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Nat Commun. 2018 Jul 25;9(1):2905. doi: 10.1038/s41467-018-05328-9.

Enhancer histone-QTLs are enriched on autoimmune risk haplotypes and influence gene expression within chromatin networks.

Author information

1
Division of Genomics and Data Sciences, Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, 73104, OK, USA.
2
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Charlestown, 02115, MA, USA.
3
Department of Pathology, Harvard Medical School, Boston, 02115, MA, USA.
4
Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital, Cincinnati, 45229, OH, USA.
5
Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, 73104, OK, USA.
6
Departments of Medicine and Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, 73104, OK, USA.
7
Division of Genomics and Data Sciences, Arthritis and Clinical Immunology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, 73104, OK, USA. Patrick-Gaffney@omrf.org.

Abstract

Genetic variants can confer risk to complex genetic diseases by modulating gene expression through changes to the epigenome. To assess the degree to which genetic variants influence epigenome activity, we integrate epigenetic and genotypic data from lupus patient lymphoblastoid cell lines to identify variants that induce allelic imbalance in the magnitude of histone post-translational modifications, referred to herein as histone quantitative trait loci (hQTLs). We demonstrate that enhancer hQTLs are enriched on autoimmune disease risk haplotypes and disproportionately influence gene expression variability compared with non-hQTL variants in strong linkage disequilibrium. We show that the epigenome regulates HLA class II genes differently in individuals who carry HLA-DR3 or HLA-DR15 haplotypes, resulting in differential 3D chromatin conformation and gene expression. Finally, we identify significant expression QTL (eQTL) x hQTL interactions that reveal substructure within eQTL gene expression, suggesting potential implications for functional genomic studies that leverage eQTL data for subject selection and stratification.

PMID:
30046115
PMCID:
PMC6060153
DOI:
10.1038/s41467-018-05328-9
[Indexed for MEDLINE]
Free PMC Article

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