FST = 0.0062). Populations from the Adriatic Sea were panmictic, while genetic differentiation was found among populations from different Mediterranean basins. Observed gene flow for European lobster suggest that populations in the north eastern Adriatic act as a source for surrounding areas, emphasizing the need to protect these populations by establishing interconnected MPAs that will be beneficial for both fisheries and conservation management.Highly selective fishing has the potential to permanently change the characteristics within a population and could drive the decline of genetic diversity. European lobster is an intensively fished crustacean species in the Adriatic Sea which reaches high market value. Since knowledge of population structure and dynamics is important for effective fisheries management, in this study, we used 14 neutral microsatellites loci and partial mitochondrial COI region sequencing to explore population connectivity and genetic structure by comparing samples from the Adriatic Sea and the adjacent basins of the Mediterranean Sea. The obtained results suggest that neutral genetic diversity has not been significantly affected by decrease in population size due to overfishing, habitat degradation and other anthropogenic activities. Global genetic differentiation across all populations was low ( Genetic connectivity among marine populations is an important driver for ecological evolutionary processes of species and reflects historical and contemporary demographic events, such as climate shifts, environmental features, oceanographic patterns or particular species behaviors . Larval Homarus gammarus) is a commercially important species for Croatian small-scale fisheries, the knowledge of its genetic diversity, stock structure and population dynamics in the Adriatic Sea is currently lacking.Genetic approaches based on gene flow and diversity estimations are highly recommended for effective conservation decisions, since genetic diversity has been one of the most important biodiversity conservation issues . On the The species is distributed in the north-eastern Atlantic Ocean from Morocco  to Arctic Norway, and in the Mediterranean Sea . The EurIn the last two decades, genetic studies have been carried out intensively, especially in northern European regions where stock enhancement programs were implemented to supplement fisheries production in heavily depleted areas . SeveralIn the present study, the population genetic variation of European lobster was investigated in the Adriatic Sea and the adjacent basins of the Mediterranean Sea using two classes of genetic markers, i.e., 14 neutral microsatellites and a sequence polymorphism of a mitochondrial DNA COI region. Based on sampling coverage, this study aimed to: (i) provide detailed insights into the genetic structure of European lobster in the Adriatic Sea and assess genetic connectivity between the Adriatic and Mediterranean basins; (ii) detect the possible impacts of intense fishing pressure on species genetic diversity and reconstruct its demographic history based on mtDNA and nuclear markers, and (iii) consider potential management implications of present findings for European lobster in the Adriatic Sea.spectrophotometer .A total of 331 individuals of European lobster were collected from the central and eastern Mediterranean . The AdrDNA samples were genotyped with 15 microsatellite markers designed for European lobster, following the protocol outlined in FIS), linkage disequilibrium (LD), departures from Hardy-Weinberg equilibrium (HWE), observed and expected heterozygosity  were assessed using GENEPOP 4.0  for the global FST values were estimated.The level of gene flow among sampling locations was estimated with pair-wise and global entities  was calcentities . To asse3 iterations and 504 MCMC (Markov chain Monte Carlo) steps. K-value ranged from 1 to the maximal number of sampled groups, including 20 replicates for each value. Using Structure Harvester 0.6.93 (P(D) and delta K-values and visualized using CLUMPP  was applied to measure local densities of distances and function image for plotting in the package MASS (Isolation by distance (IBD) analysis was tested with the package age MASS .Ne) over a relatively short period . With 20,000 replications, two-phase model (TPM) with 90% single-step mutations and 10% variance among multiple steps was tested for populations with a sample size over 20 individuals. The probability of significant heterozygote excess was tested using a one-tailed Wilcoxon signed-rank test, as recommend by M ratio test was conducted in MPVal and the critical value of Mc was estimated by CriticalM software for each population (k) and overall range in allele size (r) at a given locus. In recently reduced populations, M-ratios is expected to be smaller than in populations under mutation-drift equilibrium and, as such, may be persevered for hundreds of generations  = 3.1, and the proportion of stepwise mutations (ps) = 78% (Neμ) that correspond to a pre-bottleneck effective population size of 250, 500, and 2000, respectively.BOTTLENECK 1.2.02  was usedpulation . The M rerations  in contr of 0.68  and to ts) = 78% . Three dc) and historical gene flow that covers much longer period of time  were estimated among populations by BayesAss1.3  and mutation-scaled effective population size . The Brownian motion mutation model and FST calculations as starting parameter values were used with constant mutation rates for all loci. Uniform prior distribution was applied to estimate Θ  and M . A long chain was set to visit 1,000,000 parameter values with a burn-in of 50,000 iterations for each locus and to record 20,000 genealogies with a sampling increment of 50. To improve the MCMC searches, static heating scheme at four temperatures  was applied.Contemporary gene flow based on few generations (mesAss1.3  and MigresAss1.3 . For BayER v.171  and the ER v.171 . MigrateER v.171  and applNe estimation of an age structured lobster population with overlapping generations. Following NeEstimator V2  program c oxidase subunit 1 (COI) gene was amplified for the reduced dataset  was estimated as t = τ/2u, where τ is the mutational time scale. The mutation rate per locus per generation (2u) was calculated by multiplying the length of sequence × mutation rate × generation time. In the absence of the calibrated mutation rate of the mtDNA of European lobster, the mutation rates from 1.66 to 2.33% per million years of Sesarma COI gene were tested . After the removal of locus HGA8, no consistent support for linkage disequilibrium among the pair of loci and no significant deviation from Hardy-Weinberg equilibrium  and observed (Ho) heterozygosity showed moderate variation among populations and ontogenetic stage (adults vs. juveniles), ranging from 0.63 to 0.77  were detected between female and male individuals sampled in the Adriatic Sea (data not shown). The proportion of heterozygous loci was uncorrelated with carapace length  for both female and male individuals , internal relatedness (IR) and homozygosity by locus (HL), no statistically significant differences (Mann–Whitney FST and Dest was 0.0062 (p < 0.001) and 0.023, respectively, supporting a relatively limited level of differentiation across all populations. Following Bonferroni correction, both estimators gave congruent results in terms of pairwise comparisons, where 17 of 79 interactions were statistically significant  sampled from the outermost point in the middle region showed significant interaction with the Lošinj Island population (AD_LO) from the north region. According to the mean L(K) and delta K statistics, three discrete genetic clusters of European lobster were inferred through Bayesian clustering analysis (K = 1 (data not shown). Presence of three clusters was also supported by the optimal number of clusters identified using DAPC and successive K-means clustering analyses. When each location was treated as an a priori cluster, the DAPC plot clustered groups similarly to the structure pattern noted in STRUCTURE . Scatterplot of local densities of distances showed a patched form of genetic differentiation among populations due to the multiple densities of genetic relatedness with spatial discontinuities .Global genetic differentiation estimated with nificant . On averanalysis . All AdrTRUCTURE  where thinuities . FurtherM values, two populations from the Adriatic Sea (AD_PU and AD_VI) showed evidence of a recent size reduction, but exclusively for ancestral theta (θ) values of 0.5 (No significant heterozygosity excess was observed under the two-phase model (TPM) parameters. In addition, the M ratio test showed no signal of a recent reduction in effective size, considering that the observed mean M-ratio of 0.77 ± 0.02 for the whole dataset was higher than the 0.68, i.e., the generally accepted threshold criterion in conservation genetics . While ts of 0.5 .Estimates of contemporary gene flow with BayesAss showed that populations in the north Adriatic (AD_UM and AD_LO) were the predominant source of exogenous allelic variants, with estimated emigration rates ranging from 0.06 for the most distant Corsica (LG_CO) population from the Ligurian Sea to 0.26 for the neighboring Lošinj (AD_LO) population from the north Adriatic . In addiHistorical gene flow values using Migrate-n ranged from 0.83 to 11.3 with slightly more complex interactions between and within populations than contemporary gene flow estimates . Again, Ne, of European lobster ranged from 74 (AD_HV) to 43,751 (AD_UM), but for all estimates the upper confidence limit reached infinity, indicating insufficient sample size to capture the genetic drift signal  in the mid Adriatic and for overall estimates, i.e., pooled Adriatic samples (2094) and the whole dataset (1560). The likelihood method implemented in AgeStructure (Ne of 1651 (95% CI: 656–2051) for the pooled Adriatic populations; this value was slightly lower than the value estimated by the LD method where the 95% confidence intervals (CI) partially overlapped  to 2087 (AD_UM)  .Fs test values for overall samples were negative but not significant, where mismatch distribution analysis and SSD test supported the hypothesis of a sudden population expansion  were pooled into a single population (AD_IS), the Venice location was excluded, and the location near Bari (AD_BA) was introduced in dataset but with a limited number of individuals . A 574-bxpansion . The nonH. gammarus, a decapod crustacean species of ecological and economic importance, in the waters of the Adriatic Sea.Knowledge of species distribution, population structure and size in relation to habitat suitability across local and broad spatial scales are key parameters for sustainable and ecosystem-based fisheries management. This is especially important for the semi-enclosed Mediterranean Sea, where intense fisheries effort has been recognized as one of the main stressors on the marine ecosystem . Namely,FST = 0.0062) that overlapped with the level previously documented using the same set of microsatellite loci  as the cut off value for selecting demographically stable natural populations  necessary for the maintenance of sufficient genetic variance for adaptive response in quantitative traits  across investigated populations was consistent with data for other marine crustaceans in the Mediterranean  but loweAdriatic . In thisKnowledge about stock structure and population connectivity is important for effective fisheries management. For the first time, this study provides detailed genetic structure of the European lobster in the Adriatic Sea and information on population connectivity between the Adriatic and Mediterranean basins. The European lobster shows signs of overexploitation in the Croatian fishery . DespiteWhile sign of neutral genetic diversity loss was not observed for European lobster populations in the present study, fishery and other impacts may have caused changes in the frequency of selectively important traits that cannot be easily measured with present genetic markers. Additionally, an important limitation of assignment methods used here is their power to detect migrants in cases of low levels of population differentiation, although it can be counterbalanced by larger sample sizes and additional gene loci, resulting in suitable power to detect migrants . In mostRecently developed SNP markers using RAD sequencing have proven to be powerful in population genetic structure detection . Still, MT983889 – MT983894).The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: NCBI (GenBank acc. no. Ethical review and approval was not required for the animal study because lobster tissue samples were obtained exclusively from commercial fisheries.TŠ-B, SM-S, and MP conceived the study. MP, AT, FG, ED, and IC conducted the sampling. MP, IŽ, and TŠ-B conducted the molecular and data analysis. TŠ-B and MP wrote and revised the manuscript. SM-S obtained funding for the work. All authors have reviewed and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Castanea crenata Sieb. et Zucc.), the only fruit tree species domesticated in Japan, has been cultivated alongside natural stands since prehistorical times. Understanding the genetic diversity of this species and the relationships between cultivated and wild chestnut is important for clarifying its breeding history and determining conservation strategies. We assessed 3 chestnut cultivar populations and 29 wild chestnut populations (618 accessions). Genetic distance analysis revealed that wild populations in the Kyushu region are genetically distant from other populations, whereas other wild and cultivar populations are comparatively similar. Assignment tests suggested that cultivars were relatively similar to populations from central to western Honshu. Bayesian structure analyses showed that wild individuals were roughly classified according to geographical distribution along the Japanese archipelago, except that some wild individuals carried the genetic cluster prevalent in cultivars. Parentage analyses between cultivars and wild individuals identified 26 wild individuals presumed to have a parent–offspring relationship with a cultivar. These results suggested that the genetic structure of some wild individuals in natural stands was influenced by gene flow from cultivars. To conserve wild individuals carrying true “wild” genetic clusters, these individuals should be collected and preserved by ex situ conservation programs.Japanese chestnut ( In contrast, wild individuals distributed in various areas have become adapted to different ecological situations, with the result that wild collections derived from divergent areas have greater genetic diversity than do cultivars in some species8. Thus, wild individuals are interesting for plant breeders as a potential source of genes that have been lost during domestication. The domestication process has been studied in many crops, and several key genes selected during domestication have been identified10. Conversely, gene flow from cultivars to wild individuals has influenced the genetic diversity of wild populations of several crops15. Thus, it is quite important to co-analyze cultivated and wild populations to clarify the genetic history of both population types.In plant species, there are large phenotypic differences between cultivated and wild forms. Cultivated plants have been selected by humans for food and other useful materials. Cultivated plants generally have good morphotypes for cultivating and harvesting16. When domestication of Japanese chestnut (Castanea crenata Sieb. et Zucc.) began is a difficult but interesting question. Evidence for pre-domestication  of chestnut was found at the location of the Sannai-Maruyama ruins (3500–2000 BCE)18. The high frequency of chestnut pollen, wood, and nut remains at this site suggested that people preserved chestnut trees around the village. Interestingly, nut size increased during the early to late Jomon period, and the nut size of several remains from the late Jomon period was as large as those of modern cultivars20, suggesting that the effort to improve genetic performance of Japanese chestnut started prehistorically. The nut size is quite different between cultivars and wild individuals: today, the individual nuts of some local cultivars are more than 30 g, but those of wild individuals are generally less than 5 g . The oldest known nut remains were found in the Omiya-no-moriura ruins , in which carbonized and peeled nuts were discoveredDryocosmus kuriphilus Yasumatsu, was accidentally introduced from China into Japan around 194024 and has influenced the distribution of both cultivated and wild chestnut. During the 1960s and 1970s, producers cut down local cultivars or naturalized stands and introduced cultivars resistant to chestnut gall wasp. The area of chestnut orchards dramatically increased during that time and was maximized at about 45,000 ha in the late 1970s. On the other hand, wild populations were devastated by chestnut gall wasp until the establishment of Torymus sinensis Kamijo, a natural enemy of Dryocosmus kuriphilus, during the 1980s. For chestnuts in a natural forest setting, insect pollinators, including bumblebees and flies, disperse pollen across long distances25. Even in orchard settings, considerable amounts of pollen are carried in from wild chestnut trees by insect pollinators26. Since the 1970s, the number of actively managed chestnut orchards in mountainous areas has gradually decreased due to the inconvenience of country life, so it is possible that seeds from cultivars are carried by animals and may escape from abandoned orchards. Thus, it is important to clarify how much gene flow has occurred from cultivars to wild populations.The chestnut gall wasp, Castanea sativa Mill.), American chestnut (Castanea dentata [Marsh.] Borkh), and Chinese chestnut (Castanea mollissima Bl.)32. In any chestnut species, there are exceptional populations that are genetically different from neighboring populations, suggesting that human-mediated seed dispersal has influenced wild natural stands32. So far, however, population genetic studies of Japanese chestnut have been limited to populations from the Tohoku area33 of northeast Japan and classifications of cultivars34, and to our knowledge there are no reports describing genetic characterization of wild chestnut populations throughout Japan.Population genetic studies of wild individuals of chestnut have been done using various chestnut species, including European chestnut  and Pacific (Pacific lineage) sides of Japan38. The nut remains of these species were also discovered from several excavations during the Jomon period, but with the exception of certain Fagus species, nuts of these species contain considerable amounts of tannins39, which need to be removed before eating. Consequently, the deciduous species in the Fagaceae in Japan other than chestnut have not been domesticated for use as food. Therefore, it is interesting to compare the genetic structures of chestnut and these non-domesticated species.Chestnut is the only domesticated nut species in family Fagaceae. Several of the deciduous species in family Fagaceae are distributed throughout the Japanese archipelago. The genetic population structures of The objectives of this study were to examine the genetic structure of wild chestnut distributed across the main islands of Japan, to examine the genetic relationships between cultivated and wild populations, and to clarify the breeding history of Japanese chestnut cultivars. Because chestnut orchards are found throughout Japan, gene flow from cultivars to wild individuals should be clarified to support future conservation and breeding strategies.Ho = 0.687 and He = 0.749 for mean values of 30 nSSR markers). The null allele frequencies ranged from 0.013 (PRD84) to 0.097  of the 32 populations ranged from 4.75 to 6.33  was similar to that of the wild populations (5.55). Observed and expected heterozygosity of the 32 populations was Ho = 0.605–0.752 and He = 0.596–0.726, respectively  were similar to those of wild populations (Ho = 0.685 and He = 0.681). The inbreeding coefficient (Fis) ranged from − 0.034 to 0.077. Cultivar populations originated in regions other than KAN or TAN  and six wild populations  showed significant Fis values  by using 30 nuclear simple sequence repeat (nSSR) markers Table ; Fig. 1.Chloroplast haplotype frequencies of the 618 individuals were determined using 4 chloroplast SSR markers (cpSSRs). Markers Cmcs1 and Cmcs3 each showed a single fragment size in all individuals, whereas Cmcs2 and Cmcs5 each showed two fragment sizes. Only two chloroplast haplotypes . KAN (a cultivar population) was also close to TOK , likely because both originated in the same region  for TNN, TOK, NOS, and NAK under the two-phase model (TPM) and for NOS under the stepwise mutation model (SMM) (Supplementary Table Pairwise Jost’s vs OR 0.05). KAN (K) in STRUCTURE, we calculated ∆K values | and ∆K were lower at K = 4. The values of |L″(K)| and ∆K at K = 5 were higher than those at K = 4. Because the 3 wild populations in Kyushu were genetically distant from the other 29 populations, we also estimated ∆K values using only the 29 populations from outside Kyushu. The ∆K values for this subset were clearly higher at K = 2 and K = 4  than at other K values, both with and without the LOCPRIOR model. In addition, we applied hierarchal analyses of molecular variance (AMOVA) to estimate the variance among the clusters identified in STRUCTURE (Supplementary Table K = 2) across all 32 populations showed that 23.4% of the total variance was among clusters, 6.1% was among populations within clusters, and 70.5% was within populations. Effects both among clusters and among populations within clusters were significant (P < 0.001). The percentage of variance among clusters based on five clusters (K = 5) in all 32 populations and that based on four clusters (K = 4) in the set of 29 populations excluding populations from Kyushu were small  but significant at P < 0.001.To estimate the optimal number of genetic clusters  the cultivar populations and the wild populations on central and western Honshu island (“orange”), (2) wild populations on northeast Honshu island (“yellow”), and (3) wild populations in the Kyushu region (“blue”). When K = 5 with and without LOCPRIOR, we further identified a “red” genetic cluster corresponding to the cultivar populations and a “green” one corresponding to wild populations on western Honshu island. Hereafter, the “red”, “yellow”, “orange”, “green”, and “blue” genetic clusters at K = 5 are referred to as the “cultivar”, “northeast Honshu”, “central Honshu”, “western Honshu”, and “Kyushu” clusters, respectively. A neighbor-joining tree was constructed based on the net nucleotide distances between pairs of clusters  when K = 5  mainly showed the “northeast Honshu” cluster, whereas those from the western end of Honshu , which was not well represented in the analysis of 32 populations, mainly showed the “western Honshu” cluster. The FTBC collection did not include individuals originated in Kyushu, but a noticeable contribution of the “Kyushu” cluster was observed in FTBC individuals derived from Tottori, Shimane, and Yamaguchi, which are geographically close to Kyushu.To validate the genetic structures of wild chestnut populations in Japan, 95 wild chestnut individuals collected by the Forest Tree Breeding Center (FTBC) were combined with the 32 populations in a Bayesian structure analysis without the LOCPRIOR model .To clarify the correlation between genetic differentiation and geographical distance in wild populations, the 26 wild populations on Honshu were used for isolation-by-distance analysis. A significant correlation between genetic distance and geographic distance was detected by the Mantel test when all possible pairs of the 26 wild populations were included  and MIY is located close to a Satoyama landscape (secondary woodlands and grasslands adjacent to human settlement)42, where human activities are presumed to have had an impact on the distribution of trees. A similar result was obtained from chloroplast haplotype analysis, as MIY and KAG carried not only HAP2 (presumed to have originated in Kyushu) but also HAP1 . As the altitude of KYU is high (1037–1074 m asl), it might have had less chance to receive chestnut seed or pollen from other regions and cultivated populations. The “Kyushu” genetic cluster was also detected at low levels in some wild chestnut individuals collected by FTBC in Yamaguchi, Shimane, Hiroshima, and Tottori Prefectures, which are located on the western end of Honshu close to Kyushu island  genetic cluster with some wild chestnut populations, especially in the Kanto region , suggesting that these populations were affected by non-natural  transportation of genetic clusters from other regions. Furthermore, in Ibaraki Prefecture (the location of TSU), chestnut production and the presence of orchards dramatically increased from the 1940s to the 1960s, as wild individuals were replaced by cultivars21. Trees in these orchards might have hybridized with wild individuals in TSU. The direct parent–offspring relationships between cultivars and wild individuals identified in several regions also suggest gene flow from cultivars to wild populations in these regions  imported from western countries into native species 15. In grape, a wild population in Georgia had a high proportion of hermaphrodite vines, a character specific to cultivar genotypes, indicating gene flow from cultivated to wild types50.Gene flow from cultivars to wild populations has been identified in some fruit tree species. In the Japanese archipelago, pear shows extensive introgression of prehistorically naturalized 51. Although previous reports clarified that nut size increased during the early to late Jomon (4000–1000 BCE)18, Motoki suggested that the nuts discovered mainly in ruins in northeast Japan were not directly influenced by native cultivars that originated in the Tanba region, which is geographically far from northeast Japan23. In Bayesian structure analysis with K = 3, cultivars were closer to wild populations in central to western Honshu, the latter including the Tanba region, than to those in northeast Honshu, which includes Sannai-Maruyama ruin (Aomori Prefecture), Aota ruin, and Yachi ruin (Niigata Prefecture), where large nuts were excavated. Thus, cultivars from the Tanba region would not have been selected directly from the nuts from these ruins. On the other hand, the results of Bayesian analysis and an assignment test suggested that the candidate origin of the cultivars was central to western Honshu, though the Tanba region (western Honshu)is more likely, based on the literature22. In any case, it is quite difficult to clarify the detailed origin of cultivars by comparisons to wild populations that were influenced by gene flow from cultivars, because the direction of gene flow is opposite to that typically seen during breeding and domestication processes .Genetic studies of current chestnut populations in combination with information from preserved nut remnants can reveal clues as to how and where chestnut might have been domesticated. It is obvious that one component of the domestication syndrome in Japanese chestnut is large nut (seed) size, as in other species45. Among fruit tree species, apple is a good example of a species whose domestication appears to have taken more than a few 1000 years. The cultivated species M. domestica originated in the Tian Shan mountains from M. sieversii. During the dispersal of apple from Asia to Europe along the Silk Route, hybridization with and introgression from Caucasian and European Malus species contributed to form present-day apple cultivars52. Slow domestication of a species suggests that there were periods of pre-domestication cultivation53, or “hansaibai”, which is suggested by Kitagawa and Yasuda17 to have occurred in Japanese chestnut at the location of the Sannai-Maruyama ruin. It is possible that the effort to improve genotypes via pre-domestication cultivation and domestication of chestnut was initiated more than once, and in several regions, because large nut remains were discovered in several ruins from different eras.In cereals, it took several 1000 years to consistently obtain the non-shattering spikelet phenotype, a defining characteristic of domesticated cropsIn conclusion, this study of both cultivars and wild populations of chestnut indicates the presence of gene flow from cultivars to wild forms and reveals a possible history of cultivar breeding. The genetic relationships between cultivars and wild individuals clarified in this study will be useful for both conservation and breeding. From the perspective of chestnut breeding, wild individuals distributed in Kyushu could be valuable genetic resources because they are genetically quite distant from current cultivars. Climate change is bringing new problems of black spot nut and nut rot to chestnut, and the materials from Kyushu might be helpful for chestnut production in hot areas. For the purposes of conservation, it is important to preserve wild individuals from Kyushu that are divergent from cultivars because gene flow from cultivars to natural stands was observed in this study. To achieve this goal, wild individuals carrying true “wild” genetic clusters should be collected and preserved by ex situ conservation programs such as the gene banks of public institutions.Castanea crenata because damage from the white-striped longicorn beetle (Batocera lineolata) shortens the life of C. crenata in Japan.Thirty-two populations (618 accessions), including 3 cultivated populations and 29 wild populations, were used in this study  according to the manufacturer’s instructions.56 , 20 pmol of each forward primer labeled with a fluorescent dye (5-FAM or 5-HEX) and unlabeled reverse primer, and 2.5 ng of genomic DNA. Amplification was performed in 35 cycles of 94 °C for 1 min, 55 °C for 1 min, and 72 °C for 2 min. PCR products were separated and detected with a 3130xl Genetic Analyzer . The size of each amplified band was determined by comparison with a set of internal-standard DNA fragments  in GeneMapper software v. 5.0 (Life Technologies).The 618 accessions and the wild chestnut individuals collected by FTBC were genotyped for 30 nSSRsHo) and expected heterozygosity (He) were calculated in GenAlEx v. 6.5 software58, and inbreeding coefficients (Fis) and allelic richness  were calculated using FSTAT Version 2.9.359. Significant deviations from Hardy–Weinberg equilibrium, as indicated by deviations of Fis from zero, were tested by randomization using FSTAT. The frequencies of null alleles were estimated using CERVUS version 3.0 software60. Pairwise genetic distances based on a Jost’s D matrix among the 32 populations were calculated with GenoDive version 3.0 software61. To detect signatures of bottlenecks in the populations, we used the program INEST 2.262 to assess excess heterozygosity in each population. We ran the model using 100,000 coalescent simulations, and tested significance using the Wilcoxon signed-rank test, calculated based on 1,000,000 permutations under both the stepwise mutation model (SMM) and the two-phase model (TPM).The observed heterozygosity , both with and without the LOCPRIOR model. The LOCPRIOR model allows for sample group information to be used to aid in the clustering process64. This model has been found to detect genetic structure at lower levels of divergence than the regular mode. The analysis was run 10 times for each value of K  from 2 to 8 for 1,000,000 iterations after a burn-in period of 1,000,000 iterations. Evanno et al.’s criterion of ∆K was used to estimate the appropriate K value65. Furthermore, genetic variance among clusters was also used to perform AMOVA67 in GenoDive version 3.0 software61. Significance levels were determined using 10,000 permutations. Because the populations from Kyushu were clearly genetically distant from the others, the values of ∆K and variance among clusters were also calculated using the 29 populations from outside of Kyushu. The CLUMPAK online tool68 was applied to calculate the ∆K values and to graphically display the results produced by STRUCTURE. A neighbor-joining tree based on net nucleotide distances was generated using POPULATIONS v. 1.2.3069. The 618 accessions were used for the main analysis. For validation purposes, the 95 wild chestnut individuals collected by FTBC were co-analyzed with the 618 accessions. The results of the validation are shown in Supplementary Figure Bayesian statistical inference of the population structure was performed by use of STRUCTURE 2.3.4 software60 software, which uses a maximum-likelihood-based approach to infer parentage. The genotype data of the 30 nSSRs for 92 major cultivars . The average probability of non‐exclusion of an incorrect father using this approach was 1.5 × 10−7.To identify possible parent cultivars of wild individuals, putative parent–offspring relationships were calculated with CERVUS72. Assignment based on Bayesian criteria for computation for the 92 cultivars was carried out in GeneClass 2.073 by using the wild populations as reference sets. We applied an exclusion test using the Monte Carlo resampling method74. The genotypes were generated by Markov Chain Monte Carlo simulations of 10,000 individuals for each of the wild populations. When the probability that the wild populations in a region were sources of a cultivar was less than a given threshold (α = 0.01), the populations in that region were excluded from candidate sources for the tested cultivar.Assignment tests have been used to infer the origin of cultivars in several crops75 were used to estimate the correlation between (FST/(1 − FST)) and the geographic distances (km) between sampled populations based on 10,000 randomizations using GenAlEx v. 6.5 software. Because wild populations TSU and TOK carried substantial portions of the “cultivar” genetic cluster, correlation of genetic distance and FST/(1 − FST) was also calculated for pairs including either TSU or TOK.For the 26 wild populations on Honshu island, we tested isolation by distance. Mantel testsSupplementary Figures.Supplementary Tables.


Admixture occurs when previously isolated populations come together and exchange genetic material. We hypothesize that admixture can enable rapid adaptive evolution in human populations by introducing novel genetic variants (haplotypes) at intermediate frequencies, and we test this hypothesis through the analysis of whole genome sequences sampled from admixed Latin American populations in Colombia, Mexico, Peru, and Puerto Rico.HLA-A, HLA-DRB51, and HLA-DRB5, show independent evidence of positive selection prior to admixture, based on extended haplotype homozygosity in African populations. A number of traits related to inflammation, blood metabolites, and both the innate and adaptive immune system show evidence of admixture-enabled polygenic selection in Latin American populations.Our screen for admixture-enabled selection relies on the identification of loci that contain more or less ancestry from a given source population than would be expected given the genome-wide ancestry frequencies. We employ a combined evidence approach to evaluate levels of ancestry enrichment at single loci across multiple populations and multiple loci that function together to encode polygenic traits. We find cross-population signals of African ancestry enrichment at the major histocompatibility locus on chromosome 6, consistent with admixture-enabled selection for enhanced adaptive immune response. Several of the human leukocyte antigen genes at this locus, such as The results reported here, considered together with the ubiquity of admixture in human evolution, suggest that admixture serves as a fundamental mechanism that drives rapid adaptive evolution in human populations. Admixture is increasingly recognized as a ubiquitous feature of human evolution . Recent The conquest and colonization of the Americas represents a major upheaval in the global migration of our species and is one of the most abrupt and massive admixture events known to have occurred in human evolution , 4. The A number of previous studies have considered the possibility of admixture-enabled selection in the Americas, yielding conflicting results. On the one hand, independent studies have turned up evidence for admixture-enabled selection at the major histocompatibility complex (MHC) locus in Puerto Rico , ColombiWe attempted to resolve this conundrum by performing integrated analyses that combine information from (1) single loci across multiple populations and (2) multiple loci that encode polygenic traits. We also used admixture simulation, along with additional lines of evidence from haplotype-based selection scans, to increase the stringency of, and confidence in, our screen for admixture-enabled selection. This combined evidence approach has proven to be effective for the discovery of admixture-enabled selection among diverse African populations , 14. We n = 94), Mexico (n = 64), Peru (n = 85), and Puerto Rico (n = 104)  populations characterized as part of the 1000 Genomes Project: Colombia (zanc) is expressed as the number of standard deviations above or below the genome-wide ancestry fraction. Previous studies have used this general approach to look for evidence of admixture-enabled selection at individual genes within specific populations, yielding mixed results [For each of the four LA populations, local ancestry patterns were used to search for specific loci that show contributions from one of the three ancestral source populations which are greater than can be expected based on the genome-wide ancestry proportions for the entire population  were computed for each of the three continental ancestry components within each of the four admixed LA populations analyzed here. We then integrated gene-specific zanc values across the four LA populations using a Fisher combined score (FCS). The strongest signals of single gene ancestry enrichment were seen for African ancestry at the major histocompatibility complex (MHC) locus on the short arm of chromosome 6  and generations since admixture (g = 10), were chosen to simulate a recent bottleneck that could be expected to yield a high variance in local ancestry fractions by chance alone [P < 5 × 10−5), whereas the observed patterns of European and Native American ancestry enrichment are consistent with the range of expected levels generated by the random admixture simulation . The first genome-wide simulation was parameterized by populations’ ancestry proportions; the second simulation focused on chromosome 6 and included additional known demographic features of LA populations. The demographic features taken from the literature on these LA populations, starting effective population size  and MHC class II (HLA-DRB5 and HLA-DRB1) antigen presenting pathways of the adaptive immune system , for genes that function together to encode polygenic phenotypes, via the polygenic ancestry enrichment score (PAE)  Fig. a. ObservAE) Fig. b. InflamSeveral interconnected pathways of the innate immune system—the RIG-I-like receptor signaling pathway, the Toll-like receptor signaling pathway, and the cytosolic DNA-sensing pathway—all show evidence of Native American ancestry enrichment Fig. . All thrHuman adaptive evolution is often considered to be a slow process, which is limited by relatively low effective population sizes and long generation times –26. The Our results suggest that admixture can enable extremely rapid adaptive evolution in human populations. In the case of the LA populations studied here, we found evidence of adaptive evolution within the last 500 years (or ~ 20 generations) since the conquest and colonization of the Americas began , 4. We pThe haplotypes that show evidence of ancestry enrichment in our study evolved separately for tens-of-thousands of years in the ancestral source populations—African, European, and Native American—that mixed to form modern, cosmopolitan LA populations. Many of these haplotypes are likely to contain variants, or combinations of variants, that provided a selective advantage in their ancestral environments . These as = 0.05 for African haplotypes at the MHC locus.Our initial analysis of individual LA populations turned up numerous instances of apparent ancestry enrichment genome-wide, including enrichment for all three ancestry components in each of the four populations studied here  , 38. Whor2 > 0.1, and ADMIXTURE was run with K = 4 corresponding to African, European, Asian, and Native American ancestry components. Local continental ancestry estimates for each individual from the four LA populations were inferred using a modified version of the program RFMix [https://github.com/jordanlab/tagore).Global continental ancestry estimates for each individual from the four LA populations were inferred using the program ADMIXTURE . The haram RFMix  as previam RFMix . The comzanc) values were calculated for all three continental ancestry components  across all four LA populations. Genomic locations of NCBI RefSeq gene models were taken from the UCSC Genome Brower (hg19 build) [fanc) were computed as the number of ancestry-specific haplotypes (hanc), divided by the total number of ancestry-assigned haplotypes for that gene (htot): fanc = hanc/htot. Ancestry enrichment analysis was limited to genes that had htot values within one standard deviation of the genome-wide average for any population. Distributions of gene-specific ancestry fractions (fanc) for each population were used to calculate population-specific genome-wide average (μanc) and standard deviation (σanc) ancestry fractions. Then, for any given gene in any given population, ancestry enrichment (zanc) was calculated as the number of standard deviations above (or below) the genome-wide ancestry average: zanc = (fanc − μanc)/σanc, with gene-specific ancestry enrichment P values computed using the z distribution. A Fisher’s combined score (FCS) was used to combine gene-specific ancestry enrichment P values across the four LA populations as: FCS was computed using the χ2 distribution with 8 (2k) degrees of freedom. Correction for multiple FCS tests was performed using the Benjamini-Hochberg false discovery rate (FDR), with a significance threshold of q < 0.05 [Single gene (locus) ancestry enrichment (9 build) , and genq < 0.05 .zanc as described in the previous section. Expected levels of zanc were combined across the four LA populations to yield expected Fisher’s combined scores (FCS) and their associated P values as described in the previous section. Two independent approaches to admixture simulation were used here. For the first approach, admixed populations were simulated as collections of genes  randomly drawn from the genome-wide ancestry distributions for each LA population. Sized matched admixed populations were simulated for each LA population and combined to generate expected (FCS) and their associated P values, and admixture simulation was also conducted across a range of population sizes  to evaluate the power of the combined evidence cross-population approach used to detect ancestry-enabled selection. This approach was applied across the entire genome for all four LA populations.Three-way admixed individuals were randomly simulated for each LA population—Colombia, Mexico, Peru, and Puerto Rico—and used to calculate expected levels of ancestry enrichment https://github.com/slowkoni/admixture-simulation. Each admixed LA population was simulated using a Wright-Fisher forward simulation over 10 generations with an effective population size of n = 100 individuals. These parameters represent lower bound estimates for generations since admixture and founding population sizes in the populations studied here [FCS) and their associated P values for chromosome 6.For the second approach, admixed populations were simulated using the “Admixture simulation tool,” which can be found at ied here , 23. Forzanc) across genes that function together to encode polygenic traits. Gene sets for polygenic traits were curated from a number of literature and database sources to represent a wide array of phenotypes  were compared against the mean (μPAE) and standard deviation (σPAE) of the expected PAE values to compute the statistical significance for each trait: zPAE = (PAEobs − μPAE)/σPAE, with P values computed using the z distribution. Correction for multiple tests was performed using the Benjamini-Hochberg false discovery rate (FDR), with a significance threshold of q < 0.05.Polygenic ancestry enrichment values (PAE) were computed by combining single locus ancestry enrichment values (Integrated haplotype scores (iHS)  were cals) values to determine the values of s that correspond to the observed African ancestry enrichment levels. This allowed us to compute a positive selection coefficient corresponding to the strength of African ancestry selection at the MHC locus for each population. Additional details of this model can be found in Additional file Admixture-enabled selection was modeled for the African enriched chromosome 6 MHC haplotype using a standard recursive population genetics model for positive selection . Three aThe review history is available as Additional file Barbara Cheifet was the primary editor on this article and managed its peer review and editorial process in collaboration with the rest of the editorial team.Additional file 1:Figures S1-S11, Tables S2-S3, and Supplementary Methods.Additional file 2: Table S1. Ancestry enrichment test statistic values.Additional file 3. Review history.


Oreochromis urolepis urolepis) is an endemic cichlid in Tanzania. In addition to its importance for biodiversity conservation, Rufiji tilapia is also attractive for farming due to its high growth rate, salinity tolerance, and the production of all‐male hybrids when crossed with Nile tilapia (Oreochromis niloticus). The aim of the current study was to assess the genetic diversity and population structure of both wild and farmed Rufiji tilapia populations in order to inform conservation and aquaculture practices. Double‐digest restriction‐site‐associated DNA (ddRAD) libraries were constructed from 195 animals originating from eight wild  and two farmed (Bwawani and Chemchem) populations. The identified single nucleotide polymorphisms  were used to investigate the genetic variation within and among the studied populations. Genetic distance estimates (Fst) were low among populations from neighboring locations, with the exception of Utete and Chemchem populations (Fst = 0.34). Isolation‐by‐distance (IBD) analysis among the wild populations did not detect any significant correlation signal  between the genetic distance and the sampling (Euclidean distance) locations. Population structure and putative ancestry were further investigated using both Bayesian (Structure) and multivariate approaches . Both analysis indicated the existence of three distinct genetic clusters. Two cross‐validation scenarios were conducted in order to test the efficiency of the SNP dataset for discriminating between farmed and wild animals or predicting the population of origin. Approximately 95% of the test dataset was correctly classified in the first scenario, while in the case of predicting for the population of origin 68% of the test dataset was correctly classified. Overall, our results provide novel insights regarding the population structure of Rufiji tilapia and a new database of informative SNP markers for both conservation management and aquaculture activities.Rufiji tilapia ( The objective of the current study was to assess the genetic variation among 10 Rufiji tilapia populations of both wild and farmed origin using ddRAD‐seq. We investigate for the existence of putative genetic clusters, test for the existence of isolation by distance, and assess the efficiency of predicting population of origin‐based only on the genomic profile using cross‐validation schemes. Nevertheless, the impact to the local fauna is in many cases poorly understood  comprise a diverse group of over 70 species mostly encountered in tropical and subtropical regions  have been introduced to non‐native habitats across the country often in an unregulated manner  is an endemic species in Tanzania, distributed mainly across the south‐eastern rivers, reservoirs, and oxbow lakes of Rufiji river basin  have been introduced in Rufiji tilapia habitats  and the introduced tilapia species raising concerns regarding the impact of introgression into the native populations  and farmed (two populations) origin using ddRAD‐seq. Single nucleotide polymorphisms (SNPs) were identified across 195 animals and were subsequently used to estimate standard genetic diversity metrics both within and among populations, investigate for the existence of putative genetic clusters, test for the existence of isolation by distance, and assess the efficiency of predicting population of origin‐based only on the genomic profile using cross‐validation schemes. The aforementioned will facilitate both the conservation management of wild Rufiji tilapia populations and future breeding plans for aquaculture purposes where a broad genetic diversity is required for forming a base population.22.1O. urolepis urolepis distribution in Tanzania. In total, 10 different geographic locations were selected namely Nyamisati, Bwawani, Utete, Chemchem, Mansi, Mindu, Wami, Ruaha, Kibasira, and Kilola  in Pangani, Tanzania.Fish used in this study were collected from both wild and farmed environments in Tanzania mainland Table . Samplina Figure . In part2.2Fin clips of about 0.05 g were collected and preserved in 95% ethanol and stored at −20°C. Genomic DNA was extracted using QIAsymphony DSP DNA Mini Kit (Qiagen) and eluted into 100 μl of AE (EDTA) buffer (Qiagen) according to the manufacturer's tissue protocol and procedures. Quantification of DNA samples was done using a Qubit fluorimeter . Samples were diluted with TE buffer to 20 ng/μL followed by gel electrophoresis (1% agarose gel) to assess DNA quality.2.3Two ddRAD libraries comprised of 96 and 99 individuals, respectively, were prepared according to Peterson et al. , with mi2.4Q < 20) and missing the expected restriction sites were discarded. The retained reads were aligned to the Nile tilapia reference genome assembly [GenBank accession number GCA_001858045.1 . In the case where a single ddRAD locus had multiple SNPs, only the first encountered SNP was used for downstream analysis (‐‐write‐single‐snp). SNPs with minor allele frequency (MAF) < 0.05 and maximum heterozygosity > 0.7 across the tested samples were discarded. Moreover, the genotypes obtained for each individual were interrogated for the number of reads supporting each allele. Genotypes supported by fewer than 20 reads or where the coverage of one of the alleles was more than three times higher than the other allele were substituted as missing. Finally, only SNPs found in at least 75% of the samples in each population were retained for downstream analysis.Reads of low quality (2.5Ho) and expected (He) heterozygosity, nucleotide diversity (π), average individual inbreeding coefficients (Fis), and the corresponding standard errors (SE) were estimated using the Stacks software v2.5  were estimated using the R package StAMPP . Thereafter, a discriminant analysis step was conducted using predetermined clusters from the PCs. The selection of the optimal number of clusters (K) was based on the elbow method  of 100,000 iterations with a burn‐in period of 10,000 was carried out for each K value. For each tested K value, three independent MCMC samplings were performed. Evidence for the optimal number of clusters was based on the obtained posterior probability values  was conducted using the R package adegenet v2.1.1 for visualization purposes and for gaining insights regarding the existence of genetic clusters. The existence of putative genetic clusters was further investigated using the discriminant analysis of principal components (DAPC)  on the remaining training data set. The same procedure was followed for the second cross‐validation scheme where the origin of 25% of animals from each geographic population was masked and used as a test set. The entire procedure for both cross‐validation schemes was repeated ten times in order to minimize potential bias due to the stochasticity of sample allocation in the training/test datasets.Cross‐validation schemes (fourfold) were performed using the R package adegenet v2.1.1 . Overall, 2,182 SNPs passed all quality control steps and were retained for downstream analysis. Finally, all 195 samples had fewer than 25% missing genotypes and were utilized for the subsequent analysis.More than 320 million paired‐end reads were obtained. The sequenced reads were aligned to the Nile tilapia reference genome  and nucleotide diversity (π) estimates were largely indistinguishable with values for both parameters ranging from 0.10 to 0.37  and Wami populations . On the other hand, the lowest values were observed in samples from Bwawani and Kibasira . Observed heterozygosity (Ho) estimates ranged between 0.10 and 0.21 with the lowest values observed in samples from Bwawani and Kibasira and highest in samples from Mindu population. Moreover, regarding the inbreeding coefficient (Fis), positive estimates were obtained for nine of the tested populations. After taking into account the corresponding standard error (SE) two populations showed suggestive evidence of putative loss of heterozygosity. The most striking difference was obtained in the Wami population (Fis = 0.42). An opposite trend was observed for the Mansi population (Fis = −0.03), suggesting a slight excess of heterozygotes. However, the corresponding SE was the highest among all tested populations (SE = 0.05).The expected heterozygosity . On the other hand, the lowest genetic distance was observed between the Kibasira and Kilola populations (Fst = 0.001).The estimated genetic distances according to the s Figure . The higThe conducted isolation‐by‐distance analysis did not detect a statistically significant spatial pattern between the estimated genetic distances and the corresponding geographic locations on the studied wild populations. The correlation among the above was 0.05 with the corresponding p‐value after 100,000 permutations being 0.39  which could entail a certain level of bias during SNP detection. However, the fact that more than 94% of the sequenced reads were aligned to the reference genome indicates that the subsequent SNP detection is robust. Furthermore, even though our approach would not have been able to identify Rufiji tilapia specific loci, the high percentage of aligned reads indicates that the latter would have been most likely a very small percentage with limited effect on the downstream analysis. It would worth also to stress the fact that Nile and Rufiji tilapias can produce fully fertile hybrids , π (0.10–0.37) and Ho (0.10–0.21). Compared to previous population genetics studies on aquatic organisms using RAD‐family genotyping protocols  indicated a potential loss of heterozygosity only for the wild population from Wami. In general, high Fis values indicate the existence of nonrandom mating or population subdivision . However, several exceptions were observed with the most striking exception being the one between Chemchem and Utete populations where a moderate‐to‐high genetic distance (Fst = 0.34) was estimated. In general, Fst values below 0.05 indicate minimal genetic differentiation, while values above 0.15 indicate the existence of substantial genetic differentiation . As previously mentioned, Rufiji tilapia is the only endemic Oreochromis species in the Mindu reservoir  the possibility of sample mislabeling cannot be excluded especially in the case of the single animal from Kilola population that appeared genetically distant from its putative population of origin.Bayesian and multivariate approaches were used in the current study in order to decipher the genetic structure and putative admixture among the tested populations. Both approaches supported the hypothesis of three unique genetic clusters among the populations under study Figures , 5. To t4.3Oreochromis species in Tanzania oriented for aquaculture practices and the critically endangered Oreochromis jipe  in the scenario of predicting for population of origin. The drop in the accuracy of successful classification appears to be in line with the obtained genetic distance of the respective populations. The above was more pronounced in the case of Kilola and Kibasira where the proportion of correctly classified fish dropped to only 10% indicating that the two populations were highly similar . Moreover, a similar pattern was observed in the case of the farmed populations (Bwawani and Chemchem) and the respective wild populations of most likely putative origin (Nyamisati and Ruaha) suggested by our data. Aiming to acquire deeper insights and confirm that the reduction of successful classification for predicting population of origin was due to the low genetic distance between some of the studied populations, we tested our dataset in a theoretical scenario aiming to predict for genetic cluster. In particular, since our analysis suggested the existence of three distinct genetic clusters, we followed the same cross‐validation scheme as before for forming training and validation sets on each putative genetic cluster . The above allowed us to obtain close to 100% successful classification on the test dataset.Moreover, a similar approach was followed in our prior studies on Nile tilapia strains (mainly of farmed origin) where the SNP information allowed for correctly classifying between 77% and 97% of the tested dataset to the respective population of origin ; investigation ; methodology ; software ; writing – original draft . Matern S. P. Mtolera: Conceptualization ; funding acquisition ; investigation ; methodology ; writing – review and editing . Aviti J. Mmochi: Conceptualization ; methodology ; writing – review and editing . Fernando A. Lopes Pinto: Investigation ; writing – review and editing . Ross Houston: Conceptualization ; funding acquisition ; methodology ; supervision ; writing – review and editing . Dirk J. de Koning: Conceptualization ; methodology ; project administration ; writing – review and editing . Christos Palaiokostas: Conceptualization ; methodology ; supervision ; writing – review and editing .The current study was carried out in accordance with the law on the protection of animals against cruelty (Act No. 12/1974. of the United Republic of Tanzania) upon its approval by the Department of Zoology and Wildlife Conservation, University of Dar es salaam. All the permits required to sample wild animals in Tanzania adhered to the Research clearance from Tanzania Commission for Science and Technology (COSTECH).Figure S1Click here for additional data file.Table S1Click here for additional data file.


Garcinia kola (Heckel) is a versatile tree indigenous to West and Central Africa. All parts of the tree have value in traditional medicine. Natural populations of the species have declined over the years due to overexploitation. Assessment of genetic diversity and population structure of G. kola is important for its management and conservation. The present study investigates the genetic diversity and population structure of G. kola populations in Benin using ultra-high-throughput diversity array technology (DArT) single nucleotide polymorphism (SNP) markers. From the 102 accessions sampled, two were excluded from the final dataset owing to poor genotyping coverage. A total of 43,736 SNPs were reported, of which 12,585 were used for analyses after screening with quality control parameters including Minor allele frequency (≥ 0.05), call rate (≥ 80%), reproducibility (≥ 95%), and polymorphic information content (≥ 1%). Analysis revealed low genetic diversity with expected heterozygosity per population ranging from 0.196 to 0.228. Pairwise F-statistics (FST) revealed low levels of genetic differentiation between populations while an Analysis of molecular variance (AMOVA) indicated that the majority of variation (97.86%) was within populations. Population structure analysis through clustering and discriminant analysis on principal component revealed two admixed clusters, implying little genetic structure. However, the model-based maximum likelihood in Admixture indicated only one genetic cluster. The present study indicated low genetic diversity of G. kola, and interventions are needed to be tailored towards its conservation. Garcinia kola (Heckel) is endemic in coastal areas, lowland plains and humid lowland rainforest of West and Central Africa [Garcinia kola is an indigenous tree with cultural and medicinal importance to local populations [G. kola, and now the species is classified as “extinct in the wild” in the Benin Red List of Threatened Species [G. kola and the current conservation status of the species in Benin, there is no report on molecular genetic diversity and population structure of G. kola in Benin.l Africa . The trel Africa . Garciniulations . In folkulations , 4. It iulations , 4. Howeulations  where thulations . These a Species . In spitG. kola populations in Benin using a DArT genotyping by sequencing (GBS) approach. The specific questions addressed in this study were:Genetic diversity is important in species conservation and is correlated to population size . Therefo(i) What is the amount of genetic diversity and differentiation harbored within-and among populations?(ii) Does population structure reflect geographic locations of collection?G. kola genetic improvement activities, and provide foundation for decision-making on conservation interventions.(iii) Do populations form distinct genetic clusters? An analysis of genetic diversity and structure will generate information crucial to The study was carried out on private lands between June and August 2017. Leaders of the communities as well as agriculture extension workers were made aware of our presence and the purpose of the study. Samples were collected upon owners' permission.G. kola, which represent the collection locality/site, were sampled in the Atlantique, Oueme and Plateau regions of Benin  DNA isolation protocol with slight modifications as described by Hanaoka et al. . Extracthttp://www.diversityarrays.com) libraries were prepared using the PstI-SphI complexity reduction method [PstI Restriction Enzyme (RE) (as a rare/primary cutter) and SphI RE frequent cutter at 37°C for 3 hours, then at 60°C for 20 min [PstI-compatible) included an Illumina flow cell attachment sequence, sequencing primer sequence and, varying length barcode region [SphI-compatible overhang sequence. Samples were processed in batches of 94. For each sample, amplification of the fragments containing both PstI and SphI (mixed fragments) [Diversity Arrays Technology (DArT) Pty Ltd, Australia   was perfUsing the KDCompute 1.5.2 , each loIS) and pairwise F-statistics (FST) matrices [Genetic diversity parameters such as the average observed heterozygosity (Ho), expected heterozygosity (He), inbreeding coefficient , call rate (≥ 80%), polymorphism information content (PIC ≥ 1%) and reproducibility (≥ 95%), 12,585 SNPs were retained . A totalIS, which measures the inbreeding of an individual within a sub-population was significantly high (ranging from 0.781 to 0.848) across all the populations  were performed for the 12,585 retained SNP markers. The results of the AMOVA  also indicated significant (P <0.001) but low levels of genetic differentiation (ST = 0.082) populations.Pairwise genetic differentiation estimates (Fntiation . The higG. kola accessions into two admixed clusters (The unweighted pair group method of arithmetic averages (UPGMA) analysis clustered the 100 clusters . Clusterclusters .The visualization of the population structure using DAPC displayed two admixed genetic clusters . This geG. kola in Benin is important for the management and conservation of the species. This study provides the first-ever molecular assessment of G. kola diversity and population structure through a genome-wide SNP dataset. In this study, 12,585 informative DArTseq SNP markers were identified across 100 G. kola accessions. The PIC values were useful in studying the level of polymorphisms among the accessions. The average PIC of 0.3 indicates the markers to be moderately informative. The average PIC is also close to the value obtained for SNP markers identified using GBS in the study of rice [G. kola in Nigeria using RAPD markers reported a PIC value of 0.93 [G. kola accessions from Nigeria [G. kola is only found in home gardens, farms, and fallows and therefore may have been subjected to voluntary or involuntary selection. The results of this study are consistent with other studies reporting a reduction in genetic diversity in domesticated crops as compared to their wild progenitors [Cycad balansae [Glyptostrobus pensilis [Pulsatilla patens [IS = 0.781–0.848). This could be attributed to self-pollination in G. kola populations [G. kola is a dioecious species and the ability of G. kola to mate with half sibs may have resulted in inbreeding among closely related individuals. Low genetic diversity and inbreeding depression have been observed in many studies on threatened species as a consequence of a decrease in population size. [G. kola in Benin, which confirms the recent report of the species' disappearance in the wild [Assessment of genetic diversity and population structure of  of rice  and whea of rice  diversit of 0.93 . The bi- of 0.93  can expl Nigeria . The low Nigeria . In Benigenitors , 34. Hetbalansae , Glyptospensilis , Pulsatia patens . Furtherulations . Indeed,on size. , 37. ThiST) values is a measure of population substructure and is useful in examining the overall genetic differentiation/divergence among populations. The FST values below 0.05 indicate low genetic differentiation, while values between 0.05–0.15, 0.15–0.25, and above 0.25 indicate moderate, high, and very high genetic differentiation respectively [ST showed low but significant (p < 0.05) differentiation among the studied populations. It was also observed that genetic variation was mainly found within populations (97.86%). This could be due to the small distribution range of G. kola in Benin and the short distances between the studied populations, which facilitate gene flow between populations. In addition, G. kola populations in Benin are under heavy anthropogenic exploitation [G. kola individuals into two principal genetic clusters. Hierarchical clustering analysis performed on G. kola accessions in Nigeria also revealed two clusters [Population differentiation is important for understanding the relative effect of evolutionary gene flow, mating system, selection, adaptation, and genetic drift on populations . Pairwisectively . In the oitation . Discrimclusters . Howeverclusters , thus fuclusters . A findiG. kola in Benin. Results indicate low genetic variation among the studied populations and high variation among individuals within populations. Finally, population structure analysis indicates the studied populations of G. kola to be a single population. However, it is not possible to ascertain if these results and observations can be extrapolated to the larger distribution range of G. kola because of the small distribution of the species in Benin. Sampling from a larger area, within the natural range of G. kola in West Africa, would provide a much more robust representation of genetic diversity and population structure of the species throughout its native range.The present study provides insights into the molecular diversity of S1 Table(XLSX)Click here for additional data file.S1 FigG. kola accessions in the R package adegenet.The plot was generated using the most informative 40 PCs identified from all the 12,585 SNPs dataset across 100 (TIF)Click here for additional data file.


Oxytenanthera abyssinica) is an economically and ecologically important species which accounts about 85% of total bamboo coverage in the country. This species is experiencing population decline due to a number of anthropogenic factors. As a foundation step, genetic diversity, population structure, and gene flow analysis of various O. abyssinica populations found in Ethiopia are studied using inter‐simple sequence repeat markers. One hundred and thirty isolates of bamboo belonging to 13 geographically diverse populations were collected for DNA extraction and analysis. Heterozygosity, level of polymorphism, marker efficiency, Nei's gene diversity (H), and Shannon's information index (I) analysis, analysis of molecular variance (AMOVA), analysis for cluster, principal coordinates (PCoA), and admixture analyses were performed based on the markers banding pattern. The results indicated high genetic variation (84.48%) at species level. The H, I, observed and effective number of alleles at the species level were 0.2702, 0.4061, 1.8448, and 1.4744, respectively, suggesting a relatively high level of genetic diversity. However, genetic differentiation at the population level was relatively low. Using grouped populations, AMOVA revealed that most (61.05%) of the diversity was distributed within the populations with FST = 0.38949, FSC = 0.10486, and FCT = 0.31797. Cluster analysis grouped the populations into markedly distinct clusters, suggesting confined propagation in distinct geographic regions. STRUCTURE analyses showed K = 2 for all populations and K = 11 excluding Gambella population. Using these markers, we found strong evidence that the genetic diversity of the lowland bamboo is associated with distinct geographic regions and that isolates of Gambella Region, with their unique genetic origin, are quite different from other bamboos found in the country.Bamboo, a member of subfamily Bambusoideae in the grass family (Poaceae), is one of the most important nontimber forest resources and a potential alternative to wood and wood products. Ethiopian lowland bamboo ( Oxytenanthera abyssinica) is an economically and ecologically important species which accounts about 85% of total bamboo coverage in the country. This species is experiencing population decline due to a number of anthropogenic factors. As a foundation step, genetic diversity, population structure, and gene flow analysis of various O. abyssinica populations found in Ethiopia are studied using inter‐simple sequence repeat markers. One hundred and thirty isolates of bamboo belonging to 13 geographically diverse populations were collected for DNA extraction and analysis. Heterozygosity, level of polymorphism, marker efficiency, Nei's gene diversity (H) and Shannon's information index (I) analysis, analysis of molecular variance (AMOVA), analysis for cluster, principal coordinates (PCoA), and admixture analyses were performed based on the markers banding pattern. The results indicated high genetic variation (84.48%) at species level. The H, I, observed and effective number of alleles at the species level were 0.2702, 0.4061, 1.8448, and 1.4744 respectively, suggesting a relatively high level of genetic diversity. However, genetic differentiation at the population level was relatively low. Using grouped populations, AMOVA revealed that most (61.05%) of the diversity was distributed within the populations with FST = 0.38949, FSC = 0.10486, and FCT = 0.31797. Cluster analysis grouped the populations into markedly distinct clusters, suggesting confined propagation in distinct geographic regions. STRUCTURE analyses showed K = 2 for all populations and K = 11 excluding Gambella population. Using these markers, we found strong evidence that the genetic diversity of the lowland bamboo is associated with distinct geographic regions and that isolates of Gambella Region, with their unique genetic origin, are quite different from other bamboos found in the country.Bamboo, a member of subfamily Bambusoideae in the grass family (Poaceae), is one of the most important non‐timber forest resources and a potential alternative to wood and wood products. Ethiopian lowland bamboo ( These two species are indigenous to Ethiopia and endemic to mainland Africa  accounts for 85% of the total national coverage, while the highland bamboo  accounts for the remaining 15%  at DNA level, prompted the commencement of this research. Therefore, in the present study, we used 19 ISSR primers out of 108 initial screenings and 38 final screening of ISSR primers aiming to assess the genetic diversity, population structure, and gene flow analysis of O. abyssinica collected from lowland bamboo growing areas in Ethiopia.About half of the world`s woody bamboo species are vulnerable to extinction as a result of massive forest destruction  growing areas of Ethiopia. Since 64.07% of the country's lowland bamboo grows in the BGR  from 130 individuals belonging to 13 populations  were collected from the natural lowland bamboo  in the presence of three 3.2 mm diameter stainless steel beads in a 2‐ml sterile centrifuge tube. Genomic DNA was isolated separately using a modified 2% cetyl trimethyl ammonium bromide (CTAB) DNA isolation method at Plant Molecular Biology Laboratory (PMBL) and Plant Genetics Research Laboratory (PGRL) of Addis Ababa University. One milliliter preheated 2% CTAB extraction buffer  was added to the tube containing crushed leaf powder. The dissolved CTAB mix was incubated for 30 min at 65°C. The tubes were gently inverted every 10 min. Seven hundred microliters of the supernatant (clear liquid only) was transferred to a new sterile centrifuge tube using blue pipette tips, which were cut. Seven hundred microliters of chloroform was added, mixed thoroughly, and centrifuged at 16,000 g for 10 min at 26°C. Six hundred microliters of the supernatant was transferred to the new fresh Eppendorf tube, and 60 µl of 3 M sodium acetate (pH 5.2) was added and thoroughly mixed. Six hundred microliters of ice‐cold isopropanol was added and gently mixed by inverting the tubes 3–5 times, and then, the tubes were placed in a refrigerator at −20°C for 2 hr. The mix was centrifuged at 16,000 g at 4°C for 5 min to precipitate the DNA. The supernatant was discarded, and the DNA was washed using 1 ml of 70% ethanol by dissolving the pallet completely in the wash buffer and centrifuged at 16,000 g for 3 min at 4°C. The wash step was repeated by cold absolute ethanol (1 ml), and the pellet was air‐dried. The pellet was dissolved in 60 µl 0.1X TE (10 mM Tris‐HCl pH 8.0 and 1 mM EDTA pH 8.0) buffer containing RNase. The concentration and quality of DNA were checked by test gel electrophoresis in 1% agarose and measured by using NanoDrop (Thermo Scientific NanoDrop 2000 Spectrophotometer). Each sample was measured, and those with high DNA quality were used for PCR amplification after normalization of each sample to a concentration of 100 ng/μl. Gel documentation was taken by Bio‐Rad Gel Doc™ EZ System Imager.A total of 130 Thirty‐eight primers (35 designed from the University of British Colombia (UBC) and 3 from previous work) out of 108 ISSR primers (100 from UBC and 8 from the literature) were screened for the initial testing of polymorphism and reproducibility. Nineteen primers were found to be reproducible and polymorphic and used for further ISSR‐PCR work for the study. Among these 19 ISSR primers, ten were dinucleotide, two were tri‐nucleotide, two were tetra‐nucleotide, three were penta‐nucleotide, and two were 5′ anchored primers. Primers were further categorized into 3′ anchored, 5′ anchored, and unanchored based on anchorage property Table .2.32, PCR buffer, PCR reaction enhancer, stabilizer, and a blue tracer dye), 3.5 µl of ddH2O, 0.5 µl of ISSR primer (0.2 pmol/µl), and 0.5 µl of normalized genomic DNA (100 ng). The blue dye and a stabilizer of 2x Taq plus Master Mix helped to directly load the final products onto a gel for analysis. The thermal profile included pre‐PCR denaturation at 94°C for 4 min followed by 35 cycles of denaturing at 94°C for 30 s, annealing for 30 s at the optimized temperature , the same weight bands were marked as a line. The bands that were clearly visible and repeatable on the electrophoresis map were marked as "1," the absence of a band at the same site was marked as "0" and ambiguous bands were considered as a missing data and marked as "?". Intensity variations among fragments having approximately the same molecular size were not considered although in some cases intensity differences of the bands were observed. A binary data matrix was compiled with individuals in the column and the ISSR markers in the row for each primer set and vice‐versa according to the requirements of the software. Each amplified fragment was named by the code of the primers across the row and/or column followed by the Arabic numbers starting from the fragment having high molecular weight to the fragments with low‐molecular weight. Both the total number of bands amplified by each primer and the number of polymorphic bands were calculated.2.52.5.1H), and discriminating power (D) were inferred via iMEC (https://irscope.shinyapps.io/iMEC/) online.On the basis of the recorded band profiles, different software was employed for data analysis. POPGENE version1.32 , among populations within groups (FSC), and among groups (FCT) using Areliquin version 3.01  was used to calculate the 2.5.3NTSYS‐pc version 2.02 Rohlf,  was usedK), a burn‐in period of 50,000 was used in each run, and data were collected over 500,000 Markov Chain Monte Carlo (MCMC) replications for K = 1 to K = 13 and K = 1 to K = 12 (excluding samples from Gambella Region) using 20 iterations for each K. Each test takes more than 300 hr. for analysis using a PC with 8GB RAM and a core i7 processor. The optimum K value was predicted following the simulation method of Evanno, Regnaut, & Goudet, A Bayesian model‐based clustering algorithm in STRUCTURE ver. 2.3.4  was produced by primers UBC‐815 (24), UBC‐835 (23), UBC‐834 (22), and UBC‐888 (22) and the lowest NSB were produced by primers UBC‐844 (13) and UBC‐889 (14). The number of polymorphic loci (NPL) ranges from 24 (UBC‐815) to 9 (UBC‐889). Percentage of polymorphic loci (PPL) was 100% for primers UBC‐812, UBC‐815, and UBC‐834, the lowest PPL were exhibited by primers UBC‐888 (54.55%), and UBC‐889 (64.29%) and the average PPL for all primers were 84.48%. Based on the repeat motifs and anchorage property of primers, dinucleotide repeat motifs showed higher PPL (94.05) than tri‐ (78.12), tetra‐ (74.36), and penta‐nucleotide (80.36) repeat motifs. 3′ anchored primers showed higher PPL (94.05) than 5′ anchored (58.33). Anchored primers show higher PPL (88.24) than unanchored primers (77.95).H) value (0.1451 ± 0.1633) was shown by primer UBC‐848, and the highest (0.3747 ± 0.1784) was exhibited by primer UBC‐812. Again, dinucleotide repeats showed the highest heterozygosity (0.2894 ± 0.1780). Similarly, the maximum and minimum Shannon's information index (I) was 0.5506 ± 0.1389 by UBC‐834 and 0.5428 ± 0.2197 by UBC‐812. The highest estimate of gene flow (Nm) was observed in UBC‐888 (3.2746) and least Nm was observed in UBC‐861 (0.3456). The average Nm for overall primers was 1.5474. Tetra‐nucleotide (2.4322) and 5′ anchored (2.4821) primers showed the highest Nm values (Table The lowest heterozygosity (3.2.2H), polymorphism information content (PIC), and discriminating power (D) values were shown by anchored primers in general and 3′ anchored and dinucleotide repeats (UBC‐834 and UBC‐835) in particular. The H, PIC, MI, and D values for anchored primers were 0.503661, 0.470489, 0.503661, and 0.455827, respectively; 3′ anchored and dinucleotide repeats were 0.520932, 0.459651, 0.520932, and 0.698063; UBC‐834 were 0.732223, 0.507292, 0.732223, and 0.438911; and UBC‐835 were 0.686454, 0.508061, 0.686454, and 0.323554. The lowest H, PIC, and D values were observed in tri‐nucleotides and 5′ anchored primers. Again, dinucleotide and anchored primers showed higher D values than other repeat motif types and unanchored primers (Table The highest expected heterozygosity (3.2.3) and mean of unbiased expected heterozygosity (uHe) along with standard errors showed the highest values in the Guba  and Dabu Hena populations  (Table The highest number of band patterns was observed in the Konta population (227) followed by Guba and Pawe populations (219) each. The highest number of private bands was observed in Gambella populations (69), 6 in Konta, and 1 in the Pawe population. There were no private bands in the other populations. A majority of the bands was obtained from the number of different bands with a frequency of ≥5% (NDBF ≥ 5%). Mean of expected heterozygosity (He3.3H), Shannon's diversity index (I), observed number of alleles (Na), and effective number of alleles (Ne) along with standard deviation (SD) at species levels were also 0.2702 ± 0.1945, 0.4061 ± 0.2595, 1.8448 ± 0.3626, and 1.4744 ± 0.3960, respectively, showing a relatively high level of genetic diversity  followed by Dabu Hena or Didhesa valley population (0.2165 ± 0.2407).The Mandura, Abol, and Yasso populations were observed to be the least diverse, with gene diversity values of 0.1842 ± 0.2285, 0.1978 ± 0.2390, and 0.1922 ± 0.2342, respectively. The same diversity patterns were also observed for I, Na, and Ne, whereby Guba, Dabu Hena, and Bambasi populations showed the highest and Mandura, Yasso, and Abol populations showed the least. In general, Metekel Zone of BGR showed the highest NPL, PPL, H, I, Na, and Ne even though the Buno Bedele Zone of Oromia Region showed the highest value by single population. Polymorphism within the population was found to be lower than 50% for all populations. Additionally, the total genetic diversity (Ht) was 0.2708 ± 0.0379, the genetic diversity within populations (Hs) was 0.2047 ± 0.0327, the coefficient of gene differentiation (Gst) was = 0.2442, and estimate of gene flow among populations (Nm) was = 1.5474)  followed by Dabu Hena (45.40%) and Bambasi (44.83%). Populations from Mandura (40.52%), Gambella, and Yasso (41.09%), on the other hand, were observed to have the lowest percent polymorphism. High genetic variation at the species level was observed in the present investigation with 84.48% PPL. The values for Nei's genetic diversity  was carried out in two phases; the first phase focused on the entire population's overall loci by considering them as one geographic region and the second phase separated populations into seven groups based on administrative Zones. The analysis was carried out by computation of the distance between “haplotypes,” each individual's data pattern as one “haplotype” and computing variance components for each level , while the remaining diversity was due to differences among populations (36.35%) with a FST value of 0.36354. In both cases, the analysis of molecular variance revealed the same patterns of genetic diversity and support the larger genetic diversity found within the populations rather than among the populations, and are similar to Shannon's diversity index.Partitioning of genetic diversity by AMOVA Table  using gr3.5O. abyssinica. The UPGMA dendrogram resulting from a SAHN clustering analysis and NJ analysis on the basis of Jaccard's coefficients of similarity was constructed. The Jaccard's coefficient of similarity was obtained after pair‐wise comparisons were performed using binary character matrices (of the presence and absence of bands) that were produced from amplified fragments.Intrageographical cluster analysis of UPGMA (Unweighted Pair Group Methods using arithmetic Averages) and NJ (Neighbor‐Joining) was computed for all individuals and populations of O. abyssinica all 19 ISSR primers produced exactly the same tree topology according to their geographic distance and location.Most primer combinations in terms of nucleotide repeats and anchorage property showed almost similar clusters like the overall assessment. However, tri‐nucleotide repeat ISSR primer mixes Kurmuk samples of BGR with those of the Oromia Region, areas that are distant from one another. 5′ anchored primers, on the other hand, mix samples from the Kemash Zones of the BGR samples with those of Oromia Region. The poorest tree topology was observed by penta‐nucleotide primers that mix Assosa, Pawe, and Yasso populations in the same cluster while they were geographically very distant and even in three separate administrative zones of BGR Figure . General3.6O. abyssinica using three coordinates  to be the most likely number of clusters , NPL (195), and PPL (88.24) showed better NSB, NPL, and PPL than unanchored primers with values of 127, 99, and 77.95 respectively. This investigation, like those of Ng and Tan  and TariH, and D were shown by anchored primers in general and by 3′ anchored and dinucleotide repeats in particular. Amom et al., , and I (0.3088 ± 0.3330 and 0.3035 ± 0.3360) were found in the Guba and Dabu Hena populations. The lowest values of NPL, PPL, H, and I were observed in the Yasso, Abol and Kurmuk populations.The high number of alleles and high polymorphism are very important for the correct estimation of the genetic diversity of germplasm. The degree of polymorphism showed the extent of diversity and effectiveness of the markers , I ± SD (0.4061 ± 0.2595), Na (1.8448 ± 0.3626), and Ne (1.4744 ± 0.3960) were recorded in the current study of O. abyssinica populations based on 19 ISSR markers. Compared to other bamboo species, the O. abyssinica populations in Ethiopia showed higher genetic diversity with H = 0.2702 ± 0.1945 and I = 0.4061 ± 0.2595. The H = 0.0418 ± 0.0456 and I = 0.0624 ± 0.0651 were recorded in Chinese giant bamboo  population with low genetic diversity and high genetic differentiation  and I (0.291 ± 0.209) were observed in the Dendrocalamus hamiltonii population of the northeast Himalayas with low genetic diversity and a moderate level of genetic differentiation  Kurz: bamboo of Manipur, Northeast India , PPL (84.48%), O. abyssinica recorded the total genetic diversity (Ht = 0.2708 ± 0.0379), genetic diversity within populations (Hs = 0.2047 ± 0.0327), the relative magnitude of genetic differentiation among populations (Gst = 0.2442), and estimate of gene flow among populations (Nm = 1.5474). The Ht = 0.1961, Hs = 0.1639, Gst = 0.1942, and Nm = 2.5455 with high genetic diversity was also recorded in Melocanna baccifera (Roxb.) Kurz: using seven ISSR primers , Phyllostachys accessions (Asian bamboo) using 16 primers reported that 75% of variation was within the population and 25% among the populations. The findings of Meena et al. , and 6.28% among groups, 12.45% among populations within the group, and 81.26% within populations in four hierarchical groups. Nilkanta et al. (M. baccifera (Roxb.) Kurz: bamboo of Manipur, Northeast India, found an AMOVA of 22% among populations and 78% within populations. Yang et al.'s study  from Sri Lanka using 12 microsatellite loci reported an AMOVA result of 8.35% among groups, 7.52% among populations within groups, and 84.13% within populations. But compared to the above work on different bamboo species, the within‐population percentage of 61.05% for O. abyssinica is smaller.Our results of AMOVA with respect to grouping and without grouping populations are consistent with several works on bamboo. A study by Li et al.  on IRAP a et al.  on 19 poa et al. , who use's study  on D. mend Clark  on the sFSC = 0.10486, FST = 0.38949 and FCT = 0.31797 in seven groups and FST = 0.36354 without grouping were recorded from O. abyssinica populations of Ethiopia. FSC = 0.132, FST = 0.187, and FCT = 0.062 in four groups and FST = 0.165 without grouping were reported from D. hamiltonii , and very great or significant genetic differentiation with FST = 0.36354 was recorded in O. abyssinica populations. For the interpretation of FST, it has been suggested that a value lying below 0.05 indicates little genetic differentiation; a value between 0.05 and 0.15, moderate differentiation; a value between 0.15 and 0.25, great differentiation; and values above 0.25, very great or significant genetic differentiation  recorded in O. abyssinica was comparable to those of another bamboo species such as D. hamiltonii (GST = 0.247)    that was similar to the average of out‐crossing species (GST = 0.22)  Nybom, .4.4Dendrocalamus hamiltonii  Kurz  with an optimum population structure consisting of two and 11 sub‐populations. The delta K = 11 value is in agreement with the result of XLSTAT clustering the Ethiopian lowland bamboo into their geographic location. This implies that samples collected from the Gambella Region are different from others and may indicate a possible existence of additional bamboo species in the country.Admixture results via STRUCTURE and web‐based data retrieval from structure harvester and CLUMPAK with and without Gambella samples showed different delta 5O. abyssinica populations and to devise mechanisms for effective identification, conservation and sustainable use of bamboo resources in Ethiopia using ISSR markers. Although a relatively high level of genetic diversity exists at species level, and a relatively low genetic differentiation was observed at the population level, most of the diversity was distributed within the populations, and cluster analysis grouped the populations into sharply distinct clusters, all of which could be attributed to the plant's cross‐pollination nature and long‐standing presence in the area. Using these ISSR markers, we found strong evidence linking geographic origin with diversity. The Metekel Zone in particular is in need of a conservation strategy, as it was found to have the most diverse population and samples from the Gambella Region were found to be different from those taken from others regions, indicating the availability of additional bamboo species in the country. Though the present investigation yielded some information on the genetic diversity of O. abyssinica populations in Ethiopia using ISSR markers, there is a need for further critical work involving molecular markers giving greater genome coverage to improve our understanding of genetic diversity in bamboo at the species and population level.The aim of the present study was to explore the extent of genetic diversity, population structure, and gene flow analysis of The authors declare no conflict of interest.Oumer Abdie Oumer: Conceptualization (lead); data curation (lead); formal analysis (lead); funding acquisition (lead); investigation (lead); methodology (lead); project administration (lead); resources (lead); software (lead); supervision (lead); validation ; visualization (lead); writing–original draft (lead); writing–review and editing (lead). Kifle Dagne: Conceptualization ; data curation ; formal analysis ; investigation ; methodology ; project administration ; resources ; software ; supervision ; validation ; visualization ; writing–original draft ; writing–review and editing . Tileye Feyissa: Conceptualization (lead); data curation ; formal analysis (lead); investigation ; methodology ; software ; supervision ; validation ; visualization ; writing–original draft ; writing–review and editing . Kassahun Tesfaye: Conceptualization (lead); data curation ; formal analysis (lead); funding acquisition ; investigation ; methodology (lead); project administration (lead); resources (lead); software ; supervision ; validation ; visualization ; writing–original draft ; writing–review and editing (lead). Jayaraman Durai: Funding acquisition (lead); project administration (supporting); writing–original draft (supporting); writing–review and editing . Muhammad Zeeshan Hyder: Conceptualization ; data curation ; funding acquisition ; investigation ; methodology ; project administration ; resources ; software ; supervision ; validation ; visualization ; writing–original draft ; writing–review and editing .https://doi.org/10.5061/dryad.b5mkkwh8z.This article has been awarded <Open Data, Open Materials, Preregistered Research Designs> Badges. All materials and data are publicly accessible via the Open Science Framework at Fig S1‐S3Click here for additional data file.