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      Population Genomic Scan for Candidate Signatures of Balancing Selection to Guide Antigen Characterization in Malaria Parasites

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          Abstract

          Acquired immunity in vertebrates maintains polymorphisms in endemic pathogens, leading to identifiable signatures of balancing selection. To comprehensively survey for genes under such selection in the human malaria parasite Plasmodium falciparum, we generated paired-end short-read sequences of parasites in clinical isolates from an endemic Gambian population, which were mapped to the 3D7 strain reference genome to yield high-quality genome-wide coding sequence data for 65 isolates. A minority of genes did not map reliably, including the hypervariable var, rifin, and stevor families, but 5,056 genes (90.9% of all in the genome) had >70% sequence coverage with minimum read depth of 5 for at least 50 isolates, of which 2,853 genes contained 3 or more single nucleotide polymorphisms (SNPs) for analysis of polymorphic site frequency spectra. Against an overall background of negatively skewed frequencies, as expected from historical population expansion combined with purifying selection, the outlying minority of genes with signatures indicating exceptionally intermediate frequencies were identified. Comparing genes with different stage-specificity, such signatures were most common in those with peak expression at the merozoite stage that invades erythrocytes. Members of clag, PfMC-2TM, surfin, and msp3-like gene families were highly represented, the strongest signature being in the msp3-like gene PF10_0355. Analysis of msp3-like transcripts in 45 clinical and 11 laboratory adapted isolates grown to merozoite-containing schizont stages revealed surprisingly low expression of PF10_0355. In diverse clonal parasite lines the protein product was expressed in a minority of mature schizonts (<1% in most lines and ∼10% in clone HB3), and eight sub-clones of HB3 cultured separately had an intermediate spectrum of positive frequencies (0.9 to 7.5%), indicating phase variable expression of this polymorphic antigen. This and other identified targets of balancing selection are now prioritized for functional study.

          Author Summary

          The memory component of acquired immune responses selects for distinctive patterns of polymorphism in genes encoding important target antigens of pathogens. These are detectable by surveying for evidence of balancing selection, as previously illustrated in analyses of genes encoding malaria parasite antigens that are candidate targets of naturally acquired immunity. For a comprehensive screen to discover targets of immunity in the major human malaria parasite Plasmodium falciparum, an endemic population in West Africa was sampled and genome sequence data obtained from 65 clinical isolates, allowing analysis of polymorphism in almost all protein-coding genes. Antigen genes previously studied by capillary re-sequencing in independent population samples had highly concordant indices in the genome-wide analysis here, and this has identified other genes with stronger evidence of balancing selection, now prioritized for functional study and potential vaccine candidacy. The statistical signatures consistent with such selection were particularly common in genes with peak expression at the stage that invades erythrocytes, and members of several gene families were represented. The strongest signature was in the msp3-like gene PF10_0355, so we studied the transcript and protein product in parasites, revealing an unexpected pattern of phase variable expression. Variation in expression of polymorphic antigens under balancing selection may be more common than previously thought, requiring further study to assess vaccine candidacy.

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          Most cited references64

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          DnaSP, DNA polymorphism analyses by the coalescent and other methods.

          DnaSP is a software package for the analysis of DNA polymorphism data. Present version introduces several new modules and features which, among other options allow: (1) handling big data sets (approximately 5 Mb per sequence); (2) conducting a large number of coalescent-based tests by Monte Carlo computer simulations; (3) extensive analyses of the genetic differentiation and gene flow among populations; (4) analysing the evolutionary pattern of preferred and unpreferred codons; (5) generating graphical outputs for an easy visualization of results. The software package, including complete documentation and examples, is freely available to academic users from: http://www.ub.es/dnasp
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            The global distribution of clinical episodes of Plasmodium falciparum malaria.

            Interest in mapping the global distribution of malaria is motivated by a need to define populations at risk for appropriate resource allocation and to provide a robust framework for evaluating its global economic impact. Comparison of older and more recent malaria maps shows how the disease has been geographically restricted, but it remains entrenched in poor areas of the world with climates suitable for transmission. Here we provide an empirical approach to estimating the number of clinical events caused by Plasmodium falciparum worldwide, by using a combination of epidemiological, geographical and demographic data. We estimate that there were 515 (range 300-660) million episodes of clinical P. falciparum malaria in 2002. These global estimates are up to 50% higher than those reported by the World Health Organization (WHO) and 200% higher for areas outside Africa, reflecting the WHO's reliance upon passive national reporting for these countries. Without an informed understanding of the cartography of malaria risk, the global extent of clinical disease caused by P. falciparum will continue to be underestimated.
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              Discovery of gene function by expression profiling of the malaria parasite life cycle.

              The completion of the genome sequence for Plasmodium falciparum, the species responsible for most malaria human deaths, has the potential to reveal hundreds of new drug targets and proteins involved in pathogenesis. However, only approximately 35% of the genes code for proteins with an identifiable function. The absence of routine genetic tools for studying Plasmodium parasites suggests that this number is unlikely to change quickly if conventional serial methods are used to characterize encoded proteins. Here, we use a high-density oligonucleotide array to generate expression profiles of human and mosquito stages of the malaria parasite's life cycle. Genes with highly correlated levels and temporal patterns of expression were often involved in similar functions or cellular processes.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, USA )
                1553-7390
                1553-7404
                November 2012
                November 2012
                1 November 2012
                : 8
                : 11
                : e1002992
                Affiliations
                [1 ]Medical Research Council Unit, Fajara, Banjul, The Gambia
                [2 ]Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom
                [3 ]Wellcome Trust Sanger Institute, Hinxton, United Kingdom
                [4 ]Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
                [5 ]Division of Parasitology, MRC National Institute for Medical Research, London, United Kingdom
                [6 ]Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
                Arizona State University, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: AA-N KKAT NG-E DPK DJC. Performed the experiments: AA-N KKAT MM NG-E LBS MED OJ DJC. Analyzed the data: AA-N KKAT MM NG-E MED IHC DJC. Contributed reagents/materials/analysis tools: AA-N KKAT MM AAH EK CIN MJ SC BM DPK DJC. Wrote the paper: AA-N KKAT DJC.

                Article
                PGENETICS-D-12-00334
                10.1371/journal.pgen.1002992
                3486833
                23133397
                a4e56c18-afc1-406f-b513-f55d5959f8fb
                Copyright @ 2012

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 7 February 2012
                : 13 August 2012
                Page count
                Pages: 14
                Funding
                This research was supported by the Wellcome Trust ( www.wellcome.ac.uk: grants 074695/Z/04/B, 098051, and 090770/Z/09/Z), the UK Medical Research Council ( www.mrc.ac.uk: core funding for the MRC Gambia Unit, grant U117532067, and grant G0600718 for the Centre for Genomics and Global Health), and the European Union Network of Excellence EviMalaR ( www.evimalar.org: grant Health-2009-2.3.2-1-242095). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Evolutionary Biology
                Population Genetics
                Genetic Polymorphism
                Natural Selection
                Genomics
                Genome Sequencing
                Immunology
                Microbiology
                Immunity
                Adaptive Immunity
                Parasitology
                Parasite Evolution
                Host-Pathogen Interaction
                Medicine
                Infectious Diseases
                Parasitic Diseases
                Malaria
                Plasmodium Falciparum
                Protozoan Infections

                Genetics
                Genetics

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