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葡萄浆果内坏死病毒RT-qPCR检测技术建立及其在葡萄砧木中的时空分布规律OA北大核心CSTPCD

Establishment of RT-qPCR Detection Technology for GINV and Its Spatial and Temporal Distribution in Different Grape Rootstocks

中文摘要英文摘要

[背景]葡萄浆果内坏死病毒(grapevine berry inner necrosis virus,GINV)是近年来在中国报道的一种正单链RNA 病毒,该病毒发生普遍且危害严重.高灵敏的检测技术是病毒田间监测和无病毒苗木培育的关键.[目的]建立灵敏度较高的GINV逆转录实时荧光定量PCR(reverse transcription real-time quantitative PCR,RT-qPCR)检测体系;明确不同葡萄砧木对GINV的敏感性;明确GINV在寄主植株中的时空分布规律,为该病毒的监测预警提供技术支撑.[方法]根据GenBank已登录GINV的复制酶(replicase,RP)、移动蛋白(movement protein,MP)和外壳蛋白(coat protein,CP)基因保守序列设计 6 套引物,通过常规RT-PCR和RT-qPCR筛选特异性强、扩增效果好的引物.再通过对退火温度和引物浓度等反应条件的优化建立GINV的SYBR Green I染料法RT-qPCR检测体系,并进一步对该技术的灵敏度、特异性和田间适用性进行评价.将GINV接种到贝达、SO4、101-14、140R和 1103P 5种葡萄砧木上进行症状观察和病毒检测,以筛选GINV敏感性较高的指示植物.基于所建立的RT-qPCR技术对接种GINV葡萄砧木的不同生长时期、不同部位样品进行GINV检测,从而明确GINV在不同葡萄砧木的时空分布规律.[结果]建立了GINV SYBR Green I染料法RT-qPCR检测技术体系,其最佳引物为GINVRPYGF2/R2,最佳引物浓度为 300 nmol·L-1,最佳退火温度为 58.4℃.该技术对GINV的检测特异性强,其检测灵敏度达常规RT-PCR的1 000倍.症状观察结果表明贝达感染GINV的症状最为严重,表现为叶片系统性坏死,而其他砧木叶片仅表现褪绿斑驳和环斑症状.RT-qPCR检测结果表明GINV在EL27 时期(坐果期)的相对含量最高,5 个品种间的病毒相对含量在EL12(花序分明期)和EL27时期间无显著差异,EL31时期(果实增大期)的贝达与SO4、101-14、140R和1103P的病毒相对含量存在显著差异;GINV 的相对含量在不同组织部位存在较大差异,由高到低依次为下部叶片、上部叶片、上部茎秆、下部茎秆、根部.[结论]建立了灵敏度高、特异性强的GINV RT-qPCR检测方法,利用该方法明确了GINV在不同葡萄砧木的时空分布规律.

[Background]Grapevine berry inner necrosis virus(GINV)is a positive single-stranded RNA virus reported in China in recent years,which is widespread and harmful.Highly sensitive detection technology is the key for field monitoring of the virus and the cultivation of virus-free seedlings.[Objective]The objective of this study is to establish a high-sensitivity reverse transcription real-time quantitative PCR(RT-qPCR)detection system for GINV,clarify the sensitivity of different grape rootstocks to GINV,and to clarify the spatial and temporal distribution of GINV in host plants,so as to provide technical support for the monitoring and early warning of the virus.[Method]Six sets of primers were designed according to the conserved sequences of replicase(RP),movement protein(MP)and coat protein(CP)genes registered in GenBank.The primers with strong specificity and good amplification effect were screened by conventional RT-PCR and RT-qPCR.Then,the annealing temperature and concentration of the primers were optimized to establish the SYBR Green I dye RT-qPCR detection system for GINV,and the sensitivity,specificity and field applicability of this system were further evaluated.GINV was inoculated into five grape rootstocks,including Beta,SO4,101-14,140R and 1103P,for symptom observation and virus detection to screen indicator plants with high GINV sensitivity.Based on the established RT-qPCR technology,samples of different grape rootstocks inoculated with GINV were detected at different stages and different parts,so as to clarify the spatial and temporal distribution of GINV in different grape rootstocks.[Result]The SYBR Green I dye RT-qPCR detection technology system for GINV was established,and the optimal primer was GINVRPYGF2/R2 and the optimal primer concentration was 300 nmol·L-1,the optimal annealing temperature was 58.4℃.This technique had strong specificity and high sensitivity for GINV detection,and its detection sensitivity was 1 000 times that of conventional RT-PCR.The observation results of GINV inoculation into different grape rootstocks showed that Beta was the most severe in GINV infection,which was manifested as systemic necrosis of leaves,while the leaves of other rootstocks only showed the symptoms of green mottling and ring spots.The results of RT-qPCR showed that the relative content of GINV was the highest in EL27(setting stage),and there was no significant difference in the relative content of GINV among the five varieties during EL12(inflorescence clear stage)and EL27,and there were significant differences in the relative content of GINV between Beta and SO4,101-14,140R and 1103P in EL31(berries pea size stage),and the relative content of GINV varied greatly in different tissues,and the order from high to low was lower leaves,upper leaves,upper stems,lower stems and roots.[Conclusion]A high-sensitivity and strong-specificity RT-qPCR method for the detection of GINV was established,and the spatial and temporal distribution of GINV in different grape rootstocks was clarified by this method.

张英;原青云;任芳;胡国君;范旭东;董雅凤

中国农业科学院果树研究所国家落叶果树脱毒中心,辽宁兴城 125100

葡萄浆果内坏死病毒逆转录实时荧光定量PCR葡萄砧木时空分布

grapevine berry inner necrosis virus(GINV)reverse transcription real-time quantitative PCR(RT-qPCR)grape rootstockspatial and temporal distribution

《中国农业科学》 2024 (014)

2771-2780 / 10

国家现代农业(葡萄)产业技术体系(CARS-29-bc-1)、中国农业科学院科技创新工程(CAAS-ASTIP-RIP)

10.3864/j.issn.0578-1752.2024.14.006

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