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从 \boldsymbol2^-\boldsymbol\Delta\boldsymbol\Delta \boldsymbolC_\bfT 法到 \boldsymbol2^-\boldsymbolC_\bfT 法：一种更严谨的RT-qPCR数据分析策略

From the \boldsymbol2^-\boldsymbol\Delta\boldsymbol\Delta \boldsymbolC_\bfT Method to the \boldsymbol2^-\boldsymbolC_\bfT Method: A More Rigorous Approach to Real-time Quantitative Polymerase Chain Reaction Data Analysis

    摘要
  • 摘要:
    目的 本研究旨在通过数学原理优化RT-qPCR数据分析流程，用更严谨的 2^-C_\mathrmT 法替代存在偏差的 2^-\Delta\Delta C_\mathrmT 法，提升基因表达定量研究的准确性。
    方法 本质上CT值在比较CT法的计算逻辑里是2的指数。传统 2^-\Delta\Delta C_\mathrmT 法在计算过程中直接对CT值和ΔCT取算术平均值，忽略了CT值的指数特性，导致计算结果存在偏差。我们提出新的“ 2^-C_\mathrmT 法”，其核心是基于CT值做 2^-C_\mathrmT 变换后再进行所有计算，包括计算各样品内目的基因和内参基因的相对起始表达量、目的基因相对含量、目的基因相对变化倍数，最后基于目的基因相对变化倍数进行统计学分析。该方法严格遵循CT值的指数特性，避免了CT和ΔCT层面算术平均引入的偏差。本研究利用不同RT-qPCR数据，评估了传统 2^-\Delta\Delta C_\mathrmT 法和新 2^-C_\mathrmT 法在基因表达定量分析中的差异及其影响。
    结果 两种方法在LIVAK和SCHMITTGEN原始数据中的计算结果差异较小。但在镉暴露实验中， 2^-\Delta\Delta C_\mathrmT 法计算结果显示8 h镉暴露可使秀丽隐杆线虫的irg-6基因表达水平从1.314倍增加到7.125倍 (P=0.0002)，而 2^-C_\mathrmT 法计算结果显示irg-6基因表达水平从1倍增加到4.124倍(P=0.0015)。两种计算方法的变化倍数相差达70%。
    结论  2^-C\mathrm_T 法在数学逻辑上更严谨，能更准确地反映基因表达变化，尤其适用于CT值变异较大的实验数据，这为基因表达定量分析提供了更可靠的计算范式。

     

    Abstract:
    Objective To optimize the real-time quantitative polymerase chain reaction (RT-qPCR) data analysis process through mathematical principles by replacing the biased 2^-\Delta\Delta C_\mathrmT method with a more rigorous 2^-C_\mathrmT method, thereby improving the accuracy of gene expression quantification analysis.
    Methods Essentially, the CT value serves as the exponent in a base-2 exponential equation within the logic of comparative CT method. In the traditional 2^-\Delta\Delta C_\mathrmT method, the arithmetic means of raw CT and ΔCT values are directly calculated and the exponential nature of CT data is overlooked, which may introduce systematic bias to the calculation results. We propose a new method, entitled the 2^-C_\mathrmT method, in which all calculations are based on the transformation of CT values into 2^-C_\mathrmT . This includes computing the relative initial expression levels of target and reference genes within each sample, the relative abundance of the target gene, and its fold change across groups. Statistical comparisons are then performed based on fold change values. By strictly adhering to the exponential nature of of CT values, the biases introduced by arithmetic averaging at the CT or ΔCT level are avoided. We applied this method to multiple RT-qPCR datasets to evaluate the differences between the traditional 2^-\Delta\Delta C_\mathrmT and the proposed 2^-C_\mathrmT methods in gene expression quantification, as well as the effect of the differences.
    Results In the original dataset from LIVAK and SCHMITTGEN, the two methods produced similar results. However, in the cadmium exposure experiment, findings from the 2^-\Delta\Delta C\mathrm_T method indicated that 8-hour cadmium exposure caused an increase of irg-6 gene expression in Caenorhabditis elegans from 1.314-fold to 7.125-fold (P = 0.0002). In contrast, findings from the 2^-C_\mathrmT method showed a fold change from 1.0 to 4.124 (P = 0.0015), a 70% difference between the two methods.
    Conclusion The 2^-C_\mathrmT method provides a mathematically more rigorous approach that more accurately reflects gene expression changes, particularly in experiments with high CT variability. It offers a more reliable computational paradigm for quantitative gene expression analysis.

     

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