Assessment of genetic diversity in cultivated radishes (Raphanus sativus) by agronomic traits and SSR markers

- Genetic diversity was assessed among 126 radish F1 cultivars using 29 agronomic traits and 60 SSRs.
- In PC analysis, the first two PCs (“root shape to determine the harvest time”, “coloration of plant”) accounted for 34% of total phenotypic variance.
- In UPGMA analysis using 60 SSRs, 126 cultivars were classified into seven groups at the Jaccard's coefficient of 0.47.
- The two data sets of 29 agronomic traits and 60 SSRs were significantly correlated.
- The results would be valuable for cultivar identification and genetic diversity analysis in Raphanus sativus.

Radish (Raphanus sativus) is an economically important vegetable crop in Asia. Here, we assessed the genetic diversity of 126 F1 cultivars using 29 agronomic traits and 60 SSR markers. The 126 F1 cultivars are composed of 105 from Korea, 17 from Japan, and 4 from China. To assess the phenotypic diversity of 126 F1 cultivars, 29 agronomic traits were recorded from seedling stage to harvest, and analyzed using principal component analysis (PCA) and cluster analysis. The nine principal components (PC1-PC9) explained approximately 72% of the total variance of the 126 cultivars, and the first two PCs accounted for approximately 34%. The first PC represented “root shape to determine the harvest time”, and the second PC represented “coloration of plant”. Cluster analysis of 126 cultivars based on 29 agronomic traits resulted in three main groups in accordance with morphological affinity. To assess the genotypic diversity, we analyzed 126 F1 cultivars using 60 SSR markers. 226 polymorphic amplified fragments were obtained and the average of PIC value was 0.61. In UPGMA analysis, 126 cultivars were classified into seven groups at the Jaccard's coefficient of 0.47. 29 agronomic traits and 60 SSR markers successfully discriminated all the 126 cultivars, respectively. We examined the correlation between distance matrices of 29 agronomic traits and 60 SSRs using the Mantel test. The two data sets were significantly correlated (r = 0.527, p = 0.0001). These results would be valuable for cultivar identification and genetic diversity analysis in cultivated radishes.