A revised genome annotation of the model cyanobacterium Synechocystis based on start and stop codon-enriched ribosome profiling and proteogenomics
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A revised genome annotation of the model cyanobacterium Synechocystis based on start and stop codon-enriched ribosome profiling and proteogenomics | Research Square 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Article A revised genome annotation of the model cyanobacterium Synechocystis based on start and stop codon-enriched ribosome profiling and proteogenomics Wolfgang Hess, Vanessa Krauspe, Viktoria Reimann, Paul Minges, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8767029/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 Cyanobacteria are important primary producers and are used in biotechnology as microbial cell factories due to their ability to use solar light for oxygenic photosynthesis. Synechocystis sp. PCC 6803 is a popular model cyanobacterium, yet there are ambiguities in the precise coding regions of many genes, and numerous genes encoding small proteins have remained undetected. Here we present the results of a ribosome profiling (Ribo-seq) analysis involving inhibitors that stall ribosomes at translation initiation and termination sites (TIS- and TTS-Ribo-seq), combined with a proteogenomic reevaluation and reannotation of its entire genome. We report evidence for the translation of 3,050 annotated genes based on proteogenomics (83%), of 3,492 based on Ribo-seq (95.2%), and of 3,009 supported by both methods (82%). The data suggested both novel protein-coding genes and corrections for annotated ones. We validated 15 novel small proteins translated from antisense RNAs, from intergenic and intragenic regions and identified 69 novel, mostly small proteins based on proteogenomics. With slr0489, slr1079 and slr1082 we identified three genes with ~300 nt long intragenic out-of-frame coding regions and show that both the internal and host reading frames are translated. The resulting proteins interact with each other, resembling certain defense or toxin-antitoxin systems. Our data illustrate the enormous value of consolidating genome annotations in the context of integrated experimental data and suggest that genome annotations in general need to be extended and revised. All of our data can be accessed via an intuitive and interactive genome browser platform at https://www.bioinf.uni-freiburg.de/~ribobase/ . Biological sciences/Microbiology/Microbial genetics/Bacterial genes Biological sciences/Genetics/Genomics Biological sciences/Biochemistry/Proteomics Biological sciences/Molecular biology/Translation/Ribosome Full Text Additional Declarations There is NO Competing Interest. Supplementary Files ReviewerlinkstoData.docx Reviewer links to Data TableS1S319122025.xlsx Supplementary Dataset 1 SupplRiboSeq19012026aa.pdf Supplementary Information SupportingtablesS6919122025.xlsx Supplementary Dataset 2 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 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
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