Please use this identifier to cite or link to this item: https://doi.org/10.1093/nar/gky1005
Title: MethMotif: an integrative cell specific database of transcription factor binding motifs coupled with DNA methylation profiles
Authors: Lin, Quy Xiao Xuan
Sian, Stephanie 
An, Omer 
Thieffry, Denis 
Jha, Sudhakar 
Benoukraf, Touati 
Keywords: Science & Technology
Life Sciences & Biomedicine
Biochemistry & Molecular Biology
GENE
DIMERIZATION
RECOGNITION
ACTIVATION
EXPRESSION
CHROMATIN
ADJACENT
MOUSE
KAISO
READ
Issue Date: 8-Jan-2019
Publisher: OXFORD UNIV PRESS
Citation: Lin, Quy Xiao Xuan, Sian, Stephanie, An, Omer, Thieffry, Denis, Jha, Sudhakar, Benoukraf, Touati (2019-01-08). MethMotif: an integrative cell specific database of transcription factor binding motifs coupled with DNA methylation profiles. NUCLEIC ACIDS RESEARCH 47 (D1) : D145-D154. ScholarBank@NUS Repository. https://doi.org/10.1093/nar/gky1005
Abstract: © The Author(s) 2018. Several recent studies have portrayed DNA methylation as a new player in the recruitment of transcription factors (TF) within chromatin, highlighting a need to connect TF binding sites (TFBS) with their respective DNA methylation profiles. However, current TFBS databases are restricted to DNA binding motif sequences. Here, we present MethMotif, a two-dimensional TFBS database that records TFBS position weight matrices along with cell type specific CpG methylation information computed from a combination of ChIP-seq and whole genome bisulfite sequencing datasets. Integrating TFBS motifs with TFBS DNA methylation better portrays the features of DNA loci recognised by TFs. In particular, we found that DNA methylation patterns within TFBS can be cell specific (e.g. MAFF). Furthermore, for a given TF, different DNA methylation profiles are associated with different DNA binding motifs (e.g. REST). To date, MethMotif database records over 500 TFBSs computed from over 2000 ChIP-seq datasets in 11 different cell types. MethMotif portal is accessible through an open source web interface (https://bioinfo-csi.nus.edu.sg/methmotif) that allowsusers to intuitively explore the entire dataset and perform both single, and batch queries.
Source Title: NUCLEIC ACIDS RESEARCH
URI: https://scholarbank.nus.edu.sg/handle/10635/155185
ISSN: 0305-1048
1362-4962
DOI: 10.1093/nar/gky1005
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