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Reference gene selection and evaluation for expression analysis using qRT-PCR in Galeruca daurica (Joannis)

Published online by Cambridge University Press:  07 November 2016

Y. Tan ,
X.-R. Zhou  and
B.-P. Pang
Y. Tan
Affiliation:
Research Center for Grassland Entomology, Inner Mongolian Agricultural University, Hohhot, China
X.-R. Zhou
Affiliation:
Research Center for Grassland Entomology, Inner Mongolian Agricultural University, Hohhot, China
B.-P. Pang*
Affiliation:
Research Center for Grassland Entomology, Inner Mongolian Agricultural University, Hohhot, China
*
*Author for correspondence Phone: +86 0471 4318472 E-mail: pangbp@imau.edu.cn
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Abstract

Quantitative real-time PCR (qRT-PCR) has been used extensively to analyze gene expression and decipher gene function. To obtain the optimal and stable normalization factors for qRT-PCR, selection and validation of reference genes should be conducted in diverse conditions. In insects, more and more studies confirmed the necessity and importance of reference gene selection. In this study, eight traditionally used reference genes in Galeruca daurica (Joannis) were assessed, using qRT-PCR, for suitability as normalization genes under different experimental conditions using four statistical programs: geNorm, Normfinder, BestKeeper and the comparative ΔC t method. The genes were ranked from the most stable to the least stable using RefFinder. The optimal suite of recommended reference genes was as follows: succinate dehydrogenase (SDHA) and tubulin-alpha (TUB-α) for temperature-treated larvae; ribosomal protein L32, SDHA and glutathione S-transferase were best for all developmental stages; ACT and TUB-α for male and female adults; SDHA and TUB-α were relatively stable and expressed in different tissues, both diapause and non-diapause adults. Reference gene evaluation was validated using expression of two target genes: the P450 CYP6 gene and the heat shock protein gene Hsp70. These results confirm the importance of custom reference gene selection when studies are conducted under diverse experimental conditions. A standardized qRT-PCR analysis procedure for gene functional studies is provided that could be useful in studies on other insect species.

Keywords

reference geneqRT-PCRnormalizationGaleruca daurica

Information

Type
Research Papers
Information
Bulletin of Entomological Research , Volume 107 , Issue 3 , June 2017 , pp. 359 - 368
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Copyright
Copyright © Cambridge University Press 2016 

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References

Andersen, C.L., Jensen, J.L. & Ørntoft, T.F. (2004) Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Research 64, 5245–5250.Google Scholar
Bustin, S.A., Benes, V., Garson, J.A., 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. Clinical Chemistry 55, 611–622.Google Scholar
De Boer, M., De Boer, T., Marien, J., Timmermans, M., Nota, B., Straalen, N.V., Ellers, J. & Roelofs, D. (2009) Reference genes for QRT-PCR tested under various stress conditions in Folsomia candida and Orchesella cincta (Insecta, Collembola). BMC Molecular Biology 10, 5.Google Scholar
Derveaux, S., Vandesompele, J. & Hellemans, J. (2010) How to do successful gene expression analysis using real-time PCR. Methods 50, 227–230.Google Scholar
Ferguson, B.S., Nam, H., Hopkins, R.G. & Morrison, R.F. (2010) Impact of reference gene selection for target gene normalization on experimental outcome using real-time qRT-PCR in adipocytes. PLoS ONE 5(12), e15208.Google Scholar
Fu, W., Xie, W., Zhang, Z., Wang, S., Wu, Q., Liu, Y., Zhou, X.M., Zhou, X.G. & Zhang, Y.J. (2013) Exploring valid reference genes for quantitative real-time PCR analysis in Plutella xylostella(Lepidoptera: Plutellidae). Intentional Journal of Biological Science 9(8), 792–802.Google Scholar
Gao, J.C., Zhou, X.R., Pang, B.P., Bao, X., Luo, J.P. & Erdeng, Q. (2015) Effects of low temperature on the survivorship and development of overwintering eggs of Galeruca daurica (Coleoptera: Chrysomelidae). Acta Entomol Sinica 58(8), 881–886.Google Scholar
Hiel, M.B.V., Wielendaele, P.V., Temmerman, L., Soest, S.V., Vuerinckx, K., Huybrechts, R., Broeck, J.V. & Simonet, G. (2009) Identification and validation of housekeeping genes in brains of the desert locust Schistocerca gregariaunder different developmental conditions. BMC Molecular Biology 10, 56.Google Scholar
Hoogewijs, D., Houthoofd, K., Matthijssens, F., Vandesompele, J. & Vanfleteren, J.R. (2008) Selection and validation of a set of reliable reference genes for quantitative sod gene expression analysis in C. elegans . BMC Molecular Biology 9, 9.CrossRefGoogle ScholarPubMed
Huis, R., Hawkins, S. & Neutelings, G. (2010) Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.). BMC Plant Biology 10, 71.CrossRefGoogle ScholarPubMed
Li, R.M., Xie, W., Wang, S.L., Wu, Q.J., Yang, N.N., Yang, X., Pan, H.P., Zhou, X.M., Bai, L.Y., Xu, B.Y., Zhou, X.G. & Zhang, Y.J. (2013) Reference Gene selection for qRT-PCR analysis in the sweetpotato whitefly, Bemisia tabaci (Hemiptera: Aleyrodidae). PLoS ONE 8(1), e53006.Google Scholar
Liang, P., Guo, Y.J., Zhou, X.G. & Gao, X.W. (2014) Expression profiling in Bemisia tabaci under insecticide treatment: indicating the necessity for custom reference gene selection. PLoS ONE 9(1), 1–8.Google ScholarPubMed
Lin, Y.L. & Lai, Z.X. (2010) Reference gene selection for qPCR analysis during somatic embryogenesis in longan tree. Plant Science. 178, 359–365.Google Scholar
Lord, J.C., Hartzer, K., Toutges, M. & Oppert, B. (2010) Evaluation of quantitative PCR reference genes for gene expression studies in Tribolium castaneum after fungal challenge. Journal of Microbiological Methods 80, 219–221.Google Scholar
Lu, Y.H., Yuan, M., Gao, X.W., Kang, T.H., Zhan, S., Wan, H. & Li, J.H. (2013) Identification and validation of reference genes for gene expression analysis using quantitative PCR in Spodoptera litura (Lepidoptera: Noctuidae). PLoS ONE 8(7), 1–9.Google Scholar
Pfaffl, M.W. (2001) A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acid Res 29, e45.Google Scholar
Pfaffl, M.W., Tichopad, A., Prgomet, C. & Neuvians, T.P. (2004) Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper-Excel-based tool using pair-wise correlations. Biotechnology Letters 26, 509–551.Google Scholar
Ponton, F., Chapuis, M., Pernice, M., Sword, G.A. & Simpson, S.J. (2011) Evaluation of potential reference genes for reverse transcription-qPCR studies of physiological responses in Drosophila melanogaster . Journal of Insect Physiology 57, 840–850.CrossRefGoogle ScholarPubMed
Radonic, A., Thulke, S., Mackay, I., Landt, O., Siegert, W. & Nitsche, A. (2004) Guideline to reference gene selection for quantitative real-time PCR. Biochemical Biophysical Research Communications 313, 856–862.Google Scholar
Scharlaken, B., De Graaf, D.C., Goossens, K., Brunain, M., Peelman, L.J. & Jacobs, F.J. (2008) Reference gene selection for insect expression studies using quantitative real-time PCR: the head of the honeybee, Apis mellifera, after a bacterial challenge. Journal of Insect Science 8, 33.Google Scholar
Shen, G.M., Jiang, H.B., Wang, X.N. & Wang, J.J. (2010 a) Evaluation of endogenous references for gene expression profiling in different tissues of the oriental fruit fly Bactrocera dorsalis (Diptera: Tephritidae). BMC Molecular Biology 11, 76–85.Google Scholar
Shen, Y.M., Li, Y., Ye, F., Wang, F.F., Lu, W.G. & Xing, X. (2010 b) Identification of suitable reference genes for measurement of gene expression in human cervical tissues. Analytical Biochemistry 405, 224–229.CrossRefGoogle ScholarPubMed
Silver, N., Best, S., Jiang, J. & Thein, S.L. (2006) Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR. BMC Molecular Biology 7, 33.CrossRefGoogle ScholarPubMed
Sun, M., Lu, M.X., Tang, X.T. & Du, Y.Z. (2015) Exploring valid reference genes for quantitative real-time PCR analysis in Sesamia inferens (Lepidoptera: Noctuidae). PLoS ONE 10(1), 1–16.Google ScholarPubMed
Teng, X., Zhang, Z., He, G., Yang, L. & Li, F. (2012) Validation of reference genes for quantitative expression analysis by real-time RT-PCR in four Lepidopteran insects. Journal of Insect Science 12, 1–17.CrossRefGoogle ScholarPubMed
Toutges, M.J., Hartzer, K., Lord, J. & Oppert, B. (2010) Evaluation of reference genes for quantitative polymerase chain reaction across life cycle stages and tissue types of Tribolium castaneum . Journal of Agricultural and Food Chemistry 58, 8948–8951.CrossRefGoogle ScholarPubMed
Udvardi, M.K., Czechowski, T. & Scheible, W.D. (2008) Eleven golden rules of quantitative RT-PCR. Plant Cell 20, 1736–1737.CrossRefGoogle ScholarPubMed
Vandesompele, J., De Preter, K., Pattyn, F., Poppe, B., Van Roy, N., De Paepe, A. & Speleman, F. (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biology 3, 1–12.Google Scholar
VanGuilder, H.D., Vrana, K.E. & Freeman, W.M. (2008) Twenty-five years of quantitative PCR for gene expression analysis. Biotechniques 44, 619–626.Google Scholar
Wang, J., Zhao, J. & Liu, Y.H. (2014) Evaluation of endogenous reference genes in Bactrocera minax (Diptera: Tephritidae). Acta Entomologica Sinica 57(12), 1375–1380.Google Scholar
Xie, F.L., Sun, G.L., Stiller, J.W. & Zhang, B.H. (2011) Genome-wide functional analysis of the cotton transcriptome by creating an integrated EST database. PLoS ONE 6, 1–12.Google Scholar
Zhang, P.F., Zhou, X.R., Pang, B.P., Chang, J., Shan, Y.M. & Zhang, Z.R. (2015 a) Microsatellite marker analysis of the genetic diversity of Galeruca daurica (Coleoptera: Chrysomelidae) populations from Inner Mongolia. Acta Entomologica Sinica 58(9), 1005–1011.Google Scholar
Zhang, S.D., An, S.H., Li, Z., Wu, F.M., Yang, Q.P., Liu, Y.C., Cao, J.J., Zhang, H.J., Zhang, Q.W. & Liu, X.X. (2015 b) Identification and validation of reference genes for normalization of gene expression analysis using qRT-PCR in Helicoverpa armigera (Lepidoptera: Noctuidae). Gene 555, 393–402.Google Scholar
Zhu, X., Yuan, M., Shakeel, M., Zhang, Y.J., Wang, S.L., Wang, X., Zhan, S., Kang, T.H. & Li, J.H. (2014) Selection and evaluation of reference genes for expression analysis using qRT-PCR in the beet armyworm Spodoptera exigua (Hbner) (Lepidoptera: Noctuidae). PLoS ONE 9(1), 1–14.Google Scholar