Leishmania donovani populations in Eastern Sudan: temporal structuring and a link between human and canine transmission
© Baleela et al.; licensee BioMed Central Ltd. 2014
Received: 22 May 2014
Accepted: 21 October 2014
Published: 20 November 2014
Visceral leishmaniasis (VL), caused by the members of the Leishmania donovani complex, has been responsible for devastating VL epidemics in the Sudan. Multilocus microsatellite and sequence typing studies can provide valuable insights into the molecular epidemiology of leishmaniasis, when applied at local scales. Here we present population genetic data for a large panel of strains and clones collected in endemic Sudan between 1993 and 2001.
Genetic diversity was evaluated at fourteen microsatellite markers and eleven nuclear sequence loci across 124 strains and clones.
Microsatellite data defined six genetic subpopulations with which the nuclear sequence data were broadly congruent. Pairwise estimates of FST (microsatellite) and KST (sequence) indicated small but significant shifts among the allelic repertoires of circulating strains year on year. Furthermore, we noted the co-occurrence of human and canine L. donovani strains in three of the six clusters defined. Finally, we identified widespread deficit in heterozygosity in all four years tested but strong deviation from inter-locus linkage equilibrium in two years.
Significant genetic diversity is present among L. donovani in Sudan, and minor population structuring between years is characteristic of entrenched, endemic disease transmission. Seasonality in vector abundance and transmission may, to an extent, explain the shallow temporal clines in allelic frequency that we observed. Genetically similar canine and human strains highlight the role of dogs as important local reservoirs of visceral leishmaniasis.
Visceral leishmaniasis (VL) is caused by parasites of the Leishmania donovani complex. The L. donovani complex is distributed throughout Asia, North Africa, Latin America and Southern Europe, affecting mostly vulnerable and neglected populations. Infection is spread via the bite of haematophagous phlebotomine sand fly species, while the role of non-human reservoir hosts varies from region to region ,. The most important endemic foci in terms of prevalence, morbidity and mortality are located in India, Sudan and Brazil. Leishmaniasis is likely to have been endemic to Sudan since antiquity (e.g. Zink et al. ). Epidemic outbreaks are periodically reported (e.g. Dereure et al. ) with high mortality (e.g. Seaman et al. ). Recent surveys of disease burden still show consistently high infection and mortality rates in Eastern Sudan, with up to 16% of all deaths attributed to VL regionally . Infection rates in Sudan are thought to be seasonal, linked to moisture and sand fly abundance .
Molecular studies, such as the analysis of the ribosomal DNA internal transcribed spacer (ITS) ,, multilocus sequence typing (MLST) , and multilocus microsatellite typing (MLMT) , have shown that VL in Sudan, and the contiguous focus in Ethiopia, is caused by one to two genetic groups of L. donovani, distinct from L. infantum and other L. donovani genetic groups. Nevertheless, unlike on the Indian subcontinent, where an emergent epidemic clone seems responsible for most cases, there is significant genetic diversity within Sudanese L. donovani-. More recently, MLMT typing of Sudanese L. donovani has focussed on the role genetic recombination might have in influencing local patterns of population genetic diversity . Genetic recombination in the field and laboratory is increasingly reported within and between Leishmania species, with important consequences in terms of vector compatibility and the spread of drug resistance -. Several studies based on MLMT have used widespread homozygosity within populations as a proxy for inbreeding in Leishmania, in the face of widespread linkage disequilibrium and irrespective of whether parasites undergo `classic’ (Mendelian) gametic sex ,,,
In the current study we evaluated the genetic diversity of L. donovani in Sudan using MLST and MLMT markers in parallel, with special focus on longitudinal patterns of parasite genetic diversity in the hyperendemic village Barbar El Fugara of the Atbara River Region and around it, 1993-2001. We successfully incriminated dogs as important reservoirs of L. donovani locally, by comparisons to local strains isolated from patients. Furthermore, we were able to show significant, but minor, subdivision between L. donovani isolated from different years based on MLMT and MLST, which we discuss in the light of VL epidemiology. We found evidence for excess homozygosity across all populations and associated linkage disequilibrium, but based on the available data we are unable to attribute this pattern of diversity to either genetic exchange (inbreeding) or gene conversion.
Sampling in Barbar El Fugara was approved by both the Federal and Gedarif State Ministries of Health and by the Faculty of Medicine, Khartoum University. Informed consent was obtained from the district authorities and from the village committee as well as from all the adults who participated in the study. For younger children the consent was obtained from their parents. Other samples included in this analysis were archival or reference strains.
Strains, reference strains and clones
A panel of 124 L. donovani strains and clones was assembled (Additional file 1: Table S1). Twenty-three strains were biologically cloned (cultures founded from a single organism - one to four clones per strain) on solid media in 3.5 cm Petri dishes incubated at 24°C, using a protocol adapted from Yeo et al. . All but one sample selected for cloning originated from the Atbara River region, and our aim was to facilitate the identification of local hybrids among contemporary circulating strains. As such, cloning was undertaken to eliminate the possibility that heterozygous microsatellite loci or SNPs were the result of mixed infections and clones are indicated in Additional file 1: Table S1. Most strains were collected in the Atbara River region of Eastern Sudan in and around the village of Barbar El Fugara. Sudanese strains were collected from human and canine hosts over an eight-year period (1993-2001). However, further Sudanese samples prior to and after this period were also included for reference. In addition, a geographically representative selection of strains collected from Europe, East Africa and the Middle East was included for comparison. A subset of those strains sampled from Barbar El Fugara has been analysed previously (Additional file 1: Table S1) via MLMT but with different markers to those employed here .
Multilocus microsatellite typing and analysis
Population-level analyses of microsatellite data were undertaken exclusively on Sudanese L. donovani based on populations defined a priori by year 1993, 1997, 1998, and 2001 (Additional file 1: Table S1). First we undertook to estimate the level of gene flow between years in Arlequin v3.5 using F ST (equivalent to Weir and Cockerman’s 1984 estimator (θ w ) ) and tested this value for significance using a non-parametric random permutation procedure . Secondly, we linearised these values as in Slatkin, 1995, to facilitate direct comparison between values for population pairs . Finally, we calculated population-specific statistics by year: sample size corrected allelic richness (Ar) in FSTAT 220.127.116.11  and F IS (an index of the distribution of heterozygosity within and between individuals), per locus per population, also in FSTAT 18.104.22.168. Tests for population-level deviation from Hardy-Weinberg allele frequencies were calculated in Arlequin v3.5 and associated significance levels for p values derived after sequential Bonferroni correction to minimise the likelihood of Type 1 errors. Linkage disequilibrium was defined via the Index of Association and calculated exclusively from biological clones in two populations.
Multilocus sequence typing and analysis
Direct DNA sequences were generated from the PCR amplification products of eleven MLST targets. Targets included four housekeeping genes previously identified as suitable markers: asat-Ch24, asat-Ch35, fh-Ch24, gp63-mspC) ,, and seven new targets developed in the current study. The new targets include a housekeeping gene cytb5R-Ch22II (LinJ.22.0590), 4 hypothetical protein-coding genes (LinJ.01.0010, LinJ.28.0190, LinJ.34.0550 and LinJ.36.1190) and 2 pseudogenes (LinJ.11.0280 and LinJ.36.0350). PCR reactions to amplify these targets were undertaken in a final volume of 25 μl, comprising: 2.5 μl 10× buffer, 0.05 mM MgCl2, 2.5 μl 0.8 mM dNTPs, 12.5 pmol of each primer, 1.25 U Taq polymerase and 25 ng genomic DNA. Amplification conditions were: 30 cycles at 95°C for 1 min, 54-62°C (dependent on primer (Additional file 2: Table S2)) for 1.5 min and 72°C for 1.5 min, with a final extension at 72°C for 10 min. Amplification of targets LinJ.01.0010, LinJ.11.0280, LinJ.34.0550, LinJ.36.0350 and LinJ.36.1190 required 10% DMSO. Direct sequencing reactions were performed with internal primers, BigDye™ terminator cycle sequencing V3.1 kits (ABI PRISM® Applied Biosystems) and analysed in an ABI PRISM™ 3730 DNA sequencer (Applied Biosystems), according to the manufacturer’s instructions. Sequences were inspected and edited visually in Chromas Lite (Copyright © 2005 Technelysium Pty Ltd) and assembled using ClustalW  in BioEdit v 5.0.6 . Haplotype phases were reconstructed using the software PHASE v. 2.1.1 . MLST data were analyzed as two separately concatenated target haplotype datasets: coding and hypothetical (10995 bp in total) and non-coding pseudogenes (2173 bp in total). Genome sequences of the reference strains L. major MHOM/IL/80/Friedlin and L. infantum MCAN/ES/98/LLM-877 were obtained from www.genedb.org. Haplotypes for both coding and non-coding sequence datasets were scanned for mosaic breakpoints in RDP . Sequences for each gene were submitted to Genbank (Accession numbers: FR775540.1-FR775754.1, FR796277.1-FR846362.2, HE648217.1-HE648270.1).
Population genetic differentiation between strains from years 1997, 1998, 1999 and 2001 was calculated from sequence haplotypes in DNAsp  using KST. KST compares the expected number of nucleotide differences between a pair of sequences within one population with a pair taken across all populations . Statistical significance for observed differentiation was inferred via 10,000 random permutations.
Year on year population genetic statistics for Sudanese L. donovani populations
2.643 ± 0.289
0.201 ± 0.150
3.071 ± 0.355
0.596 ± 0.073
3.144 ± 0.339
0.479 ± 0.107
2.95 < 0.001
2.430 ± 0.291
0.275 ± 0.172
2.03 < 0.001
Pairwise F ST between years suggests incremental shifts in allelic frequencies in Sudanese populations L. donovani
Pairwise F ST linearised with Slatkin correction
In parallel to our analysis of microsatellite fragment size data, we also undertook analysis of DNA sequence data derived from a representative group of 34 strains and clones (including genomic reference strains). Both coding and non-coding regions were scanned for evidence of mosaic breakpoints that might be associated with homologous recombination, which would also potentially disrupt phylogenetic signal in subsequent trees, but no evidence for such events was uncovered. The ML topology derived from coding loci revealed substantial genetic diversity, but little bootstrap support, as one might expect between samples from the same species across a restricted area (Sudan/East Africa, Figure 2). The only clearly divergent clade contained samples classified as population 6, 8 and 1 based on microsatellite typing, as well as a single strain from Ethiopia. Correspondence between sample year and tree topology was limited (Figure 2). As a second approach we examined only those strains for which we had microsatellite data. To improve resolution, we concatenated both coding and non-coding genes and constructed an ML tree from unphased sequence haplotypes (Figure 4). In this case there was a closer match between microsatellite and sequence data. Strains from MLMT-defined populations 6 and 1 were outliers with respect to other Sudanese strains. A notable exception was strain 762 L, which grouped differently between the two sets of markers.
Genetic differentiation ( K ST ) between years based on concatenated coding sequence data
Visceral leishmaniasis in Sudan is a major and on-going public health problem . Molecular epidemiological studies like ours can have a significant role in guiding and informing public health professionals. Our first key observation in this context is that dogs and humans in the region share similar strains. PCR-based and parasitological approaches have already identified dogs as important carriers of L. donovani in Sudan ,, although circumstantial evidence also points to other truly sylvatic hosts (e.g. ). Our high-resolution genetic data clearly demonstrate sharing of parasites between dogs and humans. Previous work on a limited number of the same strains from the same area suggested the possible presence of distinct human and canine transmission cycles , however, all three clusters containing canine hosts also contained humans (Figure 1).
The stability of genetic diversity in parasite populations in space is frequently used to infer patterns of regional and global parasite spread (e.g. ). Temporal variation in parasite populations can also be highly informative, especially pre- and post- large scale treatment interventions (e.g. ,. The majority of samples we analysed came from an outbreak first reported in 1996 . Given that high rates of infection still occur in the same region today, it is not clear whether `outbreak’ successfully described the diseases’ local status . Both our sequence and microsatellite data from different years suggest incremental changes in allelic composition (although, like in an earlier study, no subdivision is detected between years 1997 and 1998 ). Mutational instability of highly variable microsatellite markers could play a role. However, it is not clear over what timescale such changes might be expected to happen. In Trypanosoma cruzi discrete typing unit I, a related trypanosomatid, two samples taken 20 years apart from the same geographic focus can be identical at 48 microsatellite loci . There are multiple examples in the current dataset where temporally separated strains are closely related to each other. Population 4, for example contains samples from 1967 and 2001. It is, thus, more likely that population processes, such as immigration, founder events and bottlenecks, define the differences between years. However, the shallow clines in allelic composition we observe in the data are not reminiscent of intense serial reductions in parasite population size. Inter-population variation is perhaps more consistent with seasonal changes in infection intensity.
As well as the defining patterns of parasite genetic diversification in the Atbara River region, a secondary goal was to evaluate evidence for genetic exchange among Sudanese L. donovani strains. Like previous authors, we were able to detect reduced heterozygosity in the populations studied . However, unlike other authors, we are reluctant to interpret our data as evidence for genetic exchange ,,. Analysis of cloned L. donovani from two populations revealed strong evidence for predominant clonality, despite consistently high values for F IS . Furthermore, sequence data showed no evidence for the mosaics that one might expect to accompany recombination. It is important to state that, although our data do not confirm the presence of genetic exchange, we cannot rule out the occurrence of some recombination/inbreeding, as suggested by Rougeron et al. . We note that extensive genomic-level hybridisation was recently detected among a population of Leishmania infantum in Turkey , while microsatellite data based on the same strains detected no such phenomenon .
Rapid, low cost, high-resolution genotyping strategies have an important role in elucidating the molecular epidemiology of visceral leishmaniasis, especially where the burden of the disease is felt the most. Population genomic studies of Leishmania have now demonstrated the power that such approaches have to reveal the extent and mechanism of genetic exchange in natural populations . It has become apparent that genetic exchange is not a rare event but a feature of natural populations of several Leishmania species ,,; experimental crosses in sand flies suggest Mendelian segregation . Although proof of genetic exchange was not evident among the Sudanese populations analysed here, excess homozygosity occurred in conjunction with LD, and this was interpreted by others as inbreeding . Furthermore, some foci of human and canine L. donovani transmission were coincident with overlapping L. donovani genotypes, indicating that dogs may have an important role in sustaining human VL in Sudan, which deserves further investigation.
RB, SF, KK, and MSL analysed the data. GS, MAM, and ILM, conceived the experiments. RB MSL MAM and ILM wrote the paper. All authors read and approved the final manuscript.
The authors gratefully acknowledge Dr Sayda El Safi and colleagues for their work collecting many of the strains genotyped in this study.
The research was funded by the Wellcome Trust, UK, and an academic merit scholarship for RB from the Islamic Development Bank (IDB).
- Hassan MM, Osman OF, El-Raba’a FM, Schallig HD, Elnaiem DE: Role of the domestic dog as a reservoir host of Leishmania donovani in eastern Sudan. Parasit Vectors. 2009, 2: 26-10.1186/1756-3305-2-26.PubMed CentralView ArticlePubMedGoogle Scholar
- Singh N, Mishra J, Singh R, Singh S: Animal reservoirs of visceral leishmaniasis in India. J Parasitol. 2013, 99: 64-67. 10.1645/GE-3085.1.View ArticlePubMedGoogle Scholar
- Zink AR, Spigelman M, Schraut B, Greenblatt CL, Nerlich AG, Donoghue HD: Leishmaniasis in Ancient Egypt and Upper Nubia. Emerg Infect Dis. 2006, 12: 1616-1617. 10.3201/eid1210.060169.PubMed CentralView ArticlePubMedGoogle Scholar
- Dereure J, El-Safi SH, Bucheton B, Boni M, Kheir MM, Davoust B, Pratlong F, Feugier E, Lambert M, Dessein A, Dedet JP: Visceral leishmaniasis in eastern Sudan: parasite identification in humans and dogs; host-parasite relationships. Microbes Infect. 2003, 5: 1103-1108. 10.1016/j.micinf.2003.07.003.View ArticlePubMedGoogle Scholar
- Seaman J, Mercer AJ, Sondorp E: The epidemic of visceral leishmaniasis in western Upper Nile, southern Sudan: course and impact from 1984 to 1994. Int J Epidemiol. 1996, 25: 862-871. 10.1093/ije/25.4.862.View ArticlePubMedGoogle Scholar
- Mueller YK, Nackers F, Ahmed KA, Boelaert M, Djoumessi JC, Eltigani R, Gorashi HA, Hammam O, Ritmeijer K, Salih N, Worku D, Etard JF, Chappuis F: Burden of visceral leishmaniasis in villages of eastern Gedaref State, Sudan: an exhaustive cross-sectional survey. PLoS Negl Trop Dis. 2012, 6: e1872-10.1371/journal.pntd.0001872.PubMed CentralView ArticlePubMedGoogle Scholar
- Zijlstra EE, el-Hassan AM: Leishmaniasis in Sudan: Visceral leishmaniasis. Trans R Soc Trop Med Hyg. 2001, 95 (Suppl 1): S27-S58. 10.1016/S0035-9203(01)90218-4.View ArticlePubMedGoogle Scholar
- Kuhls K, Mauricio IL, Pratlong F, Presber W, Schonian G: Analysis of ribosomal DNA internal transcribed spacer sequences of the Leishmania donovani complex. Microbes Infect. 2005, 7: 1224-1234. 10.1016/j.micinf.2005.04.009.View ArticlePubMedGoogle Scholar
- Mauricio IL, Howard MK, Stothard JR, Miles MA: Genetic diversity in the Leishmania donovani complex. Parasitology. 1999, 119: 237-246. 10.1017/S0031182099004710.View ArticlePubMedGoogle Scholar
- Mauricio IL, Yeo M, Baghaei M, Doto D, Pratlong F, Zemanova E, Dedet JP, Lukes J, Miles MA: Towards multilocus sequence typing of the Leishmania donovani complex: resolving genotypes and haplotypes for five polymorphic metabolic enzymes (ASAT, GPI, NH1, NH2, PGD). Int J Parasitol. 2006, 36: 757-769. 10.1016/j.ijpara.2006.03.006.View ArticlePubMedGoogle Scholar
- Zemanova E, Jirku M, Mauricio IL, Horak A, Miles MA, Lukes J: The Leishmania donovani complex: genotypes of five metabolic enzymes (ICD, ME, MPI, G6PDH, and FH), new targets for multilocus sequence typing. Int J Parasitol. 2007, 37: 149-160. 10.1016/j.ijpara.2006.08.008.View ArticlePubMedGoogle Scholar
- Kuhls K, Keilonat L, Ochsenreither S, Schaar M, Schweynoch C, Presber W, Schönian G: Multilocus microsatellite typing (MLMT) reveals genetically isolated populations between and within the main endemic regions of visceral leishmaniasis. Microbes Infect. 2007, 9: 334-343. 10.1016/j.micinf.2006.12.009.View ArticlePubMedGoogle Scholar
- Alam MZ, Kuhls K, Schweynoch C, Sundar S, Rijal S, Shamsuzzaman AK, Raju BV, Salotra P, Dujardin JC, Schönian G: Multilocus microsatellite typing (MLMT) reveals genetic homogeneity of Leishmania donovani strains in the Indian subcontinent. Infect Genet Evol. 2009, 9: 24-31. 10.1016/j.meegid.2008.09.005.View ArticlePubMedGoogle Scholar
- Gelanew T, Kuhls K, Hurissa Z, Weldegebreal T, Hailu W, Kassahun A, Abebe T, Hailu A, Schönian G: Inference of population structure of Leishmania donovani strains isolated from different Ethiopian visceral leishmaniasis endemic areas. PLoS Negl Trop Dis. 2010, 4: e889-10.1371/journal.pntd.0000889.PubMed CentralView ArticlePubMedGoogle Scholar
- Rougeron V, De Meeûs T, Hide M, Le Falher G, Bucheton B, Dereure J, El-Safi SH, Dessein A, Bañuls AL: Multifaceted population structure and reproductive strategy in Leishmania donovani complex in one Sudanese village. PLoS Negl Trop Dis. 2011, 5: e1448-10.1371/journal.pntd.0001448.PubMed CentralView ArticlePubMedGoogle Scholar
- Rogers MB, Downing T, Smith BA, Imamura H, Sanders M, Svobodova M, Volf P, Berriman M, Cotton JA, Smith DF: Genomic confirmation of hybridisation and recent inbreeding in a vector-isolated Leishmania population. PLoS Genet. 2014, 10: e1004092-10.1371/journal.pgen.1004092.PubMed CentralView ArticlePubMedGoogle Scholar
- Akopyants NS, Kimblin N, Secundino N, Patrick R, Peters N, Lawyer P, Dobson DE, Beverley SM, Sacks DL: Demonstration of genetic exchange during cyclical development of Leishmania in the sand fly vector. Science. 2009, 324: 265-268. 10.1126/science.1169464.PubMed CentralView ArticlePubMedGoogle Scholar
- Volf P, Benkova I, Myskova J, Sadlova J, Campino L, Ravel C: Increased transmission potential of Leishmania major/Leishmania infantum hybrids. Int J Parasitol. 2007, 37: 589-593. 10.1016/j.ijpara.2007.02.002.PubMed CentralView ArticlePubMedGoogle Scholar
- Sadlova J, Yeo M, Seblova V, Lewis MD, Mauricio I, Volf P, Miles MA: Visualisation of Leishmania donovani fluorescent hybrids during early stage development in the sand fly vector. PLoS One. 2011, 6: e19851-10.1371/journal.pone.0019851.PubMed CentralView ArticlePubMedGoogle Scholar
- Rougeron V, De Meeus T, Hide M, Waleckx E, Bermudez H, Arevalo J, Llanos-Cuentas A, Dujardin JC, De Doncker S, Le Ray D, Ayala FJ, Bañuls AL: Extreme inbreeding in Leishmania braziliensis. Proc Natl Acad Sci U S A. 2009, 106: 10224-10229. 10.1073/pnas.0904420106.PubMed CentralView ArticlePubMedGoogle Scholar
- Rougeron V, Banuls AL, Carme B, Simon S, Couppié P, Nacher M, Hide M, De Meeûs T: Reproductive strategies and population structure in Leishmania: substantial amount of sex in Leishmania Viannia guyanensis. Mol Ecol. 2011, 20: 3116-3127. 10.1111/j.1365-294X.2011.05162.x.View ArticlePubMedGoogle Scholar
- Yeo M, Lewis MD, Carrasco HJ, Acosta N, Llewellyn M, da Silva Valente SA, de Costa Valente V, de Arias AR, Miles MA: Resolution of multiclonal infections of Trypanosoma cruzi from naturally infected triatomine bugs and from experimentally infected mice by direct plating on a sensitive solid medium. Int J Parasitol. 2007, 37: 111-120. 10.1016/j.ijpara.2006.08.002.View ArticlePubMedGoogle Scholar
- Jombart T: adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics. 2008, 24: 1403-1405. 10.1093/bioinformatics/btn129.View ArticlePubMedGoogle Scholar
- Jombart T, Devillard S, Balloux F: Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet. 2010, 11: 94-10.1186/1471-2156-11-94.PubMed CentralView ArticlePubMedGoogle Scholar
- Minch E, Ruíz-Linares A, Goldstein D, Feldman M, Cavalli-Sforza L: MICROSAT - the Microsatellite Distance Program. 1995, Stanford University Press, StanfordGoogle Scholar
- Weir B, Cockerham C: Estimating F-statistics for the analysis of population structure. Evolution. 1984, 38: 1358-1370. 10.2307/2408641.View ArticleGoogle Scholar
- Excoffier L, Lischer HE: Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour. 2010, 10: 564-567. 10.1111/j.1755-0998.2010.02847.x.View ArticlePubMedGoogle Scholar
- Slatkin M: A measure of population subdivision based on microsatellite allele frequencies. Genetics. 1995, 139: 457-462.PubMed CentralPubMedGoogle Scholar
- Goudet J: FSTAT version 1.2: a computer program to calculate F-statistics. J Heredity. 1995, 86: 485-486.Google Scholar
- Mauricio IL, Gaunt MW, Stothard JR, Miles MA: Glycoprotein 63 (gp63) genes show gene conversion and reveal the evolution of Old World Leishmania. Int J Parasitol. 2007, 37: 565-576. 10.1016/j.ijpara.2006.11.020.View ArticlePubMedGoogle Scholar
- Thompson JD, Higgins DG, Gibson TJ: CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994, 22: 4673-4680. 10.1093/nar/22.22.4673.PubMed CentralView ArticlePubMedGoogle Scholar
- Hall TA: BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp Ser. 1999, 41: 95-98.Google Scholar
- Stephens M, Smith N, Donnelly P: A new statistical method for haplotype reconstruction from population data. Am J Hum Genet. 2001, 68: 978-989. 10.1086/319501.PubMed CentralView ArticlePubMedGoogle Scholar
- Martin D, Williamson C, Posada D: RDP2: recombination detection and analysis from sequence alignments. Bioinformatics. 2005, 21: 260-262. 10.1093/bioinformatics/bth490.View ArticlePubMedGoogle Scholar
- Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, Gascuel O: New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol. 2010, 59: 307-321. 10.1093/sysbio/syq010.View ArticlePubMedGoogle Scholar
- Posada D, Crandall KA: MODELTEST: testing the model of DNA substitution. Bioinformatics. 1998, 14: 817-818. 10.1093/bioinformatics/14.9.817.View ArticlePubMedGoogle Scholar
- Librado P, Rozas J: DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics. 2009, 25: 1451-1452. 10.1093/bioinformatics/btp187.View ArticlePubMedGoogle Scholar
- Hudson RR, Boos DD, Kaplan NL: A statistical test for detecting geographic subdivision. Mol Biol Evol. 1992, 9: 138-151.PubMedGoogle Scholar
- Elnaiem DA, Hassan MM, Maingon R, Nureldin GH, Mekawi AM, Miles M, Ward RD: The Egyptian mongoose, Herpestes ichneumon, is a possible reservoir host of visceral leishmaniasis in eastern Sudan. Parasitology. 2001, 122: 531-536. 10.1017/S0031182001007594.View ArticlePubMedGoogle Scholar
- Lukes J, Mauricio IL, Schonian G, Dujardin JC, Soteriadou K, Dedet JP, Kuhls K, Tintaya KW, Jirků M, Chocholová E, Haralambous C, Pratlong F, Oborník M, Horák A, Ayala FJ, Miles MA: Evolutionary and geographical history of the Leishmania donovani complex with a revision of current taxonomy. Proc Natl Acad Sci U S A. 2007, 104: 9375-9380. 10.1073/pnas.0703678104.PubMed CentralView ArticlePubMedGoogle Scholar
- Gosi P, Lanteri CA, Tyner SD, Se Y, Lon C, Spring M, Char M, Sea D, Sriwichai S, Surasri S, Wongarunkochakorn S, Pidtana K, Walsh DS, Fukuda MM, Manning J, Saunders DL, Bethell D: Evaluation of parasite subpopulations and genetic diversity of the msp1, msp2 and glurp genes during and following artesunate monotherapy treatment of Plasmodium falciparum malaria in Western Cambodia. Malar J. 2013, 12: 403-10.1186/1475-2875-12-403.PubMed CentralView ArticlePubMedGoogle Scholar
- Norton AJ, Gower CM, Lamberton PH, Webster BL, Lwambo NJ, Blair L, Fenwick A, Webster JP: Genetic consequences of mass human chemotherapy for Schistosoma mansoni: population structure pre- and post-praziquantel treatment in Tanzania. Am J Trop Med Hyg. 2010, 83: 951-957. 10.4269/ajtmh.2010.10-0283.PubMed CentralView ArticlePubMedGoogle Scholar
- Llewellyn MS, Miles MA, Carrasco HJ, Lewis MD, Yeo M, Vargas J, Torrico F, Diosque P, Valente V, Valente SA, Gaunt MW: Genome-scale multilocus microsatellite typing of Trypanosoma cruzi discrete typing unit I reveals phylogeographic structure and specific genotypes linked to human infection. PLoS Pathog. 2009, 5: e1000410-10.1371/journal.ppat.1000410.PubMed CentralView ArticlePubMedGoogle Scholar
- Gouzelou E, Haralambous C, Amro A, Mentis A, Pratlong F, Dedet JP, Votypka J, Volf P, Toz SO, Kuhls K, Schönian G, Soteriadou K: Multilocus microsatellite typing (MLMT) of strains from Turkey and Cyprus reveals a novel monophyletic L. donovani sensu lato group. PLoS Negl Trop Dis. 2012, 6: e1507-10.1371/journal.pntd.0001507.PubMed CentralView ArticlePubMedGoogle Scholar
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