title: Imputing Gene Expression in Uncollected Tissues Within and Beyond GTEx.
abstract: Gene expression and its regulation can vary substantially across tissue types. In order to generate knowledge about gene expression in human tissues, the Genotype-Tissue Expression (GTEx) program has collected transcriptome data in a wide variety of tissue types from post-mortem donors. However, many tissue types are difficult to access and are not collected in every GTEx individual. Furthermore, in non-GTEx studies, the accessibility of certain tissue types greatly limits the feasibility and scale of studies of multi-tissue expression. In this work, we developed multi-tissue imputation methods to impute gene expression in uncollected or inaccessible tissues. Via simulation studies, we showed that the proposed methods outperform existing imputation methods in multi-tissue expression imputation and that incorporating imputed expression data can improve power to detect phenotype-expression correlations. By analyzing data from nine selected tissue types in the GTEx pilot project, we demonstrated that harnessing expression quantitative trait loci (eQTLs) and tissue-tissue expression-level correlations can aid imputation of transcriptome data from uncollected GTEx tissues. More importantly, we showed that by using GTEx data as a reference, one can impute expression levels in inaccessible tissues in non-GTEx expression studies.
authors.affiliation: Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA.
authors.forename: Jiebiao
authors.initials: J
authors.lastname: Wang
authors.affiliation: Division of Genetic Medicine, Department of Medicine, Vanderbilt University and Vanderbilt Genetics Institute, Nashville, TN 37232, USA; Academic Medical Center, University of Amsterdam, Amsterdam 1105 AZ, the Netherlands.
authors.forename: Eric R
authors.initials: ER
authors.lastname: Gamazon
authors.affiliation: Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA.
authors.forename: Brandon L
authors.initials: BL
authors.lastname: Pierce
authors.affiliation: Section of Genetic Medicine, University of Chicago, Chicago, IL 60637, USA; Institute for Genomics and Systems Biology, University of Chicago, Chicago, IL 60637, USA.
authors.forename: Barbara E
authors.initials: BE
authors.lastname: Stranger
authors.affiliation: Section of Genetic Medicine, University of Chicago, Chicago, IL 60637, USA.
authors.forename: Hae Kyung
authors.initials: HK
authors.lastname: Im
authors.affiliation: Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA.
authors.forename: Robert D
authors.initials: RD
authors.lastname: Gibbons
authors.affiliation: Division of Genetic Medicine, Department of Medicine, Vanderbilt University and Vanderbilt Genetics Institute, Nashville, TN 37232, USA.
authors.forename: Nancy J
authors.initials: NJ
authors.lastname: Cox
authors.affiliation: Section of Genetic Medicine, University of Chicago, Chicago, IL 60637, USA; Department of Statistics, University of Chicago, Chicago, IL 60637, USA.
authors.forename: Dan L
authors.initials: DL
authors.lastname: Nicolae
authors.affiliation: Department of Public Health Sciences, University of Chicago, Chicago, IL 60637, USA. Electronic address: lchen@health.bsd.uchicago.edu.
authors.forename: Lin S
authors.initials: LS
authors.lastname: Chen
mesh_terms: D005786:Gene Expression Regulation; D005838:Genotype; D006801:Humans; D010641:Phenotype; D010865:Pilot Projects; D040641:Quantitative Trait Loci; D015203:Reproducibility of Results; D059467:Transcriptome
keywords: GTEx; eQTL; multi-tissue imputation; tissue-tissue expression-level correlation; transcriptome