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长江春大豆核心种质构建及分析
引用本文:王丽侠,李英慧,李伟,朱莉,关媛,宁学成,关荣霞,刘章雄,常汝镇,邱丽娟.长江春大豆核心种质构建及分析[J].生物多样性,2004,12(6):578-585.
作者姓名:王丽侠  李英慧  李伟  朱莉  关媛  宁学成  关荣霞  刘章雄  常汝镇  邱丽娟
作者单位:中国农业科学院作物科学研究所,农业部作物种质资源与生物技术重点开放实验室,北京,100081
基金项目:国家重点基础研究发展规划“973”“大豆核心种质构建”课题(G19980 10 2 0 3 )
摘    要:利用长江春大豆初选核心种质SSR(simple sequence repeat)标记和农艺性状表型等基础数据,对用不同个体取样方法以及不同数据类型建立的核心种质进行评价,目的是确定中国大豆(Glycine max)核心种质的最佳取样策略提供依据,结果表明,根据SSR分子数据聚类,采用类内随机取样,类内以遗传相似性系数取样以及仅依据遗传相似性系数取样都可用于大豆核心种质构建,但是综合不同评价参数发现,以类内随机取样最佳,类内按遗传相似性系数取样次之,单独以遗传相似性系数取样较差。分析不同SSR等位变异保留比例的遗传多样性指数发现,当保留90%和80%的SSR等位变异时,核心种质具有更高的遗传多样性,由于与SSR分子数据种质遗传关系评价的不一致性,农艺性状等基础数据虽然可用来构建核心种质,但其SSR分子水平代表性相对较低,本研究结果还表明,用不同方法或同一方法不同重复次数取样建立的核心种质具有异质性,且这种异质性随核心种质取样比例的降低而增大,因此,虽然可依据不同数据类型确定相应的方法建立核心种质,但综合表型和分子数据建立的核心种质更具有代表性。

关 键 词:SSR分子标记  农艺性状  聚类分析  等位变异保留比例  取样策略
文章编号:1005-0094(2004)06-0578-08
收稿时间:2004-5-13
修稿时间:2004年5月13日

Establishment of a core collection of Changjiang spring sowing soybean
WANG Li-Xia,LI Ying-Hui,LI Wei,ZHU Li,GUAN Yuan,NING Xue-Cheng,GUAN Rong-Xia,LIU Zhang-Xiong,CHANG Ru-Zhen,QIU Li-Juan Key Lab of Crop Germplasm Resources and Biotechnology of the Ministry of Agriculture.Establishment of a core collection of Changjiang spring sowing soybean[J].Biodiversity Science,2004,12(6):578-585.
Authors:WANG Li-Xia  LI Ying-Hui  LI Wei  ZHU Li  GUAN Yuan  NING Xue-Cheng  GUAN Rong-Xia  LIU Zhang-Xiong  CHANG Ru-Zhen  QIU Li-Juan Key Lab of Crop Germplasm Resources and Biotechnology of the Ministry of Agriculture
Institution:WANG Li-Xia,LI Ying-Hui,LI Wei,ZHU Li,GUAN Yuan,NING Xue-Cheng,GUAN Rong-Xia,LIU Zhang-Xiong,CHANG Ru-Zhen,QIU Li-Juan Key Lab of Crop Germplasm Resources and Biotechnology of the Ministry of Agriculture,Institute of Crop Science,Chinese Academy of Agricultural Sciences,Beijing 100081
Abstract:Sampling strategy is very important for core collection establishment. In this study, different methods to construct a core collection of Changjiang spring sowing soybean were performed based on data of SSR(simple sequence repeat) markers and agronomic traits in order to optimize the sampling strategy for core collection. The results showed that, based on cluster analysis of SSR data, each of the three methods, i.e., random sampling within each group, sampling by genetic similarity coefficient within each group and sampling by genetic similarity coefficient, could be used to construct a soybean core collection. When SSR allelic reserving ratios were maintained at 90% and 80%, the core collections had higher genetic diversity indices of SSR alleles than if maintained at 70%. Core collections could also be constructed by agronomic and other basic data if there was no molecular data; however, SSR allelic reserving ratio might be decreased, which suggested that assessment of genetic diversity by SSR data was not always consistent with assessment by agronomic data. We found that core collections were heterogeneous, either when created with different sampling methods or with the same sampling method in different repeats, because randomicity always existed in selecting individuals. This indicated that the germplasm to form a core collection was variable, so optimal sampling strategies should be chosen to establish core collections based on different data according to practical or scientific objectives. Integrating phenotypic and genotypic data together would be better for improving the representativeness of core collections.
Keywords:SSR markers  agronomic traits  cluster analysis  reserving ratio of SSR alleles  sampling strategy
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