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烟草炭疽菌的分子鉴定与检测 被引量:3

Molecular identification and detection of tobacco anthracnose pathogen
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摘要 克隆并测定烟草炭疽菌r DNA全序列,序列全长2870 bp。序列比对发现,烟草炭疽菌与胶孢炭疽菌的rDNA序列相似性最高,达96.0%~96.2%;从构建的系统关系树也可以看出,烟草炭疽菌与胶孢炭疽菌聚成一个单独的分支,说明烟草炭疽菌与胶孢炭疽菌的亲缘关系最近。因此,结合烟草炭疽菌的形态学特征,可以初步将从贵州烟草分离的烟草炭疽菌鉴定为胶孢炭疽菌(Colletotrichum gloeosporioides)。根据所测烟草炭疽菌的rDNA序列设计特异性引物,不仅可以从8种不同的烟草病原真菌中鉴定出烟草炭疽菌,而且可以从7种炭疽菌中鉴定出烟草炭疽菌。用烟草炭疽菌接种普通烟,以接种发病的病组织总DNA为模板,利用该特异性引物进行PCR扩增,同样可以扩增出特异性条带,表明该方法可用于烟草炭疽菌的鉴定和快速检测。 The r DNA complete sequence of tobacco anthracnose pathogen was cloned and sequenced. The full length of the r DNA sequence is 2870 bp. Sequence comparison results showed that the rDNA of tobacco anthracnose pathogen shared a high sequence similarity(96.0%-96.2%) with that of Colletotrichum gloeosporioides. Furthermore, from the constructed phylogenetic tree, it was indicated that tobacco anthracnose pathogen and C. gloeosporioides clustered into a separate branch, which indicated that tobacco anthracnose pathogen had the closest relationship with C. gloeosporioides. Therefore, combined with its morphology characteristic, tobacco anthracnose pathogen isolated from tobacco plant in Guizhou could be preliminarily identified as C. gloeosporioides. A pair of specific primer was designed according to the rDNA sequence of tobacco anthracnose pathogen. Not only tobacco anthracnose pathogen could be identified from 8 different pathogens isolated from tobacco plants, but also it could be identified from 7 different anthracnose pathogens. Plants of Nicotiana tabacum were inoculated with tobacco anthracnose pathogen. Using the total DNA extracted from the diseased tissue as a template, a specific band could be amplified by PCR with the specific primer. It was suggested that the method could be applied for the identification and rapid detection of C. gloeosporioides from tobacco plants.
出处 《安徽农业大学学报》 CAS CSCD 北大核心 2015年第5期803-807,共5页 Journal of Anhui Agricultural University
基金 国家质检总局公益性行业科研专项项目(201210071)资助
关键词 烟草炭疽菌 RDNA序列 分子鉴定 检测 tobacco anthracnose pathogen rDNA sequence molecular identification detection
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