The online version of this article (doi:10.1186/1475-2875-11-412) contains supplementary material, which is available to authorized users.
The authors declare that they have no competing interests.
SC conducted the molecular genetic studies, performed the genetic diversity experiments, analysed the data and wrote the first draft of the manuscript. KS performed the statistical analysis and contributed to the write up of the final draft. LV provided the samples and contributed to the editing of the manuscript. AE designed the project, supervised and directed the research and contributed to the writing and editing of the manuscript. All authors read and approved the final manuscript.
Regardless of the growing interest in detecting population structures in malarial parasites, there have been limited discussions on how to use this concept in control programmes. In such context, the effects of the parasite population structures will depend on interventions’ spatial or temporal scales. This investigation explores the problem of identifying genetic markers, in this case microsatellites, to unveil Plasmodium genetic structures that could affect decisions in the context of elimination. The study was performed in a low-transmission area, which offers a good proxy to better understand problems associated with surveillance at the final stages of malaria elimination.
Plasmodium vivax samples collected in Tumeremo, Venezuela, between March 2003 and November 2004 were analysed. Since Plasmodium falciparum also circulates in many low endemic areas, P. falciparum samples from the same locality and time period were included for comparison. Plasmodium vivax samples were assayed for an original set of 25 microsatellites and P. falciparum samples were assayed for 12 microsatellites.
Not all microsatellite loci assayed offered reliable local data. A complex temporal-cluster dynamics is found in both P. vivax and P. falciparum. Such dynamics affect the numbers and the type of microsatellites required for identifying individual parasites or parasite clusters when performing cross-sectional studies. The minimum number of microsatellites required to differentiate circulating P. vivax clusters differs from the minimum number of hyper-variable microsatellites required to distinguish individuals within these clusters. Regardless the extended number of microsatellites used in P. vivax, it was not possible to separate all individual infections.
Molecular surveillance has great potential; however, it requires preliminary local studies in order to properly interpret the emerging patterns in the context of elimination. Clonal expansions and clusters turnovers need to be taken into account when using molecular markers. Those affect the number and type of microsatellite markers, as well as, the expected genetic patterns in the context of operational investigations. By considering the local dynamics, elimination programmes could cost-effectively use molecular markers. However, population level studies need to consider the local limitations of a given set of loci in terms of providing epidemiologically relevant information.
Additional file 1: Number of alleles per loci and expected heterozygosity per year in P. vivax (A and B) and in P. falciparum (C and D) using all samples from Tumeremo.(PDF 222 KB)12936_2012_2579_MOESM1_ESM.pdf
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Imwong M, Nair S, Pukrittayakamee S, Sudimack D, Williams JT, Mayxay M, Newton PN, Kim JR, Nandy A, Osorio L, Carlton JM, White NJ, Day NP, Anderson TJ: Contrasting genetic structure in Plasmodium vivax populations from Asia and South America. Int J Parasitol. 2007, 37: 1013-1022. 10.1016/j.ijpara.2007.02.010. CrossRefPubMed
Van den Eede P, Van der Auwera G, Delgado C, Huyse T, Soto-Calle VE, Gamboa D, Grande T, Rodriguez H, Llanos A, Anné J, Erhart A, D'Alessandro U: Multilocus genotyping reveals high heterogeneity and strong local population structure of the Plasmodium vivax population in the Peruvian Amazon. Malar J. 2010, 9: 151-10.1186/1475-2875-9-151. PubMedCentralCrossRefPubMed
Pumpaibool T, Arnathau C, Durand P, Kanchanakhan N, Siripoon N, Suegorn A, Sitthi-Amorn C, Renaud F, Harnyuttanakorn P: Genetic diversity and population structure of Plasmodium falciparum in Thailand, a low transmission country. Malar J. 2009, 8: 155-10.1186/1475-2875-8-155. PubMedCentralCrossRefPubMed
Griffing SM, Mixson-Hayden T, Sridaran S, Alam MT, McCollum AM, Cabezas C, Marquiño Quezada W, Barnwell JW, De Oliveira AM, Lucas C, Arrospide N, Escalante AA, Bacon DJ, Udhayakumar V: South American Plasmodium falciparum after the malaria eradication era: clonal population expansion and survival of the fittest hybrids. PLoS One. 2011, 6: e23486-10.1371/journal.pone.0023486. PubMedCentralCrossRefPubMed
Arnott A, Barry AE, Reeder JC: Understanding the population genetics of Plasmodium vivax is essential for malaria control and elimination. Malar J. 2012, 10: 11-
Wright S: Isolation by distance. Genetics. 1943, 2: 114-38.
Gauthier C, Tibayrenc M: Population structure of malaria parasites: the driving epidemiological forces. Acta Trop. 2005, 3: 241-250. CrossRef
Volkman SK, Sabeti PC, DeCaprio D, Neafsey DE, Schaffner SF, Milner DA, Daily JP, Sarr O, Ndiaye D, Ndir O, Mboup S, Duraisingh MT, Lukens A, Derr A, Stange-Thomann N, Waggoner S, Onofrio R, Ziaugra L, Mauceli E, Gnerre S, Jaffe DB, Zainoun J, Wiegand RC, Birren BW, Hartl DL, Galagan JE, Lander ES, Wirth DF: A genome-wide map of diversity in Plasmodium falciparum. Nat Genet. 2007, 39: 113-119. 10.1038/ng1930. CrossRefPubMed
Neafsey DE, Schaffner SF, Volkman SK, Park D, Montgomery P, Milner DA, Lukens A, Rosen D, Daniels R, Houde N, Cortese JF, Tyndall E, Gates C, Stange-Thomann N, Sarr O, Ndiaye D, Ndir O, Mboup S, Ferreira MU, Moraes Sdo L, Dash AP, Chitnis CE, Wiegand RC, Hartl DL, Birren BW, Lander ES, Sabeti PC, Wirth DF: Genome-wide SNP genotyping highlights the role of natural selection in Plasmodium falciparum population divergence. Genome Biol. 2008, 9: R171-10.1186/gb-2008-9-12-r171. PubMedCentralCrossRefPubMed
Cheeseman IH, Miller BA, Nair S, Nkhoma S, Tan A, Tan JC, Al Saai S, Phyo AP, Moo CL, Lwin KM, McGready R, Ashley E, Imwong M, Stepniewska K, Yi P, Dondorp AM, Mayxay M, Newton PN, White NJ, Nosten F, Ferdig MT, Anderson TJ: A major genome region underlying artemisinin resistance in malaria. Science. 2012, 336: 79-82. 10.1126/science.1215966. PubMedCentralCrossRefPubMed
Orjuela-Sánchez P, Karunaweera ND, da Silva-Nunes M, da Silva NS, Scopel KK, Gonçalves RM, Amaratunga C, Sá JM, Socheat D, Fairhust RM, Gunawardena S, Thavakodirasah T, Galapaththy GL, Abeysinghe R, Kawamoto F, Wirth DF, Ferreira MU: Single-nucleotide polymorphism, linkage disequilibrium and geographic structure in the malaria parasite Plasmodium vivax: prospects for genome-wide association studies. BMC Genet. 2010, 11: 65- PubMedCentralCrossRefPubMed
McCollum AM, Basco LK, Tahar R, Udhayakumar V, Escalante AA: Hitchhiking and selective sweeps of Plasmodium falciparum sulfadoxine and pyrimethamine resistance alleles in a population from central Africa. Antimicrob Agents Chemother. 2008, 52: 4089-4097. 10.1128/AAC.00623-08. PubMedCentralCrossRefPubMed
Nyachieo A, VAN Overmeir C, Laurent T, Dujardin JC, D'Alessandro U: Plasmodium falciparum genotyping by microsatellites as a method to distinguish between recrudescent and new infections. AmJTrop Med Hyg. 2005, 73: 210-3.
Greenhouse B, Myrick A, Dokomajilar C, Woo JM, Carlson EJ, Rosenthal PJ, Dorsey G: Validation of microsatellite markers for use in genotyping polyclonal Plasmodium falciparum infections. AmJTrop Med Hyg. 2006, 75: 836-842.
Orjuela-Sánchez P, da Silva NS, da Silva-Nunes M, Ferreira MU: Recurrent parasitemias and population dynamics of Plasmodium vivax polymorphisms in rural Amazonia. AmJTrop Med Hyg. 2009, 81: 961-968. 10.4269/ajtmh.2009.09-0337. CrossRef
McCollum AM, Mueller K, Villegas L, Udhayakumar V, Escalante AA: Common origin and fixation of Plasmodium falciparum dhfr and dhps mutations associated with sulfadoxine-pyrimethamine resistance in a low-transmission area in South America. Antimicrob Agents Chemother. 2007, 51: 2085-2091. 10.1128/AAC.01228-06. PubMedCentralCrossRefPubMed
Park SDE: Trypanotolerance in West African Cattle and the Population Genetic Effects of Selection. PhD thesis. 2001, University of Dublin, Microsatellite tool kit version 3.1.1 available from: http://www.animalgenomics.ucd.ie/sdepark/ms-toolkit/
Pritchard JK, Stephens M, Donnelly P: Inference of population structure using multilocus genotype data. Genetics. 2000, 155: 945-959. Structure 2.3.3 available from: http://pritch.bsd.uchicago.edu/structure.html PubMedCentralPubMed
Dent Earl A, vonHoldt , Bridgett M: STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour. 2012, 4: 359-361. 10.1007/s12686-011-9548-7. Structure harvester available from: http://taylor0.biology.ucla.edu/struct_harvest/ CrossRef
Jakobsson M, Rosenberg NA: CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics. 2007, 23: 1801-1806. 10.1093/bioinformatics/btm233. CLUMPP 1.1.2 available from: http://www.stanford.edu/group/rosenberglab/clumpp.html CrossRefPubMed
Rosenberg NA: Distruct: a program for the graphical display of population structure. Molecular Ecology Notes. 2004, 4: 137-138. Distruct 1.1 available at: http://www.stanford.edu/group/rosenberglab/distruct.html CrossRef
Goudet J: FSTAT Version 1.2: a computer program to calculate F-statistics. J. Heredity. 1995, 86: 485-486. FSTAT 220.127.116.11 available from: http://www2.unil.ch/popgen/softwares/fstat.htm
Laval EG, Schneider S: Arlequin (version 3.0): an integrated software package for population genetics data analysis. Evol Bioinform. 2005, 1: 47-50.
Haubold B, Hudson RR: LIAN 3.0: detecting linkage disequilibrium in multilocus data. Bioinformatics. 2000, 16: 847-848. 10.1093/bioinformatics/16.9.847. LIAN 3.5 available from: http://adenine.biz.fh-weihenstephan.de/cgi-bin/lian/lian.cgi.pl. CrossRefPubMed
Maruyama T: Stochastic integrals and their application to population genetics. Molecular Evolution, Protein Polymorphism and the Neutral Theory. Edited by: Kimura M. 1982, Tokyo: Japan Scientific Societies Press, 151-166.
Barton DE, David F: Multiple runs. Biometrika. 1957, 44: 168-170. CrossRef
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