Comparative Transcriptomics of Floral Transition in Arabidopsis thalianaand Ortholog Prediction in Salvia hispanica

Comparative Transcriptomics of Floral Transition in Arabidopsis thalianaand Ortholog Prediction in Salvia hispanica | 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 Transcriptomics of Floral Transition in Arabidopsis thaliana and Ortholog Prediction in Salvia hispanica Saad Khan, Juan Philppe Teixeira, Miklos Maximiliano Bajay This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9066517/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 The transition from vegetative growth to reproductive development is a critical phase in the plant life cycle, shaping reproductive success and yield through coordinated responses to internal cues and environmental signals. Here, we integrated comparative transcriptomics and unsupervised machine learning to analyze time-series RNA-seq data from Arabidopsis thaliana and to prioritize flowering-time regulators in Salvia hispanica (chia). K-means clustering of Arabidopsis expression profiles recovered clusters enriched in transposable elements (e.g., AT5G28627) and pseudogenes (e.g., AT2G24110) that peaked during the flowering transition (M4–M6), suggesting participation in flowering-associated regulatory programs. Temperature-stratified profiles (Col10, Col16, Col23, Col27) revealed condition-dependent dynamics among canonical flowering regulators. Using cross-species expression correlation, we identified three high-confidence chia candidates for key Arabidopsis flowering genes (FT, FLC, and SOC1), with Pearson correlation coefficients ranging from 0.9943 to 0.9992. Together, these results provide a data-driven shortlist of candidate flowering-time regulators in chia and a reusable computational framework for transferring flowering knowledge from model to non-model plants. Bioinformatics Comparative transcriptomics flowering time Arabidopsis thaliana Salvia hispanica machine learning bioinformatics Full Text Additional Declarations The authors declare no competing interests. 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. 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-9066517","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":602694844,"identity":"9664ad18-766d-49d2-b593-bd9fd45ac437","order_by":0,"name":"Saad Khan","email":"","orcid":"","institution":"Centre for Omic Sciences, Islamia College Peshawar, Pakistan","correspondingAuthor":false,"prefix":"","firstName":"Saad","middleName":"","lastName":"Khan","suffix":""},{"id":602694845,"identity":"7ec7546c-395b-4847-b0f6-527168c9e5b6","order_by":1,"name":"Juan Philppe 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