Can exploiting natural genetic variation in leaf photosynthesis contribute to increasing rice productivity? A simulation analysis

• Published in: Plant, cell and environment Vol. 37; no. 1; pp. 22 - 34
• Main Authors: GU, JUNFEI, YIN, XINYOU, STOMPH, TJEERD‐JAN, STRUIK, PAUL C.
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell 01.01.2014; Wiley Subscription Services, Inc
• Subjects: Biological and medical sciences; Biomass; Biotechnology; canopy photosynthesis; co2 assimilation; Computer Simulation; critical-appraisal; crop model; Crop production; Crop yield; crop yields; Fundamental and applied biological sciences. Psychology; GECROS; Gene mapping; Genetic diversity; Genetic Variation; Genotype; introgression lines; leaves; Light; Models, Biological; Oryza - genetics; Oryza - growth & development; Oryza - physiology; Oryza sativa; Oryza sativa L; Photosynthesis; Photosynthesis - genetics; physiological traits; Plant Leaves - genetics; Plant Leaves - growth & development; Plant Leaves - physiology; plant-growth; Quantitative Trait Loci; Rice; rubisco; Simulation analysis; Productivity; Monocotyledones; Genetic variability; GECROS; Plant ecology; Oryza sativa L; Plant leaf; Natural; Modeling; canopy photosynthesis; Cereal crop; Oryza sativa; crop model; Simulation; Gramineae; Analysis; Angiospermae; Spermatophyta; Cultivated plant; Photosynthesis; Canopy(vegetation); Oryza sativa L
• ISSN: 0140-7791; 1365-3040; 1365-3040
• DOI: 10.1111/pce.12173

Rice productivity can be limited by available photosynthetic assimilates from leaves. However, the lack of significant correlation between crop yield and leaf photosynthetic rate (A) is noted frequently. Engineering for improved leaf photosynthesis has been argued to yield little increase in crop productivity because of complicated constraints and feedback mechanisms when moving up from leaf to crop level. Here we examined the extent to which natural genetic variation in A can contribute to increasing rice productivity. Using the mechanistic model GECROS, we analysed the impact of genetic variation in A on crop biomass production, based on the quantitative trait loci for various photosynthetic components within a rice introgression line population. We showed that genetic variation in A of 25% can be scaled up equally to crop level, resulting in an increase in biomass of 22–29% across different locations and years. This was probably because the genetic variation in A resulted not only from Rubisco (ribulose 1,5‐bisphosphate carboxylase/oxygenase)‐limited photosynthesis but also from electron transport‐limited photosynthesis; as a result, photosynthetic rates could be improved for both light‐saturated and light‐limited leaves in the canopy. Rice productivity could be significantly improved by mining the natural variation in existing germ‐plasm, especially the variation in parameters determining light‐limited photosynthesis. The lack of significant correlation between crop yield and leaf photosynthetic rate (A) is noted frequently. We examined the extent to which natural genetic variation in A can contribute to increasing rice productivity, using the mechanistic crop model GECROS. We showed that genetic variation in A of 25% can result in 22‐29% increase in biomass across different locations and years. Rice productivity could be improved by mining the natural variation in existing germplasm, especially the variation in parameters that determine light‐limited photosynthesis. Commentary: We need winners in the race to increase photosynthesis in rice, whether from conventional breeding, biotechnology, or both.