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.

/pdf/inference-of-population-structure-using-multilocus-genotype-1x75ku6urs.pdf

Inference of population structure using multilocus genotype data

Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.

http://ibgwww.colorado.edu/cdrom2009/ScriptsA/purcell/GWAS/boulder_09_plink_intro.pdf

PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

We present here a framework for the study of molecular variation within a single species. Information on DNA haplotype divergence is incorporated into an analysis of variance format, derived from a matrix of squared-distances among all pairs of haplotypes. This analysis of molecular variance (AMOVA) produces estimates of variance components and F-statistic analogs, designated here as phi-statistics, reflecting the correlation of haplotypic diversity at different levels of hierarchical subdivision. The method is flexible enough to accommodate several alternative input matrices, corresponding to different types of molecular data, as well as different types of evolutionary assumptions, without modifying the basic structure of the analysis. The significance of the variance components and phi-statistics is tested using a permutational approach, eliminating the normality assumption that is conventional for analysis of variance but inappropriate for molecular data. Application of AMOVA to human mitochondrial DNA haplotype data shows that population subdivisions are better resolved when some measure of molecular differences among haplotypes is introduced into the analysis. At the intraspecific level, however, the additional information provided by knowing the exact phylogenetic relations among haplotypes or by a nonlinear translation of restriction-site change into nucleotide diversity does not significantly modify the inferred population genetic structure. Monte Carlo studies show that site sampling does not fundamentally affect the significance of the molecular variance components. The AMOVA treatment is easily extended in several different directions and it constitutes a coherent and flexible framework for the statistical analysis of molecular data.

/pdf/analysis-of-molecular-variance-inferred-from-metric-89hl32sg7j.pdf

Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data.

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

Two monoclonal rat anti-MHC alloantibodies detect a polymorphic determinant expressed on the peripheral lymphocytes of normal human donors. The pattern of cytotoxicity observed with these antibodies correlated with theHLA type of the individual; no HLA-A-locus specificities showed significant associations, and all of the HLA-B-locus specificities showing significant association were members of the Bw6 supertype. Family studies established that the determinant detected by the monoclonal antibodies is linked toHLA. These studies therefore provide an alternative basis for the production of monoclonal antibodies to polymorphic HLA determinants based on the conservation of polymorphic MHC determinants between man and rats.

Monoclonal rat anti-MHC alloantibodies detectHLA-linked polymorphisms in humans

Dual developments in diabetes.

Reply to “On the design and analysis of gene expression studies in human populations”

Insulin expression: is VNTR allele 698 really anomalous?

A multidisciplinary study of the Guaymi of western Panama was undertaken to confirm or disprove their apparent similarity to the Yanomama of southern Venezuela and northern Brazil, inferred from allele frequencies for six polymorphic loci studied in the Guaymi by Matson and colleagues in 1965. Gene frequencies were estimated from the present sample of 484, which is more than twice as large as the previous sample and appears to be completely independent of the latter. The findings replicate the gene frequencies obtained earlier, within the terror of resampling after a decade. Leukocytes were typed for A and B locus specificities of the HLA system in 22 Guaymi. A specificity (HLA Bw15) absent from the Yanomama is present in high frequency in the Guaymi. Elsewhere we have reported that a polymorphism of serum albumin in the Yanomama is not present in the Guaymi but that the Guaymi possess polymorphisms of acid phosphatase and lactate dehydrogenase not present in the Yanomama. These findings make any close ev...

Richard S. Spielman

Papers

Monoclonal rat anti-MHC alloantibodies detectHLA-linked polymorphisms in humans

Dual developments in diabetes.

Reply to “On the design and analysis of gene expression studies in human populations”

Insulin expression: is VNTR allele 698 really anomalous?

The Evolutionary Relationships of Two Populations: A Study of the Guaymi and the Yanomama [and Comments and Reply]