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Human population history and its interplay with natural selection 10.17863/CAM.31536 Siska, Veronika 0000000280571203 Manica, Andrea 000000031895450X The complex demographic changes that underlie the expansion of anatomically modern humans out of Africa have important consequences on the dynamics of natural selection and our ability to detect it. In this thesis, I aimed to refine our knowledge on human population history using ancient genomes, and then used a climate-informed, spatially explicit framework to explore the interplay between complex demographies and selection. I first analysed a high-coverage genome from Upper Palaeolithic Romania from ~37.8 kya, and demonstrated an early diversification of multiple lineages shortly after the out-of-Africa expansion (Chapter 2). I then investigated Late Upper Palaeolithic (~13.3ky old) and Mesolithic (~9.7 ky old) samples from the Caucasus and a Late Upper Palaeolithic (~13.7ky old) sample from Western Europe, and found that these two groups belong to distinct lineages that also diverged shortly after the out of Africa, ~45-60 ky ago (Chapter 3). Finally, I used East Asian samples from ~7.7ky ago to show that there has been a greater degree of genetic continuity in this region compared to Europe (Chapter 4). In the second part of my thesis, I used a climate-informed, spatially explicit demographic model that captures the out-of-Africa expansion to explore natural selection. I first investigated whether the model can represent the confounding effect of demography on selection statistics, when applied to neutral part of the genome (Chapter 5). Whilst the overlap between different selection statistics was somewhat underestimated by the model, the relationship between signals from different populations is generally well-captured. I then modelled natural selection in the same framework and investigated the spatial distribution of two genetic variants associated with a protective effect against malaria, sickle-cell anaemia and $\beta^0$ thalassemia (Chapter 6). I found that although this model can reproduce the disjoint ranges of different variants typical of the former, it is incompatible with overlapping distributions characteristic of the latter. Furthermore, our model is compatible with the inferred single origin of sickle-cell disease in most regions, but it can not reproduce the presence of this disorder in India without long-distance migrations. University of Cambridge 2019-03-30 Thesis Doctoral Doctor of Philosophy (PhD) en The Gates Cambridge Trust provided the full funding for my PhD, including funding to attend conferences and workshop, and fourth-year funding. Trinity College helped financially through the External Honorary Research scholarship and travel funding. The Cambridge Philosophical Society contributed to funding in the fourth year of my PhD. https://www.repository.cam.ac.uk/handle/1810/284164 https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/de8ffab2-e975-4f94-850e-08a0df891a1b/download 31ce1351eaa2210a0ba502fce3d45e81 https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/1f95a295-9c67-4029-add7-4b61604ca213/download 87eda9de84448d1f82354d60eee3eb5f https://creativecommons.org/licenses/by-nc-sa/4.0/ human genetics population genetics mathematical biology computational biology natural selection malaria sickle-cell disease thalassemia neutral variation population continuity population admixture East Asia neolithic transition neolithic Upper Palaeolithic Georgia Romania paleoclimate spatially explicit modelling stochastic modeling European genetics East Asian genetics ancient genetics palaeoanthropology biological anthropology computer modelling selection statistics statistics data analysis