Introduction
Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) has become a cornerstone technique in molecular biology for quantifying gene expression levels, due to its rapidity, affordability, and ease of operation (Huggett et al., Reference Huggett, Dheda, Bustin and Zumla2005). The accuracy of RT-qPCR relies on using stable reference genes for normalisation, which is a prerequisite that ensures the reliability of comparative gene expression analyses across different samples and experimental conditions (Bustin et al., Reference Bustin, Benes, Garson, Hellemans, Huggett, Kubista, Mueller, Nolan, Pfaffl, Shipley, Vandesompele and Wittwer2009). Housekeeping genes, such as ACT, GAPDH, and Tubulin, encode proteins that are essential for maintaining basic cellular functions. These genes are commonly used as reference genes because of their stable and consistent expression across various physiological states (Derveaux et al., Reference Derveaux, Vandesompele and Hellemans2010). Yet, none of the reference genes are universal in all situations or across all species (Dheda et al., Reference Dheda, Huggett, Chang, Kim, Bustin, Johnson, Rook and Zumla2005). Therefore, the selection of suitable reference genes is indispensable for gene expression studies of organisms of interest.
Reference genes have been characterised in a few species of parasitoids. For example, RPL13 and EF1α regarding varying body tissues are identified in Anastatus japonicus (Eupelmidae), 18S and EF1α regarding different life stages in Tamarixia radiata (Eulophidae), 18S, H3, and AK regarding low temperatures in Cotesia chilonis (Braconidae), and ZFP268 and EF2 regarding diets in Trichogramma chilonis (Trichogrammatide) (Li et al., Reference Li, Li, Lu, Cao and Du2019; Guo et al., Reference Guo, Pan, Zhang, Ou, Lu, Khan and Qiu2020; Xie et al., Reference Xie, Tian, Lu, Xu, Zang, Lu and Jin2021; Liu et al., Reference Liu, Xiao, Xia, Wu, Zhao and Li2022). These factors considered for identifying reference genes are fundamental and crucial. A consideration of more factors of interest to characterise more reference genes can validate gene expression levels with higher accuracy (Lü et al., Reference Lü, Yang, Zhang and Pan2018).
Sclerodermus wasps (Hymenoptera: Bethylidae) provide ideal model systems for theoretical studies of social evolution in Hymenoptera due to their unique social behaviour among parasitoid insects. In this group of parasitoids, females share a single host and tend their communal brood (Tang et al., Reference Tang, Meng, Kapranas, Xu, Hardy and Li2014), exhibiting cooperative behaviour among females that aligns with the concept of quasi-sociality as defined by Wilson (Wilson, Reference Wilson1974). Sclerodermus parasitoids have long been applied as biocontrol agents in augmentation biological control programmes targeting wood-boring pest beetles on trees in the Chinese mainland (Yang et al., Reference Yang, Wang and Zhang2014). The ever-changing advances in molecular biology offer a novel and inspirational approach to gaining insights into the social evolution and biocontrol potentials of organisms. Some molecular studies use 18S as a reference gene in S. guani (Liu et al., Reference Liu, Fan, Zhang, Wu and Zhu2017; Wu et al., Reference Wu, Huang, Zhao, Xu and Zhu2020). But its stability remains to be validated.
In this study, we selected ten candidate genes to characterise reference genes in S.guani, including ACT, EF1α, Hsc70, Hsp70, SRSF7, α-tubulin, RPL7A, 18S, 28S, and SOD1. The majority of the above are prevalent in insects (Lü et al., Reference Lü, Yang, Zhang and Pan2018), while SOD1 is used in other insect orders besides Hymenoptera and thus may warrant further examination (Bai et al., Reference Bai, Lü, Zeng, Jia, Lu, Zhu, Li, Cui and Luan2020; Yan et al., Reference Yan, Zhang, Xu, Wang and Yang2021; Shen et al., Reference Shen, Peng, Zhang, Zeng, Yu, Jin and Li2022). We considered a variety of factors during characterisation, including body site, life stage, hormones, diet, and temperature. Reference genes identified based on these biotic and abiotic factors can be widely applicable in molecular studies of this group of parasitoids. Four common algorithms (ΔCt, BestKeeper, NormFinder, and geNorm) and one comparative algorithm (RefFinder) were applied to analyse the stability and rank the reference genes based on quantitative data. The expression profile of ACPase was assessed regarding body parts to validate the results. The target gene Acid phosphatase (ACPase) is an enzyme that catalyses the hydrolysis of phosphate esters in an acidic environment and is considered a typical venom component in parasitoids (Anand and Srivastava, Reference Anand and Srivastava2012; Liu et al., Reference Liu, Fan, Zhang, Wu and Zhu2017).
Materials and methods
Insects rearing
The colony of S. guani was established in the insectary from start-up wasps offered by the Research Institute of Forestry Protection of Jiangsu Province, at Nanjing city, Jiangsu province, China. Tenebrio molitor (Coleoptera: Tenebrionidae) pupae were used as the host, which is a viable substitutive host for S. guani (Yang et al., Reference Yang, Wu, Wu, Yuan, Qin, Bao and Tian2018). They were reared in insectary at conditions of 27 ± 1°C in temperature, 60–70% in relative humidity, and 14L:10D in photoperiod.
Biotic factor treatment
Two biotic factors were considered in the identification: life stage and body part. The life stage included the 1st and 4th instar larvae, pupae, and male, and female adults. A group of 10 individuals were operated as one sample (replicate). The body part included the head, thorax, abdomen, antennae, and leg; varying numbers of individual parts were grouped as one sample (replicate): 60 for the head, 30 for the thorax or abdomen, and ca. 100 for antennae or legs. Three replicates were operated.
Abiotic factor treatment
Three abiotic factors were examined: diet, temperature, and hormone. The dietary treatment was imposed on adults at eclosion with three diets as supplementary food: the 20% sugar solution (soaked in a cotton line as the control), T. molitor pupae, and Monochamus alternatus larvae, and these diets were provided for different periods: 24 and 48 h. Each diet by period treatment was tested for 30 female wasps. Three levels of temperature were tested: 4, 27 and 35°C, respectively corresponding to the temperatures during the mass production for cold storage, rearing in insectary, and release in the field in summer. Sample insects were taken from the colony maintained at 27°C, then moved to chambers at different temperatures and maintained there for three hours for their acclimation before moving to subsequent procedures. The hormonal treatment included an injection of 0.04 μl ecdysone at 14, 64, or 120 pg μl−1 in methanol, or of juvenile hormone at 16, 32, or 64 pg μl−1 dissolved in acetone; the same volume of methanol or acetone were used as their controls. The injection was operated by inserting nanoliter syringe Nanoject III (Drummond Scientific) through the intersegment membrane of the wasp. After the injection, the wasp was placed in a glass tube for 24 h before the identification procedure. Each sample consisted of 30 wasps and was collected into a 1.5 ml microcentrifuge tube, which was immediately frozen in liquid nitrogen and then stored at −80°C for subsequent RNA extraction. Three replicates were examined.
Reference genes selection and primer design
Ten candidate genes were selected based on the S. guani transcriptomic data (unpublished), including ACT, EF1α, Hsc70, Hsp70, SRSF7, α-tubulin, RPL7A, 18S, 28S, and SOD1. Gene-specific primers were designed using NCBI Primer-BLAST (https://www.ncbi.nlm.nih.gov/tools/primer-blast/) (table 1).
Table 1. Features of candidate reference genes in Sclerodermus guani.
RNA extraction and cDNA synthesis
Total RNA was extracted using FreeZol Reagent (Vazyme, NanJing, China) following the manufacturer's protocol. RNA was eluted in 20 μl RNase-free water. RNA quantity was measured by a NanoDrop 2000c spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) with absorbance levels of 260 and 280 nm. An aliquot of 500 ng of total RNA was used to synthesise first-strand cDNA using the PrimeScript™ RT reagent Kit with the gDNA Eraser (Perfect Real Time) (Takara, Beijing, China). The cDNA was stored at – 20°C for later RT-qPCR experiments.
RT-qPCR analysis
The RT-qPCR was performed on 7500 and 7500 Fast Real-Time PCR Systems (Applied Biosystems, Life Technologies, Carlsbad, CA, USA) using Top Green qPCR SuperMix (+Dye I) (TransGen Biotech, Beijing, China). The reaction took place in 20 μl volume including 1.0 μl template cDNA and 10 μM of each primer, and the thermal cycling conditions were as follows: 94°C for 30 s, then 40 cycles of 94°C for 5 s and 60°C for 34 s. After amplification, a melting curve analysis was performed to establish specificity of the PCR product. Three technical replicates were performed for each sample. Standard curves were generated based on a 5-fold dilution series of cDNA templates. The amplification efficiency (E) was calculated based on the equation: E = (101/slope − 1) × 100%.
Data analysis
The Cq value (quantitative cyclic value) was used as a measure of expression levels of candidate reference genes. Expression stability of each candidate reference gene was calculated and ranked by methods of the GeNorm, NormFinder, BestKeeper, and ΔCt. The optimal number of reference genes was identified by the geNorm with pairwise variation Vn/Vn +1 analysis: when the Vn/Vn +1 value was below 0.15, n reference genes were sufficient for the reliable normalisation. Afterwards, RefFinder (https://blooge.cn/RefFinder/) was used to comprehensively evaluate, screen, and rank all candidate reference genes by integrating the aforementioned results to identify the most stable reference genes.
Validation of reference genes
The Acid phosphatase (ACPase) was used as the target gene for candidate reference gene evaluation. The primer sequence of the target gene was: forward (5′-ATGAGTTTCTGGGCGACATTTA-3′) and reverse (5′-TTCCATATTAGGTCCCCTTGTG-3′). The expression profile of ACPase in variable body parts was determined according to threshold cycle value (Ct) with the 2−ΔΔCt method. ANOVA and follow-up Tukey HSD test were applied to compare mean values of the expression. Statistical analyses were run with the R software (R Development Core Team, 2023).
Results
Primer specificity and amplification efficiencies
Primer specificity of all reference genes was evaluated by single amplicons and single peaks in melting curve analyses (fig. S1); the standard curves were generated based on a five-fold serial dilution of cDNA templates (fig. S2). The analysis results showed that the RT-qPCR efficiency ranged from 95.57% (RPL7A) to 102.68% (ACT), and regression coefficients ranged from 0.9958 for Hsc70 to 0.9998 for ACT and SOD1 (table 1).
Expression profiles of ten reference genes
The cyclic threshold (Cq), representing the expression level of candidate internal reference genes under different conditions, ranged from 7.34 (18S) to 34.73 (ACT). The 18S was the most abundant reference gene under all the conditions, while the least expressed reference gene varied from 26.84 (Hsp70) regarding the life stage, 25.50 (ACT) regarding the diet, 34.73 (ACT) regarding the hormone, 27.63 (Hsp70) regarding the body part, and 23.86 (α-tubulin) regarding the temperature. From a holistic perspective, expression fluctuations were greatest for the hormone treatment, while least for the temperature (fig. 1).
Figure 1. Cq values of reference genes regarding body part (a), life stage (b), diet (c), hormone (d), and temperature (e). The dots are outliers.
Gene expression regarding biotic factors
Results from analysing S. guani body parts using all four methods showed that SOD1 exhibited the lowest level of stability. RPL7A was most stable with the analysis by ΔCt and geNorm and 18S was so by NormFinder computations. The 28S, the most stable gene by BestKeeper, ranked 8th by the other algorithms (table 2). A comprehensive analysis by RefFinder yielded the rank in order of stability from high to low: RPL7A > EF1α > 18S > α-tubulin > SRSF7 > Hsc70 > 28S > Hsp70 > ACT > SOD1 (fig. 2a). According to the V 2/V 3 value of less than 0.15 as measured by geNorm (fig. 3), suggesting two most stable genes to be sufficient for the normalisation, the most reliable reference genes for normalising RT-qPCR data regarding body parts were RPL7A and EF1α in S. guani.
Table 2. Stability of ten reference genes measured by four algorithms regarding variable conditions.
Figure 2. Stability of reference genes regarding body part (a), life stage (b), diet (c), hormone (d), and temperature (e) according to analyses with RefFinder. A lower Geomean value indicates a more stable expression.
Figure 3. Values of pairwise variation (V) measured by geNorm regarding variable conditions.
Results from analysing S. guani life stages showed that though Hsp70 was ranked 9th by BestKeeper, it was rated as the least stable one by the other algorithms. While RPL7A was ranked 6th by BestKeeper, it was regarded as the most stable reference gene by ΔCt and geNorm. The genes of α-tubulin and SRSF7 were rated as the most stable reference genes by both BestKeeper and NormFinder (table 2). According to the ranking result by RefFinder, the reference genes were ranked in order of stability from high to low as SRSF7 > RPL7A > α-tubulin > Hsc70 > SOD1 > ACT > 18S > 28S > EF1α > Hsp70 (fig. 2b). The pairwise variation analysis displayed that the V 2/V 3 value was less than 0.15 (fig. 3). The overall results indicated that SRSF7 and RPL7A were the best reference genes to normalise gene expression across life stages.
Gene expression regarding abiotic factors
Regarding the diet, Hsp70 was the least stable gene by all the four algorithms, while Hsc70 was the most stable gene by ΔCt and NormFinder but RPL7A by BestKeeper and EF1α by geNorm were so (table 2). All ten candidate genes were ranked by RefFinder in order of stability from high to low as: SRSF7 > Hsc70 > EF1α > RPL7A > 18S > α-tubulin > 28S > SOD1 > ACT > Hsp70 (fig. 2c). Based on the V 2/V 3 value of less than 0.15 (fig. 3), the most reliable reference genes for the normalisation regarding the diet were SRSF7 and Hsc70.
Regarding the hormone, ACT was the least stable gene by the four algorithms. The a-tubulin was identified by ΔCt and NormFinder as the most stable reference gene, while RPL7A by geNorm and 28S by BestKeeper were identified as the most stable (table 2). The ten candidate reference genes were ranked by RefFinder in order of stability from high to low as: RPL7A > α-tubulin > SRSF7 > Hsc70 > EF1α > 28S > SOD1 > 18S > Hsp70 > ACT (fig. 2d). According the V 2/V 3 value of less than 0.15 (fig. 3), the most stable reference genes to normalise RT-qPCR data regarding the hormone were RPL7A and α-tubulin.
Concerning the temperature, 28S was the least stable gene by the four algorithms. The α-tubulin was suggested as the most stable reference gene by ΔCt and geNorm, while EF1α by BestKeepe and SRSF7 by NormFinder were suggested instead (table 2). The reference genes were ranked by RefFinder in order of stability from high to low as: SRSF7 > α-tubulin > EF1α > RPL7A > 18S > SOD1 > Hsc70 > Hsp70 > ACT > 28S (fig. 2e). According the V 2/V 3 value of less than 0.15 by geNorm (fig. 3), the most stably reference genes for normalisation regarding temperature were SRSF7 and α-tubulin.
Validation of reference genes
To validate the selected reference genes, we assessed the relative expression of ACPase. The expression level of ACPase was normalised using RPL7A and EF1α, which were the most stable reference genes, while SOD1 was the least stable. Their difference was determined by normalising ACPase expression regarding the life stage. ACPase expression level was highest in the abdomen while lowest in the leg (fig. 4). Yet, the expression mechanism behind normalisation by the most stable reference genes, RPL7A, EF1α, or their combination, was significantly different from that by the least stable reference gene, SOD1. Using the first three reference genes yielded ACPase expression levels in descendig order across body parts: abdomen > antenna = head = thorax > leg, which was almost in line with that using RPL7A except a slightly lower expression level by the later. However, the other reference genes normalised a different ACPase expression pattern: abdomen > thorax > head > antenna = leg, and the expression level was lower overall in body parts except the abdomen than that by other reference genes.
Figure 4. Expression levels of ACPase normalised with the two most stable and one least stable reference genes across body parts. Error bars represent standard error of the mean. Means sharing a lowercase letter are not significantly different by Tukey-adjusted mean separations (alpha = 0.05, two-tailed).
Discussion
To date, RT-qPCR is a common method of quantifying gene expression. Its high sensitivity and specificity, high speed and low cost, make it the touchstone for nucleic acid quantification (Huggett et al., Reference Huggett, Dheda, Bustin and Zumla2005). Reference genes, key to achieving expression accuracy, are crucial but easily neglected in the process of RT-qPCR (Vandesompele et al., Reference Vandesompele, De Preter, Pattyn, Poppe, Van Roy, De Paepe and Speleman2002; Bustin et al., Reference Bustin, Benes, Garson, Hellemans, Huggett, Kubista, Mueller, Nolan, Pfaffl, Shipley, Vandesompele and Wittwer2009; Guénin et al., Reference Guénin, Mauriat, Pelloux, van Wuytswinkel, Bellini and Gutierrez2009). Though a number of insects have bene identified for their reference genes, parasitoids, especially Bethylid wasps, are largely unknown for them (Lü et al., Reference Lü, Yang, Zhang and Pan2018; Shakeel et al., Reference Shakeel, Rodriguez, Tahir and Jin2018). In this study of a quasi-social parasitoid wasp S. guani (Hymenoptera: Bethylidae), we place the focus on 10 candidate genes, ACT, EF1α, Hsc70, Hsp70, SRSF7, α-tubulin, RPL7A, 18S, 28S, and SOD1, using four commonly used algorithms (ΔCt, BestKeeper, NormFinder, and geNorm) and a comprehensive program (RefFinder). Most of above candidate reference genes are well studied and used frequently (Lü et al., Reference Lü, Yang, Zhang and Pan2018).
Among the ten candidate reference genes examined in this study, ACT was ranked penultimate in terms of stability concerning factors such as body part, hormone, and diet, and last for temperature. However, caution is warranted regarding this result due to the abrupt imposition of temperature changes. Furthermore, introducing ACT in hormone injections leads to a marked increase of the pairwise variation value (V 9/V 10). Actins are abundant and essential components of the cytoskeleton, playing critical roles in a wide range of cellular processes such as cell migration, cell division, immune response, and gene expression (Hunter and Garrels, Reference Hunter and Garrels1977; Bunnell et al., Reference Bunnell, Burbach, Shimizu and Ervasti2011). Owing to its highly conserved properties, ACT is often used as a reference gene in vertebrates and insects (Chapman and Waldenström, Reference Chapman and Waldenström2015; Lü et al., Reference Lü, Yang, Zhang and Pan2018; Shakeel et al., Reference Shakeel, Rodriguez, Tahir and Jin2018). But it has long been treated with scepticism ever since its application (Selvey et al., Reference Selvey, Thompson, Matthaei, Lea, Irving and Griffiths2001; Ruan and Lai, Reference Ruan and Lai2007). Previous studies suggest the exclusion of ACT in some cases as a reliable reference gene due to its high variability in Hymenoptera (Cheng et al., Reference Cheng, Zhang, He and Liang2013; Gao et al., Reference Gao, Zhang, Luo, Wang, Lu, Zhang, Zhu, Wang, Lu and Cui2017). The evidence from our study does not provide support of ACT as a reliable reference gene.
Ribosomal protein genes exhibit robust expression levels in various cell types and play a crucial role in facilitating ribosome synthesis (Petibon et al., Reference Petibon, Ghulam, Catala and Abou Elela2021). For example, RP genes are applied as a reference gene in Anastatus japonicus, Trichogramma dendrolimi, Tamarixia radiate, and T. chilonis (Guo et al., Reference Guo, Pan, Zhang, Ou, Lu, Khan and Qiu2020; Xie et al., Reference Xie, Tian, Lu, Xu, Zang, Lu and Jin2021; Huo et al., Reference Huo, Bai, Che, Ning, Lü, Zhang, Zhou and Dong2022; Liu et al., Reference Liu, Xiao, Xia, Wu, Zhao and Li2022). Our study informs that RPL7A is one of the most stable reference genes based on its ranking first regarding both body part and hormone and second regarding temperature.
The stability of two rarely documented reference genes, SRSF7 and SOD1, varied greatly in this experiment. Serine/arginine-rich (SR) proteins mediate splice site recognition and splice complex assembly during variable splicing procedures (Tang et al., Reference Tang, Xie, Huang, Zhang, Jiang, Li and Bian2022). Surprisingly, SRSF7 exhibited high stability across different diets, life stages and temperature conditions. Previously, the stability of SRSF7 as a reference gene was only demonstrated in Trichoderma japonicum (Wang et al., Reference Wang, Tian, Lu, Xu, Wang and Lü2022). Our results from this study definitely provide a new argument for the reliability of SRSF as a reference gene. Superoxide dismutase (SOD) is an essential antioxidant enzyme, whose stability as a reference gene has been investigated in some insects (Bai et al., Reference Bai, Lü, Zeng, Jia, Lu, Zhu, Li, Cui and Luan2020; Yan et al., Reference Yan, Zhang, Xu, Wang and Yang2021; Shen et al., Reference Shen, Peng, Zhang, Zeng, Yu, Jin and Li2022). Although the results of our study suggest that SOD1 is not suitable as a reference gene for S. guani, its applicability in other parasitoid wasps remains further investigations.
Validation of expression stability is required for suitable reference genes generated by the algorithms. Acid phosphatase (ACPase) is stably expressed as a component in the venom gland in the abdomen of S. guani, making it ideal for accurately verifying the relative expression of reference genes (Liu et al., Reference Liu, Fan, Zhang, Wu and Zhu2017). Our findings from this study showed that the expression level of ACPase was significantly higher in the abdomen than in the other body parts. Furthermore, the expression level and mechanism of ACPase after normalisation with SOD1 significantly varied across RPL7A, EF1α, and their combination, suggesting that the normalised result based on SOD1 may not be representative of the expression level of ACPase. Hence, a combination of RPL7A and EF1α can be employed as effective reference genes in analysing the expression level of target genes regarding body parts in S. guani.
In summary, the results from this study suggest for the first time an extensive list of suitable reference genes regarding multiple potential factors for gene expression studies in S. guani. The results indicate that two reference genes for normalisation were optimal under all the conditions, and the recommended combinations were suggested: RPL7A and EF1α for different body parts, SRSF7 and Hsc70 for various diets, RPL7A and α-tubulin for hormone injections, SRSF7 and RPL7A for varying life stages, and SRSF7 and α-tubulin for different temperatures. Our findings are informative for future research of molecular biology in S. guani.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0007485324000427.
Acknowledgements
We thank Chenhui Shen and Jing Lü (Nanjing Agricultural University) for conducting the algorithm analyses. This work was supported by Postgraduate Research &Practice Innovation Program of Jiangsu Province (KYCX22_0769) awarded to R. Zhao and by the National Key R&D Program of China (2017YFD0201000) awarded to L. M.
Author contributions
R. Z. and B. L. conceived the study and wrote the manuscript; R. Z., X. G., and L. M. took part in the experiments.
Competing interests
None.
