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      Variable kinship patterns in Neolithic Anatolia revealed by ancient genomes

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      1 , , 1 , 38 , 1 , 38 , 1 , 38 , 2 , 38 , 3 , 4 , 1 , 5 , 6 , 7 , 8 , 1 , 9 , 10 , 10 , 11 , 12 , 12 , 3 , 1 , 1 , 13 , 14 , 15 , 16 , 1 , 17 , 18 , 19 , 1 , 1 , 1 , 3 , 20 , 1 , 21 , 2 , 1 , 15 , 9 , 15 , 22 , 23 , 24 , 25 , 1 , 26 , 27 , 28 , 7 , 29 , 39 , 30 , 39 , 31 , 39 , 32 , 39 , 33 , 39 , 25 , 39 , 3 , 20 , 39 , 34 , 39 , 35 , 39 , 36 , 39 , 19 , 39 , 9 , 37 , 39 , ∗∗ , 3 , 20 , 39 , ∗∗∗ , 1 , 39 , 40 , ∗∗∗∗
      Current Biology
      Cell Press
      kinship, Neolithic transition, household composition, Anatolia, paleogenomics, identity by descent, intramural burial, relatedness

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          Summary

          The social organization of the first fully sedentary societies that emerged during the Neolithic period in Southwest Asia remains enigmatic, 1 mainly because material culture studies provide limited insight into this issue. However, because Neolithic Anatolian communities often buried their dead beneath domestic buildings, 2 household composition and social structure can be studied through these human remains. Here, we describe genetic relatedness among co-burials associated with domestic buildings in Neolithic Anatolia using 59 ancient genomes, including 22 new genomes from Aşıklı Höyük and Çatalhöyük. We infer pedigree relationships by simultaneously analyzing multiple types of information, including autosomal and X chromosome kinship coefficients, maternal markers, and radiocarbon dating. In two early Neolithic villages dating to the 9th and 8th millennia BCE, Aşıklı Höyük and Boncuklu, we discover that siblings and parent-offspring pairings were frequent within domestic structures, which provides the first direct indication of close genetic relationships among co-burials. In contrast, in the 7th millennium BCE sites of Çatalhöyük and Barcın, where we study subadults interred within and around houses, we find close genetic relatives to be rare. Hence, genetic relatedness may not have played a major role in the choice of burial location at these latter two sites, at least for subadults. This supports the hypothesis that in Çatalhöyük, 3, 4, 5 and possibly in some other Neolithic communities, domestic structures may have served as burial location for social units incorporating biologically unrelated individuals. Our results underscore the diversity of kin structures in Neolithic communities during this important phase of sociocultural development.

          Highlights

          • Genetic kinship estimated from co-buried individuals’ genomes in Neolithic Anatolia

          • Close relatives are common among co-burials in Aşıklı and Boncuklu

          • Many unrelated infants found buried in the same building in Çatalhöyük and Barcın

          • Neolithic societies in Southwest Asia may have held diverse concepts of kinship

          Abstract

          Yaka et al. use ancient genomes from Neolithic Anatolia and present evidence for diverse concepts of social kinship in Neolithic societies. In some communities, like Çatalhöyük, many genetically unrelated infants were buried together inside the same buildings, whereas in other sites, people buried together were frequently close biological kin.

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          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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            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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              PLINK: a tool set for whole-genome association and population-based linkage analyses.

              Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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                Author and article information

                Contributors
                Journal
                Curr Biol
                Curr Biol
                Current Biology
                Cell Press
                0960-9822
                1879-0445
                07 June 2021
                07 June 2021
                : 31
                : 11
                : 2455-2468.e18
                Affiliations
                [1 ]Department of Biological Sciences, Middle East Technical University (METU), Ankara, Turkey
                [2 ]Institute of Human Biology and Evolution, Faculty of Biology, Adam Mickiewicz University, Poznań, Poland
                [3 ]Department of Anthropology, Hacettepe University, Ankara, Turkey
                [4 ]Department of Health Informatics, Middle East Technical University (METU), Historic England, London, UK
                [5 ]Scientific Dating, Historic England, London, UK
                [6 ]Biological & Environmental Sciences, University of Stirling, Stirling, UK
                [7 ]Department of Anthropology, Stanford University, Stanford, CA, 94303 USA
                [8 ]Department of Genetics, University of Arizona, 85719, Tucson, AZ, USA
                [9 ]Department of Archaeology and Classical Studies, Stockholm University, Stockholm, Sweden
                [10 ]Centre for Palaeogenetics, Stockholm, Sweden
                [11 ]Archaeological Research Laboratory, Department of Archaeology and Classical Studies, Stockholm University, Stockholm, Sweden
                [12 ]Graduate School of Social Sciences, Middle East Technical University (METU), Ankara, Turkey
                [13 ]Department of Bioinformatics, Graduate School of Health Sciences, Hacettepe University, 06100, Ankara, Turkey
                [14 ]Department of Anthropology, University of Central Florida, Uppsala University, 751 05 Uppsala, Sweden
                [15 ]Human Evolution, Department of Organismal Biology, Uppsala University, 751 05 Uppsala, Sweden
                [16 ]SciLife Lab, Uppsala University, 751 05 Uppsala, Sweden
                [17 ]Department of Physical Anthropology, Institute of Forensic Medicine, University of Bern, Sulgenauweg 40, CH-3007 Bern, Switzerland
                [18 ]Centre for Archaeological Science, University of Wollongong, Wollongong, Australia
                [19 ]UMR 5199, De la Préhistoire à l’Actuel: Culture, Environnement et Anthropologie (PACEA), Université de Bordeaux, Pessac, France
                [20 ]Human G Lab, Department of Anthropology, Hacettepe University, Ankara, Turkey
                [21 ]Department of Archaeogenetics, Max-Planck Institute for the Science of Human History, Kahlaische Strasse 10, D-07745, Jena, Germany
                [22 ]Spatial Information Laboratory (SPINlab) at the Vrije Universiteit Amsterdam, Amsterdam, Netherlands
                [23 ]Department of Archaeology, Faculty of Letters, Ankara Hacı Bayram Veli University, Abant 1 Cad. No:10/2D, Yenimahalle, Ankara
                [24 ]School of Social Science, The University of Queensland, Michie Building, St Lucia, Brisbane, QLD, Australia
                [25 ]Department of Archaeology, Classics and Egyptology, University of Liverpool, 8–14 Abercromby Square, Liverpool, L69 7WZ, UK
                [26 ]Department of Prehistory, Faculty of Letters, Istanbul University, Ordu Cad. No: 6, 34459, Laleli, Istanbul
                [27 ]Faculty of Archaeology, Adam Mickiewicz University, Poznań, Poland
                [28 ]Department of Anthropology, Ohio State University, Columbus OH, USA 43210-1106
                [29 ]Institute of Social Sciences, Middle East Technical University (METU), Ankara, Turkey
                [30 ]Department of Anthropology, University of Nevada, Reno
                [31 ]Department of Modeling and Simulation, Graduate School of Informatics, Middle East Technical University (METU), Ankara, Turkey
                [32 ]Netherlands Institute in Turkey, Istanbul, Turkey
                [33 ]Department of Archaeology and History of Art, Koç University, 34450 Istanbul, Turkey
                [34 ]Mimar Sinan Fine Arts University, Istanbul 34134, Turkey
                [35 ]Department of Prehistory, Istanbul University, Istanbul 34134, Turkey
                [36 ]Department of Cross-Cultural and Regional Studies, University of Copenhagen, Copenhagen, Denmark
                [37 ]Centre for Palaeogenetics, Stockholm, Sweden
                Author notes
                []Corresponding author yakaryhn@ 123456gmail.com
                [∗∗ ]Corresponding author anders.gotherstrom@ 123456arklab.su.se
                [∗∗∗ ]Corresponding author fusunozer@ 123456hacettepe.edu.tr
                [∗∗∗∗ ]Corresponding author msomel@ 123456metu.edu.tr
                [38]

                These authors contributed equally

                [39]

                These authors contributed equally

                [40]

                Lead Contact

                Article
                S0960-9822(21)00423-1
                10.1016/j.cub.2021.03.050
                8210650
                33857427
                80d5ede3-be2d-4f34-9a43-bea2826e8dc2
                © 2021 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 19 September 2020
                : 8 January 2021
                : 15 March 2021
                Categories
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                Life sciences
                kinship,neolithic transition,household composition,anatolia,paleogenomics,identity by descent,intramural burial,relatedness

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