Understanding the genetic architecture of dairy cattle health using whole genome re-sequencing data

奶牛对某些健康问题的易感性，如乳腺炎（乳房组织的疼痛性炎症），约翰氏病（慢性，有时致命的肠道感染），代谢性疾病（皱胃移位，临床酮病，乳热等）和生育障碍（胎盘滞留、子宫炎、卵巢囊肿等）部分是遗传的在加拿大，这些健康问题在泌乳奶牛中的患病率很高：20-40%的奶牛患有一种或多种这些疾病。加拿大奶牛数量为100万头，全球奶牛数量为2.7亿头，健康性状的遗传改良可能会对大量动物产生积极影响。利用遗传改良来改善健康性状的优势是多方面的：奶牛受益于预期寿命/生活质量的提高;农民受益于牛奶产量的增加，兽医成本的降低和淘汰率的降低;消费者受益于高质量的牛奶产品;环境中抗生素的数量减少。尽管通过常规育种计划努力改善健康，但由于缺乏可靠的表型和对复杂性状背后的遗传结构的了解有限，进展受到限制。幸运的是，廉价基因组数据的使用正在为这一领域创造新的机会。动物育种者现在面临的主要挑战是缺乏准确的表型，缺乏有效的生物信息学工具和方法，以及缺乏能够处理这些大量数据的高素质人员。此外，虽然基因组学提供了一系列的好处，但该技术目前的缺点之一是在经历激烈选择的种群中近亲繁殖的水平增加。* 为了解决这些问题，需要对奶牛数量性状的遗传结构有新的见解。因此，我的长期目标是使用高密度基因组数据来获得对奶牛健康和健身性状遗传结构的基本见解，并培养有资格在这一领域工作的人员。这将通过以下方式完成：1）有效和准确地鉴定相关的遗传变异，2）开发统计方法和软件以从全基因组重测序数据计算基因组关系，3）进行全基因组关联研究以鉴定影响表型变异性的单个或多个变异或基因组区域，特别是健康性状，和4）创建一个工具，用于管理加拿大奶牛育种计划中增加的纯合性。通过将最新的基因组技术纳入育种策略的发展，我将为加拿大和全球乳制品系统培育健康，肥沃和高产的奶牛做出重大贡献。

Susceptibility of dairy cattle to certain health problems, such as mastitis (a painful inflammation of udder tissue), Johne's disease (chronic, sometimes fatal infection of the intestine), metabolic diseases (displaced abomasum, clinical ketosis, milk fever, etc.) and fertility disorders (retained placenta, metritis, cystic ovaries, etc.) is partially genetic in nature. In Canada, the prevalence of these health problems in lactating dairy cows is substantial: 20-40% have one or more of these disorders. With a Canadian dairy population of 1 million cows and a global dairy population of 270 million cows, genetic improvement of health traits could positively impact a huge number of animals. The advantages of using genetic improvement to improve health traits are manifold: cows benefit through increased life expectancy / quality of life; farmers benefit through increased milk production, reduced veterinary costs, and decreased culling rate; consumers benefit through high-quality milk products; and the amount of antibiotics in the environment is reduced.***Despite efforts to improve health through conventional breeding programmes, progress has been limited by the shortage of reliable phenotypes and a limited understanding of the genetic architecture underlying complex traits. Fortunately, the use of inexpensive genomic data is creating new opportunities in this field. The main challenges now facing animal breeders are the scarcity of accurate phenotypes, the lack of efficient bioinformatics tools and methodologies, and the shortage of highly qualified personnel capable of handling these massive amounts of data. Furthermore, although genomics provides an array of benefits, one of the technology's current drawbacks is an increased level of inbreeding in populations undergoing intense selection. ***To address these issues, novel insights into the genetic architecture underlying quantitative traits in dairy cattle are required. My long-term goal is thus to use high-density genomic data to gain fundamental insights into the genetic architecture of health and fitness traits in dairy cattle, and to train personnel qualified to work in this field. This will be done by 1) efficiently and accurately identifying relevant genetic variants, 2) developing statistical methodology and software to calculate genomic relationships from whole genome re-sequence data, 3) conducting genome-wide association studies to identify single or multiple variants or genomic regions influencing phenotype variability, specifically for health traits, and 4) creating a tool for the management of increasing homozygosity in Canadian dairy cattle breeding programs.***Through incorporation of the latest genomic technologies in the development of breeding strategies, I will make a substantial contribution to breeding healthy, fertile, and productive cows for both Canadian and global dairy systems.