Anthony Koehl

Publication Date

5-1-2016

Abstract

Admixture is a form of gene flow that occurs when long separated populations come into contact and exchange mates. Admixture has been a primary mechanism in the formation of many modern human populations. The genetic characteristics of an admixed population are intermediate to, yet distinct from, those of its ancestors. In this dissertation, I investigate biological and statistical factors that enter into the analysis of admixed populations using genetic marker data. In chapters one and two, I use genotype data from published sources that contain 618 microsatellite loci. In chapter three, I simulate genotypes of 500 microsatellite loci. In chapter two, I present an analysis of genetic diversity within and among 17 populations in the Americas that were formed by admixture among continental Indigenous Americans, Africans and Europeans. This is the first application of a new method to partition the genetic distance between pairs of populations into components related to ancestry and genetic drift. I show that the genetic relationships among the continental sources and genetic drift occurring after population formation strongly influence the genetic structure of these populations. In chapter three, I investigate a new strategy to find modern populations to serve as models for ancestors in admixture events that occurred in the past. This is a long-standing challenge to admixture studies. This chapter focuses on the Cape Coloured people of South Africa, a population that formed by mixture of indigenous Africans, Europeans, and Asians. I propose a series of models for their ancestry and use the Akaike Information Criterion to choose the best model. This method from information theory identifies a simple model that proposes only African and Asian ancestors. I interpret this result in terms of both the principle of parsimony and the evolutionary recent common ancestor of the human species. In chapter four, I use computer simulations to assess bias in ancestry fractions estimated by using maximum likelihood. These novel simulations were designed to produce data sets that mimic actual patterns of variation in human populations. I have found sampling strategies that produce reasonably unbiased results, despite the potential for maximum likelihood to produce biased estimates.

Keywords

Population genetics, admixture, ancestry

Document Type

Dissertation

Language

English

Degree Name

Anthropology

Level of Degree

Doctoral

Department Name

Anthropology

First Committee Member (Chair)

Jeffrey Longhttps://digitalrepository.unm.edu/editor.cgi?article=1038&window=annotate&context=anth_etds

Second Committee Member

Keith Hunley

Third Committee Member

Osbjourn M. Pearson

Fourth Committee Member

Lindsay Smith

Fifth Committee Member

Mark Shriver

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