4.7 Editorial Material

Next-generation sequencing as a tool for the molecular characterisation and risk assessment of genetically modified plants: Added value or not?

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TRENDS IN FOOD SCIENCE & TECHNOLOGY
卷 45, 期 2, 页码 319-326

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ELSEVIER SCIENCE LONDON
DOI: 10.1016/j.tifs.2015.07.009

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Genetically modified organism (GMO); Genetically modified plants (GMP); Risk assessment; Molecular characterisation; Next-generation sequencing (NGS)

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Background: Legislations and international organizations provide a framework to ensure proper risk assessment of Genetically Modified Organisms (GMO). With regard to the deliberate release of GMO as food or feed, applications for Genetically Modified Plants (GMP) typically contain data for the molecular characterisation at the nucleic acid level based on Southern blot and polymerase chain reaction analysis in combination with Sanger sequencing. Along with the diverse range of applications of next-generation sequencing (NGS) in genomic research, some recent research projects and product developers explored the use of NGS as an alternative tool for meeting the data requirements for the molecular characterisation of GMPs in view of their risk assessment. Scope and approach: By means of a literature survey and information collected through the organisation of an international workshop, we investigated whether NGS can replace and/or complement the currently used techniques for molecular characterisation of GMP taking into account the possibilities and current bottlenecks of NGS technologies and recent developments in molecular breeding. Key findings and conclusions: We conclude that although NGS might present clear advantages for product developers, NGS currently does not always offer a significant added value with respect to the risk assessment of GMPs. However, the approaches used so far may soon be further challenged by the fast evolution in NGS technologies and also by the recent developments in molecular breeding of plants. We postulate that setting up a common workflow for the generation of relevant and interpretable data by NGS would facilitate a scientifically sound assessment of GMPs. (C) 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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