author_facet Tang, Binhua
Zhou, Yufan
Wang, Chiou-Miin
Huang, Tim H.-M.
Jin, Victor X.
Tang, Binhua
Zhou, Yufan
Wang, Chiou-Miin
Huang, Tim H.-M.
Jin, Victor X.
author Tang, Binhua
Zhou, Yufan
Wang, Chiou-Miin
Huang, Tim H.-M.
Jin, Victor X.
spellingShingle Tang, Binhua
Zhou, Yufan
Wang, Chiou-Miin
Huang, Tim H.-M.
Jin, Victor X.
Scientific Reports
Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
Multidisciplinary
author_sort tang, binhua
spelling Tang, Binhua Zhou, Yufan Wang, Chiou-Miin Huang, Tim H.-M. Jin, Victor X. 2045-2322 Springer Science and Business Media LLC Multidisciplinary http://dx.doi.org/10.1038/s41598-017-03837-z <jats:title>Abstract</jats:title><jats:p>Despite numerous studies done on understanding the role of DNA methylation, limited work has focused on systems integration of cell type-specific interplay between DNA methylation and gene transcription. Through a genome-wide analysis of DNA methylation across 19 cell types with T-47D as reference, we identified 106,252 cell type-specific differentially-methylated CpGs categorized into 7,537 differentially (46.6% hyper- and 53.4% hypo-) methylated regions. We found 44% promoter regions and 75% CpG islands were T-47D cell type-specific methylated. Pyrosequencing experiments validated the cell type-specific methylation across three benchmark cell lines. Interestingly, these DMRs overlapped with 1,145 known tumor suppressor genes. We then developed a Bayesian Gaussian Regression model to measure the relationship among DNA methylation, genomic segment distribution, differential gene expression and tumor suppressor gene status. The model uncovered that 3′UTR methylation has much less impact on transcriptional activity than other regions. Integration of DNA methylation and 82 transcription factor binding information across the 19 cell types suggested diverse interplay patterns between the two regulators. Our integrative analysis reveals cell type-specific and genomic region-dependent regulatory patterns and provides a perspective for integrating hundreds of various omics-seq data together.</jats:p> Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns Scientific Reports
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title Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
title_unstemmed Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
title_full Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
title_fullStr Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
title_full_unstemmed Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
title_short Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
title_sort integration of dna methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
topic Multidisciplinary
url http://dx.doi.org/10.1038/s41598-017-03837-z
publishDate 2017
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description <jats:title>Abstract</jats:title><jats:p>Despite numerous studies done on understanding the role of DNA methylation, limited work has focused on systems integration of cell type-specific interplay between DNA methylation and gene transcription. Through a genome-wide analysis of DNA methylation across 19 cell types with T-47D as reference, we identified 106,252 cell type-specific differentially-methylated CpGs categorized into 7,537 differentially (46.6% hyper- and 53.4% hypo-) methylated regions. We found 44% promoter regions and 75% CpG islands were T-47D cell type-specific methylated. Pyrosequencing experiments validated the cell type-specific methylation across three benchmark cell lines. Interestingly, these DMRs overlapped with 1,145 known tumor suppressor genes. We then developed a Bayesian Gaussian Regression model to measure the relationship among DNA methylation, genomic segment distribution, differential gene expression and tumor suppressor gene status. The model uncovered that 3′UTR methylation has much less impact on transcriptional activity than other regions. Integration of DNA methylation and 82 transcription factor binding information across the 19 cell types suggested diverse interplay patterns between the two regulators. Our integrative analysis reveals cell type-specific and genomic region-dependent regulatory patterns and provides a perspective for integrating hundreds of various omics-seq data together.</jats:p>
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author Tang, Binhua, Zhou, Yufan, Wang, Chiou-Miin, Huang, Tim H.-M., Jin, Victor X.
author_facet Tang, Binhua, Zhou, Yufan, Wang, Chiou-Miin, Huang, Tim H.-M., Jin, Victor X., Tang, Binhua, Zhou, Yufan, Wang, Chiou-Miin, Huang, Tim H.-M., Jin, Victor X.
author_sort tang, binhua
container_issue 1
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description <jats:title>Abstract</jats:title><jats:p>Despite numerous studies done on understanding the role of DNA methylation, limited work has focused on systems integration of cell type-specific interplay between DNA methylation and gene transcription. Through a genome-wide analysis of DNA methylation across 19 cell types with T-47D as reference, we identified 106,252 cell type-specific differentially-methylated CpGs categorized into 7,537 differentially (46.6% hyper- and 53.4% hypo-) methylated regions. We found 44% promoter regions and 75% CpG islands were T-47D cell type-specific methylated. Pyrosequencing experiments validated the cell type-specific methylation across three benchmark cell lines. Interestingly, these DMRs overlapped with 1,145 known tumor suppressor genes. We then developed a Bayesian Gaussian Regression model to measure the relationship among DNA methylation, genomic segment distribution, differential gene expression and tumor suppressor gene status. The model uncovered that 3′UTR methylation has much less impact on transcriptional activity than other regions. Integration of DNA methylation and 82 transcription factor binding information across the 19 cell types suggested diverse interplay patterns between the two regulators. Our integrative analysis reveals cell type-specific and genomic region-dependent regulatory patterns and provides a perspective for integrating hundreds of various omics-seq data together.</jats:p>
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spelling Tang, Binhua Zhou, Yufan Wang, Chiou-Miin Huang, Tim H.-M. Jin, Victor X. 2045-2322 Springer Science and Business Media LLC Multidisciplinary http://dx.doi.org/10.1038/s41598-017-03837-z <jats:title>Abstract</jats:title><jats:p>Despite numerous studies done on understanding the role of DNA methylation, limited work has focused on systems integration of cell type-specific interplay between DNA methylation and gene transcription. Through a genome-wide analysis of DNA methylation across 19 cell types with T-47D as reference, we identified 106,252 cell type-specific differentially-methylated CpGs categorized into 7,537 differentially (46.6% hyper- and 53.4% hypo-) methylated regions. We found 44% promoter regions and 75% CpG islands were T-47D cell type-specific methylated. Pyrosequencing experiments validated the cell type-specific methylation across three benchmark cell lines. Interestingly, these DMRs overlapped with 1,145 known tumor suppressor genes. We then developed a Bayesian Gaussian Regression model to measure the relationship among DNA methylation, genomic segment distribution, differential gene expression and tumor suppressor gene status. The model uncovered that 3′UTR methylation has much less impact on transcriptional activity than other regions. Integration of DNA methylation and 82 transcription factor binding information across the 19 cell types suggested diverse interplay patterns between the two regulators. Our integrative analysis reveals cell type-specific and genomic region-dependent regulatory patterns and provides a perspective for integrating hundreds of various omics-seq data together.</jats:p> Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns Scientific Reports
spellingShingle Tang, Binhua, Zhou, Yufan, Wang, Chiou-Miin, Huang, Tim H.-M., Jin, Victor X., Scientific Reports, Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns, Multidisciplinary
title Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
title_full Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
title_fullStr Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
title_full_unstemmed Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
title_short Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
title_sort integration of dna methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
title_unstemmed Integration of DNA methylation and gene transcription across nineteen cell types reveals cell type-specific and genomic region-dependent regulatory patterns
topic Multidisciplinary
url http://dx.doi.org/10.1038/s41598-017-03837-z