Understanding drought tolerance in rice by the dissection and genetic analysis of leaf metabolism, oxidative stress status and stomatal behavior

Abstract

In Chapter 1, I explain that in the coming decades, drought episodes associated with climate change will be more frequent and erratic. Under this scenario, increasing or maintaining crop yields to meet the growing global food demand will become gradually more difficult. Rice (Oryza sativa), a staple food for more than half of the world’s population, shows the greatest sensitivity to water limitation among the cereal crops. Improving drought tolerance in rice by limiting the stress-induced yield penalties is pivotal for global food security. Drought stress impacts the physiology of plants and disrupts cellular homeostasis leading to metabolic alterations and increased oxidative stress. In this thesis, I investigate how drought- induced changes in rice physiology, central metabolism and oxidative stress status impact crop growth and yield. I also exploit the genetic diversity of a large panel of indica rice accessions to map genes and genomic regions associated with the quantitative variation in metabolic and physiological traits important for drought tolerance. In Chapter 2, I study the physiological, metabolic and antioxidative responses to drought in three indica rice varieties selected for their contrasting levels of tolerance/susceptibility to the stress. The analysis was conducted during both the vegetative and reproductive stages and different mechanisms of tolerance to drought were identified between the different tolerant varieties and between stages. This study provides a framework for the exploration of the genetic control of these mechanisms of tolerance to drought. In Chapter 3, I analyse the stress-induced changes in flag leaf central metabolism and oxidative stress status in ~300 indica rice accessions exposed to drought in the field at the reproductive stage. Photorespiration, protein degradation and nitrogen recycling were identified as the main flag leaf metabolic processes induced by drought. By integrating the metabolite data and the oxidative stress status of the accessions I showed that the activity of specific enzymatic antioxidants is important to limit the metabolic processes associated with drought stress which have a negative impact on grain yield. Finally, the levels of metabolites and oxidative stress markers/enzymes were also used to generate a multivariate model that accurately predicts grain yield loss across the accessions. The best predictors of this model can be used as biomarkers for grain yield stability in rice under drought. In Chapter 4, I quantify the differences in transpiration among the same accessions used in Chapter 3 by measuring canopy temperature, a proxy for stomatal conductance, in the field. Canopy temperature under drought at the reproductive stage was negatively correlated with the grain yield performance of the accessions, proving that leaf temperature under stress is a good predictor of drought tolerance that can be used to accelerate physiological selection in plant breeding. In addition, association mapping of canopy temperature data revealed a QTL associated with temperature differences under drought. Genetic variation for the significant markers of the QTL was present only within the tall, low-yielding landraces of rice adapted to drought-prone environments. This study confirms that these old varieties and landraces represent a strategic reservoir of genetic variation that can be tapped into for developing new varieties that are physiologically adapted to environments with unpredictable and variable water availability. In Chapter 5, I show that the multivariate model based on the set of metabolites and oxidative stress markers/enzymes developed in Chapter 3 also accurately predicts grain yield per se under well-watered and drought conditions in ~270 accessions of the population. The latter model predicted grain yield more accurately than a genomics-based model that I developed for the same genotypes. Finally, the best metabolic and enzymatic model predictors of grain yield were used as traits in a GWA study and the resulting associations allowed me to identify genetic markers that can be used in breeding to improve rice grain yield under optimal conditions and/or grain yield/yield stability under drought stress. Finally, in Chapter 6, I discuss the main findings of this thesis, connecting the results of the different experimental chapters and highlighting how they can be used to improve drought tolerance in rice.