Using population mixtures to optimize the utility of genomic databases: linkage disequilibrium and association study design in India.

When performing association studies in populations that have not been the focus of large-scale investigations of haplotype variation, it is often helpful to rely on genomic databases in other populations for study design and analysis - such as in the selection of tag SNPs and in the imputation of missing genotypes. One way of improving the use of these databases is to rely on a mixture of database samples that is similar to the population of interest, rather than using the single most similar database sample. We demonstrate the effectiveness of the mixture approach in the application of African, European, and East Asian HapMap samples for tag SNP selection in populations from India, a genetically intermediate region underrepresented in genomic studies of haplotype variation.

A private allele ubiquitous in the Americas.

The three-wave migration hypothesis of Greenberg et al. has permeated the genetic literature on the peopling of the Americas. Greenberg et al. proposed that Na-Dene, Aleut-Eskimo and Amerind are language phyla which represent separate migrations from Asia to the Americas. We show that a unique allele at autosomal microsatellite locus D9S1120 is present in all sampled North and South American populations, including the Na-Dene and Aleut-Eskimo, and in related Western Beringian groups, at an average frequency of 31.7%. This allele was not observed in any sampled putative Asian source populations or in other worldwide populations. Neither selection nor admixture explains the distribution of this regionally specific marker. The simplest explanation for the ubiquity of this allele across the Americas is that the same founding population contributed a large fraction of ancestry to all modern Native American populations.

Empirical evaluation of genetic clustering methods using multilocus genotypes from 20 chicken breeds.

We tested the utility of genetic cluster analysis in ascertaining population structure of a large data set for which population structure was previously known. Each of 600 individuals representing 20 distinct chicken breeds was genotyped for 27 microsatellite loci, and individual multilocus genotypes were used to infer genetic clusters. Individuals from each breed were inferred to belong mostly to the same cluster. The clustering success rate, measuring the fraction of individuals that were properly inferred to belong to their correct breeds, was consistently approximately 98%. When markers of highest expected heterozygosity were used, genotypes that included at least 8-10 highly variable markers from among the 27 markers genotyped also achieved >95% clustering success. When 12-15 highly variable markers and only 15-20 of the 30 individuals per breed were used, clustering success was at least 90%. We suggest that in species for which population structure is of interest, databases of multilocus genotypes at highly variable markers should be compiled. These genotypes could then be used as training samples for genetic cluster analysis and to facilitate assignments of individuals of unknown origin to populations. The clustering algorithm has potential applications in defining the within-species genetic units that are useful in problems of conservation.

Optimal estimation of transposition rates of insertion sequences for molecular epidemiology.

Outbreaks of infectious disease can be confirmed by identifying clusters of DNA fingerprints among bacterial isolates from infected individuals. This procedure makes assumptions about the underlying properties of the genetic marker used for fingerprinting. In particular, it requires that each fingerprint changes sufficiently slowly within an individual that isolates from separate individuals infected by the same strain will exhibit similar or identical fingerprints. We propose a model for the probability that an individual's fingerprint will change over a given period of time. We use this model together with published data in order to estimate the fingerprint change rate for IS6110 in human tuberculosis, obtaining a value of 0.0139 changes per copy per year. Although we focus on insertion sequences (IS), our method applies to other fingerprinting techniques such as pulsed-field gel electrophoresis (PFGE). We suggest sampling intervals that produce the least error in estimates of the fingerprint change rate, as well as sample sizes that achieve specified levels of error in the estimate.

Distinctive genetic signatures in the Libyan Jews.

Unlinked autosomal microsatellites in six Jewish and two non-Jewish populations were genotyped, and the relationships among these populations were explored. Based on considerations of clustering, pairwise population differentiation, and genetic distance, we found that the Libyan Jewish group retains genetic signatures distinguishable from those of the other populations, in agreement with some historical records on the relative isolation of this community. Our methods also identified evidence of some similarity between Ethiopian and Yemenite Jews, reflecting possible migration in the Red Sea region. We suggest that high-resolution statistical methods that use individual multilocus genotypes may make it practical to distinguish related populations of extremely recent common ancestry.

Association mapping in structured populations.

The use, in association studies, of the forthcoming dense genomewide collection of single-nucleotide polymorphisms (SNPs) has been heralded as a potential breakthrough in the study of the genetic basis of common complex disorders. A serious problem with association mapping is that population structure can lead to spurious associations between a candidate marker and a phenotype. One common solution has been to abandon case-control studies in favor of family-based tests of association, such as the transmission/disequilibrium test (TDT), but this comes at a considerable cost in the need to collect DNA from close relatives of affected individuals. In this article we describe a novel, statistically valid, method for case-control association studies in structured populations. Our method uses a set of unlinked genetic markers to infer details of population structure, and to estimate the ancestry of sampled individuals, before using this information to test for associations within subpopulations. It provides power comparable with the TDT in many settings and may substantially outperform it if there are conflicting associations in different subpopulations.

Microsatellite evolution in modern humans: a comparison of two data sets from the same populations.

We genotyped 64 dinucleotide microsatellite repeats in individuals from populations that represent all inhabited continents. Microsatellite summary statistics are reported for these data, as well as for a data set that includes 28 out of 30 loci studied by Bowcock et al. (1994) in the same individuals. For both data sets, diversity statistics such as heterozygosity, number of alleles per locus, and number of private alleles per locus produced the highest values in Africans, intermediate values in Europeans and Asians, and low values in Americans. Evolutionary trees of populations based on genetic distances separated groups from different continents. Corresponding trees were topologically similar for the two data sets, with the exception that the (deltamu)2 genetic distance reliably distinguished groups from different continents for the larger data set, but not for the smaller one. Consistent with our results from diversity statistics and from evolutionary trees, population growth statistics S k and beta, which seem particularly useful for indicating recent and ancient population size changes, confirm a model of human evolution in which human populations expand in size and through space following the departure of a small group from Africa.

Use of unlinked genetic markers to detect population stratification in association studies.

We examine the issue of population stratification in association-mapping studies. In case-control studies of association, population subdivision or recent admixture of populations can lead to spurious associations between a phenotype and unlinked candidate loci. Using a model of sampling from a structured population, we show that if population stratification exists, it can be detected by use of unlinked marker loci. We show that the case-control-study design, using unrelated control individuals, is a valid approach for association mapping, provided that marker loci unlinked to the candidate locus are included in the study, to test for stratification. We suggest guidelines as to the number of unlinked marker loci to use.