Sebastes mentella and S. fasciatus. We genotyped 860 individuals in the Northwest Atlantic Ocean using 24,603 filtered single nucleotide polymorphisms (SNPs). Our results confirmed the clear genetic distinctiveness of the two species and identified three ecotypes within S. mentella and five populations in S. fasciatus. Multivariate analyses highlighted the influence of spatial distribution and depth on the overall genomic variation, while demographic modeling revealed that secondary contact models best explained inter‐ and intragenomic divergence. These species, ecotypes, and populations can be considered as a rare and wide continuum of genomic divergence in the marine environment. This acquired knowledge pertaining to the evolutionary processes driving population divergence and reproductive isolation will help optimizing the assessment of demographic units and possibly to refine fishery management units.Understanding the processes shaping population structure and reproductive isolation of marine organisms can improve their management and conservation. Using genomic markers combined with estimation of individual ancestries, assignment tests, spatial ecology, and demographic modeling, we (i) characterized the contemporary population structure, (ii) assessed the influence of space, fishing depth, and sampling years on contemporary distribution, and (iii) reconstructed the speciation history of two cryptic redfish species,  Both species co‐occur in the Northwest Atlantic and inhabit at different depth intervals  where S. mentella and S. fasciatus live in sympatry, S. mentella releases its larvae approximately three to four weeks earlier than S. fasciatus . In 1993, this management plan was redefined based on a stronger biological basis, resulting in six Canadian management units  to (i) delineate the contemporary population genomic structure in Sebastes spp. located in the Northwest Atlantic Ocean, including the recent GSL cohorts observed, (ii) assess how space, fishing depth, and sampling years explain the contemporary distribution of species, ecotypes, and populations, and (iii) characterize the demographic history of speciation.While population genetic structure in 22.1Sebastes spp. individuals, captured from 28 sampling sites in the Northwest Atlantic Ocean  were included in this study  using BWA‐MEM  algorithm with default parameters  > 0.01 or at least a MAF > 0.05 in one location were retained for the analysis. Only one SNP was kept per locus in order to avoid bias due to linkage disequilibrium . The resulting filtered VCF files were converted into the file formats necessary for the following analyses using PGDSpider v.2.0.5.0  (n + 1 sampling sites). The support for different values of K was assessed according to the likelihood distribution  as well as a visual inspection of the co‐ancestry values for each individual. Admixture analyses were also performed at the species level in order to investigate finer patterns of genomic structure. A PCA, implemented in the adegenet package  the validity of population structure and (2) the number of SNPs necessary for accurate assignment. The first assignment test aimed to assess the validity of microsatellite classification by using genetic clusters inferred for each individual using ADMIXTURE. This first run was performed in GENODIVE  eigenfunctions, which are orthogonal variables that can be used in statistical models as explanatory variables representing spatial structure at different scales among the studied locations. Given the large spatial extent of the study area, distances among locations accounted for the earth curvature using the gcd.hf function in the codep package. To compute the MEMs, the truncation threshold was set to the length of the longest edge of the minimum spanning tree and only positive MEMs were retained using the dbmem function in the adespatial package. At three sampling sites , depth was not recorded and therefore the median of depth distribution was used instead. Years were coded as dummy variables and treated as factors, therefore not assuming a linear relationship among years, but testing for annual differences in redfish genomic variation. To overcome multicollinearity among variables, we used the variance inflation factor with a threshold of 5, meaning that if a strong correlation was found between two variables, we retained only one of the two variables.We conducted distance‐based redundancy analyses  were calculated. The adjusted 2R was quantified using the RsquareAdj function in vegan and accounts for the number of observations and number of degrees of freedom in the fitted model  and relationships with selected environmental variables. Species, ecotypes, and populations were identified by different colors in biplots to illustrate how genetic clusters were associated with selected variables. Maps of MEMs associated with redfish genomic variation were presented to visualize the most significant spatial scales.A global db‐RDA model was run with all explanatory variables, and model probability and adjusted coefficient of determination  and the effect of differential introgression affecting the rate of migration (m) along the genome  and 21m (from population 1 to population 2) were modeled. Under the SC model, the population evolved in strict isolation between splitT  and until scT  where a secondary contact (gene flow) occurs continuously up to present time. Gene flow was modeled as M = 2Nref.m. Heterogeneous introgression was modeled using two categories of loci occurring in proportions P  and 1‐P  across the genome. The same procedure was used to account for linked selection by defining two categories of loci with varying effective size. Then, we quantified linked selection using a Hill–Robertson scaling factor  to that of neutral loci (Ne). Three JSFS were constructed using 112,926 SNPs available in the raw dataset: (i) S. fasciatus and S. mentella shallow, (ii) S. fasciatus and S. mentella deep, and (iii) S. mentella shallow and S. mentella deep. It is important to note that S. mentella GSL and S. fasciatus populations were not included since the complexity of the introgression pattern observed for those populations would make difficult the interpretation of demographic models. Details of the filtering procedure are provided in supplementary materials. Model choice was performed using Akaike’s information criterion (AIC) and ΔAIC values under each given model. We used a generation time of 9.05 years for species comparisons and of 9.8 years for ecotype comparisons  a model of strict isolation (SI), (ii) a model of divergence with continuous gene flow or isolation with migration (IM), (iii) a model of divergence with migration during the first generation of divergence or ancient migration (AM), and (iv) a model of secondary contact (SC). Under IM, the two diverging populations exchange migrants at a constant rate at each generation and this gene flow can be asymmetric, so that two independent migration rates s Gascon  and a mus Gascon  for paras Gascon  with 100s Gascon , we comp33.1S. mentella and S. fasciatus, respectively. ADMIXTURE analysis revealed two highly differentiated genetic clusters  consistently showed an average of 18% of S. fasciatus ancestry . The four genetic clusters corresponded to two ecotypes already documented, shallow and deep, a new ecotype, GSL, and a fourth cluster designated as “Unknown” that had an unclear spatial distribution, with no individual having more than 50% ancestry of that cluster , were inferred to belong to GSL ecotype, suggesting the presence of a mixed ecotype composition in the NAFO divisions from 2G to 3K  and K = 8 (CV = 0.195). Yet, the clustering observed at K = 8 was less clear that the one documented at K = 5 since three genetic clusters out of 8 chaotically gather a few numbers of individuals  per sampling locations totalizing less than 18 individuals per cluster. In K = 5, 60% of all the S. fasciatus individuals  showed ancestry> 50.0% with population III , population II , population IV , and population V .For 5 CV = 0.96 and K 5 CV = 0.96 and K FST values and the results of ADMIXTURE analyses at the global and genetic cluster scales in order to examine the extent of inter‐ and intraspecific genetic differentiation. The heatmap based on FST values gave similar results to the ADMIXTURE analyses. Both analyses identified the two species, as well as the three ecotypes and five populations within S. mentella and S. fasciatus, respectively , whereas the largest FST value was between fas12 and men18 , which was in line with ADMIXTURE results showing that the delimitation of the two species captured the majority of the signal of genetic differentiation. Within S. mentella, FST values were twice larger—on average 0.0545 (ranging from 0.0004 to 0.1124)—than within S. fasciatus—on average 0.0257 (ranging from 0.0019 to 0.0715), which again was similar to ADMIXTURE finding a clearer population genomic structure in S. mentella than in S. fasciatus. Furthermore, the FST heatmap showed that the sampling location men22 is genetically more similar to GSL than to shallow ecotype  inferred from microsatellites and using the new 24,603 SNP markers genotyped, we obtained 100% assignment success at the species level.S. mentella, we assigned 100% of the individuals coming from GSL and deep ecotypes, while for shallow ecotype assignment, success varies from 68% to 97% . The sampling locations men22 and men20 showed the highest percent of misassigned individuals—on average 32%—and these individuals were inferred to belong to S. mentella GSL, which corroborate the pattern seen in ADMIXTURE  were assigned to deep ecotype , while populations I, III, and IV reached 100% of assignment success. Despite this high assignment success at the population level, we observed that sampling locations were actually composed of different populations except for fas08, fas09, fas09, fas11, and fas15 where all individuals belong to population III  was population IV . This analysis revealed that only two SNPs Figure  were nee Figures  and S6.3.3Sebastes species, ecotypes, and populations surveyed in this study seemed distinct but overlapping .As the geographic distributions of g Figure , we inven‐1) representing individuals’ genomic variation. All 859 PCs were used as response variables in the db‐RDA.First, explanatory variables were selected for the complete dataset . The elaboration of the MEMs based on geographic coordinates created 19 spatial explanatory variables (MEM1 to MEM19). The first explanatory variables  corresponded to large spatial scales, while the last ones  corresponded to fine spatial scales. A total of 21 explanatory variables were retained, namely 16 spatial variables, fishing depth, and sampling years Table . The resp‐value = .001) and accounted for 40.1% of the genomic variation (adjusted R2 = 0.401). Using a forward and a backward selection approach, we identified the variables explaining most of the genomic variation. The db‐RDA biplot shows distances among objects and relationships with selected variables  was significant  and accounted for 8.5% of the genomic variation (adjusted R2 = 0. 085). Variable selection identified seven MEMs, depth, and two sampling years  as significant drivers of genomic variations within S. mentella  was significant  and accounted for 3.9% of S. fasciatus genomic variation (adjusted R2 = 0.039). Variable selection identified 8 MEMs, depth, and sampling years  as significant  with approximately 1 MYA (million years ago) of divergence for each comparison . Estimates of migration rate were low  to the shallow population  assess population genomic structure with a dense marker set, (ii) investigate how environmental or temporal drivers may influence the population structure, and (iii) reconstruct the speciation history of two redfish species along the Northwest Atlantic Ocean. We confirmed the pronounced genetic distinction between 4.1S. mentella and S. fasciatus, and all have distinct but overlapping distributions. The largest estimate of genetic differentiation was between S. mentella and S. fasciatus species , supporting that these genetic clusters form independent demographic units.We observed a level of genetic differentiation spanning from weak to pronounced between the genetic clusters within both S. mentella, we confirmed the presence of deep and shallow ecotypes and identified a new ecotype, GSL in the Northwest Atlantic with more genetic similarities to shallow than deep ecotypes. It is then possible that GSL ecotype may have diverged from the shallow ecotype. The shallow and deep ecotypes were previously identified and described as distinct genetic clusters inhabiting different depths along the continental slope in past studies across the North Atlantic  and it is the unique ecotype present in the GSL, a partially isolated area.Within S. fasciatus, we identified five populations occurring from the Gulf of Maine to the Labrador Shelf with highly overlapping distribution. This contrasts with the more pronounced differentiation we observed between S. mentella ecotypes and consequently justifies the use of the term population (instead of ecotype) to describe these genetic clusters. Nevertheless, the five populations identified are mostly associated with distinct geographic areas along the Canadian coast , for which we hypothesize that limited water exchange or limited physical connectivity may be responsible for this pattern, as previously proposed in the red algae Palmaria palmate . For migratory fish species, estimates of genetic differentiation using thousands of neutral SNPs between trans‐Atlantic populations are of ca. 0.016 for Atlantic mackerel  suggesting limited dispersal during the larval stage and short migration distance. Their ovoviviparity, involving internal fertilization and larval extrusion, likely reduces the extent of dispersal and may reduce interspecific mating and produce reproductive isolation, thus favoring genomic differentiation on small geographic scales  that correspond to an area of contact with another Sebastes species, Sebastes norvegicus, which is present in the North Atlantic , and thus, this is likely due to our nonrandom sampling design. If logistically possible, future population genomic studies on 4.3Sebastes species inhabiting the North Atlantic using explicit demographic simulations. Here, we discovered that scenarios of secondary contact (SC) provided the best fit to the observed data for both species and ecotypes. Furthermore, modeling the process of speciation between S. mentella and S. fasciatus has never been done before, while for S. mentella deep vs. shallow comparison, Saha et al.  across their whole distribution range. Nevertheless, this signal of introgression between S. mentella and S. fasciatus may also be due to the fact that both species and ecotypes showed large Ne and recent divergence time, which may result in incomplete lineage sorting indicating that some ancestral variants are still shared. Indeed, delineating species along a continuum of genomic divergence is a major challenge in evolutionary biology but can be tackled through appropriate demographic modeling by investigating the relation between net synonymous divergence (Da) and the probability of ongoing gene flow , which supports the idea that (i) ecotypes are more recently diverged than species, as well as the fact that (ii) species and ecotypes fall within the “grey‐zone of speciation” . Yet, on the western Newfoundland coast, in the GSL, individuals shared ancestry only with the GSL ecotype and form the large new cohorts rebuilding the stock within the GSL  as shown in a wide range of species with management or conservation concerns such as harbor porpoise (Phocoena phocoena; Lah et al., Salmo trutta; Lemopoulos et al., Salmo salar; Moore et al., Pecten maximus; Vendrami et al., Sebastes spp. would serve to distinguish the two species and three ecotypes within the fish catches in order to assess the true impacts of the redfish fishery in Canada. Furthermore, a surprising high assignment success was achieved for S. fasciatus populations, with up to 96.5% of success while the vast majority of the sampling locations always exhibit a mixing proportion of different genetic clusters. This surprising result indicates that more samples might be required for enhancing the resolution of population structure and assignment test and eventually develop similar DNA chip for S. fasciatus populations.Genetic resources such as microsatellite markers were used for species identification of Fig S1Click here for additional data file.Fig S3Click here for additional data file.Fig S5Click here for additional data file.Supplementary MaterialClick here for additional data file.


Acorn barnacle adults experience environmental heterogeneity at various spatial scales of their circumboreal habitat, raising the question of how adaptation to high environmental variability is maintained in the face of strong juvenile dispersal and mortality. Here, we show that 4% of genes in the barnacle genome experience balancing selection across the entire range of the species. Many of these genes harbor mutations maintained across 2 My of evolution between the Pacific and Atlantic oceans. These genes are involved in ion regulation, pain reception, and heat tolerance, functions which are essential in highly variable ecosystems. The data also reveal complex population structure within and between basins, driven by the trans-Arctic interchange and the last glaciation. Divergence between Atlantic and Pacific populations is high, foreshadowing the onset of allopatric speciation, and suggesting that balancing selection is strong enough to maintain functional variation for millions of years in the face of complex demography. The relationship between genetic variation and adaptation to heterogeneous environments remains a central conundrum in evolutionary biology . ClassicSemibalanus balanoides) is a model system to study adaptations to ecological variability. This barnacle is a self-incompatible, simultaneous hermaphrodite which outcrosses only with adjacent individuals. Adult barnacles are fully sessile and occupy broad swaths of intertidal shores in both the North Pacific and North Atlantic oceans. These habitats experience high levels of cyclical and stochastic ecological heterogeneity which impose strong selection at multiple spatial scales: microhabitats , mesohabitats (bays and estuaries), and macrohabitats    . Barnaclaboards) . This co(1–3 Ma) . Like mo(1–3 Ma) , and mor(1–3 Ma) . As suchMpi) in barnacles across the entire North Atlantic basin , Rhode Island (RI), Iceland (ICE), Norway (NOR), and the United Kingdom (UK). For all populations, we sequenced multiple libraries including: a single individual barnacle genome to ∼50× coverage, pools of 20–38 individuals per population  , maintaiic basin . These fulations A–C. In tX I data ). We mapπ; a metric of standing genetic variation). Surprisingly, North Atlantic populations harbor more genetic variation (π = 1.05%) than their Pacific, ancestral, conspecifics , a neutrality test based on the comparison of two measures of nucleotide polymorphism: π and Watterson theta (θ). The value of the D statistic is a good proxy for the excess (D < 0), or deficit (D > 0), of rare alleles in populations. These data indicate that all North Atlantic populations, especially NOR, have negatively skewed genome-wide values of D  across populations at common allele frequencies (>5%). When linkage is removed at 500 bp, the SNP panel thins to ∼690,000. Principal component analysis (PCA), on the Linkage disequilibrium (LD) thinned SNPs, shows that variation is strongly subdivided by ocean basins D. PC1 caues of D  online.Ne) with the multiple sequentially Markovian coalescent model (MSMC) using individual whole genomes  reveal large amounts of genome-wide divergence  and the f3 analysis suggests that admixture is pervasive , deficit of rare alleles (D > 0), excess SNPs at medium allele frequencies, reduced divergence around the balanced locus (low FST), as well as the accumulation of nonsynonymous variation in the vicinity of balanced polymorphisms, a phenomenon known as sheltered load  data sets reveal 11,917 cosmopolitan SNPs  which are also TSPs  harbor an excess of nonsynonymous HE  between tips. We classified allele trees as having or lacking highly diverged alleles based on the relative mean CPD between haplotypes from the same population versus from different populations  enrichment analyses. The 150 genes with positive CPDw–d trees show enrichment for terms related to “ion channel regulation,” including genes involved in environmental sensing, and circadian rhythm regulation   . This maurvival) . This isurvival) . As suchUnder classical models of population genetics, when loci are considered to be independent of each other, the additive effects of widespread balanced polymorphism result in unbearable amounts of fitness variance and genetic death . HoweverMpi gene. Accordingly, the locus is under selection at microlevels in the Gulf of Maine   of all annotated genes are candidates of balancing selection across the entire range of the species. Although follow-up experiments are needed to determine the replicability and functional importance of these variants, our evidence for balancing selection is consistent with patterns reported for other species. For example, the number of candidate genes in 3 genes) . Similarogeneity . We mustenotypes . Despiteenotypes . This hyFST values observed within the basins arise due to shared ancestry. Moreover, they also suggest that population structure persists in the presence of gene flow. As such, although larvae have the capacity to disperse for hundreds of kilometers, ocean currents , Jamestown , Calvert Island , Reykjavik , Porthcawl , and Norddal . Additional samples were collected in Bergen (Norway), Tórshavn (Faroe Island), and Tjärnö (Sweden). For all samples, species identities were confirmed using Sanger sequencing of the mtDNA COX I region . For theVOPJ00000000; BioProject: PRJNA557548; BioSample: SAMN12406453; supplementary Drosophila melanogaster. Genes were annotated by pairwise blast against the D. melanogaster genome . All annotations are available as Samples were mapped to a genome assembled de novo for the species , the second one by all the genes annotated in Sbal3.1 . A detailed description of our analyses can be found in the Estimates of -1 suite . Estimat-2 suite . Demogra-2 suite . The f3  treemix . Bayesia treemix . ABBA/BA (Dsuite . Phyloge (Dsuite . GO enri (Dsuite  and GO tMolecular Biology and Evolution online.msaa227_Supplementary_AppendixClick here for additional data file.


Projection of genetic variability on geographic maps is a useful strategy to ascertain population structure and gene flow events when previous genetic information on the scenarios analyzed is not high. Here, we compared the performance of microsatellite sets and Single Nucleotide Polymorphism (SNP) arrays to identify the population structure and between-populations identity in a sample of West African cattle. Large SNP arrays were superior in detecting the population structure due to a more precise assessment of genotypic information of the individuals. However, the projection of genetic parameters on geographical maps was comparable between the SNP and microsatellite data. Geographic-based analyses of genetic variation areuseful inavoiding overinterpretation of the results obtained. Microsatellite markers can still be useful, particularly if the research focuses on non-model organisms or if either the funding or the availability of efficient hardware and software to handle large datasets is limited.p < 0.0001) and high. However, SNP data allowed for a better fine-scale identification of population structure within taurine cattle: Lagunaire cattle from Benin were separated from two different N’Dama cattle samples. Furthermore, when clustering analyses assumed the existence of two parental populations only (K = 2), the SNPs could differentiate a different genetic background in Lagunaire and N’Dama cattle. Although the two N’Dama cattle populations had very different breeding histories, the microsatellite set could not separate the two N’Dama cattle populations. Classic bidimensional dispersion plots constructed using factors identified via PCA gave different shapes for microsatellites and SNPs: plots constructed using microsatellite polymorphism would suggest the existence of weakly differentiated, highly intermingled, subpopulations. However, the projection of the factors identified on synthetic maps gave comparable images. This would suggest that results on population structuring must be interpreted with caution. The geographic projection of genetic variation on synthetic maps avoids interpretations that go beyond the results obtained, particularly when previous information on the analyzed populations is scant. Factors influencing the performance of the projection of genetic parameters on geographic maps, together with restrictions that may affect the election of a given type of markers, are discussed.A sample of 185 West African cattle belonging to nine different taurine, sanga, and zebu populations was typed using a set of 33 microsatellites and the BovineHD BeadChip of Illumina. The information provided by each type of marker was summarized via clustering methods and principal component analyses (PCA). The aim was to assess differences in performance between both marker types for the identification of population structure and the projection of genetic variability on geographical maps. In general, both microsatellites and Single Nucleotide Polymorphism (SNP) allowed us to differentiate taurine cattle from zebu and sanga cattle, which, in turn, would form a single population. Pearson and Spearman correlation coefficients computed among the admixture coefficients (fitting K = 2) and the eigenvectors corresponding to the first two factors identified using PCA on both microsatellite and SNP data were statistically significant (most of them having  The availability of SNP arrays including thousands of markers has the potential to address questions in population genetics such as the evaluation of distance among population, diversity, and structuring, with a higher resolution than that previously obtained with microsatellites due to increased precision and smaller confidence intervals around diversity measures .The performance of microsatellite sets and SNP arrays has mainly been compared in non-model organisms. Although the magnitude of the differentiation metrics can be quite different, estimates of the between-populations’ genetic distances obtained using either microsatellites or SNPs generally have a strong correlation ,2,3. ThiAlthough clustering methods are informative on the existence of hidden population structuring and differentiation within a sample, geographical projection of parameters summarizing genetic variation on synthetic maps is useful to shed light on the causes and patterns of the differences assessed ,7. ProjeHere, we typed 185 cattle sampled in three different West African countries with a set of microsatellite markers and SNP arrays to compare the performance of clustering methods across datasets and to ascertain whether a geographical assessment of genetic variation derived from either microsatellite or SNP polymorphisms is valid as a reflection of genetic variation and differentiation.Bos taurus; 105), zebu , and sanga (36) cattle individuals belonging to eight cattle populations of Benin, Burkina Faso, and Congo  were obtained from taurine  were analyzed for all samples. Twenty-one of these microsatellites were previously used to characterize contributions to diversity in cattle [p  ≤  0.001 were also removed. A total of 543,595 SNPs located on the 29 bovine autosomes passed the quality control for the whole sample analyzed. The whole dataset was also typed using the BovineHD BeadChip of Illumina  following standard protocols. SNP coordinates were mapped on the bovine UMD 3.1 reference genome assembly. The software GenomeStudio  was used to generate standard .ped and .map files. Sample and marker-based quality control measures were performed using the program PLINK V 1.9 . A GenCaPrincipal component analysis (PCA) was performed on microsatellite allelic frequencies, according to the recommendations by Cavalli-Sforza et al.  using thThe program PLINK V 1.9  was usedhttp://CRAN.R-project.org/) [Using either microsatellites or SNP genotyping data, eigenvectors computed for each individual via PCA were used to construct dispersion plots, and the 75% confidence interval of the dispersion of the individuals per population using the library ggplot2 of R (ct.org/) .http://CRAN.R-project.org/). Using this approach, Boxplots summarizing the information provided by the individual admixture coefficient pulation ,24. As aPearson and (rank) Spearman correlation coefficients between the individual coefficients Admixture coefficients estimated for K = 2 and PCA eigenvectors computed for each individual were also used to construct interpolation maps drawn using the Spatial Analyst Extension of the program ArcView. The inverse distance weighted (IDW) option with a power of two was selected for the interpolation of the surface. IDW assumes that each input point has a local influence that diminishes with distance. The area of sampling of each breed was used as the geographic coordinates, and the six nearest neighbors were used for the calculation. Interpolation surfaces were divided into eight equal classes.Cryptic genetic structure was assessed using the programs STRUCTURE and ADMIXTURE. The most likely number of K estimated using microsatellites was four, while that estimated using SNP genotypes was three . When miWhen software used for structure analyses was forced to assume the existence of two parental populations only (K = 2), the posterior distributions of admixture proportions of the individuals analyzed were not uniform . Althougividuals .Using microsatellites, PCA allowed us to identify 39 factors with an eigenvalue higher than 1 explaining 79% of the genetic variability. In total, the three first factors explained 44% of variability . Using SNPs, PCA allowed us to identify eight factors with an eigenvalue higher than 1, explaining 21% of the genetic variability. The three first factors identified explained 17% of variability . In general, PCA confirmed the general scenario depicted by genetic structure analyses. However, microsatellites A,B gave p < 0.0001). This could also be assessed for the second factor identified using either microsatellites or SNPs (ρ = −0.905 and ρs = −0.836). Furthermore, both Factor 2s, separating the taurine populations from the other cattle populations assessed  mucIn the wild, it is possible to find population genetics studies reporting that microsatellites have comparable (and even better) performance than SNPs. However, these studies typically use a low number of bi-allelic markers and, therefore, the performance of SNP sets cannot overcome that of the more polymorphic microsatellite markers . In non-The size of the markers’ sets is not an issue in projects targeting most livestock populations: a large number of microsatellites have beendeveloped since the 1990s and the availability of SNP arrays including thousands of SNPs is, at present, the rule. This fact, together with knowledge on the livestock breeding scenarios worldwide, makes it possible to use them (here using West African cattle) to assess the differences in performance of microsatellites and SNPs in practical terms.In general, both microsatellites and SNPs allowed us to identify the same pattern of genetic structuring in the West African cattle analyzed: there are two well differentiated subpopulations formed by taurine (Lagunaire and N’Dama breeds) and zebu cattle, with sanga cattle taking intermediate positions between those main cattle types . HoweverMicrosatellites and SNPs differed, however, in identifying particular sources of variation within this general genetic scenario, namely the existence of two differentiated genetic backgrounds within the taurine cattle analyzed: Lagunaire and N’Dama. Microsatellites and SNPs gave highly correlated solutions for admixture proportions when onlythe existence of two parental populations was assumed . It is cDifferences between the Lagunaire and N’Dama genetic background were also suggested by PCA with Factor 2 (markers nature notwithstanding), separating the Lagunaire and the N’Dama individuals. Again, SNPs allowed a clear separation between the two N’Dama populations sampled, which could not be obtained using microsatellites B,D. ThisThe number of SNPs used here greatly exceeded the size of microsatellite markers set. Therefore, it is not surprising that SNPs appeared as more suitable for detecting structuring. However, both marker types had comparable performance in the projection of genetic variability on geographic maps. This is important in practical terms because this strategy can beapplied to ascertain population structure and gene flow events when previous genetic information on the populations analyzed is not high ,8.Clustering analyses carried out forcing K = 2 gave comparable results ; Table 2Aside fromthe nature and number of loci, other factors may influence the performance of geographical analyses of genetic diversity in complex scenarios, namely habitat connectivity, sampling density, and the metrics used for the assessment of genetic relationships.Habitat connectivity makes gene flow more or less difficult, leading to different correlations of allele frequencies . Both isHere, we have used well-known metrics (PCA eigenvector and admixture coefficients) to summarize genetic diversity because of their wide use in population genetics studies ,8,26. HoThe overall information provided contributes to give insights on whether either microsatellites or SNPs markers are useful for population genetics studies on structured populations. Large SNP arrays outperform microsatellite markers in identifying fine-scale population structuring due to a more precise assessment of the genotypic information of the individuals. However, for some practical termssuch as geographic studies of genetic variation, microsatellite markers sets can be still useful, particularly if research focuses on non-model organisms in which large-scale SNP arrays are not available or, simply, if either the funding or the availability of efficient hardware and software to handle such large datasets is limited. Furthermore, the current study clearly illustrates how fine-scale structuring can be difficult to interpret when not enough previous information on the history of the populations exists.


Percichthys trucha, using 53 sequenced microsatellite DNA markers. Fish (n= 835) were collected from 16 river systems (46 locations) spanning the species range on both sides of the Andes. Eleven watersheds drain to the Pacific, five of which are trans-Andean (headwaters east of Andes). The remaining five drainages empty into the Atlantic. Three analytical approaches  revealed evidence of historic drainage reversals: fish from four of the five trans-Andean systems  exhibited greater genetic similarity with Atlantic draining systems than with Pacific systems with headwaters west of Andes. Present-day drainage (Pacific versus Atlantic) explained only 5% of total genetic variance, while ancestral drainage explained nearly 27% of total variance. Thus, the phylogeographic structure of P. trucha is consistent with episodes of drainage reversal in multiple systems and suggests a major role for deglaciation in the genetic and indeed the geographical distribution of P. trucha in Patagonia. The study emphasizes the significant role of historical processes in the current pattern of genetic diversity and differentiation in a fish from a southern temperate region.The rise of the southern Andes and the Quaternary glacial cycles influenced the landscape of Patagonia, affecting the phylogeographic and biogeographic patterns of its flora and fauna. Here, we examine the phylogeography of the freshwater fish,  The glacial cycles of the Quaternary often figure prominently among these factors –3. Our gThe processes usually described as the two most important factors in South America are the uplift of the Andes, which began approximately 23 Ma , and theAs the climate warmed following the LGM and glaciers began to melt, there were significant changes to the Patagonian landscape, especially along the backbone of the Andes. As the glaciers retreated, large proglacial lakes formed in several places along the eastern flank of the Andes –41. KnowPercicthys trucha and Galaxias platei based chiefly on mitochondrial DNA (mtDNA) polymorphism [P. trucha, over its entire geographical range on both sides of the Andes (16 drainages and 46 sampling locations) (n= 835). The use of a high number of sequenced nuclear microsatellite markers provides two advantages: (i) it addresses the general concern common to most phylogeographic studies, that patterns based on mtDNA polymorphism reflect the coalescence time and evolutionary history of a single gene, and not necessarily that of the organism a whole; and (ii) their relatively high mutation rate resulting in high polymorphism makes microsatellite markers particularly useful for phylogeographic studies, that both focus on relatively short time frames (e.g. Late Pleistocene–Holocene to present) and examine patterns at a finer geographical scale than may often be feasible with mtDNA. We examined the potential consequences that the major climatic cycles of the Quaternary and the resulting changes in regional geomorphology had on the distribution of genetic diversity, and indeed on the geographical distribution of the species. We assess whether the phylogeographic patterns described for P. trucha using mtDNA haplotypes [It has been pointed out previously that phylogeographic patterns for morphism ,22, are morphism ,40. Herecations)  and usin2.(a)Percichthys trucha, a freshwater fish species native to Patagonia and neighbouring regions to the north, is widely distributed throughout the region. The species is not harvested nor is it the focus of recreational angling, which in Patagonia focuses on introduced salmonids. The species has not ever been the subject of supplementation with hatchery reared fish in any of the river systems visited for this study. Current phylogeographic and genetic diversity patterns can thus be safely considered to be solely the result of natural, biogeographical and geomorphological processes and drivers.n= 835 Percichthys trucha collected from 16 systems throughout the geographical range of the species in Patagonia 3, were digested in proteinase K  at 55°C for 8 h. A glassmilk protocol modified from [Caudal fin clips and blood samples, both approximately 2 mmied from  was used(c)Information on primer design and testing is available in the electronic supplementary material.(d)egasat [egasat were manually verified to ensure correct allele call. Microsatellite loci were removed from further analysis if they did not amplify, were too difficult to score accurately, or were monomorphic. In total, 14 out of 75 loci were removed for these reasons. The remaining 61 were amplified  and sequenced for the remaining samples. Additional loci filtering steps occurred once data had been collected for all 835 individuals. These steps included removing loci which contained null alleles (identified using Microchecker [ayeScan v. 2.1 [Genotyping was conducted using Megasat . Microsaochecker ), exhibin v. 2.1  was run,(e)tructure 2.3.4 [tructure analysis. Structure was run using 500 000 Markov chain Monte Carlo permutations and 100 000 burn-in steps with each K value replicated five times. We used the Evanno method [tructure Harvester v. 0.6.92 [We used the program Sre 2.3.4  to asses. 0.6.92  to deterlumpp 1.1.2 [istruct 1.1 [optree2 [FST values were not calculated owing to the high variation in sample sizes , which can bias estimates [Cpp 1.1.2  was usedruct 1.1 . Poptree[optree2  was used[optree2 . The phy[optree2 . Pairwisstimates .rlequin 3.5.2.2 [P. trucha populations inhabiting trans-Andean systems (those with headwaters east of the Andes but draining into the Pacific Ocean) are more closely related to other Atlantic draining systems than they are to Pacific draining systems. We subsequently repeated this analysis changing the grouping of one trans-Andean system at a time to examine each system's relative influence on patterns of genetic diversity. Arlequin 3.5.2.2 [Two analyses of molecular variance (AMOVA) were performed using A 3.5.2.2 . In the  3.5.2.2  was usedPercichthys populations in Chile, including those in the southern Chile, are not P. trucha, but a different species entirely, Percichthys chilensis, a view the genetic and phylogeographic data we report in this study do not support (see below).We acknowledge that some authors  consider3.(a)n=835 individuals genotyped at a panel of 53 microsatellite loci, sample sizes per population were relatively small . We tested for LD between pairs of loci in the nine collections available with n ≥ 30 . We found no evidence of LD that was significant and consistent across the nine populations tested. We also tested for evidence of selection using all 46 collections, and subsets with relatively large sample sizes. These included the nine collections with n ≥ 30, the four collections within the Limay-Negro system  and the two collections within the Maullín system (both n ≥ 27). While 18, 9, 1 and 0 loci showed up as outliers in each of these tests, respectively, there was no consistency in the identity of the outlier loci across more than two of these four tests. We conclude there is no meaningful evidence of selection in any of these loci and all were retained in all subsequent analyses.Although the entire dataset consisted of (b)The neighbour-joining tree clusters all Chilean populations north of latitude 42° S together and separate from all other populations to the east in Argentina and to the south regardless of whether they drain into the Atlantic or Pacific Oceans . Within (c)In the first analysis, when populations were grouped according to present-day drainage (Pacific versus Atlantic) irrespective of whether their headwaters lie east or west of the Andes, the percentage of the total variation explained by the variance among groups is 5% . By contrast, this percentage was 26.94% when the collections from the trans-Andean systems: Puelo, Futalaufquen/Yelcho, Baker and Pascua were grouped according to their presumed ancestral drainage direction  .We then examined the relative influence of each one of these systems  on the percentage of variation explained by the variance among groups by grouping them one at a time with the Pacific draining systems. A small decline in the percentage of the variance explained by differences among groups would indicate the system had little influence in the distribution of genetic variance between the Pacific and Atlantic draining groups. In all cases, the percentage of the variance explained by differences among groups dropped considerably from 27% when their ancestral drainage was assumed to have been the Atlantic , to 15.45%, 21.75% and 11.23% when grouping each of Puelo, Futalaufquen/Yelcho and Baker individually with all other Pacific draining systems . The percentage of genetic variation explained by the differences between groups also dropped when pooling the collections from the Pascua River with their contemporary Pacific drainage, but only to 25% . This is not surprising given that only 10 individuals were available from a single location (Lake San Martín) within this system.(d)tructure analyses were conducted at four hierarchical levels. At the highest level, all 16 systems organized by drainage and latitude were analysed together. At this level, K = 2 (a), with the first cluster comprising P. trucha individuals from all systems in Chile north of latitude 42° S. These include the collections from Maipo and Nilahue at the northern edge of the species distribution to the collections from the Maullín system in the south. The second cluster comprises all collections from systems with headwaters east of the Andes from latitude 33° S to 50° S regardless of contemporary drainage . Notaby, the collections from the northern edge of the species distribution in Chile  and in Argentina  appear to exhibit some level of admixture (a).Sl, K = 2 a, with tdmixture a.Figureb) examines separately collections from the two clusters above. At this level, P. trucha from Maipo and Nilahue (populations 1 and 2) appear genetically distinguishable from those from the Rapel and Biobío systems (populations 3–5) and both groups are distinct from collections form further south including those from the Valdivia, Bueno and Maullín systems (populations 6–14), which at this hierarchical level appear indistinguishable from each other (b). The populations with headwaters in Argentina (populations 16–46) clustered into two groups, again indicating a latitudinal divide with the more northern river systems  grouping together, and a second grouping composed of the more southern systems  (b). At the third hierarchical level (c), we found: (i) no discernable difference between fish from the Maipo and Nilahue rivers with Nilahue containing some migrant and admixed individuals (c); (ii) significant differences between collections from the Rapel and Biobío systems (populations 3 versus 4 and 5); and (iii) the remaining populations in this pool (populations 6–14) clustering into two groups and thus requiring a fourth hierarchical level of analysis where differences are uncovered among the Valdivia (populations 6–8), Bueno (populations 9–12) and Maullín systems (d). We also found differences between and among Atlantic and trans-Andean draining systems to the south as well as among some of the sampling locations (lakes or rivers) within each of these systems (c). Analyses at this fourth hierarchical level were also conducted with collections from the Baker (populations 32–41) and those from the Chalia, Pascua and Santa Cruz river systems (populations 42–46), where genetic differences are manifested among populations within rivers systems probably largely as a result of genetic drift (d).The second hierarchical level b examinech other b. The pota Cruz) b. At theal level c, we fouividuals c; (ii) s systems d. We als systems c. Analysic drift d.4.P. trucha populations from throughout the species' range reflecting both the role of the Andes as a geographical barrier to dispersal and that of the glacial cycles of the Quaternary  located west of the Andes and north of where the ice sheets reached the Pacific coast during the LGM (latitude 42° S), served as the source(s) for recolonization of some of the northern river systems west of the Andes. Percichthys trucha also survived the LGM in at least two refugia east of the Andes and east and/or north of the ice sheets, one in north-central Patagonia, and the other in southern Patagonia . Atlantic-draining river systems were recolonized from these refugia, and there is a clear distinction between northern systems which were recolonized from the north and/or east, and southern systems which were recolonized from a distinct and probably more southerly refugium. The refugia east of the Andes were also the source of post-glacial colonists for at least five Pacific-draining river systems. These systems all have headwater lakes east of the Andean divide and were probably recolonized during the early stages of deglaciation, when they drained towards the Atlantic. As the glaciers receded, these drainages reversed direction, and currently flow towards the Pacific, but retain P. trucha populations derived from the eastern refugia. In fact, these are the only populations of P. trucha west of the Andes and south of 42° S, indicating (i) the absence of post-LGM north to south migration into this region, and (ii) that unlike Galaxias platei [P. trucha did not persist in small glacial refugia west of the Andes where the ice sheet reached the sea.In this study, we describe a pattern of genetic divergence among  000 BP; ) in forcatagonia a,b. Atlas platei  and othes platei ,34, P. tP. trucha populations occupying Atlantic drainages, and those in most Pacific drainages, supports the rise of the Andes (beginning an estimated 23 Ma [The deep differentiation between ed 23 Ma ), as theed 23 Ma –61, whiced 23 Ma ,22, thised 23 Ma –61 culmied 23 Ma ). Some sed 23 Ma ,62; figued 23 Ma  this stued 23 Ma ,33.egasat [P. trucha. These patterns are consistent with the presence at least two glacial refugia east of the Andes during the LGM, and at least one, and probably more refugia west of the Andes in central Chile (north of 42o S where the ice did not reach the sea). Our study also provides genetic evidence that is consistent with geographically separated and multiple episodes of drainage reversal that influenced the distribution of genetic diversity of P. trucha throughout most of its latitudinal range. We discuss the evidence for an influence of drainage reversal on patterns of genetic diversity and species distribution in more detail below.Our results demonstrate the power of a relatively large suite of nuclear microsatellite DNA markers to unravel phylogeographic patterns in a widespread freshwater fish, an approach made possible by the recent development of sequence-based protocols and software for microsatellite genotyping . Such pregasat  platform(a)P. trucha currently inhabiting river systems with their headwaters west of the Andean divide are all found north of 42° S, where the ice sheet did not reach the Pacific coast during the LGM [Populations of  the LGM . These pAbrothrix olivaceus and the steppe-dwelling mouse Abrothrix xanthorhinus [Among the other Pacific draining systems with headwaters west of the Andes, we find less genetic differentiation than for the northern four systems but more than is seen among the Atlantic draining systems (note branch lengths in horhinus . Gene fl(b)P. trucha comprise all major river systems that currently drain into the Atlantic Ocean  and several Pacific-draining, trans-Andean systems  . There is strong evidence from geomorphological studies of the Baker [ca 12 000 BP [P. trucha populations in the Baker system with populations in Atlantic-draining systems at similar latitudes is thus consistent with the geomorphological findings. In this study, we have identified three additional river systems that have probably undergone post-LGM drainage reversals: the Puelo, Futalaufquen/Yelcho, and the Pascua systems. All are trans-Andean systems, Pacific drainages with headwaters east of the Andes, and all contain populations of P. trucha that resemble populations from Atlantic drainages at similar latitudes. It is known that proglacial lakes extended over broad latitudinal ranges (42–49° S and 51–53° S) [Thus, the northern and southern genetic groupings both contain populations of  Pacific b,c. Therhe Baker ,40–41 trhe Baker ,37,39,712 000 BP ), and th2 000 BP ,38–40 an1–53° S) , but to Percichthys trucha inhabiting the trans-Andean Valdivia river system  comprise an exception to the pattern of higher genetic similarity with Atlantic than with Pacific draining systems described above for the other four southern trans-Andean systems . Grouping the collections from the Valdivia system (i.e. Panguipulli and Neltume) with those of Atlantic drainage decreased the percentage of genetic variation explained by groups (from approx. 27% to 25%) suggesting that P. trucha inhabiting these lakes originate from ancestral populations that survived in local refugia, probably preventing the dispersal and expansion of P. trucha from east of the Andean highest peaks by a ‘Founder takes all' effect [' effect .P. trucha populations outside of trans-Andean river systems. Drainage reversals are thus the only mechanism by which P. trucha was able to colonize this region after the glaciers receded, and there appears to have been no gene flow between drainages since that time. Drainage reversals are thus responsible, not only for patterns of genetic diversity, but also for the current geographical range of the species. This pattern of distribution is shared with at least one other native Patagonian fish, a catfish of the family Diplomystidae [South of latitude 42° S, where the ice sheet reached the Pacific during the LGM, there are no mystidae , providiP. trucha, a widespread Patagonian fish, colonized the western side of the Andes from the eastern side, and that this occurred in at least four distinct river systems, the Puelo, the Futalaufquen/Yelcho, the Baker, and the Pascua systems. While detailed geomorphological evidence exists only for the Baker system [P. trucha, one (possibly more) west of the Andes north of 42° S, and the other two, east of the Andes, the first in northwestern and northern Patagonia and the second on the southern Patagonian steppe. Conversely, we find no evidence that P. trucha survived the LGM west of the Andes south of 42° S. The presence of P. trucha populations west of the Andes in these southern regions is a consequence of dispersal from the east, most likely owing to drainage reversals that took place in several river systems following the LGM. Our study, therefore, highlights the synergistic value of combining genetic data from a large panel of sequenced microsatellite DNA with information on landscape evolution to develop and test biogeographic hypotheses.In summary, we have presented evidence based on a suite of 53 sequenced nuclear microsatellite DNA markers that, after the LGM, r system , drainag


Odorrana grahami is widely distributed in the high-altitude mountains in the southwestern China and northern Indochina regions. In this study, a comparative analysis of the mitochondrial COI gene sequences was performed to examine the population genetic diversity of 76 individuals from 10 localities across the distributional range of the species. Haplotype diversity and nucleotide diversity were 0.605 and 0.00199, respectively, in the total population. An AMOVA indicated that 47.3% of the total variation originated from variation within individual populations and 52.7% came from variation between the 10 geographic populations. Tests of neutral evolution indicated that a recent expansion occurred in total population. The findings provide useful information for the conservation of this species.The diskless-fingered odorous frog  Odorrana grahami is a member of the family Ranidae. It is commonly found in the high altitude (1150–3200 m) mountain streams in southeastern Asia, ranging from southwestern Sichuan, western Guizhou, and Yunnan provinces of China to northwestern Myanmar and northern Vietnam of Indochina  scattered in the distributional range of rn China ; Table 1rn China . Primersh) and nucleotide diversity (π) were estimated using DnaSP 5 , as implemented in Arlequin 3.11  for use as outgroup. For ML analyses, the best-fitting nucleotide substitution model was selected by likelihood ratio tests under the Corrected Akaike Information Criterion (AICc) implemented in JMODELTEST 2.1.7 (Guindon and Gascuel Phylogenetic relationships of haplotypes were reconstructed using maximum likelihood (ML), as implemented in the program PHYML 3.0  = 51.7% significantly higher than (C + G) = 48.3%. Eight haplotypes were recognized from 76 individuals of 10 populations of  grahami . All hap grahami ; Table 2The estimated haplotype diversity and nucleotide diversity are shown in D value was negative but not significant (p > .05), and Fu’s Fs value was significantly negative, suggesting the recent population expansion , and then H5 was clustered with this lineage (bs = 65), but haplotypes H6–H8 were almost parallel at the base of the tree. Haplotype network presented: H1 and H6 were occupied by 34 samples, respectively; H1 was linked to H6 through H5; H2–H4 each independently linked to H1; and H7 and H8 each independently linked to H6  were indicated as the domain haplotypes in the populations. H1 was occupied by 34 individuals of nine populations and H6 was also in 34 individuals from three populations, and as noted, they were linked through the third haplotype (H5). This result indicated that the species has been possibly divided into at least two lineages. ML analyses also basically fitted this model. Merely, divergence of the lineages was still shallow  occupied at least three different haplotypes, which could be commonly indicated as the dispersal center . Yet, weO. grahami, the genetic diversity and diversification level were considerably low, indicating that it might be a young species. Population with low genetic diversity was usually proposed to be experienced bottleneck effects (Miracle and Campton O. grahami frogs and their habitats, for example, the populations P3 and P5 with higher genetic diversity should be key protected populations for this species.Totally, in


For better application in human forensic cases and population genetics research, it is imperative to investigate the genetic characteristics of Guanzhong Han population using enhanced Y‐chromosomal short tandem repeats (Y‐STR) detecting system with higher discriminating power than previous ones.In this study, 38 Y‐STRs were profiled in 430 unrelated Chinese Han male individuals from Guanzhong region of Shaanxi Province, Northwest China, using the Yfiler™ Platinum PCR Amplification Kit. Haplotype frequencies and forensic parameters were calculated. Comprehensive population comparisons with geographically/ethnically different populations in China and other worldwide countries were performed.A total of 422 different haplotypes were observed with the overall haplotype diversity (HD), discriminatory power (DC) and haplotype match probability (HMP) were 0.9999, 0.9814, and 0.0024, respectively. Guanzhong Han showed genetically affinity with Han ethnicity from Shanxi and Henan provinces, while far distant from Tibetan populations.This study offered a unique insight into Guanzhong Han population, the 38 Y‐STRs included in the the Yfiler™ Platinum system are highly polymorphic and informative and can be used for forensic practice and human genetic research. Thirty‐eight Y‐STR haplotype data in the Chinese Shaanxi Han population of 430 unrelated males were first reported using the Yfiler™ Platinum PCR Amplification Kit. Our findings in the present study indicated that the 38 Y‐STR loci were informative in the Guanzhong Han population and can be used as a powerful tool in forensic practice and population genetic study. Shaanxi Han showed genetically affinity with Han ethnicity from neighboring Shanxi and Henan province, while far distant from Tibetans in China. As one https://www.yhrd.org), aiming at forensic and population genetics application in a specific population  loci with paternal lineage and haploid genetic feature, play a unique role in solving special forensic cases: revealing male donor of mixed stain for sexual assault cases, inferring paternal lineage origin and biogeographically ancestral information, and so on  and 3 Y‐InDels  of the studied population. Then, population phylogenetic relationships exploration with geographically/ethnically distinct Chinese and world populations was performed.22.1https://yhrd.org/), one consists of 19 other Chinese populations belonging to 13 ethnicities widely distributed in China, the other comprises 14 comparative populations around the world.A total of 430 unrelated Han male individuals were recruited who live in Guanzhong region of Shaanxi Province, Northwest China for at least three generations. Genomic DNA from blood samples was isolated using the Blood DNA Miniprep System (Promega) and the DNA concentration was quantified with Nanodrop‐2000 (Thermo Fisher Scientific) according to the manufacturer's instructions. The study was reviewed and approved by the Ethics Committee of Affiliated Hospital of Zunyi Medical University. For population genetic structure exploration, two reference population data sets were retrieved from the YHRD database (2.2® ID‐X software (Thermo Fisher Scientific). Negative control (H2O) and positive control (007) were genotyped in each batch of DNA amplification. We strictly followed the recommendations for the DNA commission of the International Society of Forensic Genetics (ISFG) in the present study  following the manufacturer's instructions. Amplified fragments were detected by capillary electrophoresis on the Applied Biosystems 3500 Genetic Analyzer (Thermo Fisher Scientific). The electrophoresis data were automatically analyzed by GeneMapper2.3n (1 − Σpiai2)/(n − 1), HD = n (1 − Σpihi2)/(n − 1), HMP = Σpihi2, where n represents the number of tested samples, and piai/pihi means the relative frequency of the ith genotypes/haplotypes, respectively , The genetic distance (Rst) and corresponding p values based on the 27 overlapped Y‐STRs were calculated. Multidimensional scaling analysis (MDS) was also constructed by aforementioned online tool on the basis of the Rst values.Allele and haplotype frequencies were determined by direct counting. genetic diversity (GD), haplotype diversity (HD) and haplotype match probability (HMP) were calculated using the following formulas: GD = ely Nei, . The disely Nei, . Populat3In the set of results, the haplotype distribution and frequencies are presented in Table Allele frequencies and the GD values of the 38 Y‐STR loci in 430 Guanzhong Han males are listed in Table p = .05/190 = 0.000263 after Bonferroni correction). The minimal genetic distance was observed with Shanxi Han (Rst = 0. 0038), followed by Henan Han (Rst = 0. 0081), while the largest genetic distance was found with 3 Tibetan populations from Sichuan (Rst = 0.2388), Qinghai (Rst = 0.1551), and Chamdo of Tibet (Rst = 0.1421). As shown in Figure To further describe population genetic relationships, Rst and MDS were conducted based on the raw data of 27 overlapped Y‐STR loci with the online tool at YHRD. We first carried out population comparison at the domestic level. According to their geographic positions and ethnic origins, 19 previously reported Chinese populations belonging to Han majority and 11 ethnic minorities from distinct provinces were chosen as reference populations  was obviously displayed between Guanzhong Han and all others. Rst values ranged from 0.0585  to 0.2501 (Guanzhong Han and Ireland Irish [Aliferi et al., Further comparison at the worldwide level was implemented based on our investigated population with 14 representative populations from different continents and regions. As Rst and corresponding p values calculated in Table For comparisons based on both nationwide and worldwide, obvious geographic and ethnic cluster features were demonstrated in this study via MDS. In spite of this, the diminutive genetic distances were observed between Shaanxi Han and Northwest Chinese Hui. As Northwest China's major groups once active in the ancient silk road, Hui mixed dwelling with the Han population due to commercial logistics and marriage since the Tang Dynasty, and thus the two populations had a close genetic relationship (Xie et al., 4In conclusion, this is a report to characterize the overall population and forensic genetics of Guanzhong Han population in China using Y‐STRs patterns. Our report disclosed the haplotype and forensic parameters based on 38 Y‐STR loci. The data showed highly polymorphic and informative in Guanzhong Han population and could be regarded as a valuable tool in forensic application and population genetic study. As a typical group residing in northwest area of China, population comparisons showed genetic affinity with geographic adjacent Han populations and remarkable genetic differentiation with Tibetan populations. Moreover, we observed Guanzhong Han had the close genetic relationship to East Asian populations by the result of genetic structure reconstruction, which indicated that the worldwide population substructures generally adhered to geographical distribution. For a better and in‐depth understanding of genetic background of Han population from Guanzhong region of Shaanxi province, more molecular genetic markers might be added in the future.No potential conflict of interest was reported by the authors.PYC and LYL conceived the idea for the study. FQJ, HLG, YD, and ML performed or supervised laboratory work. XH and GLH analyzed the data. PYC, LYL, and LLY wrote and edited the manuscript. Click here for additional data file.


Rattus norvegicus) and black rats (R. rattus) are among the most invasive animals on the planet, with eradication being the primary tool for established island populations. The need for increased research for defining eradication units and monitoring outcomes has been highlighted as a means to maximize success. Haida Gwaii is an archipelago ~100 km off the northern coast of British Columbia, Canada, that hosts globally significant breeding populations of seabirds that are at risk due to invasive rats. Here, we paired sampling of brown (n = 287) and black (n = 291) rats across the Haida Gwaii archipelago with genotyping by sequencing  to investigate patterns of population connectivity and infer levels/direction of gene flow among invasive rat populations in Haida Gwaii. We reconstructed three regional clusters for both species , with proximate populations within regions being largely more related than those that were more distant, consistent with predictions from island biogeography theory. Population assignment of recently detected individuals post‐eradication on Faraday, Murchison and the Bischof Islands revealed all were re‐invaders from Lyell Island, rather than being on‐island survivors. Based on these results, we identified six eradication units constituting single or clusters of islands that would limit the potential for reinvasion, some of which will need to be combined with biosecurity measures. Overall, our results highlight the importance of targeted research prior to conducting eradications and demonstrate a framework for applying population genomics for guiding invasive species management in island systems.Invasive species have led to precipitous declines in biodiversity, especially in island systems. Brown ( Even if dispersers are detected, the origin of these individuals may remain unknown if the vessel docked at multiple ports or adjacent to rat‐infested islands en route. Additionally, fine‐scale environmental data that influence dispersal (such as velocity of ocean currents through a passage) may simply not exist, and even well‐documented natural barriers to gene flow may be rendered insignificant due to the commensal spread of invasive rats.Understanding dispersal patterns, population connectivity and subsequent gene flow of invasive species provides critical information for developing management strategies to reduce or ameliorate their impacts on biodiversity and ecosystem services  across numerous islands located off the coast of Brittany, France, at eight microsatellites, revealing extensive gene flow to the degree that islands within a few hundred metres of each other should be considered a single population. Robertson and Gemmell  rats have invaded Haida Gwaii (X̱aayda Gwaay in Haida), an archipelago ~100 km off the northern coast of British Columbia often likened to Canada's version of the Galápagos Islands due to high levels of unique biodiversity, rare species and endemism , Cassin's auklet , fork‐tailed storm petrel (Oceanodroma furcate), Leach's storm petrel (O. leucorhoa), rhinoceros auklet (Cerorhinca monocerata) and tufted puffin (Fratercula cirrhata)  is ineffective in species with high fecundity, density‐dependent reproduction and the capacity to adapt through bait resistance or neophobia  of recent invasions, including an explicit testing of the survivor and re‐invader hypotheses in the Bischofs, to evaluate existing eradication methodology and inform biosecurity measures.22.1e.g. ravens, eagles) and to keep rats dry once captured. As rats are primarily nocturnal, the traps were set in the late afternoon or early evening and baited with a combination of canned sardines and the commercially available rodent attractant Provoke , and checked the following morning. This process was repeated for up to 3 days for each sampling excursion at each location. Upon successful capture, rats <250 g were first anesthetized using isoflurane and then euthanized via cervical dislocation; rats >250 g were euthanized with a strong dose of isoflurane. Whole ears were removed for downstream genomic analysis. Sample collection was performed under Parks Canada Agency Animal Care Committee protocol GHNPR11‐5.All sample collection was performed by Parks Canada staff from 2008 to 2018. Based on qualitative morphological assessment in the field, 287 putative brown rats, 296 putative black rats and 15 morphologically ambiguous rats were sampled across 12 islands throughout Haida Gwaii Figure , 2019b. 2.2® Blood and Tissue Kit and treated with RNase A (5PRIME) following the manufacturer's protocol. Double‐digest restriction enzyme‐associated DNA sequencing (ddRAD) libraries were constructed using a modified protocol described by Puckett et al. (® Inc.), and a unique combinatorial barcode and index (New England Biolabs® Inc) was ligated onto the 5′ and 3′ ends of the resultant fragments, respectively. Barcoded individuals were pooled in equimolar concentrations into libraries . Approximately 400bp fragments were size‐selected using a Pippin Prep™ (Sage Science), and the size‐selected libraries were PCR amplified for 12 cycles using Phusion PCR reagents (New England Biolabs® Inc). In total, seven libraries were constructed, with samples replicated within (n = 11) and among (n = 13) libraries to evaluate genotyping error rates. Libraries were sequenced using one full lane of Illumina HiSeq 2500 PE125  per library.Whole genomic DNA (gDNA) was extracted from 10 to 20 mg of dried ear tissue using the Qiagen DNeasyt et al. . Approxi2.3process_radtags command in stacks v2.0  were removed from downstream analysis.Raw sequence reads were demultiplexed to individuals using the gstacks and populations programs in stacksv2.0  and have a minor allele frequency exceeding 5% (min_maf = 0.05). This initial data set was used to designate individuals to species, as morphological identification can be difficult with juveniles as well as for some phenotypes. To assign individuals to species, we used a discriminant analysis of principle components as implemented by the R‐package adegenet v2.1.1  to call a SNP from 0.70 to 0.95 and the minimum minor allele frequency (‐‐min_maf) from 0.01 to 0.05 to identify optimum parameters. Only a single SNP per RADtag was retained (‐‐write_single_snp) to minimize the potential for linkage disequilibrium, and the maximum observed heterozygosity (‐‐max_obs_het) was set to 0.50 for all filtering iterations. Individual mean depth, missing data per individual, number of SNPs and number of individuals with ≥6× depth of coverage were calculated for each filtered data set using VCFtools v0.1.15  deviation from Hardy–Weinberg equilibrium (HWE) using VCFtools v0.1.15 .To examine whether the interior of Kunghit Island was acting as a barrier to dispersal, we calculated the shortest distance between each pair of populations along the shoreline , allowing for movement up to 1 km from the coastline, as this has been previously proposed to be the maximum extent of rat movement inwards on islands Harper, . We test2.6We evaluated rates of recent migration among populations using a Bayesian framework as implemented by the software BA3‐SNPs v1.1.0 . Additionally, the pre‐eradication population was considered as a reference population under the survivor hypothesis. For the Faraday and Murchison Island invasions, Lyell Island, Richardson Island, the post‐eradication population in the Bischof Islands and the town of Tlell, BC (Graham Island), were examined as the putative source. These populations were again chosen for their proximity, except in the case of Tlell, which was considered because recent lumber shipments from Tlell to Faraday Island posed a potential introduction pathway. We also assigned individuals to populations following the method outlined by Rannala and Mountain . Mean within‐ and among‐library genotyping error rates were 2.0% and 2.6%, respectively, for the brown rats and 4.2% and 2.5% for the black rats . Differentiation among sample sites on Lyell Island was low ; as such, all were grouped into a single Lyell population. Brown rats sampled from Arnold Point, Bowles Point and Gilbert Bay on Kunghit Island were not significantly differentiated, and rats from Hornby Point displayed low, but significant differentiation from these sites ; consequently, these sites were grouped into a single “NW‐Kunghit” population. There was significant, albeit low, differentiation among the east Kunghit sample sites of Marshall Island and Keeweenah Bay; as such, these sites were grouped into a single “E‐Kunghit” population. The Luxana Bay population displayed low‐to‐moderate differentiation from both the NW‐ and E‐Kunghit populations and was grouped with the E‐Kunghit population due to geography; additionally, the Rainy Island population was not significantly differentiated from any of the Kunghit sites and was also grouped with the E‐Kunghit population due to geography.Genetic diversity was high across all brown rat populations except for the Tlell (Graham Island) population, which had relatively lower levels of heterozygosity and effective number of alleles, and higher levels of inbreeding Table . We deter = .790; p < .001) and the shoreline distance  among Kunghit Island sample sites. Shoreline distance was more strongly correlated with genetic distance than Euclidean distance, though the difference was marginal.We found significant isolation‐by‐distance patterns using both Euclidean distance . There was low‐moderate differentiation (pairwise θ = 0.07–0.12) between the Faraday Passage and all other Lyell Island populations, but low differentiation (pairwise θ < 0.06) among the remaining Lyell sample sites.Genetic diversity across black rat populations was also high, though Graham Island did show low levels of inbreeding Table . Overallθ estimates . Lyell and its surrounding islands formed a centrally located cluster with some differentiation among island populations detected. We found low levels of differentiation among these islands, suggesting that there is some gene flow. Interestingly, Kunga Island was strongly differentiated from even the proximate Tanu Island  and represented a unique genetic cluster across all analyses, despite the fact that significant migration rates have been recorded between brown rat populations at this distance over open ocean in the Falkland Islands  likely due to geographic isolation, as these populations are well beyond the dispersal capacity for rats (>50 km apart)  by rapidly expanding their population numbers; in fact, the eradication of black rats on Faraday Island and Murchison Island may have even facilitated the brown rat invasion by removing any source of competition . Floating across on naturals rafts of debris, such as logs with roots, is another potential vector of unaided dispersal, especially during high tides , dispersal from Lyell Island to the Bischof Islands likely occurred without human intervention . These invasive rat populations represent a significant biosecurity threat. Ramsay Island is situated 900–1000 m from Hotspring Island and hosts the most ecologically significant seabird colony in the Gwaii Haanas National Park  is currently the only effective method of eradication   after consumption of poison bait and consumption of poisoned rat carcasses, and brodifacoum residue was detected in blood samples from bald eagles  was recently declared rat‐free following a multi‐year eradication effort  could be used to address these same basic questions, while also adding a layer of information for planning future eradications (McRae, Here, we have provided a clear framework highlighting the utility of genomic analyses to managing invasive species. Future work could use these approaches for better understanding the mechanisms behind invasive species establishment and spread (Facon et al., s McRae, . Since ls McRae, , these ds McRae,  that pre Click here for additional data file.


Rhinopithecus roxellana) are considered as a flagship species in this area. Here, we depicted the genetic structure and evolutionary history via microsatellite markers and combination with the ecological niche models (ENMs) to elucidate the intraspecific divergent and the impacts of the population demography on our focal species. Our results revealed three distinct subpopulations of R. roxellana and also uncovered asymmetric historical and symmetric contemporary gene flow that existed. Our evolutionary dynamics analyses based on diyabc suggested that the intraspecific divergence accompanied with effective population sizes changes. The ENM result implied that the distribution range of this species experienced expansion during the last glacial maximum (LGM). Our results highlighted that geological factors could contribute to the high genetic differentiation within the R. roxellana in the Qinling Mountains. We also provided a new insight into conservation management plans with endangered species in this region.The Qinling mountainous region is one of the world's biodiversity hotspots and provides refuges for many endangered endemic animals. The golden snub-nosed monkeys ( Historical processes such as geographic changes and human activities have greatly affected patterns of dispersal and genetic migration among populations; these processes could restrict gene flow and accelerate genetic differentiation through inbreeding and genetic drift , and its current estimated population size is no more than 20,000 individuals  at a small scale within the Qinling Mountains  whether and how the gene flow impacted its genetic structure.In this study, using microsatellite data, we evaluate the genetic diversity and gene flow within the Qinling populations and also investigated its complicated evolutionary history. We attempt to figure out the following: (i) whether the golden snub-nosed monkey was threatened by genetic homogeneity in fragmented habitat and, if so, (ii) whether the historical shifts facilitated the current genetic differentiation within We collected a total of 344 fecal and hair samples of five representative populations scattered among five counties , which spread over five National Nature Reserve  solution at −20°C . All samples were amplified based on the primers of 19 tetra-nucleotide microsatellite loci (see genemapper V3.7 (Applied Biosystems). To prevent genotyping errors such as false allele and allelic dropout, homozygote genotypes were confirmed by five independent replicates, with all heterozygotes observed and confirmed by at least three separate reactions , observed heterozygosity (HO), expected heterozygosity (HE), polymorphic information content (PIC), allelic richness (AR), and Wright's inbreeding coefficient at each locus utilizing genaiex V6.5  with 95% stepwise mutations and a variance of 12 and (ii) a stepwise mutation model (SMM) with iteration number set to 1,000. The second method involved calculation of the GW coefficient in arlequin V3.6  across loci with the 100,000 permutations with arlequin V3.6  of genetic clusters with the program structure harvster   among the five populations based on the microsatellite datasets. We performed maximum-likelihood analyses in migrate-n v 3.6 using three long chains  and 10 short chains , and the burn-in was set as 10,000. We repeated this procedure five times to obtain the average maximum-likelihood estimates with 95% confidence intervals (CIs).To explore the historical genetic gene flow of  Beerli,  to assesbayesass v3.0  was used in diyabc v 2.04  and the National Specimen Information Infrastructure . In total, 131 georeferenced points were obtained.Ecological niche modeling (ENM) analyses were performed with www.worldclim.org)  were retained for subsequent analyses  across the five populations. The location, population size, and sample size of each band are presented in A total of 361 samples were collected. After exclusion of 44 repeated samples as determined by microsatellite profiles, we eventually established a dataset consisting 317 individuals. With the use of HO) ranged from 0.563 to 0.624, averaging 0.595; expected heterozygosity (HE) was from 0.558 to 0.672, averaging 0.623; the polymorphism information content (PIC) was from 0.473 to 0.538, averaging 0.511; and allelic richness ranged from 2.342 to 2.642, averaging 2.511 for the populations. The values of Wright's inbreeding coefficient (FIS) showed that the effect of inbreeding to five populations was weak.The genetic diversity indices of each band are also presented in P-value was 0.060 (Wilcoxon test under TPM model in DPY). The GW coefficients of all bands were above the empirical value 0.132 .No evidence of bottleneck effects has been found from the microsatellite data for each population. The results of bottleneck effects tests are shown in FST and permutation test revealed a relatively low but significant genetic divergence among those five bands  (the probability of the data given K and the model) and ΔK  for GNG, 0.4262 (95% CI: 0.4038–0.4502) for DPY, 0.2567 (95% CI: 0.2427–0.2719) for SZZ, 0.6696 (95% CI: 0.6341–0.7078) for HTP, and 1.4484 (95% CI: 1.3051–1.5423) for CYG.Our study revealed asymmetrical historical gene flow among the five populations by 54.1218;  and the 54.1218; . Moreovediyabc analysis, the posterior probability for scenario 8 (with 95% CI) was 0.914 (95% CI: 0.906–0.942), much higher than that of the other nine scenarios  and N3 (CYG populations) (t1) from the common ancestor was 1.95 × 105 generations ago, N2 (HTP populations) diverged from the N1, and N3 (t2) was 4.51 × 104 generations ago  was close to that of the other studies of this species  associated with topographical barriers such as mountain ridges, which might lead to the reduced gene flow between populations  existing within the monkeys of the Qinling Mountains . The first divergence in our focal species that formed N1 and N3 lineages from ancestral linage was at 0.975 Ma [95% highest posterior density (HPD): 0.33–2.86 Ma]. Based on the genetic analysis and fossil data from existing populations, snub-nosed monkeys are distributed across eastern, central, southern, and southwestern China in the past 2 million years , and formed The ENM analyses also suggested that the golden snub-nosed monkeys had expanded their ranges during the LIG (0.14–0.12 Ma) to LGM. At the end of the largest glaciation (ca. 1.2–0.6 Ma), the temperature increased, and also, the relatively cold climate may have continued until the late Ionian stage (0.3–0.126 Ma) , habitat loss, human's intentional killing due to economic reasons from the local culture, and natural disasters . Our new results of the evolutionary history with the R. roxellana could also shed light on species with the same geographical distribution, as well as other threatened or endangered amphibians and reptiles in this area.The Qinling Mountains are famous for their global biodiversity hotspot and refugia for many endangered mammals and birds, particularly during the last glaciation  can be found in the article/The animal study was reviewed and approved by Wildlife Protection Society of China.BL and YL conceived the study. YL and KH performed the experiments. YL, LF, JY, and ZL contributed materials and analysis tools. BL, YL, and ST wrote the manuscript. LF and JY revised the manuscript. All authors approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Mongolia is one of a few countries that supports over 25 million goats, but genetic diversity, demographic history, and the origin of goat populations in Mongolia have not been well studied. This study was conducted to assess the genetic diversity, phylogenetic status and population structure of Mongolian native goats, as well as to discuss their origin together with other foreign breeds from different countries using hypervariable region 1 (HV1) in mtDNA.In this study, we examined the genetic diversity and phylogenetic status of Mongolian native goat populations using a 452 base-pair long fragment of HVI of mitochondrial DNA from 174 individuals representing 12 populations. In addition, 329 previously published reference sequences from different regions were included in our phylogenetic analyses.Fst) and the analysis of molecular variance values among goat populations in Mongolia showed low genetic differentiation and weak geographical structure. In addition, Kazakh, Chinese (from Huanghuai and Leizhou), and Arabian  goats had smaller genetic differentiation compared to Mongolian goats.Investigated native Mongolian goats displayed relatively high genetic diversities. After sequencing, we found a total of 109 polymorphic sites that defined 137 haplotypes among investigated populations. Of these, haplotype and nucleotide diversities of Mongolian goats were calculated as 0.997±0.001 and 0.0283±0.002, respectively. These haplotypes clearly clustered into four haplogroups , with the predominance of haplogroup A (90.8%). Estimates of pairwise differences  occur in goat populations in Mongolia, with high levels of haplotype and nucleotide diversity. Capra hircus) is one of the earliest domesticated animals. Archaeological evidence suggests that the Fertile Crescent region in the Near East (NE) was the domestication center of domestic goats, and that this event occurred more than 10,000 years ago [Capra, bezoar (C. aegagrus), ibex (C. ibex) and markhor  are phylogenetically close to the domestic type (C. hircus), and it has been suggested that all these wild species contributed to the genetic composition of domestic goats [C. aegagrus is widely agreed to be the wild ancestor of domestic goats, as all haplogroups of domestic goat occur within current C. aegagrus populations [The domestic goat  is a critical tool for tracing evolutionary and population genetics of most domesticated animals. Also, mtDNA diversity is vital in assessing the maternal origin, phylogeny, and population structure of all domestic animals –13. PrevDue to their high economic importance, goats are considered as an important livestock species in Mongolia. In 2017, the estimated population of goats in Mongolia was 27.3 million, 41.3% of the total of 66.7 million heads of livestock . All goaAll sampling procedures in this study were carried out in accordance with the recommendations of “Guide for Care and Use of Agricultural Animals in Research and Teaching, 3rd edition” published by the Federation of Animal Science Societies (ISBN: 978-1-884706-11-0) and also “Guidelines for sampling and handling animals for purposes of Veterinary and Other researches” of Livestock sector of Mongolia, with full approval from Committee Ministry of Agriculture and Food of Mongolia . The protocol approved by Committee of Ministry of Agriculture and Food of Mongolia was used in this study. Animal owners had informed consent for inclusion of their animals in the study, and they involved sampling procedures.Sampling was conducted across Mongolian territory in 2017 and 2018. In this study, a total of 158 unrelated genetic samples that consisted of 97 blood (2017), 10 ear skin, and 51 tail hair (2018) were gathered from 11 different populations . We collhttp://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi) based on a reference sequence (accession number: NC_005044). Polymerase chain reaction (PCR) amplifications were performed on a total of 20 μL final volume that included 2.0 μL genomic DNA (20 ng/μL), 0.8 μL of each primer (10 pmoles/μL), 2.0 μL 10× reaction buffer, 1.6 μL dNTP, 0.2 μL prime Taq DNA polymerase, and 12.6 μL distilled water to adjust the final PCR product volume. The reaction conditions for amplification consisted of initial denaturation at 94°C for 3 min, followed by 35 cycles with denaturation for 30 s at 94°C, annealing at 55°C for 30 s, extension for 1 min at 72°C, and final extension at 72°C for 5 min. All PCRs ran with negative controls and were performed by a thermal cycler C1000 system . After amplification, approximately 5 μL of PCR product was run on 1.5% agarose gel at a constant voltage of 150 V for 30 min in 1×TAE buffer prior bands and size checked under UV light. A service provider company  performed direct sequencing of purified PCR products using a Sanger DNA sequencing approach in an ABI Prime 3730 DNA sequence machine. All 158 novel sequences of Mongolian goats in this study were deposited in the Genbank public database under accession numbers MK165491–MK165648.To study genetic diversity and phylogenetic analyses of MG, we amplified a 452 bp mtDNA fragment of the caprine partial HV1 region in D-loop  from158 animals using a set of primers: gd-loop F (5′-CAC AAA CTT CCC ACT CCA CA -3′) and gd-loop R (5′-AGC GTG TTT AAA ACG GTG GT -3′). We designed these two internal primers using the online tool Primer3Plus   for total of 12 MG populations. To examine the phylogenetic status and the origin of MG, 174 sequences of Mongolian goats were initially edited with BioEdit v.7.2.5  and partHd), number of segregating sites (S), nucleotide diversity (Pi), and average number of nucleotide differences (K).At the individual population level, as well as all MG together, DNA Sequence Polymorphism v5.10.01 (DnaSP ) was useWe constructed a neighbor-joining (NJ) tree  to examFs and ii) mismatch distribution analysis [Arlequin v3.5  was usedanalysis , to asseanalysis , were usHd . Estimated values of Hd ranged from 0.933  to the maximum value of 1.000 , while nucleotide diversity (Pi) varied between 0.0199  and 0.0384    mutations were detected. Estimated diversity parameters for MG populations are given in  0.0283) . The meaPhylogenetic relationships of goat populations within Mongolian and between 36 breeds (MG plus foreign breeds) were initially investigated in this study based on the high polymorphic HVI region in mtDNA. Because previous studies  have desTo further discern relationships among identified haplotypes in MG populations and in the total dataset (503 sequences), a MJ network analysis was constructed separately. Results obtained from this analysis also supported four well-resolved haplogroups of MG . The topFst) and average number of pairwise differences between (PiXY) and within (PiX) population values among 12 MG populations, while we also calculated Fst values for comparison among all 36 populations. Estimates of values of genetic differences are indicated in Fst values between 12 MG populations revealed relatively low genetic differentiation and ranged between −0.065 and 0.150 (mean Fst = 0.0168). The MGG population was closely related genetically to Nomgon , followed by the distance between NOM and Ref (−0.0543), while comparison of LOG and BGN populations had a greater distance value (0.150) (Fst) and geographical (km) distances among MG populations   . There w p>0.05) . Table 2 p>0.05) .Fst values from comparisons of 36 breeds from MG and foreign countries and the majority of all possible pairwise Fst comparisons (234 of 288) indicated that MG populations were significantly (p<0.05) different from foreign populations, in particularly those from Africa, Europe, and some of southern Asia (Iran and Loas) , followed by low positive values 0.026 for Indian and MGs, and goats from Arabian countries (including the domestication center).In addition, pairwise nd Loas) . HoweverFs statistic. Because of the small sample size at the individual breed level (<25), these statistics were performed for all datasets of MG and at the haplogroup level . All MG and haplogroup A displayed multimodal and unimodal curves that mismatched distributions, respectively   and the neutrality test of Fu’s  Fs statiectively . In partp<0.001) . In addiTo date, no study has explored genetic diversity and the origin of MGs in depth. This study conducted the first assessments of genetic population structure, genetic diversity, phylogenetic status, and the origin of Mongolian goats using the most polymorphic HVI region in mtDNA. This highly polymorphic region  has been routinely used in previous studies that examined genetic diversity, phylogenetic relationships, and especially the maternal origin of most domesticated animals, including goats ,33–37.Hd and Pi of MG were 0.997 and 0.0283, respectively (Hd in Mongolian goats were slightly higher (not significant) than that found in goat breeds from Africa, Egypt, and south Asia, but significantly higher than in Chinese and European breeds , and followed by Fst values (mean = 0.103) obtained from comparisons of goat populations (n = 5) from some Arabian countries  and MG populations (n = 12), this value was lower than that found in comparisons of Chinese (n = 5) versus MG populations (0.128), as well as southern Asia   in MG populations . Consistn center , 3. The n center  and occu= 0.275) . These cFst values versus MG was 0.106 and −0.016, respectively), prior to arriving in Mongolia. This migration may have involved ancient sheep population, because since ancient times Mongolian nomads reared sheep and goat together.According to findings from this and previous studies , 22,39, Second, a domestication center was located close to Mongolia somewhere in Southeast Asia . We beliFst = 0.0168). Our results were consistent with previous studies [AMOVA analysis of all MG dataset showed very weak phylogeographic structure among 12 populations, and more than 98% of the total variation occurred within populations. This weak structure was also evidenced by limited genetic differentiations  and haplogroup A (−24.39). Relatively similar patterns of mismatch distribution and significant and negative Fu’s Fs values were obtained in previous studies [Mismatch distribution and the neutrality test of Fu’s  Fs stati studies ,36,38,39 studies ,43. Fu’spulation . Both ap studies , 39,42.  studies .In summary, we report novel information regarding genetic diversity, population structure, and origin of Mongolian goats. The findings obtained from this study reveal that abundant haplogroups (A to D) occur in goat populations in Mongolia, with high levels of haplotype and Pi. Among these haplogroups, haplogroup A was predominant, with relative frequency of 90.8%. In addition, we speculate that two independent domestication centers may have contributed to the formation of goat populations in Mongolia. Finally, we highlighted that the past nomadic pasturing system led to weak geographical structure and limited genetic differentiations among populations in different regions of Mongolia.