Scientia Agricultura Sinica ›› 2012, Vol. 45 ›› Issue (15): 3029-3039.doi: 10.3864/j.issn.0578-1752.2012.15.003

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

QTL Analysis of Lodging-Resistance Related Traits in Soybean in Different Environments

 FAN  Dong-Mei, YANG  Zhen, MA  Zhan-Zhou, ZENG  Qing-Li, DU  Xiang-Yu, JIANG  Hong-Wei, LIU  Chun-Yan, HAN  Dong-Wei, LUAN  Huai-Hai, PEI  Yu-Feng, CHEN  Qing-Shan, HU  Guo-Hua   

  1. 1.东北农业大学农学院，哈尔滨 150030
    2.黑龙江省农垦科研育种中心，哈尔滨 150090
    3.黑龙江省农业科学院齐齐哈尔分院，黑龙江齐齐哈尔 161041
    4.国家大豆工程技术研究中心，哈尔滨 150050
  • Received:2012-02-27 Online:2012-08-01 Published:2012-04-26

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Abstract: 【Objective】The objective of this study is to locate consensus QTLs of lodging-resistance related traits of soybean for breeding lodging-resistance varieties and increase yield of soybean, and convenience for mechanization harvest.【Method】In order to find out the steady and repeatable QTLs of these traits, a F2:16-F2:18 RIL population containing 147 lines derived from a cross between Charleston as female and Dongnong 594 as male parent were used in this experiment. A genetic linkage map was constructed with 164 SSR primers screened in two parents and amplified in 147 lines population. Nodes in main stem, stem thickness and stem weight QTLs of soybean were analyzed in two sites in three years. 【Result】 Sixteen nodes in main stem QTLs were detected in A1, B1, C2, D1a, D2, F, G, H and N linkage group, respectively. Ten stem thickness QTLs were detected in A1, B1, C2, D1a, E and G linkage group, respectively. Fifteen stem weight QTLs were detected in A1, A2, C2, D1a, D1b and G linkage group, respectively. In these QTLs, five QTLs for nodes in main stem, one QTLs for stem thickness and six QTLs for stem weight could be detected together by CIM and MIM, accounting for 8.6%-27.0%, 9.0%-11.0%, and 6.0%-39.0% of the general phenotypic variation, respectively. Three QTLs for nodes in main stem QTLs and two QTLs for stem weight could be detected together in more than two years, accounting for 8.0%-60.2% and 10.0%-23.0% of the general phenotypic variation, respectively. 【Conclusion】 Compared with QTLs mapped for nodes in main stem, stem thickness and stem weight, relatively large genetic correlation was found among lodging-resistance related traits of soybean.

Key words: soybean, lodging, QTL analysis

[1]Noor R B M, Caviness C E. Influence of induced lodging on pod distribution and seed yield in soybeans. Agronomy Journal, 1980, 72: 904-906.

[2]Wilcox J R, Sediyama T. Interrelationships among height, lodging and yield in determinate and indeterminate soybeans. Euphytica, 1981, 30: 323-326.

[3]Shapiro C A, Flowerday A D. Effect of simulated lodging on soybean yield. Journal of Agronomy and Crop Science, 1987, 158: 8-16.

[4]王  勇, 李朝恒. 小麦品种抗倒性的研究进展. 山东农业大学学报, 1996, 27(4): 503-508.

Wang Y, Li C H. Advances in the study of wheat lodging resistance. Journal of Shandong Agricultural University, 1996, 27(4): 503-508. (in Chinese)

[5]杨慧杰, 杨仁崔, 李义珍, 姜照伟, 郑景生. 水稻茎秆性状与倒伏性的关系. 福建农业科学, 2000, 15(2): 1-7.

Yang H J, Yang R C, Li Y Z, Jiang Z W, Zheng J S. Relationship between culm traits and lodging resistance of rice cultivars. Fujian Journal of Agricultural Sciences, 2000, 15(2): 1-7. (in Chinese)

[6]周丽华. 水稻茎秆性状与抗倒伏关系的研究综述. 中国水稻, 2006, 3: 10-11.

Zhou L H. Research of the culm trait and lodging relationship in rice. 2006, 3: 10-11. (in Chinese)

[7]张忠旭, 陈温福, 杨振玉, 华泽田, 高日玲, 高  勇, 赵迎春. 水稻抗倒伏能力与茎秆物理性状的关系及其对产量的影响. 沈阳农业大学学报, 1999, 30(2): 81-85.

Zhang Z X, Chen W F, Yang Z Y, Hua Z T, Gao R L, Gao Y, ZhaoY C. Effect of lodging resistance on yield and its relationship with stalk physical characteristics. Journal of Shengyang Agricultural University, 1999, 30(2): 81-85. (in Chinese)

[8]王  勇, 李晴祺. 小麦品种抗倒性评价方法的研究. 华北农业科学, 1995, 10(3): 84-88.

Wang Y, Li Q Q. Evaluation method of stem lodging resistance in wheat. Acta Agriculturae Boreali-Sinica, 1995, 10(3): 84-88. (in Chinese)

[9]Lee S H, Bailey M A, Mian M A R, Carter Jr T E, Ashley D A, Hussey R S, Parrott W A, Boerma H R. Molecular markers associated with soybean plant height, lodging, and maturity across locations. Crop Science, 1996, 36: 728-735.

[10]Orf J H, Chase K, Jarvik T, Mansur L M, Cregan P B, Adler F R, Lark K G. Genetics of soybean agronomic traits: I. Comparison of three related recombinant inbred populations. Crop Science, 1999, 39: 1642-1651.

[11]Wang D, Graef G L, Procopiuk A M, Diers B W. Identification of putative QTL that underlie yield in interspecific soybean backcross populations. Theoretical and Applied Genetics, 2004, 108: 458-467.

[12]Kabelka E A, Diers B W, Fehr W R, LeRoy A R, Baianu I C, You T. Neece D J, Nelson R L. Putative alleles for increased yield from soybean plant introductions. Crop Science Society of America, 2004, 44: 784-791.

[13]Zhang W K, Wang Y J, Luo G Z, Zhang J S, He C Y, Wu X L, Gai J  Y, Chen S Y. QTL mapping of ten agronomic traits on the     soybean (Glycine max L. Merr.) genetic map and their association with EST markers. Theoretical and Applied Genetics, 2004, 108: 1131-1139.

[14]周  蓉, 王贤智, 陈海峰, 张晓娟, 单志慧, 吴学军, 蔡淑平, 邱德珍, 周新安, 吴江生. 大豆倒伏性及其相关性状的QTL分析. 作物学报, 2009, 35(1): 57-65.

Zhou R, Wang X Z, Chen H F, Zhang X J, Shan Z H, Wu X J, Cai S P, Qiu D Z, Zhou X A, Wu J S. QTL analysis of lodging and related traits in soybean. Acta Agronomica Sinica, 2009, 35(1): 57-65. (in Chinese)

[15]王  珍. 大豆SSR遗传图谱构建及重要农艺性状QTL分析[D]. 南宁: 广西大学, 2004.

Wang Z. Construction of soybean SSR based map and QTL analysis important agronomic traits [D]. Nanning: Guangxi University, 2004. (in Chinese)

[16]周  蓉, 涂赣英, 沙爱华, 王贤智, 张小娟, 周新安. 大豆种质的倒伏性调查及其相关农艺性状分析. 大豆科学, 2007, 26(1): 41-44.

Zhou R, Tu G Y, Sha A H, Wang X Z, Zhang X J, Zhou X A. Analysis of lodging and some related agronomic characters in soybean germplasm. Soybean Science, 2007, 26(1): 41-44. (in Chinese)

[17]陈庆山, 刘春燕, 吕  东, 何建勋. 大豆 DNA 提取基本原理的探讨. 东北农业大学学报, 2004, 35(2): 129-134.

Chen Q S, Liu C Y, Lü D, He J X. The basic principle of DNA extraction from soybean. Journal of Northeast Agricultural University, 2004, 35(2): 129-134. (in Chinese)

[18]邱丽娟, 常汝镇. 大豆种质资源描述规范和数据标准. 北京: 中国农业出版社, 2006.

Qiu L J, Chang R Z. Descriptors and Data Standard for Soybean (Glycine spp.). Beijing: China Agriculture Press, 2006. (in Chinese)

[19]McCouch S R, Cho Y G, Yano M, Paul E, Blinstrub M, Morishima H, Kinoshita T. Report on QTL nomenclature. Rice Genetics Newsletters, 1997, 14: 11-13.

[20]陈庆山, 张忠臣, 刘春燕, 王伟权, 李文滨. 应用Charleston×东农594重组自交系群体构建SSR大豆遗传图谱. 中国农业科学, 2005, 38(7): 1312-1316.

Chen Q S, Zhang Z C, Liu C Y, Wang W Q, Li W B. Construction and analysis of soybean genetic map using recombinant inbred line of Charleston × Dongnong 594. Scientia Agricultura Sinica, 2005, 38(7): 1312-1316. (in Chinese)

[21]陈庆山, 张忠臣, 刘春燕, 辛大伟, 单大鹏, 邱红梅, 单彩云. 大豆主要农艺性状的QTL分析. 中国农业科学, 2007, 40(1): 41-47.

Chen Q S, Zhang Z C, Liu C Y, Xin D W, Shan D P, Qiu H M, Shan C Y. QTL analysis of major agronomic traits in soybean. Scientia Agricultura Sinica, 2007, 40(1): 41-47. (in Chinese)

[22]单大鹏, 刘春燕, 蒋洪蔚, 董晓慧, 陈庆山, 胡国华. 两种方法定位5个地点大豆蛋白质含量QTL. 中国油料作物学报, 2011, 33(1): 9-14.

Shan D P, Liu C Y, Jiang H W, Dong X H, Chen Q S, Hu G H. QTL analysis of soybean protein content using two methods in 5 different environments. Chinese Journal of Oil Crop Sciences, 2011, 33(1): 9-14. (in Chinese)

[23]黄中文, 赵团结, 喻德跃, 陈受宜, 盖钧镒. 大豆产量有关性状QTL的检测. 中国农业科学, 2009, 42(12): 4155-4165.

Huang Z W, Zhao T J, Yu D Y, Chen S Y, Gai J Y. Detection of QTLs of yield related traits in soybean. Scientia Agricultura Sinica, 2009, 42(12): 4155-4165. (in Chinese)

[24]吴晓雷, 王永军, 贺超英, 陈受宜, 盖钧镒, 王学臣. 大豆重要农艺性状的QTL分析. 遗传学报, 2001, 28(10): 947-955.

Wu X L, Wang Y J, He C Y, Chen S Y, Gai J Y, Wang X C. QTL mapping of some agronomic traits of soybean. Acta Genetica Sinica, 2001, 28(10): 947-955. (in Chinese)

[25]刘春燕, 齐照明, 韩冬伟, 单大鹏, 蒋洪蔚, 陈庆山, 胡国华. 大豆产量相关性状的多年多点QTL分析. 东北农业大学学报, 2010, 41(11): 1-9.

Liu C Y, Qi Z M, Han D W, Shan D P, Jiang H W, Chen Q S, Hu G H. QTL analysis of yield components on soybean under different environment. Journal of Northeast Agricultural University, 2010, 41(11): 1-9. (in Chinese)

[26]Paterson A H, Damon S, Hewitt J D, Zamir D, Rabinowitch H D, Lincoln S E, Lander E S, Tanksley S D. Mendelian factors underlying quantitative traits in tomato: Comparison across species, generations, and environments. Genetics, 1991, 127: 181-197.
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