Friday, 8 September 2017

Some highlights of Genome 10k and Genome Science 2017

Everyone comes away with different highlights from a conference, as we each see it from the perspective of our own research, but here were some of the highlights for me of Genome 10k and Genome Science 2017. The conference had multiple tracks so there were many talks I missed. The conference was also live tweeted by many under hashtag #g10kgs2017.
  1. New technology: Nanopore sequencing was mentioned by many speakers, but often from people who were just about to use it for the next step in their research. Long reads were mentioned frequently, and PacBio was still a contender for long read sequencing in talks and posters. Optalysys was advertising a hardware approach to sequence alignment, using light detected after passing through two images representing the sequences ("comparison as fast as the speed of light", except for the time it takes to refresh the images). 
  2. Assembly of long reads and assembly analysis: Those who were using long reads were often using this to produce a whole genome, and were therefore attempting assembly, though many fragments remain even with long reads. Canu was mentioned regularly during the talks, as was FALCON, and miniasm during informal chat. John Davey's talk describing detective work to understand the genome of red algae extremophile Galdieria sulphuraria stood out. After assembly he counted chromosomes by looking for telomeres and the end-of-chromosome read alignment, and still found puzzling questions: Could this 14Mbp organism have 72 chromosomes? Do some of them share regions? 
  3. Haplotyping: Sam Nicholls gave an excellent talk about the Metahaplome and resolving haplotypes in a metagenome. PacBio users now have FALCON-Unzip to phase diploid genomes assembled with FALCON.
  4. Comparative genomics, genome alignments and lineage tracing: After the genomes are assembled, the eukaryote researchers are busy comparing their species with other species (often using Cactus). This seemed to be a common topic. Comparing genomes across species is compute-intensive/expensive. Within-species comparison/alignment was discussed by Bernardo Clavijo, who had many wheat genomes to merge and used skip-mers for the alignment seeds. Graph genomes were mentioned briefly but are not yet used. Alternative RNA splicing was a topic of interest for several speakers.
  5. GC content and GC biases: seem to be responsible for everything, including undersampling for short read sequencing, missing genes in the fat sand rat, photosynthetic efficiency and the efficacy of natural selection. Steve Kelly's talk was fascinating. Plants need different amounts of nitrogen for photosynthesis and this corresponded to the GC content and codon usage of their genomes. So photosynthetic efficiency can be predicted by GC content. He went on to describe how increasing atmospheric CO2 will lead to increased mutation and speciation rate in plants.
  6. Animals with superpowers: Researchers studying animals have all the best stories. There were bats that live forever and don't get cancer (well at least 43 years), mice that can have their fur or limbs removed and have no problem regenerating them, Tasmanian devils transmit cancer by biting and passenger pigeons were once the most abundant bird in the US, migrating in flocks so dense that the sky was darkened, but are now extinct.
  7. Sketches by Alex Cagan: He drew each of the talks in the main room at lightning speed, uploading the sketched to Twitter immediately after each talk. The main room concentrated on the eukaryote genomes, so if you're interested in his summaries, see them all at https://twitter.com/search?q=%23g10kgs2017%20atjcagan
Other observations:
  • The sponsors and stall holders were mostly selling lab automation of one kind or another. Clearly, automation is what genomics researchers are likely to buy.
  • "We are a chemostat for microbes" - Lindsay Hall
  • "Strain resolution is not clustering but deconvolution" - Chris Quince
  • PerkinElmer have put a lot of work into understanding the biases of 16S kits for different hypervariable regions. 
  • Several presentations that confessed "Most of this work was done by my student" (then let your student give the presentation!). Also several people suggesting a useful paper by X where X was the last author rather than the first author. Give credit to the first author!

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