Beyond Genetics: Unveiling Epigenetic Drivers of Lifespan Heterogeneity through Yeast Single-Cell Aging Atlases

The sigmoidal shaped Gompertz curve has been long accepted to fit lifespan survival curves from the single-celled budding yeast to invertebrate worms and flies, and to all mammalian species. It is not surprising to see the broad variation in lifespan among humans and most animal models due to genetic diversity and variability in the environment. However, it is striking that similarly broad variations in lifespan are commonly observed in well-controlled experimental environment and in laboratory species where genetically homogeneous individuals, such as inbred lines, self-fertilized animals, or mitotically reproduced yeast cells, are analyzed. What causes the lifespan variation? We hypothesize that the cause of such lifespan variation lies in epigenetic variation/drifts, either stochastic or non-stochastic, or both. Intriguingly, recent studies suggest that multiple aging trajectories exist and are modifiable during yeast replicative aging, offering new clues for the molecular basis for lifespan variation. In this exploratory project, we will attempt to identify and define the factors and pathways that contribute to the observed lifespan variation beyond invariable genetic and environmental factors through unbiased single- cell transcriptomic and epigenomic analysis. First, single-cell transcriptomes/epigenomes for complete daughter cell series of individual mother cells will provide, for the first time, a sneak peak of the mother cell’s aging status, providing clues for lifespan predictors and potential sources of lifespan variation. Next, the mother-daughter series will provide a first glimpse of unbiased aging trajectories. Finally, 10X genomics-based high throughput single-cell RNA-seq and ATAC-seq for young and old cell populations will enable a complete and unbiased analysis of aging trajectories and identification of molecular pathways responsible for lifespan variation. Understanding the root cause of lifespan variation beyond genetic variation has the tremendous potential to benefit the vast majority of the population in achieving healthy and successful longevity without genetic interventions. Such non-genetic interventions are likely to be more easily deliverable and achievable. Project Number: 1R21AG101044-01 | Fiscal Year: 2026 | NIH Institute/Center: National Institute on Aging (NIA) | Principal Investigator: Weiwei Dang | Institution: BAYLOR COLLEGE OF MEDICINE, HOUSTON, TX | Award Amount: $440,000 | Activity Code: R21 | Study Section: Special Emphasis Panel[ZRG1 CDB-H (90)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11354760