Ancient Mammalian and Plant DNA from Late Quaternary Stalagmite Layers at Solkota Cave, Georgia.

Metagenomic analysis is a highly promising technique in paleogenetic research that allows analysis of the complete genomic make-up of a sample. This technique has successfully been employed to archaeological sediments, but possible leaching of DNA through the sequence limits interpretation. We applied this technique to the analysis of ancient DNA (aDNA) from Late Quaternary stalagmites from two caves in Western Georgia, Melouri Cave and Solkota. Stalagmites form closed systems, limiting the effect of leaching, and can be securely dated with U-series. The analyses of the sequence data from the Melouri Cave stalagmite revealed potential contamination and low preservation of DNA. However, the two Solkota stalagmites preserved ancient DNA molecules of mammals (bear, roe deer, bats) and plants (chestnut, hazelnut, flax). The aDNA bearing layers from one of the two Solkota stalagmites were dated to between ~84 ka and ~56 ka BP by U-series. The second Solkota stalagmite contained excessive detrital clay obstructing U-series dating, but it also contained bear bones with a minimum age of ~50 BP uncalibrated years and ancient DNA molecules. The preservation of authentic ancient DNA molecules in Late Quaternary speleothems opens up a new paleogenetic archive for archaeological, paleontological and paleoenvironmental research.

An approximate likelihood for genetic data under a model with recombination and population splitting.

We describe a new approximate likelihood for population genetic data under a model in which a single ancestral population has split into two daughter populations. The approximate likelihood is based on the 'Product of Approximate Conditionals' likelihood and 'copying model' of Li and Stephens [Li, N., Stephens, M., 2003. Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data. Genetics 165 (4), 2213-2233]. The approach developed here may be used for efficient approximate likelihood-based analyses of unlinked data. However our copying model also considers the effects of recombination. Hence, a more important application is to loosely-linked haplotype data, for which efficient statistical models explicitly featuring non-equilibrium population structure have so far been unavailable. Thus, in addition to the information in allele frequency differences about the timing of the population split, the method can also extract information from the lengths of haplotypes shared between the populations. There are a number of challenges posed by extracting such information, which makes parameter estimation difficult. We discuss how the approach could be extended to identify haplotypes introduced by migrants.

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.

Deconstructing maize population structure.

Association studies have rarely been used in plant genetics, in part because of the risk of false positives caused by population structure. A study of flowering time in maize makes the first use of recent 'structured association' methods-statistical approaches that use independent loci to control for the effects of structure and admixture.

Are rare variants responsible for susceptibility to complex diseases?

Little is known about the nature of genetic variation underlying complex diseases in humans. One popular view proposes that mapping efforts should focus on identification of susceptibility mutations that are relatively old and at high frequency. It is generally assumed-at least for modeling purposes-that selection against complex disease mutations is so weak that it can be ignored. In this article, I propose an explicit model for the evolution of complex disease loci, incorporating mutation, random genetic drift, and the possibility of purifying selection against susceptibility mutations. I show that, for the most plausible range of mutation rates, neutral susceptibility alleles are unlikely to be at intermediate frequencies and contribute little to the overall genetic variance for the disease. Instead, it seems likely that the bulk of genetic variance underlying diseases is due to loci where susceptibility mutations are mildly deleterious and where there is a high overall mutation rate to the susceptible class. At such loci, the total frequency of susceptibility mutations may be quite high, but there is likely to be extensive allelic heterogeneity at many of these loci. I discuss some practical implications of these results for gene mapping efforts.

Linkage disequilibrium in humans: models and data.

In this review, we describe recent empirical and theoretical work on the extent of linkage disequilibrium (LD) in the human genome, comparing the predictions of simple population-genetic models to available data. Several studies report significant LD over distances longer than those predicted by standard models, whereas some data from short, intergenic regions show less LD than would be expected. The apparent discrepancies between theory and data present a challenge-both to modelers and to human geneticists-to identify which important features are missing from our understanding of the biological processes that give rise to LD. Salient features may include demographic complications such as recent admixture, as well as genetic factors such as local variation in recombination rates, gene conversion, and the potential segregation of inversions. We also outline some implications that the emerging patterns of LD have for association-mapping strategies. In particular, we discuss what marker densities might be necessary for genomewide association scans.

Genetic diversity and introgression in the Scottish wildcat.

This paper describes a genetic analysis of wild-living cats in Scotland. Samples from 230 wild-living Scottish cats (including 13 museum skins) and 74 house cats from England and Scotland were surveyed for nine microsatellite loci. Pelage characteristics of the wild-living cats were recorded, and the cats were then grouped into five separate categories depending on the degree to which they conformed to the characteristics attributed to Felis silvestris Schreber, 1775. Allele frequency differences between the morphological groups are greater than those among the three house cat samples. Analysis of genetic distances suggests that more of the differences between individuals can be explained by pelage than geographical proximity, and that pelage and geographical location are not confounded. Ordination of the genetic distances suggests two main groups of wild-living cats, with intermediates, and one group is genetically very similar to the house cats, while the other group contains all cats taxonomically identified as wildcat based on morphology. A genetic mixture analysis gives similar results to the ordination, but also suggests that the genotypes of a substantial number of cats in the wildcat group are drawn from a gene pool with genotypes in approximately equilibrium proportions. We argue that this is evidence that these cats do not have very recent domestic ancestry. However, from the morphological data it is highly likely that this gene pool also contains a contribution from earlier introgression of domestic cat genes.

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.

Case-control studies of association in structured or admixed populations.

Case-control tests for association are an important tool for mapping complex-trait genes. But population structure can invalidate this approach, leading to apparent associations at markers that are unlinked to disease loci. Family-based tests of association can avoid this problem, but such studies are often more expensive and in some cases--particularly for late-onset diseases--are impractical. In this review article we describe a series of approaches published over the past 2 years which use multilocus genotype data to enable valid case-control tests of association, even in the presence of population structure. These tests can be classified into two categories. "Genomic control" methods use the independent marker loci to adjust the distribution of a standard test statistic, while "structured association" methods infer the details of population structure en route to testing for association. We discuss the statistical issues involved in the different approaches and present results from simulations comparing the relative performance of the methods under a range of models.

Inference of population structure using multilocus genotype data.

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/ approximately pritch/home. html.

Recent common ancestry of human Y chromosomes: evidence from DNA sequence data.

We consider a data set of DNA sequence variation at three Y chromosome genes (SMCY, DBY, and DFFRY) in a worldwide sample of human Y chromosomes. Between 53 and 70 chromosomes were fully screened for sequence variation at each locus by using the method of denaturing high-performance liquid chromatography. The sum of the lengths of the three genes is 64,120 bp. We have used these data to study the ancestral genealogy of human Y chromosomes. In particular, we focused on estimating the expected time to the most recent common ancestor and the expected ages of certain mutations with interesting geographic distributions. Although the geographic structure of the inferred haplotype tree is reminiscent of that obtained for other loci (the root is in Africa, and most of the oldest non-African lineages are Asian), the expected time to the most recent common ancestor is remarkably short, on the order of 50,000 years. Thus, although previous studies have noted that Y chromosome variation shows extreme geographic structure, we estimate that the spread of Y chromosomes out of Africa is much more recent than previously was thought. We also show that our data indicate substantial population growth in the effective number of human Y chromosomes.

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.

DNA analysis in a paternity case involving a triploid fetus.

BACKGROUND: A parentage testing laboratory was asked to perform testing in a case of sexual assault that resulted in the conception of a child. Samples submitted to the laboratory included blood from the mother, the alleged father, and the fetus. CASE REPORT: DNA typing was used to determine if the suspect in this sexual assault was the father of the expected child. DNA extracted from these samples was subjected to both restriction fragment length polymorphism and polymerase chain reaction/short-tandem repeat analysis at a total of 13 genetic loci. Examination of DNA profiles for selected markers suggested that the fetus was triploid. Triploidy was confirmed through the use of fluorescent in situ hybridization of chromosomes, employing three chromosome-specific alpha satellite probes and fetal trophoblast nuclei. Statistical interpretation of the test results required identifying a method for calculation that would consider two transmitted paternal genes. Attempts to modify the standard method of calculating a paternity index were unsuccessful, because it was not possible to distinguish between dispermy and diandry as the mechanism of conception. Therefore, the likelihood ratio was calculated as the reciprocal of the random men not excluded value or the proportion of the population that possesses all of the paternal markers observed in the triploid fetus. CONCLUSION: Calculation of a likelihood ratio employing the exclusionary power of a collection of DNA markers appears to be the only method suitable for assigning weight to the significance of DNA matches between an alleged father and a child who is triploid.

Population growth of human Y chromosomes: a study of Y chromosome microsatellites.

We use variation at a set of eight human Y chromosome microsatellite loci to investigate the demographic history of the Y chromosome. Instead of assuming a population of constant size, as in most of the previous work on the Y chromosome, we consider a model which permits a period of recent population growth. We show that for most of the populations in our sample this model fits the data far better than a model with no growth. We estimate the demographic parameters of this model for each population and also the time to the most recent common ancestor. Since there is some uncertainty about the details of the microsatellite mutation process, we consider several plausible mutation schemes and estimate the variance in mutation size simultaneously with the demographic parameters of interest. Our finding of a recent common ancestor (probably in the last 120,000 years), coupled with a strong signal of demographic expansion in all populations, suggests either a recent human expansion from a small ancestral population, or natural selection acting on the Y chromosome.

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.

Risky business: sexual and asexual reproduction in variable environments.

Patterns of reproductive uncertainty can have an important influence on population dynamics. There is a crucial distinction between what we describe here as aggregate uncertainty (in which reproductive output in each generation is correlated among the individuals in a population) and idiosyncratic risk (in which reproductive output is independent across individuals). All else being equal, populations experiencing idiosyncratic risk enjoy a higher asymptotic growth rate than do those experiencing aggregate uncertainty. Therefore individuals in populations of the former type will have a competitive advantage over individuals in populations of the latter type. Applying this distinction to models of randomly fluctuating environments, we point out that genetic variation among offspring can serve to reduce aggregate uncertainty, transforming it into a more idiosyncratic form of risk. We show that this transformation underlies the dynamics observed in several previous models of the role of outcrossing in the evolution of sex.

Polymorphism and divergence at a Drosophila pseudogene locus.

The larval cuticle protein (Lcp) cluster in Drosophila melanogaster contains four functional genes and a closely related pseudogene. A 630-bp fragment including the larval cuticle pseudogene locus (Lcp psi) was nucleotide sequenced in 10 strains of D. melanogaster and a 458-bp Lcp psi fragment from D. simulans was also sequenced. We used these data to test the hypotheses that the rates of synonymous and nonsynonymous substitution are equal, that the absolute levels of variation are higher than in functional genes, and that intraspecific polymorphism is correlated with interspecific divergence. As predicted, synonymous and nonsynonymous substitution rates were equivalent, and overall nucleotide divergence between D. melanogaster and D. simulans (Jukes-Cantor distance = 0.149 +/- 0.150) was extremely high. However, within-species DNA sequence comparisons at Lcp psi revealed lower levels of polymorphism (theta = 0.001 +/- 0.001) than at many functional loci in D. melanogaster. Using the HUDSON, KREITMAN, and AGUADE (HKA) test, we show that the level of polymorphism in Lcp psi within D. melanogaster is lower than expected given the amount of divergence between D. melanogaster and D. simulans when the pseudogene data are compared to the Adh 5' flanking region. Because the Lcp psi lies in a region of relatively infrequent recombination, we suggest that the low level of within-species polymorphism is the result of background selection.

Statistics for microsatellite variation based on coalescence.

The stepwise mutation model, which was at one time chiefly of interest in studying the evolution of protein charge-states, has recently undergone a resurgence of interest with the new popularity of microsatellites as phylogenetic markers. In this paper we describe a method which makes it possible to transfer many population genetics results from the standard infinite sites model to the stepwise mutation model. We study in detail the properties of pairwise differences in microsatellite repeat number between randomly chosen alleles. We show that the problem of finding the expected squared distance between two individuals and finding the variance of the squared distance can be reduced for a wide range of population models to finding the mean and mean square coalescence times. In many cases the distributions of coalescence times have already been studied for infinite site problems. In this study we show how to calculate these quantities for several population models. We also calculate the variance in mean squared pairwise distance (an estimator of mutation rate x population size) for samples of arbitrary size and show that this variance does not approach zero as the sample size increases. We can also use our method to study alleles at linked microsatellite loci. We suggest a metric which quantifies the level of association between loci-effectively a measure of linkage disequilibrium. It is shown that there can be linkage disequilibrium between partially linked loci at mutation-drift equilibrium.