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A novel strategy for selection and validation of reference genes in dynamic multidimensional experimental design in yeast.

Cankorur-Cetinkaya A, Dereli E, Eraslan S, Karabekmez E, Dikicioglu D, Kirdar B - PLoS ONE (2012)

Bottom Line: The use of these newly proposed gene sets outperformed the use of common reference genes in the determination of dynamic transcriptional response of the target genes, HAP4 and MEP2, in response to relaxation from glucose and ammonium limitations, respectively.A candidate reference gene set to be used in dynamic real-time RT-qPCR expression profiling in yeast was proposed for the first time in the present study.Suitable pools of stable reference genes to be used under different experimental conditions could be selected from this candidate set in order to successfully determine the expression profiles for the genes of interest.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical Engineering, Bogazici University, Bebek, Istanbul, Turkey.

ABSTRACT

Background: Understanding the dynamic mechanism behind the transcriptional organization of genes in response to varying environmental conditions requires time-dependent data. The dynamic transcriptional response obtained by real-time RT-qPCR experiments could only be correctly interpreted if suitable reference genes are used in the analysis. The lack of available studies on the identification of candidate reference genes in dynamic gene expression studies necessitates the identification and the verification of a suitable gene set for the analysis of transient gene expression response.

Principal findings: In this study, a candidate reference gene set for RT-qPCR analysis of dynamic transcriptional changes in Saccharomyces cerevisiae was determined using 31 different publicly available time series transcriptome datasets. Ten of the twelve candidates (TPI1, FBA1, CCW12, CDC19, ADH1, PGK1, GCN4, PDC1, RPS26A and ARF1) we identified were not previously reported as potential reference genes. Our method also identified the commonly used reference genes ACT1 and TDH3. The most stable reference genes from this pool were determined as TPI1, FBA1, CDC19 and ACT1 in response to a perturbation in the amount of available glucose and as FBA1, TDH3, CCW12 and ACT1 in response to a perturbation in the amount of available ammonium. The use of these newly proposed gene sets outperformed the use of common reference genes in the determination of dynamic transcriptional response of the target genes, HAP4 and MEP2, in response to relaxation from glucose and ammonium limitations, respectively.

Conclusions: A candidate reference gene set to be used in dynamic real-time RT-qPCR expression profiling in yeast was proposed for the first time in the present study. Suitable pools of stable reference genes to be used under different experimental conditions could be selected from this candidate set in order to successfully determine the expression profiles for the genes of interest.

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Flowchart representing the approach.This figure represents the general strategy followed for the identification of a pool of reference gene candidates and the determination of a reference gene set to be used for a specific condition in real-time RT-qPCR experiments.
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pone-0038351-g005: Flowchart representing the approach.This figure represents the general strategy followed for the identification of a pool of reference gene candidates and the determination of a reference gene set to be used for a specific condition in real-time RT-qPCR experiments.

Mentions: In this study, geNorm and NormFinder algorithms were used for the identification of the most stable genes among the candidate list. For this purpose the results obtained from these two software programs were compared and the transcripts, which displayed the most stable expression profiles in both applications, were identified. The stability of the genes was evaluated based on a scoring system that allowed to display their average stability rankings. However, obtaining similar results using both software programs highly depended on the gene set to be analyzed since geNorm algorithm might be very sensitive to the existence of any correlated gene pairs. The results clearly showed that the exclusion of one of the correlated genes altered the stability order and the stability scores of the transcripts would be low only if the correlated genes were excluded from the candidate list. Our approach (Figure 5) is based on the elimination of the correlated gene pairs according to the results of the real-time RT-qPCR experiments under the selected conditions rather than the a priori elimination of genes that were reported to be correlated in the literature. This approach enabled the observation of any possible correlations among genes investigated in the samples of the current case studies and avoided the unnecessary exclusion of the candidates, which could possibly be among the most stable genes.


A novel strategy for selection and validation of reference genes in dynamic multidimensional experimental design in yeast.

Cankorur-Cetinkaya A, Dereli E, Eraslan S, Karabekmez E, Dikicioglu D, Kirdar B - PLoS ONE (2012)

Flowchart representing the approach.This figure represents the general strategy followed for the identification of a pool of reference gene candidates and the determination of a reference gene set to be used for a specific condition in real-time RT-qPCR experiments.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3366934&req=5

pone-0038351-g005: Flowchart representing the approach.This figure represents the general strategy followed for the identification of a pool of reference gene candidates and the determination of a reference gene set to be used for a specific condition in real-time RT-qPCR experiments.
Mentions: In this study, geNorm and NormFinder algorithms were used for the identification of the most stable genes among the candidate list. For this purpose the results obtained from these two software programs were compared and the transcripts, which displayed the most stable expression profiles in both applications, were identified. The stability of the genes was evaluated based on a scoring system that allowed to display their average stability rankings. However, obtaining similar results using both software programs highly depended on the gene set to be analyzed since geNorm algorithm might be very sensitive to the existence of any correlated gene pairs. The results clearly showed that the exclusion of one of the correlated genes altered the stability order and the stability scores of the transcripts would be low only if the correlated genes were excluded from the candidate list. Our approach (Figure 5) is based on the elimination of the correlated gene pairs according to the results of the real-time RT-qPCR experiments under the selected conditions rather than the a priori elimination of genes that were reported to be correlated in the literature. This approach enabled the observation of any possible correlations among genes investigated in the samples of the current case studies and avoided the unnecessary exclusion of the candidates, which could possibly be among the most stable genes.

Bottom Line: The use of these newly proposed gene sets outperformed the use of common reference genes in the determination of dynamic transcriptional response of the target genes, HAP4 and MEP2, in response to relaxation from glucose and ammonium limitations, respectively.A candidate reference gene set to be used in dynamic real-time RT-qPCR expression profiling in yeast was proposed for the first time in the present study.Suitable pools of stable reference genes to be used under different experimental conditions could be selected from this candidate set in order to successfully determine the expression profiles for the genes of interest.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical Engineering, Bogazici University, Bebek, Istanbul, Turkey.

ABSTRACT

Background: Understanding the dynamic mechanism behind the transcriptional organization of genes in response to varying environmental conditions requires time-dependent data. The dynamic transcriptional response obtained by real-time RT-qPCR experiments could only be correctly interpreted if suitable reference genes are used in the analysis. The lack of available studies on the identification of candidate reference genes in dynamic gene expression studies necessitates the identification and the verification of a suitable gene set for the analysis of transient gene expression response.

Principal findings: In this study, a candidate reference gene set for RT-qPCR analysis of dynamic transcriptional changes in Saccharomyces cerevisiae was determined using 31 different publicly available time series transcriptome datasets. Ten of the twelve candidates (TPI1, FBA1, CCW12, CDC19, ADH1, PGK1, GCN4, PDC1, RPS26A and ARF1) we identified were not previously reported as potential reference genes. Our method also identified the commonly used reference genes ACT1 and TDH3. The most stable reference genes from this pool were determined as TPI1, FBA1, CDC19 and ACT1 in response to a perturbation in the amount of available glucose and as FBA1, TDH3, CCW12 and ACT1 in response to a perturbation in the amount of available ammonium. The use of these newly proposed gene sets outperformed the use of common reference genes in the determination of dynamic transcriptional response of the target genes, HAP4 and MEP2, in response to relaxation from glucose and ammonium limitations, respectively.

Conclusions: A candidate reference gene set to be used in dynamic real-time RT-qPCR expression profiling in yeast was proposed for the first time in the present study. Suitable pools of stable reference genes to be used under different experimental conditions could be selected from this candidate set in order to successfully determine the expression profiles for the genes of interest.

Show MeSH