尾叶桉核心种质初步构建

    Preliminary construction of core collection of Eucalyptus urophylla germplasm

    • 摘要: 【目的】为了快速、准确地从丰富的尾叶桉 Eucalyptus urophylla 种质资源中鉴定出育种上迫切需要的优异基因,初步构建了尾叶桉核心种质,以便简化管理,提高遗传资源在尾叶桉改良中的利用效率.【方法】以尾叶桉27个种源194个家系的树高、胸径、材积等17个数量性状为依据,采用不同的取样比例(5%、10%、20%、30%和40%)、3种遗传距离计算方法(欧氏距离、标准欧氏距离和马氏距离)、4种系统聚类方法(最短距离法、最长距离法、不加权类平均法和离差平方和法)和2种取样方法(随机取样法和最小距离逐步取样法)构建尾叶桉核心种质资源库,利用均值差异百分率(MD)、方差差异百分率(VD)、变异系数变化率(VR)和极差符合率(CR)作为构建核心种质的评价指标.【结果和结论】结果表明采用10%的抽样比例、标准欧氏距离、最短距离系统聚类法和最小距离逐步取样法构建的包括25个种源100个家系的尾叶桉核心种质最能代表原有的种质群体.

       

      Abstract: 【Objective】In order to rapidly and precisely identify the excellent gene for the breeding of Eucalyptus urophylla, the construction of core collection of E.urophylla was necessary. Establishing a core collection of E.urophylla could simplify the management and enhance the utilization of genetic resources in E.urophylla research programs. 【Method】Based on 17 quantitative traits, height, diameter and volume of 194 families from 27 provenances of E.urophylla, core collections were constructed using different sampling proportions (5%, 10%, 20%, 30%, and 40%), 3 distances (Euclidean distance, Standardized Euclidean distance, and Mahalanobis distance), 4 hierarchical clustering methods (Single distance method, Complete distance method, Unweighted pair-group average method and Ward’s method), and 2 sampling strategies (random sampling and least distance stepwise sampling) were employed. The genetic variation of the quantitative traits among these core collections was compared by evaluating the mean difference percentage (MD), variance difference percentage (VD), changeable rate of coefficient of variation (VR) and coincidence rate of range (CR) of the traits.【Result and conclusion】The results showed that the primary core collection was constructed with 10% sampling proportion, standardized Euclidean distance, Single distance method,and least distance stepwise sampling, which was composed of 100 families from 27 provenances of E.urophylla and the best representative of total germplasm.

       

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