Elucidating the design principles for engineering plant organ size

Area of Science:

• Plant biology
• Synthetic biology
• Mathematical modeling

Background:

• Crop morphology improvements, like semidwarfing, are crucial for agriculture but challenging to achieve across species due to complex gene expression.
• Synthetic transcription factors (SynTFs) offer a promising method for targeted gene expression changes, but their application for predictable morphological engineering is unclear.

Purpose of the Study:

• To explore the use of mathematical modeling to guide SynTF-based gene expression modulation for predictable engineering of plant organ size.
• To elucidate the design principles for engineering organ size by targeting the gibberellin (GA) signaling pathway.

Main Methods:

• Mathematical modeling was used to guide SynTF-based gene expression modulation in the GA signaling pathway.
• Experiments were conducted in *Arabidopsis thaliana* and validated in tomato (*Solanum lycopersicum*).
• Expression-parameterized models were developed to quantitatively predict organ size and growth responses to temperature.

Main Results:

• Modulation of GA signaling gene expression resulted in consistent dwarfing across tissues and environments in *Arabidopsis thaliana*, correlating with regulatory strength as predicted by models.
• Model predictions for qualitative impacts of different regulatory architectures on organ size were validated.
• Quantitative models accurately predicted organ size and temperature-dependent growth effects.

Conclusions:

• Mathematical modeling provides a framework for predictable engineering of plant organ size using SynTFs.
• This approach successfully generalized insights from *Arabidopsis thaliana* to tomato (*Solanum lycopersicum*).
• The study demonstrates a proof-of-concept for bottom-up design of plant phenotypes through model-guided gene expression engineering.