REVOLUTION: Unravelling the regulation and evolutionary innovations in grass species to engineer high water use efficiency in a global crop, rice

A major obstacle for the future of agriculture and global food security is the supply and use of water. Rice is a global food staple, feeding over half of the world's population. However, rice is currently confronted with its most significant growth deficit in two decades, primarily due to the challenges posed by a changing climate and diminishing freshwater resources. Therefore, developing rice that is more efficient in its use of water is central to the future of sustainable agriculture and global food security.
As a UKRI Future Leaders Fellow, I will pioneer the holistic understanding of water use efficiency and enhance water use traits in rice using innovative technological, genomic, molecular biology and biotechnological advances. The data arising from my FLF will define avenues for creating improved rice germplasms.
My FLF takes a dual-pronged approach to maximise successful outcomes. The first approach exploits the novel paradigm-shifting technological advancement of cereal grafting, where "water smart grafts" will be generated by grafting water-efficient rootstocks of millets and/or wild rice to elite rice landraces. Comprehensive physiological and phenotyping measurements will be undertaken to assess growth, photosynthetic performance, and yield under varying water conditions, gaining a holistic understanding of water use parameters. Moreover, gene expression profiling and the construction of gene regulatory networks will identify master regulators that will inform genetic manipulation for improved water use efficiency in rice breeding programs. The second approach will assess natural variation in water use efficiency traits. Considerable variability in water use efficiency exists amongst different rice accessions, often reflecting the climate at the region of cultivar development, such as between varieties from Asia and Africa, but the mechanistic and genetic basis of this variation remains largely undefined. The central aim of this project is to improve...