Exercise has the ability to rejuvenate stem cells and improve tissue regeneration in aging animals. However, the cellular and molecular changes elicited by exercise have not been systematically studied across a broad range of cell types in stem cell compartments. We subjected young and old mice to aerobic exercise and generated a single-cell transcriptomic atlas of muscle, neural, and hematopoietic stem cells with their niche cells and progeny, complemented by whole transcriptome analysis of single myofibers. We found that exercise ameliorated the upregulation of a number of inflammatory pathways associated with old age and restored aspects of intercellular communication mediated by immune cells within these stem cell compartments. Exercise has a profound impact on the composition and transcriptomic landscape of circulating and tissue-resident immune cells. Our study provides a comprehensive view of the coordinated responses of multiple aged stem cells and niche cells to exercise at the transcriptomic level.

The diversity of cell types is a challenge for quantifying aging and its reversal. Here we develop 'aging clocks' based on single-cell transcriptomics to characterize cell-type-specific aging and rejuvenation. We generated single-cell transcriptomes from the subventricular zone neurogenic region of 28 mice, tiling ages from young to old. We trained single-cell-based regression models to predict chronological age and biological age (neural stem cell proliferation capacity). These aging clocks are generalizable to independent cohorts of mice, other regions of the brains, and other species. To determine if these aging clocks could quantify transcriptomic rejuvenation, we generated single-cell transcriptomic datasets of neurogenic regions for two interventions-heterochronic parabiosis and exercise. Aging clocks revealed that heterochronic parabiosis and exercise reverse transcriptomic aging in neurogenic regions, but in different ways. This study represents the first development of high-resolution aging clocks from single-cell transcriptomic data and demonstrates their application to quantify transcriptomic rejuvenation.