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Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae

BACKGROUND: Real-time RT-PCR is the recommended method for quantitative gene expression analysis. A compulsory step is the selection of good reference genes for normalization. A few genes often referred to as HouseKeeping Genes (HSK), such as ACT1, RDN18 or PDA1 are among the most commonly used, as...

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Autores principales: Teste, Marie-Ange, Duquenne, Manon, François, Jean M, Parrou, Jean-Luc
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2776018/
https://www.ncbi.nlm.nih.gov/pubmed/19874630
http://dx.doi.org/10.1186/1471-2199-10-99
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author Teste, Marie-Ange
Duquenne, Manon
François, Jean M
Parrou, Jean-Luc
author_facet Teste, Marie-Ange
Duquenne, Manon
François, Jean M
Parrou, Jean-Luc
author_sort Teste, Marie-Ange
collection PubMed
description BACKGROUND: Real-time RT-PCR is the recommended method for quantitative gene expression analysis. A compulsory step is the selection of good reference genes for normalization. A few genes often referred to as HouseKeeping Genes (HSK), such as ACT1, RDN18 or PDA1 are among the most commonly used, as their expression is assumed to remain unchanged over a wide range of conditions. Since this assumption is very unlikely, a geometric averaging of multiple, carefully selected internal control genes is now strongly recommended for normalization to avoid this problem of expression variation of single reference genes. The aim of this work was to search for a set of reference genes for reliable gene expression analysis in Saccharomyces cerevisiae. RESULTS: From public microarray datasets, we selected potential reference genes whose expression remained apparently invariable during long-term growth on glucose. Using the algorithm geNorm, ALG9, TAF10, TFC1 and UBC6 turned out to be genes whose expression remained stable, independent of the growth conditions and the strain backgrounds tested in this study. We then showed that the geometric averaging of any subset of three genes among the six most stable genes resulted in very similar normalized data, which contrasted with inconsistent results among various biological samples when the normalization was performed with ACT1. Normalization with multiple selected genes was therefore applied to transcriptional analysis of genes involved in glycogen metabolism. We determined an induction ratio of 100-fold for GPH1 and 20-fold for GSY2 between the exponential phase and the diauxic shift on glucose. There was no induction of these two genes at this transition phase on galactose, although in both cases, the kinetics of glycogen accumulation was similar. In contrast, SGA1 expression was independent of the carbon source and increased by 3-fold in stationary phase. CONCLUSION: In this work, we provided a set of genes that are suitable reference genes for quantitative gene expression analysis by real-time RT-PCR in yeast biological samples covering a large panel of physiological states. In contrast, we invalidated and discourage the use of ACT1 as well as other commonly used reference genes (PDA1, TDH3, RDN18, etc) as internal controls for quantitative gene expression analysis in yeast.
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spelling pubmed-27760182009-11-12 Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae Teste, Marie-Ange Duquenne, Manon François, Jean M Parrou, Jean-Luc BMC Mol Biol Research Article BACKGROUND: Real-time RT-PCR is the recommended method for quantitative gene expression analysis. A compulsory step is the selection of good reference genes for normalization. A few genes often referred to as HouseKeeping Genes (HSK), such as ACT1, RDN18 or PDA1 are among the most commonly used, as their expression is assumed to remain unchanged over a wide range of conditions. Since this assumption is very unlikely, a geometric averaging of multiple, carefully selected internal control genes is now strongly recommended for normalization to avoid this problem of expression variation of single reference genes. The aim of this work was to search for a set of reference genes for reliable gene expression analysis in Saccharomyces cerevisiae. RESULTS: From public microarray datasets, we selected potential reference genes whose expression remained apparently invariable during long-term growth on glucose. Using the algorithm geNorm, ALG9, TAF10, TFC1 and UBC6 turned out to be genes whose expression remained stable, independent of the growth conditions and the strain backgrounds tested in this study. We then showed that the geometric averaging of any subset of three genes among the six most stable genes resulted in very similar normalized data, which contrasted with inconsistent results among various biological samples when the normalization was performed with ACT1. Normalization with multiple selected genes was therefore applied to transcriptional analysis of genes involved in glycogen metabolism. We determined an induction ratio of 100-fold for GPH1 and 20-fold for GSY2 between the exponential phase and the diauxic shift on glucose. There was no induction of these two genes at this transition phase on galactose, although in both cases, the kinetics of glycogen accumulation was similar. In contrast, SGA1 expression was independent of the carbon source and increased by 3-fold in stationary phase. CONCLUSION: In this work, we provided a set of genes that are suitable reference genes for quantitative gene expression analysis by real-time RT-PCR in yeast biological samples covering a large panel of physiological states. In contrast, we invalidated and discourage the use of ACT1 as well as other commonly used reference genes (PDA1, TDH3, RDN18, etc) as internal controls for quantitative gene expression analysis in yeast. BioMed Central 2009-10-30 /pmc/articles/PMC2776018/ /pubmed/19874630 http://dx.doi.org/10.1186/1471-2199-10-99 Text en Copyright © 2009 Teste et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Teste, Marie-Ange
Duquenne, Manon
François, Jean M
Parrou, Jean-Luc
Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae
title Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae
title_full Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae
title_fullStr Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae
title_full_unstemmed Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae
title_short Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae
title_sort validation of reference genes for quantitative expression analysis by real-time rt-pcr in saccharomyces cerevisiae
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2776018/
https://www.ncbi.nlm.nih.gov/pubmed/19874630
http://dx.doi.org/10.1186/1471-2199-10-99
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