Abstract
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; however, this can distort the dynamics of the system. Using epithelial-to-mesenchymal transition (EMT) as a test system, we show that both biology-guided low-dimensional representations and trajectory simulations in high-dimensional state space, not representations obtained with brute force dimensionality-reduction methods, reveal two broad paths of TGF-β induced EMT. The paths arise from the coupling between cell cycle and EMT at either the G1 or G2/M phase, contributing to cell-cycle related EMT heterogeneity. Subsequent multi-plex immunostaining studies confirmed the multiple predicted paths at the protein level. The present study highlights the heterogeneity of EMT paths, emphasizes that caution should be taken when inferring transition dynamics from snapshot single-cell data in two- or three-dimensional representations, and shows that incorporating dynamical information can improve prediction accuracy.