Every organ and tissue progressively loses function as it ages, but aging tissues retain a latent capacity for rejuvenation. A new study, led by Wyss Institute Core Faculty member George Church, used gene expression data and machine learning to develop a novel “transcriptomic age predictor,” which pinpoints the “transcriptional age” of cells. Using this predictor as a readout in an over-expression screen, the team identified the RNA processing factor SRSF1and demonstrated that it can rejuvenate several “hallmarks of aging,” and significantly increase the healthspan and lifespan of aged mice.