Reference gene selection for gene expression studies using RT-qPCR in virus-infected planthoppers
© Maroniche et al; licensee BioMed Central Ltd. 2011
Received: 11 February 2011
Accepted: 16 June 2011
Published: 16 June 2011
Planthoppers not only severely affect crops by causing mechanical damage when feeding but are also vectors of several plant virus species. The analysis of gene expression in persistently infected planthoppers might unveil the molecular basis of viral transmission. Quantitative real-time RT-PCR (RT-qPCR) is currently the most accurate and sensitive method used for quantitative gene expression analysis. In order to normalize the resulting quantitative data, reference genes with constant expression during the experimental procedures are needed.
Partial sequences of the commonly used reference genes actin (ACT), α1-tubulin (TUB), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), elongation factor 1 alpha (EF1A), ribosomal protein S18 (RPS18) and polyubiquitin C (UBI) from Delphacodes kuscheli, a planthopper capable of persistently transmitting the plant fijivirus Mal de Río Cuarto virus (MRCV), were isolated for the first time. Specific RT-qPCR primers were designed and the expression stability of these genes was assayed in MRCV-infective and naïve planthoppers using geNorm, Normfinder and BestKeeper tools. The overall analysis showed that UBI, followed by 18S and ACT, are the most suitable genes as internal controls for quantitative gene expression studies in MRCV-infective planthoppers, while TUB and EF1A are the most variable ones. Moreover, EF1A was upregulated by MRCV infection.
A RT-qPCR platform for gene expression analysis in the MRCV-infected planthopper vector Delphacodes kuscheli was developed. Our work is the first report on reference gene selection in virus-infected insects, and might serve as a precedent for future gene expression studies on MRCV and other virus-planthopper pathosystems.
Insect genomics is a relatively new field of research. Since the report of the fruit fly genome sequence in 2000 , several other insect genomes have been completed including three mosquitoes species, silkworm, honeybee, red flour beetle, pea aphid, three closely related parasitoid wasps and human body louse [2–5]. A considerable number of other insect genomes are in progress . In parallel, high throughput tools for functional studies in insects are being developed. For example, Gateway-based vectors applicable for the subcellular localization analysis of proteins in cultured Bombyx mori cells became available . Also important, new insect promoters for gene expression studies are being isolated and characterized  and an insect two-hybrid system to analyze protein interactions in cultured insect cells has been reported . Planthoppers (order Hemiptera, superfamily Fulgoroidea) are severe pests of plants because of their sucking damage and ability to transmit at least 18 phytopathogenic viruses . For example, the brown planthopper Nilaparvata lugens is a serious pest of rice in tropical Asia and propagatively transmits Rice ragged stunt virus (RRSV, Oryzavirus genus of the Reoviridae family), Rice grassy stunt virus (RGSV, genus Tenuivirus)  and Nilaparvata lugens reovirus (NLRV, Fijivirus genus of the Reoviridae family) . In turn, the small brown planthopper Laodelphax striatellus transmits Rice stripe virus (RSV, genus Tenuivirus) and Rice black streak dwarf virus (RBSDV, Fijivirus genus of the Reoviridae family) [13, 14] and the planthopper Peregrinus maidis transmits Maize mosaic virus (MMV: Nucleorhabdovirus genus of the Rhabdoviridae family) . Another planthopper species, Delphacodes kuscheli, is a natural vector that propagatively transmits Mal de Río Cuarto virus (MRCV, Fijivirus genus of the Reoviridae family). MRCV causes the most important maize disease in Argentina and its genome sequence has recently been completed [16–19].
Although no planthopper genonome sequencing project has yet been announced, great progress has been made with the sequencing of more than 37,000 Nilaparvata lugens ESTs originated from various tissues  and of 85,526 unigenes from different developmental stages, sexes and wing forms using short-read sequencing technology combined with a tag-based digital gene expression system . This information will certainly contribute to the unveiling of molecular events underlying virus transmission by insects. In particular, very little is known regarding the effects of persistent virus infection on planthoppers transcriptome and new robust and accurate methods for gene expression studies will be required. Most recently, massive Laodelphax striatellus parallel pyrosequencing-based transcriptome analyses was performed in both naïve and RSV-infected insects and several planthopper genes diferentially expressed during virus infection were identified .
The relative quantification of mRNA levels by RT-qPCR is currently an extensively used technique, in which reliable quantification depends on the use of one or more stably expressed endogenous genes, usually housekeeping genes, as internal controls. However, because housekeeping gene expression is not always stable and might vary depending on the samples or treatments, it is necessary to first study the stability of several endogenous gene expression in order to select suitable internal references . Thus, stability analysis of reference genes in diverse conditions and organisms are rapidly increasing [24–34]. Even though the behavior of insect housekeeping genes has been studied in bacterially challenged bees  and in Tribolium beetles infected with fungus , this kind of information is lacking for virus-infected insects. In addition, there is no information currently available on reference gene stability in Delphacodes kuscheli or any other planthopper for accurate quantification of mRNA levels by RT-qPCR. Our study aimed to examine the stability of potential reference genes expression upon MRCV infection of single D. kuscheli planthoppers and to rank them according to their reliability as internal controls. As a result, a robust RT-qPCR platform was set up for analyzing changes on gene expression upon virus infection in individual planthoppers.
Source of virus and one-to-one transmission assays
The RC MRCV isolate from the endemic disease area (County of Río Cuarto, Province of Córdoba, Argentina) was maintained on oat (Avena sativa L.) plants through successive transmissions by D. kuscheli as described previously . To obtain MRCV-infective insects, 5 III instar D. kuscheli nymphs were fed on a MRCV-infected oat plant for two days. Next, the insects were moved to a cage and fed on uninfected wheat (Triticum aestivum cv Prointa federal) seedlings (displaying one fully developed leaf) for 19 days to achieve the optimum latency period . Subsequently, each insect was placed on an individual uninfected wheat seedling for 24 h (inoculation period) and then fixed in absolute EtOH until use. Finally, after 25 days, the MRCV transmission to the wheat plants was individually determined by monitoring the presence of virus symptoms and by DAS-ELISA.
RNA extraction and cDNA synthesis
Total RNA was extracted from each planthopper using the Trizol basic protocol (Invitrogen, CA, USA) with some modifications. First, previous to the extraction the sample was pulverized by freezing in liquid nitrogen and homogenized in a 1.5 ml microcentrifuge tube, and 800 μl of Trizol were added. Second, during the isopropanol precipitation 20 μg of glycogen (Sigma, USA) was added as a carrier. RNA concentration and purity were measured with a spectrophotometer (Thermo Scientific NanoDrop™ 1000, USA) and the integrity was checked by agarose gel electrophoresis. Finally, cDNA was synthesized using Superscript III and random primers from 500 ng of DNAse I (Invitrogen, CA, USA)-treated total RNA according to the manufacturer's instructions.
Reference gene sequence isolation and primer design
Delpacodes kuscheli candidate genes for RT-qPCR
Primer sequences (5' to 3')
FW: AGCGTGGTTACAGCTTCACAAC RV: GGCCATTTCCTGTTCGAAGTC
FW: GTTTTGAACCGGCCAATCAG RV: ACGTCTTTCGGCACGACATC
Elongation factor 1- α
FW: TTGAGGCTGGTATCTCGAAGAAC RV: GCTCGGTGGAGTCCATCTTG
Ribosomal protein S18
40S ribosome subunit component
FW: TGGCTCACCCAAGACAATACAAG RV: TTCAGCCTTTCCAGGTCATCAC
FW: CGCCAAGAAGGTGATCATTTC RV: CAGGAGGCGTTCGAGATGAC
FW: CTGACCGGCAAGACGATTACG RV: GCCCTCCTTGTCCTGAATCTTC
40S ribosome subunit RNA component
FW: TCGAAGGCGATCAGATACCG RV: TCTGGTTTCCCGGAAGCTG
Quantitative real time PCR and data analysis
RT-qPCR experiments were carried out using the QuantiTec SYBR Green PCR kit (QIAGEN, Germany) according to the manufacturer's instructions, in an ABI7500 Real Time PCR System (Applied Biosystems, USA) with a standard program (1 min elongation time at 60°C). Reactions were performed in a 25 μl final volume reaction, using primers in a final concentration of 200 nM and 1 μl of a 1/10 dilution of the cDNA as template. No template was added to negative control reactions. Output results were exported as raw data, and introduced to the LinReg software  for baseline correction and PCR efficiency calculations. Resulting Ct values were used for expression stability analysis using the Microsoft Excel based tools geNorm 3.5 , Normfinder 0.953  and Bestkeeper v1  according to the developer's instructions. Statistical significance of Ct differences between treatments was calculated by the Mann-Whitney t test using the Graphpad Prism 5 software.
Results and discussion
Obtainment of MRCV-infective planthoppers and sample processing
The capacity of MRCV to replicate in plant phloem as well as in its planthopper vector tissues  suggests that the virus has the ability to regulate gene expression in both hosts. MRCV replication in plant phloem cells (where it produces severe cytopathic effects) and in planthopper vector tissues (where it establishes a persistent propagative infection) probably involves a differential regulation of gene expression in each case. To study these still unknown gene regulation processes in insects, reliable reference genes must be selected as internal controls to perform gene expression analysis. Consequently, planthoppers undoubtedly able to transmit MRCV are needed to analyze variations on potential reference gene expression levels with respect to naïve insects. One-to-one transmission assays were performed to obtain MRCV-infective insects as described in Methods. As a result, only 4 out of 50 independently evaluated insects were capable of successfully transmitting MRCV to wheat. This transmission efficiency was similar to the reported previously for this kind of assays . Only planthoppers able to transmit MRCV to wheat plants (infective insects) were kept for subsequent RT-qPCR studies along with control naïve insects subjected to the same procedure but always fed on uninfected plants.
In parallel, four different methods for insect storage were tested: immediate freezing in liquid nitrogen followed by storage at -70°C or stored for 10 days in absolute ethanol, acetone or Trizol. Next, RNA extraction was performed from each planthopper using a Trizol protocol adapted to the small size of the samples (see Methods). After measuring the resulting RNA concentration and analyzing its integrity, ethanol storage was chosen for further experiments because it was a simpler procedure and gave rise to good RNA quality (Additional file 1).
Isolation of partial sequences of candidate Delphacodes kuscheli genes for the design of qPCR primers
Seven housekeeping genes implicated in diverse cellular processes and commonly used as internal references for RT-qPCR in animals were selected as candidates for expression stability analysis. Partial sequences of Delphacodes kuscheli genes homologous to these candidate genes were obtained by RT-PCR with degenerated oligonucleotide primers (see Methods). The amplified actin (ACT), α-1-tubulin (TUB), elongation factor 1- α (EF1A), ribosomal protein S18 (RPS18), glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and polyubiquitin C (UBI) D. kuscheli sequences showed 95%, 86%, 92%, 92%, 90% and 84% identity to Nilaparvata lugens ESTs sequences, respectively, and were deposited in the GenBank database (Table 1).
Next, RT-qPCR oligonucleotides were designed for each of the D. kuscheli isolated gene fragments. Owed to the high conservation of ribosomal RNA sequences, the 18S rRNA primers were based on an available Laodelphax striatellus sequence [GenBank: AB085211]. The designed RT-qPCR primers (Table 1) were able to efficiently amplify a single product of the expected size and did not show primer dimers formation in RT-PCR experiments (Additional file 2). In addition, a primer amplification performance test by real time RT-qPCR showed that all primer combinations yield a single amplicon and the absence of primer dimers formation in the dissociation step (data not shown). The PCR amplification efficiency of each set of primers was evaluated using the LinReg software which performs, for each individual sample, a baseline correction and a PCR efficiency calculation from the linear portion of the amplification curve slope by linear regression and then calculates a mean PCR efficiency for each primer pair . The calculated PCR efficiency means ranged from 82% for UBI and TUB to 55% for 18S (Table 1). The 18S primer pair low PCR efficiency might have been caused by incomplete annealing due to mismatches, given that their design was based on a related species sequence.
Expression stability analysis of the candidate genes and optimum number of genes for normalization
A real time RT-qPCR assay was carried out to examine the expression stability of the 7 candidate genes by the following procedure. Total RNA was extracted from the previously obtained MRCV-infective planthoppers along with control (naïve) individuals, and its concentration was precisely quantified with a spectrophotometer. As a mean for normalization of the sample input, equal amounts of total RNA (500 ng) from each planthopper were treated with DNAse I to remove possible genomic DNA contamination and then used for cDNA synthesis by retrotranscription as detailed previously. Parallel reactions without RT enzyme were performed and used for RT-PCR amplification as an additional control to check that no contaminating genomic DNA was present (Additional file 3). Finally, RT-qPCR experiments were carried as described in Methods. The full sample set including both infective and naïve planthoppers was subjected to each gene expression analysis to avoid between-run variations and three independent technical replicates were performed for each sample in all the experiments. The raw data obtained from each experiment was processed using the LinReg software for baseline correction and the resulting cycle threshold (Ct) values were used in candidate gene expression stability analysis by three different methods using geNorm , Normfinder  and Bestkeeper  tools.
The Normfinder VBA program analyzes gene expression stability by means of a mathematical model, focusing in the inter- and intra-group variation . This approach ranked UBI as the most stable gene (stability value = 0.1754) followed by 18S, ACT and RPS18 (Figure 1B). This is in accordance to geNorm results, which situated UBI as the second most stable gene after ACT. However, Normfinder ranked GAPDH as the most unstable gene, whereas geNorm considered it the third most stable. This difference, due to the singular processing and assumptions of each statistical approach, indicates that it is strongly recommended to carry out more than one analysis when studying expression stability of putative reference genes.
Finally, BestKeeper Excel tool, analyzes each gene's expression variability by calculating the Ct set standard deviation (SD) and coefficient of variance (CV) and then by pair-wise comparison calculates the correlation between the genes and with the Bestkeeper index . This application ranked UBI as the least variable gene with a Ct standard deviation (SD) of 0.31 (1.24 fold change) followed by 18S with SD = 0.39 (1.31 fold change) and indicated that TUB, EF1A and GAPDH were the most variable genes (Figure 1C). When pair-wise comparing the calculated BestKeeper index against each of the candidate genes, UBI and 18S also showed the higher correlation, with R > 0.89 and p = 0.003 (Figure 1C). It is worthy noticing that according to this analysis, none of the genes can be considered inconsistent since all of the SD values were lower than 1 .
BestKeeper and Normfinder yielded comparable results, selecting UBI and 18S as the two most stable genes and GAPDH as the least stable one (Figure 1B and 1C). On the other hand, the geNorm ranking was mostly dissimilar, positioning GAPDH as the third most stable gene (Figure 1A). Nevertheless, with the exception of this conflictive gene, all three approaches clearly separated the 7 candidate genes in two distinct groups according to their stability indexes: one group of a low variability and high stability composed of UBI, ACT, 18S and RPS18 and a second one more variable and unstable composed of EF1A and TUB (Figure 1). Taken the three method's output together, the results indicate that UBI is the most reliable reference gene for quantitative analysis of MRCV-infective planthopper mRNA levels by RT-qPCR. If two (or more) genes are used for normalization, 18S and ACT are the most suitable choices as a second reference. In agreement, the ACT gene has been recently employed as an internal control for the Tomato spotted wilt virus (TSWV) quantification in individual thrip vectors, although in this case the validation of its expression stability was not previously showed .
Expression profiles of the candidate genes
Because the expression of genes classically considered as housekeeping has been found to be altered upon virus infection [22, 44], we analyzed if MRCV infection altered the expression of any of the 7 candidate genes. The Ct values obtained for each gene were compared in MRCV-infective against naïve planthoppers and the statistical significance of Ct differences between treatments was calculated by the Mann-Whitney t test using the Graphpad Prism 5 software. Interestingly, EF1A expression was significantly higher (p < 0.05) in MRCV-infective planthoppers (Figure 3B). This fact explains the instability of EF1A gene expression previously detected when using a pool of infective and naïve insects (Figure 1). In agreement, EF1A gene expression has been reported to be 97.8 times more abundant in RSV-infected versus naïve small brown planthoppers . It would be interesting to extend this study to a higher number of Delphacodes kuscheli genes, including antiviral genes of the innate immunity and RNAi pathways, to further establish if their expression is altered during persistent MRCV replication in its planthopper vector.
Insect genomics is a growing area of research. In particular planthoppers transmit many important viral diseases and the molecular basis underling insect-virus interactions are relatively poorly studied. Here, a RT-qPCR platform useful for gene expression analysis in virus infected planthoppers was developed. The evaluation of several D. kuscheli housekeeping genes expression stability showed that the UBI gene is the most reliable as internal reference control for mRNA quantification in MRCV-infective planthoppers. On the other hand, the EF1A gene was upregulated in MRCV-infected planthoppers so it shouldn't be used as an internal control. Our work is the first report on reference gene selection in virus-infected insects, and might serve as a precedent for future gene expression studies on virus-planthopper pathosystems. Particularly, these results will surely contribute to the study of gene expression profiles in D. kuscheli in the context of MRCV infection. The RT-qPCR platform developed along this work will also be useful for normalizing viral titers in insect vectors, contributing to the already developed platforms for viral quantification in vectors and to new molecular studies of transmission and epidemiology [45–50]. Finally, the study of gene expression patterns in virus-transmitting arthropods will not only improve our knowledge of the virus-vector pathosystems but might also impact in the design of new strategies for virus control.
List of abbreviations
real-time reverse transcription polymerase chain reaction.
This work was supported by Research projects PICT 2006 no. 0358 from the Argentine Agency for Promotion of Science and Technology (ANPCyT) and PE AEBIO-244621 from the National Institute of Agronomic Technology (INTA). GAM and VCM hold a doctoral fellowship from the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). MdV is a career member of CONICET. The authors would like to thank Drs. Marcelo Berretta and Sebastián Asurmendi for the critical reading of the manuscript.
- Adams MD, Celniker SE, Holt RA, Evans CA, Gocayne JD, Amanatides PG, Scherer SE, Li PW, Hoskins RA, Galle RF, George RA, Lewis SE, Richards S, Ashburner M, Henderson SN, Sutton GG, Wortman JR, Yandell MD, Zhang Q, Chen LX, Brandon RC, Rogers YH, Blazej RG, Champe M, Pfeiffer BD, Wan KH, Doyle C, Baxter EG, Helt G, Nelson CR, et al.: The genome sequence of Drosophila melanogaster. Science 2000, 287: 2185-2195. 10.1126/science.287.5461.2185View ArticlePubMedGoogle Scholar
- Consortium TIAG: Genome sequence of the pea aphid Acyrthosiphon pisum. PLoS Biol 2010, 8: e1000313. 10.1371/journal.pbio.1000313View ArticleGoogle Scholar
- Grimmelikhuijzen CJ, Cazzamali G, Williamson M, Hauser F: The promise of insect genomics. Pest Management Science 2007, 63: 413-416. 10.1002/ps.1352View ArticlePubMedGoogle Scholar
- Richards S, Gibbs RA, Weinstock GM, Brown SJ, Denell R, Beeman RW, Gibbs R, Beeman RW, Brown SJ, Bucher G, Friedrich M, Grimmelikhuijzen CJ, Klingler M, Lorenzen M, Richards S, Roth S, Schroder R, Tautz D, Zdobnov EM, Muzny D, Gibbs RA, Weinstock GM, Attaway T, Bell S, Buhay CJ, Chandrabose MN, Chavez D, Clerk-Blankenburg KP, Cree A, Dao M, et al.: The genome of the model beetle and pest Tribolium castaneum. Nature 2008, 452: 949-955. 10.1038/nature06784View ArticlePubMedGoogle Scholar
- Werren JH, Richards S, Desjardins CA, Niehuis O, Gadau J, Colbourne JK, Beukeboom LW, Desplan C, Elsik CG, Grimmelikhuijzen CJ, Kitts P, Lynch JA, Murphy T, Oliveira DC, Smith CD, van de Zande L, Worley KC, Zdobnov EM, Aerts M, Albert S, Anaya VH, Anzola JM, Barchuk AR, Behura SK, Bera AN, Berenbaum MR, Bertossa RC, Bitondi MM, Bordenstein SR, Bork P, et al.: Functional and evolutionary insights from the genomes of three parasitoid Nasonia species. Science 2010, 327: 343-348. 10.1126/science.1178028View ArticlePubMedGoogle Scholar
- Noda H: How can planthopper genomics be useful for planthopper management? In Planthoppers: new threats to the sustainability of intensive rice production systems in Asia. Edited by: Heong KL HB. Los Baños (Philippines): International Rice Research Institute; 2009:429-446.Google Scholar
- Mitsunobu H, Sakashita K, Mon H, Yoshida H, Lee JM, Kawaguchi Y, Koga K, Kusakabe T: Construction of Gateway-based Destination Vectors for Detecting Subcellular Localization of Proteins in the Silkworm, Bombyx mori. Journal of Insect Biotechnology and Sericology 2006, 75: 141-145.Google Scholar
- Lee JM, Takahashi M, Mon H, Mitsunobu H, Koga K, Kawaguchi Y, Nakajima Y, Kusakabe T: Construction of gene expression systems in insect cell lines using promoters from the silkworm, Bombyx mori. J Biotechnol 2008, 133: 9-17. 10.1016/j.jbiotec.2007.08.033View ArticlePubMedGoogle Scholar
- Mon H, Sugahara R, Hong SM, Lee JM, Kamachi Y, Kawaguchi Y, Kusakabe T: Analysis of protein interactions with two-hybrid system in cultured insect cells. Anal Biochem 2009, 392: 180-182. 10.1016/j.ab.2009.05.033View ArticlePubMedGoogle Scholar
- Hogenhout SA, Ammar el D, Whitfield AE, Redinbaugh MG: Insect vector interactions with persistently transmitted viruses. Annu Rev Phytopathol 2008, 46: 327-359. 10.1146/annurev.phyto.022508.092135View ArticlePubMedGoogle Scholar
- Hibino H: Insect-borne viruses of rice. Advances in Disease Vector Research 1989, 6: 209-241.View ArticleGoogle Scholar
- Noda H, Ishikawa K, Hibino H, Omura T: A reovirus in the brown planthopper, Nilaparvata lugens. J Gen Virol 1991,72(Pt 10):2425-2430.View ArticlePubMedGoogle Scholar
- Milne RG, Lovisolo O: Maize rough dwarf and related viruses. Adv Virus Res 1977, 21: 267-341.View ArticlePubMedGoogle Scholar
- Shinkai A: Studies on insects transmission of rice virus diseases in Japan. Bull Nat Inst Agric Sci Ser C 1962, 14: 1-112.Google Scholar
- Redinbaugh MG, Seifers DL, Meulia T, Abt JJ, Anderson RJ, Styer WE, Ackerman J, Salomon R, Houghton W, Creamer R, Gordon DT, Hogenhout SA: Maize fine streak virus, a New Leafhopper-Transmitted Rhabdovirus. Phytopathology 2002, 92: 1167-1174. 10.1094/PHYTO.2002.92.11.1167View ArticlePubMedGoogle Scholar
- Distéfano AJ, Conci LR, Muñoz Hidalgo M, Guzmán FA, Hopp HE, del Vas M: Sequence analysis of genome segments S4 and S8 of Mal de Rio Cuarto virus (MRCV): evidence that the virus should be a separate Fijivirus species. Arch Virol 2002, 147: 1699-1709. 10.1007/s00705-002-0840-4View ArticlePubMedGoogle Scholar
- Distéfano AJ, Conci LR, Muñoz Hidalgo M, Guzmán FA, Hopp HE, del Vas M: Sequence and phylogenetic analysis of genome segments S1, S2, S3 and S6 of Mal de Rio Cuarto virus, a newly accepted Fijivirus species. Virus Res 2003, 92: 113-121. 10.1016/S0168-1702(02)00325-8View ArticlePubMedGoogle Scholar
- Distéfano AJ, Hopp HE, del Vas M: Sequence analysis of genome segments S5 and S10 of Mal de Rio Cuarto virus (Fijivirus, Reoviridae). Arch Virol 2005, 150: 1241-1248. 10.1007/s00705-004-0477-6View ArticlePubMedGoogle Scholar
- Guzmán FA, Distéfano AJ, Arneodo JD, Hopp HE, Lenardon SL, del Vas M, Conci LR: Sequencing of the bicistronic genome segments S7 and S9 of Mal de Rio Cuarto virus (Fijivirus, Reoviridae) completes the genome of this virus. Arch Virol 2007, 152: 565-573. 10.1007/s00705-006-0864-2View ArticlePubMedGoogle Scholar
- Noda H, Kawai S, Koizumi Y, Matsui K, Zhang Q, Furukawa S, Shimomura M, Mita K: Annotated ESTs from various tissues of the brown planthopper Nilaparvata lugens: a genomic resource for studying agricultural pests. BMC Genomics 2008, 9: 117. 10.1186/1471-2164-9-117PubMed CentralView ArticlePubMedGoogle Scholar
- Xue J, Bao YY, Li Bl, Cheng YB, Peng ZY, Liu H, Xu HJ, Zhu ZR, Lou YG, Cheng JA, Zhang CX: Transcriptome Analysis of the Brown Planthopper Nilaparvata lugens . PLoS ONE 2010, 5: e14233. 10.1371/journal.pone.0014233PubMed CentralView ArticlePubMedGoogle Scholar
- Zhang F, Guo H, Zheng H, Zhou T, Zhou Y, Wang S, Fang R, Qian W, Chen X: Massively parallel pyrosequencing-based transcriptome analyses of small brown planthopper (Laodelphax striatellus), a vector insect transmitting rice stripe virus (RSV). BMC Genomics 2010, 11: 303. 10.1186/1471-2164-11-303PubMed CentralView ArticlePubMedGoogle Scholar
- Huggett J, Dheda K, Bustin S, Zumla A: Real-time RT-PCR normalisation; strategies and considerations. Genes Immun 2005, 6: 279-284. 10.1038/sj.gene.6364190View ArticlePubMedGoogle Scholar
- Bower N, Johnston I: Selection of reference genes for expression studies with fish myogenic cell cultures. BMC Molecular Biology 2009, 10: 80. 10.1186/1471-2199-10-80PubMed CentralView ArticlePubMedGoogle Scholar
- Brenndörfer M, Boshart M: Selection of reference genes for mRNA quantification in Trypanosoma brucei. Molecular and Biochemical Parasitology 2010, 172: 52-55. 10.1016/j.molbiopara.2010.03.007View ArticlePubMedGoogle Scholar
- Exposito-Rodriguez M, Borges A, Borges-Perez A, Perez J: Selection of internal control genes for quantitative real-time RT-PCR studies during tomato development process. BMC Plant Biology 2008, 8: 131. 10.1186/1471-2229-8-131PubMed CentralView ArticlePubMedGoogle Scholar
- Hornáková D, Matousková P, Kindl J, Valterová I, Pichová I: Selection of reference genes for real-time polymerase chain reaction analysis in tissues from Bombus terrestris and Bombus lucorum of different ages. Analytical Biochemistry 2010, 397: 118-120. 10.1016/j.ab.2009.09.019View ArticlePubMedGoogle Scholar
- Lord JC, Hartzer K, Toutges M, Oppert B: Evaluation of quantitative PCR reference genes for gene expression studies in Tribolium castaneum after fungal challenge. J Microbiol Methods 2010, 80: 219-221. 10.1016/j.mimet.2009.12.007View ArticlePubMedGoogle Scholar
- Radonic A, Thulke S, Bae HG, Muller M, Siegert W, Nitsche A: Reference gene selection for quantitative real-time PCR analysis in virus infected cells: SARS corona virus, Yellow fever virus, Human Herpesvirus-6, Camelpox virus and Cytomegalovirus infections. Virology Journal 2005, 2: 7. 10.1186/1743-422X-2-7PubMed CentralView ArticlePubMedGoogle Scholar
- Scharlaken B, De Graaf DC, Memmi S, Devreese B, Van Beeumen J, Jacobs FJ: Differential protein expression in the honey bee head after a bacterial challenge. Arch Insect Biochem Physiol 2007, 65: 223-237. 10.1002/arch.20179View ArticlePubMedGoogle Scholar
- Silveira ED, Alves-Ferreira M, Guimaraes LA, da Silva FR, Carneiro VT: Selection of reference genes for quantitative real-time PCR expression studies in the apomictic and sexual grass Brachiaria brizantha. BMC Plant Biol 2009, 9: 84. 10.1186/1471-2229-9-84PubMed CentralView ArticlePubMedGoogle Scholar
- Van Hiel MB, Van Wielendaele P, Temmerman L, Van Soest S, Vuerinckx K, Huybrechts R, Broeck JV, Simonet G: Identification and validation of housekeeping genes in brains of the desert locust Schistocerca gregaria under different developmental conditions. BMC Mol Biol 2009, 10: 56. 10.1186/1471-2199-10-56PubMed CentralView ArticlePubMedGoogle Scholar
- Weyrich A, Axtner J, Sommer S: Selection and validation of reference genes for real-time RT-PCR studies in the non-model species Delomys sublineatus, an endemic Brazilian rodent. Biochem Biophys Res Commun 2010, 392: 145-149. 10.1016/j.bbrc.2009.12.173View ArticlePubMedGoogle Scholar
- Zhou RX, Meng T, Meng HB, Cheng DX, Bin SY, Cheng J, Fu GH, Chu WY, Zhang JS: Selection of Reference Genes in Transcription Analysis of Gene Expression of the Mandarin Fish, Siniperca chuasti. Zoological Research 2010, 31: 141-146. 10.3724/SP.J.1141.2010.02141View ArticlePubMedGoogle Scholar
- Arneodo JD, Guzman FA, Conci LR, Laguna IG, Truol GA: Transmission features of Mal de Río Cuarto virus in wheat by its planthopper vector Delphacodes kuscheli . Ann appl Biol 2002, 141: 195-200. 10.1111/j.1744-7348.2002.tb00212.xView ArticleGoogle Scholar
- Ruijter JM, Ramakers C, Hoogaars WM, Karlen Y, Bakker O, van den Hoff MJ, Moorman AF: Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data. Nucleic Acids Res 2009, 37: e45. 10.1093/nar/gkp045PubMed CentralView ArticlePubMedGoogle Scholar
- Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F: Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 2002,3(7):RESEARCH0034.PubMed CentralView ArticlePubMedGoogle Scholar
- Andersen CL, Jensen JL, Orntoft TF: 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 2004, 64: 5245-5250. 10.1158/0008-5472.CAN-04-0496View ArticlePubMedGoogle Scholar
- Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP: Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper--Excel-based tool using pair-wise correlations. Biotechnol Lett 2004, 26: 509-515.View ArticlePubMedGoogle Scholar
- Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP: Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper - Excel-based tool using pair-wise correlations. Biotechnology Letters 2004, 26: 509-515.View ArticlePubMedGoogle Scholar
- Hu R, Fan C, Li H, Zhang Q, Fu YF: Evaluation of putative reference genes for gene expression normalization in soybean by quantitative real-time RT-PCR. BMC Molecular Biology 2009, 10: 93. 10.1186/1471-2199-10-93PubMed CentralView ArticlePubMedGoogle Scholar
- Tong Z, Gao Z, Wang F, Zhou J, Zhang Z: Selection of reliable reference genes for gene expression studies in peach using real-time PCR. BMC Molecular Biology 2009, 10: 71. 10.1186/1471-2199-10-71PubMed CentralView ArticlePubMedGoogle Scholar
- Rotenberg D, Krishna Kumar NK, Ullman DE, Montero-Astúa M, Willis DK, German TL, Whitfield AE: Variation in Tomato spotted wilt virus Titer in Frankliniella occidentalis and Its Association with Frequency of Transmission. Phytopathology 2009, 99: 404-410. 10.1094/PHYTO-99-4-0404View ArticlePubMedGoogle Scholar
- Brault V, Tanguy S, Reinbold C, Le Trionnaire G, Arneodo J, Jaubert-Possamai S, Guernec G, Tagu D: Transcriptomic analysis of intestinal genes following acquisition of pea enation mosaic virus by the pea aphid Acyrthosiphon pisum. J Gen Virol 2010, 91: 802-808. 10.1099/vir.0.012856-0View ArticlePubMedGoogle Scholar
- He C, Molen TA, Xiong X, Boiteau G, Nie X: Cytochrome c oxidase mRNA as an internal control for detection of Potato virus Y and Potato leafroll virus from single aphids by a co-amplification RT-PCR assay. Journal of Virological Methods 2006, 138: 152-159. 10.1016/j.jviromet.2006.08.007View ArticlePubMedGoogle Scholar
- Zhang X, Wang X, Zhou G: A one-step real time RT-PCR assay for quantifying rice stripe virus in rice and in the small brown planthopper (Laodelphax striatellus Fallen). Journal of Virological Methods 2008, 151: 181-187. 10.1016/j.jviromet.2008.05.024View ArticlePubMedGoogle Scholar
- Lijun C, Xizhi M, Lin K, Kejing D, Shouyuan Z, Changben L: Detecting Rice stripe virus (RSV) in the small brown planthopper (Laodelphax striatellus) with high specificity by RT-PCR. Journal of Virological Methods 2003, 112: 115-120. 10.1016/S0166-0934(03)00200-3View ArticlePubMedGoogle Scholar
- Zhang X, Zhou G, Wang X: Detection of wheat dwarf virus (WDV) in wheat and vector leafhopper (Psammotettix alienus Dahlb.) by real-time PCR. Journal of Virological Methods 2010, 169: 416-419. 10.1016/j.jviromet.2010.07.029View ArticlePubMedGoogle Scholar
- Moreno Casero A, Bertolini E, Olmos Castelló A, Cambra Alvarez M, Fereres Castiel A: Estimation of vector propensity for Lettuce mosaic virus based on viral detection in single aphids. Spanish journal of agricultural research 2007, 376.Google Scholar
- Boonham N, Smith P, Walsh K, Tame J, Morris J, Spence N, Bennison J, Barker I: The detection of Tomato spotted wilt virus (TSWV) in individual thrips using real time fluorescent RT-PCR (TaqMan). Journal of Virological Methods 2002, 101: 37-48. 10.1016/S0166-0934(01)00418-9View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.