A thesis submitted to the Faculty of Science, University of the
Witwatersrand, Johannesburg in fulfilment of the requirements for
the degree of Doctor of Philosophy.
June 2017, Johannesburg / As sequencing and genotyping technologies are advancing, larger and more
complex sets of biological data are being produced. Databases can be used to
efficiently store and manage the data. Typically, publicly available datasets are
accessed through web browsers that offer a user-friendly interface to a
database, making complex queries simple to execute. However, research projectspecific
data are not commonly stored in this way. In this research, a database
(designed in MySQL) and accompanying interface (developed using PHP, HTML
and CSS) has been designed for the storage and querying of the quality
controlled data from the current project using Metabochip-genotyped Birth to
Twenty (Bt20) cohort participants and their female caregivers. Users can easily
access the data to generate summary statistics on the phenotype data and
download phenotype, single nucleotide polymorphism (SNP) annotation and
association analysis data that match user-supplied criteria.
Some of the data from the database was used to investigate the genetics of
blood pressure (BP) in black South African individuals. Hypertension is a major
risk factor for cardiovascular diseases (CVDs). BP variation is known to have a
genetic component, but genetic studies in indigenous Africans have been limited.
Association analysis, carried out in a merged sample of caregivers and
participants, pointed to novel regions of interest in the NOS1AP (DBP and SBP),
MYRF (SBP) and POC1B (SBP) genes and two intergenic regions
(DACH1|LOC440145 (DBP and SBP) and INTS10|LPL (SBP)). Two SNPs in the
MYRF gene met the calculated “array-wide” significance threshold (p<6.7x10-7
for the merged dataset) for multiple testing.
Genotype imputation is a useful addition to association studies to increase the
SNP panel for association testing. An investigation into the efficiency of
imputation in this dataset using a mixed population reference panel was carried
out. Imputation was achieved with high confidence in all genes, but a more
detailed view of the region was only seen in NOS1AP (DBP and SBP in both the
merged and female caregiver datasets) and POC1B (Bt20 participant dataset
only).
Overall, the research contributed a useful tool for the efficient management of
project-specific biological data. The analysis and genotype imputation, which is a
promising tool in future studies in this or other African datasets, also provided
some insight into the genetics of blood pressure in black South Africans with
further functional and replication studies in larger samples required to confirm
and explain the findings. / MT 2017
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/23508 |
Date | January 2017 |
Creators | Hendry, Liesl Mary |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Thesis |
Format | Online resource (xl, 232 leaves), application/pdf |
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