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Graphs Show Costs of DNA Sequencing Falling Fast
kkleiner writes "You may know that the cost to sequence a human genome is dropping, but you probably have no idea how fast that price is coming down. The National Human Genome Research Institute, part of the US National Institute of Health, has compiled extensive data on the costs of sequencing DNA over the past decade and used that information to create two truly jaw-dropping graphs. NHGRI's research shows that not only are sequencing costs plummeting, they are outstripping the exponential curves of Moore's Law. By a big margin."
Sequencing has been where the focus on cost has been going. It doesn't make much sense to try and reduce the cost of analysis when it takes a very long time and a huge amount of money to accomplish. The graph was hard to read, but at this point with the cost well over $10k there's a lot more that has to be done before analysis is worth spending a lot of time economizing.
But as it gets cheaper more and more of the focus will be on the analysis side. And the cost of analysis will come down, given that insurance isn't going to cover the sequencing at this point, analysis is moot in most cases. As more research analyzes sequenced DNA I'm sure tricks and such will be discovered to bring the cost down. But right now you're dealing with low volumes and as such cost is higher than it will be with higher volumes.
We've been observing this decrease over the last few years at our sequencing lab too. Some people might find it fascinating, but I, as a bioinformatician, find it frightening.
We're still keeping up at maintaining and analysing our sequenced reads and genomes at work, but the amount of incoming sequencing data (currently a few terabytes of data per month) is increasing four-to-five-fold per year (compared to doubling each 18-24 months in Moore's law). Our lab had the first human genomes at the end of 2009 after waiting for almost 9 years since the world's first human genome, now we're getting a few genomes per month. We're not too far away of running out of installing sufficient processing power (following Moore's law) and no longer being able to process all of this data.
So yes, the more-than-exponential decrease in sequencing costs is cool and offers a lot of possibilities in getting to know your own genome, advances in personalized medicine, and possibilities for population-wide genome sequencing research, but there's no way we'll be able to process all of this interesting data because Moore's law is simply way too slow as compared to advances in biochemical technologies.
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Actually, they're not sequencing.
They're checking.
The way 23andme and most personal genome companies work is that they have those genochips (Illumina) with one million DNA sequences on them, and they check whether or not your DN has one of those sequences.
If you have a SNP not on the chip (well, you have lots of SNP not on the chip), it won't list anything. If, at a given chromosome locale, they have "all" of the "known" SNP, but you happen to have a mutant variant not on their lib, then you're not detected.
"Sequencing" involves taking your DNA, and getting every sequence, no matter what. And that's still long and very expensive. We're in the era of the "thousand genomes", meaning we expect in a couple year to complete a thousand full sequences. Of course, 10 years later, we'll sequence everyone, but, so far, it's still a way out.
'Also, my understanding is that most uses don't require sequencing the entire genome, but rather just a small subset of it.'
Very small subsets (e.g. individual genes) are still done the 'traditional' way (1990s technology!). Intermediate subsets (like the 'exome') are now done using a pre-selection 'capture' process ('target enrichment') followed by analysis on the same 'next generation' instruments that are used for whole genomes. Right now, this makes sense economically, since it requires less capacity (fewer consumables and less run time) on the expensive sequencers. But as sequencing prices continue to drop, we'll probably reach a point where it's cheaper to do the whole genome than any significant subset (since the 'capture' process is also fairly expensive). Cheaper to do the wet lab stuff, anyway - whole genomes also require much more processing power than useful subsets like exomes.
'Of course, that may just be the plateau before it falls off the next cliff.'
The next cliff is already emerging through the mist, e.g.:
http://www.genomeweb.com/sequencing/life-tech-outlines-single-molecule-sequencing-long-pieces-dna
http://www.wired.com/wiredscience/2011/01/guest-post-introduction-to-nanopore-sequencing/
It's not clear which 'single-molecule' technology will eventually win out, but it will almost certainly have the word 'nano' in it somewhere.