Genomic analysis of influenza A viruses, including avian Flu (H5N1) strains
Identifieur interne : 001592 ( Main/Merge ); précédent : 001591; suivant : 001593Genomic analysis of influenza A viruses, including avian Flu (H5N1) strains
Auteurs : Insung Ahn [Corée du Sud] ; Byeong-Jin Jeone [Corée du Sud] ; Se-Eun Bae [Corée du Sud] ; Jin Jung [Corée du Sud] ; Hveon S. Son [Corée du Sud]Source :
- European journal of epidemiology [ 0393-2990 ] ; 2006.
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- Pascal (Inist)
- Wicri :
- topic : Santé publique.
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Abstract
This study was designed to conduct genomic analysis in two steps, such as the overall relative synonymous codon usage (RSCU) analysis of the five virus species in the orthomyxoviridae family, and more intensive pattern analysis of the four subtypes of influenza A virus (H1N1, H2N2, H3N2, and H5N1) which were isolated from human population. All the subtypes were categorized by their isolated regions, including Asia, Europe, and Africa, and most of the synonymous codon usage patterns were analyzed by correspondence analysis (CA). As a result, influenza A virus showed the lowest synonymous codon usage bias among the virus species of the orthomyxoviridae family, and influenza B and influenza C virus were followed, while suggesting that influenza A virus might have an advantage in transmitting across the species barrier due to their low codon usage bias. The ENC values of the host-specific HA and NA genes represented their different HA and NA types very well, and this reveals that each influenza A virus subtype uses different codon usage patterns as well as the amino acid compositions. In NP, PA and PB2 genes, most of the virus subtypes showed similar RSCU patterns except for H5N1 and H3N2 (A/HK/1774/1999) subtypes which were suspected to be transmitted across the species barrier, from avian and porcine species to human beings, respectively. This distinguishable synonymous codon usage patterns in non-human origin viruses might be useful in determining the origin of influenza A viruses in genomic levels as well as the serological tests. In this study, all the process, including extracting sequences from GenBank flat file and calculating codon usage values, was conducted by Java codes, and these bioinformatics-related methods may be useful in predicting the evolutionary patterns of pandemic viruses.
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de Séoul</orgName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">06-0534885</idno><date when="2006">2006</date><idno type="stanalyst">PASCAL 06-0534885 INIST</idno><idno type="RBID">Pascal:06-0534885</idno><idno type="wicri:Area/PascalFrancis/Corpus">000042</idno><idno type="wicri:Area/PascalFrancis/Curation">000032</idno><idno type="wicri:Area/PascalFrancis/Checkpoint">000043</idno><idno type="wicri:explorRef" wicri:stream="PascalFrancis" wicri:step="Checkpoint">000043</idno><idno type="wicri:doubleKey">0393-2990:2006:Ahn I:genomic:analysis:of</idno><idno type="wicri:Area/Main/Merge">001592</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Genomic analysis of influenza A viruses, including avian Flu (H5N1) strains</title><author><name sortKey="Ahn, Insung" sort="Ahn, Insung" uniqKey="Ahn I" first="Insung" last="Ahn">Insung Ahn</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Bioinformatics Team, Supercomputing Center, Korea Institute of Science and Technology Information</s1><s2>Yusong-Gu, Daejon</s2><s3>KOR</s3><sZ>1 aut.</sZ></inist:fA14><country>Corée du Sud</country><wicri:noRegion>Yusong-Gu, Daejon</wicri:noRegion></affiliation><affiliation wicri:level="4"><inist:fA14 i1="02"><s1>Laboratory of Computational Biology & Bioinformatics, Graduate School of Public Health, Seoul National University, 28, Yongon-Dong</s1><s2>Chongno-Gu, Seoul</s2><s3>KOR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ></inist:fA14><country>Corée du Sud</country><placeName><settlement type="city">Séoul</settlement><region type="capital">Région capitale de Séoul</region></placeName><orgName type="university">Université nationale de Séoul</orgName></affiliation></author><author><name sortKey="Jeone, Byeong Jin" sort="Jeone, Byeong Jin" uniqKey="Jeone B" first="Byeong-Jin" last="Jeone">Byeong-Jin Jeone</name><affiliation wicri:level="4"><inist:fA14 i1="02"><s1>Laboratory of Computational Biology & Bioinformatics, Graduate School of Public Health, Seoul National University, 28, Yongon-Dong</s1><s2>Chongno-Gu, Seoul</s2><s3>KOR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ></inist:fA14><country>Corée du Sud</country><placeName><settlement type="city">Séoul</settlement><region type="capital">Région capitale de Séoul</region></placeName><orgName type="university">Université nationale de Séoul</orgName></affiliation><affiliation wicri:level="4"><inist:fA14 i1="03"><s1>Interdisciplinary Graduate Program in Bioinformatics, College of Natural Science, Seoul National University</s1><s2>Gwanak-Gu, Seoul</s2><s3>KOR</s3><sZ>2 aut.</sZ><sZ>5 aut.</sZ></inist:fA14><country>Corée du Sud</country><placeName><settlement type="city">Séoul</settlement><region type="capital">Région capitale de Séoul</region></placeName><orgName type="university">Université nationale de Séoul</orgName></affiliation></author><author><name sortKey="Bae, Se Eun" sort="Bae, Se Eun" uniqKey="Bae S" first="Se-Eun" last="Bae">Se-Eun Bae</name><affiliation wicri:level="4"><inist:fA14 i1="02"><s1>Laboratory of Computational Biology & Bioinformatics, Graduate School of Public Health, Seoul National University, 28, Yongon-Dong</s1><s2>Chongno-Gu, Seoul</s2><s3>KOR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ></inist:fA14><country>Corée du Sud</country><placeName><settlement type="city">Séoul</settlement><region type="capital">Région capitale de Séoul</region></placeName><orgName type="university">Université nationale de Séoul</orgName></affiliation></author><author><name sortKey="Jung, Jin" sort="Jung, Jin" uniqKey="Jung J" first="Jin" last="Jung">Jin Jung</name><affiliation wicri:level="4"><inist:fA14 i1="02"><s1>Laboratory of Computational Biology & Bioinformatics, Graduate School of Public Health, Seoul National University, 28, Yongon-Dong</s1><s2>Chongno-Gu, Seoul</s2><s3>KOR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ></inist:fA14><country>Corée du Sud</country><placeName><settlement type="city">Séoul</settlement><region type="capital">Région capitale de Séoul</region></placeName><orgName type="university">Université nationale de Séoul</orgName></affiliation></author><author><name sortKey="Son, Hveon S" sort="Son, Hveon S" uniqKey="Son H" first="Hveon S." last="Son">Hveon S. Son</name><affiliation wicri:level="4"><inist:fA14 i1="02"><s1>Laboratory of Computational Biology & Bioinformatics, Graduate School of Public Health, Seoul National University, 28, Yongon-Dong</s1><s2>Chongno-Gu, Seoul</s2><s3>KOR</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ><sZ>3 aut.</sZ><sZ>4 aut.</sZ><sZ>5 aut.</sZ></inist:fA14><country>Corée du Sud</country><placeName><settlement type="city">Séoul</settlement><region type="capital">Région capitale de Séoul</region></placeName><orgName type="university">Université nationale de Séoul</orgName></affiliation><affiliation wicri:level="4"><inist:fA14 i1="03"><s1>Interdisciplinary Graduate Program in Bioinformatics, College of Natural Science, Seoul National University</s1><s2>Gwanak-Gu, Seoul</s2><s3>KOR</s3><sZ>2 aut.</sZ><sZ>5 aut.</sZ></inist:fA14><country>Corée du Sud</country><placeName><settlement type="city">Séoul</settlement><region type="capital">Région capitale de Séoul</region></placeName><orgName type="university">Université nationale de Séoul</orgName></affiliation></author></analytic><series><title level="j" type="main">European journal of epidemiology</title><title level="j" type="abbreviated">Eur. j. epidemiol.</title><idno type="ISSN">0393-2990</idno><imprint><date when="2006">2006</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">European journal of epidemiology</title><title level="j" type="abbreviated">Eur. j. epidemiol.</title><idno type="ISSN">0393-2990</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Avian influenza</term><term>Codon</term><term>Correspondence analysis</term><term>Epidemiology</term><term>Genomics</term><term>Influenza A</term><term>Influenza A virus</term><term>Influenzavirus A(H5N1)</term><term>Public health</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Génomique</term><term>Grippe A</term><term>Analyse correspondance</term><term>Virus grippal A</term><term>Codon</term><term>Santé publique</term><term>Epidémiologie</term><term>Souche H5N1</term><term>Grippe aviaire</term><term>Influenzavirus A(H5N1)</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Santé publique</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">This study was designed to conduct genomic analysis in two steps, such as the overall relative synonymous codon usage (RSCU) analysis of the five virus species in the orthomyxoviridae family, and more intensive pattern analysis of the four subtypes of influenza A virus (H1N1, H2N2, H3N2, and H5N1) which were isolated from human population. All the subtypes were categorized by their isolated regions, including Asia, Europe, and Africa, and most of the synonymous codon usage patterns were analyzed by correspondence analysis (CA). As a result, influenza A virus showed the lowest synonymous codon usage bias among the virus species of the orthomyxoviridae family, and influenza B and influenza C virus were followed, while suggesting that influenza A virus might have an advantage in transmitting across the species barrier due to their low codon usage bias. The ENC values of the host-specific HA and NA genes represented their different HA and NA types very well, and this reveals that each influenza A virus subtype uses different codon usage patterns as well as the amino acid compositions. In NP, PA and PB2 genes, most of the virus subtypes showed similar RSCU patterns except for H5N1 and H3N2 (A/HK/1774/1999) subtypes which were suspected to be transmitted across the species barrier, from avian and porcine species to human beings, respectively. This distinguishable synonymous codon usage patterns in non-human origin viruses might be useful in determining the origin of influenza A viruses in genomic levels as well as the serological tests. In this study, all the process, including extracting sequences from GenBank flat file and calculating codon usage values, was conducted by Java codes, and these bioinformatics-related methods may be useful in predicting the evolutionary patterns of pandemic viruses.</div></front></TEI><affiliations><list><country><li>Corée du Sud</li></country><region><li>Région capitale de Séoul</li></region><settlement><li>Séoul</li></settlement><orgName><li>Université nationale de Séoul</li></orgName></list><tree><country name="Corée du Sud"><noRegion><name sortKey="Ahn, Insung" sort="Ahn, Insung" uniqKey="Ahn I" first="Insung" last="Ahn">Insung Ahn</name></noRegion><name sortKey="Ahn, Insung" sort="Ahn, Insung" uniqKey="Ahn I" first="Insung" last="Ahn">Insung Ahn</name><name sortKey="Bae, Se Eun" sort="Bae, Se Eun" uniqKey="Bae S" first="Se-Eun" last="Bae">Se-Eun Bae</name><name sortKey="Jeone, Byeong Jin" sort="Jeone, Byeong Jin" uniqKey="Jeone B" first="Byeong-Jin" last="Jeone">Byeong-Jin Jeone</name><name sortKey="Jeone, Byeong Jin" sort="Jeone, Byeong Jin" uniqKey="Jeone B" first="Byeong-Jin" last="Jeone">Byeong-Jin Jeone</name><name sortKey="Jung, Jin" sort="Jung, Jin" uniqKey="Jung J" first="Jin" last="Jung">Jin Jung</name><name sortKey="Son, Hveon S" sort="Son, Hveon S" uniqKey="Son H" first="Hveon S." last="Son">Hveon S. Son</name><name sortKey="Son, Hveon S" sort="Son, Hveon S" uniqKey="Son H" first="Hveon S." last="Son">Hveon S. Son</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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