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Identification and validation of stable reference genes for RT-qPCR analyses of Kobresia littledalei seedlings

BMC Plant Biology volume 24, Article number: 389 (2024) Cite this article

Abstract

Background

Kobreisa littledalei, belonging to the Cyperaceae family is the first Kobresia species with a reference genome and the most dominant species in Qinghai-Tibet Plateau alpine meadows. It has several resistance genes which could be used to breed improved crop varieties. Reverse Transcription Quantitative Real-Time Polymerase Chain Reaction (RT-qPCR) is a popular and accurate gene expression analysis method. Its reliability depends on the expression levels of reference genes, which vary by species, tissues and environments. However, K.littledalei lacks a stable and normalized reference gene for RT-qPCR analysis.

Results

The stability of 13 potential reference genes was tested and the stable reference genes were selected for RT-qPCR normalization for the expression analysis in the different tissues of K. littledalei under two abiotic stresses (salt and drought) and two hormonal treatments (abscisic acid (ABA) and gibberellin (GA)). Five algorithms were used to assess the stability of putative reference genes. The results showed a variation amongst the methods, and the same reference genes showed tissue expression differences under the same conditions. The stability of combining two reference genes was better than a single one. The expression levels of ACTIN were stable in leaves and stems under normal conditions, in leaves under drought stress and in roots under ABA treatment. The expression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) expression was stable in the roots under the control conditions and salt stress and in stems exposed to drought stress. Expression levels of superoxide dismutase (SOD) were stable in stems of ABA-treated plants and in the roots under drought stress. Moreover, RPL6 expression was stable in the leaves and stems under salt stress and in the stems of the GA-treated plants. EF1-alpha expression was stable in leaves under ABA and GA treatments. The expression levels of 28 S were stable in the roots under GA treatment. In general, ACTIN and GAPDH could be employed as housekeeping genes for K. littledalei under different treatments.

Conclusion

This study identified the best RT-qPCR reference genes for different K. littledalei tissues under five experimental conditions. ACTIN and GAPDH genes can be employed as the ideal housekeeping genes for expression analysis under different conditions. This is the first study to investigate the stable reference genes for normalized gene expression analysis of K. littledalei under different conditions. The results could aid molecular biology and gene function research on Kobresia and other related species.

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Introduction

More than 70 species of Kobresia, a perennial herb belonging to the Cyperaceae family, are found mostly in the alpine ranges of the northern hemisphere and are mainly distributed in the Qinghai-Tibet Plateau in China [1]. They represent the primary year-round food supply for local grazing animals, particularly yaks, due to their nutritional qualities and large biomass [2, 3]. The Kobresia plants are also vital for preserving the ecological equilibrium of grasslands. Kobresia littledalei is the dominant species in low-lying locations around lakes, river borders and saline marsh in alpine meadows of the Qinghai-Tibet Plateau [1]. It has an underground short rhizome and the mature height is 20 to 30 cm. K. littledalei has evolved several ideal resistance genes after a long period of natural selection in the harsh environmental conditions of the Qinghai-Tibet Plateau, especially the genes conferring resistance to cold, radiation, drought, and strong wind stress. These genes could be mined and utilized for breeding improved crop varieties [4]. Changes in the gene expression levels are the direct biomarkers that may be used to evaluate an organism’s reaction to an altered environment [5]. Few studies have explored the molecular resistance mechanisms of K. littledalei. The first reference genome of the genus Kobresia was reported in 2020 [1], and it showed that K. littledalei is a diploid (2n = 2x = 58) with a 373.85-Mb assembly size. Qu et al. [6] explored the transcriptome of K. littledalei in response to cold stress. These studies were the beginning of understanding the resistance mechanisms of K. littledalei response to such harsh environments.

The introduction of quantitative reverse transcription-polymerase chain reaction (RT-qPCR) has drastically revolutionized gene expression analysis [7] due to its several benefits, including a broad dynamic range, high sensitivity, specificity, throughput, and precision [8]. However, RNA quality, integrity, reverse transcription efficiency, and amplification efficiency can influence the precision of RT-qPCR findings [9]. Hence, reference genes are frequently employed to decrease or rectify faults during target gene quantification to ensure accurate results without analytical errors [10].

Genes involved in the maintenance of basic cellular activities and those encoding proteins have frequently been used as reference genes because their products are required for cellular biological activity and may potentially be produced under any conditions [11]. These genes include the 18 S ribosomal RNA (18 S) gene, one of the most conserved genes in all cells [12] and the glycero-aldehyde-3-phosphate dehydrogenase (GAPDH) gene, a key enzyme in the carbon fixation pathways of glycolysis, gluconeogenesis, and photosynthesis [13, 14]. An ideal reference gene should have a reasonably stable and consistent expression level across cultivars, tissues, and environmental circumstances [15]. Yet, the expression of these housekeeping genes varies significantly in different experimental conditions and plant tissues [16, 17]. For instance, the conventional reference gene ACTIN showed the most stable expression under drought stress in garlic (Allium sativum), but it was not reliable under cold stress [18]. Additionally, ACTIN is not recommended for RT-qPCR analysis of Miscanthus sacchariflorus under drought, salt, and cadmium stress conditions [11]. Copper/zinc superoxide dismutase (Cu/Zn-SOD) was reported to be the best reference gene during seed soaking and stratification treatment of Magnolia sieboldii; however, it is not suitable for various organs and seeds at different developmental stages [19]. Similarly, the elongation factor 1-alpha (EF1-alpha) was the most stably expressed reference gene in oat (Avena sativa) roots under UV-B exposure, whereas PSK SIMULATOR 1-like (PSKS1) was the most stable expressed reference gene under high light stress [13]. Hence, it is vital to choose the most suitable reference genes for the various tissues or conditions to eliminate errors and ensure the accuracy and reliability of the data.

Therefore, screening for stable reference genes of K. littledalei important for revealing its molecular mechanisms of stress tolerance and gene expression processes via qRT-PCR [20]. This study investigated the expression stability of 13 potential reference genes in distinct physiological tissues (leaf, stem, and root) of K. littledalei plants subjected to two abiotic stimuli (salt and drought) and two exogenous hormonal treatments (abscisic acid and gibberellin). Subsequently, five normalizing algorithms (Delta-Ct, geNorm, NormFinder, BestKeeper, and RefFinder) were utilized to evaluate the expression stability of the genes. Selecting reliable reference genes is recommended for standardizing RT-qPCR data in various contexts. To verify the applicability of the selected reference genes, we selected BSK5 (Brassinosteroid-Signaling Kinase 5) and AP2/ERF (APETALA2/Ethylene-Responsive Factor), involved in various plant responses under biotic or abiotic stresses [6, 21, 22], for validation. This is the first study to conduct a systematic analysis for the selection of reference genes in K. littledalei tissues subjected to various treatments. The results could facilitate future studies on the gene expression and molecular mechanisms of K. littledalei.

Materials and methods

Plant material, growth conditions and treatments

Kobresia littledalei, with a known genome, was used as the experimental plant. The Tibet Academy of Agricultural and Animal Husbandry Sciences provided mature seeds collected in 2014 from Naqu, Tibet, China, and stored at 4 °C. The seeds were surface sterilized using 75% ethanol (v/v) for 30 s and 1% sodium hypochlorite solution for 15 min. The sterilized seeds were germinated in a Petri dish (90 mm) for 30 days, sown in a pot filled with vermiculite, and moistened daily with Hoagland’s nutrient solution in an artificial climate incubator with a 25 °C / 18 °C average temperature, 70% relative humidity, and a 16 h / 8 h (light/dark) photoperiod of 1125 µM photons m−2 s−1 [23]. Kobresia represent typical drought-tolerant, cold-tolerant, and barren plants of the alpine meadows [24]. Thus, this study subjected one-year-old plants to different abiotic and exogenous hormone sprays as follows: (1) drought treatment; 400 mM mannitol; (2) salt treatment; 200 mM NaCl; (3) exogenous hormone treatment; 100 µM ABA and (4) 100 µM GA, respectively; and (5) control; normal conditions. Abiotic stress was induced by adding drugs to the hydroponic treatment; exogenous hormonal treatment involved spraying plants once. The hormones were dissolved in distilled water and sprayed on the plants until the droplets did not drip off. Finally, samples from different organs (leaves, stems, and roots) were collected from plants at 0, 2, 6, 9, 12, and 24 h after treatment, frozen in liquid nitrogen, and stored at -80 °C. Each experiment had three biological replicates, and each replicate contained at least two seedlings.

RNA extraction and cDNA synthesis

Total RNA from Kobresia was extracted using the Eastep Super Total RNA Extraction Kit (Promega Corporation, Wisconsin, USA) following the manufacturer’s instructions. The purity and concentration of RNA were evaluated using a nanodrop2000 spectrophotometer (Thermo Fisher Scientific, MA, USA). The RNA samples had optical density (OD) ratios of 1.8-2 and > 2 for OD260 / OD280 and OD260 / OD230, respectively. Then, single-stranded complementary DNA (cDNA) was synthesized from 0.5 µg RNA of each sample using the HiScript III RT SuperMix qPCR cDNA synthesis kit (Vazyme Bio, Shanghai, China) following the manufacturer’s instructions. All the cDNA samples were diluted to 1× and stored at -20 °C for later use.

Selection of candidate reference genes

The top ten primers from ICG (http://icg.big.ac.cn/index.php/Main_Page) [25] and other common housekeeping genes were used to select 13 candidate reference genes: Actin (ACTIN), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), 18 S ribosomal RNA (18 S), 28 S ribosomal RNA (28 S), TATA box binding protein (TBP), eukaryotic translational elongation factor 1 alpha (EF1-alpha), ubiquitin (UBQ), alpha-tubulin (TUA), copper/zinc superoxide dismutase (SOD), ribosomal protein, large, 6 (RPL6), cyclophilin (CYP), HIS triad family protein 3 (HIS), and Leucyl-tRNA (LEU). All the 13 candidate reference genes are commonly used as housekeeping genes in model plant species. These genes were cloned according to their coding sequences (CDS) from a recently published representative first draft whole genome of K. littledalei (NCBI accession number: ASM1111435v1) [1]. The primers were designed on the web using the Primer 3.0 plus (http://www.primer3plus.com, accessed on August 2021) software, and then the theoretical annealing temperature of each primer was predicted accordingly. The primers were synthesized by Sangon Biotech Company (Shanghai, China), and the PCR products were resolved on 1% agarose gel. The primer data of the candidate reference genes are listed in Table 1.

Table 1 Candidate reference genes, amplicon characteristics, and primer sequences
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The amplification efficiency (E) and correlation coefficients (R2) were calculated using a standard curve based on tenfold serial dilutions of a mixture of the synthesized cDNA over six dilution points, starting from 1000 ng µL−1. The threshold cycle (Ct) was measured automatically, and the corresponding RT-qPCR efficiency (E) for each gene was determined from the given slope (Table 1).

RT-qPCR conditions

After the quality tests of the primers, RT-qPCR was performed in 96-well plates in the Light Cycler480 real-time PCR System (Roche Molecular Systems, Mannheim, Germany). The reaction mixture contained 2.6 µL ultrapure water, 5 µL ChamQ SYBR qPCR Master Mix (Vayzme Bio, Shanghai, China), 2 µL cDNA, 0.2 µL forward primer (10µM), and 0.2 µL reverse primer (10 µM). The program involved denaturation for 1 min at 94 °C, 40 cycles of 10 s at 94 °C, and 30 s at 62 °C. Melt curves were obtained by heating the sample from 60 to 95 °C at a rate of 1.0 °C·s−1. Each treatment had three biological and two technical replicates.

Analysis of gene expression Stability

Raw qPCR data were collected using LightCycler® 96 software v. 1.1 (Roche Molecular Systems, Mannheim, Germany). The reference genes were ranked across all tissues and tissue combinations using the delta-Ct method [26], geNorm [7], NormFinder [27], BestKeeper [28], and RefFinder [29]. The geNorm program calculates the average expression stability measurement (M) value according to the pairwise variation between two sequences, eliminating the genes that show the worst expression stability in a stepwise manner. NormFinder calculates the stability value based on variance analysis, overcoming the limitations of geNorm, which cannot discriminate between coregulated genes. BestKeeper evaluates expression stability by calculating the standard deviation (SD) and the percentage covariance (CV). BestKeeper and geNorm are based on pairwise comparison; hence, they have the same limitations regarding coregulated genes [30]. However, the Delta-Ct method determined the ranks after pairwise comparisons of gene sets. The reference gene with the lowest SD had the most stable expression. The geNorm, BestKeeper, Delta-Ct, and NormFinder analyses were performed using the ctrlGene [31] and NormqPCR [32] packages in R 4.2.1. Finally, RefFinder (http://www.leonxie.com/refer encegene.php) was used to calculate the comprehensive ranks based on the geometric mean values from the results of the other four methods.

Validation of reference genes

Brassinosteroid-signaling kinase 5 (BSK5) and APETALA2/Ethylene-Responsive Factor (AP2/ERF) were selected as target genes to confirm the reliability of the candidate reference genes. The top two most stable genes normalized BSK5 and AP2/ERF expression stability, and RefFinder identified the most unstable gene across each treatment, tissue, and sample. The best primer pairing, ranked by geNorm, was also used to normalize the target genes. The samples were collected at the same time as described above under drought and salt stress, and the RT-qPCR amplification conditions were the same as described above. The 2−ΔΔCt method [33] was used to calculate the expression of target genes in each condition. Table S1 showed the primer sequences for BSK5 and AP2/ERF.

Results

Primer specificity and amplification efficiency of candidate reference genes

Table 1 summarizes the thirteen putative housekeeping genes, including their complete names and GeneBank accession numbers. The 1% agarose gel electrophoresis findings demonstrated that each primer had a single, bright band (Fig. 1A). Furthermore, the melting curves for all candidate genes exhibited single peaks (Fig. 1B-N) and dissolving curves demonstrated amplification efficiencies ranging from 95.106% to 130.970%, with 0.9800 to 0.9988 correlation coefficient (R2) (Table 1). The preceding results suggested that the primers had reasonable specificity. Notably, the melting temperature of LEU primers was < 80℃; hence, the LEU gene was rejected from further investigation.

Fig. 1
figure 1

Specificity of primers and amplificon lengths, and melt curves of qPCR amplification of 13 candidate reference genes. A Specific product length of each reference gene was indicated after 1% agarose gel electrophoresis. Marker represents Marker DL2000. The image is an adjacent lane of the same gel (1%), and the image size is cropped; B-N were the melt curves of reference genes

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Relative expression of candidate genes in all samples

Figure 2 shows the transcriptional abundance of 12 housekeeping genes in 30 samples under five distinct environmental circumstances (mannitol, NaCl, ABA, GA, and normal conditions) and six different time treatments (0, 2, 6, 9, 12, 24 h). The results revealed that the mean Ct values for all reference genes ranged from 10.38 to 30.72, indicating a disparity in their expression levels. GAPDH had the lowest mean Ct value (10.38), correlating to the greatest expression level. However, CYP had the highest mean Ct value and the lowest expression level. The standard deviation (SD) of the Ct indicated the variation in gene expression levels across the samples (Fig. 2). GAPDH had the lowest SD (1.36), indicating that it is more stable under diverse settings. Nonetheless, the expression of HIS varied greatly among the samples, indicated by its SD value of 3.49.

Fig. 2
figure 2

Violin plot analysis of Ct value of 12 candidate reference genes in all samples. The boxes indicate the 25th and 75th percentiles. The line across the box represents the median. The whisker shows the maximum and minimum values, respectively. The circle out of the violin represents the outside values

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Estimation of stability by Delta-Ct

The relatively low Delta-Ct values among the putative housekeeping genes suggested a relatively strong gene expression. The Delta-Ct technique results showed that ACTIN is the most stable reference gene across the treatments and tissues, including leaf tissue of the control (1.66) and drought conditions (1.68), stem tissue of the control (1.32), and root tissue under ABA treatment (1.93) (Fig. 3). RPL6 was the most stable reference gene in stem tissue under 400 mM mannitol stress (1.20) and exhibited excellent stability in leaf tissue under NaCl conditions, and stem tissue under GA treatment (1.21 and 1.37). Nevertheless, 28 S was the most stable reference gene in the GA-treated leaf and root tissues and NaCl-treated stem tissue. SOD was a good reference gene under control and mannitol conditions in root tissues and was stable in ABA-treated stem tissues. HIS was the most stable reference gene in ABA-treated leaves (1.44), while GAPDH was the most stable reference gene in salt-stressed roots (1.70). ACTIN was the most stable reference gene in each tissue under control conditions. Under abiotic stress (mannitol and NaCl), RPL6 was the most stable reference gene.

Fig. 3
figure 3

Expression stability rankings of 12 candidate reference genes using the Delta-Ct

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Further, EF1-alpha (ABA treatment) and GAPDH (GA treatment) were the most stable genes under hormone treatment. ACTIN was the most stable reference gene for all leaf and root tissues (1.91 and 1.97, respectively) and all samples (2.07), whereas SOD was the most stable reference gene for all stem tissues (1.73). (Fig. 3F). The greatest delta-Ct value was observed for UBQ (the value of all samples was 3.87), suggesting that it was the most unstable reference gene under all circumstances.

Estimation of stability by geNorm analysis

The geNorm algorithm was applied to all three tissues and their combinations to determine the stability of the 12 housekeeping genes under various conditions (mannitol, NaCl, ABA, GA, and normal conditions). In this technique, M represents the gene expression stability ranking; an M number < 1.5 is considered within the gene stability range. The lower the M value, the greater the gene stability [7]. Candidate reference genes with the most stable expression differed between tissues under stress or hormone treatments (Fig. 4). ACTIN and RPL6 were the top two stable reference genes of K. littledalei in all tissues under normal conditions (M number = 1.168). In leaf tissue, GAPDH and RPL6 were stable (0.664); ACTIN and TUA in stem tissue (0.463); and ACTIN and GAPDH in root tissue (0.533) (Fig. 4A). SOD and RPL6 were stable under drought stress (0.994), ACTIN and RPL6 in leaf (0.358), GAPDH and RPL6 in stem (0.630), and SOD and RPL6 in root (0.713) (Fig. 4B). In the salt stressed group, GAPDH and RPL6 were the most stable housekeeping genes (1.278) in the leaf, RPL6 and HIS (0.661) in the stem, SOD and RPL6 (0.813) in the root tissue, and RPL6 and TUA (0.694) (Fig. 4C). The top two genes under ABA and GA treatment were ACTIN and EF1-alpha (1.346), and ACTIN and GAPDH (1.127), respectively. GAPDH and EF1-alpha were the most stable genes in the leaf tissue of the ABA (0.767) and GA (0.578) treatment groups. RPL6 and TUA were the most stable reference genes in the tissues of the ABA-treated stem (0.610) and GA-treated root (0.659). The best reference genes for the ABA-treated root and GA-treated stem tissues were ACTIN and EF1-alpha (0.988), and ACTIN and SOD (0.409), respectively (Fig. 4D, E). ACTIN and GAPDH had the most consistent expressions across multiple tissues and treatments (1.298) (Fig. 4F). Similarly, these two genes showed the lowest M value in the leaf (1.007) and root (1.040) under all tissue circumstances. Nevertheless, SOD and RPL6 exhibited steady expression in all stem samples (1.024). UBQ, which was consistently in the final place neither in single tissues nor tissue combinations, was unsatisfactory for normalizing RT-qPCR results for K. littledalei.

Fig. 4
figure 4

Expression stability rankings of 12 candidate reference genes using the geNorm

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As required by the Minimum Information for Publication of Quantitative Real-time PCR Studies (MIQE) requirements [34], the pairwise variation V (Vn/Vn + 1) of the normalization factor was also determined (Fig. 5). All group pairwise variations were below the general assumption cutoff of 0.15, indicating that the two reference genes were adequate for normalizing RT-qPCR data. Hence, the M and Vn + 1 values provided by geNorm identified ACTIN and GAPDH as the most stable genes among all samples and the leaf and root tissues of all treatments. In contrast, SOD and RPL6 were the most stable genes in stem tissues under all circumstances. ACTIN and RPL6, SOD and RPL6, GAPDH and RPL6, ACTIN and EF1-alpha, and ACTIN and GAPDH were the most stable combinations during normal conditions, mannitol stress, NaCl stress, and ABA and GA treatment, respectively.

Fig. 5
figure 5

Pairwise variation (Vn/Vn + 1) analysis of the optimal number among ten candidate reference genes in different experimental sets

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Estimation of stability by NormFinder

The lower the NormFinder stability values, the more stable the reference genes. Thus, ACTIN was the most stable reference gene in leaf and stem tissues under normal conditions, whereas 28 S was the most stable in root tissue (Fig. 6A). Under mannitol treatment, RPL6 was the ideal reference gene in both leaf and stem tissues, and SOD was ideal in root tissue (Fig. 6B). Under salt stress, RPL6 was the most stable gene in the leaf, 28 S in the stem, and GAPDH in the root (Fig. 6C). HIS was the most stable gene in leaf tissue, whereas SOD and ACTIN were the most stable genes in stem and root tissue, respectively (Fig. 6D). 28 S was the most stable housekeeping gene in K. littledalei leaf and root tissues under GA conditions, while RPL6 was most stable in the stem (Fig. 6E). Moreover, the tissue stability value of each treatment revealed ACTIN and RPL6 as the best reference genes under control conditions, and that they perform well during drought and salt stress. EF1-alpha and ACTIN were the best candidate reference genes under the ABA condition, whereas 28 S and GAPDH were most stable under GA treatment. ACTIN exhibited the lowest stability value (0.827) across all samples, stem, and root tissue groups (0.772 and 0.837, respectively). SOD, RPL6, and ACTIN were the top three stable reference genes in all stem tissue (Fig. 6F). Meanwhile, UBQ had the lowest stability in over half of the examined population (Fig. 6).

Fig. 6
figure 6

Expression stability rankings of 12 candidate reference genes using the NormFinder.

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Estimation of stability by BestKeeper

In the BestKeeper analysis, the candidate reference genes were ordered based on the standard deviations of the original Ct values of each candidate gene under various settings. Genes with < 1.5 standard deviation values were considered the most stable—furthermore, the smaller the SD value, the greater the gene stability. The results of the stability study of samples from various treatments indicated GAPDH (1.10) as the best suitable reference gene across nearly all tissues and treatments (Fig. 7). ACTIN exhibited excellent stability in the control (1.15) and mannitol-treated (0.57) leaf tissues, and ABA- (0.82) and GA-treated (0.80) root samples. Under normal conditions, EF1-alpha was very stable in the stem (0.60) but exhibited poor stability in the stem (1.51) and root (1.50) under GA treatment. 28 S was the most stable reference gene in NaCl-treated root samples (0.60) and the most variable. GAPDH was the most stable reference gene across all samples (1.10), all leaf (0.95), and stem (0.68) tissues, and ACTIN in the root (0.92). The SD values of the HIS, UBQ, and TUA were the highest of all the reference genes, demonstrating the instability of these three genes (the average values were 2.27, 2.09, and 2.02, respectively).

Fig. 7
figure 7

Expression stability rankings of 12 candidate reference genes using the BestKeeper.

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Comprehensive ranking analysis

RefFinder is an exhaustive algorithm incorporating Delta-Ct, geNorm, NormFinder, and BestKeeper analysis tools. Table 2 displays the RefFinder results, which indicated that ACTIN was the optimal reference gene in the leaf (1.41) and stem (1.41) tissues under normal circumstances, leaf tissues (1.19) under mannitol treatment, and root tissues (1.00) responding to ABA treatment. In mannitol-treated stem and root tissues, GAPDH (1.41) and SOD (1.32) were the optimum reference genes. RPL6 was the suitable reference gene in leaf and stem samples treated with NaCl (1.32 and 1.86, respectively). EF1-alpha was the most stable reference gene in leaf tissues treated with spraying hormone (ABA was 1.73 and GA was 2.00, respectively). Further, SOD (2.06) was the optimal reference gene in the ABA-treated stem, followed by EF1-alpha (2.38). In GA-treated stem tissue, RPL6 was the most stable gene (1.57), and 28 S was the most stable gene in root tissue (1.68). RPL6 was the optimal reference gene for drought- (1.41) and salt- (1.19) stressed samples, whereas ACTIN was appropriate for normal circumstances (1.00). Besides, the best reference genes under ABA and GA treatments were EF1-alpha (1.19) and GAPDH (1.19), respectively. ACTIN and GAPDH were the two most stable reference genes in all leaf (1.19 and 1.41, respectively) and root samples (1.00 and 2.06, respectively). In contrast, SOD (1.41) and RPL6 (1.86) were the most stable reference genes in all stem samples. UBQ was determined to be the least stable reference gene in most samples. Based on the total number of samples across all circumstances, RefFinder rated the stability of the 12 candidate reference genes as follows: ACTIN > GAPDH > RPL6 > EF1-alpha > 28 S > SOD > CYP > TUA > 18 S > TBP > HIS > UBQ.

Table 2 Comprehensive stability rankings of 12 candidate reference genes
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Validation of the candidate reference genes

The expression of BSK and AP2/ERF was normalized by single or multiple reference genes to test the reliability of selected reference genes during the response of K. littledalei to drought and salt stress during 0 to 24 h (Figs. 8 and 9). In this article, the top two, stable and the least stable reference genes from mannitol- and NaCl-stressed individual tissues (leaf, stem, root) and all conditions are listed in Table 2. The best combination of stable reference genes was used for normalization. The combinations included ACTIN with RPL6 for mannitol-treated leaf, GAPDH with RPL6 for stem, SOD with RPL6 for root; RPL6 with HIS, SOD with RPL6, RPL6 with TUA for NaCl-treated leaf, stem and root; ACTIN with GAPDH for all leaf, root tissues and all combined samples; and SOD with RPL6 for all stem samples. The expression patterns of the two target genes differed in the three plant tissues exposed to drought or salt stress. The BSK and AP2/ERF expression levels were comparable when the top two reference genes were used to standardize the data. However, the expression of the target gene that was normalized using a combination of the top-ranked stable reference genes remained lower than those of the top two stable reference genes alone. The lowest-ranked reference genes (CYP for mannitol-treated leaf, UBQ for the stem, TBP for root; TUA, 18 S, and TBP for NaCl-treated leaf, stem and root, respectively; UBQ for all leaf, stem, root tissues and all combined samples) were not optimal for normalizing data, resulting in varied BSK or AP2/ERF expression levels compared to the top-ranked genes. The divergence was more pronounced in NaCl-treated leaves when the lowest-ranked TUA was applied. For instance, the relative expression of BSK in leaves under NaCl stress at 24 h was 0.99 and 1.99 when normalized to RPL6 and HIS, and 104.97 when normalized to TUA, respectively. AP2/ERF normalization also revealed the variance of the relative expression level. Moreover, the reference genes from individual tissues of each treatment could more accurately reflect the expression pattern of the target gene than the general primers selected from all treatments. Likewise, the relative gene expression was more accurate when two top-ranked reference genes were used to normalize the relative expression of BSK or AP2/ERF than when using a single gene. This pattern held true for all examined treatments and tissues. When the lowest-ranked gene was utilized alone for normalization, the expression of the target gene seemed unnaturally raised.

Fig. 8
figure 8

Relative expression level of BSK in Kobresia littledalei under mannitol and NaCl stress using selected reference genes. The results were normalized using the selected stable reference genes (alone or in combination) and the unstable genes in sample sets (alone or in combination) across treatment with A-C mannitol treatment in leaves, stems, and roots; D-F NaCl treatment in leaves, stems, and roots. The bars indicate the standard Deviation (± SD) evaluated from three biological replicates

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Fig. 9
figure 9

Relative expression level of AP2/ERF in Kobresia littledalei under mannitol and NaCl stress using selected reference genes. The results were normalized using the selected stable reference genes (alone or in combination) and the unstable genes in sample sets (alone or in combination) across treatment with A-C mannitol treatment in leaves, stems, and roots; D-F NaCl treatment in leaves, stems, and roots. The bars indicate the standard Deviation (± SD) evaluated from three biological replicates

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Discussion

The Qinghai-Tibet Plateau is a significant research target for studying the response of the alpine grassland ecosystems to climate change and human activities [35,36,37] and the degradation and restoration of alpine steppes and meadows [38,39,40]. Furthermore, the Kobresia plants on the Tibetan Plateau are a major source of stress-resistance genes [6]. Thus, the study of gene expression patterns is the basis for understanding the early responses of plants to stress [41]. Quantitative PCR is one of the most precise techniques for analyzing the expression of various genes. The technique is highly dependable, sensitive, and dependent on the selection of reference genes for normalization [34]. Therefore, the technique requires an ideal internal control that is consistently expressed under all experimental conditions, tissues, and developmental stages of the organism to reduce or prevent experimental errors and data misinterpretation. However, a single stable reference gene is almost non-existent [42, 43]. Previous studies have shown that different genes are persistently expressed in different species under different conditions [44,45,46,47]. Therefore, each species requires the most appropriate reference gene for analyzing unique sample types and experimental conditions. To date, there is no report on the most stable reference gene for normalizing gene expression in Kobresia. Thus, this study analyzed 12 candidate reference genes for the expression of K. littledalei under different conditions. The results revealed different reference genes across different tissues and conditions, consistent with Duan et al. [48] and Wang et al. [18]. For example, ACTIN and GAPDH were ideal for comparing different treatments in leaves, ACTIN and RPL6 were most suitable for leaves under mannitol stress, SOD and RPL6 were more suitable for root tissues under mannitol treatment, and EF1-alpha was suitably used to compare leaves under ABA and GA treatments, respectively.

This study used five analytical methodologies, Delta-Ct, geNorm, NormFinder, BestKeeper, and RefFinder, to estimate the expression stability of internal reference genes in different tissues during drought, salt, ABA, and GA treatments. The purpose was to circumvent the limitations of using a single algorithm analysis. The first four methods were used to evaluate the expression stability of candidate genes, and RefFinder calculated the final ranking. This reference gene ranking varied across the five algorithms for the same set of experimental data. For example, in mannitol-stressed leaves, Delta-Ct, BestKeeper, geNorm, and RefFinder proposed ACTIN, but NormFinder suggested RPL6 as the suitable reference gene. The results are similar to reports in Hylocereus undatus [49], Toona ciliate [42], Salsola ferganica [50], Prunus persica [51], Miscanthus sacchariflorus [11], Schima superba [52], and Fragaria ananassa [53]. The differences might be due to the discrepancies in the algorithms.

In brief, the variation measurements were used to determine the stability of gene transcription with the geNorm and NormFinder methods. The pairwise correlation using geNorm is successful for small sample sizes but is biased towards picking genes that are mutually associated with each other. The NormFinder model-based method requires higher sample sizes than geNorm (> 8) and discriminates between within-group and inter-group variances. Therefore, NormFinder is suitable for identifying candidate genes from different sample groups [54]. Additionally, geNorm can determine the optimal number of required reference genes. If the Vn/n + 1 is below the threshold (0.15), the advantage of utilizing another (n + 1) reference gene becomes restricted. In this study, pairwise variation analysis revealed that the V2/3 value of the two most stable reference genes was < 0.15 across all tissues and conditions, indicating that these reference genes were sufficient for normalizing the gene expression in K. littledalei.

Another method, the BestKeeper analysis, uses the correlation between the Cq and an index derived from the geometric mean of the candidate. Thus, a threshold value of SD (1.0) was considered for evaluating the stability of the reference in this method. The reference gene was considered stable if the value was < 1.0. In this study, there was at least one constant candidate gene across all samples and treatments, except the combination of all tissues under NaCl, which had one reference gene (GAPDH). In contrast, the combination of all tissues under GA treatment (GAPDH and 28 S) and all samples had GAPDH and ACTIN, respectively. Nevertheless, the ranking order was still acceptable because the expression stability is a relative concept. This cutoff is a rule of thumb; the threshold is not fixed, symbolizing the stringency for picking the reference gene [14, 55].

In this study, RefFinder was used as the final ranking algorithm. This tool selected ACTIN as the most stable reference gene in all treatments and tissues, followed by RPL6. UBQ was the most unstable reference gene. RefFinder uses the rankings of the candidate genes across these different algorithms to attribute an ordinal “weight” for each candidate gene. The final rankings are then computed as the geometric mean of the weighted rankings [56, 57]. Thus, numerous studies have commonly used this algorithm to validate reference genes [14, 41, 58]. RankAggreg, the other important tool for calculating the final ranking of selected reference genes from other algorithms, uses a cross-entropy Monte Carlo or genetic algorithm to produce aggregated ordered lists based on rankings [42, 59].

Despite their slightly different rankings, all five algorithms determined ACTIN as the best reference gene for most tissue samples and treatments. ACTIN was among the first reference genes used in gene expression quantification and remains one of the most used internal standards today [60]. The ACTIN mRNA encodes a ubiquitous cytoskeleton protein that participates in diverse physiological eukaryotic activities, such as plant and organ development, vesicle and organelle movement, and cell signaling transduction [61]. The second most stable reference gene was GAPDH, which encodes the glyceraldehyde-3-phosphate dehydrogenase, an enzyme involved in glycolytic processes. Due to its abundance and extensive expression, GAPDH is frequently utilized as an internal control in RT-qPCR [62].

In Poa pratensis, RPL was the most unstable reference gene in drought-treated leaves [63]. However, RPL6 had a relatively high ranking in the mannitol and NaCl stresses in this study, consistent with other studies [64, 65]. RPL6 belongs to the family of RPL that codes for the ribosomal protein large subunit protein, which plays an important role in cellular processes. Meanwhile, the aerenchyma structures of the K. littledalei in the alpine swamp meadow have developed to ameliorate the low oxygen stress from soil waterlogging or flooding [66]. This adaptation explains why EF1-alpha demonstrated high stability in leaf tissue following the ABA and GA treatments, similar to the results of previous research [67, 68]. The polyribosomal protein coded by the EF1-alpha gene participates in ribosomal structure and biogenesis [69]. Saraiva et al. [70] reported that EF1-alpha undergoes expression diversification in response to hormone exposure and that EF1α 3 is predominantly found in aerial tissues.

Furthermore, UBQ was the most unstably expressed reference gene in most samples, implying that it is unsuitable for K. littledalei, consistent with the results of Zhao et al. [71]. However, UBQ was the ideal housekeeping gene for studies of Oryza sativa [72], Miscanthus lutarioriparia [73], Magnolia × soulangeana [74], and Boehmeria nivea [75].

We performed a relative gene expression study of BSK and AP2/ERF, implicated in diversion plant processes, to check the validity of selected reference genes [6, 76]. The expression of BSK and AP2/ERF was analyzed in various K. littledalei tissues (leaf, stem, and root) subjected to abiotic (mannitol and NaCl) stress for various durations (0, 2, 6, 9, 12, 24 h). We normalized the data by comparing the outcomes of the top-two-ranked genes alone and combined and the most unstable reference gene. Further, normalization using the top-two-ranked genes produced a similar expression trend to each individual stably expressed target gene, consistent with the combination of stably expressed reference genes under mannitol and NaCl stress. There were subtle differences in expression levels, indicating that using the top two target genes (in combination) for normalization could further reduce the errors caused by a single reference gene [14, 77]. Similarly, Škiljaica et al. [77] showed that combining the unstable reference gene with one or two top-ranked genes for normalization may substantially mitigate the inaccuracy generated by a poorly chosen reference gene. Meanwhile, the lowest-ranked genes overestimated the relative gene expression of BSK and AP2/ERF.

Several studies have focused on the stability of candidate reference genes in single plant tissue responses to multiple stresses or treatments [50, 78, 79]. Nonetheless, the findings of the present study highlight that these studies may have overlooked the differences in the stability of the reference genes in different tissues exposed to the same stress or treatment. Under specific conditions (mannitol and NaCl stress), the reference genes selected from each unique tissue showed higher trend and relative expression accuracy of the target genes than reference genes selected from a wider range (e.g., all leaf samples, all stem samples, all root samples, and all samples). This result is consistent with the Yin et al. [13] and Wang et al. [14] findings.

Therefore, before analyzing gene expression under different experimental conditions and plant tissues, it is necessary to evaluate and confirm the reference genes to ensure the reliability of the stable reference genes. The single-use of general reference genes screened from a broader range of target gene expression patterns is less effective than the reference genes screened from specific plant species, living environments, and test tissue. However, it is undeniable that the single use of total general genes can obtain relatively reliable results under some treatments or conditions. The relative expression levels of target genes varied with the difference and number of selected reference genes [13]. Thus, target reference gene use might be a quick, convenient, and time-saving method for analyzing the relative expression of genes using stable reference genes selected from a broader range to minimize the errors caused by the single use of a total general reference gene. Furthermore, the selected reference genes, ACTIN and GAPDH, showed high stability in cold-stressed Kobresia plants, indicating that they could be used as relatively stable reference genes in the other Kobresia species (Data not shown).

Most Kobresia plants are polyploid, and the basic chromosome number of Kobresia species is 16 to 40 [80]. Thus, the stability of ACTIN and other stable reference genes in other Kobresia species and conditions requires further verification.

The following gene quantitative investigations should include preliminary tests according to species, tissues, and plant environment variations to identify stable reference genes that properly reflect the relative gene expression. Furthermore, future molecular research involving Kobresia plants under abiotic stress and hormone treatments will ensure the correctness of the RT-qPCR normalization.

Conclusion

This study presents the first systematic and exhaustive analysis of potential reference genes in the Kobresia plants (K. littledalei), validating the accuracy of the selected reference genes. The most stable reference genes were distinct in different tissues and under abiotic/hormone stresses. The combined stability of the two reference genes was better than that of the single ones. Under normal conditions, ACTIN was the most stable reference gene in the leaf and stem tissue, and GAPDH in the root tissue. Under mannitol stress, ACTIN was the most stable reference gene in the leaf tissue and GAPDH and SOD in stem and root tissues. Further, RPL6 was the most stable reference gene in the leaf and stem tissues, and GAPDH in the root tissue under NaCl stress. Under ABA treatment, EF1-alpha was the most stable for leaf tissue, and SOD and ACTIN in the stem and root tissues. Finally, EF1-alpha was the most stable reference gene under GA treatment in the leaf, and RPL6 and 28 S in the stem and root tissues, respectively.

Availability of data and materials

All data generated or analysed during this study are included in this published article (and its supplementary information files).

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Acknowledgements

We gratefully acknowledge the support provided by the Tibet Finance Department Project (grant no. XZ202001ZY0016N). Thanks are due to Dr. Zhongxing Li for his help on genetics-related questions.

Funding

The Tibet Finance Department Project (grant no. XZ202001ZY0016N).

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Authors and Affiliations

  1. College of Grassland Agriculture, Northwest A&F University, Yangling, 712100, Shaanxi Province, PR China

    Haoyang Sun, Chunping Li, Siyu Li, Jiaxin Ma, Shuo Li, Cai Gao, Rongchen Yang, Nan Ma, Jing Yang, Peizhi Yang, Xueqing He & Tianming Hu

  2. College of Natural Resources and Environment, Northwest A&F University, Yangling, 712100, Shaanxi Province, PR China

    Xin Li

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  1. Haoyang Sun
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  2. Chunping Li
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Contributions

H.S. designed the research, analyzed the data and wrote the main manuscript; C.L., S.L., J.M. and Shuo.L. provided validation analyze and data collection; X.L. reviewed and edited the manuscript; C.G., R.Y., N.M. and JY performed the experiments; P.Y., X.H. and T.H provided project and funding acquisition. X.H. and T.H. revised the manuscript and gave final approval of the version to be published. All authors read and approved the manuscript.

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Correspondence to Xueqing He or Tianming Hu.

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Sun, H., Li, C., Li, S. et al. Identification and validation of stable reference genes for RT-qPCR analyses of Kobresia littledalei seedlings. BMC Plant Biol 24, 389 (2024). https://doi.org/10.1186/s12870-024-04924-w

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BMC Plant Biology

ISSN: 1471-2229

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