Swillens Stéphane, Dessars Barbara, Housni Hakim El
Institut de Recherche Interdisciplinaire, Faculté de Médecine, Université Libre de Bruxelles (ULB), B-1070 Brussels, Belgium.
Anal Biochem. 2008 Feb 15;373(2):370-6. doi: 10.1016/j.ab.2007.10.019. Epub 2007 Oct 22.
Amplification of a cDNA product by quantitative polymerase chain reaction (qPCR) gives rise to fluorescence sigmoidal curves from which absolute or relative target gene content of the sample is inferred. Besides comparative C(t) methods that require the construction of a reference standard curve, other methods that focus on the analysis of the sole amplification curve have been proposed more recently. Among them, the so-called sigmoidal curve fitting (SCF) method rests on the fitting of an empirical sigmoidal model to the experimental amplification data points, leading to the prediction of the amplification efficiency and to the calculation of the initial copy number in the sample. The implicit assumption of this method is that the sigmoidal model may describe an amplification curve quantitatively even in the portion of the curve where the fluorescence signal is hidden in the noise band. The theoretical basis of the SCF method was revisited here for defining the class of experimental amplification curves for which the method might be relevant. Applying the SCF method to six well-characterized different PCR assays illustrated possible pitfalls leading to biased estimates of the amplification efficiency and, thus, of the target gene content of a sample.
通过定量聚合酶链反应（qPCR）扩增cDNA产物会产生荧光S形曲线，据此可推断样品中目标基因的绝对或相对含量。除了需要构建参考标准曲线的比较C(t)方法外，最近还提出了其他专注于分析单一扩增曲线的方法。其中，所谓的S形曲线拟合（SCF）方法基于将经验S形模型拟合到实验扩增数据点，从而预测扩增效率并计算样品中的初始拷贝数。该方法的隐含假设是，即使在荧光信号隐藏在噪声带的曲线部分，S形模型也可以定量描述扩增曲线。本文重新审视了SCF方法的理论基础，以确定该方法可能适用的实验扩增曲线类别。将SCF方法应用于六种特征明确的不同PCR检测，揭示了可能导致扩增效率估计偏差以及样品目标基因含量估计偏差的陷阱。
