Research Resources: Epigenomic and Transcriptomic Profile of Human Immune Cells

La Jolla Institute For Immunology, La Jolla CA

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Abstract

PROJECT SUMMARY While an enormous number of genetic variants have been associated with risk for human disease, how these variants affect gene expression in various cell types remains largely unknown. To address this gap as it relates to immune cells, as well as to identify which immune cell types are most susceptible to the effects of disease- risk variants, the DICE (Database of Immune Cell Expression, Expression quantitative trait loci (eQTLs) and Epigenomics) project was funded by the current R24 resource grant (R24AI108564). Although several autoimmune diseases like Systemic lupus erythematosus (SLE), display severe clinical manifestations in patients of Hispanic/Latino, Asian and African ancestry, the genetic risk factors that influence disease mechanisms have not been extensively studied, largely due to the exclusive focus of the initial genome-wide association studies (GWAS) on individuals of European ancestry. However, recent multi-ancestry GWAS meta- analyses that included individuals of diverse ancestries have identified many ancestry-specific disease-risk variants. To translate the biological significance of these GWAS-led discoveries in under-represented populations, high-resolution eQTL studies in immune cell types from individuals of diverse ancestries are needed to define the effects of disease-risk variants. While the current DICE cohort is more diverse (46% Europeans) compared to other large-scale eQTL studies, there remains a need to include equal representation from other globally prevalent ancestral populations. In Aim 1, we will generate transcriptomic and eQTL reference data in common and rare circulating immune cell types from equal numbers of male and female individuals of Hispanic/Latino, African, East Asian, South Asian and European ancestries (n=350; n=70/ancestral group) – DICE-Diversity resource project. We will perform single-cell RNA-seq in flow-sorted immune cell types and conduct single-cell-eQTL mapping to test associations between variants and gene expression. In Aim 2, we will define genes and cell types associated with autoimmune diseases in diverse populations, including minorities. To accomplish this objective, we will perform TWAS and colocalization analysis to integrate published multi-ancestry GWAS in autoimmune disease and eQTL datasets in immune cell types generated in this DICE-Diversity project. In Aim 3, we will make DICE data accessible and visible to the broader scientific community. We will expand our existing website to make current and newly generated experimental data and analysis tools available to the community. Overall, the renewal of the DICE project will greatly enrich this dataset with descriptions from individuals of different ancestries. The new DICE-Diversity database of transcriptomic and eQTL data for the human immune system should also facilitate mechanistic and functional investigations into the role of disease-risk variants emerging from multi-ancestry GWAS studies and eventually benefit health outcomes in diverse populations, including minorities.