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Computational modeling of chromatin accessibility identified important epigenomic regulators

Chromatin accessibility is essential for transcriptional activation of genomic regions. It is well established that transcription factors (TFs) and histone modifications (HMs) play critical roles in chromatin accessibility regulation. However, there is a lack of studies that quantify these relations...

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Autores principales: Zhao, Yanding, Dong, Yadong, Hong, Wei, Jiang, Chongming, Yao, Kevin, Cheng, Chao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8742372/
https://www.ncbi.nlm.nih.gov/pubmed/34996354
http://dx.doi.org/10.1186/s12864-021-08234-5
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author Zhao, Yanding
Dong, Yadong
Hong, Wei
Jiang, Chongming
Yao, Kevin
Cheng, Chao
author_facet Zhao, Yanding
Dong, Yadong
Hong, Wei
Jiang, Chongming
Yao, Kevin
Cheng, Chao
author_sort Zhao, Yanding
collection PubMed
description Chromatin accessibility is essential for transcriptional activation of genomic regions. It is well established that transcription factors (TFs) and histone modifications (HMs) play critical roles in chromatin accessibility regulation. However, there is a lack of studies that quantify these relationships. Here we constructed a two-layer model to predict chromatin accessibility by integrating DNA sequence, TF binding, and HM signals. By applying the model to two human cell lines (GM12878 and HepG2), we found that DNA sequences had limited power for accessibility prediction, while both TF binding and HM signals predicted chromatin accessibility with high accuracy. According to the HM model, HM features determined chromatin accessibility in a cell line shared manner, with the prediction power attributing to five core HM types. Results from the TF model indicated that chromatin accessibility was determined by a subset of informative TFs including both cell line-specific and generic TFs. The combined model of both TF and HM signals did not further improve the prediction accuracy, indicating that they provide redundant information in terms of chromatin accessibility prediction. The TFs and HM models can also distinguish the chromatin accessibility of proximal versus distal transcription start sites with high accuracy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-08234-5.
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spelling pubmed-87423722022-01-10 Computational modeling of chromatin accessibility identified important epigenomic regulators Zhao, Yanding Dong, Yadong Hong, Wei Jiang, Chongming Yao, Kevin Cheng, Chao BMC Genomics Research Chromatin accessibility is essential for transcriptional activation of genomic regions. It is well established that transcription factors (TFs) and histone modifications (HMs) play critical roles in chromatin accessibility regulation. However, there is a lack of studies that quantify these relationships. Here we constructed a two-layer model to predict chromatin accessibility by integrating DNA sequence, TF binding, and HM signals. By applying the model to two human cell lines (GM12878 and HepG2), we found that DNA sequences had limited power for accessibility prediction, while both TF binding and HM signals predicted chromatin accessibility with high accuracy. According to the HM model, HM features determined chromatin accessibility in a cell line shared manner, with the prediction power attributing to five core HM types. Results from the TF model indicated that chromatin accessibility was determined by a subset of informative TFs including both cell line-specific and generic TFs. The combined model of both TF and HM signals did not further improve the prediction accuracy, indicating that they provide redundant information in terms of chromatin accessibility prediction. The TFs and HM models can also distinguish the chromatin accessibility of proximal versus distal transcription start sites with high accuracy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-08234-5. BioMed Central 2022-01-08 /pmc/articles/PMC8742372/ /pubmed/34996354 http://dx.doi.org/10.1186/s12864-021-08234-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhao, Yanding
Dong, Yadong
Hong, Wei
Jiang, Chongming
Yao, Kevin
Cheng, Chao
Computational modeling of chromatin accessibility identified important epigenomic regulators
title Computational modeling of chromatin accessibility identified important epigenomic regulators
title_full Computational modeling of chromatin accessibility identified important epigenomic regulators
title_fullStr Computational modeling of chromatin accessibility identified important epigenomic regulators
title_full_unstemmed Computational modeling of chromatin accessibility identified important epigenomic regulators
title_short Computational modeling of chromatin accessibility identified important epigenomic regulators
title_sort computational modeling of chromatin accessibility identified important epigenomic regulators
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8742372/
https://www.ncbi.nlm.nih.gov/pubmed/34996354
http://dx.doi.org/10.1186/s12864-021-08234-5
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