#37 · Single-cell

Single-cell and population variability is used to infer aging and neurogenic mechanisms

The common thread is treating variability among cells or individuals as informative data rather than noise. A stochastic framework for adult neurogenesis fits a diffusion model to population variability alongside means, using variance structure to infer regulatory mechanisms. In aged hematopoietic stem cells, single-cell RNA-seq of murine and human HSCs, combined with a joint variant filtering strategy, reconstructs somatic mutation genealogies and reveals a divergent mutational and clonal landscape that is not linked to aging-associated clonal hematopoiesis. A manifold-based metric quantifies transcriptional entropy at single-cell resolution, tracking aging, senescence and T-cell expansion as measures of transcriptional dyscoordination. What is new is the explicit use of cell-to-cell or lineage-level heterogeneity as the inferential object across neural and hematopoietic aging contexts, rather than population means alone.