Null alleles and Wahlund effects are well known causes of heterozygote deficits in empirical population genetics studies as compared to Hardy-Weinberg genotypic expectations. Some authors have theoretically studied the relationship of Wright's FIS computed from subsamples displaying a Wahlund effect and FST before the Wahlund effect, as can occasionally be obtained from populations of long-lived organisms. In the 2 subsample case, a positive relationship between these 2 parameters across loci would represent a signature of Wahlund effects. Nevertheless, for most organisms, getting 2 independent subsamples of the same cohort and population, one with a Wahlund effect and the other without, is almost never achieved and most of the time, empirical population geneticists only collect a single sample, with or without a Wahlund effect, or with or without null alleles. Another issue is that null allele increase FIS and FST altogether and thus may also create such correlation. In this article, I show that, for organisms collected in a single sample, which corresponds to the most common situation, Wahlund effects and null alleles affect the values of both FIS and FST though in the opposite direction. I also show that Wahlund effect produces no or weak positive correlation between the 2 F-statistics, while null alleles generate a strong positive correlation between them. Variation of these F-statistics is small and even minimized for FST under Wahlund effects as compared to null alleles. I finally propose a determination key to interpret data with heterozygote deficits.

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Revisiting FIS, FST, Wahlund Effects, and Null Alleles.

Studying isolation by distance can provide useful demographic information. To analyze isolation by distance from molecular data, one can use some kind of genetic distance or coalescent simulations. Molecular markers can often display technical caveats, such as PCR-based amplification failures (null alleles, allelic dropouts). These problems can alter population parameter inferences that can be extracted from molecular data. In this simulation study, we analyze the behavior of different genetic distances in Island (null hypothesis) and stepping stone models displaying varying neighborhood sizes. Impact of null alleles of increasing frequency is also studied. In stepping stone models without null alleles, the best statistic to detect isolation by distance in most situations is the chord distance DCSE. Nevertheless, for markers with genetic diversities HS<0.4-0.5, all statistics tend to display the same statistical power. Marginal sub-populations behave as smaller neighborhoods. Metapopulations composed of small sub-population numbers thus display smaller neighborhood sizes. When null alleles are introduced, the power of detection of isolation by distance is significantly reduced and DCSE remains the most powerful genetic distance. We also show that the proportion of null allelic states interact with the slope of the regression of FST/(1-FST) as a function of geographic distance. This can have important consequences on inferences that can be made from such data. Nevertheless, Chapuis and Estoup's FreeNA correction for null alleles provides very good results in most situations. We finally use our conclusions for reanalyzing and reinterpreting some published data sets.

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Comparison of different genetic distances to test isolation by distance between populations.

Theileriosis, caused by Theileria parva, is an economically important disease in Africa. It is a major constraint to the development of the livestock industry in some parts of eastern, central and southern Africa. In Zambia, theileriosis causes losses of up to 10,000 cattle annually. Cattle blood samples were collected for genetic analysis of Theileria parva from Isoka and Petauke districts in Zambia. Microsatellite analysis was then performed on all Theileria parva positive samples for PCR using a panel of 9 microsatellite markers. Microsatellite data was analyzed using microsatellite toolkit, GenAlEx ver. 6, Fstat ver. 2.9.3.2, and LIAN computer softwares. The combined percentage of positive samples in both districts determined by PCR using the p104 gene primers was 54.9% (95% CI: 46.7 – 63.1%, 78/142), while in each district, it was 44.8% (95% CI: 34.8 – 54.8%) and 76.1% (95% CI = 63.9 – 88.4%) for Isoka and Petauke districts, respectively. We analyzed the population genetic structure of Theileria parva from a total of 61 samples (33 from Isoka and 28 from Petauke) using a panel of 9 microsatellite markers encompassing the 4 chromosomes of Theileria parva. Wright’s F index (FST = 0.178) showed significant differentiation between the Isoka and Petauke populations. Linkage disequilibrium was observed when populations from both districts were treated as a single population. When analyzed separately, linkage disequilibrium was observed in Kanyelele and Kalembe areas in Isoka district, Isoka district overall and in Petauke district. Petauke district had a higher multiplicity of infection than Isoka district. Population genetic analyses of Theileria parva from Isoka and Petauke districts showed a low level of genotype exchange between the districts, but a high level of genetic diversity within each district population, implying genetic and geographic sub-structuring between the districts. The sub-structuring observed, along with the lack of panmixia in the populations, could have been due to low transmission levels at the time of sampling. However, the Isoka population was less diverse than the Petauke population.

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Population genetic analysis and sub-structuring of Theileria parva in the northern and eastern parts of Zambia

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. 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 (NE and NC). 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. 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.

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

Background: Human African Trypanosomiasis (HAT) remains a public health problem in many poor countries. Due to lack of financial resources in these countries, cost-effective strategies are needed for efficient control of this scourge, especially the tsetse vector. It was shown that perennial water sources maintain a favourable biotope for tsetse flies and thus the transmission dynamics of sleeping sickness. The present paper aimed at assessing the transmission dynamics of HAT in a forest environment where the hydrographic network is important. Methods: Two entomological surveys were carried out in July 2009 and March 2010 in the Bipindi sleeping sickness focus of the South Region of Cameroon. Entomological and parasitological data were collected during both trapping periods (including the climate variations throughout a year) and compared to each other. The level of risk for transmission of the disease during each trapping period was also evaluated at the trap level and materialised on the map of the Bipindi focus. Results: Glossina palpalis palpalis was the most prevalent tsetse fly species captured in this focus. The overall densities of tsetse flies as well as the risk for transmission of HAT in the Bipindi focus were significantly higher in July than in March. At the trap level, we observed that these parameters were almost constant, whatever the trapping period, when the biotope included perennial water sources. Conclusions: This study shows that the spatial distribution of traps, as well as the temporal climatic variations might influence entomological and parasitological parameters of HAT and that the presence of perennial water sources in biotopes would favour the development of tsetse flies and thus the transmission of sleeping sickness. These factors should, therefore, be taken into account in order to provide more efficient vector control.

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Spatial and temporal variations relevant to tsetse control in the Bipindi focus of southern Cameroon

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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Gustave Simo

Papers

Population genetics of Glossina palpalis palpalis from central African sleeping sickness foci