Abstract
Quantitative PCR (qPCR) is a robust technology for comparing the expression profiles of target genes, however the data produced need normalization with appropriate reference genes. The purpose of this study was to evaluate the expression stability of eight candidate reference genes (EF1A 1a1, EF1A 2a, EF1A 2b, EF1B, ACT11, UKN 1, ACT and SKIP 16) for qPCR assays in soybean leaves under fungus (Cercospora kikuchii) infection and treatments with salicylic and jasmonic acids. Four programs, GeNorm, NormFinder, BestKeeper, and RefFinder were used to evaluate the expression stability. The leaves were treated according the following conditions: 1) infected with Cercospora kikuchii (CK); (2) treated with salicylic acid (SA); (3) treated with SA and infected with C. kikuchii; (4) treated with jasmonic acid (JA); and (5) treated with JA and infected with C. kikuchii. For all studied conditions, GeNorm analyses revealed that combinations of six genes were always needed for gene expression normalization. Three EF1A genes (EF1A 2a, EF1A 1a1 and EF1A 2b) were the most stable in all tested conditions and then, they were always included in gene combinations. The other three genes varied according the different conditions. In analyses with other programs, at least two EF1A genes were often ranked among the three best stable genes. The expression of a PR3 (class I chitinase) gene was used to validate the reference genes across the total samples. Our results provide a shortlist of reference genes to normalize qPCR assays in soybean under CK infection and treatments with SA and JA.
Similar content being viewed by others
References
Andersen CL, Jensen JL, Orntoft TF. (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. PMID: 15289330
Bansal R, Mittapelly P, Cassone BJ, Mamidala P, Redinbaugh MG, Michel A (2015) Recommended reference genes for quantitative PCR Analysis in soybean have variable stabilities during diverse biotic stresses. PLoS one 10(8):e0134890
Bustin SA (2002) Quantification of mRNA using real-time reverse transcription PCR (RT-PCR): trends and problems. J Mol Endocrinol 29:23–29
Bustin SA, Benes V, Garson JA, Huggett J, Hellemms J, Kubista M (2009) The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55:611–622
Chai C, Lin Y, Shen D, Wu Y, Li H, Dou D (2013) Identification and functional characterization of the soybean GmaPPO12 promoter conferring Phytophthora sojae induced expression. PLoS one 8:e67670
Chandna R, Augustine R, Bisht NC (2012) Evaluation of candidate reference genes for gene expression normalization in Brassica juncea using real time quantitative RT-PCR. PLoS one 7:e36918
Expósito-Rodríguez M, Borges AA, Borges-Pérez A, Pérez JÁ (2008) Selection of internal control genes for quantitative real-time RT-PCR studies during tomato development process. BMC Plant Biol 8:131
Fan C, Ma J, Guo Q, Li X, Wang H, Lu M (2013) Selection of reference genes for quantitative real-time PCR in bamboo (Phyllostachys edulis). PLoS one 8:e56573
Ginzinger DG (2002) Gene quantification using real-time quantitative PCR: an emerging technology hits the mainstream. Exp Hematol 30:503–512
Grossi-de-Sá MF, Pelegrini PB, Fragoso RR (2011) Genetically modified soybean for insect-pest and disease control. In: Sudaric A (ed) Soybean - molecular aspects of breeding, 1st edn, vol 4. In Tech, Brazil, pp. 429–452
Gutierrez L, Mauriat M, Guénin S, Pelloux J, Lefebvre JF, Louvet R, Rusterucci C, Moritz T, Guerineau F. Bellini C, Van Wuytswinkel O (2008) The lack of a systematic validation of reference genes: a serious pitfall undervalued in reverse transcription-polymerase chain reaction (RT-PCR) analysis in plants. Plant Biotechnol J 6:609–618
Hartman GL, Sinclair JB, Rupe JC (1999) Compendium of soybean diseases. American Phytopathological Society, St. Paul, MN
Hoagland DR, Arnon DI (1950) The water culture method for growing plants without soil. California Agricultural Experiment Station Circular 347:1–32
Hu R, Fan C, Li H, Zhang Q, Fu YF (2009) Evaluation of putative reference genes for gene expression normalization in soybean by quantitative real-time RT-PCR. BMC Mol Biol 10:93–102
Jacquard S, Veneault-Fourrey C, Delaruelle C, Frey P, Martin F, Duplessis S (2011) Validation of Melampsora larici-populina reference genes for in planta RT-quantitative PCR expression profiling during time-course infection of poplar leaves. Physiol Mol Plant Pathol 3:106–112. doi:10.1016/j.pmpp.2010.10.003
Jian B, Liu B, Bi Y, Hou W, Wu C, Han T (2008) Validation of internal control for gene expression study in soybean by quantitative real-time PCR. BMC Mol Biol 9:59
Jurczyk B, Pociecha E, Janeczko A, Paczyński R, Rapacz M (2014) Assessment of candidate reference genes for the expression studies with brassinosteroids in Lolium perenne and Triticum aestivum. J Plant Physiol 16:1541–1544
Kuma KM, Lopes-Caitar VS, Romero CCT, Silva SMH, Kuwahara MKM, Carvalho CCG, Abdelnoor RV, Dias WP, Marcelino-Guimarães FC (2015) A high efficient protocol for soybean root transformation by agrobacterium rhizogenes and most stable reference genesfor RT-qPCR analysis. Plant Cell Rep 34:1987–2000
Kunkel BN, Brooks DM (2002) Cross talk between signaling pathways in pathogen defense. Curr Opin Plant Biol 5:325–331
Le DT, Aldrich DL, Valliyodan B, Watanabe Y, Ha CV, Nishiyama R, Guttikonda SK, Quach TN, Gutierrez-Gonzales JJ, Tran L-SP, Nguyen HT (2012) Evaluation of candidate reference genes for normalization of quantitative RT-PCR in soybean tissues under various abiotic stress conditions. PLoS one 7:e46487
Li Q, Fan C-M, Zhang X-M, Fu Y-F (2012) Validation of reference genes for real-time quantitative PCR normalization in soybean developmental and germinating seeds. Plant Cell Rep 31:1789–1798
Libault M, Thibivilliers S, Bilgin DD, Radwan O, Benitez M, Clough SJ, Stacey G (2008) Identification of four soybean reference genes for gene expression normalization. The Plant Genome 1:44–54
Ma S, Niu H, Liu C, Zhang J, Hou C, Wang D (2013) Expression stabilities of candidate reference genes for RT-qPCR under different stress conditions in soybean. PLoS ONE10:e75271
Marcolino-Gomes J, Rodrigues FA, Fuganti-Pagliarini R, Nakayama TJ, Ribeiro Reis R, Bouças Farias JR, et al. (2015) Transcriptome-wide identification of reference genes for expression analysis of soybean responses to drought stress along the day. PLoS one 10(9):e0139051
Miranda VJ, Coelho RR, Viana AAB, Neto OBO, Grossi de Sá MF, Fragoso RR (2013) Validation of reference genes aiming accurate normalization of qPCR data in soybean upon nematode parasitism and insect attack. BMC Res Notes 6:196
Neto LB, de Oliveira RR, Wiebke-Strohm B, Bencke M, Weber RL, Cabreira C, Abdelnoor RV, Marcelino FC, Zanettini MH, Passaglia LM (2013) Identification of the soybean HyPRP family and specific gene response to Asian soybean rust disease. Genet Mol Biol 36:214–224
Paolacci AR, Tanzarella OA, Porceddu E, Ciaffi M (2009) Identification and validation of reference genes for quantitative RT-PCR normalization in wheat. BMC Mol Biol 10:11
Pfaffl MW (2004) Quantification strategies in real-time PCR. In Bustin SA (ed) A-Z of quantitative PCR, 2nd edn. International University Line, La Jolla, CA, pp 87–112
Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP (2004) 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
Pieterse CMJ, Van Loon LC (1999) Salicylic acid-independent plant defence pathways. Trends Plant Sci 4:52–58
Rocha AJ, Monteiro-Júnior JE, Freire JEC, Sousa AJS, Fonteles CSR (2015) Real time PCR: the use of reference genes and essential rules required to obtain normalisation data reliable to quantitative Gene Expression. J Mol Biol Res 5:45–55
Sambrook J, Russell DW (2001) Molecular cloning: a laboratory manual. Cold Spring Harbor Laboratory Press, New York
Saraiva KDC, Melo DF, Morais VD, Vasconcelos IM, Costa JH (2014) Selection of suitable soybean EF1α genes as internal controls for real-time PCR analyses of tissues during plant development and under stress conditions. Plant Cell Rep 33:1453–1465
Schmidt GW, Delaney SK (2010) Stable internal reference genes for normalization of real-time RT-PCR in tobacco (Nicotiana tabacum) during development and abiotic stress. Mol Gen Genomics 83:233–241
Sticher L, Mauch-Mani B, Métraux JP (1997) Systemic acquired resistance. Annu Rev Phytopathol 35:235–270
Subramanyam K, Arun M, Mariashibu TS, Theboral J, Rajesh M, Singh NK, Manickavasagam M, Ganapathi A (2012) Overexpression of tobacco osmotin (Tbosm) in soybean conferred resistance to salinity stress and fungal infections. Planta 236:1909–1925
Upchurch RG, Ramirez ME (2010) Defense-related gene expression in soybean leaves and seeds inoculated with Cercospora kikuchii and Diaporthe phaseolorum var. meridionalis. Physiol Mol Plant P 75:64–70
Van Guilder HD, Vrana KE, Freeman WM (2008) Twenty-five years of quantitative PCR for gene expression analysis. Biotechniques 44:619–626
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 Biol 3:RESEARCH0034
Vidal RO, Nascimento LC, Mondego JMC, Pereira GAG, Carazzolle MF (2012) Identification of SNPs in RNA-seq data of two cultivars of Glycine max (soybean) differing in drought resistance. Genet Mol Biol 35:331–334
Wang Y, Yu K, Poysa V, Shi C, Zhou Y (2011) Selection of reference genes for normalization of qRT-PCR analysis of differentially expressed genes in soybean exposed to cadmium. Mol Biol Rep 39:1585–1594
Zhao J, Zhang Y, Bian X, Lei J, Sun J, Guo N (2013) A comparative proteomics analysis of soybean leaves under biotic and abiotic treatments. Mol Biol Rep 40:1553–1562
Acknowledgments
This work was supported by National Council for Scientific and Technological Development (CNPq), Ceara State Foundation for the Support of Scientific and Technological Development (FUNCAP) and Coordination of Improvement of Higher Education (CAPES), Brazil.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that have no conflict of interest.
Electronic supplementary material
ESM 1
(DOCX 449 kb)
Rights and permissions
About this article
Cite this article
Costa, J.H., Saraiva, K.D.C., Morais, V.D. et al. Reference gene identification for real-time PCR analyses in soybean leaves under fungus (Cercospora kikuchii) infection and treatments with salicylic and jasmonic acids. Australasian Plant Pathol. 45, 191–199 (2016). https://doi.org/10.1007/s13313-016-0403-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13313-016-0403-x