A 3D Model of Photosynthesis to Inform Breeding for Improved Rice Performance in a Changing Climate

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Increasing demands for global food production over the next decades will be a huge burden on the world's shrinking farmland. It is estimated that an increase of agricultural productivity by as much as 100% is required, yet it is widely acknowledged that present agronomic practices are on a collision course with environmental and sustainability goals. Added to this, global climate change is altering the environment in which crops grow, making it unlikely that present day plants will perform well in the future. These problems will affect the whole world, but the most acute problems will be felt by the poorest people, most of whom rely on one crop, rice, for their food. The aim of this project is to provide plant breeders with information that will allow them to produce a more efficient rice plant and, moreover, a plant that is ready to cope with the challenges that climate change is going to throw at us.Breeding a new rice variety is a process which can take decades. Any procedure which shortens this process or more quickly identify the traits that farmers need to improve rice yield will have a significant affect on the lives of millions of people who depend on this crop. Moreover, due to the relative recent rapidity of climate change and the slowness of plant breeding, we need to start selecting new varieties of rice which will cope or even benefit from future elevated carbon dioxide levels (a driver of climate change) well in advance of those levels actually being reached. Exploiting the modern power of computational modelling provides the opportunity to do this. Photosynthesis is the prime driver of food production for all crops, including rice. We have a very good understanding of the biochemistry of photosynthesis and computational models have been produced which can simulate the process, allowing us to predict how photosynthesis changes to altered level of particular enzymes. However, these models have a major drawback. They are 1-dimensional, treating photosynthesis as a process that occurs uniformly in a cell. In reality, photosynthesis occurs in leaves which contain many thousands of cells and the position and shape of each cell influence the efficiency of photosynthesis in each cell. The overall performance of a leaf actually reflects the performance of all the cells put together. The aim of this project is to create a 3D model of photosynthesis which takes into account the position and shape of each cell in a rice leaf. This will allow us to investigate the affect of altering the number, size and packing of cells on photosynthesis on a computer, without having to actually breed the plants. This would save plant breeders immense time and money, allowing them to more rapidly generate the next generation of rice plants required to tackle the problems described at the beginning of this section.To achieve this aim we will use a combination of advanced imaging techniques to create 3-D leaf models and plant physiology and biochemistry techniques to measure leaf performance We will then use computational methods to model the entire process on a computer. We will then be able to ask questions such as: what pattern of cell division in the leaf is best for the efficiency of photosynthesis? Can we rationally design a rice leaf for improved performance? We will then use the new model to explore how photosynthesis is likely to respond to the increased levels of CO2 in the atmosphere which are likely to occur over the next century and test these predictions using plants grown under elevated CO2, both in laboratory and field conditions. We will explore the model to predict which aspects of leaf structure are important for plants to maintain or increase photosynthesis under the various conditions predicted by climate change models. This information will allow breeders to start selecting plants now so that in 20-30 years time rice plants will still be able to generate sufficient food for the world population.