Perspectives on human population structure at the cusp of the sequencing era

Methods for Assessing Population Relationships and History Using Genomic Data

Genetic data contain a record of our evolutionary history. The availability of large-scale datasets of human populations from various geographic areas and timescales, coupled with advances in the computational methods to analyze these data, has transformed our ability to use genetic data to learn about our evolutionary past. Here, we review some of the widely used statistical methods to explore and characterize population relationships and history using genomic data. We describe the intuition behind commonly used approaches, their interpretation, and important limitations. For illustration, we apply some of these techniques to genome-wide autosomal data from 929 individuals representing 53 worldwide populations that are part of the Human Genome Diversity Project. Finally, we discuss the new frontiers in genomic methods to learn about population history. In sum, this review highlights the power (and limitations) of DNA to infer features of human evolutionary history, complementing the knowledge gleaned from other disciplines, such as archaeology, anthropology, and linguistics.

Reconstructing the history of founder events using genome-wide patterns of allele sharing across individuals

Founder events play a critical role in shaping genetic diversity, fitness and disease risk in a population. Yet our understanding of the prevalence and distribution of founder events in humans and other species remains incomplete, as most existing methods require large sample sizes or phased genomes. Thus, we developed ASCEND that measures the correlation in allele sharing between pairs of individuals across the genome to infer the age and strength of founder events. We show that ASCEND can reliably estimate the parameters of founder events under a range of demographic scenarios. We then apply ASCEND to two species with contrasting evolutionary histories: ~460 worldwide human populations and ~40 modern dog breeds. In humans, we find that over half of the analyzed populations have evidence for recent founder events, associated with geographic isolation, modes of sustenance, or cultural practices such as endogamy. Notably, island populations have lower population sizes than continental groups and most hunter-gatherer, nomadic and indigenous groups have evidence of recent founder events. Many present-day groups––including Native Americans, Oceanians and South Asians––have experienced more extreme founder events than Ashkenazi Jews who have high rates of recessive diseases due their known history of founder events. Using ancient genomes, we show that the strength of founder events differs markedly across geographic regions and time––with three major founder events related to the peopling of Americas and a trend in decreasing strength of founder events in Europe following the Neolithic transition and steppe migrations. In dogs, we estimate extreme founder events in most breeds that occurred in the last 25 generations, concordant with the establishment of many dog breeds during the Victorian times. Our analysis highlights a widespread history of founder events in humans and dogs and elucidates some of the demographic and cultural practices related to these events.

A founder event occurs when small numbers of ancestral individuals give rise to a large fraction of the population. Founder events reduce genetic variation and increase the risk of recessive diseases. Despite their importance in evolutionary and disease studies, we still only have a limited comprehension of their prevalence and properties in humans and other species, as most existing methods require large sample sizes or phased genomes. Here, we present a flexible method, ASCEND, to infer the timing and the strength of founder events that is suitable for sparse datasets with few samples or limited coverage. ASCEND provides reliable estimates across a wide range of demographic scenarios. By applying it to data from two species (humans and dogs), we document a widespread history of recent founder events in both species and provide insights about the demographic processes related to these events. Our analysis helps to identify groups with strong founder events that should be prioritized for future studies as they offer a unique opportunity for biological discovery and reducing disease burden through mapping of recessive disease-causing genes and pathways, as previously shown in studies of Ashkenazi Jews and Finns.

Human Genomic Diversity Where the Mediterranean Joins the Atlantic

Throughout the past few years, a lively debate emerged about the timing and magnitude of the human migrations between the Iberian Peninsula and the Maghreb. Several pieces of evidence, including archaeological, anthropological, historical, and genetic data, have pointed to a complex and intermingled evolutionary history in the western Mediterranean area. To study to what extent connections across the Strait of Gibraltar and surrounding areas have shaped the present-day genomic diversity of its populations, we have performed a screening of 2.5 million single-nucleotide polymorphisms in 142 samples from southern Spain, southern Portugal, and Morocco. We built comprehensive data sets of the studied area and we implemented multistep bioinformatic approaches to assess population structure, demographic histories, and admixture dynamics. Both local and global ancestry inference showed an internal substructure in the Iberian Peninsula, mainly linked to a differential African ancestry. Western Iberia, from southern Portugal to Galicia, constituted an independent cluster within Iberia characterized by an enriched African genomic input. Migration time modeling showed recent historic dates for the admixture events occurring both in Iberia and in the North of Africa. However, an integrative vision of both paleogenomic and modern DNA data allowed us to detect chronological transitions and population turnovers that could be the result of transcontinental migrations dating back from Neolithic times. The present contribution aimed to fill the gaps in the modern human genomic record of a key geographic area, where the Mediterranean and the Atlantic come together.

Scalable probabilistic PCA for large-scale genetic variation data

Principal component analysis (PCA) is a key tool for understanding population structure and controlling for population stratification in genome-wide association studies (GWAS). With the advent of large-scale datasets of genetic variation, there is a need for methods that can compute principal components (PCs) with scalable computational and memory requirements. We present ProPCA, a highly scalable method based on a probabilistic generative model, which computes the top PCs on genetic variation data efficiently. We applied ProPCA to compute the top five PCs on genotype data from the UK Biobank, consisting of 488,363 individuals and 146,671 SNPs, in about thirty minutes. To illustrate the utility of computing PCs in large samples, we leveraged the population structure inferred by ProPCA within White British individuals in the UK Biobank to identify several novel genome-wide signals of recent putative selection including missense mutations in RPGRIP1L and TLR4.

Principal component analysis is a commonly used technique for understanding population structure and genetic variation. With the advent of large-scale datasets that contain the genetic information of hundreds of thousands of individuals, there is a need for methods that can compute principal components (PCs) with scalable computational and memory requirements. In this study, we present ProPCA, a highly scalable statistical method to compute genetic PCs efficiently. We systematically evaluate the accuracy and scalability of our method on large-scale simulated data and apply it to the UK Biobank. Leveraging the population structure inferred by ProPCA within the White British individuals in the UK Biobank, we identify several novel signals of putative recent selection.

Association analysis in a Latin American population revealed ethnic differences in rheumatoid arthritis-associated SNPs in Caucasian and Asian populations

Large genome-wide association studies (GWAS) have increased our knowledge of the genetic risk factors of rheumatoid arthritis (RA). However, little is known about genetic susceptibility in populations with a large admixture of Amerindian ancestry. The aim of the present study was to test the generalizability of previously reported RA loci in a Latin American (LA) population with admixed ancestry. We selected 128 single nucleotide polymorphisms (SNPs) in linkage equilibrium, with high association to RA in multiple populations of non-Amerindian origin. Genotyping of 118 SNPs was performed in 313 RA patients/487 healthy control subjects by mid-density arrays of polymerase chain reaction (PCR). Some of the identified associations were validated in an additional cohort (250 cases/290 controls). One marker, the SNP rs2451258, located upstream of T Cell Activation RhoGTPase Activating Protein (TAGAP) gene, showed significant association with RA (p = 5 × 10-3), whereas 18 markers exhibited suggestive associations (p < 0.05). Haplotype testing showed association of some groups of adjacent SNPs around the signal transducer and activator of transcription 4 (STAT4) gene (p = 9.82 × 10-3 to 2.04 × 10-3) with RA. Our major finding was little replication of previously reported genetic associations with RA. These results suggest that performing GWAS and admixture mapping in LA populations has the potential to reveal novel loci associated with RA. This in turn might help to gain insight into the 'pathogenomics' of this disease and to explore trans-population differences for RA in general.

Selecting among Alternative Scenarios of Human Evolution by Simulated Genetic Gradients

Selecting among alternative scenarios of human evolution is nowadays a common methodology to investigate the history of our species. This strategy is usually based on computer simulations of genetic data under different evolutionary scenarios, followed by a fitting of the simulated data with the real data. A recent trend in the investigation of ancestral evolutionary processes of modern humans is the application of genetic gradients as a measure of fitting, since evolutionary processes such as range expansions, range contractions, and population admixture (among others) can lead to different genetic gradients. In addition, this strategy allows the analysis of the genetic causes of the observed genetic gradients. Here, we review recent findings on the selection among alternative scenarios of human evolution based on simulated genetic gradients, including pros and cons. First, we describe common methodologies to simulate genetic gradients and apply them to select among alternative scenarios of human evolution. Next, we review previous studies on the influence of range expansions, population admixture, last glacial period, and migration with long-distance dispersal on genetic gradients for some regions of the world. Finally, we discuss this analytical approach, including technical limitations, required improvements, and advice. Although here we focus on human evolution, this approach could be extended to study other species.

Whole-Exome Sequencing Reveals Uncaptured Variation and Distinct Ancestry in the Southern African Population of Botswana

Large-scale, population-based genomic studies have provided a context for modern medical genetics. Among such studies, however, African populations have remained relatively underrepresented. The breadth of genetic diversity across the African continent argues for an exploration of local genomic context to facilitate burgeoning disease mapping studies in Africa. We sought to characterize genetic variation and to assess population substructure within a cohort of HIV-positive children from Botswana-a Southern African country that is regionally underrepresented in genomic databases. Using whole-exome sequencing data from 164 Batswana and comparisons with 150 similarly sequenced HIV-positive Ugandan children, we found that 13%-25% of variation observed among Batswana was not captured by public databases. Uncaptured variants were significantly enriched (p = 2.2 × 10^-16) for coding variants with minor allele frequencies between 1% and 5% and included predicted-damaging non-synonymous variants. Among variants found in public databases, corresponding allele frequencies varied widely, with Botswana having significantly higher allele frequencies among rare (<1%) pathogenic and damaging variants. Batswana clustered with other Southern African populations, but distinctly from 1000 Genomes African populations, and had limited evidence for admixture with extra-continental ancestries. We also observed a surprising lack of genetic substructure in Botswana, despite multiple tribal ethnicities and language groups, alongside a higher degree of relatedness than purported founder populations from the 1000 Genomes project. Our observations reveal a complex, but distinct, ancestral history and genomic architecture among Batswana and suggest that disease mapping within similar Southern African populations will require a deeper repository of genetic variation and allelic dependencies than presently exists.

Insights into Platypus Population Structure and History from Whole-Genome Sequencing

The platypus is an egg-laying mammal which, alongside the echidna, occupies a unique place in the mammalian phylogenetic tree. Despite widespread interest in its unusual biology, little is known about its population structure or recent evolutionary history. To provide new insights into the dispersal and demographic history of this iconic species, we sequenced the genomes of 57 platypuses from across the whole species range in eastern mainland Australia and Tasmania. Using a highly improved reference genome, we called over 6.7 M SNPs, providing an informative genetic data set for population analyses. Our results show very strong population structure in the platypus, with our sampling locations corresponding to discrete groupings between which there is no evidence for recent gene flow. Genome-wide data allowed us to establish that 28 of the 57 sampled individuals had at least a third-degree relative among other samples from the same river, often taken at different times. Taking advantage of a sampled family quartet, we estimated the de novo mutation rate in the platypus at 7.0 × 10-9/bp/generation (95% CI 4.1 × 10-9-1.2 × 10-8/bp/generation). We estimated effective population sizes of ancestral populations and haplotype sharing between current groupings, and found evidence for bottlenecks and long-term population decline in multiple regions, and early divergence between populations in different regions. This study demonstrates the power of whole-genome sequencing for studying natural populations of an evolutionarily important species.

Between Lake Baikal and the Baltic Sea: genomic history of the gateway to Europe

BACKGROUND

The history of human populations occupying the plains and mountain ridges separating Europe from Asia has been eventful, as these natural obstacles were crossed westward by multiple waves of Turkic and Uralic-speaking migrants as well as eastward by Europeans. Unfortunately, the material records of history of this region are not dense enough to reconstruct details of population history. These considerations stimulate growing interest to obtain a genetic picture of the demographic history of migrations and admixture in Northern Eurasia.

RESULTS

We genotyped and analyzed 1076 individuals from 30 populations with geographical coverage spanning from Baltic Sea to Baikal Lake. Our dense sampling allowed us to describe in detail the population structure, provide insight into genomic history of numerous European and Asian populations, and significantly increase quantity of genetic data available for modern populations in region of North Eurasia. Our study doubles the amount of genome-wide profiles available for this region. We detected unusually high amount of shared identical-by-descent (IBD) genomic segments between several Siberian populations, such as Khanty and Ket, providing evidence of genetic relatedness across vast geographic distances and between speakers of different language families. Additionally, we observed excessive IBD sharing between Khanty and Bashkir, a group of Turkic speakers from Southern Urals region. While adding some weight to the "Finno-Ugric" origin of Bashkir, our studies highlighted that the Bashkir genepool lacks the main "core", being a multi-layered amalgamation of Turkic, Ugric, Finnish and Indo-European contributions, which points at intricacy of genetic interface between Turkic and Uralic populations. Comparison of the genetic structure of Siberian ethnicities and the geography of the region they inhabit point at existence of the "Great Siberian Vortex" directing genetic exchanges in populations across the Siberian part of Asia. Slavic speakers of Eastern Europe are, in general, very similar in their genetic composition. Ukrainians, Belarusians and Russians have almost identical proportions of Caucasus and Northern European components and have virtually no Asian influence. We capitalized on wide geographic span of our sampling to address intriguing question about the place of origin of Russian Starovers, an enigmatic Eastern Orthodox Old Believers religious group relocated to Siberia in seventeenth century. A comparative reAdmix analysis, complemented by IBD sharing, placed their roots in the region of the Northern European Plain, occupied by North Russians and Finno-Ugric Komi and Karelian people. Russians from Novosibirsk and Russian Starover exhibit ancestral proportions close to that of European Eastern Slavs, however, they also include between five to 10 % of Central Siberian ancestry, not present at this level in their European counterparts.

CONCLUSIONS

Our project has patched the hole in the genetic map of Eurasia: we demonstrated complexity of genetic structure of Northern Eurasians, existence of East-West and North-South genetic gradients, and assessed different inputs of ancient populations into modern populations.

Living in an adaptive world: Genomic dissection of the genus Homo and its immune response

More than a decade after the sequencing of the human genome, a deluge of genome-wide population data are generating a portrait of human genetic diversity at an unprecedented level of resolution. Genomic studies have provided new insight into the demographic and adaptive history of our species, Homo sapiens, including its interbreeding with other hominins, such as Neanderthals, and the ways in which natural selection, in its various guises, has shaped genome diversity. These studies, combined with functional genomic approaches, such as the mapping of expression quantitative trait loci, have helped to identify genes, functions, and mechanisms of prime importance for host survival and involved in phenotypic variation and differences in disease risk. This review summarizes new findings in this rapidly developing field, focusing on the human immune response. We discuss the importance of defining the genetic and evolutionary determinants driving immune response variation, and highlight the added value of population genomic approaches in settings relevant to immunity and infection.

A genetic chronology for the Indian Subcontinent points to heavily sex-biased dispersals

BACKGROUND

India is a patchwork of tribal and non-tribal populations that speak many different languages from various language families. Indo-European, spoken across northern and central India, and also in Pakistan and Bangladesh, has been frequently connected to the so-called "Indo-Aryan invasions" from Central Asia ~3.5 ka and the establishment of the caste system, but the extent of immigration at this time remains extremely controversial. South India, on the other hand, is dominated by Dravidian languages. India displays a high level of endogamy due to its strict social boundaries, and high genetic drift as a result of long-term isolation which, together with a very complex history, makes the genetic study of Indian populations challenging.

RESULTS

We have combined a detailed, high-resolution mitogenome analysis with summaries of autosomal data and Y-chromosome lineages to establish a settlement chronology for the Indian Subcontinent. Maternal lineages document the earliest settlement ~55-65 ka (thousand years ago), and major population shifts in the later Pleistocene that explain previous dating discrepancies and neutrality violation. Whilst current genome-wide analyses conflate all dispersals from Southwest and Central Asia, we were able to tease out from the mitogenome data distinct dispersal episodes dating from between the Last Glacial Maximum to the Bronze Age. Moreover, we found an extremely marked sex bias by comparing the different genetic systems.

CONCLUSIONS

Maternal lineages primarily reflect earlier, pre-Holocene processes, and paternal lineages predominantly episodes within the last 10 ka. In particular, genetic influx from Central Asia in the Bronze Age was strongly male-driven, consistent with the patriarchal, patrilocal and patrilineal social structure attributed to the inferred pastoralist early Indo-European society. This was part of a much wider process of Indo-European expansion, with an ultimate source in the Pontic-Caspian region, which carried closely related Y-chromosome lineages, a smaller fraction of autosomal genome-wide variation and an even smaller fraction of mitogenomes across a vast swathe of Eurasia between 5 and 3.5 ka.

Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples

The distribution of fitness effects (DFE) has considerable importance in population genetics. To date, estimates of the DFE come from studies using a small number of individuals. Thus, estimates of the proportion of moderately to strongly deleterious new mutations may be unreliable because such variants are unlikely to be segregating in the data. Additionally, the true functional form of the DFE is unknown, and estimates of the DFE differ significantly between studies. Here we present a flexible and computationally tractable method, called Fit∂a∂i, to estimate the DFE of new mutations using the site frequency spectrum from a large number of individuals. We apply our approach to the frequency spectrum of 1300 Europeans from the Exome Sequencing Project ESP6400 data set, 1298 Danes from the LuCamp data set, and 432 Europeans from the 1000 Genomes Project to estimate the DFE of deleterious nonsynonymous mutations. We infer significantly fewer (0.38-0.84 fold) strongly deleterious mutations with selection coefficient |s| > 0.01 and more (1.24-1.43 fold) weakly deleterious mutations with selection coefficient |s| < 0.001 compared to previous estimates. Furthermore, a DFE that is a mixture distribution of a point mass at neutrality plus a gamma distribution fits better than a gamma distribution in two of the three data sets. Our results suggest that nearly neutral forces play a larger role in human evolution than previously thought.

Understanding rare and common diseases in the context of human evolution

The wealth of available genetic information is allowing the reconstruction of human demographic and adaptive history. Demography and purifying selection affect the purge of rare, deleterious mutations from the human population, whereas positive and balancing selection can increase the frequency of advantageous variants, improving survival and reproduction in specific environmental conditions. In this review, I discuss how theoretical and empirical population genetics studies, using both modern and ancient DNA data, are a powerful tool for obtaining new insight into the genetic basis of severe disorders and complex disease phenotypes, rare and common, focusing particularly on infectious disease risk.

Recent advances in the study of fine-scale population structure in humans

Empowered by modern genotyping and large samples, population structure can be accurately described and quantified even when it only explains a fraction of a percent of total genetic variance. This is especially relevant and interesting for humans, where fine-scale population structure can both confound disease-mapping studies and reveal the history of migration and divergence that shaped our species' diversity. Here we review notable recent advances in the detection, use, and understanding of population structure. Our work addresses multiple areas where substantial progress is being made: improved statistics and models for better capturing differentiation, admixture, and the spatial distribution of variation; computational speed-ups that allow methods to scale to modern data; and advances in haplotypic modeling that have wide ranging consequences for the analysis of population structure. We conclude by outlining four important open challenges: the limitations of discrete population models, uncertainty in individual origins, the incorporation of both fine-scale structure and ancient DNA in parametric models, and the development of efficient computational tools, particularly for haplotype-based methods.

Discovery of Gene Sources for Economic Traits in Hanwoo by Whole-genome Resequencing

Hanwoo, a Korean native cattle (Bos taurus coreana), has great economic value due to high meat quality. Also, the breed has genetic variations that are associated with production traits such as health, disease resistance, reproduction, growth as well as carcass quality. In this study, next generation sequencing technologies and the availability of an appropriate reference genome were applied to discover a large amount of single nucleotide polymorphisms (SNPs) in ten Hanwoo bulls. Analysis of whole-genome resequencing generated a total of 26.5 Gb data, of which 594,716,859 and 592,990,750 reads covered 98.73% and 93.79% of the bovine reference genomes of UMD 3.1 and Btau 4.6.1, respectively. In total, 2,473,884 and 2,402,997 putative SNPs were discovered, of which 1,095,922 (44.3%) and 982,674 (40.9%) novel SNPs were discovered against UMD3.1 and Btau 4.6.1, respectively. Among the SNPs, the 46,301 (UMD 3.1) and 28,613 SNPs (Btau 4.6.1) that were identified as Hanwoo-specific SNPs were included in the functional genes that may be involved in the mechanisms of milk production, tenderness, juiciness, marbling of Hanwoo beef and yellow hair. Most of the Hanwoo-specific SNPs were identified in the promoter region, suggesting that the SNPs influence differential expression of the regulated genes relative to the relevant traits. In particular, the non-synonymous (ns) SNPs found in CORIN, which is a negative regulator of Agouti, might be a causal variant to determine yellow hair of Hanwoo. Our results will provide abundant genetic sources of variation to characterize Hanwoo genetics and for subsequent breeding.

Population genomics of divergence among extreme and intermediate color forms in a polymorphic insect

Geographic variation in insect coloration is among the most intriguing examples of rapid phenotypic evolution and provides opportunities to study mechanisms of phenotypic change and diversification in closely related lineages. The bumble bee Bombus bifarius comprises two geographically disparate color groups characterized by red‐banded and black‐banded abdominal pigmentation, but with a range of spatially and phenotypically intermediate populations across western North America. Microsatellite analyses have revealed that B. bifarius in the USA are structured into two major groups concordant with geography and color pattern, but also suggest ongoing gene flow among regional populations. In this study, we better resolve the relationships among major color groups to better understand evolutionary mechanisms promoting and maintaining such polymorphism. We analyze >90,000 and >25,000 single‐nucleotide polymorphisms derived from transcriptome (RNAseq) and double digest restriction site associated DNA sequencing (ddRAD), respectively, in representative samples from spatial and color pattern extremes in B. bifarius as well as phenotypic and geographic intermediates. Both ddRAD and RNAseq data illustrate substantial genome‐wide differentiation of the red‐banded (eastern) color form from both black‐banded (western) and intermediate (central) phenotypes and negligible differentiation among the latter populations, with no obvious admixture among bees from the two major lineages. Results thus indicate much stronger background differentiation among B. bifarius lineages than expected, highlighting potential challenges for revealing loci underlying color polymorphism from population genetic data alone. These findings will have significance for resolving taxonomic confusion in this species and in future efforts to investigate color‐pattern evolution in B. bifarius and other polymorphic bumble bee species.

No evidence from genome-wide data of a Khazar origin for the Ashkenazi Jews

The origin and history of the Ashkenazi Jewish population have long been of great interest, and advances in high-throughput genetic analysis have recently provided a new approach for investigating these topics. We and others have argued on the basis of genome-wide data that the Ashkenazi Jewish population derives its ancestry from a combination of sources tracing to both Europe and the Middle East. It has been claimed, however, through a reanalysis of some of our data, that a large part of the ancestry of the Ashkenazi population originates with the Khazars, a Turkic-speaking group that lived to the north of the Caucasus region ~1,000 years ago. Because the Khazar population has left no obvious modern descendants that could enable a clear test for a contribution to Ashkenazi Jewish ancestry, the Khazar hypothesis has been difficult to examine using genetics. Furthermore, because only limited genetic data have been available from the Caucasus region, and because these data have been concentrated in populations that are genetically close to populations from the Middle East, the attribution of any signal of Ashkenazi-Caucasus genetic similarity to Khazar ancestry rather than shared ancestral Middle Eastern ancestry has been problematic. Here, through integration of genotypes from newly collected samples with data from several of our past studies, we have assembled the largest data set available to date for assessment of Ashkenazi Jewish genetic origins. This data set contains genome-wide single-nucleotide polymorphisms in 1,774 samples from 106 Jewish and non-Jewish populations that span the possible regions of potential Ashkenazi ancestry: Europe, the Middle East, and the region historically associated with the Khazar Khaganate. The data set includes 261 samples from 15 populations from the Caucasus region and the region directly to its north, samples that have not previously been included alongside Ashkenazi Jewish samples in genomic studies. Employing a variety of standard techniques for the analysis of population-genetic structure, we found that Ashkenazi Jews share the greatest genetic ancestry with other Jewish populations and, among non-Jewish populations, with groups from Europe and the Middle East. No particular similarity of Ashkenazi Jews to populations from the Caucasus is evident, particularly populations that most closely represent the Khazar region. Thus, analysis of Ashkenazi Jews together with a large sample from the region of the Khazar Khaganate corroborates the earlier results that Ashkenazi Jews derive their ancestry primarily from populations of the Middle East and Europe, that they possess considerable shared ancestry with other Jewish populations, and that there is no indication of a significant genetic contribution either from within or from north of the Caucasus region.

Impact of Parental Bos taurus and Bos indicus Origins on Copy Number Variation in Traditional Chinese Cattle Breeds

Copy number variation (CNV) is an important component of genomic structural variation and plays a role not only in evolutionary diversification but also in domestication. Chinese cattle were derived from Bos taurus and Bos indicus, and several breeds presumably are of hybrid origin, but the evolution of CNV regions (CNVRs) has not yet been examined in this context. Here, we of CNVRs, mtDNA D-loop sequence variation, and Y-chromosomal single nucleotide polymorphisms to assess the impact of maternal and paternal B. taurus and B. indicus origins on the distribution of CNVRs in 24 Chinese domesticated bulls. We discovered 470 genome-wide CNVRs, only 72 of which were shared by all three Y-lineages (B. taurus: Y₁, Y₂; B. indicus: Y₃), whereas 265 were shared by inferred taurine or indicine paternal lineages, and 228 when considering their maternal taurine or indicine origins. Phylogenetic analysis uncovered eight taurine/indicine hybrids, and principal component analysis on CNVs corroborated genomic exchange during hybridization. The distribution patterns of CNVRs tended to be lineage-specific, and correlation analysis revealed significant positive or negative co-occurrences of CNVRs across lineages. Our study suggests that CNVs in Chinese cattle partly result from selective breeding during domestication, but also from hybridization and introgression.

60,000 years of interactions between Central and Eastern Africa documented by major African mitochondrial haplogroup L2

Mitochondrial DNA (mtDNA) haplogroup L2 originated in Western Africa but is nowadays spread across the entire continent. L2 movements were previously postulated to be related to the Bantu expansion, but L2 expansions eastwards probably occurred much earlier. By reconstructing the phylogeny of L2 (44 new complete sequences) we provide insights on the complex net of within-African migrations in the last 60 thousand years (ka). Results show that lineages in Southern Africa cluster with Western/Central African lineages at a recent time scale, whereas, eastern lineages seem to be substantially more ancient. Three moments of expansion from a Central African source are associated to L2: (1) one migration at 70–50 ka into Eastern or Southern Africa, (2) postglacial movements (15–10 ka) into Eastern Africa; and (3) the southward Bantu Expansion in the last 5 ka. The complementary population and L0a phylogeography analyses indicate no strong evidence of mtDNA gene flow between eastern and southern populations during the later movement, suggesting low admixture between Eastern African populations and the Bantu migrants. This implies that, at least in the early stages, the Bantu expansion was mainly a demic diffusion with little incorporation of local populations.

Detecting individual ancestry in the human genome

Detecting and quantifying the population substructure present in a sample of individuals are of main interest in the fields of genetic epidemiology, population genetics, and forensics among others. To date, several algorithms have been proposed for estimating the amount of genetic ancestry within an individual. In the present review, we introduce the most widely used methods in population genetics for detecting individual genetic ancestry. We further show, by means of simulations, the performance of popular algorithms for detecting individual ancestry in various controlled demographic scenarios. Finally, we provide some hints on how to interpret the results from these algorithms.

Rare variation facilitates inferences of fine-scale population structure in humans

Understanding the genetic structure of human populations has important implications for the design and interpretation of disease mapping studies and reconstructing human evolutionary history. To date, inferences of human population structure have primarily been made with common variants. However, recent large-scale resequencing studies have shown an abundance of rare variation in humans, which may be particularly useful for making inferences of fine-scale population structure. To this end, we used an information theory framework and extensive coalescent simulations to rigorously quantify the informativeness of rare and common variation to detect signatures of fine-scale population structure. We show that rare variation affords unique insights into patterns of recent population structure. Furthermore, to empirically assess our theoretical findings, we analyzed high-coverage exome sequences in 6,515 European and African American individuals. As predicted, rare variants are more informative than common polymorphisms in revealing a distinct cluster of European–American individuals, and subsequent analyses demonstrate that these individuals are likely of Ashkenazi Jewish ancestry. Our results provide new insights into the population structure using rare variation, which will be an important factor to account for in rare variant association studies.

Toward a new history and geography of human genes informed by ancient DNA

Genetic information contains a record of the history of our species, and technological advances have transformed our ability to access this record. Many studies have used genome-wide data from populations today to learn about the peopling of the globe and subsequent adaptation to local conditions. Implicit in this research is the assumption that the geographic locations of people today are informative about the geographic locations of their ancestors in the distant past. However, it is now clear that long-range migration, admixture, and population replacement subsequent to the initial out-of-Africa expansion have altered the genetic structure of most of the world's human populations. In light of this we argue that it is time to critically reevaluate current models of the peopling of the globe, as well as the importance of natural selection in determining the geographic distribution of phenotypes. We specifically highlight the transformative potential of ancient DNA. By accessing the genetic make-up of populations living at archaeologically known times and places, ancient DNA makes it possible to directly track migrations and responses to natural selection.

The relevance of HLA sequencing in population genetics studies

Next generation sequencing (NGS) is currently being adapted by different biotechnological platforms to the standard typing method for HLA polymorphism, the huge diversity of which makes this initiative particularly challenging. Boosting the molecular characterization of the HLA genes through efficient, rapid, and low-cost technologies is expected to amplify the success of tissue transplantation by enabling us to find donor-recipient matching for rare phenotypes. But the application of NGS technologies to the molecular mapping of the MHC region also anticipates essential changes in population genetic studies. Huge amounts of HLA sequence data will be available in the next years for different populations, with the potential to change our understanding of HLA variation in humans. In this review, we first explain how HLA sequencing allows a better assessment of the HLA diversity in human populations, taking also into account the methodological difficulties it introduces at the statistical level; secondly, we show how analyzing HLA sequence variation may improve our comprehension of population genetic relationships by facilitating the identification of demographic events that marked human evolution; finally, we discuss the interest of both HLA and genome-wide sequencing and genotyping in detecting functionally significant SNPs in the MHC region, the latter having also contributed to the makeup of the HLA molecular diversity observed today.

bammds: a tool for assessing the ancestry of low-depth whole-genome data using multidimensional scaling (MDS)

Summary: We present bammds, a practical tool that allows visualization of samples sequenced by second-generation sequencing when compared with a reference panel of individuals (usually genotypes) using a multidimensional scaling algorithm. Our tool is aimed at determining the ancestry of unknown samples—typical of ancient DNA data—particularly when only low amounts of data are available for those samples.

Availability and implementation: The software package is available under GNU General Public License v3 and is freely available together with test datasets https://savannah.nongnu.org/projects/bammds/. It is using R (http://www.r-project.org/), parallel (http://www.gnu.org/software/parallel/), samtools (https://github.com/samtools/samtools).

Contact:bammds-users@nongnu.org

Supplementary information:Supplementary data are available at Bioinformatics online.

Population-specific common SNPs reflect demographic histories and highlight regions of genomic plasticity with functional relevance

BACKGROUND

Population differentiation is the result of demographic and evolutionary forces. Whole genome datasets from the 1000 Genomes Project (October 2012) provide an unbiased view of genetic variation across populations from Europe, Asia, Africa and the Americas. Common population-specific SNPs (MAF > 0.05) reflect a deep history and may have important consequences for health and wellbeing. Their interpretation is contextualised by currently available genome data.

RESULTS

The identification of common population-specific (CPS) variants (SNPs and SSV) is influenced by admixture and the sample size under investigation. Nine of the populations in the 1000 Genomes Project (2 African, 2 Asian (including a merged Chinese group) and 5 European) revealed that the African populations (LWK and YRI), followed by the Japanese (JPT) have the highest number of CPS SNPs, in concordance with their histories and given the populations studied. Using two methods, sliding 50-SNP and 5-kb windows, the CPS SNPs showed distinct clustering across large genome segments and little overlap of clusters between populations. iHS enrichment score and the population branch statistic (PBS) analyses suggest that selective sweeps are unlikely to account for the clustering and population specificity. Of interest is the association of clusters close to recombination hotspots. Functional analysis of genes associated with the CPS SNPs revealed over-representation of genes in pathways associated with neuronal development, including axonal guidance signalling and CREB signalling in neurones.

CONCLUSIONS

Common population-specific SNPs are non-randomly distributed throughout the genome and are significantly associated with recombination hotspots. Since the variant alleles of most CPS SNPs are the derived allele, they likely arose in the specific population after a split from a common ancestor. Their proximity to genes involved in specific pathways, including neuronal development, suggests evolutionary plasticity of selected genomic regions. Contrary to expectation, selective sweeps did not play a large role in the persistence of population-specific variation. This suggests a stochastic process towards population-specific variation which reflects demographic histories and may have some interesting implications for health and susceptibility to disease.

Worldwide patterns of ancestry, divergence, and admixture in domesticated cattle

The domestication and development of cattle has considerably impacted human societies, but the histories of cattle breeds and populations have been poorly understood especially for African, Asian, and American breeds. Using genotypes from 43,043 autosomal single nucleotide polymorphism markers scored in 1,543 animals, we evaluate the population structure of 134 domesticated bovid breeds. Regardless of the analytical method or sample subset, the three major groups of Asian indicine, Eurasian taurine, and African taurine were consistently observed. Patterns of geographic dispersal resulting from co-migration with humans and exportation are recognizable in phylogenetic networks. All analytical methods reveal patterns of hybridization which occurred after divergence. Using 19 breeds, we map the cline of indicine introgression into Africa. We infer that African taurine possess a large portion of wild African auroch ancestry, causing their divergence from Eurasian taurine. We detect exportation patterns in Asia and identify a cline of Eurasian taurine/indicine hybridization in Asia. We also identify the influence of species other than Bos taurus taurus and B. t. indicus in the formation of Asian breeds. We detect the pronounced influence of Shorthorn cattle in the formation of European breeds. Iberian and Italian cattle possess introgression from African taurine. American Criollo cattle originate from Iberia, and not directly from Africa with African ancestry inherited via Iberian ancestors. Indicine introgression into American cattle occurred in the Americas, and not Europe. We argue that cattle migration, movement and trading followed by admixture have been important forces in shaping modern bovine genomic variation.

The DNA of domesticated plants and animals contains information about how species were domesticated, exported, and bred by early farmers. Modern breeds were developed by lengthy and complex processes; however, our use of 134 breeds and new analytical models enabled us to reveal some of the processes that created modern cattle diversity. In Asia, Africa, North and South America, humpless (Bos t. taurus or taurine) and humped (Bos t. indicus or indicine) cattle were crossbred to produce hybrids adapted to the environment and local production systems. The history of Asian cattle involves the domestication and admixture of several species whereas African taurines arose through the introduction of domesticated Fertile Crescent taurines and their hybridization with wild African aurochs. African taurine genetic background is commonly observed among European Mediterranean breeds. The absence of indicine introgression within most European taurine breeds, but presence within three Italian breeds is consistent with at least two separate migration waves of cattle to Europe, one from the Middle East which captured taurines in which indicine introgression had already occurred and the second from western Africa into Spain with no indicine introgression. This second group seems to have radiated from Spain into the Mediterranean resulting in a cline of African taurine introgression into European taurines.

GAGA: a new algorithm for genomic inference of geographic ancestry reveals fine level population substructure in Europeans

Attempts to detect genetic population substructure in humans are troubled by the fact that the vast majority of the total amount of observed genetic variation is present within populations rather than between populations. Here we introduce a new algorithm for transforming a genetic distance matrix that reduces the within-population variation considerably. Extensive computer simulations revealed that the transformed matrix captured the genetic population differentiation better than the original one which was based on the T1 statistic. In an empirical genomic data set comprising 2,457 individuals from 23 different European subpopulations, the proportion of individuals that were determined as a genetic neighbour to another individual from the same sampling location increased from 25% with the original matrix to 52% with the transformed matrix. Similarly, the percentage of genetic variation explained between populations by means of Analysis of Molecular Variance (AMOVA) increased from 1.62% to 7.98%. Furthermore, the first two dimensions of a classical multidimensional scaling (MDS) using the transformed matrix explained 15% of the variance, compared to 0.7% obtained with the original matrix. Application of MDS with Mclust, SPA with Mclust, and GemTools algorithms to the same dataset also showed that the transformed matrix gave a better association of the genetic clusters with the sampling locations, and particularly so when it was used in the AMOVA framework with a genetic algorithm. Overall, the new matrix transformation introduced here substantially reduces the within population genetic differentiation, and can be broadly applied to methods such as AMOVA to enhance their sensitivity to reveal population substructure. We herewith provide a publically available (http://www.erasmusmc.nl/fmb/resources/GAGA) model-free method for improved genetic population substructure detection that can be applied to human as well as any other species data in future studies relevant to evolutionary biology, behavioural ecology, medicine, and forensics.

The impact of whole-genome sequencing on the reconstruction of human population history

Examining patterns of molecular genetic variation in both modern-day and ancient humans has proved to be a powerful approach to learn about our origins. Rapid advances in DNA sequencing technology have allowed us to characterize increasing amounts of genomic information. Although this clearly provides unprecedented power for inference, it also introduces more complexity into the way we use and interpret such data. Here, we review ongoing debates that have been influenced by improvements in our ability to sequence DNA and discuss some of the analytical challenges that need to be overcome in order to fully exploit the rich historical information that is contained in the entirety of the human genome.

Deciphering the fine-structure of tribal admixture in the Bedouin population using genomic data

The Bedouin Israeli population is highly inbred and structured with a very high prevalence of recessive diseases. Many studies in the past two decades focused on linkage analysis in large, multiple consanguineous pedigrees of this population. The advent of high-throughput technologies motivated researchers to search for rare variants shared between smaller pedigrees, integrating data from clinically similar yet seemingly non-related sporadic cases. However, such analyses are challenging because, without pedigree data, there is no prior knowledge regarding possible relatedness between the sporadic cases. Here, we describe models and techniques for the study of relationships between pedigrees and use them for the inference of tribal co-ancestry, delineating the complex social interactions between different tribes in the Negev Bedouins of southern Israel. Through our analysis, we differentiate between tribes that share many yet small genomic segments because of co-ancestry versus tribes that share larger segments because of recent admixture. The emergent pattern is well correlated with the prevalence of rare mutations in the different tribes. Tribes that do not intermarry, mostly because of social restrictions, hold private mutations, whereas tribes that do intermarry demonstrate a genetic flow of mutations between them. Thus, social structure within an inbred community can be delineated through genomic data, with implications to genetic counseling and genetic mapping.

Demographic histories, isolation and social factors as determinants of the genetic structure of Alpine linguistic groups

Great European mountain ranges have acted as barriers to gene flow for resident populations since prehistory and have offered a place for the settlement of small, and sometimes culturally diverse, communities. Therefore, the human groups that have settled in these areas are worth exploring as an important potential source of diversity in the genetic structure of European populations. In this study, we present new high resolution data concerning Y chromosomal variation in three distinct Alpine ethno-linguistic groups, Italian, Ladin and German. Combining unpublished and literature data on Y chromosome and mitochondrial variation, we were able to detect different genetic patterns. In fact, within and among population diversity values observed vary across linguistic groups, with German and Italian speakers at the two extremes, and seem to reflect their different demographic histories. Using simulations we inferred that the joint effect of continued genetic isolation and reduced founding group size may explain the apportionment of genetic diversity observed in all groups. Extending the analysis to other continental populations, we observed that the genetic differentiation of Ladins and German speakers from Europeans is comparable or even greater to that observed for well known outliers like Sardinian and Basques. Finally, we found that in south Tyroleans, the social practice of Geschlossener Hof, a hereditary norm which might have favored male dispersal, coincides with a significant intra-group diversity for mtDNA but not for Y chromosome, a genetic pattern which is opposite to those expected among patrilocal populations. Together with previous evidence regarding the possible effects of “local ethnicity” on the genetic structure of German speakers that have settled in the eastern Italian Alps, this finding suggests that taking socio-cultural factors into account together with geographical variables and linguistic diversity may help unveil some yet to be understood aspects of the genetic structure of European populations.

Mitogenomes from two uncommon haplogroups mark late glacial/postglacial expansions from the near east and neolithic dispersals within Europe

The current human mitochondrial (mtDNA) phylogeny does not equally represent all human populations but is biased in favour of representatives originally from north and central Europe. This especially affects the phylogeny of some uncommon West Eurasian haplogroups, including I and W, whose southern European and Near Eastern components are very poorly represented, suggesting that extensive hidden phylogenetic substructure remains to be uncovered. This study expanded and re-analysed the available datasets of I and W complete mtDNA genomes, reaching a comprehensive 419 mitogenomes, and searched for precise correlations between the ages and geographical distributions of their numerous newly identified subclades with events of human dispersal which contributed to the genetic formation of modern Europeans. Our results showed that haplogroups I (within N1a1b) and W originated in the Near East during the Last Glacial Maximum or pre-warming period (the period of gradual warming between the end of the LGM, ∼19 ky ago, and the beginning of the first main warming phase, ∼15 ky ago) and, like the much more common haplogroups J and T, may have been involved in Late Glacial expansions starting from the Near East. Thus our data contribute to a better definition of the Late and postglacial re-peopling of Europe, providing further evidence for the scenario that major population expansions started after the Last Glacial Maximum but before Neolithic times, but also evidencing traces of diffusion events in several I and W subclades dating to the European Neolithic and restricted to Europe.

SNP ascertainment bias in population genetic analyses: why it is important, and how to correct it

Whole genome sequencing and SNP genotyping arrays can paint strikingly different pictures of demographic history and natural selection. This is because genotyping arrays contain biased sets of pre-ascertained SNPs. In this short review, we use comparisons between high-coverage whole genome sequences of African hunter-gatherers and data from genotyping arrays to highlight how SNP ascertainment bias distorts population genetic inferences. Sample sizes and the populations in which SNPs are discovered affect the characteristics of observed variants. We find that SNPs on genotyping arrays tend to be older and present in multiple populations. In addition, genotyping arrays cause allele frequency distributions to be shifted towards intermediate frequency alleles, and estimates of linkage disequilibrium are modified. Since population genetic analyses depend on allele frequencies, it is imperative that researchers are aware of the effects of SNP ascertainment bias. With this in mind, we describe multiple ways to correct for SNP ascertainment bias.

Phylogeography and postglacial expansion of the endangered semi-aquatic mammal Galemys pyrenaicus

Background

Species with strict ecological requirements may provide new insights into the forces that shaped the geographic variation of genetic diversity. The Pyrenean desman, Galemys pyrenaicus, is a small semi-aquatic mammal that inhabits clean streams of the northern half of the Iberian Peninsula and is endangered in most of its geographic range, but its genetic structure is currently unknown. While the stringent ecological demands derived from its aquatic habitat might have caused a partition of the genetic diversity among river basins, Pleistocene glaciations would have generated a genetic pattern related to glacial refugia.

Results

To study the relative importance of historical and ecological factors in the genetic structure of G. pyrenaicus, we used mitochondrial and intronic sequences of specimens covering most of the species range. We show, first, that the Pyrenean desman has very low levels of genetic diversity compared to other mammals. In addition, phylogenetic and dating analyses of the mitochondrial sequences reveal a strong phylogeographic structure of a Middle Pleistocene origin, suggesting that the main lineages arose during periods of glacial isolation. Furthermore, both the spatial distribution of nuclear and mitochondrial diversity and the results of species distribution modeling suggest the existence of a major glacial refugium in the northwestern part of the Iberian Peninsula. Finally, the main mitochondrial lineages show a striking parapatric distribution without any apparent exchange of mitochondrial haplotypes between the lineages that came into secondary contact (although with certain permeability to nuclear genes), indicating incomplete mixing after the post-glacial recolonization. On the other hand, when we analyzed the partition of the genetic diversity among river basins, the Pyrenean desman showed a lower than expected genetic differentiation among main rivers.

Conclusions

The analysis of mitochondrial and intronic markers in G. pyrenaicus showed the predominant effects of Pleistocene glaciations on the genetic structure of this species, while the distribution of the genetic diversity was not greatly influenced by the main river systems. These results and, particularly, the discovery of a marked phylogeographic structure, may have important implications for the conservation of the Pyrenean desman.

Chromosome painting in silico in a bacterial species reveals fine population structure

Identifying population structure forms an important basis for genetic and evolutionary studies. Most current methods to identify population structure have limitations in analyzing haplotypes and recombination across the genome. Recently, a method of chromosome painting in silico has been developed to overcome these shortcomings and has been applied to multiple human genome sequences. This method detects the genome-wide transfer of DNA sequence chunks through homologous recombination. Here, we apply it to the frequently recombining bacterial species Helicobacter pylori that has infected Homo sapiens since their birth in Africa and shows wide phylogeographic divergence. Multiple complete genome sequences were analyzed including sequences from Okinawa, Japan, that we recently sequenced. The newer method revealed a finer population structure than revealed by a previous method that examines only MLST housekeeping genes or a phylogenetic network analysis of the core genome. Novel subgroups were found in Europe, Amerind, and East Asia groups. Examination of genetic flux showed some singleton strains to be hybrids of subgroups and revealed evident signs of population admixture in Africa, Europe, and parts of Asia. We expect this approach to further our understanding of intraspecific bacterial evolution by revealing population structure at a finer scale.

The geography of recent genetic ancestry across Europe

A genomic survey of recent genealogical relatedness reveals the close ties of kinship and the impact of events across the past 3,000 years of European history.

The recent genealogical history of human populations is a complex mosaic formed by individual migration, large-scale population movements, and other demographic events. Population genomics datasets can provide a window into this recent history, as rare traces of recent shared genetic ancestry are detectable due to long segments of shared genomic material. We make use of genomic data for 2,257 Europeans (in the Population Reference Sample [POPRES] dataset) to conduct one of the first surveys of recent genealogical ancestry over the past 3,000 years at a continental scale. We detected 1.9 million shared long genomic segments, and used the lengths of these to infer the distribution of shared ancestors across time and geography. We find that a pair of modern Europeans living in neighboring populations share around 2–12 genetic common ancestors from the last 1,500 years, and upwards of 100 genetic ancestors from the previous 1,000 years. These numbers drop off exponentially with geographic distance, but since these genetic ancestors are a tiny fraction of common genealogical ancestors, individuals from opposite ends of Europe are still expected to share millions of common genealogical ancestors over the last 1,000 years. There is also substantial regional variation in the number of shared genetic ancestors. For example, there are especially high numbers of common ancestors shared between many eastern populations that date roughly to the migration period (which includes the Slavic and Hunnic expansions into that region). Some of the lowest levels of common ancestry are seen in the Italian and Iberian peninsulas, which may indicate different effects of historical population expansions in these areas and/or more stably structured populations. Population genomic datasets have considerable power to uncover recent demographic history, and will allow a much fuller picture of the close genealogical kinship of individuals across the world.

Few of us know our family histories more than a few generations back. It is therefore easy to overlook the fact that we are all distant cousins, related to one another via a vast network of relationships. Here we use genome-wide data from European individuals to investigate these relationships over the past 3,000 years, by looking for long stretches of genome that are shared between pairs of individuals through their inheritance from common genetic ancestors. We quantify this ubiquitous recent common ancestry, showing for instance that even pairs of individuals from opposite ends of Europe share hundreds of genetic common ancestors over this time period. Despite this degree of commonality, there are also striking regional differences. Southeastern Europeans, for example, share large numbers of common ancestors that date roughly to the era of the Slavic and Hunnic expansions around 1,500 years ago, while most common ancestors that Italians share with other populations lived longer than 2,500 years ago. The study of long stretches of shared genetic material promises to uncover rich information about many aspects of recent population history.

A fast least-squares algorithm for population inference

BACKGROUND

Population inference is an important problem in genetics used to remove population stratification in genome-wide association studies and to detect migration patterns or shared ancestry. An individual's genotype can be modeled as a probabilistic function of ancestral population memberships, Q, and the allele frequencies in those populations, P. The parameters, P and Q, of this binomial likelihood model can be inferred using slow sampling methods such as Markov Chain Monte Carlo methods or faster gradient based approaches such as sequential quadratic programming. This paper proposes a least-squares simplification of the binomial likelihood model motivated by a Euclidean interpretation of the genotype feature space. This results in a faster algorithm that easily incorporates the degree of admixture within the sample of individuals and improves estimates without requiring trial-and-error tuning.

RESULTS

We show that the expected value of the least-squares solution across all possible genotype datasets is equal to the true solution when part of the problem has been solved, and that the variance of the solution approaches zero as its size increases. The Least-squares algorithm performs nearly as well as Admixture for these theoretical scenarios. We compare least-squares, Admixture, and FRAPPE for a variety of problem sizes and difficulties. For particularly hard problems with a large number of populations, small number of samples, or greater degree of admixture, least-squares performs better than the other methods. On simulated mixtures of real population allele frequencies from the HapMap project, Admixture estimates sparsely mixed individuals better than Least-squares. The least-squares approach, however, performs within 1.5% of the Admixture error. On individual genotypes from the HapMap project, Admixture and least-squares perform qualitatively similarly and within 1.2% of each other. Significantly, the least-squares approach nearly always converges 1.5- to 6-times faster.

CONCLUSIONS

The computational advantage of the least-squares approach along with its good estimation performance warrants further research, especially for very large datasets. As problem sizes increase, the difference in estimation performance between all algorithms decreases. In addition, when prior information is known, the least-squares approach easily incorporates the expected degree of admixture to improve the estimate.

HGDP and HapMap analysis by Ancestry Mapper reveals local and global population relationships

Knowledge of human origins, migrations, and expansions is greatly enhanced by the availability of large datasets of genetic information from different populations and by the development of bioinformatic tools used to analyze the data. We present Ancestry Mapper, which we believe improves on existing methods, for the assignment of genetic ancestry to an individual and to study the relationships between local and global populations. The principle function of the method, named Ancestry Mapper, is to give each individual analyzed a genetic identifier, made up of just 51 genetic coordinates, that corresponds to its relationship to the HGDP reference population. As a consequence, the Ancestry Mapper Id (AMid) has intrinsic biological meaning and provides a tool to measure similarity between world populations. We applied Ancestry Mapper to a dataset comprised of the HGDP and HapMap data. The results show distinctions at the continental level, while simultaneously giving details at the population level. We clustered AMids of HGDP/HapMap and observe a recapitulation of human migrations: for a small number of clusters, individuals are grouped according to continental origins; for a larger number of clusters, regional and population distinctions are evident. Calculating distances between AMids allows us to infer ancestry. The number of coordinates is expandable, increasing the power of Ancestry Mapper. An R package called Ancestry Mapper is available to apply this method to any high density genomic data set.

Inference of population splits and mixtures from genome-wide allele frequency data

Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In our model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data, we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.com.

Influence of admixture and paleolithic range contractions on current European diversity gradients

Cavalli-Sforza and Edwards (Analysis of human evolution. 1963. In: Geerts SJ, editor. Genetics today: Proceedings of the 11th International Congress of Genetics, The Hague, The Netherlands. New York: Pergamon. p. 923-993.) initiated the representation of genetic relationships among human populations with principal component (PC) analysis (PCA). Their study revealed the presence of a southeast-northwest (SE-NW) gradient of genetic variation in current European populations, which was interpreted as the result of the demic diffusion of early neolithic farmers during their expansion from the near east. However, this interpretation has been questioned, as PCA gradients can occur even when there is no expansion and because the first PC axis is often orthogonal to the expansion axis. Here, we revisit PCA patterns obtained under realistic scenarios of the settlement of Europe, focusing on the effects of various levels of admixture between paleolithic and neolithic populations, and of range contractions during the last glacial maximum (LGM). Using extensive simulations, we find that the first PC (PC1) gradients are orthogonal to the expansion axis, but only when the expansion is recent (neolithic). More ancient (paleolithic) expansions alter the orientation of the PC1 gradient due to a spatial homogenization of genetic diversity over time, and to the exact location of LGM refugia from which re-expansions proceeded. Overall we find that PC1 gradients consistently follow an SE-NW orientation if there is a large paleolithic contribution to the current European gene pool, and if the main refuge area during the last ice age was in the Iberian Peninsula. Our study suggests that an SE-NW PC1 gradient is compatible with little genetic impact of neolithic populations on the current European gene pool, and that range contractions have affected observed genetic patterns.

A quantitative comparison of the similarity between genes and geography in worldwide human populations

Multivariate statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been widely used to summarize the structure of human genetic variation, often in easily visualized two-dimensional maps. Many recent studies have reported similarity between geographic maps of population locations and MDS or PCA maps of genetic variation inferred from single-nucleotide polymorphisms (SNPs). However, this similarity has been evident primarily in a qualitative sense; and, because different multivariate techniques and marker sets have been used in different studies, it has not been possible to formally compare genetic variation datasets in terms of their levels of similarity with geography. In this study, using genome-wide SNP data from 128 populations worldwide, we perform a systematic analysis to quantitatively evaluate the similarity of genes and geography in different geographic regions. For each of a series of regions, we apply a Procrustes analysis approach to find an optimal transformation that maximizes the similarity between PCA maps of genetic variation and geographic maps of population locations. We consider examples in Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, as well as in a worldwide sample, finding that significant similarity between genes and geography exists in general at different geographic levels. The similarity is highest in our examples for Asia and, once highly distinctive populations have been removed, Sub-Saharan Africa. Our results provide a quantitative assessment of the geographic structure of human genetic variation worldwide, supporting the view that geography plays a strong role in giving rise to human population structure.

The spatial pattern of human genetic variation provides a basis for investigating the history of human migrations. Statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been used to summarize spatial patterns of genetic variation, typically by placing individuals on a two-dimensional map in such a way that pairwise Euclidean distances between individuals on the map approximately reflect corresponding genetic relationships. Although similarity between these statistical maps of genetic variation and the geographic maps of sampling locations is often observed, it has not been assessed systematically across different parts of the world. In this study, we combine genome-wide SNP data from more than 100 populations worldwide to perform a formal comparison between genes and geography in different regions. By examining a worldwide sample and samples from Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, we find that significant similarity between genes and geography exists in general in different geographic regions and at different geographic levels. Surprisingly, the highest similarity is found in Asia, even though the geographic barrier of the Himalaya Mountains has created a discontinuity on the PCA map of genetic variation.

A population-genetic perspective on the similarities and differences among worldwide human populations

Recent studies have produced a variety of advances in the investigation of genetic similarities and differences among human populations. Here, I pose a series of questions about human population-genetic similarities and differences, and I then answer these questions by numerical computation with a single shared population-genetic data set. The collection of answers obtained provides an introductory perspective for understanding key results on the features of worldwide human genetic variation.

Human population structure and the adaptive response to pathogen-induced selection pressures

The past few years of research in human evolutionary genetics have provided novel insights and questions regarding how human adaptations to recent selective pressures have taken place. Here, we review the advances most relevant to understanding human evolution in response to pathogen-induced selective pressures. Key insights come from theoretical models of adaptive evolution, particularly those that consider spatially structured populations, and from empirical population genomic studies of adaptive evolution in humans. We also review the CCR5-Δ32 HIV resistance allele as a case study of pathogen resistance in humans. Taken together, the results make clear that the human response to pathogen-induced selection pressures depends on a complex interplay between the age of the pathogen, the genetic basis of potential resistance phenotypes, and how population structure impacts the adaptive process in humans.

The impact of recent events on human genetic diversity

The historical record tells us stories of migrations, population expansions and colonization events in the last few thousand years, but what was their demographic impact? Genetics can throw light on this issue, and has mostly done so through the maternally inherited mitochondrial DNA (mtDNA) and the male-specific Y chromosome. However, there are a number of problems, including marker ascertainment bias, possible influences of natural selection, and the obscuring layers of the palimpsest of historical and prehistorical events. Y-chromosomal lineages are particularly affected by genetic drift, which can be accentuated by recent social selection. A diversity of approaches to expansions in Europe is yielding insights into the histories of Phoenicians, Roma, Anglo-Saxons and Vikings, and new methods for producing and analysing genome-wide data hold much promise. The field would benefit from more consensus on appropriate methods, and better communication between geneticists and experts in other disciplines, such as history, archaeology and linguistics.

Archaic human ancestry in East Asia

Recent studies of ancient genomes have suggested that gene flow from archaic hominin groups to the ancestors of modern humans occurred on two separate occasions during the modern human expansion out of Africa. At the same time, decreasing levels of human genetic diversity have been found at increasing distance from Africa as a consequence of human expansion out of Africa. We analyzed the signal of archaic ancestry in modern human populations, and we investigated how serial founder models of human expansion affect the signal of archaic ancestry using simulations. For descendants of an archaic admixture event, we show that genetic drift coupled with ascertainment bias for common alleles can cause artificial but largely predictable differences in similarity to archaic genomes. In genotype data from non-Africans, this effect results in a biased genetic similarity to Neandertals with increasing distance from Africa. However, in addition to the previously reported gene flow between Neandertals and non-Africans as well as gene flow between an archaic human population from Siberia ("Denisovans") and Oceanians, we found a significant affinity between East Asians, particularly Southeast Asians, and the Denisova genome--a pattern that is not expected under a model of solely Neandertal admixture in the ancestry of East Asians. These results suggest admixture between Denisovans or a Denisova-related population and the ancestors of East Asians, and that the history of anatomically modern and archaic humans might be more complex than previously proposed.