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Real Time RT-PCR

Real Time RT-PCR

Real-time reverse transcription-polymerase chain reaction, or Real-time RT-PCR, is an analytical tool used to determine the expression level of target genes. The method involves converting mRNA to complementary DNA with the help of an enzyme known as reverse transcriptase, followed by the PCR amplification of the cDNA. These two processes can be performed simultaneously in a single tube or separately as a two-step reaction.
The real-time quantification of the number of amplified products is...

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Affine analysis for quantitative PCR measurements.

Paul N Patrone¹, Erica L Romsos², Megan H Cleveland²

¹National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899, USA. paul.patrone@nist.gov.

Analytical and Bioanalytical Chemistry

|September 20, 2020

Summary

This summary is machine-generated.

This study introduces a novel data analysis method for quantitative polymerase chain-reaction (qPCR) to identify true signals. The approach harmonizes qPCR data, improving confidence and lowering detection limits for disease diagnostics.

Keywords:

DNA detection Data analysis Measurement sensitivity SARS-CoV-2 qPCR

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Area of Science:

Molecular Biology
Biotechnology
Data Science

Background:

Quantitative polymerase chain-reaction (qPCR) is crucial for detecting nucleic acids, but data analysis can be challenging.
Variability in qPCR amplification curves complicates accurate signal identification and interpretation, especially during the COVID-19 pandemic.

Purpose of the Study:

To develop a theoretical framework and data analysis procedure for identifying true qPCR signals.
To establish conditions for qPCR amplification curves to be identical under affine transformation.
To create a transferable master reference curve for harmonized qPCR analysis.

Main Methods:

Derivation of a theoretical result for affine transformation of qPCR amplification curves.
Development of a data analysis procedure using constrained optimization to map measurement signals to a master curve.
Application to reverse-transcriptase qPCR data for SARS-CoV-2 RNA detection.

Main Results:

Demonstrated that qPCR curves can be made identical via affine transformation (multiplicative factor and horizontal shift).
The developed procedure can decrease the fluorescence detection threshold by up to 10-fold.
Improved confidence in interpreting late-cycle amplification curves and established a transferable master curve.

Conclusions:

The proposed data analysis method enhances the reliability of qPCR measurements.
This approach can harmonize qPCR analyses across different laboratories and time points.
The method shows promise for improving diagnostic testing of emerging diseases like COVID-19 by increasing confidence and reducing detection limits.