这项研究通过对来自“1000 Genomes Project”的462个人的类淋巴母细胞系的信使RNA和微RNA进行测序和深度分析来确定人类基因组中的调控变化。分析显示了影响绝大部分基因的调控的普遍存在的基因变化,其中转录结构和表达水平的变化同样普遍,但从遗传上来说在很大程度上是独立的。对因果性调控变化的定性有助于了解调控和“功能丧失”变化的细胞机制,同时也说明可能存在与疾病相关的几十个等位基因的假想因果性变异体。(生物谷 Bioon.com)
生物谷推荐的英文摘要
Nature doi:10.1038/nature12531
Transcriptome and genome sequencing uncovers functional variation in humans
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
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.