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      SNP Genotyping Identifies New Signatures of Selection in a Deep Sample of West African Plasmodium falciparum Malaria Parasites

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          Abstract

          We used a high-density single-nucleotide polymorphism array to genotype 75 Plasmodium falciparum isolates recently collected from Senegal and The Gambia to search for signals of selection in this malaria endemic region. We found little geographic or temporal stratification of the genetic diversity among the sampled parasites. Through application of the iHS and REHH haplotype-based tests for positive selection, we found evidence of recent selective sweeps at a known drug resistance locus, at several known antigenic loci, and at several genomic regions not previously identified as sites of recent selection. We discuss the value of deep population-specific genomic analyses for identifying selection signals within sampled endemic populations of parasites, which may correspond to local selection pressures such as distinctive therapeutic regimes or mosquito vectors.

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          Most cited references15

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          Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation.

          Although many algorithms exist for estimating haplotypes from genotype data, none of them take full account of both the decay of linkage disequilibrium (LD) with distance and the order and spacing of genotyped markers. Here, we describe an algorithm that does take these factors into account, using a flexible model for the decay of LD with distance that can handle both "blocklike" and "nonblocklike" patterns of LD. We compare the accuracy of this approach with a range of other available algorithms in three ways: for reconstruction of randomly paired, molecularly determined male X chromosome haplotypes; for reconstruction of haplotypes obtained from trios in an autosomal region; and for estimation of missing genotypes in 50 autosomal genes that have been completely resequenced in 24 African Americans and 23 individuals of European descent. For the autosomal data sets, our new approach clearly outperforms the best available methods, whereas its accuracy in inferring the X chromosome haplotypes is only slightly superior. For estimation of missing genotypes, our method performed slightly better when the two subsamples were combined than when they were analyzed separately, which illustrates its robustness to population stratification. Our method is implemented in the software package PHASE (v2.1.1), available from the Stephens Lab Web site.
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            A coalescent-based method for detecting and estimating recombination from gene sequences.

            Determining the amount of recombination in the genealogical history of a sample of genes is important to both evolutionary biology and medical population genetics. However, recurrent mutation can produce patterns of genetic diversity similar to those generated by recombination and can bias estimates of the population recombination rate. Hudson 2001 has suggested an approximate-likelihood method based on coalescent theory to estimate the population recombination rate, 4N(e)r, under an infinite-sites model of sequence evolution. Here we extend the method to the estimation of the recombination rate in genomes, such as those of many viruses and bacteria, where the rate of recurrent mutation is high. In addition, we develop a powerful permutation-based method for detecting recombination that is both more powerful than other permutation-based methods and robust to misspecification of the model of sequence evolution. We apply the method to sequence data from viruses, bacteria, and human mitochondrial DNA. The extremely high level of recombination detected in both HIV1 and HIV2 sequences demonstrates that recombination cannot be ignored in the analysis of viral population genetic data.
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              Genome-wide variation and identification of vaccine targets in the Plasmodium falciparum genome.

              One goal in sequencing the Plasmodium falciparum genome, the agent of the most lethal form of malaria, is to discover vaccine and drug targets. However, identifying those targets in a genome in which approximately 60% of genes have unknown functions is an enormous challenge. Because the majority of known malaria antigens and drug-resistant genes are highly polymorphic and under various selective pressures, genome-wide analysis for signatures of selection may lead to discovery of new vaccine and drug candidates. Here we surveyed 3,539 P. falciparum genes ( approximately 65% of the predicted genes) for polymorphisms and identified various highly polymorphic loci and genes, some of which encode new antigens that we confirmed using human immune sera. Our collections of genome-wide SNPs ( approximately 65% nonsynonymous) and polymorphic microsatellites and indels provide a high-resolution map (one marker per approximately 4 kb) for mapping parasite traits and studying parasite populations. In addition, we report new antigens, providing urgently needed vaccine candidates for disease control.
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                Author and article information

                Journal
                Mol Biol Evol
                Mol. Biol. Evol
                molbev
                molbiolevol
                Molecular Biology and Evolution
                Oxford University Press
                0737-4038
                1537-1719
                November 2012
                11 July 2012
                11 July 2012
                : 29
                : 11
                : 3249-3253
                Affiliations
                1Medical Research Council Unit, Fajara, Banjul, The Gambia
                2Broad Institute, Cambridge, Massachusetts
                3Harvard School of Public Health
                4Simmons College
                5Cheikh Anta Diop University, Dakar, Senegal
                6London School of Hygiene and Tropical Medicine, London, United Kingdom
                Author notes
                *Corresponding author: E-mail: sfs@ 123456broadinstitute.org .

                A ssociate editor: Matthew Hahn

                Article
                mss151
                10.1093/molbev/mss151
                3472499
                22688945
                cde404aa-7412-4a66-8b03-afb6680fb01d
                © The Author 2012. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Page count
                Pages: 5
                Categories
                Letters

                Molecular biology
                genome,west africa,natural selection,snp,plasmodium falciparum
                Molecular biology
                genome, west africa, natural selection, snp, plasmodium falciparum

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