President Obama by Glenn “‘President Obama has a deep-seated hatred of white people’ and 75 seconds later ‘I’m not saying President Obama doesn’t like white people’” Beck and me by neoprene nancy (not to be confused with Polythene Pam) in a comment on my recent post Another rich white guy sequences own genome about Stephen Quake sequencing his own genome. The entirety of her comment is “Another blogging guy inadvertently reveals racism.” I truly find it a strange and discomforting thing that people so quickly and easily throw out accusations of racism. It is almost as though racists are adopting the approach taken by hip hop artists with the N-word: adopt the word’s use to the point of overuse to diminish its derogatory connotation. Hopefully neoprene nancy was joking. In case she was not, let’s take the accusation apart. Since she does not call me socialist or sexist and herself uses the term “guy”, I assume she is only concerned with my reference to “white” and not “rich” or “guy”. Perhaps, like Glenn Beck would have us believe about President Obama, I am a self loather and have a deep-seated hatred of white people (for those of you wondering, you can see a picture of me). Or perhaps my dissatisfaction with the selection of another healthy, white male for whole genome sequencing has to do with the fact that it will provide essentially no scientific value. This is likely why the sequence analysis was so cursory and why it got published as a letter in Nature Biotechnology rather than an article in a top-tier journal: it is essentially just a proof of concept for the Helicos platform. While knowing his sequence has provided some health insights for Stephen Quake (see Quake Traits), it does not advance our understanding of the relationship between genotype (DNA) and phenotype (traits). It does not add to our understanding of natural human variation beyond that provided by the 1000 Genomes Project. It does not help us to understand variants associated with cancer or other common diseases. It does not help us to interpret the biological role of conserved sequences in the genome that are not in genes. In short, it is a novelty and should be called out for what it is, another rich, white guy sequencing his own genome.

Following in the dubious footsteps of J. Craig Venter, Stephen Quake has sequenced his own genome using a technology he helped develop which was commercialized by a company he helped to found (lots of conflicts of interest there). The letter, Single-molecule sequencing of an individual human genome, was published in Nature Biotechnology and details the sequencing of Quake’s genome on the Helicos Genetic Analysis System (formerly Heliscope). There is a more accessible description of the letter in a friendly article over at Bio-IT World (although it does have some great quotes from the most honest guy in all of next-gen sequencing, Clive Brown).

The bottom line is that three researchers sequenced a human genome in four Helicos runs. They report that each run took one week but do not report the total amount of time the sequencing took (i.e., did they complete the project in a month or did sample preparation, instrument performance, etc. cause it to take much longer?). They report reagent costs that are on par with current second generation technology fully loaded costs (which are closer to $50,000, not the $250,000-$500,000 they report in their letter). Yes, you read that right, their reagent costs alone are on par with reagents, instrument depreciation, personnel, and IT infrastructure for second generation platforms. Quake does report in an interview that the amortized equipment cost was $10,000-$20,000. Assuming a straight line depreciation for the Helicos instrument, a $10,000-$20,000 depreciation over four one-week runs yields a $125,000-$250,000 annual depreciation. Their first instrument was sold for $963,000 and they subsequently lowered the price by 25%. So assuming their price now is $725,000 and the residual value of the instrument is $0 (not a bad assumption given the pace of change in this industry), they are estimating a life of their instrument of about three to six years. Again due to the pace of change of this industry, even three years may be generous.

As for sequence analysis, their ability to call SNPs is comparable to second generation platforms. Their ability to call copy number variations (CNVs) is perhaps better than second-generation sequencing platforms; likely due to the single-molecule nature of the Helicos system not requiring an amplification step that introduces bias. They did not even address indel detection. This is likely due to the fact that most of the Helicos sequencing errors are due to the incorporation of dark bases, leading to many false positive deletion events. It is also hard to detect indels with such short reads (average length of aligned reads was 32 bases). However the most notable thing about their analysis was how shallow it was. I suppose they thought it was more important to have only three people on the paper (they make a big deal about this, referring to it several times in the letter as the “democratization of sequencing”) than to do thorough analysis. What you can take away from this is that you may be able to sequence a human genome with three people, but it takes a village of bioinformaticians to do the sequence data justice.

Daniel MacArthur over at Genetic Future has a nice assessment of the publication and summarizes nicely.

This paper sets the bar pretty low for other third-generation sequencing contenders: it appears that formal entry into the human genome sequencing race merely requires generating a genome sequence of the standard that second-generation sequencers were achieving in early 2008, at the same price that they’re charging right now. That’s a fairly uninspiring goal.

Nonetheless, Helicos stock (NASDAQ:HLCS) has risen from $0.60 close at the end of last week to about $1.20 now, a 100% jump. I suppose it is not surprising that we have yet to learn from our past mistakes.

Perhaps an example is in order to make these abstractions more concrete. Currently, expression arrays are used to measure relative levels of gene expression in tissues. More specifically, often the expression (transcription) of genes in two different tissues, e.g., liver and pancreas or tumor and normal, are measured to determine which genes are being expressed at different levels in each of the tissues. These expression arrays contain tags of DNA complimentary to specific genes, or more specifically exons in genes. The mRNA in the tissue is collected, converted into cDNA, and the cDNA is hybridized onto the array. The degree of hybridization of each probe is measured and you obtain relative expression levels of of each exon (gene) represented on the array. In the case of tumor versus normal tissue, what you do not get is any indication as to what mutation might have caused the expression to increase or decrease in one tissue compared to the other. To get that information, you would have to selectively sequence that portion of the genome, usually a few hundred to a few thousand bases per probe. The cost of this more complete approach can be high because low resolution probes and/or lots of discrepant expression necessitate a large amount of sequencing; and this sequencing is still primarily done with more expensive, capillary-based methods. What UHTS provides is a way to short cut this approach. You can directly sequence the cDNA, thereby obtaining both the sequence and the relative expression levels. The latter is obtained by aligning each sequence, or “read”, generated against all genes. The genes that have more reads aligned to them are expressed more than those that have fewer reads aligned to them.

So as the example indicates and as I said above, experiments that have traditionally been carried out on array platforms can now be done on UHTS platforms. However, both of these platforms have grown up in different cultures with different standards and rules. This meeting was sponsored by the array folks (MGED) and the sequencing folks (Genomics Standards Consortium) to get these two groups together to either merge their current standards or come up with new standards that both groups agree on.

When the meeting started, the different cultures were apparent. The array folks have largely focused on metadata standards, i.e., data about the sample and the experiment, whereas the sequencing folks have not worried much about metadata. This difference is expected because the number and type of array experiments is large whereas sequencing has heretofore been focused on relatively fewer, larger, long-term projects. More recent sequencing efforts like The Cancer Genome Atlas have necessarily had to deal with more metadata, e.g., patient sample information, and the sequencing community has largely relied on ad-hoc standards that have differed from project to project. So this meeting was timely for both the array folks and the sequencing folks. The array folks would like to have similar standards they have enjoyed for the microarray data, e.g., MAGE-TAB and MIAME, as they transition to UHTS. And the sequencing folks would like some standards to develop around metadata exchange as the number of projects they participate in and the amount of metadata they report on increase.

Other aspects of UHTS experiments were also discussed: the different types of experiments being done on UHTS, the short-read format, vendor-specific data formats (Applied Biosystems, Illumina, and Helicos were represented), the short-read archives of NCBI and EBI, and the need for standards in general. But these topics were largely informational and the group more or less organically decided to focus on the metadata standards, of which several flavors were presented. I won’t get into the details, but suffice to say there are people who like XML (computer scientists) and people who like tab-delimited (biologists) and people who will end up having to support both (me). The meeting was a positive first step but, as with all meetings of this sort, it will not be known for some time if it was a success or not. Time and effort will determine if a standard will be developed and adopted by everyone involved.