6 months of its publication in a peer-reviewed science paper, totally independent authors are joining the fray (Jean-Claude Perez, France, 2010, Borros M. Arneth, Germany, 2010) - before it will (soon) be everywhere "that we have all been saying that the genome function was recursive, and in fact was based on my thoughts of fractal recursive iteration...". People might forget that it was my double "lucid heresy" to put to rest the two ruling false axioms that hidered genome informatics over half a Century - by discovering and publishing (now applying...) the more advanced Principle of "Recursive Genome Function".
Some may ask why do I make such a strong point about theoretical foundation of full (holo)genome function (including the epigenomic pathway through which extrinsic proteins make the hologenome "an open loop" - The Circle of Hope).
The primary of the two strong reasons is, that most of the general public (and unfortunately, even some scientists) maintain that "our genome is our destiny"; there is nothing we can do about it, and it deterministically defines our future. Clearly, this totally mistaken attitude stems from Crick's "Central Dogma", that sees a "straightforward, DNA>RNA>PROTEIN genome function that "dead end"-s with proteins, and the genome is assumed to lack even the possibility of a PROTEIN>DNA recursion. The deterministic philosophy also has deep roots in natural sciences, since e.g. in physics it was only a mere 83 years ago (a footnote in the over 2,000 years of physics) that the Heisenberg Uncertainty Principle was put forward. Physics of today is probabilistic (rather than deterministic), but such a profound change of attitude (in fact, philosophy) certainly does not happen overnight in postmodern genomics - or even biology. Most unfortunately, the old and gloomy (and false) legacy often prevails, e.g. in discouraging people of taking advantage of genomic tests; "why should I know if nothing can be done". Once I published The Principle of Recursive Genome Function (2008) I rushed to disseminate "the Circle of Hope" widely over Google Tech Talk YouTube - such that the public picks up a new wave of positive motivation based on rock-solid new science.
Unfortunately, the public's view greatly affects both the government R&D programs, as well as the sustainability of private domain R&D and applications. Those who paid $3 Billion by their taxes for sequencing a single Full Human DNA, and a decade after the same scientists openly declare that they don't have the slightest how to understand it, could significantly tone done government funding enthusiasm. Even with today's "point of inflection" when the Private Sector is taking over, the stakes are enormous if the Genome Informatics Industry gears up for "Brute Force Approaches" (that can always be done, albeit with horrific expense) - or processing of experimental data is guided (actually, predicted) by the best theories. No sane person (or Country...) would build enormous accelerators if nuclear physics would not be available to interpret the trajectories. However, there are $Billions invested into "DNA sequencing technologies" - and theories of doing away with half-a-Century dogmas often go overlooked in anywhere - but on the Google search engine "Recursive Genome Function" beating (at some peaks by close to a million hits...) both stone-age unsophistication of "Central Dogma" and "Junk DNA" - Pellionisz_at_JunkDNA.com
Mountain View's Complete Genomics to make Wall Street debut
Silicon Valley Mercury News
By Scott Duke Harris
Posted: 07/30/2010 07:39:49 PM PDT
Updated: 07/30/2010 09:03:44 PM PDT
A Mountain View startup that aims to drive the cost of sequencing a human genome to below $1,000 in hopes of advancing health care is preparing for a Wall Street debut and staking its claim to the ticker symbol GNOM.
In documents filed Friday with the Securities and Exchange Commission, Complete Genomics signaled its intent to make an initial public stock offering on the Nasdaq, hoping to sell more than $86 million in stock.
Startups that register for Wall Street debuts often postpone or withdraw such plans. Given the uncertain market for IPOs and excitement surrounding the commercial potential of DNA research, Complete Genomics' effort figures to attract considerable attention.
All life-forms carry a genome, a strand of chromosomes that is a full reflection of its hereditary traits. Complete Genomics is among a group of Silicon Valley startups at the cutting edge of DNA research — an endeavor that promises to advance human health while also playing a role in agriculture and biofuel development.
Complete Genomics' proprietary, assembly-line-like laboratory operation began sequencing human genomes about a year ago. The company has focused on doing large studies on human genomes for customers such as Genentech, the pharmaceutical giant Pfizer and major research institutions.
Sequencing the human genome was pioneered a decade ago at a cost of about $500 million for one genome. The expense has been an obstacle for researchers who are trying to decode patterns that correspond to maladies known to have genetic roots. Driving down the cost — the central mission of Complete Genomics' technology and business model — has been critical to performing large studies.
"It's all about scale. Sequencing one human genome is a scientific curiosity," Clifford Reid, co-founder and CEO of Complete Genomics, said in an interview with the Mercury News in September. That month, when the company announced it had sequenced a batch of 14 genomes, "we probably doubled the number of known genomes in the world," Reid said.
Last May, when Complete Genomics started commercial operations and after medical researchers published a report in the journal Science based on genomes it had sequenced, Reid was quoted as saying that his company was processing 500 genomes a month and had dropped the cost to $4,000.
In its filing with the SEC, Complete Genomics asserted that it has "optimized" its technology platform and is "able to achieve accuracy levels of 99.999% at a total cost that is significantly less than the total cost of purchasing and using commercially available DNA sequencing instruments."
It also touted "significant competitive advantages" as an independent lab: "Because our technology resides only in our centralized facilities, we can quickly and easily implement enhancements and provide their benefits to our entire customer base. We believe that we will be the first company to sequence and analyze high-quality complete human genomes, at scale, for a total cost of under $1,000 per genome."
[Assuming that the uncertain economic conditions will allow the successful IPO to happen, this is wonderful news - both for Complete Genomics and the rest of the world. While there are public companies that do DNA sequencing (best known are Illumina, Life Sciences), Complete Genomics aptly celebrates the 10th Anniversary of The Human Genome Project by becoming the first "pure play" human DNA sequencer company, using "assembly-line" mass-production by molecular nanosequencing. The planned IPO seems to be timed to pre-empt the company's main rival, Pacific Biosciences (of Menlo Park, CA) flooding the market with their sequencing machines. Watching carefully the market, if it will validate Craig Venter (see below) that full human DNA sequences provide "useless information" (without Analytics), or with the ramping up of full human DNA interpretation (also by HolGenTech, Inc. stealth-mode breakthrough) will contribute to a successful IPO is critical e.g. for Silicon Valley jobs. - "Andras Pellionisz" (FaceBook), Pellionisz_at_JunkDNA.com]
SPIEGEL Interview with Craig Venter: 'We Have Learned Nothing from the Genome'
Spiegel
07/29/2010
[This interview deserves to be amply commented, especially since Dr. Venter (not Mr. Venter...) made this recent statement: We’re at a frighteningly unsophisticated level of genome interpretation.” . I will make my comments as my personal opinion of Dr. Venter's statements below, based on my overall assessment that I expressed for some time that "Venter is the Tesla of PostModern Genomics" - Comments on my remarks can be posted at my FaceBook ("Andras Pellionisz") or email Pellionisz_at_JunkDNA.com]
---
Ten years ago, Craig Venter had plenty of reason to feel triumphant. Standing at the White House together with his rival Francis Collins of the National Institutes of Health as well as then-President Bill Clinton and former British Prime Minister Tony Blair, he announced the successful sequencing of the human genome. The historic press conference marked the end of a bitter race between Venter's firm Celera and the Human Genome Project, a government-sponsored consortium of around 1,000 scientists from around the world. Both groups had technically mapped the genome, but Venter's team had done it faster and cheaper. Since then, multimillionaire Venter, 63, has established a reputation within the scientific community for being a rebel. It's an image he appears to relish, and he stuns the world again and again with one brash victory after another. He is currently sailing around the world in his Sorcerer II research yacht documenting the genetic diversity of the world's oceans. He recently departed Valencia, Spain, to begin an expedition in the Mediterranean Sea. In May, he announced that his team had produced the world's first bacteria with a synthetic genome.
[Dr. Venter's perspective from sailing around the Globe might be motivated by the famous saying: "Be careful what you wish, since it might become true" ... Craig might feel that glorious emptiness, now for the second time, that he has accomplished the unthinkable, and "there is nothing simpler than a problem solved" (Faraday). Ten years ago he successfully competed in a single-handed manner (except computers...) with a world-wide consortium in full DNA sequencing of a human. Now he succeeded, after 15 years of effort, much longer than he anticipated, in synthesizing a functioning genome that was not the exact duplication, but slight modification, of a tiny DNA - and could implant it in a cell that accepted the "newcomer" DNA. Success is, like arriving at the mountain-top, a funny feeling. Glorious, yes, "mission accomplished" - but from the hilltop the next mountain presents a perhaps even more mounting challenge. Accomplishing the unthinkable can thus also is disappointing; a problem solved may reveal that the questions that it opened are even more formidable than what has just been answered. Venter said recently; "Were at a frighteningly unsophisticated level of genome interpretation". He acquired the entire set of character-sequence of the "big Russian novel" (quote from Esther Dyson) but realizes much more keenly than most, that "our 100-word dictionary" (which may be Chinese-English...) is a miserable failure to understand, let alone enjoy, the meaning of the Russian novel that myriads of characters tell us in an unknown language.
Craig is undoubtedly very aware of what's missing; actually both in making sense of the sequences, as well as synthesizing new, complex and big synthetic genomes. We can not go from "reading" to "writing" - without "understanding". Booting the modified and synthesized tiniest free-living organism could not succeed since the basic principles of genome function regulation were "frighteningly unsophisticated" for most. Since Craig is not (yet?) frontally attacking the "next big problem" (of analytics of genome regulation), some of his comments perhaps unduly play down the significance of what has actually been achieved - and his self-contradiction at times can be easily spotted. Maybe the journalistic title "we have learned nothing from the genome" picked up on a temporary disappointment, a "let down" after yet another major accomplishment. Venter says below, that (a truly frighteningly unsophisticated "genome function theory") expected maybe up to 300,000 "genes" in the human genome. We absolutely did learn from his (and the Consortium's) results, that the primitive assumption was totally wrong, didn't we?
In a year after the human DNA was sequenced, the mouse DNA showed that 98% of the (mere 20,000 or so) "genes" are functionally identical in human or mouse (and by now we realize that the "basic building materials" are astonishingly similar in practically all species; from the ringworm to human). For a biophysicist who devoted his oeuvre to the intrinsic mathematics of biology (and explained brain function for cerebellar neural nets by tensor geometry), the 98.7% of "Junk DNA" misnomer was dead on arrival of 2002. With sequencing techniques becoming widespread and available, we did absolutely learn, too, that the genome DNA>RNA>PROTEIN "forward model" is just absurdly incorrect, didn't we? Genomics and Epigenomics, therefore (particularly by experimental investigation of methylation) is almost universally accepted as the two sides of the same coin. Thus, the "Central Dogma" (having died a thousand deaths) was put to rest, along with JunkDNA - leading to The Principle of Recursive Genome Function - explaining e.g. the fractal growth of cerebellar Purkinje neurons as governed by the fractal DNA - through the epigenomic channels methylating auxiliary information in the "non-coding DNA" upon perusal in fractal iterative recursion. Perhaps we should have listened to Crick, that if his "Central Dogma" were shown to be untrue, "If it were shown that information could flow from proteins to nucleic acids, he said, then such a finding would 'shake the whole intellectual basis of molecular biology' "(Crick, 1970). What happened to the earth shake? What happened to Dr. Collins' call (wearing his scientist' hat upon concluding ENCODE in 2007 that he put together wearing his administrator's hat) that "the scientific community has to re-think long-held beliefs"? We did learn from the genome, did we not, that the genome itself (because of the epigenomic "open loop" - the "Circle of Hope") provides us with "probabilities", rather than certainties - but who says that "probability theory" equals to "useless information"? When will the philosophy sink in (like it did with the Heisenberg Uncertainty Principle) that sophisticated science at times must proceed in a way that the whole intellectual basis is shaken?
In the afterglow following a second accomplishment of the unthinkable one may be overly pessimistic on particular details. A good example is the statement that knowing his genome, Dr. Venter could not use it for anything. He is on record, however, that as early as during the process of his full DNA sequencing (since he was one of the five DNA donors) he started to take statins as the genomic signature of the sample in which he was dominant warranted controlling his cholesterol. The "close to zero" medical benefit from genomic knowledge is demonstrably untrue for individuals who showed elevated probability of e.g. colon cancer, followed up with colonoscopy and small, pre-cancerous polyps were removed.
Because of his double towering accomplishments, Dr. Venter is entitled to vocalize that "the more we know, the more we realize what we don't know". Those with lesser achievements can not afford to be less than optimistic. - You can comment at my FaceBook wall "Andras Pellionisz" or email Pellionisz_at_JunkDNA.com]
---
The world's first bacteria with a synthetic genome was even coded with an e-mail address. [Is SPAM-ing a genome a brand new epigenomic effect, or what? - AJP]
In a SPIEGEL interview, genetic scientist Craig Venter discusses the 10 years he spent sequencing the human genome, why we have learned so little from it a decade on and the potential for mass production of artificial life forms that could be used to produce fuels and other resources.
SPIEGEL: Mr. Venter, when the elite among gene researchers undertook the decoding of the human genome, you were their greatest enemy. They called you "Frankenstein," "blood sucker," "Darth Venter" and even "asshole." Why do you attract so much hostility?
Venter: Well, nobody likes to be beaten -- by superior intelligence, planning and technology. That gets people upset.
SPIEGEL: Every area of science is competitive. But it doesn't lead to that kind of hostility in all areas.
Venter: The human genome project was completely different, it was supposed to be the biggest thing in the history of biological sciences. Billions in government funding for a single project -- we had never seen anything like that before in biology. And then a single person comes along and beats scientists who have been working on it for years. It is no wonder they didn't like that.
SPIEGEL: Wasn't it more the case that your opponents were afraid that you, as a profit-oriented entrepreneur, would make the human genome your own private property?
Venter: That is totally absurd; and you know it. Initially, Francis Collins and the other people on the Human Genome Project claimed that my methods would never work. When they started to realize that they were wrong, they began personal attacks against me and made up these things about the ownership of the genome. It was all absurd.
SPIEGEL: So it was all just propaganda?
Venter: At the end of the day, it is an argument over nothing. But this battle between common good and commerce -- that is the kind of story that sells newspapers.
SPIEGEL: Was the importance of gene patents, which fueled the dispute, exaggerated?
Venter: First of all, nobody has made any serious money off patents on human genes except patent attorneys. Second, I do not hold any patents on human genes. You can do a patent search. Then you can convince yourself.
SPIEGEL: On June 26, 2000, you had a major event -- you met with Francis Collins at the White House …
Venter: … yeah, it was obviously a big historic event. It was pretty stunning, making an announcement at the White House to the entire world. It was a big triumph for me and my team because it proved that we had won.
SPIEGEL: At the time, none of you had won. Nobel Prize recipient John Sulston, one of the researchers of the government-funded genome project wrote …
Venter: … What was his quote? That he and his people were a bunch of phonies who had nothing?
SPIEGEL: In essence, he wrote that you both had nothing.
Venter: He had no idea what we had. Sulston has proven he is not the most credible source on anything other than his own data. He said they were a bunch of phonies, we have to take him at his word on that.
SPIEGEL: It seems to have been the only time in history that a new scientific discovery was announced officially by the government. How did that unusual agreement in the White House take shape?
Venter: It was a political compromise because the people at the public Human Genome Project were afraid we would announce what we had. And we were afraid they would use the White House to make it look like they had won.
SPIEGEL: It appeared at the time that you had agreed to be undecided. Do you now view yourself as the winner of the race?
Venter: I don't think it really matters.
SPIEGEL: The New York Times later declared the public Human Genome Project to be the victor. Can you really claim that you don't care?
Venter: Oh, the New York Times! How do you define the "winner" in this case? What is decisive is that it is our data that is in the databases -- not the data the consortium put together back then.
SPIEGEL: The genome project has been called the Manhattan Project or Moon Landing of its era. It has also been said that knowledge of the genes will change the future of humanity and become a "main driver of the world economy."
Venter: Who said that? I didn't. That was the people at the consortium.
SPIEGEL: You're wrong. You made all those statements in an interview with DER SPIEGEL in 1998.
Venter: Really? Those are Francis Collins' lines. So I may have said that that's how he describes it. I, on the other hand, have always said, "This is a race from the starting line to the finish."
SPIEGEL: The genome project hasn't just raised hopes -- but also worries. Do you understand those concerns?
Venter: Yes. There are two groups of people. People either want to know the information or they prefer to live like an ostrich with their head in the sand, not knowing anything. The fear is based on the ill-founded belief that those who know the DNA sequence also know every aspect of life. This nonsense has been spread by the same geneticists who were afraid of the commercialization of this stuff. From the time of the first few discoveries of gene defects -- Huntington's disease, for example, everybody thought that if you knew your genome, you would know when you would die and what you would die from. That is nonsense.
SPIEGEL: So the significance of the genome isn't so great after all?
Venter: Not at all. I can tell you from my own experience. I put my own genome on the Internet. People had the notion this was the scariest thing out there. But what happened? Nothing.
SPIEGEL: Nevertheless, Jim Watson, the co-discoverer of the DNA double helix, has said he doesn't want to know which variant of the so-called ApoE gene he has -- it could say something about his risk for developing Alzheimer's, and he's afraid of that …
Venter: That was silliness. At that age? Watson is over 80.
SPIEGEL: Are you interested in finding out what ApoE variant you have?
Venter: I know it. And according to it, I have a slightly increased risk for Alzheimer's disease. But it impresses me little because I could have dozens of other genes that counteract it. Because we do not know that, this information is meaningless.
Part 2: 'We Couldn't Even Be Certain from my Genome What My Eye Color Was'
SPIEGEL: And what about the fears about the abuse of gene data through insurers or employers, for example? Do you see that as sheer hysteria?
Venter: Abuse is not a question of whether the data is available. It is an issue of laws. You can't do anything to change the availability of genetic data. Look at this bottle that you have touched -- that's all I need to obtain your entire genetic information.
SPIEGEL: How much would you be able to learn about us by doing so?
Venter: If anything, we don't really know how to read the genome and it can't tell us very much right now. So what's the ethical debate about?
SPIEGEL: The decoding of your personal genome has so far revealed little more than the fact that your ear wax tends to be moist.
Venter: That's what you say. And what else have I learned from my genome? Very little. We couldn't even be certain from my genome what my eye color was. Isn't that sad? Everyone was looking for miracle 'yes/no' answers in the genome. "Yes, you'll have cancer." Or "No, you won't have cancer." But that's just not the way it is.
SPIEGEL: So the Human Genome Project has had very little medical benefits so far?
Venter: Close to zero to put it precisely.
SPIEGEL: Did it at least provide us with some new knowledge?
Venter: It certainly has. Eleven years ago, we didn't even know how many genes humans have. Many estimated that number at 100,000, and some went as high as 300,000. We made a lot of enemies when we claimed that there appeared to be considerably fewer -- probably closer to the neighborhood of 40,000! And then we found out that there are only half as many. I was just in Stockholm for the 200th anniversary of the Karolinska Institute. The first presentation was about the many achievements the decoding of the genome has brought. Then I spoke and said that this century will be remembered for how little, and not how much, happened in this field.
SPIEGEL: Why is it taking so long for the results of genome research to be applied in medicine?
Venter: Because we have, in truth, learned nothing from the genome other than probabilities. How does a 1 or 3 percent increased risk for something translate into the clinic? It is useless information.
SPIEGEL: There are hundreds of hereditary diseases that can be traced to defects in individual genes. You can determine a lot more than just probabilities through them. But that still hasn't led to a flood of new treatments.
Venter: There were false expectations. Take Ataxia telangiectasia, for example, a horrible disease. The nervous system degenerates, and people who have it often die in their early teens. The cause is a defect in a single gene, but it is a developmental gene. If your body is built in the wrong way, then you can't just take a magic pill to rebuild it. If your brain is wired wrong, then it is wired wrong.
SPIEGEL: Who is to blame for those false expectations?
Venter: We were simply always looking at single genes because they were the only genes we had. When people lose their keys at night, they look under the lamp post. Why? Because that's where you can still see something.
SPIEGEL: But the keys are really located in the dark?
Venter: Exactly. Why did people think there were so many human genes? It's because they thought there was going to be one gene for each human trait. And if you want to cure greed, you change the greed gene, right? Or the envy gene, which is probably far more dangerous. But it turns out that we're pretty complex. If you want to find out why someone gets Alzheimer's or cancer, then it is not enough to look at one gene. To do so, we have to have the whole picture. It's like saying you want to explore Valencia and the only thing you can see is this table. You see a little rust, but that tells you nothing about Valencia other than that the air is maybe salty. That's where we are with the genome. We know nothing.
SPIEGEL: Do you think there will be a time when you can extract all this information to yield real medical results?
Venter: For that to happen we need a lot more information: Information about your body's chemistry, your physiology, your complete medical history, your brain and your entire life. We would need to do that a million times on different people and correlate that data with their genetic information.
SPIEGEL: Will that lead in the end to the kind of personalized medicine that genetic researchers have always touted? Each person would get his or her own personal treatment that is tailored precisely to that person's genetic make-up?
Venter: That was another one of these silly naïve notions that was out there. It's not, 'Oh, we know your genome, we're going to make this drug for you.' That will never happen. It is more important that you use the information in the genome about your personal risks and reduce them through intelligent behavior.
SPIEGEL: You have complained about how naïve genome researchers were in the beginning. Will future generations eventually make fun of us in the same way for how naïve we still are today?
Venter: Only time will tell. Nevertheless, we now have what is going to be one of the most important tools for interpreting the human genome: the first synthetic cell. It will enable us to ask questions that would have been inaccessible before.
SPIEGEL: When no progress was made through the reading of the genome, you shifted to rewriting it. You sequenced the entire genome of a bacteria and used it in another cell. How is the microbe you created doing today?
Venter: It's sitting in a freezer, doing extremely well. We'll keep it for the historians.
SPIEGEL: You stored a code in the genome of this cell. Has anyone decoded it?
Venter: Yes, it is the first genome in the world to include an e-mail address. So far, 50 scientists have cracked the code and answered us.
Part 3: 'We Don't Need Any More Neanderthals on the Planet'
SPIEGEL: Many fear what might happen if humans craft new life forms. They repeatedly say that you are playing God …
Venter: Yes, and I find them frightening. I can read your genome, you know? Nobody's been able to do that in history before. But that is not about God-like powers, it's about scientific power. The real problem is that the understanding of science in our society is so shallow. In the future, if we want to have enough water, enough food and enough energy without totally destroying our planet, then we will have to be dependent on good science.
SPIEGEL: Some scientist don't rule out a belief in God. Francis Collins, for example …
Venter: … That's his issue to reconcile, not mine. For me, it's either faith or science - you can't have both.
SPIEGEL: So you don't consider Collins to be a true scientist?
Venter: Let's just say he's a government administrator.
SPIEGEL: When can we anticipate seeing the next tailor-made microbes from your laboratory?
Venter: Well, the goal is multifold. We have to start by creating minimal cells. A human cell is too complex -- we have no idea how any human cell works. We don't even know how the simplest bacterial cell works. We want to learn what the minimum cellular components are, so we're going to be taking out all the non-essential genes. But we're also trying to design new life forms for energy production, capturing carbon dioxide or to produce chemicals.
SPIEGEL: Wouldn't it be easier to modify existing bacteria using the established methods of biotechnology?
Venter: It isn't that simple. For example, there is no other way of creating a minimal cell. You can only add or take out genes at will if you have built the genome from scratch.
SPIEGEL: How long does it take to create such new forms of cells?
Venter: Right now we have the technology to make several a day, and the goal is to make a million a day.
SPIEGEL: How long will it be until the life forms you have created start producing fuel for our cars?
Venter: Not only gasoline. Plastic, asphalt, heating oil: Everything that we make from oil will at some point be made by bacteria or other cells. Whether that is in five, 10 or 20 years is unclear. Why don't we have fuel now other than alcohol from microbes? It's because nothing evolved that can produce great amounts of biofuel out of CO2. That's why we have to make it.
SPIEGEL: ExxonMobile, at the very least, appears to be convinced by your vision …
Venter: … yes, they are investing $600 million in the project, with half going to our partnership. It's a good round number. It's the same money that PerkinElmer gave me to decode the human genome. With it, we sequenced the human genome in nine months instead of many, many years. The public money that flowed into the Human Genome Project, above all, created an enormous, inflexible bureaucracy. And it is only because of private money that we can now sail across the ocean with this sailboat and discover 40 million genes -- there are only 41 million genes known to all of science. All you need are a few innovative ideas and independent funding to allow you to do things that other people can only dream about.
SPIEGEL: It took eight years from the time the first bacterial genome was decoded until the human genome was completed. How much time will elapse between the creation of the first synthetic bacteria and the creation of the first synthetic human?
Venter: There is currently no reason for us to synthesize human cells. I am, for example, a fan of the work that was done a short time ago that led to the decoding of the Neanderthal genome. But we don't need any more Neanderthals on the planet, right? We already have enough of them.
SPIEGEL: Mr. Venter, we thank you for this interview.
Interview conducted by Rafaela von Bredow and Johann Grolle
GenePlanet in Europe makes Genome Testing Global
GenePlanet.com
Headquarters:
Gene Planet Limited
Upper Pembroke Street 28
Dublin
Ireland
Logistics centre and research:
GenePlanet d.o.o.
Technology park Ljubljana
Teslova 30
Slovenia
GenePlanet genetic testing service starts with us sending you a saliva collector by mail. In the laboratory we extract your genetic material which is used to perform the analysis. As a result you will find out to which diseases you are susceptible, what effect do certain medications have on you, what are your talents and special abilities, as well as who are your ancestors.
Your personal genetic testing is now available at 549$ / 399€.
A list of diseases, talents and medications, tested by GenePlanet
Genetic testing for disease susceptibility
ARMD
Alzheimer`s disease
Ankylosing spondylitis
Asthma
Coronary artery disease
Atrial fibrillation
Bipolar disorder
Breast cancer
Celiac disease
Crohn`s disease
Depression
Dyslexia
Endometrial cancer
Gallstones
Hypertension
Long QT interval
Lung cancer
Multiple sclerosis
Peripheral arterial disease
Prostate cancer
Psoriasis
Restless leg syndrom
Rheumatoid arthritis
Type 1 diabetes
Type 2 diabetes
Genetic testing for medicament response
Beta blockers and heart
Beta blockers and tension
Efficacy of Aspirin
Headache and triptans
Statins against heart attack
The effect of antidepressants
The secret of Viagra
Genetic testing for traits and talents
Alcohol flush reaction
Avoidance of errors
Birth weight
Bitter taste perception
Earwax type
Effect of breastfeeding on IQ
Episodic memory performance
Eye colour
Fat intake and BMI
Freckles
HDL cholesterol level
Lactose intolerance
Malaria resistance
Measures of intelligence
Memory of older people
Muscle explosiveness
Norovirus resistance
Odour detection
Pain sensitivity
Skin colour
Nicotine dependence
With Geneplanet genetic testing, you can reveal what is written in your genes, it helps you understand the effect of genes on your life and advises how to make the most of your genetic advantages.
[GenePlanet released the Genome Testing genie completely out of the bottle. Silicon Valley is losing jobs left and right. Meanwhile, the Seoul (Korea) DTC picked up the Asian market. Now, after DeCodeMe in Iceland, GenePlanet metastased Genome Testing business on the Planet to Europe, with its Headquarters in Ireland, and labs in Slovenia - that some politicians can't even distinguish from Slovakia. Independent if US inventors (etc) like it or not, Genome Testing DTC is beyond control of US - Pellionisz_at_JunkDNA.com]
Pfizer to Study Liver Cancer in Korean Patients with Samsung Medical Center
GEN
Jul 14 2010
Pfizer formed a research partnership with Samsung Medical Center to generate gene-expression profiles of tumors from Koreans with liver cancer. The hope is that the findings will lead to targeted therapeutics that can be used not just in Korea but also in the rest of Asia.
A research team led by Samsung Medical Center scientists including Prof. Park Cheol-Guen, Prof. Im Ho-Young, and Prof. Paik Soon-Myung, director of the cancer research center, will conduct research in Seoul. Neil Gibson, Ph.D., vp of oncology research, will be responsible for the joint research program at Pfizer.
Samsung Medical Center has built a base of specimens in the liver cancer area. “This partnership will serve as a great opportunity to combine Pfizer's know-how in drug development and Samsung Medical Center's extensive genome information and technology in the liver cancer area,” says Dr. Gibson. “We further plan to share the ownership of collected and analyzed data with Samsung Medical Center.”
Pfizer signed a memorandum of understanding with the Ministry of Health and Welfare in 2007, agreeing to invest $300 million in R&D in Korea. As part of its commitment, the company also formed a strategic partnership with the Korea Research Institute of Bioscience and Biotechnology and has been leading joint research since then.
In February Pfizer linked up with Eli Lilly and Merck & Co. to set up the Asian Cancer Research Group (ACRG) to concentrate on drug R&D for the most common cancers in Asia. The nonprofit company will initially focus on lung and gastric cancers, which are two of the most common cancers in Asia.
The aim for ACRG is to generate a pharmacogenomic cancer database comprising data from about 2,000 lung and gastric cancer tissue samples. The resulting data will be made publicly available to researchers and expanded through the addition of clinical data from a longitudinal analysis of patients.
The ACRG will initially establish collaborative relationships throughout the Asian region to collect tissue samples and data. “The ACRG is about sharing information for the common good,” stresses Kerry Blanchard, M.D., Ph.D., vp and leader of drug development in China for Lilly.
Lee Min-joo donates 3 billion won to genome project
2010-07-26 16:45
Lee Min-joo, 62, chairman of Atinum Partners, a Seoul-based privately held investment company, donated 3 billion won ($2.5 million) Friday to the Asian Genome Road Project being conducted by the Genomic Medicine Institute at Seoul National University.
The Asian Genome Road Project aims to establish an Asian-specific genome database by sequencing individuals from across Asia, including South Koreans, Mongolians and Turks. Genome analysis will make it possible to individually tailor medical treatment.
The donation pledge was a result of year-long discussions between Seo Jeong-sun, director of GMI-SNU, and Lee about the significance of the project.
Deputies of Atinum Investment Chairman Lee Min-joo deliver his donation to Genomic Medicine Institute, Seoul National University on Friday. From left are GNI-SNU director Seo Jeong-sun; SNU College of Medicine assistant dean for academic affairs Choi Jin-ho; Atinum Partners President Chung Kyung-soo and Atinum Investment President Shin Ki-chun.
GNI-SNU
Lee has shown keen interest in the health care business. The Yonsei University graduate who majored in applied statistics started up a toy company in 1975, and grew it remarkably. Around the 1997 financial crisis, he began a regional cable television business. In March, 2008, he sold C&M, one of the largest cable TV networks in the Seoul area, to a group of investors led by Macquarie, an Australian financial company, for about 1.45 trillion won.
Lee then began to invest more boldly. For the first time as a private businessman in Korea, he acquired Sterling Energy plc, a U.S. oil company, for $90 million in December, 2009. Along with an increase in investment, he reportedly has donated about 30 billion won to Yonsei, KAIST, Myongji University and Seoul Women’s University. Atinum Partners has assets under management of over $1.5 billion.
Lee is known to have a business philosophy that investment and donation should be based on a vision of a future society and the changing needs of people.
The low-profile businessman, who refrains from public appearances, did not attend the donation ceremony held at a meeting room of the College of Medicine, Seoul National University. Instead, he sent his deputies to the event.
Seo is a pioneer in Asian genome study; his research group recently published his work on Korean whole genome analysis, being the fourth group in the world to publish a whole genome study in Nature utilizing next-generation sequencing technology. His group also completed the whole genome analysis of a Korean female, which will be the first Asian female whole genome sequence published.
[The two articles above (shipping potential US jobs to Asia, according to economics of global business) and the two articles below (shipping potential US jobs to Asia, if an overzelous "regulation" in the US would happen) could be viewed through the looking glass of Andy Grove (former CEO of Intel and a major donor to Parkinson's research). Andy Grove argues in Bloomberg BusinessNews that unless the USA finds ways to create jobs, we face a grim picture. It is known that some venture philanthropists set as a requirement that jobs must be created on their money. Suppose those who donated so generously to Parkinson's research, and e.g. an other industry giant who might contemplate donating new funds to liver cancer research would unite, and seed a "Full DNA Analytics Center" in Silicon Valley, where two of the leading sequencer companies are about to deluge genomics with sequences, yet it is questionable if "is IT ready for the dreaded DNA data deluge" - with the requirement that a certain percentage of their funds must create Silicon Valley jobs? - Pellionisz_at_JunkDNA.com]
Working with regulators—the road ahead
July 27, 2010
Navigenics,
Validity. Accuracy and quality. Clinical relevance. Security and privacy. These were among the top themes highlighted over and over when federal officials convened a series of meetings and hearings last week in the Washington D.C. area to discuss the prospects for personal genomics services and other innovative types of health-related tests.
For long-time readers of this blog, these ideas are nothing new. When Navigenics launched its personal genome service more two years ago, we issued a 10-point proposal for a set of industry standards to ensure the integrity of this new field of science and health and safeguard consumers. We reiterated the need for these principles again early last year, when we helped the Personalized Medicine Coalition convene a meeting on standards for personal genomics services.
So when last week’s events kicked off with a two-day meeting called by the U.S. Food and Drug Administration, we were pleased that the need for industry standards has been acknowledged at a high level. At the gathering of experts in health, genetics, science, and the law, many good points were raised and excellent ideas exchanged. Navigenics was among a group of leading personal genetics companies that presented a company overview to the gathering, and our CEO, Vance Vanier, M.D., was the only executive from a personal genomics service given the opportunity to speak on a panel. In its inclusiveness, broad discussion, and scientific rigor, the FDA meeting reflected the type of approach and expertise that will be required to develop effective standards for personal genomics.
The next day, however, saw a very different – and less productive – atmosphere come to light. On Capitol Hill, a subcommittee of the House of Representatives’ Committee on Energy and Commerce held a hearing on “Direct-To-Consumer Genetic Testing and the Consequences to the Public Health.” A key part of this hearing was a report by the Government Accountability Office, or GAO, on 15 personal genetic testing companies.
The ultimate aim of the GAO report was to inform and protect consumers. At its best, the report sheds further light on an important and well known issue in the personal genomics field – how the current lack of regulatory standards can lead to very different approaches between personal genetics companies. But as the writers of the report acknowledged, they “did not conduct a rigorous scientific study.” As a result, many of the report’s findings are anecdotal, partially informed, or incomplete.
We would have been happy to work with the authors of the report to answer any questions or provide further information along the way. Our CEO testified at the hearing, and we filed thousands of pages of informational documents with the committee before the hearing. But Navigenics was not permitted to see the report before its release. Nor were our company’s representatives even allowed to see a copy at the hearing itself. As a result, we could not always fully address questions from Congressional representatives during the hearing, and regret not having been given the opportunity to prepare all the answers that were sought.
Furthermore, the report makes assertions using incomplete information. We have made a formal request to the GAO for the detailed information behind these assertions. Should that detailed information be forthcoming, we are confident we can address any issue arising from the report. We are also appreciative of the fact that Congressional representatives, realizing the many questions left open by the report, extended the period of time to submit additional information for another 10 days. We look forward to submitting additional input to provide a more complete, more accurate picture of our company and our industry.
In the meantime, we will continue to pursue the path we started on more than two years ago. Our discussions with the FDA began even before our service first launched, and we most recently met with FDA officials in May of this year. We look forward to working further with the FDA to develop regulations for our industry at our next meeting with the agency next month. We also look forward to upcoming scientific studies of personal genomics services conducted by researchers at institutions such the Scripps Translational Science Institute, the Mayo Clinic, and Johns Hopkins. These studies, conducted with scientific rigor and involving participants whose only agenda was better understanding of themselves through their personal genetics, will provide useful, informative insights into how consumers interact with genetic information.
As plans for regulation unfold, we stand by our science, our service, and the standards we first proposed in 2008. The FDA, along with other federal officials, is making productive steps towards a new framework for our industry. We look forward to continuing to be part of the discussion.
[The question is not, if GAO will provide an answer - bureaucrats are paid (by our tax dollars) to produce papers. More interesting is the question if Dr. James P. Evans, M.D. will continue lending his reputation to "certify the uncertifiable"; i.e. make an admittedly "non-scientific" set of assertation of the GAO insinuation of "collective guilt", by his standards,"scientific". Prediction is clearly "NO". In some sense the outcome of the Congressional Subcommittee's investigation was predictable, once it became evident that Chairmanship was assigned to a "lame duck" politician, who had announced his retirement from politics weeks before this (inconsequential to him) "final act" - and thus will not be available to rectify a historical insult to a class of pioneer scientists, e.g. by his careless sound bite "From Gulf Oil to Snake Oil". In a larger sense, it has increasingly became evident that a multi-agency expert panel would have to propose new legislation to bring the 1976 mandate of FDA up-to-date - but the political will is simply not there to see through many years (or decades...) while Congressional Legislation would entangle itself in an exercise of futility of trailing an escalating Genome Revolution that they simply don't even pretend to understand even today. Thus, the Congress "won a battle" - but the FDA "lost the war". The extremely blunt Congressional "final act" now forces the FDA to come up with some solution, it will have to go out on a limb by resorting to "out-of-the-box solution" - without the kind of legislative background that forced them to inaction thus far, in the first place. It seems logical, therefore, that FDA will seek some sort of a "consensus" that practically makes a lot of sense - except that FDA would either take the heat of legal challenges (forcing the Judiciary to become Experts in Genomics, a very unlikely scenario, or -much more likely-) make FDA conclusions just watered-down "recommendations" for a largely self-regulated industry. It is worthy of mentioning that e.g. software industry is "self-regulated" as the market screens out inferior software without any need (or possibility) of regulators plunging into source-codes. It is important to emphasize the difference between "regulation" and "punishment of criminal actions"; e.g. if a largely unregulated software is "pirated" or "falsely advertised", certainly such inadmissible act could and should be penalized. Careful observer may note that most conspicuous allegations by GAO of unnamed SNP-DTC may fall into the across-the-board category of "false advertisement" (by some marketing and sales people), and not at all pertaining to the underlying science- AJP]
GAO Studies Science Non-Scientifically
July 23, 2010
Published by 23andMe at 11:53 am
As we posted here on the Spittoon yesterday, the Subcommittee on Oversight and Investigations of the House of Representatives Committee on Energy and Commerce held a hearing on “Direct-To-Consumer Genetic Testing and the Consequences to the Public Health.”
Central to this hearing was an investigation by the Government Accountability Office (GAO) into 15 DTC genetic testing companies.
The GAO refused to discuss its concerns or its report with 23andMe, and now that the report is public and we have had a chance to review it, we are troubled and find the report is deeply flawed. We note that while such an exercise as conducted by GAO has the potential to raise questions, it does not provide the answers that a more rigorous scientific study would provide. This report raises questions, but leads to few conclusions because of its unscientific nature. The GAO itself recognizes this, writing, “It is important to emphasize that we did not conduct a rigorous scientific study.…"
...We are confident in our service’s accuracy and reliability. It is widely accepted that the technology we are using is sound. We understand that GAO did not find any problem with the underlying data that we provide – the As, Cs, Ts and Gs. What is at question is whether or not one part of the information about that data that we provide is of value, and we believe strongly that it is.
The GAO report focused only on disease risk probabilities. It did not focus on ancestry or the trait reports we offer. It also failed to address that we also provide information about carrier status for single gene diseases such as cystic fibrosis and Tay-Sachs disease, as well as the fact that we provide information about a customer’s likely response to certain prescription medications that have been shown in clinical trials to have differing effects and side effects depending on a person’s genetic make-up. This suggests that GAO found no problems with these parts of our service.
Carrier status and drug response information are clearly useful. In fact, Dr. James Evans, the Director of Adult Genetics Services at the University of North Carolina and the Editor-in-Chief of Genetics in Medicine, admitted during the Congressional hearing that drug response information would be of great interest to him as a physician. (He was specifically referring to results pertaining to a patient’s sensitivity to the anti-viral medication abacavir.) It should be noted that during the hearing it was not clear that Dr. Evans had been the primary consultant to GAO regarding the scientific and medical relevance of the results provided by DTC genetics testing companies.
The remarks made by 23andMe Co-Founder Anne Wojcicki and General Counsel Ashley Gould at the FDA public meeting on July 20, 2010 about laboratory developed tests demonstrate the importance of the work we are doing and our commitment to ensuring that members of the public are provided unfettered access to their DNA information in a responsible manner. We embrace the ideas that the FDA offered today about stepping in to provide a regulatory framework and help set scientific and transparency standards across the industry. We look forward to helping with this process.
Read on for discussion of some of the problems with the GAO report.
One of the most unfortunate parts of the GAO report is that it unfairly lumps together reputable and well known companies such as 23andMe with un-named companies making verifiably untrue endorsement claims, spurious scientific claims, and also selling potentially fraudulent supplements in addition to genetic testing services. Some of the most troubling of these interactions between the GAO and genetic testing companies can be found in a table on pages 15-16 of the GAO report, and in a Youtube video the Office has posted.
It must be noted however, that although the companies are not identified in the video or the report, at the hearing it was revealed that 23andMe is Company 1. Other than saying that we believe customers should consult with their physician or other healthcare professional when they have questions about their data, 23andMe/Company 1 is not implicated in any wrongdoing.
GAO seems to believe that directing consumers with questions about their genetic information to their health care professionals (a stance we continue to stand behind) is “misleading” because of a pronouncement by the Department of Health and Human Services’ Secretary’s Advisory Committee on Genetics, Health and Society that physicians “cannot keep up with the pace of genetic tests and are not adequately prepared to use test information to treat patients appropriately.”...
We agree with the idea that consumers should be able to compare the risk predictions they might receive from different test providers. This is an issue that deserves serious attention and one that we believe can be solved by the implementation of broad standards throughout the industry. We have approached both the NIH and FDA for assistance in this matter (see this letter sent to the heads of both agencies and posted on our blog, The Spittoon). Instead of constructively adding to these efforts, GAO has instead implied that because results differ between companies, they are simply wrong. Their report fails to provide all relevant information, and perpetuates the misunderstandings of genetics in particular and science in general that 23andMe has since the very beginning been dedicated to changing....
In conclusion, 23andMe is extremely disappointed that we did not have the opportunity to address all of these concerns at the Congressional hearing, or sooner, due to our lack of access to the report. These are serious issues that deserve serious and thoughtful discussion. Standards are needed in the genetic testing industry. We have been working towards these since the inception of our company, and we were pleased to hear FDA say that they are interested in developing a new type of regulatory framework that can deal with the many special aspects of direct-to-consumer genetic testing while still providing consumers with the protections they need and deserve. 23andMe is meeting with the FDA today and looks forward to fruitful discussion.
[Politics, while at face value won the "battle of SNP-DTC", by its glaring inability lost the war of suffocating US-political control over the emerging global genome industry. It is already leaked out that a "completely out-of-the-box" (legal?) "solution" is emerging, to save FDA from having to rely on non-scientific studies of science (see below).
The huge question therefore is, for SNP-DTC industry, how to mitigate the sizable political damage inflicted in the public's eye (made much worse by sensationalist parts of the media further distorting reality - since most of the public might not have the time/expertise to sort out the complex science issues). Since the SNP-DTC industry is unanimously committed to advance to include analytics of full human DNA sequences anyway, an acceleration might be an answer, to make SNP-DTC transitory to full DNA analytics, made interoperable with digitalized health-records, and all overridden by personal decisions. The damaged market-appeal of "SNP-DTC alone" could thus regain ground and even spectacularly increase market-demand by a "genome computing architecture" as featured on solid scientific ground of "recursive genome function" as early as in 2008, embraced by a panel in 2009, developed for the PMWC2010 this January, and in stealth-mode breaking through just at this time when SNP-DTC just suffered a major public relation set-back. - Pellionisz_at_JunkDNA.com]
...Some lawmakers, including Committee Chairman Bart Stupak (D- Mich.), asked Shuren if FDA decided it wanted to regulate DTC genetics companies how it would go about doing so.
Shuren said that, currently, FDA is considering taking "a completely out-of-the-box approach on genetic testing" that would carve out a unique space in its regulatory tableau. This approach could involve looking at subsets of validation data on genetic variants that would enable regulators to make assumptions to trust the industry partners about some of the others.
"What we're thinking about is FDA, along with [the National Institutes of Health], pulling in from the healthcare community, pulling in from patient groups, and actually sitting there and going through the science," Shuren said.
He explained that such a regulatory council could set standards based on the available science and on the breadth and scope and veracity of the claims that the company is making in its marketing.
"And when we set the standards of what's good enough and when it's ready, then [we would] allow those claims. Those companies then would not have to come back in the door with a new application. We'd say, 'You already have a validated test, you can now make this claim,'" he said.
Shuren said that such a regulatory approach would "allow for a lot of tests to be out there" and that it "would actually be a much less expensive way of doing it for these companies as well."...
DTC Genome Testing of SNP-s “Ready for Prime Time”?
Of course not. “What is the practical value of a baby?” Francis Collins quoted on his interview by Charlie Rose the “inventor of electricity” (Faraday) when he was naively asked by the British Prime Minister visiting his laboratories “is there any practical value of electricity?” Should Faraday have today’s hyper-hyped salesmanship and marketing-frenzy around, he could have (rightly) answered “the practical value of electricity can not be overestimated”. Instead, he gave the disarmingly smiley answer about the utility of a newborn baby…
As I commented in this column on the original assessment by Boonsri Dickinson, tested years ago by the three leading DTC genome testing SNP interrogation companies (DeCodeMe, 23andMe, Navigenics), her summary (that “they were not ready for Prime Time”) was absolutely correct.
Interrogation of up to about one million single nucleotide polymorphisms (SNP-s, out of 6.2 Bn nucleotides in the diploid full human DNA) ab ovo can not be “Prime Time News”, perhaps just the “First News of the Day at 5 A.M.” As HolGenTech, Inc. presents in the 7:44 minutes short YouTube, “Prime Time” will be a show for a future “Boonsri Dickinson” where “SNP interrogation” (presently done by DTC, using microarray technology) is interoperative with personal “full DNA sequences” (already in production at $5k per full genome, whole-sale by Complete Genomics, and PacBio is about to deluge the world with full DNA sequences with 6.2 Bn bases for about the price of “1 million bases in present DTC”), as well as with “digitalized health data” (on servers like Microsoft HealthVault and/or Google Health), all overriden by “personal preferences” (on Personal Genome Computers).
We’ll need some time/money to get there. PacBio alone absorbed about $350 M in funding, full digitalization of health data will cost billions of dollars, and Genome Computing will need substantial resources (HolGenTech already accomplished a major – stealth - breakthrough with its solution even since the YouTube was taken half a year ago).
Maybe it is 7’ Clock News in the Morning?
Sorry to say, we've just been set back. Those watching the Congressional Investigation of current DTC had to witness today, however, an ugly “wet blanket” thrown in the face of some testifying DTC company officials, dampening their smiles by an embargoed surprise-report by undercover agents of the Government Accountability Office (GAO).
Back to 5:30 A.M.?
Not really. The report admits (the obvious) in its opening “Highlights” that “GAO did not conduct a scientific study”. Normally, since the topic is the utility of genomics as a science in a nascent stage, a judge would through out right away such glaringly and admittedly “inadmissible evidence”. However, the Congressional Subcommittee is neither a Forum of Science, nor is part of the Judiciary. It can do politics (easy job) or create new legislation to update e.g. the FDA mandate (1976; hard job). Clearly, the entire set-up by GAO to frame DTC verbally as “not ready for prime time” (though this – copyrighted? -coinage, "borrowed" from Boonsri Dickinson's remark made years ago nowhere appears in the written Report) was not at all about science, but about (also well known) deficiencies of marketing and sales. It may be sobering to Congress to realize that their laws are also often misrepresented by “marketing and sales” forces (in their profession called “the press”) for political purposes.
The community of researchers may wonder if hard-working pioneer scientists deserve better; e.g. the use of (available, see below) peer review instead of questionable practices of non-scientist undercover agents of “Big Brother”, who not only admit but brag about their using fictitious profiles of users (and thus getting confusing answers; a well known effect in science; “garbage in – garbage out”). Are you surprised that a Caucasian (non-scientist) customer giving the deliberately false profile that she is "Asian" is getting "off the chart" results? I am not surprised. Nor is anyone who knows how different are the genomes of Chinese (at least 9 main tribes) and various European genomes (dozens).
It is too bad, that the general media, in their rush-reporting (not always scientist-checked) further distorts the misimpression: Bloomberg reports:
“Gene-Test Services Mislead Public, U.S. Report Says” [Would it not be a better title: "U.S. Report Misleads Gene-Test Services"? - AJP]
“Gregory Kutz led a probe for the Government Accountability Office by setting up customer accounts with Navigenics of Foster City, California, 23andMe Inc. of Mountain View, California, Pathway Genomics Corp. of San Diego and DeCode Genetics Inc. of Reykjavik, Iceland, and sending them DNA from five people. The companies’ reports assessing health risks were “medically unproven and so ambiguous as to be meaningless,” Kutz said in his report, presented today at a hearing in Washington”
This brutal error is easy to spot. The Report (both in its “Highlights” and on its Page 1.) clearly states that the findings of “medically unproven and so ambiguous as to be meaningless” were in the previous GEO Report four years ago (in 2006), referring to four “Nutrigenetic Testing” websites (not the same set as currently investigated) and states at the outset of the (2010) “Highlights” that “new companies have since been touted as being more reputable”. Still in total confusion, the general newsmedia attributes the obsolete statement of one set of companies four years ago to the present state of the art of a different set of companies!
A third glaring error is, that it was verbally stated at the hearing, as if an accusation, that DTC provides “medical advice”. Such statement actually never appears in writing in the Report – moreover all (good) mothers provide “medical advice” to their kids, e.g. “eat more vegetables”, “drink more water”, “exercise”, “use sunscreen lotion on the beach” (etc). A good mother might be keenly aware of the medical fact that a fair-skinned child might develop (potentially deadly) melanoma e.g. if exposed in a prolonged manner to the intense California or Arizona solar radiation. Should she refrain from transmitting “medical advice” to her loved ones? Clearly absurd. The web, too, is teaming with all kinds of advice and recommendations; often quite medical. This is not a problem. The problem would be if mothers, friends (etc) would provide medical advice while pretending that they are licenced medical doctors. To the contrary, however, all DTC websites clearly indicate that their recommendations are not to be confused with, and not instead of, prescriptions and/or diagnosis and/or therapy and/or cure by licenced medical doctors!
In the hearing, the available “peer review” was conspicuous by its absence. Neither Founder and CEO of the first ever DTC genome testing company DeCodeMe in Iceland (warned by a US-letter) Kari Stefansson (actually, not only a World-leader genomist but also a Medical Doctor and Ph.D…) was forgotten to have been invited to testify to Congress – in addition to (or instead of) non-scientist under-cover agents but the “peer” who literally wrote the exceptionally lucid yet scientifically rock-solid book on Genome Testing as a basis of Personalized Medicine, Francis Collins, M.D., Ph.D., Head of NIH, formerly head of the “Human Genome Project” was not called as witness, either. Though Dr. Collins, M.D., Ph.D., in his quality as Head of NIH, just weeks ago co-authored in the New England Journal of Medicine the “laying down of the path towards Personalized Medicine” with FDA Commissioner Margaret Hamburg, M.D.
We can all hope – the real witnesses have not been summoned yet. However, the damage inflicted upon the US innovation, jobs and the economy is outrageous and calls for an emergency repair.
[Further coverage is here here here -241 in all, before the end of the day - AJP]
Message arrived ... "the scientific community had to re-think long held beliefs"
Perhaps the best coverage of the 10th Anniversary of "The Human Genome Project" was the interview by Charlie Rose with skeptic NYT reporter Nicholas Wade, and two top scientists of the establishment, Drs. Francis Collins (NIH Chief) and Eric Lander (Director of the Broad Institute and Science Advisor to the President).
As seen from the screen-shot taken on July 16 eve (PT), there was a huge peak of close to a million hits for "recursive genome function". Apparently, the message of the Rose interview arrived; the Second Decade will be about "recursive genome function". To remind readers, a short clip from the copyrighted transcripts is here:
[Excerpts are available in full on Charlie Rose' website. Here, only the brief "conclusion" is reproduced from the copyrighted material - AJP]
"... CHARLIE ROSE: Have there been any operating hypotheses that have been proven to be not the best route to go?
FRANCIS COLLINS: Oh, goodness.
ERIC LANDER: That’s a good question. What do you think, Francis?
FRANCIS COLLINS: I think perhaps our original expectations about what was going on in the genome that was not coding for protein may have underestimated the complexities of what’s going on there. New discoveries about micro RNAs and something from Eric’s group called link RNAs, a whole new category of RNA transcripts that have really opened our eyes to regulation and sophisticated complexities. That’s been exciting and I don’t know that we anticipated that. [Some do know to have anticipated. Prior to even NIH asking Congress for money for ENCODE I publicly announced FractoGene (2002) - AJP]
ERIC LANDER: I think that’s an interesting and important point. The genome has a lot more secrets in it. But by laying out the whole sequence of the genome, we were able to find that, oh, one percent of the genome encoded for the proteins that we’d been focusing on before, the hemoglobins and collagens and things, and three or four times as much of the genome is devoted to other things. [Four times? Why not say forty-four times of the 1.3% of protein-coding "genes"? - AJP]
We knew this because in fact evolution conserved those sequences telling us they had to be functional. So shining a light for us on things we’d never known about, gene regulation ..."
GenomeWeb
July/August 2010
By Matthew Dublin
Personalized medicine — the crossroads at which biotechnology, genomics, and medical treatment meet — is a concept that is often touted, though rarely seen in action. As with any radical idea, there needs to be a proving ground before it achieves wider acceptance among professionals and the public. The concept of a healthcare system that can someday provide predictive, preventive, personalized, and participatory medicine, or "P4 medicine" — a term coined by Leroy Hood of the Institute for Systems Biology back in 2003 — is being put to the test.
In early May, The Ohio State University Medical Center and ISB announced a partnership to establish the P4 Medicine Institute, a nonprofit consortium based in Seattle. The new institute's mission is the delivery of a healthcare model with the four-pronged "P" approach, through which patients can be treated proactively throughout their lifetime, instead of the current model of reactive clinical treatment.
While ISB is positioned to bring its biotechnology expertise to the table, OSU's clinical delivery infrastructure, including its own insurance company OSU Health Plan, will give the P4 a chance to try out lots of new ideas in a closed system with roughly 55,000 university employees enrolled in the campus health plan. By creating a matrix of genomics, protein metabolics, and molecular-based diagnostic information tailor-made for each patient, the leaders of the P4 Medicine Institute hope to map out individualized plans for health maintenance, wellness evaluation, and the diagnosis and treatment of illness.
"We're working on trying to come up with an understanding of how the healthcare system can be changed from one that is disease-based care, without an understanding of the real deep, precise biology underlying the health and wellness, to one which really looks at predicting and preventing disease by focusing on wellness in a very personal way," says Clay Marsh, executive director of Ohio State's Center for Personalized Healthcare. "We see the P4 Medicine Institute as a conduit for connecting the best people in the world, for really transforming how we do things. Our goal is to try and connect with the best people and, as a team, really define where the healthcare ecosystem is today — what elements are needed to create a tipping point or create a culture change that will transform medicine — and work as a group to do that."
Putting it together
Part of the new institute's strategy to bring genomics-based healthcare to the clinic is to connect researchers working in biology and medicine with those working in computer science and IT, as well as bringing in thought leaders from the legal, business, and medical device manufacturing sectors. "P4 is really about combining the systems biology-driven innovations and insights into human biology of ISB and the translational research and clinical delivery capabilities of one of the largest academic medical centers in the country," says Frederick Lee, the executive director of the P4 Medicine Institute. "It's really about that pragmatic and tangible bringing together of the things that we are learning about not only human biology itself, but really driving those into how the care is going to be delivered — health, wellness, and disease management — in a real P4 manner."
Lee says that ISB's decision to partner with OSU came only after a serious survey of the academic medical landscape of the United States. "ISB had spent some time evaluating and meeting with a lot of the top academic medical centers in the country, but we found that OSU had really embraced the concepts of personalized healthcare and the leadership was already very open to this approach to medicine as the way to really shine," Lee says. "Back in 2005, OSU established their own personalized healthcare center. They have also been having for the past few years a personalized medicine conference. All of these things were something that we just didn't see at any [of the] other universities."
The P4 Medicine Institute's first project will focus on using novel molecular modalities, including organ-specific proteomics, mRNA analysis, and deep sequencing of genomes in the context of families. They aim to combine that data with more conventional clinical data to establish an individual's base level of health and to determine when he is veering off that baseline into illness. A series of wellness clinics will also be established at OSU from a population base of their employees. The institute will then apply the molecular modalities and technologies from ISB along with the clinical delivery models that they will design together with OSU. "This is really interesting because OSU can and will be a closed-loop system — it's the payor for that large employee base, it's the provider of care, and it's also the patient population itself," says Lee. "We can really rewrite the rules for how care is paid for, provided, and received, and then draw out pragmatic things so that industry partners can develop the technical infrastructure to power this new type of healthcare."
The researchers at OSU have already set about one pilot project focused on wellness, a buzzword that is the cornerstone of any discussion about the P4 concept. The wellness project will include programs in exercise, nutrition, and biorhythms in order to better understand patient needs and how P4 can create "modules" to help the patient achieve optimal health. "We're very interested in looking to stratify people into groups according to exercise, nutrition, stress, sleep, and age, and merge that with genetic data and other molecular profiles so that we can then start to assign a predictive and preventive approach," OSU's Marsh says. "We'd like to give people feedback into how to improve and make changes to their lifestyle."
OSU will also initiate a chronic disease pilot project, which Marsh says will look at ways to build a team of clinicians around chronically ill patients using molecular profiling and other genomic elements to improve their quality of treatment.
Finding partners
Marsh says that one of the biggest challenges facing the P4 Medicine Institute at this early stage is making sure that additional partners are chosen carefully. Because this is still very much an experimental endeavor contained within the confines of the OSU healthcare system, those institutes looking to join in the hopes of making a profit from this new brand of healthcare are barking up the wrong the tree. "We want to produce wins for everyone involved, but we're looking for people who understand the long-term opportunity and also understand that if you're looking for some sort of committed return on an investment in a relatively short period of time, this is probably not the right partnership," he says. "We're spending a huge amount of time to make sure we're assessing the partners that are interested in what we're doing and making sure we have a level of compatibility with them so that we don't have any problems down the road because we failed to expressed our goals to each other clearly. That's a key element that we need to make this run smoothly. "
The Breakdown
Members: The Institute for Systems Biology and The Ohio State University Medical Center
Funding: ISB and OSUMC internal funding, with each institute contributing $500,000 annually for the next two years.
[LeRoy Hood' brainchild, the P4 Medicine (Participatory, Predictive Personalized Prevention) is both his "brand" - but he has gracefully consented to a generic use (like Mercedes Benz gives away all their safety patents, royalty-free, in the interest of the public at large). Thus, at the "P4 Conference in Silicon Valley" (December 9-10, 2010) Fred Lee will uphold the flag, while others like the Conference Chairman (AJP) will explore, particularly because of the location, the Personal (Holo)Genomics- and Information Technology aspects, much needed for P4. -Pellionisz_at_JunkDNA.com]
Ion Torrent, Stealthy Company Tied to Harvard’s George Church, Nabs $23M Venture Deal
Xconomy
Luke Timmerman 11/6/09
Ion Torrent Systems, a company advised by Harvard University genomics pioneer George Church, has raised $23 million in new capital to develop what it calls on its website “groundbreaking and highly disruptive technology” and to hire people who “want to do what it takes to put a dent in the universe.”
The company, which has a location near Yale University in Guilford, CT, and one in San Francisco, has raised $23 million in equity out of a financing round that could be worth as much as $26 million, according to a regulatory filing released today.
The document doesn’t say who invested, and Ion Torrent didn’t immediately respond to a request for comment. But the new company is associated with some big names, including Church and Stanford University’s Ron Davis, who serve on the company’s scientific advisory board, and CEO Jonathan Rothberg, who was the founding CEO of 454 Life Sciences before that company was sold to Roche two years ago for $140 million in cash.
Ion Torrent Systems website is pretty vague about what it is really up to, although its job postings offer some clues. It says it is looking to hire molecular biologists and biochemists to do the aforementioned universe denting, and that it offers that it offers the opportunity to work with top scientists “and have a profound impact.” It is also looking to hire software developers and “evangelists” who want to “create the biotech software platform of the future and share it with the world. Build powerful tools and create a tight-knit community that will use and develop them for years to come.”
GenomeWeb speculated back in March, based on a patent application filed by Ion Torrent Systems, that it is working on new DNA sequencing technologies, although the company wouldn’t confirm that. Major players in the field—such as Carlsbad, CA-based Life Technologies, San Diego-based Illumina, and Roche—have been in a competitive frenzy to lower the cost of sequencing full human genomes. One Mountain View, CA-based startup, Complete Genomics, raised $45 million in venture capital earlier this year to support its new model for sequencing entire genomes for as little as $5,000 apiece or less.
[While this piece of news is somewhat dated, it seems important to provide a perspective of the "lead group" of nanosequencing, especially from the news below on PacBio's F-Round - Pellionisz_at_JunkDNA.com]
PacBio Nabs $109M to Make Cheaper, Faster Gene Sequencing Tools
Luke Timmerman 7/14/10
The idea of sequencing entire human genomes for $1,000 or less, in a matter of minutes, has never been hotter, if the flow of venture capital to Pacific Biosciences is any indication. The Menlo Park, CA-based developer of super-fast gene sequencing machines has raised another $109 million in a Series F round of financing.
The company, known as PacBio for short, has now snagged a total of about $370 million in venture capital since it was founded in 2004. The company didn’t say who invested in the latest round other than San Diego-based Gen-Probe (NASDAQ: GPRO), which said it pumped in $50 million last month. But PacBio has a long list of existing investors that include Kleiner Perkins Caufield & Byers, Mohr Davidow Ventures, Alloy Ventures, and Intel Capital—as well as few names more familiar on the public-company circuit—Morgan Stanley, T. Rowe Price, Deerfield Management, and AllianceBernstein.
The vision at PacBio is to develop new gene sequencing instrument powerful enough to deliver the complete genome sequence from a human being in about 15 minutes and for a few hundred dollars. It’s the kind of technology that could enable basic researchers to run all sorts of experiments about the subtle variations in DNA that make people different, and which differences in genetic coding might be related to disease and wellness. San Diego-based Gen-Probe invested in PacBio’s technology with an eye toward using this sequencing technology as a tool doctors could use to diagnose disease.
“These funds will be used to support our operations as we begin ramping production capabilities for the commercial launch of our PacBio RS system,” said Hugh Martin, PacBio’s chairman and CEO, in a statement.
The company didn’t say in today’s statement when the machine would be commercially available.
PacBio is facing intense competition in the field of gene sequencing. Mountain View, CA-based Complete Genomics is pursuing a different business model, in which it asks researchers to send samples to a central facility instead of asking them to buy an expensive machine and run it themselves. Guilford, CT and San Francisco-based Ion Torrent Systems wowed researchers at a meeting in March when it unveiled a benchtop sequencing machine that can perform a lot of a basic experiments in a machine that only costs $50,000. The incumbents in the field whose machines generally cost 10 times that much—San Diego-based Illumina (NASDAQ: ILMN) and Carlsbad, CA-based Life Technologies (NASDAQ: LIFE)—have been launching pre-emptive strikes against the upstarts by continual improvements that have brought the cost of sequencing a human genome down to about $10,000 today.
[As the "Dreaded DNA Data Deluge" is upon us, perhaps it is worthy to look up the 2008 "Pellionisz" YouTube (about 8,333 views) if our theoretical (algorithmic) preparedness is up to the scientific challenge. My central argument was (and is) that "Big IT" will rise to the challenge, as it represents major business opportunities. However (as e.g. the Charlie Rose interviews show below) the scientific paradigm-shift towards recursive algorithms still calls for more support - Pellionisz_at_JunkDNA.com]
Recursive Genome Function at the crossroads - Charlie Rose Panel on Human Genome Anniversary
Human Genome Anniversary with Nicholas Wade of "The New York Times," Francis Collins of the National Institutes of Health, Eric Lander of MIT and the Broad Institute
Monday, July 12, 2010
[My FaceBook entry: The Panel is remarkable in not saying that without the theory of recursive genome function - where genomics and epigenomics are mathematically treated as the hologenome - we'll continue to be frustrated at looking at our medicine cabinet half-empty (or half full?) of genomic medicines. Every panelist is correct in what they do say, either from the skeptical viewpoint (Wade) implying that the meager results show that we overspent, since the paradigm failed that sequencing automatically translates into understanding (recursive) genome function (and diseases). No journalist can pinpoint what is missing, as it is up to advanced theory. Drs. Collins and Lander, to defend the establishment, dwell on the positives, how half-FULL is our "medicine cabinet" and how spectacular our technological (sequencing) and medical (genomic medicine) results are. True; the end alludes to “Junk DNA” (98.7%), acknowledging that it hides keys to regulation; yet none announce the paradigm-shift of the principle of recursive genome regulation. - AJP]
[A further comment contrasts the "stand-off" by pointing out that "recursive genome function" broke the 100,000 hits on Google (see in Table of Contents). There can be a debate if it is a fractal iterative recursion or some will publish a contending theory, but e.g. Eric Lander et al. (2009) featured on Science cover the fractal nature of the genome. - Pellionisz_at_JunkDNA.com]
The Little Flaw in the Longevity-Gene Study That Could Be a Big Problem
Newsweek, 7/7/2010
How a faulty DNA chip [an Illumina 610-Quad microarray - AJP], lax editorial review, and a few skipped steps turned a good study into bad science.
Remember that Science study from last week linking a whole bunch of genes—including unexpectedly powerful ones—to extreme old age in centenarians? NEWSWEEK reported that a number of outside experts thought it sounded too good to be true, perhaps because of an error in the way the genes were identified that could cause false-positive results. Since last Thurday, they’ve been trying to figure out what might be lurking in the data, and now there’s a suspect: a DNA chip called the 610-Quad, which is used to identify and sequence the chemical letters of DNA [not really "sequencing" but interrogating SNP-s in oligos - AJP], and which has an apparent tendency to get some small but critical details wrong. The flaw with the chip and the way it was used could cast serious doubt on the study’s strongest results, suggesting that they stem from a lab mishap rather than a real link to long life.
The flaw in question could be easily addressed with a little follow-up research. In very simplified terms, all that’s needed is for someone to rerun the analysis using a single different DNA chip. But this should have been done already, before publication. The fact that it wasn’t raises the question of how a paper with a missing piece like this got approved and published by Science.
The paper—which identified 150 genetic variants that might increase a person’s chances of making it to age 100, apparently by protecting the body against disease—had as one of its two principal components a type of research called a genome-wide association study (GWAS). These surveys, the bread and butter of modern genomics, use chips to analyze large amounts of DNA in many people, looking for variants that are more common in “cases” (here, that means centenarians) than “controls” (regular people). The variants that turn up more often in “cases” are the ones linked to the trait the scientists are curious about. The studies are usually very thoughtfully designed and reliable. What happened with this one?
The first thing to know is that not all gene-identifying chips are created equal. They [microarrays - AJP] occasionally identify letters of DNA incorrectly, and—to complicate things further—each type of chip makes different errors at different points in the genome. That phenomenon can lead to false-positive results if it's not well-controlled by experimental design, says David Goldstein, the Duke University geneticist who first raised this issue here last week. “Unfortunately, different chips have their own little problems for specific [genetic variants],” he says. The key to keeping false positives at bay is to ensure that cases and control groups are analyzed using exactly the same techniques. If you use one type of chip to analyze your cases and a different type to analyze your control group, “you can see any [variants] that are genotyped differently on the different chips ‘lighting up’ as apparently associated with the trait,” says Goldstein, when in fact that pattern is just an experimental artifact.
All of the chips used in the Science study came from the same manufacturer, Illumina, but they weren’t identical. According to a brief description in the paper, the researchers used two different chips to look at their centenarians, analyzing most people with a 370 chip that examines 370,000 genetic variants and a smaller fraction of people with a different chip (the 610-Quad) that examines 610,000 variants. The reason, says Paola Sebastiani, the Boston University biostatistician who led the study, is that at one point the 370,000-variant chip went off the market and the 610-Quad “was the best option for us in terms of costs and coverage.” The controls involved an even more varied assortment of technology—some were analyzed with the 370, some with the 610, and some with two other types of chips.
Kári Stefánsson, the Icelandic geneticist who founded deCode Genetics, knows something about the 610-Quad—his company has used it too. He says it has a strange and relevant quirk regarding two of the strongest variants linked to aging in the BU study, called rs1036819 and rs1455311. For any given gene, a person will have two “alleles,” or forms of DNA. In the vast majority of people, at the rs1036819 and rs1455311 locations in the genome, these pairs of alleles consist of one “minor” form and one “major” form. But the 610-Quad chip tends to see the wrong thing at those particular locations. It always identifies the “minor” form but not the “major” form, says Stefánsson—even if the latter really is present in the DNA, which it usually is. If you use the error-prone chip in more of your case group than your control group—as the BU researchers did—you’re going to see more errors in those cases. And because what you’re searching for is unusual patterns in your cases, you could very well mistake all those errors (i.e., false positives) for a genetic link that doesn’t actually exist.
Stefánsson says he is “convinced that the reported association between exceptional longevity and most of the 33” variants found in the Science study, including all the variants that other scientists hadn’t already found, “is due to genotyping problems.” He has one more piece of evidence. Given what he knows about the 610-Quad, he says he can reverse-engineer the math in the BU study and estimate what fraction of the centenarians were analyzed with that chip. His estimate is about 8 percent. The actual fraction, which wasn’t initially provided in the Science paper, is 10 percent, the BU researchers tell NEWSWEEK. That’s close, given that Stefánsson’s calculations look at just two of the variants found in the study and there may be similar problems with others.
One of the oddest things about this potential error is how much it stands out in an otherwise carefully designed study. The BU researchers made a serious attempt to deal with confounding factors—a challenge given that centenarians are by definition different from any possible control group, because they were born earlier—and, Sebastiani says, the team “conducted extensive quality-control procedures and cleaning of the data.”
What the group apparently didn’t do, however, is obtain a third-party analysis of their centenarians’ and controls’ DNA using a single chip for everyone. There’s “nothing in the world simpler to do,” says Goldstein. “We would do this for any ‘discovery’ we had in this kind of a situation, but when the results themselves are a bit improbable, as the results are here with the exceptional genetic control, then there is all the more necessity for that quality-control step.” Goldstein adds that such a step is standard practice for most GWAS research. That's why you can trust many other GWAS papers while withholding judgment on this one. Yes, it’s tempting to look at this study and wonder what other flaws may be hiding in other GWAS papers, even those in top-flight publications. But this episode shouldn’t be read as evidence that genome-wide association studies are untrustworthy as a rule, because the rigor that seems to be missing from this study is almost always found in others that haven’t yielded such dramatic results.
It’s possible that when that replication study is done, the genetic associations in the longevity study will hold up. (At least a few of them, such as the link between long life and APOE—which is also linked to Alzheimer’s—surely ought to, since they have been found in other studies.) The BU paper’s critics aren’t out-and-out saying it’s wrong. They’re just saying it could be.
Still, one has to wonder how the paper wound up in Science, which, along with Nature, is the top basic-science journal in the world. Most laypeople would never catch a possible technical glitch like this—who reads the methods sections of papers this complicated, much less the supplemental material, where a lot of the clues to this mystery were?—but Science's reviewers should have. It’s clear that the journal—which hasn't yet responded to the concerns raised here—was excited to publish the paper, because it held a press conference last week and sent a representative to say as much.
The BU scientists are holding a public Web chat today at 1 p.m. ET. Most of the questions they take probably won’t concern highly technical stuff like this. Sebastiani would prefer that critics’ questions be addressed directly to her in journals rather than, say, relayed to her by NEWSWEEK writers: “So far we were not approached by any of these investigators directly, only by reporters,” she says, which is “rather surprising and disappointing to me.” The Web conference, Sebastiani adds, is being held primarily to address the fact that several companies are already thinking about selling a test based on the Science paper, a notion that the study’s authors abhor and are trying to prevent. “We strongly feel that results of such a test should continue to be for research use and that it is not at all ready for use in the public domain,” says Sebastiani. “There are just too many opportunities for misuse and misinterpretation at this very early point.” Not at all ready for use in the public domain: that’s the one thing that everyone involved with this paper does seem to agree on.
One more important thing: the BU researchers put together a model for predicting whether a given person would live to 100 or not, and it was widely reported that the model had 77 percent accuracy. That was true in the study, where the researchers were applying the model to people from groups of roughly equal size—they had about the same number of centenarians as they did controls. In reality, however, only 1 in every 6,000 people lives past 100, so the real-life sample sizes, if you will, are very different. Both Stefánsson and David Altshuler, a geneticist who leads GWAS research at the Broad Institute, say that fact renders the model much less useful than you might think, because it actually tells you only that your chance of living to 100 is either really small (much less than 1 percent) or really, really small (even less than that). “For most practical purposes,” Stefánsson notes, this “makes no difference for an individual.” It’s a good reason not to rush out and get your longevity genes tested, although at this point, you don’t need another one.
UPDATE: Within an hour of this story's publication, the Science study's authors released a statement which a BU spokeswoman described as appearing "because of your inquiry and a similar one from the New York Times concerning methodology used to test 2 of the 150 genetic variants." Here is what the statement says: "Since the publication of our study in Science, which was extensively peer-reviewed, a question has been raised about two elements of the findings. One has to do with two of the 150 genetic variants included in the prediction model, while the other is related to the criteria used to determine the significance of the individual variants. On the first concern, we have been made aware that there is a technical error in the lab test used on approximately 10% of the centenarian sample that involved the two of the 150 variants. Our preliminary analysis of this issue suggests that the apparent error would not effect the overall accuracy of the model. Because the issue has been raised since the publication of the paper, we are now closely re-examining the analysis. Another question that was raised concerns the criteria used to determine if an association between a genetic variant and exceptional longevity was statistically significant. We used standard criteria for the analysis, and we are confident that the appropriate threshold was used."
[I was greatly impressed by the sub-title of first report: "Scientists Discover the Fountain of Youth! Or Not." Apparently, Mary is just as skeptical about non-existent "cancer gene", "happiness gene", "fountain of youth gene" etc. as leading scientists like Kári Stefánsson are. "Genes" (with as many definitions as the number of scientists you ask) don't do any complex phenotypes as "longevity" - they just turn out the "basic building materials" (amino-acids for proteins) as called for by the design (in intergenic and intronic sequences). True, if e.g. the concrete is defective, the "longevity" of the architecture may be reduced to the sudden death of a quick collapse. It may be time to come to realize that "the genes failed us" in old-time genomics to explain recursive genome function (hologenomics) of today. It is hard to find imperfection in Mary's science writing. With the "DNA chip" of IBM (for sequencing) coming, perhaps we should distinguish Illumina's ChIP (bead array, otherwise called "microarray") and "chip" that is usually meant either a piece of semiconductor, or that of a potato - AJP]
23andMe Letter to Heads of FDA and NIH
The Spittoon
June 24, 2010
At 23andMe, our goal is to give people the best information possible about their personal genetic data. [This brilliant sentence focuses on the key issues, virtually assuring that both DTC Genome Testing and a renewed FDA will prevail. Hopefully, the process will be cut blazingly short, to avoid the US being deprived of one her few global competitive advantages that could generate jobs and rescue health care by prevention. Contrary to the the astonishing belief that some people should be protected against information about their bodies - Esther Dyson, a board member at the company, has even called the FDA’s position “appallingly paternalistic.”- NIH Chief Dr. Collins appears to concur with sharing the information with their owners (see below in this column): "I would be very uncomfortable with a system that says no, we know better than you do, you won't understand this information so we're not going to let you have it. There's something that doesn't feel right about that." Thus, the eventual outcome of a new legislation for FDA (only to safeguard quality, not to infringe with the citizens' civil rights of accessing [genomic] information about their bodies, updating the 1976 mandate of FDA), seems assured: "to give people the best information possible about their personal genetic data" - AJP]
We believe that this goal is shared by all genetic testing providers. [Another brilliant sentence, uniting the entire US DTC Business - AJP]
You may be aware that different personal genetic testing companies, while providing completely accurate test results, may provide differing risk estimates for some diseases and conditions. While there are valid scientific reasons for such different estimates, they might nevertheless cause confusion for some consumers and physicians.
23andMe has sent a letter to Dr. Margaret Hamburg, Commissioner of the Food and Drug Administration, and Dr. Francis Collins, Director of the National Institutes of Health, asking for their respective agencies’ help in developing broadly applicable standards and guidelines to achieve consensus regarding how to provide information on genetic test results and risk estimates. The contents of this letter are reprinted below (links to the referenced article and blog post are provided here instead of attachments):
June 24, 2010
Dr. Margaret Hamburg
Commissioner of Food and Drugs
Food and Drug Administration
10903 New Hampshire Ave
Silver Spring, MD 20993-0002
Dr. Francis Collins
Director
National Institutes of Health
9000 Rockville Pike
Bethesda, Maryland 20892
Dear Drs. Hamburg and Collins,
We are writing to ask your assistance in resolving an issue of concern to 23andMe and, likely, all genetic testing companies, whether they report their results to physicians or to consumers. As you are aware, though results from 23andMe and other genetic testing companies are typically consistent, there have been reports of inconsistencies (Ng et al. 2009). We believe that it is important to emphasize that different genetic testing companies can report inconsistent results even when based on tests with proven analytical validity. The reasons for this may include: companies employ slightly different statistical models for making risk estimates; companies establish different criteria for the inclusion of associations in their reports; new associations are being discovered at a faster rate than companies’ development cycles; companies may test for an imperfectly overlapping set of genetic variants for reasons including the ability of different genotyping technologies to assay certain variants.
Although inconsistent results may have a scientifically valid basis, we recognize that they may be confusing to physicians and consumers. However, we, as an individual company, cannot address this issue alone. Therefore, we are writing to ask your two agencies to engage with us on this issue, to work towards solutions that can be broadly applied. We offer the following ideas as a starting point for discussion. An organization or group of organizations could develop:
• guidelines for acceptable analytical validity;
• standards for the positive and negative predictive value of all tests;
• “best practices” for companies, for instance necessitating transparency in reporting the positive and negative predictive values of their tests, so that results could be readily compared across companies.
We note that any framework developed for genetic testing companies must consider the multiple high throughput technologies on the horizon, including genome, exome and transcriptome sequencing. For this reason, the set of ideas we present above does not include having an organization define a specific set of markers as an acceptable genetic test.
The issue of inconsistent results was one of several discussed in an Opinion piece by Pauline C. Ng, Sarah S. Murray, Samuel Levy and J. Craig Venter that appeared in the October 8, 2009 issue of Nature. A joint response from 23andMe and Navigenics submitted to Nature but not published by Nature was posted on our web site on November 19, 2009. We have attached our open letter to Nature, and a response from one of the authors for your consideration.
Our goal is to provide the best possible information to consumers and health care practitioners. We would appreciate the opportunity to work with you towards this goal and, more broadly, to promote innovation in personalized medicine. We will follow up with a call to your offices.
Sincerely yours,
Ashley Gould
on behalf of Anne Wojcicki
Amazon Sees the Future of Biology in the Cloud
By Luke Timmerman, Xconomy.com
July 6, 2010
The future of biology, if Amazon.com (Nasdaq: AMZN) has its way, will be in the cloud.
The Seattle-based online retailer has generated buzz the past few years with its foray into cloud computing through Amazon Web Services. This is the model in which customers rent server space on a pay-as-you-go basis, and get access to their data anytime via the Internet. It's supposed to allow small businesses, governments, and anybody else to save cash and hassles by not having to buy and maintain their own in-house servers. The model is credited with enabling a new generation of lean tech startups to build businesses using far less capital. [The easiest metaphor to understand what "cloud computing" is to think of it as "car rental" instead of buying/leasing your own automobile. It immediately follows that no car rental company will tell you where and how to go (might provide a map if you don't have a GPS) - but will certainly not drive the car for you. If you want to be actually driven to a destination, think of Limousine-service with driver included (or most simplistically a "taxi cab"). For genomics, they do not exist - and ultimately they are rather expensive solutions for the long haul - AJP]
Biological researchers haven't embraced the new model as quickly as their tech brethren, but the cloud computing wave is coming to life sciences, says one of Amazon's biotech liaisons, Deepak Singh. The trend is coming out of necessity. [Like when you fly abroad, car-rental or taking a cab are frequent option, based on necessity - AJP] Gene sequencing has been on a breakneck pace of innovation over the past few years, as instrument makers like San Diego-based Illumina (Nasdaq: ILMN) and Carlsbad, CA-based Life Technologies have lowered the cost of sequencing an entire human genome to as little as $10,000. Upstarts like Mountain View, CA-based Complete Genomics seek to sequence entire genomes for as little as $5,000, while a rival, Pacific Biosciences, is aiming to sequence genomes in 15 minutes. Since every human genome has 6 billion chemical units of DNA, this faster and cheaper form of sequencing is creating enormous datasets that somebody will need to store, analyze, compare, and visualize. Without that capability, it's just a vast pile of data that doesn't really lead to valuable new insights for medicine. [Moreover, the entire sequencing industry might become unsustainable and sequences worthless unless someone actually knows what to do with the data to transform them into understanding - "the cloud has similarly limited intelligence" as a cab driver; if you tell the address, might get you there (often purposefully not along the most economical path FOR YOU)" - AJP]
Computing challenges have become a "serious blocker" to people trying to make sense of the genomic wave, Singh says. And Amazon has made it a high priority over the past couple years to become the company that stores genomic data in a cheaper and more accessible way for researchers. Customers, Singh says, "have started looking at the cloud very seriously as a possible option. Over the last year or so, that curiosity has turned into serious adoption."
Amazon's pay-as-you-go, rented server model has attracted partners and customers all over the country. The Broad Institute of MIT and Harvard in Cambridge, MA, is a user, along with Harvard Medical School. Life Technologies, an instrument maker, and Seattle-based Geospiza, a bioinformatics software company, have a partnership to use Amazon's servers to store genomic data. Palo Alto, CA-based DNAnexus, an intriguing bioinformatics startup, has built its business model around using Amazon Web Services. And one of the leading evangelists for cloud computing in genomic research is C. Titus Brown, a computer science and microbiology professor at Michigan State University, who is teaching students how to use Amazon Web Services to store the data for their experiments.
Precisely how important this is to Amazon, a company with $24.5 billion in revenue in 2009, is hard to say. In keeping with Amazon's close-to-the-vest culture, Singh would only offer vague adjectives when I asked for specifics on the number of customers, the percentage of Amazon Web Services business that comes from life sciences customers, the number of employees devoted to this effort, and the size of the market that Amazon ultimately sees for cloud computing services in life sciences.
There are still major barriers to be cleared before this can become a real earnings driver for Amazon. Much sequencing is done at centralized labs around the country that already have invested in expensive servers to store their data in a secured place on campus. So there's incentive to keep using those tools to get the most value out of them. Some labs are generating so much data from the instruments that they aren't always sure they have enough bandwidth to transmit it all to Amazon's servers. The raw experimental data is so precious to a biologist's career that it can be hard to just send it away to a vendor for safe-keeping, rather than have it under lock and key on campus.
And many researchers struggle with how to analyze, visualize and interpret the data being spit out by the sequencing machines. The software that needs to run on top of Amazon's storage capacity and databases -- the bioinformatics piece of the puzzle -- is still a cottage industry with home-made programs, piecemeal open source alternatives, and a lot of researchers still using old-school spreadsheets like Microsoft Excel.
Yet even before companies like DNANexus achieve major market traction with simple and easy-to-use bioinformatics software, many researchers still feel compelled to store the data in anticipation of the day when it will be easier to sift through. And Amazon isn't the only company wooing them. Microsoft and Google have their own cloud computing services to offer. At least one competitor, Seattle-based Isilon Systems, is making visible inroads in the life sciences market by selling of clustered servers. Isilon now generates 15 to 16% of its revenues from life sciences customers, up from 2% in early 2008, CEO Sujal Patel said at a recent Xconomy forum. Isilon's customer roster includes a lot of heavy hitters, like Merck, Genentech, Sanofi-Aventis, Bristol-Myers Squibb, Illumina, Complete Genomics, the Broad Institute of MIT and Harvard, Stanford University, and Johns Hopkins University.
Amazon's Singh knows this terrain well himself. He got his doctorate in chemistry from Syracuse University, and spent eight years of his career in the biotech industry, including stints at San Diego-based Accelrys and Seattle's Rosetta Inpharmatics. The past two years, he's been working as a business development manager for Amazon Web Services, with a particular emphasis on getting to know what the life sciences market wants from cloud computing.
Amazon has done a number of things to ease the transition for customers to cloud-based storage, Singh says. It has worked to obtain public databases and make them available to researchers. One example last month came from three recently completed pilot projects for the 1,000 Genomes Project. Putting that data out there for researchers, and enabling them to share it, has generated a lot of interest. "There's been a lot of demand for 1,000 genomes pilot data in Amazon Web Services," Singh says.
Showing the scientific value is one part of the equation, but the business proposition is just as important. Amazon's case is a pretty simple one. A lab can make a big capital expenditure upfront, but they usually have peaks and valleys of computing power needs. That means the lab isn't really fully utilizing its server capacity all the time. Plus, the new breed of sequencing instruments are getting so cheap and fast that there's no way a lab can really anticipate its server capacity needs in the future. Instead of buying expensive equipment and risk getting it maxed out in a year or two, the argument goes, why not lean on Amazon and its basically limitless capacity and flexible pay-as-you-go pricing model?
That may make sense for a lot of labs, but Amazon has found it needs to tailor its product a bit more for life sciences customers. The feedback prompted Amazon to make one curious old-economy concession to help with cloud computing. For some customers who don't have the bandwidth to efficiently communicate with Amazon's cloud, the company has set up what it calls an "import/export" service, which allows the lab to save their data on disk and physically ship it to Amazon via FedEx. This helps with some customers who want to know they can get their data to and from Amazon in a reliable way, on a predictable time schedule, without hogging up too much bandwidth on campus.
As much as academic labs might be interested in what Amazon is offering, they can only do as much as their funding agencies really allow. And there are rumblings that the U.S. National Institutes of Health, the world's primary funding agency for biomedical research, might be facing budget cuts in not so distant future.
Budget cuts at NIH could actually benefit Amazon, Singh says. It could put pressure on labs to be more careful with their capital spending, think a little harder about whether to build their own server clusters, and look more closely at alternatives like cloud computing. Even though the cloud is supposed to be cheaper, Amazon has felt the need to offer customers discounts on price. The company has started offering a cloud infrastructure service with less backup capability for the data, or "redundancy." That offering is still a more durable backup option than a lab can build on its own, Singh says, and it comes at a lower price than Amazon's regular cloud offering. The "Reduced Redundancy" service makes sense, he says, for a dataset that can be quickly reproduced (like another sequencing run on a blood sample, if the data is lost, for example).
Most of the interest in Amazon's offering is from academic labs, rather than with biotech companies and Big Pharma, Singh says. If Amazon can gain a toehold first in academia, it will almost certainly look to continue the momentum in Big Pharma, which spent an estimated $45.8 billion on R&D last year. Big Pharma spends all that money, and is still living with an abysmal success rate, in which only one out of 10 drugs that enters testing ever becomes an approved product.
Sequencing of individual human genomes, and analysis of how they differ, is one of the ways researchers are hoping to someday lower the cost and increase the odds of success in developing new medicines. It's a long-term trend that Amazon wants to be in position to reap.
"Over the past 12 months, there's been significant interest. All you have to do is look at conference agendas," Singh says. "The nature of the conversation has shifted from 'What should we do?' to 'What are we doing, and how should we do it?'"
[If we'd know what we were doing, we would'nt call it "research" - Albert Einstein - AJP]
Calling GWAS Longevity Calls into Question [Gene(s)]
GenomeWeb
July 06, 2010
According to Nature's The Great Beyond blog, the GWAS published in Science last week that identified SNPs for "exceptional longevity" has generated some criticisms within the community. Critics are calling the findings of Paola Sebastiani et al. into question amid inquiries of "subtle biases" and the team's use of "different versions of the SNP chips" from Illumina, according to Nature. The Wellcome Trust Sanger Institute's Jeffery Barrett told the Guardian that "some of the genetic variants in this study are claimed to have much, much stronger effects on longevity than we've seen in similar studies of diabetes, heart disease, and cancer. For instance, the strongest single effect makes someone 10 times more likely than average to be extremely long-lived, compared to other complex diseases where typical variants only make someone, say, one and a half times as likely to be diabetic," highlighting his skepticism. According to Nature, Sebastiani says that the variants they've reported have larger effects since becoming a centenarian is a much rarer condition than having diabetes.
Last week, the New York Times' Nicholas Wade reported that DeCode Genetics' Kari Stefansson, who has run a similar experiment using a larger group of centenarians, did not find any of Sebastiani et al.'s 150 variants in his cohort.
Nature reports that Sebastiani and her team are considering "holding an online chat next Wednesday to answer questions" and to quell any confusions that their work has generated.
[We have spent dollar billions (probably trillions) and close to half a Century trying the find the "cancer gene", "epilepsy gene", etc., etc., - only to came to a realization when the recursive genome function pinpointed that complex phenotypes (such as longevity - or even cancer) are likely to be lurking in (holo)genome regulation (via epigenomic channels) - rather than to be tied to a single (or even small enough identifiable number of) "genes". Maybe time is ripe to spend monies on the much-neglected (holo)genome regulatory functions; and e.g. to research why the absence of hereditary- and/or epigenomic damages to DNA (not just to "genes" but mostly to derail recursive regulation) lead to accelerated aging process and untimely deaths. - Pellionisz_at_JunkDNA.com]
IBM setting up cloud for genome research
July 2, 2010 10:35 AM PDT
by Lance Whitney
IBM is looking to help genome experts further their research by providing a cloud where they can better share information with their colleagues.
IBM and the University of Missouri announced Friday a new initiative to develop a cloud-computing environment where universities and medical professionals could work together on genome research on a large-scale, regional basis.
Tapping into Big Blue's high-performance computers, the joint IBM-Missouri cloud would let researchers share their findings and discoveries with each other more quickly and efficiently than they do now. Such an advancement would push the university's current bioinformatics research even further, potentially improving people's lives, IBM said.
As one example, specific genetic changes in cancer cells help doctors decide how best to treat their patents for breast cancer, colon cancer, lung cancer, and leukemia. To detect those changes, DNA samples must currently be sent out to labs for sequencing and analysis, a process that can take weeks. But by accessing IBM's genomics cloud, medical staff could sequence and analyze those samples in just a few minutes, according to IBM. [Wait a minute ... there are actually three bottlenecks. Presently, as the statement acknowledges, the main bottleneck is "sequencing" ("can take weeks"). Presently, the second bottleneck of storage and transfer to the sites of "DNA Analysis and Interpretation" is usually not through the net (requires too much bandwith, too much time - UPS of physical hard drives, laughable as it is, still "a preferred choice"; takes very few days. The third bottleneck is the actual analysis and interpretation. Presently, some projects take forever, some limited analyses can be produced in weeks, using pre-genomics computing architectures. In the future (a rough estimate is 5 years), all three bottlenecks should add up to 30-60 minutes COMBINED, to be practical e.g. in a hospital environment to do biopsy, full DNA sequencing, full DNA analysis and interpretation (and personalized recommendation e.g. of the most suitable cancer-treatment, as predicted in my 2008 YouTube). Forget UPS. Forget even the Internet-2. Hospitals will demand e.g. Ion Torrent desktop-sequencers ($50k) with on-rig serial/parallel (FPGA) hybrids, to cut out storage and transfer, and accelerate analysis and interpretation of low-bit huge-scale strings (DNA); also forecast in the above YouTube. - Pellionisz_JunkDNA.com]
"This collaboration with IBM provides our researchers, and those being trained to become tomorrow's researchers and educators, access to critical high performance computing resources needed to process massive data sets and apply increasingly more sophisticated bioinformatics tools and technologies," Gordon Springer, scientific director of the University of Missouri Bioinformatics Consortium, said in a statement. "The availability of these resources will enable discoveries that will benefit mankind and the environment."
In the first phase of the cloud project, IBM said it will offer Missouri an iDataPlex high-performance computer and software that will tie in the university's existing computers and speed up the DNA sequencing and analysis of humans, plants, and animals. In the second phase, Big Blue and the university will work together to create a prototype of the cloud environment. The final phase should see the genomics cloud become fully operational and expand to a regional scale. [Sounds like 5 years to me - AJP]
No specific time frame was given as to when the project would formally get off the ground or how long it might take to reach the final phase.
This isn't Big Blue's first foray into the world of genomics research.
Last year IBM announced new research into technology that can quickly and relatively cheaply conduct genetic testing. In the past the company has also donated hardware and software to remote areas to further study human DNA around the world. And the original job of IBM's Blue Gene supercomputer was to predict how chains of biochemical building blocks described by DNA fold into proteins.
[The "IBM/Roche DNA Transistor" and the "IBM Genome Cloud Computing". One might believe (as most did think so when the "IBM CP and its OS/2" came out, that this time "IBM cornered genomics". The bottom line is that nobody can tell the future - it may or may not happen to IBM - but "the race is on" with IBM/Roche having produced the Big One earthquake (the tectonic plates of "Big IT" and "Big Pharma" piled upon one another (that I predicted half a Century ago). Indeed, the very same IBM already "almost did it" with the World's fastest supercomputer (at that time), Blue Gene under historical governance of Caroline Kovac - upon completion of The Human Genome Sequencing Project. Also, presently a Seoul-based microarray - followed by Full DNA Sequencing Institute is backed by SAMSUNG. In the USA, Microsoft HealthVault, Google Health, DELL Life Science Division, Oracle's foray into Personalized Medicine (etc) are also "Big Players". Not everybody is "sold on the Cloud", however (e.g. see Larry Ellison going ballistic in a 4:25 minute YouTube on "Cloud Computing" in an a Churchill Club's excerpt , see full 1:26 hour YouTube , yet you can also download "Oracle Cloud Computing"... Now take Christensen's book "The Innovator's Dilemma;- When New Technologies Cause Great Firms to Fail" and factor in what happened to "IBM PC/OS2". It looks like Genomics needs a Microsoft-type "pure-play genome software start-up" for the fastest growth possible ... Pellionisz_at_JunkDNA.com]
Scientists Discover the Fountain of Youth! Or Not.
Mary Carmichael
Newsweek, July 1, 2010
They say getting old is better than the alternative, and it's much better if you manage to do it like Florrie Baldwin, who died in May after 114 years of great health. (She was still climbing ladders at 104 and almost never took any medication.) Baldwin attributed her long, hale, and hearty life to a daily fried-egg breakfast, but her true advantage was probably in her DNA. Scientists have long suspected that she and others who grow very old have genetic variants that protect against the molecular ravages of age.
The trick, though, is finding those genes [and genetic variants, more often than not, in the intergenic and intronic regulatory regions - AJP]. Much of the research so far looks more clear-cut in mice or worms or fruit flies than it does in humans. And because the topic of old age and genes in general inspires so much excitement, it's often hard to tell where any given study falls on the continuum between brilliant (last year, the Nobel Prize for medicine went to three scientists who studied the relationship between DNA and aging) and ridiculous (this year, the cosmetics company Lancôme launched an eye cream that purports to "boost genes' activity and stimulate the production of youth proteins," which is about as believable as Baldwin's fried-egg theory).
What, then, to make of the new headline-grabbing paper that identifies somewhere between 33 and 70 genes (depending on how definitive you like your results) associated with extreme longevity—and also introduces a model that claims to predict with 77 percent accuracy whether you're going to be one of those ripe old folks? If the study's findings are correct, they are a very big deal, with the potential to overhaul how scientists think about aging and genetics. Indeed, they're so striking that some of the world's top geneticists think they can't possibly be right. More on that in a bit, but first, a point that even the study's authors have to concede: the research doesn't actually describe normal aging. It concerns only genes that may govern the process in people who make it to 100 or more. "The question is, of course, do the findings apply to the general population? Can we apply your model and predict the average lifespan?" says Paola Sebastiani, the Italian researcher who led the team. "And the answer is no, we can't." So what exactly can we learn from the new study?
The paper, published today in Science, has two basic parts. The first is what's called a "genome-wide association study," or GWAS. Researchers obtained genetic data (300,000 variants) from about 1,000 very old people (those over 100 years of age) enrolled in the New England Centenarian Study, and then compared the readouts to results from a same-size group of average people often used as a standard control in genetic studies. They found 70 genes that were more common in the centenarians. Then they repeated their study with smaller groups and confirmed 33 of those. They also looked at known disease-causing genes in both centenarians and regular subjects. It turned out that the centenarians had just as many dangerous variants as everyone else, which suggests that the 70 longevity genes (or 33, if you prefer the confirmed ones) were actively protecting them against illness. In other words, very long life isn't just about not having genes that make you sick—it's also about having genes that keep you well.
Next, the researchers employed some unusual math to build a model that described the combined effects of 150 variants they had found in the centenarians. (Some of those variants were related to the same genes, so the final number of suspected genes was still 70.) Then they applied the model to each of their study subjects, blinding themselves as to whether an individual was a centenarian or a member of the control group. Seventy-seven percent of the time, the model rightly predicted which group a given person belonged to—a success rate that is not only statistically significant but unprecedentedly high for a model that predicts a complex trait. It also pointed to 19 different genetic "signatures," or combinations, that seemed to confer long and healthy life in the centenarians.
Here's the weird thing: 15 percent of the control group had those signatures, too. That means that, genetically speaking, 15 percent of us should be living to 100 or more, when in reality only about 1 in 6,000 people do. What's happening to the rest of the would-be centenarians? Thomas Perls, a co-author of the paper and a geriatrics researcher at Boston University, says that maybe they're getting bumped off by things no gene can prevent. "Remember, this generation [in the New England Centenarian Study] lost a quarter of its population to childhood infectious diseases," he says. "And just because you've been handed the genetic blueprint for long life doesn't mean you're going to get there if you smoke a lot or you get killed in World War I or you're hit by a bus."
These are provocative ideas, and that may explain the wide variety of reactions that scientists had upon seeing the paper. Some said it was groundbreaking and could lead to drugs that mimic the protective genes in those who aren't blessed with them naturally. "What this paper answers, which I think is very important, is how many variants are there that can assure longevity," says Nir Barzilai, director of the Institute for Aging Research at the Albert Einstein College of Medicine in New York City. "Now scientists can start tracking those genes down and leading the findings toward drug development." Barzilai, who has collaborated with the study's authors on previous projects, has done some of that work already, probing a gene that influences how the body processes a hormone called IGF-1.
But other researchers were concerned about the new study's methods, calling the results everything from "somewhat surprising" to "preposterous." The problems start, they say, with the size of the group the researchers examined. The New England Centenarian Study is the largest cohort of very well-seasoned people in the world, but compared to the numbers typically used in GWAS-style research, it's actually quite small. Modern GWAS techniques usually involve groups of tens of thousands or hundreds of thousands of people. To attain statistical significance in a GWAS as small as the one in the Science paper, any gene would have to have a hugely strong effect in the body. It's odd that the Science paper finds not just one strong gene but a whole raft of them, especially since common diseases are usually caused not by strong genes but by weak genes acting together. (Why is a bit of a mystery, though it's possible that many strong genes have been weeded out over time by natural selection.) Aging, of course, is humanity's most common ailment. "I am very surprised that in a cohort of this size they have found 33 variants of genome-wide significance in extreme longevity," says Kári Stefánsson, the Icelandic researcher whose company, deCODE Genetics, has led many GWAS efforts. "We haven't seen any of them in our work with a different kind of cohort, but [a] much larger [one]." Other work at deCODE has also suggested that extreme old age is influenced by just a few genes—certainly not as many as 33 or 70.
The study's authors have a response to that. Yes, they admit, the sample is smaller than you'd need to do a GWAS of a common disease (which isn't really their fault, since there aren't many centenarians available for study in the first place). But common diseases, with their panoply of weak genes, aren't the right comparison to make, they say. Centenarian status isn't just an extreme form of the common condition known as aging, they argue; it's a rare condition of its own, and rare conditions are often caused by genes with powerful effects.
There are other potential problems with the new study. David Altshuler, a leading geneticist at the Broad Institute (a collaboration between MIT and Harvard), says that "one has to be cautious in interpretation, because the cases and controls were drawn from different times and places, and the DNA from cases and controls was measured using different technologies, which could lead to false apparent relationships." Duke University's David Goldstein, also a prominent geneticist, echoed those concerns. (And Altshuler and Goldstein are renowned for rarely agreeing on anything.) The control data in the Science study came from a standard set of numbers that Goldstein's lab has used, too. "We have found when we compare samples run at Duke to the [standard] control panel, there are a lot of [variants] that appear significant just because the samples were run in different ways," he says. Until the data has been replicated using identical technologies for the centenarians and controls, he adds, "I think we've got to hold judgment on this."
The authors of the Science paper are respectable researchers, and they're not trying to sell anyone genetically enhanced snake oil. (Tom Perls, in fact, has been such a vocal critic of anti-aging hype that he was once sued by the American Academy of Anti-Aging Medicine for defamation. They settled.) Sebastiani, Perls, et al. will be doing lots of follow-up research, including, they hope, a whole-genome sequencing project that will shed more light on their findings.
But for now, their research isn't ready to be translated from the lab to the clinic. You don't need to rush out and get tested for all the genes found in the Science study (although someone somewhere is surely making plans right now to sell you such a test). You can probably get a good idea of your risk just by looking through your family scrapbooks. "Using this technology might be helpful," says Robert Marion, a clinical geneticist at Montefiore Medical Center in New York. "But I would think that by just asking how old the person's parents and grandparents were at their time of death, the accuracy would probably be higher." So, if you want to know your chances of making it to 100, you should learn your family history and eat right and exercise while you're at it. Surely you didn't need a highly technical Science paper to tell you that.
[I got fairly technical in my Google Tech Talk YouTube - 8,230 views, rising steady since late 2008 - about aging; as the result of recursive genome function running out of auxiliary (regulatory) information by de novo methylation (rendering non-coding sequences "canceled" upon perusal). Growth is fueled by information - and since we all have a finite amount of it, eventually must run out. And, indeed, one can tell the average expected lifespan from the genome fairly precisely. (Yes, you can do, too). Ever wondered why a mouse, with 98% same set of genes only lives for 2-4 years, while we can last over twenty times longer? Just look at a genome (genes are nearly identical for species from lowly worms to homo sapiens) - but the regulatory mechanism (the amount of information, as well as the "clock speed" of recursion) can be rather different. The mosquito fish lives about 2 years, a catfish about 60. Look for recursive genome function in regulatory (non-coding) part of the DNA. One can not exclude it - but "genes" are unlikely to be the clue. Your "Junk DNA" can be the treasure chest of your longevity. - Pellionisz_at_JunkDNA.com]
IBM DNA Decoding Meets Roche for Personalized Medicine
eWeek.com
Brian T. Horowitz
2010-07-01
[IBM-Roche DNA Transistor - AJP]
IBM and Roche are working together to decode DNA more quickly and cheaply, potentially allowing patients to receive customized prescription drugs. In the future, this kind of health care IT could also allow patients to purchase their own DNA code information for as little as $100.
IBM and Roche, a pharmaceutical and diagnostics company based in Basel, Switzerland, are working together to fine-tune a DNA decoding process that could lead to faster and more affordable sequencing and personalized medication.
As part of the July 1 agreement, Roche's subsidiary, 454 Life Sciences, will market and distribute future products based on IBM's DNA Transistor technology. In addition, IBM will license the technology and continue to provide expertise and resources.
Roche, which describes itself as the largest biotech company in the world, holds "expertise in medical diagnostics and genome sequencing," IBM announced.
"Sequencing is an increasingly critical tool for personalized health care," Manfred Baier, head of applied science at Roche, said in a statement. "It can provide the individual genetic information necessary for the effective diagnosis and targeted treatment of diseases. We are confident that this powerful technology, plus the combined strengths of IBM and Roche, will make low-cost whole genome sequencing and its benefits available to the marketplace faster than previously thought possible."
Ajay Royyuru, senior manager of the IBM Research Computational Biology Center, explained that DNA sequencing has come a long way in 10 years, as originally genome sequencing was not yet possible. Now the technology is available but costly, he said.
"The next step we need to take is to make it faster and better in quality of readout and scale of operation. Once we reach that point, which could be [in] the next five years or 10 years, then I think we have the potential of being able to apply that routinely to the practice of medicine," Royyuru said in an interview with eWEEK.
The goal of the project is to read DNA quickly and efficiently at a low cost. If successful, this process would allow doctors to more effectively match medication to patients.
IBM's DNA Transistor technology, comprising a combination of metal and silicon insulation, uses electrodes to thread DNA molecules through a nanopore, a hole the size of a nanometer, or one-billionth of a meter.
Royyuru compared the creation of the nanopore to punching a small hole through a piece of paper with a pencil.
"We're able to drill a hole small enough and operate it electrically to put the DNA through the pore. All of that we have shown is workable," he said.
In the next phase of development, IBM and Roche will work on moving the DNA through the nanopore.
"Then we will have shown at that point that we can control the passage of DNA," Royyuru said.
Slowing down the DNA as it travels through the nanopore makes genetic data readable, he said.
Personalized medication can eliminate some adverse side effects of current drugs. Some preliminary cancer drugs based on the DNA Transistor technology have already reached the market, Royyuru noted.
"Today what everybody does with medicine is trial and error," Royyuru said. "They give a certain treatment because it worked on most people before. But they have no way of knowing if it will work on you or not. They have side effects that are worse than what you're trying to treat."
Ultimately, the technology has the potential to improve throughput and reduce costs, so human genome sequencing could be purchased for $100 to $1,000.
In addition to the announcement, IBM has posted a video of how the DNA Transistor technology works. [See above - AJP. This announcement, though may appear "earth-shaking" for the shere size and dominance of Big IT by IBM and Big Pharma by Roche, has been expected for a long time, and both the announcement and the video actually fall short of the expectations. "Nanopore Sequencing" is not lead by IBM, but Pacific Biosciences (with IntelVC $100 M investment is about to ship their equipment to R&D labs ($695,000 apiece), Oxford Nanopore (UK, backed by Illumina) is also ahead with the technology development. Last but not least, mastermind and developer of the original 454 Roche sequencer (now largely obsolete) Jonathan M. Rothberg, Ph.D. Founded and is CEO of Ion Torrent - with a desktop-printer-size nanosequencer priced at about $50k. The announcement is particularly disappointing since it erroneously refers to "decoding DNA" - while there is not a word anywhere that IBM would focus on the NEXT STEP (beyond "sequencing" that the DNA transistor will do who knows when), and target "recursive genome function". By far the most positive aspect is, truly making history, that "doing genomics" is now branded by the world's two largest monsters as "thinking physical". Now the question is that in addition to physics of the sequencing device, where is the theoretical physics that Schrodinger started in 1943 "What is Life" with his prediction of an aperiodical chrystal where covalent bondings of H ions encode life. We can now proceed to substitute "aperiodical' with the more precise "nonlinear dynamical, fractal & chaotic arrangement (and re-arrangement... through normal and derailed recursion) of the bonding sequence. That is the true "decoding" task. - Pellionisz_at_JunkDNA.com]
How to Build a Better DNA Search Engine
The techniques for indexing Chinese language websites could dramatically improve the speed of bioinformatic searches, according to research by SOSO, the third-largest Chinese search engine.
If there's one thing that Google has taught the current generation of web savvy surfers, it is that internet searches are quick. The small print at the top of every search it delivers stamps this idea into the culture of search.
Type the word "physics" into the search engine, for example, and it delivers 102,000,000 results in 0.21 seconds. That's mind-blowingingly fast.
That might sound like good news for researchers combing bioinformatic databases. These databases are huge and growing exponentially. They contain, for example, the rapidly increasing number of genomes from different species around the planet as well as the genomes of different individuals within the same species.
Given our experience with web search, it's easy to imagine that finding a gene that is common to more than one organism or individual ought to be as quick as searching Google. But it isn't.
The reason according to Wang Liang, a computer scientist at SOSO.com, one of the big three search engines in China, is that bioinformatics has failed to exploit the basic search techniques that have made search engines like Google so quick.
Most bioinformatic searches use either the BLAST or FASTA algorithms. These essentially compare the data from one genome with the data from another, then with another and so on. That's satisfactory when there are a relatively small number of genomes but it quickly becomes unmanageable as the number of genomes increases exponentially.
Search engines faced exactly this problem 20 years ago with the growth of the world wide web. Search engines initially indexed the web by recording the words that each document contained. Searching for a specific word then meant looking for it in one web page, then in another and another and so on. This approach becomes increasingly slow as the number of documents grows..
So the engines took another approach: they turned the indexing process on its head creating what is known as an inverted index. "The idea of an inverted index is very simple," says Liang.
Instead of creating a list of web pages and the words on each page, the indexing process records for each word, a list of webpages where it appears.
So a search now looks only through the list of words that a search engine has indexed. When it finds the word, that entry also records the webpages where it appears. In other words, instead of searching an index of webpages to find a specific word, you search though an index of words to find the webpages where it appears.
That dramatically simplifies things but there are various complexities that making the indexing process tricky. For example, in English, the spaces between words show clearly where each word starts and finishes. That isn't the case in genetic data. So one important questions is what constitutes a word. [This venerable question was poised by the classic approach by Stanley et al., 1994 to "arbitrarily assume that a 'word' is a random 3-8 nucleotide string - AJP]
Liang says that an important clue comes from the way search engines index languages like Chinese where there are no spaces between words either. One way to index a Chinese document is to segment the text into n-grams, words that are n-letters long. So you start by segmenting it into 1-grams, one letter words, then 2-grams, two letter words. A search for a 3 letter word, such as ABC, can then be done by searching for the 2-grams AB and BC.
In fact, some Chinese search engines work in exactly this way, by indexing all the 2-grams.
But how many letters are there in a genetic word, what n-grams should a search engine index? A 1-gram segmentation gives only four words, the base nucleotides A, T, C and G. But that's no good because the combined searches needed for longer words are then unmanageable.
The answer comes from the statistical distribution of words in DNA sequences which Liang says follows Zipf's law. This essentially states that in any long document, 50 per cent of the words appear only once. This can be used to find a kind of average length length of DNA words.
In Chinese for example, the percentage of 1-gram words that appear only once is less than 50 per cent, the percentage of 2-gram words that appear only once is about 50 percent and the percentage of 3-gram words is less than 50 per cent. So 2-gram words are a good average.
Liang applies the same criteria to find the average length of words in the genomes of arabidopsis, aspergillus, the fruit fly and the mouse. And he finds that a good average word length is about 12 letters. So the best way to index genome data is to look for 12-grams, he says.
None of this needs any new technology to complete. Liang says that the open source search engine Lucene is the perfect forum in which to do the work and, impressively, has even used it to build a rudimentary bioinformatics search engine himself.
It makes sense that the huge improvements in search that have been made by commercial search engines ought to find application in the bioinformatics world. Perhaps there's even a decent business model in such a plan, for example by serving ads targeted at the kind of people who do bioinformatics search.
The only question is who will lead the way in this area. And if this work is anything to go by, it looks as if the Chinese search engine SOSO has the lead.
[The idea that the DNA is a "language" (certainly not English, not even a "Russian novel" as Esther Dyson likes to allude to, and while wishing good luck to the Chinese, the FractoGene approach suggests that it is no human language at all - goes back at least to Eugene Stanley et al, 1994, as elaborated by AJP in Simons and Pellionisz, 2006. However, as it was presented by Pellionisz in Cold Sping Harbor 2009 , the early approach by was tainted by (totally arbitrarily, as the authors admit) assigning a "DNA word" randomly, as a 3-8 nucleotide string. The seminal work by Rigoutsos (2006) is referenced there as a method of identifying "words" of DNA - and on that basis Pellionisz' FractoGene shows that a full DNA sequence, when broken up to "repetitive words" follows the Zipf-Mandelbrot Parabolic Fractal Distribution curve. If Dr. Collins is right that "the DNA, like mathematics, is God's language" - it is unlikely that it is English or Chinese (or any human language) - but Nature's Geometry speaks Fractal. This, actually, may be rather fortunate for creating the "universal search engine" - not optimized for either English or Chinese, but for the MEANING of concepts - AJP]
'Jumping genes' make up roughly half of the human genome
Wired
By Brandon Keim
2010-06-25
Recursion Life Cycle of a Retrotransposon
Geneticists have revealed that Transposons or 'jumping genes', which create genomic instability and are implicated in cancer and other diseases, make up roughly half of the human genome.
"Now it looks like every person might have a new insertion somewhere," says senior author Scott Devine, associate professor of medicine at the University of Maryland School of Medicine's Institute for Genome Sciences.
Transposons are like small self-replicating sequences that transfer themselves from one generation to another. But the scientists faced the overwhelming problem of finding a new insertion within three billion base pairs.
Their study indicated transposons are jumping in tumours and are generating a new kind of genomic instability. They are already known to interrupt genes and cause human diseases, including neurofibromatosis, hemophilia and breast cancer.
Scientists believe a process called methylation, which silences genes during differentiation also shuts off transposons' ability to jump. Analysing the patterns of mutations in the lung tumours suggested that during tumour formation, modified methylation patterns may be allowing transposons to re-awaken, Devine says.
The results are published in the June 25, 2010 issue of Cell. (ANI)
Reference:
R.C. Iskow, M.T. McCabe, R.E. Mills, S. Torene, E.G. Van Meir, P.M. Vertino and S.E. Devine. Natural mutagenesis of human genomes by endogenous retrotransposons. Cell (2010).
[The First Decade after The Human Genome Project was a painful transition. The Second Decade will be the Revelation of "Recursive Genome Function". While Barbara McClintock was ridiculed as a "Kook" for her "Jumping Genes" notion, and 35 years after her publication received the Nobel Prize in 1983, "The Human Genome Project" still (erroneously) assumed that the DNA is "static" (i.e. the sequence of 6.2 Bn A,C,T,G-s explains everything. In 2002, the FractoGene notion suggested nonlinear dynamics (fractal and chaotic properties) of genome function, but the "double heresy" of running against both Crick's "Central Dogma" and the "Junk DNA" axioms made it possible for the "old school" to hold the line till "The Decade of Recursion" (now "recursive genome function" stands at 69,300 hits on Google). Cancer, as the epitome of regulation-derailment, is likely to become a central target of the now liberated new decade of research, analysis, interpretation - and up to personalized therapy and cure. - AJP]
A coding-independent function of gene and pseudogene mRNAs regulates tumour biology
Laura Poliseno1,4,5, Leonardo Salmena1,4, Jiangwen Zhang2, Brett Carver3, William J. Haveman1 & Pier Paolo Pandolfi1
Nature 465, 1033-1038 (24 June 2010) | doi:10.1038/nature09144; Received 21 September 2009; Accepted 22 April 2010
Cancer Genetics Program, Beth Israel Deaconess Cancer Center, Departments of Medicine and Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts 02215, USA
FAS Research Computing & FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts 02138, USA
Human Oncology and Pathogenesis Program, Department of Surgery, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, New York 10021, USA
Abstract
The canonical role of messenger RNA (mRNA) is to deliver protein-coding information to sites of protein synthesis. However, given that microRNAs bind to RNAs, we hypothesized that RNAs could possess a regulatory role that relies on their ability to compete for microRNA binding, independently of their protein-coding function. As a model for the protein-coding-independent role of RNAs, we describe the functional relationship between the mRNAs produced by the PTEN tumour suppressor gene and its pseudogene PTENP1 and the critical consequences of this interaction. We find that PTENP1 is biologically active as it can regulate cellular levels of PTEN and exert a growth-suppressive role. We also show that the PTENP1 locus is selectively lost in human cancer. We extended our analysis to other cancer-related genes that possess pseudogenes, such as oncogenic KRAS. We also demonstrate that the transcripts of protein-coding genes such as PTEN are biologically active. These findings attribute a novel biological role to expressed pseudogenes, as they can regulate coding gene expression, and reveal a non-coding function for mRNAs.
[Bye Junk DNA - one more time... - AJP]
Business Models for the Coming Decade of Genome-Based Economy - the past and transition
June 26, 2010
Andras J. Pellionisz,
Ph.D. in Computer Engineering, Ph.D. in Biology, Ph.D. in Physics
Former Research Professor of New York University,
Founder of International Hologenomics Society
Founder of HolGenTech, Inc.
Founder of HelixoMetry
Silicon Valley, California, USA
Genomics is a Science of Heredity, right? Nuclear Physics is a Science of Fission and Fusion of Atoms, is that correct? Yes -- both Nuclear- and Genome-Experimentation and Theory started with Pure Science, before Technology Applications cut in with full force. Both “pure science approaches” quickly became mostly government-supported R&D projects of significant size and potential. After the initial paradigm-shifts of Atoms splitting, or Genomics becoming integrated with Epigenomics and transformed into Informatics (HoloGenomics), a Nuclear Industry and likewise, a new phase in Genome-Based Economy resulted. It may not grab the attention of headline-makers that the true success or failure of (untrue) “Decoding the Human Genome” really lies in the soundness of underlying business models.
With the 10th Anniversary of the “Completion” of the “Human Genome Project” (HGP) upon us by the 26th of June, 2010, there is an increasing, and increasingly controversial debate over its origin and aftermath through its First Decade. The controversial origins, as they are amply documented, will not be belabored here. Let’s take a look on the future from the perspective the sheer force of business models.
In the aftermath, the First Decade was a turbulent transition. The coming second is re-shaping the World, and some picture the US on a potential brink of a decline.
Juan Enriquez, now director of Excel Venture Management (Boston) sums it up this way: (also in his book: The Untied States of America):
“Countries that fail to commercialize their research discoveries remain diminished,” Enriquez points out. “Take the U.K., for example: They discovered penicillin and DNA, but preferred to let the knowledge sit in a college lab somewhere, rather than let the professor, god forbid, benefit from the discovery. The moment we start adopting those same attitudes in the United States, we will begin to decay.”
This perilous inflection point, leading us to the second Decade after HGP, did not come without an almost decade-old warning by Excel Venture Manager Juan Enriquez. The assessment of the past decade was actually predicted by Harvard Center of Economics director Juan Enriquez (2001) in his epoch-making bestseller “As the Future Catches You”. He established the historical comparison of “Genomics” and “Digital” for their role in Empires rising or falling.
His prediction was based the core Business Model of Genome-Based Economy-Round One, that has happened in the 1970-s - although it is not much talked about these days. Dr. Enriquez refers to Norman Burlag’s “Green Revolution” that elevated tenfold yields of crops such as rice, to a large extent by means of genetic improvements, thereby saving the lives of at least 2 Billion people from starvation. Lives saved were mostly Chinese and Indian – thus is the appreciation of about 3 Billion of presently 7 Billion people of the World. Norman Borlag’s ouvre, selling seeds of high-yield crops was based on a rock-solid simple business model for the World, driving it by feeding the starving – and as corollary making him not only the Nobel Peace Prize Laureate in 1970 but also the most decorated person of all times - second only to Mother Theresa.
The Science of Genomics, by recombinant DNA, was “consolidated” in 1972 (Ohno) into an oversimplified view of the structure of the Genome, derailing it from underlying business models. The “all-important Genes” (fairly short sequences of DNA producing RNA and then proteins), while those parts not obviously coding for proteins (as turned out later, 98.7% of human DNA) were to be "safely ignored" as “Junk DNA”, based on Crick’s “Central Dogma” (originated in 1956 that Protein information never recurses into DNA – why bother with the “Junk”?).
Based on research and technology, recombinant DNA focused therefore on genes, they industrialization was based on research by Boyer and Norman (1973). GenenTech generated a business model for Genomics, entering Medicine through Big Pharma: by the “One gene, one disease, one billion dollar pill”. Almost at once, the FDA, regulating the US business model was Chartered in 1976 based on the (false) premises to the effect that “since we all have the same genes, criteria of clear benefits overriding acceptable risks should apply to everyone; ‘one size fits all’”. The first and most significant Gene-business (Genentech, expressing a human gene in bacteria) produced hormone somatostatin in 1977, and synthetic human insulin in 1978.
In a parallel line of developments, 1975, Fredrick Sanger (the only living double Nobel-Laureate) announced that he had developed an efficient method to determine the order of base pairs of DNA. Alan Maxam and Walter Gilbert (Harvard) independently developed a completely different method. This method was announced to molecular geneticists in the summer of 1975 at scientific conferences and circulated as recipes among molecular geneticists until formal publication in 1977. Half a decade later, many groups began successfully to automate the process, in North America, Europe and Japan. The first practical prototype was produced by a team at the California Institute of Technology in 1986, under the direction of Lloyd Smith, as part of a large team under Leroy Hood. This prototype was quickly converted to a commercial instrument by Applied Biosystems, Inc., and reached the market in 1987.
Independent of business models (if any), inherent in genome sequencing, the remote possibility of sequencing the entire human genome caught the fancy of Big Science of the US Government. With the Office of Management and Budget's approval, the DOE committed its first funds for human genome research in October 1986. After the NIH started its own genome effort the next year, a coordinated project was formally launched. In 1988, the DOE and the NIH signed a Memorandum of Understanding that committed the two agencies to work together by coordinating activities and leveraging their respective strengths as assets. The official "clock" on the project was started on October 1, 1990 with Dr. Watson behind the wheel. Assumably, with a major (publicly known) motivation that his son, Rufus, is affected by schizophrenia, and a complete catalogue of all human DNA would hopefully cast the net big enough to catch “the missing gene” for this and other feared diseases. Thus the NIH-DOE led, multi-agency and multi-national (multi-governmental) HGP became perhaps overly “one gene – one disease” oriented. Since governments don’t tend to think in terms of “business model(s)”, HGP was not directed by business model(s), nor did it proceed with the diligence for speedy accomplishments. (Government-sponsored R&D projects are usually wished to be kept alive forever, understandibly with well thought-of cost-overruns, enough to justify an ever-increasing budget from year to year, yet not too big to raise eyebrows resulting in a shut-down of the government project).
Oh yes, a huge business opportunity in DNA sequencing did not escape the attention of those not so much medical research- but business-oriented. Head of the US NIH, Bernadine Healy wished that the US goes down on the pathway of patenting human genes – only to collide “head-to-head” with Jim Watson who, as an epitome of “pure research scientist” wanted Genomics remain a “free for all”. As a result, in 1992 Watson resigned and Dr. Francis Collins, M.D., Ph.D., already “with a claim to fame to his name” (having identified the gene of Cystic Fibrosis) took over governance of The Human Genome Project. With Francis Collins at the helm, the US government (with a number of countries in tow) proceeded at a snail-pace, “but free for all”, and even more “gene-focused”, with Dr. Collins, as a formerly practicing M.D. focusing on the possibility of eventually transforming medicine.
Enter Craig Venter, Ph.D., the maverick doer, turned-off by both by “medicine” as applied to some of the 70,000 Vietnam-victims with hundreds dying in his arms, and also (as someone who experienced how NIH worked, by working for it), disenchanted e.g. when one of his NIH proposals was not only rejected, but pontificated as “un-doable” (thus he did the multi-year project in a few months, with your taxpayer's money spent on who knows what).
Craig Venter threw his hat into the ring, with the much-ridiculed idea that he would sequence the human DNA by applying the “shotgun sequencing” (“even a monkey can do that…”) and would patent the found genes (“he wants to own the genome like Hitler wanted to own the World”) – and all would be based on private enterprise money (“he can’t raise that kind of money, anyway”). Craig did raise the money, deployed his “super fast monkeys” (computers) to assemble the shotgunned fragments, and while officially it was a tie exactly ten years ago, Craig Venter clearly won the race for sequencing – but lost the opportunity to patent any of it, since that business model he was banking on was invalidated. (Thus he turned later to the business model of patenting modified DNA, to be synthesized for energy and new materials business).
However, as the Human Genome Project neared its “first draft” in 2000 – with the 140,000 expected genes were nowhere to be found, the Business Model of Big Pharma with “one gene, one disease, one billion dollar pill” was dead on arrival on the news of “finishing” the Human Genome Project. As a long-shot result, as of 2009 the Swiss pharmaceutical conglomerate Hoffman-La Roche now completely owns the US pioneer-business based on gene-technology (Genentech).
Sequencing Business, however, took off as now the third generations of private enterprise-built sequencers – based on the dubious business model that Big Science US government projects (e.g. ENCODE) and foreign governments (e.g. China) did and would go ahead and sequence DNA “no matter what” (both China and Russia claims “national security” in the integrity of the Chinese and Russian genome…, Koreans are sequencing the Korean genome, the Arabs the Arab sequence, Jews the Jewish sequence) – and the general public would just get themselves sequenced once the price dips below the magic number of $1,000 per "affordable full human DNA sequence". (For what? Detroit must have been more worried about providing the network of gas-stations for their assembly-line affordable Ford T vehicles, useless without the other half of the business-model…)
There is a lot to be read these days how the First Decade spectacularly fell short of declared expectations that it would “revolutionize medicine” – that just did not happen as expected. Why don't we talk about the Business Models?
Genomics is Science and Technology -- while Medicine is a Business (in the US – in other civilized countries it is a government service). One can not turn apples into oranges. Therefore is the “surprise of the first decade” – that rather than finding cures for diseases (the much hoped for and hyped up “medical revolution”) – postmodern genomics found Business Models for Prevention faster than Business Models, while “Personalized Medicine” has to develop its verified Business Models to work.
“Medical Genomics” is to collide with the Medical Establishment; will be the strictly regulated, meticulous but high-yield "slow track". “Consumer Genomics” will be the “fast track”, since it empowers by user-friendly automated those daily decisions based on consumers’ freedom of choice that could be done “the old fashioned way” (see the much-belabored YouTube "Shop for your Life!" business model by HolGenTech, Inc.to proceed on the “fast track”
[Other emerging business models will be reviewed as this series continues - AJP]
Business Models for the Coming Decade of Genome-Based Economy - the transition and future
Representative samples (beyond the Consumer Genetics Business Model shown above) are as follows - all based on the key question of postmodern genomics; (holo)genome regulation:
INDUSTRIALIZATION OF GENOME REGULATION RESEARCH
At a first glance, this appears to be a contradiction. How can "research” be advanced by “industrialization”? A highly visible precedent provides an explanation that it is not an oxymoron. Nuclear Physics faced (and still faces) several scientific challenges – and the most notable how energy can be harvested from nuclear fission and fusion was (and is) driven by the massive force of "industrialization" (including defense industry) - rather than the relatively meager resources available for "pure research".
Likewise – as acknowledged by the new generation (over 127,000 views of YouTube "Regulatin' Genes") “regulating genomes is crucial for development”. However, though a peer-reviewed science article that opened the way by surpassing two obsolete axioms (Crick’s “Central Dogma” and Ohno’s “Junk DNA”) that together blocked genome informatics for over half a Century (“The Principle of Recursive Genome Function”) appeared in 2008 and Google yields for "Recursive Genome Function" 69,100 hits - there seems to be no program by any US government Agency that would invite spearheading a focused effort in advanced fractal & neural network theory to resolve the crucial problem of genome regulation. At least two Business Models, however, will fuel and assure progress; since both “Synthetic Genomics” and DTC of "Structural Variants" require an algorithmic (software enabling) understanding of (holo)genome regulation..
INDUSTRIALIZATION OF SYNTHETIC GENOMICS
As mentioned in the overview of the past, the Business Model by Craig Venter; patenting industrially useful genomic applications was invalidated by government decree of 2000. While patenting “genes", therefore, is not viable, the Venter Institute (with Craig Venter, Ham O’ Smith, Clyde Hutchison, John Glass et al.) invented the Business Model of modifying gene-sets of organisms with small enough DNA to synthesize them – and since a modified gene-set is not an existing product of Nature, it is patentable. However - until and unless the regulatory mechanism is understood (even in the Mycoplasma Genitalium with 7% non-coding DNA), any modification of the gene-set must be “stealth” to the largely retained regulatory sequences. Thus the 15 years to find the combination of small enough modifications to "boot the synthetic DNA". While the enormous potential in Synthetic Genomics was never questioned, and now with an "existence proof“ delivered, this Business Model will be a major industrial driver towards understanding genome regulation.
INDUSTRIALIZATION OF DTC STRUCTURAL VARIANTS
Never believing in either Crick’s Central Dogma or Ohno’s JunkDNA mistaken axioms, in 2005 I established the International PostGenetics Society, which became the first international organization to officially abandon the "Junk DNA" misnomer on its European Inaugural, October 16, 2006 (8 months before the US government’ ENCODE program concluded in the same). At the establishment of the Society (in 2008 becoming International HoloGenomics Society), I posted (and updated) the site of “Junkdna diseases” – since with the notion that 98.7% of the human DNA is not there (as Ohno stated, p.367) for “the importance of doing nothing” it followed that structural variants (to systematically describe the common patterns of human genetic variation revealed in the HAPMAP project, with the original span from 2002-2005, costing $138 Million, extended twice, 2007, 2009 with the overall cost exceeding $500 M) even in the "non-coding DNA” are associated with identifiable diseases. The fact of all kinds of “structural variants” raises both a scientific and practical dilemma. Scientifically, it seems obvious that “structural variants” could either represent harmless “human diversity”, or “genomic defects” with an impact on hologenome function. The brute force approach would have to plough through all variants and parse them according to variant genotypes if associated with harmful phenotypes or innocent to the function. In contrast, any algorithmic (software enabling) understanding of genome function would show parametric variants, separated by defects that affect the required syntax. (For instance, in a Mandelbrot set, the Z=Z^2+C, with different numbers of the C constant all yield “parametric variants”, while glitches in squaring through some of the recursions the complex number Z result in syntax errors; fractal defects.) Thus I proposed the FractoGene (2002) algorithmic approach (cost was shouldered and thus is now unencumbered by the IP-developer, AJP), and FractoSoft is now acquired by HolGenTech, Inc., with IP held under HelixoMetry.
Since the practical tool of interrogating DNA was hitherto available by Affymetrix/Illumina microarrays, yielding Single Nucleotide Polymorphisms (SNP-s), the "Industrialization of Structural Variants" started by DTC genome testing companies (DeCodeMe, 23andMe, Navigenics, etc). As reported in this column, 23andMe started a veritable revolution to correlate, in a "data-driven model", patterns of SNP genotypes with (patterns) of phenotypes. Lately, however, a great assortment of "structural variants" emerged, e.g. “copy number variations” (different numbers of repeats of sequences containing many thousands of nucleotides), etc. Structural variants with complexities beyond SNP-s require tools beyond microarrays - and call for "affordable full DNA sequences".
The Business Model of mining for, and establishing correlation of complex structural variants and pathological phenotypes will be a major driver for algorithmic (software enabling) understanding of (holo)genome regulation. An extremely complex, and socio-economically towering example is cancer research, therapy and cure, where the massive rearrangement of the genome (that a layperson might describe with the colloquial meaning of “chaotic”) – indeed (in a mathematical sense) a fractal and fractured alteration of DNA sequence – widely acknowledged to be a disease (derailment) of genome regulation (with fractal defects, “jumping genes” of retrotransposons, copy number variations, fractures of entire chromosomes). Successes of algorithmic approaches will put an enormous economic pressure both on privately held genome informatics (genome computing) companies, as well as on Big Pharma, to build the required Business Model.
INDUSTRIALIZATION OF GENOME REGULATION IN BIG PHARMA
Perhaps the biggest "disappointment" of the First Decade after The Human Genome Project was that it has not developed "cures" for some of the most dreaded hereditary diseases. In my opinion, it was (and is) entirely unrealistic to expect cures e.g. for "regulatory diseases" (like cancers) without a hard-core understanding of genome regulation. While this topic was mentioned above, another class of medications, with a historical precedent, can also illuminate the same point. Alexander Fleming did not quite understood in 1928 how the fungus Penicillium notatum stopped the growth of bacteria - could still create a revolution of antibiotics. There is already a modern precedent (Merck's aquisition of SiRNA for $1.1 Bn) to show how small interefering RNA-s could be applied - but it is also obvious that the "Big Pharma Business Models" (e.g. of the use of microRNA-s) will be fiercely proprietary. - AJP
June 18, 2010
Genomeweb
Mike Mandel, from the Mandel on Innovation and Growth blog, says the most "significant economic event of the past decade" is the "failure of the Human Genome Project to deliver medically significant results."
Ballooning healthcare spending, low job growth and a big trade deficit are strangling the US economy, he says, and "the Human Genome Project had … the potential to be a powerful antidote to all three of these problems." But Mandel says there's reason to be optimistic. The US has invested heavily in biotech, new technology and health, and "the research has gone great." All we need to do to capitalize on this investment is to bridge the gap between research and commercialization, which has been done before, Mandel adds. "So I'd say that the odds are good that the Human Genome Project will have a significant economic impact over the next 5 to10 years," he says....
[I agree with Mandel - but see some need to spell out how the Industrialization of Genomics is to be implemented; see the news on 23andMe below, and my ensuing essays - AJP]
23andMe Publishes Web-Based GWAS Using Self-Reported Trait Data
June 25, 2010
By a GenomeWeb staff reporter
NEW YORK (GenomeWeb News) - In a paper appearing online last night in PLoS Genetics, Web-Based, Participant-Driven Studies Yield Novel Genetic Associations for Common Traits researchers from 23andMe and Columbia University reported the first genome-wide association findings stemming from 23andMe's web-based, participant-driven research program.
The study, which involved more than 9,000 individuals genotyped through 23andMe's direct-to-consumer testing service, looked for genetic associations related to nearly two-dozen common traits. Using this web-based survey approach, the researchers verified previously reported associations for five traits and identified new SNPs linked to four of the traits, including hair curl, freckling, sneezing in response to light, and the ability to detect asparagus metabolite odors in urine.
"[W]e confirm that self-reported data from our customers has the potential to yield data of comparable quality as data gathered using traditional research methods," co-author Anne Wojcicki, president and co-founder of 23andMe, said in a statement.
For the study, the team drew from 23andMe's direct-to-consumer genetic testing community, bringing together SNP and survey data for thousands of customers. As such, they explained, the researchers were able to put together "a single, continually expanding cohort, containing a self-selected set of individuals who participate in multiple studies in parallel."
"Our ability to contact individuals multiple times and ask follow-up questions puts us in a position to zero in on associations that could be the building blocks for future research aimed at prevention, better treatments, and potentially cures for a multitude of diseases and conditions," lead author Nicholas Eriksson, a statistical geneticist at 23andMe, said in a statement.
Each of the 9,126 participants provided information on at least one of the 22 common traits. These traits were selected, in part, based on heritability and the feasibility of collecting related phenotype data easily in a web-based setting. The traits included everything from hair and eye color to "photic sneezing," a predisposition for sneezing when looking at the sun or other bright light.
The team then integrated this data with genotype data for 535,076 SNPs assessed using the Illumina HumanHap550+ BeadChip. At least 1,500 unrelated individuals of northern European ancestry were evaluated for each of the 22 traits.
Using this approach, the researchers found associations for eight of the 22 traits. Among them: previously reported associations for traits such as eye color, hair color, and freckling and new associations for four of the traits.
For instance, a new freckling-associated SNP turned up in an intron of the zinc finger gene BNC2, while hair curl was associated with SNPs near the TCHH, LCE3E, WNT10A, and OFCC1 genes.
In another new association, the team found that the tendency to sneeze when looking into light was linked to two SNPs: one near the ZEB2 gene and the PABPCP2 pseudogene and another near the NR2F2 gene.
The researchers also found that individuals who can smell an asparagus metabolite called methanethiol in urine tend to carry SNPs in a linkage disequilibrium block in and around 10 olfactory receptor genes. Of these, the most significant SNP fell upstream of the olfactory receptor gene OR2M7.
In an editorial appearing in the same issue of PLoS Genetics, the journal's deputy editor-in-chief Gregory Copenhaver and its gene expression profiling and natural variation section editor Greg Gibson, who are affiliated with the University of North Carolina at Chapel Hill and the Georgia Institute of Technology, respectively, addressed ethics, consent, and data access concerns related to the 23andMe study.
The pair noted that the study's publication was delayed because the journal wanted to deal with several such issues — for instance, ensuring that individuals included in the study were not pressured into partaking in the study and understood that they were participating in genetic research. The editorial also addressed institutional review board questions arising from the study.
"After considering all of the evidence, we decided that publication, accompanied by an editorial providing transparent documentation of the process of consideration was the most appropriate course," Gibson and Copenhaver wrote. "[W]e have had extensive discussion with the authors of this study to address our concerns and to update their processes, but we anticipate broad evolution of GWAS consent and review in the near future."
Meanwhile, the 23andMe team is setting its sights on additional web-based GWAS studies. In their current paper, they noted that the approach makes it possible to ask research questions using data from an ever-expanding group of individuals.
In addition, 23andMe said yesterday that it has now secured IRB approval for its web-based research protocol. According to the company's blog, The Spittoon, 23andMe customers will now be given more leeway over how their genetic information is used and must "explicitly choose to allow their genetic and survey data … to be used in published research."
[What 23andMe started is an Industrial Revolution of conducting scientific research in the future; a Google-type "data-driven" approach that will minimize the "brute force" necessary for handling masssive amounts of data. Of course, one may ask why was the effort focused on "frivolous traits" like freckles or smelling asparagus in the urine - when it is obvious that the methodology eminently applies to severe phenotypes with massive medical impact. It is noteworthy that the paper was delayed over a year since among others it alters the way how volunteers provide information. This is almost nothing (a technicality) compared to how the methods revolutionize possibly the entire medical research. Since this collides "head on" with "medicine as is", the approach carefully avoided hard-core "medical" questions - still 23andMe is one of the 5 DTC genome testing companies that will be investigated by FDA and the Congressional Committee (on Energy and Commerce...)- AJP]
Francis Collins: the extended genome anniversary interview
The Times
06/24/2010
Ten years ago on Saturday, Francis Collins and Craig Venter walked onto the White House lawn with Bill Clinton, to announce the completion of the first draft of the human genome. I had the opportunity to sit down this week with Dr Collins, who's been visiting the UK ahead of the anniversary, and my interview with him appears in the paper today.
My piece has focused on Collins's prediction that most of us, at least in the developed world, will probably have had our complete genetic codes sequenced by the time the reference genome is 20 years old. But we spoke about much more than that, and I've included some of the highlights of our conversation here.
Perhaps of greatest current interest, given the FDA's current clampdown on direct-to-consumer genomics companies, were his thoughts on how this fledgling industry should properly be regulated. He accepts that there is a case for some regulation, which should focus on risk and accurate test results. But he is very wary of over-zealous regulation that might stifle innovation, or unreasonably restrict individuals' access to the contents of their DNA. And he doesn't think such access needs always to be mediated by a doctor.
The direct quotes follow after the jump...
On regulation
I started by asking Collins what he thought of FDA's intervention on DTC genomics. He said:
"The FDA is being fairly reasonable about their approach, in the sense that I think they are sensitive in not wanting to shut down a set of scientific advances that are potentially going to become a valuable commercial enterprise.
"I think the approach they're going to take is to focus on those kinds of test that are associated with risk, and have a risk-based oversight system rather than a knee-jerk system of 'oh, it's a genetic test, we need to review it no matter what'. That's clearly what's needed, and some groups have been arguing for that for 10 years.
"I do think the time has come, when you look at some of things that are out there on the web that are quite unsubstantiated scientifically, to pay some attention to that. Peggy [Hamburg, the FDA Commissioner] and Josh Sharpstein [Hamburg's deputy] are aware of the need to do this on a rational basis and not to slam the door. But I do think the public is increasingly concerned about whether this occurring in a completely unregulated way is going to be of benefit to them.
"I'm not sure exactly where this will go over the next year or two, or what the implications will be for access to genetic information. I am both a strong proponent of the need for quality of what's offered, but I also believe in patient empowerment, and the opportunity to find out something about themselves if they want it seems like something we should be reluctant to get in the way of, so long as the information is scientifically valid.
"Regulators have a tough job. They need to be sensitive to not stifling innovation, but they also need to protect the public against really unscrupulous use of new technologies. And in that regard, by preventing the real misuse of technology, they're certainly protecting the innovators from seeing a complete meltdown and a distrust of technology that might persist for years to come.
"So in many ways the regulators are also the guardians of science, in the sense that they keep it from slipping into snake oil, which ultimately does a lot of damage to science. But there is a tough balance, which is one of the reasons the FDA has had such a hard time figuring out how to regulate genetic technology. I give Peggy and Josh a lot of credit for being willing to take this on and do something."
Collins has himself been tested by several of the DTC genomics companies, and I asked how his experience as a consumer had influenced his thoughts on regulation:
"My own experience with this did inspire me to take some action which I probably should have taken anyway. No-one should generalise from your own personal experience to make federal policy, but there's plenty of other data to show that when individuals are given predictive information about the future, at least some of them do find that useful and do modify their health behaviours, and are able to understand that these are not yes-no black-white answers, but risk factors they might want to pay attention to, just as they pay attention to their cholesterol."
Medical supervision of DTC genetic tests
Next we moved onto the sometimes vexed issue of medical supervision. Should genetic testing always be conducted in concert with a doctor or genetic counsellor? Collins said:
"That of course is one of the hot potatoes. Even within the field of medical genetics there are strong differences. The American Society of Human Genetics thinks that having a medical professional involved is not required. The American College of Medical Genetics thinks that oh yes, there are great dangers if a medical professional is not involved.
"I think my view is that people are in many instances capable of absorbing this educational information without the need for a professional to walk them through, but if they want that they should have access to it quite easily, and should not be hit with information without a medical professional to assist them.
"I've been impressed by the way in which the direct-to-consumer companies have worked pretty hard at this, in terms of providing information and what it does and doesn't mean. But there is probably no substitute for having the opportunity to ask questions of someone who is an expert in the field after you have begun to absorb your own results, and I think people ought to have a chance to do that if they want to.
"I would be very uncomfortable with a system that says no, we know better than you do, you won't understand this information so we're not going to let you have it. There's something that doesn't feel right about that."
Validity and utility
To what extent should test be regulated for scientific validity and clinical utility? Collins said:
"A lot of this debate relates to what you call clinical utility. If you're going to have a test that's marketed to the public, it should have analytical validity, that is the lab should be able to prove that they can do a DNA test and get the sequence right. And it should have clinical validity, that is the test if it says it means something, that should be clearly true. If it says your risk for this SNP goes up for diabetes, then there ought to be evidence to back that up.
"But what about clinical utility? That's so much in the mind of the beholder. I mean you may say knowing your Alzheimer's risk from APOE has no clinical validity because you can do nothing to change your risk by changing your diet or taking drugs or doing Sudoku or whatever. But for somebody who wants to know that information for purposes of planning, and that was shown very clearly by Bob Green's REVEAL study, that is useful to them. So don't tell these people this is not clinically useful. It is clinically useful from their perspective, and we shouldn't be paternalistic about it."
So, I asked, is a light touch what's called for? Collins replied:
"A light touch but a touch that is also focused on risk. For instance, if a lab is offering individuals BRCA1 testing, to individuals with a strong family history of breast cancer, with no pre-test or post-test counselling, that's a problem. If you're talking about highly penetrant conditions where the test result has high medical significance, that's probably not something you should get at Walgreens. For example."
Also important, he said, are the interpretation services that are offered:
"I gather Ozzy Osbourne has had his genome sequenced. Ozzy's probably going to need a little help figuring out what this means."
Cancer genomics
Like many observers, Collins feels that cancer will be a standard-bearer for genomic medicine:
“Cancer is I think going to be right out in front here. And I think we would all expect that within the next decade every cancer identified, at least in countries that have the resources, a full enumeration of what is going wrong in that tumour, and then an ability to match that up with the available therapeutics so you are doing the best possible job of throwing smart bombs, instead of the carpet bombing of traditional chemotherapy.”
"The question is will that be helpful because we have a nice menu of therapies, and we'll be able to pick just one or two that are going tobe active against that patient's malignancy. We have a lot of work to do.
"Could I tell you that in ten years most patients will have both a complete genomic analysis and a choice of compounds that should be clinically active? I don't know, I would hope we will be pretty close to that, and certainly well beyond the menu we have now of targeted therapeutics, which is still a pretty short list. It's going to grow."
Pharmacogenomics as a driver of widespread sequencing
Collins was clear that he thought the potential of pharmacogenomics would be the main driver of widespread sequencing.
"I think it's another great payoff over the fairly near future, and certainly over the next decade. 10 per cent of FDA approved drugs have a label saying something about genetics and its ability to predict a side effect, or something about whether that person is going to respond or have a dose adjustment.
"The problem with pharmacogenomics now, in terms of real mainstream application, is in a certain way logistic. We already know enough variations that could be used in dose adjustments, in terms of the CYP genes, but most of the time the physician doesn't know that much about the science anyway, and there's the problem of sending off the drug sample know, and where do I send it to, and I want the sample now. But, how's it going to change?
"Well, when the sequencing of your genome or mine really does drop into the affordable range of less than 1,000 dollars, it will become very compelling for pharmacogenomics in particular to do it just once, to do it right, to get it into the medical record. There would be no need to take more blood samples, it’s just a click of your mouse to know whether that drug dose ought to be adjusted, or whether there’s a risk of a nasty side-effect you want to avoid. That will be a moment when a lot of the barriers to pharmacogenomics go down." [This is hitherto the clearest endorsement of the need to automate, in a user-friendly manner, choices that by hand would require unacceptable time requirement - AJP]
"When you see the cost of sequencing dropping much faster than Moore's law for computers, we're now down to about $10,000 for a reasonably complete sequence. I can't believe it won't drop to less than 1000 within five years. Will that become the moment then, where at least to people in some kinds of health plans, when it becomes compelling to do it? Good heavens, we spend a lot more than that on all sorts of unnecessary scans.
"Why not just make the case for each of us that this is information that will only gain in value over time, and if it's possible to do it accurately it would be cost-effective, both in terms of prevention and pharmacogenomics and so on? I think that will get pretty compelling.
"What will the timetable be from when it's possible to when it actually happens? That's the key question. A lot will depend on reimbursement and who's going to pay for it? Will third parties see it as a key investment? Where's the capacity going to come from to do all these genomes? Will we have that kind of throughput abilities? I don't know.
"But certainly within ten years I will be very surprised and very disappointed if most people in the developed world will not have their genomes sequenced as part of their medical record, and I would hope it will come even sooner."
Complex disease and the missing heritability
How confident, I asked, was Collins that the "missing heritability" of complex, common diseases would be unlocked over the coming years? He said:
"Nobody knew what the structure would be of genetic variation that contributes to heritability until we started to look for it. But there's certainly a lot more there hiding in the dark matter of the genome. Presumably, that will start to come to light as we are able to look for less common variants with sequencing of lots and lots of genomes from lots and lots of studies. I'm not despondent about that at all. It's just that the structure is not what we thought it might be. [This part of high science would need much elaboration - not possible in a popular science article. Clearly, the "structure we thought it might be (Genes and JunkDNA) are officially out. Francis Collins, at the 10th Anniversary is clear about the obsolete notions on gene/junk structure of the genome, but at this time-stamp he is not yet at the (confessed) realization that the DNA is fractal - AJP]
"It doesn't seem we were wrong about heritability and its contribution to diabetes and heart disease, all of those common diseases, it looks as if heritability is about 50 per cent, which means it's somewhere in there. We just need a finer lens to discover it. That probably means that within the next decade, our ability to make finer predictions about disease risk are going to get pretty good. Then it will be I think increasingly compelling to use programmes for prevention. It's something you can do right now, so long as you're aware you're not dealing with all the information that's lurking in the genome."
Sequencing children
In April, I broke the story that the children of the Solexa entrepreneur John West, Anne and Paul, had become the first minors to be sequenced for non medical reasons. I asked Collins how he felt about that:
"Frankly, that one did make me a little bit uneasy, because here were two kids who were promoting the idea that they were glad to have this, but you have to wonder how could they say otherwise when their dad was the company founder. There are statements out there in the literature, that genetic data on minors should not be obtained unless the data needs to be known, but those may start to look a little dated.
"This leads us to the question about newborn screening, because we do after all already determine a fair amount of genetic information about every newborn. Newborn screening is recommended in the US for 29 diseases. The time will come when it's cheaper to do that by sequencing than by 29 different tests, and at that point wouldn't it make more sense just to do it, and then to have a plan to release that information in a graded fashion as it becomes actionable. I do think we need to preserve the right not to know. That's a substantial component of our resonsibilities. If every newborn is being sequenced, those newborns should have the opportunity to say at 18: 'the rest of that sequence, forget about it.'"
[This is a shining example of popular science reporting (that was obviously proofed by Dr. Collins) - thus devoid of the usual journalistic mistakes that a decade ago "The Genome was deciphered, etc, etc."). Also, the interview is extremely reassuring, especially in view of the almost inevitability that Dr. Collins will testify for the Congressional Committee investigating legislative aspects of "DTC regulators". While in the joint article in NEMJ of Drs. Hamburg (FDA) and Collins (NIH) it appeared that a multi-agency advisorship might be needed for proposing new legislation to update the 1976 mandate of FDA, presently Dr. Collins mentions YEARS, and also points out a turf-war within the Medical Establishment (about the civil rights question if the American people should have all the information about their bodies, including DNA). Thus, the prediction that a) the DTC regulatory issues will likely be parsed into "risk/no risk" subsets, and b) FDA might not have the legal mandate to "shut down" DTC and thus (especially if Dr. Collins leans towards "letting the private industry figure it"), an FDA "moratorium" on existing California legislation on DTC may be the best solution - AJP]
The Big Surprise of the First Decade - The Genome Affects You to Prevent Diseases, Before it Cures Diseases
[Cover of GEO International - with Specials on Genomics/EpiGenomics - AJP]
The "Human Genome Project" will be a Decade Old in two days. Here, in a series of articles, I present the public acceptance of the significance of HoloGenomics (YouTube, 2008, today with 8,171 views) what may become the quickest route to build a business model on results of a Big Science Government Research Project ("The Human Genome Project" - that had fiercely debated a possible "business model" - patenting "140,000 genes"; but ended up finding only about 24,500 genes, patenting none and ending with no business model at all). Francis Collins (see his YouTube at lower left, today with 1,529 views) outlines what the Genome Era may practically mean to us - but as a government administrator not in terms of business models (though his haunch of mobile devices catapulting into lead-role is visually obvious). Genome Computing applications for both genome-testing and for commercial applications were debated (YouTube [not shown], today with 2,093 views) - but the "killer app" of postmodern genomics may well become the user-friendly automation by your smart phone how to shop for goods befitting your genome (see YouTube at lower right, today with 2,100 views). At times when "Home Computers" became available, many asked the question "what it means to me to have a computer in my home?" The trump-card was provided by the software app "Visicalc" (predecessor to Excel), developed in Sunnyvale, CA; that did the same that anybody could do by hand (re-calculating values of cells in a huge spreadsheet) - but did it in an automated, user-friendly manner; blazingly fast. HolGenTech, Inc. "Your Genome; there's an app for that" does very much the same. A huge number of ingredients in myriads of goods can be cross-referenced by hand (in theory...) with known dietary- and environmental impacts of "genomic glitches". It is just not very practical if you have difficulties in memorizing e.g. the 60,000 pages of numbers (listed e.g. in your "23andMe Raw SNP file") and hold in your head that exploding knowledge-base how their dietary/environmental impacts affect your genome. HolGenTech' "killer app" is to automate it for you - AJP
Sergey Brin’s Search for a Parkinson’s Cure
By Thomas Goetz
June 22, 2010 |
Wired July 2010
Several evenings a week, after a day’s work at Google headquarters in Mountain View, California, Sergey Brin drives up the road to a local pool. There, he changes into swim trunks, steps out on a 3-meter springboard, looks at the water below, and dives.
Brin is competent at all four types of springboard diving—forward, back, reverse, and inward. Recently, he’s been working on his twists, which have been something of a struggle. But overall, he’s not bad; in 2006 he competed in the master’s division world championships. (He’s quick to point out he placed sixth out of six in his event.)
The diving is the sort of challenge that Brin, who has also dabbled in yoga, gymnastics, and acrobatics, is drawn to: equal parts physical and mental exertion. “The dive itself is brief but intense,” he says. “You push off really hard and then have to twist right away. It does get your heart rate going.”
There’s another benefit as well: With every dive, Brin gains a little bit of leverage—leverage against a risk, looming somewhere out there, that someday he may develop the neurodegenerative disorder Parkinson’s disease. Buried deep within each cell in Brin’s body—in a gene called LRRK2, which sits on the 12th chromosome—is a genetic mutation that has been associated with higher rates of Parkinson’s.
Not everyone with Parkinson’s has an LRRK2 mutation; nor will everyone with the mutation get the disease. But it does increase the chance that Parkinson’s will emerge sometime in the carrier’s life to between 30 and 75 percent. (By comparison, the risk for an average American is about 1 percent.) Brin himself splits the difference and figures his DNA gives him about 50-50 odds.
That’s where exercise comes in. Parkinson’s is a poorly understood disease, but research has associated a handful of behaviors with lower rates of disease, starting with exercise. One study found that young men who work out have a 60 percent lower risk. Coffee, likewise, has been linked to a reduced risk. For a time, Brin drank a cup or two a day, but he can’t stand the taste of the stuff, so he switched to green tea. (“Most researchers think it’s the caffeine, though they don’t know for sure,” he says. [And in my Google Tech Talk YouTube 2008 where at 7:55 I referred to Sergey's public blog and at 39:36 showed a 2003 science paper asserting modern evidence to the ancient Chinese medicine that ingredients in green tea might help mitigate predilection to Parkinson's - AJP] Cigarette smokers also seem to have a lower chance of developing Parkinson’s, but Brin has not opted to take up the habit. With every pool workout and every cup of tea, he hopes to diminish his odds, to adjust his algorithm by counteracting his DNA with environmental factors.
“This is all off the cuff,” he says, “but let’s say that based on diet, exercise, and so forth, I can get my risk down by half, to about 25 percent.” The steady progress of neuroscience, Brin figures, will cut his risk by around another half—bringing his overall chance of getting Parkinson’s to about 13 percent. It’s all guesswork, mind you, but the way he delivers the numbers and explains his rationale, he is utterly convincing.
Brin, of course, is no ordinary 36-year-old. As half of the duo that founded Google, he’s worth about $15 billion. That bounty provides additional leverage: Since learning that he carries a LRRK2 mutation, Brin has contributed some $50 million to Parkinson’s research, enough, he figures, to “really move the needle.” In light of the uptick in research into drug treatments and possible cures, Brin adjusts his overall risk again, down to “somewhere under 10 percent.” That’s still 10 times the average, but it goes a long way to counterbalancing his genetic predisposition.
It sounds so pragmatic, so obvious, that you can almost miss a striking fact: Many philanthropists have funded research into diseases they themselves have been diagnosed with. But Brin is likely the first who, based on a genetic test, began funding scientific research in the hope of escaping a disease in the first place. [Watch for the fireworks, China-style, if he is told by anyone that his software, helping eliminate any chance of him ever developing Parkinson's has to be censored ... AJP]
His approach is notable for another reason. This isn’t just another variation on venture philanthropy—the voguish application of business school practices to scientific research. Brin is after a different kind of science altogether. Most Parkinson’s research, like much of medical research, relies on the classic scientific method: hypothesis, analysis, peer review, publication. Brin proposes a different approach, one driven by computational muscle and staggeringly large data sets. It’s a method that draws on his algorithmic sensibility—and Google’s storied faith in computing power—with the aim of accelerating the pace and increasing the potential of scientific research. “Generally the pace of medical research is glacial compared to what I’m used to in the Internet,” Brin says. “We could be looking lots of places and collecting lots of information. And if we see a pattern, that could lead somewhere.”
In other words, Brin is proposing to bypass centuries of scientific epistemology in favor of a more Googley kind of science. He wants to collect data first, then hypothesize, and then find the patterns that lead to answers. And he has the money and the algorithms to do it.
[When I presentated my FractoGene (fractal algorithmic) approach in Cold Spring Harbor Personal Genome-2 meeting last September, a leading cancer-research center director elaborated on the newly found facts (since now full DNA sequences of several cancerous humans are available), that their informaticians found all kinds of "patterns" - presently hard to interpret. There, I mentioned that in my first paradigm-shift (from Artificial Intelligence to Neural Networks) "algorithmic pattern recognition" was a core of industrialization of the new science, since sound-patterns of Soviet submarines had to be discerned from the mostly harmless underwater cacophony - and suggested the re-deployment of available technology; this time against cancer. The director, whose forte was not in Informatics, asked "are you looking for a job?" Well, my HolGenTech, Inc. is open for business... - AJP]
Data-Driven Discovery Research at 23andMe
Genomeweb
June 23, 2010
In the July 2010 issue of Wired, on newsstands now, Thomas Goetz details Google co-founder Sergey Brin's investments in Parkinson's disease research. Brin, whose wife Ann Wojcicki co-founded the DTC genetic testing firm 23andMe, is pouring money into a data-driven approach to find the causes of — and potential cures for — the neurodegenerative disease that affects his mother, and that he has learned he carries a genetic disposition for. "Brin is likely the first who, based on a genetic test, began funding scientific research in the hope of escaping a disease in the first place," Goetz reports. Goetz outlines 23andMe's ambitious Parkinson's Disease Genetics Initiative, in which the company plans to mine data from 10,000 individuals "who are willing to pour all sorts of personal information into a database," he writes. So far, Brin has contributed $4 million to the initiative, which has acquired nearly 4,000 participants. "Brin proposes a different approach, one driven by computational muscle and staggeringly large data sets," Goetz writes. "In other words, Brin is proposing to bypass centuries of scientific epistemology in favor of a more Googley kind of science. He wants to collect data first, then hypothesize, then find the patterns that lead to answers. And he has the money and the algorithms to do it."
... Brin calls the effort and "information-rich opportunity," and tells Goetz that 23andMe plans to publish "several new associations that arose out of the main database, which now includes 50,000 individuals, that hint at the power of this new method." Brin also says that he is "in line to have his whole genome sequenced," and that "23andMe is considering offering whole-genome tests" at a yet-undisclosed price.
[The point at this historical announcement ("leak"- rather...) is, that speculation has been rampant that 23andMe was nearing to close business on the news of "a co-Founder having left" (for personal reasons), or that "sales were sagging", or that "regulatory pressures may become unbearable". Back to Mark Twain: "Reports on the death of 23andMe are greatly exaggerated" - AJP]
ACI Personalized Medicine Congress in Silicon Valley postponed from June 23-25 to December 9-10, 2010
The First Silicon Valley Conference on Health Care affected by Personalized Genomics, in view of impending Congressional Investigation of DTC Genomic Testing and possible new legislation proposed by NIH/FDA for updating the 1976 FDA Charter is postponed from 23-25 June, 2010 to 9-10 December. Some of the highlights from the new website:
[The 5 months advantage given away to DTC in Soul, Korea (backed by SAMSUNG) and Barcode shopping screening for allergens to Deakin University in Melbourne, Australia (backed by NESTLE) is not yet a strategical failure. Should the US be bogged down in the kind of "legislatory renovation" that took for the National Superhighways 37 years from formulating concepts (1919) to signing them into law (1956) with the project still not completed with 91 years and counting and in 1966 dollars with over a tenfold overrun is not a very rosy picture - AJP]
The Genome, 10 Years Later
EDITORIAL of The New York Times
Published: June 20, 2010
On June 26, 2000, two scientific teams announced at the White House that they had deciphered virtually the entire human genome, a prodigious feat that involved determining the exact sequence of chemical units in human genetic material. An enthusiastic President Clinton predicted a revolution in “the diagnosis, prevention and treatment of most, if not all, human diseases.”
Now, 10 years later, a sobering realization has set in. Decoding the genome has led to stunning advances in scientific knowledge and DNA-processing technologies but it has done relatively little to improve medical treatments or human health.
To be fair, many scientists at the time were warning that it would be a long, slow slog to reap clinical benefits.
And there have been some important advances, such as powerful new drugs for a few cancers and genetic tests that can predict whether people with breast cancer need chemotherapy. But the original hope that close study of the genome would identify mutations or variants that cause diseases like cancer, Alzheimer’s and heart ailments — and generate treatments for them — has given way to realization that the causes of most diseases are enormously complex and not easily traced to a simple mutation or two.
The difficulties were made clear in articles by Nicholas Wade and Andrew Pollack in The Times this month. One recent study found that some 100 genetic variants that had been statistically linked to heart disease had no value in predicting who would get the disease among 19,000 women who had been followed for 12 years. The old-fashioned method of taking a family history was a better guide. Meanwhile, the drug industry has yet to find the cornucopia of new drugs once predicted and is bogged down in a surfeit of information about potential targets for their medicines.
In the long run, it seems likely that the genomic revolution will pay off. But no one can be sure. Even if the genetic roots of some major diseases are identified, there is no guarantee that treatments can be found. The task facing science and industry in coming decades is as at least as challenging as the original deciphering of the human genome.
[Some "mainstream" US journals (e.g. Newsweek) excel by consulting actual scientists when attempting to write about science - without some gross errors that characterize e.g. the above "Editorial". There are 6 more days to correct errors... - more on my FaceBook wall as follows:
Two cardinal mistakes in the opening one sentence: (1) The code of the genome was not "decoded" - but only the sequence was (approximately) established (as Esther Dyson puts it, resulting in "The Big Russian Novel with a 100-word dictionary"...). More importantly, (2) The Human Genome Project" did deliver "scientific knowledge" (the "first draft" of the sequence...), but two further requirements were skipped (or went unnoticed by some): (a) knowledge of the genome had to be transformed into an algorithmic (not "statistical") understanding of how through epigenomic channels the fractal recursive iteration of the hologenome can be interacted with, towards equilibrium (health). (b) Even "scientific understanding" is totally inadequate if it did not come with a business model and actual business, since "medical treatments or human health" in the USA is not a science, but a business (as Francis Collins puts it "Sick Care"). - AJP]
The Path to Personalized Medicine
This article (10.1056/NEJMp1006304) was published on June 15, 2010, at NEJM.org
By Margaret A. Hamburg, M.D., and Francis S. Collins, M.D., Ph.D.
Dr. Hamburg is the commissioner of the Food and Drug Administration, Silver Spring, and Dr. Collins is the director of the National Institutes of Health, Bethesda - both in Maryland.
Major investments in basic science have created an opportunity for significant progress in clinical medicine. Researchers have discovered hundreds of genes that harbor variations contributing to human illness, identified genetic variability in patients' responses to dozens of treatments, and begun to target the molecular causes of some diseases. In addition, scientists are developing and using diagnostic tests based on genetics or other molecular mechanisms to better predict patients' responses to targeted therapy.
The challenge is to deliver the benefits of this work to patients. As the leaders of the National Institutes of Health (NIH) and the Food and Drug Administration (FDA), we have a shared vision of personalized medicine and the scientific and regulatory structure needed to support its growth. Together, we have been focusing on the best ways to develop new therapies and optimize prescribing by steering patients to the right drug at the right dose at the right time.
We recognize that myriad obstacles must be overcome to achieve these goals. These include scientific challenges, such as determining which genetic markers have the most clinical significance, limiting the off-target effects of gene-based therapies, and conducting clinical studies to identify genetic variants that are correlated with a drug response. There are also policy challenges, such as finding a level of regulation for genetic tests that both protects patients and encourages innovation. To make progress, the NIH and the FDA will invest in advancing translational and regulatory science, better define regulatory pathways for coordinated approval of codeveloped diagnostics and therapeutics, develop risk-based approaches for appropriate review of diagnostics to more accurately assess their validity and clinical utility, and make information about tests readily available.
Moving from concept to clinical use requires basic, translational, and regulatory science. On the basic-science front, studies are identifying many genetic variations underlying the risks of both rare and common diseases. These newly discovered genes, proteins, and pathways can represent powerful new drug targets, but currently there is insufficient evidence of a downstream market to entice the private sector to explore most of them. To fill that void, the NIH and the FDA will develop a more integrated pathway that connects all the steps between the identification of a potential therapeutic target by academic researchers and the approval of a therapy for clinical use. This pathway will include NIH-supported centers where researchers can screen thousands of chemicals to find potential drug candidates, as well as public–private partnerships to help move candidate compounds into commercial development.
The NIH will implement this strategy through such efforts as the Therapeutics for Rare and Neglected Diseases (TRND) program. With an open environment, permitting the involvement of all the world's top experts on a given disease, the TRND program will enable certain promising compounds to be taken through the preclinical development phase — a time-consuming, high-risk phase that pharmaceutical firms call "the valley of death." Besides accelerating the development of drugs to treat rare and neglected diseases, the TRND program may also help to identify molecularly distinct subtypes of some common diseases, which may lead to new therapeutic possibilities, either through the development of targeted drugs or the salvaging of abandoned or failed drugs by identifying subgroups of patients likely to benefit from them.
Another important step will be expanding efforts to develop tissue banks containing specimens along with information linking them to clinical outcomes. Such a resource will allow for a much broader assessment of the clinical importance of genetic variation across a range of conditions. For example, the NIH is now supporting genome analysis in participants in the Framingham Heart Study, obtaining biologic specimens from babies enrolled in the National Children's Study, and performing detailed genetic analysis of 20 types of tumors to improve our understanding of their molecular basis.
As for translational science, the NIH is harnessing the talents and strengths of its Clinical and Translational Sciences Award program, which currently funds 46 centers and has awardees in 26 states, and its Mark O. Hatfield Clinical Research Center (the country's largest research hospital, in Bethesda, MD) to translate basic research findings into clinical applications. Just as the NIH served as an initial home for human gene therapy, the Hatfield Center can provide specialized diagnostic services for rare and neglected diseases, offer a state-of-the-art manufacturing facility for novel therapies, and pioneer clinical trials of other innovative biologic therapies, such as those using human embryonic stem cells or induced pluripotent stem cells.
As genetics researchers generate enormous amounts of new information, the FDA is developing the regulatory science standards and evidence needed to use genetic information in drug and device development and clinical decision making. The agency's Critical Path Initiative aims to develop better evaluation tools, such as biomarkers and new assays. Under the Voluntary Genomic Data Submission program, companies can discuss genetic information with the FDA in a forum separate from the product-review process. These discussions give the agency and companies a better understanding of the scientific issues involved in applying pharmacogenomic information to drug development and offer an opportunity for early, informal feedback that may assist companies in reaching important strategic decisions. The goal is to help companies integrate genomics into their clinical-development plans.
Today, about 10% of labels for FDA-approved drugs contain pharmacogenomic information — a substantial increase since the 1990s but hardly the limit of the possibilities for this aspect of personalized medicine.1 There has been an explosion in the number of validated markers but relatively little independent analysis of the validity of the tests used to identify them in biologic specimens.
The success of personalized medicine depends on having accurate diagnostic tests that identify patients who can benefit from targeted therapies. For example, clinicians now commonly use diagnostics to determine which breast tumors overexpress the human epidermal growth factor receptor type 2 (HER2), which is associated with a worse prognosis but also predicts a better response to the medication trastuzumab. A test for HER2 was approved along with the drug (as a "companion diagnostic") so that clinicians can better target patients' treatment (see table).
Increasingly, however, the use of therapeutic innovations for a specific patient is contingent on or guided by the results from a diagnostic test that has not been independently reviewed for accuracy and reliability by the FDA. For example, in 2006, the FDA granted approval to rituximab (Rituxan) for use as part of first-line treatment in patients with certain cancers. Since then, a laboratory has marketed a test with the claim that it can distinguish the approximately 20% of patients who will not have a response to the drug from those who will. The FDA has not reviewed the scientific justification for this claim, but health care providers may use the test results to guide therapy. This undermines the approval process that has been established to protect patients, fails to ensure that physicians have accurate information on which to make treatment decisions, and decreases the chances that physicians will adopt a new therapeutic–diagnostic approach. The FDA is coordinating and clarifying the process that manufacturers must follow regarding their claims, including defining the times when a companion diagnostic must be approved or cleared before or concurrently with approval of the therapy. The agency will ensure that claims that a test will improve the care of patients are based on solid evidence, and developers will get straightforward, consistent advice about the standards for review and the best way to demonstrate that the combination works as intended.
Genetic tests are not perfect, in part because most gene mutations do not perfectly predict outcomes. Clinicians will need to understand the specificity and sensitivity of new diagnostics. The agency's goal is an efficient review process that produces diagnostic–therapeutic approaches that clinicians can rely on and allows companies that invest in establishing the validity and usefulness of tests to make specific, FDA-backed claims about benefits.
Patients should be confident that diagnostic tests reliably give correct results — especially when test results are used in making major medical decisions. The FDA has long taken a risk-based approach to the oversight of diagnostic tests, historically focusing on test kits that are broadly marketed to laboratories or the public (e.g., pregnancy tests or blood glucose tests); such kits are sold only if the FDA has determined that they accurately provide clinically significant information. But recently, many laboratories have begun performing and broadly marketing laboratory-developed tests, including complicated genetic tests. The results of these tests can be quite challenging to interpret. Because clinicians may order a genetic test only once, getting the results right the first time is crucial.
There are reports of problems with laboratory tests that have not had FDA oversight: women were erroneously told they were negative for a mutation conferring a very high risk of breast cancer; an ovarian cancer test, marketed before the completion of an NIH-funded study,2 gave false readings that reportedly led to the unnecessary removal of women's ovaries; and flawed, mishandled data underlying a test for Down's syndrome were discovered only days before the test was to go on the market. Through a process that includes opportunities for public input, the FDA will work to ensure the quality of key diagnostic tests, helping to protect patients and giving clinicians confidence that personalized medicine will lead to real health improvements.
In addition, the NIH will address the fact that there is no single public source of comprehensive information about the more than 2000 genetic tests that are available through clinical laboratories. On the recommendation of a federal advisory committee,3,4 the NIH — with advice from the FDA, other Department of Health and Human Services agencies, and diverse stakeholders — is creating a voluntary genetic testing registry to address key information gaps.5 Readily available information about these tests, including whether they were cleared or approved by the FDA, will help clinicians and consumers make informed decisions about using the tests to optimize health care. The registry will also support scientific discoveries by facilitating the sharing of data about genetic variants.
In February, the NIH and the FDA announced a new collaboration on regulatory and translational science to accelerate the translation of research into medical products and therapies; this effort includes a joint funding opportunity for regulatory science. Working with academic experts, companies, doctors, patients, and the public, we intend to help make personalized medicine a reality. A recent example of this collaboration is an effort to identify new investigational agents to which certain tumors, identified by their genetic signatures, are responsive.
Real progress will come when clinically beneficial new products and approaches are incorporated into clinical practice. As the field advances, we expect to see more efficient clinical trials based on a more thorough understanding of the genetic basis of disease. We also anticipate that some previously failed medications will be recognized as safe and effective and will be approved for subgroups of patients with specific genetic markers.
When the federal government created the national highway system, it did not tell people where to drive — it built the roads and set the standards for safety. Those investments supported a revolution in transportation, commerce, and personal mobility. We are now building a national highway system for personalized medicine, with substantial investments in infrastructure and standards. We look forward to doctors' and patients' navigating these roads to better outcomes and better health.
References
1. Frueh FW, Amur S, Mummaneni P, et al. Pharmacogenomic biomarker information in drug labels approved by the United States Food and Drug Administration: prevalence of related drug use. Pharmacotherapy 2008;28:992-998. [CrossRef][Web of Science][Medline]
2. Ovarian cancer research results from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial: fact sheet. Bethesda, MD: National Cancer Institute. (Accessed June 11, 2010, at http://www.cancer.gov/cancertopics/cancertopics/factsheet/detection/plco-ovarian.)
3. Secretary's Advisory Committee on Genetic Testing. Enhancing the oversight of genetic tests: recommendations of the SACGT. Bethesda, MD: National Institutes of Health, 2000. (Accessed June 11, 2010, at http://oba.od.nih.gov/oba/sacgt/reports/oversight_report.pdf.)
4. Secretary's Advisory Committee on Genetics, Health, and Society. U.S. system of oversight of genetic testing: a response to the charge of the Secretary of Health and Human Services. Bethesda, MD: National Institutes of Health, 2008. (Accessed June 11, 2010, at http://oba.od.nih.gov/oba/SACGHS/reports/SACGHS_oversight_report.pdf.)
5. Genetic Testing Registry. Bethesda, MD: National Center for Biotechnology, National Library of Medicine; 2010. (Accessed June 11, 2010, at http://www.ncbi.nlm.nih.gov/gtr.)
[The Plan by NIH/NSF is likely to be proposed to the Congressional Investigation, as the Guiterrez-video referred to the NSF Commissioner, by authorities above him, Drs. Collins and Hamburger quite certain to be in the lead roles. For the historical parallel to the National Interstate, see Wikipedia] - AJP]
FDA Cracks Down on DTC Genetic Testing
GenomeWeb
June 14, 2010
[Excerpts]
...
Pharmacogenomics Reporter, one of the Daily Scan's sister publications, reported that these letters are what the FDA calls "untitled" letters, meaning the companies have been made aware of the FDA's concerns and have a chance to address them and make whatever changes the FDA deems necessary. Based on their responses, the FDA could upgrade to "warning" letters, which are more severe. PGx Reporter's Turna Ray also reported that several presenters at the Consumer Genetics Conference in Boston in the beginning of June said they thought federal regulation of DTC tests was "imminent."
Genomics Law Report's Dan Vorhaus says the letters may not be as significant to the five companies involved - 23andMe, Navigenics, Decode Genetics, Knome, and Illumina - as everyone thinks, especially since the FDA hasn't demanded that the companies remove the products from the market pending review. "So, at least for the moment, we may see little or no immediate change while these companies weigh their options internally and through discussions with the FDA," Vorhaus writes. He suggests the companies' best option would be to change the tests in such a way that would convince the FDA they no longer qualify as medical devices - "for instance by removing the ability of consumers to purchase the product without the participation of a healthcare provider."
Daniel MacArthur at Genetic Future thinks this turn of events could spell disaster for the personal genomics industry. "Excessive regulation would negatively impact on innovation in the field by increasing the barrier to entry for new products, as well as increasing costs for consumers," he says, adding that this move looks like it's motivated by publicity on the FDA's part - in the wake of the 23andMe test results mix-up - rather than by a genuine drive to protect consumers.
...
Reply (2)
Andras [Pellionisz_at_JunkDNA.com]
Juan Enriquez predicted in 2001 that "genomics" will compare to "digital" in global impact. No doubt, but on the way to the genome revolution isn't it hard to keep track of who is doing what and what is significant? The US FDA's actions last week represent just the kind of fluctuation that shifts the scene and changes the balance. Whether that's just for now or forever remains to be seen.
The revolution's drivers have long been aware that the many subfields of genomics: consumer genomics, educational genomics, recreational genomics, genomics of ancestry, etcetera must be distinguished from medical genomics. While each category may be regulated (or not) by government, legal, economic or medical agencies in countries worldwide, I believe there is a way to cut to the chase and get on with the genome revolution. That's why yours truly focused on developing the commercial business model for genome applications, as illustrated in the YouTube Shop for Your Life!. The commercial business model offers the fastest growth and the most immediate consumer adoption, based on consumers' freedom of choice, with the least interference from lawyers, regulators and governments. ...
[Shop for your Life! - HolGenTech]but back to the US fracas and what is happening, or better said, not happening. I admire the legally precise analysis of Dan Vorhaus, who suggests that it may be a misunderstanding to think that "The FDA Cracks Down on DTC Genetic Testing". As he says, the Gutierrez letters (G-5) "may not be as significant". In fact, did FDA's Alberto Gutierrez "crack down" at all on DTC? There is no "cease and desist" order, no deadlines, no specific documentation to submit, but rather just the suggestion that there be a long brewing and largely ongoing dialog with the FDA. --doesn't sound like an enthusiastic endorsement of the genome revolution, but neither does it indicate the end of the U.S. version of the genome revolution. As he points out [at the end of] in his video, even the agency's director [Commissioner] could re-think and update somewhat blurred definitions; i.e., what "medical device" may mean in the genomic age - a giant leap away from the 1976 mandate of FDA:
Alberto Guiterrez (FDA)
Is it possible that the G-5 letters are just setting the stage for the widely heralded Congressional Investigation on DTC Genome Testing? Surely when Francis Collins, M.D., Ph.D., and Director of NIH, who wrote the book on Personalized Medicine, [now, within 6 months also in paperback, kindle and audio ...] is called to testify before the Congressional Committee on Energy and Commerce, he can be expected to offer his specific recommendations from the NIH Genetic Testing Registry and could well suggest that registration be made mandatory, pursuant to an endorsement of the Congressional Committee. Note his initiation comments this March NIH Genetic Testing Registry.
In the same spirit of educating the public through the political stage, the G-5 letters to Knome and Illumina may amount to invitations to two of the world's pre-eminent genome R&D and industrial experts, Harvard Genomics Professor George Church, co-Founder of Knome, and Illumina CEO Jay Flatley to deliver Congressional Testimonies.
With the nation watching, they could guide the Congressional Committee to bring the FDA into the genome revolution, or find/shape/create the agency or entity that will embrace it to the maximum benefit of the American public. Is it that the FDA has been remarkably passive for 3 years and now, with a Congressional Investigation imminent, feels the need to protect itself from all criticism that could suggest "it never flexed its muscles"? Sure, there was some muscle flexing when earlier G-3 letters seem to have scared Pathway Genomics away from DTC without resorting to anything that could be labeled "inappropriate regulation". The earlier Gutierrez salvo, G-3, was just a scary demand for a lot of documentation with a deadline so short there was no time for the Congressional Committee to act. Now, the G-5 may be entrée for participation in the genome revolution a la U.S. style with Congress dominant and the FDA retaining a scary innocence. So, let us watch the Congressional Committee conduct its eminently predictable hearings, and recommend appropriate legislation; through which "medical genomics" and "off-the-shelf genomics" (commercial and other non-medical utilization of information) should be clearly distinguished. We can be sure that if FDA is left to regulate Medical Genomics, it won't be the same FDA with the 1976 mandate Alberto Gutierrez notes in his video.
This said, it is still possible that forces in the U.S. may be getting ready for the big "crack down", or even planning to kill DTC in the U.S, and diminish the country's status in our Genomic Age. In fact, they could manage a big set-back for the U.S. just by imposing a cumbersome legal agenda that takes so long the U.S. could miss its chance just by having to wait, all while DTC in Asia soars. We can hope that Congress will be well aware that there isn't enough money to address escalating health care (sick care) and listen to "We the People" demanding genome-based prevention. The Congressional Committee would be well advised to keep DTC business open during legal renovations through a moratorium on any further regulation of DTC until legislation puts the regulatory houses in order.
If the U.S. does bow out or just misses the boat, I look at Asia as particularly conducive to the kind of commercial genomics I promote, which are based on a genome computing architecture that applies smart phones to empower consumers to exercise their freedom of choice using genome-based recommendations. Asia is advanced in both mobile computing and genomics already, and backed by their Big IT. The really good news is that the number of lawyers per capita is a fraction of the U.S.'s, and so is the cost of labor... more for the U.S. Congress to consider, and they had better do so quickly.
[Genomeweb comments can not be burdened by overly detailed documentation - see many more hyperlinks here - AJP]
Why the FDA Is Cracking Down on Do-It-Yourself Genetic Tests: An Exclusive Q&A
Newsweek, June 11, 2010
Mary Carmichael
Fresh off sending stern letters to five consumer-genomics companies indicating that, as currently marketed, the companies’ tests will require clearance by the FDA, Alberto Gutierrez - the agency’s director of the Office of In Vitro Diagnostics in the Center for Devices and Radiological Health - spoke to NEWSWEEK. Among the revelations: Pathway Genomics, the company that started the controversy by planning to sell its test in drugstores, will be withdrawing from the direct-to-consumer market. Gutierrez also clarified the agency’s reasoning and timing. Excerpts:
Just to clarify, it sounds like these consumer-genomics tests-as they’re marketed now - will require pre-market clearance because they qualify as medical devices under current law. Is that correct?
That’s correct. [That is; "the impression that it sounds like" is correct - AJP]
Why is this happening now instead of three years ago, when direct-to-consumer genomics tests first came to market?
Well, the claims [made by the companies] have changed constantly. The original claims from three years ago were very, very vague. For example, the claims they’re making now for the different drugs and how they’re metabolized, those weren’t being made previously. Even some of the health claims in terms of risk of chronic disease, those just started coming online about a year ago.
So the problem is that the companies are testing for genetic variants that might affect the way consumers make medical decisions?
That’s correct … If you’re making a claim about [a genetic variant that affects the metabolism of the anticoagulant drug] warfarin, and somebody decides based on the result they get that they want to change their dosing, that is a fairly risky decision. That could affect their health. If they’re not feeling well on their current dose and the drug is expensive, we don’t know what they would do.
Illumina and Knome are different from the other three companies, but they were also sent letters. Can you explain to me the thinking behind the letters to each of them?
Well, some of the other companies are buying the chip that Illumina is making. That chip is sold as for “research use only.” As such, Illumina has a responsibility. If the chip is being used for diagnostic tests instead, Illumina has to follow the law, and they are aware that the chips are not being used for research only.
Would Illumina still have to obtain pre-market clearance if it sold that chip to medical laboratories and doctors only?
Yes, if Illumina is selling their chips to clinical labs that are using those chips to provide results back to either physicians or patients, and if they know that is how the chips are being used. However, they could [sell the chips without pre-market clearance] to academic labs or clinical laboratories which are clearly in the research space - meaning they’re beginning to develop a new test and just looking what they can do with it. That’s different than providing clinical results to patients.
What Knome sells is more of a service than a device. It’s basically a software program that explains genetic data that consumers can have generated elsewhere. Can you explain to me why it requires pre-market clearance?
Software is a medical device, and they’re making medical claims. They’re taking results and making medical claims that come out of those results.
Is there a reason Pathway Genomics was not included in this round of letters?
As you’re aware, we sent Pathway a letter not too long ago. They have responded, and in that response they are noting that they are planning to move away from direct-to-consumer testing at this point. I believe they’re planning to change their business model.
What about other companies that sell their tests to doctors, rather than directly to consumers, such as Counsyl?
Counsyl actually used to be a direct-to-consumer company until we sent Pathway the “it has come to our attention” letter. Then they changed their business model. They’re going through clinics or doctors. In that case, it will depend on whether they fit under the model of a laboratory-developed test. If they don’t, they will have to come in and get their test cleared.
Is there any reason to think this action by the FDA will preempt congressional hearings?
Well, I can’t predict whether Congress will have hearings and whether it will make any difference.
[It is an interesting question if the above is an informal interview or an ex officio statement - AJP]
Breaking: FDA Likely to Require Pre-Market Clearance for DTC Personal Genomics Tests
Newsweek, June 11, 2010
Mary Carmichael
The FDA has just sent letters to five personal genomics companies outlining its intentions for regulation of direct-to-consumer tests, and if 23andMe thought it was having a bad week before, it's sure not going to be happy now. In the letters, the agency says that its test and four others, as currently marketed, will need pre-market clearance because they qualify as medical devices "intended for use in the diagnosis of disease or other conditions or in the cure, mitigation, treatment, or prevention of disease."
Requiring pre-market clearance is a drastic measure, and it's precisely the one personal-genomics companies hoped to avoid by casting their results as "educational" or recreational instead of medical. That's not all; the letters do "not necessarily address other obligations" the companies may have in selling their tests directly to consumers.
Oddly, the FDA hasn't yet sent a letter to Pathway Genomics, the company that started this whole fracas by making a deal (quickly rescinded when it went public) to sell its genomic test in drugstores. The agency tells NEWSWEEK its discussion with Pathway is still ongoing. Here's what it's telling the other five companies:
23andMe. This is the big, Google-backed player in the industry. The company was initially more focused on "fun" DNA results (do you have wet or dry earwax?), but since its launch in 2007 it's been adding medically relevant genes to the list of variants it identifies, including variants in BRCA1 and BRCA2 (breast-cancer genes) and several pharmacogenomic tests that assess patients' responses to medications such as warfarin and clopidogrel. That seems to be what got the FDA's attention: the letter to 23andMe mentions the pharmacogenomic tests and also points out that "the data generated from the 23andMe Odds Calculator, a feature of the 23andMe Personal Genome Service, includes the contribution of single-nucleotide polymorphisms (SNPs) to disease risk. Consumers may make medical decisions in reliance on this information." In other words, laypeople will think of this as a medical device, and we're going to treat it accordingly, which means you'll need to get it officially approved before selling it directly to the public. It's also not a laboratory-developed test, apparently, "because the 23andMe Personal Genome Service™ is not developed by and used in a single laboratory." That matters, because these tests aren't regulated as strictly as other medical devices and kits.
Navigenics. The letter is almost a direct facsimile of what's been sent to 23andMe-the warfarin and clopidogrel tests are notable, and so is a proprietary feature that "provides patients with genetic predispositions for important health conditions and medication sensitivities."
DeCode Genetics. Same basic deal here: consumers may use the test to make medical decisions, ergo, it's a medical device. Here, it's not pharmacogenomic tests that bother the FDA, but tests for 12 genes linked to breast cancer and a statement on the company's Web site that although "the deCODEme Cancer Scan cannot tell you whether you are going to develop cancer, it can alert you to your possible genetic risk and lead to early detection."
Illumina. This is a different kind of company. Although it has a personal-genomics component (it will sequence your entire genome, more or less, for about $20,000), that's not what has the FDA concerned at the moment. Illumina is also the company that provides 23andMe and DeCode with the genetic arrays used to scan 550,000 variants in the DNA. Those, too, may require pre-market clearance as long as they're used in direct-to-consumer genomic tests, says the FDA: "Although Illumina, Inc. has received FDA clearance or approval for several of its devices, we note that the Illumina Infinium HumanHap550 array is not one of them and is labeled 'For Research Use Only.' Yet Illumina is knowingly providing the HumanHap550 array to 23andMe and deCODE Genetics for clinical diagnostic use without FDA clearance or approval."
Knome. This, too, is a different kind of company. Knome doesn't sequence the genome so much as try to make sense of it for consumers who get their data generated elsewhere. Or, as the FDA puts it, Knome offers "a software program that analyzes genetic test results that are generated by an external laboratory in order to generate a patient specific test report." This apparently qualifies as a medical device as well.
There's still a lot more that could happen with regulation of consumer genomics. All five letters offer the companies the chance "to meet with us to discuss whether there are tests you are promoting that do not require review by FDA" and to establish what kind of information the companies need to give the agency. "We're basically telling them they need to come discuss with us whether they're marketing these legally," says FDA spokeswoman Erica Jefferson.
Congressional action may still be in the works, too. [It is not "may still be" but "will certainly be" - AJP] Congress sent letters to 23andMe, DeCode, and Pathway in late May, and the companies were due to provide an enormous amount of documents to the government last weekend. So stay tuned: this debate is far from over.
[Newsweek' perspective brings to the surface some legal definitions that are aptly analyzed by Dan Vorhaus - AJP]
The Gutierrez Letters from FDA to DTC Genome Testing Companies
Letter to Navigenics Concerning the NaviGenics Health Compass (PDF - 85KB)
Letter to Illumina, Inc. Concerning the Illumina Infinium HumanHap550 array (PDF - 88KB)
Letter to 23andMe, Inc. Concerning the 23andMe Personal Genome Service (PDF - 103KB)
Letter to Knome, Inc. Concering the KnomeCOMPLETE (PDF - 91KB)
Letter to deCODE Genetics Concerning the deCODEme Complete Scan (PDF - 96KB)
Letter to Pathway Genomics Corporation Concerning the Pathway Genomics Genetic Health Report
[For hyperlinks to facsimile-s click on headline of this entry - AJP]
What Five FDA Letters Mean for the Future of DTC Genetic Testing
Posted by Dan Vorhaus on June 11, 2010
[Likely to be the most professional legal analysis of the US-aspects of the FDA-letters - AJP]
Silicon Valley' Genome-Based Personalized Medicine Meeting Postponed to Dec 9-10
As Silicon Valley flexes its muscles with two of the leading DNA Sequencing companies (Complete Genomics and Pacific Biosciences), two of the leading DTC Genome Testing Companies (23andMe and Navigenics), two of the leading serial computer chip makers (Intel and AMD) and two of the leading parallel FPGA chip makers (Xilinx and Altera), several traditional computer integrator companies (HP, Apple) and the hybrid computer integrator (DRCcomputer), major health-care providers (Stanford just announcing its Genomic and Personal Medicine Center, El Camino Hospital and Palo Alto Medical Foundation already running theirs), with a provider excelling in digitalization of health records (Kaiser Permanente), and software giants engaged in "health data repositories" (Google Health and Microsoft HealthVault, Oracle), and HolGenTech positioned to become a "Center for Genome Analysis and Interpretation" (with every $3 investment in the USA $1 commanded from Silicon Valley VC-s), along came the news of the Congressional Investigation of DTC genome testing. Thus, the meeting originally planned for June 23-25 was postponed to the time when the dust will clear: December 9-10, 2010 - AJP]
Would Regulation Kill Genetic Testing?
It could—but the FDA and Congress also could make the burgeoning biotech industry stronger.
Newsweek, June 4
Mary Carmichael
At the Consumer Genetics Conference in Boston this week, it was nearly impossible to go an hour without hearing the words “Pathway” or “Walgreens.” That wouldn’t have been the case had the meeting been held before May 11, when Pathway Genomics of San Diego made a deal to sell its genetic testing service in the nationwide drug chain. The product lets consumers spit in a $20 test tube, send the results to a lab, pay $250 or more, and find out some of what’s lurking in their DNA.
Easy, over-the-counter access to tests that consumers may not fully understand is spurring regulators to action. But as with any emerging industry, there’s concern that stringent or misguided government rules could hamper growth and innovation. Certainly, after going unregulated for three years, direct-to-consumer (DTC) genetic tests are about to face their biggest challenge.
Apparently blindsided by the Pathway-Walgreens news, the Food and Drug Administration signaled that it might, for the first time, regulate DTC genetic tests. Congress quickly got involved, sending letters to Pathway and two similar firms, Google-backed 23andMe and Navigenics, asking for documentation on almost everything the companies do. The deadline for the companies’ response is this weekend, and Capitol Hill hearings are probably on the horizon.
DTC genomics companies are already regulated in New York and California, and most experts agree that some federal oversight is needed. If done right, FDA rules could be good for the industry, consumers, and pretty much everyone, except perhaps the random firm promoting the genetic equivalent of snake oil. But if regulation is done wrong or overdone, it could harm the industry or send genomics startups packing for countries with less stringent laws.
“The complexity of some of these tests is such that it is really hard to come to consensus” on what to do about them, says Joann Boughman, executive vice president of the American Society of Human Genetics. “But it’s time we just had to grapple with this and understand that no matter what happens, not everybody is going to be happy.”
The FDA’s reluctance to regulate health-related DTC genomic tests so far has frustrated some in the industry—and critics outside of it—who would have preferred more guidance from the beginning. But the agency has not been ignoring the tests since 2007, when they first appeared. It has been gathering information on them all along. Even in 2000 the FDA was aware of some of the concerns it now has to confront; they were invoked in a report from the secretary’s Advisory Committee on Genetic Testing that year.
Some of the report’s conclusions were reflected in the FDA’s draft guidelines for regulating in vitro diagnostic multivariate index assays that were released in 2006 and again, in a second draft, in 2007. The industry reacted badly to those two proposals. “They were vague, and it would have been expensive for independent labs to comply with them,” says Dan Vorhaus, an attorney at Robinson Bradshaw & Hinson who focuses on genomics. “There was a lot of ambiguity in what the FDA was proposing. It wasn’t clear how it would be applied.”
Recently, FDA officials have said they hope to revamp those guidelines yet again. The current rules do not cover DTC genetic tests, but theoretically, they could be expanded to do so. That might mean that DTC companies would need premarket clearance from the FDA to sell their tests—a rule that would raise the barriers to entry, possibly discouraging startups or driving them overseas. China, in particular, might look appealing: institutes there have lately been buying genetic sequencing machines in droves.
But many observers think the FDA won’t go so far as to require premarket clearance for the tests because the agency itself may not want to deal with the “insane and unsupportable burden” that would present, says Paul Kim, an attorney at Foley Hoag who briefed the Consumer Genetics Conference audience on the issue. “Does the FDA really want to have an obligation to clear thousands of new tests every year?” he says. “It’s unsustainable, and I can’t imagine the FDA would welcome or look for that kind of responsibility.”
Perhaps an easier solution would be to piggyback onto the genetic-test registry that the National Institutes of Health is already planning to build so that consumers will have a way to compare different testing services side by side. So far, the NIH’s plan is for the registry to be voluntary, but Vorhaus argues it could be mandatory instead, with companies required to explain what genes they test for, how they do it, and how they interpret and aggregate the results for consumers. “The companies may already show you the [basic science] studies they’re using,” says Vorhaus, “but all those algorithms that go into producing their reports—those are the kind of things that are going to concern the FDA.”
At the very least, says Boughman, under new regulations, DTC genetics companies should have to start proving some basic cred: that their labs are CLIA-certified (most already are) and that they can correctly identify the variants for which they’re testing. Boughman would like to see the labs regularly checked by an outside agency such as the College of American Pathologists. “We think there should be a way to confirm a result in another laboratory, either with people flipping samples or sharing a [sample with a disguised identity] once in a while,” she says.
The FDA has not yet revealed its intentions; the agency told NEWSWEEK on Thursday that it “continues to look at tests being marketed directly to consumers, and will take appropriate steps as necessary to make sure that public health needs are met in a safe and effective manner.”
But Kim says there’s at least one concrete indication of what may be in store—at least from the Hill. Last week, Reps. Patrick Kennedy (D-R.I.) and Anna Eshoo (D-Calif.) reintroduced a personalized medicine bill that first surfaced three years ago under the sponsorship of a certain then-senator from Illinois. (Yes, that one.) The new, Kennedy-Eshoo version of the bill has several tweaks, among them the creation of a new office focused on personalized medicine; a proposal for a registry like the NIH’s; and a call for the FDA, the Federal Trade Commission, and the Centers for Disease Control to evaluate DTC genomic tests. The FDA is not involved with the legislation, but the bill may be “a good bellwether” for future regulation, says Kim, who has advised Kennedy’s office.
“What people like most of all with regulation is certainty and clarity,” Kim adds. “If you have a pathway laid out, even if it’s stringent, you know what you’re dealing with.”
[Theragen of Seoul, Korea - backed by SAMSUNG would be a primary beneficiary, should US regulation decide to throw out the baby with the bathwater - AJP]
Stanford School of Medicine Launches Center for Genomics and Personalized Medicine
June 04, 2010
By a GenomeWeb staff reporter
[Michael Snyder, Stanford]
NEW YORK (GenomeWeb News) — Stanford University's School of Medicine this week announced the creation of a new Center for Genomics and Personalized Medicine designed to integrate genomics information with every aspect of medicine, as well as draw on collaborations between Stanford's basic scientists and clinical researchers, and on technologies developed in Silicon Valley.
Stanford says the center will promote personalized medicine by building on research from the sequencing of the genome of Stephen Quake, the Lee Otterson Professor of Bioengineering and co-chair of Stanford's bioengineering department. Quake made news last August by using a technology he helped invent — Helicos BioSciences' Heliscope single molecule sequencer — to sequence and publish his own genome for less than $50,000. Researchers published results from their study of Quake's genome in the May 1 issue of the Lancet.
"The center blends highly efficient, rapid sequencing technology with the research and clinical efforts of experts in genomics, bioinformatics, molecular genetic pathology and even ethics and genetic counseling to bring advances from the laboratory to the patient," Stanford said in its announcement.
The center's director is Michael Snyder, chair of the medical school's Department of Genetics. In the statement, Snyder said the center's sequencing facility is already operating with new equipment estimated to increase its sequencing capacity by about fivefold while also "significantly" reducing the cost.
Earlier this year, Snyder led a team of researchers in sequencing the transcriptomes of human embryonic stem cells in various stages of their differentiation into neural cells, using short- and paired-end reads generated with Illumina sequencing and long reads generated with the Roche 454 FLX and Titanium platforms. They identified both known and previously unannotated transcripts as well as spliced isoforms specific to the differentiation steps.
The center's equipment also includes a Single Molecule Real Time, or SMRT, DNA sequencing system purchased from Pacific Biosciences. Stanford was one of 10 institutions that purchased the system as part of Pac Bio's early access program in North America. The company has said it expects to launch commercial sales of the system in the second half of this year.
[This was only a matter of time! "The second half of this year" starts in less than 4 weeks... Pellionisz_at_JunkDNA.com]
Your Genome Is Coming [to where? - AJP]
Forbes
June 3, 2010 - 5:32 pm
Matthew Herper, senior editor at Forbes
[Your Affordable Genome is coming to WHERE? - AJP]
Just keep waiting, and soon you'll be able to afford that genome sequence you've always wanted. Makers of DNA sequencers are dropping costs and increasing speed at a rate that would make microchip manufacturers blush.
Illumina, the maker of DNA decoders, today lowered the cost of its consumer gene-sequencing product from $48,000 to $19,500, with a cost of $14,500 for people in groups of five or more that use the same physician. It also introduced a new category of customer: for patients who might get actionable medical information, such as cancer patients who could use genomic information to pick medicines, the service will be available for $9,500. The announcement was made at the Consumer Genetics Conference in Boston.
That is a stunning drop in price. Sequencing the first human genome cost $3 billion. Knome, a company that also sells consumers access to their genome and analysis of it, launched its service for $350,000 in December 2007 . Now it will sequence your genome for $39,500. Earlier this year, Illumina announced a new DNA sequencer that would decode all the genes in the human genome for just $10,000, and said it expected prices to drop further; the $9,500 price tag for people who might have a medical reason to get sequenced indicates that costs have already dropped below that level.
It's a new notion that sequencing every DNA base pair could be more useful that just doing a targeted read of several genes, a cheaper and older technique. Last October, scientists at Yale diagnosed a baby with a genetic form of diarrhea by sequencing all of its protein-coding genes. Other examples of diagnosis-by-sequencing were published earlier this year in the New England Journal of Medicine.
Cancer patients are likely to be among the first to benefit from these dropping prices. The idea is that knowing the gene sequences of a patient will help patients pick targeted cancer drugs. At $9,500, the sequencing already costs less than a course of treatment with newer cancer medicines sold by Novartis and Eli Lilly.
Hoping to accelerate this trend, Life Technologies, Illumina's biggest competitor, today announced the creation of an alliance of cancer centers that will use gene sequencing to help patients pick treatments. The founding partners, including Fox Chase Cancer Center, Scripps Genomic Medicine and the Translational Genomics Research Institute (TGen), are also launching a pilot study aimed at determining whether whole genome sequencing can improve the management of hard-to-treat cancers. The announcement was also made at the conference.
Gregory Lucier, Life's chief executive, put up the inset graphic during his presentation. It shows the price drops in gene sequencing technology over the past decade, compared to Moore's Law, the axiom about increasing microprocessor speed coined by Intel founder Gordon Moore. What's amazing is that the gene sequencers now seem to be outpacing the microchips.
[The Affordable Personal DNA Is Coming - but "Is IT Ready for the Dreaded DNA Data Deluge?" - I asked and answered in my Google Tech Talk YouTube (2008). By 2009, it was obvious that the "DTC Genome Testing Business Model" (as it was, see my Churchill Club YouTube panel) was not complete, without "Personal Genome Computer" and "Personal Genome Assistant" genome computing architecture (see my 2010 PMWC2010 YouTube):
[Need for PGC & PGA Pellionisz_at_JunkDNA.com]
Illumina Drops Personal Genome Sequencing Price to Below $20,000
BioIT World
June 3, 2010
By Kevin Davies
BOSTON – One year after Illumina introduced its personal genome sequencing service, CEO Jay Flatley announced a significant price drop to below $20,000, and potentially half that if there is clinical relevance.
Illumina’s Individual Genome Sequencing service that Flatley debuted at the Consumer Genetics Show last year launched with a price of $48,000 for a whole genome sequence at 30-fold coverage. The service has to be ordered by a physician, and the results are also delivered back to the physician to discuss with the consumer. [This will open up the related questions; a) who pays for the sequencing, and "whose genome is it, anyway", b) In this construction, there will be a very limited number of physicians to understand the full DNA (since they have never been trained for an art non-existent at the time of their schooling) let alone "discuss" it with the "consumer" (since the the time of medical doctors is far too high for "consumer discussions"). The viable business model is that of HolGenTech (see below), where consumers are empowered by interoperable health- and genomic data to make a difference in their daily life; shopping by their genome - AJP]
With the introduction of the HiSeq instrument earlier this year, Illumina said the reagent cost of sequencing a full human genome had dropped to the $10,000 mark, which made the original IGS price tag of $48,000 appear a little steep by comparison. The new pricing that Flatley introduced today reflects the dramatic reduction in sequencing cost enabled by the HiSeq instrument.
The new cost of an individual genome sequence is $19,500. For groups of five people or more, the price drops to $14,500. Flatley also said that for a physician ordering a sequence for genuine clinical relevance, the price falls further to $9,500.
The only catch with the new pricing is that the sequence is no longer delivered on an iMac. “A little less elegant, a little less cool,” Flatley admitted.
Flatley disclosed that the IGS has sequenced at least 14 individuals to date. These include Flatley,venture capitalist Hermann Hauser, Henry “Skip” Gates and his father; Glenn Close; John West (former Solexa CEO) and his family of four; a cancer patient, two centenarians, and a severely ill child.
Goes to 11
Flatley briefly discussed analysis of his own genome sequence, illustrated with a live demo of his genome on an iPad app that had members of the audience drooling. Illumina shelved an earlier genome browser app for the iPhone after concluding the device didn’t have sufficient power to run the app. [This we knew from the outset - just a few hours before Illumina's show of iPhone "business model" I presented in last years' Consumer Genetics Conference the demo of empowerment of consumers to shop by their genome using their generic smart phone ("Personal Genome Assistant"). The architecture does call, however, for a robust enough "Personal Genome Computer" to be synced with; see photo from YouTube in the article above - AJP]
Flatley said that detailed analysis of his genome, searching for known variants in mutation databases such as HBMD and PharmKB, revealed 16 candidate homozygous and 48 heterozygous ‘disease-causing’ variants potentially associated with known genetic diseases. The accuracy of some of these annotations left a lot to be desired -- much to Flatley’s relief. In some cases, the mutations were annotated as “… death in early infancy highly likely.”
After further review, Illumina eliminated all 16 of the homozygous mutations as disease-related, and 37 of the 48 heterozygous variants. That leaves Flatley as a carrier of 11 confirmed ‘disease-causing’ alleles, for six recessive disorders and five dominant disorders, most of which Flatley admitted he had never heard of. Further analysis is being conducted.
Flatley presented a live demo of his genome using a custom-built app for the iPad. (The app is not yet publicly available.) The app presented a host of features, including a list of the disorders linked to Flatley’s known variants; an “about me” tab to build a family tree and enter health information, which is linked to Microsoft’s Health Vault.
A “Favorites” tab provides access to favorite genes (Flatley gave the example of “athletic tendency”) extracting SNPs in real time. There was also a genome browser, providing the ability to drill down from the whole chromosome level to the nucleotide level; a pathways tab; and a sharing tool that could provide access to a physician.
[The significance is NOT that Illumina dropped its full DNA sequencing price by a staggering 80% - since even their lowest price is already undercut by Complete Genomics, and release of Pacific Biosciences' sequencer, providing full human DNA "for a price of a meal in a restaurant" (in maybe half an hour or so). The significance is that with Illumina dropping the smart phone application, HolGenTech is now spearheading genome computing architecture. The business model, technology and IP is available by HolGenTech - email also to Pellionisz_at_JunkDNA.com]
The Genome Project is 10 Years Old - Where is the Health Care Revolution?
Singularityhub.com
May 25th, 2010
Drew Halley
“It is fair to say that the Human Genome Project has not yet directly affected the health care of most individuals.” - Francis Collins, April 2010, Nature.
What’s in a genome? Ten years ago, the completion of the Human Genome Project promised to usher in a whole new era of heath care. Revolutionary gene therapies would soon conquer everything from cancer and heart disease to diabetes and autoimmunity. A roll-call of our genes would unlock the causes (and the solutions) to death and disease. But a decade on, most of these hopes have failed to materialize, and most of our lives haven’t changed. So where’s the revolution?
A recent retrospective in Nature includes some sobering reviews by such genetic gurus as Craig Venter and Francis Collins. Sure, there have been some significant gains. In vitro genetic screening has greatly reduced the risk of many common genetic diseases at the pre-birth stage. Risk factors for a range of adult diseases (including cancer) are coming into focus, and a host of new drugs have been developed. But as scientists expected to find common genetic determinants underlying common diseases, they quickly discovered that the genome was anything but straightforward. Instead, the genes behind disease have been shown to be highly complex and individually variable, even for widespread disorders. There isn’t a SNP for cancer.
The problem is that currently, the field of genomics is data-rich and application-poor. Thanks to companies like Complete Genomics, there is a flood of new genetic data and even more on the way - but we still don’t know how it works. So far, the primary focus of interest (and funding) has been the most easily quantifiable advances, such as sequencing speed and costs. Accomplishments in this arena have been impressive, but a complementary push for clinical applications is needed to sort through all of this genomic data that we still don’t understand.
The fate of commercial genetics hangs in the balance. Companies like deCODE and 23andMe were born on the hope that laypeople might be willing to pay for a glimpse at their own DNA. The bankruptcy of deCODE and troubling rumors about 23andMe raise the question of whether personal genomics is an industry born premature. So far, their products feed a curiosity niche, not a utilitarian one. When a genome points to little more than SNP-based correlations, few people can justify spending their recession-hit income on what remains a biotech novelty.
As Collins, Venter and others have suggested, a health care revolution requires bridging the gap between genomic data and its clinical utility. Any disappointments of the past decade point to the directions of the next. We’re learning that so-called “junk DNA” isn’t really junk, but can regulate the expression of other, coding sequences of the genome. Untangling the various networks of gene regulation will illuminate the pathways which result in a given phenotype, pathological or not. The roles of epigenetic processes are also undoubtedly complicating factors which will need to be better understood.
Most approaches over the past decade have used SNP chip analysis to identify mutations associated with particular phenotypes. This type of analysis only looks at small parts of the genome, and has largely failed to identify the genetic determinants of most diseases. The SNP chip approach will be phased out as whole-genome scans become faster and more affordable (costs should drop below $1000 within the next three years). Complete Genomics aims to sequence 1 million human genomes within the next five years, and that’s a lot of data to crunch. Venter is calling for two ways of making better sense of this flood of whole-genome scans: more detailed phenotype analyses, and the development of computational tools that can link them to their genetic counterparts.
It’s interesting to note the parallel between difficulties encountered in genomics and neuroscience. Recent years have seen an increasing shift in brain science from localization (areas of the brain that “do” things) towards neural-network approaches. Just as we’ll unlikely find a single gene that causes cancer, we’re not going to find the “irony zone” of the brain anytime soon. Reconceptualizing both genomics and the brain as complex, interactive networks remains a necessary step to significant advances in either field (e.g. a health care revolution or AI, respectively). And despite these setbacks, we can expect big things on the way.
Genetics has already revolutionized our health care in certain respects. Preimplantation genetic diagnosis (PGD) has already made huge progress towards eradicating genetic disease before birth, a significant but often overlooked accomplishment. But more lies ahead. Coming decades will see the creation of genetic therapies based around the specific molecular details of a given disorder. Diseases such as pediatric cancer are already the target of multi-year genomic research, and more diseases will benefit from genomic research as costs come down. And as the genetic underpinnings of disease come into focus, personal genetics will also undoubtedly enjoy a second life - regardless of whether today’s companies survive to see it.
[This is a remarkable overview of the "Decade since 'Genome Project'" - but is seriously flawed. It is trivial that the "Decade" was not that of any "Genome Project", but of the "Human Genome Project". More of a nuance is that the Decade since "the completion of the FIRST DRAFT" of a non-existent "human genome" (a composite of five individual donors...) WILL be a decade-old on June 25, 2010. Thus, we have some time for an unfolding national-global introspection, that is actually correct. Below, we'll draw some "talking points" that have been masked by waaaaay to much politics and ego-battles over the years. Perhaps the significant difference in viewpoints is, that IMHO one must separate "breakthroughs of science" from "industrialization of scientific achievements" - Pellionisz_at_JunkDNA.com]
Scientist: 'We didn't create life from scratch'
From CNN reports
May 21, 2010 4:45 p.m. EDT
CNN) -- Genetics pioneer J. Craig Venter announced Thursday that he and his team have created artificial life for the first time.
Using sequences of genetic code created on a computer, the team assembled a complete DNA of a bacterium, then inserted it in another bacterium and initiated synthesis, or in Venter's words "booted up" the cell.
In a statement, Venter called the results "the proof of principle that genomes can be designed in the computer, chemically made in the laboratory and transplanted into a recipient cell to produce a new self-replicating cell," controlled only by the synthetic genome.
Venter answered questions Thursday about the achievement.
CNN: What exactly have you done?
J. Craig Venter: We announced the first cell that is totally controlled by a synthetic chromosome, that we designed in a computer based on an existing chromosome.
We built it from four bottles of chemicals.. that's over a million base pairs [of chromosomes]. We assembled that and transplanted it into a recipient cell and that new chromosome started being read by the machinery in the cell, producing new proteins, and totally transformed that cell into a new species coded by the synthetic chromosome.
So it's the first living self-replicating cell that we have on the planet whose DNA was made chemically and designed in the computer.
So it has no genetic ancestors. Its parent is a computer.
Time.com: Scientist creates life. That's a good thing, right?
CNN: What's its name?
Venter: "It is software.. It's DNA software."
CNN: How big a deal is this?
Venter: It's for others to describe. It's a big deal for us. We've been working on it for 15 years. It gives us tools to work with that haven't existed before. And we have some huge challenges.
We need new tools in science. Allowing us, for example, new organisms that more efficiently can capture C02 and convert it into fuel so we can get weaned off of oil.
We can create new food substances. ... We can create new ways to create clean water. We are already going to create new vaccines to treat diseases that emerge each year like the flu, so it's a new tool for scientists to work with.
But it's also a change conceptually. This is the first time we had a life form whose genetic code was made chemically. It tells us about the dynamic nature of life...That it changes second to second.
You take away the DNA, we're dead very quickly. You can't have life without the genetic code.
CNN: What does this mean for the average person?
Venter: This is a basic science breakthrough that now takes us from what was a hypothetical possibility -- that we could have synthetic life in these tools -- to rapidly advance to get some breakthroughs.
This is the first baby step that allows us to do that.
But it's a conceptual change... because we know it's possible. It should give people hope that we have new tools to tackle these problems.
CNN: Did you create new life?
Venter: We created a new cell. It's alive. But we didn't create life from scratch.
We created. as all life on this planet is. out of a living cell.
CNN: Some critics suggest you shouldn't make life from a computer.
Venter: People have been discussing this for the past decade since we've made incremental steps trying to get to this point. This is the fourth scientific publication in a series since 2003, so you can find 100,000 blogs out there discussing philosophically what this means, where does it take us, can we build things based on our imagination. So I think this will stimulate a lot of thinking, a lot of discussion.
CNN: Could you build an actual living organism - Frankenstein like?
Venter: Well these are very small cells. They are living. They are self-replicating. But if you're trying to advance life forms like you and me, I think that's still in the realm of science fiction.
CNN: This is a big deal ... What's next?
Venter: People keep asking me that at various dates. I was asked that 10 years ago after sequencing the human genome - you couldn't possibly top that - so we consider this a more important accomplishment than sequencing the human genome. So, following through on that is what's next for us, and see if we can create some of these cures for the planet
CNN: How excited were you? Did you pop champagne?
Venter: We did, but our initial emotion was more one of relief that it finally worked. You can imagine 99 percent of your experiments fail for one reason or another. This, when it finally worked, we were more relieved than excited.
CNN: What does it mean to you?
Venter: When you work on something for 15 years, it's a great sense of accomplishment. This is a demonstration of what new multidisciplinary team science is about. and I couldn't be prouder of our team.
The Journal Science Interviews J. Craig Venter About the first "Synthetic Cell"
Get Your Genotype Tests Now Before Congress Makes Them Illegal
Ronald Bailey | May 26, 2010
A couple of weeks ago, we saw the sorry saga of the Food and Drug Administration stomping on the effort by the direct-to-consumer (DTC) genotype screening company, Pathway Genomics, to offer its tests through drugstores. Pathway had reached an agreement with Walgreens to sell its test kits over-the-counter in its 6,000 or so stores. The FDA sent a threatening letter asking Pathway to justify the unregulated sale of a "medical device" to the public, and Walgreens backed away from its deal with the company.
Now the Congressional nanny-in-chief and head of the House Energy and Commerce Committee, Rep. Henry Waxman (D-Calif.) is demanding information by June 4 from three DTC companies, Pathway Genomics, Navigenics, and 23andMe. As Bloomberg reports:
The lawmakers gave the companies until June 4 to submit documents on the ability of the tests to identify consumers’ risks for illnesses. The legislators also requested information on the proficiency of the companies’ lab testing, policies on consumer privacy and whether the kits comply with FDA rules.
Some purchasers of the screening tests may be dissatisfied with their experiences, but I would suggest that most are first-adopter types who recognize the current limitations of genetic screening science. The way that consumers learn about the upsides and downsides of new products is to try them out; just as the way companies learn how to improve their products is through customer feedback. As often occurs, the "I'm-from-the-government-and-I'm-here-to-help" types are eager interfere with this kind of speedy social learning.
If you've been thinking about buying a gene screening test, you might want to go ahead now before Congress and the FDA make it illegal for you to get this kind of information. Just saying.
Disclosure: I [Ronald Baiely] am a happy customer of 23andMe (though I really wish their test had screened for the APOE4 allele associated with a much higher risk of Alzheimer's disease). Given this news, I am going to order a new test from another company today. I own no stocks in any gene screening companies. Finally, my article on the joys of DTC gene screening and the exaggerated concerns over genetic privacy has at last been submitted to my editors at Reason who are now busy making improvements to it.
[Just as when 23andMe offered a stunning discount of $99 for their usually $499 DTC service (on DNA day), the looming Congressional Investigation may trigger another avalanche of consumers who wish to ascertain their unelianable right to know their genome. I also encourage people to do that, with the specific note that leading DTC Genome Testing companies (like 23andMe and Navigenics) include in their price that the consumer can download from the secure site their own "raw SNP data file" - which is theirs, not only because it is their own characterization of individual diversity, but also because they have already paid for it. It is important to know that NOT all DTC Genome Testing companies provide you with the raw SNP data file - maybe since according to some unofficial statements of those companies that do provide this capability, very few customers actually download the "raw SNP data file". While for average customers it looks like just a bunch of numbers, it is a treasure, since e.g. the "Shop for your life" YouTube was made with Ms. Boonsri Dickinson kindly downloading her file from a DTC Genome Testing company and under a confidentiality agreement that HolGenTech will only use those results that she herself went public with, kindly sent us her "raw SNP data file" to make it eminently usable in daily life. - Pellionisz_at_JunkDNA.com]
Who Should Control Knowledge of Your Genome?
SmartPlanet
Dana Blankenhorn | May 26
A Congressional investigation has brought into sharp relief some of the political implications of genetic testing.
Rep. Henry Waxman and his House Committee on Energy and Commerce have sent letters to the leading makers of genetic testing kits — Pathway Genomics, Navigenic, and 23andme — as the first step in an investigation of the direct to consumer (DTC) genetic testing industry.
This followed the FDA’s decision to send Pathway a letter demanding it show it either FDA approval of its tests or its reasons why such approval is not necessary.
This was prompted by Walgreens and CVS plans to offer the Pathway test in their stores. Pathway already sells its test online.
The Pathway test costs just $30 and involves collecting a bit of saliva, then sending it to the company’s lab.
(And to think just last month our Boonsri Dickenson was writing about $99 tests and her own experience with the $999 version, which said she was at risk for macular degeneration later in life.)
The investigations have sparked a hair on fire moment for the industry, with people like Andras Pellionisz (above) of HolGenTech ...
“Consumers must ask, ‘whose genome is it anyway?’” Pellionisz says.
His concern is that any restriction on Direct To Consumer (DTC) or Over The Counter (OTC) genetic testing will give foreign competitors like DeCodeMe of Iceland and Korea’s DTC Genome Testing institution (backed by Samsung) a leg-up on a lucrative market.
That may be true. But there are also some serious questions to be asked, questions that have not been asked yet, before we make genetic tests as ubiquitous as home pregnancy kits:
How useful are they, really – All of us have DNA which shows how we might die. [Not true, see e.g. George Church - AJP]. Are these kits just creating needless panic?
How accurate are they – There are reports of cancer-free women ordering mastectomies because there is breast cancer in their family history already.
Are we ready yet – Scientists don’t yet know what a complete genetic test means. Given that reality most of what a test delivers will be as useful as a palm reading.
It’s true that you can sell anything you want to people if you don’t claim it’s medicine. But genetic tests are medicine. [Not true, see below - AJP]
Even if the terms of service for 23andme prohibit sharing the data with your doctor, people will share the data with their doctors, as Steve Murphy of GeneSherpas recently noted. What other reason is there for getting the test?
Pellionisz is right about one thing. It may be way too late to put this one back in the box. Al Gore helped launch Navigenics. And 23andme co-founder Anne Wojcicki is also Mrs. Sergey Brin, as in Google co-founder Sergey Brin.
The industry has also been getting on TV, with celebrities like Larry David getting their DNA tests read out on the George Lopez Show.
It’s not the “consumer wanting to know what’s going to kill me” market that should be the political issue in any case. It’s the identification market.
This month the full U.S. House approved legislation that will pay states to collect DNA samples on all those people arrested for any crime, as a crime-fighting measure.
That’s where the money is. That’s where the politics is.
So where do you stand on the issue. Want your DNA tested? Want to be able to resist having it tested? It’s your DNA — who should know about it?
---Comment (1) by Pellionisz
05/26/10
RE: Who should control knowledge of your genome?
While I largely agree with Dana, there are some fine points to make. Perhaps the most significant disagreement is that in his opinion genome testing can be boxed into "Medical". IMHO there is plenty to think "outside the box". Indeed, establishing some A,C,T,G letters, in DTC up to 1.6 million, or in full DNA sequencing obtaining all the12.4 Megabits of information of the diploid DNA is just a mapping out of individual human diversity.
Humans differ from one-another in about 4% of their A,C,T,G bases. Such differences can [be] just individual traits with your eye color different from mine, or many Chinese friends of mine unable to metabolize lactose when they grow out of childhood while most Northern Europeans continue thrive on it. My YouTube-s ("Pellionisz"), especially the "Shop for your Life!" put an emphasis on the immediate impact on consumerism by using genomic information that is not medical, at all. Also, a genomic test that reveals your ancestry-tree is not medical.
I congratulate and support with my tax dollars those governments that well serve their taxpayers. Governments wasting resources or using them to try to prevent knowledge [for people] of their bodies are attempts that I disagree with. The US government has just poured an enormous amount of money into genomics (also because of an interest in bioenergy - nothing to do with "medical"...) and also re-vamped the health-care system.
It goes unmentioned in the posting that the US health-care will simply be unsustainable if genome-based prevention will not save trillions by preventing or delaying some of the most expensive and (not only individually, but also socially) devastating diseases (neurological disorders, cancers).
[This blog (and reply) was prompted by Dr. Pellionisz' posting in HolGenTech Blog "Justifying DTC Genome Testing with Consumerism" that (tries to...) make it clear that the fulcrum of the wild media coverage of "DTC debate" truly is that DTC Genome Testing is much bigger than "The Box of US Medicine" (and thus is a global issue, not even limited to USA). The debate is already sizable, and escalates rapidly. Thus far (as the above blog by Dana Blankenhorn also illustrates) the debate is extremely diffuse with all kinds of issues mentioned (and unmentioned...). Some of them, like "All of us have DNA which shows how we might die" are fairly common remnants of an obsolete gloomy (mis)understanding of genomics - already superseded by new knowledge supplied by epigenomics, giving us hope, that "The Genome is NOT Your Destiny". - Pellionisz_at_JunkDNA.com]
'Junk' DNA behind cancer growth
ANI, May 21, 2010, 12.00am IST
Scientists have discovered a new driving force behind cancer growth.
Researchers from the University of Leeds, UK, the Charite University Medical School and the Max Delbruck Centre for Molecular Medicine (MDC) in Berlin, Germany, have identified how 'junk' DNA promotes the growth of cancer cells in patients with Hodgkin's lymphoma.
Professor Constanze Bonifer (University of Leeds) and Dr Stephan Mathas (Charite, MDC) who co-led the study suspect that these pieces of 'junk' DNA, called 'long terminal repeats', can play a role in other forms of cancer as well.
The researchers uncovered the process by which this 'junk DNA' is made active, promoting cancer growth.
"We have shown this is the case in Hodgkin's lymphoma, but the exact same mechanism could be involved in the development of other forms of blood cancer. This would have implications for diagnosis, prognosis, and therapy of these diseases," said Bonifer.
'Long terminal repeats' (LTRs) are a form of 'junk DNA' - genetic material that has accumulated in the human genome over millions of years.
Although LTRs originate from viruses and are potentially harmful, they are usually made inactive when embryos are developing in the womb.
If this process of inactivation doesn't work, then the LTRs could activate cancer genes, a possibility that was suggested in previous animal studies.
This latest study has now demonstrated for the first time that these 'rogue' active LTRs can drive the growth of cancer in humans.
The work focused on cancerous cells of Hodgkin's lymphoma that originate from white blood cells (antibody-producing B cells).
Unusually, this type of lymphoma cell does not contain a so-called 'growth factor receptor' that normally controls the growth of other B-cells.
They found that the lymphoma cells' growth was dependent on a receptor that normally regulates the growth of other immune cells, but it is not usually found in B-cells.
However in this case, the Hodgkin-/Reed Sternberg cells 'hijacked' this receptor for their own purposes by activating some of the 'junk DNA'.
In fact the lymphoma cells activated hundreds, if not thousands, of LTRs all over the genome, not just one.
Hodgkin-/Reed Sternberg cells may not be the only cells that use this method to subvert normal controls of cell growth.
The researchers found evidence of the same LTRs activating the same growth receptor in anaplastic large cell lymphoma, another blood cancer.
The consequences of such widespread LTR activation are currently still unclear, according to the study's authors.
Such processes could potentially activate other genes involved in tumour development. It could also affect the stability of chromosomes of lymphoma cells, a factor that may explain why Hodgkin-/Reed Sternberg cells gain many chromosomal abnormalities over time and become more and more malignant.
The study has been published in Nature Medicine.
[Excerpt from Nature Medicine article]
During evolution, mammalian genomes have accumulated many LTRs derived from ancient retroviral infections1. LTRs in the human genome, of which several thousand copies belong to ‘mammalian apparent LTR retrotransposon’ (MaLR)-like sequences2, contain functional promoter and enhancer elements1. As the insertion of an active LTR can interfere with gene regulation, the mammalian organism has devised a number of surveillance mechanisms to silence these elements early in development, usually by DNA methylation3. Despite this, genome-wide analysis of the human transcriptome has revealed that an unexpectedly high proportion of transcripts initiate within repetitive elements4. However, the initiation of gene transcription from repeat elements has been documented in detail for only a few human genes, where LTRs function, for example, as alternative promoters regulating cell type-specific gene expression1. Although it has long been speculated that the aberrant activation of repeat elements could contribute to the development of human diseases and malignancies1,5, the pathogenetic relevance of repeat activation is unclear1,6. In mice, deletion of the lymphoidspecific helicase (Lsh) gene or a hypomorphic DNA methyltransferase-1 (Dnmt1) allele causes activation and transposition of endogenous retroviral elements with concomitant chromosomal instability and induction of erythroleukemias or T cell lymphomas, respectively7–10.
["Repeats" have long been considered "the Junkiest parts of "Junk DNA". Indeed, so-called "repeat maskers" got rid of them, BEFORE most DNA sequences were analyzed. This article is an experimental support that genome regulation to a large extent is based on correct (in FractoGene's terms, "free of fractal defects") action of genome regulation, based on the Principle of Recursive Genome Function (an algorithmic, thus software-enabling approach. With the article below, demonstrating that such software can be made extremely effective (fast and green) by hybrids of parallel and serial processors, we have entered the new era when the oncoming full DNA sequences will be "syntax-checked" for a slew of "structural variants" both based by the brute force of serendipituous seach, and targeted ultra-fast search of fractal defects, directed by the new axiomatic science of genome informatics. - Pellionisz_at_JunkDNA.com]
Convey Computer Hails Genomics Search Record
May 24, 2010
[Traditional serial processing -Convey is great conveying ideas ... - AJP]
[Parallel processing increases throughput - AJP]
[Hybrid architecture with quad serial and one parallel processor - AJP]
Richardson, Texas-based Convey Computer, a developer of hybrid-core computers which used hardware to accelerate software processing, reported today that it has demonstrated an implementation of a genomics analysis algorithm, the Smith-Waterman algorithm, which is a 172 times faster than conventional software. Smith-Waterman is an algorithm used to analyze DNA and protein sequences for similarity matching. Convey's hardware uses Intel Xeon processor and Xilinx FPGAs (Field Programmable Gate Arrays) to implement and speed up software operations. The firm said its hardware has started to be adopted by the life science research industry, and is being used at the University of South Carolina and Virginia Bioinformatics Institute (VBI) at Virginia Tech. Convey is backed by Braemar Energy Ventures, CenterPoint Ventures, Intel Capital, InterWest Partners, Rho Ventures, and Xilinx.
[Convey is not the first to demonstrate (the obvious) that the genome (essentially, a parallel processor with 2-bit bases of A,C,T,G-s) is ideally suited for FPGA (parallel, low-bit manipulations). Both SGI and Mitrionics has done so, earlier (also, Danish CLCbio attempted) and Dr. Pellionisz as Director of Genome Informatics to Mitrionics lent some of his energies to see if a European-based small Swedish company was ambitious and resourceful enough to break into the Genomics market in the early part of 2008 - before the major recession hit . In a rather different ecosystem of today, with the tsunami of full DNA sequences are hitting the flabbergasted genomics community, operating from the heart of "Think Big Texas", it is almost certain that time has come to turning early pioneering into major lucrative business - Pellionisz_at_JunkDNA.com]
Transparency First: A Proposal for DTC Genetic Testing Regulation
Posted by Dan Vorhaus on May 24, 2010
These are hectic days for the field of direct-to-consumer (DTC) genetic testing. Every week, and sometimes every day, seems to bring a new development. Two weeks ago it was pharmacy giants Walgreens and CVS unveiling agreements with Pathway Genomics to offer Pathway’s genetic testing kits in drugstores nationwide, to which the FDA responded first by declaring such a strategy illegal and, shortly thereafter, launching an investigation. Last week, on the same day that the University of California, Berkeley announced it would be offering genetic tests to all incoming freshmen, a House of Representatives committee announced it was launching its own investigation into three prominent DTC genetic testing companies.
These developments reflect an uncertainty about the regulatory status of DTC genetic testing that is dramatic, although it is not new. In the summer of 2008, public health officials in New York and California sent warning letters to a number of DTC companies, including 23andMe and Navigenics (both targets of the current Congressional investigation). These state regulatory activities prompted concern that other states might follow suit, potentially subjecting DTC companies to the nightmare scenario of inconsistent state-by-state regulation. Nearly two years later, those particular concerns appear to be unfounded.
An Inevitable Regulatory Response. But as the DTC genetic testing industry expanded, state and federal regulators grew increasingly conspicuous by their silence. The possibility of regulatory activity has been the elephant in the DTC room for some time now (at the Genomics Law Report we have been writing about the possibility of DTC regulation since our inception) and, indeed, many DTC companies have long indicated that they would welcome more definitive federal regulation.
The specific trigger for this recent flurry of activity by the FDA and Congress is something of a puzzle- the distinction between DTC genetic tests offered on Walgreens’ shelves as opposed to online at Amazon.com is difficult to parse, and the FDA’s initial comments, delivered through the media by a variety of spokesmen, have frequently confused rather than clarified. But the simple fact is that a regulatory response to DTC genetic testing was overdue. That it happened to be Pathway’s attempt at creative product placement will prove to be, ultimately, nothing more than a footnote to a larger ongoing discussion about the proper place of DTC genetic testing in this country. [Dan's brilliant and law-expert treatise falls short of the global issue - that DTC is already pursued - in fact, started - off-shore to US, in Iceland, and just recently a DTC genome testing institution started in Korea, with the backing of SAMSUNG - AJP]
For the remainder of this post, rather than speculate about what manner of regulatory response will be forthcoming from the FDA, Congress and elsewhere, we ask (and answer) the 550,000 SNP question instead: if a regulatory response to DTC genetic testing is inevitable, what should it look like?
A Transparent Solution. More than anything else, what the DTC genetic testing industry needs right now is enhanced transparency, and not necessarily in the form of traditional direct regulation by the FDA. Rather than driving the regulation of DTC genetic tests through traditional channels, such as the FDA’s premarket review and approval regime for medical devices, regulators should focus instead on shining a bright light on DTC genetic testing, improving their own and the public’s understanding of what information is available to consumers and how that information is actually used.
As it happens, creating greater DTC transparency can be most efficiently accomplished without the application of regulations that would be onerous for early-stage DTC companies and their investors, restrictive for consumers interested in the broadest access to their genetic information and expensive and time-consuming for regulators to enforce.
Over the next 6-9 months, the DTC genetic testing industry and regulators, working together, should take three key steps to enhance transparency industry-wide, ensure that customers, regulators and healthcare professionals are better able to understand and evaluate the products offered, and encourage the DTC industry to grow responsibly without more traditional regulation.
Step 1: Make Participation in the NIH’s Genetic Testing Registry Mandatory. The most promising development for improving transparency with respect to specific DTC genetic testing companies and products is the recently announced and NIH-backed Genetic Testing Registry (GTR). The GTR is a direct outgrowth of a 2008 report prepared by the Secretary’s Advisory Committee on Genetics, Health, and Society (SACGHS) on the “U.S. System of Oversight of Genetic Testing” (pdf). The SACGHS report recommended the following:
To enhance the transparency of genetic testing and assist efforts in reviewing the clinical validity of laboratory tests, HHS should appoint and fund a lead agency to develop and maintain a mandatory, publicly available, Web-base registry for laboratory tests. (emphasis added)
Although announced two months ago as voluntary initiative, many of the GTR’s supporters have long argued that such a registry should be mandatory, and its voluntary character is unquestionably the GTR’s most significant departure from the original SACGHS recommendation. At its current early stage of development, however, there is plenty of time for that feature to change.
The upside of the GTR is clear. It would provide a single, comprehensive source of information about DTC genetic tests for regulators, purchasers and other end users (including healthcare professionals), enabling side-by-side comparison of tests and allowing regulators or neutral third parties to evaluate the accuracy of their data and claims. It would also likely standardize (or at least clarify) test offerings, spur healthy competition between providers and enable consumers to make purchasing decisions on the basis of meaningful criteria (e.g., price, information content, insurance coverage, etc.) instead of marketing campaigns.
All of these benefits, however, depend on widespread participation in the GTR by DTC genetic testing companies. At the time of the GTR’s announcement, current NIH chief of staff (and long-time GTR proponent) Kathy Hudson conceded that, while she would have preferred a mandatory registry, it was unclear whether the NIH had the authority to enforce such a requirement. While that is likely the case, (arguably) the FDA and (certainly) Congress have the authority to render participation in the GTR mandatory for DTC genetic testing companies.1 DTC companies should be eager to embrace a mandatory GTR (as at least one already has) as a relatively painless way to demonstrate to the public and to regulators their willingness to cooperate and their commitment to providing high-quality and transparent genetic testing services.
Step 2: Continue to Improve FDA Regulatory Transparency. An editorial appearing in last week’s New England Journal of Medicine by two senior FDA officials describes the agency’s recent and substantial efforts to improve transparency. The FDA’s Transparency Task Force is currently entering its third and final phase, seeking ways to improve transparency to regulated industries.
As part of this initiative, the FDA is seeking comment on 21 proposals (pdf) designed to enhance transparency at the agency. The FDA’s recommendations, particularly recommendations 10 and 11, could significantly improve public understanding of how and when the FDA evaluates regulated medical devices. The recommendations are an important step in improving transparency at an agency that has not had enough of it in recent years. Unfortunately, none of the proposed recommendations would improve the transparency of the process by which the FDA determines which products to regulate in the first place, including DTC genetic tests.
Here is where the FDA, specifically the agency’s Office of In-Vitro Diagnostic Device Evaluation and Safety (OIVD), headed by Director Alberto Gutierrez, can help appropriately regulate DTC genetic tests without actually increasing its already substantial regulatory burden. Not only should the FDA encourage transparency across the DTC genetic testing industry by supporting the NIH in its development of the GTR, and strongly encouraging or even requiring DTC genetic testing companies to participate, it should also work closely with the NIH, industry and other key stakeholders to clarify exactly what information it would like to see included in the GTR.
One of the difficulties for the DTC genetic testing industry, at least at present, is that the FDA has been less than clear in describing the elements of DTC genetic tests that most concern the agency. Is it the list of conditions or genetic variants tested? The nature of the claims (informational vs. medical) made by the company or the product? The physical locations at which a test is sold? Or is it some other consideration entirely or, more likely, a combination of all of the above?
The FDA is clearly still refining its policy with respect to DTC genetic tests, and there is plenty of time for it to continue to do so. In the meantime, it should involve DTC companies and customers, medical professionals, policymakers and other key stakeholders in determining the relevant information to collect and review with respect to DTC genetic testing. In doing so it can use the already-in-development GTR as a public tool for transparently refining its policy and collecting relevant information. This approach would go a long way toward eliminating the case-by-case review of DTC genetic testing companies and products that appears to have categorized the FDA’s approach to date.
Step 3: Involve the Federal Trade Commission. As we wrote last week, there is another regulatory agency that could play an important role in the development of DTC genetic testing: the Federal Trade Commission (FTC).
In 2006, the FTC worked with the FDA and the CDC to publish a guidance document for consumers entitled At-Home Genetic Tests: A Healthy Dose of Skepticism May Be the Best Prescription. Four years in the area of DTC genetic testing is an eternity – the FTC’s guidance was issued before any of 23andMe, Navigenics and Pathway Genomics, the three companies currently the focus of the Congressional investigation, existed – but it indicates that the agency has at least some familiarity with the industry. More importantly, the guidance reminds consumers of the FTC’s mission, which has not changed: “to work[] for the consumer to prevent fraudulent, deceptive, and unfair business practices in the marketplace and to provide information to help consumers spot, stop, and avoid them.”
By making the GTR mandatory (Step 1) and working with the FDA to carefully specify the relevant information to be included in the registry (Step 2), the FTC would be well positioned to monitor the DTC genetic testing industry for companies unwilling to subject their products or claims to the public scrutiny afforded by the GTR (Step 3). While the FDA and Congress have launched investigations into well known DTC genetic testing companies, there are a plethora of other companies (see, for example, this list at DNA Test Index or this list at AccessDNA) that appear, for the moment, to have escaped the attention of regulators. Rather than require the FDA or Congress to investigate each new DTC genetic testing company that sprouts up, why not require those companies to register with the GTR?
This would provide the FTC, along with the rest of us, with a single point of entry to collect and evaluate registered DTC genetic testing companies, while those companies that refuse to participate in the GTR will likely be quickly ferreted out and referred to the FTC by an active community of DTC genetic testing companies and consumers with a vested interest in maintaining order industry-wide.
Reports of DTC’s Death Greatly Exaggerated? Using a community- and transparency-driven approach would make it easy to separate the DTC wheat from the chaff, enabling legitimate DTC companies to continue to provide consumers with the genetic information they desire, while minimizing the risk that consumers will be presented with false or misleading genetic testing products or services.
More importantly, focusing on transparency and sustained information gathering is an appropriate, measured response to the developing DTC genetic testing industry. One that will bring companies, consumers and regulators into closer collaboration, without imposing a regulatory regime that would risk stifling the creativity and growth of the industry or depriving consumers of the ability to directly access their genetic information. While it has long been inevitable that regulatory agencies would play a significant role in shaping the future of the genetic testing industry, there is absolutely no reason why, with that day apparently upon us, that development need spell the death of DTC.
__________________________
1 As discussed in our earlier article, there is some disagreement over whether the FDA has such authority. What is not debatable, however, is that Congress, should it desire to do so, could take action that would remove all doubt as to the authority of the FDA (or another agency of its choosing, such as CMS) to regulate DTC genetic tests.
Note, also, that a GTR that was mandatory for DTC genetic testing companies would not need to be mandatory for all providers of genetic tests. A majority of genetic tests are not provided directly to consumers, and this would be a relatively clear distinguishing characteristic upon which to evaluate whether a test was required to be included in the GTR, or simply permitted to be included at the provider’s discretion.
[Dan's continuing analysis on "DTC debate" is by and large perhaps the best, exuding his legal expertise and widespread knowledge. Thus, any notion here is not meant to take away anything from his brilliance, but in a constructive and collective way to try to even further improve upon it.
While "Transparency" is, indeed, essential, perhaps it should be made a priority that the first tasks of such transparency are 1) Definition of the subjects (e.g. this entire debate started from the confusion of a "Gene testing kit" that is indeed just a container for saliva-sample, to be sent with the consumer's separate direct order to a Genome testing company) 2) Identification of problems, if any, 3) Ownership of problems. Further, IMHO Dan's second and third Steps are to a large extent contradictory, that he is not even trying to hide.
Most importantly, while yours truly absolutely agrees with the conclusion that "DTC is not dead" IMHO the US might wish to parse the weight of the prognosis that if in the US jurisdiction is "not dead" - but given the entanglements and resolutions of Step 2 and 3 - himself talking about 6-9 months, having worked with the government my guess is more like 6-9 years - to prevent the US simply falling out from the global competition - an absolutely first imperative is to issue an ultra-quick Congressional Moratorium valid under Federal USA jurisdiction, that until the maze or regulatory agencies put their houses in order, the DTC Genome Testing stays limited to those requirements that the State of California (a known trend-setter in Federal matters) already worked out two years ago (and with which all three targeted CA-based companies absolutely comply already):
1) DTC genome testing must be conducted by the use of Certified Laboratories
2) DTC genome testing must be prescribed by a physician
I would add my blog-reply
