Angiostrongylus cantonensis is of increasing public health importance as the main zoonotic pathogen causing eosinophilic meningitis or meningoencephalitis, which has been documented all over the world. However, there are very limited studies about its phylogeography and spread pattern. In the present study, the phylogeography of A. cantonensis in southern China (including Taiwan) and partial areas of Southeast Asia were studied based on the sequences of complete mitochondrial cytochrome b (Cytb) gene. A total of 520 individuals of A. cantonensis obtained from 13 localities were sequenced for the analyses and grouped into 42 defined haplotypes. The phylogenetic tree (NJ tree and BI tree) revealed a characteristic distribution pattern of the four main lineages, with detectable geographic structure. Genetic differentiation among populations was significant, but demographic expansion could not be detected by either neutrality tests or mismatch distribution analysis, which implied a low gene flow among the local populations in different regions where the samples were collected. Two unique lineages of the A. cantonensis population in Taiwan were detected, which suggests its multiple origin in the island. Populations in Hekou (China) and Laos showed the highest genetic diversities, which were supported by both genetic diversity indices and AMOVA. These results together infer that the area around Thailand or Hekou in Yunnan province, China are the most likely origins of Angiostrongylus cantonensis. A. cantonensis worldwide, primarily in tropical and subtropical regions. Despite a relevant body of research on pathology, diagnosis and treatment, little is known about the phylogeography of A. cantonensis. Since southern China is one of the endemic regions, we performed this experiment to reveal the distribution pattern of A. cantonensis in southern China based on mitochondrial Cytb data. Our results revealed a unique pattern probably shaped by the biological features of its hosts and geographical barriers, simultaneously reflecting a low gene flow among populations. Nevertheless, the connective consanguinity between some locations (Taiwan and Southeast Asia) provides new evidence of the impact on its dispersal as influenced by human activities, indicating the emerging need of an effective strategy to control this helminth. In addition to the corresponding investigation on its hosts, more attention to the situation in southwest China and Southeast Asia is suggested to facilitate the understanding of the phylogeography of A. cantonensis.Since it was described in 1935, more than 2800 cases of the disease have reportedly been caused by  Angiostrongylus cantonensis  is one of 21 described species in its genus, and is the zoonotic parasite responsible for human eosinophilic meningitis or meningocephalitis [Rattus rattus and R. norvegicus [A. cantonensis has been isolated from a number of intermediate hosts including terrestrial and aquatic snails species such as Achatina fulica and Pomacea canaliculata, from which it moves on to a number of species that serve as paratenic hosts, such as crustaceans, monitor lizards and various frogs species. The Angiostrongylus larvae develop to the third larval stage in snails or slugs with ingestion of infected rat-feces, and the main route of human infection of this nematode is through ingestion of raw or undercooked foods containing the third stage larvae, although human beings are not the normal definitive host [A. cantonensis have been reported, mainly from Southeast Asia and the Pacific. Due to the deliberate or unintentional introduction of its hosts, the epidemic areas of the angiostrongyliasis have expanded to novel countries and regions including Australia and Latin America [Achatina fulica infected with A. cantonensis [The nematode is Chen, 935 is onis Chen, 935 is on America , 5, in atonensis . Globalltonensis , 8.A. cantonensis may provide insight into the spread of this zoonotic pathogen, as exemplified by a few recent molecular phylogeographic studies on this nematode. Four species of Angiostrongylus spp. including A. cantonensis were distinguished based on the sequence analysis of the mitochondrial cytochrome c oxidase subunit I (COI), among which China isolates and those sampled in Thailand formed two parallel subclades [A. cantonensis sampled from Japan, mainland China, Taiwan, and Thailand revealed that the current geographical distribution of A. cantonensis probably reflects multiple independent origins that are likely to have been influenced by human activities [et al. on phylogenetic relationship of COI for A. cantonensis demonstrated that some haplotypes from Brazil clustered with isolates from Asia, while the rest formed distinctly divergent clades, implying multiple origins of A. cantonensis in Brazil. Besides, Alicata [A. cantonensis originated in East Africa and spread worldwide with its host Achatina fulica, while Drozdz [A. cantonensis has emerged. Nevertheless, the results shown above suggest that Asia is one of multiple probable places of origin.A more comprehensive understanding of the phylogeography of ubclades . Anothertivities . Similartivities  et al. o Alicata  proposede Drozdz  considerA. cantonensis have been carried out recently [A. cantonensis from the Chinese mainland  and from Thailand , which therefore allowed us to study the phylogeography of this parasite based on variable mitochondrial gene sequences in different areas of China in the geographic range where it was initially reported. This species has not been previously investigated for its molecular phylogeography in China.Although numerous studies on genetic differentiation of recently , 14–18, recently , 18. TheA. cantonensis in China. Our analysis focused on the Cytb gene of A. cantonensis from Achatina fulica mainly collected from southern China (including sampling locations in Taiwan) and the surrounding region, with some samples from Laos (Vientiane) close to northern Thailand included.The objective of the current study is to reveal the pattern and processes of geographic distribution of All the samples for the present study are isolated from snails which did not concern with ethnic issue. All the experimental manipulation accorded with animal safety and ethnic rule issued by the School of Life Sciences, Sun Yat-sen University.Achatina fulica, identified by morphological characteristics, were captured from 13 different locations in southern China and Laos. These samples were collected in Guangzhou , Zhuhai , Xiamen , Fangchenggang , Baise , Hekou , Wenchang , Senya , New Taipei , Taichung , Kaohsiung , Hualien  and Laos , as presented in 3), snails were individually dissected after surface cleaning. The pulmonary membrane and part of mesenterium were obtained from each snail. After treatment in a bottle with 50 ml digestive solution  [Specimens of Genomic DNA was extracted from individual worms, strictly following the protocol provided by manufacturer . The final product extracted from each individual worm was preserved in 50 μl TE buffer solution  and stored at below -20°C.2, 0.2 μM of each dNTP, 1U of Ex Taq polymerase , 0.2 μL of extraction product for the primary amplification, and 0.2 μl of preliminary product for the subsequent nested reaction. Each reaction was carried out in a Biometra thermal cycler  using the following procedure: 3 min at 94°C for denaturation, followed by 35 cycles of 30 s at 94°C, 30 s at 50–53°C for annealing, 90 s at 72°C, and a final extension at 72°C for 3 min. The primers used for amplification are listed in supplementary The DNA product extracted from each nematode was used as the template to amplify the complete mitochondrial cytochrome b (Cytb). Amplification was conducted by nested PCR reaction in a volume of 25 μL containing 2.5 μL of 10 × Ex Taq buffer, 1.5 mM of MgClPCR products were purified with the UNIQ-10 Spi Column PCR Product Purification Kit  and subjected to automated DNA sequencing  with the same primers used for nested amplification.Nucleotide sequences were compiled and aligned in MEGA 6.0, followed by visual inspection. Nucleotide sequences were then translated into acid sequences with the invertebrate mitochondrial code to ensure that no unclear pseudogenes were amplified.H), polymorphic sites (S), haplotype diversity (h), nucleotide diversity (p) and the average numbers of pairwise nucleotide differences (k). Pairwise and overall distances among haplotype sequences were calculated in MEGA 6.0 [Dnasp 5.0  and ArleMEGA 6.0 .The best-fit substitution model for Cytb gene data and the gamma distribution parameter for the rate of heterogeneity among sites were determined using Modeltest 3.07  based onAngiostrongylus costaricensis (Genbank: GQ398122) as outgroup. The genetic distances were estimated under Tamura and Nei model of substitution suggested by Modeltest. Bootstrapping was conducted with 1,000 replicates [Neighbor-joining (NJ) trees were constructed using MEGA 6.0 with plicates  as the aplicates . Four Maplicates  with BIOplicates  using thplicates .The AMOVA was undertaken to describe the population structure, which was implemented in Arlequin 3.5 by F-statistics at three subdivided geographical hierarchical levels: the proportions of variations among regions (FCT′), among populations within region (FSC′) and within populations (FST′) with a 5,000-times permutation to assess the significance of the covariance components associated with the different possible levels of genetic structure. Both the calculation of fixation index (FST) with 10,000 permutations and statistical significance were used to evaluate the genetic differentiation between pairwise populations. The genetic distances between haplotypes was revised under the Tamura and Nei model of nucleotide substitution with a gamma shape parameter G = 0.3017) suggested by Modeltest. A comparison between the observed distribution frequency and the expectations under panmixia [17 suggesSSD) with a parametric bootstrapping approach using 10,000 replicates. The mismatch distribution of samples drawn from populations at demographic equilibrium is usually multimodal while that for samples from populations with recent demographic and distributional expansions is usually unimodal [D [Fs [D test compares two estimators of the mutation parameter θ: Watterson’s estimator θs and Tajima’s estimator θπ; significant D values are typically generated as the result of factors such as population expansion, bottlenecks and selection. In Fu’s Fs test, the number of haplotypes observed is contrasted with that expected in a random sample under the assumption of an infinite-sites model without recombination. Additionally, Fs is sensitive to demographic expansion, which generally results in a negative Fs value.Two different methods were adopted to the historical demographic analysis. First, the frequency distribution of pairwise differences among all haplotypes (mismatch distribution) was tested under the sudden expansion model of Rogers . Deviatiunimodal . Given tunimodal , both Tamodal [D  and Fu’sl [D [Fs  tests baA. cantonensis in samples representing 13 populations. Among these sequences, a total of 42 haplotypes were identified with 229 polymorphic sites including 192 transitions, 44 transversions and 8 indels. Except for 5 haplotypes  shared by multiple localities, all others are private to their specific populations. H1 and H5 appear in southern China and Hainan Island, while the distributions of H21, H23 and H25 are restricted to Taiwan Island. H1 was the most prevalent haplotype (194 of 520) and occupied the widest range of localities . The H21 haplotype was the most commonly detected haplotype in Taiwan Island  of 0.8253±0.0138 and nucleotide diversity (π) of 0.087096±0.041454, exhibiting a high level of haplotype diversity but low nucleotide diversity. Among regions, Laos and Hekou exhibited the highest haplotype diversities, 0.7385±0.0614 and 0.7357±0.0395 respectively, and the highest nucleotide diversities of 0.154297±0.074972 were also detected for samples from Laos. Samples from Xiamen and Hekou had considerably high values of nucleotide diversities, 0.029379±0.014567 and 0.022392±0.011127 respectively.Genetic diversity indices of all regions are presented in 1 consisting of the majority of haplotypes from southern China with few from two islands (Taiwan and Hainan) and A2 including samples from GZ, WC, KH and LA. In spite of the farraginous composition in clade A, the majority of haplotypes from southern China were clustered with samples from Hainan Island and accordingly separated from haplotypes from Taiwan Island (squares displayed in / 0.95), implying a genetic divergence of haplotypes between Taiwan Island and southern mainland China. In contrast with Clade A, no significant connection between haplotype composition and sampling localities was found in the other 3 clades. Nonetheless, the distribution of haplotypes among clades was tendentious and meaningful: haplotypes form HK interspersed among Clade A1, B and C; GZ interspersed among Clade A, B, and C; LA interspersed among Clade A2, B, C and D. Phylogeny of haplotypes was more distinctly and remarkably revealed in Bayesian analysis  was selected as the best-fit substitution model suggested by Modeltest to reconstruct the phylogenetic tree for Cytb haplotypes data . Haplotyanalysis . The tre2, forming a distinctive clade with haplotypes from Laos, Hainan and Taiwan regions, as shown in The NJ tree for partial Cytb sequences with additional haplotypes from Thailand obtained from GenBank under accession number KP721442—KP721453 was constructed using the same parameters . All the haplotypes from Thailand were interfused into Clade A2 appeared to be closer to Clade D than that to Clade A1 as displayed in the phylogenetic tree.The network analysis similarly revealed that the haplotypes nested into 5 clusters  correspoFst) was summarized in Fst revealed significant differences (P<0.05), implying the existence of significant population structure across the range investigated. These results were further confirmed by hierarchical AMOVA tests which attributed nearly 50% of the genetic variation to the variabilities among populations within groups  of the distribution from that expected under the expansion model  from that under neutral assumption. These results lead us to conclude that populations of A. cantonensis in the range studied were inconsistent with stable demographic history, although no strong evidence emerged in support of episodes of expansion.Despite a lack of significance of the goodness of fit test . High level values were generated between Clade D  and other clades (haplotypes) as 12.8 to 14.0%, while those of haplotypes within other three clades only ranged from 0.1 to 6.8%  of  to 6.8% . This waof 11.6% . Newly pThailand . Such reA. cantonensis, and these organisms are capable of highly promoting the spread and intraspecific transfer of this parasite. The genetic structure of populations from different regions was still different from those under random mating in some way. By contrast, owing to the high dispersal potential and lack of geographic barrier in the marine environment, marine organisms normally do not display evidence of genetic differentiation throughout wider geographic range and consequently their parasites typically exhibit a similar genetic pattern [Pseudokuhnia minor, a species of monogenean on the host of chub mackerel Scomber japonicus, exhibited no significant genetic structure along the coast of China, implying panmixia within the range of the population [A. cantonensis has many definitive and intermediate hosts, these hosts have limitations in traversing habitat barriers, such as water for Achatina fulica and low temperature on the high mountains for both Achatina fulica and Pomacea canaliculata. Inevitably, the definitive host rodents have complex impacts on the population genetic structure of A. cantonensis because of their wide adaptation in terrestrial habitats, which is in need of further study.Numerous species of rodents serve as the definitive hosts of  pattern . The phypulation . As the pulation . AlthougA. cantonensis in Taiwan based on partial COI sequence data also revealed the existence of a distinct strain of A. cantonensis in Hualien, which is distinguished from strains in other regions in Taiwan by not only the genetic distance, but also discrepancies in infectivity and pathogenicity [A. cantonensis in Taiwan.Notably, haplotypes from Hualien (HL) and Laos (LA) generated Clade D which substantially diverges from other clades, implying the population from Hualien is a unique lineage in Taiwan. The exact test and low level of genetic diversity of population from Hualien also revealed the absence of gene flow between Hualien population and populations in other regions. Another survey on the genetic diversity of genicity . Hence, Achatina fulica, it was proposed that numerous impolitic introduction and activities of the Japanese army during World War II figured importantly in establishing its range [Rattus rattus in the western Indian Ocean islands also revealed effects of human-mediated colonization [A. cantonensis has established global-scale dispersal with various organisms/hosts or vectors that are largely influenced by human transportation has gained wide acceptance [A. cantonensis populations along the west coast of Taiwan Island with those in Thailand are also supported by the reconstructed phylogeographic tree  indicating that they might share a common origin, despite the thousands-miles separation by the Pacific Ocean between these two locations. This unusual pattern may be attributed to the worldwide dispersal of the hosts of this parasite as influenced by human activities. With regard to the spread of the widely introduced and invasive land snail species around the world, ts range , 50. Phynization . The infceptance , 11, 17.ree Figs  and 4. ILithobates catesbeianus that genetic diversity was greatly reduced in colonizing populations due to demographic bottlenecks [A. cantonensis populations have significant high levels of genetic diversity  was clustered together with those from Thailand and Laos (1), the latter were also closely linked to A. cantonensis in Hekou (Clade B). Hence, it could be proposed that Hekou is more likely the site of the origin of A. cantonensis in southern mainland China. It is still unknown how the population of A. cantonensis in Hekou may have been genetically connected to populations in Laos or Thailand, an understanding that may require further insight into the potential interaction of A. cantonensis populations between these locations.In the study of invasion biology, we generally consider introduced populations as having low genetic variability , 53. Thitlenecks . Hekou aiversity . It can and Laos , the popA. cantonensis populations in Guangzhou (GZ) and Xiamen (XM), it is likely that these port cities have a high probability of accepting the A. cantonensis carrying organisms, as it has been observed that epidemics frequently break out initially in port areas [A. cantonensis from diverse regions have increased the genetic diversity in these port cities, at least in part as a consequence of human activities that influence the distribution of A. cantonensis.With regard to the notable high genetic diversities of rt areas , 56. It A. cantonensis in different species of hosts and based on more molecular markers will be required.Many relevant studies based on mtDNA sequence could reveal patterns of demographic history or association with known historic events –61, howeA. cantonensis in different areas of Southern China. The dispersal via human activities across ocean, coupled with the natural spread of its hosts might have led to the establishment of several separated lineages in Taiwan Island. Additionally, no significant indication of demographic expansion was detected in the scope of survey, although significant genetic variation of A. cantonensis was found between southern China and Southeast Asia. The structured pattern of phylogenetic lineages has no precise correspondence to geographic distribution, underscoring the complicated nature of the task of tracing the population dynamics of this species. More samples from Southeast Asia and further survey of its host organisms together could provide more detailed evidence, leading to a higher degree of resolution in our understanding of the phylogeography of this parasite.The remarkable genetic differentiation between isolations indicated a low gene flow among the populations of S1 Table(DOCX)Click here for additional data file.S2 Table(XLS)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.


Arapaima gigas, is a fish whose populations are threatened by both overfishing and the ongoing destruction of its natural habitats. In the Amazon basin, varying levels of population structure have been found in A. gigas, although no data are available on the genetic diversity or structure of the populations found in the Araguaia-Tocantins basin, which has a topographic profile, hydrological regime, and history of fishing quite distinct from those of the Amazon. In this context, microsatellite markers were used to assess the genetic diversity and connectivity of five wild A. gigas populations in the Araguaia-Tocantins basin. The results of the analysis indicated low levels of genetic diversity in comparison with other A. gigas populations, studied in the Amazon basin. The AMOVA revealed that the Arapaima populations of the Araguaia-Tocantins basin are structured significantly. No correlation was found between pairwise STF values and the geographical distance among populations. The low level of genetic variability and the evidence of restricted gene flow may both be accounted for by overfishing, as well as the other human impacts that these populations have been exposed to over the years. The genetic fragility of these populations demands attention, given that future environmental changes  may further reduce these indices and eventually endanger these populations. The results of this study emphasize the need to take the genetic differences among the study populations into account when planning management measures and conservation strategies for the arapaima stocks of the Araguaia-Tocantins basin.The arapaima,  Worldwide, the populations of many fish species are declining rapidly , with thArapaima gigas , is a fish of considerable economic importance in the neotropics, and is one of the species listed in the Convention of International Trade in Endangered Species of Wild Fauna and Flora II. The species is listed as “Data Deficient” by the IUCN , with a larger number of environments been expected to support larger numbers of fish and family groups.While arapaima stocks have been reduced by both fishing and habitat loss, few populations have been studied in the Araguaia-Tocantins basin, and there is a pressing need for the expansion of the database to provide a reliable assessment of the conservation status of these populations. The first study to use genetic markers in arapaima from the Araguaia-Tocantins basin was conducted by While the study of Arapaima gigas were obtained from five different locations on the Araguaia and Tocantins rivers, three in the state of Mato Grosso , one in Goiás (Luiz Alves), and one in Pará, Itupiranga . The municipality of Araguaiana represents the region furthest upstream of the middle Araguaia River, where the river first forms marginal lakes along its course, appropriate for A. gigas. Araguaiana is also the sector with the smallest number of lakes  were preserved in 100% alcohol, and deposited at the Cytogenetics and Animal Genetics Laboratory, of the Federal University of Mato Grosso (LabGen/GEPEMA/UFMT) in Cuiabá, Brazil. When it was necessary to handle animals, all procedures adhered to the recommendations of the Guide for the Care and Use of Laboratory Animals. The collection and transportation of biological specimens by the authors of the present study is authorized by the Brazilian Institute for the Environment and Renewable Resources (IBAMA) through permanent license number 15226-1, issued by the Chico Mendes Institute for the conservation of Biodiversity (ICMBio).The total DNA was extracted according to the saline extraction protocol of Arapaima populations of the Amazon Basin  were selected based on previous studies and also because they are highly polymorphic for the on Basin . These pISF) for each locus, which was compared with the null hypothesis (ISF = 0). Genepop was also used to determine allele frequencies, and the presence of polymorphic loci, and exclusive and rare alleles. Allele richness was estimated in Fstat 2.9.3.2 , and the divergence parameter (STR), which were all determined by Arlequin 3.5.1.2  and geographical distance, which was measured following the main channel of the river.Genetic differentiation among populations was evaluated using an Analysis of Molecular Variance (AMOVA), the molecular fixation index  of each population was derived from the theta values (θ) generated in MIGRATE-n 3.2.6  of 5.56 × 10-4 per locus per generation  by the θ values of the receptor population in each pairwise comparison. This analysis was performed using the Brownian model, with a uniform distribution and a constant mutation rate between the loci. The standard search strategy values of the MIGRATE program were used, except for the use of 20 short chains and 5 long chains.The MIGRATE-n program was also used to calculate migration rates between pairs of populations by the coalescence method. The number of migrants per generation (Nm) was obtained by multiplying the migration rates obtained by the program  were calculated for all seven microsatellite loci analyzed, together with the mean parameters for all loci (Table 2).A total of 25 alleles were identified, with an average of 3.57 alleles per locus. While all the loci were polymorphic, four were monomorphic in at least one of the arapaima populations analyzed from the Araguaia-Tocantins basin. The number of alleles, observed and expected heterozygosity, allelic richness, and the fixation index (Table 2).The population from Novo Santo Antônio had the highest genetic diversity, with 72% of the identified alleles and an allelic richness of 2.429. At the opposite extreme, the arapaima from Araguaiana were the least diverse (44.0%) with an allelic richness of only 1.521. The specimens from Araguaiana also returned the lowest heterozygosity , while those from Itupiranga had the highest values, with observed heterozygosity of 0.428 and an expected heterozygosity of 0.449 (Table 2). Only four of the 28 values estimated for the inbreeding coefficient (ISF) were significantly positive, which indicates a deficit of heterozygotes. Three of these loci were recorded in the population from Novo Santo Antônio, while the other was from São Felix do Araguaia. A single locus from Itupiranga was significantly negative, indicating an excess of heterozygotes. When the whole set of loci is considered, a significant ISF value (p < 0.001) was only for the Novo Santo Antônio presented, indicating the occurrence of inbreeding in this population.Five loci deviated from Hardy-Weinberg equilibrium, with heterozygote frequencies being either lower or higher than expected (Table 3). No new alleles were detected in this study, given that all the alleles recorded here had been reported previously by One to three alleles, with high frequencies, were recorded for most loci. All loci except AgCAm15 presented exclusive alleles for the different study populations, at frequencies ranging from 0.012 to 1.00. No exclusive alleles was detected in the population from São Felix do Araguaia (Table 3) indicated the presence of null alleles in the populations from Luís Alves (for loci AgCAm20 and AgCTm4), Novo Santo Antônio , São Félix do Araguaia (AgCAm15), and Itupiranga (AgCTm4). No systematic pattern was observed in the occurrence of null alleles in the different study populations, however. No evidence was found of either the misidentification of stutters as alleles or dropouts .The MicroChecker analysis (STF) ranged from 0.061 to 0.669, while those for the Slatkin divergence parameter (STR), varied from 0.025 to 0.688. Both indices were significant for all pairs of locations (Table 4). The results of the Mantel test rejected the hypothesis that genetic differentiation was related to geographical distance, considering the values of either STF , STR  or STF/1-STF . The results of the Bayesian inference based on the mean likelihood [Ln (K)] of the Δk . These findings were used to establish the clusters for the analysis of molecular variance (AMOVA).The values recorded for Wright index . The variation among populations within each group contributed only 12.35% (ΦST) and 11.17% (STR) of the variance, while the variance within populations is 43.51% for ΦST and 48.76 for STR. The ΦST  and  were both relatively high among the study populations.The results of the AMOVA indicated a lack of significant variation between the two groups (ΦTable 5). The MIGRATE-n coalescence analysis  excess of heterozygotes was found in the Itupiranga population using the TPM (Wilcoxon test) model.The Bottleneck program did not detect any significant deficit of heterozygotes. However, a significant , provoking the loss of genetic diversity, which leads to a reduced resilience of populations to environmental stresses and climate change, and a loss of resistance to pathogens  may further reduce the diversity of these populations, and threaten their long-term viability.This fragility is further reinforced by the differences in the genetic variability of each population in the Araguaia-Tocantins basin. Specimens collected at Araguaiana, for example, had the lowest genetic diversity of any population, indicating the smallest effective size of any population, which implies that this population is the most vulnerable to anthropogenic interference from the expansion of the agricultural frontier occurring within the basin , as wellISF values (indicating a deficiency of heterozygotes) were found in six of the eight deviations recorded. A number of studies have recorded a deficiency of heterozygotes in fish populations  to extreme (>0.25) genetic differentiation between populations. However, the Bayesian analysis points to the presence of only two genetic stocks in the Araguaia-Tocantins basin, one at Araguaiana, and the other formed by the remaining populations, at Luís Alves, Novo Santo Antônio, Sao Félix do Araguaia and Itupiranga . This arrangement contrasts with that recorded by The pairwise The structure proposed by the Bayesian analysis is also supported by the estimates of gene flow and the number of migrants between populations, given that the populations that share the same genetic stock had the highest migration rates. It is important to note that the gene flow detected here may reflect ancestral processes, rather than the recent exchange of individuals, because the number of migrants is a somewhat abstract quantity, which cannot be distinguished from the effective population size .STF and STR values. Reduced genetic differentiation was expected between the samples from Novo Santo Antônio and São Félix do Araguaia, which are the geographically closest sites (separated by a distance of only 111 km), although the STF values indicate that the populations of São Félix do Araguaia and Luís Alves (265.1 km apart) are the most similar. In addition to the basic differences in comparison with the Amazonian arapaima populations, then, the relationship between population structure and geographic distance is also distinct from that recorded by While the genetic variation found in the present study is not related systematically to geographic distance, the geographically closer populations  returned the lowest Arapaima gigas populations of the Araguaia-Tocantins basin, which can be linked directly to the environmental fragility of this river system, which reinforces the need for a better understanding of the processes that may further reduce the viability of these populations. The findings of this study also indicated that the genetic diversity of the populations is distributed heterogeneously within the study area, and that the establishment of a single protected area would be insufficient for the preservation of the genetic diversity of the arapaima populations of the Araguaia-Tocantins basin as a whole. In particular, future management measures should consider the population from Araguaiana as an independent unit, distinct from the other Araguaia-Tocantins populations. The Itupiranga region should also be defined as a priority area for conservation, given the high allelic richness found in this population.The present study confirmed the low genetic diversity of the This study was carried out in strict accordance with the recommendations provided in the Guide for the Care and Use of laboratory Animals. During the development of this work, no animals were sacrificed. Collection was authorized by SEMA (license number 104358/2011/SEMA-MT), Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis - IBAMA and Instituto Chico Mendes de Conservação da Biodiversidade – ICMBio (License number 15226-1).CV performed the molecular genetic studies, performed the statistical analyzes and drafted the manuscript. FN performed some molecular genetic studies and contributed to the correction of the text. JA and PV conceived and coordinated the study, participated in its elaboration and helped to draft the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Wenyonia virilis tapeworm, Synodontis schall catfish) are analyzed in the recently divided Turkana and Nile basins. The two basins, were repeatedly connected during the Holocene wet/dry climatic oscillations, following late Pleistocene dessication of the Turkana basin. Mitochondrial DNA sequences for cytochrome oxidase I gene (cox I) and a whole genome scanning method—amplified fragment length polymorphism (AFLP) were employed. A total of 347 cox I sequences (representing 209 haplotypes) and 716 AFLP fragments, as well as 120 cox I sequences (20 haplotypes) and 532 AFLP fragments were obtained from parasites and hosts, respectively. Although results indicate that host and parasite populations share some formative traits , their population histories/patterns differ markedly. Mitochondrial analysis revealed that parasite populations evolve significantly faster and show remarkably higher genetic variability. Analyses of both markers confirmed that the parasites undergo lineage fission, forming new clusters specific for either freshwater or saline parts of Lake Turkana. In congruence with the geological history, these clusters apparently indicate multiple colonisations of Lake Turkana from the Nile. In contrast, the host population pattern indicates fusion of different colonisation waves. Although fish host populations remain connected, saline habitats in Lake Turkana (absent in the Nile), apparently pose a barrier to the gene flow in the parasite, possibly due to its multihost lifecycle, which involves freshwater annelids. Despite partially corroborating mitochondrial results, AFLP data was not sufficiently informative for analyzing populations with recently mixed biogeographic histories.Biogeographical and ecological barriers strongly affect the course of micro-evolutionary processes in free living organisms. Here we assess the impact of a recently emerged barrier on populations of limnic fauna. Genetic diversity and population structure in a host-parasite system ( The cyclic Pleistocene climatic oscillations severely affected all biomes. Alternating hot-humid and cool-dry periods lasting for tens of millennia caused repeated contraction/expansion and/or fragmentation of vegetational belts and hydrological systems . FreshwaHydrocynus and a mochokid Synodontis [Lundberg and colleagues , furthernodontis ,15,16. TMechanisms of allopatric speciation by geology- and climate-driven isolation/fragmentation of drainages are well explained. On the other hand, the effects of isolation-related hydrological changes on limnic biotas could be more complex. Despite the obvious complementarity of lake isolation and salinization observed in numerous contemporary lakes in arid regions , the significance of salinity itself for the intraspecific diversification and/or speciation remains virtually unknown. As a result, allopatric speciation mostly serves as a universal explanation of diversity and biogeography of African freshwater organisms. One of the few exceptions is the well-known phenomenon of sympatric speciation in African cichlids ,17.The present study provides an analysis of evolutionary processes on a millennial scale, 5 thousand years ago (kya) following the Holocene split of initially continual populations of fish and their parasites in geo-historically and biogeographically allied Nile and Turkana basins, following the Late Pleistocene (near) dessication of Lake Turkana and its reestablishment and expansion during the African humid period ,19. The We proposed the following geographic model consisting of two (bio)geographic sub-systems: a non-isolated and fully freshwater basin, and an isolated endorheic basin with marked salinity gradient. Our criteria were specified for the two geographic sub-systems: i) absence of aquatic link; ii) model organisms common in both subsystems; iii) clinal salinity gradient present in the isolated sub-system; iv) isolated sub-system of sufficient size to omit size-dependent bias; v) recent disconnection of the two sub-systems.2, volume 203 km3 and average/max. depth 31/114 m. In the Late Pleistocene 35–15 kya, Lake Turkana almost completely dried out. During the Holocene, the peak of the African humid period was 11.5–10.5 kya, followed by brief periods , when the lake spilled over the Lotikipi Plain to the north-west, overflowed into White Nile [Approximately 12.5 kya, the Victoria Nile, an endorheic lake until then, and the White Nile system merged and became part of the main Nile system to form its contemporary extent . Lake Tuite Nile  and becaite Nile –26. The ite Nile ). CurrenThere is no outlet and with reduced inflows and high evaporation the chloro-carbonate alkaline water is subject to significant water level fluctuations . The lake is becoming increasingly saline along the Omo River delta (0.07) in the north, to highly saline (brackish) towards the south  . The Omo delta harbours rich Nilotic biota, whereas the major saline part of Turkana possesses depleted communities .Model organisms were selected according to their wide distribution, high abundance and reliable availability in both basins and at all localities. Additional criteria for the parasite model included narrow host specificity, complex life cycles  and well resolved taxonomy.Synodontis Cuvier (Siluriformes: Mochokidae) comprises ~120 nominal species [Synodontis spp. can mature sexually before one year of age . Synodontis schall, the only representative of the genus in Lake Turkana, was pre-selected as a model host due to its high abundance in both basins and association with several host-specific parasite taxa. Synodontis nigrita was selected as an outgroup due to its clear distinctiveness from its congeners and its availability in the study area.The endemic African catfish genus  species . Most spWenyonia Woodland, 1923 (Caryophyllidea: Caryophyllaeidae) comprises six species exclusively parasitizing Synodontis hosts. Our model, Wenyonia virilis Woodland, 1923, is the most widespread and abundant representative and unlike its congeners, present in both basins [Wenyonia is unknown but probably similar to other fish caryophyllideans, i.e. larval development in freshwater oligochaetes, no second intermediate host, maturation in the fish definitive host. In the related genus Khawia, maturation in the fish takes 1.5–6 months [The endemic African tapeworm genus h basins . The lif6 months ,33. AdulParasites and fish hosts were collected from Lake Turkana and the Nile at eight localities . The TurW. virilis, IPCAS C-503; W. minuta, IPCAS C-571; W. youdeoweii, IPCAS C-573). Genomic DNA was extracted using a standard phenol chloroform extraction method [A small piece of tissue from the worm and host liver was cut off, washed extensively in physiological saline solution and stored in 96% ethanol. The remaining part of each cestode was fixed with hot 4% buffered formalin and stained with Schuberg’s hydrochloric carmine solution . Vouchern method .5’ AGAGAGCGGTTACTGCTAATAA 3’) and Wen-cox R3 (5’ ATAATGAAAGTGCGCTACTACAAATCA 3’), were designed using sequences of related taxa from GenBank for amplifying and sequencing a partial region (~ 1100 bp) of cytochrome oxidase I gene (cox I) in Wenyonia. A PPP Master Mix (Top Bio) was used to prepare PCR reactions containing 12.5 μl of the PPP Master mix, 10 μl of ultra pure water, 5 pM of each PCR primer and 1.5 μl of isolated DNA (50 to 150ng). Cycling conditions were as follows: denaturation for 5min at 94°C, followed by 30 cycles of 30s at 94°C, 35s at 50°C, 1min 45s at 72°C, a final extension at 72°C for 10min. All products were verified on a 1% agarose gel and purified using exonuclease I (Exo I) and shrimp alkaline phosphatase (SAP) [Specific primers, Wen-cox F3 (se (SAP) . Purifiecox I) was selected for a comparison of genetic diversity with the parasites. Primers for amplification of partial cox I sequence (~800 bp), FishF2 and VF2_t1, were adopted from [Wenyonia.In fish, the same mtDNA locus , 0.625 μl of EcoRI-A and MseI-C primers (10pmol), 0.1 μl BSA (1mg/μl), 1.25 μl dNTPs (8mM), 4.6 μl ultra pure water and 0.05 μl MangoTaq™ DNA Polymerase (Bioline) (5U/μl). Cycling conditions for preselective-PCR were as follows: denaturation for 1min at 95°C, followed by 45 cycles of 15s at 95°C, 15s at 55°C, 30s at 72°C; and completed by 7min at 72°C. Fragments were verified on a 1% High Resolution Agarose gel (Invitrogen). This step was followed by selective amplification with primers containing 3 selective nucleotides at their 3'—end. Forward primers were labeled with different fluorescent colours on their 5'—end (EcoRI-ANN* and MseI-CNN) [2 (50mM), 0.05 μl of EcoRI-ANN* fluorescent labeled primer (10pmol), 0.07 μl of MseI-CNN (10pmol), 0.1 μl of BSA (1mg/μl), 0.65 μl of dNTPs (8mM), 6.52 μl of MQ water and 0.1 μl of MangoTaq DNA Polymerase (Bioline) (5U/μl). Cycling conditions for selective PCR were as follows: denaturation for 2min 94°C, followed by 10 cycles of 20s at 94°C, 30s at 66°C (decreasing by 1°C every cycle for 10 cycles), 2min at 72°C; then 20 cycles of 20s 94°C, 30s at 55°C, 2min at 72°C and completed by 15min at 60°C. Amplified fragments were checked on 1% High Resolution Agarose gel (Invitrogen) and analyzed on ABI3730XL sequencer by Macrogen Inc. . Primer combinations (Wenyonia [Synodontis [Restriction and ligation of genomic DNA was performed using AFLP Core Reagent Kit (Invitrogen) and following the manufacturer’s manual. To reduce the number of fragments in the mixture, ligated DNA fragments were amplified by PCR (Pre-selective PCR) using primers complementary to the adapter and restriction site sequence extended with an additional selective nucleotide at their 3'—ends (EcoRI-A and MseI-C) . The PCRseI-CNN)  to allowinations  were choWenyonia –42 and fnodontis ,43,44.Sequences were assembled, inspected for errors and aligned using GENEIOUS Pro software package version 6.1, software MAFFT ,46. Due As suggested for the coding genes (e.g. ), we assBI analyses were performed by software MrBAYES, run for 20 million MCMC generations, with four chains, three independent runs and were performed under the selected partition models; the coherence of each run was checked using software TRACER v1.5 . ML analWenyonia dataset were rooted using sequences of W. minuta, representing the closest available sequence from Caryophyllidae.All phylogenetic topologies (BI and ML) of To examine the evolutionary relationships among haplotypes in populations of each parasite and host species statistical parsimony networks based on pairwise differences were constructed using PopART v1.7 .Pi), Haplotype diversity (Hd), Tajima’s test (D) and Fu & Li’s test (D) were calculated using DNASP v5 [D values were tested by 10,000 coalescent simulations [To characterize the diversity of populations and their demographic history we performed several population genetic statistics for parasite and host mitochondrial datasets. Statistics of nucleotide genetic diversity , which was based on Nei’s genetic distances of markers, was computed in GenAlEx to visualize any emerging patterns of genetic structure in populations. To quantify the level of genetic variation between populations explained by geography were carried out in GenAlEx using AMOVA. Calculations were performed for host and parasite data from the Turkana freshwater and saline localities. The significance of the estimations was obtained with 999 permutations of the data. To estimate the number of population clusters or groups (K) in the dataset a Bayesian analysis was carried out using the software STRUCTURE v2.3.3 [Wenyonia and from one to nine for Synodontis. The number of MCMC generations and burn in for both datasets was 3 million and 300,000, respectively. Runs were performed for both models of population history (admixture and noadmixture). Mean value of posterior probabilities, L(K), was determined for each K value. Since L(K) did not reveal a sharp peak, the rate of change between posterior probabilities of successive runs . The thresholds were set for each primer combination . Each thE v2.3.3 . STRUCTUtistics, ) was caltistics,  and graptistics, .Wenyonia spp. as follows: W. virlis—148 samples from the Turkana-freshwater site, 102 from the Turkana-saline site, 50 from the White Nile, 7 samples from the Blue Nile, 1 sample from the Atbarah River; 4 samples of W. minuta; 13 samples of W. youdeoweii. For Synodontis spp.,120 sequences (604 bp) representing 20 haplotypes were obtained: 32 samples from the Turkana-saline site , 39 from the Turkana-freshwater site , 10 from the Turkana-medium site , 14 samples from the White Nile , 21 samples from the Blue Nile ; 6 samples of S. nigrita (Wenyonia absent).A total of 347 sequences (990 bp) representing 209 haplotypes were obtained from W. youdeoweii in obtained phylogenies  and partition schemes (PS) differed in the position of logenies . In MMS,W. youdeoweii, the information obtained for W. virilis was similar in both analyses. Samples of W. virilis formed four groups. The resulting groups almost exclusively contained samples from either the Nile or the Lake Turkana. Neither of the basins formed mutually monophyletic clades, the Turkana groups were embedded in the Nilotic clades. The most basal W. virilis clades comprised exclusively samples from the Nile. The group derived from them was formed by individuals from the saline part of Lake Turkana. A second Nile cluster was located in the centre of the tree crown. The phylogenetically most derived group consists of samples from the freshwater part of Lake Turkana. This result supports the hypothesis that the Nile represents the ancestral population and the Turkana basin was subjected either to repeated colonization, or to bottlenecks reducing ancestral diversity of the lineages.Regardless of the differences in position of W. youdeoweii was also revealed by ML analyses  only haplotypes organized into networks separated by multiple mutations without a star-like patterns—a pattern typical for older populations in equilibrium , an analysis of with the dataset split into individual localities revealed that the Lake Turkana population originated in the White Nile  and independent colonization of the Blue Nile as well as of the freshwater and saline areas of Lake Turkana from the White Nile (hypothesis 8). Similarly, according to the gene flow and migration analyses of Synodontis, the ancestral population was located in White Nile from where the colonization wave spread to the Blue Nile and Lake Turkana (hypothesis 3). Within Lake Turkana, the freshwater area was colonized first, while saline and medium salinity areas were populated separately. However, this colonization sequence is not completely testable for parasites due to their low prevalence in the medium salinity part of Lake Turkana .The likelihood scores and probabilities of the hypotheses tested using MIGRATE software are shown in W. youdeoweii and W. minuta samples, which did not create separate units  revealed that the majority of variation occurred within the sample sites for all datasets . Among sites the population structure (Turkana vs. Nile) explained only 10% of variance for Wenyonia virilis and 7% of variation for Synodontis spp. Among sites the population structure between the Turkana freshwater and saline part explained 11% variation for Wenyonia virilis and 2% for Synodontis spp.  was estimated by using the delta K statistics (DK). The number of clusters in the parasite dataset was K = 5 for the admixture model of population history  and K = the Nile . The NilWenyonia youdeoweii and W. minuta did not separate from W. virilis.Clusters, which are less frequent in the Nile , showed an increased proportional presence in Lake Turkana, concordant with the hypothesis of the Nilotic origin of the Turkana populations. The presence of different Nile clusters in the freshwater and saline parts of Lake Turkana might reflect multiple colonization events. Similar to the PCoA, AFLP clusters obtained in STRUCTURE did not match with specific mtDNA haplogroups. S. nigrita did not show a tendency to cluster separately and shared clusters with Synodontis samples from the White Nile.In the host dataset, results distinguishing the four clusters , is striking. We were not able to provide an exact calculation of the difference in the mutation rates due to the character of our data. Methods used for such estimations rely on clade to clade comparisons (e.g. *BEAST [Wenyonia virilis dataset is between 100–95.5% vs. 100–97.3% for Synodontis). An increased mutation rate in parasites is a common feature [Wenyonia-Synodontis model represents the only example documented in metazoan endoparasites, as most other examples include exclusively ectoparasites and Apicomplexa [The markedly faster rate of molecular evolution reflected by an increased sequence diversity of . *BEAST ), wherea feature ,71 and a feature . However feature ,74. Howe feature –77, the complexa ,72,78,79Both mtDNA analyses showed that tapeworms from the Nile formed two separate groups Figs  and 4a. A similar pattern to AFLP data was seen in the PCoA results. Despite poor population structure resolution the clear separation of a cluster comprising solely Lake Turkana samples  asteriskThe AFLP data were structured into 5 clusters; only one of them (magenta) was unique and occurred in both the saline and the freshwater part of Lake Turkana. The abundance of the unique Turkana cluster  was not Synodontis populations revealed by both mtDNA and AFLP data might be well explained by genomic admixture among multiple founding populations, i.e. lineage fusion. A phenomenon characteristic for some taxa in re-colonized insular biogeographic systems, such as in giant tortoises Chelonoidis becki from Galápagos Islands [In contrast to the parasite, the multiple colonization events in Lake Turkana coupled with the marked similarity of the Nile and Turkana  Islands ,81. ThusWenyonia virilis populations were most probably widespread, whereas under current conditions they are restricted to areas where suitable, presumably freshwater, intermediate hosts are available. This assumption is strongly supported by the near absence of Wenyonia spp. in the medium salinity part of Lake Turkana that lacks permanent freshwater habitats. The presence of freshwater springs in the saline part of Lake Turkana [Wenyonia tapeworms, confirm that at least locally a suitable (presumably freshwater) intermediate host is also present in the saline part of the lake. As there are no physical obstacles to host migration in Lake Turkana, isolation by adaptation can better explain the extent of the tapeworm diversification rather than isolation by distance [Wenyonia (haplo) groups might be caused by their different environmental requirements, possibly including the role of the intermediate host(s).Following the end of the Pleistocene megadrought hypersaline conditions, the Turkana basin underwent severe environmental oscillations. During the Holocene freshwater periods,  Turkana , togethedistance –84. The Wenyonia population to a particular part of the lake, makes adaptation of the two W. virilis subpopulations to the saline or freshwater conditions per se unlikely.The revealed restriction of the ‘freshwater’ subpopulation to a freshwater refugium of the Omo delta (and perhaps lower Omo) could be explained by highly saline conditions throughout most of the open lake. However, restriction of the ‘saline’ Wenyonia spp. in an individual Synodontis hosts in both basins [The documented, but quantitatively slight, geographical overlap between freshwater and saline haplogroups, i.e. sporadic occurrence of tapeworms of the freshwater haplogroup in the saline part of the lake, might be explained by migration of hosts within the lake . This inh basins  make comIn fact, the pattern observed in the Lake Turkana parasite population might reflect an uneven or non-overlapping distribution of different intermediate host species, to which individual tapeworm subpopulations might have adapted.Hence, our data suggest that the salinity causes, though possibly indirectly, the apparent ecological and near-complete geographical segregation of parasite subpopulations. This might indicate that within a single (isolated) limnic system, salinity might facilitate sympatric speciation by means of ecological segregation of subpopulations triggered by the presence of physiochemically contrasting freshwater and saline environments. Analogical processes leading to the emergence of a salinity gradient affected many African basins, and thus could have a fundamental, yet overlooked, influence on the evolution of limnic organisms throughout the Sub-Saharan Africa and elsewhere.The indication of multiple, at least two, colonization events has been shown herein by both markers. Two migration events are reflected in our dataset by the occurrence of multiple mt haplotypes in individual localities. Importantly, AFLP data are showing on-going segregation in freshwater and saline parasite (sub)populations that were probably established prior to the last colonization. However, this separation is still incomplete and population patterns shared between the Nile and Lake Turkana indicate that the last ~11 ky were not long enough to completely segregate the tapeworm populations.Our finding of almost exclusively ‘freshwater’ and ‘saline’ tapeworm subpopulations with no apparent gene flow between them represents the first described case of allopatric differentiation (lineage fission) in a clearly sympatric system in the case of endoparasites .Compared to previous studies, which successfully used AFLP for a variety of purposes including evolutionary studies of populations, drug sensitivity or detection of inbred individuals ,87–90, AWenyonia and Synodontis species were clearly differentiated by mtDNA data. Contrary to our expectations, the AFLP data reflected the interspecific genetic differentiation obtained from mtDNA only to a very limited degree, distinguishing S. nigrita in the host dataset but failing to clearly separate any of the three Wenyonia species. Similar to outcomes documented in insects [W. minuta with only 2 specimens available). However, it is certainly not the case in W. youdeoweii for which a representative population sample was obtained. Thus, it remains unknown whether the AFLP differences found in the Lake Turkana (sub)populations are directly associated with particular loci that are important for the development of differentiation/segregation between ‘freshwater’ and ‘saline’ populations, or not. Therefore, although we cannot rule out that the observed changes in genetic diversity have little or nothing to do with segregation, it is possible that we in fact demonstrate early evolutionary changes associated with it.Moreover, individual  insects  and attrWenyonia samples from Lake Turkana. Moreover, the signal of the ancestral gene flow contained in the mtDNA data was similar for both organisms and provided valuable information about historical changes in species distributions. Therefore, the suitability of AFLP data to elucidate one of the main questions of this study, i.e. significance of the salinity gradient itself, remains unanswered. Compared with other studies this study is based on a sufficiently high number of isolated loci . DespitDespite the common origin of the Lake Turkana populations in the Nile, the population genetic pattern observed in hosts implies the fusion of multiple colonisation waves, contrasting with the lineage fission (segregation) in its parasite. This pattern might be explained by ecological permeability of the specific environment in which the saline part of Turkana poses a barrier for a parasite dependent on freshwater intermediate host(s), while allowing free dispersal of the definitive fish host. The parasite populations exhibited markedly higher molecular evolutionary rates compared to the hosts, providing a rare example of the long-discussed theory of rapid evolution in parasites compared to their hosts. Although AFLP and mtDNA showed similar patterns in both host and its parasite, mtDNA provided a remarkably higher resolution of population structure, historical gene flow, evolutionary patterns, and inter- and intra-specific genetic differentiation.S1 TableThresholds were individually set for each AFLP primer combinations.(XLSX)Click here for additional data file.S1 Figcox I Wenyonia spp. for a) the model of molecular evolution computed by PHYML; b) the best-fit partitioning schemes carried out in Garli. Branches are collapsed into groups, which correspond to sampling locations. Statistical support for each group was generated from Likelihood bootstrap proportions.Phylogenetic tree of (TIFF)Click here for additional data file.S2 FigWenyonia spp. (a) and Synodontis spp. (b) and noadmixture of parasite (c) and host (d).ΔK results for historical models admixture of (TIFF)Click here for additional data file.S3 FigWenyonia spp. (a) and Synodontis spp. (b) as revealed by Bayesian inference of population structure. Each colour represents one assumed population cluster K. Multiple coloured bars display an individual’s estimated membership proportion in more than one population (q), i.e. noadmixture. Turkana—medium 1–3 refers to three different localities: 1, Central Island; 2, Kerio River delta; 3, Kalokol.Individual-based cluster representation of all sampled (TIFF)Click here for additional data file.


Cercospora isolates collected from Beta vulgaris  in the USA and Europe. Cercospora beticola was confirmed as the species predominantly isolated from leaves with Cercospora leaf spot (CLS) symptoms. However, C. cf. flagellaris also was detected at a frequency of 3% in two table beet fields in New York. Resolution of the spatial structure and identification of clonal lineages in C. beticola populations using genome-wide single nucleotide polymorphisms (SNPs) obtained from GBS was compared to genotyping using microsatellites. Varying distance thresholds  were used for delineation of clonal lineages in C. beticola populations. Results supported previous reports of long distance dispersal of C. beticola through genotype flow. The GBS-SNP data set provided higher resolution in discriminating clonal lineages; however, genotype identification was impacted by filtering parameters and the distance threshold at which the multi-locus genotypes (MLGs) were contracted to multi-locus lineages. The type of marker or different filtering strategies did not impact estimates of population differentiation and structure. Results emphasize the importance of robust filtering strategies and designation of distance thresholds for delineating clonal lineages in population genomics analyses that depend on individual assignment and identification of clonal lineages. Detection of recurrent clonal lineages shared between the USA and Europe, even in the relaxed-filtered SNP data set and with a conservative distance threshold for contraction of MLGs, provided strong evidence for global genotype flow in C. beticola populations. The implications of intercontinental migration in C. beticola populations for CLS management are discussed.Genotyping-by-sequencing (GBS) was conducted on 333  Understanding the genetic structure and evolutionary trajectory of pathogen populations in agroecosystems is fundamental to sustainable disease management . PopulatAlternatively, single nucleotide polymorphisms (SNPs) offer genome-wide coverage; and confer stable inheritance and analytical simplicity . HoweverThe advent of reduced-representation sequencing (RRS) methods  that facAn essential step in population genomics analyses using RRS genotyping techniques is filtering of poor quality reads and loci with low read depth, low minor allele frequency and a high proportion of missing data . HoweverCercospora beticola Sacc. is a haploid fungus and the cause of Cercospora leaf spot (CLS) on Beta vulgaris L.  worldwide. Previous population genetic studies using microsatellite markers uncovered cryptic recombination and high genetic diversity [C. beticola populations, yet also revealed the predominance of multiple clones in New York and Hawaii [C. beticola in its asexual form, i.e., genotype flow [C. beticola are reported to be dispersed by water or wind over short distances [iversity –38 in C.d Hawaii –38. Discistances ,40, longistances ,42, seedistances ,43,44, oistances ,43. The C. beticola may also have been a function of the low power of the 12, microsatellite loci to discriminate non-identical genotypes. In addition, due to the high mutation rate of microsatellite loci, identical multi-locus genotypes may arise through convergent evolution (homoplasy), and not be identical by descent [e.g., SNPs, and more refined genotyping methods such as GBS that provide thousands of markers and greater resolution of clonal structure may improve our understanding of genotype flow in C. beticola populations.Detection of genotype flow in microsatellite population genetics studies of C. beticola populations using microsatellites [poppr [C. beticola populations, and assessed the impact of various filtering strategies and distance thresholds on the estimation of clonal diversity and genotype flow. A complementary objective was to compare measures of clonal diversity, differentiation and structure of C. beticola populations obtained from both genotyping approaches.The primary objective of this study was to investigate the occurrence of global genotype flow in tellites ,33 and Gtellites . We useds [poppr ,45 for dCercospora isolates sampled from B. vulgaris  in the USA and Europe were included in this study (2) table beet fields with at least 2- to 3-year rotations with non-host crops. The C. beticola isolates from Michigan, North Dakota and Europe were obtained from personal collections (LEH and GAS). The identity of all isolates was confirmed as C. beticola using PCR primers CercoCal-beta and CercoCal-R [In total, 333 is study . The poprcoCal-R .n = 4), North Dakota (n = 12), and Europe (n = 25), fragment analysis, and microsatellite allele calling was conducted as described by Vaghefi et al. [poppr [C. beticola isolates collected from New York (n = 225) and Hawaii (n = 67) [Amplification of 12 SSR loci in the isolates from Michigan  .Pst1; oligonucleotide adapters were ligated onto restriction fragments; samples were pooled, enriched by PCR, and sequenced (100 bp single-end) on an Illumina Hi-Seq2500 sequencer . Due to its dependence on digestion with restriction enzymes, the GBS method developed by Elshire et al. [DNA extraction of single-conidium-derived isolates was conducted on lyophilized mycelial tissue as described by Vaghefi et al. . DNA inte et al.  is highlCercospora isolates were genotyped six to eight times  using tNew York ). Only sNew York  and VcftNew York  on the LA preliminary exploratory analysis was conducted on the entire data set using principal component analysis (PCA) in TASSEL. Genotypes were converted to numeric scores and missing data was imputed to the mean score for each site. The resulting eigenvalues were visualized within a scatter plot.C. beticola is haploid, all heterozygous sites derived from sequencing or SNP calling errors were recoded as missing. The data set was further filtered using two approaches; i) relaxed filtering for a minimum minor allele frequency of 0.01 and a maximum of 0.25 missing data for each locus; and ii) stricter filtering for a minimum locus-by-individual (genotype) read depth of three, minimum minor allele frequency of 0.01, and a maximum of 0.10 missing data for each locus, i.e., only loci with at least 90% coverage in all isolates were retained. These two SNP data sets are referred to as the “relaxed-filtered” , and all genotypes with the estimated distance threshold were collapsed into the same multi-locus lineage (MLL). In the second approach, the average bitwise distance among the replicated DNA samples was used , herein referred to as the “relaxed-filtered data set 1”; 2) relaxed-filtered contracted using a larger distance threshold (1.298 × 10−3) based on the average distance among replicated DNA samples, herein referred to as the “relaxed-filtered data set 2”; and 3) strictly filtered data set contracted with the distance threshold of zero. All subsequent analyses were conducted on the contracted data sets.Sequencing and scoring errors, somatic mutations, and missing data may inflate the number of clones by assigning individuals belonging to the same clone to separate MLGs . To redur v. 2.0 . The micr v. 2.0  “farthese) [poppr. For the microsatellite data set, allelic richness (Ra) was estimated with rarefaction in ADZE v. 1.0 [Psex in GenClone 2.0 [For the SNP and microsatellite data sets, Nei’s measure of allelic diversity (He) , the nume)  correcteE v. 1.0 . Pearsonlone 2.0 , and staD) [GST [FST [mmod [adegenet [hierfstat [ade4 [mmod, with 999 permutations, to quantify associations between values of D, GST and FST obtained from the microsatellite and SNP data sets. Discriminant analysis of principal components (DAPC) among C. beticola populations was conducted using adegenet [xvalDapc function.Jost’s measure of population differentiation (D) , pairwisD) [GST  and pairGST [FST  were estST [mmod  implemenadegenet , and hieierfstat . The Manierfstat  was perfat [ade4  implemenadegenet . The optK) and assignment of individuals to each cluster without a priori assumption of populations were estimated using the program, STRUCTURE [K = 1–10. Each model was simulated five times with 100,000 iterations and a burn-in period of 10,000 Monte Carlo Markov Chains. The optimal number of clusters was chosen by computing Evanno’s ΔK [K were combined using CLUMPAK [The number of genetic clusters  included 27,838 SNPs, which reduced to 19,126 SNPs after initial filtering by the IGD. Further filtering of the entire data set for minor allele frequency of at least 0.01, and minimum 80% coverage of loci resulted in 7,431 SNPs.Cercospora cf. flagellaris, and were not included in subsequent analyses.PCA using the entire data set  detected two distinct clusters of individuals , separatFor the relaxed-filtered data set, 2,696 SNPs were retained in 319 DNA samples ; and 4.89% of the data set was missing. Strict filtering parameters retained 1,631 SNPs in 322 DNA samples , resulting in 1.35% missing data.−4 to 1.855 × 10−3 . Using the average bitwise distance among the replicated DNA samples as the threshold resulted in 166 MLLs within the 307 individuals  included 307 MLGs. Collapsing the data set using the more conserved threshold estimated by i.e., 32 individuals had the same genotype at all 1,631 SNPs loci. The distance threshold estimated by the cutoff_predict function and maximum distance among the replicated DNA samples were estimated as zero. Therefore, the strictly filtered SNP data set was only contracted once, collapsing all the individuals with a bitwise distance of zero to the same MLL, resulting in 111 MLLs  included 275 MLGs, 111 MLLs .C. beticola populations from New York. MLLs 46 and 108 were shared between different states within the USA. Three MLLs were shared between New York and Europe, all of which occurred in Farm 2 . The probability of the recurrent MLLs having originated from independent sexual events was ≤ 0.003 for all microsatellite MLLs.Of the 120 MLLs identified using microsatellites, 43 were recurrent and nine were shared among populations . MLLs 98The strictly filtered SNP data set (111 MLLs) included 46 recurrent MLLs and nine were shared among populations from different locations . Four MLOf the 235 MLLs detected in the relaxed-filtered data set 1, 46 were recurrent and four were shared among populations. Three MLLs were shared among various farms and fields within New York, while one MLL occurred in both Farm 2 and England . Of the e) and richness estimated using microsatellite loci were not significantly correlated with the He obtained from the SNP data sets   . A signi> 0.085) . Simpson> 0.085) .D = 0.06, GST = 0.05, FST = 0.06) while the populations from the mixed-cropping farms were more differentiated from each other  and the other two fields   and North Dakota , but higher differentiation when compared to other populations  within New York  and Farm 1 in New York clustered together, and individuals from Farm 2 clustered with isolates from Europe and North Dakota  with an error rate of 0.01 [−4 to 1.855 × 10−3 among replicated samples. In contrast, strict filtering parameters resulted in an error rate of zero. It has been suggested that higher mismatch rates among replicates are associated with lower read depth [C. beticola, filtering the SNP data set for a minimum locus-by-individual read depth of three was sufficient to reduce the mismatch rate of replicated samples to zero. Stringent filtering approaches are especially critical for population genomics analyses that rely on individual identification and delineation of clonal lineages [The SNP data sets provided higher resolution in identification of MLGs compared to microsatellites but also greater error rates . A previ of 0.01 . Here, w of 0.01 . Geneticad depth . For dipad depth ,70. For lineages –71.Higher error rates and resolution of GBS approaches can substantially inflate the number of MLGs ,20. EvenC. beticola across two continents strengthens the argument for genotype flow [Detection of repeated MLLs of ype flow ,38. EvenCercospora beticola has been associated with raw sugar beet seed  [C. beticola on sugar beet seed [C. beticola on table beet seed lots in New York is also unknown. Commercially available table beet seed is not polished to remove the exterior corky layer as is done in sugar beet seed to enhance germination and reduce pathogen contamination. The seed planted in the monoculture fields in New York (Fields 3 and 5) originated from Skagit Co., Washington State, USA, where occurrence of C. beticola in seed crops is rare [C. beticola populations from table beet monoculture fields in New York is not a result of contaminated seed, transfer by agricultural machinery [A potential means of long distance migration of clonal lineages is contaminated seed.  balls’)  and popu balls’) ,44. Howeeet seed ,73; and  is rare . If the achinery ,42 or inachinery ,43 may aC. beticola inoculum in table beet and sugar beet fields is most likely to be alternative weedy hosts or volunteers [Cercospora beticola is reported to persist for 22 months to over three years on infested plant debris [C. beticola-infested field soil, respectively [C. beticola is capable of sexual reproduction, due to its heterothallic nature [C. beticola is international trade of diseased alternative hosts. For example, Groenewald et al. [C. beticola from Chrysanthemum spp. suggesting that trade in cut flowers and ornamentals could be involved. Evidence for long distance migration of C. beticola genotypes provided here warrants further investigations on potential seedborne inoculum as a means of dispersal.The predominant source of lunteers ,75, infelunteers ,77 or solunteers . Cercospt debris ,77, and ectively . CLS epiectively ,40. The ectively –81. Evenc nature , ascospoc nature . Thus, ad et al.  reportede and λ) were not associated between different marker systems, there was significant correlation among the number of clonal lineages and clonal fraction estimated from microsatellite and SNP data sets, which led to similar clonality rankings of populations across data sets. The population in Hawaii was the most clonal while the European population had the highest diversity. This is most likely an artefact of sampling strategies as the population from Hawaii was isolated from one community garden while the isolates from Europe were collected from a broad geographical area. Lack of significant correlation between expected heterozygosity obtained from microsatellites (SSR-He) and SNPs (SNP-He) has been reported, and may be due to the restricted genome coverage of microsatellites [Although measures of genetic diversity  obtained from the microsatellite and SNP data sets varied, however, there was a strong, significant correlation between the indices of differentiation, supporting results of other studies [C. beticola population is not panmictic within New York, nor worldwide, providing evidence for restricted dispersal of inoculum.Absolute values of population differentiation Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S1 File(VCF)Click here for additional data file.S2 File(VCF)Click here for additional data file.


Spheniscus demersus, is listed as Endangered by the IUCN Red List of Threatened Species due to the drastic reduction in population numbers over the last 20 years. To date, the only studies on immunogenetic variation in penguins have been conducted on the major histocompatibility complex (MHC) genes. It was shown in humans that up to half of the genetic variability in immune responses to pathogens are located in non-MHC genes. Toll-like receptors (TLRs) are now increasingly being studied in a variety of taxa as a broader approach to determine functional genetic diversity. In this study, we confirm low genetic diversity in the innate immune region of African penguins similar to that observed in New Zealand robin that has undergone several severe population bottlenecks. Single nucleotide polymorphism (SNP) diversity across TLRs varied between ex situ and in situ penguins with the number of non-synonymous alterations in ex situ populations (n = 14) being reduced in comparison to in situ populations (n = 16). Maintaining adaptive diversity is of vital importance in the assurance populations as these animals may potentially be used in the future for re-introductions. Therefore, this study provides essential data on immune gene diversity in penguins and will assist in providing an additional monitoring tool for African penguin in the wild, as well as to monitor diversity in ex situ populations and to ensure that diversity found in the in situ populations are captured in the assurance populations.The African penguin,  Spheniscus demersus, is endemic to southern Africa with breeding sites distributed at 28 locations in South Africa and Namibia [The African or “jackass” penguin,  Namibia , 2, 3. T Namibia . In 2010 Namibia  due to t Namibia , 7. Popu Namibia . Additio Namibia . The inc Namibia , 13.ex situ African penguin population was found to be comparable to the in situ populations in terms of Ho, He and HZ [in situ populations of penguins and in several cases the identification of the causative agent has been unsuccessful [ex situ penguins for example [TLR1-13) and have been organised into six major groups based on phylogenetic analysis namely; TLR2 group , TLR3 group, TLR4 group, TLR5 group, TLR 7/8/9 group and TLR11 group  [TLR1LA, TLR1LB, TLR2A, TLR2B, TLR3, TLR4, TLR5, TLR7, TLR15 and TLR21) have been reported of which four genes  have orthologs in other vertebrate groups [TLR15 appears to be unique to avian and reptile species [TLR2.It has been hypothesised that in order to maintain population fitness, a population requires high genetic diversity. Low genetic diversity has long been associated with inbreeding depression and a reduction in the survival of species , 15. Cone and HZ . Howevere and HZ . Taking e and HZ , 19, 20.ccessful . The Afr example . In addi example , Newcast example  and papi example . Sequenc example . Express example . In mamm 12, 13) . Thus fa species , 30, howin situ and ex situ African penguins to gain a more comprehensive understanding of innate immunity, as well as to develop new measures of functional diversity to assist in the management of the species. There are several genetic concerns that should be taken into account for the management of ex situ penguin populations. Since ex situ populations are derived from a small number of individuals, these populations face the similar threats to small and isolated natural populations which may jeopardise the ability of ex situ populations to reproduce and survive when returned to the wild. In addition, research has demonstrated that inbred individuals have lower resistance to disease [ex situ populations. TLR1LA, TLR1LB, TRL2, TLR5 and TLR7 were targeted in order to encompass an array of ligand/pathogen-associated molecular patterns (PAMPs) specificities, namely di-and triacylated lipoproteins found in the cell wall of bacteria, fungi and parasites recognised by TLR2 and members of the TLR1/6/10 family, flagellins of flagellated bacteria recognised by TLR5 and single-stranded viral RNA detected by TLR7 [ex situ and in situ African penguin populations will show a reduced variation at the majority of the TLR loci due to the significant population declines and bottlenecks. To our knowledge this is the first study to analyse TLR diversity in African penguin populations.In this study, we determined the levels of TLR diversity in both  disease . Thus fu by TLR7 , 35, 36.in situ colonies (Blood samples were collected from 20 African penguins in South Africa from three breeding facilities namely: Two Oceans Aquarium (n = 7), uShaka Marine World (n = 6) and National Zoological Gardens of South Africa . Currently, penguin populations are being kept in zoo and aquarium facilities throughout South Africa. As part of the management plan for this species, a Pan-African Association of Zoos and Aquaria (PAAZA) regional studbook is maintained by the NZG. The African regional studbook for the African penguin uses the Single Population Analysis and Record Keeping System (SPARKS) developed by the International Species Information System (ISIS) and the PM2000 database programme. Based on studbook information, only unrelated adult birds were selected and were included in this study. In addition, 21 samples were collected by SANCCOB from colonies  at the f™ -Tissue Miniprep kit (Zymo Research), according to the manufacturer’s protocol. Primers developed for members of Apterygiformes, Gruiformes, Psittaciformes and Passeriformes [TLR1LA, TLR1LB, TLR2, TLR5 and TLR7. Amplification was carried out in separate PCR reactions consisting of 1 × DreamTaq Green PCR Master Mix, 0.4 μM of each primer, and approximately 20 ng template DNA in a total volume of 20 μl. The temperature profile was as follows: an initial denaturation at 95°C for 3 min, 35 cycles of 95°C for 30 s, 53–58°C for 30 s, and 72°C for 1 min, followed by a final extension at 72°C for 10 min. Successful PCR products were purified with Exonuclease I and FastAP (Thermo Fisher Scientific Inc.). Gene fragments were sequenced in both directions using the BigDye Terminator v3.1 Cycle Sequencing Kit and visualised on a 3500 Genetic Analyzer (Applied Biosystems). Sequence chromatograms were edited and assembled using Geneious v.8.0.3 (created by Biomatters).DNA extraction was conducted using the ZR Genomic DNAriformes  (S1 Tablo), mean expected heterozygosity (He), and unbiased expected heterozygosity (Hz) were determined using GenAlEx [Differences in mean observed heterozygosity , Carpodacus mexicanus , Falco naumanni , Petroica austrakis rakiura , Aptenodytes forsteri , Pygoscelis adeliae  and Fulmarus glacialis , obtained from NCBI Genbank to facilitate a more robust phylogenetic analyses. Distance-based analyses  of the final dataset was conducted in MEGA v.6.06 using p-distance estimates with nodal support being assessed through 10 000 non-parametric bootstrap replications.Sequence alignments were generated using Clustal W  in BioEdSynonymous and non-synonymous SNP variations were determined by translating the TLR gene nucleotide sequences to the longest open reading frames. The identity and integrity of the respective amino acid sequences were confirmed by standard protein BLAST. Amino acid variations were visually inspected using BioEdit v.7.0.9.0 .TLR1LA, TLR1LB, TLR2, TLR5 and TLR7 amplified in all penguin samples  TLR gene sequences [Petrocia australis rakiura) [TLR7 was observed in this study. Due to the amplification of a TLR7 pseudogene, evidenced by the presence of premature stop codons, subsequent analyses of TLR7 was consequently omitted. An excess of heterozygosity at SNPs within the TLR1LA, TLR1LB, TLR2 and TLR5 gene regions was not observed providing evidence that duplicate copies are either not present or were not amplified in the case of these genes for the African penguin. In addition, it is unlikely that pseudogenes were co-amplified as there was an absence of stop codons and disrupted reading frames [Genes  samples . Based oequences , the sucequences , 41, 42.rakiura) , co-amplg frames . All SNPTLR1LA shares a 92% sequence identity to lesser kestrel ; TLR1LB shares a 97% sequence identity to Emperor penguin (Aptenodytes forsteri) and a 91% sequence identity to lesser kestrel . TLR2 shares a 97% sequence identity to both emperor penguin (Aptenodytes forsteri) and Adelie penguin (Pygoscelis adeliae) and a 94% sequence identify to northern fulmar . TLR5 shared a 99% and 98% sequence identity to two penguin species, namely emperor penguin (Aptenodytes forsteri) and Adelie penguin (Pygoscelis adeliae), respectively, and a 96% sequence identity to northern fulmar . Conservation of these regions among a wide range of bird species  as well as more common species; house finch (Carpodacus mexicanus) and lesser kestrel  (Carpodacus mexicanus) has undergone a brief but severe demographic bottleneck that was followed by population growth and range expansion [Falco naumanni) has experienced population declines and has been reported to be extinct in several locations throughout its breeding range resulting in fragmented populations with restricted gene flow due to isolation [Petroica australis rakiura) has experienced several severe bottlenecks. The New Zealand robin found on Stewart Island has experienced two bottlenecks over the last four centuries [h = 2–4, π = 0.0002–0.0020) and New Zealand robin  were comparable and were low compared to more common species; house finch  and lesser kestrel  . House fxpansion . The lessolation . Levels solation . New Zeaenturies . DiversiN) and synonymous (dS) alterations. Non-synonymous alterations (encoding different amino acid residues) were observed in all loci analysed for the in situ African penguin populations (N/dS = 6.33) and in the ex situ populations (dN/dS = 3.86). Non-synonymous alterations have been reported in African penguin (dN/dS = 16) for the MHC class II DRB-like gene [In this study we were able to determine the number per site of non-synonymous  and in situ  populations were similar (ex situ populations (n = 14) is slightly reduced in comparison to in situ populations (n = 16). It has been postulated that diversity in TLRs is required for genetic fitness and long term survival, thus it is of critical importance that diversity of TLRs are captured in the assurance populations. The loss of functional genetic diversity at TLR genes in the African penguin ex situ population may indicate a loss of adaptive potential; however the importance of polymorphism of TLRs in comparison to other protein coding immune genes has not yet been determined. Further studies on the level of expression as well as the functional relevance of these loci in African penguin would have to be conducted. In order to ensure that the ex situ population does not experience an additional bottleneck it is of critical importance that alterations in adaptive genes such as TLRs are thus captured to inform optimal management.TLR polymorphisms varied between penguins . TLR2 anh sepsis  and susch sepsis , respect surface . Heteroz similar , howeverS1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.