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QDMR: a quantitative method for identification of differentially methylated regions by entropy

DNA methylation plays critical roles in transcriptional regulation and chromatin remodeling. Differentially methylated regions (DMRs) have important implications for development, aging and diseases. Therefore, genome-wide mapping of DMRs across various temporal and spatial methylomes is important in...

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Autores principales: Zhang, Yan, Liu, Hongbo, Lv, Jie, Xiao, Xue, Zhu, Jiang, Liu, Xiaojuan, Su, Jianzhong, Li, Xia, Wu, Qiong, Wang, Fang, Cui, Ying
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3089487/
https://www.ncbi.nlm.nih.gov/pubmed/21306990
http://dx.doi.org/10.1093/nar/gkr053
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author Zhang, Yan
Liu, Hongbo
Lv, Jie
Xiao, Xue
Zhu, Jiang
Liu, Xiaojuan
Su, Jianzhong
Li, Xia
Wu, Qiong
Wang, Fang
Cui, Ying
author_facet Zhang, Yan
Liu, Hongbo
Lv, Jie
Xiao, Xue
Zhu, Jiang
Liu, Xiaojuan
Su, Jianzhong
Li, Xia
Wu, Qiong
Wang, Fang
Cui, Ying
author_sort Zhang, Yan
collection PubMed
description DNA methylation plays critical roles in transcriptional regulation and chromatin remodeling. Differentially methylated regions (DMRs) have important implications for development, aging and diseases. Therefore, genome-wide mapping of DMRs across various temporal and spatial methylomes is important in revealing the impact of epigenetic modifications on heritable phenotypic variation. We present a quantitative approach, quantitative differentially methylated regions (QDMRs), to quantify methylation difference and identify DMRs from genome-wide methylation profiles by adapting Shannon entropy. QDMR was applied to synthetic methylation patterns and methylation profiles detected by methylated DNA immunoprecipitation microarray (MeDIP-chip) in human tissues/cells. This approach can give a reasonable quantitative measure of methylation difference across multiple samples. Then DMR threshold was determined from methylation probability model. Using this threshold, QDMR identified 10 651 tissue DMRs which are related to the genes enriched for cell differentiation, including 4740 DMRs not identified by the method developed by Rakyan et al. QDMR can also measure the sample specificity of each DMR. Finally, the application to methylation profiles detected by reduced representation bisulphite sequencing (RRBS) in mouse showed the platform-free and species-free nature of QDMR. This approach provides an effective tool for the high-throughput identification of potential functional regions involved in epigenetic regulation.
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spelling pubmed-30894872011-05-09 QDMR: a quantitative method for identification of differentially methylated regions by entropy Zhang, Yan Liu, Hongbo Lv, Jie Xiao, Xue Zhu, Jiang Liu, Xiaojuan Su, Jianzhong Li, Xia Wu, Qiong Wang, Fang Cui, Ying Nucleic Acids Res Methods Online DNA methylation plays critical roles in transcriptional regulation and chromatin remodeling. Differentially methylated regions (DMRs) have important implications for development, aging and diseases. Therefore, genome-wide mapping of DMRs across various temporal and spatial methylomes is important in revealing the impact of epigenetic modifications on heritable phenotypic variation. We present a quantitative approach, quantitative differentially methylated regions (QDMRs), to quantify methylation difference and identify DMRs from genome-wide methylation profiles by adapting Shannon entropy. QDMR was applied to synthetic methylation patterns and methylation profiles detected by methylated DNA immunoprecipitation microarray (MeDIP-chip) in human tissues/cells. This approach can give a reasonable quantitative measure of methylation difference across multiple samples. Then DMR threshold was determined from methylation probability model. Using this threshold, QDMR identified 10 651 tissue DMRs which are related to the genes enriched for cell differentiation, including 4740 DMRs not identified by the method developed by Rakyan et al. QDMR can also measure the sample specificity of each DMR. Finally, the application to methylation profiles detected by reduced representation bisulphite sequencing (RRBS) in mouse showed the platform-free and species-free nature of QDMR. This approach provides an effective tool for the high-throughput identification of potential functional regions involved in epigenetic regulation. Oxford University Press 2011-05 2011-02-08 /pmc/articles/PMC3089487/ /pubmed/21306990 http://dx.doi.org/10.1093/nar/gkr053 Text en © The Author(s) 2011. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods Online
Zhang, Yan
Liu, Hongbo
Lv, Jie
Xiao, Xue
Zhu, Jiang
Liu, Xiaojuan
Su, Jianzhong
Li, Xia
Wu, Qiong
Wang, Fang
Cui, Ying
QDMR: a quantitative method for identification of differentially methylated regions by entropy
title QDMR: a quantitative method for identification of differentially methylated regions by entropy
title_full QDMR: a quantitative method for identification of differentially methylated regions by entropy
title_fullStr QDMR: a quantitative method for identification of differentially methylated regions by entropy
title_full_unstemmed QDMR: a quantitative method for identification of differentially methylated regions by entropy
title_short QDMR: a quantitative method for identification of differentially methylated regions by entropy
title_sort qdmr: a quantitative method for identification of differentially methylated regions by entropy
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3089487/
https://www.ncbi.nlm.nih.gov/pubmed/21306990
http://dx.doi.org/10.1093/nar/gkr053
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