Relative quantification based on logistic models for individual polymerase chain reactions.
ABSTRACT The quantitative real-time reverse transcription polymerase chain reaction (RT-PCR) technology measures molecular variations in specific biomarkers. Relative quantification determines the target expression relative to an external standard or reference sample and should be adjusted for the PCR efficiencies actually achieved. More accurate methods of estimating PCR efficiency require a number of serial dilutions of the target sample, which is not generally feasible for clinical specimens. Alternatively, the efficiency of a single reaction may be estimated by considering kinetic data from this reaction. The current methods of estimating individual reaction efficiency require finding its exponential phase, which may affect the accuracy and precision of efficiency estimates. Thus, a model adequately representing all available kinetic RT-PCR data is preferable, but no such model is currently in use for relative quantification. In this work, we use a logistic model for all kinetic data from each RT-PCR and propose a new method of efficiency-adjusted relative quantification based on the estimates from the fitted logistic models. This method allows incorporating multiple replicates and possibly multiple reference ('housekeeping') genes for estimating relative expression and corresponding confidence interval. Real kinetic RT-PCR data are used to compare the proposed and standard methods. The methods are applied to the clinical data from the ongoing study of guanylyl cyclase C as a biomarker for colorectal cancer.
Article: Critical evaluation of methods used to determine amplification efficiency refutes the exponential character of real-time PCR.[show abstract] [hide abstract]
ABSTRACT: The challenge of determining amplification efficiency has long been a predominant aspect of implementing real-time qPCR, playing a critical role in the accuracy and reliability that can be achieved. Based upon analysis of amplification profile position, standard curves are currently the gold standard for amplification efficiency determination. However, in addition to being highly resource intensive, the efficacy of this approach is limited by the necessary assumption that all samples are amplified with the same efficiency as predicted by a standard curve. These limitations have driven efforts to develop methods for determining amplification efficiency by analyzing the fluorescence readings from individual amplification reactions. The most prominent approach is based on analysis of the "log-linear region", founded upon the presumption that amplification efficiency is constant within this region. Nevertheless, a recently developed sigmoidal model has provided new insights that challenge such historically held views, dictating that amplification efficiency is not only dynamic, but is linearly coupled to amplicon DNA quantity. Called "linear regression of efficiency" or LRE, this kinetic-based approach redefines amplification efficiency as the maximal efficiency (Emax) generated at the onset of thermocycling. This study presents a critical evaluation of amplification efficiency determination, which reveals that potentially large underestimations occur when exponential mathematics is applied to the log-linear region. This discrepancy was found to stem from misinterpreting the origin of the log-linear region, which is derived not from an invariant amplification efficiency, but rather from an exponential loss in amplification rate. In contrast, LRE analysis generated Emax estimates that correlated closely to that derived from a standard curve, despite the fact that standard curve analysis is founded upon exponential mathematics. This paradoxical result implies that the quantitative efficacy of positional-based analysis relies not upon the exponential character of real-time PCR, but instead on the ability to precisely define the relative position of an amplification profile. In addition to presenting insights into the sigmoidal character of the polymerase chain reaction, LRE analysis provides a viable alternative to standard curves for amplification efficiency determination, based on analysis of high-quality fluorescence readings within the central region of SYBR Green I generated amplification profiles.BMC Molecular Biology 11/2008; 9:96. · 2.86 Impact Factor