【作者】 罗晶；

【导师】 杨润清；

【作者基本信息】 东北农业大学 ， 动物遗传育种， 2004， 硕士

【摘要】 本文采用Monte Carlo模拟方法分别地分析了各种因素对一对和多对（两对）普通数量性状和动态性状候选基因检测效率的影响：对于普通数量性状，采用回归分析法估计候选基因检测分析统计模型的参数；考虑了群体大小（个体数）、候选基因遗传贡献率和基因频率等3个因素。模拟试验结果表明：个体数对检测效率的影响不如遗传贡献率显著；检测高遗传贡献率的候选基因要比低遗传贡献率需要的群体要小；基因频率对候选基因的检测效率几乎没有影响。对于动态性状，将动态性状基因定位分析方法引入候选基因检测分析中，建立了动态性状候选基因遗传分析模型，采用迭代加权回归分析法估计模型参数；考虑了群体大小（个体数）、测定日频数、候选基因累计遗传贡献率和基因频率等4个因素。模拟试验结果表明：个体数对检测效率的影响不如累计遗传贡献率显著；个体数和测定日频数对动态性状候选基因检测分析具有几乎相同的作用，而且在相同样本含量条件下两者呈现互补的关系；高累计遗传贡献率的要比低累计遗传贡献率的候选基因在检测时需要较少的群体和测定日频数；基因频率对动态性状候选基因检测效率也几乎没有影响。不论是普通数量性状还是动态性状，不论是一个对候选基因还是多对（两对）候选基因，所考虑的因素对候选基因检测效率的影响都表现出两个共同的规律：（1）不同因素对候选基因检测效率的影响不尽相同；（2）各因素对候选基因检测效率的作用顺序为(累计)遗传贡献率>样本大小(个体数×测定日频数)> 基因频率。系统地分析影响数量性状候选基因检测效率的因素对候选基因的检测实践具有重要指导意义。更多还原

【Abstract】 The effects of different factors on detecting power of a pair of alleles and two pairs of candidate alleles for common and dynamic traits were investigated, respectively, by Monte Carlo simulation. The works and results included that:For common quantitative traits, the parameters in statistical models for detection of candidate alleles were estimated by using regression analysis methods; Three major factors, including number of individuals, genetic contribution ratio and candidate allele frequency, were considered. The result from simulations showed that effects of the individual numbers on detecting power were not so significant as genetic contribution ratio; The number of individuals needed for detecting candidate genes with high genetic contribution ratio were less than the low; There were almost not effect of gene frequency on detecting power of candidate genes.For dynamic traits, the statistical models for genetic analysis of candidate genes were established by applying the mathematical model for dynamic trait linkage mapping analysis into statistical analysis of their candidate genes; the parameters in the models were estimated by using iteratively weighted regression analysis methods. Four major factors, including number of individuals, test day frequency, accumulative genetic contribution ratio and gene frequency, were taken into account. The result from simulations indicated that effect of genetic contribution ratios on detecting power was significantly higher than individual numbers; the effect of individual number was almost same with test day frequency, and they showed the complementation with each other in same sample size. It would need less individual numbers and test-day records in the detection for dynamic trait candidate genes with higher accumulative genetic contribution ratio. Effect of gene frequency on detecting power of dynamic trait candidate genes was scarcely any as common quantitative trait.In summary, for both common quantitative trait and dynamic trait, the effects of considered factors on detecting power of a pair of alleles and two pairs of candidate alleles performed two common laws: (1) there were differences in the power of detecting candidate gene among the four affecting factors; (2) the order of effects of four factors on the power of detecting candidate gene was (accumulative) genetic contribution ratio >sample size (number of individuals times test day frequency)> gene frequency. Systemic analysis for the factors affecting detecting power of candidate genes will be helpful to guide the practices on detection of candidate genes. <WP=11>Master candidate：Luo JingSpecialty：Animal Genetics and Breeding Supervisor：Prof. Yang, Runqing更多还原