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Database Commons - COG


Citations: 11125

z-index 185.42

Short name COG
Full name Clusters of Orthologous Genes
Description COG contains phylogenetic classification of proteins encoded in complete genomes.
Year founded 1997
Last update & version 2014    v1.0
Availability Free to all users
University/Institution hosted National Center for Biotechnology Information
Address Bethesda, MD 2094, USA
City Bethesda
Province/State MD
Country/Region United States
Contact name Eugene V. Koonin
Contact email
Data type(s)
Major organism(s)
  • gene orthology
  • Archaeal Clusters of Orthologous Genes (arCOGs): An Update and Application for Analysis of Shared Features between Thermococcales, Methanococcales, and Methanobacteriales. [PMID: 25764277]

    Kira S Makarova, Yuri I Wolf, Eugene V Koonin
    Life (Basel, Switzerland) 2015:5(1)
    3 Citations (Google Scholar as of 2015-12-30)

    Abstract: With the continuously accelerating genome sequencing from diverse groups of archaea and bacteria, accurate identification of gene orthology and availability of readily expandable clusters of orthologous genes are essential for the functional annotation of new genomes. We report an update of the collection of archaeal Clusters of Orthologous Genes (arCOGs) to cover, on average, 91% of the protein-coding genes in 168 archaeal genomes. The new arCOGs were constructed using refined algorithms for orthology identification combined with extensive manual curation, including incorporation of the results of several completed and ongoing research projects in archaeal genomics. A new level of classification is introduced, superclusters that untie two or more arCOGs and more completely reflect gene family evolution than individual, disconnected arCOGs. Assessment of the current archaeal genome annotation in public databases indicates that consistent use of arCOGs can significantly improve the annotation quality. In addition to their utility for genome annotation, arCOGs also are a platform for phylogenomic analysis. We explore this aspect of arCOGs by performing a phylogenomic study of the Thermococci that are traditionally viewed as the basal branch of the Euryarchaeota. The results of phylogenomic analysis that involved both comparison of multiple phylogenetic trees and a search for putative derived shared characters by using phyletic patterns extracted from the arCOGs reveal a likely evolutionary relationship between the Thermococci, Methanococci, and Methanobacteria. The arCOGs are expected to be instrumental for a comprehensive phylogenomic study of the archaea.

  • Expanded microbial genome coverage and improved protein family annotation in the COG database. [PMID: 25428365]

    Michael Y Galperin, Kira S Makarova, Yuri I Wolf, Eugene V Koonin
    Nucleic acids research 2015:43(Database issue)
    27 Citations (Google Scholar as of 2015-12-30)

    Abstract: Microbial genome sequencing projects produce numerous sequences of deduced proteins, only a small fraction of which have been or will ever be studied experimentally. This leaves sequence analysis as the only feasible way to annotate these proteins and assign to them tentative functions. The Clusters of Orthologous Groups of proteins (COGs) database (, first created in 1997, has been a popular tool for functional annotation. Its success was largely based on (i) its reliance on complete microbial genomes, which allowed reliable assignment of orthologs and paralogs for most genes; (ii) orthology-based approach, which used the function(s) of the characterized member(s) of the protein family (COG) to assign function(s) to the entire set of carefully identified orthologs and describe the range of potential functions when there were more than one; and (iii) careful manual curation of the annotation of the COGs, aimed at detailed prediction of the biological function(s) for each COG while avoiding annotation errors and overprediction. Here we present an update of the COGs, the first since 2003, and a comprehensive revision of the COG annotations and expansion of the genome coverage to include representative complete genomes from all bacterial and archaeal lineages down to the genus level. This re-analysis of the COGs shows that the original COG assignments had an error rate below 0.5% and allows an assessment of the progress in functional genomics in the past 12 years. During this time, functions of many previously uncharacterized COGs have been elucidated and tentative functional assignments of many COGs have been validated, either by targeted experiments or through the use of high-throughput methods. A particularly important development is the assignment of functions to several widespread, conserved proteins many of which turned out to participate in translation, in particular rRNA maturation and tRNA modification. The new version of the COGs is expected to become an important tool for microbial genomics. Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by US Government employees and is in the public domain in the US.

  • Mimiviridae: clusters of orthologous genes, reconstruction of gene repertoire evolution and proposed expansion of the giant virus family. [PMID: 23557328]

    Natalya Yutin, Philippe Colson, Didier Raoult, Eugene V Koonin
    Virology journal 2013:10
    44 Citations (Google Scholar as of 2016-08-16)

    Abstract: The family Mimiviridae belongs to the large monophyletic group of Nucleo-Cytoplasmic Large DNA Viruses (NCLDV; proposed order Megavirales) and encompasses giant viruses infecting amoeba and probably other unicellular eukaryotes. The recent discovery of the Cafeteria roenbergensis virus (CroV), a distant relative of the prototype mimiviruses, led to a substantial expansion of the genetic variance within the family Mimiviridae. In the light of these findings, a reassessment of the relationships between the mimiviruses and other NCLDV and reconstruction of the evolution of giant virus genomes emerge as interesting and timely goals. Database searches for the protein sequences encoded in the genomes of several viruses originally classified as members of the family Phycodnaviridae, in particular Organic Lake phycodnaviruses and Phaeocystis globosa viruses (OLPG), revealed a greater number of highly similar homologs in members of the Mimiviridae than in phycodnaviruses. We constructed a collection of 898 Clusters of Orthologous Genes for the putative expanded family Mimiviridae (MimiCOGs) and used these clusters for a comprehensive phylogenetic analysis of the genes that are conserved in most of the NCLDV. The topologies of the phylogenetic trees for these conserved viral genes strongly support the monophyly of the OLPG and the mimiviruses. The same tree topology was obtained by analysis of the phyletic patterns of conserved viral genes. We further employed the mimiCOGs to obtain a maximum likelihood reconstruction of the history of genes losses and gains among the giant viruses. The results reveal massive gene gain in the mimivirus branch and modest gene gain in the OLPG branch. These phylogenomic results reported here suggest a substantial expansion of the family Mimiviridae. The proposed expanded family encompasses a greater diversity of viruses including a group of viruses with much smaller genomes than those of the original members of the Mimiviridae. If the OLPG group is included in an expanded family Mimiviridae, it becomes the only family of giant viruses currently shown to host virophages. The mimiCOGs are expected to become a key resource for phylogenomics of giant viruses.

  • Orthologous gene clusters and taxon signature genes for viruses of prokaryotes. [PMID: 23222723]

    David M Kristensen, Alison S Waller, Takuji Yamada, Peer Bork, Arcady R Mushegian, Eugene V Koonin
    Journal of bacteriology 2013:195(5)
    35 Citations (Google Scholar as of 2016-08-16)

    Abstract: Viruses are the most abundant biological entities on earth and encompass a vast amount of genetic diversity. The recent rapid increase in the number of sequenced viral genomes has created unprecedented opportunities for gaining new insight into the structure and evolution of the virosphere. Here, we present an update of the phage orthologous groups (POGs), a collection of 4,542 clusters of orthologous genes from bacteriophages that now also includes viruses infecting archaea and encompasses more than 1,000 distinct virus genomes. Analysis of this expanded data set shows that the number of POGs keeps growing without saturation and that a substantial majority of the POGs remain specific to viruses, lacking homologues in prokaryotic cells, outside known proviruses. Thus, the great majority of virus genes apparently remains to be discovered. A complementary observation is that numerous viral genomes remain poorly, if at all, covered by POGs. The genome coverage by POGs is expected to increase as more genomes are sequenced. Taxon-specific, single-copy signature genes that are not observed in prokaryotic genomes outside detected proviruses were identified for two-thirds of the 57 taxa (those with genomes available from at least 3 distinct viruses), with half of these present in all members of the respective taxon. These signatures can be used to specifically identify the presence and quantify the abundance of viruses from particular taxa in metagenomic samples and thus gain new insights into the ecology and evolution of viruses in relation to their hosts.

  • Updated clusters of orthologous genes for Archaea: a complex ancestor of the Archaea and the byways of horizontal gene transfer. [PMID: 23241446]

    Yuri I Wolf, Kira S Makarova, Natalya Yutin, Eugene V Koonin
    Biology direct 2012:7
    79 Citations (Google Scholar as of 2016-08-16)

    Abstract: Collections of Clusters of Orthologous Genes (COGs) provide indispensable tools for comparative genomic analysis, evolutionary reconstruction and functional annotation of new genomes. Initially, COGs were made for all complete genomes of cellular life forms that were available at the time. However, with the accumulation of thousands of complete genomes, construction of a comprehensive COG set has become extremely computationally demanding and prone to error propagation, necessitating the switch to taxon-specific COG collections. Previously, we reported the collection of COGs for 41 genomes of Archaea (arCOGs). Here we present a major update of the arCOGs and describe evolutionary reconstructions to reveal general trends in the evolution of Archaea. The updated version of the arCOG database incorporates 91% of the pangenome of 120 archaea (251,032 protein-coding genes altogether) into 10,335 arCOGs. Using this new set of arCOGs, we performed maximum likelihood reconstruction of the genome content of archaeal ancestral forms and gene gain and loss events in archaeal evolution. This reconstruction shows that the last Common Ancestor of the extant Archaea was an organism of greater complexity than most of the extant archaea, probably with over 2,500 protein-coding genes. The subsequent evolution of almost all archaeal lineages was apparently dominated by gene loss resulting in genome streamlining. Overall, in the evolution of Archaea as well as a representative set of bacteria that was similarly analyzed for comparison, gene losses are estimated to outnumber gene gains at least 4 to 1. Analysis of specific patterns of gene gain in Archaea shows that, although some groups, in particular Halobacteria, acquire substantially more genes than others, on the whole, gene exchange between major groups of Archaea appears to be largely random, with no major 'highways' of horizontal gene transfer. The updated collection of arCOGs is expected to become a key resource for comparative genomics, evolutionary reconstruction and functional annotation of new archaeal genomes. Given that, in spite of the major increase in the number of genomes, the conserved core of archaeal genes appears to be stabilizing, the major evolutionary trends revealed here have a chance to stand the test of time. This article was reviewed by (for complete reviews see the Reviewers' Reports section): Dr. PLG, Prof. PF, Dr. PL (nominated by Prof. JPG).

  • A tight link between orthologs and bidirectional best hits in bacterial and archaeal genomes. [PMID: 23160176]

    Yuri I Wolf, Eugene V Koonin
    Genome biology and evolution 2012:4(12)
    35 Citations (Google Scholar as of 2016-08-16)

    Abstract: Orthologous relationships between genes are routinely inferred from bidirectional best hits (BBH) in pairwise genome comparisons. However, to our knowledge, it has never been quantitatively demonstrated that orthologs form BBH. To test this "BBH-orthology conjecture," we take advantage of the operon organization of bacterial and archaeal genomes and assume that, when two genes in compared genomes are flanked by two BBH show statistically significant sequence similarity to one another, these genes are bona fide orthologs. Under this assumption, we tested whether middle genes in "syntenic orthologous gene triplets" form BBH. We found that this was the case in more than 95% of the syntenic gene triplets in all genome comparisons. A detailed examination of the exceptions to this pattern, including maximum likelihood phylogenetic tree analysis, showed that some of these deviations involved artifacts of genome annotation, whereas very small fractions represented random assignment of the best hit to one of closely related in-paralogs, paralogous displacement in situ, or even less frequent genuine violations of the BBH-orthology conjecture caused by acceleration of evolution in one of the orthologs. We conclude that, at least in prokaryotes, genes for which independent evidence of orthology is available typically form BBH and, conversely, BBH can serve as a strong indication of gene orthology.

  • Evolutionarily conserved orthologous families in phages are relatively rare in their prokaryotic hosts. [PMID: 21317336]

    David M Kristensen, Xixu Cai, Arcady Mushegian
    Journal of bacteriology 2011:193(8)
    23 Citations (Google Scholar as of 2016-08-16)

    Abstract: We have identified conserved orthologs in completely sequenced genomes of double-strand DNA phages and arranged them into evolutionary families (phage orthologous groups [POGs]). Using this resource to analyze the collection of known phage genomes, we find that most orthologs are unique in their genomes (having no diverged duplicates [paralogs]), and while many proteins contain multiple domains, the evolutionary recombination of these domains does not appear to be a major factor in evolution of these orthologous families. The number of POGs has been rapidly increasing over the past decade, the percentage of genes in phage genomes that have orthologs in other phages has also been increasing, and the percentage of unknown "ORFans" is decreasing as more proteins find homologs and establish a family. Other properties of phage genomes have remained relatively stable over time, most notably the high fraction of genes that are never or only rarely observed in their cellular hosts. This suggests that despite the renowned ability of phages to transduce cellular genes, these cellular "hitchhiker" genes do not dominate the phage genomic landscape, and a large fraction of the genes in phage genomes maintain an evolutionary trajectory that is distinct from that of the host genes.

  • A low-polynomial algorithm for assembling clusters of orthologous groups from intergenomic symmetric best matches. [PMID: 20439257]

    David M Kristensen, Lavanya Kannan, Michael K Coleman, Yuri I Wolf, Alexander Sorokin, Eugene V Koonin, Arcady Mushegian
    Bioinformatics (Oxford, England) 2010:26(12)
    63 Citations (Google Scholar as of 2016-08-16)

    Abstract: Identifying orthologous genes in multiple genomes is a fundamental task in comparative genomics. Construction of intergenomic symmetrical best matches (SymBets) and joining them into clusters is a popular method of ortholog definition, embodied in several software programs. Despite their wide use, the computational complexity of these programs has not been thoroughly examined. In this work, we show that in the standard approach of iteration through all triangles of SymBets, the memory scales with at least the number of these triangles, O(g(3)) (where g = number of genomes), and construction time scales with the iteration through each pair, i.e. O(g(6)). We propose the EdgeSearch algorithm that iterates over edges in the SymBet graph rather than triangles of SymBets, and as a result has a worst-case complexity of only O(g(3)log g). Several optimizations reduce the run-time even further in realistically sparse graphs. In two real-world datasets of genomes from bacteriophages (POGs) and Mollicutes (MOGs), an implementation of the EdgeSearch algorithm runs about an order of magnitude faster than the original algorithm and scales much better with increasing number of genomes, with only minor differences in the final results, and up to 60 times faster than the popular OrthoMCL program with a 90% overlap between the identified groups of orthologs. C++ source code freely available for download at Supplementary materials are available at Bioinformatics online.

  • Eukaryotic large nucleo-cytoplasmic DNA viruses: clusters of orthologous genes and reconstruction of viral genome evolution. [PMID: 20017929]

    Natalya Yutin, Yuri I Wolf, Didier Raoult, Eugene V Koonin
    Virology journal 2009:6
    132 Citations (Google Scholar as of 2016-08-16)

    Abstract: The Nucleo-Cytoplasmic Large DNA Viruses (NCLDV) comprise an apparently monophyletic class of viruses that infect a broad variety of eukaryotic hosts. Recent progress in isolation of new viruses and genome sequencing resulted in a substantial expansion of the NCLDV diversity, resulting in additional opportunities for comparative genomic analysis, and a demand for a comprehensive classification of viral genes. A comprehensive comparison of the protein sequences encoded in the genomes of 45 NCLDV belonging to 6 families was performed in order to delineate cluster of orthologous viral genes. Using previously developed computational methods for orthology identification, 1445 Nucleo-Cytoplasmic Virus Orthologous Groups (NCVOGs) were identified of which 177 are represented in more than one NCLDV family. The NCVOGs were manually curated and annotated and can be used as a computational platform for functional annotation and evolutionary analysis of new NCLDV genomes. A maximum-likelihood reconstruction of the NCLDV evolution yielded a set of 47 conserved genes that were probably present in the genome of the common ancestor of this class of eukaryotic viruses. This reconstructed ancestral gene set is robust to the parameters of the reconstruction procedure and so is likely to accurately reflect the gene core of the ancestral NCLDV, indicating that this virus encoded a complex machinery of replication, expression and morphogenesis that made it relatively independent from host cell functions. The NCVOGs are a flexible and expandable platform for genome analysis and functional annotation of newly characterized NCLDV. Evolutionary reconstructions employing NCVOGs point to complex ancestral viruses.

  • Clusters of orthologous genes for 41 archaeal genomes and implications for evolutionary genomics of archaea. [PMID: 18042280]

    Kira S Makarova, Alexander V Sorokin, Pavel S Novichkov, Yuri I Wolf, Eugene V Koonin
    Biology direct 2007:2
    139 Citations (Google Scholar as of 2016-08-16)

    Abstract: An evolutionary classification of genes from sequenced genomes that distinguishes between orthologs and paralogs is indispensable for genome annotation and evolutionary reconstruction. Shortly after multiple genome sequences of bacteria, archaea, and unicellular eukaryotes became available, an attempt on such a classification was implemented in Clusters of Orthologous Groups of proteins (COGs). Rapid accumulation of genome sequences creates opportunities for refining COGs but also represents a challenge because of error amplification. One of the practical strategies involves construction of refined COGs for phylogenetically compact subsets of genomes. New Archaeal Clusters of Orthologous Genes (arCOGs) were constructed for 41 archaeal genomes (13 Crenarchaeota, 27 Euryarchaeota and one Nanoarchaeon) using an improved procedure that employs a similarity tree between smaller, group-specific clusters, semi-automatically partitions orthology domains in multidomain proteins, and uses profile searches for identification of remote orthologs. The annotation of arCOGs is a consensus between three assignments based on the COGs, the CDD database, and the annotations of homologs in the NR database. The 7538 arCOGs, on average, cover approximately 88% of the genes in a genome compared to a approximately 76% coverage in COGs. The finer granularity of ortholog identification in the arCOGs is apparent from the fact that 4538 arCOGs correspond to 2362 COGs; approximately 40% of the arCOGs are new. The archaeal gene core (protein-coding genes found in all 41 genome) consists of 166 arCOGs. The arCOGs were used to reconstruct gene loss and gene gain events during archaeal evolution and gene sets of ancestral forms. The Last Archaeal Common Ancestor (LACA) is conservatively estimated to possess 996 genes compared to 1245 and 1335 genes for the last common ancestors of Crenarchaeota and Euryarchaeota, respectively. It is inferred that LACA was a chemoautotrophic hyperthermophile that, in addition to the core archaeal functions, encoded more idiosyncratic systems, e.g., the CASS systems of antivirus defense and some toxin-antitoxin systems. The arCOGs provide a convenient, flexible framework for functional annotation of archaeal genomes, comparative genomics and evolutionary reconstructions. Genomic reconstructions suggest that the last common ancestor of archaea might have been (nearly) as advanced as the modern archaeal hyperthermophiles. ArCOGs and related information are available at:

  • Comparative genomics of the lactic acid bacteria. [PMID: 17030793]

    K Makarova, A Slesarev, Y Wolf, A Sorokin, B Mirkin, E Koonin, A Pavlov, N Pavlova, V Karamychev, N Polouchine, V Shakhova, I Grigoriev, Y Lou, D Rohksar, S Lucas, K Huang, D M Goodstein, T Hawkins, V Plengvidhya, D Welker, J Hughes, Y Goh, A Benson, K Baldwin, J-H Lee, I Díaz-Muñiz, B Dosti, V Smeianov, W Wechter, R Barabote, G Lorca, E Altermann, R Barrangou, B Ganesan, Y Xie, H Rawsthorne, D Tamir, C Parker, F Breidt, J Broadbent, R Hutkins, D O'Sullivan, J Steele, G Unlu, M Saier, T Klaenhammer, P Richardson, S Kozyavkin, B Weimer, D Mills
    Proceedings of the National Academy of Sciences of the United States of America 2006:103(42)
    880 Citations (Google Scholar as of 2016-08-16)

    Abstract: Lactic acid-producing bacteria are associated with various plant and animal niches and play a key role in the production of fermented foods and beverages. We report nine genome sequences representing the phylogenetic and functional diversity of these bacteria. The small genomes of lactic acid bacteria encode a broad repertoire of transporters for efficient carbon and nitrogen acquisition from the nutritionally rich environments they inhabit and reflect a limited range of biosynthetic capabilities that indicate both prototrophic and auxotrophic strains. Phylogenetic analyses, comparison of gene content across the group, and reconstruction of ancestral gene sets indicate a combination of extensive gene loss and key gene acquisitions via horizontal gene transfer during the coevolution of lactic acid bacteria with their habitats.

  • The cyanobacterial genome core and the origin of photosynthesis. [PMID: 16924101]

    Armen Y Mulkidjanian, Eugene V Koonin, Kira S Makarova, Sergey L Mekhedov, Alexander Sorokin, Yuri I Wolf, Alexis Dufresne, Frédéric Partensky, Henry Burd, Denis Kaznadzey, Robert Haselkorn, Michael Y Galperin
    Proceedings of the National Academy of Sciences of the United States of America 2006:103(35)
    188 Citations (Google Scholar as of 2016-08-16)

    Abstract: Comparative analysis of 15 complete cyanobacterial genome sequences, including "near minimal" genomes of five strains of Prochlorococcus spp., revealed 1,054 protein families [core cyanobacterial clusters of orthologous groups of proteins (core CyOGs)] encoded in at least 14 of them. The majority of the core CyOGs are involved in central cellular functions that are shared with other bacteria; 50 core CyOGs are specific for cyanobacteria, whereas 84 are exclusively shared by cyanobacteria and plants and/or other plastid-carrying eukaryotes, such as diatoms or apicomplexans. The latter group includes 35 families of uncharacterized proteins, which could also be involved in photosynthesis. Only a few components of cyanobacterial photosynthetic machinery are represented in the genomes of the anoxygenic phototrophic bacteria Chlorobium tepidum, Rhodopseudomonas palustris, Chloroflexus aurantiacus, or Heliobacillus mobilis. These observations, coupled with recent geological data on the properties of the ancient phototrophs, suggest that photosynthesis originated in the cyanobacterial lineage under the selective pressures of UV light and depletion of electron donors. We propose that the first phototrophs were anaerobic ancestors of cyanobacteria ("procyanobacteria") that conducted anoxygenic photosynthesis using a photosystem I-like reaction center, somewhat similar to the heterocysts of modern filamentous cyanobacteria. From procyanobacteria, photosynthesis spread to other phyla by way of lateral gene transfer.

  • A comprehensive evolutionary classification of proteins encoded in complete eukaryotic genomes. [PMID: 14759257]

    Eugene V Koonin, Natalie D Fedorova, John D Jackson, Aviva R Jacobs, Dmitri M Krylov, Kira S Makarova, Raja Mazumder, Sergei L Mekhedov, Anastasia N Nikolskaya, B Sridhar Rao, Igor B Rogozin, Sergei Smirnov, Alexander V Sorokin, Alexander V Sverdlov, Sona Vasudevan, Yuri I Wolf, Jodie J Yin, Darren A Natale
    Genome biology 2004:5(2)
    344 Citations (Google Scholar as of 2016-08-16)

    Abstract: Sequencing the genomes of multiple, taxonomically diverse eukaryotes enables in-depth comparative-genomic analysis which is expected to help in reconstructing ancestral eukaryotic genomes and major events in eukaryotic evolution and in making functional predictions for currently uncharacterized conserved genes. We examined functional and evolutionary patterns in the recently constructed set of 5,873 clusters of predicted orthologs (eukaryotic orthologous groups or KOGs) from seven eukaryotic genomes: Caenorhabditis elegans, Drosophila melanogaster, Homo sapiens, Arabidopsis thaliana, Saccharomyces cerevisiae, Schizosaccharomyces pombe and Encephalitozoon cuniculi. Conservation of KOGs through the phyletic range of eukaryotes strongly correlates with their functions and with the effect of gene knockout on the organism's viability. The approximately 40% of KOGs that are represented in six or seven species are enriched in proteins responsible for housekeeping functions, particularly translation and RNA processing. These conserved KOGs are often essential for survival and might approximate the minimal set of essential eukaryotic genes. The 131 single-member, pan-eukaryotic KOGs we identified were examined in detail. For around 20 that remained uncharacterized, functions were predicted by in-depth sequence analysis and examination of genomic context. Nearly all these proteins are subunits of known or predicted multiprotein complexes, in agreement with the balance hypothesis of evolution of gene copy number. Other KOGs show a variety of phyletic patterns, which points to major contributions of lineage-specific gene loss and the 'invention' of genes new to eukaryotic evolution. Examination of the sets of KOGs lost in individual lineages reveals co-elimination of functionally connected genes. Parsimonious scenarios of eukaryotic genome evolution and gene sets for ancestral eukaryotic forms were reconstructed. The gene set of the last common ancestor of the crown group consists of 3,413 KOGs and largely includes proteins involved in genome replication and expression, and central metabolism. Only 44% of the KOGs, mostly from the reconstructed gene set of the last common ancestor of the crown group, have detectable homologs in prokaryotes; the remainder apparently evolved via duplication with divergence and invention of new genes. The KOG analysis reveals a conserved core of largely essential eukaryotic genes as well as major diversification and innovation associated with evolution of eukaryotic genomes. The results provide quantitative support for major trends of eukaryotic evolution noticed previously at the qualitative level and a basis for detailed reconstruction of evolution of eukaryotic genomes and biology of ancestral forms.

  • The COG database: an updated version includes eukaryotes. [PMID: 12969510]

    Roman L Tatusov, Natalie D Fedorova, John D Jackson, Aviva R Jacobs, Boris Kiryutin, Eugene V Koonin, Dmitri M Krylov, Raja Mazumder, Sergei L Mekhedov, Anastasia N Nikolskaya, B Sridhar Rao, Sergei Smirnov, Alexander V Sverdlov, Sona Vasudevan, Yuri I Wolf, Jodie J Yin, Darren A Natale
    BMC bioinformatics 2003:4
    2861 Citations (Google Scholar as of 2016-05-03)

    Abstract: 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 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. 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 COG database: new developments in phylogenetic classification of proteins from complete genomes. [PMID: 11125040]

    R L Tatusov, D A Natale, I V Garkavtsev, T A Tatusova, U T Shankavaram, B S Rao, B Kiryutin, M Y Galperin, N D Fedorova, E V Koonin
    Nucleic acids research 2001:29(1)
    1596 Citations (Google Scholar as of 2016-05-08)

    Abstract: The database of Clusters of Orthologous Groups of proteins (COGs), which represents an attempt on a phylogenetic classification of the proteins encoded in complete genomes, currently consists of 2791 COGs including 45 350 proteins from 30 genomes of bacteria, archaea and the yeast Saccharomyces cerevisiae (http://www.ncbi.nlm.nih. gov/COG). In addition, a supplement to the COGs is available, in which proteins encoded in the genomes of two multicellular eukaryotes, the nematode Caenorhabditis elegans and the fruit fly Drosophila melanogaster, and shared with bacteria and/or archaea were included. The new features added to the COG database include information pages with structural and functional details on each COG and literature references, improvements of the COGNITOR program that is used to fit new proteins into the COGs, and classification of genomes and COGs constructed by using principal component analysis.

  • The COG database: a tool for genome-scale analysis of protein functions and evolution. [PMID: 10592175]

    R L Tatusov, M Y Galperin, D A Natale, E V Koonin
    Nucleic acids research 2000:28(1)
    1748 Citations (Google Scholar as of 2016-05-08)

    Abstract: Rational classification of proteins encoded in sequenced genomes is critical for making the genome sequences maximally useful for functional and evolutionary studies. The database of Clusters of Orthologous Groups of proteins (COGs) is an attempt on a phylogenetic classification of the proteins encoded in 21 complete genomes of bacteria, archaea and eukaryotes (http://www. ncbi.nlm. The COGs were constructed by applying the criterion of consistency of genome-specific best hits to the results of an exhaustive comparison of all protein sequences from these genomes. The database comprises 2091 COGs that include 56-83% of the gene products from each of the complete bacterial and archaeal genomes and approximately 35% of those from the yeast Saccharomyces cerevisiae genome. The COG database is accompanied by the COGNITOR program that is used to fit new proteins into the COGs and can be applied to functional and phylogenetic annotation of newly sequenced genomes.

  • A genomic perspective on protein families. [PMID: 9381173]

    R L Tatusov, E V Koonin, D J Lipman
    Science (New York, N.Y.) 1997:278(5338)
    2928 Citations (Google Scholar as of 2016-08-16)

    Abstract: In order to extract the maximum amount of information from the rapidly accumulating genome sequences, all conserved genes need to be classified according to their homologous relationships. Comparison of proteins encoded in seven complete genomes from five major phylogenetic lineages and elucidation of consistent patterns of sequence similarities allowed the delineation of 720 clusters of orthologous groups (COGs). Each COG consists of individual orthologous proteins or orthologous sets of paralogs from at least three lineages. Orthologs typically have the same function, allowing transfer of functional information from one member to an entire COG. This relation automatically yields a number of functional predictions for poorly characterized genomes. The COGs comprise a framework for functional and evolutionary genome analysis.

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-1 Failed2018-08-10
-1 Failed2018-08-07
-1 Failed2018-08-03
-1 Failed2018-07-31
-1 Failed2018-07-27
-1 Failed2018-07-24
-1 Failed2018-07-20
-1 Failed2018-07-17
-1 Failed2018-07-13
-1 Failed2018-07-10
-1 Failed2018-07-06
-1 Failed2018-07-03
-1 Failed2018-06-29
-1 Failed2018-06-26
-1 Failed2018-06-22
-1 Failed2018-06-19
-1 Failed2018-06-15
-1 Failed2018-06-12
-1 Failed2018-06-08
-1 Failed2018-06-05
-1 Failed2018-06-01
-1 Failed2018-05-29
-1 Failed2018-05-25
-1 Failed2018-05-22
-1 Failed2018-05-18
-1 Failed2018-05-15
-1 Failed2018-05-11
-1 Failed2018-05-08
-1 Failed2018-05-04
-1 Failed2018-05-01
-1 Failed2018-04-27
-1 Failed2018-04-24
-1 Failed2018-04-20
-1 Failed2018-04-17
-1 Failed2018-04-13
-1 Failed2018-04-10
-1 Failed2018-04-06
-1 Failed2018-04-03
-1 Failed2018-02-27
-1 Failed2018-02-23
-1 Failed2018-02-20
-1 Failed2018-02-16
-1 Failed2018-02-13
-1 Failed2018-02-09
-1 Failed2018-02-06
-1 Failed2018-02-02
-1 Failed2018-01-30
-1 Failed2018-01-26
-1 Failed2018-01-23
-1 Failed2018-01-19
-1 Failed2018-01-16
-1 Failed2018-01-12
-1 Failed2018-01-09
-1 Failed2018-01-05
-1 Failed2018-01-02
-1 Failed2017-12-29
-1 Failed2017-12-26
-1 Failed2017-12-22
-1 Failed2017-12-19
-1 Failed2017-12-15
-1 Failed2017-12-12
-1 Failed2017-12-08
-1 Failed2017-12-05
-1 Failed2017-12-01
-1 Failed2017-11-28
-1 Failed2017-11-24
-1 Failed2017-11-21
-1 Failed2017-11-17
-1 Failed2017-11-14
-1 Failed2017-11-10
-1 Failed2017-11-07
-1 Failed2017-11-03
-1 Failed2017-10-31
-1 Failed2017-10-27
-1 Failed2017-10-24
-1 Failed2017-10-20
-1 Failed2017-10-17
-1 Failed2017-10-13
-1 Failed2017-10-10
-1 Failed2017-10-06
-1 Failed2017-10-03
-1 Failed2017-09-29
-1 Failed2017-09-26
-1 Failed2017-09-22
-1 Failed2017-09-19
-1 Failed2017-09-15
-1 Failed2017-09-12
-1 Failed2017-09-08
-1 Failed2017-09-05
-1 Failed2017-09-01
-1 Failed2017-08-29
-1 Failed2017-08-25
-1 Failed2017-08-22
-1 Failed2017-08-18
-1 Failed2017-08-15
-1 Failed2017-08-11
-1 Failed2017-08-08
-1 Failed2017-08-04
-1 Failed2017-08-01
-1 Failed2017-07-28
-1 Failed2017-07-25
-1 Failed2017-07-21
-1 Failed2017-07-18
-1 Failed2017-07-14
-1 Failed2017-07-04
-1 Failed2017-06-30
-1 Failed2017-06-27
-1 Failed2017-06-23
-1 Failed2017-06-20
-1 Failed2017-06-16
-1 Failed2017-06-13
-1 Failed2017-06-09
-1 Failed2017-06-06
-1 Failed2017-06-02
-1 Failed2017-05-30
-1 Failed2017-05-26
-1 Failed2017-05-23
-1 Failed2017-05-19
-1 Failed2017-05-16
-1 Failed2017-05-12
-1 Failed2017-05-09
-1 Failed2017-05-05
-1 Failed2017-05-02
-1 Failed2017-04-28
-1 Failed2017-04-25
-1 Failed2017-04-21
-1 Failed2017-04-18
-1 Failed2017-04-14
-1 Failed2017-04-11
-1 Failed2017-04-07
-1 Failed2017-04-04
-1 Failed2017-03-31
-1 Failed2017-03-28
-1 Failed2017-03-24
-1 Failed2017-03-21
-1 Failed2017-03-17
-1 Failed2017-03-14
-1 Failed2017-03-10
-1 Failed2017-03-07
-1 Failed2017-03-03
-1 Failed2017-02-28
-1 Failed2017-02-24
-1 Failed2017-02-21
-1 Failed2017-02-17
-1 Failed2017-02-14
-1 Failed2017-02-10
-1 Failed2017-02-07
-1 Failed2017-02-03
-1 Failed2017-01-31
-1 Failed2017-01-27
-1 Failed2017-01-24
-1 Failed2017-01-20
-1 Failed2017-01-17
-1 Failed2017-01-13
-1 Failed2017-01-10
-1 Failed2017-01-06
-1 Failed2017-01-03
-1 Failed2016-12-30
-1 Failed2016-12-27
-1 Failed2016-12-23
-1 Failed2016-12-20
-1 Failed2016-12-16
-1 Failed2016-12-13
-1 Failed2016-12-09
-1 Failed2016-12-06
-1 Failed2016-12-02
-1 Failed2016-11-29
-1 Failed2016-11-25
-1 Failed2016-11-22
-1 Failed2016-11-18
-1 Failed2016-11-15
-1 Failed2016-11-11
-1 Failed2016-11-08
200 OK2016-11-04
200 OK2016-11-01
200 OK2016-10-28
200 OK2016-10-25
200 OK2016-10-21
200 OK2016-10-18
200 OK2016-10-14
200 OK2016-10-11
200 OK2016-10-07
200 OK2016-10-04
200 OK2016-09-30
200 OK2016-09-27
200 OK2016-09-23
200 OK2016-09-20
200 OK2016-09-16
200 OK2016-09-13
200 OK2016-09-09
200 OK2016-09-06
200 OK2016-09-02
200 OK2016-08-30
200 OK2016-08-26
200 OK2016-08-23
200 OK2016-08-19
200 OK2016-08-16
200 OK2016-08-12
200 OK2016-08-09
200 OK2016-08-05
200 OK2016-08-02
200 OK2016-07-29
200 OK2016-07-26
200 OK2016-07-22
200 OK2016-07-19
200 OK2016-07-15
200 OK2016-07-12
200 OK2016-07-08
200 OK2016-07-05
200 OK2016-07-01
200 OK2016-06-28
200 OK2016-06-24
200 OK2016-06-21
200 OK2016-06-17
200 OK2016-06-14
200 OK2016-06-10
200 OK2016-06-07
200 OK2016-06-03
200 OK2016-05-31
200 OK2016-05-27
200 OK2016-05-24
200 OK2016-05-20
200 OK2016-05-17
200 OK2016-05-13
200 OK2016-05-10
200 OK2016-05-06
200 OK2016-05-03
200 OK2016-04-29
200 OK2016-04-26
200 OK2016-04-22
200 OK2016-04-19
200 OK2016-04-15
200 OK2016-04-12
200 OK2016-04-08
200 OK2016-04-05
200 OK2016-04-01
200 OK2016-03-29
200 OK2016-03-28
200 OK2016-03-25
200 OK2016-03-23
200 OK2016-03-21
200 OK2016-03-18
200 OK2016-03-16
200 OK2016-03-14
200 OK2016-03-11
200 OK2016-03-09
200 OK2016-03-07
200 OK2016-03-04
200 OK2016-03-02
200 OK2016-02-29
200 OK2016-02-26
200 OK2016-02-24
200 OK2016-02-22
200 OK2016-02-19
200 OK2016-02-17
200 OK2016-02-15
200 OK2016-02-14
200 OK2016-02-12
200 OK2016-02-10
200 OK2016-02-08
200 OK2016-02-07
200 OK2016-02-05
200 OK2016-02-03
200 OK2016-02-01
200 OK2016-01-31
200 OK2016-01-29
200 OK2016-01-27
200 OK2016-01-25
200 OK2016-01-24
200 OK2016-01-22
200 OK2016-01-20
200 OK2016-01-18
200 OK2016-01-17
200 OK2016-01-15
200 OK2016-01-13
200 OK2016-01-11
200 OK2016-01-10
200 OK2016-01-08
200 OK2016-01-06
200 OK2016-01-04


Protein Standard, Ontology and Nomenclature
Archaea Bacteria Eukaryota Virus
gene orthology

Record metadata

  • Created on: 2015-06-20
  • Curated by:
    • Lina Ma [2016-08-16]
    • Mengwei Li [2016-04-12]
    • Mengwei Li [2016-03-31]
    • Zhang Zhang [2015-12-13]
    • Mengwei Li [2015-12-03]
    • Lina Ma [2015-11-18]
    • Lina Ma [2015-11-17]
    • Mengwei Li [2015-06-27]