The impact of rare variation on gene expression across tissues

• Published in: Nature (London) Vol. 550; no. 7675; pp. 239 - 243
• Main Authors: Li, Xin, Kim, Yungil, Tsang, Emily K., Davis, Joe R., Damani, Farhan N., Chiang, Colby, Hess, Gaelen T., Zappala, Zachary, Strober, Benjamin J., Scott, Alexandra J., Li, Amy, Ganna, Andrea, Bassik, Michael C., Merker, Jason D., Hall, Ira M., Battle, Alexis, Montgomery, Stephen B.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 12.10.2017; Nature Publishing Group
• Subjects: 45/23; 45/91; 631/114/2401; 631/208/191/2018; 631/208/199; 631/208/514/1948; 631/208/514/1949; Bayes Theorem; Bayesian analysis; Binding sites; Data integration; Disease susceptibility; DNA methylation; DNA sequencing; Female; Gene expression; Gene Expression Profiling; Gene sequencing; Genetic aspects; Genetic code; Genetic diversity; Genetic variance; Genetic variation; Genetic Variation - genetics; Genome, Human - genetics; Genomes; Genomics; Genotype; Health risks; Human tissues; Humanities and Social Sciences; Humans; letter; Male; Mathematical models; Models, Genetic; multidisciplinary; Mutation; Observations; Organ Specificity - genetics; Outliers (statistics); Ribonucleic acid; RNA; RNA sequencing; Science; Sequence Analysis, RNA; Statistical models; Studies; Tissues
• ISSN: 0028-0836; 1476-4687; 1476-4687
• DOI: 10.1038/nature24267

The authors show that rare genetic variants contribute to large gene expression changes across diverse human tissues and provide an integrative method for interpretation of rare variants in individual genomes. Genetic effects on gene expression across human tissues The GTEx (Genotype-Tissue Expression) Consortium has established a reference catalogue and associated tissue biobank for gene-expression levels across individuals for diverse tissues of the human body, with a broad sampling of normal, non-diseased human tissues from postmortem donors. The consortium now presents the deepest survey of gene expression across multiple tissues and individuals to date, encompassing 7,051 samples from 449 donors across 44 human tissues. Barbara Engelhardt and colleagues characterize the relationship between genetic variation and gene expression, and find that most genes are regulated by genetic variation near to the affected gene. In accompanying GTEx studies, Alexis Battle, Stephen Montgomery and colleagues examine the effect of rare genetic variation on gene expression across human tissues, Daniel MacArthur and colleagues systematically survey the landscape of X chromosome inactivation in human tissues, and Jin Billy Li and colleagues provide a comprehensive cross-species analysis of adenosine-to-inosine RNA editing in mammals. In an accompanying News & Views, Michelle Ward and Yoav Gilad put the latest results in context and discuss how these findings are helping to crack the regulatory code of the human genome. 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.