基于HRM技术开发水稻抗条纹叶枯病基因STV11功能标记

doi:10.3724/SP.J.1006.2025.42051

摘要/Abstract

摘要： 水稻条纹叶枯病是一种由灰飞虱传播的重要病害，对水稻(Oryza sativa L.)生产造成威胁，其病原为水稻条纹叶枯病毒(rice stripe virus, RSV)。为了加快水稻条纹叶枯病抗性品种选育进程，本研究旨在开发可以快速准确鉴定水稻条纹叶枯病抗性基因的功能标记，有助于提高水稻种质改良的效率。STV11是从籼稻Kasalath中鉴定的条纹叶枯病抗性基因。根据Kasalath型条纹叶枯病基因STV11^KAS的6个碱基缺失的功能性多态性序列差异，通过NCBI查找克隆序列(登录号：LOC_Os11g30910)，针对其第773~779位核苷酸在抗感品种上的差异序列，设计基于高分辨率熔解曲线(high-resolution melting curve, HRM)的功能性分子标记stvHRM-3。进一步，对所检测品种的目标片段的PCR产物进行测序分析以验证鉴定结果，并对部分江苏省试验品种进行抗条纹叶枯病表型和基因型的分析。通过HRM-PCR检测结合测序分析，筛选了STV11基因1个功能区域的功能标记stvHRM-3。利用stvHRM-3对包括江苏省晚粳组区试、迟熟中粳预试材料以及育种中间材料、部分品种资源等在内的520份粳稻材料的STV11基因型进行检测。结果发现，217份水稻材料为抗病基因型；294份材料为感病基因型；9份材料为抗感杂合基因型。基于功能标记鉴定为抗病基因型的材料均表现出高抗或抗病表型特征。基于HRM-PCR技术开发的基因功能标记stvHRM-3可以快速高通量鉴定水稻STV11不同基因型，具有潜在的育种应用价值。

关键词: 水稻, 条纹叶枯病, STV11基因, 功能标记, HRM-PCR技术

Abstract:

Rice stripe disease, transmitted by the brown planthopper, poses a major threat to rice (Oryza sativa L.) production, particularly affecting japonica rice (Oryza sativa subsp. japonica). The causal agent is the rice stripe virus (RSV), which causes significant yield losses. To accelerate the breeding of rice varieties resistant to rice stripe disease, this study aimed to develop functional markers for the rapid and accurate identification of RSV resistance genes, thereby improving the efficiency of rice germplasm enhancement. STV11, a resistance gene identified in the indica variety Kasalath, was targeted. Based on a six-base deletion polymorphism in the Kasalath-type resistance allele STV11^KAS (LOC_Os11g30910), sequence data from NCBI were analyzed. A PCR-based functional molecular marker, stvHRM-3, was designed according to nucleotide differences at positions 773–779 between resistant and susceptible varieties. PCR amplification and sequencing of the target fragments were conducted to validate the marker’s specificity. Through HRM-PCR detection and sequencing analysis, stvHRM-3 was confirmed as a functional marker for the STV11 gene. Using this marker, the STV11 genotypes of 520 japonica rice accessions—including materials from the Jiangsu Provincial Late Japonica Rice Regional Trials, late-maturing medium japonica preliminary tests, breeding intermediates, and selected varieties—were analyzed. Results showed that 217 accessions carried the resistance allele, 294 carried the susceptibility allele, and nine exhibited a heterozygous genotype. Accessions identified as resistant through marker analysis consistently exhibited high or moderate levels of resistance. The stvHRM-3 marker, developed using HRM-PCR technology, enables rapid, high-throughput genotyping of STV11 alleles and provides an effective tool for the early screening of RSV resistance. This marker holds great potential for application in marker-assisted selection and breeding of stripe virus–resistant rice varieties.

Key words: rice, rice stripe disease, STV11, functional marker, HRM-PCR technology

王婵, 吴莹莹, 李文奇, 李霞, 王芳权, 周彤, 杨杰. 基于HRM技术开发水稻抗条纹叶枯病基因STV11功能标记[J]. 作物学报, 0, (): 0-.

WANG Chan, WU Ying-Ying, LI Wen-Qi, LI Xia, WANG Fang-Quan, ZHOU Tong, YANG Jie. Development of functional markers of rice stripe disease resistance gene STV11 based on HRM technique[J]. Acta Agronomica Sinica, 0, (): 0-.

参考文献

[1] Lu G, Yao M, Zhou Y J, Tao X R. Purification of rice stripe virus. Bio Protoc, 2020, 10: e3565.

[2] Cho W K, Lian S, Kim S M, Park S H, Kim K H. Current insights into research on rice stripe virus. Plant Pathol J, 2013, 29: 223–233.

[3] Nelson R, Wiesner-Hanks T, Wisser R, Balint-Kurti P. Navigating complexity to breed disease-resistant crops. Nat Rev Genet, 2018, 19: 21–33.

[4] Utomo H S, Linscombe S D. Current patents and future development underlying marker-assisted breeding in major grain crops. Recent Pat DNA Gene Seq, 2009, 3: 53–62.

[5] Liu X, Du Y R, Li X H, Li X L, Yang W Q, Wang Y. Breeding of a target genotype variety based on identified chalkiness marker-QTL associations in rice (Oryza sativa L.). Genet Mol Res, 2015, 14: 12894–12902.

[6] Xu Y, Zhang H Y, Kang G B, Wang Y J, Chen H. Studies of molecular marker-assisted-selection for resistance to Fusarium wilt in watermelon (Citrullus lanatus) breeding. Acta Genet Sin, 2000, 27: 151–157.

[7] Hayashi K, Kawahara Y, Maeda H, Hayano-Saito Y. Comparative analyses of Stvb-allelic genes reveal japonica specificity of rice stripe resistance in Oryza sativa. Breed Sci, 2022, 72: 333–342.

[8] Wang Q, Liu Y Q, He J, Zheng X M, Hu J L, Liu Y L, Dai H M, Zhang Y X, Wang B X, Wu W X, et al. STV11 encodes a sulphotransferase and confers durable resistance to rice stripe virus. Nat Commun, 2014, 5: 4768.

[9] Hayano-Saito Y, Saito K, Fujii K, Touyama T, Tsuji T, Sugiura N, Izawa T, Iwasaki M. SCAR marker for selection of the rice stripe resistance gene Stvb-i. Breed Res, 2000, 2: 67–72.

[10] 陈峰, 周继华, 张士永, 严长杰, 朱文银, 孙亚伟, 袁守江, 杨连群. 水稻抗条纹叶枯病基因Stv-bⁱ的分子标记辅助选择. 作物学报, 2009, 35: 597–601.
Chen F, Zhou J H, Zhang S Y, Yan C J, Zhu W Y, Sun Y W, Yuan S J, Yang L Q. Marker-assisted selection for Stv-bⁱ gene controlling resistance to rice stripe disease. Acta Agron Sin, 2009, 35: 597–601 (in Chinese with English abstract).

[11] 毛艇, 李旭, 张战, 付立东, 李振宇. 抗条纹叶枯病基因STV11的功能性分子标记建立及粳型抗源筛选. 中国水稻科学, 2016, 30: 661–667.
Mao T, Li X, Zhang Z, Fu L D, Li Z Y. Development of functional marker for rice stripe virus resistant gene STV11 and resistant germplasm selection in japonica rice. Chin J Rice Sci, 2016, 30: 661–667 (in Chinese with English abstract).

[12] Kiani S J, Donyavi T, Bokharaei-Salim F. Detection of CCR5 delta-32 mutation using high-resolution melting curve analysis: challenges and facts. Curr HIV Res, 2024, 22: 368–373.

[13] Muneeswaran K, Branavan U, de Silva V A, Dayabandara M, Hanwella R, Chandrasekharan N V. Genotyping SNPs and Indels: a method to improve the scope and sensitivity of High-Resolution melt (HRM) analysis based applications. Clin Chim Acta, 2024, 562: 119897.

[14] Jeong J, Yang Y S, Song M S, Won H Y, Han A T, Kim S. High-Resolution Melting (HRM) analysis of DNA methylation using semiconductor chip-based digital PCR. Genes Genomics, 2024, 46: 909–915.

[15] Hou Y L, You C G. High-throughput and rapid melting curve analysis. Clin Lab, 2018, 64: 1113–1119.

[16] Vologodskii A, Frank-Kamenetskii M D. DNA melting and energetics of the double helix. Phys Life Rev, 2018, 25: 1–21.

[17] Wittwer C T, Hemmert A C, Kent J O, Rejali N A. DNA melting analysis. Mol Aspects Med, 2024, 97: 101268.

[18] Waters D L E, Shapter F M. The polymerase chain reaction (PCR): general methods. Methods Mol Biol, 2014, 1099: 65–75.

[19] Lorenz T C. Polymerase chain reaction: basic protocol plus troubleshooting and optimization strategies. J Vis Exp, 2012: e3998.

[20] Mafi S, Dehghani M, Khalvati B, Abidi H, Ghorbani M, Jalali P, Whichelo R, Salehi Z, Markowska A, Reyes A, et al. Targeting PERK and GRP78 in colorectal cancer: genetic insights and novel therapeutic approaches. Eur J Pharmacol, 2024, 982: 176899.

[21] Pryor R J, Wittwer C T. Real-time polymerase chain reaction and melting curve analysis. Methods Mol Biol, 2006, 336: 19–32.

[22] 房文文, 王海凤, 郭涛, 薛芳, 姜艳芳, 张焕霞, 张士永. 基于PCR-HRM的水稻氮高效基因NRT1.1B功能标记开发及应用. 山东农业科学, 2023, 55(8): 21–26.
Fang W W, Wang H F, Guo T, Xue F, Jiang Y F, Zhang H X. Development and application of functional marker of rice nitrogen-efficient gene NRT1.1B based on PCR-HRM. Shandong Agric Sci, 2023, 55(8): 21–26 (in Chinese with English abstract).

[23] 兰莹, 杜琳琳, 林峰, 李晨羊, 周益军, 宋锦花, 许明, 周彤. 2015–2021年江苏省粳稻新品种(系)对水稻条纹叶枯病的抗性评价. 江苏农业科学, 2023, 51(24): 100–104.
Lan Y, Du Y Y, Lin F, Li C Y, Zhou Y J, Song J H, Xu M, Zhou T. Evaluation of resistance of new japonica rice varieties (lines) to rice stripe leaf blight in Jiangsu province from 2015 to 2021. Jiangsu Agric Sci, 2023, 51(24): 100–104 (in Chinese).

[24] 王才林, 张亚东, 朱镇, 姚姝, 赵庆勇, 陈涛, 周丽慧, 赵凌. 优良食味粳稻新品种南粳9108的选育与利用. 江苏农业科学, 2013, 41(9): 86–88.
Wang C L, Zhang Y D, Zhu Z, Yao S, Zhao Q Y, Chen T, Zhou L H, Zhao L. Breeding and utilization of new japonica rice variety Nanjing 9108 with good food taste. Jiangsu Agric Sci, 2013, 41(9): 86–88 (in Chinese).

[25] 王蓉. 南粳5055品种特性及高产栽培技术. 农业工程技术, 2020, 40(32): 61–62.
Wang R. Variety characteristics and high-yield cultivation techniques of Nanjing 5055. Agric Eng Technol, 2020, 40(32): 61–62 (in Chinese).

[26] 杨艳, 严贞, 杨居银. 淮稻5号品种特性及绿色栽培技术. 农业开发与装备, 2021, (1): 205–206.
Yang Y, Yan Z, Yang J Y. Variety characteristics and green cultivation techniques of Huaidao 5. Agric Dev Equip, 2021, (1): 205–206 (in Chinese).

[27] 赵凌, 朱镇, 陈涛, 赵庆勇, 赵春芳, 张亚东, 王才林. 水稻优良品种南粳46及其衍生品种特性分析. 植物遗传资源学报, 2023, 24: 648–660.
Zhao L, Zhu Z, Chen T, Zhao Q Y, Zhao C F, Zhang Y D, Wang C L. Analysis on characteristics of rice variety Nanjing 46 and its derived varieties. J Plant Genet Resour, 2023, 24: 648–660 (in Chinese with English abstract).

[28] 姜守全, 张世辉, 方杰, 李智谋, 郭君, 管锋, 姚仁祥, 伍振平. 优质晚稻农香39的特征特性及富硒高产栽培技术. 农业科技通讯, 2022, (12): 200–202.
Jiang S Q, Zhang S H, Fang J, Li Z M, Guo J, Guan F, Yao R X, Wu Z P. Characteristics of high-quality late rice Nongxiang 39 and its Se-enriched and high-yield cultivation techniques. Bull Agric Sci Technol, 2022, (12): 200–202 (in Chinese).

[29] 沈宏扬. 高产稳产优质杂交稻新组合两优粤禾丝苗. 中国种业, 2024, (9): 149–150.
Shen H Y, You B, He Y, Wang Q. Liangyouyuehe silk seedling, a new hybrid rice combination with high and stable yield and good quality. China Seed Ind, 2024, (9): 149–150 (in Chinese).

[30] Deng R L, Tao M, Xing H, Yang X L, Liu C, Liao K F, Qi L. Automatic diagnosis of rice diseases using deep learning. Front Plant Sci, 2021, 12: 701038.

相关文章 15

[1]	雷松翰, 范骏扬, 车艳奕, 代永东, 郑雨萌, 田维江, 桑贤春, 王晓雯. 水稻内卷叶突变体acl3的鉴定及调控基因的功能分析[J]. 作物学报, 2025, 51(6): 1467-1479.
[2]	李福媛, 杨奕, 马继琼, 许明辉, 林良斌, 孙一丁. 水稻OsPUB4基因克隆、激素诱导表达分析与互作蛋白筛选[J]. 作物学报, 2025, 51(6): 1690-1700.
[3]	王梦宁, 谢可冉, 高逖, 王飞, 任孝俭, 熊栋梁, 黄见良, 彭少兵, 崔克辉. 水稻幼穗分化期至抽穗期高温对籽粒形态和充实的影响及其与粒重的关系[J]. 作物学报, 2025, 51(5): 1347-1362.
[4]	盛倩男, 方娅婷, 赵剑, 杜思垚, 胡行珍, 余秋华, 朱俊, 任涛, 鲁剑巍. 不同养分管理措施对稻田和旱地油菜产量的影响及其对冻害的响应[J]. 作物学报, 2025, 51(5): 1286-1298.
[5]	翁文安, 邢志鹏, 胡群, 魏海燕, 廖萍, 朱海滨, 瞿济伟, 李秀丽, 刘桂云, 高辉, 张洪程. 无人化旱直播水稻产量形成特征及其能量与经济效益研究[J]. 作物学报, 2025, 51(5): 1363-1377.
[6]	朱建平, 李文奇, 许扬, 王芳权, 李霞, 蒋彦婕, 范方军, 陶亚军, 陈智慧, 吴莹莹, 杨杰. 水稻粉质胚乳突变体we2的表型分析与基因定位[J]. 作物学报, 2025, 51(4): 1110-1117.
[7]	潘炬忠, 韦萍, 朱德平, 邵胜雪, 陈珊珊, 韦雅倩, 高维维. 水稻转录因子OsERF104的克隆和功能研究[J]. 作物学报, 2025, 51(4): 900-913.
[8]	杨翠华, 李诗豪, 易徐徐, 郑飞雄, 杜雪竹, 盛锋. 聚-γ-谷氨酸对水稻产量、品质和养分吸收的影响[J]. 作物学报, 2025, 51(3): 785-796.
[9]	苏畅, 满福原, 王镜博, 冯晶, 姜思旭, 赵明辉. 铝胁迫下水稻osalr3突变体对外源有机酸和植物生长调节物质的响应[J]. 作物学报, 2025, 51(3): 676-686.
[10]	刘建国, 陈冬东, 陈玉玉, 易琴琴, 李清, 徐正进, 钱前, 沈兰. 水稻MKKs家族基因成员OsMKK4的不同等位基因型及自然变异对籽粒的影响[J]. 作物学报, 2025, 51(3): 598-608.
[11]	张正康, 苏延红, 阮孙美, 张敏, 张攀, 张慧, 曾千春, 罗琼. 疣粒野生稻中OgXa13的克隆和功能研究[J]. 作物学报, 2025, 51(2): 334-346.
[12]	李春梅, 陈洁, 郎兴宣, 庄海民, 朱靖, 杜梓君, 冯浩天, 金涵, 朱国林, 刘凯. 水稻矮化多分蘖基因DT1的图位克隆与功能分析[J]. 作物学报, 2025, 51(2): 347-357.
[13]	胡雅杰, 郭靖豪, 丛舒敏, 蔡沁, 徐益, 孙亮, 郭保卫, 邢志鹏, 杨文飞, 张洪程. 灌浆前期低温弱光复合处理对水稻产量和品质的影响[J]. 作物学报, 2025, 51(2): 405-417.
[14]	赵黎明, 段绍彪, 项洪涛, 郑殿峰, 冯乃杰, 沈雪峰. 干湿交替灌溉与植物生长调节剂对水稻光合特性及内源激素的影响[J]. 作物学报, 2025, 51(1): 174-188.
[15]	贾舒涵, 何璨, 陈敏, 刘家欣, 胡伟民, 胡晋, 关亚静. 杂交水稻不同穗萌程度种子质量差异与穗萌分级研究[J]. 作物学报, 2024, 50(9): 2310-2322.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed