sQTL

An sQTL, or splicing quantitative trait locus, is a genetic variant that influences RNA splicing of transcripts. Such variants can affect exon inclusion or skipping, intron retention, or the choice of splice sites, thereby altering the abundance of transcript isoforms without necessarily changing overall gene expression. Most sQTLs are detected in cis, located near the gene they regulate, though trans-acting sQTLs have been reported.

Splicing phenotypes used to map sQTLs are typically derived from RNA sequencing data. Common measures include percent-spliced-in (PSI) values for exons or junction-based read counts and intron-excision ratios. Statistical mapping relates genotype to these splicing phenotypes across individuals, often using linear models with covariates for population structure, sex, batch effects, and hidden factors. Analyses correct for multiple testing and are frequently replicated in independent cohorts. Methods differ in how they quantify splicing, with annotation-based approaches and annotation-free methods, such as those that cluster reads spanning introns.

Common tools and resources include specialized software for sQTL discovery and catalogs from large projects like GTEx, which have mapped sQTLs across many tissues. Annotation-free approaches, exemplified by LeafCutter, focus on splicing variation without relying on predefined isoforms, while other pipelines use junction-level or exon-level quantifications.

Biological significance arises when sQTLs colocalize with disease-associated loci, offering mechanisms by which genetic variation may influence disease through altered splicing rather than expression alone. Challenges include isoform ambiguity from short reads, linkage disequilibrium, tissue specificity, and limited sample sizes, all of which can complicate interpretation and fine-mapping.