published_or_final_version / Medicine / Master / Master of Research in Medicine

published_or_final_version / Dentistry / Doctoral / Doctor of Philosophy

published_or_final_version / Clinical Oncology / Master / Master of Philosophy

 Genome-wide mapping of susceptibility genes was conducted in two complex disorders of hypertension and epilepsy, allowing the dissection of the genetic architecture of these common diseases and related quantitative traits. The study performed comprehensive genetic analyses in a genome-wide scale, using different structure of data – sib-pairs and case-control samples. To identify genes influencing hypertension and blood pressure, a combined linkage and association study was conducted using over half a million SNPs genotyped in 328 siblings. Regions of significant linkage were identified for blood pressure traits on chromosomes 2q22.3 and 5p13.2, respectively. Further family-based association analysis of the linkage peak on chromosome 5 yielded a significant association (rs1605685, P < 7  10-5) for hypertension. One candidate gene, PDC, was replicated in the family-based association tests. A two-stage genome-wide association study (GWAS) was performed in a total of 1,087 cases and 3,444 controls, to identify common susceptibility variants of epilepsy in Chinese. The combined analysis identified two association signals in CAMSAP1L1, rs2292096 [G] (P=1.0×10-8, OR =0.63) and rs6660197 [T] (P=9.9×10-7, OR=0.69), which are highly correlated, achieving genome-wide significance. One SNP (rs9390754, P = 1.7 × 10-5) in GRIK2 was refined as a previously-implicated association. In addition to SNPs, the assessment of CNVs in GWAS was performed, which could provide valuable clues to discover genes contributing to the heritability of epilepsy. A genome-wide scan for epilepsy through the use of DNA pooling also provides an alternative approach to reducing the substantial cost and thus increase efficiency in large-scale genetic association studies. The genome-wide mapping studies in families and unrelated individuals are complementary and together offer a comprehensive catalog of common variations and structural variants implicated for both quantitative and qualitative traits. / published_or_final_version / Psychiatry / Doctoral / Doctor of Philosophy

Complex diseases, unlike Mendialian diseases, are often characterized by genetic heterogeneity and multifactorial inheritance, involving defects in genes from the same or multiple alternative pathways. Many congenital diseases and psychiatric disorders are complex diseases, and incur heavy health care burden on the society. With the advancement in high-throughput genotyping technologies and the availability of the human single nucleotide polymorphism (SNP) catalogue, genome-wide association study (GWAS) has been widely used to investigate the genetic component of complex diseases. Copy number variations (CNV) can also be identified using the data from the same SNP array. Aiming to identify more disease susceptibility loci for complex diseases, separate GWAS using a case-control design were conducted on anorectal malformations (ARMs) and schizophrenia. ARMs are rare congenital diseases with heterogeneous phenotypes which could probably be explained by the genetic heterogeneity among patients, while schizophrenia is a common psychiatric disorder that is well known for its multigenic inheritance. The GWAS studies on ARM and schizophrenia included 4,369 (patients: N=363; controls: N=4,006) and 1,231 Han Chinese (patients: N=381; controls: N=850) respectively. The two studies were mainly focused on investigating the contribution of rare CNVs to the diseases, involving analyses on global CNV burden, rare CNV association, protein-protein interaction (PPI) network, pathway and chromosomal aberrations. The associations of SNPs with ARMs were also examined. Apart from elucidating the genetic components in these two diseases, a systematic analysis on four CNV detection programs (CNV partition, PennCNV, QuantiSNP and iPattern) was also undertaken. In the study of schizophrenia, a new approach in CNV filtering which was based on latent class analysis was adopted to gather information from multiple CNV prediction programs. The study of ARMs revealed 79 genes which were disrupted by CNVs in patients only. In particular, a de novo duplication of DKK4 (an antagonist of WNT signaling) was identified, and addition of Dkk4 protein was demonstrated to cause ARMs in mice. Another 10 genes uniquely disrupted in ARMs patients are also related to WNT signaling. Interestingly, this pathway was also significantly inferred by CNV in patients with schizophrenia. A different set of genes related to WNT signaling was disrupted in ARMs patients and patients with schizophrenia. WNT signaling is crucial for the development of multiple parts in the embryo. The contribution of different WNT signaling pathways at different development stages may vary. Apart from the WNT signaling pathway, other genes with biological relevance were also implicated in the two studies through gene-network and pathway analyses. The results from these two GWAS studies support our existing understanding of complex diseases that defects in various interacting genes could contribute to the same disease. In summary, the CNV results from the two studies have demonstrated the genetic heterogeneity nature of these two complex diseases. The findings also uncovered a set of putative disease candidate genes, which can be used as reference materials for future genetic research for ARMs and schizophrenia. / published_or_final_version / Psychiatry / Doctoral / Doctor of Philosophy

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published_or_final_version / abstract / toc / Zoology / Master / Master of Philosophy

published_or_final_version / Molecular Biology / Doctoral / Doctor of Philosophy

Understanding the factors and processes that influence intraspecific genetic variation are essential to better understand evolutionary processes. In this research, I examined patterns of gene flow and their effects on the distribution of genetic variation and spatial genetic structuring at different spatial scales. I used a combination of population genetics, spatial analysis, morphometrics and phylogeography in order to understand the patterns of genetic variation and their resulting phenotypic variations in a semi-aquatic species, the muskrat (Ondatra zibethicus).