CovidV2, Pmc, Corpus, bibRecord, 000003

Selection of reliable reference genes for gene expression study in nasopharyngeal carcinoma

Identifieur interne : 000003 ( Pmc/Corpus ); précédent : 000002; suivant : 000004

Selection of reliable reference genes for gene expression study in nasopharyngeal carcinoma

Auteurs : Yi Guo ; Jia-Xin Chen ; Shu Yang ; Xu-Ping Fu ; Zheng Zhang ; Ke-He Chen ; Yan Huang ; Yao Li ; Yi Xie ; Yu-Min Mao

Source :

Acta Pharmacologica Sinica [ 1671-4083 ] ; 2010.

RBID : PMC:4003330

Abstract

Aim:

To construct a system for selecting reference genes (RGs) and to select the most optimal RGs for gene expression studies in nasopharyngeal carcinoma (NPC).

Methods:

The total RNAs from 20 NPC samples were each labeled with Cy5-dUTP. To create a common control, the total RNA from 15 nasopharyngeal phlogistic (NP) tissues was mixed and labeled via reverse transcription with Cy3-dUTP. cDNA microarrays containing 14 112 genes were then performed. A mathematical approach was constructed to screen stably expressed genes from the microarray data. Using this method, three genes (YARS, EIF3S7, and PFDN1) were selected as candidate RGs. Furthermore, 7 commonly used RGs (HPRT1, GAPDH, TBP, ACTB, B2M, G6PDH, and HBB) were selected as additional potential RGs. Real-time PCR was used to detect these 10 candidate genes' expression levels and the geNorm program was used to find the optimal RGs for NPC studies.

Results:

On the basis of the 10 candidate genes' expression stability level, geNorm analysis identified the optimal single RG (YARS or HPRT1) and the most suitable set of RGs (HPRT1, YARS, and EIF3S7) for NPC gene expression studies. In addition, this analysis determined that B2M, G6PDH, and HBB were not appropriate for use as RGs. Interestingly, ACTB was the least stable RG in our study, even though previous studies had indicated that it was one of the most stable RGs. Three novel candidate genes (YARS, EIF3S7, and PFDN1), which were selected from microarray data, were all identified as suitable RGs for NPC research. A RG-selecting system was then constructed, which combines microarray data analysis, a literature screen, real-time PCR, and bioinformatic analysis.

Conclusion:

We construct a RG-selecting system that helps find the optimal RGs. This process, applied to NPC research, determined the single RG (YARS or HPRT1) and the set of RGs (HPRT1, YARS, and EIF3S7) that are the most suitable internal controls.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4003330

DOI: 10.1038/aps.2010.115
PubMed: 21052085
PubMed Central: 4003330

Links to Exploration step

PMC:4003330

Le document en format XML

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<author><name sortKey="Guo, Yi" sort="Guo, Yi" uniqKey="Guo Y" first="Yi" last="Guo">Yi Guo</name>
<affiliation><nlm:aff id="aff1"><institution>State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University</institution>
, Shanghai 200433,<country>China</country>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Chen, Jia Xin" sort="Chen, Jia Xin" uniqKey="Chen J" first="Jia-Xin" last="Chen">Jia-Xin Chen</name>
<affiliation><nlm:aff id="aff2"><institution>Institute of Nasopharyngeal Carcinoma, the People's Hospital of Guangxi Zhuang Nationality Autonomous Region</institution>
, Nanning 530021,<country>China</country>
</nlm:aff>
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<author><name sortKey="Yang, Shu" sort="Yang, Shu" uniqKey="Yang S" first="Shu" last="Yang">Shu Yang</name>
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</nlm:aff>
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<author><name sortKey="Fu, Xu Ping" sort="Fu, Xu Ping" uniqKey="Fu X" first="Xu-Ping" last="Fu">Xu-Ping Fu</name>
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</nlm:aff>
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<author><name sortKey="Zhang, Zheng" sort="Zhang, Zheng" uniqKey="Zhang Z" first="Zheng" last="Zhang">Zheng Zhang</name>
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, Nanning 530021,<country>China</country>
</nlm:aff>
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<author><name sortKey="Chen, Ke He" sort="Chen, Ke He" uniqKey="Chen K" first="Ke-He" last="Chen">Ke-He Chen</name>
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<author><name sortKey="Huang, Yan" sort="Huang, Yan" uniqKey="Huang Y" first="Yan" last="Huang">Yan Huang</name>
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, Shanghai 200433,<country>China</country>
</nlm:aff>
</affiliation>
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<author><name sortKey="Li, Yao" sort="Li, Yao" uniqKey="Li Y" first="Yao" last="Li">Yao Li</name>
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, Shanghai 200433,<country>China</country>
</nlm:aff>
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<author><name sortKey="Xie, Yi" sort="Xie, Yi" uniqKey="Xie Y" first="Yi" last="Xie">Yi Xie</name>
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<author><name sortKey="Mao, Yu Min" sort="Mao, Yu Min" uniqKey="Mao Y" first="Yu-Min" last="Mao">Yu-Min Mao</name>
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<author><name sortKey="Guo, Yi" sort="Guo, Yi" uniqKey="Guo Y" first="Yi" last="Guo">Yi Guo</name>
<affiliation><nlm:aff id="aff1"><institution>State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University</institution>
, Shanghai 200433,<country>China</country>
</nlm:aff>
</affiliation>
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<author><name sortKey="Chen, Jia Xin" sort="Chen, Jia Xin" uniqKey="Chen J" first="Jia-Xin" last="Chen">Jia-Xin Chen</name>
<affiliation><nlm:aff id="aff2"><institution>Institute of Nasopharyngeal Carcinoma, the People's Hospital of Guangxi Zhuang Nationality Autonomous Region</institution>
, Nanning 530021,<country>China</country>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Yang, Shu" sort="Yang, Shu" uniqKey="Yang S" first="Shu" last="Yang">Shu Yang</name>
<affiliation><nlm:aff id="aff1"><institution>State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University</institution>
, Shanghai 200433,<country>China</country>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Fu, Xu Ping" sort="Fu, Xu Ping" uniqKey="Fu X" first="Xu-Ping" last="Fu">Xu-Ping Fu</name>
<affiliation><nlm:aff id="aff1"><institution>State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University</institution>
, Shanghai 200433,<country>China</country>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Zhang, Zheng" sort="Zhang, Zheng" uniqKey="Zhang Z" first="Zheng" last="Zhang">Zheng Zhang</name>
<affiliation><nlm:aff id="aff2"><institution>Institute of Nasopharyngeal Carcinoma, the People's Hospital of Guangxi Zhuang Nationality Autonomous Region</institution>
, Nanning 530021,<country>China</country>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Chen, Ke He" sort="Chen, Ke He" uniqKey="Chen K" first="Ke-He" last="Chen">Ke-He Chen</name>
<affiliation><nlm:aff id="aff2"><institution>Institute of Nasopharyngeal Carcinoma, the People's Hospital of Guangxi Zhuang Nationality Autonomous Region</institution>
, Nanning 530021,<country>China</country>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Huang, Yan" sort="Huang, Yan" uniqKey="Huang Y" first="Yan" last="Huang">Yan Huang</name>
<affiliation><nlm:aff id="aff1"><institution>State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University</institution>
, Shanghai 200433,<country>China</country>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Li, Yao" sort="Li, Yao" uniqKey="Li Y" first="Yao" last="Li">Yao Li</name>
<affiliation><nlm:aff id="aff1"><institution>State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University</institution>
, Shanghai 200433,<country>China</country>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Xie, Yi" sort="Xie, Yi" uniqKey="Xie Y" first="Yi" last="Xie">Yi Xie</name>
<affiliation><nlm:aff id="aff1"><institution>State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University</institution>
, Shanghai 200433,<country>China</country>
</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Mao, Yu Min" sort="Mao, Yu Min" uniqKey="Mao Y" first="Yu-Min" last="Mao">Yu-Min Mao</name>
<affiliation><nlm:aff id="aff1"><institution>State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University</institution>
, Shanghai 200433,<country>China</country>
</nlm:aff>
</affiliation>
</author>
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<series><title level="j">Acta Pharmacologica Sinica</title>
<idno type="ISSN">1671-4083</idno>
<idno type="eISSN">1745-7254</idno>
<imprint><date when="2010">2010</date>
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<front><div type="abstract" xml:lang="en"><sec><title>Aim:</title>
<p>To construct a system for selecting reference genes (RGs) and to select the most optimal RGs for gene expression studies in nasopharyngeal carcinoma (NPC).</p>
</sec>
<sec><title>Methods:</title>
<p>The total RNAs from 20 NPC samples were each labeled with Cy5-dUTP. To create a common control, the total RNA from 15 nasopharyngeal phlogistic (NP) tissues was mixed and labeled via reverse transcription with Cy3-dUTP. cDNA microarrays containing 14 112 genes were then performed. A mathematical approach was constructed to screen stably expressed genes from the microarray data. Using this method, three genes (<italic>YARS</italic>
, <italic>EIF3S7</italic>
, and <italic>PFDN1</italic>
) were selected as candidate RGs. Furthermore, 7 commonly used RGs (<italic>HPRT1</italic>
, <italic>GAPDH</italic>
, <italic>TBP</italic>
, <italic>ACTB</italic>
, <italic>B2M</italic>
, <italic>G6PDH</italic>
, and <italic>HB</italic>
B) were selected as additional potential RGs. Real-time PCR was used to detect these 10 candidate genes' expression levels and the geNorm program was used to find the optimal RGs for NPC studies.</p>
</sec>
<sec><title>Results:</title>
<p>On the basis of the 10 candidate genes' expression stability level, geNorm analysis identified the optimal single RG (<italic>YARS</italic>
 or <italic>HPRT1</italic>
) and the most suitable set of RGs (<italic>HPRT1</italic>
, <italic>YARS</italic>
, and <italic>EIF3S7</italic>
) for NPC gene expression studies. In addition, this analysis determined that B2M, G6PDH, and HBB were not appropriate for use as RGs. Interestingly, ACTB was the least stable RG in our study, even though previous studies had indicated that it was one of the most stable RGs. Three novel candidate genes (<italic>YARS</italic>
, <italic>EIF3S7</italic>
, and <italic>PFDN1</italic>
), which were selected from microarray data, were all identified as suitable RGs for NPC research. A RG-selecting system was then constructed, which combines microarray data analysis, a literature screen, real-time PCR, and bioinformatic analysis.</p>
</sec>
<sec><title>Conclusion:</title>
<p>We construct a RG-selecting system that helps find the optimal RGs. This process, applied to NPC research, determined the single RG (<italic>YARS</italic>
 or <italic>HPRT1</italic>
) and the set of RGs (<italic>HPRT1</italic>
, <italic>YARS</italic>
, and <italic>EIF3S7</italic>
) that are the most suitable internal controls.</p>
</sec>
</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">Acta Pharmacol Sin</journal-id>
<journal-id journal-id-type="iso-abbrev">Acta Pharmacol. Sin</journal-id>
<journal-title-group><journal-title>Acta Pharmacologica Sinica</journal-title>
</journal-title-group>
<issn pub-type="ppub">1671-4083</issn>
<issn pub-type="epub">1745-7254</issn>
<publisher><publisher-name>Nature Publishing Group</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">21052085</article-id>
<article-id pub-id-type="pmc">4003330</article-id>
<article-id pub-id-type="pii">aps2010115</article-id>
<article-id pub-id-type="doi">10.1038/aps.2010.115</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Original Article</subject>
</subj-group>
</article-categories>
<title-group><article-title>Selection of reliable reference genes for gene expression study in nasopharyngeal carcinoma</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Guo</surname>
<given-names>Yi</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
<xref ref-type="author-notes" rid="note1"><sup>#</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Chen</surname>
<given-names>Jia-xin</given-names>
</name>
<xref ref-type="aff" rid="aff2">2</xref>
<xref ref-type="author-notes" rid="note1"><sup>#</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Yang</surname>
<given-names>Shu</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Fu</surname>
<given-names>Xu-ping</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Zhang</surname>
<given-names>Zheng</given-names>
</name>
<xref ref-type="aff" rid="aff2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Chen</surname>
<given-names>Ke-he</given-names>
</name>
<xref ref-type="aff" rid="aff2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Huang</surname>
<given-names>Yan</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Li</surname>
<given-names>Yao</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Xie</surname>
<given-names>Yi</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Mao</surname>
<given-names>Yu-min</given-names>
</name>
<xref ref-type="aff" rid="aff1">1</xref>
<xref ref-type="corresp" rid="caf1">*</xref>
</contrib>
<aff id="aff1"><label>1</label>
<institution>State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Science, Fudan University</institution>
, Shanghai 200433,<country>China</country>
</aff>
<aff id="aff2"><label>2</label>
<institution>Institute of Nasopharyngeal Carcinoma, the People's Hospital of Guangxi Zhuang Nationality Autonomous Region</institution>
, Nanning 530021,<country>China</country>
</aff>
</contrib-group>
<author-notes><corresp id="caf1"><label>*</label>
E-mail <email>yaoli@fudan.edu.cn</email>
</corresp>
<fn fn-type="present-address" id="note1"><label>3</label>
<p>These authors contributed equally to this work.</p>
</fn>
</author-notes>
<pub-date pub-type="ppub"><month>11</month>
<year>2010</year>
</pub-date>
<pub-date pub-type="epub"><day>05</day>
<month>11</month>
<year>2010</year>
</pub-date>
<volume>31</volume>
<issue>11</issue>
<fpage>1487</fpage>
<lpage>1494</lpage>
<history><date date-type="received"><day>04</day>
<month>03</month>
<year>2010</year>
</date>
<date date-type="accepted"><day>07</day>
<month>07</month>
<year>2010</year>
</date>
</history>
<permissions><copyright-statement>Copyright © 2010 CPS and SIMM</copyright-statement>
<copyright-year>2010</copyright-year>
<copyright-holder>CPS and SIMM</copyright-holder>
</permissions>
<abstract><sec><title>Aim:</title>
<p>To construct a system for selecting reference genes (RGs) and to select the most optimal RGs for gene expression studies in nasopharyngeal carcinoma (NPC).</p>
</sec>
<sec><title>Methods:</title>
<p>The total RNAs from 20 NPC samples were each labeled with Cy5-dUTP. To create a common control, the total RNA from 15 nasopharyngeal phlogistic (NP) tissues was mixed and labeled via reverse transcription with Cy3-dUTP. cDNA microarrays containing 14 112 genes were then performed. A mathematical approach was constructed to screen stably expressed genes from the microarray data. Using this method, three genes (<italic>YARS</italic>
, <italic>EIF3S7</italic>
, and <italic>PFDN1</italic>
) were selected as candidate RGs. Furthermore, 7 commonly used RGs (<italic>HPRT1</italic>
, <italic>GAPDH</italic>
, <italic>TBP</italic>
, <italic>ACTB</italic>
, <italic>B2M</italic>
, <italic>G6PDH</italic>
, and <italic>HB</italic>
B) were selected as additional potential RGs. Real-time PCR was used to detect these 10 candidate genes' expression levels and the geNorm program was used to find the optimal RGs for NPC studies.</p>
</sec>
<sec><title>Results:</title>
<p>On the basis of the 10 candidate genes' expression stability level, geNorm analysis identified the optimal single RG (<italic>YARS</italic>
 or <italic>HPRT1</italic>
) and the most suitable set of RGs (<italic>HPRT1</italic>
, <italic>YARS</italic>
, and <italic>EIF3S7</italic>
) for NPC gene expression studies. In addition, this analysis determined that B2M, G6PDH, and HBB were not appropriate for use as RGs. Interestingly, ACTB was the least stable RG in our study, even though previous studies had indicated that it was one of the most stable RGs. Three novel candidate genes (<italic>YARS</italic>
, <italic>EIF3S7</italic>
, and <italic>PFDN1</italic>
), which were selected from microarray data, were all identified as suitable RGs for NPC research. A RG-selecting system was then constructed, which combines microarray data analysis, a literature screen, real-time PCR, and bioinformatic analysis.</p>
</sec>
<sec><title>Conclusion:</title>
<p>We construct a RG-selecting system that helps find the optimal RGs. This process, applied to NPC research, determined the single RG (<italic>YARS</italic>
 or <italic>HPRT1</italic>
) and the set of RGs (<italic>HPRT1</italic>
, <italic>YARS</italic>
, and <italic>EIF3S7</italic>
) that are the most suitable internal controls.</p>
</sec>
</abstract>
<kwd-group><kwd>Gene expression</kwd>
<kwd>nasopharyngeal carcinoma</kwd>
<kwd>reference gene</kwd>
<kwd>cDNA microarrays</kwd>
<kwd>real-time PCR</kwd>
</kwd-group>
</article-meta>
</front>
</pmc>
</record>

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Selection of reliable reference genes for gene expression study in nasopharyngeal carcinoma

Selection of reliable reference genes for gene expression study in nasopharyngeal carcinoma

Source :

Abstract

Links to Exploration step

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