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作物学报

作物学报 ›› 2015, Vol. 41 ›› Issue (07): 1007-1016.doi: 10.3724/SP.J.1006.2015.01007

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

用全基因组关联分析解析籼稻垩白的遗传基础

邱先进1,2,袁志华1,陈凯4,杜斌1,何文静1,杨隆维1,2,徐建龙3,4,*,邢丹英1,2,*,吕文恺1   

  1. 部工程技术中心, 湖北荆州 434025；3中国农业科学院作物科学研究所, 北京 100081；4中国农业科学院深圳农业基因组研究所, 广东深圳 518120
  • 收稿日期:2015-01-14 修回日期:2015-04-02 出版日期:2015-07-12 网络出版日期:2015-05-04
  • 基金资助:

    本研究由湖北省科技支持计划项目(2013BBB23)，长江大学作物学省级重点学科项目(2015)，全球水稻科学伙伴协作计划“水稻适应性与产量表型组学”项目(DRPC2012)，粮食作物种质创新与遗传改良重点实验室开放课题(2014lzjj04)和主要粮食作物产业化湖北省协同创新中心开放基金(2015MS08)资助。

Genetic Dissection of Grain Chalkiness in Indica Mini-core Germplasm Using Genome-wide Association Method

QIU Xian-Jin1,2,YUAN Zhi-Hua1,CHEN Kai4,DU Bin1,HE Wen-Jing1,YANG Long-Wei1,2,XU Jian-Long3,4,*,XING Dan-Ying1,2,*,LÜ Wen-Kai1   

  1. 1 College of Agriculture, Yangtze University, Jingzhou434025, China; 2 Hubei Collaborative Innovation Center for Grain Industry / Engineering Research Center of Ecology and Agricultural Use of Wetland, Ministry of Education, Jingzhou 434025, China; 3 Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China; 4 Institute of Agricultural Genomics at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
  • Received:2015-01-14 Revised:2015-04-02 Published:2015-07-12 Published online:2015-05-04

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被引次数

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摘要：

利用272份全球籼稻微核心种质的重测序SNP基因型，对海南三亚、广东深圳、浙江杭州和湖北荆州4个地点收集到的垩白粒率和垩白度性状采用TASSEL软件进行全基因组关联分析，解析籼稻垩白的遗传基础和挖掘影响垩白粒率和垩白度的优异等位基因。结果表明，依据SNP数据，可将籼稻微核心种质分成3个亚群。4个地点分别检测到42个和44个与垩白粒率和垩白度显著关联的位点，位于全部12条染色体上。两个性状分别有21个和19个位点在2个以上环境下同时被检测到，这些位点中有12个位点同时影响垩白粒率和垩白度，11个位点附近都有已克隆的水稻品质相关基因。其中，第5染色体3.3~5.3 Mb区间在4个地点都被检测到与垩白粒率显著关联，以杭州点对垩白粒率的贡献最大，优异等位基因载体品种为IRGC121689；第12染色体的17.5~18.0 Mb区间在三亚和杭州都被检测到与垩白度显著关联，以三亚点的垩白度贡献最大，优异等位基因载体品种为IRGC122285。这些位点和品种资源可作水稻外观品质分子改良的重要基因和品种资源。

关键词: 水稻, 垩白, 关联分析, SNP标记, 连锁不平衡

Abstract:

In order to dissect the genetic bases and mine novel alleles of grain chalkiness in indica, we conducted an experiment with  genome-wide association analysis using phenotypic data collected from multiple locations (Sanya of Hainan, Shenzhen of Guangdong, Hangzhou of Zhejiang, and Jingzhou of Hubei) and 6704 re-sequenced SNP markers distributed in whole genome for 272 indica mini-core germplasm collected worldwide. All accessions were classified into three subpopulations based on SNP data. Total of 42 and 44 loci were detected as significant associations with percentage of grains with chalkiness (PGWC) and degree of endosperm chalkiness (DEC), respectively, which distributed all over the 12 chromosomes. Twenty one and nineteen loci were stably expressed for PGWC and DEC in multiple locations, respectively, and 12 simultaneously affected the two traits. Eleven of the said loci were co-located in the same or near regions harboring the quality genes cloned previously. Of them, the region of 3.3–5.3 Mb on chromosome 5 was significantly associated with PGWC at all four locations, having the largest phenotypic contribution detected in Hangzhou location, and the carrier variety with the best favorable allele was IRGC121689; the another region of 17.5–22.7 Mb on chromosome 12 was significantly associated with DEC at Sanya and Hangzhou, having the largest phenotypic contribution detected in Sanya, and the carrier variety with the best favorable allele was IRGC122285. These loci and germplasms are important potential genes and variety resources that can be used in molecular breeding for rice appearance quality.

Key words: Rice, Chalkiness, Association mapping analysis, SNP marker, Linkage disequilibrium

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