Genetic control of RNA splicing and its distinct role in complex trait variation

TLDR

Most GWAS‑identified variants are noncoding and have been linked to expression quantitative trait loci, but their association with splicing QTLs remains largely unexplored. The authors aim to develop THISTLE, a new sQTL mapping method that improves power over existing approaches. They applied THISTLE and a complementary sQTL mapping strategy to 2,865 brain transcriptomes and genotypes, uncovering 12,794 cis‑sQTL genes—61 % distinct from eQTLs—and linking 244 genes to 12 brain‑related traits, 61 % of which were not detected by eQTLs. The study shows that most sQTLs play a distinct role in regulating transcription and influencing complex trait variation.

Abstract

Abstract Most genetic variants identified from genome-wide association studies (GWAS) in humans are noncoding, indicating their role in gene regulation. Previous studies have shown considerable links of GWAS signals to expression quantitative trait loci (eQTLs) but the links to other genetic regulatory mechanisms, such as splicing QTLs (sQTLs), are underexplored. Here, we introduce an sQTL mapping method,  t esting for h eterogeneity between is oform-eQ TL e ffects (THISTLE), with improved power over competing methods. Applying THISTLE together with a complementary sQTL mapping strategy to brain transcriptomic ( n = 2,865) and genotype data, we identified 12,794 genes with cis -sQTLs at P < 5 × 10 −8 , approximately 61% of which were distinct from eQTLs. Integrating the sQTL data into GWAS for 12 brain-related complex traits (including diseases), we identified 244 genes associated with the traits through cis -sQTLs, approximately 61% of which could not be discovered using the corresponding eQTL data. Our study demonstrates the distinct role of most sQTLs in the genetic regulation of transcription and complex trait variation.