By leveraging existing GWAS and eQTL resources, transcriptome-wide association studies 1 (TWAS) have achieved many successes in identifying trait-associations of genetically-regulated 2 expression (GREX) levels. TWAS analysis relies on the shared GREX variation across GWAS 3 and the reference eQTL data, which depends on the cellular conditions of the eQTL data. 4 Considering the increasing availability of eQTL data from different conditions and the often 5 unknown trait-relevant cell/tissue-types, we propose a method and tool, IGREX, for precisely 6 quantifying the proportion of phenotypic variation attributed to the GREX component. IGREX 7 takes as input a reference eQTL panel and individual-level or summary-level GWAS data. Using 8 eQTL data of 48 tissue types from the GTEx project as a reference panel, we evaluated the 9 tissue-specific IGREX impact on a wide spectrum of phenotypes. We observed strong GREX 10 effects on immune-related protein biomarkers. By incorporating trans-eQTLs and analyzing 11 genetically-regulated alternative splicing events, we evaluated new potential directions for 12 TWAS analysis. 13 * Correspondence should be addressed to Jin Liu (jin.liu@duke-nus.edu.sg) and Can Yang (macyang@ust.hk) Genome-wide association studies (GWAS) have successfully identified tens of thousands of 15 unique associations between single-nucleotide polymorphisms (SNPs) and a wide range of 16 complex traits/diseases (http://www.ebi.ac.uk/gwas/). More than 90% of identified risk 17 variants are located in non-coding regions [1], making it challenging to understand their 18 functional mechanisms. Increasing evidence [2, 3, 4, 5, 6, 7, 8, 9] has suggested that many of 19 those risk variants may affect traits/diseases via the modulation of their cis gene expression 20 levels. For example, a study of 18 complex traits revealed an enrichment for expression 21 quantitative trait loci (eQTLs) in 11% of 729 tissue-trait pairs [10]. There is great interest in 22 precisely characterizing the specific role of genetically regulated gene expression (GREX) in 23 human traits and diseases.
24It is well known that the effects of genetic variation on gene expressions depend on cellular 25 contexts [11]. The rapidly increasing availability of eQTL data from different tissue types, 26 cell types, populations and other conditions provides an unprecedented opportunity to study 27 and evaluate GREX effects in a variety of conditions. For example, the V7 release of the 28 Genotype-Tissue Expression (GTEx) project (https://gtexportal.org/home/) has collected 29 gene expression samples from 53 non-diseased tissues across 714 individuals [11]. Multiple 30 blood eQTL resources comprising thousands of individuals are made publicly available [12, 13]; 31 and other ongoing projects such as Genetics of DNA Methylation Consortium (GoDMC) and 32 eQTLGen consortium are collecting expression data with sample sizes larger than 10, 000 33 [14, 15]. Those data serve as rich eQTL resources for a comprehensive evaluation of GREX 34 effects.
35T...