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Preferential Duplication of Intermodular Hub Genes: An Evolutionary Signature in Eukaryotes Genome Networks

Whole genome protein-protein association networks are not random and their topological properties stem from genome evolution mechanisms. In fact, more connected, but less clustered proteins are related to genes that, in general, present more paralogs as compared to other genes, indicating frequent p...

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Autores principales: Ferreira, Ricardo M., Rybarczyk-Filho, José Luiz, Dalmolin, Rodrigo J. S., Castro, Mauro A. A., Moreira, José C. F., Brunnet, Leonardo G., de Almeida, Rita M. C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3582557/
https://www.ncbi.nlm.nih.gov/pubmed/23468868
http://dx.doi.org/10.1371/journal.pone.0056579
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author Ferreira, Ricardo M.
Rybarczyk-Filho, José Luiz
Dalmolin, Rodrigo J. S.
Castro, Mauro A. A.
Moreira, José C. F.
Brunnet, Leonardo G.
de Almeida, Rita M. C.
author_facet Ferreira, Ricardo M.
Rybarczyk-Filho, José Luiz
Dalmolin, Rodrigo J. S.
Castro, Mauro A. A.
Moreira, José C. F.
Brunnet, Leonardo G.
de Almeida, Rita M. C.
author_sort Ferreira, Ricardo M.
collection PubMed
description Whole genome protein-protein association networks are not random and their topological properties stem from genome evolution mechanisms. In fact, more connected, but less clustered proteins are related to genes that, in general, present more paralogs as compared to other genes, indicating frequent previous gene duplication episodes. On the other hand, genes related to conserved biological functions present few or no paralogs and yield proteins that are highly connected and clustered. These general network characteristics must have an evolutionary explanation. Considering data from STRING database, we present here experimental evidence that, more than not being scale free, protein degree distributions of organisms present an increased probability for high degree nodes. Furthermore, based on this experimental evidence, we propose a simulation model for genome evolution, where genes in a network are either acquired de novo using a preferential attachment rule, or duplicated with a probability that linearly grows with gene degree and decreases with its clustering coefficient. For the first time a model yields results that simultaneously describe different topological distributions. Also, this model correctly predicts that, to produce protein-protein association networks with number of links and number of nodes in the observed range for Eukaryotes, it is necessary 90% of gene duplication and 10% of de novo gene acquisition. This scenario implies a universal mechanism for genome evolution.
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spelling pubmed-35825572013-03-06 Preferential Duplication of Intermodular Hub Genes: An Evolutionary Signature in Eukaryotes Genome Networks Ferreira, Ricardo M. Rybarczyk-Filho, José Luiz Dalmolin, Rodrigo J. S. Castro, Mauro A. A. Moreira, José C. F. Brunnet, Leonardo G. de Almeida, Rita M. C. PLoS One Research Article Whole genome protein-protein association networks are not random and their topological properties stem from genome evolution mechanisms. In fact, more connected, but less clustered proteins are related to genes that, in general, present more paralogs as compared to other genes, indicating frequent previous gene duplication episodes. On the other hand, genes related to conserved biological functions present few or no paralogs and yield proteins that are highly connected and clustered. These general network characteristics must have an evolutionary explanation. Considering data from STRING database, we present here experimental evidence that, more than not being scale free, protein degree distributions of organisms present an increased probability for high degree nodes. Furthermore, based on this experimental evidence, we propose a simulation model for genome evolution, where genes in a network are either acquired de novo using a preferential attachment rule, or duplicated with a probability that linearly grows with gene degree and decreases with its clustering coefficient. For the first time a model yields results that simultaneously describe different topological distributions. Also, this model correctly predicts that, to produce protein-protein association networks with number of links and number of nodes in the observed range for Eukaryotes, it is necessary 90% of gene duplication and 10% of de novo gene acquisition. This scenario implies a universal mechanism for genome evolution. Public Library of Science 2013-02-26 /pmc/articles/PMC3582557/ /pubmed/23468868 http://dx.doi.org/10.1371/journal.pone.0056579 Text en © 2013 Ferreira et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Ferreira, Ricardo M.
Rybarczyk-Filho, José Luiz
Dalmolin, Rodrigo J. S.
Castro, Mauro A. A.
Moreira, José C. F.
Brunnet, Leonardo G.
de Almeida, Rita M. C.
Preferential Duplication of Intermodular Hub Genes: An Evolutionary Signature in Eukaryotes Genome Networks
title Preferential Duplication of Intermodular Hub Genes: An Evolutionary Signature in Eukaryotes Genome Networks
title_full Preferential Duplication of Intermodular Hub Genes: An Evolutionary Signature in Eukaryotes Genome Networks
title_fullStr Preferential Duplication of Intermodular Hub Genes: An Evolutionary Signature in Eukaryotes Genome Networks
title_full_unstemmed Preferential Duplication of Intermodular Hub Genes: An Evolutionary Signature in Eukaryotes Genome Networks
title_short Preferential Duplication of Intermodular Hub Genes: An Evolutionary Signature in Eukaryotes Genome Networks
title_sort preferential duplication of intermodular hub genes: an evolutionary signature in eukaryotes genome networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3582557/
https://www.ncbi.nlm.nih.gov/pubmed/23468868
http://dx.doi.org/10.1371/journal.pone.0056579
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