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Uncovering the co-evolutionary network among prokaryotic genes.


ABSTRACT: MOTIVATION: Correlated events of gains and losses enable inference of co-evolution relations. The reconstruction of the co-evolutionary interactions network in prokaryotic species may elucidate functional associations among genes. RESULTS: We developed a novel probabilistic methodology for the detection of co-evolutionary interactions between pairs of genes. Using this method we inferred the co-evolutionary network among 4593 Clusters of Orthologous Genes (COGs). The number of co-evolutionary interactions substantially differed among COGs. Over 40% were found to co-evolve with at least one partner. We partitioned the network of co-evolutionary relations into clusters and uncovered multiple modular assemblies of genes with clearly defined functions. Finally, we measured the extent to which co-evolutionary relations coincide with other cellular relations such as genomic proximity, gene fusion propensity, co-expression, protein-protein interactions and metabolic connections. Our results show that co-evolutionary relations only partially overlap with these other types of networks. Our results suggest that the inferred co-evolutionary network in prokaryotes is highly informative towards revealing functional relations among genes, often showing signals that cannot be extracted from other network types. AVAILABILITY AND IMPLEMENTATION: Available under GPL license as open source. CONTACT: talp@post.tau.ac.il. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUBMITTER: Cohen O 

PROVIDER: S-EPMC3436823 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Uncovering the co-evolutionary network among prokaryotic genes.

Cohen Ofir O   Ashkenazy Haim H   Burstein David D   Pupko Tal T  

Bioinformatics (Oxford, England) 20120901 18


<h4>Motivation</h4>Correlated events of gains and losses enable inference of co-evolution relations. The reconstruction of the co-evolutionary interactions network in prokaryotic species may elucidate functional associations among genes.<h4>Results</h4>We developed a novel probabilistic methodology for the detection of co-evolutionary interactions between pairs of genes. Using this method we inferred the co-evolutionary network among 4593 Clusters of Orthologous Genes (COGs). The number of co-ev  ...[more]

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