UC San Diego

When mapping expression quantitative trait loci, a linear additive genetic model is mostly commonly used to investigate how genetic variants influence transcript levels. This model assumes that the phenotype of heterozygotes is halfway between that of the low-homozygous and high-homozygous genotypes and may miss non-additive relationships, such as those caused by dominant alleles. Here we examine RNA-Seq data to identify dominant genetic associations with gene expression in the human genome. We applied a multiple linear regression model on genotypes and RNA-Seq data from Genotype-Tissue Expression project. With stringent permutations, we discovered that on average, 0.19% of all genes tested (including non-coding RNAs and pseudogenes) show evidence for dominant genetic associations across ten different tissues. Most dominant effect sizes are positive, implying that the phenotypes of heterozygotes tend to have similar gene expression levels to high-expression homozygotes. In 8 out of the 10 tissues we examined, we found that genes encoding major histocompatibility complex (MHC) proteins are enriched for dominant effects.