Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle
Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle
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DOI：
10.1111/jbg.12036
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发表时间：
2013-12-01
影响因子：
2.6
通讯作者：
Albuquerque, L. G.
中科院分区：
文献类型：
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作者：
Ayres, D. R.;Pereira, R. J.;Albuquerque, L. G.
牛对蜱虫的抵抗力是通过感染动物的蜱虫数量来衡量的。用于牛抗蜱遗传分析的模型经常需要对观察结果进行对数转换。本研究的目的是评估不同模型的预测能力和拟合优度的分析这一性状的杂交赫里福德x内洛尔牛。测试了三种型号：使用观测值对数变换的线性模型（MPOI）;无观测值变换的线性模型（MLIN）;以及带残差项的广义线性泊松模型（MPOI）。所有模型均包括当代组和遗传组的分类效应、记录时的动物年龄和个体杂合性的协变量以及作为随机效应的加性遗传效应。MLIN、MPOI和MPOI模型的遗传力估计值分别为0.08 +/-0.02、0.10 +/- 0.02和0.14 +/- 0.04。通过方差信息准则（DIC）和残差均方检验模型的拟合质量，表明MPOI模型的拟合优越性。通过独立样本的验证性检验比较了模型的预测能力。MPOI模型在拟合优度和预测能力方面略上级，而所有模型的观察和预测蜱虫计数之间的相关性几乎相同。在模型MPEST和MPOI之间观察到育种值之间的较高等级相关性。Poisson模型可用于抗蜱动物的筛选。
Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 +/- 0.02, 0.10 +/- 0.02 and 0.14 +/- 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals.