中国农业科学 ›› 2014, Vol. 47 ›› Issue (24): 4769-4779.doi: 10.3864/j.issn.0578-1752.2014.24.001

• 作物遗传育种·种质资源 •    下一篇

利用基因芯片技术进行小麦遗传图谱构建及粒重QTL分析

陈建省1,陈广凤1,李青芳1,张晗2,师翠兰1,孙彩铃1,邓志英1,刘凯1,谷植群1,田纪春1,3   

  1. 1山东农业大学农学院小麦品质育种研究室/作物生物学国家重点实验室,山东泰安 271018
    2山东省农业科学院作物研究所,济南 250100
  • 收稿日期:2014-05-05 出版日期:2014-12-16 发布日期:2014-12-16
  • 通讯作者: 田纪春,Tel:0538-8242040
  • 作者简介:陈建省,E-mail:jshch@sdau.edu.cn
  • 基金资助:
    国家自然基金(31171554)、山东省种质资源创制课题和省教育厅课题(J12LF03)

Construction of Genetic Map Using Genotyping Chips and QTL Analysis of Grain Weight

CHEN Jian-sheng1, CHEN Guang-feng1, LI Qing-fang1, ZHANG Han2, SHI Cui-lan1, SUN Cai-ling1DENG Zhi-ying1, LIU Kai1, GU Zhi-qun1 , TIAN Ji-chun1,3   

  1. 1Group of Wheat Quality Breeding, College of Agronomy, Shandong Agricultural University/State Key Laboratory of Crop Biology, Tai’an 271018, Shandong
    2Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan 250100
  • Received:2014-05-05 Online:2014-12-16 Published:2014-12-16

摘要: 目的小麦遗传图谱是进行小麦染色体分析和研究表型变异的遗传基础。通过利用传统分子标记和现代基因芯片技术相结合,构建高密度遗传图谱,重点开展主要产量主要构成要素——粒重的初级基因定位,确定影响粒重的主效QTL位点,为开发粒重CAPS分子标记及在分子标记辅助育种提供依据和指导,并为利用小麦粒重次级群体进行精细定位和基因挖掘奠定基础。【方法】利用90 K小麦SNP基因芯片、DArt芯片技术及传统的分子标记技术,以包含173个家系的RIL群体(F9:10重组自交系)为材料,构建高密度遗传图谱,并利用QTL network2.0进行了3年共4环境粒重QTL分析。【结果】构建了覆盖小麦21条染色体的高密度遗传图谱,该图谱共含有6 244个多态性标记,其中SNP标记6 001个、DArT标记216个、SSR标记27个,覆盖染色体总长度4 875.29 cM,标记间平均距离0.78 cM。A、B、D染色体组分别有2 390、3 386和468个标记,分别占总标记数的38.3%、54.3%和7.5%;3个染色体组标记间平均距离分别为0.80、0.75和0.80 cM。用该分子遗传图谱对4个环境下粒重进行QTL分析,检测到位于1B、4B、5B、6A染色体上9个加性QTL,效应值大于10%的QTL位点有QGW4B-17QGW4B-5QGW4B-2QGW6A-344QGW6A-137;其中QGW4B-17在多个环境下检测到,其贡献率为16%—33.3%,可增加粒重效应值2.30-2.97g,该位点是稳定表达的主效QTL。9个QTL的加性效应均来自大粒母本山农01-35,单个QTL位点加性效应可增加千粒重1.09—2.97 g。【结论】构建的覆盖小麦21条染色体的分子遗传图谱共含有6 241个多态性标记,标记间平均距离为0.77 cM。利用该图谱检测到位于1B、4B、5B、6A染色体上9个控制粒重的加性QTL,其中QGW4B-17是稳定表达的主效QTL位点,贡献率为16.5%—33%,可增加粒重效应值2.30—2.97 g。

关键词: 普通小麦, 90K基因芯片, QTL定位, 粒重, SNP

Abstract: 【Objective】Wheat genetic map is a very useful resource for genome analysis and understanding of the genetic basis of phenotypic variation. High density genetic maps were constructed by combining the traditonal molecular markers and modern gene microarray technology in order to carry out QTL analysis of grain weight, to detect the major QTL, and to supply a basis and direction of exploration of CAPS markers for molecular-assistant breeding, which could also lay a foundation for fine mapping and excavation of grain weight genes. 【Method】 A RIL (recombinant inbred lines) population including 173 lines was analyzed using wheat 90K SNP array,DArt technology and traditional moleculer technology. High density genetic map was constructed. QTL mapping for 1000- grain weight was analyzed using QTL network 2.0. 【Result】 A genetic map of wheat covering 21 wheat chrosmes was constructed and it contains 6 241 polymorphism markers, including 6 001 SNP,256 DArT,27 SSR, covering 4875.29 cM, with an average interval distance of 0.77 cM. A, B and D chromsomes possess 2 390, 3 386, and 468 polymorphism markers, accounting for the proportion of 38.3%, 54.3%, and 7.5%, separately. The average interval distances of the markers were 0.80, 0.75 and 0.80 cM, respectively. QTL analysis of 1000-grain weight was processed under four environments. Total 9 QTL controlling 1000-grain weight were detected located on 1B, 4B, 5B, and 6A. Additive effect of QGW4B-17, QGW4B-5, QGW4B-2, QGW6A-344 and QGW6A-137 was more than 10%, which were considered as major QTL. Among them, QGW4B-17 was detected under several environments, and the phenotypic variation explained by which varied from 16% to 33% with its additive effect from 2.3 to 2.97 g. All the additive effects come from big kernel parent Shannong 01-35,single QTL could increase 1.09-2.97g for 1000-grain weight. 【Conclusion】A genetic map of wheat covering 21 wheat chrosmes was constructed with 6 241 polymorphism markers, with an average interval distance of 0.77 cM. Total 9 QTL controlling 1000-grain weight located on 1B, 4B, 5B, and 6A were detected. Additive effect ofQGW4B-17 was detected under several environments, and the phenotypic variation explained by which varied at 16%-33% with its additive effect at 2.3-2.97 g.

Key words: common wheat, 90K array, QTL mapping, grain weight, SNP