Improved qPCR Quantification Method

The expression levels of human family with sequence similarity 73, member B (FAM73B) and GAPDH genes in limited dilution samples (1:10, 1:100, and 1:1000) were analyzed using qPCR. GAPDH was used as an internal control. Referring to the study design in Table 1, FAM73B is the target gene, and GAPDH is the reference gene. The original sample without any dilution is the reference, and a 1:10, 1:100, and 1:1000 dilution of the original sample are the target samples. There are 6 replicates in each combination of gene and dilution. The gene-specific primers were as follows: hgapdh-5′-ATGGAAATCCCATCACCATCTT-3′ and hgapdh-5′-CGCCCCACTTGATTTTGG-3′; hfam73b-5′-CTCCTGCAGGTGGTAGGC-3′ and hfam73b-5′-CAGAGACTGCATCAGAGCCA-3′. mRNA was extracted from human hepatoma (Huh7) cells and used as a template for reverse transcription by superscript III reverse transcriptase purchased from Invitrogen (Carlsbad, CA). All qPCR experiments were performed using the Applied Biosystems Stepone and StepOnePlus Real-Time system (Perkin-Elmer Applied Biosystems). All the amplifications were done using SYBR Green PCR Master Mix (Applied Biosystems). The thermal cycling conditions included an initial denaturation step at 95°C for 10 min, followed by 40 cycles at 95°C for 30s, 60°C for 30s, and 72°C for 30s. Melting curve analysis of every qPCR was conducted after each cycle.
In this study, we try to improve the 2^-ΔΔCT method. Our method, called the individual efficiency–corrected calculation method, is shown in Table 2. Unlike the 2^-ΔΔCT method, our method accounts for individual efficiencies of samples. We computed the amplification rate E (1 + efficiency) for each sample (Table 2, Eqs. 1-5). Specifically, the method was based on an exponential function, and background fluorescence was included in this function (Eq. 1). Then we took the difference between two consecutive PCR cycles by subtracting the fluorescence of the former cycle from that of the later cycle (Eq. 2). Therefore, the data with n cycles were transformed to data with n−1 cycles. Importantly, background fluorescence was removed. After that, a simple linear regression model (Eq. 4) was applied to the log-transformed equation (Eq. 3). The parameter (β₁) estimated using linear regression can be used to calculate E (Eq. 5). To calculate the starting DNA amount (x₀), we need to find out the new threshold cycle, CT', and we set the new threshold to T/2 (Eqs. 2 and 6). The fold change of gene expression level was calculated as the relative DNA amount of a target gene in a target sample and a reference sample, normalized to a reference gene (Eq. 7). The DNA amounts of a reference gene in reference and target samples are denoted as x_0,A and x_0,B, and the amounts of a target gene in the two groups are denoted as x_0,C and x_0,D, respectively. The derivation of CT' was based on the equal-ratio property of the difference value z_k and the cycle m, which is an integer cycle right before CT' (Eqs. 8-9). The fluorescence value z_m should be less than the new threshold T/2 because the selected data points had monotone increasing values of z_k.
For the 2^-ΔΔCT method, we directly used the threshold cycle values automatically generated by the qPCR system. For the individual efficiency corrected calculation method, we selected four successive cycles for every PCR run, the first three of which have the fluorescence values below the threshold and the last of which has a fluorescence value larger than the threshold. Therefore, the target cycles are the rounded threshold cycle and the former three cycles, or the rounded threshold cycle and the former two cycles plus the latter one.
In the individual efficiency corrected calculation method, we calculated PCR amplification efficiency for every sample. To reduce potential variation, we then took the mean of the efficiencies for the 6 replicates under each condition, which is a combination of gene and dilution. Hence, the 6 replicates had the same efficiency for further calculation, but each combination (for example, the combination of FAM73B and a 1:10 dilution) had a different efficiency.
Because the 2^-ΔΔCT method and our method are relative quantification strategies, it is difficult to assess their accuracy. This is why we planned to use a series of dilutions of the original sample to evaluate the accuracy of these two methods based on the pattern of the estimates. According to the experimental design, there were two trends in the estimates. First, for each gene, the ratios of the initial DNA amount were 1, 1:10 (0.1), 1:100 (0.01), and 1:1000 (0.001), corresponding to the four dilution conditions. The second trend was that the relative gene amounts (FAM73B/GAPDH) with respect to the four dilution conditions were the same, with a ratio of 1: 1: 1: 1 if the original sample without dilution was set to 1. The precision of the methods was then analyzed by computing coefficients of variation (CVs). The equation is:
where s and x̄ are the standard deviation and the mean of the 6 replicates in each combination of gene and dilution.