摘 要 ：以月季品种的微卫星标记数据为基础,选择7个遗传相似系数对月季品种间遗传相似度进行计算,并采用非加权组平均法(UPGMA)建立相应的系统树。通过遗传相似系数相关性、聚类结果一致性以及拟合优度等分析方法,探讨不同的遗传相似系数在微卫星遗传分析中的适用性。分析数据显示7个系数之间相关系数介于0.726～1.000。共表型相关系数rc介于0.85～0.93,表明品种间遗传差异在基于UPGMA方法的聚类树状图中有良好体现。系统树之间的CIc指数范围为0.468～1.000,表明采用不同相似系数进行聚类分析时,结果存在较大差异。7个遗传相似系数的S统计值介于16.24%～29.90%,Russel and Rao系数最低,Simple Matching等3个系数S值均大于20%。综合考虑分子标记特点、物种杂合度、Kruskal拟合优度等因素,并结合聚类分析与品种谱系比较结果,研究认为Dice系数和Jaccard系数适用于月季的微卫星遗传分析,其次是Simple Matching系数。
Abstract:Seven genetic similarity coefficients were selected to calculate pairwise genetic similarity of rose (Rosa) varieties based on microsatellite data, and the 7 corresponding dendrograms were constructed by Unweighted Pair Group Method with Arithmetic Mean. The applicability of different genetic similarity coefficients in analyzing genetic relationships based on the microsatellite in rose varieties was investigated by means of correlation analysis between genetic similar matrixes, consistency analysis between cluster trees, and test of the goodness of fit. The result showed that correlation coefficients between different similar matrixes ranged from 0.726 to 1.000. Cophenetic correlation coefficients ranged from 0.85 to 0.95, indicating that there was a good representation of similarity matrixes in the form of dendrograms. Index of CIc between pairwise dendrograms ranged from 0.468 to 1.000, which indicated that dendrograms were dependent on selection of different genetic similarity coefficients. STRESS values among the 7 genetic similarity coefficients ranged from 16.24% to 29.90%. The STRESS values of Simple Matching, Roger and Tanimoto, and Hamann coefficients were all more than 20%. Comprehensive consideration of molecular marker characteristics, species heterozygosis, STRESS value, and combined with clustering result and variety lineage, Dice coefficient and Jaccard coefficient were found to be the most appropriate for rose variety genetic analysis, followed by Simple Matching coefficient.