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Title:ALF : a strategy for identification of unauthorized GMOs in complex mixtures by a GW-NGS method and dedicated bioinformatics analysis
Authors:ID Bogožalec Košir, Alexandra (Author)
ID Arulandhu, Alfred J. (Author)
ID Voorhuijzen, Marleen (Author)
ID Xiao, Hongmei (Author)
ID Hagelaar, Rico (Author)
ID Staats, Martijn (Author)
ID Costessi, Adalberto (Author)
ID Žel, Jana (Author)
ID Kok, Esther (Author)
ID van Dijk, Jeroen P. (Author)
Files:URL URL - Source URL, visit https://www.nature.com/articles/s41598-017-14469-8
 
.pdf PDF - Presentation file, download (1,89 MB)
MD5: 17E5BCBC49437C845F0DC58B944292A0
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo NIB - National Institute of Biology
Abstract:The majority of feed products in industrialised countries contains materials derived from genetically modified organisms (GMOs). In parallel, the number of reports of unauthorised GMOs (UGMOs) is gradually increasing. There is a lack of specific detection methods for UGMOs, due to the absence of detailed sequence information and reference materials. In this research, an adapted genome walking approach was developed, called ALF: Amplification of Linearly-enriched Fragments. Coupling of ALF to NGS aims for simultaneous detection and identification of all GMOs, including UGMOs, in one sample, in a single analysis. The ALF approach was assessed on a mixture made of DNA extracts from four reference materials, in an uneven distribution, mimicking a real life situation. The complete insert and genomic flanking regions were known for three of the included GMO events, while for MON15985 only partial sequence information was available. Combined with a known organisation of elements, this GMO served as a model for a UGMO. We successfully identified sequences matching with this organisation of elements serving as proof of principle for ALF as new UGMO detection strategy. Additionally, this study provides a first outline of an automated, web-based analysis pipeline for identification of UGMOs containing known GM elements.
Keywords:biotechnology, molecular biology
Publication status:Published
Publication version:Version of Record
Publication date:26.10.2017
Year of publishing:2017
Number of pages:str. 1-12
Numbering:Vol. 7
PID:20.500.12556/DiRROS-19688-ea2175cd-4c99-fb74-e80a-2cda68322103 New window
UDC:577.2
ISSN on article:2045-2322
DOI:10.1038/s41598-017-14469-8 New window
COBISS.SI-ID:4484175 New window
Note:Nasl. z nasl. zaslona; Opis vira z dne 6. 11. 2017;
Publication date in DiRROS:25.07.2024
Views:414
Downloads:296
Metadata:XML DC-XML DC-RDF
:
BOGOŽALEC KOŠIR, Alexandra, ARULANDHU, Alfred J., VOORHUIJZEN, Marleen, XIAO, Hongmei, HAGELAAR, Rico, STAATS, Martijn, COSTESSI, Adalberto, ŽEL, Jana, KOK, Esther and VAN DIJK, Jeroen P., 2017, ALF : a strategy for identification of unauthorized GMOs in complex mixtures by a GW-NGS method and dedicated bioinformatics analysis. Scientific reports [online]. 2017. Vol. 7, p. 1–12. [Accessed 4 April 2025]. DOI 10.1038/s41598-017-14469-8. Retrieved from: https://dirros.openscience.si/IzpisGradiva.php?lang=eng&id=19688
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Record is a part of a journal

Title:Scientific reports
Shortened title:Sci. rep.
Publisher:Nature Publishing Group
ISSN:2045-2322
COBISS.SI-ID:18727432 New window

Document is financed by a project

Funder:EC - European Commission
Project number:613908
Name:Development of Cost efficient Advanced DNA-based methods for specific Traceability issues and High Level On-site applicatioNs
Acronym:DECATHLON
Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P4-0165-2015
Name:Biotehnologija in sistemska biologija rastlin
Funder:ARIS - Slovenian Research and Innovation Agency
Project number:1000-15-0105
Funder:Other - Other funder or multiple funders
Funding programme:Slovene Human Resources Development and Scholarship Fund
Project number:11012-51/2015
Funder:Other - Other funder or multiple funders
Funding programme:Dutch Ministry of Economic Affairs

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

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