Toward a method for tracking virus evolutionary trajectory applied to the pandemic H1N1 2009 influenza virus.
Identifieur interne : 000783 ( PubMed/Corpus ); précédent : 000782; suivant : 000784Toward a method for tracking virus evolutionary trajectory applied to the pandemic H1N1 2009 influenza virus.
Auteurs : R Burke Squires ; Brett E. Pickett ; Sajal Das ; Richard H. ScheuermannSource :
- Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases [ 1567-7257 ] ; 2014.
English descriptors
- KwdEn :
- Base Sequence, Computational Biology (methods), Databases, Genetic, Evolution, Molecular, Humans, Influenza A Virus, H1N1 Subtype (classification), Influenza A Virus, H1N1 Subtype (genetics), Influenza, Human (epidemiology), Influenza, Human (transmission), Influenza, Human (virology), Molecular Sequence Data, Pandemics, Phylogeny, RNA, Viral (analysis), RNA, Viral (genetics), Sequence Alignment, Sequence Analysis, RNA.
- MESH :
- chemical , analysis : RNA, Viral.
- classification : Influenza A Virus, H1N1 Subtype.
- epidemiology : Influenza, Human.
- genetics : Influenza A Virus, H1N1 Subtype, RNA, Viral.
- methods : Computational Biology.
- transmission : Influenza, Human.
- virology : Influenza, Human.
- Base Sequence, Databases, Genetic, Evolution, Molecular, Humans, Molecular Sequence Data, Pandemics, Phylogeny, Sequence Alignment, Sequence Analysis, RNA.
Abstract
In 2009 a novel pandemic H1N1 influenza virus (H1N1pdm09) emerged as the first official influenza pandemic of the 21st century. Early genomic sequence analysis pointed to the swine origin of the virus. Here we report a novel computational approach to determine the evolutionary trajectory of viral sequences that uses data-driven estimations of nucleotide substitution rates to track the gradual accumulation of observed sequence alterations over time. Phylogenetic analysis and multiple sequence alignments show that sequences belonging to the resulting evolutionary trajectory of the H1N1pdm09 lineage exhibit a gradual accumulation of sequence variations and tight temporal correlations in the topological structure of the phylogenetic trees. These results suggest that our evolutionary trajectory analysis (ETA) can more effectively pinpoint the evolutionary history of viruses, including the host and geographical location traversed by each segment, when compared against either BLAST or traditional phylogenetic analysis alone.
DOI: 10.1016/j.meegid.2014.07.015
PubMed: 25064525
Links to Exploration step
pubmed:25064525Le document en format XML
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Craig Venter Institute (JCVI), La Jolla, CA, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Das, Sajal" sort="Das, Sajal" uniqKey="Das S" first="Sajal" last="Das">Sajal Das</name><affiliation><nlm:affiliation>Department of Computer Science, Missouri University of Science and Technology, Rolla, MO, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Scheuermann, Richard H" sort="Scheuermann, Richard H" uniqKey="Scheuermann R" first="Richard H" last="Scheuermann">Richard H. Scheuermann</name><affiliation><nlm:affiliation>Informatics, J. 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Electronic address: richard.squires@nih.gov.</nlm:affiliation></affiliation></author><author><name sortKey="Pickett, Brett E" sort="Pickett, Brett E" uniqKey="Pickett B" first="Brett E" last="Pickett">Brett E. Pickett</name><affiliation><nlm:affiliation>Informatics, J. Craig Venter Institute (JCVI), La Jolla, CA, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Das, Sajal" sort="Das, Sajal" uniqKey="Das S" first="Sajal" last="Das">Sajal Das</name><affiliation><nlm:affiliation>Department of Computer Science, Missouri University of Science and Technology, Rolla, MO, USA.</nlm:affiliation></affiliation></author><author><name sortKey="Scheuermann, Richard H" sort="Scheuermann, Richard H" uniqKey="Scheuermann R" first="Richard H" last="Scheuermann">Richard H. Scheuermann</name><affiliation><nlm:affiliation>Informatics, J. Craig Venter Institute (JCVI), La Jolla, CA, USA; Department of Pathology, University of California San Diego, San Diego, CA, USA.</nlm:affiliation></affiliation></author></analytic><series><title level="j">Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases</title><idno type="eISSN">1567-7257</idno><imprint><date when="2014" type="published">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Base Sequence</term><term>Computational Biology (methods)</term><term>Databases, Genetic</term><term>Evolution, Molecular</term><term>Humans</term><term>Influenza A Virus, H1N1 Subtype (classification)</term><term>Influenza A Virus, H1N1 Subtype (genetics)</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (transmission)</term><term>Influenza, Human (virology)</term><term>Molecular Sequence Data</term><term>Pandemics</term><term>Phylogeny</term><term>RNA, Viral (analysis)</term><term>RNA, Viral (genetics)</term><term>Sequence Alignment</term><term>Sequence Analysis, RNA</term></keywords><keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>RNA, Viral</term></keywords><keywords scheme="MESH" qualifier="classification" xml:lang="en"><term>Influenza A Virus, H1N1 Subtype</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Influenza A Virus, H1N1 Subtype</term><term>RNA, Viral</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Base Sequence</term><term>Databases, Genetic</term><term>Evolution, Molecular</term><term>Humans</term><term>Molecular Sequence Data</term><term>Pandemics</term><term>Phylogeny</term><term>Sequence Alignment</term><term>Sequence Analysis, RNA</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In 2009 a novel pandemic H1N1 influenza virus (H1N1pdm09) emerged as the first official influenza pandemic of the 21st century. Early genomic sequence analysis pointed to the swine origin of the virus. Here we report a novel computational approach to determine the evolutionary trajectory of viral sequences that uses data-driven estimations of nucleotide substitution rates to track the gradual accumulation of observed sequence alterations over time. Phylogenetic analysis and multiple sequence alignments show that sequences belonging to the resulting evolutionary trajectory of the H1N1pdm09 lineage exhibit a gradual accumulation of sequence variations and tight temporal correlations in the topological structure of the phylogenetic trees. These results suggest that our evolutionary trajectory analysis (ETA) can more effectively pinpoint the evolutionary history of viruses, including the host and geographical location traversed by each segment, when compared against either BLAST or traditional phylogenetic analysis alone. </div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">25064525</PMID><DateCompleted><Year>2015</Year><Month>08</Month><Day>31</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1567-7257</ISSN><JournalIssue CitedMedium="Internet"><Volume>28</Volume><PubDate><Year>2014</Year><Month>Dec</Month></PubDate></JournalIssue><Title>Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases</Title><ISOAbbreviation>Infect. Genet. Evol.</ISOAbbreviation></Journal><ArticleTitle>Toward a method for tracking virus evolutionary trajectory applied to the pandemic H1N1 2009 influenza virus.</ArticleTitle><Pagination><MedlinePgn>351-7</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.meegid.2014.07.015</ELocationID><ELocationID EIdType="pii" ValidYN="Y">S1567-1348(14)00244-5</ELocationID><Abstract><AbstractText>In 2009 a novel pandemic H1N1 influenza virus (H1N1pdm09) emerged as the first official influenza pandemic of the 21st century. Early genomic sequence analysis pointed to the swine origin of the virus. Here we report a novel computational approach to determine the evolutionary trajectory of viral sequences that uses data-driven estimations of nucleotide substitution rates to track the gradual accumulation of observed sequence alterations over time. Phylogenetic analysis and multiple sequence alignments show that sequences belonging to the resulting evolutionary trajectory of the H1N1pdm09 lineage exhibit a gradual accumulation of sequence variations and tight temporal correlations in the topological structure of the phylogenetic trees. These results suggest that our evolutionary trajectory analysis (ETA) can more effectively pinpoint the evolutionary history of viruses, including the host and geographical location traversed by each segment, when compared against either BLAST or traditional phylogenetic analysis alone. </AbstractText><CopyrightInformation>Copyright © 2014 Elsevier B.V. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Squires</LastName><ForeName>R Burke</ForeName><Initials>RB</Initials><AffiliationInfo><Affiliation>Bioinformatics and Computational Biosciences Branch, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA. Electronic address: richard.squires@nih.gov.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Pickett</LastName><ForeName>Brett E</ForeName><Initials>BE</Initials><AffiliationInfo><Affiliation>Informatics, J. Craig Venter Institute (JCVI), La Jolla, CA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Das</LastName><ForeName>Sajal</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Department of Computer Science, Missouri University of Science and Technology, Rolla, MO, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Scheuermann</LastName><ForeName>Richard H</ForeName><Initials>RH</Initials><AffiliationInfo><Affiliation>Informatics, J. 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