Nanopore's have their own Day 1 and Day 2 writeups and an independent write-up from Arwyn Edwards.
Platform
Per the usual pattern, Oxford showed off previously announced hardware but made no solid announcements. I've put together a Storify of relevant tweets which may hold further information.
Flongle/SmidgION
SmidgION pumping out data with an attached Android phone calling the bases was a heavily tweeted and retweeted photo. Alas, Oxford apparently put release of the SmidgION/Flongle components into the second half of next year, so no SmidgIONs adorning Christmas trees this year while happy recipients sing Flongle Bells ("Oh what fun, it is to sequence, in a one horse open sleigh, hey!").
Anxiously waiting for these little bad boys to develop! SmidgION for sequencing w cell phone connection & Flongle, reduced version of a flow cell #nanoporeconf pic.twitter.com/2xsQOKPVle— Aaron Pomerantz (@AaronPomerantz) November 30, 2017
Seriously, as suggested by the previous post I think these smaller flowcells are going to be hugely popular and influential. For training and educational purposes, small is better. The targeted application of field operations will be huge.
But I think in the end the biggest use will be for many applications in which there are large numbers of samples from which small amounts of data will answer the scientific question and where multiplexing isn't a good solution.
To give one example, there is one of the burning questions of DNA sample prep: what contaminants damage flow cell performance? Obviously that isn't a question suitable for multiplexing!
But there will be many others, particularly for counting applications. Especially if "no library" approaches are developed along the lines suggested previously by ONT for their Cas9-based schemes. If creating a sequencer-ready sample consists of just pipeting a small amount of inexpensive reagent, then a lot of new applications will open up.
GridION
No real news specifically about GridION X5, other than that many people have tweeted out pictures of their new GridION instruments and there have been very few reports of problems (I know of at least one example of one being dead-on-arrival, but that seems to be rare).
But the big news tied to GridION is the launch of the first two contract research nanopore sequencing services, with the Garvan Institute in Australia and BaseClear / Future Genomics Technologies in the Netherlands. Since Oxford won't license MinION users for service sequencing, only the availability of GridION made this possible. Presumably nailing down a U.S.-based operation is a priority for ONT; I've shipped samples overseas for sequencing but it is never a calm process plus it creates additional scheduling headaches (never, never let your samples sit around at a shipping firm over the weekend!).
PromethION
I wrote a very critical piece on PromethION last year. The instrument isn't out of the woods yet, but
Twitter traffic does suggest that Oxford is sending out small quantities of good flowcells. Clive Brown tweeted that his yield from a PromethION flowcell is pushing what would be needed for 30X coverage of a human genome; of course Clive's yields are historically about 2X the best field yields and 3-4X better than what most users achieve. So perhaps PromethION will be a real star of data production for London Calling 2018 presentations, but I certainly don't see that as a sure thing.
Basecaller Widget
ONT started showing off their prototype of the FPGA-powered stand-alone basecalling widget, also announcing a contest to name the device.
Yet to be named basecaller dongle #fpga magic plug-in hardware. SmidgION for scale #nanoporeconf pic.twitter.com/PZgDpiEqX6— Martin A. Smith (@martinalexsmith) November 30, 2017
VolTRAX
VolTRAX is still in the "VIP" beta test phase, which I am not part of. I believe the only available kit is still the rapid 1D DNA kit, which hasn't attracted a fan base as the conventional protocol is so simple. ONT promised version 2 flowcells which will have capabilities such as thermocycling.
Software
On the software side, Oxford touted their improved Scrappie basecaller and a new Tombo package for modified base analysis. You can find tweets on this and others related to base modification in a Storify.
I really can't do justice to Ryan Wick's talk -- if you want to get the latest on basecalling performance, check out the publication-ready README file from Ryan Wick which compares just about every known basecaller -- including the not-yet-public Guppie GPU caller -- on a variety of metrics. Here's one example, showing raw basecalling accuracy.
With both the RNA and DNA, even this set of highly experienced labs obtained greatly varying yields.
Still, getting hundreds of thousands of RNA reads is nothing to sneeze at (particularly since that would spread RNase around the lab!).
More importantly, a large number of the direct RNA reads -- and far more than the cDNA reads -- appear to represent full length transcripts. Furthermore, the poly-A tail lengths can be accurately estimated with the direct RNA, even when they are hundreds of As long.
Basecalling accuracy is in the same neighborhood as DNA, with RNA performing slightly better.
There's a lot more in that README file -- identifying base modifications in RNA, capturing multiple splice forms, etc. I'll try to dig more into that soon.
A number of users also presented exciting RNA results, particularly for direct sequencing of RNA viral pathogens such as flu and rabies. I've put all the RNA-related tweets into a single Storify.
At least one talk debuted single-cell RNA sequencing on nanopore. Another talk referenced Deb Peattie's pioneering work on chemical sequencing of RNA back in the 1970s.
MinIONs continue to go to previously unimaginable locations -- perhaps the strangest one presented here was deep in a mine. Nick Loman reviewed again his group (particularly featuring Josh Quick) sequencing Ebola and Zika in the field. More tweets and talks in the a Storify focused on field uses.
Rachel Rubinstein of Ginkgo Bioworks described how a fast nanopore run saved hundreds of thousands of dollars by identifying the contaminating organism in a bioreactor.
There were multiple talks on antibiotic resistance and pathogen detection (disclosure: my day job is looking for new antibiotics and I am doing light consulting for a company in the sequencing-by0-diagnostics space). I've collected tweets on those topics in a Storify -- except a few I missed in preparing that from Claire Jenkins on getting pathogen sequence databases filled out.
Other worthy talks I'm going to reduce to tiny summaries: Steven Salzberg on assembling wheat,
Svetlana Madjunkova on pre-implantation genetic screening, Chia-Lin Wei on structural variants. And so many more. Watch my Twitter for announcements of a few more Storify pages from the 600 or so tweets which haven't been incorporated in the ones mentioned above.
I really can't do justice to Ryan Wick's talk -- if you want to get the latest on basecalling performance, check out the publication-ready README file from Ryan Wick which compares just about every known basecaller -- including the not-yet-public Guppie GPU caller -- on a variety of metrics. Here's one example, showing raw basecalling accuracy.
Cold Chain
ONT has been making progress in reducing the cold chain requirements for select kits. Flowcells are now being shipped wrapped in wool and they are beta-testing lyophilized versions of library prep reagents. That would of course be huge for field use, but not inconsequential would be reducing the shipping costs for all users. If you're going to be a low cost platform for hobbyists and educators, those shipping charges add up.NanoBind
Not ONT, but a company called Circulomics announced plans for a sample preparation technology called NanoBind. These are described asa thermoplastic disk that contains a high density of micro- and nanostructured silica. This unique structure enables vast amounts of DNA to bind and release without being damaged. Processing occurs through a rapid bind, wash, and elute process that parallels magnetic beads and is easily automated.Prep time is promised at 45 minutes and claimed to deliver up to milligrams of high quality, high purity HMW DNA from 1.5mL of input material
RNA
Probably the biggest splash of the meeting was the release of a large consortium RNA dataset for human cell line NA12878, with both 13 million direct RNA reads (from 30 flowcells) and 24 million cDNA reads (from 12 flowcells), all released on github.With both the RNA and DNA, even this set of highly experienced labs obtained greatly varying yields.
Still, getting hundreds of thousands of RNA reads is nothing to sneeze at (particularly since that would spread RNase around the lab!).
More importantly, a large number of the direct RNA reads -- and far more than the cDNA reads -- appear to represent full length transcripts. Furthermore, the poly-A tail lengths can be accurately estimated with the direct RNA, even when they are hundreds of As long.
Basecalling accuracy is in the same neighborhood as DNA, with RNA performing slightly better.
There's a lot more in that README file -- identifying base modifications in RNA, capturing multiple splice forms, etc. I'll try to dig more into that soon.
A number of users also presented exciting RNA results, particularly for direct sequencing of RNA viral pathogens such as flu and rabies. I've put all the RNA-related tweets into a single Storify.
At least one talk debuted single-cell RNA sequencing on nanopore. Another talk referenced Deb Peattie's pioneering work on chemical sequencing of RNA back in the 1970s.
Other User News
MinIONs continue to go to previously unimaginable locations -- perhaps the strangest one presented here was deep in a mine. Nick Loman reviewed again his group (particularly featuring Josh Quick) sequencing Ebola and Zika in the field. More tweets and talks in the a Storify focused on field uses.Rachel Rubinstein of Ginkgo Bioworks described how a fast nanopore run saved hundreds of thousands of dollars by identifying the contaminating organism in a bioreactor.
There were multiple talks on antibiotic resistance and pathogen detection (disclosure: my day job is looking for new antibiotics and I am doing light consulting for a company in the sequencing-by0-diagnostics space). I've collected tweets on those topics in a Storify -- except a few I missed in preparing that from Claire Jenkins on getting pathogen sequence databases filled out.
Other worthy talks I'm going to reduce to tiny summaries: Steven Salzberg on assembling wheat,
Svetlana Madjunkova on pre-implantation genetic screening, Chia-Lin Wei on structural variants. And so many more. Watch my Twitter for announcements of a few more Storify pages from the 600 or so tweets which haven't been incorporated in the ones mentioned above.
