A systems approach to breeding for disease resistance to necrotrophic fungal pathogens in lettuce
A. TALBOT (1), E. Ransom (1), J. Brough (2), J. Graham (3), J. Clarkson (2), P. Hand (3), K. Denby (2), D. Pink (3), C. Wagstaff (4) (1) University of Warwick, United Kingdom; (2) University of Warwick, United Kingdom; (3) Harper-Adams University, United Kingdom; (4) University of Reading, United Kingdom

Lettuce is one of the most economically important leafy vegetables worldwide, with approximately 20 million tonnes grown annually. However, lettuce is susceptible to a number of pathogens including Botrytis cinerea and Sclerotinia sclerotiorum, two fungi causing substantial losses on field-grown and protected lettuce crops. Chemical control is problematic with increased regulation and the emergence of resistance to fungicides. Development of host resistance is a more sustainable solution, but has been difficult 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 for susceptibility to these pathogens was identified in a diversity set of lettuce accessions, based on lesion size after leaf inoculation. Furthermore, susceptibility to both pathogens in different accessions was correlated increasing the likelihood of identifying alleles conferring broad resistance. Identification of disease resistance QTL from mapping populations is underway. Using RNAseq, we have generated transcriptome time series from lettuce leaves after pathogen (or mock) inoculation. We are using these time series to investigate transcriptional reprogramming after infection, to infer regulatory networks mediating this response and to predict key regulators. Co-segregation of these key regulators with disease resistance QTL could speed up identification of causal genes.

Abstract Number: P11-380
Session Type: Poster