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. 2022 Aug 30;13(9):784. doi: 10.3390/insects13090784

Identification and Validation of Reference Genes for Expression Analysis Using qRT-PCR in Cimex hemipterus (Hemiptera: Cimicidae)

Delong Kong 1,2,3, Daxia Shi 1,2,3, Changlu Wang 4, Ruyue Zhai 1,2,3, Lingling Lyu 5, Yurong He 1,2,3,*, Desen Wang 1,2,3,*
Editor: Kostas Iatrou
PMCID: PMC9502763  PMID: 36135485

Abstract

Simple Summary

Reference genes are the basis for exploring the function of target genes in insects. Recently, we identified a large number of chemoreceptor genes by transcriptome sequencing in different tissues of Cimex hemipterus (F.) (Hemiptera: Cimicidae). Additionally, we plan to study the expression patterns of these genes and clarify their functions. However, there is no report on the screening and application of the reference genes in C. hemipterus. In the present study, the expression-level stability of 10 candidate reference genes in C. hemipterus under various experimental conditions was evaluated through qRT-PCR combined with RefFinder (which integrates four computational programs: geNorm, NormFinder, BestKeeper, and ∆Ct). Results show that the optimal combination of reference genes for each experimental condition was as follows: RPL8 and EF1α for the developmental stage, RPL8 and RPS16 for adult sex, RPL8 and RPL11 for adult tissue, RPL8 and β-tubulin for gas stimulation, and RPL8 and NADH for temperature. The results will lay a foundation for the follow-up study on the expression and function of the target genes of tropical bed bugs.

Abstract

The tropical bed bug, Cimex hemipterus (F.) (Hemiptera: Cimicidae) is an important public-health pest that feeds on the blood of humans and some other animals. To explore the function of the target genes of C. hemipterus, it is essential to select suitable reference genes for the accurate quantification of gene expression. Here, we selected 10 frequently used reference genes in insects and evaluated their stability in C. hemipterus under various biotic (developmental stage, sex, and tissue) and abiotic (gas stimulation and temperature) conditions through RefFinder (which integrates four computational programs: geNorm, NormFinder, BestKeeper, and ∆Ct). Results indicate that the optimal combination of reference genes for each experimental condition was as follows: RPL8 and EF1α for the developmental stage (eggs, early instar nymphs, late instar nymphs, and adults), RPL8 and RPS16 for adult sex, RPL8 and RPL11 for adult tissue (head, thorax, abdomen, and legs), RPL8 and β-tubulin for gas stimulation (air and carbon dioxide), and RPL8 and NADH for temperature (0, 5, 17, 30, and 37 °C). Finally, the expression pattern of the HSP70 and GR21 genes were analyzed, and the results highlight the importance of appropriate reference-gene selection. Our results provide a comprehensive list of optimal reference genes from C. hemipterus for the first time, which will contribute to accurately analyzing the expression of target genes.

Keywords: Cimex hemipterus, reference gene, quantitative real-time PCR

1. Introduction

Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) testing has been widely used in the detection and quantitative analysis of mRNA transcription levels, owing to its advantages of high accuracy, high specificity, high sensitivity, easy performance, and rapidity [1,2]. Nevertheless, the precision of qRT-PCR analysis is often influenced by many biological and technical factors, for example, RNA integrity, quality, and reverse transcription efficiency, as well as PCR efficiency [2,3]. To avoid errors caused by the above variables and obtain accurate and reliable results, reference genes are often applied to normalize the expression of target genes [4].

Generally speaking, the suitable reference gene should not be controlled or affected by the experimental procedure [5]. However, many studies indicated that any reference gene is also not guaranteed to be stably expressed under all experimental conditions [6,7,8,9,10,11,12,13]. Therefore, it is necessary to select suitable reference genes under specific conditions for certain insect species rather than using common reference genes [14].

Bed bugs, Cimex hemipterus (F.) and Cimex lectularius L. (Hemiptera: Cimicidae), are cryptic and nocturnal obligate blood-sucking insects that feed on the blood of humans and some other warm-blooded animals [15,16]. In China, both C. hemipterus and C. lectularius are distributed, among which southern provinces such as Guangdong, Guangxi, Fujian, and Hainan are dominated by C. hemipterus, while other provinces are dominated by C. lectularius [17,18,19,20]. Since 2007, the number of reports of bed bug infestations has increased dramatically in China [21,22,23].

Similar to other blood-sucking insects [24,25,26], bed bugs can accurately locate their hosts and successfully feed on blood by sensing host-derived signaling substances such as CO2, host odor, and heat [27,28,29]. At present, the intrinsic mechanism of mosquito perception of host-derived signaling substances has been extensively studied, and numerous odorant receptors (ORs), gustatory receptors (GRs), and ionotropic receptors (IRs) involved in chemosensory signal transduction have been identified [24,25,30,31,32]. For bed bugs, there are relatively few studies on the chemosensory mechanisms of C. lectularius, and these mainly focus on the olfactory sensing mechanisms of aggregated pheromones and host odors, as well as repellent substances [29]; however, studies on the chemosensory mechanism of C. hemipterus have not been reported yet. Exploring the internal mechanism of bed bugs’ perceptions of host-derived signal substances and identifying the relevant chemoreceptor genes will help enrich our comprehensive understanding of the bugs’ host-search behavior and provide an important theoretical basis for the timely monitoring of bed bugs. On the other hand, it will lay the foundation for seeking new bed bug control strategies, which is of great practical significance for the realization of safe and efficient bed bug control.

Recently, we identified a large number of chemoreceptor genes by transcriptome sequencing in different tissues of C. hemipterus. Additionally, we plan to study the expression patterns of these genes (for example, in different tissues and in different developmental stages of bugs) and clarify their functions. However, there is no report on the screening and application of the reference genes in C. hemipterus. Although reference genes have been reported in C. lectularius [33,34], which belongs to the same genus as C. hemipterus, it is unknown whether these reference genes are equally suitable for C. hemipterus. Thus, the objective of the present study was to screen the stably expressed reference genes of C. hemipterus under five experimental conditions (developmental stage, sex, tissue, gas (air and carbon dioxide) stimulation, and temperature) for qRT-PCR normalization. Our results will provide the basic information for subsequent target-gene-expression analysis and functional studies in C. hemipterus and then lay the foundation for a better understanding of this pest and the formulation of rational control methods.

2. Materials and Methods

2.1. Insects

The Cimex hemipterus used in this study were collected from Guangzhou City, Guangdong Province, China in 2018 [19]. They were maintained in artificial climate chambers (26 ± 1 °C, 40 ± 10% relative humidity (RH) with a photoperiod of 12:12 (L:D) h) according to the methods of Zhang et al. (2021) [35].

2.2. Experimental Condition and Sample Collection

A total of five experimental conditions (developmental stage, sex, tissue, gas stimulation, and temperature) were set up to assess the stability of the 10 candidate reference genes in C. hemipterus. For each replication, the developmental-stage sample includes 50 eggs, 20 1st–2nd instar nymphs, 8 4th–5th instar nymphs, and 5 male adults; the sex sample contains 5 male adults and 5 female adults; the body tissue sample includes the head (containing antennae and mouthparts), thorax, abdomen, and legs, which were dissected from 50 male adults; the gas stimulation sample contains 5 CO2-treated (the concentration of CO2 was 1.6%) male adults and 5 air-treated male adults—all the male adults were stimulated by CO2 or air for 3 h with a flow rate of 500 mL/min, respectively; the temperature treatment sample contains male adults that were exposed to 0, 5, 17, 30, and 37 °C for 2 h, with 4 individuals per temperature treatment. Each experimental condition was replicated three times. The collected samples were immediately frozen with liquid nitrogen and temporarily stored under the condition of −80 °C until RNA extraction.

2.3. RNA Extraction and cDNA Synthesis

TRIzol reagent (Takara Biomedical Technology (Beijing) Co., Ltd., Beijing, China) was used for extracting total RNA from each sample following the manufacturer’s manual. The concentration and purity of RNAs were determined by a NanoDrop One Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The OD260/280 value of the total RNA was between 1.9 and 2.1, which was considered to meet the quality requirements for subsequent experiments. Then, the integrity of RNAs was examined by 0.8% agarose gel electrophoresis. First-strand cDNAs were synthesized by reverse transcribing 1 µg of total RNA with the PrimeScript RT Kit (Takara Biomedical Technology (Beijing) Co., Ltd., Beijing, China).

2.4. Reference Gene Selection, Primer Design, and qRT-PCR

Ten candidate reference genes were selected based on our recently sequenced transcriptomes for C. hemipterus (Kong et al., unpublished data). The 10 reference genes were Ribosomal protein L8 (RPL8), Ribosomal protein L11 (RPL11), Ribosomal protein L13 (RPL13), Ribosomal protein S16 (RPS16), α-tubulin (α-tubulin), β-tubulin (β-tubulin), Glyceraldehyde 3-phosphate dehydrogenase (GAPDH), Elongation factor 1 α (EF1α), NADH dehydrogenase (ubiquinone) flavoprotein 1 (NADH), and Actin (Actin). Primer pairs for amplification were designed strictly according to the principles of qRT-PCR primer design using the software Primer Premier 5.0. The primer sequence, length, and amplification efficiency (E) of the 10 reference genes are listed in Table 1.

Table 1.

The primer sets and amplification efficiency of the 10 candidate reference genes used for qRT-PCR.

Gene Primer Sequence a (5′–3′) Amplicon Length (bp) Efficiency b (%) R2 c
RPL8 F: AGGCACGGTTACATCAAAGG 131 111.07 0.9952
R: TCGGGAGCAATGAAGAGTTC
RPL11 F: GAAGAATGTCATGCGAGATGTCAGG 129 92.28 0.9987
R: CCTTTGAGAAGACTGGCTGCTG
RPL13 F: ATTGGCAGAGGTTCATTCGT 131 100.91 0.9979
R: GCATCTCACTGCTGGTCTCA
RPS16 F: AATGGTCGCCCACTTGAGAT 158 87.46 0.9976
R: GCCTGCCTGATTGCGTAGAT
α-tubulin F: TCAACTACCAACCACCCACT 139 94.93 0.9990
R: TTGGCGTACATCAAGTCAAA
β-tubulin F: CCTTTGCTGGACGCCTCATT 84 103.67 0.9902
R: CGACCCGACTGGTGCATACC
GAPDH F: GCATTTAGAGTCCCTGTCGC 149 91.12 0.9806
R: ACTTCATCTTCGGTGTAGCC
EF1α F: CGTTAGGACGTTTCGCTGTC 103 106.65 0.9893
R: GCCTTTGTCACTTTGCCACT
Actin F: GACTTCGAGCAGGAAATGGC 114 98.08 0.9989
R: TTCTGGGCAACGGAACCTCT
NADH F: AAAGACGAAGGTCGGGATTA 76 87.11 0.9812
R: GCATCAAAGAAACACGCATC
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a: F and R denote forward and reverse primers, respectively. b: qRT-PCR amplification efficiency, calculated by the standard curve method. c: Determination coefficient.

The 20 µL reaction system included 10 µL 2 × SYBR Green Premix (TIANGEN, China), 0.6 µL of 10 µM primers, 6.8 µL ddH2O, and 2 µL diluted cDNA. Reactions were conducted using a CFX-96 real-time PCR system (Bio-Rad, Hercules, CA, USA). The amplification program was as follows: 95 °C for 10 min, 40 cycles of 95 °C for 10 s, and 60 °C for 32 s. The presence of a single peak in the melting curve analysis was selected to confirm the gene-specific amplification, as well as to get rid of the non-specific amplification and the primer–dimer generation.

The amplification efficiency and correlation coefficient of each candidate reference gene were measured by applying the slope of the standard curve generated by the serial five-fold diluted cDNA template [1]. The amplification efficiency (E) of each primer pair was calculated according to the equation [5]:

E = (10[−1/slope] − 1) × 100

2.5. Determination of Reference Gene Expression Stability

The expression stability of the 10 candidate reference genes was assessed using RefFinder (https://www.heartcure.com.au/reffinder/, accessed on 10 July 2022), which integrates four major computational programs, i.e., geNorm [36], NormFinder [7], BestKeeper [4], and the ∆Ct method [37]. The suitable number of reference genes for normalizing target gene expression was determined by computing the pairwise variation (V) using geNorm [36]. If the V-value (Vn/Vn+1) is lower than 0.15, it indicates using n genes is enough for target gene expression normalization.

2.6. Validation of the Candidate Reference Genes

To further verify the accuracy of our experimental results, the expression profiles of the heat shock protein (HSP70) gene and gustatory receptor 21 (GR21) gene in C. hemipterus were normalized by the top two most stable (RPL8 and RPL11) and least stable (RPL13 and RPS16) candidates in the head (including antennae and mouthparts), thorax, abdomen, and legs. The forward primer of HSP70 was 5′-GAACGGGAACCAAGGAGGC-3′, and the reverse primer of HSP70 was 5′-TCGACGGCGAATCTCAGCA-3′. The forward primer of GR21 was 5′-CGGGCATGGTGTTTATCAAG-3′, and the reverse primer of GR21 was 5′-CTCCCAGTGTAACTCGAGGG-3′. The relative expression levels of HSP70 and GR21 in different tissues (considered as different treatments) were computed using the 2−∆∆Ct method [38]. Each treatment was replicated 3–5 times.

One-way analysis of variance (ANOVA) was used to analyze the expression differences between HSP70 and GR21 in different tissues, and Tukey’s honest significant difference (HSD) test was selected for separating the means. Statistical analysis was conducted using SPSS version 22.0 [39].

3. Results

3.1. Primer Specificity and Efficiency

Melting curves of all primer pairs were a single peak, and no nonspecific amplification products were observed, indicating that the primers were highly specific. The amplification efficiency (E) of the primers for the 10 reference genes ranged from 87.11% for NADH to 111.07% for RPL8, and the correlation coefficients varied from 0.9806 to 0.9990 (Table 1).

3.2. Ct Values of Candidate Reference Genes

The cycle threshold (Ct) values of the 10 reference genes under five experimental conditions were used for evaluating their expression levels. As shown in Figure 1 and Table 2, the Ct values ranged from 14.92 to 32.34, and the most values were distributed between 18 and 27. Actin was the most abundant transcript (the mean Ct value was 16.46 ± 0.40), and NADH was the least abundant candidate reference gene (the mean Ct value was 24.61 ± 0.56) (Table 2).

Figure 1.

Figure 1

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Cycle threshold (Ct) values of 10 candidate reference genes in C. hemipterus under different experimental conditions. The boxes show the 25th and 75th percentiles, the line inside the box depicts the median value, and whiskers indicate the standard error of the mean.

Table 2.

Cycle threshold (Ct) values (mean ± SE) of 10 candidate reference genes under five different experimental conditions.

Candidate Gene Experimental Conditions All *
Developmental Stage Sex Tissue Gas Stimulation Temperature
RPL8 19.15 ± 0.16 18.50 ± 0.42 19.33 ± 0.11 27.61 ± 0.56 21.26 ± 0.23 20.68 ± 0.40
RPL11 18.23 ± 0.57 18.62 ± 0.16 19.29 ± 0.16 26.97 ± 0.49 22.39 ± 0.23 20.78 ± 0.41
RPL13 18.75 ± 0.24 19.40 ± 0.66 22.24 ± 1.03 28.34 ± 0.60 21.53 ± 0.23 21.60 ± 0.48
RPS16 17.94 ± 0.65 17.63 ± 0.15 22.73 ± 1.19 29.70 ± 0.87 30.44 ± 0.41 24.09 ± 0.83
α-tubulin 15.74 ± 0.67 16.59 ± 0.61 16.58 ± 0.16 23.08 ± 0.47 17.67 ± 0.16 17.47 ± 0.33
β-tubulin 20.61 ± 0.44 22.18 ± 0.97 19.50 ± 0.50 27.67 ± 0.65 20.95 ± 0.17 21.46 ± 0.38
GAPDH 17.88 ± 0.53 18.30 ± 0.32 20.25 ± 0.20 27.77 ± 0.48 22.67 ± 0.19 21.06 ± 0.45
EF1α 15.54 ± 0.54 15.52 ± 0.25 16.70 ± 0.17 24.27 ± 0.46 17.94 ± 0.23 17.55 ± 0.39
Actin 15.67 ± 1.20 16.87 ± 0.88 14.92 ± 0.31 23.29 ± 0.63 15.42 ± 0.12 16.46 ± 0.40
NADH 21.26 ± 0.35 26.60 ± 2.67 23.12 ± 0.52 32.34 ± 0.60 24.61 ± 0.10 24.61 ± 0.56
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*: The mean cycle threshold (Ct) values (mean ± SE) of each reference gene under five experimental conditions in C. hemipterus.

3.3. Stability of the 10 Reference Genes under Different Experimental Conditions

For the developmental stage, there was a significant difference between the two most stable reference genes recommended by the four algorithms (Table 3). In the geNorm analysis, RPL8 and RPL11 had the best stability. In the NormFinder analysis, EF1α and NADH were the two most stable genes. The BestKeeper analysis showed that NADH and β-tubulin were the top two ranked genes. Additionally, in the ∆Ct analysis, RPL8 and EF1α were identified as the two most stable genes. Based on the RefFinder analysis results, RPL8 was the most stable reference gene in the developmental stage condition, followed by EF1α, NADH, RPL11, GAPDH, RPS16, β-tubulin, RPL13, α-tubulin, and Actin (Figure 2). The pairwise variation value of V2/3 calculated by geNorm was below the threshold value of 0.15 (Figure 3). Thus, in different developmental stages, RPL8 and EF1α were the suitable combination of reference genes.

Table 3.

Stability of 10 reference genes in Cimex hemipterus under different conditions.

Condition Rank * geNorm NormFinder BestKeeper ∆Ct
Gene Stability Gene Stability Gene Stability Gene Stability
Developmental stage 1 RPL8 0.118 EF1α 0.274 NADH 0.283 RPL8 0.622
2 RPL11 0.118 NADH 0.278 β-tubulin 0.349 EF1α 0.623
3 EF1α 0.240 RPL8 0.334 EF1α 0.410 RPL11 0.636
4 RPS16 0.269 GAPDH 0.378 GAPDH 0.428 RPS16 0.675
5 RPL13 0.356 RPL11 0.382 RPL8 0.443 NADH 0.707
6 GAPDH 0.434 RPS16 0.433 RPL11 0.457 GAPDH 0.722
7 NADH 0.497 β-tubulin 0.588 RPS16 0.490 RPL13 0.837
8 α-tubulin 0.560 RPL13 0.685 α-tubulin 0.622 β-tubulin 0.865
9 β-tubulin 0.629 α-tubulin 0.708 RPL13 0.672 α-tubulin 0.896
10 Actin 0.813 Actin 1.513 Actin 0.963 Actin 1.551
Sex 1 RPS16 0.328 RPL8 0.364 RPS16 0.290 RPL8 1.709
2 EF1α 0.328 RPL13 0.428 RPL11 0.317 RPL11 1.794
3 RPL11 0.640 RPL11 0.709 EF1α 0.385 GAPDH 1.914
4 GAPDH 0.749 GAPDH 1.133 GAPDH 0.520 RPS16 1.944
5 RPL8 0.881 α-tubulin 1.192 RPL8 0.691 α-tubulin 1.947
6 α-tubulin 1.002 Actin 1.217 α-tubulin 1.253 EF1α 1.948
7 RPL13 1.183 RPS16 1.380 RPL13 1.272 RPL13 2.039
8 Actin 1.325 β-tubulin 1.428 Actin 1.771 Actin 2.091
9 β-tubulin 1.421 EF1α 1.448 β-tubulin 1.986 β-tubulin 2.241
10 NADH 2.388 NADH 6.188 NADH 5.589 NADH 6.256
Tissue 1 RPL8 0.355 RPL8 0.178 RPL8 0.329 EF1α 1.595
2 RPL11 0.355 RPL11 0.178 α-tubulin 0.415 RPL8 1.600
3 EF1α 0.484 EF1α 0.247 RPL11 0.422 RPL11 1.667
4 GAPDH 0.556 α-tubulin 0.312 EF1α 0.490 α-tubulin 1.723
5 α-tubulin 0.632 GAPDH 0.579 GAPDH 0.524 GAPDH 1.775
6 Actin 0.847 Actin 0.830 Actin 0.808 Actin 1.915
7 β-tubulin 1.057 β-tubulin 1.165 β-tubulin 1.173 β-tubulin 2.158
8 NADH 1.313 NADH 2.099 NADH 1.524 NADH 2.656
9 RPL13 1.838 RPL13 3.835 RPL13 3.203 RPL13 4.031
10 RPS16 2.353 RPS16 4.235 RPS16 3.629 RPS16 4.412
Gas stimulation 1 Actin 0.325 RPL8 0.241 EF1α 0.893 RPL8 0.689
2 β-tubulin 0.325 β-tubulin 0.400 GAPDH 0.958 β-tubulin 0.737
3 RPL8 0.440 RPL11 0.435 α-tubulin 0.998 RPL11 0.764
4 RPL11 0.491 Actin 0.453 RPL11 1.004 Actin 0.766
5 α-tubulin 0.588 NADH 0.579 RPL8 1.100 EF1α 0.834
6 EF1α 0.624 EF1α 0.616 RPL13 1.105 α-tubulin 0.846
7 GAPDH 0.644 α-tubulin 0.651 NADH 1.180 NADH 0.857
8 NADH 0.696 GAPDH 0.718 Actin 1.231 GAPDH 0.892
9 RPL13 0.778 RPL13 0.855 β-tubulin 1.281 RPL13 1.041
10 RPS16 0.864 RPS16 1.089 RPS16 1.767 RPS16 1.207
Temperature 1 RPL8 0.230 RPL8 0.279 NADH 0.345 RPL8 0.616
2 RPL13 0.230 β-tubulin 0.343 Actin 0.390 NADH 0.653
3 EF1α 0.360 NADH 0.361 α-tubulin 0.446 β-tubulin 0.660
4 RPL11 0.416 GAPDH 0.407 β-tubulin 0.554 EF1α 0.664
5 GAPDH 0.464 EF1α 0.426 GAPDH 0.563 GAPDH 0.679
6 NADH 0.512 RPL13 0.447 RPL11 0.726 RPL13 0.688
7 β-tubulin 0.528 RPL11 0.462 RPL8 0.764 RPL11 0.702
8 Actin 0.573 α-tubulin 0.568 EF1α 0.776 α-tubulin 0.791
9 α-tubulin 0.605 Actin 0.593 RPL13 0.797 Actin 0.795
10 RPS16 0.766 RPS16 1.341 RPS16 1.211 RPS16 1.411
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*: The ranking is based on stability; the lower the value, the higher the ranking.

Figure 2.

Figure 2

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Stability ranking of 10 candidate reference genes in C. hemipterus under different treatment conditions analyzed by RefFinder (integrates four major computational programs: geNorm, NormFinder, BestKeeper, and ∆Ct). The lower the value, the higher the stability.

Figure 3.

Figure 3

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Optimal reference-gene number was required for the normalization of target-gene expression in C. hemipterus under the different experimental conditions. The pairwise variation (V) value was calculated using geNorm to evaluate the optimal reference-gene number in the qRT-PCR analysis. A value less than 0.15 indicates that n reference genes are sufficient to normalize the expression of the target gene.

For bed bug sex, the two most stable genes from the four computational programs differ significantly. For example, RPS16 and EF1α were determined to be the top two most stably expressed referenced genes by geNorm, RPL8 and RPL13 for NormFinder, RPS16 and RPL11 for BestKeeper, and RPL8 and RPL11 for ΔCt (Table 3). Based on the integrated analysis results of RefFinder, the most stable reference gene in different sex conditions was RPL8, followed by RPS16, RPL11, EF1α, GAPDH, RPL13, α-tubulin, Actin, β-tubulin, and NADH (Figure 2). The results of the geNorm analysis indicate that the pairwise variation value of V2/3 was less than the threshold value of 0.15 (Figure 3). Therefore, the combination of RPL8 and RPS16 was recommended for normalizing the qRT-PCR data in the different sexes of adult samples by geNorm.

For bed bug tissue, geNorm and NormFinder had the same top two genes in stability ranking: RPL8 and RPL11 (Table 3). However, the top two in BestKeeper were RPL8 and α-tubulin, and the top two in ΔCt were EF1α and RPL8 (Table 3). The RefFinder analysis showed that RPL8 was the most stable reference gene under this experimental condition, followed by RPL11, EF1α, α-tubulin, GAPDH, Actin, β-tubulin, NADH, RPL13, and RPS16 (Figure 2). The pairwise variation value of V2/3 was less than the cut-off value of 0.15 according to the geNorm analysis. (Figure 3). Therefore, RPL8 and RPL11 were recognized as suitable reference genes for normalizing qRT-PCR data in the different tissue samples.

For gas stimulation, NormFinder and ΔCt had the same top two gene stability rankings: RPL8 and β-tubulin (Table 3). However, based on geNorm, Actin and β-tubulin were the top two most stable genes. EF1α and GAPDH were determined to be the top two most stably expressed genes by BestKeeper (Table 3). Based on the analysis results of RefFinder, the most stable gene under the treatment of gas stimulation was RPL8, followed by β-tubulin, Actin, RPL11, EF1α, α-tubulin, GAPDH, NADH, RPL13, and RPS16 (Figure 2). The geNorm analysis results indicated that the pair-wise value of V2/3 was lower than 0.15 (Figure 3), suggesting that the combination of RPL8 and β-tubulin was sufficient for reliable normalization in different gas stimulation samples.

For temperature treatment, the top two most stable genes from the four computational programs differed from each other. They were RPL8 and RPL13 by geNorm, RPL8, and β-tubulin by NormFinder, NADH and Actin by BestKeeper, and RPL8 and NADH by ΔCt (Table 3). Based on the RefFinder analysis, the most stable reference gene under the conditions of different temperatures was RPL8, followed by NADH, β-tubulin, RPL13, EF1α, GAPDH, RPL11, Actin, α-tubulin, and RPS16 (Figure 2). The pairwise variation value of V2/3 calculated by the geNorm analysis program was less than 0.15 (Figure 3), indicating that the combination of RPL8 and NADH was adequate for optimal normalization in different temperature treatment samples.

3.4. Validation of Candidate Reference Genes in Different Tissues

The expression trend of HSP70 in different tissues was similar in the two combinations, with higher expression in the thorax and abdomen, and lower expression in the head and legs. When the two most stable reference genes (RPL8 and RPL11) were selected as reference genes, the relative expression levels of HSP70 in the legs were significantly higher than in the head (F3,16 = 17.1, p < 0.0001; Figure 4). However, when the two least stable reference genes (RPL13 and RPS16) were selected, no significant difference was observed in the relative expression of HSP70 between the head and legs (F3,16 = 9.1, p = 0.001; Figure 4). For another gene, the relative expression trend of GR21 in different tissues was inconsistent in the two reference-gene combinations (RPL8 and RPL11, RPL13 and RPS16). The relative expression of GR21 in the head was the highest, and the relative expression in the four tissues was significantly different, when normalized by RPL8 and RPL11 (F3,8 = 439.9, p < 0.0001; Figure 5). While, when normalized by RPL13 and RPS16, the tissue with the highest relative expression of GR21 was the thorax. However, there was no significant difference in the relative expression among the head, thorax, and legs; in addition, no significant difference was observed among the head, abdomen, and legs (Figure 5). Therefore, these results further indicate that the expression levels of the target genes will be different when normalized by different reference-gene combinations.

Figure 4.

Figure 4

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Tissue expression patterns of HSP70 gene in C. hemipterus. The relative expression levels of HSP70 in the head (including antennae and mouthparts), thorax, abdomen, and legs were normalized to the top two most stable (A, RPL8 and RPL11) and least stable (B, RPL13 and RPS16) candidate reference genes, respectively. Different lower letters above bars represent significant differences in gene expression among different tissues (p < 0.05, Tukey’s HSD test).

Figure 5.

Figure 5

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Tissue expression patterns of GR21 gene in C. hemipterus. The relative expression levels of GR21 in the head (including antennae and mouthparts), thorax, abdomen, and legs were normalized to the top two most stable (A, RPL8 and RPL11) and least stable (B, RPL13 and RPS16) candidate reference genes, respectively. Different lower letters above bars represent significant differences in gene expression among different tissues (p < 0.05, Tukey’s HSD test).

4. Discussion

In the present study, the expression-level stability of 10 candidate reference genes in C. hemipterus under various experimental conditions was evaluated through qRT-PCR. According to the final evaluation results of RefFinder, it was found that the stable expressed reference genes recommended for different developmental stages, different tissues of the adult males, different sexes, different temperature treatments, and bed bugs stimulated by different gases varied. Among them, RPL8 had the least variable expression levels under the five experimental conditions, which was consistent with the report of Zhu et al. [34]. In the research of Zhu et al. [34], the stability of four reference genes (RPL11, RPL8, RPS16, and HSP70) under the conditions of different populations, different developmental stages, different tissues, and dsRNA injected in C. lectularius was compared; that study also identified RPL8 as an optimal reference gene. We infer that this consistency may be related to the close genetic relationship between C. hemipterus and C. lectularius. Another report about the selection of reference genes in C. lectularius showed that RPL18 was defined as the best reference gene for various tissues and developmental stages of pesticide-exposed and susceptible strains, and their candidate reference genes include Actin, β-tubulin, EF1α, GAPDH, syntaxin (SYN), RPL18, and ubiquitin-C (UBC) [33]. However, our study did not include RPL18 as a candidate reference gene. Whether there was a difference in the stability of RPL8 and RPL18 in C. hemipterus requires further study.

Actin and GAPDH, the most widely used internal reference genes in animals, insects, and plants, did not show good expression stability in C. hemipterus (Figure 2, Table 3). This significant variance in the expression stability has been reported in many previous studies [6,8,9,33,40,41]. EF1α [33,42] and NADH [43] also have been widely used as reference genes in different species and experimental conditions. In our experiments, EF1α was one of the top two most stable genes in the developmental-stage sample set, but it did not perform well among the other four factors. Similarly, NADH was one of the top two most stable genes in different temperature treatment samples; however, its stabilization was greatly reduced under the conditions of different developmental stages and sexes. These results further demonstrate that no single reference gene is suitable for all species and different treatment conditions.

The ribosomal protein (RP) is involved in translation and protein synthesis and is one of the most highly conserved proteins in all biological cells. The RP coding gene was considered to be one stable expressed reference gene and had been widely used in insect molecular research to regulate the level of gene expression over the past 10 years [44,45,46,47,48]. These genes include RPL8 under the conditions of different populations, different developmental stages, different tissues, dsRNA injected in C. lectularius [34], different geographic populations, across developmental stages, different wing dimorphisms, different temperature treatments, and different antibiotic treatments of Metopolophium dirhodum (Walker) (Hemiptera: Aphididae) [43]; RPL13 in the different tissues of Rhopalosiphum padi L. (Hemiptera: Aphididae) [49]; and RPL11 in the conditions of different developmental stages and temperatures in Aphis craccivora Koch (Hemiptera: Aphidiae) [50]. In this study, the RPL8 gene exhibited the most stable expression level in C. hemipterus under the five experimental conditions, RPL11 was recommended as one of the top two most stable expressed genes in different adult tissues, and RPS16 was also recommended for different sexes. Our results further expand the application scope of the RP coding gene as an internal reference gene in hemiptera insects.

It has been widely accepted that introducing two or more reference genes to normalize target-gene expression levels can reduce various errors and ensure the accuracy of results in experiments [51,52]. However, using a poor stable reference gene may yield the incorrect expression pattern of the target gene and lead to erroneous interpretations [50]. In the present experiment, the expression level of GR21 was inconsistent among different tissues when normalized to the top two most stable (RPL8 and RPL11) and least stable (RPL13 and RPS16) reference genes. Therefore, it is pivotal to choose and confirm the best stable reference genes for certain insect species under specific conditions.

Over the past 20–30 yr period, there was a significant upward trend of bed bug infestations worldwide. The effective control of C. hemipterus has become a common issue in many infested countries or regions, such as China [19,20,53], southeast Asia [54,55], and South Africa [56]. Our results can provide the essential information for target-gene expression analysis and functional studies of this pest in order to lay a foundation for further exploration of new C. hemipterus control methods/strategies. However, this study only screened the reference genes of C. hemipterus under three biotic (developmental stage, tissue, and sex) and two abiotic (gas stimulation and temperature) conditions. Whether the results are also suitable for other experimental conditions (such as RNAi, insecticide treatment, etc.) in C. hemipterus or other species needs to be further verified.

5. Conclusions

In this study, we selected 10 frequently used reference genes in insects and evaluated their stability in C. hemipterus under various biotic (developmental stage, sex, and tissue) and abiotic (gas stimulation and temperature) conditions using RefFinder. The results show that the most suitable candidate combinations of reference genes were as follows: RPL8 and EF1α for the developmental stage (eggs, early instar nymphs, late instar nymphs, and adults), RPL8 and RPS16 for adult sex, RPL8 and RPL11 for adult tissue (head, thorax, abdomen, and legs), RPL8 and β-tubulin for gas stimulation (air and carbon dioxide), and RPL8 and NADH for temperature treatment. These findings will provide the basic information for subsequent target-gene-expression analysis and functional studies in C. hemipterus.

Acknowledgments

We thank Min Fan, Qiling Liang, and Shujie Mo from the South China Agricultural University for help in rearing bed bugs and preparing experimental materials.

Author Contributions

Conceptualization, D.W. and D.K.; Methodology, D.W. and D.K.; Software, D.W. and D.K.; Formal analysis, D.W., D.K. and L.L.; Resources, D.S. and R.Z.; Validation, D.S., R.Z. and L.L.; Investigation, D.S., R.Z., L.L. and Y.H.; Data curation, D.K. and D.W.; Writing—original draft preparation, D.K. and D.W.; Writing—review and editing, D.W., D.K., C.W. and Y.H.; Project administration, D.W. and C.W.; Funding acquisition, D.W. and C.W. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

Funding Statement

This research was funded by the Characteristic Innovation Project of Colleges and Universities of the Guangdong Provincial Department of Education (2020KTSCX017), the Ningbo Key Research and Development Plan and “Jie Bang Gua Shuai” Program (2022Z124), and the Jiangxi Province 2018 ‘Double Thousands Talents’ Plan (jxsq2018102116).

Footnotes

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Data Availability Statement

The data presented in this study are available on request from the corresponding author.

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