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

Kishore HariiD, Abhay Gupta, Lakshmi Malvadi ShivakumariD, Prakash KulkarniiD, Ravi SalgiaiD, Mohit Kumar JollyiD, Herbert LevineiD

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.

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02 /Specification & Classification

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