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线性反应规范模型在基因型-环境互作下预测安格斯牛的遗传优势。

Linear reaction norm models for genetic merit prediction of Angus cattle under genotype by environment interaction.

机构信息

Embrapa Southern Region Animal Husbandry, Bagé, RS, Brazil 96401-970.

出版信息

J Anim Sci. 2012 Jul;90(7):2130-41. doi: 10.2527/jas.2011-4333. Epub 2012 Jan 13.

DOI:10.2527/jas.2011-4333
PMID:22247112
Abstract

The objectives of this work were to assess alternative linear reaction norm (RN) models for genetic evaluation of Angus cattle in Brazil. That is, we investigated the interaction between genotypes and continuous descriptors of the environmental variation to examine evidence of genotype by environment interaction (G×E) in post-weaning BW gain (PWG) and to compare the environmental sensitivity of national and imported Angus sires. Data were collected by the Brazilian Angus Improvement Program from 1974 to 2005 and consisted of 63,098 records and a pedigree file with 95,896 animals. Six models were implemented using Bayesian inference and compared using the Deviance Information Criterion (DIC). The simplest model was M(1), a traditional animal model, which showed the largest DIC and hence the poorest fit when compared with the 4 alternative RN specifications accounting for G×E. In M(2), a 2-step procedure was implemented using the contemporary group posterior means of M(1) as the environmental gradient, ranging from -92.6 to +265.5 kg. Moreover, the benefits of jointly estimating all parameters in a 1-step approach were demonstrated by M(3). Additionally, we extended M(3) to allow for residual heteroskedasticity using an exponential function (M(4)) and the best fitting (smallest DIC) environmental classification model (M(5)) specification. Finally, M(6) added just heteroskedastic residual variance to M(1). Heritabilities were less at harsh environments and increased with the improvement of production conditions for all RN models. Rank correlations among genetic merit predictions obtained by M(1) and by the best fitting RN models M(3) (homoskedastic) and M(5) (heteroskedastic) at different environmental levels ranged from 0.79 and 0.81, suggesting biological importance of G×E in Brazilian Angus PWG. These results suggest that selection progress could be optimized by adopting environment-specific genetic merit predictions. The PWG environmental sensitivity of imported North American origin bulls (0.046 ± 0.009) was significantly larger (P < 0.05) than that of local sires (0.012 ± 0.013). Moreover, PWG of progeny of imported sires exceeded that of native sires in medium and superior production levels. On the other hand, Angus cattle locally selected in Brazil tended to be more robust to environmental changes and hence be more suitable when production environments for potential progeny is uncertain.

摘要

本研究旨在评估用于巴西安格斯牛遗传评估的替代线性反应规范(RN)模型。具体来说,我们检验了基因型与环境变异的连续描述之间的相互作用,以检验断奶后体重增长(PWG)中的基因型与环境互作(G×E)的证据,并比较了国产和进口安格斯公牛的环境敏感性。该数据由巴西安格斯改良计划于 1974 年至 2005 年收集,包含 63098 条记录和一个包含 95896 只动物的系谱文件。使用贝叶斯推理实现了 6 种模型,并使用偏差信息准则(DIC)进行比较。最简单的模型是 M(1),即传统的动物模型,与考虑 G×E 的 4 种替代 RN 规格相比,M(1)的 DIC 最大,因此拟合效果最差。在 M(2)中,使用 M(1)的当代组后验均值作为环境梯度,实施了 2 步程序,范围为-92.6 至+265.5kg。此外,通过在 1 步方法中联合估计所有参数的 M(3),证明了这种方法的优越性。此外,我们使用指数函数(M(4))扩展了 M(3),以允许残差异方差,并使用最佳拟合(最小 DIC)环境分类模型(M(5))规范。最后,M(6)将异方差残差方差添加到 M(1)中。在所有 RN 模型中,遗传力在恶劣环境下较低,随着生产条件的改善而增加。在不同环境水平下,使用 M(1)和最佳拟合 RN 模型 M(3)(同方差)和 M(5)(异方差)获得的遗传优势预测值之间的秩相关系数范围为 0.79 至 0.81,表明巴西安格斯 PWG 中的 G×E 具有生物学意义。这些结果表明,通过采用特定于环境的遗传优势预测,可以优化选择进展。进口北美起源公牛的 PWG 环境敏感性(0.046±0.009)明显大于(P<0.05)本地公牛(0.012±0.013)。此外,进口公牛后代的 PWG 在中高水平生产中超过了本地公牛。另一方面,在巴西当地选择的安格斯牛对环境变化的适应性更强,因此当潜在后代的生产环境不确定时,它们更适合。

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