Development of a robust SNP marker set for genotyping diverse gene bank collections of polyploid roses

Abstract

Background Due to genetic depletion in nature, gene banks play a critical role in the long-term conservation of plant genetic resources and the provision of a wide range of plant genetic diversity for research and breeding programs. Genetic information on accessions facilitates gene bank management and can help to conserve limited resources and to identify taxonomic misclassifications or mislabelling. Here, we developed SNP markers for genotyping 4,187 mostly polyploid rose accessions from large rose collections, including the German Genebank for Roses. Results We filtered SNP marker information from the RhWag68k Axiom SNP array using call rates, uniformity of the four allelic dosage groups and chromosomal position to improve genotyping efficiency. After conversion to individual PACE® markers and further filtering, we selected markers with high discriminatory power. These markers were used to analyse 4,187 accessions with a mean call rate of 91.4%. By combining two evaluation methods, the mean call rate was increased to 95.2%. Additionally, the robustness against the genotypic groups used for calling was evaluated, resulting in a final set of 18 markers. Analyses of 94 pairs of assumed duplicate accessions included as controls revealed unexpected differences for eight pairs, which were confirmed using SSR markers. After removing the duplicates and filtering for accessions that were robustly called with all 18 markers, 141 out of the 1,957 accessions showed unexpected identical marker profiles with at least one other accession in our PACE® and SSR analysis. Given the attractiveness of NGS technologies, 13 SNPs from the marker set were also analysed using amplicon sequencing, with 76% agreement observed between PACE® and amplicon markers. Conclusions Although sampling error cannot be completely excluded, this is an indication that mislabelling occurs in rose collections and that molecular markers may be able to detect these cases. In future applications, our marker set could be used to develop a core reference set of representative accessions, and thus optimise the selection of gene bank accessions.