Bettongia lesueur in a conservation translocation. Using single nucleotide polymorphisms (SNPs) identified from 215 individuals from multiple generations, we found an almost 2-fold increase in genetic diversity in the admixed translocation population compared to the founder populations, and this was maintained over time. Furthermore, hybrid class did not significantly impact on survivorship or the recruitment rate and therefore we found no indication of outbreeding depression. This study demonstrates the beneficial application of mixing multiple source populations in the conservation of threatened species for minimizing inbreeding and enhancing adaptive potential and overall fitness. Small and isolated populations are subject to the loss of genetic variation as a consequence of inbreeding and genetic drift, which in turn, can affect the fitness and long-term viability of populations. Translocations can be used as an effective conservation tool to combat this loss of genetic diversity through establishing new populations of threatened species, and to increase total population size. Releasing animals from multiple genetically diverged sources is one method to optimize genetic diversity in translocated populations. However, admixture as a conservation tool is rarely utilized due to the risks of outbreeding depression. Using high-resolution genomic markers through double-digest restriction site-associated sequencing (ddRAD-seq) and life history data collected over nine years of monitoring, this study investigates the genetic and fitness consequences of admixing two genetically-distinct subspecies of  Mammal species throughout the world have been subject to significant threats, particularly from invasive species ,2, and fTranslocations and reintroductions are widely proposed and used in conservation to counteract these demographic and genetic threats to small fragmented populations ,13,14,15Genetic variation is one factor which may influence the success of a translocation or reintroduction ,19. In pBurramys parvus) [Puma concolor coryi) [Canis lupus baileyi) [Canis lupus) [Vulpes lagopus) [Ovis Canadensis) [1 generation would be expected due to differences in allele frequencies between parental types, leading to high heterozygosity and subsequent high fitness [Further, the introduction of individuals into inbred populations can provide a ‘genetic rescue’ effect by infusing new genetic variation and relieving deleterious effects of inbreeding leading to improved fitness . This ph parvus) , the Flor coryi) ,22, the baileyi) , the Scas lupus) , the Scalagopus) , and theadensis) . Geneticadensis) , or by aadensis) . In admi fitness ,26.2 and beyond) [2 generation and, therefore, the frequency and severity of outbreeding depression in wild populations is yet to be fully understood [A possible unintended consequence of using admixture for conservation purposes is outbreeding depression, the reduction in fitness following the crossing of genetically divergent populations, which may be due to intrinsic factors, where co-adapted gene complexes may be disrupted leading to genic incompatibilities of hybridized populations, or extrinsic factors, where introduced alleles dilute locally adaptive alleles leading to reduced adaptation to the local environmental conditions ,28. As t beyond) . Few studerstood ,29. Despderstood , insectsderstood , birds [derstood , fish [3derstood ,34, and derstood .Admixture as a conservation method can be controversial due to concerns regarding whether the crossing of distinct populations will have the desired effect: to counteract inbreeding depression and recover genetic diversity; or the opposite effect: outbreeding depression and lack of viability ,27,28. CBettongia lesueur) to investigate the genetic and demographic implications of admixing highly diverged source populations in a translocation. Bettongia lesueur is listed as Vulnerable under the Australian Environmental Protection and Biodiversity Conservation Act 1999, and Conservation Dependent under the Western Australian Biodiversity Conservation Act 2016. Once widespread across two-thirds of mainland Australia  and Bettongia lesueur unnamed subspecies (Barrow Island). Multiple reintroductions to mainland Australia have been attempted  and genetic distinctness  between m et al. , the rism et al. . They alm et al. .Here, we use next-generation sequencing using double-digest restriction site-associated DNA sequencing (ddRAD-seq), in conjunction with accompanying long term fitness data from multiple generations of outcrossing to; (i) investigate the difference in genetic diversity between the founder populations and the admixed translocated population at nine years post-release, (ii) determine whether progressive introgression has led to the breakdown of genetic differentiation between the two populations over time, and (iii) examine whether survivorship and recruitment rate differ across hybrid generations, thereby testing for outbreeding depression. B. lesueur which were considered wild, self-sustaining, and have survived and reproduced for more than five years [In 2012, there were eight successful reintroductions of ve years . These iThe Matuwa population was established using individuals from Shark Bay, which were sourced from the Return to Dryandra Field Breeding Facility , hereafter referred to as Dryandra (DRY), and individuals directly sourced from Barrow Island (BWI) . Stock individuals for Dryandra were originally sourced from Dorre Island, Shark Bay . All MatAll genetic samples, including founder individuals, were collected by the Department of Biodiversity, Conservation and Attractions (DBCA) during regular population monitoring (capture-mark-recapture) trapping sessions at Matuwa between 2010 and 2018. Each trapped individual was microchipped, had a 2 mm tissue sample taken from its ear (stored in 70% ethanol), weighed, measured (head and pes length), and had their age and sex recorded. The reproductive status of females was also recorded by determining whether pouch young were present (including number and approximate length) or if they showed signs of lactation. Individuals were classified as adults if they had pouch young, one or more teats showing signs of lactation, or had a fully developed pouch or testes. B. lesueur is less likely to produce young. Data from individual trapping histories were used to assess fitness proxies (below). An additional year of trapping data (2019) was included in the fitness analyses but excluded from the genetic analyses as it was not available prior to the sample selection process. The presence of pouch young was not used in fitness analyses as trapping generally occurs around May when B. lesueur being more than three years [N = 12, Shark Bay N = 12) or ‘short lived’ strata category . Progeny samples  were further stratified based on when the individual was first trapped; individuals first trapped between 2010 and 2012 were classified as ‘caught early’ and individuals first trapped between 2010 and 2013 were classified as ‘caught late’. Progeny samples (N = 174) were then randomly selected within each of these strata categories; ‘long lived’, ‘short lived’, ‘caught early’ and ‘caught late’ . Double-digest restriction site-associated DNA sequencing (ddRAD-seq) libraries were prepared in batches of 96 samples (including a negative control and a minimum of two replicates within a plate and between plates). A total of 200 ng of DNA for each of 228 samples was sent to the Australian Genome Research Facility (AGRF) for ddRAD library preparation and Illumina sequencing. In brief, 50 ng of gDNA for each sample was digested using two restriction enzymes (PstI and Mspl) and ligated with unique barcoded adapters compatible with the restriction site overhang. Samples were purified and size selection (280–375 bp) carried out on the Blue Pippin (Sage Science). Libraries were PCR amplified with indexed primers and sequencing carried out on the Illumina NextSeq 500 with 150 cycles in HIGH-output mode over two flowcells. Short sequencing reads can be accessed via the Bioplatforms Australia data portal for the Oz Mammals Genomics Initiative  excluded from further analysis. Using the ustacks module, RAD loci were identified. Optimal parameters were systematically selected to maximize the number of polymorphic loci using the r80 optimization approach described by Paris et al. [m  from three to seven, and M  from one to eight. The effects of m and M parameter selection were evaluated based on the number of assembled loci, the number of polymorphic loci, and the number of SNPs for each value. The effects of m on stack depth/coverage was also evaluated. The optimal value of both m and M was chosen based on a trade-off between the highest retrieval of SNPs while minimizing errors. Following Paris et al. [M. Using the ustacks output, the cstacks module constructed a catalogue of consensus loci among individuals and the population module then restricted the data analysis to only the first SNP per locus minimizing linked SNPs for downstream analysis and required at least 20% of individuals in the founder population or admixed translocated population to process a locus for that population (r = 0.2). The resulting SNP dataset was output in a VCF format (http://dx.doi.org/10.17632/vg983472v3.1).STACKS v1.35 pipeline  was useds et al.  while als et al. . Optimizs et al.  recommen2) between alleles in each individual. Any loci with an r2 value greater than 0.2 was considered in LD and excluded. To avoid removing loci that are in LD or depart from Hardy-Weinberg expectations due to population structure, LD and Hardy-Weinberg were filtered separately for each founder population and for each year for the translocated population.To further improve genotyping quality for this study, loci with a minor allele frequency (MAF) less than 5%, minimum heterozygosity less than 5%, and a maximum heterozygosity greater than 95% were excluded using the program TASSEL Version 5 . Two datN = 22, DRY N = 24) or years of collection . To evaluate the genetic diversity within each of these groups, standard diversity indices were calculated in R version 3.5.1 using the package hierfstat [e) and average observed heterozygosity (Ho), number of alleles rarefied by sample size or allelic richness (AR), and the inbreeding coefficient (FIS) to quantify a deficit or excess in heterozygotes relative to random mating. The significant deviation of FIS values from Hardy-Weinberg Equilibrium were determined by calculating bootstrap confidence intervals corrected for multiple comparisons for 10,000 iterations. Individuals from 2010 were excluded from this analysis due to a small sample size (N = 4). For each genetic diversity or inbreeding parameter, differences among collection years and founder populations were tested using a Friedman’s ANOVA, with samples paired by locus using R version 3.5.1 [inbreedR [Analyses of genetic diversity were based on the 80% complete dataset, with samples grouped according to their population of origin  set to allow 90% of cumulative variance to be retained (100–110 PCs) with two clusters. Due to the social structuring associated with warren use of  lesueur  in conju lesueur  and visuadegenet . DAPC gradegenet . To achiK = 2). To ensure consistency in approximated ancestry proportions in our dataset, we also calculated Bayesian Markov chain Monte Carlo (MCMC) hybrid indexes using the R package gghybrid [The program fastSTRUCTURE  was usedgghybrid . This pagghybrid ,65. FST value of one. Allele frequencies for each of these loci (N = 954) were then calculated for each year of the Matuwa population in GenAlEx version 6.5 [To further assess patterns of introgression and changes in genetic composition within the admixed Matuwa population, variation in allele frequencies were calculated over time. This was achieved through VCFtools  where alsion 6.5 ,68.FST) between the parental populations. This was quantified using Arlequin Version 3.5 [FST values of the founder populations were calculated using default settings as part of the loci under selection method without the hierarchical island model. This dataset was then filtered manually in R, selecting the top 300 loci with an FST value equal to one. NEWHYBRIDS was then used to determine the hybrid class of each individual with a genotype frequency specified as; pure-bred Barrow Island (BWI: 1.0/0.0/0.0/0.0), pure-bred Dryandra (DRY: 0.0/0.0/0.0/1.0), F1 hybrid (F1: 0.0/0.5/0.5/0.0), F2 hybrid (F2: 0.25/0.25/0.25/0.25), backcross to pure-bred Barrow Island (F1×BWI: 0.5/0.25/0.25/0.0) and backcross to pure-bred Dryandra (F1×DRY: 0.0/0.25/0.25/0.5) [2. Since we would expect more than a single individual to belong to an advanced hybrid class after eight years, analysis was re-run using a dataset with a MAF of 0.2 (4995 SNPs) and 0.4 (1645 SNPs) to exclude rare alleles and increase the likelihood of detecting differences between hybrid classes [2 could not be detected in this study. This is likely a result of the NEWHYBRIDS program unable to detect the differentiation in interclass heterozygosity in these advanced hybrid generations [Using the 95% complete dataset, individuals from the Matuwa translocated population were assigned to one of six hybrid classes using the program NEWHYBRIDS . Due to sion 3.5 , where p.25/0.5) . Results classes . Resultserations ,71,72. TTo determine the impact of ancestry on fitness parameters  within the Matuwa population we used the R package openCR . OpenCR f) were tested to determine the best model to estimate recruitment. All JSSA models were fitted with both full and conditional likelihood forms. Models were compared using corrected AIC values with the best fit model selected based on the lowest AIC value [N = 67, DRY N = 87) were used for these analyses. Differences between covariate groups  were determined using a Friedman’s ANOVA paired by trapping session.Several reduced models were tested in openCR to determine which model was the best to estimate fitness proxies. The JSSA models with all recruitment parametrizations and the CJS model were tested to determine the best model to estimate apparent survivorship. JSSA models parameterized in terms of per capital recruitment . Similarly, Dryandra and each year of the translocated population also showed significant differences . The two founder populations were also found to have statistically significant differences in all genetic diversity parameters, with genetic diversity  being greater in the individuals from Barrow Island relative to the Dryandra individuals . In the admixed Matuwa population genetic diversity peaked in 2015 and then slightly decreased in later years . A total of 12,347 SNPs (80% complete) was used to assess genetic diversity and investigate the genetic structure of pulation . Pairwiser years . MLH wasIS values from both founder populations and all years in the translocated Matuwa population were found to be significantly different from zero  and were both significantly different to the translocated population . Average FIS values for the Matuwa samples typically decreased over time.Multi-locus From zero . AverageFST estimates show significant divergence between the two founder groups  and all collection years except for 2010 and 2011 significantly different from Barrow Island  and 2012 . This may be due to the small sample size of 2010 with only four individuals. Pairwise FST values ; 27% were classed as pure-bred Barrow Island, 23% were backcrossed to Barrow Island, 17% were classed as F1 hybrids, 14% were classed as F2 hybrids, 11% were classed as backcrossed to Dryandra and only 8% were designated as pure-bred Dryandra individuals. A total of 8182 SNPs (95% complete) were used to determine ancestry of all the progeny born at Matuwa that had a posterior probability above 0.8 in NEWHYBRIDS  and as expected, apparent survival was highest in the F1 hybrids. Both female and male F1 hybrids had statistically higher survival than all groups (p < 0.01) except F2 hybrids and individuals back-crossed to Dryandra (F1×DRY)  except for F1 hybrids and individuals backcrossed to either Barrow Island (F1×BWI) or Dryandra (F1×DRY). There was no statistically significant difference in survival between founder populations, however, male Barrow Island founders had significantly lower survival than male individuals backcrossed to Barrow Island (F1×BWI) (p < 0.05) and female Dryandra founders had significantly lower survival than pure-bred Barrow Island females from the Matuwa population  (p < 0.05), and pure-bred Dryandra individuals also had significantly lower survival rates than individuals that were backcrossed to Barrow Island (F1×BWI)  . F2 hybr2 = 182, df = 7, p < 0.01; 2 hybrids were found to have the highest recruitment rate and were significantly higher to all groups (p < 0.01) apart from Barrow Island founders and individuals backcrossed to Barrow Island ancestry (F1×BWI). Although F1 hybrids did not have as high recruitment as F2 hybrids, recruitment was still significantly higher than individuals backcrossed to Dryandra (F1×DRY) (p < 0.01) and DRY founders  except pure-bred Barrow Island (BWI) and Dryandra (DRY) individuals as well as individuals backcrossed to DRY (F1×DRY). Individuals backcrossed to Dryandra (F1×DRY) were found to have no recruitment within the population.Recruitment between founder populations was found to be significantly different with Barrow Island founders having a higher recruitment  was observed to be higher relative to both founder populations, potentially resulting in improved adaptive potential for this population to respond to environmental changes. This increase in genetic diversity is a direct result of mixing the two genetically distinct subspecies, which have been isolated for a relatively long period of time thereby different sets of alleles having occurred as a result of genetic drift [IS values of all years in the translocated population may be reflective of mating between individuals with difference ancestries to be non-random [The immigration of new individuals into small inbred populations is predicted to improve genetic diversity and decrease the proportion of individuals that are homozygous for alleles identical by descent ,26. Simiic drift ,76. Furtic drift ,77,78, an-random . Howevern-random ,24,77,78Population structure analyses indicated genetic differentiation between the Matuwa translocated population and their founding groups. The translocated population was initially significantly divergent from both founder populations and this pattern changed over time as the translocated population became more genetically similar to the Barrow Island population. This could be due to selection favoring Barrow Island alleles over Dryandra alleles , from demographic effects, such as social structuring within the population ,79, the Within the Matuwa population, ancestry proportions were variable across individuals and through time. The four individuals captured in 2010 were found to be of Barrow Island ancestry and were trapped at approximately similar times to when the Dryandra founders were released. Admixed individuals were present in 2011, the first year after all founders were initially released, and by 2015 almost all individuals were hybrids. In later years, there was a clear bias towards the Barrow Island ancestry despite only 67 founding individuals being released in comparison to the 87 Dryandra individuals. This pattern of a higher proportion of ancestry from one founder in a mixed population was also observed at Roxby Downs . It was 1 and F2 hybrids. The improved survival of F1 and F2 hybrids likely reflects heterozygosity masking the expression of deleterious recessive alleles (dominance effects), heterozygote advantage (overdominance) or possibly positive epistasis, whereby recombination of new genotypes provides a favorable interaction enabling higher survival rates and subsequent fitness [2 hybrids had significantly improved recruitment relative to all other hybrid classes, except for Barrow Island founders and individuals backcrossed to Barrow Island ancestry (F1×BWI), and although this was not observed in the F1 generation, this effect may also be explained by positive epistasis or the action of complementary genes where the combination of alleles with additive effects from each of the parental populations results in a complementary interaction [Genetic admixing can increase the fitness of individuals through heterosis ,26. This fitness ,84. Furteraction .B. lesueur and how this may differ between subspecies and in novel environments. Therefore, it is difficult to predict the behavioral consequences when admixing populations and how this may lead to assortative mating within the translocated population and the subsequent impact on genetic diversity and fitness. While individuals with Barrow Island ancestry were found to have higher survival and recruitment in comparison to individuals with Dryandra ancestry, hybrid generation classes were not found to be statistically different . Individuals backcrossed to Dryandra ancestry were found to have no recruitment within the population. Nearly all (95%) of individuals from this hybrid class were trapped prior to 2017, and since sexual maturity is expected to be reached within a year, we would expect to detect some recruitment. The observed recruitment bias may reflect intrinsic incompatibilities between source populations becoming apparent only when hybrid individuals have a high proportion of Dryandra ancestry. However, given the low recruitment of individuals with a pure Dryandra ancestry, and the consistently high recruitment of other hybrid classes, it is more likely that this reflects an overall lower recruitment rate of the Dryandra population lineage. Although morphology was not investigated in this study, Thavornkanlapachai  demonstrB. lesueur to date. Previous studies have demonstrated that admixture of diverged populations substantially increases genetic diversity in reintroduced populations, even when divergence between populations was low [These results emphasize the positive impact admixing multiple sources can have on genetic diversity with no apparent fitness consequences or outbreeding depression indicated for  was low ,77,78,86 was low ,28. Howe was low , and the2 and beyond) to adequately evaluate the outcomes of admixing and the long-term viability of translocated populations.While no negative consequences were found in regards to survivorship, there is concern in regard to the lack of recruitment of individuals backcrossed to Dryandra ancestry and how this may be contributing to the suspected continued asymmetrical introgression. This generation class and Dryandra founders were the only group to have lower recruitment and therefore lower fitness, and the genetic mechanisms behind this trend remain largely unknown. Regardless of whether admixture results in improved fitness, the mixing of multiple source populations will decrease the risks of inbreeding depression. This study further highlights the importance of genetic monitoring over multiple generations (F


Daphnia, present in a wide range of water bodies, are an important component of freshwater ecosystems. In contrast to their high dispersal capacity through diapausing eggs carried by waterfowl, Daphnia often exhibit strong population genetic differentiation. Here, to test for common patterns in the population genetic structure of a widespread Holarctic species, D. galeata, we genotyped two sets of populations collected from geographically distant areas: across 13 lakes in Eastern China and 14 lakes in Central Europe. The majority of these populations were genotyped at two types of markers: a mitochondrial gene (for 12S rRNA) and 15 nuclear microsatellite loci.The zooplanktonic cladocerans D. galeata, with distinct haplotype compositions in the two study regions but one widely distributed haplotype shared between several of the Chinese as well as European populations. At microsatellite markers, clear separation was observed at both large (between China and Europe) and small (within Europe) geographical scales, as demonstrated by Factorial Correspondence Analyses, Bayesian assignment and a clustering method based on genetic distances. Genetic diversity was comparable between the sets of Chinese and European D. galeata populations for both types of markers. Interestingly, we observed a significant association between genetic distance and geographical distance for D. galeata populations in China but not in Europe.Mitochondrial DNA demonstrated relatively shallow divergence within D. galeata across wide expanses of the Palaearctic, with one mtDNA lineage of D. galeata successfully establishing over large distances. Despite a clear differentiation of Chinese and European D. galeata at a nuclear level, the pattern of genetic variation is nevertheless similar between both regions. Overall, our findings provide insights into the genetic population structure of a cladoceran species with extremely wide geographical range.Our results indicate relatively recent spread of The online version of this article (10.1186/s12862-018-1256-4) contains supplementary material, which is available to authorized users. A major challenge in our understanding of biodiversity is why certain species have a wide distribution, spanning several biogeographical regions, while others have much more restricted ranges or are endemic. The cosmopolitanism view  holds thDaphnia galeata G. O. Sars, 1863, to improve our understanding of its dispersal and genetic diversity over small and large geographic scales. Daphnia (Anomopoda: Daphniidae) are important components of freshwater ecosystems, being grazers of phytoplankton as well as a key prey item of planktivorous fish [Daphnia are cyclical parthenogens; females mostly reproduce clonally by giving birth to parthenogenetic daughters. In unfavourable environments, however, Daphnia switch to the production of males and sexual eggs which require fertilization, and then enter diapause in a gastrula stage [Daphnia galeata, a member of the D. longispina complex , has a ised in: , being cised in: –16). Thiwl e.g. , 18). Su. SuDaphnes .D. galeata populations across Holarctic continents, using both a mitochondrial DNA (mtDNA) marker and a conservative nuclear marker (i.e. HSP90). One major mtDNA type of D. galeata was detected throughout the Holarctic with some haplotypes shared over long distances, even between Europe and North America. At the nuclear marker level, however, New and Old World D. galeata were clearly differentiated [D. dentifera to D. galeata in the New World. However, populations from China, where D. galeata is a very common zooplankter [D. galeata across China revealed low mtDNA variation; a common D. galeata haplotype (as resolved by sequencing of 12S rRNA and cytochrome c oxidase subunit I) was widespread across China, Japan, Siberia and the Western Palaearctic [D. galeata populations even on a relatively small geographical scale .D. longispina complex, D. galeata [D. galeata populations  using two types of markers, a mitochondrial gene (12S rDNA region) and 15 nuclear microsatellite loci. In the case of mtDNA, we expected pronounced divergence of D. galeata between the two study regions, but low variation within them, as mitochondrial DNA usually has low resolution to detect subtle within-species population differentiation . When apossible .Daphnia galeata localities were analysed in this study . Among D. galeata populations were processed for analyses of microsatellites. The individual DNA extractions followed the protocol reported in [D. galeata genotype (G100 from Europe) was used as a positive control to adjust for small differences in fragment length of identical alleles among runs. Genotypes were scored using GeneMapper version 3.7 (Applied Biosystems), and the alleles at each locus were defined by their fragment length (in base pairs). About 40 adult D. galeata females were genotyped from each Chinese population . Re. ReD. gaex  wer species , 24  and their interspecific hybrids, were included as reference taxa in FCA  were analysed separately. New Hybrids then assigned the newly analysed individuals together with reference individuals into six possible classes . The analysis was run for 106 iterations after a burn-in of length 106, and the probability threshold for taxon identification was set to 90%. Only individuals with pure D. galeata assignments were used further. We applied Factorial Correspondence Analysis (FCA) on all 25  used in . Forty-n used in ). Then,  used in  was applD. galeata populations between and within regions, a similar FCA was run as described above, but without the reference genotypes. In order to identify genetically homogenous groups across all 25 D. galeata populations, a Bayesian algorithm was applied in STRUCTURE V2.3.4 [K groups. For each tested value of K (i.e. 1 to 25), ten independent runs were performed and, for each run, 105 iterations were carried out after a burn-in period of 105 iterations. The most likely K was determined by the distribution of ΔK, following the methods of Evanno et al. [K: 1 to 13) and 12 European (K: 1 to 12) D. galeata populations, respectively. Next, the genetic similarity among populations from different regions was estimated by constructing an Unweighted Pair-Group Method with Arithmetic Mean (UPGMA) dendrogram based on Nei’s genetic distances [D. galeata populations into the following components: 1) between regions , 2) among populations within regions, and 3) among individuals within populations. To estimate genetic differentiation among D. galeata populations for each region, the fixation index FST was calculated in Arlequin 3.11 with 104 permutations. Finally, the correlation between pairwise geographical distance and pairwise FST was computed using a Mantel test , in FSTAT v.2.9.3.2 [D. galeata from VIR and ZEL . The le.2.9.3.2 . D. galefunction .Daphnia communities in China , they ah) and nucleotide diversity (π) for the 12S sequences were calculated in DnaSP Version 5 [t test . The unique haplotypes were identified in Arlequin, and then aligned together with 12S reference sequences of the D. longispina complex, including D. galeata from Asia (Japan) and Europe . FCA of these D. galeata individuals (without reference genotypes) revealed two main clusters clearly separating Chinese and European populations . There was evidence of genetic isolation by distance for Chinese D. galeata populations , but not for European ones . No MLGs were shared among populations on continental or on local scales.The AMOVA showed that most of the variation in the microsatellite dataset was explained by a within-population component (48%) while another significant component was between regions (33%), followed by within-region variation  were assigned to ata Fig. ; among tDaphnia species, D. galeata. Specifically, multiple populations of D. galeata, sampled from two remote geographical regions , were screened using mitochondrial (12S) and nuclear markers (microsatellites). One of seventeen mitochondrial haplotypes described here was shared between European and Chinese populations. This haplotype (CES) was also widespread within both regions, having been detected in eight out of eleven studied European populations and four out of thirteen Chinese populations. The network analysis  and nine remaining populations. The separation of these three populations was well supported by FCA, clustering method based on genetic distances  and UPGMA analysis. The clear genetic separation between Chinese and European populations could be explained by the large geographical isolation between these two parts of the Palaearctic. However, the geographical position of localities of D. galeata populations within Europe was not associated with their genetic similarity, suggesting gene flow occurs within regions. A genetic separation of VIR, ZEL and GOSL from other D. galeata populations in Europe might have resulted from introgression of D. cucullata to D. galeata. In all three localities, we detected D. cucullata . This suggests that the introgression of the mitochondrial genome occurs after initial hybridization, as observed in other animals , whereangispina , 48, 49.ls e.g. , 51)..D. galeaD. galeata populations from China (but not from Europe). One explanation for the discrepancy could be that studied European D. galeata habitats are ecologically more variable than the mostly eutrophic Chinese lakes [D. longispina complex assemblages [D. longispina complex where mixed results were reported. Specifically, a significant association between genetic distance  and geographical distance was detected for other taxa of the D. longispina complex [D. longispina, no signal for genetic isolation by distance was observed [Interestingly, there was a significant association between genetic distance and geographical distance for se lakes . In addiemblages . Because complex  but in aobserved .D. galeata populations investigated here, regardless of their origin, showed high relative clonal richness values (as assessed by microsatellites), likely a result of frequent sexual reproduction, which recreates genotypic variation. High clonal richness of D. galeata populations was also observed previously . Howeveelection . Many poelection , may surelection , 57.D. galeata populations from two regions, i.e., Eastern China and Central Europe, were found to be clearly separated from each other, which was confirmed by three types of analyses . This principal finding was supported by mitochondrial DNA data; however, we detected in both regions a common and widespread mtDNA haplotype that was shared across the whole Palaearctic. Our finding calls for further studies to investigate the colonization history of D. galeata, and zooplankton in general, in China and adjacent regions.A high number of polymorphic nuclear loci and their codominant inheritance often provide fine resolution in detecting genetic structure . Here, bAdditional file 1:Table S1. Reference sequences of the D. longispina complex used in phylogenetic analyses. (DOCX 15 kb)Additional file 2:Figure S1. UPGMA clustering of D. galeata populations sampled from Eastern China and Central Europe based on microsatellite polymorphism at 15 loci. For lake abbreviations see Table


Euterpe edulis in the Brazilian Atlantic Forest. Genetic sampling and experiments were performed in old‐growth remnants of two forest types with higher  and lower biogeographic association and environmental similarities (Submontane Rainforest vs. Restinga Forest). We first assessed the molecular genetic differentiation among populations, focusing on the group of loci potentially under selection in each forest, using single‐nucleotide polymorphism (SNPs) outliers. Further, we looked for potential adaptive divergence among populations in a common garden experiment and in reciprocal transplants for two plant development phases: seedling establishment and sapling growth. Analysis with outlier loci indicated that all individuals from the Semideciduous Forest formed a single group, while another group was formed by overlapping individuals from Submontane Rainforest and Restinga Forest. Molecular differentiation was corroborated by reciprocal transplants, which yielded strong evidence of local adaptations for seedling establishment in the biogeographically divergent Rainforest and Semideciduous Forest, but not for Restinga Forest and Submontane Rainforest. Phenotypic plasticity for palm seedling establishment favors range expansion to biogeographically related or recently colonized forest types, while persistence in the newly colonized ecosystem may be favored by local adaptations if climatic conditions diverge over time, reducing gene flow between populations. SNPs obtained by next‐generation sequencing can help exploring adaptive genetic variation in tropical trees, which impose several challenges to the use of reciprocal transplants.One of the most intriguing questions in plant ecology is which evolutionary strategy allows widely distributed species to increase their ecological range and grow in changing environmental conditions. Phenotypic plasticity and local adaptations are major processes governing species range margins, but little is known about their relative contribution for tree species distribution in tropical forest regions. We investigated the relative role of phenotypic plasticity and local adaptation in the ecological distribution of the widespread palm  E. edulis is the only species of this genus found in the Atlantic Forest, out of the center of endemism of Euterpe in the Amazon. Invasion of the E. edulis ancestor into the Atlantic Forest may have occurred in northeastern Brazil during the Pliocene and Pleistocene, when the climate was more humid and the Atlantic Forest was connected to the Amazon in this region . The invasion of Restinga Forests by E. edulis individuals coming from neighboring Submontane Rainforests is a contemporary and continuous process that may increase gene flow, as Lowland and Submontane Rainforests have always been connected to Restinga Forests , but molecular analysis with isoenzymes did not find relevant differentiation  and sapling development  for each local provenance in each site, while we expected phenotypic plasticity to lead to among‐site variations in the aforementioned traits, regardless of the superior plant performance of local genotypes.Our main hypothesis is that phenotypic plasticity is sufficient for expanding To test the aforementioned predictions, we combined two methods traditionally employed in evolutionary studies  with a novel molecular approach to estimate the adaptive differentiation among populations, using single‐nucleotide polymorphisms (SNPs). The use of these traditional methods for a tropical palm in different forest types, integrated into SNP analysis, may further contribute to advance the investigation methods of phenotypic plasticity and adaptation in tropical forests. Reciprocal transplants have predominantly been applied for herbaceous and shrubby species growing in temperate regions  involved in local adaptation, with reduced cost even in nonmodel species , all of them located in the state of São Paulo, southeastern Brazil , Carlos Botelho State Park , and Ilha do Cardoso State Park  of ~10 mm diameter and 0.6 g of dry weight  at least 100 m apart from each other. The samples were stored in liquid nitrogen in the field and further transferred to a −80°C freezer in the laboratory. Genomic DNA was extracted from root tissues using a standard cetyltrimethyl ammonium bromide protocol  and maximum distance allowed between stacks to merge them into a locus (M = 2). With tags formed by ustacks, we built a catalog with cstacks to serve as a reference genome. Sets of stacks constructed by the ustacks program were matched against the catalog through the sstacks program. Afterward, the genotypes of the individuals were corrected with the rxstacks program, based on the data from populations. The populations package was used for filtering the dataset to obtain good‐quality SNPs for the calculation of population genomic statistics, following the criteria: minimum minor allele frequency (min_maf = 0.01); minimum stack depth of coverage required for each individual (m = 3); and minimum percentage of individuals in a population required to process a locus for that population (r = 0.6).We used the program HE) and observed heterozygosity (HO), using the PopGeneKit package , allelic richness (AR), and inbreeding coefficients (Fis), using the R package diversity  according to an island model with neutral markers  of 0.1. Outlier SNPs were used in nucleotide searches with BLASTx against the genomic database of the National Center for Biotechnology Information, using blast2go . We used the same seed lots, obtained from the same mother palms in a single harvesting event, for all the experiments.2.5E. edulis seedling production. Two saplings produced with the seeds from each mother palm , thus reproducing the sapling design of seed collection, were grown in plastic pots (22 cm height × 13 cm diameter) containing fertilized soil, which were randomly distributed and kept in forest nursery conditions  were randomly planted in each plot 30 cm apart from each other (30 seedlings per plot). Sapling growth performance was evaluated according to the survival, total dry mass, and root–shoot dry mass ratio of 12‐month‐old saplings  Faraway, . When co33.1E. edulis populations detected 501 neutral SNPs that were used for genomic analysis and 307 outlier loci, with 84 of these possibly under divergent selection and 223 putatively under balancing selection. Overall, genomic diversity parameters were similar among populations, but average allelic richness was significantly higher in the Semideciduous Forest . We found a low level of genetic differentiation between Rainforest and Restinga Forest populations (pairwise FST = 0.01), and intermediate levels between these two populations and the Semideciduous Forest population , while only 12 were found for Rainforest versus Restinga Forest. The number of contigs with a significant number of blast hits in the GenBank database followed a similar pattern: 10 for Semideciduous Forest versus Rainforest, 12 for Semideciduous Forests versus Restinga forest, and only one for Rainforest versus Restinga Forest. Only one outlier locus was shared among all three populations  and with s Figure . The gens Figure . Within s Figure .3.2F57,2 = 1.50) and dry mass of roots , shoot , leaves , and the whole individual  of saplings grown in the common garden experiment (Exp. #1). However, substantial effects on seed provenance were observed in the reciprocal transplants using seeds and seedlings , site of transplant was selected for the model. Seed provenance and its combination with site of transplant were selected by most models  showed reduced molecular differentiation and no evidence of local adaptation (or genotypic differentiation). The relative contribution of phenotypic plasticity and local adaptations in favoring range expansion of E. edulis therefore depended on the biogeographic context.As expected, the more biogeographically divergent ecosystems  showed marked neutral and adaptive molecular divergences of populations and substantial evidence of local adaptations. On the other hand, the more closely associated ecosystems (i.e., Rainforest and E. edulis seeds are recalcitrant and highly sensitive to desiccation (Brancalion et al., In the Semideciduous Forest, the potential local adaptations were related to seedling emergence, which resulted in higher seedling density in the absence of differential mortality and higher root–shoot dry mass ratio for saplings. Seedlings of the Rainforest provenance showed higher aboveground mass in all sites of transplants, which is an indication that early seedling growth can be a major selective filter in humid and shaded forests. In addition, we observed reduced seedling mortality for the local provenance in the Rainforest site when compared to Semideciduous Forest seedlings, which can be related to differential shade tolerance. We observed in the field that seedlings from the Semideciduous population were more subjected to damping off than seedlings of the local provenance. Soil pathogens exert a substantial impact on tree seedling survival (Bertacchi et al., Restinga Forest populations. We are aware that the number of SNPs analyzed is limited to make claims about the genetic targets of selection, but this number was sufficient to distinguish among studied populations in terms of their adaptive divergences. A greater number of genotypes are being analyzed to confirm the results obtained here, as suggested in the studies of Fraser, McGaughran, and Chuah (Restinga sites, which can be the result of an inherently reduced vigor of Restinga Forest populations (Figure Restinga Forest gene pools can be considered a subset of the gene pool of neighboring Rainforests, founder effects could have led to stronger genetic drift and to inbreeding depression. However, we did not find any evidence of inbreeding depression in the molecular analysis, so the explanation for the reduced performance of Restinga Forest seedlings and saplings remains unclear. Adult individuals of E. edulis growing in the studied Restinga forest are much smaller than those growing in the Submontane Rainforest studied, and this difference was, so far, solely attributed to differential soil nutrient content and salinity (Brancalion et al., In contrast to the genetic differentiation observed between Semideciduous Forest and Rainforest populations, we did not find clear evidence for differentiation between Rainforest and nd Chuah . The Rais Figure . As RestThe use of potentially adaptive SNPs allowed the discrimination of populations according to their potential adaptive divergences, as did neutral microsatellite markers and reciprocal transplants, so the use of this novel approach of genetic analysis may not necessarily yield novel findings in evolutionary studies. Although we have identified the cellular component and molecular function associated with the regions of the genome under selection, we could not associate this information with any specific adaptive traits. On the other hand, linking the supposed cellular and molecular functions to adaptive traits measured in reciprocal transplants and common garden experiments may pave the way for novel findings on the study of local adaptations in plant populations.The common garden experiment was an ineffective approach for this species (but see Brancalion et al.  for the None declared.PHSB, GCXO, and RRR designed the common garden and reciprocal transplant experiments; PHSB implemented and evaluated these experiments; PHSB, MIZ, and MN collected genetic material and performed molecular analysis; SSZ and JM provided support on statistical analysis; RLC provided critical support on palm ecology and evolution; PHSB wrote a first version of the manuscript, and all authors helped to improve it through subsequent reviews.We intend to archive our data on Zenodo. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Decapterus maruadsi, a typical pelagic fish, over most of its range in the northern SCS. A 828–832 bp fragment of mitochondrial control region were sequenced in 241 individuals from 11 locations. High haplotype diversity (0.905–0.980) and low nucleotide diversity (0.00269–0.00849) was detected, revealing low levels of genetic diversity. Demographic history analysis revealed a pattern of decline and subsequent rapid growth in the effective population size during deglaciation, which showed that D. maruadsi experienced recent demographic expansion after a period of low effective population size. Genetic diversity, genetic structure, and phylogenetic relationship analysis all demonstrated that no significant genetic differentiation existed among the populations, indicating that D. maruadsi was panmictic throughout the northern SCS. Periodic sea-level changes, fluctuation of the East Asian Monsoon, and Kuroshio variability were responsible for the population decline and expansion of D. maruadsi. The demographic history was the primary reason for the low levels of genetic diversity and the lack of significant genetic structure. The life history characteristics and ocean currents also had a strong correlation with the genetic homogeneity of D. maruadsi. However, the genetic structure of the population (genetic homogeneity) is inconsistent with biological characteristics (significant difference), which is an important reminder to identify and manage the D. maruadsi population carefully.Late Pleistocene climate oscillations are believed to have greatly influenced the distribution, population dynamics, and genetic variation of many marine organisms in the western Pacific. However, the impact of the late Pleistocene climate cycles on the demographic history and population genetics of pelagic fish in the northern South China Sea (SCS) remains largely unexplored. In this study, we explored the demographic history, genetic structure, and genetic diversity of  The rempresent) . Meanwhipresent) . Nutrienpresent) . Thus, tpresent) . These hpresent) . HoweverDecapterus maruadsi , is a warm-water pelagic fish of the family Carangidae . It is widely distributed in the coastal waters of the western Pacific, including those near China, Korea, and Japan . The exposure of the shallow continental shelf of the northern SCS during the late Pleistocene climate fluctuations would inevitably change the population abundance, demographic history, and genetic variation of D. maruadsi. For these reasons, D. maruadsi is a good fish with which to research the effects of paleoclimatic fluctuations on the demographic history and population genetics of pelagic fish in the northern SCS.The round scad, nd Japan . It is ond Japan . The ann in 2002 . In the eristics . The fiseristics . MoreoveD. maruadsi have mainly focused on resource and fishery biology and little is known about their demographic history. Although the population genetics of D. maruadsi in the northern SCS have been analyzed by mitochondrial cytochrome b (Cyt b) sequence variation , which are fundamental to proper short-term management , the Zhuhai inshore water , the Yangjiang inshore water , the Maoming inshore water , the Zhanjiang inshore water , the Wenchang inshore water , the Sanya inshore water , the Sanya offshore water , the Baimajing inshore water , the Baimajing offshore water , and the Beihai inshore water . After morphological identification, muscle tissues were taken from individual fish and stored in 95% ethanol at −20 °C until DNA extraction.Two hundred forty-one adult hern SCS  namely, 2O, 5 µL 10 × EasyTaq buffer, 1 µL dNTP mixture (10 mM), 1 µL forward primer , 1 µL reverse primer  , and 2 µL template DNA (50–100 ng). PCR reactions were performed in a Veriti 96 Well Fast Thermal Cycler  under the following parameters: initial denaturation at 94 °C for 5 min followed by 35 cycles of 45 s denaturation at 94 °C, 45 s annealing at 55 °C, and 1 min elongation at 72 °C. The amplification cycle finished with a final elongation at 72 °C for 10 min. All sets of PCR included a negative control reaction tube in which all reagents were included except the template DNA. The PCR products were separated by electrophoresis on 1.2% agarose gel and the Trans 2K DNA Marker  was used for identifying the target gene size. Successfully amplified PCR products were sent to GenScript Biotech  for sequencing.Total genomic DNA was extracted from muscle tissue using the phenol-chloroform protocol . PolymerCTTT-3′) , 2.5U Eah), nucleotide diversity (π), the mean number of pairwise differences (K), indels, and polymorphic sites, were calculated using the software Arlequin 3.5  and Decapterus macrosoma (GenBank accession number: KF841444) mtDNA control regions were used as the outgroup. The genealogical relationship among the haplotypes was further evaluated using the media-joining network constructed with Network 5.0.0.3 software  values between populations with 10,000 permutations. An exact test of population differentiation based on haplotype frequencies was also examined with 100,000 steps in the Markov Chain. AMOVA, FST , and the exact test were all calculated using the software Arlequin 3.5.Hierarchical analysis of molecular variance (AMOVA) with 10,000 permutations was performed to test the population genetic structure of D. maruadsi for all populations pooled together were calculated using three different approaches. First, Tajima’s D and Fu’s Fs neutrality tests with 10,000 permutations were calculated in Arlequin 3.5 to test the selective neutrality of the D. maruadsi control region. Secondly, nucleotide mismatch distribution was performed in Arlequin 3.5 and DnaSP 5.10.01 (Hri). The statistical significance was estimated with 1,000 bootstrap replicates. Finally, the Bayesian skyline plot was implemented in BEAST 1.7.5 under the HKY+G+I nucleotide substitution model and strict molecular clock model to estimate the change in effective population size across time  was used for the Bayesian skyline plot analysis of D. maruadsi in the present study  to 0.00849 (SY1) and from 2.233 (ZJ) to 7.053 (SY1), respectively. This showed that the SY1 population had the highest level of genetic diversity, while the ZJ population had the lowest. The overall π and K were 0.00443 and 3.691, respectively, indicating low levels of genetic diversity in the D. maruadsi population in the northern SCS.The partial length sequences of the control region were 828–832 bp. The calculated genetic variations were summarized in MK294641–MK294734), of which 20 (21.28%) were shared among populations, with a relative frequency ranging from 0.83% to 15.77%  to 0.058 (between ZJ and SY2) and were statistically non-significant .Pairwise nificant . Hierarcnificant  revealedD statistics  and Fu’s Fs test  were negative and highly significant in pooled samples. The mismatch distributions of D. maruadsi for all populations pooled together showed a unimodal pattern under the sudden expansion model (p = 0.840) and Hri  were small and statistically non-significant, which showed no significant deviation between the observed distributions and expected distributions. Under the constant population size model, a poor goodness-of-fit was found between the observed and expected distributions. Both the neutrality test and mismatch distribution analyses suggested a recent population demographic expansion for D. maruadsi populations in the northern SCS. However, a low migrants per generation (M < 50) was detected under the spatial expansion model. This may lead to a larger variance of mismatch distribution and incorrectly estimating the parameters for spatial expansion , and exact tests  among three geographic groups and the other three populations . This indicated that low sample sizes for YJ, ZJ, and SY2 have not influenced the results of this study.To detect artificial statistical bias due to a low sample size from YJ, ZJ, and SY2 populations, some adjacent geographical populations were combined into three geographic groups for genetic differentiation analysis, including the western Guangdong group , Sanya group , and Baimajing group . Genetic homogeneity was demonstrated by AMOVA , pairwisD. maruadsi in the northern SCS experienced a rapid demographic expansion after a period of low effective population size during the Holocene. The results suggested better conditions  after the LGM driving the population expansion of D. maruadsi.This study revealed D. maruadsi widely distributes in the northern shallow continental shelf of the SCS within 180 m and its spawning grounds are located mainly in shallow nearshore waters less than 120 m . However, the subsequent rising sea-level of the postglacial-Holocene provided new niche space for D. maruadsi, leading to sustained and rapid growth in the effective population size of this species. Similar patterns of population dynamics have been revealed for some marine fishes in response to the postglacial rising sea-level in the northern SCS ) than the LGM (< 25gC/(m2⋅103a)) ) . The sigD. maruadsi. Similar phenomena have been reported in other fish species, such as Pampus echinogaster  and 42 g (dominant body weight = 20–60 g), respectively; while those in the eastern Hainan Island are 158.7 mm (dominant fork length = 130–220 mm) and 102.5 g (dominant body weight = 70–140 g), respectively (D. maruadsi in the northern SCS (D. maruadsi populations carefully. However, owing to maternal inheritance, the mtDNA control region sequence provides no information about male migration and has some limitations in respect of fishery management (D. maruadsi in the northern SCS.The lack of significant genetic structure implies that ectively . Additiohern SCS . For exahern SCS . The potnagement . Thus, fD. maruadsi in the northern SCS. LGM-Holocene climate change gave rise to drastic changes in the habitat and paleo-productivity, which resulted in the recent rapid population expansion. The demographic history is considered to be responsible for the low levels of genetic diversity for D. maruadsi in the northern SCS. The low genetic diversity suggests that the environmental adaptive capacity and evolutionary potential of D. maruadsi may decline from a long-term evolutionary perspective. This reminds us to strengthen fishery resource management and protection in order to sustain the productivity of D. maruadsi in the northern SCS. Moreover, no significant genetic differentiation was detected among the D. maruadsi populations, which has a close correlation to recent rapid population expansion, the dispersion of planktonic eggs and larvae on ocean currents, and overlapping spawning time and spawning grounds. However, owing to the potential mismatch between the population’s genetic structure and biological characteristics and some accuracy limitations of mtDNA to the appropriate identification of the population structure and MUs, the lack of significant genetic structure does not mean that D. maruadsi in the northern SCS should be managed as a single unit.The present study reveals that LGM-Holocene climate oscillations had an important impact on the demographic history, genetic structure, and genetic diversity of 10.7717/peerj.7953/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.7953/supp-2Supplemental Information 2Click here for additional data file.


Vireo atricapilla) populations in tandem with a demographic study  to elucidate if central Texas populations act as a source‐sink system. We genotyped 343 individuals at 12 microsatellite loci to elucidate the movement ecology of the black‐capped vireo in central Texas surrounding Fort Hood; the largest and most stable breeding population of black‐capped vireos inhabit Fort Hood. To gain insight into gene flow among populations, we analyzed genetic differentiation, migration rates, number of migrants, and parentage. We found statistically significant, but low levels of genetic differentiation among several populations, suggesting some limited restriction to gene flow. Across approaches to estimate migration, we found consistent evidence for asymmetrical movement from Fort Hood to the other central Texas sites consistent with source‐sink dynamics. Our results are complementary to black‐capped vireo demographic studies done in tandem showing that portions of Fort Hood are acting as a source population to smaller central Texas populations.Habitat fragmentation can produce metapopulations or source‐sink systems in which dispersal in crucial for population maintenance. Our objective was to investigate connectivity among black‐capped vireo ( While habitat loss and fragmentation are often conflated Fahrig, , here thFragmentation can produce metapopulations by leaving behind pockets of seemingly isolated populations that can stabilizing force by providing necessary immigrants to bolster populations  is a formerly endangered migratory songbird dependent on early successional habitats throughout much of its U.S. breeding range , a by‐product of fragmentation , or eastern screech owl (Megascops asio) song playback. We banded each bird with a unique U.S. Geological Survey band and a unique three color band combination. Birds were aged and sexed using reliable molt limits in the plumage , Taylor Valley (TV), Jack Mountain (JM), Manning 2 (MM), Maxdale (MD), and West Range (WR)] and the surrounding central Texas habitat patches  in central Texas in June of 2014 and 2015 , expected heterozygosity (He), and FIS per locus to evaluate genetic diversity in black‐capped vireos at each study site , standardized by sample size, for each study site  to determine differences between study sites , linkage disequilibrium (LD), and null alleles using GENEPOP . Fort Hood sites WR, JM, MM, and TA were pooled to for a new site labeled West Range Combined (WRc). The last Fort Hood site, MD was left as its own site. The remaining analysis used the resulting six sample sites: SS, BC, CB, ERc, MD, and WRc. We did not combine Fort Hood sites further as they are separated in space and have a history of being genetically differentiated  present with our study sites. We evaluated k values from 1 to 7, with 10 iterations, 100,000 burn‐in period and 100,000 MCMC (Monte Carlo Markov Chain) repetitions. We used the Puechmaille method to determine k in STRUCTURESELECTOR, which accounts for uneven sampling across populations and hierarchical population structure . We used the admixture model with population as a prior in STRUCTURE to determine the number of clusters  and BAYESASS (v 3.0.4). We estimated gene flow directly by first generation migrant detection in GENECLASS. We detected migrants using the Paetkau, Slade, Burden, and Estoup  simulatitimation . BAYEASSn = 174) (with a minimum of six loci genotyped) to candidate after‐second‐year parents (n = 134) which included 39 candidate mothers and 85 candidate fathers  to detect direct migration among populations  and were excluded from further analyses. None of the locus pairs were out of LD for any population following a sequential Bonferroni correction. There were no significant differences among populations as assessed by estimates of He, Ho, and Ar . We found nine pairs of populations to be significantly differentiated after a sequential Bonferroni correction  to 83.2% . All other sites contributed <5% of individuals to other sampled populations through migration, with the majority contributing <1% of individuals.Most black‐capped vireo individuals remained at their putative natal population, based on p‐value <0.01 using GENECLASS2 . Central Texas sites had low levels of migrants (<15% across sites); however, migrants comprised a larger proportion of the central Texas populations (2%–8%) compared to that of Fort Hood populations  that are isolated by surrounding grazing lands and human development. Habitat fragmentation has been responsible for restricting gene flow and subsequent population structuring in avian species across habitat types at comparable spatial scales , source populations with population growth, and sink populations with population decline (Peery et al., Conservation efforts for the black‐capped vireo should reflect knowledge of source‐sink dynamics in Texas surrounding Fort Hood, the strong‐hold for the species. Small, isolated populations, such as those of the central Texas sites, tend to be less reproductively successful due to nest parasitism and would go extinct without contributions through immigration (Diffendorfer, In conclusion, the present study inferred dispersal from Fort Hood to central Texas populations using molecular markers. We found evidence for significant population structuring with high gene flow, consistent with gene flow patterns of a metapopulation. Moreover, through multiple methods, we consistently demonstrated asymmetrical movement from Fort Hood to central Texas sites. Our results are in concordance with the collaborative demographic data (Walker et al., Samantha Hauser genotyped samples, analyzed data, and wrote the paper. Lauren Walker sampled black‐capped vireo blood samples, toenail clips, and pin feathers, extracted DNA from samples. Paul Leberg oversaw research and contributed to revisions to the paper.Microsatellite primers: Genbank accession numbers: EF363782 ‐ EF363795. Sampling locations and microsatellite genotypes will be available on Dryad.


Dascyllus trimaculatus in the Red Sea, Arabian Sea and Western Indian Ocean, using 1174 single nucleotide polymorphisms (SNPs). Neutral loci revealed a signature of weak genetic differentiation between the Northwestern (Red Sea and Arabian Sea) and Western Indian Ocean biogeographic provinces. Loci potentially under selection (outlier loci) revealed a similar pattern but with a much stronger signal of genetic structure between regions. The Oman population appears to be genetically distinct from all other populations included in the analysis. While we could not clearly identify the mechanisms driving these patterns , the datasets indicate that population-level divergences are largely concordant with biogeographic boundaries based on species composition. Our data can be used along with genetic connectivity of other species to identify the common genetic breaks that need to be considered for the conservation of biodiversity and evolutionary processes in the poorly studied Western Indian Ocean region.Population genetic analysis is an important tool for estimating the degree of evolutionary connectivity in marine organisms. Here, we investigate the population structure of the three-spot damselfish  To undeet al. ), a larget al. , revealiet al. .Dascyllus trimaculatus and determine whether they matched established biogeographic boundaries.Over the past two decades, there have been numerous phylogeographic studies of Indo-Pacific reef fishes, but comparatively few have examined patterns of population connectivity within the Western Indian Ocean ,6. At thScarus ghobban [Neosarmatium meinerti [Chaetodon trifasciatus [Epinephelus merra and Myripristis berndti also showed evidence of structure within the WIO [In general, studies that have sampled populations in the Indian Ocean find results ranging from no genetic structure ,8–15, to ghobban  and the meinerti . Some daasciatus . Detaile the WIO ,26.D. trimaculatus is an abundant species found throughout the Indo-Pacific [Dascyllus trimaculatus belongs to a species complex that comprises four species, D. trimaculatus, D. albisella, D. strasburgi and D. auripinnis [D. trimaculatus occupies nearly the entire Indo-Pacific range except the Hawaiian Archipelago, the Marquesas Islands, and the Line Islands, whereas the closely related D. albisella, D. strasburgi and D. auripinnis are only present in those restricted peripheral ranges, respectively [Dascyllus trimaculatus populations show patterns of allopatric divergence—as the Pacific Ocean populations are distinct from those of the Indian Ocean, these populations were probably isolated by restricted water flow in the Sunda Shelf during the Pleistocene sea-level changes [D. auripinnis, which has a bright yellow ventral surface and fins, is not fully genetically differentiated from D. trimaculatus. By contrast, only D. trimaculatus is present in the Indian Ocean and mitochondrial DNA (d-loop) and microsatellite comparisons showed these populations belong to a single clade [The three-spot damselfish, -Pacific , from th-Pacific  producin-Pacific , and has-Pacific . Juvenil-Pacific ,29. Dascripinnis . The recripinnis , as D. tectively . Dascyll changes . In the le clade .D. trimaculatus. Since recent biogeographic studies have found that in some species genetic boundaries match biogeographic regions in the Indian Ocean [D. trimaculatus shows moderate amounts of genetic structure throughout its range with evidence of divergence in the species complex in peripheral habitats [D. trimaculatus, D. aruanus and D. marginatus decreases as sea surface temperatures and food availability increase from north to south [D. trimaculatus, which in turn might influence its genetic structure. Currents near the African coast may also affect the genetic connectivity of D. trimaculatus in the Indian Ocean. The main oceanic current in the Indian Ocean is the South Equatorial Current  developed using restriction-site associated DNA sequencing (RADseq) to assess the population structure in Indian Ocean an Ocean , and bechabitats , we conshabitats , but curhabitats . In the to south . These rIn this study, we assessed differences between populations from the Red Sea, Arabian Peninsula, African coast, Mozambique Channel and Chagos Archipelago. We also tested for population divergence between the biogeographic NWIO and WIO provinces. To the best of our knowledge, this is one of the first studies based on extensive genomic data to compare population genetic structures in the Western Indian Ocean that simultaneously covers these two provinces.2.2.1.et al. [A total of 93 individuals from seven populations were collected while diving or snorkelling between 1998 and 2013 . Populatet al. ,34.2.2.stacks v. 1.09 [stacks ‘de novo_map.pl' pipeline, while the ‘populations' script was used to filter loci and create output files . Loci were shared between the seven populations (p = 7), in at least 65% of individuals within a group (r = 0.65) and with a coverage of 8× (m = 8). We used only the first SNP of each sequence and removed loci with minor allele frequencies lower than 1.5% . Our quality control and filtering resulted in a total of 1174 loci and a data matrix that was 84% complete. We used pgdspider 2.0 [structure files into other formats.Genomic DNA was extracted using the Qiagen DNeasy animal blood and tissue kit . The library was prepared using the double-digest RADseq protocol , with mo v. 1.09 . Loci weider 2.0  to conve2.3.n = 1174). Then, to gain more perspective on the patterns of genetic structure and its potential mechanisms, we separated neutral from outlier loci, and repeated the population genetic analyses with the neutral subset and the subset of outliers that had higher than expected FST based on neutral expectations (see below).First, we conducted population genetic analysis with all the loci  loci with fST values significantly lower than expected, and (iii) neutral loci with fST values within the expected range. The possible adaptive value of the outlier loci was explored by blasting their sequences in the NCBI nucleotide database and looking for match with genes and their functions. The search on the database nucleotide collection (nr/nt) was optimized for somewhat similar sequences (Blastn), with the default algorithm options.To identify outlier loci, we used three methods. First, we used the modified approach  implemenarlequin , which u of 0.01  using th[lositan  that alsscan 2.1 . The anafST [arlequin; for the latter, sequential Bonferroni corrections were applied [adegenet [structure [fST/(1 − fST) and minimum ocean distance with Mantel tests performed using genepop [To test for genetic structure, we conducted hierarchical AMOVAs and calculated pairwise fST  using ar applied . Discrim applied  were exeadegenet  for R  to identify potential gene functions, but no significant alignments were found .A total of 1174 loci were obtained for 93 individuals. The three outlier loci methods combined identified 26 outlier loci with high arlequin before further corrections) and all population genetic results remained unchanged, except for some fST pairwise comparisons , also identified 32 outliers potentially under balancing selection (lower than expected fST). Based on these results, we generated three datasets for the population genetic analysis: (i) all loci (n = 1174), (ii) neutral loci (n = 1117), and (iii) outlier loci (n = 25). Note that the 32 outliers thought to be under balancing selection were excluded from the neutral dataset.The n = 1174) showed evidence of a population structure within our study region. We found a global FST of 0.0127 (p < 0.0001). Pairwise FST comparisons  indicate that DJI and OMA are significantly different from all other populations, while the NRS is different from all except MAY and JNO. An AMOVA showed a very low but significant divergence between the NWIO  and the WIO  . However, structure analysis did not resolve any population clusters, while DAPC results suggest that Oman is distinct from other populations . Finally, there was statistically significant IBD , but the slope is low and there is not a strong model fit.Analyses of all loci (n = 1117) indicated high genetic connectivity and weak differentiation between the two provinces (NWIO and WIO). Global FST was low but significant , Pairwise FST comparisons showed that the population in Oman (OMA) stood out and it was significantly different from all other populations , while the DAPC analysis shows a close relationship among all populations except Oman  showed strong genetic differentiation between provinces. Global FST for the outliers was 0.3271 (p < 0.0001), and all the pairwise comparisons were significant except between Zanzibar and Diego Garcia (Chagos Archipelago), and between Zanzibar and Juan de Nova . The DAPC analysis also identified separation of the NWIO and WIO provinces (structure suggest the presence of two clusters (K = 2) that closely match the DAPC results , and the DAPC results for this dataset indicate that the populations of Oman, Djibouti and the Northern Red Sea are distinct from each other. These results suggest that gene flow is variable across the genome and it may be affected by different processes and/or operate at different scales. However, it is important to acknowledge that variation in recombination rate could also explain patterns of divergence across the genome [The present study revealed significant genetic structure between Northwestern and Western Indian Ocean populations of undaries . In addie genome .Habitat discontinuities, deep-water upwellings and the direction of prevailing currents  could beD. trimaculatus. After the last glacial maximum 26.5 to 19 kya, populations of many species began to expand into the Red Sea and Persian Gulf as habitat opened up [Sea-level fluctuations may also contribute to the observed pattern, as the Red Sea was subject to periods of extreme isolation when sea level dropped as much as 130 m below current levels during the Pleistocene . In somepened up . When a pened up . Unlike pened up ,54 and cD. trimaculatus and other species. During the summer months, the waters between the Arabian Peninsula and the Red Sea become the world's hottest sea, while in the winter they become one of the coldest environments for coral reef growth [In contrast with the more stable WIO, the NWIO is one of the most variable and environmentally extreme regions in the tropical oceans . Such dif growth . The Redf growth  (see elef growth ,56,57. Af growth  and may While it is difficult to distinguish between divergence driven by selection and drift, it is important to note that these processes are not mutually exclusive and could be acting in concert on populations found around the region, given its complex geologic history and heterogeneous environment. It is possible that physical barriers between the provinces are semipermeable, allowing for restricted dispersal, and environmental contrasts between provinces reinforce those barriers through selection. Because population sizes fluctuate with sea level, the founder effect can also influence our results: population expansions after isolation can promote adaptation if colonizing individuals carry beneficial mutations . In our Despite the lack of a clear causal mechanism, our data can be used along with data on genetic connectivity of other species to identify the common genetic breaks that need to be considered for the conservation of biodiversity and evolutionary processes in the poorly studied Western Indian Ocean region. Our results suggest that the Red Sea and Arabian populations should be managed separately from the greater Western Indian Ocean population, and the role of adaptive versus neutral variation must be examined further.


Gir is one of the main cattle breeds raised in tropical South American countries. Strong artificial selection through its domestication resulted in increased genetic differentiation among the countries in recent years. Over the years, genomic studies in Gir have become more common. However, studies of population structure and signatures of selection in divergent Gir populations are scarce and need more attention to better understand genetic differentiation, gene flow, and genetic distance. Genotypes of 173 animals selected for growth traits and 273 animals selected for milk production were used in this study. Clear genetic differentiation between beef and dairy populations was observed. Different criteria led to genetic divergence and genetic differences in allele frequencies between the two populations. Gene segregation in each population was forced by artificial selection, promoting isolation, and increasing genetic variation between them. Results showed evidence of selective forces in different regions of the genome. A total of 282 genes were detected under selection in the test population based on the fixation index (Fst), integrated haplotype score (iHS), and cross-population extend haplotype homozygosity (XP-EHH) approaches. The QTL mapping identified 35 genes associated with reproduction, milk composition, growth, meat and carcass, health, or body conformation traits. The investigation of genes and pathways showed that quantitative traits associated to fertility, milk production, beef quality, and growth were involved in the process of differentiation of these populations. These results would support further investigations of population structure and differentiation in the Gir breed. Bos indicus cattle breeds native from India that was first introduced in Brazil in late 1800s. Although Gir is an important breed for milk production in tropical South American countries, small populations are still found in North America and Australia. Few animals (<700) were imported in Brazil between 1870 and 1962. In 1938, the Brazilian Association of Zebu Cattle Breeders (ABCZ) started the registration of Gir cattle . A Among all the Gir breeding or research programs in Brazil, two are of special interest: a) PNMGL aims improving milk production traits; b) IZ, which is considered unique, aims improving beef production traits in a closed herd scheme. The PNMGL was created in 1985 to conduct progeny testing programs  aAfter adjustment for FDR within the population, SNPs displaying piHS values greater than or equal to 2.10  were considered significant for the beef population. For the dairy population, the cutoff value was 2.20 . The "fdrtool" package allows the computation of local FDR values from p-values while taking into account an empirical null model . The appSLC24A4 (solute carrier family 24 member 4) gene located on chromosome 21 was common in the two populations, which can be clearly confirmed by the iHS plots  were identified based on the XP-EHH statistics. Two SNPs were located in the region of the UGT1A1 gene, and two SNPs were located in the region of the WNT7A gene. The UGT1A1 gene was located on chromosome 3 and encodes a critical enzyme that transforms small lipophilic molecules, such as steroids, hormones, and drugs, into excretable metabolites maintaining homeostasis  in BLCORL and NCAPG genes to the cattle QTL database showed that both genes were associated with reproduction, growth, and meat and carcass traits. They are all located on chromosome 6. A number of QTL terms have been reported for cattle in the region of NCAPG and LCORL genes [LCORL and NCAPG were identified based on iHS test in the dairy population.Next, we compared our gene list with QTL regions previously reported in cattle and available for online search. In total, 35 genes with signatures of selection overlapped with QTL regions. Mapping RL genes , 72. TheKCNIP4, ANXA4, FTO, EGFR, and PAK1), reproduction , milk composition , meat and carcass , health , and body conformation . More details can be found in the supplementary Other genes with selection signatures that had overlapped with QTL terms were found being associated with production  were identified in those genomic regions, which is not suitable for a functional analysis.The dataset used for DAVID v.6.8 comprised 142, 23, 43, and 94 genes identified based on Fst, iHS beef, iHS dairy, and XP-EHH dairy tests, respectively. Regarding to the XP-EHH beef test analysis, only seven genes (The significant (P<0.05) GO terms  and KEGG pathways identified with Fst, iHS dairy, and XP-EHH dairy tests are described in Longissimus dorsi muscle from Qinchuan cattle [Longissimus dorsi intramuscular adipose tissue in Hanwoo cattle [Trypanosoma congolense [Salmonella enterica [Mycobacterium bovis [The regulation of the actin cytoskeleton (bta04810) and tight junction (bta04530) are pathways from the cellular process class, related to cellular community and cell motility, respectively. The actin cytoskeleton is a dynamic skeletal cell structure that contains actin and associated proteins, which has been associated with important functions in several biological processes including early development of oocyte organization and maturation , tendernn cattle , Longisso cattle , responso cattle  and calfo cattle , and resngolense , Salmoneenterica , and Mycum bovis .Tight junctions are essential for establishing a selectively permeable barrier to diffusion through the paracellular space between cells, which are composed of transmembrane proteins that are involved in junction assembly, barrier regulation, cell polarity, gene transcription, and among other pathways. Tight junctions are known to be related to milk mammary gland development and milk secretion, controlling the transport of lactose and K+ to the extracellular fluid, whereas Cl− and Na+ are transported into milk , 82. SinThe functional enrichment analysis with the XP-EHH dairy test results revealed one GO molecular function and three GO biological processes . The GTPEven though we used a tool available in the fdrtool R package  to contrThe number of animals used in the present study is not a major concern in the structure and signatures of selection analysis. Several studies have focused on reduced number of animals per population, for example, <150 animals , 90 and The use of non-related animals in population structure studies is difficult in livestock species, although the choice for non-related animals allows for high genetic differentiation. For a small livestock population, the choice for animals to be genotyped are usually made by their importance in the herd. It is possible that the genotyped animals are related because breeding programs use tools as non-random mating systems and reproductive technologies, which can increase the inbreeding level in the population. In the case of Gir cattle, the level of inbreeding is high and the effective population size is small for the dairy  and the We found evidence of signatures of selection for two Gir cattle populations artificially selected for different purposes . The detection of selection signatures used here can act as complementary information to current gene mapping approaches (GWAS). By comparing candidate gene regions found through the identification of selection signatures and GWAS, it is possible to test the contribution of genes under selection to phenotypes, which can subsequently be used in genomic selection . The finHigh-throughput genomic information such as SNP markers can be successfully used to study the population structure and to identify genomic regions undergone divergent selection in Gir cattle. The difference in breeding history was able to imprint a degree of genomic differentiation for both beef and dairy populations. The patterns of genotypic variation in Gir cattle were consistent with the presence of selective pressures at some point in the history of the beef and dairy populations. These findings can provide complementary information on genomic regions of interest for functional genomic studies, genome-wide associations, and the implementation of breeding schemes aiming genetic improvement and conservation of livestock populations.S1 Fig(TIF)Click here for additional data file.S1 File(XLSX)Click here for additional data file.


Adansonia digitata L.) is an iconic tree of African savannahs. Its multipurpose character and nutritional composition of fruits and leaves offer high economic and social potential for local communities. There is an urgent need to characterize the genetic diversity of the Kenyan baobab populations in order to facilitate further conservation and domestication programmes. This study aims at documenting the genetic diversity and structure of baobab populations in southeastern Kenya. Leaf or bark samples were collected from 189 baobab trees in seven populations distributed in two geographical groups, i.e. four inland and three coastal populations. Nine microsatellite loci were used to assess genetic diversity. Overall, genetic diversity of the species was high and similarly distributed over the populations. Bayesian clustering and principal coordinate analysis congruently divided the populations into two distinct clusters, suggesting significant differences between inland and coastal populations. The genetic differentiation between coastal and inland populations suggests a limited possibility of gene flow between these populations. Further conservation and domestications studies should take into consideration thegeographical origin of trees and more attention should be paid to morphological characterization of fruits and leaves of the coastal and inland populations to understand the causes and the impact of the differentiation.Baobab ( The tportance . Baobabsportance . Mainly Baobab is considered to be a semi-domesticated species . Humans However, with increasing market demand and changing climate, the pressure on natural populations may negatively influence their viability. Domestication and sustainable cultivation of baobabs can be an option to increase production and at the same time conserve current natural populations . HoweverA. digitata [A. digitata of West African versus South/East African origin. From East Africa, A. digitata was introduced by migrating people to the Indian subcontinent, most probably from coastal regions of Kenya and Tanzania [In the current study, the genetic characterization of baobab populations from Kenya is assessed by microsatellites  markers. Microsatellites are molecular markers suitable for various applications such as parentage analysis, conservation genetics, phylogeography, population genetics, etc. (as cited in ). Even tdigitata  were appdigitata , the autTanzania ; howeverIn Kenya, baobab can be found in the eastern part of the country in two belts; the inland belt (from the Tanzanian border east of Mount Kilimanjaro towards the northeast around Kitui Town) and coastal belt . In Keny2.2.1.−1, a mean annual temperature of 23°C, and the most common soils are Luvisols and Ferralsols [The present study was carried out in the Makueni and Taita Taveta Counties located in inland southeastern Kenya, and in Kwale and Kilifi Counties located on the Kenyan coast. The inland locations have a rather hot, semi-arid climate with an average rainfall from 500 to 700 mm yrrralsols . Trees frralsols . Trees s2.2.n = 146) , and in the Chyulu Hills National Park (n = 43), a population which provided baobab trees at the highest elevation in the sampling area.In total, 189 individual trees were sampled from seven populations  during July–August 2015, 2 bark sample as an alternative source of DNA if no leaves were present. Samples were inserted into permeable paper bags, labelled, stored in sealed plastic boxes with silica gel for drying and transported to Prague, Czech Republic, for genetic analysis at the molecular laboratory of Czech University of Life Sciences Prague (CULS).For each of the sampled trees, one to two healthy leaves were collected or about 5 cm2.3.−1 NaCl, 0.1 mol l−1 Tris–HCl pH 8.0, 20 mmol l−1 ethylenediaminetetraacetic acid (EDTA), 1% v/v polyvinylpyrrolidone, 0.2% v/v 2-mercaptoethanol) for 30 min at 60°C. The suspension was incubated with an equal volume of chloroform-isoamylalcohol (24 : 1), and DNA was precipitated from the aqueous phase by 0.7 volumes of isopropanol. After washing with 70% ethanol, DNA was dissolved in water and treated by RNase A (250 µg ml−1). DNA concentration and purity were measured on a NanoDrop™ spectrophotometer. Samples were diluted to final concentrations of 25 ng µl−1 for further polymerase chain reaction (PCR).For DNA extraction, the cetrimonium bromide (CTAB) method was used . Plant mA. digitata by Larsen et al. [−1), 4.4 µl of primer mix (each primer 10 mM), 0.9 µl of 10× TaqBuffer (Thermo Fisher Scientific), 0.9 µl of 10 mM dNTP Mix (Thermo Fisher Scientific), 0.9 µl of 2.5 mM MgCl2 (Thermo Fisher Scientific), 0.7 µl 5 U of Taq DNA polymerase (Thermo Fisher Scientific) and 3.2 µl of nuclease-free water. PCR amplifications were conducted separately for primer mix 1 (PM1) and primer mix 2 (PM2) in a T100 Thermal Cycler  by performing the following steps: 2 min of denaturation at 95°C followed by 36 cycles at 95°C for 30 s, 58°C for 1 min and elongation at 72°C for 2 min 30 s and a final extension for 7 min at 72°C. PCR products of PM1 and PM2 were mixed in a ratio of 1 : 2 to create a multiplex for fragment analysis by capillary electrophoresis. The PCR products thus prepared were mixed with GeneTrace 500 LIZ size standard  and analysed on a Genetic Analyser 3500 . Microsatellite alleles were scored using GeneMarker v. 2.4.0 .Nine microsatellite primer pairs  originally developed for n et al.  were app2.4.2.4.1.A. digitata, we used software SPAGeDi v. 1.5 that can handle polyploid species [Fis) were computed for all populations. The same program was used to estimate the pairwise population differentiation ρ statistic [et al. [ρ statistic is the most relevant alternative to FST to assess the population differentiation for polyploid species. Microsatellite data from tetraploid A. digitata were converted to a binary matrix to calculate Nei's genetic diversity (H) and analyses of molecular variance (AMOVA). H was computed from binary data in GenAlEx 6.5 [rlequin 3.5 [eDi and a conversion of allele data to a binary presence/absence matrix, were applied to obtain sufficient results.Considering the tetraploid nature of  species . The num species ), gene d species ), observtatistic  and geog [et al. , the ρ sAlEx 6.5 , and thequin 3.5 . Two dif2.4.2.olysat package [eDi and Structure 2.3.4 [olysat. Bayesian model-based clustering of microsatellite data was computed in Structure 2.3.4.Owing to allele copy ambiguity in tetraploid datasets, the determination of precise genotypes and allele frequencies was impossible. Here, the coding of microsatellite data was employed using the P package  in R 3.1 package . Using tre 2.3.4  were preet al. [K frequently identifies K = 2 even if more subpopulations are present; therefore, it may cause an over- or underestimation of population genetic structure. To prevent this, a division of samples was done to reveal if there is more genetic structure within each of the two regions. In Structure, the admixture model and correlated allele frequency model were applied [tructure was run for each dataset with a burn-in period of 100 000 followed by 100 000 Markov chain Monte Carlo steps. For each dataset, the number of clusters (K) was adjusted as follows: K = 1–10 for all samples, K = 1–7 for inland samples and K = 1–6 for coastal samples. Each K-value was replicated 10 times. Owing to the unbalanced sampling of populations, the ALPHA (α) parameters were set as follows: for all individuals α = 0.1, for inland samples α = 0.14, and for coastal samples α = 0.17 [tructure were analysed in the Structure Harvester [K following the ΔK method of Evanno et al. [lumpp v. 1.1.2 [istruct v. 1.1 [To reveal the number of clusters, samples were divided into three datasets: one containing all samples, one with only inland samples and one with only coastal samples. Janes et al.  reported applied . Then, Sα = 0.17 . The outarvester  to asseso et al. . Clusterv. 1.1.2 , and grat v. 1.1 .3.3.1.Fis) ranged from –0.136 to 0.049  computed for the seven populations and compared with the geographical distances are presented in ρ) between coastal and inland populations was generally high (greater than 0.090), differentiation within each of the two regions was very low. The lowest genetic differentiation was revealed between Mtito Andei and Kibwezi (0.0) as well as Chyulu populations (0.004). These were also the locations with short geographical distances of only about 29–33 km each. The highest values of genetic differentiation were found between Voi and Diani as well as Voi and Malindi (range 0.330–0.331) .Genetic differentiation (0–0.331) . In geneAMOVA calculated for all seven populations revealed low variation among (9.4%) and high variation within populations (90.6%). Separating inland and coastal regions, data showed 22.1% variance among and 77.9% within groups. AMOVAs conducted separately for inland and coastal populations revealed low variation among populations .Table 33.2.K = 2 (a), based on the Evanno et al. [tructure Harvester [K = 4 and for coastal populations K = 3. However, we did not identify any clear structure within either of the two regions . Similar results to the Structure analysis were obtained from the PCoA  was low within both inland and coastal regions which indicates sufficient gene flow within both regions. Similarly, in Sudan, low genetic differentiation was found among populations in the Nuba Mountains [ρ values were observed among both regions in Kenya. This fact suggests rather limited gene flow between inland and coastal populations. Interestingly, patterns of genetic differentiation are not correlated to geographical distances, as the geographical distance between Voi  and Kilifi  was almost similar to those between the two inland populations Kibwezi and Voi . A similar observation was made in Malawi where the closest geographical populations (56 km) were clustered separately, whereas populations 204 km apart were clustered together [Genetic differentiation  was found within the seven surveyed populations and 9.4% of the variation was observed among populations based on AMOVA analysis. Results are in line with the findings of Wiehle et al. , who als4.2.Rousettus aegyptiacus was reported to pollinate baobab flowers at the coastal region in Kenya [R. aegyptiacus might not be responsible for the pollination of baobab in inland regions and therefore not supporting gene flow between coastal and inland baobab populations. However, the behaviour of bats is largely unknown, only a few studies have been carried out  while coastal populations are found close to sea level (less than 60 m.a.s.l.), with substantially different climate conditions. Therefore, climate and elevation may explain the current population structure. Moreover, baobabs have different phenologies in the two regions. Based on personal observations, inland trees bore fruit earlier than those at the coast. This is most likely caused by different flowering times, and therefore, the gene flow between both regions is very limited. The main baobab pollinators, fruit bats , may plain Kenya , howeverin Kenya , but R. cited in ,39) and et al. [et al. [The clear differences between inland and coastal clusters as shown in the present study were observed in a similar way in some other studies. In Benin, for example, coastal populations (in the Guinean climatic zone) were also clearly divided from inland populations . A studyet al.  also des [et al.  explaine [et al. . As the  [et al. ,47. Anot [et al. . Such jo [et al. .However, the reason for such genetic differentiation remains unrevealed. Most probably, different population histories associated with climate change or even human intervention could have caused the current genetic differentiation. Therefore, nowadays baobabs from both regions are not capable of gene exchange owing to different phenology and flowering time. The fact that those findings were also observed in other parts of Africa e.g. Benin, Mozambique, Tanzania, Kenya ,6 means 5.This study has revealed high genetic diversity in all studied baobab populations and strong differentiation between inland and coastal populations. The differentiation cannot be easily explained but may have been caused by different population histories supported by particular climatic conditions, which prevent genetic exchange between the two study regions. Thus, gene flow mostly occurs within populations in both regions, a fact which is also important for conservation and management issues. The results of this study contribute to the general knowledge of baobab trees in East Africa and may help to further conservation and domestication programmes. Selection of baobab elite trees for domestication should be done separately in the two study regions to maintain the genetic diversity of the species. We also recommend more intensive sampling and analysis of the genetic and morphological characterization of coastal and inland baobab populations across Africa to assess if such differentiation could also be found in other parts of the continent. This would be helpful in revealing new facts about phylogeography, genetics and morphology of this species.