Validating internal controls for quantitative plant gene expression studies.
Identifieur interne : 004169 ( Main/Exploration ); précédent : 004168; suivant : 004170Validating internal controls for quantitative plant gene expression studies.
Auteurs : Amy M. Brunner [États-Unis] ; Igor A. Yakovlev ; Steven H. StraussSource :
- BMC plant biology [ 1471-2229 ] ; 2004.
Descripteurs français
- KwdFr :
- ARN des plantes (génétique), ARN des plantes (isolement et purification), Analyse de variance (MeSH), Facteurs temps (MeSH), Gènes de plante (génétique), Modèles linéaires (MeSH), Normes de référence (MeSH), Populus (génétique), RT-PCR (méthodes), RT-PCR (normes), Reproductibilité des résultats (MeSH), Régulation de l'expression des gènes végétaux (MeSH).
- MESH :
- génétique : ARN des plantes, Gènes de plante, Populus.
- isolement et purification : ARN des plantes.
- méthodes : RT-PCR.
- normes : RT-PCR.
- Analyse de variance, Facteurs temps, Modèles linéaires, Normes de référence, Reproductibilité des résultats, Régulation de l'expression des gènes végétaux.
English descriptors
- KwdEn :
- Analysis of Variance (MeSH), Gene Expression Regulation, Plant (MeSH), Genes, Plant (genetics), Linear Models (MeSH), Populus (genetics), RNA, Plant (genetics), RNA, Plant (isolation & purification), Reference Standards (MeSH), Reproducibility of Results (MeSH), Reverse Transcriptase Polymerase Chain Reaction (methods), Reverse Transcriptase Polymerase Chain Reaction (standards), Time Factors (MeSH).
- MESH :
- chemical , genetics : RNA, Plant.
- genetics : Genes, Plant, Populus.
- chemical , isolation & purification : RNA, Plant.
- methods : Reverse Transcriptase Polymerase Chain Reaction.
- standards : Reverse Transcriptase Polymerase Chain Reaction.
- Analysis of Variance, Gene Expression Regulation, Plant, Linear Models, Reference Standards, Reproducibility of Results, Time Factors.
Abstract
BACKGROUND
Real-time reverse transcription PCR (RT-PCR) has greatly improved the ease and sensitivity of quantitative gene expression studies. However, accurate measurement of gene expression with this method relies on the choice of a valid reference for data normalization. Studies rarely verify that gene expression levels for reference genes are adequately consistent among the samples used, nor compare alternative genes to assess which are most reliable for the experimental conditions analyzed.
RESULTS
Using real-time RT-PCR to study the expression of 10 poplar (genus Populus) housekeeping genes, we demonstrate a simple method for determining the degree of stability of gene expression over a set of experimental conditions. Based on a traditional method for analyzing the stability of varieties in plant breeding, it defines measures of gene expression stability from analysis of variance (ANOVA) and linear regression. We found that the potential internal control genes differed widely in their expression stability over the different tissues, developmental stages and environmental conditions studied.
CONCLUSION
Our results support that quantitative comparisons of candidate reference genes are an important part of real-time RT-PCR studies that seek to precisely evaluate variation in gene expression. The method we demonstrated facilitates statistical and graphical evaluation of gene expression stability. Selection of the best reference gene for a given set of experimental conditions should enable detection of biologically significant changes in gene expression that are too small to be revealed by less precise methods, or when highly variable reference genes are unknowingly used in real-time RT-PCR experiments.
DOI: 10.1186/1471-2229-4-14
PubMed: 15317655
PubMed Central: PMC515301
Affiliations:
Links toward previous steps (curation, corpus...)
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Brunner</name><affiliation wicri:level="2"><nlm:affiliation>Department of Forest Science, Oregon State University, Corvallis, OR 97331-5752, USA. Amy.Brunner@oregonstate.edu</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Forest Science, Oregon State University, Corvallis, OR 97331-5752</wicri:regionArea><placeName><region type="state">Oregon</region></placeName></affiliation></author><author><name sortKey="Yakovlev, Igor A" sort="Yakovlev, Igor A" uniqKey="Yakovlev I" first="Igor A" last="Yakovlev">Igor A. Yakovlev</name></author><author><name sortKey="Strauss, Steven H" sort="Strauss, Steven H" uniqKey="Strauss S" first="Steven H" last="Strauss">Steven H. Strauss</name></author></analytic><series><title level="j">BMC plant biology</title><idno type="eISSN">1471-2229</idno><imprint><date when="2004" type="published">2004</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Analysis of Variance (MeSH)</term><term>Gene Expression Regulation, Plant (MeSH)</term><term>Genes, Plant (genetics)</term><term>Linear Models (MeSH)</term><term>Populus (genetics)</term><term>RNA, Plant (genetics)</term><term>RNA, Plant (isolation & purification)</term><term>Reference Standards (MeSH)</term><term>Reproducibility of Results (MeSH)</term><term>Reverse Transcriptase Polymerase Chain Reaction (methods)</term><term>Reverse Transcriptase Polymerase Chain Reaction (standards)</term><term>Time Factors (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>ARN des plantes (génétique)</term><term>ARN des plantes (isolement et purification)</term><term>Analyse de variance (MeSH)</term><term>Facteurs temps (MeSH)</term><term>Gènes de plante (génétique)</term><term>Modèles linéaires (MeSH)</term><term>Normes de référence (MeSH)</term><term>Populus (génétique)</term><term>RT-PCR (méthodes)</term><term>RT-PCR (normes)</term><term>Reproductibilité des résultats (MeSH)</term><term>Régulation de l'expression des gènes végétaux (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>RNA, Plant</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Genes, Plant</term><term>Populus</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>ARN des plantes</term><term>Gènes de plante</term><term>Populus</term></keywords><keywords scheme="MESH" type="chemical" qualifier="isolation & purification" xml:lang="en"><term>RNA, Plant</term></keywords><keywords scheme="MESH" qualifier="isolement et purification" xml:lang="fr"><term>ARN des plantes</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Reverse Transcriptase Polymerase Chain Reaction</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>RT-PCR</term></keywords><keywords scheme="MESH" qualifier="normes" xml:lang="fr"><term>RT-PCR</term></keywords><keywords scheme="MESH" qualifier="standards" xml:lang="en"><term>Reverse Transcriptase Polymerase Chain Reaction</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Analysis of Variance</term><term>Gene Expression Regulation, Plant</term><term>Linear Models</term><term>Reference Standards</term><term>Reproducibility of Results</term><term>Time Factors</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse de variance</term><term>Facteurs temps</term><term>Modèles linéaires</term><term>Normes de référence</term><term>Reproductibilité des résultats</term><term>Régulation de l'expression des gènes végétaux</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b></p><p>Real-time reverse transcription PCR (RT-PCR) has greatly improved the ease and sensitivity of quantitative gene expression studies. However, accurate measurement of gene expression with this method relies on the choice of a valid reference for data normalization. Studies rarely verify that gene expression levels for reference genes are adequately consistent among the samples used, nor compare alternative genes to assess which are most reliable for the experimental conditions analyzed.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>Using real-time RT-PCR to study the expression of 10 poplar (genus Populus) housekeeping genes, we demonstrate a simple method for determining the degree of stability of gene expression over a set of experimental conditions. Based on a traditional method for analyzing the stability of varieties in plant breeding, it defines measures of gene expression stability from analysis of variance (ANOVA) and linear regression. We found that the potential internal control genes differed widely in their expression stability over the different tissues, developmental stages and environmental conditions studied.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSION</b></p><p>Our results support that quantitative comparisons of candidate reference genes are an important part of real-time RT-PCR studies that seek to precisely evaluate variation in gene expression. The method we demonstrated facilitates statistical and graphical evaluation of gene expression stability. Selection of the best reference gene for a given set of experimental conditions should enable detection of biologically significant changes in gene expression that are too small to be revealed by less precise methods, or when highly variable reference genes are unknowingly used in real-time RT-PCR experiments.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">15317655</PMID><DateCompleted><Year>2005</Year><Month>05</Month><Day>31</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2229</ISSN><JournalIssue CitedMedium="Internet"><Volume>4</Volume><PubDate><Year>2004</Year><Month>Aug</Month><Day>18</Day></PubDate></JournalIssue><Title>BMC plant biology</Title><ISOAbbreviation>BMC Plant Biol</ISOAbbreviation></Journal><ArticleTitle>Validating internal controls for quantitative plant gene expression studies.</ArticleTitle><Pagination><MedlinePgn>14</MedlinePgn></Pagination><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Real-time reverse transcription PCR (RT-PCR) has greatly improved the ease and sensitivity of quantitative gene expression studies. However, accurate measurement of gene expression with this method relies on the choice of a valid reference for data normalization. Studies rarely verify that gene expression levels for reference genes are adequately consistent among the samples used, nor compare alternative genes to assess which are most reliable for the experimental conditions analyzed.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">Using real-time RT-PCR to study the expression of 10 poplar (genus Populus) housekeeping genes, we demonstrate a simple method for determining the degree of stability of gene expression over a set of experimental conditions. Based on a traditional method for analyzing the stability of varieties in plant breeding, it defines measures of gene expression stability from analysis of variance (ANOVA) and linear regression. We found that the potential internal control genes differed widely in their expression stability over the different tissues, developmental stages and environmental conditions studied.</AbstractText><AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">Our results support that quantitative comparisons of candidate reference genes are an important part of real-time RT-PCR studies that seek to precisely evaluate variation in gene expression. The method we demonstrated facilitates statistical and graphical evaluation of gene expression stability. Selection of the best reference gene for a given set of experimental conditions should enable detection of biologically significant changes in gene expression that are too small to be revealed by less precise methods, or when highly variable reference genes are unknowingly used in real-time RT-PCR experiments.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Brunner</LastName><ForeName>Amy M</ForeName><Initials>AM</Initials><AffiliationInfo><Affiliation>Department of Forest Science, Oregon State University, Corvallis, OR 97331-5752, USA. 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Strauss</name><name sortKey="Yakovlev, Igor A" sort="Yakovlev, Igor A" uniqKey="Yakovlev I" first="Igor A" last="Yakovlev">Igor A. Yakovlev</name></noCountry><country name="États-Unis"><region name="Oregon"><name sortKey="Brunner, Amy M" sort="Brunner, Amy M" uniqKey="Brunner A" first="Amy M" last="Brunner">Amy M. Brunner</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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