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      Zoonotic origin of the human malaria parasite Plasmodium malariae from African apes

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          Abstract

          The human parasite Plasmodium malariae has relatives infecting African apes ( Plasmodium rodhaini) and New World monkeys ( Plasmodium brasilianum), but its origins remain unknown. Using a novel approach to characterise P. malariae-related sequences in wild and captive African apes, we found that this group comprises three distinct lineages, one of which represents a previously unknown, highly divergent species infecting chimpanzees, bonobos and gorillas across central Africa. A second ape-derived lineage is much more closely related to the third, human-infective lineage P. malariae, but exhibits little evidence of genetic exchange with it, and so likely represents a separate species. Moreover, the levels and nature of genetic polymorphisms in P. malariae indicate that it resulted from the zoonotic transmission of an African ape parasite, reminiscent of the origin of P. falciparum. In contrast, P. brasilianum falls within the radiation of human P. malariae, and thus reflects a recent anthroponosis.

          Abstract

          Plasmodium malariae is a cause of malaria in humans and related species have been identified in non-human primates. Here, the authors use genomic analyses to establish that human P. malariae arose from a host switch of an ape parasite whilst a species infecting New World monkeys can be traced to a reverse zoonosis.

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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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            Cutadapt removes adapter sequences from high-throughput sequencing reads

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              RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

              Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                lindsey.plenderleith@ed.ac.uk
                paul.sharp@ed.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                6 April 2022
                6 April 2022
                2022
                : 13
                : 1868
                Affiliations
                [1 ]GRID grid.4305.2, ISNI 0000 0004 1936 7988, Institute of Evolutionary Biology and Centre for Immunity, Infection and Evolution, University of Edinburgh, ; Edinburgh, EH9 3FL UK
                [2 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Department of Medicine, , University of Pennsylvania, ; Philadelphia, PA 19104 USA
                [3 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, Department of Microbiology, , University of Pennsylvania, ; Philadelphia, PA 19104 USA
                [4 ]GRID grid.121334.6, ISNI 0000 0001 2097 0141, Recherche Translationnelle Appliquée au VIH et aux Maladies Infectieuses, Institut de Recherche pour le Développement, , University of Montpellier, INSERM, ; 34090 Montpellier, France
                [5 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Department of Anthropology, , Washington University in St. Louis, ; St Louis, MO 63130 USA
                [6 ]GRID grid.512176.6, Wildlife Conservation Society, Congo Program, BP, ; 14537 Brazzaville, Republic of the Congo
                [7 ]GRID grid.435774.6, ISNI 0000 0001 0422 6291, Lester E. Fisher Center for the Study and Conservation of Apes, Lincoln Park Zoo, ; Chicago, IL USA
                [8 ]GRID grid.452614.0, ISNI 0000 0004 6015 3105, Metabiota Inc, ; San Francisco, CA 94117 USA
                [9 ]GRID grid.13652.33, ISNI 0000 0001 0940 3744, Robert Koch Institute, ; 13353 Berlin, Germany
                [10 ]Helmholtz Institute for One Health, Greifswald, Germany
                Author information
                http://orcid.org/0000-0003-1941-2876
                http://orcid.org/0000-0002-9393-3074
                http://orcid.org/0000-0003-2018-2721
                http://orcid.org/0000-0002-7196-5630
                http://orcid.org/0000-0003-4834-0509
                http://orcid.org/0000-0002-2169-7375
                http://orcid.org/0000-0002-9400-9887
                http://orcid.org/0000-0001-9771-543X
                Article
                29306
                10.1038/s41467-022-29306-4
                8987028
                35387986
                ddeff1ea-d499-4b0b-b4ed-155b30d3174b
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 October 2021
                : 7 March 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: R01 AI091595
                Award ID: R01 AI120810
                Award ID: R01 AI050529
                Award ID: P30 AI045008
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Funded by: U.S. Department of Health & Human Services | National Institutes of Health (NIH)
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                parasite evolution,parasite genomics,genome informatics,malaria
                Uncategorized
                parasite evolution, parasite genomics, genome informatics, malaria

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