The impact of rare variation on gene expression across tissues.
The impact of rare variation on gene expression across tissues.
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DOI：
10.1038/nature24267
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发表时间：
2017-10-11
期刊：
影响因子：
64.8
通讯作者：
Montgomery SB
中科院分区：
文献类型：
--
作者：
Li X;Kim Y;Tsang EK;Davis JR;Damani FN;Chiang C;Hess GT;Zappala Z;Strober BJ;Scott AJ;Li A;Ganna A;Bassik MC;Merker JD;GTEx Consortium;Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group;Statistical Methods groups—Analysis Working Group;Enhancing GTEx (eGTEx) groups;NIH Common Fund;NIH/NCI;NIH/NHGRI;NIH/NIMH;NIH/NIDA;Biospecimen Collection Source Site—NDRI;Biospecimen Collection Source Site—RPCI;Biospecimen Core Resource—VARI;Brain Bank Repository—University of Miami Brain Endowment Bank;Leidos Biomedical—Project Management;ELSI Study;Genome Browser Data Integration &Visualization—EBI;Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz;Hall IM;Battle A;Montgomery SB
罕见的遗传变异在人类中是丰富的，预计将有助于个体疾病风险1，2，3，4。虽然遗传关联研究已经成功地确定了与易感性相关的常见遗传变异，但这些研究对于确定罕见变异并不实用1，5。区分致病性变异与良性罕见变异的努力已经利用遗传密码来鉴定有害的蛋白质编码等位基因1、6、7，但对于非编码变异不存在类似的密码。因此，确定哪些罕见变异具有表型效应仍然是一个重大挑战。罕见的非编码变异已与极端的基因表达在研究中使用单一组织8，9，10，11，但其影响组织是未知的。在这里，我们通过使用来自基因型组织表达（GTEx）项目v6p版本12的全基因组和多组织RNA测序数据的组合分析，在44种人体组织中识别基因表达异常值，或显示特定基因极端表达水平的个体。我们发现，58%的低表达和28%的过表达异常值附近有保守的罕见变异，而非异常值只有8%。此外，我们开发了RIVER（RNA知情的变异对调控的影响），这是一种贝叶斯统计模型，它结合了表达数据，以比单独使用基因组注释的模型更高的准确性预测罕见变异的调控作用。总体而言，我们证明了罕见的变异有助于跨组织的大基因表达变化，并提供了一个综合的方法来解释个别基因组中的罕见变异。
Rare genetic variants are abundant in humans and are expected to contribute to individual disease risk 1, 2, 3, 4. While genetic association studies have successfully identified common genetic variants associated with susceptibility, these studies are not practical for identifying rare variants 1, 5. Efforts to distinguish pathogenic variants from benign rare variants have leveraged the genetic code to identify deleterious protein-coding alleles 1, 6, 7, but no analogous code exists for non-coding variants. Therefore, ascertaining which rare variants have phenotypic effects remains a major challenge. Rare non-coding variants have been associated with extreme gene expression in studies using single tissues 8, 9, 10, 11, but their effects across tissues are unknown. Here we identify gene expression outliers, or individuals showing extreme expression levels for a particular gene, across 44 human tissues by using combined analyses of whole genomes and multi-tissue RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project v6p release 12. We find that 58% of underexpression and 28% of overexpression outliers have nearby conserved rare variants compared to 8% of non-outliers. Additionally, we developed RIVER (RNA-informed variant effect on regulation), a Bayesian statistical model that incorporates expression data to predict a regulatory effect for rare variants with higher accuracy than models using genomic annotations alone. Overall, we demonstrate that rare variants contribute to large gene expression changes across tissues and provide an integrative method for interpretation of rare variants in individual genomes.
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DOI：
10.1126/science.1215040
发表时间：
2012-02-17
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
MacArthur DG;Balasubramanian S;Frankish A;Huang N;Morris J;Walter K;Jostins L;Habegger L;Pickrell JK;Montgomery SB;Albers CA;Zhang ZD;Conrad DF;Lunter G;Zheng H;Ayub Q;DePristo MA;Banks E;Hu M;Handsaker RE;Rosenfeld JA;Fromer M;Jin M;Mu XJ;Khurana E;Ye K;Kay M;Saunders GI;Suner MM;Hunt T;Barnes IH;Amid C;Carvalho-Silva DR;Bignell AH;Snow C;Yngvadottir B;Bumpstead S;Cooper DN;Xue Y;Romero IG;1000 Genomes Project Consortium;Wang J;Li Y;Gibbs RA;McCarroll SA;Dermitzakis ET;Pritchard JK;Barrett JC;Harrow J;Hurles ME;Gerstein MB;Tyler-Smith C
通讯作者：
Tyler-Smith C
影响因子：
12.3
作者：
McLaren W;Gil L;Hunt SE;Riat HS;Ritchie GR;Thormann A;Flicek P;Cunningham F
通讯作者：
Cunningham F
DOI：
10.1038/gim.2013.73
发表时间：
2013-07
期刊：
Genetics in medicine : official journal of the American College of Medical Genetics
影响因子：
--
作者：
通讯作者：
--
影响因子：
46.9
作者：
Hendel A;Bak RO;Clark JT;Kennedy AB;Ryan DE;Roy S;Steinfeld I;Lunstad BD;Kaiser RJ;Wilkens AB;Bacchetta R;Tsalenko A;Dellinger D;Bruhn L;Porteus MH
通讯作者：
Porteus MH
影响因子：
30.8
作者：
Kircher, Martin;Witten, Daniela M.;Jain, Preti;O'Roak, Brian J.;Cooper, Gregory M.;Shendure, Jay
通讯作者：
Shendure, Jay