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

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, testing for heterogeneity between isoform-eQTL effects (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 x10(-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.

Automated summary

Most genetic variants identified from GWAS in humans are noncoding and play a role in gene regulation. Previous studies have shown links between GWAS signals and eQTLs, but the links to other genetic regulatory mechanisms, such as sQTLs, have not been extensively explored. This study introduces a new sQTL mapping method and identifies distinct cis-sQTLs that are not associated with eQTLs in brain transcriptomic data. By integrating sQTL data into GWAS for brain-related complex traits, the study identifies genes associated with these traits that cannot be discovered using eQTL data alone.