Top scientists share their future predictions

The Sunday Times
December 27, 2009

Nothing much is going to happen in the next 10 years. [Thus far, the predictions are similar to my subdued "lowering expectations" - see below, AJP]. Of course, that’s not counting the diesel-excreting bacteria, the sequencing of your entire genome for $1,000, massive banks of frozen human eggs, space tourism, the identification of dark matter, widespread sterilisation of young adults, telepathy, supercomputer models of our brains, the discovery of life’s origins, maybe the disappearance of Bangladesh and certainly the loss of 247m acres of tropical forest.

As I said, just another decade really.

These days, “just another decade” always means 10 years of future shock. Science, technology and the contemporary mania for change combine to stun the imagination. It is the way we live now, in a condition of permanent technological revolution.

In 2000 — remember? — the internet all but died when the dotcom stock market bubble burst [Sure ... tiny Google just became Yahoo's search engine, with Yahoo refusing to buy Google for $1 M - AJP]. You could stand on top of the World Trade Center. And mobile phones were just, er, phones. Today, you still get up and eat breakfast, but, outside, it’s a different world.

Next? Well, as Woody Allen said, if you want to make God laugh, tell him your plans for the future. But, taking a punt, I reckon the brain is the one to watch. Science has been zeroing in on the 2lb 14oz of grey and white custard-like stuff between your ears for some time now. It’s not been easy. In spite of the evidence of The X Factor, the human brain is very complex custard indeed. But some people are getting very excited [Kurzweill and I tend to believe that "the brain is a probabilistic fractal"; looking complex, but "complexity is in the eye of the bewildered" - AJP].

“By 2020, genetics and brain simulation will be giving us personalised prescriptions for marriage, lifestyle and healthcare.” This is Henry Markram, director of the Blue Brain project in Switzerland, an attempt to reverse engineer the brain by building one from the ground up inside a supercomputer.

“We won’t need a psychologist to tell us why we feel unhappy. All we’ll need to do is log into a simulation of our own brain, navigate around in this virtual copy and find out the origins of our quirks ... Computers will look at a virtual copy of our brains and work out exactly what we need to stop our headaches, quiet the voices talking in our heads and climb out of the valley of depression to a world of colour and beauty.”

Gosh. But isn’t there still that pesky problem of other people and their brains? It’s their quirks that tend to get in the way of my happiness. No problem, we can climb inside each other’s brains.

“The big thing for me is being able to link two brains together for communication.” This is Kevin Warwick, a cybernetics scientist at Reading University. “This could have great implications for teaching. Sometimes, no matter how you explain something, it takes forever for the penny to drop. [The one who laughs last is the one who did not get it ...- AJP]...

James Watson, co-discoverer of the structure of the DNA molecule, thinks gene sequencing will be the key to unlock the custard and even stir it. “Disorders like Alzheimer’s disease, epilepsy, Parkinson’s disease, schizophrenia, bipolar disease, unipolar depression, obsessive-compulsive disease, attention deficit disorder and autism will finally have their genetic guts open for all to see.”

Some of the most impenetrable and harrowing mental illnesses known to man will, Watson believes, be understandable and maybe even curable.

“The exact location and biological function of the DNA variants causing many depressive disease and related disorders cannot be revealed too soon,” he says. ...

“There will be a breakthrough. My hunch is that research on motor neurone disease will provide crucial clues and by 2020 we will know why cells die in some, perhaps many, of these diseases. It could be another decade before we see the impact on health, but by 2020, we must be on the way to this ultimate goal of modern medical science,” says Blakemore. ...

Chris Rapley, director of the Science Museum and professor of climate science at University College London, says we cannot cut emissions fast enough, so we need to suck carbon dioxide out of the atmosphere, perhaps using artificial trees that eat it.

“If it can be achieved, it will allow us to exploit the substantial reserves of oil, gas and coal to sustain society through the inevitably long and hard transition to a low-carbon world, without causing dangerous climate change. If ever there were a technical project that humanity should invest in, this is it.”

Craig Venter, the genetic maverick who first sequenced the human genome, may have one solution. He’s working on making bacteria that excrete diesel, leaving the Saudis wondering what to do with all that oil. “The debate on fuels and energy is blown out of proportion. We are very close to solving the energy needs in a way that will make our children enjoy cheaper and more efficient energy than what we see today,” he says....

It’s just another decade of future shock. So it goes. Of course, the real shock will be what actually happens, which is never the same as what people say will happen. But, anyway, the shocking Noughties are over, happy new ... good grief, we haven’t even predicted a name for it! [This one is easy: "The Decade of Genome Based Economy" - AJP]

deCODE Discovers a Major Risk Factor for Type 2 Diabetes Dependent on Parent of Origin

A Single SNP That Confers Increased Risk if Inherited From the Father, but is Protective if Inherited From the Mother

REYKJAVIK, Iceland, December 16 /PRNewswire-FirstCall/ -- Scientists at deCODE genetics, Inc. (Nasdaq:DCGN) publish in the journal Nature the discovery of a version of a common single-letter variant in the sequence of the human genome (SNP) with a major impact on susceptibility to type 2 diabetes (T2D). The impact of the T2D variant is not only large, but unusual: if an individual inherits it from their father, the variant increases risk of T2D by more than 30% compared to those who inherit the non T2D-linked version; if inherited maternally, the variant lowers risk by more than 10% compared to the non T2D-linked version. Nearly one quarter of those studied have the highest risk combination of the versions of this SNP, putting them at a roughly 50% greater lifetime risk of T2D than the quarter with the protective combination. This is the second largest effect of any genetic variant for T2D apart from SNPs in TCF7L2, discovered by deCODE in 2006.

"We could make this discovery beacause we are in the unique position of being able to distinguish what is inherited from the mother from what is inherited from the father. This we can do because of the large amount of data we have assembled on the Icelandic population. These data empower us in many ways. For example, using our ability to impute sequence data, we can multiply by 100 times the amount of information generated by sequencing one individual. We can use these tools to discover and integrate rarer variants into our tests and scans, identify drug targets for licensing, and put our know-how at the disposal of our service customers. We believe that this is an important advantage for conducting large-scale whole sequence studies over the next couple of years," said Kari Stefansson, CEO of deCODE.

Because the risk is inherited and varies in this way, the SNP, located on chromsome 11, had never been linked to T2D even though it had been genotyped in large, traditional genome-wide association studies (GWAS). These do not distinguish between paternally and maternally inherited SNPs. But deCODE can track the parental origin of virtually any SNP in the genome of the tens of thousands of Icelandic participants in the company's gene discovery work. In this study, deCODE used its population-wide genealogy database and proprietary statistical tools to determine the parent of origin of a number of SNPs in some 40,000 Icelandic participants in the company's gene discovery programs. Some of these SNPs had previously been associated with different diseases and are located near "imprinted" genes - genes in which only the maternally or paternally inherited copy is "switched-on" to encode a protein. Five of these, one each in breast and skin cancer and three in T2D, showed that the parental origin of the variants affects the risk they confer.

deCODEme's embarrassing data processing glitches - lessons for companies and customers

[From the Genetic Future blog by Daniel McArthur - AJP]

Late last week I noted an intriguing offer by personal genomics company deCODEme: customers of rival genome scan provider 23andMe can now upload and analyse their 23andMe data through the deCODEme pipeline.

On the face of it that's a fairly surprising offer. As I noted in my previous post, interpretation is what generates the real value for personal genomics companies, so giving it away for free seems a bizarre approach to business - especially for a company living on the edge of a financial precipice. However, I also argued that the intention here is likely to be to generate an opportunity for deCODEme to display its interpretation skills to otherwise entrenched 23andMe customers, in preparation for the upcoming battle for interpretation supremacy in the whole-genome sequencing era.

In digging back through my archives I realised that this isn't actually the first time that this strategy has been employed in the personal genomics game: back in June this year, 23andMe offered its interpretation service free to customers of Illumina's freshly-launched $48,000 whole genome sequencing service (the original source is this subscription-only article in industry publication In Sequence).

It's nonetheless the first time that a personal genomics company has opened itself up to genome scan customers, and it's certainly a disruptive (and potentially game-changing) move. AccessDNA's Jordanna Joaquina even goes as far as to speculate that this may herald a shift in deCODEme's strategy towards pure data interpretation. I personally think this is unlikely for deCODEme itself, but I wouldn't be shocked to see a proliferation of multi-platform interpretation services over the next 12 months (Knome's recently announced discovery service is a step in that direction).

But creating an interpretation service that can deal seamlessly with data provided in a multitude of formats from different providers can be a challenging task, as deCODEme learnt in a particularly embarrassing manner this week:

--

deCODEme opens its doors to free data upload from 23andMe customers
December 17, 2009

A curious tweet this morning from personal genomics company deCODEme, barely a few weeks after the declaration of formal bankruptcy of parent company deCODE Genetics:

@decodegenetics: Migrate to deCODE this winter! Upload your genetic data for free. http://www.decodeme.com/data-upload

Here's a description of the service from the URL in the tweet:

--

deCODEme wants to give even more people the chance to enjoy the best in personal genomics. Our bioinformatics team has just launched a simple system to enable existing customers of 23andMe™ to migrate their data into deCODEme and to join our growing community. If you already have a 23andMe genetic scan, just click on the button below to begin the upload process and start to view your genome using deCODEme's many advanced features.

This service is available to existing 23andMe customers and for a limited time only.

Enjoy and spread the word!

--

Basically, the company seems to be providing its interpretation service free to customers who have already had their genome scanned by competitor 23andMe.

That's a bold and initially rather puzzling move. Those of you who've been following the personal genomics industry will know that the value of genome scans is not in the actual generation of the data (this is a straightforward procedure), but in the breadth and quality of the interpretation service.

Converting a series of half a million or so genetic data points into predictions of ancestry and disease risk is a non-trivial exercise, and requires the creation and constant, painstaking maintenance of a database of genetic associations. Parsing the literature to extract the required information can be a frustrating exercise, made even more difficult by the sheer rate that new associations are being generated.

Why, then, would deCODEme choose to give away its hard-won interpretation to customers of its most successful competitor?

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November 24, 2009
Posted by Daniel MacArthur at 8:45 AM

A short but glorious rant

Misha Angrist has a very brief but eloquent rant in response to the genomics nay-sayers in this Nature News piece on the bankruptcy of deCODE Genetics.

Here's a taste:

I agree: GWAS is of limited value and this probably contributed to deCODE's demise. But whatever deCODE's fate, if whole human genomes can be sequenced for < $2000, isn't it about time we stopped kicking GWAS's ever-stiffening corpse? Second, just because something is not a medical necessity, does it follow that it is worthless?

Genome Theory - Seven Years In The Doldrums, Taking Off In The Last 2 Years

This researcher [AJP] participated at “The Future of Life” conference – a celebration in February, 2003 of the 50th Anniversary of the Discovery of the Double Helix in Montery, California. From “Watson and Crick”, Jim was there since Dr. Crick was too ill before his passing away in 2004. Dr. Ohno died in 2000. The joyful 3-day celebration was sobered by the looming Iraq war – and the general feeling that the “Genes/Junk” system of axioms, and the “One gene – one disease – one billion dollar pill” business model of Big Pharma were perhaps mortally ill – and the quite significant concentration of business movers and shakers present did not seem to have a firm grip on how the future of genomics will be shaped.

I rose to speak very briefly (just handed over the November 21, 2002 SFGate article "Junk DNA revisited" see following Ohno's facsimile on "Junk DNA") – to announce that my intellectual portfolio held by HelixoMetry, established in August 2002, is based on the new concept of FractoGene – holding that “Fractal DNA governs the growth of fractal organelles, organs and organisms”. I did not hope for – and did not get – an instant acceptance or even much appreciation at a time when Venture Capitalists, when checked out what e.g. “introns” were, came back with the textbook answer “to keep the protein coding sections (exons) apart”… Certainly, Dr. Watson’s determination to find the gene of e.g. schizophrenia was not diminished, let alone diverted, by an initiative “to look into the Junk DNA” for answers...

At the marvellous reception in the Monterey aquarium at night of Feb. 19, 2003, chatting face-to-face with Francis Collins, he seemed to be dismissive of the radical proposal of elevating “Junk DNA” from the ash-bin of old remnants of evolution that it was assigned to by Susumu Ohno in 1972. Francis' central counter-argument was that “look at the rice, its genome is several times larger than ours – and DNA of some amoeba is inflated by a horrendous amount – that can not be anything but junk”. My pinpointing triplet-run hereditary diseases (such formations are often intronic, and as an M.D.-Ph.D. Francis was very familiar with them) visibly got him into a serious wondering mode.

So much so, that returning to D.C. Francis Collins on May 22, 2003 he asked Congress for a massive 4-year project (ENCODE) that was aimed at a deep analysis of 1% of the human DNA, to see if the gene/junk axioms were correct.

ENCODE gave a 4-year advantage to FractoGene, since it was developed based on never, for one moment, believing either Crick’s Central Dogma, or the Junk DNA misnomer. Rejection of these assumptions was based the author’s fractal model of development of Purkinje neuron 1989, that implied a “recursion”, see point 3.1.3. Unfortunately, at that time such heresy was not only forbidden in theory but was heavily oppressed in practice; resulting discontinuation of my NIH grant and outright denial of an NIH proposal (see acknowledgement in the above paper) to empower me to follow-up on a school of though that was regarded “a double lucid heresy”. Likewise, several decades of study of Purkinje neurons (search for some 17 "Purkinje" in publications) left no doubt for me that 1.3% of the DNA with 87.3% of Junk “doing nothing” just does not contain sufficient information left (a mere ~100 million A,C,T,G bases) e.g. to define development of a human being (when a 2-hour movie requires fifty times more storage on a DVD!)

As the ENCODE collaboration of a slew of countries progressed, with dozens if not hundreds of researchers meticulously looking at 1% of the human DNA, it increasingly leaked out that “Junk DNA” was anything but Junk - reinforcing the core belief of some pioneers, a select minority that never believed either the Central Dogma or Junk DNA misnomers in the first place. Realizing that millions, if not hundreds of millions of people were dying of “Junk DNA diseases” (syndromes caused by dysregulatory structural variations in the intronic and intergenic regions), this researcher felt responsible and established an International PostGenetics Society of like-minded scientists that became the first international organization to have declared on October 12, 2006 in their European Inaugural in Budapest, Hungary that “Junk DNA was a scientific misnomer”.

This facilitated the release of ENCODE data, instead of the planned September to June 14 of 2007. With the myriads of findings, most importantly that “the DNA is pervasively transcribed” in Science, Nature and 28 other Journals it was laid bare the “Junk DNA” is anything but Junk – and the architect of ENCODE, Francis Collins issued the call that “the scientific community has to re-think long-held views” (and resigned from NIHGR – to reappear in 2009 as head of the entire NIH).

In all fairness, both mistaken beliefs died a thousand deaths since their origin of 1956 (“Central Dogma” by Crick) and 1972 (“Junk DNA” by Ohno) by a slew of pioneers (see below) – but we all know that the only way to take away a toy from a child in the sandbox without screaming is to offer a “better toy” first.

With ENCODE out (and both Crick and Ohno gone) Collins’s call for “re-thinking” was heeded within 6 months (The Principle of Recursive Genome Function, submitted December 7 and accepted December 18, 2007). Main importance may be attributed to the Principle was that it superseded both obsolete dogmas (duly citing main pioneers e.g. McClintock, Jacob and Monod, Baltimore, Mattick, Boussard etc. who dealt obsolete axioms blow after blow) with the concept of Recursion – new in Genome Theory, though recursion (“feedback”) is ubiquitous in science and technology. Further, once the DNA>RNA>PROTEIN>DNA… recursion is undeniable, the question becomes not if such recursion occurs – but to further specify, as the Principle paper did, that Genome Function is to be explained in a specific form of recursion; in terms of Fractal Iterative Recursion. Further, the recursion from Proteins to DNA, via epigenomic channels united Genomics with Epigenomics in terms of Informatics. Thus, IPGS became International HoloGenomics Society (2008), and I disseminated the above views widely through Google Tech Talk and Churchill Club YouTube-s in Silicon Valley. While in some remote provinces a "scientist"-loner, known to be the epitomy of intolerance, may still cling to the disarmingly naive notion that most of our DNA is Junk, to my knowledge there is nobody in Silicon Valley still stuck with the 20th Century.

Where are we now, two years after the Principle was disseminated as an accepted manuscript?

Independent dismissals of the Central Dogma/Junk DNA misnomers and the "horror vacui" in theory.

The most significant development is the study by Eric Lander (Lieberman-Lander-Dekker et al) to show on the cover article of Science, Oct. 9, 2009 (see lead story) that "Mr. President, the DNA is fractal" – as the 19 co-authors showed at the level of structural folding a 2m long DNA strand into the nucleus of a cell that is one millionth smaller in diameter (maximal density), with the two extremely crucial consequences that a) the folding, following the Hilbert curve is “knot free”, that is, its pervasive transcription is not blocked by glitches. Second, the 3-D Hilbert curve show the maximal density yet minimal functional distance of its sequence-regions, e.g. a section at the end is about equally neighbor with a section in the middle, or at 3/4th of the length of the strand. It is noteworthy (and duly quoted) that the concept by Lieberman-Lander-Dekker (et al, 2009) originated from Alexander Grosberg (1993, pictured fifth from left, look in the top row), and reaches back to Mandelbrot’s fractal approach (1983), preceded by Hilbert (1891). Literature of fractal mathematics is well established and vibrant.

This DNA fractality is established from a quite different and independent viewpoint as FractoGene, that was deduced from the fractal model of the Purkinje brain cell (Pellionisz, 1989), that grows governed by the fractal DNA (the DNA sequence-fractality evidence was presented at Cold Spring Harbor, September 14 at the “Personal Genomes” meeting, 2009).

The apparent DNA fractality, most interestingly but not without some intrinsic incongruency, is also approached by one of the strongest Pioneers dismantling both the Central Dogma and JunkDNA misnomers, the school of Dr. Mattick (2009).

In the issue of “Natural Genetic Engineering and Natural Genome Editing” of the New York Academy, Dr. Mattick, in a paper authored alone, “deconstructs” the Central Dogma and JunkDNA misnomers, and argues against the feasibility that the theory underlying genome function might be “combinatorial geometry”:

Abstract

Since the birth of molecular biology it has been generally assumed that most genetic information is transacted by proteins, and that RNA plays an intermediary role. This led to the subsidiary assumption that the vast tracts of noncoding sequences in the genomes of higher organisms are largely nonfunctional, despite the fact that they are transcribed. These assumptions have since become articles of faith, but they are not necessarily correct. I propose an alternative evolutionary history whereby developmental and cognitive complexity has arisen by constructing sophisticated RNA-based regulatory networks that interact with generic effector complexes to control gene expression patterns and the epigenetic trajectories of differentiation and development. Environmental information can also be conveyed into this regulatory system via RNA editing, especially in the brain. Moreover, the observations that RNA-directed epigenetic changes can be inherited raises the intriguing question: has evolution learnt how to learn?

Excerpts (Mattick, 2009)

The central dogma “DNA makes RNA makes protein” … This has been a recurring problem in the history of science, wherein initially reasonable but unproven generalizations become entrenched and are then resistant to questioning and even harder to overturn. In molecular biology, belief in the proposition that genes are generally synonymous with proteins has created an entire intellectual edifice based on uncritical acceptance of comfortable assertions about the nature of genetic information and the functioning of the system, especially with regard to gene regulation. It has also fostered (as orthodoxies always do) an indifferent and sometimes dismissive response to observations that have the capacity to challenge the status quo, as well as resistance to alternative explanations that may be equally if not more cogent. The latter are all too frequently met with an unfair burden of proof, rather than receptivity and curiosity from open and enquiring minds. Indeed while objective skepticism should be equally applied to orthodox and novel ideas, especially in the face of surprising new facts, it is not. At this point it is necessary to refer to the widely accepted concept of “combinatorial control” by regulatory factors, which has been invoked to explain the “progressively more elaborate regulation of gene expression” that must occur in the more complex eukaryotes on the argument that “given the combinatorial nature of transcription regulation, even a twofold increase in the number of factors could produce a dramatic expansion in regulatory complexity”... Implicit within this claim is that this presumed combinatorial explosion of regulatory potential far exceeds that required to account for the difference between nematodes and humans.However, this is simply an assumption that has not been rigorously assessed mathematically, physically, or mechanistically, although it is superficially consistent with some co-fractionation data and the fact that gene expression can be influenced by many factors. The belief in the power of combinatorial expansion of proteomic and regulatory capacity has also been reinforced by the fact that alternative splicing can expand the proteome enormously, and the expectation that this expansion is greater in humans than in nematodes. This data also shows that combinatorial control of gene expression, at least as it is commonly conceived to operate, cannot be used to relieve the accelerating regulatory problem, at least in prokaryotes, as the relationship between numbers of regulators and genes would scale totally differently (with an exponent much less than 1). This leads to a reappraisal of what is meant (and superficially reported) as “combinatorial control,” in terms of an expansion in the levels of controls that are, as far as one can tell, binary in nature and which is entirely consistent with a body of evidence from decision theory which has not been hitherto considered. Rather it seems that the eukaryotes have expanded their regulatory options by the introduction of a hierarchical cascade of decisions, frommodification of chromatin at various levels (DNA methylation and various types of histone modifications) to the regulation of transcription, splicing, translation, RNA stability, and RNA modification and editing. Modulation of any of the regulatory factors involved will affect the outcome and can be interpreted as combinatorial control, but in reality are likely to operate at different levels within a decisional I suggest that the current protein-centric conception of molecular biology is primitive, and that the eukaryotic genome may be better viewed as an RNA machine,131 rather than simply a suite of protein-coding genes with cisacting regulatory protein binding sites. Indeed, apart from the fact that some genes encode proteins, it seems that the true situation may be completely the opposite to that assumed in ignorance of the increasingly dominant role that advanced regulatory systems play in the evolution and development of complex organisms. Finally, the phenomenon of paramutation, 178–181 by which RNA-directed epigenetic changes, including potentially those altered by RNA editing, can be inherited both mitotically and meiotically, and the existence of various classes of RNA-templated DNA synthetic and repair enzymes,175,182,183 raises the intriguing question: has evolution learnt howto learn?

Comment by AJP on the above paper might summarize that the approach by Mattick (2009) corroborates the “Principle of Recursive Genome Function” - by removing both Central Dogma and JunkDNA “show-stoppers” – but leaves the reader with the conclusion that “combinatorial control” as an underlying theory of genome function “can not be used”. Further, in any DNA-RNA-PROTEIN-DNA… recursive system the question if the genome is an “RNA machine”, “DNA machine” or “Protein machine” reminds one of the “which was first, the chicken or the egg”, as in a recursion each component plays an equally indispensable role.

Significantly, in the same issue of Natural Genetic Engineering and Natural Genome Editing (2009) Dr. James A. Shapiro also poublished a paper “Revisiting the Central Dogma in the 21st Century”, in which not only the “Central Dogma” is shredded once again, but “Lesson 2.” of Shapiro leaves the readers in the void where even the definition of “gene” vanishes: “Classical atomistic concepts of genome organization are no longer tenable. We cannot any more define a ‘gene’ as a unitary component of the genome or specify a “gene product” as the unique result of expressing a particular region of the genome”. In a separate Chapter Shapiro lays down “What New Informatic Concepts do We Need to Elaborate in a 21st-Century View of the Genome and Evolution”? – but Dr. Shapiro, though recognizes “the algorithmic nature of genome expression and genome restructuring in evolution” neither offers (an algorithmic) genome theory, nor does he reference one that was published already at the time of his essay.

In science, however, “the horror vacui” rules – i.e. phenomena without scientific explanation cry for any explanation.

Mattick’ solo manuscript has recently been followed up by Mattick, Taft and Faulkner (2009) “A global view of genomic information – moving beyond the gene and the master regulator”. “Central Dogma”, “Junk DNA”, “turning genes on and off” misnomers are completely gone (never even mentioned), and even the “master regulator” is mentioned in the context of the title (that we have to move beyond):

“such proteins [e.g. Hox-protein, AJP] are only parts of larger networks that influence muscle or hindbrain development in vivo, respectively … and do not fully explain the diversity and fine structure of organs and tissues. Similarly, chromatin-modifying proteins have a profound impact on developmental processes … because they lie at the functional centre of epigenetic regulatory networks, not because they themselves make locus-specific regulatory decisions but because they act on other information that does”.

Apparently, the concept of underlying of “combinatoric” regulation (a term used twice in the paper) seems to be adopted from Geoffrey J. Faulkner who at least since 2006 advocated a “combinatorial output from the genome”. Such an approach may have roots in “Combinatorial Chemistry” which, in turn has the underlying mathematics of “Combinatorial Geometry”.

Therefore, since the above papers all (independently) dispose obsolete notions of “Central Dogma”, “Junk DNA”, classicial definitions of “genes”, “introns”, dispose of “master regulators” and “turning genes on and off” it is possible that the approaches are convergent to the structuro-functional view of Fractal Recursive Iteration of Genome Function. However, the “Combinatorial Geometry” approach (e.g. via the arduous detour to fractals by way of "Fractal Combinatorial Geometry", instead of the fractal approach by Mandelbrot, see also SuperFractals by Barnsley) will have to cope with some of the thorniest mathematical challenges that even perhaps the greatest mathematician of modern times (Paul Erdos) could not resolve (see 70 hits on "Erdos problem" "Combinatorial Geometry", and the book of "Unsolved Problems in Geometry").

Genome Theory development (not entirely unlike development of Quantum Theory when the axiomatically un-splitable atom split) therefore, has a long road ahead. The upcoming new Decade will show a spectacular development in our understanding of Genome Regulation - and thus control of dreadful hereditary diseases, such that the new philosophy will prevail that "Your Genome is NOT Your Destiny".

The Genome Generation - The case for having your genes sequenced

By George M. Church | Newsweek Web Exclusive
Dec 15, 2009

The genomic revolution started in 1964, when Robert Holley and his colleagues at Cornell and the U.S. Department of Agriculture deciphered the first gene sequence, indirectly "reading" the order of the four bases (adenine, thymine, cytosine, guanine) that pair up to make all genes, thereby allowing us to understand the blueprint from which each human is built. At first, the process was slow and costly (77 bases required four researchers and three years), and the prospect of ever figuring out the sequence of every human gene—the 3 billion bases of the human genome—seemed remote. However, aided by robotics, several teams raced to complete the job in the 1990s. By 2003, at a cost of $3 billion, most of one human genome had been sequenced.

The success of the Human Genome Project led people to speculate that someday every person would have his or her genome sequenced. At a cost of billions per genome, of course, it was an impossible dream. But beginning in 2004, a wave of next-generation sequencing technologies emerged, and costs began to drop 10-fold each year. Today we can sequence a million individuals' genomes for what it would have cost to sequence one person's genome five years ago. At a current cost of $5,000, it's become so inexpensive that some business models project that personal genome sequencing could be provided to individuals for free by third parties (insurers, employers, governments) who might be able to use the information from the sequencing as a way to reduce health-care costs. No matter who pays for it, as technology improves, the cost will continue to go down, likely to $100 per genome, and lower.

The benefits of genome mapping for some individuals are clear. Nearly every newborn today is screened for up to 40 genetic disorders—that's more than 4 million babies per year in the U.S. (although few of these tests sequence DNA). Before genetics, for example, a baby born with two damaged PKU genes would become mentally retarded. Now, babies that screen positive for this condition go on special protective diets. Carefully reading the genome has saved thousands from this and other painful conditions.

Over 1,500 disease-related genes have been discovered, knowledge that has improved medical diagnosis, treatment, and prognosis. Among the genes routinely sequenced in adults are the BRCA1-2 and neu/HER2 genes for breast cancer, multiple genes for colorectal cancer, the LQT1-12 genes for cardiac arrhythmias, and genes that cause a person to form blood clots more easily (like the factor V Leiden and prothrombin genes).

The message is not "Here's your destiny. Get used to it!" Instead, it's "Here's your destiny, and you can do something about it!" Diseases result from a combination of genetic vulnerability and lifestyle. If you know you have high risk of certain diseases, it's in your interest to know and practice the lifestyle that reduces your risk—and the younger, the better.

Personal genomics also helps doctors choose treatments, by identifying genes that make some medication options clearly superior to others. While "pharmacogenomics" is in its infancy, it is already helping many patients. Genetic tests are used to determine whether certain drugs are prescribed, and in what dose, for HIV-AIDS (the drug abacavir), psychosis (clozapine), blood thinning (warfarin), the heart condition called long QT syndrome (beta blockers) and cancer (imatinib, irinotecan, 5-fluorouracil, mercaptopurine, or tamoxifen). Recently, a gene variant has been identified that powerfully reduces the effectiveness of the popular anticlotting drug, clopidogrel. For the roughly 30 percent of people who carry the gene variant, higher doses of the drug are required: prescribing usual doses exposes the patients to serious, even life-threatening risks.

As low-cost genomics revolutionizes biological research, it promises significant public benefits. When the personal genomes and medical histories from much larger numbers of people become available, we expect much greater progress in identifying rare genetic variations that cause common diseases like cancer and heart disease. A growing number of people are volunteering to help this effort through programs such as PatientsLikeMe, The Personal Genomes Project, and regional biobanks. By sharing their medical histories and genetic information they hope to speed the search for cures and preventatives. These altruists deserve our support.

A common concern about new technologies is that they can broaden the gap between rich and poor. Genomics is no exception, but there is reason to believe that the poor could benefit from advances in the field. Infectious diseases are rampant in the Third World, and are a powerful barrier to people raising their standard of living and getting an education. Low-cost genomics enables the monitoring of new and old disease-causing microbes and the spread of drug resistance. This in turn permits deployment of optimal treatments.

It's a good thing to make genomes available to researchers, but potential problems exist as well. There is no more personal information than the sequences of your genes. Protecting the privacy of that data is essential to the future of genomics. If companies, health-care providers and governments collect and store our genomes and medical data, can they profit by controlling access to our genomes or cells? Do we have the time or know-how to control such access personally? If one's personal genome were known to insurers or employers, it could lead to discrimination. To address this, the Genetic Information Nondiscrimination Act of 2008 (GINA) prohibits health plans and health insurers from charging higher premiums, or making hiring or promotion decisions, based solely on individuals' genetic information. (GINA does not cover long-term care or life insurance, because of the concern that the people who purchased such insurance would be those who had learned from genetic studies that they were at risk for major diseases.)

As "the first genomic generation" we will set the rules that many future generations may follow. Will we treat our genomes like our faces, which we share publicly even though they reveal details about our health, ancestry, and personality? Or will we be forced to hide them from view? Knowing our DNA could make us think of ourselves more mechanically, and yet increase our humanity by embracing our diversity. It could render us less mysterious, yet more awe-inspiring. Our genomes are a vast future resource. How we handle them will define us as a species—not as a fuzzy average, but with our individualism evident in detail.

Church ["the Edison of postmodern Genomics - AJP] is professor of genetics at Harvard Medical School. He has advised 15 of the 20 companies developing rapid genome sequencing technologies and five DNA diagnostics companies.

Dyson Sees Opportunities in Personalization

Published: 13 Dec 2009 18:24:03 PST

Forbes: How do you think the health care sector is doing? How do you think the sector will do through year-end?

Esther Dyson: I don't actually follow public stocks, but I think there are huge opportunities in companies that offer services for individuals (sometimes via doctors or institutions, and sometimes directly). With computers and all kinds of diagnostic developments, it's now possible to collect a lot of data about each individual and to generate a lot of personalized analysis and advice. Turning that into personalized services is a huge opportunity. Some of the companies I have invested in include 23andMe (personal genome information) and Keas (personal health-and-wellness plans). I'm looking at similar start-ups in immunology and metabolism. I'm also an investor in PatientsLikeMe, which lets people with specific diseases (ALS, Parkinson's, et cetera) share their own personal information with one another--and with pharmaceutical companies, who pay for the privilege; ReliefInsite, an online service that lets users monitor their pain and share the data with care-givers; HealthWorldWeb, a platform for selecting doctors; Organized Wisdom, which delivers medical information in a form comprehensible to normal people; and Voxiva, a mobile (phone) health platform that you'll be hearing more about in January.

You've been part of several start-ups. How can you tell which company will be successful and which won't be?

No one can do that perfectly, and I don't pretend to. I try to pick ones in areas that I want to learn more about, so that even if I don't make money I will at least get an education. Obviously, I try to pick intelligent, dedicated people with great ideas; so does everyone! But mostly I invest in companies doing things that I would like to see done. Since I am short of both money and time, I know I'll have to miss lots of opportunities, so I try to pick only things that wouldn't happen (or wouldn't happen as quickly).

I pick things that interest me. But then I try to "sell" the sector to other people. I think health care is a huge opportunity--precisely because most people think it is a huge problem. But where I see the biggest opportunity is "outside" the health care establishment, helping people to stay healthy so they need less health care in the first place.

You mentioned on your Web site that you've been to some emerging markets and are interested in them. How do you advise retail investors to invest in those markets, if at all?

First of all, as in most markets, the insiders usually do better than the outsiders. So I think retail investors should mostly be very careful unless they take specific advice from someone very knowledgeable.

Personally, I have become something of an insider in the Russian IT market--but certainly not in Russian business overall. I am an active investor in several Russian IT companies, starting with Yandex, the Russian analogue of Google ( GOOG - news - people ), which has over 50% market share compared with Google's 20% share in Russia. I'm also involved with IBS Group, a leading IT services company that owns Luxoft, an outsourcer; TerraLink, a specialty IT outsourcer; Live Journal, the blogging platform that has about 90% of the Russian market; and UCMS, which is "white" rather than "green": It sells legal payroll services and helps companies who may not understand all the regulations even if they want to follow them. And I'm an investor in yet another outsourcer, Epam, via a Hungarian company they acquired, but I am not active there because it competes to some extent with Luxoft.

I am a big fan of India and its still-messy democracy, which is rapidly opening up. I'm also optimistic about China, but I don't know enough to be an active investor there.

How are your start-ups in the air and space areas going? What kind of opportunities do you see there?

The air market right now is a mess and I am staying out of it. It simply requires too much capital to be of interest to an angel investor--other than Coastal Aviation Technology, which sells schedule and route optimization software. Someday the whole general aviation market has to get more efficient, but that may take awhile.

As for space, I'm quite optimistic. But it's still not a fluid market; it's mostly a collection of billionaire-funded projects. I'm looking forward to that changing. Meanwhile, I am an enthusiastic investor in Space Adventures, where I am also a customer--for a six-month stint training as a backup cosmonaut in Russia's Star City from October of last year to March of this year. And I am an investor in XCOR Aerospace, which makes rockets and will be offering suborbital space flight soon, and in Icon Aircraft, which has a light-sport aircraft that every red-blooded extreme sports enthusiast will want to fly.

How are your angel investments doing?

Well, I have more money than I started with! And I certainly know a lot more than I did back when I worked for Forbes as a fact-checker and then a reporter from 1974 to 1977. I have to say that the art of fact-checking--being skeptical and asking questions until you understand and can vouch for the answers--is great training for being an investor!

Australia boots up GPU supercomputer [NVIDIA Tesla cluster for genomics - AJP]

Hardware
By Aharon Etengoff
Wednesday, 09 December 2009 15:58

Tesla for Genomics YouTube [AJP]

Australia's national science agency has fired up a massive GPU supercomputer capable of delivering 256 Teraflops of peak performance.

The CSIRO supercomputer - which is powered by 64 Nvidia Tesla S1070 GPUs - includes 28 Dual Xeon E5462 compute nodes (or 1024 2.8GHz compute cores), 500 GB of SATA storage, a 144 port DDR InfiniBand Switch and an 80 Terabyte Hitachi NAS file system. According to Nvidia spokesperson Andrew Humber, CSIRO scientists have already reported "speedups" of 10-100X in their research applications by deploying the GPU-based system.

The new Tesla GPU cluster will be used to accelerate a number of projects, including genome research, the reconstruction of 3D medical images and modeling ocean nutrients.

Nvidia teams up with Microsoft for HPC

Hardware
By Andrew Thomas
Monday, 28 September 2009 04:50

Nvidia is to work with Microsoft to use its Tesla GPUs for high performance parallel computing using the Windows HPC Server 2008 operating system.

Nvidia says it has developed several GPU-enabled applications for Windows HPC Server 2008, including a ray tracing application that can be used for advanced photo-realistic modeling of automobiles. The company is also working with Microsoft to install a large Tesla GPU computing cluster and is investigating applications that can be optimized for the GPU.

The two companies say they are looking at applications such as data mining, machine learning and business intelligence, as well as scientific applications like molecular dynamics, financial computing and seismic processing which can take advantage of the massively parallel CUDA architecture on which Nvidia's GPUs are based.

"The coupling of GPUs and CPUs illustrates the enormous power and opportunity of multicore co-processing," said Dan Reed, corporate vice president of Extreme Computing at Microsoft.

"Nvidia's work with Microsoft and the Windows HPC Server platform is helping enable scientists and researchers in many fields achieve supercomputer performance on diverse applications."

"The combination of GPUs and the Windows platform has been a great benefit to our VMD (Visual Molecular Dynamics) user community, bringing advanced molecular visualization and analysis capabilities to thousands of users," said John Stone, senior research programmer at the University of Illinois Urbana-Champaign.

"As we move toward even larger biomolecular structures, GPUs will become increasingly important as they bring even more computational power to bear on what will be highly parallelizable computational problems."

"The scientific community was one of the first to realize the potential of the GPU to transform its work, observing speedups ranging from 20 to 200 times while using a range of compute-intensive applications," said Andy Keane, general manager of Nvidia's Tesla business.

"Researchers are increasingly using Windows on workstations and in data centers due to strong development tools like Microsoft Visual Studio, its ease of system management and its lower total cost of ownership."

back_to_top

Singapore team completes genetic map of Han Chinese

By Judith Tan
Fri. Dec. 11
Straits Times, Singapore

RESEARCHERS in Singapore have unveiled the first genetic map of the Han or southern Chinese, the largest ethnic population in the world.

The study, conducted at the Genome Institute of Singapore (GIS), drew from 8,200 DNA samples from ethnically Han Chinese all over China and in Singapore.

Associate Professor Liu Jianjun, who led the human genetics group, said the genome mapping provides a start to solving mysteries such as why more than 95 per cent of Chinese are lactose intolerant and cannot take dairy products.

It also helps identify genes that make some Chinese more susceptible to diseases such as diabetes and nasopharyngeal cancer and tailor treatment or prevention for them, he said.

Prof Liu said the map was able to show that the people of northern China were genetically different from those in the south - 'a finding that reflected and was very consistent with the migration pattern of the Han Chinese'.

'We could also use it to arrive at a person's ancestral origin, including those born and raised in foreign countries.'

Using Singapore as an example, Prof Liu said that the ancestral roots of ethnic Chinese born and bred here could be traced back to China.

'By looking at the genome-wide DNA variation, we can determine whether an anonymous Singaporean is a Chinese, his ancestral origin, and sometimes, which dialect group of the Han Chinese he belongs to,' he said.

While a majority of the Han Chinese in Singapore are from the Cantonese and Teochew dialect groups, Prof Liu said a third group - the Hakkas - also have 'residual DNAs' that showed they could be from north China, he said.

'More importantly, our study provides information for a better design of genetic studies in the search for genes that make Han Chinese susceptible to diseases such as nasopharyngeal cancer and diabetes,' Prof Liu added.

GIS executive director Edison Liu said that while genome studies have provided significant insights into genes involved in common disorders such as diabetes, high cholesterol, allergies and neurological disorders, 'most of this work has been done on Caucasian populations'.

'Prof Liu's work with his Chinese counterparts helped define the genetic causes of some of these diseases in Asians,' he said.

The research, published in the American Journal of Human Genetics last month, is part of a larger ongoing project on the genome-wide association study of diseases among the Chinese population.

The project is a collaboration between GIS and several institutions and universities in China.

As a follow-up, Prof Liu's team is currently studying the incidence of nose cancer among the southern Chinese and will be publishing the results soon.

Genome Patri - [First Indian Genome Sequenced]

10 December 2009, 12:00am IST

It took the US Human Genome Project more than a decade and $500 million to sequence genes drawn from several volunteers. A team of Indian scientists at the Institute of Genomics and Integrative Biology of the Council for Scientific and Industrial Research (CSIR) has reported mapping of the entire genome of a 52-year-old Indian male in just 10 months, at a cost of $30,000 or Rs 13.5 lakh. With this achievement, India joins the ranks of the few countries - the US, UK, Canada, China and South Korea - which have successfully sequenced the human genome. [It is interesting why and how almost the entire coverage overlooked that The Netherlands sequenced the first ever female human - thus the "club" is now at 7 - AJP] Earlier, CSIR scientists had mapped the genetic diversity of the Indian population and also completed sequencing the genome of the zebra fish, commonly used in laboratories as a model for researching human diseases.

There are greater chances of arriving at a better understanding of the genetic make-up and peculiarities of local populations with countries creating their own DNA sequences, as such knowledge is crucial in comprehending country-specific health trends and genetic traits that would otherwise remain largely a mystery. This will enrich knowledge of the different genetic variations that occur in different population groups as well as enable the identification of genes that predispose some to certain diseases.

The male, whose genome was decoded by CSIR scientists, is predisposed to heart disease and cancer, and this information has been gleaned from the sequencing of his DNA. Therefore, the technology is invaluable in diagnostics and could be useful in medical treatment as well. Drugs designed to target the affected genes could be formulated, though at present to do so would involve high costs and such an option would be out of reach of the average patient. However, as with all sci-tech breakthroughs, costs are bound to come down - as it has in the case of the genome mapping technology and various computer models - and it is only a matter of time before they become affordable.

Law and ethical resolutions tend to lag behind implementation of scientific and technological advances, and the relatively new field of DNA sequencing is no exception. What if an individual's genome patri were accessible to employers and insurance companies who might use the information against the employee or client? Should an individual choose to reveal details of his genetic 'horoscope' to his family and friends or keep it private? Would the knowledge impact the individual's own perspective of life and how he lives it? There's plenty of fodder for debate, especially since predisposition to a disease does not mean it would actually manifest in the person.

PricewaterhouseCoopers Projects 11 Percent Annual Growth in Genomically Guided Personalized Medicine

December 08, 2009
By a GenomeWeb staff reporter

NEW YORK (GenomeWeb News) – A new report by PricewaterhouseCoopers estimates the $232 billion personalized medicine market will grow 11 percent annually.

According to the professional services firm, the trend toward tailoring drugs based on clinical factors and genomic variation will create opportunities and challenges for the pharmaceutical and biotech industries. As far as the opportunities, however, the market for "a more personalized approach to health and wellness will grow to as much as $452 billion by 2015," PricewaterhouseCooper gauges.

The estimates in the report, titled "The Science of Personalized Medicine: Translating the Promise into Practice", factor in market opportunities beyond drugs and devices to included demand for data storage, data sharing, as well as increased consumer demand to know their own health risks.

Based on these considerations, PricewaterhouseCoopers expects the $24 billion drug and diagnostic market will grow by 10 percent annually, reaching $42 billion by 2015. "The personalized medical care portion of the market – including telemedicine, health information technology and disease management services offered by traditional health and technology companies – is estimated at $4 billion to $12 billion and could grow tenfold to over $100 billion by 2015 if telemedicine takes off," the report notes.

The report sees direct-to-consumer genomics firms, such as the services offered by 23andMe and Navigenics, adding to the growth of the personalized medicine market by empowering individuals with real-time information regarding medical risks.

"Market research analysts estimate the current size of the global market for genetic testing at $730 million, with a 20 percent annual growth rate. Though a relatively small portion of this market, DTC testing is expected to grow rapidly in response to consumer demands and declining prices," the report notes.

The economic downturn has hit many DTC genomics firms hard. 23andMe recently laid off some employees and raised the price of its genomic risk scans [see GenomeWeb Daily News sister publication PGx Reporter 11-04-2009]. Although many industry observers have often doubted whether the information offered by DTC gene testing firms is worth the price, other experts have recognized that the consumer-driven research model is one that empowers individuals and may catch on as people get more comfortable learning about genetic risk.

"Medical science and technological advancement have converged with the growing emphasis on health, wellness and prevention sweeping the country to push personalized medicine to a tipping point," said David Levy, global healthcare leader at PricewaterhouseCoopers, in a statement. "We are now seeing a blurring of the lines between traditional healthcare offerings and consumer-oriented wellness products and services. The market potential is enormous for any company that learns to leverage the science, target individuals and develop products and services that promote health."

One thing all healthcare stakeholders agree on is that the trend toward personalized medicine will be disruptive to the traditional way of doing things. Personalized medicine has certainly altered Big Pharma's traditional drug development model. And although drug companies are still eyeing the largest possible market for their drugs, most heads of research and development at large drug companies have unwittingly admitted that the blockbuster model is dying [see PGx Reporter 12-02-2009].

"We need to replace our current focus on treating disease with a better approach that is personalized, preventive, predictive and participatory, the basic tenants of personalized medicine," Gerald McDougall, principal in charge of personalized medicine and health sciences at PricewaterhouseCoopers, said in a statement. "Greater collaboration around personalized medicine should be a key strategy for health reform."

Within industry, 2009 was a year of Rx/Dx collaborations with several major drug firms including Pfizer, GSK, Bristol-Myers Squibb, Amgen, and AstraZeneca all inking collaborations with diagnostics firms to personalize investigational treatments, mainly for the individualization of cancer treatments using genomic markers.

In the regulatory arena, the US Food and Drug Administraiton updated the labels for the anticoagulant Plavix with gene-response data and affected a class labeling change for EGFR-inhibiting monoclonal antibodies in the treatment of colorectal cancer (ie. Erbitux and Vectibix).In updating the label for Erbitux and Vectibix the FDA considered retrospective clinical trial data from the sponsors, which offers alternative study models to the long and costly prospective, randomized-controlled study designs for companies looking to get develop personalized drugs [see PGx Reporter 10-07-2009].

The report also discusses how this projected growth in the personalized medicine market will impact technology companies. Tech firms "some with little or no health expertise, are capitalizing on emerging opportunities to manage vast quantities of genetic and other health data and build IT infrastructure and connectivity solutions," the report notes.

When it comes to genomically guided personalized care, physician education is mandatory, the report notes. "Universities will have to update their programs," it said.

"Primary care providers may have to build new service lines around prevention and wellness in order to replace revenues lost from traditional medical procedures," according to the report. "When they do, they can expect to face low-cost competition from non-healthcare companies skilled in consumer marketing and consumers armed with knowledge of their options."

Payors will also need change their reimbursement schemes. Insurance premiums are currently calculated with the general population in mind, but "personalized medicine targets small populations which are far less stable and predictable from an actuarial standpoint," the report notes.

"How payors approach personalized medicine will be critical, as their reimbursement schemes will influence the business models of pharma and diagnostics companies as well as providers who depend on third-party payment," according to the report. "Payors that want to embrace the new science will have to rethink how they define coverage."

Chromosomal Deletions Found in Severely Obese Kids

By Kristina Fiore, Staff Writer, MedPage Today
Published: December 07, 2009
Reviewed by Robert Jasmer, MD; Associate Clinical Professor of Medicine, University of California, San Francisco and
Dorothy Caputo, MA, RN, BC-ADM, CDE, Nurse Planner

[Obese kid from Dr. Farooqui' research - AJP]

Children who become severely obese at a young age may be missing a large segment of DNA, including genes that play a role in regulating hunger, researchers say.

Obese youngsters were twice as likely as controls to have large and rare deletions at 16p11.2, a region on chromosome 16 (P<0.001), Sadaf Farooqi, PhD, of the University of Cambridge, and colleagues reported in Nature.

Youngsters with this phenotype rapidly gained weight in the first years of life, and their excess weight was predominantly fat mass, the researchers wrote. They had hyperphagia, or an increased appetite, and their fasting plasma insulin levels were disproportionately elevated compared with controls.

"People with deletions involving this gene had a strong drive to eat and gained weight very easily," Dr. Farooqi said in a statement.

The study is the first to document rare copy number variants (CNVs) -- large chunks of DNA deleted from genes -- associated with severe early-onset obesity.

The rising prevalence of obesity is driven by environmental factors, but there is "considerable evidence" that weight is highly heritable, the researchers said.

So they studied 300 white patients whose severe obesity arose before age 10, and compared them with 7,366 controls. Of the 300 severely obese children, 143 also had developmental delay.

They searched each child's genome for mutations in copy number variants, which are believed to have a role in many diseases, including autism and learning disorders.

Generally, both cases and controls had a similar median number (53 and 55, respectively) of copy number variants, as well as similar sizes of the deletions (22 and 23.5 kilobases, respectively).

But rare deletions and large deletions -- those greater than 500 kilobases -- were significantly greater in patients compared with controls -- a two-fold increase, the researchers said (P<0.001) .

Obese children with developmental delay were also more likely to have large, rare deletions, they added.

Four patients with the 16p11.2 deletion reported in autism and mental retardation had mild developmental delay that required special educational support, and two also had autistic spectrum behavior.

The 16p11.2 deletions encompass several genes -- some that play a role in neurological diseases and immunity -- but all include SH2B1. This is known to be involved in leptin and insulin signaling, processes that regulate weight and adjust blood sugar levels.

The researchers added that since copy number variants exist in sections outside of SH2B1, there's a role for additional genes in the etiology of severe obesity.

Farooqi and colleagues concluded that studies looking for rare variants near susceptible genetic locations may prove fruitful in other common, complex diseases.

China to develop third-generation genome sequencing instrument

www.chinaview.cn 2009-12-05 15:10:23

BEIJING, Dec. 5 (Xinhua) -- The Chinese Academy of Sciences and Inspur Group have started a joint project to develop the third-generation genome sequencing instrument, which might slash the cost of genome sequencing by 99 percent.

The instrument is expected to sequence a person's genomes in an hour at a cost of about 1,000 U.S. dollars, compared with six weeks and 60,000-100,000 dollars by the current second-generation instrument, said Yu Jun, deputy head of the Beijing Institute of Genomics with the Chinese Academy of Sciences.

The academy and the Inspur Group, a leading supplier of computing platforms and IT application solutions in China, announced the project here on Friday, according to a report by Beijing Daily newspaper on Saturday.

"The home-made third-generation genome sequencing instrument is not only conducive to life science research, but also concerns the genetic safety of China," Yu said.

The sequencing instrument is vital for gene science research and the made-in-China third-generation instrument will help the country get a leading edge in the field, he added.

Complete Genomics And GATC Biotech Collaborate On Human Genome Sequencing Projects

December 2, 2009

Konstanz, Germany / b3c newswire / — GATC Biotech [Germany] and Complete Genomics, Inc., today announced the execution of a research collaboration agreement to sequence several human genomes from samples provided by GATC. The companies will collaborate to analyze the data obtained from the research project. Complete Genomics will sequence and assemble the genomes and provide GATC with detected variants including single nucleotide polymorphisms (SNPs) and indels. GATC will then perform additional bioinformatics analysis such as comparison of the variant data of different genomes. In addition, the company will refine the data with the aim of providing researchers and clinicians with relevant genomic details to advance their understanding of the genetic causes of disease. The pilot project has started and the first sequencing data will be evaluated by GATC soon.

"GATC aims to continually offer our customers the most innovative, efficient and integrated sequencing technologies and applications for their research projects. To achieve our 100-Human-Genome-Project goal, evaluating Complete Genomics' human genome sequencing technology is a logical step," explains Peter Pohl, CEO of GATC Biotech.

"We are pleased to be working with GATC Biotech on this project which will further demonstrate the value of our large-scale, high-quality, low-cost human genome sequencing service," said Dr. Clifford Reid, chairman, president, and CEO of Complete Genomics.

China: Nine nations in one?

[Socio-political-economical map - AJP]

Anyone who’s been trawling through the China-related web this week will surely have stumbled across the ‘Nine Nations of China’ map that surfaced on Atlantic Monthly. Patrick Chovanec, from Tsinghua University, posted his map amidst the inescapable excitement of Obama’s visit to China, reminding the US President that China is "a mosaic of several distinct regions, each with its own resources, dynamics, and historical character."

The regions Chovanec feels China could be divided into:

The Frontier, made up of Inner Mongolia, Ningxia, Gansu, Qinghai, Xinjiang and Tibet represented the mysterious desert-filled and mountainous bulk China’s land, inhabited by only 6% of its population.

South of that lies the Shangri-La region of Yunnan, Guizhou, Guangxi, a so-called paradise on earth consisting of kaleidoscopic forests, diverse ethnicities and, sadly, a front-door for illicit drugs, as it borders Burma’s Golden Triangle.

China's Back Door, meanwhile, holds on to Hong Kong, Macau, Guangdong, and Hainan for its lush jungles and economic successes

... whilst the neatly tucked-away Refuge on Sichuan, Chongqing remains an area with little investment but substantial brain drain.

The Crossroads, covering Anhui, Jiangxi, Hubei and Hunan, remain China’s transport and communications hub, neighbored by

The Straits of Fujian and Taiwan.

Up along the eastern coast is the likely Metropolis of Shanghai, Jiangsu, Zhejiang, followed by... The Yellow Land, or China’s political heart (Beijing, Tianjin, Shandong, Hebei, Henan, Shanxi, Shaanxi),

And finally, the elusive northeastern wilderness of Liaoning, Jilin, Heilongjiang. A.k.a. The Rust Belt.

As blogger Jeremiah Jenne pointed out, the idea is hardly earth shattering; not only due to the wonderful Wikipedia age of enlightenment, but also thanks to the efforts of an anthropologist by the name of Skinner, who produced a similar map in 1977, and whom Chovanec failed to cite. Jenne shows here just how similar the ‘Nine Nations’ and ‘Nine Subregions’ of China are. Danwei’s Jeremy Goldkorn and Shanghai Scrap’s Adam Minter also responded with a gentle reminder that Chovanec could have cited his predecessor. Chovanec responded later to note that the regional descriptions were his own and that he had cited Skinner, but the citations were edited out by The Atlantic under space considerations.

Attribution/citation grappling aside, both Chovanec and Jenne’s (and even Skinner's) basic argument is that we still tend to view China as one giant power, irrespective of the obvious diversities within its borders. However, Dan of China Law Blog, took a slightly different view:

"My problem I see with this map is that it is exactly that. A map. And as a map, it distinguishes among regions geographically and that is not how I view many aspects of China. Just by way of an example, I see Beijing having commonalities with Shanghai just because they are two powerful and relatively sophisticated big cities."

Which leads us to an interesting question - this One China can definitely be carved up into various divisions in order to understand it better, but what divisions could or should be in the final map?

First Chinese genetic map unveiled

It's a very significant day in science for China: the first genetic map of the Han Chinese has been published by the American Journal of Human Genetics. [See title with hyperlink and abstract below - AJP]. The study was conducted at the Genome Institue of Singapore, and draws from 8,200 DNA samples from ethnically Han Chinese all over China and in Singapore.

Through genetic variations, the map draws a historical picture of the migration of the Han from north to south. By assessing the 0.3% variations in genetic structure, scientists are able to conclude whether someone is ethnically Han, where their ancestral place of origin is, and can even tell what dialect group of Han they belong to, as genetic variation follows changes in dialect.

More importantly, the genetic map will help scientists to understand and how genes can make people more susceptible to disease, and will help to find medical methods to treat and prevent them. All things considered, a genome map for China is a great step forward for the country. It's also an interesting and novel way of looking at the "Nine Nations of China", but we admit it's not quite as entertaining a map as the ones Chinese people make for themselves.

Genetic Structure of the Han Chinese Population Revealed by Genome-wide SNP Variation
The American Journal of Human Genetics, 25 November 2009
doi:10.1016/j.ajhg.2009.10.016

Jieming Chen1, 12, Houfeng Zheng3, 4, 5, 12, Jin-Xin Bei6, 7, Liangdan Sun3, 4, 5, Wei-hua Jia6, 7, Tao Li8, 9, Furen Zhang10, Mark Seielstad1, 2, 11, Yi-Xin Zeng6, 7, Xuejun Zhang3, 4, 5 and Jianjun Liu1, 2, 3, 5, ,

1 Human Genetics, Genome Institute of Singapore, Singapore 138672, Singapore

2 Centre for Molecular Epidemiology, (Yong Loo Lin) School of Medicine, the National University of Singapore 117597, Singapore

3 Institute of Dermatology and Department of Dermatology at No.1 Hospital, Anhui Medical University, Hefei, Anhui 230032, P.R. China

4 Department of Dermatology and Venereology, Anhui Medical University, Hefei, Anhui 230032, P.R. China

5 The Key Laboratory of Gene Resource Utilization for Severe Diseases, Ministry of Education and Anhui Province, Hefei, 230032, P.R. China

6 State Key Laboratory of Oncology in Southern China, Guangzhou 510060, P.R. China

7 Department of Experimental Research, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R. China

8 The Department of Psychiatry & Psychiatric laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China

9 The Department of Psychological Medicine and Psychiatry, Institute of Psychiatry, King's College London, London SE5 8AF, UK

10 Shandong Provincial Institute of Dermatology and Venereology, Shandong Academy of Medical Science, Jinan, Shandong 250022, P.R. China

11 Department of Epidemiology, Harvard School of Public Health, Boston, MA 02115, USA

Abstract

Population stratification is a potential problem for genome-wide association studies (GWAS), confounding results and causing spurious associations. Hence, understanding how allele frequencies vary across geographic regions or among subpopulations is an important prelude to analyzing GWAS data. Using over 350,000 genome-wide autosomal SNPs in over 6000 Han Chinese samples from ten provinces of China, our study revealed a one-dimensional “north-south” population structure and a close correlation between geography and the genetic structure of the Han Chinese. The north-south population structure is consistent with the historical migration pattern of the Han Chinese population. Metropolitan cities in China were, however, more diffused “outliers,” probably because of the impact of modern migration of peoples. At a very local scale within the Guangdong province, we observed evidence of population structure among dialect groups, probably on account of endogamy within these dialects. Via simulation, we show that empirical levels of population structure observed across modern China can cause spurious associations in GWAS if not properly handled. In the Han Chinese, geographic matching is a good proxy for genetic matching, particularly in validation and candidate-gene studies in which population stratification cannot be directly accessed and accounted for because of the lack of genome-wide data, with the exception of the metropolitan cities, where geographical location is no longer a good indicator of ancestral origin. Our findings are important for designing GWAS in the Chinese population, an activity that is expected to intensify greatly in the near future.

Singapore achieves breakthrough in study of 3D Whole Genome Mapping [Structurally recursive DNA]
Singapore, Nov 5, 2009:

 [Recursive DNA - AJP]

A team of scientists at A*STAR’s Genome Institute of Singapore (GIS), led by Senior Group Leader and Associate Director of Genomic Technologies Dr Yijun Ruan and Senior Research Scientist Dr Edwin Cheung, has made a major technological breakthrough in the study of gene expression and regulation in the genome’s three-dimensional folding and looping state through the development of a novel technology called the ChIA-PET. Their results were published in the November 2009 issue of the prestigious journal, Nature under the title “An Oestrogen Receptor α-bound Human Chromatin Interactome”.

Ever since the human genome was found to be organized in a three-dimensional (3D) manner rather than in a two-dimensional linear [There is no such thing as a two-dimensional linear - AJP] fashion, scientists have been challenged to find an effective method to study the regulation of gene activity which took into account the complexities of its 3D structure. Using ChIA-PET technology, the GIS scientists have successfully met the challenge and confirmed the presence of genome-wide long-range chromatin interactions.

Using the oestrogen receptor-α (ERα) as a model, the scientists investigated how the human genome was organized in response to oestrogen signalling to control the expression of genes in breast cancer cells. They discovered that extensive ERα-bound long-range chromatin interactions in the human genome were involved as a primary mechanism for regulating estrogen-mediated gene expression.

First author of the research paper, Dr Melissa Fullwood, a PhD student when she worked on this study at the GIS, said, “Many studies have found that regions of the genome which are not near genes are very important in controlling disease. In thinking about how this can happen, many scientists hypothesized that chromatin interactions – 3-dimensional loops in DNA – might be what allow these regions to remotely talk to genes.

The subsequent discovery of chromatin interactions between specific genes and specific enhancer sites generated a lot of interest to find chromatin interactions throughout the entire genome. Our study is one of the first to be able to address this ‘Holy Grail' of genomics.”

Dr Fullwood was also one of three winners of the inaugural L’Oréal Singapore for Women in Science National Fellowship awards, presented in August 2009 for outstanding work by female researchers with the potential to contribute to science.

Prof Edison Liu, Executive Director of the GIS, said, “Our institute had been working to develop this technology to answer a fundamental question in cancer. These results show us that higher order DNA interactions on a genome scale can explain some of the contradictions in older studies. This work will pave the way for the development of highly specific anti-hormone treatments in breast cancer. “

Prof Edward Rubin, Director of the Genomics Division at the Lawrence Berkeley National Laboratory, University of California, Berkeley, Director of the U.S. Department of Energy Joint Genome Institute, and member of the GIS Scientific Advisory Board added, “The study represents a true scientific tour de force. It shows on a massive genome wide scale the interactions between a specific set of enhancers and the genes they regulate. The approach and results shown here will certainly be well received by the large community studying gene regulation.”

The ChIA-PET methodology and the ERα-bound human chromatin interaction map represent the starting point of an entirely new field for scientists to study how the human genome is folded in order to communicate the codes in regulating gene expression. ...

An oestrogen-receptor--bound human chromatin interactome

Nature 462(7269):58 (2009)

Melissa J Fullwood, Mei Hui Liu, You Fu Pan, Jun Liu, Han Xu, Yusoff Bin Mohamed, Yuriy L Orlov, Stoyan Velkov, Andrea Ho, Poh Huay Mei, Elaine G Y Chew, Phillips Yao Hui Huang, Willem-Jan Welboren, Yuyuan Han, Hong Sain Ooi, Pramila N Ariyaratne, Vinsensius B Vega, Yanquan Luo, Peck Yean Tan, Pei Ye Choy, K D Senali Abayratna Wansa, Bing Zhao, Kar Sian Lim, Shi Chi Leow, Jit Sin Yow, Roy Joseph, Haixia Li, Kartiki V Desai, Jane S Thomsen, Yew Kok Lee, R Krishna Murthy Karuturi, Thoreau Herve, Guillaume Bourque, Hendrik G Stunnenberg, Xiaoan Ruan, Valere Cacheux-Rataboul, Wing-Kin Sung, Edison T Liu, Chia-Lin Wei, Edwin Cheung and Yijun Ruan

Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672.

Genomes are organized into high-level three-dimensional structures, and DNA elements separated by long genomic distances can in principle interact functionally. Many transcription factors bind to regulatory DNA elements distant from gene promoters. Although distal binding sites have been shown to regulate transcription by long-range chromatin interactions at a few loci, chromatin interactions and their impact on transcription regulation have not been investigated in a genome-wide manner. Here we describe the development of a new strategy, chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) for the de novo detection of global chromatin interactions, with which we have comprehensively mapped the chromatin interaction network bound by oestrogen receptor (ER-) in the human genome. We found that most high-confidence remote ER--binding sites are anchored at gene promoters through long-range chromatin interactions, suggesting that ER- functions by extensive chromatin looping to bring genes together for coordinated transcriptional regulation. We propose that chromatin interactions constitute a primary mechanism for regulating transcription in mammalian genomes. DOI: 10.1038/nature08497

Knome Launches First Platform-Agnostic Human Genome Sequencing and Analysis Service for Researchers

- New service for scientists enables the next generation of genetic discovery -

CAMBRIDGE, Mass., Nov. 18 /PRNewswire/ -- Knome, Inc., a recognized pioneer in the personal genomics field, today announced the launch of KnomeDISCOVERY, the first fully integrated human genome sequencing and data processing service for researchers. The new offering meets rapidly emerging demand from biomedical researchers for a one-stop service that bundles affordable, research-tailored access to a broad range of next-generation sequencing platforms with discovery-supportive data management and analysis. KnomeDISCOVERY is expected to catalyze important genetic insights into rare and common human diseases, and to accelerate the development of effective treatments.

In 2007, only three complete human genomes were available for research. In 2010, by contrast, Knome expects to see the sequencing of thousands of genomes as government and private foundations invest hundreds of millions of dollars in grants to leverage the empirical power of individual genome sequencing.

As the cost of sequencing drops, and the tide of genome data rises, data management and analysis are emerging as pressure points that require significant computational infrastructure and expertise. Through KnomeDISCOVERY, individual research groups can leverage Knome's unparalleled sequencing platform access and experience in whole genome and exome analysis.

The new service is ideal for two types of researchers:

Researchers with expertise in medical genomics who want to streamline data management and preliminary analysis in forthcoming mass sequencing projects - Leveraging high-volume access to sequencing platforms, Knome handles the logistical hurdles of rapid-turnaround sequencing, and carries out the important but computationally intensive process of "background" genome analysis, freeing researchers to focus on specific question-driven hypothesis testing that can yield novel discoveries in genetic medicine; and

Clinically trained researchers with extensive expertise in specific diseases, for whom mass sequencing approaches are novel and unfamiliar tools - Knome's expertise in analyzing whole genome data can directly help these researchers pinpoint novel alleles that contribute to a disease of interest. Knome takes a "fine-toothed" approach to genomic data analysis, grounded in a thorough understanding of genome structure and function; protein biochemistry; population/evolutionary genetics; statistical analysis; and basic disease etiology, as refined by close consultation with the researcher. This approach can quickly identify potentially disease-relevant candidate alleles for researchers to consider for follow-up empirical assessment.

"This is a pivotal moment for genetic research, as the pace of novel genotype-phenotype discovery accelerates," said Jorge Conde, CEO of Knome. "Scientists understand the value of whole-genome and exome sequencing, but few have requisite access to the full complement of state-of-the-art sequencing machinery, data management systems and bioinformatics expertise. Having sequenced and analyzed the genomes of more individuals than any company in the world, Knome is now offering the research community a fast and cost-efficient way to move from DNA to discovery."

Knome works with researchers to create solutions tailored to their scientific aims, as well as their budget, timing and volume requirements. Pricing for KnomeDISCOVERY starts at less than $12,000 per sample, depending on desired sequence coverage and degree of custom consultation required, with turn-around in as little as eight weeks.

Knome's bioinformaticians use kGAP, the company's proprietary analysis platform, to deliver a thorough accounting of both novel and previously known sequence variants. Knome's analysis includes annotation of published allele-disease associations, as well as sophisticated prediction of potential functional effects of newly discovered variants, helping guide researchers to regions of the genome that are potentially relevant to a disease of interest.

"We are excited to bring the scientific research community the type of genome sequencing and data analysis services that have previously only been available to a small number of individuals at large institutions," said George Church, Professor of Genetics at Harvard Medical School and co-founder of Knome. "It is our hope that by making these types of services broadly accessible to many more scientists, the process of discovery will be greatly accelerated."

[In June, Boston-based Knome Inc. has teamed up with SeqWright, of Houston, Texas -AJP]

NSF Funds Petascale Algorithms for Genomic Relatedness Research

November 17, 2009
By a GenomeWeb staff reporter

[Fractal Frenzy taking off - self-assembly of a fractal hierarcy from bipeptide nanorods. - AJP]

NEW YORK (GenomeWeb News) – Scientists at three universities will use funding from the American Recovery and Reinvestment Act to develop computational biology tools that researchers will use with next-generation computers to study genomic evolution, according to Georgia Tech.

The $1 million grant from the National Science Foundation's PetaApps program, which funds development of computer technologies for petascale machines that can conduct trillions of calculations per second, will include Georgia Tech, the University of South Carolina, and Pennsylvania State University.

These researchers will develop new algorithms in an open-source software framework that will use parallel, petascale computing to study ancestral genomics in an open source code called Genome Rearrangements Analysis under Parsimony and other Phylogenetic Algorithms (GRAPPA).

"GRAPPA is currently the most accurate method for determining genome rearrangement, but it has only been applied to small genomes with simple events because of the limitation of the algorithms and the lack of computational power," explained David Bader, a lead investigator on the grant and executive director of high-performance computing at Georgia Tech's College of Computing.

GRAPPA was recently used to determine the evolutionary relation of a dozen bellflower genomes one billion times faster than a method that did not use parallel processing or optimization.

The researchers in this program will use it to test their algorithms by analyzing a collection of fruit fly genomes. They expect their algorithms will provide "a relatively simple system to understand the mechanisms that underlie gene order diversity, which can later be extended to more complex mammalian genomes, such as primates," according to Georgia Tech.

They think that the algorithms will make genome rearrangement analysis reliable and efficient.

"Ultimately this information can be used to identify microorganisms, develop better vaccines, and help researchers better understand the dynamics of microbial communities and biochemical pathways," Bader said.

How a medical revolution may transform Northern Virginia

By Steven Pearlstein
Wednesday, November 18, 2009

[Dietrich Stephan - a loss to Silicon Valley, but a gain to Northern Virginia - AJP]

Even as Washington policymakers struggle to reform the country's health-care system, about 20 miles away in Fairfax County, Dietrich Stephan is hatching a plot to revolutionize it.

The current system, as everyone knows, is the world's costliest machine for healing you when you get sick, largely by using drugs and devices and surgical procedures that have proven themselves effective with most other people with the same ailment. But what if there were a way, based on your genetic makeup, to anticipate whether you're likely to come down with cancer, heart disease or Alzheimer's and prevent it with a fix specially designed for you?

It's called personalized medicine. And while people have been anticipating it for a decade, ever since the humane genome was mapped out, it's been slow in coming. Now Stephan -- working with the Inova hospital juggernaut, the scientists at George Mason University, and the researchers and health policy experts at George Washington University -- thinks he can foment this health-care revolution and create a new economic engine for Northern Virginia.

Although it's been in the works for months, the official announcement came Monday when Gov. Tim Kaine, with his Republican successor looking on, announced that Virginia had come up with $25 million to finance operations at the new Ignite Institute. If its supervisors approve, Fairfax County will throw in $150 million in financing guarantees to construct a state-of-the-art, 300,000-square-foot research lab somewhere along the Route 28 corridor. At full strength, the institute will have an annual operating budget of $100 million and 400 employees working closely with a new Center for Personalized Medicine at Inova Fairfax Hospital, part of a $1 billion overhaul that Inova has planned for its flagship campus.

You'd be right, of course, to be a bit skeptical. For decades, we've heard how, thanks to the innovation gushing out of the National Institutes of Health and the Johns Hopkins medical complex, the fertile crescent between Rockville and Baltimore was destined to become the Silicon Valley of biotech. Watching that develop has been about as exciting as watching grass grow.

And just as Maryland has plenty of competition from other biotech clusters, Northern Virginia is the latest entry in the individualized-medicine sweepstakes, along with the Translational Genomics Research Institute (a.k.a. T-Gen) in Phoenix, where Stephan himself held the No. 2 position as director of research. Similar efforts are underway at the Institute for Systems Biology at the University of Washington, the Mayo Clinic and Duke University, along with the Broad Institute in Boston, which boasts not only the cachet and intellectual horsepower of Harvard and MIT but also a $400 million gift from Los Angeles real estate billionaire Eli Broad.

Closer to home, genome pioneer J. Craig Venter has his own genomic research empire, with headquarters in both Rockville and San Diego. And from the commercial sector, competition comes not only from every major drug and biotech company, but also from hot start-ups like Navigenics and 23andMe, which for a fee will tell you the diseases to which your genetic makeup is inclined.

Navigenics, in fact, was a spinoff of T-Gen, and Stephan was one of its co-founders. His experiences at both places, and at the genome labs of the National Institutes of Health, convinced him that the best place to launch this revolution is not a pure research lab, or a medical complex or a commercial start-up, but an entity that straddles the divide between nonprofit inquiry and for-profit commercialization and is driven by the everyday collaboration of researchers and clinicians.

Stephan considered locating his new venture in San Francisco or Boston, each of which had the necessary academic, medical and venture capital infrastructure. But in Northern Virginia he found a place where he would not be overshadowed by more-established players, and where he found public and private partners who, like himself, were ambitious and entrepreneurial and eager to break into the next big thing. If he, and they, have any competitive advantage, it is that the shift to individualized medicine will raise a myriad of questions about privacy, medical ethics and financing that will require difficult decisions from policymakers in Washington. Being close will give Stephan and his partners a front-row seat from which to participate in those conversations.

It's way too early to say whether the Ignite Institute will be able to attract superstar talent or big-time funding, or whether its partnerships with Inova and the universities will bear fruit, or whether through new company start-ups it will be able to generate lots of jobs, wealth and tax revenue for the region. But it says a lot about Virginia and Fairfax County that, even in the midst of economic downturn and budget shortfall, they saw the potential, seized the opportunity and invested in the future. Having also won funding for Metrorail's extension out to Dulles and won the headquarters competitions for Hilton, SAIC, CSC and Volkswagen of America, Northern Virginia is now primed to emerge from the economic doldrums and once again lead the region's growth.

Finding new ways to grow in Silicon Valley

By Rajeev Poduval SPECIAL TO THE WASHINGTON TIMES
Nov. 16, 2009

While established Silicon Valley companies weather the recession as best they can, newly emerging tech pioneers are showing the way back to economic growth.

Many of yesterday's moneymakers remain mired in hiring freezes and job losses. Two of the high-tech areas that lost jobs in 2008 — semiconductor and computer equipment manufacturing — have seen the pace of job losses intensify in recent months.

However, companies in fields such as biotechnology, nanotechnology and genomics are helping the tech industry in Silicon Valley find ways to flourish anew.

"The stock performance of major life science firms in the region is amazingly strong considering the overall market is down by 20 to 40 percent in the last 12 months," said Matthew Gardner, president and chief executive officer of BayBio, a nonprofit trade association serving the life-science industry in Northern California.

"We also see an enormous amount of investment coming into the industry, especially for the next generation of companies in genomics and related technologies," he said.

Mr. Gardner said these investments will inevitably translate into job growth.

BayBio estimates that the San Francisco Bay Area has the largest cluster of life-science firms in the world with more than 1,300 companies and 30 added every year, directly employing about 100,000 people. In the whole of California, there are about 1.4 million people employed in this sector directly and indirectly.

...Mike Williams, president and chief executive of West Valley Staffing Group, a high-tech staffing company that conducts its own quarterly surveys on hiring trends in Silicon Valley, said several of his clients are beginning to talk about hiring now.

"In the third quarter of 2009, there has been a moderate increment in recruitment needs, especially in computer and Internet-based technology," Mr. Williams said. "We look forward to the fourth quarter and project continued growth and uptick, especially in Silicon Valley. We get a good, optimistic feel from our clients that there is significant amount of pent-up demand in this sector," he said.

Among the fast-growing biotech firms are Gilead Sciences Inc., a research-based biopharmaceutical company; and Genentech Inc., a company that is considered the founder of biotech industry.

In genomics and the technology around it, firms moving forward despite the current economic meltdown include Complete Genomics, a firm focusing on complete human genome studies and genomic medicine; Pacific Biosciences Inc., a company involved in commercializing DNA sequencing technology and sequencing of individual genomes as part of routine medical care; and Fluidigm Corp., a firm dealing with molecular diagnostics, personalized medicine and wildlife conservation....

The current upswing in confidence reflects the fact that the emerging fields, — including biotechnology, scientific research and design, and internet-based technologies — are becoming established as sources of potentially lucrative jobs.

"The early part of 2009 was encouraging in terms of job growth in the Silicon Valley high-tech industry. Though there are some job losses in certain sectors since late spring this year, companies in biotechnology, scientific research and design, pharmaceutical research and Internet search tend to remain stable," said Mr. Mann.

...Among the high-tech giants avoiding large-scale job cuts is Intel Corp., the worlds largest semiconductor chip maker responsible for the rapid growth of the PC industry through its microprocessors in the '90s.

... Between 2001 and 2008, there was 32 percent job growth in the private sector pharmaceutical industry, and a 26 percent increase in jobs in biotechnology and other life sciences. The report indicates that despite the high cost of doing business here, the Silicon Valley region continues to be the epicenter of innovation and that the high-tech industry with its broadened scope remains the prime source of job growth in future, as well.

In Silicon Valley, the economic downturn has an upside, too. Robert I. Sutton, professor of management science and engineering at Stanford University and author of four books on management science and innovation, says the valley is rich with early-stage start-ups now because talent and real estate have become cheaper and these companies will be the engine of job creation, as in the past.

Why Can't Chimps Speak? Key Differences In How Human And Chimp Versions Of FOXP2 Gene Work

["Net Talk" - A network of genes governs the development of a Neural Net that produces speech - AJP]

ScienceDaily (Nov. 12, 2009) If humans are genetically related to chimps, why did our brains develop the innate ability for language and speech while theirs did not?

Scientists suspect that part of the answer to the mystery lies in a gene called FOXP2. When mutated, FOXP2 can disrupt speech and language in humans. Now, a UCLA/Emory study reveals major differences between how the human and chimp versions of FOXP2 work, perhaps explaining why language is unique to humans.

Published Nov. 11 in the online edition of the journal Nature, the findings provide insight into the evolution of the human brain and may point to possible drug targets for human disorders characterized by speech disruption, such as autism and schizophrenia.

"Earlier research suggests that the amino-acid composition of human FOXP2 changed rapidly around the same time that language emerged in modern humans," said Dr. Daniel Geschwind, Gordon and Virginia MacDonald Distinguished Chair in Human Genetics at the David Geffen School of Medicine at UCLA. "Ours is the first study to examine the effect of these amino-acid substitutions in FOXP2 in human cells.

"We showed that the human and chimp versions of FOXP2 not only look different but function differently too," said Geschwind, who is currently a visiting professor at the Institute of Psychiatry at King's College London. "Our findings may shed light on why human brains are born with the circuitry for speech and language and chimp brains are not."

FOXP2 switches other genes on and off. Geschwind's lab scoured the genome to determine which genes are targeted by human FOXP2. The team used a combination of human cells, human tissue and post-mortem brain tissue from chimps that died of natural causes.

The chimp brain dissections were performed in the laboratory of coauthor Todd Preuss, associate research professor of neuroscience at Emory University's Yerkes National Primate Research Center.

The scientists focused on gene expression -- the process by which a gene's DNA sequence is converted into cellular proteins.

To their surprise, the researchers discovered that the human and chimp forms of FOXP2 produce different effects on gene targets in the human cell lines.

"We found that a significant number of the newly identified targets are expressed differently in human and chimpanzee brains," Geschwind said. "This suggests that FOXP2 drives these genes to behave differently in the two species."

The research demonstrates that mutations believed to be important to FOXP2's evolution in humans change how the gene functions, resulting in different gene targets being switched on or off in human and chimp brains.

"Genetic changes between the human and chimp species hold the clues for how our brains developed their capacity for language," said first author Genevieve Konopka, a postdoctoral fellow in neurology at the David Geffen School of Medicine at UCLA. "By pinpointing the genes influenced by FOXP2, we have identified a new set of tools for studying how human speech could be regulated at the molecular level."

The discovery will provide insight into the evolution of humans' ability to learn through the use of higher cognitive skills, such as perception, intuition and reasoning.

"This study demonstrates how critical chimps and macaques are for studying humans," noted Preuss. "They open a window into understanding how we evolved into who we are today."

Because speech problems are common to both autism and schizophrenia, the new molecular pathways will also shed light on how these disorders disturb the brain's ability to process language.

The National Institute of Mental Health, the A.P. Giannini Foundation and the National Alliance for Research on Schizophrenia and Depression funded the study.

Back-up by Half a Century - Genome Regulation (1961) becomes parallel (2008)

Genomeweb - This week in Genome Biology
November 04, 2009

In Genome Biology this week, scientists at the Shanghai Institutes for Biological Sciences have studied how after gene duplication, [exonic] splicing enhancers and silencers can affect the generation of new splicing isoforms and therefore, new gene functions. Using a computational approach, they found that these enhancers and silencers diverge especially fast shortly after gene duplication and that this divergence "results in exon splicing state transitions, and that the proportion of paralogous exon pairs with different splicing states also increases over time, consistent with previous predictions." [The paper by Zhenguo Zhang (zhangzg_at_sibs.ac.cn), Li Zhou (zhouli_at_sibs.ac.cn), Ping Wang (pwang01_at_sibs.ac.cn), Yang Liu (yliu05_at_sibs.ac.cn), Xianfeng Chen (xfchen_at_sibs.ac.cn), Landian Hu (ldhu_at_srcb.ac.cn), Xiangyin Kong (xykong_at_sibs.ac.cn) concludes that the findings suggest that splicing requirement but not protein sequence mostly determines the changes of Exonic Splicing Enhancers and Exonic Splicing Suppressors.- AJP]

In other work, researchers at the RIKEN Yokohama Institute show that knocking down a swath of transcription factors in differentiating human THP-1 cells proves that they're interdependent. Using a matrix RNAi system to knock down the 78 transcription factor genes in monocytic THP-1 cells and then using qPCR to monitor gene expression changes, they identified 876 cases "where knockdown of one transcription factor significantly affected the expression of another." Using expression profiling data from the FANTOM4 study, they could classify these genes into three groups: pro-differentiative (229), anti-differentiative (76), or neither (571). [The paper by Yasuhiro Tomaru (tomaru_at_gsc.riken.jp), Christophe Simon (simon_at_gsc.riken.jp), Alistair RR Forrest (forrest_at_gsc.riken.jp), Hisashi Miura (hisabou_at_gsc.riken.jp), Atsutaka Kubosaki (kubosaki_at_gsc.riken.jp), Yoshihide Hayashizaki (yosihide_at_gsc.riken.jp), Masanori Suzuki (msuzuki_at_gsc.riken.jp) "identified 876 significant edges from 7488 possible combinations in the 78 x 96 matrix enabling us to draw a significant perturbation network. Out of these significant edges, 654 were activating edges and 222 were repressing ones". -AJP]

Case Western Reserve University's Thomas LaFramboise is senior author on work that reports a "highly sensitive and configurable method" for finding rare CNVs in SNP array data. In the paper, they applied their method to hundreds of samples and were able to not only detect known CNVs, but also previously unreported ones. [The paper states (with proper quotations): "studies have been published associating copy number variation in the genome with a variety of common diseases. Recent examples include Alzheimer disease, Crohn’s disease, autism, and schizophrenia". Noteworthy that the authors used the neural net algorithm of "Hidden Markov Model" - AJP]

In collaborative work between scientists at the University of California, San Diego, and Virginia Commonwealth University, scientists led by first author Tom Conrad found that when growing E. coli is subjected to lactate minimal media, the bacteria shows a range of genetic adaptations. Whole genome resequencing of 11 adapted strains found that in 7 of these there was an 82 base-pair deletion in the rph-pyrE operon. This mutation, they write in the abstract, "conferred ~15% increase to the growth rate when experimentally introduced to the wild-type background and resulted in a ~30% increase to growth rate when introduced to a background already harbouring two adaptive mutations." [The paper effectively elevated the "Operon regulation" to parallel systems; "genome sequencing of 11 endpoints of Escherichia coli that underwent 60-day laboratory adaptive evolution under growth rate selection pressure in lactate minimal media. Two to eight mutations were identified per endpoint. Generally, each endpoint acquired mutations to different genes. The most notable exception was an 82 base-pair deletion in the rph-pyrE operon that appeared in 7 of the 11 adapted strains." - AJP]

Getting Results Back
GenomeWeb
November 05, 2009

As part of Genomics Law Report's series, "What ELSI is New?", Daniel MacArthur considers the issue of whether researchers should return medically relevant, or even just interesting, results to study participants. He says that "in the absence of convincing evidence that disclosure of results causes harm, I would argue that the default position should be that research participants have complete access to their own genetic data if they request it." MacArthur says this is not only an ethical imperative but a move that could improve study recruitment and retention rates by providing a benefit to the participant.

Similarly, 23andMe's Anne Wojcicki says that she is "disappointed" that Kaiser Permanente will not be returning data to the 100,000 participants in its Research Program on Genes, Environment and Health, that will study genetic and environmental factors affecting common diseases. "Kaiser should afford the participants the respect they deserve by allowing them to decide for themselves whether they want to see their own genome," she writes at the Spittoon, expanding on her remarks at the TEDMED meeting.

As the Genomics Law Report points out, Kaiser Permanente's Cathy Schaefer responds at the Robert Wood Johnson Foundation Pioneering Ideas blog that all the participants know when they sign up for the study that their results won't be given back to them. "We also inform participants that if we discover something in their data or samples that may be important to their health, we will contact them to learn if they want to have the information," Schaefer adds. She says they aren't returning full results since the role of some variants in disease isn't fully known and that some results aren't actionable.

[There are two ways to resolve this obvious infringement of the "Freedom of Information Act". This researcher would not belabor the low road of litigation of fundamental rights of individuals to the information that is derived from their uttermost private property, their genomes. (This is not merely a matter of "respect" research participants deserve, but their right).

Rather, in full agreement with 23andMe, the "high road" of business aspects are emphasized here, that by Kaiser not returning full results actually MAKE the results "not actionable" (since one can not act on an information if it is not provided).

DTC companies have vital business reasons to return results (downloadable full raw SNP files) - though presently the percentage of downloads are very small. In the opinion of this researcher, the DTC business model will to a large extend depend upon the "actionability" of returned electronic files, for automation of "Preventive health care by customers". An already filed USPTO submission (patent pending) was flashed out in a Google Tech Talk YouTube a year ago, to utilize (even partial) personal profiles in a closed business model - viewed by ~6,500.

Complete Genomics cracks the door open to JunkDNA analysis in mass-production

Institute for Systems Biology to Work With Complete Genomics to Conduct Large-Scale Huntington`s Disease Study

Reuters, Mon Nov 2, 2009

Project to Sequence an Unprecedented 100 Human Genomes in Just Six Months

SEATTLE & MOUNTAIN VIEW, Calif.--(Business Wire)--

[Count a normal range of cag repeats in exon1 of the HD gene - AJP]

The Institute for Systems Biology (ISB) and Complete Genomics Inc. announced today that they are embarking on a large-scale human genome sequencing study of Huntington`s disease (HD). ISB has engaged Complete Genomics to sequence 100 genomes, the majority of which will be used to investigate this disease, with samples from affected individuals, family members, and matched controls to study modifiers of disease presentation and progression.

This will be the largest complete human genome disease association study conducted to date, and will be the first 100-genome study produced by Complete Genomics` newly expanded sequencing facility. The comparison of healthy and diseased complete human genome sequences will enable genomewide association studies with a focus on rare single nucleotide polymorphisms (SNPs), and insertions and deletions that are incompletely accessible with current genomewide SNP chip technologies. These will include rare variants in protein coding regions of the genome (the "exome") as well as in regulatory regions.

"It is when we start to look at genomics research on this scale that our sequencing technology really comes into its own and we have the potential to make truly revolutionary discoveries," said Dr. Clifford Reid, chairman, president and CEO of Complete Genomics. "I am delighted that we have the opportunity to partner with ISB in this effort to discover the genetic variants responsible for modulating the presentation and progress of Huntington`s disease."

ISB President Dr. Leroy Hood said, "We were pleased with the quality of the raw sequencing data and variations reports that Complete Genomics generated for our four-genome pilot project earlier this year. Its sequencing technology has the requisite accuracy, consistency and low price point to enable us to begin conducting this large-scale genomic study in this important patient population."

Huntington's disease is a devastating, hereditary, degenerative brain disorder for which there is, at present, no effective treatment or cure, according to the Huntington`s Disease Society of America. The Society adds that HD affects one out of every 10,000 Americans, slowly diminishing the affected individual`s ability to walk, think, talk and reason.

For this study, ISB will supply the purified DNA samples and Complete Genomics will sequence and identify variations for each genome. ISB will then do the genetic analysis at the sequence level.

By HEATHER CHAMBERS
Posted date: 11/2/2009
San Diego Business Journal Staff

Amid a glittering, eclectic gathering of technologists, futurists, media personalities, leading health care practitioners, business leaders and scientists, all mixed with a sprinkling of Hollywood stardust, the four-day TedMed conference was held last week at the Hotel del Coronado.

This assemblage of thinkers, inventors, communicators and implementers came together with the intention of harnessing the diverse knowledge of the event’s 50 speakers in search of new solutions to global health care challenges.

Organized by Richard Saul Wurman, who founded the TED conferences in 1984, the conference set not only a high standard for its speakers, but an equally high tariff for attendees, who paid $4,000 apiece to attend. Total attendance, including the speakers, was limited to 450 people.

Speakers included San Diego-based scientific pioneer J. Craig Venter, founder and president of Synthetic Genomics Inc., Dean Kamen, founder and president of DEKA Research and Development Corp., who holds more than 440 health care related patents, Dr. Sanjay Gupta, neurosurgeon and chief medical correspondent for CNN, Martha Stewart, who unveiled her new outpatient facility for geriatric care at Mount Sinai Medical Center in New York, Dr. Scott Parazynski, a veteran astronaut of seven spacewalks, Helena Foulkes, executive vice president and chief marketing officer of CVS Caremark, the largest pharmacy health care provider in the U.S., and Academy Award winning actress Goldie Hawn, who represented The Hawn Foundation, which she established in 2003 to help children reach their highest potential.

Transforming Delivery Of Health Care

Innovators from San Diego County were well represented with Qualcomm Inc. and Life Technologies Corp. showcasing inventions designed to transform the future delivery of health care, while cutting costs and reducing hospital stays.

With 4 billion cell phones, or three times the number of mobile devices than land lines in the world today, Qualcomm CEO Paul Jacobs said the timing couldn’t be better for introducing patients to new digital health tools.

“In the developing world, most people will only have a cell phone as their connection into the global telecommunications network,” he said.

While Jacobs said he doesn’t envision developing countries as a market for wireless, sensor-driven Band-Aids designed to monitor health, he said they still may benefit from digital medical cell phone technologies.

Dr. Eric Topol, a cardiologist and chief medical officer of the newly formed West Wireless Health Institute in San Diego, said the devices offer a “way to innovate out of the health care crisis today.”

With a wireless device attached to his chest, Topol demonstrated to the audience that he could monitor his blood pressure, pulse, temperature and other states of health using a discreet device placed under his shirt. [In a store where you make consumer choices "Ask NOT what the genome can do for you - ask what you can do for your genome" - by preferring items that fit or fix your genome - AJP]

With an estimated $37 billion a year spent on heart failure in the United States, Topol said constant monitoring could save on costs and readmittance rates, which run as high as 27 percent in heart failure patients.

What do they know that we don't know? - Celebs for Prevention

[Watson and Venter]

[Collins before and after]

[Sergey Brin and 23andMe Founder Anne Wojcicki]

The above are not all Nobel-winners, though Dr. Watson received the prize for work he did over half a Century ago. Two are definite candidates, and even a third might get a Peace Nobel award.

The fact is, however, that all of them induced demonstrable Genome-based Prevention, in some cases proven to be successful.

Though the first full human sequencing used five donors of DNA, for one of them (Craig Venter) the analysis compelled him to take "statins" (to control cholesterol), that he did not stop when full sequencing of the DNA of him and, separately, also Jim Watson's were fully sequenced and interpreted.

At the recent "Personal Genomes" 2nd Meeting in Cold Spring Harbor, a public question was addressed to Watson "did you specifically benefit from your full DNA analysis in your preventive health maintenance program?". He went public with at least two specific lessons, that he closely follows. His full DNA sequencing revealed - what he did not know before - that Dr. Watson is partially lactose-intolerant (the gene necessary to produce enzymes to metabolize lactose is intact in one chromosome - but is defective in the other chromosome of the pair). He was aware of some annoying cramps and belly aches throughout his life - but when he switched to the preventive health maintenance program, consuming lactose-free soy milk and other substitutes - now his cramps and belly aches are gone. (Could have saved 80 years of belly aches...). The other example he cared to go on public record was that he was taking a beta-blocker (to control his blood pressure), but his DNA information revealed that this drug personally affects him with an undue sleepiness. Doctors adjusted medication, and now this bothersome side-effect is gone.

Dr. Francis Collins (M.D., Ph.D., Head of NIH) has not had his full DNA sequenced (yet, to our knowledge). However, in the Consumer Genetics conference in Boston (May, 2009) he gave a speech, endorsing DTC genomic testing, backed by his example, that - using a pseudoname - he provided saliva-specimen to the leading 3 DTC companies (DeCodeMe, 23andMe, Navigenics), and made some very useful and largely supportive comparative analysis of their services. A couple of days ago, in Nature's blog 23andMe has 30,000 “active” genomes, launching “Relative Finder” soon
in a Personalized Medicine Colloquium, he disclosed the information and the above pair of his portraits with note: "Collins discovered that he carries two copies of the most common risk factor of type II diabetes. Collins, whose laboratory investigates the underlying genetic basis of adult-onset diabetes, said he was "surprised" by these findings since his family has no history of the disease. Upon learning the test results, Collins got off his Harley-Davidson and instigated a regular exercise regime. The svelter NIH director said he has now lost 20 pounds." With his vast knowledge and discipline, and given that late-onset Diabetes type 2 can be suppressed by diet, exercise and keeping body fat in tight control, his chances that he will never suffer from Diabetes are virtually certain.

The third "celeb" case is Google founder Sergey Brin (and his wife, Founder of 23andMe). As Sergey disclosed over a year ago in his blog, and now Anne Wojcicki talked publicly at TED, "Wojcicki said her husband recently found out that he was genetically predisposed to becoming a Parkinson’s patient thanks to a 23andMe’s analysis. Wojcicki said that just knowing about the increased likelihood has helped him to stay motivated to stay in shape, eat right and take better care of his health overall."

23andMe has 30,000 “active” genomes, launching “Relative Finder” soon

MobilHealthNews
Wednesday - October 28th, 2009 - 06:39pm EST by Brian Dolan | 23andme | Illumina | iPhone | medical apps | personal genetics | preventive medicine | TEDMED |

At the TEDMED event here in San Diego this week, personal genomics company 23andMe co-founder Anne Wojcicki announced that the company now had more than 30,000 “active” genomes in its database and that it would soon launch a “Relative Finder” service for its users.

As part of the new service, users can explore connections to other users of the site to determine how related they are to each other. 23andMe is offering free genotyping for TEDMED attendees, so Wojcicki joked that this time next year we can all find out how related we are to each other.

Wojcicki also announced that 23andMe now has more than 30,000 “active” genomes in its database right now — a figure the company has played close to the chest since its founding in 2006. About 70 percent of the site’s users have filled out at least one survey that 23andMe uses to enrich its own research. “In less than two years, we have created one of the world’s largest databases” for genomic databases in the world, Wojcicki said.

Another impressive metric that 23andMe mentioned at TEDMED: Since May of last year, in partnership with the Michael J. Fox Foundation, 23andMe has enrolled over 3.000 Parkinson’s patients within one month. In December, 23andMe plans to announce some of the results from analyzing those Parkinson’s patients’ genomes. Wojcicki noted that timeframe makes it one of the quickest turn arounds for a clinical study.

Wojcicki said her husband recently found out that he was genetically predisposed to becoming a Parkinson’s patient thanks to a 23andMe’s analysis. Wojcicki said that just knowing about the increased likelihood has helped him to stay motivated to stay in shape, eat right and take better care of his health overall.

[The world's largest genomic databank is impressive on its own right. Finding out who is a relative or a stranger will be automated. Should it not be also automated "how to eat right" with certain hereditary predilections? Less than a year ago it was flashed out in YouTube "Google Tech Talk" 34:43 ...

Full R&D and Market analysis of this "game changer" is upon request. Pellionisz; HolGenTech_at_gmail.com]

ParaHaplo: A program package for haplotype-based whole-genome association study using parallel computing

Kazuharu Misawa and Naoyuki Kamatani (RIKEN Center for Genomic Medicine, Tokyo, Japan)

Since more than one million of single nucleotide polymorphisms (SNPs) are analyzed in genome-wide association study (GWAS), multiple comparisons are problematic. To cope with multiple-comparison problems in GWAS, haplotype-based algorithms were developed to correct for the multiple comparisons at multiple SNP loci in linkage disequilibrium.

The permutation test can also control problems inherent in multiple testing; however, the calculation of exact probability and the execution of permutation tests are both time-consuming. Faster methods for calculating exact probabilities and executing permutation tests are required.

Methods: We developed a set of computer programs for the parallel computation of accurate P values in haplotype-based GWAS.

Our program, ParaHaplo, is targeted to workstation clusters using the Intel Message Passing Interface (MPI). We compared the performance of our algorithm with that of the regular permutation test on CHB and JPT of HapMap.

Results: ParaHaplo can detect smaller difference between two populations than SNP-based GWAS.

We also found that parallel-computing technique made ParaHaplo 100-fold faster than non-parallel version of the program.

Conclusion: ParaHaplo is a useful tool for haplotype-based GWAS. The executable binaries and program sources of ParaHaplo are available at http://sourceforge.jp/projects/parallelgwas/?_sl=

Credits/Source: Source Code for Biology and Medicine 2009, 4:7

Personal Genome Sequencing Identifies Mendelian Mutations

Bio-IT World
By Kevin Davies

October 22, 2009 | HONOLULU – The only downside of holding a major scientific conference in Hawaii is that, at some point, one has to step inside and attend a talk or two. But those among the more than 4600 registered attendees at the 2009 American Society of Human Genetics (ASHG) convention who ventured indoors were treated to some excellent talks on the opening day. In particular, two groups presented impressive results of next-generation sequencing studies that conclusively show how it is possible to identify previously unknown mutations responsible for Mendelian diseases.

James Lupski (Baylor College of Medicine) is an authority in the area of structural variants underlying genetic disorders (and has been for two decades). In the early 1990s, his team characterized the novel sub-chromosomal duplication that gave rise to a common form of peripheral neuropathy called Charcot-Marie-Tooth (CMT) disease. Since then, mutations in some 40 genes have been shown to give rise to CMT-like diseases. But none of them accounted for one particularly interested patient: Lupski himself.

Earlier this year, Richard Gibbs, director of the Baylor Genome Center, offered to sequence Lupksi’s entire genome in the hopes of finally identifying the mystery mutant gene. (Gibbs and Lupski were part of the team that interpreted the first personal genome delivered by next-gen sequencing, James Watson, in 2007.) Using the Life Technologies/Applied Biosystems SOLiD platform, Gibbs and colleagues sequenced Lupski’s DNA to 30-fold coverage.

Not surprisingly, the sequencing produced thousands of single-nucleotide polymorphisms (SNPs) considered putative disease-causing mutations. Gibbs applied a series of filters, removing SNPs already catalogued in the database (and thus considered too common to be the basis of a rare genetic disorder) as well as those found in HapMap samples. Lupski detailed how 6 SNPs in his genome were correlated with known behavioral disorders, 32 were cancer associated (Lupski is a cancer survivor), and 47 were implicated in common diseases.

In the end, Lupski and colleagues found different deleterious mutations in his two inherited copies of a gene called SH3TC2. The gene encodes a protein expressed in the membrane of Schwann cells that could have a role in the myelination of nerve fibers.

Miller Time

Recently, University of Washington geneticist Jay Shendure and colleagues published a report in Nature showing that exome sequencing of genes from patients with a known genetic disorder (Freeman-Sheldon Syndrome) could indeed separate the mutation signal from the noise of other variants. Exome sequencing has the advantage of sequencing just 1 percent of the DNA in the whole genome, but the analysis is limited to mutations that affect protein-coding regions.

Next, Shendure and colleagues set out to replicate their success with a Mendelian disorder where the root cause has not been found. The Shendure team used Agilent arrays to enrich the exome sequences and Illumina GA II for sequencing.

The investigators selected Miller Syndrome, a developmental disorder characterized by limb defects, first described by Marvin Miller and colleagues from the same university. Shendure’s team sequenced the exomes from four individuals with the disorder including a pair of siblings. When two filters were applied – removing variants observed in dbSNP and sequenced HapMap samples – the Shendure team was left with putative mutations in just one gene: DHODH (dehydroorotate dehydrogenase). Mutations in the same gene were subsequently found in six other children with the syndrome.

The two affected siblings studied in the original study also had respiratory infections reminiscent of cystic fibrosis. When the researchers applied a computational program to predict deleterious changes, mutations in another gene were implicated: DNAH5. Interestingly, this gene is associated with Kartagener’s syndrome, a disorder that has cystic fibrosis-like characteristics. Shendure’s conclusion is that the siblings in this unfortunate family inherited not one but two recessive Mendelian traits.

Shendure would not be drawn on the cost of exome sequencing per individual, but noted that an exome could be sequenced on two lanes of the current Illumina flow cell, which could soon be reduced to a single lane.

In subsequent discussion, David Valle (Johns Hopkins) pointed out that interpretation of these results was greatly facilitated by the wealth of medical expertise brought to bear on evaluating the biological significance of specific candidate genes. Nevertheless, as genome sequencing costs continue to drop, these studies (and others recently published in the area of cancer) strongly suggest that whole- or even partial genome sequencing can identify causal alleles associated with rare genetic diseases. Doubtless this is only the beginning.

'Personalized nutrition' is goal of Nutrigenomics initiative

High Planes Journal
Nebraska

Imagine a physician or dietitian handing you a set of individualized nutritional guidelines based on your unique genetic makeup--one that could help you ward off such diseases as cancer, diabetes and Alzheimer's. [A consesus of the Cold Spring Harbor "Personal Genomes" meeting, Sept. 14-17, 2009 was, that practicing physicians (let alone dietitians) for the basic reason of lack of their time, will simply not be able to keep up with the hyperescalating science of [holo]genomics. A distinguished Panelist emphasized that to deal with the already "out of hand" complexity, the conclusions must be automated. Thus, rather than expecting a dietitian to interpret your personal genome and handhold you through your daily life of what foods, food additives, cosmetics, etc. you should opt for (or against), your handheld "Personal Genome Assistant" that you already might have as your "smart phone" will do this handholding for you. The technology was introduced at the firts ever Consumer Genetics conference, see here - AJP]

That's the ultimate goal of the Nebraska Gateway for Nutrigenomics, a new research initiative at the University of Nebraska-Lincoln. It aims to use genome-based technologies to figure out what makes individuals and some ethnic groups susceptible to certain diseases and develop nutritional strategies to overcome those susceptibilities.

"In the old days," nutrition scientist Tim Carr said, "we used to say 'my grandfather ate bacon and eggs everyday and still lived to 103.' Those of us in the business would say, 'that's just genetics,' and we'd dismiss it.

"We're no longer dismissing it. We're trying to figure out how that works," Carr added.

Individuals' risk for certain diseases depends in part on their genetic makeup. Although those genetic makeups can't be altered, how they behave can be manipulated by diet. That's what nutrigenomics is all about.

"Looking at the genetic makeup of individuals, you can identify certain risk factors and make dietary recommendations," said Janos Zempleni, a molecular nutritionist who heads UNL's nutrigenomics initiative.

In February, a review team comprising scientists from several other universities noted that UNL is well positioned to be a leader in this burgeoning research field because it can integrate its plant-genomics expertise with its nutrition and food-science expertise. As food and nutrition scientists determine how diet interacts with the genome, agricultural scientists will be able to develop crops and livestock to put those findings into action.

"Since Nebraska is where America's diet begins, it is appropriate that UNL would be a leader in the nutrigenomic field," the team said in its report.

UNL food scientist Vicki Schlegel, another member of the research team, put it this way: "You're making agriculture a pharmacy, basically."

Schlegel imagines a day when states might carve out niches for certain kinds of health-boosting crops.

"We might say, 'in Nebraska we grow crops for heart health,'" she said. "Colorado might say, 'we grow crops to fight diabetes.'"

The U.S. Department of Agriculture's well-known diet guidelines are based on nutritional needs, said Schlegel, who specializes in neutraceuticals. "What we're talking about is a step beyond. This is considering foods from a more complex perspective."

"This is a huge shift in thinking," Carr said. "We are going from one-size-fits-all recommendations to a realization that one size doesn't fit all."

The rise of epigenomics - Methylated spirits
The human genome gets more and more complicated

From The Economist print edition
Oct 15th 2009

[This cartoon is perhaps a simple minded mechanical exaggeration. Reality is not as bad as it seems. Maybe the YouTube "call for Information Theory" a year ago to gear up Information Technology for the "Dreaded DNA Data Deluge" helped; Professionals already put forward serious theories of hologenome regulation. The one to beat is a software enabling approach that is now accepted without any objection voiced by the leading community. Thus, we no longer have to rely solely on loose metaphors as above but can advance to a stage similar to Bohr' atomic model. When he submitted his concept, his colleagues came back with this answer: "We all agree that your theory is crazy. The only thing we can not tell yet, if it is crazy enough to be true" - AJP]

IT WAS, James Watson claimed, something even a monkey could do. Sequencing the human genome, that is. In truth, Dr Watson, co-discoverer of the double-helical structure of DNA back in the 1950s, - [1953 AJP] had a point. Though a technical tour-de-force, the Human Genome Project was actually the sum of millions of small, repetitive actions by cleverly programmed robots. When it was complete, so the story went, humanity’s genes—the DNA code for all human proteins—would be laid bare and all would be light.

It didn’t quite work out like that. Knowing the protein-coding genes has been useful. It has provided a lexicon of proteins, including many previously unknown ones. What is needed, though, is a proper dictionary-an explanation of what the proteins mean as well as what they are. For that, you need to know how the genes’ activities are regulated in the 220 or so [many more - AJP] different types of cell a human body is made from. And that is the purpose of the American government’s Roadmap Epigenome Programme, results from which are published this week in Nature by Ryan Lister and Mattia Pelizzola of the Salk Institute in California, and their colleagues.

Epigenomics studies the distribution over the genome’s DNA of control molecules called methyl groups. [Therein the controversy; the methyl groups arise through the epigenomic channels, but acually sit on the genome. Thus, a separation of genomics from epigenomics cuts methylation into half. Clearly in HoloGenomics the two sides of the coin should always be considered in their interaction, with methylation as "the egede" of the coin - AJP]- These can attach themselves to cytosine, one of the four chemical bases that form the “letters” of the genetic code. In so doing, they help control a process called transcription, in which a copy of a gene is made in the form of a molecule called RNA, the first stage in the translation of a gene into a protein. The presumption is that the pattern of methylation, by controlling which proteins are manufactured, helps determine what type of cell is produced. A cell with its haemoglobin genes switched on to overdrive, for example, will become a red blood cell. One that churns out actin and myosin, which link up to form units that can expand and contract, will become a muscle cell. And so on. Dr Lister and Dr Pelizzola have tested this idea by describing the first two reasonably complete human epigenomes.

Waving or drowning?

The cells they chose to look at were embryonic stem cells, which retain the potential to turn into a variety of other cell types, and fetal lung fibroblasts, which are the end of one line of cell specialisation. They read the methylation patterns of these cells using a chemical trick that turns methylated cytosine (letter C) into another base, called uracil. In nature, this base is found in RNA, rather than DNA, but it is just as susceptible to being recorded by one of Dr Watson’s mechanical monkeys as the others are. Altogether, the researchers were able to read and compare about 90% of the genomes of their two types of cell.

Their first discovery was that the stem cells were more methylated than the lung cells—5.8% of cytosines, compared with 4.3%. Moreover, the difference was largely accounted for by something strange. Previous studies have shown that methylated cytosines are usually next to a letter called guanine (G). It is a common characteristic of the so-called promoter regions of genes, where transcription begins, that they contain long, repetitive sequences of alternating Cs and Gs. If these areas become methylated, it tends to suppress transcription of the gene in question. A quarter of the methylated cytosines in stem cells, however, were not followed by guanines. Nor were they found in the promoter regions of genes, but rather in the transcribed parts of the genes themselves. They also had the opposite effect from methylated cytosines found in promoter regions. The genes they occurred in tended to be transcribed more than usual, not less. In particular, a lot of genes involved in processing RNA were activated in the stem cells in this way.

One unexpected discovery made during the decade since the genome project was finished is that there are thousands of small genes whose RNA copies are not translated into proteins. Instead, the RNA acts in its own right. In plants, for example, it is one of the things that switches other genes on and off at their promoter sites. Whether it does so in mammals has yet to be established. But it might. In any case, unusual patterns of RNA processing in stem cells are something that will require further examination.

The complexities of methylation, then, are myriad - as are the complexities introduced by all these unexpected small genes. Reading the human genome in the first place may, indeed, have been work for mechanical monkeys. [This might be a too simplistic exaggeration - AJP]. Interpreting the result will require the finest minds that humanity can muster.

Salk-Led Team Generates First Map of Human Methylome

October 14, 2009

Genomeweb
By Andrea Anderson

[Entering the practical era of HoloGenomics (Genomics + Epigenomics, expressed in Informatics). Figure from Ecker et al. Nature paper. Note the extensive methylation of non-coding LINE repeats - a key in Recursive Genome Function - AJP]

NEW YORK (GenomeWeb News) – In a paper appearing online today in Nature, American and Australian researchers reported that they have mapped cytosine methylation across the genomes of two human cell lines.

"This paper documents the first complete mapping of the methylome, a subset of the entire epigenome, of two types of human cells — an embryonic stem cell and a human fibroblast line," Linda Birnbaum, director of the National Institute of Environmental Health Sciences, who was not involved in the study, said in a statement. "This will help us better understand how a diseased cell differs from a normal cell, which will enhance our understanding of the pathways of various diseases."

The work was done as part of a National Institutes of Health Roadmap Project on epigenetics.

The team mapped methylated cytosines to single base resolution across the genomes of an embryonic stem cell line and a differentiated lung fibroblast line, also incorporating information on messenger and small RNA transcripts and chromatin marks in the cells. When they compared the methylomes, the researchers found a slew of differences, including cell specific cytosine methylation patterns.

The study also opens the door for more extensive characterization of human epigenomes, senior author Joseph Ecker, a plant biology researcher at the Salk Institute for Biological Studies and director of the Salk Institute Genomic Analysis Lab, told GenomeWeb Daily News. "The real goal is to compare differentiating cells," he said. [To further refine, a key goal of HoloGenomics as a new field is the algorithmic, thus software-enabling theoretical understanding of hologenome-regulation - AJP]

Last spring, he and his co-workers reported that they had used a combination of sodium bisulfite sequencing and other high-throughput sequencing methods to characterize the methylome, transcriptome and small RNA transcriptome of the model plant Arabidopsis.

For the current study, Ecker and his team applied a similar approach to tackle the human epigenome, using bisulfite sequencing with the Illumina Genome Analyzer II to map cytosine methylation patterns across the genome in two human cell lines — the differentiated fetal lung fibroblast line IMR-9 and the human embryonic stem cell line H1.

Nearly all of the methylation in the differentiated fibroblast cells, was "CG methylation," occurring at sites at which cytosine is followed by guanine.

In contrast, roughly a quarter of the cytosine methylation in the stem cell was not at sites where cytosine was followed directly by guanine. This "non-CG methylation" was known to exist in stem cells, Ecker explained, but its prevalence was hard to judge in past studies that looked at only small portions of the genome.

"Non-CG methylation is not completely unheard of — people have seen it in dribs and drabs, even in stem cells. But nobody expected that it would be so extensive," co-lead author Mattia Pelizzola, a post-doctoral researcher in Ecker's lab, said in a statement. "[N]on-CG methylation was often considered a technical artifact."

By looking at the number of methyl-cytosine reads at each site, the researchers were also able to map methylation levels across the genome. For instance, the team found that differentiated fibroblast cells contained partially methylated areas that frequently corresponded with decreased gene expression, Ecker noted.

They also reported that non-CG methylation in stem cells was often depleted at transcription start sites as well as enhancer and transcription factor binding sites. In contrast, the researchers did not see this periodicity in the differentiated cells, Ecker said.

When they targeted some of the non-CG methylation loci with bisulfite sequencing in another human embryonic stem cell line called H9, the researchers found similar non-CG methylation patterns at conserved positions.

"The exclusivity of non-CG methylation in stem cells, probably maintained by continual de novo methyltransferase activity and not observed in differentiated cells, suggests that it may have a role in the origin and maintenance of this pluripotent state," the team concluded. "Essential future studies will need to explore the prevalence of non-CG methylation in diverse cell types, including variation throughout differentiation and its potential re-establishment in induced pluripotent states."

Consistent with the potential link between non-CG methylation and pluripotency, the same sites were non-CG methylated in the team's pilot experiments looking at an induced pluripotent stem cell line created by reprogramming fibroblast cells.

In the future, Ecker said, the team hopes to track changes in the epigenome, including genome-wide chromatin marks, methylation, and more, as they coax embryonic stem cells into a variety of differentiated cell types.

The single-base resolution human methylome data is available online through the Human DNA Methylome web site [see below - AJP].

Human DNA methylomes at base resolution show widespread epigenomic differences

Ryan Lister1,9, Mattia Pelizzola1,9, Robert H. Dowen1, R. David Hawkins2, Gary Hon2, Julian Tonti-Filippini4, Joseph R. Nery1, Leonard Lee2, Zhen Ye2, Que-Minh Ngo2, Lee Edsall2, Jessica Antosiewicz-Bourget5,6, Ron Stewart5,6, Victor Ruotti5,6, A. Harvey Millar4, James A. Thomson5,6,7,8, Bing Ren2,3 & Joseph R. Ecker1

Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA
Ludwig Institute for Cancer Research,
Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, California 92093, USA
ARC Centre of Excellence in Plant Energy Biology, The University of Western Australia, Crawley, Western Australia 6009, Australia
Morgridge Institute for Research, Madison, Wisconsin 53707, USA
Genome Center of Wisconsin, Madison, Wisconsin 53706, USA
Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, Wisconsin 53715, USA
Department of Anatomy, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA

Abstract

DNA cytosine methylation is a central epigenetic modification that has essential roles in cellular processes including genome regulation, development and disease. Here we present the first genome-wide, single-base-resolution maps of methylated cytosines in a mammalian genome, from both human embryonic stem cells and fetal fibroblasts, along with comparative analysis of messenger RNA and small RNA components of the transcriptome, several histone modifications, and sites of DNA–protein interaction for several key regulatory factors. Widespread differences were identified in the composition and patterning of cytosine methylation between the two genomes. Nearly one-quarter of all methylation identified in embryonic stem cells was in a non-CG context, suggesting that embryonic stem cells may use different methylation mechanisms to affect gene regulation. Methylation in non--CG contexts showed enrichment in gene bodies and depletion in protein binding sites and enhancers. Non--CG methylation disappeared upon induced differentiation of the embryonic stem cells, and was restored in induced pluripotent stem cells. We identified hundreds of differentially methylated regions proximal to genes involved in pluripotency and differentiation, and widespread reduced methylation levels in fibroblasts associated with lower transcriptional activity. These reference epigenomes provide a foundation for future studies exploring this key epigenetic modification in human disease and development.

Personalized Medicine - New Leroy Hood startup raises $30 million in financing

TechFlash
October 14, 2009

Last month, we reported that Dr. Leroy Hood's latest startup company, Integrated Diagnostics, had raised $7.5 million of a $30 million round. At the time, representatives for Hood and his Institute for Systems Biology didn't want to talk about the round. But today, the famed biotechnology pioneer is pulling back the covers on the company and officially announcing more than $30 milling in funding from InterWest Partners, The Wellcome Trust and dievini Hopp Biotech Holding.

That's an interesting syndicate of investors, combining funds from traditional venture capital with capital from non-profit entities. InterWest is a huge Silicon Valley venture fund, while the Wellcome Trust is the UK's largest charity supporting biomedical research. Meanwhile, dievini Hopp Biotech is investing as part of a collaboration agreement between Hood's ISB and the Grand Duchy of Luxembourg.

Last year, Luxembourg announced a $200 million partnership with three U.S. biomedical research groups to improve health care in the tiny European country and boost economic development in the biotech sector.

"This venture is an important element of our long-term plan to advance Luxembourg’s research and commercial capabilities in systems biology and personalized medicine," Patrizia Luchetta, deputy director, Board of Economic Development for the Grand Duchy of Luxembourg said in a release.

According to my numbers, Integrated Diagnostics' massive funding round would tie it for the third largest venture financing deal of the year in Washington state.

And the investment is a big bet on Hood, a renowned scientist who helped create biotechnology companies such as Angen, Rosetta Inpharmatics and Applied Biosystems. With Integrated Diagnostics, Hood and his team of researchers are looking to create new diagnostic tools and biomarkers to help usher in a new era of personalized medicine.

Hood explains the company's ambitious plans this way:

“Just as the DNA sequencer allowed us to decode the human genome, the technology behind Integrated Diagnostics will allow us unprecedented insight into preventing and treating diseases like cancer, diabetes and Alzheimer’s by analyzing the proteins that appear in their earliest stages. I have had the good fortune to found several successful biotechnology companies. I believe Integrated Diagnostics will prove to be among the most significant. By taking a systems approach to monitoring an individual’s health we will be able to provide physicians and patients an early warning system for preventing and treating diseases.”

Integrated, which is based in Seattle, was co-founded by Caltech chemistry professor Jim Heath, Battelle Memorial Institute Vice President and ISB professor David Galas and ISB scientific director of special projects Paul Kearney.

More scientific analysis on what Hood and his team are doing from a story in last year's MIT Technology Review.

Science adviser to Prez. Obama; Eric Lander (Dir. of Broad Institute of Harvard and MIT) et al. say The DNA is Fractal

[Science adviser to President; Eric Lander et al. say: The DNA is Fractal - AJP]

Fractal globule architecture packs two meters of DNA into each human cell, avoids knots

Scientists decipher the 3-D structure of the human genome

[Fractal is structuro-functional - AJP]

CAMBRIDGE, Mass. -- Scientists have deciphered the three-dimensional structure of the human genome, [further - see Pellionisz' FractoGene since 2002, Post-ENCODE in Pellionisz Principle of Fractal Iterative Recursion, 2008, and as recently as in Cold Springs Harbor, 2009] paving the way for new insights into genomic function and expanding our understanding of how cellular DNA folds at scales that dwarf the double helix.

In a paper featured this week on the cover of the journal Science, they describe a new technology called Hi-C and apply it to answer the thorny question of how each of our cells stows some three billion base pairs of DNA while maintaining access to functionally crucial segments. The paper comes from a team led by scientists at Harvard University, the Broad Institute of Harvard and MIT, University of Massachusetts Medical School, and the Massachusetts Institute of Technology.

"We've long known that on a small scale, DNA is a double helix," says co-first author Erez Lieberman-Aiden, a graduate student in the Harvard-MIT Division of Health Science and Technology and a researcher at Harvard's School of Engineering and Applied Sciences and in the laboratory of Eric Lander at the Broad Institute. "But if the double helix didn't fold further, the genome in each cell would be two meters long. Scientists have not really understood how the double helix folds to fit into the nucleus of a human cell, which is only about a hundredth of a millimeter in diameter. This new approach enabled us to probe exactly that question."

The researchers report two striking findings. First, the human genome is organized into two separate compartments, keeping active genes separate and accessible while sequestering unused DNA in a denser storage compartment. Chromosomes snake in and out of the two compartments repeatedly as their DNA alternates between active, gene-rich and inactive, gene-poor stretches.

"Cells cleverly separate the most active genes into their own special neighborhood, to make it easier for proteins and other regulators to reach them," says Job Dekker, associate professor of biochemistry and molecular pharmacology at UMass Medical School and a senior author of the Science paper.

Second, at a finer scale, the genome adopts an unusual organization known in mathematics as a "fractal." The specific architecture the scientists found, called a "fractal globule," enables the cell to pack DNA incredibly tightly -- the information density in the nucleus is trillions of times higher than on a computer chip -- while avoiding the knots and tangles that might interfere with the cell's ability to read its own genome. Moreover, the DNA can easily unfold and refold during gene activation, gene repression, and cell replication.

"Nature's devised a stunningly elegant solution to storing information -- a super-dense, knot-free structure," says senior author Eric Lander, director of the Broad Institute, who is also professor of biology at MIT, and professor of systems biology at Harvard Medical School.

In the past, many scientists had thought that DNA was compressed into a different architecture called an "equilibrium globule," a configuration that is problematic because it can become densely knotted. The fractal globule architecture, while proposed as a theoretical possibility more than 20 years ago, has never previously been observed [a fractal model of a Purkinje neuron was, in fact, constructed more than 20 years ago, specifically stating "3.1.3. Neural Growth: Structural Manifestation of Repeated Access to Genetic Code. One of the most basic, but in all likelihood rather remote, implication of the emerging fractal neural modeling is that it corroborates a spatial "code-repetition" of the growth process with the repetitive access to genetic code." As documented in the "acknowledgement", the study was conducted in the framework of grant application "Neural Geometry" to NIMH Program "Mathematical/Computational/Theoretical Neuroscience". However, since "recursive genome function violated both prevailing erroneous axioms, "Crick's Central Dogma" and "Ohno' Junk DNA", the grant was denied and an existing NIH grant discontinued - AJP]

Key to the current work was the development of the new Hi-C technique, which permits genome-wide analysis of the proximity of individual genes. The scientists first used formaldehyde to link together DNA strands that are nearby in the cell's nucleus. They then determined the identity of the neighboring segments by shredding the DNA into many tiny pieces, attaching the linked DNA into small loops, and performing massively parallel DNA sequencing.

"By breaking the genome into millions of pieces, we created a spatial map showing how close different parts are to one another," says co-first author Nynke van Berkum, a postdoctoral researcher at UMass Medical School in Dekker's laboratory. "We made a fantastic three-dimensional jigsaw puzzle and then, with a computer, solved the puzzle."

Lieberman-Aiden, van Berkum, Lander, and Dekker’s co-authors are Bryan R. Lajoie of UMass Medical School; Louise Williams, Ido Amit, and Andreas Gnirke of the Broad Institute; Maxim Imakaev and Leonid A. Mirny of MIT; Tobias Ragoczy, Agnes Telling, and Mark Groudine of the Fred Hutchison Cancer Research Center and the University of Washington; Peter J. Sabo, Michael O. Dorschner, Richard Sandstrom, M.A. Bender, and John Stamatoyannopoulos of the University of Washington; and Bradley Bernstein of the Broad Institute and Harvard Medical School.

This work was supported by the Fannie and John Hertz Foundation, the U.S. Department of Defense, the National Science Foundation, the National Space Biomedical Research Institute, the National Human Genome Research Institute, the American Society of Hematology, the National Heart, Lung and Blood Institute, the National Institute of Diabetes and Digestive and Kidney Diseases, the Keck Foundation, and the National Institutes of Health.

Knome Personal Genomics Service Expands to Include 93,000 Rare Mutations from the Human Gene Mutation Database Distributed by BIOBASE.

October 08, 2009 08:00 AM Eastern Daylight Time

CAMBRIDGE, Mass. and WOLFENBÜTTEL, Germany--(BUSINESS WIRE)--Knome, a recognized pioneer in the personal genomics industry, announced today that it is incorporating information from The Human Gene Mutation Database (HGMD® - Cardiff University, UK) distributed by BIOBASE, into its genome interpretation services. With over 93,000 mutations and disease-related polymorphisms in more than 3,500 genes, HGMD is one of the world’s most comprehensive databases of medically relevant genetic variation. Typically used by large research institutions and pharmaceutical companies, this is the first time the genomic data in the HGMD is being made available as part of a consumer offering.

Under the agreement, Knome will include HGMD in its KnomeXplorer™ genome browser software, and in its genome interpretation update service. The data will be continuously updated with the latest findings and distributed to Knome’s clients, giving them direct access to the most up-to-date information on a real-time basis. “Incorporating HGMD into our service will significantly expand the dataset used in our core analysis and enhance the content we provide to clients in our update service,” said Jorge Conde, CEO of Knome.

Unlike entry-level consumer genomic services that limit their focus to variants that are common in the general population, Knome informs its clients of even very rare variants that they carry, many of which are thought to be elusive causes of relatively common diseases, such as colorectal cancer and diabetes, that can dramatically affect health and quality of life. Every person likely carries many such variants, each one of which may -- due to its potentially debilitating effects in carriers or their children -- remain too rare to be included in entry-level SNP-chip based services. For example, the incorporation of HGMD adds an additional 1,698 mutations in 76 genes for colorectal cancer, and 1,435 mutations in 110 genes for diabetes, into Knome’s automated interpretation software.

Michael Tysiak, CEO of BIOBASE said, “Combined with their sequencing capabilities and interpretation services, the addition of our rare mutation database will enable Knome to provide even deeper insight into each client’s genetic profile and deliver greater customer value.”

Financial terms and conditions of the agreement were not disclosed.

Beyond the Genome [Does Fractal Iterative Recursion makes sense to you? - AJP]

Wired
By Brandon Keim October 7, 2009

[Recursive? - AJP]

When scientists finished sequencing the human genome, the answers to diseases were supposed to follow. Six years later, that promise has gone unfulfilled. Genetics just isn’t that useful for predicting who gets sick, and why. The blueprint of life turned out to be an intriguing parts list.

“It’s much more complex than we had thought. There aren’t going to be easy answers,” said Teri Manolio, director of the National Human Genome Research Institute’s Office of Population Genomics. “The genome is constantly surprising us. There’s so much that we don’t know about it.”

Manolio is the lead author of a Nature article entitled “Finding the missing heritability of complex diseases.” Published Wednesday, it’s part of a major change in how scientists see the genome.

In April, several articles in the New England Journal of Medicine featured researchers arguing over why genome-wide association studies — in which thousands of genomes are compared in a hunt for disease-linked patterns — had found so little. Several months later, a massive hunt for schizophrenia genes was described as the field’s “Pearl Harbor.” At a conference this summer at the Jackson Laboratories, the shortcomings of gene-centered explanations were a starting point for talks by some of the world’s most prominent geneticists.

It’s not that genes are suddenly unimportant. Researchers are just acknowledging their variations as pieces of an extraordinarily complicated puzzle, along with how genes are turned on, how many copies are made of each, the shape of the genome itself, and how all of the genome’s protein products mix and interact.

Wired.com talked to Manolio about the future of genomics research.

Wired.com: What do you mean by “missing heritability”?

Teri Manolio: We know that diseases cluster in families. In some diseases, the risk might be two or three times higher than normal, or 30 times higher, for a relative of someone with a disease. But when we do these genomic studies, we find maybe a 50 percent increase in risk. That gap is what’s missing.

Wired.com: The numbers can get tricky. If you’ve found that someone with a certain genetic variant has double the risk of developing a disease, but the heritable risk is a hundred-fold, then we’ve only connected two percent of the heritability to genetics?

Manolio: That’s a fair way of putting it. The gap varies. In some diseases, we’re describing half of the genetic heritability. But that’s unusual. Only macular degeneration has numbers that high. In many diseases, it’s around five percent.

Wired.com: How much of the gap is caused by our inability to link genetics to conditions, and how much has non-genetic causes?

Manolio: There’s a lot of thought that this might be DNA and environment together. If you’re not exposed to adverse environmental factors, then you may never develop a given disease. With a bad enough environmental exposure, you may get a disease regardless of your genetic makeup.

Wired.com: What about aspects of our DNA that we’re just starting to study, like variations in the number of copies we have of each gene, or how genes are activated or physically arranged inside a cell?

Manolio: All of those have been suggested. At least so far, it doesn’t look like copy numbers explain a huge amount of this. But there are other places to look, and I suspect that the answer is going to be, “all of the above.”

Wired.com: How does all this fit with what the public expected of genomics? It seems we had different expectations than the scientific community.

Manolio: Well, to be honest, I think we were a bit naive about things, too. We’d hoped that when we identified where all the genes are, and all the coding regions and all the variations one could have, then that would explain everything. Those were the hopes, and then reality came crashing in.

Wired.com: What about personalized genomics testing? That’s been the big consumer application of genomics so far.

Manolio: Since we’re not explaining a huge mount of the inherited tendencies between people, then the information you get from a genotyping company may not be very apparently useful for predicting your risk of disease in the future. That’s what emerges from many of these studies: There are likely many other factors that increase your risks, and these factors are known and explain more than genomics does now. Genomics is a promising research tool, but right now it’s really a research tool.

Wired.com: How do we find the missing heritability?

Manolio: We’ll follow multiple avenues of research. We have to be humble about how this works.

Wired.com: Do we have the tools?

Manolio: Our sequencing is in good shape — the costs are coming down, we can get everyone’s base pairs read — but interpreting them is a real challenge. Technologies for epigenetics research are still developing. And there will be other needs coming down the pipeline. [For instance, some algorithmic theories of genome function - AJP].

Wired.com: Want to put a timetable on the research?

Manolio: I don’t think we can. In the next few years, we’ll see lots of variants associated with diseases. Many will be further investigated, and their functions determined. That’s one of the missing links here: what’s the function of all these things? [Seems like a perfectly clear question - AJP]. We have over 400 variants identified in a whole variety of traits, but only in a few do we understand how they change a gene’s function, and how that may change biology. But these are great clues to biology.

Wired.com: Is that a better way of thinking about genetics — not in terms of answers, but clues?

Manolio: Absolutely. And if you’re a glass half-full person, then four years ago, we had practically no associations that we could replicate in multiple populations. Now there are hundreds. All of these are clues, and that’s wonderful. We just need to be patient in figuring out what they mean.. [Well, the "patients", suffering from "Junk DNA diseases", like Alzheimer's do not seem to be patient with billions of dollars poured into "big science projects" coming up with "a more and more intriguing 'parts list' - yet little interest in putting the parts together" - AJP]

Beckman Prepares for Genomics Services Gold Rush

Bio-IT World CHI's Network October 7, 2009

By John Russell

October 6, 2009 | Like many others, Beckman Coulter is betting the mainstreaming of genomics-based research and the future growth of personalized medicine will create a large, robust market for genomics services. Last March, the services giant purchased Cogenics and combined it with DNA sequencing specialist Agencourt Bioscience, acquired earlier, to create Beckman Coulter Genomics (BCG). As research and medical communities rush to dig gold from mounting genomics data, BCG hopes to sell the needed picks and shovels.

“If you start with the Cogenics business model, you really go to a biobank and partner with research partners or clinical partners to be able to bring samples in, to process them to do DNA and RNA extraction, to bank the nucleic acids, and then to perform a battery of tests,” says Susan Evans, general manager of Beckman Coulter Genomics. “So although we are still staunch advocates of the value of sequencing and the tremendous future of next-gen and third-gen sequencing, it was very important to develop a more comprehensive offering for our strategy.“

Today, BCG has roughly 250 staff worldwide. The company is transitioning away from the Cogenics name but will keep Agencourt as a product brand “for the time being because it’s used in the name of our nucleic acid products classification products.” BCG is headquartered in Beverly, Mass.

“We’ve all watched the trend toward outsourcing versus creating core centers internally,” says Evans, “and certainly we still believe we’re seeing more outsourcing. Also, the sequencing technology is changing so rapidly that companies are looking for an opportunity to come to a service laboratory like ours which has the expertise and experience and are going out and acquiring the new platforms. It allows them to use the technology well before they might choose to acquire a system themselves or actually get to the point of saying ‘I do not want to acquire a system.’”

Beckman, of course, has long been a leading manufacturer of biomedical testing instrument systems, tests and supplies as well as a services provider. The Fullerton, Calif.-based company reported 2007 annual sales of $2.76 billion “with more than 78 percent of this amount generated by recurring revenue from supplies, test kits and services.”

Beckman jumped firmly into the genomics services in 2006 with the purchase of Agencourt for $100 million. It quickly spun out the sequencer equipment business, Agencourt Personal Genomics, selling it to Applied Biosystems Inc. (ABI was later itself acquired by Invitrogen in 2008 for $6.5 billion.)

At Beckman, the strong Agencourt brand was retained and turned into a center of excellence for nucleic acid products and services. This year, Beckman acquired Cogenics from Clinical Data. Services currently available through BCG include sequencing, sample preparation, genotyping, gene expression, biological efficiency and safety testing, with support for all levels of regulatory compliance, including Clinical Laboratory Improvement Amendments (CLIA).

Moreover, BCG offers three commercially available next-generation sequencing platforms: Roche 454 Genome Sequencer FLX with Titanium, Applied Biosystems SOLiD and Illumina Genome Analyzer. While pricing for many sequencing platforms is declining, Evans notes the platform cost is only part of the buy-versus-outsource question. She says needed know-how, sample prep expertise, bioinformatics, and other issues increasingly incline companies to outsource. In line with this, she says BCG can collaborate on study design questions with research organizations.

The addition of Cogenics brought new customers and strengthened BCG’s global reach. Beckman Coulter is a global business, but most of Agencourt’s had been U.S.-based. The acquisition added a facility in the U.K., another in Germany, and co-marketing partnership in China. “Another important component is that Cogenics' North Carolina facility has CLIA-licensed laboratory and we do primarily work for our pharmaceutical customers in that lab. But it also creates strategic opportunity for us to think of additional ways we can use that lab and different ways we can leverage Beckman Coulter product lines and opportunities,” says Evans.

It’s also fair to say a large chunk of Agencourt’s customers were academic. “We have a very diverse customer population from academic to biotech and biopharma but probably stronger on the research, academic, and industrial (bioag) side of the business. [The] Cogenics strategy was also to value a broader customer base but to focus on partnerships with pharmaceutical companies and especially to utilize the clinical genotyping and gene expression resources and clinical genotyping for clinical trial support. They also, of course, had an almost 20-year business supporting pharma biological safety testing.”

BCG is now focused on integrating the two businesses and driving revenue. Says Evans, “Our near-term initiatives are a combination of business efficiency and operation consolidation. So like any integration, we’re looking for best practices across each of these laboratories. We’re looking for increased automation. We’re looking for ways to enhance our information flow from lab to lab and be able to integrate support for our customers. We’re now five months into [that effort] and will continue over the next number of months. On the other side it’s a redesigned sales team and establishing the broader product offering and stronger messaging. We are expecting growth and have planned for growth.”

Watching the evolution of the broadly-defined genomics services business will be interesting. It’s long been a patchwork of big and small players. Recently CROs have shown interest in expanding their genomics services offering.

Julie Moore, director of global strategic marketing for BCG, says “We’ve just seen Covance acquire the Rosetta business in Seattle. That’s an interesting expansion for their business. I think there’s increasing overlap between the CROs and the typical genomics services providers such as us.” Consequently, CROs, which constitute an important customer segment for BCG, can sometimes become competitors.

So far, the genomics services market shows few signs of the consolidation striking other biotech markets. “We’ve seen a lot of small mom and pop shops popping up with the Sanger sequencing now that it’s more available and cheaper,” says Moore.

BCG’s customer set, predictably, represents a jumble of opportunistic sales and longer-term relationships. Evans conceded they don’t know how this will evolve over time, although deeper, long-term relationships with big customers are clearly desirable. Moore adds that BCG has strong relationships with some of the top biopharma community, some of those based on Cogenics’ very solid safety testing service for biologicals.

Having broadened its products and services portfolio, BCG is now wading more forcefully into the services market, trumpeting its newly-gained global presence, its heritage of next-gen sequencing expertise, and the stability of being part of services industry powerhouse Beckman Coulter

[R&D and Market analysis of this "game changer" is upon request. Pellionisz; HolGenTech_at_gmail.com]

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IBM Looks to Make DNA Analysis Cheap and Easy

eWeek.com
October 6, 2009

IBM scientists are developing a technology that will enable physicians and other researchers to quickly and easily read and analyze strands of DNA, an advancement that could lead to greater personalized health care. The scientists are looking to create a “DNA transistor” in which a DNA molecule is threaded through a 3-nm “nanopore” and the genetic information is analyzed. The key challenge is finding a way to control the speed in which the DNA runs through the nanopore. Health care providers armed with an individual’s genetic information can more easily determine diseases to which the patient is predisposed, and which treatments would work best.

IBM scientists are developing a chip that can easily and quickly read strands of DNA, a development that could lead to more personalized health care.

The goal of the research project, announced Oct. 6, is to create the capability to analyze a person’s genome information for as little as $1,000, which could mean better diagnosis and treatment for patients.

“What is the next big thing in biotechnology?” Gustavo Stolovitzky, an IBM researcher on the project, asked in a video posted by IBM. “The answer is kind of simple, if you are in the field: You need to know how to sequence DNA fast and cheap.”

IBM researchers—from such fields as nanofabrication, microelectronics, physics and biology—are looking to do this through a silicon-based “DNA transistor.” The technique sends a DNA molecule through a 3-nanometer-wide hole—or “nanopore”—in a chip. As it’s squeezed through the nanopore, an electrical sensor reads the DNA and analyzes the genetic data within.

A nanometer is about 100,000 times smaller than the width of a human hair.

Click here to see how IBM is using DNA to build next-generation chips.

If physicians know a person’s individual genetic code, they can determine whether the person is predisposed to certain diseases, which treatments will work best and whether a particular patient will have an adverse reaction to medicine, according to IBM. It could also lead to faster discovery and testing of new products.

“Personalized medicine will become a reality,” Stolovitzky said.

The key challenge is finding a way to control the speed in which the DNA molecule travels through the nanopore, according to IBM researchers. They have created a multilayer metal/dielectric nano-structure that contains the nanopore and uses voltage between the metal layers to control the electric field in the nanopore.

The goal is to trap the DNA in the nanopore. Researchers believe that by turning these gate voltages on and off, they can slow the movement of the DNA through the nanopore at a rate—about one nucleotide per cycle—that would make DNA readable.

“We want to control the passing of DNA through the nanopore,” Stolovitzky said.

If successful, the project could lead to handheld devices that could easily and cheaply read and analyze DNA.

“The DNA transistor is one of those technologies that will, in the longer run, achieve sequencing very cheap and very fast,” Stolovitzky said, cautioning that there still is a lot of work to be done before IBM can say the project is a success.
[R&D and Market analysis of this "game changer" is upon request. Pellionisz; HolGenTech_at_gmail.com]

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IBM CEO also wants to resequence the health-care system

October 6, 2009 by Chris Seper

CLEVELAND, Ohio — IBM’s chief executive officer says electronic medical records need to go open source.

Sam Palmisano told the attendees of the Cleveland Clinic Medical Innovation Summit that health care can barely be called a “system.” “If the health system was a patient we wouldn’t be able to read its vital signs,” he told an audience of about 400 physicians, researchers, medical investors and business leaders.

To become a true system, improve results, cut medical errors and trim costs, Palmisano said the medical industry must agree to universal, open and non-proprietary standards for electronic health records. In essence, he said, electronic records have to be like generic drugs and the data must flow throughout the system in which no provider owns the process.

“When you enforce standards then you get scale,” Palmisano said. “If you could force in your industry standards then costs will drop. They will plummet.”

The open-source argument was part of Palmisano’s four-pronged approach to creating a true system in health care, which also included emphasizing wellness, creating a new code of ethics and enhancing broad collaboration between health-care stakeholders.

Many of the concepts Palmisano proposed in his speech aren’t new. But it’s the first time the IBM chief laid out his company’s specific vision for health care.

Palmisano spoke on the same day IBM announced plans to sequence the personal genome and do it for a rock-bottom price of, ultimately, $100. IBM joins nearly 20 other companies pursuing genome sequencing, and success in the field — and for a low cost — would press the fast-forward button on personalized medicine, clinical testing of new products, and determine individuals’ predisposition for specific diseases.

“To bring about an era of personalized medicine, it isn’t enough to know the DNA of an average person,” said Gustavo Stolovitzky, an I.B.M. biophysicist, told The New York Times. “As a community, it became clear we need to make efforts to sequence in a way that is fast and cheap.”

Palmisano barely touched on genome sequencing in his speech in Cleveland, instead focusing on health reform in a room full of people directly responsible for various aspects of the health of medicine.

Along with the open-source approach, Palmisano said health care also needed to:

Emphasize wellness. IBM, for example, pays for its employees’ doctor visits. It also plans to expand an incentive program for employee to leave healthy.

Increase collaboration, which would require sharing of health information and data between patients, health-care providers and insurance companies as well as redistribute the payments and responsibilities in the health system. Palmisano argued that transferring a health system into a cloud computing model — “think of if it worked liked Google” — with per-transaction charges would streamline the system.

Install aggressive ethics and public policies that accommodate the invasive nature of modern medicine. “We’re entering a different world ladies and gentlemen,” he said. “The idea of a computer chip in your body, pills you take to monitor your health, sharing data with an insurance company and your employer — I know not everyone is happy with that. Not everyone wants to be a human petri dish.”

Palmisano highlighted health care’s failings — a lack of electronic-record adoption, constant data re-entry and unnecessary testing — to question its status as a true system. He compared electronic health records as the UPC symbol or ATM machine of the health industry, allowing patients to receive better care by centralizing data and eliminating the opportunities for errors.

“Everyone agrees on its purpose: American health care must be patient-centric,” Palmisano said, but added: “Nothing is connected.”

As a company, IBM is eager to become the system manager. Palmisano noted that IBM manages Malta’s water system and the traffic systems in cities in Australia to Sweden.

But asking an IBM to take over a government’s health system has its downsides. Dan Pelino, IBM’s general manager for healthcare and life sciences, noted after Palmisano’s speech that IBM also manages the entire health system for Denmark.

When asked what would happen if Denmark ever wanted to switch vendors, Pelino said: “They probably couldn’t switch vendors.”

[R&D and Market analysis of this "game changer" is upon request. Pellionisz; HolGenTech_at_gmail.com]
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I.B.M. Joins Pursuit of $1,000 Personal Genome

New York Times
by JOHN MARKOFF

Published: October 5, 2009

One of the oldest names in computing is joining the race to sequence the genome for $1,000. On Tuesday [October 6, 2009 - AJP], I.B.M. plans to give technical details of its effort to reach and surpass that goal, ultimately bringing the cost to as low as $100, making a personal genome cheaper than a ticket to a Broadway play.

The project places I.B.M. squarely in the middle of an international race to drive down the cost of gene sequencing to help move toward an era of personalized medicine. The hope is that tailored genomic medicine would offer significant improvements in diagnosis and treatment.

I.B.M. already has a wide range of scientific and commercial efforts in fields like manufacturing supercomputers designed specifically for modeling biological processes. The company’s researchers and executives hope to use its expertise in semiconductor manufacturing, computing and material science to design an integrated sequencing machine that will offer advances both in accuracy and speed, and will lower the cost.

“More and more of biology is becoming an information science, which is very much a business for I.B.M.,” said Ajay Royyuru, senior manager for I.B.M.’s computational biology center at its Thomas J. Watson Laboratory in Yorktown Heights, N.Y.

DNA sequencing began at academic research centers in the 1970s, and the original Human Genome Project successfully sequenced the first genome in 2001 and cost roughly $1 billion [$3 Billion - AJP].

Since then, the field has accelerated. In the last four to five years, the cost of sequencing has been falling at a rate of tenfold annually, according to George M. Church, a Harvard geneticist. In a recent presentation in Los Angeles, Dr. Church said he expected the industry to stay on that curve, or some fraction of that improvement rate, for the foreseeable future.

At least 17 startup and existing companies are in the sequencing race, pursuing a range of third-generation technologies ["next" or "n-th" generation is vague. Better terms for the novel approaches are "nano-sequencing" or "single molecule sequencing" - AJP]. Sequencing the human genome now costs $5,000 to $50,000, although Dr. Church emphasized that none of the efforts so far had been completely successful and no research group had yet sequenced the entire genome of a single individual.

The I.B.M. approach is based on what the company describes as a “DNA transistor,” which it hopes will be capable of reading individual nucleotides in a single strand of DNA as it is pulled through an atomic-size hole known as a nanopore. A complete system would consist of two fluid reservoirs separated by a silicon membrane containing an array of up to a million nanopores, making it possible to sequence vast quantities of DNA at once.

The company said the goal of the research was to build a machine that would have the capacity to sequence an individual genome of up to three billion bases, or nucleotides, “in several hours.” A system with this power and speed is essential if progress is to be made toward personalized medicine, I.B.M. researchers said.

At the heart of the I.B.M. system is a novel mechanism, something like nanoscale electric tweezers. This mechanism repeatedly pauses a strand of DNA, which is naturally negatively charged, as an electric field pulls the strand through a nanopore, an opening just three nanometers in diameter. A nanometer, one one-billionth of a meter, is approximately 80,000 times smaller than the width of a human hair.

The I.B.M. researchers said they had successfully used a transmission electron microscope to drill a hole through a semiconductor device that was intended to “ratchet” the DNA strand through the opening and then stop for perhaps a millisecond to determine the order of four nucleotide bases — adenine, guanine, cytosine or thymine — that make up the DNA molecule. The I.B.M. team said that the project, which began in 2007, could now reliably pull DNA strands through nanopore holes but that sensing technology to control the rate of movement and to read the specific bases had yet to be demonstrated.

Despite the optimism of the I.B.M. researchers, an independent scientist noted that various approaches to nanopore-based sequencing had been tried for years, with only limited success.

“DNA strands seem to have a mind of their own,” said Elaine R. Mardis, co-director of the genome center at Washington University in St. Louis, noting that DNA often takes a number of formations other than a straight rod as it passes through a nanopore.

Dr. Mardis also said previous efforts to create uniform silicon-based nanopore sensors had been disappointing.

One of the crucial advances needed to improve the quality of DNA analysis is to be able to read longer sequences. Current technology is generally in the range of 30 to 800 nucleotides, while the goal is to be able to read sequences of as long as one million bases, according to Dr. Church, who spoke in July at a forum sponsored by Edge.org, a nonprofit online science forum.

Other approaches to faster, cheaper sequencing include a biological nanopore approach being pursued by Oxford Nanopore Technologies, a start-up based in England [and backed by Illumina - AJP], and an electron microscopy-based system being designed by Halcyon Molecular, a low-profile Silicon Valley start-up that has developed a technique for stretching single strands of DNA laid out on a thin carbon film. The company may be able to image strands as long as one million base pairs, said Dr. Church, who is an adviser to the company, and to several others.

“To bring about an era of personalized medicine, it isn’t enough to know the DNA of an average person,” said Gustavo Stolovitzky, an I.B.M. biophysicist, who is one of the researchers who conceived of the I.B.M. project. “As a community, it became clear we need to make efforts to sequence in a way that is fast and cheap.”

[Since the IBM project "started in 2007" one wonders why is it played up now, and why is emphasis on sequencing, or even the easy affordability of full human DNA sequences, when the often quoted George Church ("the Edison of PostModern Genomics") has been openly talking about "zero dollar sequencing" -- and puts clear emphasis on the huge gap between the cost of sequencing (~$0) and the tremendous value of understanding genome function - in connection to diseases, their prevention, and if appear their diagnosis, therapy and cure in the oncoming "personalized medicine", and beyond, to "genome-based personalization in the Genome Based Economy"? The answer is probably the third paragraph (highlighted in purple also there - AJP). "The name of the game to Genome Based Economy is understanding genome function - in terms of Genome Informatics". No wonder, therefore, that 2007 was the year not only of "starting this IBM nano-sequencing project", but also when INTEL stepped into same by massive investment to Pacific Biosciences. Thus, a truly sensational announcement would e.g. be; "Intel scoops from IBM its Watson Center genome informatics pioneer Isidore Rigoutsos" (who published in 2006, after much struggle, his breakthrough paper on "pyknon" architecture of the DNA, putting our understanding genome function on an entirely new basis) - Pellionisz; HolGenTech_at_gmail.com, Oct. 5, 2009]

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$100 million in grants thrill Medical Center [Houston]

Houston Chronicle
By TODD ACKERMAN

Sept. 30, 2009, 11:39PM

Three Texas Medical Center institutions will receive more than $100 million in research grants as part of a $5 billion stimulus package President Barack Obama announced Wednesday to fight disease and create jobs.

The program, which Obama called “the single largest boost to biomedical research in history,” will fund cutting-edge research, the hiring of researchers and other staff, and laboratory and equipment upgrades.

Targets include cancer, heart disease and autism, with an emphasis on genetic causes.

“This is huge,” said Susan Hamilton, senior vice president and dean of research at Baylor College of Medicine. “It couldn't have come at a better time, given the economic uncertainty and the slowdown in government funding the last decade.

“It'll save research jobs and create new ones, provide money for training, allow institutions to improve labs.”

Under the program, some grants of which are still to be awarded, Baylor has received more than $37 million, the most in the state; the University of Texas M.D. Anderson Cancer Center more than $29 million; and the UT Health Science Center at Houston nearly $24 million.

The National Institutes of Health is awarding the grants.

Baylor and M.D. Anderson are waiting on the awarding of grants involving the Cancer Genome Atlas project, an effort to understand the genetic underpinnings of cancer.

The program includes $175 million for the national project, and Baylor and M.D. Anderson are expecting more than $10 million apiece.

Richard Gibbs, director of Baylor's human genome sequencing center, said the cancer genome project is “going fabulously” and should produce diagnostic tests that replace existing ones in a few years.

Gibbs said that when all is said and done, the additional funding will double the Baylor's center's $50 million budget.

The biggest individual winner of the stimulus funding was Eric Boerwinkle, a UT-Houston geneticist who has spent much of his career studying the reason why heart disease runs deep in some families but not others.

The awards announced Wednesday included more than $12 million for a research project he's leading into genetic susceptibilities to heart, lung and blood diseases.

$14 million grant

Still to be announced is Boerwinkle's grant for the project's second year — an additional $14 million. It is the biggest single grant in Texas and one of the biggest in all states.

Work on grants typically doesn't begin for months after they're awarded, but Boerwinkle said his “official start date is today.”

“We're hitting the ground running,” said Boerwinkle. “That's a must when you need to spend a $26 million budget in two years.”

Boerwinkle said spending would come on equipment, hiring and the preparation of research material.

Under the program, proposals had to spell out how the project would improve the economy.

Risks and rewards

The program also called for high-risk, high-reward projects, a contrast with the more conservative approach usually favored by the NIH.

Officials at Baylor, UT-Houston and MD Anderson all agreed with Obama that there's never been a single biomedical research boost like this before.

Dr. Peter Davies, UT-Houston's vice president for research, said the institution ultimately will receive $45 million from the program in the next two years, a significant chunk considering it got $91 million in traditional funding from the NIH in 2008.

Others getting money

Other local institutions awarded grant money through the program include the UT Medical Branch at Galveston, with $10. 5 million; the Texas A&M Health Science Center, with $6.4 million; the University of Houston; with $3.4 million; and Rice with $3.2 million.

The program is funded through the $787 billion federal economic stimulus program the president signed into law in February.

Obama said the new grants will support 2,000 projects and create tens of thousands of jobs

[R&D and Market analysis of this "game changer" is upon request. Pellionisz; HolGenTech_at_gmail.com].

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Obama, Collins Laud $5B in NIH Stimulus Funds, Much for Genomics

September 30, 2009

By a GenomeWeb staff reporterNEW YORK (GenomeWeb News) – The National Institutes of Health has awarded more than 12,000 grants totaling around $5 billion so far under the economic recovery and stimulus package, the White House said today.

President Barack Obama commuted to Bethesda this morning to announce the funding as a milestone, to unveil a $175 million grant for cancer genomics, and to tour the NIH campus.

In late-morning speeches before a crowd of NIH staff, President Obama, Health and Human Services Secretary Kathleen Sebelius, and NIH Director Francis Collins loosely outlined how the $5 billion in grants over two years — nearly half of NIH’s total $10 billion appropriation under the American Recovery and Reinvestment Act — will stimulate research and create jobs.

A number of genomics-focused programs will be funded under the stimulus package, including $175 million over two years for The Cancer Genome Atlas, a joint effort between the National Human Genome Research Institute and the National Cancer Institute, according to a fact sheet released today by the White House.

“This ambitious effort promises to open new windows into the biology of all cancers, transform approaches to cancer research, and raise the curtain on a more personalized era of cancer care,” Collins said in a statement, describing the TCGA funding as “an excellent example of how the Recovery Act is fueling discoveries that will fundamentally change the way we fight disease and improve our lives.

"We are about to see a quantum leap in our understanding of cancer," Collins said. [This should be taken literally, since the fractal recursive iteration of protein synthesis, because of structural variants in the genome can result in a loss of quantum equilibrium - with the hologenomic entropy hyperescalating - AJP]

NCI and NHGRI will also each commit $50 million in non-Recovery Act funds to the Genome Atlas over this two-year period, according to NCI.

"We know that this kind of investment will also lead to new jobs: tens of thousands of jobs conducting research, manufacturing and supplying medical equipment, and building and modernizing laboratories and research facilities," Obama said in a statement. [Maybe in addition to maintaining or improving the material infrastructure and amassing data that are already close to impossible to interpret, there will be some small change left for "gray matter". After all, if the center of excellence of intellect of "Coppenhagen group" - working out quantum theory - did not exist first, it would have been foolish or outright dangerous to engage in mega-projects to release nuclear energy - AJP]

At the event, Collins told the NIH assembly that the grants "will fund trailblazing research into treating and preventing our most scary diseases.

“Since arriving [at NIH] six weeks ago I’ve spent a lot of time reviewing some of these grants — I wanted to see what was there — and they propose some of the most innovative and creative directions for research that I have ever seen in 16 years at NIH,” the new NIH director told the crowd.

More than $1 billion of the grant funding is dedicated to using technologies developed through the NIH’s genomics programs, specifically through the Human Genome Project, the White House said.

For cancer, heart disease, and many other areas, researchers will use Recovery Act funding for genomics and genetics-based research approaches to pursue knowledge about these diseases.

According to the White House, over the two years of recovery funding NIH stimulus grants will support studies including:

• Seeking to use microRNAs to predict which patients have tumors that will spread throughout the body;

• Conducting genomic sequencing of individuals with autism and their parents in order to find causes for the disease in the genome and in the environment and to develop and test diagnostic screening tools;

• Cataloging genetic [genomic - AJP] changes associated with oral cancer in order to identify and guide treatment of pre-malignant lesions;

• Sequencing the genomes of more than 10,000 individuals with known risk factors for heart disease in order to identify those risk genes; [that are affected by derailed hologenome regulation - AJP]

• Comparing the genomes of individuals with high and low HDL cholesterol levels in order to accelerate development of drugs that reduce the risk of heart attack;

• Examining the genes [genomes - AJP] of more than 7,000 heart failure patients to identify variants that will enable doctors to identify those at risk for heart failure;

• Identifying genetic [genomic - AJP] markers for increased risk of hypertension, obesity, cardiac hypertrophy, and kidney failure in African Americans;

• Finding markers that circulate in the blood that may signal the onset of a plaque rupture or of thrombosis;

• Analyzing biomarker and genetic [genomic - AJP] data from international atrial fibrillation patient pools in search of markers to identify patients that will benefit from statin therapy.

[R&D and Market analysis of this "game changer" is upon request. Pellionisz; HolGenTech_at_gmail.com]
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NIH Grants $45M for Genome Science Centers [Bye-bye Crick's "Central Dogma"- AJP]

[Beginning to "re-think long-time beliefs" - AJP in peer-reviewed paper, presented to public, and peer-reviewed acceptance in Cold Spring Harbor]

September 28, 2009

By a GenomeWeb staff reporter

NEW YORK (GenomeWeb News) – The National Institutes of Health has pledged $45 million in grants to establish two new genomics centers at the University of North Carolina at Chapel Hill and at the Medical College of Wisconsin (MCW), as well as to continue funding existing centers at Johns Hopkins University and at the University of Southern California.

The two new Centers of Excellence in Genomic Science at UNC and MCW will pursue genomics studies of mental health and gene regulation, respectively. [Non-Euclidean "Geometrization of Neuro- and HoloGenome sciences" may be helpful - AJP]

Under the new grants, MCW will receive around $8 million over three years and UNC will reap around $8.6 million over five years from the National Human Genome Research Institute and the National Institute of Mental Health.

Johns Hopkins' genomics center will receive around $16.8 million over five years to continue epigenetics of disease studies and USC will use around $12 million over the same period to conduct computational and informatics-based research of genetic variation and disease.

"Our aim is to foster the formation of innovative research teams that will develop genomic tools and technologies that help to advance human health," NHGRI's Acting Director, Alan Guttmacher said in a statement. "Each of these centers is in a position to tackle some of the most challenging questions facing biology today."

The grant to UNC will support the Center for Integrated Systems Genetics (CISGen), where scientists will seek to identify genetic and environmental factors that underlie and contribute to psychiatric disorders.

CISGen will use mouse models and computational biology to study genetic and environmental factors of such disorders, and it will develop new mouse strains specifically to study relevant behavioral traits. These models will serve as a resource of genomic studies screening for genetic variants that are linked to human psychiatric disorders.

"We can use the mouse to narrow the search space from billions of possibilities to only hundreds or even dozens," CISGen co-director and UNC Assistant Professor Fernando Pardo-Manuel de Villena said in a statement. "It's like the PowerBall when you know four or five of the six numbers for sure."

"We chose the hardest problems out there, the ones that have been most resistant to scientific inquiry in humans," explained Patrick Sullivan, CISGen's other co-director and a distinguished professor at the UNC School of Medicine. "We chose to study mouse versions of psychiatric traits potentially relevant to autism, depression and anxiety, and antipsychotic drug side effects and response to treatment."

In Wisconsin, the new center is a collaboration between the Medical College of Wisconsin, the University of Wisconsin, Madison, and Marquette University.

The team at MCW will focus on developing tools for analyzing the proteins that bind to particular DNA regions in an effort to understand the relationship between changes in protein-DNA interactions.

"What is needed, and what we will develop in this center, is technology that is able to identify all of the proteins that are interacting with the genome, even if we do not know in advance what their function may be," said the center's co-Director, Michael Oliver, a professor at MCW's Biotechnology and Bioengineering Center and the Human and Molecular Genetics Center.

Other NIH-funded Centers of Excellence in Genomic Science include centers at the California Institute of Technology, Harvard Medical School, Stanford University, Arizona State University, Yale University, and the Dana-Farber Cancer Institute.

[When Crick's (false) "Central Dogma of Molecular Biology" (i.e. "information transfer from proteins to DNA 'never happens'" - see Pellionisz, 2009, Fig.7 ) was shaken in 1970, Crick upped the ante "such a finding would shake the whole intellectual basis of molecular biology". Also, Ohno came to the rescue with his "Garbage DNA" (1970) and "Junk DNA" misnomers (1972), implying that even if such recursion would happen, it would only find "Junk DNA" whose "importance is doing nothing" - see Fig. 3. While "shaking the intellectual basis" was thus fended off a generation ago, Francis Collins started ENCODE in 2003, to conclude in 2007 that "the scientific community will need to rethink some long-held views" (ref. in Pellionisz, 2008). Some lucky few did not have to "re-think", since never believed neither the "Central Dogma"nor the "Junk DNA" false axioms in the first place, and came up with the (recursive!) fractal model of brain cell as early as in 1989 - punished for double heresy by denial of NIH grant continuation - but laying down the theory of recursive fractal iteration of (holo)genome function. With Francis Collins now at the helm of new NIH, research along "new thinking" is amply rewarded for some. - Pellionisz; HolGenTech_at_gmail.com, Sept. 29, 2009]

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David Duncan Has a Prescription for American Health Care

Thursday, 17 September 2009

[David Ewing Duncan - survival of the fiercest in prevention - AJP]

The 13th Annual Scientific Meeting of the Heart Failure Society of America (HFSA) today featured a discussion by David Ewing Duncan titled "One Man's Quest for Personalized Medicine." Over the course of one year, Duncan submitted himself to hundreds of tests that could predict and even prevent future illness.

One test made predictions about the health of Duncan's heart. By gathering data on his cholesterol levels, a heart CT scan, a genetic profile, and more, the test showed personalized predictions that were specific to Duncan's genes and physiology. One scenario showed Duncan's risk of heart attack at 70% over the next twenty years. That forecast changed dramatically if Duncan maintains his current weight instead of gaining the typical pound per year for a man over 40. With a steady weight, the risk fell to about 2 percent and with cholesterol lowering statins, Duncan's risk fell to zero.

"Many of these tests aren't ready for the general public, but they do give us an interesting glimpse into the future of medicine," said Duncan. "People are curious as to where this technology is going and we may never know unless we provide the organized push needed to learn more."

This specific test would cost nearly $1000 as demand increases but Duncan points out that a diagnostic cardiac catheterization can cost more than $25,000 and a heart bypass operation runs well over $85,000. The cost also has to be weighed against the 80 million Americans suffering from heart disease and the fact that nearly $450 billion was spent last year in direct and indirect costs for treatment of heart disease.

"David Duncan's journey through the American Health care system as a healthy person illustrates one of the major problems facing the American health care system today. That is, as health care professionals we recognize that it is imperative to identify patients who are at risk for developing heart disease, and then implement personalized strategies to reduce this risk," said Dr. Douglas Mann, HFSA President. "However, the upfront costs associated with screening large populations of patients with some of the emerging technologies may not be sustainable in the future. As we move forward in our efforts to prevent heart disease and heart failure, it will be essential to obtain outcomes data that identify the most cost effective and accurate strategies for identifying the patients who are at risk of developing heart disease and heart failure, as well as personalizing our approaches to these patients."

New Survey Finds Alzheimer's Disease a 'National Priority,' with Voter Support Across Party Lines for Congressional Action and Faster FDA Review of New Therapies

- Survey also finds concern over cost of care and strong voter willingness to make Alzheimer's an issue at the polls -

WASHINGTON, Sept. 24 /PRNewswire/ -- A new voter survey sponsored by the ACT-AD Coalition (Accelerate Cure/Treatments for Alzheimer's Disease) finds that three-quarters of Americans nationwide and across party lines say it is personally important to them to find a cure or to prevent Alzheimer's disease, while a similar proportion of the national electorate say they look to Congress to make it "a national priority" to speed up the Food and Drug Administration's (FDA) review process in specific ways for therapies that slow, halt or reverse the disease. Voters in large numbers also said that they would not be able to cover the personal cost of Alzheimer's care and that they were ready to reward or punish elected officials at the polls based on their willingness to act on Alzheimer's now.

The survey was conducted jointly by the bipartisan team of Lake Research Partners (D) and American Viewpoint (R). Findings were presented today at the Rock Stars of Science Capitol Hill Briefing, sponsored by Geoffrey Beene Gives Back((R)), Research!America , Alzheimer Association, Wyeth, and Elan; and made possible with the cooperation of The Congressional Biomedical Research Caucus and the Alzheimer's Caucus. The briefing united leaders in medical research including the Director of the National Institutes of Health, Francis S. Collins, MD, PhD, and rock star Joe Perry from Aerosmith, to rally lawmakers to increase funding for medical research priorities like Alzheimer's, cancer, HIV/AIDS and genomics.

According to Celinda Lake, President of Lake Research Partners, "There is clear voter support for action on Alzheimer's Disease. This survey sends a message to elected officials that Alzheimer's has captured the nation's attention, and that it may prove to be an important electoral issue."

Dan Perry, President of ACT-AD, a coalition of national organizations seeking to accelerate development of potential cures and treatments for Alzheimer's, believes that the survey reflects "the beginning of an Alzheimer's challenge from the American voter. We are on the verge of becoming the next generation of Alzheimer's casualties, and yet we have access to the same number of treatments to slow or stop the disease that our parents and grand parents had - none. Add to this treatment vacuum the fact that the recession leaves Americans with lower personal savings and a near-bankrupt healthcare system that is ill-prepared to manage the coming Alzheimer's explosion. It should come as no surprise that Americans are telling their representatives to find answers to this problem before it is too late."

Survey Findings

According to the survey, voters nationwide and across the political spectrum believe:

Alzheimer's is a personal and national priority.

76 percent of voters nationwide say it is personally important to find a cure for Alzheimer's and 77 percent believe it is personally important to prevent Alzheimer's disease. Sentiment is similar across party lines [Note that Prevention takes precedence over Cure! - AJP].

79 percent want Congress to make it "a national priority" to speed up the FDA's review process for therapies that slow, halt or reverse the disease.

FDA review policy on Alzheimer's should reflect this priority.

In the past, the FDA has accelerated its review programs for life threatening diseases like HIV/AIDS and cancer in order to bring urgently needed therapies to patients without sacrificing safety. The survey suggests that American voters now support the same priorities for Alzheimer's therapies.

47 percent of voters nationwide think the FDA should make all possible Alzheimer's treatments available and allow patients and doctors to decide about risks and benefits, and another 28 percent believe promising drugs for Alzheimer's deserve the same priority status and fast track review by the FDA as promising drugs for other life-threatening diseases.

A minority of 15 percent think the FDA should continue to use current procedures of delaying a therapy until it is determined to be completely safe.

Without treatment breakthroughs, Americans cannot cover the cost of Alzheimer's care.

56 percent of voters nationwide said that they are not confident that they would be able to cover the cost of long-term Alzheimer's care if they or a loved one were diagnosed, with over a third (35 percent) saying they are not at all confident about covering the cost.

Financial assistance will be needed to pay for Alzheimer's.

72 percent strongly favor expanding Medicare coverage to include Alzheimer's therapies and services in non-traditional settings like the patient's home.

71 percent strongly favor tax deductions for long term care insurance.

68 percent strongly support allowing parents under 65 who have been diagnosed with Alzheimer's to be claimed as dependents by their children.

63 percent strongly support tax incentives to caregivers whose parents have Alzheimer's.

American voters across party lines are ready to make Alzheimer's drug review an issue at the polls....

About ACT-AD

ACT-AD is a growing coalition of more than 50 national organizations representing patients, providers, caregivers, consumers, older Americans, researchers and employers seeking to accelerate development of potential cures and treatments for Alzheimer's. The Coalition is directed by an Advisory Council made up of representatives from Alliance for Aging Research (AAR), Alzheimer's Foundation of America (AFA), American Society on Aging (ASA), National Alliance for Caregiving (NAC), National Association of Area Agencies on Aging (n4a), National Consumers League (NCL), Research!America, and the Society for Women's Health Research. The Coalition is supported by educational grants from Wyeth, Elan, Pfizer, Eli Lilly, and Medivation.

[People have spoken. We all are likely to die - but it is not indifferent at all if that inevitable event will take with Alzheimer's, Parkinson's, Cancers (etc) decades of suffering and misery of not only the affected, but devastates families and ultimately societies. By proper focus on prevention of the most dreadful ways of passing away, we can have a populus that is active and happy till the inevitable comes upon us. - Pellionisz; HolGenTech_at_gmail.com, Sept. 27, 2009]

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Habits to Help Prevent Alzheimer's - How to lower your risk.

Los Angeles Times
September 17, 2009

People may be able to reduce their risk of developing Alzheimer's disease, according to two recently published studies that are the latest in a long line of research. But does that hold for everyone? And by how much can you lower the risk? Here's a look at the facts.

Alzheimer's afflicts 5.3 million Americans and that number is predicted to grow to nearly 8 million in the next 20 years, according to a 2009 report by the Alzheimer's Assn. Because the disease has no cure, medical researchers continue to focus on preventing or delaying the disease.

Two weeks ago, a paper in the journal Dementia and Geriatric Cognitive Disorders reported that people with even moderately elevated cholesterol in their 40s have twice the risk of developing Alzheimer's disease in their 60s, 70s and 80s, adding blood cholesterol to a variety of already-known risk factors for the disorder.

High blood pressure, diabetes, obesity, smoking and high-fat diets have all been associated with increasing one's risk. Last week, a paper in the Journal of the American Medical Assn. reported that people eating a so-called Mediterranean diet and exercising regularly were at lower risk -- by as much as 50%.

And in earlier studies, other lifestyle factors -- such as doing the daily crossword puzzle or other intellectually stimulating activities, maintaining an active social life and getting a college education -- have been associated with lowered Alzheimer's risk.

The recent cholesterol study was large and long -- 9,844 Californians were followed for three decades -- and the data are striking. People with high cholesterol -- 240 or higher -- were 57% more likely to develop Alzheimer's disease. Those with borderline range cholesterol -- 200 to 239 -- were 23% more likely.

Still, this is an association at best. No one can say that high cholesterol causes Alzheimer's disease: Other factors linked to it in some way could be to blame. Also not known is whether lowering cholesterol -- for instance by taking statin drugs -- would be protective.

"An association is hypothesis-generating -- it allows us to begin looking at why that relationship might exist," says Dr. Jeffrey Cummings, director of the Mary S. Easton Center for Alzheimer's Disease Research at UCLA. One possible clue comes from animal studies: Neurobiological studies have found that high cholesterol in the blood may trigger more of the brain-clogging substance beta-amyloid protein

The diet and exercise study reported last week was smaller and shorter. In it, 1,880 elderly New Yorkers were followed for an average of 5 1/2 years. It found exercise alone was linked to as much as a 50% reduced risk, diet alone by as much as 40%.

This is not the first study to suggest that diet and physical activity may be protective. The Mediterranean-type diet "combines several foods and nutrients potentially protective against cognitive dysfunction or dementia, such as fish, monounsaturated fatty acids, vitamins B12 and folate, antioxidants (vitamin E, carotenoids, flavonoids), and moderate amounts of alcohol," the authors wrote.

There have been very few studies that meet the gold standard of human trials, in which people would be randomly assigned to either receive an intervention or not, then followed into their senior years to see if they develop Alzheimer's. Of trials that have been completed, no clear preventive treatment has been identified.

...

Certain naturally occurring neuroprotective substances are stimulated by physical activity, Cummings says. "So there are direct neurobiological effects of exercise that go beyond just better blood flow."

These effects of lifestyle on Alzheimer's are not yet proven. But -- in contrast to long-term drug treatments -- there is virtually no downside to recommending them, experts say.

Cummings says he often fields questions from families of his patients about what they can do to prevent the disease from happening to them. He recommends supplements of vitamins C and E and omega-3 fatty acids, exercise three times per week for 30 minutes and taking care of one's cardiovascular risk factors such as blood pressure and cholesterol.

Even in people with genetic predisposition for developing Alzheimer's (those who carry the apolipoprotein E-e4 gene have a doubled risk), lifestyle changes can make a difference, Cummings says.

"My experience is that people who know that they're at genetic risk take the environmental interventions much more seriously."

Debra Cherry, executive vice president of the Alzheimer's Assn. California Southland Chapter, says that when she served on the Healthy Brain Initiative, a government workshop seeking evidence-based recommendations for reducing risk, the strongest case made was for aerobic activity.

"I don't know if anyone will ever be able to do a randomized, controlled study, but the evidence is pretty strong that aerobic exercise protects again heart disease and brain disease," she says. "And there's very little risk to doing it."

[R&D and Market analysis of this "game changer" is upon requiest. Pellionisz; HolGenTech_at_gmail.com, Sept. 27, 2009]

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Point of Inflection at the Cold Spring Harbor Laboratory' "Personal Genomes" Conference

[James Watson and Andras Pellionisz in Cold Spring Harbor Laboratory, Sept. 17, 2009]

A presentation of the embraced "Fractal Approach" according to the "Principle of Recursive Genome Function" that thinks outside the DNA>RNA>PROTEIN box. A list of organizers, keynote speaker, list of presenters and list of some attending without presentation is available here.

[Opening Keynote Speech and Introduction on Monday, September 14. was given by Prof. George Church (Harvard) "Setting the Tone for Personal Genomes" - envisioning a "zero dollar sequencing" with emphasis shifted to understanding of function of genome-epigenome, with the use of an unprecedented avalanche of data, analyzed both by brute force and somewhat smarter ways. Keynote Speech on Tuesday, September 15. was by C. Thomas Caskey (University of Texas Health Science Center) "Inflection point for genome science". Dr. Caskey put our field into the stunning historical perspective - likening advancement of technology to that of the aviation and satellite revolution, by the revolutionary work of Howard Hughes (personally witnessed by Dr. Caskey...). As the following masterpiece quad of articles by Bio-IT World (Kevin Davies) will cover, "Genome Computers" will mark the point of inflection, with the cost of sequencing plummeting and the amount of information skyrocketing. Core is an algorithmic understanding of HoloGenome regulation.

It may help recalling not only precedents of "point of inflection" in different fields (aviation and satellites, as even this columnist transitioned Neural Network algorithms learnt from the little brain of birds to fly F15 fighters with parallel computer control for NASA) - but also at least two precedents in Genomics itself.

It is arguable that the Venter-Collins duel of Government and Private industry in the "Human Genome Project" to yield an official "tie" hinged upon computing (summed up by the wry humor of Craig, answering the question "what is the difference between God and you?" - "We had computers!"). While Dr. Collins focused on "God's language" in an extremely wide coalition (that, by definition, resulted in a computing infrastructure that perhaps could be characterized by the word "scattered", Dr. Venter's sprint was a laser-beam focused effort to create, almost from nothing, the world's most powerful and advanced genome computing environment (both in terms of hardware, software and algorithms).

Another example is the triad of "Shotgun Sequencers" (Applied Bio's SOLiD, Roche's 454, and Illumina's Genome Analyzer). In retrospect, since we are at the point of inflection towards nanosequencing by Complete Genomics, Pacific Biosciences, Oxford Nanopore, Helicos (with no end of the list in site), one could perhaps risk the analysis that it would have been better if AB/454/Illumina would not have to develop themselves their "on rig" IT (since none of the trio was, or even aspired to become "a leading computer company") - but "Big IT" would have picked up the challenge, providing perhaps better, but certainly more uniform and standard, wide-range IT service.

Future will hinge to a great degree if "agnostic" but highly "genome informatics savvy" initiatives, e.g. such as HolGenTech's "brute force friendly but also algorithmic-preferred" initiative is scaled appropriately to face our common challenge - Pellionisz; HolGenTech_at_gmail.com, Sept. 23, 2009]

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Kuberre: Think Outside the Box

Bio-IT World
By Kevin Davies
September 17, 2009 |

FPGAs move from financial services to life sciences.

At about 3 cubic feet, the box sitting in a corner of Kumar Metlapalli’s modest office in Andover, Mass., doesn’t necessarily strike me as a “next-generation supercomputing platform.” But the box, or HANSA, might be the biggest thing to hit high-performance computing in a long time.

The founder of Kuberre Systems, Metlapalli is an avid proponent of FPGAs (field programmable gate arrays), a chip that can be programmed to provide far greater specificity and efficiency than traditional CPUs, yet offer a more affordable solution than large grids with hybrid blades a super computers.

HANSA has a scalable architecture that can include from 4 to 64 FPGAs in a 9u cabinet ranging in price from $50,000 to $500,000. It combines a new hardware design and rich software stack for use in the HPC market with a memory that scales up to 256 GB. It delivers the equivalent of a 768-CPU server grid or a 1,536 core supercomputer, at 1/3 the cost, with 2% of the energy requirements, and 1% of the floor space.

While Kuberre has carved a niche in the financial services sector, cracking the life sciences market is both a top priority and a tough challenge. “We’re getting there, but we need to build those relationships,” Metlapalli admits.

Passage from India

An electrical engineer by training, Metlapalli moved to the United States from India in 1991, got his Masters degree in computer science from the University of South Carolina, specializing in image processing. He worked for XyVision before being recruited as a “quant” for Wall Street, predicting trends based on historical data.

The idea for HANSA, which means swan (think “Lufthansa”) but also stands for Hardware Accelerator for Numerical Systems and Analysis, came in 2006, while Kuberre was providing a unified platform for financial markets. Kuberre’s sister company in India had built an accelerator card for BLAST utilizing FPGAs. Metlapalli quickly targeted the benefits of FPGA technology to financial services, but recognized the danger of becoming a black box. Given the programming flexibility of FPGA platforms, Metlapalli opted to design a software stack on top of the FPGAs, so that users can write algorithms in their native languages (see, “Swan Structure”). “We can’t be building singleton solutions,” Metlapalli said. “The library must work across verticals and provide flexibility.”

The HANSA architecture makes use of the scaLAPACK library, originally written for supercomputers or clusters, which breaks up matrices into submatrices, and lets them compute and combine.

One application Metlapalli is convinced will work on HANSA is GWAS (genome-wide association studies.) GWAS calculations are giant matrices with hundreds of thousands of values (SNPs). On HANSA, Metlapalli says “one doesn’t have to take shortcuts. You have 256 GB memory to host the data you need, the compute power you need.”

FPGAs have been around since the ’70s, but seen little application in life sciences. One exception is Scott Helgesen, who featured them in the original software for the first 454 Life Sciences sequencer. The massive parallelism of FPGAs is finding particular use in military applications such as digital signal processing and Fourier transforms.

FPGAs are one increasingly popular flavor of hybrid computing, which complements CPUs with chips such as a GPU or FPGA. Metlapalli says he’s flipped the role of the CPU, so that the CPU becomes the co-processor, and the majority of operations are performed on the FPGAs.

Unlike a CPU with millions of gates die cast, an FPGA has millions of gates controlled via software. “You’re programming the chip to perform what you want to perform, in the most optimal fashion. I take FPGA, put a software code on top of it, and everything runs on the hardware.” More logic in hardware translates to more acceleration. With FPGAs, “essentially you can transform one’s personality based on the application you’re solving.” A binary search might take 1000 gates, but because the FPGA has 1 million gates, one can optimally dedicate a particular number of cores for the search, while performing secondary searches in parallel.

Get a Life

Metlapalli doesn’t want to be constrained to a single industry. “To pick one vertical, we’d be doing a disfavor to the platform,” he says. “I want pharma to know this solution exists.”

One early prospect is an outsourcing vendor in India that works with most big pharmas. Kuberre is putting together a “business initiative document” under NDA. “They already have an idea of what they want to build,” says Metlapalli, indicating molecular comparisons using tools such as JCHEM. “Think of drug discovery as a funnel—the narrower you make the funnel, the faster the process. That requires more sophisticated computation.”

As for genome centers, Metlapalli says, “We strongly feel that the genome centers need a box like HANSA.” Metlapalli says he’s had encouraging discussions with Matthew Trunnell at the Broad Institute, but “the challenge has been allocating the research resources to look and see how the solutions will be built on this platform.”

With HANSA providing the equivalent of 2.5 racks of nodes, 80 inches tall, at your desk, Metlapalli is convinced that HANSA’s efficiencies can knock out clusters. The challenge is in “motivating these people and getting enough of their time to look at the box and build a solution on top.”

Despite all the hype over cloud computing, Metlapalli says HANSA offers a cost-effective alternative by providing the compute processing at the point of collection. “Take it, collect it, process it… It has the computational power to bypass cloud computing.”

“If you have a cluster or cloud, HANSA could be one of the nodes on that. If you need a departmental supercomputer, this is what you need.” It provides the equivalent of 1500 processors or 700 blades.

For example, Metlapalli claims HANSA offers a 1000-fold improvement in the BLAST search algorithm. Based on work for a previous client on a single board with 4 FPGAs, Metlapalli saw an 80X performance boost. “We have 16 boards in HANSA. So it’s 16x80, or 1280 or so.” If you take out the latencies between the boards, maybe 1000X. But life science customers “really don’t care” because BLAST makes up a small piece of their workflow. “They’d rather know how HANSA can solve their own workflow issues.”

As a privately funded company, Kuberre runs “a very lean and mean operation,” which is why Metlapalli is reluctant to build demo units. Instead, he challenges potentially interested researchers: “Give us a problem you’re not able to solve. We’ll do the legwork, build the prototype. Tell us that you’re going to buy it! That’s all we need. Just need an hour’s worth of time, saying what the problem is, give us the sample data, this is how the algorithm should work. Boom! We’ll do the rest.”

Swan Structure

The HANSA architecture consists of four layers. On the bottom is the physical hardware—16 boards, each containing four FPGAs. (Each FPGA has 12 processors talking to one memory bank, 12 talking to the other.) The next layer consists of expandable firmware building blocks (for example a binary search algorithm), so users do not have to deal with VHDL. Then comes a C/C++/JAVA API layer, so one of these APIs could be used in multiple building blocks underneath it to execute the programs. The icing on the cake is the user’s own applications and custom algorithms.

“What we’ve done is provide level of flexibility they need to build their own algorithms in their own native languages,” says Metlapalli. “No one has thought about building a supercomputer utilizing so many FPGAs together in a single box, or how to utilize with a software stack to solve problems.”

Out of the 16 FP[G]A boards in the box, five could be doing Monte Carlo simulations, six doing intense numerical algorithms. The other boards might capture streaming data. “That’s what you can partition through the software. In one box, you’re dividing the personalities of HANSA into sub personalities.” One might be numerical algorithms, another might be pattern matching.

HANSA contains programming capability for C/C++, MatLab, R, and Java. “Imagine running 768 legacy C/C++ programs in parallel without having to make any changes to the legacy code, just do a recompile,” says Metlapalli. Users might want a core library such as BLAST, Smith-Waterman, etc. “We don’t want to build the entire conformation on the FPGA side. I want to provide a library so they can write their own algorithms.” Kuberre provides the ScaLAPACK Library for use out of the box. “But if you want your own custom algorithms, we’ll build those for you.” K.D.

[R&D and Market analysis of this "game changer" is upon request. Pellionisz; HolGenTech_at_gmail.com]

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SMRT Software Braces for the Pacific Biosciences Tsunami

September 22, 2009
Bio-IT World
By Kevin Davies

September 18, 2009 | Earlier this year, Pacific Biosciences founder and CTO Stephen Turner ran an animation of a real-time single-molecule sequence trace as a crawl at the foot of his slides for the duration of his talk, demonstrating not merely the impressive length of DNA reads the company could generate, but also its slightly hypnotic quality. “I do hope that some of you will watch the rest of the talk,” Turner said.

The cute animation was devised by a member of Scott Helgesen’s software group at PacBio, which is not surprising. A decade ago, Helgesen and Brad Carvey composed the opening dragonfly CGI sequence for Men in Black, before Helgesen traded New Mexico for New England and a job with 454 Life Sciences.

Helgesen is now part of the software team, headed by VP Kevin Corcoran, that PacBio is depending on to handle the data from PacBio’s single-molecule sequencer next year. The third-generation sequencing system eavesdrops on a grid of DNA polymerase enzymes, tethered to the bottom of nanoscopic wells, as they synthesize DNA strands in real time. As each fluorescently tagged base is snared by the polymerase prior to being incorporated in the new DNA strand, its signal is detected. The method is dubbed single molecule, real time (SMRT).

The vital job of capturing that information and producing the informatics pipeline that converts those signals into pure sequence falls to Corcoran, who together with Helgesen, has ties with almost every competitor in the market. Corcoran formerly ran the sequencing business for Applied Biosystems (AB), and was involved in AB’s due diligence of its own next-gen sequencing acquisition, Agencourt Personal Genomics. He was previously the CEO of Lynx, which merged with Solexa in 2004, two years before Illumina acquired the new entity. Helgesen, director of software engineering, primary analysis and simulation, spearheaded software development at 454 for several years, until leaving in 2006, just as the first Genome Sequencer was released.

Real Time Analysis

PacBio has a fairly large instrumentation software group that writes hard-core firmware and builds real-time operating systems. Once acquired, the data are passed onto Helgesen’s group, which handles the primary analysis—image processing, signal processing, base calling and quality value assignments. From there, the sequence data are subjected to secondary analysis, including consensus calls and assembly.

“The biggest challenge is real-time processing of the data,” says Helgesen. “The data rates—the amount of data that comes flooding from the sensors—are really high compared to 454, much higher because we’re looking at real-time events.” Unlike at 454, where Helgesen used a CCD camera to integrate photons over time and under his control, “Now, we’re not in charge of the events happening—the molecules just do their thing and we have to watch them.”

One of Helgesen’s passions at 454 was the use of FPGA (field programmable gate array) technology. He’s circumspect on whether he sees a niche for the hybrid computing solution, but Corcoran says: “We’ll either go down the FPGA route or some of these other alternatives. Graphics GPUs are becoming very affordable and more easily programmable.”

For the prototype research instrument, which measures 3,000 DNA polymerase enzymes running in parallel, the software team has to capture the data in real time but doesn’t need to process in real time. When the commercial instrument launches in 2010, however, “the spec for the production system for shipping is capture in real time and process in real time, to keep the throughput going,” Helgesen says.

Helgesen says the processing throughput trade-off is the length of each DNA fragment and the numbers of parallel fragments going on simultaneously. The scheme is scalable, which is neat. “The big issue is the data are coming in so fast, you don’t have time to store it to disc. You cannot capture the original raw signal data, so you have to process that—first-level data reduction in real time. Even when I interviewed here and heard the number, I was like, ‘Man…!’”

Handling that problem is a concerted IT strategy, involving computers with internal blades, data reduction strategies, algorithm optimization, and more.

Reads and Errors

Late last year, PacBio published examples of its first single-molecule sequencing results in a paper in Science. The single-read errors were on the order of 15-20%, but those data were generated almost 12 months ago. “The interesting thing about single-molecule sequencing is that errors are random verses systematic,” says Corcoran. “In Sanger reads, the errors start to get worse the farther you go out. We don’t see that phenomenon.”

Another benefit of PacBio’s approach is molecular consensus. By circularizing the DNA template into a so-called SMRTBell, the polymerase could figuratively “take a couple of laps around the circular molecule, [so] you get phenomenal consensus accuracy of one particular molecule.” Turner reported individual reads of several thousand bases earlier this year.

Corcoran says a priority is to drive up the raw accuracy rates as high as possible. The consensus sequencing mode would by definition reduce throughput, but provide additional fidelity when searching for rare mutations. “In Scott’s pipeline, he has huge amounts of raw movies,” says Corcoran. “He has to identify where all the pulses are, assign a base to that pulse in real time, and then, if it’s a molecular consensus run, assign a consensus value to that particular read.”

As for the sequence traces themselves, Corcoran says customers will have the option of saving them, “but they’ll have to be saved off onto some system they provide. We’ll stream them off the instrument in real time as we’re processing.” More likely, they will go down a level and save the base calls and associated confidence values.

I asked Helgesen how PacBio compared to the nostalgic days at 454? “It’s definitely more challenging.” At PacBio, Helgesen has a team that is “really strong on simulation, figuring out everything beforehand.” “The best thing about Scott,” adds Corcoran, “is that I was explaining what I was looking for, [and] he instantaneously knew what all my problems were!”

Been There…

Kevin Corcoran was a software engineer at Applied Biosystems who became head of Genetic Analysis software group. In 1992, AB spun out Lynx (see, “Just Bead It,” Bio•IT World, Feb 2004) to develop antisense therapeutics, but redirected efforts to develop short read sequencing based on technology developed by Nobel laureate Sydney Brenner. “It was the first massively parallel sequencing in a big way—we were doing 2 million events,” says Corcoran. The MPSS (massively parallel sequencing system) produced 24-base reads, used mainly for transcriptome profiling. The technology had its challenges, but “as a service, it worked very well.”

However, the technology was way ahead of its time. “You were talking to people and trying to explain the benefits of digital expression. Today, everybody gets it! The technology was ten years too early.”

In 2003, Lynx and Solexa jointly bought the assets of a Swiss company called Manteia. With Lynx running out of money and Solexa in need of engineering expertise, they entered into a transatlantic reverse merger. “It made perfect sense,” says Corcoran. “Since we both jointly owned the Manteia technology we both had guns pointed at each others’ heads. They had cash; we were a public company.” The newly public Solexa was then swallowed up by Illumina.

Corcoran opted to return to AB and run the sequencing business for a couple of years. One of his duties, along with Andy Watson, was to identify prospects for AB’s next-gen platform. “AB had a big program, looked at a wide range of technologies. We settled on Agencourt Personal Genomics. We did due diligence on a lot of technologies.”

After that, Corcoran took ten months off and “recuperated.” But with several ex-colleagues reveling at PacBio, he inevitably got the call. Still, he admits to being “very curious about our friends at Oxford Nanopore,” having gotten to know Clive Brown and John Milton during the Solexa merger.

Helgesen’s interview at PacBio was far different than his job interview at 454, where all anybody wanted to know was how he came to create the special effects for the first two minutes of Men in Black! Joining 454, his first taste of biotechnology, Helgesen had no idea if building next-gen sequencing software was possible. “Now, after going through that experience, I’m used to that situation. I’m not as nervous about it. I’m a software engineer.”

Before joining PacBio, he did talk to 454 founder Jonathan Rothberg about his latest venture, Ion Torrent Systems, but Rothberg couldn’t seal the deal. “No way I want to move back to the East Coast,” said Helgesen honestly. Now he gets to enjoy the California climate, and more importantly, as Corcoran points out, join more than “200 people who understand where you’re going. Everybody has this idea of their responsibility.”

[R&D and Market analysis of this "game changer" is upon request. Pellionisz; HolGenTech_at_gmail.com]

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Brown & Oxford Nanopore

Bio-IT World,

Sept. 22, 2009
By Kevin Davies

September 22, 2009 | Whether Clive Brown, vice president of development and informatics for Oxford Nanopore Technologies (ONT), is indeed “the most honest guy in all of next-gen sequencing,” (as described by The Genome Center’s David Dooling), is perhaps debatable. But as someone who has already stamped his mark on the sequencing world, his views certainly count for something.

Five years ago, Brown was the director of computational biology and IT for Solexa, helping to spearhead the British company’s successful entry into the next-generation sequencing market, which spurred a $650-million acquisition by Illumina. After a spell at the Wellcome Trust Sanger Institute, Brown joined fellow Solexa alum, vice president research John Milton in moving to Oxford to commercialize nanopore sequencing. An intriguing subplot to the business of next-gen is whether Milton and Brown can catch lightning in a bottle again.

Oxford Nanopore is based around the pioneering nanopore research of Oxford University chemistry professor Hagan Bayley. CEO Gordon Sanghera remains close lipped about the firm’s platform specs, but an elegant paper in Nature Nanotechnology earlier this year showed that ONT’s nanopores can neatly discriminate between the four bases of DNA, based on the degree of current inhibition across the lipid bilayer (see, “Breathtaking Biology,” Bio•IT World, Mar 2009). ONT received further validation by inking an $18-million marketing deal with Illumina.

Under the watchful eye of Oxford Nanopore’s communications director, Zoe McDougall, Brown has to be more circumspect than is his true nature. “Things are on track—without telling you what the track is,” he says helpfully. What he will say is that many of the key risks in ONT’s technology have been addressed, and his team has built the entire informatics subsystem of the instrument.

Among the next priorities are to couple an exonuclease enzyme to the nanopore so that it can successively snip off bases from the end of a DNA strand, which will then tumble into the pore and the sequence read. ONT was recently granted a patent for its stable bilayer design. “This is a core element of our nanopore sensing system, not just for DNA sequencing,” says McDougall. Milton calls these bilayers “the workhorse of our nanopore chemistry. We use the bilayer chip to focus on single nanopores and we also operate multiple-channel versions for higher throughput experiments.”

What the Track?

Before ONT can produce an instrument, Brown has to become essentially a small genome center to test the product for months in house. Brown hired his former Sanger Institute colleague Roger Pettett to build up that infrastructure, as well as the software that goes on the instrument. It is “revolutionary new stuff, but we’re reluctant to talk about that at the moment,” says Brown, though he would say, “It does break the conventional instrument software paradigm.”

Brown says the data throughput on ONT’s sequencer will be high, “many tens of Megabytes/second.” Not as high as some high-tech military applications, but “significantly higher than traditional lab equipment.”

“Even before we were running chemistry,” Brown says, “we made software that simulated data streams at launch spec rates. We designed interconnects and wiring, computer boards and live software that would process that data. We did it all in parallel. So when it came to plugging a chip in, it all more or less worked.” But Brown knows from experience that the system must be “very, very flexible to change.”

Another priority is move the data processing close to the point of data generation. ”We have already put a huge effort into not outputting raw data, but outputting optimized processed data instead.” Brown has considered running some of the algorithms on GPUs, but worries about the power consumption demands. “The other option is to use FPGAs. They’re good accelerators, very low power requirements, but a bugger to program and so not very agile.” Brown says FPGAs might be used at the end of product development, but not before. “So far we haven’t had any problems in terms of compute speed when dealing with our data, either at the instrument level or centralized datasets.”

Brown says the data processing simulations have been instructive. “It’s quite early, and we’re not scared,” he jokes. Meanwhile, Brown is quietly checking out potential software partners, which he hopes will deal with the quality scored DNA sequence output. In addition to genome centers and large-scale laboratories, ONT is also targeting the bench-top. “In order to have a bench-top sequencer,” says Brown, “we have to provide pretty easy to use bioinformatics solutions. Otherwise, it’s just not going to happen.”

“One of the problems with all these existing sequencers is, even if you automate the sample prep and make the sequencer easy to use, you still end up with a file with a billion short reads in it. This is still beyond the capability of most non-bioinformatically trained postdocs to do anything sensible with.” ONT aims to generate even more sequence with longer individual reads.

Bench-Side Manner

Brown’s goal is to provide, for want of a better term, a “turnkey” bioinformatics solution sitting alongside the sequencer. Brown has met with several potential partners, including one unnamed company that demonstrated that its “software can deal with a whole human genome-type workflow in a day or 6 hours on a typical workstation.” Brown says that looks quite promising.

He also plans to find a partner to liaise with user IT groups and “help us to smooth the early adoption of lots of our systems. I’m more worried about the bench-top side than the high-end side.” Once ONT is fully launched, Illumina will have a large say in that part of the workflow.

Besides targeting the genome centers and the bench-top sequencer sitting next to a lab researcher, Brown thinks that service organizations such as Complete Genomics might prove another fertile market—in other words, “very large sequencing centers that are not traditional genome centers,” focusing on medical sequencing applications. “I think Complete Genomics is a perfect customer for us. In fact I think our machine’s better suited for what they want to do than theirs is!”

As Brown talks, it sounds as if ONT stands for “on track.” Surely there are problems somewhere? “I don’t want to oversell things, and remember we are still very stealthy as a company,” he responds. As at Solexa, “things just aren’t linear in a company like this. You have days when things work beautifully, and long dry periods when things aren’t working. Half of it is just keeping your nerve.”

Certainly Brown has assembled a strong team to build the IT/informatics infrastructure. Nava Whiteford, another Sanger Institute recruit, is adapting existing algorithms and developing a novel file format called Fast5 for scored sequences. Physicist Stuart Reid is driving data quality measurements and some of the basic science feeding into the platform. Lukasz Szajkowski joined from Illumina to manage the writing of the instrument software, which Brown calls “one of the most risky areas, but it’s all on track thanks to him.” Molecular modeler Mick Knaggs has implemented much of his software on GPU-enabled systems.

I don’t suppose the Sanger Institute is too happy about some of their top people being poached. “Yeah, we did have a chat about my recruitment methods,” says Brown honestly.

--- [full interview] ---

What Can Brown Do For Oxford Nanopore?

Clive Brown, vice president of development and informatics for Oxford Nanopore Technologies (ONT), a.k.a “the most honest guy in all of next-gen sequencing,” as dubbed by The Genome Center's David Dooling, is hoping to catch lightning in a bottle again. Five years ago, he was the head of software for Solexa, spearheading the British company’s entry into the second-generation sequencing market, which spurred a $650-million acquisition by Illumina and early domination of the next-gen sequencing market. After a spell at the Wellcome Trust Sanger Institute, Brown and his fellow Solexa alum, vice president research John Milton, have shuttled over from Cambridge to Oxford to commercialize the astonishing potential of nanopore sequencing. Oxford Nanopore has not yet revealed details of its future platform, but in early 2009, published a lovely paper in Nature Nanotechnology showing that its alpha-hemolysin nanopores can discriminate between the four bases of DNA (not to mention a fifth, methyl C). With a tidy $18-million marketing deal from Illumina, ONT is working on multiple fronts—chemistry, engineering, and of course, IT and informatics. Kevin Davies spoke to Brown about the company’s progress and prospects.

Bio-IT World: Before we get into Oxford Nanopore, what was your reaction to Stephen Quake’s single-molecule genome paper?

CLIVE BROWN: It’s a little bizarre. The main positive message is that they’ve done a single-molecule human genome. This is perfectly worthy of a good Nature Biotechnology paper. The numbers they’re citing give a respectable throughput of about 2 Gigabases/day. The error rates are higher but they’re going to get that with single molecule fluorescence.

But then there’s this Table 1 (Supplementary Information) with old cost claims. Their own cost seems to be exactly what Illumina is citing for their service sequencing now [$48,000]. And it’s bizarre. They’re using the number of names on the Solexa paper [Nature 2008] as evidence of how many people are required to run an instrument! Well, that Solexa paper was the culmination of 8 years work encompassing the entire development of the platform, so it had everybody’s name on it. The CEO’s name was on there, and he didn’t run any instruments.

They’re setting themselves up for a tagline: ‘Look, we only need three people to run a Helicos machine. And Illumina needs all these people and it’s much more expensive.’ If they’d just stuck to the high ground, i.e. they’ve got a working system that does single-molecule genomes, they’d be a lot better off in the credibility stakes. But, this apparent back-door marketing stuff is ridiculous. For example, their original paper had 20 or 30-odd authors for a 6-kb viral genome.

I think Helicos deserves some kudos. They’ve stuck with it, they’ve had a rough time as a company, and they’ve made it work about as good as it can work with single-molecule fluorescence, with the cameras they have. People have taken the technology outside and they’ve used it successfully. And that’s not trivial. If I was them, I’d have stuck to that message. They should stick to the high ground—you can quote me on that.

What progress have you made since your Nature Nanotechnology paper early this year?

It’s difficult to give you specifics without revealing too much, but things are on track—without telling you what the track is! We’ve taken care of a lot of the key risks in our technology. Not all of them, but a lot of them. We’re building things. On the informatics side, we’ve actually built the entire informatics subsystem of the instrument.

One of the things you have to accomplish at a company like ONT or Solexa is to become a small genome center at some point. Before launching a product, you have to run it in house for months, doing genome-center type things. In some ways it’s harder because the system is unpolished, it therefore requires more effort to manage and run and thus certain kinds of software infrastructure are required. Roger Pettett [ex-Wellcome Trust Sanger Institute] is building that infrastructure. He’s also working on software that goes on the instrument itself, which is revolutionary new stuff, but we’re reluctant to talk about that at the moment. It does break the conventional instrument software paradigm.

Does the real-time nature of the nanopore platform make a big difference to the informatics?

What we’re doing in terms of data processing is in some ways easier than Solexa, in some ways harder. Our data rate is much higher—it is many tens of Megabytes/second. If you look at the high-end real-time computing world, it’s in the middle of the data rate range. If you look at high end military radar applications, sonar, etc. we’re two-thirds down that scale. But we’re certainly significantly higher than traditional lab equipment. We decided to tackle this data processing problem very early.

So, we’ve designed and built the basic data processing subsystems very early. Even before we were running chemistry, we made software that simulated data streams at launch spec rates. We designed interconnects and wiring, computer boards and live software that would process that data. We did it all in parallel. So when it came to plugging a chip in, it all more or less worked.

The issue of data reduction close to the instrument is one we tackled very early. But one has to be very careful. When you make one of these products, typically the chemistry evolves all the way to launch, and even after launch. So the way you build things has to be agile and flexible enough to keep up with and optimize against those chemistry changes. So you can’t really build a specification-driven rigid system—it has to be high performance but very, very flexible to change. That’s a real challenge; building a high performance system consisting of hardware and software that can evolve rapidly against real data.

Are you trying to move the data processing close to the chip, and if so, why?

When you scale up, it gets harder to move data over a wire. People are complaining about copying data over a network with the current sequencers. Obviously, just imagine that 100X worse. It isn’t feasible. So you have to move more and more of the processing close to the point of data generation. If you look in other parts of the electronics world, they have the same issues, integrating more and more stuff closer to the point of generation. It’s the same with microprocessors, e.g. Intel CPUs. They put more and more on the silicon. So we have already put a huge effort into not outputting raw data, but outputting optimized processed data instead. That’s not to say you can’t output raw data, my philosophy has always been to have an open system, that lets people dig around in the raw data and algorithms and understand it all but you would need to flick a switch to get the raw data out.

Do you plan to use accelerators such as GPUs or FPGAs?

Two things are going on there. There’s what goes on inside the instrument, and then you have these interim experimental data sets to deal with during the product development phase. So, classically, what you do is write data to disc, and then you have an analysis pipeline that runs on your cluster to look at your data centrally. That’s where the Solexa software came from—the Solexa GA pipeline was actually that, but ended up being shipped for various reasons. We have that pipeline equivalent in house, and have been looking at implementing some of its algorithms on GPUs. For our internal computing needs, there are some attractions to this. But you can’t yet economically stick a GPU inside an instrument, because the power consumption gets quite high.

The other option is to use FPGAs. They’re good accelerators, very low power requirements, but a bugger to program and so not very agile. Once you’ve got your algorithms finished, specifiable, at that point, you can stick it on an FPGA. So FPGA is something we might use at the end of the development process, but not during it.

Bear in mind that standard CPUs are getting faster and faster—they’re not too shabby at all! So far we haven’t had any problems in terms of compute speed when dealing with our data, either at the instrument level or centralized datasets. We haven’t had any problems with that at all, but we are constantly trying to drive up the efficiency of data processing.

Have you started simulating the data processing in real time?

Yes, and it’s quite early, and we’re not scared! But I’ll tell you what’s hard—the hardest bit is the wiring! Wiring two bits of circuit board together… The processing side isn’t so bad, it’s all the interconnects, moving data from A to B. We’re building and designing most of the instrument internally. We use some off the shelf components, and have partnered for others, but we do a lot of our own PCB design.

You’ve said you’re having to “beat the software vendors off with a stick.” How do you see yourselves working with them eventually?

Where I see them coming in is in dealing with what comes out of the ports on the back of our sequencer, which hopefully should be a quality scored DNA sequence, possibly with some accessory information for QC. Obviously, we’re targeting high-end large-scale laboratories, but we’re also targeting the bench-top. In order to have a bench-top sequencer that does the kind of applications being pioneered in the genome centers, to have that accessible to any researcher, we have to provide pretty easy to use bioinformatics solutions. Otherwise, it’s just not going to happen, is it? One of the problems with all these existing sequencers is, even if you automate the sample prep and make the sequencer easy to use, you still end up with a file with a billion short reads in it. This is still beyond the capability of most non-bioinformatically trained postdocs to do anything sensible with. Our system will have even more of that, and we are looking at longer reads. Nevertheless, a massive amount of complex data.

We have to provide, next to our sequencer on the bench—I hate to use the word ‘turnkey’—but a pretty polished bioinformatics solution to deal with that. I’ve been talking to a number of interesting companies—there’s a current favorite—we’ve been doing some proof of principle work. They’ve been demonstrating that their workflow software can deal with a whole human genome-type workflow in a day or 6 hours on a typical workstation. For example, it reads in data from a massively fragmented human genome, then executes a standard QC and alignment workflow, and then produces graphical reports and SNP calls. They’ve done it in reasonable time, in my view, both for development effort and speed of execution. I can’t say who it is, yet, but that looks quite promising to me.

Are you writing your own alignment and variant-calling software?

Nava Whiteford is working on a paper at the moment on very long-read sequencing and its informatics. He’s adapting existing algorithms already out there. For contrast, at Solexa, Tony Cox had to come up with a completely new one called ELAND to deal with mountains of short reads. However, we think we can adapt methods that exist already in such a way as to work optimally with our data. We’ve also developed some interesting file formats for our data—called Fast5 for scored sequences. We’ve also co-developed some HDF-5 based raw data container formats and those are all public domain. We’re slowly putting in the groundwork for adoption.

You say you’re not providing IT solutions, but won’t some early customers want that?

A lot of early customers, because of the current ‘next-gen’ sequencers, will have made the IT investment anyway. A lot of that can be recycled for our sequencer. Our sequencer won’t have the IT overheads of the current sequencers—it’ll be greatly reduced, even though the output will be higher. And unless we get merged again, and all my plans get derailed, I’m going to partner with somebody in terms of the early adoption process. These people will liaise with IT groups and help us to smooth the early adoption of lots of our systems. It won’t be as big a barrier as it was at Solexa, but we will have to put some effort into it. I’m more worried about the bench-top side than the high-end side. Once we go to full commercial launch we are partnered with Illumina and there will have to be agreed and synergisitic approaches.

So you’re targeting two very different markets—genome centers on the one hand, the bench top on the other?

Traditionally, there are about 15,000 of the old capillary/gel-based sequencers. They enjoy about 4% growth per year, mostly in forensics and other conservative market segments. There are about 900 next-gen sequencers out there now. They’ve traditionally gone to people who do already do some sequencing, e.g. core facilities, genome centers etc. However, what will the future look like? Well, an obvious direction is the bench-top sequencer, which sits next to a postdoc or other lab researcher. We target that. We also target genome centers, in that they can run lots of our machines in a scaled up operation, rather like the [Illumina] Genome Analyzers are currently run.

The thing that isn’t really there yet, which oddly enough is being broached by Complete Genomics, is this idea of very large sequencing centers that are not traditional genome centers. They’re either commercial service operations or they’re run by health providers, and they’re doing medical sequencing or whatever. Those don’t exist yet, but I can’t imagine why they wouldn’t in the future. We go across the board from the very small to the very large. What’s new here is the very small and the very large. The middle bit is the old market, still important but a subset of our ambitions.

There are people out there who want to do these new sequencing applications perhaps at a smaller scale or more occasionally. These applications have been pioneered by people who already bought Solexa or SOLiD, but they’re not quite accessible yet. At the other end of the scale I think Complete Genomics is a perfect customer for us. In fact I think our machine’s better suited for what they want to do than theirs is!

It sounds like everything is on track. Where are the problems?

I don’t want to oversell things, and remember we are still very stealthy as a company. On the other side of the coin, any of the more honest people will tell you things just aren’t linear in a company like this. You have days when things work beautifully, and long dry periods when things aren’t working. Half of it is just keeping your nerve. You’ve just got to plough through it all.

Surely your Solexa experience must be helpful in this regard?

Yeah, I think so. [Former Solexa CEO] John West would always say, “You’ll be amazed what you can get to work if you put your mind to it”. The average age of employees here is just 26-27. So we’re trying to impart that attitude to people who haven’t been through this process before. It’s quite a leadership challenge, actually.

What are some of your group doing specifically?

Let me just say, I think they’re all fantastic. A few examples: Stuart Reid, a physicist by background, is doing a fantastic job. He’s very cross-disciplinary but he works in my group which also deals with product design, specification and systems integration. So a lot of what we’re doing is about data and data quality measures and targets. Stu is driving that, along with some of the fundamental science that feeds into the platform. Roger Pettett, who joined us from Sanger, is doing a critical job actually. He’s a very understated chap, but we have to build a ‘genome center’ here and Roger is driving the informatics infrastructure to accomplish that. Lukasz Szajkowski, who joined us from Illumina, is managing the writing of the instrument software. To my mind, one of the most risky areas, but it’s all on track thanks to him.

Nava Whiteford, who also came from Sanger, wrote the first proper publication on short-read sequencing feasibility. He’s doing a fantastic job across the board on bioinformatics and IT. I’ve got Gavin Harper, a statistician from GSK, churns through mountains of raw data, measuring things, and keeps us all honest. We have Mick Knaggs, a very experienced molecular modeler, who has provided key insights into the nanopore design and optimization. He has implemented a lot of his software on GPU-enabled systems in house. There are many others; they’re all actually very, very good. I’ve been very lucky to get them.

Hmm… The Sanger Institute must love you…

Yeah, we did have a chat about my recruitment methods.

[R&D and Market analysis of this "game changer" is upon request. Pellionisz; HolGenTech_at_gmail.com]

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