Metabolic biomarker-based phenotyping unveils quantitative effects of plant resistance and pathogen aggressiveness in the grapevine (Vitis spp.) - downy mildew (Plasmopara viticola) pathosystem.
Possamai, T.; Baltenweck, R.; Wiedemann-Merdinoglu, S.; Lacombe, M.-C.; Dorne, M.-A.; Bareyre, M.; Griem, E.; Fuchs, R.; Bogs, J.; Duchene, E.; Mestre, P.; Merdinoglu, D.; Hugueney, P.
Show abstract
Grapevine resistance to downy mildew has been primarily associated with major "Resistance to Plasmopara viticola" (Rpv) loci, which are extensively used in breeding programs. Resistant varieties represent an effective solution to mitigate the environmental impact of fungicide application in viticulture, but P. viticola strains able to overcome major Rpv have become a main threat to their cultivation. Pyramiding resistance loci in the same variety enhances plant resistance, but interactions involving stacked and defeated Rpv and different P. viticola strains are poorly documented. Investigation of these interactions may uncover new information for the development of efficient breeding strategies, the optimal exploitation of Rpv, and the building of durable resistance. In the present study, a grapevine offspring carrying single and pyramided Rpv1, Rpv3.1 and Rpv10 was phenotyped in laboratory conditions for the resistance to P. viticola using a naive strain and a strain virulent towards Rpv10. By using a high-resolution phenotyping strategy based on P. viticola metabolic biomarkers, we demonstrated that the efficacy of Rpv combinations and aggressiveness of P. viticola strains can be quantified in the early phase of infection and were often related to sporulation outcome. Furthermore, we described how a limited residual effect of a defeated Rpv may become significant in pyramiding. In conclusion, in addition to providing the keys to streamlining resistance utilization in grapevine, our research presents a distinctive case study that provides valuables information for breeding new resistant varieties, thanks to an innovative "omic"-based phenotyping approach, which may be adapted to other plant pathosystems.
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