我国西北春麦区小麦育成品种遗传多样性的AFLP分析

对我国西北春麦区56份小麦育成品种应用扩增片段长度多态性(Amplified Fragment Length Polmorphics，简称AFLP)分子标记技术进行遗传多样性分析。共用24对引物组合进行扩增，每对引物组合的平均多态性条带为14．7,多态性百分率为24．4，而多态性信息指数PIC范围为0．11～0．44，平均0．22。结合品种的系谱亲缘关系分析，得知依据AFLP数据的类群划分结果与品种的亲缘系谱关系基本一致，表明AFLP技术用于种质鉴定和遗传多样性研究是有效的、可取的；同时。对如何合理应用AFLP数据中的多态性带和共有带进行聚类分析，及如何正确对待小麦核心种质构建中的形态和农艺性状数据与分子数据的问题作了进一步的探讨。仅用多态性谱带产生的相似系数矩阵与用所有扩增谱带产生的相似系数矩阵之间的相关系数r=0．86，表明在利用AFLP进行品种间遗传关系分析时，利用所有扩增产物的信息是必要的；如果仅仅是为了鉴剐品种或压缩样品，完全可以只考虑多态性扩增产物。利用AFLP分子数据和田间数据对56份材料进行主成分分析(PCO)，发现用田间数据产生的PCO图，材料之间分散，遗传关系不很明了，进一步压缩样品难度较大；而分子数据产生的PCO图，可将材料分成明显的五类，聚类结果与品种系谱基本相吻合，为进一步压缩样品提供了科学依据。形态数据与分子数据聚类的结果差异较大，相关系数仅为0．310因此，在利用田间数据的基础上，必须兼顾和利用DNA数据，才能保证所建立核心种质的代表性。这也是一条比较科学、经济和可行的途径。

Genetic Diversity of Wheat Varieties Released in Northwest Spring Wheat Region Revealed by AFLP

AFLP (amplified restriction fragment polymorphism) is an efficient molecular marker system for identification of varieties and genetic diversity research. Fifty-six improved wheat varieties released in Northwest Spring Wheat Region were analyzed by AFLP. Results of cluster analysis based on the AFLP data was basically consistent with the pedigrees of these varieties. At the same time, Correlation coefficient (r=0.86) between genetic distance matrices (Dice) based on the all AFLP bands and polymorphic bands indicated that all amplified bands should be included in order to realistically reflect the genetic relationship among varieties. However, for discrimination of varieties or capture of the accessions in core collections, we can only use the polymorphic band data. Multidimensional principal coordinate (PCO) analyses of these varieties based on the AFLP data showed that they can be clearly clustered into 5 groups, which is very helpful for further capturing these varieties. However, these varieties could not be clustered into groups clearly in the PCO figure based on the agronomic and botanic data, indicating the limitation of these data in revealing the genetic relationships among varieties. The low correlation coefficient (r=0.31) between the matrices based on agronomic and botanic data and AFLP data revealed the necessity to employ the molecular data in genetic diversity research and construction of a core collection.