Evaluation of reference genes for real-time quantitative PCR studies in Candida glabrata following azole treatment
Identifieur interne : 000B72 ( Main/Exploration ); précédent : 000B71; suivant : 000B73Evaluation of reference genes for real-time quantitative PCR studies in Candida glabrata following azole treatment
Auteurs : Qingdi Quentin Li [États-Unis] ; Jeff Skinner [États-Unis] ; John E. Bennett [États-Unis]Source :
- BMC Molecular Biology [ 1471-2199 ] ; 2012.
Abstract
The selection of stable and suitable reference genes for real-time quantitative PCR (RT-qPCR) is a crucial prerequisite for reliable gene expression analysis under different experimental conditions. The present study aimed to identify reference genes as internal controls for gene expression studies by RT-qPCR in azole-stimulated
The expression stability of 16 reference genes under fluconazole stress was evaluated using fold change and standard deviation computations with the hkgFinder tool. Our data revealed that the mRNA expression levels of three ribosomal RNAs (
We recommend the use of
Url:
DOI: 10.1186/1471-2199-13-22
PubMed: 22747760
PubMed Central: 3482582
Affiliations:
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Evaluation of reference genes for real-time quantitative PCR studies in <italic>Candida glabrata</italic> following azole treatment</title><author><name sortKey="Li, Qingdi Quentin" sort="Li, Qingdi Quentin" uniqKey="Li Q" first="Qingdi Quentin" last="Li">Qingdi Quentin Li</name><affiliation wicri:level="1"><nlm:aff id="I1">Clinical Mycology Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Clinical Mycology Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892</wicri:regionArea><wicri:noRegion>20892</wicri:noRegion></affiliation></author><author><name sortKey="Skinner, Jeff" sort="Skinner, Jeff" uniqKey="Skinner J" first="Jeff" last="Skinner">Jeff Skinner</name><affiliation wicri:level="1"><nlm:aff id="I2">Bioinformatics and Computational Biosciences Branch, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Bioinformatics and Computational Biosciences Branch, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892</wicri:regionArea><wicri:noRegion>20892</wicri:noRegion></affiliation></author><author><name sortKey="Bennett, John E" sort="Bennett, John E" uniqKey="Bennett J" first="John E" last="Bennett">John E. Bennett</name><affiliation wicri:level="1"><nlm:aff id="I1">Clinical Mycology Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Clinical Mycology Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892</wicri:regionArea><wicri:noRegion>20892</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">22747760</idno><idno type="pmc">3482582</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3482582</idno><idno type="RBID">PMC:3482582</idno><idno type="doi">10.1186/1471-2199-13-22</idno><date when="2012">2012</date><idno type="wicri:Area/Pmc/Corpus">000394</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000394</idno><idno type="wicri:Area/Pmc/Curation">000394</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Curation">000394</idno><idno type="wicri:Area/Pmc/Checkpoint">000510</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Checkpoint">000510</idno><idno type="wicri:Area/Ncbi/Merge">000282</idno><idno type="wicri:Area/Ncbi/Curation">000282</idno><idno type="wicri:Area/Ncbi/Checkpoint">000282</idno><idno type="wicri:Area/Main/Merge">000B74</idno><idno type="wicri:Area/Main/Curation">000B72</idno><idno type="wicri:Area/Main/Exploration">000B72</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Evaluation of reference genes for real-time quantitative PCR studies in <italic>Candida glabrata</italic> following azole treatment</title><author><name sortKey="Li, Qingdi Quentin" sort="Li, Qingdi Quentin" uniqKey="Li Q" first="Qingdi Quentin" last="Li">Qingdi Quentin Li</name><affiliation wicri:level="1"><nlm:aff id="I1">Clinical Mycology Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Clinical Mycology Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892</wicri:regionArea><wicri:noRegion>20892</wicri:noRegion></affiliation></author><author><name sortKey="Skinner, Jeff" sort="Skinner, Jeff" uniqKey="Skinner J" first="Jeff" last="Skinner">Jeff Skinner</name><affiliation wicri:level="1"><nlm:aff id="I2">Bioinformatics and Computational Biosciences Branch, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Bioinformatics and Computational Biosciences Branch, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892</wicri:regionArea><wicri:noRegion>20892</wicri:noRegion></affiliation></author><author><name sortKey="Bennett, John E" sort="Bennett, John E" uniqKey="Bennett J" first="John E" last="Bennett">John E. Bennett</name><affiliation wicri:level="1"><nlm:aff id="I1">Clinical Mycology Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA</nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Clinical Mycology Section, Laboratory of Clinical Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892</wicri:regionArea><wicri:noRegion>20892</wicri:noRegion></affiliation></author></analytic><series><title level="j">BMC Molecular Biology</title><idno type="eISSN">1471-2199</idno><imprint><date when="2012">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>The selection of stable and suitable reference genes for real-time quantitative PCR (RT-qPCR) is a crucial prerequisite for reliable gene expression analysis under different experimental conditions. The present study aimed to identify reference genes as internal controls for gene expression studies by RT-qPCR in azole-stimulated <italic>Candida glabrata</italic>.</p></sec><sec><title>Results</title><p>The expression stability of 16 reference genes under fluconazole stress was evaluated using fold change and standard deviation computations with the hkgFinder tool. Our data revealed that the mRNA expression levels of three ribosomal RNAs (<italic>RDN5.8</italic>, <italic>RDN18</italic>, and <italic>RDN25</italic>) remained stable in response to fluconazole, while PGK1, UBC7, and UBC13 mRNAs showed only approximately 2.9-, 3.0-, and 2.5-fold induction by azole, respectively. By contrast, mRNA levels of the other 10 reference genes (<italic>ACT1</italic>, <italic>EF1α</italic>, <italic>GAPDH</italic>, <italic>PPIA</italic>, <italic>RPL2A</italic>, <italic>RPL10</italic>, <italic>RPL13A</italic>, <italic>SDHA</italic>, <italic>TUB1</italic>, and <italic>UBC4</italic>) were dramatically increased in <italic>C. glabrata</italic> following antifungal treatment, exhibiting changes ranging from 4.5- to 32.7-fold. We also assessed the expression stability of these reference genes using the 2<sup>-ΔΔCT</sup> method and three other software packages. The stability rankings of the reference genes by geNorm and the 2<sup>-ΔΔCT</sup> method were identical to those by hkgFinder, whereas the stability rankings by BestKeeper and NormFinder were notably different. We then validated the suitability of six candidate reference genes (<italic>ACT1</italic>, <italic>PGK1</italic>, <italic>RDN5.8</italic>, <italic>RDN18</italic>, <italic>UBC7</italic>, and <italic>UBC13</italic>) as internal controls for ten target genes in this system using the comparative C<sub>T</sub> method. Our validation experiments passed for all six reference genes analyzed except <italic>RDN18</italic>, where the amplification efficiency of <italic>RDN18</italic> was different from that of the ten target genes. Finally, we demonstrated that the relative quantification of target gene expression varied according to the endogenous control used, highlighting the importance of the choice of internal controls in such experiments.</p></sec><sec><title>Conclusions</title><p>We recommend the use of <italic>RDN5.8</italic>, <italic>UBC13</italic>, and <italic>PGK1</italic> alone or the combination of <italic>RDN5.8</italic> plus <italic>UBC13</italic> or <italic>PGK1</italic> as reference genes for RT-qPCR analysis of gene expression in <italic>C. glabrata</italic> following azole treatment. In contrast, we show that <italic>ACT1</italic> and other commonly used reference genes (<italic>GAPDH</italic>, <italic>PPIA</italic>, <italic>RPL13A</italic>, <italic>TUB1</italic>, etc.) were not validated as good internal controls in the current model.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Tsai, Hf" uniqKey="Tsai H">HF Tsai</name></author><author><name sortKey="Sammons, Lr" uniqKey="Sammons L">LR Sammons</name></author><author><name sortKey="Zhang, X" uniqKey="Zhang X">X Zhang</name></author><author><name sortKey="Suffis, Sd" uniqKey="Suffis S">SD Suffis</name></author><author><name sortKey="Su, Q" uniqKey="Su Q">Q Su</name></author><author><name sortKey="Myers, Tg" uniqKey="Myers T">TG Myers</name></author><author><name sortKey="Marr, Ka" uniqKey="Marr K">KA Marr</name></author><author><name sortKey="Bennett, Je" uniqKey="Bennett J">JE 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Koletsky</name></author><author><name sortKey="Harding, Mw" uniqKey="Harding M">MW Harding</name></author><author><name sortKey="Handschumacher, Re" uniqKey="Handschumacher R">RE Handschumacher</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="De Jonge, Hj" uniqKey="De Jonge H">HJ de Jonge</name></author><author><name sortKey="Fehrmann, Rs" uniqKey="Fehrmann R">RS Fehrmann</name></author><author><name sortKey="De Bont, Es" uniqKey="De Bont E">ES de Bont</name></author><author><name sortKey="Hofstra, Rm" uniqKey="Hofstra R">RM Hofstra</name></author><author><name sortKey="Gerbens, F" uniqKey="Gerbens F">F Gerbens</name></author><author><name sortKey="Kamps, Wa" uniqKey="Kamps W">WA Kamps</name></author><author><name sortKey="De Vries, Eg" uniqKey="De Vries E">EG de Vries</name></author><author><name sortKey="Van Der Zee, Ag" uniqKey="Van Der Zee A">AG van der Zee</name></author><author><name sortKey="Te Meerman, Gj" uniqKey="Te Meerman G">GJ te Meerman</name></author><author><name sortKey="Ter Elst, A" uniqKey="Ter Elst A">A ter Elst</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>États-Unis</li></country></list><tree><country name="États-Unis"><noRegion><name sortKey="Li, Qingdi Quentin" sort="Li, Qingdi Quentin" uniqKey="Li Q" first="Qingdi Quentin" last="Li">Qingdi Quentin Li</name></noRegion><name sortKey="Bennett, John E" sort="Bennett, John E" uniqKey="Bennett J" first="John E" last="Bennett">John E. 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