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Author Notes:

E-mail Address : alicia.smith@emory.edu E-mail Address : kressle@emory.edu E-mail Address : kconnee@emory.edu

AKS and KNC designed the experiments; LMA, KBM, KJR, and FAT performed the experiments or provided biological data; AKS, VK, MK, and KNC performed the analyses; AKS, VK, and KNC wrote the paper. All authors read and approved the final manuscript.

We gratefully acknowledge the study participants and staff of CANDLE and the Grady Trauma Project.

The authors also acknowledge the support of the Center for Integrative and Translational Genomics and Dr. Robert Williams at the University of Tennessee Health Science Center. Finally, we thank Cheryl Strauss for her editorial assistance.

The authors declare no competing interests.

Subjects:

Research Funding:

M. Adkins), and the Howard Hughes Medical Institute (K.J.R.).

Additional support came from a grant from the University of Tennessee Health Science Centers Clinical and Translational Science Institute to RMA and a grant from The Urban Child Institute to FT.

Keywords:

  • DNA methylation
  • meQTL
  • mQTL
  • Developmental stage
  • Ancestry
  • Race
  • Gene regulation
  • Inter-individual variation
  • Biomarker
  • Brain

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

Journal Title:

BMC Genomics

Volume:

Volume 15, Number 145

Publisher:

Type of Work:

Article | Final Publisher PDF

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.

Copyright information:

© 2014 Smith et al.; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution 2.0 Generic License ( http://creativecommons.org/licenses/by/2.0/), which permits making multiple copies, distribution of derivative works, distribution, public display, and publicly performance, provided the original work is properly cited. This license requires copyright and license notices be kept intact, credit be given to copyright holder and/or author.

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