Browsing by Subject "GWAS"
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Item Characterization of equine metabolic syndrome and mapping of candidate genetic loci(2016-01) Schultz, NicholEquine metabolic syndrome (EMS) is a clustering of clinical signs associated with increased risk of laminitis, a potentially life-threatening condition of the foot. Similar to human metabolic syndrome (MetS), generalized and/or regional adiposity, hyperinsulinemia, insulin resistance and dyslipidemia, are reported components of EMS. However, there is ongoing debate regarding the definition of EMS, its etiology and pathogenesis, and the mechanisms linking EMS to its secondary consequences. Conflicting reports regarding EMS reflect the limitations of prior EMS studies, and that EMS is likely a complex, multifactorial condition similar to MetS. The primary objectives of this thesis were to characterize metabolic variation and EMS across horse and pony breeds and to identify candidate genes for EMS risk. Chapter 2 details the largest-ever epidemiological investigation of EMS in which 11 metabolic traits were measured in >600 horses and ponies from 166 farms. The use of multivariate, multilevel regression modeling allowed, for the first time, quantification of the relative importance of environmental (farm, dietary composition, exercise, etc.) and individual (age, breed, sex etc.) factors on these metabolic traits, while accounting for the often strong correlation between the trait measures. Age, sex, breed, obesity, prior laminitis status, and time of year were all strongly associated with one or more metabolic traits. Despite strong associations, these factors only explained 9.6% to 36.3% of the variation across these 11 traits, thus the majority of the variability in these measures remained unexplained. Unexplained variation at the farm level after accounting for diet, exercise, and sampling time of year, suggests that additional unmeasured environmental factors explain the similarity in metabolic measures between horses sampled from the same farm. Similarly, unexplained variation at the individual level suggests that unmeasured individual characteristics, for example genetics, are responsible for a large proportion of individual trait variation. Differences in the incretin response may also contribute to individual trait variation. The incretin response, defined as the difference in insulinemic responses between an oral and intravenous glucose challenge, is controlled by intestinal secretion of peptides, such as GLP-1, that stimulate pancreatic insulin secretion. While the incretin response has been hypothesized to play a role in the EMS pathogenesis, this hypothesis has not been adequately tested. In Chapter 3, the glycemic, insulinemic, and total and active GLP-1 responses to an oral sugar challenge, and the activity of DPP4, the major protease that breaks down GLP-1, were characterized. The use of a longitudinal analysis, rather than the traditional area under the curve analysis, allowed for more power to detect differences in these responses, including variation due to breed, obesity, and prior laminitis status. Unexplained individual level variation and breed differences in metabolic phenotypes support the hypothesis that there is an underlying genetic susceptibility to EMS. The final objective of this thesis was to identify candidate genes associated with EMS. MetS is a highly polygenic syndrome where numerous candidate genes have been identified. Whereas MetS associated variants are typically of small effect size; it was hypothesized that in EMS a small number of moderate to large effect loci contribute to variation in metabolic traits due to the fact that horse populations do not randomly mate and experience substantial selection pressure. 286 Morgan horses were genotyped on the Illumina SNP50 chip and imputed up to >800,000 SNPs to perform a genome wide association study (GWAS) to identify candidate genes for EMS. Additive genetic variance estimated from a genomic relationship matrix calculated from genotyped SNPs (“chip heritability”) indicated that the 11 measured metabolic traits were moderately heritable. Yet initial genome-wide scans using standard linear mixed models failed to detect significant associations. In Chapter 4, an improved linear mixed model for mapping polygenic traits in a population with familial relationships similar to that in many equine GWAS was developed and validated. The model incorporates a Bayesian variable selection method to rank SNPs and a stepwise feature selection process to determine the optimal SNPs to model the random polygenic effect, while including a random effect for each sampled herd or “familial cluster”. The method was validated using the QTL-MAS 2010 dataset, and Morgan horse and Welsh pony height datasets, and demonstrated increased power while controlling the false positive rate. Using this improved linear mixed model, 76 suggestive and 17 genome-wide significant candidate loci were identified for the 11 metabolic traits in the 286 Morgan horse cohort. Candidate genes had a substantial overlap with MetS candidate genes such as VEGFA, NRXN3, GRIK2, and TRIB2. Other interesting candidate genes included ISL, which encodes insulin enhancer protein that is thought to play an important role in regulating insulin gene expression; and AHR which encodes the aryl hydrocarbon receptor, a ligand activated transcription factor known to bind endocrine disrupting chemicals such as polycyclic aromatic hydrocarbons and dioxins. AHR is an interesting candidate gene given the potential role of endocrine disrupting chemical in the pathophysiology of MetS, and unexplained sources of farm level variation in Chapter 2. A unifying theme of Chapters 2-5 was the similarities between EMS and MetS, and the complex phenotypic and genetic architecture in both species. The use of advanced statistical modeling approaches allowed for a more complete understanding of the metabolic phenotypic variation in Chapters 2 and 3, and for the identification of many associated genetic loci in Chapter 5. The shared candidate genes for metabolic syndrome in humans and horses suggests similar underlying pathophysiological mechanisms and provides opportunity for exploring similar preventative and therapeutic management strategies.Item Characterization of Tissue-Specific Functional Networks and Genome-Wide Association Study Genes(2016-01) Kuriger-Laber, JacquelynPresent-day biological research has generated a vast body of data related to variation in the human genome, but in many cases the biological role of this variation is unknown or only partially understood. In order to integrate the diverse body of experimental genetic and genomic data, systems biologists pioneered computational approaches to infer functional networks. These networks provide a powerful platform to investigate genomic findings at a functional level. Recently, systems biologists designed a second generation of functional networks that reflect tissue-specificity in gene functional interactions. We examine both characteristics of these tissue-specific functional networks and the topology of genome-wide association study (GWAS) variant-related genes in these networks. We find significant variation in network quality and suggest metrics to identify well-performing networks. Finally, we show GWAS trait-associated genes have non-random topology in tissue-specific networks and that this must be taken into account when applying network-enabled methods to genomic data.Item Exploring Variation for Fusarium Head Blight Resistance and Deoxynivalenol Distribution in the Naked Barley Diversity Panel(2022-07) Hawkins, JohnHull-less or naked barley (Hordeum vulgare L.) is a grain of growing importance in food, feed, and malting applications. Fusarium Head Blight (FHB), a disease caused by fungi in the genus Fusarium, causes significant damage to barley grain through accumulation of mycotoxins and undesirable fungal proteins and reduction of grain mass and malting quality. The most important Fusarium mycotoxin in North America is deoxynivalenol (DON). Naked barley accumulates significant amounts of DON in hull tissue, which is discarded at threshing, providing a mechanism for limiting FHB discounts due to mycotoxin contamination. For this research, genome wide association studies were performed using the Naked Barley Diversity Panel genotyped with an array of 50,000 single nucleotide polymorphisms (SNPs) and phenotyped for traits associated with DON distribution in the barley spike. Three notable quantitative trait loci (QTLs) for disease related traits were discovered. A QTL on the short arm of chromosome 3H, linked to a hydroxyproline rich glycoprotein gene was associated with reduced FHB severity. Another QTL on the long arm of 3H, linked to sdw1, was associated with shorter plants, greater FHB severity under grain spawn inoculation, and earlier heading. A third QTL on the short arm of 2H, linked to PPD-H1, was associated with taller plants, later heading, and a greater proportion of the total DON being localized in the hull. Overall, there appears to be potential for the improvement of FHB resistance and DON mitigation in naked barley.Item From research findings to educational frameworks: breeding progress and genomic insights into intermediate wheatgrass at the University of Minnesota(2024) Stoll, HannahIntermediate wheatgrass (IWG, Thinopyrum intermedium (Host) Barkworth & D.R. Dewey) is a perennial grain crop that has been under development for inclusion in continuous living cover systems worldwide since the 1980s and specifically at the University of Minnesota (UMN) since 2011. IWG offers multiple ecosystem benefits as a perennial grain crop and has the potential to support rural economies by offering farmers a high-value alternative to the relatively few annual crop options that dominate markets and the landscape. However, improving grain traits, developing markets, and establishing optimal agronomic practices are essential for establishing and ensuring the long-term sustainability of IWG as a grain crop in the Midwest and beyond. This dissertation sheds light on the amount of breeding progress and underlying genomic regions for key IWG traits at UMN and uses this knowledge to make recommendations for future breeding efforts. Thus, 242 parent genets (genetically unique individuals) from UMN IWG breeding cycles 2, 3, 4, and 5 were evaluated in 2 locations (St. Paul and Lamberton, MN) in 2021 and 2022. Genets were genotyped and phenotyped for a variety of domestication and agronomic traits including shattering, brittle rachis, seed size, seed weight, spike characteristics, anthesis timing, and plant height. This dissertation demonstrates that the rate of genetic gain for several traits is significant and improving across breeding cycles; floret and average shattering decreased by ~5% each cycle, and seed area increased by 1% each cycle. Moreover, 33 quantitative trait loci (QTL) for these traits were identified in a Genome-Wide Association Study (GWAS), individually explaining 13% of phenotypic variation, on average. Some QTL appeared to be in close proximity to previously identified domestication – related genes from other studies, and favorable allele frequencies for some QTL appeared to increase across cycles. With these findings, we conclude that the rate of IWG breeding progress could be increased by improved phenotyping methods, incorporation of identified QTL in genomic selection procedures, and decreased time per breeding cycle. In addition to exploring IWG breeding progress at UMN, this dissertation explores the potential to disseminate scientific research into relevant science curriculum. Here, concepts such as the integration of quantitative skills and active learning into curriculum are explored, and a framework for developing and evaluating these curricula is proposed.Item Genetics of Fusarium head blight resistance in barley and of rust resistance in the wild wheat relative Aegilops longissima(2023-05) Page, RaeThe use of crop wild relatives, landraces, unadapted accessions, and/or diverse panels of germplasm for discovery and deployment of disease resistance genes and/or alleles is extremely valuable in breeding crop varieties to changing disease pressures. This thesis explores two diverse germplasm panels for disease resistance in distinct pathosystems: quantitative resistance to Fusarium head blight (FHB) in barley and qualitative resistance to rust pathogens in a wild wheat relative. Fusarium head blight (FHB), a devastating disease of barley caused primarily by the fungus Fusarium graminearum, causes significant yield losses and grain contamination with mycotoxins. Enhancing resistance to FHB and the resultant accumulation of mycotoxins, such as deoxynivalenol (DON), is one of the most effective and economical methods of reducing losses caused by this disease. A diverse panel of 234 barley accessions from world-wide origins was assembled to assess the most promising FHB resistant germplasm and perform a genome-wide association study (GWAS) for FHB/DON. Multiple FHB and DON quantitative trait loci (QTL) were detected, some independent of QTL influencing heading date and plant height. These significant marker-trait associations were used to generate multi-marker haplotypes. Haplotype-trait associations were tested to analyze their diversity and effects within the panel. The rust diseases are major limiting factors in worldwide wheat production. These diseases include leaf rust caused by Puccinia triticina (Pt), stem rust caused by P. graminis f. sp. tritici (Pgt), and stripe rust caused by P. striiformis f. sp. tritici (Pst). Aegilops longissima, a wild grass closely related to the D subgenome of modern bread wheat, has been shown to carry resistance to rust and other diseases, although it remains underutilized as a resource for discovery of novel rust resistance genes. A panel of 404 Ae. longissima accessions was evaluated for resistance to several races of Pt, Pgt, and Pst. GWAS was conducted to map rust resistance loci. Nine key candidate markers were identified as promising for further investigation due to their detection via multiple GWAS models and/or their association with resistance to more than one pathogen race. The novel resistance loci identified will provide additional diversity available for use in wheat breeding.Item Genetics, Sources, and Mapping of Stem Rust Resistance in Barley(2017-04) Case, AustinStem rust is a devastating disease of cereal crops worldwide. In barley (Hordeum vulgare), the disease is caused by two pathogens: Puccinia graminis f. sp. secalis (Pgs) and Puccinia graminis f. sp. tritici (Pgt). In North America, the stem rust resistance gene Rpg1 has protected barley from losses for more 60 years; however, widely virulent Pgt races from Africa in the Ug99 group threaten the crop. To identify novel quantitative trait loci (QTL) for stem rust resistance, bi-parental and association mapping studies were undertaken in the Barley iCore Collection (BCC) held by the USDA National Small Grains Collection. Association mapping studies of the BCC were conducted for seedling resistance to Pgt race TTKSK (Ug99 group) in the greenhouse and adult plant resistance (APR) to Pgt TTKSK composite in Njoro, Kenya and Pgt race QCCJB in St. Paul, MN. A major effect QTL (Rpg-qtl-5H-11_11355) for APR in all locations was identified on chromosome 5H. This QTL represents a unique locus for APR and has been confirmed in other studies. Subsequently, 290 of the most resistant BCC accessions, the BCC Selects (BCCS), were screened for resistance Pgt races MCCFC, QCCJB, HKHJC, TTKSK, TTKST, TKTTF, and TRTTF, and also Pgs isolate 92-MN-90. From this investigation, four BCCS accessions were postulated to carry Rpg1, 14 to carry Rpg2, 91 to carry Rpg3, four to carry rpg4/Rpg5, and 59 to carry potentially novel resistance genes. To map the APR genes of Rpg2 and Rpg3 in Hietpas-5 (CIho 7124) and GAW-79 (PI 382313), respectively, two biparental populations were developed with Hiproly (PI 60693), a stem rust susceptible accession. Both populations were phenotyped to the domestic Pgt races of MCCFC, QCCJB, and HKHJC in St. Paul and to Pgt TTKSK composite in Njoro. In the Heitpas-5/Hiproly population, a major effect QTL was identified on chromosome 2H, which is proposed as the location for Rpg2. In the GAW-79/Hiproly population, a major effect QTL was identified on chromosome 5H and is the proposed location for Rpg3. The resistance sources identified and characterized in this study enhance barley breeding programs focused on stem rust resistance.Item Identification of Quantitative Trait Loci for Resistance to White Mold in Soybeans via Genome-Wide Association and Linkage Mapping(2022-06) Mayta, JuanWhite mold disease in soybeans is one of the most important causes of yield losses in the northern regions of the United States and Canada. Host resistance continues to be the most viable tactic for managing white mold; however, progress is slow due to laborious phenotyping techniques that are difficult to replicate and the polygenic nature of the white mold resistance trait. Breeding for white mold resistance will be significantly facilitated by improved screening methods and the use of molecular markers. In this work, we developed and validated a phenotyping method using spray mycelium and inoculated sorghum in two field environments. Using this methodology, a collection of 230 F5:12 recombinant inbred lines derived from the Minsoy x Noir1 cross and 280 diverse PIs and cultivars were phenotyped for white mold resistance in two field environments. Additionally, both populations were phenotyped in the greenhouse using the cut stem method. Five breeding lines and one PI with resistance levels similar to the current resistant check S19-90 were identified. This material is adapted to the Upper Midwest and could be used as potential donor germplasm to improve resistance to white mold. Linkage mapping analysis was performed on the Minsoy x Noir1 population using a set of 957 SSR and SNP markers. Four markers showed significant associations with white mold resistance on Chromosomes 6, 7, 8, and 12 (LOD>3), explaining 45% of the variability. Marker Satt567 on chromosome 7 is a new white mold resistance QTL, explaining 17% of the variability. Genome-wide association (GWAS) was performed using 1,536 SNP markers. Five QTLs showed significant associations with white mold resistance (FDR, qvalue≤0.1). The identified QTLs correspond to two regions on chromosome 19 and one region on chromosome 14. Of particular interest is marker BARC-039375-07306 on the short arm of chromosome 19; this marker corresponds with a major QTL associated with canopy architecture in soybeans. A second region on chromosome 19 consists of three markers positioned between 47,988,748 and 48,229,536 bp. Among these three markers, BARC-007569-00135 was the most significant and consistent across environments. Phenotypic variation explained by all significant markers was 13%. The QTLs on chromosome 19 were identified in field experiments, whereas the QTL on chromosome 14 resulted from the greenhouse evaluation.Item Integrating summarized imaging and genomic data with GWAS for powerful endophenotype association testing in Alzheimer’s Disease(2021-06) Knutson, KatherineGenome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex traits. However, for most diseases, individual risk variants have small effects which impact disease indirectly through upstream endophenotypes. To improve on the power and interpretability of GWAS, a number of approaches have been developed which aggregate contributions from one or multiple genetic variants to investigate the role of genetically regulated endophenotypes in complex traits. These methods include Mendelian Randomization (MR) and the Transcriptome/Imaging Wide Association Study (TWAS/IWAS, which test for associated gene expression and imaging phenotypes, respectively). In this dissertation, I will compare the performance of these approaches for detecting brain imaging derived phenotypes (IDPs) associated with Alzheimer’s Disease. I will present novel extensions to the TWAS/IWAS framework to account for key biological factors which may impact their performance in practice, namely 1) genetic pleiotropy and 2) population substructure. The first of these factors, genetic pleiotropy, describes the phenomenon in which genetic loci affect multiple intermediate risk phenotypes. The presence of pervasive pleiotropy can result in inconsistent IWAS estimates. I will present a novel extension to the IWAS model (namely, MV-IWAS) which provides consistent causal estimates of endophenotype-trait associations by directly and indirectly accounting for pleiotropic pathways. The second of these factors, population substructure, describes ancestral variation in the underlying genetic architecture of endophenotypes. This variation can lead to ancestry-specific effects of gene expression in TWAS, which go undetected in the standard TWAS framework. Here, I will present a score test to detect heterogeneity in the effects of genetically-regulated gene expression which are correlated with ancestry. By jointly analyzing samples from multiple populations, our multi-ancestry TWAS framework can improve power for detecting genes with shared expression-trait associations across populations through increased sample sizes, as compared to existing stratified TWAS approaches.Item Mapping Quantitative Trait Loci and Assessing the Prospects of Genomic Prediction for Resistance to Goss’s Wilt of Maize(2017-07) Singh, AmritpalGoss’s wilt is a bacterial disease of maize caused by the Gram-positive bacterium Clavibacter michiganensis subsp. nebraskensis (Cmn). Goss’s wilt was discovered for the first time in South Central Nebraska in 1969. Following its discovery, the disease spread to the neighboring states over the next decade. Maize germplasm was screened for resistance to Goss’s wilt, and possibly due to the deployment of partially resistant hybrids, Goss’s wilt did not cause any significant damage during the 1980s and 1990s. However, Goss’s wilt re-emerged around 2006 and has been spreading to major maize growing areas in the United States and Canada. It is important to understand the genetic basis of resistance to Goss’s wilt to devise strategies for breeding resistance into maize hybrids. The main objectives of this dissertation were to (i) map quantitative trait loci (QTL) for resistance to Goss’s wilt using linkage mapping, joint linkage mapping, and genome-wide association mapping; (ii) identify differentially expressed genes in resistant and susceptible inbred lines in response to Cmn using RNA-seq; and (iii) to explore the prospects of genomic prediction of resistance to Goss’s wilt. Three bi-parental linkage mapping families including B73 x Oh43, B73 x HP301, and B73 x P39 that were evaluated for Goss’s wilt were used for joint linkage and linkage mapping. Eleven QTL were detected for resistance to Goss’s wilt on chromosomes 1, 2, 3, 4, 5, and 10 through joint linkage mapping. Linkage mapping in each of the three families identified nine, six, and four QTL in the families B73 × Oh43, B73 × HP301, and B73 × P39, respectively. Genome-wide association analysis conducted using a diversity panel of 555 maize inbred lines and 450 recombinant inbred lines (RILs) from three bi-parental mapping populations found three SNPs in the diversity panel and 10 SNPs in the combined dataset of diversity panel and RILs that were associated with Goss’s wilt resistance. Two modules of correlated genes were discovered that showed differential regulation in response to Cmn between resistant (N551) and susceptible (B14A) inbred lines using a weighted gene co-expression network analysis. Gene ontology analysis revealed that the genes inside one of the modules were enriched in defense related functions. Genomic prediction of Goss’s wilt resistance was conducted on the data obtained from bi-parental families and the diversity panel. Highest predictive ability of 0.56 and 0.64 was achieved in the diversity panel and B73 x Oh43 population respectively. Effect of training population size, composition, and adding diverse lines to training population on predictive ability was also assessed. Results indicated that predictive ability is not highly benefited when training population is designed by adding equal number of lines from each of the three families. Adding diverse lines to the training population lead to minor changes in predictive ability. Overall, the results improved our understanding of the genetic architecture of Goss’s wilt resistance and showed that the resistance to Goss’s wilt is a complex trait, controlled by small effect QTL.Item Pharmacogenomics of Chemotherapeutic Agents: Carboplatin and Paclitaxel(2017-05) MITRA GHOSH, TARASWIPlatinum drugs are currently used as standard-of-care chemotherapy, often in combination with taxanes, for various cancers including lung cancer- the most common malignancy, and ovarian cancer- the most lethal gynecological malignancy. However, the overall response rate of carboplatin/paclitaxel-based chemotherapy is far from desirable. Drug resistance, inter-patient variation in response and toxicity are major causes of concern. Genetic factors like differential expression and/or activity in key genes due to the presence of polymorphisms may have an impact on treatment outcome and toxicity. Our approach was to use immortalized lymphoblastoid cell lines/LCLs models derived from epithelial ovarian cancer/EOC patients to identify genetic factors associated with response to carboplatin/paclitaxel single-agent and combination treatments followed by the evaluation of these predictive pharmacogenomic markers in EOC and NSCLC patients undergoing Carboplatin/Paclitaxel combination chemotherapy. We performed a comprehensive profiling of in vitro chemo-sensitivity phenotypes in our panel of ~100 EOC-LCLs following treatment with carboplatin/paclitaxel as single agent and in combination. We demonstrated extensive inter-individual variation in drug response (drug-IC50 and area under survival curve/AUC)). Using Chou-Talalay’s Combination index/CI-Isobologram Theorem we observed wide inter-individual variation in CI and dose reduction index/DRI values. To understand the pharmacogenomics of the inter-individual variation in these chemo-sensitivity parameters, we performed identification of polymorphisms within the pharmacokinetic/PK and pharmacodynamic/PD pathway of carboplatin and paclitaxel as well as analysis of gene expression of these pathway genes in the EOC-LCLs followed by genotype-phenotype association study. Our analysis revealed significant association between drug chemo-sensitivity and genetic variations in several key pathway genes. We then conducted comprehensive genome-wide association scans/GWAS of germline genotype of these patient-derived LCLs to discover predictive pharmacogenomic markers of treatment response. Further, we performed a genotype-phenotype correlation analysis in NSCLC patients treated with carboplatin/paclitaxel-based combination chemotherapy to understand the impact of genetic variations within the PK/PD pathways. We found pathway SNPs associated with treatment outcomes/PFS and toxicity/multiple adverse effects following adjusting for clinical prognostic factors in multivariate models. Thus, we could successfully develop in vitro drug response models and identify key pharmacogenomic changes associated with drug response, treatment outcome and toxicity that could be directly correlated with patient clinical responses.Item Powerful Association Testing with Application to Neuroimaging Genetics(2017-05) Xu, ZhiyuanIn spite of the huge success of the standard single-nucleotide polymorphism (SNP) based analysis in genome-wide association studies (GWASs), it has some limitations. First, it suffers power loss from a stringent significance level due to multiplicity adjust- ment for up to millions of tests. In addition, it has low power since the effect sizes of SNPs are usually small. Instead, gene-based testing might improve statistical power by aggregating moderate to weakly associated SNPs within each gene while greatly re- ducing the burden of multiple testing adjustment from millions to thousands. Second, almost all existing analyses do not explicitly account for (unknown) genetic hetero- geneity, leading to possible loss of power as convincingly shown in simulation studies (Londono et al., 2012; Qian and Shao, 2013; Zhou and Pan, 2009). Moreover, as there are many other data resources available (e.g. neuroimaging phenotypes, molecular phenotypes like gene expression) besides GWAS/DNA sequencing data, integrating them into GWAS is expected to boost statistical power. We first introduce a flexible framework to extend score-based testing in generalized linear models to more complex models, for example, mixed effect models. Second, we show that by accounting for genetic heterogeneity, more associated SNPs can be detected than the standard one-degree-of-freedom trend test in single SNP-based testing. Third, we propose a new adaptive aSPC test to detect associations between two random vectors in moderate to high dimensions; we also point out its connections to some existing association testing for multiple SNPs and multiple traits. Finally, we propose a novel gene-based association testing approach by incorporating weights derived from other data resources (e.g. from another eQTL dataset). We show the power gain of the new approach over two existing methods PrediXcan and TWAS, pointing out that both PrediXcan and TWAS are special cases of our new test.Item QTL mapping and GWAS identify sources of iron deficiency chlorosis and canopy Wilt Tolerance in the Fiskeby III X Mandarin (Ottawa) soybean population(2015-01) Butenhoff, Karl JosephAbiotic stresses are a major yield limiting component in soybean production that producers cannot directly control. Therefore, an increase in the understanding of how different abiotic stresses affect soybean, and the identification of sources of tolerance to these stresses will be critical for the continued increase of soybean productivity well into the future. Here I present three separate, but related, studies analyzing iron deficiency chlorosis and drought tolerance in several soybean populations. For the first and second studies, the objectives were to (i) characterize the Fiskeby III X Mandarin (Ottawa) recombinant inbred line (RIL) population for its tolerance to iron deficiency chlorosis (IDC) and drought; (ii) identify quantitative trait loci (QTL) via composite interval mapping for iron deficiency chlorosis and canopy wilt in the RIL population; and (iii) identify co-localization of abiotic stress QTL and putative candidate genes for iron deficiency chlorosis tolerance and delayed canopy wilt. Iron chlorosis and canopy wilt scores were significantly different across the three years tested between the RILs as well as the parents of the population. Fiskeby III consistently scored better than Mandarin (Ottawa) for tolerance to iron chlorosis and canopy wilt in all three years. Two QTL were discovered, one on chromosome five and one on chromosome six, that together accounted for approximately 25 percent of the phenotypic variation for IDC. Two QTL were also identified for canopy wilt, one on chromosome six and one on chromosome 12, that together accounted for approximately 13 percent of the phenotypic variation. The two QTL identified on chromosome six co-localized to the same confidence interval. Several previously identified QTL co-localized with the identified IDC and canopy wilt QTL in this study. In addition, a potential candidate gene was identified on chromosome five that may play a role in the soybean IDC response. The third study was undertaken to potentially validate the QTL identified for IDC in the first study in two independent soybean populations. The objectives of this study were to (i) utilize association mapping to detect markers significantly associated with IDC in two independent populations, (ii) compare significant identified markers with the QTL regions identified in the bi-parental RIL population, and (iii) validate the major QTL identified on chromosome five in the RIL population. Association mapping identified 12 significant markers that accounted for 27.2 percent and 8.9 percent of the phenotypic variation for IDC in the two populations, respectively. These markers co-localized with several known iron related QTL and genes. A significant cluster of 11 markers on chromosome five co-localized with the major IDC QTL identified in the bi-parental Fiskeby III X Mandarin (Ottawa) population. A second potential candidate gene was identified in this QTL region that may be related to IDC in soybean.Item Unraveling the genetic determinants of virulence in Cryptococcus neoformans(2023-06) Jackson, KatrinaCryptococcus neoformans is a fungal pathogen that causes meningitis, primarily in patients who are immunocompromised. It is most common in populations with advanced HIV disease in low- and middle-income countries, especially in sub–Saharan Africa, South America, and southeast Asia. Even with improvements in treatments, the mortality rate remains unacceptably high. Mortality is associated with both host and pathogen specific factors, including C. neoformans genetic background. C. neoformans has three major lineages: VNI, VNII, and VNB. VNI and VNII are both clonal and globally distributed, with the vast majority of disease caused by VNI. VNB is highly diverse and regional; disease caused by VNB isolates tends to be associated with worse outcomes. Isolates are further divided into sequence types (STs), based on an accepted multi-locus sequence typing scheme. In the last decade, several studies have linked ST to patient outcome, with some STs found to be more virulent than others. When genetically matched mice were infected with patient isolates, mortality was significantly associated with patient mortality, showing that isolate genetic background is important for strain specific mortality. The reasons for the link between patient outcome and isolate genetic background remain unclear. This thesis aims to identify mutations and genes associated with changes in virulence in both patients and mice, understand the evolutionary patterns of virulence-related mutations, and explain the mouse immune response associated with a hypervirulent disease manifestation.