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


RESULTS
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.
Department of Chemical Engineering, Bogazici University, Bebek, Istanbul, Turkey.
Ayca
A
Cankorur-Cetinkaya
Elif
E
Dereli
Serpil
S
Eraslan
Erkan
E
Karabekmez
Duygu
D
Dikicioglu
Betul
B
Kirdar
D020869:Gene Expression Profiling; D015966:Gene Expression Regulation, Fungal; D005800:Genes, Fungal / Q000235:genetics*; D056726:Genetic Association Studies; D005947:Glucose / Q000494:pharmacology; D000644:Quaternary Ammonium Compounds / Q000494:pharmacology; D012015:Reference Standards; D015203:Reproducibility of Results; D012107:Research Design; D020133:Reverse Transcriptase Polymerase Chain Reaction / Q000379:methods* / Q000592:standards*; D012441:Saccharomyces cerevisiae / Q000187:drug effects / Q000235:genetics*; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics / Q000378:metabolism; D012985:Software Design
D000644:Quaternary Ammonium Compounds; D029701:Saccharomyces cerevisiae Proteins; D005947:Glucose