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Title: Integration of genetic data and genomic annotation in the analysis of genome wide association studies
Author: Ng, Esther
ISNI:       0000 0004 6498 001X
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2017
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This thesis explored the utility of genome wide association studies (GWAS) and meta-analysis to identify variants associated with serum pollutants levels and metabolic phenotypes. The secondary aims of these thesis were to annotate these variants with regulatory information from databases and to investigate the role of copy number variation in influencing gene expression and phenotype. In the second and third chapters, we identified single nucleotide polymorphisms (SNPs) associated with pollutant and metabolic phenotypes. An example of a novel association was the relationship between SNPs in the ABCG2 gene and octachlorodibenzo-p-dioxin (OCDD). In the third chapter, we identified associations between metabolic phenotypes and SNPs. An example of an identified association was that between serum apolipoprotein B levels and rs7412, which is consistent with other GWAS. To fine map these loci and assign functional annotation, I created Bayesian credible sets and checked for overlap between SNPs in these credible sets and regulatory marks in the Encyclopaedia of DNA Elements (ENCODE) database. Annotating these credible set SNPs with functional information revealed various histone modifications and transcription factors that overlapped. This study was also successful in identifying copy number variants (CNVs) from the PIVUS cohort. There were moderately strong associations between CNVs and some of the phenotypes studied. These associations did not appear to be mediated by the SNP within the CNVs, as the latter had higher P values of associations. In addition, I identified several clinically relevant CNV-expression quantitative trait loci (CNV-eQTL) associations a separate cohort of healthy individuals. Some of these associations were cell specific and/or context specific. Many of these CNVs contained SNPs which are lead SNPs in GWAS studies on a variety of different phenotypes. In conclusion, this thesis was successful in identifying SNPs and CNVs associated with phenotypes, as well as annotating some of these variants with regulatory information. Further work is needed to clarify the mechanisms of regulation.
Supervisor: Morris, Andrew ; Knight, Julian Sponsor: Wellcome Trust
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available