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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Characterization and differentiation of three British population groups

Ballard, David January 2013 (has links)
The British population is made up of three main ethnic groups: Caucasian, Afro- Caribbean and South Asian. The history of Britain is littered with a series of invasion and colonisation events, potentially resulting in a variety of different genetic influences shaping the native population. More recent immigration trends have lead to over 11 million people within the UK describing themselves as belonging to an ethnic minority. The aim of this research is therefore to characterise these three population groups for a series of genetic markers, in the process gaining an insight into the genetics and origins of the individuals within these groups and ultimately developing a robust population-of-origin classification system for a DNA sample of unknown origin. To this end, three distinct areas of the genome were investigated. This comprised the development of a suite of PCR multiplex reactions to analyse 11 Y chromosome short tandem repeat (STR) markers, sequencing of the maternally inherited mitochondrial DNA, and analysis of a number of autosomal Single Nucleotide Polymorphisms (SNPs) known to show population specific allele distributions. The results from these studies led to the development of simple (Y chromosome and mitochondria) or complex (SNPs) classification systems enabling unknown DNA samples to be categorised into one of these 3 ethnic groups with a high degree of certainty: the YSTR population-of-origin classification algorithm had a success rate of 80%, the mitochondrial version a 90% success rate while correct prediction was achieved over 94% of the time with the autosomal SNPs.

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