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

Sophia Hu, Yong Lu, Gaohan Yu, Zhiqian Zheng, Weikang Wang, Ke Ni, Amitava Giri, Jingyu Zhang, Yan Zhang, Kazuhide Watanabe, Guang Yao, Jianhua Xing
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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, 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.

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