Expression profiling by high throughput sequencing Genome binding/occupancy profiling by high throughput sequencing
To fully comprehend how genetic variants influence phenotypes, we must understand the functions of 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.
H3K27ac ChIP-seq, H3K4me1 ChIP-seq, H3K27ac HiChIP-seq, CTCF HiChIP-seq, and RNA-seq data are generated from 25 lymphoblastoid cell lines (LCLs) from European-American patients with systemic lupus erythematosus