Population-scale skeletal muscle single-nucleus multi-omic profiling reveals extensive context specific genetic regulation

Varshney, A.; Manickam, N.; Orchard, P.; Tovar, A.; Zhang, Z.; Feng, F.; Erdos, M. R.; Narisu, N.; Ventresca, C.; Nishino, K.; Rai, V.; Stringham, H.; Jackson, A. U.; Tamsen, T.; Gao, C.; Yang, M.; Koues, O. I.; Welch, J. D.; Burant, C. F.; Williams, L. K.; Jenkinson, C.; DeFronzo, R. A.; Norton, L.; Saramies, J.; Lakka, T. A.; Laakso, M.; Tuomilehto, J.; Mohlke, K. L.; Kitzman, J. O.; Koistinen, H. A.; Liu, J.; Boehnke, M.; Collins, F. S.; Scott, L. J.; Parker, S. C.

doi:10.1101/2023.12.15.571696

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bioRxiv · 10.1101/2023.12.15.571696

Population-scale skeletal muscle single-nucleus multi-omic profiling reveals extensive context specific genetic regulation

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Abstract

Skeletal muscle, the largest human organ by weight, is relevant in several polygenic metabolic traits and diseases including type 2 diabetes (T2D). Identifying genetic mechanisms underlying these traits requires pinpointing cell types, regulatory elements, target genes, and causal variants. Here, we use 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 nearly half a million nuclei. We identify 13 cell types and integrate genetic variation to discover >7,000 expression quantitative trait loci (eQTL) and >100,000 chromatin accessibility QTLs (caQTL) across cell types. Learning patterns of e/caQTL sharing across cell types increased precision of effect estimates. We identify high-resolution cell-states and context-specific e/caQTL with significant genotype by context interaction. We identify nearly 2,000 eGenes colocalized with caQTL and construct causal directional maps for chromatin accessibility and gene expression. Almost 3,500 genome-wide association study (GWAS) signals across 38 relevant traits colocalize with sn-e/caQTL, most in a cell-specific manner. These signals typically colocalize with caQTL and not eQTL, highlighting the importance of population-scale chromatin profiling for GWAS functional studies. Finally, our GWAS-caQTL colocalization data reveal distinct cell-specific regulatory paradigms. Our 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.

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Varshney, A., Manickam, N., Orchard, P., Tovar, A., Zhang, Z., Feng, F., Erdos, M. R., Narisu, N., Ventresca, C., Nishino, K., Rai, V., Stringham, H., Jackson, A. U., Tamsen, T., Gao, C., Yang, M., Koues, O. I., Welch, J. D., Burant, C. F., Williams, L. K., Jenkinson, C., DeFronzo, R. A., Norton, L., Saramies, J., Lakka, T. A., Laakso, M., Tuomilehto, J., Mohlke, K. L., Kitzman, J. O., Koistinen, H. A., Liu, J., Boehnke, M., Collins, F. S., Scott, L. J., Parker, S. C.. 2023-12-15. Population-scale skeletal muscle single-nucleus multi-omic profiling reveals extensive context specific genetic regulation. https://doi.org/10.1101/2023.12.15.571696

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