A new set of SSR markers in a single reaction for accurate identification of sweet cherry varieties

09 Sep 2026
238

The genetic characterization of sweet cherry varieties is becoming increasingly important for the management of genetic resources, varietal improvement, and verification of the identity of nursery material.

The need for highly discriminating identification systems is particularly evident in Prunus avium, a species characterized by relatively limited genetic diversity due to the self-compatibility of some varieties and the repeated use of a limited number of genotypes in breeding programs.

This situation makes it difficult to distinguish some closely related cultivars based solely on traditional molecular markers.

A recent study addressed this limitation by developing a new set of highly discriminating SSR (Simple Sequence Repeat) markers, referred to as “16in1”, designed to enable sweet cherry genotyping through a single multiplex PCR reaction.

Genetic characterization

Starting from whole-genome sequences of 299 sweet cherry genotypes, the researchers identified 30 new highly polymorphic SSR markers.

Following a validation and selection phase based on parameters such as polymorphic information content, heterozygosity, number of alleles, and amplification capacity, 16 markers were integrated into a single PCR reaction, including 12 newly developed SSRs and four previously described markers.

The system was then validated on a collection of 315 samples, corresponding to 294 unique genotypes.

The mean polymorphic information content (PIC) was 0.767, while the overall probability that two genetically distinct samples would randomly exhibit the same profile was estimated at 1.27 × 10−19.

Discriminating performance

Comparison with the set of 16 SSR markers recommended by the European Cooperative Programme for Plant Genetic Resources (ECPGR) showed a clear improvement: the latter had a mean PIC of 0.564 and a random identity probability of 1.00 × 10−12.

The new system therefore increases the ability to discriminate between different genotypes by approximately seven orders of magnitude.

However, the researchers point out that the estimated identity probability was derived from a collection consisting of European and North American varieties and could therefore vary for populations from other geographical regions or for wild cherries.

Analysis of population genetic structure showed a more precise distribution of genotypes among the different groups, while parentage analysis provided particularly interesting results for breeding.

Parentage analysis

With the 16in1 system, at least one parental combination without allelic mismatches was identified for 123 of the 294 genotypes, and among the 34 cultivars for which both parents were known, the correct combination was identified as the sole proposed combination in 28 cases, corresponding to 82.35%.

With the ECPGR system, by contrast, the correct parental combination was identified as the sole proposed combination in only 5 out of 34 cases.

The effectiveness of the new marker set is particularly relevant in groups characterized by high inbreeding, such as the group derived from ‘Van’, where reduced genetic variability makes cultivar discrimination more challenging.

Applied perspective

From an applied perspective, the main advantage lies in integrating the 16 markers into a single reaction, thereby simplifying the analytical workflow, reducing the risk of errors, and limiting time, labor, and costs.

The new system could therefore be a useful tool not only in research laboratories and breeding programs, but also for verifying the varietal identity of nursery material and for parentage and population structure studies.

Source: Čmejlová, J., Holušová, K., Krška, B., Suran, P., Bartoš, J., & Čmejla, R. (2026). The Development of New SSR Markers and an Assay for Genotyping Sweet Cherry (Prunus avium L.) in One Reaction. International Journal of Molecular Sciences, 27(5), 2324. https://doi.org/10.3390/ijms27052324

Image source: Stefano Lugli

Andrea Giovannini
PhD in Agricultural, Environmental and Food Science and Technology - Arboriculture and Fruitculture, University of Bologna, IT 


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