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Copyright Kitchen et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. A Three-Stage Colonization Model for the Peopling of the Americas 1Department of Anthropology, University of Florida, Gainesville, Florida, United States of America 2Department of Zoology, University of Florida, Gainesville, Florida, United States of America Henry Harpending, Academic Editor University of Utah, United States of America * To whom correspondence should be addressed. E-mail: mulligan/at/anthro.ufl.edu Conceived and designed the experiments: CM MM AK. Performed the experiments: MM AK. Wrote the paper: CM MM AK. Received January 8, 2008; Accepted January 16, 2008. This article has been cited by other articles in PMC.Abstract Background We evaluate the process by which the Americas were originally colonized and propose a three-stage model that integrates current genetic, archaeological, geological, and paleoecological data. Specifically, we analyze mitochondrial and nuclear genetic data by using complementary coalescent models of demographic history and incorporating non-genetic data to enhance the anthropological relevance of the analysis. Methodology/Findings Bayesian skyline plots, which provide dynamic representations of population size changes over time, indicate that Amerinds went through two stages of growth ≈40,000 and ≈15,000 years ago separated by a long period of population stability. Isolation-with-migration coalescent analyses, which utilize data from sister populations to estimate a divergence date and founder population sizes, suggest an Amerind population expansion starting ≈15,000 years ago. Conclusions/Significance These results support a model for the peopling of the New World in which Amerind ancestors diverged from the Asian gene pool prior to 40,000 years ago and experienced a gradual population expansion as they moved into Beringia. After a long period of little change in population size in greater Beringia, Amerinds rapidly expanded into the Americas ≈15,000 years ago either through an interior ice-free corridor or along the coast. This rapid colonization of the New World was achieved by a founder group with an effective population size of ≈1,000–5,400 individuals. Our model presents a detailed scenario for the timing and scale of the initial migration to the Americas, substantially refines the estimate of New World founders, and provides a unified theory for testing with future datasets and analytic methods. Introduction For decades, intense and interdisciplinary attention has focused on the colonization of the last habitable landmass on the planet-the peopling of the Americas. The first comprehensive, interdisciplinary model for New World colonization incorporated linguistic, paleoanthropological, and genetic data and generated great controversy, which was due at least in part, to the uniquely broad scope of the research [1]. Since that time, more focused studies have resulted in agreement on the general parameters of the colonization process, such as a single migration in contrast to the original three-migration model that distinguished Amerinds, Na-Dene, and Eskimo-Aleuts [1]. However, a full understanding of the complex and dynamic nature of the timing and magnitude of the colonization process remains elusive. The majority of the genetic literature supports a single migration of Paleoindians into the New World from an East Asian source population [2]. Specifically, the reduced variation and ubiquitous distribution of mitochondrial and Y chromosome haplogroups and microsatellite diversity throughout the New World relative to Asia argue strongly for a single migration [3], [4]. However, a great many models have been proposed that differ significantly in the timing and size of this migration event [2], [5]–[15]. Different migration dates have been proposed ranging from ≈13 thousand years ago (kya) to ≈30–40 kya [2], [5]–[15]. Numerical estimates of the founder effective population size (Ne) are infrequent in the literature but vary substantially, from a high of ≈5000 [6] to a low of ≈70 Paleoindian founders [16]. These dates and population sizes have been proposed to accommodate a wealth of scenarios including ancient, recent, and/or additional migrations responsible for the peopling of the Americas. Archaeological data provide clear support for a widespread human presence in the Americas by ≈13 kya (all calendar dates are recalibrated radiocarbon dates as reported in the cited literature), the time by which the Clovis complex was established across the interior of North America [17], [18]. Older archaeological sites, e.g. the Nenana Complex in Alaska [18], the Monte Verde site in Chile [19], and the Schaefer, Hebior and Mud Lake sites in Wisconsin [20], [21], document an earlier chronology possibly 2,400 years before Clovis [18], [20], [21]. Additionally, very old radiocarbon dates have been obtained from sites in Asian Beringia suggesting that human populations had reached the north of western Beringia by ≈30 kya [22], [23]. The geological and paleoecological records for Beringia and northwestern North America provide further constraints on the timing for the peopling of the Americas. Beringia was a continuous landmass that connected Asia and North America roughly 60 kya until ≈11–10 kya [23]–[25]. However, Beringia was isolated from continental North America until ≈14 kya when an intracontinental ice-free corridor opened up between the Laurentide and Cordilleran Ice Sheets [26]. Paleoecological data indicate that Beringia was able to sustain at least small human populations. Fossil pollen and plant macrofossils from ancient eastern Beringia are indicative of a productive, dry grassland ecosystem [27] and paleontological evidence from Alaska and Siberia demonstrates that large mammals roamed Beringia [28]. After 11–10 kya, Late Pleistocene sea levels rose sufficiently to re-inundate Beringia [24], [25], creating the Bering strait that now separates the New World from Siberia by at least 100 kilometers (km) of open frigid water. Studies of human settlement throughout the Pacific Islands indicate that open water distances of >100 km constitute significant barriers to human migration, possibly because ancient people were unlikely to travel further than one day out of sight of land [29]. Similar constraints (if not worse) would apply to early humans in Alaska and Siberia, thereby severely reducing the migration rate between the New and Old World once Beringia was re-inundated. Reduced migration due to the Bering Strait remains valid even as recent rates of short-range migration have increased between Siberia and Alaska [13]. In effect, the two continents were essentially geographically isolated from 11–10 kya until modern times. No detailed, unified theory of New World colonization currently exists that can account for the breadth and complexity of these interdisciplinary data. We analyze Native American mitochondrial DNA (mtDNA) coding genomes plus non-coding control region sequences as well as a combined nuclear and mitochondrial coding DNA dataset from New World and Asian populations. Mitochondrial DNA data represent the ‘gold standard’ of genetic data types and provide the most extensive comparative database for human populations worldwide [30]. Furthermore, it has been proposed that mtDNA may be more sensitive to demographic changes, such as population bottlenecks, due to its smaller effective population size [31]. The combined nuclear and mtDNA dataset was recently used to propose an unusually small Ne for the Amerind founders [16], and thus investigation of this dataset is of much interest when attempting to reconcile the existing genetic evidence. We use two complementary coalescent methods to develop a comprehensive scenario of New World colonization, with a focus on the timing and scale of the migration process. Bayesian skyline plot analyses use data from a single population to provide an unbiased estimate of changes in Ne through time, and thus are a powerful means for estimating past population growth patterns when the nature of the growth (e.g. exponential or constant) is unknown [32]. The isolation-by-migration (IM) structured coalescent model uses data from sister populations to jointly estimate population divergence time, migration rates and a founder Ne, with an assumption of exponential growth [16]. Importantly, we explicitly incorporate archaeological, geological, and paleoecological constraints into both analyses. Our goal is to provide a comprehensive model for the initial settlement of the Americas that generates new testable hypotheses and has high predictive power for the inclusion of new datasets. In light of our results, we propose a three-stage model in which a recent, rapid expansion into the Americas was preceded by a long period of population stability in greater Beringia by the Paleoindian population after divergence and expansion from their ancestral Asian population. Results Skyline Plot Analyses Our alignment of 77 full mitochondrial coding genomes is one of the largest published alignments of Native American mtDNA coding genomes (Figure S1). It includes genomes from the four major mtDNA haplogroups in the Americas (haplogroups A, B, C, and D are each represented by 17–31% of the entire sample), as well as the minor haplogroup X (2%). Correspondingly, this set of 77 complete coding mtDNA genomes represents geographically and linguistically diverse populations distributed throughout the New World [3]. Bayesian skyline plots [32] were used to visually illustrate changes in Amerind female effective population size (Nef) over time. Bayesian skyline plots assume a single migration event, which makes the approach ideal for questions concerning the peopling of the Americas since it is generally agreed that there was a single migration [3]. Our skyline plot of the coding genomes describes a three-stage process in which there are two distinct increases in Nef at ≈40 kya and ≈15 kya that are separated by a long period of little to no growth (Figure 1 = 148–9,969] to ≈4,400 individuals (95% CI = 235–18,708) at the first inflection point, and from ≈4,000 (95% CI = 911–13,006) to ≈64,000 individuals (95% CI = 15,871–202,990) at the second inflection point. There is also an apparent decrease in Nef prior to the second inflection point in which median Nef drops to ≈2700 (95% CI = 404–36,628). We define a significant change in population size as the occurrence of non-overlapping 95% CIs at the beginning and end of an increase (see shading in Figure 1
The dataset of 812 concatenated mtDNA hypervariable region (HVR) I and II sequences is one of the largest published alignments of Native American HVRI+II sequences (Figure S2). It includes all major New World haplogroups, and represents geographically and linguistically diverse populations distributed throughout the Americas. The HVRI+II dataset was randomly divided into ten non-overlapping alignments of 81 HVRI+II sequences, which allowed for ten independent trials for parameter estimation with a sample size similar to the coding genome alignment. The HVRI+II skyline plot analyses (Figure 2 = 33.5–87.2 kya) and Nef at coalescence (820, 95% CI = 26–3,979) and the present (66,200, 95% CI = 9,839–346,289) that are similar to the coding genome analyses (Figure 1
Isolation-with-Migration Coalescent Analyses Bayesian IM coalescent analyses were performed on a set of nine coding nuclear and mitochondrial loci that had been previously analyzed by Hey [16] in support of an extremely small New World founder Ne of ≈70 individuals. Thus, we performed our analysis on his identical dataset and used the same coalescent and substitution models and model parameters with the exception of new priors on the divergence time and on migration rates between Asian and Amerind populations (mAsia→NW and mNW→Asia). The lower bound on divergence time was set to15 kya, which corresponds to the period immediately preceding the earliest archaeological evidence for human habitation in the Americas [18]–[21]. We also instituted serial constraints on m in order to gauge the effect of changing migration rates on founder Ne estimates. We interpret the various m values in comparison to an empirical estimate of m for modern Europe (m = 4.3; see Materials and Methods). In contrast to modern Europe, migration between the New World and Siberia from 15 kya to more recent times would have become increasingly limited as Late Pleistocene sea levels rose sufficiently to inundate the Bering land bridge [24], [25]. Thus, we expect m for modern Europe to be much higher than ancient migration rates between Asia and the Americas, especially after the inundation of Beringia.Constraining divergence time by applying a lower bound of 15 kya results in an estimate of ≈200 for the Amerind founding Ne. Serially constraining mAsia→NW and mNW→Asia, in conjunction with the constrained divergence time, produces increasingly larger estimates of Ne (Figure 3 = 4.3). Eliminating all migration between Asia and the New World (m = 0) results in the largest estimate of Ne for the Amerind founding population of ≈1,200 individuals.
Discussion When studying complex colonization scenarios, the interpretation of genetic data can benefit substantially from the incorporation of non-genetic material evidence. In our study, we do this in three ways. First, we interpret the skyline plot (see Figure 1 Based on our results, we propose a three-stage colonization process for the peopling of the New World, with a specific focus on the dating and magnitude of the Amerind population expansions (Figure 4
The initial stage of the colonization process involved the divergence of Amerind ancestors from the East Central Asian gene pool (Figure 4A The proposed second stage (Figure 4B The final colonization stage (Figure 4C Determination of the size of the Amerind founding population has received considerable attention. Based on the coding Bayesian skyline plot (Figure 1 = 1,000–5,400 colonized the New World in a process characterized by a rapid geographic and population expansion. The range of Ne values can be translated into an approximate census population size by applying a scale factor estimated from large mammal populations (scale factor = 5) [44], which suggests that the founder population consisted of ≈5,000–27,000 people.Our three-stage model now awaits further critical testing with new datasets of independent nuclear loci and more sophisticated methods of coalescent analysis. The extensive dataset of ≈700 autosomal microsatellites, compiled by Wang et al. [4] for both Native American and worldwide populations, offers the opportunity to evaluate critically the size, timing, and duration of each step in our model at essentially a population genomics level. Future versions of BEAST will incorporate a structured coalescent where migration as well as population growth will be allowed to occur among populations from both the New World and Asia (http://evolve.zoo.ox.ac.uk/beast/manual.html). In these BEAST analyses, the microsatellites can be modeled under a stepwise “ladder process,” whereby alleles are inter-related according to their repeat lengths. One can then summarize over these microsatellite loci by assuming independence, which thereby allows for the multiplication of their separate posterior distributions and final estimations of their combined Bayesian skyline plot. In these ways, we fully anticipate that such critical testing will lead to many important refinements of our three-step model, including a further narrowing of our proposed range for the size of the founding population as well as new details about post-peopling expansions within the New World. Materials and Methods Datasets Three datasets were collected for analysis including: (i) 77 mtDNA coding genomes; (ii) 812 mtDNA HVRI+II sequences; and (iii) combined nuclear and mitochondrial coding DNA dataset. The 77 mtDNA coding genomes were collected from publicly available resources [45]–[48] and aligned using ClustalX [49]. The resultant 15,500 base pair (bp) multiple alignment was edited by hand to minimize the number of unique gaps and to ensure the integrity of the reading frame (available online as Figure S1). A total of 812 combined HVRI+II sequences were collected from HVRbase (http://www.hvrbase.org) [50]. These sequences were aligned following the coding mtDNAs, resulting in a multiple alignment of 771 bps (available online as Supplemental Figure S2). The complete dataset of 812 HVRI+II sequences was randomly divided into ten non-overlapping alignments of 81 sequences that approximate the sample size for the coding mtDNA dataset. Skyline plot analyses of larger datasets (up to 200 HVRI+II sequences) gave the same results as the 81 sequence datasets (data not shown). Thus, the smaller datasets of 81 sequences each were emphasized here since they avoided the likelihood rounding errors that can occur when using large, heterogeneous datasets in Bayesian skyline plot analyses. The coding nuclear and mtDNA dataset from Asian and Native American populations of Hey (available at http://lifesci.rutgers.edu/heylab/) [16] consisted of two autosomal coding loci, five X-chromosome coding loci, one Y-chromosome coding locus, and the complete mtDNA coding genome (totaling 28,454 aligned bps). The sample sizes for these nuclear loci and mitochondrial genome varied from 12-108 sequences. Bayesian Skyline Plot Analyses Bayesian skyline plots [32] were used to estimate changes in Amerind Nef over time by providing highly parametric, piecewise estimates of Nef. This approach produces serial estimates of effective population size from the time intervals between coalescent events in a genealogy of sampled individuals, and utilizes a Markov chain Monte Carlo simulation approach to integrate over all credible genealogies and other model parameters. It thereby differs from previous approaches (e.g., [51]) in that Bayesian skyline plots fully parameterize both the mutation model (including relaxed clock models) and the genealogical process, whereas prior methods relied on generating estimates from summary statistics (e.g. the use of pairwise differences by [51]). In these analyses, estimates of τ (Nef×generation time) were converted to Nef by dividing by a generation time of 20 years, following convention [16]. Skyline plots were generated for the 77 mtDNA coding genome sequences and the ten datasets of HVRI+II sequences using the program BEAST v1.4 (http://beast.bio.ed.ac.uk). These BEAST analyses relied on the same coalescent and substitution models and run conditions of Kitchen et al. [52] except as noted below. Plots were generated using the established mutation rates (μ) for coding mtDNA (μ = 1.7×10−8 substitutions/site/year) [46] and HVRI+II mtDNA (μ = 4.7×10−7) [53]. Markov chains were run for 100,000,000 generations and sampled every 2,500 generations with the first 10,000,000 generations discarded as burn-in. Three independent runs were performed for all coding and HVRI+II Bayesian skyline plot analyses. Markov chain samples from the three independent mtDNA coding replicates and from the 30 HVRI+II analyses were separately combined using the LogCompiler program (distributed with BEAST) and analyzed using Tracer v1.3 to produce the final Bayesian skyline plots.Isolation-with-Migration Coalescent Analyses Bayesian IM coalescent analyses were performed using the program IM [16] to estimate Ne for the Amerind founder population (males+females) and the divergence time for Amerind and Asian populations. We used the same combined nuclear and mtDNA dataset, same coalescent and substitution models, and same model parameters as Hey [16] with the exception of new priors on the divergence time and on the migration rates between Asian and Amerind populations. All IM analyses were performed using a flat uniform prior for the divergence time of Amerind and Asian populations set to the interval 15–40 kya. The lower bound of this prior is based on accepted archaeological and climatological evidence for the first presence of humans in the Americas [18]–[21]. The upper bound of the flat uniform priors on the migration rates per mutation per generation between the Amerindian and Asian populations (mAsia→NW and mNW→Asia) was set to 12 different values (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, and 50). To help interpret these results, we relied on an estimate of the migration rate in modern Europe as obtained from census data [54]. Specifically, we converted their migration rate estimate of 0.0004 migrations per gene copy per generation (recalculated assuming a generation time of 20 years based on Hey [16]) to our units of migrations per mutation per generation (m) by dividing the former by the geometric mean of the mutation rates for the nine loci in this dataset (9.32×10−5 mutations per locus per generation ). These calculations resulted in m = 4.3 for modern Europe. In contrast, the ancient migration rates between the New World and Asia would have been significantly less, especially after their geographic separation due to the re-inundation of Beringia starting at ≈11 kya (see Introduction). Ten independent replicates were performed for each of the 12 upper bound values on the migration rates, for a total of 120 IM analyses. All Markov chains were run for 100,000,000 generations without heating.Figure S1 Multiple sequence alignment for the 77 Amerind mtDNA coding genomes used in this study. Here, “coding” refers to both protein and structural RNA genes following Pakendorf and Stoneking [30]. Gaps are represented by “-.” Position 1 of this alignment corresponds to site 546 of the Anderson Reference Sequence (ARS; [56]). The final position of this alignment (15,500) corresponds to site 16,042 of the ARS. Sequences starting with “Herrn,” “Ing,” “Kiv”, and “Mis” follow the naming conventions of Herrnstadt et al. [45], Ingman et al. [46], Kivisild et al. [47], and Mishmar et al. [48], respectively. (1.19 MB TXT) Click here for additional data file.(1.1M, txt) Figure S2 Multiple sequence alignments for the ten, randomly selected, non-overlapping sets of 81 HVRI+II sequences used in this study. In these alignments, positions 1-403 correspond to HVRI, whereas sites 404-781 refer to HVRII. In turn, these alignment positions correspond to sites 16003-16400 and 30-399 of the ARS, respectively. Gaps are represented by “-.” The HVRI+II sequences follow the naming conventions of HRVBase [50]. (0.64 MB TXT) Click here for additional data file.(628K, txt) Footnotes Competing Interests: The authors have declared that no competing interests exist. Funding: This study was supported by a grant from the National Science Foundation to CJM (BSR-0518530) and by funds from the Department of Zoology, University of Florida to MMM. References 1. Greenberg JH, Turner CG, Zegura SL. 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