Oncorhynchus keta) is an ecologically and economically important species widely distributed across the North Pacific Ocean. However, the population size of this fishery resource has declined globally. Identifying genetic integrity, diversity and structure, and phylogenetic relationships of wild populations of O. keta over an entire species' range is central for developing its effective conservation and management plans. Nevertheless, chum salmon from the Korean Peninsula, which are comprised of its southwestern range margins, have been overlooked. By using mtDNA control region and 10 microsatellite loci, we here assessed the genetic diversity and structure for 16 populations, including 10 wild and six hatchery populations, encompassing the species entire geographic range in South Korea. The analyses showed that genetic diversity is significantly higher for wild than for hatchery populations. Both marker sets revealed significant genetic differentiation between some local populations. Comparisons of six wild and their respective hatchery populations indicated that allele/haplotype frequencies considerably differ, perhaps due to a strong founder effect and/or homogenizing of hatchery populations for stocking practice. Despite its single admixed gene pool for the Korean chum salmon, some local populations housing their own unique lineages should be accorded with a high priority to safeguard their genetic integrities. The results of our comparative analyses of the Korean population with other North Pacific chum salmons  revealed a lower diversity but higher contribution to the overall species‐level genetic diversity, and also its unique genetic integrity. These findings advocate for the evolutionary significance of the Korean population for species‐level conservation.Chum salmon ( The natal philopatry sometimes leads to decreasing within‐population genetic diversity, primarily due to limited gene flow occurring among geographically disconnected populations, which may ultimately accelerate the risk of local extinction  of wild populations  resources. Goals of captive‐releasing programs include enhancing depressed wild populations in numbers, establishing new populations in nonindigenous habitats if necessary, and supplementing the number of individuals for the avoidance of local extinction  in the Korean Peninsula, comprising the southernmost limit of its geographical distribution, migrate over long distances through Russia and Alaska to the Oregon of North America  has regularly monitored and managed the annual commercial catches and hatchery releases during the last few decades. Only less than 1% of the annual catch of salmon was recorded from Korea NPAFC, , 2019. Cca Salo, . The Korca Salo, . For theca Salo, . Only a O. keta spanning nearly an entire geographical range from South Korea along the East Sea coastlines, including 10 wild and six hatchery‐reared populations. The goals of this study are (1) to analyze and compare the level of genetic diversity between wild and hatchery populations; (2) to estimate the level of genetic differentiation and structure among/within Korean wild and hatchery populations; (3) to identify the level of genetic admixture in wild populations introduced from hatchery stocks; (4) to infer the phylogenetic relationships among the entire North Pacific populations of O. keta, with a focus on the Korean clades. By analyzing and contrasting the levels of genetic diversity and divergence of the Korean population to those of other regional populations, we further discuss on the importance of Korean chum salmon population for an entire species‐level conservation. Our findings inform on conservation implications for salmon fishery resource in order to establish future effective management plans, for example, not only designing appropriate captive‐release programs in Korea, but also a whole species‐level global plan for its conservation.In this study, we investigated the local‐scale genetic diversity and population structure of chum salmon, 22.1O. keta  were collected from 10 wild populations and six hatcheries from South Korea between February 2017 and March 2019 (Tables N = 364) were obtained from returning adults during a spawning period of October to November in 2017–2018 years, and also collected in the following winter or early spring (February to March) as fry and/or juveniles  using skimming nets (Table N = 38), Buk Stream , Yangyang Namdae Stream , Yeongok Stream , Gangneung Namdae Stream , Maeup Stream , Wangpi Stream , Janggi Stream , Taehwa River , and Seomjin River  (Table N = 173) were obtained from three hatchery facilities: Korea Fisheries Resources Agency (FIRA), Gyeongsangbuk‐do Freshwater Fish Research Center (GFFRC), and Samcheok Aquatic Fisheries Resource Center (SAFRC). The FIRA, which is a major hatchery center located at the Yangyang Namdae Stream (YN), runs hatchery‐rearing and wild‐releasing practice for salmons that return to several natal streams, including the Baebong Stream , Buk Stream , Yeongok Stream , and Gangneung Namdae Stream , SAFRC the Maeup Stream , and GFFRC the Wangpi Stream , 1× PCR buffer, and approximately 10–40 ng of template DNA for a final volume of 15 μl. The amplified PCR products were purified enzymatically with Exonuclease I and Shrimp Alkaline Phosphatase (New England BioLabs). The purified mtDNA CR fragments were sequenced in a single forward direction using an ABI 3730xl Genetic Analyzer (Applied Biosystems) at the Humanizing Genomics Macrogen in Korea. The obtained DNA sequences were edited using GENEIOUS v11.1.5  was amplified by polymerase chain reaction (PCR) using tRNAthr‐2 and tRNAphe‐2 primers  were added to PCR reactions for the markers Omy1011, One102, and One114. The thermocycler conditions were consisted of 94°C for 10 min, 35 cycles at 94°C for 30–40 s, 50–65°C for 30–40 s, and 72°C for 30–40 s and a final extension step at 72°C for 5–20 min. Following PCR reactions, samples were electrophoresed on an ABI 3730xl automated DNA sequencer (Applied Biosystems). Fragment sizes were determined with the ROX 500 bp size standard (ABI) using GENEMAPPER software v5.0 (Applied Biosystems) at the Humanizing Genomics Macrogen. A single person (JEJ) carried out allele scoring for 10 loci and checked for an error with Microsatellite Toolkit in MS Excel , haplotype diversity (H), and nucleotide diversity (π) were estimated for each population and the entire pooled Korean O. keta population using ARLEQUIN v3.5 , allelic richness (AR) corrected for unequal sample sizes, number of private alleles (PA), observed (HO) and expected (HE) heterozygosity, inbreeding coefficient (FIS), and Hardy–Weinberg equilibrium (HWE) statistics were calculated using GENEPOP v4.0  and hatchery (N = 6) populations, HR, AR, HE, and HO values were statistically analyzed by each separate independent t‐test. Contemporary effective population sizes (Ne) were also calculated for each of the samples based on linkage disequilibrium (LD) method implemented in NeESTIMATOR v2.01  of 0.05 was used for the Ne estimations, and 95% confidence intervals (95% CI) were derived from jackknifing across all loci. Difference in Ne estimates between wild (N = 8) and hatchery (N = 6) populations excluding the MAw and TAw populations with infinite of Ne estimates (Table U test.To examine whether there were significant differences in the level of genetic diversity between wild (2.4.2FST with haplotype (mtDNA) and allele (microsatellites) frequencies using ARLEQUIN and GENEPOP. For the three wild populations , we performed temporal analyses of FST statistics over 3 years by pooling returning adults in the fall (October to November) and fry and/or juveniles in the following winter or spring  in the data set, we ran 10 independent runs at each K = 1–10 (considering only 10 wild populations) with a burn‐in length of 105 followed by 106 replicates of Markov Chain Monte Carlo (MCMC). The distribution of the delta K based on the rate of change in the log probability of data Ln K between successive K‐values  was performed to assess genetic relationships among populations with multilocus microsatellite genotypes using GenAlEx v6.502 , among populations within groups (FSC), and within populations (FST) for the mtDNA and microsatellites separately with 10,000 permutations.To test if the genetic structure exists between wild and hatchery samples, we analyzed the whole data set by including wild and hatchery populations together using the same STRUCTURE settings as above by assuming In addition, to test if temporal variation exists in the genetic structure among the sampling years, temporal AMOVAs were analyzed at both mtDNA and microsatellites by grouping all wild populations according to the sampling years  among wild populations based on FST values using the Mantel test in GENALEX v6.502. The geographic surface distance in kilometers between two sampling sites was acquired from the website (http://www.movable‐type.co.uk/scripts/latlong.html).Spatial patterns of genetic discontinuity were visualized using BARRIER v2.2 , Japan (N = 16), Russia (N = 10), North America (N = 21)]  from this study, Korean , Japanese (N = 731), Russian (N = 406), and North American populations (N = 979) analyzed in Sato et al.  and contribution to total diversity  and total haplotype richness . According to Petit et al. (CT) which is broken down into the genetic variation contribution (CS) and the genetic distinctiveness contribution (CD) of the population. Similarly, the total haplotype richness contributed by each population to the while (CTr) is broken down into the haplotype variation contribution (CSr) and the haplotype distinctiveness contribution (CDr). Pairwise population differentiation among the four North Pacific populations was estimated using FST statistics computed from ARLEQUIN. We also compared the microsatellite diversity across the same marker‐set of eight out of 10 microsatellites  analyzed in common between previous .To determine the level of genetic diversity and genetic integrity of Korean populations, we analyzed and compared the genetic diversity and differentiation among the entire North Pacific Ocean populations. These analyses excluded hatchery samples and included only wild populations returning to their natal rivers. A total of 2511 fishes were analyzed for the mtDNA CR, including Korean populations  and in YNw (0.644), and the lowest in WAh (0.163). HR values ranged from 1.791 (GNw) to 2.575 (YNw) for wild populations and from 1.000 (BBh) to 2.000 (BKh) for hatchery samples.Only six mtDNA CR haplotypes (599 bp) were found in 516 chum salmon individuals  to 17.4 (YNw), AR from 7.8 (BBh) to 11.8 (SEw), and PA from 1.0 (SEw) to 10.0 (BKh)  to infinity (∞)  except BKw at microsatellites. While only 19 of 120 pairwise population comparisons were significant for mtDNA CR (mean FST = 0.042), 79 pairwise FST estimates were significant among the 120 comparisons for microsatellites  and between BBh and YEh (FST = 0.070) for mtDNA and microsatellites, respectively. Based on mtDNA, all of the 19 significant pairwise FST statistics were involved with two particular hatchery samples (BBh and GNh), indicating that the remaining 14 populations are genetically homogeneous except for these two populations. By comparison, significant microsatellite FST values between wild populations always included MAw and JAw. No significant FST comparisons between populations included YNw, Yew, and SEw. Unexpectedly, two and six pairs of FST statistics between wild and hatchery populations within the same river basins revealed a significant divergence at mtDNA and microsatellites, respectively  and ΔK value that was K = 3. A ratio of three genotypes across all the populations was nearly equally distributed among clusters  and geographical distances based on mtDNA, albeit not statistically significant , but rather highly significant genetic structure among populations within groups  were grouped into three main matrilineal lineages  followed by Korea (0.399) located at the south‐western geographical limits (Table CT (0.045), which was mostly due to the strong divergence  of the Korea population from the other regional ones  differentiation was the largest for North America ( Korea 0.99 locate Korea 0.99 locatep < 0.001), although unequal sample sizes could not be corrected among the four regional populations . To our best knowledge, this study is the first to explore the “local‐scale” genetic structure of the salmon populations spanning almost its entire geographical range in South Korea from the Seomjin River  and hatchery (N = 6) populations of the Korean chum salmon, comprising its geographically peripheral populations at the southwestern distributional edges. Based on the results of the comparative analysis of levels of genetic diversity and divergence with other regional populations distributed across its entire geographical range, we show that Korean O. keta populations house the unique genetic integrity representing their own evolutionary history or trajectory, with a relatively lower genetic diversity but greater contribution to overall species‐level diversity  in mtDNA CR relative to entire North Pacific populations (H = 0.63). We now find that the level of HR in Korean populations was 5.00, which is the lowest mtDNA diversity among the regions  based on mtDNA CR. These findings highlight its own “genetic integrity” of the Korean population with reference to other regional ones. In the case of long‐range migrating organisms like chum salmon, local‐scale genetic diversity and population structure are often neglected for understanding their genetic status. However, our findings underline there is a need to pay more attention to the Korean salmon population, which has continually decreased in the population size and returning adults  are expected to be more susceptible to genetic drift effects causing the loss of unique and rare haplotypes/alleles unless gene flow is overwhelming. Our estimated mean value of median Ne for eight wild populations (without considering two populations from MAw and TAw having infinity [∞]) is approximately 373, which may provide evidence supporting the hypothesis of low genetic diversity with a small Ne for the Korean salmon population (Table The lowest mtDNA diversity (HR = 5.00) with a relatively larger contribution of Korean populations to the species‐level genetic diversity advocates safeguarding their diversity and gene pool with a high priority  tend to be greater for wild than for hatchery samples, although only AR was statistically significant. Several countries including South Korea exploited the artificial propagation of wild salmonid adults by captive breeding and rearing juveniles in hatchery environments, and then releasing back to their natal rivers, for the purpose of the conservation and management programs Seong, . StockinWe find weak, but detectable local‐scale genetic differentiation among the Korean chum salmon wild populations at a 13 to 400‐km geographic scale. Cautiously, there is detectable genetic divergence between some wild and the respective hatchery populations. The observed significant differentiation between the wild and hatchery stocks might result from the reduced genetic diversity in hatchery samples due to a founder effect  from South Carolina along the Atlantic Coast of the United States, the level of genetic differentiation among populations has gradually decreased from FST = 0.319 to 0.028 with increasing time intervals over 5 years by hatchery releasing program  introgressive hybridization and/or bottleneck with hatchery‐reared conspecifics  and Eastern (North America) of the North Pacific  were not significant except for a few stream pairs  was considered for the Korean population  will help to preserve locally adapted gene pool. For this, it would be more appropriate to use juvenile individuals born from their home streams for releasing practice on the respective wild populations. To increase or restore the level of genetic diversity for some Korean populations, breeding individuals from particular streams with high  and low (BBh) genetic diversity would be plausible. Most importantly, a continuous genetic monitoring is crucial for understanding how well these valuable populations will maintain under ongoing climate changes.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Figure S1Click here for additional data file.Figure S2Click here for additional data file.Figure S3Click here for additional data file.Table S1Click here for additional data file.Table S2Click here for additional data file.Table S3Click here for additional data file.Table S4Click here for additional data file.Table S5Click here for additional data file.


Holothuria (Metriatyla) scabra, known as sandfish, is a high-value tropical echinoderm central to the global bêche-de-mer (BDM) trade. This species has been heavily exploited across its natural range, with overharvesting and ineffective fishery management leaving stocks in the Pacific region heavily depleted. In Fiji, sandfish stocks have not recovered since a 1988 harvest ban, with surveys reporting declining populations and recruitment failure. Therefore, to inform fishery management policy for the wild sandfish resource and to guide hatchery-based restocking efforts, a high-resolution genomic audit of Fijian populations was carried out. A total of 6,896 selectively-neutral and 186 putatively-adaptive genome-wide SNPs (DArTseq) together with an independent oceanographic particle dispersal model were used to investigate genetic structure, diversity, signatures of selection, relatedness and connectivity in six wild populations. Three genetically distinct populations were identified with shallow but significant differentiation , comprising (1) Lakeba island (Lau archipelago), (2) Macuata (Vanua Levu), and (3) individuals from Yasawa, Ra, Serua island and Kadavu comprising the final unit. Small reductions in allelic diversity were observed in marginal populations in eastern Fiji . Signatures of putative local adaptation were also discovered in individuals from Lakeba island, suggesting that they be managed as a discrete unit. An isolation-by-distance model of genetic structure for Fijian sandfish is apparent, with population fragmentation occurring towards the east. Hatchery-based production of juveniles is promising for stock replenishment, however great care is required during broodstock source population selection and juvenile releases into source areas only. The successful use of genomic data here has the potential to be applied to other sea cucumber species in Fiji, and other regions involved in the global BDM trade. While preliminary insights into the genetic structure and connectivity of sandfish in Fiji have been obtained, further local, regional and distribution-wide investigations are required to better inform conservation efforts, wild stock management and hatchery-based restocking interventions for this valuable invertebrate.The sea cucumber  Holothuria (Metriatyla) scabra is a high-value tropical sea cucumber central to the global bêche-de-mer (BDM) trade [The sandfish, M) trade , 2. NatiM) trade . UnsurprM) trade . Today, M) trade , requireH. scabra population densities suggest that stock recovery has not occurred since the 1988 ban on harvests, with primarily sexually immature juveniles constituting populations at eight locations assessed [Fiji, which until recently had remained one of two Pacific Island countries maintaining an open and lightly-regulated sea cucumber fishery , 5, implIt is evident that Fiji’s sea cucumber fishery requires additional regulatory measures to arrest declining wild stocks, with strict implementation and enforcement of quotas and collection size limits , 10. TheH. scabra or other heavily depleted taxa, by identifying potential bottlenecks in the hatchery process where valuable genetic diversity is lost, ensuring that genetically diverse individuals are restocked in overfished areas [The integration of genetic data into sea cucumber stock assessments provides unique insights into stock health, including the amount of genetic diversity present in populations, the level of replenishment through gene flow from neighbouring stocks, as well as the presence of any local adaptation –17. Geneed areas –20.Consequently, a high-resolution genomic audit of wild Fijian sandfish was completed, using a robust genotyping-by-sequencing approach (DArTseq) which had been previously evaluated for use in this species . InsightHolothuria scabra were sampled from natural populations at six locations throughout Fiji  salt solution , and mai™) reduced-representation libraries were prepared as described by Kilian et al. [PstI and SphI methylation-sensitive restriction enzyme combination. Custom proprietary barcoded adapters (6–9 bp) were ligated to RE cut-site overhangs as described by Mercier et al. [Diversity Arrays Technology (DArT PL) proprietary genotyping by sequencing  clusters and designated scores of: "0" = reference allele homozygote, "1" = SNP allele homozygote and "2" = heterozygote, based on their frequency of occurrence. To ensure robust variant calling, all monomorphic clusters were removed, SNP loci had to be present in both allelic states (homozygous and heterozygous), and a genetic similarity matrix was produced using the first 10,000 SNPs called to assess technical replication error , and remOnce SNP markers were identified, they were assessed for homozygote and heterozygote call rate, frequency, polymorphic information content (PIC), average SNP count, read depth and repeatability using DArT PL’s KD Compute package. Upon receiving the raw genotype dataset from DArT PL, it was further filtered, using a nested criteria of call rate and average polymorphic information content , to retain only a single, highly informative SNP at each genomic locus for population genomic analyses. The dataset was further filtered for global call rate (95%), read depth (>8), average PIC (1%) MAF (2% per population) and average repeatability (95%). All loci were assessed for departure from Hardy-Weinberg Equilibrium (HWE) using Arlequin v.3.5.1.3 , using aFst values. Putative FST outlier loci identified during both runs were removed and segregated into a separate outlier marker dataset, and all remaining SNPs tested for departure from Hardy-Weinberg Equilibrium (HWE) in Arlequin v.3.5.1.3 [Identification of loci under potential selection was achieved using two software packages, BayeScan v.2.1 , 32 and .3.5.1.3 , using aHo) and average expected heterozygosities corrected for population sample size (Hn.b.), were computed using Genetix v.4.05.2 [Fis) per sample group and mean numbers of alleles per locus . The number of private alleles  was computed with HP-RARE v.1.0 using the rarefaction method [R package PopGenKit [NeLD) was estimated for each population, using NeEstimator v.2.01 [For assessment of genomic diversity within and between sample groups on selectively neutral markers, allelic diversity indices including the average observed  in Genetix v.4.05.2 [R package adegenet 1.4.2 [adegenet determined the optimal number of actual clusters using a Bayesian Information Criterion (BIC) method.Pairwise utations , togethev.4.05.2 . A Discret 1.4.2 –40. The For estimation of proportional ancestral contributions and population stratification among sample groups , the ADMIXTURE package was used , 42. ADMTo investigate fine-scale stratification at selectively neutral loci, network analyses were also carried out using the Netview R package , 46. Nethttps://github.com/CyprienBosserelle/DisperGPU), was used to examine potential larval transport pathways between source (sandfish sampling locations) and sink areas. The approach described by Lal et al. [H. scabra. Briefly, the analysis utilised two models: the DisperGPU particle model which simulated dispersal, and the HYbrid Coordinate Ocean Model (HYCOM) which provided hindcast current velocity data and hydrodynamic forcing to drive the former. Larvae were simulated as particles seeded into defined polygons seagrass bed area extents for each sampling location extracted from Allen Coral Atlas data . During simulations, particle positions were tracked over a fixed period of time to emulate the Pelagic Larval Duration (PLD) of H. scabra.The particle dispersal modelling software DisperGPU  of 1/12th of a degree and is output every day [DisperGPU utilises a standard Lagrangian formulation, taking into account particle position (latitude and longitude), displacement during model time steps (set as one day), eddy diffusivity and the surface current speed at the location of the particle , 51. Thevery day , 53. Furvery day , 54. To https://allencoralatlas.org) benthic cover dataset layer file, and separated from other benthic class layer objects  using QGIS v 3.14.16-Pi. To generate a seed file as input for DisperGPU, a seagrass habitat point layer was acquired by first extracting vertices from the seagrass polygon layer file described earlier and adding coordinate points as a geometry attribute in QGIS. This resulted in 3,159,114 feature points being captured. For each sampling site, a polygon was extracted to account for seagrass bed area extent where specimens were collected and imported to DisperGPU as discrete seed files.The occurrence and extent of seagrass beds in Fiji were obtained from an Allen Coral Atlas . The El Niño Southern Oscillation (ENSO) system is known to influence surface ocean current dynamics in Fiji [Particles were seeded everyday for the first 3 days; no particle mortality or competency was simulated and a uniform distribution of adult sandfish within seagrass beds was assumed. A fixed number of 256,000 particles uniformly distributed across all seed area polygons was seeded each day over 3 days, making a total of 4,608,000 particles released during simulations for each respective spawning season. This quantity of particles was selected based on constraints on available computational power, and DisperGPU input requirements , and Bayescan 2.1 outliers at an FDR = 0.01 (n = 29), resulting in the retention of 6,896 selectively neutral genome-wide SNPs. A separate dataset of 186 putatively adaptive SNPs was retained for investigation of selective signatures in genetic structure. No loci were found to deviate from HWE across the six populations, and subsequently no loci were removed from the dataset. A total of 6,896 SNPs remained in the final filtered selectively-neutral dataset, and were used for performing population genomic analyses.The raw dataset contained a total of 49,051 SNPs genotyped across 211 individuals. The removal of duplicate (clone) SNPs, resulted in 36,574 SNPs remaining (25.4% reduction), while further filtering for call rate (95%), read depth (>8), average PIC (1%) MAF (2% per population) and average repeatability (95%), left 7,082 SNPs remaining in the dataset. Screening for NeLD) varied by geographic location , Nacula island, Yasawa  and Macuata . The smallest NeLD were observed in sandfish sampled from the more isolated islands of Lakeba, Lau  and Kadavu .Effective population sizes (A) were comparable among all populations (A = 1.956 ± 0.0114 SE), varying from A = 1.912 at Lakeba island to A = 1.968 at Nacula island, Yasawa. Lakeba island was also the only population containing private alleles . The effective number of alleles were similar among all sample groups (Neff range of 1.452–1.461), with the exception of Lakeba island where Neff = 1.435. Similar trends were evident in the numbers of locally common alleles and the percentage of polymorphic loci, suggesting a small reduction in diversity at Lakeba island and Macuata.Mean numbers of alleles per locus . Serua island individuals, however, exhibited an over two-fold difference, with a value of 0.163. Trends in multi-locus heterozygosity (MLH) were similar, with the lowest value of 0.226±0.072 obtained for Serua island. Considered together, these data highlight a small but measurable heterozygote deficit in Serua island sandfish, with small reductions in allelic diversity among Lakeba Island and Macuata populations.Patterns in observed and expected heterozygosities did not differ markedly for all sample groups, with the exception of Serua island, where .284 see . Serua iFst estimates were shallow but significant for most comparisons , followed by individuals sampled from Macuata, Vanua Levu (Fst range of 0.014–0.019). Similar patterns were reflected in standard genetic distance estimates, with Lakeba island sandfish being the most divergent group . Results of the Mantel test revealed no significant relationship between genetic and geographic distances among populations , and partitioning of genetic variance by AMOVA reported that variation within (78%) and among (19%) individuals accounted for most of the variability in the dataset, with the smallest proportion (3%) originating between populations.Pairwise parisons  with theFst and genetic distance estimates, resolving two primary clusters of individuals  which influences surface water movement in Fiji. For the El Niño year simulation, dispersal was strongly directional, with admixture only evident during eddy effects in south-western Viti Levu over deeper water towards the end of the simulation  in the east, Macuata in the north, and the remaining individuals from Yasawa, Ra, Serua island and Kadavu constituting the final group. These data suggest an isolation-by-distance model of dispersal operating in Fiji with population fragmentation occurring towards the east, although both an AMOVA and Mantel test were not able to detect a significant IBD pattern. Similar partitioning of genetic variance to within individuals rather than populations was detected by Nowland et al.  for nortNPs Figs  and 3. RHolothuria atra), a congener of sandfish which is found in similar habitats. These authors reported net gene flow from east to west, with high differentiation between an island (Taveuni) and mainland (Vanua Levu) populations of H. atra. Hydrodynamic particle dispersal modelling implemented in this study to verify patterns of genetic structure and connectivity also support these conclusions, with highly directional westward transport pathways, mediated by the South Equatorial Current over both El Niño and La Niña event year simulations  in the Lau archipelago reporting that the fishery there is in severe decline to collapse, with population densities generally below the suggested within-species limit of 10–15 individuals ha-1 required to avoid depensation [Among the other Fijian populations sampled, no signatures of genetic bottlenecks were detected, perhaps due to the overriding effects of gene flow . This obensation . These lH. scabra) are exploited in the commercial bêche-de-mer trade [H. scabra are depleted, fishing effort has shifted towards low and medium-value species such as H. atra [The wild sea cucumber resource in Fiji has been assessed using traditional fishery census-based methods in several studies , 76, 77,er trade . The mos H. atra .H. scabra, it is evident that current fishery management measures have been ineffective at maintaining healthy populations. Lalavanua et al. [H. scabra (documented as Metriatyla scabra) in 1988, including the export ban of any bêche-de-mer under the size of 3 inches [H. scabra ban, as well as unregulated harvest using highly extractive fishing techniques  can be attributed to stock declines [For a et al.  report ta et al.  is sugge3 inches . In 20183 inches , 77. Thedeclines , 76. Unfdeclines .H. scabra here can be replicated for other sea cucumber species, to gain insights into the status of the multi-species Fijian sea cucumber fishery as a whole.Despite the status of the wild sandfish resource in Fiji, data generated by the current study can be used by the Fijian government to formulate national fisheries management plans specifically for this species to permit conservation and recovery of depleted populations. We recommend that special attention be paid to peripheral populations in Lakeba island and Macuata, with dedicated harvesting management or harvesting bans, and monitoring efforts to ensure recovery. It is evident that translocation of individuals (for aquaculture or restocking efforts) from Lakeba island to elsewhere in Fiji not be permitted, given signatures of putative local adaptation. Highly regulated exploitation of the sandfish resource in other areas of Fiji surveyed may be permitted on the basis of genetic data reported here, however a holistic assessment at each site including census population surveys is critical , 9, 76 bArtificial propagation of juvenile sandfish in hatchery systems offers great promise for potential restoration and recovery of depleted and/or extirpated populations , howeverHatchery production of sandfish juveniles is established in Fiji, through early efforts by Hair et al.  and HairIn other broadcast spawning taxa, losses of genetic diversity have been observed during routine hatchery operations, because of a range of factors including possible ontogenetic changes as a result of interaction with artificial surfaces  , differeWhile care must be taken with broodstock selection, spawning management and larval settlement during sandfish hatchery production, considering the particular life history characteristics of this species such as specific settlement/recruitment requirements, an assessment of diversity loss during routine hatchery operations is warranted. Such a study may permit modification of hatchery techniques to minimise differential family survival and even-out broodstock contributions, to ensure production of genetically diverse and unrelated juveniles for replenishment of depleted wild populations.H. scabra using high resolution genomic data for the first time. It presents directions for the development of fishery management policy for management of both the wild sandfish resource and informs restocking efforts to replenish depleted populations. The successful use of the DArTseq platform in this study has the potential to be applied to other sea cucumber species in Fiji, and in other regions involved in the global bêche-de-mer trade. While this study has offered preliminary insights into the genetic structure and connectivity of sandfish in Fiji, further local, regional and distribution-wide investigations are required to better understand how populations are organised.This study reports on the genetic diversity, connectivity and structure of Fijian S1 Fig(GIF)Click here for additional data file.S2 Fig(GIF)Click here for additional data file.S1 FileHolothuria scabra at 6,896 selectively neutral genome-wide SNPs are included in a standard STRUCTURE format.Genotypes of 211 individuals of (XLSX)Click here for additional data file.S2 FileHolothuria scabra at 186 putatively adaptive genome-wide SNPs are included in a standard STRUCTURE format.Genotypes of 211 individuals of (XLSX)Click here for additional data file.


Fritillaria imperialis L.) is a threatened bulbous plant which has great ornamental and medicinal values and importance. In the present study, a total of 100 specimens of wild-growing F. imperialis from 10 natural areas of Markazi province, Iran, representing one of the main centers of genetic diversity of this species, were evaluated using 37 phenotypic attributes during April 2021.Crown imperial (High level of genetic variation within populations (75%) and low levels of genetic variation among populations (25%) was revealed. The highest coefficient of variation (CV) was found in leaf trichome (82.00%) and then margin of crown leaves (80.44%). In addition, flower color (CV = 50.86%), flower number (CV = 44.61%), peduncle diameter (CV = 33.44%), and plant length (CV = 32.55%)—all important from an ornamental point of view- showed relatively high CV values. The CV was the lowest for flower shape, filament color, bulb shape, bulblet number, and floral scent. Ward cluster analysis identified two main clusters, containing 14 and 86 specimens, respectively. The first group consisted mainly of specimens from the adjacent Shahbaz and Rasvand populations. According to the principal component analysis (PCA), the first six components of data accounted for 88.36% of total variance. The Shahbaz-1, Shahbaz-2, Shahbaz-6, Shahbaz-7, Shahbaz-9, and Bolagh-8 specimens showed the highest variation and were separated from others, which they can be used further in breeding programs, while Sarchal-2, Bolagh-3, and Chepeqli-4 specimens showed the lowest variability. Moreover, the studied populations were clustered into four distinct groups, each including populations that were geographically close to one another.F. imperialis are still at risk suffering from overcollection in the most of studied areas, especially in Deh-Sad and Tureh.Although the examined specimens revealed high genetic diversity herein, the results indicated that wild-growing populations of  Prunus cerasus L. [Juglans regia L. [Rosa x damascena Mill. [Punica granatum L. [Tulipa spp. [Genetic diversity refers to the aggregate of genetic variation within and between individuals and populations, and it is one of the main factors of concern in biodiversity conservation and plant breeding programs , 2. Thusrasus L. , Juglansregia L. , Rosa x na Mill. , 9, Puniipa spp. .Fritillaria (Lilliaceae) is one of the most important genera of geophytes comprising about 140 perennial herbaceous species, which are mainly distributed in the temperate regions of the northern hemisphere [Fritillaria species have been reported in Iran, most of which are endemic to the country [Fritillaria. The species of Fritillaria have great medicinal and ornamental value and importance. From medicinal point of view, members of this genus are a botanical source of diverse medicinally active components, which have been commonly used in traditional Chinese, Turkish, Japanese, Pakistani, and South East Asian medicine for thousands of years [Fritillaria species [Fritillaria members are also widely appreciated as ornamental plants and floriculture is an important industry with estimated worldwide production value over €60 billion [Fritillaria have a high potential for use as ornamental plants. Consequently, many new ornamental plants can be developed via artificial selection and hybridization breeding techniques.misphere . In Flor country , 13. Accof years . To date species . Fritill billion . Due to Fritillaria imperialis L.  is a perennial bulbous plant with high ornamental and medicinal importance [F. imperialis is a very attractive and valuable horticultural species [F. imperialis has a native distribution range from East-Central and South-Ease Turkey to West Himalayas [F. imperialis is Iran within this range; its genetic assessment is required for effective conservation of this species. However, there are very few reports on the genetic diversity of these germplasm resources in Iran. Thus, in the present study, the assessment of genetic diversity of wild-growing F. imperialis is attempted, employing 100 specimens from 10 geographical areas of central region Iran collected; for these samples, phenotypic diversity within and among the populations was evaluated based on qualitative and quantitative attributes. The main objectives of this study were as follows: (1) to quantify the rate of morphological variation within and among populations studied, (2) to detect correlations between morphological variation and geographical distances among populations, (3) to develop recommendations for in situ conservation of this valuable species, (4) to recognize the most useful variables for discrimination within the examined specimens, and (5) to detect the specimens which might be useful as genetic resources for future breeding programs. This is the first study on genetic variation within and among population of F. imperialis in Markazi province, a central region of Iran.The portance . Due to  species . This Ir species . Unfortu species , 19. F. imalayas . Since, F. imperialis were studied from ten natural areas of Markazi province, a central region of Iran. A voucher specimen of this material has been deposited in the publicly available herbarium of Faculty of Agriculture and Natural Resources, Arak University, Iran with deposition number of FI-2342. The collection of plant was permitted from Agricultural and Natural Resources, Iran. The minimum distance between the specimens collected in each area was 20 m.During April 2021, a total of 100 wild individual specimens of F. imperialis. Geographical distribution and sampling information of the areas collected are presented in Table The studied areas have high plant diversity, so these areas were selected based on the presence and potential diversity of All morphological traits were measured and recorded at full flowering time. Thirty-seven phenotypic attributes, including qualitative and quantitative traits of flower, stem, leaf, and bulb, were used for the assessment of the genetic variability of the studied specimens. Quantitative traits, such as plant length, length and diameter of peduncle, width and length of leaf, width and length of flower, bulb diameter, and bulb length were measured using a digital caliper. In addition, qualitative traits were surveyed based on rating, scoring, and coding.Analysis of variance (ANOVA) was performed to evaluate the variation among specimens based on the traits measured using SAS software . Simple F. tubiformis var. burnatii (Planch.) Rouy. Also, high levels of genetic diversity were reported among seven populations of F. imperialis in the Zagros region of Iran [Analysis of variance (ANOVA) showed significant difference among the populations studied based on the measured characteristics Table . In agre of Iran . This hi of Iran , 24. Hig of Iran . In otheFrom an ornamental point of view, plant length, peduncle length, peduncle diameter, flower color, flower number, flower diameter, and flower length are very important defining largely the floricultural value of many species. In the present study, moderate to high genetic variations were observed in each of the above-mentioned traits. Plant length varied from 31.00 to 106.00 cm with an average of 57.52 cm, while peduncle length ranged from 17.00 to 46.00 cm. The highest plant length and peduncle length were observed in the Shahbaz-6 specimen and the lowest in the Eyvand-e-Now-10 specimen. Also, the highest peduncle diameter in downward and upward was detected in the Shahbaz-6 specimen; and the lowest peduncle diameter was detected in the Eyvand-e-Now-5 specimen. A high variation was found among specimens regarding flower number and flower color. The flower number varied from 2 to 8, and flower color varied from light orange to red. In most of the specimens, the petal was orange or dark orange (60 specimens) (Table Peduncle color was gray in most of the specimens (90), while it was dark gray in all specimens of Tureh population. Also, anther color was yellow in 90 specimens, while it was light yellow in 10 specimens Table . Leaf coCrocus sativus L. [Triticum monococcum L. subsp. aegilopoides(Link) Thell. [Allium sativum L. [Juglans regia [Corchorus olitorius L. [Emmenopterys henryi Oliv. [Principal component analysis (PCA) was used to identify patterns of variability among the specimens studied. This method is one of the mighty multivariate statistical techniques to classify the assessed characteristics into effective groups. In this method, traits are placed in the components, each containing different characters. The PCA method can reveal the major differences among the specimens surveyed and also may decrease the amount of data. The relative variance of each component indicates the importance of the component in the variance of the studied traits and is expressed as percentage. The first component justifies the greatest amount of variance, and the subsequent factors justify the remaining changes after the first component . This antivus L. , Triticu) Thell. , Allium tivum L. , Juglansns regia , Corchororius L. , and Emmyi Oliv. .For each factor, the loading of the principal component was considered to be more than 0.63, indicating that the first six components of data accounted for 88.36% of total variance  which resounded relationship among the specimens in terms of morphological characteristics and phenotypic resemblance . In the Alborj area, the specimens were highly overgrazed before the flowering stage; and in Si-Qazghan area, due to the severe decrease in rainfall in 2021, the wild-growing stands of F. imperialis were found to be chlorosized in the vegetative stage and did not enter the flowering phase; therefore, no data were collected from these two populations. Commonly, it is expected that density and sizes of populations will be sharply reduced by overgrazing and overharvesting of the wild resources of F. imperialis. Consequently, this will inevitable result to patches and local extinction events, and decreased ability to adapt to changing environments. For instance, previous reports have shown that the genetic diversity of the American ginseng has significantly decreased by random harvesting [Thymus algeriensis, with populations from the arid zone being the most affected ones [F. imperialis naturally thriving in such semi-arid and arid lowland areas is of vital importance.The results herein showed that the population of the areas with higher altitude and more snowfall, such as Shahbaz population, had higher density and quality of specimens in respect to the populations of areas with lower altitude and less snowfall, including Deh-Sad and Tureh populations. The in situ observations showed that overgrazing and overcollection by local people is exercised widely in the areas with lower altitude. Furthermore, the amount of rainfall in these areas is less compared with other areas. Based on meteorological data, the highest annual rainfall is recorded every year in Shahbaz area, which had the highest superior specimens. Compared with other areas, it is also more difficult for local people to access the Shahbaz area for grazing and harvesting. According to our field visiting, it was observed that the size and density of local populations are rapidly decreasing due to overharvesting and overgrazing, especially in low altitudes. It is known that overcollecting and overgrazing may also lead to reduced genetic diversity in wild-growing populations . Furtherrvesting , 24, 33.ted ones . Based oted ones , 36. TheF. imperialis, which would be useful as genetic resources for future breeding programs and creation of new Fritillaria varieties for ornamental purposes. The Shahbaz-1, Shahbaz-2, Shahbaz-6, Shahbaz-7, Shahbaz-9, and Bolagh-8 specimens showed the highest variation and were separated from others, which they can be used further in breeding programs, while Sarchal-2, Bolagh-3, and Chepeqli-4 specimens showed the lowest variability. From an ornamental point of view, the Shahbaz-1, Shahbaz-2, Shahbaz-6, Shahbaz-7, and Shahbaz-9, all specimens from Shahbaz area, seem to be the most promising for breeding programs, since they were characterized by high values of important ornamental features . Based on bi-plot of population analysis, the studied populations were discerned into four distinct groups, all correlated with observed geographical distances among populations (each group included adjacent populations). These results were confirmed by analysis of the pairwise population matrix of the mean binary genetic distance. Although the studied specimens have shown high genetic diversity in this study, our results and observations have shown that the wild-growing populations of F. imperialis are currently at risk of rapid depletion in the most of studied areas, especially in Deh-Sad, Tureh, Alborj, and Si-Qazghan. The main reasons for this trend were overgrazing, overharvesting, and climate change. Preservation of genetic diversity is one of the main objectives in conserving the threatened species. Therefore, the protection of existing wild-growing populations of F. imperialis in Iran is essential and vital. Limitation of overgrazing and overharvesting, surveillance and customs control are suggested to maintain effective population sizes of F. imperialis conserved in situ. Moreover, domestication, development of species-specific propagation protocols, and cultivation protocols prior to artificial selection of desired specimens, are effective measures to preserve this species allowing at the same time its sustainable exploitation in the ornamental sector.Based on morphological data, high levels of genetic variation were detected within populations of


Matsumurasca onukii . Oyo‐Kontyu Tokyo, 8(1): 19–21), one of the dominant pests in major tea production areas in Asia, currently is known to occur in Japan, Vietnam, and China, and severely threatens tea production, quality, and international trade. To elucidate the population genetic structure of this species, 1633 single nucleotide polymorphisms (SNPs) and 18 microsatellite markers (SSRs) were used to genotype samples from 27 sites representing 18 geographical populations distributed throughout the known range of the species in East Asia. Analyses of both SNPs and SSRs showed that M. onukii populations in Yunnan exhibit high‐genetic differentiation and structure compared with the other populations. The Kagoshima (JJ) and Shizuoka (JS) populations from Japan were separated from populations from China by SNPs, but clustered with populations from Jinhua (JH), Yingde (YD), Guilin (GL), Fuzhou (FZ), Hainan (HQ), Leshan (CT), Chongqing (CY), and Zunyi (ZY) tea plantations in China and the Vietnamese Vinh Phuc (VN) population based on the SSR data. In contrast, CT, CY, ZY, and Shaanxi (SX) populations clustered together based on SNPs, but were separated by SSRs. Both marker datasets identified significant geographic differentiation among the 18 populations. Various environmental and anthropogenic factors, including geographical barriers to migration, human transport of hosts (Camellia sinesis [L.] O. Kuntze) and adaptation of M. onukii to various local climatic zones possibly account for the rapid spread of this pest in Asia. The results demonstrate that SNPs from high‐throughput genotyping data can be used to reveal subtle genetic substructure at broad scales in r‐strategist insects. Matsumurasca onukii, one of the dominant pests in major tea production areas in Asia. General migration route showed that there are two diffusion sources including Yunnan and the other tea plantations of China, respectively, from where introduced to Japan tea plantations. Our findings indicate that the host plants and geographical distances are significant involved to the genetic variation of M. onukii between different Clusters and that SNPs from high‐throughput genotyping data can be used to reveal subtle genetic substructure at broad scales in r‐strategist insects.In this study, SNPs and microsatellite markers were used to capture multiscale patterns of genetic structure of  Kuntze in Japan, Vietnam, and China that are grown under a variety of ecological conditions  have become widely used in population genetic analyses, particularly genotyping‐by‐sequencing (GBS) and restriction‐associated DNA sequencing (RAD‐seq)  to compare population relationships and levels of geographic differentiation among populations from the performances of SNPs and microsatellite markers and determine if patterns reflect morphological variation among populations; and (iii) to estimated historical migration between genetic clusters for inferring the evolutionary history of M. onukii populations in East Asia. This study will reveal correlated patterns of morphological variation and hierarchical genetic structure in East Asian M. onukii population, which will be useful in monitoring species distribution and future population dynamics. This will be enable better prediction, regulation, and management of M. onukii populations in different tea producing regions of East Asia.In the present study, microsatellite markers were coupled with high‐throughput sequencing approaches to obtain three goals: (i) to assess the spatial distribution of genetic variation of 22.12) near the center of each site, spaced 100 m or more apart. Specimens from all collecting sites within a location were pooled to represent one population. All these specimens were preserved in 100% ethanol and stored in the Entomological Museum, Northwest A & F University, Yangling, China (NWAFU).Tea green leafhopper specimens of 27 representative populations, including 24 Chinese localities, two populations from Japan (Kagoshima and Shizuoka), and one population from Vietnam (Vinh Phuc), were collected during the seasons of tea green leafhopper occurrence from 2013 to 2020 Table . The samSpecies identifications were confirmed by examining the morphological characters of all specimens from each representative population by dissection under an OLYMPUS SZX‐10 Stereoscopic Zoom Microscope. Male genitalia of each specimen was separately preserved in a small tube prefilled with glycerin and diagnostic characters  among populations were checked and compared to confirm the species identification and check for intraspecific variation.2.2Thirty male adults in each population, except for the dissected male genitalia used for species identification, were used for extracting DNA using either the CTAB method or DNeasy blood and tissue kits (Qiagen). The quality of DNA was detected and quantified with a Nanodrop One (Thermo Scientific).2.32.3.1Individuals of seven populations  were genotyped using 18 previously developed microsatellite markers Table . Genotyp2.3.2E), observed heterozygosity (HO), and expected heterozygosity, (HE) were determined using GenALEx v. 6.5.The frequency and signs of null alleles were investigated using FreeNA  repetitions. The range of possible clusters was set from 1 to 27 or to 18, with 20 independent runs for each K ) and the ad hoc statistic (ΔK) using the Web server Clumpak was used to align results from replicate analyses and visualize population structure  was constructed using POPTREE v. 2.0  based on population clustering from Structure v. 2.3.4 and FST was calculated using Arlequin v. 3.11  among the 2.42.4.1Based on the SSR population genetic analysis results, one to six populations  with significant genetic differentiation were selected from four genetic clusters. The GBS libraries were constructed and sequenced following the protocol of Elshire et al.  and OnyaApeKI and 300–600 bp fragments were determined by detecting genome size and its restriction sites. DNA (more than 500 ng) extracted from one sample of M. onukii from each of the 18 populations was added to 96‐well plates with 3 μl 10 × NEB buffer and 2 μl ApeKI (5 U/μl) (reagents from New England Biolabs) to a final volume of 30 μl and heated in water for 2 h. Following ligation, samples in PCR‐96‐well plates in 40 μl with 60 picomoles barcode DNA (5′‐ACACTCTTTCCCTACACGACGCTCTTCCGATCTxxxx and 5′‐CWG yyyyA GATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT) and universal adaptor (5′‐CWGAGATCGGAAGAGCGGTTCAGCAGGAATGCCGAG and 5′‐CTCGGC ATTCCTGCTGAACCGCTCTTCCGATCT), 1 mM dNTPs, 5 units T4 DNA Ligase and 4 μl10 × T4 DNA Ligation Buffer. The reaction system was incubated for 1 h and inactivated for 30 min at 65°C. The Barcode DNA provided special identification tags for each sample, and the included universal adaptor that also provided binding sites for sequencing primers. All the DNA fragments (300–600 bp) were pooled in a sequencing library after purification and recovery. Following amplification with sequencing primers, purification, and recovery, the quality of the library was assessed using an Aglient 2100 Bioanalyzer, KAPA Library Quantification Kit and Qubit 2.0. The libraries were then sequenced on an lllumina HiSeq 2500 platform using a 150 bp Paired End protocol at Allwegene Technologies.2.4.2Raw reads were obtained by Base calling, assessed for quality, and filtered by length of fragment, Q‐value, and sequence alignment in databases. The identification of SNPs in Raw reads was accomplished using the Universal Network Enabled Analysis Kit (UNEAK) in TASSEL 3.0 , expected heterozygosity (HE), and nucletide diversity (π) were determined by VCFtool v.4.0  in random mating populations was estimated by FASTStructure with a Bayesian assignment test, and the optimal K was chosen based on analyses with K from 1 to 20 replicates for cross‐validation, with clustering pattern generated by the online software Structure Plot v. 2.0. We also implemented the best model (determined by JMODELTest v. 2.1.7) to reconstruct population relationships using maximum‐likelihood (ML) with 100 bootstrap replicates in MEGA v. 7.0.14  vitis as the outgroup. The final tree was visualized and beautified using iTOL v. 4.0 ; PCoA was performed using SNPRelate in R  and the logarithm of geographic distance matrix (Log km) were estimated using a Mantel test with 999 permutations in GenALEx v. 6.5. The geographic distance between each pair of populations was estimated by Geographic Distance Matrix Generator v. 1.2.3  analyses were conducted to test whether genetic differentiation increased with geographic distance. The correlation between the linearized pairwise 3 Ersts, .2.6M) per generation and the mutation‐scaled population size (θ) were analyzed using the Bayesian inference with full model in MIGRATE v. 3.7.2  of each population was calculated with θ = 4Neμ   was calculated as Nem = θM/4. The first run was estimated from FST, and the other three runs were started with θ and M from the previous run. During the Bayesian search, one long chain with four independent replicates was used for each run with 10,000,000 generations after an initial burn in of 100,000 interactions. Heated chain was set to: 1.0, 1.5, 3.0, and 1000,000.Given high polymorphism and mutation rates, microsatellite markers were used to estimate population size and migration parameters among clusters obtained from the results of population structure analysis. The immigration rate  of t Figure ; in cont3.2M. onukii showed high‐genetic diversity in all tea production areas, as measured by the number of effective alleles (4.11–5.93), expected heterozygosity (0.665–0.778) and AR (7.244–10.060). Higher genetic diversity was found across M. onukii populations in China than in Japan   Table .M. onukii formed four main genetic clusters: Cluster 4–1 includes four populations from Central and East China, viz. Xinyang (XY), Rizhao (RZ), Taian (TA), and Hanzhong (SX) populations; Cluster 4–2 consists of 14 populations from South China, Japan, and Vietnam, viz. Jinhua (JH), Hangzhou (HZ), Huangshan (HS), Nanchang (NC), Yichun (YT), Chengde (CD), Yingde (YD), Guilin (GL), Baise (BS), Fuzhou (FZ), Hainan (HQ), Kagoshima (JJ), Shizuoka (JS), and Vinh Phuc (VN) populations; Cluster 4–3 includes three populations from Southwest China, viz. Leshan (CT), Chongqing (CY), and Zunyi (ZY) populations; Cluster 4–4 includes six populations from Southwest China, viz. Chuxiong (CX), Pu′er (PE), Mojiang (MJ), Menghai (MH), Lincang (LX), and Jingdong (JD) populations. The six populations of M. onukii from the Southwest tea production area in China  were also clustered ; although a significant fraction of the total variation was also due to variation between clusters  and between populations  (Table M. onukii throughout the tea plantations in East Asia (FST > 0.050)  Figure .3.3M. onukii in East Asia using microsatellite data, 18 populations were chosen for GBS analyses. After quality control, a final GBS dataset of 1633 SNPs representing 180 genotypes of M. onukii was obtained for further genetic analysis. On an average, the sequence depth of populations ranged from 5.85 to 10.84. The observed heterozygosity (range 0.231–0.364), the expected heterozygosity (range 0.210–0.291) and nucleotide diversity (range 0.198–0.275) indicated that higher genetic diversity is present in populations of M. onukii from the Southwest tea production areas in China . Among all 18 populations, the genetic diversity of populations of M. onukii in China was higher than those in Japan  and Vietnam   Table .3.4amova, revealed that populations were genetically more differentiated across the three clusters  than between populations   , but not significant based on microsatellite markers . IBD tests revealed no significant geographic differentiation in genetic clusters  with weak genetic differentiation and small distribution  Figure . The IBDn Figure .3.6θ, ranged from 563 to 2053. Frequent exchange of migrants per generation was inferred to occur among clusters . Asymmetric migration was found among clusters in China and between clusters in China, Japan, and Vietnam, with effective number of migrants per generation (Nem) from Cluster 3–1 and Cluster 3–2 to SX (34.29 and 11.37) higher than numbers of migrants in the opposite direction (11.16 and 6.33). CT/CY/ZY populations displayed asymmetric migration from Cluster 3–1 (65.13), Cluster 3–2 (20.06) and SX populations (13.02); Nem from Cluster 3–1 and Cluster 3–2 to Cluster 3–3 were 32.73 and 15.83; and immigrants to the VN population were mainly from Cluster 3–1 (19.10). When SX population or CT/CY/ZY populations were included in Cluster 3–1 based on the results by SNP dataset, obvious asymmetric migration was also detected  and identify population structure between populations with similar levels of genetic diversity, which is consistent to many prior studies . The “introduction from south to north” mainly occurred in recent decades, during which major tea planting areas were established in North China   Figure .4.2M. onukii populations from the Southwest tea areas, especially among the populations from Yunnan tea plantations that also exhibit morphological variation in the aedeagus. Such correlation between genetic and morphological variation contrasts with a previous study of Asymmetrasca decedens, in which no genetic differentiation was found between individuals of two morphotypes based on differences in the shape of the aedeagus,  and Shizuoka (JS) populations from Japan and the Vinh Phuc (VN) population from Vietnam are closely related to  Figures  and 4a. 4.3M. onukii populations in Yunnan (Cluster 3–2), Japan (Cluster 3–3) and the other tea plantations of China and Vietnam. Significant asymmetrical historical migration from Cluster 3–1 and Cluster 3–2 to Cluster 3–3 is supported by non‐overlapping 95% confidence intervals  in M. onukii. Instead, our results suggest that natural or human‐assisted dispersal occurs among major tea growing areas of China but not frequently enough to prevent maintenance of population‐level differences between major tea areas and high levels of genetic variability within some populations.Analyses of population structure and phylogeography based on the SNPs reveal significant genetic differentiation between s Figure . Previous Figure , and thes Figure . AccordiM. onukii populations throughout East Asia was further elucidated in this study by SNPs, and high levels of genetic differentiation were observed between populations in different clusters. But our analyses failed to reveal fine‐scale dispersal routes between populations. Incorporation of additional SNPs into future studies by more efficient genotyping with the M. onukii reference genome (ASM1883171v1) in Genome Warehouse may allow for finer‐scale analysis of gene flow among populations  and nature geographical condition  may be significant involved to the genetic variation of M. onukii between different Clusters.Recent advances in sequencing technologies can provide genomic data for accurately identifying patterns of genetic structure with effective samples. The accurate genetic structure will be obtained when the gene markers and samples are chosen reasonably. In this study, representative populations of M. onukii, further study should encompass more SNPs and additional samples from various host plants within Camellia spp. at fine scales (such as within the southwest tea planting area). Higher‐resolution study of gene flow and its relation to geography/host associations will help elucidate the microevolution of adaptability in M. onukii populations in the East Asia.Therefore, to illuminate fine‐scale dispersal routes of Li Zhang: Conceptualization ; formal analysis (lead); investigation (lead); resources ; software ; writing – original draft (lead); writing – review and editing . Christopher H. Dietrich: Conceptualization (supporting); writing – original draft (supporting); writing – review and editing . Ye Xu: Investigation (supporting); writing – original draft (supporting); writing – review and editing . Zhaofu Yang: Software ; writing – review and editing . Maohua Chen: Conceptualization (supporting); methodology (lead); writing – review and editing . Thái H. Pham: Funding acquisition (supporting); resources (supporting); writing – review and editing (supporting). Cuong C. V. Le: Resources (supporting); writing – review and editing (supporting). Li Qiao: Resources (supporting); writing – review and editing (supporting). Masaya Matsumura: Resources (supporting); writing – review and editing (supporting). Daozheng Qin: Conceptualization ; funding acquisition (lead); investigation (supporting); resources (lead); writing – original draft (supporting); writing – review and editing .The authors declare that there are no conflicts of interest.M. onukii, is an agricultural pest, not an endangered or protected species. All the samples were collected in open tea plantations and not from any national parks or protected areas.Benefits from this research accrue from the sharing of our data and results on public databases as described earlier. No specific permits were required for this study. Tea green leafhopper, Appendix S1Click here for additional data file.


HBAD), as well as other novel potential genes  that are related to blood coagulation and cardiovascular efficiency. Our study provides novel insights regarding the evolutionary history and microevolution mechanisms of the high‐altitude adaptation in the Tibetan chicken.As an indigenous breed, the Tibetan chicken is found in highland regions and shows physiological adaptations to high altitude; however, the genetic changes that determine these adaptations remain elusive. We assumed that the microevolution of the Tibetan chicken occurred from lowland to highland regions with a continuous elevation range. In this study, we analyzed the genome of 188 chickens from lowland areas to the high‐altitude regions of the Tibetan plateau with four altitudinal levels. Phylogenetic analysis revealed that Tibetan chickens are significantly different from other altitude chicken populations. Reconstruction of the demographic history showed that the migration and admixture events of the Tibetan chicken occurred at different times. The genome of the Tibetan chicken was also used to analyze positive selection pressure that is associated with high‐altitude adaptation, revealing the well‐known candidate gene that participates in oxygen binding ( The genetic mechanism underlying high‐altitude adaptation is currently a topic of great interest and has important implications for understanding adaptation in low‐oxygen environments. Several animals have been studied to determine the genetic basis of such adaptation using high‐throughput sequencing. For example, whole‐genome selective scans have identified positive selection of a set of genes, including Gallus gallus spadiceus, which is currently predominant in southwestern China, northern Thailand, and Myanmar  using BWA‐MEM (v 0.7.17)  following the manufacturer's instructions, and index codes were added to attribute the sequences to each sample. In brief, DNA was fragmented to a size of 350 bp by sonication and end‐repaired, A‐tailed, and ligated to paired‐end adapter for sequencing with further polymerase chain reaction (PCR) amplification. The constructed libraries were sequenced on the Illumina HiSeq X Ten platform (Illumina Inc.) and paired‐end 150‐bp reads were generated. Sequence reads were filtered using fastp (v 0.12.3)   and expected heterozygosity (He) as well as run of homozygosity (ROH) with a minimum length of 100 kb containing at least 50 SNPs and a maximum of 1 heterozygous variant using Plink (v 1.9)  for each breed and population was calculated using a sliding‐window approach (100‐kb windows with 50‐kb steps).Linkage disequilibrium (LD) was calculated as the parameter 2.4K = 2–8).Principal component analysis (PCA) was performed using GCTA (v 1.91)  .To estimate the effective population size, we applied SMC++ (v1.15.4) . WLS and ZY were used as the representative middle‐altitude region chickens (MA) and CH as the reference low‐altitude area chickens (LA). We assumed that the TBC was derived from the MA populations in model 1 and from the LA populations in model 2. In model 3, we considered that the JR was derived from the LA populations. The JR and TBC were both assumed to be derived from the MA populations in model 4. For each demographic model, we performed 500,000 simulations, 50 conditional maximization cycles, and 100 replicate runs starting from different random initial values. The best fit demographic model was identified by the Akaike information criterion  enrichment analysis was performed using DAVID (v 6.8)   altitudes showed an overall slow decay rate and a high level of LD, whereas the two other “3200 m+” (SN and NX) and “1500 m” (ZY and WLS) populations showed an overall fast decay rate Figure . The hete Table . The gens Figure . A larges Figure .3.3To understand the phylogenetic relationships and population structure of the domestic chickens from the elevation gradient area, we utilized the whole‐genome SNP dataset of the 188 individuals. Using the RJF as an outgroup, the phylogenetic tree showed a distant relationship between the “3200 m+”  and “500 m” chickens, followed by “1500 m” chickens. The “3200 m+” chickens were split into two geographically structured clades. One is the TBC living in the Yarlung Zangbo River basin. Another is NX, which was grouped with the “2500 m” populations according to their geographical origin in the JR basin Figure . The PCAK ancestral populations. When K = 3, we observed a division between the RJF and TBC, as well as between the populations living at high and low altitudes. Besides, the RJF share a distinct genetic background with BG and CH based on K = 4 and 5. When K = 6, which is the best value exhibiting the lowest cross‐validation error, the result was largely consistent with the PCA results and supported that there were two divergent groups of HACs different from the lowland chicken; one group (NX) has a genetic makeup similar to that of Yunnan native chicken  tree without migration events inferred from the TreeMix analysis divided the HACs into two clusters Figure , which ae Figure . This ise Figure .f3 test, and D‐statistics were performed. The f3 test indicated that the TBC carries more genetic ancestry from NX  than other chicken breeds  with positive D values, suggesting a closer relationship between the TBC and NX chickens than between other chicken breeds, including the LJ breed that has a closer geographical location and genetic structure according to previous results  contained 1860 genomic regions and comprised 399 candidate genes  are involved in the response to hypoxia, three  are involved in oxygen transport, three  are enriched in negative regulation of vascular smooth muscle contraction, and four  are involved in regulation of heart rate. In addition, we noted that five genes  are involved in platelet alpha granule lumen, which could affect platelet degranulation and blood coagulation . The selection signatures were incompatible, which might be due to different selective pressures between the groups  and TBC populations, the top 1% s Figure . Among ton Table . We alsos Figure .Fst and XP‐nSL and detected 117 genes, providing strong evidence for the adaptive role of high‐altitude adaptation  that were highly selected in Fst, and RYR2 with high positive selection, providing further insight into the molecular mechanisms underlying the high‐altitude hypoxia adaptation of the TBC , which has the power to detect ongoing and recently completed hard and soft sweeps, and then applied this statistic to search for evidence of high‐altitude adaptation in chickens. Moreover, as the positive and negative values of XP‐nSL indicate the directionality of selection, all SNPs within an XP‐nSL value are needed to show the same directionality. The normalized top 1% absolute XP‐nSL values corresponded to longer and higher frequency haplotypes and were located in 462 genes Table . To furton Table . Among tC Figure .3.7p‐value <0.01 as the selection criterion and obtained 249,613 selected variants , but also novel genes, such as GJA5, ASIC2, and CACNA2D1. The overlapping genes were primarily related to the GO terms regulation of heart rate, negative regulation of vascular smooth muscle contraction, artery morphogenesis, and regulation of ventricular cardiac muscle cell membrane repolarization  mutation in HBAD which is present in both the TBC and NX; this mutation may increase the oxygen affinity of hemoglobin owing to the lower hydrophobicity of leucine than that of methionine, potentially stabilizing the hemoglobin oxygen structure , is also selected with high Fst values. Population genomic researches are useful for generating information about the genetic basis of high‐altitude adaptation. In Tibetan highlanders, one of the most extreme environments dwellers, such genome scans have implicated central components of the HIF signaling pathway, which orchestrates the transcriptional response to hypoxia  that reportedly play roles in the regulation of vascular smooth muscle contraction  in HBAD can increase the oxygen affinity of hemoglobin and facilitate hypoxic adaptation of chickens (Gou et al., As for NX, we identified Although some studies have reported that genes associated with high‐altitude adaptation in the TBC are mainly involved in the calcium‐signaling pathway, energy metabolism, body size maintenance, and regulation of gene expression (Li et al., In conclusion, our findings demonstrated the genomic variability, population structure, and demographic history of the TBC and revealed a variety of well‐known and novel genes, as well as important GO categories that are associated with the high‐altitude adaptation of chickens. Specifically, the gradient altitudinal model analysis revealed that the candidate genes and GO terms were functionally related to hypoxia responses, oxygen delivery, and cardiovascular system function in the plateau environment. These results lay a foundation to elucidate the mechanisms of high‐altitude adaptation in chickens and other livestock species, particularly avian species, to facilitate their survival in the QTP. Furthermore, these newly generated genome‐wide data are valuable resources for future genetic improvement of the TBC.The authors declare that they have no conflict of interest.Figure S1Click here for additional data file.Table S1Click here for additional data file.


The accumulative efficiency results indicated that the set of II-SNPs could be used as a potential tool for forensic individual identification and parentage testing in the Manchu group. The sequencing depths ranged from 781× to 12374×. And the mean allele count ratio and noise level were 0.8672 and 0.0041, respectively. The sequencing results indicated that the SNP genetic marker detection based on the massively parallel sequencing technology for SNP genetic markers had high sequencing performance and could meet the sequencing requirements of II-SNPs in the studied group.Single nucleotide polymorphism (SNP) possesses a promising application in forensic individual identification due to its wide distribution in the human genome and the ability to carry out the genotyping of degraded biological samples by designing short amplicons. Some commonly used individual identification SNPs are less polymorphic in East Asian populations. In order to improve the individual identification efficiencies in East Asian populations, SNP genetic markers with relatively higher polymorphisms were selected from the 1,000 Genome Project phase III database in East Asian populations. A total of 111 individual identification SNPs (II-SNPs) with the observed heterozygosity values greater than 0.4 were screened in East Asian populations, and then, the forensic efficiencies of these selected SNPs were also evaluated in Chinese Inner Mongolia Manchu group. The observed heterozygosity and power of discrimination values at 111 II-SNPs in the Inner Mongolia Manchu group ranged from 0.4011 to 0.7005, and 0.5620 to 0.8025, respectively, and the average value of polymorphism information content was greater than 0.3978. The cumulative match probability and combined probability of exclusion values at II-SNPs were 7.447E Therefo-8) , abilityIn 1998, a human SNP genetic map containing 2227 SNP genetic markers was first reported by However, due to the allelic frequency distributional differentiations among different continental populations, it is uncommon for some given SNPs to have high heterozygosites in different populations around the world. At present, several SNPs, including rs251934, rs1886510, rs740910, rs729172, and rs2056277, in the common kit were reported to show poor forensic efficiencies in the East Asian populations . TherefoThe detection and genotype methods of SNP genetic markers include single-strand conformation polymorphism , denaturhttp://www.stats.gov.cn/tjsj/ndsj/2021/indexch.htm), the population of Manchu  ranks the fifth largest among Chinese ethnic minorities, which are mainly distributed in the Inner Mongolia Autonomous Region, Jilin, Beijing, and other provinces. Among them, the Inner Mongolia Autonomous Region with ethnic minorities stretches from northeast to southwest in a long and narrow shape in the northern border area of China. The unique geographical locations as well as the wide distributions of ethnic minorities make it one of the long-standing and necessary regions in population genetic differentiation research. Nowadays, most of the Manchu groups living in the Inner Mongolia Autonomous Region are the descendants of the Manchurian eight banners, who were stationed in Guihua and Suiyuan cities (both of which belong to today’s Hohhot area) in the Qing dynasty  group and other reference populations.SNPs with relatively higher polymorphisms in East Asian populations were selected from the 1000 Genomes Project phase Ⅲ database . The HanThe 187 bloodstain samples were collected from Chinese Inner Mongolia Manchu individuals. All volunteers stated that they were healthy and unrelated within three generations, then signed the written consent forms. This experiment was approved by the ethics committees of the Xi’an Jiaotong University Health Science Center and Southern Medical University . The 26 populations from the 1000 Genomes Project phase Ⅲ database were included as reference populations. The detailed information on populations are listed in The first-round PCR reaction mixture was mixed with 25 μL PCR Enzyme Mix, 0.5 μL PCR Clean Enzyme, 4 μL PCR Primer Pool, and DNA template. The PCR cycle parameters were listed as follows: 12 cycles at 95°C for 15s, 60°C for 5 min, 72°C for 30s, and a final extension at 72°C for 2 min. Then the first-round PCR products were purified by DNA Clean Beads .The second-round PCR reaction mixture included 25 μL PCR Enzyme Mix, 0.5 μL PCR Clean Enzyme, 1 μL PCR Additive, and 2 μL PCR Primer A. The PCR cycle parameters were listed as follows: 16 cycles at 95°C for 15s, 60°C for 2 min, 72°C for 30s, and a final extension at 72°C for 2 min. The second-round PCR products were purified in the same way as in the previous step.® dsDNA HS Assay kit . Then the single-chain cyclization reaction solution and enzyme digestion reaction solution were prepared to cyclize and digest the library, respectively. DNA nano balls were prepared by adding 5 ng digested product and elution buffer up to 20 μL.The purified PCR products were quantified by the Qubithttps://github.com/freebayes/freebayes) based on the Bayes algorithm.DNA sequencing was based on the MGISEQ-2000RS , and the sequencing parameter was set to ‘FCL SE50+10’. The quality control and preprocessing of sequencing data were conducted by SOAPnuke software . The filp values of the HWE exact tests and linkage disequilibrium (LD) analyses were calculated by Genepop v4.0 software (http://www.cmpg.iee.unibe.ch/services/shiny/index_eng.html). The forensic parameters of 111 II-SNPs in the IMM group were visualized by the heatmap using TBtools V1.0 software (DA distances) and pairwise fixation index (FST) values among the IMM group and 26 reference populations were calculated by the DISPAN software and Arlequin V3.5 software, respectively  based on the original SNP genotyping data of the IMM group and 26 reference populations. The population genetic structure analysis of 27 populations was conducted by the STRUCTURE V2.3.4 software , allele coverage ratio (ACR), and noise level (NL) values. The box plots of DoC, ACR, and NL values were produced by Origin v2021 software. The software . The allsoftware  , and all pairwise SNPs were in linkage equilibrium (p > 0.05/6105) after Bonferroni correction. The results of LD tests at 111 II-SNPs are revealed in -51, 1-7.47E-51, and 1-4.17E-12, respectively. In The 111 II-SNPs conformed to HWE  and FST value (0.0038) were observed between the IMM group and the CHB population from East Asia. The maximal DA (0.0463) and FST values (0.1163) were observed between the IMM group and the YRI population from Africa. The smaller DA and FST values between the IMM group and East Asian populations ranged from 0.0029 (CHB) to 0.0052 (CDX), and 0.0038 (CHB) to 0.0112 (CDX), respectively. The larger DA and FST values between the IMM group and the African populations ranged from 0.0284 (ASW) to 0.0463 (YRI), and 0.0732 (ASW) to 0.1163 (YRI), respectively. As shown in the heatmaps, populations from the same continent had relatively closer genetic distances and few genetic differentiations, while the opposite situation could be observed among populations from different continents.The DA values among the IMM group and 26 reference populations. Different continents were represented by different colors. The orange, yellow, light pink, dark pink, and dark green identifiers represented East Asia, Africa, South Asia, America, and Europe, and the IMM group was highlighted in red. The red outer circle represented the DA distance values between the IMM group and 26 reference populations, whereas the blue outer circle represented the FST values between the IMM group and 26 reference populations, and the height of the bar chart represented the magnitudes of DA distances or FST values. The phylogenetic tree was mainly divided into two branches; one branch consisted of seven populations from Africa including ASW, ACB, LWK, GWD, MSL, ESN and YRI, and the other branch consisted of the remaining populations. Specifically, five populations  in Europe, five populations  in South Asia, and six populations  in East Asia, clustered in their sub-branches, respectively; and then with the four populations  from America converged into one branch. The IMM group first aggregated with the CHB population, and then merged into the East Asia sub-branch. Phylogenetic analysis results indicated that the genetic relationships between the IMM group and East Asian population were closer, and the genetic relationships between the IMM group and African populations were further.As shown in K = 2-7) in K = 2, the 27 populations were mainly divided into African populations whose main ancestral information component was magenta and the non-African populations whose main ancestral information component was purple. The optimal preset K value was 3, which was assessed by the Structure Harvester program. East Asian populations represented as blue ancestor information component could be distinguished from non-African populations, while other populations were occupied by the high European ancestor information component. With the increase of K values, the South Asian populations were mainly occupied by the green ancestral component, and the American populations (PEL and MXL) were mainly occupied by the yellow ancestral component, which could be distinguished from the European populations when K = 4 and K = 5, respectively.To infer the possible ancestral component proportion in the IMM group based on 111 II-SNPs, the population genetic structure analyses of the IMM group and 26 reference populations were conducted using STRUCTURE V2.3.4 software. We sorted the ancestral proportions from the lowest to the highest values by the preset ancestral information components  of 111 II-SNPs was greater than those of the 15 STRs (0.9999999999999999849) and 19 STRs (0.9999999999999999999942) in the Manchu group reported by He and Liu (-12) of 111 II-SNPs was greater than those of the 90 SNPs  from the Precision Identity Panel in Tibetan, Uygur, and Hui groups (-10) in East Asian populations (-51) of 111 II-SNPs was less than those of the 94 SNPs (1.03E-35) from the ForenSeq™ DNA Signature Prep kit in Chinese population  in the IMM group was significantly higher than those from African (1.5%) and European populations (2.5%) when  markers .We systematically screened 111 relatively high polymorphic autosomal SNPs for individual identification in East Asian populations and comprehensively assessed the forensic efficiency in East Asian populations from the 1000 Genomes Project phase III and further evaluated the sequencing performances, genetic polymorphisms, and forensic application values in the IMM group. The 111 II-SNPs revealed good sequencing performances and high genetic polymorphisms, which could provide effective tools for individual identification and parentage testing in the IMM group. However, to increase the widespread applications of the selected SNPs, more East Asian populations should be included, and various genetic markers should also be accommodated in the MPS platform.


Sicily is one of the main islands of the Mediterranean Sea, and it is characterized by a variety of archaeological records, material culture and traditions, reflecting the history of migrations and populations’ interaction since its first colonization, during the Paleolithic. These deep and complex demographic and cultural dynamics should have affected the genomic landscape of Sicily at different levels; however, the relative impact of these migrations on the genomic structure and differentiation within the island remains largely unknown. The available Sicilian modern genetic data gave a picture of the current genetic structure, but the paucity of ancient data did not allow so far to make predictions about the level of historical variation. In this work, we sequenced and analyzed the complete mitochondrial genomes of 36 individuals from five different locations in Sicily, spanning from Early Bronze Age to Iron Age, and with different cultural backgrounds. The comparison with coeval groups from the Mediterranean Basin highlighted structured genetic variation in Sicily since Early Bronze Age, thus supporting a demic impact of the cultural transitions within the Island. Explicit model testing through Approximate Bayesian Computation allowed us to make predictions about the origin of Sicanians, one of the three indigenous peoples of Sicily, whose foreign origin from Spain, historically attributed, was not confirmed by our analysis of genetic data. Sicilian modern mitochondrial data show a different, more homogeneous, genetic composition, calling for a recent genetic replacement in the Island of pre-Iron Age populations, that should be further investigated. Sicily is the largest island of the Mediterranean Sea, and it is widely known for its key role as a crossroad for human colonization from the early Holocene to the Middle Age. Indirect evidence of human presence in Sicily, based on lithic surface finds , 1969, cComplex demographic and cultural dynamics should have affected the genomic landscape of Sicily at different levels; however, the geographical origin of some of the cultures dwelling in the Island, as well as the relative impact of these migrations on the genomic structure and differentiation of current Sicilian populations is actually largely unknown. The available genetic data are indeed mainly from modern populations, both uniparental   and autoIn this work, we reconstructed 43 complete or nearly complete mitochondrial genomes from individuals retrieved in five necropolises located in the island of Motya (western coast of Sicily) and in the archaeological sites of Baucina, Mokarta, Lilibeo and Ispica see , with thAncient sample preparation and sequencing. We collected petrous bones and teeth of 58 individuals from five different archeological sites: 16 specimens from Motya, 34 from Baucina, five from Mokarta, one from Lilibeo and two from Ispica, spanning from the Bronze Age to the Hellenistic period . For BauMitochondrial consensus sequences reconstruction and contamination estimation. Sequencing data were demultiplexed and sorted according to the individual sample barcodes added to each DNA fragment during library preparation. Raw reads were then processed using the pipeline described in Radiocarbon dating. Radiocarbon measurements were performed on collagen extracted from petrous bones according to the modified-Longin method. After reducing to graphite the collected material, C-14 concentration in unknown samples was measured by Accelerator Mass Spectrometry . Conventhttps://www.ebi.ac.uk/ena) and GenBank (https://www.ncbi.nlm.nih.gov/genbank). The samples from http://picard.sourceforge.net/) to add read groups (AddOrReplaceReadGroups) and to remove duplicated reads from the obtained BAM files (MarkDuplicates).Data collection and processing. We collected 300 high quality complete mitochondrial genomes from the literature accessible on public databases such as The European Nucleotide Archive , Caltanissetta (n = 29), Catania (n = 10), Enna (n = 5), Messina (n = 6), Palermo (n = 81), Ragusa (n = 8), Siracusa (n = 5) and Trapani (n = 13), thus representing all the nine administrative provinces of the Island. An anonymous code was assigned to each participant and mitochondrial control region sequence was obtained, as previously described  from all administrative provinces of Sicily. After signing an informed consent, each volunteer provided a saliva sample, through mouthwash rinse, and a pedigree chart with known genealogical data. This genealogical information was analyzed to reallocate the samples based on their terminal maternal ancestor (TMA), as follows: Agrigento (escribed .http://www.phylotree.org/) (Genetic structure and differentiation. All mtDNA haplotypes were classified into haplogroups using Haplogrep 2.0  accordinee.org/) . The conee.org/) . A diachee.org/)  and condee.org/) .We also calculated FST values between groups with Arlequin v.3.5  and visuhttp://popart.otago.ac.nz/). We built a Neighbor-Joining phylogenetic trees , detailed in We obtained complete or nearly complete mitochondrial sequences from 43 individuals, with an average coverage between 6x and 511x and modern human contamination level lower than 6% for all the samples with the exception of the sample MOK2 that showed a contamination level of 32% . RadiocaThe novel sequences have been deposited in GenBank under accession number: ON496938-ON496980.For the population genetic analyses we subdivided the newly generated ancient samples into seven groups, considering geographic criteria  and/or historical and cultural information . Samples that showed a mean coverage <20x and a contamination level >6% were excluded . A detailed description of the samples analyzed is shown in We combined the newly produced mitochondrial sequences with data collected from the literature . We incln = 17) and a frequency of 37,5% in the Motya Bronze Age (n = 8) group, respectively. The same haplogroups are represented at high frequencies in previously reported samples from Early Bronze Age Sicily and mainland Iron Age Italy. The Sicilian samples attributed to the Phoenician culture belong to HV and V haplogroups, today found predominantly in the Near East and Caucasus (HV) and Northern Europe (V) (rope (V) . The Brorope (V) , whereasrope (V) . The NJ rope (V)  reflectsrope (V)  describeTo better explore the genetic relationship among Sicilian samples we run a Principal Component Analysis (PCA), on the haplogroup frequencies within groups . In FiguWe also compared the ancient mitochondrial genetic structure of Sicily with that present in modern populations of the Island. To this aim, we analyzed the mtDNA haplogroup distribution of a novel dataset of 175 modern individuals from different geographic areas of the region. The most common western Eurasian macro-haplogroups have been identified in modern Sicilians . The mosAmong the ancient populations dwelling in Sicily, the Sicanians are known to have the most controversial origin. Thucydides  claims that they descended from Iberians, while other authors have described Sicanians as Illyrians descendants  or develWe defined two alternative demographic models as shown in The study of ancient complete mitochondrial genomes from Sicily presented in this paper has generated insight into the diachronic level of population genetic structure of one of the main islands of the Mediterranean Sea. The analysis of mitogenomes from the Mediterranean allowed us to contextualize the Sicilian genetic variation with that of possibly related groups from Early Neolithic to Iron Age. Whereas the comparison with modern Sicilian variation marked the first step towards the understanding the genetic impact of ancient cultures on the modern inhabitants of the Island.p-value: 0.00139 + −0.00035) whereas in Sardinia, the other main island in the Mediterranean basin, the genetic differentiation is not significant . The mitochondrial genetic structure we identify in Sicily is in agreement with the documented historical migrations of populations belonging to different cultures, which made the Island a major Mediterranean crossroad for different populations from Europe, North Africa, and the Levant for a long time  and to the Greek culture ; the haplogroups compositions and the FST heatmap , 4 actuaAs highlighted in When ancient Sicilians were contextualized within the Mediterranean domain, we did not find any genetic link between Sicanians individuals (both from Baucina and Iron Age Polizzello) and other Iberian populations. Another interesting similarity pattern came from the Phoenicians in Motya, that showed large resemblance with Levant Late Bronze Age, and the highest FST values (about 0.3) with Phoenicians from Iberian islands. Among the haplogroups identified in the new sequenced samples the most notable is undoubtedly the L3, currently present at high frequency in Northeast Africa . This L3Finally, we compared the ancient Sicilian genetic structure with that of modern individuals with known Sicilian ancestry, coming from nine cities around the Island. From the comparison of frequency distribution of mitochondrial haplogroups of ancient and modern Sicilian populations, as well as from the structure emerging from the PCA of This study is restricted to the analysis of a uniparental marker, the mitochondrial genome. Focusing on this marker gave us the opportunity to extend the sampling and the sequencing to a higher number of individuals, so as to adequately representing different cultures dwelling in Sicily in different time periods, and allowing us to identify a structured genetic variation and quantify genetic distances among groups. Albeit limited to the maternal lineage, the present study indeed emphasizes the complex genetic scenario of Sicily since its colonization. The structured genetic variation in culturally defined groups actually supports that cultural processes and exchanges within the Island have been accompanied and promoted by movement of people, and that these dynamics left a footprint on the genetic background of ancient individuals. Modern populations present a rather different pattern of maternal genetic variation; the more homogeneous composition of contemporary uniparental gene pool within Sicily (also reported by We acknowledge that the amount of genetic information as well as the inferential power of this uniparental marker is limited with respect to genome-wide ancient DNA data. The analysis of whole-genome variation of different ancient populations from Sicily would provide a more accurate and comprehensive source of information to make inference about past dynamics, such as the time and the origin of principal migration events within the island, the extent of genetic links among contemporary and diachronic groups, and will allow us to explicitly test the hypothesis of a genetic turnover within the island in the last two to three thousand years.