Population genomics of Corsican wildcats: Paving the way toward a new subspecies within the Felis silvestris spp. complex?

In the context of the current extinction crisis, identifying new conservation units is pivotal to the development of sound conservation measures, especially in highly threatened taxa such as felids. Corsican wildcats are known by Corsican people since a very long time but have been little studied. Meaningful information about their phylogenetic position is lacking. We used ddRADseq to genotype phenotypically homogenous Corsican wildcats at 3671 genome-wide SNPs and reported for the first time their genetic identity. We compared this genomic information to domestic cats Felis silvestris catus from Corsica and mainland France, European wildcats F. s. silvestris and Sardinian wildcats F. s. lybica. Our premise was that if the Corsican wildcat, as a phenotypic entity, also represents a genetic entity, it deserves conservation measures and to be recognized as a conservation unit. Corsican wildcats appeared highly genetically differentiated from European wildcats and genetically closer to Sardinian wildcats than to domestic cats. Domestic cats from Corsica and mainland France were closer to each other and Sardinian wildcats were intermediate between Corsican wildcats and domestic cats. This suggested that Corsican wildcats do not belong to the F. s. silvestris or catus lineages. The inclusion of more high-quality Sardinian samples and Near-Eastern mainland F. s. lybica would constitute the next step toward assessing the status of Corsican wildcat as a subspecies and/or evolutionarily significant unit and tracing back wildcat introduction history of in Corsica.

Breaking down population density into different components to better understand its spatial variation.

BACKGROUND: Population size and densities are key parameters in both fundamental and applied ecology, as they affect population resilience to density-dependent processes, habitat changes and stochastic events. Efficient management measures or species conservation programs thus require accurate estimates of local population densities across time and space, especially for continuously distributed species. For social species living in groups, population density depends on different components, namely the number of groups and the group size, for which relative variations in space may originate from different environmental factors. Whether resulting spatial variations in density are mostly triggered by one component or the other remains poorly known. Here, we aimed at determining the magnitude of the spatial variation in population densities of a social, group-living species, i.e. the European badger Meles meles, in 13 different sites of around 50 km2 across France, to decipher whether sett density, group size or proportion of occupied sett variation is the main factor explaining density variation. Besides the intrinsic factors of density variation, we also assessed whether habitat characteristics such as habitat fragmentation, urbanisation, and resource availability, drove both the spatial variation of density components and local population densities. RESULTS: We proposed a new standardised approach combining use of multiple methods, namely distance sampling for estimating the density of occupied sett clusters, i.e. group density, and camera and hair trapping for genetic identification to determine the mean social group size. The density of adult badgers was on average 3.8 per km2 (range 1.7-7.9 per km2) and was positively correlated with the density of sett clusters. The density of adult badgers per site was less related to the social group size or to the proportion of occupied sett clusters. Landscape fragmentation also explained the spatial variation of adult badger density, with highly fragmented landscapes supporting lower adult densities. Density components were linked differently to environmental variables. CONCLUSIONS: These results underline the need to break down population density estimates into several components in group-living species to better understand the pattern of temporal and spatial variation in population density, as different components may vary due to different ecological factors.

Spatial variance-mass allometry of population density in felids from camera-trapping studies worldwide.

Power laws are cornerstone relationships in ecology and evolutionary biology. The density-mass allometry (DMA), which predicts an allometric scaling of population abundance, and Taylor's law (TL), which predicts a decrease in the population abundance variation along with a decrease in population density, have enhanced our knowledge of inter- and intra-specific variation in population abundance. When combined, these two power laws led to the variance-mass allometry (VMA), which states that larger species have lower spatial variation in population density than smaller species. The VMA has been predicted through theoretical models, however few studies have investigated if this law is also supported by empirical data. Here, to formally test the VMA, we have used the population density estimates obtained through worldwide camera trapping studies for an emblematic and ecologically important carnivorous taxa, the Felidae family. Our results showed that the VMA law hold in felids, as well as the TL and the DMA laws; bigger cat species showed less variation for the population density than smaller species. These results have important implications for the conservation of wildlife population and confirm the validity of important ecological concepts, like the allometric scaling of population growth rate and the slow-fast continuum of life history strategies.

Altitude shapes the environmental drivers of large-scale variation in abundance of a widespread mammal species.

AIM: Habitat quality and heterogeneity directly influence the distribution and abundance of organisms at different spatial scales. Determining the main environmental factors driving the variation in species abundance is crucial to understand the underlying ecological processes, and this is especially important for widely distributed species living in contrasting environments. However, the responses to environmental variation are usually described at relatively small spatial scales. Here, we studied the variation in abundance of a widely distributed mustelid, the European badger (Meles meles), across France. LOCATION: The whole metropolitan France. METHODS: We used (a) direct detections of 9,439 dead and living badgers, from 2006 to 2009, to estimate badger relative abundance in 703 small agricultural regions of metropolitan France and (b) a Bayesian modeling approach to identify the main environmental determinants influencing badger abundance. RESULTS: Despite a continuous distribution of badger in France, we found large variation in badger abundance between regions, explained by environmental factors. Among a set of 13 environmental variables, we demonstrated that badger abundance in lowlands (<400 m a.s.l.) was mostly driven by biotic factors such as potential food resources (earthworm abundance and fruit crops) and forest fragmentation. Conversely, in mountainous areas, abiotic factors (i.e., soil texture and climate) drove the variation in badger relative abundance. MAIN CONCLUSIONS: These results underline the importance of mapping the abundance of wildlife species based on environmental suitability and highlight the complexity of drivers influencing species abundance at such large spatial scales. Altitude shaped the environmental drivers (biotic vs. abiotic) that most influenced relative abundance of a widespread species. In the case of badger, such abundance maps are crucial to identify critical areas for species management as this mustelid is a main wild vector of bovine tuberculosis in several countries.

Does host socio-spatial behavior lead to a fine-scale spatial genetic structure in its associated parasites?

Gastro-intestinal nematodes, especially Haemonchus contortus, are widespread pathogenic parasites of small ruminants. Studying their spatial genetic structure is as important as studying host genetic structure to fully understand host-parasite interactions and transmission patterns. For parasites having a simple life cycle (e.g., monoxenous parasites), gene flow and spatial genetic structure are expected to strongly rely on the socio-spatial behavior of their hosts. Based on five microsatellite loci, we tested this hypothesis for H. contortus sampled in a wild Mediterranean mouflon population (Ovis gmelini musimon × Ovis sp.) in which species- and environment-related characteristics have been found to generate socio-spatial units. We nevertheless found that their parasites had no spatial genetic structure, suggesting that mouflon behavior was not enough to limit parasite dispersal in this study area and/or that other ecological and biological factors were involved in this process, for example other hosts, the parasite life cycle, or the study area history.

TITLE: Le comportement socio-spatial de l'hôte conduit-il à une structure génétique à fine échelle de ses parasites ? ABSTRACT: Les nématodes gastro-intestinaux, et plus particulièrement Haemonchus contortus, sont cosmopolites et pathogènes chez les petits ruminants. Étudier leur structure génétique spatiale est aussi important que d'étudier celle des hôtes pour pleinement comprendre les interactions hôtes-parasites et les processus de transmission. Pour les parasites ayant des cycles de vie simples (par exemple, les parasites monoxènes), on s'attend à ce que les flux de gènes et la structure génétique spatiale dépendent fortement du comportement socio-spatial de leurs hôtes. En utilisant cinq loci microsatellites, nous avons testé cette hypothèse pour des H. contortus échantillonnés dans une population sauvage de mouflons méditerranéens (Ovis gmelini musimon × Ovis sp.) dans laquelle les caractéristiques de l'espèce et de l'environnement génèrent des unités socio-spatiales. Nous avons néanmoins mis en évidence que leurs parasites ne présentent pas de structure génétique spatiale, ce qui suggère que le comportement des mouflons ne restreint pas la dispersion des parasites dans cette aire d'étude et/ou que d'autres facteurs biologiques et écologiques tels que d'autres hôtes, le cycle de vie du parasite, ou l'histoire de l'aire d'étude jouent un rôle dans ce processus.

Quantifying the contribution of immigration to population dynamics: a review of methods, evidence and perspectives in birds and mammals.

The demography of a population is often reduced to the apparent (or local) survival of individuals and their realised fecundity within a study area defined according to logistical constraints rather than landscape features. Such demographics are then used to infer whether a local population contributes positively to population dynamics across a wider landscape context. Such a simplistic approach ignores a fundamental process underpinning population dynamics: dispersal. Indeed, it has long been accepted that immigration contributed by dispersers that emigrated from neighbouring populations may strongly influence the net growth of a local population. To date however, we lack a clear picture of how widely immigration rate varies both among and within populations, in relation to extrinsic and intrinsic ecological conditions, even for the best-studied avian and mammalian populations. This empirical knowledge gap precludes the emergence of a sound conceptual framework that ought to inform conservation and population ecology. This review, conducted on both birds and mammals, has thus three complementary objectives. First, we describe and evaluate the relative merits of methods used to quantify immigration and how they relate to widely applicable metrics. We identify two simple and unifying metrics to measure immigration: the immigration rate it defined as the ratio of the number of immigrants present in the population at time t + 1 and the total breeding population in year t, and πt , the proportion of immigrants among new recruits (i.e. new breeders). Two recently developed methods are likely to provide the most valuable data on immigration in the near future: individual parentage (rather than population) assignments based on genetic sampling, and spatially explicit integrated population models combining multiple sources of demographic data (survival, fecundity and population counts). Second, we report on a systematic literature review of studies providing a quantitative measure of immigration. Although the diversity of methods employed precludes detailed analyses, it appears that the number of immigrants exceeds locally born individuals in recruitment for most avian populations (median πt  = 0.57, N = 45 estimates from 37 studies), a figure twofold higher than estimated for mammalian populations (median πt  = 0.26, N = 33 estimates from 11 studies). Third, recent quantitative studies reveal that immigration can be the main driver of temporal variation in population growth rates, across a wide array of demographic and spatial contexts. To what extent immigration acts as a regulatory process has however been considered only rarely to date and deserves more attention. Overall, it is likely that most populations benefit from immigrants without necessarily being sink populations. Furthermore, we suggest that quantitative estimates of immigration should be core to future demographic studies and plead for more empirical evidence about the ways in which immigration interacts with local demographic processes to shape population dynamics. Finally, we discuss how to tackle spatial population dynamics by exploring, beyond the classical source-sink framework, the extent to which populations exchange individuals according to spatial scale and type of population distribution throughout the landscape.

Data gaps and opportunities for comparative and conservation biology.

Biodiversity loss is a major challenge. Over the past century, the average rate of vertebrate extinction has been about 100-fold higher than the estimated background rate and population declines continue to increase globally. Birth and death rates determine the pace of population increase or decline, thus driving the expansion or extinction of a species. Design of species conservation policies hence depends on demographic data (e.g., for extinction risk assessments or estimation of harvesting quotas). However, an overview of the accessible data, even for better known taxa, is lacking. Here, we present the Demographic Species Knowledge Index, which classifies the available information for 32,144 (97%) of extant described mammals, birds, reptiles, and amphibians. We show that only 1.3% of the tetrapod species have comprehensive information on birth and death rates. We found no demographic measures, not even crude ones such as maximum life span or typical litter/clutch size, for 65% of threatened tetrapods. More field studies are needed; however, some progress can be made by digitalizing existing knowledge, by imputing data from related species with similar life histories, and by using information from captive populations. We show that data from zoos and aquariums in the Species360 network can significantly improve knowledge for an almost eightfold gain. Assessing the landscape of limited demographic knowledge is essential to prioritize ways to fill data gaps. Such information is urgently needed to implement management strategies to conserve at-risk taxa and to discover new unifying concepts and evolutionary relationships across thousands of tetrapod species.

Both candidate gene and neutral genetic diversity correlate with parasite resistance in female Mediterranean mouflon.

BACKGROUND: Parasite infections can have substantial impacts on population dynamics and are accordingly a key challenge for wild population management. Here we studied genetic mechanisms driving parasite resistance in a large herbivore through a comprehensive approach combining measurements of neutral (16 microsatellites) and adaptive (MHC DRB1 exon 2) genetic diversity and two types of gastrointestinal parasites (nematodes and coccidia). RESULTS: While accounting for other extrinsic and intrinsic predictors known to impact parasite load, we show that both neutral genetic diversity and DRB1 are associated with resistance to gastrointestinal nematodes. Intermediate levels of multi-locus heterozygosity maximized nematodes resistance, suggesting that both in- and outbreeding depression might occur in the population. DRB1 heterozygosity and specific alleles effects were detected, suggesting the occurrence of heterozygote advantage, rare-allele effects and/or fluctuating selection. On the contrary, no association was detected between genetic diversity and resistance to coccidia, indicating that different parasite classes are impacted by different genetic drivers. CONCLUSIONS: This study provides important insights for large herbivores and wild sheep pathogen management, and in particular suggests that factors likely to impact genetic diversity and allelic frequencies, including global changes, are also expected to impact parasite resistance.

Genetic Characterization of Toxoplasma gondii DNA Samples Isolated From Humans Living in North America: An Unexpected High Prevalence of Atypical Genotypes.

Background: Whereas in Europe most of Toxoplasma gondii genotypes belong to the type II lineage, in Latin America, type II is rare and atypical strains predominate. In North America, data on T. gondii genotypes in humans are scarce. Methods: In this study, T. gondii DNA samples from 67 patients with diagnosed toxoplasmosis in the United States were available for genotyping. Discriminant analysis of principal components was used to infer each atypical genotype to a geographic area where patients were probably infected. Associations between genotype, disease severity, immune status, and geographic region were also estimated. Results: Of 67 DNA samples, 41 were successfully genotyped: 18 (43.9%) and 5 (12.2%) were characterized as types II and III, respectively. The remaining 18 genotypes (43.9%) were atypical and were assigned to a geographic area. Ten genotypes originated from Latin America, 7 from North America, and 1 from Asia (China). In North America, unlike in Europe, T. gondii atypical genotypes are common in humans and, unlike in Latin America, type II strains are still present with significant frequency. Conclusions: Clinicians should be aware that atypical genotypes are common in North America and have been associated with severe ocular and systemic disease and unusual presentations of toxoplasmosis in immunocompetent patients.

A fast likelihood solution to the genetic clustering problem.

The investigation of genetic clusters in natural populations is an ubiquitous problem in a range of fields relying on the analysis of genetic data, such as molecular ecology, conservation biology and microbiology. Typically, genetic clusters are defined as distinct panmictic populations, or parental groups in the context of hybridisation. Two types of methods have been developed for identifying such clusters: model-based methods, which are usually computer-intensive but yield results which can be interpreted in the light of an explicit population genetic model, and geometric approaches, which are less interpretable but remarkably faster.Here, we introduce snapclust, a fast maximum-likelihood solution to the genetic clustering problem, which allies the advantages of both model-based and geometric approaches. Our method relies on maximising the likelihood of a fixed number of panmictic populations, using a combination of geometric approach and fast likelihood optimisation, using the Expectation-Maximisation (EM) algorithm. It can be used for assigning genotypes to populations and optionally identify various types of hybrids between two parental populations. Several goodness-of-fit statistics can also be used to guide the choice of the retained number of clusters.Using extensive simulations, we show that snapclust performs comparably to current gold standards for genetic clustering as well as hybrid detection, with some advantages for identifying hybrids after several backcrosses, while being orders of magnitude faster than other model-based methods. We also illustrate how snapclust can be used for identifying the optimal number of clusters, and subsequently assign individuals to various hybrid classes simulated from an empirical microsatellite dataset. snapclust is implemented in the package adegenet for the free software R, and is therefore easily integrated into existing pipelines for genetic data analysis. It can be applied to any kind of co-dominant markers, and can easily be extended to more complex models including, for instance, varying ploidy levels. Given its flexibility and computer-efficiency, it provides a useful complement to the existing toolbox for the study of genetic diversity in natural populations.

Introduction history overrides social factors in explaining genetic structure of females in Mediterranean mouflon.

Fine-scale spatial genetic structure of populations results from social and spatial behaviors of individuals such as sex-biased dispersal and philopatry. However, the demographic history of a given population can override such socio-spatial factors in shaping genetic variability when bottlenecks or founder events occurred in the population. Here, we investigated whether socio-spatial organization determines the fine-scale genetic structure for both sexes in a Mediterranean mouflon (Ovis gmelini musimon × Ovis sp.) population in southern France 60 years after its introduction. Based on multilocus genotypes at 16 loci of microsatellite DNA (n = 230 individuals), we identified three genetic groups for females and two for males, and concurrently defined the same number of socio-spatial units using both GPS-collared individuals (n = 121) and visual resightings of marked individuals (n = 378). The socio-spatial and genetic structures did not match, indicating that the former was not the main driver of the latter for both sexes. Beyond this structural mismatch, we found significant, yet low, genetic differentiation among female socio-spatial groups, and no genetic differentiation in males, with this suggesting female philopatry and male-biased gene flow, respectively. Despite spatial disconnection, females from the north of the study area were genetically closer to females from the south, as indicated by the spatial analysis of the genetic variability, and this pattern was in accordance with the common genetic origin of their founders. To conclude, more than 14 generations later, genetic signatures of first introduction are not only still detectable among females, but they also represent the main factor shaping their present-time genetic structure.

Phylogeography of Toxoplasma gondii points to a South American origin.

Toxoplasma gondii, a protozoan found ubiquitously in mammals and birds, is the etiologic agent of toxoplasmosis, a disease causing substantial public health burden worldwide, including about 200,000 new cases of congenital toxoplasmosis each year. Clinical severity has been shown to vary across geographical regions, with South America exhibiting the highest burden. Unfortunately, the drivers of these heterogeneities are still poorly understood, and the geographical origin and historical spread of the pathogen worldwide are currently uncertain. A worldwide sample of 168 T. gondii isolates gathered in 13 populations was sequenced for five fragments of genes (140 single nucleotide polymorphisms from 3153bp per isolate). Phylogeny based on Maximum likelihood methods with estimation of the time to the most recent common ancestor (TMRCA) and geostatistical analyses were performed for inferring the putative origin of T. gondii. We show that extant strains of the pathogen likely evolved from a South American ancestor, around 1.5 million years ago, and reconstruct the subsequent spread of the pathogen worldwide. This emergence is much more recent than the appearance of ancestral T. gondii, believed to have taken place about 11 My ago, and follows the arrival of felids in this part of the world. We posit that an ancestral lineage of T. gondii likely arrived in South America with felids and that the evolution of oral infectivity through carnivorism and the radiation of felids in this region enabled a new strain to outcompete the ancestral lineage and undergo a pandemic radiation.

On the evolutionary consequences of increasing litter size with multiple paternity in wild boar (Sus scrofa scrofa).

Understanding how some species may be able to evolve quickly enough to deal with anthropogenic pressure is of prime interest in evolutionary biology, conservation, and management. Wild boar (Sus scrofa scrofa) populations keep growing all over Europe despite increasing hunting pressure. In wild boar populations subject to male-selective harvesting, the initially described polygynous mating system may switch to a promiscuous/polyandrous one. Such a change in the mating system, where potentially more males sire a litter at one reproductive event, may be associated with the retention of high genetic diversity and an increase of litter size. We tested these hypotheses by estimating the number of sires per litter based on a six-year long monitoring of a wild boar population subject to particularly high harvesting pressure. Our results show a high and stable genetic diversity and high rates of multiple paternity compared to other populations, thus depicting a promiscuous/polyandrous mating system in this population. We also show that litter size is positively linked to the number of sires, suggesting that multiple paternity increases fecundity. We finally discuss that multiple paternity may be one of the factors allowing rapid evolution of this population by maintaining both genetic and phenotypic diversity.

The rural-urban effect on spatial genetic structure of type II Toxoplasma gondii strains involved in human congenital toxoplasmosis, France, 2002-2009.

Congenital toxoplasmosis involves Toxoplasma gondii type II strains in 95% of cases in France. We used spatial principal component analysis (sPCA) and 15 microsatellite markers to investigate the spatial genetic structure of type II strains involved in 240 cases of congenital toxoplasmosis in France from 2002 through 2009. Mailing addresses of patients were geo-referenced a posteriori in decimal degrees and categorized into urban or rural areas of residence. No spatial genetic structure was found for type II strains that infected mothers who were living in urban areas, but a global spatial genetic structure was found for those that infected mothers who were living in a rural environment. Our results suggest that sources of infection by T. gondii are different in rural and urban areas in France, and advocate for targeted messages in the prevention of toxoplasmosis according to the type of residence of susceptible people.

Staphylococcus aureus infective endocarditis versus bacteremia strains: Subtle genetic differences at stake.

Infective endocarditis (IE)((1)) is a severe condition complicating 10-25% of Staphylococcus aureus bacteremia. Although host-related IE risk factors have been identified, the involvement of bacterial features in IE complication is still unclear. We characterized strictly defined IE and bacteremia isolates and searched for discriminant features. S. aureus isolates causing community-acquired, definite native-valve IE (n=72) and bacteremia (n=54) were collected prospectively as part of a French multicenter cohort. Phenotypic traits previously reported or hypothesized to be involved in staphylococcal IE pathogenesis were tested. In parallel, the genotypic profiles of all isolates, obtained by microarray, were analyzed by discriminant analysis of principal components (DAPC)((2)). No significant difference was observed between IE and bacteremia strains, regarding either phenotypic or genotypic univariate analyses. However, the multivariate statistical tool DAPC, applied on microarray data, segregated IE and bacteremia isolates: IE isolates were correctly reassigned as such in 80.6% of the cases (C-statistic 0.83, P<0.001). The performance of this model was confirmed with an independent French collection IE and bacteremia isolates (78.8% reassignment, C-statistic 0.65, P<0.01). Finally, a simple linear discriminant function based on a subset of 8 genetic markers retained valuable performance both in study collection (86.1%, P<0.001) and in the independent validation collection (81.8%, P<0.01). We here show that community-acquired IE and bacteremia S. aureus isolates are genetically distinct based on subtle combinations of genetic markers. This finding provides the proof of concept that bacterial characteristics may contribute to the occurrence of IE in patients with S. aureus bacteremia.

The relationship between phenotypic variation among offspring and mother body mass in wild boar: evidence of coin-flipping?

1. In highly variable environments, the optimal reproductive tactics of iteroparous organisms should minimize variance in yearly reproductive success to maximize the long-term average reproductive success. To minimize among-year variation in reproductive success, individuals can either minimize the variance in the number of offspring produced at each reproductive attempt (classical bet-hedging) or maximize the phenotypic diversity of offspring produced within or among reproductive attempts (coin-flipping). 2. From a long-term detailed study of an intensively exploited population facing a highly unpredictable environment, we identify a continuum of reproductive tactics in wild boar females depending on their body mass. 3. At one end, light females adjusted litter size to their body mass and produced highly similar-sized offspring within a litter. These females fitted the hypothesis of individual optimization commonly reported in warm-blooded species, which involves both an optimal mass and an optimal number of offspring for a given mother. At the other end of the continuum, heavy females produced litters of variable size including a mixture of heavy and light offspring within litters. 4. Prolific heavy wild boar females diversify the phenotype of their offspring, providing a first evidence for coin-flipping in a warm-blooded species.

Environmental determinants of spatial and temporal variations in the transmission of Toxoplasma gondii in its definitive hosts.

Toxoplasmosis is a major zoonosis, and its prevention requires multiple approaches due to the complex life-cycle of its causative agent, Toxoplasma gondii. Environmental contamination by oocysts is a key factor in the transmission of T. gondii to both humans and meat-producing animals; however, its spatial and temporal variations are poorly understood. We analysed the distribution of T. gondii seropositivity in a sample of 210 cats, including the European wildcat (Felis silvestris silvestris), the domestic cat (Felis silvestris catus) and their hybrids that were collected in Central and Eastern France between 1996 and 2006. We searched for spatial variability among communes and temporal variations among years to relate this variability to landscape and meteorological conditions, which can affect the population dynamics of rodent hosts and the survival of oocysts. The overall seroprevalence was 65.2% (95% CI: 58.6-71.4). As expected, adults were more often infected than young individuals, while the occurrence of infection was not related to cat genotypes. Seroprevalence correlated significantly with farm density and the North-Atlantic Oscillation index, which describes temporal variations of meteorological conditions at the continental scale. The highest seroprevalence values were obtained in areas with high farm densities and during years with cool and moist winters. These results suggest that both farming areas and years with cool and wet winters are associated with increased T. gondii seroprevalence in cats. As cat infection determines the environmental contamination by oocysts, climate and landscape characteristics should be taken into account to improve the risk analysis and prevention of T. gondii.

Additional haplogroups of Toxoplasma gondii out of Africa: population structure and mouse-virulence of strains from Gabon.

BACKGROUND: Toxoplasma gondii is found worldwide, but distribution of its genotypes as well as clinical expression of human toxoplasmosis varies across the continents. Several studies in Europe, North America and South America argued for a role of genotypes in the clinical expression of human toxoplasmosis. Genetic data concerning T. gondii isolates from Africa are scarce and not sufficient to investigate the population structure, a fundamental analysis for a better understanding of distribution, circulation, and transmission. METHODOLOGY/PRINCIPAL FINDINGS: Seropositive animals originating from urban and rural areas in Gabon were analyzed for T. gondii isolation and genotyping. Sixty-eight isolates, including one mixed infection (69 strains), were obtained by bioassay in mice. Genotyping was performed using length polymorphism of 13 microsatellite markers located on 10 different chromosomes. Results were analyzed in terms of population structure by Bayesian statistical modeling, Neighbor-joining trees reconstruction based on genetic distances, F(ST) and linkage disequilibrium. A moderate genetic diversity was detected. Three haplogroups and one single genotype clustered 27 genotypes. The majority of strains belonged to one haplogroup corresponding to the worldwide Type III. The remaining strains were distributed into two haplogroups (Africa 1 and 3) and one single genotype. Mouse virulence at isolation was significantly different between haplogroups. Africa 1 haplogroup was the most virulent. CONCLUSION: Africa 1 and 3 haplogroups were proposed as being new major haplogroups of T. gondii circulating in Africa. A possible link with strains circulating in South and Central America is discussed. Analysis of population structure demonstrated a local spread within a rural area and strain circulation between the main cities of the country. This circulation, favored by human activity could lead to genetic exchanges. For the first time, key epidemiological questions were addressed for the West African T. gondii population, using the high discriminatory power of microsatellite markers, thus creating a basis for further epidemiological and clinical investigations.

Discriminant analysis of principal components: a new method for the analysis of genetically structured populations.

BACKGROUND: The dramatic progress in sequencing technologies offers unprecedented prospects for deciphering the organization of natural populations in space and time. However, the size of the datasets generated also poses some daunting challenges. In particular, Bayesian clustering algorithms based on pre-defined population genetics models such as the STRUCTURE or BAPS software may not be able to cope with this unprecedented amount of data. Thus, there is a need for less computer-intensive approaches. Multivariate analyses seem particularly appealing as they are specifically devoted to extracting information from large datasets. Unfortunately, currently available multivariate methods still lack some essential features needed to study the genetic structure of natural populations. RESULTS: We introduce the Discriminant Analysis of Principal Components (DAPC), a multivariate method designed to identify and describe clusters of genetically related individuals. When group priors are lacking, DAPC uses sequential K-means and model selection to infer genetic clusters. Our approach allows extracting rich information from genetic data, providing assignment of individuals to groups, a visual assessment of between-population differentiation, and contribution of individual alleles to population structuring. We evaluate the performance of our method using simulated data, which were also analyzed using STRUCTURE as a benchmark. Additionally, we illustrate the method by analyzing microsatellite polymorphism in worldwide human populations and hemagglutinin gene sequence variation in seasonal influenza. CONCLUSIONS: Analysis of simulated data revealed that our approach performs generally better than STRUCTURE at characterizing population subdivision. The tools implemented in DAPC for the identification of clusters and graphical representation of between-group structures allow to unravel complex population structures. Our approach is also faster than Bayesian clustering algorithms by several orders of magnitude, and may be applicable to a wider range of datasets.