CAJ | 학술논문

主基因加多基因混合遗传模型分离分析方法是基于数量性状表型数据的统计遗传分析方法,该方法适于育种工作者利用杂种分离世代的数据对育种性状的遗传组成做出初步判断,制订相应的育种策略,也可用以校验 QTL定位所揭示的性状遗传组成.重组自交家系群体(RIL)是一种永久性群体,可以进行有重复的比较试验,适合于环境影响较大的复杂性状的遗传研究.本研究以RIL群体为对象,将遗传模型拓展到4对主基因,建立相应的分离分析方法.新构建的模型共包括4对主基因和4对主基因加多基因两类共15个遗传模型,通过极大似然法和IECM算法估算各种模型的分布参数,由AIC值和一组适合性测验选取最佳遗传模型,再由最小二乘法估计模型的遗传参数.通过模拟实验对所建立的模型进行验证,模拟群体中一阶遗传参数的估计值与设定值之间有很好一致性.以大豆科丰1号×南农1138-2构成的RIL群体及其亲本棕榈酸含量的遗传(I-1模型,即4对加性-上位性主基因和加性-上位性多基因遗传模型)为例,说明该方法的应用效果.
주기인가다기인혼합유전모형분리분석방법시기우수량성상표형수거적통계유전분석방법,해방법괄우육충공작자이용잡충분리세대적수거대육충성상적유전조성주출초보판단,제정상응적육충책략,야가용이교험 QTL정위소게시적성상유전조성.중조자교가계군체(RIL)시일충영구성군체,가이진행유중복적비교시험,괄합우배경영향교대적복잡성상적유전연구.본연구이RIL군체위대상,장유전모형탁전도4대주기인,건립상응적분리분석방법.신구건적모형공포괄4대주기인화4대주기인가다기인량류공15개유전모형,통과겁대사연법화IECM산법고산각충모형적분포삼수,유AIC치화일조괄합성측험선취최가유전모형,재유최소이승법고계모형적유전삼수.통과모의실험대소건립적모형진행험증,모의군체중일계유전삼수적고계치여설정치지간유흔호일치성.이대두과봉1호×남농1138-2구성적RIL군체급기친본종려산함량적유전(I-1모형,즉4대가성-상위성주기인화가성-상위성다기인유전모형)위례,설명해방법적응용효과.
The segregation analysis of major genes plus polygenes is a statistical method for genetic analysis of quantitative traits. This method is particularly valuable for breeders to use their data accumulated from segregation populations to estimate the ge-netic system of target traits which is necessary for designing breeding strategies and also useful for validating the results of QTL mapping. The recombinant inbred line (RIL) population is a permanent population, which is suitable for genetic analyses of com-plex traits and can be used in replicated experiments. For RIL, the analytical procedures of three major genes plus polygenes mixed inheritance models have been established and widely used in crops. There is an increasing demand on the genetic model expanding from three major genes plus polygenes to four or more major genes plus polygenes. Therefore, the objective of the present study was to establish the analytical procedures of segregation analyses for four major genes plus polygenes mixed inheri-tance model in RIL population. Fifteen genetic models with four additive and/or epistatic major genes including those without and with polygenes were established. The genetic models and their distribution parameters were solved and estimated with maximumlikelihood method and IECM algorithm. The best model was chosen based on Akaike's Information Criterion (AIC) and a set of goodness of fit tests. The genetic parameters of the best model were estimated with the least square method. The established pro-cedure was validated with a set of Monte Carlo simulation experiments. The results showed a relatively high accuracy and consis-tency for first order parameters between the simulated population and scheduled population. For demonstration of the usefulness of the established procedure, the data of palmitic acid content obtained from a RIL population NJRIKY (derived from Kefeng 1×Nannong 1138-2) along with their P_1 and P_2 were analyzed. The results showed that the data fitted to Model I-l, i.e. four additiveand epistasis major genes plus additive and epistatic polygenes mixed inheritance model.