Single-nucleus maps of human skeletal muscle expose cell-specific genetic control of metabolic traits

Skeletal muscle does far more than move the body. It is a major metabolic organ, and genetic variants that influence traits such as diabetes risk often exert their effects through the muscle cells themselves.

A team led by researchers including Arushi Varshney and Stephen C. J. Parker used a technique called genetic multiplexing to profile 287 frozen human skeletal muscle biopsies at single-nucleus resolution. Using single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq), they measured which stretches of DNA are open and potentially active in each cell, and with single-nucleus RNA sequencing (snRNA-seq) they measured which genes are actually switched on.

The profiling identified 13 distinct cell types within the muscle samples.

By integrating genetic variation from the donors, the researchers discovered more than 7,000 expression quantitative trait loci (eQTLs), which are variants associated with gene activity levels, and more than 100,000 chromatin accessibility QTLs (caQTLs), which are variants associated with whether particular DNA regions are open. These signals were catalogued across the different cell types, and some were context-specific, showing significant interactions between genotype and cellular context.

The team identified nearly 2,000 eGenes, meaning genes whose expression is controlled by nearby or distant genetic variants, that colocalized with caQTLs. They also constructed causal directional maps linking chromatin accessibility to gene expression, an approach designed to indicate which regulatory changes are likely driving changes in gene activity rather than merely occurring alongside them.

The most striking result concerns disease genetics. Almost 3,500 signals from genome-wide association studies (GWAS) across 38 cardiometabolic and related traits colocalized with the single-nucleus eQTLs or caQTLs, and most of these did so in a cell-specific manner. In other words, the genetic variants associated with metabolic traits could be tied to particular cell types within skeletal muscle.

Notably, these GWAS signals typically colocalized with caQTLs rather than eQTLs. That pattern suggests that many disease-associated variants act first by changing chromatin accessibility, the opening or closing of DNA regions that controls how genes can be read, rather than by directly altering gene expression. The authors argue that this highlights the importance of population-scale chromatin profiling for functional follow-up of GWAS findings.

The work was published in Nature Genetics.

For researchers trying to move from GWAS hits to biological mechanisms, the resource offers a way to narrow down which cell type, which regulatory element and which target gene a candidate variant is likely to affect.

The results, the authors write, illuminate the genetic regulatory architecture of human skeletal muscle, providing a reference map that connects cell types, regulatory elements, target genes and causal variants for polygenic metabolic traits and diseases.

Subject of Research: Single-nucleus multi-omic profiling of human skeletal muscle to map cell-type-specific genetic regulation of metabolic traits

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

Article References: Varshney, A., Manickam, N., Orchard, P., Tovar, A., Ventresca, C., Zhang, Z., Feng, F., Mears, J., Erdos, M. R., Narisu, N., Nishino, K., Rai, V., Stringham, H. M., Jackson, A. U., Tamsen, T., Gao, C., Yang, M., Koues, O. I., Welch, J. D., … Parker, S. C. J. (2026). Population-scale single-nucleus multi-omic profiling of skeletal muscle reveals extensive context-specific genetic regulation. Nature Genetics. https://doi.org/10.1038/s41588-026-02786-6

Image Credits: AI Generated

DOI: 10.1038/s41588-026-02786-6

Keywords: skeletal muscle, single-nucleus multi-omics, snATAC-seq, snRNA-seq, eQTL, caQTL, chromatin accessibility, GWAS, cardiometabolic traits, gene regulation, genetics, Nature Genetics