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作物学报 ›› 2009, Vol. 35 ›› Issue (10): 1836-1843.doi: 10.3724/SP.J.1006.2009.01836

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

玉米产量及产量相关性状QTL的图谱整合

王帮太,吴建宇,丁俊强,席章营*   

  1. 河南农业大学农学院,河南郑州450002
  • 收稿日期:2008-11-11 修回日期:2009-04-24 出版日期:2009-10-12 网络出版日期:2009-07-04
  • 通讯作者: 席章营, E-mail: xizhangying@163.com
  • 基金资助:

    本研究由国家自然科学基金项目(30871580)和国家重点基础研究发展计划(973计划)项目(2006CB101700)资助。

Map Integration of QTLs for Grain Yield and its Related Traits in Maize

WANG Bang-Tai,WU Jian-Yu,Ding Jun-Qiang,XI Zhang-Ying*   

  1. College of Agronomy,Henan Agricultural University,Zhengzhou 450002,China
  • Received:2008-11-11 Revised:2009-04-24 Published:2009-10-12 Published online:2009-07-04
  • Contact: XI Zhang-Ying, E-mail: xizhangying@163.com

摘要:

利用生物信息学方法,借助高密度分子标记遗传图谱IBM2 2008 neighbors,利用图谱映射和元分析的方法,对不同试验中定位的400个玉米产量及产量相关性状QTL进行了图谱整合,构建了玉米产量及产量相关性状QTL的综合图谱和一致性图谱。结果表明,玉米产量及产量相关性状QTL10条染色体上呈非均匀分布,第1染色体上最多,第10染色体上最少;发掘出96个玉米产量及产量相关性状的一致性”QTL;关联性较强的产量性状的QTL常集中在相同或相近的座位上。

关键词: 玉米, 产量及产量相关性状, QTL, 一致性图谱, 元分析

Abstract:

Identification and fine mapping of quantitative trait loci (QTLs) for grain yield and its related traits in maize are very important for molecular breeding by design. In the past few decades, a wealth of QTLs mapping data for grain yield and its related traits in maize has been produced using molecular marker approaches. In order to unlock the full potential of the information contained in these independent experiments, four hundreds QTLs for grain yield and its related traits in maize, collected from different publications, were used to construct new QTL integrated map and consensus map using bioinformatics and meta-analysis methods with IBM2 2008 neighbors as reference. It showed that these QTLs were distributed on all 10 chromosomes unevenly, with the most on chromosome 1 and the least on chromosome 10. QTLs for ear length, cob diameter, kernel number per row, kernel weight and grain yield were mainly distributed on chromosome 1, while QTLs for ear row number on chromosome 9. Ninety-six “Consensus” QTLs for grain yield and its related traits were estimated, including 43 “Consensus” QTLs for kernel weight, 32 “Consensus” QTLs for grain yield, and 8, 5, 4, 3, 1 “Consensus” QTLs for ear diameter, ear row number, cob diameter, kernel number per row, ear length, respectively. QTLs with similar phenotype were clustered on the same or near locations. These results provide a good basis for studying genetic mechanism and molecular marker- assisted selection for grain yield and its related traits in maize

Key words: Maize, Grain yield and its related traits, QTL, Consensus map, Meta-analysis

[1] Berke T G, Rocheford T R. Quantitative trait loci for flowering, plant and ear height, and kernel traits in maize. Crop Sci, 1995, 35: 1542-1549
[2] Goldman I L, Rocheford T R, Dudley J W. Molecular markers associated with maize kernel oil concentration in an Illinois high protein ´ Illinois low protein cross. Crop Sci, 1994, 34: 908-915
[3] Schon C C, Melchinger A E, Boppenmaier J, Brunklaus-Jung E, Herrmann R G, Seitzer J F. RFLP mapping in maize: quantitative trait loci affecting testcross performance of elite European flint lines. Crop Sci, 1994, 34: 378-389

[4] Veldboom L R, Lee M. Genetic mapping of quantitative trait loci in maize in stress and nonstress environments: I. grain yield and yield components. Crop Sci, 1996, 36: 1310-1319
[5] Veldboom L R, Lee M. Molecular-marker-facilitated studies of morphological traits in maize: II. Determination of QTLs for grain yield and yield components. Theor Appl Genet, 1994, 89: 451-458
[6] Yan J-B (严建兵), Tang H(汤华), Huang Y-Q (黄益勤), Zheng Y-L(郑用琏), Chander S, Li J-S(李建生). QTL mapping major and epistatic analysis for yield and yield components using molecular markers. Chin Sci Bull (科学通报), 2006, 51(12): 1413-1421 (in Chinese)
[7] Xiang D-Q(向道权), Huang L-J(黄烈健). A preliminary study on genetic effect of maize yield component traits based on major gene and polygene mixed inheritance. Acta Agric Boreal-Sin (华北农学报), 2001, 16(3): 1-5 (in Chinese with English abstract)
[8] Xiang D-Q(向道权), Cao H-H(曹海河), Cao Y-G(曹永国), Yang J-P(杨俊品), Hang J-J(黄烈健), Wang S-C(王守才), Dai J-R(戴景瑞). Construction of a yield genetic map and location of for component traits in maize by quantitative trait loci SSR markers. Acta Genet Sin (遗传学报), 2001, 28 (8): 778-784 (in Chinese with English abstract)
[9] Xiang D-Q(向道权), Huang L-J(黄烈健), Dai J-R(戴景瑞). Progress in studies on maize yield QTL and the genetic basis of heterosis. J China Agric Univ (中国农业大学学报), 1999, 4(l): 1-7 (in Chinese with English abstract)
[10] Yang J-P(杨俊品). Construction of the molecular linkage map and QTL mapping of quantitative traits in maize. PhD Dissertation of Sichuan Agricultural University, 2001 (in Chinese with English abstract)

[11] Yang J-P(杨俊品), Rong T-Z(荣廷昭). Improvement of RFLP marker facilitated studies of QTLs in maize. J Maize Sci (玉米科学),1999, 7(1): 18-24 (in Chinese with English abstract)

[12] Yang J-P(杨俊品), Rong T-Z(荣廷昭), Xiang D-Q(向道权), Tang H-T(唐海涛), Huang L-J(黄烈健), Dai J-R(戴景瑞). QTL mapping of quantitative traits in maize. Acta Agron Sin (作物学报), 2005, 31(2): 88-196 (in Chinese with English abstract)
[13] Rudner L M, Glass G V, Evartt D L, Emery, P J. A user’s guide to the meta-analysis of research studies meta-stat: software to aid in the meta-analysis of research findings.Educational Resources Information Center Clearinghouse on Assessment and Evaluation (ERIC), 2002

[14] Goffinet B, Gerber S. Quantitative trait loci: a meta-analysis. Genetics, 2000, 155: 463-473

[15] Varshney R K, Marcel C L, Ramsay L, Russell J, Roder M S, Stein N, Waugh R, Langridge P, Niks R E, Graner A. A high density barley microsatellite consensus map with 775 SSR loci. Theor Appl Genet, 2007, 114: 1091-1103

[16] Doligez A, Adam-Blondon A F, Cipriani G, Di Gaspero G, Laucou V, Merdinoglu D, Meredith C P, Riaz S, Roux C, This P.An integrated SSR map of grapevine based on five mapping populations. Theor Appl Genet, 2006, 113: 369-382

[17] Lombard V, Delourme R. A consensus linkage map for rapeseed (Brassica napus L.): Construction and integration of three individual maps from DH populations. Theor Appl Genet, 2001, 103: 491-507

[18] Marcel T C, Varshney R K, Barbieri M, Jafary H, Kock M J D de, Graner A, Niks R E.A high-density consensus map of barley to compare the distribution of QTLs for partial resistance to Puccinia hordei and of defence gene homologues. Theor Appl Genet, 2007, 114: 487-500

[19] Li X-H(李雪华), Li X-H(李新海), Hao Z-F(郝转芳), Tian Q-Z(田清震), Zhang S-H(张世煌). Consensus map of the QTL relevant to drought tolerance of maize under drought conditions. Sci Agric Sin (中国农业科学), 2005, 38(5): 882-890 (in Chinese with English abstract)

[20] Zhang S-H(张书红), Zhang S-H(张世煌), Li X-H(李新海), Xi Z-Y(席章营). Construction of consensus map of resistance gene in maize. Chin Agric Sci Bull (中国农学通报), 2007, 23(6): 601-606 (in Chinese with English abstract)

[21] Wang Y(王毅), Yao J(姚骥), Zhang Z-F(张征锋), Zheng Y-L(郑用琏). Comparative analysis of QTL integrated mapping and statistical analysis of QTLs affecting plant height in maize. Chin Sci Bull (科学通报), 2006, 51(15): 1776-1786 (in Chinese)

[22] Ji H-L(吉海莲), Li X-H(李新海), Xie C-X(谢传晓), Hao Z-F(郝转芳), Lü X-L(吕香玲), Shi L-Y(史利玉), Zhang S-H(张世煌). Comparative QTL mapping of resistance to Sporisorium reiliana in maize based on meta-analysis of QTL locations. J Plant Genet Resour (植物遗传资源学报), 2007, 8(2): 132-139 (in Chinese with English abstract)
[23] Lan J-H(兰进好), Li X-H(李新海), Gao S-R(高树仁), Zhang B-S(张宝石), Zhang S-H(张世煌). QTL analysis of yield components in maize under different environments. Acta Agron Sin (作物学报), 2005, 31(10): 1253-1259 (in Chinese with English abstract)

[24] Li XH, Liu X D, Li M S, Zhang S H. Identification of quantitative trait loci for anthesis-silking interval and yield components under drought stress in maize. Acta Bot Sin (植物学报), 2003, 45: 852-857

[25] Teng W-T(滕文涛). Classification of heterotic groups and detection of QTL for agronomic traits using molecular markers in maize. PhD Dissertation of China Agricultural University, 2004 (in Chinese with English abstract)
[26] Stuber C W, Lincoln S E, Wolff D W, Helentjaris T, Lander E S. Identification of genetic factors contributing to heterosis in a hybrid from two elite maize inbred lines using molecular markers. Genetics, 1992, 132: 823-839.
[27] Melchinger A E, Utz H F, Schon C C. Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects. Genetics, 1998, 149: 383-403
[28] Ribaut J M, Jiang C, Gonzalwz-de-leon D, Edmeades G O, Hoisington D A. Identification of quantitative trait loci under drought conditions in tropical aize: 2. Yield components and marker-assisted selection strategies. Theor Appl Genet, 1997, 94: 887-896

[29] Agrama H A S, Moussa M E. Mapping QTLs in breeding for drought tolerance in maize (Zea mays L.). Euphytica, 1996, 91: 89-97

[30] Doebley J, Bacigalupo A, Stec A. Inheritance of kernel weight in two maize-teosinte hybrid populations: implications for crop evolution. Heredity, 1994, 85: 191-195

[31] Ajmone-Marsan P, Monfredini G, Ludwig W F, Melchinger A E, Franceschini P, Pagnotto G, Motto M. In an elite cross of maize a major quantitative trait locus controls one-fourth of the genetic variation for grain yield. Theor Appl Genet, 1995, 90: 415-424
[32] Austin D F, Lee M. Detection of quantitative trait loci for grain yield and yield components in maize across generations in stress and nonstress environments. Crop Sci, 1998, 38: 1296-1308

[33] Marsan P A, Gorni C, Chitto A, Redaelli R, Vijk R V, Stam P, Motto M. Identification of QTLs for grain yield and grain-related traits of maize (Zea mays L.) using an AFLP map, different testers, and cofactor analysis. Theor Appl Genet, 2001, 102: 230-243

[34] Ho J C, McCouch S R, Smith M E. Improvement of hybrid yield by advanced backcross QTL analysis in elite maize. Theor Appl Genet, 2002, 105: 440-448

[35] Ragot M, Sisco P H, Hoisington D A, Stuber C W. Molecular-marker-mediated characterization of favorable exotic alleles at quantitative trait loci in maize. Crop Sci, 1995, 35: 1306-1315
[36] Darvasi A, Soller M. A simple method to calculate resolving power and confidence interval of QTL map location. Behav Genet, 1997, 27: 125-132
[37] Chardon F, Virlon B, Moreau L, Joets J, Decousset L, Murigneux A, Charcosset A. Genetic architecture of flowering time in maize as inferred from quantitative trait loci meta-analysis and synteny conservation with the rice genome. Genetic, 2004, 168: 2169-2185

[38] Zhao H X, Liu X M, Chen M S. H22, a major resistance gene to the Hessian fly (Mayetiola destructor), is mapped to the distal region of wheat chromosome 1DS. Theor Appl Genet, 2006, 113: 1491-1496

[39] Sarfatti M, Abu-Abied M,Katan J, Zamir D. RFLP mapping of I1, a new locus in tomato conferring resistance against Fusarium oxysporum f. sp. lycopersici race 1. Theor Appl Genet, 1991, 82: 22-26

[40] Vander BeekJ G, Verkerk R, Zabel P, Lindhout P. Mapping strategy for resistance genes in tomato based on RFLPs between cultivars: Cf9 (resistance to Cladosporium fulvum) on chromosome 1. Theor Appl Genet, 1992, 84: 106-112

[41] Kosack K E, Jones J D G. Plant disease resistance genes: Unraveling how they work. Can J Bot,1995, 73: 495-505

[42] Witsenboer H, Kesseli R V, Fortin M G, Stanghellini M, Michelmore R W. Sources and genetic structure of a cluster of genes for resistance to three pathogens in lettuce. Theor Appl Genet, 1995, 91: 178-188

[43] Tuberosa R, Salvi S, Sanguineti M C, Landi P, Maccaferri M, Conti S. Mapping QTL regulating morpho-physiological traits and yield: case studies, shortcomings and perspectives in drought-stressed maize. Ann Bot, 2002, 89: 941-963

[44] Beavis W D, Smith O S, Grant D, Fincher R. Identification of quantitative trait loci using a small sample of top crossed and F4 progeny from maize. Crop Sci, 1994, 34: 882-896

[45] Veldboom L R, Lee M, Woodman W L. Molecular marker-facilitated studies in an elite maize population: I. Linkage analysis and determination of QTL for morphological traits. Theor Appl Genet, 1994, 88: 7-16
[46] Voorrips R E. MapChart: Software for the graphical presentation of linkage maps and QTLs. Heredity, 2002, 93: 77-78
[47] Lü X-L(吕香玲), Li X-H(李新海), Xie C-X(谢传晓), Hao Z-F(郝转芳), Ji H-L(吉海莲), Shi L-Y(史利玉), Zhang S-H (张世煌). Comparative QTL mapping of resistance to sugarcane mosaic viruses maize based on bioinformatics. Hereditas(遗传), 2008, 30(1): 101-108 (in Chinese with English abstract)
[48] Peleman J D, van der Voort J R. Breeding by design. Trends Plant Sci, 2003, 8: 330-334

[49] Wan J-M(万建民), Perspectives of molecular design breeding in crops. Acta Agron Sin (作物学报), 2006, 32(3): 455-462 (in Chinese with English abstract)
[50] Zheng C-Y(曾长英), Xu F-S(徐芳森), Meng J-L(孟金陵), Wang Y-H(王运华), Hu C-X(胡承孝). How long the way from QTL to QTGs? Hereditas (遗传), 2006, 28(9): 1191-1198 (in Chinese with English abstract)
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