CpGmotifs: a tool to discover DNA motifs associated to CpG methylation events

Giovanni Scala, Antonio Federico, Dario Greco

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Background: The investigation of molecular alterations associated with the conservation and variation of DNA methylation in eukaryotes is gaining interest in the biomedical research community. Among the different determinants of methylation stability, the DNA composition of the CpG surrounding regions has been shown to have a crucial role in the maintenance and establishment of methylation statuses. This aspect has been previously characterized in a quantitative manner by inspecting the nucleotidic composition in the region. Research in this field still lacks a qualitative perspective, linked to the identification of certain sequences (or DNA motifs) related to particular DNA methylation phenomena. Results: Here we present a novel computational strategy based on short DNA motif discovery in order to characterize sequence patterns related to aberrant CpG methylation events. We provide our framework as a user-friendly, shiny-based application, CpGmotifs, to easily retrieve and characterize DNA patterns related to CpG methylation in the human genome. Our tool supports the functional interpretation of deregulated methylation events by predicting transcription factors binding sites (TFBS) encompassing the identified motifs. Conclusions: CpGmotifs is an open source software. Its source code is available on GitHub https://github.com/Greco-Lab/CpGmotifs and a ready-to-use docker image is provided on DockerHub at https://hub.docker.com/r/grecolab/cpgmotifs.

Original languageEnglish
Article number278
JournalBMC Bioinformatics
Volume22
DOIs
Publication statusPublished - May 2021
Publication typeA1 Journal article-refereed

Keywords

  • DNA methylation
  • DNA methylation signature
  • DNA motifs
  • R-Shiny
  • Transcription factors

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

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

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