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Emergence of co-expression in gene regulatory networks

Transcriptomes are known to organize themselves into gene co-expression clusters or modules where groups of genes display distinct patterns of coordinated or synchronous expression across independent biological samples. The functional significance of these co-expression clusters is suggested by the...

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Autores principales: Yin, Wencheng, Mendoza, Luis, Monzon-Sandoval, Jimena, Urrutia, Araxi O., Gutierrez, Humberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8016302/
https://www.ncbi.nlm.nih.gov/pubmed/33793561
http://dx.doi.org/10.1371/journal.pone.0247671
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author Yin, Wencheng
Mendoza, Luis
Monzon-Sandoval, Jimena
Urrutia, Araxi O.
Gutierrez, Humberto
author_facet Yin, Wencheng
Mendoza, Luis
Monzon-Sandoval, Jimena
Urrutia, Araxi O.
Gutierrez, Humberto
author_sort Yin, Wencheng
collection PubMed
description Transcriptomes are known to organize themselves into gene co-expression clusters or modules where groups of genes display distinct patterns of coordinated or synchronous expression across independent biological samples. The functional significance of these co-expression clusters is suggested by the fact that highly coexpressed groups of genes tend to be enriched in genes involved in common functions and biological processes. While gene co-expression is widely assumed to reflect close regulatory proximity, the validity of this assumption remains unclear. Here we use a simple synthetic gene regulatory network (GRN) model and contrast the resulting co-expression structure produced by these networks with their known regulatory architecture and with the co-expression structure measured in available human expression data. Using randomization tests, we found that the levels of co-expression observed in simulated expression data were, just as with empirical data, significantly higher than expected by chance. When examining the source of correlated expression, we found that individual regulators, both in simulated and experimental data, fail, on average, to display correlated expression with their immediate targets. However, highly correlated gene pairs tend to share at least one common regulator, while most gene pairs sharing common regulators do not necessarily display correlated expression. Our results demonstrate that widespread co-expression naturally emerges in regulatory networks, and that it is a reliable and direct indicator of active co-regulation in a given cellular context.
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spelling pubmed-80163022021-04-08 Emergence of co-expression in gene regulatory networks Yin, Wencheng Mendoza, Luis Monzon-Sandoval, Jimena Urrutia, Araxi O. Gutierrez, Humberto PLoS One Research Article Transcriptomes are known to organize themselves into gene co-expression clusters or modules where groups of genes display distinct patterns of coordinated or synchronous expression across independent biological samples. The functional significance of these co-expression clusters is suggested by the fact that highly coexpressed groups of genes tend to be enriched in genes involved in common functions and biological processes. While gene co-expression is widely assumed to reflect close regulatory proximity, the validity of this assumption remains unclear. Here we use a simple synthetic gene regulatory network (GRN) model and contrast the resulting co-expression structure produced by these networks with their known regulatory architecture and with the co-expression structure measured in available human expression data. Using randomization tests, we found that the levels of co-expression observed in simulated expression data were, just as with empirical data, significantly higher than expected by chance. When examining the source of correlated expression, we found that individual regulators, both in simulated and experimental data, fail, on average, to display correlated expression with their immediate targets. However, highly correlated gene pairs tend to share at least one common regulator, while most gene pairs sharing common regulators do not necessarily display correlated expression. Our results demonstrate that widespread co-expression naturally emerges in regulatory networks, and that it is a reliable and direct indicator of active co-regulation in a given cellular context. Public Library of Science 2021-04-01 /pmc/articles/PMC8016302/ /pubmed/33793561 http://dx.doi.org/10.1371/journal.pone.0247671 Text en © 2021 Yin 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yin, Wencheng
Mendoza, Luis
Monzon-Sandoval, Jimena
Urrutia, Araxi O.
Gutierrez, Humberto
Emergence of co-expression in gene regulatory networks
title Emergence of co-expression in gene regulatory networks
title_full Emergence of co-expression in gene regulatory networks
title_fullStr Emergence of co-expression in gene regulatory networks
title_full_unstemmed Emergence of co-expression in gene regulatory networks
title_short Emergence of co-expression in gene regulatory networks
title_sort emergence of co-expression in gene regulatory networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8016302/
https://www.ncbi.nlm.nih.gov/pubmed/33793561
http://dx.doi.org/10.1371/journal.pone.0247671
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