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Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings

Understanding the three-dimensional (3D) architecture of chromatin and its relation to gene expression and regulation is fundamental to understanding how the genome functions. Advances in Hi-C technology now permit us to study 3D genome organization, but we still lack an understanding of the structu...

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Autores principales: Sauerwald, Natalie, Zhang, She, Kingsford, Carl, Bahar, Ivet
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5397156/
https://www.ncbi.nlm.nih.gov/pubmed/28334818
http://dx.doi.org/10.1093/nar/gkx172
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author Sauerwald, Natalie
Zhang, She
Kingsford, Carl
Bahar, Ivet
author_facet Sauerwald, Natalie
Zhang, She
Kingsford, Carl
Bahar, Ivet
author_sort Sauerwald, Natalie
collection PubMed
description Understanding the three-dimensional (3D) architecture of chromatin and its relation to gene expression and regulation is fundamental to understanding how the genome functions. Advances in Hi-C technology now permit us to study 3D genome organization, but we still lack an understanding of the structural dynamics of chromosomes. The dynamic couplings between regions separated by large genomic distances (>50 Mb) have yet to be characterized. We adapted a well-established protein-modeling framework, the Gaussian Network Model (GNM), to model chromatin dynamics using Hi-C data. We show that the GNM can identify spatial couplings at multiple scales: it can quantify the correlated fluctuations in the positions of gene loci, find large genomic compartments and smaller topologically-associating domains (TADs) that undergo en bloc movements, and identify dynamically coupled distal regions along the chromosomes. We show that the predictions of the GNM correlate well with genome-wide experimental measurements. We use the GNM to identify novel cross-correlated distal domains (CCDDs) representing pairs of regions distinguished by their long-range dynamic coupling and show that CCDDs are associated with increased gene co-expression. Together, these results show that GNM provides a mathematically well-founded unified framework for modeling chromatin dynamics and assessing the structural basis of genome-wide observations.
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spelling pubmed-53971562017-04-24 Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings Sauerwald, Natalie Zhang, She Kingsford, Carl Bahar, Ivet Nucleic Acids Res Computational Biology Understanding the three-dimensional (3D) architecture of chromatin and its relation to gene expression and regulation is fundamental to understanding how the genome functions. Advances in Hi-C technology now permit us to study 3D genome organization, but we still lack an understanding of the structural dynamics of chromosomes. The dynamic couplings between regions separated by large genomic distances (>50 Mb) have yet to be characterized. We adapted a well-established protein-modeling framework, the Gaussian Network Model (GNM), to model chromatin dynamics using Hi-C data. We show that the GNM can identify spatial couplings at multiple scales: it can quantify the correlated fluctuations in the positions of gene loci, find large genomic compartments and smaller topologically-associating domains (TADs) that undergo en bloc movements, and identify dynamically coupled distal regions along the chromosomes. We show that the predictions of the GNM correlate well with genome-wide experimental measurements. We use the GNM to identify novel cross-correlated distal domains (CCDDs) representing pairs of regions distinguished by their long-range dynamic coupling and show that CCDDs are associated with increased gene co-expression. Together, these results show that GNM provides a mathematically well-founded unified framework for modeling chromatin dynamics and assessing the structural basis of genome-wide observations. Oxford University Press 2017-04-20 2017-03-16 /pmc/articles/PMC5397156/ /pubmed/28334818 http://dx.doi.org/10.1093/nar/gkx172 Text en © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Computational Biology
Sauerwald, Natalie
Zhang, She
Kingsford, Carl
Bahar, Ivet
Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings
title Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings
title_full Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings
title_fullStr Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings
title_full_unstemmed Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings
title_short Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings
title_sort chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5397156/
https://www.ncbi.nlm.nih.gov/pubmed/28334818
http://dx.doi.org/10.1093/nar/gkx172
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