The COG database: an updated version includes eukaryotes
- Roman L Tatusov1Email author,
- Natalie D Fedorova1,
- John D Jackson1,
- Aviva R Jacobs1,
- Boris Kiryutin1,
- Eugene V Koonin1,
- Dmitri M Krylov1,
- Raja Mazumder2,
- Sergei L Mekhedov1,
- Anastasia N Nikolskaya2,
- B Sridhar Rao1,
- Sergei Smirnov1,
- Alexander V Sverdlov1,
- Sona Vasudevan1,
- Yuri I Wolf1,
- Jodie J Yin1 and
- Darren A Natale2
© Tatusov et al; licensee BioMed Central Ltd. 2003
Received: 20 May 2003
Accepted: 11 September 2003
Published: 11 September 2003
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.
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 euk aryotic o rthologous g roups. 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 euk aryotic o rthologous g roups (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 ~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 ~20% of the KOG set. This conserved portion of the KOG set is much greater than the ubiquitous portion of the COG set (~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.
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.
The rapid accumulation of genome sequences is a major challenge to researchers attempting to extract the maximum functional and evolutionary information from the new genomes. To avoid informational overflow from the constant influx of new genome sequences, a comprehensive evolutionary classification of the genes from all sequenced genomes is required. Such classifications are based on two fundamental notions from evolutionary biology: orthology and paralogy, which describe the two fundamentally different types of homologous relationships between genes [1–4]. Orthologs are homologous genes derived by vertical descent from a single ancestral gene in the last common ancestor of the compared species. Paralogs, in contrast, are homologous genes, which, at some stage of evolution of the respective gene family, have evolved by duplication of an ancestral gene. The notions of orthology and paralogy are intimately linked because, if a duplication (s) occurred after the speciation event that separated the compared species, orthology becomes a relationship between sets of paralogs (co-orthologs), rather than individual genes. A classic case of the interplay between orthologous and paralogous relationships is seen in the globin family: all animal globins, including myoglobin, are paralogs, but they are all co-orthologs of the plant leghemoglobin(s) .
Deciphering orthologous and paralogous relationships among genes is critical for both the functional and the evolutionary aspects of comparative genomics [4, 5]. Orthologs typically occupy the same functional niche in different species, whereas paralogs tend to evolve toward functional diversification. Therefore, robustness of genome annotation depends on accurate identification of orthologs. Similarly, knowing which homologous genes are orthologs and which are paralogs is required for constructing evolutionary scenarios involving, along with vertical inheritance, lineage-specific gene loss and horizontal gene transfer.
In principle, identification of orthologs requires phylogenetic analysis of entire families of homologous proteins, which is expected to isolate orthologous protein sets in distinct clades [6–8]. However, on the scale of complete genomes, such analysis is both extremely labor-intensive and error-prone due to the inherent artifacts of phylogenetic tree construction. Therefore shortcuts have been developed by introducing the notion of a genome-specific best hit (BeT). A BeT is the protein in a target genome, which is most similar to a given protein from the query genome [9, 10]. The underlying premise is that orthologs are more similar to each other than they are to any other protein from the respective genomes. In multiple-genome comparisons, pairs of potential orthologs identified via BeTs can be joined to form clusters of orthologs represented in all or a subset of the analyzed genomes [9, 11]. This approach to the identification of orthologous protein sets meets with two obvious complications. Firstly, many proteins belong to lineage-specific expansions, i.e., have evolved via duplication(s) after the divergence of the compared species [12–14]. In these cases, deciphering (co)orthologous relationships can be a hard task and clusters of orthologs that include such expansions should be treated with particular caution. The second complication is caused by the fact that many proteins exist in multidomain forms encoded by a single gene in some species and as products of two or more stand-alone genes in others. In protein clustering, multidomain proteins may connect distinct clusters of orthologs resulting in artifactual lumping.
The approach to the identification of orthologous protein sets based on clustering of consistent BeTs has been implemented in the collection of Clusters of Orthologous Groups (COGs) of proteins [9, 15]. The COG construction protocol included an automatic procedure for detecting candidate sets of orthologs, manual splitting of multidomain proteins into the component domains, and subsequent manual curation and annotation. The COGs started with 6 prokaryotic genomes and one genome of a unicellular eukaryote, yeast Saccharomyces cerevisiae . Subsequent updates increased the number of prokaryotic genomes in the COGs to 43 . The procedure for COG construction required that each COG included proteins from at least three sufficiently distant species. This conservative approach notwithstanding, ~60 to ~85% of the proteins encoded in prokaryotic genomes were included in the COGs.
The COG system, which includes the COGNITOR program for adding new members to COGs (RLT, unpublished results), has become a widely used tool for computational genomics. The most important applications of the COGs are functional annotation of newly sequenced genomes [16–20] and genome-wide evolutionary analyses [21–25].
Here, we present a major update to the COGs, with over 63 sequenced prokaryotic genomes and three genomes of unicellular prokaryotes now included. Furthermore, the COG system is extended to complex, multicellular eukaryotes by constructing clusters of probable orthologs, which we named KOGs (euk aryotic o rthologous g roups) for 7 sequenced genomes of animals, fungi, microsporidia, and plants.
Results and discussion
Update of the COGs
Coverage of unicellular organisms in COGs
Number of annotated proteins
Number (and percentage) of proteins in COGs
Number of COGs that include the given species
Escherichia coli K12
Escherichia coli O157:H7
Escherichia coli O157:H7 EDL933
Neisseria meningitidis MC58
Neisseria meningitides Z2491
Helicobacter pylori 26695
Helicobacter pylori J99
Low-GC Gram-positive bacteria
Mycobacterium tuberculosis H37Rv
Mycobacterium tuberculosis CDC1551
Construction of KOGs for 7 sequenced eukaryotic genomes
Eukaryotic KOGs were constructed from annotated proteins encoded in the genomes of three animals (Homo sapiens , the fruit fly Drosophila melanogaster , and the nematode Caenorhabditis elegans) , the green plant Arabidopsis thaliana (thale cress) , two fungi (budding yeast Saccharomyces cerevisiae  and fission yeast Schizosaccharomyces pombe , and the microsporidian Encephalitozoon cuniculi ). The basic procedure for KOG construction was the same as the procedure previously employed for prokaryotic genomes (Refs. [9, 15] and see Materials and Methods). Given the abundance of multidomain architectures among eukaryotic proteins and the fact that apparent orthologs often differ in domain composition [32, 39], the protocol based on the BeT analysis was amended with domain identification using the RPS-BLAST program . Proteins assigned to a KOG by the initial KOG construction procedure were kept in that KOG without splitting them into individual domains if they shared a common core of domains. In addition, proteins, which consisted solely of widespread, "promiscuous" domains (e.g., SH2, SH3, WD40 repeats or TPR repeats) and did not show clear-cut orthologous relationships, were assigned to Fuzzy Orthologous Groups (FOGs). In addition to KOGs and FOGs, we also identified provisional clusters of orthologs represented in two genomes (TWOGs) by detecting bi-directional BeTs between proteins not included in KOGs or FOGs and assigning additional members by examination of the BLAST search outputs. Finally, lineage-specific expansions (LSEs) of paralogs among the proteins from each genome not included in KOGs, FOGs, and TWOGs were detected by using the clustering procedure described previously  accompanied by a newly developed procedure for finding tight protein clusters (BK and RLT, unpublished results). The construction of TWOGs and LSEs involved more extensive case by case evaluation than the KOG construction due to the lack of well established procedures to generate these types of clusters; nevertheless, these clusters should be considered preliminary until further validation.
Representation of the 7 analyzed eukaryotic species in KOGs
Number of annotated proteins
Number of proteins in KOGs (%)
Compared to prokaryotes, a considerably smaller fraction of eukaryotic genes could be included into KOGs (Tables 1 and 2). Thus, the apparent difference in coverage with highly conserved clusters of orthologs (C/KOGs) between prokaryotes and eukaryotes, particularly complex ones, is probably due to the relatively small number of eukaryotic genomes included in this analysis and is expected to level off with the growth of the eukaryotic genome collection. This view is compatible with the observed dependence of the KOG coverage on the number of genes (Table 1), which suggests that the KOGs are still far from saturation.
The functions of human globins and globin homologs, primarily in oxygen delivery to different tissues, at different developmental stages have been studied in great detail . In contrast, the dramatic proliferation of globin-like proteins in the nematode C. elegans, while noticed, in part, in previous work , is not well understood. To our knowledge, KOG3378 is the most complete current representation of this lineage-specific expansion of globin-like paralogs; the experimental study of these genes is expected to reveal novel aspects of invertebrate physiology.
Another notable observation comes from the analysis of the yeast members of KOG3378. A BLAST search of the non-redundant protein sequence database (NCBI, NIH, Bethesda) and examination of the domain composition of the S. cerevisiae protein YGR234w shows that this protein (named flavohemoglobin) consists of the globin domain fused to a flavodoxin reductase domain and is highly similar to a variety of oxidoreductases from several bacterial species and some lower eukaryotes (e.g., slime molds and other protists), which have the same domain composition ( and data not shown). The S. pombe flavohemoglobin belongs to the same protein family but is not the closest relative of the S. cerevisiae flavohemoglobin (data not shown). These observations strongly suggest that the yeast flavohemoglobin genes have been acquired from bacteria via horizontal gene transfer and hence have an evolutionary history that is distinct and independent from those of plant and animal globins. Notably, the second member of this KOG from S. cerevisie YNL234w is not at all a close paralog of the flavohemoglobins. The only identifiable domain in this large protein is the globin domain, which is most similar to vertebrate neuroglobins. These observations illustrate an important general point to be kept in mind when perusing the KOGs: although a given set of proteins may have been legitimately brought together in the same KOG in the context of eukaryotic genome comparison, on some occasions, different KOG members have different evolutionary trajectories.
Prokaryotic and eukaryotic orthologous gene sets: evolutionary connections and functional differences
The two sets of orthologous genes overlap because the three species of unicellular eukaryotes were included in both sets; the proteins from these species obviously form connections between prokaryotic orthologous sets (COGs) and eukaryotic orthologous sets (KOGs). Such connections, suggestive of orthologous relationships, were established between 1253 COGs, each of which included at least one protein from a unicellular eukaryote (not counting COGs that consisted exclusively of eukaryotic proteins), and 2000 eukaryotic KOGs. The greater number of eukaryotic KOGs involved in this relationship is due to the fact that, on many occasions, several proteins from unicellular eukaryotes that are part of the same COG have their distinct orthologs in other eukaryotes and, accordingly, belong to several KOGs. Only relatively small fractions of the prokaryotic COGs (27% of the COGs that include at least one prokaryotic species) and eukaryotic KOGs (34% of the KOGs and TWOGs) comprised sets of putative orthologs represented in both prokaryotes and eukaryotes. This emphasizes the distinction between the repertoires of genes that are conserved in prokaryotes and in eukaryotes and the considerable amount of innovation in both groups of organisms. However, these numbers give the low bound of the shared clusters of orthologs because some of the KOGs are not represented in the relatively small genomes of unicellular eukaryotes, primarily due to gene loss in the latter, but have prokaryotic counterparts.
Using phyletic patterns to examine gene function and evolution
The second case in point that we consider here is a search for COGs, which are represented in the causative agent of plague, Yersinia pestis , but not in other Proteobacteria (the taxon to which Y. pestis belongs) or eukaryotes; this query retrieves 7 COGs (Fig. 5b). These genes probably have been acquired by Y. pestis via horizontal gene transfer. On a more practical note, some of these genes could be potential targets for highly selective anti-bacterial agents. It is noticeable that three of these genes are predicted to be involved in cell wall metabolism (COGs 2152, 2401, and 3867), whereas the functions of others remain uncharacterized.
The collection of COGs from prokaryotes and unicellular eukaryotes was substantially amended to include 66 species and eukaryotic orthologous groups (KOGs) for 7 species were constructed. The prokaryotic COG system already covers most of the globular proteins encoded in bacterial and archaeal genomes. Eukaryotic KOGs include a lower fraction of the encoded proteins but this difference is expected to level off with the growth of the eukaryotic genome collection. The eukaryotic KOG analysis revealed a substantial conserved core of eukaryotic genes as well as major lineage-specific variations. Lineage-specific expansion of paralogous families within the KOGs and expansion of families that do not have orthologs in other compared genomes make major contributions to the eukaryotic gene repertoire. Only a minority of eukaryotic KOGs have readily detectable prokaryotic counterparts and the same holds for prokaryotic COGs, emphasizing the extent of innovation in both the eukaryotic and prokaryotic divisions of life. The wide scatter of the phyletic patterns among the KOGs testifies to the importance of lineage-specific gene loss in the evolution of eukaryotic genomes.
The current collection of eukaryotic KOGs includes 7 genomes whose sequences had been available as of July 1, 2002. Manual correction and annotation of KOGs is a labor-intensive process, which precluded immediate inclusion of the genomes of the mouse , fugu fish , mosquito , the urochordate Ciona instestinalis , and the malarial parasite Plasmodium falciparum , which have become available since that date. However, once the basic system is established, it is expected that inclusion of these and other newly sequenced genomes in the KOG system proceeds at a greater pace.
The C/KOG system can be employed for functional annotation of genes from new genomes by using the COGNITOR program and for research into genome evolution. The utility of the system for both of these purposes should increase progressively with the inclusion of new genomes, particularly those of early-branching eukaryotes.
Protein sets for new genomes
The protein sets for all newly included bacterial and archaeal genomes, the yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe, the microsporidian Encaephalitozoon cuniculi, the thale cress Arabidopsis thaliana, and the fruit fly Drosophila melanogaster were extracted from the Genome division of the (NCBI, NIH, Bethesda). The protein sequences for the nematode Caenorhabditis elegans were from the WormPep67 database, the sequences for Homo sapiens were from the NCBI build 30.
Addition of new genomes to the COGs
The new genomes were added to the COGs by using the COGNITOR program, with the results validated manually, essentially as described previously [9, 15]. After the completion of the validation process, the remaining proteins were subject to the COG construction procedure, in order to detect new COGs that could not be formed without the added genomes; the validation and annotation steps were repeated with the newly detected COGs.
Sequence analysis, construction and annotation of KOGs
The construction of KOGs followed the previously outlined strategy based on sets of consistent BeTs [9, 15], but included additional steps that reflected specific features of eukaryotic proteins. Briefly, the procedure was as follows. 1. Detection and masking of widespread, typically repetitive domains, which was performed by using the RPS-BLAST program and the PSSMs for the respective domains from the CDD collection . These domains, namely, PPR (pfam01535), WD40 (pfam00400), IG (pfam00047), IGc1, Igv, IG_like, RRM (pfam00076), ANK (pfam00023), myosin tail (pfam01576), Fn3 (pfam00041), CA, (IG), ANK, kelch (pfam01344), OAD_kelch, SH3 (pfam00018), intermediate filaments (pfam00038), C2H2 finger (pfam00096), PDZ (pfam00595), POZ (pfam00651), PH (pfam00169), ZnF-C4 (pfam00105), spectrin (pfam00435), Sushi (pfam00084), TPR (pfam00017), BTB, LRR_CC, LY, ARM, SH2, and CH, were detected and masked prior to applying the COG construction procedure. Masking these domains was required to ensure the robust classification of the eukaryotic orthologous clusters with the KOG detection procedure because hits between these common, "promiscuous" domains resulted in spurious lumping of numerous non-orthologous proteins. 2. All-against-all comparison of protein sequences from the analyzed genomes by using the gapped BLAST program , with filtering for low sequence complexity regions performed using the SEG program . 3. Detection of triangles of mutually consistent, genome-specific best hits (BeTs). 4. Merging triangles with a common side to form crude, preliminary KOGs. 5. Case by case analysis of each candidate KOG. This analysis serves to eliminate the false-positives that are incorporated in the KOGs during the automatic steps and included, primarily, examination of the domain composition of KOG members, which was determined using the RPS-BLAST program and the CDD collection of position-specific scoring matrices (PSSMs) for individual domains . Generally, proteins were kept in the same KOG when they shared a conserved core domain architecture. However, in cases when KOGs were artificially bridged by multidomain proteins, the latter were split into individual domains (or arrays of domains) and steps (1)-(4) were repeated with these sequences; this results in the assignment of individual domains to KOGs in accordance with their distinct evolutionary affinities. 6. Assignment of proteins containing promiscuous domains. In cases when a sequence assigned to a KOG contained one or more masked promiscuous domains, these domains were restored and became part of the respective KOG. Proteins containing promiscuous domains but not assigned to any KOG were classified in Fuzzy Orthologous Groups (FOGs) named after the respective domains. 7. Examination of large KOGs, which included multiple members from all or several of the compared genomes by using phylogenetic trees, cluster analysis with the BLASTCLUST program ftp://ftp.ncbi.nih.gov/blast/, comparison of domain architectures, and visual inspection of alignments; as a result, some of these protein sets were split into two or more smaller ones that were included in the final set of KOGs.
The KOGs were annotated on the basis of the annotations available through GenBank and other public databases, which were critically assessed against the primary literature. For proteins that are currently annotated as "hypothetical" or "unknown", iterative sequence similarity searches with the PSI-BLAST program , the results of the RPS-BLAST searches, additional domain architecture analysis performed by using the SMART system , and comparison to the COG database by using the COGNITOR program (RLT, unpublished results) were employed to identify distant homologs with experimentally characterized functions and/or structures. The known and predicted functions of KOGs were classified into 23 categories (see legend to Fig. 4); these were modified from the functional classification previously employed for prokaryotic COGs  by including several specific eukaryotic categories.
Availability of the results
We thank L. Aravind, David Lipman, Kira Makarova and Wei Yang for useful discussions, and Igor Garkavtsev for his contributions at the initial stages of the KOG project.
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