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Open Access Highly Accessed Research article

Experimental comparison of relative RT-qPCR quantification approaches for gene expression studies in poplar

Nicole Regier12 and Beat Frey1*

Author Affiliations

1 Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903 Birmensdorf, Switzerland

2 Current Address: Université de Genève, Institut Forel, CP 416, 1290 Versoix, Switzerland

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BMC Molecular Biology 2010, 11:57  doi:10.1186/1471-2199-11-57

Published: 11 August 2010

Abstract

Background

RT-qPCR is a powerful tool for analysing gene expression. It depends on measuring the increase in fluorescence emitted by a DNA-specific dye during the PCR reaction. For relative quantification, where the expression of a target gene is measured in relation to one or multiple reference genes, various mathematical approaches are published. The results of relative quantification can be considerably influenced by the chosen method.

Results

We quantified gene expression of superoxide dismutase (SOD) and ascorbate peroxidase (APX) in the roots of two black poplar clones, 58-861 and Poli, which were subjected to drought stress. After proving the chosen reference genes actin (ACT), elongation factor 1 (EF1) and ubiquitin (UBQ) to be constantly expressed in the different watering regimes, we applied different approaches for relative quantification to the same raw fluorescence data. The results obtained using the comparative Cq method, LinRegPCR, qBase software and the Pfaffl model showed a good correlation, whereas calculation according to the Liu and Saint method produced highly variable results. However, it has been shown that the most reliable approach for calculation of the amplification efficiency is using the mean increase in fluorescence during PCR in each individual reaction. Accordingly, we could improve the quality of our results by applying the mean amplification efficiencies for each amplicon to the Liu and Saint method.

Conclusions

As we could show that gene expression results can vary depending on the approach used for quantification, we recommend to carefully evaluate different quantification approaches before using them in studies analysing gene expression.