Cellular deconvolution of GTEx tissues powers discovery of disease and cell-type associated regulatory variants

• Published in: Nature communications Vol. 11; no. 1; p. 955
• Main Authors: Donovan, Margaret K. R., D’Antonio-Chronowska, Agnieszka, D’Antonio, Matteo, Frazer, Kelly A.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 19.02.2020; Nature Publishing Group; Nature Portfolio
• Subjects: 38; 38/39; 38/43; 38/91; 631/208/199; 631/208/205; 631/208/514/1949; Animals; Composition; Disease; Gene expression; Gene Expression Profiling; Genetic diversity; Genetic Predisposition to Disease; Genetic Variation; Genome - genetics; Genomics; Genotype; Genotypes; Heterogeneity; Human tissues; Humanities and Social Sciences; Humans; Liver - cytology; Liver - metabolism; Mice; multidisciplinary; Organ Specificity - genetics; Phenotype; Quantitative Trait Loci - genetics; Ribonucleic acid; RNA; Science; Science (multidisciplinary); Skin - cytology; Skin - metabolism; Skin diseases; Tissue analysis; Tissues; Transcriptome - genetics
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-020-14561-0

The Genotype-Tissue Expression (GTEx) resource has provided insights into the regulatory impact of genetic variation on gene expression across human tissues; however, thus far has not considered how variation acts at the resolution of the different cell types. Here, using gene expression signatures obtained from mouse cell types, we deconvolute bulk RNA-seq samples from 28 GTEx tissues to quantify cellular composition, which reveals striking heterogeneity across these samples. Conducting eQTL analyses for GTEx liver and skin samples using cell composition estimates as interaction terms, we identify thousands of genetic associations that are cell-type-associated. The skin cell-type associated eQTLs colocalize with skin diseases, indicating that variants which influence gene expression in distinct skin cell types play important roles in traits and disease. Our study provides a framework to estimate the cellular composition of GTEx tissues enabling the functional characterization of human genetic variation that impacts gene expression in cell-type-specific manners. Cellular heterogeneity can confound functional genomics analyses of bulk tissues. Here, Donovan et al. deconvolute bulk GTEx RNA-seq data utilizing scRNA-seq data from the Tabula Muris project and show the power of using cell populations in eQTL analyses to identify disease and cell-type-associated regulatory variants.