FST, a measure of alternative fixation of alleles, is a common proxy for realized dispersal among natural populations, summarizing the combined influences of life history, behaviour, habitat requirements, population size, history and ecology. We test the hypothesis that population structure in the native range (FST) is negatively correlated with the geographical extent of spread of marine species in an introduced range. An analysis of the available data  revealed a significant negative correlation (R2 = 0.245–0.464) between FST and the extent of spread of non-native species. Mode FST among pairwise comparisons between populations in the native range demonstrated the highest predictive power . There was significant improvement when marker type was considered, with mtDNA datasets providing the strongest relationship . This study shows that FST can be used to make qualitative predictions concerning the geographical extent to which a non-native marine species will spread once established in a new area.Forecasting invasion success remains a fundamental challenge in invasion biology. The effort to identify universal characteristics that predict which species become invasive has faltered in part because of the diversity of taxa and systems considered. Here, we use an alternative approach focused on the spread stage of invasions.  Likewise, because the geographical scale over which genetic surveys are conducted (distance between two most distant sample sites) can influence the magnitude of genetic structure, we standardized global FST values by calculating FST per kilometre [ln/ln(km)]. We used ordinary least-squares (OLS) regression analyses to determine if FST values  are a good predictor of the extent of spread in the introduced range. Simulation studies indicate that OLS regression analyses are preferred if the purpose of the study is not to estimate the parameters of a functional relationship, but instead to simply forecast values of the response variable for given explanatory variables  as covariates. Statistical analyses were conducted using SPSS v. 17.0  except the GLM that was calculated using JMP Pro v. 10.0 . Plots of observed versus predicted residuals did not reveal any patterns that would bias the results or interpretation of the regression model (data not shown).Using the pairwise iewed in ). Geneti3.(a)n = 16; one of these is a concatenated COI/ND2 dataset), cytochrome b (n = 3), control region (n = 1) and intergenic spacers (n = 1). Nuclear markers were used in eleven studies and included: microsatellites (n = 6), allozymes (n = 2), internal transcribed spacers (n = 2) and amplified fragment length polymorphism (n = 1). Species included in this study are native to regions across the globe including Europe, Asia, America, Australia, South America and Oceania. Introduced regions were also geographically diverse, and included the above continents plus southern Africa. The recording of the green crab, C. maenas, in North America in 1817 makes this the earliest introduction in the dataset, whereas the most recent event involved the detection of the sponge Crambe crambe in the Canary Islands in 1995. The number of native populations surveyed per species ranged from three to 33 (mean = 9.66). Sample sizes per location within the 29 studies ranged from nine to 70 individuals (mean = 25.69) .Searching the literature resulted in 32 cases across 29 species that met our selection criteria: 10 molluscs, four fishes, four crustaceans, three tunicates, two vascular plants and one each of cnidarian, echinoderm, ctenophore, annelid, sponge and an alga . The majority of the studies were based on mitochondrial DNA (21 of 32), including cytochrome oxidase I , median (range = −0.018 to 0.969) and mode (range = −0.100 to 1.00) . In four studies, although pairwise FST values were available, the number of populations surveyed was low (3 or 4) and precluded the calculation of mode FST. MES varied widely among species ranging from 42 km for the tunicate Pyura praeputialis to 4344 and 4497 km for the ctenophore M. leidyi and the bivalve M. arenaria, respectively. To take secondary introductions into account, we calculated CES for each species which resulted in a narrower range from 8 km for the alga U. pinnatifida to 2583 km for the bluestripe snapper L. kasmira.Genetic surveys were conducted over a wide range of geographical distances. The shortest distance was 50 km between five populations of the Japanese oyster drill, (b)FST was poorly correlated with geographical study scale in marine organisms, explaining only 2 per cent of the variance among 149 studies. Likewise, we found no correlation between global FST and study scale in our smaller dataset : a finding that may result from the inclusion of different marker types [FST and the extent of spread , we found significant correlations between population structure in the native range and CES  with a slight improvement in predictive power when global FST was corrected for geographical scale of the study . The best predictor of CES was the mode of the pairwise FST values . While not as strongly correlated with spread as mode FST, both mean  and median  pairwise FST values were better predictors than global FST.We found no correlation between genetic structure in the native range and MES. However, when we corrected for secondary introductions and possible human-mediated dispersal within the introduced range, we detected a significant negative correlation between genetic structure and CES. Regardless of the  and CES . Global HE on the extent of spread (FST [n = 21) to determine if the correlation between FST and extent of spread improved. In all cases correlations were stronger when analyses were restricted to the mtDNA datasets  and the mode pairwise FST having the greatest predictive power .We did not find a significant effect for marker type, taxon or f spread . Howeveread . We detected a larger R2 value for the IBD slope versus CES comparison , however, the power to detect a significant correlation was limited owing to sample size.Tests for IBD among native populations were available for only 10 of the 32 studies. We found no significant correlation between IBD slope and MES . An even stronger correlation was detected when marker type was taken into account (R2 = 0.333–0.516). While there are insufficient data to determine if FST can predict the success of initial invasions, our results indicate that this metric is suitable to qualitatively predict the extent of spread once an invasive species is established.Identifying general characteristics that allow ecologists and managers to predict invaders has proved to be elusive. Here, we offer a metric with considerable power to predict the extent of spread in marine alien species. FST is not a simple measure of population differentiation, but instead is influenced by population size and genetic diversity (heterozygosity). There is a predicted relationship between population size, HE and FST [FST). Consequently, our correlation between FST and invasive spread may indicate that species that sustain large genetically diverse populations make better invaders [FST and HE in our dataset nor was there a significant relationship between extent of spread and HE, indicating that native population size is not driving the correlations described here. and FST –42. Undeinvaders . Direct FST has not been found except over small geographical scales [We restricted our study to marine species because of the strikingly different modes of dispersal between land and sea. Most marine organisms have a biphasic life cycle in which adults are benthic and largely sedentary. Dispersal, over even short distances (1–10 km), is achieved primarily during a pelagic phase (eggs and larvae); the length of which varies greatly among taxa, from 0 days to more than a year in a few taxa (spiny lobsters and eels). As a result, marine larvae can be transported 100's or even 1000's of km before settlement. However, the length of the pelagic larval phase is just one factor effecting dispersal in marine organisms. Timing of spawning, local oceanographic conditions, larval swimming and sensory ability and habitat requirements all play important roles in determining effective dispersal in marine organisms. These myriad of factors probably explain why a consistent correlation between the length of the pelagic phase and l scales ,39. In t(a)FST is a summary statistic, significant structure among populations may be a result of differences in effective population size, demographic or colonization history, migration, or some combination of these factors, especially for populations that may not have reached migration drift equilibrium, and thus direct interpretation of population structure in the context of gene flow can sometimes be problematic  also tend to become the most widespread invaders.Because  & Marko , Lowe &  & Marko  and Mark & Marko ). We arg(b)FST. Global FST had the lowest predictive power, explaining 25 per cent of the variation which increased to 39–46% using either median or mode FST. While our dataset was not sufficient to test for the effect of marker type on estimates of genetic structure, measures of FST from mtDNA are generally higher than from nDNA, complicating direct comparisons of FST among marker types ([FST (with as much as 52% of the variance explained) when only the mtDNA datasets were considered.Our data indicate that up to half of the variation in the extent of spread of marine invasive species can be explained by native population structure as measured by r types  of which the two data points with the highest FST values and correspondingly low CES had a large impact on the relationships revealed here . The former is anchored to substrate and the latter is believed to have a very brief pelagic larval stage. Omitting these two data points results in significant relationship only for median FST . Examining the data plots . However, correcting for this variation is not straightforward. First, the time disparity between first record of occurrence and the actual date of introduction can be vast. Some alien species go undetected for decades, and survey efforts vary considerably across geographical regions [The amount of time that has elapsed since introduction will influence the extent of spread. In our dataset, there is a 12-fold difference in the number of years since the earliest and most recent introductions  was insufficient for a robust analysis.Given the numerous sources of variance in the dataset, the variety of factors that determine invasion success, and the diversity of taxa and systems examined, our finding that (c)FST to predict the geographical spread of alien species is confounded by secondary introductions or human-mediated dispersal within the introduced range [The power of ed range . For exaed range , whereased range –50. The (d)Several reviews have attempted to identify characteristics that predict invader success. However, none have attempted to correlate realized dispersal with invasiveness. Kolar & Lodge  review t(e)F-statistics to predict the outcome of marine introductions is a novel approach that shows considerable promise. FST as a surrogate for realized dispersal incorporates many of the species-level characteristics that are known to influence invader success: reproductive strategy, habitat specificity and ecology [FST, our data do not address the important question of whether a species is likely to become established. Instead, FST would be most useful to wildlife managers when incorporated into specific risk assessment models with success and failure trees for each stage of introduction. In this context, STF could be used to determine which species, once established, are likely to become widespread, providing wildlife officers with a stronger scientific foundation for setting management priorities.Using  ecology . While o


Platycercus elegans) parrot species complex. Parrots are well known for their life-long vocal learning and cognitive abilities. We analysed contact calls across a ca 1300 km transect encompassing populations that differed in neutral genetic markers and plumage colour. We found steep clinal changes in two acoustic variables . The positions of the two clines in vocal traits were concordant with a steep cline in microsatellite-based genetic variation, but were discordant with the steep clines in mtDNA, plumage and habitat. Our study provides new evidence that vocal variation, in a species with vocal learning, can coincide with areas of restricted gene flow across geographically continuous populations. Our results suggest that traits that evolve culturally can be strongly associated with reduced gene flow between populations, and therefore may promote speciation, even in the absence of other barriers.Contact zones between subspecies or closely related species offer valuable insights into speciation processes. A typical feature of such zones is the presence of clinal variation in multiple traits. The nature of these traits and the concordance among clines are expected to influence whether and how quickly speciation will proceed. Learned signals, such as vocalizations in species having vocal learning , can exhibit rapid change and may accelerate reproductive isolation between populations. Therefore, particularly strong concordance among clines in learned signals and population genetic structure may be expected, even among continuous populations in the early stages of speciation. However, empirical evidence for this pattern is often limited because differences in vocalisations between populations are driven by habitat differences or have evolved in allopatry. We tested for this pattern in a unique system where we may be able to separate effects of habitat and evolutionary history. We studied geographic variation in the vocalizations of the crimson rosella ( A fundamental property of contact zones between subspecies or closely related species is the presence of stable and concordant steep clines in multiple traits. This can arise either from secondary contact of formerly isolated divergent populations or environmentally induced evolutionary divergence along environmental gradients, and can be a stage in the process of speciation Divergence between populations may be more rapid if such signals are learned rather than genetically determined Platycercus elegans) form steep plumage colour and genetic clines, however these clines are discordant P. e. elegans) and the contrastingly yellow rosella (P. e. flaveolus), meet in riparian habitats along a major river system and form a narrow hybrid zone ca 200 km west of the hybrid zone were consistently more similar genetically to crimson populations elsewhere in south-eastern Australia Studies of several parrot species to date confirm that their calls are learned throughout their lifetime and fulfil a variety of social functions P. elegans for vocal characters in and on either side of the area where we have previously identified discordance between microsatellite and phenotypic diversity P. elegans.We intensively sampled these closely related but genetically divergent populations of This study conformed to the laws for animal experimentation in Australia , and was carried out on privately owned properties with permission.P. e. flaveolus), to Canberra , which lies within the range of the crimson rosella subspecies (P. e. elegans). These sites encompassed two genetic clusters identified by a previous Geneland analysis of 14 microsatellite loci where they were termed CentralGL and EasternGL and two mtDNA (ND2) haplotype groups in earlier work by our group We recorded 182 free-living individuals from 12 sites along the Murray-Murrumbidgee river system in Australia . These sP. elegans contact call, which is the most common call produced by rosellas and is highly variable  were analyzed with Raven Pro 1.4  and Sound Analysis Pro (SAP) 1.04 r <0.378). P-values are two-tailed and results were considered significant when P<0.05.The five acoustic variables were tested separately, as combining the five acoustic variables using a principal component (PC) analysis would only allow for a small reduction in variables  and the pairwise correlation coefficients between the acoustic variables were typically low , with the fundamental frequency, where measured, typically falling into one of two frequency ranges, namely 0.7–1.0 kHz or 2.0–3.5 kHz .In most cases, contact calls consisted of harmonically rich notes  and peak frequency pattern varied clinally across the transect . FundameC-fit analysis of both the vocalization and microsatellite clines  showed tr = 0.41, P = 0.025). Mantel tests conducted on each acoustic variable separately , and possibly mean FM .A Mantel test using all five acoustic parameters at each site provided evidence for significant isolation-by-distance across the transect . This teparately  indicateP. elegans is spatially correlated with microsatellite-based genetic population structure far more strongly than with plumage coloration and mtDNA diversity over a 1300 km transect In this study we showed that learned vocal variation in C-fit allows identification of clines, tests of concordance, and comparison of unimodal, bimodal and trimodal models P. elegans colour variation, habitat matching  is unlikely to explain the vocal clines because acoustic variation was not concordant with known habitat or topographical variation: steep environmental gradients occur much further east of the vocalization and microsatellite clines, where crimson and yellow birds currently meet There are at least two possible explanations for steep vocal trait clines being roughly congruent with the steep, presumably neutral microsatellite cline, but very discordant with both plumage coloration and mtDNA variation. The simplest hypothesis is that secondary contact occurred between eastern and western populations and that the vocalization and microsatellite clines occur roughly where the contact first occurred. This could result in unimodal, bimodal or trimodal models fitting best depending on the extent of gene flow between the formerly isolated populations. The clines in plumage coloration and mtDNA may have moved eastward until they reached the present transition between open riparian woodland and higher elevation forest A second hypothesis is that the vocal traits differentiated at random and that this promoted pre-zygotic reproductive isolation arising from mate choice, which is among the functions demonstrated for parrot contact calls Amazona auropalliata) are among the most comprehensive in examining associations between avian vocal variation and genetic population structure. However, these studies did not find any evidence that geographic variation in contact calls To date, the studies by Wright et al. A likely explanation for the lack of concordance between dialects and population genetic structure reported in these and other previous studies Furthermore, habitat can determine which acoustic features of vocalizations will be favoured P. elegans, rapid geographical change in contact calls coincides with a steep, microsatellite-inferred  genetic cline across geographically continuous populations. Furthermore, these clines occur ca 100 km west of steep clines in mtDNA, plumage coloration and habitat. Our study provides new evidence that vocal variation, in a species with vocal learning, coincides with zones of relatively reduced gene flow even in the absence of barriers associated with morphological, habitat or mtDNA differences between populations. Our findings suggest that traits that may rapidly evolve culturally can be strongly associated with recent genetic divergence between populations, and therefore support the hypothesis that such traits can play a key role in promoting speciation. Whether these differences in calls are being used by individuals to discriminate between populations in the area where the genetic discontinuity was identified is unknown, and will require further research.The hypothesis that learned signals, such as many avian and mammal vocalizations, play a role in promoting population divergence and ultimately speciation remains contentious, and to date clear empirical evidence is still largely lacking. A key prediction of this hypothesis, however, is the concordant geographical patterns of signal variation and gene flow in the early stages of speciation. In this study we show that in Figure S1Histograms displaying the frequency distribution of values of all five acoustic variables for the four sites (Forest 1–4) comprising the area where clines in microsatellite markers and acoustic variation were observed. Frequencies represent the number of calls.(TIF)Click here for additional data file.Figure S2Histograms displaying the frequency distribution of values of the five acoustic variables separately for the four recording sites (Forest 1–4) comprising the area where clines in microsatellite markers and acoustic variation were observed. Each graph consists of four separate windows with histograms, each window displays the values for one recording site. Frequencies represent the number of calls.(TIF)Click here for additional data file.Figure S3Plots of Euclidian distances between five acoustic variables derived from rosella contact calls versus geographic distance along the path of the river. The acoustic variables shown are (a) call duration, (b) peak frequency, (c) fundamental frequency, (d) mean frequency modulation, and (e) peak frequency pattern. The Euclidian distance for each acoustic variable is the absolute difference between each recording site in the average value of that acoustic variable. Circles represent comparisons among the four recording sites within each microsatellite group, and bi-coloured squares represent comparisons between recording sites in different microsatellite groups. Colours indicate the microsatellite groups involved in each comparison: Central vs. Central (yellow circles), microsatellite contact zone vs. microsatellite contact zone (purple circles), Eastern vs. Eastern (red circles), Central vs. Eastern (yellow and red squares), Central vs. microsatellite contact zone (yellow and purple squares), Eastern vs. microsatellite contact zone (red and purple squares). Mantel tests indicate significant or near-significant isolation-by-distance in fundamental frequency , peak frequency pattern , and mean frequency modulation , but not call duration  or peak frequency .(TIF)Click here for additional data file.


Lutzomyia gomezi  is one of the main Leishmania (Vianna) panamensis vectors in Panama, and despite its medical significance, there are no population genetic studies regarding this species. In this study, we used the sequences of the mitochondrial gene cytochrome b/start of NADH1 and the nuclear elongation gene α-1 in order to analyze genetic variation and phylogeographic structure of the Lu. gomezi populations.Lu. gomezi individuals were captured in 38 locations where cutaneous leishmaniasis occurred. DNA was extracted with phenol/chloroform methods and amplification of genes was performed using PCR primers for mitochondrial and nuclear markers.A total of 86 We found a total of 37 and 26 haplotypes of mitochondrial and nuclear genes, high haplotype diversity (h) for all three populations were detected with both molecular markers. Nucleotide diversity (π) was estimated to be high for all three populations with the mitochondrial marker, which was opposite to the estimate with the nuclear marker. In the AMOVA Φst recorded moderate  and small (nuclear) population structure with statistical significance among populations. The analysis of the fixation index (Fst) used to measure the differentiation of populations showed that with the exception of the population located in the region of Bocas del Toro, the other populations presented with minor genetic differentiation. The median-Joining network of the mitochondrial marker reveled three clusters and recorded four haplotypes exclusively of localities sampled from Western Panama, demonstrating strong divergence. We found demographic population expansion with Fu´s Fs neutrality test. In the analysis mismatch distribution was observed as a bimodal curve.Lu. gomezi is a species with higher genetic pool or variability and mild population structure, due to possible capacity migration and local adaptation to environmental changes or colonization potential. Thus, knowledge of the genetic population and evolutionary history is useful to understand the implications of different population genetic structures for cutaneous leishmaniasis epidemiology. Leishmania (Vianna) panamensis and Lutzomyia ylephiletor, Lu. sanguinaria, Lu. panamensis, Lu. trapidoi, Lu. gomezi were identified as the transmission vectors [Cutaneous leishmaniasis is the most common form of leishmaniasis reported in the Republic of Panama; its clinical manifestations range from minor lesions to severe skin ulcers -3. In Pa vectors -8.Lutzomyia (Lutzomyia) gomezi  is the most abundant species with wide geographical distribution and their abundance has been associated with cases of clinical CL acquired in households of rural communities [Lu. gomezi other Lutzomyia species vectors have been caught in the same place and associated with a focus of cutaneous leishmaniasis infection in other American countries, incriminating this species with high potential in the transmission of the disease [In Panama, recent research has show that  disease ,10-14.Lutzomyia (Lutzomia) gomezi in Central America is present from Mexico to Panama and Trinidad Tobago (Caribbean), also recently reported in Guatemala [uatemala . In Soutuatemala -17.In general, its natural environment is a humid and dark place, such as nests, rock crevices, animal burrows and tree bark in the tropical rainforest . HoweverLu. gomezi as a Leishmania vector, few researches have targeted genetic aspects or interrelationship of host-vector species. For instance, [Lu. gomezi with the Le. braziliensis in Venezuela, in order to establish a methods for determine the circulation of Leishmania parasites in leishmaniasis endemics areas. On the other hand, [ser of the species; Lu. trinidadensis , Lu. (Psychodopygus) panamensis, Lu. (Micropygomyia) cayennensis cayennensis, Lu. dubitans (Migonei group), Lu. (Lutzomyia) gomezi, Lu. rangeliana (ungrouped) and Lu. evansi (Verrucarum group) for taxonomic purposes, considering that morphological identification can be difficult. Also, [Lu. gomezi infected with Le. naiffi in Panama, the first report for the country which prompted several hypotheses on the introduction of this parasite into this country.Despite of the potential significance of nstance,  detecteder hand,  analyzedt. Also,  detectedLu. longipalpis and Phlebotomus papatasi to determinate their genetic variation, structures and differentiation of populations [Lu. longipalpis complex has been fundamental to the understanding of leishmaniasis epidemiology. Symptoms observed for transmission of Leishmania infantum chagasi by Lu. longipalpis in Brazil and Colombia results in visceral infections, whereas the transmission of the same parasite by Lu. longipalpis in Costa Rica results in non-ulcerative lesions [Attempts to understand the role that arthropod vectors play in disease dynamics and pathogen transmission of leishmaniasis, several studies over genetic population of sandfly vectors has been performance in the Latin America, Iran, Turkey, Palestine, Israel and Egypt -30. Manyulations ,28,31,32 lesions ,34.Thus, it becomes important to analyze the population genetics and demographic history of this vector species to assess the genetic pool, gene flow and colonization potential, consequently known as the population changes and genetic variation affecting the vector competence and resistance to insecticides ,36. On tLu. gomezi species in Panama and the Americas as a whole, the goal of this research was to evaluate and compare the intra- and inter-population variability of Lu. gomezi from localities with a high incidence of cutaneous leishmaniasis in Panama. Also to identify the barriers that may influence gene flow among Lu. gomezi populations. Moreover, to infer the historical processes that defines actual geographic distributions of the species. These results may contribute on the knowledge of leishmaniasis epidemiology and improve the development of focal or large-scale programs control for leishmaniasis vectors in Panama.Due to the lack of population genetics information of The study was performed in the Republic of Panama between the coordinates 7º11′-9°39′N and 77º10′-83º03′W. The most prevalent climatic regime in Panama is tropical humid, with the dry season (January-March) presenting an average temperature of 31.5ºC and relative humidity of 75%. In other months (April-December), the average temperature is 27ºC and the relative humidity averages 90%. The vegetation in Panama varies according to climate zones and consists mainly of tropical humid forest or savannahs resulting from agricultural activity.Lu. gomezi samples were collected from the thirty-eight localities in Panama, during the dry season (January-April) and rainy season (May-June) of 2010. Thirty-four sites were chosen, representing incidence with cases of cutaneous leishmaniasis in humans during the 2006–2009 period, according to data from the Department of Epidemiology of the Ministry of Health of Panama; four sampling sites were in Panamanian tropical forests. The geographic distribution of the samples locations are indicated in Figure The characteristic of the thirty-four collecting sites according to the landscape was fragmented environment  or rural (an area without a large concentration of people). The Coiba National Park, San Lorenzo Park, Oil Pipeline Road Park, and the Serrania Filo del Tallo Park represent natural reserves (forests) protected by the National Environment Authority of Panama (ANAM). The samples localities are listed in Table Lu. gomezi used in the study were caught using CDC light traps and octenol solution utilized to attract hematophagous insects [Specimens of  insects . The traLu. gomezi were identified by morphology and genital structure using the identification keys of [A total of nine CDC light traps were exposed at a height of 1.5 m in each locality and were installed at approximately 50 m intervals. The collection period was of 12 h (18:00 h-06:00 h) for two consecutive days at each point. The specimens were sacrificed with chloroform and stored in 95% ethanol at −20°C. Adult  keys of .The DNA of 86 individual sandflies was isolated by a standard phenol/chloroform technique, precipitated with ethanol and resuspended in Tris-EDTA (TE) buffer according to , with soLu. gomezi. The region of mitochondrial genes analyzed was final Cytb gene, inter-genetic region IGS-1, tRNA-Ser, inter-genetic region IGS-2, and start of the NADH1 (CB3-NIN), and amplified using primers CB3-PDR: 5′CAYATTCAACCWGAATGATA3′/N1N-PDR:5′GGCAYWTTGCCTCGAWTTCGWTATGA3′ [Two mitochondrial and nuclear genes were analyzed to estimate the structure and geographic genetics within and among populations of WTATGA3′ . NuclearWTATGA3′ .++, 0.2 mM of each dNTPs, 0.4 μM of each primer, 1.5 units of Taq polymerase and approximately 2 μl of DNA (≈50 ng/μl) template. The details of thermal cycling conditions were outlined by [PCR amplification of genes were performed in a volume of 25 μl containing 1× buffer, 1.5 mM MgCl2lined by  for CB3-lined by  for EF αLu. gomezi stored in the database. The CodonCode Aligner software was used to edit the nucleotide sequences and identify the heterozygous as double peaks on the chromatograms of the nuclear region. The sequences were aligned with the Muscle option included in the MEGA 5.05 software [PCR products were purified and sequenced directly by the Macrogen INC., Seoul, Korea Sequencing Service in both directions with the same primers used in the amplifications. The sequences were compared to the nucleotide BLAST  tool available in GenBank NCBI  in order to verify the similarities between the sequences of software . The polTo carry out an analysis of population genetics  to specimens collected in different localities, we clustered and defined samples in western, central and eastern populations from Panama Table . Thus, tWe emphasized that heterozygotes detected in the EF α-1 were treated with recombination model in PHASE option, incorporated in the DnaSP v.5. To estimate the genetic diversity we used the following indexes: haplotypes number, haplotype diversity (h), and nucleotide diversity (π) for each population. DnaSP v.5  and ArleThe population structure was determined performing an Analysis of Molecular Variance (AMOVA) ,46. The A haplotype network for both genes was inferred through the median-joining network method , using tIn addition to this, Tajima’s D  was usedHeliconius erato[The mismatch distribution was calculated for CB3-N1N and EF α-1 as supplementary test to evidence of demographic expansion of the population, through sudden expansion model . In Arleius erato.Lu. gomezi individuals from 38 selected localities from Panama Isthmus were analyzed. Of these, an alignment of 501 nucleotides was obtained of CB3-N1N with thirty-nine polymorphic sites and nineteen single substitutions (singleton). The average base frequencies were A = 37%, C = 15%, G = 10%, and T = 38% recording a sequence rich in A-T (75%). A fragmented size of EF α-1 was 597 bp, in this case 166 sequences were obtained by clone generating with the recombination model algorithm of DnaSP v.5 considering the heterozygous individuals. Of those sequences, thirty-three polymorphic sites, six singletons and a larger proportion of G-C (53%): 23%T, 27%C, 23%A, 27%G, were detected.Overall, 86 sequences isolated of CB3-NIN and EF α-1 of For the analysis of genetic diversity indexes both CB3-NIN and EF α-1 region demonstrated high haplotype diversity (h) for all three populations Table . While tIn the AMOVA Φst estimated between the three populations, CB3-N1N region recorded moderate and EF α-1 small population structure with statistical significance among populations. The total genetic variation found within the populations was ≈ 86% (CB3-NIN) and ≈ 95% (EF α-1) as shown in Table The median-Joining network reconstructed with CB3-NIN region linked a total of 37 different haplotypes with three defined clusters . The lack of hierarchic structure is observed in the cluster “A”, this clade consists of 28 haplotypes, the most frequent, H10, was found in eleven localities sampled in Central Panama and six in Eastern Panama. It also included Altos de Piedra and Coiba haplotypes from Western Panama. Cluster “B” is constituted by four haplotypes. Of these, H15 was collected from six sites in Central Panama and nine from Eastern Panama, with H23 being the most frequent [Figure Lu. gomezi populations. The patterns of a star-like shape as similarly obtained with the mitochondrial region, showed haplotype H1 as the most frequent in the center and several haplotypes surrounding it with one and three mutational steps [Figure On the other hand, analysis linked a total of 26 haplotypes of the EF α-1 region demonstrating a lack of genetic structure in the a posteriori probability of 0.99-1.0. Other minor clusters were supported by low a posteriori probability values. The cluster with a higher a posteriori probability corroborated the divergences obtained in the haplotype network, inferred by the median-joining method [Figure The Bayesian phylogenetic tree for the CB3-NIN region showed three clusters with d Figure A and B. We found 50% of the haplotypes in the peridomestic areas of fragmented environments, 40% in rural environments, and 10% in forest environments. Although this information is additional and not the main focus of the research, the predominance of the haplotypes in these sites is important to highlight due to the anthropogenic impact on the landscape of Panama [Table The results of Tajima D test (CB3-NIN) were negative but not significant  that indicated neutrality deviation due to a demographic expansion or not neutral selection. Nevertheless, Fu´s Fs values were significantly negative  detecting that a population expanded in the past. The assessment of demographic change with EF α-1 region using both Tajima D and Fu´s Fs was significantly negative  respectively.Considering that Fu´s Fs are sensitive estimators for detecting demographic population expansion, we included the analysis of mismatch distribution for characterization of expansion detected with both genes. A bimodal curve was observed with CB3-NIN region and smoother curves with EF α-1 region. SSD value  for CB3-NIN did not reject the sudden expansion model, while SSD value  for EF α-1 region was observed. The Harpending´s raggedness index determined a good fit of data  and Culex pipiens (63%), characteristically of intron region [The use of the mitochondrial and nuclear marker in ecology has provided enough information to allow contrast of the past population processes of species . The higu. evansi,55. Thisu. evansi. A highen region ,58.Lu. gomezi. The existence of this polymorphism is important for the survival and adaptability, considering that the natural habitat of Phlebotominae sandflies is destroyed because of anthropogenic factors [The high haplotype diversity detected among populations indicated a large polymorphism or gene pool of the  factors . However factors . While t factors .Lu. longipalpis, Lu. intermedia and Lu. shannoni over a distance between 8 to 15 km, which suggested that individuals from sandfly populations were capable of flying more than 57 m, as previously recorded for sandfly species [Lu. gomezi is able to disperse over long distances, which could be gradually helped by the winds (adults) or passive movement of eggs and larvae. Studies across distant localities using other molecular markers are necessary to define vector capacity to disperse.The result obtained from AMOVA showed mild genetic structure but greater genetic variation within populations. The explanation is that gene flow occurs between the different populations, probably caused by the flying capacity of the species increasing their migratory potential. Similar results were found from the analysis of population genetics of  species ,60-64. TLu. gomezi, estimated between 175–300 meters high [Anopheles albimanus populations from Costa Rica and Panama, also suggesting that the Central American mountain range is a physical barrier that limited the gene pool of malaria vector mosquitoes [Meanwhile, pairwise Fst-value demonstrated significant genetic differentiation with the CB3-NIN region of the populations from Western Panama and Central Panama. We think that this genetic differentiation observed is influenced by the central mountain range with altitudes of 2,468 to 3,475 m. The mountain range represents a geographic barrier restricting altitudinal distribution of ers high . Similarsquitoes ,67.On the other side, slight genetic differences were detected from CB3-NIN and EF α-1 regions, among the sandfly populations from Eastern Panama and Central Panama  could be explained because of the variety of climate and vegetation in Panama. The climate of Panama is influenced by the Inter-tropical Convergence Zone, oscillating one year to other and from one region to another. This variation allowed three types of tropical climate: Afi (very humid), Ami (humid), Awi (dry), according to Köppen Climate Classification . The samLu. gomezi samples from Central Panama were collected from borderline locations of tropical forest vegetation of low lands. While the Eastern Panama populations were from areas of vegetation in regeneration with evident anthropogenic impact. Thus, both climate and vegetation defined different ecotypes that can restrict gene flow due to environmental gradient. Climate changes were also used by [Lu. whitmani.As a result, the type of tropical climate of Panama provides enough conditions to enable vegetation heterogeneity and refuge for a great diversity of species . Lu. gom used by  to justiLu. gomezi populations. The haplotypes of CB3-NIN  and haplotype EF α-1 (H-1) are older alleles or ancestral haplotypes dispersed in the Isthmus. The network patterns in clusters A and B for the CB3-NIN region and network EF α-1 region could be explained due to the sandflies migration with their hosts, mainly mammals.The star-like shape of network haplotypes, both for CB3-NIN and EF α-1, reflected a rapid and recent expansion of Lu. gomezi because fossil records from the Miocene showed the presence of sandflies in fragments of mammal hair and in the microstructure of bird plumages in the Dominican Republic, suggesting their relationship with several hosts and possibly their transportation mechanism [Several mammal species  that currently are sandfly hosts established themselves in Panama during the north–south migration that took place during the closure of the Isthmus between the Miocene-Pliocene epochs -73. We sechanism .Lu. gomezi from the continent. Coiba was a continental island separated from South America in the Eocene, laying next to the Isthmus of Panama due to the decrease in the sea level in the last glaciation. This could have enabled the migration of wild animals and later, when the sea level increased, Coiba was isolated [The H6 of CB3-NIN region from Coiba National Park (Veraguas) probably derived from the H11 detected in the populations of Central Panama, which indicates a possible migration of isolated ,76. ThesThe cluster B clearly showed the divergence in a west population (Bocas del Toro) and this strengthened significantly with the Fst-value Table , we suppLu. gomezi because of disturbed areas. However, it is necessary to establish the consequences of fragmentation forest in the population genetics by increasing sampling in local forests.The fragmentation of the forests on Panama is reported since pre-Columbian times ,78. The The neutrality tests Fu´s Fs results were significantly negative, and mismatch distribution statistic and network haplotype support the assumption of population expansion in the past. Moreover, high haplotype diversity but low nucleotide diversity in EF α- region also suggests population expansion.Is it the fact that the closure of the Isthmus of Panama affected by climate change in the world was the main factor that enabled the establishment of several species in America, allowing for faunal exchanges between North and South . An alteLu. gomezi is a species with a higher genetic pool or variability and mild population structure, due to possible capacity migration and local adaptation to environmental changes or colonization potential. However the existence of geographic barriers, such as the central mountain range separates a subpopulation. The establishment of Lu. gomezi in the Isthmus of Panama could be interpreted by the exchange of mammals in the American continent, vegetation and climate conditions of the epoch. Their relevance as a carrier of cutaneous leishmaniasis in Panama is important for health schemes, especially if we consider that sandflies have a wide-spread geographic distribution in Panama, and this distribution is possibly associated to the landscape changes caused by deforestation [In conclusion, estation . In thisCL: Cutaneous leishmaniasis; CB3-NIN: Cytb gene, inter-genetic region IGS-1; tRNA-Ser: Inter-genetic region IGS-2, and start of the NADH1; EF α-1: Elongation factor alpha-1.The authors declare that they have no competing interests.Conceived and designed the experiments: AVC, MGT. Performed the experiments: AVC. Analyzed the data: AVC. Contributed reagents/materials/analysis tools/specimens identifications: MGT, JDAF. Wrote the paper: AVC, JDAF and MGT. All authors read and approved the final version of the manuscript.Bayesian tree based on mitochondrial CB3-N1N of populations of Lu. gomezi.Click here for fileBayesian tree based on nuclear EF α-1 of populations of Lu. gomezi.Click here for fileMismatch distribution of Lu. gomezi species based on (A) mitochondrial sequence CB3-N1N and (B) nucleotide sequences EF α-1.Click here for file


Gorilla gorilla gorilla) are designated as critically endangered and wild populations are dramatically declining as a result of habitat destruction, fragmentation, diseases  and the illegal bushmeat trade. As wild populations continue to decline, the genetic management of the North American captive western lowland gorilla population will be an important component of the long-term conservation of the species. We genotyped 26 individuals from the North American captive gorilla collection at 11 autosomal microsatellite loci in order to compare levels of genetic diversity to wild populations, investigate genetic signatures of a population bottleneck and identify the genetic structure of the captive-born population. Captive gorillas had significantly higher levels of allelic diversity  and heterozygosity  than comparative wild populations, yet the population has lost significant allelic diversity while in captivity when compared to founders . Analyses suggested no genetic evidence for a population bottleneck of the captive population. Genetic structure results supported the management of North American captive gorillas as a single population. Our results highlight the utility of genetic management approaches for endangered nonhuman primate species.Western lowland gorillas ( Gorilla gorilla gorilla) are facing dramatically declining numbers, as high as 80% over three generations, as a result of habitat destruction and fragmentation, the illegal bushmeat trade, and diseases such as Ebola  are separated from eastern gorillas  by the Congo River in central Africa. Eastern gorillas are listed as endangered at the species level and the mountain gorilla subspecies (G. b. beringei) is listed as critically endangered  were obtained from fibroblast cell lines located in the Integrated Primate Biomaterials and Information Resource collection at the Coriell Institute for Medical Research.DNA samples for captive western lowland gorillas (G. g. diehli) from the Cameroon-Nigeria border (Bergl G. g. gorilla) from Loango National Park, Gabon, and Mondika in the Central African Republic  from Bwindi Impenetrable Forest, Uganda and Volcanoes National Park in Virunga Mountains, Rwanda  to be small, comparable populations.Comparative datasets for this study came from five wild populations of gorillas and one founder population of the captive North American western lowland gorillas  DNA template for a final volume of 20 μL. Thermocycler protocol included a 10 min initial denaturing at 95°C, followed by 40 cycles of 94°C denaturing for 30 sec, 55–60°C annealing for 30 sec (PCR reactions were carried out with the following: 10 μL (5 U/μL) AmpliTaq Gold , 0.4 μL (10 μmol/L) of forward and reverse primers, 7.7 μL dHr 30 sec , 72°C exr 30 sec .NA), and number of effective alleles , a measure of alleles which controls for differences in sample size, was calculated for the captive-born and Loango populations in FSTAT 2.9.3.2  using t-tests. Levels of observed heterozygosity (Ho), and expected heterozygosity (He), were calculated in GenAlEx 6.01 , was calculated similar to Nsubuga et al. ] was averaged over independent runs for each value of K. Runs of high K values can potentially increase the posterior probability as well as variance between independent runs, leading to an overestimation of K  across consecutive values of K. The use of ΔK to identify breakpoints in the dataset results in the true value of K being that with the greatest ΔK.Genetic population structure in the captive-born population of gorillas was inferred using STRUCTURE 2.3.3  in order to assess whether the captive-born population would cluster with the Loango population, which is the closest population to founders as well as being the same sub-species, to the exclusion of the Cross River and Virungas. Assignment tests were carried out in GenAlEx 6.01  and Loango (vWF), a single locus was observed to deviate from Hardy–Weinberg equilibrium. Deviations that have been previously described in Cross River (D5s1470 and D8s1106), Bwindi and Virunga populations  were attributed to the inclusion of related individuals in the sample  from STRUCTURE found a major breakpoint in the data with the highest likelihood of clusters at K = 3 . The standardized differences test was also significant (P = 0.005). These results were not surprising as only a severe bottleneck would be detectable after only two generations. Further, if there were evidence of a bottleneck it would more likely reflect the demographic history of the source populations.The results of the BOTTLENECK analysis differed based on model choice but did not suggest the occurance of a bottleneck. The BOTTLENECK results using the TPM model were not significant according to any of the three tests, under any of the step-wise runs. Similarly, under a strict SMM, all three tests were not significant. In contrast, under a strict IAM, the Wilcoxon sign-rank test was significant for a one-tailed test of NA, AR and effective alleles than the wild populations. The captive-born population was significantly higher than all wild populations in mean AR, which is the most informative measure between these datasets. This meets the expectation that the captive-born gorillas would have high levels of allelic diversity when considering that the founder gorillas also have higher measures of allelic diversity than all wild populations. For all three measures, NA, AR and AE, the founder population had higher values than the captive-born, suggesting that while still high, the captive gorilla population has lost some allelic diversity present in the founder population. Ho was significantly higher in captive-born than founders, despite there being no significant difference in He. This observation of decreased allelic diversity but increased Ho from the founder to captive-born population is interesting. We interpret this observation to be an artifact of changes to breeding protocols. Until recently breeding pairs were determined based on flawed pedigrees and closely related individuals were known to have bred  and NA have not had enough time to rebound through mutation. For measures of both allelic diversity and heterozygosity, the captive population is higher than all wild populations, despite the having lost allelic diversity since being in captivity.Concerning the genetic diversity of the North American captive population of western lowland gorillas, they show high levels of both allelic diversity and heterozygosity. The captive-born population had a higher mean Based on the results of the STRUCTURE analysis, captive-born gorillas form two clusters, which is consistent with the clustering of the wild-born founders (Nsubuga et al. All tests under both a TPM and strict SMM were not significant. Results from both the Wilcoxon sign-rank test and standardized differences test under a strict IAM were significant, yet the IAM is the least conservative mutation model. The SMM, and to a greater degree, the TPM are considered more informative models in addressing questions of demographic history. These results suggest that there is no genetic evidence for a population bottleneck in this captive collection. While the population has lost allelic diversity, enough diversity has been maintained in the population that they are still significantly higher than comparable wild populations for several diversity measures. These results also suggest that despite flaws in pedigree information on founder gorillas, genetic management of this population has been successful in maintaining high levels of genetic diversity.There is currently no scientific justification for the use of the North American captive gorilla population as a source for reintroduction of individuals to the wild (Beck et al. File with genotype dataset.Readme.txt file for above referenced data file.


Human impacts through habitat destruction, introduction of invasive species and climate change are increasing the number of species threatened with extinction. Decreases in population size simultaneously lead to reductions in genetic diversity, ultimately reducing the ability of populations to adapt to a changing environment. In this way, loss of genetic polymorphism is linked with extinction risk. Recent advances in sequencing technologies mean that obtaining measures of genetic diversity at functionally important genes is within reach for conservation programs. A key region of the genome that should be targeted for population genetic studies is the Major Histocompatibility Complex (MHC). MHC genes, found in all jawed vertebrates, are the most polymorphic genes in vertebrate genomes. They play key roles in immune function via immune-recognition and -surveillance and host-parasite interaction. Therefore, measuring levels of polymorphism at these genes can provide indirect measures of the immunological fitness of populations. The MHC has also been linked with mate-choice and pregnancy outcomes and has application for improving mating success in captive breeding programs. The recent discovery that genetic diversity at MHC genes may protect against the spread of contagious cancers provides an added impetus for managing and protecting MHC diversity in wild populations. Here we review the field and focus on the successful applications of MHC-typing for conservation management. We emphasize the importance of using MHC markers when planning and executing wildlife rescue and conservation programs but stress that this should not be done to the detriment of genome-wide diversity. ConversGenetic diversity may be reduced as a consequence of periods of fragmentation and decreased population size (bottlenecks). At first, it may seem that such loss of genetic diversity is only of concern for long-term evolutionary adaptation. However, there are immediate short-term implications as well. Loss of genetic diversity is intimately related to an increased risk of inbreeding depression resulting in decreased growth rate, fertility, fecundity and offspring viability –12. Althi.e., not directly targeted by selection. However, emerging evidence shows that patterns of variation and divergence in adaptive traits are not always associated with concomitant variation in neutral markers and several studies have questioned the validity of using only neutral markers for development of conservation strategies [During the last two decades, microsatellites (sections of DNA consisting of very short repeated nucleotide sequences) have frequently been employed in quantifying population genetic diversity and the results from such studies have often provided the basis for management recommendations (reviewed in ). The frrategies –30.Two central questions in conservation genetics are: (1) the degree to which genetic bottlenecks and low effective population size will reduce genetic diversity within a population; and (2) the impact of this reduction on the population’s long-term viability. In particular, will genetic diversity be reduced to a similar degree throughout the genome, or will some loci be affected more than others? The strength of the relationship between genetic variation and effective population size varies for different categories of markers which are subject to different intensities of selection ,21,22,312.2.1.The Major Histocompatibility Complex (MHC) plays a crucial role in the vertebrate immune system by encoding a collection of immune and non-immune related molecules ,42. The MHC Class III contains a variety of genes that do not have antigen presenting capacity, but code for other immune functions, such as complement components  and cytokines .2.2.Two, not mutually exclusive, hypotheses have been suggested to explain the high level of MHC polymorphism: (i) pathogen-driven selection –57; and It is generally believed that some form of pathogen-driven balancing selection, a broad term that identifies any kind of natural selection where no single allele is absolutely most fit, is responsible for the high polymorphism of the MHC genes, but the exact nature of the selection continues to be a topic of debate ,61. A re2.3.Ailuropoda melanoleuc) has recently been sequenced and the number of endangered species targeted for genome sequencing is rapidly increasing [Sarcophilus harrisii) [The primary use of MHC genes in conservation to date has been for quantifying genetic diversity of natural populations, without specific conservation management implications . The extcreasing . The abicreasing ,68,69. Acreasing ). A key arrisii) . The useMyodes glareolus) [Ficedula albicollis) [The rapid evolution of NGS technologies will enable such a multi-gene approach. The latest ultra high-throughput Next-Generation Sequencing (NGS) technologies are relatively low cost, quick and easy to scale up or down . A fareolus)  and the icollis) , and it icollis) . A softwicollis) ,77,78. I2.4.Maintenance of high levels of MHC polymorphism is crucial to counteract novel pathogenic challenges and to ensure organismal long-term survival ,63,79–81As mentioned previously, MHC markers have been used on endangered species (a selection of these studies is summarized in 2.5.Ailurus fulgens) [Okapia johnstoni) and the lowland gorilla (Gorilla gorilla gorilla) [In order to minimize kinship, and reduce the deleterious effects of inbreeding in captive breeding programs, zoos rely on studbooks –112. Stufulgens) , okapi (gorilla) . Captive2.6.et al. [Vipera berus) halted the population’s decline. The genetic polymorphism of MHC genes in the population increased following the introduction of new snakes. The once severely inbred and isolated population of Swedish vipers continues to thrive and expand [Translocation of individuals from genetically and demographically healthy population to populations suffering from significantly reduced genetic diversity  allet al.  showed td expand .2.7.et al. [The emergence of virus-associated, carcinogen-related wildlife cancers  and tranet al. ,122 founet al. . Devils et al. ,108. Conet al. . A thirdet al. ,124 furtet al. ,125–127.DFTD provides a powerful example of how the loss of genetic diversity within populations, together with an infectious disease with frequency-dependent transmission, can cause extinction and presents a cautionary tale and a warning for conservation biologists to be aware of unusual diseases in inbred populations . In conc3.Anthropogenic activities have resulted in the extinction of numerous species and massive reductions in the population numbers of others. A consequence of this is loss of genetic diversity and a primary focus of conservation biologists has been quantifying genetic diversity of endangered and threatened species. A wide range of different genetic markers have been employed in conservation studies. We argue that with increasing accessibility to next-generation sequencing technologies, MHC and other immune-related genes should be used in addition to other markers, to provide indirect measures of the immunological fitness of populations as well as the evolutionary and adaptive potential of populations—especially those threatened by disease. We emphasize that there is still scope to increase the use of MHC and other adaptive markers for management of captive-bred populations and for genetic rescue programs. Both of these conservation measures require understanding of complex evolutionary, genetic and non-genetic  factors, and therefore it is crucial to monitor genetic diversity pre- and post-management. Future studies should also focus on the spatiotemporal changes in host resistance to pathogens in natural populations. We envisage that NGS technologies will soon become the main tool for conservation geneticists, and will enable the real-time monitoring of microevolutionary processes, including host-parasite evolution across populations and entire species.


Procyon lotor). We measured heterozygosity at 14 microsatellite loci and modeled the effects of both multi-locus and single-locus heterozygosity on parasitism using an information theoretic approach and including non-genetic factors that are known to influence the likelihood of parasitism. The association of genetic diversity and parasitism, as well as the relative importance of genetic diversity, differed by parasitic group. Endoparasite species richness was better predicted by a model that included genetic diversity, with the more heterozygous hosts harboring fewer endoparasite species. Genetic diversity was also important in predicting abundance of replete ticks (Dermacentor variabilis). This association fit a curvilinear trend, with hosts that had either high or low levels of heterozygosity harboring fewer parasites than those with intermediate levels. In contrast, genetic diversity was not important in predicting abundance of non-replete ticks and lice (Trichodectes octomaculatus). No strong single-locus effects were observed for either endoparasites or replete ticks. Our results suggest that in outbred populations multi-locus diversity might be important for coping with parasitism. The differences in the relationships between heterozygosity and parasitism for the different parasites suggest that the role of genetic diversity varies with parasite-mediated selective pressures.Understanding factors that determine heterogeneity in levels of parasitism across individuals is a major challenge in disease ecology. It is known that genetic makeup plays an important role in infection likelihood, but the mechanism remains unclear as does its relative importance when compared to other factors. We analyzed relationships between genetic diversity and macroparasites in outbred, free-ranging populations of raccoons ( While most individuals in a host population carry few or no macroparasites of a particular species, a few individuals harbor high numbers of parasites Tribolium castaneum) that had coevolved with a microsporidian parasite had higher levels of heterozygosity than control lines that had not coevolved with the parasite. Underlying cross-population and interspecific relationships between genetic variability and parasitism is the differential susceptibility of individuals. Within populations, variance in host genetic diversity (measured as heterozygosity) can be an important predictor of parasitism. In wild populations it has been shown that individuals with lower heterozygosity may have higher infection frequencies and greater morbidity A primary focus of many theoretical and empirical studies has been to understand the linkages between the genetic diversity of host populations and their susceptibility to pathogens Associations between individual host genetic diversity and parasitism have frequently been studied using multi-locus heterozygosity at neutral genetic markers (microsatellites) as a proxy for genome-wide diversity [i.e heterozygosity-fitness correlations (HFC)]. Several studies have shown that the parasite HFCs were a consequence of inbreeding depression However, it has been difficult to generalize about correlations between neutral genetic variability and measures of parasitism since such patterns are sometimes equivocal. Results vary with the species of parasite studied and its fitness effects on the host as well as the general level of inbreeding of the host population. There are several examples where less heterozygous individuals were more susceptible to parasite infection Procyon lotor) for which we have collected data on behavioral, population, and habitat ecology and for which observational and experimental studies have identified non-genetic predictors of parasitism Here we address these issues by considering the relative importance of neutral genetic variability when compared to non-genetic factors that have been shown to be important in predicting parasitism. We focused on outbred, free-ranging populations of raccoons  and a collective measure of the extent of infection by internal macroparasites (endoparasite species richness). While ecto- and endoparasites may have important effects on host fitness, presumably these effects are less extreme and more variable than that of CDV, which can directly kill hosts. Using an information theoretic approach we selected the best models for each parasite and assessed whether individual genetic diversity is a significant predictor of the extent of ecto- and endoparasitism when placed in the context of non-genetic factors already identified as important predictors Research was carried out under Missouri Department of Conservation permit #12869, which specifically approved this study, and University of Missouri Animal Care and Use Protocol #3927.Raccoons were sampled between 2006 and 2007 at 12 forested sites located within 60 km of Columbia, Missouri, USA . DetailsRaccoons were trapped for ≥10 days at each site two to three times per year between March and November. Individuals were anaesthetized and ear-tagged, weighed, sexed, measured, and aged Dermacentor variabilis, and the chewing louse Trichodectes octomaculatusDermacentor variabilis is a 3-host metastriate tick that occurs on raccoons while feeding or mating. Adult D. variabilis are large (3–5 mm in length) and readily found and identified without magnification. We focused on adult ticks present between April and August, the primary period when this species parasitizes raccoons at our study area We focused on two species of ectoparasites: the American dog tick For sampling endoparasites, fresh feces were collected from within or below traps, homogenized, and stored in 10% formalin. The presence of endoparasite species was based on identification of ova and oocysts isolated by fecal flotation procedures using sugar and zinc sulfate centrifugation techniques. Additional methodological details and citations for endoparasite species descriptions and identification are provided elsewhere Total genomic DNA was extracted from blood samples using DNeasy Blood and Tissue Kits  with the manufacturer’s protocol and from hair samples using InstaGene Matrix kits  following enePop 3.4 www.zoo.cam.ac.uk/zoostaff/amos) we calculated three measures of individual genetic diversity: standard multilocus heterozygosity . Thus, sMLH, IR and HL were calculated based on gene frequencies pooled across all years and sites. These measures are frequently highly correlated and testing all of them could lead to pseudoreplication SMLH-IR = −0.980; rIR-HL = 0.980; rHL-SMLH = −0.992; all p<0.001). Therefore, since HL and sMLH had a correlation coefficient higher than 0.99, we excluded sMLH from further analyses. Simulations suggest that HL may be better correlated with inbreeding coefficient and genome-wide homozygosity than IR in populations that present levels of heterozygosity greater than 0.6. However, this only occurred in study populations with high genetic structure and admixture, and the differences were clearer when ≥50 markers were used We tested for deviations from expected genotype frequencies under Hardy-Weinberg equilibrium and for linkage disequilibrium between all pairs of loci using Gty sMLH;  and hetety sMLH; . sMLH rec) and then calculated the differences between the best approximating model (the model with the lowest AICc) and all the other models (ΔAICc), as well as Akaikés weights (Wi) and the evidence ratio (Δi), for each model in the candidate set For assessments of genome-wide genetic diversity effects, we used information-theoretic model selection a priori based on previous studies that identified important predictors of parasitism for each parasitic group c units of the best-fitting model and compared them to new models that included genetic diversity  as a covariate in all models that collectively included the 12 sites  to force a mean of 0 and SD of 0.5. We calculated model averaged estimates and odds ratios (±95% C.I.) for each variable in the 90% confidence set of models . All analyses were conducted using R.v.13.1 (R Development Core Team 2011); the libraries MASS, and AICcmodavg were used to carry out model selection and the library arm to standardize the variables. Ectoparasite abundance was analyzed using generalized linear models with a negative binomial distribution and a log link function For cases where the best models included a measure of genetic diversity we assessed the potential effects of single-locus heterozygosity. To do so, we selected the top model and replaced the multilocus heterozygosity measure with the single locus heterozygosity at each marker incorporated as a binary variable (0 if homozygous and 1 if heterozygous). We compared both models (the one fitting the multilocus heterozygosity and the one fitting the single locus effects) using an F-test to determine which of the two models explained significantly more variance non-replete = 0.95; Prevalencereplete = 0.55; Abundancenon-replete = 21.43; Abundancereplete = 1.99). Louse prevalence was 0.52 and mean louse abundance ranged from 0 to 55 with a mean of 3.03 (n = 307). The endoparasite community of raccoons at the study sites comprised 16 taxa Across all years tick prevalence was 96%, and individual abundance ranged from 0 to 142 with a mean of 23.43 ticks per individual n = 259; . PrevaleOf 380 raccoons sampled between 2006 and 2007, 94.7% were genotyped at ≥12 markers, and were included in subsequent analyses. Mean observed heterozygosity was 0.783 (SD = 0.094), mean expected heterozygosity was 0.793 (SD = 0.090), and mean number of alleles per locus was 11.3  and no other model fell within 3 ΔAIC units (Wi = 0.18) and the top models contained genetic terms (Wi = 0.73) (2) both alone or together with the linear IR term, revealing an underlying curvilinear association between parasite loads and IR. Model average estimates and odd ratios showed that this relation was negative , indicating that moderately heterozygous individuals had, on average, more parasites (2 (-0.52) and aggregation (0.60) were similar in magnitude and in both cases the 95% CI did not overlap 0, collectively indicating that their effects on tick abundance were significant and of similar relative importance (The results of adding genetic diversity to the best non-genetic models differed for lice and non-replete and replete ticks . GeneticIC units . In Stag = 0.73) . Interesarasites . Model aportance . Model eportance . The thrportance .2 were close to and overlapped 0. Model average estimates indicated that the most important factors were area and month followed by food, aggregation and sex. By comparison, year, age and genetic diversity had less relative importance , treatment category , and factors intrinsic to the host  . This moportance .2 fell within the 90% confidence set of models of the top predictive model (Wi = 0.01), no genetic parameter was in the final model averaged results . Two additional models had moderate support (Wi = 0.21) and included the parameters age, sex, year, and food, all of which were used in the second modeling stage which incorporated genetic parameters and the six source areas  differed by ΔAICc = 8.44 from the best model that included genetic variability.The top non-genetic model predicting endoparasite species richness comprised age and year  and host sex (β = −0.37) had effects of similar magnitude . Althougand year .Endoparasites = 0.852, p-value = 0.604; FRepleteticks = 0.157, p-value = 0.999). However, there was a clear trend for single-locus effects to differ for ectoparasites and endoparasites. For replete ticks, effect sizes were not significantly more positive or negative , whereas for endoparasites the single locus effects were significantly more negative , suggesting that higher levels of genetic diversity are associated with reduced endoparasite richness. There was no correlation between the effect size of each marker and its genetic diversity measured either as number of alleles , observed heterozygosity  or expected heterozygosity .Three markers were significantly correlated with replete tick abundance  and 2 with endoparasite abundance (PLM01 and PLM14). However, we did not find any overall evidence for significant single locus effects, since most of the effect sizes were not significantly different from 0  and the D. variabilis abundance was better predicted by a curvilinear relationship, especially for replete ticks . Our results suggest that the selective pressure of parasites might also be important for populations that are not inbred and add new evidence to support the importance of genetic diversity for coping with parasitism in outbred populations Previous studies in this population revealed that individuals that had antibodies to CDV had greater genetic diversity than individuals that were seronegative, suggesting that individuals with lower levels of genetic diversity were less likely to survive CDV D. variabilis, particularly for ticks that had been on the host long enough to obtain a blood meal. The cross-taxa differences are likely due to the different interactions of lice and ticks with the host immune system. Trichodectes octomaculatus is a raccoon-specific louse In contrast to the patterns observed for endoparasites and for CDV Borrellia and Erlichia spp. Leuciscus leuciscus) infected by the ectoparasite Tracheliastes polycolpusTicks, in contrast, are known to generate an immune response from the host, most prominently due to tick saliva When the relative importance of genetic diversity was compared with that of the non-genetic factors we observed different patterns across taxa that result from the specific interactions of the parasite, the environment, and the host. In previous studies we have observed that the relative importance of abiotic factors  was greater for non-replete ticks After analyzing the role that genetic diversity played in predicting parasitism in each group, we determined whether the effects of genetic diversity were best explained as single-locus effects or genome-wide neutral genetic diversity for endoparasite richness and replete tick abundance. We expected to find single-locus effects, since the detection of HFCs with neutral markers in non-inbred populations has usually been attributed to a particular locus Interestingly, when the local effects were analyzed, they confirm the pattern found for the global HFC: for the endoparasite richness most of the local effects were negative , but for the abundance of replete ticks there is a combination of negative and positive local effects. The combination of negative and positive local effects is probably what yields a curvilinear relationship for the global HFC in replete ticks. To our knowledge, this is the first reported case where the differences are not only based on the presence-absence of an HFC with parasitism, but also on varying types of HFC relationships. The mechanism underlying these differences is unclear. We hypothesize that selective pressure would be different in different genes, with some loci being subject to overdominance that favours the heterozygotes, and other loci showing underdominance that imposes selection against heterozygotes The extent of parasitism of an individual is a trade-off between exposure and susceptibility. Here we have shown that even small differences in genetic diversity, such as those found in an outbred population, are associated with differences in susceptibility to parasites across individuals. Furthermore, the relationship between genetic diversity and parasitism varies across taxa, probably as a result of different selective pressures. To understand the genetic basis of parasite susceptibility, future studies must simultaneously evaluate the effects of non-genetic and genetic measures in the same models.Table S1Prevalence and mean abundance for 18 species of parasites identified from raccoons in Missouri.(DOCX)Click here for additional data file.Table S2Genetic diversity measures and information for the 15 loci analyzed in an outbred raccoon population in Central Missouri (USA).(DOCX)Click here for additional data file.Table S3Ranking of models including only non-genetic terms to estimate parasite loads in a raccoon population. (a) Abundance of replete ticks; (b) Abundance of non-replete ticks ; (c) Abundance of lice  and (d) endoparasite richness (n = 250).(DOCX)Click here for additional data file.Table S4Model averaged estimates of parameters included in the 90% confidence set of models used to estimate abundance of lice (Trichodectes octomaculatus).(DOCX)Click here for additional data file.


Evaluation of genetic diversity and genetic structure in crops has important implications for plant breeding programs and the conservation of genetic resources. Newly developed single nucleotide polymorphism (SNP) markers are effective in detecting genetic diversity. In the present study, a worldwide durum wheat collection consisting of 150 accessions was used. Genetic diversity and genetic structure were investigated using 946 polymorphic SNP markers covering the whole genome of tetraploid wheat. Genetic structure was greatly impacted by multiple factors, such as environmental conditions, breeding methods reflected by release periods of varieties, and gene flows via human activities. A loss of genetic diversity was observed from landraces and old cultivars to the modern cultivars released during periods of the Early Green Revolution, but an increase in cultivars released during the Post Green Revolution. Furthermore, a comparative analysis of genetic diversity among the 10 mega ecogeographical regions indicated that South America, North America, and Europe possessed the richest genetic variability, while the Middle East showed moderate levels of genetic diversity. Triticum aestivum , and tetraploid, hard or durum-type wheat, T. durum  [Modern wheat cultivars usually refer to two species: hexaploid bread wheat, 8, AABB) . Durum wT. dicoccoides) giving rise to the first domesticated form  [T. dicoccum to become the major cultivated form of allotetraploid wheat by the second millennium BC [Wheat domestication took place 12,000 years ago in the Near East, with the wild ancestor (icoccum) . About 2nnium BC –5. Durumnnium BC , whereasnnium BC . Durum wnnium BC . That isnnium BC ,10. Espennium BC . These hi.e., adaptability to flexible and high-throughput detection methods, high efficiency with low-quantity and low-quality DNA, low-cost per assay, tight linkage to target loci, and the high level of polymorphism in breeding materials [Molecular markers are particularly useful for the evaluation of genetic diversity in wheat and other crop species with a narrow genetic base . To dateaterials ,22.Avena.[Until now, simple sequence repeat (SSR) markers relying on genomic sequences have been proven to be the most widely used DNA marker type in characterizing germplasm collections of crops, because of their easy use, relatively low cost, and high degree of polymorphism provided by the large number of alleles per locus ,24. In tAvena.). HoweveAvena..Arabidopsis[More recently, single nucleotide polymorphism (SNP) markers gained significant attention because they are bi-allelic in nature and occur at a much higher frequency in the genome than SSRs and other markers. Furthermore, their genotyping can be easily automated . In cropabidopsis, rice [3abidopsis, soybeanabidopsis, and barabidopsis. Howeverabidopsis–40, becaabidopsis,41. AlsoInformation about the genetic diversity and genetic structure in germplasm is of fundamental importance for crop improvement . It is wA total of 230,400 data points were generated by genotyping of 150 durum wheat accessions with multiplexed 1536 Illumina Golden Gate SNP assay. Out of 1536 SNPs presented in our oligonucleotide pool assay (OPA), 1366 (89%) SNPs with high quality genotype calls were obtained, while the other 10% failing to generate clear genotype clustering were removed. Out of the 1366 scoreable SNP markers, 420 were monomorphic across all the 150 accessions and the overall polymorphism rate was 69.3%. Because SNP markers are mainly bi-allelic, therefore, all SNPs showed two alleles only. The 946 polymorphic SNPs markers were used for further analysis. Marker distribution, Nei’s gene diversity, and PIC values estimated for each chromosome and genome were listed in SNPs loci were not evenly distributed across the seven homoeologous groups, and coverage ranged from 108 in group 5 to 161 loci in group 6. Nei’s gene diversity and PIC values across groups ranged from 0.2004 to 0.2508 and from 0.1656 to 0.2006, respectively. The chromosome group 1 had higher genetic diversity and the group 3, 4 and 5 had lower genetic diversity than the genome-wide average .t = 1.459, p = 0.195, paired t test) and PIC . In the A genome of durum wheat, chromosome 6A had higher genetic diversity , and chromosome 4A had lower genetic diversity  than the rest of chromosomes ) increased continuously with increasing K and there was no obvious K value clearly defining the number of populations (ΔK) [K = 2 (vs. cultivars), and pedigree information of accessions were analyzed to explain the inferred structure.Genotyping data generated by the 946 polymorphic SNP markers were used for genetic structure analysis, using the Bayesian clustering model implemented in the Structure software. The estimated log probability of the data (ulations . Howeverons (ΔK)  suggeste) [K = 2 . Thus, t) [K = 2 . HoweverGroup I contained 39 accessions, about half (20/39) of which were collected from the Americas (North America and South America). Further analysis of these accessions showed that this group is dominated by landraces (16) and cultivars released during the Post Green Revolution (PGR) (14) .Group II contained 96 accessions, which can be further divided into four big subgroups: IIa, IIb, IIc, and IId. Although the grouping pattern is very ecogeographically heterogeneous in each subgroup, the grouping pattern of some accessions appeared to be associated, to some extent, with the release period of varieties . Group It = 7.214, p < 0.001, paired t test) and PIC . The higher genetic diversity was detected using SNP markers in the cultivars with Nei’s gene diversity and PIC values of 0.2310 and 0.1919, compared to 0.2192 and 0.1800 for the landrace, respectively. Furthermore, molecular variance component in cultivars and landraces was compared to serve as a complementary indicator for genetic diversity. Analysis of molecular variance (AMOVA) revealed that individuals within cultivars (65.54%) are highly genetically variation in relation to individuals within landraces (33.97%) (As shown in (33.97%) . Similar(33.97%) . The pant = 6.484, p < 0.001, paired t test; PIC, t = 6.304, p < 0.001, paired t test), but an increase in PGR was observed . That is, genetic diversity was narrowed down from 1930 to 1980, but enhanced from 1981 to 2009.In order to explain the reasons why the higher level of genetic diversity exists within improved accessions, the 97 cultivars were further divided into three temporal groups: OC, EGR and PGR. As shown in F = 19.02, p < 0.01, ANOVA), with an average of 119.13 and 101.91, respectively.Noteworthy, plant height, as an extremely important target trait in modern wheat breeding, also showed significant variation/decrease. The “Green Revolution” in cereals was achieved by reducing plant height, thereby reducing lodging susceptibility and increasing grain yield ,48. As sFst on a locus-by-locus basis provided a cutoff for identifying loci that may be under positive selection [We conducted further analyses to identify candidate loci that are under positive selection between landraces and cultivars. An analysis of election . Therefoelection . BetweenKnowledge of genetic diversity from different ecogeographic areas was expected to have a significant impact on the conservation and utilization programs of durum germplasm, allowing breeders to develop strategies to incorporate useful diversity in their breeding programs. A summary of the genetic diversity data of the 10 mega ecogeographical regions was shown in et al. [et al. [Average Nei’s gene diversity and PIC values revealed by SNP markers in this study were 0.2280 and 0.1888, respectively . CompareT. dicoccoides[Despite this fact, a sufficient level of genetic variation and similar variation trend can be detected using SNP markers. For example, our results are in agreement with previous studies that chromosomes 4A and 4B have relatively low genetic diversity due to the evolutionary translocation events involving chromosome 4A ,51,52. Tcoccoides. These rT. durum accessions, based on the Bayesian clustering model implemented in the Structure software and NJ algorithm implemented in POWERMARKER Ver. 3.25 and PHYLIP  from Europe to the American territories . BesidesAn alternative or complementary possibility may be found in breeding history. In this study, most of the accessions selected were cultivars (97/150 = 64.7%), and cultivars experienced primarily artificial selection, and only secondarily natural selection, for certain desirable characteristics. For example, breeding efforts focused on early maturity and yield increase before 1930, disease resistance from 1930 to 1970, and multiple disease resistance and quality improvement after 1970 –58. SuchHowever, not all accessions released from the same period were clustered in the same group. In contrast, some of accessions from the same geographic region were clustered together though into different groups corresponding to their geographical regions of collection . For exaAbove all, such genetic structures and grouping patterns of the 150 durum wheat accessions were obviously affected by environmental conditions, release period of varieties, and gene flows via germplasm exchanges or artificial transfer of genes.Measurements of genetic diversity in crops have important implications for plant breeding programs and the conservation of genetic resources. In the present study, temporal and spatial genetic variation was analyzed by comparing the diversity among released periods of varieties and among different geographical origins, respectively.et al. [It has been argued that the level of genetic diversity in the modern durum wheat cultivar germplasm may have declined due to high-pure breeding selection pressure applied in breeding programs. This is also true for wild emmer wheat and wild barley due to global warming as discovered in a recent study by Nevo et al. . Howeverp < 0.001, paired t test). But the diversity was significantly increased in varieties released after the 1960s and 1970s   cultivars were used in Fu’s study.We did find a significant reduction in the diversity of varieties released in the 1960s and 1970s, compared with the diversity levels in the landraces and old cultivars (1930–1964) ( t test) . That is t test) . These r  [The low diversity levels of varieties released in 1965–1980 might be due to the “Early Green Revolution”, which was characterized by breeding semi-dwarf varieties possessing a higher yielding potential ,61. Intevs. 97 cultivars) was used.Above all, the reason why genetic diversity is larger in cultivars than in landraces may be due to breeding strategy and breeders’ efforts. Alternatively, imbalanced sample size in the two groups ; group 2, 1965–1980 ; group 3, 1981–2009  ,63,70,71et al. [w/v) Sodium dodecyl sulfate (SDS), and 0.38% (w/v) sodium bisulfate.Young leaves from each accession were collected and frozen in liquid nitrogen. Genomic DNA was isolated using a modified SDS (Sodium dodecyl sulfate) method according to Peng et al. . The extT. aestivum cv. Chinese Spring and Jagger [The 150 durum wheat accessions were genotyped with 1536 SNP markers. These SNPs, discovered in a panel of 32 lines of tetraploid and hexaploid wheat, were downloaded from the Wheat SNP Database . SNP seld Jagger ,74.A total of 150 ng of genomic DNA per genotype was used for Illumina SNP genotyping at the Genome Center of University of California in Davis using Illumina Bead Array platform and Golden Gate Assay following the manufacturer’s protocol . GenotypGenetic diversity was evaluated using POWERMARKER Ver. 3.25 . The genK, five runs were carried out. Burn-in time and replication number were both set to 100,000 for each run. Accessions with probability of membership greater than 80% were assigned to a subgroup, while those with lower probabilities were assigned to the “mixed” subgroup. Dendrograms, based on the NJ algorithm according to shared-allele distance, were also used to analyze the genetic structure of the germplasm. A phylogenetic tree was implemented by POWERMARKER Ver. 3.25. Bootstrapping over loci with 1000 replications was carried out to assess the strength of the evidence for the branching patterns in the resulting NJ tree. A consensus tree with bootstrap values was reconstructed by the consensus program of PHYLIP [In order to have a better insight into the genetic structure of durum wheat, different methods were exploited. First, we applied the Bayesian model-based clustering algorithm implemented in STRUCTURE 2.2 . Admixtuf PHYLIP  and dispFst-outlier detection method as implemented in the LOSITAN workbench [Fst values that fall outside of the 99% confidence interval, candidate loci identified under positive selection were used for further analysis.The population differentiation was assessed with the AMOVA implemented in the ARLEQUIN version 3.11software . Signifiorkbench . The anat test was used to test the significance of differences of genetic diversity between genomes using Nei’s gene diversity and PIC per chromosome as variables. The significance of differences for genetic diversity parameters between cultivars and landrace were also tested by paired t test. The plant height data were analyzed by analysis of variance (ANOVA) and the means among group were further tested by Duncan’s Multiple Range Test.SPSS V.13.0 program was used for statistical analyses . The sigIn this study, we used worldwide germplasm accessions and 946 SNP markers to estimate genetic structure and genetic diversity of durum wheat on the whole genome level. Genetic structure, based on a set 150 accessions from different places of origin, was greatly affected by many factors, such as environmental conditions, release period of varieties, and gene flows via germplasm exchanges or human activities. Genetic diversity indicated that there still existed a substantial level of genetic variation within modern cultivars of durum wheat as detected by SNP markers, despite rigorous selection pressure aimed at cultivar purity and associated breeding practices. Our results can be used to accelerate wheat improvement by addressing the patterns of genetic variation within durum wheat, conserving adequate type and number of germplasm accessions and helping breeders maximize the level of variation present in segregating populations by crossing cultivars with greater genetic distance.