Ambrosia artemisiifolia is a North American native that hasbecome one of the most problematic invasive plants in Europe and Asia. Westudied its worldwide population genetic structure, using both nuclear andchloroplast microsatellite markers and an unprecedented large populationsampling. Our goals were (i) to identify the sources of the invasivepopulations; (ii) to assess whether all invasive populations were founded bymultiple introductions, as previously found in France; (iii) to examine howthe introductions have affected the amount and structure of geneticvariation in Europe; (iv) to document how the colonization of Europeproceeded; (v) to check whether populations exhibit significant heterozygotedeficiencies, as previously observed.A.artemisiifolia, within regions but also within populations inmost parts of its invasive range, leading to high levels of diversity. InEurope, introductions probably stem from two different regions of the nativearea: populations established in Central Europe appear to have originatedfrom eastern North America, and Eastern European populations from morewestern North America. This may result from differential commercialexchanges between these geographic regions. Our results indicate that theexpansion in Europe mostly occurred through long-distance dispersal,explaining the absence of isolation by distance and the weak influence ofgeography on the genetic structure in this area in contrast to the nativerange. Last, we detected significant heterozygote deficiencies in mostpopulations. This may be explained by partial selfing, biparental inbreedingand/or a Wahlund effect and further investigation is warranted.We found evidence for multiple introductions of This insight into the sources and pathways of common ragweed expansion mayhelp to better understand its invasion success and provides baseline datafor future studies on the evolutionary processes involved during rangeexpansion in novel environments. Invasive species offer useful models for studying rapid range expansion in novelenvironments, which can imply pre-adaptation, phenotypic plasticity or adaptation.Evolutionary aspects of biological invasions have long been neglected, with mostpast focus being on ecological aspects, but recently, interest in the evolution ofinvasive species has grown e.g. . HoweverSpecies introductions are sampling events and should therefore generate geneticbottlenecks. In agreement with this prediction, loss of variation is a frequent,although not ubiquitous, feature of introductions Ambrosiaartemisiifolia L. . Thiswind-pollinated monoecious annual is a common native of North America, and has beenintroduced to South America, Europe, Asia and Australia, where it has becomeinvasive A. artemisiifolia causes largeeconomic losses by reducing crop yields in agricultural fields , represents a significant challenge to the management of naturalresources A.artemisiifolia is a self-incompatible annual species , Italy, Hungary and Russia . In several instances, the massive spread of common ragweed hasbeen correlated with major socio-economic transitions that increased the area ofdisturbed or fallow land, such as during the communist economy (1948–1989) inEastern Europe, when many sites e.g. extensive border areas and military zones wereleft uncultivated Both herbarium records A.artemisiifolia populations from the native and introduced ranges, andto shed light on the colonization history of this worldwide invader, we investigatedthe neutral genetic structure of this species, expanding previous samplings To gain insights into the historical relationships among In France, Genton et al. We addressed the following questions: (i) Can we identify the sources of thedifferent invasive populations in the world, especially of the previously unanalyzedpopulations in Australia, China and South America? Can we confirm that EasternEuropean populations originated from other sources than Western Europeanpopulations? And if so, from where did they originate? (ii) Were all invasivepopulations founded by multiple introductions? (iii) How have the introductionsaffected the amount and structure of genetic variation in Europe (compared to thepatterns observed in the native range)? (iv) In Europe, did the expansion proceed ina stepwise manner, each population being colonized by a neighboring population, oras a result of long-distance dispersal within the continent, or did populationsresult from independent colonization events from the native range? (v) Dopopulations exhibit significant heterozygote deficiencies? And if so, can we suggestplausible explanatory mechanism(s)?We used both nuclear and chloroplast microsatellite markers, that differ in theirmode of inheritance  and mutation rate , one from Argentina, twofrom China and two from Australia , Fig. 1  TGG ATA GCC GGC AGATA; c6T448_R: TTC CTT TTTCTT GGC CTT CA; s16T148_F: AGC CGT TCC AAC AAA TGA AA; s16T148_R: AAACGA TGT GGT ARA AAG CAA C; s16T690_F: ACT CATAGT CCT TTT TAT TTA GCT TCC; s16T690_R: TTT GAG AAT TAT TGA ACT TGA GTT ATG). Wechecked by direct sequencing that all differences between cpSSR size variantswere due to variable numbers of mononucleotide repeats.DNA was extracted using the DNeasy 96 Plant Kit (QIAGEN). We used a total of ninenuclear and four chloroplast microsatellite markers: three nuclearmicrosatellite markers  developed by Genton et al. Multiplex PCRs were performed, amplifying several loci simultaneously. The 16µl reaction mix contained 1 µl DNA template, 1X Taq Buffer, 2 mMMgCl2, 0.2 mM of each dNTP, varying concentrations of primers , and 0.4 U Taq polymerase per primerpair included in the reaction. Primer concentrations were experimentallydetermined so that the intensity of all microsatellites was high enough toprevent allelic drop-out and allow unambiguous genotyping. For multiplex1,primer concentrations were 0.30 µM for Amb82, Ambart04 and Ambart13, and0.08 µM for c6T448 and s16T690. For multiplex2A, primer concentrationswere 0.60, 0.16 and 0.06 µM for Amb12, Ambart27 and s16T148, respectively.And for multiplex2B, primer concentrations were 0.10, 0.30, 0.30 and 0.20µM for Ambart06, Ambart09, Ambart21 and NTCP9, respectively. The reactionprofile was the following: 40 cycles of denaturation at 95°C for 30 s,hybridization at 50°C (for multiplex1) or 52°C  for 30 s, and elongation at 65°C for 4 min,followed by a final elongation step of 10 min at 72°C. Locus Amb30 wasamplified separately using 2.5 mM MgCl2, 0.2 mM of each dNTP, 0.2 µM ofeach primer and 0.5 U Taq polymerase and the following reaction profile: 40cycles of denaturation at 95°C for 30 s, hybridization at 50°C for 30 s,and elongation at 72°C for 30 s, terminated by an elongation step of 10 minat 72°C. The PCR product was then mixed with multiplex 2A in a 1∶1ratio. Finally, the internal size standard LIZ500 was added to all samples priorto loading on an automated sequencer. This final step was performed by a privategenotyping company .Microsatellite profiles were manually genotyped using GeneScan 3.7 and Genotyper3.7. Reproducibility was checked by performing the amplification and genotypingsteps on 30 samples twice, leading to 30×9 = 270sample × locus duplicates.For both nuclear and chloroplast loci, samples from Japan and Korea werediscarded from population-level computations because they were not grouped intodiscrete natural populations and not in sufficient number to allow reliablestatistical inferences.FIS and among-populationFST indices using FSTAT. The statisticalsignificance of FIS was assessed by 5760 randompermutations of alleles in each population at each locus, followed by aBonferroni correction for multiple tests. To detect signs of recentbottlenecks, we examined deviations in heterozygosity frommutation–drift equilibrium in each population with the softwareBottleneck FST indices both at the global scale andamong all pairs of populations. We computed the 95% confidenceinterval of the global FST by bootstrapping overloci. The overall differentiation of each population was estimated as themean pairwise FST between each population andall others. Exact tests of population differentiation were also performedamong all pairs of populations using Genepop FIS and FSTamong North America, Europe (including Ukraine and Russia) and non-Europeaninvasive populations  wereassessed using permutation tests in FSTAT .Within each population, linkage disequilibrium was tested between loci basedon random permutations of genotypes performed with the software FSTAT To identify the potential sources of invasive populations, we attempted toassign all sampled individuals from invasive populations to their mostprobable source population among the sampled North American populations. Weadopted the method of Rannala & Mountain FST indices, thegenetic similarity of populations was summarized using a PrincipalCoordinate Analysis, performed in NTSYS . Hubisz et al. Structure uses Markov chain Monte Carlo (MCMC) algorithms to groupindividuals in clusters (where the numbers of clusters must be set apriori) that deviate neither from Hardy–Weinberg nor linkageequilibrium within each cluster. It also calculates the posteriorprobability of the data given the inferred clustering. Structure wasrun 20 times for each K-value from one to seven to check theconsistency of the results across runs. Each run comprised a burn-inperiod of 200000 iterations followed by 10post-hoc, Structurama employs a priordistribution of K to determine the most appropriate K-value. At eachrun, it also outputs posterior probabilities of each possibleK-value and the mean partition, i.e. a partitioning of individualsamong clusters that minimizes the squared distance to the sampledpartitions across generations of the MCMC Unlike Structure, which requires running the program several timesunder different K-values and then determining the best valueFIS indices) within the inferredclusters A. artemisiifolia sincewe detected significant departures from Hardy-Weinberg equilibriumin almost all populations were discarded from the inference of multilocus haplotypes and from thestatistics based onto these haplotypes.First, we considered all multilocus haplotypes to draw a median-joiningnetwork based on the number of mutations among all pairs of haplotypes usingthe software NETWORK FST andNST indices of among-populationdifferentiation based on unordered and ordered haplotypes, respectively. Theinput dataset contained, for each individual, the multilocus haplotypedisplayed. For the estimation ofNST's, the distancebetween haplotypes was calculated as the sum of their absolute lengthdifferences across the four loci. We performed 10000 permutations of rowsand columns of the distance matrix between haplotypes to test whetherNST > FST.Such a significant relationship suggests that distinct haplotypes are morerelated within populations than among them, i.e. that genetic structuredisplays a significant geographic trend NSTindices, and an AMOVA of haplotype frequencies, implemented in Arlequin, toassess the proportion of genetic variance found at the region (North Americavs. Europe), population and individual levels. We also performed Manteltests (using FSTAT) within North America and Europe, based onNST indices.Within populations, we computed the number of haplotypes, number of privatehaplotypes (found in only one population) and mean number of pairwisedifferences among individuals using the software Arlequin. For this, wecoded cpSSR data in a binary way, representing for each locus the number ofrepeats of the largest variant with ‘1’s and replacing theabsent repeats of shorter variants with ‘0’s. Permutation tests(in FSTAT) and non parametric Mann-Whitney tests were performed to detectany significant difference in number of haplotypes and mean number ofpairwise differences among individuals, respectively, between North America,Europe and non-European invasive populations The program SpaGeDi Reproducibility was high, with 97.7% of all sample × locus duplicatescarrying the same genotype. We did not find any evidence of linkage disequilibriumbetween pairs of nuclear microsatellite markers.We detected a mean (± S. D. among loci) of 19.7 ± 8.2 alleles pernuclear microsatellite locus  and two indicatedK = 7 (with P = 0.40±0.01).However, six of the nine mean partitions that were inferred counted fiveclusters. In the three remaining runs, the sixth cluster was a subdivision of apre-existing cluster and was present in very low proportions in severalpopulations. Using Structure and Instruct, the probability of the data lnP(D)steadily increased, and the change of probability between consecutive K-values(ΔK) steadily decreased when assuming increasing K values . HoweverAt each K-value, most runs of Structure were consistent in terms of individualassignment to the K clusters (similarity ≥ 0.75). AtK = 2, an East-West cline of cluster assignment wasobserved in North America, and the predominant cluster in western North America and ΔK values were obtained atK = 3. Utah and Montana were individualized in one clustereach, while Missouri, South Carolina, Ontario, Quebec and Bronx werepredominantly assigned to the third cluster. Minnesota was intermediate, withapproximately equal contributions of the three clusters . At K = Within Europe, lnP(D) increased with increasing K values and ΔK displayed twopeaks, for K = 2 and K = 7. AtK = 7, populations IT9, IT4, SE3, RO1 and UKR segregated inspecific clusters, indicating their strong genetic divergence . Some otFIS were significantlypositive in all populations except Bronx and IT4 (FISestimates were not significantly different between North America and Europe(P = 0.839), but were  significantly higher innon-European invasive populations than in North America and Europe (Multilocus fixation indices  and IT4 . NineteeFSTn estimate was 0.073(95% C.I.: 0.065–0.083). Analyses of Molecular Variance (AMOVAs)showed that the split between North America and Europe did not explain asignificant proportion of the observed genetic variance either at nuclear or atchloroplast markers. Furthermore, though not significantly so, Europeanpopulations showed somewhat greater among-population differentiation than didNorth American populations. At chloroplast loci,FSTcp = 0.411 andNST = 0.440 (notsignificantly different). In North America,FSTcp = 0.373 and wassignificantly lower thanNST = 0.518(P = 0.007). In contrast, in Europe,FSTcp = 0.389 and was notsignificantly different fromNST = 0.384. These resultsshowed a significant influence of the spatial component on the genetic structurein North America, but not in Europe.At nuclear loci, the overall FST values among these two groups oflow-differentiated European populations, to which we added clearlydifferentiated and geographically concomitant populations, and western andeastern North American populations, respectively. Standard deviations were largeand differences were therefore not significant, but we observed the same patternas in Structure: Central European populations were closer to eastern than towestern North American populations while Eastern European populations wereslightly closer to western North American than to eastern North Americanpopulations  and Eastern Europe , appeared clearly less differentiated from North Americanpopulations than the others . We compulations .PopulatFST indices based on nuclear DNA, was confirmed:Utah displays three cpDNA haplotypes, one of which was private and the other twothat were otherwise mostly found in RU4 (haplotype H) and UKR  were significantly correlated, both when considering all pairs ofpopulations  and when considering the mean pairwisedifferentiation indices for each population  different source populations in North America .The proPrincipal Coordinate Analyses allowed us to graphically represent the mainpatterns of genetic relationships, which were congruent with the results of theBayesian clustering, haplotype network and differentiation indices: for bothnuclear and chloroplast markers, the divergence of Austral1-Austral2 andUtah-UKR appeared clearly . BeijingMantel tests revealed significant isolation by distance patterns in North Americafor both nuclear and chloroplast loci . The time scale of this study isthus much more restricted than in traditional phylogeographic studies, and theevolution of new alleles appears very improbable given the mutation rates atnuclear and chloroplast microsatellite loci  FST = 0.065 and most exacttests of differentiation were significant). Because introductions almost alwaysinvolve sampling and founder events, we consider it improbable that populationsin the introduced range could have arisen from single population introductionsand still retain this high amount of genetic diversity. This leaves us with twoalternatives: i) populations were founded by multiple colonisations fromdifferent populations in the native range, as suggested by the assignment testand previous findings of extremely high allelic diversity in the introducedrange We observed no significant loss of genetic diversity between North America andEurope, and European populations did not appear to have undergone recentbottlenecks (except population PO2). Furthermore, European populations weregenetically differentiatedpopulations were genetically more similar to western North American populations.This clarifies the pattern observed by Gladieux et al. We also observed that the two groups of populations in Slovenia-Hungary andUkraine-Russia were less differentiated, more diverse and more admixed than mostother European populations. This may indicate more frequent colonization eventsthan in other regions, and/or higher ongoing gene flow among populations.Interestingly, these populations are located in some of the most heavilyinfested countries in Europe, i.e. Hungary and Russia. The French population wasalso sampled in a region where common ragweed is a very aggressive invader, andwas also found to have low differentiation and high diversity. Whether highergenetic diversity increases invasion success or whether areas where an invasionis particularly successful (containing high number of populations) leads to highgenetic diversity remains uncertain, but would deserve further investigations:genetic diversity has long been considered a prerequisite for invasion successbecause of the assumed correlation between variation at neutral markers andadaptive potential e.g. , but thiFIS indices compared to the native area. Thissuggests that introduction events may have been less frequent and involved alower number of differentiated source populations and/or individuals (i.e. lowerpropagule pressure), possibly leading to lower population sizes and more geneticdrift (but only the Beijing population seems to have undergone a recentbottleneck). In turn, this could cause increased rates of selfing and/orinbreeding (i.e. crosses between related plants), explaining the slightly higherFIS estimates (see below for a discussion onFIS estimates). Such a pattern would beconsistent with greater commercial isolation from North America and lessmilitary exchange with North America than was the case for Europe during the twoWorld Wars, and/or better quarantine procedure .In contrast to Europe, other invasive populations displayed reduced geneticdiversity and a trend towards increased within-populationThe two Australian populations were genetically similar and stronglydifferentiated from all other populations. They most likely originated from anunsampled source, either through a single introduction event followed bydispersal within Australia , or through two independentintroduction events from the same source population(s). A similar pattern wasobserved for the Beijing and Romanian populations, which were closely relatedbut highly differentiated from all others. The genetic similarity betweenRomania and Beijing populations may be explained either by commercial trade withthe same (unsampled) region(s) in North America, or by a secondary introductionfrom Romania to China (since we observed lower diversity in Beijing).The other non-European invasive populations, Wuhan and Argentina, were lessdifferentiated from North America and Europe. These populations were alsoslightly more diverse than Australian and Beijing populations, indicating thatthey probably experienced more introduction events or less strong foundereffects.FSTn = 0.054 vs. 0.065,respectively) and the slightly stronger genetic structure in Europe may resultfrom i) the fact that potentially divergent North American populations weremissing from our sampling and ii) the establishment, by chance, of differentgenotypes in different areas following multiple introductions (as shown inCentaurea diffusaWe observed similar levels of population differentiation in North America andEurope (NSTcp >FSTcp) but not in Europe. All these results werein agreement and, first, show that North American populations are atmigration-drift equilibrium whereas European populations are not. Second, theyindicate that range expansion in Europe occurred by a series of long-distancedispersal events and the establishment of outlying populations, similarly towhat was found in e.g. invasive Heracleum taxa in Europe Centaurea diffusa in North America Most importantly, we observed a major difference between North America and Europein how genetic diversity was structured geographically, which gave an insightinto the colonization process in Europe: i) we found significant isolation bydistance (i.e. a positive correlation between genetic and geographic distances)in North America but not in Europe; ii) although we could identify two groups ofEuropean populations originating from distinct source regions, the pattern wasnot clear-cut and did not include all sampled populations, and the overallgenetic structure was much more geographically organised in North America thanin Europe (based on the Structure results); and iii) distinct haplotypes weresignificantly more related within populations than among populations in NorthAmerica  than at nDNA (dispersed by both seeds and pollen) markers.This is congruent with previous knowledge on pollen dispersal in Genetic differentiation at the worldwide scale was low. This may be explained byweak founder effects when the species was introduced, on-going gene flow, and/orinsufficient time for genetic drift to differentiate the populations since theirestablishment. In addition, there was little spatial component to the geneticstructure: the geographic split between North America and Europe explained nosignificant part of the total genetic variance. Also, the combined use ofseveral Bayesian algorithms allowed the delineation of five genetically-basedclusters, but these clusters could not be related to clear geographicentities.FISwere significant, suggesting a deficit in heterozygotes. This was confirmed bythe software Instruct, which estimated inbreeding coefficients of 0.3–0.4within clusters. Although this result was congruent with previous populationgenetic studies of A. artemisiifoliaAlmost all within-population fixation indices FIS estimates. Although wedo not exclude this possibility, we do not favor it for several reasons. First,we did not observe any repeated amplification failure for any given locus in anypopulation . Therefore, even if there are somenull alleles, they occur at very low frequencies and contribute very little tooverall heterozygosity deficit . Second, in our study, most populations displayed significantdeficit of heterozygotes at several loci and significant monolocusFIS estimates were widely distributed acrossloci. Third, Genton et al. FIS values .Altogether, these lines of evidence suggest that null alleles are probably notthe main cause for the observed deficits of heterozygotes withinpopulations.In earlier genetic surveys FIS estimates were quite similar and there was noevidence for an evolutionary shift towards higher selfing rates in theintroduced range, as has been suggested as a general pattern in invasive speciesA. artemisiifolia and its potential variation acrosspopulations (or regions) would be interesting to better understand thesepositive FIS estimates. Such studies appearespecially needed since A. artemisiifolia was long reported asself-compatible All A.artemisiifolia populations.The present study shows how variable the history of distinct  invasive populations can be. This highlights theimportance of sampling as many populations as possible to avoid biasedinferences see also . It alsoA. artemisiifolia was introduced multiple timesin most parts of its invasive range, leading to high levels of within-populationand regional diversity. In Europe, introduction events probably mainly involvedtwo different regions of the native area, with populations of Central Europeoriginating from eastern North America, and populations of Eastern Europeoriginating from more western North America. Our results indicate that theexpansion of the European range mostly occurred through long-distance seeddispersal, explaining the weak association between genetic differentiation andgeographic location in this area . Finally, heterozygote deficiencies may beexplained by a Wahlund effect, but further investigations on the breeding systemwould provide useful information to better explain this result.We showed that A.artemisiifolia exhibits latitudinal variation in floweringphenology both in the native range A. artemisiifolia.Such data offer opportunities to study the ecological and/or evolutionary changesinvolved in the invasion process e.g. , and mayFigure S110 of interpopulation distance in km; the genetic distancewas expressed asFST/(1-FST).In North America (P  =  0.002). B) In Europe (P =  0.581). The geographic distance was expressed asthe log(TIF)Click here for additional data file.Table S1Populations are grouped into three spatial groups  and roughly ordered from West to East.Haplotypes are ordered from the most frequent to the least frequent.Haplotypes that are in bold are private to one population.(XLS)Click here for additional data file.Table S2FST estimates that are highlighted in greycorrespond to non-significant exact tests of differentiation.Populations are grouped into three spatial groups  and roughly ordered from West to East.(XLS)Click here for additional data file.Table S3The number ofindividuals assigned to each North American population is given, eitherconsidering all individuals or only individuals with assignmentprobabilities above 0.5.(XLS)Click here for additional data file.


Corallium rubrum populations, for the first time, colonies found between 58–118 m depth within the Tyrrhenian Sea were collected and analyzed. Ten microsatellite loci and two regions of mitochondrial DNA (mtMSH and mtC) were used to quantify patterns of genetic diversity within populations and to define population structuring at spatial scales from tens of metres to hundreds of kilometres. Microsatellites showed heterozygote deficiencies in all populations. Significant levels of genetic differentiation were observed at all investigated spatial scales, suggesting that populations are likely to be isolated. This differentiation may by the results of biological interactions, occurring within a small spatial scale and/or abiotic factors acting at a larger scale. Mitochondrial markers revealed significant genetic structuring at spatial scales greater then 100 km showing the occurrence of a barrier to gene flow between northern and southern Tyrrhenian populations. These findings provide support for the establishment of marine protected areas in the deep sea and off-shore reefs, in order to effectively maintain genetic diversity of mesophotic red coral populations.While shallow water red coral populations have been overharvested in the past, nowadays, commercial harvesting shifted its pressure on mesophotic organisms. An understanding of red coral population structure, particularly larval dispersal patterns and connectivity among harvested populations is paramount to the viability of the species. In order to determine patterns of genetic spatial structuring of deep water  Corallium rubrum (L.1758), also known as precious red coral, is a gorgonian endemic to the Mediterranean Sea and Eastern Atlantic Ocean occurring as a large numbers of small sized colonies above 50 m depth  and small (<1 m) scales Corallium rubrum have been collected from mesophotic habitats (58–118 m depth) to investigate patterns of spatial genetic structuring. Ten microsatellite loci and two portions of the mitochondrial DNA (mutS homolog gene and mtC putative control region) were used to analyse the collected specimens. The main goals of the present study were to quantify patterns of genetic diversity in mesophotic red coral populations, and to define population structuring at different spatial scales (from tens of metres to hundreds of kilometres). Implications of these new findings for conservation and management of mesophotic red coral populations are discussed.Knowledge concerning the biological and ecological features of red coral mesophotic populations, is clearly limited by the difficulties associated with accessing and obtaining samples from deep water habitats In July 2010 an oceanographic cruise by the RV Astrea was dedicated to the survey and sampling of mesophotic red coral populations thanks to the project “Study of red coral deep dwelling populations: structure, demography and genetics" supported and financed by the Italian Ministry of Environment. No specific permissions were required for sampling in Campania area, while for sampling in Tuscany area we obtained permission for field activity thanks to the Director of the Arcipelago Toscano National Park.Commercial SCUBA divers and a Remotely Operated Vehicle (ROV) collected 143 red coral colonies in two areas at depth ranging between 58 and 118 metres. The investigated areas were the Northern Tyrrhenian Sea (NTS) and the Southern Tyrrhenian Sea (STS), geographically separated by hundreds of kilometres . Potenti2. Fragments were preserved in 80% ethanol and stored at 4°C. Total genomic DNA was extracted using cetyltrimethyl ammonium bromide (CTAB) protocol.For each population, fragments of branches were collected from 15 to 33 live red coral colonies. Sampling was done within an area of about 50–100 mC. rubrum, COR9, COR15, COR46, COR48, COR58 Ten microsatellites specifically developed for Genotyping of individuals was carried out on an ABI 310 Genetic Analyser (Applied Biosystems), using forward primers labelled with FAM, HEX/VIC, TAMRA/NED, ROX/PET (Sigma) and LIZ HD500 (Applied Biosystems) as internal size standards. Allele sizing was conducted using GENESCAN Analysis Software version 2.02 (Applied Biosystems).Amplification of mtMSH sequences was conducted using the primers MUT4759f and MSH5376r and following 5′-CCATAAAACTAGCTCCAACTATTCC-3′) and COI16CkonojR (5′-GGTTAGTAGAAAATAGCCAACGTG-3′) (Sigma) specifically developed in this study. These primers were designed using the online PRIMER3 version 4.0 software Paracorallium japonicum and Corallium konojoiPCR amplifications of the mtC gene were performed using the primers ND618510CkonojF (IDOH) and unbiased gene diversity  were checked using GENALEX version 6.1 sity HS,  using thsity HS,  with a sIFS were estimated using Weir and Cockerham’s fSingle and multilocus O, HSH and Ar) among groups of populations were tested using a permutation procedure (1000 iterations) in FSTAT.Populations were grouped according to their geographical origin . Significant differences in genetic diversity  method in FREENA estDestD were calculated from individual loci using a harmonic mean approximation. P-values were obtained via bootstrap methods with 1000 pseudo-replications.Due to deviations from the Hardy–Weinberg equilibrium, genotypic differentiation between populations was tested with an exact test  using GENEPOP. As null alleles can induce overestimation of genetic distance, pairwise STF estimator and its significance was determined using a permutation test (10000 permutations) in ARLEQUIN.For the mtMSH and mtC sequence data sets, genetic differentiation between populations was estimated using pairwise STF and estD) and the geographical distances among populations were tested using 1000 permutations.For both microsatellite and sequence data sets, models of isolation by distance between populations were tested through a Mantel test The partition of the genetic variance among populations based on the three data sets was conducted using an analysis of molecular variance (AMOVA) in ARLEQUIN. With this purpose, red coral populations were grouped according to (A) sampling site  and (B) area (two groups: NTS and STS).Discriminant Analysis of Principal Components (DAPC) Assessment of structure within studied genotypes without a priori assumptions regarding populations was performed using a Bayesian clustering analysis implemented in STRUCTURE v2.3 When necessary, significance levels were corrected using a false discovery rate (FDR) methodology ID  = 1.16×10−11). Moreover, specimens sharing the same MLG showed identical mtMSH and mtC sequences. Both these results suggest that shared genotypes derive from fragmentation of single individual colonies, and therefore were included only once, obtaining a final data set of 135 different multilocus genotypes (Six shared multilocus genotypes (MLGs) between colonies were found. One MLG was encountered twice in Elb2, two MLGs in Pra2 and one MLG in Isc2. Within Pra1 two MLGs were encountered twice and another was encountered three times. The probability that each of these genotypes was produced through sexual reproduction was low  but did not give any amplification in STS populations , even though repeated attempts were made. Lack of amplification may be caused by the occurrence of mutations in the microsatellites flanking region. These results deserve careful evaluation since they may disclose occurrence of a major barrier to gene flow between STS and NTS areas.The eight microsatellites analysed were polymorphic in all samples. Throughout all samples, the number of alleles per locus ranged from 6 to 22, and allelic richness from 2.34 to 9.38 . Within ISF ranged from 0.22 to 0.4, showing heterozygote deficiencies in all analyzed samples (Multilocus estimates of  samples .ISF did not significantly differ among groups (P>0.05).All the considered indexes of genetic variability showed similar ranges among populations . Indeed, observed heterozygosity, gene diversity, allelic richness and Across all 135 analysed colonies the mtMSH fragment was 567 bp in length. Sequences alignments showed the presence of two previously recorded haplotypes . Haplotype GQ304903 was present in all populations and was the most common (94%). Haplotype GQ304902 occurred only in Praiano populations, with six individuals in Pra1 and two individuals in Pra2, showing a haplotype diversity of 0.42 and 0.28, respectively .C. rubrum, revealing a length of 290 bp, corresponding to positions 18624–18913 of the mitochondrial genome sequence of Paracorallium japonicum (GenBank number AB595189) and to positions 18565–18702 and 18815–18969 of the mitochondrial genome sequence of Corallium konojoi (GenBank number AB595190). The alignment of all the sequences showed the presence of four nucleotide substitutions (1.4% variation), identifying three different haplotypes (In this study the putative control region (mtC) has been analysed for the first time in plotypes . Both arSTF estimates, as well as ENA STF estimates, of the microsatellite dataset gave similar results. The pairwise STF values ranged from 0.05 (Elb1 vs. Elb2) to 0.24 (Pra2 vs. Elb2 and Isc1) and all pairwise comparisons were significant after FDR correction  to 0.59 (Elb2 vs. Pra2) and all pairwise comparisons were significant after FDR correction . Based upon both STF estimates and estD, Pra2 appeared to be the most differentiated of the populations. Moreover, the lowest values of STF and estD were observed between populations belonging to the same area , whereas a significant isolation by distance pattern was detected using estD  to 0.29 (Pra1 vs. Isc2) and all pairwise comparisons were not significant after FDR correction (STF estimates ranged from 0 (Pra1 vs. Pra2 and Isc1 vs. Isc2) to 0.77 (Pra1 vs. Elb1). Global estimates of STF were not significant both within NTS and STS areas . Pairwise multilocus estimates of STF between NTS and STS populations were generally high (0.52–0.77) and significantly different from zero after FDR correction  (STF based on the mtMSH data set (P  = 0.12).Significant isolation by distance was observed using  = 0.01) , but notPatterns of variation among populations detected by AMOVA differed accordingly to the molecular makers and the groupings of the populations (comparing the 3 sampling sites versus the 2 areas) . All theTesting the significance of the stepwise clustering procedure done in STRUCTURE resulted in a separation of the populations into two clusters . A major barrier to gene flow has been revealed between the Northern Tyrrhenian and Southern Tyrrhenian Seas.This study provides the first data on genetic structuring in mesophotic Corallium rubrum using microsatellites (mean HS  = 0.68±0.02) were low and comparable with those observed in populations at 50–70 metres depth by Costantini et al. t-test: P>0.05). A lack of significant differences in genetic variability between the NTS and STS, suggests that the low genetic variability of microsatellite loci is common to all mesophotic red coral populations. Diversity in population structure and dynamics between shallow and deep water red coral populations, as hypothesized by Bramanti et al. Estimates of multilocus polymorphisms found in C. rubrumStrong deviations from Hardy-Weinberg equilibrium were detected in all populations and at all microsatellites. Depressed heterozygosity was already found in previous studies on In this study the mitochondrial control region (mtC) gene was for the first time amplified in red coral, and showed a higher variability compared to previously analysed mitochondrial genes  and AMOVA provide similar results. In fact, a significant genetic differentiation among C. rubrum populations at all the investigated spatial scales was detected, suggesting that mesophotic red coral populations are genetically structured. Small scale patterns of genetic structuring have been previously reported in shallow-water red coral populations STF did not show an isolation by distance pattern, while estD did. estD is a good measure of genetic differentiation among populations in its own terms but, it is not yet conclusive how it can be interpreted concerning evolution of sets of populations Our microsatellite dataset revealed that both the estimators of population divergence  and deep-water (below 50 m depth) populations vice versa, thus enhancing the resilience of the species. Harvesting pressure, coupled with other anthropogenic and natural disturbances will likely increase fragmentation of mesophotic populations. This will result in an erosion of their population size, genetic diversity  and resilience; ultimately threatening the species with risks of local extinctions. Long term survival of these heavily exploited populations has to rely on local recruitment. Preservation of the reproductive potential, supported mainly by larger and more valuable colonies, has to be a priority for the conservative management of the species. Therefore, management of red coral harvesting in the mesophotic habitats should be defined at a regional  level.High genetic structuring observed in mesophotic The discovery that red coral in the mesophotic zone is genetically structured; together with the evidence of a barrier to gene flow suggest the need to protect these vulnerable marine ecosystems by creating deep-sea marine protected areas. Establishment of marine protected areas along the continental shelf, inclusive of the deep and off-shore reefs, can enhance preservation of commercially exploited, long-lived, sessile invertebrates Future efforts should focus on characterising connectivity patterns and vulnerability of mesophotic red coral populations. We suggest that this occurs in the form of 1) mapping Mediterranean deep red coral populations and 2) using a multidisciplinary approach to study population structure and dynamics of these populations. Finally, extending genetic studies to other marine species in the mesophotic zone  is needed to characterise connectivity patterns and vulnerability of these ecosystems.


Epicrates inornatus) has spent 42 years on the Endangered Species List with little evidence for recovery. One significant impediment to effective conservation planning has been a lack of knowledge of the distribution of genetic variability in the species. It has previously been suggested that boas might best be protected around caves that harbor large populations of bats. Prior study has found Puerto Rican boas at relatively high densities in and around bat caves, which they use both to feed and seek shelter. However, it is unknown whether these behaviorally distinctive populations represent a distinct evolutionary lineage, or (conversely) whether caves harbor representative genetic diversity for the species across the island. We provide the first genetic study of the Puerto Rican boa, and we examine and compare genetic diversity and divergence among two cave populations and two surface populations of boas. We find three haplogroups and an apparent lack of phylogeographic structure across the island. In addition, we find that the two cave populations appear no less diverse than the two surface populations, and harbor multiple mtDNA lineages. We discuss the conservation implications of these findings, including a call for the immediate protection of the remaining cave-associated populations of boas.The endemic Puerto Rican boa ( Epicrates represents a diverse and ecologically important group of snakes comprising ten or more endemic species– at least three in the Bahama Archipelago and at least seven in the Greater Antilles E. inornatus)  and Mata de Plátano cave [n = 5]) and two surface populations (Dorado Beach [n = 9] and Río Encantado [n = 13]). We found a total of 21 alleles across the three loci among 51 individuals from the cave and surface populations. We found no evidence of null alleles or allele dropout, and the scoring error rate was 0.013 errors/locus (2 errors across the entire dataset). Exact tests indicated that all loci were in HWE  and 0.74 (Río Encantado) [IS = 0.2) indicating potential non-random mating or declining population size in this population. Estimates of genotypic differentiation between populations revealed significant divergence between Dorado Beach and the other three populations , as well as between Agrodel cave Mata de Plátano cave (P = 0.05) [STF) between populations revealed low but significant divergence between Dorado Beach and Agrodel cave , as well as Dorado Beach and Mata de Plátano cave . Like the AMOVA analyses for mtDNA, in comparisons of cave and surface populations, the majority of the genetic variance is observed within populations, rather than among them .We screened a total of 20 microsatellite loci. Of the 12 that we successfully amplified (e in HWE . Alleliccantado) . One pop = 0.05) . PairwisIt has been suggested that cave-associated populations of boas might represent tractable conservation priorities, as these populations are denser and individuals tend to have smaller home ranges around caves ISF = 0.2) that suggests non-random mating. Since our sample from Mata de Plátano was relatively small, more samples from this cave are necessary to reveal at what sampling level allelic richness asymptotes and yield better estimates of population genetic parameters, including better estimates of population structure. However, other work suggests that the population of boas at this cave has been declining in recent years For microsatellite data, we found that cave populations contained private alleles and allelic richness that encompassed both the low  and high  estimates for the four populations. High allelic richness might be expected if there is a high level of gene flow, though in the Mata de Plátano cave population this is contradicted by estimates of an inbreeding coefficient  as well as across a deep-water channel (Turks Island Passage) Epicrates suggests that the origins of diversity are from dispersal among West Indian islands and island banks, with little evidence for intra-island speciation . Although these authors did not include one species with potential bearing on this matter, E. gracilis, which might have evolved from peripatric speciation within the island or proto-islands of Hispaniola, it is notable that there is no evidence for speciation even in large and heterogeneous islands such as Cuba. These results, combined with intraspecific studies (including the present study) showing little phylogeographic structure, might suggest that boas are vagile and have elevated genetic connectivity (gene flow) over fairly broad geographic areas. This is in stark contrast to other West Indian squamates, such as Anolis lizards. For instance, in the widespread Puerto Rican mountain garden lizard (A. krugi), although fine and broad scale connectivity exists in this species, there is a high degree of genetic structure and isolation by distance across larger areas in the apparent absence of any obvious barriers to gene flow In addition, a study of the phylogenetics and biogeography of In Puerto Rico, boas appear to exhibit little to no phylogeographic structure, as the main haplogroups are distributed across the island with no measurable partitioning by ecoregion  or across the central mountain ranges . Indeed, in the four focal populations, at least two haplogroups can be found in each population. Prior to recent anthropogenic deforestation and disturbance, it is likely that boas consistently occupied almost all habitats on the island below about 500 m elevation, though they are occasionally found at higher elevations as well Puerto Rican boas are currently known from only a handful caves in the karst belt of Puerto Rico, and we have a very incomplete understanding of cave use in this species. Though our analysis only included two cave and two surface populations and a limited number of nuclear markers, we have established a baseline from which to add additional markers and to collect genetic data from other cave populations as they are discovered. Importantly, we have provided evidence for a high level of genetic diversity in cave populations, and hence we urge that cave populations should be managed to ensure that the cave and the surrounding habitat remain intact. Furthermore, we suggest that movement of boas by people (an extremely common practice) is not likely to disrupt any existing mtDNA phylogeographic structure, though we would still discourage the practice. Boas are frequently removed from urban areas by wildlife officers and translocated to protected areas on other parts of the island . For example, between January and March 2012 at least nine boas were brought to a holding facility at Cambalache State Forest and then released in nearby protected areas. The origins of these boas are often unclear, because no data recording system is in place, but they could potentially be brought to Cambalache from anywhere on the island. Future work should explicitly evaluate whether this practice is harmful to local populations owing to the potential for outbreeding depression


Aedes aegypti have been intensively treated with temephos and deltamethrin insecticides over the last fifty years, resulting in heterogeneous levels of resistance across the island. Resistance spreading depends on standing genetic variation, selection intensity and gene flow among populations. To determine gene flow intensity, we first investigated neutral patterns of genetic variability in sixteen populations representative of the many environments found in Martinique and experiencing various levels of insecticide pressure, using 6 microsatellites. Allelic richness was lower in populations resistant to deltamethrin, and consanguinity was higher in populations resistant to temephos, consistent with a negative effect of insecticide pressure on neutral genetic diversity. The global genetic differentiation was low, suggesting high gene flow among populations, but significant structure was found, with a pattern of isolation-by-distance at the global scale. Then, we investigated adaptive patterns of divergence in six out of the 16 populations using 319 single nucleotide polymorphisms (SNPs). Five SNP outliers displaying levels of genetic differentiation out of neutral expectations were detected, including the kdr-V1016I mutation in the voltage-gated sodium channel gene. Association tests revealed a total of seven SNPs associated with deltamethrin resistance. Six other SNPs were associated with temephos resistance, including two non-synonymous substitutions in an alkaline phosphatase and in a sulfotransferase respectively. Altogether, both neutral and adaptive patterns of genetic variation in mosquito populations appear to be largely driven by insecticide pressure in Martinique.Effective vector control is currently challenged worldwide by the evolution of resistance to all classes of chemical insecticides in mosquitoes. In Martinique, populations of the dengue vector  Aedes aegypti  has spread throughout the tropics in historical times . Res. ResAe. sistance . This stple ways . The speAe. aegypti populations from Martinique. Then, we investigated the association between insecticide resistance (temephos and deltamethrin) and 319 single nucleotide polymorphisms (SNPs) in 6 populations, in order to identify candidate genes for temephos and deltamethrin resistances in Ae. aegypti. We found that both neutral (microsatellites) and adaptive (SNPs) genetic variation is affected by insecticide pressure in Ae. aegypti populations in Martinique. First, using extensive field sampling (16 populations and 31 sub-populations) in different ecotypes of the island and seven microsatellite loci, we investigated neutral patterns of genetic variability and population structure at macro and microgeographic scales across Ae. aegypti was sampled from individual houses as larvae or pupae in sixteen localities of Martinique from January to March 2009 ( Two laboratory strains from French Polynesia (Bora-Bora) and Benin (SBE) and sixteen field-caught populations were used in the study. The two laboratory strains are susceptible to all insecticides and have been used as reference strains for resistance assays. rch 2009 . Each porch 2009 . This sarch 2009 . No spec50 and RR95) of twelve field-caught populations, the SBE strain (from Benin) and using the laboratory Bora-Bora strain as the susceptible reference strain. Larval and adult bioassays were carried out using temephos (Organophosphate) and deltamethrin (Pyrethroid), respectively.  As described in , larval  Microsatellite genotyping and population genetic analyses were implemented at the macro-geographic level using 16 F0 samples of 30 females and 10 males. In 3 localities, Fort-de France, St-Anne and Vauclin, individuals from 10, 4 and 4 distinct larval breeding sites respectively, were used for a micro-geographic level analysis. DNA was extracted from adult mosquitoes of both sexes using 2% CTAB as described in . DNA pelFIS and FST estimates were calculated according to [FST /(1- FST) on the natural logarithm (Ln) of straight-line geographic distance [FIS) and environmental variables  and resistance ratio were tested using the “stat” package in the R software version 2.10 [Genetic diversity by locus and sample and overall was characterized by estimating the number of alleles and allelic richness  using trding to  and testrding to . Geneticdistance . Geneticdistance ). A bayedistance  was usedion 2.10 . Ae. aegypti laboratory strain Bora-Bora using transcriptomic data in [Ae. aegypti genome assembly AaegL 1.1  and 1520 SNPs with a coverage > 10x and a minimal allelic frequency of 5% were detected. The 318 SNPs used in this study were successfully transferred and genotyped in the natural Ae. aegypti populations of the Martinique Island [kdr-V1016I mutation in the voltage-gated sodium channel gene was also included in the SNP panel, as it was the only one found in a previous scan in Martinique populations among the four I1011M, I1011V, V1016I and V1016G kdr mutations [TM ND-1000 (NanoDrop Technologies), normalized to 50ng/µl and genotyped using the DNA Illumina GoldenGate® array genotyping platform at the Genotyping Center GENTYANE in Clermont-Ferrand, France. The fluorescent signal intensities of the specific alleles were determined by the BeadExpress Reader (Illumina Inc), and quantified and matched to genotype classes using GenomeStudio v3.1.14 (Illumina Inc) with manual adjustment when necessary. To ensure a good reliability of the genotyping data we used the GenCall50 (GC50) which indicates the reliability of each genotype call, the GenTrain which measures the cluster quality of the SNPs, and the call rate (CR) which represents the fraction of the samples that has been successfully genotyped for a given SNP. We kept SNPs with GC50 higher than 0.35, GenTrain higher than 0.50 and CR higher than 0.50.Six out of the 16 populations  representative of the range of insecticide resistance levels observed in Martinique were analysed for 319 SNPs. 318 of these SNPs were developed in the  data in . Brieflyutations  . DNA wahttp://cmpg.unibe.ch/software/bayescan/). This Bayesian method is based on a logistic regression model in which each logit value of genetic differentiation Fstij at a given locus i in population j is decomposed as a linear combination of αi and βj, corresponding to a locus effect and to a population effect, respectively. To test for the signiﬁcance of αi for each locus, the posterior probability that αi is different from zero is estimated using a Reversible Jump MCMC algorithm [i and βj were Gaussian distributions with means 0 and -2 respectively and standard errors 1 and 1.8 as in [To detect SNPs displaying higher than expected differentiation under neutrality between the 6 populations (outliers) we used BayeScan v3  and we used RR95 in association analysis in order to maximize the range of RR variation between the populations. Association analyses between RR95 and SNPs were performed using the least squares fixed effects linear model implemented in the software TASSEL v3 [P values were corrected for multiple comparisons by permutation tests with 1000 permutations and 0.05 confidence level.RRASSEL v3 . This moFst outliers, or as being significantly associated with a resistance phenotype, were blasted on the reference genome of Ae. aegypti (http://aaegypti.vectorbase.org/) to locate them inside or at proximity of potential candidate genes. The length of linkage disequilibrium can strongly vary from a genomic region to another and from a population to another, so that it is very difficult to assess an overall disequilibrium length in natural populations. In a closed population (a laboratory Ae. aegypti strain) under a standard pure-drift demographic model, overall linkage disequilibrium was estimated to be 20 Kb for neutral markers [All SNPs detected either as  markers . In a ge50 ranged from 13 fold (SJOS) to 36-fold (GMRN) and RR95 ranged from 26-fold (SJOS) to 153-fold (VCLN). The populations from the two islets showed a lower resistance level to temephos with RR50 of 5-fold for both islets, and RR95 of 17 and 21-fold for ILA and ILO, respectively. Mortality after 24 h deltamethrin exposure ranged from 19% for AJPB to 90% for the RSAL population compared to the 100% mortality in the susceptible strains Bora-Bora and SBE. For each insecticide, resistance ratios were not significantly explained by the number of insecticide treatments, or by other environmental variables such as the type of locality , human density or altitude  were not correlated  with the environmental variables measured . However, allelic richness was negatively correlated with the level of resistance to deltamethrin  underlying a significant decrease of diversity in the most resistant populations. Furthermore, FIS was significantly correlated with the level of resistance to temephos  showing an increased consanguinity in populations more resistant to temephos. A total of 31 populations were successfully genotyped with the 7 microsatellites markers that were all polymorphic except 38/38 that was not kept for further analyses. Genetic diversity was relatively homogeneous among the different populations tested at both macro and micro-geographic levels . AverageFST was low (0.079) but the populations were significantly structured both at the macro-geographic and at the micro-geographic scales  and at the local scale in Vauclin (P = 0.042), but not in Fort-de-France and Sainte-Anne (P > 0.5). Four genetic clusters were identified in Martinique . Pairwise Fst were generally smaller for SNPs than for microsatellites  and the 6 populations were at the HW equilibrium except for a slight deficit in heterozygotes in Rivière Salée. The global tellites .Fst outliers across the 6 populations tested in Martinique , confirming previous report [Fst outliers, two were significantly associated with deltamethrin resistance, and one with temephos resistance. Five other markers were associated with deltamethrin resistance and four other were associated with temephos resistance  at the whole Martinique scale. This suggests that gene flow mostly occurs at a local scale with high admixture occurring among neighbour sites. Furthermore, four genetic clusters were identified, with marked differences in the proportion of assignation of individuals to each cluster from a site to another. Northern populations were mostly assigned to one cluster (red on P = 0.042), supporting the effect of genetic drift acting on mosquito populations. Genetic drift at local scale could be due to the recurrent insecticide applications leading to local bottlenecks. Furthermore, flight activity of Ae. aegypti is limited to few hundred meters [Despite an overall low genetic differentiation among sites, most pairwise r red on  and Soutr red on . The gend meters  which isi values, indicative of directional selection. These included the knockdown resistance kdr mutation (V1016I), which is a well-characterized mechanism of resistance to pyrethroid insecticides in insects (including Ae. aegypti) and is caused by a point mutation of the para-type sodium channel [kdr mutation V1016I was not significantly associated with deltamethrin resistance; this could be due to the fact that this mutation was present at high frequency in all the main island populations Click here for additional data file.Table S2Ae. aegypti populations at the micro-geographic level in Martinique.Genetic variability and goodness of fit to Hardy-Weinberg expectation in (DOC)Click here for additional data file.Table S3Comparison of pairwise Fst obtained with microsatellites and SNPs for six populations of Martinique.(DOCX)Click here for additional data file.Table S4Genes up to 500 kb each direction from the SNP.(XLSX)Click here for additional data file.


The Strait of Gibraltar is a crucial area in the settlement history of modern humans because it represents a possible connection between Africa and Europe. So far, genetic data were inconclusive about the fact that this strait constitutes a barrier to gene flow, as previous results were highly variable depending on the genetic locus studied. The present study evaluates the impact of the Gibraltar region in reducing gene flow between populations from North-Western Africa and South-Western Europe, by comparing formally various genetic loci. First, we compute several statistics of population differentiation. Then, we use an original simulation approach in order to infer the most probable evolutionary scenario for the settlement of the area, taking into account the effects of both demography and natural selection at some loci.We show that the genetic patterns observed today in the region of the Strait of Gibraltar may reflect an ancient population genetic structure which has not been completely erased by more recent events such as Neolithic migrations. Moreover, the differences observed among the loci  across the strait suggest specific evolutionary histories like sex-mediated migration and natural selection. By considering a model of balancing selection for HLA-DRB1, we here estimate a coefficient of selection of 2.2% for this locus , which is in line with what was estimated from synonymous versus non-synonymous substitution rates. Selection at this marker thus appears strong enough to leave a signature not only at the DNA level, but also at the population level where drift and migration processes were certainly relevant.Our multi-loci approach using both descriptive analyses and Bayesian inferences lead to better characterize the role of the Strait of Gibraltar in the evolution of modern humans. We show that gene flow across the Strait of Gibraltar occurred at relatively high rates since pre-Neolithic times and that natural selection and sex-bias migrations distorted the demographic signal at some specific loci of our genome. Geneticists are often faced with the acute problem of disentangling the effects of natural selection and demographic history on the evolution of different polymorphisms ,2. Such Although recent studies on the genetic history of human populations focus on the analysis of non-coding (e.g. STRs ) or geno-4 to 6.28 × 10-4, with an average of 4.42 ± 0.76 × 10-4), although variation in effective population size between populations may actually lead to more heterogeneous estimates. Also, based on the hypothesis that non-coding regions are neutral, Meyer et al. ) than for MNSs , and is not significantly different from zero for the latter  than in SWE  where it is not significantly different from zero  gene for which significant departures from neutral expectations towards an excess of heterozygotes have been confirmed at the population level both on allele frequencies , and i G6PD/A-  and 4-9% G6PD/A- , two casNm) on each side of the Strait of Gibraltar or across it are remarkably similar for STR and SNP datasets, the genetic differentiation (CTF) between NWA and SWE measured with SNPs is more than twice that measured with STRs. This result, which was reproduced in an analysis of a smaller dataset that included exactly the same individuals tested for SNPs and STRs , is independent of the pattern of differentiation among populations: population pairwise STs F(STs Rfor STRs) were indeed highly correlated (r= 0.987). Genetic differentiation measured by STRs could be lowered because of the specific mutation process driving the evolution of microsatellite loci, which can produce alleles identical in state but not identical by descent, thereby rubbing out the effect of genetic drift [STF, because this measure is not only affected by the mutation rate at microsatellite loci but also by the mutational model governing them. On another hand, a recent study that compared large-scale SNP and STR genotyping in the Human Genome Diversity Panel (HGDP) concluded that SNP-based STs Fcould be inflated by ascertainment bias [i.e. the very high variance of genetic diversity between samples for STRs  of 1.2 to 2.2% on both sides of the Strait  involves gene flow since 20,000 years, not only between populations located on both sides of the Strait but also across the Strait. Time elapsed since the Neolithic transition was too short to allow for the current genetic structure to emerge during this period. This is revealed by the very low probability associated to scenario N compared to all other scenarios involving gene flow during the Palaeolithic , we used 4 loci  to infer the demographic scenario which best fits the current genetic structure around the Strait of Gibraltar (Western Mediterranean). Our simulations show without ambiguity that the genetic pattern observed in the Western Mediterranean was mostly constituted in pre-Neolithic times. Indeed, the most probable PN and PNI, Figure It is relatively surprising that we do not obtain a better fit to the observed data when considering the Neolithic transition and the Arabian conquests, in addition to the gene flow occurring in the Palaeolithic era . This rough estimate neither takes into account the variation of Nm over time, nor at specific periods such as after the Neolithic transition.Our results show that gene flow between populations either within South-Western Europe or within North-Western Africa is not particularly reduced. We compensated the relative lack of precision of the point estimates obtained individually with each marker by multi-locus analyses.  dataset  but is c dataset ). Under inter Nmwhich measures gene flow across the Strait of Gibraltar. We estimated a inter Nmbetween 4.2 and 64.7 with respect to the mean gene flow between populations located on each side of the Strait (within South-Western Europe and within North-Western Africa) but the overall reduction is not as strong as the one estimated for the Y chromosome (inter Nm= 2). This rough estimation confirms that the Strait of Gibraltar does not constitute such a strong barrier as suggested by Y-chromosome data. For comparison, Nm estimated on the basis of mtDNA for nowadays hunter-gatherer populations is smaller than 5 [inter Nmis that our model lacks certain features that may have impacted on the level of gene flow between populations across the Strait of Gibraltar: i) migrations may have been periodical rather than continuous over time. One can imagine that gene flow across the Strait resulted from the movement of groups of individuals at several periods of time, due for example to climatic changes (sea-level up and down) or for cultural reasons; ii) the Mediterranean Sea had a profound impact on exchanges between populations located around it [iii) very different migration patterns for males and females across the Strait may also contribute to blur the signal.Unfortunately, we did not obtain very precise estimations for the other demographic parameters, notably r than 5 . Substanround it ,76, but s = 1.9% under their model II). Such similarity indicates that this result is very robust, although Slatkin and Muirhead [et al. and ours, despite completely different approaches, indicates that our method is powerful and that a similar approach is likely to be applied successfully to estimate coefficients of selection at the other HLA loci as well. The very good fit of the two estimations obtained in the present study with the two different grid size also suggests that our estimation is relatively robust although our performance tests demonstrate a tendency to an overestimation of the coefficient of selection  genetic differentiations between populations across the Strait. The lack of genetic differentiation for HLA-DRB1 is particularly interesting because it can be explained by balancing selection (with a coefficient of selection estimated here to be around 2%). Given the huge worldwide dataset available for this locus, a better understanding on the mechanisms of selection at HLA loci could be very helpful to the study of human evolution, and more generally MHC. Our results obtained for Gibraltar have to be confirmed by further studies in other areas, especially where gene flow between populations is reduced. This work thus constitutes a step forward towards a better characterization of the combined effects of selection and demography on the genetic structure of populations, and especially on their genetic differentiation.We compiled data from populations located on each side of the Strait of Gibraltar by gathering published information for various genetic loci from the following countries: Continental Portugal, Spain and France, for South-Western Europe (SWE), and Morocco, Tunisia and the Northern part of Algeria (North of latitude 27.7°), for North-Western Africa (NWA). We restricted our compilation to markers for which many population samples were available for both sides of the Strait of Gibraltar in order to get enough information about the level of gene flow in each side of the Strait as well as across the Strait. Data on 7 different genetic loci were thus collected  and the mean heterozygosity (H). For mtDNA and the Y chromosome, H was computed as the gene diversity [We compared the genetic diversity for the various genetic loci across the Strait of Gibraltar based on the different types of markers used . We computed two standard diversity indices: the mean number of alleles within samples (iversity .i) ANOVA or AMOVA [ii) Reynolds pairwise genetic distances between populations [To evaluate the genetic diversity among populations, we performed two kinds of analyses using the software Arlequin ver 3.1 : i) ANOVor AMOVA  where thulations . When neWe developed a simulation program called SELECTOR, written in C++ and compiled on Linux. This program allows one to simulate populations of diploid individuals, generation by generation, within a spatially explicit framework. Allele frequencies in the populations, either at neutral or selected loci, may be simulated. The spatial framework as well as the demographic model used have been derived from the software SPLATCHE . This alM from a deme is computed as follows: t = mNtM, where m is the migration rate, and t Nis the population density of the deme at generation t t. Mis then distributed equally into the neighbouring demes, and the remaining individuals  are added to the emigrant pool of the next generation. The demography is logistically regulated within each deme as follows: Nt is the density at generation t, r is the growth rate, and K is the carrying capacity . All parameters r, m and K can be defined independently for each deme. These parameters can also be modified at any time during the process to allow the simulation of a large variety of demographic scenarios. The program SPLATCHE uses the same demographic model but simulates haploid individuals  that may potentially account for the genetic structure observed at the Strait of Gibraltar.We simulated 4 different evolutionary scenarios , a time depth which corresponds roughly to the upper limit attributed to the Ibero-Maurusian blade industry . It seematherers ,88. The atherers ,63.P [2. The growth rate is two times higher than for scenario P [The "Neolithic" scenario simulates gene flow between large-sized populations across the Strait of Gibraltar since the Neolithic era. The starting time is 300 generations  ago, in agreement with the beginning of the Neolithic transition in South-Western Europe , althougP , i.e. beenario P ,92.P and N. Hence, the "Palaeolithic" scenario is simulated as described above, but 300 generations before present, the carrying capacities are increased by a factor of 10 and the growth rate by a factor of 2.This scenario combines scenarios Islamic colonisation on top of the PN scenario. It is simulated by a migration wave starting 55 generations ago  and the same across the Iberian Peninsula.We add the first D., i.e. ) from thKm, but noted Nm here for consistency with previous literature. The products intra Nmand inter Nmthus measure the mean level of gene flow at equilibrium on each side of the Strait of Gibraltar  and across the Strait , respectively. Note that for autosomal markers, Nm corresponds to the effective number of both male and female migrants, while for sex-specific markers, it corresponds either to the number of males (Y chromosome) or to the number of females (mtDNA). For all scenarios, the intra-continental migration rate  was chosen between 0.025 and 0.4, which correspond to Nm values between 3 and 200 for the "Palaeolithic" scenario. Nm is 10 times higher for the Neolithic era, and 40 times higher for the Islamic colonisation. Note that inter Nmis never higher than intra Nmin any simulation.Each scenario was done using a grid made up of 256 demes of about 50 × 50 kilometres, . We .045*10-3). The lo.045*10-3. MoreoveP, N, PN, PNI,); 2°) estimate the demographic parameters for the best scenario, and estimate the selection coefficient s for HLA-DRB1 .Our simulation procedure is integrated in the Approximate Bayesian Computation (ABC) framework . This meCTF, SC Fand ST Fobtained with AMOVA/SAMOVA analyses [intra Dbetween populations within a continental area (NWA or SWE) and inter Dbetween each pair of populations belonging to different continental areas. For ABO, MNSs, GM, RH and HLA-DRB1, we also use the mean number of alleles (na) and heterozygosity (H) within samples, as well as their standard deviation. In order to use the molecular information, we use specifically for mtDNA the mean number of segregating sites S and the mean molecular diversity π (and their standard deviation) as well as, specifically for the Y-chromosome STRs, the gene diversity H and the mean allelic range R (and their standard deviation) and the gene diversity H and the number of haplotypes K for the Y-chromosome SNPs. The following steps are followed for the ABC procedure: 1°) 100,000 simulations are done for every scenario ; 2°) Euclidian distances between observed and simulated statistics are computed according to Beaumont et al. [f of the best among the 400,000 simulations is computed. Here we chose f = 1,000, which corresponds to 0.25% tolerance level, but our results are robust with various values of f (not shown); 4°) for the best scenario, we generate 900,000 additional simulations  and we estimate the most probable parameter values from the fraction f of retained simulations (again 0.25% tolerance level), independently for each locus; 5°) we also perform a multi-locus analysis by generating 500,000 demographic simulation data for 4 independent markers considered as evolving almost neutrally, i.e. RH, GM, mtDNA and the Y-chromosome STRs. We are conservative when using Y-chromosome STRs instead of SNPs because STRs are probably less affected by ascertainment bias and the dataset is much numerous. We proceed to parameter estimation using jointly the 36 statistics calculated for those 4 loci.In accordance with the ABC methodology, we repeat 100,000 times the simulation of a given scenario, each time with input parameters drawn from prior distributions (see Additional file analyses , the meat et al. , using at et al. , using tWe use SELECTOR and SPLATCHE to perform the simulations and the program abcEst  to do thMC and ASM conceived and designed the study. MC, ESP and ASM carried out the analyses, interpreted the results and wrote the manuscript. MC developed the simulation program and carried out the simulations and the ABC estimation procedure. All authors read and approved the final manuscript.Complementary information on the methods and results. This file contains additional information on: 1- Resampling procedure; 2- Ewens-Watterson and Slatkin neutrality tests; 3,4,5,6- ABC estimation procedure, such as prior distributions, detailed estimation results, distributions of statistics and performance evaluation; 7- Methodological details on the simulation of different selection coefficients in Africa and Europe; 8- Results obtained with simulations on a grid with a different resolution.Click here for file


Gentianella bohemica is a subendemic of the Bohemian Massif, where it occurs in seminatural grasslands. It has become rare in recent decades as a result of profound changes in land use. Using amplified fragment length polymorphisms (AFLP) fingerprint data, we investigated the genetic structure within and among populations of G. bohemica in Bavaria, the Czech Republic, and the Austrian border region. The aim of our study was (1) to analyze the genetic structure among populations and to discuss these findings in the context of present and historical patterns of connectivity and isolation of populations, (2) to analyze genetic structure among consecutive generations (cohorts of two consecutive years), and (3) to investigate relationships between intrapopulational diversity and effective population size (Ne) as well as plant traits. (1) The German populations were strongly isolated from each other (pairwise FST= 0.29–0.60) and from all other populations (FST= 0.24–0.49). We found a pattern of near panmixis among the latter (FST= 0.15–0.35) with geographical distance explaining only 8% of the genetic variance. These results were congruent with a principal coordinate analysis (PCoA) and analysis using STRUCTURE to identify genetically coherent groups. These findings are in line with the strong physical barrier and historical constraints, resulting in separation of the German populations from the others. (2) We found pronounced genetic differences between consecutive cohorts of the German populations (pairwise FST= 0.23 and 0.31), which can be explained by local population history . (3) Genetic diversity within populations  was significantly correlated with Ne (RS= 0.733) and reflected a loss of diversity due to several demographic bottlenecks. Overall, we found that the genetic structure in G. bohemica is strongly influenced by historical periods of high connectivity and isolation as well as by marked demographic fluctuations in declining populations.The biennial plant  Comparing historical and contemporary data on the distribution of plant species of seminatural grasslands often provides a picture of dramatic loss of populations, of decreasing population size, and of increasing habitat fragmentation. This is chiefly due to extrinsic factors such as habitat alteration and destruction, land-use intensification  in seminatural habitats, climate change, and the interaction between these threats . In EuroIn fragmented habitats, short-lived plant species with high generational turnover often experience additional pressure from intrinsic factors connected to their life cycle, which renders them more sensitive to environmental stochasticity, especially when they lack a persistent seed bank . They maGentianella aspera was investigated by Until now, the historical dimension in population genetics has mostly been studied in terms of phylogeography over large regional scales and over long time periods, for example, Pleistocene history, reviewed by Gentianella bohemica Skalicky  is a biennial plant that has become rare during the 20th century  and Bombus spp. (bumblebees). Other pollinators are Lepidoptera (butterflies), Syrphidae (hoverflies), and Muscidae (flies)  . There iermanica . Gentianirective . Data fobohemica  in the Bbohemica , the her in 1969 , we haveprograms , mostly G. bohemica in the Czech Republic, Austria, and Germany, and one population of unclear taxonomic status (G. germanica/lutescens) near Dresden, Germany. Between 25  and 33 individuals per population were selected randomly. Additional leaf samples, collected in 2007 from a subset of four G. bohemica populations, were also included. Samples were dried and stored in silica gel prior to DNA isolation. Vouchers of the sampled populations are stored in the herbaria CHEB, LI, PR, and REG. For each population, census data (number of flowering plants) were available from regional monitoring programs with census periods ranging from seven to 20 consecutive years  for scoring. Bands in the size range 100–500 bp were scored and the results were exported as a presence/absence matrix. We chose not to score fragments below a length of 100 bp due to the higher frequency of nonhomologous fragments in this size class  All samples of one Austrian population of G. bohemica were also removed, as we found an extremely high number of private fragments due to an infection. Thus, all further analyses were carried out with a final matrix of 379 fragments of 204 individuals from nine populations of G. bohemica  according to the manufacturer's protocol. AFLP fingerprint profiles were generated for  25–33 individuals per population, totaling 253 individuals, following the protocol described in ze class . NonreprNe was calculated from the harmonic mean of census sizes of flowering individuals over several years (RM). The significance of the correlations was tested by random permutation (9999 permutations). Two- and three-level hierarchical analyses of molecular variance (AMOVA) were calculated for regional groupings  and temporal groupings (cohorts of consecutive years) using the program Arlequin 3.0 (HSh) based on polymorphic fragments using the software FAMD 1.25 (HSh) for the smallest population sample  disagreed markedly, we removed this sample from all correlation analyses. The two diversity estimates then revealed the same pattern of significant correlations and were significantly correlated regardless of whether we included the 2007 samples  or considered only 2008 samples with Finsterau 2007 replacing 2008 . We therefore only present the results for HSh. Correlations (RS) between indices of genetic diversity, population sizes, and plant traits (pooled for each population) were calculated with STATISTICA 6.0  and the most likely assignment of each individual to a certain group without a priori information about population structure were estimated using models with uncorrelated allele frequencies, with or without admixture. K values ranging from 1 to 10 were tested, employing 10 independent runs for each value of K, each with 106 Markov chain Monte Carlo generations after a burn-in period of 105 generations. The optimal number of groups was determined from the similarity coefficients among replicated runs of the same K as defined by Genetically homogeneous groups of individuals were identified according to the genetic mixture analysis implemented in STRUCTURE 2.2 . The appG. bohemica. Of these fragments, 371 were polymorphic and 41 of them occurred only in one individual each. Every individual had a different multilocus AFLP phenotype. Details of the mean number of fragments, number of polymorphic fragments, and number of private fragments per population are given in Overall, 379 unambiguously scorable and reproducible fragments with lengths of 100–500 bp were found in 204 individuals of A neighbor-net analysis of all 2007 and 2008 samples (data not shown) resulted in a star-like topology of the entire dataset, with some separation between the German populations. The first three axes of the PCoA explained 64% of the total variation  and provP < 0.001) of the variation among populations in 2008 (P < 0.001)  . Accordi01)  when all populations were compared (2008 cohorts). This isolation by distance remained at the same level , when the German populations were excluded. Geographic distance therefore accounted only for about 6% (R2= 0.063) of the genetic distance among all populations and for about 8% (R2= 0.076) of genetic distance among the Czech and Austrian populations. A rigorous analysis of all 2007 and 2008 data for genetically coherent groups using STRUCTURE revealed three groups  values  values . Group 1FST with values of 0.23–0.31  between the German cohorts and a very low differentiation of 0.03 (P< 0.05) between the cohorts of the Czech population. The 2007 and 2008 cohorts were always found in their respective group of the STRUCTURE analysis except for Mauth: the 2007 cohort of this population and part of the 2008 cohort formed a group including the population at Finsterau, located a few kilometers away. The other part of the 2008 cohort was included in the large group formed by all Czech and Austrian populations. The pairwise FST between these two genetic groups of Mauth 2008 is quite high with a value of 0.55. Pairwise FST values between the 2007 cohort and the two groups of 2008 differ notably . Due to this complex structure of the 2008 cohort in Mauth, a lower differentiation among all 2008 cohorts was found by AMOVA than among the 2007 cohorts from the same populations  in the 2007 cohort than in 2008 (nF= 105), which is in part due to a higher number of low-frequency fragments and fewer fixations in the latter. There are no fixed private fragments in either cohort. Within the 2008 cohort, however, the two private fragments are confined to individuals that are included in the large genetic group of all non-German populations. Regarding this group of individuals, the private fragments occur with high frequencies of 0.7 and 0.8. Both 2008 groups show similar nF values (106 for the group joining the large cluster vs. 103).A closer inspection of the population from Mauth revealed a lower mean number of fragments (HSh) did not show any correlation with N, the current population size. However, HSh correlated significantly  with the estimated effective population size Ne. High HSh values were found for the Czech populations but also in the population at Mauth 2008 (Germany) as well as that at Leopoldschlag (Austria). In contrast, the other Austrian and all other German populations showed lower values than the Czech populations, which also exhibited the highest numbers of individuals in the 2008 census and showed the largest effective population sizes (except for Onšovice). We noted a striking difference in HSh between the 2007 and 2008 cohorts of Mauth. Among the measured plant traits, we found a significant correlation  of HSh with shoot length.The Shannon diversity index , which is covered by dense spruce forests and forms a barrier to the dispersal of pollen and diaspores. Additionally, wet fen areas, unfavorable for G. bohemica, extend across the border region. Interestingly, the genetic structure of the investigated populations indicates a scenario of former panmixis within a well-connected population system in the former Habsburg Empire (covering the regions of today's Austria and Czech Republic) from which the German populations were already disconnected in historical times despite their geographical proximity.In our study, genetic structure provided strong signals of isolation among the three German populations of e region . DespiteHistorical trade routes have provided a variety of vectors facilitating seed dispersal since medieval times. Several ancient pathways existed between Upper Austria and Bohemia for trading in salt and cattle . Two of Another reason for the strong differentiation of the German populations is found in their population history. Annual census data from 1989 to 1998 provide evidence of severe demographic bottlenecks in all German populations and evidence for local extinctions . AlthougThe very low differentiation between the two cohorts (2007/2008) of the population at Chvalšiny (Czech Republic) is in strong contrast to the high differentiation found between the 2007 and 2008 cohorts of the three German populations. This might be due to reduced seed bank activation by cattle hoofprints after a period of abandonment in the German populations, while the Czech population has experienced a much longer period of traditional grazing with additional regular soil disturbance through military training activities in recent decades . Traditional land use was practiced much longer and more intensely in this part of Bohemia than in Bavaria, where abandonment and afforestation started before the Second World War .G. bohemica results in temporal isolation among consecutive cohorts. Acyclic activation of the persistent seed bank  Pollen dispersal only carries a haploid genome and is expected to result in a pattern of significant admixture, which we did not observe. (2) Pollen dispersal is considered the major component of gene flow at the local scale, that is, within populations . In addiG. bohemica  by sheep and cattle, as such small seeds can become lodged in sheep's wool  found in bohemica  and in otianella  probablyp's wool  and are p's wool .Gentianella species. Such dynamics may act on a local scale among patches of large spatially structured populations  as suggested by G. aspera.In our study, we were able to identify a possible source area  for those migrants. It was, however, impossible to determine dispersal time and vectors from the present data. To our knowledge, conservation activities such as seed sowing in declining German populations have always used seeds from the same or nearby populations , howeverNe is a better predictor of genetic diversity (HSh) than the current population size  we found were inconclusive with respect to recent bottlenecks. A codominant marker would be needed to estimate allelic variation and heterozygosity.The low genetic diversity found in the German populations may result both from inbreeding and genetic drift effects in years with very small numbers of individuals. At neutral loci, bottlenecks have a stronger effect on allelic richness than on heterozygosity , while iG. bohemica is largely explained by earlier periods of connectivity between Czech and Austrian populations. Many populations have experienced recent demographic bottlenecks, which have affected their effective population size and genetic diversity. In the long term, the poor dispersal ability of plants limited to rare and isolated habitats is expected to result in strong genetic differentiation among populations (The genetic structure of the investigated populations of ulations . Severalulations , that is