eggNOG v3.0: orthologous groups covering 1133 organisms at 41 different taxonomic ranges

Research output: Contribution to journalArticlepeer-review

Authors

  • Sean Powell
  • Damian Szklarczyk
  • Kalliopi Trachana
  • Alexander Roth
  • Michael Kuhn
  • Jean Muller
  • Thomas Rattei
  • Ivica Letunic
  • Tobias Doerks
  • Lars J Jensen
  • Christian von Mering
  • Peer Bork

Colleges, School and Institutes

External organisations

  • European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany

Abstract

Orthologous relationships form the basis of most comparative genomic and metagenomic studies and are essential for proper phylogenetic and functional analyses. The third version of the eggNOG database (http://eggnog.embl.de) contains non-supervised orthologous groups constructed from 1133 organisms, doubling the number of genes with orthology assignment compared to eggNOG v2. The new release is the result of a number of improvements and expansions: (i) the underlying homology searches are now based on the SIMAP database; (ii) the orthologous groups have been extended to 41 levels of selected taxonomic ranges enabling much more fine-grained orthology assignments; and (iii) the newly designed web page is considerably faster with more functionality. In total, eggNOG v3 contains 721,801 orthologous groups, encompassing a total of 4,396,591 genes. Additionally, we updated 4873 and 4850 original COGs and KOGs, respectively, to include all 1133 organisms. At the universal level, covering all three domains of life, 101,208 orthologous groups are available, while the others are applicable at 40 more limited taxonomic ranges. Each group is amended by multiple sequence alignments and maximum-likelihood trees and broad functional descriptions are provided for 450,904 orthologous groups (62.5%).

Details

Original languageEnglish
Pages (from-to)D284-9
JournalNucleic Acids Research
Volume40
Issue numberDatabase issue
Publication statusPublished - Jan 2012

Keywords

  • Databases, Genetic, Genomics, Phylogeny, Proteins, Sequence Homology, User-Computer Interface, Journal Article, Research Support, Non-U.S. Gov't