ArticleBulletin of mathematical biology2026
Topological Structure of Epigenetic Forests in Flower Morphogenesis.
Article in Bulletin of mathematical biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Understanding how stable developmental patterns emerge from gene regulatory networks remains a central problem in developmental biology. Here, we study how classical homeotic mutations reshape the epigenetic landscape of the floral gene regulatory network of Arabidopsis thaliana. We represent this landscape as an Epigenetic Forest: a collection of rooted in-arborescences induced by the state transition graph of a Boolean gene regulatory network, where each tree is the basin of attraction of a stable gene expression pattern associated with a floral or meristematic identity. We apply this framework to the wild-type network, three single homeotic mutants (ap1, pi, and ag), and three double mutants (ap3-pi, ag-pi, and ap1-ag). For each genotype, we quantify landscape organization using complementary descriptors of basin structure, convergence depth, fate diversity, dominance, inequality, and Jensen-Shannon divergence from wild type. The resulting landscapes reveal distinct modes of mutant-induced deformation. The ap1 mutant restricts fate accessibility and concentrates trajectories into dominant basins, whereas pi eliminates B-function-dependent identities while largely preserving global basin organization. In contrast, ag increases effective fate diversity despite the loss of reproductive identity, reflecting defective meristem termination and convergence to WUS-associated states. Double mutants exhibit non-additive deformation: ap3-pi is indistinguishable from pi across all reported descriptors, consistent with logical saturation of the AND-like B-function module, whereas ag-pi and ap1-ag produce distinct redistributions of fate accessibility. The framework recovers canonical floral identities and experimentally observed mutant phenotypes while treating the epigenetic landscape as a finite, computable object determined by regulatory logic. The framework thus provides a topology-based description of developmental robustness, epistasis, and mutant-induced landscape deformation.
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