Where Are the Disease-Associated eQTLs?

Abstract

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.

Keywords: GTeX; GWAS; QTL mapping; complex traits; dynamic gene regulation; eQTL.

Figure 1:

Combining GWAS and eQTL data. (a) By comparing affected and control individuals, disease risk can be associated with genotype at many loci, indicated by red asterisks. Even in large studies, many loci show weak evidence of association, represented by short accumulations of asterisks, and the function of intergenic mutations is unclear. (b) Correlating genotypes with expression levels in healthy subjects can reveal the targets of eQTL variants (orange asterisks). Here, mutations from (a) correlate with expression changes in gene B but not gene A, suggesting possible involvement in disease.

Figure 2:

Features of standard eQTLs are inconsistent with roles in disease. (a) Truly deleterious alleles (red) are unlikely to affect many tissues without encountering strong selective pressures, limiting their persistence in the population. Alleles wide effects are more likely benign (purple). (b) Standard eQTL genes (blue) are shared across primates. These genes show lower levels of sequence conservation, indicating a less sensitive role in physiology.

Figure 3:

Hypothetical relationship revealed by dynamic eQTL mapping. At time (a), genotype has no detectable effect on expression. In response to changing cellular conditions, transcription of gene A is induced, but attenuated by a cis-eQTL (orange asterisk, b). At time (c), the product of gene A regulates a distal locus, leading to phenotypic divergence of the two cells. Importantly, the cis eQTL is no longer detectable and appears only as a trans effect.

Figure 4:

Single-cell profiling can uncover unique regulatory relationships. (a) Single-cell resolution can help uncover eQTLs affecting rare cell types or cell states in primary tissue or mixed cultures. (b) Identifying genetic variants that affect expression dispersion, rather than mean expression levels, may help explain incompletely penetrant phenotypes.