In wild plant populations, genetic divergence within continuous stands is common, sometimes at very short geographical scales. While restrictions to gene flow combined with local inbreeding and genetic drift may cause neutral differentiation among subpopulations, microgeographical variations in environmental conditions can drive adaptive divergence through natural selection at some targeted loci. Such phenomena have recurrently been observed in plant populations occurring across sharp environmental boundaries, but the interplay between selective processes and neutral genetic divergence has seldom been studied.Eperua falcate Aubl. (Fabaceae) through a genome-scan approach. Populations of this species grow in dense stands that cross the boundaries between starkly contrasting habitats. Within-stand phenotypic and candidate-gene divergence have already been proven, making this species a suitable model for the study of genome-wide microgeographic divergence. Thirty trees from each of two habitats  in two separate populations were genotyped using thousands of AFLPs markers. To avoid genotyping errors and increase marker reliability, each sample was genotyped twice and submitted to a rigorous procedure for data cleaning, which resulted in 1196 reliable and reproducible markers.We assessed the extent of within-stand neutral and environmentally-driven divergence in the Neotropical tree Despite the short spatial distances, we detected within-populations genetic divergence, probably caused by neutral processes, such as restrictions in gene flow. Moreover, habitat-structured subpopulations belonging to otherwise continuous stands also diverge in relation to environmental variability and habitat patchiness: we detected convincing evidence of divergent selection at the genome-wide level and for a fraction of the analyzed loci (comprised between 0.25% and 1.6%). Simulations showed that the levels of differentiation for these outliers are compatible with scenarios of strong divergent selection. Eperua falcata Aublet (Fabaceae). Consequently, mating among neighbors is frequent in aggregative tree species, causing local inbreeding and contributing to the spatial genetic structuring [Microgeographic genetic divergence , 2 , adaptiterra firme’ plateaus is associated with strong variations in tree communities [E. falcata, a recent study has revealed footprints of divergent selection between local subpopulations occupying distinct habitats at stress-response genes [E. falcata and in the congeneric E. grandiflora [E. falcata a good model for the analysis of adaptive processes over microgeographical scales.Amazonian lowland forests are characterized by complex habitat patchiness whereby environmental conditions vary at a small spatial scale (i.e. in the order of hundreds of meters). The succession of waterlogged bottomlands and well-drained ‘munities –27. Micrmunities . More prmunities . In E. fse genes . Geneticndiflora . These pE. falcata in the eastern Guiana shield (French Guiana). To achieve our goals, four populations  were scanned with approximately 1200 AFLP markers. Genome-wide spatial genetic structure was evaluated and the extent of genetic divergence was assessed at both regional and microgeographical scales. A landscape approach was combined with outlier detection tests to distinguish between neutral and adaptive sources of genetic divergence, and to determine whether microgeographic adaptation to local habitat patchiness was involved in genome-wide and/or locus-specific genetic divergence.In this study, we analyzed the neutral and adaptive sources of genetic structuring within continuous stands of E. falcata leaf samples were collected in two study sites of the Eastern Guiana shield: Laussat  and Régina . The study sites are managed by the French National Forests Office (ONF) which authorized tree labelling and leaf sampling. E. falcata is not a protected or endangered species and we certify that our experiment complies with the laws and ethical recommendations of France and French Guiana.Eperua falcata (Aublet) is a canopy-subdominant tree species, hyper-abundant in the Guiana shield [E. falcata populations located near the coast of the Eastern Guiana shield: Laussat  and Régina . These populations experience contrasted rainfall regimes, with a mean annual precipitation of 2500 mm and 3500 mm respectively (in years 2010 and 2011), and with a harsher dry season in Laussat (data from météo-FRANCE stations of ‘Iracoubo’ and ‘Régina’), terra firme, and differ in landscape raggedness. In Laussat, a permanently water-logged bottomland gently rises toward a plateau of low elevation. In Régina, narrow seasonally flooded bottomlands and streambeds lie at the foot of hills and higher-elevation plateaus with steeper slopes. In both sites, bottomlands are characterized by hygromorphic soils with a large accumulation of organic matter up to a depth of 1 m caused by intense waterlogging, while terra firme are composed of well-drained ferralitic soils, rich in iron oxides with a sand-clay texture allowing free vertical drainage (a shield . Its disa shield : heavy sdrainage .. Soil hdrainage . Canopy drainage .http://dx.doi.org/10.5061/dryad.b2q88).All trees of diameter at breast height (d.b.h.) > 20 cm were mapped in a continuous area of 6.7 ha in Régina, and in two areas of 2.5 ha and 1.8 ha in Laussat. Population density varied between 29.9 adult trees/ha and 48.11 trees/ha in Régina and Laussat respectively. In each site, two groups of 30 trees inhabiting distinct habitat types  was realized twice independently for each sample to obtain a complete replicate of the dataset .Fresh leaves were sampled and frozen at -80°C as soon as they arrived to the lab (in the evening following the sampling). Genomic DNA was extracted using a CTAB protocol , 52, and enzymes , 53–55. http://dx.doi.org/10.5061/dryad.b2q88).AFLPs were scored through an automated cleaning procedure (encoded in R): (i) negative controls were used to define thresholds of peak detection, (ii) peak profiles were scanned using PeakScanner Software v1.0 (Applied Biosystems) and the bin set was created using RawGeno v2.0  with thea priori expectation about the number of clusters to be inferred, the model was run with K (number of clusters) values from K = 1 to K = 10 . Trends in L(K) were analyzed using R software, in accordance with the ad-hoc ΔK method proposed by Evanno, Regnaut and Goudet [A Bayesian clustering analysis was performed using STRUCTURE v2.3.4  at both d Goudet . STRUCTUd Goudet  to obtaiFij) was analyzed over twenty evenly spaced distance classes between 0 and 500 m. 95% null confidence intervals were obtained through 1000 random permutations of individuals among geographical locations. Neighborhood size (Nb) and gene dispersal (σg) were estimated with prior knowledge about population densities, and the slope (b) of the regression of kinship relatedness (Fij) against geographic distance (dij) was computed with standard error estimated by jack-knifing over loci. SGS intensity was measured as Sp = b/(F(1)-1) where F(1) is the average kinship coefficient between individuals separated by distances belonging to the first distance class.Spatial genetic structuring and gene dispersal were assessed on AFLP data using the spatial autocorrelation method based on kinship coefficients, as developed by Hardy and Vekemans  and implA landscape approach was used to test whether environmental variations were involved in genome-wide genetic divergence. The simultaneous effects of neutral and adaptive sources of genetic divergence were explored through a linear model. More precisely, the model aimed at distinguishing the relative influence of geographic and environmental distances on genetic distance between individuals. Neutral components were estimated both at the regional  and local scales . Adaptive components were modelled through the environmental distance between individuals . Because light and soil temperature were poorly variable among sites and local habitats, these two factors were excluded from the model .i1,i2 is the genetic distance between the individuals i1 and i2 (Jaccard distance), μ is the global mean, and σ²R the residual variance. SITE i1,i2 describes whether the individuals i1 and i2 are from the same site or not , GEOi1,i2 and ELEVi1,i2 are the geographic (Euclidean) distances between individuals inhabiting the same site according to their two-dimensional coordinates in the x,y-plane and their one-dimensional coordinates along an elevation gradient respectively. DROUGHTi1,i2, WATERLOGi1,i2, and SOILTYPEi1,i2 describe the environmental distances between individuals for seasonal drought severity, waterlogging frequency and soil type, according to sites and local habitat environmental properties as described in http://www.openbugs.net): 10,000 iterations with a burning of 1,000. A complete description of the model and the BUGS code are provided in Where GENETFIS was estimated from an already published dataset composed of SNPs detected in sequenced ESTs [FIS (across loci) varied from -0.207 to -0.089 depending on the population considered. Allele frequencies within each study site and local habitat were inferred from AFLPs data based on a mean inbreeding coefficient of -0.14, by solving the standard equation relating inbreeding coefficient, allele frequencies and recessive genotype frequencies for each marker j, with f(00) the relative frequency of the genotype (00) and p the relative frequency of the ‘0’ allele:Because properly estimating genotypic frequencies from dominant markers requires prior knowledge of inbreeding coefficient, ced ESTs  with ARLced ESTs . The meaFST) between local habitats was estimated from inferred genotypic data through a classical analysis of molecular variance  using AFST-based approaches:fdrtool’ package in R [the coalescent-based FDIST method  implemenage in R , and thethe Bayesian method implemented in BAYESCAN , with anExcess divergence within populations inhabiting contrasting habitats was tested based on two For each outlier detected, X² tests were performed on AFLP band frequencies to test the hypothesis of equal frequencies between local habitats within each study site.FCT = 0.01). Out of the 1196 simulated markers, 1146 were simulated with average FST = 0.039 and FST = 0.026 , 25 were constrained at FST = 0.11 (Bayesian α = 3) and 25 at FST = 0.23 (Bayesian α = 5) to simulate zero, moderate and strong selection respectively. The simulations were submitted to the same outlier detection analyses as the empirical dataset, and the average number of significant markers in each class, over the global set of one-hundred simulations, were reported. The ratio of number of neutral markers detected as significant, over the total number of neutral markers, was taken as an estimate of Type I error rate. The number of markers under selection not detected as significant, out of the total number of markers under selection, was taken as an estimate of Type II error rate.Both the Bayesian- and the coalescent-based methods were submitted to a sensitivity analysis by estimating Type I and Type II error rates. To do this, we simulated one-hundred datasets with the same sample size and number of markers as our empirical datasets (two groups of two populations with divergence between groups http://dx.doi.org/10.5061/dryad.b2q88).After data cleaning, 53.3% of markers (corresponding to 1196 bins out of 2242) were retained for further analysis as described in K) was high from K = 1 to K = 7 for the regional-scale analysis  of 65.6. In Régina, autocorrelation was positive and significant until 30 m and became negative and significant beyond 250 m, with a neighborhood size Nb = 78.5. In both sites, the autocorrelation was positive at a distance corresponding to the distance separating trees inhabiting the same habitat, and became negative at a distance corresponding to the distance separating trees inhabiting two distinct habitats. Gene dispersal was estimated at 45.7 and 64.4 m in Laussat and Régina respectively. We also checked that spatial genetic structure did not vary among local habitats: significant SGS were detected in both habitats until 20 and 30 m in Laussat, and until 20 m in Régina , SGS intensity (Sp) and slope (b), Spatial genetic structure (SGS) was assessed by estimating relative relatedness in 1711 pairs of individuals in Régina and 1810 pairs in Laussat. The mean number of pairs by distance class was 86 in Laussat and 92 in Régina. Significant SGS were detected in both sites , with kin Régina ., and we-2, -5 m-1 . However, there was no positive trend elevation and genetic distances. Among environmental sources of genetic divergence, waterlogging frequency was positively related with genetic distance (θ5 = 1.5.10-2).Partitioning the genetic distance into neutral and adaptive processes through a landscape Bayesian model revealed a strong ‘site’ effect on the genetic distance between individuals  in Laussat and 0.02 (sd = 0.05) in Régina , while the differentiation between local habitats within sites was FSC = 0.03 (sd = 0.05) and the differentiation between local habitats among sites FST = 0.04 (sd = 0.06), Overall Slatkin’s n Régina .. Locus-ST), After local false-discovery rate assessment , 67, 42 To check whether variations in AFLP band frequencies between local habitats were consistent with the hypothesis of selection acting in the same direction in the two replicates, we compared the direction of inter-habitat variation in band frequencies between the two study sites for outlier loci, K = 2) can easily be explained by isolation-by-distance. To evaluate the role of neutral processes in shaping within-population genetic structure, we investigated the fine-scale genetic structuring over all loci within each study site. Kinship coefficients decreased with geographical distances in the two study sites as expected under the isolation-by-distance model. Gene flow estimates were very low in both sites (around 50 m), and the lower gene flow estimated in Laussat (45.7 m against 64.4 m in Régina) was concordant with the stronger genome-wide genetic structuring among local habitats in that site. Similar SGS patterns have been observed in many temperate [E. falcata, gene dispersal estimates (σg ranging from 45.7 to 64.4 m depending on the study site) are in agreement with these characteristics [The genetic clusters inferred by STRUCTURE were spatially aggregated. At regional scale, the genetic structuring among populations inhabiting different study sites ,emperate , 16, 22 eristics , 83.The slight variations in the fine-scale spatial genetic structuring between study sites and between local habitats within sites may possibly be caused by variations in environmental conditions and their direct effect on pollen and seed dispersal. For example, fine-scale spatial genetic structure and population differentiation were weaker, and gene flow was slightly higher, in the study site of Régina (where the relief is steep with abrupt slopes and precipitation more abundant with about 3500 mm/year) than in Laussat (where the relief is quite flat and precipitation does not exceed 2500 mm/year). Variations in topography (relief and slopes), rainfall and water flows may have a direct effect on gene flow and SGS. Even if the spatial genetic structuring was quite similar among habitat types, it was slightly weaker in the bottomland than in the plateau in Laussat, possibly because water flows caused by intense waterlogging contribute to scatter seeds and to increase gene flow in this habitat.The existence of genome-wide neutral divergence directly caused by geographic distances (between and within study sites) was also corroborated by the landscape-scale analysis of genetic divergence. Indeed, the inferred parameter θ1 revealed a site effect on the genetic divergence. Even if it is more likely to be caused by neutral processes related to the geographic distance itself (isolation-by-distance), this parameter may also capture genome-wide adaptive processes caused by variations in both abiotic and biotic conditions between the study sites . The parameter θ2 captured the effect of geographic distances on genetic distances within study sites , confirming the existence of a neutral spatial genetic structuring within study sites.FST = 0.04; sd = 0.06) was large regarding the differentiation between sites , despite the geographical scales involved . As the effects of dispersal limitation can only increase with distance, it seems unlikely that this kind of process would be stronger locally than at the regional level. This means that genome-wide divergence may be influenced by local adaptation to micro-environmental variability. In particular, waterlogging frequency influence genome-wide divergence over microgeographical scales as revealed by the landscape-scale approach, probably through its direct effect on seedlings establishment.In addition to neutral, distance-based, genome-wide divergence, variations in waterlogging frequency may constitute a source of adaptive genetic divergence as revealed by a positive estimate of the parameter θ5. Surprisingly, the waterlogging effect was of the same order of magnitude as the site effect, despite the large differences in geographical scales separating sites (hundreds of kilometers) and local habitats (hundreds of meters). This implies that a fraction of genome-wide divergence may have been caused by ‘pervasive selection’ , 69 overLocus-specific footprints of local adaptation were also detected for a fraction of the analyzed loci. Indeed, adaptive divergence may either affect many genes of low effects, or a reduced number of targeted loci (few genes of major effects) involved in key metabolic or physiologic pathways, themselves involved in fitness –92. BothFST) are robust to inter-locus variations, and theoretical models show that footprints of natural selection persist longer in differentiation indices (FST) than in intra-population estimators of genetic diversity [FST-based methods are also supposed to be robust to many demographic scenarios [Outliers may also indicate the presence of some other indirect mechanisms inducing genetic divergence that may not be directly related to environmental filters , 95, 96.iversity . FST-bacenarios , 98, parcenarios . Howevercenarios . Even ifcenarios .E. falcata. These loci may be involved in metabolic pathways crucial for seedlings establishment and growth under the particular constraints imposed by each habitat, such as waterlogging and hypoxia experienced in bottomlands, or seasonal soil drought experienced in plateaus. However, the selective agency behind the observed divergence needs to be functionally proven by showing that the putatively selected polymorphisms control adaptive traits. This will require (i) identifying the genes involved in fitness-related phenotypic traits, and (ii) targeting these loci for testing local adaptation on candidate genes [Scans for outlier detection are abundant in the literature for a variety of geographical scales and biological models, including animals and plants, both aquatic and terrestrial , 100–107te genes .E. falcata is a piece of evidence that evolution may drive genetic differentiation and subpopulation divergence even in conditions in which gene flow may easily erase the effects of weak selective forces . At such spatial scales, dispersal and population connectivity  meet evS1 FigA: Example of hemispherical photograph done in the plateau of Laussat, B and C: Examples of soil toposequences .(TIF)Click here for additional data file.S2 FigK) and ΔK values. Middle pane: individual α values for K = 2 and K = 3. Lower pane: geographical distribution of individuals belonging to the main clusters (see text).Upper pane: L((TIF)Click here for additional data file.S3 FigK) and ΔK values. Middle pane: individual α values for K = 2. Lower pane: geographical distribution of individuals belonging to the main clusters (see text).Upper pane: L((TIF)Click here for additional data file.S4 FigK) and ΔK values. Middle pane: individual α values for K = 5. Lower pane: geographical distribution of individuals belonging to the main clusters (see text).Upper pane: L((TIF)Click here for additional data file.S5 Fig(TIF)Click here for additional data file.S6 Fig(TIF)Click here for additional data file.S1 Method(DOCX)Click here for additional data file.S2 Method(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.


Vitis ficifolia Bge. The numbers of bands scored per primer combination ranged from 8 to 27, with an average of 18.6 bands. At the population level, the percentage of polymorphic bands (PPB), Nei's gene diversity index (H) and Shannon's information index (I) were the highest in the Shihe (Xinyang) population  and the lowest in the Linzhou (Anyang) population . At the species level, PPB, H and I were 80.56%, 0.2129 and 0.3075, respectively. The genetic differentiation coefficient (GST) was 0.2055 and the gene flow (mN) was 1.9328, indicating strong intra-population genetic differentiation. Based on the unweighted pair group method based arithmetic average clustering diagram, the five studied populations may be divided into three groups. The clustering results were almost in accordance with the populations’ geographical distribution.Eighteen sequence-related amplified polymorphism (SRAP) primer combinations were used to assess the genetic diversity of 126 individuals from five different geographical populations of  The genetic diversity of plant species is a major concern for geneticists and plant breeders. The currVitis spp.) is one of the most important fruit crops worldwide with more than 70 species of Vitis spp. in the world.[Vitis species have their origin in China, making China one of the major gene centres of Vitis species origination.[V. ficifolia Bge. is a subspecies of V. heyneana Roem. et Schult, and is distributed mainly in the northern and eastern China, at altitudes between 100 and 1300 m,[V. ficifolia has excellent tolerance to anthracnose, ripe rot diseases and winter cold, and is used both as table grape and in wine production.Grapevine  the levels of genetic diversity within and among populations and (3) the genetic relationships among populations.In this study, SRAP analysis was employed to investigate: (1) the levels of SRAP variations in V. ficifolia Bge. individuals of five different wild populations were selected from Henan Province of China. Their places of origin and distributions are shown in A total of 126 Total genomic DNA was isolated from fresh leaves following the procedure previously described by Liu et al. . The qua2+ and 1 U Taq DNA polymerase (TaKaRa). The amplification reaction procedure was as follows: after denaturation at 94 °C for 5 min, the reaction mixture was subjected to amplification for seven cycles consisting of 90 s at 94 °C, 75 s at 35 °C, 30 s at 72 °C, followed by 30 cycles consisting of 60 s at 94 °C, 60 s at 55 °C and 90 s at 72 °C, with a final extension at 72 °C for 5 min.The SRAP analysis was carried out using 26 primers including 13 forward (Me1-13) and 13 reverse (Em1-13) SRAP primers 11-18, for a toI), Nei's gene diversity (H), genetic identity and genetic distance, etc. AMOVA 30 software was used to estimate the relative genetic differentiation coefficient (GST) and the level of gene flow (mN). Cluster analyses were conducted on the similarity matrix with the unweighted pair group method based arithmetic average (UPGMA), and the resulting clusters were expressed as dendrograms.Amplified bands were scored as either present (1) or absent (0). The data were entered into a binary matrix and, subsequently, POPGENE 32 software was used to compute the population genetic parameters, the percentage of polymorphic bands (PPB), Shannon's information index , whereas population LZ exhibited the lowest level of variability , as shown in Genetic polymorphism may be indicative of evolutionary adaptation which plays a key role for survival of a population in the changing environment. AccurateGST) was 0.2055, which showed that the major genetic variation (72.95%) originated from intra-population diversity, and the rest (20.55%) existed among populations. The level of gene flow (mN) is a key factor that affects the genetic structure and genetic differentiation among populations. Based on the AMOVA analysis, the level of gene flow (mN) among the five populations was 1.9328.Genetic differentiation and gene flow are important indices for evaluation of the genetic structure of a group. Based on the analysis by AMOVA 30 software, the relative genetic differentiation coefficient . This indicated that high-level gene flow existed within V. ficifolia populations. This result was consistent with the previous results.[GST may lie in the morphological character of the wild V. ficifolia, with the vines growing up into tall plants, and the tall plants benefitting due to reduced resistance to pollen movement in the air. Moreover, a lack of effective geographic isolation may also contribute to the improvement of gene homogenization among populations.[V. ficifolia has wide distribution in northern and eastern China, especially in Henan Province. However, it should be noted that the V. ficifolia populations used in this study were sampled from a narrow eco-geographical area of distribution.The results obtained here showed that a high proportion of the variability was due to intra-population variability, and this high genetic variability was consistent with the previous results obtained by morphological analysis. Gene flos higher. In this  results.,27–31 Thulations. Consequeulations. V. ficifIn genetic diversity analysis, there are various genetic distance measures for analysis of molecular marker data. Genetic identity is an important index for estimation of the genetic differentiation among populations. Based on our POPGENE analysis, the genetic identity and genetic distance between each two populations, respectively, ranged from 0.9171 to 0.9825 and from 0.0176 to 0.0866. This suggested that there was a high genetic similarity between the populations, indicating lower reproductive isolation among the populations . The minElymus sibiricus populations studied by them clustered in accordance with the geographic distribution. In our study, the clustering results were almost in accordance with the geographical distribution.The dendrogram obtained with SRAP data is shown in in situ method allows continuing evolution of the species in its natural habitat and then guaranteeing the maintenance of most of the species’ genetic variation. In this study, population SH showed relatively high genetic diversity within V. ficifolia Bge., and should therefore be a priority site for in situ conservation.The V. ficifolia Bge., using SRAP markers. The results indicated that SRAP markers could be used efficiently in the study of genetic diversity and genetic variability of V. ficifolia. High-level gene flow existed within V. ficifolia populations. The clustering results based on SRAP were almost in accordance with the geographical distribution of the populations. In our study, the Shihe population (SH) showed relatively high genetic diversity within V. ficifolia Bge., and should therefore be a priority site for in situ conservation.The present study is, to the best of our knowledge, the first report of genetic investigation of


Gadus macrocephalus is a demersal, economically important fish in the family Gadidae. Population genetic differentiation of Pacific cod was examined across its northwestern Pacific range by screening variation of eight microsatellite loci in the present study. All four populations exhibited high genetic diversity. Pairwise fixation index (Fst) suggested a moderate to high level of genetic differentiation among populations. Population of the Yellow Sea (YS) showed higher genetic difference compared to the other three populations based on the results of pairwise Fst, three-dimensional factorial correspondence analysis (3D-FCA) and STRUCTURE, which implied restricted gene flow among them. Wilcoxon signed rank tests suggested no significant heterozygosity excess and no recent genetic bottleneck events were detected. Microsatellite DNA is an effective molecular marker for detecting the phylogeographic pattern of Pacific cod, and these Pacific cod populations should be three management units.The Pacific cod  Gadus macrocephalus is a demersal, economically important fish in the family Gadidae. It is mainly distributed in the North Pacific, from the Yellow Sea of China through the Sea of Japan, Okhotsk and Bering Seas to California in the eastern North Pacific [The Pacific cod  Pacific ,2. As an Pacific . Low tem Pacific ,4,5. The Pacific . Could tet al. [et al. [et al. and the current distribution pattern represents groups previously isolated during glaciations that are now in secondary contact [Studies on population genetics have attracted much attention because such information is important for understanding the pattern of biogeography and sustainable utilization of fishery resources . If we iet al.  detectedet al. . However [et al.  examined contact .et al. [These studies suggested different sensitivities of three molecular markers for detecting the genetic structure and diversity of the Pacific cod. Compared with mitochondrial DNA and allozyme markers, microsatellite DNA is a type of nuclear genetic marker that has been proven to be more sensitive in detecting population genetic structure ,15,16. Iet al. . The resA), observed heterozygosity (Ho), expected heterozygosity (He) and polymorphism information content (PIC) are shown in He) ranged from 0.496 ) to 0.957 ), and the observed heterozygosity ranged from 0.435  to 1.000 ). The PIC values ranged from 0.472–0.933, which suggested high genetic diversity of this species (PIC > 0.5) [Clear and unambiguous bands were identified by denaturing polyacrylamide gel electrophoresis. All eight microsatellite markers were highly polymorphic and the number of alleles per locus varied from eight to 24 . The numC > 0.5) . Five deFst ranged from 0.0204–0.0618 and p-values were adjusted using the sequential Bonferroni procedure . Genetic differences between population YS and the other three populations were larger and statistically significant after sequential Bonferroni correction. The Mantel test indicated no significant relationship between pairwise estimates of Fst/(1 − Fst) and geographic distance    . In orde > 0.05) . The fir > 0.05) .2 genetic distance was calculated according to the allele frequency and the results showed that population YS exhibited the larger genetic distance from the other three populations, which was in accordance with the result of the pairwise Fst. However, the (δμ)2 genetic distance between populations SJ and EH was the smallest, not between populations SJ and OS. The topology of the unweighted pair-group method analysis (UPGMA) tree based on (δμ)2 genetic distance showed the relationship of the four populations more intuitively (The (δμ)uitively .l-shaped distribution of allele frequencies as expected for a stable population under mutation-drift equilibrium.Wilcoxon signed rank tests under the three mutational models ; stepwise mutation model (SMM); two-phase mutation model (TPM)) were not significant, which suggested that no significant heterozygosity excess was detected . In addiK = 2 explained the data in a satisfactory manner, as this model resulted in the highest ΔK value currents ,19. Thoucurrents . Populatcurrents . The res [et al. .et al. [et al. [K = 3 was performed, which was supported by the results of (δμ)2 genetic distance and 3D-FCA. The topology of the UPGMA tree based on (δμ)2 genetic distance showed that populations from the Japanese coast clustered with each other at first, and then with population OS. The pairwise Fst was calculated based on the haplotype frequency, and genetic distance was based on the difference of alleles. There are alleles that may cause this difference between the two methods.The strong genetic differentiation between populations from the Sea of Japan and the Okhotsk Sea determined with mitochondrial DNA by Liu et al.  was in c [et al.  examinedHe) of Pacific cod was higher than the average values of marine fish [et al. [The conservation of genetic diversity is very important for the long-term interest of any species . Studiesine fish , and mos [et al. . Moreove [et al. ,15,16,27et al. [et al. [However, low genetic diversity of this species was detected by allozyme and mitochondrial DNA, which was in contrast with our results and Cunningham et al. . Especia [et al. . The all [et al. ,29. Prev [et al. ,30,31. TIn conclusion, microsatellite DNA is an effective molecular marker for detecting the phylogeographic pattern of Pacific cod. The results of the present study suggested these Pacific cod populations should be considered as three management units and population YS should be paid more attention because of its uniqueness.Samples from four locations across the northwestern Pacific Ocean were used in the present study , Table 6Genomic DNA was isolated from muscle tissue by proteinase K digestion followed by a standard phenol-chloroform method. Eight polymorphic microsatellite markers were employed for this study ,33 Tabl.2. The PCR amplification was carried out in a thermal cycler  under the following conditions: 5 min initial denaturation at 92 °C, and then followed by 25 cycles of 30 s at 92 °C, 30 s at annealing temperature 62–57 °C, 30 s at 72 °C and final extending for 30 min at 72 °C. We used 8% non-denaturing vertical polyacrylamide gel electrophoresis to separated PCR products and visualized by silver staining [Polymerase chain reaction (PCR) was carried out in 10 μL volumes containing 0.5 U Taq DNA polymerase , 100 ng template DNA, 0.15 μM of each forward and reverse primers, 0.2 mM each deoxy-ribonucleoside triphosphate (dNTPs), 10 mM Tris (pH 8.3), 50 mM KCl, 3.0 mM MgClstaining . A sizinA), observed heterozygosity (Ho), expected heterozygosity (He) and Polymorphism Information Content (PIC) were obtained by Microsoft Excel tools [Fst were calculated by FSTAT 2.9.3 [Fst measures were subjected to multidimensional scaling (MDS) and plotted in two dimensions , data not shown). The relationship between genetic distances and geographic distances was assessed using Reduced Major Axis (RMA) regression and Mantel tests using IBDWS [2 genetic distance by POPULATION 1.2 [2 genetic distance by MEGA 5 [K values ranged from 1 to 10 . Ten independent runs were implemented for each specific K-value in order to verify the consistency of the results. The ad hoc estimated likelihood of K (ΔK) was used to determine the most likely number of populations (K) based on the rate of change in the log probability of the data (Ln P(D)) [Deviations from the Hardy-Weinberg equilibrium (HWE) and linkage disequilibrium of each locus within each site were checked by GENEPOP 3.4 . The numel tools . The nulel tools . The valAT 2.9.3 . BottlenAT 2.9.3  was usedAT 2.9.3 . We alsoAT 2.9.3 . ARLEQUIAT 2.9.3 , and AMOng IBDWS ,43. We cTION 1.2  and consy MEGA 5 . Three-dy MEGA 5 . The posy MEGA 5 . Markov Ln P(D)) .


The field of conservation genetics, when properly implemented, is a constant juggling act integrating molecular genetics, ecology, and demography with applied aspects concerning managing declining species or implementing conservation laws and policies. This young field has grown substantially since the 1980s following the development of polymerase chain reaction and now into the genomics era. Our laboratory has ‘grown up’ with the field, having worked on these issues for over three decades. Our multidisciplinary approach entails understanding the behavior and ecology of species as well as the underlying processes that contribute to genetic viability. Taking this holistic approach provides a comprehensive understanding of factors that influence species persistence and evolutionary potential while considering annual challenges that occur throughout their life cycle. As a federal laboratory, we are often addressing the needs of the U.S. Fish and Wildlife Service in their efforts to list, de‐list, or recover species. Nevertheless, there remains an overall communication gap between research geneticists and biologists who are charged with implementing their results. Therefore, we outline the need for a National Center for Small Population Biology to ameliorate this problem and provide organizations charged with making status decisions firmer ground from which to make their critical decisions. The field of conservation genetics grew from studies of applied population genetics that started in the 1920s or earlier when scientists were concerned with conservation of germplasm resources for plants  rather than simple numeric population goals . While viability goals include more information about a population than numeric population goals, some seemingly specific viability goals [e.g., maintain 90% heterozygosity for 200 years  is a federal facility located on the Oregon State University campus. I have a faculty appointment so I can integrate teaching, graduate students, and postdocs into my research program if I wish or I can conduct research with USGS staff alone. I prefer a hybrid approach where I teach and direct more students than many of my federal colleagues but less than my academic colleagues. The FRESC Conservation Genetics Laboratory represents about half of my research program. The other component addresses population ecology of avian species, particularly shorebirds. I established these programs in 1994, and since then, significant changes have occurred in the life history strategies among laboratory members.I have had 37 graduate students and postdocs to date, 31% were geneticists, 31% worked on a mix of genetics and population ecology, and 38% had no genetics aspect to their work. Happily, all are employed at their appropriate level. In addition, two laboratory technicians (authors Draheim and Mercer) completed M.S. degrees in our laboratory and laboratory techs (authors) Draheim and Bellinger have just completed Ph.D. and are starting postdocs. The only person who did not end up in their field of choice is a former Ph.D. student who had a child as a student. She has a very good job but not as an academic as she had hoped. The pressures of field work and tenure were not what she felt was healthy for her family.Our laboratory has always enjoyed the presence of students or postdocs from various countries around the world including Brazil, Sweden, Denmark, China, Namibia, and the Netherlands. Regardless of their academic position, the international students have always broadened our perspective on approaches to science and life. We have also been involved in organizing international training courses on animal movement, migratory connectivity, and conservation genetics in the United States, Mexico, Brazil, Kenya, and Namibia. Securing funds for our travel and the students travel to a central location for classes is difficult, but it has resulted in a number of international students acquiring graduate student positions in our laboratory or another.Just as I have learned to balance my work at the office and in the field, I am part of a growing movement to encourage work/life balance for employees. Despite the tremendous changes that have taken place since I was a graduate student, postdoc and young faculty member in the 1980–90s, it is clear that as a profession, we have work to do to address lifestyle demands or we risk losing the best and brightest researchers.When I started 35 years ago, academia and the federal government were at the forefront of providing professional opportunities for women and minorities in the sciences. We all benefited from the addition of more diverse points of view at work, but it was a tremendous culture change: Women were finally getting more professional jobs but often at the cost of marriage and a family life. For example, I did not know any working women my age with Ph.D., who were married and had children. To this day, the very few women my age who have reached this seniority and have families relied on stay‐at‐home husbands when their children were young. Now as an employer, it is not easy balancing the needs of employees who must get work done with the needs of women and men who value having a family and careers. On one hand, over the past 21 years, we have been happy to celebrate the births of 12 babies among laboratory members, and an additional 13 children have parents who have worked in the laboratory  as a primary example  variable allozyme loci via starch gel electrophoresis to being able to screen tens of thousands of variable markers for hundreds of individuals in one lane on the Illumina high‐throughput platform. Concomitant with development of new molecular methods has been our ability to use simpler and less invasive sampling techniques.Early allozyme studies on Piping Plovers benefitted greatly by being able to use proteins from red blood cells rather than extracting organs and sacrificing each bird . We used these dominant markers for screening population‐specific markers in migrating shorebirds and broad‐scale population studies of Red‐cockaded Woodpeckers and Northern Spotted Owls .Few birds have been more controversial than the Northern Spotted Owl Fig. . They haS. o. caurina), California , and Mexican (S. o. lucida) with evidence for subspecies hybridization where taxa met geographically  that were quickly expanding their range into the Pacific Northwest. Not knowing how extensive this hybridization might be, we developed mtDNA, microsatellite, and AFLP markers to differentiate these taxa for use by law enforcement laboratories  typing, and whole‐genome methods  have a mean home range of less than 1 m, rendering them easy to genetically differentiate from other salamanders  museum skins from the 1800s to obtain mitochondrial DNA sequences. These data allowed us to test the hypothesis that there may have been more than one species of North American condor in the past. Results indicated there was only one species  from the Pacific islands of Pohnpei, Palau, Guam, and Ryukyu as a means of determining their true taxonomic relationships. The most immediate need for these analyses is to help plan reintroduction efforts for the Guam Kingfisher (T. c. cinnamominus). These birds went extinct in the wild in the mid‐1980s following introduction of the Brown Tree Snake (Boiga irregularis) to Guam (Savidge T. c. pelewensis) or Pohnpei (T. c. reichenbacheii) if they were are subspecies or closer. This option would only being considered if our taxonomic assessments indicated these populations were conspecifics.Similarly, we are also examining museum tissue and blood samples for four described subspecies of the Micronesian Kingfisher . They had just gone extinct in the wild as a result of the Brown Tree Snake introduction on Guam . An early opportunity occurred when Susan Haig was given the job of planning a captive recovery population for the Guam Rails , which provide important breakthroughs that will greatly facilitate analyses of pedigrees in wild populations and increase the types of information that can be gleaned from them.Once DNA fingerprinting became available, we were better able to quantify relatedness among the captive population founders  stands across the southeastern United States  able to incorporate phenomenal amounts of data across a landscape  particularly from south to north as well as a larger body size in birds further north. We noted this might be part of the reason that translocations of birds north from Florida to Kentucky were unsuccessful. In this case, climate and selection may have played a part in translocation success. We further investigated the cooperative social system of woodpeckers to better understand what types of groups might need to be moved  illustrated a significant loss of genetic diversity in contemporary birds relative to pre‐1950 birds . In this case, doctoral student, Jesse D'Elia, collected tissue from every known California Condor museum skin (n = 67) and all 14 founders to the captive population, as well as pedigree information from the remaining extant birds (n = 404). Using 526 bp of the mtDNA control region, we found 18 haplotypes in the historical samples compared to three in the extant population—an astounding 80% decline in haplotype richness  with Peter Marra and the Smithsonian Migratory Bird Center.Migratory connectivity is the geographic connection of individuals and populations between one life cycle stage and another , Semipalmated Sandpipers , and Dunlin . We also created criteria to identify winter origins of six other species. This research established the basis for identifying migratory connectivity using molecular data. Currently, selective choosing of SNPs  subspecies across Beringia in order to track the potential spread of bird flu across continents  occurs on four or more islands in the Marianas archipelago. New understanding of their seasonal movements and direction of juvenile dispersal is narrowing conservation foci to the most critical areas . This species lives in the dry forests of north central Brazil's Cerrado (savannah) region which has undergone increasing habitat alternation due to deforestation since the 1970s . We began using Landsat imagery to quantify the distribution and abundance of forest habitat in the region for three time periods: 1977, 1994, and 2008. We then used a novel measure of connection redundancy between populations to illustrate that genetic patterns in Pfrimer's Parakeet were most closely associated with forest conditions in 1977, indicating a 35+ year time lag between deforestation and contemporary genetic structure. Given continued deforestation in the region, genetic structure patterns are only expected to become stronger in the future. We are currently evaluating the future repercussions of continued deforestation in this system using spatially explicit models developed with HexSim , Southern Torrent Salamanders (Rhyacotriton variegatus), and Western White Pine (Pinus monticola). Results differed by taxa: Genetic distances and diversity for Northern Spotted Owls and Western White Pine were greater in southern versus northern locales while genetic distances were greater in northern versus southern regions for Red Tree Voles and Southern Torrent Salamanders. Subsequent analyses suggested that historical factors such as range expansion, rather than anthropogenic factors, better explained some of these patterns. These types of analyses are important to perform prior to attributing human‐based activities to genetic structure patterns within species.Landscape genetic studies tend to examine patterns at a finer scale  than phylogeographic studies, which investigate processes at greater temporal or spatial scales . Both are important approaches to understanding the underlying processes that impact spatial genetic structure of species. In a comparative study, we examined the spatial distribution of genetic variation in several species .(representing different taxonomic groups) with similar geographic distributions across Pacific Northwest forests . The cost for recovery of a listed bird species averages over $5 million per year  for the molecular data and (ii) for agency personnel and organizations to understand how it applies to their listing and recovery information needs. These listing decisions by USFWS are not trivial. For example, the decision to list a species under the ESA, or even formal consideration of whether or not to list a species, can influence the management of recreational and economic activities on millions of acres of federal lands . However, few scientists are trained to collect, carry out analyses on, and interpret this diversity of information, let alone put it in an ESA, IUCN, or other policy context. Ultimately, the field of small population biology will evolve to be stronger and more effective for solving critical questions in conservation if we treat it as a multidisciplinary field unto its own (as the zoo community does) and not just any dataset that happens to deal with small populations. Thus, we need a focus on this integrated field itself.The issues outlined above all call for a more focused, integrative, and informed approach to assessing species taxonomy or status. There are numerous short‐fixes that could be implemented such as short courses for conservation practitioners, more conservation genetics courses being taught at the undergraduate and graduate level, and sabbaticals for academics in decision‐making organizations such as USFWS endangered species offices. However, the contentious and serious nature of today's endangered species issues calls for a more significant solution.http://www.nwhc.usgs.gov/), National Wildlife Forensic Laboratory (http://www.fws.gov/lab/) and National Wetlands Laboratory (http://www.nwrc.usgs.gov/), development of a National Center for Small Population Biology would serve a similar purpose and would make major strides in bridging the gap between scientists and the decision‐makers who need to implement policies based on their results. Establishment of this Center would insure USFWS, and other partners were provided with the best information and latest technology to address an issue.Therefore, out of the same national and international need to develop focused expertise as was called for in the formation of the National Wildlife Health Laboratory  would insure accuracy in results, consistency across plans, appropriate interpretation of law and policy, and integration between research and nonresearch biologists. The Center would be a place where participating scientists could either carry out analyses themselves or review analyses for organizations such as USFWS, rendering scientific judgement on whether they were valid, if they saw problems, etc. Ultimately, it would save conservation organizations time, money, and will ensure the data are the robust, appropriate for the questions being asked, and do not require additional expert interpretation. Giving an organization like USFWS, for example, a voice from the Center that could speak to the nuances of genetics, demography, the ESA, etc. would cut short and make clearer debates about the scientific merits of particular listing and recovery decisions. Under the current system, agencies and organizations hoping to find appropriate geneticists may need to perform time‐consuming searches when an issue arises, having a ready source of experts that could design and/or carry out research or consult about a species at risk would greatly facilitate this process. Development of the Center would not preclude other scientists from carrying out molecular or other types of research to address listing and recovery type issues. Rather, it would insure USFWS and other organizations always had the appropriate resources or consultants to carry out or interpret studies in the manner in which they needed.Increasingly, ESA and similar listings require molecular analyses to determine taxonomic identification, population structure, or population status Box . This trDemographic analyses are key to developing effective recovery plans and monitoring strategies  and the American Zoo and Aquarium Association Population Management Center (PMC: www.aza.org) at the Lincoln Park Zoo. These programs, run by overlapping personnel, train zoo personnel to manage the demographics and gene pools of single species located across many zoos. CBSG or PMC personnel carry out their own research as well as travel the world meeting with groups of zoo personnel involved with a particular species. Over the course of a few days, these scientists carry out genetic and demographic analyses needed to meet recovery goals while zoo personnel advise them on the reality of choosing various individuals to breed, transfer, etc. These programs have been phenomenally successful in managing captive and reintroduced species and as a result also have produced the most cutting edge research on small population biology management in the world. While the Center we are proposing primarily involves wild animals which likely are more complex to manage, the CBSG/PMC model is an excellent guide.A similar approach to the Center has evolved in the zoo community via formation of the IUCN Conservation Breeding Specialist Group (CBSG: In many ways, our approach to single‐species conservation genetics studies has not changed since Susan Haig's initial work on Piping Plovers in the 1980s. We continue to use extensive sampling to define taxonomy and population structure across the species range, understand migratory connectivity of populations, and consider behavioral and ecological factors in final syntheses of the data. However, the molecular methods and bioinformatics tools we now apply are more complex, leading to more specific, accurate, and useful conclusions. An important component of this brave new world is the ability to bridge the gap between genetics and population ecology to provide better information for status assessments and recovery planning. Development of a National Center for Small Population Biology will help bridge that gap.


Yersinia ruckeri, the pathological agent of enteric redmouth disease (ERM) in salmonids, were investigated on the basis of concatenated multiloci sequences from isolates of different phenotypes obtained between 1965 and 2009 from diverse areas and hosts. Sequence analyses revealed genetic differentiation among subpopulations with the largest genetic distance occurring between subpopulations of Europe and Canada and/or South America. Bayesian analysis indicated the presence of three ancestral population clusters. Mismatch distribution displayed signatures characteristic of changes in size due to demographic and spatial expansions in the overall Y. ruckeri population, and also in the geographically separate subpopulations. Furthermore, a weak signal of isolation by distance was determined. A significant positive correlation between genetic and geographical distances was observed. These results revealed that the population of Y. ruckeri has undergone both ancient and recent population changes that were probably induced by biogeography forces in the past and, much more recently, by adaptive processes forced by aquaculture expansion. These findings have important implications for future studies on Y. ruckeri population dynamics, on the potential role of genetic structure to explain variations in ERM transmission, and on the effect of past evolutionary events on current estimations of gene flow.Phylogeographic patterns and population genetic structure of  Studies on the evolutionary history of organisms have benefited from the availability of an increasing amount of data, especially multiple whole genome sequences. This fact has led to more accurate reconstructions of phylogenetic relationships within several bacterial species  and eBURST analysis for the phylogenetic inferences to determine exact relationships between individual isolates , has been spread multiple times from the USA, probably by egg or carrier fish transfers, as the culture of rainbow trout (Oncorhynchus mykiss) became more widely practiced in the world , which showed some of them to be dated before the first reports of isolation by Rucker in the 1950s , the microorganism has been isolated from non-salmonid and marine fish    and described by a MLST scheme  and the concatenated sequences were downloaded from the Y. ruckeri MLST database hosted on publmlst.org (http://pubmlst.org/yruckeri/). For analyses, each ST was considered as one haplotype, and the 103 isolates of Y. ruckeri were considered as one population, which were divided into nine different subpopulations on the basis of the geographical site of isolation as designated in the MLST database (Table The data set used in this study consisted of multiloci concatenated sequences of 103 http://www.fluxus-engineering.com). Concatenated sequences of the six housekeeping genes from all Y. ruckeri isolates were previously aligned using the software DNA Alignment 1. 3 (http://www.fluxus-engineering.com), and the output file were imported into NETWORK 4.1 to conduct a network analysis using a median joining algorithm  of the 30 haplotypes  were estimated by constructing a maximum-likelihood (ML) tree with PHYML 3.0  were calculated to assess the genetic variability using the software DnaSP 5   among subpopulations, assuming a constant migration index.Haplotype polymorphism (Hd), nucleotide diversity (π), and average number of pairwise differences  sampling method that was implemented using the Structure software  of the observed data relative to the model. Harpending's raggedness (r) index . The physical distance between different pair of sampling locations was then calculated using the ARC CALC 3 Spherical Trigonometry Calculator macro (http://www.jqjacobs.net/astro/arc_form.html). The presence of phylogeographic structure was tested for individual allele frequencies in six equally-spaced classes of geographic distances by mean the spatial autocorrelation Moran's I index .Haplotype diversity ranged from 0.47 to 1.00 among subpopulations with a mean value of 0.79 for the overall population Table . The higFST values were low among several subpopulation being between −0.0253 and 0.0860, indicative of a high degree of gene flow between different pairs of subpopulations; however these values were not statistically significant (P > 0.05) . The AMOVA results indicated that the highest proportion of the molecular variance (82.67%) could be explained by variations within each subpopulation, while the rest of the variance is explained by the genetic differences among them . The net number of migrants between subpopulations per generation Nm ranged between 0.4 to infinity . Infinity values indicated the highest gene flow between pairs of subpopulations. Only the estimated gene flow for CH was low, indicating that this subpopulation is genetically isolated and/or with limited gene flow.At the finest scale, pairwise K = 3)  together with other two isolates from PE, and one isolate from UK (posterior probabilities from 0.567 to 0.872) indicating a separate diversification. However, the third genetic cluster (blue color) included in addition to the DG strains, the rest of isolates from FN, US, and CA excluded in clusters I and II . Interestingly, high levels of admixture were present within all groups.Bayesian analysis of population structure evaluated with Evanno's criterion ΔK, indicated that the data were highly consistent with the presence of three genetic populations or genetic clusters  Figure . The maj) Figure . These iK = 5 and K = 6 genetic subpopulations in cluster I , 31.8% of the variation was associated to the haplotype frequencies among the 3 clusters , whereas the remaining 9.1% of variation was attributed to within subpopulation-clusters haplotype differences . Nei's GST and Nm (P < 0.05) was detected among the three clusters with FST between 0.0886 and 0.1309, while the estimation of gene flow showed Nm values from 1.9 to 2.3 between populations, supporting limited genetic flow by genetic isolation of clusters.An AMOVA conducted by partitioning variation among and within the three clusters revealed that 59.1% of the total variation was attributed to within-population differences , which occurs when an excess of rare haplotypes are present, indicating population expansion or genetic hitchhiking events. Ramos-Onsins' R2 statistic and Strobeck's S index determined that the total population has significant positive R2 (0.056) and high S (1.00) values supporting also possible population expansion. However, FN and PO subpopulations showed positive but non-significant FS values, indicating natural selection or population growth. Positive D* values exhibited by CA and DG subpopulations suggest balancing selection, although these values were no significant. When neutrality was tested within each genetic cluster , the results indicated similar conditions to those observed for the overall population  with high raggedness value  indicating constant population at equilibrium, although raggedness P value supported spatial expansion (P = 0.12). Furthermore, the mismatch distribution for each cluster  also showed a unimodal distribution typical of demographic expansion, supported by the low values for the SSD statistic and raggedness index , from the raggedness calculation, was 1.10  for the demographic expansion, and 1.13  for the spatial expansion for the entire population of ri Table . The divP = 0.000) indicating that the allele frequencies tend to be more different at this geographical distance, and suggesting isolation by distance . The partial Mantel test determined that genetic distances and geographical distances among Y. ruckeri subpopulations were positively correlated  . However, clusters II and III provided evidence of non-significant but negative correlation within the subpopulations  supporting the signal of isolation by distance detected for the overall population.Spatial dependence of haplotype frequencies was only detected at the intermediate distance (4500–6000 km)  Figure . SimilarY. ruckeri population were analyzed on a global scale using multi-sequence data. A pattern of sequence divergence corresponding to geographical area was observed at relatively recent points in the evolutionary history of Y. ruckeri. Neighbour network showed a large number of rare haplotypes separated by single-nucleotide differences. Statistical signatures of population expansion were detectable in all subpopulations. Moreover, mismatch distribution indicate that few haplotypes spread and mutated to generate several closely related haplotypes, as is commonly observed during population expansion  in 1992  imported from the United States at least since 1981 for live-bait fishing. In addition, as pointed out by Gall and Crandell  being more closely related to isolates from UK , and in less proportion to some isolates from Portugal . The third ancestral population was formed by Y. ruckeri strains from Canada, Portugal, and Denmark not belonging to the serotype O1a, and with the majority of strains isolated from hosts different to O. mykiss. The evidenced genetic admixture in the entire Y. ruckeri population also supports the previous hypotheses of specificity of Y. ruckeri strains and niche specialization  and isolation by distance (which is consistent with evolutionary equilibrium). This phenomenon may be the result of residual effects of range expansion, and by transfer of strains through countries due to human activities. Humans have had an enormous influence on the global environment and are known to have inflicted genetic variation within other species in the recent past  can be preliminary estimated to be on the order of 2.8 × 10−7 substitutions per site per year. In theory, if an average of 100–300 generations per year is assumed , varying between 800 and 30,000 years among the different areas. This fact suggests ancient spread of Y. ruckeri long before to the emergence of modern ERM disease, and highlights the scenario of the independent ERM disease emergence events in the North America and Europe in the last centuries. However, these date ranges should be regarded as preliminary, and further studies are needed on the ancestry and molecular clock in the evolution of Y. ruckeri to confirm this hypothesis. Furthermore, the mismatch distributions observed are consistent with expansion in almost all regions, the high values of raggedness index of the Canada, Finland and Portugal subpopulations may indicate a more stable demographic equilibrium with a less sudden expansion  (Slatkin and Hudson, r Drake, , the mutY. ruckeri biotype 2. However, non-motile isolates were genetically grouped into the same group of motile strains strengthening the theory that biotype 2 has evolved from related motile Y. ruckeri strains (Wheeler et al., Y. ruckeri variants could be forced by factors extrinsic to the population such as resistance to antibiotics or vaccination.No evidence for genetic differentiation was obtained in this study to explain the emergence and spread of Y. ruckeri motile to non-motile isolates being recovered from disease outbreaks could be due to vaccine induced strain replacement (Martcheva et al., Y. ruckeri cases in Europe and USA, as well as the emergence of virulent motile isolates belonging to serotypes O1b and O2b in South America could be associated with this evolutionary change.Selective pressure induced by intensive vaccination could cause changes in phenotypic and immunogenic properties, which can cause outbreaks in vaccinated fish. The observed change from Y. ruckeri was supported by the positive correlation between genetic and geographic distances among strains and populations. The lack of a total geographic structure could be caused by similar nucleotide diversity across spatial scale among the largest subpopulations of USA, Europe and Peru. Nevertheless, geographic isolation of Y. ruckeri haplotypes was evidenced in Chile, Canada, and Denmark, which may have epidemiological implications due to differences in clinical outcomes associated with specific genotypes.Few studies have addressed questions of phylogeographic structure and dispersal limitation in bacteria on a truly global scale in discontinuos but globally common habitats (van Gremberghe et al., Y. ruckeri population, including spatial expansion, occurring theoretically at least thousands years ago, and more recent genetic divergence among regions. Furthermore, these results suggest that genetic divergence occurring in Y. ruckeri populations over last decades are independent, and in some cases isolated events, highlighting the usefulness of genetic studies in explaining the variations in the transmission and maintenance of ERM disease.In summary, this study provides phylogeographical findings of signature of ancient demographic processes in AB, CR, and JR conceived and designed the experiments; AB performed the experiments; AB and JR wrote the paper; CR critically revised the manuscript; AB, CR, and JR edited and approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Epinephelus striatus). We expected Nassau grouper to exhibit genetic differentiation among its subpopulations due to its reproductive behavior and retentive oceanographic conditions experienced across the Caribbean basin. All samples were genotyped for two mitochondrial markers and 9 microsatellite loci, and a subset of samples were genotyped for 4,234 SNPs. We found evidence of genetic differentiation in a Caribbean-wide study of this mass-aggregating marine fish using mtDNA , microsatellites  and SNPs , and identified three potential barriers to larval dispersal. Genetically isolated regions identified in our work mirror those seen for other invertebrate and fish species in the Caribbean basin. Oceanographic regimes in the Caribbean may largely explain patterns of genetic differentiation among Nassau grouper subpopulations. Regional patterns observed warrant standardization of fisheries management and conservation initiatives among countries within genetically isolated regions.To address patterns of genetic connectivity in a mass-aggregating marine fish, we analyzed genetic variation in mitochondrial DNA (mtDNA), microsatellites, and single nucleotide polymorphisms (SNPs) for Nassau grouper ( Effective management of marine populations requires knowledge of the extent of connectivity among locations sensu Nemeth Group spawning behavior exhibited in some families of reef fish may further restrict connectivity between localities. A spawning aggregation is a gathering of conspecific fish for the purposes of reproduction Epinephelus striatus) throughout the Caribbean Sea and western Atlantic Ocean makes it a suitable model species to investigate genetic subdivision in a mass-aggregating species. Nassau grouper typically aggregate to spawn for about one week per month over a period that lasts up to three months, in association with water temperature, the moon phase and maximal tidal amplitudes The broad geographic distribution of Nassau grouper (2). Given the decline of Nassau grouper across the region, our findings will have major implications for designing spatially explicit management and conservation strategies. While there are few obvious physical barriers to long-distance dispersal between most aggregation sites, if substantial genetic structure is observed among aggregations then protection of aggregation sites may be the only means by which 1) distinct subpopulations can be maintained and 2) local natural resource management authorities can effectively ensure the long-term sustainability of fisheries dependent on aggregating species.To address patterns of connectivity in a mass-aggregating marine fish we analyzed patterns of genetic variation in mitochondrial DNA (mtDNA), microsatellites, and single nucleotide polymorphisms (SNPs) for Nassau grouper. Limited genetic work on Nassau grouper has focused on a narrow subset of the species’ geographic range and used only a few microsatellite loci. These previous studies have failed to resolve any regional or local scale genetic differentiation between subpopulations All sampling protocols for this scientific study were approved by IACUC at the University of California Santa Cruz. We acquired a total of 620 Nassau grouper tissue samples (fin clips or muscle) from 19 sites across 9 countries, with samples collected between 1993 and 2013 , Table 1b. We amplified a 634 bp fragment of ATPase using primers L8331 and H9236 b using primers Gludgl and CB3H b datasets. ATPase and cytochrome b sequences were ultimately analyzed as concatenated sequences, for a combined total of 1,419 bp, because patterns of genetic variation observed in both markers were best explained by the same nucleotide substitution model.We genotyped samples for two mitochondrial markers: ATPase and cytochrome n = 8 per site. We then assessed phylogenetic relationships among sequences by generating a haplotype network using the software packages pegas We calculated molecular diversity indices including haplotype diversity (h) and nucleotide diversity (π) using Arlequin Hyporthodus acanthistius), following published PCR protocols e), observed heterozygosity (HO) and performed exact tests to detect deviations from the expectations of Hardy-Weinberg equilibrium (HWE) using Arlequin All samples were genotyped for nine polymorphic microsatellites previously designed for Gulf coney  tag libraries were created using the protocol described in Hohenlohe et al. SbfI restriction site were also filtered out. For all remaining fragments, the combined 12-bp sequence (barcode plus restriction site) was then removed. Final filtered reads (80 bp) were then utilized in a population genomic analysis executed in Stacks. Putative SNPs were selected that met the following criteria: minimum depth coverage of 6X, present in at least 80% of individuals and present in individuals from all four sampling localities.SNP discovery and genotyping were performed using modified Perl scripts . To test for evidence of regional genetic structure, we implemented an analysis of molecular variance (AMOVA) in Arlequin. We tested a four-region hypothesis based on genetically isolated regions identified in previous genetic studies in the Caribbean Sea a priori geographic assumptions about regional groups. Both methods utilized both the mtDNA and microsatellite datasets. First we used a computational geometry approach implemented in the software package Barrier a posteriori via AMOVA.We estimated global and pairwise estimates of FWe performed partial mantel tests to determine whether significant isolation by distance exists among localities for all three marker types. Because hierarchical population structure can introduce bias to isolation by distance analyses b in 395 individuals (Genbank KF706690–KF707475), resulting in a total of 89 haplotypes . Corrected haplotype diversity ranged from to 0.500 (site 13) to 0.954 (site 19).We sequenced a combined total of 1,419 bp for ATPase and cytochrome plotypes , Fig. 2.p>0.05, after Bonferroni correction). There was also no evidence of scoring error or null alleles. There was also no evidence of scoring error or null alleles. Significant departures from HWE were observed for 15 out of 171 exact tests (p<0.05). One locus (A108) departed from HWE in 6 of 19 populations, with other loci departing from HWE in four or less populations.All nine microsatellite loci were polymorphic in Nassau grouper. Microsatellite sequences were deposited to Genbank . The total number of alleles per locus per site ranged from 4 to 25 , microsatellites  and SNPs  , microsatellite  or SNP datasets .We detected genetic differentiation between subpopulations using mtDNA (F= 0.014) . Pairwisp<0.05). Regional differences accounted for approximately 18.09% of the variance in mtDNA and 0.10% of the variance in microsatellite datasets. Approximately 23.09% of the variance in mtDNA and 0.15% of the variance in the microsatellite datasets could also be explained by variance among samples within groups.We tested for evidence of regional genetic differentiation using AMOVAs . The fouST = 0.201, p = 0.026). These identified regions roughly confirm patterns seen from a priori testing of regional subdivision using AMOVAs.Three barriers to larval dispersal were identified using a computational geometry approach . The strk = 2, with one group comprised of three localities in Belize (sites 3–5) and another group comprised of all remaining sites . Microsatellite results indicate maximal variance among groups at k = 4. One group is comprised of 2 localities from Belize (sites 4 and 5), a second with the remainder of sampling localities in the Mesoamerican reef and central Caribbean , a third with all localities in the Bahamas (sites 12–14) and a final group with the remaining localities in the eastern Caribbean (sites 15–19).Results from the simulated annealing approach further support regional genetic subdivision among clusters of subpopulations . The mtDDespite the challenges of characterizing connectivity among populations in open marine systems, increased understanding of how populations are interconnected across geographic and political landscapes is invaluable for the development of effective management and conservation strategies. In the few genetic studies conducted to date on aggregating fishes in the Caribbean We described evidence for strong genetic differentiation among subpopulations of a mass-aggregating marine fish, the Nassau grouper, and detected barriers to larval dispersal in the Caribbean basin. Our findings contribute to the growing body of literature that demonstrates evidence of genetic subdivision among subpopulations of marine species in the Caribbean Sea The Caribbean Sea was once considered a single biogeographic province lacking phylogeographic barriers The strongest barrier (barrier A) detected in our dataset was located in the Bahamas. Much debate exists as to whether the Bahamas represent a distinct genetic enclave. In some genetic studies the Bahamas clustered well with the eastern Caribbean and islands of the Lesser Antilles Geographic localities in the central and eastern Caribbean showed varying levels of genetic isolation for Nassau grouper. The central Caribbean has been viewed as a region of mixing, receiving larval inputs from other regions in the Caribbean Of all potential barriers observed in our study, those in the Mesoamerican Reef are the least discussed in the literature Plectropomus areolatus]) in the Pacific Ocean demonstrated that 50% of larvae remain within 14 km of a given spawning site Isolation of the aforementioned regional clusters may be best explained by oceanography across the Caribbean. The Caribbean Current represents the strongest flow in the region, moving from the southern Lesser Antilles westward through the Yucatan strait. Mesoscale eddies form within this current and take anywhere from 6 to 10 months to move across the width of the Caribbean, challenging the notion that flow in the region is purely westward F-statistics estimated from the mtDNA versus nuclear markers suggests evidence of sex-biased dispersal or philopatry. While evidence from acoustic tagging studies suggests similar movement and migration patterns in male and female Nassau grouper While we believe that large-scale oceanographic patterns best explain regional patterns of genetic differentiation observed, there are other potential biotic and abiotic factors that cannot be discounted. A more than order of magnitude difference between We found evidence for strong genetic differentiation among Nassau grouper subpopulations. Our results suggest that the absence of physical barriers to dispersal and potential for long distance dispersal of larvae has not resulted in the genetic homogeneity of Nassau grouper subpopulations throughout the Caribbean Sea. Oceanography likely plays an important role in retaining larvae close to spawning sites at both local and regional spatial scales. Findings warrant additional detailed studies of ocean circulation patterns and dispersal kernels during the spawning period for a more direct investigation of the mechanisms driving genetic divergence among Nassau grouper subpopulations.Our results nonetheless yield important insights into the vulnerable status of Nassau grouper throughout its geographic range. Spawning aggregations do not withstand heavy and unmanaged fishing, and are not known to reestablish once they are fished out File S1(DOC)Click here for additional data file.


From domestication to the current pattern of differentiation, domestic species have been influenced by reticulate evolution with multiple events of migration, introgression, and isolation; this has resulted in a very large number of breeds. In order to manage these breeds and their genetic diversity, one must know the current genetic structure of the populations and the relationships among these. This paper presents the results of a genetic diversity analysis on an almost exhaustive sample of the sheep breeds reared in France. Molecular characterization was performed with a set of 21 microsatellite markers on a collection of 49 breeds that include five breed types: meat, hardy meat, dairy, high prolificacy and patrimonial breeds.Values of expected heterozygosity ranged from 0.48 to 0.76 depending on the breed, with specialized meat breeds exhibiting the lowest values. Neighbor-Net, multidimensional analysis or clustering approaches revealed a clear differentiation of the meat breeds compared to the other breed types. Moreover, the group that clustered meat breeds included all the breeds that originated from the United Kingdom (UK) and those that originated from crossbreeding between UK breeds and French local breeds. We also highlighted old genetic introgression events that were related to the diffusion of Merino rams to improve wool production. As a result of these introgression events, especially that regarding the UK breeds, the breeds that were clustered in the ‘meat type cluster’ exhibited the lowest contribution to total diversity. That means that similar allelic combinations could be observed in different breeds of this group.th century when wool-producing animals (Merino-like) were replaced by meat-producing breeds. These results are highly relevant to monitor and manage the genetic diversity of sheep and can be used to set priorities in conservation programs when needed.The genetic differentiation pattern of the sheep breeds reared in France results from a combination of factors, i.e. geographical origin, historic gene flow, and breed use. The Merino influence is weaker than that of UK breeds, which is consistent with how sheep use changed radically at the end of 19The online version of this article (doi:10.1186/s12711-015-0131-7) contains supplementary material, which is available to authorized users. The first major event was the use of Merino rams from a national flock that is still maintained at the Bergerie Nationale of Rambouillet. It was imported from Spain in 1786 and promoted by the Napoleonian administration to improve the French breeds’ wool quality  . Since tSeveral studies have investigated the genetic structure of sheep breeds based on molecular markers , 9–13 anOur aim was to investigate the genetic structure of sheep breeds in France using a near complete sample of the populations that are maintained over the country. For this purpose, 1826 individuals from 49 breeds were genotyped using 21 microsatellite markers, which allowed us to assess the genetic diversity of sheep breeds in France in relation to their history and conservation policy issues.Fifty-one populations belonging to 49 sheep breeds raised in France were sampled Table . These pCSRD0247, HSC, INRA49, McM42, MAF65, McM527, MAF0214, OaRFCB20). The 13 other microsatellites  were chosen from those available in the UE Econogen project [Twenty one microsatellite markers were used to perform the analysis. Eight of these microsatellites came from the French panel for parentage testing (r) higher than 0.2 were considered as potentially problematic for calculations [Ho), non-biased expected heterozygosity (He), effective number of alleles (Ae) and F-statistics [4.05.2 [4.07 [Ar) was computed with the rarefaction method using FSTAT 2.9.3.2 [3.5.1.2 [The presence of null alleles was tested using FreeNA  i.e. loculations . Allele atistics  were est [4.05.2 . GENEPOP.2 [4.07  was used.2 [4.07 . Allelic 2.9.3.2 . Signifi[3.5.1.2 . Breeds DR [4.5 [The matrix of Reynolds distances (DR ) was comDR  and usedDR  network DR [4.5 . A princDR [4.5 . The sigK clusters ranging from 1 to 10 and then equal to 15, 20, 25, 30, 35, 40, 45, 48, 51, and 55. For each value of K, 50 runs were performed with 1 000 000 iterations following a burn-in period of 100 000, under the admixture and correlated allele frequency model. Since consistency across runs seems to be an informative method for assessing species structure across breeds [K, using the LARGEKGREEDY algorithm. We selected a subset of runs that included the run with the highest number of similar runs (symmetric similarity coefficients (SSC) greater than 0.90) grouped with the corresponding similar runs. We used this subset to compute a mean Q-matrix. Breed assignment was performed as in Leroy et al. [K = 51. For clusters that comprised two breeds, runs were performed for K = 2 using only the breeds that were associated within the sub-cluster.Clustering approaches were performed on the 51 breeds using a Bayesian clustering procedure implemented in STRUCTURE  with thes breeds , we useds breeds  to estimy et al. . Animalspki be the average frequency of allele k in breed i, then, the average coancestry between breeds i and j is:The contribution of each breed to the diversity of the whole set of breeds was computed according to the method of Caballero and Toro . Let pkiGDT) is assumed to be the sum of the within-breed genetic diversity (GDWS) and the between-breed genetic diversity (GDBS):When several markers are used, coancestry is averaged over loci. The total genetic diversity  to 28 (locus UHJ616).For the complete dataset of breeds and markers, 357 alleles were identified. The average number of alleles per locus was 17 and ranged from nine (loci MNA), effective number of alleles (Ae) and allelic richness (Ar) are in Table He ranged from 0.48 in the Belle-Île breed (BeIl) to 0.76 in the Corse breed (Cors), with a mean value of 0.66 (±0.07). He were significantly higher in hardy meat breeds  and dairy breeds (P = 0.0005) than in specialized meat breeds, whereas differentiation between hardy meat and dairy breeds was not significant (P = 0.68). Ae ranged from 2.14 (BeIl) to 5.18 (Cors), with a mean value of 3.64 (±0.72). Ar values  varied from 2.96 (MeRa) to 7.72 (Cors), with a mean value of 5.6 (±1.05). FIS per breed ranged from −0.058 (Rava) to 0.117 (LaBr). The larger He, Ae and Ar values obtained for the Cors breed are probably related to a lower selection intensity than for other dairy breeds, linked to an extensive production system. After sequential Bonferroni correction, five breeds showed a significant deficit of heterozygotes for one locus, and one breed carried one locus with an excess of heterozygotes. Only one locus per breed combination out of 1071 was identified with a potential null allele  i.e. the McM42 locus in the LaBr breed. However, excluding this locus had very minor effects on FIS and He , which suggests that null alleles are not the main cause of significant FIS values (data not shown). Thus, we chose to conserve all 21 loci. Implementation of the pair-wise population differentiation test in the software GENEPOP 4.07 [FIS, FIT and FST values were equal to −0.001, 0.12 and 0.12, respectively.Heterozygosities, mean number of alleles . Likelihood values (Ln(P(D))) across runs reached a plateau when K was close to 45 [See Additional file K = 2, a group that comprised all the breeds from the UK , the Netherlands (Texe) and nine western French breeds  and the Mouton Charollais (MoCh) breed was clearly differentiated from a second group that included all the other breeds. As K increased, this first group segregated in two subgroups, one including the UK breeds and MoCh, MoVe, LaBr, RoHa, and BeIl breeds (i.e. SubGroup 1 or SG1) and the other including Texe, Avra, Cote, RoOu, and Char breeds (SG2).Bayesian clustering methods provided complementary information on the genetic relationships among the populations. For these, we used the uns Fig.  for K = K = 3 to 4, a third subgroup (SG3) that included IlFr, Boul, BeCh, Roma, Roov, and MeRa breeds was separated from the second group. As K increased (3 to 10), the breeds in SG3 clustered together. However the Mérinos de Rambouillet breed (MeRa) and the Île-de-France breed (IlFr) separated at K = 7 and K = 10, respectively [See Additional file K increased to 5 i.e. SG4 and SG5. SG4 included the MeAr, EsLM, and Mour breeds, the Southwestern breeds , two Alpine breeds (Griv and ThMa), one Mediterranean breed (Cors) and two breeds from the Massif Central . The last subdivision (SG5) included all the other breeds i.e. from the Massif Central, except for the Préalpes du Sud breed  with a differentiation pattern changing as K increased.From sed 3 to 0, the brK = 51, 41 breeds were assigned to a private cluster, i.e. they were primarily associated to the cluster that clustered the largest number of animals that belonged to the breed. For the three breeds LaBr, MoNo, and Mour, each one was associated with two clusters that consisted mainly of individuals that belonged to the same breed, and these pairs of clusters were considered as private breed clusters. Four pairs of breeds shared the same cluster BlMa/RoOu, Hamp/Suff, MoCh/Sout, and Roma/Roov, respectively. Each pair of breeds was analyzed individually (data not shown) and, in each case, individuals of the two breeds were assigned in their own private cluster. In contrast, one breed, the Barégeoise breed (Bare), was not assigned to a specific cluster and all Bare individuals except two pairs were assigned to different clusters. Finally, excluding the Barégeoise breed, 90.1 % of the individuals of the 50 remaining breeds were assigned to their putative breed , regardless of the hypothetical breed structure tested. Two models of population structure i.e. breed types and geographical origin were investigated. The greatest variation among groups  was observed with the geographical model compared to the breed type model .In the hierarchical analysis Table , the “wiGDWS ranged from −0.002 (Cors) to 0.0034 (BeIl), while ΔGDBS ranged from −0.0038 (MeRa) to 0.0013 (Bare). The largest decrease in total gene diversity (ΔGDT) was observed when the Corse , Landaise  or Basco-Béarnaise  breeds were removed. In contrast, when the Roussin de La Hague (RoHa), Blanc du Massif Central (BlMa) or Belle-Île (BeIl) breeds were removed, diversity increased by 0.0016, 0.0014 or 0.0013, respectively.Contributions to the genetic diversity are in Table Investigating the genetic structure of sheep breeds that are raised in France, using an approach based on their geographical origin and not the regions where they are currently raised, provides interesting insights into the recent history of sheep breeding in France.SG1 and SG2 were influenced by genetic introgression from UK breeds. SG1 includes breeds of French  and UK origins  related to Down meat breeds (SG1). In the SG2 group, for some breeds , introgression of former UK Longwool breeds may still have a dominant influence on population clustering, since they cluster with the Texel breed, which has a Dutch origin and is also considered as genetically similar to the Longwool breeds [SG3 group show that they are related to the extensive use of Merino rams at the end of 18th and beginning of the 19th century (“Merinization”) to improve wool production [SG3 includes Mérinos de Rambouillet (MeRa), which is the breed that was originally used for merinization in France, breeds  that were created by crossing MeRa with UK Longwool breeds such as the Dishley breed, and the Romane breed (Roma), which is a recent breed that was created by crossing the Berrichon-du-Cher (BeCh) and Romanov (Roov) breeds, Romanov being also included in the cluster. Three other breeds of Merino origin, i.e. the current Merino hardy meat breeds  and the Mourerous breed (Mour), are clustered in another group (SG4). All other breeds, including hardy meat or dairy breeds that originate from the south of France, are clustered according to two main geographical origins, namely South West (Pyrénées) of France for cluster SG4 and Massif Central for SG5. Overall, the results from the Bayesian approach are consistent with what is known on the history of introgression events that took place in French sheep populations during the 19th century [SG3 group may appear artificial since it aggregates breeds that have been influenced by Merino and Romane (Roma) breeds (see above). Genetic drift and founder effects within the French Romanov breed (Roov) together with the small number of sampled Romanov individuals, may explain why this breed clustered within the SG3 group. Neighbor-Net  was consistent with that reported in previous studies on sheep breeds . He. HeFST e , could not be assigned to any specific cluster. The relatively recent creation of this breed (beginning of the 20th century) as a sub-population of the Lourdaise breed (Lour), with a flock-book that started only in 1975, and the former use of crossbreeding with several breeds [He as well as the high rate of misassignments. When the Barégeoise breed and the breeds that are considered as historically close (AuCa and Lour) or frequently used in crossbreeding (BeCh and Tara) were analyzed independently, they were each assigned to a private cluster, with Barégeoise individuals showing more heterogeneity (data not shown). Using a larger number of markers would probably improve the assignment results and allow to register individuals that lack a known pedigree within a given selection nucleus.Among the applications of this study for breed management, our results on breed assignment  confirm that each breed constitutes a rather homogeneous genetic group. Even the four subpopulations from the Lacaune breed  that have been subjected to different selection programs for about 40 years, appeared relatively well differentiated Fig. . Many ofl breeds  explainsHe and various diversity components. This correlation was negative with ΔGDWS (r = −0.99), positive with ΔGDBS (r = 0.87), and negative with ΔGDT (r = −0.62), which indicates that breeds with a high diversity level contribute more to total genetic diversity. It is interesting to note that the three breeds with the largest contribution to total diversity , i.e. with the most negative ΔGDT, showed a high level of heterozygosity, as expected, but also shared a similar genetic background according Neighbor-Net and Structure methods. Two of these breeds are local breeds (Cors and BaBe) and the other (Land) is a rare breed. The five breeds with the lowest contribution to total genetic diversity (i.e. the highest ΔGDT) also showed a low genetic diversity and were related either to Down  or Longwool  genetic groups , we could observe a gain of total diversity  which is not sufficient to preserve this breed’s genetic variability in case of a disease outbreak. The same recommendation is made for the patrimonial breed, MeRa, which has a level of heterozygosity of only 0.50, which is expected for a breed that has been inbred for over 200 years.The last group of breeds includes rare breeds. Clearly, the Land breed stands out by its high contribution to the total genetic diversity and our recommendation is to secure the existing conservation program. For instance, there are only five rams stored in the French national Cryobank (However, regardless of our recommendations based on this work, the French Minister of Agriculture does support a global conservation of French sheep breeds. All these breeds are undergoing a selection or a conservation program, and all except MeRa are bred mostly by farmers for production. Therefore, our results rather than being used to prioritize which breeds to protect should be used as a tool to help the breeders to manage their populations.th century and the beginning of the 20th century [The genetic structure of French sheep breeds was shaped by reticulate evolution that involved both genetic drift and several introgression events, which correspond to similar patterns identified in Italian sheep breeds  or other century , which rConservation approaches could be applied to a larger number of breeds to assess conservation priorities. However, conservation issues cannot be reduced only to the analysis of genetic diversity and within- and between-population contributions. Other considerations, such as genetic structure and admixture patterns , or soci