Comparative Genomic Prediction of Resistance to Fusarium Wilt (Fusariumoxysporum f. sp. niveum race 2) in Watermelon: Insights from Parametric and Machine Learning Approaches

Comparative Genomic Prediction of Resistance to Fusarium Wilt (Fusariumoxysporum f. sp. niveum race 2) in Watermelon: Insights from Parametric and Machine Learning Approaches | 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 Comparative Genomic Prediction of Resistance to Fusarium Wilt (Fusariumoxysporum f. sp. niveum race 2) in Watermelon: Insights from Parametric and Machine Learning Approaches Anju Biswas, Pat Wechter, Venkat Ganaparthi, Diego Jarquin, Shaker Kousik, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4877259/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Jan, 2025 Read the published version in Theoretical and Applied Genetics → Version 1 posted 5 You are reading this latest preprint version Abstract Complex traits influenced by multiple genes pose challenges for marker-assisted selection (MAS) in breeding. Genomic selection (GS) is a promising strategy for achieving higher genetic gains in quantitative traits by stacking favorable alleles into elite cultivars. Resistance to Fusarium oxysporum f. sp. niveum ( Fon ) race 2 in watermelon is complex and polygenic with moderate heritability. This study evaluated GS as an alternative or additional approach to quantitative trait loci (QTL) analysis/marker assisted selection (MAS) for enhancing Fon race 2-resistance in elite watermelon cultivars. Objectives were to: 1) assess the accuracy of genomic prediction (GP) models for predicting Fon race 2-resistance in F 2 (Pop I) and recombinant inbred line (RIL) (Pop II) populations, 2) rank and select families in each population based on genomic estimated breeding values (GEBVs) for developing testing populations, and 3) verify if major QTL associated with Fon race 2-resistance are present in top selected families with the highest GEBV. Resistance ratings were based on the percentage of healthy plants at the 28-day post-seeding in Fon race 2-inoculated soil. GBS-SNP data from genotyping-by-sequencing (GBS) for 205 F 2 : 3 and 204 RIL families were used, and parental line genome sequences were used as references. Six GS models, including parametric (G-BLUP, BayesB, Bayes_LASSO) and non-parametric (Random Forest, SVM Linear, SVM Radial) methods, were tested. G-BLUP and Random Forest outperformed the other models, with correlations of 0.48 in the F 2:3 and 0.68 in the RIL populations, highlighting the GP efficacy in early-stage breeding for improving Fon race 2-resistance in elite watermelon cultivars. Watermelon breeding genomic prediction (GP) genomic selection (GS) QTL Fusarium resistance Full Text Cite Share Download PDF Status: Published Journal Publication published 24 Jan, 2025 Read the published version in Theoretical and Applied Genetics → Version 1 posted Editorial decision: Major revisions 23 Oct, 2024 Reviewers agreed at journal 14 Aug, 2024 Reviewers invited by journal 11 Aug, 2024 Editor assigned by journal 08 Aug, 2024 First submitted to journal 07 Aug, 2024 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4877259","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":338626945,"identity":"e7f3ee15-48ff-405c-8856-75c1ed04e7e6","order_by":0,"name":"Anju Biswas","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYHCCBGYGAxDN2PzgA5BiYydeC/MxwxkgLcxEWANVw5YgzYPExQn4Zzc8ky4oqEvs7z9jYGzza5s8HzMD44ePObi1SNw5kCY9w+Bw4owbOQaPc/tuG7YxMzBLztyGx5obCWnSPAYHchtu8BgY5/bcZgRqYWPmxaNFHqKlLnf++TMG0pY9t+0JajGAaGHO3XAgLUGa4cftRIJaDG8kJFsD/VK/8UbyMcPehtvJbcyMzXj9IncjJ/F2wZ86Y7nzB5sf/Phz23Z+e/PBDx/xeZ+BJwHBZmwDkw341AMB+wEkzh8CikfBKBgFo2BEAgBia1NgaHtBJQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-2544-6917","institution":"USDA-ARS: USDA Agricultural Research Service","correspondingAuthor":true,"prefix":"","firstName":"Anju","middleName":"","lastName":"Biswas","suffix":""},{"id":338626946,"identity":"93c8240e-e1b9-4da7-980e-1b9185e9f6b4","order_by":1,"name":"Pat Wechter","email":"","orcid":"","institution":"Clemson University","correspondingAuthor":false,"prefix":"","firstName":"Pat","middleName":"","lastName":"Wechter","suffix":""},{"id":338626947,"identity":"b520d0a9-4ec4-4a2f-ae52-987682448aec","order_by":2,"name":"Venkat Ganaparthi","email":"","orcid":"","institution":"Clemson University","correspondingAuthor":false,"prefix":"","firstName":"Venkat","middleName":"","lastName":"Ganaparthi","suffix":""},{"id":338626948,"identity":"8c5c3102-3b5a-4752-b89b-a448cb4556a9","order_by":3,"name":"Diego Jarquin","email":"","orcid":"","institution":"University of Florida","correspondingAuthor":false,"prefix":"","firstName":"Diego","middleName":"","lastName":"Jarquin","suffix":""},{"id":338626949,"identity":"2908e150-59e9-429e-b997-0668c3a17457","order_by":4,"name":"Shaker Kousik","email":"","orcid":"","institution":"USDA-ARS: USDA Agricultural Research Service","correspondingAuthor":false,"prefix":"","firstName":"Shaker","middleName":"","lastName":"Kousik","suffix":""},{"id":338626950,"identity":"31b76470-d4c6-4456-a737-795af1eddf91","order_by":5,"name":"Sandra Branham","email":"","orcid":"https://orcid.org/0000-0002-0373-4566","institution":"Clemson University","correspondingAuthor":false,"prefix":"","firstName":"Sandra","middleName":"","lastName":"Branham","suffix":""},{"id":338626951,"identity":"e89a8e61-1bde-4e1e-97a6-08517e207de6","order_by":6,"name":"Amnon Levi","email":"","orcid":"","institution":"USDA-ARS: USDA Agricultural Research Service","correspondingAuthor":false,"prefix":"","firstName":"Amnon","middleName":"","lastName":"Levi","suffix":""}],"badges":[],"createdAt":"2024-08-08 00:21:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4877259/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4877259/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00122-024-04813-8","type":"published","date":"2025-01-24T15:57:19+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":74859091,"identity":"a92c5169-468a-4d42-99da-ddc52830596e","added_by":"auto","created_at":"2025-01-27 16:13:30","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":266002,"visible":true,"origin":"","legend":"","description":"","filename":"WatermelonGSManuscriptBiswaset.al.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4877259/v1_covered_14200d63-8fff-4b28-92bf-e3935e8157f6.pdf"}],"financialInterests":"","formattedTitle":"Comparative Genomic Prediction of Resistance to Fusarium Wilt (Fusariumoxysporum f. sp. niveum race 2) in Watermelon: Insights from Parametric and Machine Learning Approaches","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"theoretical-and-applied-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"taag","sideBox":"Learn more about [Theoretical and Applied Genetics](https://www.springer.com/journal/122)","snPcode":"122","submissionUrl":"https://submission.nature.com/new-submission/122/3","title":"Theoretical and Applied Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Watermelon, breeding, genomic prediction (GP), genomic selection (GS), QTL, Fusarium, resistance","lastPublishedDoi":"10.21203/rs.3.rs-4877259/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4877259/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eComplex traits influenced by multiple genes pose challenges for marker-assisted selection (MAS) in breeding. Genomic selection (GS) is a promising strategy for achieving higher genetic gains in quantitative traits by stacking favorable alleles into elite cultivars. Resistance to \u003cem\u003eFusarium oxysporum\u003c/em\u003e f. sp. \u003cem\u003eniveum\u003c/em\u003e (\u003cem\u003eFon\u003c/em\u003e) race 2 in watermelon is complex and polygenic with moderate heritability. This study evaluated GS as an alternative or additional approach to quantitative trait loci (QTL) analysis/marker assisted selection (MAS) for enhancing \u003cem\u003eFon\u003c/em\u003e race 2-resistance in elite watermelon cultivars. Objectives were to: 1) assess the accuracy of genomic prediction (GP) models for predicting \u003cem\u003eFon\u003c/em\u003e race 2-resistance in F\u003csub\u003e2\u003c/sub\u003e (Pop I) and recombinant inbred line (RIL) (Pop II) populations, 2) rank and select families in each population based on genomic estimated breeding values (GEBVs) for developing testing populations, and 3) verify if major QTL associated with \u003cem\u003eFon\u003c/em\u003e race 2-resistance are present in top selected families with the highest GEBV. Resistance ratings were based on the percentage of healthy plants at the 28-day post-seeding in \u003cem\u003eFon\u003c/em\u003e race 2-inoculated soil. GBS-SNP data from genotyping-by-sequencing (GBS) for 205 F\u003csub\u003e2\u003c/sub\u003e:\u003csub\u003e3\u003c/sub\u003e and 204 RIL families were used, and parental line genome sequences were used as references. Six GS models, including parametric (G-BLUP, BayesB, Bayes_LASSO) and non-parametric (Random Forest, SVM Linear, SVM Radial) methods, were tested. G-BLUP and Random Forest outperformed the other models, with correlations of 0.48 in the F\u003csub\u003e2:3\u003c/sub\u003e and 0.68 in the RIL populations, highlighting the GP efficacy in early-stage breeding for improving \u003cem\u003eFon\u003c/em\u003e race 2-resistance in elite watermelon cultivars.\u003c/p\u003e","manuscriptTitle":"Comparative Genomic Prediction of Resistance to Fusarium Wilt (Fusariumoxysporum f. sp. niveum race 2) in Watermelon: Insights from Parametric and Machine Learning Approaches","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-06 09:37:49","doi":"10.21203/rs.3.rs-4877259/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2024-10-24T01:21:49+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-08-14T13:54:12+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-11T05:04:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-08T07:27:16+00:00","index":"","fulltext":""},{"type":"submitted","content":"Theoretical and Applied Genetics","date":"2024-08-07T20:20:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"theoretical-and-applied-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"taag","sideBox":"Learn more about [Theoretical and Applied Genetics](https://www.springer.com/journal/122)","snPcode":"122","submissionUrl":"https://submission.nature.com/new-submission/122/3","title":"Theoretical and Applied Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ce8148e9-d64d-44ee-92e7-971e5c3d1d6c","owner":[],"postedDate":"September 6th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-27T16:08:07+00:00","versionOfRecord":{"articleIdentity":"rs-4877259","link":"https://doi.org/10.1007/s00122-024-04813-8","journal":{"identity":"theoretical-and-applied-genetics","isVorOnly":false,"title":"Theoretical and Applied Genetics"},"publishedOn":"2025-01-24 15:57:19","publishedOnDateReadable":"January 24th, 2025"},"versionCreatedAt":"2024-09-06 09:37:49","video":"","vorDoi":"10.1007/s00122-024-04813-8","vorDoiUrl":"https://doi.org/10.1007/s00122-024-04813-8","workflowStages":[]},"version":"v1","identity":"rs-4877259","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4877259","identity":"rs-4877259","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}