Possible ancestral structure in human populations

Inference of Locus-Specific Population Mixtures from Linked Genome-Wide Allele Frequencies

Admixture between populations and species is common in nature. Since the influx of new genetic material might be either facilitated or hindered by selection, variation in mixture proportions along the genome is expected in organisms undergoing recombination. Various graph-based models have been developed to better understand these evolutionary dynamics of population splits and mixtures. However, current models assume a single mixture rate for the entire genome and do not explicitly account for linkage. Here, we introduce TreeSwirl, a novel method for inferring branch lengths and locus-specific mixture proportions by using genome-wide allele frequency data, assuming that the admixture graph is known or has been inferred. TreeSwirl builds upon TreeMix that uses Gaussian processes to estimate the presence of gene flow between diverged populations. However, in contrast to TreeMix, our model infers locus-specific mixture proportions employing a hidden Markov model that accounts for linkage. Through simulated data, we demonstrate that TreeSwirl can accurately estimate locus-specific mixture proportions and handle complex demographic scenarios. It also outperforms related D- and f-statistics in terms of accuracy and sensitivity to detect introgressed loci.

IntroUNET: Identifying introgressed alleles via semantic segmentation

A growing body of evidence suggests that gene flow between closely related species is a widespread phenomenon. Alleles that introgress from one species into a close relative are typically neutral or deleterious, but sometimes confer a significant fitness advantage. Given the potential relevance to speciation and adaptation, numerous methods have therefore been devised to identify regions of the genome that have experienced introgression. Recently, supervised machine learning approaches have been shown to be highly effective for detecting introgression. One especially promising approach is to treat population genetic inference as an image classification problem, and feed an image representation of a population genetic alignment as input to a deep neural network that distinguishes among evolutionary models (i.e. introgression or no introgression). However, if we wish to investigate the full extent and fitness effects of introgression, merely identifying genomic regions in a population genetic alignment that harbor introgressed loci is insufficient-ideally we would be able to infer precisely which individuals have introgressed material and at which positions in the genome. Here we adapt a deep learning algorithm for semantic segmentation, the task of correctly identifying the type of object to which each individual pixel in an image belongs, to the task of identifying introgressed alleles. Our trained neural network is thus able to infer, for each individual in a two-population alignment, which of those individual's alleles were introgressed from the other population. We use simulated data to show that this approach is highly accurate, and that it can be readily extended to identify alleles that are introgressed from an unsampled "ghost" population, performing comparably to a supervised learning method tailored specifically to that task. Finally, we apply this method to data from Drosophila, showing that it is able to accurately recover introgressed haplotypes from real data. This analysis reveals that introgressed alleles are typically confined to lower frequencies within genic regions, suggestive of purifying selection, but are found at much higher frequencies in a region previously shown to be affected by adaptive introgression. Our method's success in recovering introgressed haplotypes in challenging real-world scenarios underscores the utility of deep learning approaches for making richer evolutionary inferences from genomic data.

IntroUNET: identifying introgressed alleles via semantic segmentation

A growing body of evidence suggests that gene flow between closely related species is a widespread phenomenon. Alleles that introgress from one species into a close relative are typically neutral or deleterious, but sometimes confer a significant fitness advantage. Given the potential relevance to speciation and adaptation, numerous methods have therefore been devised to identify regions of the genome that have experienced introgression. Recently, supervised machine learning approaches have been shown to be highly effective for detecting introgression. One especially promising approach is to treat population genetic inference as an image classification problem, and feed an image representation of a population genetic alignment as input to a deep neural network that distinguishes among evolutionary models (i.e. introgression or no introgression). However, if we wish to investigate the full extent and fitness effects of introgression, merely identifying genomic regions in a population genetic alignment that harbor introgressed loci is insufficient-ideally we would be able to infer precisely which individuals have introgressed material and at which positions in the genome. Here we adapt a deep learning algorithm for semantic segmentation, the task of correctly identifying the type of object to which each individual pixel in an image belongs, to the task of identifying introgressed alleles. Our trained neural network is thus able to infer, for each individual in a two-population alignment, which of those individual's alleles were introgressed from the other population. We use simulated data to show that this approach is highly accurate, and that it can be readily extended to identify alleles that are introgressed from an unsampled "ghost" population, performing comparably to a supervised learning method tailored specifically to that task. Finally, we apply this method to data from Drosophila, showing that it is able to accurately recover introgressed haplotypes from real data. This analysis reveals that introgressed alleles are typically confined to lower frequencies within genic regions, suggestive of purifying selection, but are found at much higher frequencies in a region previously shown to be affected by adaptive introgression. Our method's success in recovering introgressed haplotypes in challenging real-world scenarios underscores the utility of deep learning approaches for making richer evolutionary inferences from genomic data.

Inferring Historical Introgression with Deep Learning

Resolving phylogenetic relationships among taxa remains a challenge in the era of big data due to the presence of genetic admixture in a wide range of organisms. Rapidly developing sequencing technologies and statistical tests enable evolutionary relationships to be disentangled at a genome-wide level, yet many of these tests are computationally intensive and rely on phased genotypes, large sample sizes, restricted phylogenetic topologies, or hypothesis testing. To overcome these difficulties, we developed a deep learning-based approach, named ERICA, for inferring genome-wide evolutionary relationships and local introgressed regions from sequence data. ERICA accepts sequence alignments of both population genomic data and multiple genome assemblies, and efficiently identifies discordant genealogy patterns and exchanged regions across genomes when compared with other methods. We further tested ERICA using real population genomic data from Heliconius butterflies that have undergone adaptive radiation and frequent hybridization. Finally, we applied ERICA to characterize hybridization and introgression in wild and cultivated rice, revealing the important role of introgression in rice domestication and adaptation. Taken together, our findings demonstrate that ERICA provides an effective method for teasing apart evolutionary relationships using whole genome data, which can ultimately facilitate evolutionary studies on hybridization and introgression.

Ghost admixture in eastern gorillas

Archaic admixture has had a substantial impact on human evolution with multiple events across different clades, including from extinct hominins such as Neanderthals and Denisovans into modern humans. In great apes, archaic admixture has been identified in chimpanzees and bonobos but the possibility of such events has not been explored in other species. Here, we address this question using high-coverage whole-genome sequences from all four extant gorilla subspecies, including six newly sequenced eastern gorillas from previously unsampled geographic regions. Using approximate Bayesian computation with neural networks to model the demographic history of gorillas, we find a signature of admixture from an archaic 'ghost' lineage into the common ancestor of eastern gorillas but not western gorillas. We infer that up to 3% of the genome of these individuals is introgressed from an archaic lineage that diverged more than 3 million years ago from the common ancestor of all extant gorillas. This introgression event took place before the split of mountain and eastern lowland gorillas, probably more than 40 thousand years ago and may have influenced perception of bitter taste in eastern gorillas. When comparing the introgression landscapes of gorillas, humans and bonobos, we find a consistent depletion of introgressed fragments on the X chromosome across these species. However, depletion in protein-coding content is not detectable in eastern gorillas, possibly as a consequence of stronger genetic drift in this species.

Resurrecting the alternative splicing landscape of archaic hominins using machine learning

Alternative splicing contributes to adaptation and divergence in many species. However, it has not been possible to directly compare splicing between modern and archaic hominins. Here, we unmask the recent evolution of this previously unobservable regulatory mechanism by applying SpliceAI, a machine-learning algorithm that identifies splice-altering variants (SAVs), to high-coverage genomes from three Neanderthals and a Denisovan. We discover 5,950 putative archaic SAVs, of which 2,186 are archaic-specific and 3,607 also occur in modern humans via introgression (244) or shared ancestry (3,520). Archaic-specific SAVs are enriched in genes that contribute to traits potentially relevant to hominin phenotypic divergence, such as the epidermis, respiration and spinal rigidity. Compared to shared SAVs, archaic-specific SAVs occur in sites under weaker selection and are more common in genes with tissue-specific expression. Further underscoring the importance of negative selection on SAVs, Neanderthal lineages with low effective population sizes are enriched for SAVs compared to Denisovan and shared SAVs. Finally, we find that nearly all introgressed SAVs in humans were shared across the three Neanderthals, suggesting that older SAVs were more tolerated in human genomes. Our results reveal the splicing landscape of archaic hominins and identify potential contributions of splicing to phenotypic differences among hominins.

A weakly structured stem for human origins in Africa

Despite broad agreement that Homo sapiens originated in Africa, considerable uncertainty surrounds specific models of divergence and migration across the continent1. Progress is hampered by a shortage of fossil and genomic data, as well as variability in previous estimates of divergence times1. Here we seek to discriminate among such models by considering linkage disequilibrium and diversity-based statistics, optimized for rapid, complex demographic inference2. We infer detailed demographic models for populations across Africa, including eastern and western representatives, and newly sequenced whole genomes from 44 Nama (Khoe-San) individuals from southern Africa. We infer a reticulated African population history in which present-day population structure dates back to Marine Isotope Stage 5. The earliest population divergence among contemporary populations occurred 120,000 to 135,000 years ago and was preceded by links between two or more weakly differentiated ancestral Homo populations connected by gene flow over hundreds of thousands of years. Such weakly structured stem models explain patterns of polymorphism that had previously been attributed to contributions from archaic hominins in Africa2-7. In contrast to models with archaic introgression, we predict that fossil remains from coexisting ancestral populations should be genetically and morphologically similar, and that only an inferred 1-4% of genetic differentiation among contemporary human populations can be attributed to genetic drift between stem populations. We show that model misspecification explains the variation in previous estimates of divergence times, and argue that studying a range of models is key to making robust inferences about deep history.

Evolutionary Genetics and Admixture in African Populations

As the ancestral homeland of our species, Africa contains elevated levels of genetic diversity and substantial population structure. Importantly, African genomes are heterogeneous: They contain mixtures of multiple ancestries, each of which have experienced different evolutionary histories. In this review, we view population genetics through the lens of admixture, highlighting how multiple demographic events have shaped African genomes. Each of these historical vignettes paints a recurring picture of population divergence followed by secondary contact. First, we give a brief overview of genetic variation in Africa and examine deep population structure within Africa, including the evidence of ancient introgression from archaic "ghost" populations. Second, we describe the genetic legacies of admixture events that have occurred during the past 10,000 years. This includes gene flow between different click-speaking Khoe-San populations, the stepwise spread of pastoralism from eastern to southern Africa, multiple migrations of Bantu speakers across the continent, as well as admixture from the Middle East and Europe into the Sahel region and North Africa. Furthermore, the genomic signatures of more recent admixture can be found in the Cape Peninsula and throughout the African diaspora. Third, we highlight how natural selection has shaped patterns of genetic variation across the continent, noting that gene flow provides a potent source of adaptive variation and that selective pressures vary across Africa. Finally, we explore the biomedical implications of population structure in Africa on health and disease and call for more ethically conducted studies of genetic variation in Africa.

Modern Japanese ancestry-derived variants reveal the formation process of the current Japanese regional gradations

Modern Japanese people have two major ancestral populations: indigenous Jomon hunter-gatherers and continental East Asian farmers. To determine the formation process of the current Japanese population, we developed a detection method for variants derived from ancestral populations using a summary statistic, the ancestry marker index (AMI). We applied AMI to modern Japanese population samples and identified 208,648 single nucleotide polymorphisms (SNPs) that were likely derived from the Jomon people (Jomon-derived variants). Analysis of Jomon-derived variants in 10,842 modern Japanese individuals recruited from all over Japan revealed that the admixture proportions of the Jomon people varied between prefectures, probably owing to the prehistoric population size difference. The estimated allele frequencies of genome-wide SNPs in the ancestral populations of the modern Japanese suggested their adaptive phenotypic characteristics to their respective livelihoods. Based on our findings, we propose a formation model for the genotypic and phenotypic gradations of the current Japanese archipelago populations.

Estimating bonobo (Pan paniscus) and chimpanzee (Pan troglodytes) evolutionary history from nucleotide site patterns

There is genomic evidence of widespread admixture in deep time between many closely related species, including humans. Our closest living relatives, bonobos and chimpanzees, may also exhibit such patterns. However, assessing the exact degree of interbreeding remains challenging because previous studies have resulted in multiple inconsistent demographic models. We use an approach that addresses these gaps by analyzing all lineages, simultaneously estimating parameters, and comparing previously models. We find evidence of considerable introgression from western into eastern chimpanzees. We also show more breeding females than males and evidence of male-biased dispersal in western chimpanzees. These findings highlight the extent of admixture in bonobo and chimpanzee evolutionary history and are consistent with substantial differences between past and present chimpanzee biogeography.

Admixture appears increasingly ubiquitous in the evolutionary history of various taxa, including humans. Such gene flow likely also occurred among our closest living relatives: bonobos (Pan paniscus) and chimpanzees (Pan troglodytes). However, our understanding of their evolutionary history has been limited by studies that do not consider all Pan lineages or do not analyze all lineages simultaneously, resulting in conflicting demographic models. Here, we investigate this gap in knowledge using nucleotide site patterns calculated from whole-genome sequences from the autosomes of 71 bonobos and chimpanzees, representing all five extant Pan lineages. We estimated demographic parameters and compared all previously proposed demographic models for this clade. We further considered sex bias in Pan evolutionary history by analyzing the site patterns from the X chromosome. We show that 1) 21% of autosomal DNA in eastern chimpanzees derives from western chimpanzee introgression and that 2) all four chimpanzee lineages share a common ancestor about 987,000 y ago, much earlier than previous estimates. In addition, we suggest that 3) there was male reproductive skew throughout Pan evolutionary history and find evidence of 4) male-biased dispersal from western to eastern chimpanzees. Collectively, these results offer insight into bonobo and chimpanzee evolutionary history and suggest considerable differences between current and historic chimpanzee biogeography.

Lower promoter activity of the ST8SIA2 gene has been favored in evolving human collective brains

ST8SIA2 is an important molecule regulating expression of the phenotype involved in schizophrenia. Lowered promoter activity of the ST8SIA2 gene is considered to be protective against schizophrenia by conferring tolerance to psychosocial stress. Here, we examined the promoter-type composition of anatomically modern humans (AMHs) and archaic humans (AHs; Neanderthals and Denisovans), and compared the promoter activity at the population level (population promoter activity; PPA) between them. In AMHs, the TCT-type, showing the second lowest promoter activity, was most prevalent in the ancestral population of non-Africans. However, the detection of only the CGT-type from AH samples and recombination tracts in AH sequences showed that the CGT- and TGT-types, exhibiting the two highest promoter activities, were common in AH populations. Furthermore, interspecies gene flow occurred into AMHs from AHs and into Denisovans from Neanderthals, influencing promoter-type compositions independently in both AMHs and AHs. The difference of promoter-type composition makes PPA unique in each population. East and Southeast Asian populations show the lowest PPA. This results from the selective increase of the CGC-type, showing the lowest promoter activity, in these populations. Every non-African population shows significantly lower PPA than African populations, resulting from the TCT-type having the highest prevalence in the ancestral population of non-Africans. In addition, PPA reduction is also found among subpopulations within Africa via a slight increase of the TCT-type. These findings indicate a trend toward lower PPA in the spread of AMHs, interpreted as a continuous adaptation to psychosocial stress arising in migration. This trend is considered as genetic tuning for the evolution of collective brains. The inferred promoter-type composition of AHs differed markedly from that of AMHs, resulting in higher PPA in AHs than in AMHs. This suggests that the trend toward lower PPA is a unique feature in AMH spread.

Refining models of archaic admixture in Eurasia with ArchaicSeeker 2.0

We developed a method, ArchaicSeeker 2.0, to identify introgressed hominin sequences and model multiple-wave admixture. The new method enabled us to discern two waves of introgression from both Denisovan-like and Neanderthal-like hominins in present-day Eurasian populations and an ancient Siberian individual. We estimated that an early Denisovan-like introgression occurred in Eurasia around 118.8-94.0 thousand years ago (kya). In contrast, we detected only one single episode of Denisovan-like admixture in indigenous peoples eastern to the Wallace-Line. Modeling ancient admixtures suggested an early dispersal of modern humans throughout Asia before the Toba volcanic super-eruption 74 kya, predating the initial peopling of Asia as proposed by the traditional Out-of-Africa model. Survived archaic sequences are involved in various phenotypes including immune and body mass (e.g., ZNF169), cardiovascular and lung function (e.g., HHAT), UV response and carbohydrate metabolism (e.g., HYAL1/HYAL2/HYAL3), while "archaic deserts" are enriched with genes associated with skin development and keratinization.

Finding unknown species in the genomes of extant species

Although many species have gone extinct, their genetic components might exist in extant species because of ancient hybridization. Via advances in genome sequencing and development of modern population genetics, one can find the legacy of unknown or extinct species in the context of available genomes from extant species. Such discovery can be used as a strategy to search for hidden species or fossils in conservation biology and archeology, gain novel insight into complex evolutionary history, and provide the new sources of genetic variation for breeding and trait improvement in agriculture.

Our Tangled Family Tree: New Genomic Methods Offer Insight into the Legacy of Archaic Admixture

The archaic ancestry present in the human genome has captured the imagination of both scientists and the wider public in recent years. This excitement is the result of new studies pushing the envelope of what we can learn from the archaic genetic information that has survived for over 50,000 years in the human genome. Here, we review the most recent ten years of literature on the topic of archaic introgression, including the current state of knowledge on Neanderthal and Denisovan introgression, as well as introgression from other as-yet unidentified archaic populations. We focus this review on four topics: 1) a reimagining of human demographic history, including evidence for multiple admixture events between modern humans, Neanderthals, Denisovans, and other archaic populations; 2) state-of-the-art methods for detecting archaic ancestry in population-level genomic data; 3) how these novel methods can detect archaic introgression in modern African populations; and 4) the functional consequences of archaic gene variants, including how those variants were co-opted into novel function in modern human populations. The goal of this review is to provide a simple-to-access reference for the relevant methods and novel data, which has changed our understanding of the relationship between our species and its siblings. This body of literature reveals the large degree to which the genetic legacy of these extinct hominins has been integrated into the human populations of today.

Introgression is widespread in the radiation of carnivorous Nepenthes pitcher plants

Introgression and hybridization are important processes in plant evolution, but they are difficult to study from a phylogenetic perspective, because they conflict with the bifurcating evolutionary history typically depicted in phylogenetic models. The role of hybridization in plant evolution is best documented in the form of allo-polyploidizations. In contrast, homoploid hybridization and introgression are less explored, although they may be crucial in adaptive radiations. Here we employ genome-wide data (ddRAD-seq, transcriptomes) to investigate the evolutionary history of Nepenthes, a radiation of c. 160 species of iconic carnivorous plants mainly from tropical Asia. Our data indicates that the main radiation is only c. 5 million years old, and confirms previous bifurcating phylogenies. However, due to a greatly expanded number of loci, we were able test for the first time the long-standing hypotheses of introgression and historical hybridization. The genus presents one very clear case of organellar capture between two distantly related but sympatric groups. Furthermore, all Nepenthes species show introgression signals in their nuclear genomes, as uncovered by a general survey of ABBA-BABA-like statistics. The ancestor of the rapid main radiation shows ancestry from two deeply diverged lineages, as indicated by phylogenetic network analyses. All major clades of the main radiation show further introgression both within and between each other, as suggested by admixture graphs. Our study supports the hypothesis that rapid adaptive radiations are hotspots of introgression in the tree of life, and highlights the need to consider non-treelike processes in evolutionary studies of Nepenthes in particular.

A history of you, me, and humanity: mitochondrial DNA in anthropological research

Within genetic anthropology, mitochondrial DNA (mtDNA) has garnered a prominent if not enduring place within the anthropological toolkit. MtDNA has provided new and innovative perspectives on the emergence and dispersal of our species, interactions with extinct human species, and illuminated relationships between human groups. In this paper, I provide a brief overview of the major findings ascertained from mtDNA about human origins, human dispersal across the globe, interactions with other hominin species, and the more recent uses of mtDNA in direct to consumer ancestry tests. Relative to nuclear DNA, mtDNA is a small section of the genome and due to its inheritance pattern provides a limited resolution of population history and an individual's genetic ancestry. Consequently, some scholars dismiss mtDNA as insignificant due to the limited inferences that may be made using the locus. Regardless, mtDNA provides some useful insights to understanding how social, cultural, and environmental factors have shaped patterns of genetic variability. Furthermore, with regard to the experiences of historically marginalized groups, in particular those of African descent throughout the Americas, mtDNA has the potential to fill gaps in knowledge that would otherwise remain unknown. Within anthropological sciences, the value of this locus for understanding human experience is maximized when contextualized with complementary lines of evidence.

Inferring archaic introgression from hominin genetic data

Questions surrounding the timing, extent, and evolutionary consequences of archaic admixture into human populations have a long history in evolutionary anthropology. More recently, advances in human genetics, particularly in the field of ancient DNA, have shed new light on the question of whether or not Homo sapiens interbred with other hominin groups. By the late 1990s, published genetic work had largely concluded that archaic groups made no lasting genetic contribution to modern humans; less than a decade later, this conclusion was reversed following the successful DNA sequencing of an ancient Neanderthal. This reversal of consensus is noteworthy, but the reasoning behind it is not widely understood across all academic communities. There remains a communication gap between population geneticists and paleoanthropologists. In this review, we endeavor to bridge this gap by outlining how technological advancements, new statistical methods, and notable controversies ultimately led to the current consensus.

The deep population history in Africa

Africa is the continent with the greatest genetic diversity among humans and the level of diversity is further enhanced by incorporating non-majority groups, which are often understudied. Many of today's minority populations historically practiced foraging lifestyles, which were the only subsistence strategies prior to the rise of agriculture and pastoralism, but only a few groups practicing these strategies remain today. Genomic investigations of Holocene human remains excavated across the African continent show that the genetic landscape was vastly different compared to today's genetic landscape and that many groups that today are population isolate inhabited larger regions in the past. It is becoming clear that there are periods of isolation among groups and geographic areas, but also genetic contact over large distances throughout human history in Africa. Genomic information from minority populations and from prehistoric remains provide an invaluable source of information on the human past, in particular deep human population history, as Holocene large-scale population movements obscure past patterns of population structure. Here we revisit questions on the nature and time of the radiation of early humans in Africa, the extent of gene-flow among human populations as well as introgression from archaic and extinct lineages on the continent.

Origins of modern human ancestry

New finds in the palaeoanthropological and genomic records have changed our view of the origins of modern human ancestry. Here we review our current understanding of how the ancestry of modern humans around the globe can be traced into the deep past, and which ancestors it passes through during our journey back in time. We identify three key phases that are surrounded by major questions, and which will be at the frontiers of future research. The most recent phase comprises the worldwide expansion of modern humans between 40 and 60 thousand years ago (ka) and their last known contacts with archaic groups such as Neanderthals and Denisovans. The second phase is associated with a broadly construed African origin of modern human diversity between 60 and 300 ka. The oldest phase comprises the complex separation of modern human ancestors from archaic human groups from 0.3 to 1 million years ago. We argue that no specific point in time can currently be identified at which modern human ancestry was confined to a limited birthplace, and that patterns of the first appearance of anatomical or behavioural traits that are used to define Homo sapiens are consistent with a range of evolutionary histories.

Mapping gene flow between ancient hominins through demography-aware inference of the ancestral recombination graph

The sequencing of Neanderthal and Denisovan genomes has yielded many new insights about interbreeding events between extinct hominins and the ancestors of modern humans. While much attention has been paid to the relatively recent gene flow from Neanderthals and Denisovans into modern humans, other instances of introgression leave more subtle genomic evidence and have received less attention. Here, we present a major extension of the ARGweaver algorithm, called ARGweaver-D, which can infer local genetic relationships under a user-defined demographic model that includes population splits and migration events. This Bayesian algorithm probabilistically samples ancestral recombination graphs (ARGs) that specify not only tree topologies and branch lengths along the genome, but also indicate migrant lineages. The sampled ARGs can therefore be parsed to produce probabilities of introgression along the genome. We show that this method is well powered to detect the archaic migration into modern humans, even with only a few samples. We then show that the method can also detect introgressed regions stemming from older migration events, or from unsampled populations. We apply it to human, Neanderthal, and Denisovan genomes, looking for signatures of older proposed migration events, including ancient humans into Neanderthal, and unknown archaic hominins into Denisovans. We identify 3% of the Neanderthal genome that is putatively introgressed from ancient humans, and estimate that the gene flow occurred between 200-300kya. We find no convincing evidence that negative selection acted against these regions. Finally, we predict that 1% of the Denisovan genome was introgressed from an unsequenced, but highly diverged, archaic hominin ancestor. About 15% of these “super-archaic” regions—comprising at least about 4Mb—were, in turn, introgressed into modern humans and continue to exist in the genomes of people alive today.

We present ARGweaver-D, an extension of the ARGweaver algorithm which can be applied under a user-defined demographic model including population splits and migration events. Given genome sequence data from a collection of individuals across multiple closely related populations or subspecies, ARGweaver-D can infer trees describing the genetic relationships among these individuals at every location along the genome, conditional on the demographic model. Like ARGweaver, ARGweaver-D is a Bayesian method, sampling trees from the posterior distribution in order to account for uncertainty. Using simulations, we show that ARGweaver-D can successfully identify regions introgressed from Neanderthals and Denisovans into modern humans. It is also well-powered to detect introgressed regions stemming from older gene-flow events. We apply ARGweaver-D to the genomes of two Neanderthals, a Denisovan, and two African humans. We identify 3% of the Neanderthal genome which is likely derived from gene flow from ancient humans. We also identify about 1% of the Denisovan genome that may be traced to an unsequenced archaic hominin; 15% of these regions were subsequently passed to modern humans. We find no convincing evidence that selection acted against any of these introgressed regions.

Learning the properties of adaptive regions with functional data analysis

Identifying regions of positive selection in genomic data remains a challenge in population genetics. Most current approaches rely on comparing values of summary statistics calculated in windows. We present an approach termed SURFDAWave, which translates measures of genetic diversity calculated in genomic windows to functional data. By transforming our discrete data points to be outputs of continuous functions defined over genomic space, we are able to learn the features of these functions that signify selection. This enables us to confidently identify complex modes of natural selection, including adaptive introgression. We are also able to predict important selection parameters that are responsible for shaping the inferred selection events. By applying our model to human population-genomic data, we recapitulate previously identified regions of selective sweeps, such as OCA2 in Europeans, and predict that its beneficial mutation reached a frequency of 0.02 before it swept 1,802 generations ago, a time when humans were relatively new to Europe. In addition, we identify BNC2 in Europeans as a target of adaptive introgression, and predict that it harbors a beneficial mutation that arose in an archaic human population that split from modern humans within the hypothesized modern human-Neanderthal divergence range.

Inferring evolutionary dynamics of mutation rates through the lens of mutation spectrum variation

There are many possible failure points in the transmission of genetic information that can produce heritable germline mutations. Once a mutation has been passed from parents to offspring for several generations, it can be difficult or impossible to identify its root cause; however, sometimes the nature of the ancestral and derived DNA sequences can provide mechanistic clues about a genetic change that happened hundreds or thousands of generations ago. Here, we review evidence that the sequence context 'spectrum' of germline mutagenesis has been evolving surprisingly rapidly over the history of humans and other species. We go on to discuss possible causal factors that might underlie rapid mutation spectrum evolution.

VolcanoFinder: Genomic scans for adaptive introgression

Recent research shows that introgression between closely-related species is an important source of adaptive alleles for a wide range of taxa. Typically, detection of adaptive introgression from genomic data relies on comparative analyses that require sequence data from both the recipient and the donor species. However, in many cases, the donor is unknown or the data is not currently available. Here, we introduce a genome-scan method—VolcanoFinder—to detect recent events of adaptive introgression using polymorphism data from the recipient species only. VolcanoFinder detects adaptive introgression sweeps from the pattern of excess intermediate-frequency polymorphism they produce in the flanking region of the genome, a pattern which appears as a volcano-shape in pairwise genetic diversity. Using coalescent theory, we derive analytical predictions for these patterns. Based on these results, we develop a composite-likelihood test to detect signatures of adaptive introgression relative to the genomic background. Simulation results show that VolcanoFinder has high statistical power to detect these signatures, even for older sweeps and for soft sweeps initiated by multiple migrant haplotypes. Finally, we implement VolcanoFinder to detect archaic introgression in European and sub-Saharan African human populations, and uncovered interesting candidates in both populations, such as TSHR in Europeans and TCHH-RPTN in Africans. We discuss their biological implications and provide guidelines for identifying and circumventing artifactual signals during empirical applications of VolcanoFinder.

The process by which beneficial alleles are introduced into a species from a closely-related species is termed adaptive introgression. We present an analytically-tractable model for the effects of adaptive introgression on non-adaptive genetic variation in the genomic region surrounding the beneficial allele. The result we describe is a characteristic volcano-shaped pattern of increased variability that arises around the positively-selected site, and we introduce an open-source method VolcanoFinder to detect this signal in genomic data. Importantly, VolcanoFinder is a population-genetic likelihood-based approach, rather than a comparative-genomic approach, and can therefore probe genomic variation data from a single population for footprints of adaptive introgression, even from a priori unknown and possibly extinct donor species.

The Impact of Recessive Deleterious Variation on Signals of Adaptive Introgression in Human Populations

Admixture with archaic hominins has altered the landscape of genomic variation in modern human populations. Several gene regions have been identified previously as candidates of adaptive introgression (AI) that facilitated human adaptation to specific environments. However, simulation-based studies have suggested that population genetic processes other than adaptive mutations, such as heterosis from recessive deleterious variants private to populations before admixture, can also lead to patterns in genomic data that resemble AI. The extent to which the presence of deleterious variants affect the false-positive rate and the power of current methods to detect AI has not been fully assessed. Here, we used extensive simulations under parameters relevant for human evolution to show that recessive deleterious mutations can increase the false positive rates of tests for AI compared to models without deleterious variants, especially when the recombination rates are low. We next examined candidates of AI in modern humans identified from previous studies, and show that 24 out of 26 candidate regions remain significant, even when deleterious variants are included in the null model. However, two AI candidate genes, HYAL2 and HLA, are particularly susceptible to high false positive signals of AI due to recessive deleterious mutations. These genes are located in regions of the human genome with high exon density together with low recombination rate, factors that we show increase the rate of false-positives due to recessive deleterious mutations. Although the combination of such parameters is rare in the human genome, caution is warranted in such regions, as well as in other species with more compact genomes and/or lower recombination rates. In sum, our results suggest that recessive deleterious mutations cannot account for the signals of AI in most, but not all, of the top candidates for AI in humans, suggesting they may be genuine signals of adaptation.

Methods for detecting introgressed archaic sequences

Analysis of genome sequences from archaic and modern humans have revealed multiple episodes of admixture between highly-diverged population groups. Statistical methods that attempt to localize DNA segments introduced by these events offer a powerful tool to investigate recent human evolution. We review recent advances in methods for detecting introgressed sequences.

Archaic hominin genomics provides a window into gene expression evolution

Differences in gene expression are thought to account for most phenotypic differences within and between species. Consequently, gene expression is a powerful lens through which to study divergence between modern humans and our closest evolutionary relatives, the Neanderthals and Denisovans. Such insights complement biological knowledge gleaned from the fossil record, while also revealing general features of the mode and tempo of regulatory evolution. Because of the degradation of ancient RNA, gene expression profiles of archaic hominins must be studied by indirect means. As such, conclusions drawn from these studies are often laden with assumptions about the genetic architecture of gene expression, the complexity of which is increasingly apparent. Despite these challenges, rapid technical and conceptual advances in the fields of ancient genomics, functional genomics, statistical genomics, and genome engineering are revolutionizing understanding of hominin gene expression evolution.

Adaptive archaic introgression of copy number variants and the discovery of previously unknown human genes

Copy number variants (CNVs) are subject to stronger selective pressure than single-nucleotide variants, but their roles in archaic introgression and adaptation have not been systematically investigated. We show that stratified CNVs are significantly associated with signatures of positive selection in Melanesians and provide evidence for adaptive introgression of large CNVs at chromosomes 16p11.2 and 8p21.3 from Denisovans and Neanderthals, respectively. Using long-read sequence data, we reconstruct the structure and complex evolutionary history of these polymorphisms and show that both encode positively selected genes absent from most human populations. Our results collectively suggest that large CNVs originating in archaic hominins and introgressed into modern humans have played an important role in local population adaptation and represent an insufficiently studied source of large-scale genetic variation.

Tracking human population structure through time from whole genome sequences

The genetic diversity of humans, like many species, has been shaped by a complex pattern of population separations followed by isolation and subsequent admixture. This pattern, reaching at least as far back as the appearance of our species in the paleontological record, has left its traces in our genomes. Reconstructing a population's history from these traces is a challenging problem. Here we present a novel approach based on the Multiple Sequentially Markovian Coalescent (MSMC) to analyze the separation history between populations. Our approach, called MSMC-IM, uses an improved implementation of the MSMC (MSMC2) to estimate coalescence rates within and across pairs of populations, and then fits a continuous Isolation-Migration model to these rates to obtain a time-dependent estimate of gene flow. We show, using simulations, that our method can identify complex demographic scenarios involving post-split admixture or archaic introgression. We apply MSMC-IM to whole genome sequences from 15 worldwide populations, tracking the process of human genetic diversification. We detect traces of extremely deep ancestry between some African populations, with around 1% of ancestry dating to divergences older than a million years ago.

Recovering signals of ghost archaic introgression in African populations

While introgression from Neanderthals and Denisovans has been documented in modern humans outside Africa, the contribution of archaic hominins to the genetic variation of present-day Africans remains poorly understood. We provide complementary lines of evidence for archaic introgression into four West African populations. Our analyses of site frequency spectra indicate that these populations derive 2 to 19% of their genetic ancestry from an archaic population that diverged before the split of Neanderthals and modern humans. Using a method that can identify segments of archaic ancestry without the need for reference archaic genomes, we built genome-wide maps of archaic ancestry in the Yoruba and the Mende populations. Analyses of these maps reveal segments of archaic ancestry at high frequency in these populations that represent potential targets of adaptive introgression. Our results reveal the substantial contribution of archaic ancestry in shaping the gene pool of present-day West African populations.

Identifying and Interpreting Apparent Neanderthal Ancestry in African Individuals

Admixture has played a prominent role in shaping patterns of human genomic variation, including gene flow with now-extinct hominins like Neanderthals and Denisovans. Here, we describe a novel probabilistic method called IBDmix to identify introgressed hominin sequences, which, unlike existing approaches, does not use a modern reference population. We applied IBDmix to 2,504 individuals from geographically diverse populations to identify and analyze Neanderthal sequences segregating in modern humans. Strikingly, we find that African individuals carry a stronger signal of Neanderthal ancestry than previously thought. We show that this can be explained by genuine Neanderthal ancestry due to migrations back to Africa, predominately from ancestral Europeans, and gene flow into Neanderthals from an early dispersing group of humans out of Africa. Our results refine our understanding of Neanderthal ancestry in African and non-African populations and demonstrate that remnants of Neanderthal genomes survive in every modern human population studied to date.

Ancient West African foragers in the context of African population history

Our knowledge of ancient human population structure in sub-Saharan Africa, particularly prior to the advent of food production, remains limited. Here we report genome-wide DNA data from four children-two of whom were buried approximately 8,000 years ago and two 3,000 years ago-from Shum Laka (Cameroon), one of the earliest known archaeological sites within the probable homeland of the Bantu language group1-11. One individual carried the deeply divergent Y chromosome haplogroup A00, which today is found almost exclusively in the same region12,13. However, the genome-wide ancestry profiles of all four individuals are most similar to those of present-day hunter-gatherers from western Central Africa, which implies that populations in western Cameroon today-as well as speakers of Bantu languages from across the continent-are not descended substantially from the population represented by these four people. We infer an Africa-wide phylogeny that features widespread admixture and three prominent radiations, including one that gave rise to at least four major lineages deep in the history of modern humans.

Identification of African-Specific Admixture between Modern and Archaic Humans

Recent work has demonstrated that two archaic human groups (Neanderthals and Denisovans) interbred with modern humans and contributed to the contemporary human gene pool. These findings relied on the availability of high-coverage genomes from both Neanderthals and Denisovans. Here we search for evidence of archaic admixture from a worldwide panel of 1,667 individuals using an approach that does not require the presence of an archaic human reference genome. We find no evidence for archaic admixture in the Andaman Islands, as previously claimed, or on the island of Flores, where Homo floresiensis fossils have been found. However, we do find evidence for at least one archaic admixture event in sub-Saharan Africa, with the strongest signal in Khoesan and Pygmy individuals from Southern and Central Africa. The locations of these putative archaic admixture tracts are weighted against functional regions of the genome, consistent with the long-term effects of purifying selection against introgressed genetic material.

Archaic hominin introgression into modern human genomes

Ancient genomes from multiple Neanderthal and the Denisovan individuals, along with DNA sequence data from diverse contemporary human populations strongly support the prevalence of gene flow among different hominins. Recent studies now provide evidence for multiple gene flow events that leave genetic signatures in extant and ancient human populations. These events include older gene flow from an unknown hominin in Africa predating out-of-Africa migrations, and in the last 50,000-100,000 years, multiple gene flow events from Neanderthals into ancestral Eurasian human populations, and at least three distinct introgression events from a lineage close to Denisovans into ancestors of extant Southeast Asian and Oceanic populations. Some of these introgression events may have happened as late as 20,000 years before present and reshaped the way in which we think about human evolution. In this review, I aim to answer anthropologically relevant questions with regard to recent research on ancient hominin introgression in the human lineage. How have genomic data from archaic hominins changed our view of human evolution? Is there any doubt about whether introgression from ancient hominins to the ancestors of present-day humans occurred? What is the current view of human evolutionary history from the genomics perspective? What is the impact of introgression on human phenotypes?

Prioritizing natural-selection signals from the deep-sequencing genomic data suggests multi-variant adaptation in Tibetan highlanders

Human genetic adaptation to high altitudes (>2500 m) has been extensively studied over the last few years, but few functional adaptive genetic variants have been identified, largely owing to the lack of deep-genome sequencing data available to previous studies. Here, we build a list of putative adaptive variants, including 63 missense, 7 loss-of-function, 1,298 evolutionarily conserved variants and 509 expression quantitative traits loci. Notably, the top signal of selection is located in TMEM247, a transmembrane protein-coding gene. The Tibetan version of TMEM247 harbors one high-frequency (76.3%) missense variant, rs116983452 (c.248C > T; p.Ala83Val), with the T allele derived from archaic ancestry and carried by >94% of Tibetans but absent or in low frequencies (<3%) in non-Tibetan populations. The rs116983452-T is strongly and positively correlated with altitude and significantly associated with reduced hemoglobin concentration (p = 5.78 × 10-5), red blood cell count (p = 5.72 × 10-7) and hematocrit (p = 2.57 × 10-6). In particular, TMEM247-rs116983452 shows greater effect size and better predicts the phenotypic outcome than any EPAS1 variants in association with adaptive traits in Tibetans. Modeling the interaction between TMEM247-rs116983452 and EPAS1 variants indicates weak but statistically significant epistatic effects. Our results support that multiple variants may jointly deliver the fitness of the Tibetans on the plateau, where a complex model is needed to elucidate the adaptive evolution mechanism.

Using hominin introgression to trace modern human dispersals

The dispersal of anatomically modern human populations out of Africa and across much of the rest of the world around 55 to 50 thousand years before present (ka) is recorded genetically by the multiple hominin groups they met and interbred with along the way, including the Neandertals and Denisovans. The signatures of these introgression events remain preserved in the genomes of modern-day populations, and provide a powerful record of the sequence and timing of these early migrations, with Asia proving a particularly complex area. At least 3 different hominin groups appear to have been involved in Asia, of which only the Denisovans are currently known. Several interbreeding events are inferred to have taken place east of Wallace's Line, consistent with archaeological evidence of widespread and early hominin presence in the area. However, archaeological and fossil evidence indicates archaic hominins had not spread as far as the Sahul continent (New Guinea, Australia, and Tasmania), where recent genetic evidence remains enigmatic.

Searching for archaic contribution in Africa

Context: Africa's role in the narrative of human evolution is indisputably emphasised in the emergence of Homo sapiens. However, once humans dispersed beyond Africa, the history of those who stayed remains vastly under-studied, lacking the proper attention the birthplace of both modern and archaic humans deserves. The sequencing of Neanderthal and Denisovan genomes has elucidated evidence of admixture between archaic and modern humans outside of Africa, but has not aided efforts in answering whether archaic admixture happened within Africa. Objectives: This article reviews the state of research for archaic introgression in African populations and discusses recent insights into this topic. Methods: Gathering published sources and recently released preprints, this review reports on the different methods developed for detecting archaic introgression. Particularly it discusses how relevant these are when implemented on African populations and what findings these studies have shown so far. Results: Methods for detecting archaic introgression have been predominantly developed and implemented on non-African populations. Recent preprints present new methods considering African populations. While a number of studies using these methods suggest archaic introgression in Africa, without an African archaic genome to validate these results, such findings remain as putative archaic introgression. Conclusion: In light of the caveats with implementing current archaic introgression detection methods in Africa, we recommend future studies to concentrate on unravelling the complicated demographic history of Africa through means of ancient DNA where possible and through more focused efforts to sequence modern DNA from more representative populations across the African continent.

Models of archaic admixture and recent history from two-locus statistics

We learn about population history and underlying evolutionary biology through patterns of genetic polymorphism. Many approaches to reconstruct evolutionary histories focus on a limited number of informative statistics describing distributions of allele frequencies or patterns of linkage disequilibrium. We show that many commonly used statistics are part of a broad family of two-locus moments whose expectation can be computed jointly and rapidly under a wide range of scenarios, including complex multi-population demographies with continuous migration and admixture events. A full inspection of these statistics reveals that widely used models of human history fail to predict simple patterns of linkage disequilibrium. To jointly capture the information contained in classical and novel statistics, we implemented a tractable likelihood-based inference framework for demographic history. Using this approach, we show that human evolutionary models that include archaic admixture in Africa, Asia, and Europe provide a much better description of patterns of genetic diversity across the human genome. We estimate that an unidentified, deeply diverged population admixed with modern humans within Africa both before and after the split of African and Eurasian populations, contributing 4 - 8% genetic ancestry to individuals in world-wide populations.

A statistical model for reference-free inference of archaic local ancestry

Statistical analyses of genomic data from diverse human populations have demonstrated that archaic hominins, such as Neanderthals and Denisovans, interbred or admixed with the ancestors of present-day humans. Central to these analyses are methods for inferring archaic ancestry along the genomes of present-day individuals (archaic local ancestry). Methods for archaic local ancestry inference rely on the availability of reference genomes from the ancestral archaic populations for accurate inference. However, several instances of archaic admixture lack reference archaic genomes, making it difficult to characterize these events. We present a statistical method that combines diverse population genetic summary statistics to infer archaic local ancestry without access to an archaic reference genome. We validate the accuracy and robustness of our method in simulations. When applied to genomes of European individuals, our method recovers segments that are substantially enriched for Neanderthal ancestry, even though our method did not have access to any Neanderthal reference genomes.

Ancient admixture from an extinct ape lineage into bonobos

Admixture is a recurrent phenomenon in humans and other great ape populations. Genetic information from extinct hominins allows us to study historical interactions with modern humans and discover adaptive functions of gene flow. Here, we investigate whole genomes from bonobo and chimpanzee populations for signatures of gene flow from unknown archaic populations, finding evidence for an ancient admixture event between bonobos and a divergent lineage. This result reveals a complex population history in our closest living relatives, probably several hundred thousand years ago. We reconstruct up to 4.8% of the genome of this 'ghost' ape, which represents genomic data of an extinct great ape population. Genes contained in archaic fragments might confer functional consequences for the immunity, behaviour and physiology of bonobos. Finally, comparing the landscapes of introgressed regions in humans and bonobos, we find that a recurrent depletion of introgression is rare, suggesting that genomic incompatibilities arose seldom in these lineages.

Whole-genome sequence analysis of a Pan African set of samples reveals archaic gene flow from an extinct basal population of modern humans into sub-Saharan populations

Background

Population demography and gene flow among African groups, as well as the putative archaic introgression of ancient hominins, have been poorly explored at the genome level.

Results

Here, we examine 15 African populations covering all major continental linguistic groups, ecosystems, and lifestyles within Africa through analysis of whole-genome sequence data of 21 individuals sequenced at deep coverage. We observe a remarkable correlation among genetic diversity and geographic distance, with the hunter-gatherer groups being more genetically differentiated and having larger effective population sizes throughout most modern-human history. Admixture signals are found between neighbor populations from both hunter-gatherer and agriculturalists groups, whereas North African individuals are closely related to Eurasian populations. Regarding archaic gene flow, we test six complex demographic models that consider recent admixture as well as archaic introgression. We identify the fingerprint of an archaic introgression event in the sub-Saharan populations included in the models (~ 4.0% in Khoisan, ~ 4.3% in Mbuti Pygmies, and ~ 5.8% in Mandenka) from an early divergent and currently extinct ghost modern human lineage.

Conclusion

The present study represents an in-depth genomic analysis of a Pan African set of individuals, which emphasizes their complex relationships and demographic history at population level.

Electronic supplementary material

The online version of this article (10.1186/s13059-019-1684-5) contains supplementary material, which is available to authorized users.

Using Genomic Data to Infer Historic Population Dynamics of Nonmodel Organisms

Genome sequence data are now being routinely obtained from many nonmodel organisms. These data contain a wealth of information about the demographic history of the populations from which they originate. Many sophisticated statistical inference procedures have been developed to infer the demographic history of populations from this type of genomic data. In this review, we discuss the different statistical methods available for inference of demography, providing an overview of the underlying theory and logic behind each approach. We also discuss the types of data required and the pros and cons of each method. We then discuss how these methods have been applied to a variety of nonmodel organisms. We conclude by presenting some recommendations for researchers looking to use genomic data to infer demographic history.

Phylogeny Estimation by Integration over Isolation with Migration Models

Phylogeny estimation is difficult for closely related populations and species, especially if they have been exchanging genes. We present a hierarchical Bayesian, Markov-chain Monte Carlo method with a state space that includes all possible phylogenies in a full Isolation-with-Migration model framework. The method is based on a new type of genealogy augmentation called a "hidden genealogy" that enables efficient updating of the phylogeny. This is the first likelihood-based method to fully incorporate directional gene flow and genetic drift for estimation of a species or population phylogeny. Application to human hunter-gatherer populations from Africa revealed a clear phylogenetic history, with strong support for gene exchange with an unsampled ghost population, and relatively ancient divergence between a ghost population and modern human populations, consistent with human/archaic divergence. In contrast, a study of five chimpanzee populations reveals a clear phylogeny with several pairs of populations having exchanged DNA, but does not support a history with an unsampled ghost population.

Model-based detection and analysis of introgressed Neanderthal ancestry in modern humans

Genetic evidence has revealed that the ancestors of modern human populations outside Africa and their hominin sister groups, notably Neanderthals, exchanged genetic material in the past. The distribution of these introgressed sequence tracts along modern-day human genomes provides insight into the selective forces acting on them and the role of introgression in the evolutionary history of hominins. Studying introgression patterns on the X-chromosome is of particular interest, as sex chromosomes are thought to play a special role in speciation. Recent studies have developed methods to localize introgressed ancestries, reporting long regions that are depleted of Neanderthal introgression and enriched in genes, suggesting negative selection against the Neanderthal variants. On the other hand, enriched Neanderthal ancestry in hair- and skin-related genes suggests that some introgressed variants facilitated adaptation to new environments. Here, we present a model-based introgression detection method called dical-admix. We demonstrate its efficiency and accuracy through extensive simulations and apply it to detect tracts of Neanderthal introgression in modern human individuals from the 1000 Genomes Project. Our findings are largely concordant with previous studies, consistent with weak selection against Neanderthal ancestry. We find evidence that selection against Neanderthal ancestry was due to higher genetic load in Neanderthals resulting from small effective population size, rather than widespread Dobzhansky-Müller incompatibilities (DMIs) that could contribute to reproductive isolation. Moreover, we confirm the previously reported low level of introgression on the X-chromosome, but find little evidence that DMIs contributed to this pattern.

Detecting archaic introgression using an unadmixed outgroup

Human populations outside of Africa have experienced at least two bouts of introgression from archaic humans, from Neanderthals and Denisovans. In Papuans there is prior evidence of both these introgressions. Here we present a new approach to detect segments of individual genomes of archaic origin without using an archaic reference genome. The approach is based on a hidden Markov model that identifies genomic regions with a high density of single nucleotide variants (SNVs) not seen in unadmixed populations. We show using simulations that this provides a powerful approach to identifying segments of archaic introgression with a low rate of false detection, given data from a suitable outgroup population is available, without the archaic introgression but containing a majority of the variation that arose since initial separation from the archaic lineage. Furthermore our approach is able to infer admixture proportions and the times both of admixture and of initial divergence between the human and archaic populations. We apply the model to detect archaic introgression in 89 Papuans and show how the identified segments can be assigned to likely Neanderthal or Denisovan origin. We report more Denisovan admixture than previous studies and find a shift in size distribution of fragments of Neanderthal and Denisovan origin that is compatible with a difference in admixture time. Furthermore, we identify small amounts of Denisova ancestry in South East Asians and South Asians.

The genetic history of present-day individuals includes episodes of mating between divergent groups, which have led to 'introgressed' genetic material persisting in modern genome sequences. Perhaps the most notable examples of such events in humans are the introgressions from Neanderthals into non-Africans 50,000 or so years ago, and from a related archaic group known as Denisovans into the ancestors of indigenous people from Papua-New Guinea and Australia. Methods to identify introgressions and the genomic regions that derive from them generally involve the use of reference genome sequences for the source populations. However, there are advantages in having methods independent of reference sequences, both to reduce bias and to detect possible introgression from groups for which we currently lack a reference genome. In this paper we describe such an approach, in a statistical framework which exploits the fact that introgressed regions will contain a high density of genetic variants that are private to the group receiving the divergent material. We apply this method to 89 Papuan genome sequences, estimating times of introgression and initial divergence between archaic and modern humans, and compare it to other related methods.

Tales of Human Migration, Admixture, and Selection in Africa

In the last three decades, genetic studies have played an increasingly important role in exploring human history. They have helped to conclusively establish that anatomically modern humans first appeared in Africa roughly 250,000–350,000 years before present and subsequently migrated to other parts of the world. The history of humans in Africa is complex and includes demographic events that influenced patterns of genetic variation across the continent. Through genetic studies, it has become evident that deep African population history is captured by relationships among African hunter–gatherers, as the world's deepest population divergences occur among these groups, and that the deepest population divergence dates to 300,000 years before present. However, the spread of pastoralism and agriculture in the last few thousand years has shaped the geographic distribution of present-day Africans and their genetic diversity. With today's sequencing technologies, we can obtain full genome sequences from diverse sets of extant and prehistoric Africans. The coming years will contribute exciting new insights toward deciphering human evolutionary history in Africa.

Evolutionary history and adaptation of a human pygmy population of Flores Island, Indonesia

Flores Island, Indonesia, was inhabited by the small-bodied hominin species Homo floresiensis, which has an unknown evolutionary relationship to modern humans. This island is also home to an extant human pygmy population. Here we describe genome-scale single-nucleotide polymorphism data and whole-genome sequences from a contemporary human pygmy population living on Flores near the cave where H. floresiensis was found. The genomes of Flores pygmies reveal a complex history of admixture with Denisovans and Neanderthals but no evidence for gene flow with other archaic hominins. Modern individuals bear the signatures of recent positive selection encompassing the FADS (fatty acid desaturase) gene cluster, likely related to diet, and polygenic selection acting on standing variation that contributed to their short-stature phenotype. Thus, multiple independent instances of hominin insular dwarfism occurred on Flores.