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The COG database: an updated version includes eukaryotes
Open accessAbstract
BACKGROUND: The availability of multiple, essentially complete genome sequences of prokaryotes and eukaryotes spurred both the demand and the opportunity for the construction of an evolutionary classification of genes from these genomes. Such a classification system based on orthologous relationships between genes appears to be a natural framework for comparative genomics and should facilitate both functional annotation of genomes and large-scale evolutionary studies. RESULTS: We describe here a major update of the previously developed system for delineation of Clusters of Orthologous Groups of proteins (COGs) from the sequenced genomes of prokaryotes and unicellular eukaryotes and the construction of clusters of predicted orthologs for 7 eukaryotic genomes, which we named KOGs after eukaryotic orthologous groups. The COG collection currently consists of 138,458 proteins, which form 4873 COGs and comprise 75% of the 185,505 (predicted) proteins encoded in 66 genomes of unicellular organisms. The eukaryotic orthologous groups (KOGs) include proteins from 7 eukaryotic genomes: three animals (the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster and Homo sapiens), one plant, Arabidopsis thaliana, two fungi (Saccharomyces cerevisiae and Schizosaccharomyces pombe), and the intracellular microsporidian parasite Encephalitozoon cuniculi. The current KOG set consists of 4852 clusters of orthologs, which include 59,838 proteins, or approximately 54% of the analyzed eukaryotic 110,655 gene products. Compared to the coverage of the prokaryotic genomes with COGs, a considerably smaller fraction of eukaryotic genes could be included into the KOGs; addition of new eukaryotic genomes is expected to result in substantial increase in the coverage of eukaryotic genomes with KOGs. Examination of the phyletic patterns of KOGs reveals a conserved core represented in all analyzed species and consisting of approximately 20% of the KOG set. This conserved portion of the KOG set is much greater than the ubiquitous portion of the COG set (approximately 1% of the COGs). In part, this difference is probably due to the small number of included eukaryotic genomes, but it could also reflect the relative compactness of eukaryotes as a clade and the greater evolutionary stability of eukaryotic genomes. CONCLUSION: The updated collection of orthologous protein sets for prokaryotes and eukaryotes is expected to be a useful platform for functional annotation of newly sequenced genomes, including those of complex eukaryotes, and genome-wide evolutionary studies.
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“The Clusters of Orthologous Group (COG) functional categories (21) (including 22 categories from PCC 7002) were downloaded from the NCBI (http://www.”
MethodPlastic biodegradation by sediment microbial populations under denitrifying conditions
Sun, X., Wang, S., Lin, Z., Chen, Z., Huang, W., Kong, T., Huang, D., Li, B., Zhang, H., & Sun, W. (2025) · Environmental Science & Technology · doi:10.1021/acs.est.4c12187 · Cited by 20
Frouin, E., Lecoeuvre, A., Armougom, F., Schrenk, M. O., & Erauso, G. (2022) · mSystems · doi:10.1128/msystems.00328-22 · Cited by 20
The Escherichia coli Fur pan-regulon has few conserved but many unique regulatory targets
Gao, Y., Bang, I., Seif, Y., Kim, D., & Palsson, B. O. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad253 · Cited by 14
Function and evolution of two forms of SecDF homologs in Streptomyces coelicolor.
Zhou, Z., Li, Y., Sun, N., Sun, Z., Lv, L., Wang, Y., Shen, L., & Li, Y.-Q. (2014) · PLoS ONE · doi:10.1371/journal.pone.0105237 · Cited by 13
The Draft Genome of a Hydrogen-producing Cyanobacterium, Arthrospira platensis NIES-46
Suzuki, S., Yamaguchi, H., & Kawachi, M. (2019) · Journal of Genomics · doi:10.7150/jgen.38149 · Cited by 12
Computational workflow for analysis of gain and loss of genes in distantly related genomes
Ptitsyn, A., & Moroz, L. L. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-s15-s5 · Cited by 11
Li, M., Yu, J., Li, W., Wu, Q., Sun, J., & Sun, Z. (2024) · Food Science and Human Wellness · doi:10.26599/fshw.2022.9250243 · Cited by 5
Fang, S., Wang, S., Liu, Y., Zhu, C., Wang, S., & Xu, F. (2026) · Food Science & Nutrition · doi:10.1002/fsn3.71420 · Cited by 4
nf-core/proteinfamilies: a scalable pipeline for the generation of protein families
Karatzas, E., Beracochea, M., Baltoumas, F. A., Aplakidou, E., Richardson, L., Fellows Yates, J. A., Lundin, D., community, N.-C., Buluç, A., Kyrpides, N. C., et al. (2026) · GigaScience · doi:10.1093/gigascience/giag009
Metadata
- Authors
- Tatusov, R. L., Fedorova, N. D., Jackson, J. D., Jacobs, A. R., Kiryutin, B., Koonin, E. V., Krylov, D. M., Mazumder, R., Mekhedov, S. L., Nikolskaya, A. N., Rao, B. S., Smirnov, S., Sverdlov, A. V., Vasudevan, S., Wolf, Y. I., Yin, J. J., & Natale, D. A.
- Venue
- BMC Bioinformatics
- Published
- 2003-09-11
- Volume
- 4
- Issue
- 1
- Pages
- 41-41
- ISSN
- 1471-2105 (ISSN-L)
- OpenAlex
- W2155606054
- Cited by
- 4,430
- References
- 5
- FWCI
- 47.93
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
