Psittacanthus calyculatus and P. schiedeanus, a Mesoamerican species complex. Using microsatellites , we document moderate genetic diversity but high genetic differentiation between widespread parental clusters, calyculatus in dry pine-oak forests and schiedeanus in cloud forests. Bayesian analyses identified a third cluster, with admixture between parental clusters in areas of xeric and tropical dry forests and high levels of migration rates following secondary contact. Coincidently host associations in these areas differ from those in areas of parental species, suggesting that past hybridization played a role in environmental and host shifts. Overall, the observed genetic and geographic patterns suggest that these Psittacanthus populations could have entered a distinct evolutionary pathway. The results provide evidence for highlights on the importance of the Pleistocene climate changes, habitat differences, and potential host shifts in the evolutionary history of Neotropical mistletoes.Host specialization after host shifting is traditionally viewed as the pathway to speciation in parasitic plants. However, geographical and environmental changes can also influence parasite speciation, through hybridization processes. Here we investigated the impact of past climatic fluctuations, environment, and host shifts on the genetic structure and patterns of hybridization and gene flow between  The duration of different stages along the speciation continuum depends on the magnitude and timing of gene flow and on the balance among other evolutionary forces including genetic drift, recombination and selection5, which in turn are likely affected by historical and environmental factors6. Understanding population divergence and species boundaries is a complex task because it needs the integration of historical, demographic and ecological data8. For instance, knowledge of historical changes of distributions of populations is essential to understand current geographic patterns of genetic structure and species diversification9.The speciation process is viewed as a continuum (the ‘speciation continuum’) with many stages that vary in space and time10. Modern-day parasites have disproportionately evolved in certain lineages and the endoparasitic habit has arisen by convergence in four clades10. In addition, single gene analyses revealed multiple horizontal transfers from host to parasite lineage, making parasitic plants a very interesting model for studying the effects of the parasitic lifestyle on plant diversification10. Mistletoe parasitism has been postulated as a major driver of speciation because the parasite’s success depends on multiple, sometimes specialized biotic interactions  that could indirectly promote the strength and evolution of traits reinforcing the long-term relationship between species enough to isolate parasite populations into distinct races19.Based on a three-gene mitochondrial DNA phylogeny of seed plants, researchers inferred at least 11 independent origins of parasitism in Angiosperms (1%), eight of which consist entirely of holoparasitic species that lack photosynthetic ability22. The life cycle of most loranth mistletoes starts with frugivorous birds dispersing the seeds from tree to tree. Once the seeds are regurgitated or defecated by the bird, these adhere to the host tree with the natural ‘glue’ viscin, and then penetrate the woody host tissue with a structure named haustorium15. Upon reaching sexual maturity, the pollen is typically moved from flower to flower by a wide range of pollinators, including several species of insects, birds and bats27. Given that most avian seed dispersers and pollinators of loranth mistletoes are not sufficiently specialized21, it is unlikely that gene dispersal vectors reproductively isolate mistletoes into populations growing on different hosts within a community . Instead, the genetic structuring of mistletoe populations is more likely to be influenced by host-parasite interactions32.The parasitic Loranthaceae  are mostly aerial mistletoes very common in temperate and tropical plant communities, and typically use a broad range of host tree species33) and, therefore, variation in host quality would account for non-random occurrence patterns of parasitic plants. Beyond these mechanisms determining the distribution at local and large geographical scales, the diversification of mistletoe species has been explained through different mechanisms linked to host-parasite interactions12. Accordingly, the most accepted explanation of mistletoe diversification is that of ‘host-race formation’36, where genetic differentiation, and eventually host-race formation, is acquired through isolation-by-distance or by ecological adaptation following the ‘invasion’ of a different host species (‘host-switching’ hypothesis12). In addition, the geographic structuring of genetic variation in some mistletoe species has been explained as the result of past climate changes38, landscape fragmentation39, emergence of biogeographic barriers38, and by the parasites’ own climatic niche preferences41.Mistletoes are expected to establish and survive on higher-quality hosts . Thus, the evaluation of the temporal and geographical patterns of hybridization in mistletoe species may shed light onto complex evolutionary scenarios of species divergence and their association with host preferences and geographic isolation of populations.Although hybridization and introgression have been acknowledged as potentially important mechanisms for adaptive evolutionPsittacanthus  are characteristic stem parasites (hemiparasites) throughout the Neotropics21. Most species are host generalists and ecologically very important because they provide food resources  to many animals13 and indirectly influence community structure in low productivity systems57. The recently diverged species complex of Psittacanthus calyculatus and P. schiedeanus (c. 2.5–1.8 Ma38) can be found infecting different host tree species under distinct environmental conditions along their wide geographical distributions60. Kuijt21 reported that these species are distributed, more or less sympatrically, from Mexico to Panama, but recent molecular data suggest that these are allopatric and restricted to Mexico41. In addition, P. calyculatus mainly parasitizes Quercus (Fagaceae) trees in the central highlands of Mexico, whereas P. schiedeanus parasitizes cloud forest trees, mainly Liquidambar styraciflua (Altingiaceae) in eastern Mexico41. Patterns of genetic structure in chloroplast DNA (cpDNA) sequences and nuclear microsatellites showed two main lineages within the species complex41, with further genetic structuring of populations and evidence of genetic admixture in particular regions41. However, the presence of highly admixed individuals within particular populations has not been explored or discussed further41. Despite clear geographic and ecological differences between the ‘calyculatus’ and ‘schiedeanus’ genetic clusters, molecular evidence suggests population admixture within the Tehuacán-Cuicatlán Valley and the Central Valleys of Oaxaca, and the Central Depression of Chiapas41. Overall, these regions have a drier climate and more xeric vegetation types than those occurring elsewhere at higher elevations. Interestingly, populations within these two regions tend to infect a different set of host species41. Furthermore, past and present distribution models predict geographic overlap between the two species in the Central Valleys of Oaxaca during the last glacial cycle (ca. 100–200 kya38). Therefore, we would hypothesize that past migrations of the two species into the more xeric lowlands led to a secondary contact zone, possibly associated with shifts in host-preferences.41 to estimate levels of hybridization among groups of populations and rates of migration and directionality over contemporary and historical timescales. We then inferred the most likely scenario and timing of secondary contact and introgression using historical demography and Approximate Bayesian Computation (ABC) methods. Specifically, we addressed the following questions: (1) Are levels of hybridization and introgression geographically concordant with differences in the climatic and host preferences of populations? (2) Are the predicted temporal changes in migration and range shifts associated with the presence of varying levels of hybridization and introgression? We discuss the main causes that could account for the complex phylogeographic patterns observed and the ecological context that could provide valuable clues for the understanding of the evolutionary course of introgressive hybridization in a parasitic plant species’ complex.In this study we re-analysed previously reported microsatellite dataHO) was lower than expected and inbreeding coefficient values ranged from 0.038 to 0.64 (Table Descriptive statistics for the two groups defined by previous species assignments (CALY and SCHI) were remarkably similar to groups defined by habitat, admixture level or geography Table , suggest64 Table . The exi64 Table . When AM64 Table .FST-NA) and allele frequencies (Jost’s D) showed the same pattern of differentiation among groups  and populations from central Mexico  and Oaxaca  and populations from the northernmost distribution (Puebla and San Luis Potosí), Oaxaca, and Chiapas .As expected, two genetic groups were recovered by STRUCTURE . The highest migration rates were inferred from the CALY population to the SCHI and HYBR populations and from the SCHI population to the CALY and HYBR populations Table . MigratiM) calculated using MIGRATE revealed generally low migration rates among populations, except for the slightly higher migration rates from the SCHI population to the CALY and HYBR populations and from the CALY population to the HYBR population. Estimates of scaled migration rates (m) ranged from 0.00018 to 0.00005 and showed the same pattern among populations. The number of migrants per generation (Nem) ranged from 0.83 to 2.37 , implying that the rate and intensity of migration have changed over time between groups, with increased gene flow from past to present.Estimates of historical migration rates  was higher between the CALY and HYBR populations than admixture between the SCHI and HYBR populations .DIYABC analyses indicated that isolation with admixture is the best-supported scenario , the genetic differentiation between groups increases (FST-NA = 0.152) when data for populations of the HYBR group are excluded, indicating that this group represents a genetic bridge between the two parental species. Overall, the admixture results confirm our prediction that the more arid Central Valleys of Oaxaca and Central Depression of Chiapas represent hybrid zones. However, the genetic distinction between parental species can be maintained by host association  and by the geographic characteristics of their ranges, even in the presence of gene flow.The distribution of individuals with signs of admixture was not restricted to the area of sympatry in the Central Valleys of Oaxaca, but also occurred in the Central Depression of Chiapas, which is separated by warmer and drier conditions along the Isthmus of Tehuantepec from most other populations of the species63, but not in other species with different dispersal mechanisms66. In addition, the Chiapas region  is also home to other species of Psittacanthus closely related with P. calyculatus and P. schiedeanus41: P. breedlovei and P. angustifolius21. Thus, it is possible that hybridization with one of these other species may be the reason for the apparent high admixture and the low genetic differentiation between mistletoes in these two regions. However, these two species can be easily recognizable based on leaf morphology and host preferences21. In addition we observed, albeit using few samples, that P. angustifolius and P. breedlovei appeared to be genetically indistinguishable from their widespread sister species41. Therefore, further exploration of the genetic patterns including more samples from the other Psittacanthus species distributed in Chiapas is needed to understand their evolutionary history within this region.Interestingly, the very low genetic differentiation and high admixture levels between populations in the Central Valleys of Oaxaca and the Central Depression of Chiapas suggest that the Isthmus of Tehuantepec may not be strong barrier to gene flow for these mistletoes, as observed for other bird-dispersed plant speciesP. schiedeanus into P. calyculatus , with fewer heterospecific matings observed than expected by chance in P. calyculatus compared to P. auriculatus. When considering other factors of ecological isolation that affect co-occurrence, the RI values indicated that isolation by hummingbird pollinators was less effective than isolation by host tree species and seed dispersers, suggesting that host usage is the most important ecological isolation factor between the two species and that the host tree species’ barrier is currently contributing the most to maintaining these species in sympatry16.Díaz Infante and collaborators32, followed by dramatic changes in the distribution of species during the last glacial period38. Under this scenario, populations of the Psittacanthus calyculatus and P. schiedeanus may have expanded into the currently xeric lowlands of Oaxaca during glacial periods, with secondary contact and formation of hybrid zones among otherwise genetically differentiated populations (sympatric stage). During the Holocene, populations of the two parental species contracted back into temperate and cloud forests at higher elevation where little genetic structure is observed . Alternatively, ancestral hybrid populations of P. calyculatus and P. schiedeanus remained in situ  and differentiation of these populations occurred under more xeric conditions and specializing on different host species (host shifting hypothesis).For the origin of the hybrid forms located in the Central Valleys of Oaxaca and the Central Depression of Chiapas regions, a late Pleistocene scenario and assumed hybridization processes seem to be a plausible alternative for some reasons. The most likely DIYABC scenario supported a hybrid origin of the populations occurring c. 99 k years ago, corresponding approximately to the early last glacial period . This is consistent with the estimated initial diversification of the species complex occurring 200 kya38. Although we tested several scenarios of speciation with gene flow, future work incorporating genomic data might give more accurate estimates of the dynamics of gene flow and test alternative and more complex scenarios of allopatric speciation followed by hybridization during secondary contact67.Individuals with signatures of admixture were most frequent in populations located in the central arid regions of Oaxaca and Chiapas (HYBR group). The observed historical and contemporary patterns of gene flow shed some light on how historical gene flow between these closely related species occurred and what geographical barriers have maintained their genetic integrity. The non-significant correlation between historical and contemporary migration rates implies that migration rates between groups have changed over the evolutionary history of the species complex. Although rates of historical and contemporary migration were low among populations, we found evidence of past migration from the CALY and SCHI populations into the HYBR populations, supporting the demographic model for the hybrid origin of these populations. Results of the DIYABC analysis supported one of the allopatric speciation scenarios and indicated that divergence between groups of populations occurred at least 100 kya, consistent with previous evidence using nuclear and chloroplast DNA sequencesP. schiedeanus and P. calyculatus from the Central Valleys of Oaxaca formed a genetic cluster different from those corresponding to the distribution of each of the two species, and recognized this region as a potential area of secondary contact38. Our study revealed that the arid Central regions of Oaxaca, as well as the Central Depression of Chiapas, represents a secondary contact hybrid zone between P. calyculatus and P. schiedeanus. An interesting feature of the overlapping distribution area in Oaxaca for these mistletoes is that the more xeric climatic conditions contrast with the adjacent pine-oak forests  and cloud forests (P. schiedeanus) that parental species inhabit41. In addition, the main host species used by HYBR individuals in the secondary contact zone are also different, with a higher prevalence (57%) on Celtis caudata (Ulmaceae) at one locality16 or strongly associated with Anacardiaceae hosts based on herbarium records41. Therefore, we propose that expansion of P. calyculatus and P. schiedeanus towards lower elevations during the last glaciation38, promoted different events of hybridization in secondary contact zones, creating a hybrid swarm, probably with low hybrid frequencies. Once the glaciation period was over, admixed individuals prevailed within the same area because these had the capacity to confront new environmental conditions with different host species, with drier climatic conditions and more xeric vegetation, whereas non-admixed individuals contracted into the highlands to their present distribution along the TMVB and SMOr associated with different sets of host species. This hypothesis does not exclude the possibility of current gene flow (though restricted) to areas where cloud forests are very close to the tropical dry forests and xeric zones, like in the Central Valleys of Oaxaca. Secondary contact and hybridization could have weakened the reproductive barriers and maintained low genetic differentiation between populations from the temperate (TMVB) and cloud forests (SMOr). In light of the weak reproductive barriers between P. calyculatus and P. auriculatus, the sister group of the P. calyculatus and P. schiedeanus species complex32, we believe that hybridization very likely occurs among populations within the complex due to close genetic relationships between species. In addition, over the 20 bird species recognized as seed dispersers and more than 20 hummingbird species that pollinate the flowers of these mistletoe species68, several species are shared16 thus increasing the probabilities of current gene flow between species. It is possible that the present hybrid population has resulted from contemporary gene flow between parental species facilitated by bird seed-dispersal, rather than the result of historical gene flow by secondary contact after the differentiation of the two parental Psittacanthus species in late Pleistocene. Our analyses showed that contemporary gene flow is present between the parental and the hybrid genetic clusters. However, we believe that if hybrid populations result only from recent gene flow, we would also have observed a significant proportion of pure parental individuals within the hybrid zone. That is, birds would transport (in independent events) pure parentals into one region and only after their establishment would these begin to hybridize. Nonetheless, first generation hybrids were almost absent in the analyses and the timing of admixture by the DIYABC analysis was congruent with the idea of secondary contact after the differentiation of the two parental Psittacanthus species in late Pleistocene.Previous phylogeographic studies using cpDNA sequences, accompanied by ecological niche modelling, provided evidence that individuals of 69. In mistletoes, controversial evidence exists about the role of host race formation as the main diversifying force. Here gene flow can be interrupted or diminished if mating, dispersal and establishment occur only among mistletoes adapted to specific hosts36. Particularly, cross-dispersal experiments have provided some evidence for host-race formation in P. schiedeanus and P. calyculatus growing on distantly related host species in sympatry, in which seedling development was greatest when seeds were placed on their source host species70. The hypothesis of host-race formation is supported by the observed low heterozygosity values that might be produced by subpopulation structure, i.e. mistletoes that aggregate in one or adjacent hosts by geographic or behavioural barriers of gene dispersal vectors to gene flow followed by genetic drift in the subpopulations (Wahlund effect14). The significant population differentiation and genetic structure in the P. calyculatus and P. schiedeanus species complex has been attributed to climatic variables, rather than to host association41. Evidence in plant, fungi and animal species has shown the potential of hybridization to the adaptation to different environmental conditions73. In our study, we found that the area with higher values of admixture corresponds to individuals from locations with drier climatic conditions, more xeric vegetation types and different associated host species, suggesting that colonization of a ‘new’ habitat is linked to hybridization and further genetic differentiation.In parasitic plants the colonization of a new environment and further differentiation could be associated to adaptations to biotic factors such as new host associations, pollinators and dispersers or through adaptations to abiotic factors (like the parasite’s own niche) or both74. On the other hand, strong selection to different environments could maintain genetic differences between populations, despite the presence of gene flow3. Further studies combining genomic scans and experimental data of host-specific relationships through cross-inoculation experiments, or reciprocal transplants to different environments comparing parental and hybrid individuals would shed light on the degree of reproductive isolation and the role of introgressive hybridization in the evolution of host specialization and environmental shifts in Psittacanthus mistletoes in particular, and other aerial parasites in general. The processes of reinforcement, introgression and transgressive segregation along with evolutionary forces like genetic drift and selection could influence the chances that the hybrid population adapts to new host species. For example, the gain of alleles in the hybrids through introgression and the presence of transgressive traits  could benefit hybrid individuals to adapt to the new environment by creating a phenotype able to colonize a new host or tolerate different temperatures. Also, if hybrid mistletoes tend to aggregate in different hosts, the role of genetic drift will could be important to reproductively isolate hybrids3. We do not yet know the specific forces leading the hybrid populations into a new host as the initial stage towards speciation. It maybe directly related to the hybrid origin, by gaining some genetic advantage permitting the invasion of a new host. Or perhaps the adaptation into a new host is related to the in situ survival of the hybrids in the region, which was subjected to floristic turnover during the last-glacial/Holocene transition. In this case, the increasing abundance of arid-adapted hosts (such as Anacardiaceae) would lead to the specialization of these mistletoes and the host shifting leading to host race formation12. Results of this study suggest that hybridization could have been important for the colonization to a new environment under past climatic changes and could help to understand the range of outcomes of climate alterations and recently human-altered environmental changes shaping current patters of diversity.With the evidence in hand, many questions arise about the role of hybridization, reinforcement and introgression for the evolution of this system, including the colonization of new environments, host shifts, host race formation, and a possible case of hybrid speciation. If the reproductive barriers are weak and there is no reinforcement (selection against hybrids), differentiation between species will be eroded and the effect of host race formation would be diluted41. These data included information of 10 microsatellite loci for 415 individuals in 54 populations throughout the species’ distribution ranges in Mexico41, an area spreading about 14° in longitude and 10° in latitude, that includes three biogeographical regions. However, due to the few individuals genotyped for some populations we pooled populations in close proximity, ending up with 51 populations for this study  clustering analysis of microsatellite data using STRUCTURE 2.3.475, as previously implemented41. The most likely number of populations was determined estimating the DeltaK (∆K) and the log likelihood of K, ln P(K) = L(K) between successive K values61. According to Evanno’s method61, we confirmed the presence of two clusters, CALY and SCHI, and additional genetic sub-structuring was observed within each of these clusters in the second-step analysis . Interestingly, several individuals scattered throughout the STRUCTURE plot show signs of admixture at K = 2 = 2 Fig. .K = 2 and the distribution of admixed individuals scattered throughout the STRUCTURE plot, we decided to reanalyse the full dataset particularly because a high number of admixed individuals (mean membership coefficient <0.75) were not included in previous analyses41. To explore the occurrence of hybridization (see77 for more details), we assigned individuals from the allopatric CALY and SCHI clusters as ‘pure parental’ when the membership coefficient (q) was q > 0.9 for either of the two clusters. Individuals from the sympatric regions  were not considered for the ‘pure parental’ assignment because the suspected high admixture in these regions could bias further assignment. The possibility that P. auriculatus, geographically restricted to the Oaxaca dry valleys, can be the donor for the hybrid population given its sympatric distribution with the P. calyculatus/schiedeanus complex is unlikely. The specific microsatellites used here41 were designed using populations of the species complex of P. schiedeanus and P. calyculatus and previous work by our lab group has shown low success in transferring these microsatellite loci into other species due to poor amplification.Given the observed patterns of genetic structure at K = 2. We set the allele frequencies to be correlated and performed ten replicates with 100 000 MCMC after 50 000 burning period. The outputs of each replicate were combined in CLUMPP for visualization78.We then performed a STRUCTURE analysis using the ‘pure parental’ information, implemented through the POPFLAG prior, to define individuals belonging to the parent populations. In order to uncover admixture between the two species, all individuals were assigned to either CALY or SCHI populations by setting 79 to calculate the posterior probability of individuals belonging to one of six categories: (1) pure CALY, (2) pure SCHI, (3) first generation hybrids, (4) second generation hybrids, (5) CALY backcrosses, and (6) SCHI backcrosses. The analysis focuses on first generation hybrids, thus helping to detect on-going hybridization between species. Assignments were done using Jeffrey’s-like prior for allele frequencies and mixing proportions as suggested in the program’s manual. We ran three replicates with 500 000 sweeps and a burn-in period of 20 000, and the prior information of pure parental individuals obtained from previous STRUCTURE included in the analysis.We then used the Bayesian model-based program NEWHYBRIDS80. For this, we used the individuals classified as parental in the STRUCTURE analysis as the starting populations and simulated 50 hybrids for several generations: first, second and third generation hybrids; and first, second and third generation backcrosses to each parental species. Data obtained for each simulation were run in STRUCTURE with the same parameters as above. The results for K = 2 were combined with CLUMPP78 and the proportion of membership was visualized using R 3.1.3 . From the simulations, we identified three categories of individuals: (1) pure species, individuals with an assignment probability of q ≥ 0.80 to one cluster; (2) backcrosses, individuals with an assignment probability between q = 0.6 and q = 0.8 to one cluster; and (3) hybrids , individuals with an assignment probability between 0.4 and 0.6 .To define assignment thresholds to each hybrid category used for our results, we performed hybridization simulations in HYBRIDLABFinally, the simulated data were also run in NEWHYBRIDS and the program correctly assigned the pure species individuals with a probability >0.9. For the first- and second-generation hybrid individuals, we considered correctly assigned individuals those with probabilities higher than 0.5. Subsequent hybrid generations and backcrosses were not identified in NEWHYBRIDS, thus we considered hybrid individuals of unknown generation those with assignment probabilities between 0.1 and 0.9. Finally, we estimated the proportion of individuals belonging to each category for each population to assess the level of admixture across populations.41, we also grouped samples according to habitat type: (1) cloud forests; (2) xeric temperate forests; and (3) tropical dry forests. Finally, populations were also grouped according to geography into four groups: (1) the Chiapas region; (2) the Oaxaca region; (3) Sierra Madre Oriental; and (4) Trans-Mexican Volcanic Belt.To analyse genetic differentiation and population structure, we used the classification provided by the initial STRUCTURE runs and grouped populations into two groups, CALY and SCHI. Because of the high levels of admixture observed in the Central Valleys of Oaxaca and the Central Depression of Chiapas, we also grouped samples into three groups as follows: (1) CALY, samples from temperate forests along the TMVB; (2) SCHI, samples from cloud forests in eastern Mexico and three populations in Chiapas; and (3) HYBR, samples from the xeric Central Valleys of Oaxaca and Central Depression of Chiapas. Given that most genetic structure has been explained by environmental factorsD) using the R package “DiveRsity”81 and rarefied allelic richness using the R package “hierfstat”82. Hardy-Weinberg equilibrium departures and linkage disequilibrium among loci were estimated in GENEPOP 1.283. We used FreeNA84 to estimate the frequencies of null alleles with the EM algorithm85 and the pairwise genetic differentiation (Weir’s FST86) among groups of populations using the ENA correction. Note that genetic structure below the level of our sampling (population subdivision) can produce significant departures from Hardy-Weinberg even in the absence of null alleles (i.e. Wahlund effect: reduction of heterozygosity in a population caused by subpopulation structure). For these analyses, locus four was eliminated because it was only present in the SCHI populations.For each of the four groupings , we estimated gene diversity and absolute allele frequency differentiation (Jost’s 87) as implemented in ARLEQUIN 3.0188. Four AMOVAs were performed with different groups of populations: (a) two clusters corresponding to each species (CALY and SCHI); three clusters corresponding to (b) habitat type  or (c) level of admixture ; and (d) four clusters corresponding to geography , whereas MIGRATE uses the coalescent approach to jointly estimate the relative effective population size θNe (4Neµ) and asymmetrical gene flow M (m/µ) between pairs of populations over much longer periods of time, approximately thousands of years (ca. 4Ne generations in the past91).We compared migration rates over contemporary and historical timescalesA), migration rate (M), and inbreeding (F). Subsequent runs incorporated different Δ to ensure that the acceptance rate for proposed changes in parameters were between 20–40% for each parameter. Adjusted final delta values used were ΔA = 0.2 (41% acceptance rate), ΔM = 0.8 (22%) and ΔF = 0.2 (48%), respectively. To ensure convergence, we performed five independent runs  each with a different seed number, comparing the posterior mean parameter estimates for convergence. We also analysed the trace file of each run with TRACER 1.592 to ensure an appropriate mixing of parameters and burn-in number. We give estimates of m from one randomly chosen run out of the three final runs as their parameter estimates were similar. We ran MIGRATE incorporating Bayesian inference analyses to estimate historical migration rates (M) among groups of populations. We used a Brownian-motion model with a constant mutation rate and FST to estimate θ. Several short runs were performed to search for the appropriate priors. After finding suitable priors, MIGRATE was run three times to confirm convergence. These final runs consisted of one long chain, 100 000 sampled trees, 1000 recorded, with a burn-in of 10000 with three replicates and each run with a different seed number. We set the minimum and maximum boundaries for theta (θ) and migration (M) as 0.0 and 30.0, with a delta value of 3. A four-chain heating at temperatures of 1, 1.5, 3 and 10000 was implemented to increase the efficiency of the MCMC89. Lastly, we performed a Mantel test with 5000 permutations to test for similarity between contemporary and historical values of m. For this analysis, we used the values of m directly generated by BAYESASS and estimated m from values of M (m/µ) generated by MIGRATE by multiplying all M values by an estimated mutation rate of 5 × 10−4 for microsatellites93. The number of migrants per generation was estimated by multiplying the θ value from the source populations to M91.BAYESASS was initially run with the default delta values (Δ) for allelic frequency  of the corresponding populations  during each time period  was set to a maximum of 30000.Approximate Bayesian Computation (ABC) analysis was performed using samples in the three clusters defined based on genetic differentiation and genetic sub-structuring: CALY, SCHI, and HYBR. Five possible divergence scenarios leading to these three clusters were included in the ABC analysis to test if the admixed populations have a hybrid origin (see Results). In each scenario, t refers to timescale ranging from 300 to 25000 generations and with a conditional prior t2 > t1, the maximum t included the predicted split between 94 to simulate ten million datasets (2 million per scenario) with the same number of populations, loci and individuals. The most likely scenario was evaluated by comparing posterior probabilities using the logistic regression approach96. Temporal and demographic parameters were estimated with a logistic regression for the best-supported model with the 1% simulated data closest to the observed data96. Finally, to assess confidence in the model selection we simulated 500 pseudo-observed datasets (PODs) to estimate type I and type II error rates96.We used DIYABC 2.1et al. (nph14471-sup-0003-NotesS2.csv)41.The dataset (microsatellites) generated and analysed during the current study are available in the Supporting Information of Ramírez-Barahona Supplementary Information


Otaria flavescens) is widely distributed along the southern Atlantic and Pacific coasts of South America with a history of significant commercial exploitation. We aimed to evaluate the population genetic structure and the evolutionary history of South American sea lion along its distribution by analyses of mitochondrial DNA (mtDNA) and 10 nuclear microsatellites loci. We analyzed 147 sequences of mtDNA control region and genotyped 111 individuals of South American sea lion for 10 microsatellite loci, representing six populations , Argentina and Falkland  Islands) and covering the entire distribution of the species. The mtDNA phylogeny shows that haplotypes from the two oceans comprise two very divergent clades as observed in previous studies, suggesting a long period (>1 million years) of low inter-oceanic female gene flow. Bayesian analysis of bi-parental genetic diversity supports significant  genetic structure between Pacific and Atlantic populations, although also suggested some inter-oceanic gene flow mediated by males. Higher male migration rates were found in the intra-oceanic population comparisons, supporting very high female philopatry in the species. Demographic analyses showed that populations from both oceans went through a large population expansion ~10,000 years ago, suggesting a very similar influence of historical environmental factors, such as the last glacial cycle, on both regions. Our results support the proposition that the Pacific and Atlantic populations of the South American sea lion should be considered distinct evolutionarily significant units, with at least two managements units in each ocean.The South American sea lion ( Anguilla Anguilla [Antimora rostrata [Delphinus delphis in the North Atlantic [Delphinus appears to have evolved during a transitional period of climate change when novel habitat was released after the last ice age due to changing current patterns [In the marine environment, there is considerable potential for connectivity and dispersion, and barriers to dispersal can be difficult to recognize. This is especially true for highly mobile species such as marine mammals and pelagic fish. While some of these species do appear to show panmixia across vast oceanographic scales , it is Atlantic  and the Atlantic . In at lpatterns . Here weOtaria flavescens  (hereafter referred as sea lion) has a broad distribution in South America [The South American sea lion  America ,8, cover America  Fig 1)..Otaria fO. flavescens show significant differences between the two sides of South America and support the existence at least of two [Skull morphometrics of t of two  or even t of two . Interest of two . The firt of two . Howevert of two ,13–16, at of two . These mt of two ,15,16. Ot of two ,13–16. Ht of two , which it of two , althougt of two . A recent of two .Philopatry of females with male-mediated gene flow is a common pattern in many species of pinnipeds ,20,21. TEl Niño events in Peru [www.iucnredlist.com). Furthermore, microsatellite data showed no association between genetic and demographic bottlenecks in Falkland/Malvinas Islands population [Populations of sea lions suffered drastic reductions in the past two centuries . The spe in Peru  as well  in Peru ). Nevert in Peru , 23) andpulation  and, mispulation , while tpulation .Here we present the first genetic study on the South American sea lions that analyzed microsatellite and mtDNA data from the main areas of occurrence of the species in both the Atlantic and Pacific Oceans. We hypothesize that, besides a divergence between Atlantic and Pacific populations, the demographic history of the species would be influenced by Pleistocene climate cycles. In this context, we aim to: (1) characterize the genetic diversity and geographical structure across the species range; (2) test whether the previous population structure with two oceanic ESUs proposed using mtDNA are also supported by microsatellite data and estimate their divergence time; (3) investigate recent migration between populations; and (4) examine the demographic history of the species.Instituto Nacional de Recursos Naturales”, in Chile issued by the current ‘Subsecretaría de Pesca” permits: N° 2100/2007, 786/2011, N° 2799/2008, N° 2396/2009, N° 1737/2010, N° 2794/2010. In Falkland/Malvinas Islands specimens were collected in 1991 and 1992 by researchers from the Sea Mammal Research Unit in affiliation with the British Antarctic Survey (BAS), working with the approval of the Falkland Islands Government, but no formal permits were required at that time. The sampling permits issued by local authorities in each country attest that the authors did not violate any ethical rule for collecting the animal samples. No samples were donated or purchased, and no sea lion was killed for the purpose of this study. All the samples used for this research derived from animals stranded and naturally dead, or from biopsied animals that were immediately released after the sampling activity.All necessary permits were obtained to collect the samples for the described study, which complied with all relevant regulations. Samples from Brazil were collected with permit N° 020-04/CMA-IBAMA, issued by the current ‘Instituto Chico Mendes de Conservacão da Biodiversidade’; in Argentina permits issued by the ‘Dirección de Fauna y Flora Silvestre, Subsecretaria de Recursos Naturales, Ministerio de Industria, Agricultura y Ganaderia’; and by the ‘Subsecretaría de Conservación y Áreas Protegidas, Secretaría de Turismo’ permits N° 008/05, N° 178/07, N° 012/08, N° 003/09, N° 196/09, N° 001/10, N° 011/11, N° 082/12, N° 304/13 and N° 032/14. In Peru, samples were collected with permit N° 119-2006-INRENA-IFFS-DCB, issue by the “O. flavescens tissue samples were collected from skin biopsies or from dead animals found ashore ; (2) ‘Northern Chile’: between Punta Negra  and Punta de Lobo ; (3) ‘Southern Chile’: between Ritoque beach  and Isla Mocha , (4) Isla Guafo , and (5) Punta Carrera ; (6) Falkland/ Malvinas Islands (British Overseas Territory): Seal Bay ; (7) ‘Argentina’: between Punta Pirámide  and Isla Pinguino ; and (8) ‘Uruguay’: from dead animals found ashore collected along southern Brazilian coast . This latter arrangement was because, during the austral autumn and spring months, many sea lions are found along the Brazilian coast as a result of the dispersal of individuals from the closest Uruguayan natal colonies, such as Cabo Polonio and Isla de Lobos, after the breeding period [Sampling sites were grouped in the following studied areas: (1) ‘g period , 30. Samb (cytb) gene were partially amplified by PCR using the following primers: L15926 5´- TCA AAG CTT ACA CCA GTC TTG TAA ACC—3´ [5´- CCT GAA GTA GGA ACC AGA TG—3´ [GLUDG-L 5′-TGA CTT GAA RAA CCA YCG TTG-3′ and CB2-H 5′- CCC TCA GAA TGA TAT TTG TCC TCA-3′ [http://technelysium.com.au). Sequences were then aligned automatically within CLUSTALW 2.1 [The mitochondrial DNA control region (CR) and cytochrome A ACC—3´ ; H16498 GA TG—3´  for the C TCA-3′  for the TALW 2.1  and manuTALW 2.1 .http://www.fluxus-engineering.com). Pairwise F-statistics (ΦST using p-distance) between populations and hierarchical Analysis of Molecular Variance (AMOVA) approach were estimated with ARLEQUIN using 10,000 permutations. Sequential Bonferroni correction was applied to the P-values to correct for multiple comparisons.Since we obtained mtDNA cytb sequences from only a few individuals from Chile, and this segment was not very informative at the population level, cytb sequences were used only in the network and phylogenetic inferences. Haplotype (Hd) and nucleotide diversities (π) were estimated using ARLEQUIN 3.5.1.2 . HaplotyO. flavescens haplotypes were estimated using 103 cyt b sequences  , and between O. flavescens and the genus Arctocephalus (5.8 ± 1.0 Ma) [http://tree.bio.ed.ac.uk/software/figtree/).Divergence times between  36) see . A fragmkeri see . A phylo 1.0 Ma) , with a  1.0 Ma)  (we used 1.0 Ma) , summariCallorhinus ursinus [Demographic history for the geographic areas with a sample size larger than 25 were estimated using the Extended Bayesian skyline plot reconstructions on the mtDNA control region dataset performed with BEASTv2.4.3. The parameters and priors used were the Extended Bayesian Skyline Plot tree prior, HKY substitution model with gamma site heterogeneity with six categories, a strict clock rate was set to a lognormal distribution with a mean of 5.8% (standard deviation of 0.4) per million years (derived for  ursinus ). We run ursinus .Z. californianus; Hg8.10 and Hg6.3 developed for Halichoerus grypus; PvcE and Pv9 described for Phoca vitulina; and M11A described for Mirounga sp. [5’- CACGACGTTGTAAAACGAC– 3’) that was used in combination with a M13 primer marked with fluorescence  [We genotyped 111 samples for ten loci of dinucleotide short tandem repeats (STR): ZcwB07, ZcwE04, ZcwG04, ZcwF07 and ZcwE12 developed for unga sp. ,49,50,51EX, NED) . AmplifiEX, NED) .ST-like method) between populations, and AMOVA were estimated with ARLEQUIN using 10,000 permutations. Sequential Bonferroni correction was applied to the P-values to correct for multiple comparisons.Significant departure (α = 0.05) from Hardy-Weinberg equilibrium (HWE) was determined using ARLEQUIN exact test with 100,000 steps Markov chain and 1000 dememorization steps. Expected (He) and observed heterozygosity (Ho), pairwise differentiation  iterations and a burn-in period of 1,000,000, using sampling locations (the six sampling areas defined above) as prior information to assist the clustering with the LOCPRIOR model [http://pophelper.com). Finally, we tested for migrants or hybrids between oceans applying the USEPOPINFO model of the STRUCTURE software . This model uses pre-defined groups/clusters as priors (in this case ocean basins–see STRUCTURE results) to test for migrants or hybrids.Genetic population structure was assessed by the Bayesian approach implemented in the program STRUCTURE 2.3.4 . First, OR model . The optOR model  as impleOR model . The exi7/2 x 108 steps that recorded every 1,000/2,000 iterations, with the first 3x106/5 x 106 discarded as burn-in. To reach the recommended acceptance rates between 20% and 60%, the values of parameters such as migration rates (ΔM), allele frequencies (ΔA) and inbreeding coefficient (ΔF) were adjusted to 0.1/0.9, 0.3/0.8 and 0.5/1, respectively. Trace files were examined for convergence to its stationary distribution in TRACER.Contemporary gene flow was estimated using a Bayesian method implemented in BAYESASS 3.0.3 . We estiDSW distance [http://tree.bio.ed.ac.uk/software/figtree/).The genetic distance between pairs of sampling areas was inferred by estimation of the distance  and thisdistance . SupportWe analyzed 147 mtDNA control region sequences of sea lions sampled in almost the entire range of the species . A totalAll sampling populations have similar high values of haplotype diversity (≥0.83) but relatively low nucleotide diversities (from ~0.5% to ~0.8%), except the northern Chilean population, that had the highest diversities (~1.6%) . The hapP <0.05)  . Within The mtDNA haplotype networks for the control region, cyt b, and the concatenated dataset showed two major and divergent clades corresponding to individuals that inhabit each ocean basin , that iscyt b sequences, that includes sequences from most of the other species of the family, Otaria forms a monophyletic and basal clade  was higher than any within-basins comparison, even between geographically closer populations from the southern tip of the continent but from different oceans, such as southern Chile versus Falkland/Malvinas Islands. The genetic distances between the three Atlantic populations were all larger than the distances between the three Pacific populations.The mtDNA pairwise Φmparison . Also, tST distance between Pacific and Atlantic was also significant . RST distances between the six sampling areas were not very high in general and all distances within-basins were not significant, as well as the distances between southern Chile and the Atlantic areas, with exception of the Uruguay   , S1 Fig,K = 3 shown that, aside from the two northernmost populations from each ocean, Uruguay and Peru, the other populations seem to share a genetic component that is absent from the former two  from Pacific to Atlantic and ~1% per generation (standard error = 0.9%) from Atlantic to Pacific, although only the former is  significantly different from zero. The BAYESASS analysis considering the six areas presented mostly very low inter-oceanic migration rates , although migration rates from some Pacific to some Atlantic areas were much higher than the others  and reciprocal monophyletic clades, even though we included individuals sampled from the southern tip of the continent, where the marine geographical distances between Atlantic and Pacific areas are very short . Our resustralis ,62, suggagoensis , and seallebaeki .The origin and long-term maintenance of this major phylogeographic break are probably related to Pleistocene climatic changes and the synergy of ecological barriers with high female philopatry. We could hypothesize that the ancient divergence of these two clades was the result of the first and perhaps only female dispersal of the South American sea lion from the Pacific to the Atlantic coast of South America, as suggested previously . Since tA question that emerges from these results is where the boundary between these clades is located (and therefore of the two ESUs), given the present absence of physical barriers between Atlantic and Pacific ESUs. A second question is how complete is this isolation. This boundary or contact zone should occur further south than our southernmost sampling areas at both ocean basins  were significant, six pairs of the equivalent microsatellite FST distances were significant . While all but one intra-oceanic mtDNA Fnificant , suggestThe mtDNA analysis showed that almost all breeding areas of the species seem well-differentiated, suggesting low or very low female gene flow between two ocean basins and supporting the existence of Pacific and Atlantic ESUs. On biparental markers (microsatellite), there seem to be two main genetic components in each ocean , supportWe also found that the genetic differentiation among the three Atlantic areas was higher than among the three Pacific areas both on the mtDNA and on the biparental markers, although in the later differentiation was much lower , 4 and 5The genetic structure results are also in partial agreement with the comprehensive analysis of skull morphology of 331 females on this species, which found four geographic groups: two different populations on the Pacific (Southern Chile and Peru) and two in the Atlantic Ocean  . HoweverIn conclusion, we suggest the existence of at least two management units (MU) in each oceanic ESU: the Atlantic group formed mainly by individuals from the Uruguay and southern populations  and the Pacific group containing individuals from Peru and northern Chile (being the southern Chile a mixture of both) in the Pacific ESU. Both ESU and MU concepts have been widely used in conservation biology, the former being genetically highly differentiated  populations that have high priory for conservation, and the latter may be considered as populations whose degree of differentiation from others is sufficient so that they should be managed separately .e.g. population declines in the Pacific colonies due El Niño events [The existence of an Atlantic and a Pacific ESU for sea lions along the coast of South America  and also the different management Units (MU) identified in each ocean, are very important information for the management strategies of the species in each ocean basin, since they face different conservation problems in each area , and based on the microsatellite results it is the most divergent among the studied Atlantic populations. This genetic differentiation coupled with the conservation problems faced by the population from Uruguay, such as the long commercial sealing period , fisheryHowever, geographically denser sampling and probably a higher number of informative markers are necessary to better define the limits between these units and to test the existence of additional ones.Our result of mtDNA showed reciprocal monophyly but reduced differentiation on biparental genetic markers between the ocean basins is consistent with a strong female philopatry and gene flow mainly mediated by males, a dispersal pattern commonly found in several pinniped species e.g. ,21,80). ,80. 21,8Engraulis rigens) to the south, where the sea surface temperature is colder than Peruvian waters [The admixture analysis  and the n waters . Consequn waters . This afn waters .Moreover, this direction of migration is mainly counter-current, especially on the Pacific coast, where the Peru (or Humboldt) current flows northward . HoweverThe pattern of long-term population size dynamics of Argentina, and for the first time of two Pacific populations, southern Chile and Peru, suggested the three populations underwent a two order of magnitude increase in the last 10 kya, more pronounced in the Argentina area Figs  and S4. The past demographic changes shown in It was suggested that this fluctuation was caused by habitat contraction during LGM, with the northern areas acting as refugia, followed by southward expansion after deglaciation . This scS1 TableAbsolute frequency in the sample and geographic distribution of haplotypes for South American sea lion.(DOCX)Click here for additional data file.S2 TableAbsolute frequency in the sample and geographic distribution of haplotypes for South American sea lion.(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(A) Number of alleles, (E) = exclusive alleles, (Ho) observed heterozygosity, (He) expected heterozygosity.* Loci that deviated from HW equilibrium after Bonferroni correction.(DOCX)Click here for additional data file.S1 Fig(A) Highest value of (ΔK) = 79.20 on K = 2. (B) Mean of estimated Ln probability of data (± sd) averaging ten runs from K = 1 to K = 10.(TIF)Click here for additional data file.S2 FigEach bar is one individual and each colour represents the assignment probability of the individual to belong to that genetic cluster.(TIF)Click here for additional data file.S3 FigInternal dashed lines are median estimates and thin lines and coloured areas are the 95% Central Posterior Density (CPD) intervals. Nef, effective female population size , kya, thousands of years ago.(TIF)Click here for additional data file.S4 FigInternal black dashed lines are median estimates and thin lines are the 95% CPD intervals. Thin green lines are the individual population trajectories. Nef, effective female population size , kya, thousands of years ago.(TIF)Click here for additional data file.


One of the major concerns in conservation today is the loss of genetic diversity which is a frequent consequence of population isolation and small population sizes. Fragmentation of populations and persecution of carnivores has posed a substantial threat to the persistence of free ranging carnivores in North America since the arrival of European settlers. Black bears have seen significant reductions in range size from their historic extent, which is most pronounced in the southeastern United States and even more starkly in Alabama where until recently bears were reduced to a single geographically isolated population in the Mobile River Basin. Recently a second population has naturally re-established itself in northeastern Alabama. We sought to determine size, genetic diversity and genetic connectivity for these two populations in relation to other regional populations. Both populations of black bears in Alabama had small population sizes and had moderate to low genetic diversity, but showed different levels of connectivity to surrounding populations of bears. The Mobile River Basin population had a small population size at only 86 individuals , the lowest genetic diversity of compared populations , and showed near complete genetic isolation from surrounding populations across multiple tests. The newly recolonizing population in northeastern Alabama had a small but growing population doubling in 3 years , relatively moderate genetic diversity compared to surrounding populations , and showed a high level of genetic connectivity with surrounding populations. One of the major concerns in conservation biology is the loss of genetic diversity , which iCarnivora are especially prone to population isolation, reduced population size, and ultimately loss of genetic diversity due to greater persecution, large home ranges, and high trophic level [Various factors such as trophic level, home range size, and reproduction rate make certain taxonomic groups of species at higher risk for these adverse population and genetic outcomes . For exaic level . Persecuic level . Furtheric level and vulneic level ,10,11. Fic level . Once reUrsus americanus) have suffered particularly sharp declines in population size and range in North America, creating conditions that would increase population isolation and decrease effective population sizes. Black bear ranges have been reduced 55% from the historical extent in North America, with an even more significant 80% reduction in the southeastern United States [Black bears , has peIn this study we aimed to evaluate the genetic diversity of these two populations and measure the factors that can influence diversity including population size and genetic connectivity to surrounding populations. Our objectives were to: 1. estimate the abundance and distribution of black bears in the core of both the MRB and NAL populations; 2. evaluate genetic connectivity with surrounding populations and 3. estimate the genetic diversity within each population and compare it to the genetic diversity of surrounding populations of black bears in the Southeastern United states. Such information will be useful for guiding future management actions aimed at promoting genetic diversity and in turn the fitness of black bears in Alabama.All sampling was done in accordance with the recommendations and permitting of the Auburn University Institutional Animal Care and Use Committee (protocol number 2012–2197) who approved this study. All samples were collected from properties with the permission of the private land owners or relevant land management agency. No permit was required from the state of Alabama, for non-invasive sampling.Bears within Alabama were sampled from two breeding populations. The MRB population samples were collected from Mobile and Washington counties in the south of the state between the Mississippi border and the Tombigbee River. The NAL samples were collected in the northeastern corner of the state in a small portion of Cherokee and DeKalb counties in and around Little River Canyon National Preserve. These two areas represent the entirety of breeding populations of black bears in Alabama .Within the MRB study area, bears utilized both natural and human-dominated landscapes. Natural and near natural habitat available to bears in the MRB varied from woody wetlands to pine plantations . Bears aThe NAL bear population had a core distribution in Little River National Preserve (LIRI) in DeKalb County. The habitat in this region was mountainous and dominated by deciduous forests and pine plantations . In addiFive comparison populations outside of Alabama were identified as possibly providing immigrants to Alabama, including two different populations in Georgia previously shown to be genetically isolated from each other North Georgia (NGA) and central Georgia , Missis2 cells  were provided by Dr. Michael Chamberlain of the University of Georgia’s Warnell School of Forestry and Natural Resources, as tissue samples from captured individuals. Northern Georgia (NGA) samples were obtained from the Georgia Department of Natural Resources as tissue samples from hunter-harvested bears. Dr. Jerrold L. Belant of Mississippi State University provided hair samples from a hair snaring study he conducted across Mississippi (MS). The Florida (FL) samples were hair samples collected from management activities conducted by the Florida Fish and Wildlife Conservation Commission. The samples from Tennessee (TN) were obtained from Dr. Joe Clark, in the form of DNA extract from hair samples collected by Katie Settlage, for her master’s thesis research ,29, Fig . GenotypDNA analysis of all collected samples was performed at the Laboratory for Ecological, Evolutionary and Conservation Genetics in the College of Natural Resources at the University of Idaho. DNA was extracted from samples using DNeasy Blood and Tissue Kits for hair and tissue and QIAamp Fast DNA Stool Mini Kit for scat . Hair and fecal samples were extracted in a lab space dedicated to the extraction of low quality DNA, and an extraction negative was included in each extraction to monitor for contamination. Collected scat samples were verified as bear using a mitochondrial DNA fragment species identification test as described in De Barba et al. (2014). Scat sasibs (probability that siblings share the same genotype) was calculated across all 14 microsatellite loci [sibs value, and the product of those values calculated starting with the two least powerful and adding another locus until the product reached an acceptable threshold  to confirm or refute differences. For NAL samples with a questionable match, the second multiplex was run, and a PIDsibs value of 0.03 was still maintained with only 8 loci, but out of 14 total . Individuals that were only represented by a single sample were required to have a Reliotype [All samples were amplified a minimum of two times to confirm a genotype. Two amplifications were required to confirm a heterozygotic genotype for all three sample types . Two amplifications were sufficient for confirmation of homozygotic genotypes for tissue and hair samples, but a third consensus genotype was require for confirmation of homozygotic genotypes derived from scat samples. Genotype matching was carried out in GenAlEx v6.5 . Sampleseliotype value of Samples collected from comparison populations  were run at all 14 loci. Additionally, once individuals were identified all loci and populations were evaluated as to whether they were in Hardy Weinberg Equilibrium . LinkagOnce samples were identified to individual, capture histories of each individual were created for analysis in capture-mark-recapture (CMR) models. The study areas extended well beyond the observed range of bears in Alabama, which was further supported by the distribution of snare success Figs  and 3. Ac,[Capture histories with the calculated spatial covariate and a sex covariate were then input into the program MARK . A Huggiulations ,50. To aulations  and N^ wes AICc,,52,53).,53.N^) fAdditionally, we analyzed the data with continuous occasion CMR models in the package Capwire  in R stua priori assumption of population membership of individuals. Model-based Bayesian clustering analysis was undertaken in the program STRUCTURE [The number of populations and grouping of individuals into populations was first evaluated to remove bias associated with any TRUCTURE –60. AdmiTRUCTURE  and confTRUCTURE . The staTRUCTURE . Due to TRUCTURE  and selePopulation assignment from STRUCTURE was confirmed utilizing a Discriminant Analysis of Principle Components . DAPC uPopulation structure among identified groups was evaluated utilizing Fst  and G”sto, He) [e) was calculated for both the MRB and NAL populations utilizing linkage disequilibrium methods corrected for missing data [Genetic diversity of all populations was estimated using observed and unbiased expected levels of heterozygosity   and alleo, He)  and FSTAo, He) , respecto, He) ,73. Finaing data ,75 usinging data .A total of 1935 samples of scat and hair were collected, of which 970 yielded consensus genotypes. In the MRB study area, 135 unique individuals were identified and in the NAL 32 unique individuals were identified  Tables. Samples used for population size analysis came strictly from hair snares, scat collection did not yield sufficient additional samples to justify the increased complexity of models necessary for its inclusion. Due to low recapture success in the MRB, only results from 2015 were used, which included 228 samples successfully identified to individual  collecteBoth study areas showed a restricted distribution of detections. Though trap density, extent, and layout varied year to year in NAL, the concentration of successful snares was consistently in and around Little River Canyon National Preserve . The MRBThe Huggins and Capwire closed capture models for the MRB provided qualitatively similar results. The two a priori Huggins models that remained after removing insignificant nested models as tested with LRT were a trap response only model and a trap response model with a constant effect from the spatial covariate . The latThe Huggins and Capwire models for the NAL showed similar qualitative agreement, and additionally showed a general agreement in the population trend from 2012–2015. After LRT, 5 Huggins models remained for consideration, of which the clear top model accounted for variation in survival between sexes, a trap response, and an equal effect of sex on both capture and recapture probabilities . The HugStructure analysis was initially run on all identified individuals. A clear plateau of the L(K) value was observed after K = 6, while the Evanno method showed substantial support for selection of a K = 2 . The twoThe second structure analysis with the MRB population reduced to 30 of the least related individuals showed a clear signal of K = 6 for both the L(K) and Evanno methods of K selection . K = 2 sThe DAPC analysis showed clear groupings of the principle components in agreement with the population assignment from STRUCTURE. To describe the data, 20 principle components were generated and 5 discriminant functions were used . The twoBoth the Fst and G”st statistics show a high level of genetic structure for bears in Alabama . The MRBe for the MRB population was 31.0 (95% CI: 20.5–47.4). Richness and He for the MRB were significantly different for 5 of 9 pairwise population comparisons (o (o of 0.56 (observed range 0.34–0.81), and He of 0.54 (observed range 0.33–0.77). Richness in the NAL population only differed significantly from the most diverse population measured (e for the NAL population was 3.4 (95% CI: 2.8–4.8).Black bears in Alabama show low to moderate genetic diversity when compared to surrounding populations. The MRB population had the lowest allelic richness at 2.15 alleles per locus, with all comparison populations ranging from 2.43–6.00 alleles per locus . Observeparisons  Tables aisons  will be critical to assessing the viability of the population.Having a complete picture of black bear genetics within Alabama and how they compare and interact regionally is particularly important as our results indicated that black bear populations in Alabama were extremely small. Both the NAL and MRB populations were estimated to be less than 100 individuals, with upper confidence limits on the estimates of less than 166 individuals. While small, the NAL population showed a clear growth trend, more than doubling in 3 years , which iOur spatially extensive sampling scheme allowed us to establish distribution patterns for both populations of black bears in Alabama. While previous analyses have suggested extensive suitable habitat for black bears in Alabama , both poWith the small population sizes of both populations, the genetic structure and interaction between Alabama bears and those of surrounding states is especially important for maintaining genetic diversity. The initial STRUCTURE analysis with all MRB samples included showed a clear division of the MRB population as a unique population, so much so that the Evanno method for K selection favored 2 populations the MRB and all others Figs  and 5. OOur results found that bears in eastern Mississippi were a part of the MRB population. The initial structure analysis reassigned 6 individuals from the eastern portion of the a priori MS population into the MRB population . ReassigThe NAL population of bears shows clear signs of being founded from the NGA population with a high level of separation from other populations. The second STRUCTURE analysis and DAPC clearly showed the NAL to be a distinct population, with NGA being a mixture of NAL and TN Figs  and 8. TThe current low level of structure between NAL and NGA could potentially be due to the recent founding of the NAL population. Bears have been present in NAL for roughly two generations , which we, easily explains the bears’ currently low genetic diversity. Bears in NAL display a more moderate level of genetic diversity, but that diversity is still in the lower range of observed diversity of bears in the southeastern U.S. The lower diversity and small Ne value of NAL bears is likely due to a founder effect. However, the NAL population still appears to have some level of connection with CGA  as well as μM concentration of primers used per individual sample for PCR, and thermocycler profile.(PDF)Click here for additional data file.S2 TableThe PIDsib values per locus is the probability that full siblings will share a genotype at that given locus. The product of the per locus PIDsib values gives the probability that full siblings share a genotype comprised of the included loci. We set a 0.03 threshold for a genotype PIDsib value. For the NAL population the threshold was met with 7 loci with multiplex 1, but rose to 8 when including both multiplexes due to lower diversity of some of the added markers. For the MRB population the threshold was met with 12 loci.(PDF)Click here for additional data file.S3 TableSummary of all samples collected and successfully genotyped for individual ID in the MRB study region. Individual totals account for total unique individuals.(PDF)Click here for additional data file.S4 TableSummary of all sample collected and successfully genotyped in the NAL study region. Individual totals account for total unique individuals.(PDF)Click here for additional data file.S5 TablePairwise Nemenyi post hoc p-values of a Kruskal-Wallis rank sum ANOVA of allelic richness estimates. Pairwise comparisons that are below a 0.05 p-value are highlighted.(PDF)Click here for additional data file.S6 Tablee estimates. Pairwise comparisons that are below a 0.05 p-value are highlighted.Pairwise Nemenyi post hoc p-values of a Kruskal-Wallis rank sum ANOVA of H(PDF)Click here for additional data file.S7 Tableo estimates. Pairwise comparisons that are below a 0.05 p-value are highlighted.Pairwise Nemenyi post hoc p-values of a Kruskal-Wallis rank sum ANOVA of H(PDF)Click here for additional data file.


SNP dataset to locate genome regions of an aquaculture strain (Saint John River) that were highly diverged from that of its putative wild founder population (Tobique River). First, admixed individuals with partial European ancestry were detected using STRUCTURE and removed from the dataset. Outlier loci were then identified as those showing extreme differentiation between the aquaculture population and the founder population. All Arlequin methods identified an overlapping subset of 17 outlier loci, three of which were also identified by BayeScan. Many outlier loci were near candidate genes and some were near published quantitative trait loci (QTLs) for growth, appetite, maturity, or disease resistance. Parallel comparisons using a wild, nonfounder population (Stewiacke River) yielded only one overlapping outlier locus as well as a known maturity QTL. We conclude that genome scans comparing a recently domesticated strain with its wild founder population can facilitate identification of candidate genes for traits known to have been under strong artificial selection.Comparative genome scans can be used to identify chromosome regions, but not traits, that are putatively under selection. Identification of targeted traits may be more likely in recently domesticated populations under strong artificial selection for increased production. We used a North American Atlantic salmon 6K  Domestication is the evolutionary process of genetic adaptation of wild animal populations to environmental conditions created deliberately or accidently by humans. This process can involve changes in morphological, physiological, behavioral, and life history traits  a hard sweep where a new favorable mutation at the major locus rapidly becomes fixed, initially resulting in a single long haplotype block surrounding the mutation that is well differentiated from the wild population along its entire length, (ii) a soft sweep where the frequency of a pre‐existing favorable allele at the major locus increases along with all the multiple original haplotypes containing it; the latter results in short haplotype blocks immediately surrounding the locus that are differentiated from the wild population but preserves pre‐existing variation in more distant regions . Changes in the genomes of different breeds of domesticated pigs detected by comparing SNP allele frequencies with those of ancestral wild boars are attributed to nearby genes under selection , with that of their putative wild founder population from the Tobique River, would be likely to identify genome regions underlying traits known to be under strong artificial selection in the hatchery environment. First, STRUCTURE was used to identify admixed individuals .All AQUA populations were primarily founded from four separate year classes of Atlantic salmon that were collected by staff from the Mactaquac Biodiversity Facility (MBF) hatchery Farmer, . The MBFThe subsequent 4–5 generations of each of the four separate AQUA populations were created by crossing the 50 male and the 100 female candidate broodstock with the highest estimated breeding values for saltwater growth in a paternal half‐sibling design .http://atlanticsalmonfederation.org/rivers/newbrunswick.html) could potentially have contributed to AQUA  can be characterized as two subspecies, the “North American” and the “European”   and those in the inner Bay of Fundy (iBoF) , using evidence from microsatellite analysis  showing Mendelian inheritance in our population and (ii) not significantly deviating from Hardy–Weinberg equilibrium were used for subsequent analyses. Nearly all SNP loci used in our analyses had been located on a North American Atlantic salmon female linkage map , thereby avoiding inappropriate clustering due to K being set too small  suggesting that their genotypes were admixed because of past hybridization.All individuals from the nine sampled putative populations were included in the Bayesian cluster population structure analysis with STRUCTURE 2.3.4  FDIST2, which compares the FST observed for a locus to the FST expected under neutrality relative to its observed heterozygosity assuming an “n‐island” model where the effective population size of all population is constant as is the pairwise population migration rate  values that also had p values <.01 as being outliers potentially under directional selection.Three of the outlier detection methods, Method 1 “nonhierarchical” using FDIST2, Method 2 “pairwise” using FDIST2, and Method 3 “hierarchical” island model, all used Arlequin 3.5's module “Detect loci under selection”  for each test , we then input all In the pairwise Arlequin analyses that we conducted for Method 2, we noticed that the outliers were very similar between the parent and grandparent generations of an AQUA population (Appendix S3). Therefore, for Methods 1 and 3, we merged the data for the parents (P) and the grandparents (G) into a single “combined” population.q‐values <0.05 were considered outliers .Method 4 used BayeScan, which employs a nonhierarchical Bayesian approach to detecting outlier loci  terms.Possible mechanisms of selection acting on outlier loci were investigated based on their similarity to known proteins. The translated DNA sequence that contained the outlier SNP was queried against the NCBI protein database (BLASTX). Simultaneously, we also referred to the “best hits” blast results for this SNP chip from Bourret, Dionne, et al. , who setSalmo salar genome to identify the location of 17 consistent outlier SNPs on the physical map of the Atlantic salmon genome  to find short DNA sequences containing the SNP that could be input into BLASTN. This allowed us to compare the position of each outlier SNP on the physical map with the position of conserved candidate genes in the growth hormone axis, gonadotropin axis, and the immune system that have recently been automatically annotated in physical map of the Atlantic salmon genome . We focused on locating adjacent genes but considered all genes in these categories within 5 Mb of the SNP. This was necessary because of the moderate density of the 6K SNP array in these North American populations.We also used BLASTN against the 2.6p‐value for a given QTL had been assigned to a SNP, subsequent QTLs for other traits from the same study would be assigned to adjacent SNPs. We then used each chromosome on the North American linkage map  was a marker with a significant p value for a published QTL for weight or for sexual maturity. This dataset was analyzed using a chi‐square test of association for the number of outliers and number of significant QTLs in each bin. In a second analysis, pairwise Pearson's correlation coefficients among the maximum values of four variables in each bin  for FST, −log10  for FCT, −log10  of a QTL, and the sum of significant QTLs) were calculated. Finally, a Manhattan plot was constructed to facilitate visual comparison between the positions of the outlier loci and that of the published QTLs. This used the continuous composite North American linkage map and −log10  for the QTLs from all ten datasets.We tested for colocalization of outlier loci and weight and maturity QTLs previously published for Atlantic salmon as has previously been done for whitefish  that did not exceed 5% in any population and then removed loci that clustered poorly because they were products of simultaneously genotyping duplicated regions  (Appendices S1–S6). A total of 3980 SNPs remained in our dataset of which 3901 could be located on the North American Atlantic salmon linkage map.3.2K = 2 groups gave the best fit to our dataset of nine putative populations . All samples known to have European ancestry were assigned to cluster 2 and were omitted from all subsequent analysis. STRUCTURE also identified 252 AQUA individuals that had more than 5% admixture from cluster 2  and these individuals were also deleted from our dataset. This left 687 individuals from five AQUA populations, 98 individuals from the TOB_WILD population, and 100 individuals from the STW_WILD population . Several of the AQUA populations were less related to each other (FST = 0.064 between 2009PO_AQUA and 2011PGN_AQUA) than they were to TOB_WILD (Table FST = 0.089) than from all of the AQUA populations. Pairwise comparisons were similar in rank whether Slatkin's linearized FST or Nei's mean number of pairwise differences was used as the standardized population distance between two populations. All pairwise population comparisons were significant at p < .001 . Two “parallel” loci (GCR_cBin15233_Ctg1_136_V2 and GCR_cBin27732_Ctg1_177) were consistently identified in pairwise comparisons of each of the six AQUA populations with the TOB_WILD population (Appendix S3).Method 2 identified an average of 39.2 and a total of 155 outlier loci under putatively divergent selection from the six pairwise comparisons between different AQUA populations and TOB_WILD population using FDIST2 (Appendix S3). SGoF+ verified that all 155 outliers had FCT outlier loci that were putatively under divergent selection between the AQUA and TOB_WILD populations. SGoF+ verified that all 54 outliers had q‐values <0.05. Of these 54 divergent FCT outlier loci, 31 were also significantly divergent FST outlier loci. Both types of outlier loci were well dispersed throughout the genome  for nonhierarchical FST analysis and thus were completely new outliers , found a total of 54 “high” FST outliers found by Method 1  and the set found by Method 3  strongly overlapped . Three of these 17 “consistent” outlier loci were also found by BayeScan . On the other hand, the hierarchical Arlequin analysis (Table S2) found a total of 47 high‐FCT outlier loci. Of these outlier loci, five were not significant (p < .01) for FST in either the nonhierarchical or hierarchical analyses and were therefore completely new outlier loci (Appendix S6). A highest number of significant high‐FCT loci were clustered on chromosomes Ssa13, Ssa15, and Ssa19 (Appendix S6). Of the five outlier SNPs identified as being between 55.1 and 63.0 cM on Ssa19 of the NA female map, two in BASS120_B7_F09 were identified as being in the intron of Importin‐4 predicted protein located on the physical map at position 74.253203 to 74.272976 Mb. The minor allele of one of three outlier SNPs in ContigGCR_hBin7522_Ctg1 (rs159404032) was identified by BLASTN to be mRNA XM_014173899 (100% identity 5e‐17) for coiled‐coil domain‐containing protein 138 (ccdc138) which is located on the physical map at 28.524355 to 28.538390 Mb on Ssa25 (CIGSSA_117402).The Method 1 nonhierarchical FDIST2 Arlequin analysis of the STW_WILD population and the six AQUA populations detected 54 outlier loci (Appendix S4) putatively under divergent selection. Just one of these (GCR_cBin8095_Ctg1_103) was also detected by both hierarchical and nonhierarchical Arlequin analyses of the AQUA populations with the TOB_WILD population (Appendices S1 and S5). This SNP was in the coding region of “protein phosphatase 1 regulatory subunit1B‐like” adjacent to the protein “stAR‐related lipid transfer protein 3‐like isoform X2”  did occur in the same regions of the linkage map as published QTL for growth and maturity  did not . In addition, the Pearson correlation between the maximum −log10p value of a QTL and the maximum −log10p value of a FCT outlier loci was not significant (Table S3). However, the correlation between the maximum −log10p value of a QTL and the maximum number of studies that had detected it was significant (Table S3).Manhattan plots showed that some as highly significant 44.1FST outlier loci  downstream from a genomic region associated with sea age in wild salmon populations . The geSsa09: 27.5 Mb and 52.7 cM female map) to one previously associated with sea age in wild Atlantic salmon populations   Table . Geneticr) Table  could ha4.4K = 2  STRUCTURE results  to remove individuals with more than 5% European ancestry from the subsequent genetic distance and outlier analyses . We acknowledge that, because of the small sample size of known pure and hybrid European fish included in our original STRUCTURE analysis, we were initially not confident that all of the 252 excluded fish had European ancestry. We also acknowledge that variation in our population sample size, which ranged from 8 to 268 for different populations in this study , appetite , sea age , and immune traits (MHC class2) into low‐density SNP assays so that the putative relationships with economically important traits can be validated in larger populations. The density of the 6K chip used here was too low to effectively detect fine‐scale patterns of among population divergence and within population homozygosity in response to population‐specific directional selection. More precise detection of long haplotype blocks from selective sweeps is now possible using the 220K SNP chip (Yáñez et al., This study detected two parallel and 17 consistently detected high‐To distinguish between linkages with causal genes and showing that a causal gene determines a quantitative trait, future eQTL work investigating the regulation of expression of candidate genes near the outlier loci discovered here might reveal their functional role in biological pathways. In this way, it may be possible to systematically elucidate how divergent selection between wild and farmed populations works on economically important quantitative traits. Relationships between the outlier SNPs and published QTLs will continue to be tested in more precise QTL‐mapping and GWAS studies using higher density SNP chips. Such studies would facilitate the application of modern marker‐assisted selection for the genetic improvement in Atlantic salmon stocks (e.g., Moen & Ødegård, http://dx.doi.org/10.5061/dryad.53b58.Data available from the Dryad Digital Repository:  Click here for additional data file. Click here for additional data file. Click here for additional data file.


HMGCR, ABCB1, VKORC1 and TCF7L2 are similar between Tunisian, Tuscan (TSI) and European (CEU). The genotype frequency of the variant rs776746 located in CYP3A5 gene is similar between Tunisian and African populations and different from CEU and TSI. The present study shows that the genetic make up of the Tunisian population is relatively complex in regard to pharmacogenes and reflects previous historical events. It is important to consider this ethnic difference in drug prescription in order to optimize drug response to avoid serious adverse drug reactions. Taking into account similarities with other neighboring populations, our study has an impact not only on the Tunisian population but also on North African population which are underrepresented in pharmacogenomic studies.Genetic variation is an important determinant affecting either drug response or susceptibility to adverse drug reactions. Several studies have highlighted the importance of ethnicity in influencing drug response variability that should be considered during drug development. Our objective is to characterize the genetic variability of some pharmacogenes involved in the response to drugs used for the treatment of Metabolic Syndrome (MetS) in Tunisia and to compare our results to the worldwide populations. A set of 135 Tunisians was genotyped using the Affymetrix Chip 6.0 genotyping array. Variants located in 24 Very Important Pharmacogenes (VIP) involved in MetS drug response were extracted from the genotyping data. Analysis of variant distribution in Tunisian population compared to 20 worldwide populations publicly available was performed using R software packages. Common variants between Tunisians and the 20 investigated populations were extracted from genotyping data. Multidimensional screening showed that Tunisian population is clustered with North African and European populations. The greatest divergence was observed with the African and Asian population. In addition, we performed Inter-ethnic comparison based on the genotype frequencies of five VIP biomarkers. The genotype frequencies of the biomarkers rs3846662, rs1045642, rs7294 and rs12255372 located respectively in  Drug response varies between individuals owing to disease heterogeneity, genetic and environmental factors –3. It deCYP2C9 and VKORC1 genes[VKORC1, rs1799853 and rs1057910 located in CYP2C9, and which are known to influence AVK dose requirement, has been highlighted [During the last years, the incorporation of pharmacogenetic testing in clinical trials has gained interest. This has been facilitated with the advancement in microarray based methods that allows genotyping Single Nucleotide Polymorphisms (SNPs) in many samples simultaneously. This method leads to the identification of loci responsible for drug response variability and adverse reactions , 13. DesRC1 genes, 21. Thehlighted . In addihlighted , metoprohlighted  and clophlighted , 26 was hlighted , 28. Othhlighted , 27, 29.A set of 135 Tunisian healthy individuals including; 32 women and 103 men, originating from two regions  were genotyped in a previous study  using thhttp://www.pharmgkb.org) which provides an overview of significant genes involved in the metabolism or response to one or several drugs. VIP genes were chosen through extensive review of a variety of sources, including the U.S. Food and Drug Administration (FDA) biomarker list, FDA-approved drug labels with pharmacogenetic information, and Clinical Pharmacogenetic Implementation Consortium (CPIC) nominations [We selected a set of very important pharmacogenes (VIP) involved in MetS components drug response from the PharmGKB database (inations . Additioftp://ftp.ncbi.nlm.nih.gov/hapmap/) and published data [PLINK v2  was usedhed data , 35. TheGenotypic data from other population mainly from South Europe and North Africa (Algeria (ALG), Egypt (EGY), Libya (LIB), Tunisia Douiret (TN_Ber), Lebanon (LEB), South Morocco (MCS), North Morocco (MCN), Sub-Saharan (SAH), South Spain (SPS), North Spain (SPN) Spain Basc (SBA) were download from the previous published study , 35.−4), minor allele frequency (MAF) < 10−2 and have missed genotyping rate ≥ to 95% for each of the studied populations.Genotypic data were managed using the PLINK v2 software. Variants were excluded if they are deviating from the Hardy-Weinberg equilibrium (HWE)  based on pruned genotypic data was performed using SNPrelate R package . CrypticThe genotype frequencies of the selected VIP in Tunisian population, were calculated and compared with 10 HapMap populations, using SNPassoc R package . In thisFixation Index (Fst) and Structure are two common analyses in population genetic studies. The R package Hierfstat  was usedBased on a large bibliographic search and PhamaGKB interrogation, we selected 24 pharmacogenes implicated in MetS components drug response modulation listed in For inter-ethnic genotypic frequency comparison and population structure analyses purposes, we kept 743 shared variants among the 22 worldwide studied populations. The MDS analysis describing the genetic landscape of these pharmacogenes shows a cluster of the Tunisian population with the North African populations , Tuscan and CEU were distinguished from the Asian and Sub Saharan African populations . This reHMGGR), rs1045642 (ABCB1), rs7294 (VKORC1) and rs12255372 (TCF7L2), were similar between the Tunisian population, Tuscany and the European populations (CEU); (p>>0.05/5*10). The genotypic frequencies of the rs776746 variant located in the CYP3A5 gene involved in the hypolipidemic susceptibility are similar between Tunisian and African populations  and significantly different from European (CEU) and Asian ; (p<<0.05/5*10)  .In order to assess the degree of similarity in the genetic structure between the different ethnic populations, we calculated the pairwise Fst values among the Tunisian population and the other 10 HapMap populations ranged from 0.00802 to 0.41201 . CompariBayesian-based STRUCTURE analysis  providedCYP2C9 and CYP2C19 variants implicated in the metabolism of anticoagulant response, concluded that Tunisians were similar to Europeans and Middle Easterners with regard to the allelic frequencies [In the recent years, the use of pharmacogenomics witnessed important success in the improvement of healthcare by developing therapeutic treatment and predicting individual response . Distribquencies . Pairwisquencies , 48–50. quencies . In the G>A transition located on chromosome 16 in the 3’Untranslated Region (UTR) of VKORC1 gene. This gene encodes the vitamin K epoxide reductase protein, which is a crucial enzyme in vitamin K cycle and therefore involved in inter-individual drug variability of the majority of coumarin derivatives, such as warfarin, acenocoumarol and phenprocoumon which are frequently prescribed as oral anticoagulants to treat and prevent thromboembolism [VKORC1 were associated with lower dose requirements and a higher risk of bleeding [TC or CC genotypes[TT genotype of rs7294 was generally lower in Tunisian population (0.09) than in African populations  respectively equal to  and East Asian populations   and similar to Europeans   and Central Asians (GIH) (0.03)  (0.03) . Indeed,A>G) transition is synonymous variant located on ABCB1 (MDR1) gene which is one of many ubiquitous adenosine triphosphate (ATP)-binding cassette (ABC) genes that is responsible for cellular homeostasis [ABCB1 C3435T (rs1045642) is extensively studied and some research showed that the ABCB1 C3435T genotype influences the absorption of clopidogrel [AA and AG genotypes of rs1045642 which respectively equal to , in Tunisian population, were respectively much lower than that are reported in other populations. . Homozygous individuals A/A exhibit 40% greater induction of full-length transcripts and 20% less alternatively spliced HMGCRv_1 transcript relative to A/G or G/G subjects [AA genotype of rs3846662 was associated with the increased induction of the alternatively spliced transcript is correlated with reduced response to simvastatin [AA genotype which consisted respectively to the values of . These results mirror that the African populations were more sensitive to the statin treatment than Tunisian population which seems having a response similar to the European    .C/T) variant located on CYP3A5 gene which is implicated in the biotransformation of the statin drugs, this variant creates a splice site in intron 3, resulting in altered mRNA splicing. The alternatively spliced isoform has an insertion in intron 3, which changes the reading frame and results in a premature termination codon and hences a non-functional protein[TT genotype are considered to be CYP3A5 poor metabolizes. Indeed, Subjects carrying this genotype have a poor response to lipid lowering drugs such as statin  [TT in Tunisian and African were low, it ranged between (0.01 to 0.08). Thus, these populations may have similar statin metabolism and will be of great clinical significance in determining future therapeutic approaches. Regarding the variant rs776746, our findings show that Tunisian population has significant similarities with African populations in predicted atorvastatin response. Yet, they display a distinct profile on PCA. This result could be due to the high heterogeneity of the Tunisian genetic structure composed of European, African, and Asian (Near Eastern) components. For this reason, it seems plausible that for some VIP variant, Tunisians are similar to the Europeans and for others, Tunisians are similar to the Africans. As stated in the study of Mizzi C et al,. 2016, the population groups are distinguished according to the results of PCA or admixture analysis using genotyping data. This approach cannot lead to broad generalizations in the application for VIP variants at the individual level. Although, the approaches aiming to identify clinically relevant actionable VIP variants are conducted in small number of variants. Moreover, this result is in agreement with other studies showing that there are multiple pharmacogenomic profiles across African and non African populations which could affect the safety and efficacy of many therapeutic drugs with CYP3A5 substrate [Rs776746 (l protein. Individastatin) , consequastatin) . The afoastatin) , 62. In ubstrate , 61. In ubstrate . Based oG>T located on chromosome 10 of TCF7L2 gene have been thoroughly studied and found to be associated with increased risk of T2DM [TCF7L2 affects susceptibility to the disease remain unraveled. Nevertheless, several studies have shown that decreased TCF7L2 protein expression inhibits the insulin secretory response to an oral glucose through impaired incretin action[TT patients undergoing early sulfonylurea treatment had approximately two-fold higher probability to fail the sulfonylureas medication (57% versus 17% for TT versus GG respectively)[TT genotype (0.19) is much lower than TSI, ASW, LWK, MKK and CHB  and much higher than CEU and MEX . Tunisian population seems to be good responder to Sulfonylureas which should be the first line drug for patients, replacing insulin injections. Genotyping the rs12255372 located in TCF7L2 should be considered when using Sulfonylureas treatment [The intronic variant rs12255372, transition 113049143  of T2DM , 65. Thein action. The GODin action. The resreatment .SNP array designed for the Genome Wide Association Study (GWAS) exploited in our study do not allow to fully assess the contributions of variants implicated in MetS drugs response due to the non-uniform coverage of all the chromosomal regions. Indeed, specialised pharmacovariants chip like DMET array increases the power to identify common and rare variations validated for their involvement in drugs metabolism –70.The current clinical pharmacogenomics practice considered that inter-individual drug response variability is mainly based on genetic common variants , 47, 71.The present study showed that Tunisian population is genetically heterogeneous regarding the studied pharmacogenes involved in the response to the MetS components. The allelic and genotypic frequencies do not differ homogenously among the components. This shows the complexity of the genetic components of response to treatment in admixed populations. This study should be extended to other North African population to take into account their peculiarities in order to effectively orient dose and drug prescription to ovoid serious adverse reactions.S1 Figftp://ftp.ncbi.nlm.nih.gov/hapmap/ and Algeria (ALG), Egyptia (EGY), Libya (LIB), Tunisia Dwiret TUN_Ber, Lebanon (LIB), Morocco South (MCS), Morocco North (MCN), Spain South (SPS), Spain North (SPN), Spain Basc (SBA),: Sub-Saharan (SAH), Canary Island (CIS); data from the literature.The plot reveals three distinct clusters showing that the Tunisian population present a close affinity with the North Africans and Europeans and distinct from South Africans and Asians. Tunisian population; Capital Tunis TU_TC, coastal city of Monastir TU_MC (AffymetrixChip 6.0 genotyping array), African ancestry in the south Western USA (ASW); a northwestern European population (CEU); the Han Chinese in Beijing, China (CHB); a Chinese population of metropolitan Denver, Colorado, USA (CHD); the Gujarati Indians in Houston, Texas, USA (GIH); the Japanese population in Tokyo, Japan (JPT); the Luhya people in Webuye, Kenya (LWK); people of Mexican ancestry living in Los Angeles, California, USA (MEX); the Maasai people in Kinyawa, Kenya (MKK); the Tuscan people of Italy (TSI); and the Yoruba in Ibadan, Nigeria (YRI); data from HapMap: (TIFF)Click here for additional data file.S2 FigThe figure shows the different bar plots according to the different K number.(DOCX)Click here for additional data file.S3 FigThe graph shows the best K equal to 3 according to delta K as proposed by Evanno.(TIF)Click here for additional data file.S4 Fig(TIF)Click here for additional data file.S1 TableThe table reveals the similarities or divergences of the Tunisian population to the other studied populations. This table highlight that the genotype frequencies of VIP variants significantly affect a population’s response to a given drug.(XLSX)Click here for additional data file.