301 Methods of genome-wide association studies and their applications in dairy cattle

Abstract

Abstract Genome-wide association studies (GWAS) has been widely used to map quantitative trait loci (QTL) of complex traits and diseases since 2007. To date, the human GWAS catalog has accumulated 4,410 publications and 172,351 associations, and the animal QTLdb has curated 983 publications and 130,407 QTLs for cattle, largest in livestock species. During the past 13 years of development, GWAS methods has evolved from simple linear regression, using principal components to address sample relatedness, mixed models, to Bayesian full model approaches. These methods have their advantages and limitations, so it is important to choose an appropriate method, especially for studies in livestock where sample size is often limited. Note that the most popular GWAS approach, the mixed model method, originated from animal breeding and genetics research. Leveraging the national cattle genomic database at the Council on Dairy Cattle Breeding (CDCB), we have conducted GWAS analyses of various dairy traits to identify QTLs and SNP markers of importance. Combining with sequence and functional annotation data, we seek to understand the genetic basis of complex traits and to reveal useful knowledge that can be incorporated into more accurate genomic predictions in the future.