Yuan Rong, Wang Miao, Li Zhen, Hong Meiyan, Su Li, Wu Gang, Zeng Xinhua
Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan, 430062, China.
College of Agriculture, Jinhua University of Vocational Technology, Jinhua, 321007, China.
Transgenic Res. 2025 Apr 5;34(1):18. doi: 10.1007/s11248-025-00438-9.
With the continuous expansion of the planting area of genetically modified (GM) crops, the demand for efficient and comprehensive monitoring systems is becoming increasingly urgent. To establish a method suitable for large-scale monitoring of genetically modified rapeseed planting, beehives were strategically deployed at specific locations around genetically modified rapeseed fields, and the TaqMan quantitative PCR (qPCR) method was used to detect and analyze the genetically modified components in the rapeseed pollen collected by bees. The results demonstrated that the average Ct values for the CaMV35S promoter, Bar gene, NPTII gene, and HPT gene in the pollen of each hive were 27.91, 29.58, 31.49, and 31.97, respectively. The average ΔCt values for these four genes in hive pollen from 100 to 200 m were - 0.35, 1.66, 2.58, and 5.06, respectively, which were significantly lower than those from 300 to 1100 m (2.85, 4.01, 6.66, and 5.63). The results of this study have demonstrated the feasibility of using pollen collected by bees for large-scale detection of genetically modified rapeseed plants. This early warning model for GM crop spread based on bee pollination provides an efficient and practical solution for monitoring and managing genetically modified crops.
随着转基因作物种植面积的不断扩大，对高效、全面监测系统的需求日益迫切。为建立一种适用于大规模监测转基因油菜种植的方法，在转基因油菜田周围的特定位置战略性地部署了蜂箱，并采用TaqMan定量PCR（qPCR）方法对蜜蜂采集的油菜花粉中的转基因成分进行检测和分析。结果表明，每个蜂箱花粉中CaMV35S启动子、Bar基因、NPTII基因和HPT基因的平均Ct值分别为27.91、29.58、31.49和31.97。100至200米处蜂箱花粉中这四个基因的平均ΔCt值分别为-0.35、1.66、2.58和5.06，显著低于300至1100米处（2.85、4.01、6.66和5.63）。本研究结果证明了利用蜜蜂采集的花粉对转基因油菜植株进行大规模检测的可行性。这种基于蜜蜂授粉的转基因作物传播预警模型为转基因作物的监测和管理提供了一种高效、实用的解决方案。
