Abstract
GC-MS based metabolomics of genetically modified rice varieties are widely reported but involves tedious derivatization processes. Broad-scale LC-MS-based metabolomics are lacking or limited to targeted analyses. In this study, metabolite diversity in natural rice variants including basmati and non-basmati rice varieties was investigated using polymeric hydrophilic interaction chromatography coupled to an Orbitrap mass analyzer. Identification was performed using exact mass and standard retention times. A total of 329 metabolites were selected using IDEOM (Identification of metabolites) software. Statistical tests were used to filter out top 50 rice varieties discriminating metabolites. Several up- or down-regulated metabolites were observed in rice varieties and can be used as biomarker compounds to differentiate between rice varieties. The developed method and generated data can be used for the comparison of genetically modified rice varieties with natural ones, an important requirement for the implementation of comparator-based GMO risk assessment procedures demanded by national and international regulations.
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