1. Introduction
Mango (Mangifera indica L.), an evergreen tree belonging to the Anacardiaceae family, is primarily distributed in tropical and subtropical regions. Known as “the king of tropical fruits”, it has gained great popularity with consumers due to its special taste, rich nutrition, various active ingredients [1], and pharmacological actions [2,3]. ‘Carabao’ mango originates from the Philippines and has an international reputation for its sweetness and exotic flavor. It is a Southeast Asian lineage representative variety with yellow-green skin and multiple embryos. Several mango genome sequences have so far been released [4,5,6], which facilitate gene expression analysis, functional gene mining, and the deciphering of metabolic pathways in mango research.
Real-time quantitative polymerase chain reaction (Real-Time PCR) is a technique that is widely used to determine the relative expression of target genes; it is rapid, specific, accurate, and highly sensitive [7]. However, the accuracy of its results is inevitably affected by various factors including RNA purity, primer design, amplification efficiency, and template quality [8,9]. Thus, it requires stable reference genes to use for standardized calibration [10,11,12]. In general, reference genes are considered to be a class of genes with relatively stable expression [13], but investigations have demonstrated that no ideal reference genes can be stably expressed in different conditions [14,15]. Therefore, housekeeping genes, such as ACTIN, GAPDH, and TUBB [13], are frequently used as reference genes due to their stable expression in specific tissues or environments [16]. Moreover, the stability of a reference gene can be affected by differences in plant species, growth environments, growth stages, and environmental stressors [14]. As such, it is common to use multiple reference genes to normalize the real-time PCR data. Currently, a stable reference gene or combinations of multiple reference genes have been screened in many plants, such as peanuts [17], Cephalotaxus hainanensis [18], Salvia hispanica [19], Quercus mongolica Fisch. ex Ledeb [20], Peucedanum praeruptorum Dunn [21], Hedera helix L. [22], and pears [23]. For these plants, ACT, polyUb, F-box, TUBA, TUBB, UBC, 18S, GAPDH, PTB3, SAND, etc. were commonly selected and validated as candidate reference genes. However, the stable reference genes in mangos have yet to be explored.
In this study, 10 candidate reference genes (ACT, polyUb, F-box, TUBA, TUBB, UBC, 18S, GAPDH, PTB3, and SAND) were screened from the ‘Carabao’ genome database (unpublished). Subsequently, real-time PCR data of 10 candidate reference genes under seven abiotic stress treatments (MeJA, Mannitol, NaCl, SA, ABA, heat, and cold) and in four different tissues (root, stem, leaf, and fruit) were obtained. When their real-time PCR data were input into four professional candidate reference gene scoring software packages (geNorm, NormFinder, BestKeeper, and RefFinder), an overall stability ranking for all reference genes was generated based on their unique algorithms. Finally, suitable reference genes were comprehensively analyzed according to this ranking. To further test the reliability of the identified reference genes, Chalcone synthase 1 (CHS-1) and Chalcone synthase 2 (CHS-2), two key genes in flavonoid biosynthesis from ‘Carabao’, were used as the target genes.
2. Materials and Methods
2.1. Plant Materials and Treatment Sets
All materials for this experiment were obtained from ‘Carabao’ mango trees in the Germplasm Repository of Mango (Mangifera indica), DanZhou City, Ministry of Agriculture, Hainan Province, China.
All materials were randomly sampled with three biological replicates. The different tissues (root, stem, leaf, and fruit) were snap-frozen in liquid nitrogen immediately after collection and were subsequently stored in a −80 °C refrigerator for subsequent RNA extraction. Leaf tissues were immediately subjected to seven abiotic stress treatments after they were collected in this study. For treatments of MeJA (100 μM), Mannitol (100 μM), NaCl (100 μM), SA (100 μM), and ABA (10 μM), the leaves were infiltrated with the corresponding concentration of the solution for about 1 min and then placed in a plastic crisper box for moisturizing at room temperature. For the heat and cold treatments, the leaves were placed in incubators at 40 °C and 15 °C, respectively. Finally, the leaves subjected to these treatments were collected at 0 h, 2 h, 6 h, 12 h, and 24 h, and then stored in a −80 °C refrigerator, after snap freezing with liquid nitrogen, for subsequent RNA extraction.
2.2. Total RNA Isolation and cDNA Synthesis
For leaf samples treated with abiotic stresses, total RNA was isolated and extracted using an RNA Rapid extraction Kit (GeneBeter, Beijing, China). Meanwhile, the Total RNA Extraction Kit (Tiangen, Beijing, China) was used for samples from different tissues, because the former kit is only suitable for the extraction of RNA in mango leaves. RNA purity and concentration were assayed using a Nano Photometer P-Class instrument (Implant, Munich, Germany). The integrity of the RNA was verified using 1% agarose gel electrophoresis. Total RNA (1.0 μg) was reverse transcribed into 10 μL of cDNA for subsequent qPCR, according to the operating instructions of HiScript® III RT SuperMix for qPCR (Novozymes, Nanjing, China), which uses the Random primers/Oligo(dT)20VN primer mix.
2.3. Primer Design and Real-Time PCR Reaction Conditions
Sequences of 10 candidate reference genes (Table S2) were obtained from the ‘Carabao’ genome. Specific primer pairs were designed using the Beacon Designer 8 software, according to primer sequences of 18–24 nucleotides, an amplicon length of 100–200 bp, a melting temperature (Tm) of 55–60 °C, and a GC content of 40–60%. All primer pairs were synthesized by a commercial company (Biotech, Shanghai, China) and amplicon products were tested using 1% agarose gel electrophoresis after performing real-time PCR. The presence of a single band on 1% agarose gel electrophoresis was used to verify the amplification product. In addition, the amplification efficiency (E) and correlation coefficient (R2) were calculated by standard curves, which were generated using the QuantStudio 6 Flex real-time PCR system (ThermoFisher, MA, USA) using 1-fold, 1/25-fold, 1/125-fold, and 1/625-fold gradient dilutions of cDNA as templates. Finally, descriptions of all candidate reference genes, regarding primer sequences, amplicon length, Tm, GC content, amplification efficiency, and correlation coefficients, are listed in Table 1.
All Real-Time PCR reactions, including standard curves, were conducted in 96-well plates using the QuantStudio 6 Flex real-time PCR system (ThermoFisher, Waltham, MA, USA). In total, 10 μL of the reaction system was used for each reaction, containing the following components: 1 μL diluted cDNA template (1 μg/μL), 5 μL 2× ChamQ Universal SYBR qPCR Master Mix (Novozymes, Nanjing, China), 0.8 μL forward primer (2.5 μM), 0.8 μL reverse primer (2.5 μM), 2.4 μL ddH2O. The SYBR mix (Novozymes) contains dNTPs, Mg2+, Champagne Taq DNA Polymerase, Specific ROX Reference Dye, etc. The reaction program was performed according to the following three steps: 1 cycle of pre-denaturation (95 °C, 30 s); 40 cycles of denaturation (95 °C, 10 s); and 40 cycles of annealing/extension (60 °C, 30 s). The cycle threshold (Ct) values were obtained when the above reaction program was completed. The melting curve was drawn by a melting curve program in which the amplification product was gradually heated from 65 °C to 95 °C after the real-time PCR reaction program. The appearance of a single peak on the melting curve was used to identify specific amplification products. Three technical replicates were set for each sample subjected to real-time PCR.
2.4. Data Analysis and Stability Evaluation of the Reference Genes
To analyze the stability of the candidate reference genes, four software programs, geNorm, NormFinder, Bestkeeper, and RefFinder, were employed according to their unique algorithms. For geNorm and NormFinder, all raw Ct values were necessarily transformed into relative quantitative data using Equation 2−ΔCt (ΔCt = corresponding Ct value − minimum Ct value). Meanwhile, the expression stability value (M), which was used to evaluate the gene stability, was calculated based on average pairwise variation (V) for each gene when relative quantitative data were imported into geNorm [24]. Similarly to geNorm, the expression stability value (M) in NormFinder can also be calculated to evaluate gene stability, but based on inter- and intra-group variation [8]. The reference genes with the lowest M-values are considered to be the most stably expressed for both software packages. For Bestkeeper, the standard deviation (SD) and the coefficient of variation (CV) can be calculated directly via the raw Ct values to assess the stability of each reference gene [25], with lower CV values implying higher stability. Finally, a comprehensive ranking was generated by RefFinder (
2.5. Validation of Reference Gene Stability
Chalcone synthase (CHS) is a key enzyme for flavonoid synthesis in plants; it catalyzes the synthesis of chalcone from p-coumaroyl-CoA and malonyl-CoA molecules, and can be regulated by stress [26]. Additionally, previous studies have shown that miCHS was variably expressed in diverse mango tissues [27]. Therefore, we screened two CHS genes from the ‘Carabao’ genome, namely, miCHS-1 and miCHS-2, and their relative expression levels were used as a criterion to verify the reliability of the reference genes in the present study. The relative expression levels of miCHS-1 and miCHS-2 were generated in different tissues and under NaCl stress using the two most stable and one least stable reference genes, respectively, which were obtained by RefFinder analysis. Relative expression results were calculated using the 2−ΔΔCt method with three technical replicates for each sample.
3. Results
3.1. Primer Validation and the Expression Levels of Candidate Reference Genes
Ordinary PCR and real-time PCR were used to test the primer specificity of all candidate reference genes. The presentation of a single target band on 1% agarose gel electrophoresis and the appearance of a single peak on the melting curve indicated that all primer pairs were capable of amplifying specific amplicons (Figure S1). Detailed descriptions of all candidate reference genes, including abbreviations, gene numbers, primer sequences, amplicon lengths, amplification efficiencies (E), and correlation coefficients (R2), are listed in Table 1. Amplification efficiencies varied from 101.8% for GAPDH to 113.9% for 18S, and the correlation coefficients ranged from 99.17% for GAPDH to 99.80% for TUBB.
The Ct values of each candidate reference gene generated by real-time PCR under different experimental conditions were used to intuitively display gene expression and stability, as presented in Figure 1. The Ct values, across all samples, ranged between 6.02 and 30.59, with 18s and GAPDH being the lowest and highest, respectively. In addition, different candidate reference genes exhibited different coefficients of variation (lower values mean a lower level of variation). As shown in Figure 1, GAPDH (12.05%) showed the largest variation and TUBB (2.57%) varied the least; the remaining values were 18S (9.67%), ACTIN (3.85%), F-box (3.09%), polyUb (3.07%), PTB3 (3.70%), SAND (2.74%), TUBA (4.49%), and UBC (2.99%).
3.2. Analysis of the Stability of the Expression of Candidate Reference Genes
3.2.1. geNorm Analysis
For geNorm, the stability of different reference genes can be compared using M-values (a lower value indicates higher stability), which can be calculated according to the average variation of a gene among different genes [24]. Meanwhile, the stability ranking of each reference gene in different experimental conditions can be generated separately according to this M-value. TUBB and F-box showed higher stability with lower M-values in most abiotic stress samples. Similarly, TUBB and UBC were more stable in different tissues compared to other candidate reference genes. In contrast, GAPDH was considered to be the most unstable gene, with the highest M-values under all experimental conditions (Figure 2). The number of suitable reference genes can also be determined by pairwise variation (V), which was calculated by geNorm algorithms where the V-value of a stable reference gene should not exceed the threshold value (0.15). In the present study, all V2/3 values were below 0.15, except for different tissue sets (Figure S2), indicating that real-time PCR results could be reliably normalized by using only two reference genes in these sets [24]. However, 0.15 was not a strict threshold parameter and was only used as a recommendation to determine the number of reference genes to normalize the real-time PCR results [24,28]. Furthermore, all M-values were below the ideal threshold of 1.5 in this study, which indicates the presence of available stably expressed reference genes. Therefore, we suggest that a single reference gene can be used in ‘Carabao’ mangos.
3.2.2. NormFinder Analysis
For NormFinder, the stability of all candidate reference genes was calculated based on intra-and inter-group variation, and their stability ranking was generated according to the expression stability value (lower values are more stable). As shown in Table 2, TUBB, UBC, and F-box were considered more stable in most of the experimental samples because of their low expression stability value, while GAPDH, 18S, and TUBA were unstable relative to the other candidate reference genes. Notably, GAPDH was the least stable both under abiotic stress and in different tissues.
3.2.3. BestKeeper Analysis
For the BestKeeper analysis, the coefficient of variation (CV) and the standard deviation (SD) could be directly calculated using the raw Ct values. Candidate reference genes with the lowest CV and SD values are defined as the most stable. Additionally, reference genes with an SD of more than 1 cannot be used to normalize the real-time PCR results. According to the ranking produced by the BestKeeper analysis (Table 3), the most stable reference genes were TUBB for the heat, ABA, and SA treatment sets, SAND for the different tissue sets, UBC for the NaCl- and cold-treated sets, and ployUb for the Mannitol- and MeJA-treated sets. Interestingly, TUBB ranked highest in both the total samples and the abiotic stress sets. Meanwhile, GAPDH was the most unstable because of its strong SD value, which was mostly above 1.
3.2.4. RefFinder Analysis
The comprehensive ranking of each candidate reference gene was further analyzed and calculated using the RefFinder algorithm based on the above results provided by the three software programs (geNorm, NormFinder, and BestKeeper) and listed in Table 4 and Table S1. TUBB was more stable than the other candidate reference genes due to its top three comprehensive rankings in all experimental conditions: it ranked first in the NaCl stress, abiotic stress, tissue, and total treatment sets; second in the heat and SA treatment sets; and third in the cold, ABA, Mannitol, and MeJA treatment sets. Conversely, GAPDH was the most unstable gene, with the lowest combined ranking in all experimental conditions.
3.3. Reference Gene Validation
To verify the stability and reliability of the selected reference genes, the expression levels of miCHS-1 or miCHS-2 were normalized using the two most stable reference genes and the one least stable reference gene under NaCl treatment or in different tissues, which were selected based on the comprehensive ranking results of the RefFinder analysis (Figure 3). Under NaCl treatment, expression of miCHS-1 or miCHS-2 in a 0 h sample was assumed as “1” to calculate their relative expression at other time points, based on the 2−ΔΔCt method. As shown in Figure 3A, the relative expression of miCHS-1 was 2.14 and 2.78 times higher for 2 h samples; 3.33 and 3.21 times higher for 6 h samples; 2.09 and 1.88 times higher for 12 h samples; and 0.86 and 0.66 times higher for 24 h samples when using the most stable reference genes (TUBB and polyUb), demonstrating little difference in the trend of miCHS-1 relative expression. Similar results can be seen in Figure 3C, when TUBB and polyUb were used to calculate the relative expression of miCHS-2. However, when using the least stable reference gene (GAPDH) to normalize the expression levels of miCHS-1 or miCHS-2, significant changes can clearly be observed, especially for the 6 h samples, where the normalization levels of miCHS-1 and miCHS-2 were 8.21 and 22.84 times higher than the 0 h samples, respectively. In different tissues, the relative expression of miCHS-1 or miCHS-2 was calculated according to the above method, but the leaf sample was assumed to be “1”, as shown in Figure 3B,D. The results were similar to those produced by NaCl treatment; there was little change in the relative expression trends of miCHS-1 or miCHS-2 in different tissues when the most stable genes (TUBB and UBC) were used for normalization, whereas large differences were generated if the least stable reference gene (GAPDH) was used.
4. Discussion
Among the different varieties of mango, ‘Carabao’ mango is popular in the Philippines due to its unique flavor and nutritional richness; as such, it is known as the ‘Philippine Super Mango’ [29]. Thanks to the elucidation of the ‘Carabao’ mango genome sequence, an increasing number of studies have focused on the ‘Carabao’ mango to uncover potential functional genes and metabolic pathways, which has greatly contributed to our understanding of the molecular mechanisms of mangos. To facilitate the mining of functional genes and the deciphering of metabolic pathways, it is necessary to accurately quantify the key functional genes. Real-time PCR is widely used to determine the relative expression of target genes, and the accuracy of its results requires the selection of stable reference genes for standardized calibration [10,11,12]. However, there are few reports of available stable reference genes for mangos. To normalize real-time PCR results in mangos, stable reference genes must be considered comprehensively, as their stability may be affected in different environments or tissues [14]. Therefore, in this study, the stability of the selected candidate reference genes was evaluated synthetically under seven abiotic stress treatments and in four different tissues. For the abiotic stress treatments, NaCl and Mannitol were used to simulate salt stress and osmotic stress [30], and stress-response-related signaling molecules, including ABA, SA, and MeJA, were used to activate the stress responses of the plants.
In the current study, we selected 10 genes as candidates: ACT, polyUb, F-box, TUBA, TUBB, UBC, 18S, GAPDH, PTB3, and SAND, which have all been identified and validated in other plant species. For example, in Hedera helix L., F-box was confirmed to be the most stable gene under all experimental conditions except for ABA treatment [22]; in Cephalotaxus hainanensis, 18S was identified as the most stable reference gene both in leaves and suspension cells under different abiotic stresses [18]; in Salvia hispanica, GAPDH remained stable when subjected to different abiotic stresses [19]. In Rhododendron [31], ACT and 18S were proven to be stable reference genes in different tissues, while TUBB was not an appropriate reference gene in these tissues. In Momordica charantia [32], PTB was among the top-three-ranked reference genes under different treatment conditions, but SAND was not considered a reference gene because of its lower stability. In Raphanus sativus L. [33], UBC and GAPDH were suitable reference genes, with the most stable expression under various stresses, whereas TUBA was better for the distant hybrid.
The raw Ct values of the candidate reference genes generated by real-time PCR can intuitively reflect gene expression levels [15]. However, the raw Ct values significantly varied under different experimental conditions, as shown in Figure 1. To obtain realistic and reliable reference genes for normalizing real-time PCR, four analysis software packages (geNorm, NormFinder, BestKeeper, and RefFinder), which are widely used to assess the stability of reference genes in relevant studies, were employed to estimate the stability of the candidate reference genes. Many studies have shown the analysis results from geNorm, NormFinder, and BestKeeper to be inconsistent due to their distinct algorithms [18,20,31,32]. Similar results can be found in this study. For example, the top three genes in the ABA treatment are F-box, UBC, and TUBB for geNorm; UBC, F-box, and PTB3 for Normfinder; and TUBB, F-box, and UBC for BestKeeper. Such results greatly hinder the screening of stable internal reference genes. Therefore, the stability of each candidate reference gene needs to be systematically analyzed by RefFinder, which can produce a comprehensive ranking based on the results of the above three software programs, and its final results were used as a basis for discussing the stability of each reference gene. Ultimately, the stability of TUBB, as calculated by RefFinder, ranked in the top three experimental samples, especially in the total sample set, the different tissue sets, and the abiotic stress sets. As a result, we concluded that TUBB is a more stable reference gene relative to the other candidate reference genes in ‘Carabao’ mangos.
To normalize real-time PCR results, multiple combinations including two or more reference genes are often used to deal with different conditions, and the optimal number can also be calculated by geNorm based on the pairwise variation (V) score, which requires a default threshold value of less than 0.15. As shown in Table S1, the V2/3 values of all the experimental samples are below 0.15, except for the tissue sets, indicating that the normalization of real-time PCR results could be performed by using just two reference genes. However, the threshold value of 0.15 is not strictly a threshold parameter; it is only used as a recommendation to determine the number of reference genes for normalizing a real-time PCR [24,28]. Moreover, all M-values, which were calculated by geNorm to measure the stability of each candidate reference gene (the smaller the value, the more stable it becomes), were lower than the specified threshold of 1.5, as shown in Figure 2. Thus, V-values are not necessary parameters to confirm the number of candidate reference genes; accurate results can also be obtained using a reference gene with a low M-value [34]. Here, we suggest that using a single reference gene with a higher comprehensive ranking under all experimental conditions may be a better option for normalizing real-time PCR in ‘Carabao’ mangos.
Finally, two genes that are key to flavonoid synthesis in ‘Carabao’ mangos, miCHS-1 and miCHS-2, were used to validate the stability of the selected reference genes, according to their relative expression, using the two most stable reference genes and the one least stable reference gene under NaCl treatment or in different tissues, respectively. The normalization results (Figure 3) demonstrate that the trend in miCHS-1 or miCHS-2 relative expression varied little when the most stable reference genes were used for normalization. Conversely, significant changes were observed when using the least stable reference gene. These results indicate that the reference genes selected and identified in this study can truly and accurately reflect the relative quantitative results of the target genes, and also illustrate that the selection and evaluation of stable reference genes are essential for normalizing real-time PCR in mangos.
5. Conclusions
In this study, the stability of 10 reference genes was tested under seven abiotic stresses and in four different tissues for real-time PCR normalization. The results showed that the stability of the different reference genes varied significantly under diverse conditions, and stable reference genes should be evaluated systematically for real-time PCR normalization in ‘Carabao’ mangos. Ultimately, TUBB was identified as the most suitable reference gene, as its stable expression enables it to cope with various conditions; this is reflected in the fact that it was ranked in the top three across all the experimental samples, based on the above results. In general, as a fundamental aspect of mango research, the selection and validation of stable reference genes will facilitate future accurate quantification of target genes by real-time PCR in mangos.
Conceptualization, Y.C. (Yeyuan Chen) and F.Q.; methodology, R.Y., H.C. and X.H.; validation, R.Y., H.C. and F.Q.; resources, Y.C. (Yeyuan Chen) and F.Q.; writing—original draft preparation, R.Y.; writing—review and editing, F.Q. and Y.C. (Yunjiang Cheng); supervision, F.Q.; funding acquisition, Y.C. (Yeyuan Chen) and F.Q. All authors have read and agreed to the published version of the manuscript.
Not applicable.
The authors declare no conflict of interest.
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Enlarge this image.Figure 1. Raw Ct values of 10 candidate genes across all samples (a), stress-treated leaf samples, (b) and different tissues samples (c). The boxes indicate the range from the 25th to 75th percentiles and are crossed by a horizontal line that represents the median. The whiskers reach down to the lowest and up to the highest values; the empty black circle in the middle of the box refers to the mean value. * refers to the maximum value.
Enlarge this image.Figure 2. Average expression stability values (M) of 10 candidate reference genes were calculated using geNorm. Expression stability was assessed in stress-treated leaf samples (cold, heat, ABA, Mannitol, MeJA, NaCl, and SA stress), different tissue samples (root, stem, leaf, and fruit), total leaf stress treatment samples, and total samples. The reference genes with lower M-values have higher stability, as is exhibited on the right.
Enlarge this image.Figure 3. Validation of reference genes. The relative expression of miCHS-1 or miCHS-2 was normalized using the most stable and least stable reference genes under NaCl treatment or in different tissues. (A) Relative expression of miCHS-1 under 100 μM NaCl treatment; (B) relative expression of miCHS-1 in the tissues set; (C) relative expression of miCHS-2 under 100 μM NaCl treatment; (D) relative expression of miCHS-2 in the tissues set. All materials subjected to 100 μM NaCl treatment were ‘Carabao’ mango leaves and were collected at 0 h, 2 h, 6 h, 12 h, and 24 h.
Description and primer sequences of candidate reference and target genes.
| Gene Symbol | Gene Name | Gene ID | Primer Sequences (5′-3′) |
Amplicon Product | E (%) |
R2 |
|
|---|---|---|---|---|---|---|---|
| Tm(°C) |
Length |
||||||
| ACT | Actin | OP047690 | CAAGGCTAATCGTGAGAAGATGA/CTCCAGAATCCAACACAATACCA | 54.7/54.7 | 134 | 107.6 | 0.9976 |
| polyUb | Polyubiquitin | OP047691 | TTCACCTGGTCCTTCGTCTC/AAGTGTGCGTCCATCCTCAA | 54.7/55.2 | 197 | 110.7 | 0.9976 |
| F-box | F-box family protein | OP047692 | AGATGGATGCTTGTCTGTGATTC/CCTGCTTATGAGATGCTAAGAAGA | 55.1/54.7 | 188 | 103.1 | 0.9964 |
| TUBA | alpha-tubulin | OP047693 | TCGTCTATGATGGCTAAGTGTGA/AGTTGGTGGCTGGTAGTTGATA | 55.4/55.1 | 189 | 104.5 | 0.9971 |
| TUBB | beta-tubulin | OP047694 | GTCGCTACCTCACTGCTTCA/CACAGACACTGGACTTGACATTA | 55.4/54.7 | 141 | 106.6 | 0.9980 |
| UBC | ubiquitin-conjugation enzyme E2 | OP047695 | GTTGATGGATTCTCTGCTGGTT/CACACTTGGAGGGCTCACA | 54.7/54.9 | 153 | 112.5 | 0.9917 |
| 18S | 18S ribosomal RNA | OP159972 | GATACCGTCCTAGTCTCAACCA/TTCAGCCTTGCGACCATACT | 54.8/55.0 | 131 | 113.9 | 0.9953 |
| GAPDH | Glyceraldehyde-3-phosphate dehydrogenase | OP047696 | AGGTCATCAAGGTTGTCACTAATC/CCTGCCTGAATGTGCTTACC | 55.0/54.6 | 130 | 101.8 | 0.9965 |
| PTB3 | polypyrimidine tract-binding protein 3 | OP047697 | AGGATGTCACTGAAGAGGAGATT/TCGGATTATAGAGCCACCAAGT | 54.9/54.7 | 178 | 111.1 | 0.9925 |
| SAND | SAND family protein | OP047698 | CACTGCCTCGTTCTTCCATATC/AAGGACCACCAATACCAATAACTG | 55.1/55.2 | 102 | 106.9 | 0.9953 |
| miCHS-1 | Chalcone synthase 1 | KF956022.1 | CTGAGAACAACAAAGGTG/CAGAACCAACAATGAGAG | 57.3/56.7 | 147 | 106.7 | 0.9956 |
| miCHS-2 | Chalcone synthase 2 | KF956023.1 | CCGAAGACATTTTGAAGG/CAGAAGATAAGGTGGGTA | 57.4/56.2 | 172 | 101.8 | 0.9942 |
Ranking of the 10 candidate reference genes based on NormFinder.
| Rank | Total | Abiotic Stresses | Tissues | Cold | Heat | ABA | Mannitol | MeJA | NaCl | SA |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | TUBB (0.325) | ACT (0.215) | TUBB (0.091) | UBC (0.133) | F-box (0.092) | UBC (0.056) | polyUb (0.112) | F-box (0.065) | polyUb (0.057) | F-box (0.182) |
| 2 | F-box (0.326) | F-box (0.295) | UBC (0.091) | polyUb (0.239) | PTB3 (0.16) | F-box (0.11) | SAND (0.259) | SAND (0.326) | TUBB (0.158) | SAND (0.311) |
| 3 | UBC (0.426) | TUBB (0.384) | SAND (0.22) | F-box (0.272) | SAND (0.191) | PTB3 (0.188) | UBC (0.306) | PTB3 (0.365) | F-box (0.191) | ACT (0.354) |
| 4 | SAND (0.469) | UBC (0.416) | polyUb (0.289) | TUBB (0.368) | TUBA (0.216) | polyUb (0.423) | ACT (0.375) | TUBB (0.395) | UBC (0.297) | TUBB (0.36) |
| 5 | polyUb (0.588) | PTB3 (0.501) | 18S (0.524) | TUBA (0.377) | UBC (0.224) | TUBB (0.424) | PTB3 (0.433) | ACT (0.413) | ACT (0.407) | 18S (0.447) |
| 6 | PTB3 (0.637) | SAND (0.516) | F-box (0.602) | ACT (0.388) | TUBB (0.49) | ACT (0.448) | TUBB (0.623) | polyUb (0.447) | TUBA (0.431) | PTB3 (0.477) |
| 7 | ACT (0.64) | polyUb (0.617) | TUBA (1.173) | SAND (0.414) | ACT (0.514) | SAND (0.485) | 18S (0.676) | UBC (0.516) | PTB3 (0.548) | polyUb (0.509) |
| 8 | TUBA (0.726) | TUBA (0.639) | PTB3 (1.344) | PTB3 (0.619) | polyUb (0.962) | 18S (0.514) | F-box (0.692) | 18S (0.707) | 18S (0.634) | TUBA (0.613) |
| 9 | 18S (0.903) | 18S (0.922) | ACT (1.384) | 18S (0.713) | 18S (1.032) | TUBA (0.68) | TUBA (0.806) | TUBA (0.754) | SAND (0.909) | UBC (0.666) |
| 10 | GAPDH (2.627) | GAPDH (2.339) | GAPDH (4.001) | GAPDH (0.997) | GAPDH (3.277) | GAPDH (2.495) | GAPDH (2.012) | GAPDH (2.17) | GAPDH (1.908) | GAPDH (1.818) |
Ranking of the 10 reference genes based on BestKeeper.
| Rank | Total | Abiotic Stresses | Tissues | Heat | Mannitol | ||||||||||
| Gene | SD | CV | Gene | SD | CV | Gene | SD | CV | Gene | SD | CV | Gene | SD | CV | |
| 1 | TUBB | 0.38 | 1.87 | TUBB | 0.38 | 1.88 | SAND | 0.29 | 1.28 | TUBB | 0.39 | 1.89 | polyUb | 0.26 | 1.43 |
| 2 | polyUb | 0.42 | 2.37 | polyUb | 0.43 | 2.39 | 18S | 0.30 | 3.90 | ACT | 0.42 | 1.78 | TUBB | 0.36 | 1.78 |
| 3 | SAND | 0.49 | 2.11 | UBC | 0.49 | 2.21 | polyUb | 0.30 | 1.68 | polyUb | 0.43 | 2.42 | UBC | 0.40 | 1.82 |
| 4 | UBC | 0.51 | 2.33 | F-box | 0.50 | 2.13 | TUBB | 0.30 | 1.50 | UBC | 0.43 | 1.91 | F-box | 0.43 | 1.82 |
| 5 | F-box | 0.54 | 2.30 | ACT | 0.51 | 2.22 | UBC | 0.36 | 1.68 | 18S | 0.48 | 6.62 | ACT | 0.45 | 1.98 |
| 6 | 18S | 0.57 | 7.68 | SAND | 0.52 | 2.23 | F-box | 0.70 | 3.05 | F-box | 0.53 | 2.21 | SAND | 0.48 | 2.07 |
| 7 | ACT | 0.65 | 2.88 | 18S | 0.60 | 8.07 | TUBA | 0.78 | 4.15 | PTB3 | 0.57 | 2.34 | 18S | 0.58 | 7.56 |
| 8 | TUBA | 0.70 | 3.58 | TUBA | 0.65 | 3.35 | ACT | 0.86 | 4.07 | SAND | 0.68 | 2.81 | TUBA | 0.58 | 2.94 |
| 9 | PTB3 | 0.75 | 3.21 | PTB3 | 0.71 | 3.06 | PTB3 | 0.90 | 3.91 | TUBA | 0.77 | 3.83 | PTB3 | 0.61 | 2.61 |
| 10 | GAPDH | 2.10 | 9.14 | GAPDH | 1.96 | 8.64 | GAPDH | 3.11 | 12.71 | GAPDH | 2.98 | 11.7 | GAPDH | 1.85 | 8.31 |
| Rank | NaCl | Cold | ABA | MeJA | SA | ||||||||||
| Gene | SD | CV | Gene | SD | CV | Gene | SD | CV | Gene | SD | CV | Gene | SD | CV | |
| 1 | UBC | 0.19 | 0.89 | UBC | 0.25 | 1.17 | TUBB | 0.12 | 0.61 | polyUb | 0.24 | 1.36 | TUBB | 0.20 | 0.99 |
| 2 | PTB3 | 0.38 | 1.65 | F-box | 0.41 | 1.77 | F-box | 0.26 | 1.12 | F-box | 0.34 | 1.43 | F-box | 0.27 | 1.16 |
| 3 | SAND | 0.38 | 1.67 | SAND | 0.42 | 1.84 | UBC | 0.27 | 1.25 | ACT | 0.37 | 1.62 | 18S | 0.30 | 3.94 |
| 4 | TUBB | 0.42 | 2.10 | TUBB | 0.43 | 2.16 | ACT | 0.33 | 1.47 | TUBB | 0.38 | 1.84 | polyUb | 0.32 | 1.77 |
| 5 | polyUb | 0.44 | 2.49 | TUBA | 0.44 | 2.33 | SAND | 0.33 | 1.44 | SAND | 0.42 | 1.85 | TUBA | 0.37 | 1.91 |
| 6 | F-box | 0.52 | 2.29 | ACT | 0.46 | 2.04 | PTB3 | 0.37 | 1.60 | PTB3 | 0.43 | 1.90 | SAND | 0.39 | 1.69 |
| 7 | 18S | 0.58 | 7.51 | polyUb | 0.48 | 2.61 | TUBA | 0.38 | 2.00 | 18S | 0.58 | 7.65 | ACT | 0.41 | 1.81 |
| 8 | TUBA | 0.66 | 3.50 | PTB3 | 0.59 | 2.52 | 18S | 0.39 | 5.48 | UBC | 0.58 | 2.59 | UBC | 0.50 | 2.29 |
| 9 | ACT | 0.69 | 3.09 | 18S | 0.64 | 9.12 | polyUb | 0.48 | 2.72 | TUBA | 0.74 | 3.79 | PTB3 | 0.59 | 2.57 |
| 10 | GAPDH | 1.94 | 9.21 | GAPDH | 0.71 | 3.23 | GAPDH | 2.22 | 10.15 | GAPDH | 1.64 | 7.43 | GAPDH | 1.50 | 6.85 |
The most stable and least stable combinations of candidate reference genes based on RefFinder.
| Experimental Treatments | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Cold | Heat | ABA | Mannitol | MeJA | |||||
| Most | Least | Most | Least | Most | Least | Most | Least | Most | Least |
| UBC | GAPDH | F-box | GAPDH | F-box | GAPDH | polyUb | GAPDH | F-box | GAPDH |
| F-box | TUBB | UBC | UBC | SAND | |||||
| TUBB | ACT | TUBB | TUBB | TUBB | |||||
| NaCl | SA | Abiotic Stresses | Tissues | Total | |||||
| Most | Least | Most | Least | Most | Least | Most | Least | Most | Least |
| TUBB | GAPDH | F-box | GAPDH | TUBB | GAPDH | TUBB | GAPDH | TUBB | GAPDH |
| polyUb | TUBB | F-box | UBC | F-box | |||||
| UBC | ACT | ACT | SAND | UBC | |||||
Supplementary Materials
The following supporting information can be downloaded at:
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; Cheng, Yunjiang 3 ; Chen, Yeyuan 4 1 Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Ministry of Agriculture, Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China; National R&D Center for Citrus Preservation, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
2 Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Ministry of Agriculture, Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
3 National R&D Center for Citrus Preservation, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan 430070, China
4 Key Laboratory of Crop Gene Resources and Germplasm Enhancement in Southern China, Ministry of Agriculture, Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China; Sanya Yazhou Bay Science and Technology City, Sanya Institute, Chinese Academy of Tropical Agricultural Sciences, Sanya 572025, China