five

Data_Sheet_1_RNA Interference-Based Genetic Engineering Maize Resistant to Apolygus lucorum Does Not Manifest Unpredictable Unintended Effects Relative to Conventional Breeding: Short Interfering RNA, Transcriptome, and Metabolome Analysis.docx

收藏
NIAID Data Ecosystem2026-03-13 收录
下载链接:
https://figshare.com/articles/dataset/Data_Sheet_1_RNA_Interference-Based_Genetic_Engineering_Maize_Resistant_to_Apolygus_lucorum_Does_Not_Manifest_Unpredictable_Unintended_Effects_Relative_to_Conventional_Breeding_Short_Interfering_RNA_Transcriptome_and_Metabolome_Analysis_doc/19226775
下载链接
链接失效反馈
官方服务:
资源简介:
The use of omics techniques to analyze the differences between genetic engineering organisms and their parents can identify unintended effects and explore whether such unintended effects will have negative consequences. In order to evaluate whether genetic engineering will cause changes in crops beyond the changes introduced by conventional plant breeding, we compared the extent of transcriptome and metabolome modification in the leaves of three lines developed by RNA interference (RNAi)-based genetic engineering and three lines developed by conventional breeding. The results showed that both types of plant breeding methods can manifest changes at the short interfering RNA (siRNA), transcriptomic, and metabolic levels. Relative expression analysis of potential off-target gene revealed that there was no broad gene decline in the three RNAi-based genetic engineering lines. We found that the number of DEGs and DAMs between RNAi-based genetic engineering lines and the parental line was less than that between conventional breeding lines. These unique DEGs and DAMs between RNAi-based genetic engineering lines and the parental lines were not enriched in detrimental metabolic pathways. The results suggest that RNAi-based genetic engineering do not cause unintended effects beyond those found in conventional breeding in maize.
创建时间:
2022-02-24
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作