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      Ancient goat genomes reveal mosaic domestication in the Fertile Crescent

      1 , 1 , 2 , 1 , 3 , 1 , 4 , 1 , 1 , 5 , 1 , 4 , 1 , 5 , 6 , 7 , 8 , 9 , 10 , 10 , 11 , 12 , 13 , 12 , 14 , 15 , 16 , 17 , 12 , 13 , 13 , 13 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 5 , 26 , 27 , 2 , 7 , 12 , 13 , 15 , 1
      Science
      American Association for the Advancement of Science (AAAS)
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          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.

          How humans got their goats

          Little is known regarding the location and mode of the early domestication of animals such as goats for husbandry. To investigate the history of the goat, Daly et al.sequenced mitochondrial and nuclear sequences from ancient specimens ranging from hundreds to thousands of years in age. Multiple wild populations contributed to the origin of modern goats during the Neolithic. Over time, one mitochondrial type spread and became dominant worldwide. However, at the whole-genome level, modern goat populations are a mix of goats from different sources and provide evidence for a multilocus process of domestication in the Near East. Furthermore, the patterns described support the idea of multiple dispersal routes out of the Fertile Crescent region by domesticated animals and their human counterparts.

          Science, this issue p. [Related article:]85

          Abstract

          Ancient goat genomes elucidate a dispersed domestication process across the Near East.

          Abstract

          Current genetic data are equivocal as to whether goat domestication occurred multiple times or was a singular process. We generated genomic data from 83 ancient goats (51 with genome-wide coverage) from Paleolithic to Medieval contexts throughout the Near East. Our findings demonstrate that multiple divergent ancient wild goat sources were domesticated in a dispersed process that resulted in genetically and geographically distinct Neolithic goat populations, echoing contemporaneous human divergence across the region. These early goat populations contributed differently to modern goats in Asia, Africa, and Europe. We also detect early selection for pigmentation, stature, reproduction, milking, and response to dietary change, providing 8000-year-old evidence for human agency in molding genome variation within a partner species.

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          Most cited references127

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          Is Open Access

          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Is Open Access

            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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              Cutadapt removes adapter sequences from high-throughput sequencing reads

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                Author and article information

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                Journal
                Science
                Science
                American Association for the Advancement of Science (AAAS)
                0036-8075
                1095-9203
                July 06 2018
                July 06 2018
                : 361
                : 6397
                : 85-88
                Affiliations
                [1 ]Smurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland.
                [2 ]Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK.
                [3 ]Department of Earth Sciences, Natural History Museum, London SW7 5BD, UK.
                [4 ]Palaeogenetics Group, Institute of Organismic and Molecular Evolution (iOME), Johannes Gutenberg University Mainz, 55099 Mainz, Germany.
                [5 ]BioArCh, University of York, York YO10 5DD, UK.
                [6 ]Museum of Natural History, University of Copenhagen, Copenhagen, Denmark.
                [7 ]National Natural History Collections, Faculty of Life Sciences, The Hebrew University, Jerusalem, Israel.
                [8 ]Gazi University, Ankara 06500, Turkey.
                [9 ]Zinman Institute of Archaeology, University of Haifa, Mount Carmel, Haifa, Israel.
                [10 ]Université Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, F-38000 Grenoble, France.
                [11 ]Groningen Institute of Archaeology, Groningen University, Groningen, Netherlands.
                [12 ]Archéozoologie, Archéobotanique (UMR 7209), CNRS, MNHN, UPMC, Sorbonne Universités, Paris, France.
                [13 ]Archaeozoology section, Archaeometry Laboratory, University of Tehran, Tehran, Iran.
                [14 ]Department of Archaeology, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran.
                [15 ]Osteology Department, National Museum of Iran, Tehran, Iran.
                [16 ]Trakya Universitesi, Edebiyat Fakültesi, Arkeoloi Bölümü, Edirne, Turkey.
                [17 ]Department of Anthropology, Whitman College, Walla Walla, WA 99362, USA.
                [18 ]Faculty of Cultural Heritage, Handicrafts and Tourism, University of Mazandaran, Noshahr, Iran.
                [19 ]Provincial Office of the Iranian Center for Cultural Heritage, Handicrafts and Tourism Organisation, North Khorassan, Bojnord, Iran.
                [20 ]School of History, Classics and Archaeology, University of Edinburgh, William Robertson Wing, Old Medical School, Edinburgh EH8 9AG, UK.
                [21 ]Prehistory Department, National Museum of Iran, Tehran, Iran.
                [22 ]Institut für Archäologische Wissenschaften, Goethe Universität, Frankfurt am Main, Germany.
                [23 ]Institute of Archaeology and Ethnology, National Academy of Sciences of the Republic of Armenia, Yerevan 0025, Republic of Armenia.
                [24 ]Department of Anthropology, University of Vienna, 1090 Vienna, Austria.
                [25 ]Institute of Archeology, University College London, London, UK.
                [26 ]Department of Anthropology, University of North Carolina, Chapel Hill, NC, USA.
                [27 ]Department of Natural Sciences, German Archaeological Institute, 14195 Berlin, Germany.
                Article
                10.1126/science.aas9411
                29976826
                06ffa860-5bc0-4f87-80e8-cdb53a949c29
                © 2018
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