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作物学报 ›› 2010, Vol. 36 ›› Issue (12): 2099-2106.doi: 10.3724/SP.J.1006.2010.02099

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

苎麻核心种质构建方法

栾明宝,陈建华*,许英,王晓飞,孙志民   

  1. 中国农业科学院麻类研究所 / 农业部茎纤维生物质与工程微生物重点开放实验室, 湖南长沙 410205
  • 收稿日期:2010-04-03 修回日期:2010-08-05 出版日期:2010-12-12 网络出版日期:2010-10-14
  • 通讯作者: 陈建华,E-mail:cjhbt@sina.com
  • 基金资助:

    本研究由农业部保种项目(NB09-2130135-41),国家自然科学基金项目(30900913)和中国农业科学院科技经费项目资助。

Method of Establishing Ramie Core Collection

LUAN Ming-Bao,CHEN Jian-Hua*,XU Ying,WANG Xiao-Fei,SUN Zhi-Min   

  1. Institute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences / Key laboratory of Stem-Fiber Biomass and Engineering Microbiology, Ministry of Agriculture, Changsha 410205, China
  • Received:2010-04-03 Revised:2010-08-05 Published:2010-12-12 Published online:2010-10-14
  • Contact: 陈建华,E-mail:cjhbt@sina.com

摘要: 选用国家长沙苎麻圃的790份种质资源, 在已有的25个性状数据的基础上, 采用不同取样方法、不同系统聚类方法、不同遗传距离方法构建苎麻核心种质, 用质量性状的多样性指数均值、表型保留比率均值和数量性状均值差异百分率、方差差异百分率、极差符合率和变异系数变化率等6个指标评价不同方法组合(取样方法、聚类方法、遗传距离)构建核心种质的优劣。选出合适的构建方法, 构建苎麻核心种质。结果表明, 不同的取样方法对质量性状和数量性状的遗传多样性影响不同, 就质量性状的最大遗传多样性而言, 选择优先取样+多次聚类随机取样方法比较适宜, 而对数量性状的最大遗传多样性而言, 选择优先取样+多次聚类变异度取样方法则较适宜。用优先取样+多次聚类随机取样方法取样时, 采用最短距离法和重心法构建的核心种质最好, 用优先取样+多次聚类变异度取样时, 采用离差平方和法则是构建苎麻核心种质的最佳聚类方法。苎麻核心种质构建与质量性状的不同遗传距离无关, 但数量性状以欧氏距离最佳。

关键词: 苎麻, 核心种质, 取样方法, 聚类方法, 遗传距离

Abstract: Ramie (Boehmeria nivea L. Gaud) is an important bast fiber crop. Its fiber, one of the best bast fibers, is widely used in textile industry and plays an indispensable and irreplaceable role in the national economy. Core collection is a representative subset of entire germplasm collection, consisting of introduced accessions with minimum genetic redundancy and retained most initial collection. To develop the method of establishing ramie core collection, based on 25 agrinomic traits data from 790 ramie germplasm of national ramie germplasm nursery, using software provided by professor Xu of Zhejiang university, we sampled a serials of subsets at 20% proportion, respectively, by six hierarchical clustering methods (single linkage, complete linkage, median method, centroid method, ward’s, unweighted pair-group method with arithmetic means), three sampling methods (stepwise clustering with random sampling strategy and preferred sampling strategy, stepwise clustering with deviation sampling strategy and preferred sampling strategy, random sampling strategy), three genetic distances in disordered qualitative traits (simple matching, jaccard, nei and li), and three genetic distances in ordered qualitative traits and quantitative characteristics (mahalanobis distance, euclidean distance, principal component). The genetic variation among subsets was compared by evaluating the I (index of genetic diversity), RPR (ratio of phenotype retained) of qualitative traits and MD (mean difference percentage), VD (variance difference percentage), CR (coincidence difference percentage), VR (variable rate of coefficient of variation) of quantitative traits. The results showed that different sampling methods have different impacts on qualitative traits and quantitative traits. For the largest genetic diversity of qualitative traits, it is effective to choose stepwise clustering with random sampling strategy and preferred sampling strategy. For the largest genetic diversity of quantitative traits, it is effective to choose stepwise clustering with deviation sampling strategy and preferred sampling strategy. The ramie core collection is the best one constructed by centroid method, single linkage clustering way under stepwise clustering with random sampling strategy and preferred sampling strategy and constructed by ward’s clustering way under stepwise clustering with deviation sampling strategy and preferred sampling strategy. Core collection in ramie was not related with genetic distances of qualitative traits, whereas the core collection of ramie constructed by euclidean distance of quantitative traits was the best.

Key words: Ramie, Core collection, Sampling method, Clustering method, Genetic distance

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