Thesis (MSc)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Described as one of the costliest and most debilitating disorders, schizophrenia has proven to be among the greatest challenges for medical researchers. The disorder poses difficulties on all levels: from genotype to phenotype. Even though it is known that there is a substantial genetic contribution to schizophrenia susceptibility (~80%), it is unknown whether this is due to common variants, rare variants, epigenetic factors, polymorphisms in regulatory regions of the genome or a combination of all these factors. Over the past few decades, many approaches have been employed to elucidate the genetic architecture of schizophrenia, with the latest and most promising being genome wide association studies (GWAS). However, nearly a decade after the first GWAS, the limitations are increasingly being recognised and new avenues need to be explored. Studies have recently started to focus on the analysis of non-coding regions of the genome since these regions harbour the majority of variants identified in GWAS thus far. This study aimed to use recently developed programs that utilize data from large scale studies such as previous GWAS, the Encyclopaedia of DNA Elements (ENCODE), 1000 Genomes, HapMap and Functional Annotation of the Mammalian Genome (FANTOM) to establish a simple, yet effective bioinformatics pipeline for the identification and assessment of variants in regulatory regions. Using the established workflow, 149 single nucleotide polymorphisms (SNPs) in regulatory regions were implicated in schizophrenia susceptibility, with the most significant SNP being rs200981. Pathway and network analysis using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and GeneMANIA respectively indicated that the most frequently affected genes were involved in immune responses or neurodevelopmental processes, which support previous findings. Yet, novel findings of this study implicated processes crucial for DNA packaging (from DNA level to chromatin level). The second part of the study used restriction fragment length polymorphism analysis of polymerase chain reaction-amplified fragments (PCR-RFLP) to genotype ten of the most significant SNPs (identified by bioinformatic analyses in the first part of the study) in a South African Xhosa cohort of 100 cases and 100 controls, while bi-directional Sanger sequencing was used to confirm the presence of these SNPs. Statistical analyses revealed two haplotypes of regulatory variants, rs200483-rs200485-rs2517611 (p = 0.0385; OR = 1.71; 95% CI = 1.01-2.91) and rs200981-rs2517611-rs3129701 (p = 0.041; OR = 0.51; 95% CI = 0.27-0.98) associated with schizophrenia susceptibility. Bioinformatic analysis indicated that these haplotypes affect DNA packaging, which supported the findings of the first part of the study and could implicate epigenetic processes. The findings of this study support the importance of regulatory variants in schizophrenia susceptibility. This study also showed the importance of combining GWAS data with additional analyses in order to better understand complex diseases. It is hoped that these findings could fuel future research, specifically in genetically unique populations. / AFRIKAANSE OPSOMMING: Skisofrenie kan beskryf word as een van die duurste en mees ernstige siektes en bly steeds een van die grootste uitdagings vir mediese navorsers. Hierdie versteuring behels probleme op alle vlakke: van genotipe tot fenotipe. Alhoewel dit bekend is dat daar 'n aansienlike genetiese bydrae tot skisofrenie vatbaarheid is (~ 80%), is dit onbekend of dit is as gevolg van algemene variasies, skaars variasies, epigenetiese faktore, variasies in regulerende gebiede van die genoom of 'n kombinasie van al hierdie faktore. Oor die afgelope paar dekades is verskeie benaderings gebruik om die genetiese samestelling van skisofrenie te bestudeer, met die nuutste en mees belowende synde genoom-wye assosiasie studies (GWAS). Byna 'n dekade na die eerste GWAS, word die beperkinge egter toenemend erken en nuwe navorsingstrategieë moet gebruik word. Studies het onlangs begin om meer te fokus op die analise van nie-koderende areas van die genoom aangesien hierdie areas die meerderheid van die variasies behels wat tot dusver in GWAS geïdentifiseer is. Hierdie studie het gepoog om onlangs ontwikkelde programme, wat gebruik maak van die data van grootskaalse studies soos vorige GWAS, die “Encyclopaedia of DNA Elements” (ENCODE), “1000 Genomes”, “HapMap” en “Functional Annotation of the Mammalian Genome” (FANTOM), te implementeer om sodoende 'n eenvoudige, maar doeltreffende bioinformatika pyplyn vir die identifisering en evaluering van variante in regulerende gebiede, te vestig. Deur die gebruik van die gevestigde bioinformatika pyplyn, is 149 enkel nukleotied polimorfismes (SNPs) in regulerende gebiede in skisofrenie vatbaarheid betrek, met rs200981 wat die mees betekenisvol was. Pad- en netwerk-analise met die onderskeidelike hulp van die “Database for Annotation, Visualization and Integrated Discovery” (DAVID) en “GeneMANIA”, het aangedui dat die gene wat die meeste geaffekteer was, betrokke is by immuunreaksies en neuro-ontwikkeling. Hierdie bevindinge ondersteun vorige studies. Tog het nuwe bevindinge van hierdie studie prosesse geïmpliseer wat uiters noodsaaklik is vir DNS verpakking (van DNS- tot chromatien-vlak). Die tweede deel van die studie het restriksie fragment lengte polimorfisme analise van polimerase ketting reaksie geamplifiseerde fragmente (PKR-RFLP) gebruik om tien van die belangrikste SNPs (wat geïdentifiseer is deur bioinformatiese ontledings in die eerste deel van die studie) in `n Suid-Afrikaanse Xhosa studiegroep van 100 skisofrenie gevalle en 100 kontroles te genotipeer, terwyl tweerigting Sanger volgordebepaling gebruik is om die teenwoordigheid van hierdie SNPs te bevestig. Statistiese analise het aangedui dat twee / National Research Foundation (DAAD-NRF)

Poliomyelitis is a foremost cause of paralysis among preventable diseases among children and adolescents globally. It is caused by persistent infection with poliovirus (PV). The PV infection does not always cause paralysis. A lack of immunization always increases the risk of paralytic polio. Genetic factors also been shown to affect the risk of developing the disease. The aim of this thesis is to investigate whether there are any genetic associations to paralytic poliomyelitis. This is based on a model for understanding its nature as a complex disease, where many genes are involved in contributing to the disease state. This is a population-based case-control study to identify genetic loci that influence disease risk. The study examined the association of genetic variation in single nucleotide polymorphisms (SNPs) across the genome with paralytic poliomyelitis susceptibility in the United States and Canadian survivors of poliomyelitis population, using a genome-wide association study (GWAS) approach. No association was observed. Loci that have been previously implicated were not found to affect the susceptibility to poliomyelitis in this study. The thesis consists of four chapters. Chapter 1 describes the epidemiology, pathogenesis and management of poliomyelitis. Chapter 2 gives an overview of the genomics of infectious diseases in general. Chapter 3 introduces the study population and presents the genome-wide analysis and associations with logistic regression to identify loci explore genes that might be associated with paralytic poliomyelitis and presents results. Chapter 4 discusses the implications of the results and explains future directions. / Thesis / Master of Science (MSc)

The publication of a draft equine genome sequence and the release by Illumina of a 50,000 marker single-nucleotide polymorphism (SNP) genotyping chip has provided equine researchers with the opportunity to use new approaches to study the relationships between genotype and phenotype. In particular, it is hoped that the use of high-density markers applied to population samples will enable progress to be made with regard to more complex diseases. The first objective of this thesis is to explore the potential for the equine SNP chip to enable such studies to be performed in the horse. The second objective is to investigate the genetic background of osteochondrosis (OC) in the horse. These objectives have been tackled using 348 Thoroughbreds from the US, divided into cases and controls, and a further 836 UK Thoroughbreds, the majority with no phenotype data. All horses had been genotyped with the Illumina Equine SNP50 BeadChip. Linkage disequilibrium (LD) is the non-random association of alleles at neighbouring loci. The reliance of many genomic methodologies on LD between neutral markers and causal variants makes it an important characteristic of genome structure. In this thesis, the genomic data has been used to study the extent of LD in the Thoroughbred and the results considered in terms of genome coverage. Results suggest that the SNP chip offers good coverage of the genome. Published theoretical relationships between LD and historical effective population size (Ne) were exploited to enable accuracy predictions for genome-wide evaluation (GWE) to be made. A subsequent in-depth exploration of this theory cast some doubt on the reliability of this approach in the estimation of Ne, but the general conclusion that the Thoroughbred population has a small Ne which should enable GWE to be carried out efficiently in this population, remains valid. In the course of these studies, possible errors embedded within the current sequence assembly were identified using empirical approaches. Osteochondrosis is a developmental orthopaedic disease which affects the joints of young horses. Osteochondrosis is considered multifactorial in origin with a variety of environmental factors and heredity having been implicated. In this thesis, a genome-wide association study was carried out to identify quantitative trait loci (QTL) associated with OC. A single SNP was found to be significantly associated with OC. The low heritability of OC combined with the apparent lack of major QTL suggests GWE as an alternative approach to tackle this disease. A GWE analysis was carried out on the same dataset but the resulting genomic breeding values had no predictive ability for OC status. This, combined with the small number of significant QTL, indicates a lack of power which could be addressed in the future by increasing sample size. An alternative to genotyping more horses for the 50K SNP chip would be to use a low-density SNP panel and impute remaining genotypes. The final chapter of this thesis examines the feasibility of this approach in the Thoroughbred. Results suggest that genotyping only a subset of samples at high density and the remainder at lower density could be an effective strategy to enable greater progress to be made in the arena of equine genomics. Finally, this thesis provides an outlook on the future for genomics in the horse.

The case-control design is one of the most commonly used designs in genome- wide asociation studies. When we increase the sample size of either the controls or, more importantly, the cases, the power of whatever test we use will certainly increase. However increasing the sample size, means that addi- tional individuals need to be genotyped and this implies extra financial costs. However, nowadays with the emergence of genetic studies, a large number of genetic data are available at low or no extra cost. Even though those data may not be completely relevant to the current study, they can still be used to increase the probability to identify true associations. Furthermore, additional information, non-necessarily genetic, can also be used to improve the power of a method. In this thesis we extend the case-control design in order to take ad- vantage of such types of additional data and/or information. We discuss three designs; the case-cohort-control, the kin-cohort and the super-case– case–control–super-control designs. For each of these, we present methods that are adjusted or modified versions of standard case-control methods but we also propose novel ones developed with those extended designs in mind. Ultimately, we describe how those methods can be used in order to increase the power of association tests, especially compared to similar methods of the case-control design.

Over the last ten years, genome-wide association studies (GWAS) have been used to identify genetic variants associated with many diseases as well as quantitative phenotypes, by exploiting naturally occurring genetic variation in large cohorts of individuals. More recently, the GWAS approach has also been applied to highthroughput RNA sequencing (RNA-seq) data in order to find loci associated with different levels of gene expression, called expression quantitative trait loci (eQTL). Because of the large amount of data that is required for such high-resolution eQTL studies, most of them have so far been carried out in humans, where the cost of data collection could be justified by a possible future impact in human health. However, due to the rapidly falling price of high-throughput sequencing it is now also becoming feasible to perform high-resolution eQTL studies in higher model organisms. This enables the study of gene regulation in biological contexts that have so far been beyond our reach for practical or ethical reasons, such as early embryonic development. Taking advantage of these new possibilities, we performed a high-resolution eQTL study on 80 inbred fruit fly lines from the Drosophila Genetic Reference Panel, which represent naturally occurring genetic variation in a wild population of Drosophila melanogaster. Using a 3′ Tag RNA-sequencing protocol we were able to estimate the level of expression both of genes as well as of different 3′ isoforms of the same gene. We estimated these expression levels for each line at three different stages of embryonic development, allowing us to not only improve our understanding of D. melanogaster gene regulation in general, but also investigate how gene regulation changes during development. In this thesis, I describe the processing of 3′ Tag-Seq data into both 3′ isoform expression levels and overall gene expression levels. Using these expression levels I call proximal eQTLs both common and specific to a single developmental stage with a multivariate linear mixed model approach while accounting for various confounding factors. I then investigate the properties of these eQTLs, such as their location or the gene categories enriched or depleted in eQTLs. Finally, I extend the proximal eQTL calling approach to distal variants to find gene regulatory mechanisms acting in trans. Taken together, this thesis describes the design, challenges and results of performing a multivariate eQTL study in a higher model organism and provides new insights into gene regulation in D. melanogaster during embryonic development.

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