Effect on metabolome of the grains of transgenic rice containing insecticidal cry and glyphosate tolerance epsps genes
文献类型： 外文期刊
作者： Peng, Cheng 1 ; Ding, Lin 1 ; Hu, Chaoyang 3 ; Chen, Xiaoyun 1 ; Wang, Xiaofu 1 ; Xu, Xiaoli 1 ; Li, Yueying 2 ; Xu, Junf 1 ;
作者机构： 1.Zhejiang Acad Agr Sci, State Key Lab Breeding Base Zhejiang Sustainable, Inst Qual & Stand Agroprod, Hangzhou 310021, Zhejiang, Peoples R China
2.Shenyang Normal Univ, Coll Chem & Life Sci, Shenyang 110034, Liaoning, Peoples R China
3.Ningbo Univ, Sch Marine Sci, Key Lab Marine Biotechnol Zhejiang Prov, Ningbo 315211, Zhejiang, Peoples R China
关键词： Metabolite profiling; Genetically modified organisms (GMOs); Secticidal cry gene; Glyphosate tolerance epsps gene; Correlation analysis
期刊名称：PLANT GROWTH REGULATION （ 影响因子：3.412； 五年影响因子：3.691 ）
ISSN： 0167-6903
年卷期： 2019 年 88 卷 1 期
页码：
收录情况： SCI
摘要： Genetically modified organisms (GMOs) need to be evaluated for safety before their release. Metabolome techniques provide effective methods to evaluate unintended effects. In this study, the grain metabolome of six transgenic rice lines containing secticidal cry and glyphosate tolerance epsps genes were tested by using an non-targeted metabolite profiling, and 161 and 138 metabolites were identified in grains at grain-filling stage and mature stage, respectively. The metabolic profiles of genetically modified (GM) lines and non-GM lines were all significantly different from each other at grain-filling stage. Although the levels of many metabolites were significantly changed in each transgenic line, only seven of them were simultaneously changed in all the six lines compared with those in non-GM lines at grain-filling stage. The number of significantly changed metabolites was much less at mature stage than that at grain-filling stage. Besides, none of these metabolites was simultaneously changed in all the six lines, suggesting that the metabolites of GMOs are different at different stages of GMO development. This study provides useful information about the metabolic variation between GMO and non-GMO in two development stages of rice grains. These findings suggest that non-targeted metabolite profiling can strengthen the assessment of risk based on metabolites.
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