Project description:Deciphering the impact of genetic variants on gene regulation is fundamental to understanding human disease. Although gene regulation often involves long-range interactions, it is unknown to what extent non-coding genetic variants influence distal molecular phenotypes. Here, we integrate chromatin profiling for three histone marks in lymphoblastoid cell lines (LCLs) from 75 sequenced individuals with LCL-specific Hi-C and ChIA-PET-based chromatin contact maps to uncover one of the largest collections of local and distal histone quantitative trait loci (hQTLs). Distal QTLs are enriched within topologically associated domains and exhibit largely concordant variation of chromatin state coordinated by proximal and distal non-coding genetic variants. Histone QTLs are enriched for common variants associated with autoimmune diseases and enable identification of putative target genes of disease-associated variants from genome-wide association studies. These analyses provide insights into how genetic variation can affect human disease phenotypes by coordinated changes in chromatin at interacting regulatory elements.
Project description:Chickens are the most abundant agricultural animals globally, with controlling abdominal fat deposition (AFD) being a key objective in poultry breeding. While GWAS can identify genetic variants associated with AFD traits, the precise roles and mechanisms of these variants remain largely unclear. This study used two distinct chicken lines, selectively bred for differing AFD, as experimental models. Through the integration of genomic, epigenomic, 3D genomic, and transcriptomic data, a comprehensive chromatin 3D regulatory network map was developed to reveal the genetic regulatory mechanisms that influence AFD traits.
Project description:Background: Germline polymorphisms can influence gene expression networks in normal mammalian tissues and can affect disease susceptibility. We and others have shown that analysis of this genetic architecture can identify single genes and whole pathways that influence complex traits including inflammation and cancer susceptibility. Whether germline variants affect gene expression in tumors which have undergone somatic alterations, and the extent to which these variants influence tumor progression, is unknown. Results: Using an integrated linkage and genomic analysis of a mouse model of skin cancer that produces both benign tumors and malignant carcinomas, we document major changes in germline control of gene expression during skin tumor development resulting from cell selection, somatic genetic events, and changes in the tumor microenvironment. The number of significant expression Quantitative Trait Loci (eQTLs) is progressively reduced in benign and malignant skin tumors when compared to normal skin. However, novel tumor-specific eQTLs are detected for several genes associated with tumor susceptibility, including Interleukin 18, Granzyme E, Sprouty homolog 2, and MAP kinase kinase 4. Conclusions: We conclude that the genetic architecture is substantially altered in tumors, and that eQTL analysis of tumors can identify host factors that influence the tumor microenvironment, MAP kinase signaling, and cancer susceptibility.
Project description: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.
