Competitive RT-PCR Strategy for Quantitative Evaluation -3
Competitive RT-PCR in Different Tilapia Tissues
Abundance levels of tiGHR I mRNA (target) in different tilapia tissues were measured using the quantitative RT-PCR by competition validated above. Liver RNA of three different tilapias was assayed in the presence of different quantities of competitor RNA. Densitometry data derived from band intensities of competitor and target for each tilapia were plotted as described in Section 2 (Fig. 5). We discarded the amplification of genomic DNA sequences because the specific oligonucleotides I and J hybridize to different exons, which means that, in the genomic DNA sequences between these oligonucleotides, there are introns. PCR amplifications from genomic DNA sequences would give a higher size than 366 bp and 473 bp expected for target and competitor amplifications, respectively. The quantity of specific RNA obtained for each tilapia liver was normalized versus the band intensity of the 28S subunit of the total RNA used in the RT reaction. The quantity of tiGHR I RNA reported here for liver is the average of the normalized data obtained from each tilapia. The coefficient of variation is presented in the Electronic supplementary material 2. The procedure with the other tilapia tissues was the same. The raw data can be seen too in file 2 of the Electronic supplementary material. The coefficients of variation of these experiments were between 10% and 50%. After the processing of all obtained data from the selected tilapia tissues, we obtained the profile of the expression levels of tiGHR I mRNA (Fig. 6).
Fig. 5 Determination of the quantity of tiGHR I RNA in tilapia liver. Lineal regressions with data from three different tilapias. The picture is an example of 2% agarose gel with the amplification products of competitive RT-PCR using total RNA from the liver of tilapia 4 and known quantities of competitor RNA. 1, molecular weight marker (leader 100 bp, Promega); 2, RT-PCR negative control; 3, RT-PCR with 5 × 105 molecules of RNA competitor alone; 4, RT-PCR with liver total RNA of tilapia alone; 5, 6, and 7, RT-PCR of liver total RNA of tilapia 4 with 3 × 105, 6 × 105, and 8 × 105 molecules of competitor, respectively.
Fig. 6 Expression of tiGHR I in different tilapia tissues. The non-parametric test of Kruskal–Wallis followed by Dunn’s post test only detected significant differences between liver and spleen and between liver and stomachs (p < 0.05).
Discussion
The exponential character of PCR amplification may compromise quantitative assays because it multiplies variations. The competitive PCR strategy used in the present study was aimed to overcome some of the limitations of the conventional RT-PCR. Co-amplification methods quantify the target DNA relative to a second control sequence in the same PCR tube. The main advantages of this technique are that the results are not affected by tube-to-tube variations in amplification efficiency and it is not necessary to restrict PCR to the exponential phase. Reliable quantification is still possible if the PCR extends into the linear phase, or even in the saturation phase, provided it is ascertained that the amplification efficiency is the same for both templates throughout the PCR, including the final cycles (12, 16). Quantitative co-amplification rests on the assumption that the product ratio of target and competitor sequences reliably reflects the ratio of their initial copy numbers. Therefore, it is requisite that efficiency is identical for both sequences. If the target sequence (T) and the competitor sequence (C) would amplify with the smallest difference in this efficiencies, it can lead to very different quantities of the end products. This can result in an erroneous estimation of the amount of initial material [12, 16]. Figure 3 shows that the efficiencies in our system for target and competitor are equal in each cycle, even if the efficiencies decrease in the later cycles. The validity of the competition reactions to each quantity of target was established by the generated regression equations with their corresponding significant R 2 values (Figure 4). The slope of the regression curves obtained was close to 1 in all five standard curves, indicating that no differential amplification rates exist between T and C in the range of assayed T. Variability in the 10,000- to 1,000,000-molecule ranges of target sequence was determined. Coefficients of variation according to non log-transformed absolute values were 8% inter-assay and ranging between 3.14% and 8.4 % intra-assay for 100,000 molecules of T. CVs of 21.89%, 36%, 12.07%, and 13.78% intra-assay for 10,000, 150,000, 200,000, and 1,000,000 molecules of T, respectively were obtained (Table 3). In general, lower target quantities give higher CVs. Our variability is in the range of the variability of the PCR assay [17, 18]. In general, CVs corresponding to reaction conditions, in which the quantity of target and competitor was equivalent or nearby, were under 10%, and CVs corresponding to reaction conditions, in which the ratio C/T was 10 or 1/10, were between 10% and 35%. Other authors affirm that more time-consuming methods of RNAse protection assay and Northern blots are more accurate and precise than RT-PCR. However, it has been reported that RNAse protection assay could detect approximately 1 × 106 target transcripts and it has been estimated that a Northern blot is about tenfold less sensitive than RNAse protection assay (19), then they are limited to study those genes that are relatively highly expressed. Our competitive PCR was able to detect at least 750 molecules of DNA target sequence in 50 µl of PCR. If we assume 10% of efficiency of the RT reaction, the LLQ of our system would be 7.5 × 103target transcripts. Therefore, this assay is more sensitive than RNase protection and Northern blot assays. Our results show that our design of competitive PCR together with RT reaction is useful to study the expression level of tiGHR I in different tissues of tilapia (O. niloticus). By using in vitro transcribed competitor RNA, we have been able to reduce sources of variation such as the variable efficiency of the reverse transcription reaction because the quantity of competitor RNA molecules that we put together with specific tissue total RNA samples is reverse transcribed with the same efficiency that the molecules of RNA target in each sample.
