ABSTRACTConsistent 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 annotation sources. A pangene set effectively summarizes our current understanding of the coding potential of a crop and can be used to inform gene model annotation in new cultivars. Here we present an approach (get_pangenes) to identify and analyze pangenes that is not biased towards the reference annotation. The method involves computing Whole Genome Alignments (WGA), which are used to estimate gene model overlaps. After a benchmark onArabidopsis, rice, wheat and barley datasets, we find that minimap2 performs better than the GSAlign WGA algorithm. Our results show that pangenes recapitulate known phylogeny-based orthologies while adding extra core gene models in rice. More importantly, get_pangenes can also produce clusters of genome segments (gDNA) that overlap with gene models annotated in other cultivars. By lifting-over CDS sequences, gDNA clusters can help refine gene models across individuals and confirm or reject observed gene Presence-Absence Variation. A collection of flowering-related genes from the barley pangenome are discussed in detail. Documentation and source code are available athttps://github.com/Ensembl/plant-scripts.
