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

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

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

Scientists working with large volumes of high-dimensional data, such as global climate patterns, stellar spectra, or human gene distributions, regularly confront the problem of dimensionality reduction: finding meaningful low-dimensional structures hidden in their high-dimensional observations. The human brain confronts the same problem in everyday perception, extracting from its high-dimensional sensory inputs-30,000 auditory nerve fibers or 10(6) optic nerve fibers-a manageably small number of perceptually relevant features. Here we describe an approach to solving dimensionality reduction problems that uses easily measured local metric information to learn the underlying global geometry of a data set. Unlike classical techniques such as principal component analysis (PCA) and multidimensional scaling (MDS), our approach is capable of discovering the nonlinear degrees of freedom that underlie complex natural observations, such as human handwriting or images of a face under different viewing conditions. In contrast to previous algorithms for nonlinear dimensionality reduction, ours efficiently computes a globally optimal solution, and, for an important class of data manifolds, is guaranteed to converge asymptotically to the true structure.

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A global geometric framework for nonlinear dimensionality reduction.

We present here a new version of the Arlequin program available under three different forms: a Windows graphical version (Winarl35), a console version of Arlequin (arlecore), and a specific console version to compute summary statistics (arlsumstat). The command-line versions run under both Linux and Windows. The main innovations of the new version include enhanced outputs in XML format, the possibility to embed graphics displaying computation results directly into output files, and the implementation of a new method to detect loci under selection from genome scans. Command-line versions are designed to handle large series of files, and arlsumstat can be used to generate summary statistics from simulated data sets within an Approximate Bayesian Computation framework.

Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows

Acceptance of the theory of evolution as the means of explaining observed similarities and differences among organisms invites the construction of trees of descent purporting to show evolutionary relationships. Whether such trees are based on fossil or living specimens, they may often be criticized for having a high subjective element. The purpose of this paper is to show how suitable evolutionary models can be constructed and applied objectively. In it we amplify and extend the methods we have given in previous communications (Edwards and Cavalli-Sforza, 1963a, b, 1964, 1965; Cavalli-Sforza and Edwards, 1964, 1966; Cavalli-Sforza, Barrai and Edwards, 1964; Cavalli-Sforza, 1966). Considering the great variety of information provided by living organisms, it is clear that the type of data will affect both the method of treatment and the validity of the results: the higher the correlation of data and genotype, the greater is the validity likely to be. Information on nucleic acid and protein structure comes first in the scale of relevance, and that on phenotypic measurements last; discrete and continuous variation demand different treatments, and evolutionary models appropriate to both cases will therefore be required for estimation purposes. Differences which are the result of mutation are formally discrete, and evolution a t the molecular level thus needs discontinuous treatment; but even in this case the limit of observation may turn the data into the

Phylogenetic analysis. Models and estimation procedures.

The history and geography of human genes

The History and Geography of Human Genes.

A number of scholars have found that concepts such as mutation, selection, and random drift, which emerged from the theory of biological evolution, may also explain evolutionary phenomena in other disciplines as well. Drawing on these concepts, Professors Cavalli-Sforza and Feldman classify and systematize the various modes of transmitting "culture" and explore their consequences for cultural evolution. In the process, they develop a mathematical theory of the non-genetic transmission of cultural traits that provides a framework for future investigations in quantitative social and anthropological science. The authors use quantitative models that incorporate the various modes of transmission (for example, parent-child, peer-peer, and teacher-student), and evaluate data from sociology, archaeology, and epidemiology in terms of the models. They show that the various modes of transmission in conjunction with cultural and natural selection produce various rates of cultural evolution and various degrees of diversity within and between groups. The same framework can be used for explaining phenomena as apparently unrelated as linguistics, epidemics, social values and customs, and diffusion of innovations. The authors conclude that cultural transmission is an essential factor in the study of cultural change.

Cultural transmission and evolution: a quantitative approach

Human genetic diversity is shaped by both demographic and biological factors and has fundamental implications for understanding the genetic basis of diseases. We studied 938 unrelated individuals from 51 populations of the Human Genome Diversity Panel at 650,000 common single-nucleotide polymorphism loci. Individual ancestry and population substructure were detectable with very high resolution. The relationship between haplotype heterozygosity and geography was consistent with the hypothesis of a serial founder effect with a single origin in sub-Saharan Africa. In addition, we observed a pattern of ancestral allele frequency distributions that reflects variation in population dynamics among geographic regions. This data set allows the most comprehensive characterization to date of human genetic variation.

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Luigi Luca Cavalli-Sforza

Papers

Phylogenetic analysis. Models and estimation procedures.

The history and geography of human genes

The History and Geography of Human Genes.

Cultural transmission and evolution: a quantitative approach

Worldwide human relationships inferred from genome-wide patterns of variation.