Transcriptomics

Dataset Information

0

Isolated fiber-type transcriptional profiles in human skeletal muscle


ABSTRACT: Skeletal muscle is a complex heterogeneous tissue comprised of diverse muscle fiber and non-fiber cell types that, in addition to movement, influences other systems such as immunity, metabolism and cognition. We investigated gene expression patterns of resident human skeletal muscle cells using both single-cell RNA-seq and RNA-seq of single muscle fiber dissections from vastus lateralis. We generated transcriptome profiles of the major multinucleated human skeletal muscle fiber-types as well as 11 human skeletal muscle mononuclear cell types, including immune, endothelial, pericyte and satellite cells.  We delineated two fibro-adipogenic progenitor cell subtypes that may contribute to heterotopic ossification and muscular dystrophy fibrosis under pathological conditions. An important application of cell type signatures is for computational deconvolution of cell type specific gene expression changes using data from bulk transcriptome experiments. Analysis of transcriptome data from a 12 week resistance exercise training study using these human skeletal muscle cell-type signatures revealed significant changes in specific mononuclear cell-type proportions related to age, sex, acute exercise and training. This characterization of human skeletal muscle cell types will resolve cell-type specific changes in large-scale physical activity muscle transcriptome studies and can further the understanding of the diverse effects of exercise and the pathophysiology of muscle disease.

ORGANISM(S): Homo sapiens

PROVIDER: GSE130977 | GEO | 2020/02/01

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2020-01-16 | GSE130646 | GEO
2020-12-21 | PXD012824 | Pride
2018-08-07 | E-MTAB-5447 | biostudies-arrayexpress
2024-10-17 | PXD036010 | Pride
2024-07-30 | PXD053003 | Pride
2018-07-24 | GSE117525 | GEO
2021-06-07 | PXD025359 | Pride
2014-11-19 | E-GEOD-59088 | biostudies-arrayexpress
2016-08-14 | E-GEOD-60833 | biostudies-arrayexpress
2019-02-16 | GSE120862 | GEO