Wow, the cover looks great! .Nice work Patrice and @roederlab.bsky.social. The GENESPACE plot uses our new @jgi Pennycress and Brassica rapa genomes built in collaboration with @SpicyBotrytis & @ktgreenham, hosted on @phytozome.

Happy to see this out!! Check out my thread over at the better place for some quick background and summaries.

RT @aeharkess: We are still looking for speakers for the PAG Plant Reproductive Genomics session - please reach out if interested!.

RT @AdamRutherford: Ok, here we go: Much of my work concerns the history and return of scientific racism. I’ve written extensively about at….

RT @carriewessi: Join us!! I'm recruiting a postdoc and grad student to work with us on parallel trait evolution, quant and pop gen, and sp….

RT @zevkronenberg: Very excited to share our work on building a benchmark of all classes of variation based on the large CEPH-1463 pedigree….

There are so many things to like about this paper — very cool data viz, nuanced treatment of complex plant #pangenomes, integrations with traits. I also appreciate a lack of the non-sensical term "super pan-genome" that is somehow now in vogue😉.

Love this!!! This is why we are calling the assembly-only follow up “DEEPSPACE”.

RT @njkooyers: Our preprint is up! Using a pop genomic dataset spanning 6 continents and 4 common gardens in the native & invasive range o….

@PlantEvolution @stup0004 @jrossibarra @christinerbeck @weng_xiaoyu.

I'm putting together an analysis of variation between genomes in model systems . what are the *two* most-used reference genomes for the following?.Human -- Hg38 / CHM13.Mouse -- GRCm39 / ?.Arabidopsis -- Araport11 / ?.Maize -- B73 / ?.Rice -- (?IRGSP1?) / ?.Soybean -- Wm82 / ?.

RT @KodaniLab: The @KodaniLab is looking for a talented lab manager and senior scientist. Come join us @hudsonalpha and work alongside @nnu….

All this work was led by @AdamHealey65, and made possible with funding and support from @hudsonalpha @jgi @BerkeleyLab @jbei. Find the genome on @phytozome: 

We combined many data sources including @PacBio HiFi, HiC, @Illumina sequencing of single chromosome sorts, and optical & genetic maps. This produced a genome that presents the full set of biological sequence variation in the R570 hybrid cultivar.

So, back to the original question - how can we make a sugarcane genome that is useful? To improve sugarcane, breeders look for genetic diversity within individuals; these are sites that segregate in selfed progeny populations — we need a genome that represents this diversity.

However, in sugarcane this isn't appropriate: since gene copy number varies we cannot know the physical location of identical sequences. This means we cannot and should not produce a 'T2T' assembly for every all 120 chromosome in R570.

In simpler genomes like auto-tetraploid potato, IDB blocks due to inbreeding can be computationally duplicated so that each biological haplotype has the full complement of sequence - a 'T2T' assembly.

But, it gets more complex. As the pedigree above shows, there is lots of inbreeding in hybrid sugarcane (R570 has only three grandparents), and about half of domesticated haplotypes are identical by descent (IBD) within the last century.

The two progenitor species are polyploid: domesticated sugarcane has 8X copies and wild has variable ploidy (4-16X). When combined with unreduced gametes and preferential but not purely disomic pairing, we get a hybrid sugarcane genome that looks like this for the R570 genotype:

This is where the complexity of sugarcane genomes comes in . while not the largest plant genome ('just' ~10 billion bases), modern sugarcane cultivars have perhaps the most complex genome of any crop.