BackgroundStellera chamaejasme Linn, an important poisonous plant of the China grassland, is toxic to humans and livestock. The rapid expansion of S. chamaejasme has greatly damaged the grassland ecology and, consequently, seriously endangered the development of animal husbandry. To draft efficient prevention and control measures, it has become more urgent to carry out research on its adaptive and expansion mechanisms in different unfavorable habitats at the genetic level. Quantitative real-time polymerase chain reaction (qRT-PCR) is a widely used technique for studying gene expression at the transcript level; however, qRT-PCR requires reference genes (RGs) as endogenous controls for data normalization and only through appropriate RG selection and qRT-PCR can we guarantee the reliability and robustness of expression studies and RNA-seq data analysis. Unfortunately, little research on the selection of RGs for gene expression data normalization in S. chamaejasme has been reported.MethodIn this study, 10 candidate RGs namely, 18S, 60S, CYP, GAPCP1, GAPDH2, EF1B, MDH, SAND, TUA1, and TUA6, were singled out from the transcriptome database of S. chamaejasme, and their expression stability under three abiotic stresses (drought, cold, and salt) and three hormone treatments (abscisic acid, ABA; gibberellin, GA; ethephon, ETH) were estimated with the programs geNorm, NormFinder, and BestKeeper.ResultOur results showed that GAPCP1 and EF1B were the best combination for the three abiotic stresses, whereas TUA6 and SAND, TUA1 and CYP, GAPDH2 and 60S were the best choices for ABA, GA, and ETH treatment, respectively. Moreover, GAPCP1 and 60S were assessed to be the best combination for all samples, and 18S was the least stable RG for use as an internal control in all of the experimental subsets. The expression patterns of two target genes (P5CS2 and GI) further verified that the RGs that we selected were suitable for gene expression normalization.DiscussionThis work is the first attempt to comprehensively estimate the stability of RGs in S. chamaejasme. Our results provide suitable RGs for high-precision normalization in qRT-PCR analysis, thereby making it more convenient to analyze gene expression under these experimental conditions.