Abstract

Motivation

Aberrant DNA methylation in transcription factor binding sites has been shown to lead to anomalous gene regulation that is strongly associated with human disease. However, the majority of methylation-sensitive positions within transcription factor binding sites remain unknown. Here we introduce SEMplMe, a computational tool to generate predictions of the effect of methylation on transcription factor binding strength in every position within a transcription factor’s motif.

Results

SEMplMe uses ChIP-seq and whole genome bisulfite sequencing to predict effects of methylation within binding sites. SEMplMe validates known methylation sensitive and insensitive positions within a binding motif, identifies cell type specific transcription factor binding driven by methylation, and outperforms SELEX-based predictions for CTCF. These predictions can be used to identify aberrant sites of DNA methylation contributing to human disease.

Availability and Implementation

SEMplMe is available from https://github.com/Boyle-Lab/SEMplMe.

Details

Title
SEMplMe: a tool for integrating DNA methylation effects in transcription factor binding affinity predictions
Author
Nishizaki, Sierra S  VIAFID ORCID Logo  ; Boyle, Alan P  VIAFID ORCID Logo 
Pages
1-14
Section
Software
Publication year
2022
Publication date
2022
Publisher
BioMed Central
e-ISSN
14712105
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2703765950
Copyright
© 2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.