Mesoscopic models of plant development

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A central question of developmental biology is how organisms acquire their form. Computational models play an important role in addressing this question. Their relevance is due, in part, to the self-organizing character of many developmental processes, which is difficult to analyze and understand without the use of models. Models of plant development constructed to date can be broadly divided into two classes. Microscopic models aim at explaining the spatio-temporal patterns of morphogenetically active substances that control growth. These models operate at the scale of molecular processes taking place in individual cells. Macroscopic models relate local growth to the global form of entire plants and operate at the level of large plant components. Examples include the elements of the branching system (apices and internodes) and organs such as leaves, flowers, and fruits. In principle, microscopic and macroscopic models are complementary, but their correspondence has been tenuous, creating a gap in the understanding of development. Addressing this gap, I propose to devise a conceptual and mathematical framework, modeling methods, and software for modeling plant development at the intermediate, mesoscopic level. This level is characterized by spatial scales larger than individual cells but smaller than whole plants, highly non-uniform growth resulting in radical changes in size and shape, feedback between patterning and growth, and the emergence of new structural elements, including differentiation of vasculature, through self-organizing patterning. I propose to harness the complexity of mesoscopic development using a two-prong approach, where the essential patterning properties of molecular and cell-level processes are distilled into geometric constitutive rules, and the development of large-scale patterns, forms and structures is characterized in terms of these rules. Theoretical notions and computational methods will draw on ideas from computer science, mathematics and physics, and will be applied to biological problems rooted in experimental data. Case studies will include the development of compound leaves, flowers and inflorescences. The results are expected to contribute a unifying perspective to developmental plant biology, and advance methods for realistic modelling of plants in computer graphics.