College of Agriculture & Natural Resources

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The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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    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.
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    GWAS and fine-mapping of livability and six disease traits in Holstein cattle
    (Springer Nature, 2020-01-13) Freebern, Ellen; Santos, Daniel J. A.; Fang, Lingzhao; Jiang, Jicai; Parker Gaddis, Kristen L.; Liu, George E.; VanRaden, Paul M.; Maltecca, Christian; Cole, John B.; Ma, Li
    Health traits are of significant economic importance to the dairy industry due to their effects on milk production and associated treatment costs. Genome-wide association studies (GWAS) provide a means to identify associated genomic variants and thus reveal insights into the genetic architecture of complex traits and diseases. The objective of this study is to investigate the genetic basis of seven health traits in dairy cattle and to identify potential candidate genes associated with cattle health using GWAS, fine mapping, and analyses of multi-tissue transcriptome data.
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    Integrating RNA-Seq with GWAS reveals novel insights into the molecular mechanism underpinning ketosis in cattle
    (Springer Nature, 2020-07-17) Yan, Ze; Huang, Hetian; Freebern, Ellen; Santos, Daniel J. A.; Dai, Dongmei; Si, Jingfang; Ma, Chong; Cao, Jie; Guo, Gang; Liu, George E.; Ma, Li; Fang, Lingzhao; Zhang, Yi
    Ketosis is a common metabolic disease during the transition period in dairy cattle, resulting in long-term economic loss to the dairy industry worldwide. While genetic selection of resistance to ketosis has been adopted by many countries, the genetic and biological basis underlying ketosis is poorly understood. We collected a total of 24 blood samples from 12 Holstein cows, including 4 healthy and 8 ketosis-diagnosed ones, before (2 weeks) and after (5 days) calving, respectively. We then generated RNA-Sequencing (RNA-Seq) data and seven blood biochemical indicators (bio-indicators) from leukocytes and plasma in each of these samples, respectively. By employing a weighted gene co-expression network analysis (WGCNA), we detected that 4 out of 16 gene-modules, which were significantly engaged in lipid metabolism and immune responses, were transcriptionally (FDR < 0.05) correlated with postpartum ketosis and several bio-indicators (e.g., high-density lipoprotein and low-density lipoprotein). By conducting genome-wide association signal (GWAS) enrichment analysis among six common health traits (ketosis, mastitis, displaced abomasum, metritis, hypocalcemia and livability), we found that 4 out of 16 modules were genetically (FDR < 0.05) associated with ketosis, among which three were correlated with postpartum ketosis based on WGCNA. We further identified five candidate genes for ketosis, including GRINA, MAF1, MAFA, C14H8orf82 and RECQL4. Our phenome-wide association analysis (Phe-WAS) demonstrated that human orthologues of these candidate genes were also significantly associated with many metabolic, endocrine, and immune traits in humans. For instance, MAFA, which is involved in insulin secretion, glucose response, and transcriptional regulation, showed a significantly higher association with metabolic and endocrine traits compared to other types of traits in humans. In summary, our study provides novel insights into the molecular mechanism underlying ketosis in cattle, and highlights that an integrative analysis of omics data and cross-species mapping are promising for illustrating the genetic architecture underpinning complex traits.