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

Progeny-based genomic selection reveals untapped genetic potential in an underutilized medicinal plant, Perilla frutescens | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Progeny-based genomic selection reveals untapped genetic potential in an underutilized medicinal plant, Perilla frutescens Sei Kinoshita, Kengo Sakurai, Takahiro Tsusaka, Miki Sakurai, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9216494/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract 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. Progeny from genomic selection-based crosses (Crs1–Crs7) outperformed those from phenotypic selection (Crs8) in the G 2 generation, demonstrating a higher mean, greater variance, and superior top individuals. The best G 2 individual exhibited nearly twofold higher levels of two target compounds relative to the existing cultivar ‘Sekiho’. This study provides the first empirical demonstration that genomic selection 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 genomic selection in underutilized medicinal plants. Crossing experiment genome-assisted breeding genomic selection medicinal plants Perilla frutescens Full Text Additional Declarations No competing interests reported. Supplementary Files RPGSsupplement.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9216494","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":615483556,"identity":"1e5b1add-abc5-4fa8-b2f3-e0b2ace47b79","order_by":0,"name":"Sei Kinoshita","email":"","orcid":"","institution":"The University of Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Sei","middleName":"","lastName":"Kinoshita","suffix":""},{"id":615483557,"identity":"456cab74-1b23-41e3-9fd8-6138af75d3ef","order_by":1,"name":"Kengo Sakurai","email":"","orcid":"","institution":"The University of 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frutescens","lastPublishedDoi":"10.21203/rs.3.rs-9216494/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9216494/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDespite 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 (\u003cem\u003ePerilla frutescens\u003c/em\u003e). 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 genomic selection-based crosses (Crs1\u0026ndash;Crs7) outperformed those from phenotypic selection (Crs8) in the G\u003csub\u003e2\u003c/sub\u003e generation, demonstrating a higher mean, greater variance, and superior top individuals. The best G\u003csub\u003e2\u003c/sub\u003e individual exhibited nearly twofold higher levels of two target compounds relative to the existing cultivar \u0026lsquo;Sekiho\u0026rsquo;. This study provides the first empirical demonstration that genomic selection can improve multiple medicinal compounds in red perilla and highlights the effectiveness of cross-selection based on predicted progeny performance. 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