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作物学报 ›› 2014, Vol. 40 ›› Issue (01): 37-44.doi: 10.3724/SP.J.1006.2014.00037

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

大豆产量及主要农艺性状QTL的上位性互作和环境互作分析

梁慧珍1,余永亮1,杨红旗1,张海洋1,董薇1,李彩云1,杜华1,巩鹏涛2,刘学义3,方宣钧4   

  1. 1 河南省农业科学院芝麻研究中心, 河南郑州 450002；2 东北油田盐碱植被恢复与重建教育部重点实验室 / 东北林业大学盐碱地生物资源环境研究中心, 黑龙江哈尔滨 150040；3 山西省农业科学院经济作物研究所, 山西汾阳 032200；4 海南省热带农业资源开发利用研究所, 海南三亚 572025
  • 收稿日期:2013-05-16 修回日期:2013-09-16 出版日期:2014-01-12 网络出版日期:2013-10-22
  • 基金资助:

    本研究由河南省科技创新杰出人才计划(114200510002)和国家转基因生物新品种培育重大科技专项(2009ZX08018-001B, 2011ZX08004-005)资助。

Epistatic Effects and QTL×Environment Interaction Effects of QTLs for Yield and Agronomic Traits in Soybean

LIANG Hui-Zhen1,YU Yong-Liang1,YANG Hong-Qi1,ZHANG Hai-Yang1,DONG Wei1,LI Cai-Yun1,GONG Peng-Tao2,LIU Xue-Yi3,FANG Xuan-Jun4   

  1. 1 Sesame Research Center, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China; 2 Key Laboratory of Ministry of Education for Saline-alkali Vegetation Ecology Restoration in Oil Field (SAVER) /Alkali Soil Natural Environmental Science Center (ASNESC), Northeast Forestry University, Harbin 150040, China; 3 Economical Crops Institute, Shanxi Academy of Agricultural Sciences, Fenyang 032200, China; 4 Hainan Institute of Tropical Agriculture Resources, Sanya 572025, China
  • Received:2013-05-16 Revised:2013-09-16 Published:2014-01-12 Published online:2013-10-22

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被引次数

27

摘要：

以栽培大豆晋豆23为母本, 半野生大豆灰布支黑豆ZDD2315为父本杂交衍生的F2:15和F2:16的447个RIL家系为遗传群体, 绘制SSR遗传图谱, 采用混合线性模型方法, 对2年大豆小区产量及主要农艺性状进行加性QTL、加性×加性上位互作及环境互作分析。结果检测到9个与小区产量、茎粗、有效分枝、主茎节数、株高、结荚高度相关的QTL, 分别位于J_2、I、M连锁群上, 其中小区产量、茎粗、株高、有效分枝和主茎节数QTL的加性效应为正值, 说明增加这些性状的等位基因来源于母本晋豆23。同时, 检测到7对影响小区产量、茎粗、株高和结荚高度的加性×加性上位互作效应及环境互作效应的QTL, 共发现14个与环境存在互作的QTL。上位效应和QE互作效应对大豆小区产量及主要农艺性状的遗传影响较大。大豆分子标记辅助育种中, 既要考虑起主要作用的QTL, 又要注重上位性QTL, 才有利于性状的稳定表达和遗传。

关键词: 大豆, 小区产量, 农艺性状, QTL与环境互作效应, 上位互作效应

Abstract:

Improving seed yield is an important goal of soybean breeding programs. In this investigation, a soybean SSR genetic linkage map constructed by a total of 447 recombinant inbred lines (RILs) derived from a cross between Jindou 23 (cultivar, female parent) and ZDD2315 (semi-wild, male parent) and the mixed linear model was used to identify the QTLs of yield and other QTLs for major agronomic traits in a two-year experiment. Nine QTLs bearing additive effects for pod position, plant height, node number on main stem, branch number, stem thickness and yield per plot were mapped in the linkage groups J_2, I, and M. The QTLs of yield per plot, stem thickness, plant height, branch number and node number on main stem showed positive additive effects donated by Jindou 23. Seven pairs of epistatic effects QTLs for pod position, plant height and stem thickness were detected, which had an interaction with environments. The results indicated that the epistatic effects and the environmental factors played an important role in yield per plot and agronomic traits in soybean. It will be very important to pay attention to not only QTLs with major effects but also those with epistatic effects in soybean molecular marker-assisted breeding in considering the stability expression and inheritance of the agronomic traits.

Key words: Soybean, Yield per plot, Agronomic traits, QTL×environment interaction effects, Epistatic effects

[1]Boerma H R, Specht J E. Soybeans: Improvement, Production and Uses, 3rd Edn. Madison, Wisconsin, USA: SSSA Publishers, 2004. pp 303–396



[2]Song Q J, Marek L F, Shoemaker R C, Lark K G, Concibido V C, Delannay X, Specht J E, Cregan P B. A new integrated genetic linkage map of the soybean. Theor Appl Genet, 2004, 109: 122–128



[3]梁慧珍, 余永亮, 杨红旗, 张海洋, 董微, 李彩云, 巩鹏涛, 刘学义, 方宣钧. 不同环境下大豆荚粒性状的遗传与QTL分析. 中国农业科学, 2012, 45: 2568–2579



Liang H Z, Yu Y L, Yang H Q, Zhang H Y, Dong W, Li C Y, Gong P T, Liu X Y, Fang X J. Genetic analysis and QTL mapping of pod-grain traits in soybean under different environments. Sci Agric Sin, 2012, 45: 2568-2579 (in Chinese with English abstract)



[4]Lee S H, Park K Y, Lee H S, Park E H, Boerma H R. Genetic mapping of QTLs conditioning soybean sprout yield and quality. Theor App Genet, 2001, 103: 702–709



[5]Hyten D L, Pantalone V R, Sams C E, Saxton A M, Landau-Ellis D, Stefaniak T R. Seed quality QTL in a prominent soybean population. Theor App Genet, 2004, 109: 552–561



[6]Reyna V, Sneller C H. Evaluation of marker assisted introgression of yield QTL alleles into adapted soybean. Crop Sci, 2001, 41: 1317–1321



[7]Hoeck J A, Fehr W R, Shoemaker R C, Welke G A, Johnson S L, Clanzio S R. Molecular marker analysis of seed size in soybean. Crop Sci, 2003, 43: 68–74



[8]Zhang W K, Wang Y J , Luo G Z, Zhang J S, He C Y, Wu X L, Gai J Y, ChenS Y. QTL mapping of ten agronomic traits on the soybean ( Glycine max L. Merr.) genetic map and their association with EST markers. Theor App Genet. 2004, 108: 1131–1139



[9]朱军. 广义遗传模型与数量遗传分析新方法. 浙江农业大学学报, 1994, 20: 551–559



Zhu J. General genetic models and new analysis methods for quantitative traits. J Zhejiang Agric Univ. 1994, 20: 551–559(in Chinese with English abstract)



[10]Wang D L, Zhu J, Li Z K, Paterson A H. Mapping QTLs with epistatic effects and QTL environment interactions by mixed linear model approaches. Theor Appl Genet, 1999, 99: 1255–1264



[11]杨钊钊, 李永祥, 刘成, 刘志斋, 李春辉, 李清超, 彭勃, 张岩, 王迪, 谭巍巍, 孙宝成, 石云素, 宋燕春, 王天宇, 黎裕. 基于多个相关群体的玉米雄穗相关性状QTL分析. 作物学报, 2012, 38: 1435–1442



Yang Z Z, Li Y X, Liu C, Liu Z Z, Li C H, Li QC, Peng B, Zhang Y, Wang D, Tan W W, Sun B C, Shi Y S, Song Y C, Wang T Y, Li Y. QTL Analysis of tassel-related traits in maize (Zea mays L.) using multiple connected populations. Acta Agron Sin, 2012, 38: 1435–1442 (in Chinese with English abstract)



[12]魏良明, 戴景瑞, 刘占先, 鄂立柱. 普通玉米蛋白质、淀粉和油分含量的遗传效应分析. 中国农业科学, 2008, 41: 3845–3850



Wei L M, Dai J R, Liu Z X, E L Z. Genetic effects of grain protein, starch and oil contents in maize. Sci Agric Sin, 2008, 41: 3845–3850 (in Chinese with English abstract)



[13]高用明, 朱军, 宋佑胜, 何慈信, 石春海, 邢永忠. 水稻永久F2群体抽穗期QTL的上位性及其与环境互作效应的分析. 作物学报, 2004, 30: 849–854



Gao Y M, Zhu J , Song Y S, He C X, Shi C H, Xing Y Z. Use of permanent F2 population to analyze epistasis and their interaction effects with environments for QTLs controlling heading date in rice. Acta Agron Sin, 2004, 30: 849–854 (in Chinese with English abstract)



[14]胡霞, 石瑜敏, 贾倩, 徐琴, 王韵, 陈凯, 孙勇, 朱苓华, 徐建龙, 黎志康. 影响水稻穗部性状及籽粒碾磨品质的QTL及其环境互作分析. 作物学报, 2011, 37: 1175–1185



Hu X, Shi Y M, Jia Q, Xu Q, Wang R, Chen K, Sun Y, Zhu L H, Xu J L, Li Z K. Analyses of QTLs for rice panicle and milling quality traits and their interaction with environment. Acta Agron Sin, 2011, 37: 1175–1185 (in Chinese with English abstract)



[15]梁燕, 张坤普, 赵亮, 梁雪, 张雯婷, 孙晓琳, 孟庆伟, 田纪春, 赵世杰. 小麦苗期光合作用及其相关性状的QTL分析. 作物学报, 2010, 36: 267–275



Liang Y, Zhang K P, Zhao L, Liang X, Zhang W T, Sun X L, Meng Q W, Tian J C, Zhao S J. Analysis of QTLs associated with photosynthesis characteristics in wheat seedlings. Acta Agron Sin, 2010, 36: 267–275 (in Chinese with English abstract)



[16]周晓果, 景蕊莲, 郝转芳, 昌小平, 张正斌. 小麦幼苗根系性状的QTL分析. 中国农业科学, 2005,38: 1951–1957



Zhou X G, Jing R L, Hao Z F, Chang X P, Zhang Z B. Mapping QTL for seedling root traits in common wheat. Sci Agric Sin, 2005, 38: 1951–1957 (in Chinese with English abstract)



[17]单大鹏, 朱荣胜, 陈立君, 齐照明, 刘春燕, 胡国华, 陈庆山. 大豆蛋白质含量相关QTL间的上位效应和QE互作效应. 作物学报, 2009, 35: 41–47



Shan D P, Zhu R S, Chen L J, Qi Z M, Liu C Y, Hu G H, Chen Q S. Epistatic effects and QE interaction effects of QTLs for protein content in soybean. Acta Agron Sin, 2009, 35: 41–47 (in Chinese with English abstract)



[18]单大鹏, 齐照明, 邱红梅, 单彩云, 刘春燕, 胡国华, 陈庆山. 大豆油分含量相关的QTL间的上位效应和QE互作效应. 作物学报, 2008, 34: 952–957



Shan D P, Qi Z M, Qiu H M, Shan C Y, Liu C Y, Hu G H, Chen Q S. Epistatic effects and QE interaction effects of QTLs on oil content in soybean. Acta Agron Sin, 2008, 34: 952–957 (in Chinese with English abstract)



[19]张晶莹, 葛一楠, 孙君明, 韩粉霞, 于福宽, 闫淑荣, 杨华. .多环境条件下大豆异黄酮主要组分的QTL定位. 中国农业科学, 2012,45: 3909–3920



Zhang J Y, Ge Y N, Sun J M, Han F X, Yu F K, Yan S R, Yang H. Identification of QTLs for major isoflavone components among multiple environments in soybean seeds. Sci Agric Sin, 2012, 45: 3909–3920 (in Chinese with English abstract)



[20]Tang Q Y, Zhang C X. Data processing system (DPS) software with experimental design, statistical analysis and data mining developed for use in entomological research. Insect Sci, DOI: 2012, 10.1111/j.1744-7917.2012.01519.x



[21]王珍, 方宣钧. 植物DNA分离. 分子植物育种, 2003, 1: 281–288



Wang Z, Fang X J. Plant DNA isolation. Mol Plant Breed, 2003, 1: 281–288 (in Chinese with English abstract)



[22]梁慧珍. 大豆子粒性状的遗传及QTL分析. 西北农林科技大学博士学位论文, 2006. pp 54–57



Liang H Z. Genetic Analysis and QTL Mapping of Seed Traits in Soybean [Glycine max (L.) Merr]. PhD Dissertation of  Northwest A＆F University. 2008. pp 54–57 (in Chinese with English abstract)



[23]Yang J, Zhu J. Predicting superior genotypes in multiple environments based on QTL effects. Theor Appl Genet, 2005, 110: 1268−1274



[24]McCouch S R, Cho Y G, Yano M, Paul E, Blinstrub M, Morishima H, Kinoshita T. Report on QTL nomenclature. Rice Genet Newsl, 1997, 14: 11–14



[25]李慧慧, 张鲁燕, 王建康. 数量性状基因定位研究中若干常见问题的分析与解答. 作物学报, 2010, 36: 918−931



Li H H, Zhang L Y, Wang J K. Analysis and answers to frequently asked questions in quantitative trait locus mapping. Acta Agron Sin, 2010, 36: 918−931 (in Chinese with English abstract)



[26]翟虎渠, 王建康. 应用数量遗传. 北京: 中国农业科学技术出版社, 2007



Zhai H Q, Wang J K. Applied Quantitative Genetics. Beijing: China Agricultural Science and Technology Press, 2007 (in Chinese)



[27]Li Z K, Yu S B, Lafitte H R, Huang N, Courtois B, Hittalmani S. QTL × environment interactions in rice: I. heading date and plant height. Theor Appl Genet, 2003, 108: 141–153



[28]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



[29]杨喆, 关荣霞, 王跃强, 刘章雄, 常汝镇, 王曙明, 邱丽娟. 大豆遗传图谱的构建和若干农艺性状的QTL定位分析. 植物遗传资源学报, 2004, (4): 309–314



Yang Z, Guan R X, Wang Y Q, Liu Z X, Chang R Z, Wang S M, Qiu L J. Construction of genetic map and QTL analysis for some agronomic traits in soybean. J Plant Genet Resour, 2004, (4): 309–314



[30]Liao C Y, Wu P, Hu B, Yi K K. Effects of genetic background and environment on QTL and epistasis for rice (Oryza sativa L.) panicle number. Theor Appl Genet, 2001, 103: 104–111
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