The core of Milestone 3 is the detection of markers and candidate genes in linkage with resistance/susceptibility to PM through a single-family QTL analysis (Activity 3.1) and a GWA study (Activity 3.2). This analysis will rely on the accurate genotyping (Milestone1) and phenotyping (Milestone2) of the two germplasm collections. The detection of molecular markers in strong linkage disequilibrium with the traits of interest will allow the in silico annotation of the genetic interval underlying each QTLs.

Activity 3.1: QTL analysis on the full-sib population

Objective: Identification of molecular markers linked to resistance/susceptibility of PM through a single-family QTL approach

Expected results: 
- Development of a genetic linkage map for the FS-POP
- List of molecular markers linked to resistance/susceptibility to powdery mildew for FS-POP 

Methodologies:
Genetic data (Activity 1.2) of the FS-POP will be used for the generation of a linkage map. The QTL analysis will be carried out employing the mapQTL software (Kyazma) and/or the R/qtl2 package.

Activity 3.2: Population genetic studies and GWAS analysis on the germplasm collection

Objective: Identification of molecular markers linked to resistance/susceptibility of powdery mildew through a GWAS approach

Expected results:
- Infer the level of genetic stratification and the degree of relatedness between local accessions selected in different areas in south Italy
- List of molecular markers linked to resistance/susceptibility to powdery mildew for germplasm collection

Methodologies:
Robust SNP detected in Activity 1.2 will be employed for a GWAS study on the germaplasm. A mixed-linear model will be carried out taking the genetic stratification and the kinship as covariates. GWAS will be carried out using the Efficient Mixed-Model Association eXpedited (EMMAX) implemented in the ‘GWAS’ function of the rrBLUP R package. To minimize type-one errors, significant associations will be detected after correcting the p-value for multiple testing using the false discovery rate (FDR) method (ER 3.4).

Activity 3.3: in silico gene annotation

Objective: Identification of the genes underlying the QTL regions

Expected results:
- Infer the linkage disequilibrium among germplasm population
- List of candidate genes located in the QTL intervals 

Methodologies:
The availability of a high-quality and annotated reference genome for grapevine will allow the in silico annotation of the QTL regions detected in Activities 3.1 and 3.2.. The analysis of the non-random association between loci through a whole-genome LD decay scan (ER 3.5) will provide insights both on the population genetic forces structuring the germplasm collection in the analysis and on the optimal genomic window for the in silico gene annotation (ER 3.6).