Regulatory stochasticity drives opposing phenotypic outcomes in cell-fate decision networks

Abstract

Gene regulatory network models treat interaction parameters as fixed, although regulatory efficacy fluctuates. We asked how temporal fluctuations in interaction strength reshape phenotype occupancy in cell-fate decision GRN motifs. Across large parameter ensembles, anchored fluctuations largely preserved deterministic occupancies. Additive fluctuations increased occupancy of all-high co-expression states, particularly where high expression was accessible. In contrast, multiplicative fluctuations biased inhibitory interactions toward stronger repression and favored single-high states in a topology-dependent manner. Deterministic controls sampled from noise-induced parameter distributions did not fully reproduce these effects. A Boolean-limit analysis revealed an intrinsic upward bias: loss of repression increased expression regardless of regulator state, whereas stronger repression acted only when the regulator was present. Analyses of epithelial-mesenchymal plasticity and gonadal-fate networks showed increased occupancy of hybrid team-expression states under additive fluctuations. Thus, regulatory noise can reshape the developmental landscape in opposing directions, pushing cell-fate systems toward either progenitor-like or terminally differentiated states.