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Updated: May 2, 2026
Methodology for Accurate Detection of Mitochondrial DNA Methylation
Published on: May 20, 2018
Methylation quantitative trait loci (meQTLs) are consistently detected across ancestry, developmental stage, and
Alicia K Smith1, Varun Kilaru, Mehmet Kocak
1Department of Psychiatry and Behavioral Science, Emory University, 101 Woodruff Circle NE; Ste 4000, Atlanta, GA 30322, USA. alicia.smith@emory.edu.
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.
