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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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Quantitative Real-Time PCR using the Thermo Scientific Solaris qPCR Assay

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Evaluating and Validating Sunflower Reference Genes for Q-PCR Studies Under High Temperature Condition.

Masood Soltani Najafabadi¹, Nazanin Amirbakhtiar¹

¹National Plant Genebank, Seed and Plant Improvement Institute, Agricultural Research, Education, and Extension Organization, Karaj, Iran.

Iranian Journal of Biotechnology

|May 25, 2023

Summary

This study identified stable reference genes for quantitative PCR (qPCR) in sunflower under heat stress. Actin2, EF-1a, SAND, and Importin are recommended for accurate gene expression normalization in different tissues and temperatures.

Keywords:

Heat stress Reference genes Sunflower

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Last Updated: Jul 29, 2025

Quantitative Real-Time PCR using the Thermo Scientific Solaris qPCR Assay

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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

Published on: February 25, 2017

Area of Science:

Molecular Biology
Plant Science
Genetics

Background:

Quantitative PCR (qPCR) is crucial for transcriptomics and validating gene expression data.
Accurate normalization is essential in qPCR to mitigate errors from RNA extraction and cDNA synthesis.
Identifying stable reference genes is vital for reliable gene expression studies, especially under stress conditions.

Purpose of the Study:

To identify stable reference genes for quantitative PCR (qPCR) in sunflower ( *Helianthus annuus* ).
To evaluate gene expression stability under varying ambient temperatures simulating heat stress.
To provide reliable normalization strategies for sunflower gene expression studies.

Main Methods:

Candidate reference genes ( *Actin2*, *SAND*, *GAPDH*, *Ubiquitin*, *EF-1a*, *Importin* ) were selected based on Arabidopsis and human homologs.
Primers were designed and specificity confirmed via melting curve analysis.
Gene expression stability was analyzed using geNorm, Bestkeeper, and Refinder algorithms across different tissues, genotypes, and temperatures (30°C and 40°C).

Main Results:

*Actin2* exhibited the highest expression level, while *EF-1a* showed the lowest.
*Actin2* was identified as the most stable reference gene across all tested conditions.
Specific combinations of reference genes (e.g., *Actin2*, *EF-1a*, *SAND* for vegetative tissues; *Actin2*, *EF-1a*, *SAND*, *Importin* for reproductive tissues) were recommended for normalization at different temperatures.

Conclusions:

This study introduces reliable reference genes for normalizing qPCR data in sunflower under heat stress.
Genotype-by-planting date interactions and tissue-specific expression patterns influence reference gene stability.
The findings facilitate accurate gene expression analysis in sunflower, particularly in response to environmental stress.