The overall objective of this thesis was to assess the loss of genetic diversity, estimate the adverse effects of increasing homozygosity on economically important traits and investigate at the genomic level the unique location causing the detrimental effects. To understand the pattern of genetic diversity losses, we investigated the rate of inbreeding (∆F), rate of coancestry (∆f) and effective population size (N_e) as important quantitative indicators of genetic diversity and evaluated the effect of the recent implementation of genomic selection on the loss of genetic diversity in Holstein and Jersey dairy cattle. The rate of inbreeding and coancestry were calculated using both the traditional pedigree method and genomic methods estimated from segment and marker-based approaches. The ∆F and ∆f per generation ranged from 0.62 to 1.16%. Therefore, the N_e ranged from 43 to 85 for the two breeds. This result suggests the need to implement measures and means for controlling the rate of inbreeding, which will help to manage and maintain farm animal genetic resources. Following the assessment of genetic diversity loss, the negative effects of the accumulation of inbreeding expected from the reducing N_e was investigated. More specifically, we investigated the effect of recent and ancient inbreeding on production and fertility traits in Holsteins. In general, negative effects of inbreeding were found on production and fertility traits with production traits having more significant negative effects. Interestingly, ancient inbreeding had no significant negative impact on traits analysed; however, recent inbreeding showed more adverse and significant impact on analysed traits. This result indicates that more attention should be focused on recent inbreeding. Furthermore, we sought to identify unique homozygous genomic regions (ROH) showing negative associations with production and fertility traits as well as investigating their effects. Unique ROH regions with unfavorable effects were identified for both production and fertility traits. These unique homozygous regions with negative effects on production and fertility traits were identified within and across multiple traits in almost all chromosomes. The identified harmful regions could be advantageously used in mate selection pipelines for minimizing their frequency in future generations.

This dissertation deals with the genetic and genomic analyses of fetal loss and stillbirth in dairy cattle. The first chapter focuses on the genetic analysis of fetal loss in dairy cattle. The genetic analysis was performed to unravel whether fetal loss is a heritable trait, and hence, whether it will respond to genetic selection, and to what extent current fertility traits, such as daughter pregnancy rate, heifer conception rate and cow conception rate currently included in national evaluations of US dairy cattle are associated with fetal loss. This study estimated that fetal loss is a heritable trait, and the magnitude of heritability estimates suggest an important scope for genetic selection. Additionally, fetal loss traits are weakly correlated with current fertility traits included in the national genetic evaluation and thus current selection and breeding efforts have little or no impact on reducing the incidences of fetal loss. The second chapter focuses on dissecting the genetic basis of fetal loss with an aim of finding and characterizing genomic regions, individual genes, and pathways responsible for the genetic variation of fetal loss trait in dairy cattle. Two complementary studies were performed, namely a whole-genome association study and a subsequent gene-set analysis. These studies identified genomic regions, and particularly individual genes and pathways responsible for pregnancy maintenance, placental development, and fetal growth. These findings contribute to a better, deeper understanding of the genetic architecture of fetal loss in dairy cattle and provide opportunities for improving pregnancy success in dairy cattle via marker-assisted selection. The third chapter aims to predict yet-to-be observed fetal loss phenotype in dairy cattle using dense SNP genotype information of cows, bulls, and embryo and considering the environmental effects, health history, and lactation performance. Phenotypic prediction of fetal loss was evaluated using alternative approaches, including kernel-based models in linear and threshold framework. These genomic prediction models could identify with reasonable accuracy the proportion of cows that had a high probability of maintaining a successful pregnancy or experience fetal loss to a given insemination. Overall, the implementation of these predictive tools will allow dairy farmers to make accurate genome-guided management decisions on reproductive management, mating, and culling. The fourth chapter deals with genetic evaluations of stillbirth for five US dairy breeds viz., Ayrshire, Guernsey, Milking Shorthorn, Brown Swiss, and Jersey. The fourth chapter has four primary tasks i) characterizing stillbirth data in terms of stillbirth rates and their distributions in five US dairy breeds ii) determining the extent to which stillbirth data were recorded in the national database iii) performing single-breed genetic evaluations using Sire-maternal grandsire model iv) determining the feasibility of routine genetic evaluations of stillbirth for these breeds, given the currently available stillbirth data. Our results based on available stillbirth data resources suggest that national genetic evaluations of stillbirth are feasible in Brown Swiss and Jersey. However, reliable genetic evaluations of stillbirth in Ayrshire, Guernsey, and Milking Shorthorn require further data reporting on stillbirth.

This dissertation investigated bull fertility in Brown Swiss cattle. Chapter One offers an overview and an outline for the contents of the dissertation. Chapter Two provides a literature review on topics such as the importance of reproduction performance in dairy cattle, the importance of dairy bull fertility, and different genetic analyses. Chapter Three focuses on the evaluation of dairy bull fertility using confirmed pregnancy records. The analysis included both factors related to the bull under evaluation and factors associated with the cow that receives the unit of semen. The results showed that there is a substantial variation in conception rate among bulls, and the prediction of service sire fertility is feasible. These findings represent the foundation for the development of novel tools that will allow the dairy industry to make enhanced management and selection decisions on Brown Swiss male fertility. Chapter Four focuses on understanding the genetic basis of male fertility in Italian Brown Swiss dairy cattle. The analyses included whole-genome scans and gene-set analyses to identify genomic regions, individual genes, and genetic mechanisms affecting Brown Swiss bull fertility. These analyses identified genomic regions, individual genes, and gene-set related to male fertility. Additionally, the results showed genomic regions with marked non-additive effects associated with bull fertility. This comprehensive study contributes to a better understanding of the genetic basis of male fertility in cattle. Chapter Five aims to assess the feasibility of predicting male fertility in Brown Swiss cattle using genomic data under different scenarios, including within-country, across-country, and incorporating markers with large effect. The analyses included the use of linear kernel-based regression models fitting all SNPs or incorporating markers with large effect, using five-fold cross-validation. The findings showed that the prediction of service sire fertility using genomic data achieves moderate to high accuracy and the inclusion of markers with large effect is a promising alternative to the standard approach. However, the use of an across-country reference population did not outperform the standard within-country approach. Genomic predictions of service sire fertility can help Brown Swiss breeders make accurate genome-guided selection and management decisions. Chapter Six evaluates the presence of homozygosity in Italian Brown Swiss dairy cattle and assesses its association with bull fertility. The findings showed that inbreeding and increased homozygosity have a negative impact on male fertility in Italian Brown Swiss cattle. The quantification of homozygosity can contribute to minimizing the inbreeding rate and avoid its negative effect on fitness-related traits, such as male fertility. Lastly, a final Chapter is provided with some concluding remarks.

Bovine Reproduction is a comprehensive, current reference providing information on all aspects of reproduction in the bull and cow. Offering fundamental knowledge on evaluating and restoring fertility in the bovine patient, the book also places information in the context of herd health where appropriate for a truly global view of bovine theriogenology. Printed in full color throughout, the book includes 83 chapters and more than 550 images, making it the most exhaustive reference available on this topic. Each section covers anatomy and physiology, breeding management, and reproductive surgery, as well as obstetrics and pregnancy wastage in the cow. Bovine Reproduction is a welcome resource for bovine practitioners, theriogenologists, and animal scientists, as well as veterinary students and residents with an interest in the cow.

There is substantial evidence that the genetic background of milk production traits changes during lactation. It is known that the genetic variances for several milk production traits change during lactation and genetic correlations between milk production traits at different lactation stages differ from unity. In addition, for the diacylglycerol O-acyltransferase 1 (DGAT1) K232A polymorphism it has been shown that its effects on milk production traits are not constant during lactation. However, most genome-wide association studies (GWAS) for milk production traits do not account for changes in genetic effects during lactation. Therefore, these GWAS might miss QTL whose effects change during lactation. The objective of this thesis was to scan the whole genome for QTL whose effects on milk production traits change during lactation. First, 4 different GWAS approaches were performed to detect QTL with changing effects on protein content during lactation including an alternative approach; GWAS for genotype by lactation stage interaction. Results showed that the GWAS for genotype by lactation stage interaction identified significant regions that were not detected in GWAS assuming constant SNP effects during lactation. The GWAS for genotype by lactation stage interaction were performed for 7 other milk production traits. In total 7 genomic regions whose effects change during lactation exhibited significant genotype by lactation stage interaction effects. Therefore, GWAS for genotype by lactation stage interaction offered new possibilities to unravel the changes in genetic background of milk production traits. Changes in genetic effects in early lactation might be related to negative energy balance. Effects of pregnancy might cause changes in late lactation. Possible effects of pregnancy were further investigated by studying genotype by pregnancy interaction. Interestingly, the effects of pregnancy on milk production traits differed for DGAT1 genotypes. Finally, GWAS for genotype by season interaction were performed and identified major interaction signals on chromosomes 3 and 14 (DGAT1).