Supplementary Materials for - Science · 2018. 5. 30. · the clothing of the deceased, a dog skull, a small scissors, and an iron spike. All, except the iron spike, have known cultural

www.sciencemag.org/content/360/6392/1024/suppl/DC1

Supplementary Materials for

Ancient human parallel lineages within North America contributed to a coastal

expansion

C. L. Scheib,* Hongjie Li, Tariq Desai, Vivian Link, Christopher Kendall, Genevieve Dewar, Peter William Griffith, Alexander Mörseburg, John R. Johnson, Amiee Potter, Susan L. Kerr, Phillip Endicott, John Lindo, Marc Haber, Yali Xue, Chris Tyler-Smith, Manjinder S. Sandhu,

Joseph G. Lorenz, Tori D. Randall, Zuzana Faltyskova, Luca Pagani, Petr Danecek, Tamsin C. O’Connell, Patricia Martz, Alan S. Boraas, Brian F. Byrd, Alan Leventhal,

Rosemary Cambra, Ronald Williamson, Louis Lesage, Brian Holguin, Ernestine Ygnacio-De Soto, JohnTommy Rosas, Mait Metspalu, Jay T. Stock, Andrea Manica, Aylwyn Scally, Daniel Wegmann,

Ripan S. Malhi,* Toomas Kivisild*

*Corresponding author. Email: [email protected] (C.L.S.); [email protected] (T.K.); [email protected] (R.S.M.)

Published 1 June 2018, Science 360, 1024 (2018) DOI: 10.1126/science.aar6851

This PDF file includes:

Supplementary Text

Figs. S1 to S14

Tables S1 to S12

Captions for data S1 to S4

References

Other supplementary material for this manuscript includes: Data S1 to S3 (Excel format)

Data S4 (zipped archive): Damage plots

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S1: Ethics Statement, Archaeological Background and Sampling

Ethics Statements

The Kenaitze Tribe A representative of the Kenaitze Tribe contacted RSM to conduct paleogenomics

research on historic ancestral remains. Prior to beginning the research, both the Kenaitze Tribe and the Malhi Molecular Anthropology Lab (MMAL) signed an MOU that defined the project and partnership and the expectations of each group. RSM visits the community regularly and works with community members from the tribe to address questions of interest to the community and the MMAL. Members of the Kenaitze Tribe have seen and contributed to the final version of the manuscript of this study.

Muwekma Ohlone Tribe

Prior to beginning paleogenomics research with the Muwekma Ohlone Tribe, two tribal members attend the Summer Internship for Indigenous peoples in Genomics (SING) workshop in 2011 and 2013. In 2016, prior to excavation of archaeological site Síi Túupentak (ALA-565/H) by Far Western, the Muwekma Ohlone recommended detailed analysis of all ancestral remains encountered. Subsequently, the Muwekma Ohlone tribal leadership approved paleogenomics analysis and partnered with the MMAL to conduct this research. The MMAL continues to conduct paleogenomic research for the tribe and has discussed the genomic results of the ancestral individual from designated Burial 1 with the Muwekma Ohlone and Far Western. Members of the Muwekma Ohlone have seen and contributed to the final version of the manuscript of this study.

Huron-Wendat Tribe

A representative from the Huron-Wendat and an archaeologist from Archaeological Servies Inc. contacted RSM about conducting paleogenomic analysis on ancestral remains from the Huron-Wendat Nation. After extensive discussion, ancestral remains were sent to the MMAL for analysis. Following analysis, RSM contacted the archaeologist (RW) and LL from the Huron-Wendat to discuss the results. A representative of the The Huron-Wendat has seen and given the opportunity to contribute to the final version of the manuscript of this study.

Lucier Site

With support of First Nations, remains from the Lucier site were provided to G.D. with permission from the University of Toronto Tri-council ethics committee (reference# 31707) in order to identify the descendant cultural/language affiliation of this prehistoric population.

Museum remains from Baja California (Mexico), California Channel Islands, Point Sal, and Pennsylvania

At the time of experimental work all human remains from United States museum collections included in this study were officially categorized as culturally unaffiliated by the museums in which they were housed. They were thus sampled with permission for destructive analysis granted by the curator(s) and/or loan committee of the respective

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institutions. In the time between the start of the project and the submission of this manuscript, the status of some of these remains changed to culturally affiliated or claims were submitted by multiple tribes. C.L.S. contacted the San Diego Museum of Man and was referred by the museum to a contact on the Kumeyaay Cultural Repatriation Committee (KCRC). C.L.S. arranged a meeting with KCRC representatives and met with them in April 2017 to share results of this study and ask for feedback. C.L.S. also gave a publicly advertised talk at the Santa Barbara Museum of Natural History at which the audience was composed primarily of Chumash descendants. Through other contacts, C.L.S. arranged a meeting in January 2018 with JohnTommy Rosas (Tongva) and a separate meeting with members of the six Luiseño bands, shared results of this study with them, and asked for feedback. C.L.S. gave another publicly advertised talk at the Santa Barbara Museum of Natural History on the results of this study at which the audience consisted mainly of members of the Santa Ynez Chumash Elders Council and other Chumash descendants. Some members of the communities mentioned have consented to collaborate on this and future work. Those members have seen multiple versions, including the final, of this manuscript and their comments/feedback has been incorporated.

In the case where ancient individuals were categorized as culturally unidentifiable by the museum at the time of writing this manuscript, C.L.S. contacted tribes historically from the region in which the remains were excavated by email, letter, and by phone to inform them that (an) individual(s) who may be related to their tribe had been radiocarbon dated and tested for ancient DNA and isotopes. Only ancient individuals for whom there was at least one potentially affiliated tribe that consented to collaborate and supported the project were included in this manuscript.

Modern DNA

Informed consent was obtained for the sequencing of mitochondrial DNA from modern individuals (J.R.J). SNP chip genotype data for present-day individuals in the (Reich et al. 2012) and (Moreno-Estrada et al. 2014) datasets are available only for demographic research under data access agreement with T.K. and C.L.S.

Description of archaeological sites Alaska

The Palm Site, 49-KEN-523, is an early 19th century Dena’ina Athabaskan (Dené) cemetery located on a remote eroding Cook Inlet beach 36km north of Kenai, Alaska. The Kenai-based Kenaitze Indian Tribe authorized Alan S. Boraas (A.S.B) to remove and describe human remains and associated artifacts before reburial at a geologically stable site. The tribal council approved DNA sample extractions and a MOU between the Malhi Molecular Anthropology Lab (MMAL) and the tribe established mutual expectations and sample handling protocols for paleogenomic research.

Three sets of human remains eroded or partially eroded from the 4m high bluff. The customary practice of pre-contact Dena’ina was to cremate their dead followed by a memorial potlatch several years later. As a result of mid-nineteenth century Russian Orthodox missionary activities, funerary practices shifted from cremation to casket

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inhumation in consecrated Orthodox cemeteries. The eroding burials at the Palm Site are inhumations in shallow (~50cm-1m below surface) wooden caskets not at an Orthodox cemetery and represent an intermediary practice of relatively short time duration.

Grave goods include numerous glass beads of European origin, no doubt sewn onto the clothing of the deceased, a dog skull, a small scissors, and an iron spike. All, except the iron spike, have known cultural symbolic significance. The historic items, and the unique mode of burial (neither cremation nor Orthodox burial) suggest an early 19th century date. During that time the Dena’ina were beset by numerous epidemics of introduced contagious diseases the most devastating of which was the 1838-40 smallpox epidemic during which up to half of the Kenai Dena’ina died. The cemetery is possibly associated with one or more of those epidemics necessitating rapid burial. Culturally, the individuals from the Palm Site are associated with Dena’ina Athabascan. San Francisco Bay Area

Síi Túupentak (ALA-565/H) is a large, intensively occupied Late Period (i.e. post cal BP 685/AD 1265) ancestral Native American Ohlone village with an associated cemetery situated along Alameda Creek in the southeastern San Francisco Bay area. Recent excavations by Far Western and the Muwekma Ohlone at the site have recovered a series of primary inhumations as well as secondary cremations, many of which have mortuary offerings.

Fifteen radiocarbon dates on human collagen from ten individuals were calibrated with a mixed marine curve based on established protocols using individual d15N values (maximum contribution of marine foods to the diet varied from 10%-16%). Median intercepts for the age of death of these individuals ranged from 501-131 years cal BP (AD 1449-1819). Half (n=5) of the individuals date to the AD 1600s: median intercepts from 313-273 cal BP (AD 1637-1677) and two sigma standard deviations from 332-266 cal BP (AD 1618-1684).

Burial 1 is a primary inhumation of an older female whose estimated age is greater than 50. There are three dates from Burial 1, with D-AMS 018555 on human bone collagen yielding a median intercept for the age of death of 273 cal BP (AD 1677), and a two standard deviation range of 309-266 cal BP (AD 1641-1684). The dates on the M1 and M3 teeth are older, consistent with expectations. California Channel Islands By Patricia Martz

Isotopic data indicate that the San Nicolas Island diet maintained a strong focus on marine resources and this did not vary appreciably throughout the 8,000 known years of occupation. In addition, relatively high instances of genetic markers, such as spina bifida, suggest that the San Nicolas islanders were relatively isolated from the mainland and possibly from the other islands. This in spite of evidence for two distinct populations through time (23-25).

The majority, if not all, of the human remains discussed in this article were excavated by Malcolm Rogers and Arthur Woodward in the 1930s, Phil Orr in the mid-1940s; and in 1959, Fred Reinman excavated several burials on the west end of the island that had been exposed by erosion (30-33). All sites provided evidence for substantial

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habitation and included extensive shell middens. Associated artifacts included Olivella shell, bone, and stone beads, fishhooks, net sinkers, abalone shell dishes, woven sea grass, steatite effigies, and flaked stone and bone tools.

C. L. Scheib:

Teeth and petrous bone were sampled from individuals excavated on the southern islands: San Clemente (n = 7), San Nicolas (n = 32) Santa Catalina (n = 2). The San Nicolas remains come from thirty-two sites on the island, thirty of which are considered substantial habitation sites. Most of the sites are found on the west end of the island, the only place with fresh water springs (25). Extracts from six additional teeth (San Miguel = 2, San Nicolas = 4) were sent the the aDNA lab in Cambridge from the Cessac collection at Le Musée de l’Homme by Phillip Endicott from (34). The DNA and AMS analyses from that thesis were funded through a grant from the US Navy for San Nicolas Island Research and sent to Oxford radiocarbon lab (34).

Point Sal

From the Point Sal site forty-seven individuals were excavated: male, female and child. Two samples were already radiocarbon dated by other researchers: 17809 was dated to AD 580-650 (Beta Analytic #159835 calibrated 68% probability) and 18130 was dated to AD 110-230 (Beta Analytic #159837 calibrated 68% probability). Sample 17809 is contemporaneous with the three new radiocarbon dates. Sample 18130 is a few hundred years older, not found within the same locus, and was ornately dressed in a beaded headdress unlike the other samples. Unfortunately, no DNA was recovered from this sample.

The site was excavated at three stratums and the absence of scrapers and choppers at

all levels was noted as they occur in high frequency throughout the rest of Southern California (35). The burials were taken from stratum III in which was found a number of Santa Barbara typed projectile points and no evidence of mano or metate (highly prevalent in Southern California sites). The burials themselves were considered unusual as they were seated with instances of mandible removal and foramen magnum enlargement as well as undisturbed burials that were incomplete. Graves contained sacrifices of beads, bowls, knives, baskets, and in one case an eagle skeleton. Carter infers that these unusual burial traits could be of a northern origin, specifically the seated burial, mutilation, and hand-held sacrifice.

The cranial morphology links them to the Northern Channel Islands and steatite

from Santa Catalina Island was found in stratum III indicating trade with the Southern Channel Islands. No fish hooks were found, which is notable given the difference in diet relative to other Channel Islanders: isotopic data indicate that Point Sal individuals consumed a mixed diet, with a high intake of terrestrial resources, and a lower level of marine resource exploitation (Table S2) (15).

Southwestern Ontario Teston and Turnbull Ossuaries

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The Teston Road ossuary is situated about 30 kilometers north of Toronto in Vaughan, Ontario, in the midst of the ancestral lands of the Wendat. It contains the commingled remains of several hundred individuals, a secondary burial pattern distinctive to the Wendat. It is associated with a 1 hectare unpalisaded village dating to the fifteenth century (36).

The Turnbull ossuary is situated on the west shore of Lake Couchiching in the

City of Orillia within Wendake, the historic homeland of the Wendat confederacy. The ossuary contains the commingled remains of several hundred individuals and dates to the fifteenth century (36).

Both of these ossuaries were uncovered during land disturbing activities and

through engagement with the Wendat nation were protected by the respective municipalities from further disturbance. Teeth were sampled from both ossuaries with the written permission of the Wendat nation to undertake aDNA and dietary isotopic analyses. La Salle-Lucier, Western Basin, Ontario

The Lucier Mortuary site (AbHs-1) is a Western Basin Tradition (WBT) cemetery located in the City of Windsor, Southwestern Ontario, Canada. This large property has produced numerous human burials primarily from the Springwell’s phase (1200 to 1450 AD) with the exception of one individual who is dated to ~4.2 ka BP (Table S2) (15). Individuals are buried in single and multiple grave pits with little to no evidence for domestic remains. There are different internment styles including primary extended, primary flexed, torso burials, secondary burials, and cremations. Of interest is the occurrence of post-mortem modifications on some individuals including both sexes and all ages, typical of the WBT (37,38). The site was excavated numerous times over many years as the city expanded but the individuals from this study were exhumed by Wintemberg in 1935 (39). With permission from the University of Toronto Tri-council ethics committee (reference# 31707) in order to identify the descendant cultural/language affiliation of this prehistoric population, we sampled fourteen individuals for aDNA.

Remains from the American Museum of Natural History

Culturally unidentifiable individuals were selected for destructive sampling based on geographical provenience and availability of loose teeth or disarticulated cranial remains. The context of the individuals is scarce and restricted to what was written in the catalogue available for viewing by request to the museum curator(s). Individual US-14 (DNA analysis showed this individual to be entirely of European descent) was found at Shohola Creek, Indian Cabin Ridge, Pennsylvania, and donated to the museum in the 1960s.

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S2: Radiocarbon dating, calibration, marine reservoir correction and stable isotope analysis

AMS Radiocarbon Dating Previously radiocarbon dated individuals were prioritized for ancient DNA analysis

(n = 6) and an additional twenty-one were sent for direct radiocarbon dating on ultra-filtrated tooth and bone collagen to Oxford University and Queens University Belfast (Table S2)(15). Collagen was generally well preserved (mean collagen yield = 16.3%, atomic C:N ratio mean of 3.2). The University of Toronto samples (n=4) were sent to DirectAMS Radiocarbon Dating Services and dental collagen was generally well preserved (C:N elemental mean ratio of 3.4) (Table S2)(15). The Carpinteria and New Cuyama samples were dated with Beta Analytic (Table S2)(15).

Calibration of radiocarbon dates

To correctly calibrate the radiocarbon dates of the human remains, we used the 2017 build of OxCal 4.3 (40). For individuals with stable isotope signals indicating a terrestrial protein diet we used the calibration curve IntCal13 (18). For individuals with a mixed marine and terrestrial protein signal, we first calculated the proportion of marine protein in the diet following (41) using observed endpoint values from North America. The value approaching a 100% terrestrial diet is ∂13C = -23.7 ‰ from Ontario, Canada and the value approaching a 100% marine diet is ∂13C = -10.0 ‰ from San Nicolas Island (42). The calculated %marine value ± 10 % was used to mix the terrestrial and marine calibration curves in OxCal (43). The marine calibration curve is Marine13 (18) with a regionally specific ΔR average of 217 ± 129 14C years for southern California (44), a ΔR average of 285±35 for the southeastern San Francisco Bay area. This significantly improves the accuracy of temporal estimates.

Stable Isotopes and dietary reconstruction

Stable isotope measurements (δ13C and δ15N) retrieved from dated individuals indicate a variety of dietary signatures directly related to the environment of each population (Table S2) (15). All the individuals from island locations in California show a strong input of marine resources (45), a pattern that has been observed in previous work on Channel Island individuals (42,46-47). The individuals from Point Sal show a mixed terrestrial/marine intake consistent with the tool assemblages found at the site (35).

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S3: DNA extraction and sequencing

Sample decontamination and extraction

In Cambridge Root portions of teeth were removed with a sterile drill wheel. These root portions

were briefly brushed to remove surface dirt, any varnish or lacquer, and microbial film with full strength household bleach (5% w/v NaOCl) using a UV-irradiated toothbrush that was soaked in 5% (w/v) bleach for at least one minute between samples. Roots were then soaked in 6% (w/v) bleach for 5-15 minutes. Samples were rinsed twice with 18.2MΩ.cm H2O and soaked in 70% (v/v) Ethanol for 2 minutes, transferred to a clean paper towel on a rack inside the glove box with the UV on for 50 minutes on each side, and then allowed to dry. They were weighed and transferred to clean, UV-irradiated 5 ml eppendorf tubes or 15 ml conical tubes for chemical extraction. Per 100 mg of each sample, 2 ml of 0.5M EDTA Buffer pH 8.0 (Fluka) and 50 µl of Proteinase K 10 mg/ml (Sigma Aldrich) was added. Tubes were rocked in an incubator for 72 hours at room temperature. Extracts were concentrated to 250 µl using Amplicon Ultra-15 concentrators with a 30 kDa filter (Millipore). Samples were purified according to manufacturer’s instructions using the MineluteTM PCR Purification Kit (Qiagen) with the only change that samples were incubated with 50 µl Elution Buffer (Qiagen) at 37C for 10 minutes prior to elution.

At University of Illinois

DNA extractions of ALA-565H-1, Palm site 523a, 05SP-46, 11SP-83 and New Cuyama were completed in an ancient DNA laboratory facility at the Carl R. Woese Institute for Genomic Biology at the University of Illinois. Surface contamination from the tooth or bone was removed by submerging it in 6% sodium hypochlorite (full strength Clorox bleach) for 6 minutes. The bleach was removed and the samples was then rinsed twice with DNA-free ddH2O and once with isopropanol to remove any remaining bleach.

The sample was then placed in a UV cross linker until dry. Approximately 0.20 grams of tooth or bone powder was obtained using a Dremel tool at low speeds to minimize the production of heat. The powder was then incubated in 4 ml of demineralization/lysis buffer (0.5 M EDTA, 33.3 mg/ml Proteinase K, 10% N-lauryl sarcosine) for 12-24 hours at 37°C. The digested sample was then concentrated to approximately 100 µl using Amicon centrifugal filter units. Following concentration, the digests was run through silica columns using the Qiagen PCR Purification Kit and eluted in 60 µl volume of DNA extract.

Preliminary screening for mtDNA All samples were quantified with the SensiMixTM SYBR® No-ROX Kit on the

CFX Connect (Bio-Rad) located in the Cambridge Department of Biochemistry Biophysics Facility. Since aDNA is often fragmented into lengths less than 200 bp (48) primers targeting a 109 bp region of the D-loop region of the human mitochondrial genome (16077 - 16186) were used. PCR prep was completed in the PCR prep room in

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the aDNA laboratory and standards added to closed plates in the post-pcr lab. All steps were performed in a flow hood with positive pressure. Samples and standards were quantified in triplicate.

In the post-PCR lab, standards were prepared from a PCR product of a 414 bp

section of the Hypervariable region of human mtDNA of a modern sample. This product was quantified using the Quant-iTTM PicoGreen® dsDNA kit (P7589, InvitrogenTM Life Technologies) on the SynergyTM HT Multi-Mode Microplate Reader with Gen5TM software. The cycling was set to: 10 minute hold at 95C, 40 cycles of 95C, 56C, 72C, followed by a standard curve created by the software using default settings. Samples that showed on average a presence of at least 101 molecules per microliter were selected for shotgun sequencing.

Double-stranded library preparation In Cambridge

Library preparation was conducted using a protocol modified from the manufacturer’s instructions included in the NEBNext® Library Preparation Kit for 454 (E6070S, New England Biolabs, Ipswich, MA) as detailed in (9). DNA was not fragmented and reactions were scaled to half volume, adaptors were made as described in (49) and used in a final concentration of 2.5uM each. DNA was purified on MinElute columns (Qiagen, Germany). Libraries were amplified using the following PCR set up: 50µl DNA library, 1X PCR buffer, 2.5mM MgCl2, 1 mg/ml BSA, 0.2µM inPE1.0, 0.2mM dNTP each, 0.1U/µl HGS Taq Diamond and 0.2µM indexing primer. Cycling conditions were: 5’ at 94C, followed by 18 cycles of 30 seconds each at 94C, 60C, and 68C, with a final extension of 7 minutes at 72C. Amplified products were purified using MinElute columns and eluted in 35 µl EB (Qiagen, Germany). Samples were quantified using Quant-iT™ PicoGreen® dsDNA kit (P7589, Invitrogen™ Life Technologies) on the Synergy™ HT Multi-Mode Microplate Reader with Gen5™ software.

At University of Illinois

Approximately 50 µl of DNA extract was used to create a genomic library with adapters that contained a unique index for each library. Genomic libraries were created using the NEB Ultra DNA Library Kit. The DNA extract was not sheared as the DNA is expected to be fragmented due to taphonomic processes. A 1:20 dilution of adapters was used, as the DNA concentration in the extract is presumably low. Multiple Ampure Bead XP clean ups were completed in an attempt to remove adapter-dimers that may have developed. A PCR amplification of genomic libraries was prepared in the ancient DNA laboratory and then transported to thermocyclers in the contemporary laboratory, across campus, in a sealed environment. The genomic libraries were amplified for 12 cycles, and was then cleaned with the Qiagen MinElute Purification Kit. The quality of the libraries was assessed on the Agilent 2100 Bioanalyzer using the High Sensitivity DNA kit and sequenced on HiSeq 4000.

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Target Capture of mtDNA A target capture of mtDNA following (50,51) was used to isolate whole mtDNA

sequences from the modern California individuals previously sequenced at the hypervariable region (JJ samples, J.R.J). In short, modern human mtDNA was sheared into roughly 500 bp lengths, biotinylated, and attached to Streptavidin-coated magnetic beads (Dynabeads® M-270 Streptavidin, Life Technologies). Amplified, indexed aDNA was added to the magnetic beads and incubated at 65C for 48 hours under constant rotation. Target DNA was released from the bait molecules, visualized on a 2% agarose gel, and quantified using the Quant-iT™ PicoGreen® dsDNA kit (P7589, Invitrogen™ Life Technologies) on the Synergy™ HT Multi-Mode Microplate Reader with Gen5™ software before sequencing.

Sequencing In Cambridge

Samples were pooled in equimolar amounts with a total concentration of 30 nmol/µl and sequenced on Illumina technology at the University of Cambridge Biochemistry DNA Sequencing Facility. The modern target-enriched mtDNA samples were sequenced on the Illumina MiSeq 150-cycle kit V3 single-end. All other samples were sequenced on the NextSeq 500.75-cycle kit single end. Fastq files were downloaded from Illumina BaseSpace and analyzed on the Estonian Biocenter server.

At the University of Illinois

Samples were sequenced on the HiSeq4000 100-cycle kit single-end.

Mapping and Genotyping Sequences were returned from the University of Cambridge Department of

Biochemistry DNA Sequencing Facility in the form of four compressed FASTA.GZ file per sample. Adapters were removed using CutAdapt (52). Three base pairs were removed from the 5’ and 3’ ends of all reads prior to alignment.

Trimmed reads were mapped to hg19 build 37.1 as well as the rCRS in a separate

file using bwa v0.6.1 (53). Files were converted to the BAM format for use with SAMTools v1.19 (54). Duplicate reads were removed using Picard Tools MarkDuplicates (http://broadinstitute.github.io/picard).

Bams were called at SNP sites within the Reich et al. (2012) Native American chip

dataset using ANGSD (55) --haplocall 1 option, which picks a random read from the set of input locations. The output was converted to plink tped format using ANGSD and merged with the comparative dataset using Plink – 1.9 (55).

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S4: Authenticity of results

Damage patterns Damage patterns of non-trimmed bam files were analyzed by MapDamage2.0 (57).

The rate of > 10% C to T transitions in the ends of 5’ to 3’ reads and G to A in the 3’ to 5’ reads matches what an expected ancient DNA pattern shown in previously published works. The distribution of fragment lengths less than 200 bp is also consistent with the degradation of DNA over time (48). In many cases there are a great number of reads greater than 75 bp, but this pattern could be related to the inefficiency of the purification process in retaining short fragments or the duplicate removal step which is designed to keep the longest fragments.

Contamination Estimates The contamination rates were estimated using two different methods, both based on

the same principle that known polymorphic sites on haploid genomes and their adjacent sites should have the same error rate unless some human contamination is present. Thus, in its simplest form, the mismatch rate in adjacent sites can be subtracted from known polymorphic sites to estimate the contamination rate. Rates of contamination were estimated on mitochondrial DNA by calculating the percentage of non-consensus bases at haplogroup-defining positions as detailed in (58). Each sample was mapped against the RSRS downloaded from phylotree.org and checked against haplogroup-defining sites for the sample-specific haplogroup.

For estimation on autosomal data using the same theoretical concept (for male

samples with over 0.5X coverage) ANGSD has a contamination analysis module for the X-chromosome based on a maximum likelihood method as detailed in (59). It generates a moment-based estimate of the error rate and a Bayesian-based estimate of the posterior probability of the contamination rate. Polymorphic sites were identified in the HapMap CEPH (60) individuals and the mismatch rate at these sites was compared to the mismatch rates at adjoining sites. Two test methods were employed, the first assumes independent error rates both within and between sites (test1) and the second uses only a single randomly sampled read (test2). The second test would theoretically be affected by low-coverage, damaged data and below an average nuclear coverage of 0.5X, the concordance rate of the two tests does decrease. In male samples both methods were compared and the two methods resulted in similar estimates.

All samples had generally low contamination rates (< 6.18%, mean 0.91%, all individuals over 2% were excluded from downstream analysis) (Table S1, Table S3 – S4) (15).

Error rate estimation Error rates were estimated using the second available ANGSD method which uses

an outgroup (Chimp) and an “error free” individual, in this case a high coverage, high quality CEU individual downloaded from the ANGSD github repository. The method is

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covered in detail in (61). We followed default parameters listed at http://www.popgen.dk/angsd/index.php/Error_estimation.

Checking effect of damage and read length To check if excessive damage at the terminal ends of reads was affecting results, we

trimmed 10 base pairs from the 5’ and 3’ ends of all reads for each Early San Nicolas individual and ran a PCA (Figure S7) (15). We also checked whether inadequate adapter removal might affect results and used CutAdapt (52) to aggressively trim Illumina Universal adapters with high mismatch rates up to 50% in the Early San Nicolas and included this set in the PCA (Figure S7) (15). Both sets produced similar results to the original pipeline indicating that neither excessive terminal damage nor missed partial adapter sequences have a detectable effect on SNP chip overlap results. Additionally, we ran a PCA using transversions only by converting all Ts to Cs and As to Gs (Figure S8) (15) and found that all ancient Native Americans still clustered with modern Native Americans.

Molecular sex determination The sex of samples was determined using a script by Pontus Skoglund available by

download online (62). This script makes use of the ratio of reads mapping to the X and Y chromosomes. It was run with default settings as suggested by Skoglund in the documentation. Results are either returned a definitive XX or XY, "consistent with XX but not XY" and vice versa, or "Not Assigned." In most cases the genetic sex was consistent with the biologically-inferred sex of the individual.

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S5: Uniparental Marker analyses

Mitochondrial haplogroups Raw reads were mapped to the revised Cambridge Reference Sequence (63) and

resulting bam files were indexed for viewing in Tablet v1.13.04.22 (64). Variants were called using SAMtools v 1.3 mpileup variant-only option and filtered using bcftools v 1.1 (54). Haplogroups were assigned using Phylotree build 16 (65) accessed at www.phylotree.org, Haplogrep (66,67) accessed at https://haplogrep.uibk.ac.at, and Haplofind (68) accessed at www.haplofind.unibo.it.

Y-chromosome haplogroups Y chromosome variants were called in ANGSD and filtered for regions that

uniquely map to Y chromosome when using short read sequencing technology. A number of Y chromosome filters have been defined previously on the basis of different sequencing approaches (69, 70, 71). The analyses in this work are based on the filters reported by (71) that retain 8.8 Mb of Y chromosome sequence and were initially used to adapt with the data generated with Complete Genomics (CG) platform. The rationale behind this choice is that CG reads are shorter and thus provide us more conservative set of uniquely mappable regions for the use of ancient DNA data than would filters based on Illumina technology. The data for 8.8 Mb accessible Y chromosome regions for the 34 male samples were merged and preliminary haplogroup assignments were made on the basis of in silico genotyping of the samples for 42,385 informative variants reported by (71). The general haplogroup affiliation of all 34 aDNA samples whose Y chromosome coverage was higher than 0.05x could be determined. For getting more detailed resolution of haplogroup Q additional whole Y chromosome sequence data sets (69,70) together with informative markers from the ISOGG data base (http://isogg.org/tree/) and relevant ancient DNA sequences from the Americas, including the Saqqaq, Anzick-1 and Kennewick Man were used to define the list of informative subclade defining SNPs in the phylogeny of haplogroup Q. These markers were further in silico genotyped in the ancient DNA samples reported to yield a synthetic tree that combines modern and ancient sequence data.

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S6: Nuclear DNA-based analyses

Compilation of comparative datasets There are two factors necessary for informative comparative analysis 1) a high

number of diverse comparative populations and 2) a high number of SNP sites that are informative within the region of interest. The Americas complicates the first (there is a limited number of comparative Native American populations without post-colonial admixture) and the nature of ancient DNA complicates the second (low coverage/missing data). For this study we used two different datasets, one that maximized the number of comparative populations (134 pops, ~180k snps) and was used for initial data exploration, f3 and D statistics: the complete unmasked data from (7) (except Algonquin, Cree, Ojibwa, and Chippewyan due to excessive European admixture—instead we used the masked data for these populations), merged with the Mexican SNP panels (72), North Americans from (14), HGDP (73, 72), HapMap (60), and Loschbour, Ust_Ishim, Stuttgart, and Kostenki14 from (75). The first and second-degree relatives were removed using KING analysis of the same dataset published in (13). Additionally, the Huichol (72), Yukpa (76), Aymara (7), Mexican (60), and Maya (73) populations were removed as well as any non-European samples that contained over 0.1% European and/or African admixture as determined by ADMIXTURE analysis at K=3 to be consistent with methods used in (7,14). The resulting dataset contained 1,674 individuals. The 91 ancient DNA samples were called at the overlapping SNP sites suing ANGSD and merged using Plink-1.9 (56).

The second dataset maximized the number of overlapping snps (70 pops, ~350k

snps) with Native American populations and was used for qpGraph analysis, Principal Component Analysis, f3 and D statistics: masked data from (7) with all Siberian and Native American populations plus French, Han, Mbuti_Pygmies, Papuans, and Melanesians (73, 74). The resulting dataset was filtered for SNP sites with a genotyping rate over 60% and contained 857 individuals and 352,972 SNPS. The 91 ancient DNA samples were called at the overlapping SNP sites suing ANGSD and merged using Plink-1.90 (56).

We added ancient genomes to both of these sets by downloading publicly available

bam files from (9,10, 11, 13, 77) and calling them at overlapping SNP sites using ANGSD --haplocall and converting to Plink for merging.

Principal Component Analysis Principle Component plots were generated using EIGENSOFT v 7.2.0 (18,78) with

the lsqproject: YES and autoshrink: YES options. Ancient samples were projected onto modern variation. The projection option is needed because ancient samples are low coverage and therefore contain a lot of missing data which, if used in the calculations, will overwhelm and skew the plot. The new autoshrink option helps to prevent this

15

distortion. We performed a worldwide PCA and a regional PCA including Native Americans and Siberians using the unmasked, unadmixed dataset and the masked dataset. In order to ensure that low coverage was not influencing our results, we down-sampled high coverage data to 0.05, 0.1, and 1x and re-ran analyses. Ultra-low coverage (< 1x) does increase the noise and uncertainty of an individual genome in the analysis, but when multiple ultra-low coverage genomes are in sufficient quantity or combined with medium and/or high coverage samples the results are consistent with high-coverage samples.

ADMIXTURE analysis After the initial QC in which the raw, unmasked worldwide panel was used to

determine individuals with European and/or African ancestry, the worldwide comparative dataset (including unmasked, unadmixed modern Native Americans and masked Algonquin, Cree, Ojibwa, and Chipewyan) was pruned for --maf 0.05 and –indep-pairwise 200 25 0.4 (~130k snps left after pruning) –geno 0.6 and –mind 0.98 (1674 individuals after filtering) using Plink v 1.9 and run through ADMIXTURE v 1.23 (19) in 100 independent runs with default settings plus --cv to identify the 5-fold cross-validation error at each k (1 through 16).

The optimal K was chosen by looking at the log likelihood difference (Figure S9) (15) and CV-index at all Ks (Figure S10) (15). Admixture output for all Ks is shown in Figure S11 (15). We also used a pared down dataset consisting of the Americas, Siberia, Asia and Oceania (823 individuals) for the main figure (Figure 1C).

f statistics All f statistics were calculated using EIGENSOFT v 7.2 and AdmixTools v 4.1

(18,78). Input populations consisted of at least three individuals except in the case of ancient genomes Anzick-1 and The Ancient One (Kennewick) or when we were testing the population affinity of individual ancient samples. Outgroup f3 was calculated in the form of f3(Test, Source1; Mbuti). Z scores greater than |3| were deemed as significant. Admixture f3s were calculated in the form of f3(Source1, Source2; Target), Z scores < -3 were deemed as significant. Values of Outgroup f3 are presented in Additional Data file S2 (15).

D statistics D-statistics were calculated using EIGENSOFT v 7.2 and AdmixTools v 4.1 (18,78)

and calculated in the form of D(Mbuti,Test;X,Y) Z-scores greater than |3| were deemed as significant. A list of results of all tests run are available in Additional Data file S2 (15).

We used D-statistics also to test whether individual San Nicolas individuals shared more derived alleles with the early or late population using D(Mbuti, Test; LSN, ESN) (Table S11)(15). The LSN and ESN populations in this case consisted only of radiocarbon dated individuals. All individuals segregated into ESN or LSN also by mtDNA haplotype except for SN-43, whom shared more derived alleles with the ESN, but has a C1b haplotype characteristic of the LSN population. This individual is the

16

oldest of the later population at ~2541 years BP (not calibrated) and may have lived close in time to the actual population admixture event(s).

Construction of tree using qpGraph We used the AdmixTools (18,78) program qpGraph (version 6.5) to fit demographic

models involving population splits and admixture events with data. We used qpGraph with default settings, Han Chinese as an outgroup, useallsnps=YES option, retaining 307,805 SNPs. We first searched for the best tree without admixture relating ancient Clovis, Northeast U.S., Californian (Early San Nicolas and Northern Channel Islands and Santa Barbara) populations with modern representatives of South (Surui) and Central (Pima) Americans. The tree without admixture (Figure S3) (15) had a poor fit with the data, including 14 f4-statistics with |Z| score >3 and the worst f2-statistic between Northern Channel Islands and Santa Barbara and Pima, Z = -4.94. We were able to improve significantly the fit with data when modelling ancient Californian and modern Central and South American populations through admixture of two basal ancestries. The model presented in Figure 2A represents a good fit with data, with no significant f4-statistics (the highest |Z| score for f4(ASO, Northern Channel Islands and Santa Barbara; Surui, Pima), Z=0.888) or f2-statistics (the highest |Z| score for f2(ASO, Pima), Z=0.311).

While the periglacial environments of North America (79-81) show 100% ANC-B ancestry, and, intriguingly, the SAM populations with the highest level of estimated ancestry from ANC-B are the Chilote and Huilliche (~70 %) on the coast of Chile overlapping the Monte Verde Pre-Clovis site (~18.5 – 14.5 kya) (Figure S12) (15), the oldest ancient population in this study (ESN, ~4.8 kya) on the west coast of North America have the highest affinity to Clovis of all ancient and modern populations. We are cautious about interpretation due to limited sample size and geography.

Similarly, in the Northern Hemisphere, the Northern Channel Islands show continuous occupation from at least 13 kya (16), while the earliest archaeological evidence of occupation of San Nicolas Island (ESN + LSN) is only ~8 kya (25). The Northern Channel Islands and Santa Barbara populations have a different relationship to CAM and SAM populations than ESN (Additional Data file S2) and show higher estimated percentages of ANC-B than the ESN (Figure 2B). This contribution can be rejected as caused by a direct, recent admixture from expanding Pima-related Uto-Aztecan speaking populations into the Northern Channel Islands and Santa Barbara (Figure S13) (15). It is generally recognized that the Southern Channel Islands draw their ancestry from the Uto-Aztecan speaking Tongva (or Gabrieleño); thus, ancient and additional modern Tongva (or Gabrieleño) genomes are needed to gain a more complete understanding of the biological/genetic history of this region.

Inference of local heterozygosity By Vivian Link & Daniel Wegmann To avoid biases introduced when estimating genetic diversity from called and filtered genotypes, we inferred local heterozygosity (θ=2Tµ) in 5Mb windows following a “reference free” approach described in (27) that also accounts for post-mortem damage

17

(PMD). We restricted our analysis to all ancient sample of this study with a genome-wide sequencing depth of > 0.2X after excluding read groups with < 0.1x. The samples were then treated as follows:

1. Splitting single end sequences by length Due to the generally short fragments in ancient DNA, most of the single-end sequences spanned the entire fragment. As a consequence, both ends of the reads were equally affected by PMD. However, the subset of reads matching the number of sequencing cycles used are likely from fragments larger than the read lengths, and hence their PMD patterns are expected to be different. We thus partitioned all single-end reads into two groups: group 1: shorter than number of cycles; group 2: length matches number of cycles.

2. Estimating Post-Mortem-Damage (PMD) Patterns We then inferred empirical PMD patterns as described in (26) independently for all read groups.

3. Base Quality Recalibration Next we recalibrated base qualities as described in (26) by fitting a logistic model to sites in ultraconserved elements as defined by (82) assumed to be monomorphic. The model was fit to each read group individually with the quality score provided by the Illumina sequencing machine, the position of the base within a read, the square of those two covariates, and the two-base context consisting of the preceding and focus base (20 contexts -A, -C, …, TT) as covariates and while accounting for PMD. Since the ultraconserved elements are spread throughout the genome we decided not to infer local base frequencies but to fix bases frequencies to ¼ for each base.

4. Inference of Heterozygosity We then inferred heterozygosity within 5-Mb windows using the method described in (26) that does account for PMD, does not require reference information nor a decision on minor or major alleles.

5. Filtering Windows For all samples, we excluded all windows closer than 5Mb to telomeres or centromeres as defined by the track Gap in group Mapping and Sequencing in the UCSC Table Browser. We also masked sites with sequencing depth > 95% of all sites in a given genome, or if this quantile was lower than 3x, we chose this cut-off. In addition, we excluded all windows in which less than 2% of all sites were covered by two or more reads as θ cannot be reliably estimated with less data. Since only sites covered twice or more contain information about heterozygosity, there are at least 105 informative sites in windows that passed out filter. At a low θ of 10-4, only ten of those are expected to be heterozygous, of which only five are observable at a depth of two (in half of the cases the two reads are expected to cover the same allele). We also note that with this filter, any θ<10-5 is impossible to be distinguished from zero. Three samples (NC-C, 523-Ac, and US-14) showed a high percentage of windows with unreliable estimates (>10%) and were excluded.

18

Comparisons with Existing Samples We compared the inferred heterozygosity of the samples presented in this study (Figure S3) to previously reported samples. In order to ensure bias-free comparisons, we obtained raw bam files for all of those and processed them exactly as described above and along the samples presented in this study. We included the following published samples: Two ancient foragers from Europe:

1. Kotias (KK1): Mesolithic forager from Georgia (83) 2. Bichon: upper Palaeolithic forager from Switzerland (83)

Two early European farmers: 1. WC1: early Neolithic farmer from the Wezmeh Cave, Zagros Mountains, Iran

(84) 2. BR2: Ludas-Varjú-dúló, Late Bronze Age individual from Hungary (85)

Several contemporary samples from the Simons Genome Diversity Project (27): 1. LP6005443-DNA_A06, S_Greek-2 2. LP6005442-DNA_G07, S_Greek-1 3. LP6005442-DNA_F10, S_English-2 4. LP6005442-DNA_E10, S_English-1 5. LP6005441-DNA_B05, S_French-2 6. LP6005442-DNA_C04, S_Iranian-1 7. LP6005443-DNA_B10, S_Iranian-2 8. LP6005441-DNA_B12, S_Surui-2 9. LP6005441-DNA_F10, S_Pima_2 10. LP6005441-DNA_A04, S_Piapoco-1 11. LP6005677-DNA_E01, S_Quechua-2 12. LP6005519-DNA_D01.srt.aln.bam , S_Chane-1 13. LP6005441-DNA_G07.srt.aln.bam, S_Mayan-1 14. LP6005441-DNA_H07.srt.aln.bam, S_Mayan-2 15. LP6005443-DNA_G11.srt.aln.bam, S_Mixtec-1 16. LP6005443-DNA_H11.srt.aln.bam, S_Mixtec-2 17. LP6005443-DNA_A12.srt.aln.bam, S_Zapotec-1 18. LP6005677-DNA_D01.srt.aln.bam, S_Zapotec-2 19. LP6005441-DNA_G06.srt.aln.bam, S_Karitiana-1 20. LP6005441-DNA_H06.srt.aln.bam, S_Karitiana-2 21. LP6005441-DNA_E10.srt.aln.bam, S_Pima-1 22. LP6005441-DNA_A12.srt.aln.bam, S_Surui-1 23. LP6005677-DNA_F01.srt.aln.bam, S_Quechua-1 24. LP6005519-DNA_G02.srt.aln.bam, S_Quechua-3 25. LP6005441-DNA_B04.srt.aln.bam, S_Piapoco-2

Power analysis To confirm that the large variation in diversity seen among the ancient American samples is not a result of variation in sequencing depth, we determined the statistical power to infer θ using simulations for nine samples spanning a large range of depth and include the samples for which we estimated particularly low diversity.

19

For each sample, we then simulated 250 windows of 5Mb for each of many different θ values following the approach described in (26) but with some important modifications to match the data of the sample:

• For each sample we simulated reads to match the average depth observed. • In contrast to (26) we simulated reads of variable length and matching the

distribution of read length for each sample. Specifically, we assumed fragment lengths to be gamma distributed and mode and variance of the observed distribution of read length. For each read we then randomly drew a fragment length from that distribution, but truncated the read length to the maximum number of sequencing cycles for each fragment exceeding that number.

• Quality scores were simulated from a normal distribution matching the mean and variance of the observed, recalibrated quality scores for each individual. Sequencing errors were then added at each position in the read with probability given by the quality scores.

• We also simulated PMD for each sample matching the observed distribution. The distribution of inferred θ for the simulated windows in shown in (Fig. S13). These results confirm high statistical power to infer a wide range of θ values. As is expected from the higher variation in simulations at low θ, estimation accuracy decreases with θ. At θ=10-4, for instance, only 75 mutations are expected to be heterozygous under the model, and of those many might not be covered twice at the ultra-low depth of some samples. As a consequence, we were not able to obtained reliable estimates for many windows at extremely low θ, where we define here an estimate to be reliable if at least 2% of the sites in a window are covered twice or more, and if θ was estimated ≥ θ<10-5. As a consequence of this filtering, estimates appear biased at low theta, but we stress that windows for which estimates could be obtained at these low θ are necessarily those with exceptionally many heterozygous sites covered twice. In conclusion, the ultra-low depth of some of our samples does not explain the particularly low diversity seen in some samples, nor may it explain the high variation in diversity observed among the ancient Americans. While accurate inference at θ below roughly 10-4 is indeed difficult for some samples, we note that very few windows of our samples demonstrate that low diversity. Indeed, we were able to obtain reliable estimates for the large majority of windows in all samples.

Haplotype segment matching By Tariq Desai, Aylwyn Scally Phased Pima and Surui chr1 genotypes were taken from the Simons Genome Project, along with the universal map ability and low-complexity mask x75.fa. Derived alleles were identified using the set of ancestral alleles taken from the 1000 Genomes Project primate EPO panel. We generated 200 MCMC samples of the chr1 ancestral recombination graph (ARG) by applying ARGweaver to the 8 Pima and Surui haplotypes. We allow 2000 burn-in iterations and sample every 10th ARG thereafter. This process was parallelised by splitting the chromosome into 5Mb regions with a 1Mb

20

overlap and running ARGweaver on each region independently. Haplotype segments for each MCMC sample were identified by the intervals corresponding to single trees in the ARG. Each modern haplotype segment was declared a match with an ancient sequence if it shared at least 1 derived allele with that ancient sequence, and if the other sequence contained the ancestral allele at all of the shared positions. These SNPs are referred to as “private” derived alleles. Ambiguous segments were ignored. Sites at which any of the ancient SNPs were not identified were ignored, as well as missing sites in the modern sequences and sites at which the ancestral allele was not identified. We assume the demographic model shown in the main section and derive the probabilities that modern segments match with either of the ancient sequences, conditioned on the event that a match occurs. The arguments are based on standard coalescent techniques (see link to detail below). Under this model, the ancestral lineages of the segments are not independent. This will lead to an over-dispersion in observed segment-sharing relative to the binomial variance derived from the demographic model. We expect, nonetheless, that the observed mean under the assumption of independence is an unbiased estimate of the expectation derived from the true demographic model. We adjust for the excess in variance first by running the analysis on segments binned by length. This limits correlations in matching probability introduced by genetic distance. This step is also required by the mutation model. Second, we infer the likelihood surface using a beta-binomial distribution (conservatively, we set parameter a=10, while b is defined so that the mean of the distribution corresponds to the relevant binomial) to account for the increased variance. The log-likelihood is calculated 100 times, each time drawing 8 “observations” corresponding to one random choice of a segment matching proportion for each haplotype from among the MCMC samples of the ARG. The additional plot A shows differences in sum of log-likelihoods between each run of the averaging process, illustrating that 100 is sufficient to reach convergence in average likelihood. Scripts for haplotype segment matching, likelihood inference, and plot generation can be accessed at https://github.com/td329/NA-hapmatch-2018, along with a coalescent derivation of the relevant algebraic quantities. A fuller treatment in a separate publication is currently being prepared. Additional analyses demonstrating robustness of findings under varying parameters Where not stated, parameters in the following plots are: N=1e4, lambda1=lambda2=1.5, merge_time=15kya, ancestry proportions are (p0, p_anzick, p_ck-13) = (0, 0.65, 0.35) for Pima samples and (0, 0.5, 0.5) for Surui samples (Figure S6).

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Visual representation of tree of Y chromosome Q lineages. Dotted lines represent low to medium coverage, solid lines represent high coverage. Red samples are from this study, orange are ancient Native Americans from published studies. Sources of reference samples: 1 - (71 ), Complete Genomics, high coverage; 2 - (99 ) 1000 Genome data, medium coverage; 3 - (70 ), Complete Genomics, high coverage; 4 - Complete Genomics, Public Personal Genomes, high coverage; 5 - (69 ), medium coverage; 6 - (86 ), screening for individual markers rather than whole genome sequencing; 7 - (8 ); 8 - THIS STUDY; 9 - (9 ), 10 - (10 ); YF - https://www.yfull.com/tree/Q/; 11 - (6 ); 12 - (87 ).

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Figure S2.Best of 100 runs of ADMIXTURE for Ks 2 - 16 using a worldwide panel.

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Fig. S3.Inferred local heterozygosity (θ, y axis) in 5Mb windows with a reference-free approach that accounts for postmortem damage inherent in ancient DNA (15). Abbreviations are ESN – Early San Nicolas, LSN – Late San Nicolas, SC – San Clemente, CT – Catalina, BA – Baja, ASO – Ancient Southwestern Ontario, A - PCNW, HG – Hunter Gatherers (Europe), EF – Early Farmers (Europe). Samples are ordered by population and by calibrated age. Numbers below boxplots indicate the percentage of windows for which θ was too low to be reliably estimated (θ estimated < 10^-5)(15).

21

Fig. S4. The best tree (qpGraph)without admixture relating ancient Clovis, Northeast U.S., Californian (Early San Nicolas and Northern Channel Islands and Santa Barbara) populations with modern representatives of South (Surui) and Central (Pima) Americans. This tree has a poor fit with the data, including 14 f4-statistics with |Z| score >3 and the worst f2-statistic between Northern Channel Islands and Santa Barbara and Pima, Z=-4.94.

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Fig. S5. Observed haplotype segment matches per MCMC sample. Scripts available online at https://github.com/td329/NA-hapmatch-2018.

23

Fig. S6. Likelihood surface plots of subpopulation merge times. (1) Merge time 13kya (2) (p0, p_anzick, p_ck-13) = (0, 0.6, 0.4) ancestry proportions (3) (p0, p_anzick, p_ck-13) = (0, 0.1, 0.9) ancestry proportions (4) lambda1 = 2, lambda2 = 1 (5) lambda1=1, lambda2=2 (6) N=5000. Scripts available to be accessed at https://github.com/td329/NA-hapmatch-2018.

24

Fig. S7. Effect of aggressive adapter removal using CutAdapt (52) (grey) and trimming of 10 base pairs from both the 5’ and 3’ ends of all reads (orange) in the Early San Nicolas population versus the normal pipeline where adapters are trimmed using default settings and 3 base pairs are trimmed from the 5’ and 3’ ends of all reads (blue).

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Fig. S8. Principal Component Analysis of ancient genomes projected onto modern world wide variation using transversions only. Most ancient Native Americans still cluster with modern Native Americans in the top right end of the distribution.

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Fig. S9. Plot of log likelihood difference across 100 independent runs of ADMIXTURE.

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Fig. S12. Close up of distribution of ANC-A and ANC-B ancestry proportions in ancient and modern (A) North Americans and (B) Southern Cone populations overlaid with glaciation levels in past 21,500 years (79-81).

30

Fig. S13. An admixture graph testing for fit of Pima related admixture into the Northern Channel Islands and Santa Barbara population which is rejected by p <10-2 , worst f-stat is Surui, EarlySN, Pima.

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31

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Table S1.

# ID Source Original ID Site Raw C14 Date YBP Date ID Depth (x) Human (%) Dupli (%). mtDNA Coverage (x) Contamination (%) MtDNA Y chrom. Sex Geo./Pop Included in autosomal analysis

1 523a RM 523a Palm Site 0.975 15.03% 39.6% 98.59 0.50% A2a Q1a-B34 M Alaskan Athabaskan Yes2 Ala1 RM Ala1 Síi Túupentak (ALA-565/H) 0.572 11.21% 20.2% 102.08 0.84% C1c1b - F San Francisco Bay Yes3 B-03 SDMM 1972-64-1 LC-218, Baja, MX 0.567 56.10% 2.6% 36.98 0.44% C1b11 Q1a-Z769 M Pericu Yes4 B-04 SDMM 16697 Comondu, Baja, MX 0.144 20.58% 1.4% 19.49 1.36% C1b41a1 - F Baja, Mexico Yes5 CH-01 JRJ Burial #1 Carpenteria, CA 1600 ± 30 BA-443411 0.037 1.48% 1.9% 4.19 0.24% A2 - F Mainland Chumash Yes6 CK-01 UT G849 Lucier, southwestern Ontario 0.007 0.37% 2.6% 4.82 nd C4c1 nd M ASO No7 CK-02 UT GS1 Lucier, southwestern Ontario 556 ± 18 D-AMS 016744 0.007 0.67% 5.3% 6.29 nd C1c - F ASO No8 CK-03 UT 3 Lucier, southwestern Ontario 729 ± 38 D-AMS 022506 0.043 3.90% 0.1% 3.99 1.06% X2a1c nd M** ASO No9 CK-04 UT GS4A Lucier, southwestern Ontario 0.003 0.19% 1.6% 2.34 nd C nd M** ASO No10 CK-07 UT GB25 Lucier, southwestern Ontario 0.002 0.07% 5.8% 8.06 1.78% C4c1 - F** ASO No11 CK-08 UT GG123 Lucier, southwestern Ontario 0.004 0.29% 6.4% 9.818 nd C1b40 - F** ASO No12 CK-09 UT 1001 Lucier, southwestern Ontario 351 ± 40 D-AMS 022504 0.169 9.90% 2.1% 123.2 0.49% A2i - F ASO Yes13 CK-10 UT GS7 Lucier, southwestern Ontario 0.036 2.28% 1.9% 0.94 0.75% C1b40 - F ASO Yes14 CK-13 UT RS14 Lucier, southwestern Ontario 4267 ± 22 D-AMS 022505 3.020 19.24% 7.7% 83.04 0.72% C1b40 - F ASO Yes15 CR-01 SDMM 16713 Santa Cruz Island, CA 1111 ± 39 UBA-31906 8.365 47.53% 11.7% 135.44 0.43% A2 - F Island Chumash Yes16 CT-01 SDMM 1973-36-1 Santa Catalina Island, CA 387 ± 38 UBA-31907 6.685 32.00% <1% 105.27 1.33% C1b41a1a Q1a* M LSCI Yes17 CT-02 SDMM 1986-22-0007-E Santa Catalina Island, CA 0.054 3.82% 1.5% 8.53 0.92% C1b41a1 - F LSCI Yes18 LU-01 UT GB-33 Lucier, southwestern Ontario 0.026 1.89% 3.7% 298.62 0.96% C nd M ASO Yes19 LU-02 UT GG-33 Lucier, southwestern Ontario 0.030 1.87% 1.3% 5.75 2.04% A2i nd M ASO Yes20 LU-03 UT GS12 Lucier, southwestern Ontario 0.025 1.39% 2.3% 5.10 5.98% C1d1a1 nd M ASO No21 LU-04 UT GX8 Lucier, southwestern Ontario 0.017 2.49% 17.0% 1.64 nd C - nd ASO No22 LU-05 UT GX9 Lucier, southwestern Ontario 0.020 1.94% 7.9% 4.51 5.63% C - F ASO No23 LU-06 UT GG-121 Lucier, southwestern Ontario 0.132 7.42% 2.3% 4.75 0.88% C1d1a1 - F ASO Yes24 MX-01 SDMM 2996 Iron Springs, MX 0.280 23.04% 2.1% 23.2 0.84% B2a5 Q1b M Baja, Mexico Yes25 NC RM NC New Cuyama, CA 1450 ± 30 BA-443413 1.120 13.31% 13.4% 172.88 0.40% D1 Q1a* M Mainland Chumash Yes26 PS-02 SDMM 17749 Point Sal, CA 0.178 4.30% 2.4% 22.37 0.81% D1t - F Mainland Chumash Yes27 PS-03 SDMM 17750 Point Sal, CA 1574 ± 40 UBA-31911 0.254 8.49% 1.8% 19 1.73% A2 Q1a M Mainland Chumash Yes28 PS-04 SDMM 17751 Point Sal, CA 0.014 1.47% 1.6% 9.78 0.52% D1t - F Mainland Chumash No29 PS-06 SDMM 17753 Point Sal, CA 1570 ± 41 UBA-31912 4.124 23.02% 5.6% 30.37 0.34% D1t Q1a* M Mainland Chumash Yes30 PS-07 SDMM 17806 Point Sal, CA 1559 ± 38 UBA-31913 0.595 18.75% 1.8% 69.83 1.09% D1t Q1a-B623 M Mainland Chumash Yes31 PS-09 SDMM 17808 Point Sal, CA 0.223 4.61% 2.8% 74.05 0.76% A2 Q1a M Mainland Chumash Yes32 PS-11 SDMM 17810 Point Sal, CA 0.004 0.42% 1.1% 6.18 0.00% D1t - F Mainland Chumash No33 PS-12 SDMM 17812 Point Sal, CA 0.006 1.14% 1.9% 0 nd na - F Mainland Chumash No34 PS-13 SDMM 17857 Point Sal, CA 0.015 0.97% 3.0% 1.26 nd D1t nd M Mainland Chumash No35 PS-17 SDMM 17862 Point Sal, CA 0.116 2.38% 1.8% 21.62 1.81% D1t - F Mainland Chumash Yes36 PS-18 SDMM 17863 Point Sal, CA 0.207 4.51% 5.9% 25.39 0.63% D1t - F Mainland Chumash Yes37 PS-19 SDMM 17864 Point Sal, CA 0.001 0.16% 4.8% 0 nd nd - F** Mainland Chumash No38 PS-22 SDMM 17867 Point Sal, CA 0.003 0.75% 16.9% 0 nd nd - F Mainland Chumash No39 PS-23 SDMM 17868 Point Sal, CA 0.089 2.75% 1.6% 61.76 0.23% D1t - F Mainland Chumash Yes40 PS-24 SDMM 17869 Point Sal, CA 0.003 0.23% 1.4% 7.17 0.63% D1t - F Mainland Chumash No41 PS-26 SDMM 17872 Point Sal, CA 0.138 1.73% 1.9% 79.12 0.46% D1t Q1 M Mainland Chumash Yes42 PS-30 SDMM 18131 Point Sal, CA 0.003 0.70% 26.3% 0 nd nd nd M Mainland Chumash No43 PS-34 SDMM 18276 Point Sal, CA 0.146 17.16% 5.8% 15.15 6.18% A2cc nd M Mainland Chumash No44 RM-83 RM na 05SP-46 (Teston Road Ossuary) 1450 AD Ceramics 0.675 26.75% 23.4% 51.86 1.14% A2i - F ASO (Huron-Wendat) Yes45 RM-85 RM na 11SP-83 (Turnbull Ossuary) 1400-1500AD Ceramics 0.043 2.58% 63.4% 19.00 0.50% C1c Q1a-B34 M ASO (Huron-Wendat) Yes46 SC-01 SDMM 2084 San Clemente Island, CA 0.545 63.11% 2.3% 27.99 0.51% Cb16a1 - F LSCI Yes47 SC-02 SDMM 2085 San Clemente Island, CA 0.010 0.60% 1.3% 0.11 nd nd - F LSCI No48 SC-03 SDMM 2086 San Clemente Island, CA 1055 ± 38 UBA-31908 0.939 33.15% 3.0% 29.57 1.36% C1b41a - F LSCI Yes49 SC-04 SDMM 2087 San Clemente Island, CA 884 ± 41 UBA-31909 0.709 45.11% 6.3% 40.23 0.98% B2a5 - F LSCI Yes50 SC-05 SDMM 1971-78-1 San Clemente Island, CA 1101 ± 41 UBA-31910 13.671 67.00% <1% 47.4 1.12% Cb16a1 - F LSCI Yes51 SC-06 SDMM 1972-60-1 San Clemente Island, CA 0.432 35.82% 2.0% 114.84 1.45% C1b41a Q1a M LSCI Yes52 SC-07 SDMM 1975-14-1 San Clemente Island, CA 0.418 54.43% 8.1% 27.13 3.07% C1b41a1a - F LSCI No53 SM-01 MDLH PE7066 San Miguel Island, CA 641 ± 25 0.235 15.37% 3.2% 24.32 1.17% A2 Q1a-B623 M Island Chumash Yes54 SM-02 MDLH PE7076 San Miguel Island, CA 826 ± 26 7.387 51.5% 29.0% 33.18 1.37% A2 - F Island Chumash Yes55 SN-01 SDMM 16715 San Nicolas Island, CA 0.272 34.7% 1.5% 138.64 0.97% B2a5b - F LSN Yes56 SN-02 SDMM 16716 San Nicolas Island, CA 0.001 0.2% 4.0% 19.48 0.00% C1b41a1 - F LSN No57 SN-03 SDMM 16719 San Nicolas Island, CA 1694 ± 56 UBA-31920 0.759 60.7% 2.1% 13.14 0.79% Cb16a1 - F LSN Yes58 SN-04 SDMM 16732 San Nicolas Island, CA 4279 ± 52 UBA-31917 0.125 17.7% 1.4% 39.49 1.65% A2ca nd M ESN Yes59 SN-09 SDMM 16739 San Nicolas Island, CA 0.095 9.9% 1.4% 39.12 0.90% B2a5b Q1a M LSN Yes60 SN-10 SDMM 16741 San Nicolas Island, CA 0.698 72.4% 1.9% 13.87 0.34% B2a5b - F LSN Yes61 SN-11 SDMM 16743 San Nicolas Island, CA 1172 ± 39 UBA-31916 9.058 54.5% 14.8% 36.01 0.95% D1 Q1a-B654 M LSN Yes62 SN-12 SDMM 17643 San Nicolas Island, CA 1269 ± 34 UBA-31921 0.085 9.5% 2.7% 41.95 1.14% C - F LSN Yes63 SN-13 SDMM 17644 San Nicolas Island, CA 881 ± 42 UBA-31915 1.745 64.3% 1.9% 31.37 0.00% C1b - F LSN Yes64 SN-15 SDMM 17658 San Nicolas Island, CA 1852 ± 44 UBA-31918 0.550 63.8% 2.9% 23.4 1.71% Cb16a1 - F LSN Yes65 SN-16 SDMM 17661 San Nicolas Island, CA 650 - 510 0.287 32.5% 1.6% 45.88 0.98% B2a5b - F LSN Yes66 SN-17 SDMM 17662 San Nicolas Island, CA 4517 ± 51 UBA-31914 7.451 40.1% 14.2% 22.45 0.78% A2ca Q1a* M ESN Yes67 SN-20 SDMM 17665 San Nicolas Island, CA 0.123 29.5% 5.1% 22.98 1.55% A2cb Q1a M ESN Yes68 SN-25 SDMM 17684 San Nicolas Island, CA 3940 ± 40 UBA-31922 0.168 14.9% 1.6% 7.7 0.63% A2cb Q M ESN Yes69 SN-31 SDMM 17702 San Nicolas Island, CA 0.024 2.8% 5.8% 22.89 0.93% A2 nd M ESN Yes70 SN-32 SDMM 17703 San Nicolas Island, CA 4455 ± 46 UBA-31919 0.259 8.8% 3.4% 9.82 0.28% A2cb Q M ESN Yes71 SN-37 SDMM 17720 San Nicolas Island, CA 0.170 14.0% 8.3% 12.39 3.23% A2ca - F ESN No72 SN-38 SDMM 17723 San Nicolas Island, CA 0.505 22.2% 2.1% 49.12 0.87% C1b41a1 Q1a-B654 M LSN Yes73 SN-39 SDMM 17728 San Nicolas Island, CA 0.121 15.1% 1.3% 14.96 0.26% A2cb - F ESN Yes74 SN-40 SDMM 17732 San Nicolas Island, CA 0.460 32.9% 3.5% 56.82 1.47% A2cb - F ESN Yes75 SN-41 SDMM 17732 San Nicolas Island, CA 0.023 3.3% 11.5% 8.57 0.00% A2ca - F ESN Yes76 SN-43 SDMM 17736 San Nicolas Island, CA 2541 ± 26 Oxa-34809 0.078 9.2% 2.2% 15.07 1.14% C1b41a - F LSN Yes77 SN-44 SDMM 17737 San Nicolas Island, CA 4647 ± 54 UBA-32254 9.361 51.2% 11.7% 109.94 0.55% A2cb Q1a* M ESN Yes78 SN-45 SDMM 17739 San Nicolas Island, CA 0.013 1.2% 3.1% 1.94 1.82% A2 nd M ESN Yes79 SN-48 SDMM 1961-36-1 San Nicolas Island, CA 0.423 45.0% 2.1% 28.68 6.02% A2 - F ESN No80 SN-50 MDLH PE7105 San Nicolas Island, CA 1593 ± 27 OxA-16576 0.990 62.6% 4.8% 101.36 1.54% C1b41a1 - F LSN Yes81 SN-51 MDLH PE7106 San Nicolas Island, CA 1620 ± 26 OxA-16577 0.400 52.4% 10.1% 127.14 1.25% C1b41a1 - F LSN Yes82 SN-52 MDLH PE10252 San Nicolas Island, CA 1013 ± 26 OxA-16578 0.439 27.8% 3.8% 66.3 1.45% B2y1 - F LSN Yes83 SN-53 MDLH PE10250 San Nicolas Island, CA 840 ± 26 OxA-16579 0.614 40.5% 3.7% 64 1.23% B2a5b - F LSN Yes84 SN-54 SK 28F-140 ID 113 San Nicolas Island, CA 3960 ± 70 Beta-124308 0.433 38.9% 3.6% 86.82 1.30% A2cb Q1a M ESN Yes85 SN-55 SK 257-69 Burial \#1 San Nicolas Island, CA 4410 ± 100 UCLA-147 0.028 3.4% 2.5% 17.29 0.44% A2 nd M ESN Yes86 SN-56 SK 257-76 Burial \#8 San Nicolas Island, CA 4410 ± 100 UCLA-147 0.044 6.2% 2.6% 95.2 0.35% A2cb nd M ESN Yes87 SN-57 SK 257-80 Burial \#12 San Nicolas Island, CA 4410 ± 100 UCLA-147 0.043 5.2% 1.9% 35.66 0.81% A2ca nd M ESN Yes88 SN-58 SK Burial \#16 San Nicolas Island, CA 4410 ± 100 UCLA-147 0.165 15.8% 5.7% 105.75 0.35% A2ca Q1a M ESN Yes89 SN-59 SK 28F - 137 San Nicolas Island, CA 4430 ± 30 NOSAMS-34058 0.160 17.7% 7.6% 112.47 0.79% A2cb Q1 M ESN Yes90 SN-60 SK 28F-70 Burial \#2 San Nicolas Island, CA 3960 ± 70 Beta-124308 0.025 0.9% 2.2% 8.56 0.35% A2cb nd M ESN Yes91 US-14 AMNH 99.1/2270 Shohola Creek, Indian Cabin Ridge, PA 269 ± 26 OxA-34348 0.448 38.9% 3.1% 48.16 1.38% U4c1a I1a-Z73 M Colonist Yes

Population ID codes: ASO - Ancient Southwestern Ontario, LSCI - Late Southern Channel Islands, LSN - Late San Nicolas, ESN - Early San Nicolas.**with low coverage samples sex determination was consistent with sex shown, but not definitive.nd = no data.

List of all samples (n=91) included in this study, source of sample, site information, radiocarbon dates if attained and ID numbers, average depth of genomic coverage measured by x times the genome length, percent reads mapping to human, percent duplication rate, average mitochondrial genome coverage, estimated contamination on the mitochondrial genome, mitochondrial haplotype, Y chromosome haplotype, genomically inferred sex, population assigned for this manuscript and whether the sample was included in autosomal analyses.

Note: ID codes of the samples: B-Baja; CH-Chumash; CK-Lucier; CR-Santa Cruz ; CT-Santa Catalina ; LU-Lucier ; MX-Iron Springs Mexico; PS-Point Sal; SC-San Clemente; SM-San Miguel; SN-San Nicolas; US-United States; RM-Ripan Malhi.Depth - Average depth of the coverage of human genome; % Human - proportion of reads mapping to human genome; % Dupli. - proportion of PCR duplicate reads mapping to human genome; % contamination estimated on mtDNA (see Supplementary Materials).Sources: SDMM - San Diego Museum of Man, MDLH - Musée de l'Homme, UT - University of Toronto, RM - Ripan Malhi, AMNH - American Museum of Natural History, SK - Susan Kerr (UCLA/Southwest Museum/U.S. NAVY), JRJ - John Johnson.

Table S2. Radiocarbon dating calibration information and stable isotopes values.

Sample ID

Other ID Site Lab ID Material Yield C:N ratio Raw C14 Error Marine13?Resevoir

ValueSE Calibrated (68% prob) D13C D15N

Dietary Signature

Sourceobserved

valuesCurve

PS-29 18130 G-1 (Point Sal) Beta-159837 Bone nd nd nd nd No 0 110 - 230 AD nd nd SDMM Mix_CurvePS-06 17753 G-1 (Point Sal) UBA-31911 Tooth root 5.30 3.20 1570 41 No 0 428 - 536 AD -16.80 12.90 C3 This study Mix_CurvePS-07 17806 G-1 (Point Sal) UBA-31912 Tooth root 12.20 3.17 1559 38 No 0 428 - 527 AD -16.30 13.90 C3 This study Mix_CurvePS-03 17750 G-1 (Point Sal) UBA-31913 Tooth root 7.20 3.22 1574 40 No 0 429 - 537 AD -16.60 12.90 C3 This study Mix_CurvePS-10 17809 G-1 (Point Sal) Beta-159835 Bone nd nd nd nd No 0 580 - 650 AD nd nd SDMM Mix_Curve

CR-01 16713Valdez Bay, Santa Cruz,

Channel islands UBA-31906 Tooth root 14.70 3.19 1111 39 Yes 217 129 1186 AD - 1389 AD -14.90 17.40 This study 64.2 Mix_CurveSC-05 1971-78-1 nd UBA-31910 Tooth root 14.00 3.20 1101 41 Yes 217 129 1190 AD - 1389 AD -15.10 16.30 This study 62.8 Mix_CurveSC-03 2086 SC-02 UBA-31908 Tooth root 14.90 3.18 1055 38 Yes 217 129 1285 AD - 1465 AD -12.90 19.90 This study 78.8 Mix_CurveSC-04 2087 SC-04 UBA-31909 Tooth root 16.50 3.20 884 41 Yes 217 129 1442 AD - 1676 AD -11.90 19.20 This study 86.1 Mix_CurveSM-02 7076 nd OxA-16581 Tooth root nd nd 826 26 Yes 217 129 1485 AD - 1800 AD -11.80 nd Valentin (2010) 86.9 Mix_CurveSM-01 7066 nd OxA-16580 Tooth root nd nd 641 25 Yes 217 129 1706 AD - Present -11.90 nd Valentin (2010) 86.1 Mix_CurveCT-01 1973-36-1 nd UBA-31907 Tooth root 5.50 3.15 387 38 Yes 217 129 1811 AD - Present -13.80 19.60 This study 72.3 Mix_CurveSN-44 17737 SN-21a (SNI-160) UBA-32254 Tooth root 10.80 3.26 4647 54 Yes 217 129 2869 BC - 2500 BC -10.80 18.90 This study 94.2 Mix_CurveSN-17 17662 SN-21a Cem. 2 UBA-31914 Tooth root 13.60 3.21 4517 51 Yes 217 129 2824 BC - 2392 BC -11.50 21.90 This study 89.1 Mix_CurveSN-32 17703 SN-23 (SNI-41) UBA-31919 Tooth root 8.00 3.21 4455 46 Yes 217 129 2611 BC - 2206 BC -10.60 19.80 This study 95.6 Mix_CurveSN-04 16732 SN-6 (SNI-1, SNI-325-7) UBA-31917 Tooth root 0.01 3.20 4279 52 Yes 217 129 2396 BC - 1993 BC -10.60 19.70 This study 95.6 Mix_CurveSN-48 1961-36-1 nd UBA-32255 Tooth root 14.90 3.22 4077 48 Yes 217 129 2123 BC - 1747 BC -11.10 20.30 This study 92.0 Mix_CurveSN-25 17684 SN-18 (SNI-16) UBA-31922 Tooth root 8.50 3.20 3940 40 Yes 217 129 1918 BC - 1564 BC -10.80 20.60 This study 94.2 Mix_CurveSN-43 17736 Oxa-34809 Tooth root 65.46 3.30 2541 26 Yes 217 129 252 BC - 62 AD -12.10 20.10 This study 84.7 Mix_CurveSN-15 17658 SN-21a (SNI-171) UBA-31918 Tooth root 6.80 3.18 1852 44 Yes 217 129 459 AD - 698 AD -13.70 20.00 This study 73.0 Mix_CurveSN-03 16719 SN-6 (SNI-1, SNI-325-7) UBA-31920 Tooth root 13.90 3.22 1694 56 Yes 217 129 704 AD - 976 AD -11.80 20.70 This study 86.9 Mix_CurveSN-51 7106 nd OxA-16577 Tooth root nd nd 1620 26 Yes 217 129 779 AD - 1062 AD -11.20 nd Valentin (2010) 91.2 Mix_CurveSN-50 7105 nd OxA-16576 Tooth root nd nd 1593 27 Yes 217 129 824 AD - 1124 AD -11.00 nd Valentin (2010) 92.7 Mix_CurveSN-12 17643 SN-19 (SNI-151-2, SNI-158) UBA-31921 Tooth root 9.00 3.19 1269 34 Yes 217 129 1080 AD - 1307 AD -12.80 18.30 This study 79.6 Mix_CurveSN-11 16743 nd UBA-31916 Tooth root 13.50 3.24 1172 39 Yes 217 129 1226 AD - 1433 AD -12.10 21.40 This study 84.7 Mix_CurveSN-52 10250 nd OxA-16578 Tooth root nd nd 1013 26 Yes 217 129 1316 AD - 1536 AD -12.10 nd Valentin (2010) 84.7 Mix_CurveSN-13 17644 SN-7a (SNI-318) UBA-31915 Tooth root 41.30 3.18 881 42 Yes 217 129 1442 AD - 1674 AD -12.00 17.40 This study 85.4 Mix_CurveSN-53 10252 nd OxA-16579 Tooth root nd nd 840 26 Yes 217 129 1523 AD - 1816 AD -10.40 nd Valentin (2010) 97.1 Mix_CurveCK-13 RS14 Lucier, SW Ontario D-AMS 022505 Tooth collagen 4267 22 No 2903 - 2887 BC This studyCK-03 3 Lucier, SW Ontario D-AMS 022506 Tooth collagen 729 38 No 1255 - 1294 AD This studyCK-02 GS-1 Lucier, SW Ontario D-AMS 016744 Bone 556 18 No 1328 - 1414 AD -6.70 Maize This studyCK-26 1001 Lucier, SW Ontario D-AMS 022504 Tooth collagen 351 40 No 1475 - 1631 AD This study

US-14 99.1/2270Shohola Creek, Indian Cabin

Ridge, PA OxA-34348 Tooth collagen 38.94 3.20 269 26 No 0 1634 - 1662 AD -16.04 10.16 This studyCH-01 SBA6B1 Carpenteria BA-443411 Bone collagen nd 3.30 1600 30 No nd nd 395 - 540 AD -15.60 16.90 This study (J.R.J.) Calibrated by Beta AnalyticNC SBA4088B1 New Cuyama BA-443413 Bone collagen nd 3.20 1450 30 No nd nd 560 - 650 AD -21.30 8.80 This study (J.R.J.) Calibrated by Beta Analytic

Note: Observed values are -23.7 for a terrestrial diet (approaching 100% terrestrial) from Ontario and -10.0 for a marine diet (approaching 100% marine) from San Nicholas islands from (41 ).

Table S3.Detailed sequencing information for whole autosomal and mitochondrial genomes generated for this study.

Sample ID Source Other IDExtraction Material

Library Prep PlatformRead

LengthRaw Reads

Aligned to Human

DuplicatesHuman

(%) Duplicate

(%)Coverage

(x)

523a RM Palm Site, Alaska Femur Double-stranded, Y adapters HiSeq4000 100 242,347,756 60,285,414 23,867,484 15.03% 39.59% 0.975Ala1 RM Síi Túupentak (ALA-565/H) Tooth Double-stranded, Y adapters HiSeq4000 100 190,355,260 26,745,349 5,405,974 11.21% 20.21% 0.572B-03 SDMM 1972-64-1 Tooth root Double-stranded NextSeq 500, Single-end 75 41,517,952 21,741,827 567,571 51.00% 2.61% 0.567B-04 SDMM 16697 Tooth root Double-stranded NextSeq 500, Single-end 75 30,254,442 5,450,771 75,639 17.77% 1.39% 0.144CH-01 JRJ Burial #1 Tooth root Double-stranded NextSeq 500, Single-end 75 26,666,327 416,452 5,981 1.54% 1.44% 0.011CK-01 UT G849 Tooth root Double-stranded NextSeq 500, Single-end 75 72,692,589 272,602 7,081 0.37% 2.60% 0.007CK-02 UT GS1 Tooth root Double-stranded NextSeq 500, Single-end 75 39,146,634 275,068 14,660 0.67% 5.33% 0.007CK-03 UT 3 Tooth root Double-stranded NextSeq 500, Single-end 75 35,809,372 1,397,447 1,961 3.90% 0.14% 0.037CK-03 UT 3 Tooth root Double-stranded NextSeq 500, Single-end 75 32,616,181 369,618 132,324 0.73% 35.80% 0.006CK-04 UT GS4A Tooth root Double-stranded NextSeq 500, Single-end 75 61,885,243 117,142 1,831 0.19% 1.56% 0.003CK-07 UT GB25 Tooth root Double-stranded NextSeq 500, Single-end 75 53,638,624 40,600 2,362 0.07% 5.82% 0.001CK-07 UT GB25 Tooth root Double-stranded NextSeq 500, Single-end 75 46,760,400 39,985 12,195 0.06% 30.50% 0.001CK-08 UT GG123 Tooth root Double-stranded NextSeq 500, Single-end 75 54,278,155 169,614 10,795 0.29% 6.36% 0.004CK-09 UT 1001 Tooth root Double-stranded NextSeq 500, Single-end 75 63,856,515 6,453,575 133,394 9.90% 2.07% 0.169CK-10 UT GS7 Tooth root Double-stranded NextSeq 500, Single-end 75 58,250,891 1,353,154 25,427 2.28% 1.88% 0.036CK-13 UT RS14 Tooth root Double-stranded NextSeq 500, Single-end 75 57,693,238 13,915,264 370,485 23.48% 2.66% 0.363CK-13 UT RS14 Tooth root Double-stranded NextSeq 500, Single-end 75 663,425,573 114,113,254 14,619,338 15.00% 12.81% 2.665CR-01 SDMM 16713 Tooth root Double-stranded NextSeq 500, Single-end 75 31,501,623 17,370,146 331,716 54.09% 1.91% 0.456CR-01 SDMM 16713 Tooth root Double-stranded NextSeq 500, Single-end 75 56,793,763 30,558,776 745,729 52.49% 2.44% 0.799CR-01 SDMM 16713 Tooth root Double-stranded NextSeq 500, Single-end 75 568,686,068 353,499,535 41,213,115 54.91% 11.66% 8.365CT-01 SDMM 1973-36-1 Tooth root Double-stranded NextSeq 500, Single-end 75 39,013,533 13,558,987 214,563 34.20% 1.58% 0.357CT-01 SDMM 1973-36-1 Tooth root Double-stranded NextSeq 500, Single-end 75 71,498,239 23,635,205 445,498 32.43% 1.88% 0.621CT-01 SDMM 1973-36-1 Tooth root Double-stranded NextSeq 500, Single-end 75 669,376,570 267,548,941 16,488,276 37.51% 6.16% 6.725CT-02 SDMM 1986-22-0007-E Tooth root Double-stranded NextSeq 500, Single-end 75 53,236,362 2,064,511 31,499 3.82% 1.53% 0.054LU-01 UT GB-33 Petrous Double-stranded NextSeq 500, Single-end 75 52,042,292 1,020,072 38,088 1.89% 3.73% 0.026LU-02 UT GG-33 Petrous Double-stranded NextSeq 500, Single-end 75 60,323,386 1,143,967 14,919 1.87% 1.30% 0.030LU-03 UT GS12 Petrous Double-stranded NextSeq 500, Single-end 75 67,860,917 963,931 21,771 1.39% 2.26% 0.025LU-04 UT GX8 Petrous Double-stranded NextSeq 500, Single-end 75 24,894,326 746,830 126,814 2.49% 16.98% 0.017LU-05 UT GX9 Petrous Double-stranded NextSeq 500, Single-end 75 37,543,602 790,704 62,174 1.94% 7.86% 0.020LU-06 UT GG-121 Petrous Double-stranded NextSeq 500, Single-end 75 66,419,246 5,045,680 116,175 7.42% 2.30% 0.132MX-01 SDMM 2996 Tooth root Double-stranded NextSeq 500, Single-end 75 45,306,401 10,667,695 227,816 23.04% 2.14% 0.280NC RM New Cuyama, CA Tooth Double-stranded, Y adapters HiSeq4000 100 314,071,322 48,307,271 6,491,299 13.31% 13.44% 1.120PS-02 SDMM 17749 Tooth root Double-stranded NextSeq 500, Single-end 75 38,840,546 1,681,192 27,642 4.26% 1.64% 0.044PS-02 SDMM 17749 Tooth root Double-stranded NextSeq 500, Single-end 75 115,329,601 5,111,880 137,235 4.31% 2.68% 0.133PS-03 SDMM 17750 Tooth root Double-stranded NextSeq 500, Single-end 75 28,000,418 2,398,660 33,327 8.45% 1.39% 0.063PS-03 SDMM 17750 Tooth root Double-stranded NextSeq 500, Single-end 75 83,880,678 7,274,721 139,739 8.51% 1.92% 0.191PS-04 SDMM 17751 Tooth root Double-stranded NextSeq 500, Single-end 75 35,510,565 528,757 8,424 1.47% 1.59% 0.014PS-06 SDMM 17753 Tooth root Double-stranded NextSeq 500, Single-end 75 53,813,091 13,407,975 240,813 24.47% 1.80% 0.353PS-06 SDMM 17753 Tooth root Double-stranded NextSeq 500, Single-end 75 72,844,481 17,660,104 331,834 23.79% 1.88% 0.464PS-06 SDMM 17753 Tooth root Double-stranded NextSeq 500, Single-end 75 542,079,050 163,027,543 9,051,068 28.40% 5.55% 4.124PS-07 SDMM 17806 Tooth root Double-stranded NextSeq 500, Single-end 75 92,687,750 17,825,971 328,254 18.88% 1.84% 0.469PS-07 SDMM 17806 Tooth root Double-stranded NextSeq 500, Single-end 75 25,702,346 4,767,807 70,748 18.27% 1.48% 0.126PS-09 SDMM 17808 Tooth root Double-stranded NextSeq 500, Single-end 75 33,492,098 882,646 10,695 2.60% 1.21% 0.023PS-09P SDMM 17808 Petrous Double-stranded NextSeq 500, Single-end 75 96,198,887 5,101,539 167,183 5.13% 3.28% 0.132PS-09P SDMM 17808 Petrous Double-stranded NextSeq 500, Single-end 75 50,509,835 2,569,152 65,718 4.96% 2.56% 0.067PS-11 SDMM 17810 Tooth root Double-stranded NextSeq 500, Single-end 75 32,415,293 139,301 1,578 0.42% 1.13% 0.004PS-12 SDMM 17812 Petrous Double-stranded NextSeq 500, Single-end 75 19,855,758 230,355 4,333 1.14% 1.88% 0.006PS-13 SDMM 17857 Petrous Double-stranded NextSeq 500, Single-end 75 56,681,920 564,576 16,721 0.97% 2.96% 0.015PS-17 SDMM 17862 Tooth root Double-stranded NextSeq 500, Single-end 75 45,151,100 1,093,413 15,117 2.39% 1.38% 0.029PS-17 SDMM 17862 Tooth root Double-stranded NextSeq 500, Single-end 75 136,372,382 3,302,494 65,198 2.37% 1.97% 0.087PS-18 SDMM 17863 Petrous Double-stranded NextSeq 500, Single-end 75 34,848,997 1,648,982 47,054 4.60% 2.85% 0.043PS-18 SDMM 17863 Petrous Double-stranded NextSeq 500, Single-end 75 136,160,626 6,550,476 437,985 4.49% 6.69% 0.164PS-19 SDMM 17864 Petrous Double-stranded NextSeq 500, Single-end 75 15,471,604 26,549 1,275 0.16% 4.80% 0.001PS-22 SDMM 17867 Petrous Double-stranded NextSeq 500, Single-end 75 15,957,213 144,196 24,333 0.75% 16.87% 0.003PS-23 SDMM 17868 Tooth root Double-stranded NextSeq 500, Single-end 75 29,675,192 854,684 11,222 2.84% 1.31% 0.023PS-23 SDMM 17868 Tooth root Double-stranded NextSeq 500, Single-end 75 91,531,308 2,533,390 41,555 2.72% 1.64% 0.067PS-24 SDMM 17869 Tooth root Double-stranded NextSeq 500, Single-end 75 42,830,556 101,420 1,424 0.23% 1.40% 0.003PS-26 SDMM 17872 Tooth root Double-stranded NextSeq 500, Single-end 75 58,802,368 1,107,131 16,065 1.86% 1.45% 0.029PS-26 SDMM 17872 Tooth root Double-stranded NextSeq 500, Single-end 75 238,802,730 4,132,972 84,430 1.70% 2.04% 0.108PS-30 SDMM 18131 Petrous Double-stranded NextSeq 500, Single-end 75 16,776,656 159,729 42,025 0.70% 26.31% 0.003PS-34 SDMM 18276 Petrous Double-stranded NextSeq 500, Single-end 75 31,758,138 5,787,241 337,535 17.16% 5.83% 0.146RM-83 RM 05SP-46 (Teston Road Ossuary) Tooth Double-stranded, Y adapters HiSeq4000 100 94,190,257 32,916,551 7,718,525 26.75% 23.45% 0.675RM-85 RM 11SP-83 (Turnbull Ossuary) Tooth Double-stranded, Y adapters HiSeq4000 100 62,691,474 4,415,030 2,799,062 2.58% 63.40% 0.043SC-01 SDMM 2084 Tooth root Double-stranded NextSeq 500, Single-end 75 32,243,813 20,818,409 468,901 63.11% 2.25% 0.545SC-02 SDMM 2085 Tooth root Double-stranded NextSeq 500, Single-end 75 59,537,125 364,219 4,683 0.60% 1.29% 0.010SC-03 SDMM 2086 Tooth root Double-stranded NextSeq 500, Single-end 75 46,796,857 7,308,617 109,451 15.38% 1.50% 0.193SC-03P SDMM 2086 Petrous Double-stranded NextSeq 500, Single-end 75 58,940,542 28,830,978 981,701 47.25% 3.41% 0.746SC-04 SDMM 2087 Tooth root Double-stranded NextSeq 500, Single-end 75 58,697,063 28,264,774 1,786,588 45.11% 6.32% 0.709SC-05 SDMM 1971-78-1 Tooth root Double-stranded NextSeq 500, Single-end 75 47,205,937 33,520,956 773,612 69.37% 2.31% 0.877SC-05 SDMM 1971-78-1 Tooth root Double-stranded NextSeq 500, Single-end 75 96,406,878 66,679,500 1,790,086 67.31% 2.68% 1.738SC-05 SDMM 1971-78-1 Tooth root Double-stranded NextSeq 500, Single-end 75 618,139,492 431,237,976 37,091,777 63.76% 8.60% 10.557SC-06 SDMM 1972-60-1 Tooth root Double-stranded NextSeq 500, Single-end 75 45,037,875 16,461,637 331,227 35.82% 2.01% 0.432SC-07 SDMM 1975-14-1 Petrous Double-stranded NextSeq 500, Single-end 75 28,649,375 16,975,127 1,381,997 54.43% 8.14% 0.418SM-01 MDLH PE7066 Tooth root Double-stranded NextSeq 500, Single-end 75 57,146,532 9,073,269 287,448 15.37% 3.17% 0.235SM-02 MDLH PE7076 Tooth root Double-stranded NextSeq 500, Single-end 75 45,728,487 33,940,820 1,817,040 70.25% 5.35% 0.860SM-02 MDLH PE7076 Tooth root Double-stranded NextSeq 500, Single-end 75 42,153,671 30,884,407 1,513,182 69.68% 4.90% 0.787SM-02 MDLH PE7076 Tooth root Double-stranded NextSeq 500, Single-end 75 447,181,909 388,448,607 112,675,051 61.67% 29.01% 7.387SN-01 SDMM 16715 Tooth root Double-stranded NextSeq 500, Single-end 75 29,314,051 10,308,390 149,492 34.66% 1.45% 0.272SN-02 SDMM 16716 Tooth root Double-stranded NextSeq 500, Single-end 75 20,752,141 52,531 2,085 0.24% 3.97% 0.001SN-03 SDMM 16719 Tooth root Double-stranded NextSeq 500, Single-end 75 46,723,096 28,939,051 593,695 60.67% 2.05% 0.759SN-04 SDMM 16732 Tooth root Double-stranded NextSeq 500, Single-end 75 26,358,945 4,724,788 67,147 17.67% 1.42% 0.125SN-09 SDMM 16739 Tooth root Double-stranded NextSeq 500, Single-end 75 35,607,838 3,580,318 50,954 9.91% 1.42% 0.095SN-10 SDMM 16741 Tooth root Double-stranded NextSeq 500, Single-end 75 36,012,354 26,568,893 492,913 72.41% 1.86% 0.698SN-11 SDMM 16743 Tooth root Double-stranded NextSeq 500, Single-end 75 34,932,575 22,983,689 536,692 64.26% 2.34% 0.601SN-11 SDMM 16743 Tooth root Double-stranded NextSeq 500, Single-end 75 55,552,919 35,745,488 991,054 62.56% 2.77% 0.931SN-11 SDMM 16743 Tooth root Double-stranded NextSeq 500, Single-end 75 530,091,003 396,947,183 58,779,450 63.79% 14.81% 9.058SN-12 SDMM 17643 Tooth root Double-stranded NextSeq 500, Single-end 75 33,346,544 3,268,661 88,771 9.54% 2.72% 0.085SN-13 SDMM 17644 Tooth root Double-stranded NextSeq 500, Single-end 75 38,456,788 25,381,153 422,998 64.90% 1.67% 0.669SN-13 SDMM 17644 Tooth root Double-stranded NextSeq 500, Single-end 75 62,770,721 41,002,490 829,321 64.00% 2.02% 1.076SN-15 SDMM 17658 Tooth root Double-stranded NextSeq 500, Single-end 75 32,206,208 21,160,699 617,077 63.79% 2.92% 0.550SN-16 SDMM 17661 Tooth root Double-stranded NextSeq 500, Single-end 75 32,951,244 10,896,102 178,559 32.53% 1.64% 0.287SN-17 SDMM 17662 Tooth root Double-stranded NextSeq 500, Single-end 75 42,191,136 20,412,648 469,974 47.27% 2.30% 0.534SN-17 SDMM 17662 Tooth root Double-stranded NextSeq 500, Single-end 75 60,375,298 28,216,142 769,073 45.46% 2.73% 0.735SN-17 SDMM 17662 Tooth root Double-stranded NextSeq 500, Single-end 75 590,397,540 324,278,964 46,113,989 47.11% 14.22% 7.451SN-20 SDMM 17665 Tooth root Double-stranded NextSeq 500, Single-end 75 15,619,057 4,850,683 249,325 29.46% 5.14% 0.123

SN-25 SDMM 17684 Tooth root Double-stranded NextSeq 500, Single-end 75 42,213,450 6,391,849 101,894 14.90% 1.59% 0.168SN-31 SDMM 17702 Tooth root Double-stranded NextSeq 500, Single-end 75 32,204,655 959,052 55,654 2.81% 5.80% 0.024SN-32 SDMM 17703 Tooth root Double-stranded NextSeq 500, Single-end 75 42,532,513 3,779,919 106,831 8.64% 2.83% 0.098SN-37 SDMM 17720 Petrous Double-stranded NextSeq 500, Single-end 75 45,454,861 6,933,243 578,639 13.98% 8.35% 0.170SN-38 SDMM 17723 Tooth root Double-stranded NextSeq 500, Single-end 75 32,013,934 7,296,861 142,924 22.35% 1.96% 0.192SN-39 SDMM 17728 Tooth root Double-stranded NextSeq 500, Single-end 75 29,893,062 4,582,602 61,737 15.12% 1.35% 0.121SN-40 SDMM 17732 Tooth root Double-stranded NextSeq 500, Single-end 75 52,282,121 17,800,057 616,545 32.87% 3.46% 0.460SN-41 SDMM 17732 Tooth root Double-stranded NextSeq 500, Single-end 75 26,283,026 978,425 112,059 3.30% 11.45% 0.023SN-43 SDMM 17736 Tooth root Double-stranded NextSeq 500, Single-end 75 31,899,813 2,991,781 66,675 9.17% 2.23% 0.078SN-44 SDMM 17737 Tooth root Double-stranded NextSeq 500, Single-end 75 40,863,296 24,847,857 555,713 59.45% 2.24% 0.651SN-44 SDMM 17737 Tooth root Double-stranded NextSeq 500, Single-end 75 56,087,926 32,371,621 784,112 56.32% 2.42% 0.846SN-44 SDMM 17737 Tooth root Double-stranded NextSeq 500, Single-end 75 586,128,260 395,796,899 46,329,876 59.62% 11.71% 9.361SN-45 SDMM 17739 Tooth root Double-stranded NextSeq 500, Single-end 75 40,711,691 512,370 15,887 1.22% 3.10% 0.013SN-48 SDMM 1963-36-1 Tooth root Double-stranded NextSeq 500, Single-end 75 35,063,469 16,136,964 341,811 45.05% 2.12% 0.423SN-50 MDLH PE7105 Tooth root Double-stranded NextSeq 500, Single-end 75 59,043,953 38,807,734 1,858,896 62.58% 4.79% 0.990SN-51 MDLH PE7106 Tooth root Double-stranded NextSeq 500, Single-end 75 28,500,437 16,594,686 1,672,167 52.36% 10.08% 0.400SN-52 MDLH PE10252 Tooth root Double-stranded NextSeq 500, Single-end 75 59,028,953 17,027,795 641,124 27.76% 3.77% 0.439SN-53 MDLH PE10250 Tooth root Double-stranded NextSeq 500, Single-end 75 56,559,354 23,787,787 875,512 40.51% 3.68% 0.614SN-54 SK 28F-140 ID 113 Tooth root Double-stranded NextSeq 500, Single-end 75 41,517,952 16,778,404 610,530 38.94% 3.64% 0.433SN-55 SK 257-69 Burial \#1 Tooth root Double-stranded NextSeq 500, Single-end 75 30,254,442 1,055,394 26,868 3.40% 2.55% 0.028SN-56 SK 257-76 Burial \#8 Tooth root Double-stranded NextSeq 500, Single-end 75 26,666,327 1,687,232 44,382 6.16% 2.63% 0.044SN-57 SK 257-80 Burial \#12 Tooth root Double-stranded NextSeq 500, Single-end 75 30,370,834 1,619,262 31,540 5.23% 1.95% 0.043SN-58 SK Burial \#16 Tooth root Double-stranded NextSeq 500, Single-end 75 38,990,934 6,538,235 375,217 15.81% 5.74% 0.165SN-59 SK 28F - 137 Tooth root Double-stranded NextSeq 500, Single-end 75 33,857,717 6,469,372 493,249 17.65% 7.62% 0.160SN-60 SK 28F-70 Burial \#2 Rib Double-stranded NextSeq 500, Single-end 75 32,806,084 309,384 6,045 0.92% 1.95% 0.008SN-60 SK 28F-70 Burial \#2 Rib Double-stranded NextSeq 500, Single-end 75 72,730,197 661,767 14,880 0.89% 2.25% 0.017US-14 AMNH 99.1/2270 Tooth root Double-stranded NextSeq 500, Single-end 75 42,942,862 17,250,853 536,311 38.92% 3.11% 0.448JJ004 JL Modern Modern Double-stranded, Y adapters HiSeq2000 n/a n/a n/a n/a n/a n/a n/aJJ064 JL Modern Modern Double-stranded, Y adapters HiSeq2000 n/a n/a n/a n/a n/a n/a n/aJJ155 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 68,800 1668 187 2.42% 11.21% 26.82JJ160* JRJ Modern Modern n/a n/a n/a n/a n/a n/a n/a n/a n/aJJ189 JRJ Modern Modern Double-stranded, Y adapters HiSeq2000 n/a n/a n/a n/a n/a n/a n/aJJ202 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 35,401 4650 389 13.14% 8.37% 77.15JJ220 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 42,768,464 11491 2753 0.03% 23.96% 39.55JJ221 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 45,432,476 13822 5202 0.03% 37.64% 39.02JJ224 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 9,310,723 1851 127 0.02% 6.86% 7.80JJ229 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 87,465 15307 4804 17.50% 31.38% 190.17JJ239 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 10,781,356 6532 888 0.06% 13.59% 25.55JJ249 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 83,001 35030 16852 42.20% 48.11% 329.13JJ253 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 80,690 45476 26020 56.36% 57.22% 352.27JJ263 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 10,206,858 3089 396 0.03% 12.82% 12.19JJ272 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 33,639,406 6395 1083 0.02% 16.94% 24.04JJ273 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 33,881,261 13006 3304 0.04% 25.40% 43.92JJ274 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 43,861,017 6152 977 0.01% 15.88% 23.42JJ275 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 56,980,785 33536 17383 0.06% 51.83% 73.12JJ276 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 61,511 33152 18143 53.90% 54.73% 271.75JJ277 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 79,346 2608 191 3.29% 7.32% 43.76JJ279 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 9,067,093 1760 81 0.02% 4.60% 7.60JJ286 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 29,984,980 11882 3600 0.04% 30.30% 37.49JJ298 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 85,099 15382 5138 18.08% 33.40% 185.48JJ299 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 69,919 35135 18316 50.25% 52.13% 304.53JJ301 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 39,707,788 1103 138 0.00% 12.51% 4.37JJ304 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 75,426 18777 7540 24.89% 40.16% 203.46JJ406 JL Modern Modern Double-stranded, Y adapters Hiseq2000 n/a n/a n/a n/a n/a n/a n/aJJ416 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 72,030 41716 22890 57.91% 54.87% 340.87JJ421 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 82,311 6652 1107 8.08% 16.64% 100.40JJ424 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 54,028 2705 320 5.01% 11.83% 43.18JJ429 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 72,915 12667 3080 17.37% 24.32% 173.58JJ469 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 69,111 16186 5355 23.42% 33.08% 196.11JJ476 JRJ Modern Modern Double-stranded NextSeq 500, Single-end 75 2,035,442 1712 70 0.08% 4.09% 7.43JJ516* JRJ Modern Modern n/a n/a n/a n/a n/a n/a n/a n/a n/aJJ523 JRJ Modern Modern Double-stranded MiSeq Nano, Single-end 300 74,753 3844 397 5.14% 10.33% 62.41JJ536* JRJ Modern Modern n/a n/a n/a n/a n/a n/a n/a n/a n/aJJ540* JRJ Modern Modern n/a n/a n/a n/a n/a n/a n/a n/a n/aJJ547* JRJ Modern Modern n/a n/a n/a n/a n/a n/a n/a n/a n/aJJ548 JL Modern Modern Double-stranded, Y adapters HiSeq2000 n/a n/a n/a n/a n/a n/a n/aJJ558 JL Modern Modern Double-stranded, Y adapters HiSeq2000 n/a n/a n/a n/a n/a n/a n/aJJ564 JL Modern Modern Double-stranded, Y adapters HiSeq2000 n/a n/a n/a n/a n/a n/a n/aJJ565 JL Modern Modern Double-stranded, Y adapters HiSeq2000 n/a n/a n/a n/a n/a n/a n/aJJ576* JRJ Modern Modern n/a n/a n/a n/a n/a n/a n/a n/a n/aJJ577* JRJ Modern Modern n/a n/a n/a n/a n/a n/a n/a n/a n/aJJ581* JRJ Modern Modern n/a n/a n/a n/a n/a n/a n/a n/a n/a

* Sequenced by Family Tree DNA

Note: source abbreviations are SDMM - San Diego Museum of Man, MDLH - Musée de l'Homme, UT - University of Toronto, RM - Ripan Malhi, AMNH - American Museum of Natural History, SK - Susan Kerr (UCLA/Southwest Museum/U.S. NAVY), JRJ - John R. Johnson, JL - John Lindo. Sequences from John Lindo were amplified in four long fragments. Bold indicates samples originally extracted by J.G.L. and further processed and sequenced in Cambridge by C.L.S. For these samples, reads mapping to human are reads mapping to human mitochondrial DNA only.

Table S4.Summary of contamination estimates for genomes generated for this study.

Time Period ID Alternate ID SitemtDNA

CoveragemtDNA

contamination est.Genomic Coverage

X chrom Method 1 Contamination

Method SEX chrom Method

2 ContamMethod 2 SE

Ancient 523a na Palm Site 98.59 0.50% 0.975 0.294% 0.089% 0.326% 0.138%Ancient Ala1 na Síi Túupentak (ALA-565/H) 102.08 0.84% 0.572 N/A N/A N/A N/AAncient B-03 1972-64-1 LC-218 36.98 0.44% 0.567 0.178% 0.031% 0.541% 0.054%Ancient B-04 16697 LC-34 19.49 1.36% 0.144 N/A N/A N/A N/AAncient CH-01 Burial \#1 SBA-06 4.19 0.24% 0.037 N/A N/A N/A N/AAncient CK-09 1001 Lucier 123.20 0.49% 0.169 N/A N/A N/A N/AAncient CK-10 GS7 Lucier 0.94 0.75% 0.036 N/A N/A N/A N/AAncient CK-13 RS14 Lucier 83.04 0.72% 0.363 N/A N/A N/A N/AAncient CR-01 16713 Cueva Valdez 135.44 0.43% 8.365 N/A N/A N/A N/AAncient CT-01 1973-36-1 Catalina Island 105.27 1.33% 6.685 0.548% 0.006% 0.633% 0.012%Ancient CT-02 1986-22-0007-E Catalina Island 8.53 0.92% 0.054 N/A N/A N/A N/AAncient LU-01 GB-33 Lucier 5.75 2.04% 0.026 N/A N/A N/A N/AAncient LU-02 GG-33 Lucier 4.75 0.88% 0.030 N/A N/A N/A N/AAncient LU-06 GG-121 Lucier 23.20 0.84% 0.132 N/A N/A N/A N/AAncient MX-01 2996 Iron Springs Mexico 22.37 0.81% 0.280 1.179% 0.190% 3.739% 0.364%Ancient NC na New Cuyama, CA 172.88 0.40% 1.120 0.890% 0.270% 1.000% 0.447%Ancient PS-02 17749 G-1 19.00 1.73% 0.178 N/A N/A N/A N/AAncient PS-03 17750 G-1 30.37 0.34% 0.254 0.887% 0.146% 2.301% 0.286%Ancient PS-06 17753 G-1 69.83 1.09% 4.124 1.434% 0.013% 1.320% 0.021%Ancient PS-07 17806 G-1 74.05 0.76% 0.595 0.281% 0.047% 0.737% 0.080%Ancient PS-09 17808 G-1 21.62 1.81% 0.223 -1.067% 0.039% -1.067% 0.055%Ancient PS-17 17862 G-1 25.39 0.63% 0.116 N/A N/A N/A N/AAncient PS-18 17863 G-1 61.76 0.23% 0.207 N/A N/A N/A N/AAncient PS-23 17868 G-1 79.12 0.46% 0.089 N/A N/A N/A N/AAncient PS-26 17872 G-1 27.99 0.51% 0.138 6.844% 0.640% 6.757% 0.926%Ancient RM-83 na 05SP-46 (Teston Road Ossuary) 51.86 1.14% 0.675 N/A N/A N/A N/AAncient RM-85 na 11SP-83 (Turnbull Ossuary) 19.00 0.50% 0.043 -0.200% 0.200% -0.200% 0.432%Ancient SC-01 2084 SC-1 29.57 1.36% 0.545 N/A N/A N/A N/AAncient SC-03 2086 SC-2 40.23 0.98% 0.939 N/A N/A N/A N/AAncient SC-04 2087 SC-4 47.40 1.12% 0.709 N/A N/A N/A N/AAncient SC-05 1971-78-1 San Clemente 114.84 1.45% 13.671 N/A N/A N/A N/AAncient SC-06 1972-60-1 Not's Pier 24.32 1.17% 0.432 0.855% 0.077% 1.748% 0.137%Ancient SM-01 PE7066 San Miguel 33.18 1.37% 0.235 -0.340% 0.082% -1.090% 0.033%Ancient SM-02 PE7076 San Miguel 138.64 0.97% 7.387 N/A N/A N/A N/AAncient SN-01 16715 SN-6 13.14 0.79% 0.272 N/A N/A N/A N/AAncient SN-03 16719 SN-6 39.49 1.65% 0.759 N/A N/A N/A N/AAncient SN-04 16732 SN-6 39.12 0.90% 0.125 -1.511% 0.160% -1.511% 0.328%Ancient SN-09 16739 SN-5 13.87 0.34% 0.095 1.824% 0.382% -1.775% 0.132%Ancient SN-10 16741 San Nicolas 36.01 0.95% 0.698 N/A N/A N/A N/AAncient SN-11 16743 San Nicolas 41.95 1.14% 9.058 1.728% 0.008% 1.796% 0.017%Ancient SN-12 17643 SN-19 31.37 0.00% 0.085 N/A N/A N/A N/AAncient SN-13 17644 SN-7-A 23.40 1.71% 1.745 N/A N/A N/A N/AAncient SN-15 17658 SN-21-A 45.88 0.98% 0.550 N/A N/A N/A N/AAncient SN-16 17661 SN-14 / SNI-25 22.45 0.78% 0.287 N/A N/A N/A N/AAncient SN-17 17662 SN-21-A 22.98 1.55% 7.451 1.296% 0.009% 1.271% 0.017%Ancient SN-20 17665 SN-24 7.70 0.63% 0.123 1.702% 0.345% 4.987% 0.683%Ancient SN-25 17684 SN-18 22.89 0.93% 0.168 0.802% 0.185% 4.200% 0.530%Ancient SN-32 17703 SN-23 9.82 0.28% 0.259 2.340% 0.160% 5.339% 0.322%Ancient SN-38 17723 SN-21-A 49.12 0.87% 0.505 1.679% 0.078% 3.180% 0.135%Ancient SN-39 17728 SN-21-A 14.96 0.26% 0.121 N/A N/A N/A N/AAncient SN-40 17732 SN-21-A 56.82 1.47% 0.460 N/A N/A N/A N/AAncient SN-41 17732 SN-21-A 8.57 0.00% 0.023 N/A N/A N/A N/AAncient SN-43 17736 SN-31 15.07 1.14% 0.078 N/A N/A N/A N/AAncient SN-44 17737 SN-21-A 109.94 0.55% 9.361 1.458% 0.008% 1.404% 0.015%Ancient SN-45 17739 SN-20 1.94 1.82% 0.013 N/A N/A N/A N/AAncient SN-50 PE7105 San Nicolas 101.36 1.54% 0.990 N/A N/A N/A N/AAncient SN-51 PE7106 San Nicolas 127.14 1.25% 0.400 N/A N/A N/A N/AAncient SN-52 PE10252 San Nicolas 66.30 1.45% 0.439 N/A N/A N/A N/AAncient SN-53 PE10250 San Nicolas 64.00 1.23% 0.614 N/A N/A N/A N/AAncient SN-54 28F-140 ID 113 SNI-16 86.82 1.30% 0.433 0.338% 0.057% 1.307% 0.111%Ancient SN-55 257-69 Burial \#1 SNI-40 17.29 0.44% 0.028 N/A N/A N/A N/AAncient SN-56 257-76 Burial \#8 SNI-40 95.20 0.35% 0.044 N/A N/A N/A N/AAncient SN-57 257-80 Burial \#12 SNI-40 35.66 0.81% 0.043 N/A N/A N/A N/AAncient SN-58 Burial \#16 SNI-40 105.75 0.35% 0.165 -1.795% 0.211% -3.520% 0.158%Ancient SN-59 28F - 137 SNI-41 112.47 0.79% 0.160 -1.472% 0.058% -1.470% 0.038%Ancient SN-60 28F-70 Burial \#2 SNI-16 8.56 0.35% 0.025 N/A N/A N/A N/AAncient US-14 99.1/2270 Shohola Creek, Pennsylvania 48.16 1.38% 0.448 0.717% 0.065% 0.631% 0.094%Modern JJ155 JJ N/A 6.70 7.39% N/A N/A N/A N/A N/AModern JJ202 JJ N/A 19.29 0.77% N/A N/A N/A N/A N/AModern JJ220 JJ N/A 12.46 7.90% N/A N/A N/A N/A N/AModern JJ221 JJ N/A 78.04 1.62% N/A N/A N/A N/A N/AModern JJ224 JJ N/A 15.61 1.52% N/A N/A N/A N/A N/AModern JJ229 JJ N/A 47.54 4.95% N/A N/A N/A N/A N/AModern JJ239 JJ N/A 51.10 3.32% N/A N/A N/A N/A N/AModern JJ249 JJ N/A 82.28 0.26% N/A N/A N/A N/A N/AModern JJ253 JJ N/A 88.07 0.35% N/A N/A N/A N/A N/A

Modern JJ263 JJ N/A 24.38 1.17% N/A N/A N/A N/A N/AModern JJ272 JJ N/A 48.09 3.13% N/A N/A N/A N/A N/AModern JJ273 JJ N/A 87.83 2.47% N/A N/A N/A N/A N/AModern JJ274 JJ N/A 4.42 1.93% N/A N/A N/A N/A N/AModern JJ275 JJ N/A 78.68 1.35% N/A N/A N/A N/A N/AModern JJ276 JJ N/A 67.94 1.00% N/A N/A N/A N/A N/AModern JJ277 JJ N/A 10.94 4.95% N/A N/A N/A N/A N/AModern JJ279 JJ N/A 15.20 0.62% N/A N/A N/A N/A N/AModern JJ286 JJ N/A 74.98 3.98% N/A N/A N/A N/A N/AModern JJ298 JJ N/A 46.37 1.55% N/A N/A N/A N/A N/AModern JJ299 JJ N/A 76.13 0.37% N/A N/A N/A N/A N/AModern JJ301 JJ N/A 0.62 9.68% N/A N/A N/A N/A N/AModern JJ304 JJ N/A 50.86 0.87% N/A N/A N/A N/A N/AModern JJ416 JJ N/A 85.22 1.21% N/A N/A N/A N/A N/AModern JJ421 JJ N/A 25.10 4.10% N/A N/A N/A N/A N/AModern JJ424 JJ N/A 10.80 2.03% N/A N/A N/A N/A N/AModern JJ429 JJ N/A 43.40 0.49% N/A N/A N/A N/A N/AModern JJ469 JJ N/A 49.03 0.81% N/A N/A N/A N/A N/AModern JJ476 JJ N/A 14.87 0.73% N/A N/A N/A N/A N/AModern JJ523 JJ N/A 15.60 2.45% N/A N/A N/A N/A N/A

Note: mtDNA contamination estimates calculated using a custom script. X chromosome estimates calcuated on bam files using ANGSD.

Table S5a. Definitions of novel mtDNA subclades.

Number of Ind.10

610

32

B2a5b 11488G 52312

104

Table S5b.Mitochondrial DNA haplogroup affiliations and variants detected in the analyses of whole mtDNA sequences.

Sample Coverage Site Haplogroup Terminal branch defining mutations Private Mutations1 B-03 36.98 Comondu, MX C1b11 16295T 72C, 194T, 16218T, 8149G, 6068G, 4533A2 B-04 19.49 Baja C1b41a1* 16319A, 16189C, 204C, 16093C, 492G 11527T, 16399G3 CH-01 4.19 Carpinteria A2 146C, 152C!, 153G, 8027A, 12007A, 16111T nd

4 CK-01 2.57 Lucier C4 6026A, 11969A, 15204C263A, 1719A, 3920T, 7198A, 13674C, 14311C, 14443T, 15148A

5 CK-02 2.96 Lucier C1c 1888A, 15390A 12696C, 13500C, 14832T6 CK-03 1.24 Lucier X2a1c 8842G, 16104T, 16147T 3738T7 CK-04 1.44 Lucier C 3552A, 9545G, 11914A!, 13263G, 14318C, 16327T

8 CK-07 2.24 Lucier C4c1 14433T, 15148A, 1243C1199A, 1719A, 3571T, 3588T, 5845T, 9025A, 13674C, 14311C, 16190T

9 CK-08 4.92 Lucier C1b40* 10031C 9686C, 118A, 12705C!

10 CK-09 123.20 Lucier A2i94A, 960.Xc, 3307.1A, 3308C, 5165T, 6620C, 14280G, 14470C, 15386T, 16325C 14180C

11 CK-10 0.94 Lucier C1b40* 10031C 9686C, 1005C, 2706A!, 7754A, 13909C12 CK-13 83.04 Lucier C1b40* 10031C 12361G, 14719G, 16354T13 CR-01 135.44 Santa Cruz A2 146C, 152C!, 153G, 8027A, 12007A, 16111T 16093C, 12810G14 CT-01 105.27 Santa Catalina C1b41a1a* 204!15 CT-02 8.53 Santa Catalina C1b41a1* 16319A, 16189C, 204C, 16093C, 492G16 JJ004 #N/A Modern A2 146C, 152C!, 153G, 8027A, 12007A, 16111T 16093C, 515, 6248, 13269, 1639017 JJ064 #N/A Modern D1t* 9966A 11002G, 195, 228, 6267, 8705, 1330518 JJ155 6.70 Modern D1 2092T, 16325C 2092C!, 5773A, 9116C, 12390G, 15884A

19 JJ160 #N/A Modern C1d 16051G63C, 64T, 66A, 7469A, 8380Y, 16188T, 16338G

20 JJ189 #N/A Modern C1c6 12414C, 16153A 195!, 1221621 JJ202 19.29 Modern C1b11a* 16295T, 33G, 72C, 146C, 194T, 6755A, 16234T

22 JJ221 78.04 Modern A2h 16526A2864C, 3866C, 4125C, 9716C, 12811C, 14053G, 16327T

23 JJ224 15.61 Modern A2r1 103A, 9518T 4847T24 JJ229 47.54 Modern C1c 1888A, 15390A 4742C, 16248T25 JJ239 51.10 Modern B2b3 13708A 93G, 146C, 334C, 16362C

26 JJ249 82.28 Modern A2v1+152 6491A, 152C42.1C, 980C, 11347G, 16497G, 16512C, 16541G

27 JJ253 88.07 Modern A2 146C, 152C!, 153G, 8027A, 12007A, 16111T 15297C, 16093C28 JJ263 24.38 Modern B2y1 16261T, 3480G 10190G, 10609C, 14572G29 JJ272 48.09 Modern C1c6 12414C, 16153A 8158G, 12216T, 16293G30 JJ273 87.83 Modern B2a 16111T, 16483A 6833G, 16325C, 16512C31 JJ274 4.42 Modern C1c6 12414C, 16153A 195!, 1221632 JJ275 78.68 Modern C1b 493G 492G, 15110A, 16093C, 16319A33 JJ276 67.94 Modern B2a 16111T, 16483A 185A, 189G, 295T, 5987T, 8902A, 15885T34 JJ277 10.94 Modern C1b 493G 72C, 14687G, 16448C35 JJ279 15.20 Modern B2a4 16092C 16147T, 16257T36 JJ286 74.98 Modern B2 8281-8290d, 3547G, 4977C, 6473T, 9950C, 11177T 2092T, 6581G, 9093G, 12757C, 13478T37 JJ298 46.37 Modern B2 8281-8290d, 3547G, 4977C, 6473T, 9950C, 11177T 58C, 6581G, 12757C, 13478T38 JJ299 76.13 Modern B2 8281-8290d, 3547G, 4977C, 6473T, 9950C, 11177T 6133G, 7948T, 11890G, 16319A

39 JJ301 0.62 Modern B2b 6755A131, 143, 195, 4224, 4755, 9540, 10398, 10873, 11101, 16343

40 JJ304 50.86 Modern C1b 493G204C, 492G, 9126C, 11963A, 16093C, 16319A

41 JJ406 #N/A Modern C1b 493G 14386G, 16362C42 JJ416 85.22 Modern D1 2092T, 16325C 9966A, 11092G, 16291T43 JJ421 25.10 Modern B2a 16111T, 16483A 185A, 189G, 295T, 5987T, 8902A, 15885T44 JJ424 10.80 Modern B2a1 10895G 61-62d, 9612A, 12880C45 JJ429 43.40 Modern C1c1b 215G, 5773A 4316G, 8727T, 10005G, 10646A46 JJ469 49.03 Modern D4h3a 3396C, 4025T, 6285A, 8946G, 9458T, 16241G 14287C, 14560A, 16234T47 JJ476 14.87 Modern B2 8281-8290d, 3547G, 4977C, 6473T, 9950C, 11177T 1619T, 8541C, 13434G

C1b40C1b41C1b41aC1b41a1

A2caA2cbA2ccB2y1a

C1b11a

**We propose to redefine B2a5 which is currently defined by five mutations: A189G, C5987T, A11884G, A13221G, and C16278T!. The majority of ancient samples in this study within B2a had two (A189G and C5987) of these five mutations, thus it is proposed that B2a5 should be re-defined by these two mutations only and what is currently called B2a5 be named B2a5a. The majority of the ancient California B2a5 samples then fall into B2a5b defined by and additional transition (A11488G).

204!

Defining VariantsG9966A14016A, 16256T226C, 6137C2308G, 16223C!16261T!, 3480G, 195C, 2968G, 14572G

16295T, 72C, 194T, 33G, 146C, 6755A, 16234T10031C16319A, 16189C, 204C16319A, 16189C, 204C, 16093C16319A, 16189C, 204C, 16093C, 492G

C1b41a1a

Clade NameD1t

48 JJ516 #N/A Modern C1b 493G 15049 JJ523 15.60 Modern D1 2092T, 16325C 9896G, 9966A, 11137C, 16261T, 16291T50 JJ536 #N/A Modern C1b 493G 72C, 9966A, 14687G, 16092C51 JJ540 #N/A Modern C1c6 12414C, 16153A 1047G, 6578G, 8843C, 9948A, 16526A

52 JJ547 #N/A Modern C1b 493G195C, 499A, 9948A, 12408C, 14070G, 16362C, 15097C, 16456A

53 JJ548 #N/A Modern C1b41a1a* 204! 15110A54 JJ558 #N/A Modern C1c1b 215G, 5773A 146C, 16325T!, 4316, 8727, 10005, 1064655 JJ564 #N/A Modern A2 146C, 152C!, 153G, 8027A, 12007A, 16111T 16093C56 JJ565 #N/A Modern A2u1 12906T, 16257T, 16344T 57 JJ576* #N/A Modern C1c1b 215G, 5773A 12630A, 15941C58 JJ577* #N/A Modern C1b11a* 16295T, 33G, 72C, 146C, 194T, 6755A, 16234T59 JJ581 #N/A Modern A2+64 64T 153C, 15670C, 15787C, 15172A, 15924G

60 LU-01 5.75 Lucier C 3552A, 9545G, 11914A!, 13263G, 14318C, 16327T150T, 4702G, 15007T, 15223T, 15326A, 16234T,

61 LU-02 4.75 Lucier A2i94A, 960.Xc, 3307.1A, 3308C, 5165T, 6620C, 14280G, 14470C, 15386T, 16325C

62 LU-03 5.10 Lucier C1d1a1 6297C, 14305A 4769A63 LU-04 1.64 Lucier C nd nd64 LU-05 4.51 Lucier C1b40* 10031C nd65 LU-06 23.20 Lucier C1d1a1 6297C, 14305A66 MX-01 22.37 Iron Springs, MX B2a5a** 189G, 5987T, 11884G, 13221G, 16278T! 1717C, 11302T, 16217T!67 PS-02 22.37 Point Sal D1t* 9966A 9804A, 16291T68 PS-03 30.37 Point Sal A2cc* 2308G, 16223C! 2833G, 8490C, 16342C, 9581C69 PS-04 5.29 Point Sal D1t* 9966A 9804A, 16291T70 PS-06 69.83 Point Sal D1t* 9966A 9804A, 16291T71 PS-07 74.05 Point Sal D1t* 9966A 9804A, 16291T72 PS-09 21.62 Point Sal A2cc* 2308G, 16223C! 2833G, 8490C, 16342C, 9581C73 PS-11 3.43 Point Sal D1t* 9966A 8480T, 4685G, 4692T, 7527A74 PS-12 0.00 Point Sal nd nd nd75 PS-13 1.26 Point Sal nd nd nd76 PS-17 25.39 Point Sal D1t* 9966A 9804A, 16291T77 PS-18 61.76 Point Sal D1t* 9966A 11002G, 8480T78 PS-19 0.00 Point Sal nd nd nd79 PS-22 0.00 Point Sal nd nd nd80 PS-23 79.12 Point Sal D1t* 9966A 11002G, 8480T81 PS-24 3.96 Point Sal D1t* 9966A 9804A, 16291T82 PS-26 27.99 Point Sal D1t* 9966A 11002G, 8480N83 PS-30 0.00 Point Sal nd nd nd84 PS-34 15.15 Point Sal A2cc* 2308G, 16223C! 4135C85 SC-01 29.57 San Clemente C1b41a1* 16319A, 16189C, 204C, 16093C, 492G 16093!86 SC-02 0.11 San Clemente nd nd nd87 SC-03 40.23 San Clemente C1b41* 16319A, 16189C, 204C 16319A, 16189C, 204C88 SC-04 47.40 San Clemente B2a5** 189G, 5987T 143A, 13105G, 14152G89 SC-05 114.84 San Clemente C1b41a1* 16319A, 16189C, 204C, 16093C, 492G 9633A, 16129A, 16183C, 16357C90 SC-06 24.32 San Clemente C1b41a* 16319A, 16189C, 204C, 16093C 3116T, 6216C, 16327C!91 SC-07 27.13 San Clemente C1b41a1a* 204!92 SM-01 33.18 San Miguel A2 146C, 152C!, 153G, 8027A, 12007A, 16111T 16093C, 7966A93 SM-02 138.64 San Miguel A2 146C, 152C!, 153G, 8027A, 12007A, 16111T 16093C, 14502C94 SN-01 13.14 San Nicolas B2a5b* 11488G 10310A95 SN-02 19.48 San Nicolas C1b41a1* 16319A, 16189C, 204C, 16093C, 492G 9633A96 SN-03 39.49 San Nicolas C1b41a1* 16319A, 16189C, 204C, 16093C, 492G 9633A, 16129A, 16183C, 16357C97 SN-04 39.12 San Nicolas A2ca* 14016A, 16256T98 SN-09 13.87 San Nicolas B2a5b* 11488G 10310A99 SN-10 36.01 San Nicolas B2a5b* 11488G

100 SN-11 41.95 San Nicolas D1 2092T, 16325C 9072G, 16319A101 SN-12 41.95 San Nicolas C1b 493G 204C, 492G, 4646C ,16093C, 16319A

102 SN-13 31.37 San Nicolas C1b 493G204C, 492G, 4105G, 4646C, 5263T, 16093C, 16319A

103 SN-15 45.88 San Nicolas C1b41a1* 16319A, 16189C, 204C, 16093C, 492G104 SN-16 22.45 San Nicolas B2a5b* 11488G105 SN-17 22.98 San Nicolas A2ca* 14016A, 16256T 146T!, 5899d106 SN-20 7.70 San Nicolas A2cb* 226C, 6137C 195C, 14130T107 SN-25 22.89 San Nicolas A2cb* 226C, 6137C108 SN-31 1.11 San Nicolas A2 146C, 152C!, 153G, 8027A, 12007A, 16111T nd109 SN-32 9.82 San Nicolas A2cb* 226C, 6137C 225A110 SN-37 12.39 San Nicolas A2ca* 14016A, 16256T 146T!, 5899d111 SN-38 49.12 San Nicolas C1b41a1* 16319A, 16189C, 204C, 16093C, 492G112 SN-39 14.96 San Nicolas A2cb* 226C, 6137C 5964C113 SN-40 56.82 San Nicolas A2cb* 226C, 6137C 5964C114 SN-41 8.57 San Nicolas A2ca* 14016A, 16256T 146T!, 5899d, 8974T, 8994A115 SN-43 15.07 San Nicolas C1b41a* 16319A, 16189C, 204C, 16093C 16319A, 16189C, 204C, 16093C116 SN-44 109.94 San Nicolas A2cb* 226C, 6137C 5964C117 SN-45 1.94 San Nicolas A2 146C, 152C!, 153G, 8027A, 12007A, 16111T 709A, 16091T, 10725A, 11992C118 SN-48 28.68 San Nicolas A2 146C, 152C!, 153G, 8027A, 12007A, 16111T119 SN-50 101.36 San Nicolas C1b41a1* 16319A, 16189C, 204C, 16093C, 492G 1193C120 SN-51 127.14 San Nicolas C1b41a1* 16319A, 16189C, 204C, 16093C, 492G 1193C121 SN-52 66.30 San Nicolas B2y1a* 16261T!, 3480G, 195C, 2968G, 14572G 11998, 6570T, 16183C122 SN-53 64.00 San Nicolas B2a5b* 11488G 204C123 SN-54 86.82 San Nicolas A2cb* 226C, 6137C 3900T, 5964A124 SN-55 17.29 San Nicolas A2 146C, 152C!, 153G, 8027A, 12007A, 16111T 151T, 393C125 SN-56 95.20 San Nicolas A2cb* 226C, 6137C 3900T, 961C126 SN-57 35.66 San Nicolas A2ca* 14016A, 16256T 146T!127 SN-58 105.75 San Nicolas A2ca* 14016A, 16256T 146T!, 5899d

128 SN-59 112.47 San Nicolas A2cb* 226C, 6137C 5964C129 SN-60 8.56 San Nicolas A2cb* 226C, 6137C 5964C130 US-14 48.16 Shohola Creek, PA U4c1a 4811G, 6146G, 9070G, 11009C, 14866T, 16179T, 3654T 2905G, 6480A 131 523a 98.59 Palm Site, Alaska A2a 3330T, 16192T132 Ala1 102.08 Síi Túupentak (ALA-565/H) C1c1b 215G, 5773A 6368A, 11518A, 16248T, 16293G

133 NC 172.88 New Cuyama, CA D1 2092T, 16325C146C, 4219A, 10310A, 11995T, 15712G, 16263C, 16359C

134 RM-83 51.86 05SP-46 (Teston Road Ossuary) A2i94A, 960.Xc, 3307.1A, 3308C, 5165T, 6620C, 14280G, 14470C, 15386T, 16325C

135 RM-85 19.00 11SP-83 (Turnbull Ossuary) C1c 1888A, 15390A 150T, 152C, 4702G, 15007T

Note: X is a deletion, .1 is an insertion, nd = no data either due to low coverage or contamination. * New subclades.

Table S6.

Outgroup A X Y D Value Z-score ABBA BABA Total SNPs

Mbuti_Pygmies Chipewyan_masked Mixe 939 -0.0057 -0.862 2,595 2,625 39,864 Mbuti_Pygmies Chukchis Mixe 939 0.0074 1.408 4,044 3,985 61,195 Mbuti_Pygmies East_Greenlanders Mixe 939 0.0052 0.876 4,082 4,040 61,195 Mbuti_Pygmies Evens Mixe 939 -0.0006 -0.111 3,966 3,971 61,195 Mbuti_Pygmies Saqqaq Mixe 939 0.0014 0.156 2,466 2,459 38,908 Mbuti_Pygmies Chipewyan_masked Mixe 523a 0.0108 2.333 4,844 4,740 72,266 Mbuti_Pygmies Chukchis Mixe 523a 0.0265 6.718 7,588 7,195 110,761 Mbuti_Pygmies East_Greenlanders Mixe 523a 0.0277 6.213 7,667 7,253 110,761 Mbuti_Pygmies Evens Mixe 523a 0.0230 5.590 7,483 7,146 110,761 Mbuti_Pygmies Naukan Mixe 523a 0.0295 7.137 7,671 7,232 110,761 Mbuti_Pygmies Saqqaq Mixe 523a 0.0374 5.104 4,765 4,421 70,588 Mbuti_Pygmies Chipewyan_masked Mixe 939_trim -0.0052 -0.778 2,594 2,621 39,869 Mbuti_Pygmies Chukchis Mixe 939_trim 0.0064 1.205 4,035 3,984 61,199 Mbuti_Pygmies East_Greenlanders Mixe 939_trim 0.0026 0.435 4,066 4,044 61,199 Mbuti_Pygmies Evens Mixe 939_trim -0.0010 -0.174 3,960 3,968 61,199 Mbuti_Pygmies Saqqaq Mixe 939_trim -0.0006 -0.066 2,458 2,461 38,913 Mbuti_Pygmies Chipewyan_masked Mixe Ala1 -0.0055 -0.951 2,794 2,824 45,376 Mbuti_Pygmies Chukchis Mixe Ala1 -0.0063 -1.387 4,273 4,327 69,663 Mbuti_Pygmies East_Greenlanders Mixe Ala1 -0.0052 -0.980 4,313 4,358 69,663 Mbuti_Pygmies Evens Mixe Ala1 -0.0063 -1.366 4,227 4,280 69,663 Mbuti_Pygmies Saqqaq Mixe Ala1 -0.0006 -0.075 2,646 2,649 44,035 Mbuti_Pygmies Chipewyan_masked Mixe Alaskan_Inuit -0.0210 -5.896 7,901 8,240 119,952 Mbuti_Pygmies Chukchis Mixe Alaskan_Inuit 0.0477 15.270 13,073 11,883 183,600 Mbuti_Pygmies East_Greenlanders Mixe Alaskan_Inuit 0.0842 21.575 13,694 11,566 183,600 Mbuti_Pygmies Evens Mixe Alaskan_Inuit 0.0280 8.719 12,658 11,969 183,600 Mbuti_Pygmies Naukan Mixe Alaskan_Inuit 0.0640 19.294 13,393 11,781 183,600 Mbuti_Pygmies Saqqaq Mixe Alaskan_Inuit 0.0540 10.106 8,224 7,382 117,979 Mbuti_Pygmies Chipewyan_masked Mixe Algonquin_masked 0.0247 8.135 7,627 7,259 115,080 Mbuti_Pygmies Chukchis Mixe Algonquin_masked 0.0000 0.014 7,286 7,286 115,080 Mbuti_Pygmies East_Greenlanders Mixe Algonquin_masked -0.0030 -0.989 7,312 7,356 115,080 Mbuti_Pygmies Evens Mixe Algonquin_masked 0.0015 0.553 7,230 7,208 115,080 Mbuti_Pygmies Saqqaq Mixe Algonquin_masked 0.0074 1.734 6,915 6,814 109,282 Mbuti_Pygmies Chipewyan_masked Mixe Anzick-1 0.0041 0.950 4,785 4,746 78,494 Mbuti_Pygmies Chukchis Mixe Anzick-1 0.0023 0.607 7,360 7,326 120,505 Mbuti_Pygmies East_Greenlanders Mixe Anzick-1 0.0041 0.947 7,433 7,371 120,505 Mbuti_Pygmies Evens Mixe Anzick-1 0.0004 0.102 7,270 7,264 120,505 Mbuti_Pygmies Saqqaq Mixe Anzick-1 0.0059 1.067 4,608 4,554 77,417 Mbuti_Pygmies Chipewyan_masked Mixe Anzick-1_trim -0.0080 -1.815 7,463 7,583 119,319 Mbuti_Pygmies Chukchis Mixe Anzick-1_trim -0.0103 -2.817 11,454 11,693 182,678 Mbuti_Pygmies East_Greenlanders Mixe Anzick-1_trim -0.0103 -2.431 11,554 11,796 182,678 Mbuti_Pygmies Evens Mixe Anzick-1_trim -0.0089 -2.366 11,349 11,552 182,678 Mbuti_Pygmies Saqqaq Mixe Anzick-1_trim -0.0067 -1.118 7,151 7,248 117,483 Mbuti_Pygmies Chipewyan_masked Mixe Arara 0.0097 2.644 6,891 6,759 114,578 Mbuti_Pygmies Saqqaq Mixe Cabecar 0.0009 0.291 7,076 7,064 118,001 Mbuti_Pygmies Chipewyan_masked Mixe Catalina 0.0006 0.158 7,401 7,392 119,026 Mbuti_Pygmies Chukchis Mixe Catalina 0.0019 0.562 11,338 11,296 182,166 Mbuti_Pygmies East_Greenlanders Mixe Catalina -0.0021 -0.544 11,380 11,428 182,166 Mbuti_Pygmies Evens Mixe Catalina -0.0041 -1.207 11,149 11,241 182,166 Mbuti_Pygmies Saqqaq Mixe Catalina 0.0031 0.541 7,099 7,055 117,139 Mbuti_Pygmies Chipewyan_masked Mixe Catalina_trim 0.0007 0.180 7,365 7,355 118,353 Mbuti_Pygmies Chukchis Mixe Catalina_trim 0.0004 0.125 11,267 11,258 181,144 Mbuti_Pygmies East_Greenlanders Mixe Catalina_trim -0.0006 -0.160 11,341 11,354 181,144 Mbuti_Pygmies Evens Mixe Catalina_trim -0.0038 -1.194 11,099 11,184 181,144 Mbuti_Pygmies Saqqaq Mixe Catalina_trim 0.0018 0.324 7,054 7,028 116,502 Mbuti_Pygmies Chukchis Mixe Chipewyan_masked 0.0073 3.711 7,784 7,671 119,974 Mbuti_Pygmies East_Greenlanders Mixe Chipewyan_masked 0.0037 1.605 7,809 7,751 119,974 Mbuti_Pygmies Evens Mixe Chipewyan_masked 0.0076 3.872 7,718 7,602 119,974 Mbuti_Pygmies Naukan Mixe Chipewyan_masked 0.0053 2.556 7,810 7,729 119,974

Results of D-test for Athabaskan (Chipewyan), Paleo- (Saqqaq) and Neo- (Greenlander,Naukan,Chukchi) Eskimo ancestry in Native American populations.

Mbuti_Pygmies Saqqaq Mixe Chipewyan_masked 0.0111 3.551 7,357 7,196 113,961 Mbuti_Pygmies Chipewyan_masked Mixe Chumash 0.0191 0.512 62 59 1,012 Mbuti_Pygmies Chipewyan_masked Mixe Chumash_trim 0.0003 0.008 53 53 906 Mbuti_Pygmies Chukchis Mixe Chumash_trim -0.0172 -0.581 81 84 1,381 Mbuti_Pygmies Evens Mixe Chumash_trim 0.0234 0.774 84 80 1,381 Mbuti_Pygmies Chipewyan_masked Mixe Cree_masked 0.0229 6.797 6,780 6,476 102,852 Mbuti_Pygmies Chukchis Mixe Cree_masked -0.0022 -0.767 6,474 6,502 102,852 Mbuti_Pygmies East_Greenlanders Mixe Cree_masked -0.0023 -0.671 6,513 6,543 102,852 Mbuti_Pygmies Evens Mixe Cree_masked 0.0003 0.114 6,432 6,428 102,852 Mbuti_Pygmies Saqqaq Mixe Cree_masked 0.0025 0.538 6,116 6,085 97,591 Mbuti_Pygmies Chipewyan_masked Mixe EarlySN -0.0070 -2.343 7,438 7,543 119,963 Mbuti_Pygmies Chukchis Mixe EarlySN -0.0045 -1.719 11,420 11,523 183,615 Mbuti_Pygmies East_Greenlanders Mixe EarlySN -0.0037 -1.187 11,514 11,600 183,615 Mbuti_Pygmies Evens Mixe EarlySN -0.0082 -3.062 11,255 11,442 183,615 Mbuti_Pygmies Saqqaq Mixe EarlySN -0.0042 -1.021 7,138 7,198 117,994 Mbuti_Pygmies Chipewyan_masked Mixe EarlySN_trim -0.0067 -2.193 7,429 7,530 119,780 Mbuti_Pygmies Chukchis Mixe EarlySN_trim -0.0035 -1.289 11,418 11,499 183,359 Mbuti_Pygmies East_Greenlanders Mixe EarlySN_trim -0.0020 -0.592 11,522 11,567 183,359 Mbuti_Pygmies Evens Mixe EarlySN_trim -0.0072 -2.566 11,255 11,419 183,359 Mbuti_Pygmies Saqqaq Mixe EarlySN_trim -0.0029 -0.666 7,140 7,181 117,824 Mbuti_Pygmies Chukchis Mixe East_Greenland 0.0392 9.918 13,172 12,178 183,570 Mbuti_Pygmies Naukan Mixe East_Greenland 0.0543 12.208 13,473 12,085 183,570 Mbuti_Pygmies Saqqaq Mixe East_Greenland 0.0468 7.046 8,300 7,557 117,966 Mbuti_Pygmies Chukchis Mixe East_Greenlanders 0.0535 21.828 13,209 11,867 183,632 Mbuti_Pygmies Evens Mixe East_Greenlanders 0.0275 11.255 12,733 12,052 183,633 Mbuti_Pygmies Naukan Mixe East_Greenlanders 0.0710 25.768 13,549 11,753 183,632 Mbuti_Pygmies Saqqaq Mixe East_Greenlanders 0.0659 15.984 8,355 7,322 118,000 Mbuti_Pygmies Chukchis Mixe Enoque65 0.0009 0.072 537 536 8,881 Mbuti_Pygmies Chukchis Mixe Enoque65_trim 0.0009 0.076 537 536 8,882 Mbuti_Pygmies Chipewyan_masked Mixe ESN -0.0097 -3.067 7,410 7,555 119,809 Mbuti_Pygmies Chukchis Mixe ESN -0.0053 -1.928 11,406 11,528 183,399 Mbuti_Pygmies East_Greenlanders Mixe ESN -0.0039 -1.171 11,508 11,598 183,399 Mbuti_Pygmies Evens Mixe ESN -0.0084 -2.986 11,250 11,440 183,399 Mbuti_Pygmies Saqqaq Mixe ESN -0.0044 -1.020 7,131 7,195 117,845 Mbuti_Pygmies Chukchis Mixe Evenkis 0.0020 0.915 13,207 13,155 183,633 Mbuti_Pygmies Chipewyan_masked Mixe IslandChumash 0.0021 0.685 7,448 7,417 119,956 Mbuti_Pygmies Chukchis Mixe IslandChumash 0.0024 0.901 11,387 11,333 183,610 Mbuti_Pygmies East_Greenlanders Mixe IslandChumash 0.0070 2.323 11,534 11,374 183,610 Mbuti_Pygmies Evens Mixe IslandChumash 0.0007 0.265 11,253 11,237 183,610 Mbuti_Pygmies Saqqaq Mixe IslandChumash 0.0038 0.910 7,140 7,086 117,992 Mbuti_Pygmies Chipewyan_masked Mixe IslandChumash_trim 0.0018 0.539 7,244 7,218 117,079 Mbuti_Pygmies Chukchis Mixe IslandChumash_trim 0.0044 1.538 11,122 11,025 179,291 Mbuti_Pygmies East_Greenlanders Mixe IslandChumash_trim 0.0083 2.531 11,257 11,072 179,291 Mbuti_Pygmies Evens Mixe IslandChumash_trim 0.0024 0.832 10,991 10,938 179,291 Mbuti_Pygmies Saqqaq Mixe IslandChumash_trim 0.0098 2.072 7,007 6,872 115,324 Mbuti_Pygmies Chipewyan_masked Mixe Kennewick -0.0161 -3.206 4,462 4,608 70,716 Mbuti_Pygmies Chukchis Mixe Kennewick -0.0101 -2.534 6,862 7,003 108,064 Mbuti_Pygmies East_Greenlanders Mixe Kennewick -0.0126 -2.682 6,901 7,078 108,064 Mbuti_Pygmies Evens Mixe Kennewick -0.0058 -1.352 6,837 6,917 108,064 Mbuti_Pygmies Naukan Mixe Kennewick -0.0129 -3.028 6,886 7,066 108,064 Mbuti_Pygmies Saqqaq Mixe Kennewick -0.0164 -2.308 4,211 4,352 68,793 Mbuti_Pygmies Chipewyan_masked Mixe Kennewick_trim -0.0189 -3.841 4,453 4,624 70,719 Mbuti_Pygmies Chukchis Mixe Kennewick_trim -0.0123 -3.104 6,850 7,020 108,062 Mbuti_Pygmies East_Greenlanders Mixe Kennewick_trim -0.0142 -3.038 6,891 7,089 108,062 Mbuti_Pygmies Evens Mixe Kennewick_trim -0.0097 -2.319 6,813 6,947 108,062 Mbuti_Pygmies Naukan Mixe Kennewick_trim -0.0158 -3.715 6,867 7,087 108,062 Mbuti_Pygmies Saqqaq Mixe Kennewick_trim -0.0173 -2.434 4,209 4,358 68,800 Mbuti_Pygmies Chipewyan_masked Mixe LateSN -0.0022 -0.974 7,482 7,514 119,972 Mbuti_Pygmies Chukchis Mixe LateSN -0.0011 -0.555 11,465 11,489 183,631 Mbuti_Pygmies East_Greenlanders Mixe LateSN -0.0017 -0.708 11,544 11,583 183,631 Mbuti_Pygmies Evens Mixe LateSN -0.0021 -1.078 11,334 11,383 183,631 Mbuti_Pygmies Saqqaq Mixe LateSN 0.0011 0.337 7,184 7,168 118,000 Mbuti_Pygmies Chipewyan_masked Mixe LateSN_trim -0.0011 -0.468 7,445 7,462 119,257 Mbuti_Pygmies Chukchis Mixe LateSN_trim -0.0005 -0.247 11,408 11,420 182,553 Mbuti_Pygmies East_Greenlanders Mixe LateSN_trim -0.0002 -0.071 11,497 11,501 182,553

Mbuti_Pygmies Evens Mixe LateSN_trim -0.0018 -0.841 11,275 11,316 182,553 Mbuti_Pygmies Saqqaq Mixe LateSN_trim 0.0028 0.767 7,151 7,111 117,318 Mbuti_Pygmies Chipewyan_masked Mixe Lucier -0.0041 -1.030 5,262 5,305 82,469 Mbuti_Pygmies Chukchis Mixe Lucier -0.0097 -3.069 7,984 8,141 126,055 Mbuti_Pygmies East_Greenlanders Mixe Lucier -0.0137 -3.669 8,005 8,228 126,055 Mbuti_Pygmies Evens Mixe Lucier -0.0051 -1.581 7,935 8,017 126,055 Mbuti_Pygmies Naukan Mixe Lucier -0.0130 -3.858 8,007 8,218 126,055 Mbuti_Pygmies Saqqaq Mixe Lucier -0.0028 -0.485 5,086 5,115 81,330 Mbuti_Pygmies Chipewyan_masked Mixe Lucier_trim -0.0063 -1.484 4,588 4,646 71,778 Mbuti_Pygmies Chukchis Mixe Lucier_trim -0.0126 -3.748 6,955 7,133 109,793 Mbuti_Pygmies East_Greenlanders Mixe Lucier_trim -0.0169 -4.293 6,974 7,215 109,793 Mbuti_Pygmies Evens Mixe Lucier_trim -0.0061 -1.765 6,926 7,011 109,793 Mbuti_Pygmies Saqqaq Mixe Lucier_trim -0.0088 -1.385 4,407 4,485 70,801 Mbuti_Pygmies Chipewyan_masked Mixe NewCuyama -0.0057 -1.106 4,102 4,148 66,808 Mbuti_Pygmies Chukchis Mixe NewCuyama -0.0027 -0.643 6,302 6,336 102,278 Mbuti_Pygmies East_Greenlanders Mixe NewCuyama 0.0023 0.490 6,386 6,356 102,278 Mbuti_Pygmies Evens Mixe NewCuyama -0.0034 -0.817 6,231 6,274 102,278 Mbuti_Pygmies Saqqaq Mixe NewCuyama 0.0069 0.933 4,030 3,975 66,516 Mbuti_Pygmies Chipewyan_masked Mixe Northern_Athabascans_1 0.0311 13.182 8,053 7,567 119,974 Mbuti_Pygmies Chukchis Mixe Northern_Athabascans_1 0.0110 5.174 12,069 11,807 183,633 Mbuti_Pygmies East_Greenlanders Mixe Northern_Athabascans_1 0.0111 4.342 12,167 11,899 183,633 Mbuti_Pygmies Evens Mixe Northern_Athabascans_1 0.0068 3.132 11,886 11,724 183,633 Mbuti_Pygmies Naukan Mixe Northern_Athabascans_1 0.0103 4.551 12,138 11,889 183,633 Mbuti_Pygmies Saqqaq Mixe Northern_Athabascans_1 0.0109 3.335 7,532 7,369 118,001 Mbuti_Pygmies Chipewyan_masked Mixe Northern_Athabascans_2 0.0287 7.275 7,995 7,549 119,949 Mbuti_Pygmies Chukchis Mixe Northern_Athabascans_2 0.0082 2.494 11,972 11,777 183,598 Mbuti_Pygmies East_Greenlanders Mixe Northern_Athabascans_2 0.0064 1.609 12,041 11,887 183,598 Mbuti_Pygmies Evens Mixe Northern_Athabascans_2 0.0053 1.562 11,804 11,680 183,598 Mbuti_Pygmies Naukan Mixe Northern_Athabascans_2 0.0092 2.697 12,068 11,847 183,598 Mbuti_Pygmies Saqqaq Mixe Northern_Athabascans_2 0.0075 1.444 7,495 7,383 117,980 Mbuti_Pygmies Chipewyan_masked Mixe Northern_Athabascans_3 0.0509 14.283 8,332 7,525 119,956 Mbuti_Pygmies Chukchis Mixe Northern_Athabascans_3 0.0064 2.054 12,134 11,980 183,597 Mbuti_Pygmies East_Greenlanders Mixe Northern_Athabascans_3 0.0028 0.766 12,184 12,116 183,597 Mbuti_Pygmies Evens Mixe Northern_Athabascans_3 0.0059 1.882 11,995 11,854 183,597 Mbuti_Pygmies Naukan Mixe Northern_Athabascans_3 0.0075 2.274 12,227 12,045 183,597 Mbuti_Pygmies Saqqaq Mixe Northern_Athabascans_3 0.0080 1.619 7,591 7,471 117,984 Mbuti_Pygmies Chipewyan_masked Mixe Ojibwa_masked 0.0163 6.168 7,591 7,348 116,578 Mbuti_Pygmies Chukchis Mixe Ojibwa_masked 0.0019 0.827 7,336 7,308 116,578 Mbuti_Pygmies East_Greenlanders Mixe Ojibwa_masked -0.0008 -0.300 7,368 7,381 116,578 Mbuti_Pygmies Evens Mixe Ojibwa_masked 0.0037 1.643 7,285 7,231 116,578 Mbuti_Pygmies Saqqaq Mixe Ojibwa_masked 0.0075 1.995 6,953 6,850 110,797 Mbuti_Pygmies Chipewyan_masked Mixe Pericu 0.0046 0.885 3,740 3,706 60,192 Mbuti_Pygmies Chukchis Mixe Pericu 0.0004 0.091 5,705 5,701 92,231 Mbuti_Pygmies East_Greenlanders Mixe Pericu 0.0025 0.550 5,765 5,736 92,231 Mbuti_Pygmies Evens Mixe Pericu 0.0014 0.332 5,654 5,638 92,231 Mbuti_Pygmies Saqqaq Mixe Pericu 0.0025 0.330 3,599 3,581 59,573 Mbuti_Pygmies Chukchis Mixe Pericu_trim 0.0049 1.171 5,109 5,059 82,537 Mbuti_Pygmies East_Greenlanders Mixe Pericu_trim 0.0073 1.558 5,162 5,087 82,537 Mbuti_Pygmies Evens Mixe Pericu_trim 0.0047 1.095 5,058 5,010 82,537 Mbuti_Pygmies Saqqaq Mixe Pericu_trim 0.0103 1.316 3,237 3,172 53,331 Mbuti_Pygmies Chipewyan_masked Mixe PointSal -0.0025 -0.777 7,317 7,354 118,254 Mbuti_Pygmies Chukchis Mixe PointSal -0.0007 -0.267 11,218 11,234 181,038 Mbuti_Pygmies East_Greenlanders Mixe PointSal -0.0008 -0.239 11,303 11,319 181,038 Mbuti_Pygmies Evens Mixe PointSal -0.0012 -0.423 11,098 11,124 181,038 Mbuti_Pygmies Saqqaq Mixe PointSal 0.0036 0.795 7,045 6,994 116,403 Mbuti_Pygmies Chipewyan_masked Mixe PointSal_trim -0.0020 -0.611 7,076 7,104 114,164 Mbuti_Pygmies Chukchis Mixe PointSal_trim -0.0014 -0.481 10,844 10,874 174,882 Mbuti_Pygmies East_Greenlanders Mixe PointSal_trim 0.0001 0.019 10,940 10,939 174,882 Mbuti_Pygmies Evens Mixe PointSal_trim -0.0027 -0.937 10,718 10,776 174,882 Mbuti_Pygmies Saqqaq Mixe PointSal_trim 0.0010 0.214 6,802 6,788 112,505 Mbuti_Pygmies Chipewyan_masked Mixe RM-83_trim -0.0054 -0.940 2,933 2,965 45,917 Mbuti_Pygmies Chukchis Mixe RM-83_trim -0.0146 -3.142 4,437 4,568 70,452 Mbuti_Pygmies East_Greenlanders Mixe RM-83_trim -0.0188 -3.517 4,455 4,626 70,452 Mbuti_Pygmies Evens Mixe RM-83_trim -0.0108 -2.277 4,409 4,505 70,452 Mbuti_Pygmies Naukan Mixe RM-83_trim -0.0178 -3.563 4,455 4,617 70,452

Mbuti_Pygmies Saqqaq Mixe RM-83_trim -0.0083 -0.972 2,808 2,855 45,419 Mbuti_Pygmies Chipewyan_masked Mixe RM-85_trim -0.0137 -0.700 213 219 3,386 Mbuti_Pygmies Chukchis Mixe RM-85_trim -0.0131 -0.843 320 328 5,072 Mbuti_Pygmies East_Greenlanders Mixe RM-85_trim -0.0201 -1.172 317 330 5,072 Mbuti_Pygmies Evens Mixe RM-85_trim 0.0007 0.045 321 320 5,072 Mbuti_Pygmies Saqqaq Mixe RM-85_trim 0.0219 0.715 216 206 3,438 Mbuti_Pygmies Chipewyan_masked Mixe SanClemente -0.0025 -0.833 7,478 7,515 119,826 Mbuti_Pygmies Chukchis Mixe SanClemente -0.0047 -1.872 11,421 11,530 183,407 Mbuti_Pygmies East_Greenlanders Mixe SanClemente -0.0055 -1.838 11,505 11,631 183,407 Mbuti_Pygmies Evens Mixe SanClemente -0.0066 -2.511 11,281 11,430 183,407 Mbuti_Pygmies Saqqaq Mixe SanClemente -0.0028 -0.657 7,153 7,193 117,884 Mbuti_Pygmies Chipewyan_masked Mixe SanClemente_trim -0.0009 -0.276 7,473 7,486 119,422 Mbuti_Pygmies Chukchis Mixe SanClemente_trim -0.0019 -0.709 11,418 11,461 182,810 Mbuti_Pygmies East_Greenlanders Mixe SanClemente_trim -0.0035 -1.114 11,491 11,571 182,810 Mbuti_Pygmies Evens Mixe SanClemente_trim -0.0038 -1.406 11,281 11,368 182,810 Mbuti_Pygmies Saqqaq Mixe SanClemente_trim -0.0030 -0.670 7,140 7,184 117,525 Mbuti_Pygmies Chukchis Mixe Saqqaq 0.0187 5.085 8,461 8,151 118,001 Mbuti_Pygmies East_Greenlanders Mixe Saqqaq 0.0007 0.145 8,344 8,333 118,001 Mbuti_Pygmies Evens Mixe Saqqaq 0.0333 8.721 8,518 7,969 118,001 Mbuti_Pygmies Chukchis Mixe Saqqaq_trim 0.0214 5.863 12,722 12,190 174,170 Mbuti_Pygmies East_Greenlanders Mixe Saqqaq_trim 0.0022 0.500 12,550 12,494 174,170 Mbuti_Pygmies Evens Mixe Saqqaq_trim 0.0374 10.261 12,809 11,886 174,170 Mbuti_Pygmies Chipewyan_masked Mixe Southern_Athabascans_1 0.0164 4.994 7,482 7,240 117,187 Mbuti_Pygmies Chukchis Mixe Southern_Athabascans_1 0.0036 1.231 11,293 11,211 179,270 Mbuti_Pygmies East_Greenlanders Mixe Southern_Athabascans_1 0.0035 0.954 11,378 11,300 179,270 Mbuti_Pygmies Evens Mixe Southern_Athabascans_1 0.0012 0.395 11,149 11,122 179,270 Mbuti_Pygmies Saqqaq Mixe Southern_Athabascans_1 0.0070 1.528 7,085 6,987 115,299 Mbuti_Pygmies Chipewyan_masked Mixe Splatsin 0.0148 5.136 7,918 7,686 119,611 Mbuti_Pygmies Chukchis Mixe Splatsin 0.0071 2.888 12,016 11,847 183,148 Mbuti_Pygmies East_Greenlanders Mixe Splatsin 0.0032 1.094 12,062 11,985 183,148 Mbuti_Pygmies Evens Mixe Splatsin 0.0061 2.525 11,876 11,731 183,148 Mbuti_Pygmies Saqqaq Mixe Splatsin 0.0100 2.578 7,546 7,396 117,651 Mbuti_Pygmies East_Greenlanders Mixe Tepehuano -0.0012 -0.565 11,411 11,439 183,633 Mbuti_Pygmies Chipewyan_masked Mixe Tlingit 0.0223 10.327 7,940 7,593 119,974 Mbuti_Pygmies Chukchis Mixe Tlingit 0.0118 6.022 12,022 11,741 183,633 Mbuti_Pygmies East_Greenlanders Mixe Tlingit 0.0158 6.747 12,175 11,795 183,633 Mbuti_Pygmies Evens Mixe Tlingit 0.0049 2.388 11,806 11,691 183,633 Mbuti_Pygmies Naukan Mixe Tlingit 0.0146 6.922 12,140 11,791 183,633 Mbuti_Pygmies Saqqaq Mixe Tlingit 0.0075 2.527 7,467 7,356 118,001 Mbuti_Pygmies Chukchis Mixe WestGreenland 0.0358 9.423 13,178 12,267 183,565 Mbuti_Pygmies East_Greenlanders Mixe WestGreenland 0.1011 20.029 14,243 11,628 183,565 Mbuti_Pygmies Evens Mixe WestGreenland 0.0143 3.866 12,734 12,374 183,565 Mbuti_Pygmies Naukan Mixe WestGreenland 0.0522 12.263 13,508 12,167 183,565 Mbuti_Pygmies Saqqaq Mixe WestGreenland 0.0436 6.693 8,289 7,597 117,963 Mbuti Chukchis Mixe Yaghan 0.0041 1.319 11,312 11,220 183,431 Mbuti_Pygmies East_Greenlanders Mixe Yaghan 0.0116 3.064 11,494 11,229 183,431 Mbuti Evens Mixe Yaghan 0.0063 1.956 11,218 11,079 183,431 Mbuti Naukan Mixe Yaghan 0.0048 1.430 11,392 11,284 183,431

Note: trim indicates samples were trimmed an extra 3bp at each end to check for the influence of terminal damage on results. Blue highlights Z-score over |3|. A negative Z-score in dicates that A shares more with X than Y.

Table S7.Affinties between Eurasian and American populations by Patterson's D test.

Outgroup A X Y D Value Z-score ABBA BABA Total SNPS

Mbuti Buryats Mixe 939 0.004 0.52 3,960 3,930 61,162 Mbuti Chukchis Mixe 939 0.007 1.43 4,044 3,985 61,195 Mbuti Evens Mixe 939 -0.001 -0.11 3,966 3,971 61,195 Mbuti Han Mixe 939 -0.005 -0.92 3,910 3,947 61,195 Mbuti Japanese Mixe 939 -0.003 -0.54 3,924 3,946 61,195 Mbuti Koryaks Mixe 939 0.007 1.22 4,016 3,964 61,195 Mbuti Nganasans Mixe 939 0.001 0.16 3,964 3,957 61,195 Mbuti Nivkhs Mixe 939 0.001 0.14 3,948 3,941 61,195 Mbuti Onge Mixe 939 -0.006 -0.48 648 655 10,770 Mbuti Papuans Mixe 939 -0.006 -1.05 3,767 3,814 61,195 Mbuti Russians Mixe 939 -0.009 -1.93 3,805 3,877 61,195 Mbuti Sindhi Mixe 939 -0.009 -1.87 3,769 3,837 61,195 Mbuti Buryats Mixe Algonquin -0.002 -0.40 7,174 7,195 115,008 Mbuti Chukchis Mixe Algonquin 0.000 0.01 7,286 7,286 115,080 Mbuti Evens Mixe Algonquin 0.002 0.55 7,230 7,208 115,080 Mbuti Han Mixe Algonquin -0.003 -0.98 7,147 7,182 115,080 Mbuti Japanese Mixe Algonquin -0.002 -0.61 7,155 7,177 115,080 Mbuti Koryaks Mixe Algonquin 0.003 1.11 7,279 7,235 115,080 Mbuti Nganasans Mixe Algonquin -0.001 -0.40 7,200 7,216 115,080 Mbuti Nivkhs Mixe Algonquin -0.001 -0.29 7,198 7,210 115,080 Mbuti Onge Mixe Algonquin -0.003 -0.47 1,202 1,209 19,899 Mbuti Papuans Mixe Algonquin -0.003 -1.00 6,895 6,938 115,080 Mbuti Russians Mixe Algonquin -0.003 -1.07 7,035 7,071 115,080 Mbuti Sindhi Mixe Algonquin -0.003 -1.11 6,965 7,001 115,080 Mbuti Buryats Mixe Anzick-1 -0.007 -1.35 7,175 7,277 120,426 Mbuti Chukchis Mixe Anzick-1 0.002 0.61 7,360 7,326 120,505 Mbuti Evens Mixe Anzick-1 0.000 0.10 7,270 7,264 120,505 Mbuti Han Mixe Anzick-1 -0.004 -1.01 7,173 7,226 120,505 Mbuti Japanese Mixe Anzick-1 -0.004 -1.10 7,176 7,235 120,505 Mbuti Koryaks Mixe Anzick-1 0.000 0.06 7,314 7,311 120,505 Mbuti Nganasans Mixe Anzick-1 -0.005 -1.20 7,216 7,281 120,505 Mbuti Nivkhs Mixe Anzick-1 -0.006 -1.48 7,187 7,275 120,505 Mbuti Onge Mixe Anzick-1 0.005 0.80 1,307 1,293 22,537 Mbuti Papuans Mixe Anzick-1 0.005 1.17 6,947 6,883 120,505 Mbuti Russians Mixe Anzick-1 0.004 1.29 7,085 7,027 120,505 Mbuti Sindhi Mixe Anzick-1 0.003 1.04 7,000 6,957 120,505 Mbuti Buryats Mixe Bribri -0.002 -0.47 11,090 11,126 183,524 Mbuti Chukchis Mixe Bribri 0.000 -0.01 11,291 11,292 183,633 Mbuti Evens Mixe Bribri 0.000 -0.01 11,170 11,170 183,633 Mbuti Han Mixe Bribri -0.001 -0.53 11,059 11,088 183,633 Mbuti Japanese Mixe Bribri 0.001 0.23 11,092 11,078 183,633 Mbuti Koryaks Mixe Bribri 0.001 0.31 11,243 11,225 183,633 Mbuti Nganasans Mixe Bribri -0.002 -0.88 11,127 11,178 183,633 Mbuti Nivkhs Mixe Bribri -0.001 -0.33 11,123 11,144 183,633 Mbuti Onge Mixe Bribri 0.007 1.46 1,847 1,821 31,745

Mbuti Papuans Mixe Bribri 0.005 1.74 10,718 10,610 183,633 Mbuti Russians Mixe Bribri -0.001 -0.58 10,844 10,872 183,633 Mbuti Sindhi Mixe Bribri 0.001 0.59 10,764 10,736 183,633 Mbuti Buryats Mixe Cabecar -0.006 -2.11 11,052 11,179 183,524 Mbuti Chukchis Mixe Cabecar -0.002 -1.21 11,276 11,329 183,633 Mbuti Evens Mixe Cabecar -0.003 -1.55 11,146 11,213 183,633 Mbuti Han Mixe Cabecar -0.004 -2.11 11,043 11,128 183,633 Mbuti Japanese Mixe Cabecar -0.003 -1.44 11,067 11,127 183,633 Mbuti Koryaks Mixe Cabecar -0.003 -1.40 11,216 11,277 183,633 Mbuti Nganasans Mixe Cabecar -0.005 -2.49 11,112 11,221 183,633 Mbuti Nivkhs Mixe Cabecar -0.005 -2.05 11,098 11,198 183,633 Mbuti Onge Mixe Cabecar 0.002 0.54 1,840 1,833 31,745 Mbuti Papuans Mixe Cabecar 0.000 0.02 10,675 10,674 183,633 Mbuti Russians Mixe Cabecar -0.005 -3.03 10,811 10,923 183,633 Mbuti Sindhi Mixe Cabecar -0.003 -1.74 10,726 10,788 183,633 Mbuti Buryats Mixe Catalina -0.007 -1.54 11,054 11,212 182,057 Mbuti Chukchis Mixe Catalina 0.002 0.56 11,338 11,296 182,166 Mbuti Evens Mixe Catalina -0.004 -1.21 11,149 11,241 182,166 Mbuti Han Mixe Catalina -0.005 -1.61 11,045 11,162 182,166 Mbuti Japanese Mixe Catalina -0.005 -1.43 11,062 11,168 182,166 Mbuti Koryaks Mixe Catalina 0.002 0.69 11,293 11,241 182,166 Mbuti Nganasans Mixe Catalina -0.001 -0.39 11,164 11,194 182,166 Mbuti Nivkhs Mixe Catalina -0.002 -0.44 11,158 11,195 182,166 Mbuti Onge Mixe Catalina 0.003 0.35 1,838 1,829 31,563 Mbuti Papuans Mixe Catalina 0.000 0.01 10,694 10,693 182,166 Mbuti Russians Mixe Catalina -0.003 -0.99 10,844 10,913 182,166 Mbuti Sindhi Mixe Catalina -0.001 -0.17 10,771 10,782 182,166 Mbuti Buryats Mixe Chipewyan -0.001 -0.40 7,604 7,620 119,901 Mbuti Chukchis Mixe Chipewyan 0.007 3.71 7,784 7,671 119,974 Mbuti Evens Mixe Chipewyan 0.008 3.85 7,718 7,602 119,974 Mbuti Han Mixe Chipewyan 0.001 0.52 7,605 7,590 119,974 Mbuti Japanese Mixe Chipewyan 0.002 0.99 7,616 7,587 119,974 Mbuti Koryaks Mixe Chipewyan 0.008 4.12 7,759 7,633 119,974 Mbuti Nganasans Mixe Chipewyan 0.005 2.45 7,686 7,610 119,974 Mbuti Nivkhs Mixe Chipewyan 0.003 1.55 7,665 7,613 119,974 Mbuti Onge Mixe Chipewyan 0.002 0.50 1,278 1,273 20,799 Mbuti Papuans Mixe Chipewyan 0.000 -0.05 7,331 7,333 119,974 Mbuti Russians Mixe Chipewyan -0.003 -1.60 7,452 7,493 119,974 Mbuti Sindhi Mixe Chipewyan -0.003 -1.55 7,382 7,420 119,974 Mbuti Buryats Mixe EarlySN -0.003 -0.71 9,088 9,140 148,441 Mbuti Chukchis Mixe EarlySN -0.003 -0.85 9,231 9,280 148,536 Mbuti Evens Mixe EarlySN -0.006 -1.86 9,103 9,207 148,536 Mbuti Han Mixe EarlySN -0.010 -3.35 8,987 9,163 148,536 Mbuti Japanese Mixe EarlySN -0.008 -2.81 9,012 9,161 148,536 Mbuti Koryaks Mixe EarlySN -0.005 -1.53 9,167 9,252 148,536 Mbuti Nganasans Mixe EarlySN -0.008 -2.61 9,068 9,217 148,536 Mbuti Nivkhs Mixe EarlySN -0.005 -1.56 9,092 9,186 148,536 Mbuti Onge Mixe EarlySN -0.005 -0.82 1,524 1,541 26,188 Mbuti Papuans Mixe EarlySN -0.003 -0.93 8,716 8,773 148,536 Mbuti Russians Mixe EarlySN -0.008 -3.09 10,961 11,130 183,615

Mbuti Sindhi Mixe EarlySN -0.008 -3.30 10,842 11,013 183,615 Mbuti Buryats Mixe Guahibo -0.002 -0.88 11,064 11,115 183,524 Mbuti Chukchis Mixe Guahibo 0.001 0.35 11,286 11,271 183,633 Mbuti Evens Mixe Guahibo -0.001 -0.30 11,153 11,166 183,633 Mbuti Han Mixe Guahibo -0.002 -1.04 11,041 11,082 183,633 Mbuti Japanese Mixe Guahibo -0.002 -0.86 11,054 11,089 183,633 Mbuti Koryaks Mixe Guahibo 0.000 0.09 11,223 11,220 183,633 Mbuti Nganasans Mixe Guahibo -0.002 -0.82 11,121 11,158 183,633 Mbuti Nivkhs Mixe Guahibo -0.002 -0.98 11,104 11,150 183,633 Mbuti Onge Mixe Guahibo 0.004 1.10 1,834 1,820 31,745 Mbuti Papuans Mixe Guahibo 0.001 0.52 10,668 10,644 183,633 Mbuti Russians Mixe Guahibo -0.001 -0.83 10,831 10,862 183,633 Mbuti Sindhi Mixe Guahibo 0.000 0.07 10,739 10,736 183,633 Mbuti Buryats Mixe Guarani -0.001 -0.34 11,105 11,128 183,521 Mbuti Chukchis Mixe Guarani 0.000 -0.13 11,285 11,292 183,630 Mbuti Evens Mixe Guarani -0.002 -1.01 11,144 11,193 183,630 Mbuti Han Mixe Guarani -0.003 -1.46 11,040 11,109 183,630 Mbuti Japanese Mixe Guarani -0.002 -1.06 11,059 11,109 183,630 Mbuti Koryaks Mixe Guarani -0.002 -0.73 11,214 11,250 183,630 Mbuti Nganasans Mixe Guarani -0.003 -1.36 11,118 11,185 183,630 Mbuti Nivkhs Mixe Guarani -0.004 -1.84 11,090 11,188 183,630 Mbuti Onge Mixe Guarani 0.005 1.23 1,836 1,818 31,744 Mbuti Papuans Mixe Guarani -0.003 -1.07 10,625 10,678 183,630 Mbuti Russians Mixe Guarani -0.006 -3.08 10,793 10,919 183,630 Mbuti Sindhi Mixe Guarani -0.004 -1.93 10,707 10,782 183,630 Mbuti Buryats Mixe IslandChumash -0.002 -0.50 11,149 11,188 183,501 Mbuti Chukchis Mixe IslandChumash 0.002 0.90 11,387 11,333 183,610 Mbuti Evens Mixe IslandChumash 0.001 0.26 11,253 11,237 183,610 Mbuti Han Mixe IslandChumash -0.001 -0.31 11,137 11,154 183,610 Mbuti Japanese Mixe IslandChumash -0.001 -0.52 11,140 11,170 183,610 Mbuti Koryaks Mixe IslandChumash 0.001 0.42 11,322 11,297 183,610 Mbuti Nganasans Mixe IslandChumash 0.001 0.46 11,244 11,215 183,610 Mbuti Nivkhs Mixe IslandChumash -0.001 -0.43 11,199 11,228 183,610 Mbuti Onge Mixe IslandChumash -0.001 -0.13 1,852 1,855 31,745 Mbuti Papuans Mixe IslandChumash 0.003 0.90 10,756 10,699 183,610 Mbuti Russians Mixe IslandChumash -0.004 -1.57 10,890 10,970 183,610 Mbuti Sindhi Mixe IslandChumash -0.002 -0.95 10,792 10,837 183,610 Mbuti Buryats Mixe Kennewick -0.009 -1.49 6,779 6,896 108,000 Mbuti Chukchis Mixe Kennewick -0.010 -2.56 6,862 7,003 108,064 Mbuti Evens Mixe Kennewick -0.006 -1.36 6,837 6,917 108,064 Mbuti Han Mixe Kennewick -0.008 -2.02 6,767 6,876 108,064 Mbuti Japanese Mixe Kennewick -0.008 -2.06 6,772 6,886 108,064 Mbuti Koryaks Mixe Kennewick -0.008 -1.89 6,859 6,964 108,064 Mbuti Nganasans Mixe Kennewick -0.007 -1.62 6,818 6,910 108,064 Mbuti Nivkhs Mixe Kennewick -0.005 -1.06 6,827 6,893 108,064 Mbuti Onge Mixe Kennewick -0.012 -1.31 1,109 1,137 18,641 Mbuti Papuans Mixe Kennewick -0.002 -0.48 6,564 6,591 108,064 Mbuti Russians Mixe Kennewick -0.006 -1.56 6,634 6,712 108,064 Mbuti Sindhi Mixe Kennewick -0.004 -1.16 6,580 6,636 108,064 Mbuti Buryats Mixe LateSN -0.007 -2.31 11,223 11,373 183,522

Mbuti Chukchis Mixe LateSN -0.001 -0.55 11,465 11,489 183,631 Mbuti Evens Mixe LateSN -0.002 -1.07 11,334 11,383 183,631 Mbuti Han Mixe LateSN -0.004 -2.09 11,221 11,311 183,631 Mbuti Japanese Mixe LateSN -0.004 -1.81 11,238 11,317 183,631 Mbuti Koryaks Mixe LateSN -0.001 -0.69 11,403 11,435 183,631 Mbuti Nganasans Mixe LateSN -0.004 -1.72 11,301 11,381 183,631 Mbuti Nivkhs Mixe LateSN -0.002 -1.13 11,303 11,357 183,631 Mbuti Onge Mixe LateSN 0.000 -0.06 1,863 1,864 31,745 Mbuti Papuans Mixe LateSN -0.001 -0.23 10,843 10,855 183,631 Mbuti Russians Mixe LateSN -0.002 -1.22 11,028 11,077 183,631 Mbuti Sindhi Mixe LateSN -0.001 -0.62 10,930 10,954 183,631 Mbuti Buryats Mixe Lucier -0.001 -0.14 7,938 7,948 125,991 Mbuti Chukchis Mixe Lucier -0.010 -3.08 7,984 8,141 126,055 Mbuti Evens Mixe Lucier -0.005 -1.59 7,935 8,017 126,055 Mbuti Han Mixe Lucier -0.005 -1.76 7,869 7,954 126,055 Mbuti Japanese Mixe Lucier -0.003 -1.10 7,893 7,946 126,055 Mbuti Koryaks Mixe Lucier -0.006 -1.80 7,975 8,068 126,055 Mbuti Nganasans Mixe Lucier -0.004 -1.13 7,931 7,991 126,055 Mbuti Nivkhs Mixe Lucier -0.010 -2.69 7,883 8,035 126,055 Mbuti Onge Mixe Lucier 0.004 0.47 1,327 1,318 22,198 Mbuti Papuans Mixe Lucier -0.001 -0.16 7,606 7,614 126,055 Mbuti Russians Mixe Lucier 0.001 0.42 7,773 7,755 126,055 Mbuti Sindhi Mixe Lucier -0.001 -0.29 7,675 7,688 126,055 Mbuti Buryats Mixe Pima -0.003 -1.38 11,212 11,288 183,524 Mbuti Chukchis Mixe Pima -0.003 -1.69 11,397 11,464 183,633 Mbuti Evens Mixe Pima -0.003 -1.87 11,276 11,351 183,633 Mbuti Han Mixe Pima -0.004 -2.57 11,170 11,266 183,633 Mbuti Japanese Mixe Pima -0.004 -2.06 11,190 11,268 183,633 Mbuti Koryaks Mixe Pima -0.002 -1.25 11,350 11,400 183,633 Mbuti Nganasans Mixe Pima -0.005 -2.73 11,240 11,353 183,633 Mbuti Nivkhs Mixe Pima -0.005 -2.51 11,224 11,333 183,633 Mbuti Onge Mixe Pima -0.001 -0.18 1,850 1,853 31,745 Mbuti Papuans Mixe Pima -0.002 -1.21 10,769 10,820 183,633 Mbuti Russians Mixe Pima -0.004 -2.29 10,958 11,036 183,633 Mbuti Sindhi Mixe Pima -0.002 -1.50 10,860 10,909 183,633 Mbuti Buryats Mixe PointSal -0.004 -1.06 10,992 11,078 180,932 Mbuti Chukchis Mixe PointSal -0.001 -0.27 11,218 11,234 181,038 Mbuti Evens Mixe PointSal -0.001 -0.42 11,098 11,124 181,038 Mbuti Han Mixe PointSal -0.003 -1.23 10,980 11,050 181,038 Mbuti Japanese Mixe PointSal -0.002 -0.75 11,006 11,049 181,038 Mbuti Koryaks Mixe PointSal -0.002 -0.59 11,151 11,186 181,038 Mbuti Nganasans Mixe PointSal -0.005 -1.77 11,031 11,141 181,038 Mbuti Nivkhs Mixe PointSal -0.002 -0.81 11,055 11,107 181,038 Mbuti Onge Mixe PointSal -0.004 -0.75 1,816 1,830 31,414 Mbuti Papuans Mixe PointSal -0.002 -0.78 10,576 10,628 181,038 Mbuti Russians Mixe PointSal -0.004 -1.84 10,754 10,849 181,038 Mbuti Sindhi Mixe PointSal -0.003 -1.11 10,662 10,718 181,038 Mbuti Buryats Mixe SanClemente -0.005 -1.36 11,246 11,355 183,298 Mbuti Chukchis Mixe SanClemente -0.005 -1.88 11,421 11,530 183,407 Mbuti Evens Mixe SanClemente -0.007 -2.52 11,281 11,430 183,407

Mbuti Han Mixe SanClemente -0.007 -2.72 11,190 11,340 183,407 Mbuti Japanese Mixe SanClemente -0.007 -2.70 11,201 11,351 183,407 Mbuti Koryaks Mixe SanClemente -0.005 -2.07 11,357 11,478 183,407 Mbuti Nganasans Mixe SanClemente -0.008 -2.94 11,249 11,425 183,407 Mbuti Nivkhs Mixe SanClemente -0.006 -2.20 11,259 11,401 183,407 Mbuti Onge Mixe SanClemente -0.007 -1.31 1,853 1,881 31,728 Mbuti Papuans Mixe SanClemente -0.004 -1.57 10,784 10,880 183,407 Mbuti Russians Mixe SanClemente -0.005 -2.13 10,995 11,106 183,407 Mbuti Sindhi Mixe SanClemente -0.004 -1.64 10,897 10,977 183,407 Mbuti Buryats Mixe Surui 0.004 1.42 11,152 11,056 183,524 Mbuti Chukchis Mixe Surui 0.002 1.05 11,304 11,254 183,633 Mbuti Evens Mixe Surui 0.003 1.45 11,196 11,126 183,633 Mbuti Han Mixe Surui 0.002 0.98 11,087 11,042 183,633 Mbuti Japanese Mixe Surui 0.003 1.43 11,114 11,045 183,633 Mbuti Koryaks Mixe Surui 0.001 0.37 11,228 11,210 183,633 Mbuti Nganasans Mixe Surui 0.000 0.12 11,145 11,139 183,633 Mbuti Nivkhs Mixe Surui 0.002 0.65 11,147 11,111 183,633 Mbuti Onge Mixe Surui 0.013 3.24 1,855 1,807 31,745 Mbuti Papuans Mixe Surui 0.006 2.39 10,722 10,591 183,633 Mbuti Russians Mixe Surui -0.001 -0.33 10,838 10,852 183,633 Mbuti Sindhi Mixe Surui 0.002 0.81 10,750 10,718 183,633 Mbuti Buryats Mixe Yaghan 0.003 0.60 11,102 11,043 183,322 Mbuti Chukchis Mixe Yaghan 0.004 1.32 11,312 11,220 183,431 Mbuti Evens Mixe Yaghan 0.006 1.96 11,218 11,079 183,431 Mbuti Han Mixe Yaghan 0.000 0.14 11,054 11,045 183,431 Mbuti Japanese Mixe Yaghan 0.001 0.35 11,072 11,048 183,431 Mbuti Koryaks Mixe Yaghan 0.005 1.54 11,268 11,158 183,431 Mbuti Nganasans Mixe Yaghan 0.003 1.00 11,164 11,091 183,431 Mbuti Nivkhs Mixe Yaghan 0.003 0.79 11,149 11,086 183,431 Mbuti Onge Mixe Yaghan 0.014 2.27 1,854 1,804 31,716 Mbuti Papuans Mixe Yaghan 0.001 0.32 10,649 10,625 183,431 Mbuti Russians Mixe Yaghan 0.001 0.22 10,838 10,825 183,431 Mbuti Sindhi Mixe Yaghan 0.000 0.13 10,726 10,719 183,431

Note: Blue indicates Z-score <-3 and Gold indicates Z-score >3.

Table S8.Estimates of contribution from ANC-A and ANC-B in modern populations.

Population n Score worst fstat Anc-A Anc-BPercent European

ancestry in unmasked data

AFR ancestry Continent Language Family

Algonquin 5 38622 -4.164 0% 100% 0.2861 0 North America AlgonquianChilote 8 3296 -2.297 29% 71% 0.3773 0.0094 South America AndeanHulliche 4 2581 -2.102 30% 70% 0.1093 0.0049 South America AndeanPima 33 652 0.888 35% 65% 0.0321 0.0004 Central America Central AmerindArara 1 2491 -1.678 36% 64% 0 0 South America Ge-Pano-CaribWichi 5 775 -1.261 37% 63% 0.0236 0.0009 South America Ge-Pano-CaribYaghan 4 1170 -1.264 39% 61% 0.1561 0.0043 South America AndeanKaingang 2 3625 2.022 40% 60% 0.1205 0.0349 South America Ge-Pano-CaribZapotec1 22 459 -1.22 41% 59% 0.0395 0.0052 Central America Northern AmerindCabecar 31 694 -1.226 42% 58% 0.0088 0.0077 Central America Chipchan-PaezanMixe 17 543 -1.163 43% 57% 0.0039 0.0013 Central America Northern AmerindDiaguita 5 609 -1.18 44% 56% 0.2257 0.0263 South America AndeanWayuu 11 477 -1.106 45% 55% 0.0667 0.0351 South America Equatorial-TucanoanBribri 4 475 -1.011 46% 54% 0.0107 0.0217 Central America Chipchan-PaezanTeribe 3 482 -1.044 47% 53% 0 0.0029 Central America Chipchan-PaezanGuahibo 6 1905 2.05 47% 53% 0 0 South America Equatorial-TucanoanKaqchikel 13 775 -1.619 47% 53% 0.0657 0.0188 South America Northern AmerindQuechua 40 1015 2.102 48% 52% 0.076 0.0043 South America AndeanWaunana 3 1299 -1.39 48% 52% 0 0 South America Chipchan-PaezanToba 4 1241 1.684 48% 52% 0.0114 0 South America Ge-Pano-CaribAymara 23 1203 2.133 50% 50% 0.0275 0.0008 South America AndeanEmbera 5 1949 1.625 50% 50% 0 0 South America Chipchan-PaezanKogi 4 2136 -2.04 50% 50% 0 0 South America Chipchan-PaezanMaya1 20 805 2.004 50% 50% 0.0841 0.0123 Central America Northern AmerindGuarani 6 1049 1.631 51% 49% 0.0855 0.0009 South America Equatorial-TucanoanGuaymi 5 719 1.023 52% 48% 0 0 South America Chipchan-PaezanSurui 16 652 0.888 52% 48% 0 0 South America Equatorial-TucanoanPalikur 3 465 -1.015 53% 47% 0.0142 0 South America Equatorial-TucanoanTicuna 6 582 -0.847 54% 46% 0.0036 0.0096 South America Equatorial-TucanoanChono 4 535 -0.885 55% 45% 0.296 0.0041 South America AndeanTepehuano 25 1161 -1.945 55% 45% 0.0371 0.0024 Central America Central AmerindParakana 1 410 -0.862 55% 45% 0 0 South America Equatorial-TucanoanChane 2 1368 -1.719 56% 44% 0 0 South America Equatorial-TucanoanJamamadi 1 423 -0.943 60% 40% 0 0 South America Equatorial-Tucanoan

47% 53%

* Only masked data was used. Linquistic affiliations from (7). Color scale is blue (0%) to red (100%).Eur Afr

0.545 0.0860.400 0.260

Correlation of B with (including Algonquin)Correlation of B with (No Algonquin)

Average

Table S9. Effect of trimming terminal 10bp of each read on SNP-chip overlap.

SampleID Missing SNPS Total SNPS %Missing Missing SNPS Total SNPS %Missing ChangeSN-04 0.12 Medium 168527 183633 91.77% 175018 183633 95.31% 3.54%SN-17 7.45 High 2357 183633 1.28% 15780 183633 8.59% 7.31%SN-20 0.12 Medium 166118 183633 90.46% 171478 183633 93.38% 2.92%SN-25 0.17 Medium 162627 183633 88.56% 170708 183633 92.96% 4.40%SN-31 0.02 Low 180116 183633 98.08% 181292 183633 98.73% 0.65%SN-32 0.26 Medium 148967 183633 81.12% 159838 183633 87.04% 5.92%SN-39 0.12 Medium 168912 183633 91.98% 174672 183633 95.12% 3.14%SN-40 0.46 Medium 131668 183633 71.70% 151490 183633 82.50% 10.80%SN-41 0.02 Low 180125 183633 98.09% 181170 183633 98.66% 0.57%SN-44 9.36 High 677 183633 0.37% 3793 183633 2.07% 1.70%SN-45 0.01 Low 181587 183633 98.89% 182276 183633 99.26% 0.37%SN-54 0.43 Medium 128880 183633 70.18% 146715 183633 79.90% 9.72%SN-55 0.03 Low 179879 183633 97.96% 181543 183633 98.86% 0.90%SN-56 0.04 Low 178577 183633 97.25% 181136 183633 98.64% 1.39%SN-57 0.04 Low 177510 183633 96.67% 179792 183633 97.91% 1.24%SN-58 0.17 Medium 160521 183633 87.41% 168611 183633 91.82% 4.41%SN-59 0.16 Medium 160682 183633 87.50% 168318 183633 91.66% 4.16%SN-60 0.03 Low 180324 183633 98.20% 181680 183633 98.94% 0.74%

Average 3.55%Note: Called at snps overlapping worldwide data merge.

Table S10.Effect of average sequence depth on the significance of Early San Nicolas deficit of allele sharing with Han.

Outgroup Test X Y N Depth range D Z ABBA BABA SNPsMbuti Han Mixe EarlySN_MID 9 0.1-0.5x -0.010 -3.22 8680 8848 143371Mbuti Han Mixe EarlySN_LO 7 0.01-0.05x -0.012 -1.78 1544 1580 25620Mbuti Han Mixe EarlySN_HI 2 7-10x -0.009 -3.11 11155 11355 183597Mbuti Han Mixe EarlySN 18 0.01-10x -0.010 -3.35 8987 9163 148536

6bp 20bpCoverage

Table S11.Values for each San Nicolas Individual of D(Mbuti, Ancient-Test; Late San Nicolas, Early San Nicolas).

Sample D value SE Z-score Sites used Blocks for Jacknife

Inferred Population by

this testC14Date Direct or

context?mtDNA

Haplotype

SN-01 -0.07 0.01 -9.87 25461 537 LateSN nd B2a5bSN-03 -0.03 0.01 -4.63 55676 543 LateSN 1694±56 Direct C1b16a1*SN-04 0.19 0.01 17.75 11626 523 EarlySN 4279±52 Direct A2ar*SN-09 -0.08 0.01 -7.61 10460 522 LateSN nd B2a5bSN-10 -0.07 0.01 -12.65 56347 545 LateSN nd B2a5bSN-11 -0.06 0.01 -12.71 114588 549 LateSN 1172±39 Direct D1SN-12 -0.05 0.01 -4.49 7573 514 LateSN 1269±34 Direct CSN-13 -0.08 0.01 -13.49 51067 543 LateSN 881±42 Direct C1bSN-15 -0.01 0.01 -1.69 44619 543 LateSN 1852±44 Direct C1b16a1*SN-16 -0.08 0.01 -10.79 29160 538 LateSN nd B2a5bSN-17 0.18 0.01 30.53 115643 550 EarlySN 4517±51 Direct A2ar*SN-20 0.14 0.01 13.22 13034 522 EarlySN nd A2as*SN-25 0.15 0.01 16.54 15472 531 EarlySN 3940±40 Direct A2as*SN-31 0.20 0.02 10.22 2610 448 EarlySN nd A2SN-32 0.19 0.01 24.44 24257 539 EarlySN 4455±46 Direct A2as*SN-37 0.19 0.01 19.64 15375 528 EarlySN nd A2ar*SN-38 -0.01 0.01 -1.41 44198 543 LateSN nd C1b16a1*SN-39 0.19 0.01 18.17 10956 522 EarlySN nd A2as*SN-40 0.19 0.01 27.90 37833 540 EarlySN nd A2as*SN-41 0.20 0.02 10.68 2501 447 EarlySN nd A2ar*SN-43* 0.06 0.01 4.51 6865 505 EarlySN 2541±26 Direct C1b16a*SN-44 0.17 0.01 29.89 116098 550 EarlySN 4647±54 Direct A2as*SN-48 0.19 0.01 29.03 39578 543 EarlySN 4077±48 Direct A2SN-50 -0.03 0.01 -4.58 74299 547 LateSN 1593±27 Direct C1b16a1*SN-51 -0.04 0.01 -6.31 38707 542 LateSN 1620±26 Direct C1b16a1*SN-52 -0.07 0.01 -10.88 41183 541 LateSN 1013±26 Direct B2y1a*SN-53 -0.07 0.01 -11.98 53343 543 LateSN 840±26 Direct B2a5bSN-54 0.14 0.01 21.56 39138 540 EarlySN 3960±70 Context A2as*SN-55 0.19 0.02 10.11 2884 457 EarlySN 4410±100 Context A2SN-56 0.15 0.02 8.99 4057 476 EarlySN 4410±100 Context A2as*SN-57 0.17 0.02 11.31 4578 481 EarlySN 4410±100 Context A2ar*SN-58 0.18 0.01 18.79 16739 530 EarlySN 4410±100 Context A2ar*SN-59 0.16 0.01 19.44 16288 531 EarlySN 4430±30 Context A2as*SN-60 0.16 0.02 7.87 2426 443 EarlySN 3960±70 Context A2as*

Note: Bold indicates that result is not significant and thus this individual shares equally with Early and Late San Nicolas populations. Only two individuals have this result and one is the second oldest Late San Nicolas individual and the other is undated. * Sample shows most affinity in autosomal to the Early San Nicolas, but has a Late San Nicolas mtDNA hapoltype. This individual is also the oldest Late San Nicolas individual and closest to the inferred migration time.

Table S12.Information about comparative populations used in this study for ADMIXTURE, D and f statistics.

Population Region Source Latitude Longitude

Adygei Caucuses Li et al. 2008 (73 ) 29.00 109.00Aeta South Asia Rasmussen et al. 2011 (59 ) 8.00 5.00Agta South Asia Migliano et al. 2013 (88 ) -16.50 -68.20Alaskan_Inuit America Raghavan et al. 2015 (13 ) -16.50 -68.20Aleutians America Reich et al. 2012 (7 ) 52.00 -176.60Algonquin America Reich et al. 2012 (7 ) 73.30 88.00Anzick-1 America Rasmussen et al 2014 (9) 45.90 -110.60Arara America Reich et al. 2012 (7 ) 73.30 88.00Aymara America Reich et al. 2012 (7 ) 64.10 95.40Bajo South Asia Pierron et al. 2014 (89 ) 57.60 -107.40Balochi South Asia Li et al. 2008 (73 ) 0.00 0.00Bantus Africa Li et al. 2008 (73 ) 16.50 -97.20Batak South Asia Migliano et al. 2013 (88 ) 57.60 -107.40Bedouins Near East Li et al. 2008 (73 ) 17.00 -97.00Biaka_Pygmies Africa Li et al. 2008 (73 ) 20.30 -87.80Brahui South Asia Li et al. 2008 (73 ) 0.00 0.00Bribri America Reich et al. 2012 (7 ) 64.10 167.90BritishColumbia Northwest Raghavan et al. 2015 (13 ) 54.29 -130.61Burusho South Asia Li et al. 2008 (73 ) -10.00 -63.00Buryats Siberia Cardona et al. 2014 (90 ) -28.50 -65.80Cabecar America Reich et al. 2012 (7 ) 63.00 76.50Cambodians Asia Li et al. 2008 (73 ) -14.50 -69.00Chane America Reich et al. 2012 (7 ) 54.50 136.50Chilote America Reich et al. 2012 (7 ) -42.50 -73.90Chipewyan America Reich et al. 2012 (7 ) 59.60 -107.30Chono America Reich et al. 2012 (7 ) -45.00 -74.00Chukchis Siberia Reich et al. 2012 (7 ) 8.00 5.00Chuvash Asia Behar et al. 2010 (91 ) 0.00 0.00Cree America Reich et al. 2012 (7 ) 50.30 -102.50Dai Asia Li et al. 2008 (73 ) 38.00 138.00Daur Asia Li et al. 2008 (73 ) 48.50 124.00Diaguita America Reich et al. 2012 (7 ) -28.50 -65.80Druze Near East Li et al. 2008 (73 ) 19.00 -99.00East_Greenland America Raghavan et al. 2015 (13 ) 67.50 -37.90East_Greenlanders America Rasmussen et al. 2010 (8 ) 67.50 -37.90Embera America Reich et al. 2012 (7 ) 64.10 167.90Enoque65 SAM Raghavan et al. 2015 (13 ) -7.72 -42.73Eskimo Siberia Cardona et al. 2014 (90 ) 0.00 0.00Estonians Europe Raghavan et al 2014 (6 ) 8.00 5.00Evenkis Siberia Raghavan et al. 2015 (13 ) 0.00 0.00Evens Siberia Fedorova et al. 2013 (92 ) 0.00 0.00French Europe Li et al. 2008 (73 ) 20.30 -87.80French_Basques Europe Li et al. 2008 (73 ) 50.40 126.50Guahibo America Reich et al. 2012 (7 ) 8.00 5.00

Guarani America Reich et al. 2012 (7 ) 48.00 107.00Guaymi America Reich et al. 2012 (7 ) 63.00 76.50Gujaratis South Asia Altshuler et al. 2010 (98 ) -9.30 159.50Han Asia Li et al. 2008 (73 ) 51.59 -122.09Hazara South Asia Li et al. 2008 (73 ) 0.00 0.00Hezhen Asia Li et al. 2008 (73 ) 32.20 114.00Huetar America Reich et al. 2012 (7 ) 9.70 -84.30Huichol America Moreno-Estrada et al. 2014 (72 ) 28.00 103.00Hulliche America Reich et al. 2012 (7 ) -41.00 -73.00Hungarians Europe Behar et al. 2010 (91 ) 55.60 47.10Inga America Reich et al. 2012 (7 ) 1.00 -77.00Jamamadi America Reich et al. 2012 (7 ) 70.00 94.00Japanese Asia Li et al. 2008 (73 ) -14.50 -69.00Kaingang America Reich et al. 2012 (7 ) -24.00 -52.50Kalash South Asia Li et al. 2008 (73 ) -24.00 -52.50Kaqchikel America Reich et al. 2012 (7 ) 15.00 -91.00Karitiana America Li et al. 2008 (73 ) 16.50 -97.20Kayah_Lebbo South Asia Pierron et al. 2014 (89 ) 61.00 40.00Kennewick Northwest Rasmussen et al 2015 (10 ) 46.21 -119.14Khanty Siberia Reich et al. 2012 (7 ) 32.00 3.00Kogi America Reich et al. 2012 (7 ) 64.10 167.90Koryaks Siberia Yunusbayev et al 2015 (93 ) 47.40 19.30Kostenki14 Eurasia Seguin-Orlando et al. 2014 (94 ) 51.39 39.04Lacandon America Moreno-Estrada et al. 2014 (72 ) 61.00 40.00Lahu Asia Li et al. 2008 (73 ) 22.00 100.00Loschbour Europe Lazaridis et al. 2014 (75 ) 49.79 6.28Makrani South Asia Li et al. 2008 (73 ) 0.00 0.00Maleku America Reich et al. 2012 (7 ) 10.60 -84.80Malta Asia Raghavan et al 2014 (6 ) 52.90 103.50Mandenkas Africa Li et al. 2008 (73 ) 11.00 -73.00Maya1 America Li et al. 2008 (73 ) 9.00 -83.20Mbuti_Pygmies Africa Li et al. 2008 (73 ) 20.30 -87.80Melanesians Oceania Li et al. 2008 (73 ) 20.30 -87.80Miaozu Asia Li et al. 2008 (73 ) 42.00 47.86Mixe America Reich et al. 2012 (7 ) 61.68 158.07Mixtec America Reich et al. 2012 (7 ) 17.00 -97.00Mongola Asia Li et al. 2008 (73 ) 32.20 114.00Mozabites Africa Li et al. 2008 (73 ) 32.20 114.00Naukan Siberia Reich et al. 2012 (7 ) 8.00 5.00Naxi Asia Li et al. 2008 (73 ) 45.00 111.00Nenets Siberia Yunusbayev et al 2015 (93 ) 0.00 0.00Nganasan2 Siberia Reich et al. 2012 (7 ) 52.00 -176.60Nganasans Siberia Rasmussen et al. 2010 (8) 67.80 178.40Nivkhs Siberia Fedorova et al. 2013 (92 ) 67.80 178.40North_Italians Europe Li et al. 2008 (73 ) 43.58 43.40North_Kannadi South Asia Behar et al. 2010 (91 ) 43.00 0.00Northern_Athabascans_1 America Rasmussen et al. 2010 (8) 9.50 -84.00Northern_Athabascans_2 America Rasmussen et al. 2010 (8) -22.30 -63.70Northern_Athabascans_3 America Rasmussen et al. 2010 (8) -42.50 -73.90

Ojibwa America Reich et al. 2012 (7 ) 46.50 -81.00Onge South Asia Reich et al. 2009 (23 ) 66.00 172.00Orcadians Europe Li et al. 2008 (73 ) -11.00 -62.00Oroqens Asia Li et al. 2008 (73 ) 21.00 100.00Palestinians Near East Li et al. 2008 (73 ) 29.30 -108.80Palikur America Reich et al. 2012 (7 ) 64.10 95.40Paniya South Asia Behar et al. 2010 (91 ) 0.00 0.00Papuans Oceania Li et al. 2008 (73 ) 19.00 -99.00Papuans_pygmy Oceania Migliano et al. 2013 (88 ) 47.40 19.30Parakana America Reich et al. 2012 (7 ) 70.00 94.00Pathan South Asia Li et al. 2008 (73 ) 0.00 0.00Piapoco America Li et al. 2008 (73 ) -14.50 -69.00Pima America Reich et al. 2012 (7 ) 32.00 3.00Purepecha America Reich et al. 2012 (7 ) 19.00 -101.50Quechua America Reich et al. 2012 (7 ) 8.00 5.00Russians Europe Li et al. 2008 (73 ) 57.70 -134.90San Africa Li et al. 2008 (73 ) 16.50 -97.20Saqqaq Greenland Rasmussen et al. 2010 (8) 52.00 94.40Sardinians Europe Li et al. 2008 (73 ) 29.30 -108.80Selkups Siberia Rasmussen et al. 2010 (8) 52.00 94.40Seri America Moreno-Estrada et al. 2014 (72 ) 63.00 130.00She Asia Li et al. 2008 (73 ) 28.00 109.00Shuka_Kaa America Lindo et al. 2017 (11 ) 55.00 -133.50Sindhi South Asia Li et al. 2008 (73 ) 0.00 0.00Solomons South Asia Kenny et al. 2012 (95 ) -3.00 37.00Southern_Athabascans_1 America Raghavan et al. 2015 (13 ) 9.50 -84.00Splatsin America Verdu et al. 2014 (12 ) 68.00 150.00Stuttgart Europe Lazaridis et al. 2014 (75 ) 48.78 9.18Surui America Reich et al. 2012 (7 ) 8.00 5.00Tarahumara America Moreno-Estrada et al. 2014 (72 ) 30.50 66.50Tepehuano America Reich et al. 2012 (7 ) 36.50 74.00Teribe America Reich et al. 2012 (7 ) 64.10 167.90Ticuna America Reich et al. 2012 (7 ) 64.10 167.90Tlingit America Raghavan et al. 2015 (13 ) -16.50 -68.20Toba America Reich et al. 2012 (7 ) 73.30 88.00Tojolabal America Moreno-Estrada et al. 2014 (72 ) 23.10 72.40Totonac America Moreno-Estrada et al. 2014 (72 ) 23.10 72.40Triqui America Moreno-Estrada et al. 2014 (72 ) 23.10 72.40Tu Asia Li et al. 2008 (73 ) 26.00 100.00Tujia Asia Li et al. 2008 (73 ) 43.58 43.40Tuscans Europe Li et al. 2008 (73 ) 43.58 43.40Tzotzil America Moreno-Estrada et al. 2014 (72 ) 26.00 64.00Ukranians Europe Yunusbayev et al 2012 (97 ) 8.50 77.00USR1 America Moreno-Mayar et al. 2018 (77 ) 65.50 -147.00USR2 America Moreno-Mayar et al. 2018 (77 ) 65.50 -147.00UstIshim Eurasia Fu et al. 2014 (96 ) 57.43 71.10Uygurs Asia Li et al. 2008 (73 ) 38.00 138.00Waunana America Reich et al. 2012 (7 ) 48.00 107.00Wayuu America Reich et al. 2012 (7 ) 48.00 107.00

WestGreenland Greenland Raghavan et al. 2015 (13 ) 33.50 70.50Wichi America Reich et al. 2012 (7 ) 73.30 88.00Xibo Asia Li et al. 2008 (73 ) 32.20 114.00Yaghan America Reich et al. 2012 (7 ) 65.00 188.00Yakuts Siberia Reich et al. 2012 (7 ) 8.00 5.00Yaqui America Reich et al. 2012 (7 ) 28.00 -110.30Yizu Asia Li et al. 2008 (73 ) 42.00 47.86Yorubas Africa Altshuler et al. 2010 (98 ) 65.30 -52.00Yukaghirs Siberia Reich et al. 2012 (7 ) 11.00 -73.80Yukpa America Moreno-Estrada et al. 2013 (76 ) 25.50 69.00Zapotec1 America Reich et al. 2012 (7 ) 64.10 95.40Zapotec2 America Reich et al. 2012 (7 ) 64.10 95.40

32

Additional Data table S1 (separate file) List of Y chromosome haplogroup Q defining sites by position. Additional Data table S2 (separate file) Populations and individuals used for PCA and ADMIXTURE analysis.

Additional Data table S3 (separate file) Results of outgroup f3 and D statistical tests for ancient populations. Additional Data table S4 (separate file) Example MapDamage and Fragment Misincorporation plots.

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Supplementary Materials for - Science · 2018. 5. 30. · the clothing of the deceased, a dog skull, a small scissors, and an iron spike. All, except the iron spike, have known cultural