基于水青树叶表型性状的核心种质资源库构建策略

Construction Strategy of Core Collection Based on Leaf Phenotypic Traits of Tetracentron sinense

[目的]为了更好地构建水青树核心种质资源库,本文以161个水青树种质为试材,利用叶表型性状的遗传变异数据,对其构建方法进行了探索。[方法]首先,采用欧氏距离和瓦尔德法对所有个体进行逐步聚类;然后,设定10个取样比例(10%、15%、20%、25%、30%、35%、40%、45%、50%、55%),分别用随机取样策略、偏离度取样策略和位点优先取样策略筛选出与之对应的核心种质资源库。将这3种不同取样策略构建的核心种质资源库进行比较,从而筛选出最适种质资源。[结果](1)三种取样策略中,位点优先取样法明显提高了其种质资源库的方差差异百分率(VD)、变异系数变化率(VR)和极差符合率(CR),且45%是最适合构建水青树核心种质资源库的比例;(2)对种质资源核心库不同数量性状进行t检验,其累计贡献率达到82%以上。[结论]在欧氏距离结合瓦尔德法聚类条件下,位点优先取样策略是构建水青树种质资源核心库的最佳方法。

[Objective] To construct the core collection bank of Tetracentron sinense.[Method] Taking 161 germplasm of T. sinense as samples, the genetic variation data of leaf phenotypic characters of T. sinense were studied. First, the methods of Euclidean distance and Wald were used to cluster all individuals step by step. Second, 10 sampling ratios (10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, and 55%) were set, and then their core collection were screened by random sampling strategy, deviation sampling strategy and allele preferred sampling strategy. The germplasm resource banks constructed under different sampling strategies were compared and then the optimum core collection was screened out.[Result](1) Among the three sampling strategies, the allele preferred sampling strategy significantly increased the percentage of variance difference (VD), the variation rate of coefficient of variation(VR) and the coincidence rate of range difference (CR) in core collection. 45% is the most suitable sampling ratio to construct core collection of T. sinense.(2) The t test for different quantitative characters of core collection showed that the cumulative contribution rate of core collection was higher than 82%.[Conclusion] The allele preferred sampling strategy is the most appropriate to construct the core collection of T. sinense with the methods of Euclidean distance and Wald.