Li Xiaobai, Yan Wengui, Agrama Hesham, Hu Biaolin, Jia Limeng, Jia Melissa, Jackson Aaron, Moldenhauer Karen, McClung Anna, Wu Dianxing
College of Life Sciences, Zhejiang University, Hangzhou, China.
Genetica. 2010 Dec;138(11-12):1221-30. doi: 10.1007/s10709-010-9521-5. Epub 2010 Nov 16.
A rice mini-core collection consisting of 217 accessions has been developed to represent the USDA core and whole collections that include 1,794 and 18,709 accessions, respectively. To improve the efficiency of mining valuable genes and broadening the genetic diversity in breeding, genetic structure and diversity were analyzed using both genotypic (128 molecular markers) and phenotypic (14 numerical traits) data. This mini-core had 13.5 alleles per locus, which is the most among the reported germplasm collections of rice. Similarly, polymorphic information content (PIC) value was 0.71 in the mini-core which is the highest with one exception. The high genetic diversity in the mini-core suggests there is a good possibility of mining genes of interest and selecting parents which will improve food production and quality. A model-based clustering analysis resulted in lowland rice including three groups, aus (39 accessions), indica (71) and their admixtures (5), upland rice including temperate japonica (32), tropical japonica (40), aromatic (6) and their admixtures (12) and wild rice (12) including glaberrima and four other species of Oryza. Group differentiation was analyzed using both genotypic distance Fst from 128 molecular markers and phenotypic (Mahalanobis) distance D(2) from 14 traits. Both dendrograms built by Fst and D(2) reached similar-differentiative relationship among these genetic groups, and the correlation coefficient showed high value 0.85 between Fst matrix and D(2) matrix. The information of genetic and phenotypic differentiation could be helpful for the association mapping of genes of interest. Analysis of genotypic and phenotypic diversity based on genetic structure would facilitate parent selection for broadening genetic base of modern rice cultivars via breeding effort.
已构建了一个由217份种质组成的水稻微型核心种质库,用以代表美国农业部核心种质库和完整种质库,其中核心种质库和完整种质库分别包含1794份和18709份种质。为提高挖掘有价值基因的效率并拓宽育种中的遗传多样性,利用基因型数据(128个分子标记)和表型数据(14个数量性状)对遗传结构和多样性进行了分析。该微型核心种质库每个位点有13.5个等位基因,这在已报道的水稻种质资源库中是最多的。同样,微型核心种质库的多态信息含量(PIC)值为0.71,在已报道的种质库中,该值除了在一个种质库中是最高的之外,在其他种质库中也是最高的。微型核心种质库中较高的遗传多样性表明,挖掘感兴趣的基因以及选择能够提高粮食产量和品质的亲本具有很大可能性。基于模型的聚类分析结果显示,低地稻包括三个组,即奥氏稻(39份种质)、籼稻(71份)及其杂交种(5份);高地稻包括温带粳稻(32份)、热带粳稻(40份)、香稻(6份)及其杂交种(12份);野生稻(12份)包括光稃稻和其他四种稻属物种。利用128个分子标记的基因型距离Fst和14个性状的表型(马氏)距离D(2)对群体分化进行了分析。由Fst和D(2)构建的两个聚类图在这些遗传群体之间达到了相似的分化关系,并且Fst矩阵和D(2)矩阵之间显示出较高的相关系数0.85。遗传和表型分化信息有助于对感兴趣的基因进行关联作图。基于遗传结构对基因型和表型多样性进行分析,将有助于通过育种工作选择亲本,以拓宽现代水稻品种的遗传基础。