Predictive models of gene regulation from high-throughput epigenomics data

Mostra el registre complet Registre parcial de l'ítem

• dc.contributor.author Althammer, Sonja Danielaca
• dc.contributor.author Pagès Pinós, Amadísca
• dc.contributor.author Eyras Jiménez, Eduardoca
• dc.date.accessioned 2015-12-07T19:01:54Z
• dc.date.available 2015-12-07T19:01:54Z
• dc.date.issued 2012
• dc.description.abstract The epigenetic regulation of gene expression involves multiple factors. The synergistic or antagonistic action of these factors has suggested the existence of an epigenetic code for gene regulation. Highthroughput sequencing (HTS) provides an opportunity to explore this code and to build quantitative models of gene regulation based on epigenetic differences between specific cellular conditions. We describe a new computational framework that facilitates the systematic integration of HTS epigenetic data. Our method relates epigenetic signals to expression by comparing two conditions. We show its effectiveness by building a model that predicts with high accuracy significant expression differences between two cell lines, using epigenetic data from the ENCODE project. Our analyses provide evidence for a degenerate epigenetic code, which involves multiple genic regions. In particular, signal changes at the 1st exon, 1st intron, and downstream of the polyadenylation site are found to associate strongly with expression regulation. Our analyses also show a different epigenetic code for intron-less and intron-containing genes. Our work provides a general methodology to do integrative analysis of epigenetic differences between cellular conditions that can be applied to other studies, like cell differentiation or carcinogenesis.ca
• dc.description.sponsorship This work was supported by Grants BIO2011-23920 and CSD2009-00080 from the Spanish Ministry of/nScience and by the Sandra Ibarra Foundation. S. Althammer was supported by an FI grant from the Generalitat de Catalunya
• dc.format.mimetype application/pdfca
• dc.identifier.citation Althammer SD, Pagès Pinós A, Eyras Jiménez E. Predictive models of gene regulation from high-throughput epigenomics data. Comparative and functional genomics. 2012;2012:284786. DOI: 10.1155/2012/284786ca
• dc.identifier.doi http://dx.doi.org/10.1155/2012/284786
• dc.identifier.issn 1531-6912
• dc.identifier.uri http://hdl.handle.net/10230/25346
• dc.language.iso engca
• dc.publisher Hindawica
• dc.relation.ispartof Comparative and functional genomics. 2012;2012:284786
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/BIO2011-23920
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/CSD2009-00080
• dc.rights © 2012 Althammer S et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citedca
• dc.rights.accessRights info:eu-repo/semantics/openAccessca
• dc.subject.other Epigènesica
• dc.title Predictive models of gene regulation from high-throughput epigenomics dataca
• dc.type info:eu-repo/semantics/articleca
• dc.type.version info:eu-repo/semantics/publishedVersionca