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

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 in...

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Detalles Bibliográficos
Autores principales: Nishizaki, Sierra S., Boyle, Alan P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351228/
https://www.ncbi.nlm.nih.gov/pubmed/35927613
http://dx.doi.org/10.1186/s12859-022-04865-x
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04865-x.