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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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Related Experiment Video

Updated: Jan 4, 2026

Single-cell Gene Expression Using Multiplex RT-qPCR to Characterize Heterogeneity of Rare Lymphoid Populations

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Published on: January 19, 2017

Selecting reference genes in RT-qPCR based on equivalence tests: a network based approach.

Emmanuel Curis^1,2,3, Calypso Nepost⁴, Diane Grillault Laroche^4,5

¹UMR-S 1144, INSERM Optimisation thérapeutique en neuropsychopharmacologie - université Paris Descartes - université Paris Diderot, Paris, France. emmanuel.curis@parisdescartes.fr.

Scientific Reports

|November 9, 2019

Summary

Selecting stable reference genes for quantitative reverse transcription PCR (RT-qPCR) is crucial. A new statistical method accounts for the compositional nature of RT-qPCR data, improving the reliability of reference gene selection.

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Area of Science:

Molecular Biology
Biostatistics
Genomics

Background:

Quantitative reverse transcription PCR (RT-qPCR) requires normalization using reference genes for accurate gene expression analysis.
Existing reference gene selection methods (NormFinder, geNorm) do not adequately address the compositional nature of RT-qPCR data, leading to potential inaccuracies.
Reliable reference gene selection is critical for the validity of gene expression studies.

Purpose of the Study:

To develop and validate a novel statistical method for selecting stable reference genes in RT-qPCR.
To address the limitations of current methods by incorporating the compositional nature of RT-qPCR data.
To provide a robust statistical framework for identifying reliable reference genes.

Main Methods:

A new method based on pairwise equivalence tests on gene expression ratios was developed.
The statistical procedure controls for the error rate in selecting inappropriate reference genes.
The method was applied to 30 candidate reference genes using RT-qPCR data from human lymphoblastoid cell lines.

Main Results:

The proposed method successfully identified 7 stable reference genes from 30 candidates.
The selection of reference genes showed consistency with geNorm but less so with NormFinder.
The study provides a statistically sound approach for reference gene identification in RT-qPCR.

Conclusions:

The developed statistical method offers a more reliable approach to reference gene selection by considering the compositional nature of RT-qPCR data.
This method enhances the fundamental basis for reference gene identification and can be applied to other gene expression analysis scenarios.
The SARP.compo R package is available for implementing this statistical procedure.