We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci— e.g. , seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.

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Inference of population structure using multilocus genotype data

Arlequin ver 3.0 is a software package integrating several basic and advanced methods for population genetics data analysis, like the computation of standard genetic diversity indices, the estimation of allele and haplotype frequencies, tests of departure from linkage equilibrium, departure from selective neutrality and demographic equilibrium, estimation or parameters from past population expansions, and thorough analyses of population subdivision under the AMOVA framework. Arlequin 3 introduces a completely new graphical interface written in C++, a more robust semantic analysis of input files, and two new methods: a Bayesian estimation of gametic phase from multi-locus genotypes, and an estimation of the parameters of an instantaneous spatial expansion from DNA sequence polymorphism. Arlequin can handle several data types like DNA sequences, microsatellite data, or standard multi-locus genotypes. A Windows version of the software is freely available on http://cmpg.unibe.ch/software/arlequin3.

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Arlequin (version 3.0): An integrated software package for population genetics data analysis

Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

Episodes of population growth and decline leave characteristic signatures in the distribution of nucleotide (or restriction) site differences between pairs of individuals. These signatures appear in histograms showing the relative frequencies of pairs of individuals who differ by i sites, where i = 0, 1, .... In this distribution an episode of growth generates a wave that travels to the right, traversing 1 unit of the horizontal axis in each 1/2u generations, where u is the mutation rate. The smaller the initial population, the steeper will be the leading face of the wave. The larger the increase in population size, the smaller will be the distribution's vertical intercept. The implications of continued exponential growth are indistinguishable from those of a sudden burst of population growth Bottlenecks in population size also generate waves similar to those produced by a sudden expansion, but with elevated uppertail probabilities. Reductions in population size initially generate L-shaped distributions with high probability of identity, but these converge rapidly to a new equilibrium. In equilibrium populations the theoretical curves are free of waves. However, computer simulations of such populations generate empirical distributions with many peaks and little resemblance to the theory. On the other hand, agreement is better in the transient (nonequilibrium) case, where simulated empirical distributions typically exhibit waves very similar to those predicted by theory. Thus, waves in empirical distributions may be rich in information about the history of population dynamics.

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Population growth makes waves in the distribution of pairwise genetic differences.

Expansions of population size leave characteristic signatures in mitochondrial "mismatch distributions." Consequently, these distributions can inform us about the history of changes in population size. Here, I study a simple model of population history that assumes that, t generations before the present, a population grows (or shrinks) suddenly from female size N0 to female size N1 . Although this model is simple, it often provides an accurate description of data generated by complex population histories. I develop statistical methods that estimate θ0 = 2uN0 , θ1 = 2uN1 , and τ = 2ut (where u is the mutation rate), and place a confidence region around these estimates. These estimators are well behaved, and insensitive to simplifying assumptions. Finally, I apply these methods to published mitochondrial data, and infer that a major expansion of the human population occurred during the late Pleistocene.

Genetic evidence for a pleistocene population explosion.

Patterns of gene differences among humans contain information about the demographic history of our species. Haploid loci like mitochondrial DNA and the nonrecombining part of the Y chromosome show a pattern indicating expansion from a population of only several thousand during the late middle or early upper Pleistocene. Nuclear short tandem repeat loci also show evidence of this expansion. Both mitochondrial DNA and the Y chromosome coalesce within the last several hundred thousand years, and they cannot provide information about the population before their coalescence. Several nuclear loci are informative about our ancestral population size during nearly the whole Pleistocene. They indicate a small effective size, on the order of 10,000 breeding individuals, throughout this time period. This genetic evidence denies any version of the multiregional model of modern human origins. It implies instead that our ancestors were effectively a separate species for most of the Pleistocene.

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Genetic traces of ancient demography

Ext. d'A.: In this paper we use a new method of analyzing mtDNA sequences that is based on a theory of how mismatch distributions -histograms of the number of pair-wise differences in the sample of DNA sequences- should preserve a record of population expansions and separations in the remote past

The Genetic Structure of Ancient Human Populations

Most social scientists would agree that the capacity for human culture was probably fashioned by natural selection, but they disagree about the implications of this supposition. Some believe that natural selection imposes important constraints on the ways in which culture can vary, while others believe that any such constraints must be negligible. This paper employs a “thought experiment” to demonstrate that neither of these positions can be justified by appeal to general properties of culture or of evolution. Natural selection can produce mechanisms of cultural transmission that are neither adaptive nor consistent with the predictions of acultural evolutionary models (those ignoring cultural evolution). On the other hand, natural selection can also produce mechanisms of cultural transmission that are highly consistent with acultural models. Thus, neither side of the sociobiology debate is justified in dismissing the arguments of the other. Natural selection may impose significant constraints on some human behaviors, but negligible constraints on others. Models of simultaneous genetic/cultural evolution will be useful in identifying domains in which acultural evolutionary models are, and are not, likely to be useful.

Alan R. Rogers

Papers

Population growth makes waves in the distribution of pairwise genetic differences.

Genetic evidence for a pleistocene population explosion.

Genetic traces of ancient demography

The Genetic Structure of Ancient Human Populations

Does Biology Constrain Culture