Van Dorp, L; (2017) Investigating processes driving genetic diversity in human populations using dense haplotypes. Doctoral thesis , UCL (University College London).

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Abstract

Although it is well established that DNA varies substantially among different world-wide human groups, the principal forces driving this genetic diversity are not well understood. This PhD thesis aims to describe genetic patterns among a wide range of human groups and characterize the primary historical, anthropological and sociological factors that contribute to observed levels of genetic diversity among these groups. In particular, through development and application of sophisticated haplotype-based techniques to several diverse human datasets, this work sheds light on the effects on genetic diversity of genetic isolation, migration, and other factors in specific geographic regions at different times in history. For example, this thesis explores the impact of recent marginalisation on genetic diversity in the Ethiopian Ari and shows that recent isolation in the Ari Blacksmiths can lead to strong genetic differentiation over a relatively short time scale. It also explores population structure in the Democratic Republic of Congo through analyses of novel genome-wide genotype data, relating these patterns to oral traditions, social practices and migration history. Studying the impact of much older events on present day population structure, this thesis also presents the first application of haplotype-based methods to study ancient DNA from some of the earliest known farmers recovered in Greece, Anatolia and Iran. Using this data, evidence is provided for demic diffusion of a Neolithic way of life into Europe, as well as documenting the presence of strong genetic structure in the first farmers of the Eastern Fertile Crescent. Finally this thesis presents preliminary work that synthesises global patterns of genetic diversity in relation to Africa as a method for investigating the temporal nature of the initial Out of Africa migrations that have contributed enormously to human genetic diversity observed today. Overall through merging these unique methods and diverse datasets, this thesis answers a number of important questions about human evolution.

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