A characterization of cis- and trans-heritability of RNA-Seq-based gene expression
Insights into individual differences in gene expression and its heritability (h2) can help in understanding pathways from DNA to phenotype. We estimated the heritability of gene expression of 52,844 genes measured in whole blood in the largest twin RNA-Seq sample to date (1497 individuals including 459 monozygotic twin pairs and 150 dizygotic twin pairs) from classical twin modeling and identity-by-state-based approaches. We estimated for each gene h2 total, composed of cis-heritability (h2 cis, the variance explained by single nucleotide polymorphisms in the cis-window of the gene), and trans-heritability (h2 res, the residual variance explained by all other genome-wide variants). Mean h2 total was 0.26, which was significantly higher than heritability estimates earlier found in a microarray-based study using largely overlapping (>60%) RNA samples (mean h2 = 0.14, p = 6.15 × 10−258). Mean h2 cis was 0.06 and strongly correlated with beta of the top cis expression quantitative loci (eQTL, ρ = 0.76, p < 10−308) and with estimates from earlier RNA-Seq-based studies. Mean h2 res was 0.20 and correlated with the beta of the corresponding trans-eQTL (ρ = 0.04, p < 1.89 × 10−3) and was significantly higher for genes involved in cytokine-cytokine interactions (p = 4.22 × 10−15), many other immune system pathways, and genes identified in genome-wide association studies for various traits including behavioral disorders and cancer. This study provides a thorough characterization of cis- and trans-h2 estimates of gene expression, which is of value for interpretation of GWAS and gene expression studies.
|Persistent URL||dx.doi.org/10.1038/s41431-019-0511-5, hdl.handle.net/1765/120603|
|Journal||European Journal of Human Genetics|
Ouwens, K.G. (Klaasjan G.), Jansen, R. (Rick), Nivard, M, van Dongen, J. (Jenny), Frieser, M.J. (Maia J.), Hottenga, J.-J. (Jouke-Jan), … Boomsma, D.I. (2019). A characterization of cis- and trans-heritability of RNA-Seq-based gene expression. European Journal of Human Genetics. doi:10.1038/s41431-019-0511-5