Transcriptome and genome sequencing uncovers functional variation in humans View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2013-09

AUTHORS

Tuuli Lappalainen, Michael Sammeth, Marc R. Friedländer, Peter A. C. ‘t Hoen, Jean Monlong, Manuel A. Rivas, Mar Gonzàlez-Porta, Natalja Kurbatova, Thasso Griebel, Pedro G. Ferreira, Matthias Barann, Thomas Wieland, Liliana Greger, Maarten van Iterson, Jonas Almlöf, Paolo Ribeca, Irina Pulyakhina, Daniela Esser, Thomas Giger, Andrew Tikhonov, Marc Sultan, Gabrielle Bertier, Daniel G. MacArthur, Monkol Lek, Esther Lizano, Henk P. J. Buermans, Ismael Padioleau, Thomas Schwarzmayr, Olof Karlberg, Halit Ongen, Helena Kilpinen, Sergi Beltran, Marta Gut, Katja Kahlem, Vyacheslav Amstislavskiy, Oliver Stegle, Matti Pirinen, Stephen B. Montgomery, Peter Donnelly, Mark I. McCarthy, Paul Flicek, Tim M. Strom, The Geuvadis Consortium, Hans Lehrach, Stefan Schreiber, Ralf Sudbrak, Ángel Carracedo, Stylianos E. Antonarakis, Robert Häsler, Ann-Christine Syvänen, Gert-Jan van Ommen, Alvis Brazma, Thomas Meitinger, Philip Rosenstiel, Roderic Guigó, Ivo G. Gut, Xavier Estivill, Emmanouil T. Dermitzakis

ABSTRACT

Genome sequencing projects are discovering millions of genetic variants in humans, and interpretation of their functional effects is essential for understanding the genetic basis of variation in human traits. Here we report sequencing and deep analysis of messenger RNA and microRNA from lymphoblastoid cell lines of 462 individuals from the 1000 Genomes Project--the first uniformly processed high-throughput RNA-sequencing data from multiple human populations with high-quality genome sequences. We discover extremely widespread genetic variation affecting the regulation of most genes, with transcript structure and expression level variation being equally common but genetically largely independent. Our characterization of causal regulatory variation sheds light on the cellular mechanisms of regulatory and loss-of-function variation, and allows us to infer putative causal variants for dozens of disease-associated loci. Altogether, this study provides a deep understanding of the cellular mechanisms of transcriptome variation and of the landscape of functional variants in the human genome. More... »

PAGES

506

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nature12531

DOI

http://dx.doi.org/10.1038/nature12531

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1052616209

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/24037378


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