Quantifying landscape-flux via single-cell transcriptomics uncovers the underlying mechanism of cell cycle

Recent developments in single-cell sequencing technology enable the acquisition of the whole transcriptome data. However, understanding the underlying mechanism and identifying the driving force of the transcriptional regulation of the cell function directly from these data remains challenging. To address this urgent need, we reconstruct a continuous vector field of cell cycle based on the discrete single-cell RNA velocity to quantify the single-cell global non-equilibrium dynamic landscape-flux. We reveal that large fluctuations disrupt the global landscape and genetic perturbations alter landscape-flux, thus identifying key genes in maintaining cell cycle dynamics and predicting associated effects on function. Additionally, we quantify the fundamental energy cost of the cell cycle initiation and reveal that sustaining the cell cycle requires curl flux and dissipation to maintain the oscillatory phase coherence. We enable the inference of the cell cycle gene regulatory networks directly from the single-cell transcriptomic data, including the feedback mechanisms and interaction intensity. This provides a golden opportunity to experimentally verify the landscape-flux theory and also obtain its associated quantifications. Our study also offers a unique framework for combining the landscape-flux theory and single-cell high-through sequencing experiments together for understanding the underlying mechanisms of the cell cycle and can be extended to other non-equilibrium biological processes, such as differentiation-development and disease pathogenesis.