Tachypleus gigas) in Indonesia. To achieve this, we collected a total of 91 samples from six main T. gigas habitats: Bintan, Balikpapan, Demak, Madura, Subang, and Ujung Kulon. The samples were amplified using primers for mitochondrial (mt) AT-rich region DNA sequences. The results showed 34 haplotypes, including seven shared and 22 unique haplotypes, across all localities. The pairwise genetic differentiation (FST) values were low (0 to 0.13) and not significantly different (p > 0.05), except among samples from Ujung Kulon-Madura and Kulon-Subang (p < 0.05). Additionally, the 34 analysis of molecular variance (AMOVA) showed the most variation within populations (95.23%) compared to less among populations (4.77%). The haplotype network showed evidence of shared haplotypes between populations. Tajima’s D and Fu’s FS test values indicated a population expansion. Our results showed a low level of differentiation, suggesting a single stock and high connectivity. Therefore, a regionally-based conservation strategy is recommended for the coastal horseshoe crab in Indonesia.Species with limited dispersal abilities are often composed of highly genetically structured populations across small geographic ranges. This study aimed to investigate the haplotype diversity and genetic connectivity of the coastal horseshoe crab ( High rates of gene flow are common in marine organisms that are spread across large geographic ranges . SeveralLimulus polyphemus) found along the eastern coast of North America from Maine to Mexico (Carcinoscorpius rotundicauda), the coastal horseshoe crab (Tachypleus gigas), and the tri-spined horseshoe crab (Tachypleus tridentatus)) )  that arentatus)) . The Asintatus)) .T. gigas was once relatively common along the northern Java Sea. However, coastal and mangrove horseshoe crab populations have an undetermined conservation status due to insufficient data , Balikpapan (BP), Demak (DK), Madura (MD), Subang (SB), and Ujung Kulon (UK), respectively. The hemolymph was collected from each individual and immediately preserved in absolute ethanol. Field experiments were approved by the Research Council of the Study Program from IPB University (letter number 1426/IT3.F3.2/KP.03.03.2019).With the help of a local fisherman, adult and juvenile ng Kulon . We coll2O, 1.25 µL forward and reverse primer, and 1 µL DNA template. The entire reaction mixture was amplified using a peqSTAR thermal cycler , following Genomic DNA was isolated from each hemolymph sample following a Genomic DNA Mini Kit  according to the manufacturer’s instructions. A fragment of the AT-rich region was amplified using a pair of primers, Hb-12S (5′-GTCTAACCGCGGTAGCTGGCAC-3′) and Hb-trna (5′GAGCCCAATAGCTTAAATTAGCTTA-3′), designed from the mitochondrial genome of the American horseshoe crab . A 25-µLπ) using DNASp v6 (FST) and analysis of molecular variance (AMOVA). The significance level threshold (α), used to determine the pattern of differentiation between locations, was 0.05. The pairwise F-statistic (FST) was calculated as the genetic distance based on the population differences using DNASp v6 , Sumatra, Bintan and Borneo . In total, 43 variable nucleotide sites and 34 haplotypes were observed. The haplotypes consisted of both unique (found only in certain locations) and common haplotypes . The genh = 0.783 to 0.945 with a mean gene diversity per population h = 0.935. Conversely, the nucleotide diversity was relatively low in all locations, ranging from π = 0.004 to 0.009. The overall diversity was similar across populations. DK had the lowest haplotype and nucleotide diversity . BP had the highest haplotype and nucleotide diversity (h = 0.945 π = 0.009), followed by UK , SB , MD , and BT   .FST values ranged from 0 to 0.13 across the populations  with the exception of UK-MD and UK-SB, indicating the restricted gene flow among these populations. Populations with higher pairwise FST values included BT-MD (p > 0.05), BT-SB (p > 0.05), UK-MD (p < 0.05), and UK-SB (p < 0.05). The pairwise FSTvalues of UK-BT, DB-DK, and SB-MD were effectively zero. Our AMOVA results showed that the majority of variation was found within (95.23%) rather than among (4.77%) populations  was quite high, while nucleotide diversity (π = 0.006) was low across all populations. Similarly high haplotype diversity values were reported in T. gigas  in Taiwan  in Indonesian coastal horseshoe crab populations. The mean haplotype diversity , with exceptions between populations UK-MD and UK-SB. This result indicated that there was little subdivision across populations. Several studies suggested restricted dispersal abilities for horseshoe crabs regarding short-term tagging. However, some others explained that this crab has a wide dispersal abilities based on long-term studies. Individual distances up to 30 km have been observed in Malaysian crabs  in Indonesia should consider population genetics. High haplotype diversity that occurs with low nucleotide diversity has been associated with population growth or expansion after a period of low effective population growth  should be conducted. This should also include expanding the scope of geographic sampling around Indonesia.A proactive management approach regarding the Asian coastal horseshoe crab (n growth . Our finT. gigas) populations in Indonesia indicated a single stock with high connectivity. A locally and regionally based conservation management method is suggested as a precautionary approach to conserving the Indonesian coastal horseshoe crab.High genetic diversity and low levels of differentiation across coastal horseshoe crab (10.7717/peerj.11739/supp-1Supplemental Information 1Click here for additional data file.


Plasmodium falciparum immunogenic proteins pose a major roadblock to developing an effective malaria vaccine with broad and long-lasting immunity. We conducted a prospective genetic analysis of candidate antigens  for malaria vaccine development on 2375 P. falciparum sequences from 16 African countries. We described signatures of balancing selection inferred from positive values of Tajima’s D for all antigens across all populations except for glurp. This could be as a result of immune selection on these antigens as positive Tajima’s D values mapped to regions with putative immune epitopes. A less diverse phistb antigen was characterised with a transmembrane domain, glycophosphatidyl anchors between the N and C- terminals, and surface epitopes that could be targets of immune recognition. This study demonstrates the value of population genetic and immunoinformatic analysis for identifying and characterising new putative vaccine candidates towards improving strain transcending immunity, and vaccine efficacy across all endemic populations.Genetic diversity of surface exposed and stage specific  An effective malaria vaccine would significantly boost malaria control and elimination efforts. However, genetic diversity and the evolutionary arms race between the parasite and the host drives antigenic diversity of surface proteins, and other life cycle stage-specific proteins targeted as potential vaccine antigens, thereby hampering the development of a widely deployable vaccine3, raising the possibility of allele-specific immunity as that seen in vaccines against influenza and other diseases7. Most of the current leading malaria vaccine candidates in clinical trials were designed and developed based on clonal laboratory strains, mostly Plasmodium falciparum strain NF54 (clone 3D7), without considering parasite genetic variability in natural populations12. RTS,S/AS01, the most advanced of these malaria vaccines, is based on a subunit of 3D7 circumsporozoite surface protein (CSP) antigen. It has shown moderate (< 50%) and time-limited protection in African children13, partly due to the low prevalence (5.2%) of 3D7-type CSP alleles9. Several other recombinant malaria vaccines are currently being evaluated in clinical trials, such as: EBA region II-non-glycosylated (EBA-175 RII NG), apical membrane antigen 1 diversity covering (AMA-1 DiCo), merozoite surface protein-3 (MSP3) long synthetic peptide (LSP), and serine repeat antigen-5. Other recombinant malaria vaccines in clinical trials are described in a recent review by Salamanca et al10. Additionally, the Cell-Traversal protein for Ookinetes and Sporozoites (CelTOS), Thrombospondin Related Adhesion Protein (TRAP), and Liver Stage Antigen 1 (LSA1), which target liver stage parasites; merozoite surface proteins (MSP2) which target blood stage parasites; and transmission blocking stage vaccines targeting Pfs230, Pfs45/48, Pfs25 and Pfs48/4515 are also in advanced development.Field trials of some of the most advanced candidate malaria vaccines have shown strain specificity19, most of these vaccine candidates would face most of the challenges observed during the RTS,S/ASO1 development. To overcome some of these difficulties and improve vaccine efficacy by generating cross-protective multi-strain immunity across diverse natural populations, next generation vaccines must use innovative design approaches that account for genetic variables such as differences in antigen allele haplotypes and their frequencies across P. falciparum populations20.Nevertheless, given our incomplete understanding of the complexity of immune responses to infection, the parasite’s mechanisms of invasion, and the parasite genome22. With the increase of next generation sequencing and openly accessible genome data from multiple endemic populations, future multi-allelic vaccines can benefit from genome scans for signatures of balancing selection. This will allow assessment of allele and haplotype frequencies across a broad range of endemic populations, particularly in sSA where parasite genetic diversity is high22. Such in silico diversity and prediction approaches should include sequence data obtained across multiple temporal and spatial populations. This could be explored to identify new candidates, refine components of current candidate vaccine antigens, with optimal components of relevant alleles from both pre-erythrocytic and erythrocytic targets prior to functional characterisation and clinical trials15.Exploring the allele frequency spectrum and haplotype diversity of vaccine candidates can inform how natural selection and demographic events shape them across multiple populations. For example, characterising genetic diversity and signatures of selection in the parasite genome or for specific antigens has been useful in identifying genes under balancing selection and genic regions that are immunogenic for further developmentphistb—that could be explored for monovalent vaccine development or as part of a multivalent vaccine. Together, this is the largest exploration of candidate vaccines’ genetic diversity for natural populations of malaria parasites from sSA, providing a framework for designing future functional studies and effective malaria vaccines.Here, we conducted population genetic and immunoinformatic analysis of selected malaria candidate vaccine antigens using single nucleotide polymorphisms (SNP) from field isolates from 16 African countries. We estimated the extent of genetic diversity in these antigens and evaluated the evidence of balancing selection that could be shaping their evolution. From this large population dataset, we described a novel putative candidate vaccine antigen—24 and the open-source, MalariaGEN . For the PDNA data, field studies were approved by the respective local ethical review committees. Venous blood (2–5 ml) was collected from study participants aged > 6 months enrolled under approved protocol(s) in each country. All participants and/or their legal guardians provided written informed consent before any study procedures. All procedures performed in studies involving human participants were in accordance with the Declaration of Helsinki. Samples were leukocyte depleted and extracted DNA sequenced by MalariaGEN at the Wellcome Sanger Institute.This study utilized data previously published by the Plasmodium Diversity Network Africa (PDNA)To utilize PDNA and the open-source data in the current analysis, this study was elaborated as part of a malaria genomic surveillance proposal reviewed and approved by the Gambian Government/MRC Joint Ethics Committee. The methods employed in this study were in agreement with the MRCG-LSHTM research governance policy.Plasmodium falciparum vaccine antigens were identified and analysed; among them, 10  were included as potential vaccine antigens. The remaining 6 antigens  were identified using Rsb (a metric for comparing integrated extended haplotype homozygosity between populations), the cross population test for signatures of selection23. Antigens were classified as pre-erythrocytic  or erythrocytic  candidates based on the P. falciparum life cycle stage of expression.A total of 16 P. falciparum antigen sequences (2375) used in this study were obtained from PDNA study sites from; Gambia (n = 247), Mali (n = 137), Cote-d’Ivoire (n = 70), Ghana (n = 423), Nigeria (n = 34), Cameroon (n = 239), Gabon (n = 55), Kenya (n = 64), Tanzania (n = 300), Ethiopia (n = 34) and Madagascar (n = 25)23. Additionally, open-source sequence data from Guinea (n = 143), Senegal (n = 137), Democratic Republic of Congo (n = 112), Mauritania (n = 86) and Malawi (n = 269) . Details of the methods and curated genotype data can be accessed from https://www.malariagen.net/resource/26 and associated publications25.The 69) Fig.  were accP. falciparum populations from individual countries were determined. Population genetic parameters were determined using PopGenome R package26. Nucleotide diversity (π) (average number of nucleotide differences per site in pairwise comparisons among DNA sequences) and theta (Ɵ) (population mutation rate) was measured for each candidate vaccine antigen by country. Nucleotide diversity was calculated both for the entire coding sequence of each antigen and in sliding windows to determine regions of increased diversity. Haplotype diversity (Hd) which represents the probability that two randomly sampled alleles are different was estimated per antigen and population.Population genetic analyses were carried out on each candidate vaccine dataset to investigate the genetic diversity as well as the frequency of known haplotypes being incorporated into vaccine candidates. The range and distribution of genetic diversity within and among the natural 27 for the entire antigen region or in consecutive sliding windows of 100 bases. Positive Tajima’s D values generally suggest balancing selection, or a population contraction is acting to maintain alleles at intermediate frequencies; negative values suggest purifying or positive selection, or population expansion that results in an excess of rare alleles.Neutrality tests designed to distinguish between neutrally evolving sequences under mutation-drift equilibrium- population expansion and contraction, and sequences evolving under non-neutral processes including directional or balancing selection, were derived. We determined Tajima’s D, Fu & Li’s F* and D* statistics. Tajima’s D uses the frequency of segregating nucleotide sites, while Fu’s F* uses the distribution of alleles or haplotypes. Both tests are based on the principle that a rapid population expansion associated with a non-neutral process will show a shift in the allele frequency spectrum compared to a neutral Wright-Fisher model consistent with population expansion under neutral evolution. For all the candidate vaccine antigens, Tajima’s D was estimated by country using vcftools2) index between alleles at physically separate loci with a minor allele frequency > 1% across all populations using PLINK v1.90b6.428. Within each population, r2 measures for each antigen were calculated between all pairs of single nucleotide polymorphisms (SNP) and observed pair-wise LD (r2) was averaged for each inter-SNP distance. Decay of LD with physical distance between SNP loci was fitted in R version 3.6.To determine correlation between antigen alleles, pair-wise LD between different polymorphic sites was computed based on the genotype correlation coefficient (r29. The fixation index (FST) was estimated for pairs of populations using the hierFstat package30. For interpretation, FST values < 0.05 was delineated as low differentiation or high gene flow between population pairs, 0.05–0.15 as intermediate, and > 0.25 as high differentiation.To assess geneflow between populations, we first estimated genetic differentiation (i.e. the difference in the average diversity within populations compared to that among populations) expressed as Wright’s fixation index using whole SNP dataset for each vaccine candidateP. falciparum from the 16 African countries were constructed using the median joining algorithm in the R packages Pegas and Ape31. The haplotype network was computed using haplotype pairwise differences as a distance measure, estimated from the number of SNP variants between haplotypes.Genetic relationships between antigen haplotypes of 32. Sequences of these antigens were uploaded on to the server in FASTA format and B-cell epitopes returned as outputs. We further compared the B cell epitopes predicted with segments of the antigens’ sequences with elevated positive Tajima’s D values. This allowed us to map contiguous regions in the proteins which are likely under immune selection and could be included in future designs of multivalent malaria vaccines.The random forest algorithm trained on epitopes annotated from antibody-antigen protein structures was employed in predicting linear B-cell epitopes for 11 candidate vaccine antigens with at least 3 SNPs, by employing BepiPred-2.0 at a threshold of 0.533. The predicted model with the highest C-score (range: 0–1), used for indicating confidence in the predicted models, was selected and epitopes and regions under balancing selection highlighted. Transmembrane helices and glycophosphatidylinositol (GPI) anchors were predicted by uploading phistb sequence into the TMHMM prediction servers and GPI-SOM respectively34.The amino acid sequence of the candidate vaccine antigen was submitted to I-TASSER for in silico prediction analysis using the default settingsU non-parametric test was used to assess statistically significant differences between groups assuming a non-Gaussian distribution. Statistical analysis was performed using GraphPad Prism version 8.0. Additionally, statistical comparison of genetic indices for antigens based on region of origin following stratification of populations into two geographical areas: West and Central Africa  versus East Africa . This stratification was based on previous reports by the PDNA describing the clustering of African malaria parasites into subpopulations23.Spearman's rank nonparametric correlation coefficient was used to measure the correlation between the three neutrality tests applied. Mann–Whitney The population dataset used in this study comprise 2375 sequences from West, Central, South Central, East and South-Eastern African countries. Three countries in the population dataset; Nigeria, Ethiopia and Madagascar had fewer parasite sequences  compared to other countries in our analysis.pfsea, and msp1, while the highest was 110 for surfin8.2  and erythrocytic  antigens showed large nucleotide diversity when aggregated across all countries. For the pre-erythrocytic antigens, pfsea had consistently lower π and Ɵ values of 0.00002890 and 0.00009980 respectively  whilst hyp10 had the highest (Table csp (Gabon) to as low as 0.0000075 for pfsea (Mauritania). For the erythrocytic antigens, the π value was as high as 0.0189404 for hyp10 (Gambia) while the lowest values was 0.0000952 for hyp9 (Cote d’Ivoire), (Table csp (except for Ethiopia) and hyp10. Nevertheless, pre-erythrocytic antigens lsa3 and pfsea had low (0.058–0.096) nucleotide diversity across all countries. Such low levels of diversity were also observed across geographical sites for erythrocytic antigens rh5, hyp9, and glurp (majority of sites). Interestingly, we observed a relatively higher nucleotide diversity at rh5 in east African sites  and the island of Madagascar (Table The lowest median number of haplotypes per country was 3 for .2 Table . All can), Table . Across ar Table .Table 1H(Hd) values across all antigens and populations were mostly > 0.4 with the exception of pre-erythrocytic antigen pfsea, (Hd ranging from 0.05 to 0.29) and erythrocytic antigen hyp9 (0.017–0.153) which were low across all populations , hyp10 (P = 0.0005), phistb (P = 0.0005) and rh5 (P = 0.0032). In our subsequent analysis, antigens with limited SNP information were excluded, which led to removal of five antigens  from Tajima’s D and LD analysis. The remaining 11 antigens were subjected to Tajima’s D, LD and linear B-cell epitope and 3D-structure prediction.The haplotype diversity index ns Table . CandidaFST) of inter-population variance in allele frequencies. Pairwise FST values for the pre-erythrocytic antigens were low suggesting low genetic differentiation among the populations or extensive genetic exchange (high gene flow), with the exception of csp in populations with low samples sizes; Nigeria, Ethiopia and Madagascar, which had high values, FST > 0.25 . Pairwise FST values for erythrocytic antigens also showed low genetic differentiation, with the exception of rh5 antigen between Madagascar and Gambia (FST = 0.3), which are separated by the widest geographic distance.We evaluated genetic differentiation among parasite populations to obtain an insight into gene flow by calculating Wright’s fixation index  between East versus West and Central Africa. This is further evidence of standing variation in these antigens across malaria endemic communities in sSA. As expected, there was strong correlation between Tajima’s D and Fu & Li’s F* values for all the antigens across the populations studied (r = 0.882). However, correlation was much lower between Tajima’s D and Fu & Li’s D* (r = 0.03), with some antigens, notably glurp, celtos and phistb, showing a negative correlation, while Fu & Li’s D* and F* had a weak correlation (r = 0.2) for the antigens except for glurp where Tajima’s D was negative but Fu and Li indices were positive , values were mostly positive for the candidate vaccine antigens, except for es Table , suggestia Table . The posceltos and csp) and 3 erythrocytic  antigens. The pre-erythrocytic antigens had a high number of haplotypes with no geographic clusters, suggesting lack of structure. Haplotype network of the erythrocytic antigens followed a similar pattern to the pre-erythrocytic antigens, except for phistb where geographic clustering of some haplotypes was evident  declined rapidly with physical separating pairs of SNPs for all antigens, falling below an rirs Fig. . Exceptiphistb, which had only 2 predominant haplotypes  site in its C-terminal region. GPI is used by proteins for anchoring to the plasma membrane  from 16 African countries. Most advanced malaria vaccine candidates were initially designed without considering genetic diversity, resulting in poor protective efficacy as shown by FMP1/AS02A MSP1 or the AMA1 candidates that had limited vaccine allele representation in naturally circulating parasites, especially in Africa36. Therefore this focused analysis on African parasite populations is relevant, given intense but heterogenous transmission, and high parasite genetic diversity across sub-populations4.We carried out a large-scale population genetic analyses of candidate vaccine antigens and hitherto uncharacterised potential antigens using SNP data of 37. As immunity could be driving balancing selection signatures against specific domains of the antigens, our scan for signatures of selection localised these segments, with sequences of known immune epitopes that could be targeted for functional evaluation. However, antigens under high immune selection pressures and balancing selection are often highly polymorphic with moderate minor allele frequencies, likely to result in variance in allele specific immune response between populations38. This applies also to well-known erythrocytic vaccine candidates based on ama1, msp1 and eba175, in which variation and selection has been a major hurdle in achieving broad efficacy across malaria endemic populations39. Like msp1 and ama1, other erythrocytic antigens such as surfin 8.2 and surfin 14.1 showed signatures of both directional and balancing selection, the latter, also due to an excess of intermediate frequency variants that may result in vaccine escape. The surfin family of proteins are expressed by genes close to the sub-telomeres where other surface variant antigens  are encoded5. These are expressed on the surface of infected erythrocytes and are known targets of protective immunity and generating heterologous antibodies associated with reduction in febrile illness due to malaria infection6. Surfin8.2 had the highest number of segregating sites and has been shown to be preferentially expressed in gametocytes41. Being a PEXEL (Plasmodium export element) negatively exported protein with a transmembrane domain42, it will be exposed to the surface and can therefore be a target for transmission blocking vaccine development. Another transmission blocking vaccine, glurp, is in advanced development alone or as a multivalent component with other erythrocytic candidates such as msp3 (GMZ2)43. Its lower Tajima’s D value and smaller number of haplotypes could provide an advantage for combination with other candidates such as surfin8.2 to provide a broad range of erythrocytic protection and transmission blocking activity.By screening for antigens with signatures of directional selection, we expected to identify those with dominant haplotypes and exposed immune epitopes, that could be included into the panel of candidates currently under development. We observed significant diversity amongst characterised vaccine candidates and new putative antigens across all populations, and this may result in poor efficacy both within clinical trials and in future deploymentceltos, lsa3, pfsea and trap. The least polymorphic one was the schizont egress antigen pfsea, whose antibodies have been associated with protection against high parasitemia and severe disease45. It is under preclinical exploration in combination with invariant carboxyl of PfGARP and PfMSP1 in a tri-valent vaccine formulation. As previously described, lsa3 also has a low number of haplotypes and is expressed on both sporozoites and the erythrocytic stages48. Thus it could also be considered as a blood stage vaccine candidate given its antibodies inhibit parasite growth in the erythrocyte48. Its further development against both erythrocytic and pre-erythrocytic stages will have to consider the African haplotypes described here. This also applies to one of the recent prominent candidates, rh5, which, despite a low number of haplotypes, had 12 non-synonymous SNPs and high between population differentiation determined by the fixation index FST. Strong differentiation between eastern versus western African parasite populations would imply that population specific variation in haplotypes need to be considered for rh5 vaccine development. Our findings also support previous studies which demonstrated that the number of haplotypes were consistently higher in countries with higher malaria transmission such as Cameroon, Mali and Malawi51. Therefore, continuous genetic screening for low diversity candidates to add to the pool of current antigens that can be combined in a multivalent malaria vaccine remains important.While erythrocytic antigens dominate the panel of malaria vaccine candidates in development, the only successful vaccine to date is the CSP-based RTS,S/AS-01. As shown already, the CSP gene is highly diverse, one of the factors contributing to reduced efficacy across populations. We assessed diversity at four other pre-erythrocytic candidates, phistb. PHIST proteins belong to the Plasmodium helical interspersed subtelomeric (PHIST) family made up of 65 gene members  and are unified by possessing a single domain termed PHIST that is predicted to be composed solely of alpha helices53. This family of exported proteins are conserved across the human Plasmodium species; P. falciparum, P. vivax and P. knowlesi52. As we identified a transmembrane domain and GPI anchors, we expect phistb to be surface anchored54. Previous studies have described phistb to localise to the host erythrocyte periphery through a PRESAN domain and an N-terminal sequence, and therefore exposed to immune interaction. Unsurprisingly, segments of the antigen had high Tajima’s D values, indicating balancing selection probably due to immune selection. These segments mapped to predicted B-cell epitopes which could be included in future candidate vaccine designs, preclinical testing and for selection of an optimal vaccine cocktail. The low genetic diversity, limited haplotypes in the population and linear B-cell epitopes of phistb are desirable features for designing an antimalarial vaccine that is less likely to produce allele-specific immune responses50. Recent studies with in vitro expressed phistb protein demonstrated the presence of significant specific anti-phistb antibodies in children, with malaria specific immune responses55. This further supports predictions from genetic analysis and epitope mapping in line with other studies that have identified potential immune targets by modelling protein structures and predicting the functional relevance and implications of different domains as vaccine candidates57. PHIST proteins are involved in remodelling infected red blood cells54. However, data on host antimalarial immune responses to these proteins, which could be crucial for vaccine development, is scarce.We demonstrated the power of this genetic analysis by exemplifying one of the low diversity candidate antigens, rh5 and new potential candidates like phistb, our study has several limitations. Samples were collected mostly in one field site per country, and thus they may not provide an accurate representation of the circulating haplotypes across each country. In addition, the number of samples available from some countries such as Madagascar, Ethiopia and Nigeria, were small. Moreover, protocols for sample collection differed by country, including the time of sampling, which may influence the parasite haplotypes due to seasonality. The analysis was limited to high quality SNPs, which could have missed important genetic variations; and there is also the possibility of ascertainment bias in the dataset that have been utilised in this study, and more broader sampling for suspected vaccine candidate genes would be useful. However, despite these limitations, the analysis was comprehensive since we used a large dataset and provide a framework and basis for future studies and considerations. To verify our findings, functional studies and expanded genetic analysis incorporating targeted sequencing data are needed to further support our findings.Despite the relevant finding on top candidates like P. falciparum isolates, it may be possible to identify the most prevalent antigen haplotypes within the continent for inclusion in a multivalent vaccine. Our findings demonstrate population genetic analysis can be used to identify antigens that consider African parasite genetic diversity for design of new vaccines.In conclusion, despite the broad genetic diversity of antigens of African Supplementary Information.


Schinus terebinthifolia is a problematic invasive alien plant (IAP) in South Africa that is a high priority target for biological control. Biological control has been implemented in the states of Florida and Hawaii (USA), where S. terebinthifolia is also an IAP. Phylogeographic work determined that there have been multiple introductions of two lineages (haplotype A and B) into the USA. Haplotype A was introduced to western Florida and Hawaii, while haplotype B was introduced to eastern Florida. Haplotypes A and B have subsequently hybridized in Florida, resulting in novel plant genotypes. Biological control agents in the USA are known to vary in efficacies on the two different haplotypes and hybrids. This study used molecular techniques to uncover the source populations of S. terebinthifolia in South Africa using chloroplast DNA and microsatellites. Populations from the introduced ranges in Florida  and Hawaii were included (n = 95). All South Africa populations (n = 51) were found to be haplotype A. Microsatellite analysis determined shared alleles with western Florida and Hawaiian populations. The likely source of South African S. terebinthifolia was determined to be western Florida through the horticultural trade. These results will help guide a biological control programme to source agents that perform well on these populations in the USA. Furthermore, the presence of only one haplotype in South Africa highlights the need to ensure no further introductions of other haplotypes of the plant are made, in order to avoid similar hybridization events like those recorded in Florida. Schinus terebinthifolia is a problematic invasive alien plant in South Africa and is a high priority target for biological control. Previous work in the USA has found that biocontrol agents on S. terebinthifolia vary in their efficacy according to plant genotype. This study explored the phylogeography of S. terebinthifolia in South Africa and found that only one haplotype is present and it was most likely introduced from western Florida. This work can help guide a biocontrol programme to source agents that perform well on the same haplotype in the USA.Brazilian peppertree,  Management of biological invasions can be assisted by knowing the introductory history of a species . PhylogeSchinus terebinthifolia (Anacardiaceae) (Brazilian peppertree) is a tree native to subtropical South America that has been widely distributed worldwide primarily for its ornamental value (S. terebinthifolia has invaded Florida and Hawaii and is one of the most widespread and destructive IAPs in these regions (S. terebinthifolia (thifolia . HaplotyLygodium microphyllum (Lygodiaceae). Mites collected from plants from the source of the invasive population performed better on the invasive genotype and had reduced fitness and efficacy on plant genotypes from other parts of the native distribution  (Act 10 of 2004) in the Eastern Cape, Limpopo, Mpumalanga and KwaZulu-Natal provinces and category 3 elsewhere  sequencing and microsatellites.As biocontrol has already been implemented in the USA, it is considered one of the options for management of seen = 95) of the 592 Florida plants analysed in [see]. The 95 samples from Florida were chosen to represent the three distinct populations that now occur in that region from the two original introductions of haplotype A into western Florida and haplotype B into eastern Florida . Samples were selected from STRUCTURE analysis that had the highest shared ancestry with each group  (eastern vs. western q > 0.85) as well as hybrids (average q in eastern/western introductions = 0.48/0.52)  reaction contained 0.4 μL of each of the primers at a concentration of 0.01 μM, 10 μl of Promega Master Mix , 0.8 μL of Promega MgCl, 3 μL of template DNA per reaction. A further 5.4 μL of Promega nuclease-free water was added to reach a final volume of 20 μL. Amplifications were performed in a T100™ thermal cycler . The PCR protocol had a 5-min denaturing step at 96 °C followed by 40 cycles of 96 °C for 45 s, annealing temperature of 52 °C for 1 min and 72 °C extension for 30 s. Polymerase chain reaction products were sequenced at Macrogen Corp., Korea using a DNA Analyser 3730x . Samples included from the introduced range (Florida and Hawaii) had already had their haplotypes determined and reported in This method was derived from S. terebinthifolia that were downloaded from GenBank  and two samples from Williams [see]. The remaining samples included from Florida and Hawaii were later included with the data set by standardizing the genotypes using the two samples for alignment. Six S. terebinthifolia microsatellite loci were grouped into two multiplex reactions according to the protocols of [see]. Applied Biosystems Inc., UK added fluorescent labels to the primers; stAAG13 with 6-FAM dye, stAAG14 with VIC dye, stGGT39F with NED dye, stCTCCTT01 with PET dye, stAAT1 with 6-FAM dye and stAAT16 with NED dye (DS-33 Matrix Standard (G5 dye set)). The PCR contained ~10 ng of DNA, 12.5 μL of Q5 High-Fidelity 2× Master Mix and 2.5 μL of each primer at concentrations of 10 μM to make a total volume of 25 μL. Reactions were cycled in a Mastercycler® nexus , 230 V/50–60 Hz using the simulated tube function. Cycling parameters were one cycle at 98 °C for 30 s, followed by 35 cycles of 10 s at 98 °C, 20 s at 50 °C (multiplex A) or 55 °C (multiplex B), 20 s at 72 °C and a final cycle at 72 °C for 2 min. Capillary electrophoresis was run on an ABI 3500XL  genetic analyser at Inqaba Biotec™.Microsatellite analysis was performed on the South African samples  were calculated. We used HP-RARE , the ancestry coefficient, which varies on a scale from 0 to 1.0, with 1.0 indicating full ancestry with a certain population.Discriminant analysis of principal components (DAPC) and Bayesian-based STRUCTURE analysis were used to investigate the pattern of population structure. The nuclear ancestry of all 191 samples was tested based on the six microsatellite loci using a Bayesian genetic clustering algorithm implemented in STRUCTURE version 2.3.4. K; . We used[see]  was used to calculate the maximum a-score according to A DAPC analysis was run to complement the STRUCTURE analysis as it is a non-parametric approach and some of the microsatellite loci and populations significantly deviated from the HWE [see] . DiscrimS. terebinthifolia sampled in South Africa (n = 51) were determined to be cpDNA haplotype A (GenBank accession number for haplotype A: AY928398). Forty-four samples from Florida were haplotype A and all samples from Hawaii were haplotype A [see]. The remaining samples from Florida were haplotype B, which were mostly found in the east of the State and from hybrid populations. The A and B haplotypes were distinguished by variance at five nucleotide positions out of 716 base pairs (All k = 2) (seen = 27), and the other cluster was samples from western Florida (n = 30), Hawaii (n = 45) and South Africa (n = 51) (n = 38) had intermediate values between these two clusters. There was no evidence of hybridization or the presence of hybrids in Hawaii or South Africa.Based on their microsatellite phenotypes, STRUCTURE HARVESTER analysis determined that all the samples clustered into two populations ((n = 51) . Hybrid a-score optimization for the DAPC analysis determined the optimum number of PCs was 10 and the cross-validation determined 25 PCs to retain [seeand]. The a-score value indicating the lower number of PCs was used for the DAPC analysis. The DAPC plot outlines the relatedness of the five populations. As with the STRUCTURE analysis the South African, Hawaii and western Florida populations were grouped together  and in the individuals from western Florida . South African populations were also closely related to the Hawaiian introduction with 11 shared alleles that are also in western Florida.F) was higher in Hawaii compared to Florida and South Africa (HO) in South African populations averaged 0.46 which was similar to populations from east (HO = 0.44) and west ancestry (HO = 0.48) in Florida (P < 0.05) [see]. There was no evidence of significant linkage disequilibrium after Bonferroni correction for multiple comparisons (P < 0.003) for any of the locus pairs [see].South Africa had intermediate levels of genetic diversity between Florida and Hawaii . The inbh Africa . Observe Florida . The evak = 3) [seeand]. However, the low Delta K values (y-axis 0–4) indicate that there is no distinct clustering of populations in South Africa. Further, there was no geographic structuring according to allelic phenotypes. Some samples (n = 9) shared the same allelic profiles, despite having considerable geographic distances, for example sample 46  and 18 .A separate STRUCTURE analysis of only South African samples grouped all the samples into three populations  human-driven movement of plants for the ornamental trade and (ii) the long-distance dispersal of seeds by migrating American robins (Turdus migratorius) , uses the plant as a host but has not been found to be suitably damaging to the seeds to impact populations and therefore additional agents are required (S. terebinthifolia within the top 20 species (out of 299) that are high priority targets  from two geographic locations in Brazil—Ouro Preto, Minas Gerais state (Ouro Preto thrips) and Salvador, Bahia State —differed in their impact on the two haplotypes in Florida  and shown to perform better on S. terebinthifolia populations in Florida compared to the Salvador thrip (Apocnemidophorus pipitzi (Coleoptera: Curculionidae)    of the 592 Florida plants analysed in Schinus terebinthifolia haplotypes.Schinus terebinthifolia.P-values for linkage disequilibrium of each pair of loci across all populations (Fisher’s method). Using the Bonferroni correction (P < 0.003) there were no significant deviations.P-values of deviations from the Hardy–Weinberg equilibrium (HWE) across populations and marker (P <= 0.05). FL East = East Florida, FL West = West Florida, FL Admixed = hybrid populations in Florida, HW = Hawaii, SA = South Africa.K values showing the ideal number of populations as k = 2 based on 191 samples of Schinus terebinthifolia from South Africa, Hawaii and Florida using six microsatellite primer pairs and the Evanno method implemented in STRUCTURE HARVESTER program according to a-score optimization showing the optimum number of retained principal components (PCs) is 10.Schinus terebinthifolia from populations in South Africa, based on Bayesian clustering analysis of microsatellite loci with STRUCTURE ([see]. Sample ordered according to Q-value. The red cluster corresponds to population 1, the green cluster corresponds to population 2 and blue corresponds to population 3. The values in ordinate the shared ancestry according to percentage membership into each population.K values showing the ideal number of populations as k = 3 based on 51 samples of Schinus terebinthifolia from South Africa using six microsatellite primer pairs and the Evanno method implemented in STRUCTURE HARVESTER program according to plab078_suppl_Supplementary_MaterialClick here for additional data file.plab078_suppl_Supplementary_Table_S2Click here for additional data file.


Hyla orientalis) sampled in the Chernobyl region about thirty years after the nuclear power plant accident to investigate microevolutionary processes ongoing in local populations. Genetic diversity estimated from nuclear and mitochondrial markers showed an absence of genetic erosion and higher mitochondrial diversity in tree frogs from the Chernobyl exclusion zone compared to other European populations. Moreover, the study of haplotype network permitted us to decipher the presence of an independent recent evolutionary history of Chernobyl exclusion zone's Eastern tree frogs caused by an elevated mutation rate compared to other European populations. By fitting to our data a model of haplotype network evolution, we suspected that Eastern tree frog populations in the Chernobyl exclusion zone have a high mitochondrial mutation rate and small effective population sizes. These data suggest that Eastern tree frog populations might offset the impact of deleterious mutations because of their large clutch size, but also question the long‐term impact of ionizing radiation on the status of other species living in the Chernobyl exclusion zone.Despite the ubiquity of pollutants in the environment, their long‐term ecological consequences are not always clear and still poorly studied. This is the case concerning the radioactive contamination of the environment following the major nuclear accident at the Chernobyl nuclear power plant. Notwithstanding the implications of evolutionary processes on the population status, few studies concern the evolution of organisms chronically exposed to ionizing radiation in the Chernobyl exclusion zone. Here, we examined genetic markers for 19 populations of Eastern tree frog ( Pollution, as part of the major drivers of biodiversity loss , has severely altered many ecosystems   ambient radiation dose rate varied from 0.044 to 32.4 µSv/h. After capture, individuals were kept in individual boxes with a perforated cover and 2 cm of water until the next morning when they were euthanized and dissected to sample tibia muscle. Collected tissue was quickly frozen at −196°C, transported to IRSN labs in Cadarache (France), and stored at −80°C until DNA extraction. All animals were collected under the permit of Ministry of Ecology and Natural Resources of Ukraine . The geographic distances separating each pairwise combination of frog populations were estimated with ArcGIS and a UTM projection.In May and June 2016, 2017, and 2018 during the breeding season, we collected a total of 216 n Figure . For sim2.290Sr, and in leg muscle for 137Cs in the IRL‐SSRI Laboratory , and then reconstructed for the total frog knowing the total frog mass and the relative mass of bones (10%) and muscles (69%)  was estimated to contribute, on average, less than a quarter of the total dose rate  following the manufacturer's protocol. After the estimation of nucleotide concentration with a spectrophotometric measurement and an electrophoresis quality check, a 957 bp fragment of mitochondrial DNA, cytochrome b, and 21 nuclear microsatellites were studied (see Appendix 2.4π)  , and three geographical areas corresponding to three groups of populations in the Chernobyl region: one in the North close to the NPP, one South of the exclusion zone, and one including the Slavutych populations  in order to estimate genetic distance between populations, and represented these distances using Neighbor‐Joining trees with genetic distances estimated with MEGA  and private estimated haplotype number (npH) using hp‐rare  Ewens,  were cal) Ewens, . To desc) Ewens,  and calcs Figure . For mics Figure , ADZE  corresponding to specimens able to reproduce after the accident, (ii) the frequencies of haplotypes in the founder population based on the current diversity observed for the Slavutych populations (H18 and G18), (iii) the population size for each year during the 10 or 15 generations (N1−n), (iv) the nucleotide substitution rate (µ) and (v) the number of generations. A haplotype network was generated for the last generation for each data set obtained with a set of value for prior parameters.Simulations of mitochondrial haplotype networks were conducted with a method close to the Approximate Bayesian Computation  and a classical rate of nucleotide substitution in mitochondrial DNA for amphibians of 20.37 × 10π), the Tajima's D, the haplotype richness (nrH), the haplotype diversity (h), and the number of steps separating the ancestral haplotype to the most distant haplotype plus one. A Principal Component Analysis (PCA) was performed to compare simulated and observed descriptive statistics. The two first principal component axes were used to visualize both sets of descriptive statistics. A Ward hierarchical cluster analysis on Euclidean distance was used to select the 5th percentile of the simulated descriptive statistics closest to the observed descriptive statistics. The mean and median of the 5th percentile simulated descriptive statistics were calculated to estimate the posterior parameters 0N, the appropriate haplotype frequencies for the founder population, N1−n, and µ. Visualization of the haplotype network for prior, 10th, and 15th generation was done using TempNet  (“isolation by distance” hypothesis), was performed using a Mantel test . The correlation between two matrices, the genetic distance matrix obtained with the  Mantel,  with the Mantel, . Because Mantel, , the par Mantel, .D  and 1 transversion (A/T) Tables . We dete3.2h = 0.7308, π = 0.0024) were significantly higher  than those of other European populations   and Luninets, Belarus (h = 0) , while the G18 population had a genetic diversity fairly close to the genetic diversity of the CEZ populations (h = 0.6444)  Figure , showed ) Figure .S = 294, rho = 0.640, p = 0.007)   Table .3.3Fst < 0.093), differentiation estimated from cytochrome b sequences was relatively high (−0.173 < Fst < 0.426). For the mitochondrial marker, the two populations with the highest genetic differentiation from other populations of the Chernobyl region were the South West A17 and the North D18 . Genetic pairwise differentiations estimated on nuclear markers were similar to those estimated on mitochondrial markers, the most differentiated population being A17 , in opposition to the variance based on geographical regions .In both AMOVA, the highest variance was observed within populations (83.75% and 79.85%). However, the inter‐group variance based on years was not significant , and mitochondrial markers . The correspondence between nuclear and mitochondrial genetic distances described from NJ trees was also significant . The correlation between genetic distances and geographic distances could not be explained by the differences in ATDRs .Isolation by distance was significant for both nuclear , the central haplotype Figure . BecauseD = −2.2180, p < 0.01; Fu and Li D* = −4.4028, p = 0.002; R2 = 0.0289, p = 0.001). In contrast, the CEZ populations present a different pattern represented by haplotypes at one and two steps from the central haplotype, shared by many individuals .We detected a discrepancy between the structure of the CEZ haplotype network and those of all other populations, since the population sampled in Slavutych segregated similarly to populations from other European areas analyzed by Dufresnes et al. : the lars Figure , in red,3.5During the first simulation with classical wild frog population prior parameters, simulated haplotype networks did not match the observed one, the closest Euclidean distance being 11.13. The diversity of CEZ populations cannot thus be obtained with this first set of parameters Figure .max =100) and a high nucleotide substitution rate of 0.04 per haplotype per generation , but not when using nDNA (<0.1). The general structure of these populations is quite similar within the CEZ between mitochondrial and nuclear markers . Since s Figure —and the 4.3Hyla orientalis species  and that mitochondrial markers are useful to assess the mutagenic effect of ionizing radiation (Kam & Banati, 4.6Genetic diversity can be sensitive to many environmental parameters (Meeks et al., 5Our study on the genetics of the Eastern tree frog populations in the CEZ suggests the existence of a strong mutation process on mitochondrial DNA, resulting in an unexpected genetic structure of the CEZ populations comparing to other European populations. One challenge now is to understand the possible consequences of this genotypic effect on population status. Due to the crucial role of mitochondria (Roubicek & Souza‐Pinto, Appendix S1Click here for additional data file.Appendix S2Click here for additional data file.


Bombus terrestris), an economically important and widespread pollinator, which is considered to be quasi-panmictic at mainland continental scales. Here we aimed to (i) quantify genetic structure in 21+ populations of the buff-tailed bumble bee, sampled throughout two Eastern European countries, and (ii) analyse the degree to which structure is explained by environmental differences, habitat permeability and geographic distance. Using 12 microsatellite loci, we characterised populations of this species with Fst analyses, complemented by discriminant analysis of principal components and Bayesian clustering approaches. We then applied generalized dissimilarity modelling to simultaneously assess the informativeness of geographic distance, habitat permeability and environmental differences among populations in explaining divergence.The environment is a strong driver of genetic structure in many natural populations, yet often neglected in population genetic studies. This may be a particular problem in vagile species, where subtle structure cannot be explained by limitations to dispersal. Consequently, these species might falsely be considered quasi-panmictic and hence potentially mismanaged. A species this might apply to, is the buff-tailed bumble bee (Genetic structure of the buff-tailed bumble bee quantified by means of Fst was subtle and not detected by Bayesian clustering. Discriminant analysis of principal components suggested insignificant but still noticeable structure that slightly exceeded estimates obtained through Fst analyses. As expected, geographic distance and habitat permeability were not informative in explaining the spatial pattern of genetic divergence. Yet, environmental variables related to temperature, vegetation and topography were highly informative, explaining between 33 and 39% of the genetic variation observed.In contrast to previous studies reporting quasi-panmixia in continental populations of this species, we demonstrated the presence of subtle population structure related to environmental heterogeneity. Environmental data proved to be highly useful in unravelling the drivers of genetic structure in this vagile and opportunistic species. We highlight the potential of including these data to obtain a better understanding of population structure and the processes driving it in species considered to be quasi-panmictic.The online version contains supplementary material available at 10.1186/s12862-022-01963-5. Detecting genetic population structure and its underlying causes is crucial to better understand basic evolutionary ecological processes and how these are affected by human actions, as well as to improve conservation strategies. Population structure is often inferred using methods that are only based on genetic data, and do not take into account the geographic relationships between populations . These mPopulation structure results of a balance between gene flow, genetic drift, natural selection, and mutation. When dispersal becomes difficult, gene flow is reduced. This may be the case with increasing distance, or when habitats become difficult to traverse, resulting in patterns of genetic divergence known as isolation by distance  and isoTo this end, the field of landscape genetics –17 proviBombus terrestris). This highly polymorphic pollinator occurs across various environmental gradients )., we expected geographic distance and landscape resistance to play only minor roles in explaining population divergence.Here we aimed to quantify population structure and its drivers in the buff-tailed bumble bee across two countries that exhibit pronounced landscape heterogeneity that is readily exploited by this species , 24. IndWe used both spatially implicit and explicit analyses to identify the most likely drivers of population structure. Deploying 12 highly polymorphic microsatellite loci, we did not detect population differentiation using spatially implicit Bayesian clustering. However, Fst analyses demonstrated subtle yet marginally significant genetic divergence among populations, a finding that was partially corroborated using discriminant analysis of principal components . We furA total of 376 out of 385 buff-tailed bumble bees were successfully genotyped at 12 microsatellite loci  linkage disequilibrium (LD) for the locus pair ms39–ms80, which was, however, not supported by population pairwise analyses, where significant LD was detected only in the populations Drӑgusani and Valea Hotarului. As null alleles, stuttering, and deviations from both HWE and LD were not consistent across either loci or populations, we retained all loci in the data set.Using Micro-Checker , we deteO) ranged from 0.46 to 0.60 in a data set containing diploid females only   and 0.041 (upper 95% CI: 0.047) for ‘dpds’ and ‘mpds’, respectively. Fst values among pairs of sampling sites ranged from 0 to 0.07  in ‘dpds’ with Fst values between 0.046 and 0.065. None of the ‘mpds’ Fst values surpassed its corresponding upper 95% confidence interval. Pairwise and global Fst estimates in ‘dpds’ calculated with polysat [Observed heterozygosity . GenAlE polysat .K). Visual interpretation of the results computed using the ‘Correlated Allele Frequency model’ [K = 1), irrespective of whether or not admixture was assumed. This pattern was consistently inferred across all independent runs for each K, ranging from 2 to 25  native to Romania and Bulgaria [B. t. terrestris was present among our samples, as its known range is limited to the western border regions. Additionally, we would expect its presence to result in pronounced clustering, something we did not observe here. In summary, while Bayesian clustering suggested that the buff-tailed bumble bee resembles a quasi-panmictic population across Romania and Bulgaria, DAPC using clusters identified de novo suggested weak but still noticeable genetic subdivision undetected by Fst analyses.Despite the potential occurrence of two subspecies . Local habitat conditions were characterised using a set of topographical, climate and vegetation variables, and resistance distances were based on a species distribution model (SDM) generated previously . GDMs exThe environmental variables retained included temperature, precipitation, topography, measures of surface moisture, and vegetation density. Response curves (splines) visualise how the retained environmental variables contributed to the observed genetic differences and which variables were most informative in explaining the spatial pattern of divergence . This species is usually considered to show subtle to no structure at mainland continental scales. Using genetic data only, we inferred weak structure across Romania and Bulgaria, two countries that harbour pronounced landscape heterogeneity. Harnessing a landscape genetics approach, we related genetic divergence to this heterogeneity in the environment. Geographic distance was not informative, nor were resistance distances derived from a species distribution model that quantifies resistance to dispersal. Population structure in buff-tailed bumble bees thus follows a pattern of isolation by environment, where differences in habitat conditions reduce the fitness of dispersing individuals [Incorporating environmental data in population genetic studies might help to explain subtle population structure in vagile species, whose dispersal is usually not constrained by geographic distance or the habitat through which dispersal takes place. To assess the informativeness of environmental data, we quantified population structure in the widespread and abundant buff-tailed bumble bee  and slope. The importance of temperature did not come as a surprise, as it is a predictor of the distribution of  species , 77, and species . Hence, pothesis , 80, thepothesis . Indeed,strongly , 83, higstrongly , 85, theEven though differences in local temperatures might thus facilitate genetic divergence, the influence of this environmental variable on the species’ life cycle is more nuanced. Facultative endothermy  and the Another important variable retained in the final models was mean LAI. The mechanism through which this measure of greenness is associated with genetic structure remains unclear. Yet, mean LAI was highly correlated with percent tree cover  is a widespread and abundant pollinator species. Its native distribution covers much of the Palearctic realm, including Europe, North Africa, and the British and most Mediterranean and Atlantic islands [The buff-tailed bumble bee  [From each individual, we extracted DNA from one or two legs using the DNeasy Blood and Tissue Kit and QIAamp DNA Micro Kit . We followed the manufacturer’s protocols except for adding 20 µl of 1 M dithiothreitol solution to each sample, which facilitates the extraction of DNA from chitinous materials . Individ workers , can be lucorum) . We therlucorum) .2O, 0.4 µl bovine serum albumin (10 mg/ml), 1 µl primer solution  and 1.5 µl sample DNA. Samples were initially denatured at 95 °C for 15 min, followed by 25 cycles of denaturation , annealing  and extension . An additional 20 cycles were run using the following settings: denaturation , annealing  and extension . PCR products were visualised on an ABI3730XL capillary DNA sequencer (Applied Biosystems) using a GeneScan 500 LIZ size standard (Applied Biosystems) at Macrogen Europe (The Netherlands). Results were analysed using GeneMarker v.2.4.0 . Samples that had not amplified successfully or for which scoring had not yielded conclusive results were re-amplified and re-scored. Individuals that repeatedly failed to amplify or yielded inconclusive results for the second time were excluded. The presence of genotyping errors was assessed by re-amplifying and re-scoring 36 randomly selected samples, representing approximately 9.5% of all individuals. Scoring results were compared between the first and second run and the mean error rate for each locus was calculated in Microsoft Excel.We then amplified 12 previously developed  microsatBombus  deflates measures of heterozygosity, we identified and excluded putative males in ‘mpds’ based on observed multilocus genotypes. More specifically, individuals were considered males if they were heterozygous for a maximum of two loci, resulting in a data set encompassing diploid individuals only  correction [After excluding putative clones, full siblings and haploid males, we tested for null alleles, stuttering and large allele dropout in Micro-Checker v.2.2.3 , applyinrrection  using thrrection . For ‘mprrection . AdditioK) from 2 to 25 (number of populations sampled) and computed 5 iterations with a burnin period of 100,000 and 1,000,000 Markov chain Monte Carlo (MCMC) repetitions. Relative admixture between populations was estimated by Structure (INFERALPHA = 1). Because previous studies suggested that buff-tailed bumble bees are quasi-panmictic, and they are highly vagile, we hypothesised that admixture is common, and the corresponding model in Structure was biologically most meaningful. Yet, we also explored the performance of Structure’s ‘No admixture’ model by running two iterations with the aforementioned burnin period and MCMC repetitions. Additionally, as uneven sampling sizes among populations might result in an incorrect number of clusters [K to 23, the first run was computed with the settings specified above while for the second run we additionally set STARTATPOPINFO to 1 to initialise each individual at its own population [Following the computation of estimates of Fst, we assessed genetic structure in ‘cpds’ through Bayesian clustering in Structure v.2.3.4  using thclusters , two furpulation . Structupulation .As complex patterns of population subdivision might not be detected reliably using only one clustering approach, we complemented Structure runs with discriminant analysis of principal components DAPC,  implemenAs the likelihood of successful dispersal between populations decreases with geographic distance, gene flow starts to become limited and populations diverge through genetic drift. Under this scenario, a positive relationship between geographic and genetic distance is anticipated, a pattern termed isolation by distance IBD, . MoreoveWe considered all three potential mechanisms of population divergence in our analyses. In addition to straight-line geographic distance, we also included a measure of habitat permeability using resistance distances based on a previously published species distribution model , as wellWe characterised environmental conditions across Romania and Bulgaria using a set of 16 environmental variables compiled for previous species distribution and landscape genetic studies , 39  of rrestris . Computarrestris  with therrestris ), they rrrestris ). One caWe established associations between genetic data and environmental variables using generalized dissimilarity modelling implemented in the gdm R package v.1.3.11 . This exAdditional file 1: Table S1. Microsatellite loci used in this work, with original locus names [m), forward and reverse primer sequences (5’–3’) as well as information on null alleles and stuttering. Table S2. Basic population genetic statistics for each sampling location encompassing diploid (‘dpds’) and both haploid and diploid individuals (‘mpds’). N: number of individuals; NA: number of alleles; NE: number of effective alleles; AR: allelic richness, rarefied for seven individuals (k); uHE: unbiased expected heterozygosity; HO: observed heterozygosity. Observed heterozygosity values between ‘dpds’ and ‘mpds’ are largely congruent, as SPAGeDi, even though capable of working with mixed-ploidy data sets, does not include haploid individuals in calculating this metric. Table S3. Below the diagonal: Multilocus pairwise Fst values calculated with GenAlEx and based on a data set containing diploid individuals only. Above the diagonal: Corresponding FDR-corrected P values. Marginally significant Fst values and P values are indicated in bold. See Table S8 for population names. Table S4. Above the diagonal: Multilocus pairwise Fst values computed with polysat and based on a data set containing both haploid and diploid individuals. Below the diagonal: Corresponding bootstrap-derived upper 95% confidence intervals. See Table S8 for population names. Table S5. Above the diagonal: Multilocus pairwise Fst values calculated with polysat and based on a data set containing diploid individuals only. Below the diagonal: Corresponding bootstrap-derived upper 95% confidence intervals. See Table S8 for population names. Table S6. Discriminant analysis of principal components (DAPC) result showing the assignment of individuals to clusters identified de novo. Table S7. Pearson correlation coefficients of environmental variables at population locations harbouring both haploid and diploid individuals. See Table S9 for the abbreviations used. Table S8. Populations sampled, including their abbreviations, locations, and the number of individuals. ‘cpds’: full data set after exclusion of full siblings and clones; ‘pop10’: ‘cpds’ after excluding populations with fewer than 10 individuals; ‘mpds’: mixed-ploidy data set encompassing both haploid males and diploid females; ‘dpds’: data set containing diploid individuals only. Table S9. Environmental variables used. Those in bold were retained after stepwise elimination with a variance inflation factor ≥ 10. Table S10. Resistance matrix derived from Circuitscape, where higher values indicate higher predicted resistance to inter-population dispersal. See Table S8 for population names.us names , the priAdditional file 2: Structure output based on the ‘complete data set’ (‘cpds’) for selected values of K; result of the a-score optimisation for the DAPC runs performed as well as the DAPC result obtained using populations as a priori groups; a curve depicting model performance for different numbers of clusters inferred de novo; GDM splines produced from data sets encompassing haploid and diploid individuals  and diploid individuals only .


In opposition to the mother tongue hypothesis, the father tongue hypothesis states that humans tend to speak their fathers’ language, based on a stronger correlation of languages to paternal lineages (Y-chromosome) than to maternal lineages (mitochondria). To reassess these two competing hypotheses, we conducted a genetic–linguistic study of 34 modern Indo-European (IE) populations. In this study, genetic histories of paternal and maternal migrations in these IE populations were elucidated using phylogenetic networks of Y-chromosomal and mitochondrial DNA haplogroups, respectively. Unlike previous studies, we quantitatively characterized the languages based on lexical and phonemic systems separately. We showed that genetic and linguistic distances are significantly correlated with each other and that both are correlated with geographical distances among these populations. However, when controlling for geographical factors, only the correlation between the distances of paternal and lexical characteristics, and between those of maternal and phonemic characteristics, remained. These unbalanced correlations reconciled the two seemingly conflicting hypotheses. In contrast, on the basis of other findings from genetic and anthropological research [The hypothesis that language usage follows matrilineal inheritance has been supported by genetic evidence, as in the Austronesian-speaking populations and South American Indians ,2. This research , populatresearch . They suresearch .In addition, quantified language affiliations, such as the designation of language families and subgroups , and divHere, we reassessed the correlation between genetic and linguistic characteristics in 34 modern IE populations Fig. , for whiNeighbour-Nets were constructed to delineate the differences between 34 IE population groups clustering at the genetic and linguistic levels Fig. . The retTo investigate the relationships between genetic and linguistic characteristics, we performed the Mantel test on the pairwise genetic and linguistic distance matrices of 34 IE populations. Fig. P-value < 10−3), as did the correlation between mtDNA and phonemic distances . In addition, we performed two alternative partial statistical tests to validate the reliability of these observations (see Methods). The results of three partial statistical tests were consistent with each other (Table S1). Such observations of unbalanced correlations, after removing the effect of geography, suggest that the change in lexicon reflects the differences in paternal lines, while phonemic dissimilarity reflects the differences in maternal lines. Moreover, we adopted an alternative lexical data set provided by Bouckaert et al. [To exclude the geographical effects, we then adopted the partial Mantel test to reappraise the relationships between genetics and linguistics in these populations Fig. . When cot et al.  to validThese observations of unbalanced correlation between genetics and linguistics could be explained by population contact and admixture at first. If there is no contact and admixture between the populations or languages, the phylogenies of genetics and linguistics should ideally follow tree-like structures and resemble each other. However, population contacts have long been known to change local population structures and language systems. The causes of such population contacts include marriage between neighbouring populations or between local people and immigrants, such as military conquerors or merchants. In particular, the different performances of female and male dispersal have confirmed that females live more locally than males  see Sup. In otheThe language learning by local women could constitute the reason for the unbalanced correlation of mtDNA to lexicon and phonemes. Due to the social prestige of male immigrants, their local spouses have to adopt the language of their husbands and pass it to future generations ,10,15. TThe co-evolution between genes and languages is asymmetrical in IE populations. Our findings provide strong statistical evidence to reconcile the conflicting father tongue and mother tongue hypotheses. The populations involved in this study are located within a single continent and all of them speak languages belonging to the IE language family. Therefore, much of the genetic pattern may have its roots in the spread of IE languages. Further cross-continental comparison between genetic and linguistic data would provide us with more remarkable co-evolutionary processes of population and language. Notably, what we observed from the correlation between linguistics and genetics is macroscopic. The scenario that the mother learns her husband's language and teaches the children is definitely one possible mechanism, which has been elaborated by historical linguist van Driem . In the et al. [http://www.splitstree.org/) using default settings.To delineate the relationships between 34 IE populations and their languages, we applied the Neighbour-Net method ,38 to thet al. , we applet al.  to compaet al. [http://www.jeromeprunier.eg2.fr/5.html).In this paper, we used the Mantel test to detect the relationships between languages and genes, and the partial Mantel test to further study the correlation between languages and genes controlled with geographical effects. All statistical tests were implemented in Matlab® R2015b . The Matlab scripts for the Mantel test and partial Mantel test were provided by Prunier et al.  . The numbers of permutations in all Mantel or partial Mantel tests were set at 10 000 in this study.To validate the credibility of the statistical results, we adopted two alternative partial correlation tests. The first was the linear Pearson's correlation test  implemenet al. , to examWe here conducted a series of principal component (PC) analyses  (PCA) toet al. [P-values for t0 values over 100,000 permutations of geographical locations. All computational procedures of PCA, Procrustes analysis and permutation tests were implemented in Matlab® R2015b .Following Wang et al. , we calcWe performed the Jackknife resampling approach to evaluate the robustness of the statistical conclusions based on a partial Mantel test. In this study, we considered the balance of the samples sizes between Indo-Iranian and European populations, and designed two schemes of Jackknife resampling approach :Scheme I: we sampled all the available Indo-Iranian populations from the data set and randomly selected equal amounts of populations from the total European populations.Scheme II: we randomly selected the same number of population samples from the total IE populations in order to compare to the resampling in scheme I.et al. For each resampling scheme, the random selection was repeated for 500 times, and thus 500 Jackknife-resampled data sets of selected population sample were generated. For each data set, we reconducted partial Mantel tests to examine the correlation between these genetic and linguistic data controlling for geographical effects . The correlation coefficients and P-values were recalculated. For the correlation coefficients obtained via the Jackknife method, we listed the statistical descriptions including the median, minimum, maximum and 95% confidence intervals in Table S2. For the distribution of P-values, we calculated quantiles  and counted the number of P-values less than 0.05 or 0.01. We counted the occurrence of P-value < 0.05 and < 0.01 out of Jackknife 500 replicates to measure the robustness. Notably, the occurrence was a relative value to compare the results of different partial Mantel tests.Accordingly, we resampled 22 IE populations  for Dunn's data set, and 18  for a new lexical data set of 207 words by Bouckaert All linguistic and genetic data that support the findings of this study are available within the paper and its Supplemental FilesClick here for additional data file.


PCLO have been associated with different pathologies in global literature, but there are no data regarding this gene in Native American populations. The Amazonian Native American populations have lower genetic diversity and are more different from other continental groups. We investigated 18 genetic variants in the PCLO gene in Amazonian indigenous and compared our results with the ones found in global populations, which were publicly available in the 1000 Genomes Project, gnmAD and ABraOM databases. The results demonstrated that the variants of the PCLO, especially rs17156844, rs550369696, rs61741659 and rs2877, have a significantly higher frequency in Amerindian populations in comparison with other continental populations. These data outline the singular genetic profile of the Native American population from the Brazilian Amazon region.Genetic variations in  PCLO gene on chromosome 7q21.11 (GRCh38) encodes a presynaptic cytomatrix protein called piccolo (piccolo presynaptic cytomatrix protein), which is involved in the establishment of active synaptic zones and in synaptic vesicle trafficking [PCLO is studied in neuroscience, as it plays a role in modulating monoaminergic transmission, e.g., transmission of serotonin (5-HT), adrenaline, noradrenaline and dopamine [PCLO have been associated with different pathologies in global literature, such as major depressive disorder [PCLO in general populations, but there are no data regarding this gene in Amerindian population. Information present in clinical databases—such as ClinVar, from National Center for Biotechnology Information  and Brazilian Initiative on Precision Medicine —regarding this gene are also rare.The 1.11 GRCh8 encodesdopamine ,5. Piccodopamine ,7,8. Thedisorder ,10, bipodisorder ,13. TherPCLO gene can be compared intra- and interpopulation. Additionally, the molecular markers may have clinical applications, working as diagnosis and treatment tools for the Amerindian population and mixed populations with strong Amerindian ancestry, as in Brazil [In the latest census in 2010, the Brazilian government estimated the Native Amerindian population in approximately 897,000 individuals with 305 ethnicities. This population has been reported in all states in Brazil; however, they are highly concentrated in the north of the country, within the Amazon region . Great en Brazil .PCLO molecular profile in Amerindian populations from the Brazilian Amazon, and to compare these findings with data from the general Brazilian population described in ABraOM, as well as with the five continental populations available in the 1000 Genomes Project and Genome Aggregation Database (gnomAD).Therefore, this study aimed to characterize the http://conselho.saude.gov.br/comissoes-cns/conep/; accessed on 13 January 2022) and by the Research Ethics Committee of the Tropical Medicine Center of the Federal University of Pará (CAE: 20654313.6.0000.5172). All individuals and community leaders signed an informed consent form (TCLE).The study was approved by the National Research Ethics Committee .http://www.1000genomes.org; accessed on 13 January 2022). This sample included 661 individuals from Africa (AFR), 503 from Europe (EUR), 347 from the Americas (AMR), 504 from East Asia (EAS) and 489 from South Asia (SAS).The Amerindian population data were compared with representatives of five continental populations obtained from the 1000 Genomes Project, a public catalog of human variation and genotype data (available at: https://gnomad.broadinstitute.org/), for the five continental populations investigated . Finally, the Native American population of the Amazon was also compared in our analyzes with the Brazilian population, which were obtained from the ABraOM database,  a repository containing genomic variants gathered by sequencing the complete exome of individuals from São Paulo, the largest city of Brazil, located in the Southwest Region. All databases were accessed on 13 January 2022 to extract genomic data.In order to use data with a larger sample, we also added to our analysis population data available in the Genome Aggregation Database  and SureSelect Human All Exon V6  kits, following the manufacturer’s recommendations. The sequencing reactions were performed on the NextSeq 500® platform  using the NextSeq 500 High-output v2 Kit 300 cycle kit .Libraries were prepared using the Nextera Rapid Capture Exome  and filtered to eliminate low quality reads . Then, the sequences were aligned with the reference genome (GRCh38) using the BWA v.0.7 tool .Reads in FASTQ format were analyzed for quality . Subsequently, the alignment had to be processed to remove duplicate readings , mapping quality recalibration and local realignment . Finally, the result was processed in search of variants  of the reference genome. The allelic variants were annotated in the ViVa®  software. Markers in PCLO gene were also selected in coverage, where the readout should be high coverage, with a minimum of 10 reads .After alignment to the reference, the generated file was indexed and sorted .All statistical analyzes were performed using the R Studio v.3.5.1 program , including the Discriminant Analysis of Principal Components (DAPC). Significant differences in allele frequencies between populations were analyzed by Fisher’s exact test. The False Discovery Rate (FDR) proposed by  was usedPCLO were classified as moderate impact, two variants as modifier impact and four as low impact variants. A total of 18 variants were identified in the Amazonian NAT, with 16 SNVs (Single Nucleotide Variants) and two INDELs (Insertion–Deletion). Based on the location and the type of the genetic modifications, 12 variants of PCLO. Frequency data of each variant in the five continental populations were taken from the 1000 Genomes project database and the frequency of markers in the Brazilian population was taken from ABraOM, so that we could compare them to the frequencies of NAT populations. Six of the eighteen variants were not found in NAT populations. The rs550369696 variant was found only in NAT population. The rs762371134 have no frequency data in the 1000 Genomes Project, so the frequency data presented in this database are the result of the gnomAD analysis. Thus, we represented their frequencies by “ND”, which means “no data” for this variant.PCLO gene according to the data described in gnomAD browser. PCLO gene markers differed the most was the African one, with 10 of the 18 having frequencies that are notably higher in Native American populations .For the American population of the 1000 Genomes project, three of the investigated variants showed significant difference from the NAT population  . We woulp-Value = 0.0021) and EUR  populations were statistically different from the NAT population regarding the SNV rs17156844. For the marker rs550369696, the Native American population did not have higher frequencies when compared to any of the continental populations or the ABraOM. However, the NAT-AFR analysis remains significant, with six  of the eighteen investigated variants being more frequent in NAT than in the African population, of which all obtained the same result in the analysis of the NAT-AFR in 1000 Genomes. In the results compared to the ABraOM population, four markers  showed a higher frequency of distribution in the Amerindian population, and with the exception of rs762371134, all of which obtained the same results in the above-mentioned analysis.When we analyzed the results from gnomAD, we noticed some differences with the data presented above for the 1000 Genomes Project . Only thThe comparative analysis of these two databases allows a more accurate visualization of the genomic data of the investigated population, as the databases use different sample numbers for each investigated continental population. Thus, the differences and similarities of each database are within the expected range.PCLO gene, modulated in the five continental populations described in the 1000 Genomes Project database and in the gnomAD database. It demonstrated a more significant distance between the population of interest (NAT) and the African population, while showing a greater proximity between the NAT population and the EAS and SAS populations.Discriminant Analysis of Principal Components (DAPC) Scatterplot is presented in PCLO encodes Piccolo, a protein that builds the presynaptic cytoskeletal matrix, which is believed to be involved in modulating neurotransmitters’ release [PCLO gene in humans can lead not only to synaptic dysfunction, but also to loss of brain and cerebellar volume, suggesting severe neuronal loss [ release ,22. Stud release . Geneticnal loss . Studiesnal loss ,13,24. To date, few genetic screening investigations have been carried out in Amerindian populations, especially in the Brazilian Amazon ones; thus, this group is epidemiologically and genetically understudied . TraditiPCLO gene in Amazonian Amerindians, a population not described in the largest available databases on human genetic variability, the 1000 Genomes Project and gnomAD. Brazilian efforts to identify genetic variants, such as ABraOM, show the importance of not only investigating Brazilian population, but also the various indigenous ethnic groups spread across all country. Our results showed that, although many investigated variants have a similar frequency distribution between continental populations and the population described in ABraOM, at least 10 variants differed significantly between Native American and African populations in the analysis of 1000 Genomes. When looking at the NAT-AFR data in gnomAD, the rs2715150, rs2522833, rs10261848, rs28680905 and rs12668093 populations showed the same result as the other analysis for these populations, corroborating data regarding the genetic variability between Native American populations and other continental populations. Likewise, the DAPC analysis of PCLO showed that the NAT and AFR populations are the most genetically distinct, confirming what is known about history of human populations, which indicates that the Amerindian and African groups represent the extremes of the evolutionary process [This is the first study to investigate the  process .p-Value 1000 Genomes = 0.0060; p-Value gnomAD = 0.0021) and rs2877  are distributed differently in the indigenous population, showing high frequency in the Amazonian Native compared with the American population. These data agree with the finding by Wang and collaborators [We also found in both analyzes that the frequencies of the variants rs17156844 , rs2715150 , rs61741659 , rs2877  and rs2522833  differed significantly between these populations. Our result endorses the observation of Santos et al. [All populations included in the study had lower allele frequencies than the NAT population in at least one s et al. , who invs et al. . Thus, tFinally, the knowledge of the different patterns of genetic diversity in human populations is important in many health and genetic areas, as it can be used, for example, to investigate and validate new insights in the study of complex diseases, thus understanding the predisposition, diagnosis, prognosis and therapies for indigenous populations, and for populations with a high level of admixed, such as the Brazilian one. Therefore, we aimed to collaborate in the creation of public policies that help to optimize the quality of life of indigenous populations. Furthermore, the knowledge produced is also basis for inferences about human evolutionary history ,36.PCLO variants have a significantly higher frequency in Native American populations, especially for rs17156844, rs550369696, rs61741659 and rs2877, than in other continental populations, as well as in population of Southwest Brazil. The data generated in the present study contributed to the understanding of the genetic influence of PCLO in a poorly studied group, in addition to providing important subsidies for future association studies, which aim to identify individuals more susceptible to pathologies due to genetic alterations of PCLO in Native American populations, as well as in other populations with a high degree of admixed with these groups. This is the first study to perform the PCLO exome in NAT populations from the Brazilian Amazon region; thus, we hope that these data may help in the establishment of future public policies for this population.The results showed that


Channa argus), and provide atheoretical basis for breeding of C. argus, the investigation of genetic diversity and population structure were investigated based on the complete sequences of mitochondrial DNA D-loop region for three cultured ‘white’ type C. argus populations, and four ‘bicolor’ type C. argus populations were used to compare with them; 28 mutation loci and 30 haplotypes were found in the D-loop sequence of all individuals with a total length of 907 bp. The highest haplotype diversity (dH) and nucleotide diversity (iP) in the ‘white’ type C. argus populations were 0.505 and 0.00057, respectively, which lower than those in the ‘bicolor’ type C. argus populations . Population differentiation values (FST) show that the four ‘bicolor’ type C. argus populations had obvious genetic differentiation (Fst: 0.21902–0.49428. p < 0.01), but not in the three ‘white’ type C. argus populations (Fst: −0.00571 to 0.07261. p > 0.05). The phylogenetic tree and Median Joining (MJ) network showed that the genetic distance among ‘white’ type C. argus populations is very close. Therefore, much attention should be paid to protecting population genetic diversity and avoiding inbreeding in the breeding of ‘white’ type C. argus.To analyze the genetic background of ‘white’ type Northern snakehead ( Channa argus) is the most widely distributed and most prolific species in the Channidae , Neijiang city (NJ), and Leshan city (LS). Besides, 200 individuals of ‘bicolor’ type C. argus were collected, among which 50 individuals each were obtained from Donghai city (DH), Wuhan city (WH), Jurong city (JR), and Huzhou city (HZ).A total of 350 individuals of two color morphs ocations ; 150 indA part of caudal fin was collected from each individual, preserved in 95% alcohol and stored at −20 °C in the herbarium of Fishery Institute of the Sichuan Academy of Agricultural Sciences. The genomic DNA was extracted using an Ezup Column Animal Genomic DNA Purification Kit  and stored at −20 °C.C. argus (GenBank NC015191.1), the upstream primers and downstream primers were 5′-GCCTCTTTCCTTTACTTCTC-3′ and 5′-GGGTGTATTGAGCCTGATA-3′, respectively. An amplification reaction was carried out in 25 μL volumes consisting of 12.5 μL of 2xTaq PCR mix buffer , 1 μL of 100 ng/μL DNA template, 1 μL of 10 mM of each primer, and 9.5 μL of sterile ultrapure water. The PCR amplification procedure was as follows: predenaturation at 94 °C for 3 min, 36 cycles of amplification , extension at 72 °C for 10 min, and finally preservation at 4 °C. The PCR products were bidirectionally sequenced by Sangon Biotech Co., Ltd.The primers were designed using Primer 5.0  of ‘bicolor’ type C. argus was 0.187–0.911, and the dH of ‘white’ type C. argus was in the middle (0.301–0.505). The nucleotide diversity (iP) and average nucleotide differential number (K) of ‘bicolor’ type C. argus  were higher than ‘white’ type C. argus . The Tajima’s D values showed that all the populations did not significantly deviate from neutral (p > 0.05).A total of 350 homologous sequences of 907 bp were used for the genetic diversity analysis. A total of 28 nucleotide variation sites and 30 haplotypes (Hap) were detected in all individuals . The hapSTF) of ‘white’ type C. argus ranged from −0.00571 to 0.07261 (C. argus was higher (0.21902–0.85314). The STF among the three ‘white’ type C. argus populations was not significant (p > 0.05); but was significant among ‘bicolor’ type C. argus populations and between the two color morphs of C. argus (p < 0.001). The gene flow (Nm) values among ‘bicolor’ type C. argus were less than 1, and the Nm absolute values among ‘white’ type C. argus were more than 1  network was constructed for the identified 30 haplotypes . Only thdH and iP proposed by Grant and Bowen , the WH and HZ ‘bicolor’ type C. argus populations  showed higher haplotype diversity, and the other populations showed lower haplotype diversity (dH < 0.5). The nucleotide diversity in all the two color morphs of C. argus was low (iP < 0.005), indicating slight genetic divergence across. However, the Pi and K of ‘bicolor’ type C. argus  were higher than that in ‘white’ type C. argus ; the genetic diversity level of ‘white’ type C. argus populations was lower than ‘bicolor’ type C. argus populations. Few new parents introduced, thus decreasing the population genetic diversity. The lower genetic diversity is less tolerant to environmental stress ; moderate differentiation was observed between the WH and JR populations ; high differentiation was observed among the other ‘bicolor’ type C. argus populations , indicating that the alleles on mitochondrial DNA D-loop region were differentiated and fixed in four ‘bicolor’ type C. argus populations. The stF of three ‘white’ type C. argus populations was −0.00571, 0.01909, and 0.07261 (p > 0.05); no significant differentiation was observed among the ‘white’ type C. argus populations. Nm < 1 between populations indicates that the population might be differentiated due to genetic drift; Nm > 1 indicates that the level of gene flow between populations was higher, and the genetic differentiation between populations was smaller (Wang et al. Nm among the four ‘bicolor’ type C. argus populations were less than 1, indicating that geographic isolation had completely hindered the gene exchange of the four populations, but the absolute values of Nm among the three ‘white’ type C. argus populations were more than 1, indicating that the level of gene flow among those populations was high.C. argus populations. The MJ network showed that the haplotype number in ‘white’ type C. argus was 10% of all the haplotypes; the genetic diversity of ‘white’ type C. argus was less than ‘bicolor’ type C. argus. The results of this study showed that the genetic diversity of ‘white’ type C. argus populations was relatively low. Therefore, attention should be paid to protecting the genetic diversity of ‘white’ type C. argus and to avoid inbreeding.Genetic distance can be used to analyze the degree of genetic differentiation among different populations. The UPGMA phylogenetic tree indicated that a closer relationship was maintained in the ‘white’ type C. argus populations and four ‘bicolor’ type C. argus populations, providing a theoretical basis for breeding, fishery resource protection, and sustainable development of C. argus. However, the genetic diversity and population structure of wild ‘white’ type C. argus populations were not analyzed in this study, and the genetic background could not be completely revealed. The studies should continue to use the mitochondrial DNA D-loop region of wild ‘white’ type C. argus populations to completely reveal the genetic background of ‘white’ type C. argus and to provide a theoretical basis for fishery resource protection in the future.In this study, the genetic diversity and population structure were evaluated based on the complete sequences of mitochondrial DNA D-loop region for three cultured ‘white’ type Wei Fan and Lu Zhang, Conceptualization, Data analysis and interpretation, Writing original draft, Writing review and revising; Su Jian, Yu Luo, and Xiao-Lei Jiao, Conceptualization, Data analysis, Validation, Writing review and editing; Zhi-Peng Huang, Han Zhao, and Zhong-Meng Zhao, Data curation, Data analysis, Writing review and editing; Yuan-Liang Duan, Qiang Li, and Jun Du, Formal analysis, Writing review and editing; Ting Zhuo, Quan-Sen Su, and Jun Wu, Conceptualization, Writing review and revising; Jian Zhou, Conceptualization, Data curation, Supervision, Funding acquisition, Writing original draft, Revising it critically for intellectual content; and the final approval of the version to be published; and that all authors agree to be accountable for all aspects of the work.This study was approved by the Institutional Animal Care and Use committee of the Neijiang Academy of Agricultural Sciences, Neijiang, Sichuan, China, under permit no. NAS-S20210501. All experiments were carried out in accordance with the Guide for the Care and Use of Experimental Animals of China.