Genome-wide identification of microRNA expression quantitative trait loci

Tianxiao Huan, Jian Rong, Chunyu Liu, Xiaoling Zhang, Kahraman Tanriverdi, Roby Joehanes, Brian H. Chen, Joanne M. Murabito, Chen Yao, Paul Courchesne, Peter J. Munson, Christopher J. O’Donnell, Nancy Cox, Andrew D. Johnson, Martin G. Larson, Daniel Levy () and Jane E. Freedman ()
Additional contact information
Tianxiao Huan: The Framingham Heart Study
Jian Rong: Boston University
Chunyu Liu: The Framingham Heart Study
Xiaoling Zhang: The Framingham Heart Study
Kahraman Tanriverdi: University of Massachusetts Medical School
Roby Joehanes: The Framingham Heart Study
Brian H. Chen: The Framingham Heart Study
Joanne M. Murabito: The Framingham Heart Study
Chen Yao: The Framingham Heart Study
Paul Courchesne: The Framingham Heart Study
Peter J. Munson: Mathematical and Statistical Computing Laboratory, Center for Information Technology, National Institutes of Health
Christopher J. O’Donnell: The Framingham Heart Study
Nancy Cox: University of Chicago
Andrew D. Johnson: The Framingham Heart Study
Martin G. Larson: The Framingham Heart Study
Daniel Levy: The Framingham Heart Study
Jane E. Freedman: University of Massachusetts Medical School

Nature Communications, 2015, vol. 6, issue 1, 1-9

Abstract: Abstract Identification of microRNA expression quantitative trait loci (miR-eQTL) can yield insights into regulatory mechanisms of microRNA transcription, and can help elucidate the role of microRNA as mediators of complex traits. Here we present a miR-eQTL mapping study of whole blood from 5,239 individuals, and identify 5,269 cis-miR-eQTLs for 76 mature microRNAs. Forty-nine per cent of cis-miR-eQTLs are located 300–500 kb upstream of their associated intergenic microRNAs, suggesting that distal regulatory elements may affect the interindividual variability in microRNA expression levels. We find that cis-miR-eQTLs are highly enriched for cis-mRNA-eQTLs and regulatory single nucleotide polymorphisms. Among 243 cis-miR-eQTLs that were reported to be associated with complex traits in prior genome-wide association studies, many cis-miR-eQTLs miRNAs display differential expression in relation to the corresponding trait (for example, rs7115089, miR-125b-5p and high-density lipoprotein cholesterol). Our study provides a roadmap for understanding the genetic basis of miRNA expression, and sheds light on miRNA involvement in a variety of complex traits.

Date: 2015
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DOI: 10.1038/ncomms7601

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