SNP) panel, we assessed the genetic diversity, population structure and admixture in six goat breeds in Uganda: Boer, Karamojong, Kigezi, Mubende, Small East African and Sebei. All the animals had genotypes for about 46 105 SNPs after quality control. We found high proportions of polymorphic SNPs ranging from 0.885 (Kigezi) to 0.928 (Sebei). The overall mean observed (OH) and expected (EH) heterozygosity across breeds was 0.355 ± 0.147 and 0.384 ± 0.143 respectively. Principal components, genetic distances and admixture analyses revealed weak population sub‐structuring among the breeds. Principal components separated Kigezi and weakly Small East African from other indigenous goats. Sebei and Karamojong were tightly entangled together, whereas Mubende occupied a more central position with high admixture from all other local breeds. The Boer breed showed a unique cluster from the Ugandan indigenous goat breeds. The results reflect common ancestry but also some level of geographical differentiation. admixture and f4 statistics revealed gene flow from Boer and varying levels of genetic admixture among the breeds. Generally, moderate to high levels of genetic variability were observed. Our findings provide useful insights into maintaining genetic diversity and designing appropriate breeding programs to exploit within‐breed diversity and heterozygote advantage in crossbreeding schemes.Uganda has a large population of goats, predominantly from indigenous breeds reared in diverse production systems, whose existence is threatened by crossbreeding with exotic Boer goats. Knowledge about the genetic characteristics and relationships among these Ugandan goat breeds and the potential admixture with Boer goats is still limited. Using a medium‐density single nucleotide polymorphism ( According to archaeo‐zoological evidence, goats were among the first ungulates to be domesticated, about 10 000 years ago near the fertile crescent that spans from Eastern Anatolia to the Zagros Mountains in Northern Iran  that are geographically isolated and are raised in diverse production systems  were sampled from 79 smallholder farms/herds, and the exotic Boer goats were sampled from a commercial multiplication centre (Ssembeguya Estates) and a government breeding centre (Rubona Stock farm), which are sources of breeding stock for goat improvement in Uganda.Sampling was carried out at selected geographical locations Fig.  accordinn = 29), Kigezi (n = 29), Small East African (n = 29), Karamojong (n = 15) and Sebei (n = 29) and at a commercial and a government breeding centre for Boer (n = 13). The ear tissue samples were collected into vials containing a desiccant and stored within 12 h in a freezer at −4 °C.Ear punch tissue was collected from the 144 goats at smallholder farms for the indigenous breeds Mubende .®). Twenty DNA samples were randomly selected and analyzed on a 1% agarose gel for a preliminary estimate of the DNA quality and quantity. The final DNA quality and quantity were validated using the Qubit® dsDNA BR (Broad‐Range) Assay Kit on the Qubit 2.0 fluorimeter (Invitrogen) prior to genotyping.Genomic DNA was extracted using the DNeasy blood and tissue kit . Genomic locations of the SNPs and cluster files were provided by IGGC. Standard SNP genotype quality control procedures were performed using plink v1.07  of 0.05 or less and SNPs whose genotypes were not in Hardy Weinberg equilibrium (P < 0.001) were excluded from downstream analysis. The dataset of SNPs used in the analysis is available from https://www.animalgenome.org/repository/pub/WAGNL2017.1002/.DNA samples were genotyped with the Illumina GoatSNP50 BeadChip. The BeadChip, developed by the International Goat Genome Consortium (IGGC), features 53 347 SNPs across the whole goat genome with inter‐SNP spacing of approximately 40 kb (Tosser‐Klopp O) and expected (HE) heterozygosities for the respective populations were calculated using plink  test  test  statistics for all possible combinations of three populations. Generally, if population A is a result of an admixture between two other populations B and C, the calculated z‐score for each tested combination of three populations would have a significant negative value. A positive z‐score may indicate either absence of admixture or substantial post‐admixture drift resulting from the alleles in the population. Meanwhile, the fourpop program from TreeMix was used to calculate f4  statistics for subsets of the population. The four‐population test f4  . The highest number of SNPs that showed a MAF of less than 0.05 was found in Small East African (n = 7818), whereas Sebei showed the lowest number of SNPs excluded (n = 6826). All animals passed the quality criteria and were used in the analysis.After quality control procedures on the 53 347 SNPs included in the SNP chip, 7242 SNPs were excluded Table , which rN) was found in Sebei (0.928) and the lowest in Kigezi (0.885); however, the differences in PN were negligible across all the breeds.Boer (0.51) and Kigezi (0.43) showed the highest and lowest proportion of SNPs with MAF greater than or equal to 0.3 respectively Fig. . The proO = 0.340 ± 0.181) and the highest in Boer (HO = 0.377 ± 0.193), indicating higher diversity in Boer compared to Kigezi. Also, the MAFs across all loci were lowest in Kigezi (0.257) and highest in Boer (0.280). In general, the observed heterozygosity was slightly lower than the expected heterozygosity (HO < HE), indicating a deficiency in heterozygosity across all the breeds.Genetic diversity was assessed within each breed Table . The resThe first principal component, eigen vector 1 (EV1) shown in Fig. Breed relationships were also assessed by computing genetic distances between each pair of individuals from the number of loci for which they differ. Based on the estimated genetic distances, a Neighbour‐Net graph was computed to depict breed clustering Fig. . The Ugaadmixture analysis at K = 2 separated the Ugandan indigenous goats from the commercial Boer goats  into the Ugandan breeds.et al. et al. et al. et al. et al. et al. et al.  to HE = 0.410 ±0.192 (Karamojong) and HO = 0.340 ± 0.181 (Kigezi) to HO = 0.377 ± 0.193 (Boer) respectively  were slightly higher than those reported for Boer populations in Canada    within all breeds. Thus, these differences may be due to a Wahlund effect rather than inbreeding.The difference between the observed and expected heterozygosity was small and within a fraction of one standard error. As a general trend, the observed heterozygosity was lower than the expected heterozygosity  test statistic, we found strong evidence of admixture in only four comparisons, all involving the Mubende goats as the admixed breed. The most significant z‐score (−19.408) was found with the Mubende f3 . All the significant f3 statistics were observed when Kigezi was one of the source populations, indicating that Kigezi might be contributing to the gene pool either through ancestral generations or crossbreeding with Mubende. The f4 statistics showed the most significant scores for the Boer and the Ugandan indigenous goats , two breeds clearly crossbred (Karamojong and Sebei) and Mubende showing signs of gene flow from all these goat populations. Nonetheless, there is rather limited Boer admixture in the Ugandan goat population. This knowledge can be exploited to devise strategies for sustainable utilization and maintenance of genetic diversity.The authors declare that they have no conflict of interest whatsoever to influence the outcome of the manuscript.RBO conceived and designed the study, collected the field samples and wrote the manuscript. MAMG, EK and RPMAC supervised the study. MRU, RBO and RM participated in data analysis. All authors have read and edited the manuscript.Figure S1 Genetic relationships among five Ugandan indigenous goat breeds and one commercial goat breed; constructed using a neighbour‐ joining tree from identity‐by‐state (IBS) distances derived from 46 105 SNPs.Click here for additional data file.Figure S2 Cross‐validation error plot indicating the choice of the appropriate K value.Click here for additional data file.Table S1 Significant f4 statistics for Ugandan goat breeds indicating gene flow in the breeds.Click here for additional data file.Table S2 Breed composition of cluster 1, 2, 3 and 4, interpreted as representative of Small East African, Karamojong/Sebei, Boer and Kigezi ancestries respectively, estimated for each individual belonging to goat populations from Uganda.Click here for additional data file.


Conservation of coastal habitats is a global issue, yet biogenic reefs in temperate regions have received very little attention. They have a broad geographic distribution and are a key habitat in marine ecosystems impacted by human activities. In the Mediterranean Sea coralligenous reefs are biodiversity hot spots and are classified as sensitive habitats deserving conservation. Genetic diversity and structure influence demographic, ecological and evolutionary processes in populations and play a crucial role in conservation strategies. Nevertheless, a comprehensive view of population genetic structure of coralligenous species is lacking. Here, we reviewed the literature on the genetic structure of sessile and sedentary invertebrates of the Mediterranean coralligenous reefs. Linear regression models and meta-analytic approaches are used to assess the contributions of genetic markers, phylum, pelagic larval duration (PLD) and geographical distance to the population genetic structure. Our quantitative approach highlight that 1) most species show a significant genetic structure, 2) structuring differs between phyla, and 3) PLD does not appear to be a major driver of the structuring. We discuss the implication of these finding for the management and conservation, suggesting research areas that deserve attention, and providing recommendations for broad assessment and monitoring of genetic diversity in biogenic reefs species. They support biodiversity by providing habitats, feeding grounds, recruitment and nursery sites for a myriad of species, and they host some of the most productive and diverse assemblages. However, they are also among the most threatened habitats globally6 owing primarily to human disturbances. They are exposed to long-term degradation, which affects species composition and abundance, and can cause dramatic declines in diversity and functioning8. Among temperate biogenic reefs, coralligenous formations, occurring in lower subtidal or twilight Mediterranean benthic environments (between 20 and 200 m), are considered one of the most valuable and diverse habitats12 , as well as local authorities, set the conservation of coralligenous reefs as a priority. The EU Habitats Directive, the Bern Convention, and the Barcelona Convention Action Plan have included coralligenous habitats in conservation plans, and the scientific literature has stressed the need to implement effective conservation policies17. To quantify the impacts of a variety of environmental and anthropogenic stressors, several studies applied a meta-analytical approach to data on the spatial and temporal distribution of coralligenous species. Giakoumi et al.15 have also stressed the importance of connectivity  in planning the conservation of coralligenous reefs, as already suggested for other marine habitats20.Biogenic temperate reefs include coral forests, maerl beds, coralligenous reefs and share several features with tropical reefs21. Its importance has been recently recognised at the policy level, as highlighted, for example, by the European Union “Marine Strategy Framework Directive” and by the Strategic Plan for Biodiversity 2011–2020 by The Convention on Biological Diversity .Connectivity is essential to population resilience following disturbance and underlies the dynamics of populations and metapopulations22. Multispecies, multiscale and multimarker studies on genetic connectivity have been proven to be effective in supporting biodiversity conservation planning24. However, most of these studies focused on tropical habitats and included comparative phylogeography, descriptive26 and meta-analytical reviews28. Only a few studies have investigated patterns of genetic connectivity in temperate biogenic reefs31 and in Mediterranean coralligenous reefs32.Different methods can be used to quantify connectivity . Genetic methods are frequently used to assess population connectivity when it is difficult to measure dispersal directly, as in the case of sessile species in the subtidal marine realmFST), summarising genetic variation among geographically separated populations. The use of FST to assess differentiation has been criticized33 since it is affected by within- population heterozygosity and tends to underestimate differentiation between populations as heterozygosity increases. Moreover, the assumption that pattern of spatial genetic differentiation (FST) primarily reflect variation in gene flow is questioned, since spatial genetic structure is also shaped by the demographic history of the populations34. Nevertheless, up to now is still the most suitable used metric37. Based on this metric, several theoretical patterns of genetic structure have been defined . Empirical evidence, summarised in a recent review42, indicates that these theoretical patterns could be observed in the same species, depending on the spatial and/or temporal scale of analysis. Understanding the drivers and the processes underlying these patterns of genetic structure is challenging. Abiotic  and biotic factors, related to the life history traits , drive patterns of genetic structuring. However, specific information on causal relationships between habitat features and the observed structure is still lacking. Only recently has the seascape ecology approach been applied in genetic studies43. Furthermore, for most marine invertebrates, information on larval ecology  is limited, and most information refers to the pelagic larval duration (PLD). PLD is commonly considered the best proxy for effective larval dispersal; therefore, its influence on connectivity has been extensively studied44. However, contrasting conclusions on the relationship between PLD and genetic structure have been reached37. A weak correlation between PLD and genetic differentiation has been highlighted in recent reviews on fishes and invertebrates35, suggesting that other life history traits45 and/or differences in effective population sizes36 could affect estimates of genetic differentiation. Nevertheless, these studies agree that direct-developers and benthic species with low mobility showed a relatively lower genetic structure to mobile species with planktonic larvae46.The most commonly used metric to estimate connectivity based on genetic data is Wright’s fixation index  in temperate habitats (from benthic to pelagic environments) have recently been published31. These studies show that genetic structuring was stronger in species with duration of dispersal phases shorter then 15 days compared to species with higher motility and dispersal, regardless of the presence of oceanographic discontinuities31.The role of the biological and ecological features of a species in determining the genetic structure may be tangled by the difference in the resolutions of the molecular markers used31), we screened all the literature and analysed separately data referring to populations sampled within single biogeographic areas. Finally, we discussed the implications of these findings for management and conservation of Mediterranean coralligenous reefs.In the present study, we have summarised the literature on the genetic structure of sessile and sedentary benthic invertebrates with negligible adult mobility that are commonly found in Mediterranean coralligenous habitats. Our aims were 1) to identify features and/or patterns in genetic diversity and structure and 2) to understand processes generating spatial genetic structuring among populations. The quantitative review has been carried out using two different statistical approaches  to investigate the roles of genetic markers, phylum, PLD and geographical distance in determining the observed patterns of genetic structure. To eliminate the confounding effect of the presence of geographical discontinuities . Only a few studies included samples collected in the Southern and Eastern Mediterranean Sea  associated with coralligenous assemblages (Supplementary Table 11). The dataset includes four major taxonomic groups: Porifera, Cnidaria, Echinodermata and Tunicata (Supplementary methods). Cnidaria and Porifera are the most represented taxa, with eight species each, followed by Tunicata, with six species. Seventeen of the 27 species (24 species + 3 species complex) were analysed at different spatial scales and using different molecular markers.The 50 analysed papers refer to 24 species and three species complexes (Paramuricea clavata) that is an external brooder and six that are broadcaster (Supplementary Table Amphipholis squamata) and species with long pelagic larval durations , with one (Leptopsammia pruvoti and Eunicella singularis) and three echinoderms  showed no genetic structure at the analysed spatial scales (but see Discussion). Ten species (37.03%) showed a chaotic genetic pattern, and six species (22.2%) showed an isolation-by-distance pattern , contrasting patterns of genetic structure were observed depending on the lineage49. The most recent paper50, which reanalyses previous data, showed a clear chaotic genetic pattern within the Amphipholis squamata species complex.Three patterns of genetic structure . Moreover, most of the observed species show a significant genetic structure across the Western and Eastern Mediterranean transition, even if the location of the shift varies, depending on the species.Most studies were not designed to test genetic structuring across Mediterranean oceanographic discontinuities, but populations were haphazardly sampled across the species distribution range. Nevertheless, the majority of taxa showed strong genetic breaks across their geographic range of distribution, with some common geographical patterns of genetic differentiation. The role of oceanographic fronts in setting connectivity patterns was recently investigated53, for which we estimated the dispersal distance. For C. rubrum and C. crambe we included in the analysis the estimated dispersal distance calculated by Ledoux et al.54 and Calderon et al.55, respectively. They found an estimated dispersal distance ranging between 20 and 30 cm in C. rubrum and of approximately 35 cm in C. crambe. For all the seven species considered, we estimated a dispersal distance ranging from 0.2 to 300 m  = 10.56, P = 0.0028; Fig. FST /geographic distance relationships among phyla, with Cnidaria appearing more structured than Echinodermata and Porifera , the best model  most species show a significant genetic structure within the biogeographic areas considered, 2) the structuring differs between phyla, 3) PLD does not appear to be a major driver of the structuring, and 4) the genetic marker used did not introduce a bias in the analyses.Leptopsammia pruvoti57 and Marthasterias glacialis58, where the sample size is small. Regarding other species, the absence of genetic structure could be attributed to the broadcast reproductive mode (Ophioderma longicauda LI (C3)48), to the large effective population size (Ophiothrix sp. II59) or to the small spatial scales investigated (Eunicella singularis60).Technical bias, such as uninformative molecular markers and/or low sampling efforts , may affect the ability to detect genetic differentiation. This could be the case for 31. Genetic shifts have been found in different locations according to the species: across the Siculo-Tunisian strait61, in the mid-Ionian Sea20, or in the eastern Ionian62. Other critical areas of discontinuities were observed31 and were species specific or shared by few species .Our qualitative synthesis highlights that, at the larger scale, a constraint to dispersal acting across multiple species was located in the Eastern-Western Mediterranean transitions. This area of discontinuity is well known for several marine species67. Both these features contribute to explain the patchy distribution of the organisms, and can influence processes acting in the early life stage of the organisms . Moreover, stochastic processes have a major influence on sessile and sedentary invertebrates with low dispersal capability (see below). Genetic differentiation was observed at smaller distances in Cnidaria, where the majority of populations were separated by less than 152 km, than in Echinodermata and Porifera, where the majority of populations were separated by more than 382 km with a median distance of 175 km . Chust et al.29 and Pascual et al.31 showed that species with similar life history traits  present a similar genetic pattern, but they did not test this effect across Phyla.The Echinodermata analysed in this study present a wide range of pelagic larval duration (see below), different reproductive modes and different nutritional modes, while Cnidaria do not. Previous studies found differences between major taxonomic groups , demographic parameters , and recruitment success70 may shape population genetic structure. These biological traits, together with the oceanographic condition, influence the reproductive success, leading to an increasing temporal and spatial variance of the effective population size (Ne). Moreover, since FST is affected by both the migration rate (m) and effective population size (Ne), a variation in Ne could also shape the correlation between FST and PLD36. Taking in account variability of the effective population size is a key task since it can mitigate the effect of genetic drift (see below).We found only a weak correlation between PLD and genetic structure. Therefore, despite PLD being the better-known larval feature, caution must be used when employing PLD as a proxy of effective dispersal. Several empirical studies71.ANCOVA analysis on mitochondrial DNA markers showed a significant negative correlation between PLD and population structure, suggesting that PLD might be a better predictor of genetic connectivity patterns when markers with low level of polymorphism and mutation rate were used. In contrast, the non-significant correlation observed using microsatellites, which have higher mutation rate, suggested that PLD is not the only factor that drives the genetic structure at a time scale of few generationssensu Johnson & Black72). In the literature, this pattern is mainly related to selection, sweepstakes reproductive success73, collective dispersal74, and temporal shifts in local population dynamics75. However, understanding the drivers determining this genetic pattern is challenging75. For example, local hydrodynamic conditions affecting both larval dispersal and the stochastic delivery of larvae from different sources could determine a high variability in reproductive success or mortality related to pre- and post-settlement processes72. The stochasticity of the early life history dynamics76 is related to the intra- and inter-specific interaction, the reproductive mode and time, the timing of larval release and larval behaviour. Laboratory experiments on life cycles and field manipulative experiments have to be implemented to better understand the primary processes acting at different temporal and spatial scales. These studies are extremely difficult to carry out due to the difficulties in manipulating small larvae and individuals in the field. However, this review, as well as other recent papers76, emphasize the need to evaluate the effective population size and estimate genetic drift in the field. For example, studies that compare the genetic makeup of dispersing larvae with the post-dispersal stages can help to clarify the role of genetic drift .In our study, many species (10 of 27) present a chaotic genetic patchiness  that act at a local scale, may be supported by nearby healthy populations or by local protection programmes. However, these actions are helpless for impacts due to climatic changes  that act at global scales and affecting all populations.Our synthesis shows that the sessile and low-mobility species inhabiting the coralligenous habitats have high genetic structuring. Occurrence of structured breeding units and genetically differentiated populations at the scale of kilometres or less suggest that conservation strategies have to consider smaller scales than previously thought37, Micheli et al.79, van der Heyden et al.26). Characterisation of the genetic structure of species inhabiting fragile Mediterranean coralligenous reefs is also needed to fill the gaps in genetic knowledge on some of the most important bio-constructors .Major efforts should be dedicated to understanding local-scale ecological processes, to developing seascape genetic approaches at the local scale, to enhancing restoration plans and to implementing the creation of Sites of Community Importance  by establishing a network of scientists and extending the studies to the eastern and southern Mediterranean Sea.We believe that comparative phylogeographic and population genetic studies, along with studies on demography and reproductive features, are fundamental to understanding the functioning of coralligenous habitats. To successfully implement these approaches, the scientific community should prioritise sampling design protocolsPromoting public awareness and implementing effective communication based on coralligenous flag species with high aesthetic and naturalistic values could help stimulate interest for the conservation of these complex, yet unique, Mediterranean habitats.FST as response variables to assess if population genetic structure is affected by genetic markers, pelagic larval duration, phylum and geographical distance. FST is a measure of population differentiation ranging between one, indicating fixation of different alleles in each population , and zero, indicating the absence of differentiation . Despite controversy over the use of Wright’s fixation index (FST81) as a measure of relative differentiation34, FST is commonly used in population genetics and is therefore the most viable parameter to include in a multi-study analysis . We observed a strong relationship between global and mean pairwise values in the studies where these values were both present . Therefore, in those studies where pairwise FST were the only available values, we estimated the global FST for the species using the following linear fit: global FST = 0.9733 × (mean pairwise FST) + 0.0052. For each study we extracted pairwise FST values to compare populations occurring within geographic areas delimited by recognized oceanographic or biogeographic barriers (see31). Maximum geographical distances included in the analysis range from less than 1 km in study carried out at a very fine scale, to about 1000 km in the Northwestern Mediterranean basin  for articles addressing the genetic variation and population structure of marine benthic invertebrates with low (negligible) adult mobility living mainly (but not exclusively) in the Mediterranean coralligenous reefs. The combination of keywords used in our queries is provided in the Supplementary methods. We examined the title and abstract of each resulting article and retained only those articles deemed eligible for the scopes of our research ; Fig. FST, we calculated the maximum distance between localities from the coordinates provided in each study. We extracted data from publication plots, maps, and tables or using the software Plot Digitizer 2.6.4 when information was graphical . For studies providing geographic coordinates of sampling locations, but not geographic distances, we calculated the least-cost distance between sampling points using Google Earth.In addition to FST values derived from mitochondrial data were converted using the equation provided by Baco et al.46 to accurately compare haploid mitochondrial values with data from diploid nuclear markers82.All FST (transformed using Rousset39) and the natural logarithm of the geographic distance between locations in each individual observation, we calculated the IBD slope and its associated standard error . In species showing a significant IBD, we estimated the dispersal distance applying the method of Kinlan and Gaines82. An alternative for the analyses was the Rousset39 method, however, both methods provide similar results (a strong log-linear relationship46), and the Kinlan and Gaines82 method was already used in other metanalysis46. We used a power function model -1.0001) following Chust et al.29. When a species was analysed with more than one method and/or using both mitochondrial markers and microsatellites, we considered the study carried out at the smallest spatial scale and using microsatellite loci. For Corallium rubrum and Crambe crambe we used the already-published values of dispersal distance calculated using an “individual based” sampling by Ledoux et al.54 and Calderon et al.55, respectively.To estimate the dispersal distance at the regional scale for each species, we re-calculated the isolation-by-distance (IBD) ant tested the pattern  between the new matrices of pairwise FST and IBD, as found directly in each paper, as follows68:FST was significant (P < 0.05) but IBD was non-significant ;Chaotic structure, defined as genetic differentiation of samples when global Isolation by distance (IBD) when the Mantel correlation was significant (P < 0.05);FST and the Mantel correlation were not significant (P > 0.05).No genetic structure: when both global We undertook a qualitative review of all the studies listed in the full dataset (Supplementary Table 35), or by the phylum. In a meta-analysis, the results from different studies are aggregated and compared by identifying a suitable ‘Effect Size’ , and importantly, the relative relevance of individual observations is weighted using the error associated with the ES84. Our ES was defined as the IBD slope, describing the relationship between the FST and the geographic distance, while we used the standard error of the slope to calculate weights. We performed meta-analyses only on a subset of the full dataset (hereafter “META-set”), for which we were able to obtain the IBD slope and its associated error from at least four pairwise comparisons. The META-set consisted of 31 observations (19 microsatellites and 12 mtDNA). Models were fitted using random-effect models with a maximum likelihood estimator . All the analyses were then repeated only on META-set observations with a long PLD , excluding observation with no or short  PLD. The significance of factors was tested by log-likelihood ratio testing between the model of interest and the reduced model . Models were then refitted using a DerSimonian-Laird estimator84 to produce a forest plot.We investigated the population genetic structure observed for several species of the coralligenous reef as a function of different factors by using both meta-analytical and linear regression approaches. Statistical analyses were restricted to mtDNA sequences and microsatellite observations since the information was insufficient for other marker types. We first performed meta-analyses to investigate whether the genetic structure of a population was affected by the genetic marker used, by the PLD .ANCOVA analyses were conducted on a subset of the full dataset that included only observations for which global FST, “Marker”, “Maximum PLD”, and maximum geographical distance (“Maximum Distance”). To meet the ANCOVA assumptions, the response variable “global FST” was log transformed, and models were fitted using GLS  with a constant variance function structure using “Marker” as a grouping factor. Assumptions were checked by graphically inspecting the residuals.We used ANCOVA to investigate the relationship between global 83 (see Supplementary methods for the R packages used).Analyses were repeated for long PLD observation only in ANCO-set , limiting the number of variables in the models to a maximum of three Statistical analyses were conducted in the R programming languageSupplementary dataSupplementary Table S1


The origin of weedy rice is supposed to be more likely from cultivated rice rather than from wild rice in mitochondrial genome level.Mitochondrial genome variations have been detected despite the overall conservation of this gene content, which has been valuable for plant population genetics and evolutionary studies. Here, we describe mitochondrial variation architecture and our performance of a phylogenetic dissection of Korean landrace and weedy rice. A total of 4,717 variations across the mitochondrial genome were identified adjunct with 10 wild rice. Genetic diversity assessment revealed that wild rice has higher nucleotide diversity than landrace and/or weedy, and landrace rice has higher diversity than weedy rice. Genetic distance was suggestive of a high level of breeding between landrace and weedy rice, and the landrace showing a closer association with wild rice than weedy rice. Population structure and principal component analyses showed no obvious difference in the genetic backgrounds of landrace and weedy rice in mitochondrial genome level. Phylogenetic, population split, and haplotype network evaluations were suggestive of independent origins of the  Plant mt genomes vary greatly in size, from ~200 kb to 2 Mb mostly, and are substantially larger than mt genomes of other eukaryotes  is generally thought to have been domesticated from O. rufipogon several thousands of years ago181920O. sativa ssp. indica and japonica, were derived from a single ancestor or were domesticated independently at different locations1019222324O. sativa L., resulting in about 120,000 different accessionsAsian cultivated rice (Oryza sativa f. spontanea Rosh.), harbors characteristics of undomesticated Oryza species, including seed dispersal mechanisms and seed dormancy. It also possesses traits of domesticated rice, such as rapid growth, and resembles domesticated rice during the seedling stage, which promotes its invasiveness in the agroecosystem2628indica-japonicaindica or japonica varieties2733Oryza genus, gaining an understanding of the genetic background of problematic weedy species by examining the underlying genomic information is important.Weedy rice  was chosen as the reference for mapping variations in the collection. Mt genome variations in the germplasm were mined and subjected to comparative analyses among different groups . The diversity and population structure of these accessions were also examined at the mt genome level. Phylogenetic analyses were performed using the maximum likelihood (ML) and Bayesian inference (BI) methods, together with population split and haplotype network analyses, which could reveal phylogenetic relationships among landrace and weedy rice, and possibly the origin of weedy rice. This report provides a case study for the rice mt genome developed from whole genome resequencing, and the data generated here could be applied to further analyses of rice mt evolution and genetics.In the present study, a collection of 60 Korean landrace and weedy rice, and 10 wild rice varieties, including A number of variations in the rice mt genome were observed in the current study. In total, 4,717 variations, including 4,507 SNPs and 210 indels, were identified across the mt genomes of landrace and weedy rice accessions, along with wild rice. However, after removing missing values and heterozygotes, only 264 high-quality (HQ) variations remained . Excludipi) of the mt genome in the whole collection and different subgroups  was calculated  among the different groups was also calculated, which revealed a very high level of breeding  between landrace and weedy rice, and a closer association between landrace rice and wild rice (0.1109) than weedy rice and wild rice (0.1228) , illustrating that the landrace_japonica was much closer with O. rufipogon than weedy_japonica. However, the breeding level between weedy_japonica and landrace_japonica was much higher than between weedy_indica and landrace_indica. In addition, overall Fst values between O. rufipogon and japonica type were lower than those between O. nivara and the indica type in landrace and weedy rice.The nucleotide diversity  . When wejaponica , the weejaponica, indica, and wild types fell into three subpopulations . However, the landrace and weedy indica types were mixed, as were the landrace and weedy japonica types. This admixture was also observed in the population structure estimation with increasing K (number of populations) values from 2 to 6  of the population with and without wild rice were also performed to compare the grouping of the different groups, which revealed that the indica, japonica, and wild types could be grouped . Generally, different mt genome variations were detected among different groups and the wild rice is more polymorphic than indica and japonica  in Korea, since there’s no wild rice in Korean farmers’ field in most cases. Another interesting event we found in the population structure was that most landrace or weedy rice only shared the background within landrace_japonica or landrace_indica, which means the indica or japonica of weedy rice may from independent cultivated rice . We then conclude that Korean weedy rice not from the wild rice but from the cultivated rice itself.Population structure analysis suggested that landrace and weedy rice in Korea have mixed genetic backgrounds and cannot be separated in mt genome level . Not onlcessions ,d. It suindica, and japonica types) were well illustrated and separated. However, consistent with previous results, landrace and weedy rice could not be clearly seperated both in indica and japonica subgroups. This supported the complicated genetic background of landrace and weedy rice in mt genome level. As we know, the genome transfer is easily happened between mt genome and nuclear genome1436indica, japonica and wild rice exists and may infers the different transfer patterns36http://rice.plantbiology.msu.edu/annotation_pseudo_organellar.shtml) were isolated and applied for further evaluation. In addition, the same reference information for the SNPs mining and non-transfer regions characterization were employed, which would also reduce the bias. Population structure and phylogenetic analysis revealed that the results were similar by using all dataset and non-transfer dataset . The similar result by using whole SNP set and non-transfer SNPs indicated that the transfer pattern has limited impact in current study. This also suggested that the variations based method for phylogenetic or evolution studies is feasible, and using all variations in mt genome is also suit for such analysis with high decent accuracy.Phylogenetic analyses using two different methods with different nucleotide substitution models revealed a same phylogenetic structure of all accessions, although the overall tree topology structure was very different . Three g dataset . Three sindica type (haplotype 1) and the japonica type (haplotype 2), respectively. Haplotype 1 harbored 15 accessions, and haplotype 2 covered 46 japonica accessions  and the hybrid rice probably has been involved in the evolution of some weedy rice accessionsO. rufipogon is still presentCurrent report suggests that mt genome–based analyses can be applied in genetic diversity studies, as well as in population genetics and phylogenetic analyses. Outcomes from the rice mt genomes reveal and support the independent origin of Oryza rufipogon and Oryza nivara) from the resequencing set developed by Xu, et al.http://www.ebi.ac.uk/ena) under accession numbers SRA023116.A core set containing 137 rice accessions with diverse types  previously generated from worldwide varieties collected from the National Genebank of the Rural Development Administration  using the program PowerCore41For the 60 landrace and weedy rice accessions, young leaves from a single plant were sampled and stored at –80 °C prior to genomic DNA extraction using the DNeasy Plant Mini Kit (Qiagen). Qualified DNA was used for whole-genome resequencing of the collected rice varieties, with an average coverage of approximately 9× on the Illumina HiSeq 2000 Sequencing Systems Platform (Illumina Inc.).http://picard.sourceforge.net/). Final realignment and identification of variation were performed using GATK software v3Resequencing raw data of all the accessions were trimmed using Sickle v1.2π), population genetic distance (Fst), and Tajima’s D in the whole collection and different groups were conducted using VCFtoolsStatistics evaluation of mt genome nucleotide diversity , which allow for estimation of founding allele frequencies and individual admixture using maximum likelihood estimatesK value range from 2 to 6, we could investigate the individual ancestry events in different clusters. A neighbor-join phylogenetic tree of the landrace, weedy and wild rice was constructed using PHYLIP package  with 1000 replicates. Principal component analysis (PCA) was conducted using TASSEL 5To estimate individual admixture assuming different numbers of clusters, the population structure was investigated using the program http://tree.bio.ed.ac.uk/software/figtree/). The consensus tree of the bootstrap in the ML method was integrated using Phylip software. Tanglegram for two trees was implemented in DendroscopeML and BI methods were applied to construct phylogenetic trees for the current collection. Briefly, appropriate nucleotide substitution models were assessed using jModeltest 2.1.751http://popart.otago.ac.nz) according to the groups in an Integer Neighbor-Joining method.A statistical model for estimating the historical relationships among populations, using a graph representation that allows both population splits and migration events was conducted using TreeMix v1.12How to cite this article: Tong, W. et al. Genetic variation architecture of mitochondrial genome reveals the differentiation in Korean landrace and weedy rice. Sci. Rep.7, 43327; doi: 10.1038/srep43327 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Genetic population analysis was conducted by analyzing 22 common SSR markers, determining first the unique genotypes, and internally assessing the population’s structure, showing the existence of two distinct Sativa and Sylvestris populations, and a third mixed one. Likewise, the relationship between the Israeli grapevine population and grapevine populations in Europe and parts of Asia was investigated, showing that the Israeli Sativa and Sylvestris populations cluster closely together, suggesting a common genetic source. Lastly, the enological characteristics of selected Sativa and Sylvestris genotypes are presented, demonstrating their potential for quality wine production. This research significantly contributes toward the re-establishment of indigenous and traditional local grapevine varieties into the modern international wine industry.The importance and extent of wine consumption in all life aspects at the Holy Land is well documented. The Muslim influence in this region led to the abandonment of winemaking practices, and possible loss of indigenous wine varieties. Here we present a country wide collection of the local grapevine population including wild and cultivated forms, and its characterization by genetic, ampelographic and enological methods. The ampelographic analysis shows clear differences between Sativa and Sylvestris groups in flower, leaf and cluster parameters, and that most Sativa belong to  Vitis vinifera ssp. sativa) is one of the classic fruits of the Old World, providing fresh berries, dried raisins, and juice for wine fermentationV. vinifera come from Early Bronze Age sites in Israel, such as Jericho5th century C.E., Muslim occupation of the region initiated a long period of gradual suppression of wine consumption and production, which is believed to have accelerated with the Mamluk occupation in the 13th century enforcing its strict religious law. This might have led to eventual abandonment of wine grape varieties by local farmers, while maintaining the practice of table grape viticultureth century was based solely on international cultivars.The domesticated grapevine  and V. vinifera spp. sylvestris (hereafter Sylvestris) were collected. Indeed, Sylvestris is considered to be the putative ancestor of the cultivated form and represents the only endemic taxon of the Vitaceae in Europe and the MaghrebIn 2011, we began to conduct an unprecedented nationwide survey to collect and characterize Israeli grapevine germplasmVitis spp.) which were collected in Israel during the years 2011–2015 were analyzed in this work. The collected material consisted of 279 Sativa, including 34 known autochthonous traditional varieties, some of which were previously describedA total of 372 grape accessions (www.eu-vitis.de) and in literature revealed that only 11 out of 61 Sativa genotypes were previously described11All accessions were first characterized at 10 SSR loci  in order to identify redundant genotypes. A total of 126 different unique genetic profiles were found, of which 61 were Sativa and 65 were within the Sylvestris population. The genotypes of Sativa included 42 new feral Sativa unknown to local growers. Out of the 34 known autochthonous traditional varieties analyzed, 19 unique genotypes were found, setting 15 varieties as synonyms. The last mentioned cultivars are all preserved in the Sataf and Neve-Yaar collections, as previously described by our groupproles orientalis, 5 in the proles pontica and 2 in proles occidentalis dentalis .Using the OIV descriptors data, a neighbor-joining dendrogram based on simple matching dissimilarity matrix was calculated . The denet al.To further characterize the final panel of 126 unique genotypes, 12 additional SSR loci were genotyped. We used the data derived from the full set of commonly used 22 SSR lociA neighbor-joining unweighted tree was built based on the SSR profiles . A generVitis germplasm and other important Vitis populations in Eurasia, we performed an additional cluster analysis including homologous SSR profiles of 278 Eurasian grapevines , representing the proles occidentalis, and table and wine Muscat grapes (Vv3) reflecting the proles orientalis sub pr. caspica. Subpopulation Vv2 was composed of both table grape varieties  and Spanish wine grapes. In addition, we included 10 diverse cultivars from the Sistan area of Iran and a set of 119 wild and cultivated genotypes originating from Georgia and Middle Asia (MA), already investigated by Marrano et al.To gain a broader understanding of the genetic relationship between the Israeli apevines . These aFollowing the determination of unique populations, vines containing a sufficient amount of grapes were harvested for micro-vinification. Wine characteristics were analyzed to help in determining the potential of quality wine making of each variety. Here we show the analysis of some red and white varieties, micro-vinificated during 2014 harvest . In the Vitis vinifera in Israel generated a large population of diverse genotypes. The Sativa population consists of two sub groups, the first of which is composed by traditional Sativa varieties, mainly considered as table grapes. Among these, there are historical indications of use of the Hamdani and Jandali varieties for winemaking in Jerusalem during the 2nd century C.E.Our broad survey of et al.222425The investigated grapevine collection included also Sylvestris accessions, the distribution of which is restricted to the Northern part of Israel. The reason for the restriction of the Sylvestris population to the above described area is unclear. Biagini Ampelographic analysis showed distinct differences between Sativa and Sylvestris populations, mostly in flower, leaf and cluster properties. These distinct differences between the Sativa and Sylvestris populations, shown by the Neighbor-joining dendrogram assure us of further classification of each individual to its correct grouping during genetic analysis.proleses was conducted following Negrul’s taxonomical system which has been independently validated by several other authors272829proles orientalis. Indeed, with accordance to our phenotypic observations, the wide genetic population analysis shows that 7 of the Israeli Sativa varieties cluster within the Vv3 group, which reflects proles orientalis subproles caspica. Some other few accessions were found to belong to the proles pontica and proles occidentalis. This polymorphism found in the Israeli population of Sativa can suggest that the initial orientalis-based population gained representatives of other proleses, as discussed below.Classification of the accessions to The neighbor-joining genetic analysis of the Israeli population based on SSR markers shows a division to a main Sativa group, a main Sylvestris and a third of mixed origin. We cannot find a clear geographical explanation to the existence of the mixed group. Indeed, 3 of the 5 Sylvestris in this group come from the Banias creek in the north, were we found both Sativa and Sylvestris growing alongside each other, but the other two Sylvestris come from the northern part of Lake Kinert, were no Sativa exist, and the Sativa accessions in this mixed group are mostly from southern regions where no Sylvestris do exist. Thus, it is not likely that the genetic relatedness is caused by natural crossings of Sylvestris with local Sativa individuals, and another explanation suggesting a common genetic source might be in favor. The above-mentioned division is also apparent from the analysis of the most likely number of clusters (K), which also indicates the existence of a Sylvestris group including 11 Sativa.It is worth noting that these Sativa and Sylvestris populations, beside a similar high level of genetic diversity as quantified by the expected heterozygosity, also have similar average of observed heterozygosity. These are positive indicators for the status of the wild group, as reduction in observed heterozygosity has been reported in wild grapevines analyzed in Spain, Portugal, France and ItalyThe genetic analysis of the Israeli collection against the European and Asian datasets shows that the Israeli Sylvestris and Sativa populations are genetically proximal. This evidence, as well as the relatedness found above in the internal genetic analysis, might suggest a local domestication in the Holy Land. This claim is supportive of the multi-local selection and domestication theory as previously proposed for the Iberian Peninsula2733proles characterizations above. This may suggest a flow of varieties originating in the Holy Land – a bridge between Africa, Asia and Europe which was conquered intensively by various empires. Indeed, the combined Israeli collection clustered within a large group including the other Vv2 genotypes, MA Sativa and Sylvestris populations and the Iranian varieties. Proximity and easy land access from these regions to the Levant may have favored the spread of plant material in both directions.In addition, the genetic analysis showed that the main Israeli Sativa cluster also includes several accessions from Middle Asia, as also noted in the Lastly, grapes fermented from some of the Sativa varieties collected in their original site show winemaking potential. The color and polyphenol characteristics of Ein-Misla, Sorek and Nitzan unique native varieties are similar or better than those of a local Cabernet Sauvignon wine used as reference. This initial potential would be further pursued and verified in the near future towards integration of these varieties into the wine industry. As mentioned above, the wines produced from some Sylvestris accessions gave rise to wines with normal alcohol and acid levels, and high polyphenolic content. After due selection, this can lead to the integration of Israeli Sylvestris cultivars into the general wine industry, bringing with them possible stress resistance, quality and health traits.Vitis spp.) were collected across Israel during the years 2011–2015. For DNA extraction, shoot tips were excised from each accession on site, usually during the spring, and kept on ice until storage at −80 °C was available.A total of 372 accessions of grapevine . Accessions were characterized morphologically according to the OIV standards adopted by the “COST Action GrapeNet FA1003” (2010–2014)Frozen leaves (70 mg) were maintained at −80 °C and weighed in 1.5 ml microtubes. The tissue was then ground with a pestle diluted with 700 μl of CTAB buffer , 0.4 M LiCl, 1% polyvinylpyrrolidone (PVP), cetyltrimethyl ammonium bromide (CTAB), 1% β-mercaptoethanol)W Size Standard (Applied Biosystems). DNA fragments were denatured and size-fractionated using capillary electrophoresis on an ABI 3500 Genetic Analyzer (Applied Biosystems). GeneMapper 5 (Applied Biosystems) was then used for allele size estimation and chromatograms were read by two independent raters. Determinations of unique accessions were performed using the “Excel Microsatellite Toolkit”34www.eu-vitis.de).Twenty two SSR markers previously applied for grape germplasm characterization were chosenet al.The final dataset of non-redundant genotypes at 22 SSR loci was used to estimate the main diversity statistics, as well as most likely subdivision (K) by using STRUCTURE 2.1 softwareAs grapes were harvested from wild or feral vines, the amount of grapes processed for winemaking was between 5–50 kg, depending on the vines prosperity.Saccharomyces cerevisiae strain BDX  per 100 kg grapes was used for vinification of red varieties, and Lalvine QA23  in the same dosage was used for whites. The cap punching operations were carried out three times a day during maceration of red varieties, which was conducted in a temperature controlled room at 25 °C. Eight days after commencing alcoholic fermentation of red varieties, wine was obtained by pressing the must using a hydraulic press machine, and kept at the same temperature until density dropped under 0.994. Immediately after press for the whites, and following completion of malolactic fermentation for the reds, sulfur dioxide was added to the wine at 60 mg/l and the wine was syphoned a week later and stored at 15 °C until used for further analyses.Whole bunches were harvested at appropriate sugar levels for winemaking, destemmed and crushed. White grapes were immediately pressed by a hydraulic press and juice cooled to 8 °C, incubated overnight, then decanted and kept at 15 °C for the fermentation period. 20 gr of the commercial 520nm + A420nm). Color hue was defined as the ratio intensities of yellow to red pigments (A420nm/A520nm)Ethanol in wine samples was determined using a Super Dee digital distillator and Super Alcomat electronic hydrostatic balance . Titratable acidity (TA) and pH were measured using a Hana HI 2211 pH meter . TA is expressed as tartaric acid in g/l and was determined by diluting the 10 ml of wine with 10 ml of distilled water and by subsequent titration with 0.1 M NaOH to pH 8.2. Color characteristics of wines were obtained by spectrophotometer . Color density was calculated as total of absorbance of red and yellow pigments  in the Holy Land, towards the renewal of ancient winemaking practices. Sci. Rep.7, 44463; doi: 10.1038/srep44463 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Apis cerana japonica, in Japan. This subspecies has little genetic variation in terms of its mitochondrial DNA sequences, and genetic variations at nuclear loci are as yet unknown. We estimated the genetic structure and environmental determinants of local genetic diversity in nuclear microsatellite genotypes of fathers and mothers, inferred from workers collected at 139 sites. The genotypes of fathers and mothers showed weak isolation by distance and negligible genetic structure. The local genetic diversity was high in central Japan, decreasing toward the peripheries, and depended on the climate and land use characteristics of the sites. The local genetic diversity decreased as the annual precipitation increased, and increased as the proportion of urban and paddy field areas increased. Positive effects of natural forest area, which have also been observed in terms of forager abundance in farms, were not detected with respect to the local genetic diversity. The findings suggest that A. cerana japonica forms a single population connected by gene flow in its main distributional range, and that climate and landscape properties potentially affect its local genetic diversity.Declines in honeybee populations have been a recent concern. Although causes of the declines remain unclear, environmental factors may be responsible. We focused on the potential environmental determinants of local populations of wild honeybees,  Population declines in both wild and managed honeybee populations are of concern in Europe and the US –3, althoApis mellifera Linnaeus in Brassica fields was positively associated with the area of woody vegetation around the fields [Apis cerana Fabricius, visitation frequency to buckwheat flowers in farms was positively correlated with the area of forest cover within 3-km radii of the farms [Local abundance of honeybees depends on environmental factors. A meta-analysis was performed to determine the effects of human activities, such as grazing, logging, and agriculture, on bee abundance in accordance with habitat loss . This ane fields . In Apishe farms . When nahe farms . These fA. mellifera colonies requires great effort because their nests, in hollow trees or earth cavities, are difficult to detect [Managed honeybees are not amenable to evaluations of the effects of environmental factors on their populations, because apicultural management affects their abundance. Although wild honeybee populations may depend on their surrounding environment, it is difficult to measure population sizes in the field. Surveying wild o detect . A geneto detect . Workerso detect . ComposiA. cerana distributed across southern, southeastern, and eastern Asia [A. mellifera, and both are cavity-nesting species [Apis cerana japonica Radoszkowski, distributed in Japan, is one of four subspecies of A. cerana [A. mellifera and A. cerana japonica in a forest habitat in Japan [A macro-ecological approach to studying wild honeybees is effective for revealing the effects of environmental factors on their population size and genetic diversity. We focused on ern Asia . This sp species . Apis ce. cerana . This su. cerana . Pollen in Japan . Thus, nA. cerana japonica is known to be relatively homogeneous in its main distributional range. Thus, local genetic diversity can be compared among various locations without the confounder of geographic patterns in genetic structure. At a mitochondrial locus, a single allele is predominant in A. cerana japonica throughout Japan, although a few different alleles have been found in the northern region of the island of Honshu [Apis cerana cerana, is distributed. The findings regarding the mitochondrial locus in A. cerana japonica suggest little genetic variation, a close relationship with Korean and Russian A. cerana cerana, and the presence of unique alleles in peripheral Japan. Genetic variations at nuclear loci have not yet been determined, although highly polymorphic nuclear loci, such as microsatellites or simple sequence repeats (SSRs), are available [The genetic structure of f Honshu , and in f Honshu . The pref Honshu ,16, in wvailable . SSRs arA. cerana japonica genotypes at many sites in its main distributional range, at which we also measured geographical, topographical, climatic, and land use properties. First, we inferred multilocus SSR genotypes of siring drones (fathers) and queens (mothers) from workers (offspring) collected at the sites, to estimate the genetic structure of A. cerana japonica. Next, to evaluate local genetic diversity, we measured the diversity of individuals and the heterozygosity of alleles, in the inferred fathers and mothers from each site. Finally, we estimated the effects of environmental factors on the diversity and heterozygosity to elucidate the potential environmental determinants of local genetic diversity in A. cerana japonica.To reveal the effects of environmental properties on local genetic diversity, we investigated A. cerana japonica workers from 139 sites on the Japanese Archipelago, including the islands of Honshu, Shikoku, Kyushu, Oki, and Iki, located between 31.398–41.266° N, 129.724–141.448° E, and 0–967 m above mean sea level , and 0.25 μL template DNA solution using a TaKaRa TP600/TP650 thermal cycler . A PCR process consisted of an initial 9 min at 95°C, followed by 35 cycles of 30 s at 94°C, 30 s at a primer-specific annealing temperature, 30 s at 72°C, and a final 10 min at 72°C. We applied the economic method to Ac2 and Ac3 using the universal M13 (–21) primer labeled with fluorescent dye [We examined 17 codominant loci of nuclear SSRs, which were amplified using 12 pairs of primers designed for nd Ap306 . We perfcent dye . Sizes oWe inferred genotypes of fathers and mothers from the worker genotypes using COLONY software ver. 2.1  for haplHE) in the haploid population and estimated the observed heterozygosity , HE, and the fixation index (FIS = (HE − HO)/ HE) in the diploid population at each locus (F/(1 − F)).To sample reproductive individuals from the main distributional range, we selected the two most frequent haploid genotypes of fathers, and the most frequent diploid genotype of mothers, which were inferred from workers collected at each of the 139 sites. We estimated population genetic parameters for 278 haploid genotypes and 139 diploid genotypes, representing the fathers and mothers, respectively, using GenePop software ver. 4.2 . First, ch locus . We alsoHS) and genetic differentiation (FST = (HT − HS)/ HT) from the base population with the heterozygosity (HT). We drew bar plots of the inferred ancestry of the clusters in the haploids and diploids.We performed Bayesian clustering of genotypes in each of the haploid and diploid populations using STRUCTURE software ver. 2.3.1  with 20 o°E) as the geographical property. Because local genetic diversity was high in central Japan and decreased in peripheral regions (see h = |o − ∑o/139|). For topographical properties, we obtained the altitude (a m) and the angle and direction of the slope. The mean slope angle (g°) and direction of the steepest slope  were calculated from a digital elevation model with 10-m grids within a 250-m mesh [s = –cos(πd/180)) with a trigonometric function. For climatic properties, we obtained the annual precipitation (p mm), annual mean of the daily mean temperature (t°C), annual maximum snow depth (w cm), and annual mean daily cumulative solar radiation (l MJm-2) by interpolating 1-km mesh data from the mean values of the past 30 years [2) of paddy field (y), farm (f), urban area (u), natural forest (n), artificial forest (c), and grassland (r) within 1, 2, 3, 4, and 5-km radii of the sites based on 1:50,000 digital vegetation maps [v = 1 − ∑e2), from the proportion (0 ≤ e ≤ 1) of the above six land use categories and three additional categories  to assess the complexity of land use.We recorded the environmental characteristics, such as geography, topography, climate, and land use, at each site. We also recorded the latitudes (°N) and longitudes (°E) of the sites as their geographical properties. Since the latitudes tended to be correlated with climatic properties, we selected longitude  to discriminate confounding effects of seasonality. In Japan, foraging and reproduction in honeybees appear to be most prevalent in June and September, with less activity occurring in July and August due to extremely high temperatures and shortages of floral resources [j = cos(π(m − 6)/6)) and latter (b = cos(π(m − 9)/6)) values with trigonometric functions.In addition to the properties of the sites, we considered collection month (esources . In wintdf1) and identical (df2) fathers. The response variables for the heterozygosity of alleles of the fathers were the number of pairs of different (hf1) and identical (hf2) alleles of the fathers. The response variables for the diversity of the mothers of workers foraging on a flower patch were the number of pairs of workers with different (dm1) and identical (dm2) mothers. The response variables for the heterozygosity of alleles of the mothers were the number of pairs of different (hm1) and identical (hm2) alleles of the mothers. For the response variables of the mothers, 76 sites in which workers were collected at nests were removed from the data because there was a single mother at each of these sites.We evaluated local genetic diversity as a response variable based on the diversity of parents and the heterozygosity of alleles of the parents at each of the 139 sites. We defined diversity as the proportion by which two randomly sampled individuals differed, and defined the heterozygosity as the proportion by which two randomly sampled alleles differed. The response variables for the diversity of fathers that mated with a single queen were the number of pairs of workers with different  to each set of response variables, the diversity and heterozygosity of fathers  and  and those of mothers  and , using glmmML ) in the glmmML package of the R software ver. 3.1.3 [We fitted a linear model of explanatory variables,  and vij , for sitr. 3.1.3 . The expWe fitted the models with possible combinations of explanatory variables, at each of the five spatial scales, to each set of response variables. Then, we selected a model with the lowest Akaike’s information criterion (AIC) value, using dredge (rank = "AIC") in the MuMIn package in R. When there were too many explanatory variables to finish the model selection within 1 hour, we removed some explanatory variables, which had small effects in the full model, from the selected models. Among the selected models at the five spatial scales, we further selected a model with the lowest AIC value. In the finally selected model, we estimated the coefficient of the fixed effects and the standard deviation (SD) of the random effects. We obtained predictions from the explanatory variables using the estimated effects, particularly those with consistent effects among the four response variables.We determined the diploid genotypes of 2,738 workers from 139 sites. At the 76 sites, from which we collected workers at nests, we inferred 717 father genotypes from 1,508 worker genotypes. We also inferred, at 63 sites, from which we collected workers at flower patches, 650 father genotypes from 1,230 worker genotypes. We inferred 254 mother genotypes for each of the 63 sites, from which we collected workers at flower patches. We also inferred 76 mother genotypes, a single mother for each of the 76 sites, from which we collected workers at nests.P = 0.020). In a population of 139 diploids representing the inferred mothers, we found no significant linkage disequilibrium (P ≥ 0.190). The expected heterozygosity (HE) was 0.530 in the father population and 0.541 in the mother population (HO) was 0.540, and the fixation index (FIS) was 0.003, in the mother population (P < 0.001). We found significant isolation by distance (P < 0.001) and positive regression slopes (B) from the log-transformed spatial distance (km) to the genetic distance (F/(1 − F)) in the father (B = 0.0253) and mother (B = 0.0356) populations.In a population of 278 haploids representing the inferred fathers, we found significant linkage disequilibrium only between Ac30 and Ac35  than cluster 2 , three topographic , four climatic , and seven land use  properties, from site i at spatial scale j , as well as two properties of collection month  and identical (4 ≤ df2 ≤ 59) fathers that mated with a single mother, and the number of pairs of different (0 ≤ hf1 ≤ 153) and identical (8 ≤ hf2 ≤ 190) alleles of fathers, for the 139 sites. We also counted the number of pairs of different (0 ≤ dm1 ≤ 165) and identical (11 ≤ dm2 ≤ 190) mothers of workers foraging on a flower patch, and the number of pairs of different (0 ≤ hm1 ≤ 49) and identical (0 ≤ hm2 ≤ 66) alleles of mothers at each locus in the 63 sites. Based on these variables, we obtained mean data, across the six loci, on the diversity of fathers (0.272 ≤ df1/(df1 + df2) ≤ 0.964) and mothers (0.000 ≤ dm1/(dm1 + dm2) ≤ 0.869), and on the heterozygosity of alleles of fathers (0.103 ≤ hf1/(hf1 + hf2) ≤ 0.592) and mothers (0.267 ≤ hm1/(hm1 + hm2) ≤ 0.643).We counted the number of pairs of different (3 ≤ h), annual precipitation (p), annual mean of the daily mean temperature (t), annual mean of daily cumulative solar radiation (l), two indices of collection month (j and b), and the proportion of urban area (u) within a 5-km radius , p, and the area of natural forest (n) within a 2-km radius  within a 1-km radius , mean angle of slope (g), p, t, annual maximum snow depth (w), j, and y and u within a 1-km radius  increased at the 1-km radius spatial scale (u) increased  is known to be positive in substructured populations due to the Wahlund effect [FIS = 0.003) in the mother population indicates weak substructure within that population  is consistent with the observed genetic structure of samples representing individual sites . To accurately estimate the effective population size and colony density, collection of drones at DCAs, or by using pheromone traps , are use valleys .A. mellifera populations in urban environments surrounded by natural desert areas, because rainfall was likely to increase floral resources in such a dry climate [Among the climatic properties, annual precipitation has negative effects on local genetic diversity . Rainfal climate .Local genetic diversity in the summer was higher than in the winter . This paA. cerana japonica forms a single population connected by gene flow across the Japanese main islands. Thus, the A. cerana japonica population can be treated as a single management unit.Population declines in honeybees have been a recent concern in Europe and the US, and conservation and management of wild honeybees is necessary ,3. WhileOur study provides no evidence of positive effects of natural forests on local genetic diversity, even though forager abundance in farms is known to increase with increasing area of surrounding natural forests –8. In coS1 Table(TXT)Click here for additional data file.S2 Table(TXT)Click here for additional data file.


Gasterosteus aculeatus). Nevertheless, cases also exist where marine-freshwater divergence is diffuse despite seemingly similar environmental settings. In order to assess what characterizes these highly different outcomes, we focused on the latter kind of system in the Odder River, Denmark. Here, a previous study based on RAD (Restriction site Associated DNA) sequencing found non-significant genome-wide differentiation between marine and freshwater sticklebacks. In the present study, we analyzed samples on a finer geographical scale. We assessed if the system should be regarded as panmictic, or if fine-scale genetic structure and local selection was present but dominated by strong migration. We also asked if specific population components, that is the two sexes and different lateral plate morphs, contributed disproportionally more to dispersal.Distinct hybrid zones and phenotypic and genomic divergence is often observed between marine and freshwater threespine sticklebacks  contains supplementary material, which is available to authorized users. Selection is a key force enabling the adaptation of populations to local environments , 2. NeveThe geographical scale over which dispersal occurs within a life-time is an important factor for understanding interactions between gene flow and selection. Furthermore, different groups of individuals within a population may contribute disproportionally to dispersal. Sex-biased dispersal is often observed in vertebrates, with male- or female biased dispersal resulting from the specific mating systems and/or extent of resource competition , 12. HowGasterosteus aculeatus) is an excellent model for studying clines and hybrid zones, as it shows pronounced adaptation to different environments that can be identified both at phenotypic and genomic levels  using STRUCTURE HARVESTER [Genetic population structure was further assessed using STRUCTURE v.2.3.4 . We assuARVESTER .ST-based outlier test implemented in the software LOSITAN [We tested for possible selection acting on the molecular markers using an F LOSITAN . We assur values and the 95% confidence interval in case of no spatial structure of individuals were estimated by bootstrapping 9999 times over pairs of individuals.We analyzed fine-scale structure using spatial autocorrelation analysis  implemenWe furthermore assessed possible sex- and morph-biased dispersal. We divided the sampled individuals into two groups: a) males and females and b) full-plated and a combined group of low-plated and partially-plated individuals. We combined the latter two groups in order to obtain sufficient statistical power, as the majority of individuals were full-plated. We conducted spatial autocorrelation analysis on the same spatial scale as described above for each sex/morph separately, and then compared results for the two sexes and classes of morphs. Non-overlapping confidence intervals, particularly for the shortest distance classes would indicate sex- or morph-biased dispersal .For each individual, the lateral plates on the left side of the fish excluding keel plates (if present) as well as pelvic and dorsal spines, rays in the pectoral, dorsal, anal, and caudal fins were counted under a stereo microscope. Lateral plate morphs were defined as (I) low-plated: sticklebacks with 10 or fewer plates, (II) partially-plated: between 11 and 21 lateral plates, (III) fully-plated: > 21 plates . As initGeometric morphometric methods  were useSchistocephalus solidus which is a widespread macro-helminth [black spot disease, which is externally visible and can be caused by several trematode taxa: Uvulifer, Crassiphilia, Cryptocotyle and others [2 test, and Fisher’s exact test.We focused on two general types of parasite infestation: a) parasites that live in the trunk of fishes, notably helminth  and b) bd others . The disd others . We did black spot disease. We constructed two different data sets: (i) one including all individuals from the marine Nor location to the very upstream part of the river, OddU and (ii) another involving only the continuously sampled downstream part of the Odder river, OddM . The three cline models described in Brumfield et al. [5 iterations with a burn-in of 104 and a separate seed for each model and then assessed convergence and stability by visualizing the MCMC traces. For each of the analyzed loci and phenotypic traits we plotted the maximum-likelihood clines for the best-fit model, selected according to the Akaike information criterion score [Using the Metropolis-Hastings Markov chain Monte Carlo algorithm implemented in the software HZAR  we applid et al.  were fiton score .Analysis of SNPs and EDA indel marker variation provided results for all markers. However, significant drop-out of genotypes at markers 19,976 (71% missing data) and 26,062 (74% missing data) led to their omission. Sex was determined for 307 individuals; 31 individuals from Nor, 246 individuals from OddM and 30 individuals from OddU; due to depletion of DNA samples some individuals could not be analyzed. A total of 136 individuals were found to be males and 171 females.e) across all loci was 0.211 in Nor, 0.216 in OddM and 0.255 in OddU, whereas observed heterozygosity (Ho) was 0.203 in Nor, 0.212 in OddM and 0.221 in OddU. After False Discovery Rate correction and at a 5% significance level no loci showed deviations from Hardy-Weinberg equilibrium in Nor, 10 loci showed significant deviations in OddM  and 6 showed significant deviations in OddU . This represented 13 cases of deficits and 3 cases of excess of heterozygotes.Average expected heterozygosity (HST between the three major groups was −0.001 and non-significant (p = 0.935). Accordingly, pairwise FST were also low and non-significant: Nor-OddM FST = −0.003 (p = 0.999), Nor-OddU FST = 0.001 (p = 0.391), OddM-OddU FST = 0.001 (p = 0.302). STRUCTURE analysis of the entire data set showed the most likely number of distinct genetic clusters to be one  as candidates for being under directional selection: Eda, 7807, 7808, 27,791, and 33,942  the markers under possible selection , 2) three SNPs tightly linked to other SNPs , 3) two SNPs with missing data in many individuals  and 4) five SNPs found on the sex chromosome 19 . We found that a geographical distance size class of 200 m represented the best compromise between geographical resolution and numbers of individuals within classes.r = 0. This was also case for the analyses in Fig. For the analysis involving all individuals Fig.  the 95% Figure There was no evidence for sex-biased dispersal Fig. , as 95% p = 0.5463), anal fin rays , dorsal fin rays  and caudal fin rays  between Nor, OddM and OddU , H = 1.2092, df = 2, p = 0.0062*). A Steel-Dwass post hoc test showed significantly more lateral plates in Nor compared to OddU  and OddM individuals  , but OddU exhibited a trend for fewer plates , H = 10.1642, df = 2, For the body shape analysis, the percentages of variance accounting for all the principal components are listed in Additional file p = 1.108E-23). The results of the pairwise comparisons of the three groups showed that there was a significant difference in the means between all pairs . The centroid size, which is a measure of body size, differed significantly across the three groups . No significant difference was detected between OddM and OddU   across all three major groups  =4.325, p = 0.1150, see Additional file black spot disease was on average 58.46%, and significantly different across the three groups (Pearson χ2 (2) = 39.081, p < 0.0001)  that were closely physically linked to other of the loci. We also omitted 21 loci that presented an overall minor allele frequency < 0.05: 2114, 3231, 5238, 7745, 8466, 9206, 9990, 13,340, 14,236, 18,262, 20,063, 20,238, 21,688, 21,858, 22,037, 22,693, 23,341, 24,457, 30,542, 31,479, 33,387. Subsequently, the cline analysis was conducted independently for 69 loci. A cline was fitted for each of the 69 loci and 7 phenotypic traits, and the model with lowest AICc value was chosen . The following loci displayed clinal patterns at both geographical scales: 2620, 11,996 , 35,236 (outlier between Nor and OddM), and 16,548  showed a cline at the small geographical scale (OddM), with rate of infection increasing with distance from the sea but only a steep increase in the large data set rather than a specific clinal pattern , centroid size, parasites (in trunk), and shape PC1  see Fig. . Black sern Fig. . PC2 andern Fig. .black spot disease), plates, PC1, PC2, standard length), and the second around 5200–5400 m from the sea . Overall, the results indicate a shallow hybrid zone and/or change of selection regimes around 4100–5400 m from the sea in the lower part of the Odder River, corresponding to ca. 350–1500 m from the outlet of the river into the Norsminde Fjord.The clinal patterns suggested two possible cline centers: the first around 4100–4600 m from the sea  relative to downstream (OddM) and marine sticklebacks (Nor). Whereas trends for these traits are in the directions expected for differentiation between marine and freshwater threespine sticklebacks , 26, 33,In the following we consider how systems like Odder River sticklebacks can be characterized, we discuss the lack of sex-biased dispersal and the finding of plate morph-biased dispersal and its biological significance. Finally, we discuss possible reasons underlying the widely different patterns of marine-freshwater divergence observed in the stickleback system, which also parallels other findings of both bi- and unimodal hybrid zones within the same species .ST values, the spatial autocorrelation analysis nevertheless showed fine-scale structure. Hence, with a genetic patch size of ca. 770 m the probability is low that individuals from e.g. the river mouth would interbreed with individuals 8 km upstream. This also leads us to rule out a simple explanation of the results showing overall low adaptive divergence throughout the system, that is anadromy. If all individuals migrated to sea and returned to freshwater to spawn, then they would all be subject to selection regimes characteristic of marine environments, which could explain the dominance of full-plated morphs. However, in order for the fine-scale structure to persist this would require accurate natal homing from the sea to specific sites in the river up to 8 km upstream. Transplantation and recapture of tagged sticklebacks in a small stream has demonstrated that they are able to home to the original point of capture when displaced up to 200 m downstream [We reject the hypothesis that the Odder River system and adjacent marine sticklebacks comprise a simple panmictic population. Even though analysis of tens of thousands of SNPs in a previous study  and analwnstream . HoweverST at this locus was relatively low (0.11); this corresponds to FST values of 0.12 and 0.10 observed in some previous studies [ST ranging from 0.38 to 0.86. Even though clines at loci and traits were shallow, the fact that there was general concordance between the geographical positions of cline centers also suggests a response to an environmental gradient. Clines at some traits, notably infection by black spot disease could in principle reflect genetic adaption. However, they could also reflect differences in environmental conditions, such as salinity, which by themselves affect the abundance of the parasites without invoking adaptive responses. Geographical differences and clinal patterns for body shape variation may also reflect phenotypic plasticity [It is also evident that some diversifying selection is ongoing in the system. Although the possibility of false positives must be taken into account when interpreting outlier tests, it is reassuring that the well-known candidate locus Eda was the most significant outlier. Nevertheless, F studies , 78, but studies , with FSasticity , 30, butasticity .ST is low between geographically more remote sites. Although it may take some generations for marine-adapted alleles to travel to the most upstream part of the population, even low amounts of gene flow may constrain local adaptation. The classically inferred relationship between gene flow/migration (m) and selection (s) is that m > s will lead to gene flow overwhelming selection [In total, the system is best characterized as a diffuse, unimodal hybrid zone, where gene flow overwhelms selection. However, gene flow affects the most upstream localities indirectly, in a step-wise manner and over generations. This result illustrates the point previously made by Peakall et al.  that in election . More elelection , 80. WhePlethodon spp.) [Microtus agrestis) [Sex-biased dispersal might account for differences in introgression of mitochondrial DNA, sex chromosomes and autosomal loci observed across some hybrid zones, such as in salamanders (on spp.)  and fielgrestis) . In thregrestis) , 48. Yetgrestis) . AlthougIn contrast to sex-biased dispersal we did, however, observe different dispersal of lateral plate morphs. Spatial autocorrelation analysis suggested that full-plated morphs exhibited higher dispersal than partial and low-plated morphs. The differences were small, but on the other hand we pooled partial and low-plated morphs to obtain sufficiently high sample sizes, and it is possible that a direct comparison between only full- and low-plated sticklebacks would have revealed stronger differences. We find it surprising that full-plated morphs normally characterizing marine sticklebacks disperse more in freshwater, but it could reflect a continual influx of full-plated marine sticklebacks that is not counter-balanced by downstream migration of low-plated individuals. Also, a behavioral study of sticklebacks exhibiting different morphs and Eda genotypes showed that individuals exhibiting full-plated alleles showed preference for a range of salinities, mainly determined by the salinities they were already acclimated to . Low-plaTriturus newt [Corthicus grasshopper [Bombina toads [One obvious explanation of our results could be recent extinction of the freshwater population and recolonization by marine sticklebacks, and that adaptive divergence therefore is still in a process of establishment. However, we find it unlikely that a major extinction event should have occurred undetected. The Odder River has a large, indigenous self-sustaining population of brown trout. Although local extinction and recolonization in a few small tributaries has been recorded, the total population is stable and has never been stocked . Hence, Another possible explanation concerns differences in fish predator composition across different freshwater environments. In the Odder River the dense brown trout population may pose a significant predator pressure on sticklebacks, which should favor full-plated phenotypes , 88. EurEven if fish predation could explain the dominance of full-plated morphs and Eda alleles in the Odder River, it remains striking that low divergence between freshwater and marine sticklebacks was a genome-wide effect, as shown by RAD sequencing . Fish prDivergence between different stickleback ecotypes has been argued to represent speciation with gene flow . HoweverNevertheless, an extended version of this scenario might be possible. It has been suggested that many instances of contact zones seemingly maintained by selection and adaptation to different environments may in fact represent endogenous genetic incompatibilities that interact with environmentally based selection . The posWhy do we see so distinct genetic and phenotypic differences between marine and freshwater sticklebacks in some , 27, 35 rus newt , Corthicsshopper  and Bombna toads , 86, indThe Odder River represents a system where the freshwater stickleback population is only weakly divergent from marine sticklebacks at the phenotypic and genetic levels. It is nevertheless best characterized as a unimodal hybrid zone, where gene flow from marine sticklebacks strongly constrains adaptive divergence in the freshwater environment. The system exhibits a fine-scale genetic structure and genetic patch size that renders it unlikely that marine immigrants can affect the most upstream part of the river within a single generation. Instead, the effects of gene flow occur indirectly over several generations. Even though the presence of both uni- and bimodal hybrid zones has been documented in other species , freshwa