Polygala chamaebuxus L.) is widely distributed in the Alps, but occurs also in the lower mountain ranges of Central Europe such as the Franconian Jura or the Bohemian uplands. Populations in these regions may either originate from glacial survival or from postglacial recolonization. In this study, we analyzed 30 populations of P. chamaebuxus from the whole distribution range using AFLP (Amplified Fragment Length Polymorphism) analysis to identify glacial refugia and to illuminate the origin of P. chamaebuxus in the lower mountain ranges of Central Europe. Genetic variation and the number of rare fragments within populations were highest in populations from the central part of the distribution range, especially in the Southern Alps  and in the middle part of the northern Alps. These regions may have served, in accordance with previous studies, as long‐term refugia for the glacial survival of the species. The geographic pattern of genetic variation, as revealed by analysis of molecular variance, Bayesian cluster analysis and a PopGraph genetic network was, however, only weak. Instead of postglacial recolonization from only few long‐term refugia, which would have resulted in deeper genetic splits within the data set, broad waves of postglacial expansion from several short‐term isolated populations in the center to the actual periphery of the distribution range seem to be the scenario explaining the observed pattern of genetic variation most likely. The populations from the lower mountain ranges in Central Europe were more closely related to the populations from the southwestern and northern than from the nearby eastern Alps. Although glacial survival in the Bohemian uplands cannot fully be excluded, P. chamaebuxus seems to have immigrated postglacially from the southwestern or central‐northern parts of the Alps into these regions during the expansion of the pine forests in the early Holocene.The shrubby milkwort ( There, it occurs mainly in pine forests and on rocky mountain slopes. In the study presented here, we tried to illuminate the origin of the species in these lower mountain regions. More specifically, our aim was (i) to identify glacial refugia of P. chamaebuxus and (ii) to analyze whether the populations of the species in the low mountain ranges can be attributed rather to glacial survival or to postglacial immigration.The shrubby milkwort  Schb. which includes five perennial species of shrubs or dwarf shrubs, with alternate, subcoriaceous leaves, flowers with a crest on the keel, winged capsule, and carunculated seeds. Actually four species of this lineage are known from Europe: P. chamaebuxus L. (widespread throughout the Alps), P. vayredae Costa , P. balansae Coss., and P. webbiana Coss. (distributed in Morocco), both taxa recently reported from southern Spain  belongs to the diploid level, P. webbiana, P. balansae, and P. vayredae are tetraploids with 2n = 28, whereas hyperhexaploidy (2n = 44) was found in P. chamaebuxus. Karyotype analysis revealed that P. chamaebuxus developed most probably by autopolyploidy from P. vayredae or the African P. webbiana or by allopolyploidy of these species. The evolution of the group concerned seems to have taken place in the southwestern Mediterranean and to have continued on the Iberian way as far as the Alps and Central Europe  can only be found in the cantons of Graubünden and Tessin and down the Apennine , 2 μl Na 2 EDTA , and 1 μl glycogen (Roche). DNA was precipitated in a 1.5‐ml tube by adding 60 μl of 96% ethanol (−20°C) and 20‐min centrifugation at 14,000 × g at 4°C. The supernatant was poured off, and the pellet was washed by adding 200 μl 76% ethanol (−20°C) and centrifugation at the latter conditions.After an initial screening of 30 primer combinations, three of them were chosen for the subsequent selective PCR reaction using labeled EcoRI primers . The resulting products were diluted twofold (D2) and fivefold (D4) with 1× TEThe pelleted DNA was vacuum dried in a vacuum concentrator. Subsequently, the pellet was dissolved in a mixture of 24.8 μl Sample Loading Solution  and 0.2 μl CEQ Size Standard 400 (Beckman Coulter) and subsequently selective PCR products were separated by capillary gel electrophoresis on an automated sequencer .Results were examined using the CEQ 8000 software (Beckman Coulter) and analyzed using the software Bionumerics 6.6 . In order to assess the reproducibility of the scored fragments, about 10% (29 samples) of all analyzed samples were repeated and the genotyping error rate ². Additionally, we calculated rarity as frequency down weighted markers (DW) for each population  simulations was computed with 20 iterations per n − 1).Furthermore, a nonhierarchical AMOVA was carried out with GenAlEx 6.41 . PopGraph is free of a priori assumptions about population geographic arrangements and uses a graph theoretical approach to determine the minimum set of edges (connections) that sufficiently explain the total among‐population covariance structure of all of the populations  within the studied populations varied between 0.16 and 0.26 with an average of 0.21, whereas the AMOVA‐derived diversity measurement SSWP/(n − 1) ranged from 14.5 to 22.0 with a mean of 17.5. The rarity index (DW) showed only little differences between populations and ranged from 4.77 to 5.51 with an average of 5.21. However, rarity was highest in populations with high levels of Nei's gene diversity as revealed by correlation analysis using Spearman's rank correlation coefficient . Genetic variation within populations and the rarity index were highest in populations from the central part of the distribution range  ranged from 43.7 to 67.2 with a mean of 53.1  and the respective geographic distance between populations .In a nonhierarchical analysis of molecular variance (AMOVA), only 16.5% of the total genetic variation was found among all populations while 83.5% were detected within populations  was comparable to the variation recently reported for other long‐lived, common, and outcrossing plant species (H = 0.20) using AFLPs  has been proved by fossil evidence (Murr, P. chamaebuxus could have survived glaciations also in this region.Following our data, especially the high level of rarity, suggests long‐term survival of ce Murr,  and prevce Murr, , which sP. chamaebuxus, which may be a sign of a comparatively short period of isolation during the LGM. It is known that the strong glaciations of the Würm glaciation were limited to few periods of extreme cold climate with culmination during the LGM (Veit, Polygala chamaebuxus exhibits a broad ecological range, which allows the species to grow under various climatic conditions and is even considered as cold germinator (Jäger, Polygala chamaebuxus may, for this reason, have been affected not that strongly by the glaciations like other highly specialized species. It is possible that the refugia described above were locations where the species survived most time of the Pleistocene. However, based on the results of the Bayesian cluster analysis, it appears likely that further locally surviving populations in other regions also contributed to the postglacial recolonization after the LGM. The geographic pattern of genetic variation revealed by the Bayesian cluster analysis may therefore reflect not only postglacial recolonization but also gene flow and range expansion from the periods before the LGM, which is also supported by the positive relationship of genetic and geographic distance in the Mantel test. Instead of postglacial recolonization from only few long‐term refugia, which would have resulted in deeper genetic splits within the data set, broad waves of postglacial expansion from multiple populations in the center to the actual periphery of the distribution range seem to be the scenario explaining the observed pattern of genetic variation most likely.However, our results indicate rather a genetic continuum than deep genetic splits between populations of GM Veit, . During r Jäger, . Polygal4.3P. chamaebuxus in the lower mountains of Central Europe, such as the Jurassic mountains, the Bavarian Forest, the Fichtelgebirge, and the Bohemian uplands, may originate from glacial survival or postglacial immigration. Interestingly, our results provide evidence for both the survival and immigration hypotheses. The number of rare fragments was not conspicuously increased, except for the population from the Bohemian massif, which could in fact indicate long‐term survival in this region. It can therefore not fully be excluded that the species survived glaciations in the Bohemian uplands.The populations of Polygonatum verticillatum in the Tatra and Sudety Mountains. Similarly, it is assumed that the boreo‐montane tall forb Cicerbita alpina survived glaciations in sheltered pockets with a humid climate in some parts of Central Europe (Michl et al., Cyclamen purpurascens may also have survived glaciations in prealpine northern refugia (Slovák et al., Melica nutans, several independent “strongly restricted and isolated” refugia in Central Europe have been detected (Tyler, P. chamaebuxus survived glaciations in the Bohemian massif.This assumption is supported by previous studies reporting glacial survival of forest‐related plant species in cryptic refugia located in the lower Central European mountain ranges (Kramp et al., d Tyler, . It is tHowever, we observed no deep genetic split between the Central European populations and populations from other regions. From this point of view, it seems to be likely that most populations spread postglacially to the range periphery and the lower mountains of Central Europe. Founder effects and long‐distance dispersal associated with this expansion may have resulted in the lower levels of genetic variation observed in the more peripheral populations. The probably remnant lineage of the Bohemian massif might have been genetically merged in the expanding wave from the northern Alps.P. chamaebuxus may have immigrated postglacially from the southwestern or central‐northern part of the Alps to the lower mountains of Central Europe. This migration process of P. chamaebuxus to the lower mountain regions may be associated with the expansion of pine forests after the last LGM. It is assumed that Pinus sylvestris survived glaciations on the Iberian and the Balkan Peninsula (Sinclair, Morman, & Ennos, Polygala chamaebuxus is considered as a species typically for these early pine forests (Hardtke & Ihl, P. chamaebuxus together with Scots pine toward the north. Migration could already have been started in the Late Glacial from 15,000 BP to 10,000 BP as pine and birch were already present in the Alps and the alpine forelands until about 8,000 BP when the continuous distribution of pine forests ended (Lang, In the PopGraph genetic network, the populations from the lower mountain regions were more closely related to the populations from the western part than to the populations from the eastern part of the distribution range. This suggests that ed Lang, .Saxifraga paniculata in a previous study (Reisch, Similarly, the species seems to have migrated from the center of the distribution range to the eastern and western Alps. In this context, it is a remarkable finding of our study that the population from the Velebit in Croatia was more closely related to the population from the Apennine and westernward populations than to the populations from the nearby southeastern Alps. This observation was also made for  Reisch,  and seemNone declared.


Espeletia, also known as frailejones. This genus has one of the highest diversification rates ever reported and is distributed in the world’s fastest evolving biodiversity hotspot, the Páramo . Our goal was to determine whether ecology plays a role in divergence within the Espeletia complex by quantifying genome-wide patterns of ecological divergence. We characterized 162 samples of the three most common and contrasting ecotypes (distinct morphotypes occupying particular habitats) co-occurring in six localities in the northern Andes using Genotyping by Sequencing. Contrasting ecotypes were caulescent cloud forest populations, caulescent populations from wind-sheltered and well-irrigated depressions and acaulescent populations from wind-exposed drier slopes. We found high polymorphism with a total of 1,273 single nucleotide polymorphisms (SNPs) that defined the relationships among nine genetic clusters. We quantified allelic associations of these markers with localities and habitats using 18 different general and mixed-effects statistical models that accounted for phylogenetic distance. Despite that these models always yielded more SNPs associated with the localities, markers associated with the habitat types were recovered too. We found strong evidence for isolation-by-distance (IBD) across populations despite rampant gene flow, as expected for plant groups with limited seed dispersal. Contrasts between populations of different habitat types showed that an isolation-by-environment (IBE) trend emerged and masked the IBD signal. Maximum likelihood estimation of the number of migrants per generation (Nem) among ecotypes confirmed the IBE pattern. This result illustrates the importance of mountains’ environmental variation at a local scale in generating rapid morphological radiations and maintaining multiple adaptations in a fast-evolving ecosystem like the Páramo.How diversity arises and what is the relative role of allopatric and ecological divergence are among the most persistent questions in evolution and ecology. Here, we assessed whether ecological divergence has enhanced the diversification of the Neotropical alpine plant complex  Diversification is recognized as an important process generating phenotypic and genetic variation in plants and animals. However, its relationship with ecological variation and genomic and morphological divergence is just starting to be understood . For ins2), may contain over 3,000 plant species, many of which are found nowhere else on the planet  are ecologically abundant in the Páramo , in which genetic and environmental distances are positively correlated independent of geographic distance, has never been tested explicitly within this system, as has been partially envisioned for other Páramo genera such as Lupinus  that likely confer adaptation to this assortment of environmental conditions (Genomic studies in plant populations have proven that genome–environment associations (GEA) are useful to identify genomic signatures of IBE, which are the genetic association with environmental variables. Mostly, these studies have associated single-nucleotide polymorphism (SNP) alleles and parameters from the environment of origin to infer genetic adaptive variants. For instance, nditions , 2016.Espeletia is typically found across several representative localities of the genus’ distribution in the Central and Eastern Cordilleras of the northern Andes, with a whole-genome genotyping method such as Genotyping by Sequencing  compute SNP allelic associations with localities and habitats in order to identify sources for genetic isolation and adaptive variation. We hypothesized that if ecological differentiation contributed to genetic divergence in the Espeletia complex, then we should be able to recover for the first time more subtle and localized signals of IBE, besides a predominant pattern of IBD.By combining a sampling spanning the three habitats where ing GBS, , we aimeEspeletia complex were used in this study . Two 96-plex genotyping-by-sequencing (GBS) libraries were performed with MsII digestions according to A total of 162 individual plants from the y Figure . These iDemultiplexing, cleaning, and filtering of Illumina reads was performed with the Illumina bcl2fastq v. 2.17.1.14 software . A total of 1 or 2 mismatches or Ns were allowed in the barcode read when the barcode distances between all libraries allowed for it. Demultiplexing of library groups into samples was done according to inline barcodes and verification of restriction site. No mismatches or Ns were allowed in the inline barcodes but Ns were allowed in the restriction site. Restriction enzyme site filtering of read 5′ ends was carried out so that reads with 5′ ends not matching the restriction enzyme site were discarded. Quality trimming of adapter-clipped reads was done by removing reads containing Ns, trimming reads at 3′-end to get a minimum average Phred quality score of 20 over a window of ten bases and discarding reads with final length < 20.1, allowing up to 5% difference. Alignment of subsampled quality-trimmed reads against all clusters was done using BWA  across all samples, and an observation of genotype frequency of at least 72% (116 samples). The filtered dataset was inspected with TASSEL v. 3.0 . Five independent runs for each K value from K = 2 to K = 19  used an admixture model with 100,000 burn-ins and 200,000 iterations in the MCMC analysis. A bar graph of the results was generated for each K value using CLUMPP  implemented in Trait Analysis by aSSociation, Evolution and Linkage v.5 . The cong CLUMPP . The optacer 1.5  and treeacer 1.5 . A conseIn order to explore subtle divergence patterns among populations and ecotypes, the entire dataset was partitioned by habitats and localities, so that the habitat-based dataset included populations from the Cocuy and Guantiva localities, whereas the locality-based dataset included populations from the remaining localities. SNP markers were filtered for each of these new datasets using the same MAF and missing data rules than for the full dataset (see previous section), leading to 897 and 812 SNP markers, respectively. This partition led to three different datasets  that were used in subsequent analyses. Four reiteratively misplaced samples led to an acceptable error rate  of 2.5% P-values were inspected to assess whether excessive numbers of false positives were generated and choose in this way the optimum model. Significant associations were determined using a strict Bonferroni correction of P-values at α = 0.05, leading to a significance threshold of 3.9 × 10-5, 6.2 × 10-5, and 5.6 × 10-5  or -log10 of 4.4, 4.2, and 4.6, for the full, locality-based and habitat-based datasets, respectively.In order to perform GEA analyses between the SNP markers and the localities, and between the SNP markers and the habitats, we used the software Trait Analysis by aSSociation Evolution and Linkage. For these GEA analyses the habitats were ranked according to the expected, hereinafter referred to as theoretical, exposure to frost and soil moisture content, as coded in Supplementary Table Espeletia complex, the entire dataset and the contrasting datasets for localities and habitats were further subdivided according to the allelic associations found in the previous section, so that SNP markers were retained if they were significantly associated with the locality, the theoretical exposure to frost or the theoretical soil moisture content. Since the full marker set was also maintained in each case, this partition series led to a total of eleven datasets. The dataset that only included contrasting populations for localities and associated markers with the theoretical soil moisture content had just one polymorphic site and was excluded from the rest of the analyses. Pairwise FST values, according to em) following FST-based methods and A single genome can exhibit heterogeneous patterns of geographic (IBD) and ecological (IBE) differentiation . TherefoFST/(1 – FST) according to dist. Therefore, for each dataset three different correlations with the genetic differentiation were considered , leading to a total of 33 Mantel tests. These tests used 1,000 permutations implemented in R (R Core Team). Significant associations were determined based on a strict Bonferroni correction of P-values at α = 0.05 . The most likely K-value of nine was selected based on the previous results and the increases in likelihood ratios between runs using K statistic , a total of 172, 39 and 28 SNP markers associated with the localities and with the habitats when these were ranked according to the theoretical exposure to frost and the theoretical soil moisture content, respectively . The fact that few SNP markers were associated with the habitats in this contrasting dataset for localities was consistent with a low rate of false positives in a species complex well known for its IBD pattern. On the other hand, when only contrasting populations for the habitats were considered, the GLM analyses yielded, based on a Bonferroni-corrected significance threshold of 4.6 -log10 , a total of 184, 123 and 87 SNPs respectively associated with the localities and with the habitats when these were ranked according to the theoretical exposure to frost and the theoretical soil moisture content.QQ-plots from the association analyses between the SNP markers and the localities, and between the SNP markers and the habitats  indicated that MLM models over-controlled for population structure by using a kinship matrix, whereas GLM analyses exhibited tolerable rates of false positives  among populations were high and ranged from 0.3 to 7.5 for the entire dataset, and from 0.4 to 3.4 and from 0.3 to 7.5 when only contrasting populations for habitats and localities were considered, respectively. Estimated migration rates were asymmetric among these three types of datasets . We found strong evidence for IBD across populations despite rampant gene flow, as well as a subtle IBE trend that emerged and masked the IBD signal when we only considered contrasting populations for habitats. This finding is supported mainly by two significant results. First, migration rates were not higher among populations from the same habitat from different localities than among populations from different habitats within the same locality only for the SNP dataset enriched for habitat comparisons. Second, Mantel tests between genetic differentiation and ecological distance based on the theoretical exposure to frost, a proxy for adaptation to Páramo environments, were significant in the dataset with contrasting populations for habitats without exhibiting an, otherwise ubiquitous, relationship with the geographic distance. In other words, we have shown how IBD breaks down at the microenvironment level, allowing IBE to come into play. Mixed signatures of IBD and IBE indicate that geographical isolation and environmental heterogeneity both contribute to the spatial genetic patterns in the Espeletia complex. Since we were able to recover subtle and localized signals of IBE, besides a predominant pattern of IBD, there is evidence that ecological differentiation may have contributed to genetic divergence in the Espeletia complex. This illustrates the importance of local-scale environmental heterogeneity in keeping multiple putative adaptations and generating rapid morphological variation in a highly diverse ecosystem like the Páramo.If ecological differentiation contributed to genetic divergence in the Espeletia complex. Results from Nem estimates >1 are often understood as an indication of panmixia . Judging by the result that maximum nine genetic clusters spanned 19 populations , we can conclude that there is little evidence pointing toward an assembly of genetically well-differentiated populations fully concordant with the ecological and morphological differentiation that is observed in the panmixia , and herpanmixia . Mosaicspanmixia . Discernpanmixia .Espeletia. First, sporadic pollen dispersal may overcome the limited seed dispersal as the mechanism for gene flow. In Espeletia it has been hypothesized that pollen dispersal may not be as constrained as seed dispersal (Espeletia complex that is well known for the high incidence of natural hybridization (Espeletia individuals may live for several centuries (Espeletia. Finally, the absence of strong population differentiation may be due to weak reproductive barriers resulting from recent divergence. The diversification of Espeletia occurred in recent geological time, after the final uplift of the Northern Andes about 2.3 Myr (Espeletia has proven to be challenging (Espeletia complex by targeting morphologically intermediate populations as well as their putative parental lineages.There are several reasons why gene flow could be rampant in organisms with limited seed dispersal such as ispersal . Second,dization . Third, enturies , sporadi 2.3 Myr . Gene flllenging , despitellenging , likely Espeletia. Such divergence may be a consequence of local patterns of exposure to frost, being more extreme in the wind-exposed high valley slopes than in the wind-sheltered depressions of those valleys or in the upper boundary of the cloud forest. On the other hand, soil moisture content, higher in the well-irrigated high valley depressions and in the upper boundary of the cloud forest than in the drier slopes of the valleys, does not contribute to divergence. These predictions, as any outcome of a reverse genetics approach like the GEA, must be further validated throughout experimental approaches, such as growth chamber experiments and field reciprocal transplant assays of contrasting ecotypes.Environmental effects play a role in shaping genetic diversity and generating morphological radiations in highly heterogeneous environments . RadiatiEspeletia. Since the role of geographic isolation has already been reported and discussed in extenso by recent works (Espeletia complex, acting as the major processes diversifying the genus.In this study we also corroborated that geographical factors are associated with divergence in nt works , here went works . FurtherEspeletia. SNP redundancy due to LD (Espeletia, we were able to provide evidence of ecological divergence in this genus, as has already been suggested for other highly diverse genera in the Páramo like Loricaria (Lupinus (Bartsia (Diplostephium (Hypericum (Oreobolus (Puya (One potential caveat of our results is the disadvantage of GBS due to missing data, for example from sequence divergence . Nonetheue to LD  may therue to LD . Howeverue to LD , are goooricaria  and Lupi(Lupinus . However(Lupinus  in other(Bartsia , Diploststephium , Hypericypericum , Oreobolreobolus  and Puyaus (Puya , in ordeEspeletia is among the genera with a high incidence of natural hybridization and countless putative hybrids have been documented based on morphological characters (ad hoc evidence of rampant gene flow, understanding the causes and consequences of hybridization in Espeletia and whether reticulate evolution has enhanced the diversification rate in this genus would ultimately require an in-depth ecological sampling design and an extended genotyping effort focused on hybrids and their putative parental populations.Besides allopatric and ecological diversification, hybridization, which was not explicitly addressed in the current sampling, is also regarded as a relevant process generating diversity in plants . Howeveraracters . Even thDespite hybrids could occupy intermediate niches, persistence of populations in heterogeneous habitats that are facing changing environmental conditions is considered to be mostly mediated by phenotypic plasticity  or by adEspeletia exhibits strong IBD and occurs in highly heterogeneous habitats, local scale variation can have important implications for their reaction to changing climatic conditions. For instance, environmental heterogeneity may provide new suitable locations for migrants within only a few meters of their current locations (Espeletia for coping with various types of stress that vary across habitats and that are expected to worsen at alpine ecosystems, such as frost (Espeletia, and other key plant groups in the Páramos, to local heterogeneous environments will thus assist with efforts to establish how future climate will impact plant populations in a highly diverse and threatened ecosystem (Espeletia can keep pace with the quick rate of climate change and human expansion.Some of the largest impacts of climate change are expected in highly heterogeneous alpine environments , where wocations , while aas frost , 2016, nas frost , alteredas frost , 2016, das frost , floodinas frost . Additiocosystem . The concosystem , is indicosystem . It thenFinally, expanding our approach to other sky islands across the world’s mountains , especiaThe data analysis pipeline configuration files and cleaned dataset are archived at the Dryad Digital Repository under doi: 10.5061/dryad.23bd3ds.AC and SM designed the study. AC, LG, and SM collected the samples. AC analyzed the data with contributions from JBV and SM. AC wrote up the results with editions from the other authors.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.


Empoasca (Matsumurasca) onukii Matsuda, is one of the dominant pests in major tea production regions of East Asia. Recent morphological studies have revealed variation in the male genitalic structures within and among populations. However, the genetic structure of this pest remains poorly understood. This study explores the genetic diversity and population structure of this pest in nineteen populations from the four main Chinese tea production areas using microsatellite markers, with one Japanese population also examined. The results show low to moderate levels of genetic differentiation with populations grouped into four clusters, i.e. the Jiangbei group, the Southwest group 1, the Southwest group 2 and the South China group. Populations from China have a close phylogenetic relationship but show significant isolation by distance. Lower genetic diversity and genetic differentiation of E. (M.) onukii were found in the Kagoshima population of Japan. Evidence for genetic bottlenecks was detected in the South China and Jiangnan populations. Population expansion was found in the Southwest, Jiangbei and Kagoshima populations. This is the most extensive study of the population genetics of this species and contributes to our understanding of its origin and evolutionary history.The tea green leafhopper,  It was first described in 1952 as an Empoasca leafhopper injurious to tea shrubs in Japan3. Although considerable economic losses caused by this pest have drawn substantial attention by farmers and government bodies in China since the 1950s, two incorrect scientific names, Empoasca (s. str.) vitis (Goëthe) and Jacobiasca formosana (Paoli) continued to be applied to the pest in mainland China and Taiwan, respectively, in both basic and applied research for many years7. Recent morphological and molecular evidences reveal this pest in China is the same species that occurs on tea in Japan8. Thus, the correct scientific name of the tea green leafhopper in China has been established as Empoasca (Matsumurasca) onukii Matsuda1. Damage caused by adults and nymphs of this pest has been described as the classical symptoms of hopperburn in young tea leaves and shoots. This damage results from the leafhoppers’ piercing-sucking mode of feeding9, leading to yield losses averaging 10–50% in China11 and up to 33% in Japan12.The tea green leafhopper is one of the most dominant pests in the major tea production regions of East Asia13, tea trees are now widely cultivated in more than 34 countries across Asia, Africa, Latin America, and Oceania14. However, so far, this pest has been officially reported only from three countries  in Asia15. In China, tea plantations now account for half the overall tea production by area worldwide, and comprise four tea regions: Jiangbei , Jiangnan , South China and Southwest China. These regions are designated based on the ecological conditions, the history of tea production, and the distribution and cultivation characteristics of tea varieties17.Despite previous studies reporting that tea production originated in Southeast China more than three thousand years ago18. Thus, it is reasonable to speculate that some genetic differentiation has developed, possibly as a result of restriction of gene flow among populations by geographic barriers  between these four Chinese tea regions. In Japan, the predominant tea cultivar ‘Yabukita’, is cultivated intensively in Shizuoka Prefecture in southern Honshu and Kagoshima Prefecture in Kyoto19, both well separated from the Chinese tea production areas, leading us to expect the genetic characteristics of Japanese E. (M.) onukii to be different from the Chinese populations.Recent morphological study has revealed variation in the structure of the male genitalia (aedeagus) within and among populations of the tea green leafhopper20 and another study that developed a haplotype network based on several geographic populations using mtDNA COI and 16S rRNA sequence data25. However, specimen sampling methods in these studies were not consistent, nor were the male genitalic characters studied to confirm the species identification and population-level variation. Unfortunately, given the past confusion over the identity of the species, it is possible that samples used in previous genetic studies have included other species besides E. (M.) onukii, and this could lead to a misunderstanding of Chinese E. (M.) onukii genetic structure. Because almost all Empoasca species (>200 species occur in the Chinese fauna) can be positively identified only by examining the male genitalia and multiple Empoasca species may coexist in the same habitat, it is crucial to confirm the identity of each individual specimen morphologically before it is incorporated into any population genetics study3.Previous attempts to explore the genetic structure of this pest include one study that compared samples from a small number of Chinese tea gardens using the RAPD method26. Twenty-one microsatellite markers were previously developed and selected for genetic studies of E. (M.) onukii in Chinese tea production areas27. Here we report the results of a comprehensive population genetic study based on these previously identified markers, incorporating specimens confirmed as E. (M.) onukii based on examination of male genitalia and obtained from all major Chinese tea production areas. Similar analyses have been conducted previously to explore the genetic differentiation, population structure and population dynamics of other species of Hemiptera36.Recently, 1569 microsatellite loci including 87 different repeat units have been found in the genome of the tea green leafhopper, among which triplet repeats (27.84%) and dinucleotide repeats (70.26%) were the most abundantE. (M.) onukii populations through comparative studies of populations in four tea production regions; (ii) examine effects of geographic isolation on the genetic differentiation and observed population genetic patterns of the tea green leafhopper; and (iii) elucidate the origin and evolutionary history of the species. This study represents the most extensive use of microsatellite markers to elucidate the origin and evolutionary history of E. (M.) onukii.The purpose of this study was to (i) assess the genetic differentiation and population dynamics of Eo-9 exhibited a significant excess of homozygosity. More than a 50% amplified fragment dropout was found for Eo-1-65 and Eo-9. Eo-29, Eo-37, Eo-54, Eo-1-52, Eo-1-57, Eo-83, Eo-1-5, Eo-F-8 and Eo-1-77 deviated from Hardy-Weinberg equilibrium (pHWE < 0.01) across different populations because of null alleles. However, null allele frequencies, lower than 0.2 for 18 markers, yielded little effect on genetic diversity and population structure, excluding Eo-4-5 38. The average frequency of null alleles at 18 markers over the populations ranged from 0.027 to 0.075  were highly polymorphic, with polymorphic information content (PIC) values ranging from 0.515 to 0.89239. At the population level, the mean Na and AR ranged from 8.4  to 10.4 (CY) and from 6.52 (JJ) to 8.27 (CY), respectively. The mean number of Ne per marker was 5.2, with the lowest value being 4.2 (JJ) and the highest being 5.9 (SX and CY). Only 69 individuals had one or more private alleles across all markers and they were spread across 17 populations. HO had a mean value of 0.679 and was lowest in the ZY population (0.615) and highest in the RZ population (0.737). The mean HE was 0.741, ranging from 0.665 (JJ) to 0.788 (CY) , the mean AR was significantly different between the PE and the other populations in China . Similarly, the mean HE was significantly different . The genetic diversity was significantly different between the CY population and the other populations . Overall genetic diversity was explained by 19 populations from China and one population from Japan also differing significantly in AR and HE .The number of alleles for the 18 microsatellites ranged from 2 to 18 over the entire population. Fifteen markers   and 2.14% among populations (P < 0.001) (Table P < 0.001). The FST ranged from 0.0012 to 0.0981 among the populations. FST values between the JJ population and the other populations ranged from 0.0267 to 0.0981, revealing moderate differentiation. The largest range of FST was found in Southwest group 2, ranging from 0.0286 to 0.0981  indicated that 2.43% of the genetic variation was partitioned among groups  onukii populations have differentiated into four groups: the Jiangbei group (purple populations), the Southwest group 1 (blue populations), the Southwest group 2 (orange populations) and the South China group (yellow populations)  and Southwest populations  were analyzed. There was a significant correlation when the South China group (including Jiangnan and South China populations)  under the SMM model. The TPM model revealed significant evidence of heterozygosity excess (P < 0.05) in XY, South China and most of the Jiangnan populations except for the CD (P = 0.054) and JH (P = 0.142) populations, which may indicate a recent genetic bottleneckE. (M.) onukii within a particular region is mainly reflected in the differences among individuals within a population. This is consistent with previous results from AMOVA based on mtDNA COI and 16S rRNA25. Analysis of microsatellite markers detected low to moderate levels of genetic differentiation among populations within the main tea growing regions of China, and much more genetic variation within populations (95.43%) than among populations (2.18%). This suggests substantial amounts of gene flow and a more homogeneous gene pool across different geographical populations. Measured genetic and geographical distances are correlated. Within a population, genetic mutation and drift are expected to yield genetic differentiation among individuals, whereas geographic isolation (such as geographic distance and geographic barriers) mainly influences genetic differentiation between populations.Our analysis of microsatellite data reveals that genetic differentiation of 27. Furthermore, different allelic richness and mean expected heterozygosity were observed in the PE and CY populations of the Southwest tea production area . These subdivisions in the Southwest tea production area populations are probably due to different combinations of geographic isolation and climatic variation. Substantial climatic differences between the Southwest tea production area and the other tea production areas and the existence of geographic barriers in this area, such as mountain ranges, basins and large rivers, may account for the genetic differentiation among E. (M.) onukii populations that have limited dispersal capacity23.The low to moderate levels of genetic differentiation and subdivision are concordant with geographic distribution. The genetic structure based on 18 microsatellite markers confirms the genetic difference between Southwest groups 1 and 2 in the topographically complex Southwest tea production area, similar to the result obtained previously41. Terpene index analysis has shown that the original tea cultivars are from Yunnan Province42. This Southwest tea production area was previously suggested as the area in which tea was first cultivated. The “original” haplotypes of 16S rRNA of E. (M.) onukii (based on a median joining haplotype network) were obtained from Yunnan and Sichuan populations22, suggesting that the tea green leafhopper expanded its range from the Southwest tea production area into other areas, following the spread of tea cultivation. Based on this evidence, as well as the genetic diversity and structure inferred in this study, we propose the following scenario for the spread of E. (M.) onukii populations in Chinese tea production areas: (1) the tea green leafhopper spread from Yunnan to Guangxi and Guangdong, and subsequently to Jiangnan and the South China tea production areas; (2) this pest then expanded to the Jiangbei tea production area from Yunnan through Shaanxi; and (3) the leafhopper was introduced to Jiangnan and the South China tea production areas from Yunnan through Guizhou, Chongqing and Sichuan provinces. The genetic pattern of E. (M.) onukii is similar to the historical propagation path of tea in China42. Low genetic diversity and moderate genetic differentiation of E. (M.) onukii observed in the Kagoshima population of Japan may have resulted from a bottleneck caused by anthropogenic transport of tea plants, geographical isolation and restricted genetic resources44. Based on Nei’s genetic identity >0.85 the Kagoshima population is closest to the populations in Jiangnan and South China. Similar tea germplasms in these populations also provide similar biotopes for this pest45.Fossil evidence suggests that tea trees originated 60–70 Mya (million years ago) in the Paleogene of the Yunnan-Guizhou plateauE. (M.) onukii are currently undergoing population expansion in the South China and Jiangnan tea production areas but are experiencing bottlenecks in other tea production areas. Mating interference and trapping of males may be used to keep E. (M.) onukii from spreading into surrounding tea production areas beyond Kagoshima, Southwest China and most of the Jiangbei populations. The South China and most of the Jiangnan populations, may show the effect of a recent genetic bottleneck, possibly resulting from heavy use of chemical pesticides. In these regions, only a few resistant individuals may have survived, leading to the genetic bottleneck effects, similar to those previously reported for Bemisia tabaci and Myzus persicae47. In these cases, pesticides may have stimulated the reproduction and expansion of pest populations, promoting gene exchange and homogenizing the genetic structure48. Integrative pest management incorporating biocontrol or organic production methods may be needed to build ecologically sustainable tea plantations in these areas50.This study suggests that different populations of 27. This may be because the present study used samples obtained from multiple localities in Sichuan. To provide more robust results, future studies should employ larger numbers of genetic markers and more individuals within the same locations to more fully represent the diversity of local E. (M.) onukii populations. The area of origin of E. (M.) onukii should be further explored by more intensive sampling of populations in the Southwest tea production area, where the level of genetic differentiation is highest. The dispersal routes of E. (M.) onukii among Chinese tea production areas should also be analyzed in more detail using more genetic loci (such as SNPs). Use of SNPs that have a high abundance throughout the genome, predictable mutation modes and low back mutation rates52 could reduce error in estimation of population parameters (such as FST and migration rates) compared to our use of microsatellite markers.Microsatellite markers revealed lower genetic differentiation between Sichuan and Yunnan populations than was shown in a previous study on this same species in the same regionE. (M.) onukii populations among the main Chinese tea production areas. Populations of this pest have differentiated into four groups: the Jiangbei group, the Southwest group 1, the Southwest group 2 and the South China group. Low genetic diversity and moderate genetic differentiation of E. (M.) onukii were found in the Kagoshima population of Japan. The observed patterns may be attributable to geographic isolation, differences in feeding preference among tea germplasms and the use of pesticides in tea production areas. Additional study is needed to elucidate the relationship between selective factors  and genetic structure.This study found low to moderate levels of genetic differentiation and segregation in E. (M.) onukii were collected by sweep net from 19 localities in four tea production areas of China and one location in Japan, representing a total of 20 geographically delimited populations . Eighteen microsatellite markers . PCR protocol was performed as described by Zhang et al.27. PCR products were run by automated capillary electrophoresis on an ABI 3130xl  genetic analyzer. Allele sizes were scored against a GeneScanTM 500LIZ standard using GeneMapper v4.0 .Total genomic DNA was extracted respectively from 30 male individuals per population  using the DNA Easy Blood and Tissue Kit  or a modified CTAB methodnull)37. Allele frequency, observed and expected heterozygosity were calculated with Genepop v.4.2 for each marker by the allele sizes from each geographical population. Deviations from Hardy-Weinberg equilibrium (HWE) were tested with 1000 permutations across markers using Genepop v.4.254. Linkage disequilibrium (LD) for each pair of markers in the populations was assessed with Genepop v.4.2. Statistical significance (P) was corrected for multiple comparisons by applying the strict Bonferroni correction55 with the same software.FreeNA was used to evaluate the frequency of null alleles (FO) and expected heterozygosity (HE), mean effective number of alleles per marker (Ne), mean number of alleles (Na) per marker and polymorphism information content (PIC) were calculated using GenALEx v. 6.556 and Cervus 2.057. The allelic richness (AR) was estimated using a minimum sample size of 26 diploid individuals in HP-Rare v1.058. Statistical significance of the genetic diversity indices between different populations was assessed using the independent samples t-test in SPSS Statistics 20 (IBM).Mean observed  was performed using Arlequin 3.11 to estimate and compare the percentage of genetic variation explained by different hierarchical levels: individual , populations  and groups . Arlequin 3.11 with 1000 permutations was also used to calculate pairwise estimates of FST and the significance (P) for each population64. The levels of differentiation between populations were measured based on FST65. Third, the genetic distances between populations were measured by DA distance in POPTREE267. A neighbor-joining tree (NJT) was constructed with POPTREE2 based on DA distance and 1000 replications. Finally, a principal coordinate analysis (PCoA) was carried out using GenALEX 6.502 based on Phi-st distances (GD) of populations56.Bayesian analysis, Analysis of Molecular Variance (AMOVA), phylogenetic analysis using the Neighbor Joining (NJ) approach and Principal Coordinate Analysis (PCoA) were used to analyze the genetic structure of the tea green leafhopper. First, Bayesian model-based clustering analysis implemented in Structure v2.3.4 was used to estimate the number of genetically distinct clusters (K) among the Chinese populations using an admixture ancestry model and correlated allele frequencies. The range of possible clusters was set from 1 to 10, with 20 independent runs for each K. Analysis parameters included a burn-in period of 50,000 iterations followed by 1,000,000 Markov Chain Monte Carlo (MCMC) repetitions. The most likely number of genetic clusters (K) in the Chinese populations was estimated by posterior probability of the data (P (K/X)), the Dirichlet parameter Alpha (α) and the ad hoc statistic (ΔK)56. Geographic distance was defined as the logarithms of the geographical distance between all pairs of population locations, and genetic distance was defined by pairwise population estimates of linearized FST/(1 − FST). The correlation between the two parameter matrices was regressed using a Mantel test, with the significance estimated by P value, and the regression coefficient (R) and the mean correlation coefficient (RXY) performed over 999 random permutations.Isolation by distance was analyzed in GenALEX 6.502 to detect the relationship between genetic and geographic distances40 was used to test whether the populations experienced a recent bottleneck or expansion. The observed heterozygosity was compared with the expected heterozygosity under a two-phase mutation model (TPM) recommended for microsatellite data68 and the step-wise-mutation model (SMM) . The significance of excess heterozygosity was assessed using a Wilcoxon test (5000 iterations).Bottleneck version 1.2.02Supplementary Fig. S1; Supplementary Table S1; Supplementary Table S2; Supplementary Table S3


Saccostrea echinata) has considerable potential for aquaculture throughout the tropics. Previous attempts to farm S. echinata failed due to an insufficient supply of wild spat; however, the prospect of hatchery-based aquaculture has stimulated renewed interest, and small-scale farming is underway across northern Australia and in New Caledonia. The absence of knowledge surrounding the population genetic structure of this species has raised concerns about the genetic impacts of this emerging aquaculture industry. This study is the first to examine population genetics of S. echinata and employs both mitochondrial cytochrome c oxidase subunit I gene (COI) and single nucleotide polymorphism (SNP) markers.The black-lip rock oyster . Mitochondrial COI analyses also revealed a ‘star-like’ haplotype network, and significant and negative neutrality tests  support a recent population expansion after a bottleneck. The SNP analyses showed significant levels of population subdivision and four genetic clusters were identified: (1) the Noumea  sample location; (2) the Bowen  sample location, and remaining sample locations in the Northern Territory, Australia (n = 8) were differentiated into two genetic clusters. These occurred at either side of the Wessel Islands and were termed (3) ‘west’ and (4) ‘east’ clusters, and two migrant individuals were detected between them. The SNP data showed a significant positive correlation between genetic and geographic distance  and supported isolation by distance. Three candidate adaptive SNPs were identified as occurring within known genes and gene ontology was well described for the sex peptide receptor gene.The mitochondrial COI data set included 273 sequences of 594 base pair length, which comprised 74 haplotypes. The SNP data set included 27,887 filtered SNPs for 272 oysters and of these 31 SNPs were identified as candidate adaptive loci. Data from the mitochondrial COI analyses, supports a broad tropical Indo-Pacific distribution of S. echinata, suggesting that management of wild and farmed stocks should be based upon multiple management units. This research has made information on population genetic structure and connectivity available for a new aquaculture species.Data supports the existence of genetically distinct populations of The online version of this article (10.1186/s12864-019-6052-z) contains supplementary material, which is available to authorized users. For farmed marine species, understanding population structure and how populations respond to the environment can inform broodstock selection, translocation boundaries, and aquaculture induced evolution , 2. PoteMany methods exist to investigate population genetics, and those such as mitochondrial genes provide useful tools for identifying and improving our understanding of relationships among species , 9. MoreCrassostrea corteziensis in the Gulf of California where allozyme analyses revealed a single panmictic population, possessing high genetic diversity [Crassostrea virginica throughout the Gulf of Mexico, despite its potential for high gene flow [Crassostrea iredalei throughout Malaysia [Ostrea edulis along the European coast [Marine bivalves are characterised by large population sizes, high fecundity, and planktonic larvae with considerable dispersal potential , 16, 17.iversity . Howeveriversity –22. For ene flow . SimilarMalaysia  and Ostran coast . TherefoSaccostrea echinata , is a tropical marine bivalve that is reported to have broad geographic distribution throughout the Indo-Pacific [S. echinata due to the success of small-scale farms (< 1 t per annum) in northern Australia, eastern Australia, and New Caledonia (JR Collison pers. comm. 2018). Production based on wild seed supply has been a bottleneck for the industry [S. echinata are planktonic and development occurs over approximately 21 days in the hatchery, after which metamorphosis and settlement takes place [S. echinata populations, before commencement of commercial-scale aquaculture, would provide biological information upon which responsible management and hatchery production could be based. This study aims to fill this knowledge gap by analysing both mitochondrial and nuclear DNA markers to assess the population genetic structure and the neutral and adaptive genetic diversity of S. echinata across northern Australia.The black-lip rock oyster, -Pacific . Researcindustry , and thiindustry , 29. Lares place . Howeveres place , 30 and es place , 24 popuThe mitochondrial cytochrome c oxidase subunit I gene (COI) data set comprised 273 sequences of 594 base pair (bp) length, which contained 74 different haplotypes. Haplotype and nucleotide diversities were high  and similar among all sample locations except Bowen, which were markedly lower   as significantly different from all other populations . Likewise, the haplotype network indicates lack of population genetic structure between populations and does not support geographical haplotype groups  loci from 282 individuals were identified. The data set was then filtered to 27,887 SNPs from 272 individuals which were used for further analyses Table . BAYESCAThe number of alleles and the allelic richness were similar among localities; the number of alleles ranged from 32,023–45,861  and 37–55 (candidate adaptive), and the allelic richness ranged from 1.083–1.444  and 1.130–1.851 (candidate adaptive). Bowen had the lowest number of alleles, with 27,585  and 28 (candidate adaptive), and an allelic richness of 0.972  and 0.892 (candidate adaptive) .While both neutral and candidate adaptive SNPs detected population structure between sampling locations, the neutral loci detected greater differentiation Fig. a–f. DiscIndividuals were assigned to their region of origin with very high success; 98.6 and 100% of individuals were correctly assigned to population of origin, with both 10,000 SNP data sets. Two migrant individuals were detected and both were from the west population, specifically the Mooroongga sample location.2350 is situated in the gene Kmt5a, which is required for cell proliferation, probably by contributing to the maintenance of higher-order structure of DNA during mitosis; (2) SNP 18035 is situated in the gene FAXC that may play a role in neural, axonal development; and (3) SNP 34199 which is situated in the sex peptide receptor (SPR) gene. The SPR gene had the most well-described gene ontology annotation terms and has been reported to be involved in controlling reproductive and sleep behaviours in fruit flies (Drosophila melanogaster) [The alignment of the 31 candidate sequences to the complete black-lip rock oyster transcriptome resulted in 19 hits. Three of these were successfully identified as belonging to known genes and are presented in Table S. echinata and it utilises both mitochondrial and nuclear DNA markers. Results support the existence of genetically distinct populations of S. echinata, and this has implications for the management of wild and farmed stocks of this new aquaculture species, that should be considered as multiple management units.This is the first study to investigate the population genetics of S. echinata; from at least Taketomi Island in Japan, to Noumea in New Caledonia, and across northern Australia; from Cone Bay in Western Australia, to Bowen in Queensland. Few studies have employed genetic data to assist in investigating the distribution of tropical oyster species within the Indo-Pacific region. The tropical rock oyster, C. iredalei, has been confirmed to occur throughout Malaysia, based on mitochondrial COI analyses [Pinctada margaritifera, which confirmed broad Indo-Pacific distribution, based on SNP analyses [S. echinata is important for countries interested in aquaculture of this species, particularly those interested in hatchery production of spat, because culture conditions and techniques are species-specific [Crassostrea gigas in Japan [C. virginica in America [C. iredalei [Anomalocardia brasiliana [Cellana talcosa [Results from the mitochondrial COI analyses, are consistent with those of McDougall , and theanalyses . Similaranalyses . Geneticspecific , 38. A rspecific  highlighspecific , 41. Higin Japan , and hig America . In the iredalei , the claasiliana , and the talcosa . These s talcosa , 45 have talcosa , to prov talcosa , 10.S. echinata in this study did not support geographical haplotype groups. The ‘star-like’ haplotype network and congruence between Tajima’s D and Fu’s Fs overall negative and significant P-values suggest a recent population expansion after a bottleneck [Relatively low haplotype and nucleotide diversity indices detected in Bowen samples may be due to unintentional sampling bias. These individuals were collected from an oyster farm and it is possible that they may have been collected from a single or few cohort(s). It is also probable that the Bowen population is close to the edge of the species range and many taxa show a general decline in genetic diversity towards range margins; a pattern known as the core-periphery hypotheses , 47, 48.ttleneck , 49.S. echinata shown by mitochondrial COI analyses, the SNP analyses showed high levels of population subdivision. Greater differentiation of nuclear SNP markers, compared with mitochondrial COI markers, was similarly reported by Varney et al. [C. virginica, in the Gulf of Mexico. Mitochondrial DNA analysis is a useful first-pass marker for investigating genetic structure, however, it is not a suitable marker for the detection of fine spatial genetic structure [In contrast to the lack of structure between sampled populations of y et al.  in a poptructure , and it tructure , such astructure –55.S. echinata populations sampled do not belong to a single panmictic unit. At a broad scale, S. echinata populations in Bowen and Noumea displayed substantial and significant divergence from all other populations. Within the Northern Territory, Australia, low but significant differentiation was observed among some of the sample locations and DAPC analyses identified two genetic clusters in this region (here termed ‘west’ and ‘east’). Some mixing was detected, by the DAPC analyses, between the west and east clusters in the Northern Territory, which was further confirmed by the detection of two migrant individuals at Mooroongga, which is part of the west cluster, that were genetically most similar to the Nhulunbuy sample location, which is part of the east cluster. Both the structure shown in the DAPC analyses and a significant positive correlation between genetic and geographic distance support isolation by distance occurring in sampled S. echinata populations.In the current study, the SNP analyses clearly showed that the S. echinata larval dispersal and thus gene flow. Furthermore, this island chain would have been a land barrier around seven thousand years ago, when sea levels were lower, which may be reflected in the genetic clusters identified [Holothuria scabra, in northern Australia, Gardner et al. [H. scabra larvae, which have a similar larval duration to larvae of S. echinata [S. echinata throughout the Gulf of Carpentaria.Distinct genetic clusters within the Northern Territory suggest that larval dispersal is limited to within these two regions. These two clusters occur either side of the Wessel Islands, a chain of small islands extending 120 km northeast from the Napier Peninsula Fig. , that arentified . In a sir et al.  reportedechinata , 59. Garechinata . The conechinata  and moreS. echinata, three candidate adaptive SNPs were successfully identified as belonging to known genes, and gene ontology was well described for the SPR gene. The SPR gene has been studied in fruit flies (D. melanogaster) and has been shown to be important for determining reproductive behaviour [S. echinata populations studied, such as differences in reproductive behaviours (e.g. the timing of reproductive cycles or of spawning). Further research is required to better understand the role of the SPR gene in relation to seascape genomics of S. echinata.When undertaking population genetic analyses with SNPs it is important to consider both neutral markers, which provide useful information about neutral evolutionary processes, and candidate adaptive markers which are more likely to display signatures of selection . In the ehaviour , 61, 62 ehaviour . A molecehaviour . The SPRHaliotis laevigata) [Crassostrea spp.) [Gadus morhua) [Pinctada margaritifera) [S. echinata. This suggests that management of wild and farmed S. echinata stocks should be based upon multiple management units, and new areas interested in farming this species should undergo genetic stock assessments to determine optimal management practises. Within the Northern Territory, Australia where most of the sample locations in this study occur, and where S. echinata aquaculture development is focused, two genetically distinct clusters exist, which may be differentially adapted to local environmental conditions. It is recommended that these distinct clusters be considered as management units; when broodstock are being selected for hatchery production, for the translocation of wild or hatchery-produced spat, and for any translocations of farmed stocks.Genetic information is an important part of fisheries and aquaculture management policy and has been used to identify management units for many commercially important species, including green-lip abalone (evigata) , 63, manea spp.) , Atlanti morhua) , and blaitifera) . Given tS. echinata across northern Australia has made data on population genetic structure and connectivity available. This study confirmed that despite the potential for high levels of gene flow, S. echinata do not belong to a single panmictic unit. The development of management policy for culture practices and translocation of farmed oysters will become increasingly important as hatchery production develops and aquaculture operations expand. Furthermore, this study has provided high quality genome-wide SNP marker sets that can be utilised for future genetic research, such as the use of genetics in stock improvements (e.g. selective breeding programs), and to improve understanding of locally important adaptations in wild oyster populations.Use of both mitochondrial and nuclear DNA markers to assess the population genetics of 2 of adductor muscle was excised from live oysters and stored in 96% ethanol in an Eppendorf tube. Exceptions to this method include samples collected from Bowen, Australia  and one in New Caledonia  protocol. The ‘Folmer’ primers [http://www.geneious.com/) and trimmed  and nucleotide (π) diversities were calculated using DnaSP 6.12.01 [D and Fu’s Fs neutrality tests were performed in the program ARLEQUIN 3.5.2.2 [ST estimates of haplotype frequency between localities were also calculated using ARLEQUIN 3.5.2.2. To determine whether an isolation by distance pattern was prevalent in S. echinata, a genetic distance (ϕST) matrix was compared with a geographic distance (km) matrix using the R package ade4 [S. echinata from previous studies (n = 21) [S. echinata were also obtained from the Government of Western Australia (n = 4) from the sampling site Cone Bay  , 71 wereDouble-digest restriction site-associated DNA (ddRAD) libraries were constructed following a protocol modified from Peterson et al. . Brieflyprocess_radtags program in STACKS 1.47 [n = 2) and a minimum stack depth of three (m = 3) . Then stacks were aligned de novo with each other to create a catalogue of putative RAD tags ). In the population module of STACKS, and following consecutive filtering steps, SNPs were retained in at least 70% of the individuals and 50% of the locations, had a minor allele frequency of at least 10%, and heterozygosity < 0.5. Analyses were restricted to one random SNP per locus (using the --write_random_snp option in the populations module). SNPs with more than 70% of missing data and individuals with more than 50% missing data were also eliminated using VCFtools [Libraries were demultiplexed using the CKS 1.47 . Reads wVCFtools . Detailshree m =   and expected heterozygosity (HE) in each locality, as well as F statistics were calculated using GenoDive 2.0 [A) and allelic richness (AR) were calculated with the R packages PopGenReport and hierfstat, respectively [NE) and 95% confidence intervals were estimated using the software NeEstimator v.2.1 using the linkage disequilibrium method [adegenet [S. echinata, a genetic distance (FST) matrix was compared with a geographic distance (km) matrix using the R package ade4 [To identify SNPs potentially under neutral and adaptive selection a combination of two outlier detection approaches were used; BAYESCAN 2.1 and  package . OutlierDive 2.0 . The numectively . Effectim method  for neutadegenet . To deteage ade4 . GeograpFST ~ 0.04) [FST values between the two population clusters was 0.03 for both data sets of 10,000 randomly chosen SNPs. In a given genotype, when the observed frequency of any allele was zero , the frequency of this allele was replaced by a fixed value of 0.005 as recommended by Paetkau et al. [LH) inferior to this threshold are thus defined as putative migrants.Assignment tests were performed in GenoDive 2.0  on two d ~ 0.04) . Pairwisu et al. , to avoiu et al.  for 5000u et al.  algorithu et al. . IndividSaccostrea lineage J by McDougall [− 6 and the highest ‘Grade’  for each hit were applied to the analyses. This yielded three candidate SNPs successfully identified as belonging to known genes, contained within the UniProtKB/ Swiss-Prot database [The basic local alignment search tool (BLAST) function, incorporated in Geneious 11.1.5, was used to BLAST the 31 candidate adaptive SNPs against the complete, annotated transcriptome of the black-lip rock oyster, referred to as cDougall . A minimdatabase . Gene onAdditional file 1:This file contains a table of Kimura 2-parameter genetic distances in mitochondrial COI sequence data. (DOCX 13 kb)Additional file 2:Saccostrea COI sequences. Bootstrap values are given on branches, and the scale bar indicates the number of substitutions per site. The clades containing Striostrea, Magallana and Crassostrea COI sequences are used as outgroups. Lineages have been designated (where possible) following Lam and Morton [Phylogenetic analysis of d Morton  and Sekid Morton . This file contain mitochondrial COI sequence data accession numbers for 273 individuals of Additional file 4:S. echinata at 27,887 genome-wide SNPs. (ZIP 12536 kb)This VCF file contains genotypic data of 272 individuals of Additional file 5:This file includes a list of identifying numbers and sequences for the 31 candidate adaptive SNPs. (DOCX 14 kb)


Drosophila mediopunctata populations from eight forest remnants dispersed on two adjacent geomorphological regions, which are physiognomic and climatically quite distinct. Microsatellite data of inversion‐free chromosomes  indicate low structuration among populations suggesting that they were panmictic and greatly influenced by gene flow. Moreover, significant differences in chromosomal inversion frequencies (adaptive genetic marker) among populations and their correlations with climatic and geographical variables indicate that genetic divergence among populations could be an adaptive response to their environment. Nonetheless, we observed a significant difference in inversion frequencies of a population in two consecutive years that may be associated with edge and demographic effects. Also, it may be reflecting seasonal changes of inversion frequencies influenced by great temperature variation due to edge effects. Moreover, the forest fragment size does not affect genetic variation of neutral markers. Our data indicate that despite oscillations in chromosomal inversion frequencies, D. mediopunctata populations from Brazilian Atlantic Forest and their divergence may be driven by adaptive factors to local differences, perhaps because it is a small flying insect easily carried by the wind increasing its migration rates.Comparison of adaptive and neutral genetic markers is a valuable approach to characterize the evolutionary consequences of populations living in environments threatened by anthropogenic disturbances, such as forest fragmentation. Shifts in allele frequencies, low genetic variability, and a small effective population size can be considered clear signs of forest fragmentation effects (due to genetic drift) over natural populations, while adaptive responses correlate with environmental variables. Brazilian Atlantic Forest had its landscape drastically reduced and fragmented. Now, several forest remnants are isolated from each other by urban and crop areas. We sampled  In the adaptive case, we expect populations to be panmictic with low genetic structure (high gene flow) and geographical differentiation of chromosomal inversion frequencies correlated to each GMR. Under the neutral case, the observed difference is a casual oscillation caused by forest fragmentation (genetic drift), and we expect to observe populations highly isolated (great genetic structure and low gene flow), great level of linkage disequilibrium in neutral markers and stochastic shifts in chromosomal inversion frequencies (with no pattern).mN), F‐statistics , and allele frequencies shifts.To test them, we sampled populations in the Campinas Area (Campinas city and Western nearby Capivari town) and in the Eastern Area , chi‐square values, respectively were as follows: PE: χ2 = 5.06, df: 4; p = 0.281; and TE: χ2 = 6.16, df: 2; p = 0.046. The other populations showed significant differences in their inversion frequencies (with Bonferroni correction): CS , CA , and IT .Actually, populations from CS, PE, CA, IT, and TE were sampled at least twice and in different seasons. PE and TE did not show a significant difference in inversion frequencies, after Bonferroni correction . In all cases, for the statistical tests, we did for chromosome inversion frequencies the results remained qualitatively the same.In spite of the variations in chromosome inversion frequencies found in the other two populations (CA and IT), we decided to pool all the samples obtained for each population to carry out the statistical analyses since this seems to introduce a smaller a priori bias. Moreover, and most importantly, all the tests we used in the paper (see below) were robust. We repeated the tests using only cold‐dry season  data, removing hot‐rainy season (Spring–Summer) data; furthermore, we also removed the data from 2010 and 2011, that were atypical years  and www.ciiagro.sp.gov.br .We obtained the geographical variables  under a microscope, identified landmarks such as polytene chromosome bands or puffs and compared them to chromosomal inversion breakpoints mapped in chromosome II  were pooled as “Other” . MMRR is essentially a multiple linear regression method applied to matrices Wang, . It may STF of the inversion frequencies using Arlequin 3.5  versus genetic data ; Itatiaia ; Colinas do Atibaia ; and three on the Peripheral Depression—Capivari ; Santa Genebra ; and Costa e Silva .We also used the samples of six populations that were still available for microsatellite genotyping in the two distinct geomorphological regions (GMRs): three on the Atlantic Plateau—Teresópolis .We extracted genomic DNA according to procedures described by Aljanabi and Martinez . We usedWe used the forward primer for each locus labeled with a M13 fluorescent‐sequence (5′‐TGTAAAACGACGGCCAGT‐3′) at the 5′ end for genotyping : initial denaturation at 94°C for 4 min; followed by 10 cycles of 94°C/30 s, annealing temperature/1 min and 72°C/1 min; followed by 25 cycles of 89°C/30 s, annealing temperature/1 min, 72°C/1 min; and a final extension at 72°C/30 min. We resolved PCR products in an ABI PRISM 3,500‐XL automated sequencer (Applied Biosystems) using GeneScan 600 Liz (Applied Biosystems) as a molecular weight marker. We read genotypes using GeneMarker v.2.2 (SoftGenetics) with manual checking.2.5AN), mean effective number of alleles (EN) and allele frequencies. Also, we estimated expected heterozygosity of microsatellite loci with Arlequin 3.5.  with Arlequin 3.5  by private allele method, implemented on Genepop on web  versus genetic data , Santa Genebra (SG), and Costa e Silva 2007 (CS07); cluster 2—Parque Ecológico (PE), Colinas do Atibaia (CA), Costa e Silva 2008 (CS08); cluster 3—Juiz de Fora (JF), Itatiaia (IT), and Teresópolis (TE). The last two groups are separated from the first, but this division has no support. Nevertheless, they reflect quite well their location in the two geomorphological regions of the area: Peripheral Depression and Atlantic Plateau; with the exception of the Costa e Silva population (CS07 and CS08). In 2007 (CS07), this population grouped with cluster 1; and in 2008 (CS08), it grouped with cluster 2 . These estimates showed that even controlling the geographical distance, the environmental factor  was still significant.Multiple matrix regression with randomization analysis showed a clear result when examining the spatial variation of chromosome inversion frequencies. We observed that geographical (geodesic) and environmental (GMRs) distances were significantly associated with chromosomal variation . Cluster 1 grouped only populations from Campinas Area which lied in Peripheral Depression  and they were not heterogeneous . Similarly, cluster 2 is not heterogeneous . However, populations only in forest fragments near Campinas area (clusters 1 and 2) were highly significantly heterogeneous . The clade with cluster 2 and cluster 3 which grouped some populations from Campinas Area  and from Eastern Samples  was highly heterogeneous ; although cluster 3 is also heterogeneous .Inversion frequency estimates for all populations showed consistent patterns with cluster analysis Table . PopulatSTF analysis of chromosomal inversion genetic distance revealed that more than 91% of the total variation was among individuals within populations with moderate levels of genetic structure among all populations . AMOVA also showed that 5% of the total variation can be explained by the structuration between the GMRs (RTF = 0.049), while 4% of total variation explained by the structuration among populations within GMRs , while OT was correlated with area . However, after applying Bonferroni procedure, only correlations between latitude, longitude, and altitude with inversions DI and DS+DP remained significant. Finally, inversions DA and DI showed similar patterns in their correlations with meteorological and geographical variables, while DS+DP showed the opposite pattern. For example, the correlations of DA and DI with temperature were, respectively, r = −0.81, p = 0.009; and r = −0.86, p = 0.003; while, DS+DP was r = 0.86, p = 0.003. However, when Bonferroni procedures are applied, no correlation with temperature remained significant.We examined the correlations between inversion frequencies and latitude, longitude, altitude, area, average monthly mean temperature, and annual sum of monthly precipitation of the collecting sites Table . We obseWe also tested independently the correlations between frequencies of inversions in the second chromosome proximal region, using only wild male karyotypes, with the same meteorological and geographical variables mentioned above (data not shown). The general pattern was consistent with the distal inversions mentioned above.3.3Costa e Silva (CS07 and CS08), Parque Ecológico (PE) and Colinas do Atibaia (CA) are distant less than 20 km from each other. We sampled these populations in different occasions  to test their genetic resilience . For each one, we performed a contingency chi‐squared test to detect variation among collections and no significant differences were observed for PE and CA populations . However, CS07 and CS08 were statistically different .Populations from 3.4AN = 15.2) and private alleles (AP = 2.2), while TE population showed the smallest mean number of alleles (AN = 13.3) and of private alleles (AP = 0.6). Mean expected heterozygosity (eH) ranged from 0.82 in IT to 0.86 in SG.We observed great variability of microsatellite markers Table , with 31LD) between pairs of loci for every population. Among 31 associations, only four remained significant after applying Bonferroni procedures: three in TE population  and one association in SG population .We analyzed linkage disequilibrium (ISF) values for every locus and every population . Population CS07 showed eight loci . TE showed six loci . Populations CA  and CV  showed four loci. Finally, Itatiaia showed only one locus with deviation (Dmed119). Out of 72 tests, only one locus (Dmed119) showed deviation of Hardy–Weinberg equilibrium in all six populations, after applying sequential Bonferroni procedures.We estimated inbreeding coefficient  among these six populations. We estimated genetic differentiation between pairs of populations , while populations most genetically distant were CS07 and CV . We observed no significant differences among hierarchical levels microsatellite‐based AMOVA (Table RTF = 0.006ns).We found relatively low levels of population genetic structure . We observed that geographical (geodesic) and environmental  distances were not associated with microsatellite both for geodesic distance (βGEOG) and ecological distance . These estimates show a clear contrast with the chromosome inversion data.Multiple matrix regression with randomization analysis for microsatellite data detected no effect of spatial variation  along a significant negative correlation with altitude, area, and precipitation . The second most common allele of locus Dmed087 showed the opposite pattern, a significant positive correlation with altitude, area, and precipitation  along a significant negative correlation with latitude and temperature . However, after the application of Bonferroni procedure, no correlation remained significant.In addition, we tested the correlation between meteorological and geographical variables of the collecting sites with the three most frequent alleles for each locus. Among the twelve loci studied, only two showed significant correlations with any geographical variation. The third most common allele of locus Nm = 7.9; while using the STF method was Nm = 11.7. The lowest Nm value found was between CA and SG (Nm = 2.4)—populations distant 15 km from each other—while the highest was between IT and CA (Nm = 6.7)—distant 267 km from each other. Geographically the closest populations are CS and SG with Nm = 5.8, while the most distant are TE and CV with Nm = 3.5. In any case, the number of migrants per generation is high.The estimated number of migrants  among all populations was 4Apart from some beneficial effects over bird guilds  is four times higher than STF revealed by microsatellites (0.022). Dissecting this genetic structure, AMOVA (Table RTF = 0.049) is eight times the non‐significant differentiation found with microsatellites (RTF = 0.006).Our results indicate an overall moderate genetic structure for chromosomal inversions and low genetic structure for microsatellite loci. It is noteworthy that overall VA Table  shows thThe patterns for population structure indicate that the chromosomes may be subject to evolutionary forces of different magnitude. Furthermore, the observed differences in chromosomal inversion polymorphism may be liable to local differentiation, reflecting the action of natural selection.Drosophila birchii. Urban and non‐urban populations of Drosophila subobscura from Serbia had their genetic structure examined, using chromosome inversions as markers. Despite a strong anthropogenic influence on the population from Belgrade, it did not show any loss in its inversion polymorphisms, as well as in its population size; therefore, this population does not seem to suffer the negative effects caused by human activity and urbanization  and DS+DP . Now, we observed similar correlation values for the same arrangements and average annual temperature of each location—negative for DA (r = −0.81) and positive for DS+DP (r = 0.86). Surprisingly, we found a strong and significant correlation between DI and longitude (r = − 0.95) as shown in Table Ananina et al.  previousVariations in genetic polymorphisms concomitant with environmental gradients can be considered signs of local adaptation which may lead to population divergence (Wellenreuther et al., In summary, our results suggest that, with few exceptions, differences in inversion frequencies of fragmented populations can be maintained according to their geomorphological origin in spite of the effects of gene flow and genetic drift.None.Drosophila mediopunctata natural populations, analyzed the data, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper. Rafael E. S. Penha carried out microsatellite genotyping and genetic structure analysis, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper. Silvia H. Sofia contributed with reagents/materials/analysis tools, wrote the paper, and reviewed drafts of the paper. Louis B. Klaczko participated of all collecting occasions, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper, conceived general project.Marcos R.D. Batista conceived general project, participated of all collecting occasions, sorted and karyotyped https://doi.org/10.5061/dryad.9r4r7p1.Data available at Dryad:  Click here for additional data file.


Pinus mugo, P. uliginosa and P. uncinata across their European distributions. Simultaneously, mitochondrial DNA markers, which are maternally inherited in pines and distributed by seeds at short geographic distance, were used to assess genetic relationships of the focal populations and taxa. The majority of nuclear loci showed homogenous patterns of variation between the taxa due to a high number of shared SNPs and haplotypes, similar levels of polymorphism, and low net divergence. However, against this common genetic background and an overall low population structure within taxa at mitochondrial markers, we identified several genes showing signatures of selection, accompanied by significant intra- and interspecific divergence. Our results indicate that loci involved in species divergence may be involved in intraspecific local adaptation.Efforts to detect loci under selection in plants have mostly focussed on single species. However, assuming that intraspecific divergence may lead to speciation, comparisons of genetic variation within and among recently diverged taxa can help to locate such genes. In this study, coalescent and outlier detection methods were used to assess nucleotide polymorphism and divergence at 79 nuclear gene fragments (1212 SNPs) in 16 populations  of the closely related, but phenotypically and ecologically distinct, pine taxa The online version of this article (10.1007/s11295-018-1296-3) contains supplementary material, which is available to authorized users. Identifying the molecular basis of evolution is a major challenge in biology. So far, efforts to detect loci under selection in plants have mostly focussed on single species. However, assuming that selection acting on variation within a species may eventually lead to speciation, a between-species comparative approach can improve the power to detect genes involved in adaptation , P. uncinata (mountain pine) and P. uliginosa (peat-bog pine). These taxa are especially suitable for comparative analyses of the pattern of polymorphism and divergence as they form a monophyletic group within Pinaceae  and molecular markers  from 16 populations, we evaluated population structure, levels of polymorphism and divergence, and tested for the signature of selection at inter- and intraspecific levels. We asked if the genes involved in genetic divergence among taxa (i.e. speciation) were also implicated in local adaptation within taxa. We also assessed whether the same genes were under selection in different taxa, which would suggest a common role in adaptive processes.In this study, we looked at the patterns of genetic variation within and among the focal taxa in populations’ representative of their distribution range in Europe to search for patterns of divergence and local adaptation in a set of orthologous genomic regions. Using a set of mitochondrial DNA markers, nucleotide sequence data from 79 gene fragments and a sample of 153 trees , Carpathians (eastern and southern) and Balkans (Pirin and Durmitor Mts). A single P. mugo population from Italy was excluded from the group comparisons. No regional groups were constructed for P. uliginosa or P. uncinata. In total, 153 samples were analysed, comprising ten individuals from most locations except for PM14 and PUG2 (N = 9) and PUG3 (N = 5)  Table . SampledP. taeda  fragments including P11 . Standard amplification procedures were used with initial denaturation at 94 °C for 3 min, followed by 35 cycles with 30 s denaturation at 94 °C, 30 s annealing at 60 °C for nuclear loci and 57 °C for mtDNA regions for 1 min, 30 s extension at 72 °C and a final 5-min extension at 72 °C. PCR fragments were purified using Exonuclease I-Shrimp Alkaline Phosphatase enzymatic treatment. About 20 ng of PCR product was used as a template in 10 μl Sanger sequencing reactions with the Big Dye Terminator DNA Sequencing Kit v3.1 (Applied Biosystems). Multilocus haplotypes were determined by direct sequencing of haploid DNA using 3730xl DNA Analyzer (Applied Biosystems). CodonCode Aligner (Codon Code Corporation) was used to edit and align sequences. Sequence data at nuclear genes are deposited in the NCBI repository , photoperiodic response and cellular transport Table . PCR priry Table .W, Watterson’s ρ/θ) was calculated to estimate their relative influence on patterns of diversity in each taxon and in regional groups. The non-linear least squares estimate of ρ  was fitted by the nls-function implemented in R (www.r-project.org) based on the correlation coefficient r2 between polymorphic informative sites and the distance in base pairs (bp) between sites. Locus-by-locus estimates of net divergence between taxa (Nei P. taeda were obtained from GenBank for outgroup comparisons. The number of haplotypes (N) and haplotype diversity (Hd) were computed for each gene using DnaSP v5  between two sequences Nei . Multilotaxa Nei , and thetaxa Nei . SequencmtDNA sites was calculated and used in principal coordinate analysis (PCoA) to show genetic relationships between populations and taxa. Genetic relationships between samples at nuclear loci were explored using BAPS 6.0  based on the mean net distance between populations across all SNPs, estimated with the Jukes-Cantor nucleotide substitution model with pairwise deletion. The hierarchical distribution of multilocus genetic variation among taxa, regional groups and populations was estimated using an analysis of molecular variance (AMOVA) with Arlequin v.3.5  were calculated based on the distribution of p values for the set of tests conducted  was greater than 0.05. A sample size of 5000 was used, with thinning intervals of 10, and 20 pilot runs each of 5000, default prior odds of 10 and burn-in of 50,000. Finally, genes that showed evidence of selection within taxa  were compared with those that showed significant divergence among taxa (outlier detection among taxa) to identify parallel signatures of adaptation at different scales . Genes that showed significant deviation from neutrality, significant between taxon divergence and a signature of selection within taxa (considering both haplotypes and SNPs) were identified.First, genetic differentiation in pairwise comparisons within and between taxa was studied locus-by-locus at both haplotype and SNP/indel level. Significance was estimated by 1000 permutations of the samples between populations, regional groups and taxa using Arlequin v.3.5. The false discovery rate (FDR) adjustment for multiple testing was conducted using the tot = 0.0039–0.0047 and multilocus silent theta θsil = 0.0049–0.0064 indicated no significant difference in the amount of nucleotide diversity between taxa or regional groups  relative to P. mugo (ρ/θ = 5.4) and P. uncinata (ρ/θ = 3.1), respectively. Variation in net divergence found at individual loci ranged from 0 to 0.0062  (Table . There were no fixed differences between the taxa at any locus and they shared 59% (P. mugo vs. P. uncinata), 63% (P. mugo vs. P. uliginosa) and 69% (Pinus uliginosa vs. P uncinata) of the polymorphic sites (Table Hd = 0.59–0.65) and for regional groups of populations (Hd = 0.54–0.60)  Table . There wes Table . Unique es Table . The avemtDNA loci provided a set of 13 SNPs resulting in 20 haplotypes that were predominantly partitioned between P. mugo and P. uliginosa as a group, vs. P. uncinata  . There was low but significant differentiation among regional groups in P. mugo .In a hierarchical AMOVA, 11% of the variation was due to differentiation between taxa Table . At the ta Table . SignifiD for all taxa , regional groups of P. mugo and most individual populations except for P. uncinata . Some of the highly diverged polymorphic sites also showed differentiation in frequency spectra within taxa, compared to the majority of SNPs  and 2 in P. uliginosa (including glutamate transporter and DNA repair helicase) were significantly differentiated both within and among taxa. These genes are involved in signal transduction, transport and cellular metabolism and appear to be of high importance in both speciation and intraspecific local adaptation y Tables  and S13.3 Mbp) and low differentiation at RAPD markers, chloroplast microsatellite loci and nuclear genes  and similar net divergence from P. taeda (0.023). This genetic similarity is likely due to recent speciation history , genome size  and “intermediate” biometric characteristics (needle and cone traits) as compared to other closely related pine taxa  , due to accumulation of new mutations and loss of shared ancestral polymorphism Nei . TherefoP. mugo and P. uliginosa populations at mtDNA loci. Some evidence of differentiation was found in P. uncinata with a single outlier population from Andorra. In all taxa, overall population structure at nuclear genes was weak, with 93–98% of variation present within populations. The generally low among-population differentiation at neutral nuclear markers found in conifers is usually attributed to wind pollination and efficient gene flow over large geographical distances. Patterns of nucleotide variation also suggested population size expansion. An excess of low-frequency mutations (i.e. negative Tajima’s D) and very similar levels of nucleotide polymorphism were observed in each taxon and most individual populations. Given the geographical isolation of the populations, the overall genetic similarity between populations could be due to shared recolonization history, recent fragmentation of populations or efficient long range, primarily pollen-mediated gene flow , whilst more genes showed taxon-specific departures from neutrality