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Abstract
Background
The 2^sup -ΔΔCT^ method has been extensively used as a relative quantification strategy for quantitative real-time polymerase chain reaction (qPCR) data analysis. This method is a convenient way to calculate relative gene expression levels between different samples in that it directly uses the threshold cycles (CTs) generated by the qPCR system for calculation. However, this approach relies heavily on an invalid assumption of 100% PCR amplification efficiency across all samples. In addition, the 2^sup -ΔΔCT^ method is applied to data with automatic removal of background fluorescence by the qPCR software. Since the background fluorescence is unknown, subtracting an inaccurate background can lead to distortion of the results. To address these problems, we present an improved method, the individual efficiency corrected calculation.
Results
Our method takes into account the PCR efficiency of each individual sample. In addition, it eliminates the need for background fluorescence estimation or subtraction because the background can be cancelled out using the differencing strategy. The DNA amount for a certain gene and the relative DNA amount among different samples estimated using our method were closer to the true values compared to the results of the 2^sup -ΔΔCT^ method.
Conclusions
The improved method, the individual efficiency corrected calculation, produces more accurate estimates in relative gene expression than the 2^sup -ΔΔCT^ method and is thus a better way to calculate relative gene expression.
Background
Quantitative real-time polymerase chain reaction (qPCR) has been extensively used to quantify gene expression levels. The two strategies for analyzing qPCR data are absolute and relative quantification (1- 3). Absolute quantification identifies the input gene amount based on a standard curve. In contrast, relative quantification determines changes in gene expression relative to a reference sample. Relative quantification is easier to perform than absolute quantification, and it requires fewer reagents, since there is no need to generate a standard curve (4). Errors caused by standard dilutions when creating a standard curve can also be avoided. In addition, sometimes the relative gene amount between two treatment groups is of more interest than exact DNA/RNA molecular numbers. Therefore, relative quantification is widely performed.
The 2^sup -ΔΔCT^ method is the method of relative quantification that is most frequently found in popular software packages for qPCR experiments (1, 5-6). The threshold...