Whole Genome Analysis of the Heat Stress Response in Commercial Baker's Yeast (Saccharomyces cerevisiae) with Comparative Statistical Approaches

Environmental conditions are quite effective during propagation and industrial application of Baker’s yeast (Saccharomyces cerevisiae). The change of temperature is one of the most important conditions which affects the dough-leaving capacity of yeast cells. Accordingly, heat changes play an essential role in the commercial and economic impact of the yeast. Recent technologies in genomics have been used for analysis of global gene expression profiles such as microarray and RNA sequencing to solve the problems related with industrial application of yeast. Hereby, the aim of this study is to explore the effects of heat stresses on global gene expression profiles and to identify the candidate genes for the heat stress response in commercial baker’s yeast by using microarray technology and comparative statistical data analyses. Data from all hybridizations and array normalization were analyzed using the GeneSpringGX 12.1 (Agilent) and the R 2.15.2 program language. In the analysis of this dataset, all required statistical methods are performed comparatively in each step and the best performed ones are used in further computations. Hence, as the first step of the analyses, different background normalization algorithms such as MAS5.0, RMA, MBEI and GC-RMA were applied and the algorithm which gives the most accurate findings was chosen for the normalization procedure. As a result, expression values, computed from CEL files, were processed by Robust Multiarray Analysis (RMA) which is the selected procedure for the normalization of the systematic differences between samples. In order to determine differentially expressed genes under heat stress treatments, two different methods, namely, the fold-change and the hypothesis testing approaches are executed. In the fold-change method, various cut-off values are implemented while different multiple testing procedures are performed for the hypothesis testing. Under the heat shock and temperature-shift stress conditions, up/down regulated differentially expressed probes were functionally categorized into the different groups via the cluster analyses. Transcriptome changes under the heat shock and temperature-shift stress treatments show that the number of differentially up-regulated genes among the heat shock proteins (HSPs) and transcription factors (TFs) changed significantly. Consequently, the identification of thousands of genes related with heat stress treatments via microarray technology and comparative statistical analysis resulted in the creation of big picture which provides the understanding of the importance for the baker’s yeast industrial applications.