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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Scalable Transcriptional Analysis Routine—Multiplexed Quantitative Real-Time Polymerase Chain Reaction Platform for Gene Expression Analysis and Molecular Diagnostics</title>
<author><name sortKey="Garcia, Elizabeth P" sort="Garcia, Elizabeth P" uniqKey="Garcia E" first="Elizabeth P." last="Garcia">Elizabeth P. Garcia</name>
<affiliation><nlm:aff id="N0x31f1be0N0x49e9fe8"></nlm:aff>
</affiliation>
</author>
<author><name sortKey="Dowding, Lori A" sort="Dowding, Lori A" uniqKey="Dowding L" first="Lori A." last="Dowding">Lori A. Dowding</name>
<affiliation><nlm:aff id="N0x31f1be0N0x49e9fe8"></nlm:aff>
</affiliation>
</author>
<author><name sortKey="Stanton, Lawrence W" sort="Stanton, Lawrence W" uniqKey="Stanton L" first="Lawrence W." last="Stanton">Lawrence W. Stanton</name>
<affiliation><nlm:aff id="N0x31f1be0N0x49e9fe8"></nlm:aff>
</affiliation>
</author>
<author><name sortKey="Slepnev, Vladimir I" sort="Slepnev, Vladimir I" uniqKey="Slepnev V" first="Vladimir I." last="Slepnev">Vladimir I. Slepnev</name>
<affiliation><nlm:aff id="N0x31f1be0N0x49e9fe8"></nlm:aff>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PMC</idno>
<idno type="pmid">16237214</idno>
<idno type="pmc">1888488</idno>
<idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1888488</idno>
<idno type="RBID">PMC:1888488</idno>
<date when="2005">2005</date>
<idno type="wicri:Area/Pmc/Corpus">000148</idno>
<idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000148</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Scalable Transcriptional Analysis Routine—Multiplexed Quantitative Real-Time Polymerase Chain Reaction Platform for Gene Expression Analysis and Molecular Diagnostics</title>
<author><name sortKey="Garcia, Elizabeth P" sort="Garcia, Elizabeth P" uniqKey="Garcia E" first="Elizabeth P." last="Garcia">Elizabeth P. Garcia</name>
<affiliation><nlm:aff id="N0x31f1be0N0x49e9fe8"></nlm:aff>
</affiliation>
</author>
<author><name sortKey="Dowding, Lori A" sort="Dowding, Lori A" uniqKey="Dowding L" first="Lori A." last="Dowding">Lori A. Dowding</name>
<affiliation><nlm:aff id="N0x31f1be0N0x49e9fe8"></nlm:aff>
</affiliation>
</author>
<author><name sortKey="Stanton, Lawrence W" sort="Stanton, Lawrence W" uniqKey="Stanton L" first="Lawrence W." last="Stanton">Lawrence W. Stanton</name>
<affiliation><nlm:aff id="N0x31f1be0N0x49e9fe8"></nlm:aff>
</affiliation>
</author>
<author><name sortKey="Slepnev, Vladimir I" sort="Slepnev, Vladimir I" uniqKey="Slepnev V" first="Vladimir I." last="Slepnev">Vladimir I. Slepnev</name>
<affiliation><nlm:aff id="N0x31f1be0N0x49e9fe8"></nlm:aff>
</affiliation>
</author>
</analytic>
<series><title level="j">The Journal of molecular diagnostics : JMD</title>
<idno type="ISSN">1525-1578</idno>
<imprint><date when="2005">2005</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass></textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en"><p>We report the development of a new technology for simultaneous quantitative detection of multiple targets in a single sample. Scalable transcriptional analysis routine (STAR) represents a novel integration of reverse transcriptase-polymerase chain reaction and capillary electrophoresis that allows detection of dozens of gene transcripts in a multiplexed format using amplicon size as an identifier for each target. STAR demonstrated similar or better sensitivity and precision compared to two commonly used methods, SYBR Green-based and TaqMan probe-based real-time reverse transcriptase-polymerase chain reaction. STAR can be used as a flexible platform for building a variety of applications to monitor gene expression, from single gene assays to assays analyzing the expression level of multiple genes. Using severe acute respiratory syndrome (SARS) corona virus as a model system, STAR technology detected single copies of the viral genome in a two-gene multiplex. Blinded studies using RNA extracted from various tissues of a SARS-infected individual showed that STAR correctly identified all samples containing SARS virus and yielded negative results for non-SARS control samples. Using alternate priming strategies, STAR technology can be adapted to transcriptional profiling studies without requiring <italic>a priori</italic>
sequence information. Thus, STAR technology offers a flexible platform for development of highly multiplexed assays in gene expression analysis and molecular diagnostics.</p>
</div>
</front>
</TEI>
<pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<front><journal-meta><journal-id journal-id-type="nlm-ta">J Mol Diagn</journal-id>
<journal-title>The Journal of molecular diagnostics : JMD</journal-title>
<issn pub-type="ppub">1525-1578</issn>
<publisher><publisher-name>American Society for Investigative Pathology</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">16237214</article-id>
<article-id pub-id-type="pmc">1888488</article-id>
<article-id pub-id-type="publisher-id">6327</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Regular Articles</subject>
</subj-group>
</article-categories>
<title-group><article-title>Scalable Transcriptional Analysis Routine—Multiplexed Quantitative Real-Time Polymerase Chain Reaction Platform for Gene Expression Analysis and Molecular Diagnostics</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Garcia</surname>
<given-names>Elizabeth P.</given-names>
</name>
<xref ref-type="aff" rid="N0x31f1be0N0x49e9fe8">*†</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Dowding</surname>
<given-names>Lori A.</given-names>
</name>
<xref ref-type="aff" rid="N0x31f1be0N0x49e9fe8">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Stanton</surname>
<given-names>Lawrence W.</given-names>
</name>
<xref ref-type="aff" rid="N0x31f1be0N0x49e9fe8">‡</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Slepnev</surname>
<given-names>Vladimir I.</given-names>
</name>
<xref ref-type="aff" rid="N0x31f1be0N0x49e9fe8">*†</xref>
</contrib>
<aff id="N0x31f1be0N0x49e9fe8">From Primera BioSystems,<label>†</label>
Providence, Rhode Island; Sention,<label>*</label>
Providence, Rhode Island; and Genome Institute of Singapore,<label>‡</label>
Singapore, Singapore</aff>
</contrib-group>
<author-notes><fn fn-type="corresp"><p>Address reprint requests to Vladimir Slepnev, 4 Richmond Sq., Providence, RI 02906. E-mail: <email>vslepnev@primerabio.com</email>
.</p>
</fn>
</author-notes>
<pub-date pub-type="ppub"><month>10</month>
<year>2005</year>
</pub-date>
<volume>7</volume>
<issue>4</issue>
<fpage>444</fpage>
<lpage>454</lpage>
<history><date date-type="accepted"><day>3</day>
<month>5</month>
<year>2005</year>
</date>
</history>
<permissions><copyright-statement>Copyright © American Society for Investigative Pathology and the Association for Molecular Pathology</copyright-statement>
<copyright-year>2005</copyright-year>
</permissions>
<abstract><p>We report the development of a new technology for simultaneous quantitative detection of multiple targets in a single sample. Scalable transcriptional analysis routine (STAR) represents a novel integration of reverse transcriptase-polymerase chain reaction and capillary electrophoresis that allows detection of dozens of gene transcripts in a multiplexed format using amplicon size as an identifier for each target. STAR demonstrated similar or better sensitivity and precision compared to two commonly used methods, SYBR Green-based and TaqMan probe-based real-time reverse transcriptase-polymerase chain reaction. STAR can be used as a flexible platform for building a variety of applications to monitor gene expression, from single gene assays to assays analyzing the expression level of multiple genes. Using severe acute respiratory syndrome (SARS) corona virus as a model system, STAR technology detected single copies of the viral genome in a two-gene multiplex. Blinded studies using RNA extracted from various tissues of a SARS-infected individual showed that STAR correctly identified all samples containing SARS virus and yielded negative results for non-SARS control samples. Using alternate priming strategies, STAR technology can be adapted to transcriptional profiling studies without requiring <italic>a priori</italic>
sequence information. Thus, STAR technology offers a flexible platform for development of highly multiplexed assays in gene expression analysis and molecular diagnostics.</p>
</abstract>
</article-meta>
</front>
<floats-wrap><fig position="float" id="F1-6327"><label>Figure 1</label>
<caption><p>Description of STAR technology. <bold>A:</bold>
Diagrammatic representation of STAR technology. See text for detailed explanation. Abbreviations: GSP, gene-specific primer; C<sub>T</sub>
, cycle threshold. To illustrate the process, three genes (arc, homer1a, and zif268) were amplified from 100 ng of rat brain total RNA in a multiplex format using 0.5 μmol/L of each gene-specific primer. Forward primers were fluorescently labeled. Aliquots collected between cycles 12 and 35 were separated by CE and analyzed by GeneScan version 3.7.1 generating electropherograms. <bold>B:</bold>
Successive electropherograms from cycles 19 through 22 are shown. Peaks representing arc, homer1a, and zif268 are marked with an <bold>asterisk</bold>
. Small repeating peaks represent DNA molecular size markers. <bold>C:</bold>
Amplification curves for arc (<bold>filled triangles</bold>
), homer1a (<bold>filled circles</bold>
), and zif268 (<bold>filled squares</bold>
) were reconstructed by plotting the area under each peak against cycle number.</p>
</caption>
<graphic xlink:href="zjx0040563270001"></graphic>
</fig>
<table-wrap position="float" id="T1-6327"><label>Table 1</label>
<caption><p>Nucleic Acid Sequence of Primers Used in This Study</p>
</caption>
<table frame="hsides" rules="groups"><thead><tr><th colspan="1" rowspan="1" align="center" valign="bottom">Gene</th>
<th colspan="1" rowspan="1" align="center" valign="bottom">Application</th>
<th colspan="1" rowspan="1" align="center" valign="bottom">Primer sequence</th>
</tr>
</thead>
<tbody><tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>Homer1a</italic>
<xref rid="TFN1-1-6327" ref-type="other">*</xref>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">TaqMan/STAR/SYBR</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-CTGCTCCAAAGGAAAGCCTTGC-3</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-AAACAACCTTCAATGCTGACGG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">TaqMan probe</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]CGTCCTCTGTGGCACCTCTGTGGGC[TAMRA]−3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>zif268</italic>
<xref rid="TFN1-1-6327" ref-type="other">*</xref>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">TaqMan/STAR/SYBR</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-GTTACCTACTGAGTAGGCGG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-TGAAGGATACACACCACATATC-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">TaqMan probe</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]CGCATTCAATGTGTTTATAAGCCA[TAMRA]-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>arc</italic>
<xref rid="TFN1-1-6327" ref-type="other">*</xref>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">TaqMan/STAR/SYBR</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-CCGACCTGTGCAACCCTTTC-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-GCAGATTGGTAAGTGCCGAGC-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">TaqMan probe</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]TGCTTGGACACTTCGGTCAACAGATGCC[TAMRA]-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>L-HA</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">Detection of artificial transcripts</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]CCATACGACGTCCCAGACTA-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>pcDNA3L</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">Detection of artificial transcripts</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-AGCTCTAGCATTTAGGTGACACTA-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>inhibin</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">12plex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-CACACGGGGCTCGACAGGAAG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]CCCCCAGATGACAGCACCAGAAG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>BMP14</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">12plex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]ACTCCATCGGGCGCTTCTTTAG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-CAGGGAGCCGTAGTGGGTAGTTCT-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>DGK</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">12plex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]TCTGCCGAGCCCACATTGAG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-GGCGTCCAGGAAACACCACTTG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>actin</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">12plex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]CACCCACACTGTGCCCAT-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-TGGTGGTGAAGCTGTAGC-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>LDH</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">12plex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]AGCCCCGACTGCACCATCATC-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-GTAACGAAACCGAGCAGAATCCAG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>PKC</italic>
γ</td>
<td colspan="1" rowspan="1" align="left" valign="top">12plex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]TGCAGCCTCCTCCAGAAGTTTGA-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-GTCCTGGGCTGGCACCGAAGAA-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>EGR3</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">12plex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-CCGCAGCGACCACCTCACTAC-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]CACCCCCTTTCTCCGACTTCTTC-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>18S rRNA</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">12plex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]CGGCTACCACATCCAAGGAA-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-GCTGGAATTACCGCGGCT-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>PIPK</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">12plex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-CACCCCACCGTCCTTTGAG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]ACCCCCACACCGCACACTG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>Nell2</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">12plex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]GACAACACAACTGCGACAAAAATG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-GGCAGGTTAACACAGCGGGAGTAG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>arc</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">12plex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-CACCCTGCAGCCCAAGTTC-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]GCCCCAGCTCAATCAAGTCCTA-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>NSE</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">12plex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-CGGCACGGGCAGGATGAG-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]TGGGGCAGCCGAGAAGGAC-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>ST1</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">Alternative priming</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]CGCTCGTAGTCGAACGCCTAACCA-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>ST2</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">Alternative priming</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM, VIC, or NED]CGACGTATGCGTAACCCGTATCGT-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>UT2</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">Alternative priming</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-GCGGCGCCTATCTTACTAT</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>ST1-dT14-VN</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">Alternative priming</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-CGCTCGTAGTCGAACGCCTAACCATTTTTTTTTTTTTTVN-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>ST2-dT14-VN</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">Alternative priming</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-CGACGTATGCGTAACCCGTATCGTTTTTTTTTTTTTTTVN-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>UT2-HA</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">Alternative priming</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-GCGGCGCCTATCTTACTATCCAGACTA-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>Rep1B</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">SARS multiplex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-AAGCCTCCCATTAGTTTTCCATTA-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]CACAACAGCATCACCATAGTCACC-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"><italic>S</italic>
</td>
<td colspan="1" rowspan="1" align="left" valign="top">SARS multiplex</td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-ACGTCAGCTGCAGCCTATTTTGTT-3′</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top"></td>
<td colspan="1" rowspan="1" align="left" valign="top">5′-[FAM]TTGTCCTGGCGCTATTTGTCTTAC-3′</td>
</tr>
</tbody>
</table>
<table-wrap-foot><fn id="TFN1-1-6327"><label>*</label>
<p>For STAR experiments, the first oligo listed is FAM labeled; for SYBR and TaqMan, oligos are unlabeled. </p>
</fn>
<fn><p>FAM, 6-carboxyfluorescein; TAMRA, 6-carboxytetramethylrhodamine. </p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig position="float" id="F2-6327"><label>Figure 2</label>
<caption><p>STAR technology is comparable to TaqMan probe-based and SYBR Green-based real-time RT-PCR. Detection of endogenous levels of <italic>arc</italic>
(<bold>a</bold>
), <italic>homer1a</italic>
(<bold>b</bold>
), and <italic>zif268</italic>
(<bold>c</bold>
) in rat brain total RNA were assessed by three real-time PCR methods: SYBR (<bold>circles</bold>
), TaqMan (<bold>triangles</bold>
), and STAR either as an individual reaction (<bold>squares</bold>
) or as part of a multiplex reaction (<bold>diamonds</bold>
). C<sub>T</sub>
s were determined from PCR amplifications performed from twofold serially diluted total rat brain RNA (400 to 0.78 ng) and plotted. For SYBR and TaqMan, C<sub>T</sub>
s were calculated using Bio-Rad ICycler software (Hercules, CA).</p>
</caption>
<graphic xlink:href="zjx0040563270002"></graphic>
</fig>
<table-wrap position="float" id="T2-6327"><label>Table 2</label>
<caption><p>Comparison of Three Real-Time Methods for Gene Expression Analysis</p>
</caption>
<table frame="hsides" rules="groups"><thead><tr><th colspan="1" rowspan="1" align="center" valign="bottom"></th>
<th colspan="3" rowspan="1" align="center" valign="bottom"><italic>homer1a</italic>
<hr></hr>
</th>
<th colspan="3" rowspan="1" align="center" valign="bottom"><italic>zif268</italic>
<hr></hr>
</th>
<th colspan="3" rowspan="1" align="center" valign="bottom"><italic>arc</italic>
<hr></hr>
</th>
</tr>
<tr><th colspan="1" rowspan="1" align="left" valign="bottom"></th>
<th colspan="1" rowspan="1" align="center" valign="bottom">Slope</th>
<th colspan="1" rowspan="1" align="center" valign="bottom">Efficiency</th>
<th colspan="1" rowspan="1" align="center" valign="bottom"><italic>r</italic>
<sup>2</sup>
</th>
<th colspan="1" rowspan="1" align="center" valign="bottom">Slope</th>
<th colspan="1" rowspan="1" align="center" valign="bottom">Efficiency</th>
<th colspan="1" rowspan="1" align="center" valign="bottom"><italic>r</italic>
<sup>2</sup>
</th>
<th colspan="1" rowspan="1" align="center" valign="bottom">Slope</th>
<th colspan="1" rowspan="1" align="center" valign="bottom">Efficiency</th>
<th colspan="1" rowspan="1" align="center" valign="bottom">r<sup>2</sup>
</th>
</tr>
</thead>
<tbody><tr><td colspan="1" rowspan="1" align="left" valign="top">TaqMan</td>
<td colspan="1" rowspan="1" align="center" valign="top">−3.46 ± 0.05</td>
<td colspan="1" rowspan="1" align="center" valign="top">94.33 ± 1.8</td>
<td colspan="1" rowspan="1" align="char" char="." valign="top">0.998</td>
<td colspan="1" rowspan="1" align="center" valign="top">−3.45 ± 0.15</td>
<td colspan="1" rowspan="1" align="center" valign="top">94.94 ± 5.4</td>
<td colspan="1" rowspan="1" align="char" char="." valign="top">0.996</td>
<td colspan="1" rowspan="1" align="center" valign="top">−4.13 ± 0.10</td>
<td colspan="1" rowspan="1" align="center" valign="top">74.73 ± 2.4</td>
<td colspan="1" rowspan="1" align="char" char="." valign="top">0.995</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top">SYBR</td>
<td colspan="1" rowspan="1" align="center" valign="top">−3.21 ± 0.16</td>
<td colspan="1" rowspan="1" align="center" valign="top">104.8 ± 7.3</td>
<td colspan="1" rowspan="1" align="char" char="." valign="top">0.981</td>
<td colspan="1" rowspan="1" align="center" valign="top">−3.49 ± 0.08</td>
<td colspan="1" rowspan="1" align="center" valign="top">93.56 ± 3.0</td>
<td colspan="1" rowspan="1" align="char" char="." valign="top">0.986</td>
<td colspan="1" rowspan="1" align="center" valign="top">−3.45 ± 0.37</td>
<td colspan="1" rowspan="1" align="center" valign="top">94.88 ± 14</td>
<td colspan="1" rowspan="1" align="char" char="." valign="top">0.878</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top">STAR single</td>
<td colspan="1" rowspan="1" align="center" valign="top">−3.79 ± 0.09</td>
<td colspan="1" rowspan="1" align="center" valign="top">83.41 ± 2.6</td>
<td colspan="1" rowspan="1" align="char" char="." valign="top">0.996</td>
<td colspan="1" rowspan="1" align="center" valign="top">−3.65 ± 0.07</td>
<td colspan="1" rowspan="1" align="center" valign="top">88.07 ± 2.4</td>
<td colspan="1" rowspan="1" align="char" char="." valign="top">0.997</td>
<td colspan="1" rowspan="1" align="center" valign="top">−3.45 ± 0.09</td>
<td colspan="1" rowspan="1" align="center" valign="top">95.10 ± 3.3</td>
<td colspan="1" rowspan="1" align="char" char="." valign="top">0.997</td>
</tr>
<tr><td colspan="1" rowspan="1" align="left" valign="top">STAR multiplex</td>
<td colspan="1" rowspan="1" align="center" valign="top">−3.61 ± 0.11</td>
<td colspan="1" rowspan="1" align="center" valign="top">89.17 ± 3.8</td>
<td colspan="1" rowspan="1" align="char" char="." valign="top">0.992</td>
<td colspan="1" rowspan="1" align="center" valign="top">−3.73 ± 0.07</td>
<td colspan="1" rowspan="1" align="center" valign="top">85.34 ± 2.3</td>
<td colspan="1" rowspan="1" align="char" char="." valign="top">0.997</td>
<td colspan="1" rowspan="1" align="center" valign="top">−3.43 ± 0.06</td>
<td colspan="1" rowspan="1" align="center" valign="top">95.78 ± 2.4</td>
<td colspan="1" rowspan="1" align="char" char="." valign="top">0.995</td>
</tr>
</tbody>
</table>
</table-wrap>
<fig position="float" id="F3-6327"><label>Figure 3</label>
<caption><p>STAR is sensitive and reproducible. <bold>A:</bold>
Artificial transcripts were 10-fold serially diluted from 3,000,000 to 3 copies in <italic>E. coli</italic>
tRNA (20 μg/ml) and amplified as a three-gene multiplex STAR assay using (FAM)L-HA and (FAM)pcDNA3L primers. C<sub>T</sub>
versus copy number plots are shown for <italic>VS31</italic>
(<bold>diamonds</bold>
), <italic>VS32</italic>
(<bold>squares</bold>
), and <italic>VS85</italic>
(<bold>triangles</bold>
). Insufficient data points were obtained for <italic>VS31</italic>
and <italic>VS85</italic>
to allow C<sub>T</sub>
calculation at three copies. <italic>R</italic>
<sup>2</sup>
values were greater than 0.99. Amplification efficiency = 10<sup>(−1/slope)</sup>
− 1. <bold>B:</bold>
To demonstrate reproducibility, four samples, each containing 300 copies of artificial transcripts <italic>VS31</italic>
, <italic>VS32</italic>
, and <italic>VS85</italic>
in a background of <italic>E. coli</italic>
tRNA (20 μg/ml), were multiplex amplified as above. Amplification curves for <italic>VS32</italic>
are represented by <bold>open circles</bold>
, <bold>squares</bold>
, <bold>triangles</bold>
, and <bold>diamonds</bold>
.</p>
</caption>
<graphic xlink:href="zjx0040563270003"></graphic>
</fig>
<fig position="float" id="F4-6327"><label>Figure 4</label>
<caption><p>Multiplex amplification of 12 endogenous genes by STAR technology. Twelve endogenous genes were multiplex amplified using gene-specific primers from 400 ng of total rat brain RNA in a one-step STAR protocol. One of each primer pair was fluorescently labeled. Aliquots from cycles 2 to 33 were analyzed by CE to generate amplification curves shown. Abbreviations and symbols: <italic>18S</italic>
, <bold>dark blue closed squares</bold>
; <italic>actin</italic>
, <bold>purple closed squares</bold>
; <italic>BMP</italic>
, <bold>orange filled circles</bold>
; <italic>inhibin</italic>
, <bold>black closed squares</bold>
; <italic>PKC</italic>
, <bold>green closed circles</bold>
; <italic>LDH</italic>
, <bold>red closed triangles</bold>
, <italic>DGK</italic>
, <bold>purple open squares</bold>
; <italic>EGR3</italic>
, <bold>orange open circles</bold>
; <italic>arc</italic>
, <bold>blue open squares</bold>
; <italic>PIPK</italic>
, <bold>green open circles</bold>
; <italic>Nell2</italic>
, <bold>orange open triangles</bold>
; <italic>NSE</italic>
, <bold>black open squares</bold>
.</p>
</caption>
<graphic xlink:href="zjx0040563270004"></graphic>
</fig>
<fig position="float" id="F5-6327"><label>Figure 5</label>
<caption><p>Alternative priming strategy using two sequence tags. <bold>A:</bold>
Schematic representation depicting the incorporation of two sequence tags during RT-PCR. Incorporation of sample-specific sequence tags during RT is followed by incorporation of a second sequence tag during second strand synthesis. PCR then proceeds using three primers, each of the sample-specific reverse sequence tags fluorescently labeled, and the common forward sequence tag. Aliquots are collected, separated, and analyzed by CE followed by analysis of relevant fragments. <bold>B:</bold>
Total rat brain RNA samples (1.75 μg) spiked with 100 pg of <italic>VS31</italic>
(<bold>top</bold>
) or unspiked (<bold>bottom</bold>
) were separately reverse transcribed using sample-specific sequence tags (ST1-dT14-VN and ST2-dT14-VN) followed by RNA hydrolysis, purification, and sample mixing. Second strand synthesis was performed using UT2-HA followed by purification. Fragments were then amplified using FAM-ST1, ROX-ST2, and UT2. Aliquots were collected, separated by CE, and analyzed to generate the electropherograms shown. <bold>C:</bold>
Total rat brain RNA (1.75 μg) was processed by STAR as described in <bold>B</bold>
except that for PCR amplification NED-ST2 replaced ROX-ST2 (<bold>top panel</bold>
) and VIC-ST2 replaced ROX-ST2 (<bold>bottom</bold>
). <bold>D:</bold>
Comparison of signal generated from 50 and 75 pg of input transcript. Two analytes were prepared in a background of 1.75 μg of total rat brain RNA. Analyte 1 was spiked with 50 pg of <italic>VS31</italic>
and 50 pg of <italic>VS85</italic>
. Analyte 2 was spiked with 50 pg of <italic>VS31</italic>
and 75 pg of <italic>VS85</italic>
. Each analyte was reverse transcribed separately using sample-specific sequence ST1dT14-VN or ST2dT14-VN generating cDNAs that were sequence tagged with either ST1 (analyte 1) or ST2 (analyte 2). Resulting cDNAs from both analytes were pooled and purified. Second strand was then synthesized using a forward sequence tag, UT2-HA. Again, excess primer was removed. Multiplex real-time PCR was performed using three primers, UT2, ROX-labeled ST1, and FAM-labeled ST2. Aliquots were taken from cycles 20 to 43 and analyzed by CE.</p>
</caption>
<graphic xlink:href="zjx0040563270005"></graphic>
</fig>
<fig position="float" id="F6-6327"><label>Figure 6</label>
<caption><p>Detection of purified SARS-CoV RNA spiked into human biological samples. Samples were 10-fold serially diluted from their original concentration to <10 copies per reaction and amplified by one-step multiplex RT-PCR STAR protocol for the <italic>S</italic>
and <italic>Rep1B</italic>
genes. Aliquots from cycles 20 to 43 were analyzed by CE to generate amplification curves. Data for the <italic>S</italic>
gene are shown for stool-derived samples (<bold>A</bold>
) [200,000 (<bold>filled squares</bold>
), 20,000 (<bold>open squares</bold>
), 2000 (<bold>filled triangles</bold>
), 200 (<bold>filled circles</bold>
), and 20 (<bold>open circles</bold>
) copies] or sputum-derived samples (<bold>B</bold>
) [56,000 (<bold>filled squares</bold>
), 5600 (<bold>open squares</bold>
), 560 (<bold>filled circles</bold>
), 56 (<bold>open circles</bold>
), and 5.6 (<bold>filled triangles</bold>
) copies]. <bold>Insets</bold>
: C<sub>T</sub>
versus copy number graphs derived from data in <bold>A</bold>
and <bold>B</bold>
.</p>
</caption>
<graphic xlink:href="zjx0040563270006"></graphic>
</fig>
</floats-wrap>
</pmc>
</record>
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