Uncovering underlying physical principles and driving forces of cell differentiation and reprogramming from single-cell transcriptomics

Advances in single-cell technology enable transcriptome data at unprecedented scales. However, identifying the driving force of cell
function from these data remains challenging. We learn cell state vector fields of cell differentiation/reprogramming from RNA velocity to quantify the global driving forces as Waddington landscape and flux from these data. Our methodology utilizes single-cell
high-throughput experiments for validating the landscape and flux theory, with associated quantifications. We identify the deviation of the optimal path and transition state from the Waddington landscape alone as the driving force due to the presence of flux. We reveal the nucleation mechanism of cell fate decision-making with transition states as nucleation sites and pioneer genes as nucleation seeds. This provides a framework for uncovering underlying physical principles of biological processes via single-cell
transcriptomics.