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Genetic evaluation in the presence of uncertain additive relationships. I. Use of phenotypic information to ascertain paternity

机译:存在不确定的加性关系时的遗传评估。 I.利用表型信息确定亲子关系

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A simulation was carried out to investigate the implementation of a genetic evaluation when the additive relationship matrix is not completely known due to the presence of uncertain paternity in the pedigree. Data were simulated and analyzed using a linear mixed model that included a fixed contemporary group effect plus random additive and residual effects. For the univariate scenario, either 1 or 2 records of a single trait with heritabilities of 33, 50, and 67% were used to compute the probability of being the true sire (PTS) of each candidate sire for a given offspring. One record of 3 correlated traits was used to compute PTS in a 3-trait scenario. A Bayesian procedure via Markov Chain Monte Carlo was used to carry out the implementation, in which the PTS was computed without the need to invert the relationship matrix. The average probability of the true sire being identified as such (PSA), as well as the percentage difference (PD) between PSA and an equal prior probability assigned to each candidate sire, were computed for the single and 3-trait scenarios. Using 1 trait, PSA increased with an increase in heritability. When repeated records were considered, the PD was increased by 50 to 386% compared with using just 1 record per animal for the varying heritabilities and number of candidate sires, suggesting that phenotypic information was better able to discriminate among candidate sires when more than 1 record was used to determine PSA. Using 3 correlated traits increased PD by 77 to 98% when compared with using 1 record of a trait with 67% heritability. Similarly, the PD was increased by 105 to 1,021%, when compared with using 1 record of a trait with 33% heritability. These results indicate that the probability of identifying the true sire increased when 3 correlated traits were used to compute PSA. The correlations between true and predicted breeding values of 3 traits were increased by 6 to 7% for all animals and 64 to 89% for animals with unknown paternity in the pedigree when estimated probability of paternity was used as compared with equal prior probability assigned to each candidate sire. For traits such as birth weight and weaning weight, in which only 1 measurement is taken, the 3-trait scenario could result in more animals being assigned the true sire than if birth or weaning weight was used separately. Further research is needed to determine the performance of this methodology in field data as well as the potential implementation of this methodology in conjunction with molecular information.
机译:当由于谱系中不确定的父子关系而无法完全了解加性关系矩阵时,进行了模拟研究以调查遗传评估的实施。使用线性混合模型对数据进行仿真和分析,该模型包括固定的当代群体效应以及随机加性和残余效应。对于单变量方案,使用遗传性分别为33%,50%和67%的单个性状的1条或2条记录来计算成为给定后代的每个候选父亲的真实父亲(PTS)的概率。在3个性状场景中,使用3个相关性状的记录来计算PTS。使用通过马尔可夫链蒙特卡洛方法进行的贝叶斯过程来执行该实现,其中无需转换关系矩阵即可计算PTS。对于单性状和3性状场景,计算了被识别为真实父亲的平均概率(PSA),以及PSA与分配给每个候选父亲的相等先验概率之间的百分比差异(PD)。使用1个性状,PSA随着遗传力的增加而增加。当考虑重复记录时,相对于每只动物仅使用1条记录的遗传性和候选父亲数目的变化,PD增加了50%至386%,这表明当多于1条记录时,表型信息能够更好地区分候选父亲。用于确定PSA。与使用1条具有67%遗传力的性状记录相比,使用3个相关性状将PD升高77%至98%。同样,与使用1条记录的遗传性为33%的性状相比,PD升高了105%至1,021%。这些结果表明,当使用3个相关性状计算PSA时,识别真父本的可能性增加。当使用估计的亲子关系概率与分配给每个特征的相等先验概率相比时,所有动物的3个性状的真实和预测繁殖值之间的相关性在全系中增加了6%至7%,在父系未知的动物中增加了64%至89%候选父亲对于仅进行1次测量的出生体重和断奶体重等性状,与单独使用出生体重或断奶体重的动物相比,在3个性状的情况下,可以将更多的动物指定为真正的父亲。需要进一步研究以确定该方法在现场数据中的性能以及该方法与分子信息结合的潜在实施方式。

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