Identifying single copy orthologs in metazoa

• Verfasst von: Creevey, Christopher J. [VerfasserIn]
• Verfasst von: Arendt, Detlev [VerfasserIn]
• Verfasst von: Bork, Peer [VerfasserIn]
• Titel: Identifying single copy orthologs in metazoa
• Verf.angabe: Christopher J. Creevey, Jean Muller, Tobias Doerks, Julie D. Thompson, Detlev Arendt, Peer Bork
• E-Jahr: 2011
• Jahr: December 1, 2011
• Umfang: 12 S.
• Fussnoten: Gesehen am 18.05.2017
• Titel Quelle: Enthalten in: Public Library of SciencePLoS Computational Biology
• Ort Quelle: San Francisco, Calif. : Public Library of Science, 2005
• Jahr Quelle: 2011
• Band/Heft Quelle: 7(2011,12) Artikelummer e1002269, 12 Seiten
• ISSN Quelle: 1553-7358
• DOI: doi:10.1371/journal.pcbi.1002269
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Comparative genomics
• Sach-SW: Genome annotation
• Sach-SW: Genomic databases
• Sach-SW: Multiple alignment calculation
• Sach-SW: Phylogenetic analysis
• Sach-SW: Phylogenetics
• Sach-SW: Sequence alignment
• Sach-SW: Sequence databases
• K10plus-PPN: 1558741305

Abstract

Author Summary The correct identification of single copy (1-to-1) orthologs is crucial for functional classification of genes and for phylogenetic studies of groups of organisms, including the Metazoa. Nevertheless, despite the recent increase in the number of genomes and short sequence read datasets (e.g. ESTs) from the Metazoa, we know little about their completeness and how useful they may be for phylogenetic studies. Here we describe a novel approach for the identification of single copy gene families at any hierarchical level and demonstrate its effectiveness by identifying a set of over one thousand gene families that have been in single copy since the last common ancestor of the Metazoa. By comparing our orthologs to those predicted by other datasets we show that our procedure identifies a significantly larger set of single copy orthologs in the Metazoa. We then use this dataset to assess 24 metazoan genomes and 61 metazoan EST datasets for their completeness. We thus identify the underlying error rate in genome annotation and suggest a mechanism for assessing the quality of genomes and EST datasets in terms of their suitability for phylogenetic studies.