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Semi-nonparametric modeling of topological domain formation from epigenetic data
BACKGROUND: Hi-C experiments capturing the 3D genome architecture have led to the discovery of topologically-associated domains (TADs) that form an important part of the 3D genome organization and appear to play a role in gene regulation and other functions. Several histone modifications have been i...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399866/ https://www.ncbi.nlm.nih.gov/pubmed/30867673 http://dx.doi.org/10.1186/s13015-019-0142-y |
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author | Sefer, Emre Kingsford, Carl |
author_facet | Sefer, Emre Kingsford, Carl |
author_sort | Sefer, Emre |
collection | PubMed |
description | BACKGROUND: Hi-C experiments capturing the 3D genome architecture have led to the discovery of topologically-associated domains (TADs) that form an important part of the 3D genome organization and appear to play a role in gene regulation and other functions. Several histone modifications have been independently associated with TAD formation, but their combinatorial effects on domain formation remain poorly understood at a global scale. RESULTS: We propose a convex semi-nonparametric approach called nTDP based on Bernstein polynomials to explore the joint effects of histone markers on TAD formation as well as predict TADs solely from the histone data. We find a small subset of modifications to be predictive of TADs across species. By inferring TADs using our trained model, we are able to predict TADs across different species and cell types, without the use of Hi-C data, suggesting their effect is conserved. This work provides the first comprehensive joint model of the effect of histone markers on domain formation. CONCLUSIONS: Our approach, nTDP, can form the basis of a unified, explanatory model of the relationship between epigenetic marks and topological domain structures. It can be used to predict domain boundaries for cell types, species, and conditions for which no Hi-C data is available. The model may also be of use for improving Hi-C-based domain finders. |
format | Online Article Text |
id | pubmed-6399866 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63998662019-03-13 Semi-nonparametric modeling of topological domain formation from epigenetic data Sefer, Emre Kingsford, Carl Algorithms Mol Biol Research BACKGROUND: Hi-C experiments capturing the 3D genome architecture have led to the discovery of topologically-associated domains (TADs) that form an important part of the 3D genome organization and appear to play a role in gene regulation and other functions. Several histone modifications have been independently associated with TAD formation, but their combinatorial effects on domain formation remain poorly understood at a global scale. RESULTS: We propose a convex semi-nonparametric approach called nTDP based on Bernstein polynomials to explore the joint effects of histone markers on TAD formation as well as predict TADs solely from the histone data. We find a small subset of modifications to be predictive of TADs across species. By inferring TADs using our trained model, we are able to predict TADs across different species and cell types, without the use of Hi-C data, suggesting their effect is conserved. This work provides the first comprehensive joint model of the effect of histone markers on domain formation. CONCLUSIONS: Our approach, nTDP, can form the basis of a unified, explanatory model of the relationship between epigenetic marks and topological domain structures. It can be used to predict domain boundaries for cell types, species, and conditions for which no Hi-C data is available. The model may also be of use for improving Hi-C-based domain finders. BioMed Central 2019-03-05 /pmc/articles/PMC6399866/ /pubmed/30867673 http://dx.doi.org/10.1186/s13015-019-0142-y Text en © The Author(s) 2019 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 Sefer, Emre Kingsford, Carl Semi-nonparametric modeling of topological domain formation from epigenetic data |
title | Semi-nonparametric modeling of topological domain formation from epigenetic data |
title_full | Semi-nonparametric modeling of topological domain formation from epigenetic data |
title_fullStr | Semi-nonparametric modeling of topological domain formation from epigenetic data |
title_full_unstemmed | Semi-nonparametric modeling of topological domain formation from epigenetic data |
title_short | Semi-nonparametric modeling of topological domain formation from epigenetic data |
title_sort | semi-nonparametric modeling of topological domain formation from epigenetic data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399866/ https://www.ncbi.nlm.nih.gov/pubmed/30867673 http://dx.doi.org/10.1186/s13015-019-0142-y |
work_keys_str_mv | AT seferemre seminonparametricmodelingoftopologicaldomainformationfromepigeneticdata AT kingsfordcarl seminonparametricmodelingoftopologicaldomainformationfromepigeneticdata |