Effects of stacking breeding on the methylome and transcriptome profile of transgenic rice with glyphosate tolerance
文献类型: 外文期刊
作者: Xujing Wang;Shance Niu;Jiangtao Yang;Yufeng Dong;Xiaojing Liu;Yue Jiao;Zhixing Wang
作者机构:
关键词: Gene interaction;Methylome;Stacking breeding;Transcriptomics;Unintended effects
期刊名称: Planta
ISSN: 0032-0935
年卷期: 2023 年 258 卷 2 期
页码:
收录情况: SCIE(2023版)
摘要: Main conclusion: Transcriptomics and methylomics were used to identify the potential effects resulting from GM rice breeding stacks, which provided scientific data for the safety assessment strategy of stacked GM crops in China. Abstract: Gene interaction is one of the main concerns for stacked genetically modified crop safety. With the development of technology, the combination of omics and bioinformatics has become a useful tool to evaluate the unintended effects of genetically modified crops. In this study, transcriptomics and methylomics were used as molecular profiling techniques to identify the potential effects of stack through breeding. Stacked transgenic rice En-12 × Ec-26 was used as material, which was obtained through hybridization using parents En-12 and Ec-26, in which the foreign protein can form functional EPSPS protein by intein-mediated trans-splitting. Differentially methylated region (DMR) analysis showed that the effect of stacking breeding on methylation was less than that of genetic transformation at the methylome level. Differentially expressed gene (DEG) analysis showed that the DEGs between En-12 × Ec-26 and its parents were far fewer than those between transgenic rice and Zhonghua 11 (ZH11), and no unintended new genes were found in En-12 × Ec-26. Statistical analysis of gene expression and methylation involved in shikimic acid metabolism showed that there was no difference in gene expression, although there were 16 and 10 DMR genes between En-12 × Ec-26 and its parents (En and Ec) in methylation, respectively. The results indicated that the effect of stacking breeding on gene expression and DNA methylation was less than the effect of genetic transformation. This study provides scientific data supporting safety assessments of stacked GM crops in China.
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