Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.

中文翻译：

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奶牛选择的基因组分析、进展和未来展望：回顾

基因组学包含一套当前有价值的技术，在奶牛商业育种计划中作为选择工具实施。基于基因组育种值 (GEBV) 的生产和繁殖性状密集后代测试对于提高奶牛生产力至关重要。了解关键基因和单倍型，包括它们的调控机制，作为生产力性状的标记，可以改善当前和未来的奶牛选择策略。全基因组关联研究 (GWAS)，例如数量性状位点 (QTL)、单核苷酸多态性 (SNP) 或单步基因组最佳线性无偏预测 (ssGBLUP) 方法已被纳入全球乳品计划中，用于估计标记-辅助选择衍生效应。基于基因组预测准确性的遗传进展的增加也有助于了解奶牛后代的遗传效应。然而，近交系内的杂交严重增加了纯合性，并累积了近交的负面影响，例如繁殖性能下降。因此，基于乳制品生产系统的经验传统模型的不准确偏差估计面临着提供次优结果的风险增加，这些结果源于仅基于低遗传力表型性状选择高遗传价值候选者时的错误。由于遗传收益显着减少，这延长了世代间隔并增加了成本。基因组预测的显着进展增加了优秀候选者的准确选择。本综述的范围是总结和讨论用于奶牛选择的基因组工具的进展和挑战，以优化育种计划和控制近交抑制对生产力的负面影响，从而实现粮食生产效率的经济有效进步。特别关注潜在的基因组选择结果，以促进现代奶牛场的精准管理，包括对新型基因组编辑方法的概述作为对未来的展望。