SEMplMe: a tool for integrating DNA methylation effects in transcription factor binding affinity predictions

Author:

Nishizaki Sierra S.ORCID,Boyle Alan P.ORCID

Abstract

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.

Funder

National Institutes of Health

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Databases and prospects of dynamic gene regulation in eukaryotes: A mini review;Computational and Structural Biotechnology Journal;2023

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