Nejc Umek (Author), Marija Meznarič (Author), Žiga Šink (Author), Kaja Blagotinšek Cokan (Author), Uršula Prosenc (Author), Simon Horvat (Author)

Abstract

Traditional transcriptomic studies often overlook the complex heterogeneity of skeletal muscle, as they typically isolate RNA from mixed muscle fibre and cell populations, resulting in an averaged transcriptomic profile that obscures fibre type-specific differences. This study assessed the potential of the recently developed Xenium platform for high-resolution spatial transcriptomic analysis of human skeletal muscle histological sections. Human vastus lateralis muscle samples from two individuals were analysed using the Xenium platform and Human Multi-Tissue and Cancer Panel targeting 377 genes complemented by staining of successive sections for Myosin Heavy Chain isoforms to differentiate between type 1 and type 2 muscle fibres. Manual segmentation of muscle fibres allowed accurate comparisons of transcript densities across fibre types and subcellular regions, overcoming limitations in the platform’s automated segmentation. The analysis revealed higher transcript density in type 1 fibres, particularly in nuclear and perinuclear areas, and identified 191 out of 377 genes with differential expression between muscle fibres and perimysium. Genes such as PROX1, S100A1, LGR5, ACTA2, and LPL exhibited higher expression in type 1 fibres, whereas PEBP4, CAVIN1, GATM, and PVALB in type 2 fibres. We demonstrated that the Xenium platform is capable of high-resolution spatial in situ transcriptomic analysis of skeletal muscle histological sections. This study demonstrates that, with manual segmentation, the Xenium platform effectively performs fibre type-specific transcriptomic analysis, providing new insights into skeletal muscle biology.

Keywords

genetika;skeletne mišice;transkriptomika;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UL BF - Biotechnical Faculty
UDC: 575
COBISS: 221773059 Link will open in a new window
ISSN: 0302-766X
Views: 66
Downloads: 24
Average score: 0 (0 votes)
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Other data

Secondary language: Slovenian
Secondary keywords: genetika;skeletne mišice;transkriptomika;
Type (COBISS): Article
Pages: str. 291-302
Volume: ǂVol. ǂ399
Issue: ǂiss. ǂ3
Chronology: 2025
DOI: 10.1007/s00441-024-03945-z
ID: 26220566
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