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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
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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. |
format | Text |
id | pubmed-3089487 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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