Many quantitative trait loci (QTLs) are in non-coding regions. Therefore, QTLs are assumed to affect gene regulation. Gene expression and RNA splicing are primary steps of transcription, so DNA variants changing gene expression (eVariants) or RNA splicing (sVariants) are expected to significantly affect phenotypes. We quantify the contribution of eVariants and sVariants detected from 16 tissues (n = 4,725) to 37 traits of ∼120,000 cattle (average magnitude of genetic correlation between traits = 0.13). Analyzed in Bayesian mixture models, averaged across 37 traits, cis and trans eVariants and sVariants detected from 16 tissues jointly explain 69.2% (SE = 0.5%) of heritability, 44% more than expected from the same number of random variants. This 69.2% includes an average of 24% from trans e-/sVariants (14% more than expected). Averaged across 56 lipidomic traits, multi-tissue cis and trans e-/sVariants also explain 71.5% (SE = 0.3%) of heritability, demonstrating the essential role of proximal and distal regulatory variants in shaping mammalian phenotypes.
Funding
The Australian Research Council's Discovery Projects (DP160101056 and DP200100499) supported R.X., M.E.G., and N.R.W. DairyBio, a joint venture project of Agriculture Victoria (Melbourne, Australia), Dairy Australia (Melbourne, Australia), and the Gardiner Foundation (Melbourne, Australia), funded computing resources used in the analysis. N.R.W. acknowledged funding from the National Health and Medical Research Council (NHMRC 1113400 and 1078901). L.F. received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sk1odowska-Curie grant (agreement no. 801215). A.T. acknowledges funding from the BBSRC through program grants BBS/E/D/10002070 and BBS/E/D/30002275, MRC research grant MR/P015514/1, and HDR-UK award HDR-9004. The authors also thank the University of Melbourne, Australia, for supporting this research.