%0 Journal Article %J Science %D 2020 %T Transcriptomic signatures across human tissues identify functional rare genetic variation. %A Ferraro, Nicole M %A Strober, Benjamin J %A Einson, Jonah %A Abell, Nathan S %A Aguet, François %A Barbeira, Alvaro N %A Brandt, Margot %A Bucan, Maja %A Castel, Stephane E %A Davis, Joe R %A Greenwald, Emily %A Hess, Gaelen T %A Hilliard, Austin T %A Kember, Rachel L %A Kotis, Bence %A Park, YoSon %A Peloso, Gina %A Ramdas, Shweta %A Scott, Alexandra J %A Smail, Craig %A Tsang, Emily K %A Zekavat, Seyedeh M %A Ziosi, Marcello %A Ardlie, Kristin G %A Assimes, Themistocles L %A Bassik, Michael C %A Brown, Christopher D %A Correa, Adolfo %A Hall, Ira %A Im, Hae Kyung %A Li, Xin %A Natarajan, Pradeep %A Lappalainen, Tuuli %A Mohammadi, Pejman %A Montgomery, Stephen B %A Battle, Alexis %K Genetic Variation %K Genome, Human %K Humans %K Multifactorial Inheritance %K Organ Specificity %K Transcriptome %X

Rare genetic variants are abundant across the human genome, and identifying their function and phenotypic impact is a major challenge. Measuring aberrant gene expression has aided in identifying functional, large-effect rare variants (RVs). Here, we expanded detection of genetically driven transcriptome abnormalities by analyzing gene expression, allele-specific expression, and alternative splicing from multitissue RNA-sequencing data, and demonstrate that each signal informs unique classes of RVs. We developed Watershed, a probabilistic model that integrates multiple genomic and transcriptomic signals to predict variant function, validated these predictions in additional cohorts and through experimental assays, and used them to assess RVs in the UK Biobank, the Million Veterans Program, and the Jackson Heart Study. Our results link thousands of RVs to diverse molecular effects and provide evidence to associate RVs affecting the transcriptome with human traits.

%B Science %V 369 %8 2020 09 11 %G eng %N 6509 %1 https://www.ncbi.nlm.nih.gov/pubmed/32913073?dopt=Abstract %R 10.1126/science.aaz5900 %0 Journal Article %J Nature %D 2017 %T Genetic effects on gene expression across human tissues. %A Battle, Alexis %A Brown, Christopher D %A Engelhardt, Barbara E %A Montgomery, Stephen B %K Alleles %K Chromosomes, Human %K Disease %K Female %K Gene Expression Profiling %K Gene Expression Regulation %K Genetic Variation %K Genome, Human %K Genotype %K Humans %K Male %K Organ Specificity %K Quantitative Trait Loci %X

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.

%B Nature %V 550 %P 204-213 %8 2017 10 11 %G eng %N 7675 %1 https://www.ncbi.nlm.nih.gov/pubmed/29022597?dopt=Abstract %R 10.1038/nature24277