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

Giovanni Scala; Antonio Federico; Dario Greco

doi:10.1186/s12859-021-04191-8

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

Giovanni Scala, Antonio Federico, Dario Greco

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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 language	English
Article number	278
Journal	BMC Bioinformatics
Volume	22
DOIs	https://doi.org/10.1186/s12859-021-04191-8
Publication status	Published - May 2021
Publication type	A1 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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10.1186/s12859-021-04191-8Licence: CC BY

s12859-021-04191-8Final published version, 1.15 MBLicence: CC BY

http://urn.fi/URN:NBN:fi:tuni-202107046181Licence: CC BY

Cite this

@article{a5ec328e0b234cfba4afe87f44587bdd,

title = "CpGmotifs: a tool to discover DNA motifs associated to CpG methylation events",

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.",

keywords = "DNA methylation, DNA methylation signature, DNA motifs, R-Shiny, Transcription factors",

author = "Giovanni Scala and Antonio Federico and Dario Greco",

note = "Funding Information: This study received funding from EU IMI2 project Biomap (Grant Agreement 821511). The funding body was not involved in the design of the study, collection, analysis, and interpretation of data, or in writing the manuscript. ",

year = "2021",

month = may,

doi = "10.1186/s12859-021-04191-8",

language = "English",

volume = "22",

journal = "BMC Bioinformatics",

issn = "1471-2105",

publisher = "Springer Verlag",

}

TY - JOUR

T1 - CpGmotifs

T2 - a tool to discover DNA motifs associated to CpG methylation events

AU - Scala, Giovanni

AU - Federico, Antonio

AU - Greco, Dario

N1 - Funding Information: This study received funding from EU IMI2 project Biomap (Grant Agreement 821511). The funding body was not involved in the design of the study, collection, analysis, and interpretation of data, or in writing the manuscript.

PY - 2021/5

Y1 - 2021/5

N2 - 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.

AB - 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.

KW - DNA methylation

KW - DNA methylation signature

KW - DNA motifs

KW - R-Shiny

KW - Transcription factors

U2 - 10.1186/s12859-021-04191-8

DO - 10.1186/s12859-021-04191-8

M3 - Article

C2 - 34039269

AN - SCOPUS:85106856567

SN - 1471-2105

VL - 22

JO - BMC Bioinformatics

JF - BMC Bioinformatics

M1 - 278

ER -

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

Abstract

Keywords

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ASJC Scopus subject areas

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