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Type: Journal article
Title: Characterization of GM events by insert knowledge adapted re-sequencing approaches
Author: Yang, L.
Wang, C.
Holst-Jensen, A.
Morisset, D.
Lin, Y.
Zhang, D.
Citation: Scientific Reports, 2013; 3(1):2839-1-2839-9
Publisher: Nature Publishing Group
Issue Date: 2013
ISSN: 2045-2322
Statement of
Litao Yang, Congmao Wang, Arne Holst-Jensen, Dany Morisset, Yongjun Lin and Dabing Zhang
Abstract: Detection methods and data from molecular characterization of genetically modified (GM) events are needed by stakeholders of public risk assessors and regulators. Generally, the molecular characteristics of GM events are incomprehensively revealed by current approaches and biased towards detecting transformation vector derived sequences. GM events are classified based on available knowledge of the sequences of vectors and inserts (insert knowledge). Herein we present three insert knowledge-adapted approaches for characterization GM events (TT51-1 and T1c-19 rice as examples) based on paired-end re-sequencing with the advantages of comprehensiveness, accuracy, and automation. The comprehensive molecular characteristics of two rice events were revealed with additional unintended insertions comparing with the results from PCR and Southern blotting. Comprehensive transgene characterization of TT51-1 and T1c-19 is shown to be independent of a priori knowledge of the insert and vector sequences employing the developed approaches. This provides an opportunity to identify and characterize also unknown GM events.
Keywords: Molecular engineering in plants; DNA recombination; Plant molecular biology; Next-generation sequencing
Rights: This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit
RMID: 0030023439
DOI: 10.1038/srep02839
Appears in Collections:Agriculture, Food and Wine publications

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