The results showed high genetic diversity and pronounced genetic differentiation among the populations of the two species with a significant phylogeographical pattern , which imply restricted gene flow among the populations and significant geographical or environmental isolation. Ten chloroplast DNA (cpDNA) and eighteen nucleus ribosome DNA (nrDNA) haplotypes were identified and clustered into two lineages. Two corresponding refuge areas were revealed across the entire distribution ranges of O. longilobus and at least three refuge areas for O. taihangensis. O. longilobus underwent an evolutionary historical process of long-distance dispersal and colonization, whereas O. taihangensis underwent a population expansion before the main uplift of Taihang Mountains. The differentiation time between O. longilobus and O. taihangensis is estimated to have occurred at the early Pleistocene. Physiographic complexity and paleovegetation transition of Taihang Mountains mainly shaped the specific formation and effected the present distribution of these two species. The results therefore support the inference that Quaternary refugial isolation promoted allopatric speciation in Taihang Mountains. This may help to explain the existence of high diversity and endemism of plant species in central/northern China.Historic events such as the uplift of mountains and climatic oscillations in the Quaternary periods greatly affected the evolution and modern distribution of the flora. We sequenced the  During the last three million years, repeated glacial and interglacial cycles have greatly affected the landform and fauna of the total earth Phylogeographical analyses can provide an understanding of how paleo-environmental changes in landscape and climate have influenced species distributions and population demography Taihang Mountains locates on 35°19′–40°51′N and 113°10′–115°48′E. As a natural boundary mountain of the east, southeast of Shanxi province and Hebei and Henan provinces, it is the important mountain range and geographical boundary for eastern China. The northern part of Taihang Mountains is higher than its southern part. Most areas of Taihang Mountains are higher than 1200 meters. The uplift of Taihang Mountains, followed by the formation of high mountains and deep valleys within the plateau Molecular techniques have provided powerful tools for studying the phylogeography or migratory footprints of species Opisthopappus longilobus Shih and Opisthopappus taihangensis (Ling) Shih belong to Opisthopappus (Asteraceae). The genus Opisthopappus is endemic to China, and its wild distribution is mainly restricted to Taihang Mountains across the provinces of Shanxi, Hebei, and Henan, occurring on the slopes at an elevation of about 1000 m or in the cracks of the steep cliffs O. longilobus is mainly distributed in the province of Hebei, whereas O. taihangensis is found in the provinces of Shanxi and Henan O. longilobus and O. taihangensis. The leaf blade of O. longilobus is smooth and subcylindrical, and most stem and leaves are pinnatifid, with one pair of bracteal leaf. O. taihangensis, apprised pubescent on both surfaces of leaf blade, stem, and leaves, is bipinnatifid, with no bracteal leaf O. longilobus and O. taihangensis have been listed among the Class II State-Protected Endangered Plant Species O. longilobus and O. taihangensis are an ideal candidate for investigating the influences of Quaternary climate change in Taihang Mountains for the following reasons: (i) Geographically, O. longilobus and O. taihangensis are distributed only in Taihang Mountains, including Shanxi, Hebei, and Henan provinces. This geographic range may be advantageous for enabling investigation into whether the glacial refuges were maintained in Taihang Mountains during the last glacial maximum, or earlier cold periods. (ii) O. longilobus and O. taihangensis have intra-specific and endemic taxa in China that display visible phenotypic differences, which are important in exploring the incipient speciation caused by isolation provided by a glacial refuge. Finally, (iii) O. longilobus and O. taihangensis are an herbaceous plant and sensitive to environmental changes. In research on the effects of climate oscillations on plant evolution, it can represent the phylogeography of an herb, and can serve as a model to reveal the historical and evolutionary processes of such plants since the period of Quaternary climate change.O. longilobus and O. taihangensis; (2) elucidate the effects of the uplift of Taihang Mountains and the Quaternary climatic oscillations on the genetic structure, divergence and distribution of O. longilobus and O. taihangensis; (3) infer the possible refugia of O. longilobus and O. taihangensis across their whole distribution range.Thus, our objectives included the following: (1) explore the phylogeographical structure and the evolutionary history of This study was conducted in accordance with all People's Republic of China laws. No specific permits were required for the described field studies because all researchers collecting the samples had introduction letters from the College of Life Science, Shanxi Normal University, Linfen.Opisthopappus were investigated in this study, covering the entire distribution area on Taihang Mountains. The samples comprised five populations of O. longilobus and eight populations of O. taihangensis , and 0.6 mM of both forward and reverse primers. The PCR parameters for all amplification programs of ITS and cpDNA were as follows: 4 min of pre-denaturation at 94°C, followed by 34 cycles of 30 s of denaturation, 40 s of annealing (49.2°C for ITS or 58.8°C for trnL-trnF or 59.8°C ndhJ–trnL), 1 min 20 s of elongation at 72°C, and a final elongation step of 7 min at 72°C. PCR products were purified using the Wizard PCR Preps DNA purification system  following the manufacturer's instructions. Cycle sequencing reactions were conducted using the purified PCR product, AmpliTaq DNA polymerase, and fluorescent BigDye terminators. The sequencing products were analyzed using an ABI Prism 310 DNA sequencer .The h) and nucleotide diversity (π) were calculated for each population  and at the species level  using DNAsp hS), total diversity (hT), geographical total haplotype diversity (VT), geographical average haplotype diversity (VS), level of population differentiation at the species level (GST), and an estimate of population subdivisions for phylogenetically ordered alleles (NST). We further tested the phylogeographical structure at the species range between (NST) and (GST) by using the U-statistic. An NST value higher than the GST value indicates that closely related haplotypes are observed more often in a given geographical area than would be expected by chance The sequences were edited manually based on the chromatograms and aligned by CLUSTAL X K) that are geographically homogenous and maximally differentiated from each other. In this analysis of haplotypes, K varied from 2 to 13, with each simulation starting from 100 random initial conditions. An FCT index of genetic differentiation among initial K groups was computed, followed by an iterative simulated annealing process to obtain the optimal configuration of groups and final FCT values. The simulated annealing process was repeated 1000 times. The configuration with the largest FCT value among the 100 tested was retained as the best grouping of populations.To quantify the genetic differentiation partitioned among different groups and total genetic variance, analyses of molecular variance (AMOVA) were carried out using ARLEQUIN Genealogical relationships between haplotypes were inferred from a maximum parsimony median-joining network calculated in NETWORK 4.5.0.2 8 generations were carried out, with sampling at every 1000 generations. The first 25% of sampled trees were discarded as burn-in, and the remaining trees were used to construct a Bayesian consensus tree. The convergence of chains was checked using Tracer 1.5 The time of the most recent common ancestor (TMRCA) of all haplotypes was estimated via a Bayesian approach implemented in *BEAST (Star BEAST) O. longilobus and O. taihangensis. Therefore, for our combined chloroplast non-coding regions, we assumed minimum and maximum values of a range of average mutation rates reported for synonymous sites of plant chloroplast genes  No fossil records or biogeographic events isolating distinct populations are available to calibrate a cpDNA-IGS substitution rate for SSD) and Harpending's To detect whether population groups experienced recent population expansion and satisfied the assumption of neutrality, a mismatch distribution analysis was performed using the DNAsp program. Tajima's D and Fu and Li's D* were calculated for the entire genus and groups of populations. The statistical significance of D and D* was estimated with coalescent simulations as implemented in this program FST) with the Isolation by Distance Web Service http://ibdws.sdsu.edu/~ibdws/), running 10,000 Mantel permutations.Finally, isolation by distance (IBD) for both nrDNA and cpDNA data was tested based on pairwise geographical and genetic distances  ranged from 0 to 0.854, and the nucleotide diversity (π) from 0 to 0.00194 in the 5 populations of O. longilobus  ranged from 0 to 0.857 and the nucleotide diversity (π) from 0 to 0.00391 in the 5 populations O. longilobus. Within 8 O. taihangensis populations, the haplotype diversity h ranged from 0 to 0.714 and the nucleotide diversity π from 0 to 0.00293. For O. longilobus, hd = 0.908, πd = 0.00537; for O. taihangensis populations, hd = 0.558, πd = 0.00158 . Thus, the division of all the 13 sampled populations approximately into two groups is appropriate.Based on ITS sequences, phylogenetic analyses were carried . All stuP<0.01) of the total variation was due to differences among the cpDNA and nrDNA populations for all studied populations, respectively  variation between species, suggesting that the two separately distributed groups have a genetic differentiation. In addition, 60.71% of the total cpDNA variation and 68.24% of the total nrDNA variation existed among O. longilobus populations  and O. taihangensis . Likewise, a significant correlation was detected among populations from cpDNA data of O. longilobus  and O. taihangensis . This indicates a significant correlation between genetic differentiation and geographical distance, implying strong IBD.Results of the Mantel test showed a significant correlation between nrDNA data differentiation among populations and the natural logarithm of the geographical distances throughout the sampled range of O. longilobus and O. taihangensis populations , which is significantly smaller than the NST value (0.761). When the nrDNA was examined, the GST value (0.253) also differed significantly from the NST value (0.641). A significant phylogeographic structure was indicated by both cpDNA and nrDNA data .Based on cpDNA data, we estimated a Hippolytia and Nipponanthemum as outgroups  and tip (derived) haplotypes  and Bayesian inferences drawn using utgroups . Similarutgroups . Lineageplotypes . For linplotypes , the happlotypes , Hn8 wasO. longilobus populations and O. taihangensis populations respectively. The resultant mismatch distribution consisted of multiple multimodal curves  (0.50–1.72), which indicated the origin of Opisthopappus during the late Tertiary periods. The divergence times, estimated at approximately 1.28 Ma (95% HPD) (0.70–2.34) between O. longilobus and O. taihangensis, are shown in the haplotype phylogenic tree  and O. taihangensis , the results of our analysis suggested that significant variation was detected from among populations rather than from variation within groups  reported by Nybom The high levels of genetic diversity were observed in ulations . These rulations . For O. n groups . MoreoveO. longilobus and O. taihangensis possess a sexual reproductive mode and a relatively long life cycle as perennial herbs, all of which are traits associated with low total genetic diversity O. longilobus and O. taihangensis are self-compatible plant species O. longilobus  and O. taihangensis . The physiographic complexity of Taihang Mountains and the deeply carved valleys and ravines between the inhabit areas probably would imposes significant barriers to gene flow among populations of O. longilobus and O. taihangensis. The genetic divergence between the two lineages occurred at 1.28 Ma, corresponding to the early Pleistocene. This divergence falls within the glaciations during the Taku Glaciation (1.05–1.20 Ma). The glaciers and/or extremely low temperature in the mountains might also have created barriers to gene flow between geographically isolated populations, which therefore promoted the divergence. For both marker systems, we generally observed a good fit of these populations to an IBD model. When coupled with high levels of population subdivision, such conditions strongly suggest that geographical isolation had a larger historical role in extant population structure compared with limited pollen and seed flow alone. The habitats of O. longilobus and O. taihangensis are either rocky or massifs, and these species grow discontinuously in different habitats along the altitudinal gradient from 700 to 1500 m, in which the variable micro-surrounding, complex topography, and great altitudinal variability of the region might promote the high degree of genetic population differentiation O. longilobus and O. taihangensis populations.Species genetic diversity and structure can be affected by life history traits  and environmental effects  O. longilobus and O. taihangensis populations have a significant phylogeographic structure. The current distribution of haplotypes could be a result of past climatic changes related to the advance/retreat of glaciations Both Opisthopappus originated during the Pliocene. Before the Pleistocene, the current range of Taihang Mountains would have been covered by grassland with roughly similar geographic conditions O. longilobus and O. taihangensis can disperse following grassland migration. On this basis, we suspect that O. longilobus and O. taihangensis were once distributed throughout Taihang Mountains and its adjacent region. With uplift of Taihang Mountains O. longilobus and O. taihangensis were fragmented and forced into the refuge areas. The flora would migrate and expand during interglacial and glacial periods. This migration and expansion resulted in ecological displacement, which might have resulted in populations situated at different spatial-temporal scales. Different habitats might enhance the isolation of plant populations and prevent gene flow, which in turn could lead to incipient allopatric speciation or further allopatric speciation O. longilobus and O. taihangensis would have remained separated and fragmented at different spatial-temporal scales for a long time. Moreover, dramatic geological changes induced by the Taihang Mountains uplift contributed to the extremely complicated landscape, which likely acted as a major driving force for the separation of the O. longilobus and O. taihangensis. Divergent selection between populations in contrasting environments, longer temporal and spatial separation and fragmentation would accelerate their differentiation, and eventually promote allopatric speciation.Our analyses suggested that O. longilobus and O. taihangensis underwent strikingly different histories. For O. longilobus, long-distance dispersal and colonization may be a major historical process. O. longilobus was divided into different lineages around 0.89 Ma, which fell within the interglacial stage between the Taku Glaciation and Lushan Glaciation. The paleovegetation grasslands of Taihang Mountains O. longilobus in Hebei province may have extended across this corridor and reached Henan province. Haplotypes H1 and Hn1 located in populations LLS and WDS or LLS and SBY imply this long dispersal   . This expothesis .O. longilobus individuals or populations gathered in lineage I  had higher haplotype diversity  between the two species. On the other hand, several haplotypes were found within a single species . Haplotydization . These tO. longilobus and O. taihangensis have a high level of genetic diversity. The following phylogeographical structure and historical scenario of O. longilobus and O. taihangensis can also be drawn. The vicariance following the uplift of Taihang Mountains and a transition of paleovegetation of Taihang Mountains mainly shaped the present distribution of these two species. The above findings imply that multiple small refugia could have been maintained in the Taihang Mountains regions, which allowed O. longilobus and O. taihangensis to persist in situ and maintain sizable haplotype and nucleotide diversity at the lineage-wide scale during the glaciations. The current distribution pattern of O. longilobus and O. taihangensis refuges is similar to that of other East Asian plants  In summary, Figure S1Phylogenetic analyses based on ITS sequences.(DOC)Click here for additional data file.Figure S2Pairwise mismatch distribution analyses (MDAs) for O. taihangensis  and O. longilobus  populations inferred from cpDNA and ITS sequences.(DOC)Click here for additional data file.Table S1The cpDNA sequences characteristic of trnL-trnF and ndhJ-trnL intergenic spacers.(DOC)Click here for additional data file.


Plasmodium vivax is the geographically most widespread human malaria parasite. To analyze patterns of microsatellite diversity and population structure across countries of different transmission intensity, genotyping data from 11 microsatellite markers was either generated or compiled from 841 isolates from four continents collected in 1999–2008. Diversity was highest in South-East Asia , intermediate in the South Pacific (8.1–9.9) Madagascar and Sudan (7.9–8.4), and lowest in South America and Central Asia (5.5–7.2). A reduced panel of only 3 markers was sufficient to identify approx. 90% of all haplotypes in South Pacific, African and SE-Asian populations, but only 60–80% in Latin American populations, suggesting that typing of 2–6 markers, depending on the level of endemicity, is sufficient for epidemiological studies. Clustering analysis showed distinct clusters in Peru and Brazil, but little sub-structuring was observed within Africa, SE-Asia or the South Pacific. Isolates from Uzbekistan were exceptional, as a near-clonal parasite population was observed that was clearly separated from all other populations (FST>0.2). Outside Central Asia FST values were highest (0.11–0.16) between South American and all other populations, and lowest (0.04–0.07) between populations from South-East Asia and the South Pacific. These comparisons between P. vivax populations from four continents indicated that not only transmission intensity, but also geographical isolation affect diversity and population structure. However, the high effective population size results in slow changes of these parameters. This persistency must be taken into account when assessing the impact of control programs on the genetic structure of parasite populations. Plasmodium vivax is the predominant malaria parasite in Latin America, Asia and the South Pacific. Different factors are expected to shape diversity and population structure across continents, e.g. transmission intensity which is much lower in South America as compared to Southeast-Asia and the South Pacific, or geographical isolation of P. vivax populations in the South Pacific. We have compiled data from 841 isolates from South and Central America, Africa, Central Asia, Southeast-Asia and the South Pacific typed with a panel of 11 microsatellite markers. Diversity was highest in Southeast-Asia, where transmission is intermediate-high and migration of infected hosts is high, and lowest in South America and Central Asia where malaria transmission is low and focal. Reducing the panel of microsatellites showed that 2–6 markers are sufficient for genotyping for most drug trials and epidemiological studies, as these markers can identify >90% of all haplotypes. Parasites clustered according to continental origin, with high population differentiation between South American and Central Asian populations and the other populations, and lowest differences between Southeast-Asia and the South Pacific. Current attempts to reduce malaria transmission might change this pattern, but only after transmission is reduced for an extended period of time. Plasmodium vivax is the human malaria parasite with the largest geographical expansion, and the predominant malaria parasite outside of Africa [th century, P. vivax transmission even occurred in large parts of Europe, Russia and the US [P. vivax is difficult to control due to relapsing liver stages, fast and constant formation of gametocytes and a large proportion of asymptomatic carriers contributing to transmission [P. vivax has become the predominant malaria parasite in several countries where P. falciparum transmission has been successfully reduced [f Africa . Transmif Africa . Prior td the US . P. vivasmission , 4. As a reduced , 6.P. falciparum [Along with other parameters, parasite diversity can be used to assess the effect of interventions, as reduced transmission is expected to result in reduced diversity. This relationship was observed for lciparum , 8. Morelciparum . Thus, gP. vivax microsatellite diversity even in regions of moderate endemicity, and high multiplicity of infection was frequently observed. While some P. vivax populations showed pronounced structuring on small geographical scale [Typing of highly polymorphic microsatellites has proven useful to describe the diversity and structure of parasite populations –14, to sal scale , 13, thial scale , 23.P. vivax diversity based on samples collected across many different sites and typed with the same set of markers. Therefore we compiled data from published studies that included samples from Peru [Differences in method of sampling with respect to geographical space as well as different panels of markers used for genotyping make direct comparison of results difficult . Lackingrom Peru , Brazil rom Peru , 21, Sudrom Peru , Cambodirom Peru , Vietnamrom Peru , Papua Nrom Peru , and comrom Peru .P. vivax prevalence ever has been recorded in the lowlands of PNG . These Province . Migratiribution . In Afrinfection . Thus, Mer areas .P. vivax microsatellite population structure on a global scale. Previous studies on P. vivax population structure across different continents mostly genotyped polymorphic antigens [The wide distribution of parasite populations included in this study permit for the first time assessing antigens , 35 or mantigens , 37. TheInformed written consent was obtained from all individuals or their parents or guardians prior to the study. Details on ethical approval are published for samples from Peru , Brazil FST compared to other populations, they were still useful for clustering analysis and principal component analysis (PCA).Details of samples included in this study are given in Samples from Central America and Mexico had been collected from travelers returning from several countries spanning from Panama to Mexico. Due to the limited number of isolates and lack of precise information on sample origin , these isolates were combined as ‘Central American’ population, despite possible sub-structuring. From Armenia and Azerbaijan 14 isolates were available; these were combined because migration between both countries is frequent and it was not always clear in which of the two countries the infection had been acquired. From Uzbekistan 20 isolates were available. For calculation of allelic richness all Central Asian countries were pooled to reach the required number of 25 samples.P. vivax microsatellite alleles and clinical disease or acquired immunity has never been reported, thus it was not to be expected that different age groups sampled across populations or different proportions of febrile and asymptomatic individuals would influence population genetic parameters.All samples were typed with the same set of 11 published microsatellite markers . Three aMinor differences in typing protocols did not affect the results; i.e. samples from PNG, Solomon Islands, Madagascar Sudan and Central Asia were amplified by nested PCR, while a single round of PCR was performed on all other samples. As the nested PCR primers were identical to the single-round primers, allele sizes can be compared directly. From each lab a subset of samples was typed again starting from DNA to ensure comparability of results. Allele lengths were very consistent for all markers, except for MS8, where variation of up to 1.5 base pairs was observed. Due to this variation and possible positive selection MS8 was excluded from analysis.FST values are not affected because allelic frequencies are assessed at population level. Clustering analysis and calculation of LD were repeated with only those samples that harbored a single allele at each marker. To obtain sufficient samples from Madagascar and Cambodia, we permitted in the analysis also isolates with >1 alleles at one of the markers. It should be noted that isolates of low multiplicity were selected for genotyping for several parasite populations. Thus the difference between the number of samples of the full data set (including predominant peak haplotypes) and the number of only single clone infections does not reflect the proportion of multiple clone infections.In case of multi-clone infections the predominant peak only was included into the analysis. Occasionally this can result in incorrect haplotype assembly. This affects analysis such as linkage disequilibrium or clustering, where individual haplotypes are needed. Diversity and HE) of markers and allelic richness were calculated using FSTAT [HE is the chance that two unrelated parasites carry a different allele of a given marker, and allelic richness is a measure of alleles per each marker adjusted for the different numbers of isolates per site. When the effective population size is reduced, e.g. as consequence of intensified malaria control, rare alleles are expected to disappear first. As a result, allelic richness changes more rapidly than HE, as the influence of low-frequency alleles on HE is small. The number of unique haplotypes was calculated by Dropout [Alleles were binned using TANDEM software  and formng FSTAT . HE is  Dropout  and link Dropout . LIAN coRelatedness between haplotypes was assessed by pairwise comparison of all samples within a population and calculating the proportion of shared alleles. Only samples with at least 7 markers available for comparison were included.Ne (i.e. the estimated number of unique haplotypes circulating in each site) was calculated using step-wise mutations models (SMM) as well as infinite allele models (IAM), using mutation rates observed in P. falciparum studies of 1.59*10−4  [Effective population size 98*10−5) . While s98*10−5) , thus boFST values among populations were calculated using FSTAT [FST values and PCA.The software STRUCTURE was used to assess clustering of isolates . This meng FSTAT . To compng FSTAT . In contng FSTAT , in the ng FSTAT  and in MIn the absence of the same measures of transmission intensity for all populations, such as entomological inoculation rate, force of infection or parasite prevalence, populations were broadly classified as low, medium and high transmission .P. vivax isolates were available for this study. P. vivax endemicity in 2010, represented as parasite rate [A total of 841 HE) was generally high, it was strongly reduced in isolates from Uzbekistan. With the exception of Uzbekistan, HE of all except 2 markers (MS5 and MS7) was >0.5 in all populations (HE of 11 markers was lowest in Uzbekistan (0.52), followed by Azerbaijan (0.67) and South America (0.68–0.71), intermediate in Africa and the South Pacific (0.77–0.83), and highest in South-East Asia (0.84–0.87). The differences between continents were slightly higher when only those markers with lower overall diversity were assessed . Mean HE ranged from 0.53 in Uzbekistan and 0.6 in Peru to 0.85 in Cambodia. Mean allelic richness showed a similar pattern  was strong and significant in South American, Madagascan, Central Asian and SE-Asian populations . No or lNe size was about twice as high in Cambodia and Vietnam (IAM: 6378 and 5553) as compared to South America , likely because they originated from different countries and thus represent different subpopulations.Effective population Across all populations a total of 759 individual haplotypes were found in 818 isolates. 11-loci haplotypes were shared only within the same country. Again isolates from Uzbekistan were unusual, as 10 out of 20 isolates were identical and another two shared the same haplotype. Ten haplotypes were observed more than once in Peru, 5 and 2 in Brazil in 2004 and 2006 (plus 1 shared between the 2004 and 2006 data set), 5 in Sudan, 2 in Azerbaijan, 2 in Vietnam (1 observed 5 times), and 1 in PNG. 730/818 haplotypes were singletons.Relatedness among haplotypes was calculated for each population . In the To assess discrimination power of a smaller panel of markers compared to the full set of markers, microsatellites were removed successively and haplotype counts recorded from each individual population, as well as for the full dataset . MS4 wasOnly taking into account haplotypes shared within populations, a set of 4 markers  identified 710/760 (93.4%) haplotypes and 3 markers  still identified 665/760 (87.5%) haplotypes. By reducing to 2 markers (i.e. MS15 and MS10), the number of haplotypes dropped considerably to 513/760 (67.5%). The proportion of haplotypes lost by omitting markers was highest in South American populations. When using only 3 markers, 13–38% of haplotypes were lost in South American populations, but <10% in populations from SE-Asia and the South Pacific .Taking into account haplotypes observed in several populations, a single haplotype was shared between Peru and Vietnam when the panel was reduced to 5 markers. With four markers 15 additional haplotypes were shared. While some were shared between populations from the same continent , 11 haplotypes occurred on different continents . As a consequence, when haplotypes shared between populations were taken into account, 4 markers identified 687/759 (91.5%) haplotypes, and 3 markers 595/759 (78.4%) haplotypes , as well as when South American populations were compared to non-American populations (0.11–0.29). Differences between Cambodia, Vietnam and South Pacific populations were lowest (0.026–0.066). The highest FST value was observed between Azerbaijan and Uzbekistan (0.37), and all values for comparisons between Uzbekistan and other populations were >0.2. FST between Madagascar and Sudan was low (0.07).Results of clustering analysis were confirmed by T values . BetweenFST values were also compared between continents or sub-continents, i.e. South America, Africa, Central Asia, SE-Asia and the South Pacific , and lowest between SE-Asia and the South Pacific (0.042) and SE-Asia and Africa (0.058). Pacific . FST waIn principal component analysis (PCA), PC1 differentiated isolates from Brazil and Peru on the one hand and the South Pacific on the other hand from a cluster containing African and Asian isolates . PC2 sepFST values and PCA showed similar results. South American populations were separated from all others, and populations from Brazil and Peru formed clearly separated groups with little admixture. African, SE-Asian and South Pacific populations each formed a large cluster with little sub-structuring. Samples from Central America, Indonesia and India grouped with SE-Asia.In summary, clustering analysis, P. vivax isolates of global origin, typed with the same markers, allowed direct comparison between populations differing in transmission intensity, geographical isolation and history of malaria control. Determination of the optimal set of microsatellite markers required for differentiation of individual parasite infections will improve strategies for genotyping. Knowledge on population structure can be used to assess the effect of interventions and help to track imported infections.Analysis of 841 HE), is a key criterion for choosing a subset of microsatellite markers for a variety of genotyping questions [Diversity of a marker, expressed as expected heterozygosity .P. vivax studies involving genotyping are also complicated by relapsing hypnozoites, which can be homologous or heterologous to the clone at baseline [Other limitations affect drug trial results, such as imperfect detectability of minority clones  and as abaseline , 54. Lonbaseline . Thus, wHE or allelic richness was high and reflected transmission levels. It was lowest in South America and Central Asia, where transmission is low, and highest in SE-Asia. In the South Pacific diversity was intermediate despite highest levels of transmission . This cLinkage disequilibrium can be the result of selfing in the mosquito of male and female gametes from the same parasite clone , as oppoIncorrect assembly of multi-locus haplotypes in multi-clone infections within a host would be expected to lead to incorrect low levels of LD, but the opposite trend was observed: lower LD was found when only single-clone infections were included in the analysis. This unexpected finding was attributed to the smaller sample size after removing multi-clone infections.FST values between all populations. While clustering analysis and PCA differentiated among those populations separated by high FST values, no within-continent subdivision was observed in the South Pacific, Africa and SE-Asia. The difference in clustering between populations from Latin American  on the one hand and from the South Pacific (no subdivision between different provinces in PNG and Solomon Islands) or Africa (no subdivision between Madagascar and Sudan) on the other hand is striking, given comparable distances between sites. While high levels of human migration in SE-Asia could explain parasite gene flow, no clusters were found in the South Pacific despite limited human movement . Likewise limited sub-structuring was evident between Madagascar and Sudan, despite open sea and countries with very low P. vivax transmission separating sampling locations. In Central Asia, clear subdivision was observed between parasites east and west of the Caspian Sea. Parasites from Azerbaijan and Armenia clustered with those from Africa, while parasites from Uzbekistan were highly clonal and formed a separate cluster.Analysis of population structure revealed significant th century in some countries. In Latin America they could also reflect different independent introductions of P. vivax, as it has been shown for P. falciparum [P. vivax had been reintroduced after its elimination, most likely from other Central Asian countries. In contrast, in SE-Asia and the South Pacific P. vivax was present much longer than in Latin America, and even during the peak of the eradications campaigns in the 1960s prevalence remained high [P. vivax colonization of South and Central America.Distinct parasite subpopulations might be the result of expansion of parasite clones after the near elimination of malaria in the second half of the 20lciparum . In Uzbened high . CentralP. vivax population structure, most importantly mtDNA and polymorphic antigens. In agreement with the present study, sequencing of mtDNA identified a separate subgroup in Latin America  [Beside microsatellites, other molecular markers have been used to assess nalysis) , as wellnalysis) . Howevernalysis) . Isolatenalysis) . The samP. vivax diversity in Latin America was as high as in SE-Asia, despite locally reduced diversity, a result confirmed by analysis of 3 whole-genome sequences from Latin America [In concordance with microsatellite results, mtDNA diversity was highest in SE-Asia and high in the South Pacific . In cont America . The preSNPs in antigens are expected to be under strong balancing selection, limiting their use to study the underlying population structure. In line with this, many antigens showed strong clustering but in contrast to microsatellites many clusters were shared between continents , 35. LikP. falciparum in the highlands of PNG [Continuous malaria control is expected to reduce parasite diversity and effective population size, and to increase differences between populations due to clonal expansion of remaining parasite strains . Indeed,s of PNG , in Solos of PNG  and in Ss of PNG . Likewiss of PNG .P. vivax diversity found high parasite diversity, even in countries now aiming to eliminate malaria [P. vivax. Low microsatellite diversity was also found in South Korea, where transmission has been low for decades and the parasite population is relatively isolated [P. vivax diversity in countries with low transmission likely indicates a high underlying effective population size and thus a large number of infected individuals. Two hallmarks of P. vivax biology add to this, namely hypnozoites in the liver, and a large proportion of asymptomatic, low-density infections that escape screenings conducted by light microscopy or rapid diagnostic test and thus a substantially underestimated parasite reservoir [In striking contrast to these findings, nearly all studies assessing  malaria –69. The isolated , as wellisolated . The higeservoir .The isolates studied here were collected prior to the renewed call for malaria elimination. Only few studies have typed samples collected after up-scaling control measures, but diversity remained high –74. It sIn recent years malaria control has been intensified reducing prevalence and incidence in PNG , many AsIn previously malaria-free regions, microsatellite typing can help to study outbreaks. Because of their high discrimination power between clones, genotyping outbreak samples can clarify whether a single clone was imported and spread across a local region, or whether steady gene flow from neighboring regions with ongoing transmission occurs, resulting in a diverse parasite population .P. vivax, as it can be done in any lab equipped for PCR. For epidemiological studies and drug trials, a limited set of 2–6 markers, depending on transmission intensity, provides sufficient resolution to distinguish individual clones. The full panel of 11 microsatellite markers showed clear population structure on a global scale, and differences in diversity reflect transmission intensity and isolation of parasite populations. These population genetic measures could potentially be used as tools to measure the impact of control programs; however, due to the large effective population size even in countries of moderate endemicity, these parameters are likely to change slowly.Microsatellite typing remains an important tool to study S1 FileHE), number of alleles sampled and allelic richness.Three measures of parasite diversity are listed by marker and population: expected heterozygosity ((XLSX)Click here for additional data file.


Salvia lachnostachys Benth were assessed. Inter Simple Sequence Repeat (ISSR) molecular markers were used to investigate the restricted distribution of S. lachnostachys in Parana State, Brazil. Leaves of 73 individuals representing three populations were collected. DNA was extracted and submitted to PCR-ISSR amplification with nine tested primers. Genetic diversity parameters were evaluated. Our analysis indicated 95.6% polymorphic loci  with a 0.79 average Simpson’s index. The Nei-Li distance dendrogram and principal component analysis largely recovered the geographical origin of each sample. Four major clusters were recognized representing each collected population. Nei’s gene diversity and Shannon’s information index were 0.25 and 0.40 respectively. As is typical for outcrossing herbs, the majority of genetic variation occurred at the population level (81.76%). A high gene flow (Nm = 2.48) was observed with a correspondingly low fixation index. These values were generally similar to previous studies on congeneric species. The results of principal coordinate analysis (PCA) and of arithmetic average (UPGMA) were consistent and all three populations appear distinct as in STRUCTURE analysis. In addition, this analysis indicated a majority intrapopulation genetic variation. Despite the human pressure on natural populations our study found high levels of genetic diversity for S. lachnostachys. This was the first molecular assessment for this endemic species with medicinal proprieties and the results can guide for subsequent bioprospection, breeding programs or conservation actions.The genetic diversity and population structure of  Salvia L. (Lamiaceae) are in Southwest Asia and the Americas, Central and South America [Salvia is mostly found in the Midwest, Southeast and South [Salvia miltiorrhiza Bunge which is used for the treatment of cardiovascular diseases [Salvia have clear pharmacological properties, including, anti-inflammatory [Salvia species [The main centers of diversity for the genus  America . In Braznd South . Represediseases . Indeed,ammatory , gastropammatory , antiplaammatory . Essenti species .Salvia lachnostachys Benth., a perennial native herb found mainly in Paraná State, southern Brazil [Salvia lachnostachys showed have anti-inflammatory and the analgesic effects in oedema, pleurisy, and hyperalgesia induced by carrageenan models in mice [One of the most geographically restricted species is n Brazil ,9. Studin Brazil . In the  in mice .S. lachnostachys is through molecular markers. A commonly used technique is inter-simple sequence repeats (ISSRs), which employs the polymerase chain reaction (PCR) and microsatellite sequences to generate multilocus markers with a high degree of reproducibility [One of the most common methods to study genetic structure and variance in geographically restricted species such as cibility . Some ofcibility ,14. Morecibility ,16, or fcibility ,18.S. lachnostachys is a prime candidate for analysis of population level genetic variability, being a native species with great medicinal potential and a highly restricted geographic distribution.Given the dramatic and ongoing threats to Brazil’s wildlife and natural landscapes , there i8YC and (AG)8A, showed the highest polymorphism.The ISSR analysis produced 10 to 22 amplified bands per primer with an average of 17.6 polymorphic fragments , Table 1Cluster analysis generated a tree A and a dS. lachnostachys are given in observed numberof alleles per locus (Ao) and expected number of alleles (Ae) were 1.70 to 1.82 and from 1.33 to 1.39, respectively. Nei’s gene diverstity (H) and Shannon’s information index (I) of different geographic groups ranged from 0.20 to 0.24 and from 0.31 to 0.37, respectively. The group of samples from Curitiba showed the highest genetic variability while the group from São Luiz do Purunã showed the lowest.A summary of the ISSR data from each population of stG = 0.1678), and within populations was 81.76%. Gene flow (Nm = 2.48) indicated low genetic differentiation among populations, and therefore, corroborates a low value for stF = 0.18.The analysis of molecular variance (AMOVA) indicated that the majority of genetic variation occurred at the population level. The genetic differentiation among populations was 16.8%  used in our study had high levels of genetic variability . This result suggests that the species is relatively resilient, and provides a good opportunity to study, collect and conserve S. lachnostachys diversity, including the use of germplasm banks. Such actions would reduce the diversity loss and genetic erosion found in cultivated species, which typically have lower diversity associated with human assisted propagation and germplasm exchange [Despite the increasing human pressure on natural areas in Brazil, the exchange ,28.Salvia. Nevertheless, the inclusion of a greater number of markers would presumably further increase the value of the Simpson index.When considered alongside the Simpson index, the sampling variance values suggest an acceptable level of precision using the selected primers . Based oS. miltiorrhiza were previously evaluated using AFLPs [S. lachnostachys (H = 0.2509). Comparisons with a cultivated population of S. miltiorrhiza reveal a lower average value of Nei’s gene diversity index (H = 0.1951) [Salvia [Wild populations of ng AFLPs . The ave 0.1951) . However [Salvia ,29, domi [Salvia ,30,31. TstG in S. lachnostachys was 0.1678 indicating that greater variation exists within populations than among populations. This result is consistent with that found for S. miltiorrhiza (stG = 0.1336). Many factors contribute to genetic structure in plant populations, especially reproductive biology, gene flow, seed dispersal and nature selection. In particular, reproductive biology plays a central role in the genetic structure [Salvia [The unrooted dendrogram obtained in the cluster analysis effectively discriminated the sampled localities in distinct clusters based on Nei and Li distances. The dendrogram suggests a consistent differentiation among the sampled populations. The high genetic variability maintained within populations is encouraging. However, the division of samples from Palmeira in two distinct clusters was not expected; this may be related to many causes, such as founder effects or restricted gene flow. The value tructure . It is cGst = 0.16. Many fS. lachnostachys in the study area may also contribute to the low levels of differentiation between populations. Specifically, a high number of migrants (Nm) may facilitate gene exchange between populations. Vegetative reproduction (sprouting) may also reintroduce genes after an extinction event  in a single sub-population. However, the most important mechanism promoting gene flow in natural populations of plants is through the spread of seeds and pollen [Salvia species. The exchange of genetic material has been observed in other Salvia species; the Nm in S. miltiorrhiza was 3.2362 [The high adaptability and wide distribution of d pollen  and it is 3.2362 . NeverthS. lachnostachys in Parana State, southern Brazil. The geomorphological profile for this State consists of an Atlantic coastal plain at its eastern limits followed by a mountain ridge and three consecutive plateaus corresponding, respectively, to Curitiba, Ponta Grossa and Guarapuava city regions. Populations of S. lachnostachys occur mainly on the Curitiba and Ponta Grossa plateaus. Three populations S. lachnostachys were chosen to represent the restricted distribution . Genomic DNA was extracted using the modified 2× CTAB method by Doyle and Doyle. DNA integrity was examined in 1% agarose gel buffered with 1× TBE (tris-borate-EDTA buffer). Quality and concentration was doubled checked with a fluorimeter and a mass ladder comparison. Samples were kept in −20 °C until ISSR PCR processing.S. lachnostachys with good repetition and distinct polymorphic bands were chosen based on the existing literature , 0.6 µM primer, 2% DMSO (dimethylsulphoxide), 1U Taq DNA polymerase, and 1–2 ng/µL of template DNA. Amplification was performed in an Mastercycler Gradient  under the following conditions: initial denaturation at 94 °C for 2 min; then 35 cycles of 94 °C for 1 min, annealing at optimal temperature (2O. PCR products were separated by electrophoresis using 1.5% agarose gel in 1× TAE (Tris-acetate-EDTA buffer), visualized with 4% ethidium bromide under ultraviolet light and photographed by 2UV Benchtop Transilluminator .Nine previously tested primers for terature . ISSR-PCperature  for 45 sISSR data are dominant and, therefore, each band represents the genotype at a single bi-allelic locus. Samples were processed in three independent amplifications for each primer. All the electrophoresis photographic files were electronically analyzed . Average bands size was computed and homology was inferred when size values were within a 2% range of error (considering their assigned size). Only fragments in the size range of 220 bp to 2.2 kb were included. The phenotypic pattern of the 73 individuals for all primers was recorded in a single binary matrix.Sampling variances were examined to determine how many markers would be required for a given level of precision in the estimate of genetic distances ,37. The PPB), observed number of alleles (Ao), effective number of alleles (Ae), Nei’s gene diversity (He) and Shannon’s information index (I) using PopGene version 3.2 [Nm) were calculated following McDermott and McDonald [5 Markov chain Monte Carlo samplings after a burn-in period of 5 × 104 iterations—following the program’s dominant marker settings, the ‘‘no admixture” model was used and uncorrelated allele frequencies among populations were assumed. The most likely number of clusters was estimated according to the model value (∆K) based on the second order rate of change, with respect to K, of the likelihood function, following the procedure described by Evanno et al. [Simpson’s index was calculated by using the following formulas:sion 3.2 . EstimatMcDonald . AnalysiMcDonald  and ArleMcDonald . GeneticMcDonald  and PAUPMcDonald . As geneMcDonald . A BayesMcDonald . Assumino et al. .To effectively conserve genetic variability in a germplasm bank, priority should be given to both the clusters of populations in the Palmeira locality. The dendrogram and Bayesian analysis indicate that this population is related to samples from Curitiba and São Luiz do Purunã. As the genetic variability is higher within populations and differences among the three examined populations are low, diversity could be maximized by concentrating sampling within the population from Palmeira.


Sustainably managing plant resistance to epidemic pathogens implies controlling the genetic and demographic changes in pathogen populations faced with resistant hosts. Resistance management thus depends upon the dynamics of local adaptation, mainly driven by the balance between selection and gene flow. This dynamics is best investigated with populations from locally dominant hosts in islands with long histories of local selection. We used the unique case of the potato late blight pathosystem on Jersey, where a monoculture of potato cultivar ‘Jersey Royal’ has been in place for over a century. We also sampled populations from the coasts of Brittany and Normandy, as likely sources for gene flow. The isolation by distance pattern and the absence of genetic differentiation between Jersey and the closest French sites revealed gene flow at that spatial scale. Microsatellite allele frequencies revealed no evidence of recombination in the populations, but admixture of two genotypic clusters. No local adaptation in Jersey was detected from pathogenicity tests on Jersey Royal and on French cultivars. These data suggest that long-distance gene flow (∼ 50/100 km) prevents local adaptation in Jersey despite a century of local selection by a single host cultivar and emphasize the need for regional rather than local management of resistance gene deployment. From an evolutionary ecology point of view, local adaptation  between hosts and pathogens results from the balance between evolutionary forces acting simultaneously on pathogen life history traits involved in trade-offs  population, through mutation or gene flow  or gene flow continuously brings into local populations genotypes maladapted to the local resistant hosts. This has been shown to occur in several Blumeria graminis populations in Europe  and quantitative phenotypic traits  in pathogen populations. They are based either on the comparisons of population differentiation for genetically neutral markers  favoring metapopulation dynamics  and (ii) with different dominant host genotypes between sites. This conjunction is well met in the potato late blight pathosystem close to the English Channel. This pathosystem is indeed characterized by the following:Phytophthora infestans – feeding on an annual host. The strict dependence of the pathogen upon living host tissue to persist in the environment and the annual rather than perennial growth habit of its hosts make periodic local extinction highly likely. This assumption is confirmed by genetic data, which showed that over 90% of the genotypes present in local populations in the Netherlands disappear between one growing season and the next , with usually two different crops a year on each plot of land. This further restricts the vegetation period of each of them and therefore reinforces the chance for local extinction of biotrophic pathogens. Potato is a major crop in Jersey, one of the Channel Islands close to the coasts of Normandy and Brittany.The oceanic situation and mid-latitude of this part of Europe goes along with a prevailing southwesterly wind regime, which may allow wind-borne spores to be dispersed easily over relatively large distances.P. infestans, according to the European Potato Database (http://www.europotato.org).In the French potato production area considered, cultivar Europa was dominant but not exclusive. By contrast, potato production on Jersey has been dedicated almost exclusively since the early 1900s to cv. Jersey Royal, a selection of the early cultivar International Kidney. Jersey Royal is grown year round in Jersey and is not produced anywhere else. Jersey therefore represents a unique situation in Europe, because of its island location, the extensive monoculture of a single potato cultivar for more than a century, and strict controls on movement of seed tubers of this cultivar into and out of Jersey , and Normandy  occurs only when A1 and A2 isolates come into contact. The mating type of each isolate was identified by pairing it on pea agar medium with known A1 and A2 tester isolates, incubating in the dark at 15°C for 10–14 days, and looking under the microscope for the presence of oospores where the two colonies met. Isolates producing oospores with the A1 tester were rated as A2 mating type and vice versa.Isolates were grown in pea broth, previously autoclaved for 20 min at 120°C and cooled to room temperature. After 10–15 days of incubation at 15°C, mycelium was washed three times in sterile water, dried on sterile paper, and lyophilized. DNA was extracted using the NucleoSpin® Tissue kit , according to the manufacturer's instructions. DNA concentration and purity were estimated for some isolates using a spectrofluorimeter Nanodrop ® ND-1000 .cacgacgttgtaaaacgactagtggagacgttgtgcagg-3′ and 5′-cacgacgttgtaaaacgaccctttagcagctcatttccg-3′, and the reverse primers were 5′-gtggctgcggatacttcttt-3′ and 5′-cgcactcgtcttgttgcac-3′. All PCRs were performed in a 12.5 μL volume, as described by Montarry et al. , 0.06 μL of 400 HD ROX™ size standards (Applied Biosystems), and 0.1 μL of PCR multiplexed products were loaded into an ABI Prism 3130xl DNA Sequencer (Applied Biosystems) and run according to the manufacturer's instructions. DNA fragments were automatically sized with GeneMapper™ v4.0, and allele sizes were calibrated to the allele sizes of reference isolates (C1–C12) kindly provided by Drs A.K. Lees and D.E.L Cooke .Amplification products were pooled into four batches, based on expected allele sizes: batch1, Pi02, Pi89, and 4B; batch 2, G11, Pi04, Pi56, Pi63, and Pi70; batch 3, D13, 4G, Pi16, and Pi33; batch 4, M19 and M34. For each batch and isolate, a 10-Plants of the potato cultivars Bintje, Europa, and Jersey Royal were grown from certified seed tubers in a glasshouse regulated at 15–20°C (night/day temperatures) and 16 h of photoperiod, in 13-cm pots (one tuber per pot) filled with sand–peat–compost mixture. Plants were watered with a nutrient solution  once a week. Leaflets were collected on 6-to 8-week-old plants. All experiments were performed from mid-September to mid-December 2007.P. infestans sporangia, prepared by flooding a 3-week-old culture with 5 mL sterile distilled water and gently scrapping the colony surface with a small glass rod. After 7 days of incubation in humid chambers under controlled conditions , the new sporangia produced on the infected leaflets were collected in sterile water, and the concentrations of the resulting suspensions were adjusted to 5 × 104 sporangia mL−1. Suspensions were kept at 4°C for approximately 2–3 h to promote zoospore release, just before being used for pathogenicity experiments  and infected by depositing a 20 μL drop of the calibrated sporangial suspension at the leaflet center. Infected leaflets were incubated for 6 days as described above. Lesion diameters were measured in two perpendicular directions, and lesion size was computed assuming an elliptic shape. Then, each leaflet was washed in 10 mL saline buffer (Isoton II), and sporangia were counted with a Beckman Coulter Z2 cell counter  to determine sporangial production per lesion.Each isolate was tested for lesion size and spore production on all three host cultivars . Six leaflets per cultivar × isolate combination were placed abaxial face up on the lids of inverted Petri dishes containing 10 g LP. infestans isolates without any missing data.Among the fourteen microsatellite loci, only twelve were analyzed because over 15% of the isolates showed multiple banding at loci M19 (28 isolates showing three bands and five showing four bands) and Pi63 , casting doubt as to the actual ploidy level at these loci. Moreover, to have a correct assignment to multilocus genotypes, all isolates with amplification in which amplification failed for at least one locus were excluded from the final data set, which therefore included 179 n) were identified using GenClone 2.0 . An exception is the computation of the genetic diversity indices, for which statistics were performed both with and without clonal copies.Repeated multilocus genotypes (MLGs), that is, isolates sharing the same alleles at all 12 loci, and the number of copies of each MLG .The evolutionary relationships among genepop (with default Markov chain parameters) to count the number of locus pairs showing significant linkage disequilibrium across all populations. A Bonferroni correction  was applied to take into account multiple testing.Linkage disequilibrium between loci was calculated with populations 1.2.30  were computed using genetix 4.05.2  was tested using the resampling method (1000 bootstraps) implemented in genetix.Genetic diversity in each population (and each cluster) was estimated as both the allelic richness (Ar) and gene diversity. Allelic richness was estimated using the rarefaction method implemented in Langella , which eP. infestans populations (FST) were estimated according to Weir and Cockerham (genepop 4.0.7 (Raymond and Rousset G-test (with default Markov chain parameters) implemented in genepop. Following the recommendations of Rousset  using xlstat 2012 .The differentiation coefficients between each pair of ockerham  using ge Rousset , the hypP. infestans isolates were clustered on the basis of their genetic relatedness using the Bayesian clustering approach implemented in structure 2.3.3 .Normality and homogeneity of variances were checked with the Shapiro–Wilk and the Leven tests, respectively, using the statistical software R, version 2.15.0  and one isolate in Ploudaniel . Among tGenClone identified 23 unique multilocus genotypes (MLGs) among the 179 P. infestans isolates, corresponding to a genetic richness of R = 0.128. Fifteen MLGs were represented by a single isolate  included only isolates belonging to the A2 mating type . CompariR = 0.30; HE) from 0.383 to 0.514  across all populations if no corrections for multiple tests across all populations were made, although none showed significant linkage disequilibrium after Bonferroni's correction.Four to nine MLGs were found in each of the five populations, the population from Ploudaniel showing the highest genotypic diversity , Saint-Malo (FST = 0.182), and Jersey (FST = 0.152). To a lesser extent, populations from Paimpol and Val de Saire were also genetically differentiated (FST = 0.062). Consequently, a significant correlation was observed between geographic distance and P. infestans population differentiation , consistent with the low differentiation among the easternmost populations sampled . That clustering analysis clearly indicated that the posterior distribution of the allele frequencies among clusters was best explained with a grouping into K = 2 genetic clusters. Applying an assignment threshold of 0.90, 91% of the MLGs (21 of 23) could be assigned to one or the other genetic cluster, confirming that the two clusters were well differentiated (FST = 0.317). The evolutionary relationships among the P. infestans MLGs from both genetic clusters were showed by a minimum spanning network  than cluster 1  had a significant effect on both lesion size and spore production  and each pathogenicity trait (lesion size and spore production), except for lesion size on Jersey Royal where the population effect was only marginally significant .All tested explanatory factors  supports the hypothesis of intensive gene flow at this scale, despite the apparent phenotypic differences in pathogenicity. Together, these observations strongly suggest that gene flow between France and Jersey is preventing the evolution of local adaptation patterns, despite persistent and widespread selection in Jersey over more than a century by a single host cultivar specific to this island.However, our data revealed no pattern of local adaptation to cv. Jersey Royal in Jersey, and extensive gene flow between FST calculations between pairs of populations. It explains the significant isolation by distance pattern when the Ploudaniel population is considered, but the lack of significance of this pattern is explained when this population, further west, is excluded from the data set. The dispersal range calculated here markedly exceeds the usual assumptions, of the order of magnitude of a few kms, regarding the effective dispersal kernels of the short-lived, fragile sporangia of P. infestans  reveals that cv. Europa has cv. Bintje among its progenitors, through cvs. Climax and Edzina. It is therefore understandable that adaptation to cv. Bintje, previously shown in French populations (Montarry et al. A further factor favoring effective dispersal and general adaptation is the genetic proximity between hosts. Searching the European Potato Database (P. infestans populations cluster into two distinct genetic groups is consistent with previous data from French isolates collected in 2004 and 2005 (Montarry et al. Psex values and the negative FIS values, indicating an excess of heterozygotes that could result from asexual reproduction (Halkett et al. Our finding that P. infestans and its host range limited to a few annual hosts should favor such local extinction. However, the widespread presence of potato crops throughout the territory and the extensive gene flow shown here imply that a metapopulation dynamics is quite unlikely to take place. This is consistent with population structures of P. infestans in western Europe being dominated by a few, widely distributed clonal lineages, such as US-1 until the early 1980s (Spielman et al. These observations have major consequences for resistance deployment strategies and the management of late blight epidemics through resistant cultivars. Such deployment strategies, to be effective, should ideally exploit local maladaptation generated when the hosts are diverse and the pathogen moves rapidly (Kawecki and Ebert ad-hoc cassettes in a cisgenesis transformation process (Haverkort et al. Therefore, it will probably be difficult to think of effective resistance deployment strategies over large scales, such as crop mosaics or refuge areas, because the strong gene flow and connection of host populations will make it hard to generate sufficient differentiation in local parasite populations for a large-scale spatial deployment strategy of resistant hosts to be effective (Skelsey et al.


QST/FST analysis using agricultural populations of the barley pathogen Rhynchosporium commune. Population divergence for eight quantitative traits (QST) was compared with divergence at eight neutral microsatellite loci (FST) for 126 pathogen strains originating from nine globally distributed field populations to infer the effects of genetic drift and types of selection acting on each trait. Our analyses indicated that five of the eight traits had QST values significantly lower than FST, consistent with stabilizing selection, whereas one trait, growth under heat stress (22°C), showed evidence of diversifying selection and local adaptation (QST>FST). Estimates of heritability were high for all traits (means ranging between 0.55–0.84), and average heritability across traits was negatively correlated with microsatellite gene diversity. Some trait pairs were genetically correlated and there was significant evidence for a trade-off between spore size and spore number, and between melanization and growth under benign temperature. Our findings indicate that many ecologically and agriculturally important traits are under stabilizing selection in R. commune and that high within-population genetic variation is maintained for these traits.Genetic drift and selection are ubiquitous evolutionary forces acting to shape genetic variation in populations. While their relative importance has been well studied in plants and animals, less is known about their relative importance in fungal pathogens. Because agro-ecosystems are more homogeneous environments than natural ecosystems, stabilizing selection may play a stronger role than genetic drift or diversifying selection in shaping genetic variation among populations of fungal pathogens in agro-ecosystems. We tested this hypothesis by conducting a  Rhynchosporium commune. We also estimated within-population genetic variation in quantitative traits and at neutral marker loci to assess the pathogen’s potential to adapt. The ability of a fungal plant pathogen to adapt to the deployment of resistant hosts, to fungicides and to changes in climate are considered to be important contributors to a pathogen’s overall risk of causing extensive damage in agro-ecosystems Quantitative genetic variation within and among populations is affected by the evolutionary processes of mutation, migration, genetic drift and selection Global anthropogenic homogenization of environmental conditions has recently been recognized as important for the emergence of new diseases and the spread of invasive species FST) with that for quantitative traits  reveals the predominant evolutionary force. This approach is based on the prediction that the difference between the two measures of divergence is due to selection acting on the quantitative traits. Higher QST values than FST values are interpreted as diversifying selection for local adaptation. Lower QST values than FST values are interpreted as stabilizing selection among populations, potentially associated with directional selection operating in the same way in each population. A correlation between the two measures indicates the signature of genetic drift.Genetic drift and selection are predicted to have different impacts on genetic variation within and among populations, and this can be used to infer their relative importance QST/FST studies QST is often larger than FST, suggesting that diversifying selection among populations is the common type of selection acting among populations. This meta-analysis also clearly documents a strong bias in study organisms towards wild species of plants and animals and a deficiency of studies using fungi and pathogens in anthropogenically-altered environments Several meta-analyses have been performed on QST/FST context and measures of within-population genetic variation were estimated for several traits that are thought to play a role in the amount of damage caused by the pathogen. Experiments were performed using nine field populations of the barley pathogenic fungus Rhynchosporium commune collected from nine countries. The traits included a classic morphological trait – spore size, fitness-related life-history traits – spore number and virulence in planta, physiological traits – in vitro thermal performance under three temperatures, and a trait related to agricultural practices – fungicide resistance.The goal of this study was to elucidate the relative roles of genetic drift and selection on population genetic divergence and to link genetic variation within populations at neutral marker loci with that for quantitative traits. Results are discussed in the context of the evolutionary forces shaping within- and among-population genetic variation in an agricultural fungal pathogen. Comparisons between populations were made within a Rhynchosporium commune is the causal agent of a serious disease called barley scald, which is found in all major barley-growing areas of the world. Barley scald causes severe yield loss and economical damage Rhynchosporium commune specifically infects Hordeum species, including domesticated and wild barley as well as Bromus diandrusR. commune and are described in previous publications Nine populations from naturally infected barley fields in nine countries were chosen from a global collection of in vitro: growth under different temperatures and fungicide concentrations, colony melanization, spore size and spore number. For all assessments, isolates were first grown for 10–14 days at 18°C in darkness and then transferred to fresh LBA plates, where growth occurred for another two weeks. Spores were harvested by adding 1.5 ml of sterile water and scraping, and then counted using a haemocytometer.The following traits were assessed 2) was measured with the image analysis software APS Assess Methods used to assess growth rate at different temperatures were described earlier For the assessment of fungicide resistance, 100 µl of a 1000 spores/ml spore solution were spread on plates amended with fungicide (0.1 ppm in one experiment and 0.025 ppm cyproconazole in a second experiment) and without fungicide (in both experiments). Each isolate-treatment combination was replicated three times and plates were incubated at 18°C. Growth rates were measured using digital images as described above. Fungicide resistance was measured by dividing the colony growth rate in the presence of fungicide by the colony growth rate in the absence of fungicide. This calculation was performed by pairing up all possible replicate combinations of the two treatments (with/without fungicide), creating 9 pseudo-estimates per isolate. Because fewer than 20% of the isolates showed detectable growth at the higher fungicide concentration, data were analysed using the average relative growth rate of randomly paired replicates of the two fungicide experiments for an isolate, totalling a maximum of 9 estimates per isolate. When in one of the treatments no growth was observed, a value of 0 for that treatment was assumed.Colony melanization on each plate used in the growth rate experiment  and the fungicide resistance experiment with 0.025 ppm cyproconazole (without control plates) was measured using Adobe Photoshop vCS5 (Adobe Systems) as the mean grey value of the colonies after 34 days of growth. Because grey values were significantly and positively correlated across all four environments, we calculated melanization for each replicate as the mean across all environments.2 agar plugs were removed from each plate and placed in 8 ml plastic tubes containing 5 ml of 1% sodium dodecyl sulfate (SDS) solution. Tubes were vortexed for 30 seconds to release spores from the agar surface and 20 µl was pipetted into a disposable Cellometer counting chamber . Spore number (spores/ml) and mean spore size (µm) were calculated automatically using the Cellometer Auto T4 cell counter (Nexcelcom Bioscience).For the assessment of spore size and spore number, mycelium was transferred to three standardized LBA plates per isolate. Because isolates from Spain and Iceland did not produce enough mycelia to be transferred to new plates, they were excluded from this experiment. Mycelium was spread using a sterile metal loop to cover the surface of each plate. After 14 days of growth at 18°C in darkness, four 49 mmin planta were described earlier 6 spores/ml and adjusted to a total volume of 5 ml. Virulence was measured on the spring barley cultivar Beatrix (Viskosa×Pasadena), which was rated as moderately susceptible to R. commune. For each isolate, three pots were sown with four seeds in each pot in a single greenhouse chamber . After 12 days of growth the second leaf was fully emerged. Plants were then inoculated in a sterile chamber with 5 ml of spore suspension per isolate. They were allowed to dry for 15–20 minutes and arranged randomly within mobile humidity chambers that were placed within the growth chamber. Using ultrasonic humidifiers the relative humidity was kept at 100% for 48 hours. After the humidity chambers were removed, the pots were randomly arranged in the greenhouse chamber and the relative humidity was set to 60%. Fifteen days after inoculation, the second leaf on all plants was cut and fixed to a paper sheet. Digital images were taken, the percentage of leaf area affected by the disease (virulence) was measured using the image analysis software APS Assess Methods used to assess virulence FST) was assessed both pairwise and overall and standard deviations for overall FST values were calculated by jackknifing over loci using FSTAT v2.9.3 A microsatellite analysis was performed on the same 126 isolates as described previously QST values may be somewhat lower than if gene effects were purely additive A general linear model analysis was performed to determine whether there were significant effects of isolate and population on trait values (PROC GLM in SAS QST) was compared to population differentiation for neutral microsatellite markers (FST) to infer the relative role of selection and neutral evolution in shaping population divergence. Population differentiation was calculated as the ratio of genetic variance among populations to the sum of genetic variances within and among populations using a haploid-modified version of the equation introduced by Spitze QST values were obtained by jackknifing over populations QST values were calculated. For overall QST and FST, 95% confidence intervals (approximated by ± 2 SE) were compared to determine whether differences were significant. For pairwise QST and FST values, Mantel tests were performed with the program GenAIEx v6.5 Population differentiation for quantitative traits (h2) was calculated as the ratio of genetic variance (VG) to total phenotypic variance within populations. To examine correlations among traits, trait values of each trait-population combination were standardized to a mean of 0 and a standard deviation of 1, and then correlation analyses between traits were performed based on isolate means . Pairwise FST ranged from 0.002 between the two Scandinavian populations of Norway and Finland to 0.42 between Switzerland and Ethiopia . We found that overall QST was significantly lower than overall FST . For the remaining two traits, the correlation was significantly negative, for growth rate at 12°C  and for growth rate at 18°C   and genetic variance .Estimates of heritability were generally high across all eight traits . The higRhynchosporium commune. Five of eight traits revealed evidence for stabilizing selection across populations, indicating that the same phenotypes had been favoured across populations. These five traits were: growth rate at 18°C, melanization, spore size, spore number and virulence , stabilizing selection appears to be more common in QST/FST comparison on similar traits in Mycosphaerella graminicola showed that for three traits  the effects of selection could not be separated from those of drift, while another three traits  were under diversifying selection Melampsora liniPuccinia striiformis f. sp. triticiWe are aware of only few studies where population differentiation for neutral markers and phenotypic traits were compared for fungi. A Mycosphaerella graminicolaRhizoctonia solaniCochliobolus heterostrophusCochliobolus carbonumM. graminicolain vitro cyproconazole resistance were in the range of 0.17–0.80 in populations of M. graminicolaR. solani, heritabilities for in vitro copper oxychloride sensitivity varied between 0.6–0.9 in planta, were only half as high in M. graminicolaWithin-population genetic variation for expressed traits, calculated as heritability, was generally high . StudiesThe generally high heritability values are surprising because many of these traits are closely linked to a pathogen’s fitness, including growth rate under optimal temperature, spore number and virulence. A likely reason is that those traits have wide fitness functions R. commune. The species emerged recently in Scandinavia through a host jump In our study, average heritability across traits was significantly negatively correlated with gene diversity assessed for neutral microsatellite loci . This coRhynchosporium commune harbour high evolutionary potential with the ability to adapt rapidly to simple disease management practices including the deployment of resistant cultivars and application of pesticides.This study represents one of the first comparisons of the relative effects of genetic drift and selection on quantitative traits in an agriculturally important fungal pathogen. On the one hand, we found strong evidence that agricultural ecosystems impose similar selection on pest populations across large geographic regions, from Europe and North America to Africa and Australasia. On the other hand, these populations harbour very high levels of genetic variation for important pathogenicity traits, possibly due to wide fitness functions within populations. If this model is correct, it implies that similar selection combined with some gene flow creates a very large species-level population that is well-adapted to a wide variety of agricultural conditions. Therefore, species like Table S1Pairwise QST values for all eight quantitative traits studied and pairwise FST values for neutral SSR markers.(DOC)Click here for additional data file.