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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Item Phenotypic and Genetic Analysis of Reasons for Disposal in Dairy Cattle(2024) Iqbal, Victoria Audrey; Ma, Li; Animal Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Reasons for disposal are defined as why a cow has left the herd during lactation and are documented as termination codes. Dairy cattle termination codes were collected by Dairy Records Processing Centers and stored in the National Cooperator Database maintained by the Council on Dairy Cattle Breeding for analysis. The list of possible termination codes is as follows: code 0 is cow lactation that ended typically without an abortion, code 1 is locomotion problems, code 2 is female transferred or sold, code 3 is low milk yield, code 4 is reproductive problems, code 5 is unspecified reasons, code 6 is death, code 7 is the presence of mastitis, code 8 is abortion, code 9 is udder problems, code A is an unfavorable phenotype, and lastly code B is undesirable temperament. Understanding termination codes is the key to understanding and improving farm management. Unfortunately, the secondary termination codes are not utilized, despite studies saying one reason is too limited. Heifer termination codes should be more utilized, and studies show that this could improve heifer management. The four processing centers' principal termination codes deviated a little from year to year, but processing center D had the most variation in principal termination codes. There were few records with termination codes 9, A, and B. There was low lameness found for Jersey cattle but more fluctuations for their termination codes 6, 7, and 8. Jersey's main reason for disposal was sold and low milk yield. As for Holstein, the main reasons for disposal were low milk production and death. Recommendations include removing termination code 5 (other reasons) and enforcing a secondary termination code for code 2 (sold). Also, including the percentage of animal records used in traits developed at the CDCB was recommended to encourage farmers to add more records to improve breeding selections. Overall, the top main reasons for disposal were low milk yield, death, and reproduction across breeds from 2011 to 2022. To determine whether health traits correlate to termination codes and how health traits change the probability of survival, a multinomial logistic regression was developed, where twelve health traits, breeds, and other factors were used as an independent variable for the termination code, the dependent variable. The output is a regression coefficient list that conveys the effect of each health trait for each termination code. The results show the apparent impacts of animal breeds on different termination codes, such as dairy crossbreeds negatively affecting termination due to reproductive advantages that follow the literature. Lastly, using termination codes as phenotype, this study focuses on developing a genome-wide association study (GWAS) using the Weighted single-step Genomic Best Linear unbiased prediction (WssGBLUP) model to find significant SNPs related to survival in Holstein cows. In summary, this study provided an understanding of reasons for disposal trends, modeled the reasons for disposal, determined the likelihood of termination post-incidence, and found the heritability and important SNPs of each termination code.Item Weighted Single-Step GWAS Identifies Genes Influencing Fillet Color in Rainbow Trout(MDPI, 2022-07-26) Ahmed, Ridwan O.; Ali, Ali; Al-Tobasei, Rafet; Leeds, Tim; Kenney, Brett; Salem, MohamedThe visual appearance of the fish fillet is a significant determinant of consumers’ purchase decisions. Depending on the rainbow trout diet, a uniform bright white or reddish/pink fillet color is desirable. Factors affecting fillet color are complex, ranging from the ability of live fish to accumulate carotenoids in the muscle to preharvest environmental conditions, early postmortem muscle metabolism, and storage conditions. Identifying genetic markers of fillet color is a desirable goal but a challenging task for the aquaculture industry. This study used weighted, single-step GWAS to explore the genetic basis of fillet color variation in rainbow trout. We identified several SNP windows explaining up to 3.5%, 2.5%, and 1.6% of the additive genetic variance for fillet redness, yellowness, and whiteness, respectively. SNPs are located within genes implicated in carotenoid metabolism (β,β-carotene 15,15′-dioxygenase, retinol dehydrogenase) and myoglobin homeostasis (ATP synthase subunit β, mitochondrial (ATP5F1B)). These genes are involved in processes that influence muscle pigmentation and postmortem flesh coloration. Other identified genes are involved in the maintenance of muscle structural integrity (kelch protein 41b (klh41b), collagen α-1(XXVIII) chain (COL28A1), and cathepsin K (CTSK)) and protection against lipid oxidation (peroxiredoxin, superoxide dismutase 2 (SOD2), sestrin-1, Ubiquitin carboxyl-terminal hydrolase-10 (USP10)). A-to-G single-nucleotide polymorphism in β,β-carotene 15,15′-dioxygenase, and USP10 result in isoleucine-to-valine and proline-to-leucine non-synonymous amino acid substitutions, respectively. Our observation confirms that fillet color is a complex trait regulated by many genes involved in carotenoid metabolism, myoglobin homeostasis, protection against lipid oxidation, and maintenance of muscle structural integrity. The significant SNPs identified in this study could be prioritized via genomic selection in breeding programs to improve fillet color in rainbow trout.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 Characterization of recombination features and the genetic basis in multiple cattle breeds(Springer Nature, 2018-04-27) Shen, Botong; Jiang, Jicai; Seroussi, Eyal; Liu, George E.; Ma, LiCrossover generated by meiotic recombination is a fundamental event that facilitates meiosis and sexual reproduction. Comparative studies have shown wide variation in recombination rate among species, but the characterization of recombination features between cattle breeds has not yet been performed. Cattle populations in North America count millions, and the dairy industry has genotyped millions of individuals with pedigree information that provide a unique opportunity to study breed-level variations in recombination. Based on large pedigrees of Jersey, Ayrshire and Brown Swiss cattle with genotype data, we identified over 3.4 million maternal and paternal crossover events from 161,309 three-generation families. We constructed six breed- and sex-specific genome-wide recombination maps using 58,982 autosomal SNPs for two sexes in the three dairy cattle breeds. A comparative analysis of the six recombination maps revealed similar global recombination patterns between cattle breeds but with significant differences between sexes. We confirmed that male recombination map is 10% longer than the female map in all three cattle breeds, consistent with previously reported results in Holstein cattle. When comparing recombination hotspot regions between cattle breeds, we found that 30% and 10% of the hotspots were shared between breeds in males and females, respectively, with each breed exhibiting some breed-specific hotspots. Finally, our multiple-breed GWAS found that SNPs in eight loci affected recombination rate and that the PRDM9 gene associated with hotspot usage in multiple cattle breeds, indicating a shared genetic basis for recombination across dairy cattle breeds. Collectively, our results generated breed- and sex-specific recombination maps for multiple cattle breeds, provided a comprehensive characterization and comparison of recombination patterns between breeds, and expanded our understanding of the breed-level variations in recombination features within an important livestock species.Item 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, LiHealth 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.Item Genome-wide identification of loci associated with growth in rainbow trout(Springer Nature, 2020-03-05) Ali, Ali; Al-Tobasei, Rafet; Lourenco, Daniela; Leeds, Tim; Kenney, Brett; Salem, MohamedGrowth is a major economic production trait in aquaculture. Improvements in growth performance will reduce time and cost for fish to reach market size. However, genes underlying growth have not been fully explored in rainbow trout. A previously developed 50 K gene-transcribed SNP chip, containing ~ 21 K SNPs showing allelic imbalances potentially associated with important aquaculture production traits including body weight, muscle yield, was used for genotyping a total of 789 fish with available phenotypic data for bodyweight gain. Genotyped fish were obtained from two consecutive generations produced in the NCCCWA growth-selection breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform a genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with bodyweight gain. Using genomic sliding windows of 50 adjacent SNPs, 247 SNPs associated with bodyweight gain were identified. SNP-harboring genes were involved in cell growth, cell proliferation, cell cycle, lipid metabolism, proteolytic activities, chromatin modification, and developmental processes. Chromosome 14 harbored the highest number of SNPs (n = 50). An SNP window explaining the highest additive genetic variance for bodyweight gain (~ 6.4%) included a nonsynonymous SNP in a gene encoding inositol polyphosphate 5-phosphatase OCRL-1. Additionally, based on a single-marker GWA analysis, 33 SNPs were identified in association with bodyweight gain. The highest SNP explaining variation in bodyweight gain was identified in a gene coding for thrombospondin-1 (THBS1) (R2 = 0.09). The majority of SNP-harboring genes, including OCRL-1 and THBS1, were involved in developmental processes. Our results suggest that development-related genes are important determinants for growth and could be prioritized and used for genomic selection in breeding programs.Item 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, YiKetosis 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.Item Genome-wide scan for common variants associated with intramuscular fat and moisture content in rainbow trout(Springer Nature, 2020-08-25) Ali, Ali; Al-Tobasei, Rafet; Lourenco, Daniela; Leeds, Tim; Kenney, Brett; Salem, MohamedGenetic improvement of fillet quality attributes is a priority of the aquaculture industry. Muscle composition impacts quality attributes such as flavor, appearance, texture, and juiciness. Fat and moisture make up about ~ 80% of the tissue weight. The genetic architecture underlying the fat and moisture content of the muscle is still to be fully explored in fish. A 50 K gene transcribed SNP chip was used for genotyping 789 fish with available phenotypic data for fat and moisture content. Genotyped fish were obtained from two consecutive generations produced in the National Center for Cool and Cold Water Aquaculture (NCCCWA) growth-selective breeding program. Estimates of SNP effects from weighted single-step GBLUP (WssGBLUP) were used to perform genome-wide association (GWA) analysis to identify quantitative trait loci (QTL) associated with the studied traits. Using genomic sliding windows of 50 adjacent SNPs, 137 and 178 SNPs were identified as associated with fat and moisture content, respectively. Chromosomes 19 and 29 harbored the highest number of SNPs explaining at least 2% of the genetic variation in fat and moisture content. A total of 61 common SNPs on chromosomes 19 and 29 affected the aforementioned traits; this association suggests common mechanisms underlying intramuscular fat and moisture content. Additionally, based on single-marker GWA analyses, 8 and 24 SNPs were identified in association with fat and moisture content, respectively. SNP-harboring genes were primarily involved in lipid metabolism, cytoskeleton remodeling, and protein turnover. This work provides putative SNP markers that could be prioritized and used for genomic selection in breeding programs.