Gene 555 (2015) 393–402

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Identification and validation of reference genes for normalization of gene expression analysis using qRT-PCR in Helicoverpa armigera (Lepidoptera: Noctuidae) Songdou Zhang a, Shiheng An b, Zhen Li a, Fengming Wu a, Qingpo Yang a, Yichen Liu a, Jinjun Cao a, Huaijiang Zhang a, Qingwen Zhang a, Xiaoxia Liu a,⁎ a b

Department of Entomology, China Agricultural University, Beijing 100193, China State Key Laboratory of Wheat and Maize Crop Science (College of Plant Protection), Henan Agricultural University, Zhengzhou 450002, China

a r t i c l e

i n f o

Article history: Received 11 August 2014 Received in revised form 11 November 2014 Accepted 15 November 2014 Available online 18 November 2014 Keywords: Helicoverpa armigera Reference gene qRT-PCR analysis Normalization Biotic conditions Abiotic conditions

a b s t r a c t Background: Recent studies have focused on determining functional genes and microRNAs in the pest Helicoverpa armigera (Lepidoptera: Noctuidae). Most of these studies used quantitative real-time PCR (qRT-PCR). Suitable reference genes are necessary to normalize gene expression data of qRT-PCR. However, a comprehensive study on the reference genes in H. armigera remains lacking. Results: Twelve candidate reference genes of H. armigera were selected and evaluated for their expression stability under different biotic and abiotic conditions. The comprehensive stability ranking of candidate reference genes was recommended by RefFinder and the optimal number of reference genes was calculated by geNorm. Two target genes, thioredoxin (TRX) and Cu/Zn superoxide dismutase (SOD), were used to validate the selection of reference genes. Results showed that the most suitable candidate combinations of reference genes were as follows: 28S and RPS15 for developmental stages; RPS15 and RPL13 for larvae tissues; EF and RPL27 for adult tissues; GAPDH, RPL27, and β-TUB for nuclear polyhedrosis virus infection; RPS15 and RPL32 for insecticide treatment; RPS15 and RPL27 for temperature treatment; and RPL32, RPS15, and RPL27 for all samples. Conclusion: This study not only establishes an accurate method for normalizing qRT-PCR data in H. armigera but also serve as a reference for further study on gene transcription in H. armigera and other insects. © 2014 Elsevier B.V. All rights reserved.

1. Introduction In the post-genomic era, quantitative real-time PCR (qRT-PCR) is a suitable method for gene transcriptomics and functional genomics, because of its high sensitivity and accuracy, good reproducibility and rapid processing (Derveaux et al., 2010; VanGuilder et al., 2008). Although qRT-PCR has been described as the golden standard for transcriptomics and functional genomics, non-specific variations caused by errors in pipetting, RNA extraction and purification, cDNA synthesis and concentration, PCR procedures, primer transcription efficiency, Abbreviations: qRT-PCR, quantitative real-time PCR; cDNA, complementary DNA; H. armigera, Helicoverpa armigera; TRX, thioredoxin; SOD, Cu/Zn superoxide dismutase; NPV, nuclear polyhedrosis virus infection; BT, Bacillus thuringiensis; 18S, 18S ribosomal; 28S, 28S ribosomal; ACT, actin; β-ACT, beta actin; α-TUB, alpha-tubulin; β-TUB, beta-tubulin; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; EF, elongation factor 1 alpha; RPL13, ribosomal protein L13; RPS15, ribosomal protein S15; RPL27, ribosomal protein L27; RPL32, ribosomal protein L32; E, efficiencies; CT, Cross Threshold; NFs, normalization factors; SD, standard deviation; MIQE, Minimum Information for Publication of Quantitative Real-Time PCR Experiments; RP, ribosomal protein; Sp, Spinetoram; Bc, beta-cypermethrin. ⁎ Corresponding author. E-mail address: [email protected] (X. Liu).

http://dx.doi.org/10.1016/j.gene.2014.11.038 0378-1119/© 2014 Elsevier B.V. All rights reserved.

utilizing qRT-PCR etc. may be encountered during analysis (Andersen et al., 2004; Bustin et al., 2009, 2010; Fleige and Pfaffl, 2006). qRT-PCR data must be normalized using reference genes to avoid these nonspecific variations or errors (Huggett et al., 2005; Radonić et al., 2004). Previous studies either selected the homologues of reference genes commonly used in model species or selected previously used reference genes (Teng et al., 2012). However, the expression levels of several commonly used reference genes, such as α-Actin, β-Actin and GAPDH, vary under certain experimental conditions (Bémeur et al., 2004; Glare et al., 2002; Selvey et al., 2001). An ideal reference gene is one that constantly shows similar transcription abundance with the target gene under different experimental conditions and does not co-regulate with the target gene (Radonić et al., 2004). To date, an ideal reference gene remains lacking (Derveaux et al., 2010; Vandesompele et al., 2002). Previous studies showed that at least two or three reference genes should be used to normalize gene expression data (Lin and Lai, 2010; Thellin et al., 1999; Vandesompele et al., 2002). Therefore, suitable reference genes must be identified to normalize qRT-PCR data. Up to now, the reference genes of several insects have been selected and validated across different biotic and abiotic conditions. These insects include the honey bee Apis mellifera (Lourenco et al., 2008), the silkworm

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Bombyx mori (Wang et al., 2008), the desert locust Schistocerca gregaria (Van Hiel et al., 2009), the oriental fruit fly Bactrocera dorsalis (Shen et al., 2010), the red flour beetle Tribolium castaneum (Lord et al., 2010), the fruit fly Drosophila melanogaster (Ponton et al., 2011), the emerald ash borer Agrilus planipennis (Rajarapu et al., 2012), the diamondback moth Plutella xylostella (Fu et al., 2013), the sweetpotato whitefly Bemisia tabaci (Li et al., 2013), the red imported fire ant Solenopsis invicta (Cheng et al., 2013), Spodoptera litura (Lu et al., 2013) and the Beet Armyworm Spodoptera exigua (Zhu et al., 2014). However, none of the reference genes from abovementioned insects exhibit uniform and suitable expression under different experimental conditions. The cotton bollworm Helicoverpa armigera (Lepidoptera: Noctuidae), which has four generations per year in Northern China, is an omnivorous and widespread lepidopteran pest that brings enormous economic loss in the cotton, corn, vegetable and other crop industries throughout Asia (Wu et al., 2008; Lu et al., 2012). Control of H. armigera had become almost impossible by the end of the 20th century because of its strong resistance to most insecticides (Lu et al., 2012). A rapid PubMed search can yield almost 959 research papers concerning H. armigera (up to July 29, 2014). Most of these papers focused on the transcriptomics and proteomics (Zhao et al., 2013; Zhang et al., 2013), insecticide resistance (Cao et al., 2013; Jin et al., 2013; Somwatcharajit et al., 2014), insect–baculovirus interactions (Arrizubieta et al., 2013), microRNAs (Jayachandran et al., 2013; Agrawal et al., 2013) and function genes in H. armigera (Mao et al., 2007; Liu et al., 2013; Wang et al., 2013; Yan et al., 2013; Zhu et al., 2012). In 2011, i5k (http://www. arthropodgenomes.org/wiki/i5K) was jointly proposed by many internationally renowned entomologists to study the genomic sequence of 5000 insects and related arthropod species. Hence, i5k presented an unprecedented opportunity to study the physiological and biological mechanism in H. armigera. H. armigera is an important agricultural pest and model insect, however a comprehensive study on its reference genes is lacking. In the current paper, 12 commonly used reference genes of H. armigera were selected to normalize qRT-PCR data. Two target genes thioredoxin (TRX) and Cu/Zn superoxide dismutase (SOD) were used to validate the selection of reference genes. The expression stability of the reference genes was evaluated under different biotic (developmental stages, larvae tissues, adult tissues, and nuclear polyhedrosis virus infection) and abiotic conditions (insecticide treatment and temperature treatment). Different combinations of reference genes were recommended for specific experimental cases. The present study aims to identify suitable reference genes and evaluate their expression stability in H. armigera before using them as internal controls in functional genomics researches. 2. Materials and methods 2.1. Insects

2.2.2. Tissues Eight larvae tissues (head, epidermis, fat body, hemocyte, midgut, Malpighian tubule, salivary glands, and central nervous system) were obtained from the fifth instar second day larvae using a dissection needle and a tweezer. Six adult tissues, including the head, thorax, abdomen, leg, wing, and flight muscle, were dissected from the adult two days after eclosion. Every adult tissue included almost equal number of male and female adults. All the tissue samples were washed three times by precooling PBS (140 mM NaCl, 2.70 mM KCl, 10 mM Na2HPO4, 1.80 mM KH2PO4, pH 7.40) solution (Liu et al., 2011) and then immediately stored at − 80 °C for later use. For each tissue, at least 15 insects were collected. Each sample repeated three times. 2.2.3. NPV infection For the virus challenge, H. armigera NPV powder was diluted with sterile water to five concentrations (104, 105, 106, 107, and 108 PIB/mL). Then, 10 μL NPV suspension at different concentrations was pipetted on the artificial diet pieces (length × width × height = 0.80 cm × 0.80 cm × 0.50 cm). The artificial diet of control group was added with an equal amount of sterile water. One piece of the treated diet and one newly molted fourth-instar larva pretreated with overnight starvation were subsequently put into one glass tube at the same time, and normal diet was replenished until the diet with NPV was eaten up. Mortality was checked every day thereafter for toxicity test. Each treatment included three independent biological replicates. LC50 and LC90 values were calculated using PoloPlus™ software (LeOra Software, Berkeley, USA) (Table S1). For gene expression experiment, fourth-instar larvae were then treated with the LC90 value of NPV as above. In the bioassay experiment, as the same fourth-instar larvae began to die from the second day under the treatment of LC90 value of NPV, so 6 surviving insects were respectively collected at 24 h, 48 h, 72 h, and 96 h, and immediately stored at −80 °C for later RNA extraction. 2.3. Abiotic factor treatments 2.3.1. Insecticide-induced stress In this study, three insecticides which were commonly applied in the management of H. armigera were chosen, including Bacillus thuringiensis (BT) powder, beta-cypermethrin, and Spinetoram. Firstly, the LC50 and LC90 values (Table S1) of all the three insecticides were determined using the above method (NPV infection experiment). Twenty fourthinstar larvae were then treated with the LC90 value of each insecticide. The control groups were treated with an equal volume of sterile water. After 24 h and 48 h, 6 surviving insects were respectively collected and immediately stored at −80 °C for later use. For each treatment, totally three independent biological replicates were completed.

The strain of H. armigera was obtained from IPM laboratory of Entomology department in Chinese Agricultural University, Beijing, China. The larvae were reared on the artificial diet as described by Wu and Gong (1997) and maintained at 27 ± 1 °C, 75 ± 10% RH under a 16:8 light–dark cycle. Larvae were individually separated after the thirdinstar stage to avoid cannibalism.

2.3.2. Temperature treatment Each group of thirty fourth instar 48 h larvae was exposed to temperatures of 4 °C (cold), 27 °C (ambient temperatures), or 40 °C (hot) in a glass tube (Li et al., 2013; Lu et al., 2013). After 2 h, 6 h, and 12 h, six insects in each temperature treatment were then collected and immediately stored at −80 °C for later RNA extraction and cDNA synthesis. For each treatment, totally three independent biological replicates were completed.

2.2. Biotic factor treatments

2.4. Selection of reference gene and primer design

2.2.1. Developmental stages 400 first-day eggs of H. armigera, 80 first-instar feeding larvae, 40 second-instar feeding larvae, 20 third-instar feeding larvae, 10 fourth-instar feeding larvae, 6 fifth-instar feeding larvae, 6 first-day male and female pupae, and 6 first-day male and female adults were collected for each replication. The samples were in triplicate and immediately stored at −80 °C for total RNA extraction.

Twelve commonly used housekeeping genes were selected (Table 1), including 18S ribosomal (18S), 28S ribosomal (28S), actin (ACT), beta actin (β-ACT), alpha-tubulin (α-TUB), beta-tubulin (β-TUB), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), elongation factor 1 alpha (EF), ribosomal protein L13 (RPL13), ribosomal protein S15 (RPS15), ribosomal protein L27 (RPL27), and ribosomal protein L32 (RPL32). The sequences of selected reference genes were obtained

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Table 1 Primer pairs of candidate reference genes and target genes used for qRT-PCR analysis. Gene name (abbreviation)

Accession number

Sequence (5′–3′)a

Product length (bp)

Primer efficiency (%)

R2b

Actin (ACT)

HM629437.1

151

107.07

0.9929

beta-Actin (β-ACT)

EU527017.1

144

107.52

0.9946

alpha-Tubulin (α-TUB)

JQ069957.1

147

95.34

0.9995

beta-Tubulin (β-TUB)

JF767013.1

106

99.25

0.9985

18S ribosomal (18S)

AB620126.1

146

96.03

0.9994

28S ribosomal (28S)

GU350477.1

100

102.70

0.9962

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH)

JF417983.1

140

98.96

0.9981

Elongation factor 1 alpha (EF)

FJ768770.1

171

102.91

0.9996

Ribosomal protein L13 (RPL13)

AY846882.1

139

97.51

0.9979

Ribosomal protein S15 (RPS15)

AY818611.1

107

88.25

0.9981

Ribosomal protein L27 (RPL27)

DQ875214.1

155

87.02

0.9983

Ribosomal protein L32 (RPL32)

JQ744274.1

152

98.70

0.9950

Cu/Zn superoxide dismutase (SOD)

JQ009331.1

132

103.97

0.9953

Thioredoxin (TRX)

JQ744277.1

F: 5′-GACGGTCAGGTCATCACCATC-3′ R: 5′-ACAGGTCCTTACGGATGTCA-3′ F: 5′-CCTGGTATTGCTGACCGTATGC-3′ R: 5′-CTGTTGGAAGGTGGAGAGGGAA-3′ F: 5′-CGTAGAGCCCTACAACTCCA-3′ R: 5′-AGACGGTTCAGGTTGGTGTA-3′ F: 5′-AGCAGTTCACCGCTATGTTC-3′ R: 5′-AGGTCGTTCATGTTGCTCTC-3′ F: 5′-CATGCATGTCTCAGTGCAAG-3′ R: 5′-CATCACTGGTCAGAGTTCTG-3′ F: 5′-CGATAGCGAACAAGTACCGT-3′ R: 5′-TTCGAGTTTCGCAGGTTTAC-3′ F: 5′-CCAGAAGACAGTGGATGGAC-3′ R: 5′-TACCAGTCAGCTTTCCGTTC-3′ F: 5′-GAAGTCAAGTCCGTGGAGATG-3′ R: 5′-GACCTGTGCTGTGAAGTCG-3′ F: 5′-CTGCAAGACGTCACCGCAG-3′ R: 5′-CCACGACCAGCACGAACCT-3′ F: 5′-CTGAGGTCGATGAAACTCTC-3′ R: 5′-CTCCATGAGTTGCTCATTG-3′ F: 5′-ACAGGTATCCCCGCAAAGTGC-3′ R: 5′-GTCCTTGGCGCTGAACTTCTC-3′ F: 5′-CATCAATCGGATCGCTATG-3′ R: 5′-CCATTGGGTAGCATGTGAC-3′ F: 5′-CATGGATTCCATGTTCACGAG-3′ R: 5′-GTTGCCGAGGTCTCCAACATG-3′ F: 5′-GTCGATCCACATCAAGGAC-3′ R: 5′-CATTGGCCATCTCATCTAG-3′

140

98.06

0.9944

a b

F and R respectively indicate forward primer and reverse primer. R2 refers to the coefficient of determination.

from the GenBank of NCBI. The primers used in qRT-PCR were designed with DNAClub software (http://www.softpedia.com/get/Science-CAD/ DNA-Club.shtml) according to the gene sequence. All primer sequences were synthesized by Sangon Biotechnology Co., Ltd. (Shanghai, China) (Table 1).

Schmittgen, 2001). The CT value of the reference gene was subtracted from the CT value of the target gene to obtain ΔCT. The normalized fold changes of the target gene mRNA expression were expressed as 2−ΔΔCT, where ΔΔCT is equal to ΔCTtreated sample − ΔCTcontrol. 2.7. Expression stability analysis

2.5. Total RNA extraction and cDNA synthesis All the samples were collected according to the above instructions and then used for total RNA extraction by TRIzol reagent (Invitrogen, USA) following the manufacturer's protocol. The purity and concentration of RNA samples were determined twice by ultraviolet spectrophotometer (Abs260) in order to reduce deviation. Total RNA of each samples was treated with DNase to exclude the genomic DNA contamination. First-strand complementary DNA (cDNA) was synthesized from 1 μg of total RNA following the manual instruction of PrimeScript RT reagent kit with gDNA Eraser (Takara, Kyoto, Japan), and immediately stored at −80 °C for later use. The cDNA samples were in triplicate. 2.6. Standard curve construction and quantitative real-time PCR The reliability of the qRT-PCR results was confirmed by the standard curve and melting curve analysis. Standard curves were created by using 10-fold dilution series of cDNA as a template for each treatment using the linear regression model (Pfaffl et al., 2004). The efficiencies (E) of corresponding primers used in qRT-PCR were calculated according to the equation: E = (10[−1/slope] − 1) × 100 (Pfaffl, 2001). QRTPCR was performed using SYBR green supermix (TaKaRa) following the manufacturer's instructions on a Bio-Rad CFX Connect™ Real-Time PCR System (Bio-Rad, USA). The amplification conditions for the realtime PCR were as follows: 95 °C for 30 s, followed by 40 cycles of 95 °C for 10 s and 60 °C for 30 s. The specificity of amplified product was further confirmed by melting curve analysis from 65 °C to 95 °C and agarose gel electrophoresis. The mRNA expression of target genes was quantified using the comparative CT (Cross Threshold, the PCR cycle number that crosses the signal threshold) method (Livak and

Four commonly used software tools, including geNorm version 3.5 (Vandesompele et al., 2002), Normfinder version 0.953 (Andersen et al., 2004), BestKeeper (Pfaffl et al., 2004), and the comparative ΔCT method (Silver et al., 2006), were used to evaluated the raw CT values of the twelve selected reference genes as described in their manuals. The raw CT values were converted into relative quantities and imported into the geNorm and Normfinder software programs. The geNorm software firstly calculates a gene expression stability value (M) and then performs a pair-wise variation (V) value to evaluate the most stably expressed gene and the optimal number of reference genes, respectively. Candidate gene with the lowest M value should be the most stably expressed reference gene. Vandesompele et al. (2002) proposed 0.15 as a cut-off value of Vn / n + 1 and V value below 0.15 indicated that an additional reference gene will not significantly improve normalization of qRT-PCR analysis. Normfinder software also uses a model-based approach to rank the expression stability of suitable reference genes (Andersen et al., 2004). Reference gene with the lowest value is also the most stable gene. The Excel based tool BestKeeper, which is based on the geometric mean of the CT values and PCR amplification efficiency, was used to rank the candidate reference genes (Pfaffl et al., 2004). The comparative ΔCT method, which compares relative expression of pairwise genes within each sample, was used to select the optimal reference gene (Livak and Schmittgen, 2001). Finally, a web-based friendly analysis tool, RefFinder (http://www.leonxie.com/referencegene.php) was used to evaluate and screen the optimal reference genes by integrating the results of the above four major software programs (Xie et al., 2011). Based on rankings from each program, RefFinder assigns an appropriate weight to an individual gene and calculates the geometric mean of their weights for the overall final ranking.

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2.8. Validation of reference gene selection Two target genes, an oxidation-reduction related gene TRX and a stress-related gene SOD, were used to evaluate the validity of selected reference genes. TRX expression levels were determined in different development stages and larvae tissues of H. armigera with specific primers (Table 1). SOD transcriptional levels were determined in the fourthinstar larvae of H. armigera treated with insecticides and NPV infection using specific primers (Table 1). Two different normalization factors (NFs) were calculated based on (1) the geometric mean derived from CT values of the optimal recommended gene combination (Table 2), and (2) CT values of a single candidate gene with the lowest or highest stability ranking order (Fu et al., 2013). The relative expression levels of two target genes in different samples were calculated according to CT value by 2−ΔΔCT method. All the experiments were performed in triplicate, and the results are expressed as means ± standard deviation (SD). Statistically significant differences from target gene expression are denoted by * (0.01 b p b 0.05) and ** (p b 0.01) as determined by the pair-wise Student's t-test analysis in SPSS 17.0 software. 3. Results 3.1. Amplification efficiency and transcriptional profiling of candidate reference genes The primer specificity of the 12 reference genes and two target genes for qRT-PCR was validated using a single sharp peak in the melting curve analysis and specific bands in the agarose gel electrophoresis analysis. The correlation coefficients (R2) of 14 genes for each standard curve were greater than 0.99 and the amplification efficiencies of all the primers were between 87.02% and 107.52% (Table 1). The CT values in qRT-PCR provided an overview of the variation in gene expression in the samples. The distributions of the mean CT values for each gene in all samples significantly varied. The CT values (n = 144 samples) of the 12 candidate reference genes ranged from 11.21 for 18S to 24.38 for α-TUB (Fig. 1). The remaining reference genes were expressed at moderate levels, with mean CT values of 22.89, 22.40, 13.90, 21.97, 24.38, 22.68, 21.90, 20.70, 20.13 and 21.36 for β-ACT, EF, 28S, ACT, α-TUB, β-TUB, RPL13, RPS15, RPL27, and RPL32, respectively (Fig. 1). The CT values of the target genes SOD and TRX were 25.86 and 21.75 respectively. The significant variation in raw expression levels indicates that selecting a suitable reference gene for normalization requires confirmation of the expression stability. 3.2. Stability of candidate reference genes under biotic conditions 3.2.1. Developmental stage The stability ranking recommended by Normfinder was closely similar to the results obtained from the ΔCT method, which revealed 28S, RPS15, and RPL32 to be the most stable genes. The most stable genes determined by geNorm were RPS15, RPL27, and RPL32, whereas those determined by BestKeeper were β-ACT, ACT, and EF (Table 3). According to RefFinder, the stability ranking of the reference genes from the most stable to the least stable across different developmental stages Table 2 Preferable reference genes in H. armigera recommended for different experimental conditions. Experimental conditions

Preferable reference genes

Biotic factors

28S RPS15 EF GAPDH RPS15 RPS15 RPL32

Abiotic factors All samples

Development stages Larvae tissues Adult tissues NPV infection Insecticide treatment Temperature treatment

RPS15 RPL13 RPL27 RPL27 RPL32 RPL27 RPS15

β-TUB

RPL27

was: 28S N RPS15 N RPL32 N β-ACT N RPL27 N ACT N EF N 18S N β-TUB N RPL13 N GAPDH N α-TUB (Fig. 2). The values of V2/3, V3/4, V4/5, V5/6 and V6/7 were all above the proposed cut-off value of 0.15, and V7/8 was less than 0.15 (Fig. 3). In view of the cost and convenient operation, geNorm recommended two reference genes (28S and RPL15) for the accurate normalization across different developmental stages (Table 2) and revealed that the threshold value of 0.15 was not absolute (Vandesompele et al., 2002). 3.2.2. Larvae tissues The four computational programs, except Normfinder, identified that ACT and β-ACT as the least stable genes and RPS15 as the most stable gene (Table 3). According to RefFinder, the stability ranking of the reference genes from the most stable to the least stable gene across larvae tissues was: RPS15 N RPL13 N RPL32 N RPL27 N 28S N 18S N GAPDH N EF N β-TUB N α-TUB N β-ACT N ACT (Fig. 2). The geNorm analysis showed that the pairwise variation values of V2/3 to V9/10 were all below the cut-off value of 0.15 (Fig. 3). Thus RPS15 and RPL13 were the suitable combination of control genes recommended for larval tissues (Table 2). 3.2.3. Adult tissues GAPDH, ACT, and α-TUB were identified as the least stable genes by the four computational programs except BestKeeper (Table 3). In the stability ranking, Normfinder identified EF, RPL27, and β-ACT as the most stable genes and similar results were obtained by the ΔCT method. The most stable genes identified by geNorm were RPS15, RPL27, and EF, whereas those identified by BestKeeper were α-TUB, 28S, and 18S (Table 3). According to RefFinder, the stability ranking of the reference genes from the most stable to the least stable under adult tissues was: EF N RPL27 N RPS15 N 28S N β-ACT N α-TUB N 18S N RPL32 N β-TUB N RPL13 N ACT N GAPDH (Fig. 2). The geNorm analysis manifested that the pairwise variation values of V2/3 was below the proposed 0.15 cutoff (Fig. 3), so the combination of EF and RPL27 was suitable for normalizing qRT-PCR data in the adult tissues (Table 2). 3.2.4. NPV infection All the four computational programs identified α-TUB, ACT, and 18S as the least stable genes (Table 3). GAPDH, β-TUB, and RPL27 were identified as the most stable genes by Normfinder and the comparative ΔCT method. But geNorm identified RPL27 and RPL32 as the most stable genes, BestKeeper identified 28S and β-TUB as the most stable genes (Table 3). According to RefFinder, the stability ranking of the reference genes from the most stable to the least stable gene across NPV infection was: GAPDH N RPL27 N β-TUB N RPL32 N β-ACT N RPS15 N 28S N RPL13 N EF N 18S N ACT N α-TUB (Fig. 2). The geNorm analysis manifested that the pairwise variation values of V3/4 were below the proposed 0.15 cut-off value (Fig. 3). The combination of GAPDH, RPL27, and β-TUB was recommended for normalizing qRT-PCR data in the NPV infection samples by geNorm (Table 2). 3.3. Stability of candidate reference genes under abiotic conditions 3.3.1. Insecticide treatment All four algorithms, except for BestKeeper, identified RPS15, RPL32, and RPL13 as the most stable genes, and identified 18S and 28S as the least stable genes (Table 4). BestKeeper identified α-TUB as the most stable gene, and identified RPL27 as the least stable gene (Table 4). According to RefFinder, the stability ranking of the reference genes from the most stable to the least stable under insecticide-induced stress was: RPS15 N RPL32 N RPL13 N RPL27 N α-TUB N ACT N β-ACT N 28S N β-TUB N GAPDH N EF N 18S (Fig. 2). The geNorm analysis showed that all pairwise variation values were below the proposed 0.15 cut-off value (Fig. 3). Thus, RPS15 and RPL32 were sufficient to normalize gene expression for the insecticide treatment samples (Table 2).

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397

Fig. 1. Expression profiles of candidate reference genes and target genes in different samples of H. armigera. Expression levels are documented as cycle threshold (CT) values of candidate reference genes and target genes used in this study. The black boxes indicate the mean value of replicated samples, while the bars indicate the standard deviation of the mean. Table 3 Expression stability of the candidate reference genes under different biotic conditions. Biotic condition

Developmental stages

Larvae tissues

Adult tissues

NPV infection

Reference gene

18S 28S ACT β-ACT α-TUB β-TUB EF GAPDH RPL13 RPS15 RPL27 RPL32 18S 28S ACT β-ACT α-TUB β-TUB EF GAPDH RPL13 RPS15 RPL27 RPL32 18S 28S ACT β-ACT α-TUB β-TUB EF GAPDH RPL13 RPS15 RPL27 RPL32 18S 28S ACT β-ACT α-TUB β-TUB EF GAPDH RPL13 RPS15 RPL27 RPL32

geNorm

Normfinder

ΔCT

BestKeeper

Stability

Rank

Stability

Rank

Stability

Rank

Stability

Rank

0.98 0.61 1.06 0.88 1.21 1.11 1.16 1.27 0.72 0.33 0.33 0.43 0.64 0.57 1.54 1.28 0.98 0.92 0.84 0.75 0.51 0.40 0.41 0.44 0.84 0.77 1.05 0.52 0.92 0.68 0.43 1.19 0.57 0.40 0.40 0.46 0.86 0.77 0.94 0.45 0.99 0.60 0.69 0.56 0.52 0.49 0.38 0.38

6 3 7 5 10 8 9 11 4 1 1 2 5 4 11 10 9 8 7 6 3 1 1 2 8 7 10 4 9 6 2 11 5 1 1 3 9 8 10 2 11 6 7 5 4 3 1 1

0.82 0.42 0.88 0.81 1.23 0.88 0.97 1.28 1.24 0.76 0.84 0.77 0.75 0.56 2.62 2.48 1.01 0.92 0.87 0.82 0.55 0.55 0.71 0.59 0.76 0.55 1.40 0.52 1.12 0.83 0.36 1.75 0.79 0.61 0.47 0.77 0.90 0.85 1.07 0.66 1.07 0.26 0.74 0.09 0.82 0.72 0.49 0.58

5 1 7 4 10 8 9 12 11 2 6 3 6 3 12 11 10 9 8 7 1 2 5 4 6 4 11 3 10 9 1 12 8 5 2 7 10 9 12 5 11 2 7 1 8 6 3 4

1.58 1.23 0.96 0.91 1.30 1.30 1.11 1.25 1.33 1.24 1.29 1.21 0.91 0.77 1.93 1.89 0.85 0.90 0.96 0.89 0.78 0.68 0.85 0.84 1.19 0.82 1.55 1.66 0.75 1.48 1.54 1.70 1.94 1.63 1.57 1.94 0.86 0.25 1.25 1.14 1.40 0.70 1.09 0.79 1.05 0.91 1.01 1.18

11 5 2 1 9 9 3 7 10 6 8 4 9 2 12 11 6 8 10 7 3 1 5 4 3 2 6 9 1 4 5 10 12 8 7 11 4 1 11 9 12 2 8 3 7 5 6 10

1.23 1.03 1.27 1.23 1.46 1.27 1.30 1.56 1.46 1.13 1.17 1.15 1.31 1.24 2.80 2.68 1.43 1.43 1.38 1.25 1.20 1.14 1.22 1.19 1.18 1.06 1.64 0.98 1.38 1.16 0.90 1.89 1.11 0.99 0.94 1.06 1.13 1.10 1.23 0.91 1.24 0.79 1.03 0.75 1.01 0.95 0.82 0.88

5 1 6 5 8 6 7 9 8 2 4 3 6 5 12 11 10 9 8 7 3 1 4 2 9 5 11 3 10 8 1 12 7 4 2 6 10 9 11 5 12 2 8 1 7 6 3 4

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3.3.2. Temperature treatment GeNorm, Normfinder and the comparative ΔCT method identified RPL15, RPL27, and RPL13 as the most stable genes, 28S, ACT, and β-ACT as the least stable genes (Table 4). BestKeeper identified 18S, EF, and ACT as the most stable genes, GAPDH, β-ACT, and α-TUB as the least stable genes (Table 4). According to RefFinder, the stability ranking of the reference genes from the most stable to the least stable under temperature treatment was: RPS15 N RPL27 N RPL13 N 18S N EF N RPL32 N β-TUB N ACT N GAPDH N α-TUB N β-ACT N 28S (Fig. 2). The geNorm analysis showed that all the pairwise variation values were below the proposed 0.15 cut-off value (Fig. 3). GeNorm considered RPS15 and EF suitable for normalizing qRT-PCR data in the temperature treatment samples (Table 2).

3.4. Ranking of H. armigera candidate reference genes across all samples Finally, geNorm and the comparative ΔCT method identified RPL32, RPS15, RPL13, and RPL27 as the most stable genes, Normfinder identified RPL32 and RPL13 as the most stable genes, BestKeeper identified 28S and RPS15 as the most stable genes (Table 5), According to RefFinder, the stability ranking of reference genes from the most stable to the least stable across all the investigated samples was: RPL32 N RPS15 N RPL27 N RPL13 N β-TUB N 28S N 18S N EF N β-ACT N ACT N α-TUB N GAPDH (Fig. 2). The geNorm analysis showed that all pairwise variation values were above the proposed 0.15 cut-off value (Fig. 3). In view of cost and operation, RPL32, RPS15, and RPL27 were considered as the most stable reference genes for normalizing qRT-PCR data (Table 2).

Fig. 2. Expression stability of the candidate reference genes in different samples. The average expression stability of the reference genes as calculated by the Geomean method of RefFinder. A lower Geomean of ranking value denotes more stable expression. A: different development stages from egg to adult; B: larvae tissues of the last instar; C: different tissues of the adult; D: H. armigera larvae infected with NPV; E: H. armigera larvae treated with different insecticides (Bacillus thuringiensis, Spinetoram, and beta-cypermethrin); F: H. armigera larvae treated with different temperatures; G: H. armigera larvae under all conditions.

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Fig. 3. Optimal number of reference genes for normalization in H. armigera. D. stages: developmental stages; L. tissues: larvae tissues; A. tissues: adult tissues; I. treatment: insecticide treatment; T. treatment: temperature treatment. The pairwise variation (Vn / Vn + 1) was analyzed by geNorm software between the normalization factors NFn and NFn + 1 to determine the optimal number of reference genes required for accurate normalization. A value b0.15 denotes that additional reference genes will not markedly improve normalization.

3.5. Validation of reference gene selection This study failed to identify a candidate reference gene with constant expression in H. armigera under all the experimental conditions. Thus, the effect of using “wrong” reference genes for normalizing qRT-PCR data must be determined. In the present study, we evaluated the expression profiles of two target genes, TRX and SOD, across different experimental conditions. The most stable reference gene [NF 1], the two most stable reference genes [NF (1–2)], the three most stable reference genes [NF (1–3)], the four most stable reference genes [NF (1–4)], or the least stable gene [NF 12] for the normalization of TRX and SOD expression levels were used under different developmental stages, larvae tissues, insecticide treatment, and NPV infection. Similar expression levels of TRX were observed when normalized using the NF 1 (28S), NF (1–2) (28S and RPL15) and NF (1–3) (28S, RPL15, and RPL32) under different developmental stages except for fifth-instar larval and pupal

stages. However the expression levels of TRX normalized using NF 12 (α-TUB) were 1.52-fold to 7.86-fold higher than those of TRX normalized using NF (1–2) (28S and RPL15) in first-, second-, third- and fourth-instar larval stages of H. armigera (P b 0.01) (Fig. 4A). In different larval tissues, the expression level of TRX normalized using NF 1 (RPS15), NF (1–2) (RPS15 and RPL13) and NF (1–3) (RPS15, RPL13, and RPL32) was 3.61-fold higher in the head than that in the fat body. By contrast, the expression levels of TRX normalized against the NF 12 (ACT) were 4.94-fold higher in the fat body than in the head (Fig. 4B). The expression level of TRX normalized using NF (1–2) (RPS15 and RPL13) and NF 12 (ACT) is significantly different in larval fat body and larval midgut (P b 0.01, Fig. 4B). The expression levels of SOD normalized using the NF 1 (RPS15), NF (1–2) (RPS15 and RPL32) and NF (1–3) (RPS15, RPL32, and RPL13) increased by 1.85 fold after 48 h than 24 h of Spinetoram treatment. However, the expression level of SOD normalized using NF 12 (18S)

Table 4 Expression stability of the candidate reference genes under different abiotic conditions. Abiotic condition

Reference Gene

Insecticide treatment

18S 28S ACT β-ACT α-TUB β-TUB EF GAPDH RPL13 RPS15 RPL27 RPL32 18S 28S ACT β-ACT α-TUB β-TUB EF GAPDH RPL13 RPS15 RPL27 RPL32

Temperature treatment

geNorm

Normfinder

ΔCT

BestKeeper

Stability

Rank

Stability

Rank

Stability

Rank

Stability

Rank

0.79 0.71 0.41 0.52 0.56 0.58 0.62 0.49 0.38 0.26 0.16 0.16 0.40 0.54 0.51 0.48 0.47 0.42 0.45 0.34 0.21 0.21 0.28 0.34

11 10 4 6 7 8 9 5 3 2 1 1 5 11 10 9 8 6 7 4 1 1 2 3

1.03 1.01 0.40 0.60 0.50 0.64 0.58 0.64 0.27 0.12 0.42 0.29 0.35 0.64 0.53 0.50 0.40 0.37 0.36 0.41 0.27 0.16 0.19 0.35

12 11 4 8 6 9 7 10 2 1 5 3 4 12 11 10 8 7 6 9 3 1 2 5

0.97 0.73 1.18 0.84 0.71 0.86 1.21 0.98 1.04 0.94 1.21 1.13 0.38 0.57 0.48 0.59 0.59 0.55 0.43 0.69 0.58 0.50 0.52 0.57

6 2 10 3 1 4 11 7 8 5 12 9 1 7 3 9 9 6 2 10 8 4 5 7

1.15 1.14 0.68 0.79 0.76 0.83 0.80 0.81 0.65 0.57 0.67 0.61 0.52 0.72 0.64 0.61 0.56 0.54 0.53 0.55 0.47 0.42 0.43 0.52

12 11 5 7 6 10 8 9 3 1 4 2 4 12 11 10 9 7 6 8 3 1 2 5

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Table 5 Expression stability of the candidate reference genes under all samples. Reference gene

18S 28S ACT β-ACT α-TUB β-TUB EF GAPDH RPL13 RPS15 RPL27 RPL32

geNorm

Normfinder

ΔCT

BestKeeper

Stability

Rank

Stability

Rank

Stability

Rank

Stability

Rank

1.05 1.17 1.58 1.46 1.70 0.86 1.34 1.77 0.71 0.48 0.48 0.63

5 6 9 8 10 4 7 11 3 1 1 2

1.31 1.70 1.73 1.43 1.80 0.75 1.26 1.85 0.74 0.77 0.86 0.55

7 9 10 8 11 3 6 12 2 4 5 1

1.63 1.16 1.91 1.74 1.77 1.30 1.66 1.81 1.36 1.19 1.36 1.34

7 1 12 9 10 3 8 11 6 2 5 4

1.80 2.03 2.12 1.90 2.14 1.50 1.77 2.22 1.46 1.43 1.47 1.38

7 9 10 8 11 5 6 12 3 2 4 1

was 9.12-fold higher than those of SOD normalized using NF (1–2) (RPS15 and RPL32) after 48 h than 24 h of Spinetoram treatment (Fig. 4C, P b 0.01). The expression levels of SOD normalized using NF 1 (GAPDH), NF (1–2) (GAPDH and RPL27), NF (1–3) (GAPDH, β-TUB, and RPL27) and NF (1–4) (GAPDH, β-TUB, RPL27, and RPL32) were similar after 24 h and 48 h of NPV infection. However, the expression levels of SOD normalized using NF (1–2) (GAPDH and RPL27) and NF 12 (α-TUB) are significantly different after 24 and 48 h of NPV infection (P b 0.01, Fig. 4D). These indicated that the expression levels of genes are significantly different when unstable reference genes are used to normalized qRT-PCR data under specific conditions. 4. Discussion qRT-PCR is extensively used to determine the mRNA expression levels of lower abundance and validate the efficiency of RNA interference in molecular biology (Bustin, 2000). However, variations in qRTPCR protocols, including RNA preparation, reverse transcription and qPCR operation, may influence actual expression variation in specific target genes (Andersen et al., 2004; Fleige and Pfaffl, 2006). Bustin et al. (2009) proposed the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines because of lacking consensus on how to operate and explain qRT-PCR experiments. Therefore, the evaluation of reference genes and primer efficiency as

indicated in MIQE must be conducted prior to gene expression studies. To the best of our knowledge, the present study is the first report on reference gene selection in H. armigera. Specifically, 12 candidate reference genes were evaluated with four algorithms (geNorm, Normfinder, BestKeeper, and the comparative ΔCT method) under different biotic and abiotic conditions. The rankings of the tested reference genes varied across the different algorithms (Tables 3, 4, and 5) and no common candidate reference gene can be applied under all conditions because of the different mathematical methods adopted by the four programs. The web-based tool RefFinder, which integrates the four computational programs mentioned above, was used to analyze the stability of the tested reference genes by calculating their geometric mean for the overall ultimate ranking. RefFinder recommended RPL32, RPS15, RPL27, and RPL13 to be the most stable reference genes for H. armigera under all tested samples (Fig. 2G). Ribosomal RNAs (rRNAs), including 18S rRNA and 28S rRNA, mainly participate in the protein synthesis and are highly expressed in all biological cells. Previous studies have considered rRNA as the ideal reference gene because RNA polymerase for rRNA synthesis is different from that for mRNA synthesis and because the regulation of rRNA synthesis is independent of mRNA level (Bustin, 2000). In the current study, 28S gene exhibited the most stable expression at the different developmental stages and the least stable expression under temperature treatments, with a mean CT value of 13.90 (Figs. 1 and 2).

Fig. 4. Validation of the gene stability measures. Expression levels of a target gene, TRX, in eight developmental stages (A) and three larval tissues (B) were tested using different normalization factors. Moreover, expression profiles of another target gene, SOD, under insecticide treatment (C) and NPV infection (D) were investigated as well. Sp.: Spinetoram; Bc.: beta-cypermethrin. The data represent the mean values ± S.D. (n ≥ 20). Bars represent the means and standard deviations of three biological replicates.

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Meanwhile, the 18S gene exhibited the least stable expression across the insecticide treatments, with a mean CT value of 11.21 (Figs. 1 and 2). This result is consistent with the findings of previous studies in B. tabaci under insecticide treatment (Li et al., 2013), Malpighian tubule of B. dorsalis (Shen et al., 2010) and the different geographical populations of Nilaparvarta lugens (Yuan et al., 2014). Nevertheless, 18S was evaluated as the most stable reference gene in different organs of Rhodnius prolixus (Paim et al., 2012) and in different body parts of N. lugens (Yuan et al., 2014). The results of the current study indicate that 18S is not a suitable reference gene for the normalization of gene expression analysis in H. armigera. Although 28S is identified as the most stable reference gene in different developmental stages of H. armigera, we should consider the expression levels of 28S and the target genes SOD and TRX before using the former as the reference gene because its expression level is much higher than that of the target genes (Fig. 1). Actins, the main structural protein of cytoplasm, serve important function in cell secretion, motility, cytoplasm flow and cytoskeleton maintenance (Hunter and Garrels, 1977). In the present study, actin and β-actin were the least stable reference genes in the different larvae tissues, and their stability ranking was not high even under other conditions (Fig. 2). Teng et al (2012) also identified actinA1 as the least stable reference gene in the different tissues of B. mori (Wang et al., 2008) and S. exigua (Zhu et al., 2014). However, actin was identified as the most stable gene in Chilo suppressalis (Teng et al., 2012), S. gregaria (Van Hiel et al., 2009) and A. mellifera (Lourenco et al., 2008). These results further prove the importance of validating the expression stability of reference genes. Ribosomal protein (RP) is the principal component of the ribosomes and is crucial in the intracellular protein biosynthesis, it is also involved in DNA repair, cell differentiation and cell growth regulation outside the ribosomes (Ladror et al., 2014). In the present study, RPS15 gene was identified as the most stable gene in H. armigera of different larvae tissues, insecticide treatments, and temperature treatments (Fig. 2 and Table 2). RPL32 exhibited the most stable expression under all tested samples in H. armigera (Fig. 2 and Table 2). RPL27 also displayed relative higher stable ranking in different treatments of H. armigera (Fig. 2 and Table 2). Previous studies also identified RP genes as the most stably expressed candidate reference genes. These genes include RP49 in the different developmental stages of B. mori (Wang et al., 2008); RPL10 in the different larval tissues, populations and food treatments of S. litura (Lu et al., 2013); RPS13 in the different developmental stages and photoperiods of P. xylostella (Fu et al., 2013) and RP18 in the different developmental stages and tissues of Leptinotarsa decemlineata (Shi et al., 2013). To date, no single universally applicable reference gene has been identified to exhibit uniform stability across all biotic and abiotic conditions. Our data also revealed that ranking of the candidate reference genes differed among various treatments based on the analysis results of different analytical tools. On the whole, the rankings of the tested reference genes were similar under developmental stages, adult tissues, insecticide treatment, and temperature treatments according to geNorm, Normfinder, and the comparative ΔCT method (Tables 3 and 4). But BestKeeper had different results. For example, RPL13, RPS15, RPL27, and RPL32 were identified as the four best reference genes under all samples by geNorm, Normfinder, and the comparative ΔCT method except BestKeeper (Table 5). The reason might be that BestKeeper only analyze the stability of reference genes individually but the other three softwares mainly consider the pairwise variation between two reference genes to determine the stability of a reference gene (Silver et al., 2006; Teng et al., 2012). Therefore, RefFinder, which integrated the analysis results of the four algorithms, was finally used to evaluate the stability ranking of the 12 candidate reference genes. Two target genes, TRX and SOD, were used to validate the reference gene selection results in different developmental stages, larval tissues, insecticide treatments, and NPV infection (Fig. 4). Meanwhile, the optimal number of reference genes in

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variable experimental conditions was recommended by geNorm which calculates the pairwise variation (Vn / Vn + 1) between the sequential NF (NFn and NFn + 1) (Fig. 3). The results of the current study demonstrated that using unstable reference genes is insufficient to normalize the gene expression data or may generate the wrong interpretation and using more than one reference gene reduces bias in normalization (Fig. 4). Therefore, we suggest that the expression stability of candidate reference genes should be validated and that multiple normalization genes should be used based on specific conditions to obtain more accurate and reliable results. 5. Conclusions In the present study, twelve candidate reference genes of H. armigera were selected and systematically evaluated for their expression stability under different biotic and abiotic conditions. The comprehensive stability ranking of candidate reference genes was recommended by RefFinder and the optimal number of reference genes was calculated by geNorm. Two target genes, TRX and SOD, were used to validate the selection of reference genes. Results showed that the most suitable candidate combinations of reference genes were as follows: 28S and RPS15 for developmental stages; RPS15 and RPL13 for larvae tissues; EF and RPL27 for adult tissues; GAPDH, RPL27, and β-TUB for nuclear polyhedrosis virus infection; RPS15 and RPL32 for insecticide treatment; RPS15 and RPL27 for temperature treatment; and RPL32, RPS15, and RPL27 for all samples. This work will benefit future studies on gene function researches of H. armigera and other insects. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2014.11.038. Conflict of interest The authors declare that they have no conflicts of interest. Acknowledgments This work was supported by a grant from the Major State Basic Research Development Program of China (973 Program) (No. 2012CB114103). The authors thank Lihua Liang of IPM laboratory in China Agricultural University for providing the Helicoverpa armigera larvae. Author contributions Conceived and designed the experiments: SZ, ZL and XL. Performed the experiments: SZ. Analyzed the data: SZ, ZL and XL. Contributed reagents/materials/analysis tools: FW, QY, YL, JC and HZ. Wrote the paper: SZ, SA, ZL, QZ and XL. References Agrawal, N., Sachdev, B., Rodrigues, J., Sree, K.S., Bhatnagar, R.K., 2013. Development associated profiling of chitinase and microRNA of Helicoverpa armigera identified chitinase repressive microRNA. Sci. Rep. 3, 2292. Andersen, C.L., Jensen, J.L., Orntoft, 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 Res. 64, 5245–5250. Arrizubieta, M., Williams, T., Caballero, P., Simón, O., 2013. Selection of a nucleopolyhedrovirus isolate from Helicoverpa armigera as the basis for a biological insecticide. Pest Manag. Sci. http://dx.doi.org/10.1002/ps.3637 (Aug 23). Bémeur, C., Ste-Marie, L., Desjardins, P., Hazell, A.S., Vachon, L., Butterworth, R., Montgomery, J., 2004. Decreased beta-actin mRNA expression in hyperglycemic focal cerebral ischemia in the rat. Neurosci. Lett. 357, 211–214. Bustin, S.A., 2000. Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. J. Mol. Endocrinol. 25, 169–193. Bustin, S., Benes, V., Garson, J., Hellemans, J., Huggett, J., Kubista, M., Mueller, R., Nolan, T., Pfaffl, M.W., Shipley, G.L., Vandesompele, J., Wittwer, C.T., 2009. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin. Chem. 55, 611–622. Bustin, S., Beaulieu, J., Huggett, J., Jaggi, R., Kibenge, F.S., Olsvik, P.A., Penning, L.C., Toegel, S., 2010. MIQE précis: practical implementation of minimum standard guidelines for fluorescence-based quantitative real-time PCR experiments. BMC Mol. Biol. 11, 74.

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Identification and validation of reference genes for normalization of gene expression analysis using qRT-PCR in Helicoverpa armigera (Lepidoptera: Noctuidae).

Recent studies have focused on determining functional genes and microRNAs in the pest Helicoverpa armigera (Lepidoptera: Noctuidae). Most of these stu...
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