%0 Journal Article %J Science %D 2020 %T The impact of sex on gene expression across human tissues. %A Oliva, Meritxell %A Muñoz-Aguirre, Manuel %A Kim-Hellmuth, Sarah %A Wucher, Valentin %A Gewirtz, Ariel D H %A Cotter, Daniel J %A Parsana, Princy %A Kasela, Silva %A Balliu, Brunilda %A Viñuela, Ana %A Castel, Stephane E %A Mohammadi, Pejman %A Aguet, François %A Zou, Yuxin %A Khramtsova, Ekaterina A %A Skol, Andrew D %A Garrido-Martín, Diego %A Reverter, Ferran %A Brown, Andrew %A Evans, Patrick %A Gamazon, Eric R %A Payne, Anthony %A Bonazzola, Rodrigo %A Barbeira, Alvaro N %A Hamel, Andrew R %A Martinez-Perez, Angel %A Soria, José Manuel %A Pierce, Brandon L %A Stephens, Matthew %A Eskin, Eleazar %A Dermitzakis, Emmanouil T %A Segrè, Ayellet V %A Im, Hae Kyung %A Engelhardt, Barbara E %A Ardlie, Kristin G %A Montgomery, Stephen B %A Battle, Alexis J %A Lappalainen, Tuuli %A Guigo, Roderic %A Stranger, Barbara E %K Chromosomes, Human, X %K Disease %K Epigenesis, Genetic %K Female %K Gene Expression %K Gene Expression Regulation %K Genetic Variation %K Genome-Wide Association Study %K Humans %K Male %K Organ Specificity %K Promoter Regions, Genetic %K Quantitative Trait Loci %K Sex Characteristics %K Sex Factors %X

Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.

%B Science %V 369 %8 2020 09 11 %G eng %N 6509 %1 https://www.ncbi.nlm.nih.gov/pubmed/32913072?dopt=Abstract %R 10.1126/science.aba3066 %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 %0 Journal Article %J Nat Genet %D 2017 %T The impact of structural variation on human gene expression. %A Chiang, Colby %A Scott, Alexandra J %A Davis, Joe R %A Tsang, Emily K %A Li, Xin %A Kim, Yungil %A Hadzic, Tarik %A Damani, Farhan N %A Ganel, Liron %A Montgomery, Stephen B %A Battle, Alexis %A Conrad, Donald F %A Hall, Ira M %K Algorithms %K Chromosome Mapping %K Gene Expression Regulation %K Genetic Variation %K Genome, Human %K Genome-Wide Association Study %K Humans %K INDEL Mutation %K Linear Models %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %K Sequence Analysis, DNA %X

Structural variants (SVs) are an important source of human genetic diversity, but their contribution to traits, disease and gene regulation remains unclear. We mapped cis expression quantitative trait loci (eQTLs) in 13 tissues via joint analysis of SVs, single-nucleotide variants (SNVs) and short insertion/deletion (indel) variants from deep whole-genome sequencing (WGS). We estimated that SVs are causal at 3.5-6.8% of eQTLs-a substantially higher fraction than prior estimates-and that expression-altering SVs have larger effect sizes than do SNVs and indels. We identified 789 putative causal SVs predicted to directly alter gene expression: most (88.3%) were noncoding variants enriched at enhancers and other regulatory elements, and 52 were linked to genome-wide association study loci. We observed a notable abundance of rare high-impact SVs associated with aberrant expression of nearby genes. These results suggest that comprehensive WGS-based SV analyses will increase the power of common- and rare-variant association studies.

%B Nat Genet %V 49 %P 692-699 %8 2017 May %G eng %N 5 %1 https://www.ncbi.nlm.nih.gov/pubmed/28369037?dopt=Abstract %R 10.1038/ng.3834