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Brief report
A safe an easy method for building consensus HIV sequences from 454 massively parallel sequencing data
Validación de un método seguro y sencillo para la elaboración de secuencias consenso del virus de la inmunodeficiencia humana a partir de los datos de secuenciación masiva 454
Jose Ángel Fernández-Caballero Ricoa,
Corresponding author
, Natalia Chueca Porcunaa, Marta Álvarez Estéveza, María del Mar Mosquera Gutiérrezb, María Ángeles Marcos Maesob, Federico Garcíaa
a Servicio de Microbiología Clínica, Hospital Universitario San Cecilio, Complejo Hospitalario Universitario Granada e Instituto de Investigación IBS, Granada, Spain
b Servicio de Microbiología Clínica, Centro de Diagnóstico Biomédico, Hospital Clínic, Universidad de Barcelona, Barcelona, Spain
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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Bootscan of the Sanger sequence &#40;A&#41;&#44; NGS-10&#37; consensus sequence &#40;B&#41; and NGS-20&#37; consensus sequence &#40;C&#41;&#44; using the REGA HIV-1 Subtyping Tool v&#46; 3&#46;0&#46; In the Bootscan&#44; the HIV A subtype value is the same in the Sanger and NGS-20&#37; consensus sequence&#44; however&#44; a CRF03&#95;AB subtype can be seen in the NGS-10&#37; consensus sequence&#46;</p>"
        ]
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Many clinical microbiology departments have started to use next generation sequencing &#40;NGS&#41; techniques to study antiretroviral resistance in HIV patients&#46; Several studies<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">1</span></a> have shown the capacity of NGS to detect low abundance viral variants by lowering sensitivity below the 1&#37; threshold &#40;minority variants&#41;&#46; This can greatly improve therapeutic decision-making and prevent therapeutic failure&#46;<a class="elsevierStyleCrossRefs" href="#bib0085"><span class="elsevierStyleSup">2&#44;3</span></a> In Spain&#44; the use of NGS for the detection of antiretroviral resistance has been prompted to a certain extent by the decision of some suppliers to discontinue supply of Sanger sequencing systems&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">Protease &#40;PR&#41; and reverse transcriptase &#40;RT&#41; sequences obtained from drug resistance tests are often used by researchers in molecular epidemiology studies&#44; using phylogenetic and phylodynamic techniques&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">4</span></a> With the introduction of NGS techniques&#44; this information can be lost due the complexity of processing and storing the sequences for this type of study&#59; in addition&#44; incorrect processing of NGS sequences can yield incorrect results&#46; Special training in sequence processing and high-performance computers capable of processing the vast amounts of data generated are needed in order to use NGS sequences in phylogenetic studies&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">5</span></a> An alternative&#44; in the case of molecular epidemiology studies&#44; is to generate a single consensus NGS sequence&#59; however&#44; some studies do not clearly describe&#44; or omit altogether&#44; the method used to generate the sequence&#46;<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">6</span></a> In addition&#44; we cannot know for certain the extent to which this consensus NGS represents the sequence obtained by Sanger methods and the effect of the thresholds used to generate this consensus&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">The objective of this study was to determine the best threshold for obtaining a consensus NGS sequence that is representative of the Sanger sequence and can be used in molecular epidemiology studies&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Methods</span><p id="par0020" class="elsevierStylePara elsevierViewall">For the purpose of our study&#44; we used sequences from 62 treatment na&#239;ve patients&#44; newly diagnosed with HIV between 2014 and 2015 and referred for antiretroviral resistance studies&#46; Sanger sequences were obtained using <span class="elsevierStyleItalic">Trugene</span><span class="elsevierStyleSup"><span class="elsevierStyleItalic">&#174;</span></span> HIV-1 Genotyping &#40;Siemens &#8211; &#91;NAD&#93;&#41;&#46; For NGS&#44; we used the GSV-type HIV-1 Drug Resistance Primer kit &#40;Roche&#41; for 454 GS-Junior&#44; based on the same RNA&#46; The NGS consensus sequences are generated using the Mesquite v&#46; 2&#46;75 software&#44; setting thresholds at 10&#37;&#44; 15&#37; and 20&#37;&#46; Prior to the use of Mesquite&#44; the sequences were filtered using Usearch fastq&#95;filter commands&#44; according to the desired amplicon length and sequence quality &#40;&#62;30 Q&#41;&#46; Mesquite<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">7</span></a> is a programme with an intuitive icon- and tab-based interface&#46; Before processing data on Mesquite&#44; the filtered sequences must be exported in <span class="elsevierStyleItalic">pfam</span> format and the threshold for the consensus sequence must be set before exporting in <span class="elsevierStyleItalic">fasta</span> format&#46; Following this&#44; the pol gene sequences &#40;PR 4&#8211;99&#59; RT 38&#8211;247&#41; are processed&#44; aligned by MUSCLE in MEGA 6&#46;06 and phylogenetic trees are generated using the maximum likelihood method&#44; using the General Time Reversible &#40;GTR&#41; model to calculate evolutionary distances&#44; with a gamma distribution equivalent to 1&#46;89 obtained with FindModel DNA&#44; and using bootstrap resampling with 1000 replicas to build the consensus phylogenetic trees&#46; To define a relationship between sequences&#44; only the branches from clusters with a bootstrap value greater than 75&#37; are taken into consideration&#46; Finally&#44; the trees are processed in FigTree v&#46; 1&#46;4&#46;2&#46; The viral subtype analysis was performed using the REGA HIV-1 Subtyping Tool v&#46; 3&#46;0&#46;</p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Results</span><p id="par0025" class="elsevierStylePara elsevierViewall">Our study included 62 treatment na&#239;ve HIV-1 patients with a median age of 37 years &#40;IQR 30&#8211;45&#41;&#44; viral load &#40;median&#41; of 74&#44;900<span class="elsevierStyleHsp" style=""></span>cp&#47;ml &#40;IQR 20&#44;715&#8211;176&#44;250&#41;&#44; CD4 count &#40;median&#41; of 430<span class="elsevierStyleHsp" style=""></span>cells&#47;ml &#40;IQR 48&#46;5&#8211;567&#46;78&#41;&#59; 82&#37; were men&#46;</p><p id="par0030" class="elsevierStylePara elsevierViewall">To evaluate concordance between the NGS consensus sequences with different thresholds and the original Sanger sequence&#44; we analysed the number of sequences with inter-related pairs and the bootstrap values between the pairs&#46; Using a 10&#37; threshold&#44; we observed that the Sanger sequence pairs were correlated with NGS from the same sample in only in 17&#47;62 &#40;27&#37;&#41; patients and in these&#44; the median bootstrap value was 88&#37; &#40;IQR 83&#46;5&#8211;95&#46;5&#41;&#46; Increasing the threshold to 15&#37;&#44; the sequence pairs were correlated in 36&#47;62 &#40;58&#37;&#41; patients&#44; with a median bootstrap value of 94&#37; &#40;IQR 85&#46;5&#8211;98&#41;&#46; At 20&#37;&#44; sequences were correlated in 61&#47;62 patients&#44; with a median bootstrap value of 99&#37; &#40;IQR 98&#8211;100&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#41;&#46; A large number of differences between base pairs were detected in cases where the NGS sequence was not correlated with the Sanger sequence&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0035" class="elsevierStylePara elsevierViewall">Most patients were infected by subtype B &#40;77&#46;4&#37;&#41;&#44; followed by CRF02&#95;AG &#40;12&#46;9&#37;&#41;&#44; A and F &#40;3&#46;2&#37;&#41; and C and G &#40;1&#46;6&#37;&#41;&#46; Using a consensus NGS threshold of 10&#37; and 15&#37;&#44; we observed 2 cases that differed from the Sanger subtype&#58; one case of subtype B-NGS and A1-Sanger and another one from subtype CRF03&#95;AB-NGS and A1-Sanger&#46; These differences disappeared when using the 20&#37; threshold consensus NGS sequences &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46; <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a> shows the bootscan plot of the subtype in the second discordant sample&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Discussion</span><p id="par0040" class="elsevierStylePara elsevierViewall">Phylogenetic studies of HIV&#44;<a class="elsevierStyleCrossRefs" href="#bib0115"><span class="elsevierStyleSup">8&#44;9</span></a> specifically studies into relatedness&#44; transmission dynamics of the HIV epidemic and molecular pol gene sequence subtyping&#44; have been used for various purposes&#44; among them to understand HIV transmission networks and clusters and the migratory networks of the different subtypes&#46; Most studies published at the international<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">10</span></a> and local level<a class="elsevierStyleCrossRefs" href="#bib0130"><span class="elsevierStyleSup">11&#44;12</span></a> have used Sanger sequencing&#46; Some of these studies have used all the information obtained through NGS<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">13</span></a> but investigators generally try to generate a single consensus sequence&#44; usually using complex computer commands&#46; The transition from Sanger sequencing to NGS for pol gene analysis of resistance mutations has changed the type of sequences used in clinical microbiology departments and can&#44; paradoxically&#44; stand in the way of local HIV molecular epidemiology studies in Spain&#46; In this study&#44; we propose using Mesquite&#44; an intuitive&#44; user-friendly&#44; software without the need for commands that simplifies the process of obtaining a consensus sequence from NGS-generated sequences&#46; We have shown that using a threshold of 20&#37; to generate this consensus yields safe&#44; reliable information that is identical to that obtained using Sanger sequencing&#46; This information can be used in molecular epidemiology studies and solves the current problems arising from the use of NGS sequences&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">As we have shown in this study&#44; the threshold must be raised to 20&#37; in order to safely use consensus sequences that are representative of Sanger sequences in HIV molecular epidemiology studies&#46; This was the only threshold that yields a median bootstrap value of 99&#37; &#40;IQR 98&#8211;100&#41; between the NGS consensus sequences and the Sanger sequence&#46; Using thresholds of 10&#37; or 15&#37;&#44; the percentage of correlated NGS-Sanger sequence pairs and the median bootstrap values are too low&#46; Because of this variability&#44; errors are made even in the determination of the viral subtype&#59; this was corrected with the 20&#37; consensus&#46; These discrepancies are due to the multitude of ambiguous base pairs generated with the 10&#37; and 15&#37; thresholds&#44; which made it impossible to correctly determine the viral subtype&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">An important part of molecular epidemiology studies is sequence alignment&#44; in which homologous positions are aligned based on the true evolutionary history of the sequences&#46;<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">14</span></a> The problem with using 10&#37; and 15&#37; NGS consensus sequences in such studies lies in the presence of ambiguous regions&#44; which present substantial uncertainty and detract from the robustness of both phylogenetic<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">15</span></a> and subtype statistical analyses&#44; yielding unexpected results&#46;</p><p id="par0055" class="elsevierStylePara elsevierViewall">It is important to point out that the methodology presented here is appropriate for obtaining consensus sequences for use in HIV molecular epidemiology studies but not for the analysis of resistance mutations&#46; The greater sensitivity of NGS to detect minority variants and its clinical utility have been studied in detail&#46;<a class="elsevierStyleCrossRefs" href="#bib0080"><span class="elsevierStyleSup">1&#8211;4</span></a> NGS provides very valuable information on the relative proportion of a mutation with respect to the total circulating viruses&#46; This information would be lost when obtaining the consensus sequence&#46;</p><p id="par0060" class="elsevierStylePara elsevierViewall">In summary&#44; we present a methodology for generating consensus sequences that are representative of the Sanger sequence for use in molecular epidemiology studies by processing sequences with a threshold of at least 20&#37;&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Funding</span><p id="par0065" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleGrantSponsor" id="gs1">Health Research Fund</span> &#40;<span class="elsevierStyleGrantNumber" refid="gs1">PI12&#47;01053</span>&#44; <span class="elsevierStyleGrantNumber" refid="gs1">PI15&#47;00713</span>&#41;&#44; RD12&#47;0017&#47;006 &#40;National R&#43;D&#43;I Programme&#44; European Regional Development Fund&#8212;<span class="elsevierStyleGrantSponsor" id="gs2">ERDF</span>&#41;&#46; Federico Garc&#237;a is part of a Research Intensification Programme from the Andalusian Health Service&#46; Jos&#233; &#193;ngel Fern&#225;ndez-Caballero has an RD12&#47;0017&#47;006 contract&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Conflicts of interest</span><p id="par0070" class="elsevierStylePara elsevierViewall">The authors declare that they have no conflicts of interest&#46;</p></span></span>"
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            0 => "Virus de la inmunodeficiencia humana"
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    "resumen" => array:2 [
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        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">To show how to generate a consensus sequence from the information of massive parallel sequences data obtained from routine HIV anti-retroviral resistance studies&#44; and that may be suitable for molecular epidemiology studies&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Material and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Paired Sanger &#40;Trugene-Siemens&#41; and next-generation sequencing &#40;NGS&#41; &#40;454 GSJunior-Roche&#41; HIV RT and protease sequences from 62 patients were studied&#46; NGS consensus sequences were generated using Mesquite&#44; using 10&#37;&#44; 15&#37;&#44; and 20&#37; thresholds&#46; Molecular evolutionary genetics analysis &#40;MEGA&#41; was used for phylogenetic studies&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">At a 10&#37; threshold&#44; NGS-Sanger sequences from 17&#47;62 patients were phylogenetically related&#44; with a median bootstrap-value of 88&#37; &#40;IQR 83&#46;5&#8211;95&#46;5&#41;&#46; Association increased to 36&#47;62 sequences&#44; median bootstrap 94&#37; &#40;IQR 85&#46;5&#8211;98&#41;&#44; using a 15&#37; threshold&#46; Maximum association was at the 20&#37; threshold&#44; with 61&#47;62 sequences associated&#44; and a median bootstrap value of 99&#37; &#40;IQR 98&#8211;100&#41;&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">A safe method is presented to generate consensus sequences from HIV-NGS data at 20&#37; threshold&#44; which will prove useful for molecular epidemiological studies&#46;</p></span>"
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        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Generar una secuencia consenso a partir de los datos de secuenciaci&#243;n masiva obtenidos en estudios de resistencias a antiretrovirales&#44; que sea representativa de la secuencia Sanger y que sirva para estudios de epidemiolog&#237;a molecular&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Material y m&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">En 62 pacientes se obtuvo la secuencia de transcriptasa reversa-proteasa&#44; mediante Sanger &#40;Trugene-Siemens&#41;&#44; y NGS &#40;454GSJunior-Roche&#41;&#46; Las secuencias consenso NGS se generaron con Mesquite&#44; seleccionando umbrales 10&#37;&#44; 15&#37; y 20&#37;&#46; Para el estudio filogen&#233;tico se emple&#243; MEGA&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Utilizando el umbral 10&#37;&#44; 17&#47;62 pacientes presentaron secuencias pareadas NGS-Sanger&#44; con una mediana de <span class="elsevierStyleItalic">bootstrap</span> del 88&#37; &#40;IQR 83&#44;5-95&#44;5&#41;&#46; La asociaci&#243;n aumenta a 36&#47;62 pacientes y el <span class="elsevierStyleItalic">bootstrap</span>&#44; a 94&#37; &#40;IQR 85&#44;5-98&#41;&#44; y alcanza el m&#225;ximo al 20&#37; en 61&#47;62 pacientes&#44; <span class="elsevierStyleItalic">bootstrap</span> 99&#37; &#40;IQR 98-100&#41;&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusi&#243;n</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Mostramos un m&#233;todo seguro para generar secuencias consenso NGS para su uso en estudios de epidemiolog&#237;a molecular procesadas con umbral 20&#37;&#44; de f&#225;cil uso y aplicaci&#243;n en los servicios de microbiolog&#237;a cl&#237;nica&#46;</p></span>"
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        "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as&#58; Fern&#225;ndez-Caballero Rico J&#193;&#44; Chueca Porcuna N&#44; &#193;lvarez Est&#233;vez M&#44; Mosquera Guti&#233;rrez MM&#44; Marcos Maeso M&#193;&#44; Garc&#237;a F&#46; Validaci&#243;n de un m&#233;todo seguro y sencillo para la elaboraci&#243;n de secuencias consenso del virus de la inmunodeficiencia humana a partir de los datos de secuenciaci&#243;n masiva 454&#46; Enferm Infecc Microbiol Clin&#46; 2018&#59;36&#58;91&#8211;94&#46;</p>"
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          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Representation of phylogenetic trees in FigTree v&#46; 1&#46;4&#46;2&#44; formed by the Sanger and NGS sequences at different thresholds&#58; &#40;A&#41; NGS-10&#37;&#59; &#40;B&#41; NGS-15&#37;&#44; and &#40;C&#41; NGS-20&#37;&#46; The bootstrap values are shown according to colour&#46; A good association is 70&#37; and over&#46;</p>"
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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Bootscan of the Sanger sequence &#40;A&#41;&#44; NGS-10&#37; consensus sequence &#40;B&#41; and NGS-20&#37; consensus sequence &#40;C&#41;&#44; using the REGA HIV-1 Subtyping Tool v&#46; 3&#46;0&#46; In the Bootscan&#44; the HIV A subtype value is the same in the Sanger and NGS-20&#37; consensus sequence&#44; however&#44; a CRF03&#95;AB subtype can be seen in the NGS-10&#37; consensus sequence&#46;</p>"
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                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " colspan="7" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">HIV subtype</th></tr><tr title="table-row"><th class="td" title="table-head  " align="" valign="top" scope="col" style="border-bottom: 2px solid black">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">B&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">G&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">F&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">C&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">A&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">crf02&#95;AG&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th><th class="td" title="table-head  " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">crf03&#95;AB&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Sanger&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">NGS-10&#37;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">49&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">48&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="char" valign="top">0&nbsp;\t\t\t\t\t\t\n
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          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Distribution of HIV viral subtypes according to the Sanger and NGS consensus sequences at the different thresholds&#44; using the REGA HIV-1 Subtyping Tool v&#46; 3&#46;0&#46;</p>"
        ]
      ]
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