eQTL mapping identifies insertion- and deletion-specific eQTLs in multiple tissues

Jinyan Huang, Jun Chen, Jorge Esparza, Jun Ding, James T. Elder, Goncalo R. Abecasis, Young-Ae Lee, G. Mark Lathrop, Miriam F. Moffatt, William O. C. Cookson and Liming Liang ()
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Jinyan Huang: State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine
Jun Chen: Harvard School of Public Health
Jorge Esparza: Max-Delbrück-Center for Molecular Medicine
Jun Ding: Laboratory of Genetics, National Institute on Aging, National Institutes of Health
James T. Elder: University of Michigan Medical School
Goncalo R. Abecasis: University of Michigan, Ann Arbor
Young-Ae Lee: Max-Delbrück-Center for Molecular Medicine
G. Mark Lathrop: McGill University and Génome Québec Innovation Centre
Miriam F. Moffatt: National Heart and Lung Institute, Imperial College London
William O. C. Cookson: National Heart and Lung Institute, Imperial College London
Liming Liang: Harvard School of Public Health

Nature Communications, 2015, vol. 6, issue 1, 1-8

Abstract: Abstract Genome-wide gene expression quantitative trait loci (eQTL) mapping have been focused on single-nucleotide polymorphisms and have helped interpret findings from diseases mapping studies. The functional effect of structure variants, especially short insertions and deletions (indel) has not been well investigated. Here we impute 1,380,133 indels based on the latest 1,000 Genomes Project panel into three eQTL data sets from multiple tissues. Imputation of indels increased 9.9% power and identifies indel-specific eQTLs for 325 genes. We find introns and vicinities of UTRs are more enriched of indel eQTLs and 3.6 (single-tissue)–9.2%(multi-tissue) of previous identified eSNPs were taggers of eindels. Functional analyses identifies epigenetics marks, gene ontology categories and disease GWAS loci affected by SNPs and indels eQTLs showing tissue-consistent or tissue-specific effects. This study provides new insights into the underlying genetic architecture of gene expression across tissues and new resource to interpret function of diseases and traits associated structure variants.

Date: 2015
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DOI: 10.1038/ncomms7821

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