分子标记回归模型与显性分子标记资料

Molecular Marker Regression Model and Dominant Molecular Marker Material

对以正交表形式表示的分子标记资料所配合的显性分子标记回归方程进行了探讨。结果表明 ,运用以正交表形式表现的显性基因显性分子标记资料 ,所配合的分子标记回归方程可以对基因的作用加以估计。而运用正交表中的资料的部分行作为自变量 ,则不能进行分子标记回归方程的配合。非标记 DNA片段增加了分子标记资料的个体数与所需筛选的群体。如果将试验时筛选下的个体分子标记资料套入得到的回归方程得到的个体表型值超出了环境变异所允许的范围 ,需增加分子标记数 ,以增加预测效果。

In this article, molecular marker regression equations fitting molecular marker material are discussed. The result shows: The genes effect can be estimated by the constant of molecular marker regression equations fitting the orthogonal layout molecular marker material. But, if only partly rows of orthogonal layout are used, the genes effect could not be estimated. The DNA segments which are not markers enhanced the individual number of molecular marker material, and enlarged the group in which the individuals are selected. If the individual quantitative trait phenotype value estimated according to the molecular marker regression equation fitting molecular marker material dont coincide with the actual quantitative trait phenotype value, the molecular marker number should be added to increase the effect of estimation. The genes locus with nonpolymorphism dont affect the accuracy of other gene relative value estimation