eggNOG: automated construction and annotation of orthologous groups of genes
Open accessAbstract
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.
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Graph-based methods cluster genes into pairs or groups of orthologs based on pairwise sequence similarity such as reciprocal best alignment hits.
“Graph-based methods cluster genes into pairs or groups of orthologs based on pairwise sequence similarity such as (reciprocal) best alignment hits (8–12).”
From Integrating gene annotation with orthology inference at scale (2023) · cites this paper as [11]
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Arnoux, J. (2026) · Thèse de doctorat, Université Paris-Saclay / PPanGGOLiN · doi:10.70675/eee354d9zf63dz48ebz9444zd1809f8fb74d
- Authors
- Jensen, L. J., Julien, P., Kuhn, M., von Mering, C., Muller, J., Doerks, T., & Bork, P.
- Affiliations
- European Molecular Biology Laboratory (DE)
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-12-23
- Volume
- 36
- Issue
- Database
- Pages
- D250-D254
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC2238944
- OpenAlex
- W2154364831
- Cited by
- 547
- References
- 1
- Citations by year
- 2026: 19 · 2025: 42 · 2024: 44 · 2023: 30 · 2022: 51 · 2021: 54 · 2020: 65 · 2019: 37 · 2018: 24 · 2017: 18 · 2016: 10 · 2015: 18 · 2014: 15 · 2013: 20 · 2012: 19
- FWCI
- 6.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (acceptedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, other-oa)
- reroDoc Digital Library (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- European Molecular Biology Laboratory
- European Commission
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
- Keywords
- eggNOG, orthogroups, comparative genomics, functional annotation, Smith-Waterman alignment, protein domains, gene annotation databases
- MeSH terms
- Animals, Genes, Phylogeny, Proteins, Quality Control, User-Computer Interface, Internet, Genomics, Databases, Genetic
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