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De novo deciphering three-dimensional chromatin interaction and topological domains by wavelet transformation of epigenetic profiles
Defining chromatin interaction frequencies and topological domains is a great challenge for the annotations of genome structures. Although the chromosome conformation capture (3C) and its derivative methods have been developed for exploring the global interactome, they are limited by high experiment...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4914103/ https://www.ncbi.nlm.nih.gov/pubmed/27060148 http://dx.doi.org/10.1093/nar/gkw225 |
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author | Chen, Yong Wang, Yunfei Xuan, Zhenyu Chen, Min Zhang, Michael Q. |
author_facet | Chen, Yong Wang, Yunfei Xuan, Zhenyu Chen, Min Zhang, Michael Q. |
author_sort | Chen, Yong |
collection | PubMed |
description | Defining chromatin interaction frequencies and topological domains is a great challenge for the annotations of genome structures. Although the chromosome conformation capture (3C) and its derivative methods have been developed for exploring the global interactome, they are limited by high experimental complexity and costs. Here we describe a novel computational method, called CITD, for de novo prediction of the chromatin interaction map by integrating histone modification data. We used the public epigenomic data from human fibroblast IMR90 cell and embryonic stem cell (H1) to develop and test CITD, which can not only successfully reconstruct the chromatin interaction frequencies discovered by the Hi-C technology, but also provide additional novel details of chromosomal organizations. We predicted the chromatin interaction frequencies, topological domains and their states (e.g. active or repressive) for 98 additional cell types from Roadmap Epigenomics and ENCODE projects. A total of 131 protein-coding genes located near 78 preserved boundaries among 100 cell types are found to be significantly enriched in functional categories of the nucleosome organization and chromatin assembly. CITD and its predicted results can be used for complementing the topological domains derived from limited Hi-C data and facilitating the understanding of spatial principles underlying the chromosomal organization. |
format | Online Article Text |
id | pubmed-4914103 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-49141032016-06-22 De novo deciphering three-dimensional chromatin interaction and topological domains by wavelet transformation of epigenetic profiles Chen, Yong Wang, Yunfei Xuan, Zhenyu Chen, Min Zhang, Michael Q. Nucleic Acids Res Methods Online Defining chromatin interaction frequencies and topological domains is a great challenge for the annotations of genome structures. Although the chromosome conformation capture (3C) and its derivative methods have been developed for exploring the global interactome, they are limited by high experimental complexity and costs. Here we describe a novel computational method, called CITD, for de novo prediction of the chromatin interaction map by integrating histone modification data. We used the public epigenomic data from human fibroblast IMR90 cell and embryonic stem cell (H1) to develop and test CITD, which can not only successfully reconstruct the chromatin interaction frequencies discovered by the Hi-C technology, but also provide additional novel details of chromosomal organizations. We predicted the chromatin interaction frequencies, topological domains and their states (e.g. active or repressive) for 98 additional cell types from Roadmap Epigenomics and ENCODE projects. A total of 131 protein-coding genes located near 78 preserved boundaries among 100 cell types are found to be significantly enriched in functional categories of the nucleosome organization and chromatin assembly. CITD and its predicted results can be used for complementing the topological domains derived from limited Hi-C data and facilitating the understanding of spatial principles underlying the chromosomal organization. Oxford University Press 2016-06-20 2016-04-07 /pmc/articles/PMC4914103/ /pubmed/27060148 http://dx.doi.org/10.1093/nar/gkw225 Text en © The Author(s) 2016. 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 | Methods Online Chen, Yong Wang, Yunfei Xuan, Zhenyu Chen, Min Zhang, Michael Q. De novo deciphering three-dimensional chromatin interaction and topological domains by wavelet transformation of epigenetic profiles |
title |
De novo deciphering three-dimensional chromatin interaction and topological domains by wavelet transformation of epigenetic profiles |
title_full |
De novo deciphering three-dimensional chromatin interaction and topological domains by wavelet transformation of epigenetic profiles |
title_fullStr |
De novo deciphering three-dimensional chromatin interaction and topological domains by wavelet transformation of epigenetic profiles |
title_full_unstemmed |
De novo deciphering three-dimensional chromatin interaction and topological domains by wavelet transformation of epigenetic profiles |
title_short |
De novo deciphering three-dimensional chromatin interaction and topological domains by wavelet transformation of epigenetic profiles |
title_sort | de novo deciphering three-dimensional chromatin interaction and topological domains by wavelet transformation of epigenetic profiles |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4914103/ https://www.ncbi.nlm.nih.gov/pubmed/27060148 http://dx.doi.org/10.1093/nar/gkw225 |
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