| Title |
Metabolic changes in transgenic maize mature seeds over-expressing the Aspergillus niger phyA2
|
|---|---|
| Published in |
Plant Cell Reports, November 2015
|
| DOI | 10.1007/s00299-015-1894-6 |
| Pubmed ID | |
| Authors |
Jun Rao, Litao Yang, Jinchao Guo, Sheng Quan, Guihua Chen, Xiangxiang Zhao, Dabing Zhang, Jianxin Shi |
| Abstract |
Non-targeted metabolomics analysis revealed only intended metabolic changes in transgenic maize over-expressing the Aspergillus niger phyA2. Genetically modified (GM) crops account for a large proportion of modern agriculture worldwide, raising increasingly the public concerns of safety. Generally, according to substantial equivalence principle, if a GM crop is demonstrated to be equivalently safe to its conventional species, it is supposed to be safe. In this study, taking the advantage of an established non-target metabolomic profiling platform based on the combination of UPLC-MS/MS with GC-MS, we compared the mature seed metabolic changes in transgenic maize over-expressing the Aspergillus niger phyA2 with its non-transgenic counterpart and other 14 conventional maize lines. In total, levels of nine out of identified 210 metabolites were significantly changed in transgenic maize as compared with its non-transgenic counterpart, and the number of significantly altered metabolites was reduced to only four when the natural variations were taken into consideration. Notably, those four metabolites were all associated with targeted engineering pathway. Our results indicated that although both intended and non-intended metabolic changes occurred in the mature seeds of this GM maize event, only intended metabolic pathway was found to be out of the range of the natural metabolic variation in the metabolome of the transgenic maize. Therefore, only when natural metabolic variation was taken into account, could non-targeted metabolomics provide reliable objective compositional substantial equivalence analysis on GM crops. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 25 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 20% |
| Student > Bachelor | 3 | 12% |
| Student > Doctoral Student | 2 | 8% |
| Student > Postgraduate | 2 | 8% |
| Lecturer | 1 | 4% |
| Other | 4 | 16% |
| Unknown | 8 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 28% |
| Biochemistry, Genetics and Molecular Biology | 3 | 12% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 8% |
| Medicine and Dentistry | 2 | 8% |
| Chemistry | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 10 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 November 2015.
All research outputs
#18,430,915
of 22,833,393 outputs
Outputs from Plant Cell Reports
#1,887
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Outputs of similar age
#278,383
of 386,425 outputs
Outputs of similar age from Plant Cell Reports
#11
of 30 outputs
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