Modeling and Inferring Cleavage Patterns in Proliferating Epithelia
Figure 3
Convergence of proliferating epithelia to an equilibrium distribution.
(A) Steady-state shape distributions for all simulated CPMs (color), sorted from high to low cell shape variance. Also included are the proliferating epithelia (grayscale) from Figure 1; these epithelia have lower variance than all but one simulated CPM (SmallestNeighbor|EqualSplit). (B) Equilibrium cell shape distributions for the stochastic Random|Random CPM and the deterministic Orthogonal|EqualSplit CPM with an initial condition of a single cell with S0 sides, where S0 ranges from 4 to 250 sides. Probabilities are mean over all runs and error bars represent range. (C) In the simulated CPMs, high hexagonal frequency is strongly correlated with lower cell shape variability as measured by standard deviation. Proliferating epithelia data (green) shows a similar relationship between high hexagonal frequency and low shape variability. (D) The fraction of hexagons in the equilibrium shape distribution for all simulated CPMs. Rows and columns correspond to the choice of first and second edge, respectively, and colors encode the resulting fraction of hexagons after generation 12.