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metagene Profiles Analyses Reveal Regulatory Element’s Factor-Specific Recruitment Patterns

ChIP-Sequencing (ChIP-Seq) provides a vast amount of information regarding the localization of proteins across the genome. The aggregation of ChIP-Seq enrichment signal in a metagene plot is an approach commonly used to summarize data complexity and to obtain a high level visual representation of th...

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Autores principales: Joly Beauparlant, Charles, Lamaze, Fabien C., Deschênes, Astrid, Samb, Rawane, Lemaçon, Audrey, Belleau, Pascal, Bilodeau, Steve, Droit, Arnaud
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4990179/
https://www.ncbi.nlm.nih.gov/pubmed/27538250
http://dx.doi.org/10.1371/journal.pcbi.1004751
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author Joly Beauparlant, Charles
Lamaze, Fabien C.
Deschênes, Astrid
Samb, Rawane
Lemaçon, Audrey
Belleau, Pascal
Bilodeau, Steve
Droit, Arnaud
author_facet Joly Beauparlant, Charles
Lamaze, Fabien C.
Deschênes, Astrid
Samb, Rawane
Lemaçon, Audrey
Belleau, Pascal
Bilodeau, Steve
Droit, Arnaud
author_sort Joly Beauparlant, Charles
collection PubMed
description ChIP-Sequencing (ChIP-Seq) provides a vast amount of information regarding the localization of proteins across the genome. The aggregation of ChIP-Seq enrichment signal in a metagene plot is an approach commonly used to summarize data complexity and to obtain a high level visual representation of the general occupancy pattern of a protein. Here we present the R package metagene, the graphical interface Imetagene and the companion package similaRpeak. Together, they provide a framework to integrate, summarize and compare the ChIP-Seq enrichment signal from complex experimental designs. Those packages identify and quantify similarities or dissimilarities in patterns between large numbers of ChIP-Seq profiles. We used metagene to investigate the differential occupancy of regulatory factors at noncoding regulatory regions (promoters and enhancers) in relation to transcriptional activity in GM12878 B-lymphocytes. The relationships between occupancy patterns and transcriptional activity suggest two different mechanisms of action for transcriptional control: i) a “gradient effect” where the regulatory factor occupancy levels follow transcription and ii) a “threshold effect” where the regulatory factor occupancy levels max out prior to reaching maximal transcription. metagene, Imetagene and similaRpeak are implemented in R under the Artistic license 2.0 and are available on Bioconductor.
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spelling pubmed-49901792016-08-29 metagene Profiles Analyses Reveal Regulatory Element’s Factor-Specific Recruitment Patterns Joly Beauparlant, Charles Lamaze, Fabien C. Deschênes, Astrid Samb, Rawane Lemaçon, Audrey Belleau, Pascal Bilodeau, Steve Droit, Arnaud PLoS Comput Biol Research Article ChIP-Sequencing (ChIP-Seq) provides a vast amount of information regarding the localization of proteins across the genome. The aggregation of ChIP-Seq enrichment signal in a metagene plot is an approach commonly used to summarize data complexity and to obtain a high level visual representation of the general occupancy pattern of a protein. Here we present the R package metagene, the graphical interface Imetagene and the companion package similaRpeak. Together, they provide a framework to integrate, summarize and compare the ChIP-Seq enrichment signal from complex experimental designs. Those packages identify and quantify similarities or dissimilarities in patterns between large numbers of ChIP-Seq profiles. We used metagene to investigate the differential occupancy of regulatory factors at noncoding regulatory regions (promoters and enhancers) in relation to transcriptional activity in GM12878 B-lymphocytes. The relationships between occupancy patterns and transcriptional activity suggest two different mechanisms of action for transcriptional control: i) a “gradient effect” where the regulatory factor occupancy levels follow transcription and ii) a “threshold effect” where the regulatory factor occupancy levels max out prior to reaching maximal transcription. metagene, Imetagene and similaRpeak are implemented in R under the Artistic license 2.0 and are available on Bioconductor. Public Library of Science 2016-08-18 /pmc/articles/PMC4990179/ /pubmed/27538250 http://dx.doi.org/10.1371/journal.pcbi.1004751 Text en © 2016 Joly Beauparlant et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Joly Beauparlant, Charles
Lamaze, Fabien C.
Deschênes, Astrid
Samb, Rawane
Lemaçon, Audrey
Belleau, Pascal
Bilodeau, Steve
Droit, Arnaud
metagene Profiles Analyses Reveal Regulatory Element’s Factor-Specific Recruitment Patterns
title metagene Profiles Analyses Reveal Regulatory Element’s Factor-Specific Recruitment Patterns
title_full metagene Profiles Analyses Reveal Regulatory Element’s Factor-Specific Recruitment Patterns
title_fullStr metagene Profiles Analyses Reveal Regulatory Element’s Factor-Specific Recruitment Patterns
title_full_unstemmed metagene Profiles Analyses Reveal Regulatory Element’s Factor-Specific Recruitment Patterns
title_short metagene Profiles Analyses Reveal Regulatory Element’s Factor-Specific Recruitment Patterns
title_sort metagene profiles analyses reveal regulatory element’s factor-specific recruitment patterns
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4990179/
https://www.ncbi.nlm.nih.gov/pubmed/27538250
http://dx.doi.org/10.1371/journal.pcbi.1004751
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