NMR-based metabonomic study of transgenic maize
| Autor: | Lorena Casciani, Cecilia Castro, Mario Motto, Cesare Manetti, Giuseppe D'Ascenzo, Cristiano Bianchetti, Maria Enrica Di Cocco, Mariano Bizzarri, Filippo Conti, Maurizio Delfini, Alfredo Miccheli, Aldo Laganà |
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| Rok vydání: | 2004 |
| Předmět: |
Multivariate statistics
Magnetic Resonance Spectroscopy Metabolite Gene Expression Plant Science Computational biology partial least squares-discriminant analysis Horticulture Biology maize Zea mays Biochemistry chemistry.chemical_compound metabonomics Least-Squares Analysis assay for genetic modification Molecular Biology Plant Proteins Principal Component Analysis Genetically modified maize business.industry Genetic Variation food and beverages General Medicine Plants Genetically Modified Nmr data Biotechnology nuclear magnetic resonance chemistry principal component analysis Seeds Principal component analysis business |
| Zdroj: | Phytochemistry. 65:3187-3198 |
| ISSN: | 0031-9422 |
| DOI: | 10.1016/j.phytochem.2004.10.015 |
| Popis: | The aim of this research was to verify the possibility of identifying and classifying maize seeds obtained from transgenic plants, in different classes according to the modification, on the basis of the concerted variation in metabolite levels detected by NMR spectra. It was possible to recognise the discriminant metabolites of transgenic samples as well as to classify non-a priori defined samples of maize. It is important to underline that the obtained results are useful to point out the metabolic consequences of a specific genic modification on a plant, without using a targeted analysis of the different metabolites, in fact it was possible to classify the seeds also without the complete assignment of the spectra. The analysis was performed by applying multivariate techniques (principal component analysis and partial least squares-discriminant analysis) to NMR data. |
| Databáze: | OpenAIRE |
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