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Related Concept Videos

Real Time RT-PCR02:57

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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Development of a Quantitative Recombinase Polymerase Amplification Assay with an Internal Positive Control
08:37

Development of a Quantitative Recombinase Polymerase Amplification Assay with an Internal Positive Control

Published on: March 30, 2015

Robust quantification of polymerase chain reactions using global fitting.

Ana C Carr1, Sean D Moore

  • 1The Burnett School of Biomedical Sciences, College of Medicine, The University of Central Florida, Orlando, Florida, United States of America.

Plos One
|June 16, 2012
PubMed
Summary
This summary is machine-generated.

A new mathematical model enhances quantitative polymerase chain reactions (qPCR) accuracy by analyzing the entire DNA amplification profile. This method overcomes limitations of existing techniques, improving reproducibility and reducing costs in molecular biology applications.

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Area of Science:

  • Molecular Biology
  • Biotechnology
  • Genetics

Background:

  • Quantitative polymerase chain reactions (qPCR) are vital for monitoring minute DNA quantity changes.
  • Reproducibility issues in qPCR arise from noisy data and analytical method sensitivity to baseline and reaction profiles.
  • Existing methods struggle with variance introduced by baseline assignment and reaction-specific shapes.

Purpose of the Study:

  • To develop a novel mathematical model for improved qPCR data analysis.
  • To address the limitations of current methods in handling baseline noise and reaction variability.
  • To enhance the accuracy and precision of template abundance quantification in qPCR.

Main Methods:

  • Developed a simple mathematical model describing the entire PCR reaction profile.
  • The model utilizes two key variables: maximum reaction capacity and feedback inhibition.
  • The model formalizes influences of baseline errors, reaction efficiencies, and signal loss.

Main Results:

  • The new model provides more accurate quantification than existing methods by leveraging later-cycle fluorescence signals.
  • Identified that the common cycle-threshold method introduces variance due to inappropriate baseline adjustments and dynamic efficiencies.
  • Demonstrated that the model accounts for baseline defects and signal loss, improving data reliability.

Conclusions:

  • The model enables high-precision template abundance determination from raw qPCR data, even with defects.
  • This advancement reduces the time and cost associated with qPCR analysis.
  • The improved method has broad applicability in academic, clinical, and biotechnological research.