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MethMotif: an integrative cell specific database of transcription factor binding motifs coupled with DNA methylation profiles. (Nucleic Acids Res, Oct 2018)

Xuan Lin QX1, Sian S1, An O1, Thieffry D2, Jha S1,3, Benoukraf T1,4.

Author information
1Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore.
2Computational Systems Biology Team, Institut de Biologie de l’École Normale Supérieure (IBENS), INSERM, École Normale Supérieure, PSL Research University, Paris, France.
3Department of Biochemistry, National University of Singapore, Singapore, Singapore.
4Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, NL, Canada.

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 ( that allows users to intuitively explore the entire dataset and perform both single, and batch queries.

PMID: 30380113