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Cellular reprogramming can offer valuable insight into disease mechanism and has the potential to provide novel tools for regenerative medicine. Yet it remains an inefficient and often incomplete process. However, experiments show that almost all somatic cells eventually give rise to the pluripotent state, albeit at different latencies, as long as expression of reprogramming transcription factors is maintained. Furthermore, it appears that specific subpopulations of cells can be identified that show enhanced propensities to be reprogrammed to the pluripotent state. It has been proposed that an initial stochastic process is responsible for this initial priming that is followed by a deterministic process that directs the primed cells into the pluripotent state. Here, we propose a population shift view of cellular reprogramming, which explains these observations and reconciles the stochastic and deterministic nature of this process. According to this view, a small population of cells, whose states are closer to the pluripotent state and reside in pre-existing energetically favorable trajectories, will be initially selected for reprogramming. Moreover, by maintaining ectopic expression of reprogramming factors, other cells enter these pathways as a result of transcriptional and epigenetic stochastic variations. Consequently, increasing numbers of cells reach the pluripotent state, and the cell population distribution shifts toward this state. Importantly, additional perturbations can change the epigenetic landscape, allowing cells more access to the reprogramming trajectories, thereby increasing reprogramming efficiency. Knowledge of the initial cellular subpopulations and pathways of states that lead to the final cellular state should allow us to design alternative perturbation strategies to improve reprogramming efficiency and fidelity.

Original publication




Journal article


Stem Cells

Publication Date





1367 - 1372


Attractor, Induced pluripotent stem cell, Pluripotency, Reprogramming, Animals, Cell Proliferation, Cellular Reprogramming, Humans, Models, Biological