Transiently increased intercommunity regulation characterizes concerted cell phenotypic transition

Phenotype transition takes place in many biological processes such as differentiation and reprogramming. A fundamental question is how cells coordinate switching of expressions of clusters of genes. To address the question, we integrated dynamical systems theories and single cell big data analyses into analyzing scRNA-seq data. Mathematical modeling based on dynamical systems theories has been extensively used in modeling small regulatory networks, while scRNA-seq data analyses are typically statistics-based approaches with limited mechanistic insights on cellular dynamics. Through analyzing single cell RNA sequencing data in the framework of transition path theory, we studied how such a genome-wide expression program switching proceeds in three different cell transition processes. For each process we reconstructed a reaction coordinate describing the transition progression, and inferred the gene regulation network (GRN) along the reaction coordinate. Our study reveals a common principle on how cells coordinate reprograming their expression program during a transition process. In all three processes we observed common pattern that the effective number and strength of regulation between different communities increase first and then decrease. The change accompanies with similar change of the GRN frustration, defined as overall confliction between the regulation received by genes and their expression states, and GRN heterogeneity. While studies suggest that biological networks are modularized to contain perturbation effects locally, our analyses reveal a general principle that during a cell phenotypic transition intercommunity interactions increase to concertedly coordinate global gene expression reprogramming, and canalize to specific cell phenotype as Waddington visioned.