Methylation quantitative trait loci (meQTLs) are consistently detected across ancestry, developmental stage, and tissue type

Abstract

Background: Individual genotypes at specific loci can result in different patterns of DNA methylation. These methylation quantitative trait loci (meQTLs) influence methylation across extended genomic regions and may underlie direct SNP associations or gene-environment interactions. We hypothesized that the detection of meQTLs varies with ancestral population, developmental stage, and tissue type. We explored this by analyzing seven datasets that varied by ancestry (African American vs. Caucasian), developmental stage (neonate vs. adult), and tissue type (blood vs. four regions of postmortem brain) with genome-wide DNA methylation and SNP data. We tested for meQTLs by constructing linear regression models of methylation levels at each CpG site on SNP genotypes within 50 kb under an additive model controlling for multiple tests.

Results: Most meQTLs mapped to intronic regions, although a limited number appeared to occur in synonymous or nonsynonymous coding SNPs. We saw significant overlap of meQTLs between ancestral groups, developmental stages, and tissue types, with the highest rates of overlap within the four brain regions. Compared with a random group of SNPs with comparable frequencies, meQTLs were more likely to be 1) represented among the most associated SNPs in the WTCCC bipolar disorder results and 2) located in microRNA binding sites.

Conclusions: These data give us insight into how SNPs impact gene regulation and support the notion that peripheral blood may be a reliable correlate of physiological processes in other tissues.

Figure 1

Distribution (probability density function) of associated (colored) and unassociated (black) SNP-CpG pairs by absolute distance in each cohort. Plot indicates that while the distance is roughly uniformly distributed between 0–50 kb for most pairs of SNPs and CpGs compared (black), the distance tends to be shorter (< 10 kb) for pairs where a meQTL was identified. Abbreviations: CB B: cord blood B, TCTX: temporal cortex, FCTX: frontal cortex, PONS: pons, CRBLM: cerebellum, CB A: cord blood A, and PB: peripheral blood.

Figure 2

Hierarchical clustering heatmap showing similarities of t-statistics of the meQTLs across all cohorts. Each row represents one SNP-CpG site tested; only SNP-CpG combinations that were significant in at least one cohort are included here. Columns represent cohorts (labels at bottom), and the hierarchical clustering tree shows relative similarity in test statistics between the tissues and cohorts. Color represents strength and direction of association t-statistics (see color key). Cohort abbreviations from left to right: CB B: cord blood B, TCTX: temporal cortex, FCTX: frontal cortex, PONS: pons, CRBLM: cerebellum, CB A: cord blood A, and PB: peripheral blood.

Figure 3

Identification of meQTLs in multiple tissues. rs10760117 associates with DNA methylation of cg21717724 in representative plots: CB B (A) and FCTX (B). See Additional file 6 for the remaining cohorts and tissues.)

Figure 4

Differences in meQTL detection between (A) tissue types; APOE, (B) developmental stage; APLNR, and (C) ancestry; CFTR. Each plot displays meQTL associations for a single CpG site (labeled at bottom center of plot): the x-axis represents genomic position of SNPs, while the y-axis represents the -log p-value of the association between the SNP and the CpG site. Cohort abbreviations: PB: peripheral blood, CB A: cord blood A, CB B: cord blood B, CRBLM: cerebellum, TCTX: temporal cortex, FCTX: frontal cortex, and PONS: pons.