Austropotamobius pallipes, is listed as “endangered” by the IUCN and included in Annex II of the EU Habitat Directive and requires especially attention. Currently, implemented conservation management strategies require a better understanding of the genetic diversity and phylogeographic patterns, as well as of its evolutionary history. For this purpose, we have generated the largest datasets of two informative ribosomal mitochondrial DNA regions, i.e., cytochrome oxidase subunit I and 16S, from selected populations of the WCC covering its geographical distribution. These datasets allowed us to analyze in detail the (i) genetic diversity and structure of WCC populations, and (ii) divergence times for Iberian populations by testing three evolutionary scenarios with different mtDNA substitution rates . The results indicate high levels of haplotype diversity and a complex geographical structure for WCC in the Iberian Peninsula. The diversity found includes new unique haplotypes from the Iberian Peninsula and reveals that most of the WCC genetic variability is concentrated in the northern and central-eastern regions. Despite the fact that molecular dating analyses provided divergence times that were not statistically supported, the proposed scenarios were congruent with previous studies, which related the origin of these populations with paleogeographic events during the Pleistocene, which suggests an Iberian origin for these WCC. All results generated in this study, indicate that the alternative hypothesis of an introduced origin of the Iberian WCC is highly improbable. The result of this study, therefore, has allowed us to better understand of the genetic diversity, structure patterns, and evolutionary history of the WCC in the Iberian Peninsula, which is crucial for the management and conservation needs of this endangered species.European crayfish species are a clear example of the drastic decline that freshwater species are experiencing. In particular, the native species of the Iberian Peninsula, the white clawed-crayfish (WCC)  Aphanomyces astaci and spread by American invasive crayfish species [Freshwater ecosystems are among the most diverse and vulnerable in the world  while ba species . This is species  and play species –10. Thus species , trigger species . TherefoPontastacus leptodactylus), the thick‐clawed crayfish (Pontastacus pachypus), the noble crayfish (Astacus astacus), the white-clawed crayfish (WCC) , the stone crayfish (Austropotamobius torrentium) [Austropotamobius bihariensis [i.e., Andalucía, Aragón, Cataluña, Extremadura, Galicia, La Rioja, Navarra and País Vasco). Thus, because of the above reasons, action and management plans have been implemented in Spain since 1996 [To date, there are six native crayfish species in Europe: the narrow-clawed crayfish, (rentium) ; and theariensis . Most ofariensis . Specifiariensis , (ii) unariensis , (iii) uariensis , and  Austropotamobius italicus, which is distributed from the Balkan to the Iberian Peninsula. The lineage A. italicus comprises four clades that are distributed from eastern to western Europe: A. i. carsicus, A. i. meridionalis, A. i. carinthiacus, and A. i. italicus [The WCC species is distributed across western, central, and southern Europe ,27. Its italicus ,29–32.A. i. italicus clade [A. italicus from its ancestral range and the subsequent differentiation may have taken place during the Pleistocene [A. i. italicus populations from the Iberian and Italian Peninsula that could have taken place during the early last glacial maximum, about 34,800 years ago [The first genetic studies on the Iberian WCC populations showed that these belonged to the us clade  and suggus clade ,33. In ous clade : (i) oneus clade ,35–39. Tus clade –39. Moreus clade –39 that istocene  as well ears ago . Howeverears ago , which a16S rRNA (16S) and/or cytochrome c oxidase subunit one (COI) mtDNA genes. Although these mitochondrial genes evolve at different rates [16S and COI mtDNA markers, such as substitution rates for arthropods [The interpretations of the origin of the Iberian WCC have been based on the selected DNA regions used in these previous studies. Most genetic studies performed in crayfish have been based on mtDNA regions, specifically the nt rates –43, bothnt rates –47 and, nt rates ,38,39,48nt rates –39. In mthropods ,50, decathropods ,51, grapthropods ,52 or snthropods ,53.16S and COI mtDNA sequences set from the whole geographical range of populations of WCC collected so far. For this purpose, we studied: (i) the genetic diversity and structure of WCC populations using two datasets with different concatenated length fragments of these mtDNA genes, and (ii) the divergence times for Iberian and Italian populations by testing three selected evolutionary scenarios with different mtDNA substitution rates . The results of this study are crucial for the management and conservation needs of this endangered species.Therefore, in this study, we aimed to elucidate the genetic diversity and structure, and the origin of the WCC in the Iberian Peninsula by generating and analyzing the information from the largest All experimental procedures, animal manipulations, and field sampling were conducted in accordance with both EU and Spanish legislation. All analyses were performed following the regulations of the Spanish Ministry of Economy (MINECO). No additional permits were necessary for the laboratory studies, as ethical approval under Spanish law is not required for working with arthropod invertebrates. Furthermore, this study was carried out in strict accordance with the recommendations and protocols established in prior research. A total of 159 specimens of WCC were collected from 35 Iberian and Italian populations  and covered the whole geographical distribution range of the WCC as well as all lineages and clades previously defined for this species complex ; and (ii) dataset 2, which included the sequences from WCC crayfish sampled in this study and 515 WCC samples corresponding to 72 populations from the Iberian Peninsula and Italy download from GenBank and generated in previous studies [16S sequences and 1151 bp for COI sequences (concatenated length of 2449 bp).To compare the resolution of two previously used approaches to study the genetic diversity and structure of WCC populations, we generated two datasets based on the total length of the  regions : (i) dat studies ,38,39. TA. i. italicus clade in order to equal the sample size in both regions and compare these results, since the number of the populations and, consequently, crayfish, was higher for the Iberian Peninsula in both datasets  and the mean rarefied number of shared haplotypes between these two regions. We statically analyzed the rarefied data with those observed applying a Pearson chi-squared test to detect differences between the number of observe and expected haplotypes. Finally, we represented the mutational changes between the sequences throughout the most parsimonious haplotype network using TCS v.1.21 [We used the program DNAsp v.5.10.01  to estimdatasets . The numS v.1.21  and the S v.1.21 .i.e., lineages and clades). We used JModelTest v.2.1.10 [16S and the COI mtDNA regions, under the Bayesian Information Criterion (BIC). We used the Bayesian Inference (BI) phylogenetic approximation, implemented in MrBayes v.3.2.6 [i.e., the 16S the COI mtDNA genes), and combined . Sequences of stone crayfish (A. torrentium), noble crayfish (A. astacus), and narrow-clawed crayfish (P. leptodactylus) were used as outgroups. Nodes with posterior probabilities (pp) values greater than 0.95 in BI were considered supported. Resulting phylogenetic trees were visualized using FigTree v.1.4.3 [To confirm the genetic identity of the sampled crayfish populations, we performed phylogenetic analyses with the different haplotypes of the mtDNA sequences of the crayfish collected here and those found in dataset 1, which included all the genetic groups defined for the WCC species  for a given K.We examined the WCC genetic structure in both datasets with a spatial analysis of the molecular variance of the populations using SAMOVA v2.0 . This to16S and COI mtDNA sequences from dataset 1. We used previously reported divergence rates for each mitochondrial gene as method of calibration of nodes. We selected different substitution rate values for each mtDNA marker, creating three divergence scenarios: (i) for the first scenario , we selected the highest substitution rate reported and used for each mitochondrial gene in previous studies, i.e., a substitution rate of 0.012 per site per million years for 16S gene [COI gene [i.e., a substitution rate of 0.008 per site per million years for 16S gene [COI gene [i.e., a substitution rate of 0.010 per site per million years for 16S gene [COI gene [16S and COI markers for all the scenarios. The “Clock model” prior was set as uncorrelated relaxed clock with a lognormal distribution [We used BEAST v1.8.4  , to esti16S gene  and 0.02COI gene ,53; (ii)16S gene  and 0.01COI gene ,50;  with the mean and 95% highest posterior density (HPD) interval for each node age.Each BEAST analysis was run with independently with 100,000,000 generations and parameters were sampled every 10,000 generations. Trace files were checked in TRACER  for convCOI sequences for the GIR5 population showed double peaks in 16 positions. These double peaks were only considered when the electropherograms were well-defined and there was a clear difference from the baseline . The dataset 2 included a total of 668 WCC samples from 106 populations (34 populations from this study and 72 more obtained from GenBank), with a longer region length of 1298 bp for 16S sequences and 1151 bp for COI sequences, i.e., a concatenated length of 2449 bp. These populations were from the Iberian and Italian peninsulas.The dataset 1 included a total of 1344 WCC samples from 249 populations (34 populations from this study and 202 more obtained from GenBank), with a length of 414 base pairs (bp) for We estimated the genetic diversity indices for the populations in each dataset. The WCC populations from dataset 1 showed 132 polymorphic sites and hosted 92 haplotypes. This dataset had a high mean haplotype diversity (Hd = 0.735). Populations CRO3, CRO6, GRA9, IT6, BOS6, BOS10, CRO17, CRO18, CRO19, CRO20, SO3, TE1 and TE7 had the highest haplotype diversity (Hd = 1), but for nine of them only two specimens were analyzed . The 18%i.e., lineages and clades) corresponding to those previously defined for the WCC species: A. pallipes, A. i. carsicus, A. i. meridionalis, A. i. italicus, and A. i. carinthiacus. Most of the specimens clustered into one of the following four haplotypes: H1 (653 specimens), H6 (201 specimens), H34 (50 specimens), and H35 (72 specimens) in dataset 1 , followed by A. i. italicus clade (20 haplotypes), A. pallipes lineage (11 haplotypes), A. i. carsicus clade (seven haplotypes) and, finally, A. i. carinthiacus clade (two haplotypes). All the Iberian populations were clustered with the A. i. italicus clade, except the GIR10 population, which belonged to the A. i. meridionalis clade. Of the 20 haplotypes belonging to A. i. italicus clade, 13 were unique from Iberian populations , five were unique from Italian populations , and only two haplotypes were shared, one with Italian populations (H1) and the other with Italian and French populations (H6)  shared by Iberian and Italian populations, seven of them unique from Italian populations  and, the other 41 of them unique from Iberian populations  . These uons (H6) . The mosons (H6)  of the Aulations , Table 1ulations . Most ofulations .A. i. italicus clade in dataset 1 , i.e., there were no statistical differences between the number of unique haplotypes in the Iberian and Italian regions. The rarefied number of shared haplotypes between these regions was the same as those of raw data; two shared haplotypes in dataset 1 and one shared haplotype in dataset 2  that clustered within A. i. italicus clade. On the other hand, the analysis of the COI region showed that all these crayfishes clustered within the A. i. italicus clade, except one , which clustered along with the A. pallipes clade . These sequences correspond to haplotypes H1, H6, H7, H11, H17, H18, H21, and H22, defined by dataset 1 . The maximum FCT value (FCT = 0.96897) was obtained for Kd1 = 20, maximizing the genetic variance between groups . The genetic variation among populations within groups and within populations were low . For dataset 2, the analysis clustered the 107 populations into 18 groups as the optimal genetic structure , Gd24 (11 populations), Gd25 (5 populations) and Gd212 (7 populations), while the other groups were formed by one or two populations. The maximum FCT value (FCT = 0.72861) was obtained for Kd2 = 18, i.e., when the percentage of genetic variation among groups was the maximum . The genetic variation among populations within groups was low (5.08%) while we obtained a slight genetic variation within populations (22.06%).The SAMOVA analyses results are shown in ture see . The maid21) with Italian populations  in all the scenarios. One of these clades, i.e., A. i. italicus, comprised the majority of the samples from the Iberian Peninsula. This clade was dated to HPD 0.1634–0.4696 Mya  for the low rates scenario  in the three scenarios. For the low rates scenario  of the Iberian and Italian populations showed similar levels in both analyzed datasets. These results showed that there are populations with high levels of haplotype diversity while others only contained a single haplotype. This finding contrasts with the hypothesis of an introduction from Italy, since in this case, we would expect a lower haplotype diversity in the Iberian populations than that of the Italians, or any diversity in the Iberians. The lack of diversity in some Iberian populations can be explained by different reasons, such as the recent intense translocations after the strike of the crayfish plague . HoweverA. astaci responsible for the devastation of up to 80% of the European crayfish populations [Moreover, we found that the nucleotide diversity in WCC of the Iberian and Italian populations is low. Previous studies reported nucleotide diversity values for several European regions  similar to those obtained in this study . Some auulations  and otheulations . Therefoi.e., b, d1 and d2-haplotypes) [i.e., a-haplotype) [The Tajima´s D and Fu´s Fs indices indicated that some Iberian and Italian populations  have suffered a sudden population contraction as it would be expected from a recent population bottleneck, and other Iberian populations  are experiencing a population expansion. The results of these indices seem to show the dynamics for all European crayfish species as a result of the impact of the crayfish plague ,81, and lotypes) –85. Howeplotype) ,87. Thusplotype)  can explA. i. italicus are unique to the Iberian or Italian populations, while the number of shared haplotypes between the populations from both peninsulas is low in both datasets. This contrasts again to what we would be expected in a scenario of an introduced population from Italy to the Iberian Peninsula. High haplotypic diversity as well as unique haplotypes have been interpreted as support for the native origin of crayfish in the Iberian Peninsula [i.e., the most common haplotype (H1), and another haplotype shared also with France (H6). This is compatible with a previously theory of a Circum-Mediterranean distribution of A. i. italicus before the Last Glacial Period (LGP) in Pleistocene [i.e., the size used in the dataset 2) allows to detect a higher variability than that of the short region size  commonly used in previous studies [Furthermore, we found that the majority of haplotypes of eninsula ,36,38,39istocene ,36,88. Tistocene ,90 associstocene ,91,92. H studies .i.e., the Iberian and Italian populations) and, therefore, support previous studies indicating an origin in the Iberian Peninsula [Austropotamobius populations. However, the lack of the genetic structure shown in dataset 1  seems to be mainly a computational artefact since the SAMOVA analysis does not allow to create more than 20 population groups. We speculate that Iberian populations from dataset 1 would show a biogeographic structure if there were no limits to the number of potential population groups.The populations of WCC in the Iberian Peninsula were geographically structured as judged from analyses of dataset 2  before the LPG in Pleistocene [The divergence time estimates suggested a separation of the Iberian and Italian populations of the WCC several thousands of years ago during the Pleistocene for all the proposed scenarios. Even though the results of molecular dating were not fully conclusive, since split nodes between Iberian and Italian populations were not supported by posterior probability values, the estimated values in the Pleistocene are in accordance to the results of previous research performed by Pedraza et al.  and Jeli studies ,36. In aistocene ,36,88.Astacus astacus have shown that claims of an anthropogenic origin of this species in Scandinavia were the result of wrong translations of historical documents [Therefore, all these results were congruent with the native origin of WCC populations of the Iberian Peninsula, as previously pointed out by Pedraza-Lara et al. , Jelić eocuments .Our results suggest the effects of the massive extinction events that the Iberian WCC have suffered during the last decades and in the past. The reduction of genetic diversity leads to the loss of adaptive potential ,95, and A. astaci haplotype  [A. i. meridionalis clade as judged by 16S region or to A. i. italicus clade as judged by COI region). Moreover, the COI region has showed double peaks in some variable positions. Once contamination has been discarded as the cause for the presence of double peaks in the COI region sequences, the obtained results appear to indicate the existence of different mtDNA sequences within these crayfishes. This phenomenon of heteroplasmy has been recently reported in many organisms, including crustaceans such as the spiny spider crab Maja brachydactyla [Callinectes sapidus [de novo mutations, (ii) recombination events, (iii) paternal leakage, (iv) biparental inheritance or (v) doubly uniparental inheritance [A. i. meridionalis and A. i. italicus crayfishes, since both groups are inhabiting the northeastern of the Iberian Peninsula, near the Pyrenees. However, there are other two different possibilities that could be explained this situation. Firstly, the formation of nuclear mitochondrial pseudogenes (NUMTs) [COI-like sequences in many crustaceans, including crayfish [Finally, we point out that there is also a need for unraveling the mitochondrial incongruence found in GIR5 population . This poplotype) . In thisydactyla ,97, or t sapidus . There aeritance ,99. This (NUMTs) ,101, whi (NUMTs) . There acrayfish ,104. Seccrayfish . FurtherS1 FigExample of double peaks in the forward (up) and reverse (down) reads of from at positions 12 and 108.(DOCX)Click here for additional data file.S2 FigBayesian inference phylogenetic tree based on the 16S rRNA region including the crayfishes from GIR5 population (in blue) and the known haplotypes of the WCC from dataset 1 . Posterior probabilities values are shown above the branches.(DOCX)Click here for additional data file.S3 FigCOI mtDNA region including the crayfishes from GIR5 population (in blue) and the known haplotypes of the WCC from dataset 1 . Posterior probabilities values are shown above the branches.Bayesian inference phylogenetic tree based on the (DOCX)Click here for additional data file.S4 FigComplete version of the Bayesian inference phylogenetic tree with the divergence time estimates for the haplotypes of the white-clawed crayfish species based on the low rates scenario from dataset 1  based on 948 bp of the concatenated mitochondrial 16S rRNA and cytochrome oxidase subunit I regions. Node branches show the estimated mean and range of the divergence time in Mya. The nodes support with high posterior probability values (pp≥0.95) show a black circle, and the divergence times are in bold.(TIF)Click here for additional data file.S5 FigComplete version of the Bayesian inference phylogenetic tree with the divergence time estimates for the haplotypes of the white-clawed crayfish species based on the intermediate rates scenario from dataset 1  based on 948 bp of the concatenated mitochondrial 16S rRNA and cytochrome oxidase subunit I regions. Node branches show the estimated mean and range of the divergence time in Mya. The nodes support with high posterior probability values (pp≥0.95) show a black circle, and the divergence times are in bold.(TIF)Click here for additional data file.S6 FigComplete version of the Bayesian inference phylogenetic tree with the divergence time estimates for the haplotypes of the white-clawed crayfish species based on the high rates scenario from dataset 1  based on 948 bp of the concatenated mitochondrial 16S rRNA and cytochrome oxidase subunit I regions. Node branches show the estimated mean and range of the divergence time in Mya. The nodes support with high posterior probability values (pp≥0.95) show a black circle, and the divergence times are in bold.(TIF)Click here for additional data file.S1 TablePopulations and locations of the white-clawed crayfish analyzed in the present study .(DOCX)Click here for additional data file.S2 TableNucleotides of the obtained sequences of the cytochrome oxidase subunit I region from the GIR5 population in positions with double peaks (on the left) in alignment with the haplotype sequences obtained for dataset 1 . Dots indicate identity with the consensus sequence, while the variable position that showed double peaks appears in parenthesis. Asterisks indicate nucleotides previously unreported in that position.(DOCX)Click here for additional data file.S3 TableGenetic diversity indices of the populations from dataset 1  based on 948 bp of the concatenated mitochondrial 16S rRNA and cytochrome oxidase subunit I regions: sample size (n), the number of polymorphic sites (S), the number of haplotypes (H), the haplotype diversity (Hd), the nucleotide diversity (π), the Tajima’s D (D), and Fu’s Fs (Fs).(DOCX)Click here for additional data file.S4 Table16S rRNA and cytochrome oxidase subunit I regions: sample size (n), the number of polymorphic sites (S), the number of haplotypes (H), the haplotype diversity (Hd), the nucleotide diversity (π), the Tajima’s D (D), and Fu’s Fs (Fs).Genetic diversity indices of the populations from dataset 2  based on 2449 bp of the concatenated mitochondrial (DOCX)Click here for additional data file.S5 TablePopulation groups obtained for the optimum genetic structure (K = 20) of the dataset 1  based on 948 bp of the concatenated mitochondrial 16S rRNA and cytochrome oxidase subunit I regions.(DOCX)Click here for additional data file.S6 TablePopulation groups obtained for the optimum genetic structure (K = 18) of the dataset 2  based on 2449 bp of the concatenated mitochondrial 16S rRNA and cytochrome oxidase subunit I regions.(DOCX)Click here for additional data file.


Quercus petraea in south-eastern Europe is limited despite the species’ significant role in the re-colonisation of Europe during the Holocene, and the diverse climate and physical geography of the region. Therefore, it is imperative to conduct research on adaptation in sessile oak to better understand its ecological significance in the region. While large sets of SNPs have been developed for the species, there is a continued need for smaller sets of SNPs that are highly informative about the possible adaptation to this varied landscape. By using double digest restriction site associated DNA sequencing data from our previous study, we mapped RAD-seq loci to the Quercus robur reference genome and identified a set of SNPs putatively related to drought stress-response. A total of 179 individuals from eighteen natural populations at sites covering heterogeneous climatic conditions in the southeastern natural distribution range of Q. petraea were genotyped. The detected highly polymorphic variant sites revealed three genetic clusters with a generally low level of genetic differentiation and balanced diversity among them but showed a north–southeast gradient. Selection tests showed nine outlier SNPs positioned in different functional regions. Genotype-environment association analysis of these markers yielded a total of 53 significant associations, explaining 2.4–16.6% of the total genetic variation. Our work exemplifies that adaptation to drought may be under natural selection in the examined Q. petraea populations.Knowledge on the genetic composition of  Forest ecosystems are undergoing unprecedented changes in environmental conditions due to global change impacts (González de Andrés https://efi.int/knowledge/models/efiscen). Among seven groups of tree species, Quercus petraea (Matt.) Liebl. was ranked fourth in terms of economic importance, being of considerable productivity  to explore the number and distribution of loci affecting the variations in the adaptively important traits by FST outlier detection and associations of SNP allele frequencies with environmental variation; and (iv) by annotating these loci, to describe the biological process, molecular function and cellular component, assuming the same function in both the resulted, already annotated model species, and Q. petraea.In this study, we identified and investigated the genetic variation at several stress-response loci in natural sessile oak populations from the Central-Eastern European region. The objectives of the study were (i) to reveal the genetic structure, diversity and differentiation of the sampled populations; (ii) to identify stress-response loci in our RAD sequencing dataset after mapping paired-end reads to the Q. petraea, extending to Bulgaria, Hungary, Romania, Serbia, Bosnia and Herzegovina, Kosovo and Albania  of nia Fig. . Altogetnia Fig. . Samplinnia Fig. . Detailenia Fig. .A variation of RAD sequencing, that is suitable for high-confidence genome-wide SNP loci discovery, double-digest RAD-seq (ddRAD-seq), was used to genotype all individuals  Unix-based HPC server, allocating 40 cores (80 threads) and 38 GB of RAM. Key steps of the bioinformatics pipeline are shown in Fig. Short read sequences (~77 M) were demultiplexed and adaptor-trimmed by using MiSeq Control Software . The resulting sequences  were 3′ and 5′ end-trimmed using the FastQ Toolkit. Reads with a mean quality score <30 and shorter than 200 bp were filtered. Computational processing of short-read data was carried out with Stacks 2.0  were filtered out  ranging from K = 2 to 9. The Python script ‘ChooseK’, included with the fastStructure package, was used to choose the number of groups that maximize the log-marginal likelihood lower bound , observed heterozygosity (Ho), and the inbreeding coefficient (FIS) were calculated for each population and for each genetic cluster in R using the ‘adegenet’ package  (Nei FST distances using the ‘ggdendro’ package in R (de Vries and Ripley Expected heterozygosity (He Goudet  using 10e Goudet . Privatee Goudet . The divFST) Nei  by creatFST) Nei . In addiFST frequency or Bayesian based) can outperform single tests in the detection of loci under directional selection, we applied distinct approaches to see if they converged and detected the same outliers , the ‘LeftTrimFraction’ was set to 0.08, the ‘RightTrimFraction’ to 0.30, and the Hmin parameter was left at the default setting (0.1). The false discovery rate threshold for calculating q-values first was 0.05, as set by default , as an example presented in Table The loci containing the significant SNPs was extracted from the initial dataset and annotated using the NCBI’s BLASTN and BLASTX services (To test for associations of loci (SNPs) with environmental variables , five different regression approaches were applied.r2 value below 0.75 and with a VIF < 10, thus were subsequently used for the association analyses. Selected environmental variables are detailed in Table First, an environmental dataset of 84 monthly, seasonal, and annual variables was created by extracting climate data from WorldClim 1.4  implemented in the ‘gdm’ package  while maintaining a relatively low false detection rate , similarly to Kwon et al. . The GLMQ. robur reference genome with an average success rate of 92.43%  for the SNP data. At this LLBO, we identified three main genetic clusters  and few introduced individuals as a separate group  and among the genetic clusters (FST ranging from 0.022–0.083). Cluster 3 showed the highest differentiation compared to Clusters 1 and 2 (FST = 0.065 and 0.083), while differentiation between Clusters 1 and 2 was much lower (FST = 0.022)  Fig. . The UPG22) Fig. .e = 0.181–0.223; Ho = 0.166–0.210), as detailed in Table e = 0.181; Ho = 0.166; Ar = 1.570). Significant inbreeding depression was not detected (p < 0.05). Private alleles were absent, and only HU3 had a unique allele. Diversity among genetic clusters was similar; only Cluster 3, which contained only the BU4 population, showed slightly lower diversity values  located at different loci, and at six different chromosomes  were considered robust outliers  served as a covariate, and last MLM where the average relationship was estimated by kinship (Q + k). Table By using the nine robust SNPs, a total of 102 significant marker-environment associations were detected, 21 with GDM, 48 with the LFMM, 9 with SFA and 14–10 with the GLM and MLM. However, similar to outlier analysis, we considered only those marker-environment associations that were detected with at least two different methods. Among the 53 jointly detected associations, the significance levels were different and ranged from 0.05 to 0.001.The GDM method found relationships only for four SNPs . In these relationships, PETCQ, prec6_16, bio3_16 were the most frequent, and presented the highest relative importance , prec6_16 (0.167 R2) and aridity (0.189 R2), and explaining 16.6–21.9% of variance . The highest |z | -score values  were found for three SNPs, namely for 227780_278, 277051_56 and 361438_297, in association with PETCQ (6.036 and 6.289), prec6_16 (6.022) and aridity (6.414). The single-factor analysis (SFA) was similar to LFMM, where the LFMM |z | -scores values were high, the SFA adjusted p values ranging from 0.05 to 0.001), however, the same associations detected by MLM, were not significant with FDR and Bonferroni-adjusted significance thresholds. The highest R2 values were detected for 50083_64 and 238771_249 in association with mCBTemp10 (both 0.150 R2). MLM, similarly to LFMM and SFA, revealed the highest significant association between 277051_56 and PETCQ (0.045 R2).The GLM and MLM detected much less numbers of associations (14 and 10), also the significance thresholds were largely different. The GLM detected associations with significant FDR and Bonferroni-adjusted thresholds (R2). SNP 50083_64, 180975_104 and 227780_278 was explained chiefly by PETCQ , 96506_153, 96534_88, 361438_297 and 437832_228 by aridity , 238771_249 by mCBTemp10 (avg. R2adj = 8.2%), 277051_56 by bio8_18 (avg. R2adj = 11.2%). By summarizing the environmental predictors, in decreasing order, aridity (81.7%), PETCQ (79.9%), bio8_16 (51.9%) and prec6_16 (49.7%) explained the highest amount of the genetic variation, thus considered to be the most important  , and this population is located at the eastern edge of the Black Sea refugium and in the eastern part of the current European distribution range of the species. Additionally, individuals of this region are considered to be a distinct subspecies in the Euro+Med Plantbase (http://ww2.bgbm.org/EuroPlusMed/query.asp) and on The Plant List (http://www.theplantlist.org), Q. petraea subsp. iberica (Steven ex M. Bieb.) Krassiln., and Schwarz   selection. Those SNPs that were presented in NCBI databases resided in four different functional regions. Two SNPs found in a gene encoding the uncharacterized protein 115976593 (NCBI ID), one in bHLH162 transcription factor, one in hydroxymethylglutaryl-CoA synthase coding region, and one in a hypothetical protein coding region (possible double-strand damage repair). No biological function can be associated to uncharacterized proteins, however, bHLH transcription factor is related to NPF genes  showed signatures of selection according to differentiation outlier analyses. The observed proportion was lower than obtained in other studies on temperate broadleaf forest trees (Derory et al. p ≤ 0.05 to 0.001. The variations seen in the analyses are due to differences in the methods used to account for demographic history or neutral genetic structure, which results in different statistical strengths for different sampling schemes or complicated demographic situations (De Mita et al. Caution must be exercised when interpreting our results, taking into account the potential for false positive selection signatures (Excoffier et al. FST outlier and environmental association analyses, which are only correlative measures (Ahrens et al. The above list of significant marker-environment associations clearly shows, that most variables are linked to aridity. To validate functional mechanisms underlying selection signatures, it is generally recommended to use annotations, which can provide additional support beyond relying solely on While sessile oak populations are well studied in Europe, in the Central-Eastern European region, including the Balkan Peninsula it is seldom tested with genome-wide genetic markers. The identification of genetic variants within populations of this region may hold the key to facilitating the sessile oak’s adaptation to the deleterious effects of modern climate change, thus underscoring the crucial significance of further investigation in this field. Through our examination, we found molecular evidence indicating that important climate-related factors, such as drought, may have influenced the adaptive divergence of sessile oak populations in the Central-Eastern European region. Moreover, our results suggest that these populations may contain beneficial genetic variants that could aid the species in responding to the rapidly changing climate. In light of these findings, it is vital that European forest tree species conservation and management programmes incorporate the Central-Eastern European sessile oak populations, including facilitated gene flow, into their strategies to combat the significant threat that climate change poses to forest tree populations.Supplementary Material


Anacardium occidentale L.) is a crop currently grown in several tropical countries because of the economic importance of cashew nuts. Despite its enormous economic worth, limited research has been conducted on the molecular diversity of cashew genetic resources. In this study, a wide comprehensive assessment of the genetic diversity of cashew trees in East Timor was performed using microsatellites (SSRs) to evaluate intraspecific diversity and population structuring.Cashew , and outgroup populations from Indonesia (one) and Mozambique (two), were analyzed with 16 cashew-specific SSRs. A comprehensive sampling of cashew trees within East Timor was performed, covering the distribution of cashew orchards in the country. Genetic diversity indices were calculated, and population structuring was determined using three different approaches: genetic distances (UPGMA and NJ), AMOVA, and individual-based clustering methods through Bayesian (STRUCTURE) and multivariate (DAPC) analyses.The population structuring analysis revealed that the genetic diversity of cashew populations in East Timor was higher in this study than previously reported for cashew trees. A higher allelic richness was found within cashew populations in East Timor compared with the outgroup populations (Mozambique and Indonesia), reinforced by the presence of private alleles. Moreover, our study showed that cashew populations in East Timor are grouped into two dissimilar genetic groups, which may suggest multiple cashew introductions over time. These new cashew genetic resources could be explored for future crop improvement.Crop diversity underpins the productivity, resilience, and adaptive capacity of agriculture. Therefore, this study provides useful information regarding genetic diversity and population structure that can be harnessed to improve cashew production in East Timor. This data is also important to creating a country-specific genetic cashew signature to increase cashew market value. Anacardium occidentale L., Anacardiaceae) is a tropical evergreen tree that can thrive in both dry and wet tropical climates. Many tropical countries use various parts of the cashew tree for consumption as well as for medicinal and industrial purposes  and RAPDs (random amplified polymorphic DNA). For example, the genetic diversity of cashew accessions have been characterized in Côte d’Ivoire , Nigeriafeni, made from ripened cashew apples. After their introduction in India, cashew trees spread to South Asia on the Moluccas Islands, Indonesia .Cashew trees were one of the many tropical crops introduced by the Portuguese from Brazil into the African continent in the sixteenth century as part of the Columbian Exchange Event . In Asiandonesia  and therndonesia . Despitendonesia . HoweverEast Timor is a small island country located in Asia, bordered by Indonesia . Agricule.g., Côte d’Ivoire  and a nd’Ivoire  applied East Timor is divided into six different agro-ecological zones  that shaηm and 260/230 ηm using a spectrophotometer , while DNA integrity was verified by agarose gel electrophoresis at 0.8% in 1x TAE running Buffer  for 30 mins at 90 volts and then visualized in a GelDoc XR image system .Individual tender leaves collected from each cashew population were used for genomic DNA (gDNA) analysis, with gDNA extracted with the InnuPREP Plant DNA Kit  following the manufacturer’s instructions with minor modifications. Approximately 100 mg of each leaf collected in the field were ground with a mortar and a pestle in liquid nitrogen, with about 25 mg of the roughly ground leaves used for the subsequent gDNA extraction protocol, by adding 400 µL of OPT lysis solution and grinding the biological material with an Eppendorf-pestle in a 1.5 mL tube. An initial incubation was done for 1 h at 65 °C, followed by the addition of 100 µL of precipitation buffer and a 5-min incubation at room temperature; the supernatant was then recovered by centrifugation at a maximum speed of 11.000 × g for 5 mins. The supernatant was then transferred to a pre-filter receiver and centrifuged at 11.000 × g for 1 min. Subsequently, 4 µL of RNAse A solution (100 mg/mL) was added and samples were incubated for 30 mins at 37 °C. After RNAse treatment, 200 µl of SBS binding solution was added and then centrifuged at 11.000 × g for 2 mins. Two washing steps with 650 µL of MS washing solution were then performed on the recovered supernatant, which was then centrifuged at 11.000 × g for 1 min. The gDNA was eluted in 40 µL of AE buffer, left to incubate at room temperature for 15 mins, and recovered by centrifugation at 11,000 × g for 1 min. DNA purity and concentration were measured at 260/280 A set of 16 available cashew-specific microsatellite (SSRs) markers  were sel2, and dNTP mix), 50–100 ηg gDNA, 2.5 ρmol of each forward and reverse primer, 0.15 ρmol of the tailed fluorescent-labeled primers (D1–D4), and a variable volume of ddH2O until the total volume reached 25 µL. Reactions were done in 96 well-plates; on each plate, one sample was repeated per run as a positive control for allele scoring. Negative PCR controls were also included. Hot start PCR methodology was used, heating the samples at 95 °C for 15 min. This was followed by a touchdown cycling protocol adapted from Before multiplexing, each SSR marker was validated in single-plex polymerase chain reactions (PCR) using a three-primer PCR approach  to asseshttps://www1.montpellier.inra.fr/CBGP/software/FreeNA/). These values were computed as described by F), observed (HO), and expected (He) heterozygosity. Deviations from the Hardy-Weinberg equilibrium (HWE) were assessed for each locus-population combination and linkage disequilibrium (LD) to determine the extent of distortion from the independent segregation of loci using GenePop v.4.5 ) by applying a sequential Bonferroni correction  using genetic distances to estimate relationships between populations; (ii) hierarchical genetic analysis by AMOVA; and (iii) individual-based clustering with a Bayesian (STRUCTURE) and a multivariate  analysis.INA), and Nei’s D distance  MZ vs ET vs IND; (2) ET vs IND populations), differences among populations within those groups (Vb), and differences among individuals within the populations (Vc). Variance components  were used to calculate the fixation indices  according to An analysis of molecular variance AMOVA,  was doneGenetically distinct clusters were identified using two different methodologies, as previously described in K-values set from 1 to 14 with 10 runs computed for each K. For the second approach, including just the cashew populations in East Timor and Indonesia, the same settings were followed by configuring K-values from 1 to 12 with 10 runs in each K. Structure Harvester v0.6.94  scores, maintaining default parameters and retaining all principal components (PCs). Cross validation was done using the xvalDapc function to determine the optimal number of PCs to retain in the Discriminant Analysis (DA). The generated DAPC script is available at Figshare ; after a sequential Bonferroni correction, only two loci (mAoR3 and mAoR35) displayed significant deviations, matching 33 of the 168 locus-population combinations (F) estimates were observed in two loci, mAoR17 (−0.03) and mAoR7 (−0.04)  , which io) varied from 0.25 (mAoR35) to 0.73 (mAoR17) with a mean of 0.40 (e) varied between 0.45 (mAoR16) and 0.84 (mAoR17).Overall, a total of 157 alleles were detected in the 207 individual cashew trees analyzed . All SSR of 0.40 , and thee) was 0.67 in East Timor, 0.56 in Indonesia, and 0.71 in Mozambique, while Ho was 0.51, 0.47, and 0.54, respectively. All populations presented positive F values, ranging from 0.12−0.25. The populations with the highest number of alleles were observed in East Timor, specifically in the ETK population which had an average of 5.17 alleles, followed by ETR3 with 5.08 alleles, while ETBAT and ETV had an average of 2.42 and 2.25 alleles, respectively. Comparing the SSR allele numbers of the populations screened identified which population harbored more allelic diversity. When analyzing this parameter, ETK and ETTR3 were the populations identified with the most allelic diversity  was observed in the ETK population, and the lowest was observed in the ETV population. Thre highest heterozygosity (Ho) was observed in the ETTR1 population, and the lowest was observed in the ETFA population. The fixation index (F) was positive in all populations except for ETSAN and ETV; the positive values in all other populations may indicate genetic stability and a higher rate of inbreeding. The absence or existence of private alleles is important for identifying a specific genetic signature, as private alleles are alleles that are unique to a population. A high number of private alleles (6) were observed in East Timor. Two private alleles were observed in Mozambique, while no private alleles were detected in the Indonesian cashew populations.In a population genetic diversity analysis , East Tisity Na, . The higD and DCINA (FreeNA) genetic distances across accessions screened for East Timor, Indonesia, and Mozambique  showed that molecular variation was mainly found within individual cashew trees (76%), whereas variation among populations and among individual trees explained 13% of the total genetic differentiation, in both cases . AMOVA rTwo different approaches were used to identify individual clusters in East Timor, using Indonesian cashew populations as the outgroup: (1) covering all populations from East Timor, Indonesia, and Mozambique, and (2) excluding Mozambique.K = 1–15). This analysis assigned K = 5 as the optimal number of groups based on the ΔK method  were retained and four discriminant functions, conserving 87.5% of the variance  and two discriminant functions (explaining 87.5% of cumulative variance) for inferring the five genetic clusters  contributed the most for the five genetic clusters. Both DAPC results (K = 9 and K = 10) identified the same variables responsible for cluster assemblage (172 (mAoR6), 328 (mAoR17), 174 (mAoR35), 170 (mAoR47)), which highlights the importance of these alleles for cluster discrimination . This analysis identified K = 2 as the optimal number of groups  as outgroups, were screened using 16 cashew-specific microsatellites.A comprehensive sampling of cashew orchards in East Timor was conducted by assessing and characterizing the genetic diversity and population structuring of 11 cashew populations from major cashew-producing districts in the country. A total of 207 individual cashew trees belonging to 14 cashew populations from three tropical countries , using Indonesia and Mozambique populations  where a lower genetic diversity (Shannon index = 0.04) was observed in 60 cashew morphotypes using eight SSR markers , a much F) were observed, which agrees with former studies  suggesting a high gene flow between populations, which is in accordance with previous studies . Cashew  studies .vs excluding the cashew populations in Mozambique highlights the complex genetic diversity of cashew trees in the context of a continental (Mozambique) country where orchards are older and have incorporated improved cashew varieties. These results are in accordance with previous results in India  exhibits values from −1 to +1. Values close to zero are expected under random mating, while substantial positive values indicate inbreeding or undetected null alleles , possibly because growers from both regions exchange seeds with the other regions. In contrast, the Cova Lima district (south) showed the highest inbreeding coefficient (F = 0.26). Both the Bobonaro and Viqueque districts displayed a significant share of planting material exchange with Bobonaro getting seeds from Indonesia and Viqueque getting seeds from Australia. In the studied populations, positive F values were observed, which may indicate some level of inbreeding. The difference between expected heterozygosity and observed heterozygosity might be due to evolutionary factors (such as inbreeding) or internal genetic factors (such as gene incompatibility). The introduction of new cashew seeds for new orchards might be another explanation; when establishing new cashew orchards, some producers used seeds from a single tree with good traits (high yield and large nuts). Moreover, according to The fixation index  alleles . Negativulations , revealiulations . Among tFST = 0.129, vs 18 SSRs in e.g., Benin, Considering the 11 populations studied from East Timor, population differentiation , p < 0.05, light blue; p < 0.000298, dark blue.)Statistical significance was assessed by running 10,000 iterations Monte Carlo Markov Chain (MCMC) test. Click here for additional data file.10.7717/peerj.14894/supp-2Table S2p-values were corrected by multiple comparisons applying a sequential Bonferroni correction , p < 0.05, light blue; p < 0.000298, dark blue if present).Statistical significance was assessed by running 10,000 iterations Monte Carlo Markov Chain (MCMC) test. Click here for additional data file.10.7717/peerj.14894/supp-3Table S3Click here for additional data file.10.7717/peerj.14894/supp-4Table S4Click here for additional data file.10.7717/peerj.14894/supp-5Figure S1Manatuto, Bobonaro, Baucau, Covalima, Manufahi, Viqueque, Indonesia and Mozambique.Click here for additional data file.10.7717/peerj.14894/supp-6Figure S2Legend: Manatuto, Bobonaro, Baucau, Covalima, Manufahi, Viqueque, and Indonesia)Click here for additional data file.10.7717/peerj.14894/supp-7Figure S3K). Variation of ΔK values according to the method outlined by STRUCTURE ad hoc statistics retrieved by Structure Harvester using 1 to 15 possible clusters  represents the best summary of the data for the populations of East Timor, Indonesia, and Mozambique.A Click here for additional data file.10.7717/peerj.14894/supp-9Figure S5Scatterplot shows the two principal components of the DAPC, and clusters are numbered and displayed by different colors, while dots represent individuals. The 2 Discriminant Functions hereby represented explain 93% of cumulative variance of the dataset.Click here for additional data file.10.7717/peerj.14894/supp-10Figure S6A) Allele loading plots from DF1 and (B) from DF2, after assigning 0.045 as the threshold.(Click here for additional data file.10.7717/peerj.14894/supp-11Figure S7K values according to the methods outlined by Variation of ΔClick here for additional data file.10.7717/peerj.14894/supp-12Figure S8Click here for additional data file.10.7717/peerj.14894/supp-13Figure S9Click here for additional data file.


Hordeum vulgare L.) is the most important cereal crop in the Qinghai-Tibet Plateau, and the yield has been seriously threatened by Blumeria graminis f. sp. hordei (Bgh) in recent years. To understand the virulence and genetic traits of different Bgh populations, 229 isolates of Bgh were collected from Tibet, Sichuan, Gansu and Yunnan provinces of China during 2020 and 2021, and their pathogenicity to 21 barley lines of different genotypes was assessed. A total of 132 virulent types were identified. The Bgh isolates from Yunnan showed the highest diversity in terms of virulence complexity (Rci) and genetic diversity (KWm), followed by those from Sichuan, Gansu, and Tibet, in that order. Single nucleotide polymorphism (SNP) in genes coding for alternative oxidase (AOX), protein kinase A (PKA), and protein phosphatase type 2A (PPA) were detected at seven polymorphic sites. Nine haplotypes (H1–H9) with an average haplotype diversity (Hd) and nucleotide diversity π of 0.564 and 0.00034, respectively, were observed. Of these, haplotypes H1 and H4 accounted for 88.8% of the isolates, and H4 was predominant in Tibet. Genetic diversity analysis using the STRUCTURE (K = 2) and AMOVE indicated that the inter-group variation accounted for 54.68%, and inter- and intra-population genotypic heterogeneity accounted for 23.90% and 21.42%, respectively. The results revealed the recent expansion of the Bgh population in Tibet, accompanied by an increase in virulence and a loss of genetic diversity.Barley ( Hordeum vulgare L.) is the fourth largest cereal crop in the world [H. vulgare L. var. nudum), known as Qingke, is more suitable to the harsh environment in the cool, high altitude regions of the Qinghai-Tibet Plateau, and is consequently cultivated as the staple food of people living there [Barley , which frequently occurs in Europe, North Africa and China [Bgh is extraordinarily adaptable, and some commonly recommended strategies involving genetic resistance may be ineffective [Bgh populations in Tibet and the surrounding areas, 12 disease nurseries were set up in 2020 and 2021. Together with the observation of the resistance expression of barley varieties and lines bearing different resistance genes (data published elsewhere), 321 Bgh isolates derived from single colonies from disease samples were collected and characterized for their virulence and SNP polymorphism of genes coding for alternative oxidase (AOX), protein kinase A (PKA), and protein phosphatase type 2A (PPA) [Barley powdery mildew is an airborne fungal disease caused by nd China ,10,11. Ind China ,13,14. Iffective . As one ffective ,17. Amonffective . However2A (PPA) .Bgh (Bgh isolates.Seeds of the susceptible control Hua 30 and 30 near-isogenic lines (NILs) harboring known resistance genes to Bgh  were proBgh isolates were obtained and kept on the seedlings of the barley variety QB01 in test tubes of 5 cm in diameter containing sterilized soil, following the methods of Xu et al. [Twelve disease nurseries including five in Tibet, three in Sichuan, two in Qinghai, and one in both Gansu and Yunnan Province , leaf segments of 5 cm in length were cut off the inoculated leaves, placed face-up onto 1% agar plates amended with 60 mg/L benzimidazole, and grown at 16 ± 2 °C, with a 16/8 h (light/dark) illumination regime. After 5–7 d of incubation, the conidia were collected onto parchment paper in the laminar flow and placed into 2.0 mL centrifuge tubes. The fresh conidia were used for the virulence assay, or first frozen in liquid nitrogen and then conserved at −80 °C for further DNA extraction [To multiply the traction .Bgh isolate by gently shaking the sporulating leaf segments. The tray was then encased in a transparent plastic bag supported by an iron framework, and incubated for 7–10 d at 18 ± 2 °C with continued illumination until susceptible QB-01 and Hua 30 showed symptoms. The infection types (ITs) of each barley NIL from different Bgh isolates were scored on a scale of 0 to 4, according to Jensen et al. [Clumps of five germinated seeds of QB-01 and Hua 30, as well as those of 30 barley NILs, were sown in 7 rows in a 26 cm × 18 cm × 2 cm enamel tray containing sterilized soil without replicates. At the 2-leaf stage, each tray was transferred into steel cylinders of 0.4 m in diameter and 1 m in height, and inoculated with the conidia of one n et al. , and resn et al. ,24.Bgh isolates was extracted using a Plant Genomic DNA kit DP305 , according to the manufacturer’s instructions. Three primer sets specific for alternative oxidase , protein kinase A , and protein phosphatase type 2A  were used to study the single nucleotide polymorphism (SNP) [2O 8.0 μL. The amplification program consisted of a pre-denaturation at 95 °C for 5 min, followed by 34 cycles of denaturation at 95 °C for 25 s, annealing at 56 °C for 25 s, extension at 72 °C for 45 s, and a final extension at 72 °C for 7 min. After that, 5 μL of the PCR products were detected using 1% agarose gel electrophoresis. The PCR products with clear and bright bands and of the expected size were sent to Tsingke Biotechnology  for sequencing.Genomic DNA of sm (SNP) . The 25 Bgh isolates. Principal coordinate analysis (PCoA) was performed using an online tool (https://hiplot.com.cn accessed on 4 November 2022). VAT software was used to identify the Bgh pathotype based on the parameters related to the virulence diversity, including average relative-virulence complexity (Rci), gene diversity (Hs), genotypic diversity (Sh) and genetic diversity (KWm) [D as well as Fu and Li’F* tests, and to infer population expansion. AMOVA  in the Arlequin 3.5 package [FCT/FST of the inter-geographic groups/inter-populations, and to conduct a neutrality test with 1000 random permutations.The QD-SHAN in NTSYSpc 2.10s package was used for the clustering analysis of the 21 differential lines of pallas, based on the virulence assessment data of 229 ty (KWm) . DNAMAN ty (KWm) . Finallyty (KWm)  was used package  was usedBgh isolates from different locations were obtained as seen in Bgh population to P01 (Mla1 + MlaAl2), P03 (Mla6 + Mla14), P04A (Mla7 + Mlk), P04B (Mla7 + MlaNo3), P06 (Mla7 + M1Lg2), P07 (Mla9 + Mlk), and P08B (Mla9) was 0. Significant differences in virulence to the other NILs were found among different Bgh populations. Virulent isolates to P08A (Mla9 + Mlk) and P10 (Mla12 + MlaEm2) emerged only at 1 or 2 locations, while virulent isolates to P09 (Mla10 + MlaDu2), P12 (Mla22), P15 (MlRu2), P18 (Mlnn) P20 (Mlat + Mla8), P23 (MlLa) and P30 were present in all of the populations. The virulence frequencies to P02 (Mla3), P05, P13 (Mla23), P16 (Mlk) and mlo5 were less than 20%. The virulence frequency to the other eight resistance genes ranged from 25% to 50%, indicating that the NILs possessing these genes had moderate susceptibility (MS) or moderate resistance (MR). The genes in P09 (Mla10 + MlaDu2), P12 (Mla22), P15 (MlRu2), P18 (mlnn), P30 and pallas were no longer efficient. Based on the resistance frequencies of different NIL lines and the clarity of their resistance genes, 21 NIls were selected as the differential lines for virulence typing . The Bgh populations at Diqing in Yunnan and Xichang in Sichuan had genetic diversity value of KWm at 0.385, while the populations at Shannan in Tibet had the lowest KWm (0.143). The relationship between the populations was analyzed based on the genetic distance Nei’s (N) and mean character difference (MCD) (N (0.192), and the MCD value (0.292) between these two population was also the highest. The N and MCD values between the populations at Lhasa, Shannan, and Qamdo in Tibet were the lowest, and were 0.017 and 0.082, respectively.The virulence diversity of the ce (MCD) . The genAfter the sequences of the genes of AOX, PKA and PPA in the genome of 321 isolates were organized through alignment analysis and assembled, the length of the sequence containing polymorphic sites was 2196 bp for all the isolates. Excluding gaps and three deletion sites, a total of seven polymorphic sites, two singleton variable sites (at positions 394 and 1883), and five parsimony informative sites  were found in the sequences. In total, nine haplotypes (H1–H9) were detected . The hapBgh populations was analyzed employing STRUCTURE software, and the K values were set from 1 to 9, to predict the optimal population structure. When K = 2, the ΔΚ value was the largest, suggesting that the optimal number of sub-populations was 2 for the grouping  was 0.00034. The Hd value ranged from 0 to 0.6485, and the π value ranged from 0 to 0.00049, illustrating the large variation between the populations. The population at Qamdo in Tibet had the highest Hd (0.64848), followed by the population at Hezuo in Gansu and Xichang in Sichuan, which were 0.34762 and 0.31169, respectively. The populations at Lhasa, Linzhi, and Shannan in Tibet and Diqing in Yunnan showed the lowest haplotype and nucleotide diversity, and only one haplotype was detected in each of these populations There were two haplotypes in the population at Rikaze  of the investigated t Rikaze .FCT, was 0.54681, and the average inter-population genetic differentiation coefficient, FST, was 0.69714, indicating that larger genetic differentiation of Bgh populations mainly existed between groups. There was a higher level of genetic differentiation and a lower level of gene exchange between the populations. The neutrality test showed that the Fu’s Fs value was −2.992, and the Tajima’s D value was −0.65769. These were non-significant (p > 0.10), indicating that the Bgh populations followed the neutral model of evolution, and there were many loci with low-frequency alleles. The Fu and Li’ D (−0.89307) and Fu and Li’F (−0.97079) were also non-significant (p > 0.10), indicating that the Bgh populations were affected by selection and recombination.The AMOVE analysis showed  that intBgh into different populations of distinct virulence and genetic composition has been reported globally [Bgh to resistance genes and or gene combinations, which shows an overall trend toward higher pathotype diversity and virulence complexity [Bgh populations in central Europe also appear to exhibit a similar trend [Bgh population and disease incidence at different disease nurseries (unpublished data), resistance genotypes Mla6 + Mla14, Mla7 + Mlk, Mla7 + Mla (No3), Mla7 + M1 (Lg2), Mla9, Mla9 + Mlk and Mla12 + MlaEm2 are highly resistant to Bgh in Tibet and the surrounding areas. Inside Tibet, Mlra, Mla23, Mlk1, Mlg + Ml(CP) and the broad-spectrum resistance gene, mlo5, are also still resistant to powdery mildew. In order to obtain higher and more durable resistance, it would be valuable to pyramid such genes in combination with Mlo, together with the continuous monitoring of the changes in the virulence frequencies of different Bgh populations.The differentiation of globally ,13,14,15mplexity ,21,31. Tar trend ,33,34. TBgh population had experienced a recent expansion, is congruent with the recent disease epidemic in the Tibet-Qinghai Plateau.While barley is newly cultivated in Xichang and rare in Chengdu and Xining, the hull-less barley has long been introduced, first into the southern and eastern areas of the Qinghai-Tibet plateau, and has experienced a process of adaptation to the environment of varying altitudes . AlthougBlumeria graminis, and [Bgh genotypes between Tibet, Yunnnan, Sichuan in the southwest and Zhejiang in the southeast of China. The Bgh genotypes in this research revealed two centers of genetic diversity, i.e., Qamdo and Hezuo. The prevalence of H1 haplotypes at Qamdo and the locations surrounding Tibet suggested the possibility of the pathogen isolates being introduced into Tibet from other areas. When populations inside Tibet were looked at closely, Bgh seemed to have originated in the areas of Qamdo and expanded to the western areas of higher altitudes and lower temperature and humidity at Linzhi, Lhasa, Shannan and Rikaze. The introduction of barley into the Tibet-Qinghai plateau has resulted in the loss of most of the genetic diversity of the crop [Bgh population compared with that in the other areas of China. In contrast to the less diversified genetic structure than that of Bgh at Qamdo, the virulence become stronger in the pathogen population at the western sites in Tibet. This could be explained by the more intensive cultivation of barley with newly introduced resistance genes in commercial cultivars in the latter locations.Both geographic isolation and long-distance migration had impacts on the population diversity of nis, and  has revethe crop . It is rthe crop  revealed


Rangifer tarandus platyrhynchus) originate from recent reintroductions or recolonizations following regional extirpations due to past overharvesting. We investigated and compared the genomic consequences of these two paths to reestablishment using whole‐genome shotgun sequencing of 100 Svalbard reindeer across their range. We found little admixture between reintroduced and natural populations. Two reintroduced populations, each founded by 12 individuals around four decades (i.e. 8 reindeer generations) ago, formed two distinct genetic clusters. Compared to the source population, these populations showed only small decreases in genome‐wide heterozygosity and increases in inbreeding and lengths of runs of homozygosity. In contrast, the two naturally recolonized populations without admixture possessed much lower heterozygosity, higher inbreeding and longer runs of homozygosity, possibly caused by serial population founder effects and/or fewer or more genetically related founders than in the reintroduction events. Naturally recolonized populations can thus be more vulnerable to the accumulation of genetic load than reintroduced populations. This suggests that in some organisms even small‐scale reintroduction programs based on genetically diverse source populations can be more effective than natural recolonization in establishing genetically diverse populations. These findings warrant particular attention in the conservation and management of populations and species threatened by habitat fragmentation and loss.Anthropogenic reintroduction can supplement natural recolonization in reestablishing a species' distribution and abundance. However, both reintroductions and recolonizations can give rise to founder effects that reduce genetic diversity and increase inbreeding, potentially causing the accumulation of genetic load and reduced fitness. Most current populations of the endemic high‐arctic Svalbard reindeer ( This resulted in a mean nuclear genome sequencing depth of 3.3× for the 90 samples sequenced to a lower target coverage and 23.4× for 10 deep‐sequenced samples, after all filtering , and the naturally recolonized southern Spitsbergen (STH) populations , respectively, originate from distinct ancestral populations , or a distinct ancestral population with some admixture with the ancestral NE population (models K = 8–10).Admixture and principal component analysis (PCA) identified clear genetic structure in the Svalbard reindeer metapopulation Figures  and 2. Tt Figure . On the  Figures  and 2. Sx Figure  indicate2 Figure . Insteads Figure , supports Figure  and segrOn a finer scale, both PCA Figures  and S6 a2.3FST estimates showed very strong genetic structure, and largely supported admixture and PCA results  to all other populations except Widefjorden.Pairwise s Figure . Populat2.3.1We detected 38 variant sites among the 96 full mtDNA genomes, comprising 16 unique haplotypes Figure . Haplotyr = 0.86, p = 0.013). Each of the two reintroduction groups (populations combined) had similar haplotype richness to ADV, and higher than all other natural populations except WDF  than the ADV source population . In contrast to the remnant natural and admixed recolonized populations with intermediate heterozygosities , the two non‐admixed naturally recolonized populations MTR  and STH  had very low heterozygosity. These recolonized populations had markedly lower heterozygosity than the reintroduced populations combined . Coalescent effective population size (Ne) showed similar patterns to heterozygosity . ADV and WDF showed the highest Ne , while MTR had the lowest (4220). Reintroduction 1 had a lower Ne (5042) than Reintroduction 2 (5544) and STH (5170), while EST and NE had similar intermediate Ne estimates .Heterozygosity was estimated for each sample individually. The median genome‐wide heterozygosity for all individuals in this study with coverage >2.5× was 3.02 × 10ty Table , with me2.3.3FROH 0.236 ± 0.063 SD, Reintroduction 2 FROH 0.237 ± 0.033) relative to their source population in Adventdalen (FROH 0.186 ± 0.042). The higher inbreeding in reintroduced populations was due to greater coverage of moderate length RoH (between 1 and 8 Mbp) that resulted in increased median RoH lengths  and longest median RoH lengths  RoH were rare. The admixed naturally recolonized population in WDF had the highest variation in total FROH consistent with high variation in the proportion of individuals' shared ancestry. The two remnant natural populations EST and NE both had high FROH in short RoH classes compared to the ADV population, with EST having low FROH in intermediate and long size classes comparable to ADV and the two samples from NE showing relatively high FROH in all size classes.Non‐admixed naturally recolonized populations MTR and STH had the highest inbreeding coefficients  than Reintroduction 2 (4%) compared to the source population. Similar genomic signatures of reintroductions have previously been identified, including in European bison Bison bonasus  , and high coverage of moderate length RoH indicates founder effects or small Ne during the last 25 generations (i.e. during recolonization). ADV, the two reintroduced populations and the naturally recolonized STH all had a similar average proportion of genomes within RoH <1 Mbp, indicating similar demographic histories >50 generations ago, consistent with these populations sharing a common origin as indicated by our admixture results. Therefore, differences in patterns of genome‐wide diversity in STH and the reintroduced populations likely reflect differences between anthropogenic reintroductions and natural recolonization, rather than differences in genetic diversity between their ancestral populations. The extremely low levels of heterozygosity and high inbreeding levels in MTR are thus likely a result of a source population with a historically small population size that harboured little genetic diversity prior to recolonization, in addition to more recent founder effects associated with the recolonization process. Indeed, this is consistent with the reported population size of reindeer in the isolated North‐West Spitsbergen area being only 2–300 individuals, 30 years after the historical overharvesting was ended  Figure . STH alsed Lønø, .Ne and eroding genetic diversity . We found stronger genetic structure among the two sampled populations in the second reintroduction group (DAU and NIF). Our mtDNA analyses also suggest that introgression possibly occurred from a westward natural recolonization from an unsampled population carrying a haplotype not sampled in other populations, possibly facilitated by more frequent sea ice in the inner parts of the fjord , making it an important consideration in conservation biology  founders and the avoidance of sequential founder effects that may be an inherent part of the natural recolonization process in fragmented landscapes. These findings also underline that translocations deserve increasing consideration as a tool to augment gene flow required for the adaptation and persistence of populations in fragmented habitats in the context of climate change . Only 16% of the archipelago's land area comprises vegetated peninsulas and valleys , the north‐west coast south to Mitrahalvøya and Wijdefjorden in north‐central Spitsbergen , which are new in this study, all samples were previously used to generate microsatellite data in a study by Peeters et al.  collected in 2014–2018 from 100 individual reindeer originating from 12 (sub)populations on the Svalbard archipelago Figure , S4. Bass et al. .4.4n = 92) is described in Peeters et al.  DNeasy Blood & Tissue extraction kit according to the manufacturer's instructions except for the addition RNase A (details in SI 1). DNA extraction for all other samples  than the Mongolian reindeer reference  or ‐doGlf3 , ‐doMajorMinor 1 and ‐doMaf 1. Variants were called with a p‐value threshold of 1e−6  only at sites for which there was sequence data in at least 50 individuals (‐minInd 50). Reads with mapping quality <30 and base quality <20, and those with multiple mapping hits, were filtered out using ‐minMapQ 30, ‐minQ 20 and ‐uniqueOnly 1, and low‐quality reads were removed with ‐remove_bads 1. Scaffolds mapped to bovine sex chromosomes by Taylor et al. .To account for the uncertainty in calling genotypes from low‐depth sequencing data, we utilized ANGSD v0.93 , only used reads with a minimum‐mapping quality of 25  and specified a confidence threshold of 30 for variant calling . We then converted the haplotype calls of variable sites to FASTA sequences for each individual. To investigate mitochondrial genetic structure and haplotype diversity, we used pegas v1.1  and removed two out of three closely related individuals in the reintroduced Daudmannsøyra population identified using NgsRelate  with which we performed variant LD pruning in PLINK v 1.9  ranging from 2 to 10, with 10 replicates of each. Only sites with a minimum minor allele frequency greater than 0.02 (using ‐minMaf 0.02) and that had data in at least half (46) of the 92 individuals in the analysis (using ‐minInd 46) were included in the analysis. We ran admixture analyses on the full dataset including all populations , and also a separate analysis on a subset including only the reintroduction source, reintroduced and Southern Spitsbergen populations . For each value of K, the replicate with the highest likelihood was selected. We calculated ΔK  using the software package PCAngsd  population site frequency spectra (SFS) including all samples. First, we generated unfolded per‐site allele frequencies (SAF) for each population using the ‐dosaf 1 argument in ANGSD with the same parameters and site filtering as when generating genotype likelihoods and specified the reference as the ancestral genome. Then, with the realSFS module in ANGSD, we used the unfolded SAF to generate folded 2D SFS priors for each pair of populations using ‐fold 1 since no ancestral states were available to polarize the ancestral/derived alleles. We then input the unfolded SAFs and the folded 2D SFS prior to realSFS to estimate per‐site and global FST, specifying the Hudson estimation method which is more suitable for smaller sample sizes  using the same downsampled samples used for the heterozygosity analysis with the same filtering and parameters, but only considering sites with data from a minimum of 2/3 of the population sample size. With the realSFS module in ANGSD, we used the unfolded SAF to generate folded single population SFS, then input the unfolded SAF and folded SFS prior to the realSFS saf2theta function to calculate per‐site thetas. We used these per‐site thetas with the thetaStat module do_stat function to calculate global Watterson's thetas (ƟW) for each population. Using the ƟW estimates, we estimated the coalescent effective population size based on the equation ƟW = 4Neμ, assuming a per‐generation mutation rate μ of 3.46 × 10−8 as estimated for caribou by Dedato et al.  likelihoods for each population  of ~1 cM/Mbp (Johnston et al., We used ngsF‐HMM (Vieira et al., The study was conceived by BBH, HJ, HB, MDM and VCB. MDM, BBH, HJ, LEL and LD provided funding for the study. ÅØP, MLM, BBH and BP collected most samples. HB, VCB, BP and MDM performed laboratory and bioinformatic analyses. HB wrote the manuscript with contributions from all authors.The authors declare no conflicts of interest.Data S1.Click here for additional data file.Table S4.Click here for additional data file.


Eimeria zuernii (Eimeriidae: Coccidia) represents a significant economic threat to the bovine industry. Understanding the evolutionary and genetic biology of E. zuernii can assist in new interaction developments for the prevention and control of this protozoosis.Coccidiosis caused by E. zuernii by sequencing the complete mitogenome and analyzing the genetic diversity and population structure of 51 isolates collected from eight yak breeding parks in China.We defined the evolutionary and genetic characteristics of E. zuernii was linear and encoded typical mitochondrial contents of apicomplexan parasites, including three protein-coding genes , seven fragmented small subunit (SSU) and 12 fragmented large subunit (LSU) rRNAs. Genome-wide comparative and evolutionary analyses showed cytb and cox3 to be the most and least conserved Eimeria PCGs, respectively, and placed E. zuernii more closely related to Eimeria mephitidis than other Eimeria species. Furthermore, cox1-based genetic structure defined 24 haplotypes of E. zuernii with high haplotype diversities and low nucleotide diversities across eight geographic populations, supporting a low genetic structure and rapid evolutionary rate as well as a previous expansion event among E. zuernii populations.The 6176-bp mitogenome of E. zuernii, and such information, together with its mitogenomic data, should contribute to a better understanding of the genetic and evolutionary biological studies of apicomplexan parasites in bovines.To our knowledge, this is the first study presenting the phylogeny, genetic diversity, and population structure of the yak The online version contains supplementary material available at 10.1186/s13071-023-05925-8. Eimeria spp., is a widespread and highly pathogenic protozoosis with a significant economic impact on the cattle industry [Eimeria responsible for this disease, including E. zurnii, E. bovis, E. auburnensis, E. canadensis, E. ellips, E. alabamensis, E. bareillyi, E. brasiliensis, E. bukidnonensis, E. cylindrica, E. kwangsiensis, E. mandela, E. pellita, E. subspherica, E. wyomingensis, E. illinoisensis, and E. stiedai-like [Eimeria zuernii is by far the most pathogenic coccidian species and poses an additional mortality threat to yak calves < 1 year old [E. zuernii can cause malabsorption of nutrients, watery or bloody diarrhea, and even death in heavily infected animals [Bovine coccidiosis, caused by industry . Similardai-like , 2. Eimeyear old . Infecti animals .E. zuernii is commonly prevalent in yak farms and is becoming the leading cause of weight reduction in young individuals across the Qinghai-Tibetan Plateau of China [E. zuernii. Current diagnosis and identification of this protozoan parasite typically rely on morphological characteristics. Unfortunately, E. zuernii has similar oocyst morphotypes and overlapping biological features with other coccidian species. In such a context, obtaining an efficient approach to identify E. zuernii infections becomes urgent for clinical diagnosis, epidemiological investigation, and control, and achieving this goal is foreseeable only through the utilization of molecular approaches. Although the internal transcribed spacer 1 (ITS-1) region and small subunit ribosomal DNA (SSU) of the nuclear ribosomal DNA (rDNA)-based PCR amplifications were applied to differentiate between bovine coccidian species, including E. zuernii [Eimeria species because of its rapid evolution rate, absence of recombination, and matrilineal inheritance [Eimeria mitogenomes have the ability to illustrate their evolution and host adaptations [E. zuernii has been characterized. Additionally, a fundamental understanding of the genetic structure and diversity of E. zuernii would also assist in the development of a long-lasting control strategy. Several in-depth studies have proven their significance and effectiveness in controlling protozoan Plasmodium spp. and Toxoplasma spp. in humans as well as Eimeria spp. in chickens by defining their genetic diversity and population architecture [E. zuernii populations [E. zuernii so far. Herein, we decoded the complete mitogenome of E. zuernii isolated from Chinese yaks and further determined its population genetic diversity by sequencing the cox1 gene of 51 E. zuernii isolates that were collected from different geographical yak breeding parks in Sichuan, China. These results would add novel insights to phylogenetic, population genetic, and molecular epidemiological studies on this yak parasite.China has the largest population of the yak in the world, with 16 million yaks accounting for > 95% of the global population [of China –10. Such zuernii –13, cumueritance . Furtherptations . Therefoptations . Unfortuitecture –23. Of culations –26. HoweEimeria oocyst-positive fecal samples were obtained from eight Yak Modern Industrial Parks in Sichuan, China: 43 in Xinlong, 102 in Hongyuan, 25 in Ya’an, 89 in Ruoergai, 32 in Luhuo, 48 in Litang, 31 in Daofu, and 86 in Ganzi . About 2.5 million E. zuernii oocysts were harvested and purified by using a combination of saturated sodium nitrate flotation and discontinuous sucrose gradient centrifugation. Following vortex breakdown, the genomic DNA was extracted from oocysts using the Genomic DNA Kit . Based on the quality and quantity assessment, ~ 2.5 µg genomic DNA was fragmented to construct a 250-bp paired-end (PE) library, followed by sequencing on an Illumina HiSeq X-TEN platform . The clean reads (~ 1.8 Gb) were assembled with MITObim v1.9.1 [http://mitos2.bioinf.uni-leipzig.de/index.py) and a whole genome-guided gene alignment against Eimeria mephitidis (accession no. KT203398). Based on the E. zuernii mitogenome sequenced here, a pair of primers, cox1-F (5′-TTGGTTGGACTCTATACCCTC-3′) and cox1-R (5′-AGATAGTACAAAATGAAAATGAGC-3′), were designed to amplify the cox1 gene (776 bp) from the remaining 50 E. zuernii isolates. PCR reactions (50 μl) containing 2 μl of template genomic DNA, 2 μl of each primer (10 pmol each), 25 μl of 2 × Taq MasterMix , and 19 μl of ddH2O were performed in a S1000 Thermal Cycler  using the following conditions: initial denaturation at 94 °C for 5 min; 35 cycles of 94 °C for 1 min, 53 °C for 30 s, 72 °C for 30 s; followed by a final extension at 72 °C for 8 min. Target bands were isolated by 1.0% agarose-TAE gel electrophoresis and purified using spin columns . The purified amplicons were cloned into the vector pMD19-T , and each clone was sequenced three times on an automatic DNA sequencer by Shenggong Biological Technology Company . The complete mitogenome sequence of E. zuernii and sequences of cox1 (776 bp) in 50 E. zuernii isolates were deposited in GenBank under accession numbers OQ476205 and OR039219–OR039268.After species identification and oocyst quantitation using a McMaster chamber among these m v1.9.1 . The genE. zuernii mitogenome were measured with MEGA X (www.megasoftware.net). The base skewnesses of different mitogenomic regions of E. zuernii were determined using the formulas AT skew = (A − T)/(A + T) and GC skew = (G − C)/(G + C) [Eimeria parasites  . The mulE. zuernii and relationships between different host-originated eimerian parasites in the genus Eimeria were inferred from the complete mitogenomes of E. zuernii and other congeneric species  as the outgroup. After nucleotide alignments using MAFFT v7.450 [http://molevol.cmima.csic.es/castresana/Gblocks.html), a 6552-bp multi-sequence dataset was built to reconstruct the phylogenetic tree with three algorithms, including maximum parsimony (MP), maximum likelihood (ML), and Bayesian inference (BI). For the MP analysis, the tree was constructed by PAUP v4.0b10 [http://iqtree.cibiv.univie.ac.at) using an ML + rapid bootstrap algorithm with 1000 replicates. The BI analysis was achieved by MrBayes v3.2.7 [https://www.linuxlinks.com/treeviewx/). In parallel, 50 E. zuernii isolates sampled from eight different geographical yak breeding parks were subjected to an assessment of population diversity using the cox1-based mt dataset. Diversity indices for these E. zuernii isolates, including the number of haplotypes, haplotype diversity, and nucleotide diversity, were calculated in DnaSP v6.12 (http://www.ub.edu/dnasp/). A phylogeny of haplotypes was estimated by MP tree using MEGA X, with the significance of each node estimated using 10,000 bootstrap replicates of the dataset. The neutrality indices, including Fu’s Fs, Tajima’s D, and the pairwise fixation index (Fst), were used to estimate the size variation among populations using Arlequin v3.5.2.2 (http://cmpg.unibe.ch/software/arlequin35/). The median-joining networks among sequences of populations from eight geographic ranges were drawn using Population Analysis with Reticulate Trees  to reflect whether the genetic differentiation between populations was associated with geographical isolations.The phylogenetic position of T v7.450  and filt v4.0b10  using eq v4.0b10  under ths v3.2.7  using ths v3.2.7  and fourE. zuernii linear mitogenome was 6176 bp in size and encoded three PCGs, cytb, cox1, and cox3, as well as seven interspersed small subunit (SSU) and twelve interspersed large subunit (LSU) rDNA fragments  with T as the most favored base and G the least favored. Across the mitogenome, there were three overlapping regions located between cytb and cox1 genes (4 bp), between LSUF and LSUG rRNA genes (7 bp), and between LSUA rRNA and cox3 genes (6 bp), respectively. Moreover, 18 intergenic spacers were also observed, ranging in size from 9 to 221 bp, in the E. zuernii mitogenome , followed by Phe (n = 104) and Ser (n = 103), similar to other Eimeria species. Furthermore, among the start codon choices, except for the cox3 gene, which was deduced to use a non-standard start codon TTG, the cox1 and cytb genes used ATA and ATG as the start codons, respectively. TAA was used as the stop codon to terminate the cytb, cox1, and cox3 genes. For SSU rDNAs, seven gene fragments included SSUA, SSUB, SSUD, SSUE, SSUF, SSU8, and SSU9 and ranged in size from 37 (SSUF) to 116 bp (SSUB). Within LSU rRNAs, 12 gene fragments included LSUA, LUSB, LUSC, LSUD, LSUE, LSUF, LUSG, LSU1, LSU2, LSU3, LSU10, and LSU13 and ranged in size from 16 (LUSC) to 188 bp (LSUE). It appeared that these fragmented rRNAs were more conserved than PCGs, possibly related to their functional constraints in the former [Within three PCGs, e former .Fig. 3CoEimeria spp., the interspecific variations between and among E. zuernii and congeneric species were determined using the nucleotide and amino acid sequences of single and concatenated mt PCGs. The interspecific variations for each PCG ranged from 11.4% to 29.4% at the nucleotide level and 6.4% to 23.5% at the amino acid level. Furthermore, on the basis of the concatenated PCGs, the interspecific variations ranged from 14.0% to 23.2% for nucleotide sequences and 9.0% to 16.3% for amino acid sequences  in contrast with the maximum values present between E. zuernii and Eimeria maxima (0.210 and 0.173), supporting that E. zuernii was closely related to E. mephitidis but diverged from E. maxima. Furthermore, among genetic distance structures, the cox3-based K2P values were all obviously larger than those of the cytb, cox1, and concatenated PCGs, in agreement with the aforementioned result in which cox3 was determined to be the most divergent gene among Eimeria PCGs. In parallel with genetic distance analysis, the selective pressure placed on mt PCGs of Eimeria during evolution was determined by qualification of the Ka, Ks, and Ka/Ks ratios , with high statistical support . Furthermore, this clade was more closely related to Eimeria species of birds (Clade II) than to Eimeria species of rabbits (Clade III), in accordance with recent mtDNA-based phylogenetic conclusions [Eimeria species of mice and horses remained to be determined because of the poor bootstrap supports observed here  of  studies –49. Notaclusions , 41, 50.ria spp. . This diria spp. . TherefoE. zuernii population were calculated and are shown in Table π value than of the Ruoergai population (0.00086 vs. 0.00143). For the Luhuo population, the respective Hd value was 0.750 and π was 0.00138, and for the Hongyuan population, the Hd value was 0.644 and π was 0.00097. Combined, these results showed that these eight E. zuernii populations had high haplotype diversities and low nucleotide diversities. Similar phenomena were seen in other protozoan parasites with large standing population sizes and extremely high fecundities, including Trichomonas vaginalis, Giardia duodenalis, and Theileria annulate [E. zuernii and also signify the occurrence of expansion of a low effective population size of E. zuernii after a period because of the rapid population growth enhancing the retention of new regions.The number of haplotypes, haplotype diversity value Hd, and nucleotide diversity π of each annulate –55, whicFs were observed in Hongyuan (Fs =  − 0.046), Xinlong (Fs =  − 0.071), and Litang (Fs =  − 1.350) populations, in contrast with the positive values of Fu’s Fs found in Daofu (Fs = 0.172), Ya’an (Fs = 0.172), Luhuo (Fs = 0.330), Ganzi (Fs = 0.469), and Ruoergai (Fs = 0.551) populations  population, in contrast with the positive values of Tajima’s D found in Luhuo (D = 1.449), Ganzi (D = 1.573), and Ruoergai (D = 1.754) populations (Table P < 0.05), followed by Fst values between Hongyuan and Ya’an populations , between Hongyuan and Litang populations , between Luhuo and Daofu populations , between Ruoergai and Daofu populations , between Ya’an and Luhuo populations , and between Ya’an and Ruoergai populations . Such high Fst values indicated a possible geographical isolation of E. zuernii. Indeed, when taking the yak’s features, including the free-ranging, high-altitude grazing, and self-reproduction model, as well as the captive history of individuals sampled here into account, it is possible that the lack of translocations and/or introductions of these host populations between parks contributes to this population isolation of E. zuernii. Interestingly, such high Fst values were also observed in other protozoan parasites, such as G. duodenalis and Cryptosporidium spp., which were sampled from self-breeding dairy farms [In addition, the negative values of Fu’s Fs = 0.17, Ya’an  and three reference isolates from GenBank, the mt cox1 sequences containing 31 variable sites (3.99%) defined 24 haplotypes of E. zuernii. The ML-based phylogenetic tree revealed that Ganzi population-specific haplotypes Hap_23 and Hap_24 closely clustered with Hap_1, and then three haplotypes together were paraphyletic with haplotypes of Daofu (Hap_21 and Hap_22), Ya’an (Hap_9 and Hap_10), LuHuo (Hap_14–16), and Xinlong plus Hongyuan (Hap_2–8)  values of eight geographic populations of Eimeria zuernii based on cox1 datasets.