Abstract:
Rice, maize, wheat, sorghum and barley are the major food crops which constitutes the most of world’s nutrient requirements. Although the overall yield of such cereals has been increasing, the growing population and adverse climatic changes pose huge challenges for their sustained production in the future. Concurrently, the advent of constraint-based metabolic reconstruction and analysis paves way to characterize cellular physiology under various stresses via the mathematical network models. The first plant metabolic modeling studies have started in Arabidopsis followed by cereals such as, rice, maize and barley. We have employed similar systems biology approach, and initially developed a core mathematical model of rice to characterize cellular behaviour and metabolic states under various abiotic stress conditions. The core model was then further expanded to reconstruct a fully compartmentalized genome scale metabolic model. Subsequently, transcriptomics and metabolomics data were systematically integrated with the model to identify the potential transcription factors. For the first time, we have developed this integrative system for identification of potential candidate regulatory genes as new breeding targets for improving rice production. This method can be applied to other cereal crops to identify agronomic traits for crop improvement.

