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dc.contributor.authorKawasaki, Junnaen
dc.contributor.authorKojima, Shoheien
dc.contributor.authorTomonaga, Keizoen
dc.contributor.authorHorie, Masayukien
dc.contributor.alternative川崎, 純菜ja
dc.contributor.alternative小嶋, 将平ja
dc.contributor.alternative朝長, 啓造ja
dc.contributor.alternative堀江, 真行ja
dc.date.accessioned2022-06-17T08:27:09Z-
dc.date.available2022-06-17T08:27:09Z-
dc.date.issued2021-08-31-
dc.identifier.urihttp://hdl.handle.net/2433/274459-
dc.description.abstractRNA viruses cause numerous emerging diseases, mostly due to transmission from mammalian and avian reservoirs. Large-scale surveillance of RNA viral infections in these animals is a fundamental step for controlling viral infectious diseases. Metagenomic analysis is a powerful method for virus identification with low bias and has contributed substantially to the discovery of novel viruses. Deep-sequencing data have been collected from diverse animals and accumulated in public databases, which can be valuable resources for identifying unknown viral sequences. Here, we screened for infections of 33 RNA viral families in publicly available mammalian and avian sequencing data and found approximately 900 hidden viral infections. We also discovered six nearly complete viral genomes in livestock, wild, and experimental animals: hepatovirus in a goat, hepeviruses in blind mole-rats and a galago, astrovirus in macaque monkeys, parechovirus in a cow, and pegivirus in tree shrews. Some of these viruses were phylogenetically close to human-pathogenic viruses, suggesting the potential risk of causing disease in humans upon infection. Furthermore, infections of five novel viruses were identified in several different individuals, indicating that their infections may have already spread in the natural host population. Our findings demonstrate the reusability of public sequencing data for surveying viral infections and identifying novel viral sequences, presenting a warning about a new threat of viral infectious disease to public health. IMPORTANCE Monitoring the spread of viral infections and identifying novel viruses capable of infecting humans through animal reservoirs are necessary to control emerging viral diseases. Massive amounts of sequencing data collected from various animals are publicly available, and these data may contain sequences originating from a wide variety of viruses. Here, we analyzed more than 46, 000 public sequencing data and identified approximately 900 hidden RNA viral infections in mammalian and avian samples. Some viruses discovered in this study were genetically similar to pathogens that cause hepatitis, diarrhea, or encephalitis in humans, suggesting the presence of new threats to public health. Our study demonstrates the effectiveness of reusing public sequencing data to identify known and unknown viral infections, indicating that future continuous monitoring of public sequencing data by metagenomic analyses would help prepare and mitigate future viral pandemics.en
dc.language.isoeng-
dc.publisherAmerican Society for Microbiologyen
dc.rights© 2021 Kawasaki et al.en
dc.rightsThis is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectRNA virusen
dc.subjectbioinformaticsen
dc.subjectmolecular epidemiologyen
dc.subjectpublic healthen
dc.subjectvirus diversityen
dc.subjectzoonosisen
dc.titleHidden Viral Sequences in Public Sequencing Data and Warning for Future Emerging Diseasesen
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.jtitlemBioen
dc.identifier.volume12-
dc.identifier.issue4-
dc.relation.doi10.1128/mBio.01638-21-
dc.textversionpublisher-
dc.identifier.artnume01638-21-
dc.identifier.pmid34399612-
dcterms.accessRightsopen access-
datacite.awardNumber19J22241-
datacite.awardNumber19K22530-
datacite.awardNumber20H05682-
datacite.awardNumber18K19443-
datacite.awardNumber21H01199-
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datacite.awardNumber16H06430-
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datacite.awardNumber19H04833-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-19J22241/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-19K22530/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-20H05682/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-18K19443/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-21H01199/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-ORGANIZER-16H06429/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-INTERNATIONAL-16K21723/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PLANNED-16H06430/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PUBLICLY-17H05821/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/grant/KAKENHI-PUBLICLY-19H04833/-
dc.identifier.pissn2161-2129-
dc.identifier.eissn2150-7511-
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.awardTitle内在性ウイルス様配列(EVE)に由来する機能性配列についての体系的解析ja
jpcoar.awardTitle中枢神経系疾患の遺伝子治療を加速させる自己編集型RNAウイルスベクターの開発ja
jpcoar.awardTitleゲノム免疫:内在性ウイルスの抗ウイルス活性の動作原理解明と機能資源としての確保ja
jpcoar.awardTitleボルナウイルス感染細胞の運命:ウイルスの新たな神経病原性を探るja
jpcoar.awardTitle真核生物におけるモノネガウイルスの感染史の解明ja
jpcoar.awardTitleネオウイルス学:生命の源流から超個体、そしてエコ・スフィアーへja
jpcoar.awardTitle「ネオウイルス学」の国際活動支援ja
jpcoar.awardTitle内在性RNAウイルスの網羅的検索と機能解析ja
jpcoar.awardTitle南極コケ坊主におけるウイルス叢の解明とウイルス化石の探索への応用ja
jpcoar.awardTitleウイルスと内在性ウイルス様エレメントの探索による現代と太古のウイルス多様性の理解ja
出現コレクション:学術雑誌掲載論文等

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