Decoding the constraints acting on a coastal fish using landscape transcriptomics

Decoding the constraints acting on a coastal fish using landscape transcriptomics | 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 Decoding the constraints acting on a coastal fish using landscape transcriptomics Emma Gairin, Saori Miura, Zoé Chamot, Camille Sautereau, Jann Zwahlen, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7230643/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Understanding how wild organisms respond to complex mixtures of environmental stressors remains a major challenge in ecology1,2. To move beyond laboratory-based studies of the effect of individual stressors on model species, landscape transcriptomics – the study of how genome-wide expression patterns reveal environmental conditions – has been suggested3. Here, we apply landscape transcriptomics to the damselfish Chrysiptera cyanea, a sentinel species from Okinawa’s coastal ecosystems, by sampling juveniles and adults across 18 sites from natural to urbanized habitats. We uncover a striking molecular signature of urbanization: fish from human-impacted sites exhibit elevated expression of genes involved in inflammation and immune responses. Remarkably, their transcriptomes resemble those of overfed individuals from laboratory feeding experiments – suggesting that urban reefs act as “fast food” environments, offering energy-rich diets while imposing chronic stress. This pattern is illustrated by the altered expression of key genes in metabolic and stress pathways (e.g., downregulation of ppargc1a and insrb, indicative of dietary intake surplus and insulin resistance; upregulation of interleukins, chemokines, toll-like receptors and caspase linked to the immune response and inflammation). Our results demonstrate that wild transcriptomes capture the invisible biological costs of environmental degradation, positioning fish as living biosensors for coastal ecosystem health. Biological sciences/Ecology/Ecological genetics Earth and environmental sciences/Environmental sciences/Environmental impact Landscape transcriptomics Coastal fish Nursery Damselfish Environmental monitoring Full Text Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Under Review 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. 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-7230643","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":500629942,"identity":"be1fe635-2ed6-4bee-ae06-8032156ba64b","order_by":0,"name":"Emma 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