Animal & Avian Sciences Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2741
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Item The Genetic Architecture of Complex Traits and Diseases in Dairy Cattle(2022) Freebern, Ellen; Ma, Li; Animal Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Genetic architecture refers to the number and locations of genes that affect a trait, as well as the magnitude and the relative contributions of their effects. A better understanding of the genetic architecture of complex traits and diseases will be beneficial for analyzing genetic contributions to disease risk and for estimating genetic values of agricultural importance. In particular, genetic and genomic selection in dairy cattle populations has been well established and exploited through genome-wide association studies, sequencing studies, and functional studies. The objective of this dissertation is to understand the genetic architecture of complex traits and apply the understanding to investigate the biological relationship between genetics and diseases in dairy cattle. First, we performed GWAS and fine-mapping analyses on livability and six health traits in Holstein-Friesian cattle. From our analyses, we reported significant associations and candidate genes relevant to cattle health. Second, we evaluated genome-wide diversity in cattle over a period of time by running GWAS and proposed a gene dropping simulation program. From this study, we identified candidate variants under selection that are associated with biological and economically important traits in cattle. Also, we demonstrated that gene dropping is an applicable method to investigate changes in the cattle genome over time. Third, we investigated the effect of maternal age and temperature on recombination rate in cattle. We provided novel results regarding the plasticity of meiotic recombination in cattle. Additionally, we found a positive correlation between environmental temperature at conception and recombination rate in Holstein-Friesian cows. Collectively, these studies advance our understanding of the genetic architecture and the biological relationship between complex traits and diseases in dairy cattle.Item ESTIMATION OF DRY MATTER INTAKE AND IDENTIFICATION OF DIETARY AND PRODUCTION PARAMETERS THAT INFLUENCE FEED EFFICIENCY OF INDIVIDUAL DAIRY COWS(2019) Iwaniuk, Marie Elizabeth; Erdman, Richard A.; Animal Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The objectives of this dissertation were to: 1) develop and validate equations used to estimate individual cow dry matter intake (DMI; kg/d) based on a nitrogen (N) balance approach, 2) determine the discriminatory power of several biological, production, and dietary variables on dairy feed efficiency (FE) as defined as energy-corrected milk (ECM; kg/d) per unit of DMI, 3) repeat the second objective using residual feed intake (RFI) to indicate FE status, and 4) determine if RFI values are dependent on the equation utilized to estimate DMI. Results from the first experiment (Chapter 3) indicated that DMI could be successfully estimated on an individual cow basis using the following commonly measured parameters: milk yield, milk protein concentration, body weight (BW; kg), and dietary N concentration. These inputs are relatively simple to measure; therefore, this equation may be used in the dairy industry as a practical method to estimate individual cow DMI when cows are fed in a group setting. The results of the second experiment (Chapter 4) suggested that days in milk (DIM), milk fat yield (g/d), and BW had the most discriminatory power (89% success rate) to discriminate between cows based on their FE status when FE was defined as ECM per unit of DMI. Therefore, dairy producers can use these 3 variables to select for cows with high FE without requiring the measurement of DMI which can be costly and difficult to obtain. Observations from the third experiment (Chapter 5) suggested that RFI is indicative of differences in metabolic efficiency between cows independent of most biological, production, and dietary variables, except DIM. These results are consistent with other studies that have suggested that RFI is indicative of true differences in metabolic efficiency between cows regardless of production parameters. Lastly, the results of the fourth experiment (Chapter 6) suggest that RFI values generated from different DMI equations are strongly correlated such that RFI values are independent of the DMI equation utilized in the calculation. Thus, dairy producers can select the equation to estimate DMI that is most suitable for their operation without causing an “equation bias” on the RFI calculation.Item Genetic Architecture of Complex Traits and Accuracy of Genomic Selection in Dairy Cattle(2018) Jiang, Jicai; Ma, Li; Animal Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Genomic selection has emerged as an effective approach in dairy cattle breeding, in which the key is prediction of genetic merit using dense SNP genotypes, i.e., genomic prediction. To improve the accuracy of genomic prediction, we need better understanding of the genetic architecture of complex traits and more sophisticated statistical modeling. In this dissertation, I developed several computing tools and performed a series of studies to investigate the genetic architecture of complex traits in dairy cattle and to improve genomic prediction models. First, we dissected additive, dominance, and imprinting effects for production, reproduction and health traits in dairy cattle. We found that non-additive effects contributed a non-negligible amount (more for reproduction traits) to the total genetic variance of complex traits in cattle. We also identified a dominant quantitative trait locus (QTL) for milk yield, revealing that detection of QTLs with non-additive effect is possible in genome-wide association studies (GWAS) using a large dataset. Second, we developed a powerful Bayesian method and a fast software tool (BFMAP) for SNP-set association and fine-mapping. We demonstrated that BFMAP achieves a power similar to or higher than existing software tools but is at least a few times faster for association tests. We also showed that BFMAP performs well for fine-mapping and can efficiently integrate fine-mapping with functional enrichment analysis. Third, we performed large-scale GWAS and fine-mapped 35 production, reproduction, and body conformation traits to single-gene resolution. We identified many novel association signals and many promising candidate genes. We also characterized causal effect enrichment patterns for a few functional annotations in dairy cattle genome and showed that our fine-mapping result can be readily used for future functional studies. Fourth, we developed an efficient Bayesian method and a fast computing tool (SSGP) for using functional annotations in genomic prediction. We demonstrated that the method and software have great potential to increase accuracy in genomic prediction and the capability to handle very large data. Collectively, these studies advance our understanding of the genetic architecture of complex traits in dairy cattle and provide fast computing tools for analyzing complex traits and improving genomic prediction.Item ROLE OF MATERNAL AND CYTOPLASMIC EFFECTS IN EARLY CALF GROWTH IN A CLOSED BREEDING NUCLEUS ANGUS HERD(2011) Carrillo, José Adrián; Siewerdt, Frank; Animal Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Maternal and cytoplasmic inheritance was investigated in a closed Angus herd. Observed traits were birth weight, weaning weight, adjusted body weight, average daily gain, hock length and scrotal circumference. Each animal in the herd was traced to one of 18 female founders. Data was analyzed with a model including contemporary group, gender and the random effects of animal, maternal, permanent environment, and cytoplasmic line. Ratios of cytoplasmic to phenotypic variances ranged from 0.000 ± 0.002 to 0.005 ± 0.006. Genetic maternal variances had ratios ranging from 0.044 ± 0.046 to 0.156 ± 0.029. Desired genetic gains indexes were computed for all traits. Inclusion of the cytoplasmic information in the index resulted in small reductions in genetic gains in direct and maternal values that can be compensated for a corresponding increase in cytoplasmic breeding value. Selection for cytoplasmic effects will lead to increased inbreeding unless new variation is created by mutations.