Multi-omics approach in a resistant grapevine inoculated with Plasmopara viticola

The destructive disease downy mildew causes significant economic losses to viticulture. Plasmopara viticola (Berk. And Curt) Berl. and Toni is the causal agent of the disease and its interaction with the grapevine needs to be further investigated. The use of grapevine varieties with durable resistance to downy mildew is a promising strategy to control the disease. Vitis-P. viticola interaction is still poorly understood, so applying a multi-omics approach can extend knowledge of how the plant system is affected by biotic stress. We used the grapevine variety Jasmine with a QTL providing resistance to P. viticola (Rpv12) to investigate the defence response to the pathogen at metabolite and transcriptional levels. Leaf discs were artificially inoculated and sampling took place at different time points at 12, 24, 48 and 96 hours post inoculation (hpi), together with not inoculated controls. We investigated primary and secondary metabolism using methods of identification and quantification for lipids (LC-MS/MS), phenols (LC-MS/MS) and primary compounds from acids, amino acids, amines/others and sugars (GC-MS), and semi-quantification for volatile compounds (GC-MS). The same samples were used for Rna-seq analysis to evaluate transcriptomic perturbation. The two datasets were explored separately to better highlight the single -omics perturbation caused by pathogen attack. Eighty eight metabolites belonging to several classes show values of the t-statistics indicating a different behaviour between the two conditions. At 12 hours we found only some terpenoid metabolite modulation. The last two time points, 48 and 96 hours were characterised by an increase in some lipid compounds (mostly fatty acids) flavonols and phenylpropanoids. At the latest stage we found an increase in amino acids and sugars after pathogen inoculation. The change in the metabolism is a reflection of transcript modulation. Rna-seq analysis showed 432 differentially expressed genes (DEGs) with general down-regulation at 24 hours and reactivation of metabolic processes at 48 and 96 hpi. A global view of transcriptome perturbation showed general down-regulation at 24 hours post infection, probably to save energy that can be used for defence responses. Metabolic processes seemed to be reactivated at the later time points; amino acid, carbohydrate and lipid related genes were up-regulated, together with secondary metabolism. Multiple Co-Inertia Analysis revealed a strong effect of perturbation due to the time course, with a similar trend in both inoculated and not inoculated samples. Good separation of the two condition samples was shown at 96 hpi; at that time point the effect of the pathogen was strongly manifested, with separation of inoculated and not inoculated samples. Future integration analysis is required to better highlight the correlation between our two –omics datasets.