(A) Analysis workflow for CD45⁺ cell scRNA-Seq and ST (Visium) of regenerating and dystrophic muscle. Cell suspensions were collected from digested TAs of adult mice at 1, 2, and 4 days after CTX injury and steady-state GAST of 2-mo D2.mdx. PBMC datasets from noninjured C57BL/6J mice were from 10x Genomics. Enhanced spatial resolution, deconvolution, and cooccurrence of myeloid subtypes are achieved by single-cell and spatial dataset integration (BayesSpace and Cell2location). (B) Single-cell transcriptomes from CD45⁺ cells at days 1, 2, and 4 after CTX injury, and PBMCs were harmony integrated and batch-effect corrected. Data (24,382 cells) are presented as a PaCMAP projection and color coded by origin. (C) Integrated transcriptomic atlas of 10 major populations (SingleR automated cell type annotation ImmGen database) (96). Cell types are color coded. Right: cell-type proportions and compositional dynamics. MFs account for 41.2% of all immune cells. (D) Cells in the macro-clusters of interest (monocytes, MFs, and DCs) were reanalyzed in isolation. t-distributed stochastic neighbor embeddingg (t-SNE) visualization reveals local differences. Cells are colored by major cell-type classification. (E) Clustering of the isolated cell types from D resolved 10 subtypes of monocytes, MFs, and DCs. Subcluster composition (absolute numbers) is presented as an alluvial plot. (F) t-SNE visualization of subtypes of monocytes, MFs, and DCs. (G) Dot plot of top DEGs distinguishing the monocyte/MF/DC clusters (3 DC: clusters 7, 9 and 10; 2 monocytic: clusters 3 and 6; 2 MF subtypes: clusters 1, 4; and 3 MF transitional states: clusters 2, 5, and 8; A). Dot size represents the percentage of cells expressing each marker within a cluster. Gpnmb, the top GFEM marker (cluster 1) is highlighted in red. (H) t-SNE colored by cluster and inferred pseudotime (Slingshot; principal curves are smoothed representations of each lineage) with 4 predicted cell fates: 1 monocyte (patrolling monocytes), 1 MF (GFEMs), and 2 DC lineages. Origin determines the circulating Ly6C^hi monocyte population, projected at the start of all trajectories. Trajectory 1 predicts the patrolling monocyte differentiation (not relevant in injury) (37). (I) Gene expression dynamics of monocyte/MF/DC subpopulations resolved along latent time. Cells were subjected to trajectory inference using Monocle’s (97) differential expression analysis to identify lineages. Top likelihood-ranked genes by branch and pseudotime are shown. Gpnmb is highlighted.