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评估泊松模型、概率单位模型和线性模型在科里代尔羊黑斑出现和数量的遗传分析中的应用。

Assessment of Poisson, probit and linear models for genetic analysis of presence and number of black spots in Corriedale sheep.

机构信息

Departamento de Producción Animal y Pasturas, Facultad de Agronomía, Universidad de la Republica, Montevideo, Uruguay.

出版信息

J Anim Breed Genet. 2011 Apr;128(2):105-13. doi: 10.1111/j.1439-0388.2010.00893.x. Epub 2010 Dec 22.

Abstract

Black skin spots are associated with pigmented fibres in wool, an important quality fault. Our objective was to assess alternative models for genetic analysis of presence (BINBS) and number (NUMBS) of black spots in Corriedale sheep. During 2002-08, 5624 records from 2839 animals in two flocks, aged 1 through 6 years, were taken at shearing. Four models were considered: linear and probit for BINBS and linear and Poisson for NUMBS. All models included flock-year and age as fixed effects and animal and permanent environmental as random effects. Models were fitted to the whole data set and were also compared based on their predictive ability in cross-validation. Estimates of heritability ranged from 0.154 to 0.230 for BINBS and 0.269 to 0.474 for NUMBS. For BINBS, the probit model fitted slightly better to the data than the linear model. Predictions of random effects from these models were highly correlated, and both models exhibited similar predictive ability. For NUMBS, the Poisson model, with a residual term to account for overdispersion, performed better than the linear model in goodness of fit and predictive ability. Predictions of random effects from the Poisson model were more strongly correlated with those from BINBS models than those from the linear model. Overall, the use of probit or linear models for BINBS and of a Poisson model with a residual for NUMBS seems a reasonable choice for genetic selection purposes in Corriedale sheep.

摘要

黑色皮肤斑点与羊毛中的有色纤维有关,是一个重要的质量缺陷。我们的目的是评估替代模型,用于对考力代羊的黑色斑点存在(BINBS)和数量(NUMBS)进行遗传分析。在 2002-08 年期间,在两个羊群中,从 2839 只羊的 5624 个记录中,在剪毛时采集了 1 至 6 岁的羊的数据。考虑了四种模型:线性和概率比模型用于 BINBS,线性和泊松模型用于 NUMBS。所有模型均包含羊群-年份和年龄作为固定效应,动物和永久环境作为随机效应。根据整个数据集拟合模型,并根据交叉验证中的预测能力进行比较。对于 BINBS,估计的遗传力范围为 0.154 至 0.230,对于 NUMBS,遗传力范围为 0.269 至 0.474。对于 BINBS,概率比模型比线性模型更适合数据。从这些模型中随机效应的预测值高度相关,并且两个模型都具有相似的预测能力。对于 NUMBS,具有剩余项以解释过分散的泊松模型,在拟合优度和预测能力方面均优于线性模型。泊松模型中随机效应的预测值与 BINBS 模型的预测值比线性模型的预测值更相关。总体而言,对于考力代羊的遗传选择目的,使用概率比或线性模型进行 BINBS,以及使用带有剩余项的泊松模型进行 NUMBS 似乎是合理的选择。

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