Pyrus calleryana Decne.  includes cultivars that in the United States are popular ornamentals in commercial and residential landscapes. Last few decades, this species has increasingly naturalized across portions of the eastern and southern US. However, the mechanisms behind this plant’s spread are not well understood. The genetic relationship of present-day P. calleryana trees with their Asian P. calleryana forebears  and the original specimens of US cultivars are unknown. We developed and used 18 microsatellite markers to analyze 147 Pyrus source samples and to articulate the status of genetic diversity within Asian P. calleryana and US cultivars. We hypothesized that Asian P. calleryana specimens and US cultivars would be genetically diverse and would show genetic relatedness. Our data revealed high genetic diversity, high gene flow, and presence of population structure in P. calleryana, potentially relating to the highly invasive capability of this species. Strong evidence for genetic relatedness between Asian P. calleryana specimens and US cultivars was also demonstrated. Our data suggest the source for P. calleryana that have become naturalized in US was China. These results will help understand the genetic complexity of invasive P. calleryana when developing management for escaped populations: In follow-up studies, we use the gSSRs developed here to analyze P. calleryana escape populations from across US. Genetic diversity and population structure of any species are important factors for determining the long-term survival of the species and their adaptation to environmental changes . The popPyrus calleryana Decne., Callery pear, is a species of pear tree native to eastern and southern China, Taiwan, Korea, and Japan ) among populations was estimated using GenAlEx [The genetic diversity indices across the 18 gSSRs and 4 population groups were calculated using R with packages ierfstat  version ierfstat  version le size) ,54. Gene GenAlEx  version P. calleryana dataset (n = 57) was used to determine the phylogeographical signal within populations as RST does not depend on GPS coordinates, whereas, only the individuals with known GPS coordinates of origin  were used to determine the phylogeographical signal among populations.In order to assess the contribution of mutation rate to the population structure, SPAGeDi performed the permutation tests to determine the phylogenetic distance between individuals using 10,000 permutations among alleles within each locus and to determine the significance of inbreeding coefficients using 10,000 permutations among gene copies . For manpoppr with 1000 permutations in order to evaluate the molecular variance partitioning within and among the population groups. Linkage Disequilibrium (LD) of the used gSSRs was determined in poppr, with significance assessed using 1000 permutations. The pairwise index of association (d) was calculated using permutation approach to assess whether the loci were linked and to ensure that the observed pattern of LD is not due to a single pair of loci [Analysis of Molecular Variance (AMOVA) was performed using the package  of loci .n = 28; ade4 [vegan [Samples with known GPS coordinates n = 28;  were ana28; ade4  version 4 [vegan  version Structure  [P. calleryana dataset utilizing a Bayesian clustering algorithm. Genetic clusters among the P. calleryana individuals were inferred using 30 independent Monte Carlo Markov Chains (MCMC) with 250,000 generations of burn-in period and 750,000 MCMC steps in the actual runs for each used number of clusters (K = 1 to 10). Structure results were then visualized with PopHelper [2 statistics whose values range from 0 (recent divergence of predefined populations or a lot of migration/admixture between populations) to 1 (strong diversification and/or population structure) [2.ructure   version opHelper  version opHelper . ObStrucopHelper  version ructure) . One-taiP. calleryana dataset was also analyzed using model-free multivariate clustering approach, Discriminant Analysis of Principal Components (DAPC) using the package adegenet [P. calleryana originating populations. A separate DAPC analysis was also performed for USA cultivars only.The population structure of the adegenet  version adegenet  among P.Pyrus × bretschneideri draft genomes. Marker polymorphism was determined based on allelic variation within each genome or across the three genome assemblies. SSR mining and primer design resulted in 105,557 SSRs with acceptable primers and of these, 90,987 were dinucleotide, 10,913 were trinucleotide, and 2891 were tetranucleotide repeats. Primers between 59 to 60 °C with <1 °C difference between forward and reverse primers melting temperatures resulted in the discovery of 15,269 single motifs monomorphic SSRs along with 306 single motifs polymorphic SSRs. Only single motifs polymorphic SSRs were considered for the further analysis. In the single motifs polymorphic SSRs collection, AG was the most frequent dinucleotide motif and AAG was the most frequent trinucleotide motif  D.A.Webb genome GCF_902201215.1 [After gSSR mining with GMATA and execution of additional in-house scripts, a total of 115,838 SSRs were discovered from three de motif . For theanalyses . Genomic201215.1   and P. amygdaliformis (89%). The developed gSSRs performed well in Malus rockii (67%). Additionally, the gDNA samples that failed to amplify in P. gharbiana, P. korshinskyi, P. regelii, and P. × hybrid  samples using our gSSRs were successfully amplified using both ITS and rps16 primers .Among the four populations, the average Shannon-Wiener Index of MLG diversity (H) was 4.04, indicating high genetic diversity in the genotypic dataset . The aved = 0 to 0.4, p-value = 0.113) indicates no linked loci and suggests distribution of gSSRs across the genome  calculated in the locus-wise manner was 4.70, ranging from 2.74 (PyC050) to 6.22 (PyC031), suggesting a high long-term adaptability and persistence potential of the P. calleryana populations. There was a moderate observed heterozygosity across 18 gSSRs overall (Ho = 0.34) ranging from 0.03 (PyC050) to 0.93 (PyC038). In addition, there was a high expected overall heterozygosity (He = 0.81) across all loci ranging from 0.41 (PyC050) to 0.92 (PyC031 and PyC017). The overall Ho < He implied the presence of population structure within our P. calleryana collection. Furthermore, the dataset indicated high gene flow across all gSSRs with an overall value of 1.79.Across the dataset, an average of about 12 alleles per locus (ranging from 5 to 20) were detected . The meaP. calleryana dataset, SPAGeDi was implemented, using 10,000 permutations among alleles within each locus. The mean permuted RST over all loci was not statistically different from FST in accordance with the expectations of this test, and the observed RST was bigger than the observed FST (Pobs > exp = 0) indicating the presence of phylogeographic signal within populations (data not shown). Furthermore, the slope test of pairwise RST was evaluated in both linear and logarithmic forms to assess the phylogeographic signal among populations. From this slope test, we found no evidence of phylogeographic signal among populations (Pobs > exp = 0.95). Only the samples with available GPS coordinates (n = 28) were used for the slope test, thus creating a possible bias in this analysis.For the assessment of phylogeographic signals within the p < 0.001) indicated the existence of population structure within the genotyped collection of P. calleryana.AMOVA was used to investigate the partitioning of the molecular variance. It suggested a low proportion of total molecular variance among populations (6.2%), with more than half of the total molecular variance partitioned within individuals (63.5%) . SignifiP. calleryana collection. Isolation by distance analysis using the Mantel test yielded no evidence of correlation between genetic and geographic distances among the analyzed P. calleryana individuals of Asian origins  . Additionally, there was a non-linear relationship of the genetic and geographic distances across the space  . The parhe space b. The amStructure indicated two genetically distinct clusters (ΔK = 2) in the genotyped P. calleryana dataset  was 0.42 ± 0.07 suggesting moderate divergence among the predefined populations and Structure-derived genetic clusters within the dataset. The information on the contribution of sampled and inferred populations to the observed structure of P. calleryana was derived by changes to R2 using iterative successive removal of the pre-defined populations and the inferred clusters using ObStruct  in R2 indicating that this population contributed the most to the population structure from among those analyzed. Additionally, the removal of the “Japan” population caused increase  in R2 which suggests that this population was of mixed ancestries and contributed the least to the population structure. Furthermore, removal of the inferred clusters resulted in no major changes in R2 indicating no major contribution of the inferred clusters to the structure within the data. In addition to this, the overall R2 between predefined and inferred clusters of the P. calleryana dataset (when K = 4) was 0.41 ± 0.02, again with no major changes when sequentially removing the pre-attributed or the inferred groups  and allelic richness, and the presence of population structure in P. calleryana. A similarly high level of genetic diversity was found in P. calleryana (He = 0.639) using 14 nSSRs to study 77 individuals [Ambrosia artemisiifolia (He = 0.776) using 13 gSSRs and 13 expressed sequence tag SSRs (EST-SSRs) to study 321 individuals [P. calleryana populations compared to other invasive species such as southwestern Puerto Rico’s invasive tree [Albizia lebbeck with He = 0.27, or southeastern US invasive species [Pueraria lobata with He = 0.25.The genetic diversity, allelic richness, and gene flow patterns of any plant species are related to their ecology and evolution ,78,79. Iividuals  and in Aive tree , Albizia species , PuerariP. calleryana populations across the species’ native range. Irrespective of the geographical barriers, high gene flow could be a possible reason for this species’ invasiveness because gene flow promotes evolution through the spread of new genes or mixture of genes throughout the range of species [A. lebbeck and Fallopia species. Such a high gene flow rate promotes exchange of genes among populations especially in self-incompatible species by providing seeds for more population growth and colonization of new habitats [P. calleryana has been able to maintain population structure with high genetic diversity. The individuals of a particular cultivar have the same self-incompatibility genotype and cannot produce fruits. However, if the rootstock is allowed to sprout then that rootstock can cross with genetically different scion resulting in fruit set with mixed cultivar types [P. calleryana dataset which could support the seeds or pollen as the far-reaching mechanism of dispersal.We recorded high gene flow among  species . The hig species ,85 such habitats . As an oar types . AdditioP. calleryana, flowers are indiscriminately visited by various generalist pollinator species and the pollen is often carried among neighboring cultivars, resulting in intraspecific hybridization [P. calleryana seedlings were found with almost no genetic similarity to nearby mature trees, implying that those seedlings might have originated from foraging birds’ defecation [Pyrus species [P. calleryana maintain high genetic diversity and high gene flow rate, aiding in the continued spread of the species by providing environment-specific genotypes needed to adapt to a varied environmental condition [In dization . Seeds cdization . In a prfecation . In addi species , as implondition .P. calleryana collection suggested the existence of population structure. Pears are expected to undergo random mating, but an unexpected positive result for the inbreeding coefficient (FIS) values was found in our study indicating the probability of alleles coming from a common ancestor. A similar positive FIS result was found in a study in P. calleryana in China [IS result could be that the sampled individuals might have experienced some human interferences, such as selection, propagation, and intentional transportation resulting in the escape of cultivation in the USA. Other explanations could be the insect pollination with limited pollen flow creating local population structure, or the selection of loci under negative selection by chance, where any mutation would be lethal. Studies testing this phenomenon in the escaped P. calleryana populations are underway.High genetic differentiation found in our in China , where tP. calleryana dataset collection. Our result is unlike the Mantel test result obtained for wild P. calleryana from China [P. calleryana, DAPC result, unrooted neighbor-joining tree, and bias of Structure towards k = 2 [P. calleryana dataset. Almost all P. calleryana individuals throughout all populations showed extensive genetic admixture, in agreement with the detected high gene flow among populations. The individuals from “China” and “USA” population groups had relatively higher assignment probability to the major genetic clusters. Furthermore, genetic distances of “China” and “USA” populations placed them close to each other. Thus, our results support the historical import records of P. calleryana from China to the USA [Our study did not indicate geographic distance as the major factor contributing to the genetic structure of the populations. A non-significant correlation between genetic and geographic distance could be a result of the small size of our om China . In addids k = 2 ,87, we a the USA  with theP. calleryana cultivars using P. calleryana as a common rootstock. We expected at least some clones within the “USA” P. calleryana individuals as such cultivars were multiplicated clonally. However, no clones within the “USA” P. calleryana individuals were found, as each “USA” P. calleryana individual was unique with no shared MLGs within this population. Our study also found no identical cultivars although named the same from the source institutions. In such case, ‘Trinity’ cultivar of one source is genetically different from ‘Trinity’ cultivar of another source. Such a great genetic composition and diversity with no clones in our “USA” P. calleryana individuals signifies the great invasive potential of the species, and alarms about the level of the previously noted cultivar mislabeling and mishandling [P. pyrifolia and 7 from Malus × domestica on 14 P. calleryana cultivars [The historical events suggest the development of handling ,88. Our P. calleryana collection suggests the high potential of the species for evolving resilience and ability to thrive in a variety of environmental conditions. In addition, the high gene flow among P. calleryana populations creates the complex genetic admixture, adding more challenge to their control. For the development of measures for improved control, it is necessary to study in detail the genetic composition and diversity, and to infer the evolutionary potential of the species across the introduced ranges. Considering the ultimate goal of well-informed control measures, we are already taking the next steps in analyses of the naturalized P. calleryana: the fine-scale study of P. calleryana in localized area of the USA using the gSSRs developed here, and the broad-scale study of P. calleryana across the USA using reduced-representation genotyping-by-sequencing. Thus, P. calleryana populations across the USA provide a great prospect for further research and study, to better understand the spread mechanism of this invasive species.The high level of genetic diversity within the investigated P. calleryana native populations that are likely to be contributing to its invasive capability within introduced range in the USA. This tree species has been able to maintain high genetic diversity, which has helped it survive and adapt under diverse environmental, physical, and geographical conditions. The genetic complexity of the species adds complications to efforts at managing naturalized populations and mitigating further spread. The evidenced mishandling of the cultivars likely contributed to enabling the species spread in the naturalized range. In order to limit the cultivar mishandling, we suggest nursery professionals to verify their cultivars with the original ones or to maintain only one/few properly identified cultivars per station, and to consider the high genetic diversity of P. calleryana in large scale production of P. calleryana saplings. Further molecular and remote imagery research is underway to better understand the mechanisms behind the observed spread of P. calleryana across the USA.Our study has highlighted factors in


While some of these FST values may appear extreme, we demonstrate that they are found across the entire phenome in the GWAS catalog. This framework demonstrates that investigation of admixed populations harbors significant advantages over GWAS in single-ancestry cohorts for uncovering the genetic architecture of traits and will improve downstream applications such as personalized medicine across diverse populations.Genome-wide association studies (GWAS) are primarily conducted in single-ancestry settings. The low transferability of results has limited our understanding of human genetic architecture across a range of complex traits. In contrast to homogeneous populations, admixed populations provide an opportunity to capture genetic architecture contributed from multiple source populations and thus improve statistical power. Here, we provide a mechanistic simulation framework to investigate the statistical power and transferability of GWAS under directional polygenic selection or varying divergence. We focus on a two-way admixed population and show that GWAS in admixed populations can be enriched for power in discovery by up to 2-fold compared to the ancestral populations under similar sample size. Moreover, higher accuracy of cross-population polygenic score estimates is also observed if variants and weights are trained in the admixed group rather than in the ancestral groups. Common variant associations are also more likely to replicate if first discovered in the admixed group and then transferred to an ancestral population, than the other way around (across 50 iterations with 1,000 causal SNPs, training on 10,000 individuals, testing on 1,000 in each population,  Genome-wide association studies (GWAS) have allowed for significant progress in the field of human complex traits. However, groups with multiple ancestral origins have seldom been a primary focus in large scale genetic studies because: (1) admixed groups, along with other non-European populations, have largely been underrepresented in GWAS designs in the past , and (2)SLC24A5; In addition, complex traits in admixed groups potentially harbor differing genetic architectures and varying environmental exposures compared to most widely studied groups such as Europeans. Some biomedical traits have higher risk prevalence in admixed groups, such as prostate cancer in African Americans , asthma APRICOT, Admixed Population poweR Inference Computed for phenOtypic Traits, a flexible mechanistic model, to address the question of power across a range of realistic scenarios of genotypic and ancestry-associated contributions. With APRICOT we compared an admixed population to a similar-sized ancestral population on its own across a range of allelic differentiation  in an admixed population of interest.where n) of LD-independent loci to form a nN local ancestry matrix, where N is the proposed sample size.The local ancestries, i.e., the source of ancestry of both the maternal and paternal copies of haplotypes at any genomic position, can be obtained from a binomial sampling with the probability equaling the global ancestry. The process is repeated independently for diploid chromosomes over a presumptive number  from a beta distribution under the Balding–Nichols model  with a gp_s is the allele frequency at an independent locus s in an ancestral population prior to the divergence and drawn from a uniform distribution unif. Within the model we additionally provide additional distributions if the focus is not on common variants as it is here. We set FST as a flexible value to increase from a baseline genome-wide FST when the ancestral allele becomes rare. This is to reflect that a rarer variant in the ancestral population is easier to drift to different frequencies in diverged populations, especially if one population has undergone a severe bottleneck (as would be expected to increase FST).where FST_G is the genome-wide background FST between the two populations of ancestral origin and is considered lower than the FST between trait-causal loci because of the difference in directional selection. MAFa is the MAF of the variant in ancestral populations and δ is the increment with regard to MAF decrease, set as 0.3 in this study. Alternatively, we also test for fixed FST under the genome-wide background value when exploring the effect on power from various FST values ranging from 0.1 to 0.9. The genotypes are then drawn from binomial sampling using the allele frequency corresponding to the local ancestry assigned at the locus  across all loci.where w out of the total n loci to be causal variants, where w is the proposed polygenicity of the trait. The weights for the causal variants are drawn from a standard normal distribution N, and the signs of the weights are tied to the prevalence of the allele in the two populations of ancestral origin: the direction of the weight, positive or negative, at a locus is decided by the binary outcome of trial with probability We randomly assign The non-genetic component is treated as the sum of two parts in admixed populations: (1) random environmental variation modeled as Gaussian noise and (2) environmental confounders correlated with ancestry, such as socioeconomic status and education, modeled as ancestry by environment interaction. Details are described in For quantitative traits, the phenotype is the direct sum of the genetic component  and the non-genetic score. For dichotomous traits, the phenotype is converted from the sum of genetic and non-genetic scores to binary case and control status based on the given liability threshold of the case prevalence.p-value above a given stringency threshold.Association between the trait and a variant is tested via a linear regression for a quantitative trait, or a logistic regression for a dichotomous trait in all three populations. The global ancestry is corrected in the admixed group. Power is defined as the proportions of causal variants with a significant p-values. This is calculated separately in each population. The background FST  between the source populations was set to a constant 0.2, while a range of FST from 0.1 to 0.9 at trait causal loci that reflect trait divergence were tested. Other parameters were set as standard as described in the result section, with 100 causal variants, heritability 0.5, and environment by ancestry effect modeled as the sum of ancestral Gaussian environmental noise proportional to global ancestry. Each set of parameters was run with 50 repetitions.A false positive rate in association tests is verified against the association stringency by calculating the proportions of non-causal variants being discovered with significant association ST at 0.2 and an increment associated with the rarity of the ancestral MAF, and other parameters the same as standard as above. We then used these weights to estimate PRS in another 1,000 individuals in each population as a test. We tested the PRS construction in two ways: firstly, we only used significant (p < 0.05) causal-variants from the training set (true positives); secondly, we included all significant variants  over a range of different stringency . The true PRS of the individuals in the test set were available through an intermediate step in the simulations , causal variants by conducting association analyses in 10,000 individuals in each simulated population . The simulations were run with 1,000 causal variants, Fulations  and wereST  only.We used the full NHGRI-EBI GWAS catalog “All associations v1.0”  to extraST  between ST , and to avoid spurious associations . To induce a difference between ancestral phenotypic distributions and a correlation between a trait and global ancestries, we tied the direction of effect sizes to the minor allele frequencies in the two populations of ancestral origin  is modeled as ancestry-weighted Gaussian noise, we explored an alternative where we model Env × Anc as linearly dependent on the ancestry percentages, which would explain a range of proportions of phenotypic variance from 0% to 1 - h2 . The pow1 - h2 .ST at causal variants (N = 877) have at least one associated variant beyond the background FST of 0.155  relative to the admixed population. The proportion of significant signals that replicate in the reciprocal group is asymmetric between the two populations. Discovery in the admixed samples was more likely to replicate in Population 1 than the other way around, and this trend becomes more exaggerated as trait Fr between the estimated values and the true value in each test group across 50 repeats of simulations. Interestingly, the prediction accuracy is also asymmetric between admixed and homogenous samples. When we constructed PRS using only true positive signals at an alpha of 0.05, the accuracy of estimating PRS in Population 1 or 2 using weights and loci trained from the admixed population is significantly higher than the other way around. This holds true when using all  positive signals at various stringency levels  constructed from discovered loci with MAF > 5% in each population by increasing the sample sizes of the training set to 10,000 per population and separately estimating the GWAS-based PRS in an additional testing set of 1,000 samples in each population. We measured the PRS accuracy as the correlation coefficient y levels , suggestAPRICOT, demonstrated that GWAS in admixed populations has greater power for discovery than in the homogenous populations of ancestral origin, given the same sample sizes. The difference in power increases when the trait is under more differentiated polygenic selection in the two populations of ancestral origin, reflected by FST. This is because when a trait is driven by more-differentiated variants, its causal variants are likely to be pushed to more extreme allele frequencies, thus weakening the statistical power of discovery in that population. In contrast, the frequency of the same causal loci in admixed populations likely have become more intermediate due to variation in ancestries, making them much easier to detect. An extreme yet classic example that echoes with the observation would be skin pigmentation, where selection is in the opposite direction in populations at high latitude and those living near the equator. A non-synonymous, skin-lightening mutation at rs1426654 is fixed in European descendants, with a high FST of 0.985 between CEU and YRI. This mutation would never have been discovered through GWAS if analyses were only conducted in European populations, but it is highly detectable through association analyses in admixed populations  and epistasis , could pulations . Additioulations . For varulations . Second,Despite the underrepresentation of admixed groups in large GWAS, recent research has highlighted the importance of conducting genetic research with more diversity. Our work joins burgeoning efforts to quantify the statistical benefits of complex trait studies in diverse populations, especially populations of mixed ancestry. Our work suggests another advantage for conducting genetic studies in admixed populations, which comes from elevated allele frequencies when traits are moderately to highly differentiated. Moreover, discoveries from such studies aid improvement in cross-population PRS, which is critical in clinical prediction in personalized medicine yet presently has suboptimal performance for many biomedical traits in non-European populations . We therftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/; Software availability: https://github.com/menglin44/APRICOT.Publicly available datasets were analyzed in this study. This data can be found here: 1000 Genomes Project: ML conducted analyses with supervision from BH and CG. ML, BH, and CG wrote the manuscript with algorithmic insights from DP and NZ. All authors edited and approved the submitted version.The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Anopheles arabiensis is a member of Anopheles gambiae complex and the main malaria vector in Sudan. There is insufficient population genetics data available on An. arabiensis for an understanding of vector population structure and genetics, which are important for the malaria vector control programmes in this country. The objective of this investigation is to study the population structure, gene flow and isolation by distance among An. arabiensis populations for developing control strategies.An. gambiae microsatellite loci primers were used to amplify the DNA of An. arabiensis samples.Mosquitoes were collected from six sites located in three different states in Sudan, Khartoum, Kassala and Sennar, using pyrethrum spray catch of indoor resting mosquitoes. Anopheline mosquitoes were identified morphologically and based on species specific nucleotide sequences in the ribosomal DNA intergenic spacers (IGS). Seven published An. arabiensis was the main malaria vector found in the six localities. Of the seven microsatellite loci utilized, six were found to be highly polymorphic across populations, with high allelic richness and heterozygosity with the remaining one being monomorphic. Deviation from Hardy–Weinberg expectations were found in 21 out of 42 tests in the six populations due to heterozygote deficiency. Bayesian clustering analysis revealed two gene pools, grouping samples into two population clusters; one includes four and the other includes two populations. The clusters were not grouped according to the three states but were instead an admixture. The genetic distances between pairs of populations ranged from 0.06 to 0.24. Significant FST was observed between all pairwise analyses of An. arabiensis populations. The Kassala state population indicated high genetic differentiation (FST ranged from 0.17 to 0.24) from other populations, including one which is also located in the same state. High gene flow (Nm = 1.6–8.2) was detected among populations within respective clusters but limited between clusters particularly with respect to Kassala state. There was evidence of a bottleneck event in one of the populations (Al Haj Yousif site). No isolation by distance pattern was detected among populations.PCR confirmed that An. arabiensis populations investigated in Sudan, with the exception of Kassala state.This study revealed low levels of population differentiation with high gene flow among the  Anopheles have been recognized globally and, of these, 41 species can transmit malaria but only a few of them are malaria vectors [Anopheles arabiensis [Anopheles gambiae and Anopheles funestus are the major vectors of malaria and their vectorial capacity may be similar to that of An. arabiensis [. This species is a highly adaptable species with the capability to feed on multiple host species, both indoors and outdoors and acclimatize to a wide range of larval habitats [An. arabiensis. Thus, there is an urgent need for effective and sustainable alternatives to these traditional vector control strategies.In Sudan, malaria remains as one of the most important public health problems. More than 400 species of abiensis –9. Howevhabitats , 11. At habitats , 13, butAn. gambiae complex [Microsatellites are genetic markers of short tracts of tandemly repeated DNA sequences. These markers have become the genetic marker of choice for studying the population genetics of many eukaryotic species, including mosquitoes. For instance, they have been widely utilized in such studies in the  complex –20. They complex .An. gambiae sensu lato (s.l.) [An. gambiae complex [An. gambiae with some limited data on An. arabiensis. Present literature on An. arabiensis has revealed the lack of subpopulation differentiation in relation to larval habitat utilization [To date, 150 polymorphic microsatellite loci have been characterized in o (s.l.) , 22, whi complex –25. Mostlization . Lack oflization , 26. Larlization  have beelization  among vilization  from Weslization  of Eastelization , 23, resAnopheles arabiensis has changeable deme sizes ranging from as low as 25 km [An. arabiensis mosquito densities decrease with increasing distance from the scheme [as 25 km  to a fewas 25 km . It was e scheme , 31. On e scheme  in addite scheme  by this e scheme . Such ale scheme  and can e scheme –36 as wae scheme  in the iAn. arabiensis and An. gambiae have shown a higher level of genetic differentiation in the latter species. Significant genetic differentiation, FST = 0.072–0.100 were observed for An. gambiae populations between western Kenya and coastal Kenya using microsatellite markers. Lehmann et al. [An. arabiensis populations from the two areas using the same loci [An. arabiensis populations in Malawi and Sudan. It thus appeared that different mechanisms of gene movement were in operation between the two species. Considering An. gambiae, these studies were discordant with another study on An. gambiae sensu stricto (s.s.) (mean FST = 0.006), which was genetically non differentiated across the 6650 km2 of the Kilombero valley landscape southern Tanzania. This suggested that the genetic differentiation in other populations was not due to physical barriers or distance. One plausible explanation is that there was environmental diversification even within the Kilombero valley [An. gambiae could have been maintained by some degree of reproductive isolation.Several comparative population studies between n et al. , 36 suggame loci . Similarame loci  noted noo valley . Thus, tAn. arabiensis, several studies have reported varying levels of genetic differentiation. Nyanjom et al. [ST but statistically significant genetic structure for An. arabiensis populations in Ethiopia and Eritrea. On the other hand, Simard et al. [An. arabiensis populations that were 240 km apart in the Indian Ocean (FST 0.080–0.215). High levels of genetic differentiation were also detected among An. arabiensis populations (mean FST = 0.066) in Kilombero valley southern Tanzania [With respect to m et al.  detectedd et al.  reportedTanzania .An. arabiensis populations in Sudan based on microsatellite markers which may assist in developing control strategies.Therefore, the objective of this investigation was to study the population structure and gene flow among An. arabiensis were collected from June 2010 to May 2011 from six different localities in Sudan representing different ecological zones separated by the River Nile and its tributaries  [Anopheles was conducted using the DNeasy blood and Tissue E kit . Seven published An. gambiae microsatellite loci primers [2 and 0.5 U Taq DNA polymerase  in a 20 uL total reaction volume. Singleplex PCR amplification was conducted for loci AGXH678, AG2H290, AG2H603, AG2H143, AG3H29, AG3H45, AG3H158 (Table Molecular classification of rs (IGS) . DNA ext primers  were useAllelic data scoring of alleles was carried out by inspection of the electrophoretograms as described in Arif et al. . Two welR), adjusted for different sample size and number of alleles (NA). To test for global deviation from HWE in a population, the inbreeding coefficient, (FIS) for each locus and population [HO) and expected (HE) heterozygosities per locus and population were estimated over all loci. Testing of deviation from Hardy–Weinberg equilibrium (HWE) was conducted using the exact tests with 10,000 steps in Markov chain and 10,000 dememorization steps in Arlequin version 3.11 [Population genetic diversity was measured based on allelic richness  which hypothesizes that each new allele is generated at a given rate, µ [Estimates of population differentiation, using Wrights FST  over all rate, µ .The program BOTTLENECK V 1.2.02  was usedAssignment of individuals to their respective source populations based on multilocus genotypic data was determined in STRUCTURE version 2.3 . An assuAn. arabiensis in Sudan were successfully genotyped and scored for all seven microsatellite loci. No evidence for scoring error due to null alleles, large allele dropout or stuttering was detected after assessing with Microchecker.All 200 individuals from six populations of An. arabiensis populations were found to be polymorphic in at least one population. However, locus AG3H29 was monomorphic in most populations. Loci AG2H143 and AG3H45 were moderately polymorphic with number of alleles per locus ranging from 6–12 and 4–10, respectively. The total number of alleles per locus ranged from 2 to 12 with an average of 7.6. The mean AR ranged from a minimum of 3.5 in Hj (Khartoum State) to a maximum of 6.8 in Se (Sennar State) and the means observed heterozygosity of alleles per locus ranged from 0.55 to 0.67, while means of expected heterozygosity ranged from 0.55 to 0.62 (Table All (except one) microsatellite markers of IS) over all loci showed that most of the populations had high excess of heterozygosity .Each population was tested separately for significant departure from HWE at each locus. Observed heterozygosity varied from 0.12 to 0.94 while expected heterozygosity ranged from 0.11 to 0.76 (Table CT) was contributed by ‘among groups’ variation, 13.61% (FSC) was ‘among populations within group’ variation .A hierarchical AMOVA performed after defining into three groups  revealed that 2.75% of the total genetic variance (FST) was observed between all An. arabiensis pairwise comparisons for all loci  and Se (Sennar State) (FST = 0.06) and Gw (Khartoum State) and H.sh  (FST = 0.08). However, high genetic differentiation was observed between An. arabiensis populations from Kr and other populations FST = 0.17–0.24 including with H.sh which is also in the same state of Kassala. Thus, although the detailed magnitudes of population differentiation vary among population comparisons in the various analyses, in summary Kr is most distant or differentiated from other populations and followed by Se to a certain extent for several pairwise comparisons.Significant differentiation among populations, , FST ranged from 0.019 to 0.20 with mean FST = 0.16. Gene flow (Nm) for loci outside the chromosomal inversions ranged from 1.04 to 43.52. The highest gene flow was between My and H.sh with Nm = 43.52, while little gene flow was found between Kr and Hj with Nm = 1.04. For loci inside the fixed chromosomal inversion, 2La, a range of Nm = 1.38 to 19.99 was observed, with the highest gene flow between Se and My with Nm = 19.99, while little gene flow was detected between Se and Kr with Nm = 1.38.Gene flow (Nm) calculated from mean FThe Wilcoxon test Table  indicateST, between the different populations, Mantel tests showed no significant correlation  between genetic differentiation measured as linearized FST (FST/(1 − FST) and geographic distance (km)  Fig. . Thus, gK = 2 revealed two main clusters . This analysis is in general in agreement with the FST analyses where Kr and to a lower degree, Se are distant from the other populations although My is closely related to the latter. In the FST analysis, Kr and Se were also found to be genetically distant. However, the phylogenetic tree showed that only Kr is distant from the other populations. On the other hand, An. arabiensis populations from Hj, GW and H.sh; My and Se are highly related genetically , a peak at ers Fig. . The dat, a peak An. gambiae [An. arabiensis populations in Sudan. Allele number per locus ranging from 2 to 12 with an average of 7.6 alleles per locus as well as heterozygosity levels are concordant with other studies in this species conducted in Central Kenya and Madagascar [An. gambiae s.s. [An. funestus in east and southern Africa [Anopheles atroparvus [In this study, a set of seven microsatellite markers, specific for  gambiae  was useddagascar  and Eastdagascar . But higdagascar , 27. Simiae s.s. , An. funn Africa  and Anoproparvus  in southroparvus  suggesteAn. arabiensis populations in Sudan suggest the existence of population subdivision. Similarly, using a different suite of microsatellite markers for An. arabiensis in Southern Tanzania, Ng’habi et al. [Analyses of linkage disequilibrium on six i et al.  observedST values of 0.06 to 0.24 and STRUCTURE analysis of K = 2, divided the six populations into two groups; comprising of Kr  and Se (Sennar State) in one group and H.sh, My, Hj and Gw  in another The FST from pooled loci reported in this study was in concordance with the reported FST values for An. arabiensis from Ethiopia and Eritrea [ST but statistically significant genetic structure in An. arabiensis populations. However, Donnelly and Townson [An. arabiensis populations within Malawi and Sudan. Chen et al. [An. gambiae in Lake Victoria islands (FST = 0.019) and among the six villages in the mainland (FST = 0.010). This shows that structuring pattern is influenced by numerous factors specific to the geographic locations.The population pairwise F Eritrea . Both st Townson  did not n et al.  also detAn. arabiensis involving certain populations in comparison with (Kr) in the current study, in agreement with that observed between the Reunion and Mauritius Islands (FST ranged from 0.080 to 0.215), located 240 km apart in East Africa Simard et al. [An. arabiensis populations (mean FST = 0.066) [An. gambiae s.s. (mean FST = 0.006) which was genetically undifferentiated across the 6650 km2 of the Kilombero valley landscape in southern Tanzania. Kayondo et al. [An. gambiae populations among islands in north-western Lake Victoria, Uganda with FST ranging from 0.014 to 0.105 and concluded that these populations were significantly genetically differentiated [ST values of 0.20 and 0.30 as described by Vicente et al. [ST values of 0.25 while Walton et al. [Anopheles dirus in South-east Asia reported FST value of 0.21–0.39. These studies highlight that pattern of population structuring may differ when comparing different sets of populations in A. gambiae as well as in other mosquito species.In particular, a high level of genetic differentiation was found in d et al. . Similar= 0.066) . This wao et al.  studied entiated . Similare et al. , Kamau ee et al.  observedn et al. , who stuAn. arabiensis. In agreement with this postulate, Kr which is far from any agricultural areas was instead highly differentiated from other populations. Coluzzi [An. gambiae complex and between the various forms of An. gambiae s.s. He postulated that inversions can group co-adapted gene complexes that confer adaptation in temporarily isolated peripheral populations with marginal ecological conditions. When secondary contact with the source population occurs, these inversions protect the co-adapted gene complexes from recombination, resulting in stable inversion polymorphisms and/or expansions of the population into new habitat, finally resulting in a more permanent isolation and differentiation.The high differentiation of Kr from the other populations may be due to its ecology which was far from agriculture areas compared to the rest which were near or within agriculture areas. Kr population is presumably reproductively isolated due to non-random mating or ecologically isolated as an effect of the AlGash River which acts as a physical barrier separating Kr from other populations. Hemming-Schroeder et al.  found th Coluzzi , hypotheAn. arabiensis in Southern Zambia. They observed high gene flow between Macha and Namwala populations, in Southern Zambia. This is also in agreement with Muturi et al. [An. arabiensis in Central Kenya. Failloux et al. [Aedes polynesiensis populations from islands in French Polynesia. These studies show that although the species can only fly within a limited distance, passive transportation could facilitate genetic homogeneity among distant populations.High genetic similarity between My and Hj which are geographically close to each other was observed, suggesting that they may represent a single population or gene pool. According to Francois et al. , neighboi et al. , who foux et al.  detectedAn. arabiensis from Ethiopia and Eritrea. Isolation by distance could occur due to the limited flight range of An. arabiensis [An. arabiensis along the River Nile. Thus, presumably, the differentiation could largely be due to other factors than geographic distance. A similar observation was seen within An. atroparvus [An. arabiensis and An. gambiae, suggesting that levels of genetic differentiation are not related to geographical distance and not associated to the side on which populations were sampled in relation to the Rift Valley. Chen et al. [An. gambiae mosquitoes on Lake Victoria islands, west Kenya revealed a significant correlation between geographic distance and pairwise distance. On the other hand, Failloux et al. [Aedes polynesiensis populations from islands in French Polynesia in contrast to the genetic structuring pattern of Culex pipiens quinquefasciatus from the same islands. In the latter species, genetic differentiation increased considerably (p < 0.01) with geographic distance [An. arabiensis (with the exception of Kr).The Mantel test showed no evidence of isolation by distance in this study, similar with that reported by Nyanjom et al.  in populabiensis , but thiroparvus , where nroparvus , using mn et al.  who studx et al.  found nodistance . These dAn. arabiensis populations of Sudan, except in AlHajYousif (Hj). This was evident based on the significance in Wilcoxon sign-rank test which was also supported by the “shifted mode” allele distribution. In comparison, the other populations had relatively higher rare alleles than common alleles, a sign that these populations were experiencing mutation-drift equilibrium. The situation at AlHaj Yousif (Hj) is likely due to the effective vector control programme in this area. This finding does not agree with Muturi et al. [An. arabiensis in central Kenya. They did not find any evidence of genetic bottlenecks in the area under different agricultural practices. Furthermore, there was no evidence of a genetic bottleneck in An. arabiensis despite a drastic reduction in mosquito numbers during the drought year in southern Zambia as reported by Kent et al. [An. arabiensis during the dry season but no occurrence of genetic bottlenecks apart from Hj which is under vector control programmes. Hj, My and Gw in Khartoum state have very strong programmes of malarial control, the ‘Khartoum Malaria Free Initiative’ started from 2001 to 2009. The significant achievement in malarial control in Khartoum state is highly evident. For example, the percentage of malaria cases among the followers of health services decreased from 20% in 2001 to just 3.3% in 2008 and the parasitological incidence went down from 91 to just 4 per 10,000 population. Another programme was initiated in 2011 and is due to end in 2015. The objective of this initiative is to decrease malaria mortality and morbidity. Specifically, the initiative aims to reduce malaria cases by 90% by 2015 in northern Sudan compared to the number of reported cases in 2009. However, results of this study in My and Gw did not show any reduction. This could be explained due to the resistance to insecticide. Therefore, this lack of reduction in these populations suggests that they are still expanding.No severe bottleneck or reduction in population size was detected in the i et al. , who stut et al. . This isAn. arabiensis has revealed the lack of subpopulation differentiation in relation to larval habitat utilization [An. arabiensis displays panmixia when population numbers are high, this can be reversed when inter population geographic distances are high and habitat alterations occur, leading to genetic isolation.Present literature on lization . Lack oflization , 24. Larlization  have beelization  among vilization  from Weslization  of Eastelization , 21, resAn. arabiensis populations from Kr and other populations FST = 0.17–0.24. Therefore, Kr populations were more genetically isolated from the rest and from each other. Additionally, Kr may be reproductively isolated due to non-random mating or movement of people from Ethiopia to Sudan. It could also be ecologically isolated as a consequence of the Al Gash River which acts a as a physical barrier separating Kr from other populations. Therefore, Kr is easier to control compared to other populations. High gene flow was detected among Se (Sennar State) with My and Gw (both Khartoum State); Hj and My (both Khartoum State). Very little gene flow was observed between Kr  and other populations. All populations had not experienced population bottleneck. However, population Hj with shifted mode suggest recent population size reduction. The phylogenetic tree showed that populations Hj, GW and H.sh, My and Se are genetically closely related, while Kr appeared to be comparatively differentiated from other populations.Microsatellite markers analysis showed that high linkage disequilibrium detected between loci and high genetic differentiation was observed between An. arabiensis. However, as discussed, both abiotic (e.g. passive transportation) and biotic (e.g. chromosome inversion) factors may influence the genetic structuring of mosquito species populations. As such, where possible it is recommended that an important consideration of any population genetics study is also to understand the underlying reasons for the pattern observed. More extensive studies on population structure and genetics of An. arabiensis in the other regions of Sudan using additional microsatellite loci are required to elucidate the factors that may affect gene flow for strategizing management and control of mosquito infestation in the country.This study concluded that genetic analysis revealed high population panmixia and continuous gene flow among the studied populations, without any signs of isolation apart from the Kr, presumably due to ecological barriers. The high migration rate and lack of interpopulation genetic variation among the Sudanese population was attributed to the continuous human and domestic animal movements among the studied localities that facilitated distribution of


The Isthmus of Panama was a crossroads between North and South America during the continent’s first peopling (and subsequent movements) also playing a pivotal role during European colonization and the African slave trade. Previous analyses of uniparental systems revealed significant sex biases in the genetic history of Panamanians, as testified by the high proportions of Indigenous and sub-Saharan mitochondrial DNAs (mtDNAs) and by the prevalence of Western European/northern African Y chromosomes. Those studies were conducted on the general population without considering any self-reported ethnic affiliations. Here, we compared the mtDNA and Y-chromosome lineages of a new sample collection from 431 individuals  belonging to either the general population, mixed groups, or one of five Indigenous groups currently living in Panama. We found different proportions of paternal and maternal lineages in the Indigenous groups testifying to pre-contact demographic events and genetic inputs (some dated to Pleistocene times) that created genetic structure. Then, while the local mitochondrial gene pool was marginally involved in post-contact admixtures, the Indigenous Y chromosomes were differentially replaced, mostly by lineages of western Eurasian origin. Finally, our new estimates of the sub-Saharan contribution, on a more accurately defined general population, reduce an apparent divergence between genetic and historical data. The Isthmus of Panama was an obligatory passage for the first peopling of the Americas and has served as a crossroads in the movement of people and goods ever since, also playing a pivotal role during European colonization and the African slave trade ,2,3. AccThis heterogeneity in culture and organization persisted upon the arrival of the Spaniards at the beginning of the 16th century CE, who described Panama’s Indigenous communities as spanning from small tribes to large chiefdoms, speaking different languages and trading all kinds of goods . Indigenhttps://inec.gob.pa/, accessed on 7 October 2021), the percentage of citizens who identify themselves as Afro-descendants is 9.2%, while 12.3% consider themselves Indigenous. The latter comprise seven groups (from west to east): Naso Tjër Di (or Naso), Bribri, Ngäbe, Bugle/Bokotà (or Bogotà), Guna, Emberá, and Wounaan. During the 20th century CE, the Ngäbe, Bugle, Guna, Emberá and Wounaan were granted territories, called “Comarcas”, administered by Indigenous authorities. At the end of 2020 CE, the Naso received their comarca , whereas the Bribri in the Chiriqui and Bocas del Toro provinces remain unprotected by comarca status.Beginning in the sixteenth century, European, African, and Indigenous populations converged on the Isthmus of Panama, leading to unions among people of different geographic and ethnic origins. The ensuing relations, coerced as well as consensual, often took place between European men and women of Indigenous American and, subsequently, African origins and descent. Free and enslaved members of African, Afro-descendent, and Indigenous communities also mixed in the cities, villages, and rural areas despite royal attempts to establish distinct Spanish, Indigenous, and Black towns ,19. AlthRecent genomic analyses of populations currently living in the Americas confirmed the existence of sex biases in the convergence of diverse ethnic groups following European contact and colonization ,21,22. TN = 10) or Moreno (N = 11). These groups include mostly individuals of mixed Hispano-Indigenous and African ancestries, respectively. Finally, a total of 210 Panamanians did not self-identify as affiliated with any of the ethnic categories listed above and were grouped together as representative of the general population for the purposes of the present study. Genomic DNA was extracted from saliva samples and purified either following a standard phenol/chloroform protocol or with automated extraction performed with the Maxwell® RSC Instrument from Promega Italia srl  according to the manufacturer’s protocol.A total of 475 healthy individuals were enrolled in this study, during a sampling campaign conducted in Panama starting in 2016. The biological specimens  were collected through mouthwash rinsing, using the saliva DNA isolation kit from Norgen Biotek. In addition to their informed consent, all participants were asked to provide genealogical information (for at least two generations) as well as ethnic affiliation and spoken language. These data were used to identify two generations Panamanian subjects unrelated on the maternal and paternal sides and belonging to different population groups. The final group of 431 unrelated individuals sampled  encompasEven if a deeper classification into sub-haplogroups could be achieved through a massive sequencing of entire mitogenomes and non-recombining regions of the Y chromosome, the main goal of the present work was to compare the different sources of uniparental haplogroups. To this aim, the Y-chromosome classification was achieved through a hierarchical screening of biallelic markers, while Sanger sequencing of the mtDNA control region allowed identifying informative SNPs for a correct mitochondrial classification, as in previous studies on the general population of Panama ,28.https://www.bmr-genomics.it/) through Sanger sequencing using the Brilliant Dye terminator 1.1 kit. The sequencing primers included a forward primer  for all individuals and a reverse primer  for those harboring the transition T16189C, which results in a poly-C tail causing premature termination of the sequencing reaction.The mtDNA control region was amplified through standard PCR for 475 individuals, using the following primers: nucleotide position (np) 15877 forward (5′-CAAATGGGCCTGTCCTTGTA-3′) and np 727 reverse (5′-AGGGTGAACTCACTGGAACG-3′). A segment of the control region (nps 16024–250) was sequenced at the BMR Genomics (http://www.genecodes.com/), which was also used to manually determine haplotypes. Haplogroup classification was obtained with HaploGrep2 [Electropherograms were aligned to the mitochondrial reference sequence (rCRS)  using SeploGrep2 . Most ofploGrep2 ,40. ThisploGrep2 .N = 39) or due to the poor quality of the sequencing data (N = 5).Of the 475 initially sequenced individuals, only 431  were inchttps://www.yfull.com/tree/; https://isogg.org/, both accessed on 7 October 2021) and according to [A total of 301 unrelated Panamanian males were sampled. Of these, 248 were successfully classified into Y-chromosome haplogroups , includirding to .The analysis of mtDNA molecular diversity indices was performed with DnaSp v.6 . HeterogHaplogroup frequencies and distributions for both genetic systems were compared for statistically significant differences with either the Chi-square test of independence or the Fisher’s exact test of independence, which were computed using R  and the p-distance method). Distances were calculated on both mtDNA (N = 248) and Y-chromosome (N = 248) data, using only variable sites (disregarding indels) from the sequenced control-region portion and from the tested SNPs, respectively. We calculated intra-population distances for each system by keeping only pairwise comparisons of individuals belonging to the same population group. Conversely, we used all pairwise values to compute the mean of Y-chromosome and mtDNA distances and convert it into a dissimilarity matrix, using the R functions mean and xtabs [cmdscale [Uniparental genetic pairwise distances between individuals were computed using MEGA X , as the nd xtabs . The rescmdscale .prcomp from the stats R package [CA function from the FactoMineR R package [ggplot2 [factoextra (https://github.com/kassambara/factoextra).Principal Component Analysis (PCA), on both mtDNA and Y-chromosome haplogroup frequencies, was computed using  package  with the package , as in [ package . All plo[ggplot2  and factN = 210) as well as five Panamanian Indigenous groups (N = 200): Naso, Bribri, Ngäbe, Guna, and Emberá (N = 10) and Moreno (N = 11), were represented in the final dataset.We generated mtDNA control-region data for 431 maternally unrelated individuals, which were sampled among the general population  and part of the HVS-II (nps 57–372), for a total of 796 sites, of which 161 are polymorphic. The total dataset includes 173 distinct haplotypes  and reach the highest frequencies in Guna (52.0%) and Naso (56.3%) populations. This lineage is found in one Mestizo individual and is also the most represented in the general population (26.2%).The macro-haplogroup A2 is the most represented, accounting for 51.7% of all individuals, which was followed by B2 (27.1%) and C1 (6.0%). D1 is found with the lowest frequency (1.4%) and only in the Emberá group. Non-Indigenous lineages account for 13.7% of the total, with West Eurasian haplogroups representing 2.3% and SAf haplogroups representing 11.4%. A2 could be further classified into two main sub-lineages. A2w represents 11.8% of the entire dataset and is found among the Ngäbe (43.7%), the Mestizo (60.0%), and the general population (6.7%). A2af1  is found across all Indigenous groups (except for the Emberá), even though its proportions within each particular Indigenous group are significantly different . The highest frequencies are reached in Emberá (46.9%) and Bribri (64.3%) populations. The haplogroups C1 and D1 are almost exclusively found in the eastern populations (Guna and Emberá), with D1 present only in the latter and C1 equally distributed  in both groups (≈20–22% in each population).The haplogroup B2 is found among all Panamanian populations sampled, with significant differences between the Indigenous groups  are only found in the general population (4.3%) with the exception of the previously cited R* mtDNA found in one Emberá. The Mestizo individuals do not present any European mtDNA lineage, showing conservation of Indigenous ancestries with no European contribution from a matrilineal point of view. Conversely, sub-Saharan African haplogroups are found in the general population (20.0%) and in the Moreno group (63.7%). In the latter group, showing a greater presence of mixed ancestries along the maternal line, the sub-Saharan maternal ancestries are represented by L2 (36.4%) and L3 (27.3%) lineages.A total of 248 Panamanian males were successfully classified into 25 Y-chromosome haplogroups, with three main geographic origins: Indigenous America (haplogroup Q), sub-Saharan Africa (haplogroups B-M60 and E-M2), and Western Eurasia/North Africa (the remaining haplogroups) .In agreement with previous observations ,49, the As shown in Among the admixed groups, Mestizo and Moreno present different genetic compositions reflecting their respective origins. Mestizo accounts for, in order of frequency, Indigenous American, Western Eurasian, and African contributions, while amongst the four Moreno Y chromosomes, three were E-M2 and one was J2-M172, thus identifying a predominantly African paternal ancestry (E-M2).Most individuals who self-declared Indigenous affiliations have retained an IAm paternal ancestry (80.9%). Only the Bribri differ from this trend, as six out of the eight males analyzed harbored Y chromosomes not belonging to haplogroup Q (five of European ancestry and one from Africa). The only two haplogroup Q Y chromosomes (25.0%) found in the Bribri both belong to Q-M848*. The frequency of this paragroup ranges from 33.3% in the Ngäbe and the Naso to 59.4% in the Guna. The most frequent sub-haplogroup among Indigenous groups is the Isthmo-Colombian Q-Y12421, which reaches its highest frequencies (≈31%) in the Guna and the Naso. Other clades highlight a number of differences between IAm populations: (i) the Q-Z780 sub-haplogroup Q-SA02 is only observed in western groups (Naso and Ngäbe), while all the Q-Z780 remain classified as Q-Z780* in the Emberá (from the eastern part of the country); (ii) no Q-Z780 Y chromosomes were identified in the Guna; (iii) Q-M925* is almost exclusively found in the Ngäbe with the exception of one Guna.tot) and the Indigenous haplogroups only (HHgQ). Htot values reveal that Indigenous groups are almost as heterogeneous  as the admixed general population (H = 0.883), with the only exception of the Guna (H = 0.565). On the other hand, HHgQ values show that, apart from external contributions, a certain diversity of the IAm component is maintained in all Indigenous groups.Heterogeneity values were calculated for each group considering both the totality of the observed haplogroups . The mtDNA haplogroup frequencies for this dataset are summarized in To compare Y-chromosome and mtDNA data, we first restricted the total mtDNA dataset of 431 individuals to the one used for Y-chromosome analyses . We did not find any statistically significant difference when comparing the mtDNA haplogroup distribution between the two datasets  and much lower for the Y-chromosome (13.4%). This trend is confirmed in other population contexts around the Isthmus, such as Mexico ,63,64,65p-value < 0.001 for both systems). Indeed, mtDNA haplogroup A2w, previously found in North and Central American modern individuals [Another outcome of the present work is the similarity between the two systems with respect to the significant difference in the haplogroup distribution among the Panamanian Indigenous groups . This cluster is only clear on the maternal side because of the matriarchal organization of many Indigenous groups, which leaves open the possibility of male introgressions of non-Indigenous lineages. In the eastern Isthmus, the Guna, who preserve the greatest traces of the newly defined autosomal ancestry UPopI, show a major legacy of very ancient uniparental footprints, the previously defined mtDNA haplogroup A2af1, and the Y-chromosome paragroup Q-M848*, while the Emberá show traces of inputs from the south . These different footprints are still evident mostly in the mitochondrial gene pool because the matrilineal lines of Indigenous populations were only marginally involved in post-contact admixtures.A cultural implication of our findings is that the individuals who participated in this study declared themselves as belonging to Indigenous groups with reference to both sides of their genealogies, unaware of the non-Indigenous male components among their ancestors and confirming their matrilineal identifications. As for the post-contact input, we have confirmed a sex bias introgression of only paternal non-Indigenous lineages into local communities, but our findings also updated previous assessments concerning sub-Saharan African genetic input in post-contact times. Here, our new estimates regarding the general population, defined more accurately as individuals not identifying as members of any specific population group, contribute to solving an apparent discrepancy between genetic and historical data. However, this and other issues should be further investigated and directly tested through the analyses of (admixed) ancient genomes from colonial times. The importance of the ancient DNA analysis was already proved by our archaeogenomic analysis on the Isthmus of Panama , as well


D statistics analyses showed that the Irabu/Ikema subpopulation received gene flows different from those of the Miyakojima subpopulations, which may be related with the historically attested immigration during the Gusuku period (900 − 500 BP). A coalescent-based demographic inference suggests that the Irabu/Ikema population firstly split away from the ancestral Ryukyu population about 41 generations ago, followed by a split of the Miyako southwest population from the ancestral Ryukyu population (about 16 generations ago), and the differentiation of the ancestral Ryukyu population into two populations (Miyako northeast and Okinawajima populations) about seven generations ago. Such genetic information is useful for explaining the population history of modern Miyako people and must be taken into account when performing disease association studies.The Ryukyu Archipelago is located in the southwest of the Japanese islands and is composed of dozens of islands, grouped into the Miyako Islands, Yaeyama Islands, and Okinawa Islands. Based on the results of principal component analysis on genome-wide single-nucleotide polymorphisms, genetic differentiation was observed among the island groups of the Ryukyu Archipelago. However, a detailed population structure analysis of the Ryukyu Archipelago has not yet been completed. We obtained genomic DNA samples from 1,240 individuals living in the Miyako Islands, and we genotyped 665,326 single-nucleotide polymorphisms to infer population history within the Miyako Islands, including Miyakojima, Irabu, and Ikema islands. The haplotype-based analysis showed that populations in the Miyako Islands were divided into three subpopulations located on Miyakojima northeast, Miyakojima southwest, and Irabu/Ikema. The results of haplotype sharing and the  Within Japan, there are two different clusters, the Hondo cluster on the Japanese Archipelago and the Ryukyu cluster on the Ryukyu Archipelago . By narrUnderstanding the regional population structure is also important for medical and human genetic research. Genome-wide association studies (GWAS) have identified many genetic loci associated with disease traits , but, onInsular regions are different from continents with respect to human migration and show a characteristic population structure. Because human migrations to islands are geographically restricted, most island populations are small and historically isolated. These populations might experience strong genetic bottlenecks and show relatively unique and uniform genetic backgrounds which differ from those of other populations. GWAS has been shown to be useful for identifying novel variants associated with disease traits in isolated populations, since unique variants with large effect might be conserved in these isolated populations under specific circumstances .In this study, we examined the genotypes of people in the Miyako Islands using genome-wide SNPs arrays as a part of the Okinawa Bioinformation Bank (OBi) Project, and we revealed that the population in the Miyako Islands was divided into three subpopulations.n = 498), aboriginal Taiwanese , and ancient Japanese (Jomon)  plot of 1,098 individuals obtained by OBi project using 491,109 SNPs that passed the quality control criteria formed several genetic clusters for individuals from the Miyako Islands, Okinawajima, and Japanese Archipelago (Hondo) . We plot (Jomon) . In this (Jomon) . We obseFST values between Miyakojima and Irabu/Ikema subpopulations were larger than those between two local subpopulations in Miyakojima  segments  online. We examined the haplotype sharing profiles between each Miyako subpopulation and populations from the 1000 genomes project  online. D statistics provide information about gene flow among the focal populations. We tested D  for JPT, CHB, Okinawajima, or Jomon as the source population . Among them, the Z score of D  was the highest  program can estimate effective migrations between neighboring demes based on the stepping-stone model . Since MIKM, 95% CI: 38–57), followed by a split of the Miyakojima southwest population from the ancestral Ryukyu population about 16 generations ago , and the differentiation of the ancestral Ryukyu population into two populations (Miyakojima northeast and Okinawajima populations) about seven generations ago . Since, the 95% CI for the point estimation of TDIVIKM did not overlap with that of any other point estimation, namely TDIVOKI, TDIVMYSW, we thought the order of the split event for the Irabu/Ikema population from the ancestral Ryukyu population was confirmed to be the most ancient. In contrast, the 95% CIs of the latter two split times, TDIVOKI and TDIVMYSW, were found to overlap, and we were unable to confirm the order of these two events exactly. Although we induced epochs for the population size change in the Irabu/Ikema population in this simulation, we did not observe the population bottleneck identified in the IBDNe analyses. Instead, an increase in the population size was observed about ten generations ago . Furthermore, we assumed recent migrations among the Ryukyu populations, and among them, a parameter for the migration between Okinawajima and Miyako northeast showed the highest in point estimation .Assuming a demographic model, we estimated the parameter values and their 95% confidence intervals (CI) by a coalescent simulation using fastsimcoal2 . In the Based on haplotype information collected through the OBi Project, we have demonstrated the fine-scale genetic structure of the Miyako Islands for the first time. Although previous studies clarified the genetic differences between the Hondo and Ryukyu people  and diff2), although the signal continuity of haplotype structures exists and absolute genetic differentiation among these subpopulations, especially two Miyakojima subpopulations is very low , which were merged to the Miyakojima government. Because the genetic distances among the different subpopulations were nearly correlated with geographic distances, we defined the three subpopulations as Miyakojima northeast (Hirara and Gusukube), Miyakojima southwest (Shimoji and Ueno), and Irabu/Ikema subpopulations. The exception is the Nishihara settlement in the Hirara locality which does not belong to the Miyakojima northeast subpopulation but rather to the Irabu/Ikema subpopulation.Based on information in the literature, the Nishihara settlement was established by immigrants from Ikema Island in 1873 . Thus, oP < 0.001), providing further evidence for a specific population bottleneck in the Irabu/Ikema subpopulation.By IBDNe program, we estimated the current effective population sizes for all the Miyako Islands, Irabu/Ikema, Miyakojima northeast, and Miyakojima southwest as 29,800, 12,600, 13,600, and 2,260, respectively. Since recent census population size of the Miyako Islands is about 55,000 and estimated effective population size of all Miyako population is broadly agree to the recent census population size. However, it has been reported that a strong population bottleneck event might influence the accuracy of the estimated population size at older generation periods in IBDNe program: The information for the remaining few haplotypes after the bottleneck event is insufficient for accurate estimation for population sizes before the bottleneck event . We furtD statistics indicate that there is little evidence for the gene flow from other populations to the Irabu/Ikema subpopulation, whereas the Miyakojima subpopulations showed signatures of migration from other populations  showed the highest Z score, we could not clarify the source population of this gene flow. However, considering the results of demographic inferences, immigration from the Northern islands, such as Okinawajima, to Miyakojima islands might be related, at least in part, to the historically attested immigration during the Gusuku period (900 − 500 BP).The Miyakojima subpopulations experienced a different history against Irabu/Ikema subpopulation. We showed that the Miyakojima subpopulations did not experienced any drastic population bottlenecks  online. ulations , suggestAlthough there are several possible explanations for the bottleneck in the Irabu/Ikema subpopulation, one remarkable disaster during this period is a strong candidate. A large earthquake and a subsequent tsunami hit the Yaeyama and Miyako Islands in 1771 (the Great Tsunami of Meiwa) . More thD statistics analyses, the time of migration into Irabu/Ikema may date back to the Gusuku period (900 − 500 BP) as described in the introduction , followed by two more recent migrations, which occurred at closer intervals (16 and 7 generations ago). Considering the archaeological evidence and the results of haplotype sharing and oduction  online, The fine-scale genetic structure information that we identified is important for performing genetic association studies for the Ryukyu people. Genome-wide polygenic risk scores (PRS) constructed from large-scale GWAS data (sample size of hundreds of thousands to a million) could precisely predict the onset of several common diseases in people of European or East Asian descent . Aside fIn this study, we produced genetic evidence that reveals the previous population isolation history and gene flow among people living in the Miyako Islands. The genetic structure we observed likely reflects past events experienced in the Miyako Islands, such as migrations and disasters. We aim to accumulate more genetic information derived from the Ryukyu Archipelago with clinical information through the OBi Project, and such data will enable us to further understand the population history of the Ryukyu Archipelago and to identify novel genetic factors related to susceptibility to several common and/or rare diseases.Saliva or blood samples were collected from 1,240 individuals living in the Miyako Islands between 2016 and 2017 as part of the OBi Project. All participants gave written informed consent before their enrollment in the study. For the survey of the origin of individual participants, we obtained information of the birthplace (islands) for their four grandparents by a questionnaire. If their birthplaces were Miyakojima or Irabu, we asked for more detailed information regarding birth areas on each island dating as far back as possible. Genomic DNA was extracted from saliva or blood samples, and we genotyped 665,326 SNPs using the Asian Screening Array . The protocol of this study was approved by the Ethics Committees at University of the Ryukyus .P > 10−6), and 4) SNPs were polymorphic in the focal population . In addition, individuals having a shared identity-by-descent (The criteria for including SNPs in our experiments were as follows: 1) SNP calling rates were 98% or higher, 2) individual calling rates were 98% or higher, 3) genotype distributions were in accordance with Hardy–Weinberg equilibrium (LINK 1.9 .ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/), aboriginal Taiwanese  from the Simon Genome diversity Project (http://sharehost.hms.harvard.edu/genetics/reich_lab/dgdp), and Jomon F23 individual . To infer the population structure in greater detail, we used the haplotype-based clustering method in the FineSTRUCTURE/ChromoPainter program (v4.0.1) in which individuals were assigned into genetically homogenous groups using a nonparametric Bayesian mixture model implemented through an MCMC algorithm . DetaileThe recent demographic histories of the local populations were inferred based on the IBD segments. We reconstructed the IBD segments using IBD-seq ver: r1206 . This meWe estimated shared IBD segments between each subpopulation in the Miyako and other populations from the 1000 genomes project using the IBD-seq program. The physical lengths of each IBD segment (in base pairs) were converted into genetic distances  by extrapolating the genetic map provided by HapMap .ij is the total sharing haplotype between individuals i and j from population I and J, respectively. We summarized the total IBD lengths of possible all pairs from two populations and computed the arithmetic mean of the shared segments for each pair of populations.To compare haplotype sharing between the two populations, we calculated the haplotype sharing index of each population pair using the following equation : IBDIJ=D statistics to infer whether the genetic differences among the Miyako subpopulations were derived from genetic drift or ancestry differences. We chose YRI as the outgroup and JPT, CHB, Okinawajima, and Jomon as the source populations of admixture. Each test was carried out using AdmixTools  along with CHB from the 1000 genomes project as an outgroup for the coalescent simulation to infer the demographic population history, including the effective population sizes, migration rates, and divergence times under the assumption of recent migrations among the Ryukyu populations. We proposed a demographic model considering the population size changes inferred from our haplotype-based analysis . DetaileMolecular Biology and Evolution online.msab005_Supplementary_DataClick here for additional data file.


Cytb gene from 58 unrelated birds sampled during the marking in the nests was sequenced and compared to the homologous Griffon vulture sequences available in publicly accessible online databases. Phylogeographic analysis based on Cytb sequences showed that the most frequent haplotype is found in all Griffon vulture populations and that each population possesses private haplotypes. Our data suggest that the Griffon vulture population from Serbia should be used as a source population for restocking and reintroduction programs in the region. The observed genetic differentiation between the populations from the Iberian and Balkan Peninsulas suggest that the introduction of foreign birds from remote populations should be avoided and that birds from indigenous or neighboring populations, if available, should be used instead.Once a widespread and common species across the region of southeast Europe, the Griffon vulture is now confined to small and isolated populations across the Balkan Peninsula. The population from Serbia with 290 couples represents its biggest and most viable population that can serve as an important reservoir of genetic diversity from which the birds can be used for the region’s reintroduction or recolonization programs. To estimate the level of genetic diversity, the mitochondrial  Gyps fulvus fulvus Hablizl, 1783) belongs to the subfamily Aegypiinae or Gypiinae, a group of Old World vultures that is listed as critically endangered on the International Union for Conservation of Nature’s Red List of Threatened Species (IUCN Red list) [The Eurasian Griffon vulture (ed list) ,3). Of 1ed list) . Many coed list) ,6,7,8,9,ed list) .Vultures play a key role in maintaining the harmonious processes and functionality of ecosystems. As obligate scavengers, their main role is the decomposition of organic matter in nature, via efficient carcass removal that reduces the rates of transmission of infectious diseases. The Griffon vulture itself is an economically and ecologically important species that provides several ecosystem services in the form of animal carcass removal, which is beneficial from both the sanitary and economic perspective ,11,12. IGyps genus. Spain holds the largest breeding Griffon vulture population in the world. Estimates are that around 75%  of the world’s total Griffon vulture population and more than 95% of European populations are situated in this country [Gyps indicus), which called for the proper genetic evaluation of birds that will be used for future restocking programs [The Eurasian Griffon vulture has a large area of distribution, ranging from Kazakhstan and Nepal to Southern Europe and the Maghreb countries  and is t country ,19,20. I country . The lat country . The Gri country ), while  country ). Accord country  and seve country  and unip country ,28,29. T country . The samprograms , furtherCytb [Cytb data were mostly used to determine the phylogeny of different vulture species, including the members of the Gyps genus [Cytb for both phylogenetic and phylogeographic analysis [Considering mtDNA, the majority of the available data for different Griffon vulture populations are based on the analysis of Cytb ,25,26,29Cytb ,28. In aps genus ,26,29, wanalysis ,28. Whilanalysis ,28, lackCytb gene is widely used in studies considering the genetic diversity of birds [Cytb has several valuable properties that can be used for inferring different evolutionary and population processes. Cytb gene sequence is characterized by both slowly and rapidly evolving codon positions as well as conserved and variable regions, which makes it ideal for deciphering diversity and systematics questions starting from detailed phylogeny [Cytb gene variability can be used to identify the signs of adaptive evolution [Properly designed conservation strategies recognize the need to analyze information from both uniparentally and biparentally inherited genetic markers ,31,32. Uof birds ,40 for dof birds ,42 and sof birds ,44. As ahylogeny ,48,49,50hylogeny ,52,53,54volution  as well volution ,57.Cytb and new data about Cytb variability in the Serbian Griffon vulture population will further improve our understanding of the population structure and local genetic variability of this significant species. In addition, Cytb can be used to decipher if specific adaptations to different climate conditions have emerged in the Griffon vulture populations inhabiting various geographical regions. With the detailed analysis performed in this study, we aim to further determine the status of the Griffon vulture population from Serbia, and its perspective as a source population for further reintroduction efforts in the Balkan Peninsula.The majority of data available for the Griffon vulture and its sister species are based on the variability of A representative sample of the Griffon vulture population from Serbia consisted of 58 unrelated birds originating from 58 different nests. Sampling was performed in a period from 2013 to 2020 in the gorge of the Uvac River, which is a part of the “Special nature reserve Uvac” as described in [Cytb data from GenBank that were found in the different Griffon vulture populations  and agarose gel electrophoresis.The DNA extraction was performed using the GeneJET Genomic DNA Purification Kit (Thermo Fisher Scientific Cat.No. K0721) and a modified salting-out protocol. For the salting-out protocol, the blood samples of 20 μL were adjusted to 100 μL using TE buffer and mixed with 300 μL of lysis buffer  with the addition of 10 μL 20% SDS, 10 μL of Proteinase K (20 mg/mL) and 20 μL of ddHTo avoid possible contamination, sample preparation and DNA extraction of the museum feather samples was performed in the forensic DNA laboratory in the Center for Forensic and Applied Molecular Genetics at the Faculty of Biology.DNA extraction was conducted from whole feathers or only the calamus depending on the feather size. Calamus was removed from the feather using a sterile scalpel blade. All feather samples were first rinsed with 3% sodium hypochlorite to remove possible surface contamination and then rinsed twice with DNase/RNase-free distilled water .DNA was extracted using the previously described protocol  in the fCytb was amplified using the GF-L13740/GF-H15014 set of primers  using PAST 4.03 [All the  10.0.4. . The gen 10.0.4. . MPD rep 10.0.4. . The samAST 4.03 .Cytb haplotypes were translated into protein sequences using MEGA 10.0.4, which allowed for the identification of synonymous and nonsynonymous substitutions. In order to evaluate whether these substitutions were under selective pressure, we ran different codon models  using the Datamonkey web designed tool .Nucleotide sequences for all available Cytb gene in birds are available. Phylogenetic relationships among detected haplotypes within the Griffon vulture species were tested by the means of Bayesian phylogenetic inference in the BEAST v 1.10.4. [Gyps genus was tested in order to acquire more precise time divergence estimates of the detected haplotypes; the sequences used for the analysis are listed in m = 0.00223 Phylogeographic analysis was performed using 128 mtDNA haplotypes found in 13 different Griffon vulture populations . The phy 1.10.4. . The phymula (1) :(1)m=10.In addition to using the estimated mutation rate for 24 ×10−6 . All par24 ×10−6  was usedOverall, four haplotypes were detected among the analyzed Serbian Griffon samples, including contemporary and museum specimens . Sample Cytb sequences used in this analysis  was used to root the network. A total of 16 different mtDNA haplotypes were detected (excluding the Cape vulture haplotype), defined by 19 polymorphic sites. The network is defined by star-like phylogeny, which indicates rapid and recent diversification. The most frequent mtDNA 14560C haplotype was present in most of the populations included in the analysis, while others were mostly private and represented by one bird in the population. Three different haplotypes were detected in the Griffon vulture population of Serbia, 14560C and two private ones. As expected, the Griffon vulture population from Spain has the highest haplotype diversity of all European populations , Slender-billed vulture (G. tenuirostris) and Himalayan vulture  exhibit similar patterns of the star-like phylogeny, indicating a recent and rapid diversification, while other Gyps species show more stable diversification. A small number of haplotypes and pronounced star-like phylogeny for Indian vulture and Slender-billed vulture is also indicative of recent loss of genetic diversity caused by the significant decrease in the number of birds that were reported for these species. Although the White-rumped vulture  and White-backed vulture (G. africanus) are labelled as “Critically Endangered” by the IUCN Red list because of decreasing numbers, the haplotype network suggests that the mtDNA genetic variability is high and stable.The mtDNA haplotype network representing phylogeographic relationships within Griffon vulture species is presented in ulations  defined ps genus . This anGyps genus phylogenetic tree of mtDNA lineages based on Bayesian tree analysis supported by high posterior probability (HPD > 95%) for each node is presented in Cytb with 95% HPD interval are presented in G. fulvus species are presented in Gyps genus corresponds to the haplotype network shown in G. fulvus species  can be observed. In addition, when populations with the highest numbers of sequenced individuals, i.e., Serbian and Spanish, were compared, a significantly high 10% of the genetic variance could be explained by the variation among populations. The observed high and statistically significant Cytb analysis revealed the existence of two distinct evolutionary lineages corresponding to breeding populations in Spain and the Balkans [The presented results are in concordance with previously reported genetic differentiation based on microsatellite variability between these two populations . It is i Balkans . Conside Balkans ,80,81,82 Balkans ,84, such Balkans ,86. This Balkans ,28.Cytb gene is under strong purifying selection, which eliminates all substitutions that could have a negative effect on phenotype, as shown in the case of low-altitude deer mice [Gerbillus species [The establishment of population-specific genetic variants may be further propelled by social monogamous behavior and multigenerational natal philopatry leading to genetic differentiation between populations, as already shown for the island populations of Crete and Sardinia ,28. Altheer mice  and four species . The sec species ,89 and d species ,90,91. I species .Gyps genus phylogenetic tree of Cytb lineages based on Bayesian tree analysis is supported by high posterior probability for each node and in concordance with previously published results based on different mtDNA genes [Gyps genus. Haplotype networks also reflect the demographic history of the species indicating a rapid diversification [The NA genes ,25. Bothfication , and it Population genetic variability of any given species is shaped by its distant and recent history, demography and biogeography. In highly philopatric, gregarious, monogamous species, such as the Griffon vulture, behavior may be a factor that also shapes genetic variability. As already demonstrated in almost all analyzed vulture species, human-induced demographic declines significantly influence standing genetic variation reflected in the loss of diversity, inbreeding depression and presence of population-specific genetic variants . All theEuropean Griffon vulture populations are the subject of several active restocking programs with variable success (reviewed in ). SuccesCytb variability in the Serbian Griffon vulture population, along with previously published data [Our analysis of hed data , is a st