Journal of Oceanology and Limnology   2021, Vol. 39 issue(5): 1985-1999     PDF       
http://dx.doi.org/10.1007/s00343-020-0238-8
Institute of Oceanology, Chinese Academy of Sciences
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Article Information

CHEN Xiaojuan, SUN Yun, ZHANG Panpan, LI Jianlong, LI Haiping, WEI Caoying, CAO Zhenjie, ZHOU Yongcan
Screening of stable internal reference genes by quantitative real-time PCR in humpback grouper Cromileptes altivelis
Journal of Oceanology and Limnology, 39(5): 1985-1999
http://dx.doi.org/10.1007/s00343-020-0238-8

Article History

Received Jun. 21, 2020
accepted in principle Sep. 18, 2020
accepted for publication Nov. 13, 2020
Screening of stable internal reference genes by quantitative real-time PCR in humpback grouper Cromileptes altivelis
Xiaojuan CHEN1,2#, Yun SUN1,2,3#, Panpan ZHANG1,2, Jianlong LI1,2,3, Haiping LI2,3, Caoying WEI1,2, Zhenjie CAO1,2,3, Yongcan ZHOU1,2,3     
1 State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou 570228, China;
2 Key Laboratory of Tropical Hydrobiology and Biotechnology of Hainan Province, Haikou 570228, China;
3 Department of Aquaculture, College of Marine Sciences, Hainan University, Haikou 570228, China
Abstract: Humpback grouper Cromileptes altivelis is one commercial fish with considerable economic value. To determine the expression stabilities of six commonly used internal reference genes in C. altivelis challenged by Vibrio harveyi and viral nervous necrosis virus (VNNV) through quantitative real-time PCR (qRT-PCR), the expression levels of selected genes in five immune organs stimulated with pathogenic infection were carefully evaluated using algorithms of geNorm, NormFinder, and BestKeeper. The results show that the expression stabilities of the six candidate internal reference genes were different. Under normal physiological conditions, RPL13 were identified as the most stably expressed genes among five different immune organs (liver, spleen, kidney, intestine, and gill). After V. harveyi stimulation, RPL13, RPL13, EF1A, RPL13, and EF1A were identified by geNorm, NormFinder, and BestKeeper as the most stable genes in liver, spleen, kidney, intestine, and gill, respectively. Combining these three algorithms suggested that under stimulation of VNNV, RPL13, EF1A, Actin, RPL13, and Actin were as the most stable genes in liver, spleen, kidney, intestine, and gill, respectively. These results suggest that specific experiment conditions and tissue types shall be considered when selecting the reference genes in qRT-PCR analysis. This study provided a solid foundation for future studies on gene expression of C. altivelis under different conditions.
Keywords: Cromileptes altivelis    reference gene    expression stability    pathogenic infection    
1 INTRODUCTION

Humpback grouper Cromileptes altivelis belongs to the family Epinephelidae of the order Perciformes (Craig et al., 2011). It is a tropical and valuable species of marine fish with high nutritional value and ornamental value, and mainly distributed in the western Pacific Ocean (Ou et al., 2015). However, humpback grouper is suffering from various pathogenic diseases due to increasing artificial cultures (Sun et al., 2018, 2019). The pathogens of Vibrio harveyi and viral nervous necrosis virus (VNNV) are common pathogenic microorganisms that cause great losses to grouper culture industry (Luo et al., 2013; Chen et al., 2018).

Quantitative real-time PCR (qRT-PCR) is a real-time monitoring of nucleic acid amplification-based technique, with the characteristics of quantitative accuracy, specificity, and high sensitivity to target genes (Huggett et al., 2005; Jain et al., 2006). qRT-PCR has overcome the shortage of traditional PCR from qualitatively to quantitatively, and effectively solved the problem that the traditional PCR technology is prone to contaminated in the process of operation and leads to high false positive rate. In recent years, qRT-PCR has been widely applied in medical detection, environmental monitoring, aquaculture, and other fields (Najafpanah et al., 2013; Li and Hou, 2015; Sun and Sun, 2015; Yang et al., 2015; Pooljun et al., 2016; Li et al., 2019). Especially, it has become the first choice for gene expression analysis (Jain et al., 2006; Resende et al., 2011; Li et al., 2019). Internal reference gene, also known as housekeeping gene, is the reference gene whose expression level is not affected by changes in research conditions and can be consistently expressed in different development stages and physiological conditions of the same tissue (Mahoney et al., 2004). However, ideal internal reference gene is nonexistent. Many studies have shown that some internal reference genes are not truly stable under certain experimental conditions, and the expression of internal reference genes is affected by many external environments (Fernandes et al., 2008; Dang and Sun, 2011; Dobnik et al., 2015; Kang et al., 2019; Wan et al., 2019). Previous studies demonstrated that the expression level of internal reference genes is varied in different tissues, since extremely high or low expression levels may preclude the usefulness of these genes as internal controls. For example, in the fathead minnow (Pimephales promelas), glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was highly expressed in liver, but the lowest expressed in gonad, while Actin was highly expressed in gonad but had a low level of expression in liver under normal physiological conditions (Filby and Tyler, 2007). The so-called constant expression of any internal reference gene is limited in a certain type of tissue or experiment. Therefore, it is necessary to calculate the expression level and evaluated the stability of the internal reference genes in different tissues and/or disease states before the start of any study with real time PCR. Up to now, research on the normalization of internal reference genes of C. altivelis under normal physiological conditions or during V. harveyi and VNNV infection has not been reported.

In this study, combining with three programs of geNorm, NormFinder, and BestKeeper, the stability of mRNA expression of six common internal reference genes, including β-2-Microglobulin (B2M), beta actin (Actin), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), tubulin tyrosine ligase-like family member 1 (TTLL1), elongation factor-1-α (EF1A), and ribosomal protein L13 (RPL13) were evaluated in five immune organs (liver, spleen, kidney, intestine, and gill) under normal physiological conditions and the stimulation of V. harveyi and VNNV by qRT-PCR. Our study will lay a solid foundation for the other studies of immune function genes related to the diseases of C. altivelis.

2 MATERIAL AND METHOD 2.1 Pathogen

Pathogenic V. harveyi had been described that showed strong pathogenicity to C. altivelis (Sun et al., 2018). The bacteria were cultured in the medium of Luria-Bertani (LB) at 28 ℃. VNNV was isolated from diseased fish at a commercial fish farm in Sanya (Hainan Province, China) with adjusting VNNV concentration to 1×107 copies/mL in phosphate-buffered saline (PBS).

2.2 Fish

A total of 50 humpback grouper (C. altivelis) (average weight, 25±3.5 g) was provided by a fish farm in Sanya (Hainan, China). The fish were maintained in aerated running seawater at 26 ℃ for one week and fed twice daily to allow to acclimatizing the laboratory environment. Prior to experiments, five fish were randomly sampled to confirm health condition (Sun et al., 2019). Then, 15 fish were used to determine the most stable reference genes in five immune organs under normal physiological condition. 30 fish were used to confirm the most stable reference genes under the stimulation of V. harveyi and VNNV. Before tissue collection, fish were anesthetized with MS-222 (Sigma, USA) (Sun et al., 2019).

2.3 Sample collection under normal physiological condition

To determine the internal reference genes in humpback grouper under normal physiological condition, tissues (liver, spleen, intestine, kidney, and gill) were collected from 15 fish under aseptic conditions, with equivalent samples from the five fish of each group mixed together to make one sample, then frozen by liquid nitrogen quickly and transferred into-80 ℃ for storage.

2.4 Infection experiment and sample collection

Fish were randomly divided into two groups (A and B, 15 fish/group), which was injected intraperitoneally (i.p.) with 100-μL V. harveyi (105 CFU/mL), and 100-μL VNNV (107 copies/mL), respectively. After that, spleen, kidney, liver, intestine, and gill from five fish in group A were sampled at 9 h after V. harveyi injection. Same tissues as above from five fish in group B were collected at 5 d after VNNV injection. The tissues were collected under aseptic conditions, then frozen by liquid nitrogen quickly and transferred into-80 ℃ for storage. The fish under the normal physiological condition was used as control. The experiments were performed in triplicate.

2.5 RNA extraction and first strand of cDNA synthesis

The total RNA of all tissues was extracted by Eastep® Super Total RNA Extraction kit (Promega, USA). The quality and concentrations of total RNA were detected by 2% agarose gel electrophoresis (Biowest Agarose, Solarbio, China) and NanoDrop 2000 (Thermo Scientific, USA). Then, the first strand of cDNA was synthesized by Eastep® RT Master Mix Kit (Promega, USA) following the manufacturer'manual.

2.6 PCR specificity of internal reference gene primers

Six internal reference genes were selected, including B2M, Actin, TTLL1, RPL13, EF1A, and GAPDH (Table 1). Primers of six internal reference genes were designed by the software of Primer Premier 5 (Table 1), and synthesized by Sangon (Shanghai, China). The cDNA samples were serially diluted 10-fold and used to build standard curve. The slope of the standard curve was used to determine the amplification efficiency (E) and determination coefficient (R2) of qRT-PCR (Chen et al., 2017).

Table 1 The primer pairs of internal reference genes used in this study and the amplification efficiencies of PCR
2.7 qRT-PCR and data analysis

qRT-PCR was used to analyze the expression level of selected internal reference genes using SYBR Green dye method (Eastep® qPCR Master Mix Kit, Promega, USA) through Quant Studio TM 6 Flex Real-Time PCR System Software (Life technologies TM, United States).

The qRT-PCR data was analyzed by geNorm (V.3.5), NormFinder (V.0.953), and Bestkeeper software programs (Vandesompele et al., 2002; Andersen et al., 2004; Pfaffl et al., 2004). Based on Microsoft Excel platform to create VBA macro program, stability parameter M (internal control gene-stability measure) value of geNorm software was calculated to analysis the stability of internal standard. The M value of genes is lower, indicating gene expression is more stable. To confirm the optimal number of internal reference genes required for accurate normalization, a pairwise variation (V) Vn/n+1 analysis between two sequential normalization factors containing an increasing number of genes was performed, and the default cut-off value of Vn/n+1 is 0.15. In NormFinder, the expression stability of candidate internal reference genes is expressed by obtaining the values of variance within and between groups, and the internal reference gene with the lowest value have the most stable expression. In BestKeeper, the most stable internal reference genes were identified based on the pairwise comparisons of raw cycle threshold (Ct) values of each gene. The standard deviation (SD), correlation coefficient (r), and coefficient of variation (CV) generated between each gene can be calculated by BestKeeper. The most stable internal reference genes are those with the smallest SD, smaller CV, and greater r. It is worth noting that when SD was bigger than 1, the internal reference gene expression was considered unstable. Finally, comprehensive ranking orders of these internal reference genes based on the three methods were recommended as described above (Zhang et al., 2020), and the most stable internal reference gene was determined according to the ranking orders.

3 RESULT 3.1 Quality of qRT-PCR amplification

Six examined internal reference genes were amplified by traditional PCR and detected by agarose gel electrophoresis. The amplification results showed that the amplified primers of each internal reference gene are specific and product is from 100 to 300 bp (Fig. 1). The melting curve analysis showed that each examined internal reference gene has only one single peak in the melting curves. The PCR efficiency (E) and determination coefficients (R2) were assessed by the slopes of the standard curves. The results showed that the E values were from 92% to 101%, and the R2 values ranged from 0.993 to 0.997 (Table 1).

Fig.1 The RT-PCR amplification of the six candidate internal reference genes of humpback grouper
3.2 Expression levels of the internal reference genes in humpback grouper before the pathogen challenge

The expression levels of six internal reference genes under normal conditions were detected by qRT-PCR. The results showed that the Ct values of the six internal reference genes were different in all the five examined tissues. The lowest mean Ct value (14.6) was in Actin of kidney, while the highest (30.1) was in TTLL1 of liver (Table 2). In different tissues, Actin showed the highest expression levels, with Ct values ranged from 14.6 to 18.6. EF1A, RPL13, GAPDH, B2M, and TTLL1 showed comparable Ct values (16.2 to 20.5, 16.9 to 19.6, 17.0 to 29.0, 18.6 to 20.7, and 24.7 to 30.1, respectively).

Table 2 The Ct values of the internal reference genes in different tissues of humpback grouper after the pathogen challenge
3.3 Expression levels of the internal reference genes in humpback grouper tissues after pathogen infection

Following V. harveyi and VNNV infection, the expressions of the six internal reference genes presented tissue-dependent manners (Table 2). In addition, the transcript abundances of all the genes were altered in various tissues. At 9-h post-infection by V. harveyi, the maximum (8.5) Ct variation value was observed in GAPDH in kidney, compared with the control group. Actin, EF1A, and RPL13 showed the least changes (Ct variations from 0.1 to 0.9, less than 1) in kidney and intestine, while all other genes exhibited Ct variations from 1 to 8.5. Moreover, GAPDH, TTLL1, and EF1A exhibited the least changes (no more than 1) in liver. In gill, Actin, B2M, and TTLL1 exhibited the least changes (less than 1), and GAPDH exhibited the highest Ct variation of 3.2. In spleen, Ct variations of all other genes exhibited greater than 1, and GAPDH exhibited the highest Ct variation of 7.4.

Following stimulation with VNNV, the GAPDH had maximum Ct variation values (10.7) between kidney and spleen (Table 2). In kidney, the maximum Ct variation of 9.9 was presented in GAPDH, compared with the control group. There were slightly differences of Ct variation observed with the RPL13 in intestine (2.2), the EF1A in liver (2.8), the Actin in liver (2.0), the B2M in intestine (5.7), the TTLL1 in intestine (6.1).

3.4 Gene expression stability in humpback grouper tissues before pathogen infection

To evaluate the gene expression stability, geNorm and NormFinder algorithms were used. geNorm analysis revealed that B2M and RPL13 were the most stable genes with the lowest M value, followed by Actin, EF1A, TTLL1, and GAPDH (Fig. 2). Similarly, the results of NormFinder analysis revealed that RPL13 were the most stable gene (0.374), followed by B2M (0.454), EF1A (1.279), Actin (1.324), TTLL1 (1.514), and GAPDH (3.853) (Table 3). According to the result of BestKeeper (Table 4), the rank of the candidate reference genes from most to least stable was: B2M > RPL13 > Actin > EF1A > TTLL1 > GAPDH. However, the SD value of Actin, EF1A, TTLL1, and GAPDH were bigger than 1, indicating these four internal reference genes were unstable. The results obtained by three methods were similar with slight differences. Finally, the comprehensive gene stability ranking order is shown in Table 5, indicating that RPL13 was identified as the most stable gene among five different immune organs under normal physiological condition.

Fig.2 The geNorm analysis of internal reference genes expression in humpback grouper tissues under normal physiological condition The expressions of the internal reference genes in humpback grouper tissues were determined by qRT-PCR, and the expression stability (M) of the genes were analyzed with geNorm.
Table 3 The expression stability of the candidate reference genes in various tissues of humpback grouper were analyzed by NormFinder under normal physiological condition
Table 4 The expression stability of the candidate reference genes in various tissues of humpback grouper were analyzed by BestKeeper under normal physiological condition
Table 5 The recommended comprehensive ranking order
3.5 Gene expression stability in humpback grouper tissues after V. harveyi infection

According to the Ct values of the internal reference genes from fish infected with V. harveyi and fish injected PBS (control), the analysis of geNorm results showed that the highest M values of the candidate genes were varied between 0.7 to 1.2 in all examined tissues, except GAPDH, which was exhibited the M value with 1.62 in kidney (Fig. 3). Moreover, Actin/RPL13 were indicated as the most stable pairs of internal reference genes in liver with the minimum M value (0.042), followed by EF1A (0.263), TTLL1 (0.345), GAPDH (0.521), and B2M (0.781) (Fig. 3d). In gill, intestine, kidney, and spleen, EF1A/TTLL1, EF1A/RPL13, Actin/EF1A, and EF1A/RPL13 were the most stable pairs of genes with the lowest M values, respectively (Fig. 3a, b, c, e). Take into account the minimum number of internal reference genes required, the V2/3 values were 0.125, 0.122, 0.083, 0.069, and 0.030 in liver, spleen, kidney, intestine, and gill, respectively, which were all less than 0.15 (Fig. 4), indicating geometric averaging of 2 genes in five tissues above after V. harveyi infection would be required for accurate normalization and the most stable genes in these tested tissues generated by geNorm are reliable and effective. To verify the ranking orders of gene expression stability, NormFinder algorithm was performed. As shown in Table 6, Actin/RPL13, RPL13, EF1A, GAPDH, and EF1A/TTLL1 appeared as the most stable genes in liver, spleen, kidney, intestine, and gill, respectively. When assessed by BestKeeper, the least overall variation was GAPDH (SD=0.45), B2M (SD=1.12), EF1A (SD=0.71), RPL13 (SD=0.32), and B2M (SD=0.82) in liver, spleen, kidney, intestine, and gill, respectively, which were classified as the best candidates (Table 7), except B2M (SD > 1) in spleen was unstable. Combined analysis of three algorithms showed that under V. harveyi stimulation, RPL13, RPL13, EF1A, RPL13, and EF1A as the stable internal reference genes in liver, spleen, kidney, intestine, and gill, respectively (Table 8). Particularly, the results of comprehensive analysis were entirely consistent with those of geNorm, and only slight different with that of NormFinder.

Fig.3 Internal reference genes expression stability in humpback grouper tissues confirmed by geNorm after 9-h post-infection Gene expression of humpback grouper tissues after challenged by PBS or Vibrio harveyi at 9-h post-infection was determined by qRT-PCR, and the expression stability (M) of the genes were analyzed with geNorm.
Fig.4 Determination of the optimal number of internal reference genes by geNorm for normalization after bacterial infection The pairwise variation between normalization factors of the internal reference genes in humpback grouper tissues were analyzed by geNorm after challenged by PBS or Vibrio harveyi.
Table 6 The expression stability of the candidate reference genes in humpback grouper tissues were analyzed by NormFinder after 9-h V. harveyi infection
Table 7 The expression stability of the candidate reference genes in humpback grouper tissues were analyzed by BestKeeper after 9-h V. harveyi infection
Table 8 The recommended comprehensive ranking order
3.6 Gene expression stability in humpback grouper tissues after VNNV infection

Compared the Ct values of the internal reference genes between fish infected with VNNV and fish injected PBS (control), geNorm analysis showed that Actin/GAPDH, GAPDH/RPL13, EF1A/RPL13, Actin/EF1A, TTLL1/RPL13 were the most stable pair of genes in gill, liver, spleen, kidney, and intestine, (0.183) respectively (Fig. 5). The further pairwise variation (V) was determined, which make sure the optimal number of genes required for data normalization. Analysis of Vn/n+1 in geNorm demonstrated that the V2/3 variations in gill, liver, spleen, kidney, and intestine were all lower than 0.15, with the lowest V2/3 value of 0.020 (spleen) and the maximum V2/3 value of 0.127 (gill) (Fig. 6), suggesting that the inclusion of the third reference gene in each case was not necessary. NormFinder analysis showed that the rankings of the most stable gene pairs were GAPDH/Actin, GAPDH/RPL13, EF1A/RPL13, RPL13, and TTL1/RPL13 in gill, liver, spleen, kidney, and intestine, respectively, which were broadly similar to the corresponding geNorm output (except for RPL13 in kidney) (Table 9). Analyzed by BestKeeper, RPL13, TTLL1, Actin, EF1A, and TTLL1 were classified as the best candidates in liver, spleen, kidney, intestine, and gill, respectively (Table 10). According to geNorm, NormFinder, and BestKeeper, the most stable genes were found to be RPL13, EF1A, Actin, RPL13, and Actin in liver, spleen, kidney, intestine, and gill, respectively (Table 11).

Fig.5 Internal reference genes expression stability in humpback grouper tissues confirmed by geNorm at 5 day post-infection Gene expression of humpback grouper tissues after challenged by PBS or viral nervous necrosis virus at 5 day post-infection was determined by qRT-PCR, and the expression stability (M) of the genes were analyzed with geNorm.
Fig.6 Determination of the optimal number of reference genes by geNorm for normalization after virus infection The pairwise variation between normalization factors of the internal reference genes in various tissues of humpback grouper were analyzed by geNorm after challenged by PBS or viral nervous necrosis virus.
Table 9 The expression stability of the candidate reference genes in humpback grouper tissues were analyzed by NormFinder after 5-d viral nervous necrosis virus infection
Table 10 The expression stability of the candidate reference genes in humpback grouper tissues were analyzed by BestKeeper after 5-d viral nervous necrosis virus infection
Table 11 The recommended comprehensive ranking order
4 DISCUSSION

Quantitative real-time PCR has become one of the most commonly used techniques in the field of molecular biology. However, many studies showed that the commonly used reference genes could not be expressed stably in many species, tissues, and experimental conditions (Czechowski et al., 2005; Luo et al., 2014; Chen et al., 2017). Erroneous normalization of the PCR data and consequently misinterpretation of the results were present if reference genes were inappropriate (McCurley and Callard, 2008). Therefore, it is necessary to confirm appropriate reference genes for specific experimental conditions to accurate profiling of gene expression. geNorm and NormFinder are common statistical software that used to pick out the best candidate genes for qRT-PCR (Andersen et al., 2004; Chen et al., 2017). The present study identified the most suitable internal reference genes from six commonly used reference genes (including B2M, Actin, TTLL1, RPL13, EF1A, and GAPDH) in five immune organs (i.e. gill, liver, spleen, kidney, and intestine) under normal physiological conditions or stimulated with V. harveyi and VNNV infection through geNorm and NormFinder. The optimum reference genes identified in this study will provide a useful guidance for the selection of internal controls in future qRT-PCR study of gene expression in C. altivelis.

In our study, six tested genes exhibited varied degrees of expressional changes in different tissues, while RPL13 was the most stable internal control genes across different tissue types. Similar investigators have been performed in other fish. For example, in zebrafish (Danio rerio), 18S rRNA and B2M are the most stably expressed in various tissues (McCurley and Callard, 2008), while in turbot (Scophthalmus maximus), RPSD and RPL17 are the most stable genes across tissue types (Dang and Sun, 2011). The difference of the most stable internal reference genes may be explained by the certain physiological differences and different gene expression patterns existing in different fish species.

Many studies suggested that internal reference genes exhibited a tissue-specific expression trend following bacterial infections (Olsvik et al., 2008; Small et al., 2008; Øvergård et al., 2010). As shown by increasing numbers of studies, tissue type has a strong effect on the determination of the optimal internal reference gene for qRT-PCR analysis of gene expression under bacterial infection (Dang and Sun, 2011; Zheng and Sun, 2011; Zhang et al., 2014). For instance, in turbot infected with Edwardsiella tarda, ACTB (beta actin) was detected as the most stable gene in liver, kidney, spleen, and gill. Meanwhile, ACTB was the least stable gene in brain and the second least stable gene in heart and muscle at 12-h post-infection (Dang and Sun, 2011). Following E. tarda infection, GAPDH is known to be most stable internal reference gene in three tissues (gill, liver, and intestine) of Japanese flounder Paralichthys olivaceus, while in contrast, GAPDH appeared to be the least stable gene in brain and muscle (Zheng and Sun, 2011). In our study, 9 h after V. harveyi infection, TTLL1 was identified as the most stable gene in gill but the least stable gene in spleen analyzed by geNorm and NormFinder. Moreover, by geNorm analysis, Actin/RPL13, EF1A/RPL13, Actin/EF1A, and EF1A/RPL13 were the most stable gene pairs in liver, spleen, kidney, and intestine, respectively. In line with the results generated by geNorm in liver and gill, the same optimal gene pairs were obtained with NormFinder. In addition, only one stable gene was identified in spleen (RPL13), kidney (EF1A), and intestine (GAPDH) through NormFinder. However, the least overall variation genes identified by BestKeeper were GAPDH, B2M, EF1A, RPL13, and B2M in liver, spleen, kidney, intestine, and gill. The large difference between BestKeeper with geNorm and NormFinder analyses might be explained by the different methods of computation, which Ct values was transformed the relative quantities for geNorm and NormFinder analyses, while Ct values directly used in BestKeeper analysis. Similar observations were reported in many studies (Fernandes et al., 2008; Wang et al., 2012). To improve the accuracy of evaluation, a comprehensive ranking order of each reference gene was performed based on the results from the three algorithms, suggesting that the most stable genes in liver, spleen, kidney, intestine, and gill at 9-h post-infection of V. harveyi were RPL13, RPL13, EF1A, RPL13, and EF1A, respectively.

VNNV is also a common pathogenic pathogen in the grouper (Asim et al., 2019). In our study, as observed with V. harveyi infection, similar results were observed after VNNV stimulation, which showed that the variations in the expression stability of the internal reference genes depended on tissue type variations. However, the most stable internal reference genes identified in most tissues were different between V. harveyi stimulation and VNNV stimulation. The results of geNorm analysis showed that, in liver, spleen, kidney, intestine, and gill, the most stable gene pairs were GAPDH/RPL13, EF1A/RPL13, Actin/EF1A, TTLL1/RPL13, and Actin/GAPDH, respectively. Since five examined tissues exhibited the V2/3 values less than 0.15, two genes sufficed as normalization factors for each of these tissues. NormFinder analysis showed that, except for RPL13 in kidney, the rankings of the most stable gene pairs in other four organs were identical to those predicted by geNorm. In BestKeeper, only RPL13 and Actin identified respectively as the least variable genes in liver and kidney were agreement with geNorm and NormFinder. In summary, the calculated comprehensive ranking order with the help of geNorm, NormFinder, and BestKeeper showed the same most stable internal reference genes compared with geNorm analysis. Consistent with previous study, our results presented similar trend, showing more comparable results between the comprehensive ranking order and the ranking by geNorm analysis (Wang et al., 2012).

5 CONCLUSION

In this study, RPL13 was identified as the most stable internal control gene among five different organs of C. altivelis under normal physiological conditions. When studying the gene expression profiles after bacteria and virus infections in C. altivelis, the most stable internal reference gene is detected in liver, spleen, kidney, intestine, and gill. Following V. harveyi challenge, the most stable genes identified by geNorm, NormFinder, and BestKeeper together were RPL13, RPL13, EF1A, RPL13, and EF1A in liver, spleen, kidney, intestine, and gill of C. altivelis, respectively. Under VNNV challenge, the most stable genes were found to be RPL13, EF1A, Actin, RPL13, and Actin in liver, spleen, kidney, intestine, and gill of C. altivelis, respectively. Taken together, these results highlight the characteristic of tissue-dependent variations in the expression of so-called internal reference genes, suggest tissue type has to be considered when selecting the reference genes in qRT-PCR analysis, and provide guidance for qRT-PCR studies of gene expression in C. altivelis.

6 DATA AVAILABILITY STATEMENT

The authors declare that all data supporting the findings of this study is available within the article.

References
Andersen C L, Jensen J L, Ørntoft T F. 2004. Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Research, 64(15): 5 245-5 250. DOI:10.1158/0008-5472.CAN-04-0496
Asim M, Babu V S, Qin Z D, Zhao L J, Su J G, Li J, Tu J G, Kou H Y, Lin L. 2019. Inhibition of Cyclophilin A on the replication of red spotted grouper nervous necrosis virus associates with multiple pro-inflammatory factors. Fish & Shellfish Immunology, 92: 172-180. DOI:10.1016/j.fsi.2019.05.064
Chen H, Cai X Y, Yu X W. 2018. Main diseases and control of grouper. Livestock and Poultry Industry, 29(1): 9-11. DOI:10.19567/j.cnki.1008-0414.2018.01.005
Chen X J, Zhang X Q, Huang S, Cao Z J, Qin Q W, Hu W T, Sun Y, Zhou Y C. 2017. Selection of reference genes for quantitative real-time RT-PCR on gene expression in Golden Pompano (Trachinotus ovatus). Polish Journal of Veterinary Sciences, 20(3): 583-594. DOI:10.1515/pjvs-2017-0071
Craig M T, Sadovy de Mitcheson Y J, Heemstra P C. 2011. Groupers of the World: A Field and Market Guide. National Inquiry Services Centre, Gland, Switzerland.
Czechowski T, Stitt M, Altmann T, Udvardi M K, Scheible W R. 2005. Genome-wide identification and testing of superior reference genes for transcript normalization in Arabidopsis. Plant Physiology, 139(1): 5-17. DOI:10.1104/pp.105.063743
Dang W, Sun L. 2011. Determination of internal controls for quantitative real time RT-PCR analysis of the effect of Edwardsiella tarda infection on gene expression in turbot (Scophthalmus maximus). Fish & Shellfish Immunology, 30(2): 720-728. DOI:10.1016/j.fsi.2010.12.028
Dobnik D, Spilsberg B, Košir A B, Holst-Jensen A, Žel J. 2015. Multiplex quantification of 12 European Union authorized genetically modified maize lines with droplet digital polymerase chain reaction. Analytical Chemistry, 87(16): 8 218-8 226. DOI:10.1021/acs.analchem.5b01208
Fernandes J M O, Mommens M, Hagen Ø, Babiak I, Solberg C. 2008. Selection of suitable reference genes for real-time PCR studies of Atlantic halibut development. Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology, 150(1): 23-32. DOI:10.1016/j.cbpb.2008.01.003
Filby A L, Tyler C R. 2007. Appropriate 'housekeeping' genes for use in expression profiling the effects of environmental estrogens in fish. BMC Molecular Biology, 8: 10. DOI:10.1186/1471-2199-8-10
Huggett J, Dheda K, Bustin S, Zumla A. 2005. Real-time RT-PCR normalisation; strategies and considerations. Genes & Immunity, 6(4): 279-284. DOI:10.1038/sj.gene.6364190
Jain M, Nijhawan A, Tyagi A K, Khurana J P. 2006. Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR. Biochemical and Biophysical Research Communications, 345(2): 646-651. DOI:10.1016/j.bbrc.2006.04.140
Kang I N, Lee C Y, Tan S C. 2019. Selection of best reference genes for qRT-PCR analysis of human neural stem cells preconditioned with hypoxia or baicalein-enriched fraction extracted from Oroxylum indicum medicinal plant. Heliyon, 5(7): e02156. DOI:10.1016/j.heliyon.2019.e02156
Li H H, Hou X M. 2015. Real-time fluorescent quantitative PCR and its application in pathogen detection. Occupation and Health, 31(18): 2 586-2 589. (in Chinese with English abstract) DOI:10.13329/j.cnki.zyyjk.2015.0893
Li W Z, Liu L, Zhang H, Xiao Q. 2019. Applications of PCR technology in diseases diagnosis in aquaculture animals. Fisheries Science, 38(5): 726-733. DOI:10.16378/j.cnki.1003-1111.2019.05.021
Luo H L, Luo K C, Luo L P, Li E X, Guan B C, Xiong D J, Sun B T, Peng K, Yang B Y. 2014. Evaluation of candidate reference genes for gene expression studies in Cymbidium kanran. Scientia Horticulturae, 167: 43-48. DOI:10.1016/j.scienta.2013.12.030
Luo M, Chen F X, Liu L L, Li W D, Zeng G Q, Tan W, Li X M. 2013. Progress in disease research of grouper aquaculture in China. Fisheries Science, 32(9): 549-554. DOI:10.3969/j.issn.1003-1111.2013.09.010
Mahoney D J, Carey K, Fu M H, Snow R, Cameron-Smith D, Parise G, Tarnopolsky M A. 2004. Real-time RT-PCR analysis of housekeeping genes in human skeletal muscle following acute exercise. Physiological Genomics, 18(2): 226-231. DOI:10.1152/physiolgenomics.00067.2004
McCurley A T, Callard G V. 2008. Characterization of housekeeping genes in zebrafish: male-female differences and effects of tissue type, developmental stage and chemical treatment. BMC Molecular Biology, 9: 102. DOI:10.1186/1471-2199-9-102
Najafpanah M J, Sadeghi M, Bakhtiarizadeh M R. 2013. Reference genes selection for quantitative real-time PCR using RankAggreg method in different tissues of Capra hircus. PLoS One, 8(12): e83041. DOI:10.1371/journal.pone.0083041
Olsvik P A, Søfteland L, Lie K K. 2008. Selection of reference genes for qRT-PCR examination of wild populations of Atlantic cod Gadus morhua. BMC Research Notes, 1(1): 47. DOI:10.1186/1756-0500-4-456
Ou Y J, Liu J H, Li J E, Wu S Q, Xie M J. 2015. Morphology and histology of head-kidney and spleen in Cromileptes altivelis. Journal of Southern Agriculture, 46(11): 2 034-2 039. (in Chinese with English abstract) DOI:10.3969/j:issn.2095-1191.2015.11.2034
Øvergård A C, Nerland A H, Patel S. 2010. Evaluation of potential reference genes for real time RT-PCR studies in Atlantic halibut (Hippoglossus hippoglossus L.); during development, in tissues of healthy and NNV-injected fish, and in anterior kidney leucocytes. BMC Molecular Biology, 11: 36. DOI:10.1186/1471-2199-11-36
Pfaffl M W, Tichopad A, Prgomet C, Neuvians T P. 2004. Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: bestkeeper-excel-based tool using pairwise correlations. Biotechnology Letters, 26(6): 509-515. DOI:10.1023/b:bile.0000019559.84305.47
Pooljun C, Direkbusarakom S, Chotipuntu P, Hirono I, Wuthisuthimethavee S. 2016. Development of a TaqMan real-time RT-PCR assay for detection of Covert mortality nodavirus (CMNV) in penaeid shrimp. Aquaculture, 464: 445-450. DOI:10.1016/j.aquaculture.2016.06.044
Resende M V, Lucio A C, Perini A P, Oliveira L Z, Almeida A O, Alves B C A, Moreira-Filho C A, Santos I W, Hossepian de Lima V F M. 2011. Comparative validation using quantitative real-time PCR (qPCR) and conventional PCR of bovine semen centrifuged in continuous density gradient. Arquivo Brasileiro de Medicina Veterinária e Zootecnia, 63(3): 544-551.
Small B C, Murdock C A, Bilodeau-Bourgeois A L, Peterson B C, Waldbieser G C. 2008. Stability of reference genes for real-time PCR analyses in channel catfish (Ictalurus punctatus) tissues under varying physiological conditions. Comparative Biochemistry and Physiology Part B: Biochemistry and Molecular Biology, 151(3): 296-304. DOI:10.1016/j.cbpb.2008.07.010
Sun Y, He M W, Cao Z J, Xie Z Y, Liu C S, Wang S F, Guo W L, Zhang X, Zhou Y C. 2018. Effects of dietary administration of Lactococcus lactis HNL12 on growth, innate immune response, and disease resistance of humpback grouper (Cromileptes altivelis). Fish & Shellfish Immunology, 82: 296-303. DOI:10.1016/j.fsi.2018.08.039
Sun Y, Sun L. 2015. CsBAFF, a teleost B cell activating factor, promotes pathogen-induced innate immunity and vaccine-induced adaptive immunity. PLoS One, 10(8): e0136015. DOI:10.1371/journal.pone.0136015
Sun Y, Xiang Y J, He M W, Zhang X, Wang S F, Guo W L, Liu C S, Cao Z J, Zhou Y C. 2019. Evaluation of Lactococcus lactis HNL12 combined with Schizochytrium limacinum algal meal in diets for humpback grouper (Cromileptes altivelis). Fish & Shellfish Immunology, 94: 880-888. DOI:10.1016/j.fsi.2019.09.059
Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F. 2002. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biology, 3(7): research0034.1. DOI:10.1186/gb-2002-3-7-research0034
Wan Y L, Hong A Y, Zhang Y X, Liu Y. 2019. Selection and validation of reference genes of Paeonia lactiflora in growth development and light stress. Physiology and Molecular Biology of Plants, 25(4): 1 097-1 105. DOI:10.1007/s12298-019-00684-2
Wang Q, Ishikawa T, Michiue T, Zhu B L, Guan D W, Maeda H. 2012. Stability of endogenous reference genes in postmortem human brains for normalization of quantitative real-time PCR data: comprehensive evaluation using geNorm, NormFinder, and BestKeeper. International Journal of Legal Medicine, 126(6): 943-952. DOI:10.1007/s00414-012-0774-7
Yang Y W, Chen M K, Yang B Y, Huang X J, Zhang X R, He L Q, Zhang J, Hua Z C. 2015. Use of 16S rRNA gene-targeted group-specific primers for real-time PCR analysis of predominant bacteria in mouse feces. Applied and Environmental Microbiology, 81(19): 6 749-6 756. DOI:10.1128/AEM.01906-15
Zhang B C, Sun L, Xiao Z Z, Hu Y H. 2014. Quantitative real time RT-PCR study of pathogen-induced gene expression in rock bream (Oplegnathus fasciatus): internal controls for data normalization. Marine Genomics, 15: 75-84. DOI:10.1016/j.margen.2014.03.001
Zhang M, Xing Y Z, Zhen Y, Mi T Z, Yu Z G. 2020. Screening of the reference genes of Skeletonema marinoi under different concentration of Fe3+ conditions in real-time quantitative PCR analysis. Haiyang Xuebao, 42(2): 124-133. (in Chinese with English abstract) DOI:10.3969/j.issn.0253-4193.2020.02.013
Zheng W J, Sun L. 2011. Evaluation of housekeeping genes as references for quantitative real time RT-PCR analysis of gene expression in Japanese flounder (Paralichthys olivaceus). Fish & Shellfish Immunology, 30(2): 638-645. DOI:10.1016/j.fsi.2010.12.014