Article Three Phases of Ancient Migration Shaped the Ancestry of Human Populations in Vanuatu Highlights d New ancient DNA supports a shift in ancestry during early migrations to Vanuatu d A single spread from New Britain can explain most of the ancestry of later groups d More recent Polynesian migrations contributed both cultural and genetic legacies Authors Mark Lipson, Matthew Spriggs, Frederique Valentin, ..., Nadin Rohland, Ron Pinhasi, David Reich Correspondence mlipson@hms.harvard.edu (M.L.), Matthew.Spriggs@anu.edu.au (M.S.), ron.pinhasi@univie.ac.at (R.P.), reich@genetics.med.harvard.edu (D.R.) In Brief Lipson et al. report new genetic data and analyses shedding light on three human migrations to Vanuatu. The first involved people with primarily East Asian-related ancestry; the second, shortly afterward, and likely following a similar route from New Britain, primarily Papuan ancestry; and the third, more recently, Polynesian ancestry. Lipson et al., 2020, Current Biology 30, 4846–4856 December 21, 2020 ª 2020 Elsevier Inc. https://doi.org/10.1016/j.cub.2020.09.035 ll ll Article Three Phases of Ancient Migration Shaped the Ancestry of Human Populations in Vanuatu Mark Lipson,1,2,* Matthew Spriggs,3,4,* Frederique Valentin,5 Stuart Bedford,4,6,7 Richard Shing,4 Wanda Zinger,8 Hallie Buckley,9 Fiona Petchey,10,11 Richard Matanik,12 Olivia Cheronet,13 Nadin Rohland,1 Ron Pinhasi,13,* and David Reich1,2,14,15,16,* 1Department of Genetics, Harvard Medical School, Boston, MA 02115, USA of Human Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA 3School of Archaeology and Anthropology, College of Arts and Social Sciences, The Australian National University, Canberra, ACT 2601, Australia 4Vanuatu National Museum, Vanuatu Cultural Centre, Port Vila, Vanuatu 5MSH Mondes, CNRS, UMR 7041, 92023 Nanterre, France 6Department of Archaeology and Natural History, College of Asia-Pacific, The Australian National University, Canberra, ACT 2601, Australia 7Max Planck Institute for the Science of Human History, 07745 Jena, Germany 8Muse
um national d’Histoire naturelle, UMR 7194 (HNHP), MNHN/CNRS/UPVD, Sorbonne Universite
, Muse
e de l’Homme, 75016 Paris, France 9Department of Anatomy, School of Biomedical Sciences, University of Otago, Dunedin 9054, New Zealand 10Radiocarbon Dating Laboratory, Division of Health, Engineering, Computing and Science, University of Waikato, Hamilton 3240, New Zealand 11ARC Centre of Excellence for Australian Biodiversity and Heritage, College of Arts, Society and Education, James Cook University, Cairns, QLD 4878, Australia 12Lelema World Heritage Committee and Vanuatu Cultural Centre, Port Vila, Vanuatu 13Department of Evolutionary Anthropology, University of Vienna, 1090 Vienna, Austria 14Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA 15Howard Hughes Medical Institute, Harvard Medical School, Boston, MA 02115, USA 16Lead Contact *Correspondence: mlipson@hms.harvard.edu (M.L.), Matthew.Spriggs@anu.edu.au (M.S.), ron.pinhasi@univie.ac.at (R.P.), reich@genetics. med.harvard.edu (D.R.) https://doi.org/10.1016/j.cub.2020.09.035 2Department SUMMARY The archipelago of Vanuatu has been at the crossroads of human population movements in the Pacific for the past three millennia. To help address several open questions regarding the history of these movements, we generated genome-wide data for 11 ancient individuals from the island of Efate dating from its earliest settlement to the recent past, including five associated with the Chief Roi Mata’s Domain World Heritage Area, and analyzed them in conjunction with 34 published ancient individuals from Vanuatu and elsewhere in Oceania, as well as present-day populations. Our results outline three distinct periods of population transformations. First, the four earliest individuals, from the Lapita-period site of Teouma, are concordant with eight previously described Lapita-associated individuals from Vanuatu and Tonga in having almost all of their ancestry from a ‘‘First Remote Oceanian’’ source related to East and Southeast Asians. Second, both the Papuan ancestry predominating in Vanuatu for the past 2,500 years and the smaller component of Papuan ancestry found in Polynesians can be modeled as deriving from a single source most likely originating in New Britain, suggesting that the movement of people carrying this ancestry to Remote Oceania closely followed that of the First Remote Oceanians in time and space. Third, the Chief Roi Mata’s Domain individuals descend from a mixture of Vanuatu- and Polynesian-derived ancestry and are related to Polynesian-influenced communities today in central, but not southern, Vanuatu, demonstrating Polynesian genetic input in multiple groups with independent histories. INTRODUCTION A key distinction within Pacific studies has been between Near Oceania, the part of the Western Pacific (comprising New Guinea; the Bismarck Archipelago, including New Britain and New Ireland; and the main Solomon Islands) settled for approximately 50,000 years by modern humans, and Remote Oceania [1]. Remote Oceania encompasses the whole of Micronesia and Polynesia and the geographically designated Melanesian island groups of Vanuatu, New Caledonia, and Fiji (as well as the scattered islands of the Reefs and Santa Cruz groups in the southeast Solomons), which were only settled starting around 3,000 years before present (BP) [1]. 4846 Current Biology 30, 4846–4856, December 21, 2020 ª 2020 Elsevier Inc. ll Article Vanuatu is a key archipelago in the history of Pacific settlement given its status both as the first major island group in southern Remote Oceania to be occupied by humans and as an important regional crossroads during the succeeding three millennia [2, 3]. Our understanding of the genetic history of Vanuatu has been advanced by three studies reporting genome-wide ancient DNA data from individuals who lived in the archipelago over the course of its human settlement [4–6]. The earliest sampled individuals, who belong to the first human migration to Vanuatu (labeled by some commentators as Migration 1 or M1 [7, 8]), are associated with early phases of the Lapita cultural complex and likely with the initial spread of Austronesian languages into Oceania (where Austronesian is now by far the most widespread language family) [9, 10]. They had almost entirely East Asianrelated ancestry, from a source that originated in Taiwan and has been termed ‘‘First Remote Oceanian’’ (FRO) [4]. Later individuals (including present-day people, who identify as ‘‘NiVanuatu’’), by contrast, have largely Papuan ancestry likely originating in New Britain, which reached the Reefs-Santa Cruz [11] and Vanuatu [5, 6] either during latest Lapita or post-Lapita times after 2800 BP. (We use the term ‘‘Papuan’’ to refer to the deep ancestral lineage that contributes the majority of the ancestry found in present-day populations from Near Oceania.) Previous papers differed in their interpretation of this second migration (M2) as being either a time-constrained event [6] or a slower process of continuing genetic exchange through time [5]. Previous studies [5, 6] also noted but did not address in detail signals of a third distinct migration stream (M3) occurring within the last millennium and associated with the establishment of ‘‘Polynesian Outlier’’ communities in Vanuatu (as in other areas of Melanesia and Micronesia): that is, islands where Polynesian sub-group languages are spoken and where elements of Polynesian material and non-material culture are practiced [12, 13]. Polynesian impacts in Vanuatu also extend to a number of islands neighboring the Outlier communities showing Polynesian influence but without full language replacement. Little is known, however, about the degree of population movement accompanying these Polynesian-derived cultural and linguistic changes [14, 15]. One such Polynesian-influenced island is Efate in central Vanuatu, where two Polynesian-language-speaking communities exist today, one on the small off-shore island of Ifira and one at Mele on the southwest of the island. Also located on Efate and the adjacent small islands of Eretok and Lelepa is ‘‘Chief Roi Mata’s Domain,’’ which was inscribed on the UNESCO World Heritage Area list in 2008 on the basis of strong links between oral traditions and a spectacular mortuary site excavated in the 1960s [16]. Some versions of the local oral traditions and aspects of the associated material culture have suggested strong Polynesian influence, illustrated by stories about Chief Roi Mata and his political role on Efate and adjacent islands of the Shepherd Group [16, 17]. The burial site at Eretok was thought initially to date to the 13th century CE [16], but subsequent radiocarbon dates from Eretok and from Mangaas (Mangaasi), the village site on Efate said to have been the home of Chief Roi Mata and his closest followers [16], now place the burials at c. 1600 CE [18]. To gain a genetic perspective on the history of Chief Roi Mata’s Domain, and more generally on the history of Polynesian influence in Vanuatu, we sampled three individuals from the Eretok (also known as Retoka or ‘‘Hat Island’’) Island complex where Roi Mata was buried (according to tradition) along with two individuals from sub-floor burials at Mangaas for ancient DNA analysis. We also report new genome-wide ancient DNA data from six additional individuals from Efate, complementing published data [4, 6]: four from the Teouma Lapita cemetery (~3000–2750 BP, thus doubling the sample size available from that site), one from the Taplins 1 rockshelter, and one from Banana Bay. We combined these 11 individuals with 26 ancient Vanuatu individuals from the literature (who have previously not been analyzed together) [4–6], eight other published ancient Oceanian individuals, and diverse present-day populations to shed light on the following primary questions pertaining to the population movements referred to above as M1, M2, and M3: M1. Does the increased sample of Lapita-period burials from Teouma, combined with other sites, reveal a more diverse founding population than was previously documented? M2. Can we better elucidate the source, timing, and duration of Papuan migration into Vanuatu? M3. Do the newly reported individuals from Eretok and Mangaas within the Chief Roi Mata’s Domain World Heritage Area show particular relatedness to Polynesians as some oral traditions and features of the archaeological record would suggest? RESULTS Sample and Data Preparation We generated genome-wide ancient DNA data for 11 new individuals (Figure 1; Table 1; STAR Methods; Data S1A) and increased sequencing coverage for one previously reported individual from Teouma [6] (I5951/TeoQE, previously 23,107 sites covered, now 120,830). In dedicated clean rooms, we extracted DNA from either petrous bone samples (Teouma, Mangaas, and two Eretok individuals) or teeth (Taplins, one Eretok, and Banana Bay) and prepared next-generation sequencing libraries, enriching for a set of ~1.2 million single-nucleotide polymorphisms (SNPs). Based on a combination of criteria, all yielded authentic ancient DNA (STAR Methods). We created genotype data for analysis by assigning the observed base from one randomly chosen sequencing read covering each targeted SNP. For most analyses, we merged the new data with published data from both ancient and present-day Oceanians [4–6] (Data S1B). We also obtained three new radiocarbon dates to help establish chronology in relation to previously dated samples [19]; notably, the dates from Eretok and Mangaas confirm that the individuals lived within the past several centuries (Table 1; Data S1C). PCA We began by performing a principal component analysis (PCA) in which we computed axes by using Kankanaey (Philippines), Nasioi (Solomon Islands), and New Guinea Highlanders and projected all other individuals (STAR Methods; Figure 2). Visually, PC1 corresponds to relative proportions of FRO ancestry (lower on the left, higher on the right), whereas PC2 corresponds to affinity to populations from the Solomon Islands versus New Guinea (up and down, respectively). Present-day groups from Current Biology 30, 4846–4856, December 21, 2020 4847 ll Figure 1. Geographic Context (A) Regional map. (B) Map of Vanuatu. (C) Map of Efate with sample sizes for newly reported individuals from each site. 4848 Current Biology 30, 4846–4856, December 21, 2020 Article ll Article Table 1. Information for Newly Reported Individuals Lab ID Skeletal Code (Element) Date Location Sex Mt Hap Y Hap I5265 Teo_B10A (petrous) [3000–2750 BP] Efate, Teouma M no call O SNPs 13,594/4,469 I5266 Teo_B10C (petrous) [3000–2750 BP] Efate, Teouma M B4a1a1 O 136,137/45,599 I5267 Teo_B30B (petrous) 3170-2810 calBP (3050 ± 49 BP, Wk-22658) Efate, Teouma M no call no call 8,612/2,802 I5268 Teo_B30C (petrous) 3010-2760 calBP (2995 ± 21 BP, Wk-22659) Efate, Teouma M no call no call 4,165/1,396 I6188 TAP_E149 (tooth) [2600–2200 BP] Efate, Mele-Taplins M Q1b C1b2a 23,812/8,088 I10966
e de l’Homme 25788 Muse (petrous) [500–200 BP] Efate, Mangaas F Q1 n/a 648,879/230,929 I10967
e de l’Homme 25787 Muse (petrous) 290-0 calBP (180 ± 20 BP, PSUAMS-5494) Efate, Mangaas F Q2a3 n/a 469,594/167,469 I10968
e de l’Homme 25793 Muse (petrous) [500–200 BP] Eretok M B4a1a1 C1b2a 848,415/295,552 I10969
e de l’Homme 25791 Muse (petrous) [500–200 BP] Eretok F P2 n/a 749,208/267,632 I14493
e de l’Homme 25797 Muse (tooth) 490-310 calBP (350 ± 20 BP, PSUAMS-6698) Eretok M P2 C1b2a 506,596/179,141 EFE005 EFE005 (tooth) 310-0 calBP (234 ± 19 BP, MAMS-29695) Efate, Banana Bay M P1d2 C1b2a 74,434/25,228 Date, calibrated radiocarbon date (95.4% CI) or burial context estimate (brackets); Mt/Y hap, mitochondrial DNA/Y chromosome haplogroup; SNPs, unique autosomal target sites covered at least once/sites covered in primary analysis dataset. See also Data S1A–S1C. New Britain and Vanuatu form a cluster with relatively uniform values along PC2 but a moderate amount of spread along PC1, with Polynesians and Polynesian Outlier populations farther to the right. Ancient individuals mostly overlap presentday groups from the same island chains, but the Lapita-associated individuals from Teouma (Vanuatu) and Talasiu (Tonga), the ancient individuals from Malakula, and some individuals from Eretok and Mangaas fall farther to the right. The direction of greatest variation within Vanuatu in Figure 2 is approximately left to right (likely reflecting differential FRO/ Papuan mixture proportions), which is well aligned with the primary direction of variation linking New Britain, Vanuatu, Polynesia, and the ancient Lapita-associated individuals. This pattern suggests the possibility that many or all of the populations along this extended cline can be modeled in a simple way as having a shared pair of ancestry components in different proportions: one represented by Papuan ancestry related to that found in some parts of New Britain and Vanuatu at close to 100% and one represented by FRO ancestry related to that found in the Lapitaassociated individuals at close to 100% [4–6]. Explicit Admixture Modeling Guided by the PCA results, we tested candidate admixture models by using the qpAdm software [20, 21]. Previous results [4–6, 11], as well as Figure 2, indicate a high degree of regional population structure in Near Oceania, with largely distinct clusters of Papuan ancestry found in New Guinea, the Solomon Islands (excluding Santa Cruz and Polynesian Outliers), New Britain, and New Ireland, although many populations (e.g., from New Ireland) can be modeled as having mixtures of multiple Papuan ancestry components. In the following analyses, we often use Nasioi (non-Austronesian speakers from the island of Bougainville) and Baining (non-Austronesian speakers from New Britain) to represent the Solomon Islands and New Britain clusters, respectively, because they are the populations with both the lowest proportions of FRO ancestry (~20% and ~5%) and the highest proportions of the distinctive local Papuan ancestry from their clusters in our dataset [4–6, 11]. For almost all of the ancient Vanuatu individuals, we obtain successful qpAdm models (i.e., high p values for model fit) using Baining (Marabu subgroup) and Kankanaey (Austronesian speakers from the Philippines related to the ancestors of FRO) as the two proxy sources, even with Nasioi as an outgroup (STAR Methods; Data S1D). Conversely, if we use Nasioi as a proxy source in place of Baining, almost none of the models are successful. We note that poor fits can result from any unmodeled shared ancestry between the outgroups and either the test population or the proxy sources, for example from small amounts of contamination (for ancient individuals) or if the FROrelated ancestry in Nasioi (as an outgroup) is a better source than the FRO-related ancestry in Kankanaey. For Polynesians and Polynesian Outliers, our power to distinguish between different lineages is limited by their lower proportions of Papuan ancestry, but we observe similar results with better fits when using Baining rather than Nasioi as a proxy source. As previously reported [5], the fits improve with Malaita (a Solomon Islands population with some New Britain-related ancestry; see Figure 2 and [6]) in place of Nasioi, but they are worse than with Baining and are rejected at p < 0.05 for most populations. The quantitative mixture proportion estimates from qpAdm (Figure 3) are also in good agreement with PCA. The lowest proportions of FRO ancestry we observe are 0%–3.6% and 0.6%–6.6% (truncated 95% confidence interval [CI]) for postLapita individuals from Efate and Tanna, respectively, and the highest proportions are 96.4%–99.2%, 96.4%–100%, and 87.4%–100% for Lapita-associated individuals from Teouma, Current Biology 30, 4846–4856, December 21, 2020 4849 ll Article Figure 2. PCA Results 0.12 Bougainville Ranongga 0.1 Vella Lavella Malaita 0.08 0.06 Makira Lavongai Polyn. anc. Lapita Van.+Tonga Solomons anc. Malakula anc. Tanna anc. Futuna anc. Epi anc. Efate ~150 BP Efate ~500 BP Taplins Mangaas Eretok Nailik PC2 0.04 Notsi Axes were computed by using three present-day populations (bottom right legend), and other present-day (no fill) and ancient (large filled symbols; newly reported with black outline) individuals were projected and plotted by using the first two PCs. Colors correspond to genetic clusters centered around the Solomon Islands (red), New Ireland (orange), New Britain (blue), New Guinea (black), and Polynesia and Taiwan (green). N.G., New Guinea; Polyn., Polynesian; Van., Vanuatu; anc., ancient. 0.02 0 Santa Cruz Vanuatu present Tolai Polyn. Outliers Sources of Papuan and FRO Ancestry Nakanai We explored the cline of Papuan and FRO -0.04 Melamela Mangseng ancestry in Remote Oceania in more N. G. Highlanders Nasioi Kankanaey detail through allele-sharing symmetry -0.06 -0.05 -0.03 -0.01 0.01 0.03 0.05 0.07 0.09 tests. To allow us to compare different PC1 populations along the cline, we plotted f4 statistics of interest as a function of a Talasiu (Tonga), and Malakula, respectively. The individuals from separate statistic (f4[X, New Guinea Highlanders; Kankanaey, Chief Roi Mata’s Domain are relatively variable, ranging from a Australian]) proportional to FRO ancestry (Figure S1). If all test low of 17.3%–22.0% total FRO ancestry for I10966 (Mangaas) populations X can be modeled as having mixtures of ancestry to a high of 38.3%–44.2% FRO ancestry for I10969 (Eretok). related to the same two source populations (in different proporWe also compared ancestry proportion estimates on the auto- tions), then such plots are expected to show a straight line somes and X chromosomes to test for possible sex-biased (STAR Methods). First, we computed the statistic f4(X, Dai; Nasioi, New admixture. We observed isolated signals of sex bias, replicating previously reported instances for present-day Polynesians and Guinea Highlanders), which tests for relative allele sharing beancient Malakula (Data S1D) [4, 5]; additional examples could tween the test population X and groups from the Solomon exist, but our statistical power is limited by sequencing coverage Islands and New Guinea (Figure 4A; Data S1E). Two test populations would be expected to yield different values of this and available sample sizes. statistic (after correcting for proportions of FRO ancestry) if they have different sources for their Papuan ancestry (for Dates of Admixture Previous work [4–6] has shown that the majority of present-day example, one from New Britain and the other from New populations in Vanuatu have average admixture dates centered Guinea, New Ireland, or the Solomon Islands). With a few exaround ~2000 BP, in line with other Oceanians, although some ceptions (Erromango, Z = 3.2; Teouma, Z = 2.5; I10969, groups, especially those with potential Polynesian-related Z = 2.3; Tutuba, Z = 4.0; all others within |Z| = 2 of the regresancestry, yield more recent dates (e.g., Futuna, ~1075 ± 225 sion line), present-day and ancient Remote Oceanians give BP [6]). We estimated dates of admixture for the Eretok and highly uniform results (purple and green points and regression Mangaas individuals by using both MALDER [22] and DATES line in Figure 4A), consistent with a common source for their [23] and inferred average dates of roughly 20–30 generations, Papuan ancestry. Tutuba, as a copra plantation island, plauor 550–850 years, before the individuals lived (i.e., ~1400–700 sibly experienced recent admixture between Ni-Vanuatu and BP; Table 2). This range extends somewhat earlier than the introduced plantation laborers from other parts of Melanesia. likely arrival of westward-moving Polynesian groups in Vanuatu, Why Erromango is an exception is unclear; it was a muchwhich, based on archaeological evidence, occurred around visited island in the 19th century by groups purchasing and 1000–750 BP [13, 24]. However, under a scenario of Polynesian cutting sandalwood and, as a result of such contacts, suffered influx, the expected average admixture dates would reflect a population collapse through introduced diseases [26]. Among combination of recent and older events, given that both Polyne- Near Oceanians, as expected, groups from New Guinea are sians and local groups would have been admixed already. We generally below the Remote Oceanian line, and groups from did not detect significant evidence of multiple waves of admix- the Solomon Islands are above. A subset of populations ture from MALDER, but because both proximal sources would from New Britain, however, closely track the Remote Oceanhave had mixtures of the same (Papuan and FRO) types of ians, suggesting that they represent good proxies for the ancestry, it is difficult to disentangle the different episodes source of Papuan ancestry that contributed (predominantly) [22]. Still, the relatively recent dates for Eretok and Mangaas, to Vanuatu and Polynesia. We confirmed this result by using together with the observed heterogeneity in mixture propor- qpWave [27], where we obtain reasonably good two-compotions [25], provide evidence of more recent admixture nent fits (rank 1 p = 0.18 without Nasioi as an outgroup, p = 0.02 with Nasioi added; STAR Methods) for 10 ancient processes. -0.02 Papua N. G. Baining Polyn. present Mamusi Ami/Atayal 4850 Current Biology 30, 4846–4856, December 21, 2020 ll Article Figure 3. Ancestry Proportions for Ancient Vanuatu Individuals 100% Results are from two-component qpAdm models estimating total proportions of Papuan and FRO ancestry, truncated at 0% for four individuals with negative point estimates. Newly reported individuals are represented by points with black outlines. Some points are shifted slightly left and right for legibility. Bars show two standard errors in both directions (for truncated individuals, upper limit of point estimate plus two standard errors). See Table 1 for full date intervals and Data S1D for full qpAdm results. Papuan ancestry 80% Eretok 60% Mangaas 40% 20% Malakula 0% 3000 2500 2000 1500 Epi Efate 1000 Tanna/Futuna 500 0 Years BP Vanuatu population groups together with present-day Tongan plus Melamela (Austronesian speakers from New Britain with | Z| < 2 deviation from the regression line in Figure 4A). Presentday Vanuatu populations require four ancestry sources (rank 3 p = 0.17 without Nasioi as an outgroup, p = 0.02 with Nasioi added), plausibly due to small proportions of distinct Papuan (as in Erromango and Tutuba) or other (e.g., East Asian or European) ancestry resulting from recent contacts. Next, we performed similar tests for possible different sources of FRO ancestry. We first computed f4(X, New Guinea Highlanders; Teouma, Kankanaey) to test relatedness of FRO ancestry across Oceania to the Teouma individuals versus present-day Kankanaey. All populations yield positive values highly correlated with levels of FRO ancestry (Figure S2A; Data S1F), indicating that the ancestry is more closely related to the Teouma individuals [4]. We then computed f4(X, New Guinea Highlanders; Teouma, Talasiu) to test whether the FRO ancestry is more closely related to the Lapita-associated individuals from Vanuatu or from Tonga. Although our statistical power is limited by the close relationship between the two Lapita-associated groups, we obtain significantly non-zero values for populations having relatively high FRO ancestry, with the negative slope implying (slightly) greater affinity to Talasiu than to Teouma (Figure S2B; Data S1G). However, we observe only minor deviations from the regression line (max |Z| = 2.5). Thus, the FRO ancestry found in sampled ancient and present-day Oceanian populations appears to be relatively uniform in its relationships to the Lapita-associated individuals from Vanuatu and Tonga, and slightly closer to the latter. Table 2. Inferred Average Dates of Admixture Test Group or Individual MALDER Result (Gen/Year) DATES Result (Gen/Year) Eretok (triple) 16.4 ± 4.5/459 ± 126 24.1 ± 5.0/675 ± 140 Mangaas (pair) 36.5 ± 15.4/1,023 ± 432 22.6 ± 6.9/633 ± 193 I10968 (Eretok) – 18.4 ± 4.6/514 ± 128 I10969 (Eretok) – 29.6 ± 9.1/828 ± 256 I14493 (Eretok) – 28.3 ± 9.3/793 ± 261 I10966 (Mangaas) – 31.7 ± 13.5/888 ± 378 I10967 (Mangaas) – 18.5 ± 7.4/517 ± 207 Gen/year, generations/years before the individuals lived (mean ± 1 SE). Polynesian Genetic Legacy By using similar methods, we tested for the presence of specifically Polynesian-related ancestry via the statistic f4(X, Tolai; Kankanaey, Tongan) (STAR Methods; Figure 4B; Figure S3; Data S1H). As expected, other Polynesians show very strong allele sharing with Tonga (|Z| > 9 for Samoa, Tahiti, and the Polynesian Outliers of Ontong Java, Rennell and Bellona, and Tikopia). Within Vanuatu, most groups are consistent with the baseline level established by Near Oceanians, but some—generally those with higher total proportions of FRO ancestry—display excess allele sharing with Tonga. These include one ~150 BP Efate (Ifira) individual (Z < 3) and present-day Aneityum, Banks, Efate, Emae, Futuna, Makura, Mele (high-FRO subgroup, from the island of Efate), and Tongoa (all Z < 4). Among our newly reported ancient individuals, both from Mangaas and two of the three from Eretok have strong signals of Polynesian affinity ( 5.0 % Z % 3.6). We also attempted to determine the source of this Polynesian affinity more precisely by using statistics f4(X, Tolai; Polynesian1, Polynesian2) (Data S1I–S1L). We did not detect significant differences in allele sharing relative to Tonga versus Samoa, but for a number of Polynesian-influenced groups in Vanuatu, we observed modest excess allele sharing with Tonga versus Polynesian Outliers (max |Z| = 3.6, 2.5, and 2.5 for Ontong Java, Rennell and Bellona, and Tikopia, respectively). One exception was excess relatedness between Namaram (from the island of Pentecost) and Ontong Java (Z = 3.2). However, for the most part, the source of the Polynesian-related ancestry in the Vanuatu groups appears to be slightly more closely related to populations from Polynesia than to other Polynesian Outlier communities in Melanesia (at least in their current genetic makeup). We then tested for excess allele sharing between the Eretok and Mangaas individuals and other Vanuatu populations (STAR Methods; Data S1M–S1Q). We detected several significant signals: (1) between the five ancient individuals and present-day Efate (Z = 1.8–3.2) and especially the high-FRO subgroup of present-day Mele (Z = 4.2–7.5), (2) between the Eretok individuals I10968 and I10969 and the ~150 BP individual from Ifira (Z = 2.7–3.6), and (3) among the five Eretok and Mangaas individuals themselves (Z = 1.8, 2.2, 2.5, 2.7, 2.9, 3.6, 6.5, 7.2, 7.4, and 16.4). A separate statistic testing for allele sharing with presentday Futuna identified a strong relationship with Aneityum (Z > 9) but confirmed no particular relatedness to Eretok or Mangaas (Data S1R). Follow-up analyses also indicated that the Eretok Current Biology 30, 4846–4856, December 21, 2020 4851 ll Article Figure 4. Allele-Sharing Regression Tests A (A) Test for differential Papuan ancestry. The regression line was computed by using groups from Vanuatu and Polynesia, except for the Lapitaassociated individuals (rightmost three points). (B) Test for Polynesian influence. The regression line was computed by using Near Oceanian populations. Filled points represent the Eretok/Mangaas individuals. The legend is the same for both panels (the ‘‘New Guinea’’ label includes some closely related populations from nearby islands; some in the far lower left in (A) are omitted for scale), and bars show two standard errors in each direction. Polyn., Polynesian. See also Figures S1–S4 and Data S1E–S1R. 0.004 0 -0.002 -0.004 Greater allele-sharing with Nasioi versus New Guinea Highlanders f4(X, Dai; Nasioi, New Guinea Highlanders) 0.002 Tutuba -0.006 Britain), one of which can parsimoniously characterize the Papuan ancestry in Melamela (New Britain), Vanuatu, and Tonga. Within Vanuatu, the model contains Greater FRO ancestry -0.01 separate two-stage admixture histories 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 FRO allele-sharing rate in the southern and central parts of the arB 0.008 New Britain New Ireland chipelago. Present-day Futuna can be New Guinea Solomon Islands Vanuatu Polyn. + Polyn. Outliers modeled as having 56% ancestry related Regression to individuals from Tanna (who them0.006 selves are inferred to have 12% FRO ancestry and 88% Papuan ancestry) and 44% related to Polynesians. For Efate, I5259 (from Mangaliliu, but not neces0.004 sarily associated with the Chief Roi Mata’s Domain sites) is inferred to have 11% FRO ancestry and 89% Papuan ancestry, and the Eretok/Mangaas group 0.002 can be modeled as having 63% of their ancestry related to I5259 and 37% related Futuna to Polynesians (for a total of ~33% FRO (present) ancestry). If we model Eretok/Mangaas 0 I10969 and Futuna as having excess FRO (but I10968 not specifically Polynesian-related) ancestry, the log likelihood of the model Greater FRO ancestry is more than 30 units lower, with residual -0.002 poorly predicted f statistics (Z > 5). Tanna 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 f4(X, New Guinea Highlanders; Kankanaey, Australian) and I5259 might not be exact representatives for the true ancestral source groups, individual I14493 and the Mangaas individual I10967 are close so the inferred proportions of Polynesian-related ancestry could family relatives (probably second degree; Figure S4), explaining be slightly inaccurate, but they are plausible proxies based on their especially high allele sharing (Z = 16.4) and confirming oral both the regional genetic context and the fit quality of the final traditions directly linking both sites in the Roi Mata stories. model. Erromango Greater allele-sharing with Tongan versus Kankanaey f4(X, Tolai; Kankanaey, Tongan) -0.008 Admixture Graph Analysis Finally, we built an admixture graph to explore relationships among multiple populations simultaneously, including presentday Tanna and Futuna, a ~600 BP individual (I5259) from Efate [6], Eretok and Mangaas, Polynesians, and diverse Near Oceanians (Figure 5; Figure S5; STAR Methods). The final model predicts all f statistics relating the populations to within 2.7 standard errors of their observed values. We inferred two admixture events [6] among four ancestral Papuan lineages (associated with New Guinea, the Solomon Islands, and two with New 4852 Current Biology 30, 4846–4856, December 21, 2020 DISCUSSION The human genetic history of Vanuatu is complex, featuring interactions between multiple populations with diverse origins. This complexity is not surprising given that the archipelago stretches for more than 1,000 km and forms a crucial intervisible link in the southwest Pacific from the Reefs and Santa Cruz (at the eastern edge of the Solomon Islands) to New Caledonia. Furthermore, in light of the great cultural diversity that characterizes Vanuatu today, it would not be surprising if different parts of ll Futuna (S. Vanuatu) Atayal Eretok/ Mangaas Kankanaey Tanna (S. Vanuatu) Tongan Efate ~600 BP Melamela (New Britain) Baining Marabu (New Britain) New Guinea Highlanders Nasioi (Solomon Islands) Article Figure 5. Schematic of Admixture Graph Results Inferred phylogeny is shown for FRO-related ancestry (light green) and four Papuan lineages (pink, black, and blue, shown separately because they are not related by a simple tree). Arrows denote Papuan ancestry found in Vanuatu and Polynesia (solid blue), admixed FRO ancestry (green), local Ni-Vanuatu ancestry (dashed blue), Polynesian-related ancestry (dashed dark green), and intra-New Britain admixture (dotted blue). Colored bars give inferred total ancestry proportions (excluding outgroups Australian and Mixe). See Figure S5 for full results. S., southern. the archipelago have experienced different demographic dynamics in the past. The results in this study further our understanding of three population movements (M1–M3) that contributed substantially to the genetic makeup of Vanuatu through time, with new evidence presented pertaining to several open questions. Four newly reported individuals from Teouma (Efate) join published data to make a total of 12 sampled Lapita-associated individuals (all represented by petrous bones) from Remote Oceania dating to 3000–2500 BP (eight from Teouma, three from Talasiu in Tonga, and one from Malakula), all of whom have nearly entirely FRO-related ancestry [4–6]. Thus, although future sampling could potentially still reveal greater genetic diversity during this period, ancient DNA results to date support the hypothesis that the first people of Remote Oceania, who were responsible for spreading the Lapita cultural complex (M1), were mostly descended from a population with roots in East and Southeast Asia [4]. After about 2500 BP, sampled individuals from post-Lapita contexts testify to an influx of Papuan ancestry (M2), although with different trajectories in different parts of Vanuatu. The three earliest individuals from this period from central and southern Vanuatu (one newly reported here) have the smallest proportions of FRO ancestry in our dataset, pointing to a major local genetic shift. The increased FRO ancestry in later populations from the same islands, combined with estimated dates of admixture that postdate the Lapita period, shows that mixture subsequently occurred between populations with different proportions of FRO and Papuan ancestry [5, 6]. Previously published lateLapita and post-Lapita individuals (2500–2000 BP) from Malakula in northern Vanuatu provide direct documentation of such an admixture process, as reflected in widely varying individual-level ancestry proportions along with recent estimated dates of admixture [5] (cf. Verdu and Rosenberg [25]). Unlike the other ancient individuals, those from Malakula come from a site that was continuously occupied for 1,000 years, from the founding Lapita population until around 2000 BP. There are also indications that elements of the Lapita culture persisted for longer in this region than in central and southern Vanuatu [28, 29]. Our reanalysis of ancient and present-day data supports a single source for the main component of Papuan ancestry found in Vanuatu from 2500 BP to the present, with most of the (few) exceptions potentially relating to post-European-contact movements. In particular, though we do not have contemporaneous ancient DNA data available from Near Oceania, the location of this source, based on the strong present-day regional genetic structure, is likely to have been New Britain, and we do not detect more than isolated evidence of gene flow from the (geographically closer) Solomon Islands (in agreement with Pugach et al. [11]). This relative homogeneity (across Vanuatu as well as through time) favors the hypothesis of a short-term migration episode responsible for introducing Papuan ancestry beginning around the late-Lapita period. Inferred dates of admixture in Vanuatu (aside from Polynesian-influenced groups) also point to mixture of FRO and Papuan ancestry around this time [5, 6]. A priori, the most likely movements and interactions would be expected to be between neighboring archipelagoes rather than distant ones, i.e., from the main Solomons chain to the Reefs and Santa Cruz to Vanuatu. However, this appears not to have Current Biology 30, 4846–4856, December 21, 2020 4853 ll be the case either for M1, on archaeological and linguistic grounds [30], or for M2, on the basis of direct genetic links between Vanuatu and New Britain to the exclusion of the Solomons. In light of results from both genetics and archaeology, a parsimonious explanation could be that M2 was effectively a continuation of M1 in late-Lapita times but involving migrants having mostly different ancestry. Cultural connections between New Britain and Vanuatu include the presence of New Britain obsidian in earliest Lapita deposits in Vanuatu [31], changes in dietary and mortuary behaviors and skeletal morphology subsequent to this earliest Lapita phase [32, 33], and distinctive practices (of unknown time depth), such as head binding and the production of fully circular pig’s tusks, that are exclusive to those locations [5, 34]. We also find that, contrary to the more complex proposals in previous studies [5, 6], we can model the Papuan ancestry found in Polynesians by using the same New Britainrelated source as for Vanuatu, raising the possibility that both were derived predominantly from the same phase of migration. However, as with the FRO component, future work is necessary to determine whether or not people carrying this ancestry passed through Vanuatu en route to Polynesia. In accordance with archaeological and anthropological evidence of Polynesian cultural influence in Efate over the past several centuries, our analysis of five individuals from the Chief Roi Mata’s Domain World Heritage Area demonstrates an influx of Polynesian-related ancestry as well (M3) through signals of higher FRO ancestry proportions, relatively recent dates of admixture, and specifically high allele sharing with Polynesians. The present-day Polynesian Outlier community of Mele, as well as other present-day and recent-past individuals from Efate and nearby islands (but not more distant groups), also display shared ancestry with the Eretok and Mangaas individuals, whereas the Polynesian Outlier population of Futuna and the neighboring island of Aneityum in southern Vanuatu likely represent a separate instance of Polynesian influence (we currently lack data for comparison from communities such as those of Lelepa and Mangaliliu in the immediate World Heritage Area vicinity). Thus, although the ancestry of present-day Ni-Vanuatu groups can largely be traced to the early human history of the archipelago, later migrations—in particular of Polynesians—have also contributed to the genetic diversity of Vanuatu today. STAR+METHODS Detailed methods are provided in the online version of this paper and include the following: d d d KEY RESOURCES TABLE RESOURCE AVAILABILITY B Lead Contact B Materials Availability B Data and Code Availability EXPERIMENTAL MODEL AND SUBJECT DETAILS B Teouma B Mangaas B Eretok B Taplins B Banana Bay 4854 Current Biology 30, 4846–4856, December 21, 2020 Article d d METHOD DETAILS B Ancient DNA laboratory procedures B Bioinformatic processing B Uniparental haplogroups and authentication B Radiocarbon Dates QUANTIFICATION AND STATISTICAL ANALYSIS B Dataset construction B PCA B Formal modeling of admixture B Dates of admixture B f4 regression analysis B Admixture graph fitting SUPPLEMENTAL INFORMATION Supplemental Information can be found online at https://doi.org/10.1016/j. cub.2020.09.035. ACKNOWLEDGMENTS We thank Ann Marie Lawson, Fatma Zalzala, Jonas Oppenheimer, Kimberly Callan, Kristin Stewardson, Matthew Ferry, Megan Michel, Nasreen Broomandkhoshbacht, Nicole Adamski, Kendra Sirak, and Francesca Candilio for ancient DNA laboratory work; Swapan Mallick and Matthew Mah for bioinformatics; Iñigo Olalde for help with kinship analysis; Rebecca Bernardos and Zhao Zhang for other data processing assistance; Douglas J. Kennett for €gele, and Cosimo help with radiocarbon dating; Johannes Krause, Kathrin Na Posth for providing the EFE005 data; Graeme K. Ward for archaeological contributions; and Nick Patterson for helpful comments. We acknowledge the
e de l’Homme from the CRMD Management permission to sample at the Muse
um national d’Histoire naturelle (Muse
e de Committee, and we thank the Muse l’Homme) for access to collections (Eretok and Mangass) and Martin Friess for assistance in sample selection. We also gratefully acknowledge the interest and support of Ralph Regenvanu and of the Chiefs of Lelepa and Mangaliliu, to whom one of us (M.S.) presented results of this work in December 2019. D.R. was supported by the National Institutes of Health (NIGMS GM100233), the John Templeton Foundation (grant 61220), and the Paul Allen Foundation (Allen Discovery Center grant); D.R. is also an Investigator of the Howard Hughes Medical Institute. AUTHOR CONTRIBUTIONS M.S., R.P., and D.R. supervised the study. M.S., F.V., S.B., R.S., W.Z., H.B., and R.P. provided samples and assembled archaeological and anthropological materials and information. F.P. performed radiocarbon dating analysis. R.M. served as a liaison for the project with other stakeholders. M.L. and D.R. analyzed genetic data. O.C. and N.R. performed and supervised ancient DNA laboratory work. M.L., M.S., and D.R. wrote the manuscript with input from all coauthors. DECLARATION OF INTERESTS The authors declare no competing interests. Received: March 30, 2020 Revised: July 14, 2020 Accepted: September 10, 2020 Published: October 15, 2020 REFERENCES 1. Green, R.C. (1991). Near and Remote Oceania: Disestablishing ‘Melanesia’ in culture history. In Man and a Half: Essays in Pacific anthropology and ethnobiology in honour of Ralph Bulmer, A. Pawley, ed. (The Polynesian Society), pp. 491–502. Article 2. Bedford, S., and Spriggs, M. (2008). Northern Vanuatu as a Pacific crossroads: The archaeology of discovery, interaction and the emergence of the ‘ethnographic present’. Asian Perspect. 47, 95–120. 3. Bedford, S., and Spriggs, M. (2018). The archaeology of Vanuatu: 3000 years of history across islands of ash and coral. In The Oxford Handbook of Prehistoric Oceania, E. Cochrane, and T. Hunt, eds. 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Inferring admixture histories of human populations using linkage disequilibrium. Genetics 193, 1233–1254. 4856 Current Biology 30, 4846–4856, December 21, 2020 ll Article STAR+METHODS KEY RESOURCES TABLE REAGENT or RESOURCE SOURCE IDENTIFIER This study See Table 1 Agilent Technologies 600412 Biological Samples Ancient human skeletal elements Chemicals, Peptides, and Recombinant Proteins Pfu Turbo Cx Hotstart DNA Polymerase Herculase II Fusion DNA Polymerase Agilent Technologies 600679 2x HI-RPM hybridization buffer Agilent Technologies 5190-0403 0.5 M EDTA pH 8.0 BioExpress E177 Silica magnetic beads G-Biosciences 786-915 Sera-MagÔ Magnetic Speed-beadsÔ Carboxylate-Modified (1 mm, 3EDAC/PA5) GE LifeScience 65152105050250 USER enzyme New England Biolabs M5505 UGI New England Biolabs M0281 Bst DNA Polymerase2.0, large frag. New England Biolabs M0537 PE buffer concentrate QIAGEN 19065 Proteinase K Sigma Aldrich P6556 Guanidine hydrochloride Sigma Aldrich G3272 3M Sodium Acetate (pH 5.2) Sigma Aldrich S7899 Water Sigma Aldrich W4502 Tween-20 Sigma Aldrich P9416 Isopropanol Sigma Aldrich 650447 Ethanol Sigma Aldrich E7023 5M NaCl Sigma Aldrich S5150 1M NaOH Sigma Aldrich 71463 20% SDS Sigma Aldrich 5030 PEG-8000 Sigma Aldrich 89510 1 M Tris-HCl pH 8.0 Sigma Aldrich AM9856 dNTP Mix Thermo Fisher Scientific R1121 ATP Thermo Fisher Scientific R0441 10x Buffer Tango Thermo Fisher Scientific BY5 T4 Polynucleotide Kinase Thermo Fisher Scientific EK0032 T4 DNA Polymerase Thermo Fisher Scientific EP0062 T4 DNA Ligase Thermo Fisher Scientific EL0011 Maxima SYBR Green kit Thermo Fisher Scientific K0251 50x Denhardt’s solution Thermo Fisher Scientific 750018 SSC Buffer (20x) Thermo Fisher Scientific AM9770 GeneAmp 10x PCR Gold Buffer Thermo Fisher Scientific 4379874 Dynabeads MyOne Streptavidin T1 Thermo Fisher Scientific 65602 Salmon sperm DNA Thermo Fisher Scientific 15632-011 Human Cot-I DNA Thermo Fisher Scientific 15279011 DyNAmo HS SYBR Green qPCR Kit Thermo Fisher Scientific F410L Methanol, certified ACS VWR EM-MX0485-3 Acetone, certified ACS VWR BDH1101-4LP Dichloromethane, certified ACS VWR EMD-DX0835-3 Hydrochloric acid, 6N, 0.5N & 0.01N VWR EMD-HX0603-3 (Continued on next page) Current Biology 30, 4846–4856.e1–e6, December 21, 2020 e1 ll Article Continued REAGENT or RESOURCE SOURCE IDENTIFIER High Pure Extender from Viral Nucleic Acid Large Volume Kit Roche 5114403001 NextSeqÒ 500/550 High Output Kit v2 (150 cycles) Illumina FC-404-2002 This paper ENA: PRJEB40109 In-house bioinformatics tools https://github.com/DReichLab/ ADNA-Tools N/A In-house data workflow https://github.com/DReichLab/ adna-workflow N/A Samtools [35] http://samtools.sourceforge.net/ BWA [36] http://bio-bwa.sourceforge.net/ Picard https://broadinstitute.github.io/picard/ N/A ADMIXTOOLS [37] https://github.com/DReichLab/AdmixTools SeqPrep https://github.com/jstjohn/SeqPrep N/A bamrmdup https://bitbucket.org/ustenzel/biohazard N/A smartpca [38] https://www.hsph.harvard.edu/ alkes-price/software/ PMDtools [39] https://github.com/pontussk/PMDtools Haplogrep 2 [40] http://haplogrep.uibk.ac.at/ htsbox https://github.com/lh3/htsbox N/A contamMix [41] contact Philip Johnson plfj@umd.edu OxCal [42] https://c14.arch.ox.ac.uk/oxcal.html MALDER [22] https://github.com/joepickrell/malder/tree/ master/MALDER DATES [23] https://github.com/priyamoorjani/DATES Critical Commercial Assays Deposited Data Raw and analyzed data Software and Algorithms RESOURCE AVAILABILITY Lead Contact Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, David Reich (reich@genetics.med.harvard.edu). Materials Availability This study did not generate new unique reagents. Data and Code Availability The aligned sequences are available through the European Nucleotide Archive under accession number ENA: PRJEB40109. Genotype data files are available at https://reich.hms.harvard.edu/datasets. EXPERIMENTAL MODEL AND SUBJECT DETAILS The following are brief descriptions of the sites and burials where the ancient individuals included in this study were found. Teouma The Teouma site is located in southern Efate, on the edge of a large sheltered bay. It was once located near the sea but due to uplift it is now some 800 m from the current coast and 8 m above sea level. It comprises a colonizing Lapita settlement and associated cemetery dating from c. 2950 BP. Six field seasons of excavation were carried out at the site [9]. They revealed an extensive cemetery with up to 68 burial features. The burials were placed in solution holes in the ancient uplifted reef or in shallow graves on the old coral beach foreshore. They were directly associated with Lapita pottery and a range of ornaments also typical of Lapita. Manipulation e2 Current Biology 30, 4846–4856.e1–e6, December 21, 2020 Article ll of the bodies and the skeletal remains was standard procedure with all the adult skulls being removed from the initial interments [10, 43]. In a number of rare cases skulls were placed within other graves. Petrous portions of four of them were analyzed here (B10A, B10C, B30B, B30C). Continuing Lapita-period occupation at the site along with subsequent post-Lapita occupation ultimately buried the cemetery. The site appears to have been abandoned by about 2500 BP. Mangaas
The Mangaas or Mangaasi site is located on the west coast of Efate opposite Lelepa Island. The site was first excavated by Jose Garanger in 1967 as part of his wider pioneering archaeological research on central Vanuatu [16]. In oral traditions the site is said to be the location of the village of Roi Mata, a powerful chief who transformed the socio-political organization of the region. Deeply buried deposits were identified that were associated with distinctive pottery, subsequently named Mangaasi. Two burials (represented by petrous bones) recovered in the upper layers of the site are the subject of analysis here while five graves and two groups of disturbed human remains were recorded by Garanger. The same site and a much more extensive area immediately adjacent to the west were subsequently re-investigated from 1996-2003 [44, 45]. It has now been established that the region was first occupied around 2800 BP with continuing settlement in the region up to the present, primarily focused parallel to the coast. The earliest settlement is now some 80 m from the current beach due to continuing uplift, and, over millennia, settlements have continued to shift to maintain their location near the coast. The earlier archaeological deposits are generally deeply buried due to subsequent slopewash and tephra deposits. Eretok Eretok (also known as Retoka or Hat Island) is located just offshore of Efate and Lelepa Islands on the west coast of Efate. It is the location of a cemetery that was associated with the death of chief Roi Mata in c. 1600 CE. Oral traditions tell of the death of this very important chief and how subsequently he was buried as part of a large communal ceremony undertaken on the island. Dozens of
Garanger in people apparently volunteered to be buried with the chief as part of the ceremony. The site was excavated by Jose 1967 after he was informed of its location by local community members working on the site of Roi Mata’s village at Mangaas [16]. More than 50 individuals were identified with many buried as couples and others individually. Three of them, represented by two petrous bones and one tooth, are analyzed here. Roi Mata is identified as being buried in a more deeply excavated zone in front of a series of standing stones, alongside a number of individuals ostentatiously decorated with traditional shell and other ornaments. Taplins Taplins comprises two rockshelters, Taplins 1 and 2, located at the base of a cliff on uplifted terraces behind Mele Bay in the southwestern part of Efate. Five subsurface graves were excavated at these sites by Graeme Ward in 1973 and 1974 [46, 47]. Both the earlier analyzed individual and the subject of this study came from Taplins 1. The loose tooth studied here was initially hypothesized to belong to the same individual as the previously published petrous bone sample [6], but the genetic analysis shows that a second individual is represented (different mtDNA and Y chromosome haplogroups, and genome-wide allele-matching rates at the level of unrelated individuals). Banana Bay Four burials were located during drainage works associated with road improvements around Efate Island [48]. The site is located on the southeast coast of the island. Local informants said that there had been a large village located in this area up to European contact. Burial 1, a burial in a supine position some 1.5 m below the current ground surface, was clearly associated with the historic period as the body was adorned with a shell and glass bead necklace. That individual was analyzed in ref. [6]. The tooth studied here is associated with a group of bones representing at least one other individual, found close by burial 1. METHOD DETAILS Ancient DNA laboratory procedures For the Teouma and Taplins samples, powder was drilled from bones or teeth in a clean room facility at University College Dublin, and DNA was then extracted in dedicated clean rooms at Harvard Medical School following previously published protocols [49–51] (additional sample preparation information can be found in Data S1A). Powder was obtained from four of the Mangaas and Eretok samples
e de l’Homme in Paris, while for I14493, the drilling step was omitted, and the tooth was subvia cranial base drilling [52] at the Muse merged directly in 1.5 mL of extraction buffer for 4 h. Laboratory work for EFE005 took place at the Max Planck Institute for the Science of Human History in Jena, Germany. The tooth was cut along the enamel/dentin junction and drilled into the pulp chamber, with the extraction then proceeding as above. Barcoded sequencing libraries (1-5 per individual) were prepared from the extracts, utilizing the enzyme uracil-DNA glycosylase (UDG; partial treatment, for all but EFE005) to reduce the rate of deamination-induced ancient DNA damage artifacts [53–56]. The libraries were enriched for sequence fragments overlapping the mitochondrial genome and ~1.2 million genome-wide SNPs via two rounds of in-solution target capture [20, 57–60], with 7-base-pair indices added for the libraries generated at Harvard Medical School [61]. The libraries were sequenced on an Illumina HiSeq machine with single-end reads (EFE005) or an Illumina NextSeq 500 machine with 76-base paired-end reads (others). Current Biology 30, 4846–4856.e1–e6, December 21, 2020 e3 ll Article Bioinformatic processing For the ten individuals for whom data were generated at Harvard Medical School, we assigned sequencing reads to their respective libraries based on their barcodes, requiring at most one mismatch per read pair. We merged overlapping reads, trimmed barcodes and adapters, and then mapped to the mitochondrial reference genome RSRS [62] and to the human reference genome (version hg19) using the ‘samse’ command with default parameters in BWA (version 0.6.1) [36]. After aligning, we removed duplicate molecules and imposed a mapping quality filter of 10. Finally, we trimmed terminal bases (2 for UDG-treated libraries and 5 for untreated) to eliminate most damage-induced errors, and we called pseudo-haploid genotypes for genome-wide analyses by selecting one allele at random per targeted SNP site. Data for EFE005 were processed at the Max Planck Institute in Jena as described elsewhere [5]. Uniparental haplogroups and authentication We determined genetic sex of each individual by examining the fractions of sequence fragments mapping to the X and Y chromosomes [63]. We called mitochondrial haplogroups using HaploGrep2 [40] and Y chromosome haplogroups by comparing SNP genotypes (using all reads) to the International Society of Genetic Genealogy Y-tree (http://www.isogg.org). We assessed the authenticity of the data through five measures (Data S1A). First, we computed the rate of damage-induced errors in terminal positions of sequenced molecules to confirm the presence of ancient DNA signatures. We then tested for possible contamination by (a) confirming that genetic sex could be determined as male or female, (b) computing the rate of matching of mtDNA sequences to the consensus haplogroup call for each individual [41], and (c) measuring apparent heterozygosity at variable sites on the X chromosome in males [64]. Finally, we noted any signals in the genome-wide ancestry analyses that could suggest possible contamination from present-day human DNA. For the individuals with lower coverage (fewer than 100,000 SNPs), the metrics are noisier, and the contamination estimates are generally less reliable, so our typical approach was to run our analyses for these individuals but to be cautious in interpreting the results and not to draw fine-grained conclusions. For the higher-coverage individuals, all metrics indicated at most a few percent contamination. One individual (I14493) had lower than expected damage rates (2.4% for mapped nuclear reads) but low contamination estimates (about 2%–5% from both mtDNA and X chromosome). As an empirical test, we fit an admixture model for I14493 in qpAdm using damage-restricted data, and the results were extremely similar to those for all data (p = 0.61, 82.7 ± 4.4% Bainingrelated ancestry, and 17.3 ± 4.4% Kankanaey-related ancestry, versus p = 0.84, 79.8 ± 1.4%, and 20.2 ± 1.4%; Data S1D). Thus, we continued to use the data in our analyses. Radiocarbon Dates We report new direct AMS radiocarbon dates for three individuals (EFE005, I10967, and I14493), which we combined with previously published dates for I5267 and I5268 [19]. Dates were calibrated using OxCal [42] version 4.3 with a mixture of the Marine13 and Intcal13 curves [65] as determined by linear interpolation between dietary terrestrial and marine d13C isotopic endpoints ( 21&/-12&) with an uncertainty of ± 10% on the percent marine carbon result, following the methodology outlined in ref. [66] to assess the proportion of marine, reef, and terrestrial food contribution to the bone protein. A location-specific reservoir correction (DR) of 40 ± 44 14C years was also applied to the marine curve to adjust for regional oceanic variation in 14C around Vanuatu [67]. QUANTIFICATION AND STATISTICAL ANALYSIS Dataset construction We merged our newly generated data with published ancient and present-day data [4–6, 68, 69]. Unless otherwise specified, we used a set of ~398,000 autosomal SNPs from the Human Origins array, excluding (a) C-to-T transition SNPs at CpG dinucleotides, and (b) a set of SNPs with high rates of missing data in present-day genotype data. For f-statistic-based analyses (as reflected in the sample sizes in Data S1B), we excluded 20 present-day individuals who were outliers relative to their ethnolinguistic groups: UV128 (Tolai); UV219 (Mengen); UV220 (Sulka); UV726 (Kuot Kabil); UV516 and UV519 (Kuot Lamalaua); UV533 (Nailik); UV1166 (Melamela); Jk2663, Jk2665, and Jk2669 (Samoan); and nine individuals from Vanuatu who were identified as outliers in previously published data curations [6]. PCA We performed PCA with smartpca [38], using the ‘lsqproject’ and ‘shrinkmode’ options. We used three populations (Kankanaey, Nasioi, and New Guinea Highlanders) to define axes and projected all other individuals. Projecting ancient individuals prevents bias due to missing data; we chose to project present-day populations as well in order to create a two-dimensional plot with equivalent procedures for all individuals (aside from the three axis populations) and with minimal effects of population-specific drift. We note that the ancient individuals with lower coverage have more uncertainty associated with their positions. Formal modeling of admixture We tested admixture models using the qpAdm software [20, 21]. Our basic outgroup list consisted of New Guinea, Australian, French, Dai, Onge, and Mixe, a set of populations with largely phylogenetically distinct positions relative to the mixing populations in our applications: Papuan, deeply Papuan-related, western Eurasian, East Asian, deep eastern Eurasian, and Native American, respectively. e4 Current Biology 30, 4846–4856.e1–e6, December 21, 2020 Article ll If a given model fits poorly (i.e., low p value), that implies that it is poorly specified, in the sense that not all of the ancestry in the test population is more closely related to the proxy sources than to the outgroups. In other words, either the test population shares some ancestry with one or more of the outgroups more closely than with the specified proxy sources, or one of the proxy sources shares ancestry with one or more of the outgroups more closely than with the test population. To search for possible sex-biased admixture, we compared mixture proportion estimates on the autosomes and the X chromosome, computing a quasi-Z-score by dividing the difference by the standard error for the X estimate (which is much larger than the autosomal standard error). To maximize coverage on the X chromosome, we did not apply the two SNP exclusion criteria described in the ‘Dataset construction’ subsection above (which should have a negligible effect on mixture proportion estimates in the units of ratios of f-statistics). When computing FRO and Papuan ancestry proportions, we used Baining as the proxy for Papuan-related ancestry and corrected the estimates for the fact that Baining themselves have ~5% FRO ancestry. We also tested the compatibility of multiple populations with having common sources of admixture without a formal model, using qpWave [27]. Our test set for ancient Vanuatu plus other Oceanian populations consisted of present-day Tongan (6 individuals) and Melamela (9), plus the following ancient Vanuatu groupings: Efate 150-400 BP (5), Efate ~600 BP (1), Efate ~2400 BP (2), Epi ~150 BP (2), Epi ~1300 BP (2), Futuna ~1100 BP (4), Malakula 2000-2500 BP (6), Tanna ~150 and ~2500 BP (2), Mangaas (2), and Eretok (3). For present-day Vanuatu, we used all population groups in our dataset. In both analyses, our outgroup set was the same as for qpAdm, either with or without Nasioi. As in qpAdm, a higher p value indicates a better fit for the proposed model, where a rank of k implies k+1 distinct ancestry sources combining to form the test set of populations. Dates of admixture We estimated dates of admixture using MALDER [22] and DATES [23]. MALDER extends the linkage disequilibrium (LD)-based model of ALDER [70] by integrating information from multiple reference populations and searching for evidence of multiple waves of admixture. We used all ~590k autosomal Human Origins SNPs, and our reference set consisted of New Guinea Highlanders, Papuan, Australian, Baining (both subgroups), Teouma, Talasiu, Kankanaey, Ami, and CDX (1000 Genomes Dai). DATES implements a regression-based ancestry covariance estimate that can be applied to single individuals. We used all ~1.15 million autosomal SNPs from our capture set, and our reference pair was Papuan [69] and CDX [68]. For both methods, we assumed an average generation interval of 28 years when converting results to years in the past and estimated standard errors by block jackknife. f4 regression analysis We used a linear regression-based method to test for asymmetrical allele-sharing in cases where the f4-statistics of interest are confounded by differential ancestry proportions across the test population set. Instead of searching directly for non-zero values, we plotted pairs of f4-statistics in which the dependent variable is the statistic of interest and the independent variable is a statistic (f4(X, New Guinea Highlanders; Kankanaey, Australian)) measuring levels of Papuan ancestry. This approach is based on the linearity of f4-statistics for a collection of test populations (‘X’) with mixtures of ancestry related to the same two source populations but in different proportions (see below for derivation). If some test populations violate the proposed two-way model, they will tend to deviate from the expected linear relationship between the dependent and independent variables. We computed the f4-statistics in ADMIXTOOLS [37], with standard errors estimated by block jackknife. This approach is in some ways similar to the f4-biplots introduced in ref. [20], but the scenarios of interest and the interpretations of the results are different. Taking the example of Figure 4B, suppose we had a collection of populations, each of whose ancestry is a mixture from the same two sources, P and F, but in different proportions. Let A = f4(P, New Guinea Highlanders; Kankanaey, Australian), B = f4(F, New Guinea Highlanders; Kankanaey, Australian), C = f4(P, Tolai; Kankanaey, Tongan), and D = f4(F, Tolai; Kankanaey, Tongan). If one of our test populations, X, has a proportion a of P-related ancestry and (1-a) of F-related ancestry, then (in expectation) f4(X, New Guinea Highlanders; Kankanaey, Australian) = a*A + (1-a)*B = a*(A-B) + B, and f4(X, Tolai; Kankanaey, Tongan) = a*C + (1-a)*D = a*(C-D) + D = [constant1]* f4(X, New Guinea Highlanders; Kankanaey, Australian) + [constant2] (where the first constant is (C-D)/(A-B) and the second is also a rational function of A, B, C, and D). Thus a pair of f4-statistics are expected to have a linear relationship under the assumption that the set of populations in the first position (with the other three positions fixed) have mixtures of ancestry from the same two sources. We performed linear regression via inverse-variance-weighted least-squares. Given the resulting best-fit equation f4(2) = m*f4 (1) + b, we evaluated the deviation of each population by calculating its empirical value of f4(2) - m*f4 (1) - b, assessing the statistical significance by a Z-test (estimating the standard error on the value directly with a block jackknife). In most cases, we used one data point for each population group, except in cases of ancient populations with substantial heterogeneity (the distinction being accommodated naturally because of the weighting scheme). To maximize power given the relatively low-coverage data for the Lapita-period individuals, we computed the statistic f4(X, New Guinea Highlanders; Teouma, Talasiu) indirectly, via f4(X, New Guinea Highlanders; CDX, Talasiu) - f4(X, New Guinea Highlanders; CDX, Teouma) (including non-overlapping SNPs), with a block jackknife to estimate the standard error. When computing deviations from the regression line for this statistic, we then used the raw standard error rather than the full residual described above; empirically, this likely results in slight underestimates of the standard error (although this is conservative, in the sense that we observe only minor deviations for this test). Current Biology 30, 4846–4856.e1–e6, December 21, 2020 e5 ll Article We note that the choice of comparison population in the second position (e.g., New Guinea in the previous paragraph) only serves to shift all statistic values up or down a constant amount, because f4(X, Pop1; Y, Z) - f4(X, Pop2; Y, Z) = f4(Pop2, Pop1; Y, Z), which is a constant for all X. For Polynesian-related ancestry tests, to improve power, we used Tolai in the second position because (a) it is the Oceanian population with the largest sample size in our dataset, (b) it has an intermediate proportion of FRO ancestry, and (c) we were not specifically interested in the history of Tolai as a test population in these analyses. When testing for specific relatedness to the Eretok and Mangaas individuals, we used the statistics f4(X, Tolai; Eretok/Mangaas individual, Futuna ~1100 BP) for each individual in turn. We used the set of four ancient individuals from Futuna [5] in the fourth position rather than a present-day group in order to prevent artificial signals of allele-sharing when X is ancient. Admixture graph fitting We built our admixture graph using the qpGraph software in ADMIXTOOLS [37], with 13 populations included: Mixe (from Mexico) and Australian as outgroups; Atayal and Kankanaey (FRO-related); New Guinea Highlanders; Nasioi (Solomon Islands); Baining (Marabu subgroup) and Melamela (New Britain); Tongan; and four groups or individuals from Vanuatu – Eretok and Mangaas, ~600 BP Efate (I5259) [6], present-day Futuna, and present-day Tanna. We specified the options ‘outpop: NULL’, ‘lambdascale: 1’, and ‘diag: 0.0001.’ For a model of this size, the space of possible topologies is extremely large, so we cannot conclude that our final graph is the unique one that provides a good fit to the data. Instead, we use it in conjunction with our other analyses to investigate which results are supported when modeling the relationships among many populations simultaneously and to discover any additional admixture events necessary to obtain a good fit. e6 Current Biology 30, 4846–4856.e1–e6, December 21, 2020