Hou Ji Laboratory in Shanxi Province, College of Life Sciences, Shanxi Agricultural University, Jinzhong, 030801, Shanxi, China.
Crops Ecological Environment Security Inspection and Supervision Center (Taiyuan), Ministry of Agriculture and Rural Affairs, Taigu, 030801, Shanxi, China.
BMC Plant Biol. 2024 Apr 25;24(1):329. doi: 10.1186/s12870-024-05035-2.
Advancement in agricultural biotechnology has resulted in increasing numbers of commercial varieties of genetically modified (GM) crops worldwide. Though several databases on GM crops are available, these databases generally focus on collecting and providing information on transgenic crops rather than on screening strategies. To overcome this, we constructed a novel tool named, Genetically Modified Organisms Identification Tool (GMOIT), designed to integrate basic and genetic information on genetic modification events and detection methods.
At present, data for each element from 118 independent genetic modification events in soybean, maize, canola, and rice were included in the database. Particularly, GMOIT allows users to customize assay ranges and thus obtain the corresponding optimized screening strategies using common elements or specific locations as the detection targets with high flexibility. Using the 118 genetic modification events currently included in GMOIT as the range and algorithm selection results, a "6 + 4" protocol (six exogenous elements and four endogenous reference genes as the detection targets) covering 108 events for the four crops was established. Plasmids pGMOIT-1 and pGMOIT-2 were constructed as positive controls or calibrators in qualitative and quantitative transgene detection.
Our study provides a simple, practical tool for selecting, detecting, and screening strategies for a sustainable and efficient application of genetic modification.
农业生物技术的进步导致全球商业化的转基因作物品种数量不断增加。虽然有几个关于转基因作物的数据库,但这些数据库通常侧重于收集和提供关于转基因作物的信息,而不是筛选策略。为了克服这一问题,我们构建了一个名为“转基因生物识别工具”(GMOIT)的新型工具,旨在整合关于基因修饰事件和检测方法的基本和遗传信息。
目前,数据库中包含了大豆、玉米、油菜和水稻中 118 个独立基因修饰事件的每个元素的数据。特别是,GMOIT 允许用户自定义检测范围,从而使用常见元素或特定位置作为检测目标,实现高度灵活的优化筛选策略。使用目前包含在 GMOIT 中的 118 个基因修饰事件作为范围和算法选择结果,建立了一个“6+4”方案(以六个外源元件和四个内源参考基因作为检测目标),涵盖了四种作物的 108 个事件。质粒 pGMOIT-1 和 pGMOIT-2 被构建为定性和定量转基因检测的阳性对照或校准物。
我们的研究为选择、检测和筛选策略提供了一个简单实用的工具,用于实现基因修饰的可持续和高效应用。