The OneK1K cohort consists of single-cell RNA sequencing (scRNA-seq) data from 1.27 million peripheral blood mononuclear cells (PMBCs) collected from 982 donors. We developed a framework for the classification of individual cells, and by combining the scRNA-seq data with genotype data, we mapped the genetic effects on gene expression in each of 14 immune cell types and identified 26,597 independent cis–expression quantitative trait loci (eQTLs). We show that most of these have an allelic effect on gene expression that is cell type-specific.

Using the top associated eQTL single-nucleotide polymorphism (eSNP) at each locus outside the major histocompatibility complex (MHC) region, we identified 990 trans-acting effects, most (63.6%) of which were cell type-specific. We show how eQTLs have dynamic allelic effects in B cells that are transitioning from naïve to memory states. Overall, we identified a set of 1988 eSNP–eGene (a gene with an eQTL) pairs expressed across the B cell maturation landscape, of which 333 have a statistically significant change in their allelic effect as B cells differentiate. Of these, 66% were only identified from the dynamic eQTL analysis and were not observed when testing for effects independently in cell types.

We integrated genetic association data for seven common autoimmune diseases and identified significant enrichment of genetic effects operating in a cell type-specific manner. Through colocalization of single-cell eQTL and genome-wide association study (GWAS) loci, we found that 19% of cis-eQTLs share the same causal locus as a GWAS risk association. Using a Mendelian randomization approach, we uncovered the causal route by which 305 loci contribute to autoimmune disease through changes in gene expression in specific cell types and subsets.