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作物学报 ›› 2009, Vol. 35 ›› Issue (4): 741-744.doi: 10.3724/SP.J.1006.2009.00741

• 研究简报 • 上一篇    下一篇

玉米丝裂病的抗性QTL定位

魏昕12，李丽华2，王振华2，宋锐1，曾兴1，张志明1，潘光堂1*   

  1. 1四川农业大学玉米研究所/教育部作物基因资源与遗传改良重点实验室，四川雅安625014；2河南省农业科学院粮食作物研究所，河南郑州450002
  • 收稿日期:2008-07-16 修回日期:2008-12-13 出版日期:2009-04-12 网络出版日期:2009-02-16
  • 通讯作者: 潘光堂
  • 基金资助:

    本研究由教育部长江学者和创新团队发展计划(IRT0453),国家高技术研究发展计划(863计划)项目(2006AA100103),引进国际先进农业科学技术重大项目(2003-Q03),国家科技支撑计划项目(2006BAD13B03)资助.

QTL Mapping of Resistance to Silk Cut in Maize

WEI Xin12,LI Li-Hua2,WANG Zhen-Hua2,SONG Rui1,ZENG Xing1,ZHANG Zhi-Ming1,PAN Guang-Tang1*   

  1. 1Maize Research Institute/Key Laboratory Crop Genetic Resources and Improvement,Ministry of Education,Sichuan Agricultural University,Ya'an 625014,China;2Cereal Crop Research Institute,Henan Academy of Agricultural Sciences,Zhengzhou 450002,China
  • Received:2008-07-16 Revised:2008-12-13 Published:2009-04-12 Published online:2009-02-16
  • Contact: PAN Guang-Tang

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2135

被引次数

7

摘要：

选用感丝裂病的玉米自交系R08与抗丝裂病的自交系Es40组配F2群体共348个单株，构建了包含115个SSR标记的分子遗传连锁图谱，覆盖玉米基因组2 178.6 cM，平均图距为18.9 cM。采用复合区间作图法，对F2:4家系丝裂病数据进行抗性QTL分析，共检测到12个QTL，分别位于第1、2、4、5和7染色体，贡献率为4.22%~37.95%。其中在第1、3染色体上检测到主效QTL，贡献率均大于30%，基因作用方式均为显性，其余10个QTL的作用方式多为加性或部分显性。

关键词: 玉米, 丝裂病, QTL定位, 遗传图谱, SSR

Abstract:

Using 115 SSR markers and the F2 population consisting of 348 lines derived from the cross between maize (Zea mays L.) inbred lines R08 and Es40, a genetic linkage map associated with the resistance to silk cut was constructed. The genetic linkage map covered 2 178.6 cM of maize genome with an average mapping distance of 18.9 cM. Using the composite interval mapping (CIM) method, 12 QTLs controlling the resistance to silk cut were detected on chromosomes 1, 2, 4, 5, and 7. These QTLs explained phenotypic variances ranging from 4.22% to 37.95%. Among them, two major QTLs on chromosomes 1 and 3, which explained more than 30% of phenotypic variances, had dominance effect, whereas, the other 10 QTLs had partial dominance effect or additive effect.

Key words: Maize(Zea mays L.), Silk-cut, QTL mapping, Genetic linkage map, SSR

[1] Wang X-M(王晓鸣), Dai F-C(戴法超). Manual for Diseases and Insect Pests in Maize (玉米病虫害田间手册). Beijing: China Agricultural Scientech Press, 2002. p49 (in Chinese)
[2] Odvody G N, Spencer N, Remmers J. A description of silk cut, a stress-related loss of kernel integrity in preharvest maize. Plant Dis, 1997, 81: 439–444
[3] Wei X(魏昕), Li L-H(李丽华), Wang J(王娟), Fan Q-Q(樊庆琦), Lan H(兰海), Wu Y-Q(吴元奇), Rong T-Z(荣廷昭), Pan G-T(潘光堂). Quantitative genetic analysis of silk cut in maize. Sci Agric Sin (中国农业科学), 2008, 41(8): 2235–2240(in Chinese with English abstract)
[4] CIMMYT. Applied Molecular Genetics Laboratory Protocol. Mexico: CIMMYT, 1998
[5] Wei X(魏昕), Rong T-Z(荣廷昭), Pan G-T(潘光堂). The genetic diversity variation revealed by SSR markers in the tropical maize population Pob32 after 5 cycles of mass selection. Sci Agric Sin (中国农业科学), 2006, 39(2): 237–245(in Chinese with English abstract)
[6] Lincoln S E, Daly M J, Lander E S. Constructing Genetics Linkage Maps with MAPMAKER/EXP Version3.0b: A Tutorial and Reference Manual, 3rd edn. Cambridge, Massachusetts: Institute for Biometrical Research, 1993
[2008-08-10]. http://www.umanitoba.ca/afs/plant_Science/psgendb/doc/mapmaker. tutorial.pdf.
[7] Wang S, Basten C J, Zeng Z B.WindowsQTLCartographer2.0. Raleigh, NC: Department of Statistics, North Carolina State University, 2003
[2008-08-10]. http://statgen.ncsu.edu/qtlcart/WQTLCart.htm
[9] Stuber C W, Edwards M D, Wendel J F. Molecular marker-facilitated investigation of quantitative trait loci in maize: II. Factors influencing yield and its component traits. Crop Sci, 1987, 27: 639–648
[10] Maize Genetics and Gonomics Database.
[2008-08-10] http://www.maizegdb.org/
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