Cargando…
Uncovering the co-evolutionary network among prokaryotic genes
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 detec...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3436823/ https://www.ncbi.nlm.nih.gov/pubmed/22962457 http://dx.doi.org/10.1093/bioinformatics/bts396 |
_version_ | 1782242705955356672 |
---|---|
author | Cohen, Ofir Ashkenazy, Haim Burstein, David Pupko, Tal |
author_facet | Cohen, Ofir Ashkenazy, Haim Burstein, David Pupko, Tal |
author_sort | Cohen, Ofir |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3436823 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-34368232012-12-12 Uncovering the co-evolutionary network among prokaryotic genes Cohen, Ofir Ashkenazy, Haim Burstein, David Pupko, Tal Bioinformatics Original Papers 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. Oxford University Press 2012-09-15 2012-09-03 /pmc/articles/PMC3436823/ /pubmed/22962457 http://dx.doi.org/10.1093/bioinformatics/bts396 Text en © The Author(s) (2012). Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Cohen, Ofir Ashkenazy, Haim Burstein, David Pupko, Tal Uncovering the co-evolutionary network among prokaryotic genes |
title | Uncovering the co-evolutionary network among prokaryotic genes |
title_full | Uncovering the co-evolutionary network among prokaryotic genes |
title_fullStr | Uncovering the co-evolutionary network among prokaryotic genes |
title_full_unstemmed | Uncovering the co-evolutionary network among prokaryotic genes |
title_short | Uncovering the co-evolutionary network among prokaryotic genes |
title_sort | uncovering the co-evolutionary network among prokaryotic genes |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3436823/ https://www.ncbi.nlm.nih.gov/pubmed/22962457 http://dx.doi.org/10.1093/bioinformatics/bts396 |
work_keys_str_mv | AT cohenofir uncoveringthecoevolutionarynetworkamongprokaryoticgenes AT ashkenazyhaim uncoveringthecoevolutionarynetworkamongprokaryoticgenes AT bursteindavid uncoveringthecoevolutionarynetworkamongprokaryoticgenes AT pupkotal uncoveringthecoevolutionarynetworkamongprokaryoticgenes |