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Transcriptome and genome sequencing uncovers functional variation in humans (2013)

T. Lappalainen ; M. Sammeth ; M. R. Friedlander ; [et al.]

Nature Publishing Group (NPG)

In: Nature. 501(7468): 506-11. doi: 10.1038/nature12531.

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Publication Date: 2013-09-17

Description: 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.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3918453/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉 〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3918453/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Lappalainen, Tuuli -- Sammeth, Michael -- Friedlander, Marc R -- 't Hoen, Peter A C -- Monlong, Jean -- Rivas, Manuel A -- Gonzalez-Porta, Mar -- Kurbatova, Natalja -- Griebel, Thasso -- Ferreira, Pedro G -- Barann, Matthias -- Wieland, Thomas -- Greger, Liliana -- van Iterson, Maarten -- Almlof, Jonas -- Ribeca, Paolo -- Pulyakhina, Irina -- Esser, Daniela -- Giger, Thomas -- Tikhonov, Andrew -- Sultan, Marc -- Bertier, Gabrielle -- MacArthur, Daniel G -- Lek, Monkol -- Lizano, Esther -- Buermans, Henk P J -- Padioleau, Ismael -- Schwarzmayr, Thomas -- Karlberg, Olof -- Ongen, Halit -- Kilpinen, Helena -- Beltran, Sergi -- Gut, Marta -- Kahlem, Katja -- Amstislavskiy, Vyacheslav -- Stegle, Oliver -- Pirinen, Matti -- Montgomery, Stephen B -- Donnelly, Peter -- McCarthy, Mark I -- Flicek, Paul -- Strom, Tim M -- Geuvadis Consortium -- Lehrach, Hans -- Schreiber, Stefan -- Sudbrak, Ralf -- Carracedo, Angel -- Antonarakis, Stylianos E -- Hasler, Robert -- Syvanen, Ann-Christine -- van Ommen, Gert-Jan -- Brazma, Alvis -- Meitinger, Thomas -- Rosenstiel, Philip -- Guigo, Roderic -- Gut, Ivo G -- Estivill, Xavier -- Dermitzakis, Emmanouil T -- 075491/Z/04/B/Wellcome Trust/United Kingdom -- 076113/Wellcome Trust/United Kingdom -- 081917/Wellcome Trust/United Kingdom -- 083270/Wellcome Trust/United Kingdom -- 085475/B/08/Z/Wellcome Trust/United Kingdom -- 085475/Z/08/Z/Wellcome Trust/United Kingdom -- 085532/Wellcome Trust/United Kingdom -- 090367/Wellcome Trust/United Kingdom -- 090532/Wellcome Trust/United Kingdom -- 090532/Z/09/Z/Wellcome Trust/United Kingdom -- 095552/Wellcome Trust/United Kingdom -- 095552/Z/11/Z/Wellcome Trust/United Kingdom -- 098381/Wellcome Trust/United Kingdom -- G0601261/Medical Research Council/United Kingdom -- MH090941/MH/NIMH NIH HHS/ -- R01 GM104371/GM/NIGMS NIH HHS/ -- R01 MH090941/MH/NIMH NIH HHS/ -- WT085532/Wellcome Trust/United Kingdom -- England -- Nature. 2013 Sep 26;501(7468):506-11. doi: 10.1038/nature12531. Epub 2013 Sep 15.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland. tuuli.e.lappalainen@gmail.com〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24037378" target="_blank"〉PubMed〈/a〉

Keywords: Alleles ; Cell Line, Transformed ; Exons/genetics ; Gene Expression Profiling ; Genetic Variation/*genetics ; Genome, Human/*genetics ; *High-Throughput Nucleotide Sequencing ; Humans ; Polymorphism, Single Nucleotide/genetics ; Quantitative Trait Loci/genetics ; RNA, Messenger/analysis/genetics ; *Sequence Analysis, RNA ; Transcriptome/*genetics

Print ISSN: 0028-0836

Electronic ISSN: 1476-4687

Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics

Published by Nature Publishing Group (NPG)

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Modelling and simulating generic RNA-Seq experiments with the flux simulator (2012)

Griebel, T., Zacher, B., Ribeca, P., Raineri, E., Lacroix, V., Guigo, R., Sammeth, M.

Oxford University Press

In: Nucleic Acids Research

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Publication Date: 2012-11-04

Description: High-throughput sequencing of cDNA libraries constructed from cellular RNA complements (RNA-Seq) naturally provides a digital quantitative measurement for every expressed RNA molecule. Nature, impact and mutual interference of biases in different experimental setups are, however, still poorly understood—mostly due to the lack of data from intermediate protocol steps. We analysed multiple RNA-Seq experiments, involving different sample preparation protocols and sequencing platforms: we broke them down into their common—and currently indispensable—technical components (reverse transcription, fragmentation, adapter ligation, PCR amplification, gel segregation and sequencing), investigating how such different steps influence abundance and distribution of the sequenced reads. For each of those steps, we developed universally applicable models, which can be parameterised by empirical attributes of any experimental protocol. Our models are implemented in a computer simulation pipeline called the Flux Simulator, and we show that read distributions generated by different combinations of these models reproduce well corresponding evidence obtained from the corresponding experimental setups. We further demonstrate that our in silico RNA-Seq provides insights about hidden precursors that determine the final configuration of reads along gene bodies; enhancing or compensatory effects that explain apparently controversial observations can be observed. Moreover, our simulations identify hitherto unreported sources of systematic bias from RNA hydrolysis, a fragmentation technique currently employed by most RNA-Seq protocols.

Print ISSN: 0305-1048

Electronic ISSN: 1362-4962

Topics: Biology