Stroke is a common multi factorial cerebrovascular disorder with a large impact on global health. It is a disorder primarily associated with old age but environmental factors, lifestyle choices and medical history are all important for the risk of developing the disorder. It is also known that heritability is important for predisposition to the disorder. The aim of this work has been to identify genetic variations that increase the risk of being affected by stroke in the population of northern Sweden, a population well apt for genetic studies due to well kept church and medical records together with limited genetic diversity. In the first paper we used linkage analysis in families with early onset of stroke. By this approach we identified a region on chromosome 5q to be linked to an increased risk of developing stroke, a region previously identified as a susceptibility locus for stroke in the Icelandic population. In the second study we used genealogy to identify common ancestry and thereby identify common susceptibility to stroke. The seven families we connected showed significant linkage to the chromosome 9q31-33 region and four of the families shared a common haplotype over 2.1 megabases. In the third manuscript we investigated sequence variation of two candidate genes, TNFSF15 and TLR4. Sequencing of the TLR4 gene revealed previously identified variations in affected individuals from two of the families. Further SNP analysis showed five separate haplotypes among the investigated families and four haplotypes for TNFSF15. However none of these co-segregated with stroke among the investigated families. In the final paper we used a case-control stroke cohort to ascertain association for genetic variation in five genes and genetic regions previously suggested to be linked with stroke. Initial analyses showed association for the 9p21 chromosomal region and a variant in Factor 5 that showed protection against stroke, but after adjustments for common risk factors for stroke, the findings were no longer significant. In conclusion, by studying selected families we have been able to show linkage to two chromosomal regions, 5q and 9q31-33, that indicate genetic predisposition for developing stroke. Further we have shown that family based studies are still an important tool in deciphering the underlying mechanisms for complex disease.

Prostate cancer is a major health burden throughout the world, yet the etiology of prostate cancer is poorly understood. Evidence has accumulated supporting the existence of a hereditary form of this disease. Improved understanding of the genetic mechanisms underlying the development and progression of prostate cancer would be a major advance for improved prevention, detection and treatment strategies. This thesis evaluates different aspects of the genetic epidemiology of prostate cancer. In a genomic scan two chromosomal regions with evidence for linkage was observed. The strongest support was found on chromosome 19p with an allele sharing LOD score of 2.91 (genome-wide P = 0.032). The second region, showing suggestive evidence of linkage, was observed in the centromeric region of chromosome 5. Linkage analyses of densely spaced markers on chromosome 8p22-23 confirmed (P = 0.03) previously reported linkage to this region. A systematic evaluation of the possible impact that the RNASEL gene have on prostate cancer was performed. Overall, limited evidence for association with prostate cancer risk was found. The results provide strong evidence against a role of RNASEL in prostate cancer etiology in Sweden. In a comprehensive evaluation of occurrence of other malignancies in HPC families, previously reported association between gastric and prostate carcinoma was confirmed. The increased risk was of the same magnitude in early and late onset HPC families and confined to only male relatives. A genome-wide linkage analysis, stratified by occurrence of gastric carcinoma, identified a novel susceptibility locus on chromosome Xp21. In summary, chromosome 5q and 19p represents the regions most likely to harbor susceptibility genes predisposing to prostate cancer in the Swedish population. A common genetic basis for both gastric and prostate cancer has been confirmed and a novel susceptibility locus on chromosome Xp21 has been identified.

Stimulation or repression of gene expression by genome-wide regulatory mechanisms is an important epigenetic regulatory function which can act to efficiently regulate larger regions or specific groups of genes, for example by compensating for loss or gain of chromosome copy numbers. In Drosophila melanogaster there are two known chromosome-wide regulatory systems; the MSL complex, which mediates dosage compensation of the single male X-chromosome and POF, which stimulates expression from the heterochromatic 4th chromosome. POF also interacts with the heterochromatin inducing protein HP1a, which represses expression from the 4th chromosome but which also has been assigned stimulatory functions. In addition to these two, there is another more elusive and less well-characterized genome-wide mechanism called buffering, which can act to balance transcriptional output of aneuploidy regions of the genome (i.e. copy number variation). In my thesis, I describe the presence of a novel physical link between dosage compensation and heterochromatin; mediate by two female-specific POF binding sites, proximal to roX1 and roX2 on the X chromosome (the two non-coding RNAs in the MSL complex). These sites can also provide clues to the mechanisms behind targeting of chromosome-specific proteins. Furthermore, to clarify the conflicting reports about the function of HP1a, I have suggested a mechanism in which HP1a has adopted its function to different genomic locations and gene types. Different binding mechanisms to the promoter vs. the exon of genes allows HP1a to adopt opposite functions; at the promoter, HP1a binding opens up the chromatin structure and stimulates gene expression, whereas the binding to exons condense the chromatin and thus, represses expression. This also causes long genes to be more bound and repressed by HP1a. Moreover, I show that buffering of monosomic regions is a weak but significant response to loss of chromosomal copy numbers, and that this is mediated via a general mechanism which mainly acts on differentially expressed genes, where the effect becomes stronger for long genes. I also show that POF is the factor which compensates for copy number loss of chromosome 4.

There are around 20.000 genes in the human genome all of which could potentially be expressed. However, it is obvious that not all of them can be active at the same time. Thus, there is a need for coordination achieved through the regulation of transcription. Transcriptional regulation is a crucial multi-component process involving genetic and epigenetic factors, which determine when and how genes are expressed. The aim of this thesis was to study two of these components, the transcription factors and the DNA sequence elements with which they interact. In papers I and II, we tried to characterize the regulatory role of repeated elements in the regulatory sequences of nitric oxide synthase 2 gene. We found that this type of repeat is able to adopt non B-DNA conformations in vitro and that it binds nuclear factors, in addition to RNA polymerase II. Therefore it is probable that these types of repeats can participate in the regulation of genes. In papers III-V, we intended to analyze the genome-wide binding sites for six transcription factors involved in fatty acid and cholesterol metabolism and the sites of an epigenetic mark in a human liver cell line. For this, we applied the chromatin immunoprecipitation (ChIP) method together with detection on microarrays (ChIP-chip) or by detection with the new generation massively parallel sequencers (ChIP-seq). We found that all of these transcription factors are involved in other liver-specific processes than metabolism, for example cell proliferation. We were also able to define two sets of transcription factors depending on the position of their binding relative to gene promoters. Finally, we demonstrated that the patterns of the epigenetic mark reflect the structure and transcriptional activity of the promoters. In conclusion, this thesis presents experiments, which moves our view from genetics to genomics, from in vitro to in vivo, and from low resolution to high resolution analysis of transcriptional regulation.

GWAS have identified several chromosomal loci associated with ovarian cancer risk. However, the mechanism underlying these associations remains elusive. We identify candidate functional Single Nucleotide Polymorphisms (SNPs) at the 9p22.2 ovarian cancer susceptibility locus, several of which map to transcriptional regulatory elements active in ovarian cells identified by FAIRE-seq (Formaldehyde assisted isolation of regulatory elements followed by sequencing) and ChIP-seq (Chromatin Immunoprecipitation followed by sequencing) in relevant cell types. Reporter and electrophoretic mobility shift assays (EMSA) determined the extent to which candidate SNPs had allele specific effects. Chromosome conformation capture (3C) reveals a physical association between Basonuclin 2 (BNC2) and SNPs with functional properties. This establishes BNC2 as a major target of four candidate functional SNPs in at least two distinct elements. BNC2 codes for a putative transcription regulator containing three pairs of zinc finger (ZF) domains. Furthermore, bnc2 mutation in zebrafish leads to developmental defects including dysmorphic ovaries and sterility, clearly implicating this protein in cellular processes associated with ovarian development. We show that BNC2 is a transcriptional regulator with a specific DNA recognition sequence of targets enriched in genes involved in cell communication through DNA binding assays, ChIP-seq, and expression analysis. This study reveals a comprehensive regulatory landscape at the 9p22.2 locus and indicates that a likely mechanism of susceptibility to ovarian cancer may include multiple allele-specific changes in DNA regulatory elements some of which alter BNC2 expression. This study begins to identify the underlying mechanisms of the 9p22.2 locus association with ovarian cancer and aims to provide data to support advances in care based on one’s genetic composition.

High-throughput methods systematically measure the internal state of the entire cell, but powerful computational tools are needed to infer dynamics from their raw data. Therefore, we have developed a new computational method, Eigen-genomic System Dynamic-pattern Analysis (ESDA), which uses systems theory to infer dynamic parameters from a time series of gene expression measurements. As many genes are measured at a modest number of time points, estimation of the system matrix is underdetermined and traditional approaches for estimating dynamic parameters are ineffective; thus, ESDA uses the principle of dimensionality reduction to overcome the data imbalance. We identify degradation dynamic patterns of a genomic system using ESDA. We also combine ESDA and Principal-oscillation-pattern (POP) analysis, which has been widely used in geosciences, to identify oscillation patterns. We demonstrate the first application of POP analysis to genome-wide time-series gene-expression data. Both simulation data and real-world data are used in this study to demonstrate the applicability of ESDA to genomic data. The biological interpretations of dynamic patterns are provided. We also show that ESDA not only compares favorably with previous experimental methods and existing computational methods, but that it also provides complementary information relative to other approaches. / text

In this dissertation we propose methodology for testing SNP-sets for genetic associations, both for sequencing and genome-wide association studies. Due to the large scale of this kind of data, there is an emphasis on producing methodology that is not only accurate and powerful, but also computationally efficient.

Genetic improvement of indigenous pig populations in tropical developing countries can make a significant contribution to the conservation and utilization of local genetic resources. Designing a swine breeding program requires knowledge of genetic parameters for economically important traits. A meta-analysis of genetic parameters determined under tropical conditions and published from 1974 to 2009 was carried out to provide consensus estimates of genetic parameters. Given that the data recording and analysis infrastructure for implementing the conventional best linear unbiased prediction (BLUP) methods is generally lacking in developing countries, Genome-wide selection (GS) provides an approach for achieving faster genetic progress without developing a pedigree recording system. A simulation study was carried out to evaluate the option of using available 60 K single nucleotide polymorphism marker panel. The observed levels of linkage disequilibrium (LD) in the tropical pig populations were simulated and utilized. Genomic predictions were from ridge regression analysis. The results showed that expected accuracies of genomic breeding values (GBV) were in the range of 0.31 - 0.86 for the validation set. Genome-wide selection improved accuracy of GBVs over conventional BLUP method for traits with low heritability and in young animals with no performance data. Crossbred training populations had higher accuracy than purebred training populations. An assessment of the opportunities for GS in tropical pig breeding was conducted. Genome-wide selection performed better than conventional methods by increasing genetic gain and maintaining genetic variation while lowering inbreeding especially for traits with low heritability, by exploiting LD and the Mendelian sampling effects. Combining GS with repeated backcrossing of crossbreds to the selected exotic population in moderate LD promises faster improvements of the commercial population. A two-step selection strategy that involves the use of GS to pre-select candidates that entered the performance test station and for selecting replacement candidates in a nucleus swine breeding program was evaluated and compared to other conventional approaches. Genome-wide selection generated an increase of about 38% to 172% in annual returns compared to other conventional approaches for previously selected population in moderate LD and about 2% to 50% increases in return for unselected population in low LD. / Canadian Commonwealth Scholarship and Fellowship Program, University of Guelph

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