Phenotypic data for 206 peach accessions and 150 apricot accessions evaluated for respectively 5 and 2 disease incidence traits in several environment-trials in France (2020-2023) and their respective genotyping information

[Lien vers la fiche source] The dataset contains raw phenotypic and genotypic dataset as well as the link to the GitLab Repository with the R scripts associated to the publication "Multi-environment GWAS uncovers markers associated to biotic stress response and genotype-by-environment interactions in stone fruit trees", Marie Serrie, Vincent Segura, Alain Blanc, Laurent Brun, Naïma Dlalah, Frédéric Gilles, Laure Heurtevin, Mathilde Le-Pans, Véronique Signoret, Sabrina Viret, Jean-Marc Audergon, Bénédicte Quilot, Morgane Roth. DETAILED METADATA: - Raw phenotypic data associated to the 206 accessions constituting the peach core collection, grown in 3 environment-trials (France, 2021 to 2023). It contains assessments of damages caused 1 pest (Leafhopper) and 3 diseases (Leaf curl, Rust, Powdery mildew and Shot hole) : Peach_CC_Pheno_data.csv - Raw phenotypic data associated to the 150 accessions constituting the apricot core collection, grown in 2 environment-trials (France, 2020 to 2023). It contains assessments of damages caused by 2 diseases (Rust and blossom blight) : Apricot_CC_Pheno_data.csv - Raw genotypic data of the 192 genotyped accessions among the peach core collection, characterized for 15,692 SNP markers obtained with the higher density IRSC 16K SNP array, after filtering to retain SNPs with call rate per marker > 90% and with a missingness per individual < 50% : Peach_CC_Geno_data.Rdata - Raw genotypic data of the 149 genotyped accessions among the apricot core collection, characterized for 588,790 SNP markers obtained with the Illumina HiSeq 2000 NGS technique, after filtering to retain only biallelic SNPs, with more than 10 reads deep/SNP, with a missingness per individual < 50%, a call rate per marker > 95% : Apricot_CC_Geno_data.Rdata - Genetic map data for peach obtained with the higher density IRSC 16K SNP array, with the 15,692 SNP markers names, their corresponding chromosome and position : Peach_CC_Map.txt - Genetic map data for apricot obtained with the Illumina HiSeq 2000 NGS technique, with the 588,790 SNP markers names, their corresponding chromosome and position : Apricot_CC_Map.txt - Vcf file of genotypic dataset for the 192 genotyped accessions among the peach core collection, characterized with the higher density IRSC 16K SNP array. The genotyping dataset was filtered to retain SNPs with call rate per marker > 90%, and missingness per individual < 50% which resulted in a final set 15,691 markers : Peach_CC.vcf.gz - Vcf file of genotypic dataset of the 149 genotyped accessions among the apricot core collection obtained with the Illumina HiSeq 2000 NGS technique, with an alignment performed on the third version of the ‘Marouch’ genome. This dataset was first filtered to retain only SNPs with a missingness per individual <50% and only biallelic SNPs with more than 10 reads deep/SNP have been conserved. This dataset consisted in 584,790 markers : Apricot_CC.vcf.gz - Links to the GitLab repository with the R scripts used for data analysis : Scripts_availability.txt ABSTRACT: While breeding for improved immunity is essential to achieve sustainable fruit production, it also requires to account for genotype-by-environment interactions (G × E), which still represent a major challenge. To tackle this issue, we conducted a comprehensive study to identify genetic markers with main and environment-specific effects on pest and disease response in peach (Prunus persica) and apricot (Prunus armeniaca). Leveraging multienvironment trials (MET), we assessed the genetic architecture of resistance and tolerance to seven major pests and diseases through visual scoring of symptoms in naturally infected core collections, repeated within and between years and sites. We applied a series of genome-wide association models (GWAS) to both maximum of symptom severity and kinetic disease progression. These analyses lead to the identification of environment-shared quantitative trait loci (QTLs), environment-specific QTLs, and interactive QTLs with antagonist or differential effects across environments. We mapped 60 high-confidence QTLs encompassing a total of 87 candidate genes involved in both basal and host-specific responses, mostly consisting of the Leucine-Rich Repeat Containing Receptors (LRR-CRs) gene family. The most promising disease resistance candidate genes were found for peach leaf curl on LG4 and for apricot and peach rust on LG2 and LG4. These findings underscore the critical role of G × E in shaping the phenotypic response to biotic pressure, especially for blossom blight. Last, models including dominance effects revealed 123 specific QTLs, emphasizing the significance of non-additive genetic effects, therefore warranting further investigation. These insights will support the development of marker-assisted selection to improve the immunity of Prunus varieties in diverse environmental conditions.