Reconstruction of composite regulator-target splicing networks from high-throughput transcriptome data

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• dc.contributor.author Papasaikas, Panagiotisca
• dc.contributor.author Rao, Arvindca
• dc.contributor.author Huggins, Peterca
• dc.contributor.author Valcárcel, J. (Juan)ca
• dc.contributor.author López Aldea, Javierca
• dc.date.accessioned 2015-11-25T17:22:29Z
• dc.date.available 2015-11-25T17:22:29Z
• dc.date.issued 2015ca
• dc.description.abstract We present a computational framework tailored for the modeling of the complex, dynamic relationships that are encountered in splicing regulation. The starting point is whole-genome transcriptomic data from high-throughput array or sequencing methods that are used to quantify gene expression and alternative splicing across multiple contexts. This information is used as input for state of the art methods for Graphical Model Selection in order to recover the structure of a composite network that simultaneously models exon co-regulation and their cognate regulators. Community structure detection and social network analysis methods are used to identify distinct modules and key actors within the network. As a proof of concept for our framework we studied the splicing regulatory network for Drosophila development using the publicly available modENCODE data. The final model offers a comprehensive view of the splicing circuitry that underlies fly development. Identified modules are associated with major developmental hallmarks including maternally loaded RNAs, onset of zygotic gene expression, transitions between life stages and sex differentiation. Within-module key actors include well-known developmental-specific splicing regulators from the literature while additional factors previously unassociated with developmental-specific splicing are also highlighted. Finally we analyze an extensive battery of Splicing Factor knock-down transcriptome data and demonstrate that our approach captures true regulatory relationships.
• dc.description.sponsorship We acknowledge support of the Spanish Ministry of Economy and Competitiveness, ‘Centro de Excelencia Severo Ochoa 2013-2017’, SEV-2012-0208. Work in JV laboratory is supported by Fundación Botín, by Banco de Santander through its Santander Universities Global Division, Consolider RNAREG, Ministerio de Economía y Competitividad and AGAUR.
• dc.format.mimetype application/pdfca
• dc.identifier.citation Papasaikas P, Rao A, Huggins P, Valcarcel J, Lopez AJ. Reconstruction of composite regulator-target splicing networks from high-throughput transcriptome data. BMC Genomics. 2015;16(Suppl 10):S7.ca
• dc.identifier.doi http://dx.doi.org/10.1186/1471-2164-16-S10-S7
• dc.identifier.issn 1471-2164ca
• dc.identifier.uri http://hdl.handle.net/10230/25221
• dc.language.iso engca
• dc.publisher BioMed Centralca
• dc.relation.ispartof BMC Genomics. 2015;16(Suppl 10):S7.
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/SEV2012-0208
• dc.rights © 2015 Papasaikas et al. 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 work is properly cited. Tca
• dc.rights.accessRights info:eu-repo/semantics/openAccessca
• dc.rights.uri http://creativecommons.org/licenses/by/4.0
• dc.subject.keyword Splicing
• dc.subject.keyword Regulatory Network
• dc.subject.keyword Module
• dc.subject.keyword Exon
• dc.subject.keyword Graphical Model
• dc.subject.keyword mRNA Processing
• dc.subject.keyword Splicing Factor
• dc.subject.keyword Regulator
• dc.subject.keyword Development
• dc.subject.other Exons
• dc.subject.other Empalmament (Genètica)
• dc.title Reconstruction of composite regulator-target splicing networks from high-throughput transcriptome dataca
• dc.type info:eu-repo/semantics/articleca
• dc.type.version info:eu-repo/semantics/publishedVersionca