The aim of this thesis has been to identify genetic variants that increase the susceptibility for Systemic Lupus Erythematosus (SLE), an autoimmune disease caused by a complex interplay between various genetic and environmental factors. Five different candidate genes were selected through different strategies, and were analysed for association with SLE in an attempt to distinguish some of the underlying mechanisms of this disease. Two of these genes, PD-L1 and PD-L2, appeared not to contain any major risk factors for SLE in the analysed European and Latin American populations. In two other genes, CD24 and STAT4, there appeared to be population-specific effects. The A57V amino acid substitution in the CD24 gene, previously implicated with multiple sclerosis, was associated in a Spanish cohort, with a weak trend in German samples, and no association in Swedish. The previously reported and highly convincing association of the STAT4 transcription factor gene was confirmed in all our cohorts. Interestingly, the results indicate the presence of at least two independent risk variants: the first, represented by a previously reported SNP, was the strongest in individuals of Northern European ancestry, and the second was more pronounced in individuals from Southern Europe and Latin America. We also report the identification of a novel susceptibility gene. The BANK1 gene, encoding a scaffold protein involved in B-cell activation, contains functional variants affecting important domains, which are associated in all investigated cohorts from Europe and Latin America. These results confirm the existence of replicable associations between genetic variants and SLE, which are common and present in many populations. The results also illustrate a certain degree of heterogeneity, where some risk factors could have variable effect in different populations.

<p>The disease process giving rise to cancer involves the consecutive accumulation of genetic or genomic alterations impacting the normal regulation of cellular functions. In cases of hereditary cancers, this process may be stepwise, with a shared initiating lesion leading to common subsequent alterations. However, in many non-hereditary forms of cancer the initiating and subsequent alterations giving rise to the tumor can vary substantially from individual to individual, and multiple molecularly distinct subsets of the disease can exist within histopathologically similar tumors. This molecular heterogeneity between patients hinders the ability to identify which alterations are responsible for tumor development and subsequent maintenance, and confounds the ability to effectively treat patients as response to a particular therapeutic intervention may be highly dependent on the molecular composition of the disease.</p><p>To further our understanding of the molecular alterations associated with tumorigenesis, we analyzed aggressive brain cancer, glioblastoma (GBM), samples for which multiple types of genome-wide information was available. We utilized a series of in vitro or clinically derived gene expression signatures by comparing gene expression of samples based on whether a particular cellular signaling pathway was known to be active or inactive. Using these signatures for cellular signaling deregulation, we examined the association between various genomic alterations and the relative activity of each pathway, identifying alterations that were enriched within patients that harbored similar profiles of pathway activation. These analyses lead to the identification of numerous previously uncharacterized alterations in GBM, including the identification of a ubiquitin-like gene, UBL3, that was associated not only with pathway signaling, but was also associated with poor patient outcome, as well as response of GBM xenograft models to treatment with standard of care therapeutic agents.</p><p>Further, given that the challenges involved in analyzing clinical samples include development methods for timely analysis of genomic data, we have described a framework to utilize these genomic signatures in a prospective setting by incorporating a non-overlapping reference dataset of similar tumor samples. This methodology allows the examination of pathway signaling, as captured by the signature, to be run in real-time when only a single patient sample is analyzed, and has a high degree of fidelity to the results generated from retrospective analysis across multiple tumor types. Together these studies have provided a novel framework for identification of significant genomic alterations that impact pathway signaling, as well as moving providing the mechanisms to analyze genomic signatures in a robust manner that accounts for the challenges associated with the prospective clinical setting.</p> / Dissertation

Genome-wide association studies (GWAS) have greatly improved our understanding of the genetic basis of complex traits. However, there are two major limitations with GWAS. First, most common variants identified by GWAS individually or in combination explain only a small proportion of heritability. This raises the possibility that additional forms of genetic variation, such as rare variants, could contribute to the missing heritability. The second limitation is that GWAS typically cannot identify which genes are being affected by the associated variants. Examination of rare variants, especially those in coding regions of the genome, can help address these issues. Moreover, several studies have recently identified low-frequency variants at both known and novel loci associated with complex traits, suggesting that functionally significant rare variants exist in the human population.

One of the main biological goals of recent years is to determine the genes in the human genome that cause disease. Recent technological advances have realised genome-wide association studies, which have uncovered numerous genetic regions implicated with human diseases. The current approach to analysing data from these studies is based on testing association at single SNPs but this is widely accepted as underpowered to detect rare and poorly tagged variants. In this thesis we propose several novel approaches to analysing large-scale association data, which aim to improve upon the power offered by traditional approaches. We combine an established imputation framework with a sophisticated disease model that allows for multiple disease causing mutations at a single locus. To evaluate our methods, we have developed a fast and realistic method to simulate association data conditional on population genetic data. The simulation results show that our methods remain powerful even if the causal variant is not well tagged, there are haplotypic effects or there is allelic heterogeneity. Our methods are further validated by the analysis of the recent WTCCC genome-wide association data, where we have detected confirmed disease loci, known regions of allelic heterogeneity and new signals of association. One of our methods also has the facility to identify the high risk haplotype backgrounds that harbour the disease alleles, and therefore can be used for fine-mapping. We believe that the incorporation of our methods into future association studies will help progress the understanding genetic diseases.

This is a bachelor thesis on the subject of aesthetics in design in the realm of video game art. Our intention is to investigate if basic, geometrical shapes will highlight certain physical attributes or characteristics, triggered by the visual appearance of a designed product in what is essentially an aesthetic response. We test this subject in the realm of videogames, through our own design and production of 3D-models. A survey is then conducted with participants observing these models and answering questions relating to certain attributes that we intended for these models to display through their visual, aesthetic appearance. The survey shows that participant responses and general opinions regarding the design of these models were largely what we expected and set out to achieve. While we can not empirically verify these results as conclusive and the opinions and theories proposed in this thesis are largely dependent on context and personal experience, we believe an attention to aesthetics in design can effectively guide the aesthetic response an observer or user may experience with a product or artefact.

As genomic sequencing technologies continue to advance, researchers are furthering their understanding of the relationships between genetic variants and expressed traits (Hirschhorn and Daly, 2005). However, missing data can significantly limit the power of a genetic study. Here, the use of a regularized generalized linear model, denoted GLMNET is proposed to impute missing genotypes. The method aimed to address certain limitations of earlier regression approaches in regards to genotype imputation, particularly multicollinearity among predictors. The performance of GLMNET-based method is compared to the performance of the phase-based method fastPHASE. Two simulation settings were evaluated: a sparse-missing model, and a small-panel expan- sion model. The sparse-missing model simulated a scenario where SNPs were missing in a random fashion across the genome. In the small-panel expansion model, a set of test individuals that were only genotyped at a small subset of the SNPs of the large panel. Each imputation method was tested in the context of two data-sets: Canadian Holstein cattle data and human HapMap CEU data. Although the proposed method was able to perform with high accuracy (>90% in all simulations), fastPHASE per- formed with higher accuracy (>94%). However, the new method, which was coded in R, was able to impute genotypes with better time efficiency than fastPHASE and this could be further improved by optimizing in a compiled language.

The U.S. is the largest maize producer in the world with a production of 300 million tons in 2012. Approximately 86% of the maize production is focused on the Midwestern states. The rest of the production is focused in the Southern states, where Texas is the largest maize producer. Grain yield in Texas ranges from 18 tons/ha in the irrigated production zones to 3 tons/ha in the dryland production zones. As a result, grain yield has increased slowly because of the poor production in the non-irrigated acres. Methods to improve the grain yield in Texas is to breed for maize varieties adapted to Texas growing conditions, including mapping genes that can be incorporated into germplasm through marker assisted selection. This dissertation includes two separate projects that exploit historical data and maize diversity to increase grain yield in Texas. For the first project, a large dataset collected by Texas AgriLife program was analyzed to elucidate past trends and future hints on how to improve maize yield within Texas. This study confirmed previous reports that the rate of increase for grain yield in Texas is less than the rate observed in the Midwestern US. For the second project, a candidate gene and whole genome association mapping analysis was performed for drought and aflatoxin resistance in maize. In order to do so, maize inbred lines from a diversity panel were testcrossed to isogenic versions of Tx714. The hybrids were evaluated under irrigated and non-irrigated conditions. The irrigated trials were inoculated with Aspergillus flavus and the aflatoxin level was quantified. This study found that the gene ZmLOX4 was associated with days to silk, and the gene ZmLOX5 gene was associated with plant and ear height. In addition, this study identified 13 QTL variants for grain yield, plant height, days to anthesis and days to silk. Furthermore, this study shows that diverse maize inbred lines can make hybrids that out yield commercial hybrids under heat and drought stress. Therefore, there are useful genes present in these diverse lines that can be exploited in maize breeding programs

Equine protozoal myeloencephalitis (EPM) is a progressive neurological disease of horses caused by Sarcocystis neurona. Two projects were conducted to identify factors involved in the development of EPM. The first study explored a possible genetic susceptibility to EPM by attempting a genome-wide association study (GWAS) on formalin-fixed, paraffin-embedded (FFPE) tissue from 24 definitively-positive EPM horses. DNA extracted from tissues older than 14 months was inadequate for SNP analysis on the Illumina Equine SNP50 BeadChip probably due to degradation and formalin cross-linking. Results were inconclusive as analysis was not possible with the small sample set. The second study evaluated an artificial infection method in creating a reliable equine EPM model. Five horses were injected intravenously at 4 time points with autologous blood incubated with 1,000,000S. neurona merozoites. Challenged horses progressively developed mild to moderate clinical signs and had detectable S. neurona serum antibodies on day 42 post challenge. Horses appeared to have produced a Th1 immune response and cleared the infection by the conclusion of the study on day 89. No histopathological evidence of S. neurona infection was found within central nervous system tissue. This artificial infection method was not effective in replicating the severe clinical EPM seen in natural infections.

Cervical cancer is the forth most commonly diagnosed cancer among women worldwide. It is caused by persistent infection with an oncogenic type of Human Papillomavirus (HPV). The HPV is a necessary but not sufficient cause of cervical cancer. Environmental factors such as smoking, high parity and long-term use of oral contraceptives increases the risk of cervical cancer. Genetic factors also affect the risk of developing the disease. The aim of this thesis is to search for and evaluate genetic risk factors for cervical cancer using both a candidate gene approach and a genome-wide association study (GWAS). Paper I examined the association of genetic variation in three Fanconi Anemia (FA) genes (FANCA, FANCC and FANCL), involved in DNA repair, with cervical cancer susceptibility in the Swedish population. No association was observed. Paper II evaluated the association of genetic variation in the TMC6 and TMC8 genes with susceptibility to cervical cancer in the Swedish population and an association of two SNPs (rs2290907 and rs16970849) with cervical cancer was observed.  In paper III the first GWAS performed in cervical cancer was reported. Three independent loci in the major histocompatibility complex (MHC) region at 6p21.3 were found to affect the susceptibility to cervical cancer. Paper IV examined the sequence variation in the TMC6 and TMC8 region and its association with cervical cancer. A highly polymorphic 21 bp sequence was identified and found to be repeated 5 to 42 times in both cases and controls. Lack of this repeat was associated with increased risk of cervical cancer. An intronic SNP (rs2926778) located in between the TNRC6C and TMC6 genes was also found to be associated with cervical cancer. The thesis provides evidence for the importance of genes in the immune system for cervical cancer susceptibility. The genetic risk factors identified explain only a part of the genetic susceptibility, implying that other risk factors remains to be identified

Human autoimmune diseases are hallmarked by inappropriate loss-of-tolerance and self-attacking response of the immune system. Studies included in this thesis are focusing on the implication and functional impact of genetic factors in three autoimmune diseases rheumatoid arthritis (RA), asthma, and systemic lupus erythematosus (SLE). Using genetic association studies, we found in study I and II that sequence variants of the interferon regulatory factor 5 (IRF5) gene were associated with RA and asthma, and the associations were more pronounced in certain disease subtypes. Distinct association patterns or risk alleles of the IRF5 gene variants were revealed in different diseases, indicating that IRF5 contributes to disease manifestations in a dose-dependent manner. In study III, we found that seven out of eight genetic risk loci for SLE, which were originally identified in East Asian populations, also conferred disease risk with the same risk alleles and comparable magnitudes of effect sizes in Caucasians. Remarkable differences in risk allele frequencies were observed for all associated loci across ethnicities, which seems to be the major source of genetic heterogeneity for SLE. In study IV we explored an exhaustive spectrum of sequence variants in the genes inhibitor of kappa light polypeptide gene enhancer in B-cells kinase epsilon (IKBKE) and interferon induced with helicase C domain 1 (IFIH1) by gene resequencing, and identified nine variants in IKBKE and three variants in IFIH1 as genetic risk factors for SLE. One of the associated variants may influence splicing of IKBKE mRNA. In study V we provided genome-wide transcriptional regulatory profiles for IRF5 and signal transducer and activator of transcription 4 (STAT4) using chromatin immunoprecipitation-sequencing (ChIP-seq). The target genes of IRF5 and STAT4 were found to play active roles in pathways related with inflammatory response, and their expression patterns were characteristic for SLE patients. We also identified potential cooperative transcription factors for IRF5 and STAT4, and disease-associated sequence variants which may affect the regulatory function of IRF5 and STAT4. In conclusion, this thesis illuminates the contribution of several genetic risk factors to susceptibility of human autoimmune diseases, which facilitates our understanding of the genetic basis of their pathogenesis.