Literature DB >> 22509807

Proteomics insight into the biological safety of transgenic modification of rice as compared with conventional genetic breeding and spontaneous genotypic variation.

Chun Yan Gong1, Qi Li, Hua Tao Yu, Zizhang Wang, Tai Wang.   

Abstract

The potential of unintended effects caused by transgenic events is a key issue in the commercialization of genetically modified (GM) crops. To investigate whether transgenic events cause unintended effects, we used comparative proteomics approaches to evaluate proteome differences in seeds from 2 sets of GM indica rice, herbicide-resistant Bar68-1 carrying bar and insect-resistant 2036-1a carrying cry1Ac/sck, and their respective controls D68 and MH86, as well as indica variety MH63, a parental line for breeding MH86, and japonica variety ZH10. This experimental design allowed for comparing proteome difference caused by transgenes, conventional genetic breeding, and natural genetic variation. Proteomics analysis revealed the maximum numbers of differentially expressed proteins between indica and japonica cultivars, second among indica varieties with relative small difference between MH86 and MH63, and the minimum between GM rice and respective control, thus indicating GM events do not substantially alter proteome profiles as compared with conventional genetic breeding and natural genetic variation. Mass spectrometry analysis revealed 234 proteins differentially expressed in the 6 materials, and these proteins were involved in different cellular and metabolic processes with a prominent skew toward metabolism (31.2%), protein synthesis and destination (25.2%), and defense response (22.4%). In these seed proteomes, proteins implicated in the 3 prominent biological processes showed significantly different composite expression patterns and were major factors differentiating japonica and indica cultivars, as well as indica varieties. Thus, metabolism, protein synthesis and destination, and defense response in seeds are important in differentiating rice cultivars and varieties.

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Year:  2012        PMID: 22509807     DOI: 10.1021/pr300148w

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  16 in total

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Journal:  Proteome Sci       Date:  2015-05-02       Impact factor: 2.480

2.  Comparative Proteomics of Leaves from Phytase-Transgenic Maize and Its Non-transgenic Isogenic Variety.

Authors:  Yanhua Tan; Xiaoping Yi; Limin Wang; Cunzhi Peng; Yong Sun; Dan Wang; Jiaming Zhang; Anping Guo; Xuchu Wang
Journal:  Front Plant Sci       Date:  2016-08-17       Impact factor: 5.753

3.  A proteomic analysis of seeds from Bt-transgenic Brassica napus and hybrids with wild B. juncea.

Authors:  Yongbo Liu; Ying-Xue Zhang; Song-Quan Song; Junsheng Li; C Neal Stewart; Wei Wei; Yujie Zhao; Wei-Qing Wang
Journal:  Sci Rep       Date:  2015-10-21       Impact factor: 4.379

4.  An integrated multi-omics analysis of the NK603 Roundup-tolerant GM maize reveals metabolism disturbances caused by the transformation process.

Authors:  Robin Mesnage; Sarah Z Agapito-Tenfen; Vinicius Vilperte; George Renney; Malcolm Ward; Gilles-Eric Séralini; Rubens O Nodari; Michael N Antoniou
Journal:  Sci Rep       Date:  2016-12-19       Impact factor: 4.379

5.  Proteomic analysis of phytase transgenic and non-transgenic maize seeds.

Authors:  Yanhua Tan; Zheng Tong; Qian Yang; Yong Sun; Xiang Jin; Cunzhi Peng; Anping Guo; Xuchu Wang
Journal:  Sci Rep       Date:  2017-08-23       Impact factor: 4.379

6.  iTRAQ-based quantitative tissue proteomic analysis of differentially expressed proteins (DEPs) in non-transgenic and transgenic soybean seeds.

Authors:  Weixiao Liu; Wentao Xu; Liang Li; Mei Dong; Yusong Wan; Xiaoyun He; Kunlun Huang; Wujun Jin
Journal:  Sci Rep       Date:  2018-12-05       Impact factor: 4.379

7.  Carbon and nitrogen partitioning of transgenic rice T2A-1 (Cry2A*) with different nitrogen treatments.

Authors:  Lin Ling; Xuexue Li; Kangxu Wang; Mingli Cai; Yang Jiang; Cougui Cao
Journal:  Sci Rep       Date:  2019-03-29       Impact factor: 4.379

8.  Morpho-Physiological and Proteomic Response of Bt-Cotton and Non-Bt Cotton to Drought Stress.

Authors:  Swetha Sudha Nagamalla; Malini Devi Alaparthi; Sunitha Mellacheruvu; Ravindar Gundeti; Jana Priya Sony Earrawandla; Someswar Rao Sagurthi
Journal:  Front Plant Sci       Date:  2021-05-10       Impact factor: 5.753

9.  Proteomics: a biotechnology tool for crop improvement.

Authors:  Moustafa Eldakak; Sanaa I M Milad; Ali I Nawar; Jai S Rohila
Journal:  Front Plant Sci       Date:  2013-02-28       Impact factor: 5.753

10.  Proteomic evaluation of genetically modified crops: current status and challenges.

Authors:  Chun Yan Gong; Tai Wang
Journal:  Front Plant Sci       Date:  2013-03-07       Impact factor: 5.753

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