Picea abies in Quaternary has affected its host-associated herbivorous beetle—Monochamus sartor. By using microsatellite markers accompanied by the geometric morphometrics analysis of wing venation, we have revealed the clear geographic structure of M. sartor in Eurasia, encompassing two main clusters: southern (Alpine–Carpathian) and eastern (including northeastern Europe and Asia), which reflects the northern and southern ecotypes of its host. The two beetles’ lineages probably diverged during the Pleniglacial  when their host tree species was undergoing significant range fragmentation and experienced secondary contact during post-glacial recolonization of spruce in the Holocene. A secondary contact of divergent lineages of M. sartor has resulted in the formation of the hybrid zone in northeastern Europe. Our findings suggest that the climatic oscillations during the Pleistocene have driven an insect-plant co-evolutionary process, and have contributed to the formation of the unique biodiversity of Europe.During the Last Glacial Maximum in the Northern Hemisphere, expanding ice sheets forced a large number of plants, including trees, to retreat from their primary distribution areas. Many host-associated herbivores migrated along with their host plants. Long-lasting geographic isolation between glacial refugia could have been led to the allopatric speciation in separated populations. Here, we have studied whether the migration history of the Norway spruce  Moving glaciers have forced many plants and animals to retreat from their primary distribution areas. When the glaciers retreated, the species started the recolonization of the previously inhospitable areas. In many taxa, the long–lasting geographic isolation that prevented or limited the gene flow resulted in a deep genetic divergence of isolated populations which might have finally led to the formation of new speciesPicea abies (L.) H. Karst) may serve as an excellent example. This tree species is the host for almost four hundred different invertebrates10. Some of them are obligatorily associated with spruce, and therefore their evolutionary history is supposed to be tightly associated with the history of their host plant.Changes in the distribution ranges of many plant species caused by the Quaternary climatic oscillations also had profound implications for other associated organisms, including herbivorous fauna. This co-dependence might be particularly noticeable in the case of woody plants, which constituted hosts for a large number of herbivorous insects. The Norway spruce 14. Nevertheless, northern and southern spruce ranges are currently separated by a “spruceless zone” running through the Middle–Polish Plains14. The two ecotypes exhibit deep genetic divergence14, and also differ morphologically and phenologically17.The phylogeography of Norway spruce is well-studied, and supported by both molecular and pollen data22. However, conclusions from these studies are inconsistent. The oldest study based on isozyme analysis and the COI mitochondrial marker suggested a significant effect of the Norway spruce glacial history on the genetic structure of Ips typographus 19, whereas similar research based on nuclear microsatellite markers showed the homogenous genetic structure of I. typographus in Europe18. In contrast, recent comprehensive studies based on a multilocus genetic approach provided strong evidence for the occurrence of genetically distinct groups in I. typographus and Pityogenes chalcographus  corresponding to the northern and southern spruce ranges22.The Norway spruce is, therefore, an excellent model to study how past range fluctuations have affected the evolution of its host–associated herbivores. So far, only a few studies aimed at exploring this issue have been conducted on bark beetles21. This may be particularly true for bark beetles (Scolytidae), which are characterized by their considerable dispersal abilities and high demographic fluctuations. Bark beetles are relatively small insects that can be carried by the wind over tens of kilometres23, and the crossbreeding of individuals from distant populations may overwrite original patterns of variation in a short time21. Moreover, the rapid population declines following outbreaks may have led to the loss of rare alleles, which may have ultimately resulted in low genetic diversity18.It should be noted that in some cases, patterns of genetic variation may be more influenced by the species’ life–history traits, rather than by past migration routesMonochamus Dejean, 1821 (Coleoptera: Cerambycidae) seem to be more suitable model organisms for comparative phylogeographic studies than bark beetles. They are too heavy for wind dispersion, and thus, their long–distance migration is naturally limited; the longest recorded distance for a single flight of Monochamus sartor  on a flight mill was 3.1 km24. Furthermore, the development of M. sartor immature stages lasts at least one year, and therefore, their populations are not a subject of such rapid demographic fluctuations such as those known in bark beetles. Moreover, several Monochamus species were successfully used in recent phylogeographic studies29, which pointed to the significant role of glacial events in the shaping of a genetic structure in some Monochamus species27.For several reasons, sawyers M. sartor within the vast part of a natural distribution range of its host tree, the Norway spruce. This will make it possible to investigate whether the past migration of the host in Quaternary has affected the genetic and morphological structure of its associated herbivore species.The main aim of this paper was to describe the genetic structure and morphological variation of the sawyer beetle M. sartor was studied only with mitochondrial COI sequences29, and the results of this study suggest low but significant divergence between populations inhabiting northern and southern spruce ranges. However, mtDNA sequences provide incomplete data on the phylogeographic structure due to their maternal inheritance and susceptibility to lineage sorting, branch length stochasticity, and to introgression across taxonomic borders32. For this reason, we used nuclear microsatellite markers along with the geometric morphometrics approach to analyze both genetic and morphological variations between populations of M. sartor within the whole Palearctic range of the species—from the Western Alps, through Central and Northern Europe, to Russian Siberia and Japan. Such an approach allowed for a reliable assessment of gene flow, and potential hybridization between Alpine–Carpathian and Asian populations of the beetle. Finally, taken together with a phylogeographic data on the Norway spruce, our study aimed at shedding light on the evolutionary co-dependence between M. sartor and its primary host—the Norway spruce.So far, genetic variability in In total, we subjected 210 samples to microsatellite genotyping. However, we obtained complete genotypes with no missing data for 161 of them (76.6%), and the results presented below are based on these samples only. We detected 3–12 alleles per locus and 23 to 32 alleles in total per region. Measures of microsatellite variation in the three assumed regions are given in Table According to INEST results, the frequency of null alleles and genotyping failure rates were negligible for all loci. Among six studied microsatellite loci, one locus (Mon_08) showed a significant departure from the Hardy–Weinberg equilibrium in the Alpine–Carpathian population, while there were four such loci  in the northeastern European and Asian populations, indicating that there may be a more complex population structure in these regions. We detected no significant linkage disequilibrium between any pair of loci within the three regions.FST between the Alpine–Carpathian and northeastern European regions was moderate and highly significant  yet still highly significant , which may be a signature of admixed ancestry. Unfortunately, because samples with a higher q have wide confidence intervals in all but one case, covering a range from zero to one, it is difficult to indicate them as clear evidence of admixture between lineages. Similarly, 13 out of 48 individuals from northeastern Europe had q < 0.9, which could be an indication of admixture from M. s. sartor. Again, wide confidence intervals meant that a straightforward interpretation of these values as proof of hybridization between subspecies could be misleading; however, four samples had q significantly smaller than one. Asian samples, all of which had q not significantly different from one, can undoubtedly be included in the M. s. urussovi cluster.Most individuals sampled in these respective regions had an overwhelming majority of their ancestry assigned to the genetic cluster representing a given subspecies Fig. b. From tSimilarly to STRUCTURE, the DAPC results fully supported the separation of the Alpine–Carpathian and Asian populations, although significant overlap occurred between samples from Northeastern Europe and Asia Fig. . The oveM. sartor was the one that assumed the hybrid origin of the northeastern European population, i.e. scenario 2 . According to the estimates, the Alpine-Carpathian population has a lower effective size compared to both the Asian and the northeastern European population Table . InteresM. s. sartor had the same Ne as ancestral population) appeared to have the highest credibility with the posterior probability of 0.48 . The second-best scenario was Scenario 1 , with the posterior probability of 0.31 . Under the most likely scenario, the current Asian population has an effective size of 228,000 and is significantly larger than the ancestral population. On the other hand, the Alpine-Carpathian population is characterized by the effective size of 53,800 and reflects no signs of population size change since its divergence. Under the assumed mutation rate, the divergence event took place 41,000 generations ago.In the case of mtDNA among tested scenarios Fig. , ScenariM. sartor females than in males .There was no significant difference in wing size between populations  and the interaction between population and sex was also non–significant .Hind (metathoracic) wings were found to be significantly larger in M. sartor differs significantly between populations  and sexes . The effect of the hind wing size on wing shape was also significant . The highest morphological difference in wing shape was observed between Alpine–Carpathian and Asian populations  was found between the Alpine–Carpathian and Asian populations. The slightly smaller difference was observed between the Alpine–Carpathian and northeastern European populations (MD2 = 4.24). The northeastern European population was more similar to the Asian population  population. The differences in hind wing shape between populations of M. sartor from the Alpine-Carpathian and eastern range were rather small and difficult to observe by eye; however, they can be found in particular in wing veins located near the wing folding line  = 37.36 P < 0.001, McFadden pseudo-R2 = 0.26 for model with STRUCTURE q- value as a dependent variable; χ2(1) = 40.91, P < 0.001, McFadden pseudo-R2 = 0.27 for model with DAPC q-value as a dependent variable; note that interpretation of McFadden pseudo-R2 differs from interpretation of regular R2 from linear model, and 0.2–0.4 indicate excellent model fit34).The probability of assignment to the eastern cluster based on hind wing venation showed a good agreement with M. sartor in the Palearctic realm, encompassing two main clusters: southern (Alpine–Carpathian) and eastern (northeastern Europe + Asia). However, the potential hybridization zone was found in northeastern Europe. The geographic variation of the species appeared to correspond well to the genetic patterns found in its host—the Norway spruce14. Moreover, our results illustrate that there is an ongoing gene flow between the southern and eastern ranges, or it has occurred in the past. An analysis of the demographic history of M. sartor provided the best support for the scenario involving the hybrid origin of the northeastern European population. Furthermore, our results showed that two important evolutionary events of M. sartor: its divergence into two lineages and its secondary hybridization  and those from northeastern Europe and Asia37. The main differences are in the structure of dorsal setation on the apical third of elytra, which is denser in specimens from northeastern Europe and Asia36. However, according to the first quantitative analysis of morphological variation in M. sartor, specimens from northeastern Poland were found to exhibit intermediate traits between those from southern Europe and Russian Siberia, which led the authors to the conclusion that they might be hybrids formed after the secondary contact of their host plant in the Holocene37. A recent study based on the analysis of COI mtDNA sequences indicated that M. sartor populations from southern Europe and those from northeastern Europe and Asia belong to distinct mitochondrial haplogroups29. However, the level of divergence between them was found to be weak, which pointed authors to the suggestion that they split into two subspecies very recently, possibly at the end of the Pleistocene glaciations29. Nevertheless, in the previous study, limited genetic data did not allow for the verification of the hypothesis about the hybrid origin of the northeastern European population or to confirm the genetic flow between populations. Hence, more research involving nuclear DNA markers were strongly suggested29.The status of the regional populations of M. sartor. The results of all conducted analyzes, including STRUCTURE, DAPC, and morphometry, fully supported the separation of the southern (Alpine–Carpathian) and eastern range of the species. Moreover, the confirmed existence of gene flow between Alpine–Carpathian and eastern cluster suggests that those subgroups should not be considered separate species, at least with regard to the generally accepted biological definition of the species. Nevertheless, the existence of a clear genetic divergence confirmed by both mitochondrial and nuclear DNA markers, external morphology, and some aspects of ecology, supports a recent change of the taxonomic status36 where two subspecies: M. s. sartor inhabiting the Alpine–Carpathian range, and M. s. urussovii associated with the eastern range, were distinguished.Here, based on nuclear DNA markers and comprehensive morphometric analysis, we provided strong evidence on the existence of two geographic clusters within the native Palaearctic range of M. sartor has most likely diverged into two lineages relatively recently, about 41,000 generations ago  as stepping stones during the post-glacial recolonization, which can explain why the secondary contact of the beetle’s populations could have happened earlier than the secondary contact of the Norway spruce.The analysis of demographic history illustrates that ago Fig. . Given tion Fig. . Due to M. sartor from northeastern Europe and Asia than between samples from northeastern European and the Alpine–Carpathian population, despite the geographic distance between northeastern Europe and Asia being markedly larger than the geographic distance between northeastern Europe and Alps or the Carpathians  in the Alpine–Carpathian region rather than in the boreal range of the species (northeastern Europe and Asia), which suggests that recolonization of this area took place at high population densities; hence the population of M. sartor from the eastern range has no signs of a significant bottleneck effect. The same conclusion was found for its host—the Norway spruce, where genetic diversity of the northern  range was markedly higher than in the southern Alpine–Carpathian region, leading to the conclusion that the Russian refugium had once occupied a large area12. Our data suggests higher levels of gene flow from southern populations to the northeast than in the opposite direction, which is consistent with the postglacial migration patterns of the Norway spruce, where the southern recolonization wave was found to be markedly more expansive40.Both genetic and morphological data showed significantly lower divergence and a larger overlap between samples of ans Fig. a. These 42. In the presented study, we found a good agreement between morphometric and molecular methods in distinguishing M. sartor subspecies. Similar agreement was also found in the case of other insects44. Although microsatellites are more powerful than morphometry, they are not always developed for a particular species. Moreover, their cost is considerably higher in comparison to morphometry. We have started our study with measuring a smaller sample of M. sartor and found an interesting pattern of shape variation37. This study allowed us to confirm the morphological data about the differences between populations and to describe them more precisely. Morphological analysis can be considered as an easy to use and inexpensive exploratory tool allowing for the detection of interesting patterns. It should be noted, however, that not all differences in shape need to be genetically determined. In many species, including M. sartor, there is significant allometry—relationship between shape and size. In this situation, appropriate statistical tools should be used to analyze various sources of the shape variation.Replacing the simple linear measurements with geometric morphometrics which involves coordinated landmarks placed on homologous morphological structures, has provided new perspectives in studies on taxonomy, paleontology as well as developmental and evolutionary biologyAlthough the six genetic markers provided enough data to disentangle subspecies, it appeared to be insufficient for the genetic assignment at the individual level, at least for some individuals. For this reason, we were not able to estimate precisely the rate of hybridization between subspecies. The limited power of markers also had an impact on the quality of estimates of demographic parameters derived from the ABC approach, despite relatively robust conclusions regarding the scenario of recent species evolution.A large effective population size is difficult to estimate precisely because it is inversely proportional to molecular signatures of genetic drift. In the case of coalescent–based methods, the same applies to time which is measured in terms of effective size. In addition, the ABC approach requires the assumption of a mutation model (including mutation rates), which may have a great impact on the estimated value of parameters. Taken together, the limited power of markers and the inherent properties of the ABC method used in this study caused poor–quality estimates of the effective size and times to the divergence or split of the study populations. Therefore, in order to better characterize the recent evolutionary scenarios, future studies should focus on high–throughput molecular methods.M. sartor could be the artificial planting of P. abies outside its native range. Such artificial spruce plantations have already occurred in some parts of the “sprucless zone” running through the Middle–Polish Plains14. Although M. sartor has limited dispersal abilities, the scattered artificial plantations of spruce can potentially serve as a stepping-stone habitat during the population spread26, and consequently lead to the hybridisation of the Alpine–Carpathian and northeastern European populations. Dispersal of this species might also be affected by the artificial relocation of individuals with infected wood. It is widely known that premature stages of wood-boring beetles (e.g. bark beetles and longhorn beetles) can survive a long time in fresh timber or even in manufactured wood, and start to spread rapidly after reaching new optimal habitats45. Nevertheless, our data showed that both divergence and secondary contact of M. sartor lineages took place well before the forest management began.One of the factors that might potentially affect the geographic structure of M. sartor, there are still some questions that need to be addressed in the future. Firstly, the application of more sophisticated high–throughput molecular methods will allow for a more reliable estimation of both divergence time and gene flow between the populations. Furthermore, many studies on closely related species highlighted the role of altitude in Monochamus radiation28, however, our sample cover did not allow for the testing of the same hypothesis in M. sartor. Therefore, more samples from the two sides of Alps and Ural chains should be analyzed in the future. It was shown that both geographic barriers and glacial events shaped the complex geographic structure of many tree-feeding longhorn beetles in the Far East, especially in the Japanese Islands48. More samples from this region will allow for the investigation on how the aforementioned factors have affected the genetic structure of M. sartor at the eastern border if its distribution. It is also still not fully understood whether the observed morphological difference  between M. sartor populations have genetic or rather environmental origin. Therefore, common garden experiments with an artificial hybridization of M. s. sartor and M. s. urussovii might provide interesting insights into the origin of the observed morphological patterns, mechanism of introgression, and the fitness of the hybrids. Lastly, the current climate change and related spruce decline observed in many regions of Europe provides interesting opportunity to study the genetic dynamic of M. sartor metapopulation under the rapid climatic and ecological change.Although our study provided new and interesting insights into the evolutionary co-dependence between the Norway spruce and its herbivore—M. sartor is a medium size (up to 34 mm body length36) sawyer beetle. Larval development usually takes place in the wood of weakened or recently dead spruces P. abies which is the species’ primary host plant, and rarely in several species from the genus Abies Mill, Pinus L., and Larix Miller49. Based on published data from eastern Russia, occasionally this species may also develop in some tree species from the genus Betula L., but the record needs further confirmation50. The range of the species coincides roughly with the spruce range in Eurasia   and M. s. urussovii  36. Recent morphological studies suggested, however, a possible gene flow between M. sartor subspecies during the potential secondary contact in the Holocene, as individuals from northeastern Poland had intermediate morphological traits37.The taxonomy of M. sartor subspecies over roughly the entire species range, from the Alps in the West to Japan in the East  (Omega Bio–Tek) following the manufacturer’s protocol.Monochamus galloprovincialis (Olivier 1795)52. Out of 12 primer pairs published for the congeneric species, we obtained the successful amplification of six loci in our M. sartor samples . All loci were amplified in a single multiplex reaction using the Multiplex PCR Kit reagent kit  according to the protocol recommended by the manufacturer. Details on PCR conditions, fragment separation and genotyping are described Supplementary Material 2.We used microsatellite loci originally developed for Since the genotyped material included both fresh insects preserved in ethanol and dry specimens from entomological collections, the individual samples differed in the success of the amplification, likely due to DNA degradation. In cases when one or more loci failed to amplify, we repeated the multiplex PCR for said particular sample up to three times. Finally, samples with missing data were excluded. Additionally, individuals that were identified as potential hybrids between subspecies (see the following paragraphs) were genotyped twice.53, departure from HWE using the exact test54 in ‘pegas’ ver. 0.1255, linkage disequilibrium using the standardized index of association, 56 in ‘poppr’ ver. 2.8.357. Multiple testing was corrected using the q–value method (q < 0.05) with ‘qvalue’ ver. 2.14.158.We assessed the potential presence of null alleles and genotyping failure rate using INEST ver. 2.1A), the effective number of alleles (Ae), allelic richness (AR) and observed heterozygosity (Ho), using ‘hierfstat’ ver. 0.4.2259. In addition, since AR may underestimate the genetic diversity in the presence of rare alleles, we attempted to extrapolate the allele accumulation curves of the less complete samples instead of rarefying the more complete samples to predict the real diversity considering the expected number of alleles undetected by the sampling effort. The analysis was performed in ‘iNEXT’ ver. 2.0.1961.For comparison of genetic variation, we calculated the number of alleles , we used the ΔK aproach62.To infer the population ancestry and potential gene flow between regions, we used STRUCTURE ver. 2.3.463 with ‘adegenet’ ver. 2.1.1 package64. Two–dimensional scatter plots were constructed to visualize the spread of the first two discriminant functions, both between and within assumed regions. Since most of the variability between regions was distributed along the first discriminant axis, we calculated the overlap between density distributions as a measure of the distinctness of the regions. The calculation was performed using ‘overlapping’ ver. 1.5.4 in R ver. 3.6.165.Since STRUCTURE relies on a specific population genetic model with restrictive explicit assumptions that may not be met in the studied beetles (i.e. populations at Hardy–Weinberg equilibrium and linkage equilibrium between loci), we also investigated population subdivision using discriminant analysis of principal components (DAPC)M. sartor demography, we performed an approximate Bayesian computation (ABC) analysis implemented in DIYABC ver. 2.1.066. We performed two groups of analyses, (1) using multilocus microsatellite genotypes, and (2) based on previously published29 cytochrome oxidase (coxI) sequences of mtDNA (MF327393–MF327421 and MF371175–MF371201). In both cases, we tested several scenarios. The choice of scenarios was based on the current knowledge of the evolutionary history of the Norway spruce, as well as the properties of markers (e.g. no recombination in mtDNA). The analyses are described in full detail in the Supplementary Material 2.To test different hypotheses of 66.In the case of microsatellite data, we considered four evolutionary scenarios Fig. . The folM. sartor originated from three geographic regions  were carefully dissected using precise tweezers, cleaned in alcohol, straightened with a small brush, and dry mounted between two microscope slides. Subsequently, high–quality images of each preparation were made by using a 10 megapixel digital camera equipped with a Ricoh 25 mm lens. The camera was mounted horizontally on a column stand. For all wing images, 23 landmarks  models were used to analyze the differences in wing size between populations and sexes, whereas mixed-design multivariate analysis of covariance (MANCOVA) models were used to analyze differences in hind wing shape in Statistica v. 13 software (TIBCO Software Inc.)70. The Mahalanobis distance was used as a measure of the morphological divergence among populations and to construct the tree of morphological similarity between populations by using the unweighted pair-group method with arithmetic mean (UPGMA) method in ‘phangorn’ ver. 2.5.5.71 package in R72. We also carried out discriminant analysis between both the eastern and southern ranges of M. sartor to obtain the posterior probabilities of the assignment of each specimen to one of two clusters.The coordinates of the landmarks were aligned using generalized orthogonal least–squares proceduresq–values and DAPC q–values, in both cases obtained for K = 2 without any prior information on sample location.We tested the agreement between probabilities of individual assignments to subspecies based on multilocus microsatellite genotypes and wing venation by fitting the fractional response regression model that is suitable for rates, proportions, and probabilities used as dependent variables. The model was specified as a generalized linear model (GLM) with the quasibinomial error structure and the logit link function. For genetic data, treated as dependent variables, we used two measures of the probability of subspecies assignment, STRUCTURE Supplementary information 1Supplementary information 2


The objectives of this study were to investigate the genetic diversity, population structure and relatedness among the five chicken populations of Bangladesh using microsatellite markers.A total of 161 individuals representing 5 chicken populations  were included in this study to investigate genetic diversity measures, population structure, genetic distance and phylogenetic relationships. Genotyping was performed using 16 selected polymorphic microsatellite markers distributed across 10 chromosomes.IS) and among (FIT) chicken populations were 0.04±0.02, 0.05 and 0.16, respectively. Analysis of molecular variance analysis revealed 88.07% of the total genetic diversity was accounted for within population variation and the rest 11.93% was incurred with population differentiation (FST). The highest pairwise genetic distance (0.154) was found between ND and AS while the lowest distance was between JF and AS (0.084). Structure analysis depicted that the studied samples can be categorized into four distinct types or varieties (ΔK = 3.74) such as ND, NN, and HI where AS and JF clustered together as an admixed population. The Neighbor-Joining phylogenetic tree and discriminant analysis of principal component also showed close relatedness among three chicken varieties namely AS, HI, and JF.The average observed and expected heterozygosity, mean number of alleles and polymorphic information content were found to be 0.67±0.01, 0.70±0.01, 10.7 and 0.748, respectively in the studied populations. The estimated overall fixation index across the loci (F), heterozygote deficiency within (FThe results reflected that indigenous chicken of Bangladesh still possess rich genetic diversity but weak differentiation among the studied populations. This finding provides some important insight on genetic diversity measures that could support the designing and implementing of future breeding plans for indigenous chickens of Bangladesh. In fact, poultry is an integral part of rural households in the least developed countries around the world. There are about 255.31 million chickens in commercial and subsistence production systems in Bangladesh ,5. All eIndigenous chickens are lower in productivity but are well adapted to adverse tropical climate and fluctuating nutritional conditions compared to exotic chicken. However, the preferences for free-range indigenous chicken might be attributed to typical pigmentation, taste, leanness, firmness, high protein content and suitability for special dishes ,6. The iMicrosatellites are widely used DNA markers for exploring genetic variation and phylogeny among populations of same species ,10. The Gallus gallus gallus and Gallus gallus spadiceus. However, blood samples were not categorized as per sub-species level for this study. All possible precautions were taken during sampling from unrelated individuals to prevent cross contamination. The blood samples were collected from wing veins by 3.0 mL disposable syringe and were stored either in vacutainer containing ethylene di-amine tetra acetic acid or in Flinders Technology Associates (FTA) classic card. The vacutainers and classic cards were then labeled with the name of chicken variety, age and sex of the birds and date of collection. The genomic DNA from whole blood samples and FTA card was extracted using both DNA isolation kit  and phenol-chloroform method.Institutional Animal Care and Use Committee (IACUC) reviewed the total experimental procedure and prior approval was obtained from IACUC for this experiment . In total, 161 unrelated blood samples were collected from 5 different chicken populations of Bangladesh: ND (n = 41), NN (n = 44), HI (n = 39), AS (n = 18), and JF (n = 19). The Native Chicken Conservation and Improvement Project of BLRI maintains ND, NN, and HI flocks and these birds were used for sampling. Besides, blood samples of AS chicken were collected from Bangladesh Agricultural University (BAU) research flock as well as from the farmers of Brahmanbaria district. JF sampling was performed from their breeding habitats, Chittagong Hill Tract regions (22.20 °N and 92.35 °E). According to Bhuiyan et al [http://www.thearkdb.org/using-arkdb/). Forward primers were labelled and modified with four types of fluorescence dye. The detailed information for primers used in this study is mentioned in Cho et al [Sixteen (16) highly polymorphic MS markers were selected from the list of markers previously reported in Cho et al , which who et al . MultiplFragment analysis was performed by capillary electrophoresis array using the Genetic analyser 3,130 xl . The genotyping reaction was performed in a 10 μL total volume including 1.0 μL of diluted PCR product, 10 μL of Hi-Di formamide  and 0.1 μL of the GeneScan-500LIZ size standard . The genotyping results were obtained using GeneMapper software ver. 3.7 .Ho, He) and fixation index (F) were computed using GenAlEx ver.6.5 [At first raw data were checked using MS tool kit (in excel) for detection of any genotyping error and null alleles. The evidence for significant deviation from population mutation-drift equilibrium (bottleneck) at 16 neutral MS markers in all populations was checked after Bonferroni correction, with 2,000 replicates under the two phase mutation model with 95% step-wise mutations (Ps = 0.95) using BOTTLENECK program [ ver.6.5 . Nei gen ver.6.5 . Pairwis ver.6.5 . Neighbo ver.6.5 . Genetic ver.6.5  with a b ver.6.5 .Ho, He, and polymorphism information content (PIC) were 0.669, 0.71 and 0.749, respectively. The ADL0259 marker had the highest number of alleles (16) while ADL0268 possessed the lowest number of alleles (6). The PIC values of locus were ranged between 0.598 (ROSS013) and 0.843 (MCW104) among the studied loci  and the lowest heterozygosity (0.64±0.03) possessed by ND and HI chicken populations. On the other hand, the average Nei’s unbiased He was 0.70±0.01 for all loci and varied between 0.68±0.03 and 0.70±0.03 in ND and NN chicken populations, respectively (F) was found 0.04±0.02 for all loci with a range between −0.02 ±0.02 (NN) and 0.08±0.03 (JF).The findings of the current study on MNA, Ho, and He are in concordance with Chinese, Ethiopian and Tanzanian chicken populations reported in several literatures[In total, 171 alleles were detected from 16 polymorphic markers . The 16 ied loci . No evid.06±0.45 . The lowectively . The ove598 ROSS0 and 0.84teratures. Howeverteratures reportedHo and He, Rudresh et al [Ho, and He between previous and present findings may be attributed with sample size, population structure, number of markers used, population specific alleles and/or allele scoring bias  and sampling strategy. The higher MNA, and mean allele richness values estimated based on the minimum sample size 17 and weighted over 16 loci indicated relatively higher genetic diversity in all populations and therefore, Bangladeshi chicken populations are more diverse. Markers with PIC values >0.5 and He values >0.6 provided high PIC for genetic diversity measures and were most reliable for population discrimination [He values than the truncated level, except for ADL0304. Taken together, the observed high heterozygosity value, PIC, Shanon’s Information Index  was found to be 0.046 considering all 16 loci and varied between −0.07 (LEI 0268 locus) and 0.14 (ADL0259 locus) (IT) and mean genetic distance (FST) were 0.16 and 0.12, respectively, over the 16 loci. Seo et al [IS, FIT, and FST values were 0.0093, 0.137, and 0.129, respectively and is comparable to the present study. Furthermore, Chen et al [IS and FIT values to be 0.002 and 0.18, respectively, in fifteen Chinese Indigenous chicken breeds and are comparable to the present study. The FIS represents a degree of non-random mating (deviation from Hardy-Weinberg equilibrium) where a positive value for FIS means selective breeding population. Only five  out of 16 markers showed a negative number. This result indicated the absence of random mating in the investigated chicken populations, which was supported by Faruque et al [IT value of the present study was due to excessive homozygosity existing in six MS markers .According to Weir and Cockerham  estimati9 locus) . The ove0.14 ADL09 locus  among the studied populations were found significant (p< 0.01) and the values ranged between 0.084 and 0.154   in Indian [ST value (0.1084) for Bangladeshi chicken varieties using mtDNA D-loop sequence analysis and strongly justified the results of this study as evidenced by population pairwise FST and AMOVA analysis. Altogether, the low genetic differentiation among the Bangladeshi chicken populations might be due to recent gene flow among themselves as well as common ancestor for constructing the populations.The populations pairwise distances (Fnd 0.154 . The higp<0.001) . Severaln Indian , Chinesen Indian  and Afrin Indian  and depin Indian  found pan Indian  who repointer se mating between AS and JF, a long tradition to the farmers, for increasing vigor and aggressiveness in AS birds . The phylogenetic tree also suggested the possible introgression of JF to AS breed and compatible with the previous mitochondrial DNA study [The Nei’s unbiased genetic distance matrices and dendrogram have shown that NN and ND were grouped into the same branch . The thrNA study . BesidesStructure program was employed to investigate the genetic structure of the 5 chicken populations of Bangladesh . The resST) that indicates poor genetic variability among the investigated populations. The phylogenetic tree and discriminant analysis of principal component analysis showed hilly chicken appeared to be genetically closer to Aseel and red jungle fowl. Structure analysis depicted a certain amount genetic admixture among the five studied populations where massive introgression was found from red jungle fowl to Aseel. Altogether, this study provides some important insight information for the first time on genetic diversity measures and population structure inferences of Bangladeshi chicken populations using microsatellite markers.The molecular study showed that indigenous chicken of Bangladesh still possesses rich genetic diversity. Analysis of molecular variance analysis revealed only 11.93% of the total genetic diversity accounted for between population differentiations (F


Meloidogyne javanica, were recovered. Morphological and morphometric studies were carried on the characters of females, males, J2s and perineal patterns. Species-specific Sequence Characterized Amplified Region (SCAR) primers confirmed morphological studies, and all these populations produced specific band in 670 bp using Fjav and Rjav primers. Genetic diversity of different populations was studied by Inter Simple Sequence Repeats (ISSR) and Random Amplified Polymorphic DNA (RAPD) markers implementing 10 primers for each approach. Results revealed a relatively low genetic diversity . The analyses of molecular variance indicated that the variation resulted from genotypic variations within region and variances among regions are 81% and 19% for RAPD, and 86% and 14% for ISSR, respectively. On the other hand, FST and Nm values are 0.140 and 1.535 for ISSR while these values are 0.188 and 1.079 for RAPD. So it can be concluded that there is a great deal of gene flow between populations due to the movement of plant material contaminated with nematodes, which results in high mixing between populations. ISSR and RAPD datasets failed to group populations according to their geographic region. There were no pathotypes or other intraspecific biological entities observed in the species.In order to investigate different species of root-knot nematodes associated with vegetable production in southern regions of Iran, 37 populations of the most predominant species,  Meloidogyne , which their population increase to damaging levels within a few seasons under susceptible crops, are so common in subtropical and tropical vegetable production that frequently they are taken to represent “nematodes” in general . The populations of M. incognita  Chitwood, 1949 and M. javanica  Chitwood, 1949 were the most recovered populations (more than 80%) from vegetable fields worldwide . Five species including M. arenaria  Chitwood, 1949, M. cruciani Garcia-Martinez, 1982, M. hapla Chitwood, 1949, M. incognita and M. javanica are the recovered RKN in vegetable production in Iran  of the genus  in Iran .Considering that morphological and morphometrical methods for the identification species of RKNs are considerably time consuming and there is a lot of ambiguity, using species-specific primers could be a rapid method for detection  , the sma species .M. enterolobii  with a random sequence and markers are considered to be uniformly distributed along the genome, whereas ISSR primers is based on the amplification of regions flanked by repeating sequences which found only between microsatellite loci. In the other hands, annealing temperature in RAPD is lower than ISSR .M. javanica collected from major vegetable growing areas in southern regions of Iran, using RAPD and ISSR markers.The aim of the present study is to infer the genetic intraspecific diversity among populations of M. javanica were collected from vegetables  and weeds of vegetable fields in several regions of southern Iran, during 2018 and 2019  and 4 μl proteinase K (600 μg/ml) were added, respectively. The samples were incubated at 65°C for 1 hr and at 95°C for 10 min. After incubation, the tubes were centrifuged for 2 min at 38,000 g and kept at –20°C for next uses.One full egg mass was put in 16 μl ddHPCR was performed containing 1 μl of DNA template, 8 μl mastermix (Amplicon Red), 1 μl of each primer (10 pmol) and 4 μl ddH2O to a final volume of 15 μl. Four set species-specific primers  were useM. javanica, 54°C for M. incognita, 61°C for M. arenaria, and 58°C for M. hapla) and 45 sec at 72°C, followed by a final step of 5 min at 72°C. All steps were repeated twice to insure the results. PCR success was visualized loading 4 μl of the PCR product into a 1.7% TBE buffered agarose gel  and visualized with ethidium bromide.The PCR amplification profile consisted of 5 min at 94°C, 35 cycles of 30 sec at 94°C, 30 sec at annealing temperature (64°C for 2O. Ten primers including (CCA)5, (GTG)6, (ATG)6, (GAG)4GC, (GACA)4, (GA)8C, (AC)8T, (CA)8G, (CTC)4GC, and (GAGA)4GG , and 8 μl ddHGAGA)4GG  were impGAGA)4GG .PCR ampliﬁcation reactions were programmed for an initial denaturation at 94°C for 3 min, followed by 35 cycles of 30 sec at 93°C, 90 sec at 48°C, 1 min at 72°C, and a ﬁnal extension of 10 min at 72°C. PCR success was visualized by loading 7 μl of the PCR product into a 1.7% TBE buffered agarose gel .2O. Ten primers , and 8 μl ddH primers  were use primers .For RAPD amplifications, the thermos-cycle profile was 5 min at 94°C; 35 cycles of 1 min at 94°C, 1 min at 35°C and 2 min at 72°C, followed by a final step of 5 min at 72°C. PCR success was visualized loading 7 μl of the PCR product into a 1.7% TBE buffered agarose gel .FST (Fixation index) and Nm (Number of migrants) used to calculate the differences of populations and amount of gene flow between populations. These two indices are inversely correlated, and by increasing fixation index, Nm is decreased  software package . The genecreased .M. javanica, M. incognita, M. arenaria, and M. hapla are 670 bp, 1200 bp, 420 bp, and 960 bp, respectively. The species-specific primers of M. javanica (Fjav and Rjav) yielded one unique fragment of approximately 670 bp in 37 populations, and no PCR product was obtained in the control template  for the four major species . Expectea region . Morphom5 primer of ISSR and OPAD10 primer of RAPD is presented in With the 10 random primers used in the RAPD analysis, a total of 180 bands were produced. All primers resulted in ampliﬁcation and different patterns were tested for population differences. The resulting gel electrophoresis for 19 populations for (CCA)M. javanica populations. The populations of Abdan and Bardkhon exhibited the highest level of genetic diversity , whereas the lowest value was shown in the populations of Jiroft . In 164 loci, 19.08% were polymorphic in all individuals of studied populations. The mean genetic variations of total indicated by H and I, were 0.080 and 0.115, respectively.In ISSR, a total of 164 loci, with average of 16.4 loci per primer, were scored. P, H, and I were used to estimate genetic diversity within the M. javanica populations with RAPD analysis were 0.043 to 0.162 (The Nei’s (1978) genetic distances (D) between pairs of to 0.162 . The lowto 0.162  and an iM. javanica populations according to their geographical region and host plants. The UPGMA trees generated using Dice coefficient for RAPD and ISSR are presented in The UPGMA trees obtained with RAPD and ISSR data showed some differences in tree topologies between calculations based on Dice and Jaccard. The positions of some populations are different by ISSR and RAPD, although the number of clades was consistent as both methods revealed four clades. None of these clades grouped FST and Nm for RAPD are 0.188 (P = 0.010) 1.079 however for ISSR are 0.140 (P = 0.010) and 1.535.In analyses of molecular variance analysis, percentages of molecular variance within and among populations were 11.36% and 2.62% for RAPD, and 8.26% and 1.33% for ISSR, respectively . FST andM. javanica was the most predominant species of RKN infesting vegetable fields and greenhouses in southern Iran. Although there was a slight genetic variation at the intraspecific level, populations of M. javanica generally showed a low level of genetic diversity. In the present study, surveyed Meloidogyne species were characterized using morphological and morphometric characters and confirmed with species-specific SCAR-PCR. The genetic diversity among populations of M. javanica was further explored by ISSR and RAPD markers.This is the first comprehensive study of RKN species in southern regions of Iran which demonstrated that M. enterolobii, M. javanica, and M. incognita was still challenging using various molecular techniques, except for SCAR-PCR , and it seems that these two markers may work independently  from each other. The PCR-based techniques using RAPD and ISSR markers were shown to be helpful for obtaining detailed information about the diversity that exists among M. javanica populations. Perhaps including more populations from distant geographic regions, and even different countries, provide better understanding of the genetic structure and gene flow of these nematodes. Further intra- and inter-specific genetic diversity of M. javanica may be explored by implementing next-generation sequencing (NGS) techniques.In this paper, the species-specific SCAR primer technique proved to be a powerful tool to distinguish the populations of the two widely distributed RKNs (


Studies on marine community dynamics and population structures are limited by the lack of exhaustive knowledge on the larval dispersal component of connectivity. Genetic data represents a powerful tool in understanding such processes in the marine realm. When dealing with dispersion and connectivity in marine ecosystems, many evidences show patterns of genetic structure that cannot be explained by any clear geographic trend and may show temporal instability. This scenario is usually referred to as chaotic genetic patchiness, whose driving mechanisms are recognized to be selection, temporal shifts in local population dynamics, sweepstakes reproductive success and collective dispersal.Pachygrapsus marmoratus that inhabits the rocky shores of the Mediterranean Sea, Black Sea and East Atlantic Ocean, and disperses through planktonic larvae for about 1 month. P. marmoratus exhibits unexpectedly low connectivity levels at local scale, although well-defined phylogeographic patterns across the species’ distribution range were described. This has been explained as an effect of subtle geographic barriers or due to sweepstake reproductive success. In order to verify a chaotic genetic patchiness scenario, and to explore mechanisms underlying it, we planned our investigation within the Ligurian Sea, an isolated basin of the western Mediterranean Sea, and we genotyped 321 individuals at 11 microsatellite loci.In this study we focused on the marbled crab We recorded genetic heterogeneity among our Ligurian Sea samples with the occurrence of genetic clusters not matching the original populations and a slight inter-population divergence, with the geographically most distant populations being the genetically most similar ones. Moreover, individuals from each site were assigned to all the genetic clusters. We also recorded evidences of self-recruitment and a higher than expected within-site kinship.P. marmoratus Ligurian Sea populations is the result of a combination of differences in reproductive success, en masse larval dispersion and local larval retention. This study defines P. marmoratus as an example of marine spawner whose genetic pool is not homogenous at population level, but rather split in a chaotic mosaic of slightly differentiated genetic patches derived from complex and dynamic ecological processes.Overall, our results suggest that the chaotic genetic patchiness we found in  Many theoretical and empirical studies have shown that, in marine populations, connectivity plays a fundamental role in population and metapopulation dynamics, community dynamics and structure, genetic diversity, and the resilience of populations to human impact –5. A comThe observed spatial genetic structure of marine species seldom fits models developed for terrestrial populations, such as the island or the stepping-stone models –9. In thEmerging evidences are showing that marine populations may be genetically structured over smaller spatial scales than was previously thought . These nUnderstanding the mechanisms which drive CGP is still a challenge in marine ecology. Researchers suggest four main alternative mechanisms to explain CGP , 27–29: First, natural selection may act on larvae in a pre- or a post-settlement phase, by means of severely fluctuating environmental conditions that could drive selection for locally beneficial alleles through differential survival of recruits , 30. CGPSecond, CGP may be driven by temporal variations in the cohorts of recruits with respect to the source populations, with juveniles that recruit in a given population possibly coming from different sources at different times. Seasonal or inter-annual changes in currents as well as asynchrony in spawning events across populations may operate a stochastic selection on planktonic larvae and favour recruits from different sources , 28, 35.Third, the high variance in reproductive success typical of marine organisms, known as sweepstakes reproduction, can also greatly contribute to reduce the effective size of local breeding groups and, consequently, it might explain the reduced genetic variation within cohorts of larvae and new recruits that represent the reproductive output of a minority of adult individuals  and markers: , 48, 50)markers: , 47, 49,markers: , 47, 49 P. marmoratus, the possible occurrence of a structure not related to geographic features at local scale, in order to depict a more defined CGP scenario and to ascertain the drivers underlying it. Following Pascual et al. [P. marmoratus life history traits make it a good candidate for local unpatterned population genetic structure. Adults are low-mobility benthic crabs with a restricted home range [The present study was specifically planned to assess, for l et al. , P. marmme range . The speme range .P. marmoratus individuals from the four sites and we genotyped them at eleven microsatellite loci. In comparison to previous studies [We selected four close sampling sites in an isolated basin of the Mediterranean Sea, the Ligurian Sea, to exclude from the analysis any subtle geographic barriers, such as variation in water temperature and salinity, that might have driven population structure at local scale. We sampled a total of 321  studies –49, we c studies . The hor studies .Fig. 1a = 25.41, p < 0.001), our data supported the hypothesis of null alleles for explaining these patterns. Thus, we corrected our dataset for null alleles following the INA method described in [The analysis performed with MICROCHEKER indicated an excess of homozygote at the four sites . Since we found a significant positive relationship between locus specific sample deviations from the expectations of Hardy-Weinberg equilibrium (HWE) and the number of individuals that failed to amplify at each locus , with number of alleles ranging from 3 (locus Pm-79) to 48 locus Pm-16). Relatively high levels of genetic variability were recorded at all sampling sites . Population assignment results indicated that individuals from all the four sites assigned to their own population with a probability always higher than 50% .Average pairwise relatedness based on the Lynch and Ritland estimator  for the P = 1.0), a weak but significant overall genetic differentiation among populations was recorded by F-statistics . The variation among populations corresponded to 1%, while within population variation exceeded 99%. The pairwise comparisons showed a significant differentiation only between LG and PM and LG and SM  suggested the presence of four distinct genetic clusters, as indicated by a rapid decrease of the Bayesian information criterion (BIC) values from K = 1 to K = 4 and a further minimal decrease for K > 4 Fig. Sa. The DAIn order to detect source-sink dynamics among our Ligurian Sea populations, we estimated recent migration rates using a Bayesian approach as implemented in BayesAss. The outcomes of the analysis showed that the recent migration rates between pairs of sites were always very low, except when LG represented the outgoing site Table . The proP. marmoratus is an example of marine spawner that exhibits local genetic heterogeneity not related to geography and patterns of chaotic genetic patchiness.It is well-known that several marine organisms with high dispersal ability can show much greater spatial genetic heterogeneity over short distances than expected –64. ThisP. marmoratus populations and cause a non-homogenous genetic pool at population level, which, ultimately, results in a mosaic of chaotic and slightly differentiated genetic patches. Another indication of chaotic genetic patchiness across the surveyed micro-geographic area comes from the slight differentiation among populations recorded by the Bayesian structure analysis, which found the geographically most distant populations to be the most similar ones from a genetic point of view.A weak evidence of population structure is detected by Fst statistics, but not confirmed by the exact test of population differentiation. The outcomes of the Bayesian structure analyses and the DAPC show the presence of genetically differentiated clusters  not related to geography. The clusters identified by both approaches do not match the original populations, since the individuals from each site are assigned to all the genetic clusters. Overall, these results suggest that dynamic ecological processes act on In recording genetic heterogeneity at local scale, we first assessed an inter-population genetic divergence not in line with the geographical distance among our populations. We then recorded the occurrence of multiple genetic patches within each population, since our analyses grouped our specimens according to genetic clusters that did not match the four native populations. This may indicate that the larval pool is not homogeneously mixing off shore, due to local ecological factors , or bioP. marmoratus is structured in few homogenous clusters in correspondence to the main phylogeographic barriers separating the Mediterranean Sea from the Atlantic Ocean and the Black Sea [P. marmoratus sampled along the Portuguese coast, detected a genetic heterogeneity not related to geographic gradients, which they explained by means of coastal hydrological events influencing larval fluxes. Fratini et al. [P. marmoratus, as already showed by Deli et al. [P. marmoratus populations of the Ligurian Sea.Across its wide distribution range, lack Sea . Converslack Sea , for P. i et al.  recordedi et al.  found poi et al. , Fratinii et al.  and Delii et al.  in descri et al. , since oi et al. , 45, 49,i et al. , 27–29, en masse larval dispersion [P. marmoratus populations from the Ligurian Sea could also be an indicator for a possible effect of natural selection acting on larvae. Indeed, the effect of post-settlement selection can be particularly relevant on P. marmoratus megalopae, which settle and grow into juveniles within the harsh and unstable intertidal zone characterised by strong daily and seasonal variations in salinity and temperature [The novel evidence of the present study, mainly due to our intensive sampling approach, is therefore the high occurrence of self-recruitment and within-site kinship at the target sites. This may be driven by active larval behavioural mechanisms favouring local larval retention to natal sites , 70. Selspersion , 73. Larspersion , 25, 74.spersion , 76. Theperature .Future directions in marine ecology should address the mechanisms that affect regional patterns of recruitment and the events that drive post-settlement selection at a local scale, and, ultimately, investigate how kin-aggregation benefits may outweigh the costs of inbreeding on a small geographical scale.P. marmoratus from the Ligurian Sea. In particular, the present study suggests that mechanisms such as differences in reproductive success (sweepstakes reproductive effect), en masse larval dispersion, local larval retention and post-settlement larval selection may act individually in driving CGP in marine populations. Yet, we cannot exclude a complex and synergistic effect, especially when they contemporarily occur in a certain species and in a determined geographic context.The observed presence of genetically differentiated clusters not corresponding to the native populations, coupled with a slight inter-population divergence not related to geography and a high percentage of individuals assigned to their own populations, strongly support a multiple set of drivers for the CGP observed in P. marmoratus is characterised by large breeding populations, sexual dimorphism towards larger males, high females’ fertility , and high dispersal potential. Moreover, natural populations of P. marmoratus are normally formed by individuals belonging to different generations and recruited during different events of settlements. We cannot therefore exclude that the genetic patchiness observed for these populations could reflect recruitment events from different source populations at different times, since the genetic patchiness in marine spawners is known to be ephemeral and temporally fluctuating [P. marmoratus should rely on the resolving power offered by genomics, which allow researchers to depict the effects of biotic and abiotic factors on population dynamics through a seascape genomic approach.In this intertidal crab, genetic drift and non-random mating can also be advocated as key determinants for local genetic heterogeneity, since ctuating . Furtherctuating , 80). InPachygrapsus marmoratus  is an intertidal crab belonging to the family Grapsidae . It is a dominant species in the supratidal fringe and at the eulittoral of rocky shores [P. marmoratus adults are relatively sedentary and are faithful to a small activity area [y shores . It is ay shores . P. marmity area . Thus, dity area . This spity area –84. Spawity area . This rhity area –87.P. marmoratus from four sites in the Ligurian Sea: Porto Mediceo of Livorno , Secche della Meloria , Le Grazie  and Riomaggiore  . Thermal profiles consisted of an initial denaturation step of 5 min at 94 °C, 35 cycles of 60 s at 94 °C, annealing for 45 s at 54–57 °C .Microsatellite alleles were checked for scoring errors due to stuttering, allele dropout and evidence of null alleles using Microchecker 2.2.3 . Since iwww.montpellier.inra.fr/URLB) to calculate allele frequencies corrected for null alleles following the INA method described in Chapuis and Estoup [Since the outcome of our analysis indicated the occurrence of null alleles, we used the software FreeNA  present in the microsatellite dataset, two clustering methods were applied: a Bayesian clustering approach  and a mK number of populations, ranging from 1 to 6, using a burn-in period of 20,000 iterations. We calculated the mean likelihood over 20 runs for each value of K using the correlated allele frequencies model, which provides greater power than the independent allele frequencies model, to detect distinct populations that are particularly closely related [K value with the highest ΔK, calculated by STRUCTURE Harvester, was then used as prior information to estimate the proportion of membership of each genotype in each of the K populations. Replicate runs for the same K were clustered and averaged to evaluate major clustering patterns using the CLUMPAK server [The Bayesian-model clustering method implemented in STRUCTURE 2.3.4  was used related , and est related . The K vK server . ResultsK server .K describing the data was identified using Bayesian information criterion (BIC) scores and the “find.clusters” function. In this analysis, the optimal K is expected to be associated with a low BIC score positioned along the BIC curve where the following BIC scores either increase or are only slightly lower than the chosen BIC value. To not overfit the discriminant function, we chose the optimal number of principal components for the DAPC using the “optim.a.score” function. The a-score captures the trade-off between the power of discrimination and overfitting using too many principal components in the analysis by measuring the proportion of successful reassignments of the DAPC analysis compared to K-means clustering (observed discrimination) and random clustering (random discrimination) [The DAPC analysis was performed using ADEGENET version 1.2.8  in the Rination) . We ran ination) .6 iterations with a sampling frequency of 2,000 and the first 1 × 106 steps discarded as burn-in. We used default setting delta values for allele frequencies, migration rates and inbreeding coefficients .In order to detect source-sink dynamics among our Ligurian Sea populations, we estimated recent migration rates using BayesAss 1.3 . Based oAdditional file 1. Dataset supporting the conclusions of this article (text file formatted as Genepop input).Additional file 2: Figure S1. Optimal number of clusters defined by Evanno et al. (2005) ∆K  and the Bayesian Information Content (BIC) value .Additional file 3: Table S1. Linkage disequilibrium among loci assessed for the totality of populations using FSTAT 2.9.3.2 (Goudet 1995). For each pair of loci analysed, the software computes a correlation coefficient r2 over the entire population and for each population. A threshold r2 value above 0.8 indicates a non-random association between the alleles present at two genetic loci . Significant P-values (after Bonferroni corrections at P < 0.001) are also reported.


Trifolium pratense L.) is a highly adaptable forage crop for temperate livestock agriculture. Genetic variation can be identified, via molecular techniques, and used to assess diversity among populations that may otherwise be indistinguishable. Here we have used genotyping by sequencing (GBS) to determine the genetic variation and population structure in red clover natural populations from Europe and Asia, and varieties or synthetic populations. Cluster analysis differentiated the collection into four large regional groups: Asia, Iberia, UK, and Central Europe. The five varieties clustered with the geographical area from which they were derived. Two methods (BayeScan and Samβada) were used to search for outlier loci indicating signatures of selection. A total of 60 loci were identified by both methods, but no specific genomic region was highlighted. The rate of decay in linkage disequilibrium was fast, and no significant evidence of any bottlenecks was found. Phenotypic analysis showed that a more prostrate and spreading growth habit was predominantly found among populations from Iberia and the UK. A genome wide association study identified a single nucleotide polymorphism (SNP) located in a homologue of the VEG2 gene from pea, associated with flowering time. The identification of genetic variation within the natural populations is likely to be useful for enhancing the breeding of red clover in the future.Red clover ( However, as we move towards a more sustainable agriculture policy, increased legume use is being encouraged, due to the recognition of their utility2. This includes increased production potential, especially in mixtures with grasses; environmentally friendly N input into grassland by virtue of their symbiotic N2 fixation; high protein content, and higher voluntary intake and thus better livestock performance2.Red clover is a forage legume, which is used primarily in temperate livestock agriculture. It declined in importance when industrially produced nitrogen fertiliser became available in the early to mid-20th century; but before that, it and other forage legumes were key to maintaining soil fertility, and providing high protein forage for ruminant livestock1. Many of the varieties currently on the market in Europe originate from a Mattenklee type of plant, with their growth habit characterised by tall upright stems. However, some natural populations show varied growth habits, characteristically with less dependency on the central crown and a more prostrate nature to stem growth. Under certain temperature and moisture conditions, stems of these prostrate plants are able to produce nodal root growth3. The genetics underlying the prostrate growth habit of such red clover ecotypes, as well as the latent disease resistance often associated with natural populations, is of considerable interest for breeding programmes, in terms of furthering the range of climatic and agricultural conditions suited to red clover growth and use4. When plants expand into new ecosystems they encounter new and diverse selective pressures6, which may lead to changes in growth habit, morphology, the partitioning of metabolic resources and disease resistance. This diversity in growth habit has enabled red clover to adapt to varied environmental conditions7.Red clover is a relatively newly domesticated species, and it was not until around 1000 years ago, that it was first intentionally grown in Southern Spain8, AFLP10 RAPD12 and SSR markers13. All of these studies reported high genetic diversity, and that within population diversity was larger than between populations. It is now possible to obtain large-scale genome wide variation in populations by using next generation sequencing (NGS) technologies. Genotyping by sequencing (GBS)14 has become a popular method with which to identify large scale variation in species both with and without a reference genome. The use of GBS has allowed researchers to identify thousands to millions of single nucleotide polymorphism (SNP) markers, which can be used to analyse genetic variation within and between populations, and facilitate the analysis and dissection of complex traits, especially those involved in adaptive selection. While the bioinformatics analysis is more challenging compared to arrays, the cost per SNP is much lower, at least in less intensely studied crop species such as red clover.The genetic diversity of natural and cultivated populations of red clover has previously been studied using methods of isoenzymesThe aim of the present work was to assess and analyse the genetic variation present in the accessions of the Genetic Resources Unit at the Institute of Biological, Environmental and Rural Sciences (IBERS). The relatively recent history of red clover cultivation and breeding, would lead to the expectation that differentiation between natural populations and varieties is likely to be small. We report here on the genotyping by GBS of 640 plants of red clover representing 70 natural populations from Europe and Asia and 5 modern varieties. These populations may represent a potential source of novel alleles, which could be used in breeding programmes to alter growth morphology and enhance traits such as disease resistance.15 as a reference, resulted in 264,927 SNPs across all 640 plants. Substantial filtering of the data (see SNP discovery in the Methods section), resulted in a panel of 12,577 robust polymorphic SNPs. In that process 10 samples were lost due to poor sequencing results. Of the 12,577 SNPs, 8,118 were mapped to the seven chromosomes, and the remaining 4,459 were located in unmapped scaffolds of the assembly. The data presented in the rest of this paper refer to the 8,118 SNPs mapped to the seven chromosomes. The SNPs were identified as transition or transversion SNPs . From these reads a total of 1,804,668 tags across all 640 plant samples were identified. The SNP analysis in Tassel v5.2, using the red clover genome assemblyThe 8,118 SNPs were used to assess the genetic relationship between the accessions according to the unweighted pair-group method of arithmetic mean (UPGMA) using the package Cluster. The change in slope angle  of the data was performed. The PCA plot Fig.  illustraK .Genetic diversity was evaluated according to the four groups identified by the hierarchical UPGMA analysis. This analysis showed that at the population level, there was more genetic diversity within the accessions than between them, as indicated by the Hes Table . In the HE Table . This waO and HE were also calculated for individual accessions. This data revealed no significant differences between the observed and expected levels of heterozygosity, as determined by the Goodness of Fit test  was performed to assess how much of the total genetic variance could be attributed to different hierarchical levels of division of the total population. The results are summarised in Supplementary Table Two main methods were used to identify outlier markers in genome scans for selection. BayeScan identified 74 loci and Samβada identified 1,020 loci. They had 60 loci in common spread across the seven chromosomes Fig. . Those lhttps://legumeinfo.org) and GO terms analysed in Revigo16 to assign biological process, cellular component and molecular function. Over half of these GO terms were assigned to a molecular function  terms. GO terms were collected from the genome browser  and Aa4038 (Finland) were all homozygous for the major allele for this SNP.During the experiment, there was considerable loss of plant material from the first full year to the second year , Aa4444 , Milvus, Aa4203 (Sweden) and Britta. Average plant width per accession ranged between 10–44 cm; the five widest accessions were in descending order Grasslands Broadway, Aa4443 , Aa4451 , Aa4525 (Iberia), and Aa4442 . To estimate the degree of prostrateness in the population a width:height ratio was calculated. A high ratio described those accessions as being wider than tall, and more prostrate. The ratio ranged between 0.09 – 0.57. The five accessions with the highest ratio were in descending order Aa4525 (Iberia), Aa4402 (UK), Aa4390 (Iberia), Grasslands Broadway, and Aa4523 (Iberia) Fig. .Figure 5The average number of stems per accession was recorded. The values ranged from 1 to 97. The six accessions with the most stems were in descending order Aa4397 (UK), Grasslands Broadway, Aa4399 (UK), Aa4403 (UK), Crossway, and Aa4525 (Iberia)  significantly higher than zero  (Table T = 0.29) and isoenzymes (HT = 0.29) in South American, Swiss, and American cultivars respectively30. Higher values were found with AFLP in Italian Red clover (HT = 0.43)10, and allo-enzyme analysis in Caucasian natural populations (HT = 0.35)8. Although the data indicated that there was no significant differences between the observed and expected levels of heterozygosity at the individual accession level, they were higher than the subpopulations in this study and HO was higher than HE  Table  is compa7. The environment, including longitude, latitude and altitude, may result in physiological challenges that in turn may lead to plant morphological and molecular adaptations32. Samβada indicated a strong correlation between longitude and adaptive SNPs, and indeed a regression of the first principal coordinate identified the same correlation  explained most of the variance. This was also evident in the genetic diversity analysis, in which H41. Breeding populations are typically small, and by their nature selected for uniformity for traits such as flowering time. It should be borne in mind that red clover breeding is a recent occurrence7, and is thus less likely to have had a major effect on allelic variation. LD is strongly dependent on recombination frequency and effective population size43, so the difference in rate of LD decay seen with the varieties versus the natural populations  and maize (r2 = 0.07)46. The results are also in line with what was reported previously for red clover15. However, as the extent of LD is very low in the whole panel of accessions used here, interpretation of differences should be treated with caution.Domestication and selective breeding would be expected to reduce allelic variation and genetic diversityVEG2 gene in pea . The VEG2 gene is an FD homolog that is essential for flowering and compound floral development17, and as such is a good candidate for further study and verification in other populations. This gene was also identified as one of the candidates potentially under selection  it is twice as tall.Vegetative growth analysis were the result of data from two time-points. They showed a variation in growth habit across the panel, especially in terms of width:height ratio Fig. . The PorBased on over 8000 SNP markers, a panel of European and Asian red clover accessions from the IBERS Genetic Resources Unit was divided into four groups according to UPGMA and structure analysis, and the diversity was strongly correlated to longitude. The varieties included in the panel were not distinguishable from the ecotypes in terms of their genetic diversity, and there was no strong evidence for a bottleneck during the breeding process. However, within two Iranian accessions the same region on LG7 was clearly identified as being under selection. Two other methods identified 60 outlier loci indicating signs of selection, but no single chromosomal region was highlighted. The high mortality rate we observed in many of the natural populations is most likely a result of them being unimproved and un-adapted to the growing conditions at IBERS. Nevertheless, this study has shown that some contain novel allelic diversity that could be a source of new variation with potential use in breeding programmes.A total of 75 accessions were used in this work. Of these, 70 were characterised as natural populations or ecotypes, originating from 16 countries in Europe, three from Asia and one from the Middle East Fig. . A furth50. The five varieties 51. Britta is a late flowering variety20 and has a degree of resistance to stem nematode7.The countries were allocated to their geographic regions according to The World Factbook and Eurovoc Table  was measured by Qubit™2.0, and 40 ng was used for PCR amplification. The PCR product was cleaned with magnetic beads, and the concentration measured by Qubit™2.0. The PCR amplification was repeated 3 more times. All of the PCR products were then mixed at equal concentration (10 ng µl−1) to form the final library, which was analysed in a 96-plex format with 125 bp single end sequencing using an Illumina HiSeq. 2000 NGS platform.DNA was extracted from 100 mg of fresh young leaf tissue using a Qiagen DNeasy extraction kit in a 96 well format. The DNA concentration was measured using a Qubit™2.0, and normalized to 10 ng µl52 and BWA53 were used in conjunction with the red clover genome15 in a reference based GBS pipeline to identify high quality SNPs within the populations. In the TASSEL5v2 pipeline, the quality of the SNP calling was set with the following parameters: 20 bp minimum and 64 bp maximum length; a Phred quality score of 20 was used ensuring a base call accuracy of 99%, or a 1:100 probability of incorrect base calling. All Phred scores in the sequences were at 30 (99.9%). There was a minimum cut off of 10 reads per SNP site, and the minor allele frequency was set to 0.05 to allow for heterozygote calling. For a SNP to pass into the final count, it had to be present in at least 80% of the genotypes. Finally, missingness was set to 0.1 per genotype. This ensured that genotypes with less than 10% of the SNP were excluded from the dataset. The data were analysed in R studio using a variety of packages54. Data re-coding and imputation of missing markers was implemented in the R package Synbreed55. The imputation was performed by random sampling from the allele distributions, with the minor allele frequency set to 0.05, and data missingness threshold to 0.2.TASSEL5v256. This package was also used to produce a dendrogram with phylogenetic relationships (termed relationship tree in the text). A principal component analysis (PCA) was performed using R, and coloured according to the derived clusters from the above analysis. To further identify delimitations in the population structure and to infer ancestry, STRUCTURE v2.357 was used with an unbiased Bayesian approach with Markov chain Monte Carlo (MCMC) clustering of samples. The data were assessed for K values ranging from 1 to 15 with burn-in and MCMC iterations set to 20,000 each. For each value of K, three replications were made. STRUCTURE harvester web v0.6.9458 was used to find the optimum K value for the population using the ΔK. This assigned the accessions to their genetic group. A total of 250 SNP were used per chromosome.Using all of the markers, the population was grouped into respective clusters by using UPGMA in the program Cluster59 was performed on the data using the R package Pegas60. A hierarchical analysis was carried out with three levels: among the four groups identified by the UPGMA analysis, and among accessions within groups, and within accessions.An analysis of molecular variance (AMOVA)O) and expected (HE) heterozygosity, and the inbreeding coefficient over loci (FIS). The genetic differentiation among populations was estimated from the fixation index (FST), the between groups diversity by FIT, and the overall genetic diversity HT. DST is the between population genetic diversity, and was obtained by subtracting the average of individual population HE from the total genetic diversity, HT. The parameters were obtained according to Nei61. The pairwise comparison of FST was obtained using the R programme StAMPP62.Once a population structure had been defined according to the UPGMA analysis, the populations were assessed for genetic diversity. The measurements included observed  on genetic diversity, the geographical coordinates were used for each sampling site. Samβada is a spatial correlation method, which uses non-random associations between cause and effect. It uses Moran’s I correlation67 which assesses the overall clustering of the data, and this is related to the first law of geography “everything is related to everything else”68. Parameters were set to spatial for the autocorrelation, and nearest neighbours 20 for the weighting. Significant loci were identified after Wald and G tests following Bonferoni correction at a 99% confidence level. Significant outlier SNPs that were common to all three analyses were identified in the genome assembly, and gene models assessed using BLAST2GO69 for biological and molecular processes, and cellular component, and to assign gene ontology (GO term).To identify candidate loci potentially influenced by selection, three methods were used: F2) between each pair of SNP loci. Alleles were only considered if the minor allele frequency was above 0.05, as r2 has large variances if rare alleles are considered70. Modelling of LD decay was performed using a custom R script derived from the method described in Wang et al.19, and modified as described71.LD was calculated as the squared allele frequency (rst April until 21st June in 2016 (day 1–81) and a further date recorded as day 100 (10th July 2016) as day of harvest. Measurements for plant height, width, number of stems and two harvest wet weights were also recorded. Any data that were not normally distributed were log transformed to improve homogeneity and analysed in Genome Association and Prediction Integrated Tool (GAPIT) for GWAS. The analysis was performed with the compressed mixed linear model72 implemented in the GAPIT R package73.Flowering time was recorded per plant from the initial start point of 1Supplementary Information.Supplementary Information2.


Stenella longirostris, Gray 1828) are widely distributed in tropical waters around the world. Although they occur in large, pelagic groups in the Eastern Tropical Pacific, elsewhere in the Pacific they are found in small and genetically isolated populations associated with islands. This species is considered to be “Least Concern” (LC) by the World Conservation Union (IUCN). To assess genetic diversity and population structure of an island-associated population in the South Atlantic Ocean we surveyed 162 spinner dolphins throughout the Fernando de Noronha Archipelago of the northeast coast of Brazil using ten microsatellite loci and sequencing a 413-bp section of the mitochondrial DNA (mtDNA) control region. Eleven mtDNA haplotypes were identified and haplotype diversity (h) and nucleotide diversity (π) were 0.3747 and 0.0060, respectively. Median-Joining Network revealed the presence of two very divergent haplotypes and F-statistics indicated some heterogeneity between two sampling years. All microsatellite loci were polymorphic  but, revealed no detectable substructure. We also compared the mtDNA haplotypes from Noronha to 159 haplotypes representing 893 individuals from 14 locations worldwide. We found that the two common haplotypes from the Fernando de Noronha Archipelago were absent in all other populations. These comparisons showed that Noronha spinner dolphins are likely more differentiated than other island populations, suggesting that they form societies with strong site fidelity mediated by females.Spinner dolphins ( Stenella longirostris, Gray 1828) is widely distributed in tropical waters around the world [(Stenella longirostris longirostris), generally associated to tropical islands of the Indian, Atlantic and Pacific Oceans; the dwarf subspecies (Stenella longirostris roseiventris), considerably small (140 cm), is found in waters of the Gulf of Thailand, Indonesia and southern China; the Central American subspecies (Stenella longirostris centroamericana), whose distribution covers coastal waters of the Pacific Ocean in Central America; the Eastern subspecies , a morphologically distinct form in the Eastern Pacific Ocean, is found in tropical and coastal waters of Mexico [The spinner dolphin  are found in oceanic waters of the Atlantic, Pacific and Indian oceans, and around volcanic islands and atolls, such as those of Hawaii, French Polynesia and Fernando de Noronha –9. TheseGray’s subspecies are the only spinner dolphin ecotype known to inhabit the South Atlantic Ocean ,6. AlongGray’s ecotype from the Fernando de Noronha Archipelago (hereafter referred to as Noronha spinner dolphins) gather in these islands to use their calm waters during the day to rest, play, care for their young and, take refuge from sharks; at night, they move out into deep sea waters to feed , 19. WhiThe social structure of the spinner dolphin is considered to be transient, with groups merging and splitting up continuously, forming the so-called "fission-fusion" groups  in whichDespite the wide occurrence of spinner dolphins around the world, there are relatively few studies of genetic structure of island-associated populations worldwide and none in the South Atlantic Ocean –4, 24–26Moderate to high levels of variability generally confer a higher probability of population survival in a medium and long term . EndangeStenella longirostris is considered to be “Least Concern” (LC) by the World Conservation Union , however, due to the scarcity of information regarding the genetics and geographical distribution patterns of S. longirostris in the Atlantic Ocean studies that focus on these issues are necessary.Here, we examine sequences of mitochondrial DNA (mtDNA) and 10 microsatellite loci to evaluate the genetic diversity of this species in the Fernando de Noronha Archipelago, and test the hypothesis of the existence of genetic structuring in the South Atlantic Ocean and haplotypes sharing among individuals from different oceans.It is very important to have a good knowledge of the basic biology of the species, including the degree of genetic variability, as well as the spatial and temporal aspects of intraspecific population structuring in order to develop appropriate strategies for the conservation and management of the populations . Stenell2 [2 distributed along the northeast-southwest direction . Licenses to transport and manipulate biological material collected at the Fernando de Noronha Archipelago were provided by the “Sistema de Autorização e Informação em Biodiversidade (SISBIO)/ Instituto Chico Mendes de Biodiversidade (ICMBio)”.A total of 162 skin samples were collected from alive Noronha spinner dolphins by the skin swabbing method ,42 in fowww.ncbi.nlm.nhi.gov/Genbank) [To compare the mtDNA haplotypes of the Noronha spinner dolphins worldwide, excluding the samples collected in Fernando de Noronha Archipelago, we reconstructed haplotypes from a total 159 sequences available in GenBank from five published papers (Genbank) , 26, 43.To reduce the complexity of the comparisons some locations were pooled, reducing from 19 island samples to 14 locations in total: Fernando de Noronha, Hawaiian Islands, Society Islands, Mariana Islands (3-Islands + Guam + Saipan + Rota), Samoa (American Samoa + Independent Samoa), Zanzibar, Mayotte, La Reunión, Palmyra, Philippines, Maldives, Indonesia, Taiwan, and North Atlantic (Gulf of Mexico + North Atlantic).2, 1.5 u of Taq polymerase (INVITROGEN) and 0.3 μM each primer, with the exception of the reverse for the SRY (0.06 μM) [Genomic DNA was extracted from skin samples using Chelex resin (SIGMA) according to manufacturer's instructions. Since it is not possible to determine the sex of the animal during the skin swabbing method due to the impossibility of visualization of the genital organ of the living animal in the water during the dolphin displacement, the sex of each Noronha spinner dolphin was molecularly determined  by the a0.06 μM) . The fin0.06 μM) . The amp0.06 μM) . The fra0.06 μM) .S. longirostris, . Fragment sizes were identified using GeneMapper software 5.0 (Applied Biosystems). The average non-exclusion probability for the identity of individuals was assessed using Cervus 3.0.3  and poteLinkage disequilibrium and Hardy-Weinberg (HWE) equilibrium were evaluated using GENEPOP on the Web ,52. MicrNa), mean number of alleles (Nam), number of private alleles (Nap), observed (Ho) and expected (He) heterozygosity and inbreeding coefficient (FIS) were calculated using Fstat v.2.9.3.2 [Pcrit value of 0.02 and 95% confidence intervals was chosen to reduce the potential bias for low frequency alleles [Only the polymorphic loci were used in the analyses of genetic diversity. Total number of alleles , a web-based program for collating results generated by the program Structure 2.3.2 [Population structure was also investigated in a Bayesian clustering analysis to estimate the most probable number of populations using Structure 2.3.2 , using are 2.3.2 .2, 0.5 units of Taq DNA polymerase (INVITROGEN), and 0.2 μM of each primer [An approximately 550bp fragment of the mtDNA control region (D-loop) was amplified with the following primers: KRAdLp 1.5 t-pro  and dLp5h primer . Cycle ch primer . Amplifih primer .π) and haplotypic (h) diversities and mismatch distribution, to test selective neutrality in mtDNA control region and population structuring. Selective neutrality in mtDNA control region was tested by the Tajima test [Arlequin 3.5.2.2  was usedima test  and Fu [ima test  using a FST and ΦST were estimated with 10,000 random generations using Arlequin 3.5.2.2 [Temporal population structuring was investigated among Noronha spinner dolphins sampled during the years 2006, 2009 and 2012, since the year 2004 was removed from this analysis due just one individual sampled. Pairwise  3.5.2.2 .FST and ФST using Arlequin 3.5.2.2 [http://www.fluxus-enginering.com), and the MP option was used to reduce the complexity [Genetic differentiation was also assessed among Noronha spinner dolphins and other locations of the world using AMOVA, Pairwise  3.5.2.2 , using h 3.5.2.2  . The remainder of samples failed to amplify.−9. None of the samples had matching genotypes.Of the 162 skin samples, 92 provided genotypes for 7–10 loci. Three loci were not used in the analysis: SL8-49 was monomorphic; SL10-26 revealed the presence of null alleles; and SL01 was discarded because of evidence of linkage disequilibrium. The seven other microsatellite loci were moderately variable, e.g. k = 4–15 . The proThree loci showed significant departure from Hardy Weinberg equilibrium, with a deficiency in homozygotes .Using NeEstimator, contemporary effective population size (Ne) for Noronha spinner dolphins was estimated to be 491.3 . The Wilcoxon one-tailed test revealed that the Noronha spinner dolphins went through a possible bottleneck event based on the TPM mutational model (P = 0.00391), but not under SMM model (P = 0.3475).FST values. The Bayesian clustering analysis revealed no detectable substructure by sampling period or overall. The greatest likelihood was K = 1, and, K = 2 showed all individuals to have similarly mixed ancestries ; no bottleneck event, TPM mutational model (P = 0.96875), SMM model (P = 0.06250); no detectable substructure by sampling period or overall  displayed the same pattern of results as the analysis containing them: no statically significant  overall .h) and nucleotide diversity (π) were 0.374 (+/- 0.044) and 0.006 (+/- 0.003), respectively.Sequences of a 413 bp fragment of the mtDNA control region were obtained for all 162 samples of Noronha Spinner dolphins and revealed 27 variable sites (20 transitions and eight transversions) representing 11 haplotypes (defined as NOR), uploaded to GenBank with accession numbers: MK184992 –MK185002. Haplotype diversity (Median-Joining network showed two very divergent haplotypes: NOR1 (N = 126) and NOR2 (N = 24); NOR1 was shared among individuals from 2004, 2006, 2009 and 2012; NOR2 was shared among the individuals of 2006, 2009 and 2012; NOR2 is distant from the majority of haplotypes by eight mutational steps .Fs  and Tajima’s D . The temporal genetic structuring test applied for individuals sampled in different years showed significant FST values for mtDNA control region between 2006 and 2012 .The mismatch distribution chart of the Noronha spinner dolphins mtDNA presented a bimodal curve . The neuTo investigate the phylogeographic relationship of Noronha spinner dolphins to other populations worldwide, we analyzed a total of 1,055 samples representing 14 regional populations , includih = 0.345) for Noronha spinner dolphins (despite the large number of specimens) to (h = 0.953) for Mayotte, whereas nucleotide genetic diversity ranged from (π = 0.005) for Hawaiian Islands to (π = 0.022) for Samoa (π = 0.006).Haplotypic diversity of the 14 populations ranged from  value was observed with Indonesia, and the lowest (FST = 0.368) with Society Islands (ST = 0.676) and the lowest between Mariana Islands and Society Islands (FST = 0.035). The AMOVA analysis revealed significant values among locations .Significant differentiation was observed between Noronha spinner dolphins and all other locations of the world; the highest  and phylogeographic coverage (15 populations) crossing 3 ocean basins. Understanding the degree of genetic variability, as well as the spatial and temporal aspects of its intraspecific population structure, is necessary for the implementation of adequate conservation and management strategies. Particularly, the lack of regional genetic study for spinner dolphin, does not allow asses population structure and consequently no effectively regional management plan has been implemented. The ecotourism industry of spinner dolphin observation in Fernando de Noronha Archipelago is a growing concern that can be impacting the dynamic of this population.FST, and high isolation from other populations around the world. These findings emphasize spinner dolphin vulnerability to genetic processes and highlight the importance of the development of conservation programs for this population.Here we used mitochondrial DNA (D-loop) and nuclear microsatellite loci to assess the patterns of genetic diversity and population structure of the spinner dolphins of Fernando de Noronha Archipelago, Southwest Atlantic Ocean. Mitochondrial DNA revealed low genetic diversity in relation to other population worldwide , high diCephalorhynchus hectori) of the north island of New Zealand [Noronha spinner dolphins revealed the lowest level of mtDNA diversity of any spinner dolphin population around the world , 43, 4 a Zealand .h = 0.395), Midway Atoll , Pearl & Hermes Reef  [However, low variability in the mitochondrial DNA control region does not necessarily reflects low levels of heterozygosity in the nuclear genome . Indeed,= 0.200) . This pa= 0.200) . InsteadThe predominance of one haplotype of Noronha spinner dolphins can be explained by the founder effect. The bimodal curve of the mismatch distribution chart indicates that this population unit has undergone a recent demographic expansion ,78 or thThe presence of two distinctive and divergent haplotypes of Noronha spinner dolphin’s lineages also suggests colonization of this archipelago by at least two different matrilines. Comparisons among locations of the world indicate genetic isolation of Noronha spinner dolphins from all other spinner dolphin’s populations. This is likely due to the geographic isolation of this island from other islands of the Atlantic and Pacific Oceans. The Fernando de Noronha Archipelago encompasses the only islands in the Southwest Atlantic Ocean with resources and rest areas to support a large number of spinner dolphins . StudiesOcean water masses of Southwest Atlantic Ocean also exercise highly significant role on the distribution of spinner dolphins and can have important role in levels gene flow of spinner dolphins in the Brazilian coast. The Brazil Current and the Malvinas Current are considered as the limit of distribution of this species in southern Brazil encouraging the displacement of these dolphins to the south of the country in hot seasons, while in colder seasons these dolphins move to the north of the country ,16.S. longirostris longirostris between Northeast and Southeast of Brazil. The South Equatorial Current can encourage the displacement of spinner dolphins of the Fernando de Noronha Archipelago towards the Brazilian coast [The vicinities of Pernambuco, where the South Equatorial Current splits to the North Brazil Current and South Brazil Current, can be the limit of distribution of an coast . This cuan coast ,83.Some evidence of heterogeneity in the Noronha population was suggested by annual difference in mtDNA frequencies, although not in microsatellite. This could be explained by feeding behavior possibly inherited matrilineally once recent observations suggest two different groups of spinner dolphins that appear to use distinct feeding strategies at Fernando de Noronha Archipelago . TypicalWe showed that Noronha spinner dolphins display low levels of genetic diversity and that the colonization of Archipelago was driven by at least two different matrilineal lines. We also suggest that these dolphins live in societies mediated by females, with strong geographic fidelity and greater genetic isolation in comparison to other island populations from different ocean basins.S1 TableTable includes source, GenBank accession number, haplotypes codes of the original papers and of the present study, and, geographic localizations with number of individuals.(DOCX)Click here for additional data file.S1 FigBayesian clustering analysis inferred with the program Structure 2.3.2 for seven microsatellite loci of Noronha spinner dolphins (Stenella longirostris): (a) ΔK from Evanno’s method is shown between successive K values, (b) mean log probability (Lk) is given for each K tested.(TIF)Click here for additional data file.S2 FigBayesian clustering analysis inferred with the program Structure 2.3.2 for four microsatellite loci of Noronha spinner dolphins (Stenella longirsotris): (a) ΔK from Evanno’s method is shown between successive K values, (b) mean log probability (Lk) is given for each K tested, and the (c) assignment probabilities of individuals to putative population clusters at K = 2 according to sampling year .(TIF)Click here for additional data file.S3 FigObserved and expected distributions under spatial expansion model are shown with bars and lines, respectively.(TIF)Click here for additional data file.