While much research attention has focused on demographic processes that enabled human diffusion on the Tibetan plateau, little is known about more recent colonization of Southern Himalayas. In particular, the history of migrations, admixture and/or isolation of populations speaking Tibeto-Burman languages, which is supposed to be quite complex and to have reshaped patterns of genetic variation on both sides of the Himalayan arc, remains only partially elucidated. We thus described the genomic landscape of previously unsurveyed Tibeto-Burman (i.e. Sherpa and Tamang) and Indo-Aryan communities from remote Nepalese valleys. Exploration of their genomic relationships with South/East Asian populations provided evidence for Tibetan admixture with low-altitude East Asians and for Sherpa isolation. We also showed that the other Southern Himalayan Tibeto-Burmans derived East Asian ancestry not from the Tibetan/Sherpa lineage, but from low-altitude ancestors who migrated from China plausibly across Northern India/Myanmar, having experienced extensive admixture that reshuffled the ancestral Tibeto-Burman gene pool. These findings improved the understanding of the impact of gene flow/drift on the evolution of high-altitude Himalayan peoples and shed light on migration events that drove colonization of the southern Himalayan slopes, as well as on the role played by different Tibeto-Burman groups in such a complex demographic scenario. This suggests that the arrival of farmers descending from the proto-Tibeto-Burman Di-Qiang tribe played as the breakthrough in the successful human diffusion across the plateau9.To date, a great effort was devoted to investigating the origins of Asian populations dwelling immediately North of the Himalayas, especially Tibetans, to infer the demographic, biological and cultural processes that enabled human colonization of the highest plateau in the world. Archeological11. Mitochondrial DNA (mtDNA), Y-chromosome and linguistic data support a common origin of Tibeto-Burmans15, but provide only a limited resolution for the reconstruction of the historical processes that led these populations to be so geographically scattered. Their current distribution encompasses Tibet and other regions in China, Nepal, Bhutan, Bangladesh, Myanmar, Northeastern India and Indochina, with high cultural heterogeneity17.Accordingly, Neolithic demic movements that involved ancestors of populations speaking Tibeto-Burman languages plausibly represent the main prehistoric events having laid the foundation for the anthropological picture observable on the Tibetan plateau and in the surrounding Himalayan regions. Moreover, the more recent history of migrations, admixture and/or geographical and cultural isolation of Tibeto-Burmans, which has been not fully elucidated so far, is supposed to be quite complex and to have further reshuffled patterns of genetic variation in such a geographical area20, the presence of Tibeto-Burmans in Northeastern India and Nepal could indicate migrations that plausibly originated on the Tibetan plateau and crossed the cordillera. Unfortunately, only a couple of studies have generated genome-wide data for Tibeto-Burman populations residing South of the Himalayan arc, and they were not aimed at disentangling the overall genetic history of such a heterogeneous population group22. For instance, few genomic datasets are available for the Tibeto-Burman Sherpas25 and none for the Tamang groups that live on the southern slopes of the Himalayas or in the high-altitude transverse valleys that connect them to Tibet. Interestingly, their integration within the melting pot of Nepalese populations could be considered as the most iconic example of the mosaic of human groups with divergent biological/cultural legacies, but coexisting in a restricted geographical area, that characterizes the regions immediately South of the Himalayas. Historical records suggest that Sherpas first moved from Eastern to Central Tibet and then, approximately five hundred years ago, to the previously uninhabited high-altitude Nepalese valleys of Khumbu26. Their close affinity to Tibetans is well-established from both uniparental and genome-wide perspectives27. Nevertheless, studies based on these different sets of genetic markers drew contrasting conclusions with regard to which of these groups represents the more recently derived lineage27. Conversely, little is known about the history of Tamangs28, except that they show greater affinity to Tibetans based on Y-chromosome lineages29 compared to mtDNA ones20. They are thus proposed to have derived from male-biased migrations originated in a putative Tibetan homeland followed by admixture with non-Tibetan females. Whether they share recent ancestors with the Sherpas is another question that remains to be tested from a genomic perspective; answering this question may provide a key for resolving the complex relationship between modern Tibeto-Burman populations.Although the Himalayas were considered to be an almost insurmountable barrier to gene flow24. Such a population picture is especially multifaceted in the Nepalese Gaurishankar Conservation Area (GCA)  populations, we aimed at providing new insights on the migration and admixture events that drove the colonization of the southern slopes of the Himalayas and at dissecting the role played by different Tibeto-Burman groups in such a complex demographic scenario.Therefore, the anthropological patchwork centered on Nepalese Sherpa and Tamang groups suggests that Tibeto-Burmans appreciably contributed to the complex network of migrations that characterized the peopling of the southern Himalayan slopes, which remains a largely understudied regionCA) Fig. , a numbeAfter applying stringent quality control filtering , we generated a “GCA” dataset of 59 samples typed for 683,180 SNPs to investigate patterns of population structure and genetic diversity within the GCA. By merging it with publicly available genome-wide data  applied on the “GCA” dataset revealed the existence of genetically distinct populations among those sampled in the GCA. However, they do not perfectly match with broad ethnic groups recognized according to individual self-reported affiliations. In fact, while Sherpa people from the Rolwaling Himal (SRH) gathered into a single well-defined cluster, Tamangs from Tashinam (TAT) and from Simigaon (TAS) occupied different positions in the PCA space. In particular, TAS cluster was displaced toward a few Indo-Aryan speaking individuals (IAR), which were considerably scattered along PC1 .In detail, SRH spread along the Sherpa cline together with samples from KhumbuADMIXTURE analysis Fig.  used to 25, Sherpas were found to be enriched in a specific ancestry component that in our study became appreciable for K values ≥ 4  and other EA populations. Moreover, high-altitude TIB also showed significant signatures of admixture involving non-admixed Sherpas (i.e. SRH and SHT) and several low-altitude EA populations.These admixture patterns received further support from the linkage disequilibrium (LD) decay-based approach implemented in the ALDER program, which also provided time estimates for the inferred admixture events (Supplementary Table A pattern of remarkable SRH intra-population homogeneity (Supplementary Information) emerged from the analyses of uniparental haplotype diversity . We thus selected a subset of EA populations and conducted two separate CHROMOPAINTER runs. In the first case (a), we searched the best matching DNA segments from individuals of each population (“recipients”) in every other individual from all the considered populations (“donors”) and by allowing for “self-copy” . Accordingly, we expected that supposed differential drift levels between Himalayan groups  would make their painting profiles substantially different. In the second case (b), we excluded these populations from the donor groups in order to remove the hypothesized drift effect and to estimate haplotype sharing of Himalayan populations with respect to all the other groups. In case a) SRH and SHT derived most of their haplotype segments from themselves , while the remaining ones derived from each other . On the contrary, TIB presented only 31% of “self-copy”, with the vast majority of haplotype segments being instead shared with neighbouring EA populations   Fig. . In caseas) Fig. , indicatas) Fig. .f3 statistics to measure shared genetic drift between GCA samples and a large set of SA/EA groups to pinpoint a plausible proxy for the ancestral population that could have introduced the EA and “Sherpa-like” genetic components in Tibeto-Burmans residing South of the Himalayas. As expected, SRH showed the highest f3 values when compared respectively with the Sherpas from Khumbu and TIB . This confirmed that TAS and TAT were more closely related to Nagas than to TIB, while the Sherpas showed closer affinity to TIB than to any other EA population . The topology of the obtained tree was conserved for all the 500 bootstrap replications performed and revealed the existence of three main EA clades that mirror the EA ancestry components pointed out by ADMIXTURE analyses. The North EA-like cluster of Yakuts branched out first and then the South EA and the Tibeto-Burman clades diverged. Within this latter group, Nagas branched out before differentiation of the Sherpas from TIB  and Naxi (498/500 replications) were proposed to originate from the admixture between Nagas and Dai. A population located on the internal node branching after the split of Birhor from Brahui was supposed to have admixed with either Nagas or a group ancestral to the divergence between Nagas and the Tibetan/Sherpa cluster, resulting in Manipuri (491/500 replications). The same SA population could have admixed again with Nagas leading to the origin of Tharu (495/500 replications). The most frequent observation for Jamatia (314/500 replications) and Tripuri (388/500 replications) pointed them as an admixture between populations located on internal North SA nodes and a putative group occupying the internal node before the divergence between Nagas and the Tibetan/Sherpa cluster. Finally, Burma presented the same source of SA ancestry of Jamatia and Tripuri, even though their EA ancestral component had nearly the same probability to derive from the internal node of Dai (258/500 replications) or of Tibeto-Burmans (237/500 replications) Fig. .We applied HAPMIX to infer local ancestry and to mask the SA ancestry chunks of Tibeto-Burman groups residing South of the Himalayas. This resulted in a clear detection of their EA ancestry as tested by projecting masked haploid data in the PCA space computed on a large set of SA/EA populations  and then to the Nagas . This confirms their recent common ancestry and suggests that differences between them are probably due to recent geographical isolation experienced by TAT, as suggested also by their high levels of homozygosity pointed out by ROH analyses , in line with the hypotheses of a recent historical arrival of the first Tamang tribes in Northern Nepal28. More accurate demographic tests (outgroup f3 and D-statistics) revealed that, in addition to different admixture patterns, also a recent shared history could be ruled out for the SRH and Tamang groups, despite that they showed a similar profile of Y-chromosome lineages  and Sherpas on the southern slopes of the Himalayas. This sheds new light on an open debate regarding the most plausible source of EA ancestry in Nepalese Tibeto-Burmans20. In fact, contrary to previous hypotheses19, our results prove that the Himalayas in most cases served as a barrier to gene flow even from North to South.In contrast, the Nepalese Tibeto-Burmans appeared to have maintained remarkable internal homogeneity, with limited genetic exchange with people of SA ancestry, most pronounced in TAS. Patterns of SA/EA admixture confirmed by f3 and ALDER analyses. Moreover, they showed reduced mtDNA and Y-chromosome diversity with respect to a large set of SA/EA groups , but is not exclusive to Himalayan populations, being shared between several other EA and SA groups. Interestingly, most populations showing significant proportions of such a component speak Tibeto-Burman languages, with the highest values observed for Nagas and Tamangs (42%–52%), setting aside high-altitude people. We argue that these findings indicate a shared ancestry among Tibeto-Burman speaking groups, which is currently in the highest proportion in the Sherpas and more diluted in other populations due to gene flow with nearby non-Tibeto-Burman gene pools, as shown for Tibetans34 and for other Tibeto-Burmans in this study  are well fitted as results of admixture between Nagas  and other populations Fig. . Accordiset Fig. . In factWe provided new insights into the network of migration and admixture events occurred on the southern slopes of the Himalayas, thus contributing to fill, at least partially, the gap of knowledge related to such a largely understudied area. In particular, by considering a previously unsurveyed Nepalese Sherpa community that is distinct from those from the Khumbu region, we attempted to disentangle the impact of admixture and drift on the history of Himalayan populations. In fact, we found genomic evidence for their common origin, which was however followed by diverging histories characterized by variable degrees of genetic isolation and recent admixture with several sources of low-altitude EA ancestry. Nevertheless, it is noteworthy to mention that the differential levels of admixture with low-altitude East Asians observed in the examined Himalayan groups should caution about the fact that the genetic structure of high-altitude Tibetan/Sherpa populations could be more complex than previously thought. Finally, we argued that Tibeto-Burman groups residing South of the Himalayas did not derive their East Asian ancestry components from the Tibetan/Sherpa lineage, which indeed originated from a branch of ancestral Tibeto-Burmans that seems to have remained confined to high-altitude regions. Instead, the peculiar East Asian genetic makeup of Southern Himalayan Tibeto-Burman populations relates to a low-altitude gene pool for which the Nagas represent a plausible present-day proxy. This ancient genetic background was progressively reshaped by admixture events having involved a number of EA/SA populations and likely occurred along migratory routes that, by circumventing the Himalayas, diffused Tibeto-Burman ancestry components from China to Nepal across India and/or Myanmar Fig. . TherefoBuccal swab and saliva samples analyzed in this study were collected during three scientific and humanitarian expeditions conducted in the Nepalese GCA in partnership with the ExPlora Nunaat International nonprofit organization. Such a sampling campaign focused on three main ethnic groups residing in the GCA and involved different villages of the Dolakha District distributed along a wide altitudinal range: Jagat , Simigaon , Tashinam , Beding , and Na  , which was designed and conducted in accordance with relevant guidelines and regulations and according to ethical principles for medical research involving human subjects stated by the WMA Declaration of Helsinki.prepIT-L2P protocol . We then quantified purified DNA with the Quant-iT dsDNA Broad-Range Assay Kit . All the 92 collected samples were sequenced for mtDNA hypervariable regions I and II (HVSI and HVSII) by means of Sanger sequencing and using the BigDye Terminator v3.1 Cycle Sequencing Kit . A subset of 63 male individuals were also typed for 23 Y-chromosome STRs loci using the PowerPlexY23 System kit . Typing of uniparental markers was performed at the Molecular Anthropology Lab of the University of Bologna. 75 samples were then selected to be genotyped for ~720,000 genome-wide SNPs with the HumanOmniExpress v 1.1 chip . Genotyping was performed at facilities of the Human Genetics Dept. of the University of Chicago and at the Center for Biomedical Research & Technologies of the Italian Auxologic Institute.We extracted DNA from buccal swab via a Salting Out modified protocol and from saliva samples collected with the Oragene DNA (OG-500) kit with the A detailed description of the analyses on uniparental haplotypes as well as of the quality control (QC) and merging steps on the genome-wide datasets are provided in Supplementary Information.35, a “GCA” dataset consisting of 59 samples successfully typed for 683,180 SNPs was generated. An “extended” dataset of 263,855 SNPs was also obtained by merging GCA genotypes with publicly available genome-wide data retrieved from phase 3 of the 1000 Genomes Project36, the HGDP project10, as well as many published studies focused on SA and EA groups (Supplementary Table 2 < 0.2) and by removing sites with a minor allele frequency (MAF) < 0.01. Such a pruned dataset was also used to measure ROH. For these purposes, the number of genomic segments in homozygosity and their mean length were calculated with PLINK v1.07 by applying default parameters settings.After QC performed with PLINK v1.0737 using default parameters and HapMap phase 3 recombination maps.Haplotype-based population structure analyses and local ancestry inference were instead applied on the unpruned “extended” dataset. Haplotypes phasing was performed by means of the statistical-based approach implemented in SHAPEIT2 v2.r790smartpca method implemented in the EIGENSOFT package v6.0.138.PCA was applied sequentially on the LD-pruned versions of both “GCA” and “extended” datasets to check for the presence of potential genotypes inconsistency due to errors occurred in the merging procedure, as well as on a subset of 75 Asian groups selected from the “extended” dataset. To compute PCA, we used the 39 assuming K = 2 to K = 12 ancestral populations. We ran fifty replicates with different random seeds for each K to monitor for convergence and only those presenting the highest log-likelihood values were plotted. Concurrently, we calculated cross-validation (CV) errors for each K in order to identify the most plausible number of ancestry components. Once verified that GCA samples showed no signatures of recent admixture involving ancestry sources ascribable to non-Asian populations, we replicated admixture analyses with the same procedure to test K = 2 to K = 10 putative ancestral groups on a representative subset of Asian populations.To obtain an overall picture of ancestry proportions for each examined genome, we applied the model-based clustering algorithm implemented in ADMIXTURE v1.22f3)40 using the ADMIXTOOLS v3.0 package41. Z-scores were calculated via a Block Jack-knife approach to assess test significance and potential source populations (i.e. those showing significant Z-scores ≤ −2) were submitted to further validation with ALDER v1.0342. This method was also used to derive the number of generations since admixture by fitting one exponential curve (i.e. assuming a single pulse of admixture) to the data. Obtained results were converted in time estimates for the inferred admixture events by assuming 25 years per generation.To formally test for admixture, we performed the three-population test , we used ADMIXTOOLS v3.0 to measure shared genetic history between two populations via the outgroup f2 statistics between each population pair by applying the procedure implemented in MIXMAPPER v2.045 and we used it to construct a neighbor-joining tree of non-admixed Asian populations selected according to f3 results. Supposed admixed populations were then fitted in the scaffold tree by resolving f2 statistics between them and each of the non-admixed groups. To evaluate the robustness of the topology of scaffold trees and of the branch point for test populations, we conducted 500 bootstraps replications.We further explored phylogenetic relationships between GCA populations, other Tibeto-Burman groups included in the “extended” panel, and putative source populations pointed out by the above-mentioned analyses, by taking into account recent admixture involving SA and EA groups. For this purpose, we calculated a matrix of 46 to “paint” haplotypes of single individuals as mosaics of all other individuals’ haplotypes observed in the dataset. For each of the performed CHROMOPAINTER runs (see Results), we first estimated the mutation/emission and the switch rate parameters with 10 steps of the E-M algorithm on a subset of chromosomes {4, 10, 15, 22}. We then averaged the obtained values across chromosomes, weighted by the number of markers, and then across individuals. We finally run CHROMOPAINTER on all chromosomes using the estimated mutation/emission and switch rate parameters.We used CHROMOPAINTERv2et al.47 by applying the dedicated functions implemented in GLOBETROTTER48 and modified as described in van Dorp et al.31 thus allowing “self-copy” between individuals belonging to the same group in order to account for intra-population haplotype sharing.To infer individual ancestry proportions (i.e. the average proportion of the genome that each recipient population copies from the donor groups), we combined the copying length matrixes between chromosomes and we obtained an estimate of the total genomic length that each recipient individual copies from each donor population. Then we performed multiple linear regression as described in Leslie 49 to infer local ancestry of Tibeto-Burmans identified as admixed by assigning an ancestry probability score for each SNP. Chunks of contiguous ancestry in the haplotypes of tested admixed individuals were identified given haploid data from two sets of reference ancestral populations. We selected as reference SA and EA 1000 Genomes Project populations included in the phased “extended” dataset. We used the mean number of generations since admixture inferred with ALDER and we recovered proportions of SA and EA admixture for individuals submitted to ADMIXTURE analysis at K = 2, finally calculating the mean proportion for each of the tested groups. We then selectively masked chunks of the genome assigned to EA ancestry with a probability lower than 90%.We used the algorithm implemented in HAPMIX v1.1lsqproject = YES function implemented in EIGENSOFT v6.0.1 to project Tibeto-Burman EA ancestry-specific samples (EA-TB) on the PCA space and overcoming potential bias related to the several missing data included in the EA-TB dataset. We then replicated PCA on a subset of EA populations. Finally, to test how the EA-TB relate to the other EA populations, we computed outgroup f3 statistics as described above.To validate results of local ancestry inference, we performed PCA on a set of 75 Asian populations using the http://www.bioanthropologybologna.eu.The dataset generated during the current study is available at the Molecular Anthropology Lab repository, Supplementary InformationSupplementary Tables S1-S8


Rana temporaria) populations in Southern Palatinate (Germany). We analyzed microsatellite data of ten loci from ten breeding pond populations located within viniculture landscape and in the adjacent forest block and compared these results with a previously developed landscape permeability model. We tested for significant correlation of genetic population differentiation and landscape elements, including land use as well as roads and their associated traffic intensity, to explain the genetic structure in the study area. Genetic differentiation among forest populations was significantly lower (median pairwise FST = 0.0041 at 5.39 km to 0.0159 at 9.40 km distance) than between viniculture populations (median pairwise FST = 0.0215 at 2.34 km to 0.0987 at 2.39 km distance). Our analyses rejected isolation by distance based on roads and associated traffic intensity as the sole explanation of the genetic differentiation and suggest that the viniculture landscape has to be considered as a limiting barrier for R. temporaria migration, partially confirming the isolation of breeding ponds predicted by the landscape permeability model. Therefore, arable land may act as a sink habitat, inhibiting genetic exchange and causing genetic differentiation of pond populations in agricultural areas. In viniculture, pesticides could be a driving factor for the observed genetic impoverishment, since pesticides are more frequently applied than any other management measure and can be highly toxic for terrestrial life stages of amphibians.Amphibian populations have been declining globally over the past decades. The intensification of agriculture, habitat loss, fragmentation of populations and toxic substances in the environment are considered as driving factors for this decline. Today, about 50% of the area of Germany is used for agriculture and is inhabited by a diverse variety of 20 amphibian species. Of these, 19 are exhibiting declining populations. Due to the protection status of native amphibian species, it is important to evaluate the effect of land use and associated stressors  on the genetic population structure of amphibians in agricultural landscapes. We investigated the effects of viniculture on the genetic differentiation of European common frog ( The survival of amphibian wildlife populations is threatened by habitat loss, fragmentation of populations, diseases, invasive species, climate change and toxic substances . UnderlyThe expansion and intensification of agriculture also involves input of a wide variety of agrochemicals into the environment. Pesticides play a crucial role in this context, since they can be highly toxic to terrestrial life stages of amphibians . AdditioAn indirect method to assess the effect of fragmentation on amphibian breeding pond populations is the use of neutral molecular markers, such as polymorphic microsatellites, i.e., non-coding DNA sequences consisting of tandem repeats and exhibiting high mutation rates . By combRana temporaria LINNAEUS 1758 (European common frog) breeding pond populations from a viniculture landscape, using ten polymorphic microsatellite loci. Also, we analyzed four populations from the adjacent Palatinate Forest as a reference for widely unhindered gene flow. We tested for significant correlation of genetic population differentiation and landscape elements, including land use and linear barriers (roads and their associated traffic intensity), to explain the genetic structure in the study area. If viniculture acts as a migration limiting barrier for amphibians, we would reject the null hypothesis of a meta-population in the study area and rather expect a detectable genetic structuring among the analyzed R. temporaria breeding pond populations. Also, we compared the estimated genetic differentiation with the results of a landscape permeability model from the same study area  were located in the vineyards of Southern Palatinate and four (P7–P10) were inside the adjacent Palatinate Forest. The distance between the sampled ponds P1–P9 varied between about 0.9 and 15 km, whereas P10 was located about 40 km northwest of the core study area near Kaiserslautern  of R. temporaria per breeding pond  and hatched them in 300 ml glass bottles filled with tap water to Gossner stages 20–25. Sampling was approved by the Structure and Approval Directorate South of Rhineland-Palatinate, department 42, Upper nature conservation authority . Three tadpoles per clutch were randomly selected for genetic analysis. Since females of R. temporaria typically lay a single clutch per breeding season  and allelic richness (NAR) using FSTAT 2.9.3.2  approach . This apTo examine the genetic structure of the sampled populations, the Bayesian clustering software STRUCTURE 2.3.4  was usedAs we expected some genetic exchange between populations, but an overall weak population structuring, we chose the admixture model with imposed sampling locations (LOCPRIOR). The model was calculated with an initial burn-in of 100, 000 and a Markov Chain Monte Carlo (MCMC) of 500, 000 repeats for each subset and each predefined cluster number K between 1 and 9. To determine the most likely number of clusters K, the program STRUCTURE HARVESTER  was usedFST and RST as well as for observed (HO) and expected (HE) heterozygosity calculations we applied the RRSG approach with 100, 000 calculations using GenePop. Only one individual genotype per clutch was automatically selected in each calculation, thus producing results for linkage disequilibrium, FST, RST, HO and HE values based on data without full-siblings. For interpretation, we used median pairwise FST (MPF) and median pairwise RST (MPR) values as well as median HO and HE values over all RRSG calculations. For the interpretation of the linkage disequilibrium we, calculated a possibility of linkage for each loci pair by forming a quotient of number of calculations where linkage was detected  divided by total number of calculations of the RRSG approach. We considered a loci pair linked when 5% or more of the 100, 000 calculations detected a statically significant linkage disequilibrium for the respective loci pair.For linkage disequilibrium over all populations, population pairwise We calculated a distance matrix for the breeding ponds and analyzed isolation by distance for MPFs and MPRs over all breeding pond pairs using Genepop’s subprogram ISOLDE . We usedTo address the spatial configuration of habitat types between breeding ponds, we adjusted the linear geographic distance with respect to present habitat types. Therefore, we obtained land cover data (ATKIS) of the study area from the State Office for Surveying and Geobasisinformation Rhineland-Palatinate (2015). We calculated the area of habitat types  and length of roads in a 200 m wide strip between breeding ponds. Since the vinicultural study area has, apart from of the ponds and their surrounding areas, no mentionable hideout and hibernation options for amphibians, we limited our analysis of the spatial configuration to the most direct migration routes for amphibians between ponds. Assuming an average daily migration distance of 100 m , 200 m wR2 of MPF as well as MPR and the corrected linear geographic distance. Afterwards, we used ISOLDE to analyze isolation by distance for MPFs as well as MPRs and the corrected linear geographic distance with the relevant habitat correction factor provided by the weighted distance model, for each habitat type separately. Finally, we combined all habitats . On the other hand, negative habitat types like settlements and viniculture may decrease the daily migration distance due to unfavorable migration conditions. In a weighted distance model, such positive and negative effects of habitat types on the migration of amphibians between breeding ponds can be addressed. We adapted a weighted distance model , which ctats see  and 3 thWe detected deviation from Hardy-Weinberg-Equilibrium due to heterozygote deficits on two loci (BFG082 and BFG129) over all populations. Forest populations showed higher values for number of sampled alleles and allelic richness in comparison to population viniculture . Over alK = 4 as the most meaningful number of clusters in our data set , P1, P2 and P4 still formed individual clusters, while the rest of the populations where assigned to the same cluster up to K = 7 (STRUCTURE HARVESTER identified  set see . For K =to K = 7 .HE = 0.852), all pond populations located in viniculture showed lower levels of heterozygosity over all loci (HE = 0.663–0.776) than populations located in the Palatinate Forest . Isolation by distance was statistically significant for MPFs of the four forest populations (p = 0.0320). However, when excluding the most distant population P10, isolation by distance was no longer statistically significant.Over all breeding pond populations, ISOLDE detected no statistically significant relation between MPFs or MPRs and linear geographic distance, number of roads or accumulated traffic intensity between population pairs  for viniculture and forest .When analyzing the linear geographic distances corrected by the weighted distance model, isolation by distance was statistically significant  of linkage disequilibrium were also detected for multiple loci pairs located on different chromosomes and for which linkage is thus unlikely. Moreover, the linkage calculations were performed over the whole dataset as one metapopulation. This could have additionally affected the linkage analyses due to the underlying population structuring, since specific allele combinations might only occur in some fragmented populations, thus inferring linked inheritage of respective loci. The vice versa assumption, that genetically linked loci might have inferred the detected population fragmentation by structure as unreal signal in our data, can be rejected, since our analyses for gene flow among all populations  as isolated from the meta-population . MoreoveRana temporaria clutches at P8, which were intentionally moved into the nearby stream due to drought by staff of the “Modenbacher Hof”, a close-by horse ranch. This stream is connected directly to P3. During major rain events, some of the clutches could have been flushed into the pond at P3. Surviving amphibians could then have contributed to the following reproduction phases, resulting in a one directional genetic exchange and explaining the rather low MPF value of 0.0179 between P3 and P8.Breeding pond populations in the agricultural landscape with a direct connection to the Palatinate Forest by permanent or seasonal streams exhibited lower MPFs to forest pond populations compared with agricultural pond populations not connected to the forest , indicatRana arvalis (FST = 0.06) in Noord-Brabant, Netherlands, where landscape permeability was low due to farming intensity and urbanization . Negative effects of high agricultural intensity on the occurrence, abundance and genetic diversity of amphibians on a regional and national scale were also found in several other studies  fungicide applications per year, within intervals of about 10–14 days between early May and mid-August  year of life  and can affect amphibians not only on the application day, like tillage operations, but up to several days after application, depending on the chemical decomposition of pesticides. Recent studies and surveys confirmed the presence of pesticides in amphibian habitats and waterbodies in general , as wellWe were not able to address differences between organic and conventional viniculture, since reference breeding sites with noteworthy portions of organic viniculture were not available in or nearby the study area. Also, it is currently unclear if the use of copper and sulfur within organic viniculture would actually improve the overall situation for amphibians .In contrast to our and others findings, some studies observed no impact of agricultural land use on the genetic differentiation of amphibians, although the investigated amphibian species were known to forage in intensively managed agricultural areas . Also, sR. temporaria is considered ‘not endangered’ in Germany (Although  Germany  and ‘lea Germany , amphibi Germany . Consist Germany . We repe Germany .Based on our results, we are concerned about the persistence of amphibians in agricultural areas, since we can recognize negative trends on the genetic diversity and differentiation of breeding pond populations. Typical visible barriers like roads with associated amphibian road mortality could not explain the genetic structuring of the breeding sites. Yet we could identify viniculture as a barrier for genetic exchange. Since pesticide applications are the most frequent management measure in viniculture and pesticides can cause high mortalities in amphibians, pesticides may have a major impact on amphibian dispersal and therefore on genetic exchange between breeding sites. Following the precautionary principle it may be advisable to reduce or avoid pesticide applications during amphibian migration phases and to mitigate pesticide contamination of amphibian breeding ponds. We recommend further research on the impact of pesticides on amphibian individuals and populations in agricultural landscapes.10.7717/peerj.3520/supp-1Supplemental Information 1Click here for additional data file.


The ancestry of the Colombian population comprises a large number of well differentiated Native communities belonging to diverse linguistic groups. In the late fifteenth century, a process of admixture was initiated with the arrival of the Europeans, and several years later, Africans also became part of the Colombian population. Therefore, the genepool of the current Colombian population results from the admixture of Native Americans, Europeans and Africans. This admixture occurred differently in each region of the country, producing a clearly stratified population. Considering the importance of population substructure in both clinical and forensic genetics, we sought to investigate and compare patterns of genetic ancestry in Colombia by studying samples from Native and non-Native populations living in its 5 continental regions: the Andes, Caribe, Amazonia, Orinoquía, and Pacific regions. For this purpose, 46 AIM-Indels were genotyped in 761 non-related individuals from current populations. Previously published genotype data from 214 Colombian Natives from five communities were used for population comparisons. Significant differences were observed between Native and non-Native populations, among non-Native populations from different regions and among Native populations from different ethnic groups. The Pacific was the region with the highest African ancestry, Amazonia harboured the highest Native ancestry and the Andean and Orinoquían regions showed the highest proportion of European ancestry. The Andean region was further sub-divided into 6 sub-regions: North East, Central West, Central East, West, South West and South East. Among these regions, the South West region showed a significantly lower European admixture than the other regions. Hardy-Weinberg equilibrium and variance values of ancestry among individuals within populations showed a potential stratification of the Pacific population. This heterogeneity is still maintained in the current Colombian population, whose diversity has been further shaped by admixture with people from other continents. The Andes is the region in which the Chibcha civilization flourished, the third most developed group in the Americas after the Aztecs and the Incas. The Caribbean region is clearly differentiated from the remaining regions, and its territory is inhabited by highly diverse ethnic groups. These two regions, both before and after the European conquest, were and remain the most densely populated and economically active in the country. The other three natural regions include the Pacific region and the forest area that today corresponds to the Orinoquía and Amazonia regions, which are the largest in the territory but the least populated and least economically developed .In a geographic framework, Colombia occupies the southern extreme of the bridge that connects the two American subcontinents. Therefore, since prehistorical times, Colombia has been subject to an intense genetic and cultural flow carried by Native American migrations, which ultimately resulted in a high diversity of ethnic groups inhabiting the country and to a noticeable heterogeneity between geographic regions ,2 , and, and13])logroups ,14–16. Elogroups ,18. Mostlogroups ,20.Although uniparental markers have been useful in revealing differences in populations with respect to paternal and maternal inheritance, a comprehensive description of the genetic profile of populations in terms of ancestry can only be achieved by the study of recombining markers.Regarding recombining autosomal markers, the studies available for Colombia have been even more fragmentary than for lineage markers and have only considered a restricted number of markers and/or population groups e.g., ,7,15,21),15,217,1Considering the complex history and the high genetic heterogeneity of the present-day populations in Colombia, more comprehensive studies are still required for a fine-scale mapping of the admixture structure of the country, which is crucial in many applied fields, including clinical and forensic genetics ,24.In an attempt to contribute to a better understanding of the ancestry of Colombians, in the present work we used a panel of 46 autosomal ancestry-informative insertion/deletion markers (AIM-Indels) to characterize patterns of variation across Native and non-Native Colombian populations from different geographic regions.The AIM-Indels that we used were previously selected by Pereira et al.  for infeGenetic variation in the Native and non-Native populations occupying the five continental regions following the settlement of Colombia  was investigated with an emphasis on the Andean region, which currently represents almost 80% of the total population . The results revealed a highly stratified population in terms of ancestry that should be considered when delineating studies and/or interpreting genetic data in different areas of research.All samples involved in the study were anonymised DNA extracts that had been previously obtained from healthy, unrelated individuals. Blood samples were collected by free and written informed consent for research purposes. The current study complies with the ethical principles of the 2000 Helsinki Declaration of the World Medical Association and, together with the informed consent, it was approved by the Ethics Committee of the Pontificia Universidad Javeriana of Colombia.A total of 761 samples were collected from unrelated individuals from 28 of the 32 departments of Colombia, as indicated in A larger sample was collected from Departments in the Andes because this is the most densely populated region of Colombia. This region was further subdivided into 6 sub-regions. The location and number of samples included in this study for each Natural Region of Colombia and for the Andean sub-regions are indicated in DNA was extracted following the salting-out protocols described by Miller et al. . DNA quaFor analysis, we included data from Native Colombian populations that were previously studied for the same AIM-Indel markers. These included (i) Natives living in the Cauca region; (ii) Emberá-Chami living in the Antioquia Department; (iii) Natives living in Guainía; (iv) Motilón-Barí living in Norte de Santander; (v) and Pijao from the Tolima Department ,29. ThesAll samples were genotyped for 46 AIM-Indel markers distributed across the autosomal genome. PCR reactions were carried out in a single multiplex containing all 46 primer pairs according to the protocol described by Pereira et al.  after ad® 3500 Series Genetic Analyzer . Automated allele calls were obtained with GeneMapper v.4.1 software .Dye-labelled PCR amplified fragments were separated by capillary electrophoresis and detected using an Applied BiosystemsFST genetic distances and resulting non-differentiation p-values, were assessed using Arlequin v3.5 [p-value of the test is the proportion of permutations leading to a FST value larger or equal to the observed one. A multidimensional scaling (MDS) plot of the pairwise FST matrix was created using the software STATISTICA v7.0. .Genetic diversity parameters, including the estimation of allele frequency, observed and expected heterozygosity, Hardy-Weinberg values, uin v3.5 . Using tThe apportionment of genetic ancestral contributions to the different regions of Colombia was estimated as the mean of each ancestry across individuals, using Admixture v1.3 software . As suggp-values below 0.05 were also observed for six additional markers in the Pacific population sample; in most cases (six out of seven), these markers were associated with an excess of homozygotes.The genotyping results obtained for the 761 Colombian samples from the present work and the 121 samples from the Native groups examined in Ossa et al.  are listBased on geographical criteria, Colombia can be divided into six natural regions, with the three Andes Mountain branches  separating the two coastal regions (Pacific and Caribe) from the two inner regions (Orinoquía and Amazonia). A sixth region includes the islands in both the Caribbean Sea and the Pacific Ocean (Insular region).The apportionment of ancestral genetic contributions from Africa, Europe, and Native America were estimated in five continental regions of Colombia: Caribe, Andes, Orinoquía, Amazonia and Pacific . The preThe Andes region had the highest European contribution, but also revealed a marked Native American contribution. Together with Amazonia, this region had the lowest values of African ancestry. A similar genetic ancestry profile was observed in Orinoquía, although with slightly higher Native American and African components than in the Andean region.The high European contribution in Andean populations is in accordance with historical data because, during European colonization, the Magdalena River, located between the Central and Western branches of the Andes, was the main route of dispersal through the interior of the territory.Amazonia had low values of both European and African gene flow, while more than 65% of its genes are Native American. This is probably due to the geographic isolation of this region, which has the lowest population density in the country. Although it had a higher proportion of non-Native influx than some Native groups  originate in different ethnic groups that share linguistic and cultural affinities. They lost their original language, and their culture and religion experienced some degree of acculturation with Hispanic influence .The similarity in the proportion of Native ancestry found in the Pijao and the population from Amazonia highlights the importance of geographic isolation in the preservation of high levels of Native ancestry in non-Native communities. It also emphasizes that the self-perception of belonging to an ethnic group cannot be determined by genetics alone, as it is the case of the Pijao indigenous community in Colombia that although subjected to a high European admixture still preserves Native American ancient traditions.th and 17th centuries, a large number of African slaves were brought to work in gold mines and, during this period, the African population become predominant. This population pattern was reinforced with the abolition of slavery in the 19th century, when a large number of Africans came to this region, especially from the Department of Cauca.As expected from its historical African background, the sample from the Pacific region has 63% African ancestry and the lowest values of both European and Native American ancestries of all regions in the country. After the arrival of the Europeans, the Pacific coast suffered different migration waves that changed its original Native American genepool. During the 16Although much lower than in the Pacific, the Caribe region also presents a significant African ancestry (23%), which can be explained by the role of Cartagena as one of the most important ports in South America during the slave trade.The Andes is the most densely populated region of Colombia. Based on cultural criteria, this region was divided into six sub-regions: Central West, West, South West, North East, Central East, and South East. When comparing the ancestry of populations across the Andes, all sub-regions are characterized by a predominant European contribution . Native The highest African contribution (14%) is found in the West sub-region , which is the Andean region that is closest to the Pacific coast. The two southern regions, including populations from the Departments of Tolima, Huila (South East), Nariño, Cauca and Putumayo (South West), have preserved a marked Native American ancestry (37–44%).The North East (comprising the Norte de Santander and Santander Departments) and Central East (Cundinamarca and Boyacá) sub-regions presented a similar ancestry profile and, although these two Andean sub-regions had been early colonized by Europeans that largely displaced the Native populations, their samples exhibited lower European ancestry than those from the Central West region.In this study, we obtained higher differences among European, African and Native American contributions than Ibarra et al.  due to tThe results we obtained are more difficult to reconcile with those reported by Rojas et al.  for elevIn previous studies, the ancestry of four Native groups from the Andes was investigated using the same set of AIM-Indel markers employed in this work ,29. WhenTo investigate the signals of recent admixtures or population stratifications, we compared the variations in individual ancestry estimates within the studied populations. Therefore, African, European and Native American membership proportions were assessed using the Admixture software, and the results are presented in The high intra-population variation found in the Pacific regions can be the result of (i) recent migration and admixture between two groups that differ in their African ancestry; (ii) the presence of population substructure in an old admixed population; or (iii) both. A recent migration of Africans is known to have occurred to the North Pacific region after the abolition of slavery. However, the new incomers joined a population that was already known to harbour an important African component. Therefore, a certain degree of population substructure can be expected in the Pacific population.In conclusion, regions with less European admixture showed higher ancestry variation among individuals, indicating more recent admixture events and/or a stronger stratification of these populations.FST genetic distances were calculated between Native and non-Native populations from Colombia and three reference samples from Africa, America and Europe.Pairwise As expected, higher values of genetic distance were obtained for the AIM-Indels included in the present work than for the SNPs previously studied by Ibarra et al. , which hSignificant differences were observed between Native and non-Native populations, as well as among non-Native populations from different regions and among native populations from different ethnic groups . When coIn the MDS plot, the Pacific sample appears closer to the African reference sample, the Amazonia sample is closer to the American Native sample, and the Andean, Orinoquía and Caribbean samples are closer to the European reference sample .In summary, the position of the non-Native populations in the MDS plot closely follows the expected results based on the ancestry estimates. The high genetic distances observed between Native populations with low non-Native American influx  cannot be explained solely by differences in the ancient background of these populations; these populations must have been subject to a strong genetic drift, including founder and/or endogamy events.Genetic differences among nearby Native American groups have been previously reported based on different types of markers, namely mtDNA, Y chromosome, HLA class II variation and ancestry informative SNPs ,16,34–36Methods of inference of genetic ancestry usually model hypothetical ancestral populations or rely on the use of samples representing those putative ancestral contributors. This modelling is not always a straightforward task because, for most genetic studies, only contemporary populations are available to be used as a reference. Such populations may harbour a more or less preserved ancestral genepool. Concerning the populations under study, it is believed that since the first admixture events with Europeans or Africans, an important part of Native American genetic diversity has been gradually lost. This loss of diversity has been caused by genetic drift, creating noticeable genetic distances among groups.Therefore, considering the perceptible differentiation among the Native American groups discussed above, we further assessed its putative impact in the inference of genetic ancestry when, for instance, using different groups as the Native American reference population. This study provides a general picture of the ancestry of the Colombian populations from the five continental regions of the country, complementing previous information on lineage and recombining markers. The overall results revealed a highly stratified population in terms of ancestry both between and within delimitated natural regions. This stratification should be taken into account when delineating studies and/or interpreting genetic data in different areas of research.S1 FigEach individual is represented along the x-axis, by three points corresponding to the differences in African, European and Native American ancestries to the average.(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 TableFor loci with 3 alleles in a population sample, the frequency of a second allele  was also indicated.(XLSX)Click here for additional data file.S3 Tablep-values above 0.05 are indicated in pink, and those below 0.001 are indicated in yellow.(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.


Aedes albopictus, the “Asian tiger mosquito,” is an aggressive biting mosquito native to Asia that has colonized all continents except Antarctica during the last ~30–40 years. The species is of great public health concern as it can transmit at least 26 arboviruses, including dengue, chikungunya, and Zika viruses. In this study, using double‐digest Restriction site‐Associated DNA (ddRAD) sequencing, we developed a panel of ~58,000 single nucleotide polymorphisms (SNPs) based on 20 worldwide Ae. albopictus populations representing both the invasive and the native range. We used this genomic‐based approach to study the genetic structure and the differentiation of Ae. albopictus populations and to understand origin(s) and dynamics of the recent invasions. Our analyses indicated the existence of two major genetically differentiated population clusters, each one including both native and invasive populations. The detection of additional genetic structure within each major cluster supports that these SNPs can detect differentiation at a global and local scale, while the similar levels of genomic diversity between native and invasive range populations support the scenario of multiple invasions or colonization by a large number of propagules. Finally, our results revealed the possible source(s) of the recent invasion in Americas, Europe, and Africa, a finding with important implications for vector‐control strategies. The pcadapt does not require grouping individuals into populations . Finally, we grouped the samples based on the sampling locality or their geographic group and compared the mean Ho per group among the following groups: (1) global , (2) native , (3) invasive , (4) Cluster1  using VCFtools and dividing the number of heterozygous loci by the number of genotyped loci in each individual. Based on Trucchi et al. , a numbeter1 see  identifiter1 see  identifip > .05) were grouped together in the same region. When the ANOVAs identified statistically significant differences, we implemented a post hoc Tukey test to detect the specific groups that differ in their mean heterozygosity.The nonparametric Kruskal–Wallis test was used to compare the mean heterozygosity between the populations as the small sample size per population  did not meet the assumptions of the parametric tests. One‐way ANOVA was used to compare the means between specified group regions. In all cases, only populations that did not differ in their mean heterozygosity  resulted in 57,931 biallelic SNPs for the global dataset. These SNPs were in the 6,867 scaffolds, which encompass ~58% of the total reference genome size (bp). The average sequence depth per individual was 16.04X ± 6.42X (SD), and the average coverage per site was 16.04X ± 6.64X (SD). The amount of missing data on a per individual was 16.15% ± 11.8% (SD) and on a per‐site basis 16.15% ± 8.44% (SD). The invasive dataset  had an average sequence depth per individual of 16.30X ± 6.75X (SD) and an average coverage per site of 16.30X ± 6.83X (SD). The native dataset  had an average sequence depth per individual of 15.04X ± 5.42X (SD) and an average coverage per site of 15.05X ± 6.18X (SD). The amount of missing data on a per‐individual basis  as well as on a per‐site basis  was similar to the global dataset.3.2p = .002) than the Fst values between sites from the same or different continents from the invasive range, although in both ranges, two genetic groups are present (Cluster1 and Cluster2), as indicated by the Admixture analysis in the global dataset . The next best clustering for K = 3 is presented as pie charts in Figure Q values > 0.75). However, some samples from both the native (Singapore and Vietnam) and invasive  ranges show evidence of genetic admixture. Several individuals have low mean Q values , suggesting that they could be the results of recent matings between individuals belonging to the two different clusters or retention of shared ancestral polymorphisms.Admixture analysis for the global dataset supported the existence of two genetically distinct clusters, each including populations from the native and the invasive range. Cluster1 .Genetic diversity Figure  was stud4Ae. albopictus has spread from it native Asian range to all continents except Antarctica, making it one of the most invasive mosquitoes on the planet . As the ddRAD tags are randomly distributed across the genome, this method makes it possible to affordably screen a large number of genomic regions in many samples. Despite the fact that only a small percentage (~6%) of the reference genome scaffolds are represented in our datasets, these are the longest scaffolds, covering more than 1 × 109 bp (out of the ~1.9 × 109 bp). This suggests that the small proportion of scaffolds in our dataset is due to the fragmented nature of the reference genome  rather than to a bias with our dataset.The implementation of the ddRAD sequencing enabled us to identify ~58,000 biallelic SNPs across the genome of The use of two REs during the ddRAD library preparation provided consistency in markers recovery . This consistency in marker recovery increases the possibility of retrieving the same loci to be sequenced across all the individuals and reduces the amount of missing data compared with other similar methodologies that use only one restriction enzyme [i.e., RAD‐tags  and the fact that they appear as a monophyletic group  reveals the human‐mediated transport. The discrepancy between this study and that of Manni et al. , did not find the genetic differentiation within the native Asian range  varies among population and sampling regions Figure . Within Ae. albopictus invasive populations , as has been proposed to explain the lack of a genetic signature of “founder effects” for the US 5Ae. albopictus and used them to provide baseline data on the evolutionary history of this highly invasive vector species. The evolutionary scenario emerging from our analyses confirms the results of other studies in describing a complex invasion history with multiple independent invasions and/or invasion of a large number of colonists from both native and previously invaded areas, followed in some cases by genetic intermixing between samples from different genetic backgrounds. Our results are novel because the power of ~58,000 SNPs distributed across the genome enabled detection of differentiation within regions that was not revealed in studies using less powerful genetic markers. These findings have profound implications for control and monitoring of this important disease vector, as they can reveal the mosquitoes' mode of transportation, the likelihood of recurrent invasions and help predict the chance of establishment based on climate matching between source and invasive localities. Furthermore, different regions of the world use different insecticides, so identifying invasion sources can help predict the effectiveness of insecticides due to resistance in the source population(s). Additionally, as Ae. albopictus populations vary in viral competence  and traits related to disease transmission, which can then be used to develop new strategies and targets for vector control. The availability of a common set of tens of thousands of variable genome markers enables independent studies to be combined and thus to take advantage of cumulative knowledge and data.The datasets used and/or analyzed during the current study are available from the PI of the study (AC) on reasonable request.None declared.PK carried out part of the molecular laboratory work, data analysis, and sequence alignments and drafted the first version of the manuscript. JBR carried out part of the molecular laboratory work and part of the data analysis and helped draft the manuscript; VP carried out part of the molecular laboratory work and helped draft the manuscript; PAA GF SU AJM provided samples and revised the manuscript critically for important intellectual content; AC and PAA conceived of the study, designed and coordinated the study, and helped draft the manuscript. All authors gave final approval for publication. Click here for additional data file.


Percocypris pingi is a near threatened cyprinid species, which has suffered a dramatic decline due to anthropogenic factors. As one response to this decline, hatchery release for P. pingi has been conducted in the lower reaches of the Yalong River since 2012. To understand the conservation status of this species and the potential impact of the release of hatchery-reared fish, we studied the genetic diversity and population structure of wild and hatchery populations of P. pingi. Two hatchery populations (Jinping [JPH] and Ya’an [YAH]) and two wild populations (Muli [MLW] and Woluo [WLW]) of P. pingi were analyzed based on microsatellite markers and the mitochondrial DNA control region. The results showed that P. pingi possesses moderate levels of genetic diversity, with observed heterozygosities ranging from 0.657 to 0.770 and nucleotide diversities ranging from 0.00212 to 0.00491. Our results also suggested WLW harbors considerable proportions of genetic diversity in this species and serves as a refuge for P. pingi during anthropogenic disturbance, thus playing an important role for the conservation of P. pingi populations. Microsatellite and mitochondrial markers both indicated close genetic relationships between YAH and MLW, JPH and WLW, respectively. The results to some extent reflected the geographical provenances for original broodstocks of the two hatchery populations, which provide some practical guidance for hatchery release of P. pingi. The existence of remarkable genetic divergence distributed along limited geographical range (approximately 10 kilometers) suggests the two wild populations should be regarded at least as two distinct evolutionary significant units (ESUs) and management units (MUs). Considering reduced intra-population genetic variation in hatchery population for release and significant genetic compositions of the two hatchery populations, some appropriate breeding strategies were proposed to benefit conservation of P. pingi. Percocypris pingi (Tchang) (Cypriniformes: Cyprinidae) is an important commercial fish [Percocypris pingi prefers lotic habitats and spawns several thousand eggs in these lotic habitats once each spring [P. pingi populations [Percocypris pingi was once widely distributed in the main channel and tributaries of the Yalong River, the largest branch of the Jinsha River, which runs through the provinces of Qinghai and Sichuan in western China. Due to the construction of a number of series of hydropower stations and overexploitation, P. pingi populations in this river have decreased dramatically in recent years, and its distribution range has been drastically reduced [P. pingi in the Qingyi and Dadu rivers were very limited based on our visiting investigation. The continuously deteriorating conservation status of P. pingi has led to its classification as a near threatened species for conservation in the IUCN Red List [P. pingi was classified as Endangered (EN) in the Red List of China’s Vertebrates [ial fish  distribuial fish ,3,4, maih spring . Becauseulations . Percocy reduced ,7. It noRed List , and itstebrates .P. pingi that could provide crucial information relevant for conservation are urgently needed. Conservation management plans with no prior knowledge of the genetic background could result in disturbance to the population structure with adverse effects on the gene pools of wild populations [P. pingi. Previous studies of P. pingi focused more on morphology, anatomy, nutriology, and artificial propagation with a few studies involved with molecular genetic issues [P. pingi population from the Mianning section of the Yalong River, using mitochondrial control region dataset. The genetic diversity and population structure of P. pingi hasn’t been carefully characterized until now, which has posed a major hindrance to conservation and management of this species.Specific conservation strategies, and additional studies on population genetics of ulations . Howeverc issues ,12,13. Oc issues  investigMugil cephalus and Rutilus frisii kutum [P. pingi has been conducted in several institutions, including the Fish Reproduction Station of Jinping-Guandi and the Zhougonghe Yayu Company in Ya’an. In order to restore populations of the species in the Yalong River, artificially propagated individuals have been released into the river by the Fish Reproduction Station of Jinping-Guandi beginning in 2012. In 2012, hatchery-reared P. pingi  were released into downstream of dam of the Jinping II Hydropower Station, the second dam downstream from the Yalong River and Muli River confluence; in 2013, hatchery-reared P. pingi (had body length 4.8–9.2 cm) were released just above of the Jinping I dam and below the Jinping II dam on the same river stretch  Most of the wild fish were collected before the hatchery release in 2013  to ensure that the “wild individuals” collected were not likely to include any hatchery-reared fish. However, due to the small number of P. pingi sampled in the Muli River, additional samples  were collected in December, 2013 (after the release). The released ones of this year all had body length 4.8–9.2 cm and couldn’t grow to the size as that we collected even in December of this year.The wild individuals were caught from the Muli River in September and December, 2013  and Woluo River in October, 2013  . To ensuP. pingi was a listed as a protected species in Sichuan Province, we sampled P. pingi with approval of the Sichuan Municipal Bureau of Aquatic Products  and the Ya’an Zhougonghe Yayu Company  from 2013 to 2014. These samples were preserved in 95% ethanol for DNA extraction.Total DNA was extracted from fin tissues by TIANamp marine animals DNA kit .Twelve tetranucleotide microsatellite markers were used for analyses: Seven  from Deng et al.  and anotAll amplified products were initially examined on 1.5% agarose gels stained with GelGreen at 90 V for 14 min and were then sent to Beijing Microread Genetics Co., Ltd.  for genotyping and fragment analysis. We then read the genotyping data manually from chromatograms. MICRO-CHECKER 2.2.3  was used2O. The PCR was programmed as follows: an initial denaturation at 94°C for 4min; 35 cycles of a denaturation at 92°C for 30s; an annealing at 62°C for 1 min; an elongation at 72°C for 1 min; and a final extension at 72°C for 10 min.The mtDNA control regions were obtained using the primer sets DL1 (ACCCCTGGCTCCCAAAGC) and DH2 (ATCTTAGCATCTTCAGTG) . The PCRAfter amplification, the PCR products were purified using a universal DNA purification Kit DP214-02  and sequenced directly on an ABI 3730XL automatic sequencer by the Invitrogen Corporation . The sequences were then proofread and assembled with the DNA analysis package DNASTAR Lasergene Seqman . All sequences were aligned using the Clustal W application in MEGA 7.0.14  and refiA), mean allelic richness across all loci per locus and per population (Ai), the polymorphic information content (PIC), the observed heterozygosity (Ho), and expected heterozygosity under random chromosome segregation (He(ce)) and under some level of chromatid segregation (He(cd)). Allele frequencies and inbreeding coefficients (FIS) per locus and per population were calculated in Fstat v2.9.3.2 [The microsatellite genetic diversity estimation, the tests for Hardy–Weinberg equilibrium (HWE), and linkage disequilibrium among loci followed Deng et al. . We evalv2.9.3.2 . Furtherv2.9.3.2 .Hd) and nucleotide diversity (π) of mtDNA control region were calculated using DnaSP v.5.10.01 [The number of haplotypes (h), haplotype diversity  for the two markers in Arlequin. Estimates of significance were obtained by 1 × 106 repetition and 1 × 105 burn-in period.The patterns of the population structure were investigated using the model-based Bayesian clustering procedure in STRUCTURE v.2.3.3 . We testhttp://www.fluxus-engineering.com).Moreover, the median-joining haplotype network from mtDNA data was established in Network 4.6.1.1  per locus and from 110 (MLW) to 141 (WLW) per population across all loci (A = 11.75), mean PIC values (PIC = 0.801), and expected heterozygosity under random chromosomal segregation (He(ce) = 0.820) and under random chromatid segregation (He(cd) = 0.765) were observed in WLW. In comparison, the MLW displayed the lowest number of alleles, PIC values, observed heterozygosity, and expected heterozygosity under two assumptions  to 16 (PM17) all loci . Of the umptions .FCd) and 23 under random chromatid segregation (FCe)), suggesting significant deviations from Hardy–Weinberg equilibrium . Significant overall values of FIS were obtained for four populations of P. pingi (P < 0.05), suggesting that inbreeding events may have occurred in the hatchery populations as well as in the two wild populations.After applying a sequential Bonferroni correction, the significant values of fixation indices were observed for almost half out of 48 locus-by-population comparisons  was shared among four populations. Five haplotypes were shared between JPH and WLW, while all other population pairs only shared two haplotypes. All the four populations had their own exclusive haplotypes. MLW and WLW both had the highest number of 9 private haplotypes. In contrast, the two hatchery populations had the lower private haplotype values of 3 in YAH and only 1 in JPH.The overall haplotype diversity and nucleotide diversity was 0.69481 and 0.00507, respectively. MLW was characterized by the highest haplotype diversity (0.69231), yet the lowest nucleotide diversity (0.00212), suggesting that this population experienced a past rapid population expansion from an initial small effective population size [FCT= 0.03543, P > 0.05) and –24.27 for mitochondrial control region  . No significant group variability was detected by AMOVA analyses, with negligible variance Values of –3.54 for microsatellite markers ( > 0.05) .FST values for microsatellite and ΦST values for mitochondrial data were significant for all population pairs (P < 0.05), with the highest FST value between YAH and JPH (0.196) and highest ɸST value (0.653) between MLW and JPH. However, the differentiation between WLW and JPH was the lowest, despite its significant P value . In addition, WLW and YAH showed relatively small genetic differentiation values of 0.161 for FST and 0.095 for ɸST . Seventy samples from four populations clustered with one major haplogroup (1), while 109 individuals mainly from three different populations  grouped with the largest haplogroup (2) .Tajima's D = –1.76785, P = 0.02400) and Fu’s FS test in MLW . Moreover, bottleneck analysis did not detect any deviation from shift test mode in allele frequencies . However, a significant heterozygosity excess (P = 0.0302) was observed in JPH under the TPM model, suggesting recent reductions in effective population size in JPH.The results from BSP analysis showed that there was a population expansion for MLW and a bottleneck for JPH . It was In 2MOD analysis, the probability of given model was estimated from the portions of 0 or 1 in the output file. And all interactions in both runs selected the migration–drift model (100% support).Analysis from the coalescent-based method using the IM model showed that there were significant historical gene flows between the two wild populations. Immigration from MLW to WLW was slightly higher than from the opposite direction (1.8 vs. 1.4) .P. pingi in Yalong River was not rich and the population structure was simple [P. pingi  = 0.726–0.820, He(cd) = 0.678–0.765, A = 9.167–11.75) was much higher than that reported in 13 other freshwater fishes  [Hd values of 0.59712–0.69231 for wild P. pingi compared to that of 0.7118–0.8800 for some other teleostean fishes [Hd values observed in wild P. pingi, the levels of π detected within populations (π = 0.00212–0.00306) are very similar to that reported for other teleostean fishes (π = 0.00143–0.00280). We, therefore, suggest that the two wild populations of P. pingi in the two tributaries of the Yalong River showed a moderate genetic diversity, which was higher than previously reported by Yue et al. [Genetic variation and evolutionary processes is highly important for the sustainability of many species . A previs simple . In the A = 9.1) . Howevern fishes ,54,55,56 π = 0.003–0.00280Additionally, the genetic diversity of a species, combined with ecological and biological data is indispensable for clarifying the purpose and priority of conservation, and for the captive breeding programs . In thisP. pingi, have become restricted to a few tributaries due to hydrological alteration and habitat fragmentation in the main channels [P. pingi in the Woluo River. Results of Bayesian analysis (STRUCTURE) confirmed it by showing that WLW also shares some of genetic component with MLW. In such cases, the Wuoluo River could serve as a refuge for P. pingi from anthropogenic disturbance. Additionally, the highest levels of genetic diversity observed in WLW would coincide with results revealed by some studies that tributaries may harbor a particular portion of the total genetic diversity of a species [In a previous study for fishes inhabiting main streams of the snowfall region in northern Honshu of Japan, tributaries might function as seasonal refuges and even as breeding habitat during the flood period . In our channels . Inward  species . This waP. pingi should be preferentially focused on maintaining the particular portions of genetic diversity in the tributaries with less anthropogenic impacts such as the Woluo River.Based on these findings, management actions for P. pingi captive breeding and hatchery release program. As for the two hatchery populations in our study, considerable genetic variations was observed for YAH, which reinforces result of our investigation that the parental fish of YAH were collected from multiple water systems, such as the Yalong, Qingyi, and Dadu rivers. We, therefore, suggest that abundant geographical sources of parents during its founding, subsequent mutation over generations  [Maintaining a high genetic variation in the hatchery samples is very critical for the success of the alleles) , or an aHd= 0.27317, π = 0.00324). As reported for other fishes [P = 0.0005) appeared to be the main explanations for the reductions of variabilities in JPH. Further massive releasing of hatchery fish with reduced genetic diversity might cause adverse impacts on adapted gene pools, consequently decreasing reproduction, growth, and adaption of wild populations [P. pingi, the use of appropriate sets of breeders for the establishment of founder broodstocks will be critical to maintain the genetic diversity in the hatchery fish.However, reduced intra-population genetic variation of JPH was detected by the mitochondrial control region dataset . Regarding these, high genetic differentiation between YAH and JPH  was detected, further confirmed by their distinct genetic compositions revealed by structure analysis. This situation is probably related to different geographical sources of broodstocks during its founding and subsequent artificial selection of P. pingi.Moderate to high levels of differentiation were found between the hatchery populations and between the hatchery and wild populations (with exception for JPH and WLW). According to Wright , the ranFST= 0.026, ɸST= 0.029). Low genetic divergence, and the results from the NJ dendrogram and Structure analysis indicated closer relationship between JPH and WLW, as confirmed by five mtDNA haplotypes commonly shared between them. It implies that the parental fish of P. pingi in the Fish Reproduction Station of the Jinping-Guandi might have originated from the Woluo River. Similarly, closer genetic relationship between the YAH and MLW was revealed by the NJ dendrogram and Bayesian clustering results  should be carried out to confirm the geographical distributions of original broodstocks of YAH, although such analyses may be constrained by the challenge of sampling in these rivers.While, weak genetic differentiation was found between JPH and WLW  from the geographically closer sampling locations showed evident genetic differences, although there was no apparent physical barrier restricting their connectivity. In addition, studies of wild populations in several fishes have revealed high genetic differences between main river channel populations and tributary populations [In the present study, the wild ulations ,66,67. Tulations . Some auulations  and contulations ,71. Howeulations ,73. TakiP. pingi are threatened by habitat fragmentation due to damming on the Yalong River, which in turn lead to geographic fragmentation of fish populations. Such populations may have experienced different natural selection regimes, and, as a result, are exhibit independent demographic processes and associated differences in their genetic diversity as well as significant genetic structure among these populations. Based on our findings, and until additional studies are performed at finer geographic scales, tributaries of major rivers probably provide the best basis for delineating possible expected increasing inter-populational differences in genetic structure within this species.Given the existence of the noticeable differences in the genetic structure between MLW and WLW, it seems that on-going gene flows between MLW and WLW were likely to have been very limited even within this small geographic distance. The two populations as well as other geographic populations of FIS analysis, which should be considered as an important factor to threat the persistence of wild populations. Consequently, we identified the two patches in the present study as two separate spatial scales that should be maintained to conserve the greatest possible genetic diversity of P. pingi within the basin. This means that conservation efforts should be directed to these two populations and their relevant habitats. Therefore, we suggest the creation of microscale protected areas for P. pingi in the Yalong River including stronger fishery supervision and habitat assessments in these areas. The creation of some protected areas is particularly important for the Woluo River Tributary, which likely functions as an important refuge for this species (and possibly for other lotic species as well). Protecting and maintaining the high genetic diversity observed in the Woluo Tributary may be critical for the future.However, there is always a possibility that if such genetic flow continues, the genetic differentiation between these two wild populations will diminish. In consideration of the significant genetic divergence between MLW and WLW, caution should be taken when establishing conservation strategies for this fish. The Muli River Tributary has clearly suffered more hydrological changes than the Woluo Tributary. With reduced genetic diversity in MLW, the special proportion of genetic diversity maintained in this population might be lost. Moreover, the inbreeding events may occurred both in MLW and WLW as well, as indicated by P. pingi. The Woluo Tributary has suffered less from anthropogenic disturbances than the surrounding areas. It is thus necessary to define Woluo River as a refuge which plays a central role in the persistence of P. pingi populations. In addition, WLW was found have relatively low genetic differentiation with YAH and JPH. The Woluo Tributary within the Yalong River system is a conservation priority for P. pingi. In addition, with regard to the reduced genetic diversity of the Muli River population, we argue the critical importance of enhancementandreleasing measures in the Muli Triburary to increase the effective population size and genetic variation of these local populations as represented by MLW.The presence of genetically differentiated populations indicates potential values for two ESUs and MUs as they represent independent evolutionary trajectories . PronounP. pingi resource in Yalong River.Previous studies elsewhere have demonstrated that small effective broodstock size for the production and releases of hatchery-reared fish is the primary cause of genetic variation reductions along with increased inbreeding ,19. SuchS1 Fig(TIF)Click here for additional data file.S2 FigP < 0.05.Boxes represent sampled and ancestral populations, horizontal lines represent splitting times, curved arrows represent migration and numbers above or below arrows represent migration rates in the direction of the arrow. Time is represented as depth on the vertical axis, with the sampled population names at the top of the figure at the most recent time point. *(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOC)Click here for additional data file.


Dactylis glomerata L. (orchardgrass) is an important perennial forage species in temperate areas of the world. It is usually used for silage, grazing and hay because of its high nutritional value and reproducibility. Central Asia, Xinjiang and Tibetan Plateau in China possess various special micro-environments that harbor many valuable resources, while different degrees of degradation of the grassland ecosystem occurred due to climatic changing and human activities. Investigating the genetic diversity of wild D. glomerat could provide basis for collection, protection, and utilization of some excellent germplasm resources. Totally 210 individuals from 14 populations—five from Xinjiang, two from Kangding (Tibetan Plateau), and seven from Central Asia were identified using AFLP technology. The average values of Nei’s genetic diversity (Hj) and Shannon information index (Ho) were 0.383 and 0.394 respectively. UPGMA tree, STRUCTURE analysis and principal coordinate analysis (PCoA) showed populations from same region clustered together. AMOVA revealed 35.10% of the genetic differentiation (Fst) occurred among populations. Gene flow (Nm) was limited among all populations. Genetic diversity of D. glomerata was high but limited under isolation-by-distance pattern, resulting in high genetic differentiation and low gene flow among populations. Adjacent regions also exhibited similar results because of the barriers of high mountains. The environmental factors, such as precipitation, elevation, latitude and longitude also had some impacts on genetic diversity and structure pattern of populations. Dactylis glomerata L., a perennial cool-season forage grass, belongs to the monotypic genera Dactylis, known as orchardgrass or cocksfoot [Dactylis is 2n = 14 and, although the species consists of diploid, tetraploid and hexaploid, the commonly used forage form is tetraploid [Dactylis is the fourth widely used grass genus following Lolium, Festuca and Phleum in global temperate areas, used as silage, hay or grazing [D. glomerata is a self-incompatible, wind-pollinated, outcrossing species, therefore various levels of ploidy and high phenotypic variation existed among species during the long term natural selection and adaptation processes [Dactylis very likely originated as D. glomerata ssp. altaica in Central Asia [ocksfoot . The bastraploid . With ag grazing . D. glomrocesses ,9. The nral Asia . During ral Asia ,12.D. glomerata is an important and valuable model grass to investigate the genetic diversity due to its agricultural importance, wide distributed limits, and resistance to diverse stress [e stress ,14. Suche stress ,16. Genee stress . The spee stress . So the e stress –21.Dactylis, various environmental conditions in Central Asia possess many valuable alleles or traits of species. These complex micro-environments are derived by mountain orogeny, which has been associated with some diversification and speciation of plants [As one of the original centers of f plants . For insf plants .Dactylis in China. Tibetan Plateau now is a still uplifted geographical region that is encircled by the western Karakorum massif, the northern Kunlun mountains, the southern Himalayas and deeply incised mountain ranges [The south Tibetan Plateau is one of the native distributed areas of n ranges ,25. It in ranges ,27. Whiln ranges . So moreD. glomerata mostly adopted morphological method or bulked DNA strategy, while the investigations on population genetic diversity that using individual DNAs rarely report yet [Traditional evaluation by phenotypic traits takes much time and endeavor to rebuild the homogenous environment for individuals in replicated field experiments . Moleculport yet ,4,8,33. The primary focus of most previous investigations is on contemporary phenotypes and diversity of current populations, but the potential driving force of specific selective evolution in population divergence is often not addressed . GeneralD. glomerata populations from three geographical regions were used to research their genetic diversity and structure patterns, and develop basis for the collection, protection, and utilization of some excellent germplasm resources. Accordingly, the objectives were: (1) to estimate genetic diversity and structure pattern of populations, (2) to study the gene flow (vs. genetic drift) among regions, (3) to evaluate the correlation of genetic diversity and environmental factors.Totally 14 wild D. glomerata were used , and had not been cultivated or actively managed for pasture improvement. Seed was collected from fifty or more randomly sampled individual plants in each population. The sampling sites ranged from the northernmost population DG2 at Heavenly Lake in Xinjiang (44°7′0″N) to the southernmost population DG19 in Kangding (29°59′0″N), and from the easternmost population DG19 in Kangding (101°57′25″E) to the westernmost population DG37 in Kulyab of Tajikistan (69°14′29″E). Some other climate factors  of each sampling site were obtained from DIVA-GIS software [Fourteen wildland site collections of ere used , with 15ere used , for a tsoftware . S1 Tabl® ND-1000 Spectrophotometer  was used for quantifying the DNA concentration.Each individual sample was comprised by 4 ~ 5 fresh leaf tissues (about 70 mg), and genomic DNA was extracted using plant DNA extraction kits . NanoDropMseI (M-GACGATGAGTCCTGAG) and EcoRI (E-CTCGTAGACTGCGTACC) primers used in amplification were selected from a set of 100 primer pairs. The amplification PCR reaction was performed in a final volume of 20 μL as Zhang et al. [® .AFLP reactions were performed following Sun et al.  with a fg et al. . The capEach band of AFLP amplification was treated as a separate locus. The clear bands were recorded as presence (1) and the alternative were absence (0) ranging from 80 and 400 bp to generate the binary matrices for further analyses.Fst) is used and allele frequencies are Dirichlet distributed in the hypothesis of Bayesian methods [10 PO > 1.0) [Fst forcing the simulation values for heterozygosity (He) with 1,000,000 Markov chain simulations. Totally three times were conducted at 95% confidence interval in order to ensure the accuracy of converged inference.In order to identify candidate AFLP loci that potentially influenced by selection, two kinds of approaches were performed: DetSel v1.02 , a free  methods . PreviouO > 1.0) ,44. For O > 1.0) . It calcHo) was calculated using POPGENE v3.0 [Ho were calculated. POPGENE v3.0 [Na) and the effective number of alleles per locus (Ne). And the Nei’s genetic diversity (Hj) was computed using AFLP-SURV v1.0 [Linkage disequilibrium (LD) was calculated for each population using ARLEQUIN v2.0  to detecENE v3.0 , assuminENE v3.0  was usedD. glomerata. We firstly computed Nei’s genetic distance (GD) matrix with 10,000 bootstrap values using AFLP-SURV v1.0 [To analysis the genetic structure, we used the UPGMA (unweighted pair group method with arithmetic mean) clustering procedure for the 14 populations of URV v1.0 . Then thURV v1.0 . The priURV v1.0  and “scaURV v1.0  in R proURV v1.0  to inferURV v1.0  was usedURV v1.0 . The resFst), the partitioning of variation at different scale was computed with Analysis of Molecular Variance (AMOVA) in “vegan” [G’st) was also estimated as G’st = (Hsp − Hpop) / Hsp . The gene flow (Nm) among populations was conducted as Nm = (1 − Fst) / 4 Fst.To study the magnitude of genetic differentiation  [Hj and environmental factors  were estimated using R package “stats” [Mantel test was performed between pairwise ce (IBD)  in “ade4ce (IBD)  in R pro “stats”  with 99%Ho) of each pair of primers ranged from 0.2945 to 0.3097 with an average level of 0.3026.Totally 643 clear bands were generated and 352 of them were polymorphic using 6 AFLP primer pairs  were significantly high deviating from 95% confidence intervals  significantly took higher values of PO >10 in DetSel (See p < 0.05)  relative to population DG32 , and population DG18 presented the lowest level . At the regional level, the genetic diversity was lowest in Kangding  and highest in Central Asia . The total genetic diversity of the species was high .Linkage disequilibrium (LD), or non-random association of alleles was calculated for each population at the 5% level, revealing a low proportion of the polymorphic loci pairs  . For genD. glomerata populations was constructed, which was composed of three clusters  for 210 individuals of e groups . All thei.e., 5 individuals of population DG33 and 4 individuals of population DG32. There were few individuals that non-assigned to any population.The assignment test indicated that 84.29% of the individuals were allocated back to their original populations with each of these individuals being 100 times more likely that they belonged to this population than any of the other populations (See Fst) occurred among populations whereas larger proportion of variation (64.90%) existed within populations (Fct = 0.09) existed between diploid and tetraploid populations of D. glomerata (G’st) revealed that 33.69% of the differentiation existed among populations. Mantel test  revealed a significant isolation-by-distance (IBD) pattern across all sampling sites (Nm = 0.4623) was seriously limited among all populations. According to geographical origins of D. glomerata germplasm , AMOVA analysis, Mantel test, and gene flow were conducted at smaller scale. The IBD pattern, low Nm, high Fst and G’st were also found between regions  showed that 35.10% of the Nei’s genetic differentiation  , especially for the precipitation in June . The population Ho demonstrated a significantly negatively pattern to longitude , and weak correlation to latitude  or annual precipitation , but significantly correlated to precipitation in June . The population Np also significantly correlated to latitude , longitude  and precipitation in June . However, no correlation was found between population LD and environmental factors.Correlation analyses revealed the population  < 0.01) , which sD. glomerata to detect the genetic diversity and to speculate on the relationships among them. An investigation of genetic diversity of wild D. glomerata germplasm by using AFLP technique based on bulked sampling method was conducted by Peng et al. [D. glomerata species by Sun et al.  [D. glomerata populations by using RAPD and bulked genomic DNAs [Hj values in previous studies on D. glomerata in Swiss permanent grassland (Hj = 0.52–0.58) and in three regions in Europe (Hj = 0.44–0.59) [D. glomerata in this study was probably caused by its life traits in long evolutionary histoty, such as outbreeding mating system and efficient pollen dispersal[Population genetic diversity is an important indicator of the capacity for adaptation to varied and changing environment . Analysig et al. , which rmic DNAs . The more Hj = 0.4–0.59 [444–0.59) . The readispersal.Nm values are less than one [Fst = 0.3510 and total G’st = 0.3369 revealed genetic variance mostly occurred within populations and it was correlated to breeding system of cross-pollination. This pattern of genetic structure was also found by previous studies on D. glomerata [Lolium multiflorum [Fst and geographical distance , indicating a significant pattern of isolation-by-distance (IBD) across all sampling sites  [r = 0.64, p = 0.01) [r = 0.39, p < 0.01) [Nm (0.4623) was very low across all sampling sites. Conversely, individuals of neighboring populations would obtain more opportunities of allelic exchange, so they tend to be genetically similar to one another.Gene flow could counteract intraspecific genetic drift and interspecific differentiation, while genetic drift would aggravate interspecific differentiation and decrease species genetic diversity when than one ,65. Typithan one ,66. In tlomerata ,62, evenlomerata  and Lolitiflorum . Mantel ng sites . Similar < 0.01) . Given tr = 0.8223, p < 0.01; KD-CA: r = 0.8385, p < 0.01) , and high genetic differentiation  was revealed. Hence, populations of Kangding independently clustered together in cluster analysis. The low gene flow and high differentiation were also detected between Xinjiang and Central Asia , although no significant IBD occurred between them (r = 0.4426). This structure pattern of D. glomerata was demonstrated more directly in PCoA that individuals tended to gather in the same group when they had close proximity in geographical distance. This pattern most likely reflects the historical evolutional traits of D. glomerata. The barrier effects of long geographical distance or high Tianshan Mountains have caused the unidirectional variation of individuals in neutral evolution but led to the directional variation and convergent genotypes of population structure, e.g. genetic drift allowed for populations to evolve traits in their local habitats by fixing or losing of alleles [Considering the very long geographical distance between Kangding and Xinjiang or Central Asia (more than 1886 km), the expectantly significant IBD patterns were found by Mantel Tests (KD-XJ:  < 0.01) . As a re alleles .D. glomerata also suggested natural selection has participated in population divergence or speciation. For example, outlier levels of genetic differentiation revealed high Fst = 0.4013 and low Nm = 0.3730 across all populations; many populations including DG14, DG16, DG32, D33 and DG37 demonstrated more complex genetic lineage in STRUCTURE analysis , revealing low population genetic diversity in high altitudes. Generally, wind-pollination is an important guarantee for D. Glomerata to cross fertilize, while this process is easily affected by environmental conditions [Hj, Ho, Np or LD in this study  may block pollen transmission in some sites. It also partly lead to the decrease in population size and erosion of genetic diversity . In present study, population Ho and Np were correlated to latitude or longitude, the similar pattern was also reported on Stipa grandis [Blysmus sinocompressus [i.e. ambient temperature, sunlight intensity and duration, wind) in different collection sites, the growth status, evolutionary direction and distributed limit of plant might sharply change and affect the genetic diversity of species.Pearson analyses revealed  in June . Typical grandis  and Blysmpressus . BecauseD. glomerata populations revealed high genetic diversity and high genetic differentiation among populations and regions. The isolation-by-distance pattern was significantly across entire distribution range. As expected, genetic differentiation was high and gene flow was limited not only among all populations but also between adjacent regions. The genetic diversity and structure of D. glomerata were affected by geographical distance and mountainous isolation. The geographical distribution and genetic relationship of populations were consistent that most likely derived by divergent selection during the long-term neutral and natural evolution. The genetic diversity was also influenced by environment like altitude, precipitation, latitude and longitude.In conclusion, the investigation of 14 wild S1 FigFst (genetic differentiation) is plotted against the log10 of the PO (posterior odds). The vertical line shows the critical PO used for identifying outlier markers. The 32 markers on the right side of the vertical line are candidates for being under positive selection.(TIFF)Click here for additional data file.S2 FigEach dot represent an AFLP locus. The dots in red board are classified as outliers potentially under divergent selection, and the alternative are netural loci.(TIFF)Click here for additional data file.S3 FigAnalysis included 210 individuals of 14 populations and was based on 352 polymorphic AFLP bands. Blue bars represented individuals assigned to their original population; red bars represented individuals assigned to a population different from the original population; brown bars represented individuals not confidently assigned to any of the 14 populations.(TIFF)Click here for additional data file.S4 Fig(TIFF)Click here for additional data file.S1 TableCodes: AMT, annual mean temperature; AP, annual precipitation.(DOCX)Click here for additional data file.S2 TableHo, Shannon information index.Codes: TNB, total number of band; NPB, number of polymorphic bands; PPB, percentage of polymorphic bands; PIC, polymorphic information content; (DOCX)Click here for additional data file.S1 Text(TXT)Click here for additional data file.