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Automatic identification of informative regions with epigenomic changes associated to hematopoiesis
Hematopoiesis is one of the best characterized biological systems but the connection between chromatin changes and lineage differentiation is not yet well understood. We have developed a bioinformatic workflow to generate a chromatin space that allows to classify 42 human healthy blood epigenomes fr...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5716146/ https://www.ncbi.nlm.nih.gov/pubmed/28934481 http://dx.doi.org/10.1093/nar/gkx618 |
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author | Carrillo-de-Santa-Pau, Enrique Juan, David Pancaldi, Vera Were, Felipe Martin-Subero, Ignacio Rico, Daniel Valencia, Alfonso |
author_facet | Carrillo-de-Santa-Pau, Enrique Juan, David Pancaldi, Vera Were, Felipe Martin-Subero, Ignacio Rico, Daniel Valencia, Alfonso |
author_sort | Carrillo-de-Santa-Pau, Enrique |
collection | PubMed |
description | Hematopoiesis is one of the best characterized biological systems but the connection between chromatin changes and lineage differentiation is not yet well understood. We have developed a bioinformatic workflow to generate a chromatin space that allows to classify 42 human healthy blood epigenomes from the BLUEPRINT, NIH ROADMAP and ENCODE consortia by their cell type. This approach let us to distinguish different cells types based on their epigenomic profiles, thus recapitulating important aspects of human hematopoiesis. The analysis of the orthogonal dimension of the chromatin space identify 32,662 chromatin determinant regions (CDRs), genomic regions with different epigenetic characteristics between the cell types. Functional analysis revealed that these regions are linked with cell identities. The inclusion of leukemia epigenomes in the healthy hematological chromatin sample space gives us insights on the healthy cell types that are more epigenetically similar to the disease samples. Further analysis of tumoral epigenetic alterations in hematopoietic CDRs points to sets of genes that are tightly regulated in leukemic transformations and commonly mutated in other tumors. Our method provides an analytical approach to study the relationship between epigenomic changes and cell lineage differentiation. Method availability: https://github.com/david-juan/ChromDet. |
format | Online Article Text |
id | pubmed-5716146 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-57161462017-12-08 Automatic identification of informative regions with epigenomic changes associated to hematopoiesis Carrillo-de-Santa-Pau, Enrique Juan, David Pancaldi, Vera Were, Felipe Martin-Subero, Ignacio Rico, Daniel Valencia, Alfonso Nucleic Acids Res Computational Biology Hematopoiesis is one of the best characterized biological systems but the connection between chromatin changes and lineage differentiation is not yet well understood. We have developed a bioinformatic workflow to generate a chromatin space that allows to classify 42 human healthy blood epigenomes from the BLUEPRINT, NIH ROADMAP and ENCODE consortia by their cell type. This approach let us to distinguish different cells types based on their epigenomic profiles, thus recapitulating important aspects of human hematopoiesis. The analysis of the orthogonal dimension of the chromatin space identify 32,662 chromatin determinant regions (CDRs), genomic regions with different epigenetic characteristics between the cell types. Functional analysis revealed that these regions are linked with cell identities. The inclusion of leukemia epigenomes in the healthy hematological chromatin sample space gives us insights on the healthy cell types that are more epigenetically similar to the disease samples. Further analysis of tumoral epigenetic alterations in hematopoietic CDRs points to sets of genes that are tightly regulated in leukemic transformations and commonly mutated in other tumors. Our method provides an analytical approach to study the relationship between epigenomic changes and cell lineage differentiation. Method availability: https://github.com/david-juan/ChromDet. Oxford University Press 2017-09-19 2017-07-17 /pmc/articles/PMC5716146/ /pubmed/28934481 http://dx.doi.org/10.1093/nar/gkx618 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 Carrillo-de-Santa-Pau, Enrique Juan, David Pancaldi, Vera Were, Felipe Martin-Subero, Ignacio Rico, Daniel Valencia, Alfonso Automatic identification of informative regions with epigenomic changes associated to hematopoiesis |
title | Automatic identification of informative regions with epigenomic changes associated to hematopoiesis |
title_full | Automatic identification of informative regions with epigenomic changes associated to hematopoiesis |
title_fullStr | Automatic identification of informative regions with epigenomic changes associated to hematopoiesis |
title_full_unstemmed | Automatic identification of informative regions with epigenomic changes associated to hematopoiesis |
title_short | Automatic identification of informative regions with epigenomic changes associated to hematopoiesis |
title_sort | automatic identification of informative regions with epigenomic changes associated to hematopoiesis |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5716146/ https://www.ncbi.nlm.nih.gov/pubmed/28934481 http://dx.doi.org/10.1093/nar/gkx618 |
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