Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 540833
Title Use of omics analytical methods in the study of genetically modified maize varieties tested in 90 days feeding trials
Author(s) Corujo, Maria; Pla, Maria; Dijk, Jeroen van; Voorhuijzen, Marleen; Staats, Martijn; Slot, Martijn; Lommen, Arjen; Barros, Eugenia; Nadal, Anna; Puigdomènech, Pere; Paz, José Luís La; Voet, Hilko van der; Kok, Esther
Source Food Chemistry (2018). - ISSN 0308-8146
DOI https://doi.org/10.1016/j.foodchem.2018.05.109
Department(s) RIKILT - BU Toxicology Bioassays & Novel Foods
VLAG
RIKILT - Business unit Contaminants & Toxins
Biometris (PPO/PRI)
Publication type Refereed Article in a scientific journal
Publication year 2018
Keyword(s) GMO (genetically modified organism) - Metabolomics - One-class model - Proteomics - Risk assessment - Transcriptomics
Abstract

Genetically modified (GM) maize and their non-modified counterparts were compared using MON810 varieties, the only GMO event cultivated in Europe. The differences in grain samples were analysed by omics profiles, including transcriptomics, proteomics and metabolomics. Other cultivated maize varieties were analysed as a reference for the variability that will exist between cultivated varieties. The observed differences between modified and non-modified maize varieties do not exceed typical differences between non-modified varieties. The use of these advanced analytical approaches to analyse novel plant materials as compared to the results from animal feeding trials with whole foods is assessed. No indications were observed for changes in the GM varieties that warrant further investigations. Furthermore, it was shown that such indications will be obtained if maize samples of inferior quality are analysed similarly. Omics data provide detailed analytical information of the plant material, which facilitates a risk assessment procedure of new (GM) plant varieties.

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