Genome-wide identification and evaluation of novel internal control genes for Q-PCR based transcript normalization in wheat
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To accurately quantify gene expression using quantitative PCR amplification, it is vital that one or more ideal internal control genes are used to normalize the samples to be compared. Ideally, the expression level of those internal control genes should vary as little as possible between tissues, developmental stages and environmental conditions. In this study, 32 candidate genes for internal control were obtained from the analysis of nine independent experiments which included 333 Affymetrix GeneChip Wheat Genome arrays. Expression levels of the selected genes were then evaluated by quantitative real-time PCR with cDNA samples from different tissues, stages of development and environmental conditions. Finally, fifteen novel internal control genes were selected and their respective expression profiles were compared using NormFinder, geNorm, Pearson correlation coefficients and the twofold-change method. The novel internal control genes from this study were compared with thirteen traditional ones for their expression stability. It was observed that seven of the novel internal control genes were better than the traditional ones in expression stability under all the tested cDNA samples. Among the traditional internal control genes, the elongation factor 1-alpha exhibited strong expression stability, whereas the 18S rRNA, Alpha-tubulin, Actin and GAPDH genes had very poor expression stability in the range of wheat samples tested. Therefore, the use of the novel internal control genes for normalization should improve the accuracy and validity of gene expression analysis.
KeywordsInternal control genes Microarray Gene expression analysis Real-time PCR Wheat
The authors thank two anonymous reviewers for their constructive suggestions. This work was supported by the National Basic Research Program of China (973 Program 2010CB1344400 and 2009CB118304) and China Transgenic Research Program (2011ZX08002).
- Faccioli P, Ciceri GP, Provero P, Stanca AM, Morcia C, Terzi V (2007) A combined strategy of “in silico” transcriptome analysis and web search engine optimization allows an agile identification of reference genes suitable for normalization in gene expression studies. Plant Mol Biol 63:679–688PubMedCrossRefGoogle Scholar
- Goidin D, Mamessier A, Staquet MJ, Schmitt D, Berthier-Vergnes O (2001) Ribosomal 18 s RNA Prevails over glyceraldehyde-3-phosphate dehydrogenase and β-actin genes as internal standard for quantitative comparison of mRAN levels in invasive and non-invasive human melanoma cell subpopulations. Anal Biochem 295:17–21PubMedCrossRefGoogle Scholar
- Mitter K, Kotoulas G, Magoulas A, Mulero V, Sepulcre P, Figueras A, Novoa B, Sarropoulou E (2009) Evaluation of candidate reference genes for QPCR during ontogenesis and of immune-relevant tissues of European seabass (Dicentrarchus labrax). Comp Biochem Physiol 153B:340–347Google Scholar