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Reference Gene: In-Species Universality Versus Between-Species Uniquity

  • Wentao Xu
Chapter

Abstract

Reference gene is widely used in species identification. According to gene expression level, it can be classified into two categories: the reference gene on the genome and on the transcriptome. Reference genes that related to the animals, plants, microorganisms, and genetically modified (GM) crops have been reported. This chapter has detailed and introduced the reference gene from definition, classification, identification methods, and application. The future research advances have been stated in the end.

Keywords

Reference gene Classification Identification methods Application 

Notes

Acknowledgments

This work is supported by National Science and Technology Major Project (2016ZX08012-004). Many thanks to Ying Shang and Wenjin Xiang, for their kindly help in manuscript conception and preparation.

References

  1. 1.
    Heid CA, Stevens J, Livak KJ, Williams PM. Real time quantitative PCR. Genome Res. 1996;6(10):986–94.PubMedCrossRefGoogle Scholar
  2. 2.
    Hurst CD, Knight A, Bruce IJ. PCR detection of genetically modified soya and maize in foodstuffs. Mol Breed. 1999;5(6):579–86.CrossRefGoogle Scholar
  3. 3.
    Vollenhofer S, Burg K, Schmidt J, Kroath H. Genetically modified organisms in food-screening and specific detection by polymerase chain reaction. J Agr Food Chem. 1999;47(12):5038–43.CrossRefGoogle Scholar
  4. 4.
    Wurz A, Bluth A, Zeltz P, Pfeifer C, Willmund R. Quantitative analysis of genetically modified organisms (GMO) in processed food by PCR-based methods. Food Control. 1999;10(6):385–9.CrossRefGoogle Scholar
  5. 5.
    Costa J, Mafra I, Amaral JS, Oliveira MBPP. Detection of genetically modified soybean DNA in refined vegetable oils. Eur Food Res Technol. 2010;230(6):915–23.CrossRefGoogle Scholar
  6. 6.
    Guo LH, Qiu B, Chi YW, Chen GN. Using multiple PCR and CE with chemiluminescence detection for simultaneous qualitative and quantitative analysis of genetically modified organism. Electrophoresis. 2008;29(18):3801–9.PubMedCrossRefGoogle Scholar
  7. 7.
    Yang LT, Chen JX, Huang C, Liu YH, Jia SR, Pan LW, Zhang DB. Validation of a cotton-specific gene, Sad1, used as an endogenous reference gene in qualitative and real-time quantitative PCR detection of transgenic cottons. Plant Cell Rep. 2005;24(4):237–45.PubMedCrossRefGoogle Scholar
  8. 8.
    Heide BR, Dromtorp SM, Rudi K, Heir E, Holck AL. Determination of eight genetically modified maize events by quantitative, multiplex PCR and fluorescence capillary gel electrophoresis. Eur Food Res Technol. 2008;227(4):1125–37.CrossRefGoogle Scholar
  9. 9.
    Kim JH, Kim SY, Lee H, Kim YR, Kim HY. An event-specific DNA microarray to identify genetically modified organisms in processed foods. J Agr Food Chem. 2010;58(10):6018–26.CrossRefGoogle Scholar
  10. 10.
    Chang KH, Mestdagh P, Vandesompele J, Kerin MJ, Miller N. MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer. BMC Cancer. 2010. doi: 10.1186/1471-2407-10-173.Google Scholar
  11. 11.
    Hernandez M, Duplan MN, Berthier G, Vaitilingom M, Hauser W, Freyer R, Pla M, Bertheau Y. Development and comparison of four real-time polymerase chain reaction systems for specific detection and quantification of Zea mays L. J Agr Food Chem. 2004;52(15):4632–7.CrossRefGoogle Scholar
  12. 12.
    Hupfer C, Hotzel H, Sachse K, Moreano F, Engel KH. PCR-based quantification of genetically modified Bt maize: single-competitive versus dual-competitive approach. Eur Food Res Technol. 2000;212(1):95–9.CrossRefGoogle Scholar
  13. 13.
    Huang HL, Cheng F, Wang RA, Zhang DB, Yang LT. Evaluation of four endogenous reference genes and their real-time PCR assays for common wheat quantification in GMOs detection. PloS ONE. 2013;8(9):e75850.Google Scholar
  14. 14.
    Van Ooyen AJJ, Dekker P, Huang M, Olsthoorn MMA, Jacobs DI, Colussi PA, Taron CH. Heterologous protein production in the yeast Kluyveromyces lactis. Fems Yeast Res. 2006;6(3):381–92.PubMedCrossRefGoogle Scholar
  15. 15.
    Pan LW, Yuen P, Lin L, Garcia EJ. Flip chip electrical interconnection by selective electroplating and bonding. Microsyst Technol. 2003;10(1):7–10.CrossRefGoogle Scholar
  16. 16.
    Akiyama H, Makiyama D, Nakamura K, Sasaki N, Minegishi Y, Mano J, Kitta K, Ozeki Y, Teshima R. A novel detection system for the genetically modified canola (Brassica rapa) line RT73. Anal Chem. 2010;82(23):9909–16.PubMedCrossRefGoogle Scholar
  17. 17.
    Scarth R, Tang J. Modification of Brassica oil using conventional and transgenic approaches. Crop Sci. 2006;46(3):1225–36.CrossRefGoogle Scholar
  18. 18.
    Chaouachi M, Giancola S, Romaniuk M, Laval V, Bertheau Y, Brunel D. A strategy for designing multi-taxa specific reference gene systems. example of application – ppi phosphofructokinase (ppi-PPF) used for the detection and quantification of three taxa: maize (Zea mays), cotton (Gossypium hirsutum) and rice (Oryza sativa). J Agric Food Chem. 2007;55(20):8003–10.PubMedCrossRefGoogle Scholar
  19. 19.
    Castillo AR, Gallardo MR, Maciel M, Giordano JM, Conti GA, Gaggiotti MC, Quaino O, Gianni C, Hartnell GF. Effects of feeding rations with genetically modified whole cottonseed to lactating Holstein cows. J Dairy Sci. 2004;87(6):1778–85.PubMedCrossRefGoogle Scholar
  20. 20.
    Jennings JC, Whetsell AJ, Nicholas NR, Sweeney BM, Klaften MB, Kays SB, Hartnell GF, Lirette RP, Glenn KC. Determining whether transgenic or endogenous plant DNA is detectable in dairy milk or beef organs. Bulletin Of the International Dairy Federation No 383/2003:41–46.Google Scholar
  21. 21.
    Guan QF, Wang XM, Teng D, Yang YL, Tian F, Yin QQ, Wang JH. Construction of a standard reference plasmid for detecting GM cottonseed meal. Appl Biochem Biotechnol. 2011;165(1):24–34.PubMedCrossRefGoogle Scholar
  22. 22.
    Elenis DS, Kalogianni DP, Glynou K, Ioannou PC, Christopoulos TK. Advances in molecular techniques for the detection and quantification of genetically modified organisms. Anal Bioanal Chem. 2008;392(3):347–54.PubMedCrossRefGoogle Scholar
  23. 23.
    Wang XM, Teng D, Xi D, Guan QF, Wang JH. Construction of a reference plasmid containing ten targets for the detection of genetically modified crops. Plasmid. 2013;69(1):108–13.PubMedCrossRefGoogle Scholar
  24. 24.
    Baeumler S, Wulff D, Tagliani L, Song P. A real-time quantitative PCR detection method specific to widestrike transgenic cotton (event 281-24-236/3006-210-23). J Agr Food Chem. 2006;54(18):6527–34.CrossRefGoogle Scholar
  25. 25.
    Zhang L, Wu G, Wu YH, Cao YL, Xiao L, Lu CM. The gene MT3-B can differentiate palm oil from other oil samples. J Agr Food Chem. 2009;57(16):7227–32.CrossRefGoogle Scholar
  26. 26.
    Wahler D, Schauser L, Bendiek J, Grohmann L. Next-generation sequencing as a tool for detailed molecular characterisation of genomic insertions and flanking regions in genetically modified plants: a pilot study using a rice event unauthorised in the EU. Food Anal Method. 2013;6(6):1718–27.CrossRefGoogle Scholar
  27. 27.
    Wang XH, Jiang DM, Yang DC. Fast-tracking determination of homozygous transgenic lines and transgene stacking using a reliable quantitative real-time PCR assay. Appl Biochem Biotechnol. 2015;175(2):996–1006. doi: 10.1007/s12010-014-1322-3.PubMedCrossRefGoogle Scholar
  28. 28.
    Wang C, Jiang LX, Rao J, Liu YN, Yang LT, Zhang DB. Evaluation of four genes in rice for their suitability as endogenous reference standards in quantitative PCR. J Agr Food Chem. 2010;58(22):11543–7.CrossRefGoogle Scholar
  29. 29.
    Takabatake R, Onishi M, Futo S, Minegishi Y, Noguchi A, Nakamura K, Kondo K, Teshima R, Mano J, Kitta K. Comparison of the specificity, stability, and PCR efficiency of six rice endogenous sequences for detection analyses of genetically modified rice. Food Control. 2015;50:949–55.CrossRefGoogle Scholar
  30. 30.
    Hernandez M, Esteve T, Pla M. Real-time polymerase chain reaction based assays for quantitative detection of barley, rice, sunflower, and wheat. J Agric Food Chem. 2005;53(18):7003–9.PubMedCrossRefGoogle Scholar
  31. 31.
    Wei J, Li F, Guo J, Li X, Xu J, Wu G, Zhang D, Yang L. Collaborative ring trial of the papaya endogenous reference gene and its polymerase chain reaction assays for genetically modified organism analysis. J Agric Food Chem. 2013;61(47):11363–70.PubMedCrossRefGoogle Scholar
  32. 32.
    Vautrin S, Zhang D. Real-time polymerase chain reaction assay for endogenous reference gene for specific detection and quantification of common wheat-derived DNA (Triticum aestivum L.). J AOAC Int. 2007;90(3):794–801.PubMedGoogle Scholar
  33. 33.
    Kim JH, Park SB, Roh HJ, Park S, Shin MK, Moon GI, Hong JH, Kim HY. A simplified and accurate detection of the genetically modified wheat MON71800 with one calibrator plasmid. Food Chem. 2015;176:1–6.PubMedCrossRefGoogle Scholar
  34. 34.
    Shang Y, Zhu PY, Huang KL, Liu WH, Tian WY, Luo YB, Xu WT. A peach (Prunus persica)-specific gene, Lhcb2, used as an endogenous reference gene for qualitative and real-time quantitative PCR to detect fruit products. LWT-Food Sci Technol. 2014;55(1):218–23.CrossRefGoogle Scholar
  35. 35.
    Yang LT, Pan AH, Jia JW, Ding JY, Chen JX, Cheng H, Zhang CM, Zhang DB. Validation of a tomato-specific gene, LAT52, used as an endogenous reference gene in qualitative and real-time quantitative PCR detection of transgenic tomatoes[J]. J Agric Food Chem. 2005;53(2):183–90.PubMedCrossRefGoogle Scholar
  36. 36.
    Xu WT, Bai WB, Guo F, Luo YB, Yuan YF, Huang KL. A papaya-specific gene, papain, used as an endogenous reference gene in qualitative and real-time quantitative PCR detection of transgenic papayas. Eur Food Res Technol. 2008;228(2):301–9.CrossRefGoogle Scholar
  37. 37.
    Murugaiah C, Noor ZM, Mastakim M, Bilung LM, Selamat J, Radu S. Meat species identification and Halal authentication analysis using mitochondrial DNA. Meat Sci. 2009;83(1):57–61.PubMedCrossRefGoogle Scholar
  38. 38.
    Kesmen Z, Gulluce A, Sahin F, Yetim H. Identification of meat species by TaqMan-based real-time PCR assay. Meat Sci. 2009;82(4):444–9.PubMedCrossRefGoogle Scholar
  39. 39.
    Ibeagha-Awemu EM, Kgwatalala P, Zhao X. A critical analysis of production-associated DNA polymorphisms in the genes of cattle, goat, sheep, and pig. Mamm Genome. 2008;19(9):591–617.PubMedCrossRefGoogle Scholar
  40. 40.
    Mane BG, Mendiratta SK, Tiwari AK. Polymerase chain reaction assay for identification of chicken in meat and meat products. Food Chem. 2009;116(3):806–10.CrossRefGoogle Scholar
  41. 41.
    Verkaar ELC, Nijman IJ, Boutaga K, Lenstra JA. Differentiation of cattle species in beef by PCR-RFLP of mitochondrial and satellite DNA. Meat Sci. 2002;60(4):365–9.PubMedCrossRefGoogle Scholar
  42. 42.
    Bai WB, Xu WT, Huang KL, Yuan YF, Cao SC, Luo YB. A novel common primer multiplex PCR (CP-M-PCR) method for the simultaneous detection of meat species. Food Control. 2009;20(4):366–70.CrossRefGoogle Scholar
  43. 43.
    Xu WT, Bai WB, Luo YB, Yuan YF, Zhang W, Guo X, Huan KL. A novel common single primer multiplex polymerase chain reaction (CSP‐M‐PCR) method for the identification of animal species in minced meat. J Sci Food Agric. 2008;88(15):2631–7.CrossRefGoogle Scholar
  44. 44.
    Thellin O, Zorzi W, Lakaye B, De Borman B, Coumans B, Hennen G, Grisar T, Igout A, Heinen E. Housekeeping genes as internal standards: use and limits. J Biotechnol. 1999;75(2–3):291–5.PubMedCrossRefGoogle Scholar
  45. 45.
    Iskandar HM, Simpson RS, Casu RE, Bonnett GD, Maclean DJ, Manners JM. Comparison of reference genes for quantitative real-time polymerase chain reaction analysis of gene expression. Plant Mol Biol Rep. 2004;22(4):325–37.CrossRefGoogle Scholar
  46. 46.
    Nicot N, Hausman JF, Hoffmann L, Evers D. Housekeeping gene selection for real-time RT-PCR normalization in potato during biotic and abiotic stress. J Exp Bot. 2005;56(421):2907–14.PubMedCrossRefGoogle Scholar
  47. 47.
    Goldsworthy SM, Goldsworthy TL, Sprankle CS, Butterworth BE. Variation in expression of genes used for normalization of northern blots after induction of cell-proliferation. Cell Prolif. 1993;26(6):511–8.PubMedCrossRefGoogle Scholar
  48. 48.
    Choi JK, Holtzer S, Chacko SA, Lin ZX, Hoffman RK, Holtzer H. Phorbol Esters selectively and reversibly inhibit a subset of myofibrillar genes responsible for the ongoing differentiation program of chick skeletal myotubes. Mol Cell Biol. 1991;11(9):4473–82.PubMedPubMedCentralCrossRefGoogle Scholar
  49. 49.
    Bjarnason R, Wickelgren R, Hermansson M, Hammarqvist F, Carlsson B, Carlsson LMS. Growth hormone treatment prevents the decrease in insulin-like growth factor I gene expression in patients undergoing abdominal surgery. J Clin Endocr Metab. 1998;83(5):1566–72.PubMedGoogle Scholar
  50. 50.
    Petersen BH, Rapaport R, Henry DP, Huseman C, Moore WV. Effect of treatment with biosynthetic human growth-hormone (Gh) on peripheral-blood lymphocyte populations and function in growth hormone-deficient children. J Clin Endocr Metab. 1990;70(6):1756–60.PubMedCrossRefGoogle Scholar
  51. 51.
    Marten NW, Burke EJ, Hayden JM, Straus DS. Effect of amino-acid limitation on the expression of 19 genes in rat hepatoma-cells. FASEB J. 1994;8(8):538–44.PubMedGoogle Scholar
  52. 52.
    Lemay S, Mao CC, Singh AK. Cytokine gene expression in the MRL/lpr model of lupus nephritis. Kidney Int. 1996;50(1):85–93.PubMedCrossRefGoogle Scholar
  53. 53.
    Finnegan MC, Goepel JR, Hancock BW, Goyns MH. Investigation of the expression of housekeeping genes in non-Hodgkin’s lymphoma. Leuk Lymphoma. 1993;10(4–5):387–93.PubMedCrossRefGoogle Scholar
  54. 54.
    Ramos D, Pellin-Carcelen A, Agusti J, Murgui A, Jorda E, Pellin A, Monteagudo C. Deregulation of glyceraldehyde-3-phosphate dehydrogenase expression during tumor progression of human cutaneous melanoma. Anticancer Res. 2015;35(1):439–44.PubMedGoogle Scholar
  55. 55.
    Wang D, Moothart DR, Lowy DR, Qian X. The expression of glyceraldehyde-3-phosphate dehydrogenase associated cell cycle (GACC) genes correlates with cancer stage and poor survival in patients with solid tumors. PLoS ONE. 2013;8(4), e61262.PubMedPubMedCentralCrossRefGoogle Scholar
  56. 56.
    Gunning PW, Ghoshdastider U, Whitaker S, Popp D, Robinson RC. The evolution of compositionally and functionally distinct actin filaments. J Cell Sci. 2015;128(11):2009–19.PubMedCrossRefGoogle Scholar
  57. 57.
    Hanukoglu I, Tanese N, Fuchs E. Complementary DNA sequence of a human cytoplasmic actin. Interspecies divergence of 3′ non-coding regions. J Mol Biol. 1983;163(4):673–8.PubMedCrossRefGoogle Scholar
  58. 58.
    Alvarez-Garcia I, Miska EA. MicroRNA functions in animal development and human disease. Development. 2005;132(21):4653–62.PubMedCrossRefGoogle Scholar
  59. 59.
    Peltier HJ, Latham GJ. Normalization of microRNA expression levels in quantitative RT-PCR assays: identification of suitable reference RNA targets in normal and cancerous human solid tissues. RNA. 2008;14(5):844–52.PubMedPubMedCentralCrossRefGoogle Scholar
  60. 60.
    Lardizabal MN, Nocito AL, Daniele SM, Ornella LA, Palatnik JF, Veggi LM. Reference genes for real-time PCR quantification of MicroRNAs and messenger RNAs in rat models of hepatotoxicity. PloS ONE. 2012;7(5):e36323.Google Scholar
  61. 61.
    Markou A, Tsaroucha EG, Kaklamanis L, Fotinou M, Georgoulias V, Lianidou ES. Prognostic value of mature microRNA-21 and microRNA-205 overexpression in non-small cell lung cancer by quantitative real-time RT-PCR. Clin Chem. 2008;54(10):1696–704.PubMedCrossRefGoogle Scholar
  62. 62.
    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. Genom Biol. 2002;3(7).Google Scholar
  63. 63.
    Chang KH, Mestdagh P, Vandesompele J, Kerin MJ, Miller N. MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer. BMC Cancer. 2010;10:173.Google Scholar
  64. 64.
    Mi QS, Weiland M, Qi RQ, Gao XH, Poisson LM, Zhou L. Identification of mouse serum miRNA endogenous references by global gene expression profiles. PloS ONE. 2012;7(2):e31278.Google Scholar
  65. 65.
    Timoneda O, Balcells I, Cordoba S, Castello A, Sanchez A. Determination of reference microRNAs for relative quantification in porcine tissues. PloS ONE. 2012;7(9):e44413.Google Scholar
  66. 66.
    Schaefer A, Jung M, Miller K, Lein M, Kristiansen G, Erbersdobler A, Jung K. Suitable reference genes for relative quantification of miRNA expression in prostate cancer. Exp Mol Med. 2010;42(11):749–58.PubMedPubMedCentralCrossRefGoogle Scholar
  67. 67.
    Wotschofsky Z, Meyer HA, Jung M, Fendler A, Wagner I, Stephan C, Busch J, Erbersdobler A, Disch AC, Mollenkopf HJ, Jung K. Reference genes for the relative quantification of microRNAs in renal cell carcinomas and their metastases. Anal Biochem. 2011;417(2):233–41.PubMedCrossRefGoogle Scholar
  68. 68.
    Huggett J, Dheda K, Bustin S, Zumla A. Real-time RT-PCR normalisation; strategies and considerations. Genes Immunol. 2005;6(4):279–84.CrossRefGoogle Scholar
  69. 69.
    De Jonge HJM, Fehrmann RSN, de Bont ESJM, Hofstra RMW, Gerbens F, Kamps WA, de Vries EGE, van der Zee AGJ, Meerman GJT, ter Elst A. Evidence based selection of housekeeping genes. PloS ONE. 2007;2(9):e898.Google Scholar
  70. 70.
    Radonic A, Thulke S, Mackay IM, Landt O, Siegert W, Nitsche A. Guideline to reference gene selection for quantitative real-time PCR. Biochem Bioph Res Co. 2004;313(4):856–62.CrossRefGoogle Scholar
  71. 71.
    Glazunova OO, Raoult D, Roux V. Partial sequence comparison of the rpoB, sodA, groEL and gyrB genes within the genus Streptococcus. Int J Syst Evol Micrbiol. 2009;59:2317–22.CrossRefGoogle Scholar
  72. 72.
    Clarridge JE. Impact of 16S rRNA gene sequence analysis for identification of bacteria on clinical microbiology and infectious diseases. Clin Microbiol Rev. 2004;17(4):840–5.PubMedPubMedCentralCrossRefGoogle Scholar
  73. 73.
    Naser SM, Thompson FL, Hoste B, Gevers D, Dawyndt P, Vancanneyt M, Swings J. Application of multilocus sequence analysis (MLSA) for rapid identification of Enterococcus species based on rpoA and pheS genes. Microbiol-Sgm. 2005;151:2141–50.CrossRefGoogle Scholar
  74. 74.
    Tenaillon O, Skurnik D, Picard B, Denamur E. The population genetics of commensal Escherichia coli. Nat Rev Microbiol. 2010;8(3):207–17.PubMedCrossRefGoogle Scholar
  75. 75.
    Szczepanek SM, Tulman ER, Gorton TS, Liao X, Lu Z, Zinski J, Aziz F, Frasca S, Kutish GF, Geary SJ. Comparative genomic analyses of attenuated strains of mycoplasma gallisepticum. Infect Immun. 2010;78(4):1760–71.PubMedPubMedCentralCrossRefGoogle Scholar
  76. 76.
    Manukhov IV, Khrul’nova SA, Baranova A, Zavilgelsky GB. Comparative analysis of the lux Operons in Aliivibrio logei KCh1 (a Kamchatka Isolate) and Aliivibrio salmonicida. J Bacteriol. 2011;193(15):3998–4001.PubMedPubMedCentralCrossRefGoogle Scholar
  77. 77.
    Martens M, Dawyndt P, Coopman R, Gillis M, De Vos P, Willems A. Advantages of multilocus sequence analysis for taxonomic studies: a case study using 10 housekeeping genes in the genus Ensifer (including former Sinorhizobium). Int J Syst Evol Microbiol. 2008;58:200–14.PubMedCrossRefGoogle Scholar
  78. 78.
    Wilson B, Muirhead A, Bazanella M, Huete-Stauffer C, Vezzulli L, Bourne DG. An improved detection and quantification method for the coral pathogen vibrio coralliilyticus. PloS ONE. 2013;8(12):e81800.Google Scholar
  79. 79.
    De la Haba RR, Marquez MC, Papke RT, Ventosa A. Multilocus sequence analysis of the family Halomonadaceae. Int J Syst Evol Microbiol. 2012;62:520–38.PubMedCrossRefGoogle Scholar
  80. 80.
    Rogall T, Wolters J, Flohr T, Bottger EC. Towards a phylogeny and definition of species at the molecular-level within the genus mycobacterium. Int J Syst Bacteriol. 1990;40(4):323–30.PubMedCrossRefGoogle Scholar
  81. 81.
    Dhar AK, Bowers RM, Licon KS, Veazey G, Read B. Validation of reference genes for quantitative measurement of immune gene expression in shrimp. Mol Immunol. 2009;46(8–9):1688–95.PubMedCrossRefGoogle Scholar
  82. 82.
    Gerard CJ, Andrejka LM, Macina RA. Mitochondrial ATP synthase 6 as an endogenous control in the quantitative RT-PCR analysis of clinical cancer samples. Mol Diagn. 2000;5(1):39–46.PubMedCrossRefGoogle Scholar
  83. 83.
    Savli H, Karadenizli A, Kolayli F, Gundes S, Ozbek U, Vahaboglu H. Expression stability of six housekeeping genes: a proposal for resistance gene quantification studies of Pseudomonas aeruginosa by real-time quantitative RT-PCR. J Med Microbiol. 2003;52(5):403–8.PubMedCrossRefGoogle Scholar
  84. 84.
    Wu YY, Rees JL. Variation in epidermal housekeeping gene expression in different pathological states. Acta Derm Venereol. 2000;80(1):2–3.PubMedCrossRefGoogle Scholar
  85. 85.
    Infante C, Matsuoka MP, Asensio E, Canavate JP, Reith M, Manchado M. Selection of housekeeping genes for gene expression studies in larvae from flatfish using real-time PCR. BMC Mol Biol. 2008;9:28.PubMedPubMedCentralCrossRefGoogle Scholar
  86. 86.
    Hu M, Polyak K. Serial analysis of gene expression. Nat Protoc. 2006;1(4):1743–60.PubMedCrossRefGoogle Scholar
  87. 87.
    Chari R, Lonergan KM, Pikor LA, Coe BP, Zhu CQ, Chan THW, MacAulay CE, Tsao MS, Lam S, Ng RT, Lam WL. A sequence-based approach to identify reference genes for gene expression analysis. BMC Med Genomics. 2010;3:32.PubMedPubMedCentralCrossRefGoogle Scholar
  88. 88.
    Velculescu VE, Zhang L, Vogelstein B, Kinzler KW. Serial analysis of gene-expression. Science. 1995;270(5235):484–7.PubMedCrossRefGoogle Scholar
  89. 89.
    Yamamoto M, Wakatsuki T, Hada A, Ryo A. Use of serial analysis of gene expression (SAGE) technology. J Immunol Methods. 2001;250(1–2):45–66.PubMedCrossRefGoogle Scholar
  90. 90.
    Chia CY, Lim CWX, Leong WT, Ling MHT. High expression stability of Microtubule Affinity Regulating Kinase 3 (MARK3) makes it a reliable reference gene. Iubmb Life. 2010;62(3):200–3.PubMedCrossRefGoogle Scholar
  91. 91.
    Too IH, Ling MH. Signal peptidase complex subunit 1 and hydroxyacyl-CoA dehydrogenase beta subunit are suitable reference genes in human lungs. ISRN Bioinform. 2012;2012:790452.PubMedCrossRefGoogle Scholar
  92. 92.
    Maccoux LJ, Clements DN, Salway F, Day PJ. Identification of new reference genes for the normalisation of canine osteoarthritic joint tissue transcripts from microarray data. BMC Mol Biol. 2007;8:62. doi: 10.1186/1471-2199-8-62.PubMedPubMedCentralCrossRefGoogle Scholar
  93. 93.
    Gur-Dedeoglu B, Konu O, Bozkurt B, Ergul G, Seckin S, Yulug IG. Identification of endogenous reference genes for qRT-PCR analysis in normal matched breast tumor tissues. Oncol Res. 2009;17(8):353–65.PubMedCrossRefGoogle Scholar
  94. 94.
    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(15):5245–50.PubMedCrossRefGoogle Scholar
  95. 95.
    Morga B, Arzul I, Faury N, Renault T. Identification of genes from flat oyster Ostrea edulis as suitable housekeeping genes for quantitative real time PCR. Fish Shellfish Immunol. 2010;29(6):937–45.PubMedCrossRefGoogle Scholar
  96. 96.
    Fu J, Bian LH, Zhao L, Dong ZH, Gao X, Luan HF, Sun YJ, Song HF. Identification of genes for normalization of quantitative real-time PCR data in ovarian tissues. Acta Bioch Bioph Sin. 2010;42(8):568–74.CrossRefGoogle Scholar
  97. 97.
    Dundas J, Ling M. Reference genes for measuring mRNA expression. Theor Biosci. 2012;131(4):215–23.CrossRefGoogle Scholar
  98. 98.
    Smith RD, Ogden CW, Penny MA. Exclusive amplification of cDNA template (EXACT) RT-PCR to avoid amplifying contaminating genomic pseudogenes. Biotechniques. 2001;31(4):776–8.PubMedGoogle Scholar
  99. 99.
    Yang LA, Takuno S, Waters ER, Gaut BS. Lowly expressed genes in arabidopsis thaliana bear the signature of possible pseudogenization by promoter degradation. Mol Biol Evol. 2011;28(3):1193–203.PubMedCrossRefGoogle Scholar
  100. 100.
    Pinto FL, Thapper A, Sontheim W, Lindblad P. Analysis of current and alternative phenol based RNA extraction methodologies for cyanobacteria. BMC Mol Biol. 2009;10(1):1–8.CrossRefGoogle Scholar
  101. 101.
    Lehmann MH, Weber J, Gastmann O, Sigusch HH. Pseudogene-free amplification of human GAPDH cDNA. Biotechniques. 2002;33(4):766–9.PubMedGoogle Scholar
  102. 102.
    Malik AN, Shahni R, Rodriguez-De-Ledesma A, Laftah A, Cunningham P. Mitochondrial DNA as a non-invasive biomarker: accurate quantification using real time quantitative PCR without co-amplification of pseudogenes and dilution bias. Biochem Bioph Res Co. 2011;412(1):1–7.CrossRefGoogle Scholar
  103. 103.
    Van Guilder HD, Vrana KE, Freeman WM. Twenty-five years of quantitative PCR for gene expression analysis. Biotechniques. 2008;44(5):619–26.Google Scholar
  104. 104.
    Patino WD, Mian OY, Hwang PM. Serial analysis of gene expression – technical considerations and applications to cardiovascular biology. Circ Res. 2002;91(7):565–9.PubMedCrossRefGoogle Scholar
  105. 105.
    Scaravelli E, Brohee M, Marchelli R, van Hengel AJ. Development of three real-time PCR assays to detect peanut allergen residue in processed food products. Eur Food Res Technol. 2008;227(3):857–69.CrossRefGoogle Scholar
  106. 106.
    Schoringhumer K, Redl G, Cichna-Markl M. Development and validation of a duplex real-time PCR method to simultaneously detect potentially allergenic sesame and hazelnut in food. J Agr Food Chem. 2009;57(6):2126–34.CrossRefGoogle Scholar
  107. 107.
    Schoringhumer K, Cichna-Markl M. Development of a real-time PCR method to detect potentially allergenic sesame (Sesamum indicum) in food. J Agr Food Chem. 2007;55(26):10540–7.CrossRefGoogle Scholar
  108. 108.
    Hernandez M, Rio A, Esteve T, Prat S, Pla M. A rapeseed-specific gene, Acetyl-CoA carboxylase, can be used as a reference for qualitative and real-time quantitative PCR detection of transgenes from mixed food samples. J Agr Food Chem. 2001;49(8):3622–7.CrossRefGoogle Scholar
  109. 109.
    Zhang MH, Gao XJ, Yu YB, Ao JX, Qin J, Yao YH, Li QZ. Detection of Roundup Ready soy in highly processed products by triplex nested PCR. Food Control. 2007;18(10):1277–81.CrossRefGoogle Scholar
  110. 110.
    Hellebrand M, Nagy M, Morsel JT. Determination of DNA traces in rapeseed oil. Z Lebensm Unters FA. 1998;206(4):237–42.CrossRefGoogle Scholar
  111. 111.
    Bustin SA, Benes V, Nolan T, Pfaffl MW. Quantitative real-time RT-PCR – a perspective. J Mol Endocrinol. 2005;34(3):597–601.PubMedCrossRefGoogle Scholar
  112. 112.
    Feuer R, Vlaic S, Arlt J, Sawodny O, Dahmen U, Zanger UM, Thomas M. LEMming: a linear error model to normalize parallel quantitative real-time PCR (qPCR) data as an alternative to reference gene based methods. PloS ONE. 2015;10(9):e0135852.Google Scholar
  113. 113.
    Ballester M, Cordon R, Folch JM (2013) DAG expression: high-throughput gene expression analysis of real-time PCR data using standard curves for relative quantification. PloS ONE. 2013;8(11):e80385.Google Scholar

Copyright information

© Springer Science+Business Media Singapore 2016

Authors and Affiliations

  • Wentao Xu
    • 1
    • 2
  1. 1.Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Food Science & Nutritional EngineeringChina Agricultural UniversityBeijingChina
  2. 2.Beijing Laboratory for Food Quality and Safety, College of Food Science & Nutritional EngineeringChina Agricultural UniversityBeijingChina

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