背景:通过环境相互作用(G×E)的基因型可以在牛种群中发挥重要作用,应包括在育种计划中,以便为不同的环境选择最佳的动物。
目的:本研究的目的是通过应用使用基因组学信息的反应规范模型来调查巴西和哥伦比亚的Gyr牛的牛奶产量的G×E,并确定与这两个国家牛奶生产相关的基因组区域。
方法:巴西和哥伦比亚的数据库包括464只动物(来自巴西的273头母牛和33头母牛,来自哥伦比亚的158头母牛)和27,505个SNP。作为原产国的函数,在巴西和哥伦比亚使用双性状动物模型将牛奶产量调整为305天,其中包括通过单步基因组反应范数模型获得的基因组信息。使用GIBBS3F90和POSTGSf90程序。
结果:根据巴西和哥伦比亚之间多头的重新排名,获得的结果表明G×E,展示了两国之间的环境差异。研究结果强调了在选择繁殖动物时考虑环境的重要性,以确保其后代的适当表现。在此背景下,在这两个国家中,公牛的重新排名以及与牛奶产量相关的不同SNP表明,G×E是一个重要的影响,应将其纳入巴西和哥伦比亚乳牛的遗传评估中。
结论:可以通过选择选择环境来优化Gyr育种计划,该环境将允许在国家内部和国家之间的不同环境中最大程度地提高牛奶生产的遗传进步。
BACKGROUND: Genotype by environment interactions (G × E) can play an important role in cattle populations and should be included in breeding programs in order to select the best animals for different environments.
OBJECTIVE: The aim of this study was to investigate the G × E for milk production of Gyr cattle in Brazil and Colombia by applying a reaction norm model used genomics information, and to identify genomic regions associated with milk production in the two countries.
METHODS: The Brazilian and Colombian database included 464 animals (273 cows and 33 sires from Brazil and 158 cows from Colombia) and 27,505 SNPs. A two-trait animal model was used for milk yield adjusted to 305 days in Brazil and Colombia as a function of country of origin, which included genomic information obtained with a single-step genomic reaction norm model. The GIBBS3F90 and POSTGSf90 programs were used.
RESULTS: The results obtained indicate G × E based on the reranking of bulls between Brazil and Colombia, demonstrating environmental differences between the two countries. The findings highlight the importance of considering the environment when choosing breeding animals in order to ensure the adequate performance of their progeny. Within this context, the reranking of bulls and the different SNPs associated with milk production in the two countries suggest that G × E is an important effect that should be included in the genetic evaluation of Dairy Gyr cattle in Brazil and Colombia.
CONCLUSIONS: The Gyr breeding program can be optimized by choosing a selection environment that will allow maximum genetic progress in milk production in different environments within and between countries.