Co-occurring expression and methylation QTLs allow detection of common causal variants and shared biological mechanisms

Brandon L. Pierce (), Lin Tong, Maria Argos, Kathryn Demanelis, Farzana Jasmine, Muhammad Rakibuz-Zaman, Golam Sarwar, Md. Tariqul Islam, Hasan Shahriar, Tariqul Islam, Mahfuzar Rahman, Md. Yunus, Muhammad G. Kibriya, Lin S. Chen and Habibul Ahsan ()
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Brandon L. Pierce: The University of Chicago
Lin Tong: The University of Chicago
Maria Argos: University of Illinois at Chicago
Kathryn Demanelis: The University of Chicago
Farzana Jasmine: The University of Chicago
Muhammad Rakibuz-Zaman: UChicago Research Bangladesh
Golam Sarwar: UChicago Research Bangladesh
Md. Tariqul Islam: UChicago Research Bangladesh
Hasan Shahriar: UChicago Research Bangladesh
Tariqul Islam: UChicago Research Bangladesh
Mahfuzar Rahman: UChicago Research Bangladesh
Md. Yunus: International Centre for Diarrhoeal Disease Research Bangladesh
Muhammad G. Kibriya: The University of Chicago
Lin S. Chen: The University of Chicago
Habibul Ahsan: The University of Chicago

Nature Communications, 2018, vol. 9, issue 1, 1-12

Abstract: Abstract Inherited genetic variation affects local gene expression and DNA methylation in humans. Most expression quantitative trait loci (cis-eQTLs) occur at the same genomic location as a methylation QTL (cis-meQTL), suggesting a common causal variant and shared mechanism. Using DNA and RNA from peripheral blood of Bangladeshi individuals, here we use co-localization methods to identify eQTL-meQTL pairs likely to share a causal variant. We use partial correlation and mediation analyses to identify >400 of these pairs showing evidence of a causal relationship between expression and methylation (i.e., shared mechanism) with many additional pairs we are underpowered to detect. These co-localized pairs are enriched for SNPs showing opposite associations with expression and methylation, although many SNPs affect multiple CpGs in opposite directions. This work demonstrates the pervasiveness of co-regulated expression and methylation in the human genome. Applying this approach to other types of molecular QTLs can enhance our understanding of regulatory mechanisms.

Date: 2018
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DOI: 10.1038/s41467-018-03209-9

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