Introduction

The interaction between transcription factors (TFs) and DNA targets is one of main subjects in gene regulation studies. It was acknowledged that DNA methylation would interfere with TF binding, while only proteins with a methyl-CpG binding domain (MBD) and several zinc finger proteins were recognized to bind to methylated DNA sequences. However, more evidence emerged recently to demonstrate that some TFs lack of a MBD can also interact with DNA in the manner of high methylation. Identification of such TFs and elucidation of their characteristics become important stepping stones towards understanding the mechanism hidden in these methylation-mediated biological processes, which have crucial implications for human disease and disease development.

We collected information about methylated DNA binding activities from two major sources: ENCODE database and published literatures. In silico method was adopted to predict methylated motifs by integrating whole genome bisulfite sequencing (WGBS) and ChIP-seq data from ENCODE database. We also manually distinguished more TFs which bind to methylated DNA sequences by reviewing relevant publications. Taking together, a new database, dubbed as methylated DNA readers (MeDReaders), was developed systematically to provide a comprehensive resource. It implemented unified access for users to most TFs involved in such methylation-associated binding actives and their corresponding binding motifs and sequences in different species and different cell lines and tissues. It also supported expert users in appending more evidences for us to expand the knowledge of our database.

The current version of the database allows users to

1. achieve methylated DNA binding motifs of TFs of user's interest or search potential TFs by matching methylated binding sequences as user requested.
2. obtain and/or compare methylation contexts of the same TF under different cell lines and/or tissues.
3. download position weight matrix (PWM) of TFs associated with methylation status (high or low methylation).
4. submit newly published information of methylated-DNA binding TFs to enrich our database.

Statistics

Transcription factors summarized from published literatures:

Species	No. of TFs	No. of Cells/Tissues
Human	601	4
Mouse	130	4

Transcription factors inferred by sillco method based on WGBS and ChIP-seq datasets:

Species	Cell/Tissue	No. of TFs
Human	GM12878	44
Human	H1-hESC	33
Human	HCT116	5
Human	HepG2	89
Human	IMR-90	6
Human	K562	110
Mouse	E14	5

Release and Version Information

Jul. 1, 2017, MeDReaders: A database for Methylated DNA Readers v1.0 was released.

Contact

Guohua Wang, professor
Harbin Institute of Technology, Harbin 150001, China
Mail: ghwang@hit.edu.cn