Population genetics of Glossina palpalis palpalis from central African sleeping sickness foci
TL;DR: This first investigation of population genetic structure of G. p.
Abstract: Background: Glossina palpalis palpalis (Diptera: Glossinidae) is widespread in west Africa, and is the main vector of sleeping sickness in Cameroon as well as in the Bas Congo Province of the Democratic Republic of Congo. However, little is known on the structure of its populations. We investigated G. p. palpalis population genetic structure in five sleeping sickness foci (four in Cameroon, one in Democratic Republic of Congo) using eight microsatellite DNA markers. Results: A strong isolation by distance explains most of the population structure observed in our sampling sites of Cameroon and DRC. The populations here are composed of panmictic subpopulations occupying fairly wide zones with a very strong isolation by distance. Effective population sizes are probably between 20 and 300 individuals and if we assume densities between 120 and 2000 individuals per km 2 , dispersal distance between reproducing adults and their parents extends between 60 and 300 meters. Conclusions: This first investigation of population genetic structure of G. p. palpalis in Central Africa has evidenced random mating subpopulations over fairly large areas and is thus at variance with that found in West African populations of G. p. palpalis. This study brings new information on the isolation by distance at a macrogeographic scale which in turn brings useful information on how to organise regional tsetse control. Future investigations should be directed at temporal sampling to have more accurate measures of demographic parameters in order to help vector control decision.
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TL;DR: Tsetse re-emergence after control interventions may be due to re-invasions from outside the treated areas, which emphasizes the need for an integrated area-wide t setse eradication strategy for sustainable removal of the tsetse and trypanosomiasis problem from this area.
Abstract: Background
Glossina fuscipes fuscipes is the main vector of African Trypanosomiasis affecting both humans and livestock in Uganda The human disease (sleeping sickness) manifests itself in two forms: acute and chronic The Lake Victoria basin in Uganda has the acute form and a history of tsetse re-emergence despite concerted efforts to control tsetse The government of Uganda has targeted the basin for tsetse eradication To provide empirical data for this initiative, we screened tsetse flies from the basin for genetic variation at the mitochondrial DNA cytochrome oxidase II (mtDNA COII) gene with the goal of investigating genetic diversity and gene flow among tsetse, tsetse demographic history; and compare these results with results from a previous study based on microsatellite loci data in the same area
10 citations
Cites background from "Population genetics of Glossina pal..."
...Melachio TTT, Simo G, Ravel S, De Meeûs T, Causse S, Solano P, et al. Population genetics of Glossina palpalis palpalis from central African sleeping sickness foci....
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...Aksoy S, Caccone A, Galvani AP, Okedi LM. Glossina fuscipes populations provide insights for human African trypanosomiasis transmission in Uganda....
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...Tsetse re-emergence is a major obstacle to elimination of the tsetse fly vector in Africa [28]....
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...Cecchi G, Paone M, Franco JR, Fèvre EM, Diarra A, Ruiz JA, et al. Towards the Atlas of human African trypanosomiasis....
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...For example, regional studies such as the one on riverine Glossina palpalis palpalis in west and central Africa [19] have provided information that is useful for control of riverine palpalis tsetse group in cross-boundary projects....
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TL;DR: Tsetse flies populations circulating in Equatorial Guinea are composed of two allopatric subspecies, one insular and the other continental, and the presence of these two G. palpalis cryptic taxa should be taken into account to accurately manage vector control strategy.
Abstract: Background: Luba is one of the four historical foci of Human African Trypanosomiasis (HAT) on Bioko Island, in Equatorial Guinea. Although no human cases have been detected since 1995, T. b. gambiense was recently observed in the vector Glossina palpalis palpalis. The existence of cryptic species within this vector taxon has been previously suggested, although no data are available regarding the evolutionary history of tsetse flies populations in Bioko. Methods: A phylogenetic analysis of 60G. p. palpalis from Luba was performed sequencing three mitochondrial (COI, ND2 and 16S) and one nuclear (rDNA-ITS1) DNA markers. Phylogeny reconstruction was performed by Distance Based, Maximum Likelihood and Bayesian Inference methods. Results: The COI and ND2 mitochondrial genes were concatenated and revealed 10 closely related haplotypes with a dominant one found in 61.1% of the flies. The sequence homology of the other 9 haplotypes compared to the former ranged from 99.6 to 99.9%. Phylogenetic analysis clearly clustered all island samples with flies coming from the Western African Clade (WAC), and separated from the flies belonging to the Central Africa Clade (CAC), including samples from Mbini and Kogo, two foci of mainland Equatorial Guinea. Consistent with mitochondrial data, analysis of the microsatellite motif present in the ITS1 sequence exhibited two closely related genotypes, clearly divergent from the genotypes previously identified in Mbini and Kogo. Conclusions: We report herein that tsetse flies populations circulating in Equatorial Guinea are composed of two allopatric subspecies, one insular and the other continental. The presence of these two G. p. palpalis cryptic taxa in Equatorial Guinea should be taken into account to accurately manage vector control strategy, in a country where trypanosomiasis transmission is controlled but not definitively eliminated yet.
10 citations
Journal Article•
TL;DR: This review mainly focuses on population genetics of t setse of the palpalis group, the main vectors of sleeping sickness, and reports recent results on tsetse population structure and on measures of gene flow between populations.
Abstract: In sub-Saharan Africa, tsetse transmitted Trypanosomiases have an enormous impact on human health and economic development. Both the World Health Organisation and African countries through the Pan African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC) have recently asserted their determination to rid the sub-continent of these diseases, and it is increasingly recognised that vector control should play an important role. This review mainly focuses on population genetics of tsetse of the palpalis group, the main vectors of sleeping sickness, and reports recent results on tsetse population structure and on measures of gene flow between populations. Implications of these studies for large-scale tsetse control programmes being undertaken in West Africa are important, particularly regarding control strategies (suppression or eradication).
9 citations
TL;DR: HATSim is developed, an agent-based model capable of simulating the possible endemic evolutions of sleeping sickness and the ability of National Control Programs to eliminate the disease, and results indicate that the current model can already help decision-makers in planning the elimination of the disease in foci.
Abstract: Although Human African Trypanosomiasis is largely considered to be in the process of extinction today, the persistence of human and animal reservoirs, as well as the vector, necessitates a laborious elimination process. In this context, modeling could be an effective tool to evaluate the ability of different public health interventions to control the disease. Using the Cormas ® system, we developed HATSim, an agent-based model capable of simulating the possible endemic evolutions of sleeping sickness and the ability of National Control Programs to eliminate the disease. This model takes into account the analysis of epidemiological, entomological, and ecological data from field studies conducted during the last decade, making it possible to predict the evolution of the disease within this area over a 5-year span. In this article, we first present HATSim according to the Overview, Design concepts, and Details (ODD) protocol that is classically used to describe agent-based models, then, in a second part, we present predictive results concerning the evolution of Human African Trypanosomiasis in the village of Lambi (Cameroon), in order to illustrate the interest of such a tool. Our results are consistent with what was observed in the field by the Cameroonian National Control Program (CNCP). Our simulations also revealed that regular screening can be sufficient, although vector control applied to all areas with human activities could be significantly more efficient. Our results indicate that the current model can already help decision-makers in planning the elimination of the disease in foci.
9 citations
Cites background from "Population genetics of Glossina pal..."
...palpalis [22], flies were programmed to have a range with a radius of 300 m in length, or a circle with a diameter of 3 cells in HATSim....
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...Considering the tropical forest environment of Lambi, which favors humidity and a great diversity of feeding hosts, and the study by Melachio et al. (2011) about the genetics of tsetse flies in Cameroon that identified panmictic subpopulations of G. p. palpalis [22], flies were programmed to have a…...
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TL;DR: Differences in the prevalence of Wolbachia and trypanosomes in G. p.
Abstract: African trypanosomiases are caused by trypanosomes that are cyclically transmitted by tsetse. Investigations aiming to generate knowledge on the bacterial fauna of tsetse have revealed distinct symbiotic microorganisms. Furthermore, studies addressing the tripartite association between trypanosomes-tsetse-symbionts relationship have so far been contradictory. Most studies included Sodalis glossinudius and, consequently, the association involving Wolbachia is poorly understood. Understanding the vectorial competence of tsetse requires decrypting these tripartite associations. In this study, we identified Wolbachia and trypanosomes in Glossina palpalis palpalis from three human African trypanosomiasis (HAT) foci in southern Cameroon. Tsetse flies were captured with pyramidal traps in the Bipindi, Campo and Fontem HAT foci. After morphological identification, DNA was extracted from whole tsetse flies and Wolbachia and trypanosomes were identified by PCR using different trypanosome-specific primers and two Wolbachia-specific primers (Wolbachia surface protein and 16S rRNA genes). Statistical analyses were performed to compare the trypanosome and Wolbachia infection rates between villages and different foci and to look for an association between these microorganisms. From a total of 2122 tsetse flies, 790 G. p. palpalis were analyzed. About 25.32% of flies hosted Wolbachia and 31.84% of non-teneral flies were infected by at least one trypanosome species. There was no significant difference between the global Wolbachia prevalence revealed by the two markers while some differences were observed between HAT foci. From 248 G. p. palpalis with trypanosome infections, 62.90% were with T. vivax, 34.68% with T. congolense forest, 16.13% with T. brucei (s.l.) and 2.42% with T. congolense savannah. Of all trypanosome-infected flies, 29.84% hosted Wolbachia and no association was observed between Wolbachia and trypanosome co-infections. This study revealed differences in the prevalence of Wolbachia and trypanosomes in G. p. palpalis according to HAT foci. The use of only one marker has underestimated the prevalence of Wolbachia, thus more markers in subsequent studies may improve its detection. The presence of Wolbachia seems to have no impact on the establishment of trypanosomes in G. p. palpalis. The tripartite association between tsetse, Wolbachia and trypanosomes varies according to studied areas. Studies aiming to evaluate the genetic polymorphism of Wolbachia and its density in tsetse flies could help to better understand this association.
8 citations
References
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TL;DR: The purpose of this discussion is to offer some unity to various estimation formulae and to point out that correlations of genes in structured populations, with which F-statistics are concerned, are expressed very conveniently with a set of parameters treated by Cockerham (1 969, 1973).
Abstract: This journal frequently contains papers that report values of F-statistics estimated from genetic data collected from several populations. These parameters, FST, FIT, and FIS, were introduced by Wright (1951), and offer a convenient means of summarizing population structure. While there is some disagreement about the interpretation of the quantities, there is considerably more disagreement on the method of evaluating them. Different authors make different assumptions about sample sizes or numbers of populations and handle the difficulties of multiple alleles and unequal sample sizes in different ways. Wright himself, for example, did not consider the effects of finite sample size. The purpose of this discussion is to offer some unity to various estimation formulae and to point out that correlations of genes in structured populations, with which F-statistics are concerned, are expressed very conveniently with a set of parameters treated by Cockerham (1 969, 1973). We start with the parameters and construct appropriate estimators for them, rather than beginning the discussion with various data functions. The extension of Cockerham's work to multiple alleles and loci will be made explicit, and the use of jackknife procedures for estimating variances will be advocated. All of this may be regarded as an extension of a recent treatment of estimating the coancestry coefficient to serve as a mea-
17,890 citations
"Population genetics of Glossina pal..." refers methods in this paper
...Population parameters were assessed through Weir and Cockerham’s unbiased estimators [21] of Wright’s F-statistics [22] and their significance assessed through 10000 permutations with Fstat 2....
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Journal Article•
TL;DR: The technic to be given below for imparting statistical validity to the procedures already in vogue can be viewed as a generalized form of regression with possible useful application to problems arising in quite different contexts.
Abstract: The problem of identifying subtle time-space clustering of disease, as may be occurring in leukemia, is described and reviewed. Published approaches, generally associated with studies of leukemia, not dependent on knowledge of the underlying population for their validity, are directed towards identifying clustering by establishing a relationship between the temporal and the spatial separations for the n ( n - 1)/2 possible pairs which can be formed from the n observed cases of disease. Here it is proposed that statistical power can be improved by applying a reciprocal transform to these separations. While a permutational approach can give valid probability levels for any observed association, for reasons of practicability, it is suggested that the observed association be tested relative to its permutational variance. Formulas and computational procedures for doing so are given.
While the distance measures between points represent symmetric relationships subject to mathematical and geometric regularities, the variance formula developed is appropriate for arbitrary relationships. Simplified procedures are given for the case of symmetric and skew-symmetric relationships. The general procedure is indicated as being potentially useful in other situations as, for example, the study of interpersonal relationships. Viewing the procedure as a regression approach, the possibility for extending it to nonlinear and multivariate situations is suggested.
Other aspects of the problem and of the procedure developed are discussed.
Similarly, pure temporal clustering can be identified by a study of incidence rates in periods of widespread epidemics. In point of fact, many epidemics of communicable diseases are somewhat local in nature and so these do actually constitute temporal-spatial clusters. For leukemia and similar diseases in which cases seem to arise substantially at random rather than as clear-cut epidemics, it is necessary to devise sensitive and efficient procedures for detecting any nonrandom component of disease occurrence.
Various ingenious procedures which statisticians have developed for the detection of disease clustering are reviewed here. These procedures can be generalized so as to increase their statistical validity and efficiency. The technic to be given below for imparting statistical validity to the procedures already in vogue can be viewed as a generalized form of regression with possible useful application to problems arising in quite different contexts.
11,408 citations
"Population genetics of Glossina pal..." refers methods in this paper
...The significance of this regression was assessed with a Mantel test of randomization of cells of one matrix [42]....
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TL;DR: MICRO - CHECKER estimates the frequency of null alleles and, importantly, can adjust the allele and genotype frequencies of the amplified alleles, permitting their use in further population genetic analysis.
Abstract: DNA degradation, low DNA concentrations and primer-site mutations may result in the incorrect assignment of microsatellite genotypes, potentially biasing population genetic analyses. MICRO - CHECKER is WINDOWS ®-based software that tests the genotyping of microsatellites from diploid populations. The program aids identification of genotyping errors due to nonamplified alleles (null alleles), short allele dominance (large allele dropout) and the scoring of stutter peaks, and also detects typographic errors. MICRO - CHECKER estimates the frequency of null alleles and, importantly, can adjust the allele and genotype frequencies of the amplified alleles, permitting their use in further population genetic analysis. MICRO CHECKER can be freely downloaded from http://www.microchecker.hull.ac.uk/.
9,953 citations
"Population genetics of Glossina pal..." refers methods in this paper
...’s method [26] and Brookfield’s second method [27]....
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TL;DR: This note summarizes developments of the genepop software since its first description in 1995, and in particular those new to version 4.0: an extended input format, several estimators of neighbourhood size under isolation by distance, new estimators and confidence intervals for null allele frequency, and less important extensions to previous options.
Abstract: This note summarizes developments of the genepop software since its first description in 1995, and in particular those new to version 4.0: an extended input format, several estimators of neighbourhood size under isolation by distance, new estimators and confidence intervals for null allele frequency, and less important extensions to previous options. genepop now runs under Linux as well as under Windows, and can be entirely controlled by batch calls.
8,171 citations
"Population genetics of Glossina pal..." refers methods in this paper
...All these isolation by distance procedures were undertaken with Genepop 4 [43] with 1000000 iterations for the Mantel test and georeferenced coordinates in Km of traps....
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7,585 citations