eQTLs

Expression quantitative trait loci (eQTLs) are genomic loci where genetic variation is associated with variation in gene expression levels. In practice, eQTL studies relate genotypes, typically single-nucleotide polymorphisms, to transcript abundance measured by RNA sequencing or microarrays in a given tissue or cell type. eQTLs are commonly divided into cis-eQTLs, acting near the regulated gene (often within about 1 megabase of the transcription start site), and trans-eQTLs, influencing distant genes or acting through regulatory networks.

Mapping eQTLs involves testing associations between genotype and expression across individuals, usually with linear regression or linear mixed models. Analysts adjust for covariates such as population structure, sex, age, batch effects, and hidden confounders. Results are corrected for multiple testing, typically using false discovery rate control. Analyses may be performed within a tissue or cell type, and may be combined across studies in meta-analyses.

eQTLs have many applications. They help characterize the genetic regulation of gene expression, reveal tissue-specific regulatory architecture, and are frequently integrated with genome-wide association study (GWAS) results to identify potential causal genes and mechanisms. Approaches such as colocalization analyses and transcriptome-wide association studies (TWAS) interpret GWAS associations in the context of eQTLs, aiding fine-mapping and prioritization of targets.

Challenges include the typically modest effect sizes of eQTLs, especially trans-eQTLs, limited sample sizes for many tissues, and tissue specificity. Replication across populations and environments can be difficult. Public resources such as the GTEx project, the eQTLGen consortium, and the eQTL Catalogue provide comprehensive summary statistics and datasets to support eQTL discovery and interpretation.