Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data

Despite the central role of quantitative PCR (qPCR) in the quantification of mRNA transcripts, most analyses of qPCR data are still delegated to the software that comes with the qPCR apparatus. This is especially true for the handling of the fluorescence baseline. This article shows that baseline estimation errors are directly reflected in the observed PCR efficiency values and are thus propagated exponentially in the estimated starting concentrations as well as ‘fold-difference’ results. Because of the unknown origin and kinetics of the baseline fluorescence, the fluorescence values monitored in the initial cycles of the PCR reaction cannot be used to estimate a useful baseline value. An algorithm that estimates the baseline by reconstructing the log-linear phase downward from the early plateau phase of the PCR reaction was developed and shown to lead to very reproducible PCR efficiency values. PCR efficiency values were determined per sample by fitting a regression line to a subset of data points in the log-linear phase. The variability, as well as the bias, in qPCR results was significantly reduced when the mean of these PCR efficiencies per amplicon was used in the calculation of an estimate of the starting concentration per sample

SPIDIA-RNA: First external quality assessment for the pre-analytical phase of blood samples used for RNA based analyses

n/

Conductive composites for oligonucleotide detection

© 2017 The Authors A new method for oligonucleotide detection is presented based on oligonucleotide cross-linked polymer composites. Conductive carbon nanoparticles are incorporated into a DNA-functionalised polymer, containing partially complementary oligonucleotide cross-linkers, which is polymerised in situ upon interdigitated electrodes. In the presence of an aqueous solution of a specific analyte oligonucleotide sequence, the cross-linkers are cleaved, leading to increased swelling. As the polymer swells the relative density of the conductive particles decreases, leading to an easily measurable decrease in electrical conductivity. We demonstrate that such are capable of discriminating between analyte and control solutions, with single-base specificity, in under 3 min. The lower detection limit of these composites is of the order of 10 nM. The swelling characteristics of these composites is confirmed by optical imaging and the effects of varying temperature upon such composites are also reported

Model based analysis of real-time PCR data from DNA binding dye protocols

BACKGROUND: Reverse transcription followed by real-time PCR is widely used for quantification of specific mRNA, and with the use of double-stranded DNA binding dyes it is becoming a standard for microarray data validation. Despite the kinetic information generated by real-time PCR, most popular analysis methods assume constant amplification efficiency among samples, introducing strong biases when amplification efficiencies are not the same. RESULTS: We present here a new mathematical model based on the classic exponential description of the PCR, but modeling amplification efficiency as a sigmoidal function of the product yield. The model was validated with experimental results and used for the development of a new method for real-time PCR data analysis. This model based method for real-time PCR data analysis showed the best accuracy and precision compared with previous methods when used for quantification of in-silico generated and experimental real-time PCR results. Moreover, the method is suitable for the analyses of samples with similar or dissimilar amplification efficiency. CONCLUSION: The presented method showed the best accuracy and precision. Moreover, it does not depend on calibration curves, making it ideal for fully automated high-throughput applications