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Sequence variation between 462 human individuals fine-tunes functional sites of RNA processing

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dc.contributor.author Ferreira, Pedro G.
dc.contributor.author Oti, Martin
dc.contributor.author Barann, Matthias
dc.contributor.author Wieland, Thomas
dc.contributor.author Ezquina, Suzana
dc.contributor.author Friedländer, Marc R.
dc.contributor.author Rivas, Manuel A.
dc.contributor.author Esteve-Codina, Anna
dc.contributor.author The GEUVADIS Consortium
dc.contributor.author Rosenstiel, Philip
dc.contributor.author Strom, Tim M.
dc.contributor.author Lappalainen, Tuuli
dc.contributor.author Guigó Serra, Roderic
dc.contributor.author Sammeth, Michael
dc.date.accessioned 2017-01-27T08:53:36Z
dc.date.available 2017-01-27T08:53:36Z
dc.date.issued 2016
dc.identifier.citation Ferreira PG, Oti M, Barann M, Wieland T, Ezquina S, Friedländer MR et.al. Sequence variation between 462 human individuals fine-tunes functional sites of RNA processing. Scientific Reports. 2016;6:32406. DOI: 10.1038/srep32406
dc.identifier.issn 2045-2322
dc.identifier.uri http://hdl.handle.net/10230/28006
dc.description.abstract Recent advances in the cost-efficiency of sequencing technologies enabled the combined DNA- and RNA-sequencing of human individuals at the population-scale, making genome-wide investigations of the inter-individual genetic impact on gene expression viable. Employing mRNA-sequencing data from the Geuvadis Project and genome sequencing data from the 1000 Genomes Project we show that the computational analysis of DNA sequences around splice sites and poly-A signals is able to explain several observations in the phenotype data. In contrast to widespread assessments of statistically significant associations between DNA polymorphisms and quantitative traits, we developed a computational tool to pinpoint the molecular mechanisms by which genetic markers drive variation in RNA-processing, cataloguing and classifying alleles that change the affinity of core RNA elements to their recognizing factors. The in silico models we employ further suggest RNA editing can moonlight as a splicing-modulator, albeit less frequently than genomic sequence diversity. Beyond existing annotations, we demonstrate that the ultra-high resolution of RNA-Seq combined from 462 individuals also provides evidence for thousands of bona fide novel elements of RNA processing—alternative splice sites, introns, and cleavage sites—which are often rare and lowly expressed but in other characteristics similar to their annotated counterparts.
dc.description.sponsorship This research leading to these results has received funding from the European Commission 7th Framework Program, Project N. 261123 (GEUVADIS). PGF received funding by POPH - QREN Type 4.2, European Social Fund and Portuguese Ministry of Science and Technology (MCTES), Contrato Programa no âmbito do Programa Investigador FCT, 2014, IF/01127/2014. MO received funding by the National Counsel of Technological and Scientific Development (CNPq) grant 310132/2015-0, and MS received funding by the Research Support Foundation of the State of Rio de Janeiro (FAPERJ) E_06/2015, and by CNPq grant 401626/2015-6.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Nature Publishing Group
dc.relation.ispartof Scientific Reports. 2016;6:32406
dc.rights © Nature Publishing Group. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title Sequence variation between 462 human individuals fine-tunes functional sites of RNA processing
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1038/srep32406
dc.subject.keyword Cell biology
dc.subject.keyword Computational biology and bioinformatics
dc.subject.keyword Molecular biology
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/261123
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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