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商业面包酵母酿酒酵母热应激反应的转录组分析。

Transcriptomic analysis of the heat stress response for a commercial baker's yeast Saccharomyces cerevisiae.

作者信息

Varol Duygu, Purutçuoğlu Vilda, Yılmaz Remziye

机构信息

Department of Statistics, Faculty of Art and Science, Middle East Technical University, Ankara, Turkey.

Department of Food Engineering, Faculty of Engineering, Hacettepe University, Ankara, Turkey.

出版信息

Genes Genomics. 2018 Feb;40(2):137-150. doi: 10.1007/s13258-017-0616-6. Epub 2017 Oct 25.

Abstract

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 (Saccharomyces cerevisiae) by using microarray technology and comparative statistical data analyses. The 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, all required statistical methods were performed comparatively. For the normalization step, among alternatives, the RMA (Robust Microarray Analysis) results were used. To determine differentially expressed genes under heat stress treatments, the fold-change and the hypothesis testing approaches were executed under various cut-off values via different multiple testing procedures then the up/down regulated probes were functionally categorized via the PAMSAM clustering. The results of the analysis concluded that the transcriptome changes under the heat shock. Moreover, the temperature-shift stress treatments show that the number of differentially up-regulated genes among the heat shock proteins and transcription factors changed significantly. Finally, the change in temperature is one of the important environmental conditions affecting propagation and industrial application of baker's yeast. This study statistically analyzes this affect via one-channel microarray data.

摘要

本研究的目的是通过使用微阵列技术和比较统计数据分析,探索热应激对商业面包酵母(酿酒酵母)全球基因表达谱的影响,并确定热应激反应的候选基因。使用GeneSpringGX 12.1(安捷伦)和R 2.15.2编程语言对所有杂交和阵列归一化的数据进行分析。在分析中,所有所需的统计方法都进行了比较。对于归一化步骤,在备选方法中,使用了RMA(稳健微阵列分析)结果。为了确定热应激处理下差异表达的基因,通过不同的多重检验程序在各种截止值下执行倍数变化和假设检验方法,然后通过PAMSAM聚类对上调/下调的探针进行功能分类。分析结果得出,热休克下转录组发生了变化。此外,温度变化应激处理表明,热休克蛋白和转录因子中差异上调基因的数量发生了显著变化。最后,温度变化是影响面包酵母繁殖和工业应用的重要环境条件之一。本研究通过单通道微阵列数据对这种影响进行了统计分析。

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