Journal Article

eggNOG: automated construction and annotation of orthologous groups of genes

Lars Juhl Jensen, Philippe Julien, Michael Kuhn, Christian von Mering, Jean Muller, Tobias Doerks and Peer Bork

in Nucleic Acids Research

Volume 36, issue suppl_1, pages D250-D254
Published in print January 2008 | ISSN: 0305-1048
Published online October 2007 | e-ISSN: 1362-4962 | DOI: http://dx.doi.org/10.1093/nar/gkm796
eggNOG: automated construction and annotation of orthologous groups of genes

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The identification of orthologous genes forms the basis for most comparative genomics studies. Existing approaches either lack functional annotation of the identified orthologous groups, hampering the interpretation of subsequent results, or are manually annotated and thus lag behind the rapid sequencing of new genomes. Here we present the eggNOG database (‘evolutionary genealogy of genes: Non-supervised Orthologous Groups’), which contains orthologous groups constructed from Smith–Waterman alignments through identification of reciprocal best matches and triangular linkage clustering. Applying this procedure to 312 bacterial, 26 archaeal and 35 eukaryotic genomes yielded 43 582 course-grained orthologous groups of which 9724 are extended versions of those from the original COG/KOG database. We also constructed more fine-grained groups for selected subsets of organisms, such as the 19 914 mammalian orthologous groups. We automatically annotated our non-supervised orthologous groups with functional descriptions, which were derived by identifying common denominators for the genes based on their individual textual descriptions, annotated functional categories, and predicted protein domains. The orthologous groups in eggNOG contain 1 241 751 genes and provide at least a broad functional description for 77% of them. Users can query the resource for individual genes via a web interface or download the complete set of orthologous groups at http://eggnog.embl.de.

Journal Article.  2236 words.  Illustrated.

Subjects: Chemistry ; Biochemistry ; Bioinformatics and Computational Biology ; Genetics and Genomics ; Molecular and Cell Biology

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