CAJ | 학술논문

主基因加多基因混合遗传模型是用于分析数量性状表型数据的统计分析方法,该方法便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初步判断,制定相应的育种策略,也可用于校验 QTL 定位所揭示的数量性状的性状遗传组成.回交自交系(BIL)群体是永久性群体,可以进行有重复的比较试验,适用于受环境影响较大的复杂性状的遗传研究.本研究以 BIL 群体为对象构建了4对主基因、主基因加多基因分离分析方法的遗传模型,包括2类11个遗传模型.利用基于IECM (iterative expectation conditional maximization)算法的极大似然分析方法估算各个混合遗传模型中的分布参数,用 AIC 值和一组适合性测验结果选取最优模型,并从入选模型的分布参数通过最小二乘法估计遗传参数.由1个模拟的随机区组试验对模型进行验证,模拟群体中遗传参数的估计值与设定值之间具有很好的一致性.利用本文建立的模型重新分析大豆回交自交系群体(Essex×ZDD2315)及其亲本对胞囊线虫(Hetero-dera glycines Ichinohe)1号生理小种的抗性数据后发现4对主基因模型优于原报道的3对主基因模型,说明本方法的有效性和正确性.
주기인가다기인혼합유전모형시용우분석수량성상표형수거적통계분석방법,해방법편우육충공작자이용잡충분리세대적수거대육충성상적유전조성초보판단,제정상응적육충책략,야가용우교험 QTL 정위소게시적수량성상적성상유전조성.회교자교계(BIL)군체시영구성군체,가이진행유중복적비교시험,괄용우수배경영향교대적복잡성상적유전연구.본연구이 BIL 군체위대상구건료4대주기인、주기인가다기인분리분석방법적유전모형,포괄2류11개유전모형.이용기우IECM (iterative expectation conditional maximization)산법적겁대사연분석방법고산각개혼합유전모형중적분포삼수,용 AIC 치화일조괄합성측험결과선취최우모형,병종입선모형적분포삼수통과최소이승법고계유전삼수.유1개모의적수궤구조시험대모형진행험증,모의군체중유전삼수적고계치여설정치지간구유흔호적일치성.이용본문건립적모형중신분석대두회교자교계군체(Essex×ZDD2315)급기친본대포낭선충(Hetero-dera glycines Ichinohe)1호생리소충적항성수거후발현4대주기인모형우우원보도적3대주기인모형,설명본방법적유효성화정학성.
The segregation analysis of major genes plus polygenes is a statistical method for genetic analysis of quantitative traits. The method is particularly valuable for plant breeders to use their data accumulated from segregation populations to estimate the genetic system of target traits, which is necessary for designing breeding strategies and also useful for validating the results of QTL mapping. The backcross inbred line (BIL) population is one of the permanent populations, which is suitable for genetic analysis of complex traits and can be used in replicated experiments. For BIL population, the analytical procedures of three and less major genes plus polygenes mixed inheritance models have been established. The objective of the present study was to estab-lish the analytical procedures of segregation analysis for four major genes plus polygenes mixed inheritance models in BIL popu-lation. Eleven genetic models with four additive and (or) epistatic major genes including those without and with polygenes were established. The component distribution parameters were solved and estimated by using maximum likelihood method based on IECM (Iterative Expectation Conditional Maximization) algorithm. Among the possible models, the best one was chosen accord-ing to Akaike’s Information Criterion (AIC) and a set of tests for goodness of fit. Then the genetic parameters of the optimal model were estimated through the least square method. For demonstration of the established procedures, a simulated data set of a randomized block experiment with three replications was analyzed and the estimated genetic parameters showed a relatively high consistency with those fixed for the model. To validate the usefulness of the established genetic models, the data of resistance to race of Cyst Nematode (Heterodera glycines Ichinohe) in soybeans from a BIL population derived from Essex×ZDD2315 along with their P1 and P2 were analyzed. The results show that the four major genes genetic model is better than three major genes ge-netic model, which illustrate the actual use of these genetic models.