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      Evolutionary analysis of the most polymorphic gene family in falciparum malaria

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          Abstract

          The var gene family of the human malaria parasite Plasmodium falciparum encode proteins that are crucial determinants of both pathogenesis and immune evasion and are highly polymorphic. Here we have assembled nearly complete var gene repertoires from 2398 field isolates and analysed a normalised set of 714 from across 12 countries. This therefore represents the first large scale attempt to catalogue the worldwide distribution of var gene sequences

          We confirm the extreme polymorphism of this gene family but also demonstrate an unexpected level of sequence sharing both within and between continents. We show that this is likely due to both the remnants of selective sweeps as well as a worrying degree of recent gene flow across continents with implications for the spread of drug resistance. We also address the evolution of the var repertoire with respect to the ancestral genes within the Laverania and show that diversity generated by recombination is concentrated in a number of hotspots. An analysis of the subdomain structure indicates that some existing definitions may need to be revised

          From the analysis of this data, we can now understand the way in which the family has evolved and how the diversity is continuously being generated. Finally, we demonstrate that because the genes are distributed across the genome, sequence sharing between genotypes acts as a useful population genetic marker.

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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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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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              New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

              PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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                Author and article information

                Contributors
                Role: Formal AnalysisRole: InvestigationRole: MethodologyRole: Project AdministrationRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – Review & Editing
                Role: Formal AnalysisRole: InvestigationRole: MethodologyRole: SoftwareRole: Visualization
                Role: Data CurationRole: Formal AnalysisRole: Investigation
                Role: Project AdministrationRole: Resources
                Role: Resources
                Role: ConceptualizationRole: Funding AcquisitionRole: InvestigationRole: MethodologyRole: Project AdministrationRole: SupervisionRole: ValidationRole: Writing – Review & Editing
                Role: ConceptualizationRole: Funding AcquisitionRole: InvestigationRole: Project AdministrationRole: SupervisionRole: Writing – Original Draft PreparationRole: Writing – Review & Editing
                Journal
                Wellcome Open Res
                Wellcome Open Res
                Wellcome Open Res
                Wellcome Open Research
                F1000 Research Limited (London, UK )
                2398-502X
                3 December 2019
                2019
                : 4
                : 193
                Affiliations
                [1 ]Parasite Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
                [2 ]Institute of Infection, Immunity & Inflammation, MVLS, University of Glasgow, Glasgow, UK
                [3 ]The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
                [4 ]Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
                [1 ]Department of Computer Science, University of Colorado Boulder, Boulder, CO, USA
                [2 ]BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, USA
                [1 ]Centre for Medical Parasitology, Department of Immunology and Microbiology (ISIM), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
                [1 ]Department of Microbiology and Immunology, Weill Cornell Medical College, Cornell University, New York, NY, USA
                Author notes

                No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Competing interests: No competing interests were disclosed.

                Author information
                https://orcid.org/0000-0002-1246-7404
                https://orcid.org/0000-0002-0248-5924
                https://orcid.org/0000-0002-9581-0377
                https://orcid.org/0000-0002-9274-3789
                Article
                10.12688/wellcomeopenres.15590.1
                7001760
                32055709
                93891e97-0530-4622-acb3-0ec056d27112
                Copyright: © 2019 Otto TD et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 26 November 2019
                Funding
                Funded by: Wellcome Trust
                Award ID: 104792;098051
                This work was supported by the Wellcome Trust [098051]. CN is funded by a Wellcome Investigator Award (104792/Z/14/Z).
                The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Articles

                plasmodium,var,evolution
                plasmodium, var, evolution

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