Reference gene selection for qRT-PCR analyses of luffa (Luffa cylindrica) plants under abiotic stress conditions.

Affiliation

Chen MD(1), Wang B(1), Li YP(1), Zeng MJ(1), Liu JT(1), Ye XR(1), Zhu HS(2), Wen QF(3).
Author information:
(1)Fujian Key Laboratory of Vegetable Genetics and Breeding, Crops Research Institute, Fujian Academy of Agricultural Sciences, Vegetable Research Center, Fujian Engineering Research Center for Vegetables, Fuzhou, 350013, Fujian, China.
(2)Fujian Key Laboratory of Vegetable Genetics and Breeding, Crops Research Institute, Fujian Academy of Agricultural Sciences, Vegetable Research Center, Fujian Engineering Research Center for Vegetables, Fuzhou, 350013, Fujian, China. [Email]
(3)Fujian Key Laboratory of Vegetable Genetics and Breeding, Crops Research Institute, Fujian Academy of Agricultural Sciences, Vegetable Research Center, Fujian Engineering Research Center for Vegetables, Fuzhou, 350013, Fujian, China. [Email]

Abstract

Selecting suitable internal reference genes is an important prerequisite for the application of quantitative real-time PCR (qRT-PCR). However, no systematic studies have been conducted on reference genes in luffa. In this study, seven reference genes were selected, and their expression levels in luffa plants exposed to various simulated abiotic stresses [i.e., cold, drought, heat, salt, H2O2, and abscisic acid (ABA) treatments] were analyzed by qRT-PCR. The stability of the reference gene expression levels was validated using the geNorm, NormFinder, BestKeeper, and RefFinder algorithms. The results indicated that EF-1α was the most stably expressed and suitable reference gene overall and for the heat, cold, and ABA treatments. Additionally, UBQ expression was stable following the salt treatment, whereas TUB was identified as a suitable reference gene for H2O2 and drought treatments. The reliability of the selected reference genes was verified by analyzing the expression of copper/zinc superoxide dismutase (Cu/Zn-SOD) gene in luffa. When the most unstable reference genes were used for data normalizations, the resulting expression patterns had obvious biases when compared with the expression patterns for the most ideal reference genes used alone or combined. These results will be conducive to more accurate quantification of gene expression levels in luffa.