Bactrocera dorsalis s.s., is one of the most important quarantine pests in many countries, including China. Although the oriental fruit fly has been investigated extensively, its origins and genetic structure remain disputed. In this study, the NADH dehydrogenase subunit 1 (ND1) gene was used as a genetic marker to examine the genetic diversity, population structure, and gene flow of B. dorsalis s.s. throughout its range in China and southeast Asia.The oriental fruit fly, B. philippinensis. Demographic analysis revealed rapid expansion of B. dorsalis s.s. populations in China and Southeast Asia in the recent years. The greatest amount of genetic diversity was observed in Manila, Pattaya, and Bangkok, and asymmetric migration patterns were observed in different parts of China. The data collected here further show that B. dorsalis s.s. in Yunnan, Guangdong, and Fujian Provinces, and in Taiwan might have different origins within southeast Asia.Haplotype networks and phylogenetic analysis indicated two distinguishable lineages of the fly population but provided no strong support for geographical subdivision in ND1 gene, the results of the present study showed B. dorsalis s.s. from different parts of China to have different genetic structures and origins. B. dorsalis s.s. in China and southeast Asia was found to have experienced rapid expansion in recent years. Data further support the existence of two distinguishable lineages of B. dorsalis s.s. in China and indicate genetic diversity and gene flow from multiple origins.Using the mitochondrial The sequences in this paper have been deposited in GenBank/NCBI under accession numbers KC413034–KC413367. Bactrocera dorsalis (Diptera: Tephritidae) is a major horticultural pest. More than 70 species have been identified within this group [B. dorsalis species are highly destructive because of their wide host-ranges, considerable ecological adaptability, pronounced reproductive potential, and dispersal capacity. The B. dorsalis s.s., B. papayae, and B. philippinensis species have become invasive in many parts of China. Despite previous studies that have described the subtle morphological characteristics distinguishing these three species [B. dorsalis s.s., B. papayae, and B. philippinensis are truly separate species [The is group . Some of species -3, taxon species ,5.B. dorsalis s.s. was first recorded in Taiwan in 1912 and is now widely distributed in most countries in the Asia-Pacific region [B. dorsalis s.s. has been observed multiple times in China during the past hundred years [B. dorsalis s.s. is distributed mostly in China’s southern provinces [c region . Specified years -9. Currerovinces .B. dorsalis s.s. populations in China and Southeast Asia [B. dorsalis s.s., B. papayae, and B. philippinensis should be considered a single species [B. philippinensis and the B. dorsalis s.s. /B. papayae transition zone  should provide clues regarding the invasion events in the region [B. dorsalis s.s. over time, the NADH dehydrogenase subunit 1 (ND1) markers in B. dorsalis s.s. have not yet been used for an evaluation of the distribution area of B. philippinensis or the B. dorsalis s.s./B. papayae transition zone [ND1 was used as a genetic marker to study the genetic structure and origin of the B. dorsalis s.s. population within China and the surrounding areas. Mitochondrial DNA is suitable for analyses of population genetics because of its relatively high rate of genetic evolution [B. philippinensis distribution area and B. dorsalis s.s. /B. papayae transition zone to (1) determine the actual number of cryptic species and cryptic lineages of B. dorsalis s.s. within China; (2) assess the molecular diversity and genetic architecture of the populations; (3) resolve the controversy of the origin and range expansion of B. dorsalis s.s. within China.Mitochondrial DNA analyses have been conducted to study the genetic structure and origin of ast Asia -15. Howee region . Althougvolution -20. The B. dorsalis s.s. populations from China and surrounding areas  and the lineage II network showed a star-like pattern with six predominant haplotypes   of the ND1 sequences was performed. The FCT values in the SAMOVA analysis of the lineage II network suggested the existence of three population groups (FCT highest for K = 3). The 19 populations clustered as follows: Guangzhou, Zhuhai, Nanning, Pingxiang, Yuxi, Hekou, Yuzhong, Guiyang, Haikou, Wenchang, Taibei, Bangkok, and Phou Phanang as Subgroup 1; Fuzhou, Zhangzhou, and Xiamen as Subgroup 2; and Manila alone as Subgroup 3. The group comprising most of mainland China, Hainan island, Taiwan island, and southeastern Asia (including mix zones) was found to be the largest subgroup among all the samples   within lineage II  but moderate amount of differentiation between three other southeast Asian populations  and all other populations (Fst range of -0.03232–0.20702). The amount of differentiation among B. dorsalis s.s. populations within China was also moderate (Fst range of -0.02021–0.10041)  (Table Hp) ranged from 6 to 25. Haplotype diversity (Hd) ranged from 0.833 to 1.000, and nucleotide diversity (π) ranged from 0.00781 to 0.02586. These differences suggested that all populations retained fairly high levels of genetic diversity. The Manila population showed the most nucleotide diversity (π), followed by the Pattaya population.Results obtained from genetic diversity analysis among the 19 geographic populations are summarized in Table The migration rate of lineage II was estimated in both directions using MIGRATE. Results are shown in Additional file ND1 genes was used to perform Tajima’s D test to determine significance of deviations from neutrality. A negative D value is produced when more than an expected number of polymorphic sites have low frequencies within a sample. This pattern can be explained by either a recent increase in the size of the population or recent selection [D = -1.08524, P = 0.17095; Table P > 0.1). This is consistent with a neutral mutation hypothesis for the polymorphisms observed in the ND1 gene. Tests of population expansion using Fu’s Fs were negative and statistically significant across the entire dataset . The mismatch distribution of lineage II populations was distinctly unimodal  and mismatch distribution analysis  . The parameters of the expansion model were θ0 = 0.002, θ1 = 11.597, and τ = 9.3203 (Table P < 0.05). The ratio between estimated effective population size after expansion (θ0) and before expansion (θ1), which can serve as an estimate of the extent of population growth, was 6589× for lineage I and 195,319× for lineage II.The mismatch distribution of lineage II was compatible with the sudden expansion model (0) Table . The parCOI and COII) have served as molecular makers in studies of the population genetics of invasive insects [B. dorsalis s.s. population have focused primarily on mitochondrial genes encoding subunits I or II of cytochrome oxidase (CO I or CO II) [B. dorsalis s.s. found in China is a recent invasion [ND1) may be suitable for the study of geographical populations and genetic evolution in insects [ND1 was chosen for the present study of B. dorsalis s.s. population genetics. Earlier claims, in terms of sampling strategy, were not based on an extensive coverage of the distribution of known species. Until recently, B. dorsalis s.s., B. papayae, and B. philippinensis were thought to belong to different species [B. philippinensis distribution area and B. dorsalis s.s./B. papayae transition zone).Molecular markers are useful tools for genetic analysis. They can be used to elucidate the mechanisms underlying biological invasion. They are applicable to the identification of cryptic invasions, reconstruction of invasion history, and assessment of the genetic structure of a population . Mitocho insects -26. Alth insects -20,27. B insects -30. Recer CO II) ,15,31-33 insects . Based o species ,5. For tND1 gene indicated the existence of two distinct lineages that are sympatric within some parts of Pattaya and Panzhihua  [Evidence from the anogaster, Drosoph simulans, Rhagoleis cerasi, mosquitis cerasi, Hemipteia tabaci,41, and pus (L.) ,43. Thespus (L.) ,42,43. Ipus (L.) .B. dorsalis s.s population had experienced a large-scale population expansion, the ARLEQUIN 3.5 software package was used to analyze mismatch distribution between the haplotypes’ base variance. The results showed significant differences between observed and expected values of the haplotypes’ base variance along with distinct unimodality distribution patterns of variation  was 190,000 times higher than before expansion (θ0)  .Median-joining networks showed that each clade contains both widespread and localized haplotypes Figure . These pn Figure . The ests is not . As indik) Table , ChineseB. dorsalis complex were based on geographical subdivisions due to the difficulties of discrimination using morphological traits [B. philippinensis and B. occipitalis but not B. dorsalis s.s are distributed in the Philippines [B. philippinensis population. In this population, three B. philippinensis individuals and the entire B. dorsalis s.s. population (Guiyang and Xiamen) were found to belong to the same clade. However, five B. philippinensis individuals deviated from the B. dorsalis s.s. populations . Geographic distance is probably responsible for this partitioning of genetic variation in the Philippines.Previous taxonomic analyses of the l traits ,45. Accolippines . HoweverB. dorsalis s.s. from China might have originated in southeast Asia   Table . The MIGsalis s.s,49. As isalis s.s,33,49. HND1 markers, the genetic structure, origin, and invasion history of B. dorsalis s.s. were investigated. It was observed that distinct lineages (both minor and major) originated from specific southeast Asian populations. Interestingly, minor lineages have not spread in China. Evidence was found indicating symmetrical migration from southeast Asia to China. Understanding origin and genetic structure of B. dorsalis s.s. will possibly assist in the development of effective management strategies to prevent biological invasion. Source-tracking and minor distinct lineage “encounter” approaches may also provide better clues to the design of appropriate control methods, such as introducing natural enemies, to minimize biological invasion of B. dorsalis s.s. in China.Using mitochondrial DNA Adult male flies were collected from 19 natural populations from different locations within China and surrounding areas. All the collections were done during 2007 and 2008. Flies were captured using traps baited with parakairomone methyl eugenol  and ND1-R (5′-GAAAAAGGTAAAAAACTCTTTCAAGC-3′) [Total DNA was extracted from 334 individual specimens using the Universal Genomic DNA Extraction Kit (TaKaRa). The AAGC-3′) . PCR wasHd), nucleotide diversity (π), average number of differences in nucleotide sequence between haplotypes (k), and standard deviation were determined using DNASP 5.0 [DNA sequences were assembled using SeqVerter™ and aligned using CLUSTALX 2.0 . They weNASP 5.0 . To depiNASP 5.0 ,54. A phNASP 5.0 .μ, where m is the immigration rate per generation and μ is the mutation rate per generation per locus) among populations. One long chain of 100,000,000 generations was set, with the initial 10,000 excluded as burn-in.The coalescence-based program MIGRATE-N 3.5.1 was used to test for and estimate gene flow between populations . MIGRATECT. An AMOVA hierarchical analysis of variance was performed using ARLEQUIN 3.5 to partition total variance into its components among groups, among populations, and within populations [Spatial analysis of molecular variance was performed using SAMOVA 1.0 to identify population groups . Sequenculations . This waP < 0.01) [The correlation of genetic differentiation (Fst) over geographic distances for all pairs of populations was tested using the Mantel permutation procedure as implemented in ARLEQUIN 3.5  .D test, Fu’s Fs test, and mismatch distribution analysis implemented in ARLEQUIN 3.5 [D and Fu’s Fs tests were carried out to examine the deviations from neutrality expected with population expansion. Significant negative D and Fs values were considered characteristic of population expansion. Mismatch distribution analysis was performed to evaluate the frequency distribution of pairwise differences between sequences. A unimodal approximate Poisson-like distribution is expected for populations that have experienced demographic expansion in the recent past, but multimodal frequency distribution is expected for populations at equilibrium [SSD) statistics using ARLEQUIN 3.5 [Demographic history was examined using neutrality statistics of Tajima’s QUIN 3.5 ,60. Tajiilibrium . PopulatQUIN 3.5 ,63.The authors declare that they have no competing interests.JTL conceived the ideas for the study; SYB, JM, HLH, XFL, and JTL collected the samples; ZZW and HML performed the experiments; ZZW analyzed the data and composed the manuscript. All authors have read and approved the final manuscript.Subgroups of lineage II. The three subgroups are shown by different colors.Click here for fileND1 identified in each population.Haplotypes of Click here for fileCoefficient of genetic differentiation  and geographic distances  of lineage II.Click here for fileNeighbor-joining tree of lineage I and II.Click here for fileImmigration rate between population pairs estimated using MIGRATE.Click here for file


Historical and contemporary evolutionary processes can both contribute to patterns of phenotypic variation among populations of a species. Recent studies are revealing how interactions between historical and contemporary processes better explain observed patterns of phenotypic divergence than either process alone. Here, we investigate the roles of evolutionary history and adaptation to current environmental conditions in structuring phenotypic variation among polyphenic populations of sunfish inhabiting 12 postglacial lakes in eastern North America. The pumpkinseed sunfish polyphenism includes sympatric ecomorphs specialized for littoral or pelagic lake habitats. First, we use population genetic methods to test the evolutionary independence of within-lake phenotypic divergences of ecomorphs and to describe patterns of genetic structure among lake populations that clustered into three geographical groupings. We then used multivariate analysis of covariance (MANCOVA) to partition body shape variation (quantified with geometric morphometrics) among the effects of evolutionary history (reflecting phenotypic variation among genetic clusters), the shared phenotypic response of all populations to alternate habitats within lakes (reflecting adaptation to contemporary conditions), and unique phenotypic responses to habitats within lakes nested within genetic clusters. All effects had a significant influence on body form, but the effects of history and the interaction between history and contemporary habitat were larger than contemporary processes in structuring phenotypic variation. This highlights how divergence can be better understood against a known backdrop of evolutionary history. Trait differences among populations and species are often interpreted as being the result of contemporary evolutionary processes, such as adaptation to current ecological conditions, or the result of historical evolutionary process such as bottle necks, genetic drift, or adaptation to past ecological conditions. Comparative approaches are frequently used to test for adaptation to ecological conditions by demonstrating a significant correlation between current conditions and organismal traits in an attempt to reject random chance as an explanation for trait differences among populations . UnexplaMore likely though, is that both contemporary and historical processes contribute to trait variation among species and populations . FurtherDisentangling the effects of historical from contemporary processes and the dynamic effects of history interacting with contemporary processes is possible when a phylogeny accurately describes the evolutionary relationships among species; or within species, population genetics is used to establish patterns of genetic structure among populations. Significant historical processes are expected to cause phenotypic similarities among populations nested in lineages that reflect patterns of common ancestry . A signiStudies investigating the phylogeography , ecologyThe pumpkinseed sunfish of North America exemplifies how a variety of mechanisms contribute to phenotypic diversity. Pumpkinseed sunfish are a common species with a wide distribution in northeastern North America that is more northerly than all other sunfish, including a substantial region of postglacial environment . Its funWe have been exploring the mechanisms that shape phenotypic diversity in pumpkinseed sunfish that inhabit postglacial lakes. Despite physical and ecological differences among lakes in this study system , consistHistorical evolutionary processes may also shape phenotypic variation here because polyphenism differs between related species of bluegill and pumpkinseed sunfish  and by mAn extreme possibility is that the phenotypic divergence between littoral and pelagic ecomorphs occurred only once in allopatry , and that descendants of these populations dispersed and subsequently colonized lakes resulting in contemporary populations of polyphenic pumpkinseed sunfish. This single historical origin hypothesis predicts that pumpkinseeds sampled from littoral and pelagic habitats from the same lake should be distantly related, and that pumpkinseeds sampled from the same habitat type from different lakes should be closely related. We evaluate these predictions using allelic variation at six microsatellite loci.A less extreme possibility is that ecomorphs within lakes have multiple contemporary origins, but that more recent historical effects nonetheless influence broad-scale patterns of phenotypic variation across the postglacial geographical landscape. This multiple historical origin hypothesis predicts that populations of pumpkinseed with different evolutionary histories have different phenotypes, regardless of contemporary mechanisms that currently structure diversity within lakes. Additionally, historical effects and adaptation to contemporary habitats do not preclude each other, and might interact . We use Pumpkinseed sunfish were collected between May and September 2002 from 12 lakes (hereafter referred to as “lake populations”), in which pumpkinseeds inhabit both the littoral and pelagic habitats ; Fig. 1.2, 0.136 µM dNTP, 0.36 µM dCTP, 0.45 µM of forward and reverse primers, 0.09 mg/mL BSA, 0.25 units of Taq DNA polymerase. Three loci  were amplified under the following temperature regime: 95°C for 5 min; 35 cycles of 95°C for 30 sec, annealing temperature (TA) for 1 min, 72°C for 1 min; then another 95°C for 30 sec, TA for 1 min, and finally 72°C for 10 min. The remaining loci  were amplified using a shorter program: 95°C for 5 min; 35 cycles of 95°C for 30 sec, TA for 45 sec, 72°C for 1 min. The final cycle was followed by 72°C for 5 min. The PCR products were separated on 6% acrylamide gels in TBE buffer and then visualized with a Hitachi FMBIO fluorescent imaging system  Allele sizes were determined, using FMBIO software, by comparing the fragment size from the samples to several known lane standards  included with every gel.DNA was isolated from pectoral fin tissue using a phenol/chloroform/isoamyl alcohol extraction method . Six locst values were calculated between ecomorphs in each lake using FSTAT  were used to compare the number of alleles in each population, averaged over all six loci.MSA software  was usedng FSTAT . PopulatF-statistics, which do not incorporate differences in allele size, and R-statistics, which incorporate the number of repeated units in a microsatellite as information (assuming the stepwise model of microsatellite mutation). We used Arlequin  compared to the permutated Rst values; F-statistics are appropriate when the observed Rst value is similar to the permutated Rst values.There was very limited evidence of genetic divergence between ecomorphs within lakes (see Results); therefore, ecomorph populations from particular lakes were pooled for all following analyses of geographic patterns of genetic structure. Patterns of genetic structuring were assessed using both Arlequin  to calcuGeDi 1.1 . This prst and Rst values. For this AMOVA, lake populations (ecomorphs pooled) were nested within watersheds. Second, we tested for isolation by distance (IBD) by evaluating the relationship between pairwise genetic distance and geographical distance between populations. Google Earth was used to calculate fluvial distance among all lakes in the St. Lawrence, Ottawa, and Lake Ontario drainages. The lake populations from the Hudson River drainage were not included in the IBD analyses, because contemporary gene flow between the Hudson populations and the rest of the study lakes along contemporary connections would require the movement of pumpkinseed through the marine environment . Pairwise Fst and Rst values (see above) were transformed to Fst/1-Fst and Rst/1-Rst  implemented in ARLEQUIN using both Fst/1-Rst  and the st/1-Rst  was usedce) to construct a consensus neighbor-joining phenogram among lake populations using software contained in the PHYLIP 3.5 package . (2) We also used the program STRUCTURE 2.1 (K (number of clusters) ranging from 1 to 20. The correction of K from the posterior probabilities for each K. We also assessed contemporary geographical population structure by visualizing the results of STRUCTURE models with constrained levels of K= 2 and K= 3 (Population clusters were assessed using two separate approaches. (1) We used  package . Statist methods . Thus, wTURE 2.1  to inferand K= 3 .The results of the above analyses of population genetic structure informed further tests of the effect of evolutionary history on contemporary within-lake divergence of pumpkinseed ecomorphs. Specifically, we implemented the statistical tests suggested by X and Y coordinates of 16 homologous landmarks on the left side of each fish . TPSDIG  was usedach fish . TPSRELWach fish  was usedach fish .2). Canonical variates associated with each effect of interest were retained and used to produce thin-plate spline diagrams using TPSREGR . All other loci exhibited approximately the number of deviations from HWE than would be predicted by chance (at α= 0.05) (5/120 populations). There was no significant linkage disequilibrium detected between pairs of loci in any ecomorph population. T-tests between the mean numbers of alleles per population averaged over all six loci indicated that the six New York populations had more alleles than the six Ontario populations (P < 0.005). No significant differences in the number of alleles were found between drainages after adjustment of P-values following the Bonferoni correction. A number of private alleles shared between local ecomorph pairs  were also discovered in five Adirondack lakes: Lma29 allele 105 is only found in the Harris lake population; RB20 allele 303 is only found in the Lake Rondaxe population; Lmar18 alleles 283 and 287 are only found in Paradox lake; RB7 allele 314 is only found in Round lake; Lmar14 allele 411 is only found in Lewey lake.The six microsatellite loci all showed moderate to high levels of polymorphism . In manyst values between local ecomorphs were very low (<0.008), and only in one lake (Round Lake) was it significantly different from zero (Fst= 0.005). Thus, ecomorph populations from the same lake were pooled in order to investigate broader geographic patterns of genetic structure.The null hypothesis of homogeneity of allele frequencies was rejected, using Fisher's exact test, in all pair-wise comparisons of ecomorph populations (P < 0.001), excluding comparisons between sympatric ecomorphs within lakes. There was only very limited evidence of genetic differentiation between pelagic and littoral ecomorphs within lake populations. Between local ecomorphs, the null hypothesis of homogeneity of allele frequencies was rejected (P < 0.05) in two lakes: Round Lake in the St. Lawrence drainage and Lewey Lake in the Hudson drainage. However, multilocus pairwise Fst- and Rst-based distances. All multilocus, pairwise estimates of Fst and Rst were greater than zero (P < 0.01) ; however, when only Rst values were considered, variation among drainages explained a greater proportion of molecular variation than variation among lakes within drainages . Despite the AMOVA results , mantel tests comparing genetic (Rst/1-Rst and Fst/1-Fst) and geographic distance matrices found no significant pattern of IBD among these lake populations . Taken together, pumpkinseeds sampled from particular lakes and drainages seem to be closely related to each other, however, these affiliations do not seem to reflect distances among contemporary waterways (see next).Allele size permutation tests revealed that geographical variation in allele sizes contributed useful phylogeographic information ; therefore, we present the results of both F < 0.01) . The hie < 0.01) . We detece distances had a robust topology with several nodes being supported in over 70% of the bootstrap replicates  contain relatively high numbers of individuals from different lakes. Cluster 5 includes individual fish from Rollins, Round, and Rondaxe lakes from the Hudson River drainage, cluster 12 includes individual fish from Ashby and Shadow lakes from Ontario , individuals from Ontario were generally distinguished from individuals from New York , individuals from New York were further subdivided into drainage-specific clusters , and in only Round Lake was this different from zero (Fst= 0.005). Expanded within-lake analyses of individual movement between habitats . Also, the STRUCTURE analysis identified K= 14 as the most likely number of clusters . Yet, we found no evidence that the magnitude of genetic differentiation among lake populations was related to distance between lakes along contemporary watersheds  that is consistent with earlier work . PelagicOur results suggest that the littoral–pelagic polyphenism is replicated because lineages of pumpkinseed sunfish become increasingly evolutionarily independent especially between biogeographic regions, while polyphenism is still found in many lakes. Replicated phenotypic polyphenisms support the role of divergent selection between littoral and pelagic habitats in many of the postglacial lakes of central Ontario and the Adirondack region of New York State. However, there was little evidence of heterogeneity in allelic frequency between ecomorphs in most lake populations, indicating that sympatric ecomorphs have not been sufficiently reproductively isolated for neutral alleles to become ecologically isolated at this scale as in other studies . While wDespite numerous studies that have documented associations between neutral genetic variation and phenotypic variation , we wereEvolutionary history has also influenced the contemporary process of phenotypic divergence between littoral and pelagic lake habitats (an interaction between genetic cluster and ecomorph; It is important to acknowledge that since our morphological analyses involved wild caught fish, we cannot discriminate between genetic versus environmental variation, although this has been the focus of substantial previous research in this system. Rearing studies demonstrate that a combination of minor genetic and substantial plastic developmental responses to dietary and predator cues shapes pumpkinseed sunfish phenotype including between these ecomorphs . Of greaOur study documents how the variable evolutionary histories of different populations diverging along a similar environmental gradient produce both shared and unique aspects of divergence. In addition, our understanding of these new regional effects on phenotype within pumpkinseed sunfish fills a gap in an array of historical effects that range from deep effects identified among Lepomid taxa predating that last glacial period , more re


Ultimately, the social and cultural traditions of the Kazakhs shaped their current pattern of genetic variation.Kazakh populations have traditionally lived as nomadic pastoralists that seasonally migrate across the steppe and surrounding mountain ranges in Kazakhstan and southern Siberia. To clarify their population history from a paternal perspective, we analyzed the non-recombining portion of the Y-chromosome from Kazakh populations living in southern Altai Republic, Russia, using a high-resolution analysis of 60 biallelic markers and 17 STRs. We noted distinct differences in the patterns of genetic variation between maternal and paternal genetic systems in the Altaian Kazakhs. While they possess a variety of East and West Eurasian mtDNA haplogroups, only three East Eurasian paternal haplogroups appear at significant frequencies . In addition, the Y-STR data revealed low genetic diversity within these lineages. Analysis of the combined biallelic and STR data also demonstrated genetic differences among Kazakh populations from across Central Asia. The observed differences between Altaian Kazakhs and indigenous Kazakhs were not the result of admixture between Altaian Kazakhs and indigenous Altaians. Overall, the shared paternal ancestry of Kazakhs differentiates them from other Central Asian populations. In addition, all of them showed evidence of genetic influence by the 13 After the Uzbek Khanate lost authority over the region north of Syr Darya due to Oirat incursions, remnants of the old Mongolian White Horde gained control over the area, forming a new political entity, the Kazakh Khanate th century, the Kazakhs divided to form three Zhüz, called the Great, Middle and Small Hordes Zhüz were not constructed along lines of common descent, but rather reflected the political divisions of the population and the unique geography of the region The Kazakhs first emerged as a political unit during the 15th century, independent Kazakh rule ended, with Russia taking control of Kazakh lands in the mid-1700s. By this time, a distinctive Kazakh ethnic group had formed, resulting in a shared common history, language and culture among the three Kazakh Zhüz. It was also at this time that some Kazakhs moved to the steppe lands northeast of Lake Zaysan in Kazakhstan. During the 19th and into the 20th centuries, Kazakhs migrated through Xinjiang, China, and eventually spread north around the Altai Mountains in western Mongolia and southern Russia. Sources suggest that these Kazakhs came from the Middle Zhüz, although multiple eastward migrations likely occurred Coming under increased pressure from the Kalmyks in the 18Kazakh culture derived from the nomadic cultures that were dominant among Turkic tribes living on the Central Asian steppe süök system and largely supported through extensive genealogies Despite these deeper connections to numerous Turkic-speaking populations, the Mongol Empire strongly influenced Kazakh political and social structure. This influence was of such significance that the Kazakh aristocracy legitimized its authority by claiming direct ancestry from Genghis Khan  through the auls becoming sedentary, with only some Kazakhs maintaining seasonal migrations süök social structures that helped to guide marriage practices lost importance, although patrilineal customs prevailed. Thus, the auls still consist mostly of extended families that can be recognized as closely related descent groups, and maintain some semblance of their previous culture practices.Policies enforced by the Russian government also had a significant impact on the lives of the Central Asian steppe nomads. Historical and ethnographic materials show that, through Russian acculturation, Kazakhs took up a semi-nomadic economy, which relied on their migratory Previous efforts to understand genetic variation within Altaian Kazakhs revealed a unique pattern of mtDNA diversity which differed from that of indigenous Kazakhs  It is within this framework that we investigated the paternal genetic history of Altaian Kazakhs by characterizing the non-recombining Y-chromosome (NRY) variation through analysis of high-resolution biallelic markers and short tandem repeat (STR) typing. This approach allowed us to investigate several aspects of the history of this population. To begin with, we assessed the genetic relationship between Altaian Kazakhs and indigenous Kazakhs to better understand the origins and differentiation of the Kazakh ethnic group. We also examined the extent of historical admixture between Altaian Kazakhs and their indigenous Altaian neighbors in the genetically diverse Altai-Sayan region of Siberia. At a broader scale, we explored the relationships between Kazakh and Central Asian populations in an effort to clarify the history of Turkic-speaking groups. We further examined the possible genetic influence of Mongol expansions (Mongol Empire) on the peoples who later formed the Kazakhs, as well as their impact on Turkic-speaking populations across Central Asia. Our results indicate that Kazakhs have low levels of paternal genetic diversity, and share a common paternal ancestry that has been influenced by Genghis Khan's descendants. Kazakh culture has also played a central role in shaping this genetic variation through constraints on population size and marriage practices within traditional Kazakh social structure.Paternal genetic variation within Altaian Kazakhs was rather low. Some 85% of the Altaian Kazakh Y-chromosomes belonged to one of only three haplogroups Table 1.The Altaian Kazakh samples came from two areas of the southern Altai Republic, the southwestern (SW) and southeastern (SE) regions Figure 1However, the NRY results showed no recognizable admixture between Kazakhs and Russians. The most frequent haplogroups present in southern Russia belong to R1a, N1c and I1b Comparisons of paternal haplogroup frequencies with Kazakhs sampled from four locations in eastern Kazakhstan (indigenous Kazakh) Despite these similarities, Altaian Kazakhs and indigenous Kazakhs showed a fair amount of difference in terms of their NRY haplogroup composition. Altaian Kazakhs tended to have higher frequencies of G1, G2 and J2 haplotypes, while indigenous Kazakhs had higher frequencies of Q and R1a. Thus, while the general pattern of paternal genetic variation was similar in these two groups, suggesting that they shared a common paternal ancestry, there were also specific genetic differences between them that likely reflected their respective genetic histories.Table S1). There was a large amount of variation between the two sample locations for each of the three major haplogroups. Interestingly, only two haplotypes were shared between regions. One was more frequent among SW Altaian Kazakhs (haplotype #3), while the other appeared at low frequencies in both locations (haplotype #1). Both of these haplotypes belonged to haplogroup C3*. No other haplotypes were shared when considering the full 17-STR profile.Analysis of 17 fast evolving Y-STRs provided additional details that helped to elucidate the paternal diversity among Kazakh populations. In total, we identified 51 haplotypes among the 119 Altaian Kazakhs .We also reduced the 17-STR profile to a 5-STR profile  to compare the Altaian Kazakh data with published data sets Figure 3Once the Y-STRs were reduced to five locus profiles, we were able to compare our Altaian Kazakh population to those from the published literature ST estimates provided evidence that the Kazakh populations are structured (Table S2). SE Altaian Kazakhs and SW Altaian Kazakhs were not significantly different from Kazakh1. They were also separated from Kazakh2 and Kazakh3 by large genetic distances (FST >0.139). This finding suggested that at least two subpopulations of Kazakhs exist in the regions of western Kazakhstan and the Altai Republic. Whether there are additional Kazakh subpopulations from central or eastern Kazakhstan remains to be determined.The RTo gain a better understanding of Kazakh Y-chromosome lineages, we analyzed haplogroups C3*, C3c and O3a3c*. The assessment of variation within these haplogroups was undertaken to better discern their origins, or the time at which they entered the Kazakh gene pool. While caution must be exercised when considering coalescence estimates calculated from Y-STR analysis The resulting estimates showed similarities between haplogroups and populations (Altaian Kazakh compared to indigenous Kazakh). Rho statistic estimates using the pedigree Y-STR mutation rate yielded coalescence dates for haplogroups C3* and C3c that were consistent with a source roughly 800 years ago Table 4.Using the evolutionary mutation rate, we obtained coalescence estimates that were three times older than those calculated from the pedigree rate. Accordingly, the TMRCAs for haplogroups C3* and C3c were each over 2,100 years ago. At that time (when Greek and Roman historians were first recording the activities of nomadic steppe peoples), the Scythians and Sarmatians controlled much of Central Asia In this regard, the TMRCAs based on rho statistics are likely to be underestimates. Median networks must assume that all haplotypes are identical by descent when, in fact, because of the high mutation rate of Y-STRs, there is good reason to believe that at least some could be identical by state. The Bayesian analysis generally gave higher estimates than calculations based on the rho statistic. The use of the pedigree mutation rates provided estimates between 600 and 2,300 years ago for haplogroups C3* and C3c, with expansion times 200 years later. Estimates for O3a3c* using the two methods were generally consistent. Such estimates have very broad 95% confidence intervals and, thus, cannot be used to precisely pinpoint the original source of these lineages.The 14-locus profile used to generate extended haplotypes provided greater resolution for the Altaian Kazakhs and, thus, allowed additional analysis of its populations. For each of the three major haplogroups, haplotype clusters were identified using median network analysis. These clusters could represent clans within the Altaian Kazakhs similar to the “identity cores” described in Central Asian populations Molecular diversity estimates and genetic distances were calculated to quantify the levels of genetic variation within and between Altaian Kazakhs and Central Asian populations. We used haplogroup frequencies from 28 populations for the principal components analysis (PCA) Figure 4ST estimates computed from the Y-STR data and plotted using multidimensional scaling (MDS)  had limited genetic affinities with Central Asian populations aside from the Kazakh1. The remaining Kazakhs were positioned on the opposite side of the plot. Unlike the PCA, the Altaian Kazakhs were clearly separated from the indigenous Kazakh populations, with the latter showing greatest affinities with lowland Kyrgyz.Populations were also compared using Rng (MDS) Figure 5Comparisons of Central Asian Y-STR haplotypes provided additional evidence for the distinctiveness of the Kazakh Y-chromosome gene pool. The most frequent Altaian Kazakh haplotypes were shared with one or more of the three indigenous Kazakh populations. All but one of these haplotypes was also shared with Mongolians. Aside from the modal haplotypes, few were shared among Kazakhs and Central Asians . The Kyrgyz showed even greater differentiation from Central Asians than did Kazakhs. Thus, the Kazakhs and Kyrgyz are unique for Central Asia in not sharing many haplotypes with their neighbors. However, unlike the Kyrgyz, the populations with the greatest affinities to Altaian Kazakh populations were Mongolians.Haplotype diversity and average pairwise differences indicated a lower level of genetic diversity among the Kazakh populations when compared to published data from other Central Asians. Turkmen and Kara-kalpak showed similarly low levels, with only the highland Kyrgyz being significantly less. These same populations showed the greatest distances from the central cluster in the MDS plot. All of these low-level diversity groups recently shared a similar semi-nomadic lifestyle, and are organized by patrilineal descent groups.ST findings. This split resulted in an increase to 7.1% “among group” and a decrease to 4.1% for “among population within group.” About 12.8% of the variation was explained in the “among population within group” for the language and geography categories, with non-significant values for the “among group” category. The influence of geography on genetic variation was also explored using SAMOVA, but no clear geographic groupings showed significant “among group” values (data not shown).AMOVA was used to examine the partitioning of the genetic variation for these Central Asian and Mongolian populations Table 6.In this study, we characterized NRY variation in Altaian Kazakhs of the Altai-Sayan region of Siberia using high-resolution biallelic marker and STR analysis. To our knowledge, this is the highest NRY resolution data set for any Central Asian or Siberian population that has been published. The primary objectives of this study were to assess the paternal genetic variation in Altaian Kazakh populations and their population histories, to understand the paternal origins of Kazakhs, and to elucidate the process by which this ethnic group formed.Altaian Kazakhs do not represent a single genetically isolated population. The paternal lineages present in the Altaian Kazakhs are generally distinctive from those appearing in indigenous populations among which the Kazakhs live. However, the interactions between indigenous Altaian and Kazakh groups differ between the two regions examined in this study. This difference, in turn, affects the overall amounts of genetic diversity within each Kazakh group and the extent of genetic relatedness they have with each other and their neighbors.Interestingly, SW Altaian Kazakhs share NRY lineages with indigenous Altaians, while SE Altaian Kazakhs do not. While one must be cautious in interpreting these results due to the relatively small sample size of SW Altaian Kazakhs, this population still possessed higher levels of Y-chromosome diversity than the numerically larger SE Altaian Kazakhs. In addition, lineages not typically found in other Kazakh populations were present in the SW population. These findings were further supported by genealogical information collected in the field.Zhüz to this village The samples from the SW region came primarily from one location. Historical evidence shows that this location is a community that consisted of Russian, indigenous Altaian and Kazakh individuals who have lived amongst each other for the past 150 years Despite the differences observed among Altaian Kazakhs from these two regions of the Altai Republic, similarities at the haplogroup level were observed. Comparisons of Altaian Kazakhs and indigenous Kazakhs ultimately reveal a shared biological history. High frequencies of haplogroups C3* and C3c accompanied by the near absence of R1a1a* not only connect these Kazakh populations, but also sets them apart from other Central Asian populations. The ubiquity of haplogroup C-derived lineages in all Kazakh populations indicates that this ethnic group likely arose from a common source, even though political necessity – not common ancestry – defined the Kazakh Khanate in its beginning. Undoubtedly, not all of the lineages making up the Kazakh Khanate in its initial construction survived to the present, but at least a large portion of those that did survive are related.Within this framework of common paternal ancestry, the Y-STR data highlight the fact that Kazakh populations are not entirely homogenous. Overall, the genetic differences between the two groups of Altaian Kazakhs are relatively small. However, they do share affinities with one set of indigenous Kazakhs (Kazakh1). Zerjal et al. To some extent, these findings are not surprising. Differentiation of NRY haplotypes among populations (even within an ethnic group) is known to be common for pastoral Central Asian populations Zhüz) has played in maintaining and/or redistributing genetic variation among Kazakh populations. These Zhüz were not based on common descent, but neither was the Kazakh Khanate in its infancy. In fact, the Kazakh Khanate reportedly formed from people associated with the Uzbek Khanate, which itself was an amalgam of Turkicized Iranian peoples, Eastern Kipchak nomads and Chagatai Turks One potential source for this distribution may have to do with the role that political organization  süök also claimed descent from Genghis Khan. NRY lineages (C3*) that putatively belong to Genghis Khan and his descendants are, in fact, found in high frequencies among the Kazakhs. Thus, these lineages could have spread by social selection The Indeed, social structure has played an important role in shaping genetic variation in Central Asian populations. The cultural customs of descent lines, marriage and residence patterns significantly affect patterns of maternal and paternal lineage diversity süök) to increase in frequency.The small population sizes, in addition to the sex-specific nature of gene flow, produced the differences noted between the paternal and maternal genetic systems. As previously mentioned, only a small number of NRY haplogroups and haplotypes are present in Altaian Kazakhs, reflecting low levels of Y-chromosome diversity. However, the mtDNA evidence suggests that Altaian Kazakhs have a heterogeneous maternal ancestry, as would be expected given the patrilocal and patrilineal social structure of Kazakhs. Therefore, while the Kazakhs' social structure promoted change through genetic drift, social selection caused particular lineages  had on Central Asian populations is harder to untangle. NRY haplogroups C3* and C3c are found in nearly every Altaic-speaking population Haplogroups R1 and Q are also well attested in Altaic-speakers th century CE. The presence of the C3* haplotype cluster in the Kazakh also supports the genealogical assertions that (for at least some Kazakh men) there is a direct paternal connection to Genghis Khan.The difficulty in reliably determining the coalescent dates for the lineages found in Kazakh populations makes it nearly impossible to determine whether these lineages were present in ancestral nomadic steppe groups  or were contributed by the descendents of Genghis Khan and the Mongol armies that, at one time, held control over the region. An important reason for caution here is the current debate about the most appropriate mutation rate for NRY coalescence estimates. The evidence provided by Zerjal et al. th century CE.If the evolutionary rate is the more accurate value for Y-STRs, then the Kazakh lineages coalesce to roughly 2,000 years ago. This date suggests a far older source for them, possibly with the westward movements of Altaic-speaking peoples around the second and first centuries BCE. In this case, we would expect to see multiple haplotype clusters exhibiting a similar pattern as the Genghis Khan cluster. However, we do not observe this pattern. As Zerjal et al. Ultimately, the genetic variation in Central Asian populations clearly depends on the social and cultural contexts within which these populations exist(ed). Populations that have small effective population sizes and follow patrilocal customs and patrilineal descent are prone to genetic drift while, at the same time, able to maintain a dominant patrilineal group composed of closely related men. Thus, while founder effects likely occurred during the ethnogenesis of the Kazakhs, their cultural practices subsequently shaped and maintained their paternal genetic diversity.Blood samples were collected from participants during several field expeditions conducted between 1991 and 2002. A total of 119 male Altaian Kazakh samples were collected from four locations in two regions of the Altai Republic, Russia Figure 1To elucidate the phylogeographic connections of Altaian Kazakhs to other populations in Central and East Asia, we compared their NRY data to those obtained from the published literature. For the haplogroup  analysis, we used data from the following groups: Kazakh, Kyrgyz, Uzbek, Tajik, and Dungan For comparisons with both biallelic marker and STR data, we condensed our high-resolution data set to make it compatible with those available in published studies. Thus, the paternal haplogroups were collapsed into 14 larger clusters that were more inclusive of the published data sets . Similarly, the STR haplotypes were reduced to six loci  to permit as broad a comparison as possible.lSTR Yfiler PCR Amplification Kit (Applied Biosystems), and read on a 3130xl Genetic Analyzer with GeneMapper ID v3.2 software.Genomic DNA was extracted using standard phenol/chloroform methods The assignment of each sample to NRY haplogroups followed the conventions outlined by the Y Chromosome Consortium ST values between populations and AMOVA were calculated using Arlequin v3.11. RST values were calculated from STR haplotypes and visualized using multidimensional scaling (MDS) with SPSS 11.0.0.Summary statistics were calculated using Arlequin v3.11 AMOVA was used to assess the amount of genetic variation partitioned “among groups”, “among populations within groups” and “within populations” for geographic, ethnic and linguistic categories. The nature of genetic variation within Altaian Kazakh and that between them and indigenous Kazakh populations was examined, with Altaian Kazakhs being placed in one group and the indigenous Kazakhs in the other. Geographic structuring of diversity was also explored using three regional groupings: (1) Altai region, including Altaian Kazakhs and indigenous Altaians; (2) Central Asia; and (3) Mongolia/Northern China. We also used two linguistic categories, with Central Asians, Kazakhs and Altaians belonging to one group (Turkic) and Mongolians to a second (Mongolic). Finally, we analyzed variation in populations based on their respective ethnic group membership.Lineages consisting of biallelic markers and STR data provided the basis for the phylogenetic analysis. Relationships between haplotypes were studied using Network 4.5.1.6 and Network Publisher 1.2.0.0 The time to the most recent common ancestor (TMRCA) and expansion times were calculated with Batwing. The prior distributions for Batwing follow those established in previous studies, and were run for 50,000 cycles, with the removal of a 5,000 cycle burn-in Table S117 Y-STR haplotypes for Altaian Kazakhs.(PDF)Click here for additional data file.Table S2ST value matrix of Central Asian and Mongolian populations.R(PDF)Click here for additional data file.


The human populations of the Iberian Peninsula are the varied result of a complex mixture of cultures throughout history, and are separated by clear social, cultural, linguistic or geographic barriers. The stronger genetic differences between closely related populations occur in the northern third of Spain, a phenomenon commonly known as “micro-differentiation”. It has been argued and discussed how this form of genetic structuring can be related to both the rugged landscape and the ancient societies of Northern Iberia, but this is difficult to test in most regions due to the intense human mobility of previous centuries. Nevertheless, the Spanish autonomous community of Asturias shows a complex history which hints of a certain isolation of its population. This, joined together with a difficult terrain full of deep valleys and steep mountains, makes it suitable for performing a study of genetic structure, based on mitochondrial DNA and Y-Chromosome markers. Our analyses do not only show that there are micro-differentiation patterns inside the Asturian territory, but that these patterns are strikingly similar between both uniparental markers. The inference of barriers to gene flow also indicates that Asturian populations from the coastal north and the mountainous south seem to be relatively isolated from the rest of the territory. These findings are discussed in light of historic and geographic data and, coupled with previous evidence, show that the origin of the current genetic patterning might indeed lie in Roman and Pre-Roman sociopolitical divisions. The Iberian Peninsula, also called by its ancient Greek name “Iberia”, is a crossroads between mainland Europe, northern Africa, the Atlantic Ocean and the Mediterranean Sea The northern third of the Peninsula, which comprises the Spanish autonomous communities of Galicia, Asturias, Cantabria, Basque Country, Navarre, Aragon and Catalonia, is separated from the rest of the territory by the mountains of the central plateau. Even close populations from these communities show distinctive distributions of uniparental genetic markers such as the mitochondrial DNA (mtDNA) and the non-recombining portion of the Y-Chromosome (NRY), a situation that has been defined by some authors with the terms “micro-differentiation” or “micro-geographical differentiation” th–20th centuries Of the aforementioned Spanish communities, Asturias  comprises the most mountainous region of Iberia and one of the most mountainous of Atlantic Europe th century, it is unclear how the social organization evolved in Asturias, and the ensuing internal division that is well-known is that of the Medieval Feudal and Monastic lordships th century, and are the origin of the current eight territorial regions in which Asturias is politically divided, as defined by the Decree for the Asturian Territorial Planning (Law 11/1991–24th January).The land area of Asturias, of around 10.000 square kilometers, has not changed much since it was demarcated by the Roman Emperor Vespasian in 73 CE The availability of such a long lasting internal division, coupled with the difficult terrain and the proposed tendency to isolation, makes this region suitable for assessing not only the possibility of micro-differentiation, but also for comparing genetic and sociopolitical structuring in the aforementioned manner. In fact, some evidence of regional differences was already found in classical anthropological studies of the Asturian population based on blood groups and dermatogliphics Samples of buccal cells were obtained from volunteers recruited in various cities and towns of Asturias during the period 2009–2011 using swabs with Dacron tips . All female volunteers confirmed having at least two generations of autochthonous maternal ancestry (i.e. grandmothers born in Asturias), while male volunteers confirmed having at least two generations of autochthonous maternal and/or paternal ancestry (i.e. grandmothers and/or grandfathers born in Asturias). After sample collection, volunteers from both sexes with suitable maternal ancestry were used for the mtDNA study (361), while Y-Chromosome was analyzed only for males with suitable paternal ancestry (184). A protocol based on the Chelex-100 resin  was used for DNA extraction for all samples rd).The study was approved by the Research and Ethics Committees of the Central University Hospital of Asturias and the University of Leon (Spain) and a written informed consent was obtained from each sample donor, according to the Spanish Law for Biomedical Research  of the 361 samples used in the present study was PCR-amplified for a previous work 14 Unique-Event Polymorphisms (UEPs) of the non-recombining portion of the Y-Chromosome of 184 samples were amplified and genotyped using the PCR-RFLP protocols described in An updated haplogroup assignment was performed for all mtDNA samples with the software HaploGrep Haplogroup assignment for NRY samples was performed on the basis of the PCR-typed UEPs, using the most updated phylogenetic tree available Traditional population genetic statistics were obtained with Arlequin v3.512 ST matrix, computed separately for each dataset. To assess the possibility of a phylogenetic subdivision between populations ST matrix based on Tamura-Nei distances for the mtDNA data ST matrix for NRY haplotypes Population differentiation was analyzed by means of a classic FGeographic distribution of the different haplogroups was assessed by a principal component analysis (PCA) of haplogroup frequencies of the different regions performed with PRIMER v6 ST/RST distances. For comparison purposes, other AMOVAs based on FST distances and landscape features of the Asturian territory were also computed.To further analyze the effect of geography on the genetic structure of Asturian populations, the software SAMOVA was used to define groups of genetically and geographically homogeneous populations maximally differenced from each other ST/RST distance matrices. To test for barrier significance, 100 bootstrap replicates of each dataset were computed in MATLAB v7.8 The existence of barriers to gene flow, which usually is a determinant for the establishment of genetic patterns, was assessed with the software BARRIER v2.2 Finally, a rooted and dated tree of population splits was computed using BATWING Geographic maternal origin of all samples is reported in ST-analogues which already include corrections for unequal and small sample sizes Data on census population size and territorial extension of all populations is reported on ST/FST matrices, both shown in ST matrix, especially in pairwise comparisons involving the populations of Oriente and EoNavia. Equivalent values in the ΦST matrix were zero or non-significant, thus indicating an uncoupling between haplotype and molecular differences inside the Asturian maternal pool. The same approach was used for the comparative analysis involving neighboring Spanish autonomous communities, which have been found to be substantially differentiated from most Asturian regions  are higher than their equivalent haplotype distances (FST) in most pairwise comparisons, but some of those involving the Oriente and EoNavia regions are again showing the opposite trend. The comparative analysis with other neighboring populations follows closely the results obtained for the mtDNA, showing particular NRY pools for each of them  should be downwardly biased in respect to indexes based on molecular distances (ΦST/RST), as the frequency of most haplotypes is extremely rare The Asturian population, as a whole, presents a complex genetic makeup that is highlighted due to the extreme variability of the mitochondrial control region and the NRY microsatellite loci. To obtain an accurate picture of genetic diversity within the Asturian sample, we examined its subpopulations separately. Theoretically, for hypervariable loci such as those used in this study, population differentiation indexes based on haplotype frequencies  is similar to the other regions. Differences in haplogroup composition are related to the high levels of mitochondrial haplogroup U4 (15%) and Y-chromosomal basal haplogroup F (20%). The first is a typical Eastern European lineage scarce in Southwestern Europe This study has combined two highly variable uniparental markers, the mtDNA and the NRY, to assess the diversity, on a regional level, of the population of Asturias. This has allowed us to find, for such a small territory, evidence of micro-differentiation patterns remarkable even in comparison to others found in the Northern third of the Iberian Peninsula. These are explained by considering models of population subdivision based on geographical barriers, but emphasizing the effect of historical events. The resulting structure is compatible with Roman and pre-Roman social and political divisions. While the influences of these are difficult to quantify, their consideration provides a better understanding of genetic data, and of the causes behind its patterning. Further work is needed to characterize and understand the local processes that have took place in such a complex territory and to see if they are can be used to infer demographic and phylogeographic processes at a regional or national scale.Table S1PCR-RFLP protocols used for the NRY haplogroup determination.(PDF)Click here for additional data file.Table S2Additional genetic data used in the population differentiation analyses.(PDF)Click here for additional data file.Table S3Additional haplogroup frequency data used in the PCA plots.(PDF)Click here for additional data file.Table S4Geographic and genetic details of samples used in the mtDNA analyses.(PDF)Click here for additional data file.Table S5Extended version of  from manuscript, including effective population estimators and demographic indicators.(PDF)Click here for additional data file.Table S6ST/FST matrices showing a comparison of Asturian regions with neighboring populations, based on mtDNA data.Φ(PDF)Click here for additional data file.Table S7Geographic and genetic details of samples used in the NRY analyses.(PDF)Click here for additional data file.Table S8ST/FST matrices showing a comparison of Asturian regions with neighboring populations, based on NRY data.R(PDF)Click here for additional data file.Reference List S1Additional references used in Supporting Information files.(PDF)Click here for additional data file.


Picoides pubescens), a common member of the forest bird communities in North America with a continental distribution. DNA sequences from the mitochondrial tRNA-Lys, and ATPase 6 and 8 genes, and microsatellite data from seven variable loci were combined with a species distribution model (SDM) to infer possible historical scenarios for this species after the last glacial maximum. Analyses of Downy Woodpeckers from 23 geographic areas suggested little differentiation, shallow genealogical relationships, and limited population structure across the species’ range. Microsatellites, which have higher resolution and are able to detect recent differences, revealed two geographic groups where populations along the eastern edge of the Rocky Mountains  were genetically isolated from the rest of the sampled populations. Mitochondrial DNA, an important marker to detect historical patterns, recovered only one group. However, populations in Idaho and southeast BC contained high haplotype diversity and, in general were characterized by the absence of the most common mtDNA haplotype. The SDM suggested several areas in the southern US as containing suitable Downy Woodpecker habitat during the LGM. The lack of considerable geographic structure and the starburst haplotype network, combined with several population genetic tests, suggest a scenario of demographic expansion during the last part of Pleistocene and early Holocene.The glacial cycles of the Pleistocene have been recognized as important, large-scale historical processes that strongly influenced the demographic patterns and genetic structure of many species. Here we present evidence of a postglacial expansion for the Downy Woodpecker ( Continental North America has been a climatically and biologically dynamic place during the last two million years, especially during the last part of the Quaternary ice ages, 21,000 years ago when the polar ice sheets were at their maximum extent oN with the Pacific Northwest, Northeast coast, Southwest US and Beringia serving as the major refugia for a diverse array of organisms. Some examples of species that may have used these refugial areas include the Chestnut-backed Chickadee (Poecile rufescens), Steller’s (Cyanocitta stelleri) and Mexican Jays (Aphelocoma ultramarina) Glaucomys sabrinus), Red-backed Voles (Clethrionomys gapperi), American Marten (Martes americana); Spotted Salamander (Ambystoma maculatum) and Western Diamondback Rattlesnake  . In contrast to Europe mountain ranges in North America run north-south and patterns of postglacial colonization from southern refugia differ between the two continents North America has been one of the main areas for studies on post-glacial expansion, and as such is an area where the impacts of the last glacial maximum (LGM) on organisms from a geological and biological perspective are best understood Despite the knowledge gained from multiple studies during the last two decades, the understanding of how different lineages and species responded in a spatio-temporal context to the retreat of the ice sheets following the LGM is still in its infancy Junco hyemalis and J. phaeonotus) have high morphological and ecological differentiation Studies on phylogeography and population genetics of Nearctic birds have uncovered an array of different trends Patterns of genetic variation can be used to make predictions about the demographic and evolutionary history of an organism within the context of the LGM. One extreme are species with genetically structured populations displaying a gene genealogy with highly differentiated groups and collections of unique mitochondrial haplotypes or nuclear alleles restricted to specific areas, in addition to high nucleotide and haplotype diversities Picoides pubescens, Picidae) a small, sexually dimorphic woodpecker inhabiting a variety of habitats including coniferous, deciduous and mixed forest and tall shrubbery. It is a year-round resident ubiquitously distributed in North America from Alaska to Florida  differing mostly in characteristics such as body mass and plumage coloration. Larger birds inhabit northern latitudes and higher elevations, and smaller birds live further south and at lower elevations Picoides villosus), the Brown Creeper (Certhia americana) and the Dark-eyed Junco  present some similarities, for instance, there are several subspecies, and geographic variation in terms of body size and natural history traits Here we focused on the Downy Woodpecker ( Florida  [32]. SoPicoides pubescens) using a series of population genetic statistics derived from mitochondrial DNA sequences and microsatellite data and created for the first time a species distribution model (SDM) at 21 kya. Preliminary evidence suggests that the Downy Woodpeckers were different than today’s in terms of population size and distribution during the late Pleistocene We studied geographic patterns of genetic variation for the Downy Woodpecker (dH = 0.5839) diversity was moderate. Population π ranged from 0.0002–0.0031 and dH from 0.182 to 1.000 , and Louisiana exhibited the highest diversity for the same two genetic indices  was low while haplotype (to 1.000 . Among t indices .P = 0.0217) and Vancouver Island  deviated from Hardy-Weinberg equilibrium, but neither was significant after correction for multiple tests. No evidence of linkage disequilibrium was found among loci as indicated by Fisher’s exact test .MICRO-CHECKER showed no evidence of scoring errors due to allele dropout or stutter for any of the loci. The only evidence for null alleles arising from an excess of homozygotes was at DlU5. Both Illinois-Wisconsin  or longitude .The seven variable microsatellite markers had moderate levels of genetic variation among loci and across populations. The number of alleles per locus (and average number) ranged from 4 (2.7±0.159) in DMD9 to 17 (9.4±0.608) in DMD118. On average, Alaska had the lowest number of alleles (3.3±0.71), while Nova Scotia – New Brunswick had the highest (6.1±1.08) . MicrosaFST comparisons across 21 sampling locations revealed minor differences among most pairs of populations (FST/(1-FST)) as a function of the geographic distance among populations revealed no significant relationship .Mitochondrial-based pairwise ulations . Most ofulations . PlottinFST comparisons among 15 sampling locations ranged from −0.007 to 0.086 .Microsatellite pairwise to 0.086 . In geneQ >0.6) for each individual, one group includes Utah, Montana, Colorado and southern Alberta, and the second group includes most of the other populations. The exceptions to these two groups were Alaska, Michigan and central Alberta in which most individuals were equally assigned to both groups . Likewise, Tajima’s D rejected a scenario of selective neutrality and population equilibrium . Fu and Li’s D*  and F*  were both negative and significant, supporting the results of Fu’s Fs and Tajima’s D. Nonetheless, a unimodal mismatch distribution signals that Downy Woodpecker populations have undergone periods of population growth  (P = 0.36).Statistical parsimony analysis of the 55 mitochondrial haplotypes produced a starburst pattern, a common, central haplotype different from most of the other haplotypes by one or two nucleotide differences, suggestive of a demographic expansion. Expansion times for the different populations suggest a time frame between 6,294 and 178,764 years, where the time of expansion for several areas is after the LGM  . This waThe absence of any geographic pattern in the haplotype distribution in the TCS network suggests limited phylogeographic structure of breeding populations of the Downy Woodpecker in North America . A singlThe resulting models for the current and LGM 21 kya Downy Woodpecker distribution in North America were constructed based on 16,271 presence records used for testing and 5,423 for training. The predicted models for the current distribution and at 21 kya were statistically robust using guidelines suggested by The predicted model for the current distribution suggests a strong correspondence with other sources of information related to the current species’ distribution . The preThis study examined on rangewide patterns of genetic variation in the Downy Woodpecker in the context of postglacial expansion and colonization of North America and expands on previously published work Patterns in genetic diversity indices for mtDNA and microsatellites have been shown to be similar, but can also vary in the same species FST based differences suggest partially incongruent patterns between mtDNA and microsatellite data, which is expected under equilibrium due to different effective population sizes and other factors, such as higher mutation rates in microsatellites than mtDNA 2r = 0.0091, P = 0.220, microsatellites: 2r = 0.1103, P = 0.070). Therefore, over a large geographic scale, the effects of genetic drift may be stronger than gene flow explaining why patterns of significant FST values do not necessarily correspond to geographically clustered populations. A similar pattern albeit at a different geographic scale is found in the Greater Prairie-Chicken (Tympanuchus cupido) d = 0.18); however, tests for recent bottlenecks were not significant (P = 0.62). In contrast, gene flow in the eastern Rockies  may be restricted by a number of factors including habitat and landscape barriers Three sets of populations: Alaska, populations east of the Rocky Mountains and populations in the Intermountain West (Revelstoke BC and Idaho) show evidence of restricted gene flow. The patterns for the first two sets of populations are only evident with microsatellite markers. In the case of Alaska allele frequency differences may be the result of a founder event as evident from the low mtDNA variation (HdH) diversities and allelic richness (AR) than others , it is possible that populations are not reproductively isolated, and individuals are moving between distant geographic areas. However, we cannot claim there is or has been continuous gene flow since some populations (e.g. Illinois-Wisconsin or Missouri) have higher haplotype  suggest that current Downy Woodpecker populations expanded from 178,764 (BC Revelstoke) years to 6,294 years (Alaska). Several populations such as Washington and southern Alberta expanded around the 21 kya period whilst other  predates the LGM boundary. Although these estimates can be a reference to understand the demographic history, the putative times should not be taken as conclusive as they are highly dependent on the mutation rates.In much the same way, the genetic patterns depicted here are suggestive of at least three explanations for the Pleistocene demographic history of this species. One is the rapid population expansion typified by starburst as seen in the mtDNA network  and supps and Tajima’s D rejected the null hypothesis of population stability.Several independent lines of evidence support a postglacial expansion by the Downy Woodpecker during the last 21 kya. First, a star-like haplotype network characterized by a predominant haplotype and accompanied by a collection of low frequency peripheral haplotypes differing by one or two mutational steps from the main haplotype Finally, the species distribution model for the Downy Woodpecker at 21 kya suggests two distinct refugial areas, one in the southeastern US and the second in the west from Arizona to Oregon. Assuming that this distribution model represents a realistic scenario, it strongly favors a limited number of southern refugia. The predicted LGM habitat does not support any additional areas north of the ice sheets, such as Beringia, for Downy Woodpeckers. From a genetic point of view, both mtDNA and microsatellite data, Alaska has the lowest genetic diversity of all the populations (and lacks unique genetic variants), suggesting that it was recently colonized from other populations. Finally, mtDNA data do not support surviving lineages originating from multiple refugia; however the nuclear data do support the presence of at least two genetically distinct groups. It is possible that a reduction in gene flow detected in the microsatellite data arose after the LGM.Our results show limited phylogeographic structure in the Downy Woodpecker supporting a previous mtDNA RFLP study Individuals were sampled through: fieldwork (blood samples), toe-pads from museum birds, or tissue loans from different institutions. A total of 262 birds were used for mtDNA and 257 for microsatellite analysis see  with difTotal genomic DNA was extracted from muscle, blood, feather shaft and toe-pads from bird skins using a modified Chelex extraction 2, 15 pmol of each primer (L8929 - COII 5′- GGMCARTGCTCAGAAATCTGYGG -3′ and H9855– ATP6 5′-ACGTAGGCTTGGATTAKGCTACWGC -3′) 2H3O2 precipitation. Samples were left to incubate at 4°C for 20 min and centrifuged at 13,000 rpm for 20 minutes, followed by two sequential rinses to remove residual salts: first with 100 µl cold 70% ethanol, spun at 13,000 rpm for 5 min, and second 35 µl cold 70% ethanol centrifuged at 13,000 rpm for 5 min. Ethanol was removed after each step. Samples were left to evaporate in the dark at room temperature for 60 min, re-suspended in 10 µl of hi-di formamide, and sequenced using an ABI3130 sequencer.Partial tRNA-Lys, ATPase 6 and 8 genes were sequenced for 263 individuals (GenBank accession numbers: JX094511-JX094773). We were able to amplify the targeted regions for 262 individuals; however, some museum specimens could not be amplified  5′-GCAAAAGCCAGTTCCTGTGCATGG-3′) A1), and 60 s at 72°C; seven cycles of 60 s at 94°C, 30 s at TA2, 45 s at 72°C. Annealing temperatures  were 45–48°C for DMA2, DMD9, DMD118; 48–50°C for DMC111; 50–52°C for: DlU5, DMC115 and Ptri3. DNA amplification was carried out in 10 µl reactions under the following conditions: ∼200 ng DNA, 100 µM dNTP, 2.5 mM  or 1.5 mM  MgCl2, 5 pmol of each F and R primer (and M13 primer), 1X PCR buffer, and 0.5 U of Taq polymerase. Amplification products were loaded on a Li-COR 4300 analyzer. DNA fragments were sized using Li-COR size standards and internal controls (three samples run on every load). Both authors checked microsatellite genotypes for every locus independently. We also developed a check plate containing multiple samples from each gel to confirm the original scores and check for shifts in allele sizes during scoring.Only populations with ten or more individuals were genotyped . SamplesdH) diversity indices FST was calculated in Arlequin version 3.1 FST/(1-FST)) and geographic distances with those expected under a stepping-stone model of population structure Sequences were aligned manually using MEGA version 4 s is very powerful at detecting population expansions (increases in effective population size) by estimating departures from neutrality s values reject the null hypothesis of population stasis. Fs were calculated in DnaSP version 4.50.1 and significance was evaluated with 10,000 coalescent simulations. Similarly, Tajima’s D was used to test against selective neutrality and population equilibrium s and Tajima’s D are not, then background selection is more likely creating the observed pattern Phylogeographic and demographic history of the Downy Woodpecker were studied using two complementary approaches. First, genealogical relationships among haplotypes were visualized using the software TCS version 1.21 We used mismatch distributions to help visualize signatures of demographic expansion for all the samples combined, and to test the null hypothesis of population growth http://www.uni-graz.at/zoowww/mismatchcalc/mmc1.php developed by We estimated the putative time of population expansion most of the populations from the statistic tau (τ). τ is equal to 2ut, where u equals 2 µk, μ is the mutation rate and k is the length of the sequence and t the time of expansion Ho) and expected heterozygosity (He) were calculated for every population and each locus using the package GenAlEx version 6 MICRO-CHECKER FSTFST. For microsatellite analysis of population structure, FST is preferred over RST when the number of loci is less than 20 Genetic differentiation among sampled populations was evaluated using a priori population information. Ten replicates were performed at each value of K for the initial and final runs. Average ln P(X|K) was plotted against K to visualize the number of possible clusters as suggested by the authors. Although STRUCTURE is widely used, the biological meaning of the number of groups (K) can be problematic to infer when there are few available loci or the populations are not strongly differentiated http://taylor0.biology.ucla.edu/struct_harvest/). ΔK eliminates the possibility of overestimating the potential number of populations or groups due to the fluctuating nature of probability ln P(X|K) as K increases. One limitation with the ΔK method is it cannot detect when K = 1 is the true number of clusters. Finally, isolation by distance (IBD) analysis was carried out for microsatellites in order to test the relationship between genetic and geographic distances.The Bayesian clustering program STRUCTURE version 2.3.3 To gain a better understanding of the possible areas where the Downy Woodpecker survived during the LGM, a distribution model was constructed using the maximum entropy method implemented in Maxent version 3.3.3e http://data.gbif.org), and included the localities used in the genetic analyses. Duplicate records were removed as part of the default setting in Maxent to avoid pseudo-replication. To test if the modeled distribution of the Downy Woodpecker during the LGM corresponds to a realistic model, we used two basic techniques implemented by the software. The first is the omission plot. If the data using for training deviates from the predicted omission line then the model is statistically weak. The second if the area under the curve (AUC), which test if the model predicted with the training data , is similar to the testing data, and if both are not better than a random model. Values range from 0 to 1, and values under 0.5 are not better than a random model Sets of 16,271 localities were used to generate current and historical distribution maps. All the records were downloaded from the Global Biodiversity Information Facility (GBIF) data portal (


Petrogale penicillata;n = 279 from 31 sites), to assess historic evolutionary and biogeographic processes in southeastern Australia. Our results  confirmed three geographically discrete and genetically divergent lineages within brush-tailed rock-wallabies, whose divergence appears to date to the mid-Pleistocene. These three lineages had been hypothesized previously but data were limited. While the Northern and Central lineages were separated by a known biogeographic barrier , the boundary between the Central and Southern lineages was not. We propose that during particularly cool glacial cycles, the high peaks of the Great Dividing Range and the narrow adjacent coastal plain resulted in a more significant north–south barrier for mesic taxa in southeastern Australia than has been previously appreciated. Similarly, located phylogeographic breaks in codistributed species highlight the importance of these regions in shaping the distribution of biodiversity in southeastern Australia and suggest the existence of three major refuge areas during the Pleistocene. Substructuring within the northern lineage also suggests the occurrence of multiple local refugia during some glacial cycles. Within the three major lineages, most brush-tailed rock-wallaby populations were locally highly structured, indicating limited dispersal by both sexes. The three identified lineages represent evolutionarily significant units and should be managed to maximize the retention of genetic diversity within this threatened species.Mesic southeastern Australia represents the continent's ancestral biome and is highly biodiverse, yet its phylogeographic history remains poorly understood. Here, we examine mitochondrial DNA (mtDNA) control region and microsatellite diversity in the brush-tailed rock-wallaby ( The recent explosion in phylogeographic studies is rapidly increasing our understanding of how different species in various habitats responded to the climatic cycles of the Plio–Pleistocene  at a narrow hybrid zone  and microsatellite markers to: (1) determine phylogeographic patterns of population differentiation; (2) infer the biogeographic barriers associated with these patterns; (3) estimate the timing of these divergences; (4) use these findings to increase our understanding of the phylogeographic processes that have shaped the distribution of diversity in southeastern Australia; and (5) assess the implications of these spatial patterns for the management of the species.n = 279; Table P. assimilis: Pa55, Pa297, Pa385, Pa593, Pa595, Pa597; Spencer et al. Macropus eugenii: Me2, Me14, Me15, Me16, Me17; Taylor and Cooper α33-P labeling visualized by autoradiography  was amplified using conserved marsupial primers , and one sequence from each of P. lateralis (AF348694) and P. purpureicollis (AY057377) for use as outgroups.Mitochondrial DNA control region , assessed following Kass and Raftery , to asseST was calculated using the HKY+G distance model, described below, with significance evaluated with 10,100 permutations. Few haplotypes were shared among populations; therefore, standard FST values (based only on haplotype frequency) would have been unlikely to provide reliable estimates of genetic differentiation. Some of the 31 populations were excluded or pooled with neighboring sites for the AMOVA, as the ΦST distance estimates derived from “populations” with very small sample sizes of only one or two samples were likely to be poor estimates of the true values. Populations with sample sizes less than four were excluded  unless the small sample size was reflective of the census size . Populations with n < 4 but within 5 km or less of a neighboring site were pooled , resulting in 20 populations  was tested across the entire range and within two of the identified phylogeographic groups . Sampling for the Southern lineage was not adequate for an IBD analysis. We compared geographic distances (km) and corrected average pairwise population differences, calculated in ARLEQUIN, using Mantel tests with 10,000 permutations in GenAlEx v6.1  that were merged together to create a single population because they were within a 5 km distance of each other  for all loci were estimated using the program POPGENE 1.3.2 and allelic richness  was calculated for each sampled colony using FSTAT version 2.9  present using values of K between 1 and 14, with 10 replicates of each. The inferred number of populations within the sample was deduced using both maximum posterior probability (L(K) Pritchard et al. STRUCTURE HARVESTER 0.6.93  among the 254 P. penicillata individuals, resulting in 36 haplotypes , supporting the presence of a 4-way polytomy within the P. penicillata/P. herberti complex. Molecular clock dating suggests the major lineages within the P. penicillata/P. herberti complex initially diverged in the early Pleistocene ; range 0.00–1.00 (Table ST estimates were more moderate (0.64 ± 0.05). The AMOVA examining genetic variation at different hierarchical levels revealed that most of the total molecular variance was partitioned among the three identified phylogeographic regions , with 23% partitioned among colonies within regions . Only 5% of total molecular variance partitioned within colonies , as could be expected given the large number of sample sites represented by only a single haplotype.Most pairwise Φ00 Table . CompariP. penicillata CR haplotypes, a significant pattern of isolation by distance was found between genetic and geographical distances . This significant isolation by distance spatial patterning was also present within each of the examined mtDNA lineages . Mismatch distributions for all haplotypes and for haplotypes within the Southern and Northern lineages were consistent with the demographic expansion model , except the Pa595 and Pa385 combination in Drews Creek and Bowmans Road (P = 0.00). None of the loci deviated significantly from HWE in any of the 14 sampled colonies after table-wide sequential Bonferroni corrections. Loci were moderately polymorphic, with 6–18 alleles per locus ; however, two locations showed lower levels , with Northern lineage populations showing the lowest levels of differentiation (0.179 ± 0.020). A Mantel test detected a strong positive correlation between geographic distance and genetic differentiation among the 14 populations , with ∼54% of the variation in genetic differentiation explained by distance among the sampled colonies (r2 = 0.536).Most pairwise ns Table . The exc90 Table . CompariL(K)) or two (maximum ΔK) populations were present in the complete data set , the major break between the Central and Southern lineages did not coincide with any known barrier.Our mtDNA and microsatellite analysis found brush-tailed rock-wallaby populations to be highly structured both locally and regionally throughout southeastern Australia. Our data supported the three geographically discreet and divergent Petaurus breviceps) also found evidence for an eastern coastal Plio-Pleistocene refugium  and comparatively dry lowlands of the Hunter River Valley in central NSW create a major break in the Great Dividing Range from the coast ∼180 km west to the western slopes  and north of East Gippsland (Vic) late last century , nevertheless the periglacial zone of largely treeless steppe was much larger, extending in some glacial cycles down to 1000 m , which were the site of most glaciation that occurred in Australia during Pleistocene arid cycles  than those reported here for brush-tailed rock-wallabies (mid-Pliestocene), reinforcing the long-term impacts of these barriers on the fauna of southeastern Australia , intralineage divergence was modest (∼1.6%) and mostly lacked geographic structuring. While this pattern is consistent with expansion and recolonization from refugia, molecular evidence for a recent expansion is inconclusive (Table Potorous tridactylus)  , and high ΦST values were found among almost all populations. These data support the high levels of female philopatry previously reported in this species  in eastern Victoria  (sensu Moritz


Extinction and re-colonisation of local populations is common in ephemeral habitats such as temporary streams. In most cases, such population turnover leads to reduced genetic diversity within populations and increased genetic differentiation among populations due to stochastic founder events, genetic drift, and bottlenecks associated with re-colonisation. Here, we examined the spatio-temporal genetic structure of 8 alpine caddisfly populations inhabiting permanent and temporary streams from four valleys in two regions of the Swiss Alps in years before and after a major stream drying event, the European heat wave in summer 2003.M-ratio method, but in no populations when using a heterozygosity excess method, indicating differential sensitivity of bottleneck detection methods.We found that population turnover after 2003 led to a loss of allelic richness and gene diversity but not to significant changes in observed heterozygosity. Within all valleys, permanent and temporary streams in any given year were not differentiated, suggesting considerable gene flow and admixture between streams with differing hydroperiods. Large changes in allele frequencies after 2003 resulted in a substantial increase in genetic differentiation among valleys within one to two years (1-2 generations) driven primarily by drift and immigration. Signatures of genetic bottlenecks were detected in all 8 populations after 2003 using the A. uncatus populations changed markedly both temporally and spatially in response to the extreme climate event in 2003. Our results highlight the magnitude of temporal population genetic changes in response to extreme events. More specifically, our results show that extreme events can cause rapid genetic divergence in metapopulations. Further studies are needed to determine if recovery from this perturbation through gradual mixing of diverged populations by migration and gene flow leads to the pre-climate event state, or whether the observed changes represent a new genetic equilibrium.We conclude that genetic differentiation among  Fluctuations in population size are common ecological phenomena in all species that use patchy habitats. In metapopulation theory, subdivided groups of local populations are thought to persist in a balance between migration, extinction and re-colonisation - that is, local populations turnover at a specific rate that is determined by patch structure, metapopulation size and density of patches ,2. The fPopulation turnover, here defined as re-colonisation after catastrophic local extinction, often leads to genetic bottlenecks during colonisation (founder effects). Bottlenecks can cause a rapid loss of genetic variation, fixing mildly deleterious alleles and increasing the degree of inbreeding, thereby reducing the adaptive potential of the population -9. More e) and accelerates genetic drift with different alleles being lost from each population. Recurring local extinctions will then limit the time available for subsequent gene flow to equalize allele frequencies . We l method  in NeESTOR v.1.3 , and tes6 iterations and different random number seeds to confirm chain convergence. Migration rates and 95% confidence intervals were determined for each population pair.We estimated gene flow (m = proportion of migrants) between population pairs using BayesASS+ v.1.3 . We chosA. uncatus sampled populations  were found in the 24 e and migration rate estimation) were performed with and without Allo 17 for comparison (see below). Deviations from HWE were primarily due to the presence of null alleles and not inbreeding since FIS values were reduced to essentially zero in all 24 sampled populations when null alleles were accounted for (IIM FIS range: 0.012 - 0.063). It is important to note that although the frequency of null alleles was fairly high in some 2003 samples, several lines of evidence suggest that any potential bias stemming from these is not likely to alter the outcome of our study. For instance, simulation studies have shown that null alleles lead to an underestimation of allelic diversity and observed and expected heterozygosity, but that this bias is particularly low for expected heterozygosity . Altvergence , these mvergence . After aulations ,5,16,57. sources ,44. Inde sources . Both drA. uncatus led to high levels of admixture within valleys, but greater differentiation among valleys. Based on these results, we suggest that valleys represent 'semi-independent networks' sensu Hanski [A. uncatus populations' abilities to cope with future environmental change.In this study, we found that turnover of local populations of u Hanski  and are u Hanski . Models u Hanski . Under tWe conclude that the European heat wave in 2003 was associated with bottlenecks that led to reduced genetic diversity within all of our studied populations. Local population turnover led to large changes in allele frequencies among valleys over time, driven by genetic drift and immigration. Our results highlight the magnitude of temporal and spatial population genetic changes in response to extreme climate events, and demonstrate how such events can cause rapid genetic divergence in metapopulations.LNSS, CTR and JJ conceived and designed the study. LNSS, CTR and KBK conducted field sampling. LNSS and KBK acquired and analysed the data. All authors were involved with interpreting the data. LNSS drafted the manuscript. KBK, CTR and JJ provided critical revisions. All authors have approved the final version.ST values for the 8 A. uncatus populations sampled over multiple yearsPairwise F. FST values are shown below and significance is shown above the diagonal. Population codes as in Table Click here for fileA. uncatus populations sampled over multiple yearsDirectional gene flow estimates (m) for each pair of . Gene flow estimates represent the mean migration rate and 95% confidence intervals (in parentheses) for a pair of populations.Click here for file