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      ZOVER: the database of zoonotic and vector-borne viruses

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          Abstract

          Emerging infectious diseases significantly threaten global public health and socioeconomic security. The majority of emerging infectious disease outbreaks are caused by zoonotic/vector-borne viruses. Bats and rodents are the two most important reservoir hosts of many zoonotic viruses that can cross species barriers to infect humans, whereas mosquitos and ticks are well-established major vectors of many arboviral diseases. Moreover, some emerging zoonotic diseases require a vector to spread or are intrinsically vector-borne and zoonotically transmitted. In this study, we present a newly upgraded database of zoonotic and vector-borne viruses designated ZOVER ( http://www.mgc.ac.cn/ZOVER). It incorporates two previously released databases, DBatVir and DRodVir, for bat- and rodent-associated viruses, respectively, and further collects up-to-date knowledge on mosquito- and tick-associated viruses to establish a comprehensive online resource for zoonotic and vector-borne viruses. Additionally, it integrates a set of online visualization tools for convenient comparative analyses to facilitate the discovery of potential patterns of virome diversity and ecological characteristics between/within different viral hosts/vectors. The ZOVER database will be a valuable resource for virologists, zoologists and epidemiologists to better understand the diversity and dynamics of zoonotic and vector-borne viruses and conduct effective surveillance to monitor potential interspecies spillover for efficient prevention and control of future emerging zoonotic diseases.

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          Most cited references24

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          A pneumonia outbreak associated with a new coronavirus of probable bat origin

          Since the outbreak of severe acute respiratory syndrome (SARS) 18 years ago, a large number of SARS-related coronaviruses (SARSr-CoVs) have been discovered in their natural reservoir host, bats 1–4 . Previous studies have shown that some bat SARSr-CoVs have the potential to infect humans 5–7 . Here we report the identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China. The epidemic, which started on 12 December 2019, had caused 2,794 laboratory-confirmed infections including 80 deaths by 26 January 2020. Full-length genome sequences were obtained from five patients at an early stage of the outbreak. The sequences are almost identical and share 79.6% sequence identity to SARS-CoV. Furthermore, we show that 2019-nCoV is 96% identical at the whole-genome level to a bat coronavirus. Pairwise protein sequence analysis of seven conserved non-structural proteins domains show that this virus belongs to the species of SARSr-CoV. In addition, 2019-nCoV virus isolated from the bronchoalveolar lavage fluid of a critically ill patient could be neutralized by sera from several patients. Notably, we confirmed that 2019-nCoV uses the same cell entry receptor—angiotensin converting enzyme II (ACE2)—as SARS-CoV.
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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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              Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

              S Altschul (1997)
              The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                07 January 2022
                11 October 2021
                11 October 2021
                : 50
                : D1
                : D943-D949
                Affiliations
                NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College , Beijing, P.R. China
                NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College , Beijing, P.R. China
                NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College , Beijing, P.R. China
                NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College , Beijing, P.R. China
                NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College , Beijing, P.R. China
                NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College , Beijing, P.R. China
                NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College , Beijing, P.R. China
                Author notes
                To whom correspondence should be addressed. Tel: +86 10 6787 5146; Email: chenlh@ 123456ipbcams.ac.cn
                Correspondence may also be addressed to Jian Yang. Email: yangj@ 123456ipbcams.ac.cn
                Correspondence may also be addressed to Zhiqiang Wu. Email: wuzq2009@ 123456ipbcams.ac.cn

                The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

                Author information
                https://orcid.org/0000-0002-8826-5198
                Article
                gkab862
                10.1093/nar/gkab862
                8728136
                34634795
                19ac7bea-35bb-45e0-843d-f6e62a03307c
                © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 16 September 2021
                : 08 September 2021
                : 15 August 2021
                Page count
                Pages: 7
                Funding
                Funded by: CAMS Innovation Fund for Medical Sciences;
                Award ID: 2020-I2M-2-001
                Funded by: Beijing Natural Science Foundation, DOI 10.13039/501100004826;
                Award ID: M21002
                Funded by: Non-profit Central Research Institute Fund of CAMS;
                Award ID: 2019PT310029
                Categories
                AcademicSubjects/SCI00010
                Database Issue

                Genetics
                Genetics

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