Compostelandrilus cyaneus; this risk can be assessed by implementing potential distribution modeling and genetic diversity monitoring to their known populations. Genetic barcoding was performed in representatives of four populations (three of them newly sampled) in order to estimate genetic diversity and population genetics parameters. Ensemble species distribution models were built by combining several algorithms and using the five more relevant bioclimatic and soil variables as predictors. A large amount of genetic diversity was found in a small area of less than 20 km2, with populations located in less managed, better-preserved habitats showing higher genetic variability than populations isolated from natural habitats and surrounded by anthropic habitats. Potential distribution appears to be strongly restricted at a regional scale, and suitable habitats within the extent of occurrence appear fragmented and relatively limited. In addition, the main variables determining the ecological niche of C. cyaneus suggests a vulnerability to climate change and increasing soil compaction. Based on this knowledge, this species was assessed as Critically Endangered following the IUCN Red List of Threatened Species criteria, and some potential conservation actions are suggested.In spite of the high conservation value of soil fauna, the evaluation of their conservation status has usually been neglected. This is more evident for earthworms, one of the most important ecosystem service providers in temperate habitats but rarely the subject of conservation research. These studies have not been developed in Western Europe, which comprises high diversity and several early-branching, relic genera. One potentially menaced representative of this fauna is  The conservation value of soil fauna has historically been disregarded, despite the ecological importance and high diversity of these animals ,2. It haEarthworms  constitute a special case within soil fauna in regard to their conservation value. The instrumental value of earthworms encompasses both direct and indirect economic benefits. The indirect economic value of earthworms as one of the most important ecosystem service providers in temperate habitats is widely known : their aMegascolides australis has been the subject of particularly detailed conservation research [Even though comprehensive, large-scale works have been published on global patterns of earthworm diversity distribution , researcresearch ,22, leadresearch . The basresearch . Prelimiresearch , althougGaliciandrilus Domínguez, Aira, Porto, Díaz Cosín & Pérez-Losada 2017 and Compostelandrilus Domínguez, Aira, Porto, Díaz Cosín & Pérez-Losada 2017, are isolated in the NW Iberian Peninsula but appear to be closely related to Kritodrilus Bouché 1972 and Vindoboscolex Marchán 2021 in a surprisingly disjunct distribution [Galiciandrilus and Compostelandrilus appears to be extremely patchy and associated with habitats such as cork oak and holm oak forests, which are not widespread in the NW Iberian Peninsula. To add to the intrinsic conservation value of these species, each has highly divergent morphological characters, stressing the importance of each of them as reservoirs of the past morphological radiation of the aforementioned lineages.The native earthworm fauna of Western Europe (belonging to the families Lumbricidae and Hormogastridae) is of great interest from evolutionary and ecological perspectives. The Iberian Peninsula , southern France, Corsica, and Sardinia possess high diversity and endemicity and can be considered earthworm biodiversity hotspots. In addition, these terranes, which constituted a continuous landmass from the Cretaceous to the Oligocene-Miocene , have beribution . This suC. cyaneus  is the easternmost species of this complex, known from a single location in León (104 km from its closest relative). The surrounding area has been greatly modified by different types of agricultural land use, and the original habitats of this species have been reduced to hills and slopes unsuitable for crops. The species is, therefore, a priority target for conservation evaluation.Potential distribution modeling/niche characterization ,31,32 anC. cyaneus, (ii) to investigate the genetic diversity of known populations of this species, and (iii) to use this information for evaluating the conservation status of the species, establishing a template for other endemic earthworm species.The aims of this study are (i) to characterize the distribution and niche of C. cyaneus were collected in a sampling survey carried out in León, northwestern Spain, in November 2020. León is geologically heterogeneous, with three differentiated units: the Cantabrian mountain range to the north, the Bierzo depression and Galaico-Leonés mountain range to the west, and a Tertiary-Quaternary sedimentary basin in the rest of the province—the Meseta (plateau) [Specimens of plateau) . In the plateau) . The genplateau) .Compostelandrilus. Sampling points were spaced as regularly as possible (between 3 and 8 km), and natural-to-seminatural habitats were preferred  in the area between the known populations of referred .C. cyaneus was found are as follows:Habitat type and soil characteristics of the locations where 2O): 8.02, organic matter content: 2.0944%, nitrogen content: 0.1938%, C/N: 10.81.The north population (N) was sampled in a land mosaic of pastures with sclerophyllous vegetation and arable land in the close vicinity of the town of Villarmún. Soil characteristics: loam soil, coarse sand: 0%, fine sand: 47.63%, coarse silt: 8.014%, fine silt: 21.41%, clay: 22.94%, pHH (pH in HThe west population (W) was sampled within bushy pastures in an isolated hillock surrounded by non-irrigated arable land. Soil characteristics: clayey-sandy-loam soil, coarse sand: 0%, fine sand: 56.83%, coarse silt: 5.22%, fine silt: 9.15%, clay: 28.80%, pHH: 8.24, organic matter content: 1.45%, nitrogen content: 0.13%, C/N: 10.94.The east population (E) was sampled within relatively unmodified sloping pastures with sclerophyllous vegetation. Soil characteristics: silty-loam soil, coarse sand: 11.28%, fine sand: 33.89%, coarse silt: 7.32%, fine silt: 43.82%, clay: 3.69%, pHH: 8.36, organic matter content: 1.59%, nitrogen content: 0.14%, C/N: 10.91.The south population (S) was sampled within a large, continuous, sloping patch of pastures with sclerophyllous trees. Soil characteristics: fine sandy loam soil, coarse sand: 18.35%, fine sand: 35.64%, coarse silt: 5.41%, fine silt: 27.94%, clay: 12.66%, pHH: 8.26, organic matter content: 2.38%, nitrogen content: 0.25%, C/N: 9.58.Earthworms were collected by digging and hand-sorting and were then rinsed with water and fixed in 96% ethanol. Sampling was qualitative, and a standardized sampling effort of one hour of digging by four researchers was applied to every location. The sampling and handling of specimens followed ethical considerations and conformed to Directive 2010/63/EU. The species were identified from the external and internal morphological characters analyzed by Domínguez et al. .COI) was amplified by polymerase chain reaction (PCR), with the primers and conditions described by Pérez-Losada et al. [After morphological identification, up to 10  specimens of each population were chosen for further analysis. Total genomic DNA was extracted from ventral integument samples of approximately 5 mm × 5 mm using the DNeasy Blood & Tissue Kit (Qiagen). Cytochrome oxidase C subunit 1  generated in Domínguez et al. [Sequences from the other species of the genus z et al.  were retSequences were aligned using MAFFT v.7 , with deape v5.2. to convert the Maximum Likelihood tree into an ultrametric tree by non-parametric rate smoothing (NPRS). A relative calibration (root age = 1) was implemented: this approach provides an approximate visualization of the relative age of the clades without relying on external calibrations or assumptions of vicariance.Maximum Likelihood phylogenetic inference was performed using RAxML-NG  in the CA uniform distribution with an initial value = 0.002 (ranging from 0.00005 to 0.02) was specified through the ucld.mean parameter, and a uniform distribution with an initial value = 0.10 (ranging from 0 to 10) was specified for the ucld.stdev parameter. A relative calibration of 1  was implemented as a normal prior for the root of the tree. Fifty million generations were specified for the Monte-Carlo Markov chain, and sampling was conducted every 5000th generation. The log file was visualized in Log Tracer v. 1.7  to checkHaplotype networks were obtained using PopART 1.7  for grapGenetic diversity and population genetics parameters were determined using DnaSP 6 : haplotyhttp://www.worldclim.org/, accessed on 1 December 2020), and Corine Land Cover 2018 (100 m × 100 m resolution) (available online: https://land.copernicus.eu/pan-european/corine-land-cover/clc2018?tab=download (accessed on 3 January 2022)) was chosen to represent land use and vegetation type.Twenty large-scale variables were chosen as putative predictor variables: the suite of bioclimatic variables BIO1-BIO19 was downloaded from Worldclim (available online: https://doi.org/10.5281/zenodo.2525665 (accessed on 3 January 2022)), clay content (available online: https://doi.org/10.5281/zenodo.2525663 (accessed on 3 January 2022)), sand content (available online: https://doi.org/10.5281/zenodo.2525662 (accessed on 3 January 2022)), organic carbon content (available online: https://doi.org/10.5281/zenodo.2525553 (accessed on 3 January 2022)), soil water content (available online: https://doi.org/10.5281/zenodo.2784001 (accessed on 3 January 2022)), and soil pH (available online: https://doi.org/10.5281/zenodo.2525664 (accessed on 3 January 2022)).The following six soil variables from SoilGrids , correspAll layers were aggregated to the smallest resolution possible (100 m × 100 m).− BIO 4: Temperature Seasonality (TEMPSEA)− BIO 15: Precipitation Seasonality (PRSEA)− BIO 8: Mean Temperature of Wettest Quarter (MTWQ)− Soil water content (SOILW)− Soil bulk density (SOILBD)In order to select the most suitable predictor variables, a Boosted Regression Tree analysis was performed following a modified version of the script by Irving et al.  in R. AfEcological niche models were obtained using the R package ‘SSDM’  with staExtent of occurrence (EOO) and area of occupancy (AOO) were calculated in QGIS 3.16.3. The area of suitable habitat was determined according to the dominant land use. The latter was obtained from SIGPAC  for 2012 and 2020 for calculation of potential habitat loss.All of the individuals studied possessed internal and external morphological characters consistent with the original description  and withFor the north population (N), a total of 23 individuals were sampled: 1 mature, 16 semi-mature (showing developed tubercula pubertatis and hints of clitellum), and 6 immature. For the west population (W), 8 individuals were sampled: 5 semi-mature and 3 immature. For the east population (E), 10 individuals were sampled: 4 semi-mature and 6 immature. For the south population (S), 10 individuals were sampled: 1 mature, 5 semi-mature and 4 immature.C. cyaneus were recovered as a sister clade to C. bercianus and C. menciae by the phylogenetic analysis  distance based on the COI sequences between the four populations ranged between 1.08% and 5.78% . The lowThe haplotype network  displayeHaplotypic diversity (H)  was highNone of the estimated demographic parameters  were statistically significant.Both ecological niche models obtained (presence–absence and presence-only) displayed high predictive power, with high AUC and kappa values , high sensitivity and specificity , and low omission rates (0.00) .The geographical representation of the predicted suitability values of the presence–absence model is shown in The relative contributions of the predictor variables to each model are shown in 2. The area of suitable habitat, according to the SIGPAC dominant land-use types . There was no estimated loss of suitable habitat in the 2012–2020 period.The extent of occurrence (EOO) (the polygon delimiting the known populations) covered an area of 17.48 kmC. cyaneus can be used to infer the long-term viability and connectivity of the populations and their relationship with the environment.The information obtained about the genetic diversity of the known populations of 2), known populations of C. cyaneus harbor a large amount of genetic diversity. Populations E and S, located in less managed, better-preserved habitats, showed the highest amount of genetic variability; on the other hand, populations W and N, which were isolated from natural habitats and surrounded by anthropic habitats (non-irrigated arable land), showed significantly lower genetic diversity. Together with population genetic parameters, this suggests that the latter populations colonized their current habitats from the southeastern populations and became isolated by land-use changes and a reduction in suitable habitat. The reduction in genetic diversity may be explained by low connectivity with other populations and lower habitat suitability [For such a small area , genetic diversity would be higher for certain preferred values of these variables; yet, such an effect was not observed. It is possible that the geographical distance between the populations is too small for them to display significant environmental heterogeneity. Another possibility is that a single molecular marker is not enough to capture the effect of such an environmental pressure on genetic diversity; landscape genomics analyses (such as in ) could hC. cyaneus appears to be strongly restricted at a regional scale, corresponding to roughly 10% of the area of the province of León.The potential distribution of C. cyaneus , climate change and increasing soil compaction may have historically modified the area of suitable habitat for this species and may further modify it in the future. These are two of the main threats to soils and to agriculture sustainability [Even without taking land use into account (as Corine Land Cover was excluded in the selection step), suitable habitat within the EOO appears fragmented and relatively limited. Considering the main variables determining the ecological niche of nability ,64.Suitable habitat, as inferred from the preferred types of land use (pastures with or without bushes or trees), also shows a high degree of fragmentation, with large gaps of unfavorable habitat between patches. While preferred habitats do not appear to have decreased in the last 8 years, they are evidently scarce in the area, as arable land and reforested woodland appear to be the dominant types of land use.Due to the characteristics of their habitat, ecological preferences and the fine-scale distribution of soil fauna are generally poorly known when compared with more conspicuous animals; in fact, soils have been described as the “third biotic frontier”  . EcologiThe following assessment roughly follows the structure and format of the IUCN Red List of Threatened Species.TaxonomyKingdom Animalia, Phylum Annelida, Order Megadrili, Family LumbricidaeCompostelandrilus cyaneus Taxon Name: Taxonomic Source(s):Zoological Journal of the Linnean Society, 182(2), 258-274.Domínguez, J., Aira, M., Porto, P. G., Díaz Cosín, D. J., & Pérez-Losada, M. (2018). Multigene phylogeny reveals two new isolated and relic earthworm genera (Oligochaeta: Lumbricidae). Zophoscolex  into French and Iberian genera. Zoological Journal of the Linnean Society.Jiménez, S., Marchán, D.F., Novo, M., Trigo, D., Domínguez, J., Díaz Cosín, D.J. (2021). Sorry atlanticus, you are not my type. Molecular assessment splits Assessment InformationRed List Category & Criteria: Critically Endangered B1ab(iii)+2ab(iii) ver 3.1Justification:This species is assessed as Critically Endangered owing to the restricted extent of occurrence (EOO), estimated area of occupancy (AOO), the expected decline in quality of habitat, and occurrence in only four locations.Geographic RangeRange Description:This species has only been found in four locations in the province of León , in the vicinities of the localities of Villarmún, Valle de Mansilla, San Miguel de Escalada and Palazuelo de Eslonza.2.The extent of occurrence (EOO) for this species is 17.48 km², and the estimated area of occupancy (AOO) is 4.5 kmCountry occurrence:Native: SpainDistribution MapSee maps in PopulationFour populations of this species have been discovered.Current population trend: unknown. Population genetics suggest that two of the known populations display low genetic diversity and may have suffered recent bottlenecks.Habitat and EcologyQuercus ilex rotundifolia), usually restricted to isolated hillocks and slopes when the habitat is surrounded by arable land. It has not been found in reforested woods composed of pines or other non-native, commercial species. Other earthworm species are rarely found within the same patches as C. cyaneus, the most frequent being Aporrectodea trapezoides  and Aporrectodea rosea .The species has been found in natural pastures with sclerophyllous bushes and/or trees  could be developed, owing to the easy recognition of the surface casts of this species c. This wEven though different earthworm species show significant differences in ecological preferences  and theiC. cyaneus as they act as genetic diversity reservoirs from which the recolonization of surrounding habitats could be eventually achieved. To avoid isolation between those patches and recently established populations that are in genetic drift, with reduced fitness and eventual extinction, connectivity between populations should be encouraged. For that, corridors of native vegetation should be preserved or restored. The importance of hedgerows and grass field margins for invertebrate diversity [C. cyaneus.The preservation of patches of original, unmodified habitat appears to be key to narrowly distributed, endogeic earthworms such as iversity  and soiliversity  is well iversity  should mEven though native, endemic species can be occasionally found in unfavorable land uses such as arable lands, they are usually outcompeted by exotic or cosmopolitan earthworms in such highly-productive soils , hinderiGenetic diversity estimation based on COI molecular barcoding and ecological niche modeling based on large-scale and soil predictor variables has provided useful insight into the conservation status of a narrowly distributed, endemic earthworm from the highly diverse Iberian Peninsula. The more vulnerable populations were identified based on low genetic diversity and habitat isolation. In addition, threats for its populations were inferred from the most influential environmental variables. This approach appears promising in terms of facilitating research on earthworm conservation evaluation and compensating for the lack of attention to this key element of soil ecosystems in conservation biology.


Anthonomus eugenii Cano (Coleoptera: Curculionidae) is a pest of economic importance for Capsicum species pepper in North America that attacks the reproductive structures of the plant. The insect is distributed across Mexico, the United States, and the Caribbean, and is occasionally found during the pepper growing season in southern Ontario, Canada. Continuous spread of the insect to new areas is partially the result of global pepper trade. Here, we describe the genetic diversity of the pepper weevil using the mitochondrial COI barcoding region across most of its geographic range. In this study, 44 (H1–H44) highly similar haplotypes were identified, the greatest number of haplotypes and haplotype diversity were observed among specimens from its native Mexico, followed by specimens from the United States. Unlike Mexico, a low haplotype diversity was found among specimens from Canada, the Dominican Republic, Italy, and the Netherlands. Out of these 44 haplotypes, 29 are reported for the first time. Haplotype diversity in the Canadian population suggests either multiple and continuous introductions of the pepper weevil into this area or a single introduction of genetically diverse individuals. We discuss the importance of such population genetic data in tailoring pepper weevil management programs, using Canada as an example.The pepper weevil  The colonization, establishment, and dispersal of non-native insects into new environments can pose a challenge to conservation and agricultural pest management . How welToday, a gamut of molecular tools is available to study the population genetics of non-native species. Among these, studying the sequence variation in the mitochondrial Cytochrome Oxidase subunit I (COI) barcoding gene region remains one of the most frequently used tools in species identification, delimitation , and hapAnthonomus eugenii Cano (Coleoptera: Curculionidae) is a pest of economic importance to the global cultivation of Capsicum species. It is native to Mexico . In doing so, we aimed to enhance our understanding of the movement and establishment potential for different populations of this species, as well as to assist in identifying effective management tactics based on the characteristics of the originating populations using pepper weevil in Canada as an example. This will assist global agencies in better predicting the risk of invasion of this and other invasive arthropod species in future.n = 86), Mexico (n = 138), and the United States (n = 44). Canadian specimens were obtained from infested pepper fruit collected from field and mostly greenhouse crops in 2016. Specimens from the United States were collected from infested fruit in 2018, and those from Mexico represented both preserved and freshly emerged individuals reared from field-collected fruit between 2015–2018. In addition, 127 publicly available pepper weevil mitochondrial CO1 sequences (n = 22), the United States (n = 26), Dominican Republic (n = 45), Italy (n = 2), and the Netherlands (n = 32). In total, analyses were conducted in 395 sequences representing six countries and 16 populations.A total of 268 pepper weevil individuals (adults and larvae) were collected throughout the current geographic range of this pest in Canada  and visualized using a Gel Doc . The remaining volume of PCR products was then purified with ExoSAP-IT  following manufacturer guidelines and clean amplicons were bidirectionally Sanger sequenced using LCO1490 and HCO2198 primers .Whole-body DNA was extracted from pepper weevil specimens using Chelex 100 chelating resin . Briefly, specimens were incubated in 100 µL of 5% Chelex and 2 µL of Proteinase K solution before incubation at 55°C for 24 h. Afterwards, the proteinase K was denatured by incubation of extracts at 99°C for 10 min, followed by centrifugation at 13,000 rpm for 5 min to pellet the Chelex beads. Fifty µL of the supernatant containing DNA was transferred to new tubes and DNA samples were stored at –20°C until PCR amplification. Each PCR reaction mixture included 25 µL of Froggamix 2X Plus , 1 µL of 10 µM of forward and reverse primers, 22 µL of DNA free water, and 1 µL of diluted DNA template giving a 50 µL total reaction volume. Due to changes in reagents availability, a second PCR mixture was used in later amplifications. In this case, the new PCR mixture included 0.25 µL of 10 µM of each forward and reverse primers, 2.5 µL of 10X PCR buffer, 1.25 µL of 50 mM MgClAATCA–3’ . The amph) and nucleotide (π) diversities, and Tajima’s D statistic  was highest in Mexican populations ranging from 0.9 to 0.7, and with 40 haplotypes out of the total 4. The Canadian populations had the lowest haplotype diversity with values of 0.3 (n = 2) and the Netherlands (n = 32). The rarefaction curve, with 10,000 bootstraps did not reach an asymptote and the expected haplotype richness was of 75 haplotypes based on the Chao1 index (The target COI barcode region (658 bp) was successfully amplified and sequenced for 268 pepper weevil specimens , Fig. 1.s of 0.3 . Only ono1 index .GST values of population differentiation were overall low, and maximum values were only recorded between the Canadian population in Dresden and various populations in Mexico and the United States (P = 0.06). However, significant genetic variation (P < 0.01) was detected among populations within countries and within populations, accounting for 11% and 77% of the total variation, respectively  along with the Netherlands, while Canada, the United States, Dominican Republic, Italy, and Northern/Western Mexico grouped together , for which different haplotypes correspond to strains that each feed and rely on distinct host plant types (Bemisia tabaci (Gennadius)   for whictentials . Taken tieac012_suppl_Supplementary_Table_S1Click here for additional data file.ieac012_suppl_Supplementary_Table_S2Click here for additional data file.


Rutidosis leptorrhynchoides) was a common component of grassy ecosystems in south-eastern Australia. It is now endangered due to extensive habitat loss and the impacts of livestock grazing, and is currently restricted to a few small populations in two regions >500 km apart, one in Victoria, the other in the Australian Capital Territory and nearby New South Wales (ACT/NSW). Using a genome-wide SNP dataset, we assessed patterns of genetic structure and genetic differentiation of 12 natural diploid populations. We estimated intrapopulation genetic diversity to scope sources for genetic management. Bayesian clustering and principal coordinate analyses showed strong population genetic differentiation between the two regions, and substantial substructure within ACT/NSW. A coalescent tree-building approach implemented in SNAPP indicated evolutionary divergence between the two distant regions. Among the populations screened, the last two known remaining Victorian populations had the highest genetic diversity, despite having among the lowest recent census sizes. A maximum likelihood population tree method implemented in TreeMix suggested little or no recent gene flow except potentially between very close neighbours. Populations that were more genetically distinctive had lower genetic diversity, suggesting that drift in isolation is likely driving population differentiation though loss of diversity, hence re-establishing gene flow among them is desirable. These results provide background knowledge for evidence-based conservation and support genetic rescue within and between regions to elevate genetic diversity and alleviate inbreeding.Conservation management can be aided by knowledge of genetic diversity and evolutionary history, so that ecological and evolutionary processes can be preserved. The Button Wrinklewort daisy ( Biodiversity is declining globally at an unprecedented rate with tens of thousands of species facing impending extinction  is a perennial plant in the daisy (Asteraceae) family, endemic to Australia, and that was once widespread in grassy ecosystems in south-eastern Australia . In an attempt to stem population decline, management actions have been undertaken including habitat restoration, monitoring and supplementary planting.The Button Wrinklewort  and ten microsatellites  showed differentiation among sampled populations of only R. leptorrhynchoides and describe patterns of genome-wide diversity and structure in populations across its distribution. We aimed to: (1) quantify levels of genome-wide differentiation between sampling locations and explore the underlying processes driving this differentiation; (2) assess levels of genome-wide genetic diversity within sampling locations and test whether they accord with previously published allozyme and microsatellite-based estimates; (3) infer some key parameters of population genetic history: population tree topology, divergence times and effective population sizes  were estimated by a coalescent tree method based on SNPs, and the role of gene flow in population isolation or admixture was explored via a maximum likelihood population tree based on SNP allele frequencies; and (4) use these results to define populations for conservation management planning. The molecular approaches we apply are likely to be affordable in many management scenarios, can be outsourced, do not require existing genome resources and hence are applicable to a wide range of species.In this study we use a dataset of 12,965 single nucleotide polymorphism (SNP) loci to investigate the evolutionary history of Rutidosis leptorrhynchoides is a perennial herb endemic to south-eastern Australia. It occurs in grassy eucalypt woodlands and treeless grasslands, most of which are dominated by kangaroo-grass, Themeda triandra  and majority of southern populations being autotetraploid, often with additional non-diploid karyotypes  across the current distribution of diploid TM (reduced-genome representation) platform , and 4 individuals with >15% missing data . To control for very close physical linkage, we retained only one SNP per sequenced fragment (~69 bp), which removed a further 3640 loci. We also filtered for monomorphic loci, but found none.The raw genomic dataset comprised 53,758 codominant, genome-wide, biallelic SNPs. Data filtering was done using the DARTR package .K) and membership of each individual in each genetic cluster using STRUCTURE v2.3.4 , each with a burn-in of 500,000 followed by 1,000,000 Markov chain Monte Carlo (MCMC) iterations. We used the admixture model without prior population information. To identify further patterns of substructure, we performed additional STRUCTURE runs on only northern (ACT/NSW) populations, which belonged to a single cluster based on K = 2 analysis, testing a range of genetic clusters from K = 1 to 10  method of Pritchard & Wen  and performing a Mantel test using the function ‘gl.ibd’ in DARTR for all 12 populations and for populations only within the ACT/NSW region.To quantify genetic differentiation among populations, we estimated pairwise Weir & Cockerham  FST in t Goudet,  using thHo), gene diversity (HS), allelic richness (AR) and FIS for each population were estimated using HIERFSTAT. Genetic diversity analyses were also performed on the no-missing dataset and yielded similar results .A correlation between low diversity and high population-specific µ = 1, v = 1, coalescence rate = 10, priors: α = 11.75, β = 109.73, κ = 1, λ = 0.00765) and ran two independent replicate MCMC runs of 1,000,000 iterations with sampling every 1000 steps and a burn-in of 10%. To ensure the choice of individuals and loci did not influence our results, this analysis was repeated on another set of randomly sampled individuals and 2000 randomly sampled loci.To explore history of population divergence, we inferred a population tree using a coalescent model and Bayesian MCMC approach implemented in SNAPP  of the PCoA analysis explained 6.17% of the total variance and clearly separated VIC locations from ACT/NSW  and northern (ACT/NSW) locations, the runs were insufficiently consistent to determine a best K according to ln Pr(X|K) method  method supported eight , and sampling locations within regions explained 21.50% . Similarly, pairwise FST comparisons showed significant pairwise differentiation among most sampled locations, with largest values observed for comparisons involving MI and CF in NSW, and SA in VIC  and relatively low AR (1.14) even though it is one of the larger populations, estimated to number >28,000 plants  of the 25,930 alleles in the full dataset were shared in common between samples from ACT/NSW and those from VIC. While 19.8% of the 25,930 were present only in ACT/NSW, and 18.3% were unique to VIC, most of these private alleles were rare, representing <5% of the sample for a given marker  were highly correlated with estimates of genetic diversity per population (Supplementary Table There was strong support for a genetic split between VIC (TR and SA) and all northern locations, according to the SNAPP MCC population trees produced by the two different datasets  showed topology largely concordant with population clustering inferred by the PCoA, STRUCTURE and SNAPP analyses Fig. . The twoThe strongly positive TreeMix residuals among some pairs of locations indicate that these may be more closely related than they appear in the tree, and are thus candidates for potential admixture events Fig. . Tree toR. leptorrhynchoides, which was hinted at but not resolved in previous population genetic studies of this species  found major genetic structure between the regions, dating back to the late Pliocene  and northern (ACT/NSW) populations of R. leptorrhynchoides distribution to contract to the grassy woodlands of ACT and the grassy plains of VIC, promoting divergence  glacial oscillations likely repeatedly caused  Bowler, . Few iso Bowler, . Because Bowler, , gene fl Bowler,  would haR. leptorrhynchoides. Our data implicate genetic drift in isolation as the driving force behind this differentiation, particularly within the southern NSW locations of CF, BB and MI. CF was previously identified as isolated, using STRUCTURE analysis  compared to the duration of habitat destruction , and relatively long longevity  populations of S-allele diversity may be limiting reproduction (Young et al., Due to their small and declining population sizes, VIC populations are vulnerable to extinction through environmental stochasticity, and would benefit from demographic rescue. The surprisingly high genetic diversity at TR and SA given their census sizes indicate that demographic augmentation may be of greater urgency than is elevating genetic diversity. Nonetheless, both locations will be losing genetic variation by drift, and SA in particular comprises so few individuals that low Rodger et al. HDY-20-A0167RRR Supplementary Material


We found sharp differentiation among populations separated by the African continent with both mitochondrial and nuclear markers, while only mitochondrial markers allowed characterizing the five nominal lineages. No differentiation could be detected within these five lineages, questioning the strong level of philopatry showed by these shearwaters. Finally, we propose that Atlantic populations likely originated from the Indian Ocean. Within the Atlantic, a stepping‐stone process accounts for the current distribution. Based on our divergence time estimates, we suggest that the observed pattern of differentiation mostly resulted from historical and current variation in sea surface temperatures.Seabirds, particularly Procellariiformes, are highly mobile organisms with a great capacity for long dispersal, though simultaneously showing high philopatry, two conflicting life‐history traits that may lead to contrasted patterns of genetic population structure. Landmasses were suggested to explain differentiation patterns observed in seabirds, but philopatry, isolation by distance, segregation between breeding and nonbreeding zones, and oceanographic conditions (sea surface temperatures) may also contribute to differentiation patterns. To our knowledge, no study has simultaneously contrasted the multiple factors contributing to the diversification of seabird species, especially in the gray zone of speciation. We conducted a multilocus phylogeographic study on a widespread seabird species complex, the little shearwater complex, showing highly homogeneous morphology, which led to considerable taxonomic debate. We sequenced three mitochondrial and six nuclear markers on all extant populations from the Atlantic ( We conducted a multilocus phylogeographic study on a widespread shearwater and sequenced three mitochondrial and six nuclear markers on all extant populations. We found sharp differentiation among populations separated by the African continent with both markers, while only mitochondrial markers allowed characterizing the five nominal lineages. We propose that Atlantic populations originated from the Indian Ocean. Within the Atlantic, a stepping‐stone process accounts for the current distribution. Using this single marker, three distinct lineages were recognized in the North Atlantic: lherminieri in the Caribbean and off Brazil, baroli in the Azores, Canaries, and Madeira, and boydi in Cape Verde , Réunion (bailloni) and many islands in the Pacific Ocean . Within the bailloni lineage, breeding populations are characterized by different breeding phenologies on the northern and southern parts of Réunion  are long‐lived birds showing slow demographic rates, for example, life expectancy up to or above 15 years Warham, . They bre Figure  and are e Figure , a pattee Figure . Unsurpr Warham,  or subspPuffinus assimilis–lherminieri complex. We sampled birds from all but one known breeding localities in the North Atlantic  and in the northern Indian Ocean , as well as three populations of interest for bailloni and nicolae in the Indian Ocean, were included in our study  spanning the entire known breeding distribution of cox1, cytb, and the mitochondrial control region, CR) and six nuclear markers  were targeted  using NucleoSpin® Tissue XS Kit . Samples were incubated overnight in 4 mg of Proteinase K. Purified genomic DNA was eluted twice in 50 µl of TE buffer preheated at 70℃. DNA concentration was measured using Nanodrop spectrophotometry. Three mitochondrial markers , per marker, using DNAsp v.5.10.01 . For AMOVAs, samples were stratified into five groups, corresponding to the five nominal lineages  and populations  was estimated using 1000 permutations. To visualize relationships among lineages, we inferred NeighborNet networks using SplitsTree v 4.14.2 . Including the CR led to excess variation in the dataset and resulted in a spurious delimitation of 89 species. Also, the signal‐poor nuclear sequences were not used for this analysis.For each population, we calculated haplotype frequencies, interhaplotype distances, haplotype diversity, and nucleotide diversity  represented by fewer than five individuals from each sex. Sex‐biased dispersal was tested at both intra‐ and interlineage scales. We calculated average pairwise relatedness for each sex, within each population, using the triadic likelihood estimator . 2.5p‐value <.0005). We therefore used, for each marker, an uncorrelated lognormal relaxed clock model. The clock rate was fixed to 0.00553 ± 0.00115 substitution per site per million year for cox1 and 0.00631 ± 0.0035 for cytb  were added to the *BEAST inference. This taxon can be considered as the best representative taxon for the central Pacific, as it is the most widespread and numerous, since polynesiae is considered synonym to dichrous  has never been sequenced, and actually, the location(s) of its breeding colony(ies) is(are) unknown. Three dichrous cytb sequences retrieved from GenBank (AY219949‐AY219951) and three individuals from our own collection were used. We ran a second *BEAST analysis by adding all the nuclear markers independently to the three mitochondrial markers, using the same MCMC parameters. Clock rate priors were set to 0.019 substitutions per site per million year for βfib and 0.013 substitution per site per million year for rag1, since these rates were estimated for birds  presented any insertion, deletion, nonsense, or stop codon following translation  still showed double peaks at 73 positions, as well as 37 positions for 22 individuals (10%) for cytb. Double peaks were not specific to any population or sex and were not linked to the position of the individuals in the sequencing plate  and two at nuclear loci only . Patterns of population structure at seven out of 13 localities might therefore be influenced by selection and/or recent demographic changes, in addition to neutral processes.Mitochondrial and nuclear results from Fu's boydi) were supported in *BEAST (PP ≥ 0.95) using all concatenated markers. For both mtDNA markers, and all markers concatenated, the central Pacific dichrous lineage was nested within the bailloni/nicolae clade, although node supports for dichrous position within Indian Ocean clade were weak (PP ranging between 0.27 and 0.73). Assignment to an ocean basin based on nuclear haplotype networks was, however, discordant from the mitochondrial data for 33 individuals, for at least one nuclear locus , while the other haplotype phase (father) clustered with the nicolae phylogroup for four nuclear markers (the two remaining could not be assigned to any particular lineages). This individual might be the result of hybridization, although further analyses based on additional markers would be necessary to detect more robustly hybridization among lineages. The ambiguous assignment of the other individuals might be due to introgression or incomplete lineage sorting (see below).Gene trees and phylogenetic inference with *BEAST and MrBayes& revealed a hierarchical structure composed of two well‐supported (posterior probabilities PP ≥ 0.95) reciprocally monophyletic clades corresponding to the two oceans, within which individuals from the five lineages further clustered into monophyletic subclades Figure  and S7. s Figure  and S8: FST showed consistently higher values among than within lineages for both marker types, with mostly nonsignificant values within each lineage . The variance among sampling localities within lineages accounted for 0.5–4.1%, while variance within sampling localities represented 11.0–37.5%. Pairwise ge Table . Moreovees Table . Populates Table .r = 0.88 and 0.70, n = 45, p < .005 for mtDNA and nuDNA, respectively; Figure Genetic distance increased clearly with geographic distance Figure , but Mancox1 and cytb concatenated) supported four groups, based on the best asap‐score . The lineages herminieri, boydi, and baroli were each considered as a separate species, while bailloni and nicolae were clustered as a single species.The ASAP species delimitation analysis (p = .42); 49 individuals could not be sexed successfully and were therefore excluded from sex‐biased dispersal analyses. Indian Ocean populations (nicolae and bailloni) showed stronger female dispersion as indicated by significantly stronger deficit of heterozygotes and a significantly lower average relatedness in females  and boydi . In addition, population structure within lineages, as measured with FST, was similar between sexes, but between oceans, a larger range of FST values was observed for males with higher maximum values, suggesting that males were more structured at least for some pairs of populations , and nicolae and bailloni split at 0.70 My ago (0.33–1.13). The *BEAST analysis based on all nine markers showed the same topology, though, with generally lower divergence times and higher confidence intervals . Introgressive hybridization has been documented in shearwaters , which showed that one individual (of mixed ancestry) foraged around South Trinidad Is, off Brazil, and even in the northern Atlantic , Austin et al.  and C. diomedea (North Atlantic and Mediterranean) 0.7–0.9 My ago  and Puffinus puffinus (North Atlantic) 0.2–1.0 My , and such high rate or speciation may be the result of the high climatic oscillation that occurred over the last 2 million years, which may have favored high rates of colonization and extinction on coastal islands.Dispersal limitation has been suggested as a speciation mechanism in seabirds. However, isolation by distance within each lineage was not detected here, since Mantel tests showed a strong correlation between geographic and genetic distances only among lineages, that is, at large scale. Therefore, distance alone could not be a factor of population divergence at this smaller scale. Rather, we argue that sea temperature could be the most important factor of divergence in our case, even at this scale. Seabirds indeed depend on both sea and the islands where they breed; thus, SST has strong impacts on their phenology, breeding, survival, and abundance , while SST has been a more important driver at smaller scale (within oceans). However, since these seabirds depend on the geographic distribution of their breeding islands and because they are relatively “poor” flyers, island distribution becomes a major constraint resulting in the present geographic structure, promoting local adaptation to small‐scale ecological constraints and reducing gene flow. Strict marine organisms can disperse far more or alternatively are unconstrained by island distribution, and thus show much less geographic structure within taxa. The terrestrial organisms tend to disperse far less, and isolation by distance tends to be a main driver of population differentiation ; data curation ; formal analysis ; methodology ; writing‐original draft ; writing‐review & editing . Eric Pante: Conceptualization ; data curation ; formal analysis ; methodology ; project administration ; supervision ; validation ; writing‐original draft . Jacob González‐Solís: Resources ; writing‐original draft . Amélia Viricel: Formal analysis ; writing‐original draft . Cécile Ribout: Methodology . Francis Zino: Resources ; writing‐original draft . Will MacKin: Resources ; writing‐original draft . Carine Precheur: Resources . Julie Tourmetz: Resources . Licia Calabrese: Resources . Teresa Militão: Resources . Laura Zango: Resources . Hadoram Shirihai: Resources ; writing‐original draft . Vincent Bretagnolle: Conceptualization ; funding acquisition (lead); supervision ; writing‐original draft ; writing‐review & editing .Supplementary MaterialClick here for additional data file.


In the present study, twenty microsatellite loci were tested to assess and analyze the genetic diversity between and within 17 different populations of Turkish water buffalo. The total number of animals sampled was 837, collected from six geographical regions: Marmara Region (MRM), Black Sea Region (BSR), Aegean Region (AER), Central Anatolia Region (CAR), Eastern Anatolia Region (EAR) and Southeastern Anatolia Region (SAR). All studied microsatellites markers showed allelic polymorphism. In this study, the results indicated a definite genetic diversity among the Turkish water buffalo populations which indicates the existence of at least two major clusters.IS value was 0.091 and all loci were observed significantly deviated from Hardy–Weinberg Equilibrium (HWE), most likely based on non-random breeding. The 17 buffalo populations were genetically less diverse as indicated by a small mean FST value (0.032 ± 0.018). The analysis of molecular variance (AMOVA) analysis indicated that about 2% of the total genetic diversity was clarified by population distinctions and 88 percent corresponded to differences among individuals. The information produced by this study can be used to establish a base of national conservation and breeding strategy of water buffalo population in Turkey.The present study was aimed to investigate the genetic diversity among 17 Turkish water buffalo populations. A total of 837 individuals from 17 provincial populations were genotyped, using 20 microsatellites markers. The microsatellite markers analyzed were highly polymorphic with a mean number of alleles of (7.28) ranging from 6 (ILSTS005) to 17 (ETH003). The mean observed and expected heterozygosity values across all polymorphic loci in all studied buffalo populations were 0.61 and 0.70, respectively. Observed heterozygosity varied from 0.55 (Bursa (BUR)) to 0.70 (Muş (MUS)). It was lower than expected heterozygosity in most of the populations indicating a deviation from Hardy–Weinberg equilibrium. The overall value for the polymorphic information content of noted microsatellite loci was 0.655, indicating their suitability for genetic diversity analysis in buffalo. The mean F Water buffaloes have been reported to be of great importance to the lives of farmers and thus to the economies of many countries worldwide . The numAccording to 1974 FAO statistics, at that time, there was one million buffalo heads in Turkey. From 1984 to 1998, there has been a decrease in the buffalo breeding population of 75 percent, and the reason for this decrease in water buffaloes has been the preference for cattle breeding and increasing technology in agriculture over buffalos in the Aegean and Marmara Regions, where many buffaloes were found. In this period, all the improvement efforts for genotypes were only practiced on cattle in Turkey.In Turkey, most farmers keep one or two buffaloes for family consumption, and this system is very widespread in villages, while farms with around 100 heads are located near the big cities. Despite the popular indifference, farming of this species has survived in order to promote productive systems in agreement with sustainable rural development and the trend to revalue autochthonous genetic types . Thanks Water buffaloes in Turkey originate from Mediterranean Water Buffaloes, a subgroup of river water buffaloes and are known as Anatolian Water Buffalo . Turkey Genetic diversity can be detected with molecular markers, such as random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), single nucleotide polymorphism (SNP) and, most commonly used, microsatellites ,7,8, becThis experiment was conducted at the National Anatolian Water Buffalo Breeding Project breeders buffalo in 6 different geographical regions in Turkey. The experimental protocol was approved by the Republic of Turkey Ministry of Agriculture and Forestry Pendik Veterinary Control Institute Local Ethics Committee . This study was conducted between June 2013 and June 2015.In this study, a total of 837 blood samples from unrelated Turkish water buffalo  individuals were collected at random from 17 different populations located in 6 different geographical regions  . These rhttp://www.genometri.com.tr/, accessed date 10 August 2020) in Istanbul.Blood samples were collected in vacutainer tubes that include EDTA  and stored at +4 °C until DNA extraction. Around 8 mL of blood per buffalo was taken, and the purification of genomic DNA was performed from 2 mL blood samples, using High Pure PCR Template Preparation Kit , following the manufacturer’s protocol. All DNA extraction and polymerase chain reaction (PCR) amplification were performed by Geometry Biotechnology . The PCR was performed with a total reaction volume of 25 µL, using the following thermal conditions, 94 °C for 10 min, followed by 32 cycles of 94 °C for 1 min, 55 °C for 30 s, 56 °C for 3 min and a final extension at 60 °C for 1 h. Amplified DNA was controlled in 1% agarose gel, using SYBR™ Safe DNA Gel Stain.A total of 20 heterologous buffalo microsatellite loci were studied from a panel of 30 markers recommended by the International Society for Animal Genetics (ISAG) and Food and Agriculture Organization of the United Nations (FAO) working group for biodiversity study. The criterion for selection of the microsatellite loci was based on the high polymorphism information content value (PIC) and the number of exhibited alleles of the loci . Informa® 3130 Genetic Analyzer , using the GeneScan® Analysis Software , which check different alleles via size comparison with standard DNA size markers GeneScan 500 ROX Dye . Allele sizes were calculated with the GeneMapper®Software V4.0 After agarose gel electrophoresis for 20 microsatellites, allele size was identified on all samples with an ABI Prisma), the number of effective alleles (Ne), allelic richness (RS), polymorphic information content for each locus (PIC), observed heterozygosity (HO), expected heterozygosity (HE), Shannon’s information index (I), Hardy–Weinberg equilibrium and null allele frequencies, using Genetix v4.05 [ST, FIS and FIT), as proposed by Weir and Cockerham [®software [T), diversity within populations (HS), diversity between populations (DST) and coefficient of gene differentiation (GST) values were analyzed with FSTAT v2.9.4 [AS genetic distances  were caes , the number of effective alleles (Ne), observed (HO) and unbiased expected (HE) heterozygosity, Shannon’s information index (I) and the deficit of heterozygotes (FIS) values for individual subpopulations and overall population are presented in A summary of statistic results for genetic diversity is shown in a) was the highest in Central Anatolia (Kayseri (KAY) and Sivas (SVS)) Region buffalo individuals (8.80) and the lowest in Black Sea Region (Giresun (GIR)) buffalo individuals (5.70). The number of effective alleles per locus (Ne) and allelic richness (Rs) values are a measure of the genetic diversity. The effective number of alleles per population (Ne) showed lower values, which varied from 2.87 (Bursa (BUR)) to 4.14 (Muş (MUS)). Additionally, the RS means ranged from 5.03 to 6.83 in the Marmara, Black Sea and Aegean Regions buffaloes, being lower than that in the Central Anatolia, Eastern Anatolia and Southeastern Anatolia Regions buffaloes. The observed (HO) and unbiased expected (HE) heterozygosity per population varied from 0.55 (BUR) to 0.70 (MUS) and 0.58 (BUR) to 0.73 (MUS), respectively , but the differences were not statistically significant. It is thought that the reason for this difference may be due to the geographical proximity of the buffalo to the domestication center, the fact that the buffalo breeding in these regions consists of small family businesses and there is no selection in this population. The inbreeding coefficient (FIS) within the populations varied between 0.017 and 0.183. Additionally, the SVS and Amasya (AMS) populations have shown that the lowest and highest genetic diversity, respectively. All of the FIS values were determined to be positive and statistically significant   and therefore different from zero. Shannon’s information index (I) across populations ranged from 1.15 (BUR) to 1.58 (MUS).The mean number of alleles (Nectively . The HO < 0.001) . The avea) ranged between 4.29 and 12.59 for the same loci (e ranged from 1.80 (CSSM033) to 7.74 (CSSM047) for the Turkish water buffalo population based on 20 polymorphic microsatellite loci. The value of allelic richness (Rs) ranged from 3.99 (ILSTS005) to 12.08 (ETH003), with a mean of 6.87. PIC and the Shannon information index are another measure of genetic variability indicating the informativeness of the assessed loci. The polymorphic information content (PIC) was analyzed for each locus and varied from 0.412 (CSSM033) to 0.859 (CSSM047), which has the highest number of alleles per locus in the current study. A total of 16 of these 20 microsatellite loci had polymorphic information content (PIC) values greater than (0.5), which make them useful in genetic diversity studies. Additionally, four loci  showed moderate polymorphism (PIC > 0.40)  to 17 (ETH003), while the mean number of alleles per locus (Name loci . Ne rang > 0.40) . ShannonIS, FST and FIT) for the overall populations are given in IS  was moderate to low, while HS (0.67) was relatively high.The values of fixation indexes , the expected heterozygosity (He), the coefficient of gene distinction (GST), the DST value and Nei’s gene diversity index (HT) per locus was given in The observed heterozygosity (HST) over the 20 loci was 0.030 ± 0.021 (p < 0.01). The GST values for single loci varied from −0.001 for CSSM029 to 0.098 for CSSME070. The gene differential coefficient GST (3%) indicated that most of the total genetic variation was due to intra-population difference and only a few existed among populations, which implied these Turkish water buffalo populations had relatively less genetic diversity and distinctiveness. Nei’s gene diversity index (HT) for loci ranged from 0.44 (CSSM033) to 0.88 (CSSM045), with an average of 0.69.The average coefficient of gene distinction (Gp < 0.001) in the whole population, whereas the other two loci showed different significant differences  (p > 0.05). The number of these markers ranged between 5 loci in İstanbul-Çatalca (IST) to 14 loci in Tekirdağ (TEK) and GIR populations. All the studied populations performed highly significant departure  from the Hardy–Weinberg equilibrium when considering all microsatellite loci. This departure and the high positive mean values of FIS  to 0.241 (BMC1013). We identified only one locus (BMC1013) that had potential null alleles at high frequency (r ≥ 0.2) in at least one breed. It has been observed that the frequencies of other microsatellite loci are lower than (0.20) (Eighteen of the 20 microsatellite loci found a highly important departure from Hardy–Weinberg equilibrium (HWE) ( < 0.05) . But, whs of FIS  may reman (0.20) .ST, Reynold’s and Nei’s DAS genetic distances in ST values of pairwise comparisons among the 17 Turkish water buffalo populations are given in ST values of pair-wise comparisons among the 17 populations (the matrix is shown in ST of (0.032 ± 0.018) and pairwise FST values ranging from 0.0000 ) to 0.0866 (BUR vs. Çorum (COR))  for all the studied loci (p < 0.05). For Hypothesis (II), AMOVA analyses outcomes indicated that the variation among groups, among populations within groups, among individuals within populations and within individuals was 2.15%, 2.02%, 8.34% and 87.49%, respectively. Variance components among groups, among populations within groups, among individuals within populations and within individuals were significant (p < 0.001) for all the studied loci implementing significant Reynold’s genetic distances distribution in studied Turkish water buffalo populations  test was performed to evaluate genetic variability is distributed within and among populations. We calculated possible structures by composing and contrasting different population groups. We performed the analysis under two hypotheses: For Hypothesis (I), the AMOVA analyses results showed that most of the molecular variation occurred within individuals (88.33%), while it represented 0.55% among geographic groups, 2.69% among populations within groups and 8.42% among individuals within populations . Variancied loci , implemeulations .The principal component analysis (PCA) of 17 Turkish water buffalo populations due to 20 microsatellite markers is shown in The genetic structure of each population was identified regarding admixture level for each water buffalo individual using a correlated allele frequencies model implemented within the STRUCTURE software. The results of Delta K (∆K = 92.42) represented that the optimal number of genetic clusters indicating most like ancestral breeds was at K = 2 A. The vaHypothesis I:Populations were assigned according to geographical distribution into six groups: (1) MRM = IST, TEK, BAL and BUR; (2) BSR = DUZ, GIR, AMS, TOK, COR, SIN and SAM; (3) AER = AFY; (4) CAR = KAY and SVS; (5) EAR = MUS and BIT; and (6) SAR = DYB.Hypothesis II:Populations were assigned according to neighbor-net dendrogram constructed from Reynold’s genetic distances distribution into three groups: (I) BSR = GIR, AMS, TOK, COR and SIN; (II) AER = AFY; and (III) IST, DUZ, BAL, BUR, DIY, TEK, SVS, KAY, SAM, BIT and MUS.The studies of genetic diversity play a significant role in developing breeding strategies and programs for livestock. In order to retain genetic variation, breeding strategies that increase effective population size minimizing the genetic drift effect should be performed. Microsatellite markers in combination with recent scientific applications of statistic showed a powerful tool for the conservation of native breeds .The advantage of using microsatellite DNA polymorphism to estimate genetic diversity among breed and among associated populations has been researched in livestock such as water buffalo ,40,41,42a), the number of effective alleles (Ne), allelic richness (Rs), Shannon’s Information Index (I) and polymorphic information content values (PIC) showed that most of the studied loci were highly informative, indicating high polymorphism across the loci, thus suggesting the suitability of these microsatellite markers for genetic diversity studies in Turkish water buffalo populations. The values of genetic diversity parameters were higher compared with a similar study of Asian water buffalo population  [a, Ne, PIC and HO) obtained from this study were higher than previous research in Turkish water buffalo [All measures of genetic diversity: the mean number of alleles (Nd China) ,53,54,55d China) ,38,56, Nd China) ,56,57, sd China)  and Soutd China) . Molecul buffalo ,17,18. TThe allele diversity for Turkish water buffalo populations was lower than that of the Colombian buffalo population studied with 10 microsatellite loci ,58,59,60E = 0.53), Ravi(HE = 0.55), Nili-Ravi (HE = 0.54), Kundhi (HE = 0.45), Azi-Kheli (HE = 0.44) [E = 0.4048; Popa et al. [E = 0.527; Rushdi et al. [E = 0.649), Brazilian Jaffarabadi (HE = 0.643), Cuban Buffalypso/Carabao hybrid (HE = 0.599) [E = 0.44; Saputra et al. [E = 0.61, Sraphet et al. [E = 0.54, Acosta et al. [E = 0.509, Uffo et al. [E respectively; 0.57 and 0.59; Moioli et al. [E = 0.558; Marques et al. [E = 0.70; Ángel-Marín et al. [E = 0.67; Aminafshar et al. [E = 0.5359; Özkan Ünal et al. [E = 0.50; Barker et al. [E = 0.53, Zhang et al. [E = 0.75; Darestani et al. [E = 0.86; Jaayid and Dragh, [E = 0.71–0.78; Kumar et al. [E = 0.759; Van Hooft et al. [Another measure of genetic variability is expected heterozygosity where the maximum expected heterozygosity (0.7280) was showed in the MUS population and the minimum 0.5833) was shown in the BUR population. This study results indicate the 17 tested Turkish water buffalo population have substantial amount of genetic diversity, when compared to some other water buffalo breeds around the world where, Pakistan water buffalo breeds such as, Nili (H = 0.44) , Romania33 was shi et al. ); Cuban = 0.599) , Indonesi HE = 0., Kundhi a et al. ; HE = 0.o et al. ), Italiai et al. ), Brazils et al. ), Colombn et al. ), Guilanr et al. ), some ol et al. ), Asian r et al. ) and ChiviHE = 0., Nili-Rar et al. ), and Aft et al. ).IS) shows the excess of homozygosity in a subpopulation and, with reference to molecular markers, informs if a pattern of reduction in diversity based on several causes exists. The positive FIS values showed heterozygotes deficiency within populations. This deficit might be because of inbreeding and the Wahlund effect. The mean FIS value of the Turkish water buffalo populations was 0.1170 (p < 0.05) and is similar to that obtained by Uffo et al. [IS [IS in Turkish water buffalo can be considered higher compared with other populations (FIS = 0.1170) like the results reported by Shokrollahi et al. [p < 0.001) FIS value (0.1820) showed a rather high inbreeding degree within the population. The heterozygote deficiency performed in the AMS population could be because of the higher rate of inbreeding, the population subdivision (Wahlund effect) and the presence of “null alleles” . Another possible reason for the high values of inbreeding could be due to their small population size, a small number of breeding males and their limited geographical area of dispersion [The estimate of inbreeding value , indicating that there is a general lack of heterozygous individuals in the Turkish water buffalo populations of 12%. In the study that the FIT value was considerably lower than the Pakistan buffalo populations [The Fulations , Cuban wulations  and Turkulations ,18, and ulations , Darestaulations , Marreroulations  and Acosulations .ST and genetic distance values. The null allele frequencies in the studied microsatellite loci were below 20% except for BMC1013 loci (24.09%). The lowest and highest null allele frequencies were 0.168 (CSSM036) and 0.2409 (BMC1013), respectively. Taking this value into consideration, it has been implemented that the studied 19 loci can be safely used in paternity tests (except for BMC1013 loci).The presence of null alleles, defined as non-amplifying alleles, due to mutations at PCR priming sites, causes overestimation of both FPIC value is a parameter indicative of the degree of in formativeness of a microsatellite, may range from 0 to 1. PIC values calculated in this study were comparable with those revealed by Popa et al.  in the RST value obtained from this study can be considered as an indicator of low genetic diversity between 17 Turkish water buffalo populations. The average GST value obtained from the overall loci pointed out that 3% of total genetic diversity resulted from the differences between the populations. In all other respects, it can be said that 97% of genetic variation is caused by the difference between individuals. The GST values were considerably lower than Ángel-Marín et al. [p > 0.05, p > 0.01, p > 0.001).Mean value of DST indicating genetic diversity between populations, GST, which is an important indicator of the relative magnitude of genetic differentiation, and HT, described as total genetic diversity, values were found as 0.021, 0.030 and 0.694, respectively. The Dn et al.  in ColomST index. In regard to all pairwise differences (Slatkins linearized FST) in this study, the distribution of FST represented low genetic divergence (0.000 < FST < 0.0866) among populations in general. The FST comparison values obtained were significant in 118 pairwise calculations . The highest level of differentiation was obtained between COR–BUR and TOK–BUR populations (FST > 0.0866), and the lowest between KAY–BIT and KAY–SVS populations (FST = 0.000), respectively. Thus, the average proportion of genetic differentiation among breeds was 3.2%. This value is lower than the 16.8% found in another genetic study on Asian buffalo [ST value differences between the buffalo populations belonging to the provinces that are geographically close to each other are quite low but important. The reason for this is thought to be due to the male bull changes between nearby provinces.Population differentiation was analyzed by estimation of the F buffalo , Indian  buffalo , Turkish buffalo , Cuban a buffalo  and Paki buffalo , but hig buffalo . In the ST index findings; AFY population clustered in an intermediate position between the Black Sea Region’s buffaloes  (Cluster I) and another branch (III) formed by Marmara , BSR , Eastern Anatolia (MUS and BIT), Southeastern Anatolia (Diyarbakır (DYB)) and Central Anatolia (KAY and SVS) Regions’ buffaloes. Cluster II: we can obtain the nearest position at the center of the admixture network, indicating a lower genetic distance of TEK, DYB, BAL, SVS, KAY, MUS and BIT with the cluster comprising IST, DUZ and BUR populations. The results of the PCA are concordance with the neighbor-net representing the Reynolds distance network obtained in the present study , though fundamentally smaller than the within individual’s component.An AMOVA was implemented to analyze the relative contribution of different factors to the observed genetic variation, with each factor considered in a separate analysis, i.e., six groups according to the geographical prevalence , three groups according to Reynold’s genetic distances distribution: The first group is the BSR populations ; the second group is the AER population (AFY); third group comprises the MRM populations , BSR buffaloes , CAR buffaloes , EAR buffaloes  and SAR buffaloes (DYB). The AMOVA analysis data implemented that the majority of the obtained variance is because of differences among individuals within populations. Most of the variation is obtained within the individuals (88.33% Hypothesis I and 87.49% Hypothesis II), yet the differences among groups show only 0.55% and 2.15% of the variation, respectively. Among groups, among populations within groups and among individuals within populations were also an important origin of variation (ST, PCA and genetic distance results. Our results provide a broad perspective on the extant genetic variation and population structure of Turkish water buffalo populations.In this study, the analysis with the STRUCTURE program showed that Turkish water buffalo populations were grouped into two major lineages when K = 2 B. ClusteIdentification of within and between populations genetic diversity is a prerequisite for well-structured and sustainable animal breeding and conservation programs. The study, which was carried out by using 20 microsatellite markers, showed that within population genetic diversity was higher than between population diversity. This situation can be seen as an opportunity in terms of breeding programs and genetic conservation programs for these populations. Hence, it can be concluded that the Turkish water buffalo population possessed a considerable amount of genetic diversity due to the low pressure of artificial selection and the possibility of random mating; however, Turkish buffalo populations require a scientific production system in order to improve the production, without losing the significant genetic structure of these economically important animals.In this paper, we have provided noticeably powerful data on genetic diversity and population structure of Turkish water buffalo populations, which might be helpful for similar studies. Our results suggested the relatively low but statistically significant genetic diversity of 17 Turkish water buffalo populations and brought insight into the structure of the analyzed populations. This study is the first assessment of the molecular genetic diversity of six geographical regions’ water buffalo populations in Turkey. The findings on the genetic structure of Turkish water buffalo populations in the present study will have significant implications in formulating the future strategies for conservation and breeding programs.


Sinonovacula constricta is a commercially important bivalve in Japan. The current distribution of this species in Japan is limited to Ariake Bay, where the fishery stock is declining. It is necessary to understand the genetic population structure of this species in order to restore the fishery stock while preserving the genetic diversity of the clam. Here, we report for the first time the genetic population structure of S. constricta in Ariake Bay, Japan. Paired-end restriction site-associated DNA sequencing (RAD-Seq) analyzed samples of S. constricta collected from seven mudflats located along Ariake Bay. Two different genetic populations exist in Ariake Bay, one inhabiting wild habitats and the other inhabiting the transplanted area of artificial seedlings. Our results suggest that genetic differentiation occurred between these two populations , and a high level of genetic differentiation is maintained between the two groups. In the future, monitoring the interbreeding status of the two genetically distinct populations and the genetic differentiation within each population is important for conserving the genetic diversity of S. constricta in Japan.The razor clam  In artificial seed production, large numbers of seedlings are often produced by a few broodstocks and released into natural seawater, which reduces the genetic diversity of wild populations in the field. Therefore, when seedlings are produced and released into natural seawater, there is a need to understand the genetic structure within the wild population in order to preserve genetic diversity.The technique of artificially producing seedlings and releasing them into fishing grounds is an effective method of aquaculture enhancement. This technique has been implemented with a variety of fishery species  is an important economic species in East Asian coastal waters10 and is widely farmed in China10. This species was once distributed from central to western Japan12 but is now restricted to the mudflats around Ariake Bay on the west coast of Kyushu in western Japan. In Japan, razor clams are not farmed, and the catch depends on the amount of resources in natural seawaters. According to a report by Ministry of the Environment, Japan13, the annual catch of S. constricta in Ariake Bay often recorded more than 1000 tons per year from the 1900s to the early the 1920s, but it decreased to less than 500 tons in most years from the latter half of the 1920s to the latter half of the 1980s, and no catches have been made since 1994 because of the marked decline in the abundance of this species. In order to restore the S. constricta resources, the Saga Prefectural Ariake Fisheries Research and Development Center has developed seed production techniques15, and since 1988, artificial seedlings of S. constricta have been released into the transplanting areas established in natural seawaters16 and have been conserved in transplanting areas as populations to produce subsequent generations. However, the genetic population structure of S. constricta within Ariake Bay has not been examined.The razor clam 20. In the present study, to clarify the genetic population structure of S. constricta in Ariake Bay, we conducted field sampling surveys at 11 mudflats located along the bay in 2019  mm for the 3-year-old seedlings produced in 2016  and 92.9 (± 1.1 SD) mm for the 5-year-old seedlings produced in 2014 .We collected 28 razor clams from seven of the 11 mudflats and found no razor clams on the remaining four mudflats  than those in the wild habitat (from 0.53 to 0.56). There were no significant differences in shell morphology between these two genetically different populations  showed different results from other seedlings collected in the same area, and belonged to a population consisting of individuals collected from the wild habitat Figs. , 5a,b. SS. constricta have been released by the Saga Prefectural Ariake Fisheries Research and Development Center into transplanting areas established in several mudflats along the coast of Ariake Bay. The seedlings collected from the transplanted area in this study (Takori_b and Takori_c) originated from parents at the Nanaura mudflat (hereinafter referred to as Nanaura lineage population), since the parents were collected from the Nanaura mudflat before 2010 and released into the transplanting areas of the Takori mudflat. In contrast, individuals collected from the wild habitat of Kashima, Nanaura, and Takori mudflats are likely to have originated from parents of Kashima mudflat (hereinafter referred to as the Kashima lineage population). In 2017 and 2018, the seedlings produced by parents collected from Kashima mudflat were released into new transplanting areas at Takori and Nanaura mudflats due to declining populations in wild and transplanted areas in these mudflats. Therefore, the 1- to 2-year old individuals collected in wild habitats in 2019 were likely the offspring of the transplanted Kashima seedlings in 2017 and 2018.The reason for the differences between these two populations is the different parental origins of the seedlings. The parental origins can be divided into the Nanaura mudflat and the Kashima mudflat for a number of reasons. Artificial seedlings of 24, including that of S. constricta 25. Anthropogenic transplantation likely strongly influenced the distribution of the genetic population structure of S. constricta in Japan. Comparison of the genetic distribution of species with a life history similar to that of S. constricta but those that are not exploited for fisheries can enhance our understanding of anthropogenic impacts on the genetic distribution of S. constricta in the Ariake Bay.Artificial transplantation of aquatic organisms has been reported to alter the geographic genetic structure of wild populationsFst values are widely used as a measure of the degree of genetic differentiation among and within populations28. According to Niu et al.25, the Fst value among populations of S. constricta at ten sites along the coast of mainland China is 0.044. The Fst value between the two populations in the present study was 0.052, suggesting that a similar level of genetic differentiation occurred between the two populations in Ariake Bay, Japan.For artificial seed production and release of seedlings, it is necessary to understand the distribution of populations with different genetic structures in natural seawater. Therefore, it is necessary to select broodstocks and release areas according to the degree of genetic differentiation among and within populations. For these two populations, the genetic differentiation within each population was maintained at a high level, and its variation was greater within the population consisting of individuals collected from the transplanted area Fig. . There aS. constricta is estimated to be very low based on the CPUE results of this study  avoidance of line breeding, (II) selective use of wild-born individuals, (III) line breeding, (IV) avoidance of artificial breeding of males, and (V) selective use of wild-born malesion Fig. . TherefoS. constricta in the Ariake Bay, Japan. Additionally, our results suggests that genetic differentiation within each population is maintained at a high level. In the future, monitoring the interbreeding status of the two genetically distinct populations and the genetic differentiation within each population is important to enhance the stock of S. constricta in Japan by producing and releasing seedlings, while preserving genetic diversity. As there was no significant difference in the morphology of the shells of these genetically distinct populations , calculated as the number of clam individuals collected divided by the number of explorers and sampling time . The samples were stored at − 80 °C until genomic DNA extraction. In addition to the collected individuals, the oldest seedlings  stored at the Saga Prefectural Ariake Fisheries Research and Development Center, were included in the RAD-Seq analysis for comparison with seedlings produced in the past. Genomic DNA was extracted from finely chopped foot tissue of the specimens using DNAs-ici!-F , and the concentration of the DNA was assessed using a Qubit 3.0 Fluorometer (Thermo Fisher Scientific).Sampling of the razor clam the EcoRI RAD-Seq library has been described previously28, based on the established method31. The library was sequenced with 150 bp paired-end reads in one lane of an Illumina HiSeq X . The RAD-Seq data were analyzed using the Stacks program (version 2.52)32. The data were quality filtered using the process_radtags program in the Stacks package . Filtered sequences were registered in the DRA (DRA accession number: DRA010922). The data were aligned with the reference genome of S. constricta33 (NCBI/DDBJ BioProject number: PRJNA508451) using BWA-MEM (version 0.7.17)34. Aligned data were analyzed using the ref_map.pl script of the Stacks package.The preparation for 35. The VCF file was created by the populations program of the Stacks package 36. The admixture analysis was conducted based on the PLINK file using ADMIXTURE (v. 1.3.0)37. The PLINK file was created with the same Stacks populations program that created the VCF file38. The genetic diversity of razor clams among and within populations was assessed using AMOVA Fst values obtained from ‘populations.fst_files’, which were calculated by the Stacks populations program. To visualize the distribution of all data points, pairwise Fst values between individuals in each population are shown in boxplot with beeswarm using R (package: ‘beeswarm’)39.Principal component analysis (PCA) was conducted based on a variant call format (VCF) file using the SNPrelate program (v.1.18.1)40  = 1000, and −m = GTRGAMMA). The SVDquartets analysis based on the coalescent model was computed as implemented in PAUP ver. 4.0a 167 using multiple alignments42. The number of bootstrap analyses replicates was 1000. In each analysis, the oldest samples , were used as the root.Phylogenetic tree analysis was performed using two different approaches: the maximum likelihood (ML) method and SVDquartets analysis. Multiple alignments within the cluster were obtained using the Stacks package populations program mentioned earlier. The phylogenetic tree based on the ML method was constructed using the RAxML program (version 8.2.12)Supplementary Figure.


The mitochondrial DNA (mtDNA) has been used to trace population evolution and apply to forensic identification due to the characteristics including lack of recombination, higher copy number and matrilineal inheritance comparing with nuclear genome DNA. In this study, mtDNA control region sequences of 91 Kirgiz individuals from the Northwest region of China were sequenced to identify genetic polymorphisms and gain insight into the genetic background of the Kirgiz ethnic group. MtDNA control region sequences of Kirgiz individuals presented relatively high genetic polymorphisms. The 1,122 bp sequences of mtDNA control region could differ among unrelated Kirgiz individuals, which suggested the mtDNA control region sequences have a good maternal pedigree tracing capability among different Kirgiz individuals. The neutrality test, mismatch distribution, Bayesian phylogenetic inference, Bayesian skyline analysis, and the median network analyses showed that the Kirgiz group might occurred population expansion, and the expansion could be observed at about ∼53.41 kilo years ago (kya) when ancestries of modern humans began to thrive in Eurasia. The pairwise population comparisons, principal component analyses, and median network analyses were performed based on haplogroup frequencies or mtDNA control region sequences of 5,886 individuals from the Kirgiz group and the 48 reference populations all over the world. And the most homologous haplotypes were found between Kirgiz individuals and the East Asian individuals, which indicated that the Kirgiz group might have gene exchanges with the East Asian populations. The Kirgiz group is one of the official minority ethnic group in China. According to the seventh census, there are about 186 thousand Kirgiz individuals in China, which are mainly located in the Northwest China. Additionally, hundreds of Kirgiz individuals are settled in Chinese Heilongjiang Province. The Kirgizs speak Kepchak, which is a subgroup of the Turkic group of Altaic language family. In China, the history of the Kirgiz group can be traced back to the period of Emperor Wu of the Western Han Dynasty (109–91 BC), and since then the Kirgizs have the appearance characteristics of both European and East Asian people according to the historical record . Later, In previous studies researchers Guo et al. , Xie et The control region, also known as the D-loop region, is a sequence of 1,122 bp on the mtDNA, including two segments at 1-576 and 16024-16569, respectively . The mulBased on the massively parallel sequencing (MPS) platform, the influences of multiple copies of mtDNA and the homologous fragments of nuclear DNA make that the mtDNA data often require deeper sequencing depth, and well-balanced sequencing read and amplicon to ensure the obtained reliable results . In addiIn total, bloodstains within FTA™ cards were collected from 91 unrelated healthy individuals of the Kirgiz group in the Northwest region of China. The detailed sampling locations of all 49 populations including Kirgiz group and 48 reference populations were shown on the world map in Genome mtDNA of the 91 bloodstain samples was extracted with the PrepFiler BTA™ forensic DNA extraction kit . The magnetic bead method was used for DNA extraction by the above kit. The extraction method selected in this study combined uniquely structured magnetic particles and the optimized multi-component chemistry surface, to provide efficient DNA binding capacity and high DNA recovery rate. The extracted genome DNA was quantified with the Qubit™ dsDNA HS assay kit (Thermo Fisher Scientific) at the Qubit™ four Fluorometer (Thermo Fisher Scientific). The mtDNA control region sequences of 91 unrelated individuals and positive control samples (007 and 9947A) were amplified using the Precision ID mtDNA Control Region Panel (Thermo Fisher Scientific). The libraries were prepared with Precision ID DL8 Kit (Thermo Fisher Scientific) on Ion Chef™ System (Thermo Fisher Scientific). The mtDNA control region was amplificated with 14 primer pairs in two primer pools. The libraries were quantified using the Ion Library TaqMan™ Quantitation Kit (Thermo Fisher Scientific) on the 7,500 Real-Time PCR System (Thermo Fisher Scientific). The sequencing templates were prepared using with the Ion S5™ Precision ID Chef & Sequencing Kit (Thermo Fisher Scientific), and were loaded to the Ion 530™ Chip (Thermo Fisher Scientific) on the Ion Chef™ System (Thermo Fisher Scientific). The sequencing runs were accomplished using the Ion S5™ Precision ID Chef & Sequencing Kit (Thermo Fisher Scientific) on Ion S5™ XL System (Thermo Fisher Scientific). All the above experimental procedures were performed strictly according to the manufacturer’s recommendations.http://www.phylotree.org/tree/index.htm) of human mitochondrial DNA lineages, further allocated the haplotypes to the closest haplogroups, which were submitted to the EMPOP database for quality control  of MPS mtDNA module with HID Genotyper 2.2 of default parameters. After aligning to the Revised Cambridge Reference Sequence (rCRS) , all the control . The hap control . The anaA total of 5,795 individuals from 48 reference populations distributed all over the world were chosen for further investigation of the genetic relationships among the studied Kirgiz ethnic group and the reference populations based on the mtDNA control region sequences. The sample size of each selected population was more than 30 individuals. The 48 reference populations included seven populations from Africa, five populations from North America, six populations from South America, nine populations from Europe, four populations from Central Asia, eight populations from East Asia, four populations from South Asia, two populations from Southeast Asia and four populations from West Asia. The detailed information of the Kirgiz group and these 48 reference populations was showed in To evaluate the sequencing performance, we calculated several parameters including the true allelic ratio, noise ratio, ratio of two sequencing directions and the mean depth of each sample, the average depth of each amplicon, and the depth ratio between two primer pools of each sample. The true allele ratios were calculated by dividing the read depth of the true allele into total read depth of each sample, and the remaining undefined reads were defined as noise. The sequencing ratios were calculated by dividing the coverage of 5′ reads into the 3’ reads. The mean depth per sample and average depth of each amplicon were also calculated directly. The depth ratios were by dividing the lowest read depth into the greatest read depth of each sample.https://haplogrep.i-med.ac.at/app/index.html) under the Kulczynski measure. The example case of U1a2 with detailed calculation formula could be found at the website https://haplogrep.i-med.ac.at/2018/06/21/explaining-the-formula/. These mutations including 309.1C(C), 315.1C, 515-522 InDel of AC, A16182C, A16183C, 16193.1C(C), C16519T and T16519C were excluded when the phylogenetic tree was reconstructed, and the tree was showed in The haplogroup frequencies based on the mtDNA control region sequences of 91 Kirgizs were calculated directly. The phylogenetic tree for 91 Kirgiz mtDNA control region sequences was performed using the online tool of HaploGrep 2 v2.0  million years ago (MYA) (http://tree.bio.ed.ac.uk/software/figtree/). The detailed geographical coordinates and the macrohaplogroup compositions of all the populations were visualized using Tableau Desktop v 2021.1. Heatmap was constructed using the ‘heatmap’ package of R statistical software based on the pairwise FST values between the Kirgiz group and 48 reference populations (https://www.r-project.org/). A neighbor-joining (NJ) tree was built using Molecular Evolutionary Genetics Analysis (Mega) v10.2.1 based on the pairwise FST values among 49 populations. And the NJ tree was displayed and annotated using the online tool iTOL v 6.1.2 (https://itol.embl.de/itol.cgi). The two-dimensional (2D) and three-dimensional (3D) principle component analyses (PCA) were constructed using the dimensionality reduction analysis module of SPSS Statistics v.19.0 based on the haplogroup frequencies generated from mtDNA control regions of the Kirgiz group and 48 reference populations. The haplogroup network calculations were performed using Network v.10.2.0.0 of the median joining module based on the mtDNA control region sequences from the Kirgiz and the 48 reference populations, finally, of which 1,403 individuals from the 48 reference populations sharing the same or similar haplogroups with the target Kirgiz individuals were selected to participate in the network relationship evaluations. The following network plots were visualized with the network publisher (https://www.fluxus-engineering.com/nwpub.htm).DNA Sequence Polymorphism v6 (DnaSP v6)  was usedgo (MYA) . The adago (MYA)  and the All the mtDNA control region sequences from the 91 Kirgiz individuals and the positive control samples (9947A and 007) were successfully generated from four sequencing runs on the Ion S5™ XL system. The true allelic ratios and noise ratios were shown in The phylogenetic tree of mtDNA control region mutations generated from 91 unrelated Kirgiz individuals was performed using the online tool HaploGrep v.2.0 based on the latest mtDNA tree Build 17, and the result was shown in A total of 66 haplogroups and 81 haplotypes were identified from 91 Kirgiz unrelated individuals based on mtDNA control region sequences. The variants , haplotypes and allocated haplogroups of 91 Kirgiz individuals were shown in p-value < 0.05) and Fu’s FS test  of mtDNA variants for the 91 Kirgiz individuals were both calculated to be relatively large negative values, and the results might indicate that the variants were significantly deviated from neutral mutations.DNA polymorphisms of the studied Kirgiz group were evaluated, and the results of indexes were presented as follow, number of polymorphic site (S: 107), number of haplotype (h: 81), haplotype diversity (Hd: 0.997), nucleotide diversity (Pi: 0.00842) and the average number of nucleotide difference (k: 9.017), these parameters indicated the relatively high genetic diversities of mtDNA control region sequences was in Kirgiz group. The Tajima’s D test , 0.00689  for the sudden expansion model, 0.00216  and 0.00689  for the spatial expansion model, respectively. The median network calculation was performed based on the mtDNA control region sequences of the 91 Kirgiz individuals, and the network plot of 91 Kirgiz individuals was shown in . The expansion time with the largest slope of the BSP abscissa was directly read. And the BSP abscissa showed that the Kirgiz group had grown at about 53.41 kya , Valles (VAL) and Colombian in Medellin (CLM). Among Chinese nine populations, the smallest three FST values were observed between Kirgiz and Beijing Han Chinese (CHB), East Pamiri Kyrgyz (EPK) and Southern Han Chinese (CHS).Pairwise PCA was conducted to evaluate the genetic affinities among Kirgiz group and reference populations based on the haplogroup frequencies in terms of maternal inheritance, and the haplogroup distributions of Kirgiz group and 48 reference populations were shown in To evaluate the network relationships between Kirgiz and other reference populations, all the 91 Kirgiz mtDNA control region sequences were compared with the individual sequences from 48 reference populations, and six median network graphs were finally generated. In total, 460 different individual sequences of macrohaplogroup M were distributed into seven different haplogroups, as 62 of D4, 36 of M1, 216 of M, 44 of G, 63 of M8, eight of D1, and 31 of D5, respectively. The median network diagrams of macrohaplogroup M with the largest proportion of Kirgiz group were labeled by different colors for different geographical locations, and different haplogroups were shown in The commonly observed Western Eurasian haplogroup including the H, T, U, W, X2, J1, N1, HV and R0 was the second-largest haplogroup in the Kirgiz group. These 27 Kirgiz individuals were allocated into this category. The Western Eurasian haplogroup of 27 Kirgiz individuals was allocated into nine above-mentioned haplogroups and nine different network plots labeled with colors for different continents  and diffThe 14 individuals of Kirgiz group were allocated into the macrohaplogroup R. Combining with 263 individuals from reference populations, 277 mtDNA control region sequences were distributed into four different haplogroups. And these four different network plots were shown in The smallest macrohaplogroup proportion of 91 unrelated Kirgiz individuals was N macrohaplogroup. The 25 sequences from the reference populations and seven sequences from the Kirgiz group were used to draw the median network diagram of the N macrohaplogroup. And the diagram of each haplogroup was labeled by different continents and haplogroups with different colors . Within p-value < 0.05) and Fu’s FS test  indicated that the Kirgiz group experienced population expansion during its history as the previous study recommended , haplotype and nucleotide diversities (Hd:0.997 and Pi: 0.00842), and the average number of nucleotide differences (k:9.017) as Zimmermann said . The 91 ommended . The smaommended . The expscovered . AdditioFST values were calculated based on haplogroup frequencies. And the FST heatmap showed the genetic differentiations between Kirgiz group and the reference populations. In the NJ phylogenetic tree, most of populations from the same continent clustered together except the immigrant populations like African America and Caucasians from North America. In addition, the Kirgiz group had the three smallest FST values with CHB, EPK and CHS populations from China, which indicated relatively close genetic affinities between Kirgiz and these three populations according to the criteria of genetic differentiations of Wright  were identified among these mtDNA control region sequences of Kirgiz individuals. In addition, we evaluated the mtDNA genetic diversities in the Kirgiz group and gained insight into its genetic relationships with 48 reference populations all over the world. This study on the genetic diversities of mtDNA control region sequences in Kirgiz ethnic group might promote the understanding the genetic background of Kirgiz ethnic group and lay the foundation for the researches of maternal pedigrees, and promote the case investigations involving matrilineal families.


Thunnus maccoyii Castelnau, 1872) is distributed across most of the southern temperate ocean and migrates extensively between 30°S and 50°S. Since T. maccoyii has been continually and heavily exploited, it is necessary to investigate the genetic diversity, population structure and demographic history of T. maccoyii for effective management and conservation. Thirty-seven gonad tissues of T. maccoyii were sampled from two locations, which were in the eastern Indian Ocean and the eastern Atlantic Ocean, by scientific observers onboard Korean T. maccoyii longline vessels in 2015. We compared 1240-bp sequences of combined mitochondrial DNA (mtDNA) from the cytochrome c oxidase subunit I  and control region  sequences. The pairwise fixation index (FST) and maximum-likelihood tree showed that two clades (A and B) were formed regardless of locations. Clade A occurred more commonly than clade B in both localities: the occurrence ratio of clade A was 69% in the Indian Ocean, and 79% in the Atlantic Ocean, respectively. Our findings suggest that a historic differentiation event may have occurred in T. maccoyii, but recently the connectivity between the two oceans may be possible in T. maccoyii populations.Southern bluefin tuna ( Thunnus maccoyii Castelnau, 1872) is a large, long-lived, and highly migratory fish found throughout most southern temperate oceans except the more easterly regions of the southern Pacific  and hypervariable portion of the control region (CR) have been broadly used to identify fish species, including tunas, and to clarify population structure  and in the eastern Atlantic Ocean (G2) from April to September 2015 . The thermal regime consisted of an initial denaturation at 94 °C for 5 min; 34 cycles of denaturation at 94 °C for 40 s, annealing at 51 °C for 45 s, extension at 72 °C for 1 min; and final denaturation at 72 °C for 5 min; the mixture was then maintained at 4 °C. The ∼650-bp fragment of COI was amplified using the primers VF2_t1 (5′-TCA ACC AAC CAC AAA GAC ATT GGCAC-3′) and FishR2_t1 (5′-ACT TCA GGG TGA CCG AAG AAT CAG AA-3′)  with a Bio-Rad T100 Thermal Cycler (Bio-Rad). The thermal regime consisted of an initial denaturation at 95 °C for 5 min; 34 cycles of denaturation at 95 °C for 1 min, annealing at 52 °C for 1 min, extension at 72 °C for 1 min; and final denaturation at 72 °C for 5 min; the mixture was then maintained at 4 °C. The PCR products were purified with ExoSAP-IT  and then were sequenced with the ABI PRISM BigDye Terminator v3.1 Ready Reaction Cycle Sequencing Kit on an ABI 3730xl DNA Analyzer .Genomic DNA was extracted using 10% Chelex 100 Resin  from the gonadal tissues. The 736-bp fragment of the CR was amplified using the primers JEGY-F (5′-ACC GGA CGT CGG AGG TTAAA-3′) and JEGY-R (5′-TGG GCC ATA AAA TAC CCC ACTC-3′) that were newly designed to suit T. maccoyii deposited at the National Center for Biotechnology Information (NCBI), USA (h) (Nei π) (Nei and Li FST) was calculated to investigate the genetic differentiation between the populations, and using Arlequin. A haplotype network was inferred from the median-joining network constructed using Network ver. 4.6.1.3 software . Evidence of population expansion was tested with Fu's Fs  , USA . DnaSP vBI), USA  was used (h) Nei  and Nucl's Fs Fu  and neutD Tajima  using Arnsion Li  and θ0 ad Wilson  and Mandd Wilson . FurtherT. maccoyii individuals. The COI sequences from two localities identified 37 haplotypes, and 13 polymorphic sites were detected, with 12 transitions and one transversion. The CR sequences identified 37 haplotypes, and 217 polymorphic sites were detected, with 187 transitions and 28 transversions. Haplotype diversities (h) were 1.000 in both localities and markers, while nucleotide diversities (π) differed greatly between markers: 0.002 in COI, but 0.033–0.039 in CR. The COI and CR genes showed that the T. maccoyii population had consistent haplotype and nucleotide diversities between two localities, indicated by the high level of haplotypes and the low level of nucleotides. And for the combined gene the h value was 1.000 and the π value ranged from 0.017 to 0.020      between the two localities did not have statistically significant values, so the indices between the two clades (A and B) were observed  based on the combined sequences   of two clades indicates that the sudden population expansion is estimated to have occurred 229,461 years ago.Tajima's < 0.001) , which m