Nuphar (Nymphaeaceae) comprises aquatic plant species inhabiting freshwater bodies of the Northern hemisphere temperate regions known as yellow water-lilies. Nuphar lutea and N. pumila are the only representatives in the European continent and present different ecologies: the former is a widespread generalist, while the latter is restricted to northern latitudes or high-altitudes due to its requirements for colder and oligotrophic waters. The Central Europe mountainous areas, the Massif Central (France) and the Cantabrian Mountains (north Iberian Peninsula) harbor relict isolated N. pumila populations endangered by eutrophication and hybridization with N. lutea. We aim to detect hybridization processes in the Massif Central and Cantabrian Mountains populations and compare the genetic diversity of N. pumila in the relict populations of Central Europe by using microsatellite (SSR) markers. No evidence of hybridization was found in the Iberian population, whereas the admixture between N. pumila and N. lutea in the Massif Central populations could be due to hybridization or ancient introgression. Our current knowledge would benefit from genetic diversity studies focusing on both species throughout their distributional range. The Iberian and Massif Central N. pumila populations were genetically distinct, representing two different clusters from other relict populations, with low genetic diversity and a genetic boundary within Central Europe.The genus  Nuphar Sm. (1809) comprises 11 perennial herbaceous aquatic species, commonly known as yellow water-lilies, which inhabit freshwater bodies of the Northern hemisphere temperate regions [Nuphar lutea (L.) Sm. (1809) and Nuphar pumila (Timm) DC. (1821) [N. lutea is a more generalist species that inhabits warmer waters and tolerates higher salinity, moderately eutrophic habitats and water movements, while N. pumila—which is considered to be part of the “boreal–alpine glacial relicts”—prefers higher altitudes at southern latitudes , not very deep colder acid waters of mountain lakes, and oligotrophic and dystrophic habitats [The Nymphaeaceae genus phar Sm. 809 compr regions ,3,4. In . 1821) . These c821 . The. (1821) , display. (1821) ,7,8,9. Thabitats ,7,8,9,10N. lutea occupies vast territories in southern latitudes extending from the British Islands and the Mediterranean basin in the West—including the Balkans and most the Italic and Iberian Peninsulas—to China and Japan in the East [N. pumila comprises a series of relict populations confined to the British Islands and European mountainous areas of the Alps, the French Massif Central and the Cantabrian Mountains (North Spain) in the West, and the northern lakes of Mongolia, east China and Japan in the East [N. pumila populations in their natural range have been reported to have disappeared due to hybridization with N. lutea—which generates the fertile hybrid Nuphar × spenneriana Gaudin—and Nuphar japonica DC. (1821) in Japan; the degradation of their habitat due to human activity ; the eutrophication of water ; or the decrease in water levels [N. pumila in several European red lists with different degrees of concern, such as Least Concern (LC) at a continental and global scale in the European red list of vascular plants [Both species are distributed through the lakes of Eurasia, being widespread in northern latitudes ,11,12,13the East ,15,16,17the East ,20,21,22r levels ,19,23,24r levels ,25. Thesr plants  and The r plants ; Vulnerar plants ; Endanger plants ,30,31,32r plants ,33,34,35Nuphar by Ouborg et al. [Nuphar × spenneriana) and introgression processes between N. pumila and N. lutea in Central Europe [Nuphar × spenneriana using microsatellites, thus suggesting that the presence of this hybrid is one of the major threats for the survival of N. pumila in the area [Nuphar × spenneriana has been suggested to be capable of displacing either of its parental species depending on the scenario [The development of primers for the use microsatellite markers ) in g et al.  has allol Europe ,9 and thl Europe . In thisthe area ,9,10. Hothe area  based onthe area ,15,37. Mscenario ,8.N. pumila populations isolated from Western Europe, a recent molecular study based on an Internal Transcribed Spacer (ITS) and the plastid markers trnL-F and trnH-psbA, which focused on the Massif Central and the Cantabrian Mountains, did not find evidence of hybridization with N. lutea; suggesting that other factors—such as desiccation of water bodies—could represent a greater threat in southwest Europe [N. pumila to reproduce via clonal reproduction, more genetic information is needed to correctly implement conservation plans in order to guarantee the mid- and long-term viability of this population [N. lutea, we aim to use SSRs to (1) determine whether there is hybridization between the Iberian Peninsula and Massif Central N. pumila populations and their neighboring N. lutea populations, and (2) to compare the genetic composition of the Iberian Peninsula and Massif Central N. pumila populations with the populations in the Alps and their surrounding areas in order to determine the number of conservational units, their genetic affinity and the spatial genetic patterns existing between the three N. pumila refugia.Regarding the t Europe . Nevertht Europe , more sepulation ,20,25. INuphar  was collected for this study and deposited in the Herbarium of the University of Oviedo (FCO)  (PopFr1) and N. pumila population of the Lac de La Landie  (PopFr2). The third isolated population is the north Iberian N. pumila population of the Laguna de Reconcos . The samples were kept in silica gel during transport and before DNA extraction.Fresh foliar tissues and voucher materials from 43 individuals belonging to three different isolated populations of FCO) see . Two of ® Plant Minikit . The extracted DNA was preserved at −20 °C before utilization. A pilot study was conducted using microsatellites or Single Sequence Repeats (SSRs) in Nuphar [The genomic DNA of the sampled individuals was extracted using the Qiagen DNeasyn Nuphar , followen Nuphar . The use® [AN), the effective number of alleles per locus (EN), the expected heterozygosity (EH) and the observed heterozygosity (OH) were estimated for each of the three different populations. Additionally, the Shannon Information Index (I) (Shannon 1948), which measures variation among populations, and the standardized coefficient of genetic differentiation (STG″) [The sequences were visualized using GeneMarker®  and code®  to asses® ,42,43. Tn (G″ST) ,45 usingSTF [The divergence between the populations was estimated by calculating the pairwise Nei’s standard genetic distance (D) ,47, whicFST , which cSTF to calculate the genetic distance between the populations and 9999 random permutations to estimate the Fixation Index (STF); the Inbreeding Coefficient (ISF), which measures inbreeding due to differentiation within the subpopulations; the Total Inbreeding Coefficient (ITF), which measures inbreeding due to differentiation within and among the subpopulations; and the number of effective migrants per generation (Nm) [p-value) of the AMOVA analysis, which null hypothesis is the absence of difference between populations (STF = 0), was set at p-value ≤ 0.05. The genetic similarity between populations was also determined using the distance-based method Principal Coordinate Analysis (PCoA), following the method of [An Analysis of Molecular Variance (AMOVA) ,50,51,52ion (Nm) ,42,43 usion (Nm)  methods.ethod of  as impleethod of .Nuphar populations. The analysis consisted of 10 independent runs for each K value, which consisted of a burn-in fraction of 10.000 and 100.000 Markov Chain Monte Carlo (MCMC) repetitions while considering the independence of allele frequencies and the admixture model. Since individuals from 3 populations were tested, the number of assumed clusters (K) was set to 9. Since the number of individuals sampled from each population was unequal, the most adequate value of K was determined using the Evanno method [We used the Bayesian methods implemented in STRUCTURE v.2.3.4 ,57 to deo method  and the o method  as impleo method ,61. The o method ; howevero method . Hence, o method ,60, whico method . The popo method . Finallyo method . The STRo method ,63.N. pumila populations were combined with our data to compare the observed genetic diversity and structure of the south-west European isolated N. pumila population with the N. pumila populations belonging to the south-east European limit of distribution. Since the main aim of these analyses was to assess the N. pumila population, the reintroduced populations of the Bétrisey et al. [N. pumila different populations , the effective number of alleles per locus (EN), the expected heterozygosity (EH), the observed heterozygosity (OH), the number of different genotypes (MLG), the expected number of different genotypes (MLGE), the percentage of polymorphic loci and the number of private alleles for each population using the GeneALEx 6.5 and Poppr v 2.9.3 R package [I) [STF estimated based on the method of Weir and Cockerham [The genetic diversity of the isolated south-east and south-west European  package ). The Shkage [I)  and the ockerham  were useockerham .N. pumila populations was complemented by performing a PCoA [The genetic structure of the isolated south-west European g a PCoA  in GeneAg a PCoA , which ag a PCoA . In the g a PCoA . The memg a PCoA , was perg a PCoA ,71,72 ang a PCoA .N. pumila populations, the isolation by distance (IBD) was tested using the means of a Mantel test [STF based on the method of [In order to determine the relevance of geographical distance in the observed genetic patterns, various tests that incorporated geographical data were conducted. Given the geographical distance that separated the studied tel test  as impletel test , which tethod of  in hierfethod of  as impleethod of . The stasPCA analyses was determined by performing the Monte Carlo tests for Local and Global structure using 9999 permutations [The potential spatial patterns of the observed genetic variability were assessed using a spatial explicit multivariable method, the spatial Principal Component Analysis (sPCA), as implemented in Adegenet v.2.1.8 . For thiutations .The potential boundaries between the studied populations were detected using the Monmonier algorithm , which sN. pumila and N. lutea south-west European isolated populations ranged from 100 to 152 repetitions and from 115 to 172 repetitions, respectively  than the isolated population of N. pumila and N. lutea from the north Iberian Peninsula and the Massif Central , whereas the French and the Iberian isolated N. pumila populations exhibited a higher number of private alleles  than the N. lutea population . The isolated N. lutea population of the Massif Central had a fixed allele at the locus NLTG/GA1 , while the other two populations had no fixed allele  , while the observed heterozygosity was lower than the expected value in the case of the north Iberian isolated N. pumila population (PopAS: EH = 0.401 ± 0.105 and OH = 0.287 ± 0.237). Regarding genetic diversity, both the fixation index and the Shannon Information Index revealed that the Massif Central isolated N. pumila population was the most diverse (PopFr2: I = 1.480 ± 0.169), followed by the north Iberian N. pumila population (PopAs: I = 0.774 ± 0.238) and the Massif Central isolated N. lutea population (PopFr1: I = 0.630 ± 0.630). The STG″ indicated a high differentiation between the three populations, while the mean number of migrants per generation did not reach one individual . The NLGA7 and NLTG/GA1 alleles found in the vely see  indicate.00) see . The expN. pumila population and the isolated N. lutea population of the Massif Central were the most different pair of populations , while the Massif Central pair was the less genetically differentiated . The isolated N. pumila populations had a moderate level of differentiation . The axes of the PCoA analysis  explained 49% of the observed genetic differences, followed by the variation among populations , which explained 43% of the observed variation, and the variation among individuals , which explained 8% of the variation. This indicated that the variation among the populations outweighed the variation within the populations.The pairwise measurements of genetic differentiation, as estimated by the fixation indexes and the Nei distance see A, revealysis see B, which ysis see  indicateN. pumila population was dominated by an exclusive cluster, while the French populations were both dominated by the same majority cluster  and the Evanno methods indicated that the most adequate K value was K = 3, while the more restrictive Puechmaille method analysis (Q = 0.8) indicated that the most adequate K values were K = 2 and K = 3, as the median-based estimators (MedMeaK and MedMedK) indicated this interval see C,D. Thusster see E.N. pumila were studied using the STRUCTURE cluster analyses. This group of populations comprised one population from the north of the Iberian Peninsula (PopAs), one population from the Massif Central (PopFr2), one population from Jura (ABB), two populations from the west Swiss Plateau (BGF and JON), one population from Vosges (BAC), six populations from the east of the Swiss Plateau , four populations from the German Alps  and one population from the east of the Alps found in Austria (HAL).A total of 188 individuals belonging to 17 different Southern and Central European relict populations of N. pumila populations (see N. pumila (PopFr2) belonged to two genetic clusters, which were different from the Central European populations’ clusters , focused on 131 individuals belonging to 9 different populations  and a higher effective number of alleles (EN) than the isolated population from the Central European relict populations. The latter had AN ranging from 1.500 in the case of the populations of Vosges, east Swiss Plateau and eastmost German Alps to 2.500 in the case of westmost German Alps population , and NE ranging from 1.500 in the Vosges, east Swiss Plateau and eastmost German Alps populations to 1.727 in the case of the Austrian Alps population . The Iberian and the Massif Central populations did not present fixed alleles at any locus, with these populations having more private alleles  for both markers than the Central European populations, where only two populations presented private alleles . Some of the Central European populations presented fixed alleles at the locus NLTG/GA1: the east Swiss Plateau populations (KAM and GRA) and eastmost German Alps population of SIG had 133 fixed alleles , and the Vosges and the Austrian Alps populations of BAC and HAL had 131 fixed alleles (BAC and HAL: %P = 0.500). The graphical representation of the allelic composition of all these populations  and a higher estimated number of different genotypes at the lowest common populations size  than the Alps N. pumila population with a similar populations size (see EH) was higher in the north Iberian and Massif Central populations than in the Central European populations. The lowest observed heterozygosity (OH) was that of the north Iberian population. The Massif Central population was a special case among the latter, as the Standard Error (SE) of this population was lower than in the other populations, which presented high SE values. The Shannon Information Index (I) also showed higher values for the north Iberian and south-west French populations than for the Alps populations, which ranged from 0.347  in the case of the populations of the Vosges, the east Swiss Plateau and the eastmost German Alps populations to 0.540 in the case of the westmost German Alps population of STO . The genetic differentiation measured by the pairwise STF , with the former being more differentiated from the Central European populations, obtaining values ranging from 0.597 in the case of the Jura population (PopAS-ABB STF = 0.587) to 0.668 in the case of the eastmost Swiss Plateau population of GRA (PopAs-GRA STF = 0.668). The results also revealed that the south-west isolated French population from the Massif Central was more differentiated from the Iberian isolated population from the Cantabrian Mountains than from the Central European populations, as the STF values obtained ranged from 0.429 when compared to the Jura population (PopFr2-ABB STF = 0.429) to 0.355 when compared to the eastmost Swiss Plateau population of GRA (PopFr2-GRA STF = 0.547). These results indicate that the Massif Central population is distant to both the Iberian and the Central European populations. Regarding the Central European populations, the German Alps populations (STO and SIG) and the eastmost Swiss Plateau population (GRA) had little to no differentiation among each other , with the eastmost Swiss Plateau population (KAM) being the least differentiated population of these three populations . All the German Alps and east Swiss Plateau populations were most differentiated from the Vosges population (BAC) . On the other hand, the Vosges population was less differentiated from the Austrian Alps and the Massif Central populations (HAL and PopFr2), which were less differentiated from each other (BAC-HAL: STF = 0.456 and BAC-PopFR2: STF = 0.467).The north Iberian and the south-west French isolated ions see A also resize see . Regardi FST see B revealeThe PCoA see C, which The ML-based clustering method using snapclust indicated that the most adequate number of clusters was around K = 8 see A,B. HoweST . The two different networks used as based on the sPCA analyses, with one assuming only the disconnection of the Cantabrian Mountains population and the other assuming the disconnection of both the Cantabrian Mountains and the Massif Central populations, also suggested the existence of local and global structures . Hence, both positive and negative eigenvalues were used to estimate the sPCAs. The sPCA that assumed only the disconnection of the Cantabrian Mountains population indicated that the Cantabrian Mountains population belonged to a group separated from that of the Massif Central population, which belonged to a different group from that of the Central European populations  and Juncus balticus Willd. (1809) [N. pumila populations of the relict areas of Western and Central Europe. This has implications for the conservation of these populations at the European level since there seems to be between five and seven conservational units, with the Iberian and the Massif Central populations having two of these conservational units no matter how conservative the estimation is. Moreover, the detected signals of isolation based on genetic distance and the low gene flow detected between the Iberian and the other N. pumila populations suggest that the Cantabrian Mountains population could potentially be subjected to stochastic processes, which could lead to genetic decline and the extinction of this genetically unique population [N. pumila has been considered as the subspecies Nuphar luteum subsp. pumilum (Timm) Bonnier & Layens (1894) (=Nuphar lutea subsp. pumila (Timm) E.O.Beal, J. Elisha Mitchell (1956)) in recent years [Nuphar populations that have been registered as N. lutea could in fact be N. pumila. Hence, a morphological revision of the reported Nuphar populations should be considered, especially in lakes and ponds of the Pyrenees and north Iberian mountainous systems, to match the ecological references of N. pumila relict populations [In a wider context, the ulations  and has . 1809) . Interespulation ; these fpulation . Neverth809 . Intta L. 175 and Junculations  in orderN. pumila population is more complicated since the observed genetic distance, the overlap PCoA and the STRUCTURE analyses, along with the unexpectedly high heterozygosity, when compared to the Central European population suggest the possibility of an ongoing hybridization process with its neighboring N. lutea population. However, this is at odds with the results of Cires et al. [N. pumila populations in areas where N. pumila is considered relict, as well as in other areas of distribution of both species, as highlighted in [N. pumila relict population meta-analysis reveals that the allelic composition of the Massif Central population is different from those of the Central European populations, representing a different conservational unit.The case of the Massif Central s et al. , who fous et al.  when it s et al.  and Bétrs et al. , or to as et al. . To elucghted in ,6. Furthghted in  is suppoN. pumila meta-analysis revealed that the populations of the mountainous systems of the Cantabrian Mountains, the population of the Massif Central, and the group formed by the Jura, the Swiss Plateau and the German Alps populations represent three different genetic groups. We favor the hypothesis that the Vosges and the Austrian Alps populations belong to two different genetic groups, as the various clustering methods employed in this study retrieved results—which could be greatly influenced by the fixation of the same allele at the locus NLTG/GA1—that support both hypotheses, while the boundary detection analysis suggested the existence of a discontinuity between the Vosges population and the populations at the intermediate geographical position with the Austrian Alps population. Nonetheless, more information is needed in order to determine whether there is genetic continuity joining the west Swiss Plateau with the group formed by the Jura, the Swiss Plateau and the German Alps populations or not. The Monmonier algorithm detected a boundary between the Vosges population and the group formed by the Jura and the Swiss Plateau populations and between the German Alps and the Vosges populations based on our hypothesis . These results, together with the sPCA and the MSN results, raise new questions regarding the connection between the Western and Central Europe mountainous systems as this boundary could be caused by (1) the existence of at least two different converging colonization routes in Central Europe, with one coming from the north connecting the Vosges, the Jura and the Massif Central and one coming from the east connecting the Austrian and German Alps and the Swiss Plateau, or (2) the existence of an ancient or a recent abrupt disconnection between the Austrian and German Alps and between the Swiss Plateau and the Vosges. Thus, our understanding of the history of the Central European population would benefit from studies focusing on the genetic diversity of the north and east Europe populations.In this sense, the N. pumila would also shed light on the connectivity among the relict populations. In this context, bird endozoochory is regarded as being far less relevant than epizoochory and hydrochory for N. lutea long-distance dispersal [N. lutea and N. pumila [N. pumila populations and the use of more loci would clarify these results.Furthermore, studies on the long-distance dispersal mechanism of ispersal ,84. The . pumila ,85. Howe. pumila . This coN. pumila is listed in the IUCN Red List of Threatened Species [N. pumila populations in certain parts of its range, its categorization as LC is based on it being “wide-spread” in the United States and Canada, although neither the Flora of North America nor the Database of Vascular Plants of Canada (VASCAN) report the presence of this species [N. lutea.In a global context,  Species  as Least species ,87. This species ,6,9,19,  species  in the g


Sus scrofa lineages and interspecific hybrids. No prior study has determined the population structure and genetic diversity of PhNPs on multiple islands and provinces, which is essential for establishing conservation priorities. In this study, we explore the population structure and genetic diversity of various PhNP populations in Luzon and the Visayas, Philippines, to identify conservation priorities. We analyzed seven PhNP populations  and four transboundary breeds present in the Philippines . The pigs were compared against a panel of 20 microsatellite markers recommended by the ISAG–FAO. We tested for population structure at the island, region, and province levels. Strong genetic differentiation between native and transboundary breeds was confirmed by Bayesian clustering (k = 2) and Nei's DA genetic distance (100% bootstrap support for the PhNP cluster). PhNP exhibited high heterozygosity (Ho: 0.737), a high allele count (Na: 7.771), and a low inbreeding coefficient (Fis: −0.040–0.125). Bayesian clustering supported genetic differentiation at the island , region (k = 3), and population (k = 8) levels. The pairwise F'st between PhNP populations ranged from 0.084 (N and I) to 0.397 (Q and K), confirming that some PhNP populations exhibited sufficient genetic distance to be considered separate populations. This study shows that native pigs from B, K, I, Q, M, and S are unique genetic units for conservation. Furthermore, the small effective population sizes of B, I, Q, M, and S  necessitate immediate conservation actions, such as incentivizing PhNP farming.The Philippine native pig (PhNP) is a unique genetic resource composed of multiple domesticated  The Philippine native pig is a unique genetic resource consisting of multiple domesticated pig lineages and interspecies hybrids. Using microsatellite analysis, we demonstrate the population structure at the provincial level that supports six locally recognized populations. Low effective population sizes require immediate conservation actions. Samples from international transboundary breeds, pigs that can be found in many countries, were collected from accredited breeding farms in the Philippines as follows: Large White (LW), n = 11 samples; Landrace (LR), n = 9 samples; and Duroc (DC), n = 9 samples. These three breeds are the major pig breeds farmed in the Philippines and were used as references to verify admixture by crossbreeding, as well as provide a reference for assessing PhNP from an international perspective . BS has been intensively used in the past for the upgrading of PhNP  disease occurred in the Philippines. At least 40 animals were sampled based on FAO  recommenive FAO, . Additio2.2Twenty‐one microsatellite markers for swine Table  recommen2.3p‐values were adjusted by controlling the false discovery rate (FDR) by using the formula: rank* m/k, where k is the position of a p‐value in the sorted vector and m is the number of independent tests  between alleles at two loci (regardless of chromosome location) was conducted using default parameters in GENEPOP Rousset,  and LINKNa), the effective number of alleles (Ea), Shannon's information index (I), observed (Ho) and expected (He) heterozygosity, the fixation index (F), the F‐statistics , and the effective number of migrants (Nm) were estimated with GENALEX v6.5 . The polymorphic information content (PIC) was computed from all samples by POWERMARKER  was computed in NEESTIMATOR v2.1  following the methods of Meirmans  as well as variance due to between‐population differences  and between‐individual differences (within population), using allelic identity and allelic size. The standardized pairwise F'st  was computed via AMOVA using the codom‐allelic setting, with 999 permutations as implemented in GENALEX v6.5. Dendrograms were constructed using the unweighted pair group method with arithmetic mean (UPGMA) approach, the neighbor‐joining (NJ) method and Nei's DA genetic distance matrix . Ten independent runs were performed at each k . Each run consisted of 1,000,000 Markov chain Monte Carlo (MCMC) replicates after a 1,000,000 burn‐in. The resulting f‐files from STRUCTURE were then analyzed using STRUCTURE HARVESTER v0.6.94 , 4.366 effective alleles (Ea), and 0.279 private alleles (Pa) across loci (Table Na: 8.850) was observed in the N population, while the lowest (Na: 6.850) was in the B population. The observed heterozygosity (Ho) was 0.737. The B, K, and S populations deviated from HWE according to the heterozygote deficiency method, suggesting further population stratification. The inbreeding coefficient suggested no to moderate inbreeding among PhNPs  and lower heterozygosity . Furthermore, the regional difference in highland PhNPs, lowland PhNPs, and transboundary breeds was 7%. In general, lower values were obtained using IAM. Our results show that the SMM attributes larger variance to the regional differences between highland and lowland PhNPs, indicating that it is a better model than IAM when the analysis includes the highland PhNPs (B population).We further assessed the sources of diversity in the PhNP to determine whether it is attributable to the individual, the subpopulation, or to any of the five regional distributions, in particular highland versus lowland PhNPs, and tested two mutation models (SMM and IAM). The AMOVA results indicated that the variation in genetic diversity between highland and lowland PhNPs, attributable to region, population (between‐population level), and individual (within‐population level), was 18%, 5%, and 78%, respectively, when allele size was incorporated into the analysis  ranged from 0.084 to 0.175, and those between the SLV  ranged from 0.137 to 0.183. On the other hand, low F'st values (below 0.150) were observed between the following populations: N and I, N and M, and Q and M. Recent gene flow between these populations was supported by a high number of migrants  between the Q and M populations. The results indicate that PhNP populations from different islands (NL and SLV) are more likely to have stronger genetic differentiation than those from the same island. On the other hand, pairwise F'st showed high differentiation between the PhNPs and transboundary breeds, with values ranging from 0.328 (Q vs. LR pigs) to 0.714 (K vs. BS pigs) (Table Nm: 0.733–3.152).The high between‐population variation among PhNPs was further dissected by pairwise analysis using standardized DA genetic distances were computed, and dendrograms were constructed. All PhNPs formed a distinct cluster  from the transboundary breeds  of each of the seven previously assigned PhNP populations. The effective population size ranged from 3.9 (the B population) to 125.9 (the K population), with the majority (except K and N) having critical Ne values below 50  of Monleon et al. , necessitating the need for immediate conservation actions. We also show the low admixture between native and transboundary breeds, which should be maintained in favor of conservation of the distinct PhNP populations. The Philippine government supports the conservation of native animals through the Philippine Native Animal Development (PNAD) program, where the NSPRDC is the implementing arm for the ex situ conservation of native pigs . Furthermore, the Department of Science and Technology‐Philippine Council for Agriculture, Aquatic and Natural Resources Research and Development (DOST‐PCAARRD) supports research and development projects of state universities and colleges (SUCs) that encourage PhNP farming and increased productivity and profitability . Our previous analysis of the mitochondrial DNA (mtDNA) D‐loop region revealed three ancestral origins of the PhNPs used in this study, that is East Asia (haplotype D2), Southeast Asia (haplotype D7), and the Cordillera clade  differentiating the NL and SLV regions, respectively  and showed further subdivision below provincial boundaries Figure . Geneticy Figure . We prevy Figure . ThereafBerkjala, which is now extinct  between highland and lowland populations supports a long period of divergence, according to the assumptions of the SMM , presumably due to introgression of wild pig alleles via interspecific hybridization. Having a high Ne is beneficial in that it increases the fitness of organisms  and having indigenous communities with their own rituals and traditions, the pig population in K had a high effective population size  are immediate conservation priorities  must be conserved to facilitate long‐term viability. Additionally, PhNP is an important repository of genetic variation, as shown by its high allele count (Na: 7.771) and heterozygosity (Ho: 0.737), thereby further warranting investments in their conservation. This study emphasized the importance of PhNP as a repository of genetic variation, primarily for adaptation traits. Further studies on the genetic basis of adaptation of the PhNP may be explored. Last, due to the economic advantage of using transboundary breeds, we recommend incentivizing native pig farming by funding agrobiodiversity conservation services to improve the sustainability of in situ or on‐farm conservation of the PhNP  to address the needs of modern farmers for a faster‐growing native pig while systematically avoiding population admixture. On the other hand, indigenous communities that raise PhNPs for cultural traditions, rather than income, must be incentivized to increase private benefits for utilizing PhNPs and subsequently sustaining on‐farm conservation. Since the majority are smallholder swine farms in the Philippines PSA, , a largeJoy B.Banayo: Conceptualization (lead); formal analysis (lead); funding acquisition ; investigation (lead); methodology (lead); project administration (lead); validation (lead); visualization (lead); writing – original draft (lead); writing – review and editing (lead). Kathlyn Louise V. Manese: Formal analysis (supporting); investigation (supporting); project administration (supporting); writing – review and editing (supporting). Kaito O. Furusho: Formal analysis (supporting); visualization (supporting); writing – original draft (supporting). Agapita J. Salces: Conceptualization (supporting); funding acquisition (supporting); project administration (supporting); supervision (supporting); writing – review and editing (supporting). Takahiro Yamagata: Conceptualization (supporting); funding acquisition ; project administration (supporting); supervision (lead); writing – review and editing (supporting).This work was supported by Nagoya University‐Asian Satellite Campus Institute (NU‐ASCI), the University of the Philippines (UP), and the Department of Science and Technology ‐ Philippine Council for Agriculture, Aquatic and Natural Resources Research and Development (DOST‐PCAARRD).The authors have no relevant financial or nonfinancial interests to disclose.https://doi.org/10.5061/dryad.b8gtht7gg].This article has earned an Open Data badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. The data is available at [Tables S1.–S3.Click here for additional data file.


Annona senegalensis Pers., an important multipurpose wild plant, distributed exclusively in natural ecosystems but facing several threats. The study assessed the genetic and morphological diversity, structure, and differentiation of the species in populations from Western (Benin) and Southern (Mozambique) Africa. The material was evaluated to ascertain the environmental (climatic) determinants of the variation within this species.Understanding morpho-genetic diversity and differentiation of species with relatively large distributions is crucial for the conservation and sustainable management of their genetic resources. The present study focused on Four sub-populations comprised of 154 individuals were phenotyped based on nineteen plant, fruit, and leaf morphological traits and further genotyped using ten polymorphic nuclear microsatellite (nSSR) markers.A. senegalensis.The results indicated strong differences in plant, fruit, and leaf morphological traits between Western and Southern populations. Furthermore, the studied populations were characterized by high genetic diversity, with an average genetic diversity index of 1.02. Western populations showed higher heterozygosity values (0.61–0.71) than Southern populations (0.41–0.49). Western and Southern populations were clearly differentiated into two different genetic groups, with further genetic subdivisions reflecting four sub-populations. Genetic variation between regions (populations) was higher (69.1%) than among (21.3%) and within (9.6%) sub-populations. Four distinct morphological clusters were obtained, which were strongly associated with the four genetic groups representing each sub-population. Climate, mainly precipitation and temperature indexes, explained the relatively higher variation found in morphological traits from Western (40.47%) in relation to Southern (27.98%) populations. Our study suggests that both environmental and genetic dynamics play an important role in the development of morphological variation in  The change in land use and climate are fragmenting the natural habitats of many useful wild edible fruit trees . As a coi.e., more resilient, productive, and nutritive  and Southern (Mozambique) Africa and the role of climate and genetic factors in shaping phenotypic variability. Specifically, we have assessed, (i) the genetic diversity, population structure, and differentiation; (ii) the morphological diversity, and structure; (iii) the overlapping between genetical and morphological clustering of individuals; and (iv) the relative importance of climate in the morphological variation.n Africa . Its disng plant . It is ang plant . Differeng plant . As a tr habitat . Despite habitat , geneticn Malawi . In West climate . Whether climate . Simple  climate . The pre2 and has been described as the largest protected area of Mozambique and the third largest in Africa , Mozambique (Southern Africa), and in the Sudanian zone, Benin (Western Africa), two locations where the species is best known and used. NSR is located in Northern Mozambique approximately between latitudes 12°8′40′N and 12°22′40′N; and longitudes 37°21′00′E and 37°45′00′E . It coven Africa . Seventya Benth. . The clia Benth. . About 6a Benth. . Slash-aa Benth. .Isoberlinia spp., Combretum spp., Acacia spp., Hyparrhenia spp., Loudetia spp., and Andropogon spp.  according to the procedures described by the manufacturer, using 50 mg of ground leaves. The yield and purity of each sample was determined by spectrophotometry at 230, 260, and 280 nm , and complemented by agarose gel electrophoresis . Based oPCR reactions were performed under the following conditions: 94 °C for 1 min; 94 °C for 30 s, 55 °C for 30 s (45 °C for LMCH29), 72 °C for 1 min (35 cycles); and 72 °C for 5 min. Each reaction was performed in a final volume of 15 µL containing 100 ng of genomic DNA, 0.4 µM each primer , 1.25U MData were collected in Mozambique from January to April 2021 and in Benin from June to September 2021, after fruiting. Six morphological descriptors were measured on plants, namely total height, bole height, crown height, trunk diameter at breast height, crown diameter, and crown shape. The bole height is the height from the ground to the first big branch and the crown height is the difference between total height (m) and bole height (m). The crown shape was derived from the ratio of crown height over crown diameter. To determine the crown diameter (m), four radii were measured from the projection of the crown on the ground . At leasUsing the GPS coordinates of each individual in QGIS 3.16.2 , bioclimK) with ten replications per K. Models were run assuming ancestral admixture and correlated allele frequencies using run lengths of 300,000 interactions for each K after 50,000 burn-in steps. The optimum K was determined using STRUCTURE HARVESTER , mean number of alleles per locus (Na), Shannon’s information index (H), mean expected heterozygosity (He), mean observed heterozygosity (Ho), inbreeding coefficient (FIS), and Polymorphism Information Content (PIC) using GenAlEx 6.51 . The BayARVESTER , which id the ΔK . The resPP 1.1.2 . A PrincPP 1.1.2  to detecPP 1.1.2 . The relPP 1.1.2  implemenPP 1.1.2  using thcv %) was used to assess the variability of each morphological trait, considering a cv < 25% an indicator of weak variability , the corresponding non-parametric test  was applied. When the Analysis of Variance (ANOVA) indicated a significant difference, a SNK-test was applied as a multiple comparison test in the package AGRICOLAE  within the VEGAN package was carried out on the least square mean values of the morphological descriptors and bioclimatic variables . The RDA was first carried out separately for the Western, and the Southern sub-populations. Another RDA analysis was implemented with the merged populations. These RDA analyses were intended to assess whether the relative importance of the relationships between bioclimatic variables and morphological variation was similar for the two regions. All analyses were implemented in R statistical software version 4.1.2 .Annona senegalensis samples. The number of alleles varied from 27 in the Southern (Moz_MAV sub-population) to 55 in the Western (Ben_BGN sub-population) region . This pattern was also observed in the average number of alleles , the Shannon Diversity Index , and the observed  and expected heterozygosity   i.e., higher in the Western than in the Southern population  region . The tot= 0.024) . The perpulation . FIS shopulation  suggestiK = 2 differentiating the samples collected in Benin from the ones collected in Mozambique  and ΔK values for zambique . Neverthclusters . Despiteclusters . The samclusters . The firTRUCTURE . The degTRUCTURE .p < 0.001). In addition, 21.3% of variation occurred among populations while the remaining was found within sub-populations. In addition, the Mantel test confirmed the existence of a significant positive correlation between Nei’s genetic distance and geographic distance for all pairwise sub-populations .AMOVA revealed that a high proportion of genetic variation was attributable to significant differences between the two regions (69.1%) supported by high levels of genetic differentiation  and taller  than those from Northern populations  (cv) was high (cv > 25%) for all traits. However, Northern populations had the highest cv values irrespective of the traits, except for the crown shape. A significant difference was reported among sub-populations. However, the sub-population Ben_BGN (North Benin) had a similar trunk diameter at breast height (DBH) to that of Moz_MEC (South Mozambique). Within Southern populations, sub-populations Moz_MEC and Moz_MAV had similar values for bole height. The cv value decreased from both populations (31.04% to 65.55%) to sub-populations (15.49% to 65.00%), but was still relatively high. The DBH, bole height, crown height, crown diameter, and crown shape were more diverse in Moz_MAV, while the total height highly varied in Ben_MPE  . Irrespe Ben_MPE .cv regarding all traits, except fruit length, width, and fruit shape  suggested a significant association between genetic and morphological variation, and hence, an effect of genetic factors on the morphological variation i.e., the distribution of trees in genetic clusters is not independent of the morphological clusters. For instance, 86.67% of the individuals included in morphological cluster 1 corresponded to genetic cluster 1; and 70% of the individuals included in morphological cluster 3 correspond to the genetic cluster 3  and explained the extent to which variation in morphological traits is related to bioclimatic variables. In Western populations, the model considered nine out of the 19 bioclimatic variables . The first axis (RDA1) explained 80.77% of the total variance and was a combination of mean diurnal air temperature range (chelsa_b_1), temperature seasonality (chelsa_b_3), mean daily maximum air temperature in the warmest month (chelsa_b_4), annual range of air temperature (chelsa_b_6), mean daily air temperature of the wettest quarter (chelsa_b_7), mean daily air temperature in the warmest quarter (chelsa_b_9), and mean monthly precipitation in the coldest quarter (chelsa_b_18). The second axis (RDA2) explained 8.56% of the total variation and combined mean annual air temperature (chelsa_bio), and annual precipitation (chelsa_b_11).The redundancy analysis showed that there was a significant correlation between morphological traits and bioclimatic variables. Furthermore, this relationship varied in diverse ways according to the two regions. In all cases, only the first two axes were significant  explained 67.17% of the total variance and was a combination of mean annual air temperature (chelsa_bio), mean diurnal air temperature range (chelsa_b_1), temperature seasonality (chelsa_b_3), and mean daily maximum air temperature in the warmest month (chelsa_b_4). The second axis (RDA2) explained 21.74% of the total variation and only considered the annual range of air temperature (chelsa_b_6).In Southern populations, the model considered only five out of the 19 bioclimatic variables . The first axis (RDA1) explained 83.44% of the total variance and was the combination of isothermality (chelsa_b_2); temperature seasonality (chelsa_b_3); mean daily minimum air temperature in the coldest month (chelsa_b_5); mean daily air temperature of the wettest quarter (chelsa_b_7); mean daily air temperature of the driest quarter (chelsa_b_8 ); annual precipitation (chelsa_b_11); amount of precipitation in the wettest month (chelsa_b_12); amount of precipitation in the driest month (chelsa_b_13); precipitation seasonality (chelsa_b_14); and mean monthly precipitation in the wettest quarter (chelsa_b_15). The second axis (RDA2) explained 6.19% of the variation and only considered the mean daily air temperature in the warmest quarter (chelsa_b_9). However, some of these bioclimatic variables such as mean annual air temperature, temperature seasonality, mean monthly precipitation in the coldest quarter, annual range of air temperature, and the mean monthly precipitation in the wettest quarter were not statistically significant in these different models , mean diurnal air temperature range (chelsa_b_1), temperature seasonality (chelsa_b_3), and the mean daily maximum air temperature in the warmest month (chelsa_b_4) , 9.Considering the global set of sub-populations, morphological parameters were all loaded in RDA 1 except limb length, leaf width, the ratio leaf length to petiole length, and leaf weight. The DBH, total height, bole height, crown height, crown diameter, crown shape, fruit length, fruit width, fruit shape, fruit weight, number of seeds per fruit, seeds weight, pulp mass, and leaf length were positively influenced by the mean daily minimum air temperature in the coldest month (chelsa_b_5) and mean daily air temperature of the driest quarter (chelsa_b_8 ) , 9. The Annona senegalensis samples. This is much higher than the values reported by A. senegalensis samples collected in nine Malawi populations, and using a limited number of molecular markers. Heterozygosity values varied between 0.22 and 0.62 being attributed to changes in population size and habitat heterogeneity. The values reported in this study were even higher than those observed in Anona cherimola Mill, another edible tree that has economic importance in many Mesoamerican countries, where wild and cultivated trees grow  collected from various locations and based on 11 RAPD and 12 SSRs markers, identified similar levels of heterozygosity. The high genetic diversity may be explained by protogynous dichogamy, a common breeding characteristic in Annonaceae, where female and male structures do not mature simultaneously , Moz_MEC, and Moz_MAV (from the Southern region) into four different genetic clusters. These findings were supported by the PCoA which showed a clear spatial separation between Western and Southern populations and also between sub-populations within each geographical region. This genetic structure could be explained by the wide geographical distance that occurs between the two countries, which does not favour gene flow between them (Our results showed a high level of genetic differentiation in the studied populations. The Bayesian clustering program STRUCTURE presented the highest LnP(D) and ΔK values for K = 2 differentiating the samples collected in the Western from those collected in the Southern region. STRUCTURE also revealed secondary high LnP(D) and ΔK values at een them . This exeen them , beetlesi.e., the distribution of trees in genetic clusters was not independent of the morphological clusters. The strong association with genetic and morphological data might therefore reflect a high local adaptation of the species.Likewise, high variation in morphological traits was observed between populations. Individuals from the two sub-populations from the Western region and the two from the Southern region were grouped into four different clusters. The chi-square test performed on morphological and genetic data confirmed a significant association between the two, showing that the studied populations were morphologically and genetically connected, A. senegalensis populations to different environments, in agreement with the findings of A. senegalensis. Yet the availability of high genetic diversity in the studied populations is a sign of biological adaptability that can enable A. senegalensis to respond in various ways to changes in the environment.Morphological traits were also found to be highly influenced by the environment, mainly by temperature and precipitation indexes  and 9. IA. senegalensis from Western (Benin) and Southern Africa (Mozambique). Strong differences were observed in the morphological traits scored in whole plants, fruits, and leaves between Western and Southern populations. Moreover, high genetic diversity was found in the studied populations. A significant association was found between morphological traits and genetic parameters. Precipitation and temperature extremes were found to be the most important climate factors, influencing A. senegalensis morphological traits. Our study provides crucial information for the sustainable management of this species.The present study reported the morpho-genetic diversity in populations of 10.7717/peerj.15767/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.15767/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.15767/supp-3Supplemental Information 3Click here for additional data file.


Miichthys miiuy), a species of fish with significant commercial value, is found in the coastal seas of Korea, China, and Japan. The genetic diversity and population structure of a representative sample of brown croaker specimens were assessed based on the control region of their mitochondrial DNA (mtDNA). Samples from a total of 115 individuals were collected from three separate locations, one in China (Lianyungang) and two in Korea (Mokpo and Gyeongnyeolbiyeoldo Island). Analysis of the 436-base-pair mtDNA control region revealed that the haplotype diversity ranged from 0.973 ± 0.025 to 0.988 ± 0.008, while the nucleotide diversity ranged from 0.012 ± 0.006 to 0.017 ± 0.009. The level of genetic diversity, star-shaped haplotype network, significant Fu’s Fs test, and analysis of the mismatch distribution all suggested that this species has experienced population expansion. Fixation index analysis indicated that the population collected at the site in China differed significantly from the two populations obtained in Korea. The findings of this study extend the general understanding of the population structure of M. miiuy and can be used to develop strategies for effective resource management.Brown croaker ( M. miiuy (brown croaker) is a semi-benthic member of the Sciaenidae family that is found throughout the coastal waters of Korea, China, and Japan on muddy to sandy bottoms at a depth of 15–100 m [15–100 m ,3. In Ko15–100 m ,7,8,9. I15–100 m . Brown c15–100 m . However15–100 m .FST analysis, with the exception of one population (Zhoushan) despite the fact that no obvious physical barriers existed between the sampled populations. However, to the best of our knowledge, no studies of the brown croaker population structure have been conducted in Korean waters. Therefore, this study represents an attempt to characterize the population structure in Korean waters and to discern whether these populations differ significantly from those in China.The development of suitable management strategies for the sustainable use of resources relies on an understanding of the genetic structure of fish populations, investigations of which also advance the general understanding of biotic evolution ,14. AlthMany molecular marker techniques have been developed in recent years to investigate the genetic structure of plant and animal populations for conservation and/or to ensure the sustainable yields of commercial species . In partA total of 115 individual wild brown croakers  were colGenomic DNA was extracted using proteinase K and a Wizard genomic DNA purification kit . A pair of universal primers, L15926 (5′-TCAAAGCTTACACCAGTCTTGTAAACC-3′)  and H-16FST), and its significance was tested using 1000 bootstraps. To observe the relationship among haplotypes, a phylogenetic network was constructed using the obtained haplotypes with the neighbor-joining method [Bahaba taipingensis control region of the mtDNA sequence was employed. To observe the phylogenetic relationship, a maximum-likelihood-based phylogenetic tree was also constructed in MEGA 5. Geographical relationships between the haplotypes were also investigated by constructing a minimum-spanning network using the ARLEQUIN and Hapstar software programs [D test [Fs test [D and Fu’s Fs values were interpreted as signatures of demographic expansion, which was further investigated using mismatch distribution analysis. The distribution is unimodal for a population that has undergone population expansion, whereas it is multimodal for a population at demographic equilibrium. Neutrality tests and mismatch distributions were calculated in AELEQUIN.The 115 brown croaker mtDNA control region sequences were checked and aligned using clustalW , which wg method  implemeng method . Completg method  in MEGA programs . Genetic [D test  and Fu’s[Fs test  for seleut, where u is the mutation rate for the whole sequence under study per generation and t is the time measured in generations since expansion. For marine fishes, the molecular clock has not been precisely determined for the control region and varies between different taxonomic groups. The control region of mtDNA is assumed to mutate at the same rate as the protein-coding region, with mutation rates observed for different fish species such as snooks (3.6% divergence per million years (MY)) [M. miiuy has a faster molecular clock as observed for other vertebrates [The demographic expansion parameter τ   was calcrs (MY)) , East Afrs (MY)) , and Ausrs (MY)) . Howeverrs (MY))  and Arctrs (MY)) . Considetebrates . In the After checking and aligning the 115 sequences, a 436 bp segment of the mtDNA control region was obtained. A total of 87 haplotypes were detected with 79 substitutions. The haplotypes were deposited in the NCBI under the accession number OR142674-OR142760. The haplotype diversity ranged from a low of 0.973 ± 0.025 in Lianyungang to a high of 0.988 ± 0.008 in Mokpo, while the nucleotide diversity ranged from a low of 0.012 ± 0.006 in Mokpo to a high of 0.017 ± 0.009 in Lianyungang. The pooled haplotype and nucleotide diversity were 0.987 ± 0.004 and 0.015 ± 0.008, respectively . The nucFs tests were indicative of population expansion, which was also supported by a low and insignificant Harpending’s raggedness index and sum-of-square deviation  and Fu’s Fs tests and the low and insignificant Harpending’s raggedness index and sum-of-square deviation were all consistent with population expansion [Larimichthys polyactis [Hexagrammos otakii [Clupea pallasii [The demographic history of brown croaker in the Northwest Pacific is largely unknown. The phylogenetic tree constructed using the neighbor-joining method was shallow, with short branches and low bootstrap support. The haplotypes from individuals at different locations were scattered throughout the tree, which indicates that the species has undergone recent population expansion, which was supported by the star-shaped minimum-spanning tree. However, the mismatch distribution for the Mokpo population was unimodal, whereas the Gyeongnyeolbiyeoldo and Lianyungang populations had a slightly bimodal mismatch distribution. The significantly negative results for the Tajima’s xpansion . The higxpansion ,46. Durixpansion  in the Eolyactis , Hexagras otakii , and Clupallasii .FST analysis but no strong phylogenetic break, which may be due to recent population expansion. Only one haplotype (MMM24) was shared by all three populations, though the frequency of occurrence within the Chinese population was very low. The heterogenic frequency of this haplotype suggests a non-panmictic population [FST values. Xu et al. [Marine fish species usually exhibit high levels of gene flow and shallow population structures due to the absence of obvious physical barriers to genetic exchange, their high dispersal capabilities, and large effective population sizes . Howeverpulation ,52. Manypulation ,54. A prpulation  of brownu et al.  conducteSynechogobius ommaturus between Chinese and Korean populations [C. pallasii between Chinese and Japanese populations [M. miiuy may follow these to maximize their retention, survival, and self-recruitment. In marine fish, their early life history influences their survival [In the present study, the study locations were in China and Korea, thus covering a broad geographical range for the first time for this species. Similar results over a broad geographical range have been observed for ulations  and C. pulations . Brown culations , whereasulations ,5,7. Theulations ,55. Prevulations  and M. msurvival  and playsurvival .H. otakii [Sebastes miniatus [Gadus macrocephalus [Charybdis japonica [G. macrocephalus [Lianyungang is a pocket-shaped area that is influenced by coastal currents. The China coasts are strongly influenced by the Yellow Sea Coastal Current and the China Sea Coastal Current , and som. otakii , Sebasteminiatus , Gadus mcephalus , and Chajaponica . The wescephalus .M. miiuy.However, mtDNA contains a low number of loci, which can make it difficult to accurately distinguish between populations. Because microsatellite DNA (msDNA) is highly polymorphic, it is often used as a sensitive marker in fish population studies. Therefore, it will be necessary to conduct additional studies on the population structure of brown croaker using sensitive markers such as msDNA for samples collected from various regions in Korea and China. In addition, the number of individuals collected from China was lower than for the two locations in Korea. Therefore, the collection of larger samples from a broader range of Chinese waters may gain clearer insights into the population structure of


Yungui Plateau in Southwest China is characterized by multi-language and multi-ethnic communities and is one of the regions with the wealthiest ethnolinguistic, cultural and genetic diversity in East Asia. There are numerous Tai-Kadai (TK)-speaking populations, but their detailed evolutionary history and biological adaptations are still unclear.Here, we genotyped genome-wide SNP data of 77 unrelated TK-speaking Zhuang and Dong individuals from the Yungui Plateau and explored their detailed admixture history and adaptive features using clustering patterns, allele frequency differentiation and sharing haplotype patterns. TK-speaking Zhuang and Dong people in Guizhou are closely related to geographically close TK and Hmong-Mien (HM)-speaking populations. Besides, we identified that Guizhou TK-speaking people have a close genetic relationship with Austronesian (AN)-speaking Atayal and Paiwan people, which is supported by the common origin of the ancient Baiyue tribe. We additionally found subtle genetic differences among the newly studied TK people and previously reported Dais via the fine-scale genetic substructure analysis based on the shared haplotype chunks. Finally, we identified specific selection candidate signatures associated with several essential human immune systems and neurological disorders, which could provide evolutionary evidence for the allele frequency distribution pattern of genetic risk loci.Our comprehensive genetic characterization of TK people suggested the strong genetic affinity within TK groups and extensive gene flow with geographically close HM and Han people. We also provided genetic evidence that supported the common origin hypothesis of TK and AN people. The best-fitted admixture models further suggested that ancestral sources from northern millet farmers and southern inland and coastal people contributed to the formation of the gene pool of the Zhuang and Dong people.The online version contains supplementary material available at 10.1186/s12864-023-09412-3. Tai-Kadai (TK) people are mainly distributed in South China and Southeast Asia, including Zhuang, Dong, Sui, Mulao, Maonan, Li, Gelao, Buyei and Dai, etc. According to historical records, the TK-speaking populations are descendants of the ancient Baiyue people from southeastern China . Recent Yungui Plateau, also called the Yunnan-Guizhou Plateau, is located in the flatter highland areas or the mountainous area of rolling hills, gorges, and karst topography region of Southwest China, which stretches from Yunnan’s Red River Fault in the southwest, across most of Guizhou Province and to the Hunan’s Wuling Mountains in the northeast and neighbours Chongqing and Sichuan in the north and Guangxi in the South. TK people are widely distributed in the Yungui Plateau and the surrounding South China and Mainland Southeast Asia regions. There are still some debates on the admixture events and evolutionary history of the genetic diversity of the TK populations , 11, 12.Anatomically modern humans originated in Africa and interbred with archaic Neanderthal and Denisovan people in Eurasia . About 1f3/f4 statistics, etc., to deeply analyze the genetic origin of the TK population in Southwest China and explore and determine the positive natural selection signals of the TK populations.Based on previous genetic, linguistic, ethnic, and archaeological findings, we have the basic knowledge of the admixture history of TK people from China and Southeast Asia. However, fine-scale genetic structure and adaptive history based on the allele frequency differentiation and sharing haplotype patterns of Guizhou Dong and Zhuang people from the Yungui Plateau keep unknown. Besides, the genetic relationship between Zhuang and Dong people and their genetic relationship with other populations must be explored. Therefore, here, we integrated high-density data of 679,920 SNPs from Zhuang and Dong groups in the Congjiang county from Guizhou Province with modern and ancient SNP data from worldwide or East Asian populations included in the Allen Ancient DNA Resource (AADR) version v54.1 , 26. We ~ C). When we projected ancient samples from Guangxi and South China, the studied TK populations overlapped with ancient populations from South China, including Taiwan_Hanben, Liangdao1_EN and Xitoucun_LN in PC1 (0.74%) and PC2 (0.67%)  and Dong_Congjiang (CJD) in Guizhou Province Fig. A. We merNext, we dissected and presented the ancestry proportions of CJZ and CJD using model-based ADMIXTURE in the context of modern and ancient reference populations, where the cross-validation error of the K = 8 model was the lowest Fig. . The newTo further dissect the genetic similarities and differences between newly-studied Guizhou TK populations and modern populations in East Asia, we explored the fine-scale population structure based on the genome-wide patterns of shared haplotype chunks generated from the merged 670 K dataset. We phased the haplotype fragments of 77 people from TK language families and other East Asians to explore the fine-scale population structure based on shared haplotype chunks Fig. A. The neTo further explore the population substructure between Guizhou TK people and reference TK people from geographically different China and Mainland Southeast Asia, we merged our data with 60 publicly available TK-speaking populations and neighbours , 27. We f3-statistics of the form f3. Our findings demonstrated that the identified clustering pattern based on the outgroup-f3 matrix was compatible with intercontinental geographic division  to explore the genomic heterogeneity or homogeneity among all studied TK populations  suggested that the studied TK-speaking people shared more alleles with the geographically close HM populations than Dai   further reinforced the findings that AN-speaking populations in South China shared more alleles with the TK-speaking people compared to northern East Asians  Fig. . The conf3-statistics in the form f3 to explore the potential ancestral sources from 126 sampled modern and ancient Eurasian populations , suggesting that ancient people related to geographically close HM people and northern ST people contributed to the gene pool of Guizhou Dong. When we used ancient East Asian populations as primary ancestry of potential ancestral populations, we found an admixture signature when Shenxian and China_Miaozigou_MN were used as the source populations, such as f3 = − 3.153*SE. The Gaohuahua population from Guangxi also generated a robust mixed signal with northern East Asian populations, as shown by the fact that the Z-score of f3 was − 6.668. However, we did not observe significantly negative Z-scores in admixture f3-statistics in the form of f3, which showed that Zhuang people obtained relatively little recent gene flow from others  and Atayal_Taiwan (50%) both contributed to the gene pool of TK people Table . When YiSecondly, we estimated the admixture date based on the exponential decay pattern of admixture-induced linkage disequilibrium and probability patterns of two chromosome ancestry segments in admixed individuals derived from two ancestry sources to explore when ancient populations from the northern and southern East Asians entered the gene pool of studied TK populations. Previous ancient genome research reported that the ancestors of TK-speaking people might be 1500-year-old BaBanQinCen, a possible ancestor who speaks TK languages, a meta-population of archaeological sites that lived in Guangxi 1,500 years ago [CSMD1, EXOC4, GALNT18, GALNTL6, HLA-DRA, JAZF1, KCNQ1, LINC00486, LRP1B, NELL1, OPCML, RBFOX1, SMYD3, STK32B and TENM4. These targeted loci were used as the top selected adaptive genes, whose annotation information was mainly associated with the immune system and neurological disorders  to identify the highly-differentiated variants and used haplotype-based approaches, including the cross-population extended haplotype homozygosity (XPEHH) and integrated haplotype score (iHS), to examine the status of sweep selection in TK people. Ultimately, we screened 15 genes based on the intersection obtained by XPEHH, iHS and Fst, namely ers Fig. . Some fulearning . EXOC4 ismission . LRP1B afunction . OPCML isduction . RBFOX1 HLA-DR genes with rheumatoid arthritis (RA) patients varies among different ethnic groups (or geographic regions) in China. DRB1*10 and DRB4*01 may be susceptibility genes for Zhuang RA patients. HLA-DRA acts as the sole alpha chain for DRB1, DRB3, DRB4 and DRB5 and plays a central role in the immune system and response by presenting peptides derived from extracellular proteins, particularly pathogen-derived peptides of T cells. Therefore, TK’s RA susceptibility may induce positive selection. Meanwhile, we also focused on the selection signals associated with the pathogenesis of diabetes, JAZF1 and KCNQ1. JAZF1 acts as a transcriptional corepressor of orphan nuclear receptor NR2C2 and plays a role in glucose homeostasis by improving glucose metabolism and insulin sensitivity [KCNQ1 is associated with type 2 diabetes (T2D) [The association of sitivity . KCNQ1 ies (T2D) .Furthermore, we performed functional annotation and enrichment analysis for 329, 562 and 926 candidate genes screened based on Fst, XPEHH and iHS, respectively. The overlap between the three sets containing these genes and the pathways enriched to them was visualized  to strengthen the dynasty’s rule and capture the Baiyue region [The ancestral composition of Guizhou TK populations inferred from the two-way or three-way admixture models suggested that the primary ancestry of TK people derived from Yellow River millet farmers in northern East Asia and AN-speaking Taiwan indigenous people associated with ancient rice farmers. The fitted models indicated that the gene flow from ancient millet farmers in the Yellow River valley and rice farmers from the Yangtze River valley contributed to the formation of Guizhou TK populations. We found that the genetic diversity of CJD resulted from the genetic admixture of ancient and modern populations in southern and northern East Asia based on the admixture e region . Recent e region , 27, 41.e region . ALDER-bf3 and identified the geographically close HM, modern and ancient northern East Asians contributed these mixed signals, especially with the Hans. This was consistent with the genetic patterns observed in PCA. In f4, the CJZ shared more alleles with Dai compared with the CJD (Table Although the newly-studied TK populations had similar composition and close genetic relationship with previously reported TK populations (Dong_Hunan) and geographically close HM populations, we observed that the proportion of ancestral composition of reported TK populations (except Dong_Hunan) was completely different from that of CJZ and CJD. ADMIXTURE results showed that the TK-related component in reported TK was higher than that in CJZ and CJD. Previous studies have also revealed the genetic differentiation among TK populations from different regions, such as the Hainan island TK people and Chinese mainland TK people , 42, 43.JD Table . InteresHLA-DR alleles strongly associated with Chinese RA patients are HLA-DRB1*0405, 0401, 0404, 0410, etc. [HLA-DR genes with RA patients varied by ethnicity (or geography) [HLA-DR (DRB1*10 and DRB4*01) has been shown to be a susceptibility gene for the development of RA in the TK population [HLA-DRA genes play an essential role in immune diseases such as RA and SLE [HLA-DRB1 haplotype and RA susceptibility in Han populations shows that the HLA-DRB1*0405 gene isassociated with RA in the Han population (P = 1.35 × 10− 6) [JAZF1 is associated with assessing reduced glomerular filtration rate and is involved in the pathogenesis of T2D by regulating lipid metabolism processes. It has been shown that JAZF1 is associated with T2D in the Chinese ST population (Han and She) [Genetic studies showed that ethnolinguistically diverse populations underwent different statuses of pathogen exposure, which may remain as different patterns of the allele frequency spectrum and extended haplotype homozygosity under natural selection processes. We explored the genome-wide candidate loci targeted by natural selections based on the reconstructed haplotype data and allele frequency differentiation. The 10, etc. . Howeverography) . The prepulation . HLA-DRA and SLE  and may × 10− 6) . Genetic× 10− 6) . Additioand She) , 51, whiand She) , Trans-Oand She)  and the and She) , have acand She) , 10K_CPGand She)  and Westand She)  have triTaken together, our work focused on the genome-wide SNP data of TK populations from Southwest China, directly demonstrating their genetic affinity with ancient people in the Yellow River and Yangtze River Basins and suggesting the complex admixture processes that contributed to the formation of Guizhou TK people. We also identified Guizhou people who shared a close genetic relationship with geographically close HM people and geographically distant AN-speaking Atayal and Paiwan people, suggesting ancient genetic common origin and recent population admixture played an important role in the observed patterns of genetic diversity of modern TK people. Additionally, unique patterns of naturally-selected signatures in TKs have identified many candidate genes associated with biological processes and pathways of the crucial immune system. In general, our findings provided direct evidence that supported an admixture model in which TK populations are a mixture of North and South East Asian populations and complex interaction with geographically close HM people and Han Chinese.We randomly collected 77 TK-speaking samples (23 Zhuangs and 54 Dongs) from Congjiang County in Guizhou Province, Southwest China. The parents and grandparents of these samples participating in this study were all indigenous people who had lived here for at least three generations and were not genetically related to each other. Genomic DNA was extracted and isolated by drawing 200ul of blood from each sample and diluting it with 30ul of genomic elution buffer using the PureLink Genomic DNA Mini Kit. Subsequently, we performed a preliminary determination of DNA concentration using a NanoDrop 2000 spectrophotometer. Second, the 7500 real-time PCR system was used to accurately quantitate DNA concentration using the Quantifiler Trio DNA Quantification Kit and the Quantifiler Human DNA Quantification Kit according to the appropriate instructions. 77 DNA samples were genotyped using the Affymetrix WeGene V1 array, which covered about 700 K SNPs. And SNPs with low-profile or batch effects were removed by quality control. We used PLINK (version v1.90)  to filteReference datasets and integration of data.We merged genome-wide SNP data from CJZ and CJD with previously reported population data from modern and ancient populations included in the AADR and publicly available genomic projects , 25, 26.We performed a PCA using the smartpca program of EIGENSOFT v.6.1.4  based on2 > 0.4 and --indep-pairwise 200 25 0.4) [We used the unsupervised model-based statistical technique to dissect the ancestral composition of CJZ and CJD populations. We performed two model-based clustering analyses using ADMIXTURE based on the merged HO and WGS datasets. We used PLINK v1.90 to prune the linked SNPs with the following parameters (r 25 0.4) . After eWe used SHAPEIT software (Segmented HAPlotype Estimation & Imputation Tool) to phase our dense SNP data with the default parameters (--burn 10 --prune 10 --main 30) . And we To explore the possible exiting phylogenetic topologies, we used TreeMix version 1.12  with migf3/f4 statistics using the qp3Pop and qpDstat programs of ADMIXTOOLS [f3 to measure the shared drift between populations X and studied TK people since their divergence from the outgroup. We used the African Mbuti as the outgroup population. And then, we performed admixture-f3 to evaluate the potential admixture signature with different ancestral source surrogates. The estimated negative Z-scores less than − 3 indicated that our targeted population was a mixed population with two ancestral sources related to source1 and source2. We computed the f4 with different reference populations to formally test whether W or X harboured more Y-related ancestry. We applied the f4-statistics in the form of f4 to estimate the genetic homogeneity and heterogeneity between studied TK populations and used f4 to evaluate whether TK people shared alleles with Dai compared with East Asian and non-East Asian populations. Finally, we calculated the f4 to test whether additional gene flow entered the studied TK populations compared to the used East Asian ancestral source proximity.We conducted a series of MIXTOOLS  with defWe used qpAdm  with theWe applied the R package of REHH  to run tTo explore the biological processes and signaling pathways in which candidate genes may be involved, we performed functional annotation and pathway enrichment analysis using the online tool Metascape . We inteBelow is the link to the electronic supplementary material.Supplementary Material 1Supplementary Material 2Supplementary Material 3Supplementary Material 4Supplementary Material 5Supplementary Material 6Supplementary Material 7Supplementary Material 8Supplementary Material 9Supplementary Material 10Supplementary Material 11Supplementary Material 12Supplementary Material 13Supplementary Material 14Supplementary Material 15Supplementary Material 16Supplementary Material 17


Sepsis cynipsea and S. neocynipsea (Diptera: Sepsidae). Based on microsatellite genotypes, we first inferred a baseline demographic history using Approximate Bayesian Computation. We then used genomic data from pooled DNA of natural and laboratory populations to test for past interspecific gene flow based on allelic configurations discordant with the inferred population tree (ABBA–BABA test with D-statistic). Comparing the detected signals of gene flow with the contemporary geographic relationship among interspecific pairs of populations , we made two contrasting observations. At one site in the French Cevennes, we detected an excess of past interspecific gene flow, while at two sites in Switzerland we observed lower signals of past microsatellite genotypes gene flow among populations in sympatry compared to allopatric populations. These results suggest that the species boundaries between these two species depend on the past and/or present eco-geographic context in Europe, which indicates that there is no uniform link between contemporary geographic proximity and past interspecific gene flow in natural populations.The extent of interspecific gene flow and its consequences for the initiation, maintenance, and breakdown of species barriers in natural systems remain poorly understood. Interspecific gene flow by hybridization may weaken adaptive divergence, but can be overcome by selection against hybrids, which may ultimately promote reinforcement. An informative step towards understanding the role of gene flow during speciation is to describe patterns of past gene flow among extant species. We investigate signals of admixture between allopatric and sympatric populations of the two closely related European dung fly species The online version contains supplementary material available at 10.1007/s11692-023-09612-5. Speciation entails the evolution of reproductive isolation (RI) among lineages derived from a common ancestral population and is considered completed if the diverged populations remain reproductively isolated even after coming into secondary contact  generally depend on decaying organic matter for reproduction and development, and have become a model for the study of sexual selection and ecological adaptation  S. cynipsea, or vice versa. Despite strong similarities in morphology and behaviour  are genetically distinct and show quantitative differences in mating system ; at other sites we only detected S. cynipsea alone . By contrast, lower levels of inferred gene flow in sympatry than allopatry could either indicate that allopatric populations share a hitherto undisclosed evolutionary history involving post-split gene flow, or, conversely, that divergent selection has reduced effective gene flow at sites of sympatry  and the French Cevennes (Le Mourier), and from one low-altitude site in Zürich  and Estonia (Pehka), where S. neocynipsea does not occur  at low altitudes in Europe (except Zürich). To increase the number of S. neocynipsea samples, we obtained two further high-altitude S. neocynipsea populations in Switzerland where S. cynipsea also occurs , assembled with Canu  from http://www.cgae.de/seto_01_genome.fasta and http://www.cgae.de/seto_01_genome_masked.fasta. Despite using a PCR-free sequencing library preparation kit, we employed PCR duplicate removal with Picard v. 1.109 (http://broadinstitute.github.io/picard/), which is part of our standard mapping pipeline, and we realigned reads around indels in each raw alignment file using RealignerTargetCreator and IndelRealigner from GATK v. 3.4–46 .The variant caller Pool-SNP , we first inferred a baseline demographic history of the two species in Europe using Approximate Bayesian Computation , Petroia , Zürich , and Sörenberg , and for S. neocynipsea the populations from Geschinen , Sörenberg (SoN), and Zürich (ZuN). For S. cynipsea we additionally included a fifth population from Geschinen (GeC). The GeC population is not represented in our whole-genome dataset, but its inclusion in the microsatellite dataset meant that our sampling design for the ABC demographic analyses was balanced in the sense that it comprised data from both species for all three Swiss sites . To establish a baseline genealogy for all these 8 European S. cynipsea and S. neocynipsea populations, we assumed a basal split of S. cynispsea and S. neocynipsea at time S. cynipsea, pairwise S. neopcynipsea populations GeN, SoN, and ZuN . Individual candidate topologies however differ by whether PhC and PtC find a common ancestor before they merge with the common ancestor of the Swiss populations. We assigned to each branch in the topology an effective population size, and to each population a split time before present. We then compared the fit of the resulting species-specific demographic scenarios  to the data using ABC model comparison . After identifying the best-fitting demographic models for each species, we combined these species-specific models into four joint demographic scenarios including both species . For S. cynipsea, scenario 1 is the only one in which PhC and PtC do not find a common ancestor before they merge with the common ancestor of the three Swiss S. neocynipsea populations . In contrast, scenarios 2 to 4 assume that PhC and PtC are more closely related to each other than to any of GeN, SoN, and ZuN. Scenarios 2 to 4 only differ in the relationships among GeN, SoN, and ZuN . We again compared the fit of these four scenarios to the data using ABC (Supplementary Text S3). For the best-fitting joint scenario we also estimated the effective population sizes and split times using ABC (Supplementary Text S3).From the 20 populations in the microsatellite dataset of Baur et al. . For S. To complement the ABBA–BABA tests for admixture described below, we included discrete pulses of bidirectional interspecific gene flow to a pruned version of the population genealogies pertaining to the demographic scenario without gene flow that best fitted the microsatellite data from Baur et al. . PruningD-statistic, a scaled difference across a set of bases between counts of ABBA and BABA configurations bounded by − 1 and + 1  and refer to the respective test statistics as DD and DS. Our script also computes jackknifed z-scores based on a matrix of allele frequencies for previously defined high-confidence SNPs (see Supplementary Text S4 for details). We adopted the commonly used significance threshold of |z| > 3  in the ABBA–BABA tests could lead to biased estimates of gene flow. We therefore mapped the three ingroup and the outgroup species against the reference genome of yet another species, u et al.  indicatemis Fig. A. We themis Fig. .DS and DD in genomic windows of 500 consecutive SNPs  and computed genome-wide statistics by averaging across all windows.We focused our analysis of interspecific sympatric sampling gene flow on the three sites Zürich, Sörenberg, and Le Mourier Table . In all S. cynipsea populations from Geschinen (GeC), Sörenberg (SoC) and Zürich (ZuC) are genetically more similar to each other than any of them is to the populations from Pehka  and Petroia , as expected from geographic distances among populations  find a common ancestor before merging with the low-altitude Zürich population (ZuC), whereas for S. neocynipsea the high-altitude Sörenberg population SoN still finds a common ancestor with the low-altitude Zürich population ZuN before this ancestral population merges with the second high-altitude population GeN  for all Swiss populations of S. cynipsea  and S. neocynipsea . Only the most northern S. cynipsea population, PhC, exhibited a markedly lower Ne of 405 , which might be explained by this population being close to the northern margin of the species’ distribution. We note that posterior means for Ne of our eight populations were 3.6 to 6.5 times higher than their respective posterior medians, and both point estimates fell substantially closer to the respective lower bounds of the 95% PCI than to the upper bounds (Table S3). These observations are consistent with an observed asymmetry of the posterior distributions for these parameters.Parameter estimates obtained with ABC under scenario 2 revealed similar effective population sizes  to 37  generations  to 283  generations ago from their common ancestors  was inferred as merely 2100 generations ago , which further emphasizes the close relatedness of these two sister species. However, as for Ne, posterior means of the split times were higher (1.2 to 1.9 times) than the respective posterior medians, and means and medians were much closer to the lower than the upper 95%-PCI bounds (Table S3). Overall, our point estimates of the demographic parameters indicate very recent species and population divergence, although credible intervals suggest that these point estimates might considerably underestimate divergence times and effective population sizes.We found splitting times among Swiss populations of S. cynipsea and S. neocynipsea populations (Table D-statistic used (DS vs. DD). We first conducted tests involving two (sympatric) S. neocynipsea populations from the Swiss Alps  and P3 . We observed a significant deficiency of ABBA patterns in all configurations , whereas for S. neocynipsea we only used a pool of flies from an isofemale laboratory line (Table D statistic (DS vs. DD) and the P1 ingroup , but higher for the Zürich populations . In summary, the majority of our ABC inference analyses with gene flow supported our findings based on the ABBA–BABA tests in suggesting lower levels of interspecific gene flow in sympatry than allopatry. The ABC analyses further suggested that the sympatric interspecific pair of Sörenberg populations split about eight times more recently than the sympatric interspecific pair of Zürich populations .Complementary to the ABBA−BABA analyses, we conducted ABC and coalescent simulations with and without gene-flow in sympatry and allopatry for the two Swiss sites Sörenberg and Zürich following the best fitting scenario 2. Consistent with the ABBA−BABA results, these analyses identified scenario 2B with reduced local gene flow  as best-fitting for Sörenberg  and Zürich  when using PhC as the P1 ingroup. When using PtC as the P1 ingroup, scenario 2B was still best fitting for Sörenberg , whereas for Zürich scenario 2C without gene flow fitted best . However, the posterior probability of scenario 2B was only slightly lower . We further found that the estimated time S. cynipsea and S. neocynipsea populations from Le Mourier in the southern French Cevennes mountains (790 m), ca. 450 km southwest of the Sörenberg and Zürich sampling sites in Switzerland. Surprisingly, we found opposite patterns to those observed at the Swiss sites. All tests based on DS showed a highly significant excess of ABBA patterns, hence more interspecific gene flow in sympatry than allopatry  occurs. As discussed in detail below, depending on the focal sympatric site, we found two qualitatively opposite patterns of interspecific gene exchange in sympatry versus allopatry: a relative reduction in genetic admixture in sympatry at two sampling sites in Switzerland, but also a relative excess of admixture in sympatry at a sampling site in Southern France.Previous population genetic analyses of microsatellite markers , respectively. In contrast, less gene flow in sympatry than allopatry was observed in studies of Drosophila arizonae/mojavensis . Such a scenario could in principle explain the contrasting patterns of interspecific gene flow we observed at our sites of contemporary sympatry in the French Cevennes and Switzerland. Future demographic analyses of Heliconius butterflies  gene flow between these two dung fly sister species in sympatry varies with local environmental or selective conditions.Similar to research in Well-documented differences in climate between Southern France and the Swiss Alps, and also between alpine and sub-alpine Swiss sites, could provide ecological explanations for the qualitative and quantitative differences in interspecific gene flow observed at the various locations  in the southernmost part of a contact zone in northern Italy compared to the northern parts of the zone. The authors showed that a suite of sexual traits that evolved recently in the southern part of the zone and that affects male-male competition is likely causing this difference. Meleshko et al. (Sphagnum) was partially explained by variation in habitat quality . Even though we do not currently know what factors drive geographic variation in secondary-contact gene flow in our system, these examples suggest multiple potential reasons for variation in sympatric gene exchange between S. cynipsea and S. neocynipsea. Future research in this system should focus on identifying the causal factors.We are not aware of many studies reporting empirical evidence for geographic variation in the extent of intraspecific gene flow in sympatry between two taxa in secondary contact. However, Riemsdijk et al.  recentlyg et al.  found loo et al.  found thS. cynipsea and S. neocynipsea populations relied on the ABBA–BABA test, which was initially designed for the analysis of haploid genotypes of one individual from each of four lineages . This implementation allows restricting the ABBA–BABA test to high-confidence SNPs that pass a set of user-defined filters. Such filtering can reduce artefacts of pool-sequencing  was very close to the significance threshold of |z| = 3. We also found that variances of DD estimated by jackknifing were up to one order of magnitude larger than those of DS ecological niches, such as different breeding times or phenologies, and/or where some pre- or postmating reproductive barriers might have evolved Supplementary material 2 (PDF 64.6 kb)Supplementary material 3 (ZIP 10.1 kb)Supplementary material 4 (DOCX 427.2 kb)Supplementary material 5 (XLSX 31.1 kb)Below is the link to the electronic supplementary material.


Babesia gibsoni is a tick-borne apicomplexan protozoan causing canine babesiosis. This parasite has diploid sexual reproduction in ticks, during which genetic exchanges can occur leading to increased genetic diversity, which is an important factor in adapting to environmental changes. Exploring the genetic variation of B. gibsoni population can provide a foundation for understanding the patterns of disease transmission and developing babesiosis control strategies. Partial 18S rRNA fragment sequences were obtained from 11 B. gibsoni isolates collected from different regions in China and 117 publicly available sequences were from 12 geographical areas including China. The genetic variation, demographic expansion and population structure were examined. A total of 34 haplotypes were identified among B. gibsoni populations. Analysis of molecular variance, pairwise Fst and structure analysis showed that high genetic variation within populations, low genetic differentiation and obvious mixture haplotype were apparent in a single continent, but higher genetic differentiation was detected across different continents. Neutrality tests implied that B. gibsoni populations had experienced population extension. These findings will contribute to understand the genetics and evolution of B. gibsoni and will be useful for formulating effective management strategies to prevent and control this parasite. Babesia gibsoni, one of tick-borne intracellular hemoprotozoan parasites, is considered to be an important pathogen responsible for wild and domestic canine babesiosis. This parasite is transmitted mainly by Haemaphysalis longicornis and Rhipicephalus sanguineus, but other sources of transmission to dogs have been demonstrated including dog fighting, blood transfusion and transplacental transmission  gene. These findings will help to understand the distribution and dynamics of genetic difference among B. gibsoni populations, which is necessary for designing effective control strategies to manage and prevent this parasite.The present study aimed to explain the genetic differentiation, population dynamics and population structure of A total of 197 blood samples were collected from dogs in pet clinics from five cities, including Chongqing, Linyi, Quanzhou, Wuhan and Xiangyang, as seen in Babesia spp. was detected by a nested polymerase chain reaction (PCR). A region of the 18S rRNA gene fragment 1,379 bp in length was amplified using Piro1-S: 5′-CTTGACGGTAGGGTATTGGC-3′, Piro3-AS: 5′-CCTTCCTTTAAGTGATAAGGTTCAC-3′ and then a small fragment 405 bp in length was amplified using Piro-A: 5′-ATTACCCAATMCBGACACVGKG-3′ and Piro-B: 5′-TTAAATACGAATGCCCCCAAC-3′ in the second round of PCR , 0.1 μM of primer pair and 2 μl of DNA template. The PCR reaction conditions were initial denaturation at 95°C for 3 min, followed by 35 cycles of denaturation at 95°C for 30 s, annealing at 55°C for 30 s and extension at 72°C for 90 s, with a final extension of 72°C for 5 min. Positive products were cloned into pMD19-T vector  and transformed into Escherichia coli Trans5α competent cells . The positive clones were then sequenced by M13-F/M13-R primers . DNA isolated from blood of a dog infected with B. gibsoni and distilled water were used as positive and negative control, respectively.The presence of DNA from d of PCR . Brieflyhttps://blast.ncbi.nlm.nih.gov) and deposited in GenBank under the accession numbers OM392053-OM392060 and ON810382-ON810384.The 18S rRNA sequences were analyzed using the NCBI BLASTn program . Tajima's D  was analyzed to assess the genetic variation within and among quin 3.5 . For thiK (K = 1–10) was run with 10 iterations based on the Bayesian Markov Chain Monte Carlo approach. The optimal number of clusters (K) were inferred by ΔK using the online program Structure Harvester  by BLAST. The two sick dogs were identified as B. gibsoni positive. In total, 11 partial 18S rRNA sequences of B. gibsoni were used for the following analysis.The results indicated that the positive rate of B. gibsoni isolates from 12 areas, as seen in B. gibsoni populations from Asian countries, the haplotype diversity and nucleotide diversity ranged from 0.000 to 0.667 and from 0.0000 to 0.0035, respectively, as shown in Among the 409 aligned nucleotide sites, 32 variable sites were detected. Of 34 distinct haplotypes identified in 128 individuals, 31 were private haplotypes, as seen in D and Fu's Fs values were significantly negative for China and Japan, indicating a recent population expansion. When Asian populations were considered as a single group, the Tajima's D and Fu's Fs values were also significantly negative, revealing that the population had experienced recent expansion, as seen in D and Fu's Fs analyses with statistically significant negative values and a star-like haplotype network, as seen in Tajima's Fst values ranging from 0.000 to 0.0585 and Nst values ranging from 0.000 to 0.0578, as shown in Fst values ranging from 0.0403 to 0.0585 and Nst values from 0.0405 to 0.0578, as seen in Fst and Nst values were also conducted between samples from Asia and those from America and Europe. The comparison results revealed that the highest differentiation was observed between America and Europe with an Fst value of 0.1765 and an Nst value of 0.1768, whereas the lowest differentiation was obtained between America and Asia with an Fst value of 0.0131 and an Nst value of 0.0130, as seen in The Asian population differentiation is described in FCT and FSC values with no statistical significance, as shown in The AMOVA indicated that most genetic variation occurred within populations, when either Asian countries or the three continents were treated as a single group, as shown in B. gibsoni populations from Asia, America and Europe (data not shown). Bayesian clustering analysis indicated that there were three distinct clusters . These findings suggested a low genetic sub-structuring among B. gibsoni populations. Overall, these results were supported by the pairwise Fst analysis and AMOVA, with low genetic differentiation among populations.Structure analysis showed that obvious mixture haplotypes were observed, indicating a weak population structure among populations in Asia, as seen in s K = 3, , suggest in Asia . The ManB. gibsoni populations. These results were much lower than that of H. canis , three subgroups were found in Asia that could be supported by Bayesian (K = 3) and DAPC analyses. The obvious mixture of haplotypes indicated that the separation among these populations was incomplete and similar findings have been reported in P. vivax and T. annulata (B. gibsoni spread is influenced by human activities or the migration of birds will be essential. Collectively, there are many important factors such as transmission intensity, parasite-host coevolution, geographic and ecological segregation and selective pressure, which can promote the formation of the complex and unique of genetic structure and epidemic patterns among B. gibsoni populations.Although no correlation between genetic and geographical distances among annulata , 66. In annulata . Ticks aannulata . TherefoB. gibsoni was systematically analyzed. These results revealed that low genetic differentiation, high gene flow and high genetic variation within populations were observed among B. gibsoni populations from a single continent, but higher genetic differentiation was detected among those across different continents. Neutrality tests indicated that these populations had experienced demographic expansion. These findings will contribute to a comprehensive understanding of genetic diversity of B. gibsoni and its complex population structure and provide a reference for developing better control strategies for the public health diseases.In this study, the genetic diversity of The data presented in the study are deposited in the GenBank repository, accession number OM392053-OM392060 and ON810382-ON810384.This study was approved by the Institutional Animal Care and Use Committee of Southwest University. All pet dogs were handled in accordance with the Animal Ethics Procedures and Guidelines of the People's Republic of China. Written informed consent was obtained from the owners for the participation of their animals in this study.FY, HY, and FL conceived the project. DL collected blood samples. FY, CG, ZT, DM, and HL carried out laboratory work. FY performed the data analyses and prepared the manuscript with the support from GG and FL. All authors read and approved the final version of the manuscript.