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      Selective sweeps and genetic lineages of Plasmodium falciparum multi-drug resistance ( pfmdr1) gene in Kenya

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          There are concerns that resistance to artemisinin-based combination therapy might emerge in Kenya and sub-Saharan Africa (SSA) in the same pattern as was with chloroquine and sulfadoxine–pyrimethamine. Single nucleotide polymorphisms (SNPs) in critical alleles of pfmdr1 gene have been associated with resistance to artemisinin and its partner drugs. Microsatellite analysis of loci flanking genes associated with anti-malarial drug resistance has been used in defining the geographic origins, dissemination of resistant parasites and identifying regions in the genome that have been under selection.


          This study set out to investigate evidence of selective sweep and genetic lineages in pfmdr1 genotypes associated with the use of artemether–lumefantrine (AL), as the first-line treatment in Kenya. Parasites (n = 252) from different regions in Kenya were assayed for SNPs at codons 86, 184 and 1246 and typed for 7 neutral microsatellites and 13 microsatellites loci flanking (± 99 kb) pfmdr1 in Plasmodium falciparum infections.


          The data showed differential site and region specific prevalence of SNPs associated with drug resistance in the pfmdr1 gene. The prevalence of pfmdr1 N86, 184F, and D1246 in western Kenya (Kisumu, Kericho and Kisii) compared to the coast of Kenya (Malindi) was 92.9% vs. 66.7%, 53.5% vs. to 24.2% and 96% vs. to 87.9%, respectively. The N FD haplotype which is consistent with AL selection was at 51% in western Kenya compared to 25% in coastal Kenya.


          Selection pressures were observed to be different in different regions of Kenya, especially the western region compared to the coastal region. The data showed independent genetic lineages for all the pfmdr1 alleles. The evidence of soft sweeps in pfmdr1 observed varied in direction from one region to another. This is challenging for malaria control programs in SSA which clearly indicate effective malaria control policies should be based on the region and not at a country wide level.

          Electronic supplementary material

          The online version of this article (10.1186/s12936-018-2534-8) contains supplementary material, which is available to authorized users.

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          Most cited references 66

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          Emergence of artemisinin-resistant malaria on the western border of Thailand: a longitudinal study

          Summary Background Artemisinin-resistant falciparum malaria has arisen in western Cambodia. A concerted international effort is underway to contain artemisinin-resistant Plasmodium falciparum, but containment strategies are dependent on whether resistance has emerged elsewhere. We aimed to establish whether artemisinin resistance has spread or emerged on the Thailand–Myanmar (Burma) border. Methods In malaria clinics located along the northwestern border of Thailand, we measured six hourly parasite counts in patients with uncomplicated hyperparasitaemic falciparum malaria (≥4% infected red blood cells) who had been given various oral artesunate-containing regimens since 2001. Parasite clearance half-lives were estimated and parasites were genotyped for 93 single nucleotide polymorphisms. Findings 3202 patients were studied between 2001 and 2010. Parasite clearance half-lives lengthened from a geometric mean of 2·6 h (95% CI 2·5–2·7) in 2001, to 3·7 h (3·6–3·8) in 2010, compared with a mean of 5·5 h (5·2–5·9) in 119 patients in western Cambodia measured between 2007 and 2010. The proportion of slow-clearing infections (half-life ≥6·2 h) increased from 0·6% in 2001, to 20% in 2010, compared with 42% in western Cambodia between 2007 and 2010. Of 1583 infections genotyped, 148 multilocus parasite genotypes were identified, each of which infected between two and 13 patients. The proportion of variation in parasite clearance attributable to parasite genetics increased from 30% between 2001 and 2004, to 66% between 2007 and 2010. Interpretation Genetically determined artemisinin resistance in P falciparum emerged along the Thailand–Myanmar border at least 8 years ago and has since increased substantially. At this rate of increase, resistance will reach rates reported in western Cambodia in 2–6 years. Funding The Wellcome Trust and National Institutes of Health.
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            Soft sweeps: molecular population genetics of adaptation from standing genetic variation.

            A population can adapt to a rapid environmental change or habitat expansion in two ways. It may adapt either through new beneficial mutations that subsequently sweep through the population or by using alleles from the standing genetic variation. We use diffusion theory to calculate the probabilities for selective adaptations and find a large increase in the fixation probability for weak substitutions, if alleles originate from the standing genetic variation. We then determine the parameter regions where each scenario-standing variation vs. new mutations-is more likely. Adaptations from the standing genetic variation are favored if either the selective advantage is weak or the selection coefficient and the mutation rate are both high. Finally, we analyze the probability of "soft sweeps," where multiple copies of the selected allele contribute to a substitution, and discuss the consequences for the footprint of selection on linked neutral variation. We find that soft sweeps with weaker selective footprints are likely under both scenarios if the mutation rate and/or the selection coefficient is high.
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              Microsatellite markers reveal a spectrum of population structures in the malaria parasite Plasmodium falciparum.

              Multilocus genotyping of microbial pathogens has revealed a range of population structures, with some bacteria showing extensive recombination and others showing almost complete clonality. The population structure of the protozoan parasite Plasmodium falciparum has been harder to evaluate, since most studies have used a limited number of antigen-encoding loci that are known to be under strong selection. We describe length variation at 12 microsatellite loci in 465 infections collected from 9 locations worldwide. These data reveal dramatic differences in parasite population structure in different locations. Strong linkage disequilibrium (LD) was observed in six of nine populations. Significant LD occurred in all locations with prevalence <1% and in only two of five of the populations from regions with higher transmission intensities. Where present, LD results largely from the presence of identical multilocus genotypes within populations, suggesting high levels of self-fertilization in populations with low levels of transmission. We also observed dramatic variation in diversity and geographical differentiation in different regions. Mean heterozygosities in South American countries (0.3-0.4) were less than half those observed in African locations (0. 76-0.8), with intermediate heterozygosities in the Southeast Asia/Pacific samples (0.51-0.65). Furthermore, variation was distributed among locations in South America (F:(ST) = 0.364) and within locations in Africa (F:(ST) = 0.007). The intraspecific patterns of diversity and genetic differentiation observed in P. falciparum are strikingly similar to those seen in interspecific comparisons of plants and animals with differing levels of outcrossing, suggesting that similar processes may be involved. The differences observed may also reflect the recent colonization of non-African populations from an African source, and the relative influences of epidemiology and population history are difficult to disentangle. These data reveal a range of population structures within a single pathogen species and suggest intimate links between patterns of epidemiology and genetic structure in this organism.

                Author and article information

                +1-301-273-5658 ,
                Malar J
                Malar. J
                Malaria Journal
                BioMed Central (London )
                30 October 2018
                30 October 2018
                : 17
                [1 ]ISNI 0000 0001 0155 5938, GRID grid.33058.3d, Global Emerging Infections Surveillance Program, United States Army Medical Research Directorate-Africa, , Kenya Medical Research Institute, ; P.O. Box 54, 40100 Kisumu, Kenya
                [2 ]ISNI 0000 0000 9146 7108, GRID grid.411943.a, Department of Biochemistry, School of Biomedical Sciences, , Jomo Kenyatta University of Agriculture and Technology, ; P.O. Box 62000, 00200 Nairobi, Kenya
                [3 ]ISNI 0000 0001 0560 6544, GRID grid.414467.4, Walter Reed National Military Medical Center, ; Bethesda, Maryland USA
                © The Author(s) 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

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