Introduction

Bletilla striata (Thunb.) Reihb.f. is a kind of perennial herbaceous plant belonging to the Bletilla genus of Orchidaceae. The dried tuber is usually regarded as medicinal and is named “Bai-ji” in Chinese. This tuber is considered to be a precious traditional Chinese herbal medicine. Hundreds of compounds have already been isolated from B. striata, such as polysaccharides, bibenzyls, stilbenes, phenanthrenes, triterpenoids and steroids (Zhang et al. 2019). These compounds have a variety of biological activities and functions. In traditional medicine, B. striata has been widely used for thousands of years to stop bleeding mainly from the stomach and lungs and for detumescence. Modern pharmacology research has further proven that B. striata fights against bacteria (Li et al. 2014; Guo et al. 2016; Jiang et al. 2019), influenza A virus (Shi et al. 2017), fibrosis (Wang et al. 2014) and tumorigenesis (Zhan et al. 2014) and promotes wound (Diao et al. 2008; Luo et al. 2010) and oral ulcer healing (Liao et al. 2019). Additionally, B. striata is used as a hemostatic agent since it promotes rapid blood coagulation (Hung and Wu 2016; Zhang et al. 2017). “Yunnan Bai Yao”, made mainly from B. striata, has been popular for wound healing for more than a hundred years. In addition to applications in the medical field, B. striata has also been widely used in food and chemical industries because of its high anti-oxidative (Qu et al. 2016) and anti-aging (Lee et al. 2013) activities. Facial masks containing products derived from B. striata have whitening effects and prevent or cure common oral and dental disease when added to toothpaste with negligible adverse effects.

B. striata is also identified as a high-end ornamental flower because of its bright purple perianths and pleasant fragrance. Due to its wide range of application, the demand for B. striata has increased sharply. Meanwhile, B. striata possesses the general character of orchids in that its seed has no endosperm. Therefore, the natural reproduction rate is determined to be very low. The increasing demand and low reproduction rate of B. striata have resulted in the rapid depletion of B. striata as a wild resource. Therefore, artificial or semi-artificial cultivation has been adopted for B. striata in many areas. Currently, B. striata is under second-class protection on the national rare and endangered wild plant conversion list in China (Zhang et al. 2019).

B. striata is mainly distributed between 100 and 3200 meters of altitude in south and southwest China, Japan, Thailand, and Myanmar (Zhuang et al. 2019). It grows in damp gullies or hillsides, prefers shade and humid environments, and has no resistance to high temperatures or sun exposure. The leaves turn yellow, and development is inhibited significantly under ambient temperatures higher than 36°C. Therefore, the discovery of heat-resistant genes is one of the most important efforts in breeding research on B. striata.

Quantitative real-time PCR (qRT-PCR) analysis, with many benefits of simplicity, accuracy, specificity, short turn-around time and high-throughput characteristics, has been used in a variety of fields about study relative expression level of target genes (Bustin et al. 2005; Huggett et al. 2005; Shukla et al. 2019). There are many rules that must be followed to ensure reproducible and accurate results using qRT-PCR (Udvardi et al. 2008; Derveaux et al. 2010). Among them, use of reliable reference genes for data normalization is crucial for proper analysis (Gutierrez et al. 2008). Previous reports have suggested that expression profiles of reference genes vary between species, tissues, and treatments, even that of genes that are widely used as references (Argyropoulos et al. 2006). No single reference gene has been determined that is always expressed stably under any condition (Argyropoulos et al. 2006). Accordingly, it is crucial to discover suitable internal control genes with stable expression for the study of specific transcriptional profiles of genes of interest under a certain experimental condition for a certain species (Yang et al. 2019). There are many reports on screening for proper reference genes in plants, however, there has been no report regarding reference genes for the study of B. striata.

In this study, seven potential reference genes were isolated from the leaves of B. striata using a homologous cloning method, and then, gene-specific primers for qRT-PCR were designed. The transcription levels of these candidates in different tissues with heat treatment for different durations were measured using qRT-PCR, and the stability of the transcript levels was evaluated using three conventional statistical software and comprehensive RefFinder algorithms. Moreover, the expression profile of one target gene which involved in photosynthesis, BsrbcL, was analyzed to verify the reliability of selected reference genes. These results are of significance to the study of genes involved in high temperature resistance and genetic breeding for B. striata.

Materials and Methods

Plant materials and treatments

Two-year-old B. striata plants were selected and pre-cultured in a growth chamber (PERCIVAL E-41HO2, USA) under controlled conditions 26°C, 12 h light/12 h dark, 70% relative humidity, 100 μmol·m^-2·s^-1of light intensity for a week. Then, the plants were cultured at 40°C to induce high temperature stress for different durations and the other conditions remained unaltered. Five seedlings were used for each sampling, and the experiment was replicated three times. The leaves, tubers, and roots were sampled separately at 0, 1, 2, 4, 8, 12, 24, and 48 h under high temperature stress. Then all samples were immediately frozen in liquid nitrogen and stored at −80°C for further step.

Template preparation

Total RNA from different tissues of B. striata seedlings was then extracted using an HP Plant RNA Kit R6837-01 (OMEGA Biotech, China). Then, a RevertAid First Strand cDNA Synthesis Kit was used to synthesize the first cDNA strand for ordinary PCR and clone the candidate reference genes. PrimeScript RT reagent Kit with gDNA Eraser (TakaRa, Japan) was used to synthesize the first cDNA strand for real-time PCR.

Isolation of potential reference genes

A total of seven genes for candidates including glyceraldehydes-3-phosphate dehydrogenase (GAPDH), α-tubulin (TUA), β-tubulin (TUB), 18S ribosomal RNA (18S), ubiquitin (UBI), elongation factor 1 alpha (EF1α), and NAC domain protein (NAC) were selected for expression studies in B. striata under high temperature stress. Degenerate primers were designed according to conserved regions of the seven candidate genes. The reaction conditions for ordinary PCR were as follows: 5 min for pre-denaturing at 94°C, followed by 35 cycles of denaturing for 40 s at 94°C, annealing for 40 s at 55–58°C, and extension for 40–80 s at 72°C. Additionally, extension at 72°C for 10 min was performed as the final step.

qRT-PCR analysis of candidate genes

Specific primer pairs for qRT-PCR were designed according to the obtained seven gene sequences isolated from B. striata using ordinary PCR. Each reaction mixture contained 10 μL of 2 × SYBR Premix Ex Taq II, 2 μL of cDNA, 0.8 μL of primer (10 μM) and add ddH₂O to the total volume of 20 μL. Reaction conditions were as follows: 30 s for pre-denaturing at 95°C and 40 cycles of 15 s at 95°C, 15 s at 58°C, and 15 s at 72°C. Melting curve analysis was conducted by melting the templates at temperatures from 60°C to 95°C. Amplification efficiencies (E) and correlation coefficients (R²) of each primer pair for the seven genes were obtained based on serial tenfold dilutions of pooled cDNA.

Detection of candidate reference genes stability

Transcript level stability of seven genes from B. striata in leaves with different periods under high temperature and in different tissues treated for 0 and 8 h was evaluated using three algorithms: geNorm (Vandesompele et al. 2002), NormFinder (Andersen et al. 2004) and BestKeeper (Pfaffl et al. 2004). The optimum reference gene was screened using geNorm software based on calculation of the average transcript level stability value (M value) of each candidate. Generally, this software suggests at least two optimum reference genes for transcript level normalization, making the results more accurate. M values ＜1.5 were considered to be acceptable. The lowest M value implied the most stable and vice versa. NormFinder software was used to assay transcript level stability based on intra-class variance and inter-class variance. The ranks and stability values were directly recorded to determine the single most stable gene. BestKeeper algorithm screened out the best gene according to standard deviations (SD) and coefficients of variation (CV) of Ct values. Finally, RefFinder (Xie et al. 2012) was used to integrate and analyze the comprehensive ranking.

Verification of selected reference genes

To validate the transcript level stability of identified genes, the relative expression level of BsrbcL gene, which encodes the large subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO), was measured using qRT-PCR analysis.

Results

Isolation of candidate genes

Seven genes were studied for screening of suitable reference genes for analysis of transcript levels of target genes in B. striata under high temperature stress. Partial mRNA fragments of the seven candidates were isolated from the leaf of B. striata using homologous cloning. Fragments ranged from 357 bp to 1,792 bp and had 87–99% homologous sequences compared to other plants.

Specificity and amplification efficiency of primer pairs

Quantitative RT-PCR primers for the seven genes were designed according to the sequences obtained using PCR amplification, and their specificity was assayed according to the results of gel electrophoresis and melting curve. As shown in Fig. 1A, the results of electrophoresis indicated that there was only one target band obtained by PCR for each gene, and the positions were corresponding to expected size. The melting curves for each primer set showed a single amplification peak indicating stability and specificity (Fig. 1B). E ranged from 90.9 to 110.2%, and R² varied from 0.981 to 0.999 (Table 1).

Expression analysis of candidate genes

Transcript level stability among different samples is an important criterion in selecting a suitable internal reference gene. The transcript level is presented in the form of a cycle threshold value (Ct), which indicates transcript abundance as measured using qRT-PCR analysis. Lower Ct values indicate higher transcript abundance, and higher values represent lower abundance. Under high temperature stress, the average Ct values of seven genes ranged from 12.84 to 29.27 among different treatment durations in leaves (Fig. 2A), while they ranged from 12.35 to 28.93 among different tissues (Fig. 2B).

As shown in Fig. 3, 18S gene had the lowest Ct value of 12.84 ± 0.36 (mean ± SD), thus showing the highest expression level among different treatment durations in leaves and 12.35 ± 0.50 among different tissues, followed by GAPDH with 21.07 ± 0.87 and 20.78 ± 0.62 among different treatment durations in leaves and different tissues, respectively. In contrast, the highest values were 29.27 ± 1.30 for TUA among different treatment durations in leaves and 28.93 ± 1.66 for NAC among different tissues, followed by 29.12 ± 1.37 for NAC and 27.66 ± 2.49 for TUA among different treatment time durations in leaves and different tissues, respectively. These values indicated that these genes had the lowest transcript abundance.

Evaluation of transcript level stability of candidates

geNorm analysis: The results of geNorm analysis are presented in Table 2. The M values of seven genes expressed in leaves treated for different periods at high temperature and in different tissues treated with high temperature for 0 and 8 h were all Table 1: Characteristics of qRT-PCR for seven genes

Gene name	GenBank ID	Primer sequence (5’-3’)	Product length	Tm (℃)	E (%)	R²
UBI	MT781955	F: CGCCGATTACAACATCCAGAA R: TTCTTGGGCTTGGTGTATGTC	102 bp	83	90.9	0.986
GAPDH	MT781952	F: CAGTCTTTGGCGTCAGGAA R: CAACAACAAACATTGGAGCATC	177 bp	85.5	92.6	0.998
18S	MT781956	F: TTTATGAAAGACGAACCACTGC R: TCGGCATCGTTTATGGTTG	121 bp	81.5	93.4	0.999
TUA	MT781953	F: TTTATGAAAGACGAACCACTGC R: TGAGGCGGTAAGGGATGAA	126 bp	83.5	100.3	0.991
TUB	MT781954	F: GGAGGGCAATGTGGCAA R: TAAGCACAGCCCTCGGAAC	172 bp	85.2	93.5	0.996
EF1α	MK448293	F: GCCGTCCTTATTATTGATTCCA R: GGATCTTATCAGGATTGTAACCA	233 bp	82.5	99.5	0.996
NAC	MT781957	F: TGGTATTTCTTCACCCCGC R: TTGCCTTCCAGTAACCCGA	85 bp	82	110.2	0.981

Table 2: Rankings of seven genes calculated using geNorm algorithm

Rank	Different periods		Different tissues
Rank	Gene	Stability	Gene	Stability
1	18S/UBI	0.69	18S/UBI	0.52
2	GAPDH	0.77	EF1α	0.62
3	EF1α	0.85	GAPDH	0.75
4	TUB	0.92	TUB	0.86
5	TUA	1.08	NAC	1.22
6	NAC	1.21	TUA	1.55

Table 3: Rankings of seven genes calculated by NormFinder algorithm

Rank	Different periods		Different tissues
Rank	Gene	Stability	Gene	Stability
1	TUB	0.263	UBI	0.163
2	GAPDH	0.436	18S	0.214
3	18S	0.459	GAPDH	0.314
4	UBI	0.478	TUB	0.392
5	EF1α	0.596	EF1α	0.448
6	TUA	0.889	NAC	1.431
7	NAC	0.921	TUA	1.582

determined to be lower than 1.50 with the exception of TUA in different tissues. Interestingly, the most stable genes were 18S and UBI, and the least stable was NAC in the two treatment groups. Under different periods of high temperature treatment, 18S and UBI demonstrated the lowest M value of 0.69, followed by GAPDH with a value of 0.77. In different tissues treated with high temperature for 0 and 8 h, 18S and UBI presented the lowest M value of 0.52, followed by EF1α with an M value of 0.62.

NormFinder analysis: As shown in Table 3, under different periods of high temperature treatment, TUB had the lowest M value of 0.263, indicating that it was the most stable, followed by GAPDH and 18S with M values of 0.436 and 0.459, respectively. NAC was ranked last with a value of 0.921, suggesting that it was the least stable transcript. In different tissues treated with high temperature for 0 and 8 h, the most stable gene was UBI with an M value of 0.163, followed by 18S and GAPDH with M values of 0.214 and 0.314, respectively. TUA proved to be the most unstable gene with the highest M value of 1.582.

BestKeeper analysis: The SD values for NAC among different periods of high temperature treatment and for NAC and TUA genes in different tissues treated with high temperature for 0 and 8 h were found to be greater than 1.0. According to BestKeeper criteria, transcript levels of these genes were unstable. As shown in Table 4, 18S and EF1α were identified as the most stable transcripts among different periods of high temperature treatment; while 18S and GAPDH were the most stable genes in different tissues treated with high temperature for 0 and 8 h. Overall, the most stable transcript was 18S.

RefFinder analysis: The results of geNorm, NormFinder, and BestKeeper were further integrated and analyzed using RefFinder program. The comprehensive ranking of the seven genes generated by RefFinder is shown in Table 5, and the rankings of each gene obtained by the four programs are then presented in Fig. 4. The transcript level of 18S was ranked as the most stable among the different periods of high temperature treatment, followed by TUB and UBI. Transcripts of 18S and UBI were suggested to be the most stable in different tissues treated with high temperature for 0 and 8 h. Transcripts of 18S and UBI were ranked as the two highest among all samples.

Table 4: Rankings of seven genes calculated by BestKeeper algorithm

Rank	Different periods			Different tissues
Rank	Gene	SD	CV	Gene	SD	CV
1	18S	0.27	2.1	18S	0.41	3.35
2	EF1α	0.60	2.39	GAPDH	0.48	2.31
3	UBI	0.64	2.5	EF1α	0.56	2.35
4	TUB	0.66	2.56	UBI	0.64	2.66
5	GAPDH	0.73	3.45	TUB	0.92	3.69
6	TUA	0.91	3.1	NAC	1.19	4.13
7	NAC	1.03	3.54	TUA	1.89	6.83

Table 5: Comprehensive analysis results of seven genes stability obtained by RefFinder program

Rank	Different periods		Different tissues		All samples
Rank	Gene	Stability	Gene	Stability	Gene	Stability
1	18S	1.86	18S/UBI	1.41	18S	1.57
2	TUB	2.12			UBI	2.21
3	UBI	2.45	GAPDH	2.91	EF1α/TUB	2.94
4	GAPDH	2.78	EF1α	3.66
5	EF1α	3.76	TUB	4.73	GAPDH	3.36
6	TUA	6.00	NAC	6.00	TUA	6.24
7	NAC	7.00	TUA	7.00	NAC	6.74

Verification of the selected reference genes

In order to verify the utility of the proposed internal control genes, the relative transcript levels of the BsrbcL gene in leaves of B. striata under high temperature treatment were measured using the most stable (18S, UBI, and 18S combined with UBI) and least stable (NAC and TUA individually) reference genes as calibrators. The results showed the transcript level of BsrbcL gradually decreased with increasing treatment time. Similar trends were observed when using 18S alone, UBI alone, or 18S combined with UBI to normalize the data (Fig. 5A). It is worth noting that the expression pattern was more uniform when using 18S and UBI simultaneously as calibrators than when using each reference gene individually. However, an incorrect expression profile for BsrbcL was exhibited when the least stable reference genes NAC or TUA were used (Fig. 5B).

Discussion

Bletilla striata tends to grow in a cool, damp, and ventilated environment, and its vegetative period is very short, spanning from April to September. In October, the leaves start to turn yellow and fall off, at which time the underground stem goes into dormancy. In the central area of China, summer is relatively hot and long. The growth and development of B. striata is usually inhibited under high temperature. Therefore, it is essential to study heat-resistant genes and their biological functions in order to breed new heat-resistant varieties of B. striata. qRT-PCR is the most commonly used molecular technique for quantifying gene expression level because it has many benefits. The accuracy of quantitative results relies heavily upon suitable internal control genes as normalization factors, which should exhibit stable transcript levels in all samples. Hence, the first step for expression analysis of target genes under a specific experimental condition is the selection of stable internal references. However, little information regarding suitable reference genes for the genus Bletilla has been published.

Fig. 2: Ct distributions of seven genes in leaves with different periods of high temperature treatment (A) and in different tissues treated with high temperature for 0 and 8 h (B)

Fig. 3: Ct values of seven candidate genes expressed in leaves with different heat treatment durations (A) and expressed in different tissues treated with high temperature for 0 and 8 h (B)

Fig. 1: Specificity of qRT-PCR amplification for the seven genes. (A) PCR products for each gene. (B) Melting curves for qRT-PCR amplification of seven candidate genes

In this study, the sequences of seven candidate internal control genes were obtained from B. striata, and transcript stabilities of the candidates were evaluated using geNorm, NormFinder, and BestKeeper algorithm. The rankings of seven genes were different for each algorithm. For example, in leaves under different periods of high temperature treatment, TUB was ranked the top which implied the most ideal by NormFinder, while geNorm and BestKeeper identified 18S and UBI as the optimum. Therefore, in the present study, we also used RefFinder to integrate these analyses into a comprehensive ranking of the candidates according to the results of the three algorithms.

In general, internal control genes are typically housekeeping genes, which commonly involves in the processes of basic metabolism and cell components. In the present study, six traditional housekeeping genes including GAPDH, TUA, TUB, 18S, EF1α, and UBI were selected as candidate reference genes. They have been widely reported and possess good performance within a given species. For example, EF1α was the most appropriate reference gene under cold stress in Eleusine coracana (Jatav et al. 2018), and under drought stress in Setaria italica (Kumar et al. 2013). GAPDH was the best choice in Chinese cabbage (Qi et al. 2010) under drought stress, in Eleusine coracana (Jatav et al. 2018) under cold, salinity or heat stress conditions, and under ABA stress in Polygonum cuspidatum (Wang et al. 2019). UBI showed peak stability under ABA stress in Hordeum brevisubulatum (Zhang et al. 2018), under cold stress in Morus alba (Shukla et al. 2019), under drought stress in wheat (Kiarash et al. 2018; Dudziak et al. 2020), and across different tissues in Miscanthus lutarioriparia (Cheng et al. 2019). The most proper reference gene for cold stress in Hordeum brevisubulatum (Zhang et al. 2018), salinity stress in Panicum virgatum (Huang et al. 2014) and drought stress in Miscanthus sinensis (Zhong et al. 2020) was 18S. TUA was reported as the first stable in different tissues of Hordeum brevisubulatum (Zhang et al. 2018) and PEG-treated stems and leaves of Betula luminifera (Wu et al. 2017). TUB had the highest ranking under drought and cold in Panicum virgatum (Huang et al. 2014), under ABA stress in Polygonum cuspidatum (Wang et al. 2019) and in vegetative tissues of Phalaenopsis (Yuan et al. 2014). Additionally, a novel candidate, NAC domain protein gene, has been used as a candidate reference gene (Lin et al. 2014; Huang et al. 2014). It was reported that NAC was the most stable in stressed roots from Codonopsis pilosula (Cao et al. 2017). Therefore, NAC was added as a candidate gene.

Fig. 4: Comparison of the ranking for each gene based on their M values generated by geNorm, NormFinder, BestKeeper, and RefFinder

Fig. 5: Relative expression levels of BsrbcL normalized using the selected most stable (A) and unstable genes (B) in leaves of Bletilla striata under high temperature stress

In leaves under different periods of high temperature treatment, 18S and UBI exhibited the most stable transcripts using geNorm, while TUB emerged as the optimal transcript from NormFinder analysis, and 18S was the best candidate as analyzed using BestKeeper and RefFinder. However, the results obtained by the four methods were consistent in that the least stable gene was invariably NAC. In different tissues treated with high temperature, UBI was the best reference gene as determined by the NormFinder algorithm and 18S was the best as determined by BestKeeper. However, 18S and UBI were the most stable genes according to the results of geNorm and RefFinder. The results obtained by the four methods were consistent in that the most unstable candidate was TUA. Among all samples, 18S was the optimum reference gene, followed by UBI. The most unsuitable genes were NAC, followed by TUA.

It was reported that EF1α in Caragana korshinskii (Yang et al. 2014) and Hordeum brevisubulatum (Zhang et al. 2018), GAPDH in Eleusine coracana (Jatav et al. 2018) and Caragana korshinskii (Yang et al. 2014), and 18S and TUB in Panicum virgatum (Huang et al. 2014) were ideal reference genes under heat stress. However, TUB has exhibited bad performance in Caragana korshinskii (Yang et al. 2014). In this study, 18S isolated from B. striata had the optimal ranking among the seven candidates among different periods of heat stress, followed by TUB. TUA was the least suitable reference gene for Polygonum cuspidatum under different conditions (Wang et al. 2019). In this study, TUA was also suggested to perform badly among different tissues. NAC was found to be an ideal internal control gene in other plant species but was a poor reference gene for B. striata.

Validation of the two most stable and unstable candidates were conducted using the target gene BsrbcL, which encodes a constituent of RuBisCO, an important enzyme for plant photosynthesis. These results demonstrate that 18S and UBI are appropriate for transcript normalization in B. striata under high temperature stress. Moreover, the most suitable reference genes were able to detect a slight decrease in BsrbcL. These results demonstrate that reliable reference genes for qRT-PCR analysis were vital for this species and that using inappropriate genes as calibrators may lead to incorrect expression analysis of target genes.

Conclusion

18S and TUB were the best reference genes for relative expression analysis of target genes in leaves from Bletilla striata among different periods under heat stress, 18S and UBI were the best reference genes among different tissues. Altogether, 18S and UBI were identified to be the best reference genes for all samples.

Acknowledgements

This work was supported by Aid program for Science and Technology Innovative Research Team of Zhengzhou Normal University, and Science and Technology Project of Henan Province (No. 182102110369).

Author Contributions

Fang Liang carried out the qRT-PCR and prepared the writing-original draft. Suhua Jiang and Ping’an Hao carried out cloning of the seven genes. Yan Zhang and Shenping Xu analyzed the data. Suyan Niu and Shiming Han modified the draft and editing. XiuyunYuan and Bo Cui presided over the research.

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