Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada, T6G 2P5.
Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada, T6G 2P5.
J Dairy Sci. 2019 Jul;102(7):5853-5870. doi: 10.3168/jds.2018-16126. Epub 2019 Apr 25.
Dairy cattle science has evolved greatly over the past century, contributing significantly to the improvement in milk production achieved today. However, a new approach is needed to meet the increasing demand for milk production and address the increased concerns about animal health and welfare. It is now easy to collect and access large and complex data sets consisting of molecular, physiological, and metabolic data as well as animal-level data (such as behavior). This provides new opportunities to better understand the mechanisms regulating cow performance. The recently proposed concept of feedomics could help achieve this goal by increasing our understanding of interactions between the different components or levels and their impact on animal production. Feedomics is an emerging field that integrates a range of omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics, and metatranscriptomics) to provide these insights. In this way, we can identify the best strategies to improve overall animal productivity, product quality, welfare, and health. This approach can help research communities elucidate the complex interactions among nutrition, environment, management, animal genetics, metabolism, physiology, and the symbiotic microbiota. In this review, we summarize the outcomes of the most recent research on omics in dairy cows and highlight how an integrated feedomics approach could be applied in the future to improve dairy cow production and health. Specifically, we focus on 2 topics: (1) improving milk yield and milk quality, and (2) understanding metabolic physiology in transition dairy cows, which are 2 important challenges faced by the dairy industry worldwide.
奶牛科学在过去一个世纪中取得了巨大的发展,为当今提高牛奶产量做出了重大贡献。然而,需要一种新的方法来满足对牛奶生产的不断增长的需求,并解决人们对动物健康和福利日益增加的担忧。现在,很容易收集和访问由分子、生理和代谢数据以及动物水平数据(如行为)组成的大型和复杂数据集。这为更好地了解调节奶牛性能的机制提供了新的机会。最近提出的饲料组学概念可以通过增加我们对不同成分或水平之间的相互作用及其对动物生产的影响的理解来帮助实现这一目标。饲料组学是一个新兴领域,它整合了一系列组学技术(例如基因组学、表观基因组学、转录组学、蛋白质组学、代谢组学、宏基因组学和宏转录组学)来提供这些见解。通过这种方式,我们可以确定提高动物整体生产力、产品质量、福利和健康的最佳策略。这种方法可以帮助研究界阐明营养、环境、管理、动物遗传学、代谢、生理学和共生微生物群之间的复杂相互作用。在这篇综述中,我们总结了最近在奶牛组学方面的研究成果,并强调了如何在未来应用综合饲料组学方法来改善奶牛生产和健康。具体来说,我们关注 2 个主题:(1)提高牛奶产量和牛奶质量,(2)了解处于过渡期的奶牛的代谢生理学,这是全球奶牛业面临的 2 个重要挑战。