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作物学报 ›› 2011, Vol. 37 ›› Issue (09): 1511-1524.doi: 10.3724/SP.J.1006.2011.01511

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

利用小麦关联RIL群体定位产量相关性状QTL

丁安明1，李君1，崔法1，赵春华1，马航运2，王洪刚1,*   

  1. 1作物生物学国家重点实验室 / 山东省作物生物学重点实验室 / 国家小麦改良中心泰安分中心 / 山东农业大学农学院，山东泰安 271018；2枣庄市农业科学研究院，山东枣庄 277100
  • 收稿日期:2011-01-14 修回日期:2011-05-20 出版日期:2011-09-12 网络出版日期:2011-06-28
  • 通讯作者: 王洪刚, E-mail: hgwang@sdau.edu.cn, Tel: 0538-8242141
  • 基金资助:

    本研究由国家重点基础研究发展计划(973计划)项目(2006CB101700)资助。

QTL Mapping for Yield Related Traits Using Two Associated RIL Populations of Wheat

DING An-Ming1,LI Jun1,CUI Fa1,ZHAO Chun-Hua1,MA Hang-Yun2,WANG Hong-Gang1,*   

  1. 1 State Key Laboratory of Crop Biology / Shandong Key Laboratory of Crop Biology / Tai’an Subcenter of National Wheat Improvement Center / Agronomy College, Shandong Agricultural University, Tai’an 271018, China; 2 Zaozhuang Municipal Academy of Agricultural Sciences, Zaozhuang 277100, China
  • Received:2011-01-14 Revised:2011-05-20 Published:2011-09-12 Published online:2011-06-28
  • Contact: 王洪刚, E-mail: hgwang@sdau.edu.cn, Tel: 0538-8242141

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被引次数

41

摘要： 为定位控制小麦产量相关性状的QTL位点，获得与重要位点连锁的分子标记和染色体区段，以分别含有229和485个家系的关联重组自交系(RIL)群体WY和WJ为材料，在4个环境中，用完备区间作图法(ICIM)对产量相关性状进行了QTL定位分析。结果表明，产量相关性状QTL分布在小麦21条染色体上。在WY群体中检测到每穗小穗数、主茎穗粒数、单株穗数、千粒重和单株产量的QTL分别有9、9、4、7和5个，其中16个(55.2%)解释大于10%的表型变异；在WJ群体中检测到这5个性状的QTL分别有20、16、11、14和9个，其中只有3个(6.7%)在单个环境中解释超过10%的表型变异。在WY群体中有5个QTL在2个环境中被重复检测到；在WJ群体中，有11个QTL在2个或2个以上环境中被重复检测到。在2个群体中均检测到产量相关性状的QTL在染色体上形成了含有一因多效或紧密连锁QTL的染色体区段，并在2个群体检测到可能相同的9对QTL和2个染色体区段。

关键词: 小麦, 产量相关性状, 完备区间作图法(ICIM), QTL

Abstract: Using inclusive composite interval mapping (ICIM) method, we detected QTLs responsible for spikelet number per spike (SN), grain number per spike (GN), spike number per plant (PN), 1000-grain weight (GW), and grain yield per plant (GY) in associated RIL populations WY (229 lines) and WJ (485 lines), which were planted in four growing environments. Numerous QTLs for the five yield-related traits were located on 21 chromosomes of wheat. In the WY population, nine, nine, four, seven, and five QTLs were detected for SN, GN, PN, GW, and GY, respectively. Among these QTLs, 16 explained more than 10% of the phenotypic variations. In the WJ population, the numbers of QTLs for the above five traits were 20, 16, 11, 14, and 9, respectively, of which only three QTLs had phenotypic contribution higher than 10%. In addition, five QTLs were identified in two environments in the WY population and 17 QTLs were identified in at least two environments in the WJ population. Pleiotropy phenomenon or chromosome regions with closely linked QTLs were observed in both populations. Nine pairs of QTLs and two chromosome regions were inferred to be identical between the two populations because these QTLs and chromosome regions shared the same flanking markers. These results may enrich the QTL information for yield components of wheat and facilitate marker assisted selection.

Key words: Wheat, Yield-related traits, Inclusive composite interval mapping method (ICIM), QTL

[1]Li S S, Jia J Z, Wei X Y, Zhang X C, Li L Z, Chen H M, Fan Y D, Sun H Y, Zhao X H, Lei T D, Xu Y F, Jiang F S, Wang H G, Li L H. An intervaietal genetic map and QTL analysis for yield traits in wheat. Mol Breed, 2007, 20: 167–178
[2]Kuchel H, Williams K J, Langridge P, Eagles H A, Jefferies S P. Genetic dissection of grain yield in bread wheat: I. QTL analysis. Theor Appl Genet, 2007, 115: 1029–1041
[3]Yao Q(姚琴), Zhou R-H(周荣华), Pan Y-M(潘昱名), Fu T-H(傅体华), Jia J-Z(贾继增). Construction of genetic linkage map and QTL analysis of agronomic important traits based on a RIL population derived from common wheat variety Yanzhan 1 and Zaosui 30. Sci Agric Sin (中国农业科学), 2010, 43(20): 4130–4139 (in Chinese with English abstract)
[4]Wang R-X(王瑞霞), Zhang X-Y(张秀英), Wu L(伍玲), Wang R(王瑞), Hai L(海林), Yan C-S(闫长生), You G-X(游光霞), Xiao S-H(肖世和). QTL mapping for grain filling rate and thousand-grain weight in different ecological environments in wheat. Acta Agron Sin (作物学报), 2008, 34(10): 1750-1756 (in Chinese with English abstract)
[5]Börner A, Schumann E, Fürste A, Cöster H, Leithod B, Röder M S, Weber W E. Mapping of quantitative trait loci determining agronomic important characters in hexaploid wheat (Ttiticum astivum L.). Theor Appl Genet, 2002, 105: 921–936
[6]Kumar N, Kulwal P L, Balyan H S, Gupta P K. QTL mapping for yield and yield contributing traits in 2 mapping population of bread wheat. Mol Breed, 2007, 19: 163–177
[7]Simon M, Loudet O, Durand S, Berard A, Brunel D, Sennesal F X, Durand-Tardif M, Pelletier G, Camilleri C. Quantitative trait loci mapping in five new large recombinant inbred line populations of Arabidopsis thaliana genotyped with consensus single-nucleotide polymorphism markers. Genet Soc Am, 2008, 178: 2253–2264
[8]O’Neill C M, Morgan C, Kirby J, Tscheop H, Deng P X, Brennan M, Rosas U, Fraser F, Hall C, Gill S, Bancroft I. Six new recombinant inbred populations for the study of quantitative traits in Arabidopsis thaliana. Theor Appl Genet, 2008, 116: 623–634
[9]Murray M G, Thompson W F. Rapid isolation of high-molecular weight plant DNA. Nucl Acids Res, 1980, 8: 4321–4325
[10]Cui F, Li J, Ding A M, Zhao C H, Wang L, Wang X Q, Li S S, Bao Y G, Li X F, Feng D S, Kong L R, Wang H G. Conditional QTL mapping for plant height with respect to the length of the spike and internode in two mapping populations of wheat. Theor Appl Genet, 2011, DOI: 10.1007/s00122-011-1551-6
[11]Li H H, Ye GY, Wang J K. A Modified Algorithm for the Improvement of Composite Interval Mapping. Genet Soc Am, 2007, 175: 361–374
[12]Austin D F, Lee M. Comparative mapping in F2:3 and F6:7 generations of quantitative trait loci for grain yield and yield components in maize. Theor Appl Genet, 1996, 92: 817–826
[13]Yano M, Sasaki T. Genetic and molecular dissection of quantitative traits in rice. Plant Mol Biol, 1997, 35: 145–153
[14]Mackay T F C. The genetic architecture of quantitative traits. Annu Rev Genet, 2001, 35: 303–339
[15]Vales M I, Schon C C, Capettini F, Chen X M, Corey A E, Mather D E, Mundt C C, Richardson K L, Sandoval-Islas J S, Utz H F, Hayes P M. Effect of population size on the estimation of QTL: a test using resistance to barley stripe rust. Theor Appl Genet, 2005, 111: 1260–1270
[16]Wang R X, Hai L, Zhang X Y, You G X, Yan C X, Xiao S H. QTL mapping for grain filling rate and yield related traits in RILs of the Chinese winter wheat population Heshangmai × Yu 8679. Theor Appl Genet, 2009, 118: 313–325
[17]Huang X Q, Kempf H, Canal M W, Roder M S. Advanced backcross QTL analysis in progenies derived from a cross between a German elite winter wheat variety and a synthetic wheat (Triticun aestivum L.). Theor Appl Genet, 2004, 109: 933–943
[18]Kato K, Miura H, Sawada S. Mapping QTLs controlling grain yield and its components on chromosome 5A of wheat. Theor Appl Genet, 2000, 101: 1114–1121
[19]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. Genet Soc Am, 1991, 127: 181–197
[20]Varshney R K, Prasad M, Roy J K, Kumar N H S, Dhaliwal H S, Balyan H S, Gupta P K. Identification of eight chromosomes and a microsatellite maker on 1AS associated with QTL for grain weight in bread wheat. Theor Appl Genet, 2000, 100: 1290–1294
[21]Huang X Q, Coster H, Ganal M W, Roder M S. Advanced backcross QTL analysis for identification of quantitative trait loci alleles from wild relatives of wheat (Triticun aestivum L.). Theor Appl Genet, 2003, 106: 1379–1389
[22]Huang X Q, Cloutier S, Lycar L, Radovanovic N, Humpphreys D G, Noll J S, Somers D J, Brown P D. Molecular detection of QTLs for agronomic and quality traits in a double haploid population derived from two Canadian wheats (Triticun aestivum L.). Theor Appl Genet, 2006, 113: 753–766
[23]Kumar N, Kulwal P L, Gaur A, Tyagi A K, Khurana J P, Khurana P. QTL analysis for grain weight in common wheat. Euphytica, 2006, 151: 135–144
[24]Quarrie S A, Steed A, Calestani C, Semikhodskii A, Lebreton C, Chinoy C, Steele N, Pljevljakusic D, Waterman E, Weyen J, Schondelmaier J, Habash D Z, Farmer P, Saker L, Clarkson D T, Abugalieva A, Yessimbekova M, Turuspekov Y, Abugalieva S, Tuberrosa R, Sanguineti M C, Hollington P A, Aragues R, Royo A, Dodig D. A high-density genetic map of hexaploid wheat (Triticun aestivum L.) from the cross Chinese Spring × SQ1 and its use to compare QTLs for grain yield across a range of environments. Theor Appl Genet, 2005, 110: 865–880
[25]Liao X-Z(廖祥政), Wang J(王瑾), Zhou R-H(周荣华), Ren Z-L(任正隆), Jia J-Z(贾继增). Mining favorable alleles of QTLs conferring 1000-grain weight from synthetic wheat. Acta Agron Sin (作物学报), 2008, 34(11): 1877–1884 (in Chinese with English abstract)
[26]Ramya P, Chaubal A, Kulkrani K, Gupta L, Kadoo N, Dhaliwal H S, Chhuneja P, Lagu M, Gupta V. QTL mapping of 1000-kernal weight, kernel length, and kernel width in bread wheat (Triticum aestivum L.). J Appl Genet, 2001, 51: 421–429
[27]Kirigei F M, Ginkel M V, Brown-Guedira G, Gill B S, Paulsen G N, Fritz A K. Makers associated with a QTL for grain yield in wheat under drought. Mol Breed, 2007, 20: 401–413
[29]Song Y-X(宋彦霞), Jing R-L(景蕊莲), Huo N-X(霍纳新), Ren Z-L(任正隆), Jia J-Z(贾继增). Detection of QTLs for heading in common wheat using different populations. Sci Agric Sin (中国农业科学), 2006, 39(11): 2186–2193 (in Chinese with English abstract)
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