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MeDReaders: a database for transcription factors that bind to methylated DNA

Understanding the molecular principles governing interactions between transcription factors (TFs) and DNA targets is one of the main subjects for transcriptional regulation. Recently, emerging evidence demonstrated that some TFs could bind to DNA motifs containing highly methylated CpGs both in vitr...

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Detalles Bibliográficos
Autores principales: Wang, Guohua, Luo, Ximei, Wang, Jianan, Wan, Jun, Xia, Shuli, Zhu, Heng, Qian, Jiang, Wang, Yadong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753207/
https://www.ncbi.nlm.nih.gov/pubmed/29145608
http://dx.doi.org/10.1093/nar/gkx1096
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author Wang, Guohua
Luo, Ximei
Wang, Jianan
Wan, Jun
Xia, Shuli
Zhu, Heng
Qian, Jiang
Wang, Yadong
author_facet Wang, Guohua
Luo, Ximei
Wang, Jianan
Wan, Jun
Xia, Shuli
Zhu, Heng
Qian, Jiang
Wang, Yadong
author_sort Wang, Guohua
collection PubMed
description Understanding the molecular principles governing interactions between transcription factors (TFs) and DNA targets is one of the main subjects for transcriptional regulation. Recently, emerging evidence demonstrated that some TFs could bind to DNA motifs containing highly methylated CpGs both in vitro and in vivo. Identification of such TFs and elucidation of their physiological roles now become an important stepping-stone toward understanding the mechanisms underlying the methylation-mediated biological processes, which have crucial implications for human disease and disease development. Hence, we constructed a database, named as MeDReaders, to collect information about methylated DNA binding activities. A total of 731 TFs, which could bind to methylated DNA sequences, were manually curated in human and mouse studies reported in the literature. In silico approaches were applied to predict methylated and unmethylated motifs of 292 TFs by integrating whole genome bisulfite sequencing (WGBS) and ChIP-Seq datasets in six human cell lines and one mouse cell line extracted from ENCODE and GEO database. MeDReaders database will provide a comprehensive resource for further studies and aid related experiment designs. The database implemented unified access for users to most TFs involved in such methylation-associated binding actives. The website is available at http://medreader.org/.
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spelling pubmed-57532072018-01-05 MeDReaders: a database for transcription factors that bind to methylated DNA Wang, Guohua Luo, Ximei Wang, Jianan Wan, Jun Xia, Shuli Zhu, Heng Qian, Jiang Wang, Yadong Nucleic Acids Res Database Issue Understanding the molecular principles governing interactions between transcription factors (TFs) and DNA targets is one of the main subjects for transcriptional regulation. Recently, emerging evidence demonstrated that some TFs could bind to DNA motifs containing highly methylated CpGs both in vitro and in vivo. Identification of such TFs and elucidation of their physiological roles now become an important stepping-stone toward understanding the mechanisms underlying the methylation-mediated biological processes, which have crucial implications for human disease and disease development. Hence, we constructed a database, named as MeDReaders, to collect information about methylated DNA binding activities. A total of 731 TFs, which could bind to methylated DNA sequences, were manually curated in human and mouse studies reported in the literature. In silico approaches were applied to predict methylated and unmethylated motifs of 292 TFs by integrating whole genome bisulfite sequencing (WGBS) and ChIP-Seq datasets in six human cell lines and one mouse cell line extracted from ENCODE and GEO database. MeDReaders database will provide a comprehensive resource for further studies and aid related experiment designs. The database implemented unified access for users to most TFs involved in such methylation-associated binding actives. The website is available at http://medreader.org/. Oxford University Press 2018-01-04 2017-11-14 /pmc/articles/PMC5753207/ /pubmed/29145608 http://dx.doi.org/10.1093/nar/gkx1096 Text en © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
Wang, Guohua
Luo, Ximei
Wang, Jianan
Wan, Jun
Xia, Shuli
Zhu, Heng
Qian, Jiang
Wang, Yadong
MeDReaders: a database for transcription factors that bind to methylated DNA
title MeDReaders: a database for transcription factors that bind to methylated DNA
title_full MeDReaders: a database for transcription factors that bind to methylated DNA
title_fullStr MeDReaders: a database for transcription factors that bind to methylated DNA
title_full_unstemmed MeDReaders: a database for transcription factors that bind to methylated DNA
title_short MeDReaders: a database for transcription factors that bind to methylated DNA
title_sort medreaders: a database for transcription factors that bind to methylated dna
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753207/
https://www.ncbi.nlm.nih.gov/pubmed/29145608
http://dx.doi.org/10.1093/nar/gkx1096
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