Quercus gilva, restricted to a few habitats on Jeju Island, and compared them with the southern Kyushu populations. We also evaluated their evolutionary potential and conservation value. The genetic diversity and structure were analyzed using 40 polymorphic microsatellite markers developed in this study. Ecological Niche Modeling (ENM) has been employed to develop our insights, which can be inferred from historical distribution changes. Contrary to our expectations, we detected a similar level of genetic diversity in the Jeju populations, comparable to that of the southern Kyushu populations, which have been regarded as long-term glacial refugia with a high genetic variability of East Asian evergreen trees. We found no signatures of recent bottlenecks in the Jeju populations. The results of STRUCTURE, neighbor-joining phylogeny, and Principal Coordinate Analysis (PCoA) with a significant barrier clearly demonstrated that the Jeju and Kyushu regions are genetically distinct. However, ENM showed that the probability value for the distribution of the trees on Jeju Island during the Last Glacial Maximum (LGM) converge was zero. In consideration of these results, we hypothesize that independent massive postglacial colonization from a separate large genetic source, other than Kyushu, could have led to the current genetic diversity of Jeju Island. Therefore, we suggest that the Jeju populations deserve to be separately managed and designated as a level of management unit (MU). These findings improve our understanding of the paleovegetation of East Asian evergreen forests, and the microevolution of oaks.Jeju Island is located at a marginal edge of the distributional range of East Asian evergreen broad-leaved forests. The low genetic diversity of such edge populations is predicted to have resulted from genetic drift and reduced gene flow when compared to core populations. To test this hypothesis, we examined the levels of genetic diversity of marginal-edge populations of  It is well known that the population genetic structure in extant plants is affected by various factors, including the dispersal ability of pollinators, seed dispersal modes, reproductive systems, and historical migration patterns; the historical range change during Quaternary climatic oscillations is also considered a primary factor ,2,3. AltPeripheral, especially marginal/edge, populations, might reflect genetic impoverishment as a result of genetic drift and reduced gene flow when compared to core populations ,11,12,13The volcanic Jeju Island of South Korea is characterized by its high endemism, unique altitudinal zonation of vegetation, and untouched environments , and thuQuercus gilva Blume (Fagaceae) is a large, ecologically important tree of evergreen broad-leaved forests in East Asia [Q. gilva is widely distributed in East Asian forests [Q. gilva was attempted using RAPD (Random Amplified Polymorphic DNA) [ast Asia . Althoug forests ,24, its  forests  and logg forests . The pop forests ) and dis forests . As of 2hic DNA)  and ISSRhic DNA)  analysishic DNA) ,31,32.Fossils and pollen grains could be utilized for unraveling evolutionary clues that contribute to present genetic diversity, but the situation is complicated by historically complex distribution changes ,34. HoweQ. gilva are most closely related to those in Kyushu, Japan, which is geographically adjacent and has a similar establishment history. Therefore, we characterized the genetic compositions of the Q. gilva populations in Jeju Island, located at the disjunctive edge of their distribution range. The genetic diversity was compared to the Kyushu populations, regarded as long-term glacial refugia with a high genetic variability of East Asian warm temperate evergreen broad-leaved trees. The purposes of the present study are (1) to develop a high-resolution and cost-effective polymorphic microsatellite set so that researchers can continue periodic genetic monitoring, (2) to evaluate the evolutionary potential and conservation value of marginal-edge Jeju populations by inferring the history of population establishment, and (3) to provide conservation guidelines for the recovery and management of the threatened Jeju populations. The genetic diversity and structure were analyzed using 40 polymorphic microsatellite markers developed in this study through high-throughput sequencing data. ENM was also employed to examine historical distribution changes.As has been observed in other warm temperate species in East Asia ,6,39, thQ. gilva from three populations in Jeju Island, Korea and three populations in Kyushu, Japan. Since Q. gilva is protected as an endangered species in Korea, we first requested permission from the Ministry of Environment and then proceeded with the material collection. We selected the trees with a diameter at breast height (DBH) of more than 20 cm while maintaining minimal intervals of more than 5 m between individuals. One leaf sample was collected per individual to minimize damage to the species. In Jeju populations, a total of 77 leaves, including 32 from Gueok-ri (k-GU), 27 from Jeoji-ri (k-JJ), and 18 from Seogwang-ri (k-SG), were obtained, with an average of 25.6. In the Kyushu populations, an average of 27 and total of 81 leaf samples were collected from Kitadake, Kumamoto Prefecture , and Aoidake  and Enodake  in Miyazaki Prefecture. Collected leaf samples were stored at −80 °C in a deep freezer at the lab of Biological Education, Chonnam National University until use. Total genomic DNA was extracted from dried leaf samples using the DNeasy Plant mini kit  following the manufacturer’s instructions. The concentration of extracted DNA was determined using Nano-300 , and diluted to 15 ng/μL to obtain the same concentration of template DNA in each sample.We collected a total of 158 leaf samples of Q. gilva, we produced high-throughput sequencing data in a fresh leaf collected from Gueok-ri, Seogwipo-si, JeJu Island, Korea. A voucher specimen was deposited in the herbarium of Chonnam National University (BEC) (Voucher no. LeeQg20180502). A shotgun library construction for DNA sequencing was generated using the Illumina MiSeq platform . According to the method of Cho et al. [In order to develop polymorphic microsatellite markers for o et al. , we deteo et al. . After ao et al. . In the o et al.  in the GTM-500LIZTM Size Standard (Applied Biosystems). Allele sizes and peaks for each sample were determined three times via Peak Scanner software 2 to minimize genotyping errors. We selected 46 polymorphic microsatellite loci with clear, strong peaks for each individual. Then, we tested the remaining 126 individuals from five populations according to the DNA extraction and PCR protocols described above.To assess the polymorphisms for the designed microsatellite loci, we conducted a preliminary PCR analysis with 32 individuals from the Gueok-ri population. PCR amplification was performed with a Veriti 96-well thermal cycler  using 5 μL volumes that were composed of 15 ng of extracted DNA, 2.5 μL Multiplex PCR Master Mix , 0.01 μM forward primer, 0.2 μM reverse primer, and 0.1 μM of the M13 primer (fluorescently labeled). PCR amplification was performed as follows: initial denaturation at 95 °C for 15 min; 35 cycles of denaturation at 95 °C for 30 s, annealing at 56 °C for 1.5 min, and extension at 72 °C for 1 min; a final extension at 72 °C for 10 min. The PCR products were diluted at 1:30, and 1 uL was analyzed on an ABI 3730XL sequencer with GeneScanBefore inferring the genotyping data, we estimated the null allele frequency using INEst  software based on the individual inbreeding model (IIM), which calculates the null allele frequency regardless of the effect of inbreeding . This anNA), the number of private alleles (PA), the private allele rate (Priv), the mean expected heterozygosity (HE), the mean observed heterozygosity (HO), and the fixation index (FIS), calculated using GenAlEx 6.5 [AR) and genetic differentiation among populations (FST) were determined by calculating the overall FIS according to the method of Weir and Cockerham [FST was tested using the log-likelihood (G)-based exact test in FSTAT. To test for departures from Hardy–Weinberg equilibrium (HWE) and linkage equilibrium, we conducted exact tests based on a Markov chain method (1000 permutations), using GENEPOP 4.0 [The summary genetics statistics were calculated at the population and pooled regional population levels. These included the number of alleles  from 1000 iterations for K = 2, using random input orders.To analyze the population structure, we used a Bayesian clustering approach implemented in STRUCTURE 2.3, as calculated from microsatellite markers , using 1ARVESTER . CLUMPP ARVESTER  with theFST values, and measurements of geographic distance between populations. To identify genetic boundaries between populations, we performed a barrier analysis [DA standard genetic distance [Q. gilva, a principal coordinate analysis (PCoA) was conducted by the covariance standardized approach of pairwise Nei’s genetic distances in GenAlEx 6.5.To test for the presence of isolation-by-distance (IBD), we used Mantel tests in GenAlEx 6.5  with 999analysis  based onanalysis  with 100distance  that werdistance . The disdistance . To findQuercus gilva using Maxent 3.4.1 [http://chelsa-climate.org/; [https://www.usgs.gov/land-resources/eros/coastal-changes-and-impacts/gmted2010), and for the LGM from CHELSA. To reconstruct the historical distributions, we utilized three past climate models for LGM: the Community Climate System Model  potential distributions of nt 3.4.1 . Occurrent 3.4.1  and GBIFnt 3.4.1 . We obtant 3.4.1  to reducte.org/; ). We obtte.org/; —from the , the Ea , and th . The total number of reads containing microsatellites identified through the SSR-pipeline was 100,849 reads, including 55,084 reads with dinucleotide motifs, 41,037 reads with trinucleotide motifs, and 4,728 reads with tetranucleotide motifs. Of these, the di-, tri-, and tetranucleotide motifs with planking areas of >100 bp and having repeating units of at least 12, 6, and 6, respectively, were 29,058 reads, 21,424 reads, and 2,562 reads.Q. gilva from Gueok-ri populations in Korea, 46 polymorphic microsatellite markers with clear and strong peaks for each allele were selected (NA) per locus ranged from 2 to 19, with an average of 8.370 alleles per locus. Values for observed heterozygosity (HO) and expected heterozygosity (HE) ranged from 0.044 to 0.918 (mean: 0.616) and from 0.067 to 0.899 (mean: 0.664), respectively (FIS) for each locus ranged from −0.135 to 0.669. The null allele frequency identified by INEst software ranged from 0.0018 to 0.2774. Comparing the genetic diversity (NA and HE) by the locus of di-, tri-, and tetranucleotide motifs, the results were higher in loci with dinucleotide motifs  than with tri-  or tetranucleotide motifs   .Q. gilva.All the developed markers were deposited in in the National Center for Biotechnology Information’s GenBank database . As a reQ. gilva, are shown in Q. gilva populations, the levels of genetic diversity showed no noticeable difference; the number of alleles ranged from 224 to 261 (mean of 244.7); HE ranged from 0.615 (j-NB) to 0.651 (k-SG) (mean of 0.639); AR ranged from 5.201 (j-NB) to 5.940 (j-MY) (mean of 5.726); PA ranged from 4 (k-JJ and j-NB) to 11 (k-GU) (mean of 7); FIS ranged from −0.024 (k-GU) to 0.043 (k-SG) (mean of 0.007). The k-SG population had the highest genetic diversity values, while the j-NB population had the lowest . In the comparison between the Jeju and Kyushu populations, the levels of genetic diversity were almost equivalent, showing only a slight difference in degree depending on the parameters (p > 0.05), as well as a mode shift , in concordance with the clustering results obtained by STRUCTURE . This differentiation was also seen between populations within Jeju Island , and within populations of Kyushu . Therefore, the fact that the highest value of genetic differentiation is from the overall population means that it results from a difference between Jeju Island and Kyushu  (To infer the population structure of  regions . In termTRUCTURE . The priTRUCTURE . The fir regions . Althougd Kyushu b. Additi= 0.025) a.Q. gilva . Previol-cached ,71. TherQ. gilva populations are distributed like shadows along the flow of the present KC as well as the LGM (AR) and private allele rate (Priv) comparable to those of Kyushu populations. Although, such indicators provide a strong possibility for the existence of refugia in this area [Q. gilva. In agreement with our assumption, ENM showed that the probability values for the distribution of the trees on Jeju Island during the LGM converged at zero. East Asian evergreen oaks prefer different habitats depending on the elevation gradient along the mountain slopes. A previous study suggested that Jeju Island was the refugia of Q. acuta [Q. gilva shows a bias towards low-elevation stands, generally forming a community with Q. glauca [Q. acuta occupies the middle of Mt. Halla on Jeju Island (approximately 600 m a.s.l.), while Q. gilva is distributed very close to the southern coastline (average: 168 m a.s.l.). It should be taken into account that the Quaternary climate oscillations caused not only latitudinal changes in the distribution of a given species but also vertical elevation migration [Regardless of the latitude, the distribution of warm temperate evergreen broad-leaved forests in East Asia, such as in Korea, China, and Japan, is clearly related to the flow of the Kuroshio warm current (KC), showing a unique distribution structure ,72,73. T the LGM . Therefohis area ,78,79, wQ. acuta , which oQ. acuta . By comp. glauca . In factigration . During Quercus species frequently dominate the landscape in extensive regions of East Asia, because they are better able to form dense and crowded stands [Q. gilva might have been large enough to weaken the effect of genetic drift. Therefore, we suggest that a massive postglacial colonization, which maintained a high genetic diversity from separately stable and large genetic sources other than Kyushu, could have led to the current genetic diversity of Jeju Island. Further work using additional samples, including from broad areas such as the Ryukyu Islands and Eastern China, and the markers developed in this study might provide a better understanding of the historical migration of the warm temperate evergreen tree Q. gilva in Jeju Island. In particular, how the Jeju populations relate to East Asian populations other than Kyushu populations should be tested.One plausible scenario might be hypothesized for the unusual level of genetic diversity in Jeju Island, i.e., a massive postglacial immigration, demographically independent of Kyushu. Most oak species have common ecological traits, but their distinct adaptability also facilitates domination in such areas. In fact, evergreen d stands ,82. In gQ. gilva that conservation efforts should be focused on prohibiting the large-scale industrial development of the habitat, because large trees are not vulnerable to personal interference, such as overcollection. Thus, first, we recommend that all known habitats be protected in situ by law to prevent further damage. To prepare for inevitable land development, we suggest that ex situ preservation should be preceded by efforts to store good-quality seeds. Finally, if the artificial restoration of habitats is required, note that the source for the Jeju populations is not Kyushu.There are several definitions for determining the levels of CUs, such as Evolutionarily Significant Units (ESUs) and Management Units (MUs), because “high divergence” is too vague a term for practical purposes ,84,85. H


Hormosira banksii) from temperate Australia. Population surveys across ~2,000 km of the species range revealed strong genetic structuring at regional and local scales  reflecting extremely limited gene flow, while common garden experiments  revealed strong site differences in early development and mortality in response to elevated temperature. Embryos from many sites spanning a longitudinal thermal gradient showed suppressed development and increased mortality to elevated water temperatures, but populations originating from warmer and more variable thermal environments tended to be less susceptible to warming. Notably, there was significant local‐scale variation in the thermal responses of embryos within regions which was corroborated by the finding of small‐scale genetic differences. We expect the observed genetic and phenotypic differentiation to lead to uneven responses to warming sea surface temperatures in this important marine foundation species. The study highlights the challenges of predicting species responses to thermal stress and the importance of management strategies that incorporate evolutionary potential for “climate‐proofing” marine ecosystems.Rising ocean temperatures and extreme temperature events have precipitated declines and local extinctions in many marine species globally, but patterns of loss are often uneven across species ranges for reasons that are poorly understood. Knowledge of the extent of local adaptation and gene flow may explain such patterns and help predict future trajectories under scenarios of climate change. We test the extent to which local differentiation in thermal tolerance is influenced by gene flow and local adaptation using a widely distributed intertidal seaweed ( Rising ocean temperatures, increasing acidification, and changing ocean currents are contributing to fundamental and irreversible ecological transformations in marine ecosystems at a global scale  Decaisne is the dominant intertidal macrophyte across temperate Australasia and is an autogenic ecosystem engineer with no functional equivalents . Second, we undertake a common garden experiment to explore spatial variation in thermal responses among populations with different thermal histories by comparing embryo development at different experimental temperatures. Outcomes from these analyses will help determine the role of gene flow and local adaptation in affecting responses of populations to thermal stress. We expected populations under thermal extremes in the sampling range to be phenotypically adapted to those temperature environments, particularly in the presence of low levels of gene flow. Any adaptive changes would produce uneven thermal responses among populations across the species range. We discuss the implications of our results in the context of the future evolutionary potential of H. banksii, and conservation/ restoration approaches that might be considered to catalyze adaptation and recovery processes in light of climate change.In this study, we assessed the potential adaptability of 22.1Hormosira banksii is a perennial, dioecious, habitat‐forming fucoid macroalga with a distribution extending >2,000 km from Albany in Western Australia to Lennox Head in New South Wales on mainland Australia, around Tasmania, the North and South Islands of New Zealand, and some of the smaller offshore islands in southern Australasia , intermediate scale (regions separated by 100s km), and small scale (sites separated by 10s km). We sampled from two rocky‐shore sites within each of nine regions within three states : three regions in each of South Australia, Victoria, and New South Wales .Tissue samples of 2.2.2H. banksii individuals from 26 sites spanning New South Wales, Victoria, and South Australia were genotyped at 10 microsatellite loci previously developed by Bellgrove et al. , and a global estimate of population differentiation (FST) with 95% confidence limits . In order to overcome potential limitations of FST calculations using multiallelic loci  were generated using GenAlEx 6.5 , implemented in the adegenet package for R  and expected (He) heterozygosity were determined using the Excel Microsatellite Toolkit Park,  and deviJombart, , summariK), five independent simulations for K = 1–18 with 100,000 burn‐in and 1,000,000 data iterations were run. Analyses were performed using the admixture model of population structure  with no prior population information included, and allele frequencies set as independent among populations. The most likely K was estimated using Evanno's ΔK  iterations were used following a burn‐in period of 107 and a sampling interval of 500 steps. Chains were compared with a stationary posterior distribution for convergence by performing multiple runs with dispersed starting values. The proportion of individuals that were assigned as migrants (migration rates), and associated 95% confidence intervals (CIs) were estimated among each of the sampling locations.Rates of recent migration were estimated among each of the sampling locations using a Bayesian algorithm implemented in BAYESASS v.3.0.3  were reared under common culture conditions for experimental purposes following the collections outlined in Section 2.3.1. Thermal response experiments were performed by exposing zygotes from each site to three controlled temperature treatments, 15, 18, and 21℃. These temperatures were based on 15 and 18℃ falling within the bounds of annual sea surface temperatures (SST) across all regions, while only sites from the PPB region are exposed to average summer SSTs as high as 21℃ (Table ‐2s‐1) lights on 12:12‐hr light:dark cycle. Petri dishes representing the different sample locations were also randomized within the cabinets.1℃ Table , whereby1℃ Table . Male an1℃ Table . Once st1℃ Table . Twenty https://imagej.net).Embryonic development for each sample location under each temperature treatment was assessed microscopically , with developmental milestones being recorded for 100 individuals per replicate, adapted from Kevekordes and Clayton : fertili2.3.3region  and sites nested within regions . Data from the common garden experiment were then analyzed by partially nested, mixed model (split plot) design ANOVAs with temperature , region , and sites nested within regions . Assumptions of normality and homogeneity of variances were visually checked with box plots and residual plots  analyses examined the effects of temperature for each region separately with a reduced 2‐factor ANOVA design (temperature and site) using the error term from the full model to test the effect of temperature  with Relationships between home site temperature environments and thermal response were estimated by regressing site‐level mean summer sea surface temperatures and mean seasonal variation in sea surface temperatures  for the years 1995–2015) against mean values for each thermal response variable from each site in the 21°C treatment of the common garden experiment.QST–FST comparisons were also performed to determine whether the degree of phenotypic differentiation observed among sites departs from neutral expectations, where QST > FST suggests that quantitative traits show a higher level of differentiation than what would have been expected under the influence of genetic drift, indicative of selection. The R package Pstat  for each thermal response variable for each site in the 21°C treatment , using PST = c/h2σ2b/(c/h2σ2b + 2σ2w), where σ2b and σ2w are the respective phenotypic variances between and within groups of populations, c is an estimate of the proportion of the total variance due to additive genetic effects across populations, and h2 is narrow‐sense heritability, the proportion of phenotypic variance due to additive genetic effects  for these sites. Closer inspection indicated that a single locus influenced these deviations for site LOB, while several different loci influenced deviations for sites FLW and POR, suggesting caution when interpreting estimates of differentiation involving these sites.Across the 10 microsatellite loci and 18 sample locations, we detected a total of fifty‐one alleles , with a mean of 6.0 alleles per locus (range 4–8). Levels of genetic diversity  were largely consistent across sites over all loci and heterozygosity, with a mean allelic richness of 2.59 (range 2.16–3.00) and a mean observed heterozygosity of 0.41  = 0.20–0.29; Dest = 0.29; 95% CI = 0.17–0.31] indicating limited gene flow between sampling sites. Out of 153 pairwise population comparisons of FST, only two did not differ significantly from zero, reflecting restricted gene flow among regions and most sites within regions , and 16% of the variance due to differences among sites within regions . The relationship between genetic and geographic distance . These analyses were repeated for New South Wales (NSW), Victoria (VIC), and South Australia (SA) separately, with only Victorian sites exhibiting significant isolation by distance .We detected strong genetic structure among sites with global estimates of e Figure  suggesteK = 3; Figure K = 3) corresponding with the Central Coast, Sydney, and South Coast regions. Similarly, significant regional differences were observed in SA where individuals were assigned to three population clusters (ΔK = 3) corresponding with the Fleurieu Peninsula, Yorke Peninsula, and Eyre Peninsula regions. Regional genetic structuring was less evident in Victoria where two population clusters were determined (ΔK = 2), but not reflecting an obvious geographic pattern. We expect this is likely due to comparatively lower level of genetic differentiation among Victorian sample locations, and the limited ability of STRUCTURE to resolve fine‐scale patterns of genetic structure  of the microsatellite variation Figure . When alResults from the Bayesian migration analyses indicated limited migration among sites within the last three generations Table . Estimat3.23.2.1SE: 92.7 ± 0.98%, N = 81 pooling across sites; Figure F = 5.08; p = .051) and no significant difference among sites within regions  = 1.09; p = .377) at the beginning of the experiment. This was expected as all gamete mixes were initially prepared under common temperatures (15°C), where fertilization was expected to be largely complete within minutes ; F = 0.77; p = .685) but not among regions  = 8.58; p = .002). There was no significant difference in the percentage of mature embryos among temperature treatments for sites from the PPB region  = 2.352; p = .137; Figure p < .05; Figure temperature; F = 13.91; p = .001; Tukey's HSD p < .05 for all pairwise comparisons); this pattern was consistent across sites within regions (ANOVA temperature × site(region); F = 1.66; p = .082) and among regions  = 2.35; p = .114; Figure The response of developing embryos to different temperature treatments was complex and variable among sites and regions. The percentage of mature embryos at day 7 (>4 cell divisions and presence of rhizoids) among temperature treatments were consistent across sites within regions (ANOVA ion); F1,135 = 0.ion); F1,135 = 0.ion); F1,135 = 0.3.2.3N = 162) but varied among sites within regions with temperature (ANOVA temperature × site(region) interaction; F = 3.12; p = .001; Figure Bonferroni‐p = .017 & .004, respectively; Figure temperature × site(region); F = 2.66; p = .003; Figure 5), but temperature effects on meristematic activity were consistent among regions  = 2.55; p = .093). Overall, there were significantly more embryos with apical hairs at day 14 in the 21°C treatment compared with both 18 and 15°C treatments , but this pattern was only significant for 2 sites in each of the PPB and East regions  and 14‐day mortality  at 21°C  and 14‐day mortality  at 21°C , and 14‐day apical hair development  at 21°C.Regression analyses suggest an association between home site temperature environments and thermal response in the common garden experiment. We found a significant negative relationship between home site mean seasonal variation in sea surface temperature and 7‐day rhizoid development (PST) estimates were highest for 14‐day mortality , intermediate for 14‐day apical hair development  and 7‐day rhizoid length , and lowest for percentage of mature embryos after 7 days . While PST for percentage of mature embryos was similar to FST, PST measures for the remaining three traits were significantly higher than FST globally , between regions (FST = 0.09), and within regions (FST = 0.17).Phenotypic variance , our study suggests the potential for selection to increase thermal tolerance across the species range. Our common garden experiments indicate strong differences in early development between sites sampled from three geographical regions in response to differences in temperature. High water temperatures (21°C) often led to suppressed embryonic development and increased mortality in individuals from sites from cooler regions, while others from warmer and more variable temperature regions were relatively unaffected. Our correlation analyses indicated negative linear relationships between homesite, sea surface temperatures , and thermal response at 21°C. These findings suggest genetically determined variation in thermal tolerance across broad thermal gradients in H. banksii, consistent with results reported for other fucoid and laminarian macrophytes  populations separated by as little as 12 km have been previously demonstrated  demonstrated clear home site advantages ; for instance, macroalgae often show plastic responses in morphology and physiology to changes in temperature  will help in further elucidating patterns of differentiation across sites. Such methods provide unprecedented sensitivity for resolving fine‐scale genetic structure, as well as identifying signatures of selection and putative candidate genes that underlie adaptive differences between species populations (Jordan et al., 4.3H. banksii in areas affected by coastal development, urbanization, and thermal stress (Bellgrove et al., H. banksii also suggests that gene flow is unlikely to assist populations in adapting to warming sea surface temperatures via the migration of thermally adapted genotypes (Alestra & Schiel, Our findings have implications for predicting the recovery potential of depleted H. banksii, adaptive management strategies might be needed. These could include assisted migration of thermally adapted genotypes to populations showing signs of climate stress. Such approaches are being widely advocated as a tool for “climate proofing” threatened marine and terrestrial animal and plant communities (Aitken & Whitlock, H. banksii where thermal adaptations across the species range are heterogeneous. In such cases, assisted migration strategies may require composite provenancing approaches, involving mixed genotypes from multiple source populations (Broadhurst et al., While our study suggests that thermally resistant genotypes can occur, selection may struggle to keep pace with a rapidly shifting climatic envelope and increasingly frequent extreme temperature events (Wernberg, Bettignies, et al., None declared.This project was conceived by A.D.M, A.B, M.A.C, and C.D.H.S, with the population genetic data collected by A.D.M, A.B, J.C, and M.A.C, and analysis led by A.D.M. Common garden experiments were led by A.D.M, A.B, and A.A.H; the collection of phenotypic data was assisted by R.C and Z.N, with A.D.M, A.B, A.A.H, M.A.C, and C.D.H.S contributing to data analyses. Writing of the manuscript was led by A.D.M. with assistance from all authors. Click here for additional data file.


Aedes japonicus japonicus has expanded beyond its native range and has established in multiple European countries, including Belgium. In addition to the population located at Natoye, Belgium, locally established since 2002, specimens were recently collected along the Belgian border. The first objective of this study was therefore to investigate the origin of these new introductions, which were assumed to be related to the expansion of the nearby population in western Germany. Also, an intensive elimination campaign was undertaken at Natoye between 2012 and 2015, after which the species was declared to be eradicated. This species was re-detected in 2017, and thus the second objective was to investigate if these specimens resulted from a new introduction event and/or from a few undetected specimens that escaped the elimination campaign.nad4 and seven microsatellite loci was surveyed in 224 and 68 specimens collected in Belgium and Germany, respectively. German samples were included as reference to investigate putative introduction source(s). At Natoye, 52 and 135 specimens were collected before and after the elimination campaign, respectively, to investigate temporal changes in the genetic composition and diversity.Population genetic variation at At Natoye, the genotypic microsatellite make-up showed a clear difference before and after the elimination campaign. Also, the population after 2017 displayed an increased allelic richness and number of private alleles, indicative of new introduction(s). However, the Natoye population present before the elimination programme is believed to have survived at low density. At the Belgian border, clustering results suggest a relation with the western German population. Whether the introduction(s) occur via passive human-mediated ground transport or, alternatively, by natural spread cannot be determined yet from the dataset.Ae. japonicus towards the west. Our results also point to the complexity of controlling invasive species, since 4 years of intense control measures were found to be not completely successful at eliminating this exotic at Natoye.Further introductions within Belgium are expected to occur in the near future, especially along the eastern Belgian border, which is at the front of the invasion of The online version contains supplementary material available at 10.1186/s13071-021-04676-8. Aedes species, are regularly introduced together with the worldwide transport of used tyres, ornamental plants and water-holding machinery [Aedes japonicus japonicus , generic name following [As a result of globalisation and international trade, non-native species are being introduced into Europe, which may eventually establish reproducing and overwintering populations in new territories. The introduction of potential disease vectors is of major concern since these constitute a threat to human and animal health. Mosquitoes (Diptera: Culicidae), such as achinery . The Asiollowing ), is a collowing , includiollowing , Japanesollowing , chikungollowing , dengue ollowing  and Zikaollowing , 8. Origollowing . The arrollowing –14. The ollowing .Ae. japonicus in Belgium in 2002  [Aedes japonicus was most likely introduced through the second-hand tyre trade located at this site [Ae. japonicus re-appeared [Deblauwe et al., Monitoring of exotic mosquitoes in Belgium (MEMO): Final Report Phase 7 Part 1: MEMO results. Antwerp: NEHAP, unpublished report, i.e., whether they represented undetected survivors of the elimination and/or involved new colonisers from other source populations.Since the first detection of rovince) , successrovince) –18. Natorovince) . Subsequrovince) –21, in Srovince) , in Hungrovince) , in Croarovince) –26, in Irovince)  and in Srovince) , 29. Thehis site . The exahis site . Its prehis site , 31. Thehis site . HoweverAe. japonicus has rapidly spread throughout the southwest region of Germany, following its first observation in 2008 in the federal state of Baden-Wuerttemberg [Aedes japonicus was subsequently detected in 2012 in the western region of the country  [Ae. japonicus was monitored in Belgium between 2017 and 2019 at the Belgian–German parking lot of Lichtenbusch and along the road and highway between two cemeteries (Raeren and Rocherath) along the German border. Specimens were collected in an allotment garden in Eupen  . Aedes japonicus was also detected in 2018 during the monitoring of Aedes koreicus, another non-native mosquito species that has established in Belgium, in that same period at an industrial area in Maasmechelen  . Hence, elucidating the relationships between these Belgian specimens and the western German population is of great interest to understand the introduction events in Belgium, and it might help customising surveillance and control efforts in Belgium.In contrast to the situation at Natoye, ttemberg –37. Its ttemberg , 39. Aedatinate) , in 2013atinate)  and finaatinate) . It is natinate) . The wesAe. japonicus, several population genetic investigations have been conducted in the past [nad4) locus. These DNA markers enabled researchers to study the population genetic structure of Ae. japonicus [N = 18) collected at Natoye in 2008 and 2010 were included in these population genetic analyses, revealing that the Natoye population had the lowest genetic diversity of all populations examined [To uncover the relationships between the geographically separated European populations of the past , 42, 43.aponicus , 38, 42 aponicus , and revexamined , 42. In examined , with a nad4 and seven microsatellite loci was surveyed in two ways: (i) a comparison of allelic frequencies and haplotypic diversities between populations from Eupen, Maasmechelen, and reference material from Germany, to assess if the Eupen and Maasmechelen populations are linked to those from the western part of Germany, and (ii) a comparison of the genetic composition and diversity of the population at Natoye between 2012–2013 and 2017–2019, to assess potential effects of the elimination campaign.The objectives of the present study were to determine: (i) if the mosquito specimens collected along the Belgian border were introduced from the nearby existing western German population, and (ii) if the population at Natoye resulted from a new introduction event and/or from a few undetected specimens that escaped elimination. To answer these questions, population genetic variation at Aedes j. japonicus specimens from Belgium and Germany were incorporated in the present study (Table N = 52) collected in 2012 and during a survey from 2013 to 2016 at Natoye was incorporated in this study to investigate the temporal fine-scale genetic structure changes at that location. During the latest monitoring project , Ae. japonicus eggs, larvae and adults were collected at Natoye , Eupen  and Maasmechelen  (Table N = 9) were reared in the laboratory to adults for morphological identification, while eggs collected in 2017 (N = 6) were identified by mitochondrial cytochrome oxidase I gene (COI) DNA barcoding [In total, 292 dy Table . Of thesarcoding , followiarcoding   from well-identified German population clusters based on microsatellite data [Further, ite data  were incite data . SpecimeDNA was extracted from legs, abdomens or eggs using either the NucleoSpin® Tissue DNA extraction kit  or the QIAamp DNA Micro kit , following the manufacturers’ protocols, except that the elution volume was set to 70 µl.nad4 locus was sequenced using published primers and PCR cycling conditions [2, 0.2 mM dNTP, 0.4 µM of each primer and 0.03 U/µl of Platinum™ Taq DNA Polymerase . PCR products and negative controls were run in a 1.5% agarose gel, using a UV transilluminator and the MidoriGreen™ Direct  method. Positive PCR amplicons were subsequently purified using the ExoSAP-IT™ protocol, following the manufacturer’s instructions, and sequenced in both directions on an ABI 3230xl capillary DNA sequencer using BigDye Terminator v3.1 chemistry . The quality of the sequencing output was checked with Geneious® R11 , following which strands were trimmed, corrected, translated into amino acids and assembled using the same software. Consensus sequences were extracted and aligned using ClustalW in Geneious® R11 (https://www.geneious.com).A fragment of the nditions . The PCRAe. japonicus [Taq PCR Master Mix (Qiagen) and 2 μl of DNA. PCR conditions started with an initial activation step at 94 °C/15 min; followed denaturation (94 °C/30 s), annealing (54 °C/30 s) and extension (72 °C/30 s) for 30 cycles; and a final extension step at 60 °C for 30 min. PCR products were sized on a 3130XL Genetic Analyzer  using 2 μl of PCR product, 12 μl of Hi-Di™ formamide (Applied Biosystems) and 0.3 μl of GeneScan™ 500 LIZ size standard (Applied Biosystems). Length variation visualisation and determination were performed using Geneious® R11.Specimens were genotyped for seven microsatellite loci developed for aponicus , using taponicus , except aponicus , 54. Thenad4 sequences (N = 48) were downloaded from GenBank and then aligned with the nad4 consensus sequences generated in this study, as well as with one outgroup sequence of Aedes aegypti, using Geneious® R11. A rooted Neighbour-Joining (NJ) tree was constructed based on the HKY distance model implemented in Geneious® R11, with branch support assessed by 1000 bootstrap replicates.Available F-statistics, as implemented in Arlequin v3.5 [k) and average gene diversity over nucleotide positions (H) were calculated. A haplotype network was constructed using the minimum spanning network method (Minspnet in Arlequin v3.5), with default settings.We performed a pairwise comparison of nucleotide frequencies between populations using Wright’s uin v3.5   was run ten times. The Markov chain convergence was checked between each ten iterations for each K. The results and visual output of the ten iterations for each K value were summarised using the web application CLUMPAK [http://clumpak.tau.ac.il/index.html) and the software DISTRUCT v1.1 [A multilocus Bayesian cluster analysis was performed using Structure v2.3.4, without prior information on geographic origin , 57. A b CLUMPAK   and inbreeding coefficient (FIS) per population were estimated using Genetix v4.05 [P values. The number of alleles (N), mean number of alleles per locus (NA) and number of private alleles (PA) per population were estimated using GenAlEx v6.51b2 [AR), as a standardised measure of the number of alleles per locus independent of the sample size, was calculated using FSTAT v2.9.4 [FST values between populations across all loci were estimated in Arlequin v3.5 . To further investigate the putative origin of the specimens collected along the Belgian border, a principal coordinates analysis (PCoA) was performed with GenAlEx v6.51b2 [FST values.The presence of null alleles was tested with Micro-Checker v2.2.3 . Heterozix v4.05 , with 10 v6.51b2 . AllelicT v2.9.4 . Pairwis v6.51b2 , based oRecent demographic bottlenecks were explored with Bottleneck v1.2.02  based onnad4 fragment was scored in 278 specimens , and was named H47 (GenBank accession number: MT462840), in continuation of the numbering of nad4 haplotypes within the species [Ae. japonicus [, 103 individuals could not be assigned to single haplotypes .Additionally, seven polymorphic microsatellite loci were scored in 292 specimens of nad4 displayed an unresolved topology. Likewise, the minimum spanning network revealed no association between haplotypes and geography. The number of haplotypes per location varied from one (Eupen and Maasmechelen) to five (southwestern Germany). Haplotype H1 was encountered at almost all locations, and usually in higher frequencies (except at Natoye and in northern Germany), as elsewhere in the world [The NJ tree based on he world , 52.K = 2) and six (second highest posterior probability for K = 6) genotypic clusters , and pairwise significant nad4 and microsatellite FST between Natoye and the other populations were 0.339 and 0.116 (P < 0.0005), respectively. At K = 6, four genotype groups corresponded with geographical populations, with different degrees of admixture: (i) Maasmechelen; (ii) northern and southwestern Germany; (iii) western Germany and Eupen; and (iv) Natoye , which also occurred in the western and southwestern German populations (Table P > 0.05) using Bottleneck, nor did the German populations. Based on the microsatellite loci, Maasmechelen displayed significant pairwise FST values with all other populations  . Three haplotypes were each only detected in 1 year at Natoye, namely H23 in 2012, H5 in 2017 and H47 in 2019  Fig. . The FSTes Table . The Botnad4 and for the microsatellite data, with a high prevalence of nad4 haplotype H9 . This haplotype also occurs in the USA, Germany, Austria, the Netherlands and Slovenia [NTOT = 32) [nad4 data did not show any geographical relationships, the source area(s) of the original introduction at Natoye remain elusive. The lack of structure also observed in previous studies is likely linked to the randomness of international introduction events [The present results indicate that the Natoye population is significantly differentiated from all other populations considered in this study, both for Slovenia , 42, 44,FST values and the Bayesian clustering in Fig. nad4 data  , as suggested by the significant  Hesse)  compared to 2017  and 2018 , with evidence of a spread in the southwest direction in 2019 using the forest as a ‘shrub-corridor’ . Several studies indicate that Ae. japonicus uses forest edges to spread [The Natoye population present in 2012–2013 is, however, believed to have survived since a shift in the genetic signature before and after the elimination campaign was identified based on microsatellite data, but without complete replacement  were previously analysed based on the same set of microsatellite loci in [Ae. japonicus populations  were collected over the whole activity season of the mosquito, and also from a 2-km-wide perimeter around the tyre company site, which minimises the risk of biases due to relatedness.A few individuals collected in Natoye in 2008 and 2010  . Since these two trapping dates are close to each other, it is possible that the specimens derived from the same single introduction and eventually reproduced on site. The observed population genetic structure might therefore result from a strong genetic drift . It is therefore not possible to make any further inferences about the potential origin of these specimens.Considering that both the sample sizes and the number of DNA markers used to investigate the genetic diversity of the Belgian populations along the border between Begium and Germany were limited, the results should be interpreted cautiously and should consider information collected in the field during the monitoring campaign. Additionally, the observed possible relatedness of the specimens cannot be dismissed without some reflection. For example, despite intensive monitoring efforts during the whole season, adult Ae. japonicus specimens were collected—once in 2017 (September), seven times in 2018  and three times again in 2019 . The larvae collected in 2017 were most likely siblings as they were collected on the same date and at the same spot. In 2018, all life stages were collected in and around the allotment garden, while only larvae were found in 2019. Considering the monitoring efforts, these results indicate summer reproduction but the species is not believed to have established and overwintered yet, which rather points to multiple introductions at Eupen. Population clustering results based on microsatellite data at K = 6 and the PCoA suggest a relation between Eupen and the population of western Germany , only a few ny Figs. , which iAe. japonicus populations, including representatives of its native and invasive ranges, in additional to the use of genome wide genetic data, would be required.To further investigate the population genetic relationships, gain insight in the introduction pathways and investigate changes in the allelic frequencies over time in the frame of surveillance and elimination programmes, thorough sampling of all Ae. japonicus in Germany, its recent establishment in Luxembourg, the increasing population densities in Germany and Belgium [Ae. japonicus toward the west, while the present results also show that the elimination campaign undertaken over years at Natoye was not completely successful, which underlines the complexity of controlling invasive species. Sensibilisation along the German and Luxembourg border and control through larviciding and mechanical removal of breeding sites at the tyre-trading company in Natoye could help keeping densities and spread as low as possible.Considering the international movement of goods and people, the colonising behaviour of  Belgium , 14 and Additional file 1: Fig. S1. Results of the Bayesian clustering analysis with Structure v2.3.4 software, reporting the ΔK values calculated according to Evanno et al. [o et al.  with theAdditional file 2: Fig. S2. Map of Belgium and Germany displaying the clustering analysis results for K = 2, based on our microsatellite database per sampling locality .Additional file 3: Fig. S3. Results of the Bayesian clustering analysis with Structure v2.3.4 software at Natoye, reporting the ΔK values calculated according to Evanno et al. [o et al.  with the


Myrmecophaga tridactyla) using an individual sampling scheme (ISS) on a regional geographic scale. Data were collected from 41 specimens from twenty different locations in São Paulo State, Brazil, and six polymorphic microsatellite loci were genotyped. Our results indicate that barriers to gene flow exist and have segregated individuals of the farther away areas into two spatially structured clusters. The populations were also found to have high genetic diversity. The experimental sampling approach used herein enabled an analysis of the population dynamics of the giant anteater on a regional scale, as well as the identification of priority populations for genetic resource conservation for this species. The results reflect the need for adequate management plans. The efficacy of the sampling scheme may vary based on the study model used, but we argue that the use of an ISS combined with suitable molecular markers and statistical methods may serve as an important tool for initial analyses of threatened or vulnerable species, particularly in anthropized regions where populations are small or hard to characterize.Habitat loss is the main threat to biodiversity conservation worldwide. Some species may be particularly susceptible to the effects of fragmentation and the isolation of populations. The impacts of human activity on wild animal populations may be understood through relationships between individual genetic data and spatial landscape variables, particularly when considering local population dynamics influenced by fragmented habitats. Thus, the objective of this study was to analyze the population structure and genetic diversity of the giant anteater ( Myrmecophaga tridactyla) using an individual sampling scheme (ISS) on a regional geographic scale in São Paulo State, Brazil. Our results indicate that barriers to gene flow exist, and the populations present high genetic diversity, which reflects the importance of these populations and the necessity of immediate conservation actions.Habitat loss is the main threat to biodiversity conservation worldwide, and some species may be particularly susceptible to the effects of fragmentation and the isolation of populations. Thus, the objective of this study was to analyze the population structure and genetic diversity of the giant anteater ( Some of the species’ biological characteristics may lead to low rates of population growth: a low metabolic rate and low thermoregulatory capacity, limited reproductive potential, prolonged parental care, a long gestation period, and solitary habits  located in the cities of São José do Rio Preto and Mirassol. Other animals were obtained in search‐and‐capture campaigns in and around the Santa Bárbara Conservation Area (EESB) located in the city of Águas de Santa Bárbara. The use of animals from these locations permitted inferences about the status of individuals and populations in habitats in and around these conservation areas.The EENP conservation area is 500 ha in size when combined with the Noroeste Paulista State Forest and is considered to be seriously threatened by urbanization and real estate speculation. It is surrounded by pastures, farms, and urban neighborhoods  were obtained from different sources. Some were collected by veterinarians and park rangers after the collection of animals that had been run over or had been victims of crop burning (n = 35). In other cases, blood samples were obtained from animals captured alive in field studies for other purposes and were provided to our laboratory (n = 6).The samples included in this study .All biological material collection herein was authorized for scientific purposes by the Biodiversity Information and Authorization System (SISBIO) from the Brazilian Federal Environmental Agency (IBAMA) under certificate number 43854‐4 and was approved by the research ethics committees at the universities involved in this study . For the captures in the EESB conservation area (the samples provided from previous studies), sampling licenses were obtained , as was authorization from the local institutional animal care and use committees (CEUA No. 003414/13). Details on the origin of the samples, geographic coordinates, and genotypes are available in the Dryad Data Repository , and 10 µl of ultrapure water , 72°C for 30 s, plus 25 additional cycles , and the final extension for 5 min at 72°C. After the amplifications were confirmed in 3% agarose gel, the fragments were identified in an ABI 3500 Genetic Analyzer (Applied Biosystems). The DS‐33 GeneScan™ Installation Standard (Applied Biosystems) was used for the capillary electrophoresis run, and the reactions were organized into two groups based on the expected fragment sizes.®, version 4.1 . The correct identification of the alleles is crucial for a reliable interpretation of the microsatellite data , the test provided by Mantel Mantel,  was perfSubsequently, we performed the principal component analyses (PCA) of individual genetic variation using R version 4.0.2  the population of the conservation area—EENP, (b) the population of the conservation area—EESB, and (c) a population defined by the animals sampled in other areas across the northwest region of São Paulo State—NP. This subdivision allowed us to compare and evaluate the genetic patterns among the animals in conservation areas and animals farther away from the protected areas.Cluster analysis was also performed in PAST  and within the subpopulations of the conservation areas, from which the average allelic richness and gene diversity (HE) were calculated. Finally, genetic divergence between populations was estimated by calculating the unbiased estimate of F33.13.1.1K = 2 in STRUCTURE as the most probable number of clusters after calculating ΔK . The posterior probability maps indicated that the individuals belong to specific clusters, with a low probability of occupation in farther away areas  and the posterior probability for individuals belonging to cluster 1 and cluster 2 (<0.56), both results indicate the population subdivision and corroborate the hypothesis that there are two groups in the studied area. Besides, the relatively low values may be due to the experimental sampling method and the number of individuals used.Despite the low Delta 3.1.2Monmonier's algorithm placed the main boundary separating the individuals/populations of the northwestern region and the central‐southern region. The other contiguous barrier showed that the individuals sampled in the most urbanized area are isolated (including the EENP area population), and the result is suggestive of isolation by barrier—IBB (figure not shown).r = 0.06982, p = .195). The allelic aggregation index, which is calculated based on the overall spatial distribution of all of the alleles and loci (RjAVE), was 0.778477556 (p = .00633). This result indicates that the samples presented a clumped spatial distribution (RjAVE < 1) and supports the structure found in the Bayesian spatial analysis.The Mantel test was performed to test the isolation by distance (IBD) hypothesis, and no evidence of IBD was found (figure not shown) since there was no correlation between genetic and geographic distances  was carried out to define in few vectors all data collected from the genotypes studied Figure . The PCAM. tridactyla.EENP population diverges from the others (NP and EESB). Also, NP and EESB have the same average, but NP has much greater variation than EESB. This variation was expected due to the number of individuals sampled per population. It is important to emphasize that the existing variability in the total population of the state of São Paulo shows the importance of the conservation of these populations for the maintenance of the genetic resources to the species The EESB population showed less variation, but a similar average to the NP population , and the EENP population stands out mainly to PC2. Each ellipse comprises  95% of the population, and this explains the elements that are external to the ellipse (outliers).3.2.2The dendrogram based on the NJ algorithm revealed two discrete clusters.Results presented high bootstrap support values Figure , a findi3.3The population of São Paulo State  presented high genetic diversity, both in relation to the expected heterozygosity (0.7188) and in relation to allelic richness .p > .05). Analyses were also performed between individuals found close to the EENP conservation area (n = 10) and those found close to the EESB conservation area (n = 6) to investigate the genetic diversity and differentiation between the population of the conservation areas. The results reflected greater genetic differentiation between these two groups (FST = 0.1739) and relatively low/moderate FIT (0.1348) and FIS (0.0912) values.Descriptive analyses indicate that all of the loci were highly polymorphic. After the application of Bonferroni's correction, two loci exhibited deviations from Hardy–Weinberg equilibrium, and the tests for linkage disequilibrium were found not to be statistically significant (3.4m = 0.615729).Gene flow analyses were carried out for testing levels of gene flow among individuals belonging to different areas, and the results showed that the number of migrants per generation is lower between two areas that are farther away from each other. This reduction in the migration rate at regional levels may have led to population differentiation. Also, we were able to infer migration between the animals that were obtained in the portions of the landscape surrounding the conservation areas and the result indicated a lower level of migration between the populations of the EENP and EESB (N44.1K = 2), and high rates of genetic diversity. The genetic structure of the giant anteater populations in this region is best explained by the presence of barriers to gene flow than by geographic distance.The use of microsatellite markers in this study aided in the identification of substantial intrapopulation variance, population subdivision , considering the small sample size.Few studies have been performed to evaluate population dynamics and the genetic variability of giant anteater populations , as well as a high degree of inbreeding (FIT = 0.879). According to the authors, the low level of diversity in these loci may be the result of the natural history and evolution of M. tridactyla, or it may be a consequence of population bottlenecks due to the decades‐long history of recurrent fires in the area .m = 0.615729) indicates the subdivision of the population since rates lower than one migrant per generation are insufficient for counteracting the effects of genetic drift ; Formal analysis ; Investigation (lead); Methodology (lead); Project administration ; Resources ; Software (lead); Visualization ; Writing‐original draft (supporting); Writing‐review & editing (lead). Alessandro Garcia Lopes: Methodology ; Visualization ; Writing‐review & editing . Luiz Paulo Nogueira Aires: Methodology ; Visualization ; Writing‐review & editing . Rita de Cassia Bianchi: Formal analysis ; Funding acquisition ; Validation ; Visualization ; Writing‐review & editing . Cinara Cássia Brandão: Formal analysis ; Supervision (supporting); Validation ; Visualization ; Writing‐review & editing . Adriana Coletto Morales: Formal analysis ; Validation ; Visualization ; Writing‐review & editing . Lilian Castiglioni: Conceptualization (lead); Data curation ; Formal analysis ; Funding acquisition (lead); Project administration (lead); Resources ; Supervision (lead); Validation (lead); Visualization ; Writing‐original draft (lead); Writing‐review & editing .


Anopheles funestus threatens malaria control efforts in Africa. Cytochrome P450-mediated metabolic resistance is best understood for CYP6P9 genes in southern Africa in An. funestus. However, we do not know if this resistance mechanism is spreading across Africa and how it relates to broader patterns of gene flow across the continent. Nucleotide diversity of the CYP6P9a gene and the diversity pattern of five gene fragments spanning a region of 120 kb around the CYP6P9a gene were surveyed in mosquitoes from southern, eastern and central Africa. These analyses revealed that a Cyp6P9a resistance-associated allele has swept through southern and eastern Africa and is now fixed in these regions. A similar diversity profile was observed when analysing genomic regions located 34 kb upstream to 86 kb downstream of the CYP6P9a locus, concordant with a selective sweep throughout the rp1 locus. We identify reduced gene flow between southern/eastern Africa and central Africa, which we hypothesise is due to the Great Rift Valley. These potential barriers to gene flow are likely to prevent or slow the spread of CYP6P9-based resistance mechanism to other parts of Africa and would to be considered in future vector control interventions such as gene drive.Pyrethroid resistance in major malaria vectors such as  Anopheles funestus is one of the most important malaria vectors in Africa. The vector has a wide geographic distribution ranging from south of the Sahara Desert to northern South Africa and Madagascar [An. funestus is the dominant malaria vector, due to its highly anthropophilic and endophilic preferences [Anopheles mosquitoes to develop resistance to various types of insecticides is endangering these fragile gains [dagascar . In manyferences ,3. Sub-Sferences . This haferences ,6,7. Unfle gains . Resistale gains . This maAn. funestus [An. funestus cytochrome P450s CYP6P9a and CYP6P9b genes were identified as the main drivers of resistance in Mozambique and southern Malawi [An. funestus populations across Africa [An. funestus. Monitoring of the genetic diversity and signatures of selection on P450-based resistance loci, such as that driven by CYP6P9a, is necessary to better understand the dynamic and evolution of such major mechanism of resistance to insecticides in malaria vectors.Resistance to pyrethroids has been reported in many populations of malaria vectors in the southern part of Africa, notably in funestus ,13,14,15funestus ,17. Morefunestus ,19. In tfunestus , continun Malawi ,17,19, ys Africa ,19,20,21s Africa . It remaCYP6P9a across southern and East Africa and infer the dynamics of the spread of this resistance allele between the different mosquito populations. We confirm the presence of a strong selective sweep spanning a 120 kb previously-identified major cytochrome P450-based pyrethroid resistance locus [Here, we provide an overview of the genetic diversity and selection acting on the major pyrethroid resistance gene ce locus ,18 with Anopheles funestus mosquitoes were collected between 2012 and 2018 from nine localities in six countries in southern, eastern and central Africa (An. funestus using a cocktail PCR [An. funestus sensu stricto (hereinafter referred to as An. funestus) mosquitoes were used in this study.l Africa . The saml Africa . Additiotail PCR  and furttail PCR . Only coCYP6P9a gene and the surrounding genomic region was assessed by PCR amplicon sequencing. Primers from Riveron et al. [resistance-to-pyrethroids 1 (rp1) quantitative trait loci (QTL) region of the 2R chromosome of An. funestus genome were also amplified in order to assess the presence of a selective sweep around CYP6P9a across Africa. These loci: 0 BAC, 25 BAC, 63 BAC, 95 BAC and 120 BAC were originally characterized in the laboratory resistant strain, FUMOZ-R, and are located at −34 kb, −9 kb, +29 kb, −61 kb and +86 kb upstream and downstream of the start of the CYP6P9a locus respectively [rp1 fragment located upstream and downstream of CYP6P9a, one pair of primers previously published [Nucleotide diversity in the n et al.  were usen et al. . Five adectively ,18. For CYP6P9a and 1 unit of KapaTaq  for BAC clone. Reactions were added of 0.2 mM dNTPs, 0.5 μM of each primer, respective buffer solutions for GC rich templates and at least 10 ng of genomic DNA (1 µl). PCR reactions were carried out in PCR System 2720 thermal cycler  under the following conditions for CYP6P9a gene: 1 min at 98 °C, followed by 35 cycles of 10 s at 98 °C, 30 s at 62 °C and 2 min at 72 °C and a final extension of 10 min at 72 °C. BAC fragments was amplified using a program of 5 min at 95 °C, followed by 35 cycles of 30 s at 95 °C, 30 s at a primer-specific temperature  for perature , and 1 mCYP6P9a locus, in order to ensure coverage of the full-length sequence. To ensure reliability of the sequencing data, PCR amplicons were sequenced in both directions, and any remaining ambiguities in the sequences resolved by repeated PCR amplification and re-sequencing.PCR products were purified using the EXOrSAP reagent  or the QIAquick PCR Purification Kit (Qiagen) and directly sent for sequencing using PCR primers. We designed additional internal overlapping primers  for sequSequence alignment was conducted with the ClustalW module of MEGA X version 10.1 . HeterozHaplotype analysis was conducted using DnaSP to count the number of haplotypes (h) and the haplotype diversity (Hd) of each locus. TCS software  and its CYP6P9a and BAC sequences using MEGA X. Before running ML trees, final alignments were submitted to MEGA X Models program to select the best model for phylogenetic analysis based on Bayesian and Akaike Information Criterions (BIC and AICc). The evolutionary history of all sequences was derived using the Maximum likelihood method based on the Kimura 2-parameter (K2) or the Hasegawa-Kishino-Yano with γ distribution (HKY+G) models. The tree with the highest log likelihood was selected. To test the robustness of tree topologies, 1000 bootstrap replicates were performed. Trees were drawn to scale, with branch lengths measured in the number of substitutions per site. For STF distance pairwise comparisons, Neighbor-Joining trees were generated and optimal trees with bests sum of branch length were selected.Phylogenetic trees generated by the Maximum likelihood (‘ML’) and Neighbour joining (NJ) methods were inferred on CYP6P9a gene and 750 bp of the 25 BAC fragment, we calculated piN/piS ratios (non-synonymous polymorphism rate/polymorphism substitution rate) between the different populations to investigate selection pressure on the gene. A piN/piS ratio significantly greater than one implies positive selection, less than one implies purifying selection, and a ratio of one indicates a selectively neutral locus.For protein coding sequences, 642 bp of the STF, the fixation index shows the overall differentiation by measuring how likely, two homologous genes, randomly chosen in a subpopulation, result from a single gene in the subpopulation [STG although analogous to the previous, was calculated to double check the STF values and verify the consistency of the results. STG, is a multi-allele generalization of STF, which was defined as the relative difference between the expected heterozygosity of the whole population and the mean expected heterozygosity of the individual demes [STK statistic was used to estimate the levels of pair-wise genetic differentiation between populations in terms of the relative number of shared alleles among the populations, without regard to their frequencies [STH which is related to haplotype frequency was also calculated. STH is a differentiation metric which weighs alleles by their population frequency [STH values increase with the addition of private alleles in a population while it will decrease when a given allele dominating in the population will rise in frequency. Finally, STN has been calculated to take into account the phylogenetic relationships between haplotypes, and to test the occurrence of a phylogeographic pattern in the dataset [STN significantly greater than STG, implies a phylogeographic structure [STN estimates were associated with the number of migrations per generation (Nm) to help evaluate gene flow among studied populations. The statistical significance of STH and STK estimates was assessed by permutation of subpopulations identities and recalculating indexes 10,000 times as implemented in DnaSP 6.12.We estimated genetic diversity in the different geographical populations by calculating population differentiation indexes in DnaSP software. pulation ,33,34. Gal demes . The KSTquencies . HST whitructure . NST estCYP6P9a locus. After alignment and assessment in MEGA X [An. funestus field-collected mosquitoes from ten localities in seven countries , Malawi (Fulirwa), Zambia (Kaoma), Tanzania , Uganda (Tororo), Democratic Republic of Congo  and Cameroon (Lagdo)) for which good sequence data were obtained. This included 465 bp of the partial 5′ upstream intergenic region, 32 bp of 5′UTR and 642 bp of partial gene’s first exon. The examination yielded 84 single nucleotide polymorphisms (SNPs) and 6 insertions or deletions (Indels) in the 1.139 bp region  found in Palmeira and Magania da Costa. Similarly, all sites in Tanzania presented similar patterns of low diversity with π ranging from 0.00010 to 0.00033. Overall, nucleotide diversity was lowest in both countries, Mozambique (0.00014) and Tanzania (0.00027), compared to Zambia (0.00042), Malawi (0.00061) and Uganda (0.00109). Cameroon and DR Congo displayed higher but comparable diversity (respectively 0.00200 and 0.00304) corresponding to their geographical proximity . NucleotCameroon .CYP6P9a gene reveal a loss in diversity in the entire first exon of the gene in southern and eastern African mosquito populations as highlighted by the sharp peak at around 400 bp in sequences from central Africa  in the first exon coding region of CYP6P9a that occurred in Mozambique, Malawi, Zambia and Tanzania were non-synonymous  suggesting strong positive selection of CYP6P9a resistance allele in the country. In mosquito populations from Zambia and Mozambique however, purifying selection was observed as shown by ratios values that were less than one (0.31 to 0.94 respectively). In other countries where there is no synonymous and/or non-synonymous substitution, we were not able to calculate the ratio .CYP6P9a in southern Africa and Tanzania where less diversity and divergence is observed, but not in other parts of the continent where we had higher divergence among individuals of the same population  along with Tanzania (TZ), Eastern (UG) and Central Africa . Mosquito populations from Southern Africa plus Tanzania share the same cluster, while those from Uganda and Central Africa form two distinct clades driven by the same branch . UG forms a distinct haplotype related to CAM and DRC also forming two distinct but related haplotypes with respect to their geographical proximity  and an associated high gene flow between them (Nm = 10.87). There were higher levels of genetic differentiation among populations from Central Africa and Uganda than when compared to those from southern Africa (STF = 0.53 to 0.97)  but not for southern African populations (Genetic differentiation among populations was tested using to 0.97) . The samto 0.97) . These re values . Moreoveulations . This reCYP6P9a, the extent of nucleotide polymorphism was examined at five loci around the resistance gene, within the BAC genomic region spanning the rp1 QTL, approximately 120 kb long  for southern African (plus Tanzanian) mosquito populations was lower at all six loci including l Africa . In Eastl Africa . Analysifragment . This wafragment . The relc region .CYP6P9a and CYP6P9b loci as well as other P450s and esterase loci  at loci from −9 kb to +86 kb, but markedly high at−34 kb and CYP6P9a loci (4.84 and 4.96 respectively) . Overallase loci  where a CYP6P9a resistance gene locus. The same is true for eastern Africa. However, in central Africa average Hd values were much higher across all six loci including the gene CYP6P9a  than for the  CYP6P9a . Tajima’location .rp1 QTL studied. Construction of maximum likelihood (“ML”) phylogenetic trees revealed reduced diversity close to the CYP6P9a locus in the resistant populations of Mozambique, Malawi, Zambia and Tanzania. Uganda and DR Congo plus Cameroon samples show different profiles, forming distinct clusters  and +86 kb (120 BAC) loci . The sign Africa b. CYP6P9a. A very low genetic differentiation associated with a high geneflow was observed between southern African mosquito population. Populations from central and eastern Africa exhibited lower levels of genetic differentiation and gene flow between them compared to those from southern Africa , in a panel of different An. funestus populations across Africa. The goal was to establish the Africa-wide population structure of this major malaria vector, providing key evidence of the contemporary response of mosquito populations to insecticide interventions. Insecticide resistance among malaria vectors is expanding across Africa, threatening the success of malaria control methods. Continuous monitoring of the evolutionary patterns of vectors population behaviour regarding insecticide-based interventions is thus of great importance. Selection of insecticide-resistance variants has been shown to result in severe reduction of genetic diversity at loci involved during multiple insecticide-based interventions in both public health and agricultural sectors that have been conducted across Africa to control malaria vectors and crop pest insects ,38. CYP6funestus ,17,19 buSTF estimates and all other genetic differentiation indexes reported, southern African plus Tanzania populations are genetically differentiated from other populations at the rp1 locus; among them, the resistance has spread and is now almost fixed. They always form a unique cluster distinct from those formed by central and eastern African mosquito populations. An. funestus mosquito populations from Mozambique and Malawi have previously been reported to share similar genetic differentiation patterns [CYP6P9a in Zambia in 2010 [An. funestus and An. gambiae [An. funestus population across Africa [CYP6P9a resistance variant and not prevent it completely. Further monitoring is thus necessary especially since genome-wide microsatellite-based Bayesian clustering analysis data recently revealed Ugandan An. funestus mosquito population clustering with those from southern Africa, notably Mozambique and Zambia [We observed the predominance of one major haplotype made up of mosquito populations from Mozambique, Malawi, Zambia and Tanzania; southern African countries plus one Eastern African country. Taken together, our results support the possible presence of barriers to gene flow among mosquito populations from these four countries on one side, and central  and eastern (Uganda) African mosquito populations on the other. Based on phylogenetic relationships, haplotype diversities, patterns ,39,40,41 gambiae ,43,44. Ts Africa ,40,45,46d Zambia .rp1 region which is one of the major pyrethroid resistance QTL where P450 genes, including CYP6P9a, associated with metabolic pyrethroid resistance have been identified [CYP6P9a key insecticide resistance genes as well as others fragments from the BAC clone in the vicinity of the gene. It is important to mention that these BAC fragments, in addition to overlap CYP6P9a gene locus, also covers genes like CYP6P9b, CYP6P4a, CYP6P4b, located in the same rp1 region and that have already been identified to play an important role in pyrethroid resistance in An. funestus [We confirmed a major selective sweep in the entified ,19. Overfunestus .CYP6P9a was observed in Mozambique, Malawi, Zambia and Tanzania, mirroring the predominant role of cytochrome P450 genes in the metabolic resistance observed in An. funestus population as previously reported in southern Africa [An. gambiae [Aedes mosquitoes [CYP6P9a that occurred in Mozambique, Malawi, Zambia and Tanzania were shared and non-synonymous  resistance in An. funestus populations West/Central Africa. A clear example is that provided by the resistant samples from Benin exhibiting a GSTe2-derived resistant haplotype which is almost fixed while DDT susceptible populations remained highly polymorphic at this locus in 2014 [Distinct genes associated with insecticide resistance, including the glutathione S-transferase ectively ,24,41,51CYP6P9a showed southern African plus Tanzanian mosquito populations to be significantly differentiated from populations from other regions. Again, this pattern mimics the one of GSTe2 gene in west Africa and further supports the presence of barriers to gene flow between southern Africa plus Tanzania on one side and Uganda plus Central Africa on the other side. It is important to note that Tororo, the collection site in Uganda, is surrounded by east and west branches of the African rift Valley and is located north of Lake Victoria on the border with Kenya. The predominant CYP6P9a haplotype formed by southern African plus the Tanzanian mosquito population was completely absent from the other countries in line with the low level of gene flow observed between the two defined regions. This haplotype is a resistant allele similar to a CYP6P9a resistant cluster from Mozambique and Malawi [Patterns of genetic differentiation based on d Malawi ,18,40 thd Malawi ,18,52,53CYP6P9a resistance allele has moved from southern Africa to part of eastern Africa but has not (yet) crossed the rift valley into Uganda. This contrasting distribution mirrors the distribution of the GSTe2 resistance allele which is completely absent from southern Africa and present in Uganda [296S resistant allele initially located only in West to East Africa and completely absent from southern Africa in 2010 [kdr) mutations in other mosquito species such as An. gambiae [Ae. aegypti [In contrast to previous reports ,18,40,41n Uganda . There i in 2010  that has in 2010 . The sam gambiae  or Ae. a aegypti .rp1 QTL in An. funestus population across Africa found reduced polymorphisms around CYP6P9a in almost all populations except in those from central Africa. In general, the selection on the rp1 region appears to be more extensive in southern and parts of eastern Africa in line with previous reports [An. funestus reduced the efficacy of insecticide-treated bed nets in southern Africa [CYP6P9a from −9 kb upstream the gene to +29 kb downstream, where lower levels of polymorphism were recorded (AFUN008365), overlaps +86 kb locus , suggesting the arrival of a southern resistance allele in central Africa. The resistance allele in question was not identified in Kinshasa, hence the possible existence of a further barrier that crosses DRC. The polymorphism pattern at locus +86 kb in DRC could also be evocative of the presence of a different resistance patterns occurring at this level as supported by the recent characterisation of another resistance marker located in the 3L chromosomal region spanning the rp3 QTL of An. funestus genome; the P450 pyrethroid metabolizer CYP9J11 gene which is commonly overexpressed in all countries across Africa [CYP6P9a and beyond +86 kb, implying it is greater than the 120 kb region studied, it is necessary to analyse chromosomal-level regions using the recently available An. funestus genome assembly [Polymorphism analysis of the  reports ,18,53. Tn Africa . In thesrecorded b. At locrecorded b. In therecorded a, the dikb locus . This prn humans ,58. One s Africa . Since iassembly  to clearAn. funestus. Through several analytical approaches, our results show that the P450-based resistance mechanism is not confined to the southern part of Africa but is now fixed there and has spread to Tanzania in eastern Africa. Our findings are also supportive of the presence of barriers to gene flow between populations of An. funestus which are likely to prevent or slow the spread of the CYP6P9-based resistance mechanism from southern Africa to other parts of Africa. We identified that the rift valley region probably acts as a strong barrier to gene-flow, stressing the importance of continuous monitoring of major vectors population structure for vector control programmes. Finally, we highlight that, despite the heterogenous population structure of An. funestus across Africa being favourable to resistance management, it will be a challenge to the deployment of any genetic-based vector control approaches such as gene-drive mechanisms. We provide vital information that should be taken into account in resistance monitoring as well as in the implementation of novel vector control strategies that rely on populations intermixing freely.This study provides evidence for the spread of a selective sweep on a cytochrome P450 responsible for metabolic resistance to insecticides in the major malaria vector