Support from the relationship of genetic and geographic distance in human populations for a serial founder effect originating in Africa

Molecular biogeography: towards an integrated framework for conserving pan-African biodiversity

BACKGROUND

Biogeographic models partition ecologically similar species assemblages into discrete ecoregions. However, the history, relationship and interactions between these regions and their assemblages have rarely been explored.

METHODOLOGY/PRINCIPAL FINDINGS

Here we develop a taxon-based approach that explicitly utilises molecular information to compare ecoregion history and status, which we exemplify using a continentally distributed mammalian species: the African bushbuck (Tragelaphus scriptus). We reveal unprecedented levels of genetic diversity and structure in this species and show that ecoregion biogeographic history better explains the distribution of molecular variation than phenotypic similarity or geography. We extend these data to explore ecoregion connectivity, identify core habitats and infer ecological affinities from them.

CONCLUSIONS/SIGNIFICANCE

This analysis defines 28 key biogeographic regions for sub-Saharan Africa, and provides a valuable framework for the incorporation of genetic and biogeographic information into a more widely applicable model for the conservation of continental biodiversity.

Mitochondrial DNA phylogeography and mating compatibility reveal marked genetic structuring and speciation in the NE Atlantic bryozoan Celleporella hyalina

The marine bryozoan Celleporella hyalina is a species complex composed of many highly divergent and mostly allopatric genetic lineages that are reproductively isolated but share a remarkably similar morphology. One such lineage commonly encrusts macroalgae throughout the NE Atlantic coast. To explore the processes leading to geographical diversification, reproductive isolation and speciation in this taxon, we (i) investigated NE Atlantic C. hyalina mitochondrial DNA phylogeography, and (ii) used breeding trials between geographical isolates to ascertain reproductive isolation. We find that haplotype diversity is geographically variable and there is a strong population structure, with significant isolation by distance. NE Atlantic C. hyalina is structured into two main parapatric lineages that appear to have had independent Pleistocene histories. Range expansions have resulted in two contact zones in Spain and W Ireland. Lineage 1 is found from Ireland to Spain and has low haplotype diversity, with closely related haplotypes, suggesting a recent population expansion into the Irish Sea, S Ireland, S England and Spain. Lineage 2 is found from Iceland to Spain and has high haplotype diversity. Complete reproductive isolation was found between some geographical isolates representing both lineages, whereas it was incomplete or asymmetric between others, suggesting these latter phylogeographical groups probably represent incipient species. The phylogeographical distribution of NE Atlantic C. hyalina does not fall easily into a pattern of southern refugia, and we discuss likely differences between terrestrial and marine system responses to Pleistocene glacial cycles.

BRCA1 and BRCA2 status in a Central Sudanese series of breast cancer patients: interactions with genetic, ethnic and reproductive factors

The etiology of breast cancer in Africa is scarcely investigated. Breast cancer was responsible for 456/2,233 cancer patients (20.4%) ascertained between 1999 and 2004 at Gezira University, Central Sudan. Male breast cancer accounted for 16/456 patients (3.5%), 275/440 female patients (62.5%) were premenopausal and 150/440 cases (34%) occurred in women with > or =5 childbirths. We characterized for germline BRCA1/2 mutations a one-year series of patients (34 females, 1 male) selected by diagnosis within age 40 years or male gender. Overall 33/35 patients were found to carry 60 BRCA1/2 variants, of which 17 (28%) were novel, 22 (37%) reported in populations from various geographic areas and 21 (35%) reported worldwide. Detected variants included 5 truncating mutations, one of which (in BRCA2) was in the male patient. The 55 non-truncating variants included 3 unclassified variants predicted to affect protein product and not co-occurring with a truncating mutation in the same gene. Patients were from different tribes but AMOVA showed that most BRCA1/2 variation was within individuals (86.41%) and patients clustered independently of tribe in a phylogenetic tree. Cluster analysis based on age at cancer diagnosis and reproductive variables split female patients in two clusters that, by factor analysis, were explained by low versus high scores of the total period occupied by pregnancies and lactation. The cluster with low scores comprised all 4 patients with truncating mutations and 3 of the 4 carriers of unclassified variants predicted to affect protein product. Our findings suggest that in Central Sudan BRCA1/2 represent an important etiological factor of breast cancer in males and young women less exposed to pregnancy and lactation. Factors other than BRCA1/2 may contribute to breast cancer in young highly multiparous women who breast-fed for prolonged periods.

Generalized analysis of molecular variance

Many studies in the fields of genetic epidemiology and applied population genetics are predicated on, or require, an assessment of the genetic background diversity of the individuals chosen for study. A number of strategies have been developed for assessing genetic background diversity. These strategies typically focus on genotype data collected on the individuals in the study, based on a panel of DNA markers. However, many of these strategies are either rooted in cluster analysis techniques, and hence suffer from problems inherent to the assignment of the biological and statistical meaning to resulting clusters, or have formulations that do not permit easy and intuitive extensions. We describe a very general approach to the problem of assessing genetic background diversity that extends the analysis of molecular variance (AMOVA) strategy introduced by Excoffier and colleagues some time ago. As in the original AMOVA strategy, the proposed approach, termed generalized AMOVA (GAMOVA), requires a genetic similarity matrix constructed from the allelic profiles of individuals under study and/or allele frequency summaries of the populations from which the individuals have been sampled. The proposed strategy can be used to either estimate the fraction of genetic variation explained by grouping factors such as country of origin, race, or ethnicity, or to quantify the strength of the relationship of the observed genetic background variation to quantitative measures collected on the subjects, such as blood pressure levels or anthropometric measures. Since the formulation of our test statistic is rooted in multivariate linear models, sets of variables can be related to genetic background in multiple regression-like contexts. GAMOVA can also be used to complement graphical representations of genetic diversity such as tree diagrams (dendrograms) or heatmaps. We examine features, advantages, and power of the proposed procedure and showcase its flexibility by using it to analyze a wide variety of published data sets, including data from the Human Genome Diversity Project, classical anthropometry data collected by Howells, and the International HapMap Project.

Humans exhibit great genetic diversity. Understanding the factors that contribute to and sustain this diversity is an important research area. Not only can such understanding shed light on human origins, but it can also assist in the discovery of genes and genetic factors that contribute to debilitating diseases. Statistical analysis methods that can facilitate the identification of factors contributing to or associated with human genetic diversity are growing in number as new high-throughput molecular genetic assays and technologies are developed. We consider the use of an analysis method termed generalized analysis of molecular variance (GAMOVA), which builds off of previously proposed analysis methods for testing hypotheses about the factors associated with genetic background diversity. We apply the method in a wide variety of settings and show that it is both flexible and powerful. GAMOVA has great potential to assist in population-based human genetic studies, as it can be used to address questions such as: Is a sample of affected cases and unaffected controls from a homogeneous population, or is there evidence of heterogeneity that could affect the results of an association study? Is there reason to believe that the ancestry of a set of individuals influences the traits that they have?

An African origin for the intimate association between humans and Helicobacter pylori

Infection of the stomach by Helicobacter pylori is ubiquitous among humans. However, although H. pylori strains from different geographic areas are associated with clear phylogeographic differentiation, the age of an association between these bacteria with humans remains highly controversial. Here we show, using sequences from a large data set of bacterial strains that, as in humans, genetic diversity in H. pylori decreases with geographic distance from east Africa, the cradle of modern humans. We also observe similar clines of genetic isolation by distance (IBD) for both H. pylori and its human host at a worldwide scale. Like humans, simulations indicate that H. pylori seems to have spread from east Africa around 58,000 yr ago. Even at more restricted geographic scales, where IBD tends to become blurred, principal component clines in H. pylori from Europe strongly resemble the classical clines for Europeans described by Cavalli-Sforza and colleagues. Taken together, our results establish that anatomically modern humans were already infected by H. pylori before their migrations from Africa and demonstrate that H. pylori has remained intimately associated with their human host populations ever since.

An African origin for the intimate association between humans and Helicobacter pylori

Infection of the stomach by Helicobacter pylori is ubiquitous among humans. However, although H. pylori strains from different geographic areas are associated with clear phylogeographic differentiation, the age of an association between these bacteria with humans remains highly controversial. Here we show, using sequences from a large data set of bacterial strains that, as in humans, genetic diversity in H. pylori decreases with geographic distance from east Africa, the cradle of modern humans. We also observe similar clines of genetic isolation by distance (IBD) for both H. pylori and its human host at a worldwide scale. Like humans, simulations indicate that H. pylori seems to have spread from east Africa around 58,000 yr ago. Even at more restricted geographic scales, where IBD tends to become blurred, principal component clines in H. pylori from Europe strongly resemble the classical clines for Europeans described by Cavalli-Sforza and colleagues. Taken together, our results establish that anatomically modern humans were already infected by H. pylori before their migrations from Africa and demonstrate that H. pylori has remained intimately associated with their human host populations ever since.

Signatures of positive selection in genes associated with human skin pigmentation as revealed from analyses of single nucleotide polymorphisms

Phenotypic variation between human populations in skin pigmentation correlates with latitude at the continental level. A large number of hypotheses involving genetic adaptation have been proposed to explain human variation in skin colour, but only limited genetic evidence for positive selection has been presented. To shed light on the evolutionary genetic history of human variation in skin colour we inspected 118 genes associated with skin pigmentation in the Perlegen dataset, studying single nucleotide polymorphisms (SNPs), and analyzed 55 genes in detail. We identified eight genes that are associated with the melanin pathway (SLC45A2, OCA2, TYRP1, DCT, KITLG, EGFR, DRD2 and PPARD) and presented significant differences in genetic variation between Europeans, Africans and Asians. In six of these genes we detected, by means of the EHH test, variability patterns that are compatible with the hypothesis of local positive selection in Europeans (OCA2, TYRP1 and KITLG) and in Asians (OCA2, DCT, KITLG, EGFR and DRD2), whereas signals were scarce in Africans (DCT, EGFR and DRD2). Furthermore, a statistically significant correlation between genotypic variation in four pigmentation candidate genes and phenotypic variation of skin colour in 51 worldwide human populations was revealed. Overall, our data also suggest that light skin colour is the derived state and is of independent origin in Europeans and Asians, whereas dark skin color seems of unique origin, reflecting the ancestral state in humans.

Ascertainment Bias and the Pattern of Nucleotide Diversity at the Human ALDH2 Locus in a Japanese Population

Many East Asian human populations harbor a high-frequency deficiency allele for the aldehyde dehydrogenase 2 (ALDH2) enzyme, a critical protein involved in the metabolism of ethanol. Here we use resequencing and long-range SNP haplotype data from a Japanese sample to test whether patterns of nucleotide diversity and linkage disequilibrium at this locus are compatible with a standard neutral model of evolution. Examination of the pattern of polymorphism at a locus such as this, where the frequency of a common allele is known a priori, introduces an ascertainment bias that must be corrected for in analyses of the frequency spectrum of polymorphisms. We apply a flexible and generally applicable simulation approach to correct for this bias in our ALDH2 data and, also, to explore the effect of bias on the commonly used summary statistics Tajima's D, Fu and Li's D, and Fay and Wu's H. Our study finds no evidence that the pattern of genetic variation at ALDH2 differs from that expected under a standard neutral model. However, our general examination of ascertainment bias indicates that a priori knowledge of segregating alleles greatly affects the expected distributions of summary statistics. Under many parameter combinations we find that ascertainment bias introduces an elevated rate of false positives when summary statistics are used to test for deviations from a standard neutral model. However, we also show that over a wide range of conditions the power of all summary statistics can be greatly increased by incorporating prior knowledge of segregating alleles.

Genetic, geographic, and environmental correlates of human temporal bone variation

Temporal bone shape has been shown to reflect molecular phylogenetic relationships among hominoids and offers significant morphological detail for distinguishing taxa. Although it is generally accepted that temporal bone shape, like other aspects of morphology, has an underlying genetic component, the relative influence of genetic and environmental factors is unclear. To determine the impact of genetic differentiation and environmental variation on temporal bone morphology, we used three-dimensional geometric morphometric techniques to evaluate temporal bone variation in 11 modern human populations. Population differences were investigated by discriminant function analysis, and the strength of the relationships between morphology, neutral molecular distance, geographic distribution, and environmental variables were assessed by matrix correlation comparisons. Significant differences were found in temporal bone shape among all populations, and classification rates using cross-validation were relatively high. Comparisons of morphological distances to molecular distances based on short tandem repeats (STRs) revealed a significant correlation between temporal bone shape and neutral molecular distance among Old World populations, but not when Native Americans were included. Further analyses suggested a similar pattern for morphological variation and geographic distribution. No significant correlations were found between temporal bone shape and environmental variables: temperature, annual rainfall, latitude, or altitude. Significant correlations were found between temporal bone size and both temperature and latitude, presumably reflecting Bergmann's rule. Thus, temporal bone morphology appears to partially follow an isolation by distance model of evolution among human populations, although levels of correlation show that a substantial component of variation is unexplained by factors considered here.

Worldwide analysis of multiple microsatellites: Language diversity has a detectable influence on DNA diversity

Previous studies of the correlations between the languages spoken by human populations and the genes carried by the members of those populations have been limited by the small amount of genetic markers available and by approximations in the treatment of linguistic data. In this study we analyzed a large collection of polymorphic microsatellite loci (377), distributed on all autosomes, and used Ruhlen's linguistic classification, to investigate the relative roles of geography and language in shaping the distribution of human DNA diversity at a worldwide scale. For this purpose, we performed three different kinds of analysis: (i) we partitioned genetic variances at three hierarchical levels of population subdivision according to language group by means of a molecular analysis of variance (AMOVA); (ii) we quantified by a series of Mantel's tests the correlation between measures of genetic and linguistic differentiation; and (iii) we tested whether linguistic differences are increased across known zones of increased genetic change between populations. Genetic differences appear to more closely reflect geographic than linguistic differentiation. However, our analyses show that language differences also have a detectable effect on DNA diversity at the genomic level, above and beyond the effects of geographic distance.

Standardized subsets of the HGDP-CEPH Human Genome Diversity Cell Line Panel, accounting for atypical and duplicated samples and pairs of close relatives

The HGDP-CEPH Human Genome Diversity Cell Line Panel is a widely-used resource for studies of human genetic variation. Here, pairs of close relatives that have been included in the panel are identified. Together with information on atypical and duplicated samples, the inferred relative pairs suggest standardized subsets of the panel for use in future population-genetic studies.

Population structure and eigenanalysis

Current methods for inferring population structure from genetic data do not provide formal significance tests for population differentiation. We discuss an approach to studying population structure (principal components analysis) that was first applied to genetic data by Cavalli-Sforza and colleagues. We place the method on a solid statistical footing, using results from modern statistics to develop formal significance tests. We also uncover a general "phase change" phenomenon about the ability to detect structure in genetic data, which emerges from the statistical theory we use, and has an important implication for the ability to discover structure in genetic data: for a fixed but large dataset size, divergence between two populations (as measured, for example, by a statistic like FST) below a threshold is essentially undetectable, but a little above threshold, detection will be easy. This means that we can predict the dataset size needed to detect structure.

Population structure and eigenanalysis

Current methods for inferring population structure from genetic data do not provide formal significance tests for population differentiation. We discuss an approach to studying population structure (principal components analysis) that was first applied to genetic data by Cavalli-Sforza and colleagues. We place the method on a solid statistical footing, using results from modern statistics to develop formal significance tests. We also uncover a general "phase change" phenomenon about the ability to detect structure in genetic data, which emerges from the statistical theory we use, and has an important implication for the ability to discover structure in genetic data: for a fixed but large dataset size, divergence between two populations (as measured, for example, by a statistic like FST) below a threshold is essentially undetectable, but a little above threshold, detection will be easy. This means that we can predict the dataset size needed to detect structure.

Genetic population structure and contemporary dispersal patterns of a recent European invader, the Chinese mitten crab, Eriocheir sinensis

Genetic studies of recently established populations are challenging because the assumption of equilibrium underlying many analyses is likely to be violated. Using microsatellites, we investigated determinants of genetic structure and migration among invasive European-Chinese mitten crab populations, applying a combination of traditional population genetic analyses and nonequilibrium Bayesian methods. Consistent with their recent history, invasive populations showed much lower levels of genetic diversity than a native Chinese population, indicative of recent bottlenecks. Population differentiation was generally low but significant and especially pronounced among recently established populations. Significant differentiation among cohorts from the same geographical location (River Thames) suggests the low effective population size and associated strong genetic drift that would be anticipated from a very recent colonization. An isolation-by-distance pattern appears to be driven by an underlying correlation between geographical distance and population age, suggesting that cumulative homogenizing gene flow reduces founder bottleneck-associated genetic differentiation between longer-established populations. This hypothesis was supported by a coalescent analysis, which supported a drift + gene flow model as more likely than a model excluding gene flow. Furthermore, admixture analysis identified several recent migrants between the UK and Continental European population clusters. Admixture proportions were significantly predicted by the volume of shipping between sites, indicating that human-mediated transport remains a significant factor for dispersal of mitten crabs after the initial establishment of populations. Our study highlights the value of nonequilibrium methods for the study of invasive species, and also the importance of evaluating nonequilibrium explanations for isolation by distance patterns.

African human diversity, origins and migrations

The continent of Africa is thought to be the site of origin of all modern humans and is the more recent origin of millions of African Americans. Although Africa has the highest levels of human genetic diversity both within and between populations, it is under-represented in studies of human genetics. Recent advances have been made in understanding the origins of modern humans within Africa, the rate of adaptations due to positive selection, the routes taken in the first migrations of modern humans out of Africa, and the degree of admixture with archaic populations. Africa is also in dire need of effective medical interventions, and studies of genetic variation in Africans will shed light on the genetic basis of diseases and resistance to infectious diseases. Thus, we have tremendous potential to learn about human variation and evolutionary history and to positively impact human health care from studies of genetic diversity in Africa.

A worldwide survey of haplotype variation and linkage disequilibrium in the human genome

Recent genomic surveys have produced high-resolution haplotype information, but only in a small number of human populations. We report haplotype structure across 12 Mb of DNA sequence in 927 individuals representing 52 populations. The geographic distribution of haplotypes reflects human history, with a loss of haplotype diversity as distance increases from Africa. Although the extent of linkage disequilibrium (LD) varies markedly across populations, considerable sharing of haplotype structure exists, and inferred recombination hotspot locations generally match across groups. The four samples in the International HapMap Project contain the majority of common haplotypes found in most populations: averaging across populations, 83% of common 20-kb haplotypes in a population are also common in the most similar HapMap sample. Consequently, although the portability of tag SNPs based on the HapMap is reduced in low-LD Africans, the HapMap will be helpful for the design of genome-wide association mapping studies in nearly all human populations.

Population genetics models of common diseases

The number and frequency of susceptibility alleles for common diseases are important factors to consider in the efficient design of disease association studies. These quantities are the results of the joint effects of mutation, genetic drift and selection. Hence, population genetics models, informed by empirical knowledge about patterns of disease variation, can be used to make predictions about the allelic architecture of common disease susceptibility and to gain an overall understanding about the evolutionary origins of such diseases. Equilibrium models and empirical studies suggest a role for both rare and common variants. In addition, increasing evidence points to changes in selective pressures on susceptibility genes for common diseases; these findings are likely to form the basis for further modeling studies.

Human population genetic structure and diversity inferred from polymorphic L1(LINE-1) and Alu insertions

BACKGROUND/AIMS

The L1 retrotransposable element family is the most successful self-replicating genomic parasite of the human genome. L1 elements drive replication of Alu elements, and both have had far-reaching impacts on the human genome. We use L1 and Alu insertion polymorphisms to analyze human population structure.

METHODS

We genotyped 75 recent, polymorphic L1 insertions in 317 individuals from 21 populations in sub-Saharan Africa, East Asia, Europe and the Indian subcontinent. This is the first sample of L1 loci large enough to support detailed population genetic inference. We analyzed these data in parallel with a set of 100 polymorphic Alu insertion loci previously genotyped in the same individuals.

RESULTS AND CONCLUSION

The data sets yield congruent results that support the recent African origin model of human ancestry. A genetic clustering algorithm detects clusters of individuals corresponding to continental regions. The number of loci sampled is critical: with fewer than 50 typical loci, structure cannot be reliably discerned in these populations. The inclusion of geographically intermediate populations (from India) reduces the distinctness of clustering. Our results indicate that human genetic variation is neither perfectly correlated with geographic distance (purely clinal) nor independent of distance (purely clustered), but a combination of both: stepped clinal.

Resources for Genetic Variation Studies

The rapid growth of genome-wide diversity databases, as well as ongoing large-scale resequencing projects targeting genes and other functional components of our genome, provide valuable resources of natural variation at the DNA sequence level. In this review, we briefly summarize the wealth of data on DNA polymorphisms in humans, the distribution of this diversity in the genome as well as among individuals, and the consequence of recombination on its organization. These data provide a set of powerful tools that can be used to better understand inherited phenotypic variation in humans. We discuss the implications for the design of studies investigating correlations between genotypes and phenotypes, both at the fundamental level of genome function and regulation, and for the mapping of disease genes.

Identifying the environmental factors that determine the genetic structure of populations

The study of population genetic structure is a fundamental problem in population biology because it helps us obtain a deeper understanding of the evolutionary process. One of the issues most assiduously studied in this context is the assessment of the relative importance of environmental factors (geographic distance, language, temperature, altitude, etc.) on the genetic structure of populations. The most widely used method to address this question is the multivariate Mantel test, a nonparametric method that calculates a correlation coefficient between a dependent matrix of pairwise population genetic distances and one or more independent matrices of environmental differences. Here we present a hierarchical Bayesian method that estimates F(ST) values for each local population and relates them to environmental factors using a generalized linear model. The method is demonstrated by applying it to two data sets, a data set for a population of the argan tree and a human data set comprising 51 populations distributed worldwide. We also carry out a simulation study to investigate the performance of the method and find that it can correctly identify the factors that play a role in the structuring of genetic diversity under a wide range of scenarios.

A geographically explicit genetic model of worldwide human-settlement history

Currently available genetic and archaeological evidence is generally interpreted as supportive of a recent single origin of modern humans in East Africa. However, this is where the near consensus on human settlement history ends, and considerable uncertainty clouds any more detailed aspect of human colonization history. Here, we present a dynamic genetic model of human settlement history coupled with explicit geographical distances from East Africa, the likely origin of modern humans. We search for the best-supported parameter space by fitting our analytical prediction to genetic data that are based on 52 human populations analyzed at 783 autosomal microsatellite markers. This framework allows us to jointly estimate the key parameters of the expansion of modern humans. Our best estimates suggest an initial expansion of modern humans approximately 56,000 years ago from a small founding population of approximately 1,000 effective individuals. Our model further points to high growth rates in newly colonized habitats. The general fit of the model with the data is excellent. This suggests that coupling analytical genetic models with explicit demography and geography provides a powerful tool for making inferences on human-settlement history.

Comment on "Ongoing adaptive evolution of ASPM, a brain size determinant in Homo sapiens" and "Microcephalin, a gene regulating brain size, continues to evolve adaptively in humans"

Mekel-Bobrov et al. and Evans et al. (Reports, 9 Sept. 2005, p. 1720 and p. 1717, respectively) examined sequence data from modern humans within two gene regions associated with brain development, ASPM and microcephalin, and concluded that selection of these genes must be ongoing. We show that models of human history that include both population growth and spatial structure can generate the observed patterns without selection.

Analysis of nucleotide diversity of NAT2 coding region reveals homogeneity across Native American populations and high intra-population diversity

N-acetyltransferase 2 (NAT2), an important enzyme in clinical pharmacology, metabolizes antibiotics such as isoniazid and sulfamethoxazole, and catalyzes the transformation of aromatic and heterocyclic amines from the environment and diet into carcinogenic intermediates. Polymorphisms in NAT2 account for variability in the acetylator phenotype and the pharmacokinetics of metabolized drugs. Native Americans, settled in rural areas and large cities of Latin America, are under-represented in pharmacogenetics studies; therefore, we sequenced the coding region of NAT2 in 456 chromosomes from 13 populations from the Americas, and two from Siberia, detecting nine substitutions and 11 haplotypes. Variants *4 (37%), *5B (23%) and *7B (24%) showed high frequencies. Average frequencies of fast, intermediate and slow acetylators across Native Americans were 18, 56 and 25%, respectively. NAT2 intra-population genetic diversity for Native Americans is higher than East Asians and similar to the rest of the world, and NAT2 variants are homogeneously distributed across native populations of the continent.

Why did modern human populations disperse from Africa ca. 60,000 years ago? A new model

Recent research has provided increasing support for the origins of anatomically and genetically "modern" human populations in Africa between 150,000 and 200,000 years ago, followed by a major dispersal of these populations to both Asia and Europe sometime after ca. 65,000 before present (B.P.). However, the central question of why it took these populations approximately 100,000 years to disperse from Africa to other regions of the world has never been clearly resolved. It is suggested here that the answer may lie partly in the results of recent DNA studies of present-day African populations, combined with a spate of new archaeological discoveries in Africa. Studies of both the mitochondrial DNA (mtDNA) mismatch patterns in modern African populations and related mtDNA lineage-analysis patterns point to a major demographic expansion centered broadly within the time range from 80,000 to 60,000 B.P., probably deriving from a small geographical region of Africa. Recent archaeological discoveries in southern and eastern Africa suggest that, at approximately the same time, there was a major increase in the complexity of the technological, economic, social, and cognitive behavior of certain African groups, which could have led to a major demographic expansion of these groups in competition with other, adjacent groups. It is suggested that this complex of behavioral changes (possibly triggered by the rapid environmental changes around the transition from oxygen isotope stage 5 to stage 4) could have led not only to the expansion of the L2 and L3 mitochondrial lineages over the whole of Africa but also to the ensuing dispersal of these modern populations over most regions of Asia, Australasia, and Europe, and their replacement (with or without interbreeding) of the preceding "archaic" populations in these regions.

Patterning of geographic variation in Middle Pleistocene Homo frontal bone morphology

A quantitative assessment of the frontal bone morphology of a sample of Middle Pleistocene hominins was undertaken in order to address questions regarding their population structure and evolutionary history. Outline tracings of the frontal bones of forty-seven fossil crania were obtained, and size-standardized measurements were then computed using an Elliptical Fourier analysis of these tracings. Principal component scores of the Fourier harmonic amplitudes were derived and served as a quantitative representation of the morphology of the frontal bone. Morphological, geographical, and temporal distance matrices were then constructed between each pair of fossils. A partial Mantel matrix correlation test was performed between morphological and geographical distance matrices, controlling for temporal distance, in order to determine if the pattern of geographical differentiation in features of the frontal bone of mid-Pleistocene Homo followed that of an isolation-by-distance model of population structure. The results of the partial Mantel tests indicate that the overall patterning of differentiation in the features of the frontal bone cannot best be explained by a population structure shaped by isolation-by-distance. Additionally, various aspects of the frontal bone quantified here follow different patterns of geographical differentiation, suggesting that a mosaic pattern of evolution holds true for characters within one cranial region and not just for those between regions.

How reliable are empirical genomic scans for selective sweeps?

The beneficial substitution of an allele shapes patterns of genetic variation at linked sites. Thus, in principle, adaptations can be mapped by looking for the signature of directional selection in polymorphism data. In practice, such efforts are hampered by the need for an accurate characterization of the demographic history of the species and of the effects of positive selection. In an attempt to circumvent these difficulties, researchers are increasingly taking a purely empirical approach, in which a large number of genomic regions are ordered by summaries of the polymorphism data, and loci with extreme values are considered to be likely targets of positive selection. We evaluated the reliability of the "empirical" approach, focusing on applications to human data and to maize. To do so, we considered a coalescent model of directional selection in a sensible demographic setting, allowing for selection on standing variation as well as on a new mutation. Our simulations suggest that while empirical approaches will identify several interesting candidates, they will also miss many--in some cases, most--loci of interest. The extent of the trade-off depends on the mode of positive selection and the demographic history of the population. Specifically, the false-discovery rate is higher when directional selection involves a recessive rather than a co-dominant allele, when it acts on a previously neutral rather than a new allele, and when the population has experienced a population bottleneck rather than maintained a constant size. One implication of these results is that, insofar as attributes of the beneficial mutation (e.g., the dominance coefficient) affect the power to detect targets of selection, genomic scans will yield an unrepresentative subset of loci that contribute to adaptations.

Genomic Boundaries between Human Populations

Different authors disagree on whether human genome variation should be described as continuous or discontinuous; in the latter case, by attributing an individual's genotype to one genetic cluster, one would also obtain information on the individual's genome in general. An analysis of 377 microsatellites of the CEPH human diversity panel was interpreted as evidence that most genotypes cluster into one of five distinct groups, approximately corresponding to continents, which were pro- posed by some authors as the major biological subdivisions of humankind. Here we analyse the same dataset by a specific numerical method, designed to detect genomic boundaries, i.e. zones of increased change in maps of genomic variation. We show that statistically significant boundaries can be described between groups of populations, but different clusters are identified, depending on the assumptions of the model. In addition, these clusters do not correspond to the clusters inferred from previous analyses of the same or of other polymorphisms. We conclude that it is indeed possible to cluster genotypes according to geography, but no study so far identified unambiguously anything that can be regarded as a major genetic subdivision of humankind, and hence discontinuous models of human diversity are unsupported by data.

A general population-genetic model for the production by population structure of spurious genotype-phenotype associations in discrete, admixed or spatially distributed populations

In linkage disequilibrium mapping of genetic variants causally associated with phenotypes, spurious associations can potentially be generated by any of a variety of types of population structure. However, mathematical theory of the production of spurious associations has largely been restricted to population structure models that involve the sampling of individuals from a collection of discrete subpopulations. Here, we introduce a general model of spurious association in structured populations, appropriate whether the population structure involves discrete groups, admixture among such groups, or continuous variation across space. Under the assumptions of the model, we find that a single common principle--applicable to both the discrete and admixed settings as well as to spatial populations--gives a necessary and sufficient condition for the occurrence of spurious associations. Using a mathematical connection between the discrete and admixed cases, we show that in admixed populations, spurious associations are less severe than in corresponding mixtures of discrete subpopulations, especially when the variance of admixture across individuals is small. This observation, together with the results of simulations that examine the relative influences of various model parameters, has important implications for the design and analysis of genetic association studies in structured populations.

Proportioning whole-genome single-nucleotide-polymorphism diversity for the identification of geographic population structure and genetic ancestry

The identification of geographic population structure and genetic ancestry on the basis of a minimal set of genetic markers is desirable for a wide range of applications in medical and forensic sciences. However, the absence of sharp discontinuities in the neutral genetic diversity among human populations implies that, in practice, a large number of neutral markers will be required to identify the genetic ancestry of one individual. We showed that it is possible to reduce the amount of markers required for detecting continental population structure to only 10 single-nucleotide polymorphisms (SNPs), by applying a newly developed ascertainment algorithm to Affymetrix GeneChip Mapping 10K SNP array data that we obtained from samples of globally dispersed human individuals (the Y Chromosome Consortium panel). Furthermore, this set of SNPs was able to recover the genetic ancestry of individuals from all four continents represented in the original data set when applied to an independent, much larger, worldwide population data set (Centre d'Etude du Polymorphisme Humain-Human Genome Diversity Project Cell Line Panel). Finally, we provide evidence that the unusual patterns of genetic variation we observed at the respective genomic regions surrounding the five most informative SNPs is in agreement with local positive selection being the explanation for the striking SNP allele-frequency differences we found between continental groups of human populations.

Clines, clusters, and the effect of study design on the inference of human population structure

Previously, we observed that without using prior information about individual sampling locations, a clustering algorithm applied to multilocus genotypes from worldwide human populations produced genetic clusters largely coincident with major geographic regions. It has been argued, however, that the degree of clustering is diminished by use of samples with greater uniformity in geographic distribution, and that the clusters we identified were a consequence of uneven sampling along genetic clines. Expanding our earlier dataset from 377 to 993 markers, we systematically examine the influence of several study design variables--sample size, number of loci, number of clusters, assumptions about correlations in allele frequencies across populations, and the geographic dispersion of the sample--on the "clusteredness" of individuals. With all other variables held constant, geographic dispersion is seen to have comparatively little effect on the degree of clustering. Examination of the relationship between genetic and geographic distance supports a view in which the clusters arise not as an artifact of the sampling scheme, but from small discontinuous jumps in genetic distance for most population pairs on opposite sides of geographic barriers, in comparison with genetic distance for pairs on the same side. Thus, analysis of the 993-locus dataset corroborates our earlier results: if enough markers are used with a sufficiently large worldwide sample, individuals can be partitioned into genetic clusters that match major geographic subdivisions of the globe, with some individuals from intermediate geographic locations having mixed membership in the clusters that correspond to neighboring regions.