Epithelial-mesenchymal transition couples with cell cycle arrest at various stages.

Numerous computational approaches have been developed to infer cell state transition trajectories from snapshot single-cell data. Most approaches first require projecting high-dimensional data onto a low-dimensional representation, raising the question of whether the dynamics of the system become distorted. Using epithelial-to-mesenchymal transition (EMT) as a test system, we show that both biology-guided low-dimensional representations and stochastic trajectory simulations in high-dimensional state space, not representations obtained with brute force dimension-reduction methods, reveal multiple distinct paths of TGF-β-induced EMT. The paths arise from coupling between EMT and cell cycle arrest at either the G1/S, G2/M or M checkpoints, contributing to cell-cycle related EMT heterogeneity. The present study emphasizes that caution should be taken when inferring transition dynamics from snapshot single-cell data in two- or three-dimensional representations, and that incorporating dynamical information can improve prediction accuracy.