Ryan Wick Profile picture
22 Feb, 11 tweets, 4 min read
Excited to announce a new preprint! We did a study comparing two different @nanopore library prep approaches (ligation and rapid) for bacterial genomes with small plasmids:
biorxiv.org/content/10.110…
(1/11)
I really like this paper because it has a clear conclusion simple enough to fit in a tweet: rapid preps are better than ligation preps at recovering small plasmids.
(2/11)
Figure 1 gives a simplified illustration of why we think this is the case: due to their size, small circular plasmids can avoid fragmentation during DNA extraction, leaving no ends for adapter ligation. Rapid preps, in contrast, don't depend on DNA ends.
(3/11) Image
Figure 2 shows our main results: using Illumina reads to approximate true plasmid abundance, the smaller a plasmid is, the more underrepresented it will likely be in a ligation read set. But not in a rapid read set!
(4/11) Image
I like the plots in Figure 2 because the effect is obvious - I didn't even think it was necessary to do statistics (xkcd.com/2400). But I reluctantly did do linear regressions 😄
(5/11)
We also found another interesting difference between ligation and rapid: there were fewer chimeric reads in the rapid sets. This makes sense because rapid preps don't involve ligase, so there is less chance of combining two DNA fragments together.
(6/11)
So the advantages to using ligation preps are: better yield, more versatility and greater multiplexing of samples. For these reasons, it's what the @DrKatHolt lab mostly uses for Nanopore sequencing of bacterial isolates.
(7/11)
The advantages to using rapid preps are: simpler/faster procedure, potential for longer reads (if you're careful with DNA extraction), better representation of small plasmids and fewer chimeras.
(8/11)
The main takeaway of the paper is this: if you're doing Nanopore-only sequencing of a bacterial isolate and small plasmids matter to you, we recommend rapid preps! If you use a ligation prep, you might miss the small plasmids.
(9/11)
If you're doing hybrid (Nanopore+Illumina) sequencing, then ligation should be fine because the small plasmids will be captured by the Illumina reads. But expect the small plasmids to be underrepresented in your Nanopore reads.
(10/11)
Many thanks to the co-authors (@JuddLmj, @KelWyres and @DrKatHolt) and all the other members of the Holt Lab. And more generally, thanks to all the researchers out there who help make @nanopore bacterial genomics so good!
(11/11)

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More from @rrwick

22 Sep 20
We've once again updated our paper benchmarking long-read assemblers for bacterial genomes! Take a look at the fresh results here:
f1000research.com/articles/8-2138

Updates since the last version include...
(1/9)
New versions of some assemblers: Canu v2.0, Flye v2.8, Raven v1.1.10 and Shasta v0.5.1. My favourite change here is that Flye no longer requires a genome size parameter.
(2/9)
I've also added a new assembler to the comparison: NextPolish/NextDenovo. It performed well on chromosomes but not on plasmids, and it was more cumbersome to run than the other tools.
(3/9)
Read 9 tweets
28 Jul 20
I'm releasing a new tool today: Trycycler!
github.com/rrwick/Trycycl…

It is for generating a consensus long-read assembly of a bacterial genome.

(1/9) Image
I.e. you give Trycycler multiple different long-read assemblies of the same genome, and it produces a single consensus assembly that is better than any of the inputs.

(2/9)
In doing so, Trycycler can repair most of the problems that hide in long-read assemblies. These include:
1) missing/spurious contigs
2) bad circularisation
3) glitchy sequence regions

(3/9)
Read 9 tweets
23 Apr 20
The first update to my long-read assembler benchmarking paper is up on F1000Research:
f1000research.com/articles/8-2138

Updates include...
(1/8)
The results now include fresh versions of some the assemblers: Flye (v2.6 -> v2.7), Raven (v0.0.5 -> v0.0.8) and Shasta (v0.3.0 -> v0.4.0)
(2/8)
I've also added a new assembler to the comparison: NECAT
github.com/xiaochuanle/NE…
(3/8)
Read 8 tweets
2 Jan 20
New paper for the new year! It compares different long-read assemblers for microbial genome assembly:
f1000research.com/articles/8-213…

Two Twitter threads follow - one about the paper itself and one about my experience with @F1000Research.
(1/n)
In this paper, we did a ton of long-read microbial genome assemblies (using both real and simulated long-read sets) to see how the current assemblers perform.
(2/5)
I won't get into detailed results here, but very briefly: Flye, Raven and Miniasm/Minipolish were our favourites, each excelling in particular ways 🏆
(3/5)
Read 10 tweets
3 Dec 19
I've got a little new tool to share: Minipolish
github.com/rrwick/Minipol…

It does Racon-polishing on a miniasm long-read assembly. Why not just use Racon directly? For a few reasons...

(1/6) Image
1. Minipolish keeps the assembly in graph form (GFA format) whereas Racon produces FASTA sequences.

2. Racon has a nasty habit of sometimes truncating sequences a little bit when it polishes them - Minipolish will repair this.

(2/6)
3. Minipolish 'rotates' circular contigs (like in bacterial genomes) between polishing rounds. This ensures that final polished contigs circularise cleanly (no missing or overlapping bases).

(3/6)
Read 6 tweets
13 Aug 19
I have a little tool to share, in case it's useful to anybody else:
github.com/rrwick/Assembl…

Nothing too fancy, but if you work with large numbers of bacterial genomes, read on... (1/9)
I occasionally encounter a situation where I have lots of genome assemblies, but some are quite redundant. Often because the set contains outbreaks of near-identical genomes. (2/9)
For example, if you download all Klebsiella pneumoniae genomes, you'll get many thousands, but common disease-causing lineages (like CG258) are heavily represented. (3/9)
Read 9 tweets

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