Regulatory stochasticity drives opposing phenotypic outcomes in cell-fate decision networks
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…
Gene regulatory networks, which dictate cell fate decisions, typically assume fixed interaction parameters. However, fluctuating regulatory efficacy can alter phenotype occupancy. Researchers investigated how temporal fluctuations in interaction strength modify outcomes in cell-fate decision networks. Overall, fluctuations largely maintained deterministic occupancies, but additive fluctuations boosted all-high co-expression states, especially when high expression was achievable.
Conversely, multiplicative fluctuations skewed inhibitory interactions to stronger repression, favoring single-high states depending on network topology. Deterministic controls derived from noise-induced parameter distributions failed to replicate these effects. A Boolean-limit analysis uncovered an inherent bias: repression loss boosted expression irrespective of regulator presence, while stronger repression only occurred with active regulators.
Epithelial-mesenchymal plasticity and gonadal-fate networks demonstrated increased hybrid team-expression state occupancy under additive fluctuations. Therefore, regulatory noise can steer developmental landscapes in contradictory ways, leaning either toward progenitor-like or terminally differentiated states.
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