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Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity

BACKGROUND: Network analysis is a powerful way of modeling chromatin interactions. Assortativity is a network property used in social sciences to identify factors affecting how people establish social ties. We propose a new approach, using chromatin assortativity, to integrate the epigenomic landsca...

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Autores principales: Pancaldi, Vera, Carrillo-de-Santa-Pau, Enrique, Javierre, Biola Maria, Juan, David, Fraser, Peter, Spivakov, Mikhail, Valencia, Alfonso, Rico, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4939006/
https://www.ncbi.nlm.nih.gov/pubmed/27391817
http://dx.doi.org/10.1186/s13059-016-1003-3
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author Pancaldi, Vera
Carrillo-de-Santa-Pau, Enrique
Javierre, Biola Maria
Juan, David
Fraser, Peter
Spivakov, Mikhail
Valencia, Alfonso
Rico, Daniel
author_facet Pancaldi, Vera
Carrillo-de-Santa-Pau, Enrique
Javierre, Biola Maria
Juan, David
Fraser, Peter
Spivakov, Mikhail
Valencia, Alfonso
Rico, Daniel
author_sort Pancaldi, Vera
collection PubMed
description BACKGROUND: Network analysis is a powerful way of modeling chromatin interactions. Assortativity is a network property used in social sciences to identify factors affecting how people establish social ties. We propose a new approach, using chromatin assortativity, to integrate the epigenomic landscape of a specific cell type with its chromatin interaction network and thus investigate which proteins or chromatin marks mediate genomic contacts. RESULTS: We use high-resolution promoter capture Hi-C and Hi-Cap data as well as ChIA-PET data from mouse embryonic stem cells to investigate promoter-centered chromatin interaction networks and calculate the presence of specific epigenomic features in the chromatin fragments constituting the nodes of the network. We estimate the association of these features with the topology of four chromatin interaction networks and identify features localized in connected areas of the network. Polycomb group proteins and associated histone marks are the features with the highest chromatin assortativity in promoter-centered networks. We then ask which features distinguish contacts amongst promoters from contacts between promoters and other genomic elements. We observe higher chromatin assortativity of the actively elongating form of RNA polymerase 2 (RNAPII) compared with inactive forms only in interactions between promoters and other elements. CONCLUSIONS: Contacts among promoters and between promoters and other elements have different characteristic epigenomic features. We identify a possible role for the elongating form of RNAPII in mediating interactions among promoters, enhancers, and transcribed gene bodies. Our approach facilitates the study of multiple genome-wide epigenomic profiles, considering network topology and allowing the comparison of chromatin interaction networks. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-1003-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-49390062016-07-10 Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity Pancaldi, Vera Carrillo-de-Santa-Pau, Enrique Javierre, Biola Maria Juan, David Fraser, Peter Spivakov, Mikhail Valencia, Alfonso Rico, Daniel Genome Biol Research BACKGROUND: Network analysis is a powerful way of modeling chromatin interactions. Assortativity is a network property used in social sciences to identify factors affecting how people establish social ties. We propose a new approach, using chromatin assortativity, to integrate the epigenomic landscape of a specific cell type with its chromatin interaction network and thus investigate which proteins or chromatin marks mediate genomic contacts. RESULTS: We use high-resolution promoter capture Hi-C and Hi-Cap data as well as ChIA-PET data from mouse embryonic stem cells to investigate promoter-centered chromatin interaction networks and calculate the presence of specific epigenomic features in the chromatin fragments constituting the nodes of the network. We estimate the association of these features with the topology of four chromatin interaction networks and identify features localized in connected areas of the network. Polycomb group proteins and associated histone marks are the features with the highest chromatin assortativity in promoter-centered networks. We then ask which features distinguish contacts amongst promoters from contacts between promoters and other genomic elements. We observe higher chromatin assortativity of the actively elongating form of RNA polymerase 2 (RNAPII) compared with inactive forms only in interactions between promoters and other elements. CONCLUSIONS: Contacts among promoters and between promoters and other elements have different characteristic epigenomic features. We identify a possible role for the elongating form of RNAPII in mediating interactions among promoters, enhancers, and transcribed gene bodies. Our approach facilitates the study of multiple genome-wide epigenomic profiles, considering network topology and allowing the comparison of chromatin interaction networks. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-016-1003-3) contains supplementary material, which is available to authorized users. BioMed Central 2016-07-08 /pmc/articles/PMC4939006/ /pubmed/27391817 http://dx.doi.org/10.1186/s13059-016-1003-3 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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
Pancaldi, Vera
Carrillo-de-Santa-Pau, Enrique
Javierre, Biola Maria
Juan, David
Fraser, Peter
Spivakov, Mikhail
Valencia, Alfonso
Rico, Daniel
Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity
title Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity
title_full Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity
title_fullStr Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity
title_full_unstemmed Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity
title_short Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity
title_sort integrating epigenomic data and 3d genomic structure with a new measure of chromatin assortativity
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4939006/
https://www.ncbi.nlm.nih.gov/pubmed/27391817
http://dx.doi.org/10.1186/s13059-016-1003-3
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