51
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Ancient DNA suggests modern wolves trace their origin to a Late Pleistocene expansion from Beringia

      research-article
      1 , 2 , 3 , 4 , , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 10 , 14 , 15 , 6 , 6 , 6 , 6 , 16 , 17 , 2 , 6 , 18 , 13 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 9 , 26 , 27 , 27 , 28 , 27 , 5 , 29 , 30 , 2 , 31 , 32 , 8 , 31 , 33 , 34 , 35 , 6 , 36 , 9 , 37 , 1 , , 2 , 38 , 39 , , 2 ,
      Molecular Ecology
      John Wiley and Sons Inc.
      Approximate Bayesian Computation, ancient DNA, coalescent modelling, megafauna, Pleistocene, population structure, population turnover, wolves

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Grey wolves ( Canis lupus) are one of the few large terrestrial carnivores that have maintained a wide geographical distribution across the Northern Hemisphere throughout the Pleistocene and Holocene. Recent genetic studies have suggested that, despite this continuous presence, major demographic changes occurred in wolf populations between the Late Pleistocene and early Holocene, and that extant wolves trace their ancestry to a single Late Pleistocene population. Both the geographical origin of this ancestral population and how it became widespread remain unknown. Here, we used a spatially and temporally explicit modelling framework to analyse a data set of 90 modern and 45 ancient mitochondrial wolf genomes from across the Northern Hemisphere, spanning the last 50,000 years. Our results suggest that contemporary wolf populations trace their ancestry to an expansion from Beringia at the end of the Last Glacial Maximum, and that this process was most likely driven by Late Pleistocene ecological fluctuations that occurred across the Northern Hemisphere. This study provides direct ancient genetic evidence that long‐range migration has played an important role in the population history of a large carnivore, and provides insight into how wolves survived the wave of megafaunal extinctions at the end of the last glaciation. Moreover, because Late Pleistocene grey wolves were the likely source from which all modern dogs trace their origins, the demographic history described in this study has fundamental implications for understanding the geographical origin of the dog.

          Abstract

          Related collections

          Most cited references60

          • Record: found
          • Abstract: found
          • Article: not found

          The genetic history of Ice Age Europe

          Modern humans arrived in Europe ~45,000 years ago, but little is known about their genetic composition before the start of farming ~8,500 years ago. We analyze genome-wide data from 51 Eurasians from ~45,000-7,000 years ago. Over this time, the proportion of Neanderthal DNA decreased from 3–6% to around 2%, consistent with natural selection against Neanderthal variants in modern humans. Whereas the earliest modern humans in Europe did not contribute substantially to present-day Europeans, all individuals between ~37,000 and ~14,000 years ago descended from a single founder population which forms part of the ancestry of present-day Europeans. A ~35,000 year old individual from northwest Europe represents an early branch of this founder population which was then displaced across a broad region, before reappearing in southwest Europe during the Ice Age ~19,000 years ago. During the major warming period after ~14,000 years ago, a new genetic component related to present-day Near Easterners appears in Europe. These results document how population turnover and migration have been recurring themes of European pre-history.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Assessing the causes of late Pleistocene extinctions on the continents.

            One of the great debates about extinction is whether humans or climatic change caused the demise of the Pleistocene megafauna. Evidence from paleontology, climatology, archaeology, and ecology now supports the idea that humans contributed to extinction on some continents, but human hunting was not solely responsible for the pattern of extinction everywhere. Instead, evidence suggests that the intersection of human impacts with pronounced climatic change drove the precise timing and geography of extinction in the Northern Hemisphere. The story from the Southern Hemisphere is still unfolding. New evidence from Australia supports the view that humans helped cause extinctions there, but the correlation with climate is weak or contested. Firmer chronologies, more realistic ecological models, and regional paleoecological insights still are needed to understand details of the worldwide extinction pattern and the population dynamics of the species involved.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data.

              Molecular sequences obtained at different sampling times from populations of rapidly evolving pathogens and from ancient subfossil and fossil sources are increasingly available with modern sequencing technology. Here, we present a Bayesian statistical inference approach to the joint estimation of mutation rate and population size that incorporates the uncertainty in the genealogy of such temporally spaced sequences by using Markov chain Monte Carlo (MCMC) integration. The Kingman coalescent model is used to describe the time structure of the ancestral tree. We recover information about the unknown true ancestral coalescent tree, population size, and the overall mutation rate from temporally spaced data, that is, from nucleotide sequences gathered at different times, from different individuals, in an evolving haploid population. We briefly discuss the methodological implications and show what can be inferred, in various practically relevant states of prior knowledge. We develop extensions for exponentially growing population size and joint estimation of substitution model parameters. We illustrate some of the important features of this approach on a genealogy of HIV-1 envelope (env) partial sequences.
                Bookmark

                Author and article information

                Contributors
                liisaloog@gmail.com
                greger.larson@arch.ox.ac.uk
                aeriksson75@gmail.com
                am315@cam.ac.uk
                Journal
                Mol Ecol
                Mol. Ecol
                10.1111/(ISSN)1365-294X
                MEC
                Molecular Ecology
                John Wiley and Sons Inc. (Hoboken )
                0962-1083
                1365-294X
                02 January 2020
                May 2020
                : 29
                : 9 ( doiID: 10.1111/mec.v29.9 )
                : 1596-1610
                Affiliations
                [ 1 ] Research Laboratory for Archaeology and History of Art University of Oxford Oxford UK
                [ 2 ] Department of Zoology University of Cambridge Cambridge UK
                [ 3 ] Manchester Institute of Biotechnology School of Earth and Environmental Sciences University of Manchester Manchester UK
                [ 4 ] Department of Genetics University of Cambridge Cambridge UK
                [ 5 ] Department of Pediatric Gastroenterology and Metabolic Diseases Poznan University of Medical Sciences Poznan Poland
                [ 6 ] EvoGenomics GLOBE Institute University of Copenhagen Copenhagen Denmark
                [ 7 ] Natural History Museum University of Oslo Oslo Norway
                [ 8 ] The Qimmeq Project University of Greenland Nuussuaq Greenland
                [ 9 ] Institute for Archaeological Sciences University of Tübingen Tübingen Germany
                [ 10 ] Senckenberg Centre for Human Evolution and Palaeoenvironment University of Tübingen Tübingen Germany
                [ 11 ] Institute of Evolutionary Medicine University of Zurich Zurich Switzerland
                [ 12 ] Department of Human Evolution Max Planck Institute for Evolutionary Anthropology Leipzig Germany
                [ 13 ] OD Earth and History of Life Royal Belgian Institute of Natural Sciences Brussels Belgium
                [ 14 ] Department of Geosciences, Palaeobiology University of Tübingen Tübingen Germany
                [ 15 ] School of Integrative Biology University of Illinois at Urbana‐Champaign Urbana IL USA
                [ 16 ] BioArch, Department of Archaeology University of York York UK USA
                [ 17 ] OD Taxonomy and Phylogeny Royal Belgian Institute of Natural Sciences Brussels Belgium
                [ 18 ] Breeding Centre for Endangered Arabian Wildlife Sharjah United Arab Emirates
                [ 19 ] Mammoth Museum Institute of Applied Ecology of the North of the North‐Eastern Federal University Yakutsk Russia
                [ 20 ] Institute of Archaeology and Ethnography National Academy of Sciences of the Republic of Armenia Yerevan Republic of Armenia
                [ 21 ] Heidelberg Academy of Sciences and Humanities: The Role of Culture in Early Expansions of Humans Tübingen Germany
                [ 22 ] Department of Anthropology University of West Bohemia Pilzen Czech Republic
                [ 23 ] Moravian museum Brno Czech Republic
                [ 24 ] Hrdlička Museum of Man Faculty of Science Charles University Praha Czech Republic
                [ 25 ] Institute of Palaeoanatomy Domestication Research and History of Veterinary Medicine Ludwig‐Maximilians‐University Munich Munich Germany
                [ 26 ] Geological Institute Russian Academy of Sciences Moscow Russia
                [ 27 ] Institute for Material Culture History Russian Academy of Sciences St Petersburg Russia
                [ 28 ] Arctic and Antarctic Research Institute St Petersburg Russia
                [ 29 ] Institute of Biomedicine and Biocenter of Oulu Medical Research Center and University Hospital University of Oulu Oulu Finland
                [ 30 ] Carl R. Woese Institute for Genomic Biology University of Illinois at Urbana‐Champaign Urbana IL USA
                [ 31 ] Centre for GeoGenetics Globe Institute University of Copenhagen Copenhagen Denmark
                [ 32 ] Wellcome Trust Sanger Institute Cambridge UK
                [ 33 ] Department of Archaeology, Classics and Egyptology University of Liverpool Liverpool UK
                [ 34 ] Department of Archaeology University of Aberdeen Aberdeen UK
                [ 35 ] Department of Archaeology Simon Fraser University Burnaby BC Canada
                [ 36 ] Norwegian University of Science and Technology University Museum Trondheim Norway
                [ 37 ] Max Planck Institute for the Science of Human History Jena Germany
                [ 38 ] Department of Medical & Molecular Genetics King's College London Guys Hospital London UK
                [ 39 ] cGEM, Institute of Genomics, University of Tartu Tartu Estonia
                Author notes
                [*] [* ] Correspondence

                Liisa Loog, Department of Genetics, University of Cambridge, Cambridge, UK.

                Email: liisaloog@ 123456gmail.com

                Greger Larson, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK.

                Email: greger.larson@ 123456arch.ox.ac.uk

                Anders Eriksson, cGEM, Institute of Genomics, University of Tartu, Tartu, Estonia.

                Email: aeriksson75@ 123456gmail.com

                Andrea Manica, Department of Zoology, University of Cambridge, Cambridge, UK.

                Email: am315@ 123456cam.ac.uk

                Author information
                https://orcid.org/0000-0002-1770-101X
                https://orcid.org/0000-0003-1371-219X
                https://orcid.org/0000-0001-7310-9574
                https://orcid.org/0000-0003-3436-3726
                Article
                MEC15329
                10.1111/mec.15329
                7317801
                31840921
                908b3b12-4e24-4bcf-b463-43d215aef9d8
                © 2019 The Authors. Molecular Ecology published by John Wiley & Sons Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 05 October 2018
                : 16 October 2019
                : 03 December 2019
                Page count
                Figures: 5, Tables: 0, Pages: 15, Words: 11567
                Funding
                Funded by: Russian Science Foundation , open-funder-registry 10.13039/501100006769;
                Award ID: N16‐18‐10265 RNF
                Funded by: Grantová Agentura České Republiky , open-funder-registry 10.13039/501100001824;
                Award ID: GAČR15‐06446S
                Funded by: Polish National Science Center
                Award ID: 2015/19/P/NZ7/03971
                Funded by: Lundbeckfonden , open-funder-registry 10.13039/501100003554;
                Award ID: R52‐5062
                Funded by: Natural Environment Research Council , open-funder-registry 10.13039/501100000270;
                Award ID: NE/K003259/1
                Award ID: NE/K005243/1
                Funded by: H2020 European Research Council , open-funder-registry 10.13039/100010663;
                Award ID: 339941‐ADAPT
                Award ID: 647787‐LocalAdaptation
                Award ID: 681396‐Extinction Genomics
                Award ID: ERC‐2013‐StG 337574‐UNDEAD
                Categories
                From the Cover
                FROM THE COVER
                Population and Conservation Genetics
                Custom metadata
                2.0
                May 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.8.4 mode:remove_FC converted:26.06.2020

                Ecology
                approximate bayesian computation,ancient dna,coalescent modelling,megafauna,pleistocene,population structure,population turnover,wolves

                Comments

                Comment on this article