Introduction

Quantitative real-time PCR (RT-qPCR) is a reliable and widely used technique to quantify target gene expression patterns in various fields of biological research, due to its high sensitivity, accuracy and reproducibility1,2,3. However, the accuracy of RT-qPCR is influenced by various factors, including the quantity of mRNA templates, enzymatic efficiency in cDNA synthesis and PCR amplification4. Thus, to avoid bias, it is necessary to select reliable reference genes that are steadily expressed under different experimental conditions before determining the expression pattern of a target gene by RT-qPCR.

Traditional reference genes, such as elongation factor 1 alpha (EF1α), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), actin (ACT) and ubiquitin (UBQ), are mostly involved in intermediary metabolism or other basic cellular processes5,12, have been developed for the evaluation of potential reference gene(s) in different experimental systems.

Flowers of higher plants are reproductive organs that are widely studied and are important ornamental characteristics of ornamental plants. A number of reference genes have been reported for different flowering stages of various ornamental plants species, such as chrysanthemum13, petunia14, azalea15 and tree peony16, but little information is available concerning reference genes for Iris. Iris germanica L., which is often referred to as Pogon iris, is one of the most important ornamental species in the Iris genus17, the posture of the flower is peculiar and the flowers are rich and have high ornamental and economic value. However, the spring-time flowering habit and short duration of flowering of I. germanica hinder its year-round supply and economic benefits. To enable additional detailed and in-depth studies of the expression level of key genes involved in flowering, it is necessary to identify the stability of candidate reference genes at various flowering stages in I. germanica. Recently, studies have been shown that ACT11 performed well in different tissues but poorly in different flower development stages in I. germanica cultivar ‘Huang**jia’. Furthermore, TUA performed best in different flower development stages but was the worst in different tissues18. Nevertheless, limited information is available concerning reference genes for flowering stages in I. germanica.

In the present study, the expression stability of eight candidate reference genes, IgEF1α, IgGAPDH, IgACT6, IgUBQ, IgUBC (ubiquitin-protein ligase), IgEF1β (elongation factor 1β), IgPGK (phosphoglycerate kinase), IgTUB (beta-tubulin), was validated by RT-qPCR during flower development in different cultivars of I. germanica. Four statistical algorithms, GeNorm10, BestKeeper12, NormFinder11, and Ref-finder (http://www.leonxie.com/referencegene.php) were used to evaluate the most suitable reference genes needed for normalization. To verify the usefulness of the selected reference genes, the relative expression levels of IgFT, a putative homolog of Flowering Locus T (FT) gene in Arabidopsis, was analyzed during flower bud development and in different genotypes of I. germanica. This is the first report about the selection of reference genes during flower bud development and will benefit future studies on gene expression of flowering stages in I. germanica and other related species.

Results

Assessment of primer specificity and amplification efficiency of reference genes

The gene names, primer sequences and amplicon length characteristics of the 8 reference genes are summarized in Table 1. The primer specificities were verified by agarose gel electrophoresis, only a specific product of the expected size was observed, and no primer dimers were detected (Supplementary Fig. S1). In addition, only a single peak was found in the melting curves of the amplified products of all genes, indicating that no primer dimers were generated (Supplementary Fig. S2). The amplification efficiency (E) of each reference gene varied from 98.47% for IgGAPDH to 101.74% for IgUBQ, and the correlation coefficients (R2) ranged from 0.9984 to 0.9998 (Table 1). The amplicon size ranged from 107 for IgACT6 to 295 bp for IgUBQ.

Table 1 Primer sequences and characteristics of PCR amplifications in I. germanica.
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Expression levels and profiles of reference genes

The quantification cycle (Cq) values of eight reference genes were assayed by RT-qPCR analysis, with lower Cq values representing relatively higher mRNA transcript levels. Cq values for each of the 8 candidate reference genes in three different genotypes of I. germanica are listed in supplementary Table S1. The average Cq values of these reference genes ranged from 19.83 to 27.61 for the highest and lowest expression levels, respectively, across all samples (Fig. 1). In addition, the standard deviations (SD) of Cq values were used to determine reference gene stability levels. Genes with relatively high SD of Cq values showed more variable expression than did those with lower SD. IgGAPDH showed the least variation in gene expression (23.69 ± 0.36) and presented the lowest SD, while IgEF1β showed the most variable levels of expression (23.16 ± 1.38).

Figure 1
figure 1

Cq values of the 8 candidate reference genes in all samples of I. germanica. Line across the box-plot of Cq value depicts median values. The outside box is determined by the 25th and 75th percentiles. The whiskers represent the maximum and minimum values.

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Expression stability of reference genes

To further select the most appropriate reference gene for RT-qPCR-based analysis in the investigation of flower development across three different I. germanica cultivars, four software programs, GeNorm, NormFinder, BestKeeper and RefFinder were used to analyze the expression stability of each reference gene.

GeNorm analysis

GeNorm program was used to evaluate the expression stability of the 8 candidate reference genes by calculating average expression stability (M) values based on the average pairwise variation among all the tested genes. According to GeNorm algorithm, stably expressed genes had M values below 1.5, and a relatively low M value indicates a relatively stable expression10. In this study, all of the tested genes showed high expression stability, with M-values of < 1.5, indicating that they all conformed to basic requirements for function as reference genes. IgUBC and IgGAPDH were the most stable reference genes in both ‘00246’ and ‘Elizabeth’, while IgTUB and IgGAPDH were identified as the most stable in ‘2010200’. In terms of the total samples tested, IgUBC and IgGAPDH were recommended as the most stable reference genes. In contrast, IgUBQ with the highest M value was identified as the least stable reference gene in all of the samples (Fig. 2).

Figure 2
figure 2

Average expression stability values (M) of 8 candidate reference genes predicted by GeNorm software. The most stable genes are on the right, while the least stable genes are on the left. (A) ‘00246’, (B) ‘2010200’, (C) ‘Elizabeth’, and (D) all samples.

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The optimal number of reference genes was also measured by determining the pairwise variation between sequentially ranked genes (Vn/Vn + 1) based on the GeNorm algorithm (Fig. 3). Generally speaking, a cutoff of 0.15 (Vn value) has been recommended as the threshold to determine the optimal number of reference genes10. Our results reveal that the V2/3 values of the ‘00246’, ‘2010200’ and ‘Elizabeth’ samples were lower than 0.15 (Fig. 3), suggesting that two reference genes were sufficient for accurate normalization. However, the value of 0.15 should not be a fixed threshold, and higher cutoff values of Vn/n + 1 have been shown in several reports19,20. Our data showed small variation between V2/3 and V3/4 across all the samples, suggesting that two reference genes were sufficient for normalization (Fig. 3), which was similar to results in bermudagrass21 and Kentucky bluegrass22.

Figure 3
figure 3

Pairwise variation (V) of 8 candidate reference genes were calculated by GeNorm. Vn/Vn + 1 value were used to determine the optimal number of reference genes.

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NormFinder analysis

NormFinder is used to determine the stability value of reference genes, based on inter- and intragroup variance in different sample groups11. The stability value is then calculated, with a relatively low stability value meaning that the gene is relatively stable. Reference gene stability values were calculated by NormFinder, as shown in Table 2. IgUBC and IgGAPDH were the two most stable genes among the total group, while IgUBQ was the least stable. The top two most stably expressed genes were IgUBC and IgGAPDH in both ‘00246’ and ‘2010200’, and IgUBC and IgTUB in ‘Elizabeth’. The ranking order generated by this method was slightly different from that of GeNorm.

Table 2 Expression stability analysis of 8 candidate reference genes calculated using NormFinder software.
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BestKeeper analysis

BestKeeper evaluates the stability of reference genes based on the standard deviation (SD) and coefficients of variation (CV) of Cq values, with relatively low SD and CV representing relatively high stability12. The results of BestKeeper analysis are listed in Table 3. IgGAPDH and IgUBC were recommended as the most stable genes in ‘00246’, ‘Elizabeth’ and across all the samples, which was similar to the results from the GeNorm and NormFinder analysis. In ‘2010200’ samples, IgTUB and IgACT6 were detected as the most stable genes via BestKeeper analysis, whereas IgACT6 was ranked fourth by GeNorm and sixth by NormFinder.

Table 3 Expression stability analysis of 8 candidate reference genes calculated using BestKeeper software.
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RefFinder analysis

RefFinder (http://www.leonxie.com/referencegene.php) was used to obtain the comprehensive rankings of reference genes by integrating three common analysis programs: GeNorm, NormFinder and BestKeeper13,27. The putative homologs of 8 reference genes were identified from the transcriptomic data sequences of Iris lactea var. chinensis49. All the candidate reference genes were cloned in Stage 4 samples and confirmed through sequencing. Primers were designed using Primer 5.0 software (Premier Biosoft International) with melting temperatures (TM) of 55–65 ℃, primer lengths of 18–25 bp and amplicon lengths of 107–295 bp (Table 1). The performance of the primers was tested by qPCR and the specificity of the primer amplicons was further verified by 2% (w/v) gel electrophoresis.

Quantitative real-time PCR (RT-qPCR)

qPCR was performed using a Mastercycler ep realplex 2S device (Eppendorf, Germany) in conjunction with SYBR Premix Ex Taq II (TaKaRa, Dalian, China). Reactions were performed in a total volume of 20 μL containing 5 μL of diluted cDNA, 0.6 μL of each of forward and reverse primer (10 μM), 10 μL of 2 × SYBR Premix and 3.8 μL of ddH2O. The amplification program comprised an initial denaturation step (95℃ for 2 min), followed by 40 cycles of 95℃ for 5 s, 60℃ for 30 s, and 72 ℃ for 30 s, and a melting curve protocol (60–95 ℃ with a temperature increment of 0.5 ℃ s−1). Each RT-qPCR was performed for three biological and three technical replicates, and negative controls were included for each primer pair. Amplification efficiency (E) and correlation coefficient (R2) values were obtained from standard curves generated using a tenfold diluted cDNA series, the starting quantity of cDNA was 500 ng/μL50.

Data analysis

The stability of the eight candidate reference genes was assessed using GeNorm10, NormFinder software11, BestKeeper12, and Ref-finder (http://www.leonxie.com/referencegene.php). For GeNorm and NormFinder analysis, quantification cycle (Cq) values were transformed into relative expression levels using the formula: 2−∆Cq, in which ∆Cq = each corresponding Cq value-the minimum Cq value16. The expression stability measurement (M) was determined by the GeNorm program based on the average pairwise variations (V) among all the other reference genes. NormFinder program estimates intra- and intergroup variations, and the lowest stability is ranked the highest. Calculations of the BestKeeper program are calculated based on the coefficients of variation (CV) and the standard deviations (SD) of the Cq values, and the lowest CV and SD were used as detection indexes for the most-stable reference genes. Ref-finder is an online tool that integrates the results of the currently available major computational programs, including GeNorm (M values), NormFinder (stability values), BestKeeper (CV and SD), and ∆Cq values.

Validation of selected reference genes

To validate the influence of the choice of different reference genes on the final normalized outcome, the relative expression levels of IgFT which plays an important role in promoting flowering51 in three cultivars were analyzed using individual stably expressed or unstably expressed genes or a combination of stable reference genes, as determined by GeNorm48. The primers used for IgFT are presented in Table 1. The fold change of gene expression was calculated using the 2−∆∆Ct method24.

Conclusions

This research provided the first systematic analysis for the selection of stable reference genes as the internal control in RT-qPCR analysis in different flowering stages and different genotypes of I. germanica cultivars. Analysis using GeNorm, NormFinder, BestKeeper, and Ref-finder revealed that IgUBC, IgGAPDH, and IgTUB could be considered as appropriate reference genes for gene expression analysis in future molecular researches that aim to understand the mechanisms of flowering stages in I. germanica.