Spatial arrangement of distinct Amazonian environments through time and its effect on specialized biota remain poorly known, fueling long-lasting debates about drivers of biotic diversification. We address the late Quaternary sediment deposition that assembled the world's largest seasonally flooded ecosystems. Genome sequencing was used to reconstruct the demographic history of bird species specialized in either early successional vegetation or mature floodplain forests. Sediment deposition that built seasonally flooded habitats accelerated throughout the Holocene  under sea level highstand and intensification of the South American Monsoon, at the same time as global increases in atmospheric methane concentration. Bird populations adapted to seasonally flooded habitats expanded due to enlargement of Amazonian river floodplains and archipelagos. Our findings suggest that the diversification of the biota specialized in seasonally flooded habitats is coupled to sedimentary budget changes of large rivers, which rely on combined effects of sea level and rainfall variations. This study found that millennial periods of higher rainfall combined with rising sea level enhanced sediment accumulation in Amazonian rivers valleys. This fuelled synchronous expansion of vegetation adapted to seasonally flooded substrates and its specialized bird populations, showing how global climate changes can affect specific Amazonian species. The relationship between landscape evolution and Neotropical species diversification has been intensely debated during the last decades2. Time-calibrated phylogenetic data show that most Amazonian extant species emerged during the late Pliocene and Pleistocene (last ~5 Ma)5. However, the mechanisms through which populations respond to changes in the physical environment are poorly constrained in time and space. Previous studies that interpret biotic diversification driven by landscape changes consider geological or climatic processes that operate in periods of million to thousand years such as mountain building since the Miocene6, development of large rivers during the Pliocene and Pleistocene7, or climate-forced shifts in upland forests distributions during the Pleistocene8. Often, lack of congruent spatial and, especially, temporal phylogenetic patterns have led to the alternative interpretation that landscape change had a minor role in Amazonian diversification, with most diversification driven by long-distance dispersal or intrinsic biotic processes9. However, both views are limited by the scarcity of chronological information (i) to constrain the presumed environmental changes that split populations or (ii) to support landscape stability during the diversification of specific taxa. Thus, the main challenge to test whether environmental changes drove biotic diversification is reconstructing the landscape and biotic histories under the same spatiotemporal framework.Amazonia hosts the largest biodiversity on Earth11, where the South American Monsoon System (SAMS) and the continental-scale river system determine the distribution of two end-member types of environments:12 non-flooded uplands (terra firme) and seasonally flooded habitats (várzea and igapó). Sediments accumulated within valleys of large Amazonian rivers shape substrates that are colonized by vegetation adapted to seasonal flooding12, originating the world’s largest flooded ecosystem that covers an area of 8.4 × 105 km2 13. The Amazonian seasonally flooded habitats sustain a rich and specialized biota13. Among the 4962 Amazonian tree species, 2166 species occur in seasonally flooded habitats, and up to 30% may be endemic to these habitats16. Besides, more than 150 species of Amazonian nonaquatic birds are restricted to or highly dependent on seasonally flooded habitats, including several species specialized in river islands20. The distribution and diversification of organisms adapted to seasonally flooded ecosystems are possibly linked to the current and past availability and connectivity of floodplains and islands built by sediment deposition within major river valleys21. The dynamics of sediment transport and accumulation that create or erode alluvial plains drive the expansion (or fragmentation) of Amazonian flooded substrates in a thousand-year timescale22. Hence, the spatial distribution and population dynamics of species adapted to seasonally flooded habitats are presumably dependent on the sedimentary budget of Amazonian rivers, but data necessary to test the synchronicity between historical environmental changes and the biotic response are absent so far.Amazonia is a mosaic of landscapes and ecosystemsn = 93) and radiocarbon (n = 23) ages that were combined with ages (n = 53) compiled from the literature (Supplementary Data várzea) as well as in major blackwater and clearwater tributaries (igapó). This includes the formation chronology of the Anavilhanas archipelago in the Negro River, and the Tabuleiro do Embaubal archipelago in the Xingu River, respectively the largest archipelagos in blackwater and clearwater tributaries of the Amazon River.Here, we determine the formation chronology of seasonally flooded habitats in lowland Amazonia Figs.  and 2 us23. Birds are the vertebrate group for which species limits and distributions are best known, and thus this group has frequently been used to infer biogeographic processes in Amazonia, where biodiversity patterns for many other animal groups are still poorly understood2. We reconstruct past demography for populations of five bird species specialized in early successional habitats, mainly in river islands, and four species specialized in floodplain forest environments  to the atmosphere25. Hence, tracking periods of expansion or retraction of the Amazonian floodplains allows the appraisal of potential connections between the sedimentary budget of large tropical rivers and global climate.In parallel, we reconstruct the demographic history of populations of birds specialized in seasonally flooded habitats in early (young islands and river banks) and late (mature floodplain forest) vegetation successional stages using reduced genome sequencing 26. In general terms, the sedimentary successions display marked fining-upward trends and are coarser-grained at the bar-heads. The typical succession representing the progressive conversion of migrating sand bars into stabilized marginal floodplains or islands covered by seasonally flooded vegetation can be described as follows:Seasonally flooded habitats within large Amazonian river valleys expand when sand bars are exposed and colonized by vegetation during periods of low-stage water level Fig. . Pioneer26. In bar-head areas, coarse sand beds mark the cross-strata foresets  around 21 ka, but with acceleration during the Holocene (last 11.7 ka) , fluvial deposits representing substrates colonized by seasonally flooded vegetation in the Solimões and Amazon Rivers also show depositional and colonization rates varying from centennial to millennial timescales.Sediment accumulation rates decrease from 10Cranioleuca vulpecula, Furnarius minor, Knipolegus orenocensis, Mazaria propinqua, and Stigmatura napensis) and four species specialized in floodplain forests 33. Isolation by distance (IBD) and population structure generating unequal gene flow among individuals are known to potentially mislead demographic inferences34. We show for all taxa studied here that regions of lower and higher migration differ from IBD expectations  as indicated by our geochronological dataset Fig. . Genomic ka as inF. minor. Furthermore, the statistical model comparisons performed using Demographic Inferences with Linked Selection (DILS35) recovered models of population expansion instead of retraction or stability, with high posterior probabilities for all taxa (>0.98) , which was followed by a slightly more recent expansion on C. vulpecula  dates to 30–20 ka ago , population stability is rejected, as the 95% confidence interval of the population size change parameter does not include 0 for all studied taxa, with the exception of 37. Although autogenic fluvial processes lead to heterogeneous filling of river valleys in decadal to secular timescales, as pointed out by the formation chronology of islands in the Xingu and Negro Rivers  of clearwater and blackwater tributaries of the Solimões-Amazon River. In these settings, flow expansion due to channel widening leads to decreasing water velocity and net sediment deposition. Indeed, the expansion of both archipelagos since 4 ka  compared to wide and long-lasting  mature seasonally flooded forests, implying a changing environment. Thus, species that occupy wide floodplains with mature forests at large rivers’ valleys may have sustained expansion or retraction through time, avoiding local extinctions and maintaining connectivity, because the development of continuous seasonally flooded substrates bounding river channels depends on the sediment accumulation-erosion balance operating at longer time-scales.Demographic growth observed in birds from floodplain forests during the last 200 ka Fig.  agrees w ka Fig. . However ka Fig. . This ma19, and genomic data suggest recent introgression between closely related populations in central Amazonia61. Evidence for distinct populations of island birds in the Negro and Solimões Rivers also indicates reduced connectivity across central Amazonia in the past62. This evidence, combined with our demographic results, points to a history of changing connectivity of seasonally flooded habitats in central Amazonia, suggesting that the current connectivity may have been recently attained. Space available for the development of floodplains can also increase with valley widening during phases of stable erosion base level, especially in areas such as western lowland Amazonia, where valleys are flanked by Pleistocene soft sedimentary terrains22. This condition would provide larger and more resilient floodplains in western than in central Amazonia, where river valleys are narrower due to the higher resistance of the rocky substrates63. Therefore, central Amazonia is susceptible to faster floodplain loss if the Solimões-Amazon River main stem shifts to an erosional regime.The connectivity of seasonally flooded habitats across the Amazon basin depends on the availability of floodplains along the main stem of the Solimões-Amazon River. However, bird community composition differs between eastern and western AmazoniaWe conclude that the coincidence between the strengthening of the SAMS and sea-level highstand promoted the last expansion of Amazonian flooded environments and their specialized bird populations, which responded differently depending on their habitat association. It is important to note that these last events of bird populations expansion that we characterize here were preceded by a long history of occupation of seasonally flooded habitats by these lineages, with the stem ages of the nine species studied here ranging from about 1 to 6 Ma (Supplementary Data 4) to the atmosphere. Most of the global CH4 budget variability during the Quaternary has been associated to variations in wetlands extent during glacial (wetlands decrease) and interglacial (wetlands increase) periods64. Superimposed on this long-term pattern, changes in the atmospheric CH4 levels follow the precession cycle 67. There is at present no consensus on whether this rise in CH4 concentration was anthropogenic, mainly linked to rice paddies in eastern Asia , or caused by changes in natural sources .The expansion or retraction of floodplains of large tropical rivers can also influence the atmospheric concentration of greenhouse gases since flooded environments are major sources of methane , the expansion of seasonally flooded habitats proposed in this work may have played an important role on global CH4 budgets. This scenario is consistent with model simulations69 and ice-core records71 that suggest southern tropical wetlands as the most likely source for the late Holocene CH4 upsurge. However, specific studies are needed to confidently test the connection between the expansion of Amazonian floodplains and global CH4 budgets.Our results show that the unexpected global CHnia Fig. . This re63 point out to a synchronous response of the lowland fluvial landscape in the millennial timescale. Notwithstanding these limitations, a similar pattern of late Pleistocene channel incision followed by Holocene expansion of floodplains was also documented in other large South American tropical rivers, such as the Cuiabá megafan draining the Pantanal wetland72 and the Paraná River73, where the SAMS also controls the hydroclimate.Despite our confidence in the timing of the expansion of seasonally flooded habitats across lowland Amazonia, we cannot exclude the possibility of a slight bias in the geochronological dataset assembled here. This is due to the different preservation potential of sediment bars. Stratigraphic preservation bias is also expressed by the decrease in sedimentation rates with increasing timespan  or polymineral aliquots (silt fraction). The preparation of quartz or polymineral concentrates for the determination of equivalent radiation doses included wet sieving to isolate the <63, 63–125, 125–180, or 180–250 µm grain size fractions  at densities of 2.75 and 2.62 g/cm3, respectively. The heavy liquid separation was not performed for samples dated using the fine silt fraction (4–11 µm). Quartz concentrates in the sand fraction  were submitted to HF 38% treatment for 40 min to etch the outer rind of grains damaged by alpha particles followed by another HCl treatment to eliminate eventually precipitated compounds and wet sieving to keep grains in the target grain size interval. Luminescence measurements for equivalent dose determination were carried out in two Risø TL/OSL DA-20 readers  equipped with built-in beta radiation sources (Sr90/Y90), with dose rates ranging from 0.075 to 0.112 Gy/s, blue and infrared LEDs for stimulation and Hoya U-340 filters for light detection in the ultraviolet band. For pure quartz aliquots (sand fraction), equivalent doses were estimated using the single-aliquot regenerative (SAR) dose protocol78. Some muddy samples (fine silt fraction) from riverbanks along the Solimões River did not allow the extraction of pure aliquots of quartz. Thus, luminescence dating of these samples was performed using polymineral aliquots (quartz and feldspar). Then, equivalent doses were estimated using the post-infrared blue stimulated luminescence signal79. This approach aimed to measure the OSL signal from quartz after depletion of the feldspar signal. Ages obtained through polymineral aliquots were cross-checked through comparison with ages of pure quartz aliquots from sandy layers occurring in the same profile. The protocols used for equivalent dose estimation are summarized in Supplementary Material  concentrations determined using gamma-ray spectrometry with a high purity germanium detector, with an energy resolution of 2.1 keV and relative efficiency of 55%, encased in an ultralow background shield (Canberra Instruments). Radionuclides concentrations were converted to dose rates using conversion factors81. The contribution of cosmic radiation to dose rate was calculated through sample depth, elevation, latitude, and longitude82. Besides the sediment burial ages obtained in this study, we compiled OSL and radiocarbon ages from the literature. Thus, our geochronological dataset to constrain sediment deposition in the floodplains and archipelagos of the Amazonian rivers include 93 OSL ages and 23 radiocarbon ages obtained in this study, and 53 OSL and radiocarbon ages from published works. Supplementary Data Sediment samples for OSL and radiocarbon dating were collected during field surveys performed between 2011 and 2015. Samples were retrieved during the low water season (September–November) in outcrops along channel margins, pits (0.5–1 m depth) or through coring (up to ~10 m depth) using a manual auger adapted to collect samples using opaque plastic liners. Samples were collected in terraces along channel margins or islands covered by 59. Sequences from each species were processed independently from raw reads to final UCE alignments through the Phyluce pipeline83. First, using the illumiprocessor function, raw reads were cleaned from adapter contamination. Second, a single sample with high amounts of reads was assembled into contigs using SPAdes84. Contigs were matched to the UCE probes sequences with phyluce_assembly_match_contigs_to_probes, and recovered contigs were used as a reference to all other samples. Afterward, each sample’s reads were mapped against reference alignments and phased using phyluce_snp_bwa_multiple_align and phyluce_snp_phase_uces, respectively85. Finally, all samples’ recovered sequences were aligned into separate UCEs sequences files with MAFFT86 using phyluce_align_seqcap_align and trimmed to improve alignment quality using phyluce_align_get_gblocks_trimmed_alignments_from_untrimmed. Samples with low coverage  were discarded and we selected only UCE alignments including all samples with phyluce_align_get_only_loci_with_min_taxa to be used in subsequent analyses.For each of the nine studied species, samples were selected aiming to cover most of their known geographic distribution, spanning seasonally flooded habitats throughout Amazonia  were recovered to add information from a distinct genomic source and provide additional information for time calibration of demographic reconstructions. The mitochondrial genome is usually recovered as a byproduct of UCE sequencing89. For each species, Euclidean genetic distances between samples were estimated from the SNPs data with ADEGENET’S dist.genpop function . The described distribution of a species was used as the distribution polygon, which was further edited in Qgis when necessary to include samples outside the polygon. Depending on the size and complexity of the species’ distribution polygon, from 500 to 700 demes were selected. We present a single run of 1 × 107 generations for each species, excluding the first 5 × 106 as burn-in. The convergence of the runs was visually assessed in the posterior probability trace plots. Additional tests for some of the studied species with longer chains and different numbers of demes were also run to confirm the consistency of the results.Since population structure and isolation by distance can mislead demographic analyses, three different methods were used to assure that demographic analyses were performed on the best population arrangement. To look for areas of higher or lower gene flow than expected under simple isolation by distance, we modeled the EEMS , and the best result was chosen by the smallest value of cross-entropy. The k-means classification in ADEGENET is applied with find.clusters function and infer the number of genetic clusters in our samples comparing the Bayesian Information Criterion of each classification. Both sNMF and k-means yielded similar results, suggesting K value of 1 population for all species except for K. orenocensis, for which both analyses indicate the existence of 2 distinct genetic groups  was used in demographic analyses.We used two different classification approaches to estimate the best population arrangement using sNMF and k-means, implemented through LEA and ADEGENET R packages, respectively93. We followed the approach suggested by Trucchi et al.94, where they show highly consistent results comparing datasets of 50 nuclear loci with 2, 3, and 4 to 6 SNPs per loci, but used loci with 4 to 6 SNPs for being more informative, and suggested a calibration strategy combining information from nuclear and mtDNA markers. We thus randomly sampled 50 UCE loci with at least four informative sites, plus the two mitochondrial loci for all individuals of each species94. Site models were inferred independently for each locus in jModeltest95. Site models and clocks were unlinked for all loci and the tree was linked only for the two mitochondrial loci. To avoid over-parameterization, strict clocks were used for estimating the rates. Tree prior for each locus was set as “Coalescent Bayesian Skyline” and ploidy was set as 0.5, 1.5, and 2 for mitochondrial, Z-linked, and autosomal loci respectively. To identify Z-linked UCEs, they were mapped to a complete Z chromosome of Zebra-finch downloaded from Genbank (Accession: CM020861) using Geneious. A normal distribution clock prior was used for mitochondrial markers to calibrate the demographic reconstructions, with initial and mean values set as 0.0105 and sigma parameter as 0.0034, encompassing the widely used rate of 2% substitution/site/million years for birds’ mtDNA96. For each UCE, a gamma clock prior was used with alpha set as 0.1256, beta as 1.0, offset as 1 × 10−5, and initial value as 0.0025. This setting centers the median, and therefore most of the estimates, around 0.0025 matching the proposed mean substitution rate for the genome of birds of 2.5 × 10−9 substitutions per site, per generation, and one year generation time for birds specialized in seasonally flooded Amazonian environments97. The populationMean.alltrees prior was set as normal with 1.0 as mean and 0.1 as Sigma, and “alltrees” operators were multiplied by the number of loci98. Finally, chain length was set as 5 × 108, storing every 5 × 104 for tracelog and 1 × 104 for EBSPlogger. For each demographic reconstruction, ESS values of parameters were checked on Tracer99. Following the tracer log, 3 to 5 independent runs were performed for each species and combined with logcombiner removing the first 10% as burnin. For all species, after combining the independent EBSP runs, most parameters reached very high ESS values (>1000). Although some analyses had low ESS values for individual parameters (<100), the observed consistency across different runs and acceptable values for the most important parameters support the convergence of the analyses.Demographic analyses were performed for each taxon independently with EBSP in BEAST 2.535. To keep most loci and considering the data were already filtered in Phyluce, in data filtering max_N_tolerated was set to 0.3, Lmin to 100 and nMin to the number of sequences per species. The same previously used mutation rate of 2.5 × 10−9 substitutions/site/generation with a one year generation time was used to calibrate the analyses. Minimum and maximum time of demographic change were set to 100 and 5 × 105 generations, respectively, and limits of population sizes were left as the default values of 100 for the minimum and 106 for the maximum. Time of demographic changes was assessed based both on the posterior and optimized posterior probabilities from the Neural Network algorithm.Two additional analyses were performed to further explore the demographic history of the studied species using a larger portion of the UCE dataset. Firstly, demographic models representing population expansion, stability or retraction were compared for each species using an Approximate Bayesian Computation Framework in DILSEcoevolity36. For that, we used the complete phased UCE dataset, concatenated in a single nexus file per species, as recommended36. In event_model_prior, a gamma_distribution with shape = 0.7 and scale = 8 was set for the concentration parameter of the Dirichlet process. For our data, this setting results in similar prior probabilities for most estimates of demographic changing events, reducing prior bias in model choice (Supplementary Fig. 5 years. For the Markov Chain Monte Carlos, a chain length of 15 × 105 steps sampling every 1000 samples was defined. Operator settings were left as default. An uninformative uniform prior was set for the population size, with mean, minimum and maximum values of 5 × 105, 1000 and 106, respectively. The same mutation rate of 2.5 × 10−9 substitutions/site/generation was used, with an uniform distribution and minimum and maximum values of 1.5 × 10−9 and 3.5 × 10−9. Three independent runs were performed and checked for convergence using Tracer.The second analysis aimed to test for shared responses to environmental changes, which would result in temporally congruent demographic changes. In this analysis, we used the full Bayesian model choice framework applied in Further information on research design is available in the Supplementary InformationPeer Review FileSupplementary Dataset 1Supplementary Dataset 2Supplementary Dataset 3Supplementary Dataset 4Reporting Summary


Coregonus clupeaformis) within Lake Michigan, USA. However, ambiguity in genetic stock assignments suggested those neutral microsatellite markers did not provide adequate power for delineating lake whitefish stocks in this system, prompting calls for a genomics approach to investigate stock structure. Here, we generated a dense genomic dataset to characterize population structure and investigate patterns of neutral and adaptive genetic diversity among lake whitefish populations in Lake Michigan. Using Rapture sequencing, we genotyped 829 individuals collected from 17 baseline populations at 197,588 SNP markers after quality filtering. Although the overall pattern of genetic structure was similar to the previous microsatellite study, our genomic data provided several novel insights. Our results indicated a large genetic break between the northwestern and eastern sides of Lake Michigan, and we found a much greater level of population structure on the eastern side compared to the northwestern side. Collectively, we observed five genomic islands of adaptive divergence on five different chromosomes. Each island displayed a different pattern of population structure, suggesting that combinations of genotypes at these adaptive regions are facilitating local adaptation to spatially heterogenous selection pressures. Additionally, we identified a large linkage disequilibrium block of ~8.5 Mb on chromosome 20 that is suggestive of a putative inversion but with a low frequency of the minor haplotype. Our study provides a comprehensive assessment of population structure and adaptive variation that can help inform the management of Lake Michigan's lake whitefish fishery and highlights the utility of incorporating adaptive loci into fisheries management.Understanding patterns of genetic structure and adaptive variation in natural populations is crucial for informing conservation and management. Past genetic research using 11 microsatellite loci identified six genetic stocks of lake whitefish ( HistoriExamination of genome‐wide variation among populations indicates that genomic differentiation can be relatively uniform across the genome or localized in specific genomic regions, commonly referred to as genomic islands of differentiation  in the Laurentian Great Lakes of North America are an excellent model for investigating adaptive differentiation as they spawn in heterogenous habitats, ranging from eutrophic tributaries to oligotrophic rocky reefs, and at least some lake whitefish exhibit spawning site fidelity  sequencing . We then used HDPlot . We removed loci with mapping quality less than 30 and loci that were mapped to multiple alignment positions. Additionally, only one locus every ~20 Kb was retained. Bait development (80 nt baits with 2× tiling density) was conducted by Arbor Biosciences  and only the baits closest to the 5′ ends for each locus were kept.DNA was isolated from fin clip samples preserved in >95% ethanol using Qiagen DNeasy Blood and Tissue Kits. DNA extracts were quantified and normalized to 20 ng/μl. A single RAD library was prepared using the restriction enzyme 2.2Using the rapture panel that we developed, we sequenced 951 baseline samples collected during the spawning seasons from 2014–2019 from 19 known spawning locations in Lake Michigan Figure , Table 1https://arborbiosci.com/mybaits‐manual/) and Euclide et al. . Adaptor sequences were clipped from reads using trimmomatic v0.39 . Called SNPs were filtered with VCFtools to remove SNPs with a minor allele count of less than 3 and SNPs genotyped in fewer than 70% of individuals. Individuals missing more than 50% of retained SNPs were also removed. Putative sample duplicates were identified by calculating relatedness between samples using VCFtools (‐‐relatedness). We estimated relatedness only using loci with minor allele frequency (MAF) ≥ 0.05 to avoid upward bias and we did not identify any sample duplicates with a relatedness greater than 0.9. We further removed RAD loci with more than 10 haplotypes  using the 2.3To assess the extent of genetic structure among populations, we performed an individual‐based principal component analysis (PCA) using PLINK v2.0 . Overall weighted FST , to the in‐water distance between populations. The in‐water distances corresponded to the length of the shortest, direct within‐water path between two given locations, and were computed as least‐cost path distances between all pairs of populations by assigning infinite resistance to land areas and resistance of one to water using the function costDistance of the R package gdistance v1.1.1  and observed (HO) heterozygosity, and the mean measure of inbreeding coefficient (FIS) for each population using the population.sumstats_summary.tsv file produced by the populations module in STACKS. Effective population size (Ne) was estimated in each population using the program NeEstimator v2.1 in the R packages bigsnpr v1.8.7 . We adjusted the resulting p values for false discovery rate by computing q values using the R package qvalue v2.16.0  following the same procedure as described above. The outliers identified by pcadapt in either the full dataset or the region‐specific dataset were termed “pcadapt outliers”.We performed a genome scan to identify genomic islands of adaptive divergence using 6.0 Lai, . An SNP pcadapt outliers, likely to be the candidate regions for genomic islands of adaptive divergence, we conducted a sliding window analysis across the genome using a window size of 250 SNPs and a step size of 50 SNPs. Chromosome 40 was removed from the sliding window analysis as it was very small and only contained 73 SNPs. We defined windows with at least 10 pcadapt outliers (q < 0.01) as candidate windows under selection. Consecutive candidate windows were combined into candidate regions. To reduce the effect of window size on defining the size of candidate regions, we used the minimum pcadapt outlier SNP position as the start position and the maximum pcadapt outlier SNP position as the end position for each candidate region. We repeated the sliding window analysis separately using pcadapt outliers identified in the full dataset and each geographic region‐specific dataset.To identify genomic regions enriched for FST using pcadapt outliers within each candidate region with genet.dist function (method=“WC84”) in hierfstat v.0.5.7  in hierfstat. A pairwise FST value was considered significant if its confidence interval did not include zero. We further compared pairwise FST values calculated using pcadapt outliers in each candidate region and those with all SNPs and tested significance using Wilcox test. We also calculated population‐specific alternate/non‐reference allele frequencies (AF) of pcadapt outliers within candidate regions using PLINK v2.0  for SNPs with MAF ≥0.01 and located at least 400 bp from one another for each chromosome with a candidate region. We compared LD between pcadapt outliers within a candidate region and random SNPs  on the same chromosome, visualized the differences using boxplots, and tested for significance using permutation tests with 10,000 iterations following the permutation test procedures described in Shi et al.  of each candidate region, we calculated i et al. . BrieflyLDheatmap v0.99.7  over an extended distance (>1 Mb), we conducted a series of post hoc analyses to examine whether it was a putative chromosomal inversion. First, we conducted a local PCA analysis using the R package lostruct  or heterozygotes. We calculated the haplotype frequency of a chromosomal inversion in each population using the formula F=2C0or2+C12N , C1 is the number of individuals assigned to the heterozygous cluster (cluster 1) in the PCA, and N is the number of individuals in each population. Without genome comparison with closely related species, it is difficult to conclude with confidence which haplotype represents the ancestral state or the derived state. We thus name them according to their haplotype frequency (major vs minor).We visualized the overall LD pattern for each chromosome with a candidate region using the R package Jombart, . Lastly,33.1Preliminary RAD sequencing on 30 samples produced a total of 1,804,982,884 reads, of which 1,799,135,539 were retained. Following the STACKS pipeline and all quality control filters, a total of 150,000 loci were sent to Arbor Biosciences for bait development, of which baits were successfully designed for 105,073. We further removed loci with low/high GC content and retained a final panel of 100,000 loci with an average GC content of 44%.3.2Demultiplexed rapture sequencing data of 951 baseline samples yielded a total of 8,211,065,462 retained reads, with an average of 8,634,138 retained reads per individual . Out of these reads, 86.7%  were mapped to the European Alpine whitefish reference genome (GCA_902810595.1) in proper pairs with mapping quality greater than 20, with an average of 7,488,929 reads per individual . After quality filtering, the final dataset consisted of 829 baseline samples across 17 populations (Table 3.3FST = 0.0065). PCA showed the largest genetic break between the northwestern and eastern sides of the lake  and the IBD signal remained significant after MSKG was removed . However, when considering populations in each lake region separately, the correlation between genetic distance and in‐water distance became nonsignificant . Overall, similar to the pattern from Figure HE of 0.124 (0.117 to 0.134), HO of 0.154 (0.144 to 0.177), and FIS of −0.064 (−0.101 to −0.046). Estimates of Ne for all populations were infinity, highlighting the challenges of obtaining non‐infinite Ne estimates in large populations in the full dataset and each region‐specific dataset combined  than those using all SNPs in the full dataset except for the region on chromosome 20 , but low AF in others . In the region on chromosome 10, the mean AF of pcadapt outliers was high in CXVL (0.47) and LTTV (0.47), but low in others (0.22). The pattern in the region on chromosome 20 was less clear, with only subtle allele frequency differences among populations.Comparisons of allele frequencies (AF) of s Figure  corrobor3.5r2 between pcadapt outliers were generally higher compared to the chromosomal backgrounds  extending almost its entire ~8.5 Mb region from 45.4 to 53.8 Mb  along PC1 and the grouping pattern was not associated with populations , as well as more variation on the northeastern side compared to the southeastern side. Other factors may play a role, such as shoreline structure, bottom type, and riverine inputs , and these two populations were the last to be divided into separate genetic groups, suggesting difficulty in discriminating between them. In addition, the genetic differentiation between NMNL and BBDN does not seem to be temporally stable  and low pairwise FST values (FST = 0–0.0138). Systematic estimation of lake whitefish spawning site fidelity at a broad scale is lacking, though tagging data suggest some lake whitefish exhibit spawning site fidelity , and straying to neighboring spawning populations , where several genomic islands of divergence were found throughout the genome  and between populations (dXY), which can be accurately calculated using a sliding window‐based approach with all sites included (variant and invariant sites) such as the approach implemented in pixy  was a large LD block, which showed a distinct population structure pattern compared to the rest of the chromosome and a clear haplotype structure, suggesting a putative chromosomal inversion. The minor haplotype of this putative inversion was very rare , with similar frequencies across populations (2.7%–21.1%). Unlike a typical chromosome inversion with three genotypic clusters  indicates local adaptation plays a central role in maintaining high frequencies of particular adaptive genetic variants in specific populations. Management agencies could consider actions that extend location‐specific harvest closures to ensure certain stocks are protected during spawning, despite interannual variability in the timing of spawning. However, given that most lake whitefish harvest occurs outside of spawning, future mixed stock analyses could be used to establish the spatial range of each stock throughout the year to enable stock‐based management in favor of current geographically delineated management boundaries. The outlier SNPs uncovered here provide ample power for future SNP panel design that would permit such research to be efficiently performed.Anthropogenic selection pressure such as fishing can lead to genetic changes on top of natural selection. Though fisheries‐induced evolution might be a slow and less obvious process on decadal time scales, it is often unavoidable even with optimal management practices (Eikeset et al., The authors declare no conflict of interest.Figure S1Click here for additional data file.Figure S2Click here for additional data file.Figure S3Click here for additional data file.Figure S4Click here for additional data file.Figure S5Click here for additional data file.Figure S6Click here for additional data file.Figure S7Click here for additional data file.Tables S1–S5Click here for additional data file.


Colletes gigas is a pollen‐specialist pollinator of Camellia oleifera, one of the most important staple oil crops in China. Ca. oleifera blooms in cold climates and contains special compounds that make it an unusable pollen source to other pollinators. Thus, C. gigas undoubtedly plays a key role as the main pollinator of Ca. oleifera, with biological and economic significance. Here, we use a population genomic approach to analyze the roles of geography and climate on the genetic structure, genetic diversity, and demographic history of C. gigas. A total of 1,035,407 SNPs were identified from a 582.77 Gb dataset. Clustering and phylogenetic analyses revealed a marked genetic structure, with individuals grouped into nine local clusters. A significant isolation by distance was detected by both the Mantel test  and linear regression . Precipitation and sunshine duration were positively and significantly  correlated with observed heterozygosity (Ho) and expected heterozygosity (He). These results showed that C. gigas populations had a distinct phylogeographic pattern determined by geographical distance and environmental factors (precipitation and sunshine duration). In addition, an analysis of paleogeographic dynamics indicated that C. gigas populations exhibited patterns of glacial expansion and interglacial contraction, likely resulting from post‐glacial habitat contraction and fragmentation. Our results indicated that the peculiar phylogeographic patterns in C. gigas populations may be related to their specialization under long‐term adaptation to host plants. This work improves our understanding of the population genetics in pollen‐specialist bees. The distinct genetic clusters identified in this study should be taken into consideration for the protection and utilization of this specialized crop pollinator.Diet specialization may affect the population genetic structure of pollinators by reducing gene flow and driving genetic differentiation, especially in pollen‐specialist bees.  Colletes gigas, a pollen‐specialist pollinator of Camellia oleifera. A marked genetic structure and a significant isolation by distance effect were detected among populations. Precipitation and sunshine duration were positively and significantly correlated with population genetic heterozygosity. The historical population dynamics exhibited patterns of glacial expansion and interglacial contraction, likely resulting from post‐glacial habitat contraction and fragmentation. Our results indicated that the peculiar phylogeographic patterns in C. gigas populations may be related to their specialization under long‐term adaptation to host plants.In this study, we use a population genomic approach to analyze genetic structure, genetic diversity, and demographic history of  In addition, compounds in the pollen and/or nectar are toxic to most other bees, including managed honeybees  as a premium health‐grade edible oil  regional‐scale population structure and differentiation, (b) genetic diversity in local populations, and (c) the population history and relationships with environmental factors, including precipitation, sunshine duration, and temperature to obtain insight into climate‐driven demography and the demographic stability of this important crop pollinator. We also explored whether these climatic variables were helpful in explaining the genetic structure observed in C. gigas populations. This study provides new insights into adaptive genetic variation in this specialist bee and the roles of environmental variables and host plants in its evolution. Additionally, the results provide an important reference for predicting bee survival and for crop pollinator management.In this study, 55 samples from nine regions were collected from the main distribution of 22.1C. gigas (N = 55) were collected between October and December in 2019 and October in 2020, using a systematic sampling strategy to ensure the uniformity of spatial distribution , following the manufacturer's protocols. DNA libraries with ~350 bp insertions were constructed. Then, a genomic library with an insert size of 150 base pairs was constructed. Genome resequencing for each sample was performed using the Illumina HiSeq 2000 sequencing platform   was used to count the number of SNPs that are unique within populations and common among populations from a VCF format file.To detect population‐level SNPs, clean reads were mapped to the 2.3K) ranging from 2 to 9. The best K value was identified based on the cross‐validation procedure. A covariance matrix calculated from genotype likelihoods of SNPs with PLINK2 . Theoretically, FST cannot be less than 0, but sometimes calculations through software still give a small number of negative values. We set these negative FST estimates to 0, which means that there is no genetic subdivision between the populations considered  and expected heterozygosity (He) were calculated for each population using PLINK2  was calculated using SMC++  was performed using the ade4 package in R ) and geographical distance (log10 transformed). Precipitation, sunshine duration , and average temperature were considered as the most effective predictors of bee ranges .The geographic distance (in km) was calculated using the ArcGIS platform. The Mantel test of the geographic distance and genetic distance . When the K value was 9, CN finally showed independent status from other populations. We also explored the relationship of the species using PCA performing on the genetic covariance matrix among all individuals. The PCA results showed a considerable degree of interpopulation differentiation, with most species formed distinct point clusters in the space of the first two principal components  to 0.377 (between XJ and RX), with an average of 0.174. FST between RX and the other populations ranged from 0.299 to 0.377 (mean FST = 0.336), much higher than those among the other populations, indicating elevated genetic differentiation of RX from the other populations. There was very limited genetic differentiation among other populations (FST < 0.2), suggesting that gene flow was common among these populations. To further investigate the influence of geographic distance on divergence, we evaluated the correlation between the geographic distance matrix and pairwise FST matrix. The Mantel test showed a significant positive correlation between geographic distances and genetic distances . Similarly, linear regression showed a significant correlation between FST/(1−FST) and geographical distance (Log10 transformed)  and mean expected heterozygosity (He) were 0.218 (0.105–0.255) and 0.199 (0.079–0.253), respectively (Table Ho was greater than eH at the population level. There were significant differences (p < .01) in Ho and He among the nine populations. DY had the highest heterozygosity, while RX had the lowest heterozygosity. The high heterozygosity among populations might be explained by the combined effects of mutation, selection, and genetic drift. We found that the genetic diversity of C. gigas decreased from southeast to northwest and/or north with respect to the geographical distribution. The correlations between genetic diversity (Ho and He) and environmental factors  were analyzed. Precipitation was positively correlated with Ho  and He . Sunshine duration was also positively correlated with Ho  and He . However, there was no correlation between genetic diversity and temperature . These results indicated that genetic diversity was higher in areas with more precipitation and sunshine duration, where gene flow in C. gigas was also more frequent. Accordingly, the clinal changes in genetic diversity were consistent with geographical patterns of precipitation and sunshine duration.The mean observed heterozygosity  were estimated using SMC++. All populations underwent multiple changes in population size during their evolutionary history    than those of the other populations (0.32–0.51), indicating that RX had a higher demographic fluctuation. Moreover, RX showed the greatest decline among the nine populations since the LGM, which may reflect the high sensitivity of this population to climatic events and a lack of gene flow with surrounding populations, thus forming a strongly isolated population.To explore the demographic history of y Figure . The spey Figure . The mos4C. gigas revealed a marked genetic structure. First, a cluster analysis based on ADMIXTURE showed that there was very limited shared genetic variation between RX and any other population. Except for CN and YX, all populations were relatively independent and only showed minor shared variation. Second, the phylogeny based on individuals showed that all nine populations formed independent monophyletic clades, indicating significant genetic differentiation among C. gigas populations. Third, pairwise FST among populations was positively correlated with geographical distance, suggesting that geographical distance had a significant effect on the genetic differentiation among populations of C. gigas. The three analyses consistently proved that there is substantial genetic structure and differentiation among the populations of C. gigas.Overall, the SNP analyses of nine population pools of Colletes bees, which usually have weak migration ability. For example, both Colletes floralis    , consistent with the flowering season for its exclusive host plant. It is obvious that the low temperature in the two seasons is not conducive to foraging activity and long‐distance flight. Additionally, C. gigas depends on the pollen and nectar of Ca. oleifera for breeding  or even direct  influences on bee fitness  is likely to be strongly affected by the geographical and temporal distributions of host plants  but increased with decreasing global temperature . This pattern suggested that global temperature had a strong effect on the effective population sizes of C. gigas. A markedly different pattern has been observed for the Quaternary paleogeographic dynamics for many other bee species. These bee populations experienced sharp declines during the last ice age, followed by rapid expansion and species diversification from glacial refugia after the end of the last ice age . This finding suggested that the southeastern populations had more time to accumulate higher genetic variation under suitable environmental conditions. However, it is interesting to note that Ne for the RX population had a higher standard deviation than those of the other populations, suggesting that RX had a higher demographic fluctuation. Although there was some delay during the glacial period, the precise reasons are unknown. This population suffered its worst decline since LGM and was smaller than all other populations. This might be explained by a severe bottleneck when the population declined and became an isolated group. Small, isolated populations often present an increased risk of extinction due to various intrinsic factors, such as inbreeding and genetic drift  is relatively stable in the subtropical region, but present much larger fluctuation in the northwest ; Methodology ; Software ; Writing – original draft . Bo He: Methodology ; Writing – original draft . Fang Zhao: Funding acquisition . Kai Jiang: Resources . Gonghua Lin: Methodology ; Software ; Writing – review & editing . Zuhao Huang: Conceptualization ; Funding acquisition ; Resources .Supplementary MaterialClick here for additional data file.


German-derived ethnicities are one of the largest ethnic groups in Hungary, dating back to the formation of the Kingdom of Hungary, which took place at the beginning of the 11th century. Germans arrived in Hungary in many waves. The most significant immigration wave took place following the collapse of the Ottoman Empire in East-Central Europe which closed the 150 year long Ottoman occupation. To date, there are no comprehensive genome-wide studies investigating the genetic makeup of the Danube Swabians. Here we analyzed 47 Danube Swabian samples collected from elderly Swabian individuals living in the Dunaszekcső-Bár area, in Danube side villages of Southwest Hungary. These Swabians, according to self-declaration, did not admix with other ethnic groups for 3–6 succeeding generations. Using Illumina Infinium 720 K Beadchip genotype data, we applied allele frequency-based and haplotype-based genome-wide marker data analyses to investigate the ancestry and genetic composition of the collected Danube Swabian samples.Haplotype-based analyses like identity by descent segment analysis show that the investigated Danube Swabians possess significant German and other West European ancestry, but their Hungarian ancestry is also prominent. Our results suggest that their main source of ancestry can be traced back to Western Europe, presumably to the region of Germany.This is the first analysis of Danube Swabian population samples based on genome-wide autosomal data. Our results establish the basis for conducting further comprehensive research on Danube Swabians and on other German ethnicities of the Carpathian basin, which can help reconstruct their origin, and identify their major archaic genomic patterns.The online version contains supplementary material available at 10.1186/s12864-022-09092-5. The term “Danube Swabians”  is a collective term for the German-speaking ethnicity populating various countries of East-Central Europe, especially in the valley of the Danube River. While there were German immigrations with smaller numbers also in the 12th century, most of them are the descendants of late 18th century German settlers recruited by the Austrian Empire to repopulate the area and restore agriculture after the defeat of the Ottoman Empire. Danube Swabians can be found in the territory of Hungary, Romania, Serbia, and Croatia.Hungary has been a multicultural, multiethnic region since the foundation of the former Kingdom of Hungary at the beginning of the 10th century. Germans form the third largest ethnicity in today’s Hungary following the Hungarians and the Romani people. Their estimated number in 2016 was about 178 837 people, which is 1.8% of the total population of Hungary [Germans migrated into the Carpathian basin in multiple waves from several areas . The mosThe village of Dunaszekcső was first settled by Germans in the 18th century with the inhabitants originating from Tyrol, Silesia, Bamberg, Donau-Eschingen, Black Forest, Bavaria and Switzerland, Vienna and Saxony. These settlers dealt mainly with agriculture, handicrafts and viticulture . The popThe aim of our study was to conduct a pilot genome-wide autosomal investigation of Swabian individuals living in the Dunaszekcső and Bár area   populatiIn the ADMIXTURE analysis of Swabians and various European populations, the cross-validation error was the lowest at K = 2. The resulting ADMIXTURE graph strengthens the results of PCA and reflects a very similar relationship of the investigated populations Fig. . AccordiTreeMix also reflects the same relationships, as the drift parameter is most similar in case of West Europeans to Swabians within the branch consisted of Europeans Fig. . TreeMixst matrix) quantifies the results of PCA and shows that Swabians are similarly close to Hungarians, Germans and French, but they have the lowest fixation index value with the German samples  share of Swabians is the lowest with Adygei 0.768) and Sardinians (1.122) -anticoagulated whole blood and was genotyped on the Illumina Infinium Global Screening Array Beadchip platform which contains 725 831 single-nucleotide polymorphisms (SNPs). Isolation, genotyping, and preliminary quality control of the samples was carried out by the third-party service provider Human Genomics Facility (HUGE-F) in the Netherlands at the University of Rotterdam. Quality control and data preparation of the marker data was carried out domestically applying in-house scripts and the PLINK1.9 and 2.0 software packages , 15. TheThis study belongs to a series of investigations that were approved by the National Ethics Board (ETT TUKEB), and by Regional Ethics Committee of Pécs and follows the principles expressed in the Declaration of Helsinki.Genome-wide autosomal marker data from other open genotype databases was also considered in the study. We used the 1000 Genomes Project (1KGP) and Human Genome Diversity Project (HGDP) datasets which are openly available from the respected sources , 16–18. st) matrix calculation were achieved using the SMARTPCA software of the EIGENSOFT 6.1.4 package [Population structure analysis along with fixation index  samples from England and Scotland (GBR), Finnish from Finland (FIN), Iberian samples from Spain (IBS), Toscani from Italy (TSI) and Utah residents with Northern and Western European ancestry from the collection of CEPH (CEU).A second merged dataset containing the Swabian samples with various European groups using HGDP, AADR and Estonian Biocentre data was also created and analyzed using PCA. This dataset includes the HGDP populations French, French Basques, Orcadians, North Italians, Sardinians, Tuscans, Russians and Adygei. Populations from the AADR were the English, Scottish, Spanish, Finnish, and Greek, including also 1KGP samples of these groups. From the Estonian data, Hungarians, Romanians, and Germans were used.n = 556 individuals and 159 240 SNPs, the secondly created dataset featuring various European populations from various repositories contained n = 666 individuals and 106 121 SNPs. SNPs with strong background linkage disequilibrium (LD) were also pruned out with the ‘indep-pairwise’ command of PLINK1.9 setting the r2 threshold to 0.3. It is necessary before the analyses due to strong background LD can bias the PCA method, but also expectation maximization-based ancestry estimation algorithms like ADMIXTURE and TreeMix which were used in this study. After the pruning process, 149 979 and 79 757 SNPs remained in our first and second dataset, respectively. We used SMARTPCA with default settings, the σ-threshold was set to 6.0. Fst calculations were carried out with our second dataset using the “fstonly” option of the SMARTPCA software.The first, 1KGP dataset contained Ancestry estimation was carried out with the ADMIXTURE 1.22 algorithm which is a maximum likelihood estimation method using an expectation maximization approach . We carrn = 681, 79 757 SNPs).TreeMix was also applied along with ADMIXTURE analysis on this dataset, to better describe the relationship of these populations in a maximum-likelihood tree-based manner in addition to the stacked column styled ancestry estimation . The sizIn order to test the relationship of Swabians and other investigated populations in the second dataset, we utilized a formal test of admixture, the 4-population test. The qpDstat program from the ADMIXTOOLS 4.1 package was used for this purpose, and as its name suggests, this test was implemented here as D-statistics . For the), ), ), ). These tests intended to show the relationship of Swabians to the Hungarian host population, to the Germans and to various European populations.n = 601 individuals and 110 733 SNPs. Before the analysis, the data was converted according to the needs of the algorithm using the PLINK1.9 software. The major alleles were set as A2 allele and the dataset was converted to Variant Call Format 4.1 with the PLINK/SEQ software [For assessing the sources of ancestry in the investigated Swabian samples, we implemented here the Refined IBD algorithm of Beagle 4.1 . The sofsoftware . The minividuals . Using tij is the length of the IBD segment shared between individuals i and j. The n and m are the number of individuals in the groups I and J [IBD I and J .We also calculated the average number and average length of IBD segments between Swabians and the investigated various populations.Besides IBD segments, Refined IBD simultaneously detects homozygous by descent (HBD) segments, which allows us also to infer the genome-wide autozygosity of respective populations. This can imply the degree of isolation and degree of inbreeding of these groups. Therefore, average length and number of HBD segments were also calculated.Additional file 1.Additional file 2.Additional file 3.Additional file 4.Additional file 5.


Toxoplasma gondii is a cyst-forming apicomplexan parasite of virtually all warm-blooded species, with all true cats (Felidae) as definitive hosts. It is the etiologic agent of toxoplasmosis, a disease causing substantial public health burden worldwide. Few intercontinental clonal lineages represent the large majority of isolates worldwide. Little is known about the evolutionary forces driving the success of these lineages, the timing and the mechanisms of their global dispersal. In this study, we analyse a set of 156 genomes and we provide estimates of T. gondii mutation rate and generation time. We elucidate how the evolution of T. gondii populations is intimately linked to the major events that have punctuated the recent history of cats. We show that a unique haplotype, whose length represents only 0.16% of the whole T. gondii genome, is common to all intercontinental lineages and hybrid populations derived from these lineages. This haplotype has accompanied wildcats (Felis silvestris) during their emergence from the wild to domestic settlements, their dispersal in the Old World, and their expansion in the last five centuries to the Americas. The selection of this haplotype is most parsimoniously explained by its role in sexual reproduction of T. gondii in domestic cats. Toxoplasma gondii can infect all warm-blooded animals, with felidae being the definitive hosts. Despite this broad host range, most clinical and animal isolates belong to few clonal lineages. Here, Galal et al. perform whole-genome sequencing of isolates from distinct geographical regions and estimate T. gondii mutation rate and generation time. They find that recent waves of migration disseminated the parasite from Old to New World and identify a unique haplotype that likely accompanied the global expansion of cats and is today common to all intercontinental lineages and hybrid populations. Toxoplasma gondii is a zoonotic protozoan that has spread globally. This apicomplexan parasite infects all warm-blooded species, including humans, and its wide range of host species suggests multiple routes for short and long-distance parasite migrations1. T. gondii is found in ~30% of the human population and is the etiologic agent of toxoplasmosis, a disease causing a substantial public health burden worldwide2. Infection with T. gondii has been long considered benign, or even asymptomatic, except for certain risk groups like the developing foetus in case of congenital infection with 200,000 new cases each year3, and immunocompromised patients for whom toxoplasmosis can have severe health consequences either during primo-infection or reactivation. However, certain T. gondii populations have been associated with severe toxoplasmosis in immunocompetent individuals6. More importantly, an increasing number of epidemiological studies suggest that chronic infection with T. gondii is associated with a wide variety of neuropsychiatric disorders, substantially raising the public health importance of this global and highly prevalent parasite7. Given gaps in both the current preventive (no vaccine available for humans) and therapeutic strategies9, active research to discover new ways to target this clinically important protozoan is still needed.T. gondii hosts get infected after ingestion of oocysts shed into the environment by contaminated faeces of felids. Another source of infection for humans and other meat-consuming species is the ingestion of raw or undercooked meat from animals harbouring infective tissue cysts. In the domestic environment, cats and rodents are considered the most significant reservoirs for human infection, since life cycle completion relies mainly on transmission between these two categories of animal hosts, the rodents being the main prey of cats11. Sexual recombination is possible when two different strains are found simultaneously in the cat’s gut. For this to occur, a cat has to ingest within a few hours two prey infected with different strains. There is, therefore, a time barrier for recombination to occur, or alternatively, the cat has to ingest a single prey infected with two different strains (mixed infection), a rare event in nature given that intermediate hosts develop immunity to new infections following their first infection.T. gondii is characterized by contrasting patterns of strain diversity, mainly varying according to geographical origin and ecotype. To date, most studies of diversity have relied on the analysis of microsatellite markers (MS), or Restriction Fragment Length Polymorphism (RFLP)  and Africa 413. Few other clonal lineages have been described in certain countries, such as Chinese 1 in China14 and Africa 3 in Gabon15, and strains not belonging to these major lineages have been rarely isolated16. This genetic evidence argues that sexual recombination between different strains is very rare in these regions. In the New World (North and South America), the most common Old World clonal lineages  are also found beside a diversity of local clonal lineages and non-clonal populations specific to South or North America17. In contrast to the pattern observed in the Old World, the genotypic composition of strains from wildlife differs importantly from strains commonly isolated in the domestic environment18. These T. gondii populations—isolated from wild animals or from humans in contact with wildlife and genetically distinct from T. gondii populations found in the domestic environment—are associated with environments where the presence of wild felids is well-established19. This observation supports the notion that specific co-adaptations have occurred between T. gondii strains and different feline species22.From a genetic point of view, the population structure of T. gondii lineages and populations remains unclear24. In addition, conflicting scenarios have been proposed to explain the global spread of T. gondii populations27, often with no distinction between ancient and recent histories. Given the crucial importance of domestic cats and rodents in the transmission of T. gondii, a presumed role of these host species in the recent global spread of the major clonal lineages has been repeatedly evoked in the literature29. However, this hypothesis could not be formally tested previously29 owing to the paucity of T. gondii samples in many regions31. Moreover, a lack of good estimates of parasite mutation rate and generation time has hampered attempts to date dispersal time in relation to the expansion history of the principal hosts.To date, population genetic studies have only partially deciphered the phylogenetic relationship between strains from different geographical areas. In particular, the phylogenetic positioning of the most common intercontinental clonal lineages relative to other T. gondii, which is assumed to have been strongly influenced by migrations of strains between Old and New Worlds29. Using the largest dataset of T. gondii genomes produced to date (n = 156), we revisit the ancestry and admixture patterns of T. gondii populations worldwide. We provide a direct estimate of T. gondii mutation rate and an estimate of its generation time, allowing us to date the major events that have shaped the parasite genome evolution. We use selection inference tools to identify the major selective processes acting on current T. gondii populations. We uncover candidate genes whose geographic distribution, genomic and stage-specific patterns of expression are most parsimoniously explained by a role in transmission by domestic cats.To address these questions, we focused our analyses on the recent evolutionary history of n = 107) and wild animals (n = 17) in addition to a number of human isolates (n = 40) (Supplementary Data n = 3), but the predominant lineages found in the continent14 were represented in our dataset . Note that most Old World samples included in this study belonged to clonal lineages previously identified and defined from MS markers  and Europe , the most likely source populations for the recent human-mediated global expansion of T. gondii strains. Isolates from the New World originated from both coastal areas , and inland areas, including wild environments in South and North America. In addition, several isolates came from the Caribbean islands , which are well-known for their importance in maritime history linking Old and New Worlds. New identifiers were assigned to strains included in this study, indicating the country of origin of each strain.Paired-end sequence reads from 59 publicly available haploid genomes and from 105 newly determined haploid genomes were aligned to the recent PacBio reference assembly RH-88. These samples included isolates from domestic , resulting in a dataset of 71 strains and 588,777 SNPs. The optimal number of ancestral groups was determined to be five , but we also examined different K values. Old World strains not belonging to the predominant lineages  were found to be putative hybrids of these lineages , most strains belong to one of the previously defined intercontinental clonal lineages, with rare hybrids observed between the different lineages. On the other hand, most New world parasites isolated from wild environments form well-defined distinct populations, and most of those isolated from domestic environments are probably the result of hybridizations between intercontinental lineages and a number of New World-specific wild populations  in order to detect genomic regions of unexpectedly high divergence between the three groups. A unique outlier region of marked divergence between input groups was identified  presence of missense (nonsynonymous) variants specific to intercontinental lineages and hybrids; (2) expression, increased expression, or specific expression during enteroepithelial stages (EES) of development ; and (3) degree of conservation in comparison to orthologs from the closest species to T. gondii (Hammondia or Neospora). Sixteen genes were considered to be poor candidates as they did not carry missense variants, were not expressed, showed a significant decrease in their expression during EES, or were highly conserved (>95%). Among the five remaining candidate genes, only one was found to be specifically expressed during EES: TGRH88_020330 (TGME49_295920) and is annotated as encoding a hypothetical protein. Five missense variants specific to intercontinental lineages and hybrids were found for this gene (Supplementary Table In order to determine which gene(s) is/are most likely concerned with the selective process acting on the outlier region, we carefully analysed the predicted function of the 21 candidate genes present in the ~100 kb genomic regionT. gondii lineages have recently hybridized with a number of New World populations, leading to the emergence of numerous hybrid T. gondii populations in the New World. We identified a unique haplotype of ~100 kb (0.16% of the whole T. gondii genome) on chromosome 1a common to all intercontinental T. gondii lineages and hybrid strains and under strong positive selection in these populations. On the opposite, New World non-hybrid populations carried a diversity of divergent haplotypes in this genomic region. Note that a number of intercontinental T. gondii lineages and hybrid strains share the same haplotype for the whole length of chromosome 1a, a pattern previously noticed in past studies31. Our results indicate that this pattern can be explained by the much stronger linkage disequilibrium (often reaching the whole length of chromosome 1a) observed in these strains relative to New World non-hybrid populations around the ~100 kb outlier region, which probably persists due to the combined effects of selection and rarity of sexual recombinations in most T. gondii populations.We showed that intercontinental T. gondii strains from the Old World carried the ~100 kb unique haplotype of T. gondii on chromosome 1a, whether they were isolated in a domestic or wild environment34. Almost all T. gondii strains from the New World carried the same haplotype when they were isolated in the domestic environment. However, this haplotype showed various degrees of dissemination to wildlife in North and South America according to geographic area35 , which also emerged in the Old World from wildcats (Felis silvestris) before reaching the New World in the last few centuries46. This would support a temporal association between this haplotype and the presence of cats . In consequence, the most straightforward scenario would be that these lineages originated in the Old World and subsequently seeded to the New World, although other scenarios could be considered  before domestication. The domestication of cats first occurred in the Near East coincident with agricultural village development in the Fertile Crescent about 10,000 years ago46. Since this period, regular genetic exchanges occurred between domesticated cats (Felis catus) and their wild counterparts (Felis silvestris), probably contributing to the pattern of low level of differentiation observed between modern wild and domestic cat genome sequences47. It is therefore likely that T. gondii populations transmitted by wildcats did not need further adaptation to occupy the new niches offered by domesticated cats, as shown by the marked genetic conservation of the ~100 kb haplotype from the emergence of type II until today. T. gondii strains carrying this haplotype could have accompanied cats of subspecies F. s. lybica (one of the five known clades of wildcats of species Felis silvestris found in different regions of the Old World) that established themselves in human settlements in the Near East, or emerged later in the domestic environment from other wildcat populations in Africa, Asia or Europe following the expansion of the Neolithic revolution to those regions. At least three genetic populations of this haplotype were at the origin of its spread in the domestic environment: Africa 4, which expanded in Africa and Asia, Chinese 1 found today in Eastern Asia and type II, at the origin of its global expansion.It is noteworthy that this haplotype was circulating in the Old World well before these recent times and even before cat domestication , according to phylogeny. For example, type II, one of the lineages carrying this haplotype, was estimated to have emerged 26,000 years before the present. Therefore, it is likely that this haplotype was already circulating in wildcats . It is noteworthy that hybrid strains are more diversified in South America compared to the rest of the World, indicating more frequent recombination events, likely due to the effect of superinfections50  are probably more efficient at being transmitted in the form of oocysts by cats than wild strains from the same area. This should be confirmed on larger sample sizes, but the study of T. gondii sexual reproduction is hampered by the important ethical concerns associated with the use of live cats.A 33. A selective process taking place during host cell recognition or invasion before the initiation of sexual reproduction should also be a hypothesis to consider. In this case, other genes on the ~100 kb outlier region of chromosome 1a could merit consideration despite not being expressed during the different phases of sexual reproduction stricto sensu. TGRH88_020330 (TGME49_295920) was selected as the top candidate gene, as it was the only gene specifically expressed by T. gondii during the early stages of sexual reproduction in cat enterocytes, which also carried variants of putative functional relevance (missense) segregating the ~100 kb unique haplotype from divergent ones. However, it was not possible to determine which of these missense variants has functional relevance. The genomic region carrying this gene exhibits strong linkage disequilibrium among strains carrying the ~100 kb unique haplotype, implying that most variants associated with this haplotype (n = 310) have been fixed by hitch-hiking. Di Genova et al.53 have recently produced cat intestinal organoids for experimental purposes, an important breakthrough to study the sexual reproduction of T. gondii and testing the function of the most promising candidate genes identified in this study. In the same way, developing similar experimental models from intestinal cells of wild felids could enable a more comprehensive understanding of the function of these genes.In the present study, we identified five genes within the ~100 kb genomic region on chromosome 1a which fulfil the criteria of promising candidate genes due to their possible involvement in sexual reproduction in cat enterocytesT. gondii genomes and provided estimates of the parasite’s mutation rate and generation time. We show that a ~100 kb unique haplotype on chromosome 1a has recently spread worldwide. It has been largely conserved since its initial emergence from wilderness to domestic settlements in the Old World, its dissemination, and its recent expansion to the New World. Our results argue that the selection of this haplotype can be explained by its role in augmenting the efficiency of sexual reproduction of T. gondii in cats. This haplotype could be conferring a selective advantage to strains carrying it in the domestic environment and could be one of the key adaptations at the origin of the global spread of this parasite, estimated to be infecting one-third of the world’s human population2. Our findings constitute an example of the profound effect exerted by human activities on pathogen diversity brought about by two major events in human history: domestication during the Neolithic revolution and globalization of trade in the few last centuries.In summary, we have produced a large dataset of high-quality T. gondii isolates provided by the French Biological Resource Centre (BRC) for Toxoplasma (http://www.toxocrb.com/). This certified structure (NF S96-900 standard) manages the storage of T. gondii strains from human or animal toxoplasmosis to make them available to the scientific community. Our analyses were complemented with whole-genome sequence data of 59 strains (100 bp paired-end reads) from a previous study24 made publicly available on the European Nucleotide Archive (https://www.ebi.ac.uk/ena/browser/home). Following parasite culture  was used for TUB2, XI.1, B18, N83, N61, M33 and M48; hexachlorofluorescein (HEX) for MS TgM-A, B17, N82, W35 and IV.1; and 2,7′,8-benzo-5′-fluoro-2,4,7-trichloro-5-carboxyfluorescein (NED) for AA, N60 and M102. The PCR reaction was carried out using a 25 µl reaction mixture composed of 12.5 µl of 2× Qiagen Multiplex PCR Master Mix , 5 pmol of each primer and 5 µl DNA. Cycling conditions were as follows: initial denaturation 15 min at 95 °C, followed by 35 cycles of 94 °C for 30 s, 61 °C for 3 min, 72 °C for 30 s, and 30 min at 60 °C. PCR products were diluted 1:10 in deionized formamide . One microliter of each diluted PCR product was mixed with 0.5 µl of a dye-labelled size standard  and 23.5 µl of deionized formamide (Applied Biosystems). This mixture was denatured at 95 °C for 5 min. The PCR products were then electrophoresed using an automatic sequencer . The size of the alleles in bp was estimated using GeneMapper analysis software . This genotyping step was necessary to check for cross-contaminations between samples during culture and to identify mixed infections. Mixed infection was identified in one isolate  by the presence of two alleles at 12 loci; only one strain was genotyped at the time of isolation, and it is therefore likely that the second strain initially had a lower tissue load in the infected host, and took longer to grow to levels sufficient for library construction. Only the mono-strain isolates (n = 105) were sequenced. DNA was sheared into 400–600-base pair fragments by focused ultrasonication . Standard indexed Illumina libraries were prepared using the NEBNext DNA Library Prep kit (New England BioLabs), followed by amplification using KAPA HiFI DNA polymerase (KAPA Biosystems). 150 bp paired-end reads were generated on the Illumina NextSeq 500 according to the manufacturer’s standard sequencing protocol.We studied 106 T. gondii, which still fall under the category of “non-model” organisms. Ribeiro et al.55 explored the relationship between the choice of tools and parameters in non-model organisms, and their impact on false positive variants, and formulated recommendations for variant calling. Here, we followed their recommendations in order to minimize the call of false positive variants, which was a critical point regarding our objective of estimating the occurrence times of recent events in T. gondii evolution. In this sense, reads were submitted to a stringent mapping configuration (not more than 2% of mismatches), by using BWA 0.7 against the newly available PacBio reference genome RH-88 . Mapped reads were sorted with Samtools 1.11, and duplicate reads were marked with Picard ‘MarkDuplicates’ 2.25. Individual BAMs were subsequently merged, and variant calling was performed with FreeBayes 1.3.556, which is considered better than the routinely used Genome Analysis Toolkit (GATK) in non-model organisms57. At the individual level, alignments having a mapping quality  less than 20, a coverage (--min-coverage) less than 3, and alleles having a supporting base quality  less than 20 were excluded from the analysis. Genotype calls having a fraction of conflicting base calls of more than 10% were also excluded. Finally, only individuals having missing genotype data of less than 5% were kept for subsequent analyses to minimize false negative calls. At the population level, singletons SNPs and SNPs having a high missing genotype rate (>10%) were filtered out. With the above filters in place, two individuals were excluded (missing genotype data >5%), before excluding an additional six samples due to unreliable information about the country of origin and/or the ecotype. The filtered set of SNPs was annotated with snpEff 5.0 6 using the RH-88 annotation file.Recent advances in variant calling enabled the use of publicly available panels of validated single-nucleotide polymorphisms (SNPs) and indels to estimate the accuracy of each base call and minimize the generation of false positive SNPs. Unfortunately, building these panels is labour-intensive and such data is lacking for under-studied organisms such as T. gondii apicoplast genome, mapping of reads was performed against the ME49 reference genome assembly , as the PacBio reference genome, RH-88 had a high proportion of low complexity sequence (~70% in RH-88 genome versus ~30% in ME49 reference genome). The mapping quality of reads in these low complexity regions was too low, and therefore these regions were not exploitable for sequence analysis. A mapping configuration and variant calling parameters identical to those used for the nuclear genome were used for the apicoplast genome. In addition to the six samples having unreliable information about the country of origin and/or the ecotype, six additional samples were excluded due to a high frequency of missing genotype data (>5%).For the 35 kb 58 specifically addresses issues with the analysis of clonal and partially clonal populations. We first used this package to collapse individuals into clonal groups, by defining a genetic distance threshold based on 3 different clustering algorithms using the function mlg.filter58. This initial step, besides enabling the definition of clonal lineage boundaries, is a necessary partial correction for a bias that affects metrics of most computational tools that often rely on allele frequencies assuming panmixia. A dissimilarity matrix was produced by poppr to compute genetic distances between genomes, and a minimum spanning network was drawn based on these calculations, by collapsing individuals based on the previously defined genetic distance threshold.Most computational tools for population genetics are based on concepts developed for sexual model organisms. Microbial pathogens are often clonal or partially clonal, and hence require different tools to address their population dynamics and evolutionary history. The R package poppr 2.059. ADMIXTURE is useful as an exploratory tool in analyses of genetic structure but should be interpreted with caution since such model-based algorithms often provide only a caricature of a complex reality. The dataset was clone-censored  and pruned for linkage disequilibrium in PLINK60 (v. 1.07) using parameters --indep-pairwise 50 5 0.2 . ADMIXTURE was run using the unsupervised mode with cross-validation (--cv). The number of ancestral populations (K) varied between 2 and 10.In order to identify ancestral populations and characterize the admixture patterns in our dataset, we used ADMIXTURE 1.361, known to be particularly useful to discern signatures of recent admixture. ChromoPainter estimates the number of “chunks” of ancestry inherited by an individual or a population from a “donor” individual or population and builds a co-ancestry matrix that summarizes the degree of sharing of ancestry among all pairs of individuals. Unlike ADMIXTURE, ChromoPainter takes into account patterns of linkage disequilibrium, allowing one to combine information across successive markers to increase the ability to capture fine-scale population structure. Hence, linkage disequilibrium pruning was not required for this analysis, and we used the unpruned clone-censored dataset.We complemented our global ancestry analyses with ChromoPainter62. Ancestry_HMM is based on a novel hidden Markov model that does not require genotypes from reference panels and that is generalized to arbitrary ploidy, and is hence suitable for non-model haploid organisms. In addition, a TCS network was produced from the apicoplast sequences using PopART.Local ancestry inference  is the task of identifying the regional ancestral origin of chromosomal segments in admixed individuals. It requires specifying a set of candidate non-admixed populations as putative ancestors of the admixed individuals. After defining ancestral and admixed individuals using approaches of global ancestry inference, we carried out local ancestry analysis using the recently released Ancestry_HMM softwareT. gondii based on the in vivo mutation rate of the RH strain, through the successive passage in outbred mice for 30 years (Supplementary Note −9 to 11.7 × 10−9 (mean: 7.4 × 10−9) mutations per site per year. This mutation rate was used for dating the emergence of intercontinental lineages and for estimating the migration times of T. gondii populations between Old and New Worlds. These dating analyses were carried out using the Bayesian Markov chain Monte Carlo (MCMC) approach implemented in BEAST v1.10.4. The General Time-Reversible (GTR) nucleotide substitution model with a gamma distribution and a proportion of invariant sites (GTR + Γ + I) was identified as the best fitting model by jModelTest v2.1.10. The Markov Chain Monte Carlo (MCMC) was run for 100 million steps with sampling parameters and trees every 10,000 steps. The convergence of all parameters was assessed by calculating effective sample sizes (ESS), setting their threshold at 200 after discarding the initial 10 per cent of each run as a burn-in using Tracer v1.7.1. By using the above-mentioned model configuration, genomic sequence datasets were produced using Bcftools consensus 1.11. A genotype call falling below minimal quality requirements  was considered as a low-quality genotype and was masked with an N character to symbolize that the nucleotide base at this position is unknown.We estimated the mutation rate of −9 and the standard deviation to 2.15 × 10−9. When strains of a given intercontinental lineage shared the same ancestry with other strains at a given chromosome , their genetic closeness was confirmed by building a chromosome-specific neighbour-joining tree using ape R package that computed genetic distances based on the dissimilarity matrix produced by poppr R package. Following this verification step, a specific dataset was produced for the chromosome sequences of these two groups to estimate their divergence times. Independent runs were launched for each specific dataset in BEAST under an uncorrelated lognormal relaxed clock. Uncorrelated relaxed clocks allow each branch of a phylogenetic tree to have its own evolutionary rate63 to account for possible variability in evolutionary rates within the tree. The mean rate of the molecular clock (ucld.mean) was set to 7.4 × 10−9 and the standard deviation (ucld.stdev) to 2.15 × 10−9. In order to estimate divergence times between Old and New Worlds T. gondii populations, the TMRCA of each New World strain with its closest Old World relative was extracted from the phylogenetic trees generated with BEAST using FigTree 1.4.4. All these TMRCA values were used to generate a boxplot to graphically visualize their distribution.For genomes of each intercontinental lineage, a specific dataset was produced, and an independent run was launched to estimate their TMRCA as an approximation of lineage emergence time. We assumed a strict molecular clock in model configuration since the genomic sequences used in each run were all from the same lineage. Clock rate was set to 7.4 × 1064. This method enables to detection of genomic regions of unexpectedly high differentiation between different pre-defined groups , a pattern indicative of directional selection66. In parallel, in order to ascertain candidate SNPs, we used the bcftools 1.1 -- private function to identify SNPs common to intercontinental linages and hybrid strains derived from these lineages. SNPs identified with these two approaches were annotated with SnpEff in order to define a primary list of candidate genes. To determine which candidate genes are most likely to be under positive selection, we focused on functional evidence. We carefully searched the literature for the function of candidate genes and their stage-related patterns of expression. Selection can result in patterns of extended linkage disequilibrium (LD) and extended haplotype homozygosity (EHH) around the selected site, especially relative to the alternative allele. EHH is defined as the probability that two randomly chosen chromosomes carrying the same allele at a focal SNP are identical by descent over a given distance surrounding it. Hence, for outlier SNPs validated by all types of evidence—environmental, statistical and functional—we computed EHH using the REHH 2.0 R package67 to examine the extent of linkage disequilibrium around them.To identify candidate genes involved in the process of adaptation to the domestic environment, a multistage process was used. We first carried out a divergence-based selection scan using the population branch statistic (PBS) software PBScanFurther information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Reporting SummaryPeer Review File


F. paralugubris by AFLP assay and found that it was higher in the introduced populations, while native ones showed a higher diversity between nests. Overall, the genetic structure was dominated by among-worker variation regardless of different grouping arrangement .Red wood ants are ecologically dominant ant species that play key roles in boreal forest ecosystems, where they greatly influence the habitat dynamics with their predatory activity. During the last century, they were largely employed as biocontrol agents in Italy against forest pests, and thousands of nests were transplanted from the Alps to the Apennines for this aim. We compared genetic variability and structure of native and introduced populations of Formica rufa group comprises several ant species which are collectively referred to as “red wood ants” and play key roles in boreal forest ecosystems, where they are ecologically dominant and greatly influence habitat dynamics. Owing to their intense predatory activity, some of these species are used as biocontrol agents against several forest insect pests and for this aim in Italy, nearly 6000 ant nests were introduced from their native areas in the Alps to several Appeninic sites during the last century. In this work, we assessed and compared the genetic variability and structure of native and introduced populations of F. paralugubris, thus evaluating the extent of genetic drift that may have occurred since the time of introduction, using amplified fragment length polymorphism (AFLP) markers. PCR amplification with a fam_EcoRI-TAC/MseI-ATG primers combination produced a total of 147 scorable bands, with 17 identified as outlier loci. The genetic variation was higher in the introduced population compared to the native ones that, on the other hand, showed a higher diversity between nests. AMOVA results clearly pointed out that the overall genetic structure was dominated by among-worker variation, considering all populations, the Alpine vs. Apennine groups and the comparison among native and related introduced populations . Genetic analyses unveiled the existence of six main different groups that do not entirely mirror their geographic subdivision, pointing towards a wide admixture between populations, but, at the same time, rapid diversification of some Apennine populations. Future studies based on high-throughput genomic methods are needed to obtain a thorough understanding of the effects of environmental pressure on the genetic structure and mating system of these populations.The  Formica rufa Palearctic complex, which in Western Europe comprises at least six species: F. rufa , F. aquilonia , F. lugubris , F. paralugubris , F. polyctena  and F. pratensis . All these species are characterised by the ability to build large aboveground nest mounds, and by the red and black coloration of their bodies. From the ecological point of view, RWA are keystone species, and they deeply impact the functioning of their forest ecosystems across multiple trophic levels [Red wood ants (RWA) are ecologically dominant species native of boreal forests of Central and Northern Europe . They bec levels . These sc levels ,5 and, uYarrow, 155, F. luF. lugubris/paralugubris, F. polyctena and F. aquilonia were repeatedly transferred from the Alps to the Apennines and other Italian mountainous areas [Owing to their intense predatory activity, some RWA species have been employed as biocontrol agents against several forest insect pests . For thius areas . These ius areas . While ius areas ,13. The us areas . StudyinFormica paralugubris was one of the most frequently introduced species in the Italian peninsula, but also to Canada [F. lugubris by Seifert [Formica paralugubris can form huge supercolonies, composed of tens to hundreds of interconnected nests that may cover areas of over 0.5 km2 [o Canada ,15 and w Seifert . Since i Seifert . Formica 0.5 km2 ,19, wher 0.5 km2 . Each ne 0.5 km2 . The two 0.5 km2 .F. paralugubris, using amplified fragment length polymorphism (AFLP) analysis. AFLPs are a PCR-based highly replicable dominant marker that allows rapid screening of genetic diversity and intraspecific variation without a priori sequence knowledge and at a low cost [In the present study, we investigated the genetic variability in two native and four introduced populations (two from each native population) of low cost . Our goaFormica paralugubris ants were collected from six populations—two native from the Alps and four introduced in the Apennine , and beech . LC and FF were also characterised by mixed forest, but the local dominant conifer species is the silver fir , while AA and LM are covered by almost pure silver fir stands. More details on the ecology of the introduced populations and the history of their introduction can be found in [Apennine —from Junfound in ,13.® 10, accuracy ~3 m, Garmin, Olathe, KS, USA). Ants were stored in plastic test tubes (8 mL volume) filled with pure reagent-grade ethanol. All samples were transferred to the laboratory within 24 h from collection and stored at −80 °C for genetic analysis.For each population, we selected ten nests located at least 50 m apart, and ten ants were collected from the surface of each nest, for a total of 600 workers. The geographic position of the sampled nests was recorded by a GPS locator . The sample was gently stirred and incubated at 56 °C for 4 h, adding 4 µL of Proteinase K. After centrifugation at 13,000 for 3 min, the upper aqueous supernatant was precipitated with 100% ethanol and 3 M sodium acetate, pH 5.2. This mixture was incubated at −20 °C for 20 min and then centrifuged at maximum speed for 10 min. The resulting pellet was washed by adding 70% ethanol and then centrifuged for 10 min at maximum speed. The supernatant was discarded and the pellet was airdried, resuspended in 30 µL of DNase-free water  and used as a template for PCR amplification. The extracted DNA was quantified using a Qubit 4 fluorometer (Invitrogen) with the dsDNA HS Assay kit (Invitrogen™ Q33231).Genomic DNA was extracted from a single adult thorax , with a modified Chelex method . Thorax An analysis of AFLP divergence was performed following the procedure described by Coppi et al. . The quaSince AFLP are dominant markers, the presence or absence of every single fragment (100–2000 bp) was scored in each sample and coded by 1 or 0, creating a binary data matrix used to evaluate the within-population genetic variation as percentage of polymorphic loci (PL%), standard Nei’s measure of genetic diversity (“h”) as “average gene diversity over loci”  and ShanST-POP), as difference in the allele frequency between nests.The analysis of molecular variance (AMOVA) was performed using the ARLEQUIN v. 2.000  to deterA pairwise distances matrix among workers was computed following the Tamura–Nei method  and thenThe analysis of population structures was performed following a model-based Bayesian clustering method implemented in STRUCTURE v.2.3.4 . An admiThe AFLP dataset resulted from the analysis of 534 samples , since tThe percentage of polymorphic loci (PL%) among population ranged from a maximum of 90.48% (LC) to a minimum of 51.7% (BA). A summary of all the diversity measured is reported in ST-POP, h and I), it appeared that the two native populations had the lowest values of genetic diversity . Nearly the same situation was found between the native populations and their related introduced ones . A genetic structure dominated by among-worker variation  and, more importantly, in climate, being located more than 250 km south of the Alps. The concurrent action of these factors could have imposed local selective pressures underlying the observed changes. Moreover, we also know that most of the original nest mounds introduced  had disappeared a few years later, and in nearly all areas the populations had reduced to three to six mounds . We do nF. paralugubris, while transplanted populations should be preserved through specific conservation policies and plans.The population genetic makeup obtained with STRUCTURE suggests the existence of six strongly admixed groups that do not correspond to the geographic origin. Admixture included elements from both the Apennine and the Alps, though AA, LC, LM and FF were seemingly different from their native ones. One point that needs to be carefully considered, however, is that the populations introduced to the Apennines 70 years ago may represent an important source of genetic diversity. Considering the low genetic variability of the native populations and increasing evidence of local declines and extinction in several parts of the species range, Alps included, these findings may have relevant implications for the conservation of RWA. Further studies are needed to better assess the status of the Alpine populations of F. polyctena and F. aquilonia. As far as our populations are concerned, a double-digest restriction-site-associated DNA sequencing (ddRADseq) approach could be a powerful tool to compare the genetic variation, structure and mating system across populations [Finally, AFLP analysis turned out to be an efficient and cost-effective tool for assessing genetic diversity and variation in these populations, at least for a first screening based on population genetic variance. Compared to other markers such as RAPD (random amplified polymorphic DNA) and SSR (short sequence repeat) based on a polymerase chain reaction (PCR) step, AFLP can rapidly generate a great number of polymorphisms with a high number of assayed loci in virtually any organism, being often used for diversity and population genetics studies in ants and other insects ,48,49. Tulations ,53 alongulations .F. paralugubris in Italy. The results may not only assist the conservation of native RWA populations but also better our understanding of the dynamics experienced by ant species when transplanted outside their distribution range.In conclusion, this study provides the first information about variation in genetic diversity of native and introduced populations of