The COG database: a tool for genome-scale analysis of protein functions and evolution

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. nih.gov/COG). 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.     

The COG database: new developments in phylogenetic classification of proteins from complete genomes

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.     

EPPS: mining the COG database by an extended phylogenetic patterns search

SUMMARY: EPPS runs under Microsoft Windows. It is an extended version of the phylogenetic patterns search (PPS). The output condition of PPS is the exact match of a user defined phylogenetic pattern with the pattern represented by the respective cluster of orthologous groups (COG). In contrast, the software described here is less restrictive. The user may define the accuracy of the search by the number of genomes that are allowed not to match the predefined phylogenetic pattern. Thus, EPPS has the advantage to detect COGs even if organisms defined to be included are not or organisms defined to be excluded are present in the output COGs.     

A Novel Bioinformatics Strategy for Function Prediction of Poorly-Characterized Protein Genes Obtained from Metagenome Analyses

As a result of remarkable progresses of DNA sequencing technology, vast quantities of genomic sequences have been decoded. Homology search for amino acid sequences, such as BLAST, has become a basic tool for assigning functions of genes/proteins when genomic sequences are decoded. Although the homology search has clearly been a powerful and irreplaceable method, the functions of only 50% or fewer of genes can be predicted when a novel genome is decoded. A prediction method independent of the homology search is urgently needed. By analyzing oligonucleotide compositions in genomic sequences, we previously developed a modified Self-Organizing Map ‘BLSOM’ that clustered genomic fragments according to phylotype with no advance knowledge of phylotype. Using BLSOM for di-, tri- and tetrapeptide compositions, we developed a system to enable separation (self-organization) of proteins by function. Analyzing oligopeptide frequencies in proteins previously classified into COGs (clusters of orthologous groups of proteins), BLSOMs could faithfully reproduce the COG classifications. This indicated that proteins, whose functions are unknown because of lack of significant sequence similarity with function-known proteins, can be related to function-known proteins based on similarity in oligopeptide composition. BLSOM was applied to predict functions of vast quantities of proteins derived from mixed genomes in environmental samples.     

Comparative genomic analysis by microbial COGs self-attraction rate

Whole genome analysis provides new perspectives to determine phylogenetic relationships among microorganisms. The availability of whole nucleotide sequences allows different levels of comparison among genomes by several approaches. In this work, self-attraction rates were considered for each cluster of orthologous groups of proteins (COGs) class in order to analyse gene aggregation levels in physical maps. Phylogenetic relationships among microorganisms were obtained by comparing self-attraction coefficients. Eighteen-dimensional vectors were computed for a set of 168 completely sequenced microbial genomes (19 archea, 149 bacteria). The components of the vector represent the aggregation rate of the genes belonging to each of 18 COGs classes. Genes involved in nonessential functions or related to environmental conditions showed the highest aggregation rates. On the contrary genes involved in basic cellular tasks showed a more uniform distribution along the genome, except for translation genes. Self-attraction clustering approach allowed classification of Proteobacteria, Bacilli and other species belonging to Firmicutes. Rearrangement and Lateral Gene Transfer events may influence divergences from classical taxonomy. Each set of COG classes’ aggregation values represents an intrinsic property of the microbial genome. This novel approach provides a new point of view for whole genome analysis and bacterial characterization.     

An Integrated Sequence-Structure Database incorporating matching mRNA sequence, amino acid sequence and protein three-dimensional structure data.

We have constructed a non-homologous database, termed the Integrated Sequence-Structure Database (ISSD) which comprises the coding sequences of genes, amino acid sequences of the corresponding proteins, their secondary structure and straight phi,psi angles assignments, and polypeptide backbone coordinates. Each protein entry in the database holds the alignment of nucleotide sequence, amino acid sequence and the PDB three-dimensional structure data. The nucleotide and amino acid sequences for each entry are selected on the basis of exact matches of the source organism and cell environment. The current version 1.0 of ISSD is available on the WWW at http://www.protein.bio.msu.su/issd/ and includes 107 non-homologous mammalian proteins, of which 80 are human proteins. The database has been used by us for the analysis of synonymous codon usage patterns in mRNA sequences showing their correlation with the three-dimensional structure features in the encoded proteins. Possible ISSD applications include optimisation of protein expression, improvement of the protein structure prediction accuracy, and analysis of evolutionary aspects of the nucleotide sequence-protein structure relationship.     

Using the COG Database to Improve Gene Recognition in Complete Genomes

A complete understanding of the biology of an organism necessarily starts with knowledge of its genetic makeup. Proteins encoded in a genome must be identified and characterized, and the presence or absence of specific sets of proteins must be noted in order to determine the possible biochemical pathways or functional systems utilized by that organism. The COG database presents a set of tools suited to these purposes, including the ability to select protein families (COGs) that contain proteins from a specified set of species. The selection is based upon a phylogenetic pattern, which is a shorthand representation of the presence or absence of a particular species in a COG. Here we present the use of phylogenetic patterns as a means to perform targeted searches for undetected protein-coding genes in complete genomes.     

Detecting non-orthology in the COGs database and other approaches grouping orthologs using genome-specific best hits

Correct orthology assignment is a critical prerequisite of numerous comparative genomics procedures, such as function prediction, construction of phylogenetic species trees and genome rearrangement analysis. We present an algorithm for the detection of non-orthologs that arise by mistake in current orthology classification methods based on genome-specific best hits, such as the COGs database. The algorithm works with pairwise distance estimates, rather than computationally expensive and error-prone tree-building methods. The accuracy of the algorithm is evaluated through verification of the distribution of predicted cases, case-by-case phylogenetic analysis and comparisons with predictions from other projects using independent methods. Our results show that a very significant fraction of the COG groups include non-orthologs: using conservative parameters, the algorithm detects non-orthology in a third of all COG groups. Consequently, sequence analysis sensitive to correct orthology assignments will greatly benefit from these findings.     

Model of amino acid substitution in proteins encoded by mitochondrial DNA

Mitochondrial DNA (mtDNA) sequences are widely used for inferring the phylogenetic relationships among species. Clearly, the assumed model of nucleotide or amino acid substitution used should be as realistic as possible. Dependence among neighboring nucleotides in a codon complicates modeling of nucleotide substitutions in protein-encoding genes. It seems preferable to model amino acid substitution rather than nucleotide substitution. Therefore, we present a transition probability matrix of the general reversible Markov model of amino acid substitution for mtDNA-encoded proteins. The matrix is estimated by the maximum likelihood (ML) method from the complete sequence data of mtDNA from 20 vertebrate species. This matrix represents the substitution pattern of the mtDNA-encoded proteins and shows some differences from the matrix estimated from the nuclear-encoded proteins. The use of this matrix would be recommended in inferring trees from mtDNA-encoded protein sequences by the ML method. Received: 3 May 1995 / Accepted: 31 October 1995     

Neighboring-site effects of amino acid mutation

Although the context dependence of nucleotide mutation has been supported by accumulating theoretical and experimental evidence, whether this effect can be extended to amino acid mutation remains obscure. As the amino acid doublets (20 x 20) are much more diverse than their nucleotide counterparts (4 x 4), any attempt to address the neighboring-site effects of amino acid mutation was frustrated by deficient amino acid mutation data. Based on the recently revealed 599,745 mutation sites in 45,137 orthologous proteins, we provide solid evidence for the first time to support the existence of neighboring-site effects in amino acid mutation, which is significantly important to improving the prevalent protein-evolution models.     

Advantages of a mechanistic codon substitution model for evolutionary analysis of protein-coding sequences

BACKGROUND: A mechanistic codon substitution model, in which each codon substitution rate is proportional to the product of a codon mutation rate and the average fixation probability depending on the type of amino acid replacement, has advantages over nucleotide, amino acid, and empirical codon substitution models in evolutionary analysis of protein-coding sequences. It can approximate a wide range of codon substitution processes. If no selection pressure on amino acids is taken into account, it will become equivalent to a nucleotide substitution model. If mutation rates are assumed not to depend on the codon type, then it will become essentially equivalent to an amino acid substitution model. Mutation at the nucleotide level and selection at the amino acid level can be separately evaluated. RESULTS: The present scheme for single nucleotide mutations is equivalent to the general time-reversible model, but multiple nucleotide changes in infinitesimal time are allowed. Selective constraints on the respective types of amino acid replacements are tailored to each gene in a linear function of a given estimate of selective constraints. Their good estimates are those calculated by maximizing the respective likelihoods of empirical amino acid or codon substitution frequency matrices. Akaike and Bayesian information criteria indicate that the present model performs far better than the other substitution models for all five phylogenetic trees of highly-divergent to highly-homologous sequences of chloroplast, mitochondrial, and nuclear genes. It is also shown that multiple nucleotide changes in infinitesimal time are significant in long branches, although they may be caused by compensatory substitutions or other mechanisms. The variation of selective constraint over sites fits the datasets significantly better than variable mutation rates, except for 10 slow-evolving nuclear genes of 10 mammals. An critical finding for phylogenetic analysis is that assuming variable mutation rates over sites lead to the overestimation of branch lengths.     

PCOGR: Phylogenetic COG ranking as an online tool to judge the specificity of COGs with respect to freely definable groups of organisms

Background  

The rapidly increasing number of completely sequenced genomes led to the establishment of the COG-database which, based on sequence homologies, assigns similar proteins from different organisms to clusters of orthologous groups (COGs). There are several bioinformatic studies that made use of this database to determine (hyper)thermophile-specific proteins by searching for COGs containing (almost) exclusively proteins from (hyper)thermophilic genomes. However, public software to perform individually definable group-specific searches is not available.     

In vitro and in silico cloning of Xenopus laevis SOD2 cDNA and its phylogenetic analysis

By using the methodology of both wet and dry biology (i.e., RT-PCR and cycle sequencing, and biocomputational technology, respectively) and the data obtained through the Genome Projects, we have cloned Xenopus laevis SOD2 (MnSOD) cDNA and determined its nucleotide sequence. These data and the deduced protein primary structure were compared with all the other SOD2 nucleotide and amino acid sequences from eukaryotes and prokaryotes, published in public databases. The analysis was performed by using both Clustal W, a well known and widely used program for sequence analysis, and AntiClustAl, a new algorithm recently created and implemented by our group. Our results demonstrate a very high conservation of the enzyme amino acid sequence during evolution, which proves a close structure-function relationship. This is to be expected for very ancient molecules endowed with critical biological functions, performed through a specific structural organization. The nucleotide sequence conservation is less pronounced: this too was foreseeable, due to neutral mutations and to the species-specific codon usage. The data obtained by using AntiClustAl are comparable with those produced with Clustal W, which validates this algorithm as an important new tool for biocomputational analysis. Finally, it is noteworthy that evolutionary trees, drawn by using all the available data on SOD2 nucleotide sequences and amino acid and either Clustal W or AntiClustAl, are comparable to those obtained through phylogenetic analysis based on fossil records.     

A Collection of Amino Acid Replacement Matrices Derived from Clusters of Orthologs

Sequence divergence among orthologous proteins was characterized with 34 amino acid replacement matrices, sequence context analysis, and a phylogenetic tree. The model was trained on very large datasets of aligned protein sequences drawn from 15 organisms including protists, plants, Dictyostelium, fungi, and animals. Comparative tests with models currently used in phylogeny, i.e., with JTT+Γ±F and WAG+Γ±F, made on a test dataset of 380 multiple alignments containing protein sequences from all five of the major taxonomic groups mentioned, indicate that our model should be preferred over the JTT+Γ±F and WAG+Γ±F models on datasets similar to the test dataset. The strong performance of our model of orthologous protein sequence divergence can be attributed to its ability to better approximate amino acid equilibrium frequencies to compositions found in alignment columns. Electronic Supplementary Material Electronic Supplementary material is available for this article at and accessible for authorised users. [Reviewing Editor : Dr. Martin Kreitman]     

ON COMBINING PROTEIN SEQUENCES AND NUCLEIC ACID SEQUENCES IN PHYLOGENETIC ANALYSIS: THE HOMEOBOX PROTEIN CASE

Abstract— Amino acid encoding genes contain character state information that may be useful for phylogenetic analysis on at least two levels. The nucleotide sequence and the translated amino acid sequences have both been employed separately as character states for cladistic studies of various taxa, including studies of the genealogy of genes in multigene families. In essence, amino acid sequences and nucleic acid sequences are two different ways of character coding the information in a gene. Silent positions in the nucleotide sequence (first or third positions in codons that can accrue change without changing the identity of the amino acid that the triplet codes for) may accrue change relatively rapidly and become saturated, losing the pattern of historical divergence. On the other hand, non-silent nucleotide alterations and their accompanying amino acid changes may evolve too slowly to reveal relationships among closely related taxa. In general, the dynamics of sequence change in silent and non-silent positions in protein coding genes result in homoplasy and lack of resolution, respectively. We suggest that the combination of nucleic acid and the translated amino acid coded character states into the same data matrix for phylogenetic analysis addresses some of the problems caused by the rapid change of silent nucleotide positions and overall slow rate of change of non-silent nucleotide positions and slowly changing amino acid positions. One major theoretical problem with this approach is the apparent non-independence of the two sources of characters. However, there are at least three possible outcomes when comparing protein coding nucleic acid sequences with their translated amino acids in a phylogenetic context on a codon by codon basis. First, the two character sets for a codon may be entirely congruent with respect to the information they convey about the relationships of a certain set of taxa. Second, one character set may display no information concerning a phylogenetic hypothesis while the other character set may impart information to a hypothesis. These two possibilities are cases of non-independence, however, we argue that congruence in such cases can be thought of as increasing the weight of the particular phylogenetic hypothesis that is supported by those characters. In the third case, the two sources of character information for a particular codon may be entirely incongruent with respect to phylogenetic hypotheses concerning the taxa examined. In this last case the two character sets are independent in that information from neither can predict the character states of the other. Examples of these possibilities are discussed and the general applicability of combining these two sources of information for protein coding genes is presented using sequences from the homeobox region of 46 homeobox genes fromDrosophila melanogasterto develop a hypothesis of genealogical relationship of these genes in this large multigene family.     

Phylogenomic and functional analysis of pterin-4a-carbinolamine dehydratase family (COG2154) proteins in plants and microorganisms

Pterin-4a-carbinolamine dehydratases (PCDs) recycle oxidized pterin cofactors generated by aromatic amino acid hydroxylases (AAHs). PCDs are known biochemically only from animals and one bacterium, but PCD-like proteins (COG2154 in the Clusters of Orthologous Groups [COGs] database) are encoded by many plant and microbial genomes. Because these genomes often encode no AAH homologs, the annotation of their COG2154 proteins as PCDs is questionable. Moreover, some COG2154 proteins lack canonical residues that are catalytically important in mammalian PCDs. Diverse COG2154 proteins of plant, fungal, protistan, and prokaryotic origin were therefore tested for PCD activity by functional complementation in Escherichia coli, and the plant proteins were localized using green fluorescent protein fusions. Higher and lower plants proved to have two COG2154 proteins, a mitochondrial one with PCD activity and a noncanonical, plastidial one without. Phylogenetic analysis indicated that the latter is unique to plants and arose from the former early in the plant lineage. All 10 microbial COG2154 proteins tested had PCD activity; six of these came from genomes with no AAH, and six were noncanonical. The results suggested the motif [EDKH]-x(3)-H-[HN]-[PCS]-x(5,6)-[YWF]-x(9)-[HW]-x(8,15)-D as a signature for PCD activity. Organisms having a functional PCD but no AAH partner include angiosperms, yeast, and various prokaryotes. In these cases, PCD presumably has another function. An ancillary role in molybdopterin cofactor metabolism, hypothesized from phylogenomic evidence, was supported by demonstrating significantly lowered activities of two molybdoenzymes in Arabidopsis thaliana PCD knockout mutants. Besides this role, we propose that partnerless PCDs support the function of as yet unrecognized pterin-dependent enzymes.     

Genome-wide comparative analysis of simple sequence coding repeats among 25 insect species

We present a detailed genome-scale comparative analysis of simple sequence repeats within protein coding regions among 25 insect genomes. The repetitive sequences in the coding regions primarily represented single codon repeats and codon pair repeats. The CAG triplet is highly repetitive in the coding regions of insect genomes. It is frequently paired with the synonymous codon CAA to code for polyglutamine repeats. The codon pairs that are least repetitive code for polyalanine repeats. The frequency of hexanucleotide and dinucleotide motifs of codon pair repeats is significantly (p<0.001) different in the Drosophila species compared to the non-Drosophila species. However, the frequency of synonymous and non-synonymous codon pair repeats varies in a correlated manner (r(2)=0.79) among all the species. Results further show that perfect and imperfect repeats have significant association with the trinucleotide and hexanucleotide coding repeats in most of these insects. However, only select species show significant association between the numbers of perfect/imperfect hexamers and repeat coding for single amino acid/amino acid pair runs. Our data further suggests that genes containing simple sequence coding repeats may be under negative selection as they tend to be poorly conserved across species. The sequences of coding repeats of orthologous genes vary according to the known phylogeny among the species. In conclusion, the study shows that simple sequence coding repeats are important features of genome diversity among insects.     

Protein phylogeny gives a robust estimation for early divergences of eukaryotes: phylogenetic place of a mitochondria-lacking protozoan, Giardia lamblia

A partial nucleotide sequence of the mRNA encoding a major part of elongation factor 1 alpha (EF1 alpha) from a mitochondria-lacking protozoan, Giardia lamblia, was reported, and the phylogenetic relationship among lower eukaryotes was inferred by the maximum- likelihood and maximum-parsimony methods of protein phylogeny. Both the methods consistently demonstrated that, G. lamblia among the four protozoan species being analyzed, is the earliest offshoot of the eukaryotic tree. Although the Giardia EF1 alpha gene showed an extremely high G+C content as compared with those of other protozoa, it was concentrated only at the third codon positions, resulting in no remarkable differences of amino acid frequencies vis-a-vis those of other species. This clearly suggests (a) that the amino acid frequencies of conservative proteins are free from the drastic bias of genome G+C content, which is a serious problem in the widely used tree of ribosomal RNA, and (b) that protein phylogeny gives a robust estimation for the early divergences in the evolution of eukaryotes.      

Cladistic analysis of anuran POMC sequences

Procedures for performing cladistic analyses can provide powerful tools for understanding the evolution of neuropeptide and polypeptide hormone coding genes. These analyses can be done on either amino acid data sets or nucleotide data sets and can utilize several different algorithms that are dependent on distinct sets of operating assumptions and constraints. In some cases, the results of these analyses can be used to gauge phylogenetic relationships between taxa. Selecting the proper cladistic analysis strategy is dependent on the taxonomic level of analysis and the rate of evolution within the orthologous genes being evaluated. For example, previous studies have shown that the amino acid sequence of proopiomelanocortin (POMC), the common precursor for the melanocortins and beta-endorphin, can be used to resolve phylogenetic relationships at the class and order level. This study tested the hypothesis that POMC sequences could be used to resolve phylogenetic relationships at the family taxonomic level. Cladistic analyses were performed on amphibian POMC sequences characterized from the marine toad, Bufo marinus (family Bufonidae; this study), the spadefoot toad, Spea multiplicatus (family Pelobatidae), the African clawed frog, Xenopus laevis (family Pipidae) and the laughing frog, Rana ridibunda (family Ranidae). In these analyses the sequence of Australian lungfish POMC was used as the outgroup. The analyses were done at the amino acid level using the maximum parsimony algorithm and at the nucleotide level using the maximum likelihood algorithm. For the anuran POMC genes, analysis at the nucleotide level using the maximum likelihood algorithm generated a cladogram with higher bootstrap values than the maximum parsimony analysis of the POMC amino acid data set. For anuran POMC sequences, analysis of nucleotide sequences using the maximum likelihood algorithm would appear to be the preferred strategy for resolving phylogenetic relationships at the family taxonomic level.     

Genome bias influences amino acid choices: analysis of amino acid substitution and re-compilation of substitution matrices exclusive to an AT-biased genome

The genomic era has seen a remarkable increase in the number of genomes being sequenced and annotated. Nonetheless, annotation remains a serious challenge for compositionally biased genomes. For the preliminary annotation, popular nucleotide and protein comparison methods such as BLAST are widely employed. These methods make use of matrices to score alignments such as the amino acid substitution matrices. Since a nucleotide bias leads to an overall bias in the amino acid composition of proteins, it is possible that a genome with nucleotide bias may have introduced atypical amino acid substitutions in its proteome. Consequently, standard matrices fail to perform well in sequence analysis of these genomes. To address this issue, we examined the amino acid substitution in the AT-rich genome of Plasmodium falciparum, chosen as a reference and reconstituted a substitution matrix in the genome's context. The matrix was used to generate protein sequence alignments for the parasite proteins that improved across the functional regions. We attribute this to the consistency that may have been achieved amid the target and background frequencies calculated exclusively in our study. This study has important implications on annotation of proteins that are of experimental interest but give poor sequence alignments with standard conventional matrices.