High levels of genetic differentiation between Ugandan Glossina fuscipes fuscipes populations separated by Lake Kyoga

Development and characterization of microsatellite markers for the tsetse species Glossina brevipalpis and preliminary population genetics analyses

Tsetse flies, the vectors of African trypanosomes are of key medical and economic importance and one of the constraints for the development of Africa. Tsetse fly control is one of the most effective and sustainable strategies used for controlling the disease. Knowledge about population structure and level of gene flow between neighbouring populations of the target vector is of high importance to develop appropriate strategies for implementing effective management programmes. Microsatellites are commonly used to identify population structure and assess dispersal of the target populations and have been developed for several tsetse species but were lacking for Glossina brevipalpis. In this study, we screened the genome of G. brevipalpis to search for suitable microsatellite markers and nine were found to be efficient enough to distinguish between different tsetse populations. The availability of these novel microsatellite loci will help to better understand the population biology of G. brevipalpis and to assess the level of gene flow between different populations. Such information will help with the development of appropriate strategies to implement the sterile insect technique (SIT) in the framework of an area-wide integrated pest management (AW-IPM) approach to manage tsetse populations and ultimately address the trypanosomoses problem in these targeted areas.

Spatial analysis of G.f.fuscipes abundance in Uganda using Poisson and Zero-Inflated Poisson regression models

BACKGROUND

Tsetse flies are the major vectors of human trypanosomiasis of the form Trypanosoma brucei rhodesiense and T.b.gambiense. They are widely spread across the sub-Saharan Africa and rendering a lot of challenges to both human and animal health. This stresses effective agricultural production and productivity in Africa. Delimiting the extent and magnitude of tsetse coverage has been a challenge over decades due to limited resources and unsatisfactory technology. In a bid to overcome these limitations, this study attempted to explore modelling skills that can be applied to spatially estimate tsetse abundance in the country using limited tsetse data and a set of remote-sensed environmental variables.

METHODOLOGY

Entomological data for the period 2008-2018 as used in the model were obtained from various sources and systematically assembled using a structured protocol. Data harmonisation for the purposes of responsiveness and matching was carried out. The key tool for tsetse trapping was itemized as pyramidal trap in many instances and biconical trap in others. Based on the spatially explicit assembled data, we ran two regression models; standard Poisson and Zero-Inflated Poisson (ZIP), to explore the associations between tsetse abundance in Uganda and several environmental and climatic covariates. The covariate data were constituted largely by satellite sensor data in form of meteorological and vegetation surrogates in association with elevation and land cover data. We finally used the Zero-Inflated Poisson (ZIP) regression model to predict tsetse abundance due to its superiority over the standard Poisson after model fitting and testing using the Vuong Non-Nested statistic.

RESULTS

A total of 1,187 tsetse sampling points were identified and considered as representative for the country. The model results indicated the significance and level of responsiveness of each covariate in influencing tsetse abundance across the study area. Woodland vegetation, elevation, temperature, rainfall, and dry season normalised difference vegetation index (NDVI) were important in determining tsetse abundance and spatial distribution at varied scales. The resultant prediction map shows scaled tsetse abundance with estimated fitted numbers ranging from 0 to 59 flies per trap per day (FTD). Tsetse abundance was found to be largest at low elevations, in areas of high vegetative activity, in game parks, forests and shrubs during the dry season. There was very limited responsiveness of selected predictors to tsetse abundance during the wet season, matching the known fact that tsetse disperse most significantly during wet season.

CONCLUSIONS

A methodology was advanced to enable compilation of entomological data for 10 years, which supported the generation of tsetse abundance maps for Uganda through modelling. Our findings indicate the spatial distribution of the G. f. fuscipes as; low 0-5 FTD (48%), medium 5.1-35 FTD (18%) and high 35.1-60 FTD (34%) grounded on seasonality. This approach, amidst entomological data shortages due to limited resources and absence of expertise, can be adopted to enable mapping of the vector to provide better decision support towards designing and implementing targeted tsetse and tsetse-transmitted African trypanosomiasis control strategies.

Population Structure and Migration Patterns of the Tsetse Fly Glossina fuscipes in Congo-Brazzaville

Tsetse flies of the palpalis group, particularly Glossina fuscipes, are the main vectors of human African trypanosomiasis or sleeping sickness in Congo-Brazzaville. They transmit the deadly human parasite, Trypanosoma brucei gambiense and other trypanosomes that cause animal trypanosomiasis. Knowledge on diversity, population structure, population size, and gene flow is a prerequisite for designing effective tsetse control strategies. There is limited published information on these parameters including migration patterns of G. fuscipes in Congo-Brazzaville. We genotyped 288 samples of G. fuscipes from Bomassa (BMSA), Bouemba (BEMB), and Talangai (TLG) locations at 10 microsatellite loci and determined levels of genetic diversity, differentiation, structuring, and gene flow among populations. We observed high genetic diversity in all three localities. Mean expected heterozygosity was 0.77 ± 0.04, and mean allelic richness was 11.2 ± 1.35. Deficiency of heterozygosity was observed in all populations with positive and significant F IS values (0.077-0.149). Structure analysis revealed three clusters with genetic admixtures, evidence of closely related but potentially different taxa within G. fuscipes. Genetic differentiation indices were low but significant (F ST = 0.049, P < 0.05), indicating ongoing gene flow countered with a stronger force of drift. We recorded significant migration from all the three populations, suggesting exchange of genetic information between and among locations. Ne estimates revealed high and infinite population sizes in BEMB and TLG. These critical factors should be considered when planning area-wide tsetse control interventions in the country to prevent resurgence of tsetse from relict populations and/or reinvasion of cleared habitats.

Developing and quality testing of microsatellite loci for four species of Glossina

Microsatellite loci still represent valuable resources for the study of the population biology of non-model organisms. Discovering or adapting new suitable microsatellite markers in species of interest still represents a useful task, especially so for non-model organisms as tsetse flies (genus Glossina), which remain a serious threat to the health of humans and animals in sub-Saharan Africa. In this paper, we present the development of new microsatellite loci for four species of Glossina: two from the Morsitans group, G. morsitans morsitans (Gmm) from Zimbabwe, G. pallidipes (Gpalli) from Tanzania; and the other two from the Palpalis group, G. fuscipes fuscipes (Gff) from Chad, and G. palpalis gambiensis (Gpg) from Guinea. We found frequent short allele dominance and null alleles. Stuttering could also be found and amended when possible. Cryptic species seemed to occur frequently in all taxa but Gff. This explains why it may be difficult finding ecumenical primers, which thus need adaptation according to each taxonomic and geographic context. Amplification problems occurred more often in published old markers, and Gmm and Gpg were the most affected (stronger heterozygote deficits). Trinucleotide markers displayed selection signature in some instances (Gmm). Combining old and new loci, for Gmm, eight loci can be safely used (with correction for null alleles); and five seem particularly promising; for Gpalli, only five to three loci worked well, depending on the clade, which means that the use of loci from other species (four morsitans loci seemed to work well), or other new primers will need to be used; for Gff, 14 loci behaved well, but with null alleles, seven of which worked very well; and for G. palpalis sl, only four loci, needing null allele and stuttering corrections seem to work well, and other loci from the literature are thus needed, including X-linked markers, five of which seem to work rather well (in females only), but new markers will probably be needed. Finally, the high proportion of X-linked markers (around 30%) was explained by the non-Y DNA quantity and chromosome structure of tsetse flies studied so far.

The population genomics of multiple tsetse fly (Glossina fuscipes fuscipes) admixture zones in Uganda

Understanding the mechanisms that enforce, maintain or reverse the process of speciation is an important challenge in evolutionary biology. This study investigates the patterns of divergence and discusses the processes that form and maintain divergent lineages of the tsetse fly Glossina fuscipes fuscipes in Uganda. We sampled 251 flies from 18 sites spanning known genetic lineages and the four admixture zones between them. We apply population genomics, hybrid zone and approximate Bayesian computation to the analysis of three types of genetic markers: 55,267 double-digest restriction site-associated DNA (ddRAD) SNPs to assess genome-wide admixture, 16 microsatellites to provide continuity with published data and accurate biogeographic modelling, and a 491-bp fragment of mitochondrial cytochrome oxidase I and II to infer maternal inheritance patterns. Admixture zones correspond with regions impacted by the reorganization of Uganda's river networks that occurred during the formation of the West African Rift system over the last several hundred thousand years. Because tsetse fly population distributions are defined by rivers, admixture zones likely represent both old and new regions of secondary contact. Our results indicate that older hybrid zones contain mostly parental types, while younger zones contain variable hybrid types resulting from multiple generations of interbreeding. These findings suggest that reproductive barriers are nearly complete in the older admixture zones, while nearly absent in the younger admixture zones. Findings are consistent with predictions of hybrid zone theory: Populations in zones of secondary contact transition rapidly from early to late stages of speciation or collapse all together.

Diversity and phylogenetic relationships of Glossina populations in Nigeria and the Cameroonian border region

Background

Tsetse flies are vectors of trypanosomes, parasites that cause devastating disease in humans and livestock. In the course of vector control programmes it is necessary to know about the Glossina species present in the study area, the population dynamics and the genetic exchange between tsetse fly populations.

Results

To achieve an overview of the tsetse fly diversity in Nigeria and at the Nigeria-Cameroon border, tsetse flies were trapped and collected between February and March 2014 and December 2016. Species diversity was determined morphologically and by analysis of Cytochrome C Oxidase SU1 (COI) gene sequences. Internal transcribed spacer-1 (ITS-1) sequences were compared to analyse variations within populations. The most dominant species were G. m. submorsitans, G. tachinoides and G. p. palpalis. In Yankari Game Reserve and Kainji Lake National Park, G. submorsitans and G. tachinoides were most frequent, whereas in Old Oyo National Park and Ijah Gwari G. p. palpalis was the dominant species. Interestingly, four unidentified species were recorded during the survey, for which no information on COI or ITS-1 sequences exists. G. p. palpalis populations showed a segregation in two clusters along the Cameroon-Nigerian border.

Conclusions

The improved understanding of the tsetse populations in Nigeria will support decisions on the scale in which vector control is likely to be more effective. In order to understand in more detail how isolated these populations are, it is recommended that further studies on gene flow be carried out using other markers, including microsatellites.

A spatial genetics approach to inform vector control of tsetse flies (Glossina fuscipes fuscipes) in Northern Uganda

Tsetse flies (genus Glossina) are the only vector for the parasitic trypanosomes responsible for sleeping sickness and nagana across sub-Saharan Africa. In Uganda, the tsetse fly Glossina fuscipes fuscipes is responsible for transmission of the parasite in 90% of sleeping sickness cases, and co-occurrence of both forms of human-infective trypanosomes makes vector control a priority. We use population genetic data from 38 samples from northern Uganda in a novel methodological pipeline that integrates genetic data, remotely sensed environmental data, and hundreds of field-survey observations. This methodological pipeline identifies isolated habitat by first identifying environmental parameters correlated with genetic differentiation, second, predicting spatial connectivity using field-survey observations and the most predictive environmental parameter(s), and third, overlaying the connectivity surface onto a habitat suitability map. Results from this pipeline indicated that net photosynthesis was the strongest predictor of genetic differentiation in G. f. fuscipes in northern Uganda. The resulting connectivity surface identified a large area of well-connected habitat in northwestern Uganda, and twenty-four isolated patches on the northeastern margin of the G. f. fuscipes distribution. We tested this novel methodological pipeline by completing an ad hoc sample and genetic screen of G. f. fuscipes samples from a model-predicted isolated patch, and evaluated whether the ad hoc sample was in fact as genetically isolated as predicted. Results indicated that genetic isolation of the ad hoc sample was as genetically isolated as predicted, with differentiation well above estimates made in samples from within well-connected habitat separated by similar geographic distances. This work has important practical implications for the control of tsetse and other disease vectors, because it provides a way to identify isolated populations where it will be safer and easier to implement vector control and that should be prioritized as study sites during the development and improvement of vector control methods.

Temporal genetic differentiation in Glossina pallidipes tsetse fly populations in Kenya

BACKGROUND

Glossina pallidipes is a major vector of both Human and Animal African Trypanosomiasis (HAT and AAT) in Kenya. The disease imposes economic burden on endemic regions in Kenya, including south-western Kenya, which has undergone intense but unsuccessful tsetse fly control measures. We genotyped 387 G. pallidipes flies at 13 microsatellite markers to evaluate levels of temporal genetic variation in two regions that have been subjected to intensive eradication campaigns from the 1960s to the 1980s. One of the regions, Nguruman Escarpment, has been subject to habitat alteration due to human activities, while the other, Ruma National Park, has not. In addition, Nguruman Escarpment is impacted by the movement of grazing animals into the area from neighboring regions during the drought season. We collected our samples from three geographically close sampling sites for each of the two regions. Samples were collected between the years 2003 and 2015, spanning ~96 tsetse fly generations.

RESULTS

We established that allelic richness averaged 3.49 and 3.63, and temporal Ne estimates averaged 594 in Nguruman Escarpment and 1120 in Ruma National Park. This suggests that genetic diversity is similar to what was found in previous studies of G. pallidipes in Uganda and Kenya, implying that we could not detect a reduction in genetic diversity following the extensive control efforts during the 1960s to the 1980s. However, we did find differences in temporal patterns of genetic variation between the two regions, indicated by clustering analysis, pairwise FST, and Fisher's exact tests for changes in allele and genotype frequencies. In Nguruman Escarpment, findings indicated differentiation among samples collected in different years, and evidence of local genetic bottlenecks in two locations previous to 2003, and between 2009 and 2015. In contrast, there was no consistent evidence of differentiation among samples collected in different years, and no evidence of local genetic bottlenecks in Ruma National Park.

CONCLUSION

Our findings suggest that, despite extensive control measures especially between the 1960s and the 1980s, tsetse flies in these regions persist with levels of genetic diversity similar to that found in populations that did not experience extensive control measures. Our findings also indicate temporal genetic differentiation in Nguruman Escarpment detected at a scale of > 80 generations, and no similar temporal differentiation in Ruma National Park. The different level of temporal differentiation between the two regions indicates that genetic drift is stronger in Nugruman Escarpment, for as-yet unknown reasons, which may include differences in land management. This suggests land management may have an impact on G. pallidipes population genetics, and reinforces the importance of long term monitoring of vector populations in estimates of parameters needed to model and plan effective species-specific control measures.

Genetic diversity and population structure of the tsetse fly Glossina fuscipes fuscipes (Diptera: Glossinidae) in Northern Uganda: Implications for vector control

Uganda is the only country where the chronic and acute forms of human African Trypanosomiasis (HAT) or sleeping sickness both occur and are separated by < 100 km in areas north of Lake Kyoga. In Uganda, Glossina fuscipes fuscipes is the main vector of the Trypanosoma parasites responsible for these diseases as well for the animal African Trypanosomiasis (AAT), or Nagana. We used highly polymorphic microsatellite loci and a mitochondrial DNA (mtDNA) marker to provide fine scale spatial resolution of genetic structure of G. f. fuscipes from 42 sampling sites from the northern region of Uganda where a merger of the two disease belts is feared. Based on microsatellite analyses, we found that G. f. fuscipes in northern Uganda are structured into three distinct genetic clusters with varying degrees of interconnectivity among them. Based on genetic assignment and spatial location, we grouped the sampling sites into four genetic units corresponding to northwestern Uganda in the Albert Nile drainage, northeastern Uganda in the Lake Kyoga drainage, western Uganda in the Victoria Nile drainage, and a transition zone between the two northern genetic clusters characterized by high level of genetic admixture. An analysis using HYBRIDLAB supported a hybrid swarm model as most consistent with tsetse genotypes in these admixed samples. Results of mtDNA analyses revealed the presence of 30 haplotypes representing three main haplogroups, whose location broadly overlaps with the microsatellite defined clusters. Migration analyses based on microsatellites point to moderate migration among the northern units located in the Albert Nile, Achwa River, Okole River, and Lake Kyoga drainages, but not between the northern units and the Victoria Nile drainage in the west. Effective population size estimates were variable with low to moderate sizes in most populations and with evidence of recent population bottlenecks, especially in the northeast unit of the Lake Kyoga drainage. Our microsatellite and mtDNA based analyses indicate that G. f. fuscipes movement along the Achwa and Okole rivers may facilitate northwest expansion of the Rhodesiense disease belt in Uganda. We identified tsetse migration corridors and recommend a rolling carpet approach from south of Lake Kyoga northward to minimize disease dispersal and prevent vector re-colonization. Additionally, our findings highlight the need for continuing tsetse monitoring efforts during and after control.

Northern Uganda is an epidemiologically important region affected by human African trypanosomiasis (HAT) because it harbors both forms of the HAT disease (T. b. gambiense and T. b. rhodesiense). The geographic location of this region creates the risk that these distinct foci could merge, which would complicate diagnosis and treatment, and may result in recombination between the two parasite strains with as yet unknown consequences. Both strains require a tsetse fly vector for transmission, and in Uganda, G. f. fuscipes is the major vector of HAT. Controlling the vector remains one of the most effective strategies for controlling trypanosome parasites. However, vector control efforts may not be sustainable in terms of long term reduction in G. f. fuscipes populations due to population rebounds. Population genetics data can allow us to determine the likely source of population rebounds and to establish a more robust control strategy. In this study, we build on a previous broad spatial survey of G. f. fuscipes genetic structure in Uganda by adding more than 30 novel sampling sites that are strategically spaced across a region of northern Uganda that, for historical and political reasons, was severely understudied and faces particularly high disease risk. We identify natural population breaks, migration corridors and a hybrid zone with evidence of free interbreeding of G. f. fuscipes across the geographic region that spans the two HAT disease foci. We also find evidence of low effective population sizes and population bottlenecks in some areas that have been subjects of past control but remain regions of high tsetse density, which stresses the risk of population rebounds if monitoring is not explicitly incorporated into the control strategy. We use these results to make suggestions that will enhance the design and implementation of control activities in northern Uganda.

High performance computation of landscape genomic models including local indicators of spatial association

With the increasing availability of both molecular and topo-climatic data, the main challenges facing landscape genomics - that is the combination of landscape ecology with population genomics - include processing large numbers of models and distinguishing between selection and demographic processes (e.g. population structure). Several methods address the latter, either by estimating a null model of population history or by simultaneously inferring environmental and demographic effects. Here we present samβada, an approach designed to study signatures of local adaptation, with special emphasis on high performance computing of large-scale genetic and environmental data sets. samβada identifies candidate loci using genotype-environment associations while also incorporating multivariate analyses to assess the effect of many environmental predictor variables. This enables the inclusion of explanatory variables representing population structure into the models to lower the occurrences of spurious genotype-environment associations. In addition, samβada calculates local indicators of spatial association for candidate loci to provide information on whether similar genotypes tend to cluster in space, which constitutes a useful indication of the possible kinship between individuals. To test the usefulness of this approach, we carried out a simulation study and analysed a data set from Ugandan cattle to detect signatures of local adaptation with samβada, bayenv, lfmm and an F_ST outlier method (FDIST approach in arlequin) and compare their results. samβada - an open source software for Windows, Linux and Mac OS X available at http://lasig.epfl.ch/sambada - outperforms other approaches and better suits whole-genome sequence data processing.

Evidence of temporal stability in allelic and mitochondrial haplotype diversity in populations of Glossina fuscipes fuscipes (Diptera: Glossinidae) in northern Uganda

BACKGROUND

Glossina fuscipes fuscipes is a tsetse species of high economic importance in Uganda where it is responsible for transmitting animal African trypanosomiasis (AAT) and both the chronic and acute forms of human African trypanosomiasis (HAT). We used genotype data from 17 microsatellites and a mitochondrial DNA marker to assess temporal changes in gene frequency for samples collected between the periods ranging from 2008 to 2014 in nine localities spanning regions known to harbor the two forms of HAT in northern Uganda.

RESULTS

Our findings suggest that the majority of the studied populations in both HAT foci are genetically stable across the time span sampled. Pairwise estimates of differentiation using standardized FST and Jost's DEST between time points sampled for each site were generally low and ranged between 0.0019 and 0.1312 for both sets of indices. We observed the highest values of FST and DEST between time points sampled from Kitgum (KT), Karuma (KR), Moyo (MY) and Pader (PD), and the possible reasons for this are discussed. Effective population size (Ne) estimates using Waple's temporal method ranged from 103 (95% CI: 73-138) in Kitgum to 962 (95% CI: 669-1309) in Oculoi (OC). Additionally, evidence of a bottleneck event was detected in only one population at one time point sampled; Aminakwach (AM-27) from December 2014 (P < 0.03889).

CONCLUSION

Findings suggest general temporal stability of tsetse vectors in foci of both forms of HAT in northern Uganda. Genetic stability and the moderate effective population sizes imply that a re-emergence of vectors from local residual populations missed by control efforts is an important risk. This underscores the need for more sensitive sampling and monitoring to detect residual populations following control activities.

Mitochondrial DNA sequence divergence and diversity of Glossina fuscipes fuscipes in the Lake Victoria basin of Uganda: implications for control

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.

METHODS

We collected 429 Gff tsetse fly samples from 14 localities in the entire Ugandan portion of the Lake Victoria coast, covering 40,000 km(2). We performed genetic analyses on them and added data collected for 56 Gff individuals from 4 additional sampling sites in the basin. The 529 pb partial mitochondrial DNA cytochrome oxidase II (mtDNA COII) sequences totaling 485 were analysed for genetic differentiation, structuring and demographic history. The results were compared with findings from a previous study based on microsatellite loci data from the basin.

RESULTS

The differences within sampling sites explained a significant proportion of the genetic variation. We found three very closely related mtDNA population clusters, which co-occurred in multiple sites. Although Φ ST (0 - 0.592; P < 0.05) and Bayesian analyses suggest some level of weak genetic differentiation, there is no correlation between genetic divergence and geographic distance (r = 0.109, P = 0.185), and demographic tests provide evidence of locality-based demographic history.

CONCLUSION

The mtDNA data analysed here complement inferences made in a previous study based on microsatellite data. Given the differences in mutation rates, mtDNA afforded a look further back in time than microsatellites and revealed that Gff populations were more connected in the past. Microsatellite data revealed more genetic structuring than mtDNA. The differences in connectedness and structuring over time could be related to vector control efforts. 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 tsetse eradication strategy for sustainable removal of the tsetse and trypanosomiasis problem from this area.

Genetic diversity and population structure of Trypanosoma brucei in Uganda: implications for the epidemiology of sleeping sickness and Nagana

Background

While Human African Trypanosomiasis (HAT) is in decline on the continent of Africa, the disease still remains a major health problem in Uganda. There are recurrent sporadic outbreaks in the traditionally endemic areas in south-east Uganda, and continued spread to new unaffected areas in central Uganda. We evaluated the evolutionary dynamics underpinning the origin of new foci and the impact of host species on parasite genetic diversity in Uganda. We genotyped 269 Trypanosoma brucei isolates collected from different regions in Uganda and southwestern Kenya at 17 microsatellite loci, and checked for the presence of the SRA gene that confers human infectivity to T. b. rhodesiense.

Results

Both Bayesian clustering methods and Discriminant Analysis of Principal Components partition Trypanosoma brucei isolates obtained from Uganda and southwestern Kenya into three distinct genetic clusters. Clusters 1 and 3 include isolates from central and southern Uganda, while cluster 2 contains mostly isolates from southwestern Kenya. These three clusters are not sorted by subspecies designation (T. b. brucei vs T. b. rhodesiense), host or date of collection. The analyses also show evidence of genetic admixture among the three genetic clusters and long-range dispersal, suggesting recent and possibly on-going gene flow between them.

Conclusions

Our results show that the expansion of the disease to the new foci in central Uganda occurred from the northward spread of T. b. rhodesiense (Tbr). They also confirm the emergence of the human infective strains (Tbr) from non-infective T. b. brucei (Tbb) strains of different genetic backgrounds, and the importance of cattle as Tbr reservoir, as confounders that shape the epidemiology of sleeping sickness in the region.

Human African Trypanosomiasis (HAT) is a major health problem in Uganda, as there are recurrent sporadic outbreaks of the disease in traditionally endemic areas in south-east Uganda, and continued spread to new unaffected areas in central Uganda. In this study, we evaluate the evolutionary dynamics underpinning the origin of new disease foci and the impact of host species on parasite genetic diversity in Uganda. We found three distinct genetic clusters of T. brucei in Uganda and southwestern Kenya. Clusters 1 and 3 include isolates from central and southern Uganda, while cluster 2 contains mostly isolates from southwestern Kenya. These three clusters are not sorted by subspecies designation (T. b. brucei vs T. b. rhodesiense), host or date of collection. Our results show expansion of the disease to new foci in central Uganda occurred from the northward spread of T. b. rhodesiense. They also confirm the emergence of the human infective strains from non-infective T. b. brucei strains of different genetic backgrounds, and the importance of cattle as Tbr reservoir, as confounders that shape the epidemiology of sleeping sickness in the region.

Analysis of multiple tsetse fly populations in Uganda reveals limited diversity and species-specific gut microbiota

The invertebrate microbiome contributes to multiple aspects of host physiology, including nutrient supplementation and immune maturation processes. We identified and compared gut microbial abundance and diversity in natural tsetse flies from Uganda using five genetically distinct populations of Glossina fuscipes fuscipes and multiple tsetse species (Glossina morsitans morsitans, G. f. fuscipes, and Glossina pallidipes) that occur in sympatry in one location. We used multiple approaches, including deep sequencing of the V4 hypervariable region of the 16S rRNA gene, 16S rRNA gene clone libraries, and bacterium-specific quantitative PCR (qPCR), to investigate the levels and patterns of gut microbial diversity from a total of 151 individuals. Our results show extremely limited diversity in field flies of different tsetse species. The obligate endosymbiont Wigglesworthia dominated all samples (>99%), but we also observed wide prevalence of low-density Sodalis (tsetse's commensal endosymbiont) infections (<0.05%). There were also several individuals (22%) with high Sodalis density, which also carried coinfections with Serratia. Albeit in low density, we noted differences in microbiota composition among the genetically distinct G. f. fuscipes flies and between different sympatric species. Interestingly, Wigglesworthia density varied in different species (10(4) to 10(6) normalized genomes), with G. f. fuscipes having the highest levels. We describe the factors that may be responsible for the reduced diversity of tsetse's gut microbiota compared to those of other insects. Additionally, we discuss the implications of Wigglesworthia and Sodalis density variations as they relate to trypanosome transmission dynamics and vector competence variations associated with different tsetse species.

Genetic comparison of Glossina tachinoides populations in three river basins of the Upper West Region of Ghana and implications for tsetse control

Tsetse flies are the cyclical vectors of African animal trypanosomosis (AAT) and human African trypanosomosis (HAT). In March 2010, the Government of Ghana initiated a large scale integrated tsetse eradication campaign in the Upper West Region (UWR) (≈18,000 km(2)) under the umbrella of the Pan-African Tsetse and Trypanosomosis Eradication Campaign (PATTEC). We investigated the structuring of Glossina tachinoides populations within and between the three main river basins of the target area in the UWR. Out of a total sample of 884 flies, a sub-sample of 266 was genotyped at nine microsatellite loci. The significance of the different hierarchical levels was tested using Yang's parameters estimated with Weir and Cockerham's method. A significant effect of traps within groups (pooling traps no more than 3 km distant from each other), of groups within river basins and of river basins within the whole target area was observed. Isolation by distance between traps was highly significant. A local density of 0.48-0.61 flies/m(2) was estimated and a dispersal distance that approximated 11 m per generation [CI 9, 17]. No significant sex-biased dispersal was detected. Dispersal distances of G. tachinoides in the UWR were relatively low, possibly as a result of the fragmentation of the habitat and the seasonality of the Kulpawn and Sissili rivers. Moreover, very high fly population densities were observed in the sample sites, which potentially reduces dispersal at constant habitat saturation, because the probability that migrants can established is reduced (density dependent dispersal). However, the observed spatial dispersal was deemed sufficient for a G. tachinoides-cleared area to be reinvaded from neighboring populations in adjacent river basins. These data corroborate results from other population genetics studies in West Africa, which indicate that G. tachinoides populations from different river basins cannot be considered isolated.

Genetically distinct Glossina fuscipes fuscipes populations in the Lake Kyoga region of Uganda and its relevance for human African trypanosomiasis

Tsetse flies (Glossina spp.) are the sole vectors of Trypanosoma brucei—the agent of human (HAT) and animal (AAT) trypanosomiasis. Glossina fuscipes fuscipes (Gff) is the main vector species in Uganda—the only country where the two forms of HAT disease (rhodesiense and gambiense) occur, with gambiense limited to the northwest. Gff populations cluster in three genetically distinct groups in northern, southern, and western Uganda, respectively, with a contact zone present in central Uganda. Understanding the dynamics of this contact zone is epidemiologically important as the merger of the two diseases is a major health concern. We used mitochondrial and microsatellite DNA data from Gff samples in the contact zone to understand its spatial extent and temporal stability. We show that this zone is relatively narrow, extending through central Uganda along major rivers with south to north introgression but displaying no sex-biased dispersal. Lack of obvious vicariant barriers suggests that either environmental conditions or reciprocal competitive exclusion could explain the patterns of genetic differentiation observed. Lack of admixture between northern and southern populations may prevent the sympatry of the two forms of HAT disease, although continued control efforts are needed to prevent the recolonization of tsetse-free regions by neighboring populations.

Glossina fuscipes populations provide insights for human African trypanosomiasis transmission in Uganda

Uganda has both forms of human African trypanosomiasis (HAT): the chronic gambiense disease in the northwest and the acute rhodesiense disease in the south. The recent spread of rhodesiense into central Uganda has raised concerns given the different control strategies the two diseases require. We present knowledge on the population genetics of the major vector species Glossina fuscipes fuscipes in Uganda with a focus on population structure, measures of gene flow between populations, and the occurrence of polyandry. The microbiome composition and diversity is discussed, focusing on their potential role on trypanosome infection outcomes. We discuss the implications of these findings for large-scale tsetse control programs, including suppression or eradication, being undertaken in Uganda, and potential future genetic applications.

Polymorphic microsatellite markers for the tsetse fly Glossina fuscipes fuscipes (Diptera: Glossinidae), a vector of human African trypanosomiasis

Our understanding of Glossina fuscipes fuscipes, a major vector of sleeping sickness, has been severely constrained by a lack of genetic markers for mapping and population genetic studies. Here we present 10 newly developed microsatellite loci for this tsetse species. Heterozygosity levels in Moyo, an Ugandan population, averaged 0.57, with only two loci showing very low heterozygosity. Five loci carried more than six alleles. Together with five recently published microsatellite loci, this brings the number of available microsatellite loci for this species to 15. Their availability will greatly facilitate future studies on the genetics of this important human disease vector.

Wolbachia association with the tsetse fly, Glossina fuscipes fuscipes, reveals high levels of genetic diversity and complex evolutionary dynamics

Background

Wolbachia pipientis, a diverse group of α-proteobacteria, can alter arthropod host reproduction and confer a reproductive advantage to Wolbachia-infected females (cytoplasmic incompatibility (CI)). This advantage can alter host population genetics because Wolbachia-infected females produce more offspring with their own mitochondrial DNA (mtDNA) haplotypes than uninfected females. Thus, these host haplotypes become common or fixed (selective sweep). Although simulations suggest that for a CI-mediated sweep to occur, there must be a transient phase with repeated initial infections of multiple individual hosts by different Wolbachia strains, this has not been observed empirically. Wolbachia has been found in the tsetse fly, Glossina fuscipes fuscipes, but it is not limited to a single host haplotype, suggesting that CI did not impact its population structure. However, host population genetic differentiation could have been generated if multiple Wolbachia strains interacted in some populations. Here, we investigated Wolbachia genetic variation in G. f. fuscipes populations of known host genetic composition in Uganda. We tested for the presence of multiple Wolbachia strains using Multi-Locus Sequence Typing (MLST) and for an association between geographic region and host mtDNA haplotype using Wolbachia DNA sequence from a variable locus, groEL (heat shock protein 60).

Results

MLST demonstrated that some G. f. fuscipes carry Wolbachia strains from two lineages. GroEL revealed high levels of sequence diversity within and between individuals (Haplotype diversity = 0.945). We found Wolbachia associated with 26 host mtDNA haplotypes, an unprecedented result. We observed a geographical association of one Wolbachia lineage with southern host mtDNA haplotypes, but it was non-significant (p = 0.16). Though most Wolbachia-infected host haplotypes were those found in the contact region between host mtDNA groups, this association was non-significant (p = 0.17).

Conclusions

High Wolbachia sequence diversity and the association of Wolbachia with multiple host haplotypes suggest that different Wolbachia strains infected G. f. fuscipes multiple times independently. We suggest that these observations reflect a transient phase in Wolbachia evolution that is influenced by the long gestation and low reproductive output of tsetse. Although G. f. fuscipes is superinfected with Wolbachia, our data does not support that bidirectional CI has influenced host genetic diversity in Uganda.

Priorities for the elimination of sleeping sickness

Sleeping sickness describes two diseases, both fatal if left untreated: (i) Gambian sleeping sickness caused by Trypanosoma brucei gambiense, a chronic disease with average infection lasting around 3 years, and (ii) Rhodesian sleeping sickness caused by T. b. rhodesiense, an acute disease with death occurring within weeks of infection. Control of Gambian sleeping sickness is based on case detection and treatment involving serological screening, followed by diagnostic confirmation and staging. In stage I, patients can remain asymptomatic as trypanosomes multiply in tissues and body fluids; in stage II, trypanosomes cross the blood-brain barrier, enter the central nervous system and, if left untreated, death follows. Staging is crucial as it defines the treatment that is prescribed; for both forms of disease, stage II involves the use of the highly toxic drug melarsoprol or, in the case of Gambian sleeping sickness, the use of complex and very expensive drug regimes. Case detection of T. b. gambiense sleeping sickness is known to be inefficient but could be improved by the identification of parasites using molecular tools that are, as yet, rarely used in the field. Diagnostics are not such a problem in relation to T. b. rhodesiense sleeping sickness, but the high level of under-reporting of this disease suggests that current strategies, reliant on self-reporting, are inefficient. Sleeping sickness is one of the 'neglected tropical diseases' that attracts little attention from donors or policymakers. Proper quantification of the burden of sleeping sickness matters, as the primary reason for its 'neglect' is that the true impact of the disease is unknown, largely as a result of under-reporting. Certainly, elimination will not be achieved without vast improvements in field diagnostics for both forms of sleeping sickness especially if there is a hidden reservoir of 'chronic carriers'. Mass screening would be a desirable aim for Gambian sleeping sickness and could be handled on a national scale in the endemic countries - perhaps by piggybacking on programmes committed to other diseases. As well as improved diagnostics, the search for non-toxic drugs for stage II treatment should remain a research priority. There is good evidence that thorough active case finding is sufficient to control T. b. gambiense sleeping sickness, as there is no significant animal reservoir. Trypanosoma brucei rhodesiense sleeping sickness is a zoonosis and control involves interrupting the fly-animal-human cycle, so some form of tsetse control and chemotherapy of the animal reservoir must be involved. The restricted application of insecticide to cattle is the most promising, affordable and sustainable technique to have emerged for tsetse control. Animal health providers can aid disease control by treating cattle and, when allied with innovative methods of funding (e.g. public-private partnerships) not reliant on the public purse, this approach may prove more sustainable. Sleeping sickness incidence for the 36 endemic countries has shown a steady decline in recent years and we should take advantage of the apparent lull in incidence and aim for elimination. This is feasible in some sleeping sickness foci but must be planned and paid for increasingly by the endemic countries themselves. The control and elimination of T. b. gambiense sleeping sickness may be seen as a public good, as appropriate strategies depend on local health services for surveillance and treatment, but public-private funding mechanisms should not be excluded. It is timely to take up the tools available and invest in new tools - including novel financial instruments - to eliminate this disease from Africa.

The population structure of Glossina fuscipes fuscipes in the Lake Victoria basin in Uganda: implications for vector control

Background

Glossina fuscipes fuscipes is the primary vector of trypanosomiasis in humans and livestock in Uganda. The Lake Victoria basin has been targeted for tsetse eradication using a rolling carpet initiative, from west to east, with four operational blocks (3 in Uganda and 1 in Kenya), under a Pan-African Tsetse and Trypanosomiasis Eradication Campaign (PATTEC). We screened tsetse flies from the three Ugandan PATTEC blocks for genetic diversity at 15 microsatellite loci from continental and offshore populations to provide empirical data to support this initiative.

Methods

We collected tsetse samples from 11 sites across the Lake Victoria basin in Uganda. We performed genetic analyses on 409 of the collected tsetse flies and added data collected for 278 individuals in a previous study. The flies were screened across 15 microsatellite loci and the resulting data were used to assess the temporal stability of populations, to analyze patterns of genetic exchange and structuring, to estimate dispersal rates and evaluate the sex bias in dispersal, as well as to estimate demographic parameters (N_E and N_C).

Results

We found that tsetse populations in this region were stable over 4-16 generations and belong to 4 genetic clusters. Two genetic clusters (1 and 2) corresponded approximately to PATTEC blocks 1 and 2, while the other two (3 and 4) fell within PATTEC block 3. Island populations grouped into the same genetic clusters as neighboring mainland sites, suggesting presence of gene flow between these sites. There was no evidence of the stretch of water separating islands from the mainland forming a significant barrier to dispersal. Dispersal rates ranged from 2.5 km per generation in cluster 1 to 14 km per generation in clusters 3 and 4. We found evidence of male-biased dispersal. Few breeders are successfully dispersing over large distances. Effective population size estimates were low (33–310 individuals), while census size estimates ranged from 1200 (cluster 1) to 4100 (clusters 3 and 4). We present here a novel technique that adapts an existing census size estimation method to sampling without replacement, the scheme used in sampling tsetse flies.

Conclusion

Our study suggests that different control strategies should be implemented for the three PATTEC blocks and that, given the high potential for re-invasion from island sites, mainland and offshore sites in each block should be targeted at the same time.

Implications of microfauna-host interactions for trypanosome transmission dynamics in Glossina fuscipes fuscipes in Uganda

Tsetse flies (Diptera: Glossinidae) are vectors for African trypanosomes (Euglenozoa: kinetoplastida), protozoan parasites that cause African trypanosomiasis in humans (HAT) and nagana in livestock. In addition to trypanosomes, two symbiotic bacteria (Wigglesworthia glossinidia and Sodalis glossinidius) and two parasitic microbes, Wolbachia and a salivary gland hypertrophy virus (SGHV), have been described in tsetse. Here we determined the prevalence of and coinfection dynamics between Wolbachia, trypanosomes, and SGHV in Glossina fuscipes fuscipes in Uganda over a large geographical scale spanning the range of host genetic and spatial diversity. Using a multivariate analysis approach, we uncovered complex coinfection dynamics between the pathogens and statistically significant associations between host genetic groups and pathogen prevalence. It is important to note that these coinfection dynamics and associations with the host were not apparent by univariate analysis. These associations between host genotype and pathogen are particularly evident for Wolbachia and SGHV where host groups are inversely correlated for Wolbachia and SGHV prevalence. On the other hand, trypanosome infection prevalence is more complex and covaries with the presence of the other two pathogens, highlighting the importance of examining multiple pathogens simultaneously before making generalizations about infection and spatial patterns. It is imperative to note that these novel findings would have been missed if we had employed the standard univariate analysis used in previous studies. Our results are discussed in the context of disease epidemiology and vector control.

Influence of host phylogeographic patterns and incomplete lineage sorting on within-species genetic variability in Wigglesworthia species, obligate symbionts of tsetse flies

Vertical transmission of obligate symbionts generates a predictable evolutionary history of symbionts that reflects that of their hosts. In insects, evolutionary associations between symbionts and their hosts have been investigated primarily among species, leaving population-level processes largely unknown. In this study, we investigated the tsetse (Diptera: Glossinidae) bacterial symbiont, Wigglesworthia glossinidia, to determine whether observed codiversification of symbiont and tsetse host species extends to a single host species (Glossina fuscipes fuscipes) in Uganda. To explore symbiont genetic variation in G. f. fuscipes populations, we screened two variable loci (lon and lepA) from the Wigglesworthia glossinidia bacterium in the host species Glossina fuscipes fuscipes (W. g. fuscipes) and examined phylogeographic and demographic characteristics in multiple host populations. Symbiont genetic variation was apparent within and among populations. We identified two distinct symbiont lineages, in northern and southern Uganda. Incongruence length difference (ILD) tests indicated that the two lineages corresponded exactly to northern and southern G. f. fuscipes mitochondrial DNA (mtDNA) haplogroups (P = 1.0). Analysis of molecular variance (AMOVA) confirmed that most variation was partitioned between the northern and southern lineages defined by host mtDNA (85.44%). However, ILD tests rejected finer-scale congruence within the northern and southern populations (P = 0.009). This incongruence was potentially due to incomplete lineage sorting that resulted in novel combinations of symbiont genetic variants and host background. Identifying these novel combinations may have public health significance, since tsetse is the sole vector of sleeping sickness and Wigglesworthia is known to influence host vector competence. Thus, understanding the adaptive value of these host-symbiont combinations may afford opportunities to develop vector control methods.

Cryptic diversity within the major trypanosomiasis vector Glossina fuscipes revealed by molecular markers

BACKGROUND

The tsetse fly Glossina fuscipes s.l. is responsible for the transmission of approximately 90% of cases of human African trypanosomiasis (HAT) or sleeping sickness. Three G. fuscipes subspecies have been described, primarily based upon subtle differences in the morphology of their genitalia. Here we describe a study conducted across the range of this important vector to determine whether molecular evidence generated from nuclear DNA (microsatellites and gene sequence information), mitochondrial DNA and symbiont DNA support the existence of these taxa as discrete taxonomic units.

PRINCIPAL FINDINGS

The nuclear ribosomal Internal transcribed spacer 1 (ITS1) provided support for the three subspecies. However nuclear and mitochondrial sequence data did not support the monophyly of the morphological subspecies G. f. fuscipes or G. f. quanzensis. Instead, the most strongly supported monophyletic group was comprised of flies sampled from Ethiopia. Maternally inherited loci (mtDNA and symbiont) also suggested monophyly of a group from Lake Victoria basin and Tanzania, but this group was not supported by nuclear loci, suggesting different histories of these markers. Microsatellite data confirmed strong structuring across the range of G. fuscipes s.l., and was useful for deriving the interrelationship of closely related populations.

CONCLUSION/SIGNIFICANCE

We propose that the morphological classification alone is not used to classify populations of G. fuscipes for control purposes. The Ethiopian population, which is scheduled to be the target of a sterile insect release (SIT) programme, was notably discrete. From a programmatic perspective this may be both positive, given that it may reflect limited migration into the area or negative if the high levels of differentiation are also reflected in reproductive isolation between this population and the flies to be used in the release programme.

Polyandry is a common event in wild populations of the Tsetse fly Glossina fuscipes fuscipes and may impact population reduction measures

BACKGROUND

Glossina fuscipes fuscipes is the main vector of human and animal trypanosomiasis in Africa, particularly in Uganda. Attempts to control/eradicate this species using biological methods require knowledge of its reproductive biology. An important aspect is the number of times a female mates in the wild as this influences the effective population size and may constitute a critical factor in determining the success of control methods. To date, polyandry in G.f. fuscipes has not been investigated in the laboratory or in the wild. Interest in assessing the presence of remating in Ugandan populations is driven by the fact that eradication of this species is at the planning stage in this country.

METHODOLOGY/PRINCIPAL FINDINGS

Two well established populations, Kabukanga in the West and Buvuma Island in Lake Victoria, were sampled to assess the presence and frequency of female remating. Six informative microsatellite loci were used to estimate the number of matings per female by genotyping sperm preserved in the female spermathecae. The direct count of the minimum number of males that transferred sperm to the spermathecae was compared to Maximum Likelihood and Bayesian probability estimates. The three estimates provided evidence that remating is common in the populations but the frequency is substantially different: 57% in Kabukanga and 33% in Buvuma.

CONCLUSIONS/SIGNIFICANCE

The presence of remating, with females maintaining sperm from different mates, may constitute a critical factor in cases of re-infestation of cleared areas and/or of residual populations. Remating may enhance the reproductive potential of re-invading propagules in terms of their effective population size. We suggest that population age structure may influence remating frequency. Considering the seasonal demographic changes that this fly undergoes during the dry and wet seasons, control programmes based on SIT should release large numbers of sterile males, even in residual surviving target populations, in the dry season.

Temporal stability of Glossina fuscipes fuscipes populations in Uganda

BACKGROUND

Glossina fuscipes, a riverine species of tsetse, is the major vector of human African trypanosomiasis (HAT) in sub-Saharan Africa. Understanding the population dynamics, and specifically the temporal stability, of G. fuscipes will be important for informing vector control activities. We evaluated genetic changes over time in seven populations of the subspecies G. f. fuscipes distributed across southeastern Uganda, including a zone of contact between two historically isolated lineages. A total of 667 tsetse flies were genotyped at 16 microsatellite loci and at one mitochondrial locus.

RESULTS

Results of an AMOVA indicated that time of sampling did not explain a significant proportion of the variance in allele frequencies observed across all samples. Estimates of differentiation between samples from a single population ranged from approximately 0 to 0.019, using Jost's DEST. Effective population size estimates using momentum-based and likelihood methods were generally large. We observed significant change in mitochondrial haplotype frequencies in just one population, located along the zone of contact. The change in haplotypes was not accompanied by changes in microsatellite frequencies, raising the possibility of asymmetric mating compatibility in this zone.

CONCLUSION

Our results suggest that populations of G. f. fuscipes were stable over the 8-12 generations studied. Future studies should aim to reconcile these data with observed seasonal fluctuations in the apparent density of tsetse.

Phylogeography and population structure of Glossina fuscipes fuscipes in Uganda: implications for control of tsetse

Background

Glossina fuscipes fuscipes, a riverine species of tsetse, is the main vector of both human and animal trypanosomiasis in Uganda. Successful implementation of vector control will require establishing an appropriate geographical scale for these activities. Population genetics can help to resolve this issue by characterizing the extent of linkage among apparently isolated groups of tsetse.

Methodology/Principal Findings

We conducted genetic analyses on mitochondrial and microsatellite data accumulated from approximately 1000 individual tsetse captured in Uganda and neighboring regions of Kenya and Sudan. Phylogeographic analyses suggested that the largest scale genetic structure in G. f. fuscipes arose from an historical event that divided two divergent mitochondrial lineages. These lineages are currently partitioned to northern and southern Uganda and co-occur only in a narrow zone of contact extending across central Uganda. Bayesian assignment tests, which provided evidence for admixture between northern and southern flies at the zone of contact and evidence for northerly gene flow across the zone of contact, indicated that this structure may be impermanent. On the other hand, microsatellite structure within the southern lineage indicated that gene flow is currently limited between populations in western and southeastern Uganda. Within regions, the average F_ST between populations separated by less than 100 km was less than ∼0.1. Significant tests of isolation by distance suggested that gene flow is ongoing between neighboring populations and that island populations are not uniformly more isolated than mainland populations.

Conclusions/Significance

Despite the presence of population structure arising from historical colonization events, our results have revealed strong signals of current gene flow within regions that should be accounted for when planning tsetse control in Uganda. Populations in southeastern Uganda appeared to receive little gene flow from populations in western or northern Uganda, supporting the feasibility of area wide control in the Lake Victoria region by the Pan African Tsetse and Trypanosomiasis Eradication Campaign.

Glossina fuscipes fuscipes is the most common species of tsetse in Uganda, where it transmits human sleeping sickness and nagana, a related disease of cattle. A consortium of African countries dedicated to controlling these diseases is poised to begin area wide control of tsetse, but a critical question remains: What is the most appropriate geographical scale for these activities? To address this question, we used population genetics to determine the extent of linkage between populations of tsetse confined to discrete patches of riverine habitat. Our results suggest that Uganda was colonized by two distinct lineages of G. f. fuscipes, which now co-occur only in a narrow band across central Uganda. Evidence for interbreeding at the zone of contact and movement of genes from the south to the north suggest that this historical genetic structure may dissolve in the future. At smaller scales, we have demonstrated that exchange of genes among neighboring populations via dispersal is at equilibrium with the differentiating force of genetic drift. Our results highlight the need for investment in vector control programs that account for the linkage observed among tsetse populations. Given its genetic isolation and its location at the far edge of G. fuscipes' range, the Lake Victoria region appears to be an appropriate target for area wide control.

MultiTest V.1.2, a program to binomially combine independent tests and performance comparison with other related methods on proportional data

Background

Combining multiple independent tests, when all test the same hypothesis and in the same direction, has been the subject of several approaches. Besides the inappropriate (in this case) Bonferroni procedure, the Fisher's method has been widely used, in particular in population genetics. This last method has nevertheless been challenged by the SGM (symmetry around the geometric mean) and Stouffer's Z-transformed methods that are less sensitive to asymmetry and deviations from uniformity of the distribution of the partial P-values. Performances of these different procedures were never compared on proportional data such as those currently used in population genetics.

Results

We present new software that implements a more recent method, the generalised binomial procedure, which tests for the deviation of the observed proportion of P-values lying under a chosen threshold from the expected proportion of such P-values under the null hypothesis. The respective performances of all available procedures were evaluated using simulated data under the null hypothesis with standard P-values distribution (differentiation tests). All procedures more or less behaved consistently with ~5% significant tests at α = 0.05. Then, linkage disequilibrium tests with increasing signal strength (rate of clonal reproduction), known to generate highly non-standard P-value distributions are undertaken and finally real population genetics data are analysed. In these cases, all procedures appear, more or less equally, very conservative, though SGM seems slightly more conservative.

Conclusion

Based on our results and those discussed in the literature we conclude that the generalised binomial and Stouffer's Z procedures should be preferred and Z when the number of tests is very small. The more conservative SGM might still be appropriate for meta-analyses when a strong publication bias in favour of significant results is expected to inflate type 2 error.

Evidence for a discrete evolutionary lineage within Equatorial Guinea suggests that the tsetse fly Glossina palpalis palpalis exists as a species complex

Tsetse flies of the palpalis group are major vectors of Human African Trypanosomiasis in Africa. Accurate knowledge of species identity is essential for vector control. Here, we combine ribosomal internal transcribed spacer 1 (ITS1), mitochondrial Cytochrome Oxidase 1 (COI) and microsatellites to determine the population structure and phylogenetic relations of Glossina p. palpalis in Equatorial Guinea. CO1 sequence data suggest that G. p. palpalis in Equatorial Guinea is a distinct subspecies from previously described G. p. palpalis in West Africa and Democratic Republic of Congo. Glossina p. palpalis in Equatorial Guinea and DRC share a common ancestor which diverged from West African G. p. palpalis around 1.9 Ma. Previous ITS1 length polymorphism data suggested the possible presence of hybrids in Equatorial Guinea. However, ITS1 showed incomplete lineage sorting compared with clearly defined COI groups, and data from 12 unlinked microsatellites provided no evidence of hybridization. Microsatellite data indicated moderate but significant differentiation between the populations analysed (Rio Campo, Mbini and Kogo). Moreover, unlike previous studies of G. p. palpalis, there was no evidence for heterozygote deficiency, presence of migrants or cryptic population structure. Variance effective population size at Rio Campo was estimated at 501-731 assuming eight generations per year. This study of the population genetics of G. p. palpalis in central Africa provides the first estimate of genetic differentiation between geographically separated G. p. palpalis populations.

Tsetse flies: genetics, evolution, and role as vectors

Tsetse flies (Diptera: Glossinidae) are an ancient taxon of one genus, Glossina, and limited species diversity. All are exclusively haematophagous and confined to sub-Saharan Africa. The Glossina are the principal vectors of African trypanosomes Trypanosoma sp. (Kinetoplastida: Trypanosomatidae) and as such, are of great medical and economic importance. Clearly tsetse flies and trypanosomes are coadapted and evolutionary interactions between them are manifest. Numerous clonally reproducing strains of Trypanosoma sp. exist and their genetic diversities and spatial distributions are inadequately known. Here I review the breeding structures of the principle trypanosome vectors, G. morsitans s.l., G. pallidipes, G. palpalis s.l. and G. fuscipes fuscipes. All show highly structured populations among which there is surprisingly little detectable gene flow. Rather less is known of the breeding structure of T. brucei sensu lato vis à vis their vector tsetse flies but many genetically differentiated strains exist in nature. Genetic recombination in Trypanosoma via meiosis has recently been demonstrated in the laboratory thereby furnishing a mechanism of strain differentiation in addition to that of simple mutation. Spatially and genetically representative sampling of both trypanosome species and strains and their Glossina vectors is a major barrier to a comprehensive understanding of their mutual relationships.