Relationship between gene regulatory network structure and the inheritance function

Determine the dependence of the inheritance function p(x, y)—the conditional probability density that a daughter cell has epigenetic state x given that its mother cell has epigenetic state y—on the topology and parameters of the underlying gene regulatory network controlling gene expression dynamics during the cell cycle, in order to characterize how network structure influences epigenetic state transmission across cell divisions in heterogeneous stem cell populations.

Background

The paper studies how to connect single-cell gene regulatory network dynamics with population-level stem cell regeneration by introducing and empirically deriving an inheritance function p(x, y) that describes the stochastic mapping of epigenetic states from mother to daughter cells at division. Existing phenomenological models have used beta or gamma distributions to describe molecular inheritance, largely independent of the specific regulatory network structure.

The authors explicitly note that the way gene regulatory network structure (e.g., topology and regulatory strengths) might shape or be reflected in the inheritance function remains unknown. They propose a data-driven computational scheme that infers p(x, y) from simulations of a hybrid model integrating gene regulation and cell cycling, but the general theoretical characterization of this dependence is left unresolved.