Integrating gene annotation with orthology inference at scale
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- dc.contributor.author Kirilenko, Bogdan M.
- dc.contributor.author Munegowda, Chetan
- dc.contributor.author Osipova, Ekaterina
- dc.contributor.author Jebb, David
- dc.contributor.author Sharma, Virag
- dc.contributor.author Blumer, Moritz
- dc.contributor.author Morales, Ariadna E.
- dc.contributor.author Ahmed, Alexis-Walid
- dc.contributor.author Kontopoulos, Dimitrios-Georgios
- dc.contributor.author Hilgers, Leon
- dc.contributor.author Lindblad-Toh, Kerstin
- dc.contributor.author Karlsson, Elinor K.
- dc.contributor.author Zoonomia Consortium
- dc.contributor.author Hiller, Michael
- dc.date.accessioned 2024-03-25T07:10:11Z
- dc.date.available 2024-03-25T07:10:11Z
- dc.date.issued 2023
- dc.description.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.
- dc.format.mimetype application/pdf
- dc.identifier.citation Kirilenko BM, Munegowda C, Osipova E, Jebb D, Sharma V, Blumer M, et al. Integrating gene annotation with orthology inference at scale. Science. 2023 Apr 28;380(6643):eabn3107. DOI: 10.1126/science.abn3107
- dc.identifier.doi http://dx.doi.org/10.1126/science.abn3107
- dc.identifier.issn 0036-8075
- dc.identifier.uri http://hdl.handle.net/10230/59551
- dc.language.iso eng
- dc.publisher American Association for the Advancement of Science (AAAS)
- dc.relation.ispartof Science. 2023 Apr 28;380(6643):eabn3107
- dc.rights This is the author’s version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science. 2023 Apr 28;380(6643):eabn3107, DOI: 10.1126/science.abn3107.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.subject.keyword Comparative genomics
- dc.subject.keyword Orthology inference
- dc.subject.keyword Gene annotation
- dc.subject.keyword Genome alignment
- dc.subject.keyword Gene loss
- dc.subject.keyword Machine learning
- dc.title Integrating gene annotation with orthology inference at scale
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/acceptedVersion