Longitudinal lineage tracing reveals early clonal attrition during <i>Drosophila</i> midgut aging
Article excerpt
by Han Gong, Kehui Liu, Shanjun Deng, Jinwen Wang, Xionglei He, Li Liu The dynamics of stem cell maintenance and proliferative patterns are key determinants of tissue aging in multicellular organisms. Leveraging our previously developed SMALT system with enhanced sequencing…
by Han Gong, Kehui Liu, Shanjun Deng, Jinwen Wang, Xionglei He, Li Liu
The dynamics of stem cell maintenance and proliferative patterns are key determinants of tissue aging in multicellular organisms. Leveraging our previously developed SMALT system with enhanced sequencing compatibility, we performed longitudinal lineage tracing of the adult Drosophila melanogaster midgut across different developmental stages. Using ubiquitous Tubulin-GAL4-driven labeling, we first profiled midgut-wide clonal dynamics during early adulthood (3, 33 days post-eclosion). Phylogenetic reconstruction revealed that clonal diversity peaked immediately after eclosion and began to decline earlier than anticipated, accompanied by a reduction in effective population size. To further investigate stem cell-specific dynamics during late adulthood, we employed intestinal stem cell (ISC)-specific Dl-GAL4-driven labeling (33, 63 days post-eclosion) and observed sustained clonal attrition in the posterior midgut. This progressive loss of diversity was consistent with an age-associated change in effective proliferative behavior and reduced lineage maintenance capacity, as reflected by a decline in net proliferative output inferred from lineage topology. Remarkably, ISC lineages emerging within the first 10 days post-eclosion exhibited sustained clonal dominance in aging populations, with a single lineage comprising over 63% of sampled cells by Day 63. Bayesian survival modeling confirmed that these early-origin lineages have the highest probabilities of long-term persistence, while a graph neural network model accurately predicted their structural evolution across successive stages. Together, we delineate a timeline for clonal attrition and deliver topology-driven predictors of clone survival and structural change, enabling prospective identification of dominant and failing clones during aging.