Crossposted from microBEnet
Every year for the last few years I have given a talk on the “Evolution of DNA Sequencing” at the “Workshop in Applied Phylogenetics” at Bodega Bay Marine Lab. I just did the talk and thought I would post the slides here. I note – I also added an evolutionary tree of sequencing methods which I include here as a separate animated gif too.
I note I posted a request to Twitter the day before the talk pointing to last years slides and I got lots of helpful suggestions from people about what to add or change. I included links to Tweets in the talk and thanked those people on the slides. But I would like to thank everyone here too. Published originally on March 10, 2015. Updated 10/20/15 with information below and republished. Finally posted the video of the talk (recorded using Camtasia) to Youtube. It is imperfect (there are a few things I said that came out wrong .. it was late at night). But since it may be helpful to people I am posting it.
For the last year or so I have become a big fan of Illumina sequencing. We are using it for everything in the lab. And many others are using it quite a lot too. All sorts of interesting applications. But of course -there are other sequencing systems that each have some advantages relative to Illumina. And one of the key limitations of Illumina sequencing has been the read length (though that limitation gets less and less as read lengths get longer and longer from Illumina machines).
The UC Davis Genome Center has had Illumina sequencing systems for many years now and we use them extensively. However, we felt for some time that we and others around town could benefit from complementary methods, especially those that could get longer reads. So we sought funding to buy other systems. And fortunately we got an NSF MRI grant to do just that -which we used to buy a Roche 454 Jr machine and contribute to the purchase of a Pacific Biosciences machine. These are good to have around because they open up new windows into sequencing – not just long reads but other areas as well. For example, the PacBio system also has the ability to use it to detect modifications to bases like methylation.
Alas, both the 454 and PacBio systems have higher error rates than the Illumina systems. And this makes some analyses challenging and limits the benefits that come from the longer reads. So what to do? For a while people have been using Illumina sequencing to “correct” the errors make by 454 and PacBio sequencing. And today Matt Herper at Forbes (For A New DNA Sequencer, A Technical Fix May Have Come Too Late – Forbes) discusses a new further improvement in the ability to do this error correction (a paper just came out on the topic from Adam Phillippy, Sergey Koren, Michael Schatz, and others).
I find this whole concept a bit funny / interesting. Not only does Illumina sequencing have many uses but one of its uses in essence helps keep aloft the potential of some of it’s competitors. In this way – Illumina can be considered the duct tape of sequencing systems. 1001 uses. Not sure the Illumina folks will be overly thrilled with this use but that is the way it goes …
(As an aside – any high throughput highly accurate sequencing method could be used in the same way as Illumina in most cases – ABI solid for example. But alas for ABI Illumina has kind of taken over this part of the market).
(An another aside – we will have to wait and see how/if the Ion Torrent systems take off in the sequencing ecosystem)
(As another aside – still waiting to see some more detail from the Oxford Nanopores folks … I would be happy to be a beta tester if anyone from Oxford is reading this).
Quick post — nice review worth checking out: The ISME Journal – Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms
from Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, Knight R.
A key part of the paper, with highlighting from me:-
These observations, in agreement with studies that have addressed this question directly (Kuczynski et al., 2010), suggest that increasing the sequencing depth is not likely to provide additional insight into questions of beta diversity, and we therefore argue that (for questions of beta diversity in particular) the decreased cost of sequencing should be applied to study microbial systems using many more samples, for example, in dense temporal or spatial analyses, rather than with many more sequences per sample. Of course, if the objective is to identify taxa that are very rare in communities, deeper sequencing will be advantageous. Additionally we note that while as few as 10 sequences per sample may be useful for differentiating very different environment types (for example, soil and feces), as environments become more similar (for example, two soil samples of different pH) more sequences will be required to differentiate them.