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Selection of reference genes for real-time quantitative PCR analysis of gene expression in Glycyrrhiza glabra under drought stress

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Biologia Plantarum

Abstract

Licorice (Glycyrrhiza glabra L.) is an important medicinal plant accumulating high-value secondary metabolites. Real-time reverse transcription quantitative PCR (RT-qPCR) has become a common method for studying gene expression, and the availability of stable reference genes is a prerequisite to obtain accurate quantification of transcript abundance. Therefore, an experiment was designed to determine appropriate reference genes for gene expression studies in licorice. Based on reports in the literature and the availability of genomic sequences, eight putative reference genes were chosen. Further, the expression stabilities of these genes were evaluated in leaf and root tissues under normal and drought stress conditions using three distinct statistical algorithms including geNorm, NormFinder, and BestKeeper. Among the investigated genes, ubiquitin-conjugating enzyme E2 (UBC2), elongation factor 1 α (EF1), and actin (ACT) under normal conditions and ACT, β-tubulin (BTU), and UBC2 under drought stress conditions were the most stable genes in leaves, whereas BTU, ACT, and UBC2 under normal and drought stress conditions were identified as the most stable genes in roots. Nevertheless, the use of glyceraldehyde-3-phosphate dehydrogenase, F-box protein, and BTU have not been approved as reference genes for RT-qPCR data normalization. The findings in this study highlight the importance of the use of well-validated reference genes to the success of gene expression analysis using RT-qPCR.

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Abbreviations

ACT:

actin

BTU:

β-tubulin

Cq:

quantification cycle

CV:

coefficient of variation

EF1:

elongation factor 1 α

FBP:

F-box protein

GAPDH:

glyceraldehyde-3-phosphate dehydrogenase

HIS3:

histone H3

M:

expression stability

RT-qPCR:

reverse transcription quantitative polymerase chain reacion

UBC2:

ubiquitin-conjugating enzyme E2

References

  • Andersen, C.L., Jensen, J.L., Orntoft, T.F.: Normalization of quantitative real-time 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, 2004.

    Article  CAS  PubMed  Google Scholar 

  • Asl, M.N., Hosseinzadeh, H.: Review of pharmacological effects of Glycyrrhiza sp. and its bioactive compounds. — Phytother. Res. 22: 709–724, 2008.

    Article  CAS  PubMed  Google Scholar 

  • Barsalobres-Cavallari, C.F., Severino, F.E., Maluf, M.P., Maia, I.G.: Identification of suitable internal control genes for expression studies in Coffea arabica under different experimental conditions. — BMC mol. Biol. 10: 1, 2009.

    Article  PubMed  PubMed Central  Google Scholar 

  • Bookout, A.L., Cummins, C.L., Mangelsdorf, D.J., Pesolak, J.M., Kramerm, M.F.: High-throughput real-time quantitative reverse-transcription PCR. - Curr. Protocols mol. Biol. 73: 15.8:15.8.1–15.8.28, 2006.

  • Boratyn, G.M., Camacho, C., Cooper, P.S., Coulouris, G., Fong, A., Ma, N., Madden, T.L., Matten, W.T., McGinnis, S.D., Merezhuk, Y., Raytselis, Y., Sayers, E.W., Tao, T., Ye, J., Zaretskaya, I.: BLAST: a more efficient report with usability improvements. - Nucl.. Acids Res. 41: W29–W33, 2013.

    Article  PubMed  PubMed Central  Google Scholar 

  • Bustin, S.A., Nolan, T.: Pitfalls of Quantitative real-time reverse-transcription polymerase chain reaction. — J. Biomol. Technol. 15: 155–166, 2004.

    Google Scholar 

  • Condori, J., Nopo-Olazabal, C., Medrano, G., Medina-Bolivar, F.: Selection of reference genes for qPCR in hairy root cultures of peanut. — BMC Res. Notes 4: 392, 2011.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Cui, S.J., He, Q.L., Chen, Y., Huang, M.R.: Evaluation of suitable reference genes for gene expression studies in Lycoris longituba. — J. Genet. 90: 503–506, 2011.

    Article  PubMed  Google Scholar 

  • Czechowski, T., Stitt, M., Altmann, T., Udvardi, M.K., Scheible, W.R.: Genome wide identification and testing of superior reference genes for transcript normalization in Arabidopsis. — Plant. Physiol. 139: 5–17, 2005.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • De Almeida, M.R., Ruedell, C.M., Ricachenevsky, F.K., Sperotto, R.A., Pasquali, G., Fett-Neto A.G.: Reference gene selection for quantitative reverse transcriptionpolymerase chain reaction normalization during in vitro adventitious rooting in Eucalyptus globules Labill. — BMC. mol. Biol. 11: 73, 2010.

    Article  PubMed  PubMed Central  Google Scholar 

  • Dheda, K., Huggett, J.F., Chang, J.S., Kim, L.U., Bustin, S.A., Johnson, M.A., Rook, G.A., Zumla, A.: The implications of using an inappropriate reference gene for real-time reverse transcription PCR data normalization. — Anal. Biochem. 344: 141–143, 2005.

    Article  CAS  PubMed  Google Scholar 

  • Die, J.V., Roman, B., Nadal, S., Gonzalez-Verdejo, C.I.: Evaluation of candidate reference genes for expression studies in Pisum sativum under different experimental conditions. — Planta 232: 145–153, 2010.

    Article  CAS  PubMed  Google Scholar 

  • Farajalla, M.R., Gulick, P.J.: The α-tubulin gene family in wheat (Triticum aestivum L.) and differential gene expression during cold acclimation. — Genome. 50: 502–510, 2007.

    Article  CAS  Google Scholar 

  • Gachon, C., Mingam, A., Charrier, B.: Real-time PCR: what relevance to plant studies. — J. exp. Bot. 55: 1445–1454, 2004.

    Article  CAS  PubMed  Google Scholar 

  • Galli, V., Borowski, J.M., Perin, E.C., Da Silva Messias, R., Labonde, J., Dos Santos Pereira, I., Dos Anjos Silva, S.D., Rombaldi, C.V.: Validation of reference genes for accurate normalization of gene expression for real time-quantitative PCR in strawberry fruits using different cultivars and osmotic stresses. — Gene 554: 205–214, 2015.

    Article  CAS  PubMed  Google Scholar 

  • Guo, J.L., Ling, H., Wu, Q.B., Xu, L.P., Que, Y.X.: The choice of reference genes for assessing gene expression in sugarcane under salinity and drought stresses. — Sci. Rep. 4: 7042, 2014.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Gutierrez, L., Mauriat, M., Guenin, S., Pelloux, J., Lefevre, J.F., Louvet, R., Rusterucci, C., Moritz, T., Guerineau, F., Bellini, C., Van Wuytswinkel, O.: The lack of a systematic validation of reference genes: a serious pitfall undervalued in reverse transcription-polymerase chain reaction (RTPCR) analysis in plants. — Plant. biotechnol. J. 6: 609–618, 2008.

    Article  CAS  PubMed  Google Scholar 

  • Hansen, U., Seufert, G.: Terpenoid emission from Citrus sinensis (L.) Osbeck under drought stress. — Phys. Chem. Earth. 24: 681–687, 1999.

    Article  Google Scholar 

  • Hayashi, H., Huang, P., Kirakosyan, A., Inoue, K., Hiraoka, N., Ikeshiro, Y,, Kushiro, T., Shibuya, M., Ebizuka, Y.: Cloning and characterization of a cDNA encoding β-amyrin synthase involved in glycyrrhizin and soyasaponin biosyntheses in licorice. — Biol. pharm. Bull. 24: 912–916, 2001.

    Article  CAS  PubMed  Google Scholar 

  • Hayashi, H., Huang, P., Takada, S., Obinata, M., Inoue, K., Shibuya, M., Ebizuka, Y.: Differential expression of three oxidosqualene cyclase mRNAs in Glycyrrhiza glabra. — Biol. Pharm. Bull. 27: 1086–1092, 2004.

    Article  CAS  PubMed  Google Scholar 

  • Hayashi, H,, Sudo, H.: Economic importance of licorice. — Plant. Biotechnol. 26: 101–104, 2009

    Article  CAS  Google Scholar 

  • Hellemans, J., Mortier, G., De Paepe, A., Speleman, F., Vandesompele, J.: - qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. - Genome. Biol. 8: R19, 2007.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hoenemann, C., Hohe, A.: Selection of reference genes for normalization of quantitative real-time PCR in cell cultures of Cyclamen persicum. — Electron. J. Biotechnol. 14: 12–13, 2011.

    Google Scholar 

  • Hu, R., Fan, C., Li, H., Zhang, Q., Fu, Y.F. Evaluation of putative reference genes for gene expression normalization in soybean by quantitative real-time RT-PCR. - BMC mol. Biol. 10: 93, 2009.

    Article  PubMed  PubMed Central  Google Scholar 

  • Huis, R., Hawkins, S., Neutelings, G.: Selection of reference genes for quantitative gene expression normalization in flax (Linum usitatissimum L.). — BMC Plant. Biol. 10: 71, 2010.

    Article  PubMed  PubMed Central  Google Scholar 

  • Janska, A., Hodek, J., Svoboda, P., Zamecnik, J., Prasil, I.T., Vlasakova, E., Milella, L., Ovesna, J.: The choice of reference gene set for assessing gene expression in barley (Hordeum vulgare L.) under low temperature and drought stress. — Mol. Genet. Genomics 288: 639649, 2013.

    Article  Google Scholar 

  • Jarosova, J., Kundu, J.: Validation of reference genes as internal control for studying viral infections in cereals by quantitative real-time RT-PCR. — BMC Plant. Biol. 10: 146–154, 2010.

    Article  PubMed  PubMed Central  Google Scholar 

  • Karlen, Y., Mcnair, A., Perseguers, S., Mazza, C., Mermod, N.: Statistical significance of quantitative PCR. — BMC Bioinformatics. 8: 131, 2007.

    Article  PubMed  PubMed Central  Google Scholar 

  • Kozera, B., Rapacz, M.: Reference genes in real-time PCR. — J. appl. Genet. 54: 391–406, 2013.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Le, D.T., Aldrich, D.L., Valliyodan, B., Watanabe, Y., Ha, C.V., Nishiyama, R., Guttikonda, S.K., Quach, T.N., Gutierrez-Gonzalez, J.J., Tran, L.S., Nguyen, H.T.: Evaluation of candidate reference genes for normalization of quantitative rt-pcr in soybean tissues under various abiotic stress conditions. — PloS ONE 7: e46487, 2012.

    Article  Google Scholar 

  • Long, X.Y., Wang, J.R., Ouellet, T., Rocheleau, H., Wei, Y.M., Pu, Z.E., Jiang, Q.T., Lan, X.J., Zheng, Y.L.: Genome-wide identification and evaluation of novel internal control genes for Q-PCR based transcript normalization in wheat. — Plant. mol. Biol. 74: 307–311, 2010.

    Article  CAS  PubMed  Google Scholar 

  • Luo, H., Chen, S., Wan, H.J., Chen, F., Gu, C., Liu, Z.: Candidate reference genes for gene expression studies in water lily. — Anal. Biochem. 404: 100–102, 2010.

    Article  CAS  PubMed  Google Scholar 

  • Marino, E.R., Borges, A.A., Perez, A.B., Perez, J.A.: Selection of internal control genes for quantitative real-time RT-PCR studies during tomato development process. — BMC Plant. Biol. 8: 131, 2008.

    Article  Google Scholar 

  • Marum, L., Miguel, A., Ricardo, C.P., Miguel, C.: Reference gene selection for quantitative real-time PCR normalization in Quercus suber. — PloS ONE 7: e35113, 2012.

    Article  Google Scholar 

  • McDowell, J.M., Huang, S., McKinney, E.C., An. Y.Q., Meagher, R.B.: Structure and evolution of the actin gene family in Arabidopsis thaliana. — Genetics. 142: 587–602, 1996.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Obolentseva, G.V., Litvinenko, V.I., Ammosov, A.S.: Pharmacological and therapeutic properties of licorice preparations (a review). — Pharm. Chem. J. 33: 24–31, 1999.

    Article  Google Scholar 

  • Paolacci, A.R., Tanzarella, O.A., Porceddu, E., Ciaffi, M.: Identification and validation of reference genes for quantitative RT-PCR normalization in wheat. — BMC mol. Biol. 10: 11, 2009.

    Article  PubMed  PubMed Central  Google Scholar 

  • Pfaffl, M.W.: A new mathematical model for relative quantification in real-time RT-PCR. — Nucl. Acids Res. 29: 2002–2007, 2001.

    Article  Google Scholar 

  • Pfaffl, M.W.: Quantification strategies in real-time PCR. - In: Bustin, S.A. (ed.): The Real-Time PCR Encyclopedia A–Z of Quantitative PCR. Pp. 87–120. International University Line, La Jolla 2004.

    Google Scholar 

  • Pfaffl, M.W., Tichopad, A., Prgomet, C., Neuvians, T.P.: Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: bestkeeper excel-based tool using pair-wise correlations. — Biotechnol. Lett. 26: 509–515, 2004.

    Article  CAS  PubMed  Google Scholar 

  • Piotr, C., Sacchi, N.: The single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction: twenty-something years on. — Nat. Protocols 1: 581–585, 2006.

    Article  Google Scholar 

  • Radonic, A., Thulke, S., Mackay, I.M., Landt, O., Siegert, W., Nitsche, A.: Guideline to reference gene selection for quantitative real-time PCR. — Biochem. biophys. Res. Commun. 313: 856–862, 2004.

    Article  CAS  PubMed  Google Scholar 

  • Rebouças, E.D.L., Costa, J.J.D.N., Passos, M.J., Passos, J.R.D.S., Hurk, R.V.D., Silva, J.R.V.: Real time PCR and importance of housekeepings genes for normalization and quantification of mRNA expression in different tissues. — Braz. Arch. Biol. Technol. 56: 143–154, 2013.

    Article  Google Scholar 

  • Reid, K.E., Olsson, N., Schlosser, J., Peng, F., Lund, S.T.: An optimized grapevine RNA isolation procedure and statistical determination of reference genes for real-time RTPCR during berry development. — BMC Plant. Biol. 6: 27, 2006.

    Article  PubMed  PubMed Central  Google Scholar 

  • Schmidt, G.W., Delaney, S.K.: Stable internal reference genes for normalization of real-time RT-PCR in tobacco (Nicotiana tabacum) during development and abiotic stress. — Mol. Genet. Genomics 283: 233–241, 2010.

    Article  CAS  PubMed  Google Scholar 

  • Schmittgen, T.D., Lee, E.J., Jiang, J.: High-throughput real-time PCR Methods. — Mol. Biol. 429: 89–98, 2008.

    CAS  Google Scholar 

  • Selmar, D., Kleinwachter, M.: Influencing the product quality by deliberately applying drought stress during the cultivation of medicinal plants. — Ind. Crop Prod. 42: 558–566, 2013.

    Article  CAS  Google Scholar 

  • Seki, H., Ohyama, K., Sawai, S., Mizutani, M., Ohnishi, T., Sudo, H., Akashi, T., Aoki, T., Saito, K., Muranaka, T.: Licorice β-amyrin 11-oxidase, a cytochrome P450 with a key role in the biosynthesis of the triterpene sweetener glycyrrhizin. — Proc. nat. Acad. Sci. USA. 105: 14204–14209, 2008.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Seki, H., Sawai, S., Ohyama, K., Mizutani, M., Ohnishi, T., Sudo, H., Fukushima, E.O., Akashi, T., Aoki, T., Saito, K., Muranaka, T.: Triterpene functional genomics in licorice for identification of CYP72A154 involved in the biosynthesis of glycyrrhizin. — Plant Cell 23: 4112–4123, 2011.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Shabani, L., Ehsanpour, A.A., Esmaeili, A.: Assessment of squalene synthase and beta-amyrin synthase gene expression in licorice roots treated with methyl jasmonate and salicylic acid using real-time qPCR. — Russ. J. Plant. Physiol. 57: 480–484, 2010.

    Article  CAS  Google Scholar 

  • Silva, R.L.O., Silva, M.D., Neto, J.R.C.F., De Nardi, C.H., Chabregas, S.M., Burnquist, W.L., Kah, G., Benko-Iseppon, A.M., Akio Kido, E.: Validation of novel reference genes for reverse transcription quantitative real-time PCR in drought-stressed sugarcane. — Sci. World J. 2014: 357052, 2014.

    Google Scholar 

  • Tian, C., Jiang, Q., Wang, F., Wang, G.L., Xu, Z.S., Xiong, A.S.: Selection of suitable reference genes for qPCR normalization under abiotic stresses and hormone stimuli in carrot leaves. — PLoS ONE 10: e0117569, 2015.

    Google Scholar 

  • Thellin, O., Zorzi, W., Lakaye, B., Borman, D.B., Coumans, B., Hennen, G., Grisar, T., Igout, A., Heinen, E.: Housekeeping genes as internal standards: use and limits. — J. Biotechnol. 75: 291–295, 1999.

    Article  CAS  PubMed  Google Scholar 

  • Untergrasser, A., Cutcutache, I., Koressaar, T., Ye, J., Faircloth, B.C., Remm, M., Rozen, S.G.: Primer3 - new capabilities and interfaces. — Nucl. Acids Res. 40: e115, 2012.

    Article  Google Scholar 

  • Udvardi, M.K., Czechowski, T., Scheible, W.R.: Eleven golden rules of quantitative RT-PCR. — Plant. Cell. 7: 1736–1737, 2008.

    Article  Google Scholar 

  • Vallone, P.M., Butler, J.M.: AutoDimer: a screening tool for primer-dimer and hairpin structures. — Biotechniques 37: 226–231, 2004.

    CAS  PubMed  Google 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. 3: 0034.1-0034.11, 2002.

  • Zhang, L., He, L.L., Fu, Q.T., Xu, Z.F.: Selection of reliable reference genes for gene expression studies in the biofuel plant Jatropha curcas using real-time quantitative PCR. — Int. J. mol. Sci. 14: 24338–24354, 2013.

    Article  PubMed  PubMed Central  Google Scholar 

  • Zhuang, H., Fu, Y., He, W. Wang, L., Wei, Y.: Selection of appropriate reference genes for quantitative real-time PCR in Oxytropis ochrocephala Bunge using transcriptome datasets under abiotic stress treatments. — Front. Plant Sci. 6: 475, 2015.

    Article  PubMed  PubMed Central  Google Scholar 

  • Zhu, J., Zhang, L., Li, W., Han, S., Yang, W., Qi, L.: Reference gene selection for quantitative real-time PCR normalization in Caragana intermedia under different abiotic stress conditions. - PloS ONE 8: e531968–e53196, 2013.

    Google Scholar 

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Correspondence to A. Maroufi.

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Acknowledgments: This study was financially supported by the University of Kurdistan, Sanandaj, Iran.

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Maroufi, A. Selection of reference genes for real-time quantitative PCR analysis of gene expression in Glycyrrhiza glabra under drought stress. Biol Plant 60, 645–654 (2016). https://doi.org/10.1007/s10535-016-0601-y

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  • DOI: https://doi.org/10.1007/s10535-016-0601-y

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