Where Are the Disease-Associated eQTLs?

• Published in: Trends in genetics Vol. 37; no. 2; pp. 109 - 124
• Main Authors: Umans, Benjamin D., Battle, Alexis, Gilad, Yoav
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.02.2021
• Subjects: Animals; complex traits; dynamic gene regulation; eQTL; Gene Expression - genetics; Gene Expression Regulation - genetics; Genetic Predisposition to Disease - genetics; GTeX; GWAS; Humans; QTL mapping; Quantitative Trait Loci - genetics; Regulatory Sequences, Nucleic Acid - genetics; GTeX; complex traits; GWAS; eQTL; dynamic gene regulation; QTL mapping
• ISSN: 0168-9525
• DOI: 10.1016/j.tig.2020.08.009

Most disease-associated variants, although located in putatively regulatory regions, do not have detectable effects on gene expression. One explanation could be that we have not examined gene expression in the cell types or conditions that are most relevant for disease. Even large-scale efforts to study gene expression across tissues are limited to human samples obtained opportunistically or postmortem, mostly from adults. In this review we evaluate recent findings and suggest an alternative strategy, drawing on the dynamic and highly context-specific nature of gene regulation. We discuss new technologies that can extend the standard regulatory mapping framework to more diverse, disease-relevant cell types and states. Mapping of regulatory quantitative trait loci (QTLs) has emerged as a powerful tool to functionally annotate noncoding DNA variants that are associated with disease risk.Large surveys of gene expression variation in healthy, adult, steady-state tissues have discovered at least one cis expression QTL (eQTL) for nearly every human gene.The properties of standard eQTLs may be inconsistent with mutations that are associated with a fitness cost, in contrast to what might be expected for mutations associated with disease.Regulatory QTL mapping during dynamic cellular processes such as differentiation and perturbation response can reveal otherwise hidden regulatory variation that may be especially relevant for disease.New platform technologies, including in vitro differentiated cell types and single-cell profiling, extend the scope of dynamic eQTL studies.