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

Multiple sclerosis (MS) is a human demyelinating disease. The etiology is unknown, but evidence suggests that a genetic component influences MS susceptibility. In studies of monozygotic twins, Ebers et al. I observed a concordance rate for the development of MS of approximately 26%. Various studies suggest that the rate may be even higher. Dizygotic twins and nontwin siblings, however, displayed a much lower concordance rate of approximately 2%. Spielman and Nathanson' noted an association between MS and certain human leukocyte antigen (HLA) types, especially HLA-DR2. It is of interest to examine the HLA class I1 region more closely to identify polymorphisms associated with susceptibility to MS. One method of studying genetic variation is to examine restriction fragment length polymorphisms (RFLPs). Analyses at the molecular level offer several advantages over serologic comparisons. Because the number of serologically defined haplotypes is currently limited, RFLPs can provide superior, highly sensitive indicators of the complexity of HLA genes. Furthermore, they may be used to study genes encoding proteins that are not expressed on the cell surface or to identify underlying differences that are silent at the protein level. In MS, RFLPs may be used to identify a polymorphism more closely associated with MS than is the serologically defined HLA-DR2 phenotype. In this study, DNA from MS-affected or control individuals was examined for the presence of RFLPs, in linkage disequilibrium with MS, detected by HLA class I1 cDNA probes. The approach taken here was to pool DNA samples from approximately 50 affected or control individuals matched for HLA-DR type and ethnic origin. Pooled DNA was digested with restriction endonucleases; the fragments were separated by agarose gel electrophoresis and transferred to GeneScreenPhs or Genentran membranes. These blots were probed with D R beta or DQ beta cDNAs and then examined for evidence of RFLPs in linkage disequilibrium with MS. Pooling of DNA is a powerful technique, allowing rapid, simultaneous screening of many individuals. The

Determination of RFLPs Linked to Multiple Sclerosis Susceptibility

Meiotic recombination plays an important role in reproduction and evolution. The individual global recombination rate (GRR), measured as the number of crossovers (CO) per gametes, is a complex trait that has been shown to be heritable. The sex chromosomes play an important role in reproduction and fertility related traits. Therefore, variants present on the X-chromosome might have a high contribution to the genetic variation of GRR that is related to meiosis and to reproduction.We herein used genotyping data from 58,474 New Zealand dairy cattle to estimate the contribution of the X-chromosome to male and female GRR levels. Based on the pedigree-based relationships, we first estimated that the X-chromosome accounted for 30% of the total additive genetic variance for male GRR. This percentage was equal to 19.9% when the estimation relied on a SNP-BLUP approach assuming each SNP has a small contribution. We then carried out a haplotype-based association study to map X-linked QTL, and subsequently fine-mapped the identified QTL with imputed sequence variants. With this approach we identified three QTL with large effect accounting for 7.7% of the additive genetic variance of male GRR. The associated effects were equal to + 0.79, - 1.16 and + 1.18 CO for the alternate alleles. In females, the estimated contribution of the X-chromosome to GRR was null and no significant association with X-linked loci was found. Interestingly, two of the male GRR QTL were associated with candidate genes preferentially expressed in testis, in agreement with a male-specific effect. Finally, the most significant QTL was associated with PPP4R3C, further supporting the important role of protein phosphatase in double-strand break repair by homologous recombination.Our study illustrates the important role the X-chromosome can have on traits such as individual recombination rate, associated with testis in males. We also show that contribution of the X-chromosome to such a trait might be sex dependent. 

/pdf/high-male-specific-contribution-of-the-x-chromosome-to-296ukysc.pdf

High male specific contribution of the X-chromosome to individual global recombination rate in dairy cattle

https://www.neurologic.theclinics.com/article/S0733-8619(02)00003-8/pdf

Bridging genetics and genomics in neurology.

Summary A population association hasconsistently beenobserved between insulin-dependent diabetes mellitus (IDDM) andthe"class 1"alleles oftheregion oftandem-repeat DNA (5' flanking polymorphism [5'FP]) adjacent tothe insulin gene on chromosome 11p.Thisfinding suggeststhat theinsulin generegion contains a geneor genes contributing toIDDMsusceptibility. However, several studies that havesought toshowlinkage withIDDMby testing forcosegregation inaffected sibpairs havefailed tofind evidence forlinkage. Asmeans foridentifying genesforcomplex diseases, boththeassociation andtheaffected-sib-pairs approaches havelimitations. Itis wellknownthat population association between a disease anda genetic marker canarise asan artifact of population structure, evenintheabsence oflinkage. Ontheother hand, linkage studies withmodest numbers ofaffected sibpairs may fail todetect linkage, especially ifthere islinkage heterogeneity. We consider an alternative method totestforlinkage with agenetic marker whenpopulation association hasbeenfound. Using datafromfamilies with atleast oneaffected child, we evaluate thetransmission oftheassociated marker allele from aheterozygous parenttoan affected offspring. Thisapproach hasbeenusedbyseveral investigators, but thestatistical properties ofthemethod asa testforlinkage have notbeeninvestigated. Inthepresent paperwe describe thestatistical basis forthis "transmission testforlinkage disequilibrium" (transmission/disequilibrium test[TDT]). Wethenshowtherelationship ofthis testtotestsofcosegregation that arebased on theproportion ofhaplotypes or genesidentical bydescent inaffected sibs. TheTDT provides strongevidence forlinkage between the5TPandsusceptibility toIDDM.Theconclusions fromthis analysis apply ingeneral tothestudy ofdisease associations, wheregenetic markers areusually closely linked tocandidate genes.Whena disease is found tobeassociated withsuch a marker, theTDT may detect linkage even whenhaplotype-sharing tests donot.

https://courses.washington.edu/b516/articles_2009/TDT.pdf

Transmission TestforLinkage Disequilibrium: TheInsulin GeneRegionandInsulin-dependent Diabetes Mellitus (IDDM)

Genes that contribute to complex genetic diseases can sometimes be identified by studies that show genetic linkage, or association, with marker genes. The transmission/disequilibrium test is a procedure that tests for the simultaneous presence of these two genetic phenomena.


Keywords:

linkage disequilibrium;
linkage;
association;
transmission/ disequilibrium test;
family-based tests

Richard S. Spielman

Papers

Determination of RFLPs Linked to Multiple Sclerosis Susceptibility

High male specific contribution of the X-chromosome to individual global recombination rate in dairy cattle

Bridging genetics and genomics in neurology.

Transmission TestforLinkage Disequilibrium: TheInsulin GeneRegionandInsulin-dependent Diabetes Mellitus (IDDM)

Relatives‐based Test for Linkage Disequilibrium: The Transmission/Disequilibrium Test (TDT)