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牛病毒性腹泻病毒SYBR Green Ⅰ实时荧光定量PCR检测方法的建立及应用

Establishment and Applicaton of SYBY Green Ⅰ Quantitative Real-Time PCR for Detection of BVDV

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【作者】 任亚初朱彤楚会萌程凯慧解晓莉张亮孙阳阳杨宏军

【Author】 Ren Yachu;Zhu Tong;Chu Huimeng;Cheng Kaihui;Xie Xiaoli;Zhang Liang;Sun Yangyang;Yang Hongjun;Dairy Cattle Research Center, Shandong Academy of Agricultural Sciences;

【通讯作者】 程凯慧;杨宏军;

【机构】 山东省农业科学院奶牛研究中心

【摘要】 本研究旨在建立一种灵敏度高、特异性强、重复性好,能快速检测牛病毒性腹泻病毒(BVDV)的方法。根据BVDV的E2基因保守序列,设计合成一对特异性引物,建立了检测BVDV的SYBR GreenⅠ实时荧光定量PCR方法。将标准阳性样品10倍梯度稀释检测灵敏度,用能感染奶牛的其它病毒做对照检测特异性,用临床样本检测重复性。结果表明,该方法与能感染奶牛的其它几种病毒均无交叉反应,检出敏感度达4.87×10~1 copies/μL,比常规PCR检测方法高10倍。同时检测了5个规模化奶牛场送检的67份奶牛腹泻样本,其BVDV检出率为46.27%(31/67)。本研究成功建立了BVDV SYBR GreenⅠ实时荧光定量PCR检测方法,为BVDV的快速诊断和定量分析提供了技术支撑,具有很好的应用前景。

【Abstract】 The experiment was conducted to establish a method to rapidly detect bovine viral diarrhea virus with high sensitivity, high specificity and good reproducibility. In the study, a pair of specific primers were designed and synthesized according to the conservative sequence of E2 gene in BVDV, and the SYBR Green Ⅰquantitative real-time PCR detection method was established. The standard positive samples were diluted 10 times gradient to detect sensitivity. The specificity was tested with other viruses that could infect the cow, and the repeatability was tested with clinical samples. The results showed that this method did not have cross-react with other cow viruses, and the detection sensitivity was up to 4.87×10~1 copies/μL, which was 10 times higher than that of the conventional PCR method. At the same time, 67 diarrhea samples from 5 large-scale dairy farms were tested, and the detection rate of BVDV was 46.27%(31/67). The study successfully established BVDV SYBR Green Ⅰ quantitative real-time PCR detection method, and provided technical support for the rapid diagnosis and quantitative analysis of BVDV. It would have a better application prospect.

【基金】 “十三五”国家重点研发计划项目(2016YFD0500904,2017YFD0500904);现代农业(奶牛)产业技术体系科学家岗位项目(CARS-36);山东省自然科学基金项目(ZR2016CP09);山东省农业科学院农业科技创新工程项目(CXGC2018E14,CXGC2016B14,CXGC2016A10)
  • 【文献出处】 山东农业科学 ,Shandong Agricultural Sciences , 编辑部邮箱 ,2019年12期
  • 【分类号】S858.23
  • 【被引频次】10
  • 【下载频次】288
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