Integrating gene annotation with orthology inference at scale
Kirilenko, Bogdan M ; Munegowda, Chetan ; Osipova, Ekaterina ; Jebb, David ; Sharma, Virag ; Blumer, Moritz ; Morales, Ariadna E ; Ahmed, Alexis-Walid ; Kontopoulos, Dimitrios-Georgios ; Hilgers, Leon ... show 3 more
Citations
Student Authors
Faculty Advisor
Academic Program
UMass Chan Affiliations
Document Type
Publication Date
Keywords
Subject Area
Embargo Expiration Date
Link to Full Text
Abstract
Annotating coding genes and inferring orthologs are two classical challenges in genomics and evolutionary biology that have traditionally been approached separately, limiting scalability. We present TOGA (Tool to infer Orthologs from Genome Alignments), a method that integrates structural gene annotation and orthology inference. TOGA implements a different paradigm to infer orthologous loci, improves ortholog detection and annotation of conserved genes compared with 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 501 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. TOGA is a powerful and scalable method to annotate and compare genes in the genomic era.
Source
Kirilenko BM, Munegowda C, Osipova E, Jebb D, Sharma V, Blumer M, Morales AE, Ahmed AW, Kontopoulos DG, Hilgers L, Lindblad-Toh K, Karlsson EK; Zoonomia Consortium‡; Hiller M. Integrating gene annotation with orthology inference at scale. Science. 2023 Apr 28;380(6643):eabn3107. doi: 10.1126/science.abn3107. Epub 2023 Apr 28. PMID: 37104600; PMCID: PMC10193443.