jueves, 8 de junio de 2017



Descubren en Marruecos los fósiles de 'Homo sapiens' más antiguos, con 315.000 años.....



















RTVE.es / EUROPA PRESS


Los restos más antiguos conocidos de Homo Sapiens han sido hallados en un lugar de Marruecos llamado Yebel Irhoud, unos 150 kilómetros al oeste de Marrakech, según un estudio publicado en la revista especializada Nature. Este descubrimiento cambiaría el origen de nuestra especie, situado hasta ahora en África Oriental, en diferentes puntos de Etiopía, aunque según el trabajo científico los restos confirman que el Homo Sapiens estuvo presente en todo el continente africano.

Los hallazgos datan de hace unos 315.000 años y representan la evidencia fósil más antigua de la especie humana, según los autores.

Tanto los datos genéticos de los seres humanos actuales como los restos fósiles apuntan a un origen africano del Homo sapiens

Anteriormente, los fósiles de esta especie más antiguos y con datación segura eran del sitio de Omo Kibish, en Etiopía, fechado hace 195.000 años. En Herto, también en Etiopía, un fósil de Homo sapiens está fechado hace 160.000 años.
"Solíamos pensar que había una cuna de la humanidad hace 200.000 años en el este de África, pero nuestros nuevos datos revelan que el Homo sapiens se extendió por todo el continente africano hace unos 300.000 años. Mucho antes de la dispersión fuera de África del Homo sapiens, hubo dispersión dentro de África", ha explicado el paleoantropólogo Jean-Jacques Hublin.

Jebel Irhoud es el sitio más antiguo y más rico de homínidos en África

El sitio marroquí de Jebel Irhoud ha sido bien conocido desde la década de 1960 por sus fósiles humanos y por sus artefactos de la Edad de Piedra. Sin embargo, la interpretación de los homínidos de Irhoud ha sido complicada por las persistentes incertidumbres que rodean su edad geológica. El nuevo proyecto de excavación, que comenzó en 2004, dio lugar al descubrimiento in situ de nuevos fósiles de Homo sapiens, aumentando su número de seis a 22.

Estos hallazgos confirman la importancia de Jebel Irhoud como el sitio más antiguo y más rico de homínidos de la Edad Media de la Edad de Piedra en África, una etapa temprana de nuestra especie. Los restos fósiles de Jebel Irhoud comprenden cráneos, dientes y huesos largos de al menos cinco individuos.

Para proporcionar una cronología precisa de estos hallazgos, los investigadores utilizaron el método de datación por termoluminiscencia sobre pedernales calentados encontrados en los mismos depósitos. Estos pedernales eran de hace aproximadamente 300.000 años y, por lo tanto, empujan hacia atrás los orígenes de nuestra especie en 100.000 años.

El cráneo de los seres humanos modernos que viven hoy se caracteriza por una combinación de rasgos que nos distinguen de nuestros parientes fósiles y antepasados: una cara pequeña y una caja del cráneo globular.

Los fósiles de Jebel Irhoud exhiben un rostro y dientes de apariencia moderna y una coraza grande, pero de apariencia más arcaica. Hublin y su equipo utilizaron exploraciones micro tomográficas computarizadas de última generación y análisis de forma estadística basados en cientos de medidas 3D para mostrar que la forma facial de los fósiles de Jebel Irhoud es casi indistinguible de la de los seres humanos modernos que viven hoy.

Sin embargo, en contraste con su morfología facial moderna, la cría de Jebel Irhoud conserva una forma arcaica algo alargada de la cintura. "La forma interna de la caja del cráneo refleja la forma del cerebro", ha señalado el paleontólogo Philipp Gunz, del Instituto Max Planck de Antropología Evolutiva de Leipzig. "Nuestros hallazgos sugieren que la moderna morfología facial humana se estableció desde el principio en la historia de nuestra especie y que la forma cerebral y posiblemente el cerebro, que se desarrolló dentro del linaje del Homo sapiens".


Las comparaciones de ADN antiguo extraído de Neanderthales y denisovanos al ADN de los seres humanos actuales han revelado diferencias en los genes que afectan al cerebro y el sistema nervioso. La morfología y la edad de los fósiles de Jebel Irhoud también corroboran la interpretación de un enigmático cráneo parcial de Florisbad, al sur de África, como uno de los primeros representantes del Homo sapiens.


Conexiones estrechas del Magreb con el resto del continente

Los primeros fósiles Homo sapiens se encuentran en todo el continente africano: Jebel Irhoud, Marruecos (315.000 años), Florisbad, Sudáfrica (260.000 años) y Omo Kibish, Etiopía (195.000 años), lo que indica una compleja historia evolutiva de nuestra especie, posiblemente involucrando a todo el continente africano.

·     Este descubrimiento amplía los orígenes de nuestra especie en 100.000 años
·     Cambiaría la cuna de la humanidad, situada hasta ahora en Etiopía
·     Los restos son cráneos, dientes y huesos largos de al menos cinco individuos




"Se ha descuidado el norte de África en los debates sobre el origen de nuestra especie. Los espectaculares descubrimientos de Jebel Irhoud demuestran las conexiones estrechas del Magreb con el resto del continente africano en el momento de la emergencia del Homo sapiens", dice Abdelouahed Ben-Ncer. Los fósiles se encontraron en depósitos que contenían huesos de animales que mostraban evidencia de haber sido cazados, siendo las gacelas la especie más frecuente.

Las herramientas de piedra asociadas con estos fósiles pertenecen a la Edad Media de Piedra y los artefactos de Jebel Irhoud muestran el uso de técnicas de Levallois y las formas puntiagudas son las más comunes. La mayoría de las herramientas de piedra se hicieron de sílex de alta calidad importados en el sitio. Las hachas de mano, una herramienta comúnmente encontrada en sitios antiguos, no están presentes en Jebel Irhoud.

"Los artefactos de piedra de Jebel Irhoud parecen muy similares a los de depósitos de edad similar en el este y sur de África. Es probable que las innovaciones tecnológicas de la Edad Media de Piedra en África estén relacionadas con la aparición del Homo sapiens", ha dicho el arqueólogo del Instituto Max Planck, Shannon McPherron.

FUENTE: http://www.rtve.es/noticias/20170607/descubren-marruecos-fosiles-homo-sapiens-mas-antiguos-hace-300000-anos/1561647.shtml

viernes, 2 de junio de 2017


FRANCIA REHUSA ACEPTAR LA DECISION DE TRUMP 
Y LLAMA A FILAS...
A LOS NORTEAMERICANOS QUE REHUSEN LA  ABSURDA DECISION DEL PRESIDENTE NORTEAMERICANO  
DE NEGAR LA EXISTENCIA DEL CAMBIO CLIMNTICO 
Y POR TANTO SABEN DE LA NECESIDAD DE LUCHAR EN SU CONTRA......



miércoles, 5 de octubre de 2016

A genomic history of Aboriginal Australia



Nature
 
 
doi:10.1038/nature18299
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Received
 
Accepted
 
Published online
 

Abstract

The population history of Aboriginal Australians remains largely uncharacterized. Here we generate high-coverage genomes for 83 Aboriginal Australians (speakers of Pama–Nyungan languages) and 25 Papuans from the New Guinea Highlands. We find that Papuan and Aboriginal 
Australian ancestors diversified 25–40 thousand years ago (kya), suggesting pre-Holocene population structure in the ancient continent of Sahul (Australia, New Guinea and Tasmania). However, all of the studied Aboriginal Australians descend from a single founding population that differentiated ~10–32 kya. We infer a population expansion in northeast Australia during the Holocene epoch (past 10,000 years) associated with limited gene flow from this region to the rest of Australia, consistent with the spread of the Pama–Nyungan languages. We estimate that Aboriginal Australians and Papuans diverged from Eurasians 51–72 kya, following a single out-of-Africa dispersal, and subsequently admixed with archaic populations. Finally, we report evidence of selection in Aboriginal Australians potentially associated with living in the desert.
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Author information

Author footnotes

  1. These authors contributed equally to this work.

    • Anna-Sapfo Malaspinas, 
    • Michael C. Westaway, 
    • Craig Muller, 
    • Vitor C. Sousa, 
    • Oscar Lao, 
    • Isabel Alves & 
    • Anders Bergström

Affiliations

  1. Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5–7, 1350 Copenhagen, Denmark

    • Anna-Sapfo Malaspinas,
    •  
    • Craig Muller,
    •  
    • Ashot Margaryan,
    •  
    • Thorfinn S. Korneliussen,
    •  
    • J. Víctor Moreno-Mayar,
    •  
    • Martin Sikora,
    •  
    • Paula F. Campos,
    •  
    • Robert A. Foley,
    •  
    • Marta Mirazón Lahr,
    •  
    • Rasmus Nielsen &
    •  
    • Eske Willerslev
  2. Institute of Ecology and Evolution, University of Bern, Baltzerstrasse 6, 3012 Bern, Switzerland

    • Anna-Sapfo Malaspinas,
    •  
    • Vitor C. Sousa,
    •  
    • Isabel Alves,
    •  
    • Isabelle Dupanloup &
    •  
    • Laurent Excoffier
  3. Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland

    • Anna-Sapfo Malaspinas,
    •  
    • Vitor C. Sousa,
    •  
    • Isabel Alves,
    •  
    • Stephan Peischl,
    •  
    • Isabelle Dupanloup &
    • Laurent Excoffier
  4. Research Centre for Human Evolution, Environmental Futures Research Institute, Griffith University, Nathan, Queensland 4111, Australia

    • Michael C. Westaway,
    •  
    • Tim H. Heupink,
    •  
    • Sankar Subramanian,
    •  
    • Joanne L. Wright &
    •  
    • David M. Lambert
  5. CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain

    • Oscar Lao
  6. Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain

    • Oscar Lao
  7. Population and Conservation Genetics Group, Instituto Gulbenkian de Ciência, 2780-156 Oeiras, Portugal

    • Isabel Alves
  8. Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK

    • Anders Bergström,
    •  
    • Yali Xue,
    •  
    • Chris Tyler-Smith,
    •  
    • Richard Durbin,
    •  
    • Manjinder S. Sandhu &
    •  
    • Eske Willerslev
  9. Bioinformatics Research Centre, Aarhus University, 8000 Aarhus, Denmark

    • Georgios Athanasiadis,
    •  
    • Jade Y. Cheng,
    •  
    • Mikkel H. Schierup &
    •  
    • Thomas Mailund
  10. Department of Integrative Biology, University of California, Berkeley, California 94720, USA

    • Jade Y. Cheng,
    •  
    • Jacob E. Crawford &
    •  
    • Fernando Racimo
  11. Verily Life Sciences, 2425 Garcia Ave, Mountain View, California 94043, USA

    • Jacob E. Crawford
  12. Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany

    • Enrico Macholdt,
    •  
    • Chiara Barbieri,
    •  
    • Irina Pugach,
    •  
    • Shengyu Ni &
    •  
    • Mark Stoneking
  13. Interfaculty Bioinformatics Unit University of Bern, Baltzerstrasse 6, CH-3012 Bern, Switzerland

    • Stephan Peischl
  14. Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Kemitorvet, Building 208, 2800 Kongens Lyngby, Denmark

    • Simon Rasmussen
  15. Department for Archaeogenetics, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany

    • Stephan Schiffels
  16. The Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaløes Vej 5, 2200 Copenhagen, Denmark

    • Anders Albrechtsen &
    •  
    • Ida Moltke
  17. Department of Linguistic and Cultural Evolution, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany

    • Chiara Barbieri
  18. Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK

    • Anders Eriksson,
    •  
    • Andrea Manica &
    •  
    • Eske Willerslev
  19. Integrative Systems Biology Laboratory, Division of Biological and Environmental Sciences & Engineering, King Abdullah University of Science and Technology, 23955-6900 Thuwal, Saudi Arabia

    • Anders Eriksson
  20. Institute for Theoretical Physics, ETH Zürich, Wolfgang-Pauli-Str. 27, 8093 Zürich, Switzerland

    • Ivan P. Levkivskyi
  21. Jeffrey Cheah School of Medicine & Health Sciences, Monash University Malaysia, Jalan Lagoon Selatan, Sunway City, 46150 Selangor, Malaysia

    • Farhang A. Aghakhanian &
    •  
    • Maude E. Phipps
  22. Evolutionary Medicine Group, Laboratoire d’Anthropologie Moléculaire et Imagerie de Synthèse, UMR 5288, Centre National de la Recherche Scientifique, Université de Toulouse 3, 31073 Toulouse, France

    • Nicolas Brucato &
    •  
    • Francois-Xavier Ricaut
  23. Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Blegdamsvej 3B, 2200 Copenhagen N, Denmark

    • Søren Brunak
  24. CIMAR/CIIMAR, Centro Interdisciplinar de Investigação Marinha e Ambiental, Universidade do Porto, Rua dos Bragas 289, 4050-123 Porto, Portugal

    • Paula F. Campos
  25. National Parks and Wildlife, Sturt Highway, Buronga, New South Wales 2739, Australia

    • Warren Clark
  26. Explico Foundation, Vågavegen 16, 6900 Florø, Norway

    • Sturla Ellingvåg
  27. Giriwandi, Gimuy Yidinji Country, Queensland 4868, Australia

    • Gudjugudju Fourmile
  28. Research Department of Genetics, Evolution and Environment, University College London, Gower Street, London WC1E 6BT, UK

    • Pascale Gerbault &
    •  
    • Mark G. Thomas
  29. UCL Department of Anthropology, 14 Taviton Street, London WC1H 0BW, UK

    • Pascale Gerbault &
    •  
    • Andrea B. Migliano
  30. Yinhawangka elder, Perth, Western Australia 6062, Australia

    • Darren Injie
  31. Papua New Guinea Institute of Medical Research, PO Box 60, Goroka, Papua New Guinea

    • George Koki,
    •  
    • William Pomat &
    •  
    • Peter Siba
  32. Archaeology, School of Humanities & Social Sciences, University PO Box 320, University of Papua New Guinea & College of Arts, Society & Education, James Cook University, Cairns, Queensland 4811, Australia

    • Matthew Leavesley
  33. Ngadju elder, Coolgardie, Western Australia 6429, Australia

    • Betty Logan
  34. Wongatha elder, Kurrawang, Western Australia 6430, Australia

    • Aubrey Lynch
  35. Department of Anatomy, University of Otago, Dunedin 9054, New Zealand

    • Elizabeth A. Matisoo-Smith
  36. 2209 Springbrook Road, Springbrook, Queensland 4213, Australia

    • Peter J. McAllister
  37. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK

    • Alexander J. Mentzer
  38. Estonian Biocentre, Riia 23b, Tartu 51010, Estonia

    • Mait Metspalu
  39. 86 Workshop Road, Yarrabah, Queensland 4871, Australia

    • Les Murgha
  40. Esperance Nyungar elder, Esperance, Western Australia 6450, Australia

    • Doc Reynolds
  41. Atakani Street, Napranum, Queensland 4874, Australia

    • Thomas Wales
  42. 2 Wynnum North Road, Wynnum, Queensland 4178, Australia

    • Colleen Ma’run Wall
  43. School of Anthropology and Museum Ethnography, Oxford University, Oxford OX2 6PE, UK

    • Stephen J. Oppenheimer
  44. Centre for Rock Art Research and Management, M257, University of Western Australia, Perth, Western Australia 6009, Australia

    • Joe Dortch
  45. Leverhulme Centre for Human Evolutionary Studies, Department of Archaeology and Anthropology, University of Cambridge, Fitzwilliam Street, Cambridge CB2 1QH, UK

    • Robert A. Foley &
    •  
    • Marta Mirazón Lahr
  46. Department of Linguistics, Yale University, 370 Temple Street, New Haven, Connecticut 06520, USA

    • Claire Bowern
  47. Institute for Human Genetics, University of California, San Francisco, California 94143, USA

    • Jeffrey D. Wall
  48. Departments of Integrative Biology and Statistics, University of California, Berkeley, California 94720, USA

    • Rasmus Nielsen

Contributions

G.A., J.Y.C., J.E.C., T.H.H., E.M., S.P., S.R., S.Sc., S.Su. and J.L.W. contributed equally and are listed alphabetically in the author list; A.A., C.Ba., I.D., A.E., A.Mar., I.M. and I.P. contributed equally and are listed alphabetically in the author list; T.S.K., I.P.L., J.V.M.-M., S.N., F.R., M.Si. and Y.X. contributed equally and are listed alphabetically in the author list. E.W. and D.M.L. initially conceived and headed the project. L.E. led the genetic load and the SFS-based demographic analyses. M.S.S. headed the research at the Wellcome Trust Sanger Institute. A.-S.M. planned and coordinated the genetic analyses and the sequencing of the Aboriginal Australian genomes. C.M., J.L.W., T.H.H., P.F.C., W.C., G.F., D.I., B.L., A.L., P.J.M., L.M., D.R., T.W., C.W., J.D., M.C.W. and E.W. collaborated with local groups to collect Aboriginal Australian samples. N.B., P.G., G.K., M.L., A.J.M., A.B.M., W.P., F.-X.R., P.S., M.G.T. and S.J.O. collaborated with local groups to collect Papuan samples. S.E. collaborated with local groups to collect the Rapanui sample. A.Mar. extracted DNA for the Aboriginal Australian genomes. M.S.S., A.B. and C.T.-S. coordinated the design and sequencing of the Papuan genomes. O.L., V.C.S., I.A., A.-S.M., A.B., G.A., J.Y.C., J.E.C., T.H.H., E.M., S.P., S.R., S.Sc., S.Su., J.L.W., A.A., C.Ba., I.D., A.E., A.Man., I.M., I.P., T.S.K., I.P.L., J.V.M.-M., S.N., F.R., M.Si., F.A., S.B., L.E., J.D.W. and T.M. analysed genetic data. C.Bo. collected and analysed linguistic data. L.E., E.W., D.M.L., Y.X., M.E.P., C.T.-S., R.D., M.S.S., A.Man., M.H.S., T.M., M.St. and R.N. supervised genetic analyses. M.C.W., C.M., W.C., G.F., D.I., B.L., A.L., P.J.M., L.M., D.R., T.W., C.W., E.A.M.-S., M.M., M.E.P., S.J.O., J.D., A.B.M., R.A.F. and M.M.L. provided archaeological, anthropological and historical context. A.-S.M., V.C.S., O.L., I.A., A.B., M.M.L., R.N., L.E., D.M.L. and E.W. wrote the manuscript with critical input from G.A., T.H.H., E.M., S.Sc., S.Su., J.L.W., C.Ba., A.E., I.P., E.A.M.-S., M.S.S., S.J.O., C.T.-S., R.D., M.G.T., J.D., A.Man., M.H.S., R.A.F., C.Bo., J.D.W., T.M., M.St. and all other coauthors. A.-S.M., V.C.S., O.L., I.A. and A.B. revised and compiled the Supplementary Information.

Competing financial interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to: 
The Aboriginal Australian and Papuan whole genome sequence data generated in this study have been deposited at the European Genome-phenome Archive (EGA, http://www.ebi.ac.uk/ega/), which is hosted by the EBI, under the accession numbers EGAS00001001766 andEGAS00001001247, respectively. The Papuan SNP array data generated in this study can be found under http://geogenetics.ku.dk/latest-news/alle_nyheder/2016/data.

Extended data figures and tables

Extended Data Figures

  1. Extended Data Figure 1: Per-individual admixture proportions of K = 7 ancestral components including Aboriginal Australians, New Guineans, Europeans, Africans, Melanesians and Polynesians. (581 KB)
    The genome of each individual is depicted as a bar and is coloured according to the estimated genome-wide proportions of ancestry components. An unrooted tree showing the relationships between the identified ancestral components is also estimated by our method. Each ancestry has been labelled with the name of the population (see also map) showing the highest fraction of that ancestral component. The cross-validation error is minimized for this value of K for fivefold cross-validation. The rooted tree supports the shared genetic origin of Aboriginal Australians, Papuans and Bougainvilleans. Note that only individuals with more than 50% of Aboriginal Australian ancestry in their genomes (defined in Supplementary Information section S06) were included in the analyses. Refer to ref. 58 and Supplementary Information section S05 for details about the method and the analysis. Map data ©2016 Google, INEGI. Tree constructed with http://jade-cheng.com/trees/.
  2. Extended Data Figure 2: Genetic relationships of Aboriginal Australians and Papuans. (491 KB)
    a, Genetic affinities between a western central desert (WCD02) genome and Aboriginal Australians and Papuans. Outgroup f3 statistics between WCD02 and all other Aboriginal Australians and Highland Papuan individuals that were whole-genome sequenced for this study, using the genotypes called from the sequencing data. Because the widespread recent admixture in Aboriginal Australians has large confounding effects on the f3statistics, the values were adjusted using the slope coefficient from a simple linear regression model fitted to the relationship between f3 and the fraction of non-indigenous (that is, neither Aboriginal Australian nor Papuan) ancestry in each individual genome. The adjusted f3 statistics display a genetic gradient that separates western and eastern Aboriginal Australian populations. However, we find no differences between Papuan population samples in their level of Aboriginal Australian affinity (Kruskal–Wallis test, P = 0.083). Horizontal lines correspond to ±1 standard error. b, Genetic affinities between a Papuan highlander genome and Aboriginal Australians and Papuans. The Papuan highlander sample MAR01 from the Marawaka area was arbitrarily chosen as a reference point for this analysis. f3 values were adjusted for recent admixture as in a. All Aboriginal Australian groups display a similar level of Highland Papuan affinity (with the exception of three outlier individuals from the north-eastern WPA and CAI populations: WPA06, WPA05 and CAI10, the latter two of which are known to have at least one parent with origins in Papua New Guinea or the Torres Strait Islands). While some differences between groups are actually statistically significant (Kruskal–Wallis test, P = 0.0002, after removing the three outliers), which could be consistent with, for example, low levels of Papuan gene flow into some Aboriginal Australian groups (see Supplementary Information sections S06 and S07), we caution that some of these differences are probably due to imperfect adjustment for Eurasian admixture (the adjusted f3 is highest in the WCD population, which has the least Eurasian admixture). Horizontal lines correspond to ±1 standard error. c, MSMC analyses. Linear interpolation through the midpoints of the time intervals of the relative cross coalescence rate estimates from MSMC25 using pairs of individuals including one HGDP-Papuan and one other individual as indicated. We used CAI01, PIL06, WCD01, WON03 and an ECCAC sample for this analysis (see Supplementary Information section S08 for details). The MSMC results were scaled using a mutation rate of 1.25×10−8 per generation per site as suggested in ref. 41 and a generation time of 29 years, corresponding to the average hunter–gatherer generation interval for males and females42.
  3. Extended Data Figure 3: Introgressed archaic sites and putative Denisovan and Neanderthal haplotypes. (876 KB)
    a, Distribution of number of putative introgressed sites per individual from archaic humans. The number of Neanderthal-specific introgressed sites per individual increases from Europe to Australia, and then decreases in Amerindians, which is consistent with recurrent Neanderthal (or Neanderthal-related archaic) gene flow during the expansion into Eurasia. Our results are thus indicative of several pulses of Neanderthal gene flow into modern humans, as inferred previously484950. We note, however, that the apparent high levels of Neanderthal-specific introgressed sites in Australo-Papuans can be explained by the expected number of misclassified Neanderthal introgressed sites resulting from the shared ancestry with Denisovans (see Supplementary Information section S11 for details). be, Putative Denisovan (PDH) and Neanderthal haplotypes (PNH). The putative haplotypes correspond to clusters (four or more SNPs spanning at least 4 kb) of heterozygous or homozygous genotypes in complete linkage disequilibrium (‘diplotypes’) that are potentially the result of Neanderthal or Denisovan admixture. Those diplotypes are homozygous ancestral in 10 Africans, homozygous derived in the Denisovan for the PDH (respectively Neanderthal for the PNH), homozygous ancestral in the Neanderthal for the PDH (respectively Denisovan for the PNH), and with the derived allele segregating in all other contemporary non-African humans (see Supplementary Information section S10 for details). We report the average number of PDHs and PNHs (b), the correlation between the estimated amount of Australo-Papuan ancestry (see Fig. 2aExtended Data Fig. 1Supplementary Information section S05) and the number of identified PDHs for each Australian sample (c), the sum of the lengths (d) and the average length (e) of the PDHs and PNHs per individual for worldwide populations included in our reference panel (see Supplementary Information section S04).
  4. Extended Data Figure 4: Out of Africa: admixture graphs based on D-statistics and MSMC analyses. (303 KB)
    a, Admixture graphs representing some of the topologies considered for the two waves and one wave Out of Africa models assuming Denisovan admixture. All topologies are identical except for the coloured lineages representing Australo-Papuans (green), Neanderthal (Nea, orange) and Denisovan (Den, blue). The graphs differ in (1) the number of OoA events, and (2) the number of Neanderthal admixture pulses. Png, HGDP-Papuan. b, Sum of squared errors between the observed D-statistics and the expectations for each quartet in the graph involving the chimpanzee as an outgroup for each of the admixture graphs shown in a and the corresponding four without Denisovan admixture. Each point is the result of the optimization procedure with a different starting point. See Supplementary Information section S09 for details. c, Relative cross coalescence rate (CCR) estimates from MSMC25 for pairs of individuals including one African sample (Yoruba, Dinka and San) and one other, as indicated in the legend. d, Simulation study to assess the effect of archaic admixture on the CCR rates. Relative CCR estimated for data simulated under a simple two-population divergence model where one of the populations admixed at different rates with an archaic population. SeeSupplementary Information section S08 for details.
  5. Extended Data Figure 5: Inferred deleterious mutations. (121 KB)
    a, Box plot of the number of derived homozygous sites per individual for worldwide populations that are predicted to be deleterious. Deleteriousness of SNPs was inferred using genomic evolutionary rate profiling (GERP) rejected substitution scores. Derived alleles with a rejected substitution score larger than 2 were considered to be deleterious, see Supplementary Information section S11bc, Average rejected substitution score per individual calculated across heterozygous sites (b), and derived homozygous sites (c). Each coloured symbol corresponds to estimates from a single individual. Homozygosity is calculated as the number of derived homozygous sites divided by the number of sites at which an individual carries at least one copy of the derived allele. Solid lines show the linear regression of homozygosity against average rejected substitution score per individual for non-African modern humans. Dashed lines indicate the 95% confidence interval for the linear regression. See Supplementary Information S11 for details.
  6. Extended Data Figure 6: Effective population size changes over time. (213 KB)
    a, Population size estimates from MSMC for pairs of individuals from several populations within and outside of Australia. For each run, we used two individuals from each population, that is, four haplotypes in each run. MSMC results were scaled as in Fig. 3b, Bayesian skyline plots (BSP) calculated from the mtDNA genome sequences, showing the effective population size estimates over time when considering either groups from northeastern Australia (CAI, WPA) or groups from southwestern Australia (ENY, NGA, WCD, WON). Solid lines are the estimates, dashed lines are the corresponding 95% credible intervals (see Supplementary Information section S12).
  7. Extended Data Figure 7: Genetics mirrors geography and languages. (488 KB)
    ab, Procrustes analyses of the first two dimensions of a classical multidimensional scaling (MDS) analysis of the Aboriginal Australian genome sequences (autosomes). We considered two cases: an analysis including all variants (a), or only the variants remaining after genomic regions of putative recent European and East Asian origin are ‘masked’ (b,Supplementary Information section S06). Both MDS plots have been rotated towards the best overlap with geographic sampling locations as defined by Procrustes analysis51. In each plot, the connecting lines indicate the error of the MDS coordinates towards the assigned population-sampling geographic coordinates. We find that the genetic relationships within Australia mirrors geography, with a significant correlation for both cases, that is, rGEN,GEO = 0.59, P < 0.0005 for all variants and even higher, rGEN,GEO = 0.77, P <0 .0005="" 65="" a="" aboriginal="" an="" angle="" approach="" at="" australian="" axis="" bearing="" compared="" correlogram="" data-saferedirecturl="https://www.google.com/url?hl=en&q=http://www.nature.com/nature/journal/vaop/ncurrent/full/nature18299.html%23supplementary-information&source=gmail&ust=1475765934850000&usg=AFQjCNEPahU7QRpnRRAgqfCbdabAJgn6Rw" data.="" differentiation="" direction="" equator="" find="" for="" genetic="" genomes="" href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature18299.html#supplementary-information" in="" is="" main="" masked="" northeast="" of="" southwest="" style="color: #5c7996; text-decoration: none;" target="_blank" that="" the="" to="" using="" we="">Supplementary Information section S13
). cd, Correspondence between genetics and linguistics. c, Unrooted neighbour-joining FST-based genetic tree (cladogram). Weir and Cockerham FST distance was computed between the Aboriginal Australian populations after masking the Eurasian tracts. Statistical robustness of each branch was estimated by means of a bootstrap analysis (1,000 replicates, Supplementary Information section S05). d, Bayesian phylogenetic tree for the 28 different Pama–Nyungan languages represented in this sample (from ref. 13, see Supplementary Information section S15). Posterior probabilities are also indicated. Note that one language group can be shared by different Aboriginal Australian groups. The linguistic tree was built with BEAST52eg, Gene flow across the continent. e, Mantel non-parametric r (estimating the goodness of fit between genetic differentiation and connectivity) versus ratios of resistance of inland to coastal nodes, showing a peak at 1.7.f, Best fit of pairwise population genetic differentiation, FST (computed between the nine Aboriginal Australian groups after masking Eurasian tracts (Supplementary Information section S06)), versus pairwise connectivity based on the environment (estimated as resistance) when moving inland is 1.7 times harder than moving along coastal nodes. g, Gene flow across the Australian landscape, quantified as the cumulative current for pairwise connections among Aboriginal Australian groups (black circles), with larger current (warmer colours) representing greater gene flow.
  • Extended Data Figure 8: European, East Asian and Papuan genomic tracts in Aboriginal Australians. (137 KB)
    a, Distribution of the tracts assigned to Aboriginal Australian (WCD), Papuan, East Asian or European ancestry for 58 unrelated non-WCD Aboriginal Australian samples. Most of the shorter tracts were of Papuan origin, suggesting that a large fraction of the Papuan gene flow is much older than that from Europe and East Asia, consistent with a Papuan influence spreading slowly from northeastern to southwestern Australia by ancient migration. b, Corresponding scatter plot with fitted line of per-individual variance in Papuan tract length versus geographic distance from WCD, the latter calculated using the great-circle distance formula for pairs of individual GPS coordinates. Papuan tract distribution showed a strong and significant correlation with distance from WCD (r = 0.64;P < 1 × 10−5), with ‘younger tracts’ (that is, with a larger variance) closer to New Guinea and ‘older tracts’ (that is, with a smaller variance) closer to WCD. This is also consistent with continuous Papuan gene flow spreading from the northeast.
  • Extended Data Tables

    1. Extended Data Table 1: Whole genome sequence depth of coverage, haplogroup and language assignments for the Aboriginal Australian samples (413 KB)
    2. Extended Data Table 2: Selection scan in Aboriginal Australians (365 KB)

    Supplementary information

    PDF files

    1. Supplementary Information (18 MB)
      This file contains Supplementary Text and Data, Supplementary Figures, Supplementary Tables and additional references (see Contents for more details).
      FIGURES: Show only the first Figure. The rest must be consulted at the original site. 




















      SOURCE: NATURE

      Nature
       
       
      doi:10.1038/nature18299
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