Computational biology of plant development: Towards a deductive science

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Computational Biology of Plant Development: Towards a Deductive Science Since the early 2000s, a mechanistic understanding of plant development has begun to emerge through a combination of molecular genetics, advances in microscopy, and computational models. Surprisingly, the development of diverse structures may result from related mechanisms expressed in different contexts. For instance, the development of leaves leading to their various shapes, and their positioning on the supporting stem, are manifestations of a common molecular mechanism involving the interaction between the plant hormone auxin and its transporters, the PIN proteins. The universality of this and other mechanisms (e.g., competition between plant organs for space) suggests that the essence of diverse developmental processes in plants can be reduced to, and deduced from, a small number of fundamental principles. The quest for such principles is the overarching objective of my proposed research. I plan to proceed by devising mathematically well-founded methods for representing and simulating the development of heterogeneous plant structures. As a starting point, I will use the models of leaves with embedded veins that were previously developed in my lab. The resulting methods will be applied to address the patterning of flower heads: the flower-like inflorescences (flower clusters) characteristic of plants in the aster family, such as gerbera, sunflower and daisy. The conspicuous regularity and mathematical properties of the spiral patterns found in these heads have attracted interdisciplinary interest over centuries, yet the patterning mechanism has remained unknown. Based on unique data obtained in collaboration with biologist colleagues and computational models being devised in my lab, I believe that we can solve this long-standing problem. The solution will provide a point of departure to explain a related phenomenon, the development of the vascular structure of flower heads. The results will be generalized to a wider spectrum of biological structures. Taken together, this work will constitute a step towards characterizing diverse processes and structures in plants in terms of broadly applicable, general principles. The proposed research has an inherently interdisciplinary character, applying methods of computer science and mathematics to problems originating in biology, and involves collaborations with plant scientists. Computational models based on experimental data will be devised and used to explore causal relations in the self-organizing developmental processes under study. The geometric aspects of the emerging structures link this research program to computer graphics.