eggNOG: automated construction and annotation of orthologous groups of genes

By Lars Juhl Jensen, P. Julien, Michael Kuhn, C. von Mering, Jean Muller, Tobias Doerks, Peer Bork. 2007

560 citations recorded by the source corpus.

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.

Subfields: Molecular Biology

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Citations in the corpus

eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses (2018, background): “An Orthologous Group (OG) is defined as a cluster of three or more homologous sequences that diverge from the same speciation event (16,17).”
MMseqs2: sensitive protein sequence searching for the analysis of massive data sets (2017, methodology): “The speed and quality bottleneck is to find for each OMRGC sequence homologous clusters in the eggNOGv3 [15] and KEGG databases.”
Proteinortho: Detection of (Co-)orthologs in large-scale analysis (2011, background): “For protein-coding genes, several well-known databases, including InParanoid [2], OrthoMCL-DB [3], COG [4], Homogene [5], eggNOG [6], OMA Browser [7] and Ensembl Compara [8] compile such information.”
A human gut microbial gene catalog established by metagenomic sequencing (2010, methodology): “We used BLASTP to search the protein sequencesofthepredictedgenesintheeggNOGdatabase 26 andKEGGdatabase 24 with e -value # 1 3 10 2 5 .”
STRING 8—a global view on proteins and their functional interactions in 630 organisms (2008, methodology): “For the latter, STRING relies on an updated and extended version of the COGs [‘Clusters of Orthologous Groups’ (29)], which is being maintained at the eggNOG database (30).”
Genomics of bacteria and archaea: the emerging dynamic view of the prokaryotic world (2008, methodology): “The COGs were from the EggNOG database (41), and the proteins from each genome were assigned to these clusters using a modified COGNITOR method (42).”
Phylogenetic and Functional Assessment of Orthologs Inference Projects and Methods (2009, methodology): “It appears that COG, EggNOG and OrthoMCL suffer from comparatively high falsepositive rates, which is reflected in the significantly reduced amount of correctly reconstructed gene trees.”
Ortholog identification in the presence of domain architecture rearrangement (2011, background): “Reciprocal BLAST Hit (RBH), COGs [34], InParanoid [35], OrthoMCL [36], eggNOG [37], ClusTr [38], ProtoNet [39] and Systers [40] are examples of graph-based methods.”
The human small intestinal microbiota is driven by rapid uptake and conversion of simple carbohydrates (2012, methodology): “Input data were BLASTp results of the proteins against the STRING 7 database (Jensen et al., 2008).”
eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences (2015, methodology): “We maintain a database of Orthologous Groups (OGs) and functional annotations called eggNOG (evolutionary genealogy of genes: Non-supervised Orthologous Groups) (21).”
Linking pangenomes and metagenomes: the Prochlorococcus metapangenome (2018, background): “12.6 ( Huerta-Cepas et al., 2016 ) outputs for our genes with the program ‘anvi-import-functions’ to import annotations from other databases, including PFAM ( Bateman et al., 2004 ), and eggNOG ( Jensen et al., 2008 ).”