Different orthology inference algorithms generate similar predicted orthogroups among Brassicaceae species.

Premise: Orthology inference is crucial for comparative genomics, and multiple algorithms have been developed to identify putative orthologs for downstream analyses. Despite the abundance of proposed solutions, including publicly available benchmarks, it is difficult to assess which tool is most suitable for plant species, which commonly have complex genomic histories.

Methods: We explored the performance of four orthology inference algorithms-OrthoFinder, SonicParanoid, Broccoli, and OrthNet-on eight Brassicaceae genomes in two groups: one group comprising only diploids and another set comprising the diploids, two mesopolyploids, and one recent hexaploid genome.