scholarly journals Cloning and promoter analysis of palladin 90-kDa, 140-kDa, and 200-kDa isoforms involved in skeletal muscle cell maturation

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Boimpoundi Eunice Flavie Ouali ◽  
Tzu-Yu Liu ◽  
Chun-Yen Lu ◽  
Pei-Yuan Cheng ◽  
Chao-Li Huang ◽  
...  
In Vivo ◽  
2020 ◽  
Vol 34 (6) ◽  
pp. 3247-3254
Author(s):  
SHIORI ANDO ◽  
MIRUTO TANAKA ◽  
NAOKI CHINEN ◽  
SHINSUKE NAKAMURA ◽  
MASAMITSU SHIMAZAWA ◽  
...  

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

2021 ◽  
Author(s):  
Peter Orchard ◽  
Nandini Manickam ◽  
Christa Ventresca ◽  
Swarooparani Vadlamudi ◽  
Arushi Varshney ◽  
...  

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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