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      BPhyOG: An interactive server for genome-wide inference of bacterial phylogenies based on overlapping genes

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      BMC Bioinformatics
      BioMed Central

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          Abstract

          Background

          Overlapping genes (OGs) in bacterial genomes are pairs of adjacent genes of which the coding sequences overlap partly or entirely. With the rapid accumulation of sequence data, many OGs in bacterial genomes have now been identified. Indeed, these might prove a consistent feature across all microbial genomes. Our previous work suggests that OGs can be considered as robust markers at the whole genome level for the construction of phylogenies. An online, interactive web server for inferring phylogenies is needed for biologists to analyze phylogenetic relationships among a set of bacterial genomes of interest.

          Description

          BPhyOG is an online interactive server for reconstructing the phylogenies of completely sequenced bacterial genomes on the basis of their shared overlapping genes. It provides two tree-reconstruction methods: Neighbor Joining (NJ) and Unweighted Pair-Group Method using Arithmetic averages (UPGMA). Users can apply the desired method to generate phylogenetic trees, which are based on an evolutionary distance matrix for the selected genomes. The distance between two genomes is defined by the normalized number of their shared OG pairs. BPhyOG also allows users to browse the OGs that were used to infer the phylogenetic relationships. It provides detailed annotation for each OG pair and the features of the component genes through hyperlinks. Users can also retrieve each of the homologous OG pairs that have been determined among 177 genomes. It is a useful tool for analyzing the tree of life and overlapping genes from a genomic standpoint.

          Conclusion

          BPhyOG is a useful interactive web server for genome-wide inference of any potential evolutionary relationship among the genomes selected by users. It currently includes 177 completely sequenced bacterial genomes containing 79,855 OG pairs, the annotation and homologous OG pairs of which are integrated comprehensively. The reliability of phylogenies complemented by annotations make BPhyOG a powerful web server for genomic and genetic studies. It is freely available at http://cmb.bnu.edu.cn/BPhyOG.

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          Most cited references20

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          The use of gene clusters to infer functional coupling.

          Previously, we presented evidence that it is possible to predict functional coupling between genes based on conservation of gene clusters between genomes. With the rapid increase in the availability of prokaryotic sequence data, it has become possible to verify and apply the technique. In this paper, we extend our characterization of the parameters that determine the utility of the approach, and we generalize the approach in a way that supports detection of common classes of functionally coupled genes (e.g., transport and signal transduction clusters). Now that the analysis includes over 30 complete or nearly complete genomes, it has become clear that this approach will play a significant role in supporting efforts to assign functionality to the remaining uncharacterized genes in sequenced genomes.
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            A phylogenomic approach to bacterial phylogeny: evidence of a core of genes sharing a common history.

            It has been claimed that complete genome sequences would clarify phylogenetic relationships between organisms, but up to now, no satisfying approach has been proposed to use efficiently these data. For instance, if the coding of presence or absence of genes in complete genomes gives interesting results, it does not take into account the phylogenetic information contained in sequences and ignores hidden paralogies by using a BLAST reciprocal best hit definition of orthology. In addition, concatenation of sequences of different genes as well as building of consensus trees only consider the few genes that are shared among all organisms. Here we present an attempt to use a supertree method to build the phylogenetic tree of 45 organisms, with special focus on bacterial phylogeny. This led us to perform a phylogenetic study of congruence of tree topologies, which allows the identification of a core of genes supporting similar species phylogeny. We then used this core of genes to infer a tree. This phylogeny presents several differences with the rRNA phylogeny, notably for the position of hyperthermophilic bacteria.
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              Redundancy, antiredundancy, and the robustness of genomes.

              Genetic mutations that lead to undetectable or minimal changes in phenotypes are said to reveal redundant functions. Redundancy is common among phenotypes of higher organisms that experience low mutation rates and small population sizes. Redundancy is less common among organisms with high mutation rates and large populations, or among the rapidly dividing cells of multicellular organisms. In these cases, one even observes the opposite tendency: a hypersensitivity to mutation, which we refer to as antiredundancy. In this paper we analyze the evolutionary dynamics of redundancy and antiredundancy. Assuming a cost of redundancy, we find that large populations will evolve antiredundant mechanisms for removing mutants and thereby bolster the robustness of wild-type genomes; whereas small populations will evolve redundancy to ensure that all individuals have a high chance of survival. We propose that antiredundancy is as important for developmental robustness as redundancy, and is an essential mechanism for ensuring tissue-level stability in complex multicellular organisms. We suggest that antiredundancy deserves greater attention in relation to cancer, mitochondrial disease, and virus infection.
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                Author and article information

                Journal
                BMC Bioinformatics
                BMC Bioinformatics
                BioMed Central (London )
                1471-2105
                2007
                25 July 2007
                : 8
                : 266
                Affiliations
                [1 ]MOE Key Laboratory for Biodiversity Science and Ecological Engineering and College of Life Sciences, Beijing Normal University, Beijing 100875, China
                Article
                1471-2105-8-266
                10.1186/1471-2105-8-266
                1940028
                17650344
                ffd8b739-85cb-4175-9c40-8c9236fe3ea0
                Copyright © 2007 Luo et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 23 October 2006
                : 25 July 2007
                Categories
                Database

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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