Decades of work has led researchers to believe that risk for complex behavioral phenotypes, such as alcohol use disorders, is likely influenced by multiple genes of small effect acting in conjunction with each other and the environment. Currently, the field of psychiatric genetics is developing methodologies for the identification of genetic risk variants that predispose individuals to the development of complex behavioral disorders. Several challenges related to the complex and polygenic nature of these phenotypes, must be considered. This dissertation study attempts to address these important challenges in the context of alcohol use disorders and related phenotypes. A rich twin and family study literature has indicated that 40-70% of the variance in alcohol use disorders (AUDs) is influenced by genetics. Recent attempts to identify specific x genetic risk variants associated with AUDs have been met with limited success. Meanwhile, evidence of the moderating effects of the environment on AUDs has been mounting, providing a strong rationale for examining gene-environment interaction. In the following chapters several studies will be described that integrate established twin methodologies into gene identification projects in an effort to reduce heterogeneity (both phenotypic and genotypic), elucidate environmental constructs that moderate genetic influences, and to enhance statistical power to detect the subtle genetic influences on alcohol related phenotypes.

Background: Coronary heart disease (CHD) is one of the leading causes of death worldwide, and global mortality rates are expected to continue to rise over the coming decades. In Pakistan in particular, chronic diseases are responsible for 50% of the total disease burden. Circulating lipids are strongly and linearly associated with risk of CHD; however, despite considerable efforts to demonstrate causality, available evidence is conflicting and insufficient. Study of the underlying metabolic pathways implicated in the association between lipids and CHD would help to disentangle and elucidate these complex relationships. Objectives: The primary objectives of this dissertation were to (1) identify the genetic determinants of lipid metabolites and (2) advance understanding of the effect of perturbations in lipid metabolite levels on CHD and its risk factors. Methods: Direct infusion high-resolution mass spectrometry was performed on 5662 participants from the Pakistan Risk of Myocardial Infarction Study to obtain signals for 444 known lipid metabolites. Correlations and associations of the lipids with smoking, physical activity, circulating biomarkers, and other CHD risk factors were assessed. Genome-wide analyses were conducted to analyse the association of each lipid with over 6.7 million imputed single nucleotide polymorphisms. Functional annotation and Gaussian Graphical Modelling were used to link the variants associated with each lipid to the most likely mediating gene, discern the underlying metabolic pathways, and provide a visual representation of the genetic determinants of human metabolism. Mendelian randomisation was also implemented to examine the causal effect of lipids on risk of CHD. Results: The lipids were highly correlated with each other and with levels of major circulating lipids, and they exhibited significant associations with several CHD risk factors. There were 254 lipids that had significant associations with one or more genetic variants and 355 associations between lipids and variants, with a total of 89 sentinel variants from 23 independent loci. The analyses described in this dissertation resulted in the discovery of four novel loci, identified novel relationships between genetic variants and lipids, and revealed new biological insights into lipid metabolism. Conclusion: Analyses of lipid metabolites in large epidemiological studies can contribute to enhanced understanding of mechanisms for CHD development and identification of novel causal pathways and new therapeutic targets.

Doctor of Philosophy / Genetics Interdepartmental Program / Jesse A. Poland / A central question in modern biology is to understand the genotype-to-phenotype (G2P) link, that is, how the genetics of an organism results in specific characteristics. However, prediction of phenotypes from genotypes is a difficult problem due to the complex nature of genomes, the environment, and their interactions. While the recent advancements in genome sequencing technologies have provided almost unlimited access to high-density genetic markers, large-scale rapid and accurate phenotyping of complex plant traits remains a major bottleneck. Here, we demonstrate field-based complex trait assessment approaches using a commercially available light-weight Unmanned Aerial Systems (UAS). By deploying novel data acquisition and processing pipelines, we quantified lodging, ground cover, and crop growth rate of 1745 advanced spring wheat lines at multiple time-points over the course of three field seasons at three field sites in South Asia. High correlations of digital measures to visual estimates and superior broad-sense heritability demonstrate these approaches are amenable for reproducible assessment of complex plant traits in large breeding nurseries. Using these validated high-throughput measurements, we applied genome-wide association and prediction models to assess the underlying genetic architecture and genetic control. Our results suggest a diffuse genetic architecture for lodging and ground cover in wheat, but heritable genetic variation for prediction and selection in breeding programs. The logistic regression-derived parameters of dynamic plant height exhibited strong physiological linkages with several developmental and agronomic traits, suggesting the potential targets of selection and the associated tradeoffs. Taken together, our highly reproducible approaches provide a proof-of-concept application of UAS-based phenomics that is scalable to tens-of-thousands of plots in breeding and genetic studies as will be needed to understand the G2P and increase the rate of gain for complex traits in crop breeding.

Recently, the pace of growth in the amount of data sources within Life Sciences has increased exponentially until pose a difficult problem to efficiently manage their integration. The data avalanche we are experiencing may be significant for a turning point in science, with a change of orientation from proprietary to publicly available data and a concomitant acceptance of studies based on the latter. To investigate these issues, a Network of Excellence (EMBRACE) was launched with the aim to integrate the major databases and the most popular bioinformatics software tools. The focus of this thesis is therefore to approach the problem of seamlessly integrating varied data sources and/or distributed research tools. In paper I, we have developed a web service to facilitate allergenicity risk assessment, based on allergen descriptors, in order to characterize proteins with the potential for sensitization and cross-reactivity. In paper II, a web service was developed which uses a lightweight protocol to integrate human endogenous retrovirus (ERV) data within a public genome browser. This new data catalogue and many other publicly available sources were integrated and tested in a bioinformatics-rich client application. In paper III, GeneFinder, a distributed tool for genome-wide association studies, was developed and tested. Useful information based on a particular genomic region can be easily retrieved and assessed. Finally, in paper IV, we developed a prototype pipeline to mine the dog genome for endogenous retroviruses and displaying the transcriptional landscape of these retroviral integrations. Moreover, we further characterized a group that until this point was believed to be primate-specific. Our results also revealed that the dog has been very effective in protecting itself from such integrations. This work integrates different applications in the fields of protein allergology, biotechnology, genome association studies and endogenous retroviruses. / EMBRACE NoE EU FP6

Diseases that affect dairy cattle have serious economic and animal welfare implications. The inclusion of immune response (IR) traits in breeding indices has been suggested to improve inherent animal health, and decrease the use of antimicrobials. The objectives of this research were to (1) evaluate cell-mediated (CMIR) and antibody-mediated immune responses (AMIR) on 680 Holstein cows from 58 herds across Canada, (2) estimate genetic parameters of these traits (3) examine the associations with routinely evaluated traits as well as the incidence of mastitis, (4) evaluate the correlation of natural and specific antibody and (5) perform a genome-wide association study (GWAS) to determine genetic markers associated with high or low IR. In collaboration with the Canadian Bovine Mastitis Research Network cows were immunized with both a type 1 and type 2 test antigen to stimulate CMIR and AMIR, respectively. A cutaneous delayed-type hypersensitivity test to the type 1 test antigen was used as an indicator of CMIR, and serum antibody (IgG1 and IgG2) to the type 2 test antigen as an indicator of AMIR. IR phenotypes varied significantly by cow, herd and region in Canada. Heritability estimates were moderate, 0.19 for CMIR and 0.16-0.43 for AMIR depending on time in the immunization protocol and antibody isotype. Beneficial associations between AMIR and some reproductive traits were found. Using estimated breeding values, cows were classified as high, average or low responders. High AMIR cows had significantly lower incidence rates of clinical mastitis compared to average and low cows. No difference was found when cows were classified based on CMIR. Natural antibody was not genetically correlated with specific antibody nor was it associated with mastitis. The GWAS found 198 genetic markers significantly associated with AMIR, with the majority on chromosome 23 where the major histocompatability complex is located. Other significant genes involved in IR include those associated with the complement system, interleukin 17 and tumor necrosis factor. This research confirms the benefit of identifying high IR cows and gives a glimpse of current IR profiles in Canadian Holsteins. This was the first GWAS for IR traits in dairy cattle and suggests it may be possible to include IR traits in genomic selection indices. / This research was financed by grants to B.A. Mallard from National Sciences and Engineering Research Council of Canada, Alberta Milk, Dairy Farmers of New Brunswick, Nova Scotia, Ontario and Prince Edward Island, Novalait Inc., Dairy Farmers of Canada, DairyGen council of Canadian Dairy Network, Agriculture and Agri-Food Canada, Public Health Agency of Canada, Technology PEI Inc., Université de Montréal and University of Prince Edward Island through the Canadian Bovine Mastitis Research Network. Kathleen Adele Thompson Crispi was funded by the Dairy Farmers of Ontario Doctoral Research Assistantship.

Genome-wide association studies (GWAS)s provide an unbiased means of exploring the landscape of complex genetic disease. As such, these studies have identified genetic variants that are robustly associated with a multitude of conditions. I hypothesize that these genetic variants serve as excellent tools for evaluation of the genetic interface between epidemiologically related conditions. Herein, I test the association between SNPs associated with either (i) plasma lipids, (ii) rheumatoid arthritis (RA) or (iii) diabetes mellitus (DM) and late-onset Alzheimer’s disease (AD) to identify shared genetic variants. Regarding the most significantly AD-associated variants, I have also attempted to elucidate their molecular function. Only cholesterol-associated SNPs, as a group, are significantly associated with AD. This association remains after excluding APOE SNPs and suggests that peripheral and or central cholesterol metabolism contribute to AD risk. The general lack of association between RA-associated SNPs and AD is also significant in that these data challenge the hypothesis that genetic variants that increase risk of RA confer protection against AD. Functional studies of variants exhibiting novel associations with AD reveal that the lipid-associated SNP rs3846662 modulates HMGCR exon 13 splicing differentially in different cell types. Although less clear, trends were also observed between the RA-associated rs2837960 and the expression of several BACE2 isoforms, and between the DM-associated rs7804356 and expression of a rare SKAP2 isoform, respectively. In conclusion, the overlap of lipid-, RA- or DM-associated SNPs with AD is modest but in several instances significant. Continued analysis of the interface between GWAS of separate conditions will likely facilitate novel associations missed by conventional GWAS. Furthermore, the identification of functional variants associated with multiple conditions should provide insight into novel mechanisms of disease and may lead to the identification of new therapeutic targets in an era of personalized genomic medicine.

Cervical stenotic myelopathy (CSM) is an important musculoskeletal and neurologic disease of the horse. Clinical disease occurs due to malformations of the vertebrae in the neck causing stenosis of the cervical vertebral canal and subsequent spinal cord compression. The disease is multifactorial in nature, therefore a clearer understanding of the etiology and pathogenesis of CSM will allow for improved management and therapeutic practices. This thesis examines issues of equine CSM diagnosis, skeletal tissue pathology, and inherited genetic determinants utilizing advances in biomedical imaging technologies and equine genomics. Magnetic resonance imaging (MRI) data provided a more complete assessment of the cervical column through image acquisition in multiple planes. First, MRI was compared to standing cervical radiographs for detection of stenosis. Using canal area or the cord canal area ratio, MRI more accurately predicted sites of compression in CSM cases. Secondly, articular process skeletal pathology localized on MRI was found to be more frequent and severe in CSM horses compared to controls. In addition, lesions were generalized throughout the cervical column and not limited to the spinal cord compression sites. A subset of lesions identified on MRI was evaluated using micro-CT and histopathology. Osteochondrosis, osseous cyst-like structures, fibrous tissue replacement of bone, and osteosclerosis were observed. These lesions support likely developmental aberrations of vertebral bone and cartilage maturation with secondary biomechanical influences. Bone cyst-like structures are a novel finding in this disease. Finally, the long-standing question of the contribution of genetic determinants to CSM was investigated using a genome wide association study (GWAS). Multiple significant loci were identified supporting the influence of a complex genetic trait in clinical disease. A simple Mendelian trait controlled by one gene is unlikely given the detection of variants across multiple chromosomes. Major contributions from this research include documentation of articular process bone and cartilage pathology in horses with CSM, support for abnormal cervical vertebrae development being an important contributing factor in the etiology and/or pathogenesis of equine CSM, and evidence that multiple genetic loci contribute to the CSM disease phenotype.

No description available.

The release of the Illumina BovineSNP50 BeadChip in late 2007 has drawn attention from cattle breeders around the world to develop breeding programs that leverage association of these single nucleotide polymorphism (SNP) with economically important quantitative trait loci (QTL). In that context this project has come to study applications of the SNP panel in beef cattle. Analysis of linkage disequilibrium (LD) existing in Angus, Charolais, and crossbred animals revealed the pattern of LD within each breed group, as well as the persistence of LD phase between pairs of the breed groups. This is important for genomic selection where SNP are trained in one population and used to predict breeding value for animals in another population. Detection of chromosome regions potentially carrying QTL or causative mutations affecting the phenotypic variation in economically important traits was presented at individual SNP and haplotype levels. There were 269 SNP associated (P<0.001) with birth weight (BWT), weaning weight (WWT), average daily gain (ADG), dry matter intake (DMI), mid-test metabolic weight (MMWT), residual feed intake (RFI). They explained 1.64% - 8.06% of the phenotypic variation in these traits. There were 520 SNP associated (P<0.001) with carcass quality traits, namely hot carcass weight, back fat thickness, ribeye area, marbling scores, lean yield grade by Beef Improvement Federation, steak tenderness, and six rib dissection traits. These SNP explained 1.90 - 5.89% of the phenotypic variance of the traits. Many of the significant SNP were located on chromosome 6. Six haplotypes were found associated (P<0.05) with ADG, DMI, and RFI. In order for genomic selection to happen in beef cattle, higher density SNP panels should be made available at low genotyping cost. However, the cost of genotyping animals for high density SNP chip is still high, thus genotype imputation has come to practice. The last chapter of this thesis compared two approaches presently used in genotype imputation, investigated factors affecting imputation accuracy, as well as the impact of imputation accuracy on genomic estimated breeding value (GEBV). It proved that the highest possible accuracy of GEBV is attainable with sufficiently large groups of reference animals. / Ontario Ministry of Agriculture, Food and Rural Affairs. Ontario Cattlemen’s Association. Ontario Farm Innovation Program. Agriculture and Agri-Food Canada’s Growing Forward Program. Agriculture Adaptation Council. Ontario Research and Development Program. MITACS Accelerate. Beef Improvement Opportunities.

Hybrid male sterility (HMS) is typically the first mechanism fortifying reproductive isolation resulting from genomic incompatibilities. Three interspecies feline breeds derived from domestic cat crosses to wild cat species (Asian leopard cat and African serval) manifest HMS through several generations of backcrossing before eventually regaining fertility. This work utilized 199 hybrid individuals with varying fertilities in a genome wide association study (GWAS) comprising 63,000 genome wide SNPs. Leveraging these results with whole-testis transcriptome sequencing and quantitative real-time PCR data facilitated the comparison of transcripts in sterile and fertile hybrids. This dissertation describes four loci with highly significant and fifty with moderately significant association to sterility within each individual hybrid domestic breed and combinations of breeds. These associations help identify epistatic targets for hybrid incompatibility contributing to sterility. Comparative QTL mapping between pairs of species provides a framework to describe the accumulation of clade-specific reproductive isolating loci. Detailed exploration of gene misregulation between domestic and hybrid individuals, as well as between littermate hybrids of varying fertilities outlines a pattern of expression consistent with a meiotic sex-chromosome inactivation failure in early generations and apoptotic failure in later hybrid generations. Combining comparative genomic association and transcriptomic characterization among hybrid felids of varying divergence, new insight is gained into the mechanisms of mammalian reproductive isolation.