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Archaeogenomic evidence reveals prehistoric matrilineal dynasty

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      Abstract

      For societies with writing systems, hereditary leadership is documented as one of the hallmarks of early political complexity and governance. In contrast, it is unknown whether hereditary succession played a role in the early formation of prehistoric complex societies that lacked writing. Here we use an archaeogenomic approach to identify an elite matriline that persisted between 800 and 1130 CE in Chaco Canyon, the centre of an expansive prehistoric complex society in the Southwestern United States. We show that nine individuals buried in an elite crypt at Pueblo Bonito, the largest structure in the canyon, have identical mitochondrial genomes. Analyses of nuclear genome data from six samples with the highest DNA preservation demonstrate mother–daughter and grandmother–grandson relationships, evidence for a multigenerational matrilineal descent group. Together, these results demonstrate the persistence of an elite matriline in Chaco for ∼330 years.

      Abstract

      In ancient cultures without a writing system, it is difficult to infer the basis of status and rank. Here the authors analyse ancient DNA from nine presumed elite individuals buried successively over a 300-year period at Chaco Canyon, and show evidence of matrilineal relationships.

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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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        MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform.

        A multiple sequence alignment program, MAFFT, has been developed. The CPU time is drastically reduced as compared with existing methods. MAFFT includes two novel techniques. (i) Homo logous regions are rapidly identified by the fast Fourier transform (FFT), in which an amino acid sequence is converted to a sequence composed of volume and polarity values of each amino acid residue. (ii) We propose a simplified scoring system that performs well for reducing CPU time and increasing the accuracy of alignments even for sequences having large insertions or extensions as well as distantly related sequences of similar length. Two different heuristics, the progressive method (FFT-NS-2) and the iterative refinement method (FFT-NS-i), are implemented in MAFFT. The performances of FFT-NS-2 and FFT-NS-i were compared with other methods by computer simulations and benchmark tests; the CPU time of FFT-NS-2 is drastically reduced as compared with CLUSTALW with comparable accuracy. FFT-NS-i is over 100 times faster than T-COFFEE, when the number of input sequences exceeds 60, without sacrificing the accuracy.
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          Fast and accurate long-read alignment with Burrows–Wheeler transform

          Motivation: Many programs for aligning short sequencing reads to a reference genome have been developed in the last 2 years. Most of them are very efficient for short reads but inefficient or not applicable for reads >200 bp because the algorithms are heavily and specifically tuned for short queries with low sequencing error rate. However, some sequencing platforms already produce longer reads and others are expected to become available soon. For longer reads, hashing-based software such as BLAT and SSAHA2 remain the only choices. Nonetheless, these methods are substantially slower than short-read aligners in terms of aligned bases per unit time. Results: We designed and implemented a new algorithm, Burrows-Wheeler Aligner's Smith-Waterman Alignment (BWA-SW), to align long sequences up to 1 Mb against a large sequence database (e.g. the human genome) with a few gigabytes of memory. The algorithm is as accurate as SSAHA2, more accurate than BLAT, and is several to tens of times faster than both. Availability: http://bio-bwa.sourceforge.net Contact: rd@sanger.ac.uk
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            Author and article information

            Affiliations
            [1 ]Department of Anthropology, Pennsylvania State University , University Park, Pennsylvania 16802, USA
            [2 ]Department of Anthropology, University of Virginia , Charlottesville, Virginia 22904, USA
            [3 ]Division of Anthropology, American Museum of Natural History , New York, New York 10024, USA
            [4 ]Department of Genetics, Harvard Medical School , Boston, Massachusetts 02115, USA
            [5 ]Broad Institute of MIT and Harvard , Cambridge, Massachusetts 02142, USA
            [6 ]Howard Hughes Medical Institute, Harvard Medical School , Boston, Massachusetts 02115, USA
            [7 ]Peabody Museum of Archaeology and Ethnology, Harvard University , Cambridge, Massachusetts 02138, USA
            [8 ]Department of Biology, Pennsylvania State University , University Park, Pennsylvania 16802, USA
            Author notes
            [*]

            Present address: Department of Anthropology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013, USA

            Journal
            Nat Commun
            Nat Commun
            Nature Communications
            Nature Publishing Group
            2041-1723
            21 February 2017
            2017
            : 8
            28221340
            5321759
            ncomms14115
            10.1038/ncomms14115
            Copyright © 2017, The Author(s)

            This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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