Removal of artifact bias from qPCR results using DNA melting curve analysis

Abstract

Quantitative PCR (qPCR) allows the precise measurement of DNA concentrations and is generally considered to be straightforward and trouble free. However, analyses using validated Sybr Green I-based assays regularly amplify both the correct product and an artifact. Amplification of more than 1 product can be recognized when melting curve analysis is performed after the qPCR. Currently, such reactions need to be excluded from further analysis because the quantification result is considered meaningless. However, when the fraction of the fluorescence associated with the correct product can be determined, the quantitative result of the qPCR analysis can be corrected. The main assumptions of this correction model are: 1) the melting peak of the correct product can be identified, 2) the PCR efficiencies of all amplified products are similar, 3) the relative size of the melting peaks reflects the relative concentrations of the products, and 4) the relative concentrations do not change as the reaction reaches plateau. These assumptions were validated in a series of model experiments. The results show that the quantitative results can be corrected. Implementation of a correction for the presence of artifact amplification in the analysis of qPCR data leads to more reliable quantitative results in qPCR experiments.-Ruijter,

Lamin A/C Is Dispensable to Mechanical Repression of Adipogenesis

“…In this study, we did not validate our RNA-seq data using qPCR. While this may be seen as a limitation of the study, qPCR can be highly biased as it depends upon primer sequence design, variances in the target annealing temperatures, and the fact that results are usually referenced to a reference gene [ 45 , 46 ]. RNA-seq, in contrast, minimizes these inherent biases, especially the ones related to unforeseen variances in the reference gene due to experimental conditions, as the raw mRNA fragments are sequenced and aligned to the entire genome, thus providing an unbiased view of gene expression across all samples.…”

Use and Misuse of Cq in qPCR Data Analysis and Reporting

“…Substitution of Equation ( 8) into Equation (11), cancelling out N q and subsequent rearrangement results in the classic equation for efficiency-corrected relative quantification [14]:…”

“…Using a dataset with 93 validated assays, we have shown that amplification of nonspecific products occurs frequently, and that amplification of these products cannot simply be identified from a deviating PCR efficiency or a high C q value, indicated by the slopes and the positions of the amplification curves, respectively [12]. The PCR efficiency observed for reactions that amplify correct products, artefacts or both, are indistinguishable (Figure 7A) [11]. Although the C q value distributions overlapped for all assays, only 5% of the reactions that amplified only correct products had a C q above 34, whereas only 5% of the reactions with a C q under 27 amplified an artefact.…”

“…In case of a DNA-binding dye assay, melting curve analysis is a quick and easy way to identify the presence of another than the intended target in the amplification reaction (Figure 7B) [43]. When a saturating dye is used, the contribution of the artefact to the observed fluorescence can be determined from the melting curves and used for correction of the observed C q and N 0 values [11]. Figure 7.…”

“…In most sections of this paper, we will assume that the PCR only amplifies the intended specific product, without amplification of artefacts. However, amplification of artefacts may contribute to the observed fluorescence and thus lower the C q value [11]. Therefore, in Section 8, the relation between C q and artefact amplification will be discussed.…”