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Sci Rep. 2016 Sep 12;6:32406. doi: 10.1038/srep32406.

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

Author information

1
Bioinformatics and Genomics, Center for Genomic Regulation (CRG), 08003 Barcelona, Catalonia, Spain.
2
Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland.
3
Instituto de Investigação e Inovação em Saúde, (i3S) Universidade do Porto, 4200-625 Porto, Portugal.
4
Institute of Molecular Pathology and Immunology (IPATIMUP), University of Porto, 4200-625 Porto, Portugal.
5
Institute of Biophysics Carlos Chagas Filho (IBCCF), Federal University of Rio de Janeiro (UFRJ), 21941-902 Rio de Janeiro, Brazil.
6
Institute of Clinical Molecular Biology, Christians-Albrechts-Universität zu Kiel, 24105 Kiel, Germany.
7
Institute of Human Genetics, Helmholtz Center Munich, 85764 Neuherberg, Germany.
8
Center for Human Genome and Stem-cell research (HUG-CELL), University of São Paulo (USP), 05508090 São Paulo, Brazil.
9
Science for Life Laboratory, Stockholm University, Box 1031, 17121 Solna, Sweden.
10
Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, United Kingdom.
11
Centre Nacional d'Anàlisi Genòmica, 08028 Barcelona, Catalonia, Spain.
12
Center for Research in Agricultural Genomics (CRAG), Autonome University of Barcelona, 08193 Bellaterra, Catalonia, Spain.
13
Institute of Human Genetics, Technische Universität München, 81675 Munich, Germany.
14
Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland.
15
Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland.
16
Pompeu Fabra University (UPF), 08003 Barcelona, Catalonia, Spain.
17
National Center of Scientific Computing (LNCC), 2233-6000 Petrópolis, Rio de Janeiro, Brazil.

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.

PMID:
27617755
PMCID:
PMC5019111
DOI:
10.1038/srep32406
[Indexed for MEDLINE]
Free PMC Article

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