Viral Phylogenomics Using an Alignment-Free Method: A Three-Step Approach to Determine Optimal Length of k-mer.
Identifieur interne : 000E11 ( PubMed/Curation ); précédent : 000E10; suivant : 000E12Viral Phylogenomics Using an Alignment-Free Method: A Three-Step Approach to Determine Optimal Length of k-mer.
Auteurs : Qian Zhang [États-Unis] ; Se-Ran Jun [États-Unis] ; Michael Leuze [États-Unis] ; David Ussery [États-Unis] ; Intawat Nookaew [États-Unis]Source :
- Scientific reports [ 2045-2322 ] ; 2017.
Descripteurs français
- KwdFr :
- MESH :
- génétique : Virus.
- Bases de données génétiques, Biologie informatique, Génome viral, Génomique, Phylogénie, Taille du génome, Virus.
English descriptors
- KwdEn :
- MESH :
- classification : Viruses.
- genetics : Viruses.
- methods : Genomics.
- Computational Biology, Databases, Genetic, Genome Size, Genome, Viral, Phylogeny, Whole Genome Sequencing.
Abstract
The development of rapid, economical genome sequencing has shed new light on the classification of viruses. As of October 2016, the National Center for Biotechnology Information (NCBI) database contained >2 million viral genome sequences and a reference set of ~4000 viral genome sequences that cover a wide range of known viral families. Whole-genome sequences can be used to improve viral classification and provide insight into the viral "tree of life". However, due to the lack of evolutionary conservation amongst diverse viruses, it is not feasible to build a viral tree of life using traditional phylogenetic methods based on conserved proteins. In this study, we used an alignment-free method that uses k-mers as genomic features for a large-scale comparison of complete viral genomes available in RefSeq. To determine the optimal feature length, k (an essential step in constructing a meaningful dendrogram), we designed a comprehensive strategy that combines three approaches: (1) cumulative relative entropy, (2) average number of common features among genomes, and (3) the Shannon diversity index. This strategy was used to determine k for all 3,905 complete viral genomes in RefSeq. The resulting dendrogram shows consistency with the viral taxonomy of the ICTV and the Baltimore classification of viruses.
DOI: 10.1038/srep40712
PubMed: 28102365
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type="state">Tennessee</region></placeName><wicri:cityArea>Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory Oak Ridge</wicri:cityArea></affiliation></author></analytic><series><title level="j">Scientific reports</title><idno type="eISSN">2045-2322</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Computational Biology</term><term>Databases, Genetic</term><term>Genome Size</term><term>Genome, Viral</term><term>Genomics (methods)</term><term>Phylogeny</term><term>Viruses (classification)</term><term>Viruses (genetics)</term><term>Whole Genome Sequencing</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Bases de données génétiques</term><term>Biologie informatique</term><term>Génome viral</term><term>Génomique ()</term><term>Phylogénie</term><term>Taille du génome</term><term>Virus ()</term><term>Virus 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new light on the classification of viruses. As of October 2016, the National Center for Biotechnology Information (NCBI) database contained >2 million viral genome sequences and a reference set of ~4000 viral genome sequences that cover a wide range of known viral families. Whole-genome sequences can be used to improve viral classification and provide insight into the viral "tree of life". However, due to the lack of evolutionary conservation amongst diverse viruses, it is not feasible to build a viral tree of life using traditional phylogenetic methods based on conserved proteins. In this study, we used an alignment-free method that uses k-mers as genomic features for a large-scale comparison of complete viral genomes available in RefSeq. To determine the optimal feature length, k (an essential step in constructing a meaningful dendrogram), we designed a comprehensive strategy that combines three approaches: (1) cumulative relative entropy, (2) average number of common features among genomes, and (3) the Shannon diversity index. This strategy was used to determine k for all 3,905 complete viral genomes in RefSeq. The resulting dendrogram shows consistency with the viral taxonomy of the ICTV and the Baltimore classification of viruses.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">28102365</PMID><DateCompleted><Year>2018</Year><Month>10</Month><Day>18</Day></DateCompleted><DateRevised><Year>2020</Year><Month>03</Month><Day>25</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">2045-2322</ISSN><JournalIssue CitedMedium="Internet"><Volume>7</Volume><PubDate><Year>2017</Year><Month>01</Month><Day>19</Day></PubDate></JournalIssue><Title>Scientific reports</Title><ISOAbbreviation>Sci Rep</ISOAbbreviation></Journal><ArticleTitle>Viral Phylogenomics Using an Alignment-Free Method: A Three-Step Approach to Determine Optimal Length of k-mer.</ArticleTitle><Pagination><MedlinePgn>40712</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1038/srep40712</ELocationID><Abstract><AbstractText>The development of rapid, economical genome sequencing has shed new light on the classification of viruses. As of October 2016, the National Center for Biotechnology Information (NCBI) database contained >2 million viral genome sequences and a reference set of ~4000 viral genome sequences that cover a wide range of known viral families. Whole-genome sequences can be used to improve viral classification and provide insight into the viral "tree of life". However, due to the lack of evolutionary conservation amongst diverse viruses, it is not feasible to build a viral tree of life using traditional phylogenetic methods based on conserved proteins. In this study, we used an alignment-free method that uses k-mers as genomic features for a large-scale comparison of complete viral genomes available in RefSeq. To determine the optimal feature length, k (an essential step in constructing a meaningful dendrogram), we designed a comprehensive strategy that combines three approaches: (1) cumulative relative entropy, (2) average number of common features among genomes, and (3) the Shannon diversity index. This strategy was used to determine k for all 3,905 complete viral genomes in RefSeq. The resulting dendrogram shows consistency with the viral taxonomy of the ICTV and the Baltimore classification of viruses.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Qian</ForeName><Initials>Q</Initials><AffiliationInfo><Affiliation>UT-ORNL Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN 37996, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory Oak Ridge, TN 37831 USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jun</LastName><ForeName>Se-Ran</ForeName><Initials>SR</Initials><AffiliationInfo><Affiliation>Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory Oak Ridge, TN 37831 USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Leuze</LastName><ForeName>Michael</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Joint Institute for Computational Sciences, University of Tennessee, Knoxville, TN 37831, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Computational Biomolecular Modeling and Bioinformatics Group, Computer Science and Mathematics Division, Oak Ridge National Laboratories, Oak Ridge, TN 37831, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ussery</LastName><ForeName>David</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Comparative Genomics Group, Biosciences Division, Oak Ridge National Laboratory Oak Ridge, TN 37831 USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Biomedical Informatics, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR 72205, 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