description
- Wheat yellow rust disease, caused by the fungus Puccinia striiformis f. sp tritici (PST), is a substantial threat to wheat production worldwide and has recently re-emerged as a major constraint on UK agriculture. We recently developed a novel approach called "field pathogenomics" for pathogen population surveillance. This method uses high-resolution genotypic data to improve our understanding of the genetic sub-structure within a population, which provides essential information on the evolutionary forces that drive pathogen evolution within an agroecosystem. However, for wheat yellow rust our understanding of the patterns of transmission and dispersal remain limited. Building effective agro-ecological models that address this lack of knowledge could contribute to a proactive early warning system for wheat yellow rust in the UK. A mathematical model of the spatio-temporal population dynamics of yellow rust would have a number of applications, including optimizing surveillance, targeting chemical sprays and designing regional diversification schemes. Predictive models are already used by the UK Government to inform policy surrounding tree diseases. However, models are less well developed for crop pathogens. Obtaining detailed information on PST genetics through our field pathogenomics study provides an opportunity to link epidemiological modelling and genomic data, improving the predictive power of models.