Social genetic effects (SGE) are the effects of the genotype of one animal on the phenotypes of other animals within a social group. Because SGE contribute to variation in economically important traits for pigs, the inclusion of SGE in statistical models could increase responses to selection (RS) in breeding programs. In such models, increasing the relatedness of members within groups further increases RS when using pedigree-based relationships; however, this has not been demonstrated with genomic-based relationships or with a constraint on inbreeding. In this study, we compared the use of statistical models with and without SGE and compared groups composed at random versus groups composed of families in genomic selection breeding programs with a constraint on the rate of inbreeding. When SGE were of a moderate magnitude, inclusion of SGE in the statistical model substantially increased RS when SGE were considered for selection. However, when SGE were included in the model but not considered for selection, the increase in RS and in accuracy of predicted direct genetic effects (DGE) depended on the correlation between SGE and DGE. When SGE were of a low magnitude, inclusion of SGE in the model did not increase RS, probably because of the poor separation of effects and convergence issues of the algorithms. Compared to a random group composition design, groups composed of families led to higher RS. The difference in RS between the two group compositions was slightly reduced when using genomic-based compared to pedigree-based relationships. The use of a statistical model that includes SGE can substantially improve response to selection at a fixed rate of inbreeding, because it allows the heritable variation from SGE to be accounted for and capitalized on. Compared to having random groups, family groups result in greater response to selection in the presence of SGE but the advantage of using family groups decreases when genomic-based relationships are used.

中文翻译：

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统计模型和测试设计，可在受到社会遗传影响的猪的基因组育种计划中通过约束近交增加对选择的响应

社会遗传效应（SGE）是一种动物的基因型对一个社会群体中其他动物的表型的影响。由于SGE有助于猪的重要经济性状发生变化，因此在统计模型中包含SGE可能会增加育种程序中对选择（RS）的反应。在这样的模型中，当使用基于血统的关系时，增加组内成员的相关性会进一步增加RS。但是，这尚未通过基于基因组的关系或近亲繁殖的限制得到证明。在这项研究中，我们比较了在有和没有SGE的情况下使用统计模型的情况，并比较了在基因组选择育种计划中随机分组与家庭分组组成的群体对近交率的限制。当SGE处于中等水平时，当考虑选择SGE时，在统计模型中包含SGE会大大增加RS。但是，当将SGE包括在模型中但不考虑进行选择时，RS的增加和预测直接遗传效应（DGE）的准确性取决于SGE和DGE之间的相关性。当SGE的幅度较小时，在模型中包含SGE不会增加RS，这可能是由于效果的分离差以及算法的收敛问题。与随机组组成设计相比，由家庭组成的组导致较高的RS。与基于谱系的关系相比，使用基于基因组的关系时，两组成分之间的RS差异略有减少。使用包含SGE的统计模型可以以固定的近交率显着改善对选择的反应，因为它允许考虑和利用SGE的可遗传变异。与具有随机组相比，在使用SGE的情况下，家庭组对选择的反应更大，但是当使用基于基因组的关系时，使用家庭组的优势会降低。