A Robust Mathematical Model of Adaxial-Abaxial Patterning

Biological development results from intricate and dynamic interactions between members of gene regulatory networks. This is exemplified by the production of flat leaf architecture. Leaves flatten by driving growth along the boundary between their adaxial (top) and abaxial (bottom) domains. These domains are generated by interactions between a complex network of transcription factors and small RNAs. Despite its complexity, flat leaf production is robust to genetic and environmental noise. To help us study this system, we mathematically modeled the determinants and interactions that pattern the adaxial-abaxial boundary. Our model recapitulates observations of adaxial-abaxial patterning and small RNA-target interactions. Positioning of the adaxial-abaxial boundary is highly robust to noise in the model. Furthermore, we identify degradation rates as possible factors contributing to robustness of adaxial-abaxial patterning.