Abstract:
Recent developments in technology and computation have encouraged
a shift towards a whole-genome approach to genetic analysis. Two key
contributors to this shift, the Human Genome Project and the HapMap
project, sparked an interest in studying the genetic patterns found in particular
groups of individuals. The Maori population of New Zealand is an
ideal, yet untapped, model for such studies due to recent partial mixture of
two distinct population groups, and a culture of good documentation of
genealogical information. A previous study carried out by the author found
observable genetic differences between Maori and European populations
in markers of forensic significance, yet no particular genetic patterns were
found that were uniquely Maori. This study extends the previous work by
developing methods to determine to what scale these differences exist, as
well as demonstrating that a knowledge of these differences and methods
could be used to improve current practices for clinical diagnosis.
The current project began by taking a ‘candidate gene’ approach, studying
two regions where there were known large genetic differences between
Maori and European individuals: the region of Alcohol Dehydrogenase
genes on Chromosome 4 (Chapter 2), and the Monoamine Oxidase A gene
region on Chromosome X (Chapter 3). In both of these regions, large
frequency differences were observed between Maori and non-Maori populations
at both a single mutation level, and at a haplotype level.
Despite the differences that were observed, no particular combinations
of mutations could be considered uniquely Maori or uniquely non-Maori,
so studies were expanded to the entire genome. This epansion was made
possible due to the recent and continuing developments in genome-wide
technology and advancements in computational speed and efficiency. Once
it was possible to carry out a genome-wide study of genetic differences, the
goal of research changed from determining whether or not Maori and European
individuals were uniquely different at a genotype level, to how small
a marker set could be produced while maintaining population-uniqueness
at a genotype level.
A method that uses bootstrap sub-sampling and other internal validation
techniques has been developed for the generation of such a signature
set for a Maori tribe (Ngati Rakaipaaka), and the generated set has been
validated in other similar populations (Chapter 4). As a consequence of
producing this set, the degree of European admixture was estimated in the
tribe (28.7%), with over 15% of individuals within Rakaipaaka found to
have no discernible European genomic ancestry.
In a validation of the signature set generation method itself, the marker
selection procedure was repeated for Type 1 Diabetes, a disease with high
heritability. An analysis of case and control individuals using this signature
set found that the generated set is able to perform better than a
genome-wide reference set of mutations known to be associated with Type
1 Diabetes. This validation study, other potential uses, and a more detailed
discussion of the signature set generation method are presented in
Chapter 5.
