Segregation analysis method for detecting major gene controlling endosperm traits
2005
Xu Chenwu,Hu Zhiqiu,Wang Xuefeng
Китайский. 根据胚乳性状的数量遗传模型，发展出专用于胚乳性状主基因检测、主基因效应与变异估计的分离分析方法。该方法以EM算法实现的极大似然估计方法进行主基因的分离比例、主基因效应和剩余变异估计，以似然比统计量进行主基因检测。用水稻杂交组合IR50×CP231的P1、P2和F2胚乳世代直链淀粉含量（AC）资料演示了分析程序。结果表明该组合的AC遗传涉及一个主基因，该主基因无第一显性效应，其加性效应和第二显性效应分别为5.37和6.85；主基因变异尺度约为微基因变异尺度的两倍。
Показать больше [+] Меньше [-]Английский. Based on the quantitative genetic model for endosperm traits, a new segregation analysis method for detecting major gene controlling endosperm traits was proposed, which includes major gene detection and its effect and variation estimation. The segregation ratios and genetic effect of major gene as well as model residual error caused by polygenes and environments were estimated by the maximum likelihood method implemented via EM algorithm. Major gene effects were tested with the likelihood ratio test (LRT) statistic. An example of the amylose content (AC) for P1, P2 and F2 endosperm generations in rice cross IR50×CP231 was used for the illustration. The results indicate that the genetic difference of AC in this cross refers to only one major gene. The major gene shows no first dominance effect. The additive effect and the second dominance effect of this major gene were estimated as 5.37 and 6.85, respectively. The genetic standard deviation caused by this major gene is about two times of the genetic standard deviation of the polygenes.
Показать больше [+] Меньше [-]