A Systems Approach to Disease Resistance Against Necrotrophic Fungal Pathogens

The fungal pathogens Botrytis cinerea and Sclerotinia sclerotiorum have broad host ranges and cause serious disease on many horticultural crops. Both fungi can cause substantial losses on field-grown and protected lettuce crops, an industry worth almost £200 M annually in the UK. B. cinerea is a particular problem post-harvest, whereas S. sclerotiorum can result in up to 50% crop loss pre-harvest. Chemical control is problematic as few effective compounds are available, the number of sprays is restricted and timing is difficult. Moreover, the fungicides are medium to high risk for development of resistance. Development of durable resistance in the crop is a more sustainable solution, but has been an intransigent problem for lettuce breeders. The objective of this proposal is to demonstrate that a novel approach to breeding for pathogen resistance is possible.

We will apply genomic and systems biology (computational) approaches in lettuce, and combine this with quantitative genetics studies to identify novel genes for increasing the resistance of lettuce to both B. cinerea and S. sclerotiorum. This will provide a foundation to develop similar resistance to these pathogens in other horticultural crops.

We have two hypotheses we want to test. Firstly, that we can identify genes which confer resistance to both B. cinerea and S. sclerotiorum, two necrotrophic fungal pathogens. Genome sequencing of these fungi has indicated they share a range of genes associated with infection and colonization of plants, hence host resistance mechanisms against one pathogen might also confer resistance to the other.

Secondly, we want to test the feasibility of applying systems biology research into horticultural crop species. We have used systems biology approaches to generate network models of how genes interact during the defence response of Arabidopsis to infection by B. cinerea. We combined large-scale gene expression data with mathematical modelling to predict the key resistance genes. In this work, we will carry out network analysis of the lettuce defence response and test whether the same genes are involved in disease resistance, and/or whether the hub genes in the network are important. This is a completely new approach to crop improvement, relying on gene-gene interactions during defence against pathogen infection. We will also look for conservation of disease resistance genes in tomato and Brassica, key crops affected by these pathogens.

At the same time we will employ a more traditional quantitative genetic analysis to identify regions of the lettuce genome that influence resistance against both of these pathogens. We will screen nearly 100 lettuce accessions and cross accessions with the greatest resistance to a standard cultivar to generate mapping populations. A pre-existing mapping population (known to be segregating for disease resistance) will be screened for disease resistance to both B. cinerea and S. scerotiorum to identify important genomic regions for these traits.

Finally we will integrate our quantitative genetic analysis and results from network analysis to generate lettuce lines and markers for use in breeding programmes. This project is possible because of the lettuce genome sequence that is available, as well as the extensive lettuce germplasm and genetic and genomic resources that Warwick has generated. The work will be exploited primarily through A.L.Tozer to develop lettuce varieties with increased resistance to B. cinerea and S. sclerotiorum fungal pathogens.

We will use systems biology approaches in lettuce combined with quantitative genetics studies to identify novel genes for increasing the resistance of lettuce to both Botrytis cinerea and Sclerotinia sclerotiorum, two important fungal pathogens. In a previous project, we generated network models predicting regulatory interactions between Arabidopsis genes during infection by B. cinerea. This network analysis significantly improved our detection of major defence genes and demonstrated the power of systems biology to predict the targets governing a particular trait. We will now test whether this approach can be used in crop plants using lettuce as our exemplar, where breeding for resistance against B. cinerea and S. sclerotiorum has not been very successful.

Firstly we will profile lettuce gene expression over time following B. cinerea infection and use this data in network inference to identify the key lettuce hub genes. We will screen a lettuce diversity collection for resistance against both pathogens and use the accessions with extreme phenotypes to test whether expression of the key genes is correlated with disease resistance. We will use RNAi and overexpression to directly test the function of a small number of key genes in lettuce, and ask whether it is possible to identify sources of resistance against both pathogens using network analysis. We will also test whether hub genes are conserved in lettuce, Arabidopsis, tomato and Brassica and hence broadly applicable.

Secondly, we will screen a lettuce mapping population (generated from parents differing in disease resistance) to identify quantitative trait loci (QTL) for resistance against B. cinerea and S. sclerotiorum, as well as eQTL for expression of the lettuce network hub genes. Integrating QTL with eQTL, hub gene location and polymorphisms will enable us to identify markers for beneficial lettuce alleles, and produce pre-breeding material for the development of disease resistant lettuce cultivars.

Food security is currently a major research challenge and the yield and economic losses associated with plant diseases continue to have a great impact on our ability to ensure the production of good quality vegetable crops. Reducing the inputs required for production is a high priority for increasing the sustainability of food production. This project aims to address this by identifying and mapping novel alleles associated with increased resistance to Botrytis cinerea and Sclerotinia sclerotiorum in lettuce. New genetic resources, markers and the knowledge generated in this research will accelerate the ability of the industry partner A.L. Tozer and other breeders to develop commercially acceptable lettuce cultivars incorporating this valuable resistance trait. This will result in significant economic gains for both growers and breeders as well as environmental benefits. For UK growers, a 50% reduction in disease due to B. cinerea/S. sclerotiorum would save at least £10M p.a. given an average crop loss of 10%. As more than 90% of UK lettuce crops (22,000 ha) are treated with fungicides targeted at these pathogens (2-3 sprays per crop), a 50% reduction in these applications due to the deployment of more resistant lettuce cultivars would result in total savings of >£7.1M p.a. Moreover, there would also be a concomitant reduction in pathogen inoculum (particularly a reduction in sclerotia returned to the soil by S. sclerotiorum) which would benefit disease management in many of the other susceptible crops in rotations. The associated environmental benefits would therefore include a reduction in crop waste, and more efficient use of resources and inputs such as land, water, pesticides and fuel. Consumers would also then have access to good quality lettuce grown in a more sustainable way.

Crucially, demonstration of network analysis as a successful method for gene discovery in a horticultural crop would provide a framework for similar approaches in other crops, and even, if key disease resistance genes are conserved, candidate genes to immediately test. Collaboration with East Malling Research (transformation of diploid strawberry) and Syngenta (the SAMUTAGENE tomato TILLING population) will be sought to build on our results in lettuce and initiate direct testing of hub genes in strawberry and tomato. We will also exploit the Brassica resources available at Warwick in further funding applications. B. cinerea and S. sclerotiorum are pathogens with wide host ranges, hence the potential applicability of our generated data and approach is applicable to a broad range of crops. Integration of our systems knowledge with existing QTL phenotyping can accelerate the identification of other beneficial alleles.

An important aspect of our proposed research is the training that the PDRA on the project would receive. Warwick is recognised for its expertise in interdisciplinary training and the Systems Biology MSc and Doctoral Training Centre have successfully trained biologists, mathematicians, and computer scientists to be systems biologists working in an interdisciplinary manner. The PDRA would be exposed to this environment, have the opportunity to take modules of the various MSc courses at Warwick (including Systems Biology, Food Security, and Sustainable Crop Production) and also receive training in various transferable skills.
The next generation of young scientists will benefit from knowledge gained from this project and learning about the combined experimental and theoretical approaches used to add value to crop research. Furthermore, the integration of up to date network analysis with applied crop science is likely to catch the imagination of students from high school to undergraduate level and help spark interest in plant science. It is essential we build interest in plant science amongst young people if we are to build a generation of capable of meeting the global food security challenge.