Euphorbia fulgens is an ornamental species cultivated in Europe and endemic to Mexico; its ecological, genetic, and evolutionary aspects are not known. The objectives of this study were to determine its distribution, describe the places it inhabits, and analyze the diversity and genetic structures of wild populations of E. fulgens. A bibliographic review of the herbarium specimens and a field evaluation were carried out to develop a potential distribution map based on a multi-criteria analysis of the climatic and topographic variables. Three populations  from pine–oak and cloud forests located in the Southern Sierra of Oaxaca were analyzed using ten microsatellite loci. The analysis was conducted using Arlequin v. 3.5, Mega v. 10, and Structure v. 2.3 programs. Eight loci were polymorphic, and a total of thirty-eight alleles were obtained. The average number of alleles per polymorphic locus was 4.6. The average heterozygosity of the three populations was high (Ho = 0.5483), and genetic differentiation between populations were low, with a high genetic flow, suggesting that it could be an ancestral population that became fragmented and was just beginning to differentiate genetically. The information generated on this restricted distribution species can be used in conservation programs pertaining to human activities that endanger the habitats where it is found. Euphorbia is a diverse genus with 245 species, of which, 132 are endemic [Euphorbia fulgens Karw. ex Klotzsch belongs to the subgenus Chamaesyce sect. Alectoroctonum [The family Euphorbiaceae is represented by 8000 to 9000 species ,2, makin endemic . There aroctonum .Euphorbia fulgens is found in three localities in the state of Oaxaca; it is collected from wild populations and is used for religious purposes. In other countries, ornamental cultivated varieties are sold mainly as cut flowers and potted plants. It is a phytogenetic resource that can be sustainably exploited in Mexico. Since it has aesthetic values and adapts easily to cultivation conditions, recently, differences in morphological vegetative and reproductive structures were found in wild and cultivated populations [ulations .However, it has been studied very little and the ecological, evolutionary, diversity, and genetic structural aspects that provide information on its endemism are unknown. Studies on the genetic diversities and structures using microsatellites help estimate the genetic variations in wild populations, especially in species of restricted and endemic distributions. Knowing whether populations are genetically differentiated at different levels makes it possible to identify the environmental factors that affect them. Estimating the genetic flow between populations, in turn, helps to determine the levels of inbreeding or exogamy, which is convenient for the management and conservation of plant genetic resources ,10,11.Euphorbia; abundant genetic variations in wild populations of Euphorbia pulcherrima in several localities have been found in Mexico via plastid  and nuclear (G3pdh) regions [Euphorbia kansui, endemic to this country, was molecularly characterized using 12 microsatellites. The number of alleles ranged from 2 to 11, with an average of 4.1 alleles per locus [Euphorbia palustris, a species endemic to Europe, seven microsatellites were used to study the genetic structures and gene flow among its populations; between 3 and 13 alleles per locus were found, as well as high levels of heterozygosity [Euphorbia lamarckii, a species endemic to the Canary Islands, was molecularly characterized, using 10 microsatellite loci, between 2 and 13 alleles per locus were found [There are few studies on the genetic diversity of the genus  regions . In Chiner locus . In a stzygosity . Additiore found .Guaiacum unijugum, it was found that genetic differentiations among them were reduced and attributed to the presence of rare and unique alleles [Paeonia jishanensis, endemic to China, genetic diversity and population structures were assessed using 21 microsatellite loci, and moderate levels of genetic diversity were detected [Petunia secreta, a rare species endemic to Brazil, 15 microsatellite loci found high genetic diversity among them [Sophora alopecuroides, a species endemic to China, 18 microsatellite loci allowed researchers to estimate a low genetic diversity based on the number of effective alleles; such genetic variabilities were higher within populations than among them [Molecular studies using microsatellites in plant species belonging to other families with restricted distributions were useful to evaluate the genetic differentiation between populations. Thus, using ten microsatellites in populations of  alleles . In Paeodetected . In the ong them . The stuong them .Euphorbia, with species that are endemic to Mexico. The objectives were to define the geographic distribution, describe the habitat, and determine the genetic diversity and structure of wild populations of Euphorbia fulgens, which are so far unknown. It will provide valuable information for the management and preservation of this species. Considering that this species presents a restricted distribution and is endemic to Mexico, it must have low genetic diversity and genetic flow.Therefore, the present study is the first of its kind for the genus Euphorbia fulgens is only distributed in the State of Oaxaca. So far, only three populations have been documented: (a) in the municipality of San Jerónimo Coatlán; (b) on the borders of the municipalities of Santiago Jamiltepec and Santiago Tetepec, 80 km in a straight line from (a); and (c) in the municipality of Santa Catarina Juquila, 50 km from (b), so this species is considered endemic to Sierra Sur de Oaxaca.The populations are in canyons with steep slopes that are difficult to access; in areas with pine–oak forests (POFs); a combination of pine–oak forests and cloud forests (POF-CFs); cloud forests (CFs), and the secondary vegetation derived from the above. Population 1 is located at 1421 m in a POF; population 2 is located at 1160 m in a POF-CF and CF zone; population 3 is located at 1130 m in a CF and the secondary vegetation derived from it .Population 1 is located in places that are difficult to access, with steep slopes that are far from human populations, so there is little disturbance . Population 2 is located on steep slopes, with habitat alterations due to agricultural and cattle-ranching activities. Finally, population 3 is in conserved areas with secondary vegetation derived from CFs. In the latter case, there are disturbances due to the proximity of human settlements, so the survival of this species is at risk.The analysis of climatic variables (temperature and precipitation), topographic variables , and vegetation type at the collection points showed that the species is distributed within the ranges of precipitation, temperature, slope, altitude, and vegetation type indicated in −1, and a bulk densities (BD) of 1.0 g cm−3. The soil of population 1 contained 53.3% sand, 29.3% silt, and 17.2% clay. The soil of population 2 presented 55.5% sand, 31.3% silt, and 13.2% clay, while the soil of population 3 contained 65.9% sand, 16.0% silt, and 18.1% clay. The soil of population 1 had the lowest organic matter content (4.48%). The soil of population 2 had higher Ca (910 mg kg−1), Mg (227 mg kg−1), Fe (110 mg kg−1), Zn (1.28 mg kg−1), and Mn (14.56 mg kg−1) contents compared to the other populations . The analysis at the intra-population level indicated that in the eight loci, the average observed heterozygosity in population 1 was 0.6468, in population 2, it was 0.5835, and in population 3, it was 0.4148. Population 1 showed higher genetic diversity by observed heterozygosity and the number of observed genotypes (Go = 114) compared to populations 2 and 3 , Ep05 , E97, Ep61 , and the rest with 3 alleles. The average number of alleles per polymorphic locus was 4.6, so allelic diversity was relatively low to moderate. Total heterozygosity (HT) for the three analyzed populations of  2 and 3 , indicatThe overall molecular analysis of variance (AMOVA) using the eight amplified loci showed that the most significant proportion of molecular variability was located among individuals (93.84%) and not among populations (5.58%). Wright’s F-statistics for measuring genetic structure showed low values of genetic differentiation between populations (FST = 0.05587) and low levels of total inbreeding in the three populations (FIS = 0.00602 and FIT = 0.06156). Although there were missing data when we used all eight loci, AMOVA was performed with the three most representative loci . The results indicate that 5.57% of the genetic variations are between populations, 6.55% are in individuals within populations, and 87.88% are within individuals of the three populations . Wright’t-tests indicates that population 1 differs from populations 2 and 3. However, the latter does not differ  . The expEuphorbia fulgens (HT = 0.5483) indicated a high genetic diversity despite its endemic and restricted distributions. Population 1 had the highest genetic diversity and was separated from populations 2 and 3. However, this difference was not significant according to the Bayesian analysis conducted with Structure software. The levels of genetic diversity in E.fulgens are similar to those obtained in E. kansui, a species endemic to China [E. lamarckii, a species endemic to the Canary Islands [E. palustris, with a peculiar distribution limited to the banks of rivers in Central Europe [Euphorbia, such as Pityopsis ruthii [Seseli farrenyi [Aristolochia delavayi [Eriocaulon bilobatum, an aquatic species with sexual and asexual reproduction, monoecious, and that is pollinated by insects with isolated and scarce populations [Lilaea scilloides is widely distributed, it has shown low genetic diversity within and among the populations analyzed [The total heterozygosity for the three populations of to China , E. lama Islands , and E. l Europe . Similars ruthii , Seseli farrenyi , and Aridelavayi . Howeverulations . Althouganalyzed .E. fulgens showed that the highest proportion of molecular variability was found within individuals rather than between populations. There were low values of genetic differentiation between populations and low levels of total inbreeding in the three populations; the same occurs in endemic species, such as Paeonia decomposita, where the highest proportion of molecular variability is found within populations [Aristolochia delavayi [t-tests indicated that population 1 differed from populations 2 and 3, but the latter did not differ. The gene flow level between the three populations was high, especially between populations 2 and 3. This suggests that this is an allogamous species with pollination mainly by dipterans, tiny wasps, bugs, and ants observed in the inflorescences during fieldwork. However, no studies have documented the pollinators of E. fulgens, so it is proposed that researchers conduct studies to verify the pollination and reproduction systems of this species of Euphorbia and, thus, complement the factors that contribute to the high gene flow levels.The genetic structure analyzed for ulations . This haulations  or in spdelavayi . A pairwSeseli farrenyi, an endemic species with a minimal distribution range in the Mediterranean Basin [It should be noted that the populations are not very far from each other; the distance between populations is less than 100 km in a straight line. Populations 2 and 3 are in a cloud forest and ecotone 1 (POF-CF) inhabited areas. In contrast, population 1 inhabits a pine–oak forest and ecotone 1 (POF-CF), but at a higher altitude than the other populations and with difficult access, which also explains why it is the population with the most significant genetic variation and slight differentiation; however, the gene flow between the three populations is still being maintained. It agrees with what was obtained via the Bayesian analysis of genetic structuring using Structure software, which indicated that the analyzed populations were divided into two large genetic groups or clusters (K = 2), and that most of the individuals of population 1 were grouped in group 1 and the remaining (populations 2 and 3) in group 2. However, there is a mixed population with a slight genetic differentiation between individuals of group 2 and individuals of group 1 (without being significant). The high gene flow values suggest a lower genetic differentiation due to the entry of genes related to cross-pollination or allogamy; the same is documented in an Basin . TherefoEuphorbia fulgens was obtained from the databases of national and international open access collections available on the internet January 2018: Global Biodiversity Information Facility , Red Mundial de Información Sobre Biodiversidad (REMIB) , the open data website of the Universidad Nacional Autónoma de México (UNAM) , and the Tropicos database of the Missouri Botanical Garden . In addition, information was collected from herbarium specimens deposited in the most important collections in Mexico . A database was constructed containing the state, municipality, locality, latitude, longitude, type of vegetation, altitude, collector number, collector, name of the identifier, and herbarium of where it was located, with the records of the herbarium specimens. Additionally, specialists in the family Euphorbiaceae were consulted on the geographic distribution of the species in Mexico.The geographic distribution information of −1), percentage of organic matter, inorganic nitrogen (mg kg−1), phosphorus (mg kg−1), potassium (mg kg−1), calcium (mg kg−1), magnesium (mg kg−1), iron (mg kg−1), copper (mg kg−1), zinc (mg kg−1), manganese (mg kg−1), boron (mg kg−1), bulk density (g cm−3), and texture .Data on altitude, vegetation type, and geographic coordinates were taken between December 2018 and January 2019 at the collection sites. In addition, in order to have physical and chemical characterizations of the soil, three samples of one kilogram were taken at a depth of 20 cm and analyzed to obtain the pH, electrical conductivity , terrain slope, altitude, and vegetation type obtained from the UNAM database and the Instituto Nacional de Estadística y Geografía  Table 9Table 9.® bags and transported under refrigerated conditions to the laboratory for analysis. DNA was extracted using the CTAB methodology [−1) were determined using a Thermo Scientific®  brand Nanodrop Lite, for which all samples were diluted to 10 ng/µL−1. DNA quality was evaluated by 2% agarose gel electrophoresis at 120 volts for one and a half hours, which was subsequently stained with ethidium bromide and documented with low-cost image acquisition and documentation of gels, Digidoc-lt®  Imaging System.Molecular characterization was performed on 45 individuals from 3 populations. Youngs, healthy leaves were collected and packaged in Ziplochodology  with somEuphorbia fulgens, in the present study, ten microsatellite molecular markers used in other species of the same genus, E. kansui, endemic to China [E. lamarckii, endemic to the Canary Islands [E. palustris, native to Europe [®, Meridian Life Science Inc. USA), 0.5 µL of forwarding primer (T4Oligo®), 0.5 µL of reverse primer (T4Oligo®), 0.15 µL of Taq polymerase (Bioline® 500 U), and 2.00 µL of DNA. Amplification was performed with Techne Flexigene®  thermal cyclers with the following PCR sequence: 1 pre-denaturation cycle at 94 °C for 5 min, 35 denaturation cycles at 94 °C for 30 s, 1 alignment cycle of 30 s at the optimal recommended temperature for each primer pair, 35 extension cycles at 72 °C for 30 s, and 1 final extension cycle at 72 °C for 5 min. The amplified fragments were separated by electrophoresis at 110 volts for 40 min on 3.5% MetaPhor®-Nusieve®  agarose gels and 1X TBE buffer. Gels were developed using a Red SafeTM  staining solution; the gels were documented with a Labnet®  ultraviolet light transilluminator.Since there were no previous molecular characterization studies of to China , E. lama Islands , and E. o Europe , were usThe following statistical tests were performed from the banding patterns: Hardy–Weinberg, analysis of molecular variance (AMOVA), average Wright’s F-statistics, and an exact test of the population differentiation for the population pairs. From these tests, and using Arlequin v. 3.5 , statistOn the other hand, estimates of the most probable numbers of populations (K) were obtained using the Structure program, version 2.3 . The proEuphorbia fulgens has a distribution restricted to a single state; three geographically separated populations were located, making it endemic to the Sierra Sur region of Oaxaca. Genetic diversity was high without significant genetic differentiation, and the molecular genetic structure revealed that there are only two genetic populations instead of the three that had been defined a priori based on their geographic locations; these populations maintain a high level of gene flow and prevent genetic divergence. Genetic differentiation between populations 2 and 3 is very low; both likely came from population 1, which is fragmented and just beginning to differentiate genetically. This study provides information that can be used in conservation programs due to the risk of extinction related to habitat fragmentation and shows the need for further ecological–evolutionary studies, to determine the pollination systems of these plants, to know their pollinators, and elucidate their evolutionary history to explain their endemism.


Boechera fecunda (Brassicaceae), a rare, self‐compatible perennial plant endemic to Montana, USA, and use integral projection models to estimate the stochastic population growth rate (λS) and extinction risk of each population. We then combine these demographic estimates with previously published metrics of genetic variation in the same populations to test whether genetic diversity within populations is linked to demographic performance. Our results show that in this predominantly inbred species, standing genetic variation and demography are weakly positively correlated. However, the inbreeding coefficient was not strongly correlated with demographic performance, suggesting that more inbred populations are not necessarily less viable or at higher extinction risk than less inbred populations. A contemporary re‐census of these populations revealed that neither genetic nor demographic parameters were consistently strong predictors of current population density, although populations showing lower probabilities of extinction in demographic models had larger population sizes at present. In the absence of evidence for inbreeding depression decreasing population viability in this species, we recommend conservation of distinct, potentially locally adapted populations of B. fecunda rather than alternatives such as translocations or reintroductions.Quantifying relationships between genetic variation and population viability is important from both basic biological and applied conservation perspectives, yet few populations have been monitored with both long‐term demographic and population genetics approaches. To empirically test whether and how genetic variation and population dynamics are related, we present one such paired approach. First, we use eight years of historical demographic data from five populations of  The comDespite the many plausible biological links between genetic variation and population viability, most studies assessing the fitness effects of genetic variation and ID assess fitness components  rather than integrated metrics  , a rare and threatened species endemic to southwestern Montana, USA . In undisturbed communities, competition between B. fecunda and heterospecific neighbors appears to be weak , and it is unlikely that there are undetected populations nearby. This disjunct distribution, combined with the species' predominantly self‐pollinating reproductive mode  and gravity‐dispersed seeds, makes it unlikely that these populations are connected by dispersal or gene flow.We focused on five of the 21 known s Figure . Most poIn 1990, transects were established spanning each of the five focal populations, and 1 m × 1 m quadrats were laid along each transect. The five focal populations were selected because they span the majority of the elevational range of the species, and also because they captured apparent variation in population size and vigor at the outset of the study Walsh, . Because2.3In this species, most plants progress through the life cycle as follows: (1) seeds germinate and establish as a vegetative basal rosette, (2) vegetative rosettes may or may not bolt, i.e., produce a flowering stalk, (3) flowering stalks may produce fruits, which bear seeds and start the life cycle again Figure A. BoltinB. fecunda individuals may produce a bolting stalk from the terminal bud at the center of the rosette  iteroparous reproduction, we used integral projection models (IPMs) to model population dynamics. In an IPM framework, vital rates of growth, survival, fecundity, and recruitment are treated as functions of a continuous size variable  and potential changes in vital rate functions across states. In general, we constructed a multimatrix structure  to give good statistical power to estimate vital rates even after partitioning the full dataset into population‐specific subsets. Second, with only five populations, it is a somewhat arbitrary decision whether a population effect in a larger model should be treated as a fixed or a random effect if included in a model. Third, inclusion of population as an effect (either fixed or random) in vital rate models raises the possibility that population‐by‐year, population‐by‐size, and higher order interactions may also be relevant to include; however, interpretation of such effects can be difficult, and can result in spurious overfitting of vital rate models. Fourth, because we were predominantly interested in looking at continuous patterns in demographic trends across populations, not, e.g., comparing means across categories, there was no need to test the “significance” of population on vital rates or demographic outcomes. Finally, fitting vital rate regressions separately allows for the estimation of the shapes of size‐based relationships to vary independently across populations, free from any assumptions constraining parameter estimation in a larger model.We fit vital rate models and performed model selection separately for each of the five censused populations, allowing the shapes of the functions and the parameters retained in best‐fit models to differ across populations. We chose to model populations separately rather than, e.g., including population as an effect in one larger model, for several reasons. First, sample size was sufficient , Because dormant individuals have no aboveground tissue Figure C, they aSimilarly, 10% of individuals  were bolters in at least one census year. To avoid overestimation of shrinkage to 0 or small sizes in our growth models, we treated bolters as a separate discrete state. We identified bolters in the dataset based on the criteria that survival was scored as 1 and rosette diameter was scored as 0 or NA.In this long‐term dataset, we found that bolters may become dormant aboveground and dormant plants may become bolters. As such, in addition to fitting separate vital rate regressions for each state, we modeled the probability of transitioning between bolter, dormant, and “normal” states, making these transitions size‐dependent if warranted  and to project population sizes. Specifically, we built one multimatrix for each intercensus interval, adding annual deviations to the overall model intercept by sampling from the Normal distribution of the random year coefficient, incorporating parameter uncertainty in the random effect variance  of each of the 5 censused populations. For each bootstrap sample of the vital rate regression coefficients, we calculated the set of seven annual multimatrix projection kernels as described above. Beginning with population vector representing a uniform size distribution  to 2019. For projections, we scaled the starting size vector  We calculated the mean of the predicted population size in 2019 (Pred[N2019]) as the grand mean of the 5000 bootstrapped mean population size predictions. Similarly, we calculated the mean probability of local extinction (Prext) from the 5000 bootstrapped estimates of the proportion of population trajectories ending in extinction. We calculated 95% confidence intervals for both of these metrics from the distributions of bootstrapped values.In addition to e vector ppendix AAppendix . Across 2.52.5.1Boechera fecunda is closely related to other model organisms in the family Brassicaceae, including Arabidopsis thaliana and Boechera stricta; as such, it is amenable to study using molecular genetic techniques , were estimated from these data (Table pers. comm.). Many of these genetic metrics capture similar information, and, as such, are highly correlated across populations , na , ne , Hs (gene diversity) and Rs  , which is influenced by inbreeding and/or population structure  on the natural log scale and Pe, HO, and FIS on the logit scale. We adjusted all values of Pred(N2019) and Pe with a small constant to avoid dropping 0 and 1 values, respectively, during transformation. After transformation, we tested for linear correlations between demographic parameters and both genetic parameters by calculating the Pearson correlation coefficients.We combined the two focal genetic parameters with the outcomes of our demographic analyses described above to test whether population genetic characteristics predict population performance. Because several of these metrics are bounded by 0 and/or 1, we transformed estimates to test correlations on a linear scale. Specifically, we transformed B. fecunda range, with two main population groups, East and West, showing divergent evolutionary histories ) and genetic  predictors, after transforming density measurements on the natural log scale.In September 2019, at the end of the growing season, we revisited all five focal populations to estimate contemporary population persistence, size, and density. Markers of original transect, quadrat, and individual plant locations were not maintained in the intervening 22 years, so we used a handheld GPS to locate the coordinates marking the approximate center of the historical census sites. We searched in a ~150 m radius of each central point for any 2 quadrats utilized at that site. Then, to obtain the average historical density for each population, we took the mean value of these 8 annual density estimates. We also converted demographic predictions into density estimates by dividing mean Pred(N2019) and the 50th, 2.5th, and 97.5th quantiles of Pred(N2019) by the number of quadrats utilized at each site to obtain the mean, median, and 95% CI of population density predicted by the demographic simulations.Finally, to more straightforwardly compare the data from the contemporary recensus to historical data and predicted outcomes, we converted the latter from population size to density. First, using the historical data, we divided the census size of each population in each year by the number of 1 m2.7We performed all data processing, analysis, demographic modeling, and data visualization using R v. 4.0.2 ; more genetically diverse populations had higher long‐term growth rates and greater predicted contemporary population sizes  although the maximum sample size of 5 populations in these regressions limits statistical power.When considering populations across both genetic groups  and consistently far from statistical significance  in all populations  and demographic performance in this species .We leveraged both long‐term historical demographic data and population genetic parameters to explicitly test for relationships between genetic variation and demography in s Figure , left. Ws Figure , althougs Figure . This fis Figure , althougFIS) most directly quantifies the level of inbreeding within these populations, and thus is most relevant to the question of how ID might affect population dynamics. While other population genetics statistics describe directly the observed levels of genetic variation in the population, FIS describes the deficit of heterozygosity relative to Hardy–Weinberg expectations that inbreeding and/or population structure cause . Even when many years of demographic data are available, population projections must inherently make predictions about population growth from a limited set of observed environmental conditions. Limited sampling of environments is particularly problematic if populations experience nonlinear changes in vital rates at environmental extremes that may not be encountered during a demographic study, even one of moderate duration. This type of pattern essentially causes the shape of vital rate functions to “change” over time even in the absence of evolutionary change, since the ability to detect linear vs. nonlinear effects of environmental drivers on demography depends upon the range of environments sampled; relationships may seem linear under one range of environmental conditions, but nonlinear under a broader range.B. fecunda fitness , it would be expected to increase as populations decline in size, buffering against further decline. Population densities were quite high in some populations during the census period Figure , suggest Lesica, , this me4.3per se, and caution against the interpretation of it as such in absence of data on genetic variation underlying adaptive traits.Neither observed heterozygosity nor the inbreeding coefficient was significantly correlated with contemporary population densities Figure , althougB. fecunda , environment , and evolutionary history  interact to inform and complicate relationships between genetics and population performance. Thus, in applying these results to the conservation of other species, we emphasize that, while biological links between genetic variation and demographic performance indeed exist, the magnitude and direction of those relationships, and their stability over time, are not always straightforward to predict. Thus, we recommend the collection of empirical data capturing both demographic trends and genetic variation in rare populations whenever feasible.4.5B. fecunda populations, as changes in genetic variation over time may be better predictors of demographic trends than fixed estimates  may remain fairly constant over time  when the sample size is 5 . Despite this limited power, some tested relationships still showed significant or marginally significant correlations  of statistical significance at |r| > 0.9 when the of statiFinally, because we relied on previously published population genetic summary statistics, we could not account for the effect of uncertainty in estimates of genetic variation, which may reduce the power to detect relationships between genetic variation and demographic trends  are agnostic to Hardy–Weinberg assumptions. For B. fecunda specifically, the recent assembly and annotation of reference genomes for both East and West genetic groups (Zhang et al., New analytical frameworks that explicitly account for genetic variation when modeling demography may broaden the ways in which such relationships can be quantified and prompt further integration of these subfields (de Vries & Caswell, Finally, in addition to caveats such as changing environments discussed above, one factor that may frequently dampen the predictive power of demographic models is evolution in the focal populations over time. Over time, as genetic variation and/or traits that contribute to adaptation change, they may cause subsequent changes to population dynamics. For example, extinction risk in some populations may be buffered by the process of adaptation (i.e., experience evolutionary rescue; Bell, The authors declare no competing interests.This research was executed in consultation with the Montana Natural Heritage Program, and the data and results described in this manuscript were shared with program botanists to facilitate monitoring and management of the focal species. Benefits from this research also accrue from the sharing of our data and results on public databases, as described above.Appendix S1Click here for additional data file.


FST values showed moderate genetic differentiation between wild yak, Geermu yak, and the other Qinghai yak breeds/populations. Positive selection signals were detected in candidate genes associated with disease resistance , heat stress , pigmentation , vision , milk quality (OPLAH and GRINA), neurodevelopment , and meat quality (ZRANB1), using the integrated PI, composite likelihood ratio (CLR), and FST methods. These findings offer new insights into the genetic mechanisms underlying target traits in yak and provide important information for understanding the genomic characteristics of yak breeds/populations in Qinghai.The Qinghai Province of China is located in the northeast region of the Qinghai–Tibetan Plateau (QTP) and carries abundant yak genetic resources. Previous investigations of archaeological records, mitochondrial DNA, and Y chromosomal markers have suggested that Qinghai was the major center of yak domestication. In the present study, we examined the genomic diversity, differentiation, and selection signatures of 113 Qinghai yak, including 42 newly sequenced Qinghai yak and 71 publicly available individuals, from nine yak breeds/populations  using high-depth whole-genome resequencing data. We observed that most of Qinghai yak breeds/populations have abundant genomic diversity based on four genomic parameters . Population genetic structure analysis showed that Qinghai yak have two lineages with two ancestral origins and that nine yak breeds/populations are clustered into three distinct groups of wild yak, Geermu yak, and seven other domestic yak breeds/populations.  Bos grunniens) is descended from wild yak (Bos mutus)  of the Qinghai–Tibetan Plateau (QTP) and nearby high-altitude regions . Domestis mutus)  and is as mutus) . The Qins mutus) . Due to s mutus) .According to our previous reports on genetic variations in Y-chromosomal markers, both wild and domestic yak in Qinghai have relatively high paternal genetic diversity with weak phylogeographic structures and two paternal origins . In addiIt is essential to thoroughly ascertain the genomic diversity, population structure, and selection signature of Qinghai yak breeds/populations to increase their potential breeding value. In this study, we performed high-depth WGS analysis of 113 yak, including 42 newly sequenced yak from nine Qinghai yak breeds/populations, to identify single-nucleotide polymorphisms (SNPs) based on the latest yak reference genome  and to reveal their genomic diversity and population structure, as well as candidate signatures of positive selection. The gathered information provides a baseline for the exploration and evaluation of yak breeds/populations in Qinghai, China. Moreover, it contributes to the conservation and utilization of these precious yak genetic resources.This study was conducted following animal welfare requirements. The procedures approved for experiments were based on the recommendations of the Regulations for the Administration of Affairs Concerning Experimental Animals of China. The Institutional Animal Care and Use Committee of the Academy of Animal Science and Veterinary Medicine, Qinghai University, approved all the animal experiments in this study.n = 6), Yushu , Xueduo , Huanhu , Geermu , Qilian , Tongde , and Huzhu white . Genomic DNA was extracted using the Whole Blood DNA Extraction Kit  (n = 19), Datong , Yushu , Huanhu , Geermu , and Qilian . In total, this study analyzed 113 whole-genome sequences from nine Qinghai yak breeds/populations  . Pair-en, China) . To systulations .http://broadinstitute.github.io/picard) were used to filter potential duplicate reads. We used the “Haplotype Caller,” “Genotype GVCFs,” and “Select Variants” modules of the Genome Analysis Toolkit    to remov5c1c3ef)  to call 5c1c3ef) . In addi5c1c3ef) .FHom), linkage disequilibrium (LD) decay, and runs of homozygosity (ROH) for nine Qinghai yak breeds/populations .To reveal the genomic variations of Qinghai yak, we calculated the genomic parameters, including nucleotide diversity (Pi), expected heterozygosity (He), observed heterozygosity (Ho), inbreeding coefficient (FHom), which was the canonical estimate of genomic FHom based on excess SNP homozygosity (r2 > 0.2) within a sliding window of 50 SNPs advanced by five SNPs at a time (We estimated the genomic nucleotide diversity of each yak breed/population using VCFtools (v0.1.12) software . The output of the -het function by VCF tools was a summary for each individual of the observed number of homozygous sites [O(hom)] and the expected number of homozygous sites [E(hom)]. It also included the total number of sites for which the individual had data and the inbreeding coefficient  software. SNPs with minor allele frequencies (MAF < 0.05) were excluded due to instability. PLINK (v1.9) software was used for sliding windows of a minimum of 50 SNPs across the genomes to identify ROHs, allowing for two missing SNPs and one heterozygous site per window. The minimum number of continuous homozygous SNPs constituting an ROH was set to 100. The minimum SNP density coverage was set to at least 50 SNPs per kb, allowing centromeric and SNP-poor regions to be algorithmically excluded from the analysis. The maximum gap between two consecutive homozygous SNPs was set at 100 kb. The number and length of ROHs for each yak breed/population were estimated, and the length of ROHs was divided into three categories: 0.5–1 Mb, 1–2 Mb, and > 2 Mb, reflecting ancient, historical, and recent inbreeding, respectively .K), and the results were visualized via R (v3.6.1) software. Based on the pairwise distance matrix among individuals, a neighbor-joining (NJ) tree was constructed by MEGA (v10.2.6) (FST) between nine Qinghai yak breeds/populations, and the results were visualized via ImageGP (http://www.ehbio.com/ImageGP/). To further explore the relationships among nine Qinghai yak breeds/populations, we calculated the linearized RST values (RST = FST/(1- FST)). Based on the RST values, the cluster pattern among nine Qinghai yak breeds/populations was revealed by multidimensional scale (MDS) analysis using SPSS (v18.0) software.VCFtools (v0.1.12) software was used to convert the VCF files into the PLINK format. Linkage sites in the genomic data were removed with parameters (-indep-pair-wise 50 5 0.2) using PLINK (v1.9) software, and then the filtered data were used for principal component analysis (PCA) and admixture analysis. The population genetic structure was estimated using ADMIXTURE (v1.3.0) , considev10.2.6) . The PCAv10.2.6)  to estimv10.2.6)  softwareFST), were used to detect the selection signatures in Qinghai yak. The CLR was computed using SWEEPFINDER2 software to detect SNPs within a non-overlapping 50 kb window , and FDR < 0.05 was used as a threshold to detect significantly enriched genes and pathways.Only SNPs with less than 10% missing nucleotides were used for selective sweep scanning. To explore the selection pressure of domestic and wild yak in Qinghai, we performed a detection of positive selection signature. In this study, three methods, including composite likelihood ratio (CLR), nucleotide diversity (PI), and pairwise fixation index , followed by Qilian, Yushu, Geermu, Huanhu, Datong, Xueduo, Tongde, and Huzhu white yak (Nucleotide diversity (Pi) ranged from 0.0006 to 0.0015 among nine Qinghai yak breeds/populations ; Table 1hite yak . We founhite yak . Larger hite yak .To determine the population genetic structure and relationships among nine different yak breeds/populations, we conducted a series of analyses, including phylogenetic reconstructions, PCA, and Bayesian clustering, using WGS data. In a phylogenetic analysis, the NJ tree showed different clades for wild yak and eight domestic yak breeds/populations in Qinghai and inferred two lineages (lineages I and II)  and threvia ADMIXTURE software through clustering models  shared a small amount of this new ancestry. When K ≥ 4, cross-validation errors (≥0.3043) for ancestry models increased gradually, which suggested false results for the ancestry analysis  explained 3.07% of the total variation separating wild yak and Geermu yak from the other seven yak breeds/populations . The secg models . In clusanalysis .FST) values between nine yak breeds/populations ranged from 0.003 to 0.076 (FST < 0.15) between wild yak, Geermu yak, and the other seven yak breeds/populations. However, there was weak genetic differentiation (0 < FST < 0.05) among the other seven yak breeds/populations  genes were identified (p < 0.05) , heat stress , pigmentation , vision , milk quality (OPLAH and GRINA), neurodevelopment , and meat quality (ZRANB1)  exhibited higher FST and differential Tajima’D and PI values between wild and domestic yak (http://kobas.cbi.pku.edu.cn/) to find vital KEGG and GO pathways. In total, 29 KEGG pathways and 383 GO terms were found in our enrichment results , as well as five genes  related to disease resistance, growth, and heat stress  were found to be associated with immunity, heat stress, and milk quality. We also detected significant GO terms responsible for growth  . In addition, some significant GO terms  related to disease resistance were detected, which may contribute to disease resistance of yak in harsh high-altitude environments.In this study, we used the CLR, PI, and  Qinghai . As a reentified , with on < 0.05) . These i < 0.05) . Annotat(ZRANB1) . As a suronments . Here, istic yak . However results . As for  results , the KEGt stress . GO term071560”)  involvinGenetic diversity is an important component of biological diversity. It is the basis of biological evolution and species differentiation, with great significance for population maintenance and adaptation to habitat change. In a previous study, ROH has gradually become an important index for identifying inbreeding degrees and genetic variation patterns in livestock populations . Here, tK = 2, yak populations were divided into domestic and wild yak, while when K = 3–5, yak samples could not be divided into different ancestries, which indicates extensive genetic mixing among domestic yak. In our present study, we explored the population genetic structure of wild yak and Qinghai domestic yak breeds/populations. The ADMIXTURE analysis showed that at K = 2, nine yak breeds/populations had two ancestral components (domestic yak and wild yak), while Geermu yak carried a high genetic component of wild yak. At K = 3, a third new ancestral component appeared in a few wild yak individuals and in all domestic yak breeds/populations except for Huzhu white yak. Geermu yak showed more similar ancestral composition to wild yak, and other domestic yak breeds/populations in Qinghai showed similar ancestral components that differed from wild yak. The size of cross-validation errors could affect the authenticity of ancestry , moderate (0.05–0.15), or significant (0.15–0.25) population differentiation. The degree of differentiation is considered extremely significant when the index exceeds 0.25  gene is a regulator of the heat stress response, maximizing heat shock protein expression, and thus is certified to be associated with heat tolerance in Jersey, Angus, Simmental, and indicine cattle  linked to milk yield and fat contents in Holstein cows  were identified as PSGs by all three methods. We believe that these three genes are more likely to participate in hair formation and pigmentation in yak, although additional functional experiments are needed for verification. Additionally, SUSD4, a gene coding for a complement-related transmembrane protein involved in neurodevelopment , and the Geermu yak carry a high genetic component originating from wild yak. Moreover, Qinghai yak are clustered into wild, Geermu, and other seven yak breeds/populations, while weak genetic differentiation is displayed among the seven other domestic yak breeds/populations. The candidate genomic regions are involved in disease resistance, heat stress, pigmentation, vision, milk quality, neurodevelopment, and meat quality. This research indicates for the first time that Geermu yak, Qilian yak, and the other domestic yak breeds/populations exhibit genetic differences at the genomic level. These findings provide a theoretical basis for the reasonable protection and utilization of Qinghai yak genetic resources in the future.


The evolution of parasites is often directly affected by the host's environment. Studies on the evolution of the same parasites in different hosts are of great interest and are highly relevant to our understanding of divergence.Parascaris univalens from different Equus hosts . Phylogenetic and selection analyses were performed to study the divergence and adaptability of P. univalens.Here we performed whole-genome sequencing of P. univalens is mainly separated into two clades (horse-derived and zebra & donkey-derived). This divergence began 300–1000 years ago, and we found that most of the key enzymes related to glycolysis were under strong positive selection in zebra & donkey-derived roundworms, whereas the lipid-related metabolic system was under positive selection in horse-derived roundworms, indicating that the adaptive evolution of metabolism has occurred over the past few centuries. In addition, we found that some drug-related genes showed a significantly higher degree of selection in diverse populations.At the genetic level, multiple lines of evidence indicate that P. univalens in different hosts for the first time. Its results indicate that the divergence of P. univalens is a continuous, dynamic process. Furthermore, the continuous monitoring of the effects of differences in nutritional and drug histories on the rapid evolution of roundworms is conducive to further understanding host-parasite interactions.This work reports the adaptive evolution and divergence trend of The online version contains supplementary material available at 10.1186/s12864-022-08702-6. Parascaris univalens is a large parasitic nematode that predominantly infects foals and weanlings. P. univalens has a direct lifecycle in which infective eggs ingested from the environment hatch in the horse’s stomach. The larvae then penetrate the intestinal wall and moult by migrating to the liver and lungs and eventually return to the small intestine to develop into adults. Understanding the genetic characteristics of Parascaris worms in different regions or environments is essential for monitoring the development of new variants [P. univalens have been conducted in several areas [Equus caballus), zebra (Equus zebra) and donkey (Equus asinus), are the reservoir hosts of P. univalens. Despite the close relationships of these hosts, the extent of their habitats, food composition, digestion levels, and history of human intervention are very different, and the impact of these factors on large parasites living in these hosts remains unknown. Studying selection and evolutionary processes in different living environments provides insight into the adaptation of P. univalens.variants . Studiesal areas , 3. The P. univalens include a variety of equine species, and the geographical distributions, dietary structures and immune abilities of these hosts are also different. Donkeys have much lower energy and protein requirements than other equids [Nematodes have evolved to exploit highly diverse ecological niches. Parasitic nematodes have adapted to a wide range of threats, including climatic and nutritional threats, and the immune responses of hosts . These fr equids , and ever equids , which mr equids . The genr equids . The genr equids . StudyinP. univalens populations found in three main hosts: horse , zebra (E. zebra) and donkey (E. asinus) in northeastern China. We present the first report on the recent divergence of P. univalens populations, and speculate that it might be linked to host digestion and metabolic preferences. In addition, the role of selection pressure in the population was evaluated at the genomic level. This work provides insight into P. univalens differentiation and metabolism and drug selection pressure.The control of parasitic nematodes feeding on animals relies almost exclusively on anthelmintics, which have proven to be effective in the short-term management, but their long-term effectiveness has been questioned due to the widespread emergence of drug resistance . There iP. univalens populations of Equus , zebra , and donkey  hosts from Inner Mongolia and Heilongjiang, China, were performed whole-genome sequencing . We randomly selected 1–4 samples from each sampling site for karyotype identification and found that all samples had two chromosomes , and the relationships were distant and could represent the whole population . All PCs showed that PEz and PEa were in the same cluster. In addition, the phylogenetic relationships among the three populations inferred based on the ML tree highlighted a similar division to that indicated by PCA  supported the clear separation among ons Fig. a, with PPCA Fig. b. The trPCA Fig. c. We scaPCA Fig. , Fig. S5P. univalens populations, we constructed a molecular clock phylogenetic tree based on the calibrated mutation rate using all SNP sites. The tree topology showed that the divergence time of PEc and PEz&PEa was approximately 900–1500 years ago when the posterior probability was > 95%  of three populations , and the other was zebra & donkey-derived (PEz&PEa). The conservative divergence time was estimated to be within the last 300 years. Finally, we used fastsimcoal2 to evaluate the population size after divergence based on the observed joint site frequency spectrum  was computed for each population based on all samples. Additionally, we identified genomic regions as candidate divergent regions (CDRs) among the PEc, PEz and PEa populations . The collective selection of enzymes in the glycolysis process and tricarboxylic acid cycle showed that PEz&PEa presented a greater demand for this process than PEc. In addition, members of the lipid synthase family, which are involved in the uptake of fatty acids, were significantly positively selected in PEc. Parasitic helminths contain appreciable quantities of lipids. However, most intestinal helminths do not utilize significant amounts of lipids even during starvation and under aerobic conditions [In-depth genome scanning and functional annotation helped us to understand the observed population divergence. Genome-wide nucleotide diversity  waes Fig. S. The PEznditions , mainly π) and Tajima’s D value of the three populations with 10 kb sliding windows. The results showed that multiple resistance-related genes were under strong positive selection among different populations , which is related to ivermectin resistance, showed strong positive selection in the PEa populations. Three gene of cytochrome P450 family  showed strong positive selection in the PEc populations. The positive selection of these gene regions differed in the three populations, which may be related to the drug history in different environments. Nevertheless, it was obvious that certain instances of genetic selection were highly conserved and significant in some populations. The results show that the selection of these resistance-related genes will be maintained in independent populations and will continue to be passed down to the next generation. It should be noted that these instances of selection were population specific and have the potential to promote population differentiation.Current anthelmintics mainly present two modes of action, one mode is characterized by more rapid action on membrane ion channels, and the other is a relatively slow biochemical reaction. These common types of anthelmintics include benzimidazoles (BZs), macrolides (MLs), nicotinic acetylcholine receptor agonists , and amins Table a. Howevens Table c. Selectns Table —S17. ForP. univalens populations. In addition, the demographic history showed that P. univalens is undergoing divergence. We summarize the main findings regarding the diversification of P. univalens, and provide a perspective for the future monitoring of roundworm ecology in a timely manner to address possible unfavourable mutations.The ecological environment inhabited by parasites differs from that encountered by ordinary animals, and the survival of parasites is more dependent on the intestinal environment. The evolution of a single species is a long and complicated process. Numerous environmental changes and related factors affect this process. Our study used a combination of explicit genetic analysis and demographic models to determine the possibly diversified mechanisms that occur in different intestinal environments. We estimated the population histories of three populations using the PSMC and SMC +  + methods, and their population histories showed exactly the same trend before 10,000 years ago, while differences were found in recent population history estimates. In addition, we applied δaδi 2D/3D models to simulate the possible demographic history. The ancient migration or secondary contact model and the immediate size change model, were found to be effective in explaining the demographic differences and recent divergence of the The host's influence on parasite evolution cannot be ignored. A change in the host's diet represents both an opportunity and a challenge for parasites. From the perspective of glycolysis, we found that most of the key enzymes involved in glycolysis were subjected to a higher degree of recent positive selection in PEz and PEa than in domestic horses. Glycolysis and tricarboxylic acid cycle, which represent the most important route whereby roundworms obtain ATP, seem to have "degraded" in domestic horse roundworm populations. Experiments have shown that the contents of fatty acids such as palmitic acid, palmitoleic acid, stearic acid, and oleic acid in a parasite are almost the same as those in its specific host and the changes in the ratio of fatty acids tend to be synchronized between these organisms . ImmunolP. univalens is highly adaptable and evolves quickly. As the gene frequency of certain drug-related genes in specific populations further increases, it is likely that P. univalens will differentiate into new subpopulations with specific phenotypes.The issue of drug resistance has been widely mentioned over the past two decades. Parasites show strong adaptability, and roundworms lay more than 200,000 eggs per day , almost P. univalens cannot be fully considered. We only considered two types of highly significant factors (metabolism and anthelmintics), and other selection effects still need to be verified in a broader range of P. univalens populations in the future.This work provides a reference for monitoring the evolution of parasites and elucidating evolution under the action of both natural selection and drugs. Due to the limitation of sample size, some accidental or other environmental factors potentially related to natural selection in E. caballus) treated with anthelmintics on a farm located in the Ordos, Inner Mongolia, China. While two horse roundworm individuals were collected after anthelmintic treatment from a farm in Harbin, Heilongjiang, China. Five roundworms from three donkeys (E. asinus) were collected after anthelmintic treatment from a farm in Chifeng, Inner Mongolia, China. Eighteen roundworms from ten zebra (E. zebra) were obtained after anthelmintics treated from Harbin Northern Forest Zoo, Heilongjiang, China. It is worth noting that at the Harbin Zoo, zebras and domestic horses share the same pasture. Before treatment with anthelmintic, we collected the feces of all zebras and domestic horses in the Zoo to detect the infection of the roundworms. Interestingly, P. univalens eggs were only detected in some zebra feces but not in domestic horse feces. All specimens were washed extensively in sterile physiological saline (37 °C), snap-frozen and transported with dry ice, and then stored at -80 °C until further use.Seventeen roundworms were collected from six naturally infected horses  using BWA-MEM (0.7.13-r1126) [Parascaris equorum reference genome (WormBase project ID: PRJEB514) was used for species identification. Duplicated reads were marked with the Picard Tools . Then Genome Analysis Toolkit (GATK v 4.0.3.0) [High-quality reads were aligned to the 3-r1126)  was used4.0.3.0)  was used4.0.3.0)  for downπ) and Tajima’s D were computed by sliding windows of 1 kb using all individuals in each population using VCFtools (v0.1.13). The Weir-Cockerham fixation index (Fst) was estimated among three populations with genotype data using the VCFtools (v0.1.13).SNP density was counted with a 10 kb sliding window using VCFtools (v0.1.13) software . Genome-Baylisascaris schroederi was selected as an outgroup. Population structure was analyzed using the ADMIXTURE (v1.3.0) program with a block-relaxation algorithm. To explore the convergence of individuals, we predefined the number of genetic clusters of K from 2 to 4.Principal component analysis (PCA) was carried out using EIGENSOFT  softwareP. univalens populations in a coalescent framework with SNAPP implemented in BEAST v2.6.3 [P. univalenswas 0.17 year, and converted the SNAPP analyses into units of real-time using a mutation rate (μ) of 9 × 10–9 per generation per site.We investigated the relationships within T v2.6.3 . We perfT v2.6.3 . AccordiNe) of each population. We used 0.17 year per generation (g) and a mutation rate (μ) of 9 × 10–9 per generation per site to rescale the time to year [μ) of P. univalens for SMC +  + and MSMC2 have used the same values as for PSMC.The pairwise sequentially Markovian coalescent (PSMC) method  was used to year , 37. Mor to year , which c to year  to do th to year , then thP. univalens populations. We chose only SNPs located in intergenic regions to avoid the influence of SNPs under selection [https://github.com/dportik/dadi_pipeline.We used the fastsimcoal2  approachelection . We usedelection  to inveshttps://cran.r-project.org/web/packages/rehh/vignettes/rehh.html). The regions with P values < 0.01 were considered significant signals in the population of interest.Extended Haplotype Homozygosity (EHH) and Integrated Haplotype Score (iHS) methods were used for detecting SNPs under a recently positive selection of three roundworm populations . We use P. univalens is the main parasitic pathogen that infects equine, and it is also the chief culprit in horses' weight loss and weakened immunity. The genetic variation and host differences complicate the development of broad-spectrum diagnostics, therapeutic. Here we report the recent divergence of P. univalens and reveal that the rapid evolution of glycolysis-related genes drove this divergence. It is also a key factor leading to the parasitic preference of roundworm populations. In addition, we found that resistance-related genes have a similar tendency, which was the potential impact of overuse of anthelmintics. We have established a rapid evolution gene set of P. univalens, which will help managers decide on therapeutic strategies targeting specific populations and allow researchers to monitor the ongoing evolution and diversification of P. univalens.Table S1. Sequencing data. Table S2. Summary of sequencing data. Table S3. Estimates of expected heterozygosity and observed heterozygosity. Table S4. Four rounds of increasingly focused optimizations used in δaδi. Table S5. Maximum-likelihood parameter estimates obtained from the joint demographic inference analysis 2D and 3D. Table S6. Genomic regions identified as candidate divergent regions. Table S7. GO enrichment (Top 20) of iHS significant selection sites in PEc and PEz&PEa clades. Table S8. KEGG enrichment of XP_EHH significant selection sites in PEc and PEz&PEa clades. Figure S1. SNPdensity. Figure S2. Sequencing depth. Figure S3. Karyotyping. Figure S4. The mapping ratio and shared SNPs distribution. Figure S5. Shared identity-by-descent (IBD) region among PEa, PEc and PEz populations. Figure S6. The shared IBD and paired Fst values of the three populations. Figure S7. Observed SFS between PEc and PEz & PEa clades. Figure S8. 3D divergence model used in δaδi. Figure S9. 2D divergence model used in δaδi. Figure S10. Fst distribution of PEc vs PEa & PEz. Figure S11. The iHS score distribution of PEc, PEa and PEz populations. Figure S12. KEGG enrichment of iHS significant selection locis of PEc and PEa & PEz respectively. Figure S13. GO enrichment of XP_EHH analysis of PEa and PEc & PEz respectively. Figure S14. Network diagram of GO function enrichment obtained by XPEHH analysis of PEa and PEc & PEz clades. Figure S15. Detection of mutations in three drug-resistant sites of β-tubulin. Figure S16. The π distribution and tajima’D distribution in the pgp-3 regions. Figure S17. The π distribution and tajima’D distribution in the unc-38, nrf-6, glc-1 and cup-4 regions. Figure S18. The π distribution and tajima’D distribution in the CYP3A31, CYP4C1, mrp-1 and CYP4V2 regions.Additional file 1:


Hedyotis chyrsotricha (Rubiaceae), in two contrasting island systems of southeast China. Based on RAD-Seq data, our results showed that populations from the artificially created Thousand-Island Lake (TIL) harbored significantly higher levels of genetic diversity than those from the Holocene-dated Zhoushan Archipelago (ZA) , while genetic differences between island and mainland populations were significant in neither the TIL region nor the ZA region. A certain level of population substructure was found in TIL populations, and the level of gene flow among TIL populations was also lower than in ZA populations (m = 0.019 vs. 0.027). Overall, our comparative study revealed that genetic erosion has not become much stronger for the island populations of either the TIL or ZA regions. Our results emphasized that the matrix of water in the island system may facilitate the seed (fruit) dispersal of H. chrysotricha, thus maintaining population connectivity and providing ongoing resilience to the effects of habitat fragmentation over thousands of years. The genetic effects of habitat fragmentation are complex and are influenced by both species traits and landscape features. For plants with strong seed or pollen dispersal capabilities, the question of whether the genetic erosion of an isolated population becomes stronger or is counterbalanced by sufficient gene flow across landscapes as the timescales of fragmentation increase has been less studied. In this study, we compared the population structure and genetic diversity of a distylous herb,  Over the past 200 years, human activities have altered more than 80% of the terrestrial world, leading to increasing habitat reduction and fragmentation of almost all ecosystems ,2,3. TheCastanopsis sclerophylla (Lindl. & Paxton) Schottky in a recently fragmented island system. Due to the disappearance of a genetic barrier, the genetic structure of post-fragmentation cohorts was significantly weakened by increased wind speeds and easier pollen movement over water. In contrast, our previous study on the distylous herb Hedyotis chrysotricha  Merr in the Thousand-Island Lake (TIL) region revealed that 53 years of fragmentation has led to the loss of c. 17.4% of the initial genetic diversity in the island populations  against geographic distance (log10 transformed) was performed in GENALEX v6.1 [We calculated the observed heterozygosity (N v3.5.2 . PopulatN v3.5.2 . The numARVESTER . A ManteLEX v6.1  for each7 iterations with a burn-in of 106 generations), each with a different initial seed. Model convergence was assessed by the program TRACER v1.5 [GST method. To test for asymmetric flow (significantly higher in one direction than the other), 95% confidence intervals were calculated from 1000 bootstrap replicates [For each region, we estimated the levels of interpopulation gene flow using the program BAYESASS v3.03 . First, CER v1.5 . In addiCER v1.5  to calcuplicates .H. chrysotricha populations underwent significant reductions in effective population size (Ne). We used Wilcoxon’s signed rank test, which examines whether populations exhibit a greater level of heterozygosity than predicted in a population at mutation-drift equilibrium, to detect bottlenecks occurring over approximately the last 2–4 Ne generations. For each H. chrysotricha population, we performed 10,000 simulations for each of three mutation models . Statistical significance was set at the 0.05 level.We used the program BOTTLENECK v1.2.02  to deterH. chrysotricha to short-term and long-term habitat fragmentation. The levels of genetic diversity and the population substructure of H. chrysotricha populations were both higher in the TIL region than in the ZA region, while gene flow was higher and less asymmetric among ZA populations. The differences in genetic diversity between island and mainland populations in both regions were not significant, suggesting that genetic erosion of island populations does not increase as the spatial and temporal scales of fragmentation increase. Population connectivity in H. chrysotricha has also not been greatly modified by either short-term or long-term habitat fragmentation. The strong fruit (seed) dispersal capacity of H. chrysotricha, facilitated by the matrix of water in the island system, could buffer against the negative effects of habitat fragmentation and maintain the population connectivity over thousands of years.Based on high-resolution SNPs, we compared the genetic response of


P = 0.048, and Oromo, P = 1.6x10-5). Those traits are mainly related to anthropometry, circulatory and respiratory systems, energy metabolism, and calcium homeostasis. Our results reinforce the notion that endurance running is a systemic activity with a complex genetic architecture, and indicate new candidate genes for future studies. Finally, we argue that a deterministic relationship between genetics and sports must be avoided, as it is both scientifically incorrect and prone to reinforcing population  stereotyping.Since the 1960s, East African athletes, mainly from Kenya and Ethiopia, have dominated long-distance running events in both the male and female categories. Further demographic studies have shown that two ethnic groups are overrepresented among elite endurance runners in each of these countries: the Kalenjin, from Kenya, and the Oromo, from Ethiopia, raising the possibility that this dominance results from genetic or/and cultural factors. However, looking at the life history of these athletes or at loci previously associated with endurance athletic performance, no compelling explanation has emerged. Here, we used a population approach to identify peaks of genetic differentiation for these two ethnicities and compared the list of genes close to these regions with a list, manually curated by us, of genes that have been associated with traits possibly relevant to endurance running in GWAS studies, and found a significant enrichment in both populations (Kalenjin,  The vasWhile the regional and ethnical clustering of best-ever performing athletes may suggest a shared genetic or cultural background as important factors, no simple explanation for their dominance has emerged yet . This isRegarding genetic factors, only two candidate genes have been investigated in East African populations ,5. Yang et al. [Tucker et al.  criticizIn the present study, we followed this reasoning by comparing genomic populational data among different ethnicities in East Africa. We hypothesize that the alleles that predispose to endurance running should be common in the general population of these ethnic groups and, consequently, that genetic factors associated with athletic success in Kalenjin and Oromo should be, at least partially, close to the genomic regions of greater differentiation in these ethnicities, enabling the identification of molecular processes that contribute to long-distance running . This apa priori from the GWAS catalog database [P = 0.048, odds ratio (OR) = 2.003, and P = 1.6x10-5, OR = 2.918, respectively; see Material and Methods for details), the Luhya, from Kenya, showed no significant enrichment , while the Amhara, from Ethiopia, were enriched for endurance-relevant traits . However, in both cases, these populations had, respectively, fewer endurance-relevant traits than its national counterparts .Using the normalized Population Branch Statistic (PBSn1) , we idendatabase , we founMaterial and Methods for details), we also selected the genes in the five most differentiated genomic regions, highlighting seven candidate genes for Kalenjin: TRAM2-AS1, WWOX, ARHGEF1, GATAD1, AMOTL1, GSTO1, and MRAP2; and eight for Oromo: LTBP1, COL5A2, MIR6797, ADAMTS9-AS2, EXOC4, EXOC5, EXOC6B, and LIPE-AS1 whose biological function is related to the endurance-relevant gene-sets. These functions affect anthropometric/biomechanical traits , lung function (WWOX), blood pressure and the circulatory system , glucose metabolism , fatty acids metabolism (MRAP2 and LIPE-AS1) and calcium homeostasis .Thus, genes close to highly differentiated genomic regions are enriched for endurance-relevant traits in Kalenjin and Oromo, and both have more endurance-relevant gene-sets than its national pairs. The 10 endurance-relevant gene-sets for Kalenjin and the 27 for Oromo comprised 49 and 96 candidate genes . For eacIn this study, we used publicly available genomic data to tackle the hypothesis that genetic variation could be associated with endurance running in East African populations , but theet al. [LTBP1, one of the most differentiated genes for Oromo, participates in the molecular pathway associated with those phenotypes. LTBP1 binds to TGF-ß1, facilitating its export to the extracellular matrix of bone cells, where it plays a key role in chondrocyte maturation, mineralization, and bone remodeling [There was an abundance of anthropometric-related traits, such as height, waist circumference, and waist-to-hip ratio, among the enriched sets for both Kalenjin and Oromo. Eksterowicz et al.  found thet al. ,17,18. Lmodeling ,20.TRAM2-AS1 and COL5A2, respectively, are associated with the synthesis and organization of type I collagen, the main protein in ligaments and tendons [TRAM2-AS1 encodes an antisense RNA against TRAM2, which participates in type I collagen’s biosynthesis [TRAM2-AS1 may modulate the synthesis of type I collagen. Likewise, COL5A2 encodes, together with COL5A1 and COL5A3, one of the three alpha chains that form type V collagen, which on its turn regulates the assembly and structure of type I collagen fibrils [COL5A2 or COL5A1 account for over 90% of the cases of the classic Ehlers-Danlos syndrome, characteristic for joint hypermobility [COL5A1  have been directly associated with performance in long-distance running, with individuals carrying the T/T or AGGG/AGGG genotypes being considerably faster and less flexible [COL5A2 may have a similar effect to COL5A1, considering that these genes encode different subunits of the same protein and that mutations in both have the same clinical outcome [The structure of bones and tendons also plays an important role in physical activity, including long-distance running. Less flexibility and greater stiffness are observed in the lower limb’s tendons of long-distance runners ,22, and  tendons . TRAM2-Aynthesis . Given tynthesis , TRAM2-A fibrils ,28. Mutamobility . Two polflexible ,31. Vari outcome .LTBP1, previously discussed, other highly differentiated genes that could affect this trait are WWOX, shared by both populations, MIR6797 in Oromo, and TRAM2-AS1 in Kalenjin. The products encoded by these genes interact with the transcription factor RUNX2, the major regulator of bone development [RUNX2 expression, controlling osteoblast differentiation [TRAM2 in bone cells, affecting the availability of type I collagen in the bone extracellular matrix [Long-distance running has also been associated with bone mineral density, which is increased in the legs and reduced in the vertebrae of runners compared to controls –34. We felopment . The firntiation ,37. Indentiation . RUNX2 ar matrix .2max, high capacity to mobilize oxygen and energy), but will consume less oxygen to run at intermediate speeds  [2max (h2 ≅ 0.56) [WWOX, present in the gene lists of both populations, has been associated with lung function in GWAS [Together with anthropometric traits, physiological processes are central to endurance running . In geneirement) . The effirement) . Lung fuirement) ,41, and irement) , as expe ≅ 0.56) . We foun in GWAS ,45, case in GWAS , even thADAMTS9-AS2, encodes the antisense RNA of the ADAMTS9, which codes for a metalloproteinase essential for the normal development and homeostasis of the heart and arteries [ARHGEF1, GATAD1, AMOTL1, and GSTO1) participate in biological processes related to BP. ARHGEF1 is activated by angiotensin II in arterial smooth muscle cells, leading to increased BP [ACE codes for the enzyme that produces angiotensin II, and has been associated with endurance running success in other studies [GATAD1 and AMOTL1 seem to be more important in cardiac muscle development, but may affect BP indirectly. GATAD1 is expressed in ventricular myocytes, and mutations in this gene cause dilated cardiomyopathy, a disease characterized by excessive enlargement of cardiac ventricles [AMOTL1 has been associated with the enlargement and proliferation of cardiomyocytes, cardiac hypertrophy [GSTO1 downregulates the activity of the cardiac ryanodine channel RYR2, which releases calcium from the sarcoplasmic reticulum into the cytoplasm to perform muscle contraction [RYR2 is in the Oromo gene list—in the gene sets associated with lung function , on the amount of available hemoglobin, and tissue vascularization. Diastolic BP has been identified as a predictor of endurance performance ,48, and arteries . Unlike eased BP . ACE cod studies , though ntricles . AMOTL1 ertrophy , and angertrophy ,56. Finatraction . Interesfunction , and hasuropeans .EXOC4, EXOC5, and EXOC6B). The exocyst is essential in the insulin-induced transport to the cell membrane of the main glucose transporter (GLUT4) in the muscle  and adipose tissue [WWOX deficient cells show an increase in HIF1α levels and activity, as well as an increase in glucose uptake [HIF1A, the gene encoding HIF1α, has already been directly associated with elite long-distance runner status [Most metabolic energy for endurance running comes from aerobic glycolysis in the mitochondria . Both Kae tissue ,61. The e tissue –62. Withe uptake . HIF1A, r status .LIPE-AS1 encodes the antisense RNA for LIPE, which codes for the main regulator of lipolysis in adipocytes, responsible for releasing fatty acids from stored triglycerides. Mutations in this gene are directly related to several metabolic diseases [MRAP2 codes for an accessory protein that modulates the activity of melanocortin receptors, in particular MC4R [MRAP2 and MC4R cause obesity in both humans and mice [Mc4r knocked-out (MC4RKO) mice are obese, but have a specific metabolic profile, with lower heart rate, lower lean body mass, lower muscle strength, lower bone density, and lower performance in endurance running [On the other hand, the use of fatty acids in energy metabolism is linked to the ability to maintain physical activity for a longer period while preserving the systemic glucose levels . Again, diseases . In the lar MC4R ,68. MC4Rlar MC4R . Mutatioand mice ,71. Mc4r+, Na+, Cl- or Mg2+. Many genes discussed previously, like WWOX, MIR6797, MRAP2, GSTO1, and RYR2 affect calcium homeostasis. Considering the system GSTO1/RYR2, high intrinsic aerobic exercise capacity in mice was associated with greater contraction amplitude in cardiomyocytes, an increased peak of calcium release, and increased expression of RYR2 [2+ sensibility in cardiac muscle cells [Finally, muscle contraction in both skeletal and cardiac muscles depends on the calcium ion release from the sarcoplasmic reticulum into the cytoplasm . Both Ka of RYR2 . Besidesle cells .COL5A2 and COL5A1, ARHGEF1 and ACE, and WWOX and HIF1A). This indicates that, while the same pathways are important for endurance running in different ethnicities, different genes may be more important in a population-specific context. RYR2 and its regulator, GSTO1, being highly differentiated in Oromo and Kalenjin, respectively, further highlights this point. The overrepresentation of Eurasian populations in GWAS studies [WWOX, MRAP2, TRAM-AS1, and GSTO1) seem to affect more than one trait, while all traits seem to be influenced by multiple genes, in a complex many-to-many relationship [The fact that most genes discussed here have not been previously associated with endurance running may be due to differences in study design. Indeed, an important assumption of our study is that interpopulation comparisons may be more informative to explain the overrepresentation of East African ethnicities among elite runners . On the  studies  may also studies . Severaltionship  that is tionship .RYR2, in the Oromo list, that has been previously associated with high-altitude adaptation in studies involving East African (Amhara) populations [LIPE-AS1, whose target, LIPE, was shown to affect survival rates in Drosophila exposed to low oxygen conditions [Because we rely on a general measurement of population differentiation, our approach is also unable to test if endurance running evolved as an adaptation or should be seen as a by-product of neutral demographic processes. Another possibility is that adaptation to high-altitude favors some East African populations in endurance events, even though the direct relationship between being born in high-altitude and increased endurance performance is controversial . We founulations , and anonditions . Howeverth century that, among other things, antagonized athleticism and intellectual ability [Finally, we would like to emphasize that genetic predisposition does not mean predestination, and success in sports should not be taken as a racial  stereotype (even if a putatively “positive” one). First, we must be very careful to avoid reinforcing the horrific racist ideas from the late 19 ability . A recen ability ,86. Thes ability ,88. EvenOur study assumes a “populational effect” for the dominance of some East African ethnicities in endurance running events . That iset al. [FST statistic, uses allele frequency data to estimate the degree of genetic differentiation specific to a population of interest, or focal population, in relation to two reference populations, generally one closely related to the focal population and another more distantly related [FST, which is the basis of PBS (and PBSn1) calculation, is affected by several evolutionary processes [For estimating the peaks of genomic differentiation, we used the Population Branch Statistic (PBS) , in its et al. . This st related ,13. It irocesses . When nerocesses . In thisSimilarly, when the studied populations are admixed for different ancestries, differences in allele frequencies between ancestry components may affect genetic differentiation statistics. This must be corrected if the aim is to detect signals of natural selection ,91. HoweWe obtained curated genotyped SNP data made available by the African Genome Variation Project (AGVP), for 1,152,000 single nucleotide polymorphisms (SNPs) across the genome of 1,481 individuals from 18 ethnolinguistic groups from Sub-Saharan Africa using the Illumina Omni2.5 chip . The datFollowing demographic studies for Kenyan and Ethiopian athletes ,3, we seFor the PBSn1 calculations, we used a focal population, a closely related and a distantly related population for all possible combinations, except for the two combinations that would include the Amhara and Eurasia. Those combinations were excluded because the Amhara have the highest level of Eurasian ancestry (47.82–54.70%) , and spuWhen there is an adaptive hypothesis about the phenotype of interest, demographic simulations can be used to determine an empirical threshold above which the PBSn1 values are indicative of an adaptive process . HoweverP<0.05 after Benjamini-Hochberg False Discovery Ratio (FDR) correction. FUMA-GWAS performs the analysis using hypergeometric tests [We used the Ensembl platform  to annotic tests  to test ic tests  for traiic tests  for biolOur study design does not allow the specific detection of genes associated with endurance running success. However, we expect that genes associated with endurance running success will be among highly differentiated genomic regions in general. Conversely, many gene-sets with no biological relation with endurance running will show enrichment in the analysis.P = 0.019) for “Skin pigmentation traits” (genes BNC2 and FANCA). This example also illustrates the benefits of not controlling for admixture in some settings, since it is likely this difference would not emerge if only the sub-Saharan ancestry in the Oromo and Luhya were considered, given that it is probably associated with the large Eurasian ancestry in Ethiopian populations.As a “proof-of-concept”, we also reasoned that our approach should be able to detect genetic signals of other traits for which differences among populations are known. Ethiopian populations have lighter skin pigmentation compared to Kenyan populations. Therefore, the comparison  should be enriched for gene-sets associated with skin pigmentation. Indeed, we found significant enrichment  to 3.09 (P = 0.008). For Kalenjin, six parameter combinations resulted in statistically significant enrichment, with ORs varying from 1.47 (P = 0.012) to 2.70 (P = 0.034). However, the two combinations including 30 SNPs windows and 0.1% of windows retained resulted in non-significant values , possibly because the number of total sets (and hence the number of endurance-related sets) was too small, reducing the statistical power of Fisher’s exact test. All endurance-related gene-sets detected in the sensitivity analyses are shown in We also performed some sensitivity analyses to test the robustness of our results to parameter changes. We varied window size , the percentage of top-PBSn1 windows retained , and the reference list for endurance-relevant traits  that checked the list of GWAS traits; alternative criteria: a trait had to be flagged by at least three authors (3A)). This alternative list of endurance-relevant traits is shown as S1 Fig(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S1 Dataset(XLSX)Click here for additional data file.S2 Dataset(XLSX)Click here for additional data file.S3 Dataset(XLSX)Click here for additional data file.S4 Dataset(XLSX)Click here for additional data file.S5 Dataset(XLSX)Click here for additional data file.S6 Dataset(XLSX)Click here for additional data file.S7 Dataset(XLSX)Click here for additional data file.


Odontobutis potamophilus is a popular food fish in China, distributed mainly in the middle and lower reaches of the Yangtze River, where it is a famous delicacy and a newly focused species for aquaculture. The wild populations of O. potamophilus are facing the problem of overfishing and habitat degradation. Therefore, it is very necessary to investigate and protect the wild populations of O. potamophilus. In this study, 72 fish were sampled from 18 different sites over its distribution range. Nuclear sequence data of 4,267 loci were collected using a gene-capture method. Phylogenetic reconstruction revealed that there were three major clades: Oujiang clade (OJ), Qiantang and lower Yangtze clade (QY), and middle Yangtze clade (MY). The discriminant analysis of principal components (DAPC) and a STRUCTURE analysis confirmed that there are three major groups within O. potamophilus. A fastsimcoal2 analysis corroborated the population history and suggested that there was discernible gene flow among these three groups, especially between QY and MY. Estimated pairwise FST suggested that Linhai (LH) and Shexian (SX) populations were the most divergent pair (FST = 0.7077). Taking the nucleotide diversity, population divergence, and admixture status altogether into consideration, we recommend that the LH, Gaoyou (GY) and Chaohu (CH) populations could be protected as the preferred resource for breeding projects. According to the results of genetic analyses, all populations of O. potamophilus should be protected due to low genetic diversity. Odontobutis contains a group of freshwater sleepers endemic to China, Japan, and the Korea Peninsula  species  among populations, absenting gene flow between populations. However, in the studies of O. potamophilus with low genetic diversity were found , restriction site associated DNA sequencing (RAD Sequencing) . Another species .O. potamophilus. The results of this research can provide a reference for the selective breeding programs of O. potamophilus with high genetic diversity or populations with low genetic diversity but unique in terms of genetic composition.In this study, we collected 72 fish from 18 different sites of the Huaihe River, the Yangtze River, the Qiantang River, and the Oujiang River basins. We applied a target-gene enrichment approach  and the O. potamophilus were collected from Meicheng (MC), Cixi (CX), Hangzhou (HZ), Huzhou (HU), Baoying (BY), Gaoyou (GY), Jingjiang (JJ), Guangfu (GF), Jiangba (JB), Shanghai (SH), Meizhu (MZ), Xingfu (XF), Shuiyang (SY), Chaohu (CH), Zhongmiao (ZM), Luan (LA), Shexian (SX), and Linhai (LH) of the Huaihe River, the Yangtze River, the Qiantang River, and the Oujiang River basins  was used to extract DNA from the tissue samples. The concentration of purified DNA was determined by a NanoDrop 3300 Fluorospectrometer  and visualized using agarose gel electrophoresis.A total of 72 r basins . Two samDNA was fragmented to ∼250 bp using a Covaris M220 focused ultrasonicator . One µl of sheared DNA was used in agarose gel electrophoreses to check the size of sheared DNA fragments. The Illumina sequencing libraries were constructed using a modified library preparation method . In the Rhinogobius giurinus. The baits’ length was 80 bp, covering the target sequences with 2X tiling. MYbaits RNA baits targeting the 4,434 loci were synthesized at Arbor Biosciences .According to the 4,434 single-copy nucleotide coding sequence markers of bony fish developed by Gene capture procedures were repeated twice followed http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/, accessed on 10 July 2021) and cutadapt v1.2.1 (The raw Illumina data were distinguished by the 8 bp P7 barcodes and the 6 bp inline indices . Trim_gat v1.2.1  was usedt v1.2.1 .http://broadinstitute.github.io/picard) was used to remove PCR repeats. GATK-3.4.0 (FST), nucleotide diversity (pi), and mean genetic distance (Phi_st) were calculated in the Stacks program .The captured genes were concatenated for phylogenetic tree inference. The phylogenetic tree was constructed using the maximum likelihood method to reveal the relationship of 72 otstraps . FigtreeO. potamophilus. The individuals were coded as 18 populations according to their geographical sampling sites. The STRUCTURE operating parameter was set to 20,000 for the length of the burn-in period, and 200,000 for the number of MCMC reps after burn-in. The analyses of k = 1–18 were repeated five times. The most likely K value was determined using Structure Harvester 0.6.93  was performed twice for each replication using R  package The results of cluster analysis showed that fish from the 18 sampling sites could be lumped into three major groups: The Oujiang clade (OJ), the Qiantang and lower Yangtze clade (QY), and the middle Yangtze clade (MY). We hypothesized four models for the evolutionary history of the three groups: model 1–3, either OJ, QY, or MY diverged first from the other two groups; model 4, the best model from the previous three but with migration allowed between different groups.Different models were tested using fastsimcoal2 version 2.7 . FastsimO. potamophilus and O. yaluensis, 4,267 genes (96.23% of 4434 genes) were enriched in more than 22 (>30%) individuals and used for phylogenetic reconstruction.A total of 287,518,950 reads were generated, with an average of 3,993,319 reads per individual. A total of 223,207,564 reads were retained, after the adapter sequences and the low-quality sequence (Q < 20) were trimmed, with an average of 3,100,106 reads per individual. After excluding PCR duplicates, 77.63% of the trimmed data were retained. An average of 2,635 loci were enriched in each sample, with the highest of 3,571 loci captured in CL1221_2, and the lowest of 202 loci in CL 1981_5. There were 3,750 loci on average captured for the two outgroup samples . After mFST > 0.25) accounted for 60.13%, medium degree of genetic difference (0.25 > FST > 0.15) accounted for 16.34%, and existed genetic difference (0.05 < FST < 0.15) accounted for 23.53%. LH, ZM, LA, and SX were the most divergent populations from the others. The maximum genetic divergence was found between LH and SX (FST = 0.7077), and the lowest genetic differentiation was between GF and HU (FST = 0.0492) , keeping 11,932 out of the 12,988 SNPs. At least one SNP was called for 472 loci after selecting one SNP from each locus to avoid linkage disequilibrium. The average nucleotide diversity (pi) of variant positions was 0.1250 with the highest 0.1846 for MC, and the lowest 0.0471 found in LH . Populat 0.0492) .O. potamophilus can be divided into three groups (The sampled sites can be divided into three groups (k = 3) , includie groups . Accordie groups , the firO. potamophilus  is an indicator to measure genetic differences between populations. The maximum value of FST was 0.7077 between LH and SX, indicating the greatest genetic difference between the two populations. In fact, the FST values between LH and all other populations were greater than 0.25, suggesting that LH is a unique genetic resource and breeding material. Therefore, LH should be protected for breeding programs, but more sites in the Oujiang River basin should be surveyed to examine the genetic diversity of O. potamophilus within the Oujiang River system. In the MY group, the population with the highest nucleotide diversity was SY (pi = 0.1351). However, many admixed individuals were observed in the SY population, so we should not use it for breeding programs. We suggest that the CH population, which had the second high nucleotide diversity (pi = 0.1330) but with no admixed individuals could be used for breeding projects. In the QY group, the population with the highest nucleotide diversity was MC (pi = 0.1846) but many admixed individuals were found in this population, so we suggest the GY (pi = 0.1438) population as the representative population due to the higher pi value and no admixed individuals. Taking the parameters of nucleotide diversity, FST, and admixture status all into consideration, we suggest that LH, GY, and CH populations should be protected. Those populations could be the preferred resource as founder populations for breeding projects, representing the OJ, QY, and MY groups, respectively.In the OJ group, LH was the only population sampled, with a nucleotide diversity of 0.0471. Mean pairwise population differentiation  and SX (Pi = 0.0701), due to their low genetic diversity compared to other populations. In these populations with low genetic diversity, the loss of individuals may lead to a decrease in the ability of the population to adapt to long-term environmental changes. Therefore, populations with low genetic diversity also should be protected, for example, by banning illegal fishing, to prevent anthropogenic destruction of the ecological environment, and creating a favorable habitat environment to maintain the wild populations of Odontobutis potamophilus is distributed in the Huaihe River, the Yangtze River, the Qiantang River, and the Oujiang River basins; however, how many divergent groups of O. potamophilus in these river systems have not been identified previously. The results of ML tree, DAPC, and STRUCTURE analyses unequivocally supported the division of O. potamophilus into three groups. The first differentiated group (OJ) was a clade of samples collected from the Oujiang River at Linhai, Zhejiang Province. Compared with other water systems, the Oujiang River is located in the southernmost part of the distribution range, so OJ population can be regarded as an independent population and it is crucial to protect the population of O. potamophilus in Oujiang. The other populations were divided into two groups, with Lake Tai as the boundary. The QY group is located to the east of Lake Tai, which is composed of populations from the Huaihe River, the Qiantang River, and lower Yangtze River. To the west of Lake Tai is MY group, which is composed of populations from the middle Yangtze River in Anhui Province. A similar pattern was also reported in previous research . Most lakes in the middle and lower reaches of the Yangtze River dried up during the glacial periods due to the decline of sea level  had little gene flow with QY groups, probably because the Oujiang River has no direct connections with the Qiantang River or the Yangtze River. There were possibly few river capture events between the Oujiang River and the Qiantang River, therefore, a few individuals from MC and CX (the Qiantang River) showed admixture genotype with some alleles from the LH population .O. potamophilus should be divided into three management units, that is, the group to the east of Lake Tai, the group to the west of Lake Tai, and the Oujiang group.Sample CL478-8 was collected from GF, which belongs to the QY group but clustered with individuals of the MY group in the phylogenetic tree . We specO. potamophilus can meet consumer demand, the quantities of wild O. potamophilus caught can be reduced. Although artificial breeding of O. potamophilus has been successful, there is yet no selected strain for aquaculture. Nonetheless, within-species crossing produced obvious heterosis in O. potamophilus (O. potamophilus. A famous example of breeding based on within-species crossing and subsequent selection is the “GIFT tilapia”. The successful breeding of GIFT tilapia indicates that the high genetic diversity of founder populations can improve the genetic gain of breeding (O. potamophilus, that is, a founder population can be formulated by crossing LH, GY, and CH, the representative populations of the three groups to increase the background diversity of the founder population; and, then subsequent selection can be carried out on it. Meanwhile, the wild populations of the three groups should be conserved separately to keep the wild diversity of this fish.If the volume of farmed mophilus , so therbreeding . We arguO. potamophilus could be divided into three major groups. Based on the nucleotide diversity, pairwise population differentiation, and admixture status of the populations analyzed, we recommended three candidates for the founder population and a strategy for selective breeding for O. potamophilus. All of the O. potamophilus populations should be considered for conservation to preserve their genetic diversity.In this study, we found that