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Cambridge NERC Doctoral Training Partnerships

Graduate Research Opportunities
 

Lead Supervisor: Guy Jacobs, Archaeology

 

Brief summary: 
Study how human populations diverge and evolve at small scales by combining simulation modelling with genomic and transcriptomic data from traditional Indonesian societies.
Importance of the area of research concerned: 
Recent advances in molecular genetics have greatly enriched understanding of human evolution. In particular, patterns of diversity and genetic differences between populations at continental scales clearly reveal the impact of selective forces. At the same time, increasing evidence from ancient DNA supports the complexity of genetic adaptation. Locally common functional variants rarely rose in frequency smoothly, a result of random effects but also potentially ancestry- and culturally-structured gene flow and adaptive regimes. Thus, while signals of selection may neatly resolve over large temporal and spatial scales, microevolutionary processes over short time frames are considerably more complex. These are the scales of action and experience – of the founding and dissolution of communities, and of interactions between them – and studying evolution at such scales is central to understanding the process of adaptation, both in the human context and more broadly. This project will develop statistical and modelling techniques and apply these to biological data to study human evolution at small scales.
Project summary : 
The project will draw on population genetic theory, computational modelling and genomic and transcriptomic (gene expression) data to study what drives genetic and biological differentiation between villages and islands in Indonesia. It will involve building fine-resolution models of human demography and evolution, and comparing their predictions to genetic data, detecting how intense selection may have been in the past, and quantifying the geographic scales at which such selection signals become visible. Although selection is widely studied in human genetic data, local adaptation is often understood through case studies. The project will integrate i) information on village-scale biological divergence using transcriptomic data ii) information on genetic mechanisms behind regulatory divergence (expression quantitative trait loci) and iii) models of evolutionary processes to build a richer,
What will the student do?: 
The student will build simulation models describing genetic and transcriptomic evolution – both neutral and including selection – in structured groups of villages and islands. This will involve demographic analysis of available data as well as further simulation, and will allow for theoretical exploration of neutral and adaptive processes. The student will analyse village-scale genetic and transcriptomic data, profiling signals of selection and differential expression as well as combining datasets to detect expression quantitative trait loci and signals of ancestry driving differential expression. The student will then combine these simulation and data analyses to determine the extent to which biological and genetic data conform to model expectations, and hence assess evidence for adaptive variation and the relevance of neutral theory at local and regional scales. There may be opportunities to extend existing datasets with genetic and transcriptomic data collected from new populations in Indonesia, particularly hunter-gatherers.
References - references should provide further reading about the project: 
Natri, H.M. et al 2020. Genome-wide DNA methylation and gene expression patterns reflect genetic ancestry and environmental differences across the Indonesian archipelago. PLoS Genetics, 16(5), p.e1008749.
Khaitovich, P., Pääbo, S. and Weiss, G., 2005. Toward a neutral evolutionary model of gene expression. Genetics, 170(2), pp.929-939.
Koch, E.M., 2019. The effects of demography and genetics on the neutral distribution of quantitative traits. Genetics, 211(4), pp.1371-1394.
Applying
You can find out about applying for this project on the Department of Archaeology page.
Dr Guy Jacobs
Department of Archaeology Graduate Administrator