Validation of suitable reference genes for gene expression analysis in the halophyte Salicornia europaea by real-time quantitative PCR

Front Plant Sci. 2015 Jan 21;5:788. doi: 10.3389/fpls.2014.00788. eCollection 2014.


Real-time quantitative polymerase chain reaction (RT-qPCR), a reliable technique for quantifying gene expression, requires stable reference genes to normalize its data. Salicornia europaea, a stem succulent halophyte with remarkable salt resistance and high capacity for ion accumulation, has not been investigated with regards to the selection of appropriate reference genes for RT-qPCR. In this study, the expression of 11 candidate reference genes, GAPDH (Glyceraldehyde 3-phosphate dehydrogenase), Actin, α-Tub (α-tubulin), β-Tub (β-tubulin), EF1-α (Elongation factor 1-α), UBC (Ubiquitin-conjugating enzyme), UBQ (Polyubiquitin), CYP (Cyclophilin), TIP41 (TIP41-like protein), CAC (Clathrin adaptor complexes), and DNAJ (DnaJ-like protein), was analyzed in S. europaea samples, which were classified into groups according to various abiotic stresses (NaCl, nitrogen, drought, cold and heat), tissues and ages. Three commonly used software programs (geNorm, NormFinder and BestKeeper) were applied to evaluate the stability of gene expression, and comprehensive ranks of stability were generated by aggregate analysis. The results show that the relatively stable genes for each group are the following: (1) CAC and UBC for whole samples; (2) CAC and UBC for NaCl stress; (3) Actin and α-Tub for nitrogen treatment; (4) Actin and GAPDH for drought stress; (5) α-Tub and UBC for cold stress; (6) TIP41 and DNAJ for heat stress; (7) UBC and UBQ for different tissues; and (8) UBC and Actin for various developmental stages. These genes were validated by comparing transcriptome profiles. Using two stable reference genes was recommended in the normalization of RT-qPCR data. This study identifies optimal reference genes for RT-qPCR in S. europaea, which will benefit gene expression analysis under these conditions.

Keywords: RT-qPCR data normalization; drought stress; gene quantification; halophyte; housekeeping gene; nitrogen stress; salt stress; temperature stress.