Quercus cerris L.) is widely distributed in Italy, where it is the ecologically dominant oak on sandy and acidic soil. In this work, we analysed 23 natural populations by means of eight SSR (microsatellite) markers, to obtain the first synthetic map of genetic variability for this species and to study its dispersion during the Holocene, due to the possibility that at least one refugium during the Last Glacial Maximum was in Italy. The analyses showed a good amount of genetic variability together with fair differentiation between populations, as indicated by STF = 0.059. A Bayesian analysis of the amount of admixture among populations revealed the presence of four putative gene pools of origin and a rough subdivision of the populations according to their geographic location, as confirmed by the spatial analysis. No evidence for the existence of putative refugial populations was found; however, this study paves the way for the planning of conservation strategies also with regard to the relationship between Turkey oak and other oak species in Italy.The Turkey oak ( However, aside from their importance for human culture, the different species of the genus Quercus are also of great interest for the study of the evolution of trees. In fact, it is commonly recognised a “complex of species” belonging to Quercus, due to the occurrence of a fair amount of hybridisation between the different species. This has been demonstrated for pedunculate and sessile oak, Quercus robur and Q. petraea, respectively; [Q. ilex and Q. suber [Q. petraea and Q. pubescens [Q. crassifolia and Q. crassipes [Q. coccifera and Q. ilex in Spain [robur, petraea, pubescens and frainetto) all interbreed [Quercus species is present but apparently not intermixing—this is Q. cerris, the object of our study.The oak is arguably the most famous amongst trees. Across Europe, oak trees have been revered as sacred to the major divinities of many cultures; the Latin name itself, “ctively; ,2,3 for Q. suber ,5,6,7,8,ubescens ,10; and rassipes . In the in Spain . Interspin Spain  for a reterbreed . In the Quercus cerris, a species of still uncertain provenance despite its common name and whose habitat is essentially limited to the Italian and Balkan peninsulas  in Italy, we sampled across most of the species’ Italian distribution range, discovering, in the process, at least one natural population in an area where the presence of Q. cerris was not previously described. In particular, we sampled 22 populations along the Italian peninsula and one in Sicily  throughout the species’ Italian distribution. Interestingly, a number of our sampled areas had unexpected Q. cerris distribution and represent a new finding in the Italian natural history of the species. These lie outside what is considered its ‘native distribution’ [To assess the genetic diversity of the Turkey oak  according to the manufacturer’s instructions.For every single tree, 4–5 young leaves, collected mostly in spring to early summer, were stored at room temperature in 10 mL of 95% ethanol until DNA extraction. Approximately 1 cmQ. macrocarpa [Q. petraea [Q. robur [Q. cerris and mapped onto different chromosomes in a comparative genetic map for Q. robur and C. sativa [a) for each SSR are listed in 2 25 mM , 0.4 µL 10 mM dNTPs , 0.4 µL 10 µM of each primer , 0.1 µL 5 U/µL GoTAQ® Flexi DNA Polymerase  and 1.5 µL genomic DNA 7.5 ng/µL. After screening several dinucleotide and trinucleotide simple sequence repeat (SSR) markers available from the literature, eight heterologous markers were selected: MSQ4 and MSQ13 developed in crocarpa ; QpZAG9  petraea ; QrZAG4,Q. robur . These m. sativa . The pria for 20 s and 72 °C for 30 s; followed by a final step at 4 °C.Amplification profiles of various loci included an initial denaturation step (94 °C for 2 min); followed by 35 cycles of 94 °C for 20 s, T™ as the molecular standard . Different amplicons were marked using fluorescent-labelled primers . Amplicons were scored using MegaBACE™ Fragment Profiler software version 1.2 (Amersham Biosciences).Genotyping was carried out on a MegaBACE™ 1000 automatic sequencer  in multiplexed runs (three markers each) and with the use of ET-Rox 400oH) and expected (eH) heterozygosity. Deviations from the Hardy–Weinberg equilibrium were assessed by Fisher’s exact test using a Markov Chain algorithm [F-statistics. In particular, ISF estimates which proportion of the total genetic variation is due to a departure from the Hardy–Weinberg equilibrium at the population level and STF estimates the amount of total genetic variation due to differentiation between populations. The STF analogue for microsatellites STR [STF/(1 − STF) and log-transformed geographical distances between populations underwent a Mantel test [genepop 4.0 [genetix [rstcalc [First, we estimated at each locus, for all populations, allele frequencies and observed  to assess the upper bound in the maximum number of clusters. As evidenced by Durand et al. [K. According to these results, the software was run 10 times for each number of clusters ranging from K = 2 to 10. Both these steps were carried out under the no-admixture model with 25,000 iterations, of which 10,000 were discarded as burn-in and setting the spatial interaction parameter at 0.6. To identify the most probable number of clusters and model options, we used an iterative approach. We first performed 20 runs, setting the number of clusters at d et al. , once thK were significantly lower than the model with (K − 1) using a series of one-tailed paired t-tests carried out with R 4.1.3 (One Push-up) [K by computing the coefficient of similarity based upon the G’ matrix pairwise similarity statistics implemented by the software clumpp 1.1.2 [The choice of the most probable number of clusters fitting the data was based on the score of the Deviance Information Criterion (DIC), which is computed by TESS and represents the average model deviance penalised by the effective number of parameters used in the model . Since bPush-up) . The propp 1.1.2 . A GreedK under the admixture model with 50,000 iterations, of which 30,000 were discarded as burn-in. Since gene flow is expected to be spatially restricted due to the species’ limited dispersal capabilities, we aimed at comparing models accounting either for broad-scale  and fine-scale  patterns or fine-scale patterns only. Hence, we ran both full regression models  and models without a spatial trend , respectively. We carried out 10 replicates for each model and then ranked them according to the lower DIC values. An additional 100 runs were completed for the most likely model, of which the 10 highest likelihood runs were retained and their clustering results were averaged using clumpp 1.1.2 by applying the Greedy algorithm with 10,000 replicates [We carried out a further series of runs for the selected plicates .The posterior spatial predictions were displayed on the geographic map of Italy using functions from the R 2.14.0  packagesdiyabc v2.1.0 [eN) to vary freely; this makes it possible for any demographic event to occur. The second method instead compares two opposite scenarios—a single expansion event or a single contraction event; these are then analysed using logistic regression to confirm the demographic model computed using the first method. The PABC index . The mutation model used was based on the GSM, Generalised Stepwise Mutation [−5; max = 10−3) and a stepwise constant P . Chosen summary statistics chosen were the average number of alleles, average genetic diversity and variance of average allele size. A total of 106 datasets were simulated for each scenario with the aforementioned variables. Approximate Bayesian Computation (ABC) was successively used on the four ancestral gene pools computed by TESS to conduct a model selection analysis, which infers possible variations in demographic scenarios. These analyses were performed using c v2.1.0  followinc v2.1.0 . The fire et al. ) was alsMutation  using anQuercus cerris samples were analysed using eight microsatellite markers, resulting in the identification of 265 distinct alleles. All studied loci are highly polymorphic: the number of detected alleles per locus across all the populations ranges from 20 (locus QrZAG96) to 40 (locus QpZAG9) with an average of 35 alleles/locus. No alleles were found to be fixed at any of the loci, nor did we find evidence that specific alleles were harboured by a given population. In general, the number of alleles/locus/population is remarkably constant, between 10 and 14 with the exception of populations VC , ES and VT . Genetic diversity, as measured by Nei’s heterozygosity (eH), is high  and 0.81 (MT population). A total of 809  is high , with thISF from zero under the null hypothesis. ISF values are significantly different from zero for at least four loci out of eight in all populations; two populations, MT and BS, have no loci in equilibrium. In most cases, deviation from the Hardy–Weinberg equilibrium was associated with positive ISF values, while negative ISF values were found in six cases only . The Hardy–Weinberg equilibrium was tested for all the loci and populations by testing the departure of The non-random association of the alleles at different loci, or linkage disequilibrium (LD), was investigated. Since the number of comparisons for pairs of loci with eight loci is 28 per population, we expect one or two false positives per population. When all populations showing only one or two pairs of loci in disequilibrium are removed, only nine populations display a significant departure from equilibrium at the 5% level: CM, BC, LI, MA, MG, BS, CO, BA and MD. Of these, the MA population is characterised by the presence of 10 pairs of loci in LD.STF and STR  out of 253 for STF and a few more for STR. The maximum STF value of 0.135 was found between the MG and LA populations, and the maximum RST value of 0.273 between the FI and CM populations. The MG population is noteworthy in the sense that it displays STF values higher than 0.09 in 15 out of 22 comparisons and higher than 0.2 in 16 out of 22 for STR. It is also to be noted that, overall, the pairwise STR values are constantly higher than the respective STF values. The genetic divergence among populations was measured using both  and RST . Their sSTF = 0.054 , it was estimated that about 5% of the genetic variance can be attributed to differentiation between populations. The same procedures for STR yielded an estimated overall STR = 0.071, with a confidence interval at 95% of 0.070 ≤ STR ≤ 0.104. The presence of correlation between genetic differentiation and geographic distance between populations was not evidenced by a Mantel test , indicating that the present distribution of genetic variation among the studied populations of Quercus cerris cannot be seen as the result of equilibrium between drift and gene flow.The overall genetic differentiation between populations was significant. By means of Q. cerris has not been studied yet in this regard in Italy, it is important to estimate K—the most probable number of ‘gene pools’ present in the data—in order to be able to suggest possible mechanisms that have shaped genetic variability and to recommend conservation strategies. This was achieved by applying the spatial Bayesian clustering method, as implemented by TESS, which allowed us to define spatially the region of most probable admixture of the alleles carried by each of the putative gene pools of origin. Because K was based on the DIC criterion  except the Sicilian/Pop4 (r0 = 1.53), who did not show a significant demographic change. The posterior coefficient r0 was also represented as distribution densities  than Q. robur and Q. petraea (0.79 and 0.85). The high variability is not restricted to the nuclear genome; as shown by Simeone et al. [Q. cerris shows very high diversity both for plastid DNA and for the spacer of 5S RNA when compared with other oaks of the sect. Cerris.The 23 natural y plants : all eigf et al.  in the se et al. , Q. cerrH. The latter hypothesis is the most likely, since we used SSR primers developed in the congener species Q. macrocarpa, Q. petraea and Q. robur for our analysis. In particular, the primers derived from Q. macrocarpa, the most phylogenetically distant species, are those displaying, on average, the lowest eH values in our populations. The possibility that linkage disequilibrium has arisen as a consequence of physical linkage between the loci can be ruled out. This is because SSRs that mapped on different chromosomes in a composite Fagaceae map [The detected deviation from the Hardy–Weinberg equilibrium is almost exclusively associated with a significant deficit of heterozygotes. It is possible to explain the heterozygote deficiency observed in the present study by a selection against heterozygotes or by the presence of null alleles (possibly arising from mutations in the region of homology to the SSR primers), which could have led to an underestimation of ceae map  were choceae map . HoweverQ. cerris. The estimate, based on STF = 0.054, is in the range already observed for other members of the Oak family; Muir and Schlötterer [STF values between 0.001 and 0.232, average 0.05, between Quercus petraea and Quercus robur analysing 20 microsatellites in 12 populations. In the only other large-scale study conducted in Italy, five populations of Q. petraea analysed at five SSRs were characterised by STG = 0.18 [STF = 0.148), was an outlier also in Quercus petraea and Quercus robur [Q. cerris; a support to this possibly comes from the other “outlier” in our study—the heterologous marker MSQ13. This marker has in fact been developed in the more distant Quercus macrocarpa and, hence, has possibly been unwillingly selected for its higher ability to detect differentiation. Genetic variability at this locus is low and results in the presence of different homozygotes in the populations studied. While the latter is a marker known for displaying high differentiation values in oak populations [He values, based on heterologous primers devised in Q. macrocarpa. If we remove MSQ13 from the dataset, the overall estimate for genetic differentiation will be STF = 0.059 (0.037 ≤ STF ≤ 0.099).A significant level of genetic differentiation was found between the Italian populations of lötterer  observedT = 0.18 . In oaksus robur , this inSTR, the STF analogue based on the stepwise mutation model. An overall value of STR = 0.071 was found, indicating that the populations studied were more differentiated in the past due to the ability of STR to detect differentiation events older than those revealed by STF. Range expansion and increased gene flow have both contributed to the homogenisation of genetic differences among populations. Genetic differentiation was evaluated also between pairs of populations and proved significant in most cases, based on a permutation test. Further, in this case, STR values are consistently higher than corresponding STF. The lowest differentiation was found, concerning STF, for the population pair AC–CV and BC–MA (STF = 0.05), BF–LI (STF = 0.01), and MT–SA (STF = 0.00), and concerning STR, for couples LA–ES (STR = 0.02), MA–BC and CO–CF (STR = 0.01), BE–BC, and CO–BA and MT–BR (STR = 0.00).The genetic divergence between populations was also estimated by Q. cerris is of the same order, albeit lower, than that experienced by other Quercus species. In the already cited paper by Curtu et al. [STF = 0.174 for isozymes and STF = 0.092 for SSRs. According to Corti et al. [Q. cerris is native to South-central and Southeastern Europe; Fineschi and Vendramin [What do these data tell us about the natural history of the species? It appears that the amount of genetic differentiation for u et al. , the ovei et al. , Q. cerrendramin  suggesteendramin  used fosK, the most probable number of ancestral gene pools or ‘inferred populations’ from the used data, is of both conservationist and phylogeographic importance. This is usually obtained by means of a Bayesian approach, a methodology that has been increasingly popular in the last two decades [K = 4. Each of these ancestral gene pools contributed in a different way to the twenty-three populations of Q. cerris sampled. The detection of  decades ,51. In tK, the number of panmictic units or ‘gene pools’ in the data, in order to be able to suggest possible mechanisms that have shaped the genetic variability observed. The use of a Bayesian approach to the detection of K has become increasingly popular in the last decade [K = 4 as the number of inferred populations from which the studied populations derive. The most precise interpretation of this value is that four homogeneous gene pools contributed to the twenty-three populations sampled. The distribution of the populations deriving their genetic makeup from the four pools, if not clear-cut, shows evidence of some geographic structuring, roughly northwest vs. southeast, with a zone of low admixture corresponding to a high degree with the valley of the Tiber river. It appears from these data that the colonisation of the Italian peninsula can be thought as having followed two routes; however, it is not possible yet to indicate their origin with an acceptable degree of certainty. The use of uniparentally inherited markers will allow us to further investigate this issue. Under this aspect, of particular interest could be the analysis of the scattered populations present in Southern France, because a reduced speed of re-colonisation for some European trees than previously estimated has been suggested [When dealing with conservation and phylogeographic issues, it is often necessary to detect t decade ,51. In tuggested . If thisr0 (present/past genetic diversity), as indicated by the sharp posterior distributions of r0 and the values of the PABC index, which are, with the exception of the “North” one, comparable with those deemed acceptable in previous studies [Q. cerris [The ABC approach allowed us to reliably estimate the posterior coefficient  studies . The gen. cerris  dated di. cerris .Q. cerris found a favourable environment in the Italian peninsula, leading to an increase in forest cover for this species in the last few hundred millennia. It has to be borne in mind, however, that Q. cerris lives in sympatry with several other species of white oaks; therefore, a genetic analysis at the genomic level could shed more light on the ecology of this species complex.In general, it looks like Quercus genu; so, it will be necessary to resort to a genetic analysis with higher resolution power to take into account the possible problems raised by sympatric species. The concept of “glacial refugia” has been recently challenged. Bennett and Provan  argued t


Lepidochelys includes the wide-ranging and abundant olive ridley (L. olivacea), and the geographically restricted and ‘Critically Endangered’ Kemp’s ridley (L. kempii). To investigate their historical biogeography, we analyzed a large dataset of mitochondrial DNA (mtDNA) sequences from olive (n = 943) and Kemp’s (n = 287) ridleys, and genotyped 15 nuclear microsatellite loci in a global sample of olive ridleys (n = 285). We found that the ridley species split ~ 7.5 million years ago, before the Panama Isthmus closure. The most ancient mitochondrial olive ridley lineage, located in the Indian Ocean, was dated to ~ 2.2 Mya. Both mitochondrial and nuclear markers revealed significant structure for olive ridleys between Atlantic (ATL), East Pacific (EP), and Indo-West Pacific (IWP) areas. However, the divergence of mtDNA clades was very recent (< 1 Mya) with low within- clade diversity, supporting a recurrent extinction-recolonization model for these ocean regions. All data showed that ATL and IWP groups were more closely related than those in the EP, with mtDNA data supporting recent recolonization of the ATL from the IWP. Individual olive ridley dispersal between the ATL, EP, and IN/IWP could be interpreted as more male- than female-biased, and genetic diversity was lowest in the Atlantic Ocean. All populations showed signs of recent expansion, and estimated time frames were concordant with their recent colonization history. Investigating species abundance and distribution changes over time is central to evolutionary biology, and this study provides a historical biogeographic context for marine vertebrate conservation and management.Globally distributed marine taxa are well suited for investigations of biogeographic impacts on genetic diversity, connectivity, and population demography. The sea turtle genus The online version contains supplementary material available at 10.1007/s10592-022-01465-3. Understanding the impacts of past biogeographic processes on recent demographic and genetic patterns is fundamental to the fields of evolutionary and conservation biology. For instance, historical climate cycles throughout glacial and interglacial periods significantly influenced temporal and spatial distributions of extant taxa (Dynesius and Jansson Lepidochelys spp.). The olive ridley (L. olivacea) is listed as ‘Vulnerable’ and is the most abundant sea turtle, occupying all tropical and temperate oceans except the North Atlantic (Abreu-Grobois and Plotkin L. kempii) is the rarest marine turtle, with a nesting distribution primarily restricted to the Gulf of Mexico. Most Kemp’s ridley nests occur in the vicinity of Rancho Nuevo, Mexico, and Padre Island National Sea Shore, USA, where olive ridleys do not generally nest  are currently under threat of extinction. Six species are classified globally from ‘Vulnerable’ to ‘Critically Endangered,‘ and the seventh is considered ‘Data Deficient’ IUCN . Extant The two ridley species’ taxonomic distinctiveness and evolutionary history were obscured by their morphological similarity  26,000–19,000 years before present (YBP) and the Holocene onset ~ 11,700 YBP, sea-level rise would have flooded many sea turtle rookeries but allowed colonization of new nesting areas. Indeed, synchronous population expansion after the LGM was revealed in most global sea turtle mtDNA lineages, including ridleys  of mtDNA control region and genotypes for 15 nuclear microsatellites Fig. . AustralSamples from nesting beaches were collected from either tissue  or blood . Different sampling and extraction methods were used per the samples’ origin as described in the original papers , an ~ 800 bp mtDNA control region segment was amplified using primers LCM15382 and H950 . Some of the earliest published data were limited to short segments (~ 470 bp). Here we only included longer sequences (> 700 bp) to potentially increase power to resolve population structure. In total, 283 Kemp’s ridley  diversities, polymorphic sites (PS), Fu’s Fs  were used as the outgroup. Details on calibration points and BEAST parameters are displayed in Supplementary Text 1.Genetic relationships and species divergence times were estimated using the Bayesian approach in BEAST2 v2.6.3 . For details on genotyping, see Supplementary Text 2, and for a description of primers used, see Table S3. The microsatellite data were screened for null alleles and genotyping errors  using Micro-Checker , and expected heterozygosity (He) under Hardy-Weinberg equilibrium, with sequential Bonferroni corrections (p = 0.05). The Polymorphic Information Content (PIC) was estimated using Cervus v3.0 , observed (K clusters [Pr (X|K)]. Because of differences in sample sizes between populations, the recommended priors in Wang  were also run to identify possible migrants or individuals with an ancestor from a different cluster. In STRUCTURE, individuals with admixture proportions (Q) from 0.2 to 0.8 were considered potentially admixed, and migrants were individuals who had Q > 0.8 of a genetic component associated with populations different from their origin  to choose the best K from 1 to 20. The number of principal components that explained 90% of the cumulative variance was retained. DAPC was also run with sampling areas as prior information.To assess the pattern of microsatellite genetic variability among individuals, Discriminant Analysis of Principal Components (DAPC), which is based on Discriminant Analysis clustering of individuals after a Principal Components Analysis (PCA), was employed. The Neµ, where Ne is the effective population size and µ is the neutral mutation rate per site per generation) for each ocean region, and the asymmetrical immigration rate (M = m/µ) between each one. The best colonization model was estimated using their marginal likelihoods. Details of the method are in Supplementary Text 1.Bayesian inference was employed to estimate demographic parameters and test 21 colonization models between the three ocean regions  using Migrate-n v.4.4.0 (Beerli and Felsenstein Ne) and past (Na) effective sizes and the time of size change  were estimated using logit transformation for the 10,000 best simulations.Finally, an Approximate Bayesian Computation approach (ABC) implemented in DIYABC 2.1.0  and included 558 new unpublished sequences for both species (nL. kempii = 4). Nine Kemp’s ridley haplotypes with nine substitutions were detected (Tables S1 and S2). There were 53 olive ridley haplotypes containing 49 polymorphic sites, and 732 samples came from L. olivacea rookeries. The number of olive ridley haplotypes and haplotype diversity varied between the three ocean regions (Table S1). The lowest number of haplotypes was found in the Atlantic , followed by the Eastern Pacific  and the Indian-West Pacific .The 653 bp-long mtDNA alignment was obtained for a total of 1,230 ridley sequences  (Table S5). Within the Indian-Western Pacific there were significant ΦST values, suggesting strong intra-regional population structure. Conversely, there was no difference between Oman and Sri Lanka , the two rookeries that bore haplotypes from the endemic and basal Indian Ocean clade.Pairwise ΦST comparisons, the Median-Joining Network, and haplotypic geographic distribution patterns . Between regions, pairwise ΦST values were also high .AMOVA analysis was run using groupings formed based on rookery pairwise Φns Figs.  and 2. OThe Bayesian phylogenetic tree Fig.  was concIn total 285 individuals from 12 globally distributed olive ridley sites, of which 11 were rookeries and one was a feeding ground, were genotyped (Table S1). Almost all loci were polymorphic in the sampled populations. On average, 95% of the individuals were genotyped entirely, but a dataset of 227 individuals (including 11 from the EP feeding ground) that presented at most one missing marker was used for DAPC and STRUCTURE analyses. Similar to the mtDNA results, Atlantic olive ridley populations had lower diversity values than those of the East-Pacific and Indian-West Pacific (Table S1).K = 3 or K = 2 with the highest likelihood depending on the method . Nonetheless, there was clear geographic differentiation between ocean regions . Unlike the mtDNA pattern, a distinctive Indian Ocean group was not found using nuclear microsatellites. Running similar STRUCTURE analyses for each major ocean region separately revealed no finer-scale population differentiation, indicating prevalent dispersal within ocean regions . Migration analysis with STRUCTURE using ocean regions as location priors (K = 3) revealed that 11 of the 216 individuals sampled from the rookeries were likely migrants, and an additional seven appeared to be admixed between ocean regions . The three clusters in the K = 3 analysis without prior grouping mostly matched the main ocean areas .The DAPC results were similar to those of STRUCTURE. Most areas presented distinct genetic components in comparison to each other, but were relatively homogeneous within, except for the EP in which only Costa Rica was differentiated Fig.  C. Analyeas Fig. E, but poFST and G’’ST estimates between rookeries showed that the genetic composition of some populations within the same ocean region was not significantly different (Tables S6 and S7). Guinea-Bissau had the highest divergence values among Atlantic Ocean rookeries, indicating structure between the eastern and western Atlantic. Differentiation values were low within the East Pacific, although statistically significant between Mexico and Costa Rica. Indian-West Pacific populations also had low FST. However, FST values between populations outside these three oceanic regions were significantly different and usually higher than within regions.Similarly, pairwise Ne estimates for the three ocean regions were significantly different, with median values estimated at 1,302 for the Atlantic, 2,208 for the East Pacific, and 1,769 for the Indian-West-Pacific  were detected immigrating to IN/IWP from ATL median 100 ipg) than to IN/IWP from EP (median 15 ipg). This rate was higher than to ATL from both EP and IN/IWP (median ~ 4 ipg) (Tables S1 and S8). Moreover, the historical 00 ipg thNa) was similar for all three areas, while recent estimates showed EP to have the largest Ne, followed by ATL and IN/IWP . The ancestral population size , endemic to the Indian Ocean and dated herein to ~ 2.2 Mya, is the most divergent lineage of olive ridley haplotypes  than the split of IN lineage, as expected given the climatic instability of other oceanic areas. Previous work hypothesized recent East Pacific and Atlantic (re)colonization from the Indian Ocean  recolonization of the Atlantic from the Indian-West Pacific is upheld by the sister relationship between ATL and IWP clades Fig.  in additIn comparison to other sea turtles, olive ridley populations have shallow evolutionary histories  movement between these areas Fig.  does notWithin ocean regions, olive ridley mtDNA differentiation among regional rookeries ranged from moderate to non-significant, and populations were less structured than in other sea turtle species. This pattern could indicate relatively recent colonization, as suggested above, or generally low levels of natal philopatry. In favor of the latter hypothesis, in Costa Rica some solitary nesting females breed at multiple beaches hundreds of kilometers apart during the same nesting season  of most The DAPC results with sample sites as priors indicated that all nesting areas, except Mexico and Baja California, presented characteristic genetic profiles despite some inter-rookery migration within oceanic regions   . In comparison to flatbacks  and their limited nesting range in the Gulf of Mexico, particular conservation efforts should be implemented to ensure no further population declines that could affect their long-term survival.L. olivacea lineages : two in the Atlantic Ocean (east and west), three in the Indian , and three in the Pacific   and many haplotypes diverge by a single base pair from this frequent sequence  (Table S1), in agreement with our finding of very recent regional population expansion . For instance, our parameters for the Atlantic Ocean are broadly concordant with recent Ne estimates of ~ 1,000 for Brazilian olive ridleys based on whole genomes  Table S, in agreNe. As ridleys are known for their oceanic habit, distant migrations, and long generation times, conservation and management should be carried out by international agreements and cooperation considering all life stages and migratory routes used by the species in the different oceans.There is no doubt that human exploitation of olive and Kemp’s ridleys and other current threats have severely reduced some populations (Cornelius et al. Below is the link to the electronic supplementary material.Supplementary Material 1Supplementary Material 2Supplementary Material 3


Bipolaris sorokiniana is a fungal pathogen that infects wheat, barley, and other crops, causing spot blotch disease. The disease is most common in humid, warm, wheat-growing regions, with South Asia’s Eastern Gangetic Plains serving as a hotspot. There is very little information known about its genetic variability, demography, and divergence period. The current work is the first to study the phylogeographic patterns of B. sorokiniana isolates obtained from various wheat and barley-growing regions throughout the world, with the goal of elucidating the demographic history and estimating divergence times. In this study, 162 ITS sequences, 18 GAPDH sequences, and 74 TEF-1α sequences from B. sorokiniana obtained from the GenBank, including 21 ITS sequences produced in this study, were used to analyse the phylogeographic pattern of distribution and evolution of B. sorokiniana infecting wheat and barley. The degrees of differentiation among B. sorokiniana sequences from eighteen countries imply the presence of a broad and geographically undifferentiated global population. The study provided forty haplotypes. The H_1 haplotype was identified to be the ancestral haplotype, followed by H_29 and H_27, with H_1 occupying a central position in the median-joining network and being shared by several populations from different continents. The phylogeographic patterns of species based on multi-gene analysis, as well as the predominance of a single haplotype, suggested that human-mediated dispersal may have played a significant role in shaping this pathogen’s population. According to divergence time analysis, haplogroups began at the Plio/Pleistocene boundary. Bipolaris sorokiniana (Sacc.) Shoemaker, belonging to the order Pleosporales (Pleosporaceae family), is one of the major production constraints in warmer areas worldwide [Cochliobolus sativus) Drechs. Ex Dastur is the sexual (perfect) stage for this fungus. Except for Zambia, C. sativus has not been discovered in nature; however, sexual reproduction in this pathogen has been documented very rarely [B. sorokiniana, on the other hand, reproduces primarily by the generation of asexual conidia [Spot blotch of wheat and barley caused by the fungus orldwide ,2. The iy rarely ,4. B. soB. Sorokiniana results in huge genetic variability of the pathogen [Yield losses are reported to vary from 15.5 to 19.6% and may be up to 100% under congenial conditions in vulnerable genotypes, reducing the seed quality ,5. Spot pathogen ,8,9. AltB. sorokiniana, understanding its genetic diversity throughmolecular characterization is critical. The analysis of the ITS  region has been widely used in studying fungal phylogenetic relationships [B. sorokiniana, which causes spot blotch disease in wheat, have been reviewed elsewhere [The high genetic variability among fungal pathogen populations across a wide range of environments, as well as the involvement of minor genes in governing resistance in foliar blight or spot blotch breeding programs, continues to be a challenge for breeders. Considering the yield losses caused by the fungus ionships . Its sholsewhere .B. sorokiniana is a variable fungus due to somatic hybridization, sexual reproduction, and heterokaryosis [B. sorokiniana showed a significant degree of diversity from various geographic regions [Pyrenophorateres f. sp. maculata have also been utilized for evaluating variations among B. Sorokiniana isolates [B. sorokianana using ITS, β-tubulin, and TEF-1α gene markers [Bipolaris species delimitation using ITS and glyceraldehyde-3-phosphate dehydrogenase gene (GPDH). Brn1 gene sequences from B. sorokiniana were also utilised for designing the primer pairs. Information regarding species diversity at geographical level is a prerequisite for developing disease-resistant cultivars and disease management. The aim of this study was to understand the phylogeographic patterns of B. sorokiniana isolates infecting wheat and barley worldwide using ITS, GPDH, and TEF-1α sequences to elucidate the demographic history and divergence time estimation. The diversity analysis will not only aid in the designing and improving of wheat-breeding programmes to develop new cultivars, but also aid in the development of effective chemical management strategies for the control of leaf blight disease.In the past, several molecular techniques such as cleaved amplified polymorphic sequence (CAPS) and random amplified polymorphic DNA  have beekaryosis ,15. The karyosis ,16. The  regions . A phylo regions . Zhong e regions  developeisolates . EST-SSRisolates ,22,23,24isolates  also rep markers . Bhunjun markers  also repTM, Waltham, MA, USA) (100 rpm). After a week, fungal mycelia were harvested using double-layered filter paper and dried in between sterilized filter layers under a laminar flow cabinet. The dried mycelia were kept at −20 °C for molecular research.Fungal-infected leaves of wheat and barley were collected from different locations in India . Small mB. sorokiniana was processed using the CTAB method as described with minor modification [B. sorokiniana isolates, fungal specific universal primers (ITS1 and ITS4) were used [For extraction of fungal genomic DNA, 40 mg of dried mycelium of each isolate of fication . A UV/VIere used . PCR ampere used . The ampGAPDH and 74 TEF-1α sequences of B. sorokiniana retrieved from NCBI, including 21 ITS sequences obtained in this study, were used to perform multiple sequence alignment (MSA) using ClustalW of MEGA-X [In the present study, 162 ITS sequences, 18 of f MEGA-X  as well TEF-1α, and GAPDH was used for combined analysis  was calculated using the same program and the premise of panmictic populations. In general, multimodal distributions are compatible with demographic stability or numerous expansion events, whereas unimodal distributions commonly indicate that the population has recently expanded in both population and geographic terms [The Ric terms . The misBiloparis sorokinana populations, including Bipolaris oryzae as an out-group, using the GTR nucleotide substitution model, which was found to be the best model for the data in MEGA7 [BEAST 1.8.3  was usedin MEGA7 . We utilin MEGA7 .B. sorokiniana were sequenced bidirectionally. The sequences thus obtained had been deposited in GenBank  were identified in 254 sequences of okiniana . Howeverokiniana , and theGAPDH, and TEF-1α genes to determine the population structure and evolutionary ancestry of B. sorokiniana  when considered as a single group comprising all the populations. This analysis revealed 5.8% interspecies variation and 94.15%intraspecies variation  represented a low value of ariation . This stariation .By examining the frequency distribution of pairwise differences across sequences, Roger  proposedD and Fu’s Fs tests. The findings of Tajima’s D test and Fu’s Fs test are shown in D values were significant, including China, Turkey, Azerbaijan, Argentina, and Kazakhstan. However, except for Syria, Fu’s Fs were positive, and p-values for numerous groups were statistically significant, showing that there was an excess of low-frequency polymorphisms relative to expectation, indicating that the null hypothesis of population neutrality could be rejected  split 2.1 million years ago (Mya). Divergence within B. sorokiniana began 1.2 Mya, in the middle of the Pleistocene period. The divergence of B. sorokiniana in Asian countries occurred 0.47 Mya. It was discovered that divergence between Indian isolates and American isolates began around 0.35 Mya. Our research focused on determining the time of divergence of Asian isolates (particularly Indian samples), and we discovered that Indian lineages diverged around 0.38 Mya. We also discovered that the Japan, Russia, Jordan, and China lineages broke off at 0.16 Mya (The demographic history of earlier population increases was deciphered using Tajima’s rejected . The low0.16 Mya . The divB. sorokiniana (using ITS as well as with genes GAPDH and TEF1α region of B. sorokiniana) to acknowledge the evolution and phylogeography of the species.Spot blotch has emerged as one of the most important pathogens, particularly with regard to wheat and barley production throughout the world, including Southeast Asia ,21. HostB. Sorokiniana was a single species with no distinct groups, since all of the sequences taken from different countries were clustered together in a single group and outgroups were put into separate groups. Haplotype diversity is influenced by mutation, marker discovery, recombination, and demography [B. Sorokiniana isolates revealed that few haplotypes were population-specific and unique, while others were evolutionarily distinctive (H_1) and exhibited significant levels of gene flow among populations. The Asian haplotypes H_2, H_4, H_6, H_7, H_12, H_15, H_16, H_17, H_18, H_19, H_20, H_21, H_22, H_23, H_25, H_26, and H_39 appeared to have evolved from the predominant haplotype H_1 (Fs and Tajima’s D) owing to spot blotch fungal population expansion. B. sorokiniana host plant introduction, domestication, and continuing cultivation may therefore be a plausible explanation for population growth in different wheat-producing zones. This type of fungal population movement has been observed across several fungal infections [According to phylogenetic study, mography . Based omography . The restype H_1 . The haptype H_1 . We founfections ,44,45.D was negative for most of the groups but statistically positive, and Fu’s Fs were negative for only Syria but statistically significant, indicating that the B. sorokiniana populations did not match a simple model of neutrality and rejected the null hypothesis of constant population size. These findings postulated that the divergence from neutrality for constant population size (Tajima’s D and Fu’s Fs) was caused by the recent population diversification. The introduction of B. sorokiniana might be the cause of the species’ recent population expansion, as Bipolaris now exhibits pathogenic specialization on a variety of wild and cultivated host plants. This type of range expansion has also been reported in many fungal and insect species [B. Sorokiniana originated from the Middle Miocene era (~19 Mya). The Miocene era had the longest and most humid environments in geological history. According to paleogeographic analysis, the western part of Central Asia transitioned from a humid climate to a semi-arid climate [B. sorokiniana (the oldest ones). This study also showed that the divergence of B. sorokiniana in Asian countries occurred 0.47 million years ago. It was discovered that divergence between Indian isolates and American isolates began 0.35 Mya, whereas it was 0.05 Mya between African isolates. In conclusion, the presence of one haplotype at a very high frequency and low genetic differentiation in B. sorokiniana suggests that the durability of resistance in host plants against pathogens could be improved by the exchange of elite resistance lines from different countries. Based on the current distribution of species, divergence time analysis suggests that haplogroups began at the Plio/Pleistocene boundary.The indices were non-significantly positive in the Indian group, showing divergent demographic histories among the analysed regions. Tajimas’ species ,47. The  climate ,49. This


Petroica traversi) is arguably the most inbred bird species in the world. It avoided imminent extinction in the early 1980s and after a remarkable recovery from a single pair, a second population was established and the two extant populations have evolved in complete isolation since then. Here, we analysed 52 modern and historical genomes to examine the genomic consequences of this extreme bottleneck and the subsequent translocation.Understanding the micro-evolutionary response of populations to demographic declines is a major goal in evolutionary and conservation biology. In small populations, genetic drift can lead to an accumulation of deleterious mutations, which will increase the risk of extinction. However, demographic recovery can still occur after extreme declines, suggesting that natural selection may purge deleterious mutations, even in extremely small populations. The Chatham Island black robin (We found evidence for two-fold decline in heterozygosity and three- to four-fold increase in inbreeding in modern genomes. Moreover, there was partial support for temporal reduction in total load for detrimental variation. In contrast, compared to historical genomes, modern genomes showed a significantly higher realised load, reflecting the temporal increase in inbreeding. Furthermore, the translocation induced only small changes in the frequency of deleterious alleles, with the majority of detrimental variation being shared between the two populations.Our results highlight the dynamics of mutational load in a species that recovered from the brink of extinction, and show rather limited temporal changes in mutational load. We hypothesise that ancestral purging may have been facilitated by population fragmentation and isolation on several islands for thousands of generations and may have already reduced much of the highly deleterious load well before human arrival and introduction of pests to the archipelago. The majority of fixed deleterious variation was shared between the modern populations, but translocation of individuals with low mutational load could possibly mitigate further fixation of high-frequency deleterious variation.The online version contains supplementary material available at 10.1186/s12864-022-08963-1. In the current biodiversity crisis, an increasing number of species survive in ever smaller and fragmented populations –3. TheseNipponia nippon ),Oligosoma nigriplantare nigriplantare;  and CpG sites using the GenErode bioinformatics pipeline [To identify Z- and W-linked scaffolds in the black robin assembly, we used the snakemake workflow findZX  and profindZX/; . We usedpipeline .https://github.com/jstjohn/SeqPrep) to trim and merge forward and reverse reads for historical samples. Next, reads for modern and historical data were mapped using BWA v0.7.17 mem and aln algorithms respectively, while sorting and removing PCR duplicates were done using SAMtools v1.12 [Mapping and variant calling for historical and modern data was done using a beta version of the GenErode bioinformatics pipeline . Brieflyls v1.12 . Finallyls v1.12 . We thenVariant calling was done with bcftools mpileup command and bcftools v1.8 , 86. We complete’ dataset that was used as input for population structure analyses. For all other analyses involving population comparisons including demographic analysis , we used PLINK v1.9 [n = 13; Maung’ Rē, n = 9; and Hokorereoro, n = 20), hereafter referred to as the ‘three populations’ dataset, with a genome coverage We obtained a total of 2,731,301 high-quality SNPs across our 52 genomes, hereafter referred to as the 'INK v1.9  to retaiDrymodes brunneopygia; GCA_013400955.1) as described in [For analyses that required the calling of variants relative to an ancestral allele , we replaced the reference allele in the vcf file with that of Southern scrub robin . This model identifies historical recombination events across a single diploid genome to infer the time to the most recent common ancestor (TMRCA) between genome segments. Assuming that pairwise sequence divergence is proportional to the timing of the coalescent events, parts of the genome with low heterozygosity indicate recent coalescence while regions of high heterozygosity correspond to more ancient coalescent events. Similarly, because the rate of coalescence is inversely proportional to Ne [e.To infer past demography of black robin we used the Pairwise Sequentially Markovian Coalescent (PSMC) v0.6.5  to estimal to Ne , it can -9 substitutions/site/generation based on a direct estimate for flycatcher  [We generated consensus sequences for all autosomes of one high-coverage genome per population  using the SAMtools mpileup  command icollis) .e. First, we used the SMC + + v.1.15.2 [e from the observed spectrum of linkage disequilibrium . We only retained the 85 largest autosomes and used the following parameters: PHASE = 2; cMMb = 1; DIST = 1; NGEN = 2000; NBIN = 400; MAF = 0.0; ZERO = 1; maxNCHROM = 85; maxNSP = 50,000; hc = 0.05; REPS = 40; threads = -99. For this analysis, we grouped Maung’ Rē and Hokorereoro into a single modern population (n = 29).Because the PSMC relies on a single diploid genome, there are only a few coalescent events in the recent past, thereby limiting the power in detecting recent past population fluctuations  using the sliding-window approach implemented in PLINK v1.9. Because ROH identification is sensitive to input parameters, we ran the analysis with three different sets of parameters: a sliding window size of 100, 250 or 500 SNPs (homozyg-window-snp 100/250/500); no more than 1, 3 or 5 heterozygous site per window to assume a window as homozygous (homozyg-window-het 1/3/5); at least 5% of all windows including a given SNP to define the SNP as being in a homozygous segment (homozyg-window-threshold 0.05); a homozygous segment was defined as a ROH if the segment included ≥ 25 SNPs (homozyg-snp 25) and covered ≥ 100 kb (homozyg-kb 100); the minimum SNP density was one SNP per 50 kb (homozyg-density 50); and the maximum distance between two neighbouring SNPs was ≤ 1,000 kb . Finally, we set the value at 750 heterozygous sites within ROH (homozyg-het 750) in order to prevent sequencing errors to cut ROH. The inbreeding coefficient FROH was then estimated as the overall proportion of the genome (autosomes only) contained within ROH. The main results are based on: homozyg-window-het 5, homozyg-window-snp 500 (seeWe identified Runs of Homozygosity (ROH) regions across the genomes and calculated individual inbreeding coefficients  with the GERP + + software [Since genetic load cannot be estimated in the absence of fitness data, we estimated relative mutational load as a proxy for genetic load in each individual genome from the ‘software , as descsoftware  and Dusssoftware . Brieflyhttps://github.com/lh3/htsbox). GERP + + was then used to calculate conservation scores (GERP scores) for each site in the genome for which at least three bird species could be accurately aligned to the black robin reference. We considered mutations at sites with a GERP score within the top 1%  of the GERP score distribution as highly deleterious, and mutations at sites with low GERP scores (< 1) as neutral.To identify highly conserved regions in the black robin, we aligned and reconstructed the phylogeny of 124 avian genomes including black robin Table S from Genthree populations’ dataset using a Tukey HSD test in R [Next, the distribution of GERP scores was divided into categories , and for each category and individual, the following formula was used to calculate relative mutational load:  / . Higher relative mutational load values indicate that a relatively larger proportion of derived alleles is found at conserved genomic sites, thus indicating higher mutational load. We statistically compared the relative mutational load based on GERP-scores for the ‘est in R .Taeniopygia guttata; GenBank: GCA_000151805.2) following Uniprot90 guidelines using a custom script. We only retained sequences with at least 90% sequence identity to, and 80% overlap with, the longest sequence. Next, we used the exon-aware, protein-to-genome aligner SPALN2 [Aves’ as taxonomic scope, the ‘Restrict to one-to-one’ and the ‘Use experimental terms only’ options to prioritise precision, quality of matches and also to remove multiple matches which could represent pseudogenes. Overall, we obtained 9,891 annotated gene models.We used SnpEff v4.3  to annotr SPALN2  and the r SPALN2 , we obtar SPALN2 . We seleP. traversi using the protein sequences extracted from our annotation. We first identified putative deleterious variants by allocating them to three different impact categories as defined in the SnpEff manual: a) Low: mostly harmless or unlikely to change protein behaviour ; b) Moderate: non-disruptive variants that might change protein effectiveness ; c) High: variants assumed to have high (disruptive) impact on protein, probably causing protein truncation, loss of function or triggering nonsense mediated decay and including stop gained codons, splice donor variant and splice acceptor, start codon lost [. [i divided by twice the total number of segregating sites for category i) as described in Mathur & DeWoody [three populations’ using Tukey HSD in R [.We then generated a database for don lost . Because lost [. . Secondl DeWoody . By takiHSD in R .xy ratio as described in Dussex et al. [xi = dxi /nxi, where nxi corresponds to the total number of alleles scored in population x and dxi to the total number of derived alleles. Similarly, we define fyi for population y. For each C category of variants we then calculated:We then estimated the difference in frequency of Moderate and High impact variants for each population pair comparison by calculating the Rx et al. . We calcxy = Freqpop-x / Freqpop-y ratio. Rxy equal to 1 corresponds to no change in frequency between two populations, whereas Rxy < 1 or > 1 corresponds to a decrease or an increase in frequency in population x relative to population y, respectively. The variance in the Rxy ratio was estimated with a jack-knife procedure across chromosomes in R. We only included sites where at least one out of all alleles is derived in both populations in the estimation of Rxy.We then calculated the Rtwo populations’  dataset. Since our datasets were filtered for missing data, performing this analysis for the ‘two populations’ dataset only, allowed us to maximise the number of variants discovered and thus provide a more comprehensive understanding of gene and biological functions affected by mutational load. After excluding Z- and W-linked scaffolds (Table SFinally, we ran the SnpEff analysis to identify High impact variants in coding regions for a reduced ‘Gallus gallus as reference set. We performed this analysis only on the 29 genomes from the ‘two populations’ dataset.We performed a functional classification and overrepresentation test for genes containing High variants identified with the SnpEff using a Gene Ontology analysis implemented in Panther v17  using GaAdditional file 1. Additional file 2.


Chimonobambusa utilis (Keng) Keng F is an endemic species distributed only in the Daluoshan Mountains, southwest China. Ch. utilis is popular due to its unique flavor and deliciousness and plays an important role in the industrial revolution in many counties in China. A total of 20 natural populations were sampled from the entire distribution range of Ch. utilis. In the present study, we used five EST-SSR molecular markers, three chloroplast DNA , and one ITS molecular marker to elucidate the genetic diversity and phylogeography analyses of these Ch. utilis populations. The results exhibited that Ch. utilis populations showed lower genetic diversity than other angiosperms . A total of 40 alleles were detected for five polymorphic loci. We detected 20 polymorphic sites and 11 haplotypes within 1,398 bp of cpDNA and 59 polymorphic sites and 32 haplotypes within the 589 bp of the ITS sequence. Based on the haplotype distribution, we infer that there were at least two glacial refuges of Ch. utilis populations during the Quaternary Ice Age. The genetic and geographic distance were correlated (p < 0.05), indicating that narrow distribution might be the primary cause of the low genetic differentiation of Ch. utilis populations. Based on the genetic diversity of Ch. utilis populations, we recommend implementing effective genetic resource management and sustainable utilization. Chimonobambusa utilis, a member of the Poaceae family Chimonobambusa, is an endemic species of southwest China and is widely distributed in the Daloushan Mountain area within an altitude range of 1,000 to 2,300 m. It has strong soil adaptability with pH 4.0–8.0, such as black forest soil, nursery loam, and even karst environment  and one ITS sequence to make the results more comprehensive and reliable. We expect to find the causes of the genetic variation by studying the genetic diversity and phylogenetic geography of Ch. utilis, and based on the level of genetic diversity and genetic differentiation of Ch. utilis. Finally, based on the discussion of various conclusions, put forward the management strategy of scientific and feasible protection measures, and provide a certain scientific theoretical basis for the protection, development, and utilization of the Ch. utilis germplasm resources.Here, after a comprehensive investigation and extensive sampling of the natural population of Ch. utilis from 20 populations, which presents its entire geographical distribution. Twenty to twenty-five individuals were collected from each population, and each individual was 45 m apart . DNA quality was tested using 1.5% agarose gel electrophoresis. The amount of DNA was estimated by spectrophotometry . Then, dilution was performed by standardizing all samples to 20 ng DNA/μl and storing it at −80°C.trnH-psbA, atpF-atpH, and psbK-psbI) were amplified , 0.5 μl of each primer, 1 μl of template DNA, and 8 μl of double-distilled water. The reactions were conducted with the following conditions: initial 2-min denaturation at 95°C followed by 30 cycles of 1-min denaturation at 95°C, 55°C for 10 s with a ramp of 0.3°C/s to 65°C, and 65°C for 1 min, with a final extension at 65°C for 10 min. Agarose gel electrophoresis detection of all PCR products showed clear bands without the occurrence of the indistinct band; obvious primer dimmer and tailing phenomena were directly purified and sequenced. The purified PCR products were sequenced in an ABI 3730 (Thermo Fisher Scientific). The results of chloroplast DNA sequences and nuclear fragments were checked using Chromas 2.6, then manually aligned employing CLUSTAL W in MEGA 6 and adjusted . All sequence results were deposited in the GenBank database under accession numbers (ON211020–ON211030 for cpDNA and ON206010–ON206041 for ITS).2O. The reaction parameters of PCR amplifications were as follows: pre-denaturation at 94°C for 3 min, denaturation at 94°C for 30 s, annealing at 55–60.2°C for 30 s, extension at 72°C for 1 min, a total of 30 cycles, and extension at 72°C for 5 min. The selected primer pairs were labeled with a fluorescent dye (FAM) at the 5′ end, and PCR products were analyzed using an ABI3730.Twenty pairs of EST-SSR primers were selected, from which five pairs of EST-SSR primers were successfully amplified with high polymorphism and homology (Hd), nucleotide diversity (Pi), and the number of polymorphic sites (π). Population differentiation indices (Gst and Nst) were calculated using the program PERMUT with 1,000 permutations (http://www.fluxus-engineering.com/sharenet.htm). The geographical distribution of populations and haplotypes was mapped in ArcGIS v.10.2.Sequences from three cpDNA fragments and ITS sequences were concatenated into a sequence by the software PhyloSuite v1.1.15 . The Dnautations . The genHS), total genetic diversity (HT), and the genetic variation, differentiation, and pairwise fixation indices (STF) within and among populations were statistically tested through analyses of molecular variance (AMOVAs) in ARELQUIN v3.1.16 (https://www.fousoft.com/arlequin.html). To better understand the population growth and expansion of cpDNA and nrDNA fragments of Ch. utilis, both neutrality tests and mismatch analysis were implemented in DnaSP v.5.Average genetic diversity within populations (He), observed heterozygosity (Ho), effective numbers of alleles (Ne), the mean number of alleles (Na), percentage of polymorphic loci (PPB), and Wright’s F statistics parameters  were analyzed using GenAIEx6.5  (http://taylor0.biology.ucla.edu/structureHarvester/) of genetic clusters based on both log-likelihood L (K) and Delta K (ΔK)   methods.a K (ΔK) .Ch. utilis. The software was then used to detect correlations between genetic distance and geographical distance, genetic distance, and population altitude. Bottleneck 1.2.02 (PopGene32 software  was usedk 1.2.02  was usedPi) of all populations was 0.00038, with most populations having a null value, and the average was 0.00013. Total haplotype diversity (Hd) was 0.4641, and the average was 0.4343 .We identified the cpDNA consensus sequences from 410 individuals in 20 populations with a total of 1,398 bp in length containing 20 polymorphic sites  were identified based on nrDNA fragments. Among them, haplotype H3 contains 105 individuals with the highest frequency and the widest range of distribution, and we speculate that this is an ancient haplotype. At the species level, using ITS data, the Ch. utilis. It is apparent that a higher genetic variation was observed between populations  than within populations  at the cpDNA level. The STF value was 0.84135, which also indicates a significant level. The ITS sequence shows the same result, similar to those of cpDNA, the variation came from among populations, and the STF value was 0.84135  was done using Permut v.2.0 (TH) and the average within-population diversity (SH) were 0.956 and 0.507, respectively, based on combined cpDNA sequences. The population genetic differentiation coefficients  showed a significant pedigree geographical structure among populations of Ch. utilis. The ITS sequence shows that total genetic (TH) and the average within-population diversity (SH) were 0.868 and 0.495, respectively. The population genetic differentiation coefficients are similar to the cpDNA data . The gene flow based on the two molecular markers was 0.11 and 0.56, respectively.Genetic structure analysis of ut v.2.0 Table 5.For combined cpDNA, the H1 haplotype has the widest distribution and the highest frequency, followed by haplotype H3. According to the NETWORK analysis, these two widespread haplotypes are located at the central position of the network diagram and are likely the ancestral haplotypes. The remaining eight haplotypes with low frequency were located at external positions relative to the two main haplotypes; these may be young haplotypes derived from recent differentiation. The ITS sequence haplotype network diagram results supported the congruent cpDNA haplotypes, which showed that the haplotypes H3 and H1 were distributed in the central position and that the remaining haplotypes were distributed in the outside nodes of the network diagram Figure 3Ch. utilis, maximum likelihood analysis was performed for the 11 cpDNA haplotypes and 32 ITS haplotypes with Chimonobambusa hejiangensis as an outgroup, with 1,000 bootstrap replications  and Fu and Li’s F* , implying that the populations had experienced directional selection or population expansion. The ITS sequence displayed a significant negative Tajima’s D value  and non-significant negative Fu and Li’s F* value , whereas the mismatch distribution analysis was bimodal with ITS data  per locus ranged from 3.143 (EST-SSR5) to 4.741 (EST-SSR1), with a mean of 3.848. The effective allele number (Ne) per locus ranged from 2.544 (EST-SSR3) to 3.767 (EST-SSR1), with an average value of 3.111. Shannon’s Information Index (I) had an average of 0.170 and ranged from 0.991 (EST-SSR3) to 1.373 (EST-SSR1). The observed heterozygosity (Ho) and expected heterozygosity (He) varied from 0.993 (EST-SSR5) to 1.000 (EST-SSR1–4), and from 0.596 (EST-SSR3) to 0.886 (EST-SSR2), with an average of 0.999 and 0.653, respectively. The value of the polymorphism information content (PIC) ranged from 0.592 (EST-SSR3) to 0.886 (EST-SSR2) with a mean of 0.732, showing highly polymorphic loci for five primers. In summary, the highest level of genetic diversity was detected in the locus EST-SSR1, while the lowest level of genetic diversity was detected in the locus EST-SSR3 (To assess the diversity of Ch. utilis genetic diversity at the population levels. The Na and Ne per population ranged from 3.000 (CS) to 4.800 (XZ) and from 2.448 (HYS) to 3.714 (QB), with mean values of 3.843 and 3.111, respectively. The PIC value shows the genetic diversity of populations; its value ranged from 0.948 (HYS) to 1.346 (YL), with an average of 1.170. The Ho value was 1.000 in all populations apart from the QB population (Ho = 0.980), with an average of 0.999. The He reflected the richness and evenness of the population and varied from 0.584 (HYS) to 0.712 (YL), with an average of 0.653. The genetic diversity of the XZ, QB, YL, and GL populations investigated in the present study was high; however, the genetic diversity of the HYS and CS populations was low. At the population level, the polymorphic loci (PPL) percentage was 100% in all populations (Ch. utilis showed that a higher genetic variation was observed within populations (94.98%) than among populations (5.02%), which indicated that the genetic variation mainly occurred within populations. Moreover, the Fixation Index (STF) was 0.05021 at the population level  was at the value K = 3. Overall, there were different degrees of introgression among 140 individuals from different populations  under the IAM, TPM, and SMM models. Also, the significant probabilities of Wilcoxon (p > 0.05) showed that some populations, such as KKS, QB, JS, XZ, HYS, and CS, experienced a recent bottleneck event , the range of nucleotide polymorphism (π) ranged from 0.5 × 10−3 to 6.3 × 10−3 based on cpDNA fragment analysis  of the other 124 angiosperms (by 0.637). However, compared with the above cpDNA data, the results based on nrDNA analysis showed that the STG of Ch. utilis was higher than the average STG (STG = 0.430) of 77 angiosperms by 0.184  was higher than that of the Ch. utilis population . This may be because the effective population size of the organelle DNA of C. taliensis is smaller than that of nuclear DNA, resulting in strong genetic drift and a higher level of population differentiation. However, the degree of genetic differentiation among populations of Ch. utilis was higher than that of some conifers , we should implement conservation in situ strategies to maintain the existing population size, avoid the loss of haplotypes caused by environmental changes, and improve the adaptability of the population. At the same time, special haplotype populations are transplanted to places with similar environments, and conservation ex situ strategies are implemented. For example, the construction of seed resources or nature reserves, such as the established Dashahe Nature Reserve and Kuanshui Nature Reserve, improves the survival rate of cultivation and improves management.Based on the distribution characteristics of the Ch. utilis were collected, including 13 populations in Guizhou Province, two populations in Chongqing, two populations in Yunnan Province, and three populations in Sichuan Province. Five pairs of EST-SSR molecular markers were used to analyze the genetic diversity, genetic structure, and bottleneck effect of 14 populations. Three cpDNA fragments  with uniparental inheritance and one ITS sequence with biparental inheritance were used to study the genetic diversity, genetic structure, and dynamic population history of 410 individuals from 20 populations of Ch. utilis. We detected a very significant positive correlation between genetic distance and geographical distance among populations, indicating that the genetic variation among populations of Ch. utilis is mainly affected by geographical barriers. In addition, the neutral test results of the two markers were significantly negative, indicating that the population of Ch. utilis underwent a recent rapid expansion event. Based on the present population distribution, genetic diversity, and geographical pedigree structure of Ch. utilis, a scientific and feasible strategy for protection and utilization was put forward. This study aimed to provide a theoretical basis for an in-depth understanding of the population genetic structure, germplasm sampling, geological events, and climate change on the genetic differentiation and geographical distribution pattern formation mechanism of Ch. utilis.In this study, 20 populations of The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/YL performed the experiments, analyzed the data, and approved the final draft. MW contributed to the investigation. XX and ZX prepared figures and/or tables. ZD and GG conceived and designed the experiments. All authors agree to be accountable for the final manuscript. All authors contributed to the article and approved the submitted version.This work was supported by the Breeding of Improved Bamboo Varieties for Shoot (Te-Lin-Yan 2020-17).We thank the Investigation of Bamboo Resources and Excavation of Economic Bamboo Species in Guizhou Province.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


R. portoi predominates in dry forests of the Northeast associated with the Caatinga phytogeographic domain. This species is morphologically close to R. angustifolia, which is known for a single location in the Atlantic Forest in Southern Bahia, and is considered to be threatened by extinction. Besides problems with taxonomic focus, actions for its conservation are complicated because it is not certain if it must be considered an independent species or included in the more widespread R. portoi. In this study, we used coalescent multispecies (MSC) theory approaches combined with genetic structure analyses in an attempt to delimit these two species. Different analyses were congruent and the species delimitation using MSC inferred distinct lineages supporting their recognition as two species. These results solved the taxonomic doubts and also showed the power of these approaches to delimit species as lineages, even in groups with weak morphological divergence and low genetic variability, and also impacting our knowledge for conservation purposes.Species delimitation in herbaceous bamboos has been complex and, in some genera, a great part of its diversity has been confirmed only based on genetic information, as is the case of the genus Raddia. It includes nine species, all occurring in Brazil, but only  Species delimitation, alongside phylogeny reconstruction, are the main objectives of Systematics . The tasCoalescent models  allow for estimating the species of trees without the need for allele monophyly . Unlike Genetic clustering approaches are useful for species discovery without a priori information about groups and relationships among them. Two efficient and popular clustering methods are STRUCTURE  and GausAn interesting group to test the power of such methods is the herbaceous bamboos (the grass tribe Olyreae). This group inhabits mainly Neotropical forests and is often underestimated in most systematics studies, having a great unexplored potential for discovery of new species and identification of new lineages. Problems of species delimitation are still common in various groups of Olyreae, for example in Raddia Bertol ,14, PireR. guianensis (Brongn.) Hitchc., which also occurs in northern Brazil and neighboring countries in northern South America  ≥ 0.99). Additionally, all three tested species receive strong support as distinct lineages  and , P) was the tree with the best PP support  plot . The number of loci per population ranged from 72 in the populations PIB and PFS of ulations a; howeve(K) plot b indicatK = 2, the scheme of individuals from the two genetic clusters showed two well-defined clusters from all nine populations. Populations of Raddia angustifolia and R. brasiliensis consisted of one shared genetic cluster, and the populations of R. portoi comprise a different one. , with 80% of the total variation within populations , and those varied between 0.04 and 0.28  from all other populations. A second barrier (87% bootstrap) suggested the isolation of R. angustifolia from populations of the other two species  barrier isolating populations of  species .Raddia angustifolia and eight populations of R. portoi in Bahia, Sergipe, Rio Grande do Norte, and the Pernambuco states in Northeast Brazil, including the type localities of both R. portoi  and R. angustifolia  , except for population from Tobias Barreto, deposited at the herbarium of the Universidade Federal de Sergipe  . We alsoy Thiers ) (Table ® (Qiagen Corp.). The amplification protocol suggested by the manufacturer was adapted to a total volume of 15 μL, containing 0.2 μM of each primer and 10–20 ng template DNA.We used 20 µg of silica gel dehydrated leaves using the CTAB 2× protocol described by J.J Doyle and J. L. Doyle , scaled ITS region was amplified with the 17SE and 26SE primers [The ribosomal DNA  primers . PCR wastrnD-trnT was amplified using the universal trnD primer [trnT specific primer for Poaceae, due to an inversion that species of this family present at the annealing site of primers [The plastid spacer D primer  and a tr primers . PCR was® v. 3.1 kits with the same primers used in PCR for trnD-trnT. For ITS we used ITS4 [ITS92 [®  at LAMOL/UEFS.PCR products were purified by precipitation using PEG (polyethylene glycol)  and weresed ITS4  and ITS94 [ITS92  primers.Electropherograms were edited in Staden Package 2.0.0b11  saving tRaddia angustifolia; B, R. brasiliensis; P, R. portoi) based on the genetic structure results (see Results), resulting in the means 0.0001 for θs and 0.0015 for τABP.We used Bayesian Phylogenetics and Phylogeography (BPP) v4.3  to reconAfter that, we run an A11 analysis (species delimitation and species tree estimation). This analysis was implemented on version 3 of the program and, differently from an A10 analysis, eliminates the need for a user-specified guide tree ,43. As tFor the A11 analysis, inverse-gamma priors based on A00 run results were diffusely informed for θ ~ IG and τ ~ IG. As has been noted that those priors can impact the posterior probabilities, we tested the effects of different priors on the obtained results using nine schemes similar to what was done by Leaché and Fujita : sometimEach run consisted of a burn-in period of 8000 iterations and a sampling period of 100,000 iterations, logged every two, for a total of 50,000 samples. The fine-tune parameters were obtained by trial and error as recommended in the BPP manual and can be checked on the control files . Two ind® , 1× CoralLoad Concentrate, 4.8 pmol of primer, and 10 ng template DNA to a final volume of 7.2 μL. We tested the 20 primers described on the ISSR Resources website, archived at https://web.archive.org/web/20170605202905/http://www.biosci.ohio-state.edu/~awolfe/ISSR/protocols.ISSR.html (accessed on 25 July 2020).) and from the UBC primer kit #9  with one sample of each population, chosen randomly, for the verification of the amplification profile. The primers MANNY: (CAC)4 -RC, MAO: (CTC)4-RC, ISSR-4: (GA)8-YC; M9: (GACAC)3; DAT: (GA)7-RG; TERRY: (GTG)4-RC; 898: (CA)6-RY and 901: (GT)6-YR presented satisfactory resolution and polymorphism and were selected for genotyping. To certify the reproducibility of the obtained band patterns, we performed replications of the reactions for 25% of the total sample size, using samples chosen at random.Fragments were amplified by PCR (Polymerase Chain Reaction) using 1× TopTaq Master Mix The amplifications were based on Wolfe et al.  as follo® v. 5.1  in order to assess size homology and produce a binary matrix with zeroes representing absences, ones for the presences of bands, and −1 for missing data  to determine the size and concentration of the obtained fragments, followed by photo-documentation. These data were entered into the GelCompar II ing data .K = 1—11) using the admixture model with correlated allele frequencies. The analysis of each cluster consisted of 20 independent runs of 300,000 Markov chain Monte Carlo (MCMC) replicates following an initial burn-in of 100,000. To estimate the number of clusters, we used the ∆K [For the ISSR matrix, we used the model-based Bayesian approach implemented in STRUCTURE 2.3.4 ,45,46 tod the ∆K  and the d the ∆K , both cad the ∆K . We usedd the ∆K  to creatd the ∆K  with thed the ∆K  to draw We conducted an analysis of principal coordinates modal clustering (PCO-MC) ,54 withiCaatinga and Atlantic Forest). To verify if the result is not only a sampling artifact, we contrasted the empirical values with a null distribution generated by 999 randomizations of the original data, in which the individuals were swapped between populations by chance.We calculated the distribution of genetic variation through an Analysis of Molecular Variance (AMOVA)  in GenAlFinally, we tested for genetic barriers among populations using an autocorrelation analysis between genetic and geographic distances using Barrier v. 2.2 . For thiR. portoi and R. angustifolia, we used here different species delimitation approaches, even though both are from the same source of variation and DNA data, it sums up the previous information and gives greater reliability in the delimitation of these species. The approaches used here are generally used to find structure among populations of the same species, but they can also be used to find cryptic lineages within species complexes and taxonomic species in which it is speculated that they may contain more than one evolutionary lineage  graph, we see that it reaches a plateau at K = 5. We decided to present the two graphical representations. Despite having a different number of clusters, both structure graphs indicate a similar pattern, with the populations of Raddia portoi showing up separate from the others, and with sharing of gene pool (s) between the populations of R. angustifolia and R. brasiliensis. The five clusters found in the mclust analysis also indicate the separation between the populations of R. portoi from the others since three of the clusters  are almost exclusive to the populations of this species; one is exclusive to the population of R. angustifolia, and the rest are shared by the populations of R. brasiliensis and the population of R. angustifolia.In the STRUCTURE analysis, we chose to test two approaches to choose the best number of of K = 2 . Here, KST value found in AMOVA, the structure found here most likely reflects speciation processes rather than intraspecific population structure. The ΦST, an FST analogue, of 0.20 indicates that there is less than one migrant per generation between the populations (emN < 1), which is considered a rule of thumb to assume populations different enough to be treated as evolutionarily significant units (ESU) [ST results show that the greatest genetic divergences are between the Raddia brasiliensis populations and the others, with the majority of the ΦST values > 0.20. Among the populations of R. portoi this divergence was mostly ΦST < 0.10, except for the PFS population, which presents high divergences to the others of the same species. This implies an efficient gene flow between populations of the same species, with PFS being the most isolated population of R. portoi.Based on the high Φts (ESU) ,76 sensuts (ESU) , what meRT). The regions we tested correspond to the biomes in which the populations occur: Caatinga (for most of Raddia portoi populations) and Atlantic Forest (for R. angustifolia and R. brasiliensis populations). This result indicates that the populations of R. angustifolia and R. brasiliensis, represent distinct lineages apart from R. portoi, and also agrees with the fact that there is sympatry in some Raddia species [We also found a high and significant regional structure through the AMOVA analysis .The analysis of genetic barriers is also congruent with this result, showing that the barriers occur between putative species, and are not related to geographical distance or barriers to gene flow. For example, even though the two populations of ene flow ,82,83,84Brazilian forests harbor the highest diversity of herbaceous bamboos, ca. 92 out of 127 known species, distributed mainly along the Atlantic Forest and Amazon . HoweverBahia state contains the highest number of genera and species of Olyreae in Brazil, based on herbarium revisions and field collections . It alsoHerbaceous bamboos deserve special attention because they are important components of neotropical flora, and in recent decades have become extremely rare due to the intense increase in anthropic action in the Brazilian Atlantic Rainforest . This isR. portoi and R. angustifolia [R. angustifolia and R. portoi are different lineages. Genetic similarity between populations of R. portoi is higher than that between R. angustifolia and populations of R. portoi. Additionally, the population of R. angustifolia showed more genetic similarity with the populations of R. brasiliensis than with R. portoi itself in the STRUCTURE results and the BPP species trees. Although, this is a limited phylogeny since the 95% credibility set includes all three models. This low phylogenetic information has been observed in other studies with the A11 analysis [Previous phylogenetic studies including Raddia were inconclusive regarding the relationships and delimitation of stifolia . Nonetheanalysis . The higanalysis , which iRaddia angustifolia represents a different lineage from R. portoi, reaffirming its conservation status as a highly endangered species, for which conservation measures should be directed in order to preserve its genetic diversity. Populations of R. angustifolia are located in highly disturbed areas, so we should prioritize its conservation. It is considered endemic to southern Bahia, occurring on disturbed fragments of the Atlantic Forest [Raddia angustifolia was also recently listed in the Brazilian threatened flora compilation [According to our results, we can confirm that c Forest ,24, the c Forest . Raddia pilation .Raddia portoi, it has a wider distribution in dry forests of eastern Brazil, coinciding with the limits of the Brazilian semiarid region, and has not been listed as threatened. Although its populations are more numerous, we cannot ignore the fact that the populations are distributed in areas highly fragmented by human activities and the fact that the Caatinga is the less protected phytogeographic domain of Brazil [Regarding f Brazil .


Amygdalus mongolica is a relict and endangered shrub that occurs primarily in arid areas of northwestern China. Based on variation patterns present at three cpDNA regions  and in one nDNA sequence (ITS1-ITS4) in 174 individuals representing 15 populations, the spatial genetic structure and demographic history of A. mongolica was examined across its entire geographic range. The 17 different haplotypes and 10 ribotypes showed two lineages, distributed across the Western  and Eastern regions  according to the median-joining network and the BI (Bayesian inference) and ML (Maximum likelihood) trees. AMOVA analysis demonstrated that over 65% of the observed genetic variation was related to this lineage split. The expansions of the Ulanbuhe and Tengger deserts and the eastward extension of the Yinshan Mountains since the Quaternary period likely interrupted gene flow and triggered the observed divergence in the two allopatric regions; arid landscape fragmentation accompanied by local environmental heterogeneity further increased local adaptive differentiation between the Western and Eastern groups. Based on the evidence from phylogeographical patterns and the distribution of genetic variation, A. mongolica distributed in the eastern and western regions are speculated to have experienced eastward migration along the southern slopes of the Lang Mountains and westward migration along the margins of the Ulanbuhe and Tengger deserts to the Hexi Corridor, respectively. For setting a conservation management plan, it is recommended that the south slopes of the Lang Mountains and northern Helan Mountains be identified as the two primary conservation areas, as they have high genetic variation and habitats that are more suitable.Quaternary period geological events and climatic oscillations significantly affect the geographic structure and genetic diversity of species distribution in arid northwestern China.  Tugarinovia mongolica from Inner Mongolia due to habitat fragmentation following enhanced aridification  supported two fragmented geographic groups among different populations of A. mongolica  and a nuclear marker (ITS1-ITS4). This study aimed to assess the spatial genetic structure and intraspecific differentiation and detect whether incomplete lineage sorting exists in A. mongolica populations in northwestern China according to cpDNA and nDNA sequences variation, inference of phylogeographic and demographic history of A. mongolica populations during Quaternary climate fluctuations and desert expansion was also performed, along with comprehensive identification of potential conservation areas for A. mongolica populations.Previous studies have shown that a variety of genes, such as maternally inherited chloroplast DNA (cpDNA) markers in combination with biparentally inherited nuclear DNA (nDNA) markers, show an integral view for identifying the relationships and genetic structure among taxonomic groups and populations . Here, mA. mongolica from 15 natural populations were investigated (http://www.resdc.cn/).A total of 174 individuals of stigated  throughostigated . The detstigated , includistigated . Fresh ypsbK-psbI, trnL-trnF and trnV  to conduct the polymerase chain reaction (PCR) . The DNA amplification profile was 94 °C for 2 min, followed by 30 cycles of 94 °C for 30 s, annealing at 52 °C , 54 °C (trnV) and 55 °C (ITS1-ITS4) for 30 s, 72 °C for 90 s, and a final extension at 72 °C for 10 min. The processing method of all PCR products were previously described in Ma , and nucleotide diversity (π) based on cpDNA and nDNA dataset, were calculated in DNASP 6.0 (https://cran.r-project.org/web/packages/ggplot2/index.html) (HT), average genetic diversity within populations (HS), and two parameters of population differentiation  were calculated using HAPLONST 3.0   . Total gONST 3.0 . PERMUT ST, NST)  with 1,0than GST .A. mongolica using the ‘vegan’ package in R 4.0.5  analysis with MEGA-X ver. 10.1.8  was used for tree-visualization  (−9 to 8.69 × 10−9 s/s/y)  , and sub9 s/s/y) , we used for ITS . The Mar for ITS .D , the sum of squared deviation (SSD) and their p values were computed to test the significance of this population expansion model. A non-significant value (p > 0.05) of SSD and Hrag indicated population expansion  according to the previous sequence mutation rate in Bayesian inference, and Tracer 1.5 was used to generate the BSP  for the last glacial maximum  and present (1970–2000) periods generated in MAXENT 3.4.1 to a “dispersal cost layer (resistance layer)”; Second, based on the least-cost path (LCP), the resistance layer of lbox 2.0  in ArcGIongolica . The datongolica .A. mongolica were employed to identify the potential conservation areas for A. mongolica (Hd and Rd) of each studied population and interpolated by using an established inverse-distance-weighted interpolation algorithm (http://www.resdc.cn/). According to the characteristics of suitable habitats of A. mongolica  was implemented to test the relationship between genetic diversity values among GWR was a spatial regression model that was an extension of traditional regression to predict, detect and estimate spatial non-stationary coefficient for model variables , it can Hd and Rd) of each population from both cpDNA and nDNA as the response variable. As predictor variables, we choosed 8 environmental factors from species distribution model and altitude data , then we removed multicollinearity (variance inflation factor > 7.5) between variables independent variables, and finally we kept five factors which were altitude, annual mean temperature (Bio1), isothermality (Bio3), temperature annual range (Bio7), and mean temperature of driest quarter (Bio9). In order to obtain dependent variable, we used the fishing net tool generate points with resolution of 2,000 m, and then extracted the dependent variable and independent variable information in ArcGIS10.5. GWR4.08 (https://gwrtools.github.io/) software was used to finish geographically weighted regression analysis, and ARCGIS10.5 was used to analyze the results visually.We used the genetic diversity values  and 5 ribotypes (R1–R5) in the Clade 1 are from the populations of the Western group, and the remaining 8 haplotypes (H10–H17) and 5 ribotypes (R6–R10) in the Clade 2 belong to the Eastern group, and no genotype was shared between the two groups . The resThe Western group mainly distribute in Alxa Left Banner and Hexi Corridor. The most widespread haplotype was H5, which shared by 4 populations and mainly distributed in Alxa Left Banner , and there are 7 private haplotypes  in the Western group. The most common ribotype was R3, which distributed among 5 populations, mainly from Hexi Corridor (YCQ) and Alxa Left Banner , Yinshan Mountains (YMM and YMF), and Urad Houqi (WLB); and five private haplotypes  were revealed. The most common ribotype was R8, which distributed in Urad Zhongqi (WLJ), the Yinshan Mountains (YMF and YMM) and Urad Houqi (WLB); R7, R9 and R10 were detected as three private ribotypes .Hd, Rd) among the 15 populations ranged from 0 to 0.567 (cpDNA) and 0 to 0.676 (nDNA); Nucleotide diversity (π) ranged from 0 to 0.00962 (cpDNA) and 0 to 0.00922 (nDNA), respectively  was much higher than HS  with both cpDNA and nDNA data, indicating considerable population differentiation. A higher level of NST  than GST , indicated a significant phylogeographical structure across the species range  and 0.31 Ma  in cpDNA and nDNA for the overall populations or the two groups in cpDNA and nDNA , high distribution suitability as determined by MAXENT (>0.80), and more natural habitats with little human activity .Considering the overall genetic diversity, distribution suitability of ountains . These tA. mongolica  between the Western and Eastern groups based on two cpDNA sequences, and phylogenetic analysis also revealed incomplete genealogical sorting , YMF (foot of the Yinshan Mountains) and WLJ (Urad Zhongqi) in the Eastern group, and in the WSH (northern Helan Mountains), WSM (Wusutu town of Alxa Left Banner), and ZQL (Southern Helan Mountains) in the Western group . An inteongolica . Overallongolica . HoweverA. mongolica. For this species, the enhanced aridity along with expansions of the Ulanbuhe and Tengger deserts, and the eastward extension of the Yinshan Mountains since the Quaternary period likely interrupted gene flow, triggering the current divergence in the two allopatric regions. The south slopes of the Lang Mountains and northern Helan Mountains were identified as having the most potential to be important protected areas for A. mongolica which is meaningful for the management of this endangered species. Future experiments will focus on how to better quantitatively describe gene flow.This study suggests a combination of climatic fluctuations and aridification during the Quaternary period combined with significant environmental heterogeneity in the Western and Eastern groups to play an important role in the phylogeographic structure and genetic diversity of 10.7717/peerj.13345/supp-1Supplemental Information 1Bootstrap values equal or larger than 0.60 are shown above branches.Click here for additional data file.10.7717/peerj.13345/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.13345/supp-3Supplemental Information 3http://www.worldclim.org). Through principal components analysis and Pearson correlation analysis, 8 remaining variables  were used to model the species distributions in MAXENT 3.4.1.Nineteen bioclimatic variables data were derived from the World Climatic Database (Click here for additional data file.10.7717/peerj.13345/supp-4Supplemental Information 4Click here for additional data file.10.7717/peerj.13345/supp-5Supplemental Information 5Click here for additional data file.10.7717/peerj.13345/supp-6Supplemental Information 6Click here for additional data file.10.7717/peerj.13345/supp-7Supplemental Information 7Click here for additional data file.10.7717/peerj.13345/supp-8Supplemental Information 8Click here for additional data file.