Reconstructing Native American population history

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The peopling of the Americas has been the subject of extensive genetic, archaeological and linguistic research; however, central questions remain unresolved1, 2, 3, 4, 5. One contentious issue is whether the settlement occurred by means of a single6, 7, 8 migration or multiple streams of migration from Siberia9, 10, 11, 12, 13, 14, 15. The pattern of dispersals within the Americas is also poorly understood. To address these questions at a higher resolution than was previously possible, we assembled data from 52 Native American and 17 Siberian groups genotyped at 364,470 single nucleotide polymorphisms. Here we show that Native Americans descend from at least three streams of Asian gene flow. Most descend entirely from a single ancestral population that we call ‘First American’. However, speakers of Eskimo–Aleut languages from the Arctic inherit almost half their ancestry from a second stream of Asian gene flow, and the Na-Dene-speaking Chipewyan from Canada inherit roughly one-tenth of their ancestry from a third stream. We show that the initial peopling followed a southward expansion facilitated by the coast, with sequential population splits and little gene flow after divergence, especially in South America. A major exception is in Chibchan speakers on both sides of the Panama isthmus, who have ancestry from both North and South America.

At a glance


  1. Geographic, linguistic and genetic overview of 52 Native American populations.
    Figure 1: Geographic, linguistic and genetic overview of 52 Native American populations.

    a, Sampling locations of the populations, with colours corresponding to linguistic groups. b, Cluster-based analysis (k = 4) using ADMIXTURE shows evidence of some West-Eurasian-related and sub-Saharan-African-related ancestry in many Native Americans before masking (top), but little afterwards (bottom). Thick vertical lines denote major linguistic groupings, and thin vertical lines separate individual populations. c, Neighbour-joining tree based on Fst distances relating Native American to selected non-American populations (sample sizes in parentheses). Native American and Siberian data were analysed after masking, but consistent trees were obtained on a subset of completely unadmixed samples (Supplementary Fig. 3). Some populations have evidence for substructure, and we represent these as two different groups (for example Maya1 and Maya2).

  2. Distinct streams of gene flow from Asia into America.
    Figure 2: Distinct streams of gene flow from Asia into America.

    We present an AG that gives no evidence of being a poor fit to the data and is consistent with three streams of Asian gene flow into America. Solid points indicate inferred ancestral populations, drift on each lineage is given in units proportional to 1,000×Fst, and mixture events (dotted lines) are denoted by the percentage of ancestry. The Asian lineage leading to First Americans is the most deeply diverged, whereas the Asian lineages leading to Eskimo–Aleut speakers and the Na-Dene-speaking Chipewyan are more closely related and descend from a common Siberian ancestral population that is a sister group to the Han. The inferred ancestral populations are indicated by filled circles, and the lineages descending from them are coloured: First American (blue), ancestors of the Na-Dene-speaking Chipewyan (green), and Eskimo–Aleut (red). The model also infers a migration of people related to Eskimo–Aleut speakers across the Bering Strait, thus bringing First American genes to Asia (the Naukan are shown, but the Chukchi show a similar pattern; Supplementary Notes).

  3. A model fitting populations of entirely First American ancestry.
    Figure 3: A model fitting populations of entirely First American ancestry.

    We show an AG depicting the relationships between 16 selected Native American populations with entirely First American ancestry along with two outgroups (Yoruba and Han). The Colombian Inga are modelled as a mixture of Andean and Amazonian ancestry. The Paraguayan Guarani are fitted as a mixture of separate strands of ancestry from eastern South America. The Central American Cabecar are modelled as a mixture of strands of ancestry related to South Americans and to North Americans, supporting back-migration from South into Central America. The colouring of edges indicates alternative insertion points for the admixing lineages leading to the Cabecar that produce a similar fit to the data in the sense that the χ2 statistic is within 3.84 of the AG shown. The red colouring shows that the South American lineage contributing to the Cabecar split off after the divergence of the Andean populations, and the blue colouring shows that the other lineage present in the Cabecar diverged before the separation of Andeans. Estimated admixture proportions are shown along the dotted lines, and lineage-specific drift estimates are in units proportional to 1,000×Fst.


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Author information


  1. Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA

    • David Reich &
    • Arti Tandon
  2. Broad Institute of Harvard and the Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA

    • David Reich,
    • Nick Patterson,
    • Arti Tandon &
    • Alkes L. Price
  3. Department of Genetics, Evolution and Environment, University College London WC1E 6BT, UK

    • Desmond Campbell,
    • Stéphane Mazieres,
    • Maria V. Parra,
    • Winston Rojas,
    • Constanza Duque,
    • Natalia Mesa,
    • Claudio M. Bravi,
    • Tábita Hünemeier &
    • Andrés Ruiz-Linares
  4. Department of Psychiatry and Centre for Genomic Sciences, The University of Hong Kong, Pokfulam, Hong Kong SAR

    • Desmond Campbell
  5. Anthropologie Bio-culturelle, Droit, Ethique et Santé (ADES), UMR 7268, Aix-Marseille Université/CNRS/EFS, Marseille 13344, France

    • Stéphane Mazieres
  6. Institute for Environmental Sciences, and Forel Institute, University of Geneva, Geneva 1227, Switzerland

    • Nicolas Ray
  7. Universidad de Antioquia, Medellín, Colombia

    • Maria V. Parra,
    • Winston Rojas,
    • Constanza Duque,
    • Natalia Mesa,
    • Luis F. García,
    • Omar Triana,
    • Silvia Blair,
    • Amanda Maestre &
    • Gabriel Bedoya
  8. Fundación Salud para el Trópico, Santa Marta, Colombia

    • Juan C. Dib
  9. Instituto Multidisciplinario de Biología Celular (CCT La Plata-CONICET, CICPCA), 1900 La Plata, Argentina

    • Claudio M. Bravi &
    • Graciela Bailliet
  10. Servicio de Huellas Digitales Genéticas and CONICET, Universidad de Buenos Aires, Argentina

    • Daniel Corach
  11. Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre 91501-970, Brazil

    • Tábita Hünemeier,
    • Maria Cátira Bortolini &
    • Francisco M. Salzano
  12. Departamento de Genética, Universidade Federal do Paraná, Curitiba 81531-980, Brazil

    • María Luiza Petzl-Erler
  13. National Institute of Anthropology and History, México City 06100, México

    • Victor Acuña-Alonzo
  14. Departamento de Endocrinología y Metabolismo, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, México City 14100, México

    • Carlos Aguilar-Salinas
  15. Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán/Universidad Nacional Autónoma de México, México City 14000, México

    • Samuel Canizales-Quinteros,
    • Teresa Tusié-Luna &
    • Laura Riba
  16. Departamento de Biología, Facultad de Química, Universidad Nacional Autónoma de México, México City 04510, México

    • Samuel Canizales-Quinteros
  17. Unidad de Investigación Médica en Nutrición, Hospital de Pediatría, CMNSXXI, Instituto Mexicano del Seguro Social, México City 06720, México

    • Maricela Rodríguez-Cruz &
    • Mardia Lopez-Alarcón
  18. Sección de Posgrado, Escuela Superior de Medicina del Instituto Politécnico Nacional, México City 11340, México

    • Ramón Coral-Vazquez
  19. Laboratorio de Biología de la Reproducción, Departamento de Salud Reproductiva y Genética, Centro de Investigaciones Regionales, Mérida Yucatán 97000, México

    • Thelma Canto-Cetina
  20. Instituto Nacional de Medicina Genómica, México City 14610, México

    • Irma Silva-Zolezzi,
    • Juan Carlos Fernandez-Lopez,
    • Alejandra V. Contreras &
    • Gerardo Jimenez-Sanchez
  21. Universidad Autónoma de Nuevo León, San Nicolás de los Garza, Nuevo León 66451, México

    • Maria José Gómez-Vázquez
  22. Centro de Investigaciones Biomédicas de Guatemala, Ciudad de Guatemala, Guatemala

    • Julio Molina
  23. Instituto de Ciencias Forenses, Universidade de Santiago de Compostela, Fundación de Medicina Xenómica (SERGAS), CIBERER, Santiago de Compostela, Galicia 15782, Spain

    • Ángel Carracedo &
    • Antonio Salas
  24. Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima 15102, Peru

    • Carla Gallo &
    • Giovanni Poletti
  25. Department of Human Genetics, University of Chicago, Chicago 60637, USA

    • David B. Witonsky,
    • Gorka Alkorta-Aranburu &
    • Anna Di Rienzo
  26. Laboratory of Human Molecular Genetics, Institute of Molecular and Cellular Biology, Siberian Branch of the Russian Academy of Sciences, Novosibirsk 630090, Russia

    • Rem I. Sukernik
  27. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk 630090, Russia

    • Ludmila Osipova
  28. Department of Molecular Genetics, Yakut Research Center of Complex Medical Problems and North-East Federal University, Yakutsk, Sakha (Yakutia) 677010, Russia

    • Sardana A. Fedorova
  29. Instituto Boliviano de Biología de la Altura, Universidad Autonoma Tomás Frías, Potosí, Bolivia

    • René Vasquez &
    • Mercedes Villena
  30. Département de Pédiatrie, Centre de Recherche du CHU Sainte-Justine, Université de Montréal, Montréal, Quebec H3T 1C5, Canada

    • Claudia Moreau &
    • Damian Labuda
  31. Escuela de Biología, Universidad de Costa Rica, San José, Costa Rica

    • Ramiro Barrantes
  32. Center for Human Genetic Research, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA

    • David Pauls
  33. Computational and Molecular Population Genetics Laboratory, Institute of Ecology and Evolution, University of Bern, 3012 Bern, Switzerland

    • Laurent Excoffier
  34. Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland

    • Laurent Excoffier
  35. Instituto de Alta Investigación, Universidad de Tarapacá, Programa de Genética Humana ICBM Facultad de Medicina Universidad de Chile and Centro de Investigaciones del Hombre en el Desierto, Arica 1001236, Chile

    • Francisco Rothhammer
  36. Anthropologie Moléculaire et Imagerie de Synthèse, CNRS UMR 5288, Université Paul Sabatier Toulouse III, Toulouse 31000, France

    • Jean-Michel Dugoujon &
    • Georges Larrouy
  37. School of Public Health, University of California, Berkeley, California 94720, USA

    • William Klitz
  38. Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520, USA

    • Judith Kidd &
    • Kenneth Kidd
  39. Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California 90095, USA

    • Nelson B. Freimer
  40. Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA

    • Alkes L. Price
  41. Present addresses: BioAnalytical Science Department Nestec Ltd, Nestlé Research Center, 1000 Lausanne, Switzerland (I.S.-Z.); Global Biotech Consulting Group, México City 09010, México (G.J.-S.).

    • Irma Silva-Zolezzi &
    • Gerardo Jimenez-Sanchez


D.R., N.B.F., A.L.P. and A.R-L. conceived the project. D.R., N.P., D.C., A.T., S.M., N.R. and A.R-L. performed analyses. D.R. and A. R.-L. wrote the paper with input from all the co-authors. A.R.-L. assembled the sample collection, directed experimental work and coordinated the study. All other authors contributed to the collection of samples and data.

Competing financial interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to:

The data analysed here are available for non-profit research on population history under an inter-institutional data access agreement with the Universidad de Antioquia, Colombia; queries regarding data access should be sent to A.R.-L. (

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Supplementary information

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  1. Supplementary Information (3.1M)

    This file contains Supplementary Text 1-7, Supplementary Figures 1-5 and Supplementary Tables 1-3.


  1. Report this comment #52208

    rossi andrea said:

    Native American population genetic and cholesterol gallstones
    Andrea Cariati, MD
    General Surgery, San Martino, IST, University Hospital, Genoa, Italy
    Address for correspondence:
    Andrea Cariati, MD
    Via fratelli Coda 67/5 A
    16166 Genova, Italy
    Tel 00390103724909
    E mail:

    Dear Editor, I read with great interest the article on reconstructing Native American population history, published on Nature (1). Authors stated that the peopling of the Americas occurred mainly by means of a first large migration from the interior of Siberia (Central Asia), during the last Great Ice Age, via the Bering Strait land bridge (Beringia) and that the initial settlement followed a southward expansion facilitated by the coast from North America to Central and South America (1). We agree completely with these conclusions, in fact, during our studies on gallstones disease (2) we have found that gallstones incidence (especially cholesterol gallstones) is higher, also in our city, Genoa, among people from Ecuador, Mexico and Peru. As Carey described (3) Paleo-Indians were big game hunters who became trapped within Beringia for more than 15000 years. In this area there was scant food and the harsh winter have been present for 10-11 months in a year. Paleo- Indians (or Native Americans) used to trap and kill large animals as mastodon, wild horse and mommoth to feed their families, usually in the summer month. These climatic and alimentary conditions led that the survival and the reproduction depended on genes that produced a favorable advantage by efficient fat storage. Only the subset of the ?first migration? population with the thrifty genes survived and migrate in Americas (the New Land); that?s why Native Americans and American Indian tribes as Maricopa, Pima, Apache, Caddo, Comanche, T?ohono O?otham (from Arizona), Delaware, Fort Still Apache, Sioux, Cheyenne, Chilean Mapuche, Mexican Americans have similar genes patterns (1, 2, 3). These thrifty genes appear primary to be involved with lipid physiology, hepatobiliary function, and metabolism as the ABCB4 gene mutation, the apolipoprotein E gene, the CYP7A1 gene (rate-limiting enzyme of bile salt synthesis) and other alleles (2). It is likely that the major effect of these genes was to facilitate the calorie storage in adipose tissue to be used during the hard winters. In the present era, with the actual climatic conditions, these genes cause cholesterol gallstones and the so-called metabolic epidemic syndrome (obesity, dyslipidemia, hyperinsulinemia and type 2 diabetes) (2, 3); for these motivations, it could be expected that these groups could necessitate oral treatment with statins with higher incidence respect to general population and in particular respect to people from Africa.
    1) Reich D, Patterson N, Campbell D, et al. Reconstructing Native American population history. Nature 2012; 488: 370-374
    2) Cariati A, Piromalli E. Limits and perspective of oral therapy with statins and aspirin for the prevention of symptomatic cholesterol gallstone disease. Expert Opinion Pharmacother 2012; 13: 1223-1227
    3) Carey M, Paigen B. Epidemiology of the American Indian?s burden and it likely genetic origin. Hepatology 2002; 36: 781-791

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