Enhancements to crop morphology, such as the semidwarfing that helped drive the green revolution, are often driven by changes in gene expression. These are challenging to translate across species, which slows the rate of crop improvement. Synthetic transcription factors (SynTFs) offer a rapid alternative to generate targeted alterations to gene expression. However, the complexity of developmental pathways makes it unclear how to best apply them to predictably engineer morphology. In this work, we explore whether mathematical modeling can guide SynTF-based gene expression modulation to help elucidate the design principles of engineering organ size. We targeted genes in the phytohormone, gibberellin (GA), signaling pathway, which is a central regulator of cell expansion. We demonstrate that modulation of GA signaling gene expression can generate consistent dwarfing across tissues and environments in Arabidopsis thaliana, and that the degree of dwarfing is dependent on the strength of regulation, as predicted by modeling. We further validate the model's predictive power by demonstrating its capacity to predict the qualitative impacts of different regulatory architectures for engineering organ size. Additionally, we develop expression parameterized models to quantitatively predict organ size and elucidate how temperature will affect growth. Finally, we show that these insights can be generalized for engineering organ size in tomato (Solanum lycopersicum). This work creates a framework for predictable engineering of an agriculturally important trait across tissues and plant species. It also serves as a proof-of-concept for how mathematical models can guide SynTF-based alterations in gene expression to enable bottom-up design of plant phenotypes.
Bull et al. (Mon,) studied this question.