Research Resources: Epigenomic and Transcriptomic Profiles of Human Immune Cells

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DESCRIPTION (provided by applicant): Genome-wide association studies (GWAS) have identified genetic variants (often single-nucleotide polymorphisms, SNPs) associated with increased susceptibility to many human diseases. The vast majority of these variants are located in non-coding genomic regions, and so are thought to influence disease outcome by perturbing the functions of cis-regulatory DNA elements that control gene expression on the same allele. To understand the role of common genetic variations in human disease, we propose here to perform epigenomic and transcriptomic analyses of 13 purified circulating immune cell types from healthy human subjects. Aim 1: For each immune cell type from each donor, we will determine the genome-wide locations of H3K4me2 and H3K27Ac, two histone modifications associated with functional enhancers; we will also obtain the transcriptional profiles of the cells as well as genotype and whole-genome haplotype information. This will allow us to determine, for each human cell type, the gene expression profiles as well as the strength and cell type-specificity of cis-regulatory elements. Aim 2: We will identify cis-regulatoy elements that harbor disease- associated variants, predict if they disrupt transcription factor binding sites, and use data from heterozygous subjects to determine if allele-specific differences in cis-regulatory activity are linked to corresponding changes in gene expression on the cis allele. This will allow us to establish a computational pipeline that predicts, for each set of disease-associated genetic variations, which cis-regulatory elements, transcription factors, genes, immune cell types and molecular pathways are most likely to be disrupted. Aim 3: We will make our experimental results and analysis tools available on a dedicated website that will be designed and optimized to provide immunologists with intuitive interfaces that maximize the ability to answer research questions without requiring advanced bioinformatics expertise. RELEVANCE: For many human diseases, large-scale genomic studies have identified common genetic variants that occur more frequently in people with cardiovascular, autoimmune, inflammatory and infectious diseases, diabetes and asthma than in those without these diseases. Here we propose to understand how these variants cause susceptibility to disease, focusing on diseases related to the immune system, and use this information to find novel therapeutic targets for these diseases.