Skeletal muscle cell MHC I expression: Implications for statin-induced myopathy

2009 ◽  
Vol 41 (2) ◽  
pp. 179-184 ◽  
Author(s):  
Pratibha Singh ◽  
Danielle Kohr ◽  
Manfred Kaps ◽  
Franz Blaes
Keyword(s):  
Skeletal Muscle ◽  
Muscle Cell ◽  
Skeletal Muscle Cell ◽  
Mhc I

THE MYOGRAM OF THE ISOLATED SKELETAL MUSCLE CELL

Science ◽  
1930 ◽  
Vol 72 (1853) ◽  
pp. 17-18 ◽  
Author(s):  
D. E. S. Brown ◽  
F. J. M. Sichel
Keyword(s):  
Skeletal Muscle ◽  
Muscle Cell ◽  
Skeletal Muscle Cell

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

2021 ◽  
Author(s):  
Peter Orchard ◽  
Nandini Manickam ◽  
Christa Ventresca ◽  
Swarooparani Vadlamudi ◽  
Arushi Varshney ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Muscle Cell ◽  
Muscle Fiber ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Skeletal Muscle Cell ◽  
Rna Seq ◽  
Rat Skeletal Muscle ◽  
Integrative Analyses ◽  
Single Nucleus

Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. 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 additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples. 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 33,862 nuclei and identify seven cell types ranging in abundance from 59.6% to 1.0% 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 (∼3.5% of nuclei). Finally, we overlay these chromatin accessibility maps on GWAS data to nominate causal cell types, SNPs, transcription factor motifs, and target genes for type 2 diabetes signals. These chromatin accessibility profiles for human and rat skeletal muscle cell types are a useful resource for nominating causal GWAS SNPs and cell types.

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