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The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants

BACKGROUND: Since their first commercialization, the diversity of taxa and the genetic composition of transgene sequences in genetically modified plants (GMOs) are constantly increasing. To date, the detection of GMOs and derived products is commonly performed by PCR-based methods targeting specific...

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Autores principales: Block, Annette, Debode, Frédéric, Grohmann, Lutz, Hulin, Julie, Taverniers, Isabel, Kluga, Linda, Barbau-Piednoir, Elodie, Broeders, Sylvia, Huber, Ingrid, Van den Bulcke, Marc, Heinze, Petra, Berben, Gilbert, Busch, Ulrich, Roosens, Nancy, Janssen, Eric, Žel, Jana, Gruden, Kristina, Morisset, Dany
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3765097/
https://www.ncbi.nlm.nih.gov/pubmed/23965170
http://dx.doi.org/10.1186/1471-2105-14-256
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author Block, Annette
Debode, Frédéric
Grohmann, Lutz
Hulin, Julie
Taverniers, Isabel
Kluga, Linda
Barbau-Piednoir, Elodie
Broeders, Sylvia
Huber, Ingrid
Van den Bulcke, Marc
Heinze, Petra
Berben, Gilbert
Busch, Ulrich
Roosens, Nancy
Janssen, Eric
Žel, Jana
Gruden, Kristina
Morisset, Dany
author_facet Block, Annette
Debode, Frédéric
Grohmann, Lutz
Hulin, Julie
Taverniers, Isabel
Kluga, Linda
Barbau-Piednoir, Elodie
Broeders, Sylvia
Huber, Ingrid
Van den Bulcke, Marc
Heinze, Petra
Berben, Gilbert
Busch, Ulrich
Roosens, Nancy
Janssen, Eric
Žel, Jana
Gruden, Kristina
Morisset, Dany
author_sort Block, Annette
collection PubMed
description BACKGROUND: Since their first commercialization, the diversity of taxa and the genetic composition of transgene sequences in genetically modified plants (GMOs) are constantly increasing. To date, the detection of GMOs and derived products is commonly performed by PCR-based methods targeting specific DNA sequences introduced into the host genome. Information available regarding the GMOs’ molecular characterization is dispersed and not appropriately organized. For this reason, GMO testing is very challenging and requires more complex screening strategies and decision making schemes, demanding in return the use of efficient bioinformatics tools relying on reliable information. DESCRIPTION: The GMOseek matrix was built as a comprehensive, online open-access tabulated database which provides a reliable, comprehensive and user-friendly overview of 328 GMO events and 247 different genetic elements (status: 18/07/2013). The GMOseek matrix is aiming to facilitate GMO detection from plant origin at different phases of the analysis. It assists in selecting the targets for a screening analysis, interpreting the screening results, checking the occurrence of a screening element in a group of selected GMOs, identifying gaps in the available pool of GMO detection methods, and designing a decision tree. The GMOseek matrix is an independent database with effective functionalities in a format facilitating transferability to other platforms. Data were collected from all available sources and experimentally tested where detection methods and certified reference materials (CRMs) were available. CONCLUSIONS: The GMOseek matrix is currently a unique and very valuable tool with reliable information on GMOs from plant origin and their present genetic elements that enables further development of appropriate strategies for GMO detection. It is flexible enough to be further updated with new information and integrated in different applications and platforms.
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spelling pubmed-37650972013-09-07 The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants Block, Annette Debode, Frédéric Grohmann, Lutz Hulin, Julie Taverniers, Isabel Kluga, Linda Barbau-Piednoir, Elodie Broeders, Sylvia Huber, Ingrid Van den Bulcke, Marc Heinze, Petra Berben, Gilbert Busch, Ulrich Roosens, Nancy Janssen, Eric Žel, Jana Gruden, Kristina Morisset, Dany BMC Bioinformatics Database BACKGROUND: Since their first commercialization, the diversity of taxa and the genetic composition of transgene sequences in genetically modified plants (GMOs) are constantly increasing. To date, the detection of GMOs and derived products is commonly performed by PCR-based methods targeting specific DNA sequences introduced into the host genome. Information available regarding the GMOs’ molecular characterization is dispersed and not appropriately organized. For this reason, GMO testing is very challenging and requires more complex screening strategies and decision making schemes, demanding in return the use of efficient bioinformatics tools relying on reliable information. DESCRIPTION: The GMOseek matrix was built as a comprehensive, online open-access tabulated database which provides a reliable, comprehensive and user-friendly overview of 328 GMO events and 247 different genetic elements (status: 18/07/2013). The GMOseek matrix is aiming to facilitate GMO detection from plant origin at different phases of the analysis. It assists in selecting the targets for a screening analysis, interpreting the screening results, checking the occurrence of a screening element in a group of selected GMOs, identifying gaps in the available pool of GMO detection methods, and designing a decision tree. The GMOseek matrix is an independent database with effective functionalities in a format facilitating transferability to other platforms. Data were collected from all available sources and experimentally tested where detection methods and certified reference materials (CRMs) were available. CONCLUSIONS: The GMOseek matrix is currently a unique and very valuable tool with reliable information on GMOs from plant origin and their present genetic elements that enables further development of appropriate strategies for GMO detection. It is flexible enough to be further updated with new information and integrated in different applications and platforms. BioMed Central 2013-08-22 /pmc/articles/PMC3765097/ /pubmed/23965170 http://dx.doi.org/10.1186/1471-2105-14-256 Text en Copyright © 2013 Block et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database
Block, Annette
Debode, Frédéric
Grohmann, Lutz
Hulin, Julie
Taverniers, Isabel
Kluga, Linda
Barbau-Piednoir, Elodie
Broeders, Sylvia
Huber, Ingrid
Van den Bulcke, Marc
Heinze, Petra
Berben, Gilbert
Busch, Ulrich
Roosens, Nancy
Janssen, Eric
Žel, Jana
Gruden, Kristina
Morisset, Dany
The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants
title The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants
title_full The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants
title_fullStr The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants
title_full_unstemmed The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants
title_short The GMOseek matrix: a decision support tool for optimizing the detection of genetically modified plants
title_sort gmoseek matrix: a decision support tool for optimizing the detection of genetically modified plants
topic Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3765097/
https://www.ncbi.nlm.nih.gov/pubmed/23965170
http://dx.doi.org/10.1186/1471-2105-14-256
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