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RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding

Gene regulatory regions contain short and degenerated DNA binding sites recognized by transcription factors (TFBS). When TFBS harbor SNPs, the DNA binding site may be affected, thereby altering the transcriptional regulation of the target genes. Such regulatory SNPs have been implicated as causal va...

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Autores principales: Santana-Garcia, Walter, Rocha-Acevedo, Maria, Ramirez-Navarro, Lucia, Mbouamboua, Yvon, Thieffry, Denis, Thomas-Chollier, Morgane, Contreras-Moreira, Bruno, van Helden, Jacques, Medina-Rivera, Alejandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906655/
https://www.ncbi.nlm.nih.gov/pubmed/31871587
http://dx.doi.org/10.1016/j.csbj.2019.09.009
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author Santana-Garcia, Walter
Rocha-Acevedo, Maria
Ramirez-Navarro, Lucia
Mbouamboua, Yvon
Thieffry, Denis
Thomas-Chollier, Morgane
Contreras-Moreira, Bruno
van Helden, Jacques
Medina-Rivera, Alejandra
author_facet Santana-Garcia, Walter
Rocha-Acevedo, Maria
Ramirez-Navarro, Lucia
Mbouamboua, Yvon
Thieffry, Denis
Thomas-Chollier, Morgane
Contreras-Moreira, Bruno
van Helden, Jacques
Medina-Rivera, Alejandra
author_sort Santana-Garcia, Walter
collection PubMed
description Gene regulatory regions contain short and degenerated DNA binding sites recognized by transcription factors (TFBS). When TFBS harbor SNPs, the DNA binding site may be affected, thereby altering the transcriptional regulation of the target genes. Such regulatory SNPs have been implicated as causal variants in Genome-Wide Association Study (GWAS) studies. In this study, we describe improved versions of the programs Variation-tools designed to predict regulatory variants, and present four case studies to illustrate their usage and applications. In brief, Variation-tools facilitate i) obtaining variation information, ii) interconversion of variation file formats, iii) retrieval of sequences surrounding variants, and iv) calculating the change on predicted transcription factor affinity scores between alleles, using motif scanning approaches. Notably, the tools support the analysis of haplotypes. The tools are included within the well-maintained suite Regulatory Sequence Analysis Tools (RSAT, http://rsat.eu), and accessible through a web interface that currently enables analysis of five metazoa and ten plant genomes. Variation-tools can also be used in command-line with any locally-installed Ensembl genome. Users can input personal collections of variants and motifs, providing flexibility in the analysis.
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spelling pubmed-69066552019-12-23 RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding Santana-Garcia, Walter Rocha-Acevedo, Maria Ramirez-Navarro, Lucia Mbouamboua, Yvon Thieffry, Denis Thomas-Chollier, Morgane Contreras-Moreira, Bruno van Helden, Jacques Medina-Rivera, Alejandra Comput Struct Biotechnol J Research Article Gene regulatory regions contain short and degenerated DNA binding sites recognized by transcription factors (TFBS). When TFBS harbor SNPs, the DNA binding site may be affected, thereby altering the transcriptional regulation of the target genes. Such regulatory SNPs have been implicated as causal variants in Genome-Wide Association Study (GWAS) studies. In this study, we describe improved versions of the programs Variation-tools designed to predict regulatory variants, and present four case studies to illustrate their usage and applications. In brief, Variation-tools facilitate i) obtaining variation information, ii) interconversion of variation file formats, iii) retrieval of sequences surrounding variants, and iv) calculating the change on predicted transcription factor affinity scores between alleles, using motif scanning approaches. Notably, the tools support the analysis of haplotypes. The tools are included within the well-maintained suite Regulatory Sequence Analysis Tools (RSAT, http://rsat.eu), and accessible through a web interface that currently enables analysis of five metazoa and ten plant genomes. Variation-tools can also be used in command-line with any locally-installed Ensembl genome. Users can input personal collections of variants and motifs, providing flexibility in the analysis. Research Network of Computational and Structural Biotechnology 2019-11-07 /pmc/articles/PMC6906655/ /pubmed/31871587 http://dx.doi.org/10.1016/j.csbj.2019.09.009 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Santana-Garcia, Walter
Rocha-Acevedo, Maria
Ramirez-Navarro, Lucia
Mbouamboua, Yvon
Thieffry, Denis
Thomas-Chollier, Morgane
Contreras-Moreira, Bruno
van Helden, Jacques
Medina-Rivera, Alejandra
RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding
title RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding
title_full RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding
title_fullStr RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding
title_full_unstemmed RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding
title_short RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding
title_sort rsat variation-tools: an accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906655/
https://www.ncbi.nlm.nih.gov/pubmed/31871587
http://dx.doi.org/10.1016/j.csbj.2019.09.009
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