Identification of stable reference genes for qPCR studies in common wheat ( Triticum aestivum L.) seedlings under short-term drought stress

Abstract

Background

Quantitative PCR (qPCR) is one of the most common and accurate methods of gene expression analysis. However, the biggest challenge for this kind of examinations is normalization of the results, which requires the application of dependable internal controls. The selection of appropriate reference genes (RGs) is one of the most crucial points in qPCR data analysis and for correct assessment of gene expression. Because of the fact that many reports indicate that the expression profiles of typically used RGs can be unstable in certain experimental conditions, species or tissues, reference genes with stable expression levels should be selected individually for each experiment. In this study, we analysed a set of ten candidate RGs for wheat seedlings under short-term drought stress. Our tests included five ‘traditional’ RGs (GAPDH, ACT, UBI, TUB, and TEF1) and five novel genes developed by the RefGenes tool from the Genevestigator database.

Results

Expression stability was assessed using five different algorithms: geNorm, NormFinder, BestKeeper, RefFinder and the delta Ct method. In the final ranking, we identified three genes: CJ705892, ACT, and UBI, as the best candidates for housekeeping genes. However, our data indicated a slight variation between the different algorithms that were used. We revealed that the novel gene CJ705892, obtained by means of in silico analysis, showed the most stable expression in the experimental tissue and condition.

Conclusions

Our results support the statement, that novel genes selected for certain experimental conditions have a more stable level of expression in comparison to routinely applied RGs, like genes encoding actin, tubulin or GAPDH. Selected CJ705892 gene can be used as a housekeeping gene in the expression analysis in wheat seedlings under short-term drought. The results of our study will be useful for subsequent analyses of gene expression in wheat tissues subjected to drought.