欢迎访问作物学报，今天是
作物学报

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

PDF

1596

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)
[1] 胡文静, 李东升, 裔新, 张春梅, 张勇. 小麦穗部性状和株高的QTL定位及育种标记开发和验证[J]. 作物学报, 2022, 48(6): 1346-1356.
[2] 郭星宇, 刘朋召, 王瑞, 王小利, 李军. 旱地冬小麦产量、氮肥利用率及土壤氮素平衡对降水年型与施氮量的响应[J]. 作物学报, 2022, 48(5): 1262-1272.
[3] 于春淼, 张勇, 王好让, 杨兴勇, 董全中, 薛红, 张明明, 李微微, 王磊, 胡凯凤, 谷勇哲, 邱丽娟. 栽培大豆×半野生大豆高密度遗传图谱构建及株高QTL定位[J]. 作物学报, 2022, 48(5): 1091-1102.
[4] 付美玉, 熊宏春, 周春云, 郭会君, 谢永盾, 赵林姝, 古佳玉, 赵世荣, 丁玉萍, 徐延浩, 刘录祥. 小麦矮秆突变体je0098的遗传分析与其矮秆基因定位[J]. 作物学报, 2022, 48(3): 580-589.
[5] 冯健超, 许倍铭, 江薛丽, 胡海洲, 马英, 王晨阳, 王永华, 马冬云. 小麦籽粒不同层次酚类物质与抗氧化活性差异及氮肥调控效应[J]. 作物学报, 2022, 48(3): 704-715.
[6] 刘运景, 郑飞娜, 张秀, 初金鹏, 于海涛, 代兴龙, 贺明荣. 宽幅播种对强筋小麦籽粒产量、品质和氮素吸收利用的影响[J]. 作物学报, 2022, 48(3): 716-725.
[7] 马红勃, 刘东涛, 冯国华, 王静, 朱雪成, 张会云, 刘静, 刘立伟, 易媛. 黄淮麦区Fhb1基因的育种应用[J]. 作物学报, 2022, 48(3): 747-758.
[8] 徐龙龙, 殷文, 胡发龙, 范虹, 樊志龙, 赵财, 于爱忠, 柴强. 水氮减量对地膜玉米免耕轮作小麦主要光合生理参数的影响[J]. 作物学报, 2022, 48(2): 437-447.
[9] 张艳波, 王袁, 冯甘雨, 段慧蓉, 刘海英. 棉籽油分和3种主要脂肪酸含量QTL分析[J]. 作物学报, 2022, 48(2): 380-395.
[10] 王洋洋, 贺利, 任德超, 段剑钊, 胡新, 刘万代, 郭天财, 王永华, 冯伟. 基于主成分-聚类分析的不同水分冬小麦晚霜冻害评价[J]. 作物学报, 2022, 48(2): 448-462.
[11] 陈新宜, 宋宇航, 张孟寒, 李小艳, 李华, 汪月霞, 齐学礼. 干旱对不同品种小麦幼苗的生理生化胁迫以及外源5-氨基乙酰丙酸的缓解作用[J]. 作物学报, 2022, 48(2): 478-487.
[12] 马博闻, 李庆, 蔡剑, 周琴, 黄梅, 戴廷波, 王笑, 姜东. 花前渍水锻炼调控花后小麦耐渍性的生理机制研究[J]. 作物学报, 2022, 48(1): 151-164.
[13] 孟颖, 邢蕾蕾, 曹晓红, 郭光艳, 柴建芳, 秘彩莉. 小麦Ta4CL1基因的克隆及其在促进转基因拟南芥生长和木质素沉积中的功能[J]. 作物学报, 2022, 48(1): 63-75.
[14] 韦一昊, 于美琴, 张晓娇, 王露露, 张志勇, 马新明, 李会强, 王小纯. 小麦谷氨酰胺合成酶基因可变剪接分析[J]. 作物学报, 2022, 48(1): 40-47.
[15] 李玲红, 张哲, 陈永明, 尤明山, 倪中福, 邢界文. 普通小麦颖壳蜡质缺失突变体glossy1的转录组分析[J]. 作物学报, 2022, 48(1): 48-62.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备15008789号-2