Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops

被引:271
作者
Catchpole, GS
Beckmann, M
Enot, DP
Mondhe, M
Zywicki, B
Taylor, J
Hardy, N
Smith, A
King, RD
Kell, DB
Fiehn, O
Draper, J [1 ]
机构
[1] Univ Wales, Inst Biol Sci, Aberystwyth SY23 3DA, Dyfed, Wales
[2] Univ Wales, Dept Comp Sci, Aberystwyth SY23 3DA, Dyfed, Wales
[3] Max Planck Inst Mol Plant Physiol, D-14424 Golm, Germany
基金
英国生物技术与生命科学研究理事会;
关键词
genetically modified substantial equivalence; machine learning;
D O I
10.1073/pnas.0503955102
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:14458 / 14462
页数:5
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