Literature DB >> 29356248

Effect on transcriptome and metabolome of stacked transgenic maize containing insecticidal cry and glyphosate tolerance epsps genes.

Xu-Jing Wang1, Xin Zhang1, Jiang-Tao Yang1, Zhi-Xing Wang1.   

Abstract

Gene stacking is a developing trend in agricultural biotechnology. Unintended effects in stacked transgenic plants are safety issues considered by the public and researchers. Omics techniques provide useful tools to assess unintended effects. In this paper, stacked transgenic maize 12-5×IE034 that contained insecticidal cry and glyphosate tolerance G10-epsps genes was obtained by crossing of transgenic maize varieties 12-5 and IE034. Transcriptome and metabolome analyses were performed for different maize varieties, including 12-5×IE034, 12-5, IE034, and conventional varieties collected from different provinces in China. The transcriptome results were as follows. The nine maize varieties had obvious differences in gene expression. There were 3561-5538 differentially expressed genes between 12-5×IE034 and its parents and transgenic receptor, which were far fewer than the number of differentially expressed genes in different traditional maize varieties. Cluster analysis indicated that there were close relationships between 12-5×IE034 and its parents. The metabolome results were as follows. For the nine detected maize varieties, the number of different metabolites ranged from 0 to 240. Compared with its parents, 12-5 and IE034, the hybrid variety 12-5×IE034 had 15 and 112 different metabolites, respectively. Hierarchical cluster analysis with Pearson's correlation analysis showed that the differences between 12-5×IE034 and its parents were fewer than those between other maize varieties. Shikimate pathway-related genes and metabolites analysis results showed that the effects of hybrid stacking are less than those from transformation and differing genotypes. Thus, the differences due to breeding stack were fewer than those due to natural variation among maize varieties. This paper provides scientific data for assessing unintended effects in stacked transgenic plants.
© 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

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Keywords:  breeding stack; metabolome; transcriptome; transgenic maize plant; unintended effect

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Year:  2018        PMID: 29356248     DOI: 10.1111/tpj.13825

Source DB:  PubMed          Journal:  Plant J        ISSN: 0960-7412            Impact factor:   6.417


  15 in total

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