Analytical and Bioanalytical Chemistry

, Volume 406, Issue 26, pp 6485–6497 | Cite as

GMO quantification: valuable experience and insights for the future

  • Mojca Milavec
  • David Dobnik
  • Litao Yang
  • Dabing Zhang
  • Kristina Gruden
  • Jana Žel
Part of the following topical collections:
  1. Nucleic Acid Quantification


Cultivation and marketing of genetically modified organisms (GMOs) have been unevenly adopted worldwide. To facilitate international trade and to provide information to consumers, labelling requirements have been set up in many countries. Quantitative real-time polymerase chain reaction (qPCR) is currently the method of choice for detection, identification and quantification of GMOs. This has been critically assessed and the requirements for the method performance have been set. Nevertheless, there are challenges that should still be highlighted, such as measuring the quantity and quality of DNA, and determining the qPCR efficiency, possible sequence mismatches, characteristics of taxon-specific genes and appropriate units of measurement, as these remain potential sources of measurement uncertainty. To overcome these problems and to cope with the continuous increase in the number and variety of GMOs, new approaches are needed. Statistical strategies of quantification have already been proposed and expanded with the development of digital PCR. The first attempts have been made to use new generation sequencing also for quantitative purposes, although accurate quantification of the contents of GMOs using this technology is still a challenge for the future, and especially for mixed samples. New approaches are needed also for the quantification of stacks, and for potential quantification of organisms produced by new plant breeding techniques.


GMOs Quantification Real-time PCR Digital PCR New generation sequencing 


  1. 1.
    James C (2013) Global status of commercialized biotech/GM crops: 2013. ISAAA briefs 46Google Scholar
  2. 2.
    Secretariat of the Convention on Biological Diversity (2000) Cartagena protocol on biosafety to the convention on biological diversity: text and annexes. Secretariat of the Convention on Biological Diversity, MontrealGoogle Scholar
  3. 3.
    Gruère GP, Rao SR (2007) A review of international labeling policies of genetically modified food to evaluate India’s proposed rule. AgBioforum 10:51–64Google Scholar
  4. 4.
    Holst-Jensen A (2009) Testing for genetically modified organisms (GMOs): past, present and future perspectives. Biotechnol Adv 27:1071–1082CrossRefGoogle Scholar
  5. 5.
    European Commission (2003) Regulation (EC) No 1830/2003 of the European Parliament and of the Council of 22 September 2003 concerning the traceability and labelling of genetically modified organisms and the traceability of food and feed products produced from genetically modified organisms and amending Directive 2001/18/EC. Off J Eur Union 268:24–28Google Scholar
  6. 6.
    European Commission (2004) Commission recommendation of 4 October 2004 on technical guidance for sampling and detection of genetically modified organisms and material produced from genetically modified organisms as or in products in the context of Regulation (EC) No 1830/2003. Off J Eur Union 348:18–26Google Scholar
  7. 7.
    European Commission (2011) Regulation (EU) No 619/2011 of 24 June 2011 laying down the methods of sampling and analysis for the official control of feed as regards presence of genetically modified material for which an authorisation procedure is pending or the authorisation of which has expired. Off J Eur Union 166:9–15Google Scholar
  8. 8.
    European Union Reference Laboratory for Genetically Modified Food and Feed (2011) Technical guidance document from the European Union Reference Laboratory for Genetically Modified Food and Feed on the implementation of Commission Regulation (EU) No 619/2011Google Scholar
  9. 9.
    Ministry of Agriculture and Forestry (2000) Guidelines for labeling genetically modified agricultural products. MAF Notification No. 2000-31Google Scholar
  10. 10.
    Korea Food and Drug Administration (2000) Labeling standards for genetically modified foods. KFDA Notification No. 2000-43Google Scholar
  11. 11.
    Ministry of Agriculture, Forestry and Fisheries (2007) Notification No. 1173 (October 1, 2007) for the amendment of Notification No. 517Google Scholar
  12. 12.
    Ministry of Agriculture, Forestry and Fisheries (2000) Notification No. 1775Google Scholar
  13. 13.
    Brazil (1990) Consumer protection code. Law No. 8078 of September 11, 1990. Provides for consumer protection and other measuresGoogle Scholar
  14. 14.
    Brazil (2003) Decree No. 4680 of April 24, 2003. Regulates the right to information, provided by Law No. 8078 of September 11, 1990, regarding food and food ingredients for human consumption or animal feed containing or produced from GMOs, without prejudice to compliance with other applicable rulesGoogle Scholar
  15. 15.
    Trapmann S, Corbisier P, Schimmel H, Emons H (2010) Towards future reference systems for GM analysis. Anal Bioanal Chem 396:1969–1975CrossRefGoogle Scholar
  16. 16.
    Holst-Jensen A (2013) Real-time PCR analysis of genetically modified organisms. In: Rodriguez-Lazaro D (ed) Real-time PCR in food science. Caister Academic, NorfolkGoogle Scholar
  17. 17.
    Broeders SRM, De Keersmaecker SCJ, Roosens NHC (2012) How to deal with the upcoming challenges in GMO detection in food and feed. J Biomed Biotechnol 2012:402418–402429CrossRefGoogle Scholar
  18. 18.
    Žel J, Milavec M, Morisset D, Plan D, Van den Eede G, Gruden K (2012) How to reliably test for GMOs. Springer, New YorkGoogle Scholar
  19. 19.
    Lipp M, Shillito R, Giroux R, Spiegelhalter F, Charlton S, Pinero D, Song P (2005) Polymerase chain reaction technology as analytical tool in agricultural biotechnology. J AOAC Int 88:136–155Google Scholar
  20. 20.
    Hernandez M, Rodriguez-Lazaro D, Ferrando A (2005) Current methodology for detection, identification and quantification of genetically modified organisms. Curr Anal Chem 1:203–221CrossRefGoogle Scholar
  21. 21.
    Huggett J, Bustin SA (2011) Standardisation and reporting for nucleic acid quantification. Accred Qual Assur 16:399–405CrossRefGoogle Scholar
  22. 22.
    Kodama T, Kurosawa Y, Kitta K (2010) Tendency for interlaboratory precision in the GMO analysis method based on real-time PCR. J AOAC Int 93:734–749Google Scholar
  23. 23.
    European Network of Genetically Modified Organisms Laboratories (2008) Definition of minimum performance requirements for analytical methods of GMO testing. Publications Office of the European. Union, LuxembourgGoogle Scholar
  24. 24.
    European Commision (2003) Regulation (EC) No 1829/2003 of the European Parliament and of the Council of 22 September 2003 on genetically modified food and feed. Off J Eur Union 268:1–23Google Scholar
  25. 25.
    Codex Committee on Methods of Analysis and Sampling (2010) Guidelines on performance criteria and validation of methods for detection, identification and quantification of specific DNA sequences and specific proteins in foods. CAC/GL 74-2010. Codex Alimentarius Commision – WHO, RomeGoogle Scholar
  26. 26.
    European Network of GMO Laboratories (2011) Verification of real time PCR methods for GMO testing when implementing interlaboratory validated methods - guidance document from the European Network of GMO laboratories (ENGL). Publications Office of the European Union, LuxembourgGoogle Scholar
  27. 27.
    Technical Committee of National Agricultural Genetically Modified Organisms safety Management and Standardisation. China. Notification on the issuance of the “validation protocol of GMO detection methods”. Notification 2012-1Google Scholar
  28. 28.
    Caprioara-Buda M, Meyer W, Jenyov B, Corbisier P, Trapmann S, Emons H (2012) Evaluation of plasmid and genomic DNA calibrants used for the quantification of genetically modified organisms. Anal Bioanal Chem 404:29–42CrossRefGoogle Scholar
  29. 29.
    European Commision (2004) Commission Regulation (EC) No. 641/2004 of 6 April 2004 on detailed rules for the implementation of Regulation (EC) No. 1829/2003 of the European Parliament and of the Council as regards the application for the authorisation of new genetically modified food and feed, the notification of existing products and adventitious or technically unavoidable presence of genetically modified material which has benefited from a favourable risk evaluation. Off J Eur Union 102:14–25Google Scholar
  30. 30.
    Gruden K, Allnutt TR, Ayadi M, Baeumler S, Bahrdt C, Berben G, Berdal KG, Bertheau Y, Bøydler Andersen C, Brodmann P, Buh Gašparič M, Burns MJ, Burrel AM, Cankar K, Esteve T, Holst-Jensen A, Kristoffersen AB, La Paz J, Lee D, Løvseth A, Macarthur R, Morisset D, Pla M, Rud RB, Skjœret C, Tengs T, Valdivia H, Wulff D, Zhang D, Žel J (2012) Reliability and cost of GMO detection. In: Bertheau Y (ed) Genetically modified and non-genetically modified food supply chains: co-existence and traceability. Wiley-Blackwell, OxfordGoogle Scholar
  31. 31.
    Meyer W, Caprioara-Buda M, Jenyov B, Corbisier P, Trapmann S, Emons H (2012) The impact of analytical quality criteria and data evaluation on the quantification of genetically modified organisms. Eur Food Res Technol 235:597–610CrossRefGoogle Scholar
  32. 32.
    Regulation (EC) No. 882/2004 of the European Parliament and of the Council of 29 April 2004 on official controls performed to ensure the verification of compliance with feed and food law, animal health and animal welfare rules. Off J Eur Union 165:1–141Google Scholar
  33. 33.
    Trapmann S, Charles Delobel C, Corbisier P, Emons H, Hougs L, Philipp P, Sandberg M, Schulze M (2013) European technical guidance document for the flexible scope accreditation of laboratories quantifying GMOs. Publications Office of the European Union, LuxembourgGoogle Scholar
  34. 34.
    International Organization for Standardization (2006) EN ISO 24276:2006. Foodstuffs – methods of analysis for the detection of genetically modified organisms and derived products – general requirements and definitions. International Organization for Standardization, GenevaGoogle Scholar
  35. 35.
    International Organization for Standardization (2013) EN ISO 24276:2006/A1:2013. Foodstuffs – methods of analysis for the detection of genetically modified organisms and derived products – general requirements and definitions. International Organization for Standardization, GenevaGoogle Scholar
  36. 36.
    Trapmann S, Burns M, Broll H, Macartur R, Wood R, Žel J (2009) Guidance document on measurement uncertainty for GMO testing laboratories. Office for Official Publications of the European Communities, LuxembourgGoogle Scholar
  37. 37.
    Van den Bulcke M, Bellocchi G, Berben G, Burns M, Cankar K, De Giacomo M, Gruden K, Holst-Jensen A, Malcewsky A, Mazzara M, Onori R, Papazova N, Parlouer E, Taverniers I, Trapmann S, Wulff D, Zhang D (2012) The modular approach in GMO quality control and enforcement support systems. In: Bertheau Y (ed) Genetically modified and non-genetically modified food supply chains: co-existence and traceability. Wiley-Blackwell, OxfordGoogle Scholar
  38. 38.
    Bhat S, Curach N, Mostyn T, Bains GS, Griffiths KR, Emslie KR (2010) Comparison of methods for accurate quantification of DNA mass concentration with traceability to the international system of units. Anal Chem 82:7185–7192CrossRefGoogle Scholar
  39. 39.
    Folloni S, Bellocchi G, Prospero A, Querci M, Moens W, Ermolli M, Van den Eede G (2010) Statistical evaluation of real-time PCR protocols applied to quantify genetically modified maize. Food Anal Methods 3:304–312CrossRefGoogle Scholar
  40. 40.
    Cankar K, Stebih D, Dreo T, Žel J, Gruden K (2006) Critical points of DNA quantification by real-time PCR–effects of DNA extraction method and sample matrix on quantification of genetically modified organisms. BMC Biotechnol 6:37CrossRefGoogle Scholar
  41. 41.
    Demeke T, Jenkins G (2010) Influence of DNA extraction methods, PCR inhibitors and quantification methods on real-time PCR assay of biotechnology-derived traits. Anal Bioanal Chem 396:1977–1990CrossRefGoogle Scholar
  42. 42.
    Morisset D, Demšar T, Gruden K, Vojvoda J, Štebih D, Žel J (2009) Detection of genetically modified organisms—closing the gaps. Nat Biotechnol 27:700–701CrossRefGoogle Scholar
  43. 43.
    Ghedira R, Papazova N, Vuylsteke M, Ruttink T, Taverniers I, De Loose M (2009) Assessment of primer/template mismatch effects on real-time PCR amplification of target taxa for GMO quantification. J Agric Food Chem 57:9370–9377CrossRefGoogle Scholar
  44. 44.
    Papazova N, Zhang D, Gruden K, Vojvoda J, Yang L, Buh M, Blejec A, Fouilloux S, De Loose M, Taverniers I (2010) Evaluation of the reliability of maize reference assays for GMO quantification. Anal Bioanal Chem 396:2189–2201CrossRefGoogle Scholar
  45. 45.
    Hernández M, Río A, Esteve T, Prat S, Pla M (2001) 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 Agric Food Chem 49:3622–3627CrossRefGoogle Scholar
  46. 46.
    Paternò A, Marchesi U, Gatto F, Verginelli D, Quarchioni C, Fusco C, Zepparoni A, Amaddeo D, Ciabatti I (2009) Finding the joker among the maize endogenous reference genes for genetically modified organism (GMO) detection. J Agric Food Chem 57:11086–11091CrossRefGoogle Scholar
  47. 47.
    Taverniers I, Papazova N, Allnutt T, Baumler S, Bertheau Y, Esteve T, Freyer R, Gruden K, Kuznetzov B, Luis La Paz J, Nadal A, Pla M, Vojvoda J, Wulff D, Zhang D (2012) Harmonised reference genes and PCR assays for GMO quantification. In: Bertheau Y (ed) Genetically modified and non-genetically modified food supply chains: co-existence and traceability. Wiley-Blackwell, OxfordGoogle Scholar
  48. 48.
    Wei J, Li F, Guo J, Li X, Xu J, Wu G, Zhang D, Yang L (2013) Collaborative ring trial of the papaya endogenous reference gene and its polymerase chain reaction assays for genetically modified organism analysis. J Agric Food Chem 61:11363–11370CrossRefGoogle Scholar
  49. 49.
    European Union Reference Laboratory for Genetically Modified Food and Feed (2006) Event-specific method for the quantitation of sugar beet line H7-1 using real-time PCR - validation report. IHCP, IspraGoogle Scholar
  50. 50.
    Chaouachi M, Alaya A, Ali IB, Hafsa AB, Nabi N, Bérard A, Romaniuk M, Skhiri F, Saïd K (2013) Development of real-time PCR method for the detection and the quantification of a new endogenous reference gene in sugar beet “Beta vulgaris L”.: GMO application. Plant Cell Rep 32:117–128CrossRefGoogle Scholar
  51. 51.
    Guan Q, Wang X, Teng D, Yang Y, Tian F, Yin Q, Wang J (2011) Construction of a standard reference plasmid for detecting GM cottonseed meal. Appl Biochem Biotechnol 165:24–34CrossRefGoogle Scholar
  52. 52.
    Ballari RV, Martin A, Gowda LR (2013) A calibrator plasmid for quantitative analysis of insect resistant maize (Yieldgard MON 810). Food Chem 140:382–389CrossRefGoogle Scholar
  53. 53.
    Brod FC, Dinon AZ, Kolling DJ, Faria JC, Arisi AC (2013) Development of plasmid DNA reference material for the quantification of genetically modified common bean embrapa 5.1. J Agric Food Chem 61:4921–4926CrossRefGoogle Scholar
  54. 54.
    Zhang D, Corlet A, Fouilloux S (2008) Impact of genetic structures on haploid genome-based quantification of genetically modified DNA: theoretical considerations, experimental data in MON 810 maize kernels (Zea mays L.) and some practical applications. Transgenic Res 17:393–402CrossRefGoogle Scholar
  55. 55.
    Holst-Jensen A, De Loose M, Van den Eede G (2006) Coherence between legal requirements and approaches for detection of genetically modified organisms (GMOs) and their derived products. J Agric Food Chem 54:2799–2809CrossRefGoogle Scholar
  56. 56.
    Liu D, Shen J, Yang J, Zhang D (2010) Evaluation of the impacts of different nuclear DNA content in the hull, endosperm, and embryo of rice seeds on GM rice quantification. J Agric Food Chem 58:4582–4587CrossRefGoogle Scholar
  57. 57.
    Cankar K, Chauvensy-Ancel V, Fortabat M, Gruden K, Kobilinsky A, Žel J, Bertheau Y (2008) Detection of nonauthorized genetically modified organisms using differential quantitative polymerase chain reaction: application to 35S in maize. Anal Biochem 376:189–199CrossRefGoogle Scholar
  58. 58.
    Berdal KG, Bøydler C, Tengs T, Holst-Jensen A (2008) A statistical approach for evaluation of PCR results to improve the practical limit of quantification (LOQ) of GMO analyses (SIMQUANT). Eur Food Res Technol 227:1149–1157CrossRefGoogle Scholar
  59. 59.
    Lee D, La Mura M, Greenland A, Mackay I (2008) Quantitation using informative zeros (QUIZ): application for GMO detection and quantification without recourse to certified reference material. Food Chem 118:974–978CrossRefGoogle Scholar
  60. 60.
    Guo J, Yang L, Chen L, Morisset D, Li X, Pan L, Zhang D (2011) MPIC: a high-throughput analytical method for multiple DNA targets. Anal Chem 83:1579–1586CrossRefGoogle Scholar
  61. 61.
    Guo J, Yang L, Chen L, Liu X, Gao Y, Zhang D, Yang L (2012) A multiplex degenerate PCR analytical approach targeting to eight genes for screening GMOs. Food Chem 132:1566–1573CrossRefGoogle Scholar
  62. 62.
    Kim J, Zhang D, Kim H (2014) Detection of sixteen genetically modified maize events in processed foods using four event-specific pentaplex PCR systems. Food Control 35:345–353CrossRefGoogle Scholar
  63. 63.
    Shao N, Jiang S, Zhang M, Wang J, Guo S, Li Y, Jiang H, Liu C, Zhang D, Yang L, Tao S (2014) MACRO: a combined microchip-PCR and microarray system for high-throughput monitoring of genetically modified organisms. Anal Chem 86:1269–1276CrossRefGoogle Scholar
  64. 64.
    Rudi K, Rud I, Holck A (2003) A novel multiplex quantitative DNA array based PCR (MQDA-PCR) for quantification of transgenic maize in food and feed. Nucleic Acids Res 31:e62. doi:10.1093/nar/gng061 CrossRefGoogle Scholar
  65. 65.
    Morisset D, Dobnik D, Hamels S, Žel J, Gruden K (2008) NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs. Nucleic Acids Res 36:e118. doi:10.1093/nar/gkn524 CrossRefGoogle Scholar
  66. 66.
    Dobnik D, Morisset D, Gruden K (2009) NAIMA as a solution for future GMO diagnostics challenges. Anal Bioanal Chem 396:2229–2233CrossRefGoogle Scholar
  67. 67.
    Heide B, Dromtorp S, Rudi K, Heir E, Holck A (2008) Determination of eight genetically modified maize events by quantitative, multiplex PCR and fluorescence capillary gel electrophoresis. Eur Food Res Technol 227:1125–1137CrossRefGoogle Scholar
  68. 68.
    Morisset D, Štebih D, Milavec M, Gruden K, Žel J (2013) Quantitative analysis of food and feed samples with droplet digital PCR. PLoS ONE 8(5):e62583CrossRefGoogle Scholar
  69. 69.
    Baker M (2012) Digital PCR hits its stride. Nat Methods 9:541–544CrossRefGoogle Scholar
  70. 70.
    Burns MJ, Burrell AM, Foy C (2010) The applicability of digital PCR for the assessment of detection limits in GMO analysis. Eur Food Res Technol 231:353–362CrossRefGoogle Scholar
  71. 71.
    Corbisier P, Bhat S, Partis L, Rui Dan Xie V, Emslie K (2010) Absolute quantification of genetically modified MON810 maize (Zea mays L.) by digital polymerase chain reaction. Anal Bioanal Chem 396:2143–2150CrossRefGoogle Scholar
  72. 72.
    Bhat S, Herrmann J, Armishaw P, Corbisier P, Emslie KR (2009) Single molecule detection in nanofluidic digital array enables accurate measurement of DNA copy number. Anal Bioanal Chem 394:457–467CrossRefGoogle Scholar
  73. 73.
    Heide B, Heir E, Holck A (2008) Detection of eight GMO maize events by qualitative, multiplex PCR and fluorescence capillary gel electrophoresis. Eur Food Res Technol 227:527–535CrossRefGoogle Scholar
  74. 74.
    Kiddle G, Hardinge P, Buttigieg N, Gandelman O, Pereira C, McElgunn C, Rizzoli M, Jackson R, Appleton N, Moore C, Tisi L, Murray J (2012) GMO detection using a bioluminescent real time reporter (BART) of loop mediated isothermal amplification (LAMP) suitable for field use. BMC Biotechnol 12:15CrossRefGoogle Scholar
  75. 75.
    Chen X, Wang X, Jin N, Zhou Y, Huang S, Miao Q, Zhu Q, Xu J (2012) Endpoint visual detection of three genetically modified rice events by loop-mediated isothermal amplification. Int J Mol Sci 13:14421–14433CrossRefGoogle Scholar
  76. 76.
    Li Q, Fang J, Liu X, Xi X, Li M, Gong Y, Zhang M (2013) Loop-mediated isothermal amplification (LAMP) method for rapid detection of cry1Ab gene in transgenic rice (Oryza sativa L.). Eur Food Res Technol 236:589–598CrossRefGoogle Scholar
  77. 77.
    Randhawa GJ, Singh M, Morisset D, Sood P, Žel J (2013) Loop-mediated isothermal amplification: rapid visual and real-time methods for detection of genetically modified crops. J Agric Food Chem 61:11338–11346CrossRefGoogle Scholar
  78. 78.
    Soleimani M, Shams S, Majidzadeh-A K (2013) Developing a real-time quantitative loop-mediated isothermal amplification assay as a rapid and accurate method for detection of Brucellosis. J Appl Microbiol 115:828–834CrossRefGoogle Scholar
  79. 79.
    Huang X, Chen L, Xu J, Ji H, Zhu S, Chen H (2014) Rapid visual detection of phytase gene in genetically modified maize using loop-mediated isothermal amplification method. Food Chem 156:184–189CrossRefGoogle Scholar
  80. 80.
    Sykes PJ, Neoh SH, Brisco MJ, Hugues E, Condon J, Morley AA (1992) Quantitation of targets for PCR by use of limiting dilution. Biotechniques 13:444–449Google Scholar
  81. 81.
    Pinheiro LB, Coleman VA, Hindson CM, Herrmann J, Hindson BJ, Bhat S, Emslie KR (2012) Evaluation of a droplet digital polymerase chain reaction format for DNA copy number quantification. Anal Chem 83:1003–1011CrossRefGoogle Scholar
  82. 82.
    Hindson BJ, Ness KD, Masquelier DA, Belgrader P, Heredia NJ, Makarewicz AJ, Bright IJ, Lucero MY, Hiddessen AL, Legler TC, Kitano TK, Hodel MR, Petersen JF, Wyatt PW, Steenblock ER, Shah PH, Bousse LJ, Troup CB, Mellen JC, Wittmann DK, Erndt NG, Cauley TH, Koehler RT, So AP, Dube S, Rose KA, Montesclaros L, Wang S, Stumbo DP, Hodges SP, Romine S, Milanovich FP, White HE, Regan JF, Karlin-Neumann GA, Hindson CM, Saxonov S, Colston BW (2011) High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal Chem 83:8604–8610CrossRefGoogle Scholar
  83. 83.
    Sanders R, Huggett JF, Bushell CA, Cowen S, Scott DJ, Foy CA (2011) Evaluation of digital PCR for absolute DNA quantification. Anal Chem 83:6474–6484CrossRefGoogle Scholar
  84. 84.
    Weaver S, Dube S, Mir A, Qin J, Sun G, Ramakrishnan R, Jones RC, Livak KJ (2010) Taking qPCR to a higher level: analysis of CNV reveals the power of high throughput qPCR to enhance quantitative resolution. Methods 50:271–276CrossRefGoogle Scholar
  85. 85.
    Whale AS, Huggett JF, Cowen S, Speirs V, Shaw J, Ellison S, Foy CA, Scott DJ (2012) Comparison of microfluidic digital PCR and conventional quantitative PCR for measuring copy number variation. Nucleic Acids Res 40:e82CrossRefGoogle Scholar
  86. 86.
    Whale AS, Cowen S, Foy CA, Huggett JF (2013) Methods for applying accurate digital PCR analysis on Low copy DNA samples. PLoS ONE 8:e58177CrossRefGoogle Scholar
  87. 87.
    Dingle TC, Sedlak RH, Cook L, Jerome KR (2013) Tolerance of droplet-digital PCR vs real-time quantitative PCR to inhibitory substances. Clin Chem 59:11CrossRefGoogle Scholar
  88. 88.
    Pérez Urquiza M, Acatzi Silva AI (2014) Copy number ratios determined by two digital polymerase chain reaction systems in genetically modified grains. Metrologia 51:61–66CrossRefGoogle Scholar
  89. 89.
    McDermott GP, Do D, Litterst CM, Maar D, Hindson CM, Steenblock ER, Legler TC, Jouvenot Y, Marrs SH, Bemis A, Shah P, Wong J, Wang S, Sally D, Javier L, Dinio T, Han C, Brackbill TP, Hodges SP, Ling Y, Klitgord N, Carman GJ, Berman JR, Koehler RT, Hiddessen AL, Walse P, Bousse L, Tzonev S, Hefner E, Hindson BJ, Cauly TH 3rd, Hamby K, Patel VP, Regan JF, Wyatt PW, Karlin-Neumann GA, Stumbo DP, Lowe AJ (2013) Multiplexed target detection using DNA-binding dye chemistry in droplet digital PCR. Anal Chem 85:11619–11627CrossRefGoogle Scholar
  90. 90.
    Yang L, Wang C, Holst-Jensen A, Morisset D, Lin Y, Zhang D (2013) Characterization of GM events by insert knowledge adapted re-sequencing approaches. Sci Rep 3:2839Google Scholar
  91. 91.
    Polko JK, Temanni MR, van Zanten M, van Workum W, Iburg S, Pierik R, Voesenek LA, Peeters AJ (2012) Illumina sequencing technology as a method of identifying T-DNA insertion loci in activation-tagged Arabidopsis thaliana plants. Mol Plant 5:948–950CrossRefGoogle Scholar
  92. 92.
    Fullwood MJ, Wei CL, Liu ET, Ruan Y (2009) Next-generation DNA sequencing of paired-end tags (PET) for transcriptome and genome analyses. Genome Res 19:521–532CrossRefGoogle Scholar
  93. 93.
    Campbell PJ, Stephens PJ, Pleasance ED, O'Meara S, Li H, Santarius T, Stebbings LA, Leroy C, Edkins S, Hardy C, Teague JW, Menzies A, Goodhead I, Turner DJ, Clee CM, Quail MA, Cox A, Brown C, Durbin R, Hurles ME, Edwards PA, Bignell GR, Stratton MR, Futreal PA (2008) Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing. Nat Genet 40:722–729CrossRefGoogle Scholar
  94. 94.
    Hormozdiari F, Hajirasouliha I, McPherson A, Eichler EE, Sahinalp SC (2011) Simultaneous structural variation discovery among multiple paired-end sequenced genomes. Genome Res 21:2203–2212CrossRefGoogle Scholar
  95. 95.
    Tengs T, Zhang H, Holst-Jensen A, Bohlin J, Butenko M, Kristoffersen A, Sorteberg H-G, Berdal K (2009) Characterization of unknown genetic modifications using high throughput sequencing and computational subtraction. BMC Biotechnol 9:87CrossRefGoogle Scholar
  96. 96.
    Dubose AJ, Lichtenstein ST, Narisu N, Bonnycastle LL, Swift AJ, Chines PS, Collins FS (2013) Use of microarray hybrid capture and next-generation sequencing to identify the anatomy of a transgene. Nucleic Acids Res 41:e70CrossRefGoogle Scholar
  97. 97.
    Kovalic D, Garnaat C, Guo L, Yan Y, Groat J, Silvanovich, Ralston L, Huang M, Tian Q, Christian A, Cheikh N, Hjelle J, Padgette S, Bannon G (2013) The use of next generation sequencing and junction sequence analysis bioinformatics to achieve molecular characterization of crops improved through modern biotechnology. Plant Genome 5:149–163Google Scholar
  98. 98.
    Taverniers I, Papazova N, Bertheau Y, De Loose M, Holst-Jensen A (2008) Gene stacking in transgenic plants: towards compliance between definitions, terminology, and detection within the EU regulatory framework. Environ Biosaf Res 7:197–218CrossRefGoogle Scholar
  99. 99.
    Akiyama H, Watanabe T, Wakabayashi K, Nakade S, Yasui S, Sakata K, Chiba R, Spiegelhalter F, Hino A, Maitani T (2005) Quantitative detection system for maize sample containing combined-trait genetically modified maize. Anal Chem 77:7421–7428CrossRefGoogle Scholar
  100. 100.
    Akiyama H, Minegishi Y, Makiyama D, Mano J, Sakata K, Nakamura K, Noguchi A, Takabatake R, Futo S, Kondo K, Kitta K, Kato Y, Teshima R (2012) Quantification and identification of genetically modified maize events in non-identity preserved maize samples in 2009 using an individual kernel detection system. Food Hyg Saf Sci 53:157–165CrossRefGoogle Scholar
  101. 101.
    Shin K, Suh S, Lim M, Woo H, Lee J, Kim H, Cho H (2013) Event-specific detection system of stacked genetically modified maize by using the multiplex-PCR technique. Food Sci Biotechnol 22:1763–1772CrossRefGoogle Scholar
  102. 102.
    Mano J, Yanaka Y, Ikezu Y, Onishi M, Futo S, Minegishi Y, Ninomiya K, Yotsuyanagi Y, Spiegelhalter F, Akiyama H, Teshima R, Hino A, Naito S, Koiwa T, Takabatake R, Furui S, Kitta K (2011) Practicable group testing method to evaluate weight/weight GMO content in maize grains. J Agric Food Chem 59:6856–6863CrossRefGoogle Scholar
  103. 103.
    Xu W, Yuan Y, Luo Y, Bai W, Zhang C, Huang K (2009) Event-specific detection of stacked genetically modified maize Bt11 x GA21 by UP-M-PCR and real-time PCR. J Agric Food Chem 57:395–402CrossRefGoogle Scholar
  104. 104.
    Lusser M, Parisi C, Plan D, Rodríguez-Cerezo E (2011) New plant breeding techniques. State-of-the-art and prospects for commercial development. JRC Technical Report EUR 24760 EN. European Commission Joint Research Centre, RomeGoogle Scholar
  105. 105.
    Lusser M, Parisi C, Plan D, Rodríguez-Cerezo E (2012) Deployment of new biotechnologies in plant breeding. Nat Biotechnol 30:231–239CrossRefGoogle Scholar
  106. 106.
    Querci M, Foti N, Bogni A, Kluga L, Broll H, Van den Eede G (2009) Real-time PCR-based ready-to-use multi-target analytical system for GMO detection. Food Anal Methods 2:325–336CrossRefGoogle Scholar
  107. 107.
    Kluga L, Folloni S, Van den Bulcke M, Van den Eede G, Querci M (2012) Applicability of the real-time PCR-based ready-to-use multi-target analytical system for GMO detection in highly processed food matrices. Eur Food Res Technol 234:109–118CrossRefGoogle Scholar
  108. 108.
    Cottenet G, Blancpain C, Sonnard V, Chuah PF (2013) Development and validation of a multiplex real-time PCR method to simultaneously detect 47 targets for the identification of genetically modified organisms. Anal Bioanal Chem 405:6831–6844CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Mojca Milavec
    • 1
  • David Dobnik
    • 1
  • Litao Yang
    • 2
  • Dabing Zhang
    • 2
  • Kristina Gruden
    • 1
  • Jana Žel
    • 1
  1. 1.Department of Biotechnology and Systems BiologyNational Institute of Biology (NIB)LjubljanaSlovenia
  2. 2.Collaborative Innovation Centre for Biosafety of GMO, National Centre for Molecular Characterisation of GMOs, School of Life Science and BiotechnologyShanghai Jiao Tong UniversityShanghaiChina

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