Genetic diversity analysis of industrial Saccharomyces cerevisiae strains

Genetic diversity analysis of industrial Saccharomyces cerevisiae strains | 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 Genetic diversity analysis of industrial Saccharomyces cerevisiae strains Liping Lei, Qiuli Bin, Changhua Yu, Xuemei Qin, Renzhi Wu, Shuwei Cao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8514431/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Sugarcane molasses serves as a vital non-food feedstock for ethanol fermentation, and its efficient utilisation depends on breeding of excellent microbial strains. Therefore, identification of industrial strains for ethanol fermentation are central to improving fermentation efficiency. To identify high-efficiency ethanol-fermenting strains, we developed a method for preparing high-throughput polymerase chain reaction (PCR) templates within 3 min using seven industrial Saccharomyces cerevisiae strains, integrating single-cell morphology and phenotypic variations in ethanol fermentation. Method specificity was confirmed by amplifying and sequencing the internal transcribed spacer region, and the efficiency was validated by extracting genomic DNA using cetyltrimethylammonium bromide. Subsequent genetic diversity analysis using random amplified polymorphic DNA (RAPD) with eight effective primers screened from twenty-two random primers revealed genetic similarity coefficients ranging between 0.47–0.96. The high-yield strains 1015-04-01 and 1002-03-03 showed the highest similarity (0.96), whereas strain 1015-04-01 and the low-yield strain 1415 exhibited the lowest similarity (0.47). Unweighted pair group method with arithmetic mean cluster analysis demonstrated that the high-yield strain 1016-02-04, and strains 1415 and 1313 formed a major cluster, and the low-yield strains 1415 and 1313 formed a distinct subcluster; four other high-yield strains constituted a separate cluster, indicating significant genetic differentiation between the high- and low-yield strains. The RAPD results showed substantial concordance with variations in ethanol yield and single-cell morphological differences, providing a molecular basis for rapid identification, breeding, and development of high-performance strains for sugarcane molasse-based ethanol fermentation. Yeast ethanol fermentation RAPD genetic diversity Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 26 Feb, 2026 Reviews received at journal 23 Feb, 2026 Reviews received at journal 11 Feb, 2026 Reviewers agreed at journal 03 Feb, 2026 Reviewers agreed at journal 30 Jan, 2026 Reviewers invited by journal 28 Jan, 2026 Editor assigned by journal 05 Jan, 2026 Submission checks completed at journal 05 Jan, 2026 First submitted to journal 04 Jan, 2026 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. 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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-8514431","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":581926718,"identity":"13796ff8-1229-40a1-89e4-a000f90bffc9","order_by":0,"name":"Liping Lei","email":"","orcid":"","institution":"Guangxi Minzu University","correspondingAuthor":false,"prefix":"","firstName":"Liping","middleName":"","lastName":"Lei","suffix":""},{"id":581926719,"identity":"e975cb6c-7f15-4250-acf2-286001903f56","order_by":1,"name":"Qiuli Bin","email":"","orcid":"","institution":"Guangxi Minzu 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