For every 200 births in the UK, one will end in a stillbirth. Stillbirth is classified as a baby born dead after 24 weeks gestation. Mutations in genes that cause ion channelopathies are known to cause sudden cardiac death in adults and children. Prenatal diagnosis of LQT has been possible for decades, creating a disease spectrum where channelopathies may fatally influence pregnancy. We sequenced 35 candidate genes in 70 unexplained stillbirth cases. Thirty-nine cases harboured a predicted damaging protein missense variant. Two novel and two rare variants were observed in the transient receptor potential melastatin 7 (TRPM7) gene and five rare genetic variants were found in A-kinase anchor protein 9 (AKAP9). The aim of this PhD was to perform functional studies of these variants in TRPM7 and AKAP9. TRPM7 is an ion channel indispensable for mouse cardiogenesis. Two TRPM7 variants (p.G179V and p.T860M) showed significantly reduced current compared to wild-type channels. Conversely, cells expressing p.R494Q TRPM7, had a significant increase in current compared to WT channels, but only in CHO-K1 cells. Western blot analyses failed to detect full length TRPM7 in cells transfected with either p.G179V or p.T860M compared to wild-type expressing cells. Proteosomal inhibition using MG132 produced a small but visible band in p.T860M transfected cells. Expression of TRPM7 in iPSC-derived cardiomyocytes increases during cell maturation, and TRPM7-like current was measured in 20-23 day old cardiomyocytes. AKAP9 is required to couple adrenergic stimulation in the heart with faster cardiac repolarisation. Cells expressing WT AKAP9 alongside the KCNQ1/KCNE1 potassium channel responded to β-adrenergic stimulation, however those transfected with p.A3043T AKAP9 did not respond to treatment with forskolin. Our analyses supports two deleterious variants in TRPM7 and one in AKAP9 in unexplained stillbirth cases. These heterozygous variants could lead to haploinsufficiency and may be a cause of stillbirth.

No description available.

Separate domestication events and strong selective pressures have created diverse phenotypes among existing cattle populations; however, the genetic determinants underlying most phenotypes are currently unknown. Bos taurus taurus (Bos taurus) and Bos taurus indicus (Bos indicus) cattle are subspecies of domesticated cattle that are characterized by unique morphological and metabolic traits. Because of their divergence, they are ideal model systems to understand the genetic basis of phenotypic variation. Here, we developed DNA and structural variant maps of cattle genomes representing the Bos taurus and Bos indicus breeds. Using this data, we identified genes under selection and biological processes enriched with functional coding variants between the two subspecies. Furthermore, we examined genetic variation at functional non-coding regions, which were identified through epigenetic profiling of indicative histone- and DNA-methylation modifications. Copy number variants, which were frequently not imputed by flanking or tagged SNPs, represented the largest source of genetic divergence between the subspecies, with almost half of the variants present at coding regions. We identified a number of divergent genes and biological processes between Bos taurus and Bos indicus cattle; however, the extent of functional coding variation was relatively small compared to that of functional non-coding variation. Collectively, our findings suggest that copy number and functional non-coding variants may play an important role in regulating phenotypic variation among cattle breeds and subspecies.

Insertion and deletion (indel), a common form of genetic variation, has been shown to cause or contribute to human genetic diseases and cancer. Despite this importance and being the second most abundant variant type in the human genome, indels have not been studied as much as the single nucleotide polymorphism (SNP). With the advance of next-generation sequencing technology, many indel calling tools have been developed. However, performance comparison of commonly used tools has shown that (1) the tools have limited power in identifying indels and there are significant number of indels undetected, and (2) there is significant disagreement among the indel sets produced by the tools. These findings indicate the necessity of improving the existing tools or developing new algorithms to achieve reliable and consistent indel calling results. Two indels are biologically equivalent if the resulting sequences are the same. Storing biologically equivalent indels as distinct entries in databases causes data redundancy and misleads downstream analysis. It is thus desirable to have a unified system for identifying and representing equivalent indels. This dissertation describes UPS-indel, a utility tool that creates a universal positioning system for indels so that equivalent indels can be uniquely determined by their coordinates in the new system. Results show that UPS-indel identifies more redundant indels than existing algorithms. While mapping short reads to the reference genome, a significant number of short reads are unmapped and excluded from downstream analyses, thereby causing information loss in the subsequent variant calling. This dissertation describes Genesis-indel, a computational pipeline that explores the unmapped reads to identify missing novel indels. Results analyzing sequence alignment of 30 breast cancer patients show that Genesis-indel identifies many novel indels that also show significant enrichment in oncogenes and tumor suppressor genes, demonstrating the importance of rescuing indels hidden in the unmapped reads in cancer and disease studies. Somatic mutations play a vital role in transforming healthy cells into cancer cells. Therefore, accurate identification of somatic mutations is essential. Many somatic mutations callers are available with different strengths and weaknesses. An ensemble approach integrating the power of the callers is warranted. This dissertation describes SomaticHunter, an ensemble of two callers, namely Platypus and VarDict. Results on synthetic tumor data show that for both SNPs and indels, SomaticHunter achieves recall comparable to the state-of-the-art somatic mutation callers and the highest precision, resulting in the highest F1 score. / Doctor of Philosophy / Insertion and deletion (indel), a common form of genetic variation in the human genome, is associated with genetic diseases and cancer. However, indels are heavily understudied due to experimental and computational challenges. This dissertation addresses the computational challenges in three aspects. First, the current approach of representing indels is ambiguous and causes significant database redundancy. A universal positioning system, UPS-indel, is proposed to represent equivalent indels unambiguously and the UPS-indel algorithm is theoretically proven to find all equivalent indels and is thus exhaustive. Second, a significant number of indels are hidden in DNA reads not mapped to the reference genome. Genesis-indel, a computational pipeline that explores the unmapped reads to identify novel indels that are initially missed, is developed. Genesis-indel has been shown to uncover indels that can be important genetic markers for breast cancer. Finally, mutations occurring in somatic cells play a vital role in transforming healthy cells into cancer cells. Therefore, accurate identification of somatic mutation is essential for a better understanding of cancer genomes. SomaticHunter, an ensemble of two sensitive variant callers, is developed. Simulated studies using whole genome and whole exome sequences have shown that SomaticHunter achieves recall comparable to state-of-the-art somatic mutation callers while delivering the highest precision and therefore resulting in the highest F1 score among all the callers compared.

Introduction: The continual increase of type 2 diabetes (T2D) prevalence is a global public health concern. The aetiology of T2D has not been fully elucidated and this is hampering the development of effective preventative and curative interventions to curb the T2D burden. Although much has been done to elucidate the environmental risk factors associated with T2D, little is known about the precise genetic risk factors that predispose people to it. There is limited knowledge about the common variants associated with T2D risk in the black South African population. However, evidence of shared common variants associated with T2D among people of different ethnicities has been documented. Nonetheless, the majority of the common variants that have been reported to be associated with T2D in other ethnicities are still yet to be evaluated in the black South African population. Objectives: The aim of this study was to evaluate the association of previously reported common genetic variants with T2D susceptibility, as indicated by impaired glucose tolerance (IGT), in a black South African population of Tswana descent. Methods: This study was a case-control study of 180 cases and 180 controls nested in the Prospective Urban Rural Epidemiology (PURE) study baseline data, which was collected in 2005. The DNA samples of the participants were genotyped for 77 single nucleotide polymorphisms (SNPs), using Illumina® VeraCode technology on the BeadXpress® platform. The gPlink software was used to evaluate the standard genetic models of disease penetrance for the association of the common variants with impaired glucose tolerance (IGT) while adjusting for age, sex and body mass index. Results: Four out of the 66 SNPs that were evaluated through the genetic association tests in this study were noted to be significantly associated with IGT (p< 0.05). Of the four SNPs, only rs1436955 was associated with an increase in T2D risk, while the other three variants, rs831571, rs8050136 and rs7542900, were noted to be associated with a decreased risk of T2D. However, none of the four SNPs was significantly associated with IGT after correcting for multiple testing (p <0.05). Conclusions: Black South Africans of Tswana descent might not share common variants associated with T2D risk, as indicated by IGT in other ethnicities. Wellpowered studies are required to evaluate the association of common variants with T2D risk in this population group. The results from this study emphasise the need for population-specific variants to assess the genetic susceptibility of complex diseases such as T2D in the black South African population. / MSc (Nutrition), North-West University, Potchefstroom Campus, 2014

Introduction: The continual increase of type 2 diabetes (T2D) prevalence is a global public health concern. The aetiology of T2D has not been fully elucidated and this is hampering the development of effective preventative and curative interventions to curb the T2D burden. Although much has been done to elucidate the environmental risk factors associated with T2D, little is known about the precise genetic risk factors that predispose people to it. There is limited knowledge about the common variants associated with T2D risk in the black South African population. However, evidence of shared common variants associated with T2D among people of different ethnicities has been documented. Nonetheless, the majority of the common variants that have been reported to be associated with T2D in other ethnicities are still yet to be evaluated in the black South African population. Objectives: The aim of this study was to evaluate the association of previously reported common genetic variants with T2D susceptibility, as indicated by impaired glucose tolerance (IGT), in a black South African population of Tswana descent. Methods: This study was a case-control study of 180 cases and 180 controls nested in the Prospective Urban Rural Epidemiology (PURE) study baseline data, which was collected in 2005. The DNA samples of the participants were genotyped for 77 single nucleotide polymorphisms (SNPs), using Illumina® VeraCode technology on the BeadXpress® platform. The gPlink software was used to evaluate the standard genetic models of disease penetrance for the association of the common variants with impaired glucose tolerance (IGT) while adjusting for age, sex and body mass index. Results: Four out of the 66 SNPs that were evaluated through the genetic association tests in this study were noted to be significantly associated with IGT (p< 0.05). Of the four SNPs, only rs1436955 was associated with an increase in T2D risk, while the other three variants, rs831571, rs8050136 and rs7542900, were noted to be associated with a decreased risk of T2D. However, none of the four SNPs was significantly associated with IGT after correcting for multiple testing (p <0.05). Conclusions: Black South Africans of Tswana descent might not share common variants associated with T2D risk, as indicated by IGT in other ethnicities. Wellpowered studies are required to evaluate the association of common variants with T2D risk in this population group. The results from this study emphasise the need for population-specific variants to assess the genetic susceptibility of complex diseases such as T2D in the black South African population. / MSc (Nutrition), North-West University, Potchefstroom Campus, 2014

Background: The human Aldoketoreductase 1B10 gene (AKR1B10) encodes one of the enzymes belonging to the family of aldoketoreductases and may be involved in detoxification of nutrients during digestion. Further, AKR1B10 mRNA (messenger ribonucleic acid) expression was diminished in brain regions potentially involved in the regulation of eating behavior in rats which are more sensitive to cocaine and alcohol. We hypothesized that the human AKR1B10 gene may also play a role in the regulation of human eating behavior.

No description available.

Chicken is a major protein source and intensively selected for economically important traits by humans. As such, this generated a huge range of phenotypes that representing a diverse spectrum of genetic variation. Understanding the functional basis of the genetic variants that underlie these traits, however, remains a formidable endeavour particularly for complex traits. Nonetheless, molecular phenotyping of an organism from sequenced data is doable with the advances in bioinformatics analysis and unparalleled surveys of genome wide genetic variants. This provides the opportunity to gain insights into the genome architecture and assists in identifying chromosomal regions underlying selection through a “sequences to consequences” approach. Combining a whole genome re-sequencing (WGS) approach with the knowledge of selection history, this thesis aimed to study the chromosomal regions and genetic variants underlying traits of interest in various selected chicken populations. To achieve this, genetic (quantitative and population genetics), genomic and bioinformatics approaches were employed and integrated to investigate the genome wide selection signatures in a number of different lines of chicken selected for different complex traits. This includes analysing: (i) divergently selected broilers for fatness traits (Chapter 2), (ii) a closed population of layer chickens (Chapter 3), (iii) selection signatures unique to broiler or layer chickens (Chapter 4) and (iv) selection signatures in colony stimulating factor 1 (CSF1) associated with gene expression differences in broiler and layer populations (Chapter 5). Candidate genes and nucleotides underlying potential selection regions were identified, and attempts were made to further elucidate the potential interplay between genes and the biological pathways involved in regulating traits in these selected chicken lines. Incorporating integrative approaches, variants within selection signatures were annotated to provide further evidence of their functional consequences. Overall, non-coding regions were enriched in selection signatures implied that causative variants may have regulatory roles. Capitalising on the millions of genetic variants discovered from WGS, chromosomal regions subject to selection were detected using a number of population genetics statistics. In broiler chicken lines divergently selected for very low-density plasma lipoprotein (VLDL) (Chapter 2), incorporating signatures of selection helped to improve the resolution of previously mapped quantitative traits loci (QTL) intervals. This research demonstrated that the integration of the analysis of selection signatures with functional annotation of genetic variants enabled refinement and characterisation of the QTL for fatness traits. In a closed population of brown leghorn layers (Chapter 3), evidence of selection signatures was found through Tajima’s D analysis. The analysis unravelled selection signatures encoding genes involved in numerous pathways and genes having key roles such as in behaviour, including feather pecking. Combining population differentiation statistic (FST) and Tajima’s D, a number of regions subject to divergent selection between broilers and white egg layers were identified (Chapter 4). Selection signatures were found to harbour mutations involved in cellular and tissue development, including genes having important roles in growth, fatness, egg shell strength and muscle development. These regions and the overlapping genes thereby may be potentially contributing to the different phenotypic variations observed between broilers and layers. In Chapter 5, a revised gene model for colony stimulating factor 1 (CSF1) showing complex pattern of alternate transcripts was predicted from transcriptome analysis of RNA isolated from 21 different tissues. In parallel, selection signatures analysis with the FST statistic, identified selection signatures that differentiate broilers to white egg layers (3 regions) or brown egg layers to white egg layers (4 regions). All these selection signatures were located within non-coding regions, indicating potential divergent selection of CSF1 within regulatory regions. Overall, the results presented in this thesis using the “sequences to consequences” approach, link several genomic regions and genes to phenotypic variation in domesticated chicken lines. The work reported here serves as a foundation for further study to decipher the relationship between “genotype and phenotype” and its functional consequences due to selection.

Introduction Vitamin D status is an important public health issue due to the high prevalence of vitamin D insufficiency and deficiency, especially in high latitude areas. Furthermore, it has been reported to be associated with a number of diseases. In a previous umbrella review of meta-analyses of randomized clinical trials (RCTs) and of observational studies, it was found that plasma/ serum 25-hydroxyvitamin D (25(OH)D) or supplemental vitamin D has been linked to more than 130 unique health outcomes. However, the majority of the studies yielded conflicting results and no association was convincing. Aim and Objectives The aim of my PhD was to comprehensively explore the association between vitamin D and multiple outcomes. The specific objectives were to: 1) update the umbrella review of meta-analysis of observational studies or randomized controlled trials on associations between vitamin D and health outcomes published between 2014 and 2018; 2) conduct a systematic literature review of previous Mendelian Randomization studies on causal associations between vitamin D and all outcomes; 3) conduct a systematic literature review of published phenome wide association studies, summarizing the methods, results and predictors; 4) create a polygenic risk score of vitamin D related genetic variants, weighted by their effect estimates from the most recent genome wide association study; 5) encode phenotype groups based on electronic medical records of participants; 6) study the associations between vitamin D related SNPs and the whole spectrum of health outcomes, defined by electronic medical records utilising the UK Biobank study; 7) explore the causal effect of 25- hydroxyvitamin D level on health outcomes by applying novel instrumental variable methods. Methods First I updated the vitamin D umbrella review published in 2015, by summarizing the evidence from meta-analyses of observational studies and meta-analyses of RCTs published between 2014 and 2018. I also performed a systematic literature review of all previous Mendelian Randomizations studies on the effect of vitamin D on all health outcomes, as well as a systematic review of all published PheWAS studies and the methodology they applied. Then I conducted original data analysis in a large prospective population-based cohort, the UK Biobank, which includes more than 500,000 participants. A 25(OH)D genetic risk score (weighted sum score of 6 serum 25(OH)D-related SNPs: rs3755967, rs12785878, rs10741657, rs17216707, rs10745742 and rs8018720, as identified by the largest genome wide association study of 25(OH)D levels) was constructed to be used as the instrumental variable. I used a phenotyping algorithm to code the electronic medical records (EMR) of UK Biobank participants into 1853 distinct disease categories and I then ran the PheWAS analysis to test the associations between the 25(OH)D genetic risk score and 950 disease outcome groups (i.e. outcomes with more than 200 cases). For phenotypes found to show a statistically significant association with 25(OH)D levels in the PheWAS or phenotypes which were found to be convincing or highly suggestive in previous studies, I developed an extended case definition by incorporating self-reported data collected by UK Biobank baseline questionnaire and interview. The possible causal effect of vitamin D on those outcomes was then explored by the MR two-stage method, inverse variance weighted MR and Egger's regression, followed by sensitivity analyses. Results In the updated systematic literature review of meta-analyses of observational studies or RCTs, only studies on new outcomes which had not been covered by the previous umbrella review were included. A total of 95 meta-analyses met the inclusion criteria. Among the included studies there were 66 meta-analyses of observational studies, and 29 meta-analyses of RCTs. Eighty-five new outcomes were explored by meta-analyses of observational studies, and 59 new outcomes were covered by meta-analyses of RCTs. In the systematic review of published Mendelian Randomization studies on vitamin D, a total of 29 studies were included. A causal role of 25(OH)D level was supported by MR analysis for the following outcomes: type 2 diabetes, total adiponectin, diastolic blood pressure, risk of hypertension, multiple sclerosis, Alzheimer's disease, all-cause mortality, cancer mortality, mortality excluding cancer and cardiovascular events, ovarian cancer, HDL-cholesterol, triglycerides and cognitive functions. For the systematic literature review of published PheWAS studies and their methodology, a total of 45 studies were included. The processes for implementing a PheWAS study include the following steps: sample selection, predictor selection, phenotyping, statistical analysis and result interpretation. One of the main challenges is the definitions of the phenotypes (i.e., the method of binning participants into different phenotype groups). In the phenotyping step, an ICD curated phenotyping was widely used by previous PheWAS, which I also used in my own analysis. By applying the ICD curated phenotyping, 1853 phenotype groups were defined in the participants I used. In PheWAS, only phenotype groups with more than 200 cases were analysed (920 phenotypes). In the PheWAS, only associations between rs17216707 (CYP24A1) and "calculus of ureter" (beta = -0.219, se = 0.045, P = 1.14*10-6), "urinary calculus" (beta = -0.129, se = 0.027, P = 1.31*10-6), "alveolar and parietoalveolar pneumonopathy" (beta = 0.418, se = 0.101, P = 3.53*10-5) survived Bonferroni correction. Nine outcomes, including systolic blood pressure, diastolic blood pressure, body mass index, risk of hypertension, type 2 diabetes, ischemic heart disease, depression, non-vertebral fracture and all-cause mortality were explored in MR analyses. The MR analysis had more than 80% power for detecting a true odds ratio of 1.2 or larger for binary outcomes. None of explored outcomes were statistically significant. Results from multiple MR methods and sensitivity analyses were consistent. Discussion Vitamin D and its association with multiple outcomes has been widely studied. More than 230 outcomes have been linked with vitamin D by meta-analyses of observational studies and RCTs. On the contrary, evidence from Mendelian Randomization studies is lacking. In particular I identified only 20 existing MR studies and only 13 outcomes were suggested to be causally related to vitamin D. In the systematic literature review of previous PheWAS studies, I summarized the applied methods, predictors and results. Although phenotyping based on ICD codes provided good performance and was widely applied by previous PheWAS studies, phenotyping can be improved if lab data, imaging data and medical notes can be incorporated. Alternative algorithms, which takes advantage of deep learning and thus enable high precision phenotyping, needs to be developed. From the PheWAS analysis, the score of vitamin D related genetic variants was not statistically significantly associated with any of the 920 phenotypes tested. In the single variant analysis, only rs17216707 (CYP24A1) was shown to be associated with calculus outcomes statistically significantly. Previous studies reported associations between vitamin D and hypercalcemia, hypercalciuria, nephrolithiasis and nephrocalcinosis, may be due to the role of vitamin D in calcium homeostasis. In the MR analysis, I found no evidence of large to moderate (OR > 1.2) causal associations of vitamin D on a very wide range of health outcomes. These included SBP, DBP, hypertension, T2D, IHD, BMI, depression, non-vertebral fracture and allcause mortality which have previously been proposed to be influenced by low vitamin D levels. Further, even larger studies, probably involving the joint analysis of data from several large biobanks with future IVs that explain a higher proportion of the trait variance, will be required to exclude smaller causal effects which could have public health importance because of the high population prevalence of low vitamin D levels in some populations.