Literature DB >> 34097556

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

Weixiao Liu1, Haiming Zhao2, Chaohua Miao1, Wujun Jin1.   

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.

Entities:  

Keywords:  Maize seeds; gene stacking; genetically modified; iTRAQ-based quantitative proteomics; unintended effects; widely targeted metabolomics

Mesh:

Year:  2021        PMID: 34097556      PMCID: PMC8189116          DOI: 10.1080/21645698.2021.1934351

Source DB:  PubMed          Journal:  GM Crops Food        ISSN: 2164-5698            Impact factor:   3.074


  41 in total

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4.  Metabolic profiling based on LC/MS to evaluate unintended effects of transgenic rice with cry1Ac and sck genes.

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Journal:  Plant Mol Biol       Date:  2012-01-22       Impact factor: 4.076

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Authors:  Agnès E Ricroch; Jean B Bergé; Marcel Kuntz
Journal:  Plant Physiol       Date:  2011-02-24       Impact factor: 8.340

7.  A novel integrated method for large-scale detection, identification, and quantification of widely targeted metabolites: application in the study of rice metabolomics.

Authors:  Wei Chen; Liang Gong; Zilong Guo; Wensheng Wang; Hongyan Zhang; Xianqing Liu; Sibin Yu; Lizhong Xiong; Jie Luo
Journal:  Mol Plant       Date:  2013-05-23       Impact factor: 13.164

8.  A comparative proteomics approach to detect unintended effects in transgenic Arabidopsis.

Authors:  Yanfei Ren; Jun Lv; Hua Wang; Linchuan Li; Yufa Peng; Li-Jia Qu
Journal:  J Genet Genomics       Date:  2009-10       Impact factor: 4.275

9.  Mode of inheritance of primary metabolic traits in tomato.

Authors:  Nicolas Schauer; Yaniv Semel; Ilse Balbo; Matthias Steinfath; Dirk Repsilber; Joachim Selbig; Tzili Pleban; Dani Zamir; Alisdair R Fernie
Journal:  Plant Cell       Date:  2008-03-25       Impact factor: 11.277

10.  Proteomic analysis of elite soybean Jidou17 and its parents using iTRAQ-based quantitative approaches.

Authors:  Jun Qin; Feng Gu; Duan Liu; Changcheng Yin; Shuangjin Zhao; Hao Chen; Jianan Zhang; Chunyan Yang; Xu Zhan; Mengchen Zhang
Journal:  Proteome Sci       Date:  2013-03-26       Impact factor: 2.480

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  3 in total

1.  Recent applications of metabolomics in plant breeding.

Authors:  Nozomu Sakurai
Journal:  Breed Sci       Date:  2022-02-03       Impact factor: 2.014

2.  Comparative proteome analyses of rhizomania resistant transgenic sugar beets based on RNA silencing mechanism.

Authors:  Sara Hejri; Azam Salimi; Mohammad Ali Malboobi; Foad Fatehi
Journal:  GM Crops Food       Date:  2021-09-08       Impact factor: 3.074

3.  Effects of Insect-Resistant Maize 2A-7 Expressing mCry1Ab and mCry2Ab on the Soil Ecosystem.

Authors:  Shuke Yang; Xin Liu; Xiaohui Xu; Hongwei Sun; Fan Li; Chaofeng Hao; Xingbo Lu
Journal:  Plants (Basel)       Date:  2022-08-26
  3 in total

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