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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Adaptive molecular evolution of virulence genes of avian influenza - A virus subtype H5N1: An analysis of host radiation</title><author><name sortKey="Kumar, Rocky" sort="Kumar, Rocky" uniqKey="Kumar R" first="Rocky" last="Kumar">Rocky Kumar</name></author><author><name sortKey="Halder, Partho" sort="Halder, Partho" uniqKey="Halder P" first="Partho" last="Halder">Partho Halder</name></author><author><name sortKey="Poddar, Raju" sort="Poddar, Raju" uniqKey="Poddar R" first="Raju" last="Poddar">Raju Poddar</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">17597913</idno><idno type="pmc">1891714</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1891714</idno><idno type="RBID">PMC:1891714</idno><date when="2006">2006</date><idno type="wicri:Area/Pmc/Corpus">000919</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000919</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Adaptive molecular evolution of virulence genes of avian influenza - A virus subtype H5N1: An analysis of host radiation</title><author><name sortKey="Kumar, Rocky" sort="Kumar, Rocky" uniqKey="Kumar R" first="Rocky" last="Kumar">Rocky Kumar</name></author><author><name sortKey="Halder, Partho" sort="Halder, Partho" uniqKey="Halder P" first="Partho" last="Halder">Partho Halder</name></author><author><name sortKey="Poddar, Raju" sort="Poddar, Raju" uniqKey="Poddar R" first="Raju" last="Poddar">Raju Poddar</name></author></analytic><series><title level="j">Bioinformation</title><idno type="eISSN">0973-2063</idno><imprint><date when="2006">2006</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>The phenomenon of host radiation is strongly influenced by the rates of mutation of their virulence genes. We have studied
the molecular evolution of virulence genes (HA, NS, PB2) of the Avian Influenza Virus H5N1 from avian to human hosts.
We used a site-specific comparison of synonymous (silent) and non-synonymous (amino acid altering) nucleotide
substitutions for the three chosen genes in parasite populations from different hosts. Analyses were made using Maximum
Likelihood (ML) genealogies for the null and alternate hypothesis based on differential gamma distribution rates. The null
hypothesis had a higher rate of substitution and was found to be more suitable for all the studied genes by Likelihood Ratio
Test (LRT). The study showed the NS gene to be having the fastest rate of evolution.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Bioinformation</journal-id><journal-id journal-id-type="publisher-id">Bioinformation</journal-id><journal-title>Bioinformation</journal-title><issn pub-type="epub">0973-2063</issn><publisher><publisher-name>Biomedical Informatics Publishing Group</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">17597913</article-id><article-id pub-id-type="pmc">1891714</article-id><article-id pub-id-type="publisher-id">77-1-2006</article-id><article-categories><subj-group subj-group-type="heading"><subject>Hypothesis</subject></subj-group></article-categories><title-group><article-title>Adaptive molecular evolution of virulence genes of avian influenza - A virus subtype H5N1: An analysis of host radiation</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Kumar</surname><given-names>Rocky</given-names></name></contrib><contrib contrib-type="author"><name><surname>Halder</surname><given-names>Partho</given-names></name></contrib><contrib contrib-type="author"><name><surname>Poddar</surname><given-names>Raju</given-names></name><xref ref-type="corresp" rid="COR1">*</xref></contrib><aff>Department of Biotechnology, Birla Institute of Technology, Mesra, India</aff></contrib-group><author-notes><corresp id="COR1"><label>*</label>Raju Poddar
E-mail:
<email>rpoddar@bitmesra.ac.in</email>; Phone: +91 651 2276223; Fax: +91 651 22755401; Corresponding author</corresp></author-notes><pub-date pub-type="collection"><year>2006</year></pub-date><pub-date pub-type="epub"><day>26</day><month>12</month><year>2006</year></pub-date><volume>1</volume><issue>8</issue><fpage>321</fpage><lpage>326</lpage><history><date date-type="received"><day>11</day><month>12</month><year>2006</year></date><date date-type="rev-recd"><day>24</day><month>12</month><year>2006</year></date><date date-type="accepted"><day>25</day><month>12</month><year>2006</year></date></history><permissions><copyright-statement>© 2005 Biomedical Informatics Publishing Group</copyright-statement><copyright-year>2005</copyright-year><license license-type="open-access"><p>This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.</p></license></permissions><abstract><p>The phenomenon of host radiation is strongly influenced by the rates of mutation of their virulence genes. We have studied
the molecular evolution of virulence genes (HA, NS, PB2) of the Avian Influenza Virus H5N1 from avian to human hosts.
We used a site-specific comparison of synonymous (silent) and non-synonymous (amino acid altering) nucleotide
substitutions for the three chosen genes in parasite populations from different hosts. Analyses were made using Maximum
Likelihood (ML) genealogies for the null and alternate hypothesis based on differential gamma distribution rates. The null
hypothesis had a higher rate of substitution and was found to be more suitable for all the studied genes by Likelihood Ratio
Test (LRT). The study showed the NS gene to be having the fastest rate of evolution.</p></abstract><kwd-group><kwd>avian influenza A virus (H5N1)</kwd><kwd>adaptive molecular evolution</kwd><kwd>hemagglutinin</kwd><kwd>NS</kwd><kwd>PB2</kwd><kwd>host niche</kwd><kwd>nucleotide substitution rates</kwd><kwd>positive selection</kwd><kwd>Markov model</kwd><kwd>Likelihood ratio test</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>Background</title><p>A common phenomenon in parasite evolution is their ability to expand their niche to new host species. This process of acquiring of new host ranges is called host
change event or host radiation. The selective force on a particular parasite gene may change after host radiation due to reasons like adaptive alteration of protein functionality
or host's immune-mediated selection. Since a host change event comprises three stages namely transmission to new host species, replication within new host and transmission
between individuals of the new host species, with the last two steps being rate limiting, host radiation events are rarely successful. According to the general theory of
‘ecological specialization’ the host specific adaptations act as ecological barriers. [<xref ref-type="bibr" rid="R01">1</xref>] These host change events though
rare, do occur and may be detrimental to the new host, some eminent examples of which are the Spanish Flu pandemic and the latest H5N1 outbreaks.</p><p>The avian influenza A virus is commonly found in most wild birds especially migratory water fowl and wild ducks which act as their natural reservoirs and carriers. It is
however fatally infectious to domestic birds like chicken, duck, turkeys etc. There are many subtypes of the virus differing in the combination of subtypes of HA
(Hemagglutinin) and NA (Neuraminidase) surface proteins. Human infections were first reported in Hong Kong (1997) with the latest one being the H5N1 outbreak. [<xref ref-type="bibr" rid="R02">2</xref>] Though
the outbreaks were local and man to man transmission was rare, the highly mutable nature of influenza virus raises concerns. This is due to the lack of ‘proofreading’
mechanisms and repair of errors that occur during replication. Little or no immune protection among human population due to lack of prior infection, may lead to
pandemic outbreaks. [<xref ref-type="bibr" rid="R03">3</xref>]</p><p>Past influenza pandemics have led to high levels of illness, death, social disruption and economic loss. There were three major influenza-A pandemics during the 20<sup>th</sup> century,
namely (1) Spanish flu (H1N1) 1918-19, (2) Asian flu (H2N2) 1957-58, and (3) Hong Kong flu (H3N2) 1968-69, which caused thousands of death in the United States. Of
the various subtypes, H5N1 is of greatest pandemic concern currently because of the following reasons: rapid spread throughout poultry flocks in Asia; endemic
outbreaks in eastern Asia; highly rapid rate of mutation; propensity to acquire genes from viruses infecting other animal species; causes severe disease in humans with a
high fatality rate of approximately 70 %. [<xref ref-type="bibr" rid="R04">4</xref>]</p><p>Studies on the genetic basis revealed that three genes of avian influenza virus are responsible for their virulence. These are HA, NS and PB2 genes. HA (hemagglutinin)
gene is responsible for high cleavability of the hemagglutinin glycoprotein. It is like glue that binds to the sialic acid on cell receptors and hampers its function, NS
(non structural) gene antagonizes the induction of interferon protein levels and leads to lethal viral infection [<xref ref-type="bibr" rid="R05">5</xref>]
and PB2 gene encodes an internal polymerase that influences the outcome of infection. [<xref ref-type="bibr" rid="R06">6</xref>,<xref ref-type="bibr" rid="R07">7</xref>] Another study
showed that a mutation at position 627 in the gene PB2, which identifying positions in the parasite genome underlying the phenotypic differences between hostspecific
strains may give insights about the molecular basis of species-specific adaptation.</p><p>The fundamental objective behind our work is to study how selection acts on variants of genes responsible for virulence i.e. HA, NS and PB2 genes of different hosts comprising
birds and humans. To do so, we use a site-specific comparison of synonymous (silent) and non-synonymous (amino acid altering) nucleotide substitutions in the parasite
populations from different hosts. Methods for performing the analyses on a site-specific level have focused on amino acid conservation as an indication of protein function. The
purpose of the work is to gain a better understanding of the evolutionary processes in H5N1 avian influenza virus that has undergone host radiation from birds to humans.</p></sec><sec sec-type="methods" id="s2"><title>Methodology</title><p>The assumption behind this approach is based on functional constraint i.e. functionally important residues and sequences are under stronger selective constraints that
lower their evolutionary rates. Investigation of changes in evolution was done by developing a likelihood ratio test based on Markov model of codon substitution for detecting significant rate shifts.</p><p>Our work is based on the model proposed by Goldman and Yang. [<xref ref-type="bibr" rid="R08">8</xref>] In this model Markov process is used to describe
substitutions between codons and transition/ transversion rate bias and codon usage bias are allowed. Further selective restraints at the protein level are accommodated
using physicochemical distances between the amino acids coded for by the codons.</p><p>The utility of the model is illustrated on a data set of virulence gene sequences from the influenza A virus. The sample of coding sequences from homologous genes
responsible for virulence was taken from influenza A virus of strain H5N1 which infects two different host types, birds and humans. The sequences of HA, NS and PB2 genes of
viruses isolated from aves and humans were downloaded from the Influenza Sequence Database at <ext-link ext-link-type="uri" xlink:href="http://www.flu.lanl.gov/">http://www.flu.lanl.gov/</ext-link>.</p><p>Multiple sequence alignment was done using ClustalX (ver 1.81) software. [<xref ref-type="bibr" rid="R09">9</xref>] The genealogy of the chosen isolates
was inferred under the maximum likelihood (ML) criteria by the dnaML algorithm [<xref ref-type="bibr" rid="R10">10</xref>] provided in PHYLIP package
(ver 3.6, 2004) which can be downloaded from <ext-link ext-link-type="uri" xlink:href="http://evolution.genetics.washington.edu/phylip.html">http://evolution.genetics.washington.edu/phylip.html</ext-link>. The
program was used to find the most significantly positive branches and their corresponding branch lengths. Plot of trees were made with the help of drawgram program of the
PHYLIP package. A Bayesian estimate of the posterior genealogy distribution was performed using the MrBayes (ver 3.1.2) program. [<xref ref-type="bibr" rid="R11">11</xref>] This can
be downloaded from <ext-link ext-link-type="uri" xlink:href="http://mrbayes.net">http://mrbayes.net</ext-link>. The estimation was performed with a
general time reversible (GTR) model of substitution and a gamma distribution on rate heterogeneity. Phylogenetic analysis by employing maximum likelihood method was
done by a computer program ‘PAML’ [<xref ref-type="bibr" rid="R12">12</xref>] which can be downloaded from the Web site
<ext-link ext-link-type="uri" xlink:href="http://abacus.gene.ucl.ac.uk/software/paml.html">http://abacus.gene.ucl.ac.uk/software/paml.html</ext-link>. A
program ‘codeml’ of the package was used to find the base frequencies and different codon usage. All the statistical analyses were done by statistical software ‘OriginPro 7.5
SRO’ from Origin Lab Corp. USA.</p></sec><sec sec-type="discussion" id="s3"><title>Discussion</title><p>Analyses were performed using the genealogies estimated by maximum likelihood. Results of the analysis of both hypotheses for the three genes are shown in <xref ref-type="table" rid="T1">tables 1</xref>. The
hypothesis H<sub>1</sub> was approximated by a Gamma distribution of rates among the sites where as the hypothesis H<sub>0</sub> was approximated by a Gamma distribution plus a class of invariant sites.</p><p>The hypotheses were tested by using the LRT method. [<xref ref-type="bibr" rid="R13">13</xref>] The test statistics can be given by:
U = -2log L<sub>1</sub> /L<sub>0</sub>
Where U is the log likelihood ratio for the models and L<sub>1</sub> and L<sub>0</sub> are the log likelihood values for hypothesis H<sub>1</sub> and H<sub>0</sub> respectively. Because H<sub>1</sub> is a special case of H<sub>0</sub> (the
hypotheses are nested), the likelihoods will always obey the relationship that L<sub>1</sub> ≤ L<sub>0</sub>. This means that U will never be negative. Minimum probability ‘p’ of not rejecting H<sub>0</sub>, is
given by the equation: U≤ (1 - α) x 100% (where α equals the probability of rejecting H<sub>0</sub>).</p><p>The test showed that the hypothesis H<sub>0</sub> gives a better fit than hypothesis H<sub>1</sub>. Besides the H<sub>0</sub> model having an additional class of invariant sites is responsible for faster
rate of evolution. Further the probability of not rejecting hypothesis H<sub>0</sub> is highest in case of the NS gene followed by that of HA and PB2. Thus we can infer that NS has the
fastest rate of evolution and seems to be most significant for molecular adaptation of the parasite. This was also confirmed by determining the trees generated for these
genes by a maximum likelihood algorithm. The trees for the different genes are shown in <xref ref-type="fig" rid="F1">fig-1</xref>, <xref ref-type="fig" rid="F2">fig-2</xref> and
<xref ref-type="fig" rid="F3">fig-3</xref> for NS, HA and PB2 gene respectively.</p><p>As per <xref ref-type="table" rid="T2">table 2</xref>, it has also been shown that the hypothesis H<sub>0</sub> gives a wide range of values for the rates of change for all the considered genes, as compared to that of H<sub>1</sub> meaning
that the chances of positive selection is greater in the model H<sub>0</sub>.</p><p>Further in our study on codon usage, we found that the most important base responsible for non-synonymous substitution in case of HA genes is T at first position and C
for second position as they have the highest standard deviation among the four bases for a given position which means that they are the least conserved bases and have high
chances of getting substituted and thus are important candidate for molecular evolution. Similarly for PB2 the most important base at first and second position are A and
C respectively and for NS gene the most important base at first and second position are T and C respectively. The results are shown in the <xref ref-type="table" rid="T3">table 3</xref>.</p><p>The result also showed that the standard deviation for substitution of bases of NS gene was highest among all the three considered genes which shows and confirms that NS
gene is the most evolving gene followed by HA and PB2. These results were also confirmed with the simulation studies for Markov Chain Monte Carlo samples based on a
total of 19502 samples from 2 runs. Each run produced 10001 samples of which 9751 samples were included (data not shown).</p></sec><sec sec-type="conclusions" id="s4"><title>Conclusion</title><p>We found out that during the process of molecular evolution of avian influenza virus from birds to humans, the most important gene responsible for causing virulence
in humans is NS followed by HA and PB2. Our motivation here was to study the evolution of virus undergoing host radiation, but the study addresses the more general problem
of describing the substitution process in two groups of related organisms. The codon-based approach which we used uses a comparison between the two different types of
nucleotide substitution, thus enabling use of the full information in the nucleotide sequence and also includes the known biological phenomenon of transitiontransversion
bias. However the gamma parameter used in the study is a very crude indicator and the indicators such as, e.g., shifts between biochemically different groups of
amino acids etc. can improve the study. We have assumed that the rates of synonymous and nonsynonymous substitution scale identically with changes in the mutation
rate after a viral host change because of alterations. This scaling can be hold for sites where all amino acid substitutions are either neutral or strongly deleterious.
However, for sites undergoing positive selection if the process of fixation is limited by factors other than the availability of mutations, this may not be the case. We
believe that our study may prove to be useful to identify candidate genes and codons for the molecular biological investigation of species-specific adaptation in viruses.</p></sec></body><back><ack><p>We are thankful to our Department of Biotechnology, Government of India for the funds to set up a Sub-Distributed Information Center (BTISnet SubDIC) at our
Department of Biotechnology, Birla Institute of Technology, Mesra where this work was done.</p></ack><ref-list><title>References</title><ref id="R01"><label>1</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Turner</surname><given-names>PE</given-names></name><name><surname>Elena</surname><given-names>SF</given-names></name></person-group><source>Genetics</source><year>2000</year><volume>156</volume><fpage>1465</fpage><pub-id pub-id-type="pmid">11102349</pub-id></citation></ref><ref id="R02"><label>2</label><citation citation-type="web"><comment><ext-link ext-link-type="uri" xlink:href="http://www.who.int/csr/disease/avian_influenza/en/">http://www.who.int/csr/disease/avian_influenza/en/</ext-link></comment></citation></ref><ref id="R03"><label>3</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Webby</surname><given-names>RJ</given-names></name><name><surname>Webster</surname><given-names>RG</given-names></name></person-group><source>Science</source><year>2003</year><volume>302</volume><fpage>1519</fpage><pub-id pub-id-type="pmid">14645836</pub-id></citation></ref><ref id="R04"><label>4</label><citation citation-type="web"><comment><ext-link ext-link-type="uri" xlink:href="www.cidrap.umn.edu">www.cidrap.umn.edu</ext-link></comment></citation></ref><ref id="R05"><label>5</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Li</surname><given-names>Z</given-names></name><etal></etal></person-group><source>J Virol</source><year>2006</year><volume>80</volume><fpage>11115</fpage><pub-id pub-id-type="pmid">16971424</pub-id></citation></ref><ref id="R06"><label>6</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Hughes</surname><given-names>MT</given-names></name><etal></etal></person-group><source>J Virol</source><year>2000</year><volume>74</volume><fpage>5206</fpage><pub-id pub-id-type="pmid">10799596</pub-id></citation></ref><ref id="R07"><label>7</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Hatta</surname><given-names>M</given-names></name><etal></etal></person-group><source>Science</source><year>2001</year><volume>293</volume><fpage>1840</fpage><pub-id pub-id-type="pmid">11546875</pub-id></citation></ref><ref id="R08"><label>8</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Goldman</surname><given-names>N</given-names></name><name><surname>Yang</surname><given-names>Z</given-names></name></person-group><source>Mol Bio Evol</source><year>1994</year><volume>11</volume><fpage>725</fpage><pub-id pub-id-type="pmid">7968486</pub-id></citation></ref><ref id="R09"><label>9</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Thompson</surname><given-names>JD</given-names></name><etal></etal></person-group><source>Nucleic Acids Res</source><year>1997</year><volume>24</volume><fpage>4876</fpage><pub-id pub-id-type="pmid">9396791</pub-id></citation></ref><ref id="R10"><label>10</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Felsenstein</surname><given-names>J</given-names></name><name><surname>Churchill</surname><given-names>GA</given-names></name></person-group><source>Mol Biol Evol</source><year>1996</year><volume>13</volume><fpage>93</fpage><pub-id pub-id-type="pmid">8583911</pub-id></citation></ref><ref id="R11"><label>11</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Huelsenbeck</surname><given-names>JP</given-names></name><name><surname>Ronquist</surname><given-names>F</given-names></name></person-group><source>Bioinformatics</source><year>2001</year><volume>17</volume><fpage>754</fpage><pub-id pub-id-type="pmid">11524383</pub-id></citation></ref><ref id="R12"><label>12</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Yang</surname><given-names>Z</given-names></name><etal></etal></person-group><source>Computer Applications in BioSciences</source><year>1997</year><volume>13</volume><fpage>555</fpage><pub-id pub-id-type="pmid">9367129</pub-id></citation></ref><ref id="R13"><label>13</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Knudsen</surname><given-names>B</given-names></name><name><surname>Miyamoto</surname><given-names>MM</given-names></name></person-group><source>PNAS</source><year>2001</year><volume>98</volume><fpage>14512</fpage><pub-id pub-id-type="pmid">11734650</pub-id></citation></ref></ref-list><sec sec-type="display-objects"><title>Figures and Tables</title><table-wrap id="T1" position="float"><label>Table 1</label><caption><title>Analysis of the genes from the influenza A virus using ML method</title></caption><table frame="hsides" rules="groups"><thead><tr><th align="center" valign="top" rowspan="1" colspan="1">Gene responsible for virulence</th><th align="center" valign="top" rowspan="1" colspan="1">Likelihood value of hypothesis H<sub>0</sub></th><th align="center" valign="top" rowspan="1" colspan="1">Likelihood value of hypothesis H<sub>1</sub></th><th align="center" valign="top" rowspan="1" colspan="1">U (log likelihood ratio)</th><th align="center" valign="top" rowspan="1" colspan="1">P value</th></tr></thead><tbody><tr><td align="center" rowspan="1" colspan="1">HA</td><td align="center" rowspan="1" colspan="1">-7266.62128</td><td align="center" rowspan="1" colspan="1">-7755.29608</td><td align="center" rowspan="1" colspan="1">12.3834</td><td align="center" rowspan="1" colspan="1">0.8761</td></tr><tr><td align="center" rowspan="1" colspan="1">NS</td><td align="center" rowspan="1" colspan="1">-5745.40265</td><td align="center" rowspan="1" colspan="1">-6008.68716</td><td align="center" rowspan="1" colspan="1">11.1465</td><td align="center" rowspan="1" colspan="1">0.8853</td></tr><tr><td align="center" rowspan="1" colspan="1">PB2</td><td align="center" rowspan="1" colspan="1">-10923.83329</td><td align="center" rowspan="1" colspan="1">-12150.27347</td><td align="center" rowspan="1" colspan="1">14.2237</td><td align="center" rowspan="1" colspan="1">0.85776</td></tr></tbody></table></table-wrap><table-wrap id="T2" position="float"><label>Table 2</label><caption><title>Estimation of rates of change and their probability for both hypotheses</title></caption><table frame="hsides" rules="groups"><thead><tr><th align="center" valign="top" rowspan="1" colspan="1">State in HMM</th><th colspan="2" align="center" valign="top" rowspan="1">Rates of change</th><th colspan="2" align="center" valign="top" rowspan="1">Probability</th></tr><tr><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1">H<sub>1</sub></td><td align="center" rowspan="1" colspan="1">H<sub>0</sub></td><td align="center" rowspan="1" colspan="1">H<sub>1</sub></td><td align="center" rowspan="1" colspan="1">H<sub>0</sub></td></tr></thead><tbody><tr><td align="center" rowspan="1" colspan="1">1</td><td align="center" rowspan="1" colspan="1">0.528</td><td align="center" rowspan="1" colspan="1">0.359</td><td align="center" rowspan="1" colspan="1">0.474</td><td align="center" rowspan="1" colspan="1">0.895</td></tr><tr><td align="center" rowspan="1" colspan="1">2</td><td align="center" rowspan="1" colspan="1">9.472</td><td align="center" rowspan="1" colspan="1">6.110</td><td align="center" rowspan="1" colspan="1">0.026</td><td align="center" rowspan="1" colspan="1">0.103</td></tr><tr><td align="center" rowspan="1" colspan="1">3</td><td align="center" rowspan="1" colspan="1">0.000</td><td align="center" rowspan="1" colspan="1">20.531</td><td align="center" rowspan="1" colspan="1">0.500</td><td align="center" rowspan="1" colspan="1">0.0025</td></tr></tbody></table></table-wrap><table-wrap id="T3" position="float"><label>Table 3</label><caption><title>Values of standard deviation of base frequency for different codon position and different bases</title></caption><table frame="hsides" rules="groups"><thead><tr><th align="center" rowspan="1" colspan="1">Base</th><th align="center" rowspan="1" colspan="1">HA</th><th align="center" rowspan="1" colspan="1">HA</th><th align="center" rowspan="1" colspan="1">PB2</th><th align="center" rowspan="1" colspan="1">PB2</th><th align="center" rowspan="1" colspan="1">NS</th><th align="center" rowspan="1" colspan="1">NS</th></tr></thead><tbody><tr><td align="center" rowspan="1" colspan="1"></td><td align="center" rowspan="1" colspan="1">*SD for 1<sup>st</sup> position</td><td align="center" rowspan="1" colspan="1">SD for 2<sup>nd</sup> position</td><td align="center" rowspan="1" colspan="1">SD for 1<sup>st</sup> position</td><td align="center" rowspan="1" colspan="1">SD for 2<sup>nd</sup> position</td><td align="center" rowspan="1" colspan="1">SD for 1<sup>st</sup> position</td><td align="center" rowspan="1" colspan="1">SD for 2<sup>nd</sup> position</td></tr><tr><td align="center" rowspan="1" colspan="1">T</td><td align="center" rowspan="1" colspan="1">0.00609</td><td align="center" rowspan="1" colspan="1">0.00337</td><td align="center" rowspan="1" colspan="1">0.00129</td><td align="center" rowspan="1" colspan="1">0.00196</td><td align="center" rowspan="1" colspan="1">0.00632</td><td align="center" rowspan="1" colspan="1">0.00254</td></tr><tr><td align="center" rowspan="1" colspan="1">C</td><td align="center" rowspan="1" colspan="1">0.00422</td><td align="center" rowspan="1" colspan="1">0.00446</td><td align="center" rowspan="1" colspan="1">0.0019</td><td align="center" rowspan="1" colspan="1">0.00256</td><td align="center" rowspan="1" colspan="1">0.00327</td><td align="center" rowspan="1" colspan="1">0.00442</td></tr><tr><td align="center" rowspan="1" colspan="1">A</td><td align="center" rowspan="1" colspan="1">0.00345</td><td align="center" rowspan="1" colspan="1">0.00313</td><td align="center" rowspan="1" colspan="1">0.00452</td><td align="center" rowspan="1" colspan="1">0.0014</td><td align="center" rowspan="1" colspan="1">0.00475</td><td align="center" rowspan="1" colspan="1">0.0016</td></tr><tr><td align="center" rowspan="1" colspan="1">G</td><td align="center" rowspan="1" colspan="1">0.00338</td><td align="center" rowspan="1" colspan="1">0.00333</td><td align="center" rowspan="1" colspan="1">0.0035</td><td align="center" rowspan="1" colspan="1">0.00139</td><td align="center" rowspan="1" colspan="1">0.00312</td><td align="center" rowspan="1" colspan="1">0.00297</td></tr></tbody></table><table-wrap-foot><fn><p>*SD = Standard deviation </p></fn></table-wrap-foot></table-wrap><fig id="F1" position="float"><label>Figure 1</label><caption><p>Genealogy of the NS sequences used in the study using ML method</p></caption><graphic xlink:href="97320630001321F1"></graphic></fig><fig id="F2" position="float"><label>Figure 2</label><caption><p>Genealogy of the HA sequences used in the study using ML method. Sequences are listed with GeneBank
accession (A/C) numbers and the branch length in units of expected substitutions per codon is indicated by the scale bar</p></caption><graphic xlink:href="97320630001321F2"></graphic></fig><fig id="F3" position="float"><label>Figure 3</label><caption><p>Genealogy of the PB2 sequences used in the study using ML method</p></caption><graphic xlink:href="97320630001321F3"></graphic></fig></sec><fn-group><fn id="FN1" fn-type="other"><p><bold>Citation:</bold>Kumar
<italic>et al.</italic>, Bioinformation 1(8): 321-326 (2006)</p></fn></fn-group></back></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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