Abstract/Summary

Apple is one of the most important fruit crops grown in temperate regions. Ex situ conservation of apple genetic resources mainly relies on grafted trees maintained in orchards, which can be space- and labor-intensive. To help collection managers to compare their germplasm with others’ at both the national and international levels, Malus UNiQue genotype codes (MUNQ) were proposed for all accessions sharing the same genetic marker profile. These genetic profiles were initially obtained using a standardized set of 16 SSRs. However, an impending difficulty in SSR analysis is expected and many genetic studies nowadays use SNP markers. SNP-based MUNQ assignment is expected to be more streamlined, but just like for SSRs, it will be essential that a consistent marker set is used across studies worldwide to enable comparisons among them without genotyping each new unique individual with a more expensive array. For this reason, we developed a set of 96 SNP markers that can unequivocally distinguish cultivars in apple collections and detect redundancy faster at low cost. To support this approach, we started from genome-wide SNP genotypic data obtained with the apple 20K and/or 480K arrays for 2120 unique individuals, including 2036 with a MUNQ code assigned through SSR markers. A total of 182 SNPs were tested using the KASP technology in nanofluidic Integrated Fluidic Circuit (IFC) to finally choose a set of 96 SNPs ensuring that each pair of individuals among all 2120 was distinguished by at least 6 SNPs in the absence of missing data. A comparison of MUNQ code assignment for 754 newly genotyped accessions using the standardized set of 16 SSRs and the new set of 96 SNPs was performed. It was possible to group accessions with essentially unique profiles using SNP data, and the groups obtained were almost always consistent with groups obtained with SSR data. Thus, a transition from the SSR-based MUNQ system to a SNP-based MUNQ system will be possible.