Scientia Agricultura Sinica ›› 2024, Vol. 57 ›› Issue (14): 2771-2780.doi: 10.3864/j.issn.0578-1752.2024.14.006

• PLANT PROTECTION • Previous Articles     Next Articles

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

ZHANG Ying(), YUAN QingYun, REN Fang, HU GuoJun, FAN XuDong(), DONG YaFeng()   

  1. National Center for Eliminating Viruses from Deciduous Fruit Trees, Institute of Pomology, Chinese Academy of Agricultural Sciences, Xingcheng 125100, Liaoning
  • Received:2024-01-24 Accepted:2024-03-01 Online:2024-07-24 Published:2024-07-24
  • Contact: FAN XuDong, DONG YaFeng

Abstract:

【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.

Key words: grapevine berry inner necrosis virus (GINV), reverse transcription real-time quantitative PCR (RT-qPCR), grape rootstock, spatial and temporal distribution

Table 1

Sequences of GINV primers used in RT-qPCR detection"

引物名称
Primer name
目标基因
Target gene
引物/探针序列
Primer/probe sequence (5′-3′)
产物大小
Product size (bp)
GINVRPYGF2/R2 RP F: ACAGGTACGCCCACCAAACT 108
R: GCCACATCCTCGGGTTCCAT
GINVRPYGF3/R3 RP F: GCGAACCAGCTGTGCCATAC 100
R: GCAGATAGGGAGGTTCCGGC
GINVMPYGF1/R1 MP F: AGGTCTGAAAGGGTCGGCAG 102
R: GGGATGGTCGTGACACGGAAT
GINVCPYGF1/R1 CP F: GTGACAAAGCGCCAGAGATGG 163
R: GCACCCTCGCTTGAAGATGTG
GINVCPYGF2/R2 CP F: TGTGACAAAGCGCCAGAGATG 166
R: AAGCACCCTCGCTTGAAGATGT
GINVCPYGF3/R3 CP F: TTCGGAGGACAAACAGGTCCTT 108
R: ACTGTCTCCTCTGATGTCCCCT

Fig. 1

RT-PCR amplification electrophoresis of six pairs of GINV primers"

Fig. 2

Standard curve for GINV by primers GINVRPYGF2/R2 (A) and GINVRPYGF3/R3 (B)"

Fig. 3

The amplification curve of GINV detected by RT-qPCR at different temperatures (A) and primer concentrations (B)"

Fig. 4

Comparison of the sensitivity of conventional RT-PCR (A) and RT-qPCR (B) for GINV detection"

Fig. 5

GINV specificity test by RT-qPCR"

Table 2

Conventional RT-PCR and RT-qPCR GINV detection of grape samples in the field"

采集品种(株树)
Variety (Number)
时期
Period
常规RT-PCR(阳性数/总数)
Conventional RT-PCR (Positive/Total)
RT-qPCR(阳性数/总数)
RT-qPCR (Positive/Total)
贝达Beta (3) EL5 0/3 0/3
品丽珠Cabernet Franc (3)、贝达Beta (3)、SO4 (3)、101-14 (3)、140R (3)、1103P (3) EL12 15/18 18/18
EL19 12/18 18/18
EL27 18/18 18/18
EL31 18/18 18/18
品丽珠Cabernet Franc (3)、贝达Beta (3) EL35 6/6 6/6

Fig. 6

Symptoms caused by GINV on five grape rootstocks"

Fig. 7

Relative virus content in different grape rootstocks"

Fig. 8

Relative virus content at different sites in Beta at different periods"

[1]
SINGH J, COBB-SMITH D, HIGGINS E, KHAN A. Comparative evaluation of lateral flow immunoassays, LAMP, and quantitative PCR for diagnosis of fire blight in apple orchards. Journal of Plant Pathology, 2021, 103: 131-142.
[2]
TOMLINSON J A, OSTOJA-STARZEWSKA S, WEBB K, COLE J, BARNES A, DICKINSON M, BOONHAM N. A loop-mediated isothermal amplification-based method for confirmation of Guignardia citricarpa in citrus black spot lesions. European Journal of Plant Pathology, 2013, 136: 217-224.
[3]
范旭东, 董雅凤, 张尊平, 任芳, 胡国君, 朱红娟. 葡萄病毒分子检测技术研究进展. 园艺学报, 2014, 41(5): 1009-1019.
FAN X D, DONG Y F, ZHANG Z P, REN F, HU G J, ZHU H J. Progress on molecular detection of grapevine viruses. Acta Horticulturae Sinica, 2014, 41(5): 1009-1019. (in Chinese)
[4]
罗丽婷, 蒋君梅, 李向阳, 谢鑫. 环介导等温扩增(LAMP)技术在果树病毒病检测中的应用. 山地农业生物学报, 2022, 41(5): 43-52.
LUO L T, JIANG J M, LI X Y, XIE X. Application of loop-mediated isothermal amplification (LAMP) in virus disease detection of fruit trees. Journal of Mountain Agriculture and Biology, 2022, 41(5): 43-52. (in Chinese)
[5]
YOSHIKAWA N, IIDA H, GOTO S, MAGOME H, TAKAHASHI T, TERAI Y. Grapevine berry inner necrosis, a new trichovirus: Comparative studies with several known trichoviruses. Archives of Virology, 1997, 142(7): 1351-1363.

pmid: 9267448
[6]
范旭东, 胡国君, 陈绍莉, 任芳, 杜乃凡, 战良, 张尊平, 董雅凤. 我国葡萄扇叶衰退病相关病毒研究进展. 中国果树, 2023(9): 1-5.
FAN X D, HU G J, CHEN S L, REN F, DU N F, ZHAN L, ZHANG Z P, DONG Y F. Research progress of viruses associated with grapevine fanleaf degeneration disease in China. China Fruits, 2023(9): 1-5. (in Chinese)
[7]
FAN X D, ZHANG Z P, REN F, HU G J, LI C, ZHANG B D, DONG Y F. Development of a full-length infectious cDNA clone of the grapevine berry inner necrosis virus. Plants, 2020, 9(10): 1340.
[8]
FAN X D, HONG N, ZHANG Z P, YANG Z K, REN F, HU G J, LI Z N, ZHOU J, DONG Y F, WANG G P. Identification of a divergent variant of grapevine berry inner necrosis virus in grapevines showing chlorotic mottling and ring spot symptoms. Archives of Virology, 2016, 161(7): 2025-2027.

doi: 10.1007/s00705-016-2856-1 pmid: 27068163
[9]
BEUVE M, SEMPE L, LEMAIRE O. A sensitive one-step real-time RT-PCR method for detecting grapevine leafroll-associated virus 2 variants in grapevine. Journal of Virological Methods, 2007, 141: 117-124.

pmid: 17223202
[10]
AL RWAHNIH M, OSMAN F, SUDARSHANA M, UYEMOTO J, MINAFRA A, SALDARELLI P, MARTELLI G, ROWHANI A. Detection of grapevine leafroll-associated virus 7 using real time qRT-PCR and conventional RT-PCR. Journal of Virological Methods, 2012, 179: 383-389.

doi: 10.1016/j.jviromet.2011.11.026 pmid: 22172968
[11]
REN F, ZHANG Z P, FAN X D, HU G J, ZHANG M Y, DONG Y F. A sensitive SYBR Green RT-qPCR method for grapevine virus E and its application for virus detection in different grapevine sample types. Journal of Integrative Agriculture, 2020, 19(7): 1834-1841.

doi: 10.1016/S2095-3119(19)62784-X
[12]
周俊, 范旭东, 董雅凤, 张尊平, 胡国君, 任芳, 李正男. 葡萄扇叶病毒实时荧光定量RT-PCR检测方法的建立及应用. 园艺学报, 2016, 43(3): 538-548.

doi: 10.16420/j.issn.0513-353x.2015-0946
ZHOU J, FAN X D, DONG Y F, ZHANG Z P, HU G J, REN F, LI Z N. Development and application of a quantitative RT-PCR approach for quantification of grapevine fanleaf virus. Acta Horticulturae Sinica, 2016, 43(3): 538-548. (in Chinese)

doi: 10.16420/j.issn.0513-353x.2015-0946
[13]
张梦妍, 张尊平, 任芳, 胡国君, 范旭东, 董雅凤. 葡萄蚕豆萎蔫病毒实时荧光定量RT-PCR检测方法及应用. 园艺学报, 2020, 47(1): 187-194.

doi: 10.16420/j.issn.0513-353x.2019-0216
ZHANG M Y, ZHANG Z P, REN F, HU G J, FAN X D, DONG Y F. Establishment and application of a real-time fluorescent quantitative RT-PCR for detection of grapevine fabavirus. Acta Horticulturae Sinica, 2020, 47(1): 187-194. (in Chinese)

doi: 10.16420/j.issn.0513-353x.2019-0216
[14]
任芳, 董雅凤, 张尊平, 范旭东, 胡国君. 葡萄病毒A实时荧光定量RT-PCR检测技术的建立及应用. 园艺学报, 2018, 45(11): 2243-2253.

doi: 10.16420/j.issn.0513-353x.2018-0124
REN F, DONG Y F, ZHANG Z P, FAN X D, HU G J. Development and application of a quantitative RT-PCR approach for detection of grapevine virus A. Acta Horticulturae Sinica, 2018, 45(11): 2243-2253. (in Chinese)

doi: 10.16420/j.issn.0513-353x.2018-0124
[15]
王玉倩, 薛秀花. 实时荧光定量PCR技术研究进展及其应用. 生物学通报, 2016, 51(2): 1-6.
WANG Y Q, XUE X H. Research progress and application of real-time fluorescence quantitative PCR technology. Bulletin of Biology, 2016, 51(2): 1-6. (in Chinese)
[16]
COOMBE B G. Adoption of a system for identifying grapevine growth stages. Australian Journal of Grape and Wine Research, 1995, 1: 104-110.
[17]
范旭东, 董雅凤, 张尊平, 任芳, 胡国君, 朱红娟. 葡萄病毒E分子检测及基因序列分析. 植物病理学报, 2014, 44(5): 455-460.
FAN X D, DONG Y F, ZHANG Z P, REN F, HU G J, ZHU H J. Molecular identification and gene sequence analysis of grapevine virus E. Acta Phytopathologica Sinica, 2014, 44(5): 455-460. (in Chinese)
[18]
HU G J, DONG Y F, ZHU H J, ZHANG Z P, FAN X D, REN F. Detection and distribution of grapevine rupestris stem pitting- associated virus in grapevine. Scientia Horticulturae, 2018, 239: 64-69.
[19]
乾义柯, 张娜, 魏霜, 陆平, 张祥林. 基于DPO引物的SYBR Green I实时荧光RT-PCR检测葡萄卷叶伴随病毒3号. 植物保护学报, 2017, 44(2): 343-344.
QIAN Y K, ZHANG N, WEI S, LU P, ZHANG X L. Using SYBR Green I RT-PCR based on DPO primers to detect grapevine leafroll-associated virus 3. Journal of Plant Protection, 2017, 44(2): 343-344. (in Chinese)
[20]
任芳, 张尊平, 范旭东, 胡国君, 张梦妍, 董雅凤. 应用实时荧光定量RT-PCR高效检测葡萄病毒B. 植物病理学报, 2019, 49(4): 569-576.
REN F, ZHANG Z P, FAN X D, HU G J, ZHANG M Y, DONG Y F. Effective detection of grapevine virus B by real-time fluorescent quantitative RT-PCR. Acta Phytopathologica Sinica, 2019, 49(4): 569-576. (in Chinese)
[21]
FAN X D, ZHANG Z P, REN F, HU G J, ZHOU J, LI Z N, WANG G, DONG Y F. Occurrence and genetic diversity of grapevine berry inner necrosis virus from grapevines in China. Plant Disease, 2017, 101(1): 144-149.

doi: 10.1094/PDIS-05-16-0694-RE pmid: 30682318
[22]
梁子英, 刘芳. 实时荧光定量PCR技术及其应用研究进展. 现代农业科技, 2020(6): 1-3, 8.
LIANG Z Y, LIU F. Research progress on real-time quantitative PCR technology and its application. Modern Agricultural Science and Technology, 2020(6): 1-3, 8. (in Chinese)
[23]
王莹. 高温抑制柠檬黄脉病症状表现的机理初探[D]. 重庆: 西南大学, 2022.
WANG Y. Preliminary study on the mechanism of high temperature inhibiting the symptoms of lemon yellow vein clearing disease[D]. Chongqing: Southwest University, 2022. (in Chinese)
[24]
CHUNG B N, CHOI K S, AHN J J, JOA J H, DO K S, PARK K S. Effects of temperature on systemic infection and symptom expression of turnip mosaic virus in Chinese cabbage (Brassica campestris). The Plant Pathology Journal, 2015, 31: 363-370.
[25]
曹鹏, 许建建, 李楚欣, 王新亮, 王春庆, 宋晨虎, 宋震. 柑橘黄化花叶病毒的实时定量 PCR 检测及其在寄主植株中的时空分布规律. 中国农业科学, 2023, 56(18): 3574-3584. doi: 10.3864/j.issn.0578-1752.2023.18.007.
CAO P, XU J J, LI C X, WANG X L, WANG C Q, SONG C H, SONG Z. Real-time quantitative PCR detection of citrus yellow mosaic virus and its spatial and temporal distribution in host plants. Scientia Agricultura Sinica, 2023, 56(18): 3574-3584. doi: 10.3864/j.issn.0578-1752.2023.18.007. (in Chinese)
[26]
弟豆豆. 苹果坏死花叶病毒烟台分离物的鉴定与表达特性分析[D]. 烟台: 烟台大学, 2020.
DI D D. Identification and analysis of expression characteristics of apple necrosis mosaic virus Yantai isolate[D]. Yantai: Yantai University, 2020. (in Chinese)
[27]
李美璇, 张向昆, 王莉, 乔月莲, 师校欣, 杜国强. 沙地葡萄茎痘相关病毒在‘阳光玫瑰’葡萄树不同物候期和不同部位的变化规律. 中国农业科学, 2023, 56(21): 4234-4244. doi: 10.3864/j.issn.0578-1752.2023.21.008.
LI M X, ZHANG X K, WANG L, QIAO Y L, SHI X X, DU G Q. The variation of GRSPaV in different parts of shine muscat grapevines during their phenological periods. Scientia Agricultura Sinica, 2023, 56(21): 4234-4244. doi: 10.3864/j.issn.0578-1752.2023.21.008. (in Chinese)
[28]
KREBELJ A J, ČEPIN U, RAVNIKAR M, NOVAK M P. Spatio- temporal distribution of grapevine fanleaf virus (GFLV) in grapevine. European Journal of Plant Pathology, 2015, 142: 159-171.
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