Progeny-based genomic selection reveals untapped genetic potential in an underutilized medicinal plant, Perilla frutescens

Despite their substantial therapeutic value, medicinal plants have undergone limited genetic improvement through breeding because of the scarcity of expert breeders. Moreover, quantifying bioactive compounds is expensive. Genomic selection (GS), which leverages genome-wide markers to predict breeding values and assemble favorable alleles, offers a practical way to unlock latent genetic potential. As a model case, we evaluated GS in red perilla ( Perilla frutescens ). Building on previous work, we implemented a cross-selection strategy that prioritized segregation variance by selecting crosses based on predicted additive genotypic values of the progeny, and evaluated its effectiveness through actual crossing experiments targeting three key medicinal compounds. Progeny from GS-based crosses (Crs1 to Crs7) outperformed those from phenotypic selection (Crs8) in the G2 generation, demonstrating a higher mean, greater variance, and superior top individuals. The best G2 individual exhibited nearly twofold higher levels of two target compounds relative to the existing cultivar ′Sekiho′. This study provides the first empirical demonstration that GS can improve multiple medicinal compounds in red perilla and highlights the effectiveness of cross-selection based on predicted progeny performance. In addition, the evidence presented here supports the broader application of GS in underutilized medicinal plants.