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Evidence for a common evolutionary rate in metazoan transcriptional networks

Genome sequences diverge more rapidly in mammals than in other animal lineages, such as birds or insects. However, the effect of this rapid divergence on transcriptional evolution remains unclear. Recent reports have indicated a faster divergence of transcription factor binding in mammals than in in...

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Autores principales: Carvunis, Anne-Ruxandra, Wang, Tina, Skola, Dylan, Yu, Alice, Chen, Jonathan, Kreisberg, Jason F, Ideker, Trey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4764585/
https://www.ncbi.nlm.nih.gov/pubmed/26682651
http://dx.doi.org/10.7554/eLife.11615
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author Carvunis, Anne-Ruxandra
Wang, Tina
Skola, Dylan
Yu, Alice
Chen, Jonathan
Kreisberg, Jason F
Ideker, Trey
author_facet Carvunis, Anne-Ruxandra
Wang, Tina
Skola, Dylan
Yu, Alice
Chen, Jonathan
Kreisberg, Jason F
Ideker, Trey
author_sort Carvunis, Anne-Ruxandra
collection PubMed
description Genome sequences diverge more rapidly in mammals than in other animal lineages, such as birds or insects. However, the effect of this rapid divergence on transcriptional evolution remains unclear. Recent reports have indicated a faster divergence of transcription factor binding in mammals than in insects, but others found the reverse for mRNA expression. Here, we show that these conflicting interpretations resulted from differing methodologies. We performed an integrated analysis of transcriptional network evolution by examining mRNA expression, transcription factor binding and cis-regulatory motifs across >25 animal species, including mammals, birds and insects. Strikingly, we found that transcriptional networks evolve at a common rate across the three animal lineages. Furthermore, differences in rates of genome divergence were greatly reduced when restricting comparisons to chromatin-accessible sequences. The evolution of transcription is thus decoupled from the global rate of genome sequence evolution, suggesting that a small fraction of the genome regulates transcription. DOI: http://dx.doi.org/10.7554/eLife.11615.001
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spelling pubmed-47645852016-02-25 Evidence for a common evolutionary rate in metazoan transcriptional networks Carvunis, Anne-Ruxandra Wang, Tina Skola, Dylan Yu, Alice Chen, Jonathan Kreisberg, Jason F Ideker, Trey eLife Computational and Systems Biology Genome sequences diverge more rapidly in mammals than in other animal lineages, such as birds or insects. However, the effect of this rapid divergence on transcriptional evolution remains unclear. Recent reports have indicated a faster divergence of transcription factor binding in mammals than in insects, but others found the reverse for mRNA expression. Here, we show that these conflicting interpretations resulted from differing methodologies. We performed an integrated analysis of transcriptional network evolution by examining mRNA expression, transcription factor binding and cis-regulatory motifs across >25 animal species, including mammals, birds and insects. Strikingly, we found that transcriptional networks evolve at a common rate across the three animal lineages. Furthermore, differences in rates of genome divergence were greatly reduced when restricting comparisons to chromatin-accessible sequences. The evolution of transcription is thus decoupled from the global rate of genome sequence evolution, suggesting that a small fraction of the genome regulates transcription. DOI: http://dx.doi.org/10.7554/eLife.11615.001 eLife Sciences Publications, Ltd 2015-12-18 /pmc/articles/PMC4764585/ /pubmed/26682651 http://dx.doi.org/10.7554/eLife.11615 Text en © 2015, Carvunis et al http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Carvunis, Anne-Ruxandra
Wang, Tina
Skola, Dylan
Yu, Alice
Chen, Jonathan
Kreisberg, Jason F
Ideker, Trey
Evidence for a common evolutionary rate in metazoan transcriptional networks
title Evidence for a common evolutionary rate in metazoan transcriptional networks
title_full Evidence for a common evolutionary rate in metazoan transcriptional networks
title_fullStr Evidence for a common evolutionary rate in metazoan transcriptional networks
title_full_unstemmed Evidence for a common evolutionary rate in metazoan transcriptional networks
title_short Evidence for a common evolutionary rate in metazoan transcriptional networks
title_sort evidence for a common evolutionary rate in metazoan transcriptional networks
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4764585/
https://www.ncbi.nlm.nih.gov/pubmed/26682651
http://dx.doi.org/10.7554/eLife.11615
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