Population Genetics of Hunter-Gatherer Groups

Population Genetics of Hunter-Gatherer Groups

 

African populations have the greatest genetic diversity among all human groups, but remain poorly represented in human genomic studies. The hundreds of distinct populations in African can be highly diverged from one another and only the broad outlines of the complex population history of this continent have been inferred from genetic data. We are engaged in several genotyping and genome sequencing projects to discover new genetic variants in Africa and to model the origins of modern humans. 

Recent Balancing Selection in the HLA
This project seeks to identify signatures of recent balancing selection in the HLA region of the genome. The human-specific major histocompatibility complex (HLA) is a 4 Mb region on chromosome 6 that plays a crucial role in the genetic basis of the immune system and is implicated in many GWAS hits. The major HLA loci experience disease-driven selection pressure as they code for cell surface proteins that aid the immune system in effectively responding to pathogens. The HLA exhibits exceptional diversity, which has contributed to its use as an example of balancing selection; however, differentiating between specific mechanisms that contribute to such high diversity has remained challenging. In addition to high genetic diversity, the HLA exhibits high gene density and a low recombination rate that differentiate it from the rest of the genome. In the past 2,000 years, novel disease pressures have been introduced to southern Africa via pastoralist migrations and colonialism. This project seeks to address the importance of controlling for these unique characteristics of the HLA genomic region in selection scans and aims to detect signatures of pathogen-driven balancing selection that coincide with specific demographic events in southern African populations. To do this, we are working with HLA sequence data from the ≠Khomani San and Nama populations, as well as simulated data, which we use to train a machine learning approach—SWIF(r)—which incorporates multiple summary statistics to calculate the probability of selection at a particular site.

Migration Genetics and Cultural Evolution in Southwest Ethiopia
Inter-ethnic migration between small-scale societies that practice subsistence-based foraging, horticulture, and agriculture represents an important demographic process both in contemporary societies and across human evolutionary history. We are working to establish an in-depth, quantitative understanding of the processes that drive these smaller-scale migratory patterns in order to elucidate previously observed macro-patterns in human evolution and cultural diversification. We will be investigating the genetic and demographic mechanisms that underlie regional migratory patterns in Southwest Ethiopia to gain a comprehensive understanding of how migration affects cultural change. Specifically, how the gender of migrants affects which cultural traits spread between groups, particularly in the context of subsistence strategy. To address this, and related questions, I utilize both ethnographic fieldwork and computationally intensive genetic analyses.