1. Kirilenko, B.M., Munegowda, C., Osipova, E., Jebb, D., Sharma, V., Blumer, M., Morales, A., Ahmed, A.-W., Kontopoulos, D.-G., Hilgers, L., Zoonomia Consortium, and Hiller, M. (2022). TOGA integrates gene annotation with orthology inference at scale. bioRxiv 2022.09.08.507143.


Annotating coding genes and inferring orthologs are two classical challenges in genomics and evolutionary biology that have traditionally been approached separately, which limits scalability. We present TOGA, the first method that integrates gene annotation and orthology inference. TOGA implements a novel paradigm to infer orthologous genes, improves ortholog detection and annotation completeness compared to state-of-the-art methods, and handles even highly-fragmented assemblies. TOGA scales to hundreds of genomes, which we demonstrate by applying it to 488 placental mammal and 308 bird assemblies, creating the largest comparative gene resources so far. Additionally, TOGA detects gene losses, enables selection screens, and automatically provides a superior measure of mammalian genome quality. Together, TOGA is a powerful and scalable method to annotate and compare genes in the genomic era.

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