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首页> 外文期刊>BMC Genomics >Combinatorial effects of environmental parameters on transcriptional regulation in Saccharomyces cerevisiae: A quantitative analysis of a compendium of chemostat-based transcriptome data
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Combinatorial effects of environmental parameters on transcriptional regulation in Saccharomyces cerevisiae: A quantitative analysis of a compendium of chemostat-based transcriptome data

机译:环境参数对酿酒酵母转录调控的组合影响:基于化学恒化器的转录组数据汇编的定量分析

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Background Microorganisms adapt their transcriptome by integrating multiple chemical and physical signals from their environment. Shake-flask cultivation does not allow precise manipulation of individual culture parameters and therefore precludes a quantitative analysis of the (combinatorial) influence of these parameters on transcriptional regulation. Steady-state chemostat cultures, which do enable accurate control, measurement and manipulation of individual cultivation parameters (e.g. specific growth rate, temperature, identity of the growth-limiting nutrient) appear to provide a promising experimental platform for such a combinatorial analysis. Results A microarray compendium of 170 steady-state chemostat cultures of the yeast Saccharomyces cerevisiae is presented and analyzed. The 170 microarrays encompass 55 unique conditions, which can be characterized by the combined settings of 10 different cultivation parameters. By applying a regression model to assess the impact of (combinations of) cultivation parameters on the transcriptome, most S. cerevisiae genes were shown to be influenced by multiple cultivation parameters, and in many cases by combinatorial effects of cultivation parameters. The inclusion of these combinatorial effects in the regression model led to higher explained variance of the gene expression patterns and resulted in higher function enrichment in subsequent analysis. We further demonstrate the usefulness of the compendium and regression analysis for interpretation of shake-flask-based transcriptome studies and for guiding functional analysis of (uncharacterized) genes and pathways. Conclusion Modeling the combinatorial effects of environmental parameters on the transcriptome is crucial for understanding transcriptional regulation. Chemostat cultivation offers a powerful tool for such an approach.
机译:背景技术微生物通过整合来自其环境的多种化学和物理信号来适应其转录组。摇瓶培养无法精确地控制单个培养参数,因此无法对这些参数对转录调控的(组合)影响进行定量分析。稳态化学恒温器培养物确实能够精确控制,测量和操纵单个培养参数(例如特定生长速率,温度,生长受限营养素的特性),似乎为此类组合分析提供了有希望的实验平台。结果提出并分析了170种酵母酿酒酵母稳态化学培养物的微阵列汇编。 170个微阵列包含55种独特条件,可以通过10种不同培养参数的组合设置来表征。通过应用回归模型评估培养参数(组合)对转录组的影响,大多数酿酒酵母基因受多种培养参数的影响,并且在许多情况下受培养参数的组合作用的影响。在回归模型中包含这些组合效应会导致基因表达模式的更高解释差异,并在后续分析中导致更高的功能富集度。我们进一步证明了简编和回归分析对于基于摇瓶的转录组研究的解释以及对(未表征的)基因和途径的功能分析的指导的有用性。结论模拟环境参数对转录组的组合效应对于理解转录调控至关重要。 Chemostat的种植为这种方法提供了强大的工具。

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