May 15, 2012 : Jeffey Rosenfeld : In the past few years, the prices of sequencing have plummeted and now for a few thousand dollars, the complete sequence of an individual can be obtained. Even so, many scientists have opted to sequence just the exome (coding regions) of an individual and to ignore the rest of the genome. This focus on the exome has some justification, but I think that it is shortsighted and despite the higher cost, the sequencing of a complete genome is more valuable even if that means sequencing fewer samples.

The supporters of exome sequencing generally make the following points to justify their position:

A. The sequencing of an exome is much cheaper than the sequencing of a genome. It must be substantially cheaper to sequence 1% of the genome than the whole genome.
B. We don’t understand how to interpret non-coding variants and therefore we should limit our sequencing to genes that are well annotated.
C. Variants that are associated with a genetic disease are more likely to be found in a coding region since they directly alter the structure of a protein.

I am not going to deny that there is some validity to these points, but I don’t think that they outweigh the shortcomings of exome sequencing and the benefits of whole genome sequencing that I will outline below. I understand that this is a contentious issue, and I welcome your comments whether you agree or disagree with my position.

1. Cost  

The first reason the people generally look to exome sequencing is that of cost. Intuitively, the sequencing of 1% of the genome (the exome) should be cheaper than sequencing the entire genome. While this is true, the price differential is nowhere near 1:100 and is closer to 2:1 or 3:1 depending upon how the costs of the sequencing is calculated. Currently, a whole genome costs ~$4,000 and an exome costs ~$1,500. Why are these prices so close to each other? The answer is that the actual reagent cost of running the sequencer is not the only factor in the cost of a genome or an exome. For either type of experiment, library prep is required along with the costs associated with setting up a sequencing run of any size. For an exome, there is the additional cost of purchasing the selection kit which allow one to extract the coding sequences from raw DNA either using a microarray or in solution. This kit can cost several hundred dollars, and is therefore a substantial portion of the cost of exome sequencing.

Because of the lack of strong cost differential, the economic argument of favoring exome sequencing is not very strong. For the same amount of funding, a researcher would need to choose between say, 30 exomes and 10 genomes. While 30 samples are obviously better than 10, this is not a great differential. It is much less than the 1:100 differential that one would naively think of concerning the price of genome and exome sequences. An additional factor affecting the cost of exome sequencing is the time required to perform the hybridization. For the Nimblegen protocol, 72 hours of time are required for hybridization and 24 hours are required for the Agilent approach. These times add a delay into the time taken from sample to sequence which may be problematic for clinical applications. As an example, the Ion Torrent machine is being pitched as a tool for rapid sequencing that will produce results in a single day. When an exome is targeted using Agilent or NImblegen, this will grow to at least 2 or 4 days of time.

2. Exome coverage 

The definition of an exome is somewhat elusive. It can refer to:
a) All of coding exons of the genome
b) A + microRNA genes
c) A + 5’ UTR and 3’ UTR regions
d) Unannotated transcripts that have been discovered in RNA-seq experiments or from the ENCODE project
e) All "functional" portions of the genome

These five definitions will include very different portions of the genome and some of them such as E are difficult to define in and of themselves. It has been shown in multiple studies that there pervasive transcription along substantial portions of the genome. Should all of these regions be considered part of the exome? In general these are not included in the exome kits since their inclusion would push the size of the exome much closer to that of a genome and any potential savings from the lesser amount of sequencing will decrease. Instead, the exome is generally limited to coding genes with some level of annotation along with microRNAs and to some extent UTRs.

Each of the different vendors that produce exome kits have taken different approaches to defining the exome. A recent paper http://www.nature.com/nbt/journal/v29/n10/full/nbt.1975.html compared the exome selection offering from the three main players in the field Agilent, Nimblegen and Illumina.

This figure gives a great comparison of the different technologies. Firstly, the approaches to selecting the exome sequence differ. Nimblegen uses overlapping DNA baits, Agilent uses RNA baits which are distinct but contiguous and Illumina uses distinct DNA baits that are not contiguous and contain breaks of un-targeted sequence. Because of this, Nimblegen contains many times the number of probes as the other two technologies. The rest of the figure shows Venn diagrams illustrating the overlap between the targeted regions. For two different defintions of human genes, RefSeq and Ensembl, there is substantial agreement between the technologies as indicated by the 28.5 and 28.4Mb of sequence that they all cover. The biggest discrepancy is with regard to UTR regions where Illumina has 28 Mb that are missing from the other two platforms.

A different technique to assess coverage is to look at the amount of the exome target from a particular kit that is covered at a sufficient threshold to make a confident call of a variant. For many scientists, a threshold of 20x coverage is required to trust a variant derived from an exome sequence. Any loci with lesser amounts of coverage are ignored. Since the general sequencing coverage for an exome is 80x, in theory, it should be no problem to achieve 20x coverage of the entire targeted region. In practice, this is not the case for three reasons. Firstly, exome sequencing, as with all sequencing, produces reads in a statistical distribution and not evenly along the genome. Randomly, some regions are going to have their DNA sequenced more often and thus have a higher number of reads. This idea forms the basis of the famous Lander-Waterman statistics that are used for designing sequencing projects. The second reason for variation in coverage is that some of the baits used for selecting the exomic DNA will have a higher affinity than other baits, mainly due to GC content.. Those probes with higher affinity for their targets will produce greater amounts of sequenced DNA. The final concern is due to the repetitive nature of the genome. The selection probes need to target a unique location in the genome to ensure that they are truly obtaining the DNA that they intend to select. If the targeted region is repeated in the genome, then sequence from all of matching regions will be equally selected. Many human genes share domains with other proteins, and any shared sequences cannot be targetted. This is an equivalent problem to the unique mapping of sequencing reads which is a big concern in the use of short sequence reads. Any reads that map to more than one location of the genome cannot be uniquely placed and are generally discarded.

These concerns are illustrated in this figure from Agilent regarding their SureSelect sequencing:

This is an old figure, but I think that while the numbers might have changed a bit, the overall message remains. The read depth is extremely variable and you do not achieve anything close to 100% coverage of the exome. While accurate data is available for 80% of the exome (depth > 20x) this also means that 20% of the exome is missed. In odds terms, this means that for a disease study where an exomic variant correlates with the disease, there is a 1:5 chance of not having the variant included in the data. A researcher could conclude that there is no coding variant associated with their disorder when in actuality, it was just that it fell into the 20% that was missed. An error level of 20% is not trivial and cannot be lightly dismissed.

3. Whole Genomes 

When a whole genome is sequenced, many of the issues regarding exome sequencing are not relevant. There is no need to buy a hybridization kit or to wait for the kit to hybridize. While there are sequencing biases (as there are in any sequencing experiment), there are not the additional biases introduced from the exome selection. Overall, there is probably the standard 5% error in sequencing giving a confidence level of 95%.

But, the biggest gain from a whole-genome sequencing is that the entire genome (excluding some unclonable regions) is obtained. If one wants to focus on the exome because it is easier to understand and interpret, they can easily filter out the non-coding portions of the genome to obtain an in silico exome. This is an easy action to perform and if a positive result is not found in the exome, then you already have the rest of the genome sequenced to begin looking for an intronic variant related to splicing, or a non-coding promoter or enhancer variant. In a traditional exome experiment, this is not possible. If no variant is found in the exome, then there is no result and one needs to go back and sequence the whole genome again from scratch.

To give a picture of the fraction of disease associated variants that are coding or non-coding, I looked at the UCSC collection of GWAS studies. The current list contains 5454 unique SNPs loci that were identified as part of a GWAS study. Of these SNPs, 3047 (56%) of them are not within coding genes. Thus, more than half of the identified important genomic variants are not in coding regions and would not be covered by exomes. (Some of these SNPs may be in UTRs or non-coding RNAs which are targeted by some of the platforms)

I see this as a betting situation. Would you rather spend $1,500 and have a 44% chance of getting the answer of spend $4,000 and have a 95% chance of getting the answer? I think that the $4,000 genome is much more reasonable. Just because we don’t understand non-coding sequence does not mean that we can or should ignore it. As scientists, we have an obligation to try our best to investigate human disease and not to only focus on things that are easy to understand.

As a final point, there has been some recent talk concerning variants that are only found from exome sequencing and not genome sequencing. These results are not a fair comparison of apples to apples. The exomes are generally sequenced at 80x coverage, and the genomes are sequenced at 30x coverage. For the specific variants under discussion, 80x sequencing coverage is required to identify them from any technique. This 80x coverage could have been of just the exome, or the entire genome. If the whole genome were sequenced to 80x for a true comparison, then I am confident that there would not have been an advantage for the exome over the genome.

April 19, 2012 : Nathaniel Pearson: In time, finer data and statistical models will test the specific claims of a widely discussed recent paper, by Bert Vogelstein and colleagues, on the prospect of genomic risk prediction. Though the paper’s meta-analysis of twin studies has taken some heat for repackaging longstanding knowledge about heritability, the fuss over it has usefully underscored real complexities of disease and healthcare. And thoughtful responses to the paper have made clearer, to the public, that few geneticists are the zealous determinists of caricature; rather, we tend to grasp the causal basis of disease (and other phenotypes) with inclusive nuance.

But while the dialog may have enlightened many, both the paper and its critiques have largely missed two pertinent points:
1) In the world of genetic risk, cancers are big exceptions.
2) Inasmuch, they prove some underlying rules.
And in the context of the paper itself, these points nestle into one nutshell:

In research, twins with tumors are no longer really twins. 

To see why, and fold this point into the wider discourse on genomically personalized healthcare, let’s peer briefly through the looking-glass of cancer genetics. 

Gemini, Cancer, and genomic horoscopes
As noted, the new paper aimed to summarize what studies of twins say about how well our genomes, alone, may predict what diseases we’ll get. The premise, of course, is that twins from the same fertilized egg resemble live runs of a telling thought experiment: if you and your genome lived twice, would you get the same diseases? 

The basic answer has long been clear: twins don’t always get sick the same way. But Vogelstein and colleagues reasonably asked, for particular common adult diseases, how often they do.  

Sensibly, they reviewed available twin data for several complex (and interrelated) epidemic killers, such as heart disease, diabetes, and stroke. To boot, they also combed the literature on pregnancy complications (an intriguing evolutionary nexus of health), some nerve and autoimmune diseases, and more mysterious ailments like chronic fatigue and irritable bowel syndromes.  

But nine of the twenty-four diseases they surveyed — the bulk, by class — were cancers. And this choice sapped any suspense from their findings. For while cancers indeed kill many people (so demand study), they are long known to be far less heritable — that is, to show a smaller portion of cases running in families — than many other grave diseases. As Vogelstein (a renowned cancer researcher) surely knows, loading a heritability survey with cancers is like padding a Russian presidential ballot with token dissidents. Conclusion: foregone. 

To be fair, the authors likely didn’t set out to mislead. After all, they could only survey available studies of twins. And a big study of cancers was ripe to include (in the end, it supplied all their data on the question). While that study did find some evidence of genetic heritability in cancers, it concluded that such heritability plays little role in most cases, bolstering the well-established bottom line: in the grand scheme, cancers rarely run in families. 

Where the authors shouldn’t be excused so easily is in a) actively hyping their findings as novel, while b) burying this key grain of salt, far from headlines and press releases, in a brief aside near the end of the paper: 

For diseases with a lower heritable component, such as most forms of cancer, whole-genome based genetic tests will be even less informative. 

Which any clinical geneticist could have told you, thirty years ago. 

And yet…
Unsurprisingly, all nine surveyed cancers in Vogelstein’s survey were deemed less genetically predictable (heritable) than the other diseases studied. Nonetheless, any oncologist will tell you that cancers are quintessentially genetic diseases. As we’ll see, they require — and are even defined by — genomes gone awry. 

Indeed, some of the most widely screened-for genetic risk variants underlie rare familial forms of breast and colon cancer. And whole genome interpretation is finding its first vital clinical use in treating tumors, along with sick children.  

So what gives? How can cancers be intrinsically genetic, yet so hard to predict from our genomes?  

The answer, it turns out, is that it matters which genomes we mean. 

The hive within
To understand cancer’s peculiar nature as a genetic disease, first picture your body…as a colony of bees.  

Bear with me here: both entities — you and the swarm — are, ultimately, teeming masses of individuals (cells or bees), most of whom work hard to help just a few of their kind (eggs or sperm, or the hive’s queen and few males) breed on their behalf. 

In this view, the two basic kinds of cells in your body — gametes (which biologists also call the germline) and somatic cells — respectively resemble a bee colony’s two main castes, breeders and workers.  

In a sexual many-celled organism, like you, somatic cells vary kaleidoscopically in form, embodying the many specialized tissues that that help a body thrive from moment to moment. Gametes, by contrast, specialize mainly in storing DNA for coming generations, and — as big, slow, costly eggs, or small, fast, cheap sperm — in finding a partner gamete to merge with. 

In most animals, the cells that become the germline split from other cells very early in embryonic development. As with bee royalty, it’s nearly impossible for a somatic commoner to infiltrate their reproductively privileged ranks later. 

While details prompt debate¹, natural selection is thought to have driven the emergence of the soma-germline and worker-queen distinctions, and in both cases to have brokered a lasting social compact between the two kinds of individuals.  

In this contract, a somatic cell in your hand, like a dutiful worker bee, effectively says to your gametes 

Cousins, if you spread our shared genes, I’ll give my life to help you. Count on me to build sturdy shelter, find good food, fend off attackers, write honeyed words to entice a mate, and care tenderly for the children that come after. You do the rest, and send our line forth. 

Seen in this Hobbesian light, a tumor is, effectively, a mutiny of somatic cells, who break that evolutionary covenant with their germline cousins. A budding tumor cell effectively says `Hell no, I won’t work and die for other cells — I’ll reproduce, myself, instead,’ and starts proliferating unchecked.² 

A disease of genomes
Crucially, the cellular treachery of each cancer case typically traces to one or more sudden changes — mutations — in the genome of a somatic cell. The mutations in question may be slight — say, the miscopying of one DNA letter from the parent cell’s genome. Or they may be drastic, as when a rogue gamma ray shatters a whole chromosome. In the latter case, the cell may, in mending the resulting fragments of DNA, inadvertently scramble them. 

Whether slightly or severely altering DNA sequence, the mutations that turn cells into tumors tend to do so in particular ways. Typically, they either throw, or freeze stuck, one or more functional switches in the budding tumor cell’s genome — switches that had, til then, tightly governed the reproduction of that cell’s immediate ancestors, yoking their proliferation to the overall best interests of the developing body. 

The switches in question are often protein-coding genes that directly govern a) whether a cell divides or, instead, takes a moribund, tissue-specific form; and/or b) how the cell exchanges signals with other cells, e.g., halting growth at the touch of a neighboring cell, or telling that neighbor to build more blood vessels, to bring more food and oxygen. In some cases, the key switch may govern how well the cell corrects DNA copying errors; one mutation in such a gene may thus spark many more, some of which eventually knock out other switches that more directly reined in the cell’s growth. 

In the end, a tumor grows unchecked thanks directly to one or more newly arisen genetic variants that distinguish it from other cells in the same body.³ Importantly, such cellular mutinies are (with some exceptions⁴) typically doomed: in their greed for resources, the rebelling cells weaken the body overall, and, with no way to escape, sink with the ship that they’ve commandeered.  

Sui genetis
All this switch-throwing ultimately means that tumors grow, spread, and kill specifically because their genomes differ from other genomes. As such, cancers are not just genetic in origin, but break a key assumption underlying Vogelstein’s paper: that monozygotic twins are genetically identical.  

That is, as soon as a person is diagnosed with a tumor, all bets premised on her genetic identity – or even near identity – to a twin are off.⁵ Not only do billions of her cells now differ genetically from those of her twin, but they differ in ways that are, by definition, biologically important. That is, the distinctive genetic variants in question drastically change the way that cells work, letting them divide unchecked.  

In this sense, a tumor genetically distinguishes its host — of whom it is intrinsically part — from other people de facto, much as inherited genetic variants may distinguish someone with a strongly heritable disease from other people. Notably, this insight tempers any expectation that the person’s twin should get the same disease (a cancer driven by genetic variants that the twin likely doesn’t carry). And it underscores the uniformitarian rule that cancers, in their poor heritability, seem at first to violate: in diseases of all stripes, genomic differences matter.  

Tumor genomes: noisy, mixed, changing
The first active clinical uses of whole genome sequencing have been in pediatrics and oncology. And this makes sense. In bluntly formal terms, sick kids and tumors are both masses of cells — one beloved, the other loathed — that are growing awry. And they’re both growing, as such, too fast for us to wait for sequencing to get cheaper, or for medical knowledge to get deeper. We’ll sequence now, if we can afford to, in order to gain some foothold into the medical mystery at hand.  

For tumors in particular, we hope that sequencing the tumor (and, importantly, healthy tissue for comparison) will reveal key genetic clues to how it arose, grows, spreads, and might be slowed or killed. Alas that turns out to be hard to do, for three key reasons. 

First, as noted, tumor genomes are pocked by mutation. Small spelling changes often abound, hiding a few functionally important ones (called drivers) in a cacophony of incidental noise (passengers). And, at bigger scales, long segments of chromosomes are often repeated, missing, or scrambled. Such rampant genetic variation is not just tough to functionally interpret, but also makes it hard to draw an accurate picture of the genome in the first place. Why? It turns out that the computer algorithms used in modern sequencing work poorly for genomes that differ greatly from the standard reference genome, because snippets of raw sequence data that don’t match up well to that genome (like puzzle pieces that don’t closely match the picture on the box) are hard to correctly place. Moreover, tracts of DNA letters that appear in multiple spots in a genome (like uniform fenceposts in a farmscape puzzle) are especially hard to accurately sequence — an acute challenge in tumors, where rampant mutational copying, cutting, and pasting turns the genome into a bewildering house of broken mirrors. 

Second, each tumor actually harbors not one, but a mix, of such noisy genomes — often with non-tumor cell genomes inadvertently mixed in. While a tumor is indeed a clump of closely related cells that distinctively share particular variants, it’s also a population of genetically varied cell lines, each effectively striving to grow faster than the others, thanks to its own secondary stock of functionally relevant variants. But because sequencing today requires pooling many cells, genetic variation in the tumor tends to get homogenized, as if in a blender. An important variant carried only in a few cells may not be prominent enough to show up in the final reckoning of a singular tumor genome sequence. 

Third, the mix of genomes in the tumor evolves, partly in response to treatment. Thus we may want to track how treating the tumor with a particular regimen kills of some cell lines in the tumor, while letting other lines, by chance resistant to the treatment, spread quickly. To best characterize and treat a tumor, we might want to see a movie, rather than just a snapshot, of its mix of genomes, letting us watch how they change in response to treatment. But doing so is, for the foregoing reasons, tough — and will be until we can sequence fewer cells at a time, for less money, and with longer snippets of raw sequence (analogous to bigger puzzle pieces that can be more reliably pieced together to get the whole moving picture). 

Epilogue
On a late summer afternoon when I was six, my mom came to my room, sat next to me, and showed me fresh bruises on her arms and legs. Speaking with determined nonchalance, she trained a young boy’s restless attention to a moment of revelation.  

Each squall-blush in her skin was, I learned, real bloodshed from a war below. In the marrow of her bones, delinquent cells were teeming, wrecking the nurseries of sticky platelets that she needed to heal small, everyday blood vessel leaks. The bruises were collateral damage from that mutiny — her own cells betraying her, and those she loved. 

She sought treatment, but leukemia wore her down quickly. On Halloween night, muted by breathing tubes in intensive care, she could welcome my visit only with a tiny nod and a waiting cup of candy. She died a few days later, at 34. My first-grade classmates, struggling to comprehend from afar, sketched colorful cards of condolence that I still keep. 

Writing today, on her birthday, I’m older than she got to be. Childhood reading, long before Vogelstein’s paper, taught me that leukemia shows little heritability. Yet I still watch for bruises…and admit to a tinge of affirmed relief that, among the diseases that the paper assayed for genetic predictability, leukemia came in last. 

But the comfort is cold. Cancers remain an especially vexing kind of plague: sprung from our own selves, tumors are, in the paper’s geminal terms, something like evil conjoined twins. Growing relentlessly, ever changing, they cloak genomic secrets in genomic smoke, and evade our harshest treatments. They are the last horcrux. 

At a recent conference, I listened to Washington University’s Elaine Mardis explain how she and her colleagues are systematically characterizing the genomes of thousands of tumors. Their yeoman work is building a broadly useful critical mass of detailed knowledge about how tumors arise, grow, and spread. But their findings are also helping real doctors and patients, today, choose treatments that lengthen lives and lessen suffering. 

After Mardis’s talk, I told her how touched I am not just by her team’s work itself, but to know that Wash U (where my mom earned her PhD) and Barnes Hospital (where she gave birth to me, and died) now spearhead a data-driven fight against leukemia and other cancers.  

And I’m proud that my own work at Knome supports such efforts. By thoroughly characterizing tumor genomes, and developing algorithms to do so better, we’re helping clinical researchers spot genetic variants that directly drive tumor growth or, more rarely, predispose some families to recurrent cancers. That work, like Mardis’, is already leveraging individuated genome data to help people live longer.  

Looking ahead, those of us lucky enough to afford good healthcare today will likely be talking a lot about tumor genomes, with our families and friends, in coming decades. Relevant insights will likely guide vital choices for many of us and those we love.  

We’ll see how soon other major adult diseases — think of those surveyed by Vogelstein et al., but also of liver and kidney diseases, mental illnesses, breathing problems (asthma, respiratory tract infections), bone diseases, etc. — likewise become more amenable to personal genomic insights, first for diagnosis, and, in the long run, for prognosis too. Here’s to those twin prospects. 

¹In bees (as well as ants and termites), this compact is thought to be reinforced by the fact that a queen and her worker sister may be especially closely related — often moreso than either would be to her own daughter. This odd twist of kinship follows from male bees having just one copy of each chromosome (having hatched from unfertilized eggs), while females have two (hatching from fertilized eggs). As a result, bee full sisters share, on average, three-fourths of their DNA with each other, while mothers and daughters share just half.  

In a real hive, the numbers are complicated by many pairs of workers being just half-sisters (with different dads). But that turns out not to matter much; the strong social contract of eusociality can be mathematically understood even without the extra-closeknit kinship that bee sisters share. 

²As in many personified examples of rivalry between organisms, the tumor cell’s effective strategy is not conscious, but rather a mathematical truism — that is, cells in which a chance mutation tears the web of reproductive constraint that natural selection has woven will, at least in the short term, tend to outgrow neighboring cells. 

³Importantly, a person may be born with at least one such genetic switch already thrown; this scenario underlies rare cases of strong familial cancer risk. Cancer can then strike as soon as a second switch — a copy of the same gene, or another gene — is randomly thrown by a new mutation.  

People born with one broken copy of the cell growth-suppressing RB1 gene, for example, tend to eventually get tumors in both eyes. In such cases, their working second copy of RB1 tends to eventually mutate in one of the fast-dividing, light-bombarded cells of the retina of one eye, leading to a first tumor. Later, a second such mutation may strike a retinal cell in the other eye, spawning a tumor there too.  

Thus even in rare forms of cancers that run in families, getting a tumor requires some new mutation in a somatic cell. And that mutation may, in turn, be driven by some environmental factor (such as radiation, toxins, or even infectious germs), highlighting that both genetic and environmental factors are key to understanding cancers — just as in other diseases. 

⁴One tumor that beat the odds, living on beyond its original victim, belonged to American Henrietta Lacks. As detailed in Rebecca Skloot’s compelling personal and cellular biography, in 1951, Lacks’s doctor took cells, without her consent, from the ovarian tumor that was killing her, and grew them in dishes. Though born in suffering and scientific misconduct, those cells nonetheless proved remarkably resilient in laboratory culture, and have since spread worldwide as a key resource for six decades of biomedical research.  

Another tumor that slipped the mortal coil of its origins is the contagious facial cancer that plagues Tasmanian devils — the subject of a fascinating recent paper. And some rare cancers of germline (rather than somatic) cells may manage to make gametes healthy enough to transmit themselves — rampant cell growth and all — to coming generations. 

⁵Of course, even monozygotic twins without tumors aren’t really genetically identical. The genome’s great size, and the many generations of mutation-prone cell division needed to build the myriad cells in their bodies, nearly assure that no single cell in either one is genetically identical to the fertilized egg from which they came — much less to a typical cell pulled from the other twin. 

But tumors flout the genetic identity assumption of twin studies even more severely. The many cells that make up a tumor tend to be especially closely related to each other, thanks to their recent growth spurt. Thus the newly arisen genetic variants that the tumors’ cells share, and that distinguish them from other cells in the body (and even moreso from cells of the other twin, thanks to the extra rounds of cell division that separate the two cell lineages in question), are especially common among the cells of the person overall. As such, if we think of a person’s genome as comprising, at each site, a weighted mix of the genotypes of all her cells, then a tumor makes her particularly genetically distinctive — even beyond the prospect that those differences may be more functionally important in tumors than in other kinds of cells. 

Editor’s Note: In the following guest blog post, X-Prize Foundation's Grant Campany provides an overview of the Archon Genomics X PRIZE whole genome sequencing competition. For more information visit: http://genomics.xprize.org/  

April 9, 2012 : Grant R. Campany (Senior Director & Prize Lead, Archon Genomics X PRIZE, X-Prize Foundation) : One of the most fascinating aspects of the Archon Genomics X PRIZE presented by Medco®, is the validation protocol we designed to declare the $10 million winner of our Competition.  Our scientific advisors are collaborating with agencies nationally and internationally to establish our protocol as a global, consensus-driven “standard” for whole human genome sequencing, once the Competition ends. Our efforts so far have earned support from the FDA, NIH and NIA. http://www.youtube.com/watch?v=oWC1knVaQHI. 

To those of you unfamiliar with the Archon Genomics X PRIZE presented by Medco, it is an incentivized prize competition that will award $10 million to the first WGS Team to submit 100 human genome sequences in 30 days or less at a maximum cost of $1K per genome, at an accuracy score of no more than one error per 1,000,000 bases, present each genome as 98% complete, and provide accurate haplotype phasing. 

If those thresholds are met or exceeded, it will define for the first time, what it means to have a complete and accurate “medical grade" whole human genome sequence.  

Since each WGS Team is required to sequence the same set of 100 genomes, we thought long and hard to identify a disease set that would benefit most from the data our Competition will produce. It was suggested that instead of selecting a disease, to find the healthiest and long lived among us to sequence.  All 100 genomes will be donated by 100 centenarians (ages 100 or older) from all over the world, and will be known as the Medco 100 Over 100. Sequencing the genomes of the Medco 100 Over 100 presents an unprecedented opportunity to identify those "rare genes" that protect against diseases, while giving researchers valuable clues to health and longevity.  

The result will be the world's first "medical grade” centenarian genome, a critically-needed clinical standard that will transform genomic research into usable medical information to improve patient diagnosis and treatment.  

The goal of this global competition is to inspire breakthrough genome sequencing innovations and technologies that will usher in a new era of personalized medicine. 

Editor’s Note: The following was originally posted on EdgeBio's Views from the EDGE blog, and is reposted here with permission. - Janine Holley  

 March 19, 2012 :  Dean Gaalaas (CEO, EdgeBio) : I attended the Human Genome Meeting last week in Sydney, Australia, due to our involvement with the X Prize. It was my first time at the meeting and I came away very impressed at the level of sequencing being presented during the talks. Many of the talks led off by John McPherson’s talk on Cancer Genomics, and were highlighted by Michael Snyder’s talk on using Omics profiling for assessing disease risk and heath states. Through all of the talks a central theme emerged in my eyes, that the $1,000 genome would lead to widespread adoption of NGS as a clinical diagnostic tool. Much has been written and said about the promise of genomics technology and its impact on personalized medicine. However, that is not the focus of this spot. I would prefer to assess the merits of the premise that the cost alone will lead to rapid adoption sequencing as a clinical assay.

To me this seems like an overly simplistic view of what is needed to bring NGS to the clinic. I’ve attended many talks over the past few years and most believe that sequencing is essential to learn more about complex diseases such as cancer and neurological disorders. This draws an interesting parallel to sequencing. As a species, we humans seem drawn to the simplistic view of cause and effect. In the case of human health we tend to think that a change in one gene will cause a disease state and that by fixing this one gene, through a variety of methods, we can cure that disease state. However, we know this not to be true for a majority of disorders.

When it comes to the adoption of NGS, I believe we are falling prey to this overly simplistic model. The current thought is, if we can just make sequencing more affordable like the $1,000 genome, that the adoption curve will start to go asymptotic. To me, it seems that getting NGS into the clinic as a matter of Standard of Care, will be much more complex. Yes, cost plays an enormous role and is a fair enough starting point but there are many more factors that need to be considered. The factor that is most intriguing to me, and the one I have heard least about, is how do we get insurers to reimburse?

In Australia, many of my international colleagues posited that if sequencing were to only cost $1,000 USD, that many would turn to it as an out of pocket expense as this is a matter of routine for most outside of the US. Fair enough, but what will sequencing your genome once tell you about your disease state? Presumably, you are paying that money out of pocket because you suffer, at the time, from a particular ailment. Michael Snyder’s talk focused on looking at his genome over several time points, referencing his genome at a baseline (relatively healthy state), versus disease state (rhinovirus infection), post-infection, and so on. To me this seems like a very reasonable assessment on how to use sequencing as a diagnostic; to monitor changes in the genome over the lifespan of a patient. This means having your genome sequenced multiple times, which makes it doubtful that patients would be willing to pay out-of-pocket as many times as necessary.

Certainly in the US, few if any are willing to pay out-of-pocket for medical expenses. So, will the $1,000 genome cause insurers to line up to reimburse? My thought is no. They wouldn’t rush to reimburse even if it were $100 per genome. The health industry in the US tends to move at what could best be described as a gingerly pace. Standard of Care is routinely cited, and Standard of Care tends not to change in lockstep with discovery or technological advances. No, it tends to change based on legal risk and cost. Tort reform in the health industry is a pet cause of mine but not the focus of this post, so let’s just look at cost.

Insurers are very black and white when it comes to reimbursement, if reimbursing for a test will save them money over what is currently available, they can be convinced to change. Consider, if you will, what is needed to convince insurers that this will indeed save them money. A reasonable scenario may look like this : insurers actuarial tables (and they have reams of data to support them) say that a typical head (term for insured) will stay with the insurance company for an average of 6.8 years and generate $20,000 of revenue for the insurance company over that lifespan. What needs to be shown is that by leveraging NGS as a matter of Standard of Care, the amount of revenue generated per head is greater than $20,000. A very simplistic model to be sure, but should serve to illustrate the point. Clearly a study could be designed to do this, correct? Certainly, but how much power would a study like this need? Over how long of a time period?

I came away from the Human Genome Meeting more excited than ever at some of the groundbreaking research being done across the globe with NGS technology. Now, if we could just match it with groundbreaking research on the cost impact of leveraging NGS in the clinic we will be much closer to the promise that the $1,000 genome seemingly offers.

February 27, 2012

Kevin Davies :  Four years ago, I met three young executives from a small British start-up, just off a 10-hour flight from London to California. We adjourned to the patio of a San Diego hotel, where they promptly ordered a round of beers and whipped out a laptop to show some tantalizing unpublished data that could pave the way to a cheap, high-throughput next-gen sequencing device using bacterial nanopores.

The head of the group - Oxford Nanopore’s co-founder and chief executive Gordon Sanghera - struggled to contain his enthusiasm. “One of the things we do bang on about is a British company finally delivering something,” he said. But when the time was eventually right to unveil the technology, they would make the announcement with a minimum of flash.

“There’ll be no fireworks,” Sanghera said, referring coyly to the Pacific Biosciences beachfront pyrotechnics display at the AGBT conference a few weeks earlier. “We’ll just give our presentation in a very dry British way. We might open up with Monty Python’s ‘And now for something completely different’… That’ll be as close as we get. We want to come over as a very reputable science and technology company.”

Fast forward four years: During his presentation at AGBT earlier this month, chief technology officer Clive Brown didn’t imitate John Cleese, but he did slip in a slide of the killer bunny from Monty Python and the Holy Grail. The premise was that Oxford Nanopore’s new MinION USB stick sequencer can reportedly sequence DNA from rabbit blood.

Brown joined Oxford Nanopore in 2008, having played a key role in building the Solexa sequencing technology that Illumina acquired the year before for $650 million. In an interview for my book The $1,000 Genome a few years back, he said: “I wasn’t convinced initially [on interviewing for the Oxford Nanopore job]. After 30 minutes, I was sold.” But he urged Sanghera to hire his former Solexa colleague John Milton, believing that Oxford would need the services of an expert industrial chemist. The two men joined that summer.

A Great Disturbance 

Brown and his colleagues chose to stay quiet for four years, sticking with the philosophy espoused at Solexa, spurning many opportunities and invitations to announce incremental milestones.

The initial reviews of Brown’s 17-minute presentation – widely reported by myself at Bio-IT World, the New York Times, Keith Robison at Omics! Omics!, Nick Loman at Pathogens: Genes and Genomes, Luke Jostins at Genomes Unzipped, Omically Speaking, and many other sources - have been extraordinarily positive. The real-time reviews on Twitter following Brown’s talk give you a sense:

“When can I buy one?”
“The first problem is I'm going to have to clean up all this drool.”
“Screw the #iPhone introduction, this is truly mind-blowing.”
“obi-wan: I felt a great disturbance in the force, as if a million #illumina investors cried out in pain.”
“The @nanopore press release also reveals that the MinION syncs with iTunes, acts as a 3G modem, and has a fresh lemon scent.”
“I feel sorry for anyone else giving a talk today.”
“This may be disappointing, but the only thing I have on my USB stick is my talk.” 

The only mild criticism:
“In the cold light of day, vaguely sad that tech vaporware stole the show from real biology.” 

And Eric Olivares, impresario of SeqAnswers, said:
“Waiting to see the 48.5kb lambda read… #makemeeatmywords” 

Oxford Nanopore posted a link to their 2011 Christmas card, wondering if anyone spotted the deliberate clue?!

As the announcement took a swift toll on the stock prices of NGS competitors (note that Illumina has a 15% stake in Oxford Nanopore and thus in essence a hedge against such downturns), Forbes’ Matthew Herper sought comment from Ion Torrent founder Jonathan Rothberg, who was the toast of the industry just one month ago with the introduction of the Ion Proton. He likened the furor around Oxford Nanopore to cold fusion, and wondered why for example the company hadn’t presented a bacterial genome sequence?

Such cynicism prompted Michael Eisen to respond on Twitter: “Nobody knows about overhyped and not ready for prime time sequencing tech like jonathan rothberg.”  

Brown had a quick retort as well: “We had MinION systems with us in our suite. I held one up during the talk, I understand it’s so small it may not have been visible from the back of the room.”  

New Generation  

On the face of it, Oxford Nanopore’s new generation sequencing (as they call it) technology boasts many desirable features. Here are ten reasons (I could think of more) to be excited:

10. Long reads, sufficient to sequence a virus in a single run
9. Even quality without degradation across the entire length of the read. Accuracy good (96% raw read) with road to improvement
8. Sequence of both sense and anti-sense strands in succession courtesy of a hairpin loop at the end of the DNA template
7. Ease of sample prep – no fluidics!
6. Proprietary nanopore and synthetic polymer bilayer for greater robustness
5. A topoisomerase of some description (helicase? gyrase?) for unzipping double-stranded DNA prior to sequencing, rather than the use of a polymerase to ratchet the DNA through the pore
4. A novel bioinformatic method for reading the sequence in overlapping triplets, involving Hidden Markov models and Viterbi algorithms
3. “Run until done” modality in which experiments are monitored in real time and halted depending on results
2. The world’s first disposable sequencer on a USB stick, with no ownership overheads and an accessible workflow for a single researcher
1. A pathway to the $1,000 genome in under an hour by 2013 using an 8k array

Now, all this is well and good, but until raw data are presented and published, a degree of skepticism is to be expected. As Elaine Mardis told an audience at NHGRI last week, “We are scientists after all.” Keith Robison has a considered plea for data release at Omics! Omics! 

But those requests will be answered soon, no doubt. The early access program is apparently set, and eager users shouldn’t have to wait more than 6-9 months before commercial release.

January 10, 2012

Kevin Davies :Researchers at Children’s Hospital in Boston have launched the CLARITY Challenge - a $25,000 competition intended to set and advance standards for clinical genomic analysis and interpretation.

CLARITY stands for Children’s Leadership Award for the Reliable Interpretation and appropriate Transmission of Your genomic information. While the much publicized Archon X PRIZE presented by Medco will offer $10 million in prize money for essentially reaching the $1,000 genome early next year, the CLARITY contest focuses squarely on best practices in clinical genome interpretation and data delivery. The winning team will receive a $25,000 prize underwritten by Children's Hospital

The competition is open to academic and commercial researchers worldwide, with applications due no later than March 1, 2012. For logistical reasons, a maximum of 20 teams will be selected to participate in the competition. The winner of the competition, chosen by a panel of seven judges, will be announced in October 2012.

Industry partners include Life Technologies, which raised the prospect of a $1,000 genome in 2013 with the unveiling of its Ion Proton sequencer last week, and Complete Genomics.

“With the swift decline in the cost of sequencing, the time is rapidly approaching when genomic information will leap from the research bench to the doctor’s office and become a part of everyday care,” said Isaac Kohane, director of Children’s Hospital Boston’s informatics program and one of three competition co-organizers.

Coming Together   

Kohane told Bio-IT World that the idea for launching the contest emerged from the success his group enjoyed in running challenges for i2b2 (informatics for integrating biology & the bedside), focused on making data widely available. “The competitive aspect was nice, adds some spice, but [more importantly] it catalyzes teams coming together. I think that there’s a certain social process around these competitions, creating teams for a purpose that otherwise didn’t exist.”

In addition to helping the patients and their families, Kohane hopes to identify and bring together the best elements of competing pipelines, as he expects that there will be stronger and weaker components for each pipeline. “There’ll be one overall winner, but separate and transparent grading of different components of the pipelines.”

“Clearly, we’re going to need teams” to tackle the challenges of clinical genome interpretation, he says. “One of my favorite publications in 2011 was a paper in Nature Biotechnology from Mike Snyder and colleagues, in which they compared Complete Genomics sequence data to Illumina. They found that there was [only a] 93% concordance for single nucleotide polymorphisms (SNPs), which is terrible! And on copy number variants (CNVs), only 24% concordance. That tells me that every point in the pipeline -- from measurement to assembly to annotation, interpretation and generation of reports – all those points are, to be kind, open for improvement.”

The best way to stimulate “a public and transparent improvement of that pipeline” is to compare them side by side, he says, not only for the Consumer Reports-style value but also “to promote best practices in different pipelines, so they can be adopted and shared.”

Three pediatric patients at the Manton Center have been selected, including two with neuromuscular disorders. In each case, doctors strongly suspect a genetic basis for the childrens’ conditions, but “despite the best efforts of clinical geneticists at several sites, the genetic lesion has yet to be identified,” says Kohane.

Manton Center director Alan Beggs recruited the three families taking part. “Their response ranged from enthusiastic and very excited to cautiously optimistic,” says Kohane. Getting IRB approval from Children’s Hospital was tough, he says, in part because of the data sharing requirements.

Each patient and their parents will be sequenced. Life Technologies will sequence the exomes of each volunteer, while Complete Genomics will do whole genome sequencing.

“The project underscores Complete Genomics’ commitment to, and the industry’s path towards, using high quality, accurate genomic information from whole-genome sequencing (WGS) to improve patient care,” said Complete Genomics CEO Clifford Reid. “Through this CLARITY Challenge, we anticipate the discovery of the genetic basis of the children’s unknown disorders and also the creation of best practices for interpreting and presenting actionable results to physicians, patients and their families.”

Judge and Jury 

The seven judges were chosen for their expertise in different parts of the pipeline. They are: Russ Altman (Stanford), Elaine Lyon (ARUP Labs), Joseph Majzoub (Children’s Hospital), David McCallie Jr (Cerner Medical Informatics Institute), Peter Neupert (Microsoft Health Solutions Group), Peter Szolovits (MIT) and Hunt Willard (Duke University).

Among the questions they will be asking: Is the assembly done well? Are the annotations credible? Does the report look readable? Does it make clinical sense? “Not inconsequentially, for a medical director, can they understand the link between the report and the original data? For example, the details of a CNV algorithm are not always transparent to the clinical end user,” says Kohane.

Kohane praises the progress made by a handful of genomics groups in annotating medical genomes, including the work of the team at the Medical College of Wisconsin. “They all did a terrific job, heroic efforts – from the publications, it seems evident they’ve used lots of computation and inspiration and knowledge of the disease(s). What’s not clear is that the effort could be generalized, across a large number of diseases. We’ve seen panels of experts working hard to help one patient using everything they had, where much of it is in their head.”

Children’s Hospital staff note a number of potential pitfalls to be overcome by the contesting teams, including:

- Inconsistent or non-specific sequencing results and non-interoperable processes
- Conflicting gene variant annotations and classification
- A hodge-podge of non-standardized databases
- Lack of standards concerning individual privacy and data access
- Resulting reports that are not clear or useful to doctors, genetic counselors and patients

Full information about the CLARITY Challenge is available at: http://www.childrenshospital.org/CLARITY 

January 10, 2012

Kevin Davies : 

In its blog, The Spittoon, 23andMe recently posted a Top Ten list of the consumer genomics firm’s favorite research papers of 2011 

Not surprisingly, the selections focus on the plethora of genome-wide association studies (GWAS) that still dominate many of the leading genetics journals. 23andMe’s top choice just happened to be one of its own papers, but I wouldn’t quibble with that decision too much.

Last summer in PLoS Genetics, 23andMe researchers published a paper mapping two novel risk genes for Parkinson’s disease by mining data on thousands of Parkinson’s sufferers among its 125,000 customers. The 23andMe strategy flips traditional GWAS on its head: rather than select thousands of individuals with a particular disorder and then perform a GWAS, 23andMe performs the genotyping first on its full database, and then stratifies by disease. It is groundbreaking science like this that serves as a swift rebuttal to those who insist on maligning the consumer genomics company as merely “recreational genomics."

What if we broaden the criteria slightly and consider papers focusing on NGS? Of the papers that stood out to me, several focused on the introduction of exome and genome sequencing and analysis in the clinic. Pride of place goes to the landmark report in Genetics in Medicine by Elizabeth Worthey, Howie Jacob and colleagues at the Medical College of Wisconsin in ending the diagnostic odyssey surrounding Nicholas Volker, a 7-year-old boy with a mysterious intestinal disorder who was successfully treated following the discovery of a rare genetic mutation. The peer review paper was formally published in 2011, a couple of months after a Pulitzer Prize-winning series of articles ran in the Milwaukee Journal Sentinel. 

Two papers in the Journal of the American Medical Association from the Washington University team led by Timothy Ley, Elaine Mardis and Richard Wilson illustrated the potential of whole-genome sequencing analysis in cancer patients. One revealed a cryptic fusion oncogene in a patient with acute promyelocytic leukemia with therapeutic implications; the other identified a novel p53 mutation in a patient with increased cancer susceptibility. 

Also of note was the sequencing of a pair of teenage twins with Dopa-responsive dystonia, by Matthew Bainbridge, Richard Gibbs and colleagues at the Baylor College of Medicine that pinpointed the causative gene mutation, and was published in Science Translational Medicine. 

From China, BGI published twenty NGS papers in 2011, including the genomes of the naked mole rat and the hybrid Escherichia coli strain responsible for several fatalities in a food poisoning outbreak in Germany last summer.

So what were your favorite, most impressive NGS papers of 2011?

January 6, 2012

Richard Holland : Capitalizing on next-generation sequencing requires as much attention to technology and computer science as life science. The biggest players in the life sciences have also realized that no one will get ahead by “going it alone.” Instead, they are working together pre-competitively to develop open solutions that will benefit the entire industry. The Pistoia Alliance has succeeded in building a unique coalition of industry players - the world’s top pharma companies, life science information, services, and technology suppliers, and academic researchers - to resolve common barriers to R&D innovation, such as the handling of “big data”.

An exciting example of a Pistoia Alliance-led project of particular interest to the NGS community is the Pistoia Alliance Sequence Squeeze Competition, which will award a $15,000 cash prize to the developer of the best new, open-source algorithm for compressing NGS data.

Currently available compression technologies, which enable labs to store data from sequencing runs, are faltering under the data volumes produced by NGS. Pistoia Alliance members recognize that compression solutions may well come from computer scientists or mathematicians - hence the Alliance’s willingness to put forward a generous monetary incentive to encourage anyone to develop a better algorithm.

The judging panel further highlights the importance of this issue to the sequencing community: BGI, the Broad Institute, and the Wellcome Trust Sanger Institute have all put forward staff to judge the competition.

The competition is open to ANYONE, because it recognizes that life scientists may not necessarily have the expertise to resolve this “big data” problem. The answer may lie in statistics, mathematics, computer science, physics, or other non-biological disciplines, so the Alliance is spreading the word as widely as possible in order to encourage entries from previously untapped sources.

Entries can be submitted via the contest website at http://www.sequencesqueeze.org, which also contains details of the functional requirements for entries and some sample code to use as a starting point. Judging of entries takes place within the Amazon EC2 cloud and so we require entries to be submitted using Amazon's S3 file system.

As an incentive to have a go and enter the contest, Amazon is generously offering the first 40 entrants a $20 voucher for use with their cloud services. The competition closes to new entries at 5:00 pm GMT on March 15, 2012. Winners will be announced at the Pistoia Alliance Conference in Boston on April 24, 2012 (held in conjunction with this year’s Bio-IT World Conference & Expo).

The Sequence Squeeze Competition is just one of the projects the Pistoia Alliance is sponsoring. We also have an active effort underway to develop shared cloud services for storing and analyzing NGS data, which we call Sequence Services. The Alliance website at http://www.pistoiaalliance.org has full details of this and other ongoing projects.

December 14, 2011

Kevin Davies :  Last week’s NGS Leaders webinar on De Novo Assembly of Complex Plant and Animal Genomes prompted more than 300 scientists and informaticians to pre-register, which speaks to the ubiquity and challenge of assembly complex genomes using short reads. Our three speakers – Mario Caccamo (The Genome Analysis Centre, UK), Ian Korf (UC Davis) and Jeffrey Rosenfeld (UMDNJ), outlined several key pointers in tackling complex genome assembly.

“Every genome has its own story in terms of repeats,” says Ian Korf, associate director of bioinformatics at the University of California Davis Genome Center. Korf is one of the principal organizers of  the Assemblathon - a competition to identify best practices in the de novo assembly of complex plant and animal genomes.

Results of the first phase of the Assemblathon were recently published in Genome Research. You can also read more about the Assemblathon at Bio-IT World.

“Every genome is a complex genome - even the simpler ones are pretty complex. There’s no easy genome,” said Korf.

The Assemblathon participants – 17 groups in all - were challenged to assemble a synthetic chromosome of some 96 million bases. Commenting on the results, Korf said: “A lot did a pretty good job, but it’s more difficult to assemble regions with more mutations, so the coding regions were assembled better than non-coding regions.”

The assemblies were ranked by various criteria, including contig and scaffold paths, structural and copy number errors. The top five entrants emerged as:

 -Broad Institute (ALLPATHS-LG)
 -BGI (SOAPdenovo)
 -Wellcome Trust Sanger Institute (SGA)
 -DOE Joint Genome Institute (Meraculous)
 -Cold Spring Harbor Lab (Quake, Celera, Bambus2)

Several useful tools emerged, says Korf, but experience in using the tools makes a big difference. “We found that sometimes two groups will use the same assembler, but the group that knows a bit more about the assembler might do a slightly better job. It’s something of an art at this point,” said Korf.

Choose Wisely 

Korf says that wisely choosing the many different parameters involved in de novo genome assembly is difficult and “probably shouldn’t be attempted by amateurs.” He advises inexperienced users to “contact one of the major sequencing centers and get them to help you. Doing it on your own is pretty much guaranteed to give you a sub-optimal assembly… Don’t jump into genome assembly thinking it’s just like any other bioinformatics problem you can hack with some Perl scripts.”

It starts as far upstream as DNA library preparation. “You don’t want to choose the assembler as the last thing you do,” says Korf. “It must be in conjunction with the sequencing technology, how are the libraries made, the full equation. You can’t do it stepwise… So much is dependent on having high quality sequence and making your libraries correctly.”

Another wise move, says Korf, is to perform a pilot project to explore the content and gauge the overall repeat content of the genome in question. “You should do a little homework ahead of time to get an idea of GC content and other factors,” says Korf.

The availability of longer read lengths, such as those produced by the Pacific Biosciences platform, should prove a boost for genome assemblies. “The long reads are fantastic, but the error rate is a bit of an issue,” said Mario Caccamo, head of bioinformatics at TGAC and a fellow co-author of the Assemblathon I report.

But Korf says the PacBio reads can prove very useful in integrating with short read data: “Genome assembly with longer reads will get much, much easier. The game will be completely changed with reads on the order of 10 kilobases.”

Korf believes the NGS community - “super smart people, full of competitive spirit” – will figure out how to use these 3rd-generation technologies. “Right now, they haven’t had enough time to figure out how to put it all together, but they will pretty soon,” he says. “What you’ll get three years from now will be a lot better than today.”

Clearly audience response suggests we revisit this topic in the near future. What NGS-related topics would you like to see presented in a free NGS Leaders webinar?   Email Janine with suggestions.

November 15, 2011 

Tony Flynn : Last week, I attended the Personalized Medicine Conference (PMC), moderated by Dr Raju Kucherlapati. It was, yet again, outstanding in terms of quality of content, presenters, and networking. Immediately afterwards, GenomeQuest and NGS Leaders hosted over 30 moderators and Dx executives at a post-conference workshop to immediately exercise and apply the “best ideas” from the Personalized Medicine Conference across six topic areas. Below are my top “takeaways” from the conference and workshop: 

1) 80% say sequencing value will be in “interpretation”
In the case study on “sequencing technology” run by Richard Hamermesh of HBS, the audience was asked:
In 2021, which of the following sequencing segments will be strongest: hardware, consumables, service, or interpretation?
The answer: eighty percent said interpretation. The viewpoint that interpretation of the data will be challenge #1 in personalized medicine was repeated by several presenters, including: Lee Hood of ISB, Stephen Spielberg of the FDA, Dave King of Labcorp, John Nierderhuber of Inova, and Hakan Kakul of Pfizer.

Immediate good news here: I think that we’re getting over the initial fear of the whole-genome sequencing (WGS) “ocean of data." Yes, we’re understanding that WGS is a technology and that we don’t have to digest everything it produces — we can focus on the data of most interest and use.  Just like we don’t have to watch all 800+ TV channels to justify and enjoy cable service, there’s amazing value in “targeted interpretation.” And, over time, we’ll learn more and expand our targets.

2) PM industry integration is happening
In order to take hold, personalized medicine requires a tighter integration of the healthcare pieces — otherwise, benefits won’t accrue to the investors and the new economic wheel won’t turn. Here, I am encouraged as I see a combination of top-down and bottom-up change agents at work.  Industry leaders such as PMC/FDA/VA are proactively creating an environment for motivating and guiding this integration.  And, industry players — including VCs, Dx companies, labs, sequencing vendors and payers — are working amongst themselves to understand and incrementally affect this integration.
(BTW, progress and thoughts on the regulation front: we heard from many Dx leaders that the FDA is open-minded and willing to be led in PM – so meet early and often in the development/approval process.) 

3) Our aim should be squarely on whole-genome sequencing
While the intermediate technologies of gene-panels and whole-exome sequencing will offer substantial rewards and lessons learned, the economies-of-scale and medical revelations granted by WGS justify that our major investments and best minds focus on this final destination.  After all, according to Partners Scientific Director, Scott Weiss, “WGS will render targeted sequencing obsolete in 4 years.”
As breathtaking as the falling cost-curve of sequencing has been in the past decade, I think we’ll be equally awed by sequencing cost and quality improvements in the next few years. Specifically, I believe that the market force of an expanding set of 3rd generation vendors and technologies (over 10 listed in HBS case study) will enable whole new personalized medicine applications and create whole new markets.

4) VCs and Wall Street are becoming increasingly supportive of PM/MDx
I appreciated the inflective thoughts of Brook Byers of Kleiner (“we are entering the early days of PM“) and Amanda Murphy of William Blair (“we’re at an economic peak of uncertainty in PM“).  Byers was most enthused about the Dx side and influenced by long-term, wellness managers and payers. Also indicating enthusiasm are the funding of the above 3rd generation vendors and warming of MDx acquisition activity, including the $.5B acquisition of Clarient by GE Heathcare.

One of the more interesting dynamics as we arc from genomics for drug/disease research to clinical application is the associated pivot from a largely foundation-funded market to a commercial market — aiming to improve and provide economic value to a $5T global healthcare market.  In my opinion, this adjustment to a commercial market is where much of the management challenges and opportunities lie.

5) The industry needs to agree on a global “atlas” of genotype/phenotype database
This is front and center of many thoughtful personalized medicine talks over the past year.  At PMC, I began to see significant movement in this direction: a) organizations planning the integration of genomics with the EHR which will speed genotype/phenotype associations, b) teams structuring phenotype-rich, genotype-enabled clinical trials, and c) a proposal for a standard platform for research labs to establish and share clinical evidence.

6) Much effort/$ should be put into enabling PM at community hospitals 
Gregory Feero of NHGRI thought it worth noting — from a conference operating deep inside HMS — that 95% of healthcare happens outside academic medical centers.  Well played.  One example of progress is the KEW Group, which is building a national network of PM-based community cancer care centers.

7) The Dx industry is preparing its economic case for MDx
On the one hand, Dx informs 70% of medical decisions and MDx holds immense promise for fundamentally improving healthcare.  On the other, Dx amounts to just $40B of the $5T healthcare industry and the assigned skeptic at the conference (artfully played by Dr Ezekiel Emanuel) waged a blistering attack that personalized medicine makes little/no economic sense. What gives?

Clearly, MDx is undervalued in the healthcare industry — our payment system favors therapy/technology over diagnostics/interpretation.  One giant step forward would be to argue the economic case for MDx.  And I foresee the PM coalition and industry preparing two pieces: a holistic, multi-factor economic argument for MDx to spur reimbursement change and the associated decision support to inform day-to-day care.

8) We continue to be guided and inspired by Dr Lee Hood
n accepting his leadership award, Lee Hood offered a wonderful combination of science vision and medical practicality to guide the path forward.  In particular, he was most excited about: a) family-based studies, proven to reduce errors by 70% and shrink solution space by 100x, b) analysis of single cells, and c) system-level considerations and tools required to address the “grand challenge” of personalized medicine (complexity).

 November 2, 2011

Kevin Davies : A remarkable public-private coalition of universities, medical centers, technology partners and private philanthropists has created the New York Genome Center (NYGC). The center was officially unveiled in a ceremony at Frank Gehry’s ICA Building in Manhattan this morning.

The coalition is a triumph for Nancy Kelley, NYGC’s founding executive director, who made the creation and funding of the center something of a personal quest over the past 15 months, together with Columbia University’s Tom Maniatis and Sloan Kettering Institute director Thomas Kelly.

"When I first talked to Tom Maniatis and Tom Kelly about this, we were operating with a cell phone and a Hotmail account! 12 months later, to have raised $120 million and brought this number of institutions together is really quite extraordinary," said Kelley.

Kelley recently gave Bio-IT World her first in-depth interview about the creation and vision of NYGC. (Excerpts from her interview will also be published in the November/December issue of Bio-IT World.)

"This is one of the most exciting national developments in genomics and medicine," said Richard Gibbs, director of the Baylor College of Medicine Human Genome Sequencing Center. "This new venture will synergize the efforts of some of the nation’s strongest research institutions, most outstanding researchers and vibrant communities. New York will be a new hub of genomics."

"Nancy Kelley and Tom Maniatis have done a remarkable job of bringing the 11 academic institutions together around this shared purpose," Marc Tessier-Lavigne, president of Rockefeller University, told Bio-IT World. "It required vision, determination and keen diplomatic skills to get the leaderships of the different institutions to realize how much more we could accomplish together than in isolation, and then to get everyone to sign on the dotted line."

Tessier-Lavigne continued: "It is a terrific accomplishment in itself, and also provides an important model for cooperation among New York institutions, which will be increasingly important as we work to build the biomedical enterprise in New York City and to attract pharma and biotech companies here."

One of the frst decisions made by NYGC was to select Illumina as its initial sequencing platform. "By choosing Illumina as its next-generation sequencing (NGS) provider, NYGC is showing its commitment to making the vision of revolutionizing personal healthcare a reality," said Jay Flatley, president and CEO of Illumina. "The launch of NYGC ranks as a significant development in advancing the knowledge and understanding of health-related genomics."

Harold Swerdlow, head of sequencing technology at the UK’s Wellcome Trust Sanger Institute, expressed excitement about the arrival of a major genomics hub in his home town. "The coming together of so many great institutions to form the New York Genome Center represents the culmination of a lot of hard work and a clear vision. Nancy and the other founding members should be applauded for this achievement. As one of NYGC's nearest neighbours to the east, we wish them all the success in building a world-class facility."

Also offering congratulations was Spike Willcocks, VP business and corporate development at Oxford Nanopore, a British NGS company. "We are excited that the NYGC team is building an exceptional technology development team as well as building a world class core facility," said Willcocks. "This is the mark of a team seeking to lead with innovation as well as provision of genomics services. We are really looking forward to working with NYGC’s Innovation Center."

The funding for NYGC, which could open as early as March 2012 with a location in central Manhattan almost settled, comes from a variety of public and private sources, including 11 institutional founding members (see below), private philanthropists, founding member companies, technology collaborators, as well as the New York City Economic Development Corporation and the New York City Investment Fund.

Made in Manhattan  

Kelley is a lawyer and commercial real estate developer who spent much of the past two decades working on behalf of biotech and non-profit medical organizations. Several years ago, while working for Alexandria Real Estate, she oversaw the development of the East River Science Park in Manhattan -- three towers, nearly $1 billion and 1 million square feet.

Two years ago, Kelley began working with a client seeking to establish an institute for personalized medicine, discussions that flirted with New York as a possible location. But while that institute did not materialize as originally conceived, Kelley said it "opened up the idea and possibility of introducing a large sequencing operation in New York. Given the fact I’d been working there for ten years and had many long-standing relationships with scientists there, I brought it to New York to see if there was interest… Things developed from there."

Kelley admits there was enormous skepticism around the proposal, but she was undaunted. After consulting with Maniatis and others, she met with representatives from leading New York medical institutions in August 2010. "It started with Columbia, went to Sloan Kettering and Rockefeller University," she recalled. "They enthusiastically endorsed it, to the extent that within 30 days, we had eight institutions putting seed money into a feasibility study." The seed funding was less than $1 million, but enough to get the venture going.

Eventually 11 charter institutions signed on (see below) including Cold Spring Harbor Laboratory and the Jackson Lab from Maine (where Kelley serves on the Board of Trustees). Perhaps the only notable abstention among New York academic organizations is the Albert Einstein College of Medicine of Yeshiva University. A spokesperson told Bio-IT World: "Einstein chose not to join NYGC because we felt it was not the most cost-effective approach to providing our faculty with genome sequencing services."

Kelley says the vision for NYGC is "to achieve transformational results for healthcare and research… For a long time, [New York has] had the leading global institutions in healthcare, but for whatever reason, haven’t always come together to collaborate and leverage that strength. With this enterprise, it will allow them to do that and take their role on the global stage -- as they should be."

At the core of NYGC will be large high-throughput sequencing center, offering services to founding members and other organizations. Much of the research focus will be in bioinformatics. "There’s also the idea of an innovation center that would introduce new technologies that would be utilized throughout New York," she says.

Kelley said getting NYGC off the ground has been "very, very challenging," but the process was helped by institutional leadership "knowing how important this was going to be for New York." Another key factor was the "participatory and collaborative" nature of the process. "That helped everyone feel they were… on the same playing field, no matter what their size," she said.

Many issues inevitably cropped up about the way the center would be governed. "Some institutions stepped back and stepped forward again," says Kelley. "The reasons for hesitation by some Institutions were more organizational than financial. Some of the institutions are in the midst of major building projects and research programs, so [had to ask] whether spending capital in this area was more important to their ongoing operations."

Kelley’s Heroes  

Funding NYGC proved to be a massive undertaking. "There are a number of pieces to the quilt that had to be knit together to be able to put this all together," said Kelley. "One of the strengths of this effort is that its success is not dependent upon one funding source, especially a public funding source, which has proved to be a problem in some other large projects like this one."

Kelley says Maniati played a pivotal role. "He was the first person whom I talked to about this, and has been instrumental at every level in guiding this forward. So we’ve really done this together."

She also praised Kelly and the relatively new leadership at Sloan Kettering and Rockefeller University -- Craig Thompson and Marc Tessier-Lavigne respectively. Russ Carson (Welsh Carson/New York City Investment Fund) "immediately saw the benefits of this to the City," and is now chairman of NYGC’s Board of Directors.

NYGC’s bioinformatics center will be named after the Simons Foundation, the first major philanthropic donor, offering a $20-million matching challenge grant. The Bloomberg Philanthropies have kicked in $2.5 million. In addition to Tony Evnin’s "very significant commitment to the Center," Carson has also pledged what Kelley calls "a very substantial sum of money."

There are two industrial partners – Hoffman La Roche and Illumina. Kelley says both Illumina and Life Technologies were invited to make presentations on how they would partner with NYGC. "In the end, there’s just been enormous progress made by Illumina in their productivity and turnaround times this year, and that proved to be one of the deciding factors," says Kelley.

NYGC expects to launch with 30 next-gen sequencing instruments in its first year. "This will not be an exclusive technology in any way," Kelley noted. "In the Innovation Center, we’ll be testing new technologies and making them available to the scientists in New York."

A search committee (chaired by Evnin) has been assembled to recruit a world-class scientific director. In addition to the sequencing center, serving the founding members, pharma collaborators and hospitals, Kelley says there will be "a very robust bioinformatics presence" and an internal research program.

The Innovation Center will allow scientists to use the facility and develop new technologies and products. A training component is planned in conjunction with Cold Spring Harbor Laboratory and other organizations. And, Kelley said, there will be a small philanthropic unit.

Kelley fully expects there to be a strong clinical component to NYGC. "There will be a CLIA-certified portion of the facility and we’ll be interacting very closely with hospitals like NewYork-Presbyterian Hospital and North Shore-LIJ."

As for Kelley’s future role, she points out that creating the strategic plan and raising the money is only a small component of building a successful institute. "There’s a huge ongoing financial, executive and operational role that has to be put together with a large organization, and I’d expect to play a key role in doing that," she said.

"At one point, Richard Gibbs said something to me: ‘You have to be absolutely fearless to do this.’ He’s right… I don’t think there was one day this year when I had full confidence we’d actually make it, but I knew it was important to try."

 October 24, 2011

 Kevin Davies :  Two weeks ago, I was making conversation with guests at the Burrill Personalized Medicine Meeting in San Francisco, when I casually asked Dietrich Stephan (co-founder of Navigenics) what he’d been up to lately.  

Stephan replied that he was involved in a couple of exciting new ventures. One was a still unnamed company just getting off the ground in the genome interpretation space. The other was a “4^th-generation” nanopore sequencing start-up called Genia. He asked if I’d like to meet the CEO, Stefan Roever, and the next day, we were holding an interesting conversation in the hotel bar about Genia’s platform and prospects. The full story can be found over at bio-itworld.com today.

Roever says Genia can be considered a 4^th-generation platform as follows:
“If Ion Torrent (electrical detection but requiring amplification) and Pacific Biosciences (single-molecule but optical) are 3^rd-generation [sequencing technologies], then we're 4^th-generation (single molecule, electrical detection). That's the holy grail, because it combines low-cost instruments with simple sample prep. So we'd like to think of it as last-gen!”

Roever has enjoyed considerable success in his entrepreneurial career, but has never taken on something like Genia. The touted hallmarks of the platform include high parallelization, a base/second read out, and control over DNA traversing the nanopores. These are still very early days, however, and it will likely be a year or two before we see much in the way of real sequence data, let alone a working prototype instrument.

That hasn’t stopped Life Technologies from placing a sizeable bet (Stephan says “double digit” millions of dollars) on Genia, as the sequencing giants jockey for the next big (or little) thing in next-gen sequencing (NGS).

Speaking at the Burrill meeting in early October, Life Technologies CEO Greg Lucier was asked about the status of single-molecule sequencing technologies such as the “StarLite” program (brought about by the union of acquired technologies from Quantum Dot and VisiGen), which was presented at a couple of high-profile conferences in 2010. Lucier replied that single-molecule sequencing was still very active in the company, but if used, it would likely be on a derivative of the Ion Torrent chip.

Whether Genia will be a major player in the 4^th-generation of NGS platforms will be a fascinating question in the years ahead. Still, the arrival of a new player is to be welcomed. As far as new NGS platforms go, the field has been in a bit of a lull lately, waiting impatiently for the long-anticipated launch of new platforms from the likes of Oxford Nanopore and NABsys.

At CHI’s NGx conference in Providence, RI, last month, there was a pair of intriguing presentations from GnuBio and another nanopore technology, NobleGen. Another company, Intelligent Bio-Systems, has also been demoing its Max-Seq Genome Sequencer instrument (distributed by Azco Biotech).

October 20, 2011 

Keith Robison : (Part 2 of 2) The following joint session was on next-next-generation sequencing, the possible technologies of the future. Two of the talks were intriguing but describing very distant futures: single-molecule reversible terminator sequencing with optical tweezers and an optical variant on nanopore sequencing. The talk I would have love to have yanked into my session was a natural follow-on, with John Healy of GnuBIO describing their progress on a platform they hope to launch in the first half of next year.

In my talk I described a process of PCR amplifying samples in a thermocycler and then shipping them off to a vendor to run on the PGM. Barcoding was a natural inclination, given a sometime need to analyze multiple samples and amortize the run cost over those many samples. Gnu’s vision compresses this and simplifies it, as a single instrument both performs the amplifications and analyzes them, returning to the user a list of differences rather than data which must be processed further. All from a box slated to cost $50K and with consumables in the $50-$100 per sample range with sample-to-data times projected at 3 hours.

Gnu’s approach is based on picodroplet technology and continues the trend of pushing most of the guts of the technology into the disposable cartridge. Microfluidic channels in the cartridge convert samples to large droplets which are merged with droplets bearing primer pairs; imagine one of those droplet-generating desk toys shrunk a few zillion-fold. A serpentine channel moves each such amplification droplet through hot and cold zones to perform PCR. Each droplet is then split further into smaller droplets, which are in turn merged with detection droplets. Each detection droplet contains a specific hexameric detection probe, and is also color-coded. After performing a primer extension reaction, the color codes and signal are read. All of the microfluidics are in the disposable card, with new applications requiring new card designs.

The detection chemistry is a simple variant on sequencing-by-hybridization (SBH). Hybridized hexameric probes are extended, resulting in the activation of a dye molecule. GNU is aiming this towards the resequencing market, which greatly simplifies SBH. By examining both the positive and negative signals and comparing against the known sequences of the amplicons, variants can be detected as unusual signatures. This is very much easier than attempting de novo SBH, which must reconstruct the sequence from the signals. Furthermore, the system should be robust to a certain degree of false positive and false negative probes; the complete ensemble of probe signals can be used to weight various models of what sequence the amplicon contains.

Note also that the signals are purely binary; presence of two copies of a hexamer does not lead to a different signal from an amplicon containing only one. The “read length” of the system is currently approaching a kilobase, but it is important to note the differences from reads on other platforms. SBH cannot read any repeat longer than the probe length (6), and it is easy to construct variant scenarios that cannot be distinguished. Read lengths here are really amplicon lengths, with the limitation being the complexity of the probe library required. Healy proposed that another four-fold increase in amplicon size by lengthening the probes to heptamers and using four cards, each with a different quarter of the library, to sequence these. But, while these are important caveats, they simply rule out a small number of genotyping or mutation detection applications. Also, in the cancer space one generally works with FFPE DNA, which is inherently fragmented to about 450 base pairs; GNU is already reading much longer than this.

A number of strengths from this approach are apparent. In my PGM experiments differential primer performance led to different sensitivities for different amplicons; in GNU’s approach each amplicon is analyzed in its own picodroplet, eliminating cross-talk. The proposed cost of the consumables pretty much eliminates the temptation to bar-code; why bother when the run cost is so small? However, on the negative side the current system has a minor allele frequency somewhere around 20-30%, about that of Sanger sequencing. This is because each original amplification droplet is expected to carry many copies of each amplification template. However, in response to my question on this topic, Healy commented that by diluting the sample so each droplet contains about half a genome, then very high sensitivity should be achievable. It is also easy to imagine how the system could be used for other detection modalities, such as single-base extension or a probe ligation assay or just a probe-hybridization assay. The system would also naturally be able to slide into digital PCR. Could COLD-PCR be adapted to this platform? That would require the hinted common thermal profile across amplicons, but once this is accomplished it would appear to be a natural fit and another possible approach to detecting rare alleles.

Whether any or all of this will come to pass will depend on successful launch of their platform next year. Until then and probably continuing afterwards, many will be performing experiments similar to mine to develop the next generation of cancer mutation assays, as well as using rapid platforms such as PGM and MiSeq to follow-up on discoveries from germline and somatic exome or whole-genome sequencing. 

Read Part 1 

October 11, 2011 

Keith Robison : (Part 1 of 2) I had an opportunity recently to chair a session at CHI’s Applying Next-Generation Sequencing meeting in Providence RI which was a nice microcosm of cancer genomics, covering in three talks one important corner of that vast space. I’ll also steal a bit from a talk in the joint session with Next-Generation Data Management which followed, as if I had been an omniscient and all-powerful chair, I would have yanked it into my session.

Giulia Fabbri of Columbia University led off by describing a successful scan of chronic lymphocytic leukemia (CLL) patient samples to identify recurrent causative mutations.  Using exome sequencing on five CLL samples, a set of 48 candidate mutations were identified, which were then validated on a larger panel.  The big fish netted by this campaign are activating mutations in NOTCH1.  The most common type of NOTCH1 mutation seen is interesting, as they are frameshifts near the C-terminus, which is the location of a destabilizing domain that targets NOTCH1 protein to the proteasome.  Hence, the mutations remove a negative influence, enabling a higher degree of oncogenic signaling. Other NOTCH1 mutations seen in CLL apparently have a similar effect, as Fabbri reported that so far there seems to be no difference in the clinical course of the truncating mutations versus other mutations.  Any NOTCH1 mutation appears to be a serious negative prognostic for the patient.  One striking bit of luck is that the frequency of NOTCH1 in CLL is about 1%, which means a sample of 5 samples could well have not included this mutation.  Further studies will use larger cohorts to scan for other mutations, as well as cohorts focused on more aggressive forms of the disease.

Mike Makrigiorgos of the Dana Farber followed with a discussion of his COLD-PCR technique and its extension to second-generation sample preparation. COLD-PCR is a twist on standard PCR in which each cycle contains two extra steps which result in perfectly matched sequences staying double-stranded and encouraging mutation-bearing fragments to be single-stranded. This is much like the reverse of consensus methods in synthetic biology for reducing errors; whereas in gene synthesis the common, correct matches are desired, in hunting rare mutations from clinical cancer samples there is a desire to prejudice the amplification against the wild-type. Makrigiorgos showed data on the Illumina platform in which samples with a minor allele frequency of a few percent were buried in noise with standard PCR, but became very strong signals with COLD-PCR sample preparation. Many of the questions after the talk were aimed at better understanding the degree to which each amplicon must have a custom COLD-PCR protocol; the early experiments benefitted from a thermocycler capable of running each well on a different program. But, Makrigiorgos gave brief sketches of extending COLD-PCR to emulsion PCR and hinted at changes which will allow each sample to be run in a common thermocycling scheme.

The final talk of the session was given by me describing my work recently at Infinity Pharmaceuticals on using PCR and the Ion Torrent PGM platform to search for mutations.  I described some of the successes and challenges I’ve discovered, some of which will be familiar to readers of my Omics! Omics! Blog. An attraction of the platform is the ability to quickly design and validate assays, We’ve had success detecting mutations spiked into samples at less than 1% frequency, can detect many alleles simultaneously and generally observed good linearity between the predicted number of sequencing reads and the observed number of reads. The sensitivity we’ve observed on PGM is much better than Makrigiorgos was reporting for Illumina, though other groups have achieved very high sensitivity on the Illumina as well with standard PCR. On the other hand, we’ve also had great variability in the number of reads coming off the instrument and sometimes the reads decay badly before they get to the region bearing the interesting alleles. Attempts to barcode samples were successful, but different barcodes sometimes amplified at wildly different frequencies and a first attempt to correct this did not yield much improvement.  Primer designs for the same amplicon also behaved wildly different, suggesting that empirical validation will be necessary. We also observed some unexpected KRAS alleles in a mixed cell line experiment; some of these appear to be noise that may result in different sensitivities for different alleles, whereas another unexpected allele appears to be the result of an unusual compound heterozygote in KRAS.

I also displayed one case of trying to find a 5-bp deletion with the PGM which was complicated by the homopolymer-calling errors on that platform. While the most commonly called allele was the correct one, several other deletion alleles were called in the neighborhood which could be rationalized as results of homopolymer miscalls. Also, inconsistency in the alignment of some nucleotides contributed to confusion in this case.  For example, the COSMIC-annotated deletion and the most common call were not identical, but given the sequence were equivalent. This points the need for better indel-calling software which can collapse such results.  One general advantage of the amplicon approach is it is not wedded to a platform; once MiSeq is available it should be straightforward to convert these amplicons to ones suitable for that instrument.

To summarize so far, Fabbri led us off with finding mutations by exome sequencing and then being faced with the challenge of scanning a larger sample cohort to assess frequency and relation to clinical characteristics.  Performing that scanning, and later routine testing in the clinic, is most commonly via PCR. Makrigiorgos proposed COLD-PCR as an approach to enrich that signal, since tumor specimens are always heterogeneous. I described a more head-on assault using Ion Torrent, though COLD-PCR might be an interesting twist, except when quantitative results are required (any allele-biased enrichment, by definition, distorts the allele frequency).

Read Part 2 

 September 29, 2011

Kevin Davies :  Ever since its launch in 2007, the personal genomics company 23andMe co-founders Anne Wojcicki and Linda Avey made no secret of their plans to offer their clients access to their individual genome sequence once the technology matured and the price dropped sufficiently.

A significant step came earlier this week, when 23andMe announced it would soon begin offering a $999 exome sequencing service, first come first served. The exome is just a small percentage of one’s total genome sequence, but it’s still a major leap forward for a company that has only offered genotyping until now.
 

23andMe isn’t trumpeting the news as much as one might have expected, in part because this information will be overkill to a large majority of 23andMe’s 100,000 (and counting) customers. As the company notes:

“The exome sequencing pilot is the first of its kind, and it is suitable for customers who are comfortable managing and understanding raw genetic data. If you don't know your exons from your introns, this pilot is probably not for you. This is for early adopters and supplies are limited.”
 

The company adds: “You'll be a trailblazer, one of the first people on the planet to know their personal exome sequence!”

23andMe anticipates taking its first orders soon.

 September 22, 2011

Kevin Davies :  At the outset, I should point out that one of the corporate partners that helped launch and support NGS Leaders is a Massachusetts software company called GenomeQuest. To their immense credit, the management team at GQ has stayed in the background and refrained from blogging or otherwise touting its services on this site.

However, having just stumbled upon a video of GenomeQuest CEO Richard Resnick presenting at the TEDx conference in Boston a couple of months ago, I cannot resist sharing it here.

Goodness knows it is hard to do justice to the excitement of a field as dynamic as NGS in a mere ten minutes, let alone communicate that to a broad audience, and do so with dollops of humor and panache. But Resnick manages to do all of those things.

You would be hard-pressed to find a better introduction to the growth and potential of NGS than right here...

 September 13, 2011

Kevin Davies :  Former VP Dick Cheney and the queen of hip-hop soul, Mary J. Blige, were two of the headliners at the annual Rodman & Renshaw conference in New York this week, featuring hundreds of private, small- and mid-cap companies reviewing financials and warning about forward-looking statements to large audiences of well-groomed investors and analysts.

During an evening reception held in the modest confines of the Metropolitan Museum of Art, R&R auctioned four items to benefit the McCarton Foundation for autism research. Three of the items were your standard all expense paid vacations to exotic destinations including a celebrity hideaway in Los Cabos and a retreat at 'the spiritual home of The Macallan' (normally only available to the scotchmakers' directors). The value of those getaways was put as high as $70,000.

None could compare with the value of the fourth item, however - a 'priceless' personal genome sequence, courtesy of Illumina and Knome, to be delivered on a portable hard drive. 

"Join celebrities like Glenn Close, Archbishop Desmond Tutu, Ozzy Osbourne, and Larry King [really?], who have obtained their sequences for tens of thousands of dollars," the guide read.

The organizers apparently felt that the bidding process would be aided if they held the auction several hours into an open bar, although pity the auctioneer trying to maintain order before an increasingly restless crowd of inebriated investment bankers waiting for Blige to hit the stage.

Suffice to say, the auctioneers didn't quite get their reserve price...

 September 7, 2011

 Kevin Davies :  It would be hard to confuse Paul Billings, chief medical officer of Life Technologies, with Matt Damon, and Mark Stevenson is definitely no Jude Law (despite the accent).

Nevertheless, these two Life Technologies executives play starring roles in a short new video that the San Diego-based company, in conjunction with the CDC (Centers for Disease Control and Prevention), has timed to coincide with the release of Contagion, the new all-star movie directed by Steven Soderbergh, which opens this week. Contagion is an action flick that centers around the sudden, catastrophic outbreak of a lethal infectious microbe.  

One of the chief advantages of the new Ion Torrent sequencing platform, which Life Technologies acquired last year, is its ability to generate sequence data quickly, with relatively long read lengths. Both attributes served the company well in responding to the deadly E coli outbreak in Germany last summer.

"We have the tools to respond to [an outbreak], and we can control it in most cases," says Billings reassuringly. Stevenson adds that Life Technologies offers a complete 'soup-to-nuts' solution to deal with future outbreaks, from sequence to confirmation to software.

August 9, 2011 : Mary Ann Brown (Executive Director, Conferences, Cambridge Healthtech Institute) : Making connections at conferences is my primary objective in participating. Sometimes these connections happen by chance outside the lecture room, but at times these connections need time and space to develop. For this reason, I created the Successful Sequencing Discussion Groups at my conferences. These tables facilitate conversations on specific discussion topics over morning coffee. At every conference the feedback from these discussion tables is: “we want more: more time and more topics.”

 Often for me, it is hard to decide which table to join because all the topics are relevant. The hour flies by too quickly. I know how difficult it is to stop the discussions and move back into the session room. Great science is achieved by sharing and listening!

So, I need your help in adding even more to these discussion tables. I am always looking for stimulating discussion topics and have encouraged speakers, sponsors, and exhibitors to host tables at the NG^x: Applying Next-Generation Sequencing conference this September 27-29. This year, I am also looking to the NGS Leaders community to suggest topics and potentially host a discussion table. Your online forum is perfectly suited to start a discussion. So what research questions keep you up at night? What would you like to discuss with the NGS community? Topics can range from instruments, research applications, pipelines, data analysis, trouble-shooting, protocols,  and what’s next. The NGS Leaders Community is growing rapidly. Leaders, lead the way.

Contact me for more information. I look forward to seeing you in Providence! ~ Mary Ann 

July 21, 2011

Mary Ann Brown (Executive Director, Conferences, Cambridge Healthtech Institute) : I was once asked, “Why do you organize conferences?” My answer: In my own way I am advancing scientific research. Specifically I design conferences to bring researchers together. All of my conference participants have different backgrounds, from academic research centers to start-up entrepreneurial companies to established research firms from biotech and pharma. These attendees are focused and excited about their research. It is evident by the energy and discussions that take place either from the scientific podium, during the question and answer sessions, at the poster sessions, in the exhibit hall, or just in the hallway. From my perspective, bringing the right researchers together and setting aside the time to focus on a specific research topic creates a collaborative community to advance science.

As an example, the NG^x Applying Next-Generation Sequencing and the Next-Generation Sequencing Data Management meetings this September 26-28 in Providence, Rhode Island are noted for advancing NGS technologies into the clinic specifically in the areas of personalized medicine and cancer. The companion data management meeting completes the picture with analyzing these NGS data sets. They are also affectionately known as the Providence NGS meetings.

Recently, I had the pleasure of interviewing three speakers from the meeting: Toby Bloom, Director, Informatics, Genome Sequencing Platform, at the Broad Institute; David Smith, Professor, Lab Medicine & Pathology, Mayo Clinic, and Gholson Lyon, Research Scientist, Center for Applied Genomics, Children’s Hospital of Philadelphia.

In these interviews, I asked about their experiences with NGS and how they are benefiting from the data bonanza. Toby discusses The Broad’s current and future data management infrastructure to support a major sequencing center’s data outpoint. David addresses his role in setting up a sequencing laboratory at a major cancer clinic and Gholson highlights his use of the software VAAST to discover rare Mendelian disorders.  

It has been a pleasure to watch the next-generation sequencing field explode over the last six years. When I first started organizing NGS meetings, it was difficult to even find a sequencing paper in PubMed let alone find a research scientist that was willing to part with their brand new sequencer to attend a meeting and share insights. A lot has changed since then. This disruptive technology has changed the research landscape and the landscape of research possibilities. NGS now allows rapid and in depth interrogation of the genome from DNA sequence to DNA regulation to transcription to determine the genomic underpinnings of health and disease. To sequence or not to sequence is no longer the question...

Click here to listen to the podcasts... Enjoy!

July 14, 2011
Allison Proffitt (Managing Editor, Bio-IT World) : What single event could most positively impact the future of NGS?  One response sums it up: “Uniformity in standards, analysis, more trained informaticians. The cost of sequencing is moot, now the data deluge is coming and none of the experiments are reproducible because of data storage and sharing data issues.”

When the results came in from the three surveys that make up The Future of Next-Gen Sequencing report, I was anxious to read through them—and it certainly was an undertaking! With over 1,400 respondents and more than 18,000 words worth of write-in responses, the full study represents a wealth of information and the message from respondents was loud and clear: there is a huge need for standards in the industry.

When we asked directly about standards, respondents were split over the best way to develop industry reference points for data management. Very few respondents thought the government should intervene, but researchers and informaticians generally favored user-driven directives while those IT professionals who support core facilities and manage and store data preferred that vendors include standards in their products. Perhaps that breakdown is predictable.

Though any solution will certainly evolve as the user community grows and more researchers have experience with the NGS workflow, the survey shows that it is already a problem worth addressing. Where are standards needed besides the inevitable question of how long and which data to keep? Should the standards be different for research data and clinical data? If our end goal is personalized medicine, is there really a distinction between the two? How do we balance standards that ensure reproducibility while still allowing for maximum creativity in dealing with a relatively new data type?

One respondent suggested “the development of industry standards that guarantee that only processed NGS data need to be stored (small footprint) and that those data are stored in a consistent format that is appropriate for any downstream analyses researchers from a variety of backgrounds may require.”

A tall order, indeed.

Over the next several months there will be much discussion here on NGS Leaders about what all of this loquacity actually means, and if you didn’t get to participate in the surveys on the first three rounds, there will be plenty of opportunities still to join the conversation. 

April 18, 2011                 

 Kevin Davies :  In May, I was privileged to be a guest speaker at the second annual conference on personalized medicine hosted by Larry Gold, professor at the University of Colorado (“CU”) and founder/CEO of protein biomarker company SomaLogic.

The GoldLab symposium brings together an impressively wide variety of speakers discussing trends in all facets of ‘omics research, personalized medicine and healthcare. Gold is an advocate of what he calls “longitudinal ‘omics,” the idea that personal health can (and eventually will) be monitored via a recurring series of simple blood tests using a sophisticated molecular techniques to detect fluctuations in select groups of protein biomarkers that predict the onset of cancer, cardiovascular disease, and many other conditions.

All of the videos from the 2011 GoldLab Symposium are now available on YouTube. Particular standouts in my mind, quite unrelated to next-gen sequencing, include Brandeis University professor Greg Petsko on the coming epidemic of neurological disorders and New York fashion photographer Rick Guidotti’s astonishing work on behalf of an organization called Positive Exposure, instilling extraordinary self-esteem in children with neglected disorders through the power of photography.

 

As for my own talk, with University of Colorado Nobel Laureate Tom Cech in the front row, I thought it only fitting to begin by congratulating the CU faculty and student body for its superb accomplishment in taking prime position in the latest ranking of North American party schools, published in that esteemed journal Playboy. From there, it was best to move on and talk about the technology and pioneers paving the road to the $1,000 genome:

Editor’s Note: In light of the recent E coli outbreak in Germany, NGS Leaders invited Joyce Peng from BGI to comment on the organization’s efforts to understand the culprit. Below Joyce describes BGI’s efforts to rally the international community in combating the outbreak. – Eric Glazer 

In response to the recent E. coli outbreak in Germany, BGI and its collaborators at the University Medical Centre Hamburg-Eppendorf have released their third version of the assembled genome, which includes new data from this E. coli O104 (ftp://ftp.genomics.org.cn/pub/Ecoli_TY-2482/Escherichia_coli_TY-2482.contig.20110606.fa.gz ). The FTP site contains a file that provides the PCR primer sequences which researchers have used to create diagnostic kits for rapid identification of this highly infectious bacterium.

Bioinformatics analysis revealed that this E. coli is a new strain of bacteria that is highly infectious and toxic. BGI and its collaborators, as well as a growing number of researchers around the world “crowdsourcing” this data, are exploring in depth the European disease outbreak and helping to trace the origin and spread of the lethal E. coli strain. The latest evidence is that a previous 2001 German strain is the most likely ancestor of the current strain, perhaps suggesting that a fast evolution resulted in the gain of more genes over the last 10 years. Further comparisons between the genomes of these bacteria will clarify why the latest outbreak has been so exceptionally pathogenic, and help frontline healthcare workers fight to control this new global outbreak.

Unfortunately the 2001 German strain currently has no publicly available genome sequence, although it was preliminarily analyzed during the original outbreak and stocks and samples were hopefully stored. In the great strides already made in just a few days by the community from sharing original genomic data, BGI has made an appeal to any labs which have isolates of this key strain to share samples and respective data.

The international community “crowdsourcing” and analyzing BGI’s most up-to-date genomic data now has a repository for this preliminary data, and BGI encourages scientists to use its latest improved assembly (http://www.ncbi.nlm.nih.gov/bioproject/67657) and follow the repository and its Twitter feed (@BGI_Events) for announcements and data updates https://github.com/ehec-outbreak-crowdsourced/BGI-data-analysis 

BGI and the Beijing Institute of Microbiology and Epidemiology researchers have also developed a straightforward PCR diagnostic protocol for rapid identification of the outbreak strain. The diagnostic method consists of two pairs of amplification primers that target the enteroaggregative- and hemorrhagic-associated genes (more detailed protocol is available on the BGI FTP site). Diagnostic results can be obtained within 2–3 hours after receiving the sample, and thus will be extremely useful for epidemic surveillance and detection of the bacterium. The complete test protocol for E. coli O104 is available at ftp://ftp.genomics.org.cn/pub/Ecoli_TY-2482/Specific_primers_for_PCR_detection.pdf. In an effort to help control the spread of this lethal bacteria, BGI and the Beijing Institute of Microbiology and Epidemiology will provide the designed and synthesized primers free to any disease control and research agency worldwide.

This comparative work is now of the utmost urgency, so please contact BGI to collaborate in this effort by contributing samples or data from strain HUSEC041/01-09591 (contact caosujie@genomics.org.cn).

Joyce Peng, PhD is Marketing Director for BGI Americas Corporation (www.bgiamericas.com). She can be reached at joyce.peng@bgiamericas.com  

June 1, 2011

Alexander Kamb : It's hard to read the writing when you’re at the blackboard, but we seem to be in the midst of a revolution. If you step back, you can see how NGS may be more than mind-blowing technology—it may actually reignite drug discovery and transform medical practice.

Like the dawn of recombinant DNA, monoclonal antibodies and PCR, medical science may be poised—after a long pause—for another discontinuous jump forward. It’s taken a full decade and a radical new technology to illuminate the path from the human genome sequence.

The realization of personalized medicine 

When I went to the doctor recently with (as it turned out) a minor ailment, his first question was: Do you have any relatives who have had heart problems? Imagine the improvement in precision of diagnosis if he had access to my genetic risk profile! Different DNA sequence variants are associated with different disease risks, and in the coming years the quantitative implications of these risk variants, in whatever combination you happen to possess them, will clarify.

Challenges of interpretation, privacy, and basic genetic understanding will persist (the subject of a future blog), but the benefits of this type of information are progressively attractive. Sooner than later, a once-in-a-lifetime genome-sequence determination will be part of our health care system. At a cost of $1,000 (or less), individuals and their physicians will view personal genetic information alongside symptoms to increase the reliability of diagnosis. Furthermore, genome sequence will play an increasing role in drug prescription, helping to select one drug from a menu to improve the chances of patient-specific efficacy and avoid adverse reactions, including serious ones like life-threatening liver toxicities. This myriad of genetic data will be acquired for everyone in a single NGS assay, and will be flagged on our personal health records.

Cancer diagnosis and therapy hold a special place for the utility of NGS. Given the enormous quantity of somatic DNA change that NGS is currently unmasking, we may assume that in the future the relation between a patient’s tumor DNA and his/her normal germline DNA will inform which drugs are prescribed, and how tumor burden is assessed following therapy. If the tumor bears an activating K-RAS mutation, for instance, it is futile to use an EGFR antagonist since the pathway is short-circuited. Furthermore, as tumors wane, and then wax, it will be vital to track the genetic changes that account for this evolution, to give the oncologists solid guidance for their counterattack on the relapsed tumor.

New targets and disease mechanisms 

Human genetics has been a rich source of new targets and disease mechanisms; for instance, oncogenes and tumor suppressor genes in cancer. Now we have the power of N: the technical capacity and economics to look at millions of common variants across tens of thousands of patients, or to examine smaller sets of individual genomes at the highest resolution possible—the nucleotide. With NGS, we can identify rare variants with larger effects much more easily than before. And with other genotyping techniques we can identify and quantify small contributions of individual loci to disease risk. Since small effects on gene function may be amplified by good pharmacologic agents (i.e. drugs), we now have a burgeoning number of new avenues for mechanistic studies, and pending some follow-up work, drug targets.

Two recent examples from the fields of Alzheimer’s disease (AD) and schizophrenia underscore the prospects for the new genomics. For more than a decade the only known genetic risk factor for late-onset AD was the APOE4 allele indentified by Allen Roses and colleagues in 1993. But in the past couple of years, nearly a dozen new loci have been defined that implicate several new biological mechanisms in the disease process, including immune function and protein internalization. In genetic studies of schizophrenia this year, Sebat and coworkers reported that gene duplication and resultant overexpression of VIPR2 causes disease—the impetus for a direct assault on this GPCR as a potentially druggable target. The pace of medically relevant discovery is accelerating in challenging diseases such as these, and in others such as autism.

Fatigue—even cynicism--followed the failure of genomics to live up to its post-Genome Project hype. In anticipation of the first publications of the human genome sequence, many genomics companies were valued at billions of dollars apiece. When it dawned on investors that disease cures weren’t declaring themselves among the billions of base pairs, much of this value evaporated. Malaise set in. But in fact, the genome sequence was useful infrastructure—no more, but no less. At last we have the technologies to begin to exploit it. The coming decade will realize some of the original promise: new biological insights and better medicines.

Alexander Kamb leads the neuroscience division at Amgen. He is on the Advisory Board of NGS Leaders. Email: akamb@amgen.com 

May 25, 2011

Eric Glazer : Last month I had the pleasure of being invited to BGI Americas’ first-anniversary party at the swank Bull & Finch club in downtown Boston. (The club sits above the famous Cheers pub.) I joined about 100 industry “dignitaries” for cocktails, dinner and entertainment which, along with guest toasts, sand painting, an illusionist and a DJ, included a passionate presentation from BGI America’s president, Huanming Yang.  

Like its European counterpart, BGI Americas was established in 2010 to broker (and maybe eventually perform) NGS services for academic and industry partners and customers. Guests at the anniversary reception included some of BGI Americas’ first big pharma customers – Pfizer, Merck, Eli Lilly, and Novartis – along with many of their support vendors (PR, marketing, etc), and the media (I guess that’s where I slipped in, although calling me a journalist would be an insult to those in the profession).

The following day, my colleague Kevin Davies (Editor-in–Chief of Bio-IT World and a true journalist) and I were invited to sit down for a discussion with Professor Yang, surrounded by a group of BGI staff including Joyce Peng (Director of Marketing, BGI Americas) for a fascinating interview. A more complete account of that discussion will appear in print at some point, but I thought Yang made some interesting points.

- A major moment in BGI’s early growth was marked by President Clinton’s public acknowledgement and support of BGI in 1999.

- BGI’s large purchase in 2010 of Illumina’s HiSeq NGS instruments was viewed as a huge yet calculated risk for the organization, but consistent with its philosophy of buying in bulk to take advantage of the economics.

- A big part of BGI’s culture is “to do something others are unable or unwilling to do.”

- BGI must “promote or stimulate global genius through international collaboration” and “genomics cannot be done alone but may be done internationally.”

- Yang predicted that BGI’s bank loans would all be paid off in about two years!

- BGI sees its two competitive advantages as its “scale effect” and its “young talent and bioinformatics expertise.” 

- “Personal relationships and trust are their most important assets.”

My favorite comment was when Dr Yang said: "BGI is not doing marketing at all." You should have seen Joyce's face when he said that!

April 18, 2011                 

 Kevin Davies :  In recent talks about NGS and the $1,000 genome, I’ve been quipping that the recent series of articles in the Milwaukee Journal Sentinel about the inspiring tale of Nicholas Volker had “Pulitzer Prize written all over it.”

Turns out I was right. The team of journalists and photographers have deservedly won the 2011 Pulitzer Prize for Explanatory Reporting, putting a human face on the potential clinical benefit of genomic medicine.

Volker was just 4 years old when doctors at the Medical College of Wisconsin sequenced his exome in a last-gasp attempt to find the root cause of his mystery intestinal disorder that required 143 surgical procedures.

The journalists first heard about the case in 2009, not long after Volker’s physicians had decided to embark upon sequencing. They were given permission by the medical team to follow the case, which identified a mutation in a known gene, XIAP. This in turn lead to a successful bone marrow transplant. The resulting three-part multimedia story was published in December 2010: http://www.jsonline.com/dna  

The Pulitzer Prize commendation reads as follows:

“For a distinguished example of explanatory reporting that illuminates a significant and complex subject, demonstrating mastery of the subject, lucid writing and clear presentation, using any available journalistic tool including text reporting, videos, databases, multimedia or interactive presentations or any combination of those formats, in print or online or both, Ten thousand dollars ($10,000)." 

“Awarded Mark Johnson, Kathleen Gallagher, Gary Porter, Lou Saldivar and Alison Sherwood of the Milwaukee Journal Sentinel for their lucid examination of an epic effort to use genetic technology to save a 4-year-old boy imperiled by a mysterious disease, told with words, graphics, videos and other images.” 

As I reported in the latest issue of Bio-IT World, the Medical College of Wisconsin team, led by Howard Jacob, is now employing whole-genome sequencing for certain additional patients after in-depth review and consent. At least two health insurance companies have paid for the sequencing, according to Jacob.

April 4, 2011                 

Eric Glazer : Over 150 people filled a ballroom at the San Diego Hilton earlier this month for a panel discussion, hosted by NGS Leaders and our partner GenomeQuest, on WGS applied to clinical diagnostics. The panel discussion was scheduled during Cambridge Healthtech Institute's Second Annual X-GEN Congress & Expo. In addition to the live audience, over 200 members of the NGS Leaders community logged into the webcast. The session was engaging and informative, and we are pleased to provide members of NGS Leaders with access to the on-demand version.  

In addition to the insights from participants in our panel discussion, I heard many other interesting comments throughout the week at X-GEN Congress, a conference with over 500 attendees from more than 20 countries. Many of the most interesting conversations took place outside of the sessions, in hallways or in smaller roundtables. Here I share some of the more memorable quotes...

· Countries with social medicine are more apt to participate in mass sequencing projects. 
· We need consortia that can educate the public on the risks and rewards of NGS. 
· We need to work together as an industry, even competitors, to educate physicians on leveraging NGS. 
· In 4-5 years, teenagers are going be posting their genome on Facebook for everyone to see. 
· NGS allows us to ask things we didn’t think to ask for.  
· Closing the gap between data and knowledge is our biggest challenge. 
· Making data findings actionable is the most important progress we can make (in next 24-36 months).  
· Harnessing the biologic diversity in the Amazon basin is one of the most important things we can do.  
· NGS can make dramatic changes in how healthcare works.  
· The rain forest holds cures to diseases that have yet to emerge. 

 March 23, 2011                 

 Kevin Davies, Editor-in-Chief, Bio-IT World :  Howard Jacob began his scientific career studying the genetics of rats with Broad Institute director Eric Lander, but for the past several years he has been telling anyone who will listen that genomic sequencing will reach the clinic by about 2014. His colleagues responded dismissively: “It will be a long time before we use genomic sequencing in the clinic—and no-one will ever pay for it,” they kept telling Jacob.

It turns out they were all wrong. In Milwaukee, Wisconsin, clinical sequencing has already arrived. Even more remarkably, insurance companies are (in some cases) offering reimbursement.

Jacob and his medical and informatics colleagues at the Medical College of Wisconsin made headlines late last year after they successfully identified the rogue gene mutated in a little boy named Nicholas Volker, who suffers from a rare and undiagnosed intestinal disorder. In a captivating talk at The Future of Genomic Medicine conference at the Scripps Institute last month, Jacob recalled the circumstances surrounding Volker’s diagnosis. (The Volker saga was reported in a superb three-part series in the Milwaukee-Wisconsin Journal Sentinel that has Pulitzer Prize written all over it.)

On June 27, 2009, Nicholas’ pediatric gastroenterologist, Alan Mayer, e-mailed Jacob to ask whether it was possible to sequence the genome of 6-year-old Volker. For six months, the boy underwent more than 100 surgeries to repair holes (fistulae) in his intestine, and his colon was removed piece by piece. Jacob decided his group could indeed sequence Volker’s genome—“How could you not?” he asked rhetorically—but elected to sequence just the exome (the protein-coding genes), as this would be simpler and, besides, it was all they could really afford at the time. Jacob collaborated with Roche/454 for five rounds of exome sequencing, at a cost of about $75,000.

Sequencing was easy compared to the data analysis problem—how to whittle down more than 16,000 unique DNA variants in Volker’s exome to a single causative mutation? Jacob paid tribute to his colleagues led by Elizabeth Worthey (ex-Rosetta), David Dimmock (ex-Baylor) and his bioinformatics team, even though their initial list of some 2,000 candidate genes proved incorrect.

The team found a point mutation in a highly conserved region of XIAP (X-linked Inactivation of Apoptosis). Jacob’s hunch is that Volker developed an immune response (perhaps to something he ate), but the mutated XIAP protein bound irreversibly, causing cell death in the intestines. But there was a more immediate concern: mutations in XIAP are linked with XLP2, a lymphoproliferative disease requiring a bone marrow transplant. Jacob informed the parents they had found a suspect mutation, but their son had a risk of cancer and could die if he didn’t have a transplant.

David Margolis, the program director of blood and bone marrow transplantation at the Children’s Hospital of Wisconsin, told Jacob: “If you put it in the medical record that it’s XIAP deficiency and the child is at risk for XLP2, I will do a bone marrow transplant.” “That’s the level of precision you have to have in order to effect an action,” said Jacob.

The Volker case study was published in Genetics in Medicine. Why such an obscure journal? “Because no-one else would take it!” Jacob shrugged. Editors and reviewers griped that Rick Lifton and colleagues at Yale had already reported a successful diagnosis using exome sequencing (in 2009), and that science is more than reporting a single case. I’m astounded at such short-sightedness.

No One-Hit Wonder 

It would be tempting to dismiss Volker as a one-hit wonder. “We’re from the Medical College of Wisconsin. No-one’s ever heard of us!” Jacob joked. But Jacob and colleagues are on a mission “to end diagnostic odysseys.” His group has switched to an Illumina HiSeq 2000 and moved to whole-genome sequencing, even though that “just created a whole series of new problems” in data interpretation.

The move to push genome sequencing into routine clinical practice requires as much skill in navigating bureaucracy as interpreting base pairs. “Trying to get this CAP- and CLIA-certified is a nightmare,” said Jacob. The Sanger sequencing validation alone required 547 pages of documentation. But there’s no choice: “If you want your clinical colleagues to use this, they want this certified,” said Jacob.

Jacob’s team has jerry-rigged a series of data analysis guidelines, dubbed Illumina Carpe Novo (“seize the new”), designed for clinical geneticists to analyze whole-genome sequences, not as a research tool.

Since the Volker case, Jacob’s team has taken on six more cases, five of which had been sequenced and were undergoing analysis as of early March. Cases, which must be deemed actionable, must be nominated by two physicians. Following case review and consent (which takes 6-8 hours on average), the patient’s genome is sequenced, the data analyzed, and counseling offered.

The sequencing step must be clinically useful, said Jacob. “This is not for research. Case selection is based on the interest to the patient, not scientific knowledge.” Another tenet is equal access: cases are selected regardless of the family’s ability to pay. Jacob is focusing on putative monogenic disorders that give rise to a distinctive phenotype. “We’re not ready for common complex diseases,” he said. Moreover, “WGS must have the ability to enhance medical decision making, not make a diagnosis. We don’t make a decision [solely] on a variant in the sequence,” he said.

The review committee, which meets monthly, is chaired by the hospital’s chief medical officer, and includes ethicists, a genomics expert, and three external physicians. Some cases might be approved, others held in a “parking lot,” while others require further testing. Even after the Volker episode, Jacob was told that physicians were too busy or uncomfortable to recommend genome sequencing. But since October 2010, the committee has been reviewing 5-6 cases per month.

Another thorny issue is data return and retention. What information is given back to the patient or family? The ethics team decided that data return was “morally permissible” and “should remain at the discretion of the informed parental choice.” Parents are asked from the beginning which data they want returned.

As for the conviction that no insurance company would pay for genome sequencing, Jacob said he’d placed a $100 wager with a British colleague that two insurance companies would cover the costs by the end of 2011. “He owes me $100!” said Jacob.

Even more remarkably, Jacob has been approached by an unnamed insurance company interested in collaborating to develop “an evaluation clinic” to assess clients before expensive diagnostics testing. The company wrote: “In situations where you determine that on average, the cost of routine testing will exceed the current contract price of whole-genome sequencing, we will authorize whole-genome sequencing as a first-line clinical test . . . We are excited about the ongoing clinical utility monitoring you have established as part of your clinical whole-genome sequencing program.”

Whole-genome sequencing might sound like overkill, but Jacob argues it can be highly economical for two reasons. First, obtaining a complete genome sequence can cost less than running a handful of single-gene tests (some of which costs thousands of dollars). “I think we’ve overlapped,” said Jacob. “I’m going for the once versus every single gene. It’s simply easier to do the whole [genome].” And of course, the pay-off should a causative, actionable mutation be discovered could save (tens of) thousands of dollars in unnecessary medical procedures.

Jacob says he’s not scared by the falling cost of data generation. Data management and education around clinical decisions, on the other hand: “that gives me heart palpitations.” The security of the data remains an issue. Patient families are naturally concerned about who will see the data and will the data be in the public record? Physicians don’t want to be liable for interpreting the rest of the genome. Jacob’s team has concluded that the genome sequence and variants are not part of the electronic medical record.

Nicholas Volker didn’t eat solid food for nine months, but before he left hospital, he was eating steak with A1 sauce. He is now home and “doing quite well.”

Whole-genome sequencing is just “another lab value,” said Jacob. “It’s not a crystal ball until we prove it’s a crystal ball. That doesn’t mean it doesn’t have utility. Let’s not forget: individualized medicine is about choices. We think data is part of that.”

“Whole genome sequencing has the ability to effect change,” said Jacob. As for the full cost of Volker’s analysis, he said: “I have no idea—and I’m not going to count.”

 February 11, 2011                 

 Kevin Davies, Editor-in-Chief, Bio-IT World :  MARCO ISLAND, FL - The annual Advances in Genome Biology and Technology (AGBT) conference remains the premier destination to witness the latest technologies and applications of next-gen sequencing (NGS). This year’s meeting, expanded by some 200 people to accommodate some of the overwhelming demand (several registrants from Boston and elsewhere didn’t make it), didn’t quite live up to the razzamatazz of recent years. But the absence of any brand new third- (or fourth-?) generation NGS platforms allowed attendees to focus more on some excellent science and range of applications.

Admirably comprehensive, real-time blog coverage (where allowed) was provided by an army of Twitter aficionados and the tireless Anthony Fejes at Fejes.ca. There’s also a very good two-part review from Prithwish Pal at Omically Speaking.

What follows are a few of my own observations and takeaways:

• Ion Torrent (now part of Life Technologies), which debuted its $50,000 Personal Genome Machine at AGBT last year, received some timely validation from the Broad Institute’s Chad Nusbaum. Over past 12 months, the Broad has pushed the machine’s run output up to Megabases (Mb), with one use being DNA quality control for Illumina runs (probably not the market niche Ion is looking for). Ion says it is currently getting 300,000 reads of more than 100 bases/run, while the Broad is typically about two weeks behind them. Improving the quality of the reads while halving the sample prep time are two key priorities for Ion this year, for which it is looking to the NGS community for help willing to reward handsomely.
• Congrats also to Baylor’s Adam English for overhauling teams from Liverpool and Tufts to win a free PGM: http://twitpic.com/3wm67t#  It’s (relatively) easy to give away a machine when it costs a tenth of the competition. Ion also offered yoga classes at 7 each morning, a nifty and original marketing ploy that I happily slept through.
• Life Technology’s 2^nd-gen SOLiD platform was overshadowed by Illumina in a procession of talks on opening day from some of the major NGS labs, but is pushing cancer genome applications as one of its most attractive applications. That is evident from its latest promotional campaign and the validation from speakers such as TGen’s David Craig, who spoke about SOLiD’s “sweet spot” in analyzing cancer genomes because of its accuracy, approaching 99.9%.
• PacBio screened its documentary, “The New Biology,” which first aired at the Air & Space Museum in Washington DC last November. It’s an impressive film, though I did miss Charlie Rose and the roundtable. Opening PacBio’s commercial workshop, co-founder Steve Turner creditably addressed the accuracy rate, which is hovering at 85% (c.f. 99%+ for more established platforms). While there is clearly room for improvement, some of which may come from incorporating data from the kinetics of nucleotide incorporation, there is impressive uniformity of sequence accuracy across a wide spectrum of GC content, in stark contrast to some other platforms. In the closing talk, CSO Eric Schadt discussed PacBio’s recent cholera genome paper in the New England Journal and “connecting molecular biology to clinical medicine.” There were also early signs of the value of integrating PacBio’s long reads with the more abundant short-read coverage of an Illumina for de novo genome assemblies.
• Illumina representatives brought along the new MiSeq machine, which will be officially released later this year. CSO David Bentley said the HiSeq 2000 (which had a launch spec of 200 Gb/run) has surpassed 1 Terabase/run in house. So much for Moore’s Law... There was also some promising early data on the genetic changes in the evolution of chronic lymphocytic leukemia (CLL). “This technology had the potential to direct future clinical trials and therapeutic decisions,” said Bentley.
• I thought one of the best talks was from Harvard Med School’s Tim Yu, who discussed the analysis of 40 genomes from Complete Genomics, selected from consanguineous families from the Middle East. Yu’s team was able to identify variations in five suspected autism genes, including potentially mild variants in a pair of known metabolic disease genes.
• My previously published interview with Complete CEO Cliff Reid made a bit of news. Reid says Complete will be producing somewhere between 800-1,200 human genomes by the end of 2011. The company is currently generating 400 genomes/month. Reid said Complete could expand its service to include transcriptome sequencing later this year, and hinted that expansion into Asia is another real possibility. I’m also struck that Lee Hood’s Institute of Systems Biology recently placed its third order with Complete, this one for 600 genome sequences.
• Oxford Nanopore unveiled its GridION “box” just days before AGBT, but none of the firm’s contingent attending the show spoke on the program, preferring it seems to lounge by the hotel pool. ONT’s scientific founder, Oxford chemistry professor Hagan Bayley, was a late scratch, but collaborator Mark Akeson (University California Santa Cruz) demonstrated some recent significant progress in single-strand DNA sequencing using nanopores coupled to DNA polymerase, which ratchets the strand through the pore. Akeson said that the system should be working for short reads, at least in an academic setting, later this year.
• Steve Salzberg (U Maryland) presented impressive benchmarking of Ben Langmead’s Bowtie DNA alignment software, which seems to outperform BGI’s SOAPdenovo and other established tools by a considerable margin. Bowtie 2 is on tap for release this spring, Salzberg said.
• Rob Knight (HHMI/U Colorado), with a quaint kiwi accent and sense of humor, presented an excellent talk on ‘the human microbiome’ – the results of metagenomic profiling of bacteria living in – and on – people, including detailed analyses of the different species living on different parts of our face, hands etc.
• Two notable absences from AGBT this year were representation from Helicos, the first single-molecule sequencing company, and BGI, the Chinese organization that last year launched a subsidiary called BGI Americas to offer access to its enormous sequencing resource in Hong Kong.

As usual, ABGT concluded with the organizers polling the audience for suggestions on the future size and scope of the conference. There was broad consensus that the size of the meeting was just about right. Suggestions for future topics can be sent to NHGRI’s Eric Green, Washington University’s Elaine Mardis, or any of the other organizers. I’d like to see more talks on genomic medicine and the data management aspects of NGS, but I doubt the organizers will have too much trouble attracting talks on those themes for next year.

In the meantime, you can get your next NGS fix at conferences including CHI’s X-GEN Congress in San Diego (March 14-18), Human Genome Meeting 2011 in Dubai (March 14-17), and Bio-IT World Conference & Expo in Boston (April 12-14).

Eric Glazer, VP Marketing/Online Communities, Cambridge Healthtech Associates : If you are finding us for the first time… welcome. Our vision is for the NGS Leaders community to become the platform to both network with peers and exchange ideas related to progressing genomics and next-generation sequencing. Membership is free for anyone who wants to join the conversation.

 Currently, we are working diligently to ensure that your user experience is a positive one (we recently made the NGS Leaders site public as we complete our final refinements).  Until that time, feel free to register and peruse the site keeping in mind that the site has not launched officially. We hope you take the time to offer input by posting to the discussion forum NGS Leaders Website Feedback or contacting us via twitter (@NGSLeaders). You can also email me directly.

Many industry leaders have been instrumental in providing us with ideas on what features to include on the website and how NGS Leaders can best serve industry professionals. We encourage everyone to continue to provide suggestions. I am not guaranteeing we can integrate every suggestion but I will guarantee that we’ll read your comment, and do our best to incorporate the suggestions that make the most sense for the greater good of the community, taking into account the resources available to us.

The mission of NGS Leaders is to do our part in “forwarding the progress of the next-generation sequencing by facilitating the exchange of ideas”  To accomplish this lofty goal we will continuously strive to develop and manage this online community and social network so it meets the following objectives:

1) Easy to register and participate
2) Integrates (and promotes) content from other relevant websites through link sharing, content syndication and guest moderators
3) Facilitates and promotes discussion among members by identifying the most timely and interesting topics
4) Provide content through discussion forums, blogs, webinars, videos, articles, white papers, etc
5) Continuously communicate and respond to our members

NGS Leaders is hosted by Cambridge Health Associates, a wholly-owned subsidiary of Cambridge Healthtech Institute.

Thank you for taking the time to visit. Please check back frequently as we continue to make improvements to the site.

                 

Kevin Davies, Editor-in-Chief, Bio-IT World : The term next-generation sequencing (NGS) has been around for so long it has become almost meaningless. We use “NGS” to describe platforms that are so well established they are almost institutions, and future (3rd-, 4th-, or whatever) generations promising to do for terrestrial triage what Mr Spock’s Tricorder did for intergalactic health care. But as the costs of consumables keep falling, turning the data-generation aspect of NGS increasingly into a commodity, the all-important problems of data analysis, storage, and medical interpretation loom ever larger. 

 “There is a growing gap between the generation of massively parallel sequencing output and the ability to process and analyze the resulting data,” says Canadian cancer research John McPherson, feeling the pain of NGS neophytes left to negotiate “a bewildering maze of base calling, alignment, assembly, and analysis tools with often incomplete documentation and no idea how to compare and validate their outputs. Bridging this gap is essential, or the coveted $1,000 genome will come with a $20,000 analysis price tag.”

 “The cost of DNA sequencing might not matter in a few years,” says the Broad Institute’s Chad Nusbaum. “People are saying they’ll be able to sequence the human genome for $100 or less. That’s lovely, but it still could cost you $2,500 to store the data, so the cost of storage ultimately becomes the limiting factor, not the cost of sequencing. We can quibble about the dollars and cents, but you can’t argue about the trends at all.

 But these issues look relatively trivial compared to the challenge of mining a personal genome sequence for medically actionable benefit. Stanford’s chair of bioengineering, Russ Altman, points out that not only is the cost of sequencing “essentially free,” but the computational cost of dealing with the data is also trivial. “I mean, we might need a big computer, but big computers exist, they can be amortized, and it’s not a big deal. But the interpretation of the data will be keeping us busy for the next 50 years.” Or as Bruce Korf, the president of the American College of Medical Genetics, puts it: “We are close to having a $1,000 genome sequence, but this may be accompanied by a $1,000,000 interpretation.”

 Arbimagical Goal
 The “$1,000 genome” is, in the view of Infinity Pharmaceuticals’ Keith Robison, an “arbimagical goal”—an arbitrary target that has nevertheless obtained a magical notoriety through repetition. The catchphrase was first coined in 2001, although by whom isn’t entirely clear. The University of Wisconsin’s David Schwartz insists he proposed the term during a National Human Genome Research Institute (NHGRI) retreat in 2001. During a breakout session, he said that NHGRI needed a new technology to complete a human genome sequence in a day. Asked to price that, Schwartz paused: “I thought for a moment and responded, ‘$1,000.’” However, NHGRI officials say they had already coined the term.

 The $1,000 genome caught on a year later, when Craig Venter and Gerry Rubin hosted a major symposium in Boston (see, “Wanted: The $1000 Genome,” Bio•IT World, Nov 2002). Venter invited George Church and five other hopefuls to present new sequencing technologies, none more riveting than U.S. Genomics founder Eugene Chan, who described an ingenious technology to unfurl DNA molecules that would soon sequence a human genome in an hour. (The company abandoned its sequencing program a year later.)

 Another of those hopefuls was 454 Life Sciences, which in 2007 made Jim Watson the first personal genome using NGS, at a cost of about $1 million. Since then, the cost of sequencing has plummeted to less than $10,000 in 2010. Much of that has been fueled by the competition between Illumina and Applied Biosystems (ABI). When Illumina said its HiSeq 2000 could sequence a human genome for $10,000, ABI countered with a $6,000 genome dropping to $3,000 at 99.99% accuracy.

 Earlier this year, Complete Genomics reported its first full human genomes in Science. One of those belonged to George Church, whose genome was sequenced for about $1,500. CEO Cliff Reid told us earlier this year that Complete Genomics now routinely sequenced human genomes at 30x coverage for less than $1,000 in reagent costs.

 The ever-quotable Clive Brown, formerly a central figure at Solexa and now VP development and informatics for Oxford Nanopore, a 3rd-generation sequencing company says: “I like to think of the Gen 2 systems as giant fighting dinosaurs, ‘[gigabases] per run—grr—arggh’ etc., a volcano of data spewing behind them in a Jurassic landscape—Sequanosaurus Rex. Meanwhile, in the undergrowth, the Gen 3 ‘mammals’ are quietly getting on with evolving and adapting to the imminent climate change... smaller, faster, more agile, and more intelligent.”

 Nearly all the 2nd-generation platforms have placed bets on 3rd-gen technologies. Illumina has partnered with Oxford Nanopore; Life Technologies has countered by acquiring Ion Torrent Systems; and Roche is teaming up with IBM. PacBio has talked about a “15-minute” genome by 2014, Halcyon Molecular promises a “$100 genome,” while a Harvard start-up called GnuBio has placed a bet on a mere $30 genome.

 David Dooling of The Genome Center at Washington University, points out the widely debated cost of the Human Genome Project included everything—the instruments, personnel, overhead, consumables, and IT. But the $1,000 genome—or in 2010 numbers, the $10,000 genome—only refers to flow cells and reagents. Clearly, the true cost of a genome sequence is much higher (see, “The Grand Illusion”). In fact, Dooling estimates the true cost of a “$10,000 genome” as closer to $30,000, by the time one has considered instrument depreciation and sample prep, personnel and IT, informatics and validation, management and overheads.

 “If you are just costing reagents, most of the vendors could claim a $1,000 genome right now,” says Brown. “A more interesting question is: ‘$1,000 genome—so what?’ It’s an odd goal because the closer you get to it the less relevant it becomes.”

This article also appeared in the September-October 2010 issue of  Bio-IT World. 

Ernie Bush, VP and Scientific Director, Cambridge Healthtech Associates : The following is an interview that Ernie Bush conducted with Paul Watkins in September 2010.     

Paul Watkins, Professor of Medicine and Pharmacy at the University of North Carolina, Chapel Hill, and director of the Hamner-UNC Institute for Drug Safety Sciences, spoke with me about the Hamner Institute’s efforts to leverage information from the human genome to explore issues around drug induced liver injury.

EB: Could you describe the work you’re doing at the Hamner Institute?

PW: Rare idiosyncratic drug induced liver injury (DILI) is the major drug toxicity that terminates a new molecular entity in clinical development and it’s also the major organ toxicity that leads to regulatory actions on drugs post approval. And there’s really been very little insight to date on what is the mechanism of these adverse events, i.e. why a drug that’s safe for the vast majority of people can cause life threatening liver injury in a rare person, say 1 in 10,000 or 1 in 50,000. And a very exciting endeavor that’s been ongoing now for five years and funded by the NIH is the drug induced liver injury network or DILIN.

I chair the steering committee and I also chair the genetics sub-committee for this initiative. It involves finding people around the country who’ve actually had these rare reactions and recovered, in some cases after a liver transplant. And one of the first areas we’re starting on is the genetics. All of these subjects are going to undergo the million SNP chip analysis for a genome-wide association study (GWAS). About half of the 850 have already had this GWAS and there have been some successes just doing this technique.

To extend this assessment, what we’re now embarking on, and this is in collaboration with David Goldstein’s group at Duke, is whole exome sequencing with cases due to certain drugs where we have a relatively large number of well-characterized subjects... There’s also a parallel effort in Europe...

All these studies in the U.S. and Europe are, of course, generating a huge amount of data. Therefore, the real challenge now is: How do we mine that large data set to get mechanistic insight of why an individual would be susceptible to DILI drug reactions. So here at the Hamner, we’ve begun several research initiatives designed to synergize and capitalize on these other resources.

One is that we’re looking at panels of inbred mice that are genetically very well characterized but one strain is significantly different from the other. We use these strains as a model for genetic variation that exists in people. We were fortunate enough to get an NIH grant—that’s myself and David Threadgill who’s the chair of genetics at NC State University—to start giving drugs to these mice to see if we could find one particular strain or a couple of strains that would manifest the toxicity, just as it occurs in people. Because the genetics is very well worked out and established in these mice, we can immediately see candidate genes that account for the susceptibility in mice and then compare that to the human genetic data in the DILIN and SAE consortium gene banks to test these hypotheses.

The other approach is to study the effects of these drugs, the ones implicated as causing liver injury, in primary cultures of human hepatocytes with additional cells that are present in the liver; particularly Kupffer cells to see if we can define the pathways that these drugs perturb as you go from physiologic concentrations to toxic concentrations. These studies may generate a list of suspect genes that we can then go over to the human genetic data and actually look very closely at these genes to see if there’s any variation that might cause a susceptibility to DILI.

Likewise as David Goldstein’s group comes up with certain genetic variations that they say statistically are different between the cases and controls, we can go to our hepatocytes and look to see if that makes sense mechanistically.

And then lastly, we’re putting all this information together in an in silco model called DILI-SIM. This work is a collaboration between the Food and Drug Administration and a Bay area company called Entelos where we’ve already begun modeling the major pathways taken by drugs and the major perturbations that drugs cause that can lead to liver toxicity.

EB: At the World Pharmaceutical Congress, you presented preliminary data that suggest not so much a metabolic difference in these individuals, but an immune system difference, is that correct?

PW: That’s right. One of the surprises in the GWAS analysis, both done in the DILIN and the SAE consortium, was that for some drugs the major susceptibility factor that we could identify was within what’s called the HLA region of the genome. So this is involved in the immune response—what’s called the acquired immune response, suggesting that these severe events may in some cases be due to the body’s immune system attacking the liver.

In addition to that, we found suggestions for other types of genes including drug metabolism and transporter genes. But, the associations so far have been weak and we’ve actively working to improve and expand these findings.

This article also appeared in the September-October 2010 issue of Bio-IT World.  

Patients participate in blogs, online advocacy groups, or third party communities like PatientsLikeMe. They are able to collaborate, share solutions and therapy options, physician referrals, and rehabilitation approaches. Physicians collaborate through “doctor only” communities like Medscape Connect and Sermo. They advise each other on treatment options and share new insights on medications and devices. The benefits are just as rich for R&D. Online peer-to-peer consulting and collaboration can streamline processes, improve efficiencies and reduce the overall costs in drug development.

In our view, the dynamic field of next-generation sequencing (NGS) can benefit from a community dedicated to sharing ideas and strategies, a virtual meeting place where academics and industry professionals, bench scientists and bioinformaticians can discuss key trends and brainstorm solutions. Cambridge Healthtech Associates (CHA, a sister organization to Bio•IT World) is incorporating these ideas as we plan the October launch of our latest online community, NGS Leaders (www.nglsleaders.org; twitter.com/ngsleaders), a free online membership for pioneers in next-generation sequencing.

In 2009, we created a similar online community, the Drug Safety Executive Council, (DSEC) dedicated to the vital topics of drug safety. DSEC currently boasts some 2,000 members who meet regularly online to gather and share pre-competitive information. The community spawned a working consortium that cooperatively validates novel, predictive nonclinical assays, reducing the cost and time associated with the evaluation of predictive safety technologies

The challenge is developing and maintaining a self-sustaining, member-driven community culture. This is especially difficult in the heavily-regulated, conservative culture of life sciences where leaders are less apt to express opinions. However there are some best practices for making a life sciences community successful.

• Key Opinion Leaders (KOLs) and Evangelists
  NGS Leaders will feature an advisory board of key opinion leaders and evangelists representing government, academic/research centers, biopharmaceutical companies and leading technology and software providers The board will influence community policies, programming, and content, and board members will contribute content including online discussions, guest blog posts, webinars, and face-to-face events.
   
• Programming and Member Participation
  NGS Leaders will feature live events that tackle subject matter that is highly relevant to members. Some members will be invited to sit on panels during the webinars and others may also be asked to be “question askers” in the audience. In a recent industry survey conducted by CHA, 74% of respondent said discussion forums are a “must have” for a closed, industry-specific community. Thus we are asking KOLs and other subject matter experts that make up the membership to lead online discussions leading to member-driven online discussions. “Assigning” member involvement is a critical task during the first 12-18 months of a community’s life. The ancillary benefit to your hard work is it allows you to nurture relationships with your most important peers and colleagues.
   
• Product Reviews
  Ill-advised investments in new technologies contribute to the rising cost of R&D. During our last industry survey, more than 90% of respondents agreed that an online product review or evaluation forum would be valuable. An easy-to-navigate product review feature harnesses the power of the community and translates into smarter investment decisions by R&D organizations. NGS Leaders will enable members to rate and comment on various technologies like sequencers, informatics software, hardware, and more. The site will also allow members to search products by type or rating.
   
• Inclusivity and Promoting Other
  We believe it is important to promote good content no matter if it’s our own or someone else’s. The mission of NGS Leaders is to further fuel the progress of next-generation sequencing so it may positively impact patients sooner. To that end we will promote other sources—like SeqAnswers and Genomes Unzipped—that are important to fulfilling our mission.
   

Communities like DSEC and NGS Leaders provide an environment to build trust and exchange ideas around the industry’s shared challenges. James Surowiecki proclaims in The Wisdom of Crowds, that “groups are remarkably smart, smarter even sometimes than the smartest people in them.” In many ways online communities tap into this dynamic.

This article also appeared in the September-October 2010 issue of Bio-IT World.