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Ancient mitochondrial DNA provides high-resolution time scale of the peopling of the Americas

1 , * , 2 , 1 , 1 , 3 , 4 , 5 , 3 , 4 , 5 , 3 , 4 , 5 , 6 , 1 , 7 , 8 , 8 , 9 , 9 , 10 , 9 , 11 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 17 , 18 , 19 , 19 , 6 , 3 , 4 , 5 , 20 , 1 , * , 1 , *

Science Advances

American Association for the Advancement of Science

Ancient DNA, Native America, colonization, Beringia

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      Abstract

      Native American population history is reexamined using a large data set of pre-Columbian mitochondrial genomes.

      Abstract

      The exact timing, route, and process of the initial peopling of the Americas remains uncertain despite much research. Archaeological evidence indicates the presence of humans as far as southern Chile by 14.6 thousand years ago (ka), shortly after the Pleistocene ice sheets blocking access from eastern Beringia began to retreat. Genetic estimates of the timing and route of entry have been constrained by the lack of suitable calibration points and low genetic diversity of Native Americans. We sequenced 92 whole mitochondrial genomes from pre-Columbian South American skeletons dating from 8.6 to 0.5 ka, allowing a detailed, temporally calibrated reconstruction of the peopling of the Americas in a Bayesian coalescent analysis. The data suggest that a small population entered the Americas via a coastal route around 16.0 ka, following previous isolation in eastern Beringia for ~2.4 to 9 thousand years after separation from eastern Siberian populations. Following a rapid movement throughout the Americas, limited gene flow in South America resulted in a marked phylogeographic structure of populations, which persisted through time. All of the ancient mitochondrial lineages detected in this study were absent from modern data sets, suggesting a high extinction rate. To investigate this further, we applied a novel principal components multiple logistic regression test to Bayesian serial coalescent simulations. The analysis supported a scenario in which European colonization caused a substantial loss of pre-Columbian lineages.

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      Fast and accurate short read alignment with Burrows–Wheeler transform

      Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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        BEDTools: a flexible suite of utilities for comparing genomic features

        Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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          Bayesian Phylogenetics with BEAUti and the BEAST 1.7

          Computational evolutionary biology, statistical phylogenetics and coalescent-based population genetics are becoming increasingly central to the analysis and understanding of molecular sequence data. We present the Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package version 1.7, which implements a family of Markov chain Monte Carlo (MCMC) algorithms for Bayesian phylogenetic inference, divergence time dating, coalescent analysis, phylogeography and related molecular evolutionary analyses. This package includes an enhanced graphical user interface program called Bayesian Evolutionary Analysis Utility (BEAUti) that enables access to advanced models for molecular sequence and phenotypic trait evolution that were previously available to developers only. The package also provides new tools for visualizing and summarizing multispecies coalescent and phylogeographic analyses. BEAUti and BEAST 1.7 are open source under the GNU lesser general public license and available at http://beast-mcmc.googlecode.com and http://beast.bio.ed.ac.uk
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            Author and article information

            Affiliations
            [1 ]Australian Centre for Ancient DNA, School of Biological Sciences and The Environment Institute, The University of Adelaide, Adelaide, South Australia 5005, Australia.
            [2 ]Department of Anthropology, University of California, Santa Cruz, Santa Cruz, CA 95064, USA.
            [3 ]Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
            [4 ]Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
            [5 ]Howard Hughes Medical Institute, Boston, MA 20815, USA.
            [6 ]Department of Archaeology and History, La Trobe University, Melbourne, Victoria 3086, Australia.
            [7 ]School of Mathematical Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia.
            [8 ]Museo de Sitio Huaca Pucllana, Miraflores, Lima 18, Peru.
            [9 ]Departamento de Humanidades, Pontificia Universidad Católica del Perú, Lima 32, Peru.
            [10 ]Centro de Investigaciones Arqueológicas del Museo de Sitio de Ancón, Lima 38, Peru.
            [11 ]Instituto Nacional de Antropología e Historia, Ciudad de Mexico, Mexico City 6500, Mexico.
            [12 ]Unidad de Arqueología y Museos, Ministerio de Culturas y Turismo de Bolivia, La Paz 3165, Bolivia.
            [13 ]Universidad de Magallanes, Punta Arenas 6210427, Chile.
            [14 ]Peabody Museum of Archaeology and Ethnology at Harvard University, Boston, MA 02138, USA.
            [15 ]Instituto de Investigaciones de Alta Montaña, Universidad Católica de Salta, Salta 4400, Argentina.
            [16 ]Consejo Nacional de Investigaciones Científicas y Técnicas, Godoy Cruz 2290, Cdad. Autónoma de Buenos Aires, Argentina.
            [17 ]National Geographic Society, Washington, DC 20036, USA.
            [18 ]Instituto de Investigaciones Arqueológicas y Paleontológicas del Cuaternario Pampeano–Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina.
            [19 ]Instituto de Alta Investigación, Universidad de Tarapacá, Arica 1000000, Chile.
            [20 ]School of Biological Sciences, University of Sydney, Sydney, New South Wales 2006, Australia.
            Author notes
            [†]

            These authors contributed equally to this work.

            [‡]

            Present address: Department of Integrative Biology, University of Texas at Austin, Austin, TX 78712, USA.

            [§]

            Equal senior authors.

            [¶]

            Present address: Max Planck Institute for the Science of Human History, Jena 07745, Germany.

            Journal
            Sci Adv
            Sci Adv
            SciAdv
            advances
            Science Advances
            American Association for the Advancement of Science
            2375-2548
            April 2016
            01 April 2016
            : 2
            : 4
            27051878
            4820370
            1501385
            10.1126/sciadv.1501385
            Copyright © 2016, The Authors

            This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

            Funding
            Funded by: FundRef http://dx.doi.org/10.13039/501100000923, Australian Research Council;
            Award ID: ID0EPPCM6714
            Award Recipient :
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            Research Article
            Research Articles
            SciAdv r-articles
            Anthropology
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            Meann Ramirez

            colonization, native america, beringia, ancient dna

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