Acropora digitifera. We show that three genetically distinct populations are present in northwestern Australia, and that their rapid divergence since the last glacial maximum (LGM) can be explained by a combination of founder-effects and restricted gene flow. Signatures of selective sweeps, too strong to be explained by demographic history, are present in all three populations and overlap with genes that show different patterns of functional enrichment between inshore and offshore habitats. In contrast to rapid divergence in the host, we find that photosymbiont communities are largely undifferentiated between corals from all three locations, spanning almost 1000 km, indicating that selection on host genes, and not acquisition of novel symbionts, has been the primary driver of adaptation for this species in northwestern Australia.Climate change threatens the survival of coral reefs on a global scale, primarily through mass bleaching and mortality as a result of marine heatwaves. While these short-term effects are clear, predicting the fate of coral reefs over the coming century is a major challenge. One way to understand the longer-term effect of rapid climate change is to examine the response of coral populations to past climate shifts. Coastal and shallow-water marine ecosystems such as coral reefs have been reshaped many times by sea-level changes during the Pleistocene, yet few studies have directly linked this with its consequences on population demographics, dispersal, and adaptation. Here we use powerful analytical techniques, afforded by haplotype-phased whole-genomes, to establish such links for the reef-building coral,  Glacial cycling during the Pleistocene is thought to be a major driver of biodiversity dynamics , and itsThroughout the tropics, the dominant effect of low sea levels during the LGM was a dramatic reduction in the amount of shallow water habitat . In broaEmerging techniques based on the sequentially Markovian coalescent (SMC) can be used to reconstruct demographic histories of species in unprecedented detail, potentially revealing links with past climate . HoweverEven in systems where the effects of past climate change on biodiversity are relatively well understood, the role of natural selection and adaptation in response to climate change remains uncertain . AddressAcropora digitifera, in northwestern Australia. In this region, A. digitifera is common on offshore atolls at the shelf-edge and also forms part of a diverse inshore (IN) community (in the Kimberley region) that thrives despite extreme heat, frequent aerial exposure, and highly variable turbidity  with GATK  and fineSTRUCTURE analysis fig. 1C;  online sst were markedly lower (Fst ∼ 0.007) between offshore populations than between north-offshore and inshore (Fst ∼ 0.02) and south-offshore and inshore (Fst ∼ 0.02). Despite low overall divergence (as measured with genome-wide Fst) between these populations, admixture coefficients , suggesting that migration is rare or non-existent between locations. Demographic modeling with fastsimcoal2 (see below) confirmed this as it supported a model with recent gene flow but with very low migration coefficients   (E) revealed similar levels of within-location to between-location diversity, confirming that there were no consistent differences in symbiont composition between locations.Based on the relative proportion of reads classified as Symbiodiniaceae by Kraken , all samdocopium  online, docopium . To inveequences  online fef (GBR) . Since mef (GBR) , and canef (GBR) . This reef (GBR)  online. ength k)  in the sength k) E revealeAcropora (−8 per base per generation) based on recently published divergence times  and alternative plausible values for generation time . Variation in these parameters did not result in qualitative changes to the shape of Ne curves but generally led to more recent estimates for key events such as bottlenecks and population splits . In agreement with the existence of a bottleneck and subsequent population expansion, genome-wide estimates of Tajima’s D for all three populations were negative , along with elevated inbreeding coefficients (E) and linkage disequilibrium (LD) (D). Differences between the two offshore populations were less pronounced than between offshore and inshore, however it was clear that the north offshore population retained the highest overall levels of diversity as it had the lowest inbreeding coefficient, smallest proportion of HBD segments and highest SMC++ estimated Ne during the recent stable period (2–5Kya).Populations differed in the timing and severity of the bottleneck, with the strongest and most recent effects seen inshore. This was evident in the SMC++ trajectory as well as the much higher prevalence of homozygous-by-descent (HBD) segments in inshore F, along ficients E and linium (LD) D. DifferC; st values and population structure analyses (see above). Estimates from SMC++ were in approximate agreement with this (9Kya) but did not differentiate between inshore-offshore and offshore-offshore splits.Divergence time estimates from both SMC++ and fastsimcoal2 indicate a recent split for all three populations that coincides with the same post-glacial time window as bottlenecks observed in SMC++ analyses. Bootstrap estimates for the inshore-offshore split based on the best-fitting model in fastsimcoal2 fig. 2C;  online wC inset) with constant migration between offshore populations and secondary contact between inshore and offshore provides a better fit to the SFS than competing models with strict isolation (SI), ancient migration (AM) or continuous migration (IM) (-4),   online. M) (-4),  online. M) (-4),  online sM) (-4),  but prodM) (-4),  online, M) (-4), .B), and the relative rarity of strongly segregating loci in pairwise SFS plots (st) and elevated absolute divergence dxy  maintained ancient divergence  or 2) enfig. 2FS plots  online. ence dxy . Althougas small  online, st; by fivefold for the inshore-offshore split and 2.5-fold for the split between offshore locations  and other parameters, including split times and migration rates, set to their best-fitted values. Compared with simulations under the full model, removing the bottleneck dramatically reduced pairwise Focations  online.A. digitifera populations identified above, we performed a genome-wide scan for signatures of selective sweeps . As the primary basis for this scan, we used three statistics  that summarize patterns of extended haplotype homozygosity (EHH) because these have high power to detect selective sweeps within independent populations (iHS) .To investigate the effects of natural selection on the ns (iHS)  or as a ns (iHS) . Followins (iHS) , we idenfig. 3A;  online aTo control for demographic effects such as bottlenecks, we used simulated data under the best-fitting (IMc) demographic model to calculate threshold values for the PBS that would result in fewer than 1% false positives. As expected, given its more severe bottleneck, this threshold was higher for inshore (IN:0.76) compared with offshore populations . Even at this higher threshold, however, the inshore population had more sweep regions identified by EHH statistics that also overlapped SNPs with significant PBS values  compared with the north offshore  and the south offshore .P < 0.005; at least two distinct sweep regions) in these genes (B). Since multiple genes often overlapped with each sweep region, we also calculated enrichment statistics based on sweep regions rather than genes as independent units and found that all these terms were also enriched (Fisher’s exact test P < 0.005) in at least one population under this criterion (B).Of the 1015 genes that overlapped with loci putatively under selection , 515 could be assigned a GO term using InterProScan 5  based onse genes  online cse genes  online ise genes B. Since riterion B.Three groups of GO terms showed exclusive enrichment in either inshore or offshore locations, potentially reflecting broad patterns of selection related to contrasting environmental conditions. Terms related to membrane G protein-coupled receptors  were strongly enriched in both offshore populations but not in the inshore, with genes underpinning this pattern distributed across 23 independent sweep regions. Exclusive enrichment in inshore was observed for the GO terms, transcription factor activity (GO:0000981) and regulation of apoptotic process (GO: 0042981). Genes supporting enrichment of transcription factor activity in inshore included a diverse range of transcription factors, including those containing homeobox, C2H2 zinc finger, T-box, and forkhead domains, all of which are involved in regulating early development. Enrichment for the GO term, apoptotic process was supported by two independent sweeps, one containing a Bcl-2-like protein (IPR026298) and another that hosted a cluster of 6 genes, each containing a single death effector domain (IPR001875).A), low Tajima’s D (A), and had a clear differentiation between selected and background haplotypes (B). It also contained by far the largest number  of near-privately fixed SNPs , and of these, over 90% were contained within a single gene, s0150.g24.To investigate the link between selection, climate change, and gene function in additional detail, we chose to focus on one of the strongest signatures of selection in the inshore population. This locus was associated with the highest PBS values  and these formed part of a cluster of eight peroxinectin genes found within 200 kb of the sweep. A genome-wide search for haem peroxidases (IPR019791), the parent superfamily that contains peroxinectins, revealed a total of 15 in A). An estimate for the timing of selection on this gene based on the inferred time to the most recent common ancestor for selected haplotypes   , which sAcropora digitifera is among the majority of corals that spawn in autumn (A. tenuis identified strong population structure (Fst > 0.25) separating Rowley Shoals and Scott Reef. Although divergence times have not been estimated for A. tenuis populations in WA, previous microsatellite work has shown that the species comprises two deeply diverged spawning lineages , frequent aerial exposure at low tide, and highly variable turbidity . The comf corals , howeverf corals  and respf corals . HoweverIn our study, we identified a highly localized signal on a gene (s0150.g24) within a locus dominated by other genes from the same family (peroxinectin-like haem peroxidases). This provides a rare instance in which a gene family targeted by selection is relatively unambiguous. Peroxinectins are best characterized in arthropods where they mediate the immune response via cell adhesion  and prosAcropora and related taxa. Since the selected haplotypes differ in amino acid sequence from the background, further functional genetic work has a strong chance of identifying the precise nature of the beneficial change, thereby providing a rare opportunity to associate gene function with local adaptive benefit in a wild population.Our results highlight the potential importance of peroxinectins in adaptation to the extreme conditions experienced by inshore corals and invite future work to characterize the evolution and function of co-located peroxinectins in Acropora digitifera to past climate change. They suggest that this species was likely extirpated throughout much of western Australia during the LGM, but recolonized and underwent rapid population expansion when conditions became favorable. Signatures of selection in all three populations indicate that dispersal and diversification were also accompanied by local adaptation via selective pressure on many loci. Of particular interest in the context of future climate change are the inshore Kimberley populations as these corals are known for their ability to survive extreme heat, turbidity, and exposure  in coral populations is a key deciding factor in their ability to adapt to climate change  and March 2018  across our three study locations. DNA extractions were performed by Diversity Array Technology Pty Ltd. (DArT P/L) and the extracted DNA was then sent to the QB3 UC Berkeley sequencing center for whole genome sequencing. Initial sequencing was performed on a single NovaSeq S4 flowcell to obtain ∼3 billion 2 × 150 bp paired-end reads across all samples. Additional sequencing was then performed on a second NovaSeq S4 flowcell for 33 samples because they failed to achieve the target depth of 10x in the first batch. Samples included in the second batch of sequencing were spread across all sites in the study  were within 5 bp of InDels, 2) failed to meet recommended GATK hard filtering quality thresholds, 3) were located within simple repeats, 4) had more than 10% missing genotype calls, and 5) had read coverage outside expected bounds. After filtering, we obtained 9,656,554 high-quality biallelic SNPs from 75 samples. A summary of the number of missing genotypes in all samples after filtering is provided in π), Tajima’s D, LD, and heterozygosity were calculated genome-wide using the unphased, filtered variant set. The het function in PLINK2 (v2.00a3) (r2) was calculated in 1Mb windows using plink v1.9   was usedv2.00a3) , respectv2.00a3)  to removink v1.9  based onP-value < 1e-4). SNPs in high LD were removed using PLINK v1.9 (—indep pairwise 50 10 0.1). PCA analysis was performed using smartpca from EIGENSOFT v6.1.4  analysis  on the pGenomic regions inherited by descent (IBD) were identified using the package Refined IBD Brian L. . Breaks A. digitifera populations from this study within a broader phylogenetic context, we extracted established phylogenetic markers  using BWA (v0.7.17). A consensus sequence corresponding to a 1000 bp interval around the central base of each probe was then called using BCFtools (1.11), with ambiguous bases arising from heterozygous sites encoded using their corresponding IUPAC codes. Consensus sequences for Western Australian samples were called based on bam files generated for variant calling. For Japanese samples, raw reads were mapped to the genome using BWA MEM and duplicates marked using GATK, as was done for our own samples. After mapping a total of 16 Japanese samples, we selected five with coverage >15x . After extracting consensus sequences for all samples, we then used MAFFT (v7.394)   to alignhttps://github.com/pomo-dev/cflib based on alignments across all UCE/Exon loci and inference was performed using the HKY + P model with 1000 ultrafast bootstraps. For the traditional phylogenetic approach, we used the same alignments as for PoMo and created a partition file in Nexus format listing them. Using modelfinder elfinder , we idenelfinder .−8 per base per generation, and starting and ending time points set to 20-200 000 generations. Divergence times for each population pair were inferred using the SMC++ split command with marginal estimates produced by using the estimate option. To address the uncertainty in SMC++ analysis from mutation rate and generation time parameters, we tested two additional mutation rates: 1.86e−8 . The vcf files of each scaffold were converted into SMC++ input format using the vcf2smc script while masking large uncalled regions. Multiple SMC files were generated for each scaffold by varying the choice of ‘distinguished individual’ over all samples. To estimate population size histories, all SMC++ input files were used together in a single run with the options, thinning 3000, 50 EM iterations, 40 knots, mutation rate 1.20e 1.86e−8 ; 2.98e−86e−8  to generate a joint three-dimensional folded SFS with 257,314 SNPs. To utilize the mutation rate in branch length calculations, we estimated the number of monomorphic sites based on the proportion of mappable sites defined by the SNPable pipeline.To prepare data for fastsimcoal2 , we usedFirst, we tested four alternative topologies, indicating alternative splitting modes among three populations  online. We generated simulated data under the best fitting parameter set for the IMc model using fastsimcoal2 with an identical model specification file to that used for SFS fitting. We performed 50 independent simulations, each of which used parameters drawn randomly from a uniform distribution across a 90% confidence interval based on our bootstrap estimates (see above). Each simulation generated 20 scaffolds of length two mb. Based on this data, we then calculated: 1) the length of HBD segments using ibdseq, 2) inbreeding coefficient using plink2, 3) Tajima’s D using vk tajima, 4) admixture coefficients using ADMIXTURE, and 5) population branch statistics using plink. All calculations were performed using identical settings to those used for real data. The results are shown in st and performed PCA using plink2. Results are shown in Simulations based on a modified version of the IMc model were used to assess the contribution of population size changes  to population differentiation. The IMc model was modified so that the total population was conserved at its ancestral size, dividing this at population splits to achieve equal populations in the most recent time period. All other parameters were left unmodified. We ran 10 independent simulations using the same process described above with parameter draws allowing variation in divergence times and migration rates but not population sizes. Based on this data, we calculated pairwise FWe used selscan v1.3.0  with defst statistics genome-wide for all pairs of populations, using the default Fst calculation (Hudson). These Fst values were then used to calculate the population branch statistic as described in its original paper , which measure the change in allele frequency in a focal population since its divergence from two other populations. First, we used the –fst function in PLINK to calculate Fal paper . We thenal paper . Our appA. digitifera genes, assigning GO terms via blast and Interproscan searches  with a given term and comparing this to the background count across all regions.To support GO enrichment analysis, we performed functional annotation of ches see . The R pches see  with theAcropora digitifera genome assembly, we classified raw reads from all samples using kraken v1.0  reads originating from Symbiodiniaceae. Next, we mapped the reads to the mitochondrial genome of Cladocopium C1 and built a haplotype network using PopART  to calculate the d2s metric based on shared k-mers in sequencing reads from each pair of samples. This produced a set of pairwise distances which we visualized using an MDS plot (E).Using a custom database composed of the genomes of five common coral associating Symbiodiniaceae genera and the ken v1.0 . This cog PopART  with theg PopART  databaseMDS plot E.Although the d2s metric has previously been shown to discriminate between whole genome sequences of different Symbiodiniaceae species , its powA). Of these 75 sites, we chose three spanning the length of the gene . After performing visual checks of haplotype structure   to estimfig. 4ture see  we then tion see , a chain−8 per base per generation, and a recombination rate (3.2e−8 per base per generation) as used for starTMRCA.To estimate the time of origin for derived alleles in the peroxinectin locus, we used Genealogical Estimation of Variant Age (GEVA) . First aAcropora millepora, Acropora tenuis, Porites lutea, and Pachyseris speciosa. Protein sequences for all genes identified as belonging to the haem peroxidase family (IPR019791) by Interproscan were extracted from Acropora digitifera. Using these as query sequences, we identified all close homologs  from the protein sets of all other species using blastp. These were then aligned using the MAFFT (v7.394)   with the(v7.394)  was usedmsac201_Supplementary_DataClick here for additional data file.


Actinidia species from large-scale sympatric and allopatric regions. Genome sequence data revealed that hexaploid Actinidia deliciosa originated from Actinidia chinensis and supported the speciation-with-gene-flow model in sympatric regions. The common ancestor of Actinidia setosa and A. deliciosa migrated from the mainland to the Taiwan Island ~2.91 Mya and formed A. setosa ~0.92 Mya, and the speciation of A. setosa is consistent with the divergence-after-speciation model with selective sweeps. Geographic isolation resulted in population contraction and accelerated the process of lineage sorting and speciation due to natural selection. Genomic islands contained genes associated with organ development, local adaptation, and stress resistance, indicating selective sweeps on a specific set of traits. Our results highlight the patterns of genomic divergence in sympatric and allopatric speciation, with the mediation of geographic isolation in the formation of genomic islands during Actinidia speciation.Isolation by geographic distance is involved in the formation of potential genomic islands and the divergence of genomes, which often result in speciation. The mechanisms of sympatric and allopatric speciation associated with geographic distance remain a topic of interest to evolutionary biologists. Here, we examined genomic divergence in three  Speciation based on geographical distance can be categorized into sympatric and allopatric types . SympatrUnderstanding the process of speciation and post-speciation ecological adaptation has been advanced by studies of genomic polymorphism and divergence among the genomes of closely related species , 7, and Actinidia species  and to elucidate their adaptation to local selection in nature, employing population genomic resequencing. The Actinidia genus (named Mihoutao in Chinese) originated in China and is now mainly distributed from the Qinling Mountains to the Hengduan Mountains. The geographic distribution of A. chinensis and A. deliciosa has sympatric regions, with the former predominating in the eastern part of China and the latter in the west, whereas A. setosa, an endemic species, is restricted to the island of Taiwan and is allopatric to the other two species. Island and mountain topography separate biological populations and accelerate population differentiation and speciation because of limited gene flow between populations ..ActinidiA. chinensis “Hongyang” reference genome [The remaining high-quality paired-end reads were mapped to the diploid e genome  using BWe genome  with thee genome . SAMtoole genome . After aTo solve the difference in SNPs from diploid and polyploid populations, we have called SNPs with the GATK software setting HaplotypeCaller “—ploidy 4” for tetraploid populations and “—ploidy 6” for hexaploid populations. However, most software packages, including ADMIXTURE, PLINK, and VCFtools, cannot deal with multiallelic SNPs but only with biallelic SNPs, which limits the next analysis. We only obtained an NJ tree based on multiallelic SNPs for polyploid populations after low-quality SNP filtering, and the tree was the same as that constructed from biallelic SNPs. This may indicate that the analysis of biallelic SNPs is reliable for polyploid populations, as previous studies have suggested . In addiIndividual-based maximum-likelihood (ML) and neighbor-joining (NJ) trees were constructed based on the p-distance using TreeBeST v1.9.2 software . The pop2) of alleles to estimate linkage disequilibrium (LD) using Haploview [2 value was calculated for pairwise markers in 500-kb windows and averaged across the whole genome, and LD decay figures were drawn using an R script.Nucleotide diversity (θπ) of each population was calculated using a sliding-window approach (40-kb windows with 20-kb increments). We calculated the correlation coefficient  model [*2 þ 4 þ 6’”. The mutation rate (μ) was set to 5.4 × 10−9 per base per generation [To investigate the demographic history of the three species, the effective population size (Ne) of the three C) model . Parametneration , and theref × L, where μ was the mutation rate (5.4 × 10−9) and L was the number of SNPs. To ensure selective neutrality, only the SNPs within intergenic regions of autosomal chromosomes were used. We evaluated model fitting and optimized model selection using a composite-likelihood ratio test. The optimal model was selected with the highest log-likelihood value from five constructed divergence models.We inferred the demographic history of the three species using the diffusion approximation for demographic inference (∂a∂i) approach . We usedActinidia populations in China was estimated under a Bayesian approach using BEAST v2.3.4 [−9). MCMC runs were performed for 10 000 000 generations, with sampling every 1000 generations following a burn-in of the initial 50% of cycles. We examined the sampling adequacy and convergence of the chains to a stationary distribution using Tracer v1.5. TreeAnnotator summarized a post burn-in tree and produced a maximum clade credibility chronogram showing mean estimated divergence time with 95% HPD intervals [The divergence time of these natural T v2.3.4  accordinntervals .A. chinensis populations using TreeMix v.1.12 [A population-level admixture analysis was conducted to detect historical gene flow between wild x v.1.12  with thex v.1.12 . From onA. chinensis, A. deliciosa, and A. setosa) and effects of geographic isolation on speciation. Geographic isolation included three scenarios, i.e. oceanic island (TWS + ZSC as one oceanic population vs. TPC + YAC + SYC + JZD + ZLD as one mainland population), lake island (JSC island vs. YMC land), and mountain isolation . A sliding window approach (40-kb window and 20-kb step size) was used to identify selected regions associated with specific adaptations. The genome-wide distribution of FST and Tajima’s D was calculated using VCFtools [XYD) was calculated from sample allele frequency posterior probabilities at each site and was then averaged over each 20-kb window using an in-house python script.To identify genome-wide selective sweeps associated with natural adaptation, we measured genome-wide variation for the pairwise comparisons of the three species (VCFtools . Absolutec) were estimated for diploid species between each pair of SNPs and then weight-averaged over each 20-kb window using the program LDhelmet v.1.10 [Population-scaled recombination rates  were identified as highly divergent regions and designated genomic islands. Z-FST was defined by the formula Z-FST = (FST × FST′)/std-FST , where FST was a per-window estimate, and FST′ and std-FST were the mean and standard deviation of FST across windows. To identify regions in the genome linked to potential lineage-specific adaptations, genetic diversity, the number of SNPs, Tajima’s D, and XYD in genomic islands were compared with genomic background for any pairwise comparisons. We compared characteristics of genomic islands in the pairwise comparisons.Genomic regions with significant high FST and log2 (θπ ratio) values simultaneously as candidate outliers under strong selective sweeps for pairwise comparisons of the three species and geographic isolation scenarios. All outlier windows were assigned to corresponding SNPs and genes.We considered the windows with the top 5% XYD between genomic islands and the rest of the genome for each pairwise comparison using R software.ANOVA and randomization analysis were used to detect differences in A. chinensis “Hongyang” reference genome. Enrichment analyses of these genes were conducted using the Gene Ontology (GO) [http://www.genome.jp/kegg/) databases. Significant enriched gene function was tested using a false discovery rate (FDR) with a corrected binomial distribution probability approach at the level of P < 0.0545. The functions of the candidate genes were inferred from the NCBI (http://www.ncbi.nlm.nih.gov) and PIR (http://www.uniprot.org) databases.We annotated genes in outlier genomic regions using the ogy (GO)  and KEGGA. chinensis had a value of “0” (absence) and A. deliciosa a value of “1” (presence). To reduce the risk of false positives from population structure, we conducted the analysis with the genome-wide efficient mixed-model association (GEMMA) software package [α and β are fixed effects representing marker effects and non-marker effects, respectively; y represents phenotype; and μ represents unknown random effects. X, S, and K are the incidence matrices for α, β, and μ, respectively, and e is a vector of random residual effects. The S matrix for population-structure correction was built up using the top three PCs. We built up the K matrix using the matrix of simple matching coefficients.A total of 3 556 911 SNPs  were used in GWAS for the trichome trait. The trichome trait was defined here as a presence or absence trait;  package . For mixAfter stringent quality filtering, we identified a total of 3 556 911 high-quality SNPs from the initial collection of 44 549 362 raw SNPs. The number of SNPs varied among the populations and ploidy races, and the percentage of heterogeneous SNPs in hexaploid and tetraploid populations was higher than that in diploid populations, with the lowest percentage in the TWS population .A. setosa (TWS) had short clade branch lengths. The ZSC population (tetraploid A. chinensis) and the SMD population (tetraploid A. deliciosa) clustered together and were located in the middle of diploid TIC and TPC + YAC + SYC.Based on phylogenetic analysis, individuals from the same population clustered together, and each of the three species clustered into a different subclade . A. setoA. setosa (TWS) from the other two species, and the second principal component  separated hexaploid A. deliciosa (JZD and ZLD) from the other lineages. The geographically isolated populations  within A. chinensis were separated by the third principal component (variance explained = 13.5%). The PCA results were consistent with the clustering analyses that showed geographic populations (best K = 6)  had a genetic background from other populations in cases of all K values, indicating that it is likely to be an intermediate phenotype produced in the heterozygote, which may be attributed to shared ancestral polymorphism or introgression events  of SNP genotypes among all individuals clearly revealed a history of population divergence . The firt K = 6) . Three cormation . The tetn events .ec) of A. setosa were the lowest of the three species  and population-scaled recombination rate  of A. chinensis and A. setosa began to decrease at ~1 Mya, experienced an increase at ~0.3–0.5 Mya, and then experienced a bottleneck event at ~100 kya  [A. chinensis and the other two species was ~10.1 Mya  . The div10.1 Mya , and A. . setosa .At the population scale, BEAST analysis showed that the TWS population diverged from the inland populations ~2.91 Mya  . The twoSTF distribution varied in the three pairwise species comparisons  (STF) was highly heterogeneous along genomes  ≥2, corresponding to 4–5% of windows, were considered to be genomic islands for pairwise comparisons. We identified 56 common genomic islands among the three pairwise comparisons. These genomic islands showed reduced π and Tajima’s D values, indicating that linked selection had acted on these islands (The landscape of the weighted 2.2e−16) . Genetic genomes  and nega genomes ; Fig. 3A islands .XYD in genomic islands compared with the rest of the genomes in pairwise comparisons of the three species  (A. chinensis and A. deliciosa) or allopatric species (A. setosa vs. A. chinensis or A. deliciosa). Genomic islands showed a significantly reduced recombination rate (ρ) compared with the rest of the genome for the three pairwise comparisons  , irrespeFST (genomic islands) and log2 (θπ ratio) simultaneously  were significantly higher than the value for lake isolation (<0.2) (A. chinensis did not show an isolation-by-distance effect of STF (The genetic diversity (θπ) of oceanic and lake islands was not significantly different from those of land populations . FST valn (<0.2) . The fout of FST .−16, Mann–Whitney U test) , indicating positive selection or a bottleneck effect in oceanic islands . Moreove U test) , reflect U test) .XYD were positively correlated with STF for oceanic isolation but not for lake isolation  in oceanic island populations, whereas genomic islands had reduced Tajima’s D values and nucleotide diversity for lake isolation . The valsolation . These rXYD was elevated in genomic islands compared with the rest of the genomes in the lake island comparison (P < 0.001), whereas XYD decreased in genomic islands in the oceanic island comparison (P < 0.001) .< 0.001) . The decSTF values and θπ ratio cutoffs  for the trichome trait was performed to test the local adaptation of the three species, and it revealed 2268 SNPs and 2033 genes for the trichome trait . The selGWAS analysis for the trichome trait revealed genes involved in trichome initiation, formation, and development, such as zinc finger proteins (ZFPs), TCP proteins, bHLH and WD40 proteins, MYB transcription factors, DUF/TBL1(trichome birefringence-like) proteins, and cellulose synthase, and in ecological adaptation via biotic and abiotic stress resistance, such as members of the WRKY gene family, PERK1, auxin response factors and induced proteins, and genes in the ethylene (EIN3) and gibberellin (GA) phytohormone pathways .Actinidia species. The genomic islands of divergence that distinguish the three Actinidia species most likely derived from gene flow in the sympatric regions, lineage sorting of ancient polymorphisms, and ecological adaptation under selective sweeps. Geographic isolation plays a key role in the formation of genomic islands during speciation, which varies with the time length of divergence.Our population genomic analysis suggests heterogeneous patterns of genomic divergence in the sympatric and allopatric speciation of three A. deliciosa and A. setosa diverged from A. chinensis at ~10.1 Mya. A. chinensis and A. deliciosa interbreed in sympatric regions but maintain distinct morphologies. A previous study found that A. deliciosa has a family of repeat sequences not present in diploid A. chinensis, which suggests that it may be an allopolyploid species and that other species were involved in the origin of A. deliciosa [A. deliciosa diverged from A. chinensis, but there was insufficient information to support its allopolyploid or autopolyploid origin. Diploid A. chinensis is probably itself a cryptic polyploid or rediploidized paleopolyploid because its basic chromosome number (n = 29) is high [A. chinensis have Robertsonian-like centromeric translocations [A. deliciosa increased rapidly, which presumably was advantageous for ecological adaptation. Morphological intermediates and hybrid forms between A. deliciosa and A. chinensis have been found in nature [Our results indicate the common ancestor of eliciosa . In the  is high , 48. Mosocations . Polyploocations , which in nature , and then nature .A. setosa is derived from the last common ancestor shared with A. deliciosa in mainland China ~2.91 Mya and formed a separate species in the Taiwan Island at ~0.92 Mya. The divergence time (~2.91 Mya) of A. setosa was less than the formation time (~5 Mya) of the Taiwan Island [A. setosa genetic diversity [A. setosa is a separate species [A. setosa diverged from A. chinensis and A. deliciosa based on chloroplastic and mitochondrial DNA sequences [A. setosa resulted from its low effective population size under island isolation, with minimal gene flow, reduced recombination, and increased genetic drift due to a high hitchhiking effect or selective sweeps [Our results suggest that n Island . A low eiversity . Liang a species , and Chaequences . We conce sweeps .STF) between the three species was highly heterogeneous along the genome, probably owing to demographic processes and genetic drift [A. setosa) or population expansion due to gene flow and introgression (A. deliciosa) resulted in rapid stochastic loss or fixation of alleles (haplotypes) [XYD) was elevated in genomic islands for both sympatric speciation (A. chinensis–A. deliciosa) and allopatric speciation (A. deliciosa–A. setosa and A. chinensis–A. setosa). Elevated XYD in genomic islands resulted from differential gene flow between genomic regions or from the presence of anciently diverged haplotypes [A. chinensis occurs mostly at altitudes between 200 and 1200 m, whereas A. deliciosa is usually found at 800–1400 m and A. setosa at 1300–2600 m [A. setosa in the Taiwan Island but fixed the variation of neutral loci through a hitchhiking effect and increased genetic diversity in genomic islands, which exhibited a low recombination rate compared with the background genome. Low recombination regions are generally associated with a high hitchhiking effect or selective sweeps [The level of divergence (ic drift . Populatlotypes) . Howeverplotypes . In sympplotypes . In alloplotypes . Divergeplotypes . Moreoveplotypes , 12, as 0–2600 m . We conce sweeps . This sue sweeps .XYD values in genomic islands of oceanic island populations (TWS + ZSC) compared with mainland populations, indicating ongoing background selection and recurrent selective sweeps due to linked selection in the genomic islands of isolated populations [Interestingly, we found reduced ulations . This suulations , 60. Islulations .STF) from mainland populations, whereas short-term lake isolation did not. A new species (A. setosa) was formed on the Taiwan Island, and a tetraploid population of A. chinensis was generated in the Zhoushan Archipelago. Geographic isolation is one of the main reasons for population differentiation and eventual speciation, with limited gene flow among populations [Aeonium resulted from geographic isolation. We suppose that the Zhoushan Archipelago population derived from the SMD population because the Zhoushan Archipelago and the Siming mountains belonged to the Tiantai Mountain Chain before formation of the Zhoushan Archipelago as a result of rising sea levels. The high LD of the ZSC population indicates that individuals experienced positive selection or selective sweeps in the isolated Zhoushan Archipelago, which may explain the maintenance of high divergence between species despite extensive gene flow [A. chinensis populations. The dioecy characteristics of A. chinensis can decrease its inbreeding rate and counteract the negative effects of geographic isolation [Our results showed that the genetic effects of geographic isolation varied with the time length of isolation, over 60 years for the thousand-island lake isolation, 7000–9000 years for the Zhoushan Archipelago, and ~5 Mya for the Taiwan Island . Long-teulations , 61–63. ulations  found thene flow . In addisolation . Gene flsolation –70. The solation .A. deliciosa plants with trichomes.Genes in genomic islands have been associated with local adaptation, organ development, and reproductive isolation, and they are likely to experience morphological and ecological divergence between lineages due to geographic isolation . For exaActinidia species and sheds light on the mechanisms by which geographic isolation influences speciation through its effects on population size and gene flow among populations. Regardless of the large-scale or small-scale biogeographic patterns, the three species showed post-speciation adaptation to the local environment, with the trichome trait phenotype and related genes. The results distinguished the mechanisms of genomic divergence for sympatric and allopatric speciation processes of the three species, involving gene flow, ancestral polymorphisms, and selective sweeps. Our study suggests that geographic isolation represents an important factor in speciation with selective sweeps or background selection, and it highlights the significance of the time length of divergence.In conclusion, our study provides insights into the phylogenetic relationships, speciation histories, and corresponding genomic divergence of three We thank Liu F., Han W., and local farmers for their assistance in field sampling and Prof. Cheng F. and Dr. Yang Y. for their assistance in the analysis of recombination rate. This work was financially supported by the Biodiversity Survey, Observation and Assessment of the Ministry of Ecology and Environment, China (2019HJ2096001006) and the General Research Project of CRAES, China (No. 2016YSKY-08).Y.L. designed the study. Y.L., W.Y., B.W., and J.L. performed the experiment. Y.L. wrote the manuscript. All authors read and approved the manuscript.Data will be uploaded after acceptance.The authors declare that they have no conflict of interest.Horticulture Research Journal online.Web_Material_uhac054Click here for additional data file.


Callinectes sapidus, has always been a well-known crab species all along the temperate and tropical American east coast. Over the past century, there have been increasing reports of this species from Africa, Asia, and Europe. However, the corresponding introduction pathways remain a reason for speculation. Its long larval development in marine plankton and tolerance towards varying salinities are prerequisites for a successful dispersal by marine currents or in ballast waters. On the other hand, being a highly valued seafood, it is conceivable that C. sapidus may have been intentionally released to establish breeding populations elsewhere. The species started expanding conspicuously in the east Mediterranean after the 1930s . On the other hand, western Mediterranean records are much more recent and regionally confined. The reconstruction of their origin is the main goal of the current study. For that purpose, the genetic composition of populations from the American native range and from the entire Mediterranean needed to be included and used for the overall comparison. It appears that only a few founding individuals are responsible for the invasion into Spanish and Italian waters, arguing in favor of a dispersal theory.Due to its large size and importance in commercial and recreational fishery, the blue crab, Callinectes sapidus is a particularly successful invader in estuarine ecosystems worldwide. Despite increasing awareness of its potential harm, the invasion history and underlying genetic diversity of this species within the Mediterranean Sea remain unknown. This study constitutes the first large-scale approach to study phylogeographic patterns of C. sapidus in Europe, facilitated by the first comparison of all currently available COI sequence data. For this investigation, 71 individuals of C. sapidus were newly analyzed and the entire COI gene was sequenced and used for a comparative phylogeographic analyses. For the first time, two separately used adjacent regions of this gene were combined in a single dataset. This allowed emphasizing the prevalence of three geographically defined lineages within the native range: (1) eastern North America, including the Gulf of Mexico, (2) the Caribbean, and (3) Brazil. New data from the Mediterranean reveal that non-native populations of C. sapidus are characterized by a conspicuously low genetic diversity , and that there is surprisingly low connectivity among established populations. The occurrence of strong genetic bottlenecks suggests few founder individuals. This confirms that, even under a scenario of restricted large-scale gene flow, a very limited number of invasive individuals is sufficient for a massive impact.The American blue crab  Recent studies document an alarming loss of biodiversity over the past few decades, roughly one-tenth of the global wildlife over the past twenty years alone . This ocThe immediate impact of most non-indigenous species on newly colonized ecosystems remains largely unexplored ,15, but Callinectes sapidus Rathbun, 1896 is considered a particularly successful invader in Mediterranean coastal ecosystems [More than 70 non-indigenous decapod species have been introduced into the Mediterranean Sea, now co-existing or competing with 309 indigenous species ,20. Amonosystems ,22. It iosystems . Individosystems . The speosystems . Other bosystems ,23,24 prosystems ,26,27.C. sapidus was often misidentified as one of the Indo-Pacific invasive species, i.e., Portunus pelagicus  in 1951 or Portunus segnis  [C. sapidus in the Mediterranean Sea was in 1947 in the Aegean Sea [C. sapidus remained undetermined.The documented colonization of European waters began in 1900 along the Atlantic coasts of France , which wl, 1775) . The firgean Sea . Nowadaygean Sea . A recengean Sea  assessedC. sapidus in the Mediterranean Sea. In order to do so DNA-sequences of the almost complete mitochondrial gene cytochrome c oxidase subunit I (COI) from C. sapidus specimens from the Mediterranean Sea, namely from Albania, Italy, Romania, Spain, and Turkey, were compared with samples from the entire native distribution range in the western Atlantic, including the Gulf of Mexico and the Caribbean Sea. Maximum parsimony networks and analyses of molecular variance were applied to provide insights into the ancestry, degree of genetic differentiation, and gene flow among the studied native and invasive populations. The gene flow analyses not only provide information about the genetic connectivity among Mediterranean populations but should also allow predictions of the expected rate of future spread in this region. Considering the vast genetic variability of Callinectes sapidus in its native area and the many possible vectors of invasion throughout the past century, our expectation was to also encounter a relatively high genetic variability within representatives of the species in the Mediterranean Sea.In the present study, our aim was to find answers to the question of the potential origin and number of introduction events, the genetic diversity of introduced populations, and the intraspecific phylogeographic relationships of C. sapidus in the Mediterranean Sea were the Italian lagoons of Acquatina, Lesina, and Torre Colimena, as well as the coastal waters of Albania, Italy, and Spain. In addition, three samples were kindly made available from the Romanian Black Sea. Four additional sequences were obtained from native populations in Brazil, Jamaica, Mexico, and Louisiana (USA). In total, new DNA sequences from 71 individuals were obtained. The here presented phylogeographic analyses are based on samples collected by us from various locations or kindly provided by colleagues. Most of the animal material originated from European waters. Sampling sites of C. sapidus, available sequences from GenBank (including native American and introduced Turkish populations) were also retrieved for subsequent analyses , after extracting muscle tissue from a pereiopod. To analyze phylogeographic relationships up to 1554 basepairs (including primers) of the mitochondrial DNA encoding the enzyme cytochrome oxidase subunit 1 (COI) of the mitochondrial respiratory chain were amplified. The PCR was performed according to the GoTAQ® Flexi DNA Polymerase Protocol  in 25µL samples. Amplification was conducted according to the following temperature profile: initial denaturation for 4 min at 94 °C; 40 cycles of 45 s at 95 °C for denaturation, 1 min at 50 °C for primer annealing and 1 min at 72 °C for elongation; final extension for 4 min at 72 °C. The following primers were used: COL6a (5′-CAAATCATAAAGAYATTGG-3′) and COL6E  as forward primers and COH900  and COH6 (5′-TGRTTYTTTGGHCAYCCHGAAGTHTA-3′) as reverse primers . PCR proΦST, based on Tajima-Nei distance) and haplotype frequencies (FST). Significance levels of these two F-statistics were assessed by a randomization procedure with 10,000 permutations, as implemented in Arlequin [Quantification of overall genetic differentiation, by means of one level AMOVA, and assessment of gene flow, through pairwise comparison of genetic distances, were conducted in Arlequin 3.5.2.2  for two Arlequin .Callinectes sapidus outside the native distribution range seems to have been driven by the potential effect of a severe genetic bottleneck. In order to statistically assess this assumption, genetic diversity, demographic estimates, and population genetic differentiation were computed and compared between blue crab populations from the native and invaded sampling sites. For this purpose, the first 637 basepairs of the COI sequence data were used for a comparison of six populations from the native distribution area  and five from newly invaded regions . The choice of these two groups (representative of native and invaded areas and with comparable sample size) allows avoiding biased results when using all available sequences of C. sapidus, provided that the generated COI sequences for the native range markedly outnumber those obtained so far for the invaded sampling area. Genetic variability was estimated for each population, as well as for each regional dataset, by means of number of haplotypes (Nh), haplotype (h) and nucleotide (π) diversities, and the mean number of nucleotide differences (K). These measurements were determined with the software DNASP 5.10 [D [Fs [D and Fs are reliable indicators of demographic expansion [D and Fu’s Fs, however, usually hint at the occurrence of population demographic contractions or genetic bottlenecks [C. sapidus from native and invaded sampling sites. We used the same statistical procedure, implemented in Arlequin, as previously described to assess pairwise comparisons of genetic differentiation.Based on the outcome of the mitochondrial genealogy (see Results), the genetic makeup of the newly established populations of ASP 5.10  and comp 5.10 [D  and Fu’s0 [D [Fs . These sxpansion ,40. Positlenecks . ProvideCallinectes sapidus based on different regions of the mitochondrial molecular marker COI, we used all available sequences (self-generated and from GenBank) and listed them in For the construction of three haplotype networks of The first haplotype network  is basedThe second network  is basedIn this network, a closer connection between the Caribbean and North American Atlantic populations seems to be the case. Two single haplotypes from South Carolina were characterized by a great similarity to the central Caribbean haplotype. In this gene region, the highest genetic divergence can be ascribed to Brazilian haplotypes. The central Brazilian haplotype (ht III) was recovered in more than 50 individuals and was markedly distinct from the North American haplotypes (at least 17 fixed mutations). Furthermore, several singletons were present in the Brazilian population, which mostly differ in only one nucleotide base from the main haplotype. This network also demonstrates a high genetic diversity within the distribution area of the US Atlantic coast, including the Gulf of Mexico. This diversity is expressed in the high number of haplotypes, which often show only single or few mutations in their sequences.The most frequent haplotype (ht I) along the North American Atlantic coast can be considered as the extension of ht I from the ’Folmer region’. However, in this case, this central haplotype was no longer restricted to North American samples, and a few from Brazil, but was also found in three Spanish individuals carrying the western European haplotype (CSWM2). In this DNA region, three different haplotypes were present among the European specimens. The more common and widespread haplotype in Europe (CSWM1) was found in sequences from Ebro, Casalvelino, Romania, Albania, and Virginia. Two specimens from Torre Colimena (ToCo) differ in two positions, forming a separate haplotype. No specimens from Turkey were included in this network, because from there no sequences from the ’Palumbi region’ are available in GenBank.C. sapidus were also analyzed with a longer COI fragment of 998 bp, as a combination of both previous regions, and are summarized in Genetic differences between American and European populations of Consistent with the network in ΦST) of 0.486 and a haplotype frequency (FST) of 0.03 .The analysis highlighted significant differences in the haplotype frequencies and nucleotide divergences of the South American population. ΦST = 0.764, FST = 0.492; p < 0.001; see The one-level AMOVA of the European populations gives evidence of significant overall genetic differentiation . This divergence from the other populations was already visible in the first haplotype network (ΦST (based on nucleotide diversities), ranging from 0.219 to 0.766, and those of FST (based on haplotype frequencies), from 0.258 to 0.464, of the only North American population include (Virginia) showed the same pattern. An exchange of genes with the other populations can thus be ruled out. Furthermore, no gene flow barriers between the populations from the Tyrrhenian Sea and the Eastern Mediterranean Basin could be detected, as well as between the two Spanish populations. In contrast, the genetic differentiation of the Ebro population to the populations from the Tyrrhenian Sea and Eastern Basin revealed weakly significant values .The individuals from Turkey were genetically differentiated, with highly significant values for both nucleotide divergences and haplotype frequencies  was recorded in the population of Florida, while those corresponding to the nucleotide diversity (π) and mean number of nucleotide differences (K) were highlighted for the South American population. Trends of variation in genetic variability across the invaded sampling area unveiled higher outputs of h for the Ebro populations and π, and K for the Turkish samples. The lowest levels in these three parameters were recorded in the Tyrrhenian population. Overall, population genetic diversity of the blue crab C. sapidus from the native distribution area was found to be markedly higher than that recorded in newly invaded sites for all examined DNA diversity metrics   . This fi, and K) .D and Fu’s Fs) unraveled contrasting patterns among samples of C. sapidus from native and invaded sites, resulting in overall significantly negative outputs within the native range, opposed to positive values of both indices across newly invaded territories , a second one to the Caribbean Sea in Central America (Caribbean lineage), and the third one to the southwest Atlantic (South American lineage). These lineages have already been mentioned in previous studies: Santos & D’Incao [C. sapidus  cluster within the North American clade, suggesting possible human introductions within the American continent.The phylogeographic comparisons carried out in the present study on native and invasive populations of the Atlantic blue crab  D’Incao  and Rodr D’Incao  distingu D’Incao  recogniz D’Incao . InteresC. sapidus from the Gulf of Mexico and the northwest Atlantic. This low genetic structuring within the North American lineage is supported by the knowledge that a long pelagic larval duration facilitates a high degree of gene flow over long distances and leads to low genetic differentiation, as shown for many other marine species . In . In C. sd Burton , giving d Burton  determind Burton , but redic coast ,55. The a et al. . They dia et al. .Callinectes sapidus in Mediterranean waters, which so far has not been explored at a whole-basin scale. The genetic diversity in the western Mediterranean Basin only reflects a minimal fraction of the one known from the Americas, and the occurrence of only two frequent haplotypes , all favor the possibility that the gene pools across invaded sites were shaped by a recent genetic bottleneck, as a consequence of the recent invasion of the Mediterranean Sea. Genetic analyses of complementary nuclear markers in geographically extended and more representative samples from the Mediterranean Sea would help to consolidate these findings. Genetic impoverishment is often found in newly established populations [Carcinus, for which an analysis of microsatellite markers revealed that island populations significantly differ from continental ones [The ultimate goal of the present study was the genetic characterization of nd CSWM2 ) can be ulations . This efulations . The lowtal ones .C. sapidus has been present in the Gulf of Saros and Thessaloniki since 1935 [C. sapidus from the Turkish Black Sea. In agreement with our results, the study showed that the founder of the population encountered in the Black Sea probably originated from the North American lineage. Their comparison of populations from the Black Sea  and Levantine Sea (Turkish specimens in GenBank) also suggested a strong differentiation. The physical barriers of the Dardanelles Strait and the Bosporus and the northeastern Aegean Front may maintain restricted gene flow. In general, when determining the impact of hydrodynamic processes on the population genetic connectivity, it is imperative to include seasonality and intensity fluctuations of fronts and currents. This phenomenon is already known from many other fronts and currents [Our results of the pairwise comparisons of genetic differentiation among the European populations are of especially high interest. With a few exceptions, the gene flow among these populations is largely restricted. Significant genetic differentiation could be demonstrated over the entire Mediterranean Sea, as for example between the Spanish and Italian populations or between both and Turkish populations. This genetic structuring stands in sharp contrast with the extensive (mostly unrestricted) gene flow observed in North America. Possibly, several oceanographic factors in the Mediterranean Sea maintain genetic differentiation. This marginal sea is subdivided into several basins characterized by different current systems and ecological conditions , and a nnce 1935 ,63. Furtnce 1935 , and it nce 1935  geneticacurrents ; an examcurrents .C. sapidus in the Mediterranean Sea could be habitat discontinuities. By virtue of the complex life cycle of the blue crab, temperature and salinity are critical factors in the establishment of populations [C. sapidus. Global warming in recent decades, however, may have facilitated its settlement [An additional potential explanation for the low population-specific connectivity of ulations . The migulations . After mulations . Deviatittlement ,65.C. sapidus may represent a further factor driving genetic differentiation in the Mediterranean Sea, as brachyuran larvae can actively choose suitable habitats, e.g., by tidal vertical migration [C. sapidus [The larval behavior of igration , and bluigration ,71. Acco sapidus ,70,72.C. sapidus in the Mediterranean Sea. Further sampling in the native region will most likely report (more frequently) the haplotypes predominantly found throughout the Mediterranean Sea. The beneficial effect of including longer DNA regions, as applied in this study, became clear in the haplotype network in For further research, it will be essential to increase the number of samples in order to supplement the results of our phylogeographic assessment of Callinectes sapidus in the Mediterranean Sea, it will be useful to include populations from both sides of potential barriers to gene flow. This way, the influence of hydrodynamic patterns can be directly examined, and other feasible environmental factors can be excluded. Moreover, it would be interesting to draw a comparison among individuals from the Black Sea and the Mediterranean Sea, as only a few samples from Romania could be included in this study. Another factor that should be of importance for further research is the migration behavior of C. sapidus. Much is known about migration in the native area of the blue crab, but this knowledge cannot be extrapolated to the Mediterranean Sea without its corresponding verification. It is uncertain whether the life cycle and migration patterns of this species are comparable in the Mediterranean Sea. Since the life cycle is critical to the distribution of this species, future research should focus on it. Analyses of gene flow among Mediterranean populations should be intensified, as this not only reveals information about genetic connectivity, but also enables predictions of the expected speed of further spreading and possible damages caused by this highly invasive species.To advance our knowledge of the ecology of Callinectes sapidus. In contrast, a very different population genetic structure becomes apparent in the Mediterranean Sea: Extremely low genetic variability was recorded, probably due to a founder effect, and there is evidence of high genetic differentiation as a consequence of restricted gene flow. The ancestors of the European populations can be traced back to the Atlantic coast of North America. This study represents the first larger-scale assessment of the genetic diversity and reconstruction of the invasion events of C. sapidus in the Mediterranean Sea. Since invasive species are known to endanger native biodiversity by unbalancing the stability of ecosystems, and C. sapidus is a highly successful invader, further research in this field is essential for considering and developing appropriate conservation measures.The present study confirms a high level of genetic diversity with extensive gene flow, but three clearly discernible genetic lineages, within the native area of


Melia azedarach L.) are important for clarifying patterns in the population differentiation of this species across its natural range. M. azedarach is an economically important timber species, and its phenotype is highly variable across its range in China. Here, we collected M. azedarach seeds from 31 populations across its range and conducted a common garden experiment. We studied patterns of genetic differentiation among populations using molecular markers (simple sequence repeats) and data on phenotypic variation in six traits collected over five years. Our sampled populations could be subdivided into two groups based on genetic analyses, as well as patterns of isolation by distance and isolation by environment. Significant differentiation in growth traits was observed among provenances and families within provenances. Geographic distance was significantly correlated with the quantitative genetic differentiation (QST) in height (HEIT) and crown breadth. Climate factors were significantly correlated with the QST for each trait. A total of 23 climatic factors were examined. There was a significant effect of temperature on all traits, and minimum relative humidity had a significant effect on the survival rate over four years. By comparing the neutral genetic differentiation (FST) with the QST, the mode of selection acting on survival rate varied, whereas HEIT and the straightness of the main trunk were subject to the same mode of selection. The variation in survival rate was consistent with the variation in genetic differentiation among populations, which was indicative of local adaptation. Overall, our findings provide new insights into the responses of the phenological traits of M. azedarach to changes in the climate conditions of China.Studies of local adaptation in populations of chinaberry ( Melia Linnaeus (Meliaceae: Melioideae: Melieae) are deciduous trees or shrubs that occur in tropical and subtropical areas of the eastern hemisphere, including south of the Yellow River in China. The genus Melia has been proposed to comprise either one (M. azedarach Linn.) or three  species [Melia species can grow rapidly, and they are widely grown in China, especially M. azedarach, because of the mechanical properties of their wood, which makes them resistant to insects, pathogens, and corrosion [Melia species are also often used as medicinal plants for the treatment of various diseases, including diarrhea, diabetes, rheumatic diseases, and hypertension [M. azedarach and M. toosendan [Melia might provide useful future medicines in light of their diverse medicinal properties.Members of the genus  species ,2,3,4, aorrosion . Melia srtension . Severaloosendan ,7. PlantMelia species, such as the genes underlying differences in phytochemicals and the phylogenetic relationships among species, have not been thoroughly explored. This deficiency in our knowledge of the features delimiting these species affects the efficiency of genetic breeding programs, as well as the ability of Melia species to be used as medicinal plants. Morphological differences among Melia species are subtle. M. azedarach has the following distinguishing features: 3–6-loculed ovaries, small fruits less than 2 cm in length, leaflets with blunt teeth, and inflorescences as long as the leaves. M. toosendan has the following distinguishing features: 6–8-loculed ovaries, large fruits approximately 3 cm in length, leaflets with indistinct blunt teeth on the entire margin, and inflorescences half as long as the leaves. M. dubia has the following distinguishing features: petals pilose on both sides, elliptic drupes, and distribution restricted to south of the Five Ridges. M. toosendan is often considered a synonym of M. azedarach, and it has been infrequently documented in China [M. azedarach and M. toosendan overlap; they also show overlap in their flowering time (April to May for M. azedarach vs. March to April for M. toosendan). These species were likely generated by a sympatric speciation event, and they might naturally hybridize given that their flowers are diecious. Populations of the genus Melia in China thus represent a M. azedarach species complex; M. azedarach is considered the model species of the genus Melia [The features often used to distinguish in China ,4. The gus Melia .FST) and quantitative genetic differentiation (QST); genome scans can be used to identify genes involved in local adaptation, and genomic regions under selection can be identified in populations via high-density genetic markers [Local adaptation occurs when the mean fitness of a population is greater in its native habitat than in foreign habitats ,9,10. Lo markers ,15,16. L markers ,18,19. G markers ,21.Platycladus orientalis [Populus fremontii [Populus trichocarpa [Eucalyptus dunnii [Pinus caribaea [M. azedarach complex have focused on estimating heritability and predicting genetic gain to aid breeding programs [M. azedarach complex, as well as the role that lineage sorting has played in mediating local adaptation, has not yet been clarified. Here, we used provenance trials over five years to determine the role that selection has played in driving differentiation among populations of the M. azedarach complex. The results of this analysis provide key information that will aid forest breeding programs.The provenance trial approach is generally used to (i) characterize variation in quantitative traits among populations, (ii) determine progeny performance, and (iii) estimate genetic parameters . This apientalis , Populusremontii , Populuschocarpa , Eucalyps dunnii , and Pincaribaea . Provenacaribaea ,29,30,31caribaea ,33. Prevprograms ,35,36. HM. azedarach complex.Simple sequence repeat (SSR) markers are generally considered selectively neutral, and an analysis of SSRs can provide information complementary to data on adaptive molecular variation among populations . SpecifiFst)  and thatt) [Qst)  can be uM. azedarach populations according to analyses of phylogenetic relationships and population structure derived from molecular markers, and (ii) whether ecological adaptation plays a role in species differentiation through provenance trials. The results of these analyses will provide new insights into the role of natural selection in shaping patterns of differentiation among M. azedarach populations.The aims of this study were to determine (i) whether there is local adaptation among M. azedarach complex  per block in 3 m intervals, with a spacing of 1.5 m between plots. A total of 11,800 trees were planted on 1 May 2014.Leaf samples were obtained from 31 populations  and storM. azedarach complex . The reactions were conducted in an Eastwin Thermal Cycler  with the following thermal cycling conditions: 4 min at 94 °C; 21 cycles of 94 °C, annealing at 56 to 60 °C for 30 s, with the annealing temperature decreased by 0.5 °C in each cycle, and an extension at 72 °C for 1 min; 25 cycles of 94 °C for 30 s, annealing at 52 to 62 °C for 30 s, with the annealing temperature decreased by 0.5 °C each cycle, and an extension at 72 °C for 1 min; and a final extension for 10 min. The samples were then stored at 4 °C for genotyping. Polymorphic bands of SSR markers were detected using silver staining methods via 6% denaturing polypropylene gel electrophoresis [A total of 15 SSR markers were screened from tests of 135 primer pairs for the phoresis .M. azedarach for five consecutive years from 2015 to 2019: maximum stem height (HEIT), diameter at breast (1.3 m) height (DBH), the ground diameter in the first year (GBH), and the crown breadth (CRB). Measurements were also taken on the straightness of the main trunk (SMT), the number of branches (NOB), and the clear bole height (CBH) in 2016. Measurements of the survival rate (SR) were taken every year.We measured the following growth traits of ith measurement, with i = 1, 2, 3, 4, and 5 corresponding to measurements taken in 2015, 2016, 2017, 2018, and 2019, respectively. Other traits were referred to using a similar notation. A total of 30 traits were measured for five consecutive years  at the ve years .ijklY is the lth observation in the kth family of the jth provenance in the ith block, μ is the overall mean, iB is the fixed effect of the ith block , jP is the random effect of the jth provenance , jFi). These monthly climate data were collected from 22 weather stations in China from 1951 to 2012, and the means of each climatic factor were calculated , Mantel tests, and allele frequency estimates were obtained using GenAlEx v. 6.502 [FST were estimated at multiple loci using Genepop v4.7 [A micro-checker was used to detect null alleles for all the genotypes obtained from 15 SSR primer pairs . Analysev. 6.502 . Linkagepop v4.7 .http://taylor0.biology.ucla.edu/structureHarvester/, accessed on 5 December 2015), [Genetic relationships among populations were inferred using Nei’s genetic distance  and the r 2015), ) was useL) formula based on the longitude, latitude, and elevation:i = 1, 2), respectively, and R is the radius of the Earth. Regression analysis [R scripts.To evaluate the relative importance of IBD, the geographic distance between populations was computed using the spherical distance , [QST and correct for variable sample sizes [QST and FST were compared against the simulated expected distribution under a neutral hypothesis. Significant differences indicated the presence of natural selection [Differences between l 2019), ) to assel 2019),  was usedle sizes . In thiselection .FIS) were generally negative at individual loci, and the observed heterozygosity was not greater than the expected values under a HWE.Null alleles were absent at all 15 SSR loci in the 31 populations according to the micro-checker analysis. A total of 110 of the 465 alleles (23.65%) were not in a Hardy–Weinberg equilibrium (HWE) after a Bonferroni correction (α = 0.05/465 = 0.00011) . The inbI) was highest (1.81 ± 0.46) in Ceheng, Guizhou province, and I was lowest (1.46 ± 0.43) in Wuzhishan, Hainan province; the average value of I was 1.69 ± 0.39. The number of observed alleles ranged from 6.00 ± 2.93  to 8.60 ± 3.44 , and the average number of observed alleles was 7.27 ± 2.46. The number of effective alleles ranged from 4.09 ± 1.86 to 5.78 ± 2.62, and the average number of effective alleles was 5.05 ± 1.85. The mean expected heterozygosity (He) ranged from 0.74 ± 0.11  to 0.83 ± 0.06 , and the average He was 0.80 ± 0.08. The He in each population was greater than the average value of Nei’s gene diversity.The average polymorphic information content (PIC) was approximately 73.9%; the highest PIC value was observed in Liuyang, Hunan province (77.3%) and the lowest PIC value was observed in Wuzhishan, Hainan province (66.6%) . Shannonp < 0.001; GST values ranged from 0.0327 at the SSR120 locus to 0.1281 at the SSR117 locus. Significant relationships between the inverse number of migrants between populations inferred from GST/(1 − GST) and the logarithm of the geographic distance were observed for the loci SSR54, SSR74, SSR111, SSR117, and SSR123  values ranged from 0.034 to 0.242, and the natural logarithm of the geographic distance ranged from 10.28 to 14.51. Mantel’s test based on multilocus FST/(1 − FST) and geographic distance matrices revealed weak IBD effects at multiple loci , which indicated that the 31 populations could be divided into two groups  to 1.2996 (525–1060), and the mean was 0.5684 ± 0.1575. A consensus tree of genetic relationships revealed two distinct groups , which cp < 0.0001). Significant variation was observed in 29 traits among families within provenances (p < 0.0001); however, the p-value for CBH5 was only below 0.01. The significant variation observed in all 30 traits indicated that these populations were highly differentiated.Two-factor analyses of variance of the provenances and families within provenances were conducted for each trait in each year of the provenance trials . Highly QST matrix was computed for the 30 traits across the five years of the provenance trials , the correlation coefficients of the four crown traits ranged from −0.373 to −0.157 (p < 0.0171), and the correlation coefficients of the three DBH traits and three SR traits ranged from −0.183 to 0.0210 (0.0272 < p < 0.001). These findings indicated that the QST matrices of the HEIT, CRB, and SR were affected by geographic distance in five, four, and three of the years, respectively  (p < 0.01 in more than four years). The GBH/DBH was most strongly affected by the wind direction with the maximum wind speed . The NOB/CBH was significantly affected by the extreme minimum temperature, average temperature, average vapor pressure, and mean maximum and minimum temperatures. The SMT was most strongly affected by the wind direction with the maximum wind speed (p < 0.05 in four years), average vapor pressure (p < 0.001 in three years), and average temperature (p < 0.01 in three years). The CRB was affected by the extreme maximum temperature and average station pressure in four years (p < 0.05). SR was most strongly affected by the minimum relative humidity in four years (p < 0.05); it was also affected by mean temperature anomalies in four years (p < 0.05). Temperature had a significant effect on all the traits and was thus the main cause of the differentiation in phenotypic traits.The environmental factors were mostly negatively correlated with the < 0.001) . The HEIQST value in the second year was 0.508, which was significantly lower than that of the other years (0.732–0.743); this indicated that the pattern of local adaptation in the second year was different from that in the other years  across the five years of the study. The mean er years a. Three er years b. None oQST and FST significantly differed for the maximum stem height, the straightness of the main trunk, and the survival rate . The QST value of SMT 6 was −0.0725 lower than the FST (p = 0.0072). The QST values of SR 5, 6, 7, and 8 were 0.1047, 0.1016, 0.1254, and 0.1235 higher than the FST values . The QST values of growth traits were generally lower than the FST values, which indicated that the phenotypic differentiation was driven by uniform selection. The QST value for the survival rate was higher than the FST value, which indicated divergent selection; this finding is consistent with the relationships among the populations inferred from the SSR data.val rate . The QSTof M. azedarach populations in Yunnan, Guizhou, Sichuan, and Gansu (Group I). The seedlings from southern Guizhou and northern Guangxi were the tallest and had the highest DBH and survival rates [M. azedarach provenances collected from 17 provinces revealed that the geographic variation in the stones and seeds was affected by both longitude and latitude; however, the geographic variation was more pronounced with latitude than with longitude [M. azedarach. Below, we provide a more detailed discussion of the main findings.We obtained strong evidence for the local adaptation al rates . The famal rates . A sharpongitude . These fGST/(1 − GST) for five loci and geographic distance. Patterns in the GST and FST revealed a significant but weak IBD effect . A sharp decrease in seedling survivorship to 54.6% was observed in the second year, and the mean QST value was 0.508 in this year. This phenomenon has also been appeared in another trial [Significant differences were detected in six growth traits in each of the five years according to an analysis of variance, which indicated substantial differentiation among populations. The er trial . FollowiM. azedarach in China has been divided into 11 phenological areas [M. azedarach, such as the timing of various developmental stages, flowering, and fruiting, ranges from August in Bogor to September in Gambung, West Java [M. azedarach are indicative of local adaptation.According to twelve phenological indexes and three geographic factors, the distribution of al areas . To facial areas . The floest Java . All theM. azedarach, are consistent with local adaptation in this species. Climate is the most important factor shaping the patterns of population differentiation, and the temperature and minimum relative humidity play the most important roles in shaping patterns of local adaptation.The patterns of genetic differentiation and growth trait differentiation, as well as variation in the phenology of QST. The QST matrices of 30 traits significantly differed among the 22 provenances in a half-sib experiment (p < 0.0001). High sample sizes enhanced the accuracy of the QST estimates [QST values to generally be significantly lower than the FST values, especially for the HEIT and SMT, which indicates uniform selection. This uniform selection on growth traits indicates the importance of rapid growth as a survival strategy in chinaberry, which is a pioneer tree species in forest ecosystems.We conducted a common garden experiment with a randomized block design, and a total of 11,055 individuals from all populations were used to estimate the stimates . The trestimates ; Table 4M. azedarach revealed IBD and isolation by environment, and provided insights into the genetic relationships and genetic structure (Melia have been dated to the middle Miocene (20 MYA) of central Washington [M. azedarach has been characterized in northern latitudes (18–38°) and eastern longitudes (100–122°) in China [M. toosedan and putative M. azedarach were inferred by constructing a tree with 10,000 bootstrap replicates. The QST–FST distribution for each traittreatment combination was used to infer the empirical p-values associated with our point estimates of QST–FST. The QST of the SR was generally significantly higher than the FST at various latitudes, suggesting that natural selection has played a comparatively larger role in shaping the observed variation compared with genetic drift. The minimum relative humidity, average temperature, and geographic distance were the main environmental factors shaping local adaptation in M. azedarach.A population genetic differentiation analysis of tructure . Fossil shington , the Midshington , the Uppshington , and theshington . Geograpin China ,67. The M. azedarach. The QST of traits was calculated using a common garden experiment with a half-sib design. The QST was significantly correlated with climate and geographic factors in all years. An analysis of the SSRs revealed significant population genetic differentiation. The survival rate was significantly affected by the population genetic differentiation, and patterns of local adaptation were affected by the minimum relative humidity, average temperature, and geographic distance. Generally, QST–FST comparisons are effective for clarifying patterns of local adaptation in M. azedarach.Growth traits significantly varied with latitude and longitude in


Rickettsia contains the lineages spotted fever group (SFG), typhus group (TG), and transitional group (TRG). The spotted fever group Rickettsia (SFGR) is transmitted by ticks. The tick species Dermacentor nuttalli is considered the main vector carrying SFGR in Inner Mongolia. Studying the genetic diversity and population structure of Rickettsia is essential for developing effective control strategies and predicting evolutionary trends of Rickettsia.The genus D. nuttalli in the Inner Mongolia Autonomous Region, detected the percentage of Rickettsia-positive specimens, and characterized the haplotypes. From the Rickettsia-positive ticks, the gltA and ompA genes were extracted, amplified, and sequenced.In 2019 we collected 408 gltA gene and 22 haplotypes of the ompA gene were obtained. The phylogenetic analysis showed that the haplotypes G1–G7 and G9 of the gltA gene cluster with Rickettsia raoultii, while G8 and G10 cluster with Rickettsia sibirica. Haplotypes O1–O15, O18 and O20–O22 of the ompA gene cluster with R. raoultii, while O16 and O19 cluster with R. sibirica. The average haplotype diversity was 0.3 for gltA and 0.7 for ompA. The average nucleotide diversity was greater than 0.05. Neutrality tests were nonsignificant for Tajima’s D results and Fu’s Fs results. The fixation index values (FST) showed that the degree of genetic differentiation between most sampled populations was small (FST < 0.05), whereas some populations showed a medium (FST > 0.05) or large (FST > 0.15) degree of differentiation. Analysis of molecular variance (AMOVA) revealed that the variation within populations was greater than that between populations. The mismatch analysis of Rickettsia showed double peaks.Ten haplotypes of the Rickettsia spp. (R. raoultii and R. sibirica). The high genetic disparity of Rickettsia allows for easy adaption to different environments. Genetic differentiation between populations is small, and Rickettsia populations do not show a geographically differentiated structure. The high rates of retention and infection of Rickettsia in D. nuttalli together with the animal husbandry exchange in Inner Mongolia gradually led to the harmonization of genetic characteristics of Rickettsia across various regions. Overall, the significant genetic diversity and geographical structure of Rickettsia in D. nuttalli are critical for SFGR control.We found two The online version contains supplementary material available at 10.1186/s13071-022-05387-4. Rickettsia belong to three monophyletic groups: spotted fever group (SFG), typhus group (TG), and transitional group (TRG). SFG is transmitted by ticks [Dermacentor nuttalli is the dominant tick species and is probably the main vector carrying spotted fever group Rickettsia (SFGR) in Inner Mongolia [Rickettsia heilongjiangensis, Rickettsia raoultii, Rickettsia slovaca, Rickettsia sibirica, Rickettsia mongolotimonae, Rickettsia monacensis, and Candidatus Rickettsia hebeiii and Candidatus Rickettsia jingxinensis have been detected in ticks. Furthermore, Rickettsia raoultii, Rickettsia heilongjiangensis, and R. sibirica have been reported in emerging tick-borne diseases of humans. In recent years, the threat that SFGR poses to public health in China has been magnified by the increasing number of potentially novel SFGR detected in ticks [Rickettsiosis is an important zoonosis, which brings serious harm to the health of humans and animals , 2. The by ticks , 4, whilby ticks . The vasMongolia –8. SFGR in ticks –11.Rickettsia species. 16S rRNA can accurately identify a specimen as belonging to Rickettsia. However, it is difficult to distinguish the species, because the 16S rRNA sequence is highly conserved in almost all prokaryotes. The gltA and ompA genes are used for species identification in Rickettsia [gltA gene encodes a citrate synthase, the sequence of which allows for highly reliable identification of the evolutionary distances among Rickettsia. The ompA gene is an outer membrane protein gene. It is considered the “gold standard” for species identification in Rickettsia, owing to the highly specific 5′ end [Molecular biological techniques allow for the identification of ckettsia –14. The c 5′ end .D. nuttalli, allowing for its existence in different geographical environments [Rickettsia in D. nuttalli are scarce. Therefore, in our study, we included a high number of tick specimens, and explored the percentage of Rickettsia-positive samples and the genotype distribution to identify the genetic diversity of Rickettsia. Studying the genetic diversity of Rickettsia is essential for developing effective control strategies and predicting pathogen evolutionary trends.Previous studies found high genetic disparity in ronments . HoweverIn this study, a total of 408 ticks were collected from 1078 sheep at four sampling spots in Inner Mongolia, China: Chengchuan Town, early Banner of Etoke Banner Ordos (EEDS); Siziwang Banner, Hohhot (SZWQ); the Bayan WenduSumu area Arukorqin Banner Chifeng (CF); and Xinbarhu right Banner, Hulun Buir (HLBE). The locations of the sampling areas are shown in Additional file D. nuttalli through morphological characteristics [D. nuttalli samples were individually extracted using a TIANamp Tissue and Blood Kit  [Rickettsia DNA, the gltA and ompA genes were amplified by polymerase chain reaction (PCR), following the protocols described by Bermúdez et al. [gltA and ompA genes of Rickettsia from D. nuttalli were synthesized by Shanghai Sangon. DNA was amplified using a system of 40 μl, each including Taq PCR Master Mix , 2 μl of DNA from each sample, and 1 μl of each reverse and forward primer, and filled to volume with double-distilled water. The PCR primers, amplification sizes (base pairs), and annealing temperatures are listed in Additional file Ticks were identified as eristics . All D. , China) . For ampz et al. . Specifihttps://submit.ncbi.nlm.nih.gov/about/bankit/), with accession numbers OK638141-OK638150, OL304270-OL304271, OL348251-OL348270. Multiple sequence alignment and sequence similarity calculations were done using DNAMAN 7.0. Phylogenetic trees were constructed with the neighbor-joining algorithm using MEGA 7 with 1000 bootstrap replicates to assess tree stability [Rickettsia populations was estimated by analysis of molecular variance (AMOVA) and FST values [Rickettsia varied among the four sampling localities in Inner Mongolia. Neutral tests were analyzed using Tajima’s D and Fu’s Fs tests using Arlequin 3.5 and DNAsp 5.10. PopART  version 1.7 software was used to evaluate the relationships between haplotypes by constructing TCS haplotype network maps.Sequences were edited in SeqMan 7.1 and identified by comparative analysis with sequences deposited in GenBank, using the National Center for Biotechnology Information (NCBI) BLAST search engine. Sequencing data are available at the NCBI Sequence Read Archive , EEDS (n = 85), SZWQ (n = 30), and HLBE (n = 74) .We collected and tested a total of 408 nuttalli . Across gltA sequences and 22 haplotypes of ompA sequences. The sequences had the highest similarity with R. raoultii and R. sibirica, as registered in GenBank, with 98% and 99% identity, respectively. In the gltA phylogenetic trees, haplotypes G1–G7 and G9 were clustered with R. raoultii, while G8 and G10 were clustered with R. sibirica. Furthermore, we found high similarity with Candidatus Rickettsia uralica, with 98% identity, and distinctly lower similarity in Rickettsia asembonensis. In the ompA phylogenetic trees, haplotypes O1–O15, O18, and O20–O22 clustered with R. raoultii, while O16 and O19 clustered with R. sibirica. The highest similarity was found with Candidatus R. uralica, with 98% identity, and substantially lower similarity with Rickettsia montana. The phylogenetic trees for both genes showed that the haplotypes of Rickettsia clustered into one branch with the ingroup, which contained the genotypes of R. raoultii and R. sibirica . Numerically, the most common haplotype was G1, with 167 sequences  . Neutrality analysis revealed nonsignificant values of Tajima's D and Fu's Fs results, confirming that the population had not experienced recent expansion . Numerically, the most common haplotypes were O1, O2, and O3, with 170 sequences  . Neutrality results were the same as those for gltA, indicating that the population had not experienced expansion recently (Table FST value between CF and HLBE was greater than 0.25, indicating that there was high genetic differentiation between populations. The FST values between HLBE, SZWQ, and EEDS were all greater than 0.05, confirming a moderate genetic differentiation between populations, with a small extent of gene flow. The FST values between the other regions were less than 0.05, confirming a very small genetic differentiation between these populations, likely on account of high gene flow (Additional file gltA results (Additional file In the Rickettsia infection, it is of utmost importance to continuously monitor the emergence of new species, study the population structure, and investigate the genetic diversity of the pathogen. In this study, two Rickettsia species were identified in Inner Mongolia, R. raoultii and R. sibirica, both belonging to the SFGR. In recent years, human infection with R. raoultii has led to tick-borne lymphadenitis in many countries [R. raoultii.For planning effective control measures against ountries –30. To sgltA and ompA genes of Rickettsia from four localities of Inner Mongolia. The aim of the investigation was to find new possibilities for controlling the transmission and reproduction of Rickettsia. Our results showed that the gltA and ompA genes have shared haplotypes in four regions. These are dominant haplotypes characterized as primitive and stable. Shared haplotypes indicate that the degree of genetic communication is high in Rickettsia populations. Furthermore, the lowest genetic diversity was found in HLBE in the gltA gene. The diversity of the ompA was higher in HLBE. The different results for the two genes indicate that the genetic diversity of species is affected by many factors, such as geographical distribution and population size [Rickettsia is in accord with different environments. The high rate of genetic communication in Rickettsia populations not only leads to a higher positive rate of Rickettsia in Inner Mongolia, but also increases the probability of Rickettsia transmission among and between humans and livestock.This study analyzed the genetic diversity of a region within ion size . Differeion size . OverallFST values revealed that the degree of genetic differentiation was highest between HLBE and the other three regions. Obviously, HLBE is not only a beneficial habitat for ticks but also an important pastoral region in Inner Mongolia [Rickettsia-positive rate and the highest genetic differentiation in Rickettsia populations in Inner Mongolia.Regarding the four geographical populations investigated, there is genetic differentiation between populations from AMOVA results. Further studies on Mongolia . It alsoD and Fu’s Fs are used to test the historical dynamics of populations. If both are significantly negative, it indicates that the D. nuttalli population has historically experienced rapid population expansion. In this study, we did not find evidence of a recent rapid expansion of the population. Furthermore, the mismatch analysis for the two genes gltA and ompA showed genetic differentiation with no population expansion. The haplotypes of Rickettsia did not branch in relation to the clustering of geographical regions, indicating that the Rickettsia populations did not form a geographical differentiation structure. Therefore, in recent years, Rickettsia populations have not experienced excessive outbreaks, and the phenomenon of high genetic diversity may be a historical effect.The neutrality test values of Tajima’s Rickettsia can be transmitted either vertically or horizontally, the high carry and infection rates of Rickettsia in D. nuttalli, together with the animal husbandry exchange in Inner Mongolia, gradually led to the harmonization of genetic characteristics of Rickettsia across various regions. The National Center for Disease Control and Prevention should strengthen the monitoring of tick-borne Rickettsia in Inner Mongolia and develop effective control measures.Since gltA and ompA genes were used to study the genetic diversity of Rickettsia from four geographical localities in Inner Mongolia. This study provides a reference for detecting new genotypes and complex genetic structures of Rickettsia populations. It also indicates that although Rickettsia species in Inner Mongolia have adapted to different environments, effective control measures of tick-borne Rickettsia transmission is crucial, especially in the HLBE region.The Additional file 1: Table S1. Sample information of D. nuttalli populations. Table S2. Primers of PCR and amplification conditions. Table S3 Haplotype distribution of Rickettsia based on the gltA gene. Table S4.FST values among different groups of Rickettsia based on the gltA gene. Table S5. AMOVA of gltA gene of Rickettsia population. Table S6 Haplotype distribution of Rickettsia based on the ompA gene. Table S7FST values among different groups of Rickettsia based on the ompA gene. Table S8 AMOVA of the ompA gene of the Rickettsia population.