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Validation of reference genes for real-time quantitative PCR normalization in soybean developmental and germinating seeds

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An Erratum to this article was published on 04 August 2012

Abstract

Most of traditional reference genes chosen for real-time quantitative PCR normalization were assumed to be ubiquitously and constitutively expressed in vegetative tissues. However, seeds show distinct transcriptomes compared with the vegetative tissues. Therefore, there is a need for re-validation of reference genes in samples of seed development and germination, especially for soybean seeds. In this study, we aimed at identifying reference genes suitable for the quantification of gene expression level in soybean seeds. In order to identify the best reference genes for soybean seeds, 18 putative reference genes were tested with various methods in different seed samples. We combined the outputs of both geNorm and NormFinder to assess the expression stability of these genes. The reference genes identified as optimums for seed development were TUA5 and UKN2, whereas for seed germination they were novel reference genes Glyma05g37470 and Glyma08g28550. Furthermore, for total seed samples it was necessary to combine four genes of Glyma05g37470, Glyma08g28550, Glyma18g04130 and CYP for normalization.

Key message We identified several reference genes that stably expressed in soybean seed developmental and germinating processes.

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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

    Article  PubMed  CAS  Google Scholar 

  • Barrero JM, Talbot MJ, White RG, Jacobsen JV, Gubler F (2009) Anatomical and transcriptomic studies of the coleorhiza reveal the importance of this tissue in regulating dormancy in barley. Plant Physiol 150:1006–1021

    Article  PubMed  CAS  Google Scholar 

  • Cadman CS, Toorop PE, Hilhorst HW, Finch-Savage WE (2006) Gene expression profiles of Arabidopsis Cvi seeds during dormancy cycling indicate a common underlying dormancy control mechanism. Plant J 46:805–822

    Article  PubMed  CAS  Google Scholar 

  • Czechowski T, Stitt M, Altmann T, Udvardi MK, Scheible WR (2005) Genome-wide identification and testing of superior reference genes for transcript normalization in Arabidopsis. Plant Physiol 139:5–17

    Article  PubMed  CAS  Google Scholar 

  • Dekkers BJ, Willems L, Bassel GW, van Bolderen-Veldkamp RP, Ligterink W, Hilhorst HW, Bentsink L (2012) Identification of reference genes for RT-qPCR expression analysis in Arabidopsis and tomato seeds. Plant Cell Physiol 53:28–37

    Article  PubMed  CAS  Google Scholar 

  • Graeber K, Linkies A, Wood AT, Leubner-Metzger G (2011) A guideline to family-wide comparative state-of-the-art quantitative RT-PCR analysis exemplified with a brassicaceae cross-species seed germination case study. Plant Cell 23:2045–2063

    Article  PubMed  CAS  Google Scholar 

  • Gutierrez L, Mauriat M, Guenin 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

    Article  PubMed  CAS  Google Scholar 

  • Gutierrez-Gonzalez JJ, Guttikonda SK, Tran LS, Aldrich DL, Zhong R, Yu O, Nguyen HT, Sleper DA (2010) Differential expression of isoflavone biosynthetic genes in soybean during water deficits. Plant Cell Physiol 51:936–948

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  Google Scholar 

  • Holdsworth MJ, Bentsink L, Soppe WJ (2008) Molecular networks regulating Arabidopsis seed maturation, after-ripening, dormancy and germination. New Phytol 179:33–54

    Article  PubMed  CAS  Google Scholar 

  • Howell KA, Narsai R, Carroll A, Ivanova A, Lohse M, Usadel B, Millar AH, Whelan J (2009) Mapping metabolic and transcript temporal switches during germination in rice highlights specific transcription factors and the role of RNA instability in the germination process. Plant Physiol 149:961–980

    Article  PubMed  CAS  Google Scholar 

  • Hruz T, Wyss M, Docquier M, Pfaffl MW, Masanetz S, Borghi L, Verbrugghe P, Kalaydjieva L, Bleuler S, Laule O, Descombes P, Gruissem W, Zimmermann P (2011) RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization. BMC Genomics 12:156

    Article  PubMed  CAS  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • 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

    Article  PubMed  Google Scholar 

  • Karlen Y, McNair A, Perseguers S, Mazza C, Mermod N (2007) Statistical significance of quantitative PCR. BMC Bioinform 8:131

    Article  Google Scholar 

  • Kulcheski FR, Marcelino-Guimaraes FC, Nepomuceno AL, Abdelnoor RV, Margis R (2010) The use of microRNAs as reference genes for quantitative polymerase chain reaction in soybean. Anal Biochem 406:185–192

    Article  PubMed  CAS  Google Scholar 

  • Le BH, Wagmaister JA, Kawashima T, Bui AQ, Harada JJ, Goldberg RB (2007) Using genomics to study legume seed development. Plant Physiol 144:562–574

    Article  PubMed  CAS  Google Scholar 

  • Le BH, Cheng C, Bui AQ, Wagmaister JA, Henry KF, Pelletier J, Kwong L, Belmonte M, Kirkbride R, Horvath S, Drews GN, Fischer RL, Okamuro JK, Harada JJ, Goldberg RB (2010) Global analysis of gene activity during Arabidopsis seed development and identification of seed-specific transcription factors. Proc Natl Acad Sci USA 107:8063–8070

    Article  PubMed  CAS  Google Scholar 

  • Lee PD, Sladek R, Greenwood CM, Hudson TJ (2002) Control genes and variability: absence of ubiquitous reference transcripts in diverse mammalian expression studies. Genome Res 12:292–297

    Article  PubMed  Google Scholar 

  • Libault MT, Bilgin D, Radwan O, Benitez M, Clough SJ, Stacey G (2008) Identification of four soybean reference genes for gene expression normalization. Plant Genome 1:44

    Article  CAS  Google Scholar 

  • Linkies A, Muller K, Morris K, Tureckova V, Wenk M, Cadman CS, Corbineau F, Strnad M, Lynn JR, Finch-Savage WE, Leubner-Metzger G (2009) Ethylene interacts with abscisic acid to regulate endosperm rupture during germination: a comparative approach using Lepidium sativum and Arabidopsis thaliana. Plant Cell 21:3803–3822

    Article  PubMed  CAS  Google Scholar 

  • Narsai R, Ivanova A, Ng S, Whelan J (2010) Defining reference genes in Oryza sativa using organ, development, biotic and abiotic transcriptome datasets. BMC Plant Biol 10:56

    Article  PubMed  Google Scholar 

  • Okamoto M, Tatematsu K, Matsui A, Morosawa T, Ishida J, Tanaka M, Endo TA, Mochizuki Y, Toyoda T, Kamiya Y, Shinozaki K, Nambara E, Seki M (2010) Genome-wide analysis of endogenous abscisic acid-mediated transcription in dry and imbibed seeds of Arabidopsis using tiling arrays. Plant J 62:39–51

    Article  PubMed  CAS  Google Scholar 

  • 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

    Article  PubMed  CAS  Google Scholar 

  • Preston J, Tatematsu K, Kanno Y, Hobo T, Kimura M, Jikumaru Y, Yano R, Kamiya Y, Nambara E (2009) Temporal expression patterns of hormone metabolism genes during imbibition of Arabidopsis thaliana seeds: a comparative study on dormant and non-dormant accessions. Plant Cell Physiol 50:1786–1800

    Article  PubMed  CAS  Google Scholar 

  • Schmid M, Davison TS, Henz SR, Pape UJ, Demar M, Vingron M, Scholkopf B, Weigel D, Lohmann JU (2005) A gene expression map of Arabidopsis thaliana development. Nat Genet 37:501–506

    Article  PubMed  CAS  Google Scholar 

  • Suzuki T, Higgins PJ, Crawford DR (2000) Control selection for RNA quantitation. Biotechniques 29:332–337

    PubMed  CAS  Google Scholar 

  • 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

    Google Scholar 

  • Weitbrecht K, Muller K, Leubner-Metzger G (2011) First off the mark: early seed germination. J Exp Bot 62:3289–3309

    Article  PubMed  CAS  Google Scholar 

  • Xi W, Liu C, Hou X, Yu H (2010) MOTHER OF FT AND TFL1 regulates seed germination through a negative feedback loop modulating ABA signaling in Arabidopsis. Plant Cell 22:1733–1748

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

This work was partly supported by Transgenic program (Nos 2009ZX08009-133B, 2011ZX08009-001 and 2011ZX08004-005), the Chinese National Key Basic Research “973” Program (2010CB125906), and the National Natural Science Founds (31000680 and 31000681).

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. MOA Key Lab of Soybean Biology (Beijing), National Key Facility of Crop Gene Resource and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, People’s Republic of China

    Qing Li, Cheng-Ming Fan, Xiao-Mei Zhang & Yong-Fu Fu

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  1. Qing Li
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  2. Cheng-Ming Fan
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  3. Xiao-Mei Zhang
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  4. Yong-Fu Fu
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Correspondence to Yong-Fu Fu.

Additional information

Communicated by H. Judelson.

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Li, Q., Fan, CM., Zhang, XM. et al. Validation of reference genes for real-time quantitative PCR normalization in soybean developmental and germinating seeds. Plant Cell Rep 31, 1789–1798 (2012). https://doi.org/10.1007/s00299-012-1282-4

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  • DOI: https://doi.org/10.1007/s00299-012-1282-4

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