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

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...

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Bibliographic Details
Published in:BMC bioinformatics 2021-05, Vol.22 (1), p.278-278, Article 278
Main Authors: Scala, Giovanni, Federico, Antonio, Greco, Dario
Format: Article
Language:English
Subjects:
Analysis
Binding sites
Central pattern generators
Composition
Computer applications
CpG Islands
Deoxyribonucleic acid
Deregulation
DNA
DNA Methylation
DNA methylation signature
DNA motifs
Eukaryotes
Experiments
Gene sequencing
Genome, Human
Genomes
Humans
Medical research
Methylation
Nucleotide Motifs
Nucleotide sequence
R-Shiny
Software
Source code
Transcription factors
Trends
Citations: Items that this one cites
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Summary: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. 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. 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 .
ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-021-04191-8