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  • Aging disrupts gene express...
    Kurland, Jesse V.; Cutler, Alicia A.; Stanley, Jacob T.; Betta, Nicole Dalla; Van Deusen, Ashleigh; Pawlikowski, Brad; Hall, Monica; Antwine, Tiffany; Russell, Alan; Allen, Mary Ann; Dowell, Robin; Olwin, Bradley

    Stem cell reports, 06/2023, Letnik: 18, Številka: 6
    Journal Article

    Skeletal muscle function and regenerative capacity decline during aging, yet factors driving these changes are incompletely understood. Muscle regeneration requires temporally coordinated transcriptional programs to drive myogenic stem cells to activate, proliferate, fuse to form myofibers, and to mature as myonuclei, restoring muscle function after injury. We assessed global changes in myogenic transcription programs distinguishing muscle regeneration in aged mice from young mice by comparing pseudotime trajectories from single-nucleus RNA sequencing of myogenic nuclei. Aging-specific differences in coordinating myogenic transcription programs necessary for restoring muscle function occur following muscle injury, likely contributing to compromised regeneration in aged mice. Differences in pseudotime alignment of myogenic nuclei when comparing aged with young mice via dynamic time warping revealed pseudotemporal differences becoming progressively more severe as regeneration proceeds. Disruptions in timing of myogenic gene expression programs may contribute to incomplete skeletal muscle regeneration and declines in muscle function as organisms age. •Comparison of pre- and post-fusion nuclei during regeneration in young and aged mice•Quantified altered gene expression timing in aged mice during muscle regeneration•Timing of myogenic gene networks are disrupted in aged mice compared with young mice•In aging, disrupted gene expression timing is exacerbated as regeneration proceeds In this article, Olwin, Dowell, and colleagues identify pervasive changes in gene expression timing during skeletal muscle regeneration occurring in aged mice compared with young mice. These changes in timing of gene expression networks, as identified via single-nucleus RNA sequencing and quantified with in-depth bioinformatic analyses, likely contribute to aging muscle phenotypes.