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Strategies on Sample Size Determination and Qualitative and Quantitative Traits Integration to Construct Core Collection of Rice (Oryza sativa)

查看全文 作　　者：LI Xiao-[1]ling;LU Yong-[1]gen;LI Jin-[1]quan;XU Hai-[2,3]ming;Muhammad Qasim [1]SHAHID 高影响力作者 机构地区：[1]Guangdong Provincial Key Laboratory of Plant Molecular Breeding, South China Agricultural University, Guangzhou 510642, China;[2]Department of Agronomy, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310029, China;[3]Now work at Hubei Provincial Key Laboratory of Natural Products Research and Development, China Three Gorges University, Yicang 443002, China高影响力机构 出　　处：《Rice science》索引2011年第18卷第1期,共10页高影响力期刊 基　　金：supported by the National Natural Science Foundation of China (Grant No. 30700494);the Principal Fund of South China Agricultural University, China (Grant No. 2003K053) 摘　　要：The development of a core collection could enhance the utilization of germplasm collections in crop improvement programs and simplify their management. Selection of an appropriate sampling strategy is an important prerequisite to construct a core collection with appropriate size in order to adequately represent the genetic spectrum and maximally capture the genetic diversity in available crop collections. The present study was initiated to construct nested core collections to determine the appropriate sample size to represent the genetic diversity of rice landrace collection based on 15 quantitative traits and 34 qualitative traits of 2 262 rice accessions. The results showed that 50-225 nested core collections, whose sampling rate was 2.2%-9.9%, were sufficient to maintain the maximum genetic diversity of the initial collections. Of these, 150 accessions (6.6%) could capture the maximal genetic diversity of the initial collection. Three data types, i.e. qualitative traits (QT1), quantitative traits (QT2) and integrated qualitative and quantitative traits (QTT), were compared for their efficiency in constructing core collections based on the weighted pair-group average method combined with stepwise clustering and preferred sampling on adjusted Euclidean distances. Every combining scheme constructed eight rice core collections (225, 200, 175, 150, 125, 100, 75 and 50). The results showed that the QTT data was the best in constructing a core collection as indicated by the genetic diversity of core collections. A core collection constructed only on the information of QT1 could not represent the initial collection effectively. QTT should be used together to construct a productive core collection. 关 键 词：核心种质 数量性状 样本大小 ORYZA 水稻 遗传多样性 收集利用 集成
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