Spatial transcriptomics reveal markers of histopathological changes in Duchenne muscular dystrophy mouse models

Abstract

Duchenne muscular dystrophy (DMD) is caused by mutations in the DMD gene, leading to lack of dystrophin. Chronic muscle damage eventually leads to histological alterations in skeletal muscles. The identification of genes and cell types driving tissue remodeling is a key step to develop effective therapies. Here we use spatial transcriptomics in two DMD mouse models differing in disease severity to identify gene expression signatures underlying skeletal muscle pathologies and directly link this to the muscle histology. Deconvolution analysis allowed the identification of cell types contributing to histological alterations. We show how the expression of specific genes is enriched in areas of muscle regeneration (Myl4, Sparc, Hspg2), fibrosis (Vim, Fn1, Thbs4) and calcification (Bgn, Ctsk, Spp1). Finally, our analysis of differentiation dynamics in the severely affected D2-mdx muscle shows a subset of the muscle fibers are predicted to become affected in its future state. Genes associated with tissue remodeling could enable to design new diagnostic and therapeutic strategies for DMD.

SIRV: Spatial inference of RNA velocity at the single-cell resolution

“…Currently, a wide range of protocols [10][11][12][13][14][15][16][17] is available which varies in spatial resolution, gene detection sensitivity and number of simultaneously measured genes. In principle, it is possible to apply RNA velocity analysis to spatial transcriptomics measured using sequencing-based protocols, such as 10x Visium and Slide-seq 10,11 , as the spliced and unspliced expression ratios can be directly obtained from the sequencing data 11,18 . However, the spatial resolution of these protocols is currently limited to measuring tissue spots consisting of multiple cells.…”

High-Resolution Spatial Transcriptomic Atlas of Mouse Soleus Muscle: Unveiling Single Cell and Subcellular Heterogeneity in Health and Denervation

“…Previously, transcriptome-level studies in skeletal muscle were only conducted in scRNA/snRNA-seq platforms or the 10X VISIUM platform, which erases spatial information or only provides very coarse (100 µm center-to-center resolution) spatial information. Due to the limitations in spatial resolution, all spatial transcriptomics studies in skeletal muscle performed to date only utilized horizontal cross-sections [16][17][18], and therefore could not profile continuous transcriptomic mapping along the muscle fiber's length and thus fails to address zonal differences along the longitudinal axis. By providing submicrometer-level spatial information while still characterizing whole transcriptome without target selection, we provided an unprecedented level of detail of how transcriptome structure is organized histologically in longitudinal section of the skeletal muscle.…”

“…However, this method faced significant challenges when applied to skeletal muscle research. One major limitation is the resolution; current spatial transcriptomics techniques, such as the 10X Visium platform, offer a resolution that is often too coarse to distinguish individual cells or subcellular structures, such as the intricate arrangement of muscle fibers and neuromuscular junctions [16][17][18]. This limitation means that the heterogeneity and complex interactions within skeletal muscle tissue can be obscured, with the resulting data representing a mixture of signals from multiple cell types.…”

“…Spatial transcriptomics provides a two-dimensional map of transcriptomic data, allowing researchers to visualize gene expression patterns in relation to the tissue architecture [13][14][15]. Several recent studies used this technique to understand muscle transcriptome in health and disease states [16][17][18]. However, this method faced significant challenges when applied to skeletal muscle research.…”

Multiomic characterization of disease progression in mice lacking dystrophin

“…Example of known fibrosis markers present in LF1 are Cola1, Cola2, Col3a1, Bgn, Fn1, Spp1 and Ftl1 genes [46][47][48][49][50][51]. Genes involved in muscle regeneration (Myl4, Mybph, Sparc, Gpx1, Myod1 and Myog) and immune response (Lyz2, Spp1, Ctsb) were also represented in LF1 [52]. We further looked into whether the 883 genes whose loadings have absolute value above 2 had previously been associated reported to be associated with neuromuscular disorder.…”