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<p>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, 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 genomic selection in red perilla (<i>Perilla frutescens</i>). 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. Several genomic selection-based crosses produced G₂ progeny with high perillaldehyde and rosmarinic acid contents and broad phenotypic variation under the tested field condition. The best individual derived from the genomic selection-based crosses exhibited nearly twofold higher levels of two target compounds relative to the existing cultivar ‘Sekiho’. Because only one phenotypically selected cross was included, this experiment was not designed to provide a statistical comparison between genomic and phenotypic selection. Instead, it serves as an empirical case study demonstrating the application of progeny-based cross selection in an underutilized medicinal plant breeding program.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月3日

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  • Sei Kinoshita,
  • Kengo Sakurai,
  • Takahiro Tsusaka,
  • Miki Sakurai,
  • Kenta Shirasawa,
  • Sachiko Isobe,
  • Hiroyoshi Iwata

摘要

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, 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 genomic selection 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. Several genomic selection-based crosses produced G₂ progeny with high perillaldehyde and rosmarinic acid contents and broad phenotypic variation under the tested field condition. The best individual derived from the genomic selection-based crosses exhibited nearly twofold higher levels of two target compounds relative to the existing cultivar ‘Sekiho’. Because only one phenotypically selected cross was included, this experiment was not designed to provide a statistical comparison between genomic and phenotypic selection. Instead, it serves as an empirical case study demonstrating the application of progeny-based cross selection in an underutilized medicinal plant breeding program.