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Global analysis of gene expression by differential display: a mathematical model.

机译:通过差异显示对基因表达进行全局分析:一个数学模型。

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Differential display (DD) is one of the most commonly used approaches for identifying differentially expressed genes. However, there has been lack of an accurate guidance on how many DD polymerase chain reaction (PCR) primer combinations are needed to display most of the genes expressed in a eukaryotic cell. This study critically evaluated the gene coverage by DD as a function of the number of arbitrary primers, the number of 3' bases of an arbitrary primer required to completely match an mRNA target sequence, the additional 5' base match(s) of arbitrary primers in first-strand cDNA recognition, and the length of mRNA tails being analyzed. The resulting new DD mathematical model predicts that 80 to160 arbitrary 13mers, when used in combinations with 3 one-base anchored oligo-dT primers, would allow any given mRNA within a eukaryotic cell to be detected with a 74% to 93% probability, respectively. The prediction was supported by both computer simulation of the DD process and experimental data from a comprehensive fluorescent DD screening for target genes of tumor-suppressor p53. Thus, this work provides a theoretical foundation upon which global analysis of gene expression by DD can be pursued.
机译:差异显示(DD)是鉴定差异表达基因的最常用方法之一。但是,对于显示真核细胞中表达的大多数基因需要多少个DD聚合酶链反应(PCR)引物组合,仍然缺乏准确的指导。这项研究严格评估了DD的基因覆盖率与任意引物数量,完全匹配mRNA靶序列所需的任意引物3'碱基数量,任意引物的其他5'碱基匹配的关系在第一链cDNA识别中,并分析了mRNA尾巴的长度。由此产生的新的DD数学模型预测,当与3个一碱基锚定的oligo-dT引物结合使用时,80至160个任意的13聚体将允许真核细胞中任何给定的mRNA分别以74%至93%的概率被检测到。 。 DD过程的计算机模拟和来自全面荧光DD筛查肿瘤抑制因子p53靶基因的实验数据均支持该预测。因此,这项工作提供了一个理论基础,可以进行基于DD的基因表达的整体分析。

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