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      Stone Age Yersinia pestis genomes shed light on the early evolution, diversity, and ecology of plague

      research-article
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      Proceedings of the National Academy of Sciences of the United States of America
      National Academy of Sciences
      ancient DNA, plague, Yersinia pestis

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          Significance

          The bacterium Yersinia pestis has caused numerous historically documented outbreaks of plague and research using ancient DNA could demonstrate that it already affected human populations during the Neolithic. However, the pathogen’s genetic diversity, geographic spread, and transmission dynamics during this early period of Y. pestis evolution are largely unexplored. Here, we describe a set of ancient plague genomes up to 5,000 y old from across Eurasia. Our data demonstrate that two genetically distinct forms of Y. pestis evolved in parallel and were both distributed across vast geographic distances, potentially occupying different ecological niches. Interpreted within the archeological context, our results suggest that the spread of plague during this period was linked to increased human mobility and intensification of animal husbandry.

          Abstract

          The bacterial pathogen Yersinia pestis gave rise to devastating outbreaks throughout human history, and ancient DNA evidence has shown it afflicted human populations as far back as the Neolithic. Y. pestis genomes recovered from the Eurasian Late Neolithic/Early Bronze Age (LNBA) period have uncovered key evolutionary steps that led to its emergence from a Yersinia pseudotuberculosis-like progenitor; however, the number of reconstructed LNBA genomes are too few to explore its diversity during this critical period of development. Here, we present 17 Y. pestis genomes dating to 5,000 to 2,500 y BP from a wide geographic expanse across Eurasia. This increased dataset enabled us to explore correlations between temporal, geographical, and genetic distance. Our results suggest a nonflea-adapted and potentially extinct single lineage that persisted over millennia without significant parallel diversification, accompanied by rapid dispersal across continents throughout this period, a trend not observed in other pathogens for which ancient genomes are available. A stepwise pattern of gene loss provides further clues on its early evolution and potential adaptation. We also discover the presence of the flea-adapted form of Y. pestis in Bronze Age Iberia, previously only identified in in the Caucasus and the Volga regions, suggesting a much wider geographic spread of this form of Y. pestis. Together, these data reveal the dynamic nature of plague’s formative years in terms of its early evolution and ecology.

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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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              The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

              Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                12 April 2022
                26 April 2022
                12 April 2022
                : 119
                : 17
                : e2116722119
                Affiliations
                [1] aDepartment of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology , 04103 Leipzig, Germany;
                [2] bDepartment of Archaeogenetics, Max Planck Institute for the Science of Human History , 07745 Jena, Germany;
                [3] cInstitute for Archaeological Sciences, Eberhard Karls University of Tübingen , 72074 Tübingen, Germany;
                [4] dBiology and Biotechnology Faculty, Al-Farabi Kazakh National University , 050040 Almaty, Kazakhstan;
                [5] eInstitute of Genetics and Physiology, Al-Farabi Kazakh National University , Almaty, 050060 Kazakhstan;
                [6] fFaculty of Mathematics and Computer Science, Friedrich-Schiller University , 07743 Jena, Germany;
                [7] gBegazy-Tasmola Research Center of History and Archeology , 050008 Almaty, Kazakhstan;
                [8] hNasledie Cultural Heritage Unit , 355006 Stavropol, Russian Federation;
                [9] iResearch Institute and Museum of Anthropology, Lomonosov Moscow State University , 125009 Moscow, Russian Federation;
                [10] jDepartment of Heritage Management, Archaeological Heritage Office Saxony , 01108 Dresden, Germany;
                [11] kDepartment of Prehistoric Archaeology, Institute of Archaeology, Czech Academy of Sciences , 11801 Prague, Czech Republic;
                [12] lDepartment of Geography, Prehistory, and Archaeology, University of the Basque Country , Vitoria-Gasteiz, 01006 Spain;
                [13] mDepartment of Anthropology, National Museum of Natural History, Smithsonian Institution , Washington, DC 20560;
                [14] nInstitute of Archaeology, University of Wrocław , 50139 Wrocław, Poland;
                [15] oArcheolodzy.org Foundation , 50316 Wrocław, Poland;
                [16] pEurasia-Department, German Archaeological Institute , 14195 Berlin, Germany;
                [17] qDepartment of Organismic and Evolutionary Biology, Harvard University , Cambridge, MA 02138;
                [18] rDepartment of Genetics, Harvard Medical School , Boston, MA 02115;
                [19] sFaculty of Biological Sciences, Friedrich-Schiller University , 07743 Jena, Germany;
                [20] tEvolutionary Pathogenomics, Max Planck Institute for Infection Biology , 10117 Berlin, Germany;
                [21] uInstitute of Ethnology and Anthropology, Russian Academy of Science , 119991 Moscow, Russian Federation;
                [22] vResearch Laboratory of Paleoanthropological Study, Institute of Archaeology named after A.Kh Margulan , Almaty, 50010 Kazakhstan;
                [23] wHistory Department, Al-Farabi Kazakh National University , 050040 Almaty, Kazakhstan;
                [24] xCentre for Egyptological Studies of the Russian Academy of Sciences, Russian Academy of Sciences , 119991 Moscow, Russian Federation;
                [25] yCurt Engelhorn Center Archaeometry , 68159 Mannheim, Germany;
                [26] zTransmission, Infection, Diversification & Evolution Group, Max Planck Institute for the Science of Human History , 07745 Jena, Germany;
                [27] aaInstitute of Evolutionary Biology, Consejo Superior de Investigaciones Cientificas-Universitat Pompeu Fabra , 08003 Barcelona, Spain;
                [28] bbDepartment of Anthropology, University of Auckland , 01010 Auckland, New Zealand;
                [29] ccInstitute for Pre- and Protohistoric Archaeology and Archaeology of the Roman Provinces, Ludwig Maximilian University Munich , 80539 Munich, Germany;
                [30] ddDepartment of Human Evolutionary Biology, Harvard University , Cambridge, MA 02138;
                [31] eeBIOMICs Research Group, University of the Basque Country Universidad del Pais Vasco/Euskal Herriko Unibertsitatea , 01006 Vitoria-Gasteiz, Spain;
                [32] ffArchaeological Centre , 779 00 Olomouc, Czech Republic;
                [33] ggDepartment of Evolutionary Anthropology, University of Vienna , 1030 Vienna, Austria;
                [34] hhInstitute of Fundamental Medicine and Biology, Kazan Federal University , Kazan, 420008 Russian Federation;
                [35] iiLaboratory for Structural Analysis of Biomacromolecules, Federal Research Center “Kazan Scientific Center of the Russian Academy of Sciences” , 420111 Kazan, Russian Federation;
                [36] jjDepartment of Anthropology, Harvard University , Cambridge, MA 02138
                Author notes

                Edited by Nils Chr. Stenseth, Universitetet i Oslo, Oslo, Norway; received September 21, 2021; accepted February 14, 2022

                Author contributions: A.A.V., G.U.N., M.A.S., L.M., W.H., J.K., and A. Herbig designed research; A.A.V., G.U.N., M.A.S., L.M., F.A., A. Beisenov, A.B.B., A. Buzhilova, M.C., L.B.D., M.D., M.E., J.F.-E., B.F., M.F., A. Hałuszko, S.H., É.H., A.N.H., A. Hübner, F.M.K., E. Khussainova, E. Kitov, A.O.K., C.K., C.L.-F., J.L., K.M., A.M., J.A.M.-A., I.O., L.P., S.P., J.P., R.P., D.R., S.R., R.S., H.S., R.I.T., S.V., E.V., C.W., P.W.S., W.H., J.K., and A. Herbig performed research; F.A., A. Beisenov, A.B.B., A. Buzhilova, M.C., L.B.D., M.D., M.E., J.F.-E., B.F., M.F., A. Hałuszko, S.H., É.H., E. Khussainova, E. Kitov, A.O.K., C.K., C.L.-F., J.L., K.M., A.M., J.A.M.-A., I.O., L.P., S.P., J.P., R.P., D.R., S.R., R.S., H.S., R.I.T., S.V., E.V., C.W., and P.W.S. contributed new reagents/analytic tools; A.A.V., G.U.N., M.A.S., L.M., A. Hübner, and F.M.K. analyzed data; and A.A.V., G.U.N., M.A.S., L.M., K.I.B., D.K., W.H., J.K., and A. Herbig wrote the paper.

                1A.A.V., G.U.N., M.A.S., and L.M. contributed equally to the work.

                Author information
                https://orcid.org/0000-0002-1737-2228
                https://orcid.org/0000-0001-8591-890X
                https://orcid.org/0000-0003-4126-8612
                https://orcid.org/0000-0003-2524-264X
                https://orcid.org/0000-0001-6398-2177
                https://orcid.org/0000-0002-6745-9903
                https://orcid.org/0000-0001-5327-5030
                https://orcid.org/0000-0003-4847-8532
                https://orcid.org/0000-0002-9860-2610
                https://orcid.org/0000-0002-3558-3440
                https://orcid.org/0000-0002-6714-4629
                https://orcid.org/0000-0003-3572-9996
                https://orcid.org/0000-0003-2812-6636
                https://orcid.org/0000-0002-0159-3288
                https://orcid.org/0000-0002-4274-4636
                https://orcid.org/0000-0002-7724-0702
                https://orcid.org/0000-0002-2130-6338
                https://orcid.org/0000-0003-2012-0782
                https://orcid.org/0000-0003-1629-8131
                https://orcid.org/0000-0002-7037-5292
                https://orcid.org/0000-0002-8107-6300
                https://orcid.org/0000-0002-5915-9337
                https://orcid.org/0000-0002-1040-0951
                https://orcid.org/0000-0003-0128-6568
                https://orcid.org/0000-0002-4528-5877
                https://orcid.org/0000-0003-2475-2007
                https://orcid.org/0000-0001-9144-3920
                https://orcid.org/0000-0003-1176-1166
                Article
                202116722
                10.1073/pnas.2116722119
                9169917
                35412864
                842dde26-5e20-4100-902b-31b2ae147840
                Copyright © 2022 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

                History
                : 14 February 2022
                Page count
                Pages: 11
                Funding
                Funded by: Max-Planck-Gesellschaft (MPG) 501100004189
                Award ID: NA
                Award Recipient : Aida Andrades Valtueña Award Recipient : Gunnar U Neumann Award Recipient : Maria A Spyrou Award Recipient : Franziska Aron Award Recipient : Kirsten I Bos Award Recipient : Alina N Hiss Award Recipient : Alexander Hübner Award Recipient : Felix M Key Award Recipient : Denise Kühnert Award Recipient : Alissa Mittnik Award Recipient : Luka Papac Award Recipient : Raphaela Stahl Award Recipient : Christina Warinner Award Recipient : Philipp W Stockhammer Award Recipient : Wolfgang Haak Award Recipient : Johannes Krause Award Recipient : Alexander Herbig
                Funded by: EC | H2020 | H2020 Priority Excellent Science | H2020 European Research Council (ERC) 100010663
                Award ID: 771234
                Award Recipient : Gunnar U Neumann Award Recipient : Maria A Spyrou Award Recipient : Franziska Aron Award Recipient : Svend Hansen Award Recipient : Alina N Hiss Award Recipient : Luka Papac Award Recipient : Sandra Penske Award Recipient : Wolfgang Haak Award Recipient : Johannes Krause Award Recipient : Alexander Herbig
                Funded by: EC | H2020 | H2020 Priority Excellent Science | H2020 European Research Council (ERC) 100010663
                Award ID: 856453
                Award Recipient : Gunnar U Neumann Award Recipient : Maria A Spyrou Award Recipient : Franziska Aron Award Recipient : Svend Hansen Award Recipient : Alina N Hiss Award Recipient : Luka Papac Award Recipient : Sandra Penske Award Recipient : Wolfgang Haak Award Recipient : Johannes Krause Award Recipient : Alexander Herbig
                Funded by: EC | H2020 | H2020 Priority Excellent Science | H2020 European Research Council (ERC) 100010663
                Award ID: 834616
                Award Recipient : Gunnar U Neumann Award Recipient : Maria A Spyrou Award Recipient : Franziska Aron Award Recipient : Svend Hansen Award Recipient : Alina N Hiss Award Recipient : Luka Papac Award Recipient : Sandra Penske Award Recipient : Wolfgang Haak Award Recipient : Johannes Krause Award Recipient : Alexander Herbig
                Funded by: Heidelberger Akademie der Wissenschaften (Heidelberg Academy of Sciences and Humanities) 100008661
                Award ID: WIN Kolleg
                Award Recipient : Ken Massy Award Recipient : Alissa Mittnik Award Recipient : Philipp W Stockhammer
                Funded by: Deutsche Forschungsgemeinschaft (DFG) 501100001659
                Award ID: 390713860
                Award Recipient : Alexander Hübner
                Funded by: Ministry of Education and Science of the Republic of Kazakhstan (Ministry of Education and Science, Republic of Kazakhstan) 501100004561
                Award ID: AP08856654
                Award Recipient : Lyazzat Musralina Award Recipient : Leyla B Djansugurova Award Recipient : Elmira Khussainova
                Categories
                419
                Biological Sciences
                Genetics

                ancient dna,plague,yersinia pestis
                ancient dna, plague, yersinia pestis

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