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转基因和基因叠加玉米品系种子的蛋白质组学和代谢组学综合分析。

Integrated proteomics and metabolomics analysis of transgenic and gene-stacked maize line seeds.

机构信息

Biotechnology Research Institute, Chinese Agricultural and Academic Sciences, Beijing, P.R. China.

State Key Laboratory of Agrobiotechnology and National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, P. R. China.

出版信息

GM Crops Food. 2021 Jan 2;12(1):361-375. doi: 10.1080/21645698.2021.1934351.

Abstract

Unintended effects of genetically modified (GM) crops may pose safety issues. Omics techniques provide researchers with useful tools to assess such unintended effects. Proteomics and metabolomics analyses were performed for three GM maize varieties, 2A-7, CC-2, and 2A-7×CC-2 stacked transgenic maize, and the corresponding non-GM parent Zheng58.Proteomics revealed 120, 271 and 135 maize differentially expressed proteins (DEPs) in the 2A-7/Zheng58, CC-2/Zheng58 and 2A-7×CC-2/Zheng58 comparisons, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that most DEPs participated in metabolic pathways and the biosynthesis of secondary metabolite. Metabolomics revealed 179, 135 and 131 differentially accumulated metabolites (DAMs) in the 2A-7/Zheng58, CC-2/Zheng58 and 2A-7×CC-2/Zheng58 comparisons, respectively. Based on KEGG enrichment analysis, most DAMs are involved in the biosynthesis of secondary metabolite and metabolic pathways. According to integrated proteomics and metabolomics analysis, the introduction of exogenous EPSPS did not affect the expression levels of six other enzymes or the abundance of seven metabolites involved in the shikimic acid pathway in CC-2 and 2A-7×CC-2 seeds. Six co-DEPs annotated by integrated proteomics and metabolomics pathway analysis were further analyzed by qRT-PCR.This study successfully employed integrated proteomic and metabolomic technology to assess unintended changes in maize varieties. The results suggest that GM and gene stacking do not cause significantly unintended effects.

摘要

转基因作物的非预期效应可能会带来安全问题。组学技术为研究人员评估这些非预期效应提供了有用的工具。本研究对三个转基因玉米品种 2A-7、CC-2 和 2A-7×CC-2 及其相应的非转基因亲本郑 58 进行了蛋白质组学和代谢组学分析。蛋白质组学分析显示,在 2A-7/郑 58、CC-2/郑 58 和 2A-7×CC-2/郑 58 比较中,分别有 120、271 和 135 个玉米差异表达蛋白(DEPs)。京都基因与基因组百科全书(KEGG)通路富集分析表明,大多数 DEPs 参与代谢途径和次生代谢物的生物合成。代谢组学分析显示,在 2A-7/郑 58、CC-2/郑 58 和 2A-7×CC-2/郑 58 比较中,分别有 179、135 和 131 个差异积累代谢物(DAMs)。基于 KEGG 富集分析,大多数 DAMs 参与次生代谢物和代谢途径的生物合成。根据整合的蛋白质组学和代谢组学分析,外源性 EPSPS 的引入并未影响 CC-2 和 2A-7×CC-2 种子中其他六种酶的表达水平或 7 种参与莽草酸途径的代谢物的丰度。通过整合蛋白质组学和代谢组学途径分析注释的六个共同 DEPs 进一步通过 qRT-PCR 进行分析。本研究成功地采用了整合的蛋白质组学和代谢组学技术来评估玉米品种的非预期变化。结果表明,转基因和基因叠加不会导致明显的非预期效应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a0a/8189116/ba4f702781b6/KGMC_A_1934351_F0001_OC.jpg

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