摘要
[目的]探讨厚朴种源间、种源内家系及家系内个体间的遗传多样性，为厚朴良种选育提供理论依据。[方法]采用AFLP分子标记技术，分析来自湖北、广西和浙江的厚朴种源间、半同胞家系间及家系内单株间的遗传多样性。[结果]3个种源材料遗传距离为0．0482～0．1284，广西资源和浙江景宁2个群体相似性较高。种群遗传多样性平均水平、总种群基因多样度、基因流分别为0．2035、0．2541、3．4217。观测等位基因数和有效等位基因数平均数分别为1．6583和1．3414；Nei’s基因多样性和Shannon多样性指数均值分别为0．2035和0．3087，其中湖北五峰的遗传多样性水平最高（为0．2258），浙江景宁遗传多样性水平最低（为0．1739）。湖北五峰、广西资源、浙江景宁家系内遗传多样性分别为0．2644、0．1819、0．1738，Shannon多样性指数为0．4154。[结论]湖北五峰种源遗传多样性水平最高，湖北五峰家系内的遗传多样性最丰富，存在较大的遗传分化。不同种源内家系之间的多样性指数及信息指数相差不多，说明在各自的生态环境中的变异水平相近。在厚朴良种选育过程中应充分重视优良种源、优良家系与优良单株的配合选择。
Abstract
Objective] The aim was to investigate the genetic diversity of Magnolia officinalisfrom different provenances,families and individu-als, provide a theoretical basis for breeding.[ Method] Amplified fragment length polymorphism( AFLP) was used to evaluate the genetic di-versity of Magnolia officinalis from Hubei, Guangxi and Zhejiang among different provenances, families, individuals.[ Result] The genetic dis-tance between the 3 provenances was 0.048 2-0.128 4, and the similarity between Guangxi and Zhejiang was higher than Hubei.The aver-age level of population genetic diversity, total population gene diversity, gene flow were 0.203 5, 0.254 1, 3.421 7.The average number of observed alleles and effective alleles were 1.658 3 and 1.341 4; Nei’s and Shannon diversity index were 0.203 5 and 0.308 7.The genetic diversity level of Hubei was the highest (0.225 8), Zhejiang Jingning was the lowest (0.173 9).The genetic diversity in families were 0.264 4, 0.181 9 and 0.173 8, Shannon diversity index was 0.415 4.[Conclusion]The genetic diversity of Hubei Wufeng was the highest, and so was the genetic diversity among individuals.The diversity index and information index among different provenances were close which in-dicate that the variation level of the different species in families was similar in the respective ecological environment.It should be payed full at-tention to the selection of superior provenances,families and superior individuals in the process of breeding of Magnolia officinalis.
国家科技期刊平台
NSTL
维普
万方数据