PSIV-B-20 Genome-Wide Association Analyses Revealed Potential Molecular Mechanisms Affecting Milk Fever in Dairy Cattle

Abstract

Abstract Milk fever, or hypocalcemia, has a significant economic impact on the dairy industry and increases the risk of other costly disorders including ketosis and displaced abomasum. The objective of this study was to identify genetic variants, genes and molecular mechanisms causing genetic variation in the development of milk fever. A genomic based mixed linear animal model was fitted to include single nucleotide polymorphisms (SNPs), breed, and pen as fixed effects and implemented in GCTA software. A total of 436 Jersey and Holstein cows with varying milk fever history were genotyped for high density SNP chip (782,139 SNP). A total of 401 animals with 617,527 SNPs passed the quality control and were included in the association analyses. Two SNPs located on chromosome 1 were found significant at 5% genome-wide false discovery rate. The 100 most significant SNPs were mapped to corresponding genes using the Ensemble database. A total of 24 genes were found to overlap with the significant SNPs and analyzed using the in-silico functional analyses implemented in DAVID software. The genomic heritability estimated in this population was 0.11. The study identified potential biological pathways associated with milk fever including regulation of Ras and GTPase signal transduction, mammary gland development and ossification. The identified genomic regions and genes will be validated in a larger population. These results could enable us to develop genomic testing tools based on the identified genes to select for cows with low incidence of milk fever and provide insights on which animals within the herd will likely require dietary or management adjustments to prevent and treat milk fever.