A Novel Strategy for Selection and Validation of Reference Genes in Dynamic Multidimensional Experimental Design in Yeast Ayca Cankorur-Cetinkaya, Elif Dereli, Serpil Eraslan, Erkan Karabekmez, Duygu Dikicioglu, Betul Kirdar* 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. Citation: Cankorur-Cetinkaya A, Dereli E, Eraslan S, Karabekmez E, Dikicioglu D, et al. (2012) A Novel Strategy for Selection and Validation of Reference Genes in Dynamic Multidimensional Experimental Design in Yeast. PLoS ONE 7(6): e38351. doi:10.1371/journal.pone.0038351 Editor: Francisco Jose´ Esteban, University of Jae´n, Spain Received November 10, 2011; Accepted May 3, 2012; Published June 4, 2012 Copyright: 2012 Cankorur-Cetinkaya et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: The research was financially supported by Bogazici University Research Fund through Projects No 07M106 and 5562, TUBITAK through Project No 106M444, and Turkish State Planning Organization through Project No DPT 09K120520. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: kirdar@boun.edu.tr Introduction Single time point experiments provide a static measurement of gene expression although transcription is a temporal process. Time series gene expression experiments are useful in elucidating the dynamic mechanism behind a biological process. The high- throughput data obtained from microarray technology enables the identification of differentially expressed genes. Real-time RT- qPCR is the favoured method for conducting a detailed study on a gene set of interest, which is determined from high-throughput studies. It is a widely preferred method for quantitative gene expression analysis due to its high sensitivity, specificity and wider dynamic range. However, data normalization for the elimination of sample-to sample differences is the main obstacle of this method even in non-transient studies [1,2,3,4]. The multidimensional and temporal nature of time series data renders its analysis more complicated thus drawing attention to the importance of normalization. Normalization with internal control genes, generally referred to as the housekeeping or reference genes, is a commonly used method among various normalization techniques for the determi- nation of gene expression using real-time RT-qPCR. A suitable reference gene should be constitutively expressed in the tissues or cells under investigation regardless of the experimental perturba- tion. A single reference gene was frequently used in many studies in order to normalize mRNA fraction without any validation of stability. However growing evidence indicates the absence of a single universal reference gene, which may be independent of all kind of experimental conditions. Since the normalization of real- time RT-qPCR data using a non-validated single reference gene may engender misleading conclusions, in recent years, the calculation of a normalization factor based on the geometric average of validated multiple reference genes was suggested to discard possible outliers and differences in the abundance of different genes [5]. PLoS ONE | www.plosone.org 1 June 2012 | Volume 7 | Issue 6 | e38351