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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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Updated: Jul 1, 2025

Author Spotlight: Advancements in DNA Nanosensors – Addressing Sensitivity and Selectivity Challenges in Molecular Detection

Author Spotlight: Advancements in DNA Nanosensors – Addressing Sensitivity and Selectivity Challenges in Molecular Detection

Published on: February 9, 2024

Assumption-free analysis for amplification-based quantitative nucleic acid detection.

Yu Fu^1,2, Lu Lin^1,2, Chuanbo Liu¹

¹State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, People's Republic of China.

The Journal of Chemical Physics

|March 14, 2024

Summary

This summary is machine-generated.

Accurate nucleic acid quantification is crucial. This study introduces a new method that reconstructs amplification efficiency, improving accuracy over traditional threshold methods, especially with inhibitors.

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Area of Science:

Molecular Biology
Biotechnology
Bioanalytical Chemistry

Background:

Accurate detection and quantification of nucleic acids are vital for life sciences, biosecurity, food safety, and environmental monitoring.
Quantitative polymerase chain reaction (qPCR) is the gold standard for nucleic acid detection due to its sensitivity and precision.
Current qPCR data analysis relies on standard curves and a threshold method, which has limitations due to assumptions about amplification kinetics.

Purpose of the Study:

To address the limitations of the traditional threshold method in qPCR data analysis.
To develop a novel approach for absolute nucleic acid quantification that overcomes the constant efficiency assumption.
To enhance the reliability of nucleic acid quantification, particularly in challenging conditions like the presence of inhibitors.

Main Methods:

Utilized stochastic simulation to analyze the limitations of the threshold method in qPCR.
Developed a new method involving reconstruction of amplification efficiency profiles across cycles.
Employed cumulative amplification folds to construct a standard curve, bypassing the constant efficiency assumption.

Main Results:

Demonstrated the limitations of the threshold method stemming from its assumptions on amplification kinetics.
Validated the proposed method through experimental nucleic acid amplification, including in the presence of potent inhibitors.
Showcased improved accuracy in nucleic acid quantification compared to the traditional threshold method, mitigating systematic errors.

Conclusions:

The novel method provides more reliable absolute quantification of nucleic acids by accounting for kinetic variability.
This approach enhances the accuracy of qPCR analysis, especially in scenarios where traditional methods face challenges.
The findings contribute to more dependable nucleic acid detection and quantification for critical applications.