Stipa purpurea is a dominant grass species in the alpine steppe and meadow of the Qinghai-Tibetan Plateau (QTP). Ecological niche modelling was applied to S. purpurea, and its distribution was found to be most strongly correlated with the annual precipitation and the mean temperature of the warmest quarter. We established a north-to-south transect over 2000 km long on the QTP reflecting the gradients of temperature and precipitation, and then we estimated the morphological by sampling fruited tussocks and genetic divergence by using 11 microsatellite markers between 20 populations along the transect. Reproductive traits (the number of seeds and reproductive shoots), the reproductive-vegetative growth ratio and the length of roots in the S. purpurea populations varied significantly with climate variables. S. purpurea has high genetic diversity (He = 0.585), a large effective population size , and a considerable level of gene flow between populations. The S. purpurea populations have a mosaic genetic structure: some distant populations (over 1000 km apart) clustered genetically, whereas closer populations (< 100 km apart) had diverged significantly, suggesting local adaptation. Asymmetrical long-distance inter-population gene flow occurs along the sampling transect and might be mediated by seed dispersal via migratory herbivores, such as the chiru (Pantholops hodgsonii). These findings suggest that population performance variation and gene flow both facilitate the response of S. purpurea to climate change.Estimating the potential of species to cope with rapid environmental climatic modifications is of vital importance for determining their future viability and conservation. The variation between existing populations along a climatic gradient may predict how a species will respond to future climate change.  Continuous climate change has a major impact on population persistence and species distribution . EstimatPopulation divergence results from a delicate balance between the opposing forces of gene flow and diversification via environmentally-generated heterogeneous selection , 12. WheStipa purpurea and assess the role of gene flow and biomass allocation in explaining the population divergence of S. purpurea along the strong environmental gradients occurring in the QTP to assess population features that may be useful to respond to climate change.Although numerous studies of population divergence have been published, models incorporating phenotypic variation, genetic divergence and gene flow combined with climatic variables have proven inadequate to thoroughly understand the response of plant species to ongoing climate change . PhenotyS. purpurea is a dominant species in the alpine steppe and meadows of the QTP. The QTP is the highest place in the world and is known as “the Third Pole of the Earth.” It is considered a key biodiversity hotspot [ hotspot . Due to  hotspot . In addiS. purpurea populations and corresponding morphological responses to local habitats. On the other hand, given the continuous distribution of S. purpurea on the QTP, considerable inter-population gene flow may counteract the population divergence. To test these two hypotheses, we used ecological niche modelling (ENM) to find the most likely climate factors influencing the distribution of S. purpurea and then established a transect across the QTP based on the results of ENM analyses, along which the genetic and morphological variation of S. purpurea was surveyed. We aimed to answer the following questions: 1) Is there strong population divergence in S. purpurea? 2) Is the morphological and genetic variation between populations correlated with climatic variables? and 3) How does gene flow influence population divergence and response to the local environment?The remarkable environmental gradients on the QTP may lead to strong divergence of No special permits were required for locations and samplings in this study. All samples were collected by researchers with introduction letters of IBSFU (Institute of of Biodiversity Science), Fudan University. The collection was completed with the help of local herdsmanStipa purpurea is endemic to the QTP, Pamirs Plateau and the high mountains of Central Asia [S. purpurea can also propagate clonally by tillering [S. purpurea plays a paramount role in biodiversity, soil and water conservation [ral Asia . It is aillering . The seeervation . Its disS. purpurea sample locations derived from three sources for ENM. We obtained 69 records from the Chinese Virtual Herbarium , 150 records from the Global Biodiversity Information Facility , and 28 records from published population genetics studies [http://www.worldclim.org). The resolution of all climatic layers was 2.5 arc-minutes (5 km) to ensure compatibility with the resolution of the location data. The study area was defined according to the commonly accepted range of the QTP, between 73.31°E, 104.78°E, 26.00°N and 39.78°N [We used a total of 218  studies  and the  39.78°N .S. purpurea was estimated based on the layers for the current climate and the maximum-entropy algorithm . To avoEnt 3.3; . The proTwarm) and the annual precipitation (AP) are the factors that are most highly correlated with the S. purpurea distribution. We therefore set up a north-to-south transect over 2000 km to sample S. purpurea populations across temperature and precipitation gradients on the QTP. A total of 20 populations were sampled along the transect, ranging from 30°N to 37°N in latitude, 91°E to 100°E in longitude and 3200–5100 m in altitude . Thus, we performed trait measurements on 17 populations in total.Nroot). We also recorded the number of vegetative (Nvshoot) and reproductive shoots (Nrshoot) for each plant. We considered reproductive shoots as spikes and measured the height of the longest spike (Lspike). The length of the longest vegetative shoot (Lvshoot) and the root (Lroot) of the plants were measured as well. The seeds were counted and weighted, and the number of seeds (Nseed) and the weight of 100 seeds (M100seed) were recorded. The root mass (Mroot), vegetative shoot mass (Mvshoots) and reproductive shoot mass (Mrshoot) were measured by weighing after drying in an oven at 60°C to constant weight. The above-ground mass (Mshoot) was the sum of the shoot masses , and the total mass  was the sum of the shoot and root mass . To determine the plant’s resource allocation, the root/shoot ratio (RSR) was calculated as RSR = Mshoot/Mroot. The allocation of above-ground biomass to reproduction (RVR) was expressed as RVR = Mrshoot/Mvshoot.In the laboratory, each plant was separated into roots and shoots. The roots were thoroughly washed and counted  was performed to reduce the trait dataset to sets of interrelated traits using SPSS v19.0.p < 0.05.We determined the proportion of reproductive biomass (R) versus vegetative biomass (V) and shoot biomass (A) versus root biomass (U) using the classical allometric model, R = aVb and A = aUb, fitted as log R = log a + b log V and log A = log a + b log U . The parDNA was extracted from 25–30 mg of dried leaf material, and a total of 11 SSR loci were amplified as described previously  S2 Tabl. PCR proHe), observed heterozygosity (Ho) and Wright’s fixation index F using GenAlEx v6.3 [Ae) and allelic richness (Ar) were calculated. Genotypic disequilibrium (LD) between all pairs of loci and the Hardy–Weinberg equilibrium (HWE) were determined for each population, and p-values were adjusted with sequential Bonferroni correction for multiple comparisons.MICROCHECKER v2.2.3  was usedlEx v6.3 . In addiFst using GenAlEx v6.3. Partitioning of the total genetic variation within and between populations was further analysed by AMOVA with 1,000 permutations using Arlequin v3.0. The genetic structure was explored using STRUCTURE v2.3.3. The program was given no prior information on ancestral populations and run 10 times for each value of K ancestral populations, with K varying from 1 to 20, under the admixture model with uncorrelated allele frequencies using 100,000 Markov Chain Monte Carlo iterations and a burn-in of 50,000 iterations. We inferred K using the ad hoc statistic ΔK [GGD) matrix and genetic distance (pairwise Fst/(1-Fst)) were generated in GenAlEx v6.3 and the Mantel test was performed with 1,000 bootstraps.We estimated the global istic ΔK . Nei’s gistic ΔK  with 1,0S. purpurea populations at the landscape scale based on a frequency-weighted average over all alleles and loci and on the correlation coefficients of genotypes in relation to their spatial distance. The distance class was set to 50 km, and the autocorrelations were performed using GenAlEx v6.3 with 1,000 permutations.We first used a spatial autocorrelation according to the method Peakall and Smouse’s  to deterS. purpurea, we applied a coalescent-based approach using the Bayesian and maximum likelihood inference methods implemented in MIGRATE [M). MIGRATE jointly estimates the effective population size ϑ (4Ne μ) and asymmetric gene flow M (m/μ) between pairs of populations over a long period of time (~4Ne generations). Three runs were conducted. First, two shorter runs were performed  and used to verify that the MCMC had estimated the parameters correctly. Then, a final long run was performed , and M values from this final run are reported. The initial run used an estimate of the Fst as a starting parameter to calculate ϑ, Ne and M. Each subsequent run used the Maximum-Likelihood (ML) estimates from the previous run as new starting parameters.To assess the long-term gene flow and the effective population size of  MIGRATE  to estimm, migration rates) that reflect gene flow over the last few generations. For BAYESASS analyses, each run consisted of 3 000 000 iterations with the chain sampled after 2000 iterations. A burn-in of 1 000 000 was used, and D values were adjusted to ensure that 40–60% of the total changes were accepted. As recommended by [BAYESASS  was usedended by , we perfMoreover, MIGRATE and BAYESASS were used to estimate the long-term and contemporary asymmetric gene flow between the genetic groups revealed by STRUCTURE in order to assess the migration rates between regions.We used all 19 bioclimatic variables to infer habitat heterogeneity. The geographical information for each population was collected with a GPS navigator when sampling. Given the high degree of cross-correlation between climatic variables, PCA was used to reduce the dimensionality of the climatic data set.MD) were obtained by calculating Euclidean distances between standardized values for the morphological variables of the plants collected in the field. If geographical distance (GGD) and genetic distance (pairwise Fst) were both significantly correlated with MD, then partial Mantel tests were performed to evaluate their relative importance to morphological traits. Morphological variation that significantly correlated with the GGD or pairwise Fst was further analysed using a partial Mantel test between the MD and three climatic principal components difference matrices (PC1clim to PC3clim) after controlling for GGD or pairwise Fst.To test for correlations between morphological, geographical, and genetic distances among populations, Mantel tests were performed for the 17 populations with trait measurements. Morphological distances , the annual precipitation  and the precipitation of wettest quarter  were the most influential climatic variables for S. purpurea distribution, because they explained about 54% of the variance  and the mean temperature of wettest quarter  , the biomass of the shoot (Mvshoot), and the total biomass  (Mrshoot), the biomass of 100 seeds (M100seed), and the reproductive fraction of biomass of the above-ground material (RVR), explaining 18.3% of the total variance. PC3 was highly correlated with the height of the plants  and seed number (Nseed), and explained 11.7% of the total variance. A scatterplot of PC1 against PC2 showed that the morphological variations of populations P13 and P18 are distinct  . PC2 wasdistinct .Mrshoot and log Mvshoot (r) or a violation of the assumption of normality. In addition, there was no sign of allometric allocation between Mshoot and Mroot (data not shown).Only 3 of the 17 S. purpurea populations in which traits were measured showed a significant positive correlation between log  Mvshoot . P6 and Ae) varied from 2.1 to 3.9 per locus, with an average value of 3.0 (Ar) at different loci ranged from 2.7 to 6.1, with an average value of 5.1. No significant departures from linkage equilibrium were detected for any pair of loci in each population, whereas significant deviations from Hardy–Weinberg equilibrium were detected for 10 loci after Bonferroni correction (p < 0.05). The S. purpurea populations had high genetic diversity, with an expected heterozygosity (He) ranging from 0.442 to 0.704. The overall inbreeding coefficient (F) ranged from -0.288 to 0.026  was 0.198 for the 11 SSR markers  clustered together   .S. purpurea populations have relatively large effective population sizes, with Ne > 1,000 (M = 1.343), which is similar to the estimate based on Fst values (Nm = 1.184)  up to a distance class of 200 km , indicat > 1,000 , and con= 1.184) . The meaK = 2 the sample map is divided into five regions (M) ranged from 0.027 to 1.613, with the highest migration rate observed from Hoh Xil to the Inland Tibet region (M = 1.613) (M <0.612), whereas higher gene flow occurred between the other regions (M = 0.723–1.613). Long-term migration between regions was asymmetrical, as shown by the number of migrants (M) in m) between regions ranged from 0.0016 to 0.1651  . The esto 0.1651 , with a MD) against geographic distance (GGD) between populations revealed a significant effect of isolation by distance on the differentiation of Mvshoot, Nrshoot, Mrshoot, Lroot, Mtotal and Nseed  controlling for GGD or Fst revealed that Mvshoot, Nrshoot, Lroot, Nseed and Mtotal were significantly influenced by climatic variables  (When a trait was significantly correlated with  any MD) .Nseed was correlated with annual mean temperature (bio1) and mean temperature of the coldest quarter (bio11), explaining 21.1% and 5.9% of total variance, respectively; Nrshoot was mainly dependent on precipitation during the harsh period of the year (bio17 and bio19), accounting for 3.2% and 10.7% of total variance; and Lroot was associated with temperature seasonality (bio4) and precipitation of the driest quarter (bio17), though those only accounted for 4.8% and 4.2% of the total variance, respectively , ectively . AlthougS. purpurea, which may indicate an adaptive response to local climatic variables.Plants interact with the changing environment in multiple ways. In this study, we found environmentally associated morphological variation and a mosaic population genetic structure with asymmetrical inter-population gene flow in Mtotal, Mvshoot, Nvshoot, M100seed, Mrshoot, Mtotal, Lspike, and RVR (reproductive/vegetative growth ratio) best explained the morphological divergence between populations  [Pedicularis on the QTP along an elevation gradient. Nevertheless, our findings do not preclude the possibility of adaptive divergence between populations. For instance, RVR contributed to population variation  and the others involve allocation. These findings demonstrate the importance of modifications to reproductive strategy for plants to survive under different conditions [S. krylovii [S. purpurea may open a high fraction of florets in relatively warm places to increase pollination but may allocate more to reproduction under relatively dry conditions. We found that Lroot decreased with an increase in temperature seasonality and the precipitation of the driest quarter [He = 0.774  [Genetic variability is required for populations to evolve in response to environmental changes.  the QTP . These bdex data  suggest al. 2013 ; Hamashaal. 2013 ). The hial. 2014); Siberial. 2014) ).Ne, heterozygote advantage, and self-incompatibility [Significant heterozygote excess was observed in most populations . There atibility . Heteroztibility . This astibility , though S. purpurea populations is moderate (Fst = 0.198). Significant IBD was supported by a Mantel test and the result of autocorrelation analyses ; insteaulations , Fig 7. S. purpurea is capable of dispersing pollen over relatively long distances by wind, wind-based pollen dispersal is unlikely to be effective over such a long distance between the sampled populations. Anemochorous seed dispersal over large distances for S. purpurea is next to impossible [Pantholops hodgsonii, also called chiru) and nomadic livestock . For instance, chiru females migrate a distance of around 300 km to the calving habitats in the northern QTP  in May and June of each year to give birth to their calves, and then migrate back to the wintering habitats in the southern QTP with their calves to reunite with males in August [S. purpurea is at the fruiting stage. Stipa spp. are the main fodder grasses of the chiru; their seeds easily attach to the body of chiru and may stay in the fur for hours or even days, resulting in long-distance zoochory [Even if possible . Long-din August , just whzoochory . Even ifzoochory . SufficiIn general, high levels of genetic diversity and unrestricted gene flow within a species are crucial for adaptation, especially when facing unpredictable local environmental changes . The abiS. purpurea along environmental gradients. In particular, morphological variation analyses revealed that temperature and precipitation are likely to act as major drivers of selective responses in this alpine plant. This finding is consistent with previous studies that have demonstrated the prominent role of temperature and precipitation in the general adaptation of plants [At the same time, population structure analysis and the morphological variation investigated here show that adaptive divergence between populations is associated with climatic factors. This finding is consistent with previous studies in perennial herb species, which found that patterns of local adaptation appear to be more common over large scales but rarer at small spatial scales . It alsof plants . Such inS1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 FigThe ΔK is based on the rate of change of ln P (X/K) between successive K values.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 TableNm = (1/4)(1-Fst)/Fst.(DOCX)Click here for additional data file.S3 TableNvshoot, the number of vegetative shoots; Lvshoot, the height of vegetative shoots; Mvshoot, the weight of vegetative shoots; Nrshoot, the number of reproductive shoots; Lspike, the height of the longest spike; Mrshoot, the weight of reproductive shoots; Nseed, the number of seeds; M100seed, the weight of 100 seeds; Nroot, the number of roots; Lroot, the length of roots; Mroot, the total weight of roots; Mtotal, the total biomass; RVR, reproductive biomass/vegetative biomass; RSR, underground biomass/aboveground biomass.(DOCX)Click here for additional data file.S4 TableBold-faced slopes indicate a significant deviation from 1.(DOCX)Click here for additional data file.S5 TableNe = ϑ/μ (μ = 10−3).(DOCX)Click here for additional data file.S6 TableThe migration rates are from the populations in the vertical row into the populations in the horizontal column, 95% confidence interval is shown in brackets.(DOCX)Click here for additional data file.S7 Table(DOCX)Click here for additional data file.


Silene cordifolia All. and Viola argenteria Moraldo & Forneris. The predicted suitable area for last glacial maximum roughly fitted current known distribution. Our results suggest that separation of the major clades predates the last glacial maximum and the following repeated glacial and interglacial periods probably drove differentiations. The complex phylogeographical pattern observed in the study species suggests that both populations and genotypes extinction was minimal during the last glacial maximum, probably due to the low impact of glaciations and to topographic complexity in this area. This study underlines the importance of cumulative effect of previous glacial cycles in shaping the genetic structure of plant species in Maritime and Ligurian Alps, as expected for a Mediterranean mountain region more than for an Alpine region.Quaternary glaciations and mostly last glacial maximum have shaped the contemporary distribution of many species in the Alps. However, in the Maritime and Ligurian Alps a more complex picture is suggested by the presence of many Tertiary paleoendemisms and by the divergence time between lineages in one endemic species predating the Late Pleistocene glaciation. The low number of endemic species studied limits the understanding of the processes that took place within this region. We used species distribution models and phylogeographical methods to infer glacial refugia and to reconstruct the phylogeographical pattern of  Quaternary glaciations and mostly late Pleistocene glaciation (0.120–0.018 Ma) have shaped the contemporary distribution of many species . PopulatIn the last few years several phylogeographical studies have supported this general view concerning the importance of the last glacial maximum  in shaping species distribution  and contPrimula allionii Loisel. was separated into two geographically disjoined groups during the Early/Mid Pleistocene border (0.781 Ma) and the region probably contains other paleoendemic species representing living examples of an ancient Tertiary flora present prior to the onset of the Mediterranean climate regime and subsequent Quaternary glaciations. However, the low number of endemic species that have been studied in this region limits our capacity to understand the processes that took place within the Maritime and Ligurian Alps [Situated at the crossroads of the Mediterranean Basin and the Alps, the Maritime and Ligurian Alps are a hotspot for plant biodiversity , 15 and ian Alps , 19, 20.Silene cordifolia All. and Viola argenteria Moraldo & Forneris (Silene cordifolia is a strict endemic species restricted to the Maritime Alps that represents an old Tertiary lineage [Viola argenteria is a disjoint endemic species (sensu [S. cordifolia and V. argenteria before the last Pleistocene glaciation? (2) Is there any evidence that populations of S. cordifolia and V. argenteria were influenced by Pleistocene climate fluctuations, and, if so, how?In the present study we used species distribution models (SDMs) and phylogeographical methods to infer glacial refugia and to reconstruct the phylogeographical pattern of two endemic species of the area, Forneris . Silene  lineage  and currs (sensu ) that has (sensu . More spwww.silene.eu) of the Conservatoire Botanique National Méditerranéen de Porquerolles (CBNMed), from Florence, Turin and Genoa Herbaria  and from our own field surveys. We thus gathered a total of 369 points  for S. cordifolia and 224 points  for V. argenteria.We collected all occurrence data from the SILENE database (http://www.worldclim.org). We used data from the Community Climate System Model (CCSM), the Model for Interdisciplinary Research on Climate (MIROC) and from the Max Planck Institute for Meteorology (MPI) to hindcast LGM . These data were statistically downscaled from the original resolution to 30 arcsec with the Delta method [2 <|0.80|). To model species distributions, we used the following six variables: BIO3, isothermality; BIO4, temperature seasonality; BIO14, precipitation of driest month; BIO19, precipitation of coldest quarter; the presence/absence of suitable substrate. We removed duplicates using ENMTools [S. cordifolia and 223 presence records for V. argenteria were applied in SDM analysis.At the local scale, species distribution models provide excellent spatial projections by additionally using non-climatic predictors . For thia method . This doa method . We useda method  and thatENMTools . FinallyTo account for model-based uncertainties, we applied six SDM techniques: multivariate adaptive regression splines (MARS–), generaet al. [Analyses were implemented with BIOMOD2 v. 1.3.5 package  for R v.et al.  tips  and seven cpDNA regions in V. argenteria  were chosen , number of segregating sites (S) and nucleotide diversity (π) [T), population differentiation (GST) and an estimation of population subdivision for phylogenetically ordered alleles (NST) were calculated using the program PERMUT [sensu [ST to GST using 1000 permutations to obtain statistical significance with the program PERMUT. To evaluate the genetic structure, we conducted an analysis of molecular variance (AMOVA) in ARLEQUIN 3.1 [ST) and geographic pairwise population distance matrices was evaluated using a Mantel test [S. cordifolia and V. argenteria and on the Maritime and Ligurian Alps’ populations only in V. argenteria.Haplotype number (H), haplotype diversity (Hsity (π)  were calsity (π) . The totm PERMUT . We furtT [sensu ), comparQUIN 3.1 , partititel test  with 10,et al. [sensu [To determine the genetic relationship among populations, we followed the method implemented by Muñoz-Pajares  in the Set al. , indels . [sensu ).http://web.unife.it/progetti/genetica/Isabelle/samova.html) was used to identify groups of populations that are geographically homogeneous and maximally differentiated from each other without assuming any prior association between populations. The algorithm identifies the optimal number of groups of populations (k) by maximizing FCT  and minimizing FSC (genetic differentiation among populations within groups). SAMOVA was run for 10,000 iterations from each of 100 random initial conditions, and testing the predefined number of groups (k) from 2 to 10.Spatial analysis of molecular variance et al. [S. cordifolia while in V. argenteria it predicted a range wider than present in Corsica and narrower in the Maritime and Ligurian Alps. Despite this variation, the ensemble maps of all climates and algorithms suggested the presence of suitable areas in the current distributional range  respectively. In all, there were 13 variable sites among the sampled individuals of S. cordifolia and 65 in V. argenteria  Ma. The first  is mainly present in south-eastern populations (H01-H04) but also in some north-western populations (H05 and H11) while the second lineage  is mainly present in north-western populations  but also in some south-eastern populations (H08). Similarly, V. argenteria differentiated into two main lineages at 0.37 (0.12–0.79) Ma. The first lineage (H01 and H02) is exclusive of the north-western populations while the second lineage (H03-H16) is exclusive of the south-eastern and Corsican populations. However, the node age estimates should be interpreted with caution given the width of the 95% confidence intervals for each node . The populations showing the higher values of haplotype diversity were located in the central-northern part of distribution range. The total gene diversity was high  while the within-population diversity was low . The differentiation among populations based on cpDNA variation  indicates a moderate degree of population genetic structure within S. cordifolia. Allelic differentiation  is greater than but not significantly different from GST, indicating a weak genetic differentiation among populations. In V. argenteria 14 populations contained just one haplotype, five populations contained two haplotypes and the remnant two populations contained three and four haplotypes, respectively. Ten populations, mainly located in the southern part of Maritime Alps and in Corsica, showed private haplotype . The populations showing the higher values of haplotype diversity were located in the central-southern part of distribution range. The total gene diversity was high  while the within-population diversity was low . The differentiation among populations based on cpDNA variation (GST = 0.760 SE = 0.0785) indicates a large degree of population genetic structure within V. argenteria. Allelic differentiation (NST = 0.921 SE = 0.0486) is greater than and significantly different from GST, indicating a strong genetic differentiation among populations. AMOVA  of the chloroplast variation was partitioned among the population groups identified by SAMOVA. In contrast, the component of among-populations variation within groups was the lowest . The proportion of variation residing within populations  was consistent with the relatively low value of within-population diversity. Mantel test revealed a significant isolation-by-distance pattern in both species .In s. AMOVA  showed tS. cordifolia  in S. cordifolia and V. argenteria, probably survived the LGM in the sites where they were already present  and V. argenteria . We thus suggest that these two species illustrate the persistence of an ancient genetic structure through several Pleistocene climatic cycles. A similar time frame has been previously suggested for other animal and plant species from other biogeographical regions [The palaeo-distribution models inferred in this work together with the low and patchy ice sheet coverage of LGM in the Maritime and Ligurian Alps , 61 suggal sensu ). The we [et al.  showed tthe Alps , 4. In lanalyses  suggest  regions , 64.P. allionii where the separation into two groups dates back to the Middle Pleistocene [S. florulenta the differentiation of two ancestral gene pools seems to have been influenced by range contractions that were more recent than the glacial oscillations [S. florulenta compared to those of our study species agrees with the observation that, although recurrent patterns exist, some species may exhibit distinct patterns reflecting the unique, rather than the shared, aspects of species’ histories [Our results are also congruent with the palaeo-climatic reconstructions. In fact, the most extensive glaciation in Mediterranean mountains occurred during the Middle Pleistocene 0.780–0.120 Ma), in particular a major phase probably occurred during Mindel glaciation . Moistocene . In cont Ma, in pllations . Neverthistories , 72.S. cordifolia and V. argenteria point out the importance of not just the LGM but also previous glacial cycles in shaping the contemporary genetic structure of plant species in the Maritime and Ligurian Alps. The results thus corroborate the notes inferring the necessity to go beyond interpretations that relate only to the role of a small number of major historical events, such as the LGM and the Messinian Salinity Crisis [In general, our results for y Crisis .In general, current patterns of genetic variation are explained by contraction/expansion model in association with climatic oscillations. In this model refuge populations are associated with multiple genetic lineages and higher genetic diversity compared to more recently established populations . Due to S. cordifolia  and V. argenteria  are similar and the total gene diversity is higher than the mean value  S.H. Fu: HT = 0.981, [Arenaria provincialis Chater & Halliday: Hd = 0.94, [V. argenteria than in S. cordifolia . In addition, the high proportion of variation residing among the population groups identified by SAMOVA indicates that past climatic oscillations would have stimulated a stronger intraspecific diversification and population genetic differentiation in V. argenteria. According to this result, the higher within-population diversity detected in S. cordifolia may be due to its larger altitudinal range. This may have facilitated short-distance altitudinal migrations likely decreasing the impact of founder effects and the genetic signature of glaciations. A similar pattern of short-distance altitudinal shift and recurrent re-colonizations of neighbouring populations was reported in Armeria genus growing at high altitude [S. cordifolia and in southern populations for V. argenteria, and with the stronger effect of glaciation on the latest. V. argenteria growing only in the alpine belt probably survived glaciation in a southern peripheral refugium while S. cordifolia may have survived to last glaciation in several refugia at lower altitudes, showing so its higher diversity in the contact zone.The total gene diversity and haplotype diversity  detected= 0.670; ) detecte [et al. . Compara= 0.852, ; Rhodiol= 0.981, ; 2010; A = 0.94, ). Althourdifolia , resultibird see  below. Haltitude . This isV. argenteria may have originated by a rare long-distance dispersal of seed by birds rather than by vicariance due to Corsica-Sardinia microplate disjunction (15 Ma). In fact, seeds of violets have been shown to be capable of bird-mediated endozoochorous dispersal [V. argenteria .The recent origin of haplotypes detected in Corsica suggests that the disjoint Corsican populations of ispersal . Moreoveispersal . This raPrimula spp. using both SDM and phylogeographical approaches [The complex phylogeographical pattern observed in the studied species would indicates that, even if some species-specific differences are detected, both population and genotype extinction was minimal during the LGM, probably due to the low impact of glaciations and to topographic complexity in this area . This reproaches ; howeverproaches . These fproaches , 8 ratheproaches , 58, wheS1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S1 Fig(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.


Amorphophallus paeoniifolius (Dennst.) Nicolson) are important foods in the local diet in many Asian regions. The crop has high productivity and wide agroecological adaptation and exhibits suitability for the agroforestry system. Although the plant is assumed to reproduce via panmixia, a comprehensive study on the genetic background across regions to enhance wider consumer palatability is still lacking. Here, ten informative microsatellites were analyzed in 29 populations across regions in India, Indonesia and Thailand to understand the genetic diversity, population structure and distribution to improve breeding and conservation programs. The genetic diversity was high among and within regions. Some populations exhibited excess heterozygosity and bottlenecking. Pairwise FST indicated very high genetic differentiation across regions (FST = 0.274), and the Asian population was unlikely to be panmictic. Phylogenetic tree construction grouped the populations according to country of origin with the exception of the Medan population from Indonesia. The current gene flow was apparent within the regions but was restricted among the regions. The present study revealed that Indonesia and Thailand populations could be alternative centers of the gene pool, together with India. Consequently, regional action should be incorporated in genetic conservation and breeding efforts to develop new varieties with global acceptance.The corms and leaves of elephant foot yams ( Amorphophallus paeoniifolius (Dennst.) Nicolson synonym A. campanulatus (Roxb.) Blume) is a perennial herbaceous diploid Araceae  that is found across Australasian and African countries [Elephant foot yam  ; thus, mA. paeoniifolius has two morphotypes—rough and smooth types—of petioles called var. sylvestris and var. hortensis, respectively [ectively , with nuectively . The rouectively , 24. Howectively –27. TherA. paeoniifolius originated in India and was distributed by humans to other regions [A. paeoniifolius, which exhibits a short life cycle and adapts to humid tropical areas in Asia, is essential for better conservation genetic and breeding for global palatability acceptance strategies.The plant is assumed to be panmictic . However regions –31. Loca regions , 32–36; Leaf samples were obtained using a method that was nondestructive to the mother plant. Sterile field tools were used to ensure that no disease transmission occurred among the plants during sampling.All the dried leaf samples were collected by authorized persons in the country of origin—i.e., Kasetsart University and Royal Forest Department, Central Tuber Crops Research Institute Kerala, and Bogor Agricultural University and Indonesian Institute of Sciences for sampling in populations from Thailand, India and Indonesia, respectively. The collection procedures for each country were performed in compliance with the national regulation. In Thailand, the collection procedures followed “Act on Wildlife Reservation and Protection B.E. 2535 (1992)”, “Act on Plant Varieties Protection B.E. 2542 (1999)”, and “Act on Protection and Promotion of Traditional Thai Medicinal Intelligence B.E. 2542 (1999)”. In India, these procedures followed “Act on Wild Life (Protection) Amendment 39 (2006)”, and in Indonesia, these procedures followed “Act on Conservation of Living Resources and Their Ecosystems 5 (1990)” and “Act on United Nation Convention on Biological Diversity 5 (1994)”.We declare that permissions to enter and collect samples from private lands, including farmer properties, were granted by the lands owner. The individuals who participated in this manuscript have agreed and provided written informed consent to publish these case details.During the rainy seasons (August to December) from 2003–2010, leaflets were collected from semi-wild and wild populations in India, Indonesia and Thailand . We consElephant foot yam was identified based on a common description , 30. It The specimens of Indian samples are stored at the Central Tuber Crops Research Institute in Kerala, and Thai samples are maintained by Kasetsart University in Bangkok. Living specimens from the MED, KUN, YOGs and LOMBs populations are maintained at Bogor Agriculture University, Bogor-Indonesia, and the specimens from the BALs and LOMBs populations are maintained at Bali Botanical Garden, Bali-Indonesia.http://dx.doi.org/10.17504/protocols.io.ht3b6qn. DNA was extracted using the modified CTAB method according to the protocol described by Lian et al. [Molecular analysis including DNA extraction was carried out at the Laboratory of Forest Ecology, University of Tokyo, Japan, from 2010 to 2012, as listed step-by-step at n et al. . DNA fron et al.  were evam reverse primer tailed with U-19 , 0.5 μM U-19 primer labeled with Texas Red, 0.2 mM each dNTP, 1× PCR buffer , 2.5 mM MgCl2, and 0.5 U of AmpliTaq Gold DNA polymerase (Applied Biosystems). PCR  was performed using hot start as follows: one cycle of 9 min at 94°C, 30 s at the locus-specific annealing temperature (Ta) and 1 min at 72°C; 38 cycles of 30 s at 94°C, 30 s at the locus-specific Ta and 1 min at 72°C; one cycle of 30 s at 94°C, 30 s at the locus-specific Ta and 5 min extension at 72°C; and ending at 4°C. We extended initial denaturation in PCR step to improve bands clarity.PCR was carried out in a 5-μL tube, and a 0.5-μL aliquot of extract was used in each PCR amplification to approximately contain 5–20 ng of DNA. All SSR markers and DNAs were amplified with a PCR reagent mix of 0.5 μM forward primer, 0.1 μNext, 1.5 μL of the PCR product was mixed with 3.5 μL of loading dye, denatured using the Thermal cycle TAKARA for five minutes at 95°C, and then placed on ice immediately for five minutes prior to loading. Two-microliter aliquots were then loaded onto a 6% denaturing polyacrylamide gel and run using the SQ-5500 sequencer . The band patterns were analyzed with FRAGYLS ver. 2  and verified. Two bands were considered different alleles if the difference was two or larger than two base pairs considering all primers used were dinucleotides. In rare case, bands of different alleles were identified as homo alleles by FRAGYLS software due to the imperfect gel separation of a particular individual. In such cases, the bands needed adjustment in the FRAGYLS software. We adjusted the band size manually considering the band quality and identified the particular alleles as homo or hetero to avoid the bias estimate of FRAGYLS software.SIB<0.001) is the likelihood that the genotype of one individual will have the same ramet as that of a second individual; the ramet from one population was excluded. Thus, plants with the same SSR profile were considered one individual.Multilocus genotypes were identified using CERVUS 3.0 –41. The Na) and the observed (HO) and expected heterozygosity (HE) were calculated. The allelic diversity, frequency of null alleles and Hardy-Weinberg equilibrium (HWE) tests were estimated using CERVUS 3.0 and GENALEX softwares [FST (fixation index) and FIS (inbreeding coefficient) for each allele and subpopulation HE were estimated using GENALEX [FST was estimated using the program FSTAT 2.9.3 [The number of alleles  was estimated from the FST estimates using 9,999 permutations in GENALEX [FST/(1 − FST) [FST was classified as low (<0.05), moderate (0.05–0.15), high (0.15–0.25) and very high (>0.25) genetic differentiation [FST value ‘0’ indicates no population structuring or panmixia, while ‘1’ indicates the existence of perfect barriers of gene flow. Inbreeding was concluded in a particular population based on FIS estimate [AMOVA was conducted to examine genetic variation among regions, among populations, and among individuals. Genotypic differentiation was evaluated for each population by calculating the ockerham . The lik GENALEX . Genetic1 − FST) . Isolati1 − FST) . FST wasntiation . The FSTestimate .K, was set from 1 to 15, and the model was run for 10 independent simulations for each K. True K was selected according to the assignment of Evanno et al. [Population structure was examined using STRUCTURE ver 2.3.4 , followeo et al. .Na ranged from 10 to 61 (average 26.7), and 267 alleles were generated from 10 loci (HO>0.600), except for Ampa10 and Ampa15. Locus Ampa15 had the lowest HO (0.288) and HE (0.351). Six of ten loci expressed excess heterozygosity. The average FIS, FIT and FST for each locus were -0.032, 0.249, and 0.279, respectively. Most loci generated high to very high FST values (0.201 to 0.476), except for Ampa17 (FST = 0.191). All loci were in HWE (P<0.0000), demonstrating the suitability for population study. The frequency of null alleles from all loci ranged from 0.039 to 0.337. The loci Ampa10 and Ampa15 generated high null allele frequencies—i.e., 0.275 and 0.337, respectively. The LDE test for each locus pair across all populations was insignificant (P<0.0000)—except for the locus pairs Ampa04-Ampa07, Ampa07-Ampa15, Ampa07-Ampa19, Ampa15-Ampa16, and Ampa10-Ampa15, which exhibited low linkage equilibrium.All loci produced highly polymorphic alleles across populations, and the polymorphic information content ranged from 0.620 (Ampa19) to 0.937 (Ampa06), with an average of 0.803. The  10 loci . All locFrom 1,046 total accessions, 200 individuals had the same multilocus genotypes and were treated as ramet. Ramet existed in 11 populations—i.e., KUN, YOG1, YOG2, KOL1, KOL2, KOL3, KOL4, PAT1, PAT2, PAT3 and PAT4 . All locThe overall genetic diversity was high across regions as confirmed by morphological variation of the leaf and corm . The perNa in each population ranged from 3 to 11 , and the number of effective alleles ranged from 1.98 to 5.73  (I) within a population ranged from low (0.722) to moderate (1.724). The average HO and HE were 0.623 and 0.596, respectively. Twelve of 29 populations expressed excess heterozygosity—i.e., three from Indonesia  and nine from India . Consequently, according to Allendorf [The  allele) . The divllendorf , these tllendorf  showed nllendorf .FST) across regions was 0.274, which is classified as very high according to Hartl and Clark [FIS value within a population was low  to very high  (FST among populations ranged from low (FST<0.000) to very high (FST >0.450) differentiation  and Sumatera (MED) populations. The FST of Thai populations was low to high. Surprisingly, the RAY1 population in east Thailand had a similar population structure to that of the MAE3 population in north Thailand. Indian, Indonesian and Thai populations clustered together in 90% of the trees, and the Indian and Thai populations further clustered in 87% of the dendrogram (The genetic differentiation (nd Clark . The FIS= 0.839) . The paintiation  but was to 0.391 . The FSTndrogram . The IndPhylogenetic analysis grouped the populations into their respective regions ; the booThe present study shows that genetic variation in elephant foot yams among different regions was evident . The varThe utilization of elephant foot yams in Indonesian and Thailand has declined due to the increasing popularity of rice. In eastern Thailand, the plant is considered a weed. The decreased palatability of local peoples has led to reduced areas for elephant foot yam cultivation and conversely increased areas for semi-wild populations. In MAEs and RAYs of Thailand, some populations have been conserved due to underutilization, resulting in larger plant sizes . A singlIn a recent case in Indonesia, especially for LOMBs, intense intercropping programs in conservation forests using cash crops such as maize and upland rice threatened the habitat of the wild elephant foot yam population. The remaining populations were likely to have developed from the survivor after escaping from intense soil plowing. As a result, wild populations were mostly clumped along the forest edge, as well as on abandoned land, riverbanks or the edges of conservation forests .HO . Spongy berries might enable the seeds to float and maintain their viability. The plant produces polyembryony seeds at a rate of up to 0.96%, and optimum germination is obtained at 6 weeks after harvest . Althougm) across regions was 1.126.The Mantel test showed no isolation by distance, indicating that the present distribution might reflect the gene flow. High genetic differentiation among regions but low genetic differentiation within regions indicated that gene flow was restricted among regions. The average migration rate  to harvest teak timber that might include the elephant foot yams. Second, there is a high number of private alleles in the MED population that are shared with the Java (YOGs and KUN) and eastern Thai (RAYs) populations but a low number that is shared with Indian populations. The lack of influence of Indian alleles was demonstrated by the Ampa17 locus in Indonesian populations, indicating the uniqueness of the MED and LOMBs populations. The microsatellite profiles also indicated that the populations of KUN, YOGs, MED, LOMBs and RAYs share the same ancestor. Geographically, MED and RAYs were separated by the Malacca Strait, Malaysian Peninsula and Thai Peninsula  by a large genetic distance . Accordieninsula . ManeenoThe ancestry model did not support the panmixia population of elephant foot yams . The widThe BALs clustered in one group with all Indian populations, and all Thailand populations clustered with the MED populations . ConsequNot surprisingly, Indonesian populations clustered with Indian populations, indicating the intimacy the cultures shared. Human migration from the Indian subcontinent with more agricultural vision to southern Asia has been studied –62. It im within the Indian population was Nm = 4.369, but Nm = 1.789 and Nm = 0.654 within the Thailand and Indonesia populations, respectively. A tendency for elephant foot yam to be an underutilized crop in Indonesia and Thailand might be the present genetic barrier to its spread over the population within the particular region.There was a close genetic relationship among populations within regions, indicating intense exchange within regions. The mainland type of India and Thailand supported a high gene flow, contrary to that of archipelagic Indonesia. Southern Indian populations (KOLs and PATs) were likely descendants from northern territories . It has FST values (FST = 0.152–0.220)  . Similar2–0.220) —converseAmorphophallus has been elucidated [In a simulation at a farm of Bogor Agriculture University, a founder population was established within four years supported by the effective propagation of cormlets and seeds. The successful transmigration program from Java and Bali to the outer islands from 1904 to 1980s –65 mightBali populations (BALs) were important in Indonesia because they were linked tightly to the WEST population of India; similarly, the MED population was linked to the RAYs populations of Thailand. The LOMB populations, as neighbors of the BALs, genetically separated into a different sub group, but both populations shared a similar ancestor to KUN in west Java. Simultaneous reintroduction might exist in the Lombok, Bali and Rayong populations. Therefore, the effect of gene flow enables the maintenance and recovery of allelic richness .FST values (0.215–0.375) of MED to the other Indonesian populations Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 TableFST values for microsatellite loci are given below the diagonal line, and those for genetic distance are given above the diagonal line.(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.


Capra aegagrus. Furthermore, most comparisons of pairwise population FST values within and between these five Omani goat breeds as well as between Omani goats and nine populations from nearby countries were not significant. These results suggest strong gene flow among goat populations caused by the extensive transport of goats and the frequent movements of human populations in ancient Arabia. The findings improve our understanding of the migration routes of modern goats from their region of domestication into southeastern Arabia and thereby shed light on human migratory and commercial networks during historical times.The Sultanate of Oman has a complex mosaic of livestock species and production systems, but the genetic diversity, demographic history or origins of these Omani animals has not been expensively studied. Goats might constitute one of the most abundant and important domestic livestock species since the Neolithic transition. Here, we examined the genetic diversity, origin, population structure and demographic history of Omani goats. Specifically, we analyzed a 525-bp fragment of the first hypervariable region of the mitochondrial DNA (mtDNA) control region from 69 Omani individuals and compared this fragment with 17 mtDNA sequences from Somalia and Yemen as well as 18 wild goat species and 1,198 previously published goat sequences from neighboring countries. The studied goat breeds show substantial diversity. The haplotype and nucleotide diversities of Omani goats were found equal to 0.983 ± 0.006 and 0.0284 ± 0.014, respectively. The phylogenetic analyses allowed us to classify Omani goats into three mtDNA haplogroups : haplogroup A was found to be predominant and widely distributed and accounted for 80% of all samples, and haplogroups B and G exhibited low frequencies. Phylogenetic comparisons with wild goats revealed that five of the native Omani goat populations originate from  Capra hircus) are among the most important farm animals in many parts of the world, particularly Africa and Asia. Goats were thought to have been domesticated in the ninth and eighth millennia BC during the Pre-Pottery Neolithic B (PPNB) period, specifically between 8700 and 6800 cal BC in the Zagros Mountains, which forms part of modern Iran [Domesticated goats  [The history of native goats in Oman is long and complex and remains a subject of dispute. Nonetheless, evidence of the ancient presence of goats based on ancient rock engravings and paintings of domesticated goats, likely from the fifth and fourth millennia BC , can be found in many caves and rocks throughout Oman . Accordiegagrus) , and theMitochondrial genome (mtDNA) analysis is a critical tool in the fields of evolutionary and population genetics, including molecular ecology. Indeed, the mtDNA diversity has been proven to be particularly useful in assessing the origin, phylogeny, maternal lineage and population structure of many livestock species throughout the world –14. PrevCapra, the bezoar (C. aegagrus), markhor  and ibex (C. ibex), are closely related to the domestic goat (C. hircus), and it has been suggested that these species contributed to the gene pool of domestic goats [C. aegagrus is the wild ancestor of domestic goats, and this finding has been confirmed by the presence of all “domestic” haplogroups in the current C. aegagrus populations [Three wild species of the genus ic goats –23, possic goats ,23. It iulations ,23.Capra biodiversity in Oman, the hypothesis that C. aegagrus is the wild progenitor of the Omani domestic goat was evaluated.Due to the lack of an extensive evaluation of the genetic diversity within Omani goat breeds, we analyzed four economically important Omani goat breeds and one additional strain. All of the studied strains are phenotypically distinct from each other and have very different geographic ranges. The genetic diversity and distribution of mitochondrial haplogroups among these breeds were examined, and the level of maternal introgression of goat populations from different putative domestication centers was also assessed. Finally, to support our genetic data and initiate a detailed documentation of Animals from five Omani provinces were sampled. With the consent of the flock owners (villagers), tissue samples were collected from native goats by veterinarians or under veterinary supervision during routine veterinary care. We obtained permission to use the facilities of the Director General of Animal Wealth of the Ministry of Agriculture and Fisheries Wealth in Oman.Sampling was conducted in four different geographical regions of Oman , which are the locations where breeding of the main native Omani goat breeds, Jabal Akhdar (n = 20), Batinah (n = 12), Dhofar (n = 12) and Ash Sharqiyah (n = 13), is concentrated. The Musandam goat strain (n = 12) from northern Oman (Musandam peninsula) was also examined. Brief descriptions of the Omani goat populations are provided in 5′-CGTGTATGCAAGTACATTAC-3′) and CAP-R (5′-CTGATTAGTCATTAGTCCATC-3′). Polymerase chain reaction (PCR) amplification was performed in a final volume of 20 μL, which included 0.8 μM of each primer, 2.5 mM MgCl2 (50 mM), 0.3 mM dNTPs (10 mM each), 0.25 U of Platinum Taq Polymerase , 1X PCR buffer, 0.3 μg/μL bovine serum albumin  and variable amounts of genomic DNA. All reactions were performed with negative controls. The PCR conditions for amplification consisted of a pre-denaturation step of 94°C for 10 min followed by 40 cycles of 94°C for 30 s, 61°C for 30 s and 72°C for 30 s and a final extension step at 72°C for 5 min. The PCR products were examined on 1% agarose gels and sequenced with an ABI 3130xL capillary sequencer using a Dye Terminator Cycle Sequencing Reaction Kit .Genomic DNA from skin tissue was extracted using DNeasy Blood and Tissue Kit  according to the manufacturer’s recommended protocols. We amplified a 598-bp fragment of the mitochondrial hypervariable region 1 (HV1) between positions 15,653 and 16,250 in the reference goat mitochondrial genome AF533441  using thC. hircus mtDNA reference sequence. One fragment from the Jabal Akhdar goat was 480-bp, and the 45 missing nucleotides were treated as missing data. The sequences were deposited at GenBank under the accession numbers KY399058-KY399142 and KY449044.Both forward and reverse DNA sequences of the 69 Omani goats were examined, edited, aligned and trimmed manually to produce a single concatenated file with a consensus region of approximately 598-bp. The concatenated sequences were aligned against the reference sequence AF533441  and furtTo provide more complete information regarding the origin of Omani goats, new mtDNA sequences from Somalia  and Yemen  were included, and mtDNA sequences from wild and domesticated goats were also downloaded from GenBank  Tables. k). The differentiation within Omani goat breeds was assessed based on pairwise differences (FST) and through analysis of molecular variance (AMOVA) using Arlequin ver. 3.5.1.2 [For each goat breed, Arlequin ver. 3.5.1.2  was used 3.5.1.2  with 1,0http://popart.otago.ac.nz/index.shtml) with the default settings.To identify possible haplogroups of each individual Omani goat according to reference sequences , phylogeFST values among the Omani goat populations and nine other populations were calculated using Arlequin ver. 3.5.1.2 [FST) and the geographic distance (km) based on mtDNA data from the ten populations was evaluated through the Mantel test implemented in GenAlEx ver. 6.501 [https://www.freemaptools.com/how-far-is-it-between.htm). FST values were set to zero.Additionally, population pairwise  3.5.1.2 . The star. 6.501  using 9,Fs [0 and θ1 (before and after population growth), and τ . In addition, mismatch frequency graphs were generated to evaluate possible historical events of population expansion or a stationary population history [t) of Omani goats and each haplogroup were roughly estimated using parameters of demographic expansion with the equation t = τ/2u. In this equation, τ is the empirical peak of the mismatch distribution, and u is the mutation rate of 6.09X10−4, which was estimated based on the dataset published by Colli et al. [u = mtμ, where mt is the length of the sequence and μ is the substitution rate, μ = 3.95X10−8. The τ values and their confidence intervals were obtained with Arlequin ver. 3.5.1.2 using 1,000 bootstrap replications [Signs of historical demographic expansions were also explored with Arlequin ver. 3.5.1.2  using twFs , to asseFs , θ0 and  history . Finallyi et al.  with theications .We examined hypervariable region 1 (HV1) fragments of the mitochondrial DNA control region in 69 goats belonging to five different goat populations and representing five different geographic regions of Oman. An analysis of the combined dataset of sequences of Omani goats revealed high polymorphism, with the presence of 45 different maternal haplotypes and 94 polymorphic sites in the 525-bp aligned fragment. The polymorphic sites include 87 transitions, two transversions and five indels, with a ratio of transition to transversion of 43.5. The average base composition is as follows: A, 30.19%; T, 30.97%; G, 16.18%; and C, 22.66%. Thus, the percentage of A+T nucleotide pairs is higher than that of C+G pairs in this region . Haplotype H38 was found to exhibit the highest frequency; specifically, this haplotype was observed in five different individuals from two distinct populations: Musandam and Ash Sharqiyah.k) for DHR and JKH goats was higher than those for all other breeds (k > 16), and the number of haplotypes (Hn), number of polymorphic sites (S) and mean number of pairwise differences (k) for the MSN strain  were lower than those for the other Omani goat breeds.Genetic diversity indices based on the mtDNA HV1 region sequences showed substantial variation among Omani breeds . An analThe phylogenetic relationships among individuals were investigated using the NJ tree, and the individuals were classified into haplogroups according to a previous classification system . The NJ C. aegagrus . The pairwise FST comparisons revealed significantly greater (P<0.05) genetic differentiation between the MSN goat strain and the other breeds, with the exception of the SHR goat population . A hierarchical AMOVA revealed very low variation among the studied populations within the geographical area of Oman. The AMOVA results indicated that the within-population variation contributes 93.98% of the total variation, whereas the among-population variation contributes only 6.02%of the total variation  different from all other populations, with the exception of some adjacent or nearby populations  to 0.134 . Additionally, a significant correlation between FST values and geographic distances was detected, as indicated by the Mantel test results  (P<0.05) and a low negative Tajima’s D value (-0.763) that was not statistically significant (P>0.05) were calculated for Omani goats (The mismatch distribution and Fu’s n growth . A highlni goats .P>0.05), indicating that the data showed a relatively good fit to the model of population expansion [0 and θ1, Omani goats expanded from a small to a very large population, with a 95% confidence interval (CI)  was 0.005. Both of these values were non-significant  . The misval (CI) . The resFs values and mismatch distribution for haplogroups A and G and observed a unimodal bell-shaped distribution (FS = -20.187), with high significance (P = 0.000), but not for haplogroup G  for each haplogroup, negative (-1.288) for haplogroup A and positive (0.118) for haplogroup G. Additionally, we observed low non-significant Rg and SSD values for both haplogroups  for haplogroups A and G were very small, indicating that the mtDNA variation within these two haplogroups originated from a very small doe population.To explore the demographic history of the Omani goat population in further detail, we estimated the Fu’s ribution , similar P>0.05, . The est95%: 2.459–23.525) for the Omani goat populations. The approximate time since expansion is therefore 4,119  years. With the exception of haplogroup B due to its single haplotype, we also obtained the time since expansion for each haplogroup in our datasets. The estimated expansion times for haplogroups A  and G  based on 95% confidence intervals are approximately 5,389  and 6,353  years ago, respectively.Finally, we estimated the time since the expansion of Omani goats as well as the minimum and maximum values for expansion times based on 95% confidence intervals. These expansion times, which are expressed in mutational units (τ), were estimated to be 5.016  observed in a sample of 69 animals. The genetic diversity parameters of Omani breeds were within the range of those observed for other goat populations from Africa  and AsiaA sequence analysis of Omani goat mtDNA revealed a comparative lack of genetic structure, supporting a geographic distribution that confirms the main trends observed in previous studies of mtDNA diversity in goats ,17. AMOVC. aegagrus than to other wild goats in the phylogenetic tree and thus possess ancient haplotypes. The most ancient rock art in Oman displays wild animals such as ibex, gazelle, ass, auroch and ostrich [Many studies have investigated the origin of modern domestic livestock, and evidence of high diversity of maternal lineages has been observed in many domesticated animals . The res ostrich ,8,43. Of ostrich ,45. AccoC. aegagrus populations in Iran. Although Oman is located on the other side of the Southern Zagros, Central Iranian Plateau and Sistan and Baluchestan Province of Iran, where C. aegagrus is widely distributed, some early domestic goats in Oman likely acquired mitochondrial genes through the fertilization of C. aegagrus in these regions.The results of our phylogenetic analysis in combination with 22 goat maternal haplogroup references from GenBank  revealedFST values, and the genetic distance typically increased in both value and significance with increasing geographic distance , myrrh, copper and animals of southern Arabia. To understand the genetic history of goats in Oman, a brief review of the history of the region, particularly in terms of cultural and population contacts with other peoples, is indispensable. Substantial evidence from Neolithic tools (pottery and ceramic) reveals a historical connection between the Oman Peninsula (Magan and Melukhah Empires) and Mesopotamia (Iraq) since the end of the last glaciation  [Thus, information on Arabian history can provide indirect clues regarding the genetic history of goats in the Arabian Peninsula. From a very early period, Arabs had extensive contact with their Near Eastern neighbors, Mesopotamia, the Levant, Egypt and the peoples of the Mediterranean, East African and Indian Subcontinent. These contacts were particularly associated with commerce in frankincense (ars ago) . Burial ars ago) . The copars ago) . Bronze ars ago) . In addiars ago) . Furtherars ago) –54.Thus, the apparent lack of significant population structuring among Omani goats and nearby populations can be attributed to ancient contact between Oman and Mesopotamia, southern Arabia and the Indus valley as well as eastern Africa. In addition, goat herds in Oman are reared under two traditional pastoral systems, specifically Badawi (nomadic) and Jabali or Shawawi, i.e., mountain goat herding (semi-nomadic), and the herding and movement characteristics are determined by the availability of food and the climatic conditions. Of course, this type of herding most likely resulted in an increase in apparent admixture with exotic blood. Nonetheless, humans prefer to keep goats during migratory movements because these animals can survive in the most adverse circumstances and supply a full range of useful products . MoreoveThe estimate of 4,119 years for the relative time since the expansion of the Omani goat shows that although the Zagros mountains, as the center of origin of the domestic goat, are located at the other side of the Arabian Gulf , extant Omani goats descend from a much more recent expansion event. In addition, we calculated approximate expansion dates of 5,389 years ago for haplogroup A and 6,353 years ago for haplogroup G, which are more recent than the estimates reported by Colli et al.   and signArchaeological results indicate that animal husbandry appeared in Oman at approximately 7,000–6,500 cal BC and that the Omani goat might have been domesticated during the Neolithic period, between 5,500 and 3,200 cal BC ,10. ThisC. aegagrus and belong to three mtDNA haplogroups . Pairwise FST comparisons revealed that populations from geographically proximal sites are more likely to undergo gene exchange. The inclusion of more samples of wild goat species or ancient goats in future studies will provide additional insights into the history and gene flow of goat populations in Oman.This study provides the first insights into the genetic diversity and evolutionary background of domestic goats in Oman and provides a basis for further studies on the temporal fluctuations of domestic goat populations. Our results indicate high diversity within the five examined Omani domestic goat populations. Phylogenetic analyses revealed that the five breeds descended from S1 File(DOCX)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S7 Table(DOCX)Click here for additional data file.


Aedes aegypti inhabits much of the tropical and subtropical world and is a primary vector of dengue, Zika, and chikungunya viruses. Breeding populations of A. aegypti were first reported in California (CA) in 2013. Initial genetic analyses using 12 microsatellites on collections from Northern CA in 2013 indicated the South Central US region as the likely source of the introduction. We expanded genetic analyses of CA A. aegypti by: (a) examining additional Northern CA samples and including samples from Southern CA, (b) including more southern US populations for comparison, and (c) genotyping a subset of samples at 15,698 SNPs. Major results are: (1) Northern and Southern CA populations are distinct. (2) Northern populations are more genetically diverse than Southern CA populations. (3) Northern and Southern CA groups were likely founded by two independent introductions which came from the South Central US and Southwest US/northern Mexico regions respectively. (4) Our genetic data suggest that the founding events giving rise to the Northern CA and Southern CA populations likely occurred before the populations were first recognized in 2013 and 2014, respectively. (5) A Northern CA population analyzed at multiple time-points (two years apart) is genetically stable, consistent with permanent in situ breeding. These results expand previous work on the origin of California A. aegypti with the novel finding that this species entered California on multiple occasions, likely some years before its initial detection. This work has implications for mosquito surveillance and vector control activities not only in California but also in other regions where the distribution of this invasive mosquito is expanding.The yellow fever mosquito  Aedes aegypti, also known as the yellow fever mosquito, are of growing concern in tropical and subtropical regions. Dengue and Zika incidences are increasing, and no vaccines are currently available. Here we investigate the origin of California A. aegypti and find that this mosquito likely entered California on multiple occasions, at least once from the South Central US region and once from the Southwest US/northern MX region. The evidence suggests that the first invasion event likely occurred some years before its initial detection in 2013, despite California’s extensive and active surveillance program, implying that this invasive mosquito can go undetected. Understanding the invasion dynamics, gene flow, and population structure of A. aegypti can improve the monitoring of mosquitoes and prevent outbreaks of vector-borne disease.Infectious diseases transmitted by  Aedes aegypti. The incidence of dengue has increased 30-fold in the past 50 years [Dengue, Zika, and chikungunya are severe mosquito-borne infectious diseases that are of growing concern in tropical and sub-tropical regions, and yellow fever is re-emerging in many regions . The vir50 years  with an 50 years . Followi50 years . With noA. aegypti is a zoophilic sub-species called formosus [A. aegypti is a domestic mosquito that primarily bites humans, lays eggs in manmade water-containers, and can disperse over long distances using human transportation systems [A. aegypti likely migrated to the Americas in European slave ships in the fifteenth through seventeenth centuries [A. aegypti [A. aegypti are distributed throughout most of the southern United States, especially below the 33-degree north latitude line [A. aegypti is not common in the United States, but there were locally transmitted cases of Zika in Miami-Dade County, Florida and Cameron County, Texas in 2016 [The ancestor of the domestic form of formosus . It is lformosus . Outside systems . As such systems , 8. A. aenturies , 9, and  aegypti . The firude line . Populatude line , 11. Loc in 2016 . There h in 2016 , 14.A. aegypti and in implementing vector control. Validated genetic markers can be used to determine the source of new invasions [A. aegypti is due to new introductions each year or overwintering. Mosquitoes are more likely to be present and abundant in an area where they can survive the winter, and overwintering is especially concerning in cases where the vectored viruses can also persist through the winter, either in inseminated females or through vertical transmission from mother to eggs.  A A. aegypti were only occasionally detected near airports and other ports of entry [A. aegypti had been found in 96 cities and census designated places from 12 different counties in CA [California (CA) has an extensive mosquito-monitoring program, and historically of entry . Breedinof entry . Throughes in CA , 22.A. aegypti populations in CA originated from a single or from multiple introductions, 2) to characterize the genetic structure of CA A. aegypti populations, and 3) to determine if the genetic data are consistent with overwintering by A. aegypti, especially in the northern parts of CA. We found clear genetic differentiation between the Northern and Southern CA populations and found support for the hypothesis that at least two introductions of A. aegypti into CA are responsible for the current populations within the state.In this analysis, we have built upon our previous work by adding 13 new samples from CA, including 8 from southern CA . The priA. aegypti mosquitoes from 12 sites in CA and 16 sites from across the southern United States and northern Mexico were considered in analyses  [A total of 34 samples of analyses . The meaanalyses . All mostainers) , the useFor convenience, we have grouped the samples into five broad geographic regions referred to throughout this paper as Southern California, Northern California, Southwest US, South Central US, and Southeast US. The regions are described in A. aegypti populations around the world [Whole genomic DNA was extracted from 286 whole adult mosquitoes from ten CA sites collected in 2015 using the Qiagen DNeasy Blood and Tissue kit according to manufacturer instructions, including the optional RNAse A step. All individuals were genotyped at 12 highly variable microsatellites, as in Brown et al. . These lA total of 107 individuals from ten CA samples  and expected heterozygosity (HE) were calculated using the software GenAlEx 6.5 [Observed heterozygosity , Principle Component Analyses (PCA), and plots illustrating F. 2.0.2. , availab. 2.0.2. . DAPC op. 2.0b27 . We alsoWhile the SNP chip has 50,000 probes, only 27,674 passed the initial stringent testing requiring unambiguous genotyping, biallelic and polymorphic markers, and Mendelian inheritance . FurtherFor SNP data, we ran four runs with the Bayesian program fastSTRUCTURE to estimate the number of genetic clusters and calculate ancestry fractions for each individual given K numbers of genetic clusters . The resWe inferred demographic history and estimated relevant parameters using microsatellite data and Approximate Bayesian Computation methods  as impleFor the DIYABC analyses, we first simulated 1,000,000 datasets for each scenario, resulting in 4,000,000 total simulated datasets. To determine which scenario was most supported by the data, we evaluated the relative posterior probability using a logistic regression on the 4,000 (1%) simulated datasets closest to the observed dataset. To estimate demographic parameters, we chose scenario 1 and estimated posterior distributions of parameters taking the 1,000 (1%) closest simulated datasets, after applying a logit transformation of parameter values. To evaluate confidence in the posterior probability of scenarios (in the form of Type I and Type II errors), we used a logistic regression on 250 test datasets simulated for each scenario with the same values that produced the original dataset. Priors and parameters are provided in For microsatellites, 17 out of 2,241 (0.76%) loci pairs were found to be in linkage disequilibrium, and 3 out of 360 (0.83%) locus-population pairs were not in agreement with Hardy Weinberg equilibrium after Bonferroni correction for multiple comparisons. This is consistent with previous work indicating that these 12 microsatellites are single-copy and can be treated as independent loci for population genetic analyses , 16.Genetic diversity was significantly lower within CA populations than among other North American populations . The meaST values ranged from 0.0010 to 0.42 . In contrast, Exeter and the Southern California sites had significantly higher mean FST values when paired with themselves (0.26±0.11 SD) or with all the CA populations (0.26±0.10) . ST values , and the IBD test on just the populations from CA was not significant .Among California populations, pairwise F to 0.42 . ExcludiST values between Madera 2015 and the two Madera 2013 populations is lower (0.01 and 0.047) than between Madera 2015 and any of the sites in the Central South populations (range = 0.091–0.15). The FST between San Mateo 2014 and San Mateo 2015 is higher (0.16) than between San Mateo 2014 and some of the Central South populations, such as New Orleans (0.13).In regard to overwintering, the FBayesian clustering analysis for microsatellite data on all CA populations identified two primary clusters (K = 2), which divided the Northern California populations from the Southern California populations with the exception of Exeter and most of the Clovis individuals . At highA PCA analysis using microsatellites from California populations found that the first Principal Component accounted for 13.17% of the variation and the second accounted for 9.71%. Using the same data for a DAPC analysis, the “find.clusters” command in Adegenet found the data could best be described by 12 clusters . The firAnalysis of the SNP data largely reinforced the microsatellite results. Seven genetic clusters were identified by fastSTRUCTURE and six by Admixture’s CV Error method of K selection on the final dataset of 15,698 SNPs . San MatIncluding microsatellite data from all analyzed populations from this study , the BayThe Bayesian clustering method implemented by STRUCTURE showed Northern California clustering with the South Central and Southeast regions, and Southern California clustering with the Southwest region. Since Gloria-Soria et al. showed that Houston or New Orleans was the likely origin of the Northern Californian populations , we used95%: 0.983–0.996). Scenario 4, the neutral model in which the four populations diverge from the same ancestor simultaneously, had the next highest posterior probability (0.0079 CI95%: 0.0019–0.0138).Evaluation of the relative posterior probability of each of the four competing scenarios in The type I error rate was 0.14, and the type II error rates under the three other scenarios were 0.16, 0.11, and 0.064. The estimated time of divergence of the Central South from the Southwest populations was 4,200 generations (approximately 420 years), and the 95% credible interval was 1,730–5,900 generations assuming 10 generations/year. The estimated time of divergence of Northern California populations from South Central populations was 292 generations or approximately 29 years , and the estimated time of divergence of Southern California from the Southwest was 224 generations or approximately 22 years . Full details are provided in 95%: 0.9991–0.9999). The estimated time of divergence between Southern California and Southwest was approximately 35 years , and the estimated time of divergence between Northern California and the South Central/Southeast was approximately 8 years . Full details are provided in The results from the second analysis (in which no populations were excluded) were mostly similar including a high support for Scenario 1 , a more recent time of divergence (~8yrs) was estimated between Northern California and South Central/Southeast. This is more consistent with personal communications from CA vector control professionals who think it is unlikely the invasion could have occurred more than a year or two prior to initial detection.The DIYABC analysis using representative populations suggests that the Northern California lineage diverged from the South Central lineage 292 generations ago, estimated to be ~29 years, and that the Southern California lineage diverged from the Southwest/MX lineage ~22 years ago. These estimates have large credible intervals, so we cannot tell which invasion into California happened first. The lower bounds of the intervals containing 95% probability are both more than 3 years, so it seems likely the invasions occurred at least a year prior to the initial detection of A. aegypti population size.Invasion events are often accompanied by a bottleneck in population size and subsequent decrease in genetic diversity, especially allelic richness. Consistent with Gloria-Soria et al. , we founA. aegypti to be broken into almost entirely isolated small local populations given the evidence suggesting this mosquito avoids crossing major roads/highways [We observed significant population structure with genetic differentiation even among populations in close geographic proximity, particularly among Southern California populations. For example, Anaheim, Orange, Garden Grove, and Santa Ana are each less than 12km apart from the others, but they are genetically distinguishable . The denhighways . SimilarST values between Southern California sites may indicate limited gene flow among the populations, consistent with the relatively short active dispersal distance that has been found for A. aegypti [A. aegypti control in one locality may not be easily influenced by migration from neighboring localities. Further analysis taking into account both timing of invasion and connectivity through human transportation routes may help us understand the patterns we see in the structure of both Southern and Northern CA populations.The large pairwise F aegypti . The obsST values between Madera 2013 and 2015 were lower than any of the FST values between Madera and populations from South Central US, suggesting this is a stable population and not one recolonized each year. The genetic diversity also changed very little: for example, the allelic richness was 3.5 in 2013 and 3.6 in 2015. San Mateo 2013 and San Mateo 2014 did not follow these patterns, and the small sample size of San Mateo 2014 (N = 7) could be a factor. It is unlikely that this change in genetic diversity is due to recolonization of the area by another northern California population because the mosquitoes were collected from the same confined area in 2013 and 2014, and were not detected elsewhere in the county. In both cases the populations are always part of the same genetic cluster determined with Bayesian clustering , these populations did not show genetic differentiation, suggesting no population structure within a city.In two cases, we analyzed CA populations from the same location from two different years: Madera 2013 and 2015, and San Mateo 2013 and 2014. We found strong evidence for overwintering in Madera and mixed results for San Mateo. The Fing e.g. , consistulations . StrikinA. aegypti. We found the same genetic structure using both types of markers, which speaks to the robustness of our methods and results. Our results suggest the microsatellite markers, which are more cost-efficient, are sufficient for these types of analyses. However, we expect the SNP chip will continue to provide essential information in other situations, for example, at finer-scales, when fewer individuals are available, or when building phylogenies.Our paper is the first to combine SNP data and microsatellites to address the population structure and origins of the CA A. aegypti invaded CA multiple times, probably years before its first detection in 2013, has important implications for vector control. It implies CA and other regions with a temperate climate may be more vulnerable to invasion than previously thought. Additionally, we find that CA A. aegypti populations near one another are often genetically distinct. A challenge to providing effective vector control is the potential for reinvasion in targeted regions. At least in Southern CA it appears that there is little evidence for extensive migration and gene flow among populations. The disparate genetic backgrounds in these A. aegypti populations may represent populations capable of responding differently to control measures such as pesticides, or perhaps these populations may have different vector competence for infectious pathogens. CA has one of the most extensive mosquito-monitoring systems in the US, so the possibility that A. aegypti was in CA years before detection may mean mosquito invasions have occurred elsewhere in the US but escaped notice. Understanding and accounting for the invasion dynamics of A. aegypti will continue to be essential for detecting new invasions, monitoring vector presence, and preventing disease outbreaks in California and other regions.That S1 FigST value between the corresponding populations on the horizontal and vertical axes. The darker the color of the box, the higher the FST value is. The legend on the bottom shows how each color corresponds to FST values between 0.05 and 0.3.Each box represents the F(TIF)Click here for additional data file.S2 FigEach vertical bar represents an individual. The proportion of each color assigned to each individual represents the proportion of that individual’s ancestry attributable to each of K theoretical genetic clusters. Letters within the plot refer to city as in (TIF)Click here for additional data file.S3 FigEach vertical bar represents an individual. The proportion of each color assigned to each individual represents the proportion of that individual’s ancestry attributable to each of K theoretical genetic clusters. (A) K = 3. (B) K = 4.(TIF)Click here for additional data file.S4 FigA) This chart shows the composition of each of the 12 inferred genetic clusters; the larger the black box, the more individuals included. For example, inferred group 4 contains all the individuals from Mission Viejo and inferred group 10 contains a mixture of the individuals from the two San Diego populations. (See (TIF)Click here for additional data file.S5 Figa priori based on regional location and the first two principle components served as the axes.In this plot, populations were selected (TIF)Click here for additional data file.S6 FigThe fraction of each vertical bar assigned to each color represents the proportion of that individual’s ancestry attributable to each of 6 theoretical genetic clusters. Letters within the plot refer to city as in (TIF)Click here for additional data file.S1 FileSNP data from the CA populations indicated in (VCF)Click here for additional data file.S2 FileMicrosatellite data from all populations indicated in (XLSX)Click here for additional data file.S1 Tableo = observed heterozygosity; He = expected heterozygosity; AR = allelic richness estimated by rarefaction (n = 30 genes)H(DOCX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 TableRegional groups composed of individuals from representative populations from each region.(DOCX)Click here for additional data file.S4 TableRegional groups composed of individuals from all populations from each region.(DOCX)Click here for additional data file.


CSD), when individuals are homozygous for this locus. Diploid males are expected to be more frequent in genetically eroded populations (such as islands and captive populations), as genetic diversity at the csd locus should be low. However, only a few studies have focused on the relation between population size, genetic diversity, and the proportion of diploid males in the field. Here, we developed new microsatellite markers in order to assess and compare genetic diversity and diploid male proportion (DMP) in populations from three distinct habitat types – mainland, island, or captive –, in the parasitoid wasp Venturia canescens. Eroded genetic diversity and higher DMP were found in island and captive populations, and habitat type had large effect on genetic diversity. Therefore, DMP reflects the decreasing genetic diversity in small and isolated populations. Thus, Hymenopteran populations can be at high extinction risk due to habitat destruction or fragmentation.Sex determination is ruled by haplodiploidy in Hymenoptera, with haploid males arising from unfertilized eggs and diploid females from fertilized eggs. However, diploid males with null fitness are produced under complementary sex determination ( For this, we compared mainland, island, and captive populations, with the expectation of a lower genetic diversity and a higher proportion of diploid males in captive populations compared to insular populations and in insular populations compared to mainland populations.We developed this study with a threefold objective: (1) develop microsatellite markers in order to assess male ploidy and conduct population genetic studies on arrhenotokous V. canescens were collected during summer 2010 in two natural populations located in southern France near Nice and Valence  were hung in trees. Infested semolina is impregnated with host kairomones and is very attractive for V. canescens females , Gozo , Crete (Greece), Sicily , and Cyprus. Several sites per island were sampled. In 2013, the same protocol was followed to capture males on French islands (Porquerolles and Corsica), in Mallorca (Spain), Cyprus, and in Crete (Greece) , Solliès , and Vinyols and Vila‐Seca . In 2012, we searched e) Table . On eachE. kuehniella obtained by rearing 50 mg of E. kuehniella eggs (about 2000 eggs) provided by Biotop  in plastic boxes (8 × 12 × 25 cm) set with 250 g of wheat semolina. Each week, three boxes containing second to fifth instar host larvae were inoculated with 50 males and 50 females of V. canescens emerging from all available (about six) rearing boxes.In parallel, we collected males in three captive (laboratory mass‐reared) populations differing in their history and geographic origin Table : (1) a 2V. canescens recently collected from the Nice population and kept in the laboratory for a few generations. The obtained DNA solution was enriched in microsatellites and pyrosequenced by the company Genoscreen , following the protocol described in Malausa et al. . Six primer pairs designed by Mateo Leach et al. , DNA was extracted from a single 1.5‐mL tube containing a pool of 20 adult females of a et al. . Using ta et al. , primer a et al. , among wh et al.  were als® version 1.75 . Monomorphic markers were discarded, and the remaining markers were combined according to their size and fluorochrome in several multiplex PCRs that were tested on the same seven individuals and in the same PCR conditions as previously described. Finally, we selected 19 microsatellite loci amplified using two multiplex PCRs  were used in a monoplex PCR with the DNA samples and conditions previously described. Two microliters of PCR product was added to 8.75 μL of Hi‐Di formamide and 0.25 μL of GeneScan500 Liz size standard (Applied Biosystems). The mix was loaded on an ABI 3130XL genetic analyzer (Applied Biosystems), and alleles were scored using Gene MarkerWe used the genetic markers from the multiplex PCR I Table  to detecWe performed flow cytometry analyses as described in de Boer et al. . Only thTo be used in population genetic studies, each marker must have several detectable alleles and must not be linked with any other marker or locus under selection. We therefore measured genetic polymorphism, estimated frequencies of null alleles, and test for departures from Hardy–Weinberg (HW) equilibrium and linkage disequilibrium on the two mainland populations from Valence and Nice where enough females were captured in 2010 Table  was used, a mean number of alleles for each locus in each population, with populations weighted in inverse proportion to their sample sizes in order to give the same weight to all populations. As FSTAT is not able to handle haploid and diploid data in the same analysis, we merged the haploid data from pairs of males to create “false diploids” without changing allelic frequencies. We then analyzed all “diploids” in a single run.For all males captured, DNA was extracted, PCR were performed with multiplex I, and genotypes were analyzed as previously described. Only males with at least eight loci genotyped were used for the analysis. Coexistence of male haploidy and diploidy impedes the estimation of classical population genetic statistics such as observed and expected heterozygosity or Wright's F statistics. We therefore computed a value of allelic richness per locus and per population with FSTAT version 2.9.3.2 Goudet  and calcAllelic richness (All_rich) and number of private alleles  nested in the habitat type (Habit), that is, mainland, island, or captive  to assess the effect of population structure on the proportion of diploid males (DMP). Population structure was characterized by different nested explanatory variables:  d Cohen  with effP‐values were corrected for multiple testing via the false discovery rate (FDR) procedure  and in Valence . The number of alleles ranged from 2 to 14 . The markers had a maximum frequency of null alleles equal to 8.5%  and a null median frequency for both populations. No departure from the HW equilibrium was found in any of the populations (Table o) was similar in the two multiplex PCRs in both populations  and VC107/Vcan106 . However, when populations were analyzed separately, the pairs of loci were linked only in one population , we therefore decided to keep all loci. Therefore, the two multiplex PCR can be used for genetic studies with equivalent performance.For all the nineteen microsatellites developed, amplification was obtained for all the arrhenotokous P = 0.0023) to rely on microsatellites for ploidy assessment. This was confirmed by the congruence between flow cytometry and microsatellite genotyping results. Haploid and diploid males were easily discriminated by flow cytometry, with diploid males presenting a profile similar to that of diploid females  were successfully genotyped and used in the analysis.χ2 = 5.68, df = 2, P = 0.058), and allelic richness significantly differed between habitat types  and populations . Both measures shared the same trend suggesting that the diversity is the lowest in captive populations and the highest in mainland . The sampling year had no impact on the mean allelic richness for populations sampled over 2 years . Allelic richness of the captive population from Israel (CapIsr) appeared different from all the other populations except the captive populations from Nice and Valence . As the CapIsr population was highly differentiated from the other populations, it could potentially drive the significant trend observed. Indeed, when allelic richness was compared without CapIsr, the difference between populations disappeared , and the difference between habitat types became only marginally significant .The population structure was estimated through different parameters such as allelic richness (All_Rich) and the number of private alleles  from male genotyping data Table . The num= 0.02 ± 0.02 in CapVal to DMP = 0.16 ± 0.05 in CapIsr; Table χ2 = 0.760, df = 1, P = 0.383 and Mlc12–Mlc13: χ2 = 5.10−32, df = 1, P = 1). As expected, the DMP was affected by habitat type , but we still found a negative influence of allelic richness (nested within habitat types) on DMP , increased proportion of diploid males, decreased population growth rate, and, if dramatic enough, population extinction  is in the order of magnitude of estimations in other species of parasitoids with sl‐CSD: 10% in a native population of C. glomerata  was observed in the captive population from Israel, which is congruent with the lowest genetic diversity estimated. In other species, diploid male production was also found to be higher in isolated population compared to larger genetically diverse populations , for two consecutive years. It is therefore possible that the trend of lower genetic diversity and higher proportion of diploid males compared to mainland populations are due to a peculiar composition specific to Mallorca population, and rather than an effect of the habitat type “island” and its isolation. The habitat isolation effect is nonetheless corroborated by the genetic erosion observed in captive populations, and thus likely to be real, but would require new samplings in other islands to be confirmed.C. glomerata, a biased fertilization occurs and limits genetic incompatibility, leading to a DMP lower than expected in field populations (Ruf et al. C. rubecula could explain the relatively high DMP observed in its field populations (de Boer et al. Bracon brevicornis have reported an avoidance of mating with a partner harboring the same allele at the sl‐CSD locus (i.e., avoidance of matched matings; Thiel et al. V. canescens (Metzger et al. Behaviors such as natal dispersal and mate choice can mitigate the effects of decreased genetic diversity and hence attenuate diploid male production. In V. canescens could result from a lower genetic diversity in isolated populations, or a downgrade in discrimination of females against related males. In a number of species, females adapt future mate choice according to the genotype of their first mate [lizards (Laloi et al. V. canescens because females are monoandrous (Metzger et al. csd locus is higher; possibly, successive encounters with low‐quality males before mating could lead to an adaptive decline in sib‐avoidance. This could explain the increase in diploid male production in small or isolated populations. At last, the presence of diploid males even in mainland populations where the genetic diversity is high and where no departure from HW equilibrium was detected could also be due to imperfect sib‐mating avoidance, as observed under the laboratory conditions (Metzger et al. The higher proportion of diploid males in captive and island populations of Our study suggests that diploid male production in insects of the order Hymenoptera reflects fitness decline resulting from inbreeding in small and isolated habitats. Sex determination via sl‐CSD imposes a major genetic constraint and may reflect an “unintelligent design” (sensu van Wilgenburg et al. None declared.