(773b) A Whole-Plant Genome-Scale Model of Maize

A whole-plant metabolic model of maize was used to analyze the transport of metabolites between organs, as well as evaluate the unique metabolic properties of the major organs. The model links the root, stalk, leaf, kernel, and tassel organs using the phloem as the main tissue for metabolite transport among the organs. The network of metabolic reactions in each organ was determined using whole-plant transcriptomic data to determine organ or tissue specific gene protein reaction (O-GPR or T-GPR) relationships. 3017, 2714, 3372, 3242, and 3206 genes corresponding to metabolic reactions were expressed in the root, shoot, leaf, tassel, and kernel organs, respectively. Once reactions with known activity were allocated into each organ, the flow through the biomass reaction of each organ was restored by preferentially adding reactions known to occur in maize with no organ or tissue localization information over reactions corresponding to low expression in the focus organ. Organ-specific biomass equations were defined and ATP requirements were determined for photosynthetic vs. non-photosynthetic organs based on literature. Three growth stages of maize development representing the vegetative leaf growth, tassel development, and kernel filling stages were modeled based on the change in dry weight of each organ over time. Additionally, the transport between organs was normalized based on the proportion of dry weight at each growth stage modeled. Using parsimonious analysis, the total number of reactions required during leaf growth, tassel development, and kernel filling stages were identified with approximately 80% of the reactions in the vegetative leaf growth stage common among all growth stages. As expected, sucrose is transported to the kernel during the kernel filling stage from all other organs. Using a whole-plant model, we aim to further enhance the understanding of the metabolites transported between organs, as well as identify the reactions underpinning nitrogen utilization efficiency.