Matthias Steinrücken

Genomic evidence for the Pleistocene and recent population history of Native Americans

Genetic history of Native Americans Several theories have been put forth as to the origin and timing of when Native American ancestors entered the Americas. To clarify this controversy, Raghavan et al. examined the genomic variation among ancient and modern individuals from Asia and the Americas. There is no evidence for multiple waves of entry or recurrent gene flow with Asians in northern populations. The earliest migrations occurred no earlier than 23,000 years ago from Siberian ancestors. Amerindians and Athabascans originated from a single population, splitting approximately 13,000 years ago. Science, this issue 10.1126/science.aab3884 Genetic variation within ancient and extant Native American populations informs on their migration into the Americas. INTRODUCTION The consensus view on the peopling of the Americas is that ancestors of modern Native Americans entered the Americas from Siberia via the Bering Land Bridge and that this occurred at least ~14.6 thousand years ago (ka). However, the number and timing of migrations into the Americas remain controversial, with conflicting interpretations based on anatomical and genetic evidence. RATIONALE In this study, we address four major unresolved issues regarding the Pleistocene and recent population history of Native Americans: (i) the timing of their divergence from their ancestral group, (ii) the number of migrations into the Americas, (iii) whether there was ~15,000 years of isolation of ancestral Native Americans in Beringia (Beringian Incubation Model), and (iv) whether there was post-Pleistocene survival of relict populations in the Americas related to Australo-Melanesians, as suggested by apparent differences in cranial morphologies between some early (“Paleoamerican”) remains and those of more recent Native Americans. We generated 31 high-coverage modern genomes from the Americas, Siberia, and Oceania; 23 ancient genomic sequences from the Americas dating between ~0.2 and 6 ka; and SNP chip genotype data from 79 present-day individuals belonging to 28 populations from the Americas and Siberia. The above data sets were analyzed together with published modern and ancient genomic data from worldwide populations, after masking some present-day Native Americans for recent European admixture. RESULTS Using three different methods, we determined the divergence time for all Native Americans (Athabascans and Amerindians) from their Siberian ancestors to be ~20 ka, and no earlier than ~23 ka. Furthermore, we dated the divergence between Athabascans (northern Native American branch, together with northern North American Amerindians) and southern North Americans and South and Central Americans (southern Native American branch) to be ~13 ka. Similar divergence times from East Asian populations and a divergence time between the two branches that is close in age to the earliest well-established archaeological sites in the Americas suggest that the split between the branches occurred within the Americas. We additionally found that several sequenced Holocene individuals from the Americas are related to present-day populations from the same geographical regions, implying genetic continuity of ancient and modern populations in some parts of the Americas over at least the past 8500 years. Moreover, our results suggest that there has been gene flow between some Native Americans from both North and South America and groups related to East Asians and Australo-Melanesians, the latter possibly through an East Asian route that might have included ancestors of modern Aleutian Islanders. Last, using both genomic and morphometric analyses, we found that historical Native American groups such as the Pericúes and Fuego-Patagonians were not “relicts” of Paleoamericans, and hence, our results do not support an early migration of populations directly related to Australo-Melanesians into the Americas. CONCLUSION Our results provide an upper bound of ~23 ka on the initial divergence of ancestral Native Americans from their East Asian ancestors, followed by a short isolation period of no more than ~8000 years, and subsequent entrance and spread across the Americas. The data presented are consistent with a single-migration model for all Native Americans, with later gene flow from sources related to East Asians and, indirectly, Australo-Melanesians. The single wave diversified ~13 ka, likely within the Americas, giving rise to the northern and southern branches of present-day Native Americans. Population history of present-day Native Americans. The ancestors of all Native Americans entered the Americas as a single migration wave from Siberia (purple) no earlier than ~23 ka, separate from the Inuit (green), and diversified into “northern” and “southern” Native American branches ~13 ka. There is evidence of post-divergence gene flow between some Native Americans and groups related to East Asians/Inuit and Australo-Melanesians (yellow). How and when the Americas were populated remains contentious. Using ancient and modern genome-wide data, we found that the ancestors of all present-day Native Americans, including Athabascans and Amerindians, entered the Americas as a single migration wave from Siberia no earlier than 23 thousand years ago (ka) and after no more than an 8000-year isolation period in Beringia. After their arrival to the Americas, ancestral Native Americans diversified into two basal genetic branches around 13 ka, one that is now dispersed across North and South America and the other restricted to North America. Subsequent gene flow resulted in some Native Americans sharing ancestry with present-day East Asians (including Siberians) and, more distantly, Australo-Melanesians. Putative “Paleoamerican” relict populations, including the historical Mexican Pericúes and South American Fuego-Patagonians, are not directly related to modern Australo-Melanesians as suggested by the Paleoamerican Model.

An Accurate Sequentially Markov Conditional Sampling Distribution for the Coalescent With Recombination

The sequentially Markov coalescent is a simplified genealogical process that aims to capture the essential features of the full coalescent model with recombination, while being scalable in the number of loci. In this article, the sequentially Markov framework is applied to the conditional sampling distribution (CSD), which is at the core of many statistical tools for population genetic analyses. Briefly, the CSD describes the probability that an additionally sampled DNA sequence is of a certain type, given that a collection of sequences has already been observed. A hidden Markov model (HMM) formulation of the sequentially Markov CSD is developed here, yielding an algorithm with time complexity linear in both the number of loci and the number of haplotypes. This work provides a highly accurate, practical approximation to a recently introduced CSD derived from the diffusion process associated with the coalescent with recombination. It is empirically demonstrated that the improvement in accuracy of the new CSD over previously proposed HMM-based CSDs increases substantially with the number of loci. The framework presented here can be adopted in a wide range of applications in population genetics, including imputing missing sequence data, estimating recombination rates, and inferring human colonization history.

A Simple Method for Finding Explicit Analytic Transition Densities of Diffusion Processes with General Diploid Selection

The transition density function of the Wright–Fisher diffusion describes the evolution of population-wide allele frequencies over time. This function has important practical applications in population genetics, but finding an explicit formula under a general diploid selection model has remained a difficult open problem. In this article, we develop a new computational method to tackle this classic problem. Specifically, our method explicitly finds the eigenvalues and eigenfunctions of the diffusion generator associated with the Wright–Fisher diffusion with recurrent mutation and arbitrary diploid selection, thus allowing one to obtain an accurate spectral representation of the transition density function. Simplicity is one of the appealing features of our approach. Although our derivation involves somewhat advanced mathematical concepts, the resulting algorithm is quite simple and efficient, only involving standard linear algebra. Furthermore, unlike previous approaches based on perturbation, which is applicable only when the population-scaled selection coefficient is small, our method is nonperturbative and is valid for a broad range of parameter values. As a by-product of our work, we obtain the rate of convergence to the stationary distribution under mutation–selection balance.

A sequentially Markov conditional sampling distribution for structured populations with migration and recombination

Conditional sampling distributions (CSDs), sometimes referred to as copying models, underlie numerous practical tools in population genomic analyses. Though an important application that has received much attention is the inference of population structure, the explicit exchange of migrants at specified rates has not hitherto been incorporated into the CSD in a principled framework. Recently, in the case of a single panmictic population, a sequentially Markov CSD has been developed as an accurate, efficient approximation to a principled CSD derived from the diffusion process dual to the coalescent with recombination. In this paper, the sequentially Markov CSD framework is extended to incorporate subdivided population structure, thus providing an efficiently computable CSD that admits a genealogical interpretation related to the structured coalescent with migration and recombination. As a concrete application, it is demonstrated empirically that the CSD developed here can be employed to yield accurate estimation of a wide range of migration rates.

Terminal Pleistocene Alaskan genome reveals first founding population of Native Americans

Despite broad agreement that the Americas were initially populated via Beringia, the land bridge that connected far northeast Asia with northwestern North America during the Pleistocene epoch, when and how the peopling of the Americas occurred remains unresolved. Analyses of human remains from Late Pleistocene Alaska are important to resolving the timing and dispersal of these populations. The remains of two infants were recovered at Upward Sun River (USR), and have been dated to around 11.5 thousand years ago (ka). Here, by sequencing the USR1 genome to an average coverage of approximately 17 times, we show that USR1 is most closely related to Native Americans, but falls basal to all previously sequenced contemporary and ancient Native Americans. As such, USR1 represents a distinct Ancient Beringian population. Using demographic modelling, we infer that the Ancient Beringian population and ancestors of other Native Americans descended from a single founding population that initially split from East Asians around 36 ± 1.5 ka, with gene flow persisting until around 25 ± 1.1 ka. Gene flow from ancient north Eurasians into all Native Americans took place 25–20 ka, with Ancient Beringians branching off around 22–18.1 ka. Our findings support a long-term genetic structure in ancestral Native Americans, consistent with the Beringian ‘standstill model’. We show that the basal northern and southern Native American branches, to which all other Native Americans belong, diverged around 17.5–14.6 ka, and that this probably occurred south of the North American ice sheets. We also show that after 11.5 ka, some of the northern Native American populations received gene flow from a Siberian population most closely related to Koryaks, but not Palaeo-Eskimos, Inuits or Kets, and that Native American gene flow into Inuits was through northern and not southern Native American groups. Our findings further suggest that the far-northern North American presence of northern Native Americans is from a back migration that replaced or absorbed the initial founding population of Ancient Beringians.

A NOVEL SPECTRAL METHOD FOR INFERRING GENERAL DIPLOID SELECTION FROM TIME SERIES GENETIC DATA

The increased availability of time series genetic variation data from experimental evolution studies and ancient DNA samples has created new opportunities to identify genomic regions under selective pressure and to estimate their associated fitness parameters. However, it is a challenging problem to compute the likelihood of non-neutral models for the population allele frequency dynamics, given the observed temporal DNA data. Here, we develop a novel spectral algorithm to analytically and efficiently integrate over all possible frequency trajectories between consecutive time points. This advance circumvents the limitations of existing methods which require fine-tuning the discretization of the population allele frequency space when numerically approximating requisite integrals. Furthermore, our method is flexible enough to handle general diploid models of selection where the heterozygote and homozygote fitness parameters can take any values, while previous methods focused on only a few restricted models of selection. We demonstrate the utility of our method on simulated data and also apply it to analyze ancient DNA data from genetic loci associated with coat coloration in horses. In contrast to previous studies, our exploration of the full fitness parameter space reveals that a heterozygote-advantage form of balancing selection may have been acting on these loci.

An explicit transition density expansion for a multi-allelic Wright-Fisher diffusion with general diploid selection.

Characterizing time-evolution of allele frequencies in a population is a fundamental problem in population genetics. In the Wright-Fisher diffusion, such dynamics is captured by the transition density function, which satisfies well-known partial differential equations. For a multi-allelic model with general diploid selection, various theoretical results exist on representations of the transition density, but finding an explicit formula has remained a difficult problem. In this paper, a technique recently developed for a diallelic model is extended to find an explicit transition density for an arbitrary number of alleles, under a general diploid selection model with recurrent parent-independent mutation. Specifically, the method finds the eigenvalues and eigenfunctions of the generator associated with the multi-allelic diffusion, thus yielding an accurate spectral representation of the transition density. Furthermore, this approach allows for efficient, accurate computation of various other quantities of interest, including the normalizing constant of the stationary distribution and the rate of convergence to this distribution.

Transition Densities and Sample Frequency Spectra of Diffusion Processes with Selection and Variable Population Size

Advances in empirical population genetics have made apparent the need for models that simultaneously account for selection and demography. To address this need, we here study the Wright–Fisher diffusion under selection and variable effective population size. In the case of genic selection and piecewise-constant effective population sizes, we obtain the transition density by extending a recently developed method for computing an accurate spectral representation for a constant population size. Utilizing this extension, we show how to compute the sample frequency spectrum in the presence of genic selection and an arbitrary number of instantaneous changes in the effective population size. We also develop an alternate, efficient algorithm for computing the sample frequency spectrum using a moment-based approach. We apply these methods to answer the following questions: If neutrality is incorrectly assumed when there is selection, what effects does it have on demographic parameter estimation? Can the impact of negative selection be observed in populations that undergo strong exponential growth?

Inference of complex population histories using whole-genome sequences from multiple populations

There has been much interest in analyzing genome-scale DNA sequence data to infer population histories, but inference methods developed hitherto are limited in model complexity and computational scalability. Here we present an efficient, flexible statistical method, diCal2, that can utilize whole-genome sequence data from multiple populations to infer complex demographic models involving population size changes, population splits, admixture, and migration. Applying our method to data from Australian, East Asian, European, and Papuan populations, we find that the population ancestral to Australians and Papuans started separating from East Asians and Europeans about 100,000 years ago, and that the separation of East Asians and Europeans started about 50,000 years ago, with pervasive gene flow between all pairs of populations.

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.