Lucanus cervus (L.), the stag beetle, is a saproxylic beetle species distributed widely across Europe. Throughout its distribution the species has exhibited pronounced declines and is widely considered threatened. Conservation efforts may be hindered by the lack of population genetic data and understanding of the spatial scale of population connectivity. To address this knowledge gap this research details the first broad scale phylogeographic study of L. cervus based on mitochondrial DNA (mtDNA) sequencing and microsatellite analysis of samples collected from 121 localities across Europe. Genetic data were complemented by palaeo-distribution models of spatial occupancy during the Last Glacial Maximum to strengthen inferences of refugial areas. A salient feature of the mtDNA was the identification of two lineages. Lineage I was widespread across Europe while lineage II was confined to Greece. Microsatellites supported the differentiation of the Greek samples and alongside palaeo-distribution models indicated this area was a glacial refuge. The genetic endemism of the Greek samples, and demographic results compatible with no signatures of spatial expansion likely reflects restricted dispersal into and out of the area. Lineage I exhibited a shallow star like phylogeny compatible with rapid population expansion across Europe. Demographic analysis indicated such expansions occurred after the Last Glacial Maximum. Nuclear diversity and hindcast species distribution models indicated a central Italian refuge for lineage I. Palaeo-distribution modelling results also suggested a western refuge in northern Iberia and south-west France. In conclusion the results provide evidence of glacial divergence in stag beetle while also suggesting high, at least on evolutionary timescales, gene flow across most of Europe. The data also provide a neutral genetic framework against which patterns of phenotypic variation may be assessed. Lucanus cervus L. (Coleoptera: Lucanidae) is distributed widely across Europe [L. cervus shows an aggregated distribution, wood management may be critical for the species to counter local extinction. Furthermore, in species with presumed high levels of genetic structuring a significant loss of cryptic diversity is expected under changing conditions, such as climate change, when conservation policies do not incorporate these genetic differences [The stag beetle, s Europe . Past ans Europe , 3. In ls Europe . Conservs Europe , distancs Europe  reportedferences , 7. On aferences . In addiPleistocene glaciations have influenced current patterns of genetic diversity and structure of fauna and flora , 10. DurThe sedentary nature of stag beetles , 16 is pL. cervus has been used to investigate processes like hybridisation [L. c. akbesianus from Turkey and L. c. fabiani (synonym L. pontbrianti) from France appeared to be different species, using cytochrome c oxidase subunit I (COI) sequences, while others could not be differentiated from L. c. cervus [L. c. cervus at both regional and local geographical scales across Europe using both mtDNA and nuclear microsatellites. We combine genetic data with ecological niche modelling to robustly identify patterns of historical vicariance, glacial refugia locations and postglacial expansion dynamics. This study informs spatial conservation through identification of unique components of the species’ biodiversity and provides a valuable genetic baseline for future studies on the species.To date, the genetic approach used in studies on disation  and locadisation , or the disation . The lat. cervus . In thisLucanus cervus cervus. Most samples were collected during the period 2001–2017, except for two samples from Craiova (Romania), collected in 1988, and six samples from Kursk (Russia), collected in 1990  [A haplotype network was constructed using the median-joining algorithm implemented in PopArt . Phylogedex.php)  with 100dex.php) .COI of tenebrionid beetles [8 generations, sampling one tree every 1,000 generations. After verifying parameter convergence and effective sample size (>200) using Tracer v.1.6 [4 generations using LogCombiner v. 2.4.8 [The Bayesian analysis was conducted with a Markov chain Monte Carlo (MCMC) phylogenetic search using BEAST v. 2.4.8 . We firs beetles . MCMC aner v.1.6 , we discer v.1.6  and visuer v.1.6 . Owing tv. 2.4.8 .h). The seven geographic regions were defined to increase and balance sample sizes of the groups while taking the genetic structure (see below) into account , pairwise genetic differentiation among populations (FST) was calculated using Arlequin v. 3.5.1.2 [Population structure was investigated using the Bayesian program BAPS v. 6.0 . We perf 3.5.1.2  with 10,Lucanus cervus. First, we assessed population expansion of each cluster, as was defined by BAPS clustering results, and of the total dataset using Arlequin to calculate Tajima’s D [COI sequences. Whilst unimodal distributions represent expanding populations, populations of constant size show a multimodal distribution [Several approaches were explored to investigate the demographic history of jima’s D  and Fu’sjima’s D  with 2,0ribution . Additioribution .9 for lineage I , except for the number of MCMC in one of both lineages, which was 1 x 10ge I see . SamplinST values with and without such loci using Genalex v. 6.503 [The DNA was eluted in 70 μl AE buffer. The integrity of DNA of 10% of the samples was assessed on 1% agarose gels. DNA quantification was performed with Quant-iT PicoGreen dsDNA Assay Kit (Life Technologies) using a Synergy HT plate reader (BioTek). Samples were genpotyped at the loci Lcerv-1, Lcerv-3, Lcerv-4, Lcerv-6, Lcerv-7, Lcerv-8, Lcerv-9, Lcerv-16, Lcerv-17, Lcerv-20, Lcerv-21, Lcerv-25, Lcerv-28, Lcerv-29, Lcerv-30, Lcerv-31 and Lcerv-36, described by McKeown et al. . The priv. 6.503 , 48.5 iterations. We chose the admixture model and used the correlated allele frequency option and the localities as prior information (locprior). The optimal K was determined based on the average natural logarithm of the probability of the data (Ln Pr(X|K)) and the Evanno method [ST values were calculated among populations with at least five samples and visualised in a principal coordinate analysis (PCoA) using Genalex v. 6.503. Significance of these values was assessed using 9,999 permutations.As with the mitochondrial sequences, we applied the BAPS v. 6.0 spatial clustering of individuals . The proo method  in STRUCo method . As the o method  is likelo method . Furtherhierfstat’ v. 0.04–22 [R), observed (HO) and expected heterozygosity (HE). Also the fixation index FIS was estimated. The same measures were estimated for the different predefined geographical regions  was present with a Mantel test based on 9,999 replicates implemented the R package ‘adegenet’ v. 2.0.1 [We calculated the following estimates of genetic diversity using the R package ‘ 0.04–22  for the  regions  followinv. 2.0.1 .L. cervus was performed using MaxEnt v. 3.4.1 [dismo’ v. 1.1–4 [Modelling of the geographical distribution of v. 3.4.1  implemenv. 1.1–4 , based oGSIF’ v. 0.5–4 [‘spThin’ v. 0.1.0 [MaxentVariableSelection’ v. 1.0–3 [Species records from the Global Biodiversity Information Facility (GBIF)  complemev. 0.5–4 , which cv. 0.5–4 . Since Gv. 0.1.0  which rev. 0.1.0 . Each lav. 1.0–3  that redv. 1.0–3 , 64. A r‘kuenm’ v. 1.1.1 (https://github.com/marlonecobos/kuenm) [In order to assess if the analysis region during the LGM has similar environmental conditions as it has at present and if extrapolation risks exist, we used the mobility-oriented parity (MOP) metric  implemens/kuenm) .L. cervus , while diversity decreased with increasing latitude   .According to the ML tree the haplotypes spread across Europe formed a clade with moderate support and was separated from the majority of the Greek haplotypes. The latter, however, seemed to be paraphyletic . This chST values (0.380–0.831) were found among populations of Greece (Neraida and Vlahava) and the remaining populations, representing the two lineages (ST = 0.488–0.787). Other population comparisons resulted in lower to non-significant FST values, except for the population from Essex which was well differentiated, even from other populations in the ‘UK’ region (FST > 0.193), Kent not included (FST = 0.039).High Flineages . PopulatIn lineage I, Tajima’s D and Fu’s FS were significantly negative indicating demographic expansion, while only the latter was significant in lineage II . FurtherST values after excluding Lcerv-16, Lcerv-29 or both. Because FST values hardly changed, both were included for further analysis. Mean error rate was 4% and no samples were discarded of a total of 416.Eight loci deviated from HWE in one to three localities of which four in Marmirolo and three in Vlahava. The locus deviating from HWE in three localities , Lcerv-30, also showed an elevated proportion of null alleles (> 20%) in 13 localities, while loci Lcerv-16 and Lcerv-29 showed such levels in respectively seven and eight localities. There was no sign of LD among pairs of loci. We discarded locus lcerv-30, but tested for changes in population structure through the calculation of pairwise FThe spatial clustering analysis using BAPS resulted in an optimum of four clusters . Some adST values ranged from 0.025 to 0.207  and central Italian populations . However, the Berezovka population in Ukraine from region ‘North’ displayed high FST values, although it was assigned to the most abundant and wide spread cluster. Sample size for this population was, however, only five.Pairwise Fto 0.207 . The pat results , differeE and AR were quite high in Lanouaille and Lurais in Central France of region ‘West’ (HE ranged from 0.579 to 0.596 and AR from 3.625 to 5.063). Multilocus FIS values were not significant in any sample. The HE and AR decreased with increasing latitude   , but no A total of 37,851 occurrence records was reduced to 16,493 records having unique coordinates with a precision of at least 2 km. After filtering these records to one occurrence per grid cell of 2.5 arc minutes, a total of 2325 points remained. This number dropped to 1279 observations when thinned using a nearest neighbour distance of 5 km . The modThe present species distribution model encompassed mainly the north-western part of Europe, but also northern Iberia, parts of Italy, east of the Adriatic Sea through to Albania and the north of Greece, Serbia and Bulgaria, and the Black Sea coast of Turkey . When prThe MOP analyses revealed areas during LGM with environments comparable to the present-day environments in southern Europe . TowardsThis study is the first phylogeographic investigation of stag beetle to incorporate both regional and fine scale sampling, and analysis of both mtDNA and nuclear genetic markers. mtDNA analysis revealed a clear spatial pattern wherein most of the European range was dominated by a single clade (lineage I). A second clade (lineage II) was found to be restricted to samples from Greece, with the differentiation of Greek samples also apparent at microsatellite loci. Microsatellite analysis further differentiated samples mainly from Central Italy that was part of lineage I on the basis of mtDNA. Nuclear data also subdivided Lineage I in two clusters. Apart from an increase in genetic clusters, differentiation among populations using nuclear markers was low to moderately high and was in agreement with the spatial structure results.Rosalia alpina was also found in north-western Greece by Drag et al. [Quercus spp., a major host species group of stag beetle, where only a limited increase in distribution range was observed [The populations in Greece did not seem to have experienced a demographic change and stayed largely isolated from populations in other regions, as the mtDNA and nuclear markers indicated. During the LGM, possible habitat is predicted to be limited to the north-western corner of Greece but was connected with a larger habitat area in southern Albania. The fact that the Greek lineage did not expand after the LGM is potentially due to the mountain ranges of northern Greece which were glaciated during the Pleistocene and could have acted as barriers isolating the populations on this part of the Balkan Peninsula . Similarg et al. . Howeverobserved . Likewisobserved . Thus thThe star-like topology of lineage I is compatible with a sudden range expansion, a scenario supported by neutrality test and mismatch distribution results. The expansion appeared to be of a demographic nature as well as of a spatial nature. The BSP showed a strong increase in population size after the LGM. All diversity measures had a significant negative relation to latitude which is in line with a general pattern of increased southern refugial richness found in studies investigating post-glacial recolonisation processes in the northern hemisphere , 72. DurOur results suggested that, apart from Greece, another refugium was located in southern Europe. Next to Greece, Italy seemed to hold the highest genetic diversity, mitochondrial as well as nuclear. According to our palaeo-distribution model, several parts of southern Italy seemed to be a candidate refugium, going from the north in Piemonte and Genoa, through Lazio and Umbria in Central Italy, to the utmost south in Calabria. This is assuming historical climate preference to be the same as current, where winter and summer temperatures  and humidity levels appeared to be important factors, which concurs with earlier findings , 73–75. Diversity measures of the mtDNA correlated positively with longitude. This seemed to exclude northern Iberia and south-west France as refugia, although the palaeo-distribution model showed high probabilities for the presence of stag beetle in those areas. The lack of genetic richness in these areas may reflect postglacial bottlenecks. Even though in Central France higher levels of nuclear gene diversity and allelic richness were present, we have no samples from the southwest of France that could corroborate the area to have been another refugium. If this were the case, it could explain why we found cluster 4 with individuals across region ‘West’, based on nuclear DNA, which could represent another lineage. Our genetic data might also not hold enough resolving power to distinguish a secondary refuge in the southwest of France and/or northern Iberia.L. cervus in ancient times. Female stag beetles especially have the tendency to stay close to their site of emergence [Quercus species, through Europe progressed [Although the species is attributed limited vagility, our results showed a substantial and rapid range expansion of mergence , 77, 78.mergence  and undemergence . Thomaesmergence  found thogressed , suitablogressed .ST values within clusters and the lack of a significant signal of IBD when Greek samples were excluded. This might suggest gene flow among populations with distances exceeding the assumed home range between them to be possible. Nonetheless, the FST values may represent the historical rather than the present pattern, due to shared alleles from an ancestral population. Furthermore, population differentiation was often significant, even among nearby populations (e.g. the Belgian populations). Finer scale resolution of the drivers of structure here will require further sampling.While mtDNA remains the classical phylogeographical marker it may lack the power to detect population structure on fine spatio-temporal scales, particularly in cases where individuals are derived from star-shaped phylogenies. Microsatellites, owing to their high levels of variability, may confer greater fine scale resolution. Founder effects and genetic bottlenecks during colonisation would have reduced local population genetic diversity and increased genetic differentiation among populations, especially when rates of population growth remained small after colonisation . HoweverL. cervus seemed to lie in south-eastern Europe where they resided during the LGM. The identification of such regions, especially in Greece and Italy, could help conservation managers to prioritise actions to preserve the current level of genetic diversity of the species. The study delivered new knowledge on the colonisation history of L. cervus in Europe after the LGM, as the data demonstrated that a single clade successfully colonised most of Europe. However, further research is needed on a more local scale to evaluate the drivers of fine scale structure among populations under current conditions and if effective population sizes are high enough to counter the negative effects of isolation.As for many other species hot spots of genetic diversity for S1 FigOnly bootstrap values greater than 70% are shown (100 replicates). The scale bar corresponds to the mean number of amino acid substitutions per site on the respective branch. Lineages I and II are indicated with blue and pink, respectively.(TIF)Click here for additional data file.S2 Fig(A) The BAPS results showing four clusters, (B-D) STRUCTURE results with (B) K = 2 main clusters involving all samples, and with (C) K = 2 subclusters and (D) K = 4 subclusters after excluding Greek samples assigned to one cluster in . The estimated probabilities of assignment to each cluster (indicated in different colours) are shown on the y-axes.(TIF)Click here for additional data file.S3 FigThis is based on STRUCTURE results (A) using all samples and (B) after excluding the Greek samples.(TIF)Click here for additional data file.S4 FigThe insert shows part of Southern England where grey crosses are occurrence sites before the final thinning step using the nearest neighbour distance of 5 km.(TIF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 TableSignificant values (p < 0.05) are indicated in bold.(PDF)Click here for additional data file.S4 TableSignificant values (p < 0.05) are indicated in bold.(PDF)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.


Bombus huntii in western North America. Pleistocene and contemporary B. huntii habitat suitability (HS) was estimated with an environmental niche model (ENM) by associating 1,035 locality records with 10 bioclimatic variables. To estimate genetic variability, we genotyped 380 individuals from 33 localities at 13 microsatellite loci. Bayesian inference was used to examine population structure with and without a priori specification of geographic locality. We compared isolation by distance (IBD) and isolation by resistance (IBR) models to examine population differentiation within and among the Bayesian inferred genetic clusters. Furthermore, we tested for the effect of environmental niche stability (ENS) on population genetic diversity with linear regression. As predicted, high‐latitude B. huntii habitats exhibit low ENS when compared to low‐latitude habitats. Two major genetic clusters of B. huntii inhabit western North America: (a) a north genetic cluster predominantly distributed north of 28°N and (b) a south genetic cluster distributed south of 28°N. In the south genetic cluser, both IBD and IBR models are significant. However, in the north genetic cluster, IBD is significant but not IBR. Furthermore, the IBR models suggest that low‐latitude montane populations are surrounded by habitat with low HS, possibly limiting dispersal, and ultimately gene flow between populations. Finally, we detected high genetic diversity across populations in regions that have been climatically unstable since the last glacial maximum (LGM), and low genetic diversity across populations in regions that have been climatically stable since the LGM. Understanding how species have responded to climate change has the potential to inform management and conservation decisions of both ecological and economic concerns.Climate oscillations have left a significant impact on the patterns of genetic diversity observed in numerous taxa. In this study, we examine the effect of Quaternary climate instability on population genetic variability of a bumble bee pollinator species,  SThe availability of microsatellite markers and environmental niche modeling techniques provides the opportunity to examine the effects of late Pleistocene climate variability on population genetic variability  are an appropriate organismal model for studying the effects of climate oscillations on contemporary bioclimatic niches, range dynamics, and population‐level divergence during the Quaternary. They are large‐bodied insects and have the capacity to disperse over several kilometers in search of food, nesting sites, and hibernacula   based on contemporary occurrence records and bioclimatic variables. Then, operating under the principle of niche conservatism  . We predict that high‐latitude populations will exhibit greater niche instability compared to low‐latitude populations since the LGM due to the presence of the glaciated regions in northern latitudes  and isolation by resistance models (IBR), respectively. Bumble bees are sensitive to environmental variation; thus, we predict that IBR will be a better predictor than IBD for examining population differentiation  map to test the hypothesis that climate instability predicts contemporary genetic diversity across B. huntii populations. We predict that patterns of genetic diversity can be explained by ENS patterns, with stable areas (low‐latitude regions) associated with low genetic diversity and unstable areas (high‐latitude regions) associated with high genetic diversity  and filtered for unique spatial coordinates  test. From each pairwise correlation coefficient estimate, we retained only one variable for the final model if r ≥ 0.75. Rather than randomly select a variable for the analyses, we chose to retain the variables that reflect annual and seasonal trends in precipitation and temperature as bumble bees are primarily active during the summer months, but also need to survive winter hibernation  statistic and a permutation of variable importance. AUC values closer to 0.5 (random) suggest poor predictive performance, whereas values closer to 1 (nonrandom) suggests high predictive performance. Permutation tests of variable performance employed within the MAXENT software platform used the training points to assess the relative contribution of each variable to the final averaged model in the context of the AUC statistic. A significant drop in the AUC statistic after a bioclimatic variable is removed suggests that the variable significantly contributes to the estimation of HS. Locality data are presented in decimal latitude and longitude with the WGS1984 coordinate system and the North American Albers Equal Area Conic geographic projection. Geographic visualization of the ENMs was made with ArcGIS v10.1 .Occurrence records were aggregated with 18 spatially explicit bioclimatic variables representing contemporary conditions (1950–2000) from the WorldClim v1.4 Bioclim dataset (2.5 arc minutes)  using the constraints of the contemporary bioclimatic associations of the B. huntii ENM mapped to paleoclimate data available within the WorldClim database  to 1 (high niche stability).Operating under the principle of niche conservatism  female bees were collected (n = 380). DNA was extracted from the mid‐leg of each bumble bee using a modified‐Chelex100™ protocol described in Strange, Knoblett, and Griswold  and separated on an Applied Biosystems 3730xl automatic sequencer at the Center for Integrated Biology at Utah State University. The allele sizes were scored manually using GENEIOUS v8 , to which an individual can be assigned based on their genotype without a priori delineation of populations. We set the model to run with 20,000 burn‐in steps and 100,000 samples, with 10 iterations for each K, where K ranged from 1 to 10. To determine the optimal K, the distributions of the probability of the data LnP(K) and ΔK  to infer poplation structure  iterations with every 1,000th iteration saved; our maximum Poisson at 100; spatial coordinate uncertainty at 1; maximum number of nuclei in the Poisson–Voronoi tessellation to 350; and applied the null allele, uncorrelated frequencing, and spatial models. Ten independent runs were performed for K values from one to ten. To determine the best fit of the microsatellite genotypes, we chose the independent run with highest log likelihood values following a burnin of 100, 200, 300, 400, and 500. In addition to examining log likelihood values, we assessed the MCMC plot to determine the stationarity of the model along the chain, as well as the number of populations inferred from an indendepent run.To compliment our STRUCTURE analysis, we also used the program GENELAND v4.05 . We first examined pairwise genetic differentiation by geographic distance by incorporating all the sampling sites genotyped in a single test of IBD. However, we also partitioned the dataset based on the STRUCTURE results to test for the effect of geographic distance on pairwise F’ST within a defined genetic cluster.We estimated pairwise population differentiation with multilocus d Smouse . We treaB. huntii. We implemented CIRCUITSCAPE in pairwise mode with an eight‐neighbor cell connection scheme using average resistances and set the raster conductance so that values closer 1 (high HS) would reduce resistance and values closer to 0 (low HS) would increase resistance. Significance of geographic distance or environmental resistance between paired populations was tested with Mantel tests with ecodist R library   fit to the genetic data. Higher r values suggest a better fit of the IBD or IBR variable to the pairwise F’ST estimates, granted that they are significant at an alpha level of p ≤ 0.05.Both IBD and IBR patterns are hypothesized to capture the relationship between gene flow and genetic drift in the context of geographic and environmental distribution of populations. Our inference on the best predictor  was based on the Mantel correlation coefficient (2.6AD) and (b) expected heterozygosity (He) using Nei's genic diversity metric. Given our unequal sampling across field sites, we used rarefaction to estimate genetic diversity by standardizing our estimates to four gene copies per population  effective allelic diversity . Unless otherwise indicated, all statistical tests conducted in our study were executed with the R statistical computing platform with the appropriate statistics libraries  for the training occurrences and 0.89 (±0.01 SD) for the test occurrences. The contemporary HS map is reflective of the range‐extent maps generated in the past , annual precipitation BIO 12), precipitation seasonality (BIO 15), precipitation of warmest quarter (BIO 18), precipitation of coldest quarter (BIO 19), mean diurnal range (BIO 2), max temperature of warmest month (BIO 5), temperature annual range (BIO 7), mean temperature of wettest quarter (BIO 8), and mean temperature of driest quarter (BIO 9). Average AUC for the subsampled contemporary ENM was 0.90 , we retained 26 populations (n = 364) for further analyses as they were represented by more than four individuals. In our analyses of the 26 populations, the locus BTERN02 did not amplify in >50% of the specimens genotyped and was removed from any further data processing. MICRO‐CHECKER results indicated that the locus BTMS0059 was suspected to have null alleles in 48% of the populations and was also excluded from further analyses.Of the original 33 sampling sites (p = 0.02) and Baker populations , but not in the remaining locus by population combinations (91.3% of the data). BTMS0062 showed significant devation from HWE in the Flagstaff population , but not in the remaining locus by population combinations (96.2% of the data). BT28 showed significant deviation from HWE in the Black Hills population , but not in the remaining locus by population combinations (95.0% of the data). BT10 showed significant devation from HWE in the Ayahualulco population , but not in the remaining locus by population combinations (96.2% of the data). Finally, BT30 showed significant devation from HWE in the Ada population , but not in the remaining locus by populations combinations (96.0% of the data). Of all the 1,106 locus by population combinations, we detected significant LD only between BTMS0066 and B96 in the Artega‐Galena population . We did not detect any significant LD in any of the remaining 1,105 loci by population combinations (99.9% of the data) after Bonferroni corrections. Given that deviations from HWE or LD are not consistent across any locus by population combination or locus by locus combination, respectively, we elected to retain 11 loci for further sibship and population genetic analyses.B124 showed significant deviation from HWE in the Ada . Thus, the final sample size used in subsequent analyses reflects the numbers of unrelated individuals (n = 350) available after the COLONY analysis  = −12,351.01). The ΔK statistic (=82.55) was greatest at K = 2, with significantly less explanatory power gained by including additional K clusters  of B. huntii's geographic distribution  are chiefly assigned to the “north cluster”  are chiefly assigned to the “south cluster” , fractional genotype assignment associated with the Cidudad Guerrero (CIG) population  formed a distinct cluster with Artega‐Galena (ARG) and General Zaragoza‐Miquiuana (GZM)   and Sierra Nevada Oriental   of all the iteration (1–10) and burnin combinations (100–500)  + Aspen Park ecoregion (EDM) to form cluster 1, the Black Hills population (BLH) to form cluster 2, the Ciudad Guerrero (CIG) population to form cluster 3 , Artega‐Galena (ARG) and General Zaragoza‐Miquiuana (GZM) populations to form cluster 4 , and the seven populations found in Trans‐Mexican Volcanic Belt to form cluster 5  revealed significant differences in population differentiation across samplings sites. Combining all 26 populations (North cluster + South cluster) in a single analysis found IBD to be significant   . We next partitioned the data by STRUCTURE genetic cluster assignment to examine cluster‐specific IBD and IBR models. However, because ARG and GZM were assigned to both north and south clusters    and IBR . However, the Mantel test r was much smaller than the South+ models stated above. Excluding ARG and GZM populations from the North cluster analyses found IBD to be significant     (North+)  Figure a, but no) Figure b. Howeve) Figure c and IBR) Figure d when in3.4AD and He found one population, Ciudad Guerrero (CIG), to be a sample outlier relative to the other 25 B. huntii populations. The CIG population is associated with low average AD (=1.41 ± 0.46 SE) and low average He (=0.37 ± 0.11 SE)  = 123.5, p < 0.001)  = 13.62, p = 0.001)  = 17.55, p < 0.001) . We found no difference between the North and South+ genetic clusters in measurements of contemporary mean diurnal range    Figure f and max) Figure g. Averag) Figure h. Furthe) Figure c.4B. huntii found that populations in regions that have been climatically unstable since the LGM  exhibit high genetic diversity, whereas regions that have been climatically stable since the LGM  exhibit low genetic diversity . Populations distributed throughout the north genetic cluster are associated with much colder annual temperatures, a pattern that is certainly correlated with increasing latitude  at distances greater than >500 km  across populations  within a matrix of unsuitable environments  the B. huntii ENS map predicts low‐latitude environments to be more climatically stable in comparison with high‐latitude environments over the past 22,000 years; (b) there are at least two genetic clusters (north and south) that a population can be assigned to based on a priori Bayesian analysis, with further evidence for genetic subdivision across Mexican populations found across different mountain ranges; (c) IBD and IBR models are significant across populations in the south genetic cluster, whereas only IBD is significant in the north genetic cluster; (d) genetic diversity increases with latitude and, therefore, decreases within increasing ENS; and (e) there are significant bioclimatic differences between the north and south genetic clusters, with southern populations inhabiting mesic environments with low variation in precipitation across seasons.A wealth of phylogeographic studies supports the hypothesis that Quaternary climate variability has shaped range‐wide patterns of population genetic diversity and divergence that are observed in extant populations and species. In our study, we discover clear geographic and environmental differences in the contemporary ,The results of this study contribute to our understanding of how historic and contemporary climate may have shaped the patterns of genetic variability observed in insects, an understudied group of animals, relative to vertebrate organisms. Bumble bees are a valuable model to study how climate variability affects patterns of genetic variability as they are highly sensitive to recent climate change. Over the past century, bumble bee populations have responded to a warming climate by emerging earlier in the spring, evolved shorter proboscis, and potentially shifted in latitudinal distribution  under a CC BY 4 license. Georeferenced records and associated WorldClim variables are available on FigShare  under a CC BY 4 license.Microsatellite genotypes and collection locations are available on FigShare ( Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


One of the best documented Indo-European civilizations that inhabited Bulgaria is the Thracians, who lasted for more than five millennia and whose origin and relationships with other past and present-day populations are debated among researchers. Here we report 25 new complete mitochondrial genomes of ancient individuals coming from three necropolises located in different regions of Bulgaria – Shekerdja mogila, Gabrova mogila and Bereketska mogila – dated to II-III millennium BC. The identified mtDNA haplogroup composition reflects the mitochondrial variability of Western Eurasia. In particular, within the ancient Eurasian genetic landscape, Thracians locate in an intermediate position between Early Neolithic farmers and Late Neolithic-Bronze Age steppe pastoralists, supporting the scenario that the Balkan region has been a link between Eastern Europe and the Mediterranean since the prehistoric time. Spatial Principal Component Analysis (sPCA) performed on Thracian and modern mtDNA sequences, confirms the pattern highlighted on ancient populations, overall indicating that the maternal gene pool of Thracians reflects their central geographical position at the gateway of Europe. Some archaeological sites associated with early farmers, as well as the earliest evidence of copper metallurgy in Europe, indicates that this area played a significant role both in the Neolithic and in the Metal Ages4. One of the best documented Indo-European civilizations that inhabited Bulgaria consists in the Thracians, whose cultural legacy is still evident in the modern society.Bulgaria is situated in the eastern part of the Balkan Peninsula, at the connection point between Southeastern Europe, Eurasian steppe, Anatolia and the Aegean islands. The presence of modern humans in this region is attested starting from 40 kya by the Paleolithic series at Bacho Kiro and Temnata Dupka Caves7, a period characterized by strong cultural changes and movements of people westward from the Steppe8. During the 5th and 4th millennium BCE, the inhabitants of the eastern region of Balkans were organized in different groups of indigenous people that, over time, were named under the single ethnonym of “Thracians”11. According to historical and archaeological sources, the Thracian culture flourished during the 2nd and 3rd millennia BCE13. The rich cultural and historical heritage, represented by fortresses and necropolises, as well as by the world-famous Panagyurishte, Valchitran, Lukovit and Rogozen treasures, dates back to this period. In the later periods, several populations  arrived in the Balkans, reaching the lands occupied by Thracians and mixing with them, thus influencing their cultural and biological identity11.Different theories have been historically proposed about the origin of the Thracians. Today it is assumed that the Thracian culture emerged and formed in the early Bronze Age14 and uniparental genetic markers17 of present-day Bulgarians, locate them between Eastern European and Mediterranean populations, with a particular affinity to the neighboring groups from Greece and the Balkans16. In addition, the Bulgarian maternal genetic pool particularly suggests a major Western Eurasian origin, tracing their ancestry to lineages that witness a complex genetic structure of the region today and reflect different peopling and admixture events from the Upper Paleolithic to the onset of the Neolithic and Post-Neolithic in Europe15. Recent genome-wide ancient DNA (aDNA) based studies on Southeastern Europe, have shown that Neolithic population from present-day Bulgaria was closely related with the northwestern-Anatolian-Neolithic ancestry that signals the spread of Early farmers across Europe, except for the individuals lived in the mid-sixth millennium BC in Malak Preslavets, who revealed a significantly higher level of hunter-gatherer-related ancestry than the other Balkan Neolithic individuals18. Starting from the early 3rd millennium BCE, migrations from the adjacent Pontic-Caspian and Eurasian steppe also played an important role in the transformation of the European genetic landscape, and the contribution of Steppe ancestry to Southeastern European populations increased particularly during the Bronze Age18. Although our understanding of the population and cultural dynamics occurred in the (pre-) history of Balkan Peninsula is starting to be increasingly elucidated, the genetic details on the local civilization remain unknown and this information is only partly available for the ancient (proto-) Bulgarian people19. We now have the opportunity to investigate the genetic structure of the Thracians, an ancient people that lasted for more than five millennia and whose origin and relationships with other past and present-day populations are still debated among researchers.Genetic analyses on both autosomal variationsTo investigate the genetic structure and population history of this ancient civilization, we analyzed 25 complete mitochondrial genomes from three Thracian necropolises Fig.  along wiWe successfully reconstructed complete or almost entire mitochondrial genomes for 26 individuals, 3 from Shekerdja mogila, 1 from Gabrova mogila and 22 from Bereketska mogila 21. In ancient samples, HV has been identified in one Mesolithic specimen from Sicily22 and in early Neolithic remains from Spain23, Germany8 and Russia24; Mathieson et al.18 reported a HV haplotype in one sample from Serbia dating from 5800 BCE. Moreover, haplogroup HV was observed in Copper Age specimens from Scotland, Hungary and Germany25 and in Hungarian and Israeli samples from the Chalcolithic period27The direct radiocarbon dating performed on the samples BM 44, SM 8.1 and GM 30.3 placed the remains at II-III millennium BC  Table . Phyloge28 and K1c is particularly common in Slavic-speaking countries. In ancient populations, the haplogroup K1c has been identified in six hunter-gatherers dated before the arrival of farming , in two Bronze-Age individuals from Hungary and Bulgaria31 and in two Central-Europe farmers associated with the Bell-Beaker culture33. The phylogenetic network analysis . All the haplotypes contain the expected K1c defining variants with the following private polymorphisms: GM-30.3, 309.1T, 310C, 7441T and 16519C; BM-51A, 16519C; BM-58A, 310C, 513.1CA and 16519C; BM-68, 5297T and 16519C. Nowadays the highest observed European frequency of the lineage K is in Bulgaria (13.3%)et al.34 suggested that during the LGM, haplogroup J sub-lineages arose in the Near Eastern refugia and recolonized Europe following the end of the last glaciation. In particular, J1c is not yet found in any hunter-gatherers, and the oldest individuals belonging to this lineage were found in Iran35 and in Anatolia30 dating to 8000-7700 BCE. It is possible that J1c arrived in Thracia from Anatolia during the early stages of the Neolithic expansion. The expansion of farmers played an important role also in the diffusion of haplogroup T, which has been found in three Thracian samples with the T2b (BM-15 and BM-59A) and T2e (BM-40) sub-lineages. Pala et al.34 particularly suggested that these lineages entered Europe from Anatolia in the Late Glacial period, and have been later diffused around Europe by Neolithic agriculturalists after intermingling with the inhabitants of Southeast Europe. Overall, while haplogroups H, K, J and T arose throughout the Neolithic increasing frequencies in different later communities and present-day European populations, the haplogroup U sub-lineages including U2, U4, U5 and U8 instead mark the genetic pool of European pre-LGM hunter-gatherers38.Three samples belong to haplogroup J1c . The SM-4 individual shows three personal transitions previously identified at positions 199C, 8730G and 13928A, and a private mutation at 13686G. The haplotypes of samples BM-31 and BM-61 fall within the sub-haplogropus J1c9 and J1c6, respectively. Currently, J1c, which dates to ∼16 ka ago, is found mainly in Europe, especially in Central Europe, Balkans and Ukraine, where it encompasses almost 80% of total J1 lineages. Pala 33. From an autosomal genetic perspective, besides showing the clear discontinuity of Paleolithic hunter-gatherers, recent genome-wide aDNA studies, have indeed outlined two opposite genetic components contributing to the European genetic ancestry: i.e. the ancestry of the Early European farmers related to Anatolian farmers and pre-farming Levant populations and, on the other side, the so-called Steppe ancestry eventually spread into Europe and Asia during the Bronze Age migrations of Yamnaya herders. In this scenario, the mtDNA genetic composition of analyzed Thracian population located them in the middle of this cline, clustering closely to the Peloponnese-Neolithic individuals (Peloponnese_N) and the Chalcolithic and Bronze Age populations of the Balkans . This finding seems to support a mitochondrial genetic profile of the Thracians that reflects their geographical position at the gateway of Europe. In a more general perspective, Thracians show a mtDNA genetic composition that is thus intermediate between the western Eurasian and the Mediterranean populations, documenting a prolonged interaction between people of these regions during the Bronze Age. On the other hand, the relatively higher distance with the Bronze Age populations from the Steppe (Steppe_EMBA and Steppe_MLBA), may support the hypothesis that the Thracians largely derived from local people11 with only a low percentage of the gene flow from the Steppe, at least during the early stages of their cultural development. However, in order to better explore this hypothesis, it is worth emphasizing that the perspective offered here by the analysis of mitochondrial genomes should be integrated by the possibility of testing the results obtained with Y-chromosome and autosomal genome-wide data. At this respect, several studies have indeed pointed out the sex-biased nature of the recent demographic changes and expansions in Eurasia43, thus suggesting possible sex-specific patterns of migration.The mtDNA genetic relationships between Thracians and the other ancient Eurasian populations  Bulgarian maternal gene pool and were mainly limited to HVS1 data from the medieval period19. In this study, we provide, for the first time, genetic details of an ancient population, which is particularly relevant from both a chronological and a geographical point of view. In accordance with their geographical location, Thracians show a genetic composition clearly intermediate between East Europe and Mediterranean, that suggests multiple admixture events and population movements occurred across what is now the modern day Bulgaria. Albeit limited to DNA transmitted along the female lines of descent, our genetic data on ancient Thracians provide a direct evidence of how the Balkan region has been a link between East and West Europe since the prehistoric time, and particularly during the Neolithic and post-Neolithic events. In this perspective, future studies will certainly benefit from the analysis of nuclear genome  in order to integrate the observed mtDNA genetic patterns within a more comprehensive overview and for testing the possibility of different sex-biased migrations in the area.Several studies demonstrated that Balkan Peninsula has been in different times a crossroad for people moving from and to Europe and beyondOverall, the ancient mtDNA data presented in this study integrate the existing database and has important implication for understanding the origins of the peopling in this part of Europe and for enlarging the knowledge on the ancient Bronze Age civilizations. How and to what extent ancient Thracian people has contributed to the present-day Bulgarian gene pool remain largely unknown due to the lack of large mitogenomes from contemporary populations from the area, necessary for a phylogenetically and demographically informative comparison.We processed 41 archaeological human remains, retrieved from three necropolises located in different regions of Bulgaria: Shekerdja mogila (SM), Gabrova mogila (GM), and Bereketska mogila (BM)  is a rectangular pit embedded in the mound embankment with a size of 0.48 per 1 m and a 0.21 m depth. The buried individual is a 3–4 years old child with remnants of red ochre on the bones and skull. Grave 24 (examined sample SM 24.2) is a mass grave; anatomically scattered bones and skulls of 7 individuals were found. One of the skulls has been placed in a large ceramic vessel. The anthropological research showed that the skeletons belong to two women (20–30 years old), one male (30–35 years old), three children (2.5 and 6 years old) and a neonate. Sample SM 24.2 belongs to 6 years old child with remnants of red ochre on the bones. Amulets of wolf/dog, short obsidian, clay pot and a fragmented ceramic bowl placed inside an urn were found close to the skeletons.The tumulus Shekerdja mogila is located near to the village of Kamen, 1 km north of the Sliven region in east-central Bulgaria. This necropolis is a mass grave in which many Early Bronze Age remains have been discovered. Funerary objects and a body in the hocker position , characteristic of the Thracian culture, were found in the southern side of the tumulus47. We analyzed 6 graves from the early Bronze Age. Grave No. 30 (examined sample GM 30.2) is located almost in the geometric center of the mound at 3.10 m from the central benchmark. The tomb pit has a rectangular shape and has east-west orientation. It is filled with dense loam soil and four adults were found at the bottom of the pit. The corpses are placed in a stretched position on their backs and their arms are bent in their elbows with slightly spaced legs. The buried individuals are male and the skeleton No. 2 (GM 30.2) is 20 years old. The inventory found in the grave consists of metallic, ceramic, bone and flint objects. A bronze ax was discovered, which is typical for the early Bronze Age. Amulets of wild boar teeth have been placed next to the skulls of the four skeletons.The tumulus Gabrova mogila is located near the Shekerdja mogila, north of the village of Kamen, Sliven region, east-central Bulgaria. This tumulus has many funerary and ritual objects typical of the Thracian period49. The burials excavated showed individuals in hocker position on the right and left side, in a bent position of the back, in double and multiple inhumations. Funerary context, as well as the presence of ochre and stone pounders undoubtedly bears witness to the contacts between Early Bronze Age Thracians and the North Pontic area, particularly the Yamnaya culture.The tumulus Bereketska mogila is the largest prehistoric necropolis in Bulgaria. It is located on the right bank of Bereketska River, in central Bulgaria. So far, this tumulus is the only flat necropolis from the Early Bronze Age that has been studied50. DNA libraries were prepared from the extracts following a custom double-indexing protocol52 optimized for ancient samples, in order to make the DNA immortalized, barcoded and available for the Next Generation Sequencing (NGS). Negative controls were processed during each experimental step. A target enrichment strategy was followed to select the DNA molecules attributed to the mitochondrial genome53. Enriched libraries were pooled in equimolar amount and paired-end sequenced (2 × 75 + 8 + 8 cycles) on Illumina MiSeq platform.Molecular analyses of the anthropological samples were performed in the Laboratory of Molecular Anthropology and Paleogenetics, University of Florence, following strict guidelines and standard precautionary measures to avoid contamination during all experiments. The sampling of bone powder was conducted using a microdrill, selecting the compact bone from the inner part of long bones and the dentine part from teeth. Fifty milligrams of bone or dentine powder were used for DNA extraction using a silica-based technique that allows ancient DNA molecules to be efficiently recovered54. Adaptor sequences were trimmed and paired-end reads were merged into single sequences with a minimum overlap of 10 bp, in order to exclude all the sequences derived from molecules longer than 140 bp. Only reads with a minimum length of 30 bp were kept. Filtered reads were mapped to the revised Cambridge Reference Sequence  using CircularMapper, a mapping method especially designed for circular reference genomes; reads with mapping quality below 30 were discarded. PCR duplicates were removed using DeDup and consensus sequences for the mitochondrial genomes of all samples were called using schmutzi (parameters: “–logindel 1 –uselength”)55. DNA damage patterns at the ends of the molecules and average fragment length were taken into account to identify and call endogenous bases. Present-day human contamination estimates were performed using a non-redundant database of 197 human mitochondrial genomes available in the software package. Misincorporation patterns at the 5′ and 3′ ends were computed using contDeam, a program provided with the schmutzi package. A summary of the results for each analyzed sample is provided in Table 56 based on PhyloTree build 1757, followed by manual verification of each diagnostic variant  was performed on Thracian and modern mtDNA sequences, by using the R software package adegenet58. Contrary to classic PCA where eigenvalues are calculated by maximizing variance of the data, in sPCA analysis the eigenvalues are obtained by maximizing the product of variance and spatial (Moran’s I index) autocorrelation58. To test the significance of the detected sPCA geographical structures the Global and Local random tests implemented in the adegenet functions have been applied.To set the observed mtDNA variation into a wider genetic landscape and with the aim of investigating possible genetic relationships with both modern and ancient populations, the Thracian mitogenomes were compared with those of reference datasets extracted from the literature. The modern comparison dataset consisted of 320 individuals from 16 West Eurasian populations for which comparable mtDNA whole genome sequencing data were available30. The available ancient mitogenomes were classified into geographically and culturally distinct population groups, as detailed in Supplementary Table www.fluxus-engineering.com) and checked manually. The Median Joining Network was calculated with the Network software v.5 (www.fluxus-engineering.com) setting the ε value to 0 and weighting the transversions 3x the weight of the transitions. The resulting network was drawn without pre- or post-processing steps and graphically visualized with Network Publisher. To summarize the relationships of Thracians with the other ancient populations, a correspondence analysis (COA) was performed by using the dudi.coa function of the R software package ade459. Ancient population groups with N<5 were excluded from the analyses in order to avoid possible biases due to low population sizes.In order to diachronically compare the genetic data of Thracians with ancient population patterns, whole mitochondrial genomes of 417 ancient individuals belonging to European and Mediterranean population groups, ranging from the Upper Paleolithic to the Iron Age, were accessed through publicly available datasets (Supplementary Table Dataset 1Dataset 2


A number of studies carried out since the early ‘70s has investigated the effects of isolation on genetic variation within and among human populations in diverse geographical contexts. However, no extensive analysis has been carried out on the heterogeneity among genomes within isolated populations. This issue is worth exploring since events of recent admixture and/or subdivision could potentially disrupt the genetic homogeneity which is to be expected when isolation is prolonged and constant over time. Here, we analyze literature data relative to 87,815 autosomal single-nucleotide polymorphisms, which were obtained from a total of 28 European populations. Our results challenge the traditional paradigm of population isolates as structured as genetically  uniform entities. In fact, focusing on the distribution of variance of intra-population diversity measures across individuals, we show that the inter-individual heterogeneity of isolated populations is at least comparable to the open ones. More in particular, three small and highly inbred isolates  were found to be characterized by levels of inter-individual heterogeneity largely exceeding that of all other populations, possibly due to relatively recent events of genetic introgression. Finally, we propose a way to monitor the effects of inter-individual heterogeneity in disease-gene association studies. Studying groups subject to barriers to gene flow provides a unique opportunity to understand how inbreeding and drift have shaped the structure of human genetic diversity. A very large number of investigations carried out since early ‘70s has examined the effects of isolation on intra- and inter-population variation in diverse geographical contexts, using genetic polymorphisms varying in mode of inheritance and evolutionary rate –5. CurreIn a previous paper, we have compared intra and inter-population measures of genomic variation in a large sampling of European populations in order to understand to what extent the discrete open and isolated dichotomous categories correspond to the way in which their genomic diversity is structured . In thisOur dataset includes 610 healthy unrelated adult individuals from 28 European populations , nine of-6).The samples genotyped with the GenoChip 2.0 array were merged with literature data and then filtered according to the standard genotype quality control metrics using PLINK : (i) SNPPrincipal components Analysis was performed using PLINK package (v. 1.9). The position of the centroid for each population was identified by averaging the values for the two axes, while the distance of each point from the centroid was calculated using the formula The following statistics were also calculated using PLINK package (version 1.9): (i) the proportion of homozygous loci (HOM) for each individual; (ii) the proportion of identical genotypes between pairs of individuals within each population (IBS); (iii) the number and total length of stretches of contiguous homozygous genotypes, RoH-KB and RoH-NSEG, respectively. For the HOM, RoH-KB and RoH-NSEG statistics, the median was taken as a population value, while individual IBS values were then calculated as the mean of each distribution. The RoHs were identified using default settings , with a minimum-length cut-off of 500 kb and 14 homozygous SNPs . To measWe used SHAPEIT v2.r790  to phaseThe comparison of inter-individual heterogeneity for measures of intra-population variation as well as CHR_P was estimated through the equality of variances (Brown-Forsythe Levene type procedure), after the application of Bonferroni correction (R package lawstat).Maximum likelihood estimates of individual ancestries were obtained using ADMIXTURE v1.23 under default values. Its algorithm is relatively robust to SNP ascertainment bias  since itAdmixture dates were inferred using the number of ancestry switches and ancestry proportions following Johnson et al . Phased As a first sight to the results of inter-individual genomic heterogeneity, we plotted a PCA and evaluated the level of scattering within each population . The resThereafter, In order to explore more exhaustively the genomic heterogeneity occurring among individuals within populations, we used four intra-population measures of genomic diversity, based either on single nucleotide  or haplotype variation , for which intra-population variance can be calculated. In contrast with the traditional paradigm of population isolates as genetically uniform entities, taken as a whole isolated populations showed heterogeneity values comparable  or higher  than the open ones . These rLooking at single populations, the most inbred ones—Sauris, Sappada and Timau—were found to be among the most diverse for all measures along with North Sardinians.Then, we compared heterogeneity for ancestry proportions (ADX_HET). Also, in this case, isolates, as a whole, were found to be more heterogeneous than open populations (1.38E-03 vs 6.44E-04), but the difference was statistically insignificant . The greatest values were again obtained in the three population isolates from the eastern Italian Alps, followed by North Sardinians , with a Finally, we took into account the heterogeneity of the total length of haplotype chunks shared between individuals (CHR_P). The distribution of this parameter reconfirmed the patterns observed for groups  and single populations . As the only peculiarity, a noticeable signal was provided also from the Orkney islanders .In order to understand if the results obtained for the three north eastern Italian isolates might be due to introgression of exogenous genetic components, Sappada and Timau samples were splitted into two sub-groups on the basis of ADMIXTURE ancestry proportions . In the case of Sauris, sub-groups would had been too small to be separately analyzed. Individuals with a highly prevalent village-specific ancestry  were taken separate from those with more heterogeneous ancestry, who were termed as SAP_HTA and TIM_HTA. Thereafter, we performed the Levene’s tests for equality of variances between all populations . Only comparisons with a ratio between standard deviations >1 and significant after Bonferroni correction are shown in Given the support received by genetic introgression in generating the observed pattern from the analyses described above, we went to infer the time frames of the admixture which likely occurred between SAP_HTA and TIM_HTA sub-groups and geographically-close Italian speaking populations. We preliminarily tested the reliability of our estimates panel using genomic profiles of African-Americans obtained with a much denser SNP set. To this purpose, we retrieved data from the 1000 genomes project phase 3 and used a simple three population model with 30 randomly chosen individuals from the African-American population (ASW) as targets and an equal number of individuals of European (CEU) and African (YRI) origin as sources. Estimates obtained by using our SNP panel and another including 8,142,382 markers (with MAF<0.05) were close each other and consistent with previous results based on molecular data .The results described above should be interpreted in the light of a number of potential biases and confounding factors. A first issue concerns the adequacy of our SNP panel to represent the genetic variation of the populations under analysis. Although it contains a relatively small number of SNPs compared to those used in other surveys of genomic variation, the GenoChip array should provide an adequate coverage of diversity across European populations due to their large number (92) in the reference panel ,32. FurtA second potential issue is related to the likely under-representation of rare alleles in our panel, since they have been shown to retain signals of between and within population differentiation stronger than common alleles . ObviousThird, only one of the parameters used here  was estimated using phased data. Despite its relatively low density, the Geno chip has been proved useful to reconstruct informative haplotype chunks after phasing procedure . In ordeTaking into account all these aspects, we believe that our approach is suitable for a preliminary assessment of inter-individual genomic heterogeneity in European populations.Previous GWA studies, which analyzed genetic variation of isolated human populations, focused on measures which summarize single nucleotide and haplotype variation within or among groups e.g. ,36,37). ,37. 36,3To gain new insights into the genomic structure of isolated populations, we decided to focus on the distribution of variance (heterogeneity) of intra-population diversity measures across individuals within populations, rather than relying on their average values. In contrast with their common view as groups of genetically homogeneous individuals, we observed that the inter-individual genomic heterogeneity of isolated populations is at least comparable to that of the open ones. It is worth reminding that applying standard measures of intra-population diversity to our dataset produced the expected pattern, with isolates characterized by higher homozygosity, longer and more numerous ROHs and higher IBS values than open populations, although a clear discontinuity of values between the two groups is not noticeable (see ).Interestingly, three small and highly inbred isolates  were characterized by particularly high heterogeneity values, which largely exceeded those calculated in all other populations. Given that there is no evidence to support the presence of sub-groups with distinct matrimonial behaviours for any of them, this finding could hardly be put down to population subdivision. However, the observed patterns could be explained, at least in part, by relatively recent events of genetic introgression, such as those suggested by our admixture dates based on ancestry switches. In fact, after removing the individuals with higher percentages of mixed ancestries from the Sappada and Timau samplings, their number of statistically significant pairwise comparisons for inter-individual heterogeneity diminished substantially . We reasA retrospective look at previous studies shows that other small-sized European isolates with a very high ratio between sample and census size, namely Clauzetto, Erto, Illeggio, Resia and (another sampling from) Sauris, show a similar pattern to what we observed . A high Whatever the cause of this high genomic inter-individual heterogeneity we observed in Sappada, Sauris and Timau, we cannot ignore the question: “what do our results imply for the way in which bio-medical studies are carried out in population isolates?”. Although, the most robust evidence was noticed in some young and small-sized population isolates—which are less used in association studies than the older and larger ones —our resuWe suggest that genetic clustering algorithms may be used to test for the presence of individuals with different ancestry proportions within isolated populations, similarly to what has been previously done by Esko et al.  Click here for additional data file.S2 FigPlots from K = 2 to K = 10 for the 28 populations under study.(PDF)Click here for additional data file.S1 TableMedian and variance distance values were obtained for each population over the PCA plots (first 4 components). Labels as in (XLSX)Click here for additional data file.S2 TableMann-Whitney U-test p-values comparing variance values between open and all isolated population (first column), excluding Sauris (second column) and excluding all three German-speaking islands . Bold numbers indicate significant values .(XLSX)Click here for additional data file.S3 TableAnalysis based on the Admixture components proportion recorded at K = 4.(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.S7 TableCalculated as the proportion of the autosomal genome in runs of homozygosity, excluding the centromeres.(XLSX)Click here for additional data file.


Pinus albicaulis (whitebark pine) is a widely-distributed but rapidly declining high elevation western North American tree and a candidate for listing under the U.S. Endangered Species Act. Our objectives were to develop reliable nuclear microsatellite markers that can be used to assess within-population genetic diversity as well as seed and pollen migration dynamics, and to validate markers using two geographically proximal P. albicaulis populations. We identified 1,667 microsatellite-containing sequences from shotgun DNA libraries of P. albicaulis. Primer pairs were designed for 308 unique microsatellite-containing loci, and these were evaluated for PCR amplification success and segregation in a panel of diploid needle tissue. DNA was extracted with an SDS protocol, and primers were screened through gel electrophoresis. Microsatellites were genotyped through fluorescent primer fragment analysis. Ten novel and 13 transferred loci were found to be reproducible in analyses based on 20 foliage samples from each of two locations: Henderson Mountain, Custer Gallatin National Forest, Montana, and Mt. Washburn, Yellowstone National Park, Wyoming (USA). Transferred loci had higher numbers of alleles and expected heterozygosities than novel loci, but also revealed evidence for a higher frequency of null alleles. Eight of the 13 transferred loci deviated significantly from Hardy-Weinberg Equilibrium, and showed large positive FIS values that were likely inflated by null alleles. Mantel’s tests of transferred and novel markers showed no correlation between genetic and geographic distances within or among the two sampled populations. AMOVA suggests that 91% of genetic variability occurs within populations and 9% between the two populations. Studies assessing genetic diversity using these microsatellite loci can help guide future management and restoration activities for P. albicaulis. North American forest trees have been exposed to a number of unprecedented health challenges that are likely to be exacerbated by warming temperatures . These cPinus albicaulis Engelm.  is a widely distributed western North American tree species of subalpine and treeline elevations ranging from about 37° to 55° N latitude. It functions as an ecological keystone and foundation species in these high elevation communities . Ov. Ov11]. ght DBH; .GenAlEx 6.5 , [, [P. albfamilies . The lowfamilies . The sucsibirica . While tP. albicaulis previously studied using allozyme analysis [P. albicaulis—including allozymes [Our secondary objective was to provide a case example of the utility of these microsatellites for population genetic research by comparing genetic diversity in two populations of analysis . Despiteanalysis . Comparellozymes  and SNPsllozymes —the micrllozymes . The surP. albicaulis, or a presence/absence polymorphism in some chromosomal lineages. In these instances, null alleles fail to amplify, leading to decreased observed heterozygosity and apparent reaction failure in null homozygous individuals [IS values, which are large and positive for both populations, leading to potentially erroneous inferences of moderate inbreeding. Six loci—RPS119, RPS127, P5, P45, P63, and PisATG0012—were estimated to have high null allele frequencies in both populations. Loci that diverge from HWE and show evidence of null alleles should be used with caution as they inflate homozygosity and thus may not be applicable for all analyses  and are most likely the result of allelic dropout . All loci that violate HWE are transferred loci, which may indicate imperfect conservation of primer binding sites in ividuals . The potanalyses . Lookingm mating . For stuMantel's test revealed low genetic differentiation among populations and high gene flow, with no correlation between geographic distance and genetic relatedness among populations. Within populations, Mantel’s correlation shows no spatial autocorrelation at Henderson Mountain, with individuals no more or less closely related genetically to those nearby geographically than expected at random. There is weak evidence for isolation by distance in the Mt. Washburn population, with a positive Mantel correlation indicating that genetic distance between individuals increases with increasing physical distances. However, the AMOVA, which revealed that 9% of genetic differentiation occurred between populations, indicates greater population differentiation compared to SNP findings . A largeP. albicaulis reveal that locus transferability is a viable option for developing microsatellites in five-needle pines, with the caveat that null alleles may show high frequencies in some interspecific comparisons. Other efforts in cross-species amplification in Pinus, however, have had mixed results, with some cases appearing successful [P. albicaulis genome .Our results with ccessful , 83, 84,ccessful , 85. It P. albicaulis genetic diversity, population structure, and parentage. Employing high-level PCR multiplexing [P. albicaulis into five “seed zones” in the Inland West [P. albicaulis, and for the exploration of climate change mitigation strategies . These s e.g., , 88). Si. SiP. als , ca, caP. alS1 FigA) difference in mean number of alleles (-0.74) and 95% confidence interval of the difference (-2.29 to 0.81) and B) difference in mean expected heterozygosity (-0.015) and 95% confidence interval of the difference (-0.178 to 0.148) of 23 microsatellite loci for two populations of Pinus albicaulis Engelm. (Pinaceae): Henderson Mountain, Custer Gallatin National Forest, MT, and Mount Washburn, Yellowstone National Park, WY. Plotted points are the difference in means, Washburn minus Henderson, and the lines are the 95% confidence intervals around those points.(TIF)Click here for additional data file.S2 Figxy versus the observed Rxy (red line) for 9999 permutations, from Mantel’s test on two Pinus albicaulis Engelm. (Pinaceae) populations . Rxy is the correlation between geographic and genetic distance between individuals. A positive value indicates individuals are more closely related genetically to those nearby geographically than random, and a negative value indicating individuals are less closely related to those nearby.Frequency distribution of random R(TIF)Click here for additional data file.S3 FigPinus albicaulis Engelm. (Pinaceae) populations. A) Henderson Mountain, Custer Gallatin National Forest, MT showing no correlation between genetic and geographic distances  and B) Mount Washburn, Yellowstone National Park, WY showing a positive correlation .Correlation between geographic distance and genetic distance, from Mantel’s test on two (TIF)Click here for additional data file.S1 TablePinus albicaulis Engelm. (Pinaceae). Bold entries successfully transferred.Locus name, source species of primer development, and allele size range for 49 primers screened for transferability to (DOCX)Click here for additional data file.S2 TablePinus albicaulis Engelm. (Pinaceae) sampled at two populations .Minimum, maximum, and mean diameter at breast height (DBH) in centimeters compared between (DOCX)Click here for additional data file.S3 TablePinus albicaulis Engelm. (Pinaceae) sampled at two populations . Rxy and P(rxy-rand > = rxy-data) from Mantel’s correlation, showing isolation by distance and spatial autocorrelation, testing for each population and for all individuals combined.Minimum, maximum, and mean distance between (DOCX)Click here for additional data file.


Sphedanolestes impressicollis (Hemiptera: Reduviidae), is widely distributed in East Asia. It is an ideal model for evaluating the effects of climatic fluctuation and geographical events on the distribution patterns of East Asian reduviids. Here, we used two mitochondrial genes and one nuclear gene to investigate the phylogeographic pattern of the assassin bug based on comprehensive sampling in China, Japan, South Korea, Vietnam, and Laos. High levels of genetic differentiation were detected among the geographic populations classified into the northern and southern groups. A significant correlation was detected between genetic and geographical distances. The East China Sea land bridge served as a “dispersal corridor” during Pleistocene glaciation. The estimated divergence time indicated that the northern group may have separated from the eastern Chinese populations when the sea level rapidly rose during the “Ryukyu Coral Sea Stage” and the East China Sea land bridge was completely submerged. Demographic history and ecological niche modeling suggested that appropriate climatic conditions may have accounted for the rapid spread across the Korean Peninsula and Japan during the late Pleistocene. Our study underscores the pivotal roles of the Pleistocene sea level changes and climatic fluctuations in determining the distribution patterns of East Asian reduviids.The assassin bug,  During the Quaternary, at least six glacial advances affected the physical and biological environments of the Northern Hemisphere . GlaciatEast Asia has long been considered a biodiversity hotspot. Its complicated topography and changeable climatic conditions provided effective refugia for organisms during glaciation. In East Asia, glacial advances were not as extensive as those in Europe or America because of monsoons caused by differential heating between the Asian continent and the Pacific Ocean . The AsiSphedanolestes impressicollis Stål belongs to the subfamily Harpactorinae and was first described in 1861 in Hong Kong and thereafter in Japan and South Korea. This assassin bug has been identified on the Japanese islands of Kyushu, Shikoku, and Honshu; throughout South Korea and China; and in parts of Vietnam, Laos, and India [Sphedanolestes impressicollis is one of the most widely distributed assassin bug species in East Asia and the surrounding areas. It adapts to long-distance diffusion and is relatively sensitive to temperature changes, making it an ideal model for the evaluation of phylogeographic patterns and the assessment of the effects of topography and climatic cycles on the demographic history of East Asian reduviids and other indigenous insects [The assassin bug nd India . It livend India . Sphedan insects . Since s insects ,24. AnalCOI) and cytochrome b (Cytb) and the nuclear gene elongation factor-1α (EF-1α) were used to establish the phylogeographic pattern and correlative demographic history of Sphedanolestes impressicollis based on comprehensive sampling from various geographic distributions , 225 sites were variable among these individuals. There were 131 parsimony informative sites and 94 singleton variable sites. These polymorphic sites defined 152 haplotypes across the species ranges. The overall haplotype (Hd) and the nucleotide (π) diversities for all populations were 0.9905 and 0.00744, respectively. The average haplotype diversity range for all populations from China, Japan, South Korea, Vietnam, and Laos was 0.000–1.000 and the mean nucleotide diversity range was 0.000–0.0085 . Of the EF-1a sequences (898 bp) obtained from 87 individuals, eight haplotypes were defined by seven segregating sites. The overall Hd and π for all populations were 0.713 and 0.00164, respectively . In contrast, it was 18.77% among populations within groups and 36.53% within populations. Pairwise STF based on the concatenated mitochondrial dataset between the N and S groups was 0.46026 (p < 0.0001). For the nuclear EF-1a gene sequence, AMOVA disclosed that 51.14% of the variation was between N and S (p < 0.0001). Only 27.42% of the variation was among populations within groups and 21.44% was within populations  revealed significant genetic variance based on both the concatenated mitochondrial dataset and the nuclear gene at different hierarchical levels . For theulations . The datMedian-joining network results based on 152 mitochondrial haplotypes showed a structure resembling that resolved by phylogenetic analyses . Both thEF-1a gene sequence, only eight haplotypes were identified for all 87 sequences  and estimated divergence time for pivotal nodes are shown in τ localizes the mismatch distribution crest and roughly estimates the time at which rapid population expansion began for Sphedanolestes impressicollis. τ was 16.90000 units of mutational time in all samples  = 416,543 generations . τ for the S group (14.97266) was much larger than that of the N group (2.38867). The calculated expansion time for the N group was 58,875 generations  and that for the S group was 369,039 generations . BSP analysis revealed two significant increases in the effective population size for all samples which occurred ~0.1 Ma and ~0.5 Ma  [Sphedanolestes impressicollis. Recent studies showed a similar demographic pattern of certain organisms in China, whose population expansions started before LGM [Sphedanolestes impressicollis distributions across East Asia. Since sample size and molecular markers were limited, however, we could not elaborate on the potential genetic structure or accurately localize the refugia in the present study. A higher level of individual sampling and more genome-wide molecular markers are needed to elucidate the detailed evolutionary history of Sphedanolestes impressicollis.In the present study, phylogenetic haplotype trees based on a concatenated mitochondrial dataset disclosed generally unresolved topologies and comparatively few substantial indications of the intraspecific phylogeographical structure in China . The dem0.46 Ma) ,41. The 0.46 Ma)  further fore LGM ,15,42,43Sphedanolestes impressicollis individuals were sampled from 48 localities in Mainland China, Taiwan Island, South Korea, Japan, Vietnam, and Laos (COI and Cytb) and the nuclear gene (EF-1α) are listed in TM  under the following conditions: initial denaturation at 94 °C for 5 min; 35 cycles at 94 °C for 30 s; 45–50 °C for 30 s; 72 °C for 1.5 min; and a final single extension at 72 °C for 6 min. All PCR products were purified and sequenced in both directions with an ABI 3730XL DNA analyzer . All sequences were assembled in Geneious v. 11.1.3 (http://www.geneious.com/) and deposited into GenBank under the following accession numbers: .In total, 199 and Laos . They weSphedanolestes trichrous, Sphedanolestes gularis, and Sphedanolestes pubinotus were designated as outgroups for the phylogenetic analyses. Split networks based on the concatenated mitochondrial dataset were constructed with Splitstee v. 4.13.1 [www.fluxus-engineering.com) based on the concatenated mitochondrial dataset and the nuclear gene sequences.Each gene was independently aligned with Mafft v. 7  and the . 4.13.1 , which c. 4.13.1  with NetSTF values were estimated between large populations (N > 5). Mantel tests were run based on the mitochondrial dataset to identify the isolation-by-distance model for all samples and the N and S groups. Correlations between genetic distances (STF) and linear geographic distance (ln Km) were plotted with 999 replicates in the ade4 v. 1.7 module of R.To test genetic diversity and differentiation, the number of segregating sites (S), number of haplotypes (H), haplotype diversity (Hd), and nucleotide diversity (π) were calculated for all populations with DnaSP v. 5.0 . HierarcBEAST v. 2.5.1  was usedSphedanolestes impressicollis. To confirm whether expansion occurred, mismatch distributions were examined. These are typically ragged or multimodal for populations at stationary demographic equilibrium. In contrast, they are smooth or unimodal for populations which have undergone demographic expansion [t) and calculated from t = τ/2μ, where τ (tau) is the expansion time in mutation units and μ is the mutation rate per generation for the DNA sequence. The Sphedanolestes impressicollis generation time was taken to be 1 y. To identify the changes in effective population over time, Bayesian skyline plots (BSP) were generated in BEAST v. 2.5.1 [Tajima’s D  and Fu’sxpansion . The fitv. 2.5.1 , based ohttp://www.esri.com/software/arcgis). The bioclimatic variables most likely to affect the distribution were mean temperature (BIO1), mean diurnal temperature range (BIO2), maximum temperature of the warmest month (BIO5), minimum temperature of the coldest month (BIO6), annual mean precipitation (BIO12), precipitation of the wettest month (BIO13), and precipitation of the driest month (BIO14). They were obtained from the Worldclim database at a 2.5-min resolution (http://www.worldclim.org/). ENM analysis was executed with maximum entropy in Maxent v. 3.3.3k [A total of 104 localities were used for the ENM, including 48 sample localities and another 56 records of dry preserved specimens . Modern . 3.3.3k . The anaSphedanolestes impressicollis populations in East Asia, which were classified into the N and S groups. A significant correlation was detected between genetic and geographical distances. The ECS land bridge served as a “dispersal corridor” during Pleistocene glaciation. The N group separated from the eastern Chinese populations when the sea level rapidly rose during the “Ryukyu Coral Sea Stage” and the ECS land bridge was completely submerged. The rapid spread across the Korean Peninsula and Japan during the late Pleistocene benefited from appropriate climatic conditions for Sphedanolestes impressicollis. Our study highlights the crucial roles of the Pleistocene sea level changes and climatic fluctuations that determined the distribution patterns of East Asian reduviids.In this study, we resolved the phylogeographic pattern among


Arapaima gigas) is one of the largest freshwater fish in the world, and has a long history of commercial exploitation in the Amazon region. To estimate levels of genetic variability and historical and recent connectivity in Arapaima, we examined variation in eleven microsatellite DNA markers in individuals from 22 localities in Brazil, Colombia, and Peru. The results of analysis of molecular variance, Bayesian clustering and discriminant analysis of principal components showed that Arapaima in our samples represents two major populations, one in the Amazonas and one in the Araguaia-Tocantins River basins. The Amazonas population is further structured by isolation-by-distance with the hydrologically largely unconnected Amapá locality representing the eastern-most extreme of this continuum; gene flow predominates at distances of less than 1500 km with localities separated by over 2000 km dominated by genetic drift and effectively forming different populations. We saw no evidence of multiple species of Arapaima in the Amazonas basin, and analysis of pairwise genetic divergence (FST) with Mantel tests and correlograms indicated that this largest population exhibits a large-scale pattern of isolation-by-distance, with which results from MIGRATE-N agreed. The degree and significance of genetic divergence indicates that most sampled localities represent demographically independent sub-populations, although we did identify several recent migration events between both proximal and more distant localities. The levels of genetic diversity were heterogeneous across sites, including low genetic diversity, effective population sizes, and evidence of genetic bottlenecks in several places. On average the levels of gene diversity and rarefied allelic richness were higher for localities along the Amazonas mainstem than in the tributaries, despite these being the areas of highest fishing pressure, while the lowest values were found in tributary headwaters, where landscape modification is a significant threat. We recommend that managers consider the regional and local threats to these populations and tailor strategies accordingly, strategies which should ensure the ability of young A. gigas to disperse through floodplain corridors to maintain genetic diversity among otherwise sedentary adult sub-populations.Arapaima, pirarucu or paiche ( Melanosuchus niger) and spectacled caimans (Caiman crocodilus)  Santarém, Para State, Brazil, only known from the holotype (MNHN A.8837); 2) Arapaima mapae  described from Lago do Amapá or Lago Grande in Região dos Lagos in Amapá State, Brazil, only known from the holotype (MNHN A.8836); 3) Arapaima arapaima  described from Guyana (Essequibo basin), only known from the holotype (BMNH 2009.1.19.1) but the holotype is misplaced or lost; 4) Arapaima agassizii  described from “Brazilian Amazon”, only known from an illustration of the holotype by Spix and Agassiz , we, weArapa sampled , and the sampled , 62, we A. gigas in the upper Araguaia-Tocantins—a basin that become effectively isolated from the Amazon basin at the Plio-Pleistocene boundary . How. HowArapn aierba .Arapaima gigas is a floodplain specialist, inhabiting lakes and lagoons that are connected by channels to the riverine network of the Amazonas basin. Although A. gigas is not a “migratory” species, these fishes do make small lateral movements through the network of lakes and channels of the Amazon floodplain, which provide abundant food for growing young [The floodplain has been reported as the environment with the highest productivity in the Amazon drainage basin, and is the most common environment of the Solimões-Amazonas axis. The flood-ebb system of the flooded forest, or 'flood pulse', provides exceptional availability of diverse habitats and seasonal resource abundance . Howeverng young . These rng young .Arapaima gigas are the differences among the Araguaia and Amazon basins and the hydrologically isolated Região dos Lagos (Amapá), the Amazonas population is structured by isolation-by-distance at the largest scale—with the Região dos Lagos representing its eastern-most extreme, we discovered statistically significant genetic divergence (i.e. FST) among most localities . As sucnt Units . This woA. gigas may regularly engage in polygamous reproduction [A. gigas are warranted.In this context, the results indicating recent population declines (genetic bottlenecks) compounded onto long-term demographic declines potentially associated with the extent and distribution of Amazonian floodplains , 91 and oduction , therebyoduction . Howeveroduction , and theoduction . Given tArapaima gigas was banned by IBAMA , except in management areas such as the Mamirauá and Piagaçu-Purus Sustainable Development Reserves (RDS) where fishing is controlled, preventing local overexploitation [A. gigas have been reported for community based management initiatives in which individual communities or families restrict access to spatially delimited populations of A. gigas e.g. [A. gigas remains to be seen, especially with regard to evidence of low effective population sizes, genetic bottlenecks, and the potential for erosion of genetic diversity recovered here  observed here corroborate the findings of Vitorino et al. [A. gigas in both basins implies, they share a close biogeographic history and exhibit similar icthyofaunas [Inia araguaiaensis [A. gigas is in keeping with these trends.Although the population in the Amazonas basin o et al. , who shoo et al. , who disyofaunas , along wyofaunas , 108 andaiaensis . The conA. gigas, which presented as a genetic intermediate between the Araguaia and eastern Amazon sub-population in STRUCTURE and DAPC analyses, presents something of a conundrum. The sampling locations in the upper Araguaia River , in addition to being about 1,340 and 890 km, respectively, from the reservoir, are also separated by numerous rapids which may limit the gene flow between these areas, implying that the pattern of admixture may be natural. However, the dam itself was also built downstream of the historical barrier (Itaboca), trapping some of the downstream fauna within the flooded region. Thus, the admixture of lower Amazon/lower Tocantins and upper Tocantins lineages may instead be an anthropogenic effect of reservoir construction. Indeed, several other studies have suggested that aquatic organisms of Tucuruí exhibit unique patterns of admixture or hybridization different from that of the lower Tocantins e.g. [The most likely feature promoting divergence of aquatic organisms in the upper Tocantins basin is, ironically, one that no longer exists, the Itaboca waterfalls that were submerged when the Tucuruí hydroelectric dam was constructed. As such, the Tucuruí population of ins e.g. . In the A. gigas in this region, despite relatively low fishing pressure, should thus be considered highly threatened, especially considering these fishes exhibited the lowest observed levels of genetic diversity. Whether this reduced diversity results from natural (e.g. Pleistocene-age colonizations or bottlenecks) or anthropogenic effects, the ability of this unique population to remain viable in the face of ongoing habitat modifications should be closely monitored.The Araguaia-Tocantins basin is considered highly threatened not only by hydroelectric projects in the headwaters of tributary rivers, but it is also among the areas in Brazil with the highest rates of landscape modification for cattle ranching, road construction, and agriculture . The uniArapaima gigas from the Região dos Lagos in Amapá are significant as well. This region, which is technically connected to the Amazonas basin by freshwater from the Amazonas outflow, exhibits an icthyofauna with affinities both for that of the Amazon, as well as those of coastal Guyana drainages to the north [A. gigas here is thus not a surprise, although, considering the strong and turbulent current that runs along the coast and probably limits dispersal, nor is their distinctness from the other populations. Fortunately, a significant portion of the Região dos Lagos is protected by a state park which limits exploitation, although it remains unknown if A. gigas from the Araguari River are part of this population as well. In either case, habitat degradation from cattle ranching and urban development continues to encroach upon the watersheds were this population is found, and being limited to such a relatively small area, this unique population could easily be placed at risk if current protections were to prove inadequate.The population of he north . The preArapaima gigas populations, given the evidence of reduced genetic capacity and the intersection of threats against them. These data should contribute toward the design of management and conservation programs for this species in the Amazon, Amapá, and Araguaia-Tocantins regions.The findings presented here should be seen as an important warning about the fragility of Permits for field collection and molecular analyses were given by IBAMA/CGEN 11325–1. This study involved no experimentation, manipulation or euthanasia of any animals on part of the researchers. We simply collected tissue samples of exemplars fished by local communities for food and as fishes were brought to market. In these instances our institution (UFAM) does not require IACUC approval. Finally, this research could not have been submitted to IACUC for analysis since this committee became operational only after the completion of this study.S1 Fig(EPS)Click here for additional data file.S2 Fig(EPS)Click here for additional data file.S3 Fig(EPS)Click here for additional data file.S4 Fig(EPS)Click here for additional data file.S1 TableA = Total number of alleles; AR = Allelic richness; HO = Observed Heterozygosity; HE = Expeted Heterozygosity; mono = Monomorphic locus; * significant P value for deviation from HWE after Bonferroni correction (P = 0.00455).N(DOCX)Click here for additional data file.S2 TableRow localities are sending individuals, while column localities are receiving individuals. Locality codes are: 1- Santa Cruz, 2- Puerto Nariño, 3- Carauari, 4- Eirunepé, 5- Mamirauá, 6- Coari, 7- RDS Piagaçu-Purus, 8- Tapauá, 9- Lábrea, 10- Manuel Urbano, 11- Manacapuru, 12- Resex Unini, 13- Careiro da Várzea, 14- Borba, 15- Nhamundá, 16- Santarém, 17- Jacareacanga, 18- Região dos Lagos, 19- Mexiana, 20- Tucuruí, 21- Ilha do Bananal, 22- APA Meandros do Araguaia.(XLSX)Click here for additional data file.S3 TableNote: significant differences at p < 0.05 and after Bonferroni correction are in bold.(XLSX)Click here for additional data file.