欢迎访问作物学报,今天是

作物学报 ›› 2014, Vol. 40 ›› Issue (05): 779-787.doi: 10.3724/SP.J.1006.2014.00779

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

水稻纹枯病抗性关联分析及抗性等位变异发掘

孙晓棠,卢冬冬,欧阳林娟,胡丽芳,边建民,彭小松,陈小荣,傅军如,贺晓鹏,贺浩华*,朱昌兰*   

  1. 江西农业大学农学院 / 作物生理生态与遗传育种教育部重点实验室, 江西南昌 330045
  • 收稿日期:2014-09-24 修回日期:2014-01-12 出版日期:2014-05-12 网络出版日期:2014-03-24
  • 通讯作者: 朱昌兰, E-mail: zhuchanglan@163.com, Tel: 0791-83828171; 贺浩华, hhhua64@163.com, Tel: 0791-83828198
  • 基金资助:

    本研究由江西省重大科技专项计划(20114ABF03102),国家转基因生物新品种培育重大专项(2011ZX08001-002),高等学校博士学科点专项科研基金项目(20113603110001)和国家科技支撑计划项目(2012BAD14B1)资助。

Association Mapping and Resistant Alleles Analysis for Sheath Blight Resistance in Rice

SUN Xiao-Tang,LU Dong-Dong,OU-YANG Lin-Juan,HU Li-Fang,BIAN Jian-Min,PENG Xiao-Song,CHEN Xiao-Rong,FU Jun-Ru,HE Xiao-Peng,HE Hao-Hua*,ZHU Chang-Lan*   

  1. College of Agronomy, Jiangxi Agricultural University / Key Laboratory of Crop Physiology, Ecology and Genetic Breeding, Ministry of Education, Nanchang 330045, China
  • Received:2014-09-24 Revised:2014-01-12 Published:2014-05-12 Published online:2014-03-24

摘要:

采用苗期微室接种鉴定法,用144个分布于水稻全基因组的多态性标记,利用TASSEL软件GLM (Q)MLM (Q+K)MLM (PCA+K) 3种模型对456份水稻材料组成的自然群体进行纹枯病抗性关联分析。结果发现,有13标记位点至少在两种模型中均被检测到与纹枯病抗性显著关联,单个位点可解释表型变异的1.84%~8.42%;其中10个标记位点位于以往报道的连锁定位的抗纹枯病QTL附近,3个标记位点(RM1036RM5371RM7585)是未曾报道的新的抗病相关位点。抗性等位变异RM7585-150对纹枯病发病病级减效效应最大;有259份材料携带抗性等位变异RM5371-129占供试材料总数的56.8%,只有26份材料携带抗性等位变异RM1036-82,占供试材料总数的5.7%。水稻纹枯病发病病级与其含有的抗性等位变异数量呈极显著的负相关。本研究结果将为水稻抗纹枯病分子标记辅助育种提供理论依据。

关键词: 水稻, 纹枯病, 关联分析, 抗性等位变异

Abstract:

To identify and map sheath blight (ShB) resistance loci in rice, we carried out association analysis of 456 rice accessions using 144 genome-wide markers based on GLM (Q), MLM (Q+K), and MLM (PCA+K) models of TASSEL software. The phenotyping were assayed at the seedling stage with a micro-chamber screening method. The results showed that thirteen markers were significantly associated with ShB resistance detected by using at least two models, which explained from 1.84% to 8.42% of the phenotypic variance. In addition, ten of the identified resistant loci were either quite near or within the interval of previously identified QTLs. RM1036, RM5371, and RM7585 were novel resistant loci that had not been previously reported. The resistant allele 150 of RM7585 showed the largest negative effect to ShB rating, allele 129 of RM5371 existed in 259 (56.8%) of 456 rice accessions, and 82 of RM1036 existed in 26 (5.7%) rice accessions. The number of putative resistant alleles presented in rice was highly and significantly correlated with the decrease of ShB rating. The resistant alleles identified in this study are readily available and can be exploited for marker-assisted selection.

Key words: RiceSheath blight, Association mapping, Resistant alleles

[1]Savary S, Teng P S, Willocquet L, Nutter F W. Quantification and modeling of crop losses: a review of purposes. Annu Rev Phytopathol, 2006, 44: 89–112



[2]Pinson S R M, Capdevielle F M, Oard J H. Confirming QTLs and finding additional loci conditioning sheath blight resistance in rice using recombinant inbred lines. Crop Sci, 2005, 45: 503–510



[3]Channamallikarjuna V, Sonah H, Prasad M, Rao G J N, Chand S, Upreti H C, Singh N K, Sharma T R. Identification of major quantitative trait loci qSBR11-1 for sheath blight resistance in rice. Mol Breed, 2009, 25: 155–166



[4]Zuo S M, Yin Y J, Pan C H, Chen Z X, Zhang Y F, Zhu L H, Pan X B. Fine mapping of qSB-11LE, the QTL that confers partial resistance to rice sheath blight. Theor Appl Genet, 2013, 126: 1257–1272



[5]Che K P, Zhan Q C, Xing Q H, Wang Z P, Jin D M, He DJ, Wang B. Tagging and mapping of rice sheath blight resistant gene. Theor Appl Genet, 2003, 106: 293–297



[6]Liu G, Jia Y, Correa-Victoria F J, Prado G A, Yeater K M, McClung A, Correll J C. Mapping quantitative trait loci responsible for resistance to sheath blight in rice. Phytopathology, 2009, 99: 1078–1084



[7]谢学文, 许美容, 藏金萍, 孙勇, 朱苓华, 徐建龙, 周永力, 黎志康. 水稻抗纹枯病QTL 表达的遗传背景及环境效应. 作物学报, 2008, 34: 1885–1893



Xie X W, Xu M R, Zang J P, Sun Y, Zhu L H, Xu J L, Zhou Y L, Li Z K. Genetic background and environmental effects on expression of QTL for sheath blight resistance in reciprocal introgression lines of rice. Acta Agron Sin, 2008, 34: 1885–1893 (in Chinese with English abstract)



[8]李芳, 程立锐, 许美容, 周政, 张帆, 孙勇, 周永力, 朱苓华, 徐建龙, 黎志康. 利用品质性状的回交选择导入系挖掘水稻抗纹枯病QTL. 作物学报, 2009, 35: 1729–1737



Li F, Cheng L R, Xu M R, Zhou Z, Zhang F, Sun Y, Zhou Y L, Zhu L H, Xu J L, Li Z K. QTL mining for sheath blight resistance using the backcross selected introgression lines for grain quality in rice. Acta Agron Sin, 2009, 35: 1729–1737 (in Chinese with English abstract)



[9]Liu G, Jia Y, McClung A, Oard J H, Lee F N, Correll J C. Confirming QTLs and finding additional loci responsible for resistance to rice sheath blight disease. Plant Dis, 2013, 97: 113–117



[10]韩月澎, 邢永忠, 陈宗祥, 顾世梁, 潘学彪, 陈秀兰, 张启发. 杂交水稻亲本明恢63对纹枯病水平抗性的QTL定位. 遗传学报, 2002, 29: 565–570



Han Y P, Xing Y Z, Chen Z X, Gu S L, Pan X B, Chen X L, Zhang Q F. Mapping QTLs for horizontal resistance to sheath blight in an elite rice restorer line, Minghui63. Acta Genet Sin, 2002, 29: 565–570 (in Chinese with English abstract)



[11]Sharma A, McClung A M, Pinson S R M, Kepiro J L, Shank A R, Tabien R E, Fjellstrom R. Genetic mapping of sheath blight resistance QTLs within tropical japonica rice cultivars. Crop Sci, 2009, 49: 256–264



[12]Li Z K, Pinson S R M, Marshetti M A, Stansel J W, Park W D. Characterization of quantitative trait loci (QTLs) in cultivated rice contributing to field resistance to sheath blight (Rhizoctonia solani). Theor Appl Genet, 1995, 91: 374–381



[13]Mackay I, Powell W. Methods for linkage disequilibrium mapping in crops. Trends Plant Sci, 2007, 12: 57–63



[14]Breseghello F, Sorrells M E. Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genetics, 2006, 172: 1165–1177



[15]Huang X H, Wei X H, Sang T, Zhao Q, Feng Q, Zhao Y, Li C Y, Zhu C R, Lu T, Zhang Z W, Li M, Fan D L, Guo Y L, Wang A H, Wang L, Deng L W, Li W J, Lu Y Q, Weng Q J, Liu K Y, Huang T, Zhou T Y, Jing Y F, Li W, Lin Z, Buckler E S, Qian Q, Zhang Q F, J Y, Han B. Genome-wide association studies of 14 agronomic traits in rice landraces. Nat Genet, 2010, 42: 961-967



[16]Jia L M, Yan W G, Zhu C S, Agrama H A, Jackson A, Yeater K, Li X B, Huang B H, Hu B L, Mcclung A, Wu D X. Allelic analysis of sheath blight resistance with association mapping in rice. PLoS One, 2012, 7(3): e32703



[17]王子斌, 左示敏, 李刚, 陈夕军, 陈宗祥, 张亚芳, 潘学彪. 水稻抗纹枯病苗期快速鉴定技术研究. 植物病理学报, 2009, 39: 174–182



Wang Z B, Zuo S M, Li G, Chen X J, Chen Z X, Zhang Y F, Pan X B. Rapid identification technology of resistance to rice sheath blight in seedling stage. Acta Phytopath Sin, 2009, 39: 174–182 (in Chinese with English abstract)



[18]Jia Y, Correa-Victoria F, McClung A, Zhu L, Liu G, Wamishe Y, Xie J, Marchetti M A, Pinson S R M, Rutger J N, Correll J C. Rapid determination of rice cultivar responses to the sheath blight pathogen Rhizoctonia solani using a micro-chamber screening method. Plant Dis, 2007, 91: 485–489



[19]陈夕军, 王玲, 左示敏, 王子斌, 陈宗祥, 张亚芳, 周而勋, 郭泽建, 黄世文, 潘学彪. 水稻纹枯病寄主-病原物互作鉴别品种与菌株的筛选. 植物病理学报, 2009, 39: 514–520



Chen X J, Wang L, Zuo S M, Wang Z B, Chen Z X, Zhang Y F, Zhou E X, Guo Z J, Huang S W, Pan X B. Screening of varieties and isolates for identifying interaction between host and pathogen of rice sheath blight. Acta Phytopath Sin, 2009, 39: 514–520 (in Chinese with English abstract)



[20]Liu K, Muse S V. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics, 2005, 21: 2128–2129



[21]Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol, 2005, 14: 2611–2620



[22]Hardy O J, Vekemans X. SPAGeDi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Mol Ecol Notes, 2002, 2: 618–620



[23]Bradbury P J, Zhang Z, Kroon D E, Casstevens T M, Ramdoss Y, Buckler E S. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics, 2007, 23: 2633–2635



[24]文自翔, 赵团结, 郑永战, 刘顺湖, 王春娥, 王芳, 盖钧镒. 中国栽培和野生大豆农艺及品质性状与SSR标记的关联分析II. 优异等位变异的发掘. 作物学报, 2008, 34: 1339–1349



Wen Z X, Zhao T J, Zheng Y Z, Liu S H, Wang C E, Wang F, Gai J Y. Association analysis of agronomic and quality traits with SSR markers in Glycine max and Glycine soja in China: II. Exploration of elite alleles. Acta Agron Sin, 2008, 34: 1339–1349 (in Chinese with English abstract)



[25]左示敏, 王子斌, 陈夕军, 张亚芳, 陈夕军, 陈宗祥, 潘学彪. 水稻纹枯病改良新抗源YSBR1的抗性评价. 作物学报, 2009, 35: 608–614



Zuo S M, Wang Z B, Chen X J, Zhang Y F, Chen X J, Chen Z X, Pan X B. Evaluation of resistance of a novel rice germplasm YSBR1 to sheath blight. Acta Agron Sin, 2009, 35: 608–614 (in Chinese with English abstract)



[26]Cardon L R, Palmer J L. Population stratification and spurious allelic association. Lancet, 2003, 361: 598–604



[27]Yu J M, Pressoir G, Briggs W H, Bi I V, Yamasaki M, Doebley J F, McMullen M D, Gaut B S, Nielsen D M, Holland J B, Kresovich S, Buckler E S. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet, 2006, 38: 203–208 



[28]Zhao H H, Fernando R L, Dekkers J C. A power and precision of alternate methods for linkage disequilibrium mapping of quantitative trait loci. Genetics, 2007, 175: 1975–1986



[29]左示敏, 张亚芳, 陈宗祥, 陈夕军, 潘学彪. 水稻抗纹枯病遗传育种研究进展. 中国科学: 生命科学, 2010, 40: 1014–1023



Zuo S M, Zhang Y F, Chen Z X, Chen X J, Pan X B. Current progress in genetics and breeding in resistance to rice sheath blight. Sci Sin Vitae, 2010, 40: 1014–1023 (in Chinese with English abstract)



[30]王晓鸣, 金达生, 戴法超, 梁克恭. 作物遗传资源的抗病虫多样性与农业可持续发展. 中国农业科技导报, 2000, (5): 67–70



Wang X M, Jin D S, Dai F C, Liang K G. The diversity of resistance to disease and pest in crop germplasm and the sustainable developing on agriculture. J Agric Sci Technol, 2000, (5): 67–70 (in Chinese with English abstract)

[1] 习千辉, 徐梓瑗, 刘梦梦, 王宏艺, 郎凯琳, 井震海, 陈锋, 赵磊. 小麦籽粒铜含量的全基因组关联分析及候选基因预测[J]. 作物学报, 2026, 52(6): 1604-1617.
[2] 毛嘉琦, 黄朋雨, 赵佳佳, 郑兴卫, 武棒棒, 郝宇琼, 屈非, 刘成, 马朋涛, 郑军. 山西小麦品种白粉病抗性评价及抗病基因分子检测[J]. 作物学报, 2026, 52(6): 1669-1681.
[3] 唐宽强, 李公允, 宋美毅, 赵雪, 常春玲. 大豆株高性状全基因组关联分析及预测模型构建[J]. 作物学报, 2026, 52(6): 1743-1756.
[4] 胡赵, 钱润, 谢丰璞, 应素平. 水稻SPX基因家族鉴定及响应磷处理的表达分析[J]. 作物学报, 2026, 52(6): 1902-1912.
[5] 邹仪妹, 徐敏, 汪海洋, 姚辉, 王加峰, 刘浩, 任代胜. 两系不育系水稻幼苗根系响应盐胁迫的转录因子调控网络鉴定[J]. 作物学报, 2026, 52(6): 1728-1742.
[6] 杨欣雨, 崔文涛, 迪力尼格尔·阿力木, 汪凯翔, 吴鹏昊, 任姣姣. 玉米穗上叶片数全基因组关联分析和全基因组选择[J]. 作物学报, 2026, 52(5): 1573-1590.
[7] 闫安, 蒋昆炜, 王蓉圆, 田林, 张璐, 王韵, 徐建龙. 水稻剑叶小维管束数基因SVN7的鉴定与克隆[J]. 作物学报, 2026, 52(5): 1364-1372.
[8] 陈伟, 卫万娟, 赵其兵, 常东伟, 余凌波, 翟鹏飞, 冯志明, 陈宗祥, 任仰涛, 杨鹏, 刘海浪, 李珍富, 杨永乐, 金彦刚, 左示敏. 利用CRISPR/Cas9编辑Hd6基因创制优质早熟水稻新种质[J]. 作物学报, 2026, 52(4): 1046-1056.
[9] 石少阶, 刘凯, 陈姿夷, 王卉颖, 李三和, 周雷, 游艾青. 水稻矮化多分蘖基因DMT1的克隆与功能分析[J]. 作物学报, 2026, 52(4): 1022-1034.
[10] 张超, 郭欢, 李忠玲, 岳淑宁, 赵娜. 基于BSA-seq技术定位玉米籽粒花青素关联基因[J]. 作物学报, 2026, 52(3): 780-789.
[11] 叶凡, 李帅, 李思宇, 陈云, 窦超银, 刘立军. 不同节水灌溉方式对东北稻区水稻产量和群体质量的影响[J]. 作物学报, 2026, 52(3): 895-907.
[12] 覃奕琰, 付瑶, 苏畅, 李娜, 徐静茹, 程笑然, 张琪, 赵明辉. OsST41调控水稻苗期耐盐性的功能分析[J]. 作物学报, 2026, 52(3): 802-812.
[13] 鲁雅妮, 丁超杰, 张煜, 杜习军, 齐学礼, 胡琳, 许为钢. 河南省200份小麦品种苗期茎基腐病抗性鉴定与全基因组关联分析[J]. 作物学报, 2026, 52(2): 363-375.
[14] 李诗晴, 王茜, 王素华, 张耀文, 王丽侠. 绿豆种质资源苗期耐盐性鉴定及相关基因发掘[J]. 作物学报, 2026, 52(2): 376-388.
[15] 李云香, 郭千纤, 侯万伟, 张小娟. 引进ICARDA小麦苗期根系抗旱性状的全基因组关联分析[J]. 作物学报, 2025, 51(9): 2387-2398.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!