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Identification of methylation states of DNA regions for Illumina methylation BeadChip

BACKGROUND: Methylation of cytosine bases in DNA is a critical epigenetic mark in many eukaryotes and has also been implicated in the development and progression of normal and diseased cells. Therefore, profiling DNA methylation across the genome is vital to understanding the effects of epigenetic....

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Autores principales: Luo, Ximei, Wang, Fang, Wang, Guohua, Zhao, Yuming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057447/
https://www.ncbi.nlm.nih.gov/pubmed/32138668
http://dx.doi.org/10.1186/s12864-019-6019-0
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author Luo, Ximei
Wang, Fang
Wang, Guohua
Zhao, Yuming
author_facet Luo, Ximei
Wang, Fang
Wang, Guohua
Zhao, Yuming
author_sort Luo, Ximei
collection PubMed
description BACKGROUND: Methylation of cytosine bases in DNA is a critical epigenetic mark in many eukaryotes and has also been implicated in the development and progression of normal and diseased cells. Therefore, profiling DNA methylation across the genome is vital to understanding the effects of epigenetic. In recent years the Illumina HumanMethylation450 (HM450K) and MethylationEPIC (EPIC) BeadChip have been widely used to profile DNA methylation in human samples. The methods to predict the methylation states of DNA regions based on microarray methylation datasets are critical to enable genome-wide analyses. RESULT: We report a computational approach based on the two layers two-state hidden Markov model (HMM) to identify methylation states of single CpG site and DNA regions in HM450K and EPIC BeadChip. Using this mothed, all CpGs detected by HM450K and EPIC in H1-hESC and GM12878 cell lines are identified as un-methylated, middle-methylated and full-methylated states. A large number of DNA regions are segmented into three methylation states as well. Comparing the identified regions with the result from the whole genome bisulfite sequencing (WGBS) datasets segmented by MethySeekR, our method is verified. Genome-wide maps of chromatin states show that methylation state is inversely correlated with active histone marks. Genes regulated by un-methylated regions are expressed and regulated by full-methylated regions are repressed. Our method is illustrated to be useful and robust. CONCLUSION: Our method is valuable for DNA methylation genome-wide analyses. It is focusing on identification of DNA methylation states on microarray methylation datasets. For the features of array datasets, using two layers two-state HMM to identify to methylation states on CpG sites and regions creatively, our method which takes into account the distribution of genome-wide methylation levels is more reasonable than segmentation with a fixed threshold. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-6019-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-70574472020-03-10 Identification of methylation states of DNA regions for Illumina methylation BeadChip Luo, Ximei Wang, Fang Wang, Guohua Zhao, Yuming BMC Genomics Methodology BACKGROUND: Methylation of cytosine bases in DNA is a critical epigenetic mark in many eukaryotes and has also been implicated in the development and progression of normal and diseased cells. Therefore, profiling DNA methylation across the genome is vital to understanding the effects of epigenetic. In recent years the Illumina HumanMethylation450 (HM450K) and MethylationEPIC (EPIC) BeadChip have been widely used to profile DNA methylation in human samples. The methods to predict the methylation states of DNA regions based on microarray methylation datasets are critical to enable genome-wide analyses. RESULT: We report a computational approach based on the two layers two-state hidden Markov model (HMM) to identify methylation states of single CpG site and DNA regions in HM450K and EPIC BeadChip. Using this mothed, all CpGs detected by HM450K and EPIC in H1-hESC and GM12878 cell lines are identified as un-methylated, middle-methylated and full-methylated states. A large number of DNA regions are segmented into three methylation states as well. Comparing the identified regions with the result from the whole genome bisulfite sequencing (WGBS) datasets segmented by MethySeekR, our method is verified. Genome-wide maps of chromatin states show that methylation state is inversely correlated with active histone marks. Genes regulated by un-methylated regions are expressed and regulated by full-methylated regions are repressed. Our method is illustrated to be useful and robust. CONCLUSION: Our method is valuable for DNA methylation genome-wide analyses. It is focusing on identification of DNA methylation states on microarray methylation datasets. For the features of array datasets, using two layers two-state HMM to identify to methylation states on CpG sites and regions creatively, our method which takes into account the distribution of genome-wide methylation levels is more reasonable than segmentation with a fixed threshold. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-6019-0) contains supplementary material, which is available to authorized users. BioMed Central 2020-03-05 /pmc/articles/PMC7057447/ /pubmed/32138668 http://dx.doi.org/10.1186/s12864-019-6019-0 Text en © The Author(s). 2020 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 Methodology
Luo, Ximei
Wang, Fang
Wang, Guohua
Zhao, Yuming
Identification of methylation states of DNA regions for Illumina methylation BeadChip
title Identification of methylation states of DNA regions for Illumina methylation BeadChip
title_full Identification of methylation states of DNA regions for Illumina methylation BeadChip
title_fullStr Identification of methylation states of DNA regions for Illumina methylation BeadChip
title_full_unstemmed Identification of methylation states of DNA regions for Illumina methylation BeadChip
title_short Identification of methylation states of DNA regions for Illumina methylation BeadChip
title_sort identification of methylation states of dna regions for illumina methylation beadchip
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057447/
https://www.ncbi.nlm.nih.gov/pubmed/32138668
http://dx.doi.org/10.1186/s12864-019-6019-0
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