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Quantitative RT-PCR can be a very sensitive and powerful technique for measuring differential gene expression. Changes in gene expression induced by abiotic stresses are complex and multifaceted, which make determining stably expressed genes for data normalization difficult. To identify the most suitable reference genes for abiotic stress studies in soybean, 13 candidate genes collected from literature were evaluated for stability of expression under dehydration, high salinity, cold and ABA (abscisic acid) treatments using delta CT and geNorm approaches. Validation of reference genes indicated that the best reference genes are tissue- and stress-dependent. With respect to dehydration treatment, the  Fbox / ABC ,  Fbox / 60s  gene pairs were found to have the highest expression stability in the root and shoot tissues of soybean seedlings, respectively.  Fbox  and  60s  genes are the most suitable reference genes across dehydrated root and shoot tissues. Under salt stress the  ELF1b / IDE  and  Fbox / ELF1b  are the most stably expressed gene pairs in roots and shoots, respectively, while  60s / Fbox  is the best gene pair in both tissues. For studying cold stress in roots or shoots,  IDE / 60s  and  Fbox / Act27  are good reference gene pairs, respectively. With regard to gene expression analysis under ABA treatment in either roots, shoots or across these tissues,  60s / ELF1b ,  ELF1b / Fbox  and  60s / ELF1b  are the most suitable reference genes, respectively. The expression of  ELF1b / 60s ,  60s / Fbox  and  60s / Fbox  genes was most stable in roots, shoots and both tissues, respectively, under various stresses studied. Among the genes tested,  60s  was found to be the best reference gene in different tissues and under various stress conditions. The highly ranked reference genes identified from this study were proved to be capable of detecting subtle differences in expression rates that otherwise would be missed if a less stable reference gene was used.

Evaluation of Candidate Reference Genes for Normalization of Quantitative RT-PCR in Soybean Tissues under Various Abiotic Stress Conditions