The information required to generate robust developmental patterns arises from complex interactions among genetic and non-genetic factors. Thus, network models may be useful instruments to study how the collective dynamics of such factors are related to particular phenotypical traits, enabling a further understanding of the origin and evolution of forms in multicellular organisms. Epidermal cell-type patterning in the model plant Arabidopsis thaliana provides an extraordinary system to address this issue as it has been thoroughly characterized experimentally, allowing for the elaboration of empirically-grounded models. We developed a model of gene regulatory networks (GRNs) that are coupled via protein diffusion and comprise a meta-GRN implemented on cellularized domains. The meta-GRN model exhibits robust steady states that correspond to the gene expression profiles characterizing epidermal cell types. Simulations also render spatial patterns that match the cellular arrangements observed in root and leaf epidermis. We validated the model by corroborating it could reproduce the patterns of reported mutants. The meta-GRN model shows that interlinked sub-networks contribute redundantly to the formation of robust epidermal cell patterns and has allowed the postulation of novel and testable predictions regarding the effect of cell shape, signaling pathways and additional gene interactions affecting spatial patterning. This model constitutes a base to systematically integrate the molecular data that are continuously being published for this system and serves as a tool to test the contribution of specific molecular interactions to the overall developmental patterns. Finally, even though this model was developed for a particular system, it enables the discussion of more general aspects such as the origin of positional information. A repertoire of well-characterized regulatory modules like the one mentioned here are helping to uncover generic principles and trends in patterning-associated networks, some of which will be mentioned and discussed.
Mariana Benítez Keinrad studied biology at the National Autonomous University of Mexico (UNAM) and then obtained a MSc in Complex Systems and Non-Linear Dynamics. She is currently in the last year of her PhD program in the Plant Molecular Genetics, Evolution and Development lab at UNAM. Her advisor is Dr. Alvarez-Buylla, with whom she is working on the elaboration of gene regulatory network models aimed at understanding how the concerted action of genetic and non-genetic factors gives rise to the information needed for cell-type determination and patterning to take place in plant systems.