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基于转录组数据的害虫抗药性综合检测方法
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引用本文:陈龙飞,聂僖曼,梁沛,李飞,韩召军.基于转录组数据的害虫抗药性综合检测方法.植物保护学报,2020,47(1):18-25
DOI:10.13802/j.cnki.zwbhxb.2020.2019055
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作者单位E-mail
陈龙飞 南京农业大学植物保护学院, 南京 210095  
聂僖曼 中国农业大学植物保护学院, 北京 100193  
梁沛 中国农业大学植物保护学院, 北京 100193  
李飞 浙江大学昆虫科学研究所, 杭州 310058 lifei18@zju.edu.cn 
韩召军 南京农业大学植物保护学院, 南京 210095 zjhan@njau.edu.cn 
中文摘要:为建立基于转录组数据的害虫抗药性检测方法,以3种重要害虫家蝇Musca domestica、白纹伊蚊Aedes albopictus和小菜蛾Plutella xylostella的8个抗性/敏感种群的转录组数据为对象,使用已开发的乙酰胆碱酯酶抗性突变检测程序ACE检测不同种群中的乙酰胆碱酯酶抗药性突变,并使用Bowtie 2软件和R程序包DESeq2检测其解毒酶基因的表达量变化,分析这3种害虫对有机磷类和氨基甲酸酯类杀虫剂的抗性分子基础。结果显示,在家蝇2个抗性种群KS8S3和ALHF中检测到ace2基因上发生了G227A抗药性突变,突变频率分别为0.318和1.000;在白纹伊蚊抗性种群Tem-GR中检测到CCEae3a基因的表达量较敏感种群Par-GR上调了7.175倍;在小菜蛾抗性种群ZZ中检测到ace1基因上发生A201S和G227A抗药性突变,突变频率分别为0.656和0.692。根据上述突变频率和解毒酶基因表达量变化评估的3种害虫种群抗药性情况与其之前的报道基本相符,表明基于转录组数据同时对靶标抗性机制和代谢抗性机制进行检测的害虫抗药性综合检测方法可以很好地反映害虫种群的抗药性状况。
中文关键词:害虫  抗药性检测  靶标突变  解毒酶基因  转录组数据
 
The comprehensive method for detecting insecticide resistance by RNA-Seq data analysis
Author NameAffiliationE-mail
CHEN Longfei College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, Jiangsu Province, China  
NIE Ximan College of Plant Protection, China Agricultural University, Beijing 100193, China  
LIANG Pei College of Plant Protection, China Agricultural University, Beijing 100193, China  
LI Fei Institute of Insect Sciences, Zhejiang University, Hangzhou 310058, Zhejiang Province, China lifei18@zju.edu.cn 
HAN Zhaojun College of Plant Protection, Nanjing Agricultural University, Nanjing 210095, Jiangsu Province, China zjhan@njau.edu.cn 
Abstract:In order to develop a reliable method for monitoring insecticide resistance based on RNASeq data, and to confirm the genotypes associated with resistance to organophosphates and carbamates in three important insect pests, Musca domestica, Aedes albopictus and Plutella xylostella, the RNASeq data from eight resistant/sensitive populations of these three insects were analyzed using a previously reported program, ACE, to detect the target resistant mutations in acetylcholinesterase (ace), and by Bowtie 2 and R package DESeq2 to detect the expression changes of detoxification genes. The results showed that a resistance-related mutation G227A in ace2 was detected in two resistant M. domestica populations KS8S3 and ALHF with the ratios of 0.318 and 1.000, respectively; the expression of a resistance-related detoxification gene CCEae3a in a resistant A. albopictus population Tem-GR was 7.175 fold higher than that in the sensitive population Par-GR, and two resistance-related mutations A201S and G227A in ace1 were detected in resistant ZZ population of P. xylostella with the ratios of 0.656 and 0.692, respectively. The resistance estimated in different pest populations based on the frequencies of detected mutations and the expression change of detected detoxification genes were well consistent with the previous reports of these populations. These results indicated that the estimation of the resistance level by combining the mutation frequency and the expression change of detoxification genes based on RAN-Seq data was feasible, providing a new omics-based resistance monitoring method.
keywords:insect pest  insecticide resistance detection  target mutation  detoxification gene  RNA-Seq data
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