Assessing the Potential for Genome-Assisted Breeding in Red Perilla Using Quantitative Trait Locus Analysis and Genomic Prediction.

Red perilla is an important medicinal plant used in Kampo medicine. The development of elite varieties of this species is urgently required. Medicinal compounds are generally considered target traits in medicinal plant breeding; however, selection based on compound phenotypes (i.e., conventional selection) is expensive and time consuming. Here, we propose genomic selection (GS) and marker-assisted selection (MAS), which use marker information for selection, as suitable selection methods for medicinal plants, and we evaluate the effectiveness of these methods in perilla breeding. Three breeding populations generated from crosses between one red and three green perilla genotypes were used to elucidate the genetic mechanisms underlying the production of major medicinal compounds using quantitative trait locus analysis and evaluating the accuracy of genomic prediction (GP). We found that GP had a sufficiently high accuracy for all traits, confirming that GS is an effective method for perilla breeding. Moreover, the three populations showed varying degrees of segregation, suggesting that using these populations in breeding may simultaneously enhance multiple target traits. This study contributes to research on the genetic mechanisms of the major medicinal compounds of red perilla, as well as the breeding efficiency of this medicinal plant.

Genetic diversity among Japanese indigenous common buckwheat (Fagopyrum esculentum) cultivars as determined from amplified fragment length polymorphism and simple sequence repeat markers and quantitative agronomic traits.

We assessed the genetic diversity in Japanese indigenous common buckwheat (Fagopyrum esculentum) cultivars using amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) markers and investigated the relationships between the genetic diversity and agronomic traits. The average expected intracultivar hetero zygosity was 0.303 for AFLP and 0.819 for SSR. The differentiations among agroecotypes, among cultivars within an agroecotype, and among cultivars were small (0.002, 0.024, and 0.026 for SSR and 0.013, 0.013, and 0.026 for AFLP, respectively) but statistically significant from zero except for the SSR differentiation among agroecotypes. In principal coordinates analysis, cultivars within the same agroecotype tended to cluster, indicating that agroecotypes well reflected the genetic relationships among cultivars. In AFLP, the differentiation among the agroecotypes was more distinct than in SSR, and genetic distance showed a moderate correlation with the difference in quantitative traits, indicating that AFLP can resolve the relationships among cultivars with better resolution than SSR. By contrast, SSR may be more sensitive to demographic changes. Four of the five SSR markers showed a significant positive correlation (Kendall's tau = 0.382-0.607) between allelic richness and variation in flowering timing, indicating that cumulative bottleneck events have occurred during the population history, with a decline in the variation of photosensitivity of flowering.