Single-nucleus chromatin and gene expression profiling across hundreds of skeletal muscle samples reveals context-specific regulation

Skeletal muscle is relevant to several polygenic metabolic traits and diseases including type 2 diabetes (T2D). Identifying genetic mechanisms underlying these traits requires pinpointing the relevant cell-types, regulatory elements, target genes, and causal variants. Here, we used genetic multiplexing to generate population-scale single nucleus (sn) chromatin accessibility (snATAC-seq) and transcriptome (snRNA-seq) maps across 287 frozen human skeletal muscle biopsies representing 456,880 nuclei. We identified 13 cell-types that collectively represented 983,155 ATAC summits. We integrated genetic information to identify 6,866 expression quantitative trait loci (eQTL) and 100,928 chromatin accessibility QTL (caQTL) (5% FDR) across the five most abundant cell-types, and show atlas-level snATAC maps often miss peaks. We identified 12,046 e-caQTL colocalizations and inferred causality between chromatin accessibility and gene expression through mediation analyses. 3,378 genome-wide association study (GWAS) signals across 43 relevant traits colocalized with sn e/caQTL, 52% in a cell-type-specific manner. 77% (3,616) GWAS signals colocalized with caQTLs and not eQTL, highlighting the importance of sn-caQTL maps for GWAS functional studies. GWAS-e/caQTL colocalization showed distinct cell-type-specific regulatory paradigms. For example, a C2CD4A/B T2D GWAS signal colocalized with caQTLs in muscle fibers and imputed chromatin contacts nominated VPS13C - a glucose uptake gene. The caQTL peak overlapping caSNP rs7163757 showed allelic regulatory activity differences in a human myocyte cell line massively parallel reporter assay. These results illuminate the genetic regulatory architecture of human skeletal muscle at high-resolution epigenomic, transcriptomic, and cell state scales and serve as a template for population-scale multi-omic mapping in complex tissues and traits.