Population level genome-wide association studies in dairy cattle

Abstract: In recent years, genome-wide association studies (GWAS) has become a dominant tool for detecting genetic architectures for complex traits. Thousands of associated genetic variants have been reported. However, the resolution of these studies was limited by the available marker density for the quantitative trait loci (QTL) region. Moreover, the X chromosome and non-additive genetic effects has often been excluded from GWAS, despite of their potentially important biological functions. In chapter 2, we carried out the fine-mapping of a previously reported QTL in Holstein cattle on Bos taurus autosome 18 (BTA18) for calving traits, using imputed high-density SNP chip (HD) genotypes followed by imputed whole-genome sequence (WGS) variants. Genes SIGLEC12, CD33 and CEACAM18 were proposed as candidate genes. In addition, pleiotropic effects of this QTL region were observed on direct calving traits and conformation traits. In chapter 3, we performed a GWAS for growth traits in Nordic Holstein, Jersey, and Red Dairy Cattle. First, GWAS was performed within breeds using WGS variants. Then a meta-analysis was performed to combine information across the three breeds. Several QTL were identified to have large effects on growth traits in Holstein and Red Dairy Cattle, but only one QTL located nearby gene CYP19A1 on chromosome 10 was shared between Holstein and Red Dairy Cattle. Meta-analysis of these three breeds enhanced the power to detect QTL. In chapter 4, we performed the imputation of markers on the X chromosome in Holstein cattle for non-genotyped animals and animals genotyped with low density (Illumina BovineLD) chips, using animals genotyped with medium density (Illumina BovineSNP50) chips. We found that the imputation accuracy of markers on the X chromosome was improved by treating the pseudoautosomal region as autosomal and by increasing the proportion of females in the reference group. In chapter 5, we aimed to detect dominance effects on female fertility traits in Danish Holstein cattle using Illumina BovineSNP50 data, and evaluate the power, precision, and type 1 error of detecting dominance effects through simulations. Four QTL were detected for IFL in heifers, while one QTL was detected for cows. All these five QTL were detected with significant additive and dominance effects. Simulations showed that the current sample size had limited power to detect dominance effects for female fertility in cattle.