WITHDRAWN: Cattle breed used in single-cell RNA-Seq impacts fiber-type proportions from deconvolution analyses of muscle RNA-Seq: A comparison of software tools

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Abstract Bulk RNA sequencing offers a comprehensive view of global transcriptomes but lacks cell-type specificity. Single-cell RNA sequencing (scRNA-seq) overcomes this limitation by providing detailed insights at the individual cell level, though it incurs higher costs. Deconvolution methods can estimate cell-type proportions in bulk RNA-seq data, but their results may vary based on the scRNA-seq reference data and software used. This study investigates the estimation of muscle fiber type proportions through deconvolution analysis of Longissimus dorsi muscle bulk RNA-seq data from late gestation Holstein Friesian multiparous cows. Four software tools (i.e., CIBERSORTx, Cellanneal, DeconvR-NNLS, and DeconvR-RLM) were compared using scRNA-seq reference data from Brahman and Wagyu cattle breeds, which included proportions of types I, IIA, and IIX myofibers. Deconvolution results were benchmarked against histological classifications of muscle fiber types in Holstein cattle. Kruskal-Wallis and Dunn's tests revealed that the breed of reference data influenced the proportions of type IIA and IIX muscle fibers. Fiber-type distributions calculated using CIBERSORTx and DeconvR-RLM with Brahman reference data closely matched histological classifications. The study highlights the potential of deconvolution analysis for estimating muscle fiber-type distribution in cattle and emphasizes the impact of reference data breed and software tools on the results.
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WITHDRAWN: Cattle breed used in single-cell RNA-Seq impacts fiber-type proportions from deconvolution analyses of muscle RNA-Seq: A comparison of software tools | 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 Article WITHDRAWN: Cattle breed used in single-cell RNA-Seq impacts fiber-type proportions from deconvolution analyses of muscle RNA-Seq: A comparison of software tools Raphael P. Moreira, Marcelo R. Vicari, Henrique A. Mulim, Theresa M. Casey, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6207260/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Editorial Note The full text of this preprint has been withdrawn, as it was submitted in error. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author. Editorial notes are used to provide important context regarding the topic of a preprint or to alert readers to potential issues concerning that preprint or a downstream publication associated with it. For more information on editorial notes, see our Editorial Policies . Abstract The full text of this preprint has been withdrawn, as it was submitted in error. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author. Biological sciences/Genetics/Animal breeding Biological sciences/Genetics/Gene expression Full Text The authors have withdrawn this preprint from Research Square. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions 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-6207260","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":445759771,"identity":"d1d448dc-bfe7-4fe6-8f33-c76da8d13406","order_by":0,"name":"Raphael P. Moreira","email":"","orcid":"","institution":"Federal University of Paraná","correspondingAuthor":false,"prefix":"","firstName":"Raphael","middleName":"P.","lastName":"Moreira","suffix":""},{"id":445759772,"identity":"42415cf0-7b7d-4b23-99d9-06456d1ee70e","order_by":1,"name":"Marcelo R. 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