Anoplophora glabripennis (Motschulsky)) to spread beyond its native range and become a globally regulated invasive pest. Within its native range of China and the Korean peninsula, human‐mediated dispersal has also caused cryptic translocation of insects, resulting in population structure complexity. Previous studies used genetic methods to detangle this complexity but were unable to clearly delimit native populations which is needed to develop downstream biosurveillance tools. We used genome‐wide markers to define historical population structure in native ALB populations and contemporary movement between regions. We used genotyping‐by‐sequencing to generate 6102 single‐nucleotide polymorphisms (SNPs) and amplicon sequencing to genotype 53 microsatellites. In total, we genotyped 712 individuals from ALB’s native distribution. We observed six distinct population clusters among native ALB populations, with a clear delineation between northern and southern groups. Most of the individuals from South Korea were distinct from populations in China. Our results also indicate historical divergence among populations and suggest limited large‐scale admixture, but we did identify a restricted number of cases of contemporary movement between regions. We identified SNPs under selection and describe a clinal allele frequency pattern in a missense variant associated with glycerol kinase, an important enzyme in the utilization of an insect cryoprotectant. We further demonstrate that small numbers of SNPs can assign individuals to geographic regions with high probability, paving the way for novel ALB biosurveillance tools.Human‐assisted movement has allowed the Asian longhorned beetle (ALB,  Within its native range, ALB is considered an important forest pest, damaging and killing many tree species, such as poplar (Populus spp.), willow , and maple (Acer spp.)  at 29 Hz for 1 min. DNA was extracted using the DNeasy 96 Blood &Tissue Kit (Qiagen) following the manufacturer's instructions. The quality and quantity of DNA samples were assessed using the NanoDrop ND‐1000 spectrophotometer and Qubit 2.0 Fluorometer, respectively. For each sample, a total of 1μg or 2μg DNA was prepared for sequencing.2.2GBS libraries were prepared and sequenced at the Institut de Biologie Intégrative et des Systèmes  with the Ion Proton sequencer  following the procedure described in detail by Abed et al. . We modiThe Fast‐GBS pipeline v1.0 was adopted to process raw sequencing reads , and expected heterozygosity (eH) using the function “populations” in STACKS v2.3e , observed heterozygosity  and the geographical distance between populations using stat_cor in R.We assessed population structure among native ALB populations using three complementary multivariate ordination methods: principal component analysis (PCA)  using an infinite allele model in GenoDive 3.04  of 100 to estimate the individual ancestry coefficients. We also computed a maximum likelihood (ML) phylogeny using 1000 bootstrap replicates under the GTRGAMMA model in RAxML v8.2.9 .Contemporary movement of ALB was previously hypothesized by authors  resampling method in BayesAss 3.04, which estimates recent migration rates between populations as the proportion of migrants per generation . We used one long chain with four replicates for each run with 1,000,000 iterations and a burn‐in of 10,000. We compared the models using the log marginal likelihood  to generate the joint site frequency spectrum (SFS). We performed 100 independent parameter estimations to obtain the maximum composite likelihood of the joint SFS, each run with 100,000 iterations and 40 cycles of expectation conditional maximization (ECM)  and P2 (MspI) adaptors to the fragmented DNA and targeting large fragments (sizes selected for 350–550 bp) for 2 × 300 bp paired‐end sequencing on an Illumina Miseq platform (Cornell University's Biotechnology Resource Center). After an initial quality check using FastQC, raw Illumina reads were assembled into contigs (unique consensus sequences from multiple reads) using NGen  and default parameters. The resulting contigs were used as the reference file to re‐align all raw Illumina reads to assess coverage and the presence of microsatellite loci for each contig.To independently assess population structure with a different set of data, we genotyped 232 new ALB specimens collected independently from 16 locations in China Table  within tgenepop 1.1.7 , average gene diversity over loci (D), observed heterozygosity (oH), and expected heterozygosity (eH) under HWE were estimated in Arlequin 3.5  for each location and pairwise FST after correcting for sample size differences. Samples with fewer than five specimens were omitted from the estimation.Mean number of alleles per locus  present in both datasets. We performed the ‘mantel.rtest’ analysis on the two FST matrices with 9999 permutations.To assess the congruence between the two marker sets, we performed a Mantel test using a Monte‐Carlo method on the pairwise F2.5To identify markers for downstream diagnostic tool development, we wished to identify SNPs that could accurately assign individuals to their source populations. To do so, we used Mycorrhiza 0.0.28, a genotype assignment software that employs machine learning and phylogenetic networks to identify informative SNPs that can assign individuals to their source population  North versus South, as defined by our sPCA results; and (2) Six regional groups, as defined by our DAPC results Figure .33.1We obtained 524 million reads for 480 individuals  from GBS and identified 664,178 variants with the fastGBS pipeline. After variant filtering , and Pocheon   and Pocheon (KNA) were lower than for all Chinese populations  .Chinese ALB populations in the NW, S, and NE regions formed distinct clusters, while populations from the N region separated into three clusters, one that was unique, and the others were split among the NE and NW regions Figure . The sPC) Figure , which wth Table . DAPC anth Table  further th Table A for BICFST values for these populations , Changchun (CHC), and Shenyang (SHY) populations (NE region).Individual admixture estimates identified eight distinct populations Figure  based onns Table . We alsoThe ML phylogenetic tree Figure  revealed3.1.3We estimated contemporary gene flow within and among regions using our SNP dataset. The migration rates ranged from 0.004 ± 0.004 to 0.124 ± 0.060 migrants per generation (Nm), with an average across all populations estimate of 0.01 ± 0.0006 Nm Figure . We see −03 between populations . Through modeling by Fastsimcoal, the divergence between the North and the Northwest populations was traced back to 16,349 generations ago  was predicted within the hypothetical ancestral population , with a moderate reduction in eN following divergence of the NE , NW  and S  descendant populations. The population of ALB in the North exhibited surprisingly low eN (104 ± 4796)  Table .3.1.4fsthet . Of those 58 SNP outliers directly within the CDS, there were 31 synonymous variants and 26 missense variants, and one splice variant. We assigned functional annotations to each locus based on flanking sequence similarity with previously published results. Over half of the flanking sequences (n = 213) could not be characterized. For loci that were functionally similar to previously annotated regions, we identified loci associated with a range of molecular functions and biological processes (Table GLK) gene . The SNP under selection was annotated as a missense mutation under positive selection (FST = 0.335)  Table . We compa Figure , includia et al. . We plota et al. .3.2p < 0.01). Linkage disequilibrium was minimal among those 53 microsatellite loci, as only six out of all 1378 (0.44%) pairwise comparisons had significant false discovery rate‐adjusted p‐values. LD was also checked for within each population. There were no loci pairs found showing LD in every population, and the maximum number of populations that shared an LD loci pair was seven, which was less than half of the total number of populations.After correcting for sample size variation, allelic richness is similar across locations Table . A slighK = 4 to 6 (24 PCs retained), with K = 5 having the lowest Bayesian Information Criterion (BIC) score  merged with cluster 1. And if clustering was increased to K = 6, an additional cluster was formed by seven specimens from Zunyi (ZUY) that became separated from cluster 1. However, another five specimens collected in the same location remained with cluster 1. For the AMOVA with K = 5, most of the genetic variance  is found within locations, with 7.22% (p < 0.001) of the variance among locations within clusters, and 8.22% (p < 0.001) of the total variance among clusters.The Ward algorithm did not determine a single optimum number of genetic clusters and found approximately equal support for models from a range of e Figure C. When te Figure . The NE 3.3FST matrices generated from SNPs and microsatellites to assess congruence between our marker and specimen sets  based on 9999 replicates between the two datasets. We observed similar, although not identical, clustering in our two DAPC analyses on these distinct datasets , an enzyme that catalyzes an important rate‐limiting step in the utilization of glycerol at diapause termination  with a moderate genetic differentiation between six populations (FST = 0.083), the assignment accuracy reached 99.78% with 57 SNPs  accurate detection of regulated pests to enable an early, rapid response; (b) ability to trace interceptions back to the source and inform trade regulations and policies  and biotic , that shaped the complex genetic structure we observed in this pest. The patterns of genetic structure varied among regions and while large‐scale human‐assisted ALB population migration was limited, we were able to detect it in both datasets. Our ability to resolve this complex pattern of movement in the native range demonstrated the ability for our markers set to serve as a diagnostic tool to track invasive ALB populations outside their native range. Using our genome‐wide markers in a diagnostic framework will lead to the development of biosurveillance tools to aid rapid screening and pathway analyses of new ALB interceptions in support of plant protection agencies and regulatory bodies.The authors declare no conflict of interest.Figure S1‐S12Click here for additional data file.Tables S1‐S12Click here for additional data file.


Salicornia is a halophyte plant capable of being irrigated with seawater, which can be used as an alternative food. Given this, it is necessary to study the potentials of this plant’s morphological diversity in the natural environment. In this study, 33 wild populations of Salicornia were collected from different geographical areas around Urmia Lake during the flowering stage, and 55 morphological traits and 25 ISSR loci of the plant were analyzed. Based on morphological and molecular traits and the cluster analysis, Salicornia populations were divided into four and two groups, respectively.K=2 was calculated.Overall, the high percentage of polymorphic loci (65.69%), the average number of effective alleles per locus (1.63), and the Shannon data index (0.540) indicate that ISSR markers was used to identify genetic diversity. Molecular data cluster analysis divided the studied populations into two main groups, which included 12.12% and 87.88% of the populations, respectively. Based on the effective analysis of the population’s genetic structure and the precise classification of individuals into suitable sub-populations, the value of Salicornia have a considerable diversity in morphological traits. Furthermore, markers UBC823, B, A7, and K, as well as markers with the Shannon index, effective allele, and large heterozygosis values, are the most effective markers in comparison with other markers used in this study. The findings of this study will aid in parental selection studies for breeding programs of Salicornia in future.The research findings indicated that the populations of  Genetic diversity in crops and orchards is an issue long considered by plant breeders searching for new sources of germplasm to perform gene transfer, phylogenetic testing, and marker selection, among other things .Salicornia consists of approximately 15 genus and 68 species [Given the role of genetic diversity in advancing breeding programs and the importance of the local population, it is necessary to study the local population’s genetic diversity . A varie species . HoweverSalicornia iranica Akhani, an endemic species of Salicornia in Iran, grows in central Iran and is a diploid genus of Salicornia [Salicornia iranica [Besides the loss of leaves and morphological identification indices and the small amount of dry matter compared to wet tissue, the accurate identification of species is difficult . Salicorlicornia . The hablicornia . Accordi iranica .Salicornia is important as a medicinal plant, and given the fact that there are not adequate and comprehensive studies in different fields of production. The current survey was conducted in order to (1) estimate the morphological and molecular variation among 33 wild Salicornia populations, (2) search for genetic structure of Salicornia populations and identify the most effective ISSR markers, and (3) identify the relationships between morphological characteristics and ISSR markers to partition the genetic variation within and among populations, and provide basic information for conservation and breeding programs. In this study, 33 populations of Salicornia grown around Urmia Lake were collected, and to evaluate the morphological and genetically diversity between different populations, 55 different morphological traits and 25 ISSR markers were studied; also, for future genetic modification and parent plant selection, the results can be made available to the breeders.The Salicornia in full bloom and plant seeds were collected from different geographical areas in the lake’s vicinity . This software was also used for estimating the membership share matrix (Q). With this matrix, it is shown that each member to what extent fits to the clusters. Using the same software, the average stabilization index (FST) was calculated for potential subgroups. The approach proposed by Evanno et al. [K statistic breaking a function’s slope when there is the maximum probability for a hypothetical number.The combination of markers was used for obtaining population structure according to the data by the use of STRUCTURE software 2.3.4 (30) with 50,000 MCMC repetitions and 50,000 in-Burn time in Admixture mode in varying values of o et al.  was usedThe ANOVA and variation within-group were expressed as coefficient of variation for quantitative descriptors calculated for each group and the whole collection. Principal components analysis (PCA) was performed using XLSTAT 2018.1 statistical software. The first and second principal component axes scores were plotted to aid visualization of origin group differences and detect morphological variation in the collection.Population structure was studied using bands from all marker matrices. Using different algorithms, such as UPGMA, single linkage, and complete linkage, cluster analysis was performed. These algorithms were employed as zero (absence) and one (presence) scoring. The clusters were drawn in the present work using Mega software. Also other data were analyzed using the following software: NTSYSpc version 2.0.1.5, SAS 9.2 , SPSS (means), Mega , and PopGene .Salicornia, the non-fertile parts on the longest secondary branch (V29) (84.75%), the fertile parts on the longest secondary branch (V28) (81.49%), and the flowering plants in the first lateral branch (V34) (66.13%) had the highest diversity  obtained have eigenvalues greater than 2. Together, they accounted for about 67.28% of the total variance of its Fig. . The firits Fig.  and 5. PSalicornia populations were assigned to four groups  alleles ranged from 1.25 for UBC849 and 1.92 for in PB with an average 1.63 per locus. Maximum value of this statistic shows that alleles have identical frequency in this location, and this statistic’s minimum shows the rarity of other alleles and one allele’s high frequency in samples.In investigating allelic diversity, the highest observed heterozygosity was found by B marker with 0.477; however, the lowest observed heterozygosity was noticed by UBC849 marker with 0.199. Besides, the highest expected heterozygosity was observed at approximately 0.484 by B marker, and the lowest expected heterozygosity was observed at approximately 0.203 in the UBC849 marker. Examining Shannon index (I) values showed that the highest value for this index was in marker B with a 0.670 and the lowest value was in UBC849 marker as 0.351 , which was classified into two subgroups. The first one is composed of just the P13 population. Also, this population was approximately different from other ones  in the cultivars under study. The group was specified  and 5 populations in the second group (green), with 2 populations had a complex structure  is a common and appropriate measure for genetic differentiation among groups and populations. When the FST is higher, a better allele differentiation is obtained, with a higher allele stabilization rate. Potential subgroups in s Tables  and 5 inure Fig. .Fig. 6PoSalicornia [Salicornia’s two species in Iran . In S. biglawi species, raising the salinity of irrigation water to 45 dS/m reduces the height and dry weight of the plant. In Persica species, increasing the irrigation water salinity had no effect on plant height but significantly decreased the dry weight [The results showed that there was a significant difference between the studied populations in terms of traits in the question. Based on the mean of traits measured in the population, traits with a high percentage of variance had a wide range of trait quantities and offered a more extensive choice for traits. This difference is due to the impact of both genetic and environmental factors. Studies have shown that fluctuations in soil and water salinity lead to physiological and phenotypic changes in the plant. Also, high plant density in a population restricts the number of branches and glaciers formed in the plant . Self-policornia . The phelicornia . Togethey weight .Salicornia pusilla, researchers have found that the plant seeds remain attached to the inflorescence after ripening, and the spikes are trapped by a separating layer of the plant isolated in the water that may keep moving with the flow of water up to 3 months. They may even germinate but do not grow until the seeds are deposited in sediments [S. bigelovii populations in the field and divided the cluster analysis of studied populations into four groups [Salicornia ramosissima populations in central Germany showed that it is consistent with geographical distribution [Salsola manifested a significant difference in this plant and the environmental conditions of the plant, suggesting that disparity in salinity, nutrition, pH, and soil moisture changes the vegetative type of plants [Salicornia populations were divided into three separate groups: the first component (46.11%), the second component (41.35%), and the overall component (87.46%) of the entire diversity. The study of the morphological diversity patterns of 52 Salicornia populations in 31 regions of Northern Europe using 28 morphological traits demonstrated diversity in the studied populations. The main components’ analysis revealed the first five components accounted for 79.8% of the total diversity. In the first component, characteristic spikes included the length of fertile segment and length of the spike  [The cluster analysis results showed that Fig.  the clusediments . This fer groups . Contrarribution . A revief plants . The resf plants . Based oversity) . The finSalicornia’s population diversity. The degree of morphological differentials is significantly noticeable in different populations from four groups.Though the association between regional diversity was not that evident, a close look at the scatter plot revealed some regional adaptation level was observed. Such regional variability could be due to geographic isolation and microclimatic differences between regions. Factors such as plant population isolation, adaptation to the environment due to declining lake water levels, and strong self-pollination within the plant population may contribute to The research findings indicated that markers UBC823, B, A7, and K, and with the Shannon index, effective allele, and large heterozygosity values, are markers with the highest effectiveness compared to other markers utilized, and they are used better than other compounds in genetic distance.Salicornia herbacea in South Korea, where 6 ISSR markers were used, 39 polymorphic bands were obtained out of 49 bands, with an average of the effective allele for each gene locus as 1.22. The mean genetic index was 0.249 and the mean Shannon index was 0.382. These researchers mentioned that for achieving high diversity in populations Salicornia, a wider research scope is required to be chosen [As stated by Dirlewanger et al. , there ie chosen . Using Ie chosen .S. Iranica [These populations were separately gathered because of varying morphological types compared to other populations. Also, this difference is shown in the results. The second subgroup included P26 and P1 populations, with different appearances compared to other populations. They had a taller plant than average, particularly the taller plant was observed in P26 population among all populations. Moreover, long glazes were observed in these two populations. Additionally, it shows all botanical properties of Salicornia, 36 samples of Salicornia were collected by Heydarian [Salicornia populations were evaluated by Mohammadi [S. iranica are presented, all in a group. In this research, S. iranica species were separated from S. persica species using the AFLP marker, and they were placed in a subgroup. Additionally, the populations gathered from each area were put in a different subgroup. The genetic diversity in 11 Salicornia brachiata populations was evaluated in India using 15 ISSR and 15 RAPD primers [In earlier Iranian research works on eydarian  from difohammadi , which w primers . The invThe resulting bar plot showed that when the membership percentage to a cluster for a genotype is higher than or equal to 0.7, the genotype is allocated to that cluster, while if the percentage is below it, it is considered as a mixed genotype (hybrid) . GeneralSalicornia populations growing around Urmia Lake had considerable diversity in morphological and ISSR characteristics. The incompatibility of population clustering with their geographical distribution may be due to different populations’ exact seed origins. The populations under the genetic study were divided into two major groups based on marker data, including 12.12% and 87.88%. The K value was obtained as two according to the practical analysis of the population’s genetic structure and the accurate individuals’ classification to suitable sub-populations. The populations under study were classified into two groups because Salicornia is a self-pollinated plant. Differences in morphological and genetic grouping may be due to the environment’s effect on morphological traits, while in genetic traits, the difference between the populations may be due to the populations’ isolation due to the lowering of the lake water, and the plant was directed towards self-breeding. Combining morphological and ISSR data may be more effective for defining genetic variation and genetic diversity within the Salicornia population.This study showed that


The two herds were generally similar based on a number of genetic parameters. Overall, the study implied reduced genetic diversity in the two herds, calling for corrective measures to maintain the diversity of the South African Nguni cattle.Knowledge of linkage disequilibrium (LD), haplotypes blocks, and selective sweeps is important for effective application of genomics in breed characterization, improvement, and conservation, amongst other uses. The South African Nguni cattle breed is a Sanga breed that is well known for its ability to adapt to various environmental conditions such as harsh pedoclimatic and socio-economic conditions which exist in semiarid areas. Nguni cattle are characterized by many eco-types and research populations have been established in an effort to conserve the diversity within the breed by sampling in animals from different ecotypes into the herds. In this study, we calculated autosomal linkage disequilibrium, haplotype block structure, and screened for selection sweeps in two Nguni conservation herds of Bartlow Combine (r2) estimates were 0.413 ± 0.219 for Bartlow Combine and 0.402 ± 0.209 for Kokstad. Genome-wide average LD (r2) decreased with increasing genetic marker distance for both populations from an average of 0.76 ± 0.28 and 0.77 ± 0.27 at 0–1 kb bin to 0.31 ± 0.13 and 0.32 ± 0.13 at 900–1000 kb bin in Bartlow Combine and Kokstad populations, respectively. Variation in LD levels across autosomes was observed in both populations. The results showed higher levels of LD than previously reported in Nguni field populations and other South African breeds, especially at shorter marker distances of less than 20 kb. A total number of 77,305 and 66,237 haplotype blocks covering a total of 1570.09 Mb (61.99% genome coverage) and 1367.42 Mb (53.96% genome coverage) were detected in Bartlow Combine and Kokstad populations, respectively. A total of 18,449 haploblocks were shared between the two populations while 58,856 and 47,788 haploblocks were unique to Bartlow Combine and Kokstad populations, respectively. Effective population size (Ne) results demonstrated a rapid decrease in Ne across generations for both Bartlow Combine and Kokstad conservation herds. Two complementary methods, integrated haplotype score (iHS) and Extend Haplotype Homozygosity Test (XP-EHH), were implemented in this study to detect the selection signatures in the two herds. A total of 553 and 166 selected regions were identified in Bartlow Combine and Kokstad populations, respectively. DAVID and GO terms analysis of the regions under selection reported genes/QTLs associated with fertility, carcass weight, coat colour, immune response, and eye area pigmentation. Some genes, such as HCAR1, GNAI1, PIK3R3, WNT3, RAB5A, BOLA-N (Class IB MHC Antigen QA-2-Related), BOLA (Class IB MHC Antigen QA-2-Related), and Rab-8B, etc., were found in regions under selection in this study. Overall, the study implied reduced genetic diversity in the two herds calling for corrective measures to maintain the diversity of the South African Nguni cattle. This study presented a comprehensive analysis of the genomic architecture of South African Nguni cattle populations, providing essential genetic information of utility in the management of conservation flocks.The Nguni cattle of South Africa are a Sanga breed, characterized by many eco-types and research populations that have been established in an effort to conserve the diversity within the breed. The aim of this study was to investigate the overall genetic diversity as well as similarities and differences within and between two conservation herds of the South African Nguni Cattle. Mean LD ( The Nguni (Sanga type) cattle breed is one of the major indigenous cattle breeds that is hardy and is uniquely adapted to different ecological regions of South Africa . MigratiIndigenous breeds such as the Nguni are not well characterized or described and are rarely subjected to structured breeding efforts to improve their performance . More imThe steady deterioration of the Nguni gene pool will ultimately result in the loss of vital genes that have allowed the Nguni to thrive and produce for generations under the country’s extreme environmental conditions . In recee), and signatures of selection are key genomic parameters that can be used to assess genetic diversity, regions under positive selection, and to determine whether the conservation populations are viable or at another risk of extinction. Haplotype block structures are characterized as areas with a high marker–marker LD and a low haplotype diversity separated by short regions of very low LD , where Φ(x) represents the Gaussian cumulative distribution function  and piHS is the two-sided p-value associated with the neutral hypothesis . The maximum allowed gap between two SNPs was set to 500 Kb, and 1-Mb sliding windows that partially overlapped 10 kb with adjacent windows were set. Candidate regions of positive selection were defined as genomic regions having an unusual clustering of SNPs with high iHS statistics (≥3). This was estimated as the proportion of SNPs surpassing the significance threshold of log10  = 3, equivalent to a p-value of 0.001. Candidate regions of positive selection were identified as windows with the top 1% density of high iHS SNPs.Windows with less than 10 SNPs were removed. To determine the p-value).A pairwise comparison was performed for Bartlow Combine and Kokstad Nguni cattle populations to identify genomic regions under increasing differentiation using XP-EHH (cross-population extended haplotype homozygosity). To detect alleles with higher frequency to the point of fixation or near-fixation in the Bartlow Combine population compared to the Kokstad Nguni cattle population, the XP-EHH scores were computed using the rehh R package v2.0.4 with default parameters . FastPhaGenes overlapping the genomic region under selection were determined using the ARS-UCD1.2/bosTau9 bovine reference genome  and the Both the unique and common genes were functionally annotated by performing Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis  and GeneA total of 643,275, 650,317, and 650,430 SNPs remained after quality control for the Bartlow Combine, Kokstad, and overall populations, respectively, and were utilized for downstream analysis, as illustrated in The distribution of MAF for each population is shown in PC1 and PC2 explained 7.12% and 4.93% of the total genetic variation, respectively, and reported three genetic clusters  decreased with increasing genetic distance between markers for all populations. The differences in r2 values observed in Bartlow Combine, Kokstad, and overall Nguni cattle populations, across all genetic distances, were very small, as illustrated in r2 values for Bartlow Combine (0.76 ± 0.28), Kokstad (0.77 ± 0.27), and overall population (0.75 ± 0.28) were observed at a short distance (0–1 kb). Across populations, there was a lower LD that progressively declined with increasing genomic distance, especially for distances higher than 10 kb. The most rapid decline was observed over the first 100 kb. However, there were very small differences in LD decay between the Bartlow Combine, Kokstad, and overall populations.Genome-wide average LD  showed the smallest coverage, while Chr 1 (66.88%) and Chr 6 (59.63%) showed the greatest coverage in Kokstad and Bartlow Combine Nguni cattle populations, respectively The number of blocks that were above 500 kb was almost the same in all three populations . About 5e was computed based on linkage disequilibrium between SNPs, with sample size, mutation, and recombination rate being taken into account. Each line depicts the trend in effective population size across generations. The result showed that all populations had experienced a rapid decline, including the most recent generation  to 55, 54, and 56 (50th generation ago) in Bartlow Combine, Kokstad, and overall populations, respectively. The estimated Ne in the three populations revealed that the herd formation was the same within the last 100 generations.In the fifth generation (from the present), NThe most extreme iHS peaks were on BTA 1, 4, and 8 for the Bartlow Combine Nguni cattle population and chromosomes 1, 4, 8, 17, and 23 for the Kokstad population. The highest |iHS| value were 6.41 (SNP: BovineHD0400008236) and 4.72 (SNP: BovineHD0400032209) for Bartlow Combine and Kokstad populations, respectively. The results for the overall population are presented in CD14, WDR55, PCDHA3, RF00026, etc.,  and Kokstad  populations. The two blocks identified in Bartlow Combine and Kokstad populations overlaps the genes such as 6, etc., . A total6, etc., . A total6, etc., .Shared and unique genes within/between the two populations and signatures of selection methods are represented in Staphylococcus aureus infection, lipid and atherosclerosis, vascular smooth muscle contraction, Salmonella infection, and melanogenesis. The selected regions overlapped with QTLs associated with productive, functional (including resistance to diseases), and morphological traits  unique to Kokstat, (ii) unique to Bartlow Combine, (iii) common between the two populations, and (iv) on those from XP-EHH. The candidate genes that were detected in the Bartlow Combine population encompassed a wide spectrum of molecular functions, biological processes, cellular components, and pathways, and were enriched in 183 gene ontology (GO) and 61 KEGG pathways, as shown in l traits .Wnt signaling pathway, and the defense response to Gram-negative bacterium  in both Bartlow Combine and Kokstad Nguni populations revealed 49 GO terms and 2 KEGG pathways. The identified GO terms were involved in processes such as the maintenance of gastrointestinal epithelium, the defense response to Gram-negative bacterium, and antigen processing and presentation .MHC class II, the defense response to bacterium, an inflammatory response, the detection of chemical stimulus involved in the sensory perception of bitter taste, the epoxygenase P450 pathway, antimicrobial humoral immune response mediated by antimicrobial peptide, an immune response, defense response, and adaptive immune response, the regulation of MAPK cascade, the activation of MAPK activity, and DNA methylation GO terms.The annotation of genes identified by the XP-EHH revealed 137 GO terms and 37 KEGG pathways . This seMTX2, U6, THSD7A, TMEM106B, DTNB, DNMT3A, bta-mir-1301, POMC, EFR3B, DNAJC2, ZNF280A, YWHAH, SLC5A1, SLC5A4, ZNF280B, and ADCY3 for carcass and body weight, ABCA12, SNORA70, ATIC, FN1, and bta-mir-2285l for reproduction, ZNF830, CCT6B, SNORA70, THSD7A, TMEM106B, and TMEM132E for residual feed intake, and RASL11B, SCFD2, GPAT4, bta-mir-486, 5S_rRNA, GOLGA7, SFRP1, NKX6-3, and GINS4 for milk production.A total of 907 bovine QTLs overlaps  were obsConservation of animal genetic resources focuses not only on endangered breeds but also on those that are underutilized. Locally adapted breeds are constantly in danger of becoming extinct, especially when local populations favor imported breeds. The Bartlow Combine and Kokstad Nguni cattle conservation herds were established in an attempt to conserve the eroding Nguni genetic resources in South Africa. The two herds and other conservation and research population are often used for research purposes as representatives of the Nguni breed. As in any other species , conservThis study characterized the pattern of LD, haplotype block structures, effective population sizes, and the genomic signatures of selection in the Bartlow Combine and Kokstad Nguni cattle conservation herds. As both were established from the same breed, the study hypothesized that the two herds will be genetically similar and present the same genomic architectures. Differences between the two herds would imply the presence of unique genetic diversity or a possibility of different forces of evolution acting upon these two conservation herds.Minor allele frequency (MAF) is commonly utilized in population genetic studies because it allows researchers to distinguish between common and uncommon variations. The MAF values were similar between the Bartlow Combine cattle, Kokstad Nguni cattle, and the overall population . The MAFThe Nguni MAF results from the study of Zwane et al.  also repNatural selection, genetic drift, and gene flow affect allele frequencies , and theBos indicus and Bos taurus cattle using medium- and high-density SNP chips. Karimi et al. [The occurrence of the highest number of SNPs in the MAF category 0.1–0.2 is a common observation in indicine breeds, and opposite tendency is observed in the taurine breeds, where most of the SNPs are located in the last two categories ,54. Simii et al. , howeverLD is a fundamental approach for identifying the genetic structure of economically important traits in livestock species . Karimi e in local breeds and established herds.LD estimates obtained in the Bartlow Combine and Kokstad research stations are therefore similar though slightly higher than those reported by Makina et al. , who stuA small finite population size is normally reflected by high levels of linkage disequilibrium . SelectiThe LD decreased with increasing physical distance between markers in both Nguni herds, as well as in the overall population . SimilarIn our study, the highest LD values were observed on chromosome 7 in the Bartlow Combine population and in chromosomes 7 and 8 in the Kokstad population, which might imply the presence of QTLs with large effects that have been subjected to intense selection and generate high LD with neighbouring markers in the associated chromosomes. Chromosomes 7 and 8 harbour QTLs associated with milk production, meat traits, and disease or nematode resistance ,62,63, wOur study went on to examine haplotype diversity as a measure of genetic diversity in the Bartlow Combine and Kokstad cattle and observed similar haplotype frequency (0.23) in both herds. The slightly higher number of haplotypes and haplotype blocks in Bartlow Combine than the Kokstad population could be an effect of the differences in sample sizes . HaploblIn the present study, the largest haploblocks were found on chromosome 1  in Bartlow Combine and Kokstad populations, respectively. The longest haplotype blocks were found in chromosome 7  in the Bartlow Combine and Kokstad populations, respectively. Wang et al.  also fouThe length of haplotype blocks in the Bartlow Combine and Kokstad populations were longer than those of the Nguni populations studied by Wang et al.  and MakiThe generational transfer of genetic resources between breeds is possible thanks to haplotype sharing . The shae observed in the two conservation herds might be related to an increase in inbreeding levels and a reduction in genetic variety, both of which are common in animals with small, finite populations [e (~2500) in a Nguni field cattle population compared to the present study. Continuous genetic erosion and decline in these populations increases the risk of losing some economically important traits of the Nguni cattle breed. Effective population sizes were the same in both populations: 55 in the Bartlow Combine population and 54 in the Kokstad population. The Ne observed in both populations corresponded to similar r2 at 1000 kb (0.31 and 0.32) in Bartlow Combine and Kokstad populations, respectively. Overall, the LD, LD Decay, Haplotype, and Ne results are suggestive of the fact that the two conservation herds are genetically similar with minimum divergence between them and from the field populations analysed in previous studies. The results also demonstrated the impact of movement into conservation herds, which resulted in slightly lower effective population sizes and higher LD and haplotype diversity than would be observed in field populations.The effective population sizes obtained for both the Bartlow Combine and Kokstad Nguni cattle populations, as well as for the overall population, in this study, were in agreement with those reported by de Roos et al. . The deculations . When thulations  observedThe next set of analysis investigated signatures of selection in the genomes of the two conservation herds. Based on the PCA results, genetic cluster 2, which consisted of animals from both populations, was excluded from this analysis. Both the iHS and XP-EHH plots indicated that common selective pressure on both populations, probably due to a common founding breed and similar production goals, is contrasted with selection toward different genomic regions, most likely due to differences in habitats, genetic drift, effective population size, inbreeding, and recombination occurring between the two herds.WNT3, RAB5A, ASIP, WINT9A, WLS, WNT9B, WNT11, MAPK1, WWTR1, G3BP, PIK3R3, FSHB, EDNRA, ADCY4, and ADCYAP1R1. The presence of coat colour-related genes in both populations is in line with the common perception that coat colour is a breed-defining trait under selection in Nguni cattle [HCAR1, GNAI1, PIK3R3, FSHB, EDNRA, ADCY4, ADCYAP1R1, and HTR1E. According to Bang and Zippin [The melanogenesis pathway was enriched in both Bartlow Combine and Kokstad populations and involved genes such as d Zippin , cAMP isd Zippin . SignifiBOLA-N (Class IB MHC Antigen QA-2-Related), BOLA (Class IB MHC Antigen QA-2-Related), and Rab-8B) are potential targets of natural selection. Exon 2 of the BoLA-DRB3 gene is extremely important and is involved in the T-cell response to pathogens [MHC is a genetically diverse region in natural populations that is involved in the production of glycoproteins that adhere to foreign substances and redirect them to important immune system components [p < 0.05) mean egg counts (MEC) for S. papillosus than local crossbreds.Other genomic regions under selection in both populations included those responsible for immune response mechanisms. Nguni cattle are known to be tolerant to different endemic parasitic diseases , therefoathogens . The MHCmponents . Marufu mponents  conducteSalmonella, Escherichia coli, Mycobacterium avium subspecies paratuberculosis and Cryptosporidium parvum, and it is crucial to understand how these pathogens interact with the bovine intestinal epithelium [Another enriched Go-term was the maintenance of gastrointestinal epithelium, which is defined as the protection of epithelial surfaces of the gastrointestinal tract from proteolytic and caustic digestive agents. Cattle are natural reservoirs for a range of important enteric pathogens, including ithelium . Two KEGithelium , salivarFurthermore, a number of QTLs relating to milk production, meat, and carcass traits and pigmentation overlapped with genes in region under selection in both populations. These results were expected because the Nguni is being selected for milk production, meat production, coat colour, as well as tick or disease resistance. The presence of these GO-terms only in genes unique to either the Bartlow or Kokstad population might be suggestive of different natural and artificial selection pressures between the two herds. Such differences could be due to nutrition, management, and environmental and climatic factors .® BovineHD Genotyping BeadChip. Overall, similarities were observed between the two herds and also with the field populations based on results from previous studies. The slightly high levels of LD at short distances reported in this study might be due to the fact that Bartlow Combine and Kokstad are conservation research herds with smaller and more finite population sizes, whilst the other studies characterized field populations. The study provided evidence of a rapid decline in the effective population size in both Bartlow Combine and Kokstad conservation herds.This study provided a comprehensive analysis of the genomic architecture of Nguni cattle conservation herds using the IlluminaSeveral candidate genomic regions showing a positive selection signature were identified using two haplotype-based methods. Our analyses revealed important genes related to coat colour, adaptation, immune response, and production traits in both studied research populations. The use of two different statistical approaches (iHS and XP-EHH) facilitated the wider spectrum of the detection of selection signatures within and between Bartlow Combine and Kokstad Nguni cattle populations. The findings can provide valuable knowledge for further functional genomic studies, GWAS, and genomic selection, implementing breeding schemes and conservation programs.


The Analysis of genomic data is an important resource for the effective management of small and endangered populations. The aim of this work was to study the genomic structure of a local goat named Mascaruna. Overall, the results indicate moderate genetic variability and a defined population structure and represent a starting point for the creation of monitoring and conservation plans.Italy contains a large number of local goat populations, some of which do not have a recognized genetic structure. The “Mascaruna” is a goat population reared for milk production in Sicily. In this study, a total of 72 individuals were genotyped with the Illumina Goat_IGGC_65K_v2 BeadChip with the aim to characterize the genetic diversity, population structure and relatedness with another 31 Italian goat populations. The results displayed a moderate level of genetic variability for Mascaruna, in concordance with the estimated values for Italian goats. Runs of homozygosity islands are linked to genes involved in milk production, immune response and local adaptation. Population structure analyses separated Mascaruna from the other goat populations, indicating a clear genetic differentiation. Although they are not conclusive, our current results represent a starting point for the creation of monitoring and conservation plans. Additional analyses and a wider sampling would contribute to refine and validate these results. Finally, our study describing the diversity and structure of Mascaruna confirms the usefulness of applied genomic analyses as valid tools for the study of the local uncharacterized genetic resources. Capra hircus) are economically important domestic animals reared for milk, meat and fiber production. Italy is the European country with the highest number of local goat populations and, therefore, a precious reservoir of genetic diversity [Goats , restricted gene flow and higher inbreeding values compared to what is expected from outbred individuals . TherefoThe findings from genomic data have become an invaluable resource for effective management of breeding programs in small and endangered populations . The avaIn this study, we used genomic tools to genotype the Mascaruna goat with the aim to characterize the genetic diversity, population structure and relationships with other Italian goat populations and to widen the picture of the genome-wide diversity of Italian caprine species.A total of 72 Mascaruna goat DNA samples  were genotyped. DNA was extracted from blood using the commercial Illustra blood genomic Prep Mini Spin kit . Animals were chosen on the basis of their phenotypic profile  and the information provided by farmers in order to collect unrelated individuals.All animals were genotyped with the Illumina Goat_IGGC_65K_v2 BeadChip containing 59,727 SNPs . The raw data of Mascaruna goat were merged with the genotypic data of Italian Goat Consortium2 (IGC2)  as descrThe genomic coordinates for each marker were obtained using the assembled goat genome . SNPs without position or assigned to the X chromosome were discarded. The software PLINK v. 1.9 [O) and expected (HE) heterozygosities, inbreeding coefficient (FIS) and the minor allele frequencies (MAF) in order to compare the results with those reported in the literature for all Italian goat populations [ROH) for each animal, the mean number of ROH per individual, the mean total length of ROH and the mean length of ROH per individual were estimated.After applying the above quality filters, all the analyses within the Mascaruna goat population were conducted using 67 individuals and 50,291 SNPs. PLINK v. 1.9  was usedulations . Moreoveulations  by usingulations  and follulations . The inbhttps://www.ncbi.nlm.nih.gov/genome/gdv?org=capra-hircus&group=bovidae accessed on 4 July 2022) and a precise literature research.Highly homozygous genomic regions (ROH islands) were also identified. The percentage of SNPs present in ROH was calculated based on their frequency across individuals . The topIn order to understand the genetic relationships and the population structure, the datasets were also filtered to remove SNPs in high LD (r2 > 0.2) by using the --indep-pairwise (50 10 0.2) function in PLINK v. 1.9 , generatST. All these analyses were carried out both on 32POP and 8POP datasets. Patterns of ancestry and admixture were examined by the model-based clustering algorithm implemented in the ADMIXTURE software v1.3.0 [membercoef.circos function in the R package BITE [The genetic relationships among populations were estimated using an identity-by-state (IBS) matrix of genetic distances calculated by PLINK v. 1.9  and plote v1.3.0 , by applage BITE . In ordeage BITE . For thiage BITE .Genetic diversity indices, estimated using different approaches, were adopted to identify the levels of genetic variability in Mascaruna goat. Descriptive statistics are reported in In total, 2381 ROHs were identified, ranging from 4 to 101 ROH per individual. The average number of ROH per animal was 35.5, with an average length of 4.85 Mb. The majority of ROH segments (79.25%) were shorter than 8 Mb in length, while 166 segments (~7%) were longer than 16 Mb. The relationship between total number of ROH and the total genomic length for each animal showed that most of the individuals (64%) led from 4 to 40 ROH with a total length <200 Mb. There were animals with a large number of ROH (above 70), with more than 500 Mb of total length of genome in ROH .The top 0.999 SNPs of the percentile distribution were selected, and adjacent SNPs over this threshold were merged into genomic regions corresponding to ROH islands in Mascaruna . In the Capra hircus chromosome (CHI) 2 and CHI6, respectively, and two on CHI12. These regions ranged from 580 kb (CHI2) to 1.83 Mb (CHI6). We identified a total of 18 known genes together with uncharacterized loci (LOC). The region on CHI6 contained, among the others, 13 SNPs with the highest H value (45%) (ue (45%) .To examine the genetic relationships within and between populations, we used an MDS plot of the pairwise IBS distances (32POP). The first and second dimensions explained 4.29% and 2.65% of the observed variation, respectively . The resThe MDS plot was also created only for the southern goat populations (8POP) . The resST value among all 32 populations ranged from 0.001 (Messinese vs. Argentata dell’Etna) to 0.163 . Moderate genetic differentiation was observed between Mascaruna and several Italian goat populations. Genetic differentiation ranged from 0.037 (Mascaruna vs. Argentata dell’Etna) to 0.12   to 0.086 (Mascaruna vs. Girgentana) (The pairwise F breeds) , 32POP. gentana) , 8POP.To provide additional indications regarding the relationships and the origin of Mascaruna, we depicted a neighbor-net graph based on Reynolds genetic distances , 32POP.The graph showed a clear clusterization among populations that originated from the same geographic area, confirming a north-to-south genetic pattern from right to left. Mascaruna branched with Girgentana, Aspromontana, Messinese and Argentata dell’Etna, grouped in one cluster in which Girgentana and Aspromontana showed a closer relationship. A branch with moderate length was observed for Mascaruna, whereas the longest one was found for Orobica, Girgentana and Vallesana. The neighbor-net analysis using only the southern populations , 8POP coThe results of the admixture analysis agreed with the finding outlined above . We repooptM function supported only one migration event ; the graph shows a clear distribution of clusters according to the geographic origin of goat populations. However, the statistic calculated over five iterations for m from 0 to 10 indicated, at m9, a gene flow event between the base of the branch, including the Maltese populations and Mascaruna goat  and the genotypic data of Bezoar as outgroup . The optuna goat .The genetic diversity of autochthonous livestock populations is an important resource for food security and sustainable rural development. Moreover, indigenous populations are a valuable resource to preserve for their adaptation to harsh climatic conditions and resistance or tolerance to infection diseases common in their natural habitat . HoweverIS, In this study, we performed the first genome-wide assessment of the genetic diversity and population structure of the local Mascaruna goat. The genetic diversity indices  previously reported within a QTL related to milk production traits in cattle [LCORL, which was shown to regulate body size in goats [FAM184B, and NCAPG [NBEA, a gene involved in regulating body temperature in cattle with heat stress [DCLK1, is reported as significantly associated with climatic variables in a landscape genomics study on Italian goat breeds [Currently, the method based on ROH is considered one of the most powerful approaches to estimate genomic inbreeding . Despitee system . On CHI6n cattle  and PPM1 in milk . Within n cattle ,38. The in goats , FAM184Bnd NCAPG ,41, assond NCAPG . Moreovend NCAPG ,31, and nd NCAPG  and withnd NCAPG . Finallyt stress . This geST) among populations from the same geographic area, which basically confirms this genetic structuring. Previously, a similar geographical pattern was described for Italian sheep [Regarding population structure analyses, the results distinguished Mascaruna from other goat populations, indicating clear genetic differences compared with other Italian goats. The presence of a clear north–south geographical distribution of the genetic diversity  was highan sheep  and cattan sheep . The Admm1). Therefore, it is likely that this population experienced reproductive isolation and reduced gene flow and, thus, acquired a genetic identity.In general, the MDS separated Mascaruna from the other goat populations and, in particular, from northern and central Italian populations. Mascaruna goat formed a non-overlapping cluster and was clearly separated from the other populations. On the other hand, there were animals from officially recognized breeds that grouped together  and showTo explore in detail the relationship with the other goat populations of southern Italy, a further analysis was carried out considering only Mascaruna and these populations. The results confirmed the differentiation between Mascaruna and southern populations, which could be hypothesized as its potential ancestors, as above reported. Compared with these populations, the Mascaruna goats are relatively more dispersed within their cluster in MDS, which is typical of population that show higher genetic diversity or admixture with other breeds . In geneA breed is a breed if enough people say it is”. Historical information provided by farmers indicated that the Mascaruna was reared in Sicily since the Second World War, and is widely known among local goat farmers, who consider it an official breed. Several studies reported a weak structuring of goat populations and showed the perspective that many so called breeds are actually landraces at best and panmixia predominates in these genetic reservoirs [Recently, Dadousis et al. , taking servoirs ,53,54. Lservoirs  suggesteservoirs . TherefoIn this study, we reported the first genome-wide results on the genetic diversity and population structure of the local Mascaruna goat. The results indicate the existence of a defined genetic background to safeguard. For conservation in farms, breeders need to be financially supported by local and international authorities , and thi


Fagus orientalis), aiming to assess the potential risks involved due to possible future distribution changes in the species. Using nuclear microsatellites, we analyze 32 natural populations from the Georgia and Azerbaijan (South Caucasus). We found that the species colonization history is the most important driver of the genetic pattern. The detected west–east gradient of genetic differentiation corresponds strictly to the Colchis and Hyrcanian glacial refugia. A significant signal of associations to environmental variables suggests that the distinct genetic composition of the Azerbaijan and Hyrcanian stands might also be structured by the local climate. Oriental beech retains an overall high diversity; however, in the context of projected habitat loss, its genetic resources might be greatly impoverished. The most affected are the Azerbaijan and Hyrcanian populations, for which the detected genetic impoverishment may enhance their vulnerability to environmental change. Given the adaptive potential of range‐edge populations, the loss of these populations may ultimately affect the specie's adaptation, and thus the stability and resilience of forest ecosystems in the Caucasus ecoregion. Our study is the first approximation of the potential risks involved, inducing far‐reaching conclusions about the need of maintaining the genetic resources of Oriental beech for a species' capacity to cope with environmental change.Predicting species‐level effects of climatic changes requires unraveling the factors affecting the spatial genetic composition. However, disentangling the relative contribution of historical and contemporary drivers is challenging. By applying landscape genetics and species distribution modeling, we investigated processes that shaped the neutral genetic structure of Oriental beech ( We applied landscape genetics and ecological niche modeling, aiming at disentangling the historical and contemporary processes underlying the neutral genetic structure of Oriental beech across the South Caucasus. Our study is the first approximation of the potential risks involved, inducing far‐reaching conclusions about the need of maintaining the genetic resources of Oriental beech for a species' capacity to cope with environmental change. SpecifiFagus sylvatica , observed (HO), and expected (HE) heterozygosity using INEST whereas the number of private alleles (PA) was computed using GenAlEx  based on the rarefaction method was obtained using FSTAT v.2.9.3  among the main population demes  was tested in FSTAT with 104 permutations.To assess how diversity varied within and among populations, we calculated the mean number of alleles , we used the individual inbreeding model (IIM) implemented in INEST. The calculations were run with 5 × 105 MCMC iterations with every 200th updated and a burn‐in of 5 × 104. To assess the factors affecting the homozygosity level in populations, the competition of the full model  with the random model  was applied based on the Deviance Information Criterion (DIC).To estimate the inbreeding coefficient including “null alleles” correction (FST) with the Excluding Null Alleles (ENA) correction implemented in FreeNA  assuming a proportion of one‐step mutations (ps) of 0.22 and a mean size of multi‐step mutations (Δg) of 3.1. The significance of the deficiency in the M‐ratio was tested using the Wilcoxon signed‐rank test.The M‐ratio method , ranging from one to 33 with a burn‐in period of 105 steps followed by 2 × 105 MCMC iterations. Following Cullingham et al. ; Pritchard et al., K   given to genetic clusters is >0.5 to exclude the spurious cluster, which constitutes a doubtful biological grouping. However, being aware of the complexity of the K‐selection procedures, we included all clustering results that warrant biogeographic interpretation  to calculate the three landscape metrics: current and past climatic suitability, and distance from the climatically stable area in the LGM. As our point was also to predict the possible changes in the species distribution in future, we constructed the theoretical distribution of the species under different future climate scenarios.The species occurrence acquisition is detailed in Appendix vif function implemented in the usdm R package  values of the receiving operator curve (ROC) as a threshold‐independent evaluation metric , distance from LGM refugium in Colchis (DistLGM), genetic admixture (GADMIX), latitude and longitude, while AR and HE were used as response variables.To detect the drivers governing the spatial distribution of genetic diversity, we employed generalized linear models (GLMs) to test the hypothesis that past climate may explain the observed pattern , and Akaike weights (wi) calculated using the function compareGLM in rcompanion R package , geography (geo.), recent migration (mig.), demographic history (anc.), and topographic heterogeneity (top.) in explaining the detected genetic differentiation  with ENA correction as the response variable and a set of explanatory/conditioning variables described below. The analyses were run using the function capscale in vegan R package  were performed to unravel the relative contribution of climate  were retained into the final dbRDA models.To explore the association of genetic composition with local climate within the isolation by environment (IBE) model, we first selected potentially relevant climatic variables to avoid overfitting and collinearity in the subsequent dbRDAs. To do this, we applied the forward selection procedure using the geo.) estimated from a raster layer depicting a “flat” landscape using QGIS. The current migration matrix was estimated using the divMigrate method , we calculated a matrix of the Euclidean geographical distances among sampled populations (top.) on genetic connectivity. Circuitscape 4.0  model was applied to test the effect of topographic heterogeneity  obtained from the STRUCTURE analysis for K = 3 (see Results), assuming that the genetic ancestry (anc.) was an appropriate proxy of the postglacial colonization history of the species. We conducted a principal component analysis (PCA) on the set of Q‐value and retained the first two PCs obtained using the prcomp R function . We used the ancestry coefficient  were transformed into vectors using the principal coordinates of neighbor matrices  was very similar across all populations, reaching an average of 0.687  than in other regions. The populations from the Lesser Caucasus were characterized by having the highest gene diversity (HE = 0.706). Allelic richness (AR) ranged from 5.366 (HZ_02) to 7.936 (LC_05) with a mean on 8.189 and was again significantly lower in the Hyrcanian populations  was detected in all populations except for LC_01 and AZ_07. The inbreeding coefficient (FIS) ranged from −0.003 to 0.205 with a mean on of 0.123 and did not differ significantly among regions (p = .368). FIS estimated with a “null alleles” correction (FISNull) was lower in most of the populations (0.020 on average). The presence of null alleles (ca. 6% on average) was indicated as the likely factor of homozygosity excess; in four populations inbreeding likely had a substantial impact on this estimation . Pairwise FST ranged from −0.002 to 0.137 and was significantly higher than zero in all populations  and Lesser  Caucasus populations, while the Hyrcanian (HZ) and Azerbaijan (AZ) stands were moderately differentiated . A significant difference among the geographic regions in terms of pairwise FST was inferred (p < .05). The highest FST were found between the West‐Central Caucasus and Hyrcanian populations (FST = 0.097), and the latter with the Azerbaijan group (FST = 0.075), while the lowest between West‐Central Caucasus and Azerbaijan (FST = 0.011).The global Appendix . The mos3.2K, the most supported number of genetic clusters was K = 2, which showed a west–east gradient of differentiation , and also the populations located in the western part of Azerbaijan (AZ_01–04) with relatively high Q‐values reaching >75%. The remaining Azerbaijan populations (AZ_05–11) were mostly placed in Cluster II (average Q = 67%) together with the Hyrcanian stands  that showed the most limited genetic admixture to the remaining populations.According to Δn Figure . The mosK = 4  method  and Azerbaijan (except for AZ_2 and AZ_07) showed signs of a significant bottleneck (Table 3.3LGM) had the highest support. For both AR and HE, the DistLGM model consistently had the highest Akaike weights (wi >0.68) and Nagelkerke R2’s , pointing to west–east decreasing patterns , explaining 74% of the total variance  and the temperature seasonality (bio4) were defined as the most important variables limiting the distributional patterns of the species with a relatively high contribution of >68% and >16%, respectively, in all tested models  and Shaki Region (AZ_06) strengthened the hypothesis on the refugial areas there. Additionally, SDM indicated the local foci of the species occurrence in the Ganja‐Gazakh and Karabakh regions (<30% of suitability) in Azerbaijan, which needs further genetic confirmation.Climatically suitable areas during the glacial phase were additionally revealed in the Iori Plateau, Alazani valley, and some gorges of the western Azerbaijan part of the Greater Caucasus (suitability >60%). Palaeobotanical evidence that Oriental beech survived in the eastern part of the South Caucasus during the LGM is lacking Connor,  but earlAbies alba  to the Hyrcanian gene pool suggests the possible contribution of the Hyrcanian refugium to the colonization of Oriental beech in the eastern South Caucasus. However, the extremely arid conditions that have prevailed in the Kura‐Araz region (eastern Caucasus) since the LGM  and Lesser Caucasus (FST = 0.012) populations.Considering the topographic complexity of the Caucasus and the IBC hypothesis that involves both historical and adaptation processes as drivers of the population's divergence . It seems that the mid‐elevation areas in the west‐central Caucasus and northern Azerbaijan part of the species range act as corridors for the extensive gene flow in the species. On the contrary, the finding that the Kura‐Araz lowland acts as a substantial barrier to gene flow among the Hyrcanian and the remaining Caucasian populations supports our assumption that the detected differentiation is structured by the environmental resistance and evolutionary history. Indeed, our results indicated that climate and ancestry explained the largest amount of among‐population variation  after omitting the insignificant effect of topography, geography, and migration. A significant proportion of the variation could be attributed exclusively to genetic ancestry that refers to the IBC model (17%).The clear west–east gradient of genetic differentiation in Oriental beech could suggest a strong pattern of IBD. However, given that IBD does not account for the landscape heterogeneity . Consequently, the current distinctiveness of the Azerbaijan sites could be a weak signal of the initial founder effect originating from the colonization stage. According to IBE model, the selection against maladapted migrants may allow the genetic signal of the initial structure to be preserved in the neutral diversity for generations  could also have been caused by local adaptation, given the climatic distinctiveness of the East Caucasus. The detected significant signal of IBE, accounting for 6% of the total variation, suggests that the genetic composition is partially structured by local climate. Specifically, aridity, maximum temperature, precipitation of the wettest month, and annual potential evapotranspiration were significantly associated with genetic distance. According to the autecology diagram, these range‐edge populations can be considered as ecologically marginal Figure , which m4.3In contrast to some studies ; data curation (lead); formal analysis ; investigation (lead); methodology (lead); project administration (supporting); supervision (lead); visualization (lead); writing – original draft (lead). Irina Danelia: Resources ; writing – review and editing (supporting). Vahid Farzaliyev: Resources ; writing – review and editing (supporting). Hamid Gholizadeh: Resources (supporting); writing – review and editing (supporting). Grzegorz Iszkuło: Investigation (supporting); resources (supporting); writing – review and editing (supporting). Alireza Naqinezhad: Resources (supporting); writing – review and editing (supporting). Elias Ramezani: Writing – review and editing (supporting). Peter A. Thomas: Resources ; writing – review and editing (supporting). Dominik Tomaszewski: Writing – review and editing (supporting). Łukasz Walas: Formal analysis ; writing – review and editing (supporting). Monika Dering: Conceptualization ; data curation ; funding acquisition (lead); project administration (lead); resources ; supervision (supporting); writing – review and editing (supporting).Appendix S1–S3Click here for additional data file.


The Y-chromosomal short tandem repeat polymorphisms (Y-STRs) are the male-specific markers. The characteristics of paternal lineages make it a valuable tool for tracing familial relationships . Y-STR aAnalysis of allele frequencies of Y-STRs is indispensable for forensic reference database construction and population genetics. To determine the genetic polymorphism and haplotype frequency of 41 Y-STRs in the Shandong Han population in China, 567 unrelated male individuals were recruited for the present study. Genomic DNA was extracted from the bloodstain samples, using the Chelex-100 protocol described by Walsh et al. [The Goldeneye® Y-Plus Kit  was used to genotype Y-STRs, including 41 Y-STR loci . Fluorescent multiplex polymerase chain reaction (PCR) was conducted according to the manufacturer’s protocols. The STRs were genotyped using a 3500 ABI Prism Genetic Analyzer , and the resulting data were analyzed using GeneMapper ID-X software (Applied Biosystems).k refers to the number of haplotypes. Haplotype diversity (HD) or genetic diversity (GD) was calculated using the formula, n refers to the sample size. Discrimination capacity (DC) was calculated using the formula, https://yhrd.org/amova). Phylogenetic analyses were conducted on MEGA 7.0 software [Haplotype and allele frequencies were calculated using the direct counting method. Forensic parameters were calculated using the formulas described by Nei . Haplotysoftware  using thsoftware .Supplementary Tables S1 and S2, 563 unique haplotypes were detected. Only one non-unique haplotype was detected in two individuals, and the haplotype frequencies ranged from 0.1864% (1/567) to 0.3527% (2/567). The allele frequencies are shown in Supplementary Table S3; DYS385 was the most polymorphic STR (GD = 0.9618), followed by DYF387S1 (GD = 0.9425), DYS527 (GD = 0.9378), and DYF404S1 (GD = 0.8975). It has been reported that the discrimination capacity and haplotype diversity can be increased if more markers are included [Supplementary Table S2). The results suggested that a large value was produced by a larger panel size, and that the 41 Y-STRs could enable further efforts to improve the discrimination capability.As shown in included . Forensihttps://yhrd.org/amova), which included 27 Chinese ethnic groups and 15 populations of different nationalities. The results showed significant differences between the Shandong Han population and others (Supplementary Tables S4 and S5). The largest genetic distance to the Shandong Han population was exhibited by the Aba Tibetan population , followed by the Garzê Tibetan , Chamdo Tibetan , and Sichuan Tibetan populations . The closest genetic distance was exhibited by the Shaanxi Han , Jiangsu Han , and Jiangxi Han populations  (Supplementary Table S4). The MDS plots showed that the Shandong Han population was clustered with the populations of East China , and was away from the populations of the Middle-South China (Guangdong Han), South-west China (Xinjiang and Qinghai), and North-west China . Furthermore, all 11 populations of Tibetan highlanders clustered in one dimension . These results suggested that the geographic location played an important role in genetic distance, and the regions of geographic proximity shared more genetic similarities. Both the Hunan Miao and Hunan Tujia populations resided in Hunan Province, and the evolutionary relationship was close . The same result was also reflected by the MDS plot, wherein the data points of the Hunan Miao population overlapped that of the Hunan Tujia population . Comparable results were also obtained at the global scale; the lowest genetic distance value was exhibited by the Swiss and Belgian populations , and the highest genetic distance value was exhibited by the Irish and African American populations  . Interesting, although the Guizhou Province is located in the Southwest, the Miao population was genetically closer to the other Chinese Han populations. The same observation was also reported by Tao et al. [To compare the Rst values of the Shandong Han population and others, 42 population data points were extracted from the YHRD website . Although China is a multi-ethnic country, similar population characteristics could also be observed among Chinese ethnic groups. Most of the Han populations gathered in one dimension, and all Tibetan populations converged in the upper right dimension . As for the other ethnic groups, the populations of different ethnic minorities seldom clustered together .Owing to global migration and labour market construction, many people have moved to prosperous areas. Migration is likely to result in a demographic transition , 13. As In conclusion, the present study yielded valuable genetic data on 41 Y-STRs in the Chinese Shandong Han population. The forensic parameters demonstrated that the Y-STR marker sets were highly polymorphic, and hence constituted a promising panel for familial relationship estimation in the fields of forensics and population geography. The Shandong Han population was most similar to the Shaanxi Han population, and it was quite different from geographically distant populations such as the Irish population, and the other ethnic minorities such as the Tibetan population. The results of genetic distance suggested that the population differed according to the geographic location and human ancestry.Click here for additional data file.


Trichiurus nanhaiensis is one of the most important commercial fish species in the South China Sea. This study aimed to investigate the level of genetic variation and population genetic structure of T. nanhaiensis in the South China Sea for the first time, using 281 individuals collected from seven locations along the coast of mainland China, Taiwan, and Hainan Island. A high level of haplotype diversity and low nucleotide diversity were detected in the mitochondrial DNA cyt b gene and nuDNA RYR 3 gene. The overall expected heterozygosity (He = 0.693) among the seven populations ranged from 0.681 to 0.706 in microsatellite DNA data, which revealed high levels of genetic diversity. Significant genetic differentiation was found in Taidong populations in Taiwan, revealing the prevention of gene flow caused by the Kuroshio Current. Two major lineages based on the cyt b gene suggested that the Taiwan Strait acted as a geographic barrier for T. nanhaiensis during the glacier periods in the late Pleistocene. The Bayesian skyline plot also revealed that population demographic expansion of T. nanhaiensis was estimated to have occurred in 0.1 Mya. Our results indicated that all populations of T. nanhaiensis had experienced a recent genetic bottleneck following recent expansion based on ABC analysis. The population genetic pattern and phylogeographic structure in marine species are contingent on historical factors, including Pleistocene climatic oscillations, glacial vicariance, ocean current systems, and life‐history traits for organisms3. With a wide distribution, as well as extensive larval and adult dispersal, some marine fish are characterized by weak genetic structure and inferred connectivity5. Several important studies have revealed that species with broad regions, as expected from larval dispersal, showed extensive gene flow and genetic homogeneity6. Furthermore, in many cases, this extensive gene flow and genetic homogeneity might be attributed to fewer barriers to gene flow as well as large population sizes. Many previous molecular studies have shown that many marine fish with high mobility exhibit low genetic structure in the northwestern Pacific, such as in the Chinese beard eel (Cirrhimuraena chinensis)7 and ponyfish (Nuchequula mannusella)8. Increasing phylogeographic evidence indicates that cyclical glacial fluctuations shaped the distribution of species, demographic expansions, and genetic divergence of marine fish species. During the Pleistocene glacial-interglacial cycles, the area and configuration of marginal seas in the northwestern Pacific changed dramatically. The emergence of the Taiwan Strait associated with sea-level falls measuring approximately 120–140 m during glacial periods might act as phylogeographic barriers that impede the dispersal of marine fish between both sides of the strait10. Recent mtDNA studies indicate that there are two distinct lineages due to vicariance events in some marine fish, such as in Chinese black sleeper (Bostrychus sinensis)5, large yellow croaker (Larimichthys crocea)11, Lepturacanthus savala10, and yellow seabream (Acanthopagrus latus)12. Understanding the genetic characteristics of marine fish, including their genetic diversity, genetic structure, and population historical demography, provides reference opinions for the long-term management and protection of species germplasm resources13.Because of the rise in overfishing, degradation, pollution, and industrialization, understanding the genetic diversity and population structure of economically important marine species is one major crucial objective of species conservation strategies and fisheries managementTrichiurus nanhaiensis, Wang and Xu 1992 featuring a very elongated and highly compressed body with a deeply forked caudal fin, is a benthic fish of the family Trichiuridae that inhabit the continental shelves and shallow seas (20–200 m) of tropical and temperate waters, and is wide geographical distribution in the Indo-Pacific Ocean, including the South China Sea. The Taiwan Strait is thought to be the northernmost limit of its range in the Western Pacific. Trichiurus nanhaiensis is one of the most important commercial fish species in the South China Sea, accounting for 13.7–14.2% of the total annual fishing catch in the South China Sea between 2019 and 2020. Previous studies on T. nanhaiensis have focused mainly on the mitogenome taxonomy14, DNA barcoding15, characterization of microsatellite DNA16, reproduction17 and demographic history19. Understanding the genetic structure of T. nanhaiensis populations is necessary and is required to formulate strategies for the effective protection and utilization of marine fishery resources20. In addition, previous population genetic studies of T. nanhaiensis using limited genetic data were used to delineate population structure, and discrepancies among studies have to some extent hindered the effectiveness of fisheries management and conservation19.Cutlassfishes (of the family Trichiuridae) belonging to the suborder Scombroidei of Perciformes is a diverse group of demersal fishes, including three subfamilies, eight genera, and twelve species in mainland China. The fisheries of cutlassfishes showed declining trends over recent years on the coast of mainland China and the third most marine catches in the South China Sea (SCS). 21. Direct comparisons among mtDNA, nuDNA and microsatellite loci can be very informative for population diversity and genetic structure, as they provide valuable information for evaluation and conservation issues. This study aimed to investigate the level of genetic variation and population genetic structure of T. nanhaiensis in the South China Sea  for the first time, and it used mitochondrial, nuclear, and microsatellite DNA markers to reveal the distribution of genetic variation in T. nanhaiensis. Additionally, our results provide a workable and responsible stock for scientific and conservation purposes to maintain long-term sustainability and resilience to the fishing pressure of T. nanhaiensis resources.Nuclear DNA is inherited from two parents, and recombination of genes from the parents in every generation, whereas mtDNA is haploid and only maternally inherited, reflecting changes in population structure faster due to its lower effective population size and therefore rapid coalescence time. Microsatellites are simple repetitive sequences and codominant throughout the eukaryote nuclear genome, showing high resolution at the population levelb gene and nuclear RYR 3 gene from 281 T. nanhaiensis individuals, respectively  (Supplementary Table b gene was high (0.989), ranging from 0.981 (ST) to 0.995 (ZJ), and the average nucleotide diversity (θπ) was low (0.005), ranging from 0.004 (ZJ) to 0.005 (YJ) (Table π) was low (0.001), ranging from 0.001 (SZ) to 0.002 (SY)  to 0.084 (between TD and SZ), with a mean value of 0.023 in the mtDNA cyt b gene. The pairwise FST values between the populations from TD and other populations were differentiated, except for the YJ population in the mtDNA cyt b gene  to 0.060 (between YJ and ZJ), with a mean value of 0.020 in the nuDNA RYR 3 gene. No significant correlation was found between genetic distance and geographic distance by using IBD analyses .The pairwise b gene and nuclear RYR 3 gene, i.e., one group , two groups , two groups , and three groups  . Likewise, the same results were supported by the presence of a star-like topology in the cyt b gene tree and by the results of mismatch distribution analysis, which showed unimodal distributions  from the probable factors shaping genetic structure demonstrated that most of the genetic variation was among individuals within populations in the mtDNA cyt es Figs. , S2. Neu23. A total of 118 alleles were detected for the 13 polymorphic markers, and the number of alleles per marker ranged from 3 to 27, with an average of 9.0, in 281 individuals, with 72 unique alleles in the total population. The sample size, number of alleles (Na), number of allelic richness (AR) per population, expected heterozygosity (HE), observed heterozygosity (HO), inbreeding coefficient (FIS), and deviation from Hardy–Weinberg equilibrium (HWE) for each population are shown in Table FIS) in all populations was positive, indicating that the heterozygote deficiencies ranged from 0.100 (YJ) to 0.191 (TD)  and allelic richness (AR) per locus were 9.0 and 7.8, ranging from 3 (Tna3) to 27 (Tna16) and from 2.771 (Tna3) to 22.406 (Tna16), respectively. The observed heterozygosity (HO) and the expected heterozygosity (HE) were 0.594 and 0.693, ranging from 0.244 (Tna1) to 0.759 (Tna14), and ranging from 0.343 (Tna1) to 0.951 (Tna16), respectively . The characteristics of all 13 microsatellite loci in T. nanhaiensis are shown in Supplementary Table FST values, with an average of 0.042(10–2), ranged from − 0.002 (between ZJ and YJ) to 0.014 (between SY and TD), and the RST values, with an average of 0.009, ranged from − 0.014 (between TD and SZ) to 0.040 (between ZJ and TD)  = − 172.360; Stdev LnP(K) = 27.976; Delta K = 6.036)  to analyze the genetic diversity of T. nanhaiensis, which is of importance to biodiversity conservation and the sustainable use of biological resources. High haplotype diversity (h = 0.989) and low nucleotide diversity (0.005) were found in T. nanhaiensis populations based on the mitochondrial cyt b gene. High haplotype diversity was similar to the haplotype diversity of most marine fishes on the coastlines of mainland China, suggesting large effective population sizes over time . The nucleotide diversity of T. nanhaiensis was higher than the nucleotide diversity of L. savala8 but lower than the nucleotide diversity of T. japonicas in the family Trichiuridae along the coastlines of mainland China18. Population size is considered to be an important factor in the maintenance of genetic variation, and small populations should show lower levels of genetic variability than large populations29. The current effective population sizes of T. japonicas, the dominant cutlassfish species, were larger than the current effective population sizes of T. nanhaiensis throughout Taiwan and the coast of mainland China30.Monitoring genetic diversity is an integral part of conservation biology, and maximizing the maintenance of genetic variation is necessary to dissect the integrated effects of evolutionary and ecological processes following environmental changesT. nanhaiensis were relatively lower than the average number of alleles per population of the relative species L. savala and other marine fish populations along the coast of mainland China . In this study, the average value of expected heterozygosity (0.693) of T. nanhaiensis was relatively lower than the average value of expected heterozygosity of marine fish (average HE = 0.790) with many marine fish populations34. In this study, the positive inbreeding coefficient (FIS = 0.145) of T. nanhaiensis indicates heterozygosity deficiency in all populations, which might be attributed to inbreeding. Previous studies have reported that low observed heterozygosity points to a deficiency of heterozygotes and high levels of inbreeding in the waters off mainland China , as well as in other related species . In addition, the loss of genetic diversity may reflect past historical events associated with current evolutionary forces, such as fishing pressure or habitat loss19. Loss of genetic diversity is most often associated with reduced population adaptive capacity fitness through inbreeding depression, the maintenance of the high levels of genetic variability in natural populations has been recommended for conservation.The values of the average number of alleles per population (9.0) of Helice36, B. sinensis9, and L. savala10. Our results revealed that haplotype networks and phylogenetic trees support the formation of two major lineages based on the cyt b gene, and genetic clusters do not correspond to geographical groups. During the Pleistocene, the East China Sea and the South China Sea were semienclosed marginal seas and separated by the Taiwan Strait. We suggested that the Taiwan Strait acted as a geographic barrier for T. nanhaiensis during the glacier periods in the late Pleistocene and gene flow due to the absence of physical barriers during glacial retreat, while more recent secondary contacts could have played a major role37. The results of the AMOVA test based on mitochondrial, nuclear, and microsatellite DNA data indicated that there were no significant differences at all hierarchical levels. All genetic markers, including mitochondrial, nuclear, and microsatellite markers, congruently showed a similar genetic pattern, revealing overall low genetic differentiation among T. nanhaiensis populations, by previous studies on other marine fishes among the geographical stocks in the South China Sea . The results from STRUCTURE indicated the presence of two clusters after independent clustering of all populations based on microsatellite DNA data, which may be explained by the high dispersal capacity of T. nanhaiensis. The scenario of evolutionary diversification of lineages followed by postglacial expansion facilitating secondary contacts was observed in previous studies . A previous study in Trichiurus species suggests a genetic well mixture and a lack of distribution barrier for T. nanhaiensis17. Ocean currents, which change with the monsoon and are highly variable in the SCS, play an important role in transporting eggs, larvae, or juveniles of T. nanhaiensis41. We suggested that the high dispersal ability of marine fish may be appeared by gene flow following divergence, indicating that divergent mitochondrial lineages arose within a panmictic population. The results from DAPC and the heatmap of allele distribution and frequency across populations revealed that population TD was distinctly separated from the other geographic populations. Population TD was located in southern Taiwan, and samples were collected from the Pacific Ocean. We suggest that population TD belonging to peripheral populations may always have low genetic variability due to isolation and founder effects, but the differentiation of the populations is high owing to genetic drift and reduced gene flow under the influence of the Kuroshio Currents42.Many previous studies suggested that the major drop in sea level in the Taiwan Strait acted as a biogeographic barrier during major falls in sea level in the Pleistocene and might have cut off migration on either side of the strait and presented two lineages in marine fishes, such as the genera D and Fu’s Fs tests suggested that T. nanhaiensis populations indicate recent demographic expansion. Moreover, the star-like structure of the haplotype network shows consistent evidence for past recent population bottlenecks followed by population expansion. The Bayesian skyline plot also revealed that population demographic expansion of T. nanhaiensis was estimated to have occurred in 0.1 Mya. The presence of a consistent signal of recent population expansion gives a similar estimated expansion time to other previous studies in T. nanhaiensis, which suggests that the population expansion event took place in the late Pleistocene19. Furthermore, the results of our comparison to the previous study of marine fish in the South China Sea thus provide considerable evidence of population growth and expansion in T. nanhaiensis . However, a higher θω than θπ indicated population decline, and all seven populations appeared to experience genetic bottlenecks based on the microsatellite markers in T. nanhaiensis. The demographic scenario of T. nanhaiensis illustrates an even more complex history. Our best-fitting ABC model [Scenario 5 (DECINC model)] was identified with recent expansion preceded by a bottleneck. Our results support previous studies showing that the population of T. nanhaiensis steadily declined during 45–165 kya and exhibited a pattern of glacial growth18.Both mismatch distribution analyses and neutrality indices of Tajima’s T. nanhaiensis were collected from seven locations in the South China Sea in 2019  gene was amplified using the gsCY4-F (5′-TCCCTCATTGACCTTCCA-3′)/gsCY4-R (5′-GGTTGCGGTTCAGTTGAG-3′) primer pair, and the nuclear DNA gene (its protein-coding sequence) for ryanodine receptor 3 (RyR3) was amplified using the primers RYR3-F22 (5′-TCGGTAAGCARATGGTGGACA-3′) and RYR3-R931 (5′-AGAATCCRGTGAAGAGCATCCA-3′). The 13 microsatellite loci were referenced from a previous study14. PCRs were performed in 25 μl of the total volume containing 3 μl genomic DNA, 12.5 μl Taq mix, 1 μl primer, and 7.5 μl ddH2O. PCR amplification was performed in a Biometra thermal cycler under the following conditions: 94 °C for 5 min for initial denaturation, followed by 33 cycles of 92 °C for 0.5 min, 57 °C for 1 min, extension at 72 °C for 1 min, and a final extension at 72 °C for 10 min. All PCR products were purified and sequenced commercially . Electrophoresis and genotyping were conducted by an ABI PRISM 3730 Genetic Analyzer automated DNA sequencer  and GeneMapper 4.0 (Applied Biosystems). All nucleotide sequences were deposited in GenBank (accession numbers: OM303509-OM303789 for Cyt b and OM388568-OM389129 for RYR3).The mitochondrial cytochrome b and RyR 3 sequence alignments for all 281 samples were separately performed using Clustal X 2.0 software44. The PHASE algorithm in DnaSP v5.0 software45 was used to resolve the haplotype phases of RyR3 sequences that contained more than one ambiguous site and analyze summary statistics such as the number of haplotypes (Nh), haplotype diversity (h), and nucleotide diversity (θπ and θω)22. We constructed neighbor-joining (NL) trees using MEGA X46 to analyze the phylogenetic relationship of T. nanhaiensis. Bayesian inference (BI) and maximum likelihood (ML) were performed using PhyloSuite v1.2.247. The best-fit partitioning strategy and nucleotide substitution model for BI and ML tree were selected by ModelFinder installed in Phylosuite v1.2.2 with the greedy algorithm and BIC (Bayesian information criterion) criteria. Haplotype networks for Cyt b and RyR 3 were computed using the minimum-spanning network method (minspnet in Arlequin 3.5)48. In addition, the neutrality test (Tajima’s D49 and Fu’s Fu test50) and mismatch distributions were evaluated to test the hypothesis of demographic expansion using DnaSP v5.0 software45. Bayesian skyline plots (BSPs) were implemented in BEAST v1.8.2 for T. nanhaiensis to determine the effective population size changes over time51. The MCMC chains were run three times each for 100 million generations, sampling every 10,000th generation for each data set. In the BSPs analysis, the effective sample size (ESS) values for each parameter was larger than 200, and the 95% highest posterior density (HPD) intervals were reported. Bayesian skyline plots (BSPs) were analyzed and drawn using the tracer v1.6 program52. A 2.03%/MY divergence rate has been calibrated for the mtDNA cyt b genes in Trichiurus fishes for population expansion18.The Cyt FST between all pairs of populations and analysis of molecular variance (AMOVA) were executed in Arlequin 3.548. Seven populations were grouped with three scenarios based on geographical barriers: (1) Scenario I: two independent groups divided by the Taiwan Strait ; (2) Scenario II: two independent groups divided by the Qiongzhou Strait ; (3) Scenario III: three independent groups that included the mainland group, the Taiwan island group and the Hainan island group . In addition, an isolation-by-distance Mantel test was performed to examine correlations between genetic differentiation and geographic distance by IBD 1.52 for Windows53. The Google Earth database (http://earth.google.com) was used to measure the geographic distance in kilometres from GPS locations between sampling sites.Pairwise 23. In this study, Arlequin 3.548 was used to calculate the number of alleles (Na), mean observed heterozygosity (HO), mean expected heterozygosity (HE), and deviation from Hardy–Weinberg equilibrium (HWE) for each population. Allelic richness (AR) and inbreeding coefficient (FIS)54 were estimated using FSTAT version 2.9.355. Population differentiation of T. nanhaiensis was studied by estimation of the FST and RST using Arlequin48 and AMOVA procedures as mitochondrial DNA data (mentioned above).All loci were tested for possible genotyping errors, the presence of null alleles, and allelic dropout using MICRO-CHECKER 2.2.3 software56. A series of 10 independent runs for each K (ranging from 2 to 5) was performed using 100,000 iterations of the Markov chain Monte Carlo (MCMC) with a burn-in period of 20,000 chains. Structure Harvester Web 0.6.94 was used to determine that the optimum number of genetic clusters within the data were predicted using the delta K method and Evanno method57. GenAIEx version 6.503 was used to calculate allelic frequency58, and the R package “pheatmap” was used for data visualization and allele frequency heatmap construction. Moreover, to investigate the genetic relationship between populations, discriminant analysis of principal components (DAPC)59 was performed using the ‘“adegenet 2.0.1”’ package in R 3.2.2 software 60.STRUCTURE v.2.2.3 was used to delineate the optimum number of homogenous groups of sampled individuals (K)T. nanhaiensis, we used a coalescence analysis implemented in the program DIYABC v.2.0.461 to obtain relevant and detailed information on the population history. We separately tested the five scenarios of possible demographic changes for T. nanhaiensis based on Cyt b and RyR3 sequences and microsatellite data , assumed populations of T. nanhaiensis decline and had experienced a bottleneck event; In scenario 3 (INC model), assumed populations of T. nanhaiensis expansion recently; In scenario 4 (INCDEC model), assumed populations of T. nanhaiensis expanded followed by a single instantaneous decrease in population size; and in scenario 5 (DECINC model), assumed populations of T. nanhaiensis bottleneck followed by re‐expansion. To obtain robust results, a total of 3,000,000 simulations were performed as recommended by DIYABC for all five demographic scenarios  method is incorporated into different historical and demographic evolutionary models that can be suited to complex problems that arise in scenarios in population genetics. To explore the possible historical demography of ata Fig. . The HKYios Fig. . We calcSupplementary Information 1.Supplementary Information 2.