Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits

Abstract

<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases, mobility, and quality of life. It is composed of several different cell and muscle fiber types.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We capture type I and type II muscle fiber signatures, which are generally missed by existing single-cell RNA-seq methods. We perform cross-modality and cross-species integrative analyses on 30,531 nuclei, representing 11 libraries, profiled in this study, and identify seven distinct cell types ranging in abundance from 63% (type II fibers) to 0.9% (muscle satellite cells) of all nuclei. We introduce a regression-based approach to infer cell types by comparing transcription start site-distal ATAC-seq peaks to reference enhancer maps and show consistency with RNA-based marker gene cell type assignments. We find heterogeneity in enrichment of genetic variants linked to complex phenotypes from the UK Biobank and diabetes genome wide association studies in cell-specific ATAC-seq peaks, with the most striking enrichment patterns in muscle mesenchymal stem cells (∼3% of nuclei). Finally, we overlay these chromatin accessibility maps on GWAS data to nominate causal cell types, SNPs, and transcription factor motifs for creatinine levels and type 2 diabetes signals.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>These chromatin accessibility profiles for human and rat skeletal muscle cell types are a useful resource for investigating specific cell types and nominating causal GWAS SNPs and cell types.</jats:p></jats:sec>

Single-nuclei Transcriptome of Human AT Reveals Metabolically Distinct Depot-Specific Adipose Progenitor Subpopulations

“…Future steps will also include the addition of single nuclear ATAC strategies and multiomic analysis to identify the regulatory regions that are responsible for the gene expression changes as has been recently performed for skeletal muscle in diabetes. 58 (which was not certified by peer review) is the author/funder. All rights reserved.…”

An Evidence-Based Narrative Review of Mechanisms of Resistance Exercise–Induced Human Skeletal Muscle Hypertrophy

“…Studies applying new methods, using in vivo measurement of rRNA synthesis, might bring additional input to assess the role of translational capacity in skeletal muscle hypertrophy, and endocrine-related factors, such as AR content in skeletal muscle and female sex hormones, may yet help us understand the role of these variables in skeletal muscle physiology and hypertrophy. More work is still required, but with the rapid development of technology, the up-to-date techniques in skeletal muscle, such as single-cell isolation and single-cell RNA-seq (139,140), could be considered to accelerate to uncover the mechanisms underpinning RET-induced skeletal muscle hypertrophy in humans.…”

“…content in skeletal muscle and female sex hormones, may yet help us understand the role of these variables in skeletal muscle physiology and hypertrophy. More work is still required, but with the rapid development of technology, the up-to-date techniques in skeletal muscle, such as single-cell isolation and single-cell RNA-seq (139,140), could be considered to accelerate to uncover the mechanisms underpinning RETinduced skeletal muscle hypertrophy in humans.…”

Spatial transcriptomics tools allow for regional exploration of heterogeneous muscle pathology in the pre-clinical rabbit model of rotator cuff tear

“…Muscle cells, however, can be several centimeters long [17] and thus, clearly exceed the length capacity of high-throughput droplet-based single-cell technologies. As an innovative alternative, single-nuclei RNA sequencing (snRNA-seq) has been employed for skeletal muscle [18][19][20]. This approach, too, has at least three noteworthy limitations for skeletal muscle: (1) muscle fibers are multinucleated cells-it is often unknown how many and which nuclei were derived from which cell, (2) the vast majority of RNA molecules are located outside the nucleus [21,22] and therefore missed by snRNA-seq, and (3) there is significant heterogeneity in the spatial distribution of RNA molecules within muscle fibers [21,22] and nucleus translocation to the fiber center during degeneration and regeneration [6,7,23].…”