Detecting authorized and unauthorized genetically modified organisms containing vip3A by real-time PCR and next-generation sequencing |
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Authors: | Chanjuan Liang Jeroen P. van Dijk Ingrid M. J. Scholtens Martijn Staats Theo W. Prins Marleen M. Voorhuijzen Andrea M. da Silva Ana Carolina Maisonnave Arisi Johan T. den Dunnen Esther J. Kok |
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Affiliation: | 1. RIKILT Wageningen UR, P.O. Box 230, 6700 AE, Wageningen, The Netherlands 2. School of Environmental and Civil Engineering, Jiangnan University, Wuxi, 214122, Jiangsu, China 3. Laboratory of Molecular Biology of Trypanosomatids and Sandflies, Instituto Oswaldo Cruz, Fiocruz, Av. Brasil 4365, Rio de Janeiro, 21045-900, Rio de Janeiro, Brazil 4. Federal University of Santa Catarina, Av Admar Gonzaga, 1346, 88034-001, Florianópolis, Santa Catarina, Brazil 5. Leiden Genome Technology Center, Human and Clinical Genetics, Leiden University Medical Center, P.O. Box 9600, 2300 RC, Leiden, The Netherlands
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Abstract: | The growing number of biotech crops with novel genetic elements increasingly complicates the detection of genetically modified organisms (GMOs) in food and feed samples using conventional screening methods. Unauthorized GMOs (UGMOs) in food and feed are currently identified through combining GMO element screening with sequencing the DNA flanking these elements. In this study, a specific and sensitive qPCR assay was developed for vip3A element detection based on the vip3Aa20 coding sequences of the recently marketed MIR162 maize and COT102 cotton. Furthermore, SiteFinding-PCR in combination with Sanger, Illumina or Pacific BioSciences (PacBio) sequencing was performed targeting the flanking DNA of the vip3Aa20 element in MIR162. De novo assembly and Basic Local Alignment Search Tool searches were used to mimic UGMO identification. PacBio data resulted in relatively long contigs in the upstream (1,326 nucleotides (nt); 95 % identity) and downstream (1,135 nt; 92 % identity) regions, whereas Illumina data resulted in two smaller contigs of 858 and 1,038 nt with higher sequence identity (>99 % identity). Both approaches outperformed Sanger sequencing, underlining the potential for next-generation sequencing in UGMO identification. Figure ? |
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