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Updated: Sep 2, 2025
High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy
Published on: February 7, 2019
SEMplMe: a tool for integrating DNA methylation effects in transcription factor binding affinity predictions
Sierra S Nishizaki1,2, Alan P Boyle3,4
1Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48109, USA.
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 .
