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.

Prostate-specific antigen (PSA) testing has caused a steep increase in the incidence of prostate cancer, especially the incidence of localised low risk disease. In order to decrease the overdiagnosis accompanied by PSA testing, analysis of inherited genetic variants have been suggested as potential tools for clinical assessment of disease risk. With the aim of minimizing overtreatment and postpone side-effects of curative treatment for low risk prostate cancer, active surveillance, a treatment strategy with initial surveillance and deferred radical prostatectomy at the time of progression has evolved.  The aim of this thesis was to study the validity of PSA (paper I) and inherited genetic variants (paper II) for early diagnosis of prostate cancer, to assess the extent of PSA testing in Sweden (paper III), and to study the safety of deferred radical prostatectomy in localised low to intermediate risk prostate cancer (paper IV). The study designs were i) case-control studies nested within the Västerbotten intervention project (paper I and II), ii) observational study in the Cancer Register of Sweden (paper III), and iii) observational study in the NPCR Follow-up study (paper IV). PSA had a high validity in predicting a prostate cancer diagnosis with an area under the receiver operating characteristics (ROC) curve of 0.86 (95% CI, 0.84 to 0.88). A combined test, including PSA, the ratio of free to total PSA, and 33 single nucleotide polymorphisms (SNPs) in a genetic risk score, increased the area under curve to 0.87 (95% CI, 0.85 to 0.89). The estimated uptake of PSA testing among men aged 55 to 69 years increased from zero to 56% between 1997 and 2007 and there were large variations in the uptake of PSA testing between counties in Sweden. After a median follow-up time of eight years there was no significant difference in presence of any one or more adverse pathology features or prostate cancer specific mortality after primary compared to deferred radical prostatectomy in localised low to intermediate risk prostate cancer. Results from these studies indicate that PSA and the hitherto identified SNPs are not suitable biomarkers in single-test prostate cancer screening. It is possible to estimate the uptake of PSA testing on a population level. Initial surveillance and deferred radical prostatectomy represent a feasible treatment strategy in localised low to intermediate risk prostate cancer.

Introduction: As a part of the Gene Regulators in Disease project (GRID), this study aims to create a novel high throughput method to discover the genetic effect on gene translation, taking advantage of the rationale that efficiently translated mRNAs associate with multiple ribosomes, while less active ones with fewer or none. / Methods: Lymphoblastoid cell lines (LCLs) from 44 HapMap European individuals were used for polyribosomal fractionation and establishing the sample bank for the future study. The fractionated mRNA samples of 10 out of the 44 individuals were run on an Illumina GoldenGate Beadarray to detect allelic imbalance (developed by the group of T.J. Hudson and T.M. Pastinen). / Results: This study established a high-quality RNA bank, including 1,100 RNA fraction samples. By the Illumina chip, translational imbalance was detected in 75 out of 1483 (5.06%) assays, and 63 out of269 (23.4%) genes. The translational effect was well replicable by the resequencing method. / Conclusion: This study found that genetic effect on gene translation is a common mechanism of expression regulation. Our best hit found in the integrin beta 1 binding protein 1 gene (ITGB1BP1 ) highlights the role of mRNA 3'UTR secondary structure in gene translation. / Keywords: Gene translation, High throughput genotyping, Human genetics, Polyribosome, RNA, Single nucleotide polymorphism

Genome-wide Association (GWA) studies have become a widely used method for analyzing genetic data. It is useful in detecting associations that may exist between particular alleles and diseases of interest. This thesis investigates the dataset provided from problem 1 of the Genetic Analysis Workshop 16 (GAW 16). The dataset consists of GWA data from the North American Rheumatoid Arthritis Consortium (NARAC). The thesis attempts to determine a set of single nucleotide polymorphisms (SNP) that are associated significantly with rheumatoid arthritis. Moreover, this thesis also attempts to address the question of whether the one-sided alternative hypothesis that the minor allele is positively associated with the disease or the two-sided alternative hypothesis that the genotypes at a locus are associated with the disease is appropriate, or put another way, the question of whether examining both alternative hypotheses yield more information.

The cost of feed remains an important factor affecting the profitability of beef production, and the difficulty of recording feed intake is a major limitation in an industry-wide selection program. Novel genomics approaches offer opportunities to select for efficient cattle. Therefore, the main objective of this work was to identify genetic markers responsible for genetic variation in feed efficiency traits as well as to understand the molecular basis of feed efficiency traits. The candidate gene approach revealed new single nucleotide polymorphisms (SNPs) in the Cholecystokinin B receptor (CCKBR) and pancreatic anionic trypsinogen (TRYP8) genes that showed strong evidence of association with feed efficiency traits. An in silico approach was proposed as a cost-effective method for SNP discovery. SNPs within genes Pyruvate carboxylase, ATPaseH+, UBQEI, UCP2, and PTI showed evidence of association with carcass traits without negatively affecting feed efficiency traits. The polymorphisms within genes CCKBR and TRYP8 were associated with pancreas mass and pancreatic exocrine secretion. A fine-mapping study on 1,879 SNPs revealed 807 SNPs with significant associations corresponding to 1,012 genes. These 807 SNPs represented a genomic heritability of 0.32 and 89% of the genetic variance of residual feed intake (RFI). Genomic breeding values estimated from the SNP set (807) were highly correlated (0.96) to the breeding values estimated from a mixed animal model. The 10 most influential SNPs were located in chromosomes 16, 17, 9, 11, 12, 20, 15, and 19. Enrichment analysis for the identified genes (1,012) suggested 110 biological processes and 141 pathways contributed to variation in RFI. The 339 newly identified SNPs corresponding to 180 genes identified by fine-mapping were tested for association with feed efficiency, growth, and carcass traits. Strong evidence of associations for RFI was located on chromosomes 8, 15, 16, 18, 19, 21, and 28. Combing validated SNPs from fine-mapping and the candidate gene approach may help develop a DNA test panel for commercial use and increase our understanding of the biological basis of feed efficiency in beef cattle. / The Ministry of Higher Education of Egypt

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The aim of this thesis is to apply recently developed technologies for genomic variation analyses, and to ensure quality of the generated information for use in preclinical cancer research. Faster access to a patients’ full genomic sequence for a lower cost makes it possible for end users such as clinicians and physicians to gain a more complete understanding of the disease status of a patient and adjust treatment accordingly. Correct biological interpretation is important in this context, and can only be provided through fast and simple access to relevant high quality data. Therefore, we here propose and validate new bioinformatic strategies for biomarker selection for prediction of response to cancer therapy. We initially explored the use of bioinformatic tools to select interesting targets for toxicity in carboplatin and paclitaxel on a smaller scale. From our findings we then further extended the analysis to the entire exome to look for biomarkers as targets for adverse effects from carboplatin and gemcitabine. To investigate any bias introduced by the methods used for targeting the exome, we analyzed the mutation profiles in cancer patients by comparing whole genome amplified DNA to unamplified DNA. In addition, we applied RNA-seq to the same patients to further validate the variations obtained by sequencing of DNA. The understanding of the human cancer genome is growing rapidly, thanks to methodological development of analysis tools. The next step is to implement these tools as a part of a chain from diagnosis of patients to genomic research to personalized treatment. / <p>QC 20121105</p>