A Systems Approach to Breeding Disease Resistance in Lettuce Against Necrotrophic Fungal Pathogens

Botrytis cinerea and Sclerotinia sclerotiorum are fungal pathogens of global importance, each causing multi-million pound annual crop losses pre- and post-harvest on many dicotyledonous crops including field-grown and protected lettuce crops. Chemical control is problematic with restrictions on spraying and fungicides being medium-high risk for development of resistance. Development of host resistance is a more sustainable solution, but has been an intransigent problem for breeders.

We are taking a novel approach to breeding for disease resistance against B. cinerea and S. sclerotiorum in lettuce combining systems biology and quantitative genetics. Genetic variation in susceptibility to these pathogens was identified in a set of diverse lettuce accessions, based on lesion size following leaf inoculation, which was confirmed in whole plant assays. Susceptibility to both pathogens was also correlated across different accessions thereby increasing the potential of identifying alleles conferring broad resistance. Identification of disease resistance QTL from mapping populations is underway.

We have developed a network analysis gene discovery strategy in Arabidopsis exploiting time series transcriptome data and are now applying this methodology in lettuce to predict genes conferring disease resistance against B. cinerea and S. sclerotiorum. Using RNAseq we generated a time series of gene expression in lettuce leaves over 12 time points, between 9 and 42 hours after inoculation with S. sclerotiorum or mock inoculation. From this time series data we have investigated the chronology of transcriptional reprogramming in lettuce following infection, inferred regulatory networks mediating this response and predicted key regulators of disease resistance within these networks. The expression of these key genes will be tested in diversity set lines showing extreme resistance phenotypes to examine correlation of expression with resistance. Co-localisation of these key regulators with resistance QTL could fast-track the identification of causal genes and associated markers for integration into lettuce breeding programmes.