Tailoring a dynamic model of photosynthetic metabolism towards greater carbon assimilation in rice

Abstract Modelling crops in silico can identify bottlenecks in photosynthetic metabolism that limit the realization of maximum theoretical crop yields. Resource investment among photosynthetic enzymes in C 3 photosynthesis can be optimized to maximize carbon assimilation via targeted alterations, e.g. by regulating the expression of proteins in the Calvin Benson Bassham (CBB) cycle. In this work, the e-Photosynthesis dynamic model of C 3 metabolism was modified to create a rice-specific version. Species-specific equations for temperature dependences of ribulose-1,6-bisphosphate carboxylase/oxygenase (Rubisco) catalytic properties were combined with leaf-level gas exchange measurements for Oryza sativa cv. IR64 to derive photosynthetic parameters describing CBB cycle activity (Vcmax and J). These were used to re-scale enzyme activities in e-Photosynthesis before identifying redistributions of protein among photosynthetic enzymes that were optimal for CO 2 assimilation at different [CO 2]s. Target sets of enzymes were identified for over-expression to engineer improved photosynthesis under [CO 2] scenarios of limited diffusion, as might be experienced during abiotic stress, current yield potential, and future elevated [CO 2]. These were evaluated using sensitivity analysis that assumed variability around achieved protein fold-changes for photosynthetic improvement reported in the literature. Increases in as few as two to as many as six enzymes would achieve photosynthetic rates upto 28% higher under water stressed conditions. In non-stressed leaves under current and future [CO 2], increases in photosynthesis of upto 22% required over-expression of 4–6 enzymes.