Metabolomic datasets of an apple progeny carrying resistance quantitative trait loci to apple scab before or after inoculation of the pathogen .

Phytosanitary treatments are massively used in orchards to fight apple scab, a disease caused by the fungus (). To reduce these treatments, resistant varieties are largely deployed but their effectiveness can decrease over time. The combination of complementary molecular mechanisms within new varieties could enhance the durability of genetic resistance however, the underlying resistance mechanisms remain poorly understood. An apple pseudo-F1 progeny was previously widely investigated for its quantitative trait loci (QTL) controlling resistance to scab and at least three of them seem to act complementarily; notably, one of them is specific to some isolates while the others have a broader spectra of action. The aim of this approach is to better understand the underlying molecular mechanisms and metabolites associated with resistance alleles by exploring apple leaf specialized metabolism. A total of three experiments was conducted: one experiment included non-inoculated leaves whereas in the two other experiments, leaf samples were collected five days after inoculation with two different isolates, including one known to overcome one QTL. Metabolic content was extracted in aqueous methanol before performing an untargeted metabolomic analysis using an Orbitrap IDX mass spectrometer, allowing high-resolution mass spectrometry (HRMS) detection. This approach without enables the detection of potentially new chemical families involved in resistance to apple scab. The current data article includes 1) the protocol of plant sample production with a table summarizing key elements of the experimental designs, 2) overview of the raw metabolomic profiles from all three experiments and 3) assessment of metabolic feature reproducibility between replicates in each dataset through Principal Component Analysis. The raw data files are available on the recherche.data.gouv repository (10.57745/XJBD8V). These datasets are valuable resources to further investigate the molecular mechanisms underlying genetic resistance to apple scab, with a focus on specialized metabolism. In the long term, it should improve apple breeding strategies by informing on how to combine appropriate genetic and biochemical factors in new varieties to ensure a more durable resistance.