Researchers introduced CellRank, a computational framework designed to map cellular development and regeneration trajectories using single-cell data. The methodology utilizes Markov chains and Schur decomposition to identify initial and terminal states while calculating the probability of a cell reaching a specific fate. In the pancreas, the tool discovered several novel regulator genes involved in delta cell maturation. When applied to lung injury models, it predicted an unexpected dedifferentiation path where goblet cells revert to basal stem cells. This biological prediction was confirmed through immunofluorescence staining, which identified intermediate cell stages only present during the repair phase. Overall, the sources detail a robust mathematical approach for uncovering unseen lineage transitions in complex tissues.

References:

• Lange, M., Bergen, V., Klein, M. et al. CellRank for directed single-cell fate mapping. Nat Methods 19, 159–170 (2022). doi.org