bioRxivGenomicsPreprint
Adipose tissue eQTL meta-analysis reveals the contribution of allelic heterogeneity to gene expression regulation and cardiometabolic traits
Sarah M. BrotmaniD, Julia S. El-Sayed MoustafaiD, Li GuaniD, K. Alaine BroadawayiD, Dongmeng WangiD, Anne JacksoniD, Ryan WelchiD, Kevin W. Currin, Max TomlinsoniD, Swarooparani VadlamudiiD, Heather M. StringhamiD, Amy L. RobertsiD, Timo Antero LakkaiD, Anniina OravilahtiiD, Lilian Fernandes SilvaiD, Narisu NarisuiD, Michael R. ErdosiD, Tingfen YaniD, Lori L. BonnycastleiD, Chelsea K. RaulersoniD, Yasrab N. RazaiD, Xinyu YaniD, Stephen C.J. ParkeriD, Johanna KuusistoiD, Päivi PajukantaiD, , Laura J. ScottiD
Abstract
Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. Here, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34K conditionally distinct expression quantitative trait locus (eQTL) signals in 18K genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared to primary signals, non-primary signals had lower effect sizes, lower minor allele frequencies, and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTL with conditionally distinct genome-wide association study signals for 28 cardiometabolic traits identified 3,605 eQTL signals for 1,861 genes. Inclusion of non-primary eQTL signals increased colocalized signals by 46%. Among 30 genes with [≥]2 pairs of colocalized signals, 21 showed a mediating gene dosage effect on the trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation.
- organism: human
- assay: bulk RNA-seq
- research focus: eQTL / molecular QTL mapping
- approach: statistical model
- Citations
- 11
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