不同数据结构和动物模型对高山美利奴羊经济性状遗传参数估计的比较

Comparison of Different Data Structures and Animal Models for Genetic Parameter Estimation of Economic Traits of Alpine Merino Sheep

本试验旨在比较不同数据结构和单性状动物模型对高山美利奴羊(14月龄)重要数量性状遗传参数估计的影响,筛选出估计体重、产毛量、净毛率、净毛量、羊毛纤维直径、羊毛纤维直径变异系数和羊毛长度7个重要经济性状遗传参数的最适模型,准确估计遗传力并为下一步遗传评定奠定基础。使用R语言数据整理相关函数将涉及20720只14月龄高山美利奴羊数据按系谱完整度和数据量分为数据集1和数据集2。采用R语言ANOVA分析检验鉴定年份、出生类型(单胎或双胎)、群别、性别4个非遗传因素在两个数据集中的显著性,将极显著效应(P<0.01)放入动物模型中作为固定效应。将两个数据集和两个单性状动物模型组合得到4个模型,其中模型1、模型2分别使用数据集1、数据集2,随机效应为个体加性遗传效应、残差效应;模型3、模型4分别使用数据集1、数据集2,随机效应为个体加性遗传效应、个体永久环境效应和残差效应。用ASReml4软件实现方差组分估计。通过AIC准则、BIC准则评价各模型,用LRT检验比较各模型。最后,针对各性状选出最适模型进行遗传力估计。结果显示:①非遗传效应显著性检验得到鉴定年份和群别对数据集1和数据集2中所有性状均极显著(P<0.01),出生类型对体重和数据集1中产毛量极显著(P<0.01),性别仅对体重反应极显著(P<0.01)。②各模型估计的体重遗传力为0.1614~0.2392;产毛量遗传力为0.1958~0.3254;净毛率遗传力为0.4395~0.5539;净毛量遗传力为0.2003~0.2393;羊毛纤维直径遗传力为0.4024~0.5897;羊毛纤维直径变异系数遗传力为0.3174~0.6077;毛长遗传力为0.2960~0.3669。③似然比检验结果表明,模型1和模型3对所有性状差异均不显著(P>0.05);模型1和模型4对体重和毛长差异极显著(P<0.01);模型2和模型3对净毛量差异极显著(P<0.01),对其他性状差异不显著(P>0.05);模型2和模型4对所有性状差异不显著(P>0.05)。最终得到对净毛量最适模型为模型1,体重、产毛量、净毛率、羊毛纤维直径、羊毛纤维直径变异系数、毛长的最适模型为模型2。所有性状受个体永久环境影响均不显著(P>0.05)。基于最适模型估计高山美利奴羊(14月龄)体重、产毛量、净毛率、净毛量、羊毛纤维直径、羊毛纤维直径变异系数、毛长遗传力分别为0.2392、0.3254、0.4394、0.2893、0.4222、0.3175、0.3670。

This study was aimed to investigate the effects of different data structures and animal models on the estimation of genetic parameters of economic traits of Alpine Merino sheep(14 months),and select the best animal model.The best model was used to estimate the genetic parameters of weight,greasy fleece weight,clean fleece yield,clean fleece weight,average fiber diameter,coefficient of variation of fiber diameter and staple length,which could provide the theoretical basis for the breeding of Alpine Merino sheep.The data of 20720 sheep were divided into data set 1 and data set 2 according to the genealogical integrity and data amount using the correlation function of data sorting in R language.The significance of four non-genetic factors year of identification,birth type(single or twin),group and sex in two data sets were tested by ANOVA with R language.Extremely significant effect(P<0.01)was put into the animal model as fixed effect.Four models were obtained by combining two data sets and two single-trait animal models.Model 1 and model 2 used data set 1 and data set 2,respectively.The random effects were individual additive genetic effect and residual effect.Model 3 and model 4 used data set 1 and data set 2,respectively,and the random effects were individual additive genetic effect,individual permanent environmental effect and residual effect.Variance component estimation was implemented by ASReml4 software.The Akzo information criterion(AIC)and Bayesian information criterion(BIC)were used to evaluate each model,and Likelihood ratio test(LRT)was used to compare each model.Finally,the optimal model was selected to estimate the heritability.The results showed that,①Fixed effect significance test showed that all traits in data set 1 and data set 2 of identification year and gender were extremely significant(P<0.01),birth type was extremely significant for weight and greasy fleece weight in data set 1(P<0.01),and gender was only extremely significant for weight(P<0.01).②The direct heritabilities were 0.1614-0.2392,0.1958-0.3254,0.4395-0.5539,0.2003-0.2393,0.4024-0.5897,0.3174-0.6077,0.2960-0.3669 for weight(WT),greasy fleece weight(GFW),clean fleece yield(CFY),clean fleece weight(CFW),average fiber diameter(FD),coefficient of variation of fiber diameter(CVAFD)and staple length(SL),respectively.③Likelihood ratio test showed that there was no significant difference between model 1 and model 3 for all traits(P>0.05).Model 1 and model 4 showed significant differences in body weight and staple length(P<0.01).Model 2 and model 3 showed significant difference in clean fleece weight(P<0.01),but no significant difference in other traits(P>0.05).There was no significant difference between model 2 and model 4 for all traits(P>0.05).In conclusion,the optimal model of clean fleece weight was model 1,and the optimal model of WT,GFW,CFY,CFW,FD,CVAFD and SL was model 2.All traits were not significantly affected by individual permanent environment(P>0.05).Based on the optimal model,WT,GFW,CFY,CFW,FD,CVAFD and SL heritability of alpine merino sheep were estimated to be 0.2392,0.3254,0.4394,0.2893,0.4222,0.3175 and 0.3670,respectively.