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作物学报 ›› 2015, Vol. 41 ›› Issue (07): 1064-1072.doi: 10.3724/SP.J.1006.2015.01064

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

大麦农艺性状与SSR标记的关联分析

司二静1,2,张宇1,2,汪军成1,2,孟亚雄1,2,李葆春1,3,马小乐1,2,尚勋武2,王化俊1,2,*   

  1. 1甘肃省干旱生境作物学重点实验室 / 甘肃省作物遗传改良与种质创新重点实验室, 甘肃兰州 730000; 2甘肃农业大学农学院, 甘肃兰州 730000; 3甘肃农业大学生命科学技术学院, 甘肃兰州 730000
  • 收稿日期:2014-11-14 修回日期:2015-04-02 出版日期:2015-07-12 网络出版日期:2015-05-04
  • 通讯作者: 王化俊, E-mail:whuajun@yahoo.com
  • 基金资助:

    本研究由国家自然科学基金项目(31171558),国家现代农业产业技术体系建设专项(CARS-05)和甘肃省财政厅专项基金(035-041047)资助。

Association Analysis between SSR Markers and Agronomic Traits in Barley

SI Er-Jing12,ZHANG Yu12,WANG Jun-Cheng12,MENG Ya-Xiong1,2,LI Bao-Chun1,3,MA Xiao-Le12,SHANG Xun-Wu2,WANG Hua-Jun1,2,*   

  1. 1 Gansu Provincial Key Laboratory of Aridland Crop Science / Gansu Key Laboratory of Crop Improvement & Germplasm Enhancement, Lanzhou 730070, China; 2 College of Agronomy, Gansu Agricultural University, Lanzhou 730070, China; 3 College of Life Science and Technology, Gansu Agricultural University, Lanzhou 730070, China
  • Received:2014-11-14 Revised:2015-04-02 Published:2015-07-12 Published online:2015-05-04
  • Contact: 王化俊, E-mail:whuajun@yahoo.com

摘要:

为了解大麦亲本材料遗传特性和主要农艺性状特征,采用156份不同来源的大麦材料,在86个多态性SSR位点上检测遗传多样性,同时对7个农艺性状在两试验点作表型鉴定,利用GLM和MLM模型进行分子标记与表型性状的关联分析。结果共检测出392个等位变异,平均每个标记4.6个,PIC值变异范围为0.0612~0.8560。群体遗传结构分析将156份材料分为2个亚群。利用GLM模型分析结果表明,与株高、穗长、芒长、穗粒数和千粒重5个性状相关联的标记有18个,单个标记对表型变异的解释率为4.81%~20.75%;利用MLM模型分析,与株高、穗长、芒长、分蘖数、穗粒数和千粒重6个性状相关联的标记有14个,单个标记对表型变异的解释率范围为6.64%~31.55%。这些关联标记对后续研究有参考价值。

关键词: 大麦, SSR, 群体结构, 农艺性状, 关联分析

Abstract:

This study aimed at understanding the population structure of barley parent materials and identifying SSR markers associated with plant height, spike length, awn length, tiller number, effective tiller number, grain number per spike and thousand-grain weight. A total of 392 alleles were identified in 156 accessions using 86 polymorphic SSR markers with an average of 4.6 alleles per locus. The polymorphic information content ranged from 0.0612 to 0.8560. The 156 genotypes were divided into two populations according to structure analysis with SSR data. Eighteen markers were found to be associated with plant height, spike length, awn length, grain number per spike and thousand-grain weight using GLM (General Linear Model), and the phenotypic variation explained by a single marker ranged from 4.81% to 20.75%. Fourteen markers were found to be associated with plant height, spike length, awn length, effective tiller number, grain number per spike and thousand-grain weight using MLM(Mixed Linear Model), and the phenotypic variation explained by a single marker ranged from 6.64% to 31.55%. These associated markers provide a basis for future research.

Key words: Barley, SSR, Population structure, Agronomic trait, association analysis

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