Developing Novel Genomic Tools for Reducing Fetal Loss and Stillbirth in Dairy Cattle PDF Download

Author: Anil Sigdel
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Languages : en
Pages : 0

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Book Description
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.