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Predicting expression: the complementary power of histone modification and transcription factor binding data

BACKGROUND: Transcription factors (TFs) and histone modifications (HMs) play critical roles in gene expression by regulating mRNA transcription. Modelling frameworks have been developed to integrate high-throughput omics data, with the aim of elucidating the regulatory logic that results from the in...

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Autores principales: Budden, David M, Hurley, Daniel G, Cursons, Joseph, Markham, John F, Davis, Melissa J, Crampin, Edmund J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4258808/
https://www.ncbi.nlm.nih.gov/pubmed/25489339
http://dx.doi.org/10.1186/1756-8935-7-36
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author Budden, David M
Hurley, Daniel G
Cursons, Joseph
Markham, John F
Davis, Melissa J
Crampin, Edmund J
author_facet Budden, David M
Hurley, Daniel G
Cursons, Joseph
Markham, John F
Davis, Melissa J
Crampin, Edmund J
author_sort Budden, David M
collection PubMed
description BACKGROUND: Transcription factors (TFs) and histone modifications (HMs) play critical roles in gene expression by regulating mRNA transcription. Modelling frameworks have been developed to integrate high-throughput omics data, with the aim of elucidating the regulatory logic that results from the interactions of DNA, TFs and HMs. These models have yielded an unexpected and poorly understood result: that TFs and HMs are statistically redundant in explaining mRNA transcript abundance at a genome-wide level. RESULTS: We constructed predictive models of gene expression by integrating RNA-sequencing, TF and HM chromatin immunoprecipitation sequencing and DNase I hypersensitivity data for two mammalian cell types. All models identified genome-wide statistical redundancy both within and between TFs and HMs, as previously reported. To investigate potential explanations, groups of genes were constructed for ontology-classified biological processes. Predictive models were constructed for each process to explore the distribution of statistical redundancy. We found significant variation in the predictive capacity of TFs and HMs across these processes and demonstrated the predictive power of HMs to be inversely proportional to process enrichment for housekeeping genes. CONCLUSIONS: It is well established that the roles played by TFs and HMs are not functionally redundant. Instead, we attribute the statistical redundancy reported in this and previous genome-wide modelling studies to the heterogeneous distribution of HMs across chromatin domains. Furthermore, we conclude that statistical redundancy between individual TFs can be readily explained by nucleosome-mediated cooperative binding. This could possibly help the cell confer regulatory robustness by rejecting signalling noise and allowing control via multiple pathways. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1756-8935-7-36) contains supplementary material, which is available to authorized users.
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spelling pubmed-42588082014-12-09 Predicting expression: the complementary power of histone modification and transcription factor binding data Budden, David M Hurley, Daniel G Cursons, Joseph Markham, John F Davis, Melissa J Crampin, Edmund J Epigenetics Chromatin Research BACKGROUND: Transcription factors (TFs) and histone modifications (HMs) play critical roles in gene expression by regulating mRNA transcription. Modelling frameworks have been developed to integrate high-throughput omics data, with the aim of elucidating the regulatory logic that results from the interactions of DNA, TFs and HMs. These models have yielded an unexpected and poorly understood result: that TFs and HMs are statistically redundant in explaining mRNA transcript abundance at a genome-wide level. RESULTS: We constructed predictive models of gene expression by integrating RNA-sequencing, TF and HM chromatin immunoprecipitation sequencing and DNase I hypersensitivity data for two mammalian cell types. All models identified genome-wide statistical redundancy both within and between TFs and HMs, as previously reported. To investigate potential explanations, groups of genes were constructed for ontology-classified biological processes. Predictive models were constructed for each process to explore the distribution of statistical redundancy. We found significant variation in the predictive capacity of TFs and HMs across these processes and demonstrated the predictive power of HMs to be inversely proportional to process enrichment for housekeeping genes. CONCLUSIONS: It is well established that the roles played by TFs and HMs are not functionally redundant. Instead, we attribute the statistical redundancy reported in this and previous genome-wide modelling studies to the heterogeneous distribution of HMs across chromatin domains. Furthermore, we conclude that statistical redundancy between individual TFs can be readily explained by nucleosome-mediated cooperative binding. This could possibly help the cell confer regulatory robustness by rejecting signalling noise and allowing control via multiple pathways. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1756-8935-7-36) contains supplementary material, which is available to authorized users. BioMed Central 2014-11-24 /pmc/articles/PMC4258808/ /pubmed/25489339 http://dx.doi.org/10.1186/1756-8935-7-36 Text en © Budden et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. 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 work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Budden, David M
Hurley, Daniel G
Cursons, Joseph
Markham, John F
Davis, Melissa J
Crampin, Edmund J
Predicting expression: the complementary power of histone modification and transcription factor binding data
title Predicting expression: the complementary power of histone modification and transcription factor binding data
title_full Predicting expression: the complementary power of histone modification and transcription factor binding data
title_fullStr Predicting expression: the complementary power of histone modification and transcription factor binding data
title_full_unstemmed Predicting expression: the complementary power of histone modification and transcription factor binding data
title_short Predicting expression: the complementary power of histone modification and transcription factor binding data
title_sort predicting expression: the complementary power of histone modification and transcription factor binding data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4258808/
https://www.ncbi.nlm.nih.gov/pubmed/25489339
http://dx.doi.org/10.1186/1756-8935-7-36
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