Genetic architecture refers to the number and locations of genes that affect a trait, as well as the magnitude and the relative contributions of their effects. A better understanding of the genetic architecture of complex traits and diseases will be beneficial for analyzing genetic contributions to disease risk and for estimating genetic values of agricultural importance. In particular, genetic and genomic selection in dairy cattle populations has been well established and exploited through genome-wide association studies, sequencing studies, and functional studies. The objective of this dissertation is to understand the genetic architecture of complex traits and apply the understanding to investigate the biological relationship between genetics and diseases in dairy cattle. First, we performed GWAS and fine-mapping analyses on livability and six health traits in Holstein-Friesian cattle. From our analyses, we reported significant associations and candidate genes relevant to cattle health. Second, we evaluated genome-wide diversity in cattle over a period of time by running GWAS and proposed a gene dropping simulation program. From this study, we identified candidate variants under selection that are associated with biological and economically important traits in cattle. Also, we demonstrated that gene dropping is an applicable method to investigate changes in the cattle genome over time. Third, we investigated the effect of maternal age and temperature on recombination rate in cattle. We provided novel results regarding the plasticity of meiotic recombination in cattle. Additionally, we found a positive correlation between environmental temperature at conception and recombination rate in Holstein-Friesian cows. Collectively, these studies advance our understanding of the genetic architecture and the biological relationship between complex traits and diseases in dairy cattle.