We selected the top-associated cis-eQTLs at PeQTL < 5 × 10−8 for 4257 genes in GTEx-muscle and matched the selected genes with those in the other data sets (the number of matched genes ranged from 1113 to 3841) (Supplementary Table 2, i.e., up to 90%, with the lower numbers matched representing data sets with gene expression data for fewer genes). Note that all the matched genes were expressed in both tissues (i.e., genes which have at least 10 samples with reads per kilobase per million mapped reads (RPKM) > 0.1 and raw read counts >6)13. It should also be noted that our analysis below shows that the test-statistic for the difference in gene expression between tissues was almost independent of the test-statistic for the difference in SNP effect on gene expression between tissues, therefore selecting genes by cis-eQTL P-values would not bias mean gene expression in any specific tissue. We used the Jackknife approach that removes one gene at a time to estimate the sampling variance of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat r_b$$\end{document}r^b (Methods) assuming
