TY - JOUR
T1 - Hierarchical metabolomics demonstrates substantial compositional similarity between genetically-modified and conventional potato crops
AU - Catchpole, Gareth
AU - Beckmann, Manfred
AU - Enot, David Pierre Louis
AU - Mondhe, Madhav
AU - Zywicki, Britta
AU - Taylor, Janet
AU - Hardy, Nigel William
AU - Smith, Aileen Roberta
AU - King, Ross Donald
AU - Kell, Douglas B.
AU - Fiehn, Oliver
AU - Draper, John
N1 - Catchpole, G. S., Beckmann, M., Enot, D. P., Mondhe, M., Zywicki, B., Taylor, J., Hardy, N., Smith, A., King, R. D., Kell, D. B., Fiehn, O., Draper, J. (2005). Hierarchical metabolomics demonstrates substantial compositional similarity between genetically-modified and conventional potato crops. Proceedings of the National Academy of Science USA, 102 (40), 14458-14462.
Sponsorship: Food Standards Agency (London)
PY - 2005/10/4
Y1 - 2005/10/4
N2 - There is current debate whether genetically modified (GM) plants might contain unexpected, potentially undesirable changes in overall metabolite composition. However, appropriate analytical technology and acceptable metrics of compositional similarity require development. We describe a comprehensive comparison of total metabolites in field-grown GM and conventional potato tubers using a hierarchical approach initiating with rapid metabolome “fingerprinting” to guide more detailed profiling of metabolites where significant differences are suspected. Central to this strategy are data analysis procedures able to generate validated, reproducible metrics of comparison from complex metabolome data. We show that, apart from targeted changes, these GM potatoes in this study appear substantially equivalent to traditional cultivars.
AB - There is current debate whether genetically modified (GM) plants might contain unexpected, potentially undesirable changes in overall metabolite composition. However, appropriate analytical technology and acceptable metrics of compositional similarity require development. We describe a comprehensive comparison of total metabolites in field-grown GM and conventional potato tubers using a hierarchical approach initiating with rapid metabolome “fingerprinting” to guide more detailed profiling of metabolites where significant differences are suspected. Central to this strategy are data analysis procedures able to generate validated, reproducible metrics of comparison from complex metabolome data. We show that, apart from targeted changes, these GM potatoes in this study appear substantially equivalent to traditional cultivars.
KW - genetically modified substantial equivalence machine learning
U2 - 10.1073/pnas.0503955102
DO - 10.1073/pnas.0503955102
M3 - Article
SN - 1091-6490
VL - 102
SP - 14458
EP - 14462
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
IS - 40
ER -