Abstract
Consistent gene annotation in crops is becoming harder as genomes for new cultivars are frequently published. Gene sets from recently sequenced accessions have different gene identifiers to those on the reference accession, and might be of higher quality due to technical advances. For these reasons there is a need to define pangenes, which represent all known syntenic orthologues for a gene model and can be linked back to the original sources. A pangene set encapsulates the coding potential of a crop and can inform gene model annotation and allele mining in new cultivars. I will present an approach (GET_PANGENES) for calling pangenes that is not biased towards the reference. It involves computing Whole Genome Alignments (WGA), which are subsequently used to estimate gene model overlaps. A benchmark on plants with increasing genome size shows that pangenes recapitulate phylogeny-based orthologies and produce complete soft-core gene sets. Moreover, WGAs support lift-over and help confirm gene presence-absence variation. I will discuss challenges such as repeat masking, computing costs, tandem gene copies and a few examples of allelic variation on barley. Finally, I will summarize an ongoing pangene analysis of the MAGIC15 Asian rice population.