Numenius phaeopus) and Eurasian curlew (N. arquata). Using genome-wide markers from populations across the Palaearctic, we applied a multitude of population genomic and phylogenomic approaches to elucidate population structure. Most importantly, we tested for isolation by distance and visualized barriers and corridors to gene flow. We found shallow Palaearctic population structure in subpolar bog and tundra-breeding whimbrels, consistent with other species breeding at a similarly high latitude, indicating connectivity across the tundra belt, both presently and during southward shifts in periods of global cooling. In contrast, the temperate grassland-breeding Eurasian curlew emerged in three distinct clades corresponding to glacial refugia. Barriers to gene flow coincided with areas of topographic relief in the central Palaearctic for whimbrels and further east for Eurasian curlews. Our findings highlight the interplay of historic and ecological factors in influencing present-day population structure of Palaearctic biota.Intracontinental biotic divisions across the vast Palaearctic region are not well-characterized. Past research has revealed patterns ranging from a lack of population structure to deep divergences along varied lines of separation. Here we compared biogeographic patterns of two Palaearctic shorebirds with different habitat preferences, Whimbrel ( It is surmised that the impact of Quaternary climate oscillations on biogeography differs according to a suite of variables, such as latitude and topography2. During cyclical periods of global cooling, the formation of barriers has facilitated intercontinental biotic differentiation as revealed by traditional DNA markers7. While intra-continental population structure is equally impacted by Quaternary climate oscillations, it has not been studied as intensely, with most research focusing on North America and Europe11. The Nearctic and Palaearctic, both large northern hemispheric landmasses, are characterized by a zoogeographical division into an eastern and a western sub-region. The boundary between North America’s sub-regions runs along a suture zone through the center of the Great Plains and has been well described20. In the Palaearctic, a vast zoogeographic region stretching across the world’s most sizeable landmass, Eurasia22, the large-scale division into western and eastern sub-regions has long been established based on the distinct faunal elements present on either side24. However, resolution of the boundary of these two sub-regions across biota has so far eluded biogeographers.Extreme climatic events in the Earth’s recent past have played an important role in shaping population genetic structure of animals28. Population genetic inquiries on many vertebrates31, especially songbirds35, and invertebrates37 have revealed a primary divide between Far-Eastern populations  and the much more expansive western and central Palaearctic populations. An alternative dividing line within wide-ranging Palaearctic species has been proposed further west in the Central Palaearctic39. In other studies, Palaearctic populations have also been characterized by divisions into multiple clusters corresponding to glacial refugia during the Last Glacial Maximum (LGM)41. Conversely, some wide-ranging species lack or show only shallow population structure despite the vast geographical area involved44. Explanations for these phylogeographic patterns often invoke geographical features and environmental conditions both presently and historically44, which interact with life-history traits such as dispersal capability9, natal homing45, prey availability42, non-breeding habitat preference46, mating system49 as well as the evolutionary history unique to each species28. This complicated interplay of factors accounts for substantial variability in the boundary between eastern and western Palaearctic population units across species.Novel population genomic approaches relying on massive panels of genome-wide loci afford an opportunity to identify intra-Palaearctic barriers and contrast them among different species. The last two decades have seen an increase in molecular studies on population genetic divisions of wide-ranging species complexes, revealing a variety of phylogeographic patterns traversing the Palaearctic2. In this study, we used thousands of genome-wide markers to elucidate fine-scale population structure across the Palaearctic in two migratory shorebirds – the whimbrel  and Eurasian curlew . The Eurasian curlew breeds in temperate grassy mires and wet meadows, with a relatively short-distance migratory behavior. Contrarily, the whimbrel generally breeds in extensive bogs in woodlands and tundra of subpolar latitudes, predominantly wintering at (sub-)tropical latitudes  are phenotypically distinct as the palest taxa53. By comparing the phylogeography between two congeneric shorebird species with a similar biology but important differences in breeding habitat, we aim to shed light on habitat-specific effects of Quaternary climate oscillations on biotic differentiation across the Palaearctic.There continues to be a dearth of comparative research on Palaearctic biota across different habitat types to help shed light on the historic mechanisms that have shaped their evolutionary historiesdes Fig. . An exceA total of 54 double digest restriction-site associated DNA sequencing (ddRADseq) libraries spanning 38 whimbrels, 15 Eurasian curlews and one common redshank were successfully prepared  and western  populations  analysis identified a barrier of low effective migration overlapping with and slightly east of the continental divide between Europe and Asia, indicating an area where the decay of genetic similarity with increasing geographic distance is significantly higher than expected under exact isolation-by-distance . At other values of K, the three Eurasian curlew populations remained discrete  between genetic and geographic distance in Eurasian curlews. Further investigation into isolation by distance using EEMS analysis, accordingly, found no evidence for significant corridors or barriers within the Eurasian curlew’s range  and may disperse more widely among different breeding populations74. Previous shorebird studies have found mating system and migratory strategy to have an effect on population differentiation48. These are, however, not pertinent to differences in genetic structure between whimbrels and Eurasian curlews as both species are monogamous and overlap in non-breeding habitats74.In contrast, the Eurasian curlew emerged as three distinct populations Fig.  correspoalboaxillaris and steppe curlew suschkini, from their respective conspecifics. However, only a single steppe whimbrel sample with moderate sequence coverage was available and deeper sampling will be needed for more authoritative statements on its genomic distinctness. The steppes south of the Urals are arid and experience warm summers75. The pale plumages of these subspecies are consistent with Gloger’s Rule76, which predicts that more arid environments harbour less heavily pigmented populations. The discordance between morphological and genetic differentiation may indicate a rapid evolution of ecomorphological adaptations controlled by few genes77 or phenotypic plasticity in response to environmental conditions83. The steppe whimbrel is now known to be an exceedingly rare taxon84. Even if future research upholds a lack of deep genomic differentiation in steppe whimbrels, their distinct plumage still warrants conservation efforts to preserve unique ecomorphological adaptations85.In both species, we found no evidence for a deep genomic separation of the palest taxa breeding in the South Urals, steppe whimbrel rogachevae from central Siberia and phaeopus breeding in sub-Arctic Europe  and blood samples were loaned  was performed with Pippin Prep . Pools were combined at equimolar volumes. The final library was spiked with 30% phiX and 150 bp paired-end reads were sequenced on a HiSeq. 4000 Illumina platform (Genome Institute of Singapore).DNA extractions were performed with the DNEasy Blood & Tissue Kit  with an additional incubation step with heat-treated RNase. We prepared a reduced representation library using a modified ddRADSeq protocolFastQC 0.11.5 (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). As all bases had a mean phred score >30 , no truncation was necessary. Raw sequences were demultiplexed and cleaned using process_radtags in Stacks 1.4495. We mostly discarded reads with uncalled bases (–c) but rescued reads if their barcodes contained two or fewer mismatches from the barcodes provided (–r). Only samples with more than 400,000 reads were retained for downstream analysis. We then aligned sequences to the Ruff Calidris pugnax genome97 using BWA-MEM 0.7.199 to identify homologous regions. Alignment quality was checked with samtools flagstat and sorted according to coordinate order with samtools sort in samtools 1.3.1100.We checked the accuracy of sequencing of each base via phred scores with ref_map.pl in Stacks, followed by filtering using populations. We retained loci present in 90% of individuals (–r) and with a stack depth  of 10 and 5 for Eurasian curlews and whimbrels, respectively (see Supplementary Table 2 threshold of 0.9) using PLINK 1.9101. Using PLINK, we also quantified missing data per individual. Relatedness analysis was conducted to estimate identity by descent using maximum-likelihood (ML) estimation in ‘SNPRelate’ as implemented in R 3.5.1103  all whimbrels, (2) all Palaearctic whimbrels, (3) Palaearctic whimbrels in breeding areas only, and (4) all Eurasian curlews. Loci were identified from sequences aligned to the reference genome using –p 2) during SNP calling in populations. This practice mitigated low coverage and missing data in this sample and ensured that all loci identified would be informative for this taxon of interest. No population partitioning was implemented for Eurasian curlews during SNP calling.We aimed to resolve the genomic affinity of the palest populations breeding in the South Urals. However, one of the taxa in question, the steppe whimbrel, was only represented by one individual with moderate sequence coverage. Hence, we partitioned this individual from other whimbrels  simulations. Consensus structure results for each K value were obtained using CLUMPP 1.1.2106 and an optimal number of clusters was inferred where required54.To investigate population structure, we conducted PCA on three datasets: all whimbrels, only Palaearctic whimbrels, and Eurasian curlews, using ‘SNPRelate’. Population structure within Palaearctic populations of both species was further investigated in 107 by performing three independent chains of 8 million MCMC iterations with a 1 million iteration burn-in using 200, 400 and 600 demes. Results were checked for consistency across the different regimes implemented and for convergence of MCMC runs. Finally, results across runs were combined and visualized using ‘rEEMSplots’107.For analyses involving geographic information, only individuals from breeding localities in the Palaearctic were included. We tested for isolation by distance using a Mantel’s test with 999 replicates in ‘poppr’. We also implemented EEMSPyRAD 3.0.64108 to identify sequence data for phylogenomic analysis of all whimbrels109. The ddRADseq loci were assembled de novo using only the first read in each pair of paired-end sequences (ddrad) and an overall clustering threshold of 0.88 was applied. Loci had to be present in 90% of individuals (MinCov 26) with a minimum coverage of five per cluster (MinDepth 5) and a maximum of four undetermined (“N”) sites. A maximum of three shared polymorphic sites per locus was allowed (maxSH 3) to avoid inclusion of paralogs with fixed differences.We employed RAxML version 8.2.9110 using concatenated sequence reads identified by PyRAD. We applied two general time reversible models, with an optimisation of the substitution rate under a gamma distribution and a site-specific optimization of the substitution rate. A total of 1000 alternative trees were constructed in a rapid bootstrap analysis. The model with the lowest Akaike Information Criterion was selected and the best-scoring ML tree was visualised using Mesquite 3.2111.A ML tree was constructed for whimbrels in Supplementary information


FST values from multi-locus coalescent isolation-with-migration models, and couple them with estimates of quantitative trait divergence, or PST, to test drift as the evolutionary process responsible for phenotypic divergence in island populations of the Pteronotus parnellii species complex. Compared to traditional comparisons of PST to FST, the migration-based estimates of FST are unidirectional instead of bidirectional, simultaneously integrate variation among loci and individuals, and posterior densities of PST and FST can be compared directly. We found the evolution of higher call frequencies is inconsistent with genetic drift for the Hispaniolan population, despite many generations of isolation from its Puerto Rican counterpart. While the Hispaniolan population displays dimorphism in call frequencies, the higher frequency of the females is incompatible with sexual selection. Instead, cultural drift toward higher frequencies among Hispaniolan females might explain the divergence. By integrating Bayesian coalescent and trait analyses, this study demonstrates a powerful approach to testing genetic drift as the default evolutionary mechanism of trait differentiation between populations.Determining the processes responsible for phenotypic variation is one of the central tasks of evolutionary biology. While the importance of acoustic traits for foraging and communication in echolocating mammals suggests adaptation, the seldom-tested null hypothesis to explain trait divergence is genetic drift. Here we derive  Determining the evolutionary processes shaping phenotypes has been a central task of genetics since its inception Wright . While tIn the absence of selection, traits—including acoustic traits—will evolve through neutral processes, reflecting population genetic structure and effective population size  and Puerto Rico . Within minutes of capture, skin tissue was sampled using an Acu-Punch sterile, disposable 2-mm skin biopsy punch . Punctures were transferred to ~0.7 g indicator silica for desiccation and transport . Recordings were made with a Larson Davis 6.25 mm instrumentation microphone (model no. 2520) and Larson Davis preamplifier (model no. PRM 422), and amplified with a PCB Piezotronics Signal Conditioner (model no. 480E09). Calls were recorded onto a laptop computer using a National Instruments A–D card (DAQCard-6062E), recording at 356 kHz using BatSound Pro v3.31 (Pettersson Elektronik). We placed bats into the cage and allowed them to calm briefly. With the microphone held ~10 cm from the bat’s head, we recorded three to five files of 5 s in duration.We analysed the vocalizations using the callViewer-18 script compiled with Matlab by Mark Skowronski. The spectrogram parameters of the program were set at a window length of 3 ms and an FFT size of 16,384 points resulting in a resolution of 22 Hz. Automated detection parameters set a frame rate of 10,000 frames per second (resulting in a frame duration of 0.1 ms), a bandpass filter between 20 and 130 kHz, and a minimum energy of 45 dB. We focused frequency analysis on the constant frequency (CF) portion of the second harmonic of the calls, as this is known to be the highest amplitude and most consistent component of the biosonar calls of this species, and relates directly to the best frequency of the cochlea, auditory nerve, and central nervous system , among other parameters. Segments of calls were included in analysis when their slopes were zero for a minimum of 1 ms (10 consecutive frames). Within a single call, variations in the frequency of the CF component were accepted if they shifted within one increment of resolution, provided that the shift persisted for a minimum of 1 ms. These variations correspond to Doppler-shifts induced by motion of the bat in the cage. All frames of a call deemed to be of constant frequency were averaged and this value was taken as the frequency of the CF portion of the call.Taq polymerase and primers for the entire mitochondrial cytochrome b (cytb) gene, and partial sequences from four nuclear loci: stat5a, plcb4, rag2, and atp7a. Primers and amplification conditions for each locus have been described in detail elsewhere , and following the manufacturer’s protocol for animal tissues , 472 bp for rag2 , 307 bp for plcb4 , 429 bp for stat5a , and 637 bp for atp7a . Sample sizes for the nuclear loci are given as numbers of sequenced chromosomes. McDonald and Kreitman ; in no case did we find evidence of selection . The remaining data were then filtered using the Perl script IMgc  for each of the populations from Hispaniola, Puerto Rico, and the most recent common ancestor, m  in each direction, and τ . Priors were set to uniform distributions (U)  for θ and migration parameters, and U for τ. Five independent runs were allowed to burn-in for ~5 million steps each, after which each Markov chain Monte Carlo (MCMC) search was allowed to continue for ~10 million steps. Each run consisted of 30 heated chains with heating parameters ha = 0.975 and hb = 0.75. Relative substitution rates for each locus were estimated in IMa2 and converted to substitutions/site/year based on a cytb rate of 2.99 × 10−8 substitutions/site/year from a fossil-calibrated phylogenetic analysis of Noctilionoidea including P. parnellii s.l.  were converted to natural parameters  as described above using the geometric mean of locus-specific substitution rates (=5.67 × 10−7 substitutions/locus/year) and a generation time of 2 years. After verifying that all runs converged on similar posterior distributions, we used IMa2 to calculate the joint posterior densities for each parameter based on the 47,983 coalescent genealogies resulting from all five separate runs.Previous analyses indicated the two populations are completely discontinuous  from IMa2  of populations, in which:Nm from FST values have long been criticized as overly simplistic  from the multi-locus sequence data, including a correction for finite number of subpopulations  will exceed the neutral genetic divergence (FST), indicating the comparison is robust, and thus greater confidence in the inference of quantitative divergence exceeding neutral genetic divergence.The divergence in a quantitative, heritable trait is expressed as an analogue of the  Brommer . In thisical Eq.  for the  Brommer :4\documeFST values from posteriors for directional migration rates  models , and the splitting time (τ) for the two daughter populations. The scaled population size parameter for Hispaniola  was consistently estimated to be greater than that for Puerto Rico . Assuming a mean multilocus substitution rate of 1.13 × 10−6 substitutions/locus/generation, these θ estimates correspond to modal effective population sizes of ~ 138,000 individuals in the Hispaniolan population  and ~28,000 individuals in the Puerto Rican population  is much larger in area than the range of P. portoricensis (Puerto Rico). These analyses converged on an estimate of the scaled splitting time parameter τ = 0.703 ; this corresponds to a splitting time of ~1.24 Ma  = 1.875  and mPR = 0.025 . These estimates correspond to estimates of the effective number of migrants per generation (Nm) of NmDR = 0.325  and NmPR = 0.049  ≥ 405.6, P value < 2e-16, Fig. F = 0.436, P value = 0.512, Fig. F = 2.01, P value = 0.162, Fig. F = 0.258, P value = 0.614, Supplementary Figure F = 7.39, P value = 0.010, Supplementary Figure t test  = 17.46, P = 1.042e-07; Wilk’s Λ = 0.467, partial η2 = 0.53).Empirical frequency distributions of echolocation frequencies showed complete separation between Puerto Rican and Hispaniolan recordings Fig. . AnalyseKruschke , we founKruschke . The firFST values , while the c / h2critical values of almost all other comparisons were several times larger, and even >1 for the body size data from Puerto Rico. Comparisons of the distributions of PST and FST show overlap in distributions ≥4.9% for body size variables and Puerto Rico, while the lowest overlap corresponded to PST call frequency and FST Hispaniola  overcomes the limitations of traditional approximations by integrating both stochastic variation from individual sampling and variance across loci and by allowing for asymmetric rates of gene flow  from the sequence data , and like the transformed Bayesian posterior distribution of Nm for Hispaniola, the global G′ST shows no overlap with PST for the call frequency, but does overlap with PST for both body mass and forearm length. Unlike our approach using transformed posterior distributions, the traditional approach assumes an equilibrium model with gene flow being equal in both directions, and so would lead to rejection of genetic drift for the Puerto Rican population with a c / h2critical value of 0.03. In contrast, the method presented here accounts for directional differences in FST that lead to a sixfold higher c / h2critical for the Puerto Rican (0.080) compared to the Hispaniolan population (0.014), resulting in much greater robustness for the rejection of drift for the latter.An analysis using the traditional method of estimating a distribution of genetic differentiation illustrates some benefits of the proposed approach. We estimated global  Hedrick , and booFST distributions from Bayesian posterior distributions of Nm may be practically implemented in future studies. Here, we chose the IMa2 software package to estimate distributions of Nm because the underlying demographic model is directly applicable to the sampled populations of P. portoricensis and P. pusillus, two sister species with no genetic structure within islands and DNA sequence data well described by the infinite sites model. In other applications, more complex demographic scenarios and/or different data types may apply different methods to estimate the Nm posterior . Regardless of the specific method used to estimate these posterior distributions, we urge that the data be tested for neutrality, that appropriate demographic models be used, and that appropriate substitution models be specified in the analysis. In addition, we expect that, regardless of the method used, Bayesian estimates of the Nm composite parameter will yield more precise posteriors with larger datasets, particularly with an increase in the number of variable markers rather than an increase in the number of sampled individuals (Knowles and Carstens Our method of deriving Pteronotus pusillus) and Puerto Rican (P. portoricensis) populations in the P. parnellii species complex (Dávalos Previous analyses had shown genetic differentiation between the Hispaniolan ( Dávalos . We conf Dávalos , but if  Dávalos , and wou Dávalos . In cont Dávalos . These oPteronotus pusillus and P. portoricensis are allopatric, insular populations with a long history of isolation for approximately 1.2 million years (Fig. c / h2 < 1or additive proportion of heritability (Table ars Fig. . This loars Fig. , ambientars Fig. , acoustiars Fig. , ecologiars Fig. , female ars Fig. , and culars Fig. . Crucialars Fig. . Here, tty Table . This fiPteronotus pusillus. Male calls, however, were significantly lower in this population even after accounting for their somewhat smaller body size (Table As high-frequency calls are an honest signal of body condition, females seem to select for higher-frequency males in at least one constant-frequency echolocating bat species (Puechmaille et al. ze Table . If thisze Table . In thisze Table .FST and thereby test genetic drift as an evolutionary mechanism to explain phenotypic divergence across multiple traits. This approach directly calculates the extent of overlap between posterior distributions of FST and PST. Coalescent-based analyses revealed isolated populations with minimal subsequent migration, leading to high FST values, while trait analyses showed acoustic divergence and sexual dimorphism in call frequency. Comparisons between FST and PST rejected genetic drift as a probable evolutionary mechanism behind acoustic divergence in Pteronotus pusillus, and somewhat less robustly in P. portoricensis. The significantly higher calls of the Hispaniolan population, together with lower calls of males make female choice an unlikely evolutionary mechanism, and instead leave open the possibility of female-mediated cultural drift. By integrating Bayesian coalescent and trait analyses, this study demonstrates a powerful approach to testing genetic drift as the key evolutionary process in trait differentiation.In conclusion, we have introduced a Bayesian coalescent-based approach to estimate Sampling locations, morphological data, R scripts and Bayesian models available from Dryad: 10.5061/dryad.fg53g0j.cytb: KX787941-KX787953, KX787967-KX787994, stat5a: KY077747- KY077757, plcb4: KY077790-KY077814, rag2: KY077758-KY077789, and atp7a: KY077742-KY077746.DNA sequences: Genbank accessions We have deposited the primary data underlying these analyses as follows:Supplementary tables and figuresFigure S1Figure S2Figure S3Figure S4


Anastrepha obliqua (Macquart), the West Indian fruit fly, is one of the most economically important pest species in the Neotropical region. It infests an extensive range of host plants that include over 60 species. The geographic range of A. obliqua is from northern Mexico to southern Brazil and includes the Caribbean Islands. Previous molecular studies have revealed significant genetic structure among populations. We used sequences from a fragment of the mitochondrial protein-coding gene cytochrome c oxidase I to estimate structure and genetic diversity of A. obliqua populations from Brazil. We analyzed a total of 153 specimens from the Amazon Forest, Atlantic Forest, Cerrado, and Caatinga biomes. Our study revealed weak genetic structure among the A. obliqua Brazilian populations sampled. Collections from the Amazon Forest had similar haplotype diversity compared to previously reported estimates for collections from the Caribbean and both populations are also closely related to each other, thus challenging the hypothesis that A. obliqua originated in the Caribbean and then moved to other regions of the Americas. Therefore, further evidence is necessary to draw a definite conclusion about the putative center of origin for A. obliqua. Additionally, we suggest a putative historical migration from the west to the east for the A. obliqua Brazilian populations, which could explain the high genetic diversity for this fly in the Amazon Forest and low genetic diversity in the other Brazilian biomes. Anastrepha (Diptera: Tephritidae) is endemic to the Neotropical region where it is widespread and comprises around 296 species [Anastrepha have been reported infesting over 275 hosts in 48 plant families [Tephritidae is one of the largest families of Diptera with over 4.500 species worldwide and includes some of the world’s most economically important fruit pests , 2. The  species . In BrazAnastrepha obliqua (Macquart), the West Indian fruit fly, is the second most polyphagous species within this genus in Brazil and therefore one of the most economically important pest species. It belongs within the fraterculus taxonomic group, which encompasses a total of 34 formally described species that can be distinguished only by morphological characters [A. obliqua vary along a geographic cline and even from specimens reared from same host in Brazil [A. obliqua has been reported infesting 49 hosts [aracters . The acun Brazil . This spn Brazil . It has n Brazil , all of n Brazil . It infen Brazil –8. In BrA. obliqua populations [fraterculus group [A. obliqua individuals were clustered into two clades: (I) a clade containing Brazilian A. obliqua, Anastrepha fraterculus (Wiedemann), and Anastrepha sororcula specimens; and (II) a monophyletic lineage of four A. obliqua from Mexico, Brazil, and Colombia. Therefore, A. obliqua populations were not recovered as a monophyletic group raising the question of whether A. obliqua is a cryptic species complex.Molecular studies using mitochondrial DNA (mtDNA) sequences revealed a high genetic diversity among ulations ,10. Baseus group , eight Aet al. [fraterculus group, suggesting there could be cryptic species in A. obliqua. The study also showed high haplotype diversity among specimens from the Caribbean and thus those authors raised the hypothesis that the Caribbean, most likely the Greater Antilles, could be the center of origin of A. obliqua. In a recent study, Scally et al. [A. obliqua and interspecific relationships within the fraterculus group using a multi-locus data set . The results from the nuclear loci support monophyly of this species, however, analysis of the mtDNA sequences showed high variability revealing mito-nuclear discordance in A. obliqua. Those authors suggested that mitochondrial introgression between A. obliqua and A. fraterculus is one possible explanation for this discrepancy and alternatively incomplete lineage sorting could have caused the high mitochondrial diversity observed in A. obliqua.A molecular study by Ruiz-Arce et al.  on the Wy et al.  analyzedA. obliqua populations has also been documented in behavioral and ecological studies. In Mexico, A. obliqua matings took place in the early morning [A. obliqua populations in Brazil mated in the afternoon [A. obliqua in Colombia, which formed two groups and probably more than one biological entity could be present within the nominal species [Variation among  morning , contrasfternoon . Additio species .et al. [A. obliqua populations are structured considering different Brazilian biomes. An in-depth knowledge of the genetic diversity and the population history of a species are important for pest management because it improves the capacity of action agencies and pest programs to predict how it will react to environmental changes [A. obliqua populations in four Brazilian biomes: Amazon Forest, Cerrado, Caatinga, and Atlantic Forest.The study by Ruiz-Arce et al.  detected changes , 16. HerA permit for the collection of insects was provided by SISBIO (permanent permit number 30206–1 to RA). No collections involved endangered or protected species.Anastrepha obliqua samples were collected in 33 localities covering four distinct Brazilian biomes . A partial fragment of the Cytochrome oxidase subunit I (COI) was amplified by the Polymerase Chain Reaction (PCR) using primers: LCO-1490 (5-GGTCAACAAATCATAAAGATATTGG-3) and HCO-2198 (5-TAAACTTCAGGGTGACCAAAAAATCA-3) [2, 2.5 μl of 1 mM of dNTPs, 1.0 μl of 20 μM of each primer, 2 U of Taq DNA polymerase (Fermentas), and 2 μl of DNA. Cycling conditions for amplification were 3 min at 94 °C, followed by 39 cycles of 1 min at 94 °C, 1 min at 50 °C and 2 min at 72 °C, and a final extension step of 10 min at 72 °C. PCR products were purified using exonuclease I of Escherichia coli (EXOI) and shrimp alkaline phosphatase (SAP) (Fermentas/Thermo). Bi-directional sequencing was performed using the BigDye Terminator v3.1 Cycle Sequencing kit on an ABI 3730 of Life Technologies–Applied Biosystems at the Centro de Estudos do Genoma Humano, Universidade de São Paulo, Brazil. The forward and reverse sequences were imported to BIOEDIT v7.0.5.2 [n biomes . Adults AATCA-3) . PCR wasv7.0.5.2  to produwww.fluxus-engineering.com) to infer the relationships among haplotypes and their geographical distribution. We examined genetic structure among populations using F-statistics [et al. [2P model was used to calculate pairwise distances using MEGA v6 and Arlequin v3.1.We initially delineated populations according to Brazilian biomes, as follows: Amazon Forest (AM), Cerrado (CE), Caatinga (CA), and the Atlantic Forest (AF). We constructed a haplotype network using median-joining method  in Netwoatistics  and Analatistics , consideatistics  implemenatistics . Bayesiaatistics  to inferatistics  with 100 [et al. . The K2PAnastrepha serpentina (Wiedemann) obtained from the Genbank (GenBank: RX130130) was used as the outgroup.BI was carried out with two simultaneously runs of 10 million generations each with four chains and sampled every 1,000 generations. We used Tracer v1.6  to examiS) for the entire dataset and for each group using DNAsp v5.0 [Finally, we calculated the nucleotide diversity (π), number of haplotypes (h), haplotype diversity (Hd), and number of polymorphic/segregating sites  analysis  implemencer v1.6  was usedA. obliqua haplotypes (Our sequence data set comprised 621 base pairs (bp) of the mtDNA COI fragment from 153 specimens. The sequenced region contained 27 variable sites defining 20 different haplotypes. No premature stop codons or indels were found in the COI fragment. The most common haplotype (H1) was detected in 66% (n = 101) of the samples and it was observed over a widespread geographic range and among all geographic groups . The collections from AM showed 15 haplotypes, out of which 14 were singletons. The CE, CA, and AF populations showed two, four and two haplotypes, respectively . The aveplotypes .Our unrooted haplotype network  demonstrA. obliqua Brazilian populations  and unimodal curves that fit a sudden expansion model. Conversely, the mismatch distribution for the AM group showed a bimodal shape  indicating that there was gene exchange between the A. obliqua populations. Lack of population structure could be due to human-aided dispersal and/or that these populations cross naturally in the field.Previous molecular studies using mitochondrial DNA genes have shown a relatively high genetic diversity of the West Indian fruit fly ,10. Our et al.  study anThe fly populations from the CE, CA, and AF biomes had low mtDNA haplotype and nucleotide diversity values, which could indicate that these populations have experienced a recent population expansion after a small effective population size or a bottleneck effect. Low haplotype and nucleotide diversity can indicate that demographic events have affected populations, such as a decline in population size or founding effect . When thA. obliqua populations from Mesoamerica and Western Mexico [A. obliqua populations from Northeastern and Southeastern Brazil and also observed low genetic diversity using nuclear genes, which could be associated with a founder and bottleneck events followed by a recent population expansion, thus corroborating our results on A. obliqua populations from eastern Brazil .Low levels of genetic diversity were detected in n Mexico . Similarn Mexico  analyzedBactrocera dorsalis (Hendel) and Anastrepha ludens (Loew) [A. obliqua [A. obliqua. Resolving the origin and pathway for these sequence types may require additional and unlinked markers. With respect to collections gathered from the biomes included in our study, the haplotypes diversity estimates suggest the Amazon Forest is probably the source of this species in this region.Considering our sampling, the populations from the Amazon region showed the highest levels of haplotype (Hd = 0.8298) and nucleotide (π = 0.00847) diversity. These populations had several private haplotypes, which could have resulted from limited migration and gene flow among them. Ancestral populations generally show high levels of genetic diversity in contrast with populations established more recently . Moreoves (Loew) ,42. Base obliqua . Interes obliqua . Both thA. obliqua Brazilian populations. Long-distance dispersal events tend to result in reduced genetic diversity due to sequential founding events and genetic drift [et al. [A. obliqua populations were incongruent since the mismatch distribution was unimodal and consistent with a population expansion event, but the neutrality tests were not significant. Hence, based only on the demographic tests both scenarios on the origin of A. obliqua (Caribbean versus Amazon) are equally parsimonious.The negative values of neutrality tests and unimodal mismatch distribution suggest that the populations from eastern South America (CA+CE+AF) have undergone a recent demographic expansion. In contrast, the AM group exhibited multimodal mismatch distribution patterns suggesting demographic equilibrium or a stable population, indicating that these populations have been stable over time. Thus, we detected signals of demographic expansion in the East  but not in the West (AM) for ic drift . The tes [et al.  for the A. obliqua Brazilian populations. Similarly, Ruiz-Arce et al. [A. obliqua populations from Mesoamerica, suggesting a bottleneck event followed by expansion. Changes in the geographic and climatic patterns over time might be associated with the distribution of genetic variability in A. obliqua populations from South America.Our BSP analysis revealed stability followed by a recent population expansion in the e et al.  verifiedA. obliqua and A. fraterculus [As our results are based solely on mtDNA sequence data, they should be viewed with some caution, since our conclusions might be biased due the intrinsic mutation rate, mode of inheritance, and effective population size of mtDNA markers . Additioterculus  and thatS1 Table2P model.Analyses were conducted using the K(DOCX)Click here for additional data file.


After 568 AD the Avars settled in the Carpathian Basin and founded the Avar Qaganate that was an important power in Central Europe until the 9th century. Part of the Avar society was probably of Asian origin; however, the localisation of their homeland is hampered by the scarcity of historical and archaeological data. Here, we study mitogenome and Y chromosomal variability of twenty-six individuals, a number of them representing a well-characterised elite group buried at the centre of the Carpathian Basin more than a century after the Avar conquest. The studied group has maternal and paternal genetic affinities to several ancient and modern East-Central Asian populations. The majority of the mitochondrial DNA variability represents Asian haplogroups . The Y-STR variability of the analysed elite males belongs only to five lineages, three N-Tat with mostly Asian parallels and two Q haplotypes. The homogeneity of the Y chromosomes reveals paternal kinship as a cohesive force in the organisation of the Avar elite strata on both social and territorial level. Our results indicate that the Avar elite arrived in the Carpathian Basin as a group of families, and remained mostly endogamous for several generations after the conquest. After 568 AD, the Avars settled in the Carpathian Basin and founded their empire which was a powerful player in the geopolitical arena of Central and Eastern Europe for a quarter of a millennium2.The hypothesis of the Asian origin of the Avars appeared as early as the 18th century. Since then various research approaches emerged indicating different regions as their home of origin: i.e. Central or East-Central Asia (see SI chapter 1b for explanation of this geographic term). This debate remained unresolved, however a rising number of evidences points towards the latter one4.The history of the Avars is known from external, mainly Byzantine written accounts of diplomatic and historical character focusing on certain events and important people for the Byzantine Empire. As an example, the description of a Byzantine diplomatic mission in 569–570 AD visiting the Western Turkic Qaganate in Central Asia, claimed that their ruler complained about the escape of his subjects, the Avars5.The linguistic data concerning the Avars are limited to a handful of personal names and titles  mostly of East-Central Asian origin, known from the same Byzantine written accounts. The available evidence is not sufficient for defining the affiliation of the Avars’ language, however the scarce remains suggest Proto-Mongolian, Proto-Turkic and/or a still undefined Central Asian or Siberian language7. This group of lavishly furnished burials -the focus of our study- is located in the Danube-Tisza Interfluve  and is dated to the middle of the 7th century , showed Central and North European genomic ancestry in recent studies13. Their maternal gene pool showed predominantly Southern- and Eastern-European composition, with Asian elements presenting only 15.3% of the variation. Another recent study of a mixed population of the Avar Qaganate from the 8th-9th centuries from present-day Slovakia showed a miscellaneous Eurasian mtDNA character too, with a lower frequency (6.52%) of East Eurasian elements14.Few ancient DNA studies have focused on the Avars, and these studies analysed only the control region of the mitochondrial DNA (mtDNA). One research focused on a 7th-9th century Avar group from the south-eastern part of the Great Hungarian Plain (Alföld) of the Carpathian Basin15, while three are located east of the Tisza river where a secondary power centre can be identified in the 7th century16 . Seven out of ten sites are located in the Danube-Tisza InterfluveOur main research questions concern the origin and composition of this ruling group of the Avar polity. Was it homogeneous or heterogeneous? Is it possible to identify a migration and if yes what can we tell about its nature? Were maternal and paternal lineages of similar origin? Did biological kinship play a role in the organisation of this elite stratum?Using whole mitogenome sequencing and Y chromosomal short tandem repeat (Y-STR) and single nucleotide polymorphism (Y-SNP) analyses, our current research focused on the uniparental genetic diversity of the leading group of the Avar period society from the 7th century AD.The studied Avar group comprises 18 males and 8 females, based on the combined anthropological and genetic data. Sex determination resulted from morphological analyses and shallow shotgun sequencing. Mitochondrial genomes of 25 individuals were sequenced, using a hybridisation capture method (42x average coverage), and Y chromosome variability of 17 males were analysed ; five samples to macrohaplogroup D , and three individuals to F (one F1b1b and two F1b1f). Each haplogroup M7c1b2b, R2, Y1a1 and Z1a1 is represented by one individual. One further haplogroup M7 (probably M7c1b2b) was detected (sample AC20); however, the poor quality of its sequence data (2.19x average coverage) did not allow the further analysis of this sample.European lineages  are represented by the following haplogroups: H (one H5a2 and one H8a1), one J1b1a1, two T1a (two T1a1), one U5a1 and one U5b1b Table . One fur17, because this haplotype is shared by the most populations and it is more diverse than Cluster 2.The haplotype diversity of 22 samples used for mitogenome sequence-based analyses was 0.987. On the other hand, Y-STR analyses of 17 males gave evidence of a strikingly homogeneous Y chromosomal composition , all of them buried in the Danube-Tisza Interfluve Table . We founA third N-Tat lineage (type III) was represented only once in the Avar dataset (AC8), and has no direct modern parallels from the YHRD database. This haplotype on the MJ network  detected through FGC29201, Y16310/Z35292 and Y16327/Z35300 SNPs in three individuals  chromosomes is close to the Transbaikal region of Southern Siberia and Mongolia. A recent Y-SNP study of Central Asian populations by Balinova et al. found this N-F4205 subhaplogroup also frequent (52.2%) among the nomadic herder Tsaatans , living in Mongolia and the Tuva Republic19. We conclude based on our STR network that most Avar N-Tat chromosomes probably originated from a common source population of people living in the Mongolian and Baikal area, in line with the results of Ilumäe et al.18.We classified the Avar samples to downstream subgroup N-F4205 within the N-Tat haplogroup, which is supported by our Y-SNP data  within N-Tat lineage for all samples is 7.0 kya (95% CI: 4.9–9.2 kya), considering the core haplotype (Cluster 1) to be the founding lineage. (See detailed results on the N-Tat and N-F4205 haplotypes in the SI chapter 1f.) Y haplogroup N-Tat has not been detected in large scale Eurasian palaeogenomic studieset al., subhaplogroup Q1a2-M25 constitutes 43.5% of paternal lineages of the Tsaatans population19.Two males (AC4 and AC7) from the Transtisza group belong to two different haplotypes of Y-haplogroup Q1 Table . Both Q1We detected two identical F1b1f mtDNA haplotypes  and two identical C4a1a4 haplotypes  from the same cemetery of Kunszállás; these matches indicate the possible maternal kinship of these individuals. A further pair is AC9 female and AC14 male, who shared the same T1a1 mtDNA lineage.The detected Y chromosomal lineages probably all belong to one shared N-Tat haplotype at Kunszállás , which indicates that it was a cemetery used by both maternally and paternally closely related individuals.13, because the latter shows predominantly Eastern European maternal genetic composition. This result is comparable with the archaeological record, i.e. this Avar population buried the deceased in niche graves, following Eastern European traditions.The elite group originating mainly from the Danube-Tisza Interfluve does not exhibit a genetic connection to the previously investigated small Avar period population from southeast HungaryOne sample in our dataset (HC9) comes from this population, and both his mtDNA (T1a1b) and Y chromosome (R1a) support Eastern European connections. The observed genetic differences among the Avars correlate well with the cultural and physical anthropological differences of this group and demonstrate the heterogeneity of the Avar population.11, which has more genetic affinity to other ancient European populations  with identical sequence to the Avar HC9, which might indicate the genetic continuity of certain maternal lineages between the 7th and 9th-10th centuries. Some further haplogroup-level matches exist between ancient Hungarians25 and Avars, but these do not mean close phylogenetic relationships. A possible continuity of the Avar population should be studied on a larger dataset covering the entire spectrum of Avar society.The overall mtDNA composition of the Avar elite group and the 9th-12th century populations of the Carpathian Basin differ significantly, population continuity is not observable. The T1a1b mtDNA phylogenetic tree contains one individual from the Hungarian conquest period  are common in the modern populations of East-Central Asia (Table 27 (see SI chapter 1c). Further DNA data from Central and East Asia are needed to specify the ancient genetic connections; however, genomic analyses are also set back by the state of archaeological research, i.e. the lack of human remains from 4th-5th century Mongolia, which would be a particularly important region in the study of the origin of the Avar period’s elite28.There is a single sequenced genome from Mongolia  dated to the 5th century that belongs to mtDNA haplogroup D4b1a2a1, whose frequency had probably increased in the Asian population ca. 750 years agoia Table . This reWe performed Principal Component Analysis (PCA) using the Avar dataset and haplogroup frequencies of another 47 ancient groups Table . The AvaBecause whole mitochondrial genome datasets of ancient populations are still scarce , we applied a smaller reference dataset (n = 932) in the genetic distance calculations using full mitogenomes see Fig. .ST = −0.00116, p = 0.42382), and a group of medieval samples from the Central Asian Steppe and the Tian Shan  from most ancient populations. Only two groups from Central Asia have non-significant differences from the Avar elite: one group containing Late Iron Age samples (originating from the Late Iron Age and Hun period from the Kazakh Steppe and the Tian Shan)  plots based on linearised Slatkin Fs Tables  and S5 oAlthough the DNA composition of modern populations can only give us indirect information about past populations, the lack of ancient Asian reference data leads us to use modern populations as proxy to ancient peoples in the phylogeographic analyses.We performed PCA and MDS with modern mitogenome datasets Table , S7 and 29. Shared lineages with the Avars might refer to the relative proximity of their homelands, or admixture of the Yakuts with Mongolians before their migration to the north. The mtDNA results of Yakuts show a very close affinity with Central Asian and South Siberian groups, which also suggests their southern origin23.Modern East Siberian populations, namely Yakuts and Nganasans are close to the Avar elite based on their haplogroup composition Figs. . Phylogeet al. recently summarised the genetic research of the Buryats, who show connections to Chinese and Japanese but also to Turkic and Mongolic speaking populations30. Yunusbayev et al. concluded based on genome wide genotype data that Tuvinians, Buryats and Mongols are autochthonous to their current southern Siberian and Mongolian residence31. The Buryats represent a population that did not migrate much in the last millennia; therefore, they can be a good proxy for the medieval population of South Siberia. Unfortunately, modern whole mitogenomic data are underrepresented from the East-Central Asian region (e.g. Mongolia), which region was  an important source of early medieval nomadic migrations.The genetic connection of the Avars with Russian Trans-Baikalian Mongolian-speaking Buryats and Barguts is displayed on C4a1a, D4i and D4j phylogenetic trees Figs. , S10c. T32 is shown by the detected low genetic distance between the Avar elite group and modern Uyghur individuals compared to the other 43 modern populations ns Table , Fig. 6.ns Table . The NJ ns Table b-h, S10o34, the connections of which are shown on the MDS plot  Table 34, the clot Fig.  and on tlot Fig. . Interesree Fig. .The Central Asian Kazakhs and Kyrgyz cluster together with the Avar group on PCA plots and clustering tree Figs. . UnfortuCaucasian genetic connection is presented only by one sample on the phylogenetic tree of haplogroup H8a, where the AC17 sample from the Avar period is situated on one branch that also contains ancient and modern Armenians Fig. .36. The Avar Qaganate can be regarded as a composition of heterogeneous groups regardless of linguistic, cultural or ethnic affiliations2. The highest social stratum however shows a homogeneous cultural and anthropological character. The historical sources suggest that this group introduced titles and institutions of a nomadic state in the Carpathian Basin2.In 568 AD, the Avars arrived in the Carpathian Basin, which was inhabited in the 6th century by mixed Barbarian and Late Antique (Romanised) groups19.The paternal genetic data of the studied Avar group is very homogeneous compared to the maternal gene pool, and is mostly composed of N-Tat haplotypes, which uniquely occur in the Danube-Tisza Interfluve. N-Tat haplotype II could signalize shared common genetic history of the Avars with ancestors of Mongolians and Uralic populations Figs. , S4. BasThe analyses of the other Q1b1a3 L330 haplogroup suggest an Altaic or South Siberian paternal genetic origin of the juvenile Avar male individual Fig. .The maternal gene pool of the investigated Avar elite group is more complex, it contains both Western and Eastern Eurasian elements; nevertheless, Eastern Eurasian maternal lineages dominate the diverse spectrum in 69.5%. Only loose connections are detectable between the Avar elite and the available mtDNA data of ancient populations in Eurasia, with the highest affinities to Central and East-Central Asian ancient populations. The comparisons are encumbered by the geographically and chronologically scattered nature of the available ancient whole mitogenomes Fig. . The comDue to the lack of ancient reference data, we also compared the maternal and paternal genetic data of the investigated elite group to modern Eurasian populations. The results support the East-Central Asian genetic dominance in the genetic composition of the Avar elite group. The Avar period group shows low genetic distances and close phylogenetic connections to several modern East Eurasian populations. Phylogeographic data on individual mtDNA lineages point toward East-Central Asian populations such as Uyghurs and Buryats. Further genetic connections of the Avars to modern populations living to southwest (Hazara) and north  of East-Central Asia probably indicate common source populations.7. The crescent-shaped gold sheet from Kunbábony interpreted as an insignia could indicate a more symbolic connection towards Mongolia and Northern China . Ring-pommel swords covered with golden or silver sheets were used as prestige goods from the Carpathian Basin as far as the Altai Region, or even China, Korea and Japan Fig. 7. The crina Fig. 28,37,38.In this study, we produced novel information regarding the social organisation of the Avar elite stratum. The new Y chromosomal data suggest that this Avar-period elite group had strong biological ties, possible paternal kinship relations. Therefore, we conclude that the Avar elite probably inherited their power and wealth through the paternal line. Paternal kinship was detected to be an organizing rule within the communities of two studied sites, Kunszállás and Kunpeszér.2. It is widely accepted that kinship ties  were of higher importance for nomads than for settled groups. Kinship is a social segment that is defined based on the proximity of individuals to each other in the system of biological relationship. Among the nomadic societies of Central Asia, strict patrilineality has been observed, but matrilineal lineages were also recorded and noted in certain cases. Kinship is also a way of understanding the world and creating order in it, and also served as a framework within which social order was maintained41.Avar society has been understood in the framework of nomadic societies42. The idea of a chosen or sacred segment is a known political notion in Central Asian nomadic societies41.While nomadic societies are described as segmentary, they are not necessarily egalitarian. In segmented societies the rank and the relationship between individuals and/or groups is determined as well as their place in the wider society, thus a system is created, where no one has his/her exact equal. The kinship system differentiates between superior and inferior lineages and emergence of a dominant lineage could occur. The paternal kinship relations among the investigated individuals buried in lavishly furnished graves indicate the presence of such a dominant lineage in Avar society. The importance of kinship in nomadic societies has been challenged, but never in the case of the elite stratumBased on our current knowledge about the previous populations of the Carpathian Basin, we presume that the Asian components of the Avar elite entered the region with the Avar conquest. Considering that the investigated Avar elite group was at least 3–4 generations younger than the time of the Avar conquest, mitochondrial DNA of both males and females gives us valuable information about the social structure of the Avar period elite.Our results suggest that the Avar elite did not mix with the local 6th-century population for ca. a century and could have remained a consciously maintained closed stratum of the society.The dominance of the Asian mtDNA lineages  suggest, that only after that period did the number of intermarriages with local women increase, and the Avar elite was mostly endogamous (within the stratum of Avars of Asian origin) in the Carpathian Basin. Moreover, while it does not contradict the models of elite migrations, it shows that the Avar elite arrived in family groups, or at least men and women migrated together.43, but could have led to different representational forms. To get more insights and define the uniqueness of the Avar period elite’s paternal and probably maternal gene pool, the common people of Avar society have to be studied as well.It is important to note that the investigated elite group consists of mostly male burials (n = 18); the women belonging to the same social stratum is archaeologically barely visible. From the investigated sites in the Danube-Tisza Interfluve, only one female individual was buried with high value artefacts; the other richly furnished female burials are located in the Transtisza region. Male power appeared in the public sphere, while female power manifested probably in the family sphere. This did not mean, however, that women could not wield public power/influenceWe present here the first complete mitogenome dataset with Y-STR and Y-SNP profiles from the Avar period of the Carpathian Basin. Our results attest that the maternal and paternal genetic lineages of the Avar period elite in the Carpathian Basin were different from the European uniparental genepool of their period, and were mostly of East-Central Asian origin. The detected East-Central Asian maternal and paternal genetic composition of the elite was preserved through several generations after the Avar conquest of the Carpathian Basin.This result suggests a consciously maintained closed society, probably through internal marriages or intensive contacts with their regions of origin. The results also hold valuable information regarding the social organisation of the Avar period elite. The mitochondrial DNA data suggest that not only a military retinue consisting of males migrated, but an endogamous group of families. The Y-STR information supports that the Avar elite was organized by paternal kinship relations, and kinship also had an important role in the usage of the elite’s cemeteries. The kinship relations among the investigated elite individuals buried in lavishly furnished graves indicate the presence of a dominant lineage that correlates with the known political notion of a chosen or sacred segment of nomadic societies.Our first genetic results on the leading class of the Avar society provide new evidence for the history of an important early medieval empire. Nevertheless, further genetic data from ancient and modern Asian populations and from the Avar period of the Carpathian Basin is needed to describe the genetic relations and the genetic substructure of the Avar-period population in greater detail.15. The primary focus of the sample selection was to target all available members of the highest elite group of Avar society.The studied individuals were excavated at ten different sites . Seven out of ten sites are located in the Danube-Tisza InterfluveOut of the 26 investigated Avar period samples, eight individuals show similar archaeological characteristics with weaponry covered with precious metal foils, ornamented belt sets and drinking vessels made of gold or silver . The wealth of the 50–60 years old male from Kunbábony is outstanding with the 2.34 kilograms of gold buried with him , that are not characteristic to the 6th century local populations and are rare in the 7th century as wellTo have a better understanding of this elite group, we later collected samples from 18 individuals from the same region from one of the sites where the elite burial was unearthed as part of a larger burial ground  and from the neighbouring Transtisza region, a secondary power centre , with skulls with similar morphological traits (see Table Twenty-six samples were collected from ten different cemeteries dated to the Avar period (7th-8th centuries) according to their geographical position, grave goods, funerary custom and anthropological characteristics  and/or bleach and irradiated with UV-C light. All steps were carried out in separate rooms. In order to detect possible contamination by exogenous DNA, one extraction and library blank were used as a negative control for every batch of five/seven samples. Haplotypes of all persons involved in the ancient DNA work were determined and compared with the results obtained from the ancient bone samples.All stages of the work were performed under sterile conditions in a dedicated ancient DNA laboratory  following well-established ancient DNA workflow protocolsUsually, petrous bone fragments of the temporal bones were used for analyses, except for three individuals where teeth and long bone fragments were collected because the skulls were not preserved Table .et al.47 with some modifications described also by Lipson et al.46. DNA libraries were prepared using UDG-half treatment methods48. We included library negative controls and/or extraction negative controls in every batch. Unique P5 and P7 adapter combinations were used for every library49. Barcode adaptor-ligated libraries were then amplified with TwistAmp Basic (Twist DX Ltd), purified with AMPure XP beads (Agilent) and checked on a 3% agarose gel. The DNA concentration of each library was measured on a Qubit 2.0 fluorometer. In solution hybridisation method was used to capture the target sequences that covered the whole mitochondrial genome and 564 SNPs on the Y chromosome  was ordered from CustomArray Inc. Amplification of the bait happened as in Fu et al.50. Captured samples as well as raw libraries for shotgun sequencing were indexed using universal iP5 and unique iP7 indexes49. NGS sequencing was performed on an Illumina MiSeq System using the Illumina MiSeq Reagent Kit v3 (150-cycles).The DNA extraction was performed based on the protocol of Dabney me Table  as descrwww.nevgen.org. We searched for STR haplotype matches in YHRD database (YHRD.ORG by Sascha Willuweit & Lutz Roewer).AmpFLSTR Yfiler PCR Amplification Kit (Thermo Fisher Scientific) was used for the Y chromosome STR analyses. We followed the instructions of the manufacturer’s user manual, except applying 34 cycles for PCR amplification instead of the standard 30 cycles protocol. Fragment analyses of PCR products were performed on a 3130 Genetic Analyzer in accordance with the manufacturer’s instruction. Data evaluation, allele sizing and genotyping were determined by using GeneMapper® ID v3.2.1 software (Applied Biosystems). We amplified and analysed each sample at least twice and alleles were designated according to the parallel analyses with minimum detection threshold at 50 RFU. STR results are seen in Table https://github.com/jstjohn/SeqPrep), allowing a minimum overlap of 5 bp and minimum length of 15 bp. Then, the reads were filtered by size and barcode content using cutadapt version 1.9.151, allowing no barcode mismatch, and a minimum length of 15 bp. BWA version 0.7.12-r103952 was used to map the capture sequencing reads to the Cambridge Reference Sequence (rCRS) and the shotgun sequencing reads to hg38 and hg19 (latter without merging) human genome assembly allowing a 3 bp difference in seed sequence, 3 bp gap extension and 2 gap opening per reads. The downstream analyses including SAM-BAM conversion, sorting, indexing and PCR duplicate removal was performed by samtools version 1.653.The final BAM files were obtained by a custom pipeline for both shotgun and capture datasets. The paired-end reads were merged using SeqPrep master (https://github.com/broadinstitute/picard) and GATK version 3.654. The presence of a deamination pattern was estimated by MapDamage version 2.0.8 (https://ginolhac.github.io/mapDamage/) and summarised in Table schmutzi in most cases; therefore, the final validation of the mitochondrial sequences was performed by eye on the final bam files. The shotgun sequencing provided a raw estimate of the endogenous content and genetic sex determination according to Haak et al.9. These data are summarised in Table For capture data, indel realignment was performed using Picard tools version 2.5.0 (55 and RSRS56 (with a minimum variant frequency of 0.7 and minimum coverage of 5×) were generated by Geneious 8.1.7 software (https://www.geneious.com/). The whole mitochondrial fasta sequences were submitted to the NCBI GenBank under accession numbers MH894746-MH894769. The mitochondrial haplogroups were determined using HaploGrep (v2.1.1) (https://haplogrep.uibk.ac.at/) based on Phylotree version 1757.The consensus sequences (with a minimum coverage of 3×) and SNP calls according to rCRS58. Terminal SNPs were checked on the Y tree of ISOGG version 14.04 (https://isogg.org/tree/). All STR-based predicted haplogroups were supported by detected derived SNPs, except for samples RC26 and HC9. This can be explained by the overall low quality of DNA in these samples  were used for the Y-HD calculation.The haplotype diversity (HD) of 22 mitogenomes and 11 Y-STR haplotypes was calculated using the equation HD = n(1 − ∑Pi2)/(n − 1) by NeiST values were calculated based on 4,015 modern-day and 1,096 ancient whole mitochondrial sequences using Arlequin 3.5.2.261. The Tamura and Nei substitution model was used62 with a gamma value of 0.62, 10,000 permutations and significance level of 0.05 in case of comparison between the investigated Avar elite population and 43 modern-day Eurasian populations  and visualised on two-dimensional plots  were performed based on mtDNA haplogroup frequencies of 64 modern and 48 ancient populations. Thirty-two mitochondrial haplogroups were considered in the PCA of ancient populations, while 36 mitochondrial haplogroups in the PCA of modern populations were considered Tables -S3. The 65 and Euclidean distance measurement method were used based on haplogroup frequencies of ancient and modern populations and displayed as a dendrogram in R3.4.1 . We did not use bootstrap analyses due to the low quantity of informative positions, which highly biases the supporting values.Phylogenetic analyses aimed to detect close maternal relative lineages within the group of samples belonging to a certain haplogroup. All available human mitochondrial genome sequences in NCBI  were downloaded and sorted according to their haplogroup assignments. Multiple sequence alignment was performed for each sample set using the same procedure mentioned in the Population genetic analyses section, with an exception that instead of discarding sequences, the ambiguous bases were aligned manually. Then neighbour joining trees were calculated using the http://www.fluxus-engineering.com). Haplogroups predicted as 162 N-Tat samples from 12 populations, 127 N-F4205 samples from six populations and Q1b-M346 samples from 15 populations were included in the networks  networks were constructed using the Network 5.0 software (Supplementary Information.Csaky et al. Supplementary tables


The split time of the big (Capri) and small (Scopolo) islands was determined using geological events, like sea-level rises. To infer molecular evolution, we compared five complete mitochondrial genomes for each population to reconstruct the phylogeography and estimate the divergence time between island and mainland lizards. We found a lower mitochondrial mutation rate in Scopolo lizards despite the phenotypic changes achieved in approximately 8,000 years. Furthermore, transcriptome analyses showed significant differential gene expression between islet and mainland lizard populations, suggesting the key role of plasticity in these unpredictable environments.The ecological theory of island biogeography suggests that mainland populations should be more genetically divergent from those on large and distant islands rather than from those on small and close islets. Some island populations do not evolve in a linear way, but the process of divergence occurs more rapidly because they undergo a series of phenotypic changes, jointly known as the Island Syndrome. A special case is Reversed Island Syndrome (RIS), in which populations show drastic phenotypic changes both in body shape, skin colouration, age of sexual maturity, aggressiveness, and food intake rates. The populations showing the RIS were observed on islets nearby mainland and recently raised, and for this they are useful models to study the occurrence of rapid evolutionary change. We investigated the timing and mode of evolution of lizard populations adapted through selection on small islets. For our analyses, we used an  Island populations have provided insights on evolutionary processes such as species radiations  and the The ecological theory of island biogeography has been extended to an evolutionary scale, suggesting that populations on large and distant islands should be more genetically divergent from the mainland than populations on small and close islands . HoweverWhile the mainland populations evolve more slowly than their island relatives, small island populations evolve very quickly over brief periods, ranging from decades to thousands of years. The rate of evolution for island species slows down after the initial period of accelerated change, approaching rates observed on the mainland ,20. IsolThe changes related to the insular syndrome may be a direct effect of gene expression more than mutational events that affect the speed of phenotypic evolution . A speciad hoc model system, including two isolated monophyletic populations, one under RIS and the other not affected by the syndrome, may be an interesting case study.According to the RIS hypothesis, the rates of genetic changes in isolated populations should be less than rates observed in a population undergoing the syndrome. To verify this hypothesis, an Podarcis siculus): one of these living on the mainland and two on islands. The island closest to the mainland is a big island called Capri  meanwhile the second islet is Scopolo, close to Capri and inhabited by blue lizards (P. siculus subspecies have been described on the islet: P. siculus coerulea (Eimer 1872)  to infer molecular evolution across lineages of lizard populations and sequenced brain transcriptomes to investigate differential nuclear gene expression.The mtGenome is an excellent tool to study rates of molecular evolution, genomic structure and function, phylogenetic relationships and biodiversity . Moreovede novo identified transcripts, replacing traditional single-gene approaches [Transcriptome responses to environmental changes in lizards would elucidate how they adapt to local environments. Transcriptome-wide analysis allows the evaluation of gene expression levels of thousands of known and proaches . RNA-seqUnder our hypothesis, the adaptations developed by Scopolo population (under RIS) were the result of changes in gene expression ,24,25. TLizards were collected during March and April 2017, using a nylon loop and only 3-year-old males were considered for subsequent analyses. Lizards were aged using their snout-vent length (SVL) which is correlated with age , applyinSkeletochronology was performed both on phalanges and femora of euthanized animals. Bones were decalcified with 3% nitric acid for a time ranging between 1h30' and 3 h depending on their size, rinsed in tap water and cross sectioned using a cryostat. Diaphyseal cross sections (12 μm thick) were stained with Ehrlich's haematoxylin (20') and mounted in aqueous resin. Periosteal lines of arrested growth (LAGs) were then counted by using a light microscope equipped with an image analyser. We assumed that each LAG corresponds to an annual arrest of individual growth. Therefore, a lizard's age in years equals the number of visible LAGs. Growth rate (in mg/day) was estimated using least squares regression of body weights of individuals versus the number of LAGs transformed into days by assuming each LAG represents a 365-day interval. Individuals with shed tails and individuals in evidently poor conditions (either badly wounded or loaded with parasites) were excluded from the analyses.The animals were kept with the authorization of the Ministry of the Environment and Protection of Land and Sea  (prot. 4363/2015) and with the permission of the local county authority . Experimental procedures were approved by the Ethical Committee for Animal Experiments, University of Naples Federico II (ID: 2013/0096988) and were performed according to Italian law.The study area involved the mainland and two islands: Punta Campanella and Punta Licosa promontories represent the mainland ; Capri is a big island ; and Scopolo is an islet .A total of 15 mtGenomes  were sequenced. Whole mtDNA extractions  were performed using PureLink HiPure Plasmid DNA Purification Kits (Invitrogen), according to manufacturer’s recommendations, except for using 25 mg of tissue and initial mechanical disruption of samples for 1 h in a Phosphate Buffered Saline  Blank exBefore sequencing, we checked the concentration and quality of the DNA extracted using the Qubit Fluorometer 3.0 (Thermo Fisher Scientific) and the Agilent 4200 TapeStation system (Agilent Technologies), respectively.http://www.genomix4life.com/it/).Large-scale sequencing of the total mitochondrial genome was performed on the Illumina 2500 platform (Illumina) following the Nextera XT DNA Sample Preparation protocol as reported in manufacturer’s guidelines, at Genomix4Life s.r.l. (http://www.bioinformatics.babraham.ac.uk) was used to perform a quality control check on the short raw reads obtained from the high throughput sequencing.FastQC software v0.11.4  from this study have been deposited in GenBank (accession number MH046197 and MH157265 to MH157278).S) and of haplotypes (H), haplotype diversity (Hd), and variance of haplotype diversity (Hd variance).To assess the genetic variation of lizard mitogenomes, we measured the levels of molecular diversity of mtDNA in DnaSP: number of polymorphic sites  and nonsynonymous  mutations are neutral, then the ratio of synonymous to nonsynonymous polymorphisms within a species will be like the ratio of synonymous to nonsynonymous divergences between population (fixed differences). We also reported the neutrality index (NI) [Tests of selection based on McDonald-Kreitman  and Tajidex (NI) , which sTo infer modulation of gene expression between Scopolo and wild type lizards from mainland, we performed transcriptional profiling of three adult male brains from each population.http://www.genomix4life.com/it/), resulting in a total of 94,136,322 raw read pairs. Transcriptome sequencing data were deposited in NCBI SRA archive with the following accession numbers: Scopolo , Mainland . Read quality was assessed by FastQC software v0.11.4 (http://www.bioinformatics.babraham.ac.uk), and read quality trimming was performed by Trimmomatic software [de novo assembled using the whole quality trimmed read data set, concatenated into two paired fastq files. The Trinity assembler [P. muralis transcriptome dataset [To perform differential gene expression analysis, total RNA was extracted as described in Trapanese et al., 2017 . Indexedssembler , run wit dataset   as a prior estimate for the coalescence of all lineages, was performed in BEAST v.2.0 . Our resDue to the wide uniform priors, we used for the calibration points, the confidence interval remains large, depending on the type of analysis. However, the initial divergence within the ancestral population, from which Capri and Scopolo arose, was estimated to have occurred between approximately 3,000–6,000 years BP .Tests of selection on the mtGenome would greatly improve our understanding of how changes in gene polymorphism have been driven by selection.A McDonald-Kreitman test on all loci combined revealed a significant departure from homogeneity comparing Capri and Scopolo populations, with a significant NI value > 1 consistent with purifying selection . The maiIn other words, phenotypic variation of insular lizard is allowed only if it does not affect survivability. Accordingly, the Tajima’s D test had a significant positive value only for the Scopolo population , suggesting the action of balancing selection with alleles maintained at intermediate frequencies.We performed a differential gene expression analysis on brain tissues by RNA-seq to gain more information about lizards undergoing the RIS. We identified 603 upregulated and 499 downregulated transcripts in Scopolo specimens with respect to the mainland (Punta Licosa). In Individual organisms can mitigate the effects of environmental variations in two ways to weaken the selection pressure in a short time: they can move to a new site according to the habitat tracking hypothesis  or modulOn the contrary, in response to environmental factors, the regulation of the expression in some genes triggers specific adaptations, implying epigenetic mechanisms, which have been proposed as key in the plasticity model ,63. SomePodarcis siculus are not associated with mutations in the coding region of the MC1R gene but seem to be related to a concomitant variation of expression for this gene in skin tissue [Lizard populations on small islands undergoing the reverse island syndrome are ideal subjects for this evolutionary topic because rapid phenotypic changes are often visible in a short time ,64. Thesn tissue .We inferred the split time of the populations using geological dating ,45, assuSplitting events and length of branches have compared considering the geological scenario.Mitochondrial DNA topology confirms the geological data of land separation. In fact, a common ancestor between Scopolo and Capri is more recent than what unites Capri to Mainland.The estimation time of the coalescent lineage using mtGenomes suggests a lower rate of sequence divergence for Capri–Scopolo , calibrating the geological time clock on Capri–Punta Campanella that split 15,000 years BP, despite the extraordinary phenotypic variation observed in Scopolo lizards suffering RIS, characterized by strong melanization ,65.All the above could make it possible to interpret the observed genetic variation of Scopolo lizards in the context of adaptive plasticity. The differential expression of genes underlying some traits could lead to plasticity, adapting the same genotype to a wide range of environmental conditions. This plasticity could affect the dispersion of phenotypes under different selective pressures, promoting the genome evolution.If lizards change based on their plasticity, the severity of the selection on these phenotypes will also change; consequently, variation on mtDNA resulting from selection may arise more rarely/slowly than expected, as we found for the Scopolo population. Interestingly, a lack of nucleotide variation on mtDNA was observed in this population, which is suffering from purifying and balancing selection, as revealed by tests. The purifying selection shaped the mtDNA evolution in animal populations, because all mtDNA genes play crucial roles in the animal’s life ,66–68.Indeed, Tajima’s D test and McDonald-Kreitman test for Scopolo, agree with low number of mutations at the mtGenome level compared to the expected, even if we consider the effect of population subdivision and decline .The hypothesis of adaptive plasticity suggests that this is the earliest key step during adaptive evolution process, driving the persistence of the populations in new environments, since that selection fixes variations ,64,69–72We hypothesize that Scopolo lizards respond quickly to the environment by modulating the expression level of many genes, as highlighted by the differential gene expression analysis performed between Scopolo and mainland brain tissues. In fact, the two groups of lizards show a clear population-specific global expression pattern , in partHowever, our hypothesis of adaptive plasticity will require future explicit tests to clarify the specific environmental conditions under which the syndrome may (or may not) have evolved and the molecular mechanisms underlying plasticity.Recent studies suggest that phenotypic plasticity can be mediated through epigenetic effects –80, suchS1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.


Littorina sitkana have very little mitochondrial DNA (mtDNA) sequence diversity and show no significant population structure despite lacking dispersive planktonic larvae. A contrasting pattern of high mtDNA diversity in the northwestern Pacific (NWP) suggests that L. sitkana may have recently colonized the NEP from the NWP via stepping-stone colonization through the Aleutian-Commander Archipelago (ACA) following the end of the last glacial 20,000 years ago. Here, we use multi-locus sequence data to test that hypothesis using a combination of descriptive statistics and population divergence modeling aimed at resolving the timing and the geographic origin of NEP populations. Our results show that NEP populations share a common ancestor with a population of L. sitkana on the Kamchatka Peninsula ∼46,900 years ago and that NEP populations diverged from each other ∼21,400 years ago. A more recent population divergence between Kamchatka and NEP populations, than between Kamchatka and other populations in the NWP, suggests that the ACA was the most probable dispersal route. Taking into account the confidence intervals for the estimates, we conservatively estimate that L. sitkana arrived in the NEP between 107,400 and 4,100 years ago, a range of dates that is compatible with post-glacial colonization of the NEP. Unlike other congeners that are relatively abundant in the Pleistocene fossil record of the NEP, only one report of L. sitkana exists from the NEP fossil record. Although broadly consistent with the molecular data, the biogeographic significance of these fossils is difficult to evaluate, as the shells cannot be distinguished from the closely-related congener L. subrotundata.The demographic history of a species can have a lasting impact on its contemporary population genetic structure. Northeastern Pacific (NEP) populations of the rocky shore gastropod  Resolving the contemporary and historical factors affecting patterns of spatial genetic variation is a fundamental goal of population genetics and phylogeography . For neuInferences about the historic biogeography of plants and animals have relied heavily on mitochondrial DNA (mtDNA) sequence data. In addition to being relatively easy to amplify and sequence, the haploid structure and maternal mode of inheritance in most animals results in an effective population size that is one-quarter that of chromosomes in the nuclear genome . CombineOne of the major contributions of mtDNA phylogeography has been frequent characterization of low genetic diversity at high latitudes among plants and animals, a pattern widely interpreted as reflecting post-glacial colonization from low-latitude refugia e.g., . AlthougLittorina sitkana (Philippi 1846), population genetic sub-structuring is nearly non-existent in the NEP , mtDNA data from many  marine species are consistent with the idea that many nearshore benthic species likely retreated to southern refugia during the last glacial maximum (LGM), only recently returning to higher latitudes during the present warm interglacial e.g., . Among N the NEP , but muc the NEP . Based oL. sitkana. Although the smaller effective population size and the greater sensitivity to genetic drift make mtDNA especially useful for detecting range expansions, this aspect of mtDNA evolution, which makes it a “leading indicator” of evolutionary divergence  and seven in the northeastern Pacific (NEP) (Specimens of ic (NEP) . Collectic (NEP) , re-suspCYTB) and introns from three nuclear loci: 881 bp of adenosine triphosphate synthase subunit alpha (ATPSα), 612 bp of adenosine triphosphate synthase subunit beta (ATPSβ), and 597 bp of aminopeptidase (APN54). CYTB sequences were collected from new NWP samples  but previously published CYTB sequences were electronically-retrieved for samples from NEP populations . Mitochondrial DNA (mtDNA) was directly sequenced with both primers, assembled into contigs and edited with Sequencher 4.8 (GeneCodes Corp.), and aligned with other consensus sequences.Using previously published primers  and methE. coli cells (Promega) were transformed with the vector by electroporation. Sequences were edited and aligned with Sequencher and then aligned with ClustalX v1.83.1 (MN120839 –MN120881).For the nuclear DNA (nDNA), we cloned, plated, and sequenced PCR products from a subset of four localities in the west  and three in the east  for use in coalescent analyses and demographic modeling. PCR products were inserted into a vector with the pGEM Easy Vector System; Electromax DH10B  v1.83.1 . For eacπ) and haplotype (h) diversities, D, Fs, and R2. Significance of the descriptive statistics was evaluated with 10,000 permutations (Arlequin) or coalescent simulations (DNAsp) of the data. We then used an analysis of molecular variation (AMOVA) to estimate ΦST between all pairs of samples for all four loci. The best-fitting substitution model for each locus was then chosen with ModelTest version 3.8 (We used Arlequin version 3.5.1.2  and DNAssion 3.8  using thw) statistic (ATPSα (P < 0.035) and APN54 (P < 0.01) showed significant evidence of recombination whereas ATPSβ did not (P = 0.653). We then used an implementation of the four-gamete test . We then used PopART to construct unrooted minimum spanning networks for each locus  for the migration priors. Exponential priors are conservative with respect to inferring gene flow (a greatest prior probability at m = 0) but they do not discount the likelihood of gene flow given they lack an explicit upper bound.We used IMa2  to estimt) into demographic quantities  using a divergence rate of 1% per million years. This rate was chosen based on divergence rates inferred for protein-coding mtDNA genes in fossil calibrated phylogenies of gastropods  in which the run was repeatedly restarted by loading the state space from the previous run . After each 72-hour interval, convergence was assessed by comparing the parameter estimates and trend plots between the first and second half of the run. When a run had converged, we then restarted the run as before but with the sampled values from each previous run reloaded until 100,000 genealogies had been sampled. Convergence was also assessed by repeating each pairwise analysis three times with different random number seeds. We converted estimates of genetic diversity (Θ) and divergence times  modeling . The firDIYABC 2.0.4  available in DIYABC. The most likely scenario was identified with a polychotomous logistic regression , we used BC 2.0.4  to modelBC 2.0.4  for demogression  computedgression .We assessed confidence in the top two models by estimating the type I and type II error rates from 500 a posteriori simulations of each scenario . The falWe estimated population parameters using both IMa3 and ABC. For IMa3, we first estimated the priors for the demographic parameters using the best-fitting population tree inferred with IMa3 and DIYABC, with hyperpriors for all demographic parameters, such that the parameter priors are included in the state space and updated over the course of the run. The updated parameter priors from this first step are then used in a second IMa3 step in which population divergence times, effective population size, and gene flow are estimated. Convergence was assessed as described above and parameter estimates were obtained after 1,000,000 genealogies had been sampled. Effective population size and population divergence times were estimated with ABC using a local linear regression on the 1% closest simulated datasets after use of a logit transformation to parameter values .Littorina sitkana . All three nuclear loci showed spatial patterns of differentiation that were like those from the mtDNA, with relatively low and non-significant estimates of ΦST in the NEP, higher and more statistically significant estimates in the NWP, and similarly high but variable values between NEP and NWP samples, some of which were not statistically significant (Pairwise estimates of Φ samples . The majnificant –S9.2 Nm) between NEP and NWP populations rose asymptotically as 2 Nm approached zero (not shown), meaning that none were significantly different from zero , no single tree had relatively high support. However, the top 100 trees sorted by PPCP all included a monophyletic grouping of the three NEP populations  and the NWP population from the Kamchatka Peninsula (PET). Among these top 100 trees , 62 inclA posteriori simulations of Scenario 1 showed that the type I error rate was only 15.3%. Based on simulations of the other three scenarios, the average type II error rate was 16.9%.Scenario 1 received significantly greater support  over Scenario 3 , the next best-fitting population history . A postet1, t2, 2Nm) parameters either overlapped with zero or rose asymptotically as 2 Nm approached zero (not shown), indicating that no gene flow could be detected. The parameter estimates from DIYABC were similar, indicating that the NEP populations coalesced down to a common ancestor ∼22,400 years ago and merged with PET ∼54,400 years ago  to estimate demographic parameters with IMa3 and DIYABC. Going backwards in time, IMa3 inferred that NEP populations coalesced down into a common ancestor ∼21,400 years ago t1, , mergingears ago .Littorina sitkana recently colonized the northeastern Pacific (NEP) from the northwestern Pacific (NWP). The primary evidence for this conclusion is the extremely recent divergence times among all populations within the NEP and between all NEP populations and some populations in the NWP on Sakhalin Island and the Kamchatka Peninsula. This recent biogeographic connection is evident in the haplotype network of each locus, as the most common allele in the NEP is always the most abundant allele at three of four loci in our new sample from Kamchatka, the northeastern most sampled population in the NWP. Much smaller effective population sizes in the NEP is also consistent with the recent colonization hypothesis, as is the large reduction in population size in the ancestral NEP population  across many loci, creating a pattern similar to a founder effect. However, the most important piece of evidence in this study, evident in both the IMa3 and DIYABC analyses, is that the Kamchatka population (PET) shares a more recent common ancestry with NEP populations than the Kamchatka population does with any other NWP population, a result that can only be explained by the hypothesis that L. sitkana recently dispersed to North America from the NWP.Consistent with previous studies of  sitkana , we founL. sitkana in North America is probably best estimated by the full-likelihood methods , whereas cold glacial climates result in extinction of northern populations and the closure of this dispersal corridor . Althoug PET t2,  and the  t2, t1,  are bothar rates . Becausear rates , a more ar rates . Using aL. sitkana is the only species studied with genetic data that shows a phylogeographic history consistent with post-glacial dispersal in either direction between the NWP and NEP. Several other species with amphi-Pacific distributions show large differences in genetic diversity between NWP and NEP populations, but all show relatively high levels of genetic differentiation between NWP and NEP populations  has been reported from the NEP Pleistocene fossil record  inspected photographs of the fossils (UCMP B-7493) and were unable to provide a positive identification, as the relatively small and smooth shells could be either Columbia , suggesti debris . The geniversity  from wesL. sitkana is best explained by a recent and rapid range expansion from the NWP. Although the founder events associated with the spread of L. sitkana throughout the NEP depleted mtDNA and nuclear DNA diversity, the four loci that we used contained enough information to estimate the arrival of L. sitkana in North America between 107,400 and 4,100 years ago. Reductions in genetic diversity may ultimately limit range expansions , Tajima’s D, Fu’s Fs, and Ramos-Onsins and Rozas’ R2. Standard deviations in parentheses. Boldface indicates statistically significant values. See Table 1 for sample locality abbreviations. NWP: Northwest Pacific; NEP: Northeast Pacific.Mitochondrial cytochrome b (CytB) sample sizes , haplotype diversity (h), nucleotide diversity , Tajima’s D, Fu’s Fsstatistic, and Ramos-Onsins and Rozas’ R2 statistic. Standard deviations in parentheses. Boldface indicates statistically significant values. See Table 1 for sample locality abbreviations. NWP: Northwest Pacific; NEP: Northeast Pacific.Nuclear-encoded adenosine triphosphate synthetase subunit a intron sample sizes , haplotype diversity (h), nucleotide diversity , Tajima’s D, Fu’s Fs statistic, and Ramos-Onsins and Rozas’ R2 statistic. Standard deviations in parentheses. Boldface indicates statistically significant values. See Nuclear-encoded adenosine triphosphate synthetase subunit b intron sample sizes , haplotype diversity (h), nucleotide diversity , Tajima’s D, Fu’s Fs statistic, and Ramos-Onsins and Rozas’ R2 statistic. Standard deviations in parentheses. Boldface indicates statistically significant values. See Nuclear-encoded aminopeptidase intron sample sizes , haplotype diversity (h), nucleotide diversity  with ancestral populations numbered 7 to 12, ordered numerically as they coalesce going backwards in time. Note that each of the top 100 trees have a clade consisting of the three northeastern Pacific populations  and the easternmost population in the northwestern Pacific (3-PET), indicated by boldface.Best 100 tree topologies ranked by the product of the posterior clade probabilities (PPCP) for diverged populations of Click here for additional data file.