Mota Rodrigo R, Tempelman Robert J, Lopes Paulo S, Aguilar Ignacio, Silva Fabyano F, Cardoso Fernando F
Department of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.
Department of Animal Science, Michigan State University, East Lansing, USA.
Genet Sel Evol. 2016 Jan 14;48:3. doi: 10.1186/s12711-015-0178-5.
The cattle tick is a parasite that adversely affects livestock performance in tropical areas. Although countries such as Australia and Brazil have developed genetic evaluations for tick resistance, these evaluations have not considered genotype by environment (GE) interactions. Genetic gains could be adversely affected, since breedstock comparisons are environmentally dependent on the presence of GE interactions, particularly if residual variability is also heterogeneous across environments. The objective of this study was to infer upon the existence of G*E interactions for tick resistance of cattle based on various models with different assumptions of genetic and residual variability.
Data were collected by the Delta G Connection Improvement program and included 10,673 records of tick counts on 4363 animals. Twelve models, including three traditional animal models (AM) and nine different hierarchical Bayesian reaction norm models (HBRNM), were investigated. One-step models that jointly estimate environmental covariates and reaction norms and two-step models based on previously estimated environmental covariates were used to infer upon G*E interactions. Model choice was based on the deviance criterion information.
The best-fitting model specified heterogeneous residual variances across 10 subclasses that were bounded by every decile of the contemporary group (CG) estimates of tick count effects. One-step models generally had the highest estimated genetic variances. Heritability estimates were normally higher for HBRNM than for AM. One-step models based on heterogeneous residual variances also usually led to higher heritability estimates. Estimates of repeatability varied along the environmental gradient (ranging from 0.18 to 0.45), which implies that the relative importance of additive and permanent environmental effects for tick resistance is influenced by the environment. Estimated genetic correlations decreased as the tick infestation level increased, with negative correlations between extreme environmental levels, i.e., between more favorable (low infestation) and harsh environments (high infestation).
HBRNM can be used to describe the presence of GE interactions for tick resistance in Hereford and Braford beef cattle. The preferred model for the genetic evaluation of this population for tick counts in Brazilian climates was a one-step model that considered heteroscedastic residual variance. Reaction norm models are a powerful tool to identify and quantify GE interactions and represent a promising alternative for genetic evaluation of tick resistance, since they are expected to lead to greater selection efficiency and genetic progress.
牛蜱是一种寄生虫，对热带地区的家畜生产性能有不利影响。尽管澳大利亚和巴西等国家已开展了蜱抗性的遗传评估，但这些评估未考虑基因型与环境（GE）的相互作用。由于种畜比较在环境上依赖于GE相互作用的存在，特别是如果不同环境下的剩余变异性也存在异质性，遗传进展可能会受到不利影响。本研究的目的是基于具有不同遗传和剩余变异性假设的各种模型，推断牛蜱抗性的G*E相互作用是否存在。
数据由Delta G Connection Improvement项目收集，包括4363头动物的10673条蜱计数记录。研究了12种模型，包括三种传统动物模型（AM）和九种不同的层次贝叶斯反应规范模型（HBRNM）。使用联合估计环境协变量和反应规范的一步模型以及基于先前估计的环境协变量的两步模型来推断G*E相互作用。模型选择基于偏差准则信息。
拟合效果最佳的模型指定了10个子类别的异质剩余方差，这些子类由当代组（CG）蜱计数效应的每个十分位数界定。一步模型通常具有最高的估计遗传方差。HBRNM的遗传力估计通常高于AM。基于异质剩余方差的一步模型通常也会导致更高的遗传力估计。重复性估计值沿环境梯度变化（范围从0.18到0.45），这意味着加性和永久环境效应对抗蜱抗性的相对重要性受环境影响。随着蜱感染水平的增加，估计的遗传相关性降低，极端环境水平之间存在负相关，即较有利（低感染）和恶劣环境（高感染）之间。
HBRNM可用于描述赫里福德和布拉德福德肉牛蜱抗性的GE相互作用的存在。在巴西气候条件下，针对该群体蜱计数进行遗传评估的首选模型是考虑异方差剩余方差的一步模型。反应规范模型是识别和量化GE相互作用的有力工具，是蜱抗性遗传评估的一种有前途的替代方法，因为它们有望带来更高的选择效率和遗传进展。
