Gene-for-gene coevolution between Albugo candida and Arabidopsis; mining non-host resistance genes for white rust control in Brassicaceae crops Completed Project uri icon

description

  • Plant disease results in substantial losses in crop production, and imposes great costs on farmers. For example, control of potato blight costs UK farmers ~ £60M/year, and Asian soybean rust costs Brazilian farmers ~$800M/year. We aim to provide resistance genes that enable disease to be controlled by genetics rather than chemistry. To provide reliable genetic solutions, we need a better understanding of how plants and their pathogens interact. Albugo species cause white rust (WR) disease in crucifer plants, including Brassica crops (eg broccoli and oilseed rape), and the model plant Arabidopsis. WR-infected plants become extremely susceptible to other diseases; we wish to understand the basic mechanisms by which this happens. Pathogens deliver molecules called effectors to host cells that interfere with host immune mechanisms. Plant resistance (R) genes recognize such effectors and then activate immunity. To overcome R genes, pathogens must evade detection by mutations in genes that encode effectors. We aim to identify the WR effector repertoire, and the best way to identify effectors is to find those that are recognized by R genes. Plant breeders often use R genes from wild relatives by crossing them into crop varieties. However, single R genes can be rapidly overcome by resistance-breaking pathogen races. We aim to clone multiple WR resistance (WRR) genes from the model plant Arabidopsis that act against WR strains that infect Brassica or other crucifer crops. By transforming crops with multiple independently acting WRR genes, the risk is reduced that a single mutation in the pathogen will create a resistance-breaking strain. In India, Australia and Canada, Brassica juncea is an important oilseed crop, fungicides are expensive for poor farmers and there are insufficient sources of WRR. Arabidopsis genes have already been identified against B. juncea strains of WR; we aim to discover and deploy additional such genes. The oilseed Camelina sativa has been engineered to produce 25% of its seed oil as "heart-healthy" polyunsaturated fatty acids identical to those in fish oil, but C. sativa is susceptible to UK WR strains. We will survey Arabidopsis natural genetic variation to identify and clone additional WRR genes against these strains, and verify their efficacy in C. sativa, prior to building a multigene stack to protect C. sativa against known UK strains of WR. We used a genetic trick to identify variation in Arabidopsis for WRR genes that act against B juncea strain of WR. However, this trick did not work to identify variation for resistance to B. oleracea (broccoli, cauliflower, Brussels sprouts) strains of WR. We will test a different trick that enables us to mutate all candidate R genes that might confer WRR to the B. oleracea strains, and thus identify new WRR genes against these strains. Such genes have the potential to provide an excellent source of resistance against B. oleracea-infecting WR strains. To identify effectors from WR that are recognized by WRR genes, we can transiently co-express a WRR gene with a set of various effector candidate genes in tobacco leaves using Agrobacterium, and if there is recognition, activation of defence results in cell death in the infiltrated part of the leaf. We can thus identify which effector is recognized by which WRR gene. Such knowledge is essential to ensure that different WRR genes really do recognize different effectors, and also as a prelude to investigating how each effector suppresses host immunity in future experiments These studies will provide multigene stacks that should provide durable resistance. Success with this approach using the Arabidopsis model system to facilitate isolation of multiple distinct WRR genes, will validate conceptually similar approaches to cloning multiple R genes from wild relatives of wheat or potato, to protect the crop against rusts or late blight.

date/time interval

  • December 1, 2014 - January 31, 2018