2021/07/01 by Rahul Shaw, C. Y. Maurice Cheung · 1 voice · 1 citation
Biochemistry, Genetics and Molecular Biology · #Metabolomics and Mass Spectrometry Studies #Microbial Metabolic Engineering and Bioproduction #Photosynthetic Processes and Mechanisms
paper · pdf · doi:10.1093/insilicoplants/diab020
openalex publication_date 2021/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
Abstract Rice is a major staple food worldwide and understanding its metabolism is essential for improving crop yield and quality, especially in a changing climate. Constraint-based modelling is an established method for studying metabolism at a systems level, but one of its limitations is the difficulty in directly integrating certain environmental factors, such as water potential, to the model for predicting metabolic changes in response to environmental changes. Here, we developed a framework to integrate a crop growth model and an upgraded diel multi-organ genome-scale metabolic model of rice to predict the metabolism of rice growth under normal and water-limited conditions. Our model was able to predict distinct metabolic adaptations under water-limited stress compared to normal condition across multiple developmental stages. Our modelling results of dynamic changes in metabolism over the whole-plant growth period highlighted key features of rice metabolism under water-limited stress including early leaf senescence, reduction in photosynthesis and significant nitrogen assimilation during grain filling.