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!

The metahaplome

A sample of water, soil or gut contents will contain a whole community of microbes, cooperating and competing. We now have the sequencing technology to begin to explore these communities, to find out the variation that they possess. This can be useful in the search for new anti-microbials, or in the search for better enzymes for biofuels. However, the sequencing technology is not quite there yet. The very short length of the reads, together with the errors introduced, combine to make the problem of reassembling the underlying genomes much more complex.

We introduce the concept of the 'metahaplome': the exact sequence of DNA bases (or "haplotype") that constitutes the genes and genomes of every individual present. We also present a data structure and algorithm that will recover the haplotypes in the metahaplome, and rank them according to likelihood.

Our preprint about the metahaplome is now available at bioRxiv: Probabilistic Recovery Of Cryptic Haplotypes From Metagenomic Data.

Aros yn Ewrop : the metagenome of our countries

My thoughts on the parallels between our work in metagenomics and the referendum on June 23rd 2016.

A community of species
sharing cross-genomic pieces,
co-existing in the rumen
work to chew the grass around.

A community of nations
with historical relations
can assemble a consensus
to agree on common ground.

The variation that we're seeing
gives an accent to each being
and to the metagenome union,
and the medley swings in sound.

Vote to stay, aros yn ewrop!
Exchange people, plans and workshops.
In a globe of sequence differences
we can learn from each one found.

Seamless gene deletion

2015 is the year that genome editing really became big news. A new technique, "CRISPR/CAS", was named as Science magazine's breakthrough of the year as voted by the public from a shortlist chosen by staff.

However, people have been manipulating DNA through many useful methods long before CRISPR/CAS made headlines. Gene deletion is an important tool when trying to understand the function of genes. Take out a gene and see what effect it causes. Genes can be disrupted (by removing a portion of the DNA or inserting some extra DNA) or can be interfered with, for example via their RNA production, or they can be entirely deleted. It's common practice when removing a gene to insert a marker, so that we can easily select for the cells where this procedure has been successful. For example, to insert an antibiotic resistance gene as a marker, so that we can now grow the cells on a plate with an antibiotic. Then only those that have lost our gene of interest and gained antibiotic resistance will now grow. The trouble with this is that many gene deletions have no visible effect by themselves. If we also want to delete a second gene and a third, then we need more markers, or we need to be able to remove and reuse the marker we inserted. We also don't want the process to leave any scars behind that could destabilise the genome. We've just published a paper to help solve this problem.

This process of 'swap a gene of interest for a marker gene' can be achieved in many organisms by homologous recombination. This is a process used by many cells to repair broken strands of DNA. If we provide a piece of DNA that has a good region of similarity to the region just downstream of our gene of interest, and also a good region of similarity to the region just upstream of the gene of interest, but instead of the gene of interest, has the marker gene between these regions, then the normal cellular processes of homologous recombination will exchange the two. Some organisms perform homologous recombination very readily (S. cerevisiae for example). Others may need a little more encouragement, such as creating a double stranded break.

Our new paper A tool for Multiple Targeted Genome Deletions that Is Precise, Scar-Free and Suitable for Automation with Wayne Aubrey as first author uses a 3-stage PCR process to synthesise a stretch of DNA (a 'cassette') that will do everything. It will have good regions of similarity to the regions upstream and downstream of the gene of interest. It will contain a marker gene. And (here's the good bit), it will contain a specially designed region ('R') before the marker gene that is identical to the region that occurs just after the gene of interest. In this way, after homologous recombination has done its thing and inserted the DNA cassette instead of the gene of interest, there will be two identical R regions, one before the marker gene, and one after the marker gene. Sometimes the DNA will loop round on itself, the two R regions will match up and homologous recombination will snip out the loop, including the marker gene.

We can encourage this to happen and select for the cells that have had this happen if our marker is also 'counter-selectable'. That is, we'd like a marker for which we can add something to the growth medium so that now only cells without the marker will now grow. That is, we'd like to use a marker or marker combination for which we can first select for its presence and then counter-select for its absence. When we have this we can select for cells that have had the marker replace the gene, and then counter-select for cells that have now lost the marker too. So we have a clean gene deletion.

Of course we're always standing on the shoulders of giants when we do science. Our method is an improvement on a method by Akada 2006, so that no extra bases are lost or gained and the method requires no gel purification steps. Just throw in your primers and products and away you go. It's not fussy about quantity. No purification steps means that it could be automated on lab robots. And it could be used to delete any genetic component, not just genes. Give it a try!