Although Siberia was inhabited by modern humans at an early stage, there is still debate over whether it remained habitable during the extreme cold of the Last Glacial Maximum or whether it was subsequently repopulated by peoples with recent shared ancestry. Previous studies of the genetic history of Siberian populations were hampered by the extensive admixture that appears to have taken place among these populations, because commonly used methods assume a tree-like population history and at most single admixture events. Here we analyze geogenetic maps and use other approaches to distinguish the effects of shared ancestry from prehistoric migrations and contact, and develop a new method based on the covariance of ancestry components, to investigate the potentially complex admixture history. We furthermore adapt a previously devised method of admixture dating for use with multiple events of gene flow, and apply these methods to whole-genome genotype data from over 500 individuals belonging to 20 different Siberian ethnolinguistic groups. The results of these analyses indicate that there have been multiple layers of admixture detectable in most of the Siberian populations, with considerable differences in the admixture histories of individual populations. Furthermore, most of the populations of Siberia included here, even those settled far to the north, appear to have a southern origin, with the northward expansions of different populations possibly being driven partly by the advent of pastoralism, especially reindeer domestication. These newly developed methods to analyze multiple admixture events should aid in the investigation of similarly complex population histories elsewhere. S1, Supplementary Material online). This vast territory is inhabited by a relatively small number of indigenous peoples, with most populations numbering only in the hundreds or few thousands. These indigenous peoples speak a variety of languages belonging to the Turkic, Tungusic, Mongolic, Uralic, Yeniseic, Chukotko-Kamchatkan, and Aleut-Yupik-Inuit families as well as a few isolates. There is also variation in traditional subsistence patterns: The populations of southern Siberia are cattle and horse pastoralists; those of the Amur region focus mainly on fishing, hunting, and gathering; the peoples of central and northern Siberia frequently practice reindeer herding in addition to hunting; and along the coast of the Chukotka and Kamchatka peninsulas the Yupik, Chukchi, and Koryaks are sea mammal hunters and fishers of salmon  20-18 kya. Whereas some interpret the archaeological evidence as suggesting continued uninterrupted human occupation throughout the LGM , probablDespite Siberia's evident importance for understanding the peopling of North Asia and the New World, there are few genetic studies which focus specifically on the history of the Siberian populations, and these are mainly confined to mitochondrial DNA (mtDNA) and Y chromosome markers . Previousupplementary table S1, Supplementary Material online) to investigate the relationships among the indigenous populations of Siberia. The assembled data set includes new as well as previously published data . The test only becomes unreliable when the variance around the mean of all ancestry components in the sample is approximately the same, in which case any existing covariance between the components is obscured. In addition, if the final admixture proportion of one or more components in the population under study is very low (below 5%), the accuracy of the method decreases .The performance of this new approach was tested with simulated data. In general, the order of admixture events was identified correctly by the algorithm and with great precision for a wide variety of scenarios and even for admixture events involving four sources of ancestry and for small sample sizes .Once the sequence of admixture events is determined by the AHG approach, we use wavelet transform (WT) analysis  to estimsupplementary fig. S1, Supplementary Material online), fall closer to the Evens and Evenks than to their linguistic relatives. Further PCs and the results of the PCA on a subset of the data set are shown in supplementary figures S3 and S4, Supplementary Material online, respectively.To understand the general patterns of relatedness between the samples in the data set, we started with two widely used exploratory tools: principal components analysis (PCA) . Although the lowest cross-validation error is obtained for K = 7 , the error obtained for K = 6 is also very low, and the standard deviations of these two values overlap. At K = 7, the Yakuts are differentiated from the other Siberian populations , while at K = 6, Yakut ancestry is characterized in terms of components found in neighboring groups, and hence these results are more valuable for understanding the prehistory of the Yakuts. Therefore, all AHG analyses to reconstruct the order of admixture events  and admixture dates reported here are based on the results for K = 6. The six main components identified in this analysis can be roughly ascribed to Europe, East Asia, Western Siberia (present at highest frequency in the Khanty), Yupik-Inuit (present at highest frequency in the Naukan Yupik), Far East (Koryaks and Chukchi), and Central Siberia (found at highest frequency in the Nganasan).In order to investigate the patterns of potential gene flow, we estimated individual ancestry components using ADMIXTURE . ResultsStrikingly, this analysis paints a very complex picture, revealing that most of the Siberians trace their ancestry to multiple potential ancestral sources. These results suggest that admixture has been important in shaping the history of Siberia. However, some of the observed variations seem to be of a clinal nature and follow a geographical gradient. For example, the Central Siberian component (blue) is observed at highest frequency in the north, and decreases progressively southward. The opposite is true of the East Asian component (pink), while the Far Eastern component (red) seems to follow an east to west cline. While such clinal patterns could be indicative of admixture, they could also be explained by isolation-by-distance processes . Hence, A, Supplementary Material onlinesupplementary table S2 and text S1) confirm many, but not all, of the putative signals of admixture suggested by the PCA and ADMIXTURE analyses. TreeMix results were not easy to interpret and seem to contradict well-accepted aspects of human population history . The overall complexity and contradictory signals from the f3 tests and TreeMix could be explained by the putative complexity of the Siberian population history, which potentially includes recent shared ancestry, a multilayered history of admixture, and bottlenecks. These features of Siberian population dynamics violate the underlying assumptions of these methods, i.e., instantaneous admixture at single time points and tree-like population history   and Tree history .A, Supplementary Material onlinesupplementary fig. S8), there are distortions that are improved by allowing admixture , and overall the model which incorporates migration and admixture is preferred over a simple isolation-by-distance scenario , while the relatively low level of population-specific drift  shows that the Siberian populations are closely related and share large amounts of population history . SpaceMix also identifies sources for the inferred admixture events; however, it allows for only a single admixture event per population , the sources inferred by SpaceMix were not easily interpretable and are therefore not shown.To test if isolation-by-distance alone can account for all of the observed genetic variation in Siberia, we applied the recently developed SpaceMix software . This prscenario . In partpulation . As mostTo better understand the patterns of relatedness of the Siberian populations and to elucidate to what extent the observed structure can be explained by recent local migrations, we inferred and analyzed chunks of DNA that were inherited without recombination by each pair of individuals from their most recent common ancestor, that is, segments that are identical by descent (IBD) . We expesupplementary fig. S10, Supplementary Material online). This result is corroborated by the pattern of genome-wide linkage disequilibrium (LD), where the Koryaks and the Nganasan  exhibit much higher genome-wide LD than that observed for the Han Chinese or Europeans . This indicates that these populations living on the margins of the Siberian landmass likely experienced an extreme or several bottlenecks, possibly during successive migrations further north- and northeastwards.In terms of within- (and not between-) population IBD sharing, in general the individuals from the populations that now reside in the extreme North or the Far East  share more IBD blocks with individuals from the same population than do individuals from populations with a more central location, such as the Altaians and the Tuvans . The most striking exceptions are the Altaians, Tuvans, and Mongolic populations, who share almost no IBD segments with any other population in the data set, and the Evens, who share IBD segments even with geographically distant populations such as the Nganasan and Dolgans from the Taimyr or the Oroqen from North China. In keeping with the SpaceMix results, such patterns of sharing indicate that although isolation-by-distance and recent local migration could explain most of the genetic variation in Siberia, they cannot account for all of the observed diversity. Rather, other demographic processes such as large-scale population dispersals and rapid expansion and/or gene flow , the PC map inferred from the number of shared IBD blocks reveals that most of the genetic distances between the Siberian populations are smaller than expected based on their actual location on a geographic map . Adding rivers as facilitators of gene flow improves the fit of the observed genetic distances to geography, increasing the Rsq by 0.02 (P < 0.001). We then jackknifed over populations by sequentially removing each population and refitting the regression (P < 0.001) . The general conclusion from this analysis is that geography  indeed explains a large part of the genetic variance; however, it cannot explain all of the genetic relationships in Siberia. Instead, long-distance migration and admixture are likely to have further shaped the gene pool of Siberian populations.To further explore how genetic distances between populations are influenced by geography and to what extent the genetic variation in Siberia might be explained by isolation-by-distance, we used multiple regression of genetic distances on geographic distances . Historigression . The larsupplementary text S3 and figures S14–S17, Supplementary Material online.In summary, our exploratory analyses demonstrate that the prehistory of Siberian populations has been complex, and even though local effects of geographical proximity (isolation-by-distance) do explain much of the genetic diversity in Siberia, large-scale dispersals and variable degrees of admixture must have also played an important role in structuring the genetic variation of these peoples. These analyses also demonstrate that individual populations have had different historical trajectories, with those of the periphery being notably distinct from the others. In the following section, we analyze signals of admixture and discuss the genetic prehistory of the populations of South Siberia, while the analyses pertaining to the other populations are described in supplementary text S2, Supplementary Material online).The populations of southern Siberia are mainly pastoralists who speak Turkic (Altaians and Tuvans) or Mongolic languages (Buryats). Evidence for the use of domesticated animals  in this region goes back to the Neolithic . The resThe ancestry composition in Altaians, Tuvans, and Buryats is almost the same , even thB, Supplementary Material onlinesupplementary text S1). As both issues are relevant for South Siberia, we performed further tests to validate the different inferred admixture sequences we obtain for the South Siberian populations .Despite the overall similarity of the ADMIXTURE results, the AHG analysis (which is consistent across the best 30% of the ADMIXTURE runs) infers different admixture graphs  for the Altaians as compared to Tuvans and Buryats . Howeversupplementary table S3, Supplementary Material online) is shown in supplementary table S3, Supplementary Material online) in that the first admixture event in Altaians involved West Siberian and European ancestries, whereas for Tuvans and Buryats the first event involved the European and Central Siberian ancestries. The estimated dates of the admixture events, however, are roughly comparable, with the first event taking place ∼3,000–3,500 ya and the most recent event ∼2,000 ya. Since the average width of blocks of East Asian ancestry and the variance around the mean are larger in Buryats than in Altaians and Tuvans . The AHGs and the dates of the admixture events inferred here for the South Siberian populations are consistent with the archaeological record .The configuration most supported by the AHG calculation : South Siberian populations have consistently higher LD than Europeans, but lower short-range and higher long-range LD than Han Chinese. The short-range LD patterns suggest an intermediate-sized bottleneck in the past in South Siberian populations . We find that practically all Siberian populations show evidence of extensive and deeply complicated admixture. Admixture events are often reciprocal, with many populations showing signals of multiple independent pulses of gene flow and/or of gene flow occurring over a prolonged period of time. Disentangling the ancestries from many different (often related) sources that mixed at different time points in the past, and often more than once, is a very challenging problem. To unravel this complexity we developed a new method, the AHG, which infers the sequence of admixture events in a population with a complex admixture history. The approach was tested on simulated data, and we show that it is applicable to a wide variety of admixture scenarios . The information obtained via the AHG test can then be used to date multiple admixture events involving more than two sources of ancestry. To this end, we adapted and tested with simulated data a previously published admixture dating method  suggest that many of the dates we infer are below the data-inherent limit of resolution; therefore, the inferred dates are unlikely to seriously underestimate the true dates of admixture. These recent dates are also indirectly supported by recent studies, which have shown massive bidirectional migrations of peoples across the Eurasian steppe and which suggest major changes in the genetic structure of Eurasia, such as admixture and replacement of autochthonous populations, to have occurred in the Bronze Age  includes four different Turkic-speaking groups: Altaians and Tuvans (South Siberia), Yakuts (three groups from the Sakha Republic), and Dolgans (from the Taimyr peninsula and the northwest of the Sakha Republic); four Mongolic-speaking populations ; four Uralic populations: Samoyedic-speaking Nganasan (Taimyr peninsula), Nenets , and Selkup, as well as the Finno-Ugric Khanty from western Siberia; and Tungusic-speakers from five ethnolinguistic groups representing all the branches of the Tungusic family: Northern , southern (Hezhen), and Manchu (Xibo). The Even samples come from five and the Evenk samples from two different locations across Siberia. Furthermore, we included Yukaghirs and Kets , and populations of Chukotka and Kamchatka: Chukchi, Koryaks (who speak languages of the Chukotko-Kamchatkan family) and Naukan Yupik (who speak a language of the Aleut-Yupik-Inuit family). For comparative purposes we augmented the data set with Aleuts as well as Inuit populations of Greenland, and added European , Han Chinese, and Japanese populations from the HGDP .The data set  were excluded from the IBD, regression, and dating analyses because no geographical coordinates were available for these samples, and because we had other samples from the same populations  whose PCA and ADMIXTURE results overlapped with those of the Reich et al. samples  One individual from the Selkup population, as this sample is an outlier with respect to others in terms of its admixture profile: It is the sample with the highest proportion of Central Siberian and the lowest proportion of European ancestry ; 2) one Yamal Nenets sample, as for this sample we estimated 28% European admixture (while the population average is 4%); 3) two Xibo samples with no Far Eastern ancestry  and higher than the population average of European ancestry (19% and 9% vs. population average of 2%); 4) two Taimyr Dolgans with no European ancestry, while this ancestry is present on average at 12% in the remaining Dolgans; 5) in the HGDP sample of Yakuts, European admixture ranges from 4% to 30%, while in the Verkhoyansk Yakuts it ranges from 4% to 7%; therefore to exclude recent Russian admixture, we limited the analysis in the HGDP Yakuts to individuals with European admixture not exceeding 8% .Furthermore, PCAdmix runs failed to resolve ancestry for some chromosomes of Altaians and Tuvans (for these populations ancestry was inferred using four source populations). These chromosomes were removed prior to the admixture dating analysis. In total, 66 (out of 528) and 78 (out of 704) haploid chromosomes  were removed from the Altaians and Tuvans, respectively. In addition, for the same reason in the Tuvans chromosome 20 was completely removed prior to dating.PCA was performed using the StepPCO software  on 353,3K = 3 through K = 10, and performed ten independent runs for each value of K. We confirmed consistency between runs and used the cross-validation procedure implemented in ADMIXTURE to find the best value of K . We ran an additional 90 runs for K = 6 , and used the top 30% of all runs to confirm consistency of the inferred AHGs. We also calculated the standard errors on all admixture estimates for K = 6 via bootstrapping as implemented in ADMIXTURE . Geodesic distances were calculated using the distonearth R function  Populations do not choose their own locations, nor can they draw admixture ; 2) populations are not allowed to choose their own locations, but they do draw admixture , 3) populations choose their own locations, but no admixture , and 4) populations choose their own locations and they draw admixture .SpaceMix analysis was performed with default settings , namely http://support.illumina.com/array/array_kits/human660w-quad_dna_analysis_kit/downloads.ilmn, last accessed March 31, 2016). In particular, we binned genotype data from each population into 50 evenly spaced recombination distance categories (0.005–0.25 cM). For each population and for every pair of SNPs in each distance category, we calculated the squared correlation in allele frequencies (Rsq) by selecting from each population 11 individuals showing the least amount of admixture (as determined by ADMIXTURE). For this analysis, individuals from different sampling locations of the same population were grouped. To account for missing data, each pairwise measurement was adjusted by sample size.Genome-wide LD calculation was performed using custom scripts, as described D, Supplementary Material onlinesupplementary text S1, for validation). To aid interpretation, we also analyzed the length distribution of blocks of different ancestry, as inferred by PCAdmix.To analyze signals of admixture in the Siberian populations involving more than two ancestral populations, we adopted the following workflow: The data were phased with the BEAGLE software , then thK = 6, and populations that had been assigned their own ancestry component at this value of K were chosen as proxies for the true ancestral populations. Specifically, for the European ancestry component we used Italians as the parental group, for the West Siberian component we used the Khanty, for the Central Siberian component we used the Nganasan, for the East Asian component we used the Han Chinese, for the Far Eastern component we used the Koryaks, and for the Yupik-Inuit component we used the Greenland Inuit. We assigned an equal number of individuals per parental group and selected only those individuals with not more than 1% admixture. Because Greenland Inuit, whom we used as a proxy parental population for the admixture signal observed in Chukchi and Naukan Yupik, are themselves heavily admixed, we made an exception for this group and accepted up to 10% admixture in this parental population . Because WT analysis (see below) requires 2n windows per chromosome (n = 10), 512 windows across chromosomes 9–18 and 20 (n = 9), and 256 windows across chromosomes 19, 21, and 22 (n = 8).Our choice of parental populations for the PCAdmix analysis was guided by the results of the ADMIXTURE analysis for romosome , we usedD and fig. S20, Supplementary Material onlinesupplementary text S1) and additional gene flow . We also assessed the time-depth resolution of the method , and its robustness to misspecification of parental groups , as well as addressed concerns related to potential errors in ancestry estimation by PCAdmix and phasing errors . These confirm that the method results in the accurate estimation of dates of multiple admixture events.Once the sequence of admixture events was determined by the AHG approach (see Novel Approaches), we first considered the most recent admixture episode. PCAdmix estimates ancestry along individual chromosomes and assigns chunks of the genome to any of the three or more ancestral populations. In estimating the date for the most recent episode, we treated the population receiving the gene flow as already admixed, and its ancestry composed of ancestry blocks originating from previous admixture events, that is, we treated all blocks of ancestry assigned by PCAdmix to two (or more) older admixture contributors (as determined by AHG) as the same, and considered this part of the genome as coming from population 1. The part of the genome assigned by PCAdmix to the most recent admixture contributor (as determined by the AHG) was considered as originating from population 2. We then proceeded to use WT analysis  to estimTo comply with the informed consent under which the samples were obtained, we make the data available upon request by asking the person requesting the data to agree in writing to the following restrictions: 1) The data will only be used for studies of population history, 2) the data will not be used for medical or disease-related studies, or for studies of natural selection, 3) the data will not be distributed to anyone else, and 4) no attempt will be made to identify any of the sample donors.Supplementary tables S1–S3, figures S1–S24, and text S1–S3 are available at Molecular Biology and Evolution online .


Thremma gallicum, by sequencing a 658-bp fragment of the mitochondrial CO1 gene, and 12,514 nuclear RAD loci. T. gallicum has a highly disjunct distribution in southern and central Europe, with known populations in the Cantabrian Mountains, Pyrenees, Massif Central, and Black Forest. Both datasets represented rangewide sampling of T. gallicum. For the CO1 dataset, this included 352 specimens from 26 populations, and for the RAD dataset, 17 specimens from eight populations. We tested 20 competing phylogeographic scenarios using approximate Bayesian computation (ABC) and estimated genetic diversity patterns. Support for phylogeographic scenarios and diversity estimates differed between datasets with the RAD data favouring a southern origin of extant populations and indicating the Cantabrian Mountains and Massif Central populations to represent highly diverse populations as compared with the Pyrenees and Black Forest populations. The CO1 data supported a vicariance scenario (north–south) and yielded inconsistent diversity estimates. Permutation tests suggest that a few hundred polymorphic RAD SNPs are necessary for reliable parameter estimates. Our results highlight the potential of RAD and ABC-based hypothesis testing to complement phylogeographic studies on non-model species.Repeated Quaternary glaciations have significantly shaped the present distribution and diversity of several European species in aquatic and terrestrial habitats. To study the phylogeography of freshwater invertebrates, patterns of intraspecific variation have been examined primarily using mitochondrial DNA markers that may yield results unrepresentative of the true species history. Here, population genetic parameters were inferred for a montane aquatic caddisfly,  In particular, we addressed the question of whether or not RAD data from many loci across the genome for few individuals can significantly improve the resolution of phylogeographic studies based on single locus CO1 data from many individuals. Furthermore, we estimated the number of RAD loci necessary to obtain robust estimates of population genetic parameters.Here, we analyzed the population structure and phylogeographic history of a European montane caddisfly species, ange Fig.. The speT. gallicum specimens , 0.2 mmol/L dNTPs, 0.5 μmol/L of each primer, 0.025 U/μL HotMaster Taq (5Prime), 1–3 μL DNA (5–20 ng), and a sufficient volume of double-distilled H2O to yield a final volume of 25 μL. Bidirectional sequencing was performed by GATC-Biotech  and Macrogen .Genomic DNA (gDNA) was extracted from 352 ens Table using thCO1 parsimony network was computed using TCS v. 1.2.1 . Next, 200 ng of purified gDNA was digested with 15 U (1.5 μL) of the frequent cutter Csp6I (recognition site G↑TAC) and 15 U (1.5 μL) of the rare cutter NsiI  in 3 μL FastDigest buffer. The volume was filled to 30 μL with H2O. Digestion success was checked on 1.5% TBE agarose gel using 3 μL of the digested sample. The remaining 27 μL was purified with the Qiagen Reaction Cleanup Kit according to the manufacturer's protocol. After this step, the universal P2 adapters (5′-AGATCGGAAGAGCGGTTCAGCAGGAATGCCGAG-3′)  and customized P1 adapters (5′-ACACTCTTTCCCTACACGACGCTCTTCCGATCTxxxxxxTGCA-3′) , which contained individual 6-bp barcode sequences (Table S2), were ligated to the fragments. Ligation was performed in 1 × T4 ligase buffer and 0.5 μL of high-fidelity T4 ligase   at 16°C for 2 h. The complete ligation reaction was run on a 1.5% TAE agarose gel, stained with 1% SYBR Green dye  for 10 min, and visualized on a blue light illuminator. Gel regions in the 250 to 500-bp range were excised and purified using the Qiagen Gel Purification Kit. PCR was run with 25 μL of sample, 10 μL Q5 buffer (New England Biolabs), 5 μL P5 primer , and 5 μL P2_rev primer , 0.5 μL Q5 Taq 2U/uL (New England Biolabs), and 5 μL dNTPs (2 mmol/L). PCR started with an initial denaturation step at 98°C for 30 sec followed by 16 cycles of denaturation at 98°C for 10 sec, annealing at 65°C for 30 sec, and elongation at 72°C for 30 sec, followed by a final elongation step of 72°C for 5 min. After PCR, the samples were purified with the Qiagen Reaction Cleanup Kit and eluted in 30 μL H2O. Seventeen individual sample concentrations were quantified and approximately 25 ng of DNA per sample was pooled for sequencing by GenXPro  on an Illumina HiSeq 2000.RAD libraries were prepared for 2–10 individuals per geographic region . Information on the modules of the Stacks pipeline can be found in Catchen et al. (https://github.com/evoeco/radtools), we created an output file that was loaded into Geneious for further processing and export into other formats. The Stacks parameters chosen were as follows: minimum stack depth (-m), 3; maximum intra-individual distance (-M), 2; maximum number of mismatches for the alignment of secondary reads (-N), 2; and number of mismatches when building the catalog (-n), 2. All loci with more than two alleles were removed, as they may represent paralogous genes. For the final dataset, only loci sequenced with ≥5× coverage and ≤2 SNPs that were present in at least nine analyzed specimens  were considered, resulting in 12,514 loci containing 15,305 SNPs. For phylogeographic hypothesis testing with the software DIYABC 2.03 . From the resulting datasets, we calculated the average heterozygosity and standard deviation for the four geographically defined populations  and two representatives of each population with the highest and lowest heterozygosity . Graphs were visualized using the SVGGraph library 2.13  to a reference phylogeny computed for the full  dataset. Permutations were designed in a similar manner to that described above with the exception that the range of alignment sizes was in 100-loci increments and alignment length was extended to 5000 loci. To facilitate comparison of tree distances, the complexity of the reference tree was reduced to an unrooted, partially resolved tree, consisting of clades reflecting individual populations and the main subdivision of the two southern and the two northern populations. Specimens from the Massif Central were not united in a single clade, as placement of this grouping on the dichotomous trees was not consistent. The constrained topology of the reference tree was thus designed as follows: (((Black Forest), Massif Central 1, Massif Central 2), ). For each alignment, a neighbor-joining tree based on Kimura-2-parameter distances was reconstructed and the symmetric-difference metric  ranged from 1 to 400,000 for the RAD dataset and from 0.25 to 100,000 for the mitochondrial dataset . Priors for the generation times between divergence events were set to 1000 to 10 million. Simulations were run for 5 million generations after which summary statistics were generated for: (1) mean of pairwise differences, (2) variance of pairwise differences, (3) Tajima's D, (4) number of segregating sites, (5) mean of pairwise differences (w), (6) mean of pairwise differences (b), and (7) FST. For the RAD dataset, priors for the mutation rate were set to a mean of 10−7 . The number of invariant sites was set to 98% as we allowed for up to two SNPs per 100-bp stack. For the mitochondrial dataset, the mutation rate was left on default setting  and the number of invariant sites was set to 95%. All other settings were left as suggested in the DIYABC documentation for RAD and mitochondrial datasets, respectively. Posterior probabilities of scenarios were calculated by direct estimation and logistic regression considering between 500 and 50,000 datasets that were closest to the observed values.In order to test specific hypotheses of demographic history for this species, we utilized an ABC approach in the software DIYABC v. 2.0.3  and lowest in the Massif Central (π = 0.0005). The Pyrenees and Black Forest populations had intermediate values .Haplotype diversity was higher in the Pyrenees (H = 0.68), Cantabrian Mountains (H = 0.63), and Black Forest (H = 0.67) than in the Massif Central (H = 0.29). Nucleotide diversity was highest in the Cantabrian Mountains (Average heterozygosity was clearly lower in the Black Forest (2.6% ± 0.60) and Pyrenees (3.5 ± 1.02%) than in the Cantabrian Mountain (12.6 ± 1.84%) and Massif Central (11.4 ± 0.11%) populations. The relative patterns of heterozygosity remained similar across the parameter ranges tested. However, for the full dataset, that is, including loci found in single individuals, heterozygosity of the Cantabrian Mountains population was even higher than estimates from the current dataset, where at least nine individuals had to be present for a locus to be included. In order to assess reliability and stability of these estimates, we plotted average heterozygosity (±SD) for each population based upon permuted datasets of different sizes (10–1000 loci)  and lowest  heterozygosity, no overlap in standard deviation was found when sampling more than 290 loci . The split between the Massif Central and Black Forest populations dated to 0.2101 mya (95% HPD: 0.0724–0.3802 mya). Populations from the Cantabrian Mountains and the Pyrenees were not reciprocally monophyletic and thus divergence dating was performed for the two main splits that occurred between populations on the Iberian Peninsula  host the oldest population ,) (logistic regression: 0.9902). The second and third most supported scenarios, 9 (logistic regression: 0.002) and 12 (logistic regression: 0.0063)  and the RAD dataset  support a history of long-term isolation of geographically distinct populations from the four mountain ranges. In the CO1 dataset, the divergence between populations from the Iberian Peninsula (Pyrenees and Cantabrian Mountains) was rather shallow, implying a relatively recent split between them. The paraphyletic Cantabrian Mountain specimens colonization events of high-altitude habitats after differe nt glaciations. Molecular clock estimates are, however, error prone  for reconstruction of demographic history is a concern. Thus, we also addressed similar hypotheses with our RAD dataset, which supports two populations with high genetic diversity  and two with low (Pyrenees and Black Forest). Both the Black Forest and Pyrenees populations may be genetically less diverse due to recolonization from lower altitudes. Analogously, an upward recolonization in the Pyrenees was observed for the high-altitude caddisfly CO1 datasets support two competing scenarios  revealed contradicting results for the CO1 dataset. While both nucleotide and haplotype diversity are lowest in the Massif Central, nucleotide diversity is highest in the Cantabrian Mountains, but haplotype diversity is highest in the Pyrenees. These results, however, could simply reflect the low number of analyzed specimens per stream and sampling sites for some regions. Only seven specimens from one sampling site could be analyzed for the Massif Central population, possibly explaining the low values for H and π found. But, sampling numbers aside, additional estimates of these important population genetic measures from other loci, especially those in the nuclear genome can greatly increase confidence in downstream results. RAD sequencing overcomes this challenge by sampling thousands of loci per individual and computing genetic diversity estimates averaged across all loci (observed heterozygosity), which is a far more reliable indicator of genetic diversity than mitochondrial haplotype and nucleotide diversity (Bazin et al. T. gallicum, the distance between the simulated and the optimal tree only converged when more than 3780 loci were included (Fig.n = 2, reliable differentiation estimates can be obtained when thousands of markers are genotyped (Willing et al. A recurring question in population genetics is the minimum number of individuals and loci required to address a particular question of interest (e.g., Nei e et al.  assessedCO1 and RAD data in non-model species (Emerson et al. CO1 dataset, the RAD data allowed for clearer identification of divergence and differentiation patterns in T. gallicum by utilizing thousands of nuclear markers and thus overcoming the inherent shortcomings of CO1 data in cases of recurring gene flow following historic lineage separation. This study highlights the potential of RAD to reliably analyze genome-wide intraspecific genetic variation and demographic history even in non-model taxa. To the latter point, this combination of thousands of markers paired with ABC simulations makes it possible to test competing phylogeographic scenarios without the need to obtain an excessively large number of specimens or rely on one or a small number of loci each with their own independent evolutionary histories. For these reasons, RAD sequencing is a particularly interesting and promising tool for ecological and evolutionary studies for any taxonomic group, but especially for rare or endangered species with small population sizes.Very few studies have used both


An. gambiae s.s.Indoor-based control strategies against Anopheles vectors remain indispensable in the current effort to reduce malaria transmission. However recent reports indicate that vectors are increasingly biting outdoors in areas where coverage of insecticide-treated nets is high - potentially a sign of behavioural adaptation ,2. UsingAn. gambiae s.s. were collected by human landing catches from indoor and outdoor locations approximately 60-200 m apart in The Gambia. Genomic analysis was performed on single-nucleotide polymorphisms (SNPs) ascertained from whole-genome sequencing.We examined the diversity, divergence and deviation from neutrality of different genomic regions to look for evidence of genetic differentiation between the two populations. We also performed a genome-wide association study (GWAS) to test for any associations of SNPs with the outdoor-biting phenotype.st = 0.00004). There was no difference in the pattern of nucleotide diversity and Tajima’s D statistics between the two populations which exhibited variations within and between chromosomes. Linkage disequilibrium (LD) was low across all chromosomes, except for elevated peaks within inversions and centro-/telomeric regions. With no known loci implicated in biting-behaviour, we examined all loci and defined a cut-off at P < 1 x 10–5 for significant associations yielding a total of 53 SNPs of interest. We found that most of these SNPs were in non-coding regions.Estimates of population structure show weak differentiation between the two populations (FThis is the first study investigating the genetic differentiation between indoor and outdoor-biting populations. We detected very little genetic differences between the two populations except for a few SNPs that were identified in the GWAS. These SNPs are currently under investigation in a comparison panel comprising of Ugandan samples.


The demographic history of human populations in North Africa has been characterized by complex processes of admixture and isolation that have modeled its current gene pool. Diverse genetic ancestral components with different origins  and genetic heterogeneity in the region have been described. In this complex genetic landscape, Algeria, the largest country in Africa, has been poorly covered, with most of the studies using a single Algerian sample. In order to evaluate the genetic heterogeneity of Algeria, Y-chromosome, mtDNA and autosomal genome-wide makers have been analyzed in several Berber- and Arab-speaking groups. Our results show that the genetic heterogeneity found in Algeria is not correlated with geography or linguistics, challenging the idea of Berber groups being genetically isolated and Arab groups open to gene flow. In addition, we have found that external sources of gene flow into North Africa have been carried more often by females than males, while the North African autochthonous component is more frequent in paternally transmitted genome regions. Our results highlight the different demographic history revealed by different markers and urge to be cautious when deriving general conclusions from partial genomic information or from single samples as representatives of the total population of a region. The human history of North Africa has been shown to be a complex demographic process characterized by multiple migrations, admixtures and founder effects. It has been suggested that the first occupation of the area by modern humans, attested by the Aterian culture, might be dated back to ~160,000 years ago . DespiteThe genetic characterization of North African populations has been carried out with the analysis of uniparental  and autosomal markers ,6–17. Be2; of which 80% is occupied by the Algerian Sahara. On this vast territory, which extends from the Mediterranean environment in the north to the Saharan desert in the South, various human groups use the same language, the Berber, a generic name for any spoken Amazigh dialects. In fact, there are various Berber dialects spoken by different Berber groups in Algeria: Chaoui, Kabyle, M'zab, Zenete, Chleuh, and Touareg. Despite the human diversity described in Algeria and its geographical extent in the area, the knowledge about the human genetic diversity in the country is relatively scarce. A few studies have focused on a single Algerian sample in the area [Within the North African context, Algeria represents a key point to understand the human population history of the region. Located in the fertile coastal plain of North Africa, Algeria shares borders with Morocco, Western Sahara, Mauritania, Mali, Niger, Libya, and Tunisia. Taken together, Algeria, Morocco, and Tunisia form what is known as the Arab Maghreb. Algeria is now Africa's largest country, covering an area of nearly 2.4 million kmthe area ,8–10,18 the area ; and allIn order to overcome these limitations and to explore the genetic heterogeneity within Algeria, the present study describes the distribution of the uniparental lineages (mtDNA and Y-chromosome) and whole genome autosomal SNPs in several Algerian samples, including Arab- and Berber-speaking groups.Written informed consent was obtained from the participants and analyses were performed anonymously. The present project obtained the ethics approval from the local Institutional Review Board, Comitè Ètic d’Investigació Clínica–Institut Municipal d’Assistència Sanitària (CEIC-IMAS) in Spain (2013/5429/I), as well as the approval from the local committee CRASC  in Oran, Algeria.Four populations from Algeria were genotyped in this study  . The samBlood samples were anonymously collected from unrelated healthy adult volunteers and an informed consent was systematically signed by the individuals having understood all the necessary information concerning the project and agreed to be included in this study. The socio-demographic data, including genealogical and spoken dialect information, were collected from a questionnaire beforehand established. DNA was extracted using the standard salting-out method  and thenlSTR® Yfiler® PCR Amplification Kit (Applied Biosystems) according to manufacturer’s instructions. DNA fragments were separated and detected in an ABI Prism 3130 Genetic Analyzer (Applied Biosystems). Two additional Y-STRs  were typed using a PCR multiplex including 6 Y-SNPs  [http://www.isog/tree).Samples were genotyped for seventeen Y-chromosome STRs using the Ampnd M139)  (S1 Tablnd M139) . The Reand M139)  and analnd M139) , and refwww.phylotree.org  Y-chromosome and mtDNA haplogroup and haplotype frequencies and diversities were calculated using Arlequin software version 3.5 [ST and FST distances between populations and their significance assessed by a nonparametric permutation test. Since Y-chromosome and mtDNA haplogroup resolution was not uniform across studies, the haplogroups were reduced to the most informative derived shared markers. Principal component analyses (PCA) were performed using IBM SPSS Statistic 19 version . Furthermore, the mtDNA sequence comparison was carried out on HVSI positions from 16024 to 16383, and 10 shared Y- chromosomal STRs  were considered to study the haplotype diversity and to perform the non-metric multidimensional scaling (MDS) by IBM SPSS statistics 19  using RST and FST distances between populations. MDS co-ordinates were plotted with R 2.15.3.The hypervariable segment I (HVSI) of mitochondrial DNA (mtDNA) was sequenced. The mtDNA control region was PCR amplified using primers pairs H408/L15996 . Successsion 3.5 , as wellIn order to examine the Algerian population structure, genetic variation was apportioned within and among populations by grouping them according to their North-South geographic regions, and Arab/Berber origins using AMOVA by means of Arlequin software version 3.5 . AMOVA ahttp://figshare.com/articles/Zenata_genotypes/1534498). The two other populations include the Mozabite Berbers  and an Arab sample from Algerian general population collected in Algiers [Autosomal data from three Algerian samples was included in the present analysis. The Zenata Berber sample from Timimoun was newly genotyped with Affymetrix 6.0 array  plots and ADMIXTURE analysis . PCA wasThe correlation between autosomal and X-chromosome ancestral frequencies found with ADMIXTURE was calculated with R 2.15.3.The paternal lineage composition in Algerian samples is similar to other NW African populations, being E1b1b1b-M81 the most frequent haplogroup, followed by E1b1b1a-M78 and J subgroups . AlthougST) were calculated among samples  and multidimensional scaling (MDS) analyses were performed. The PCA plot performed on the Y-chromosome haplogroup frequencies  shows th samples  and sign samples . Both AlThe genetic heterogeneity in paternal lineages in Algeria shown in the previous analyses was demonstrated in an AMOVA when considering all samples together . GeograpAn admixture of Eurasian, North African, and sub-Saharan African mtDNA lineages is found in all Algerian samples  as shownPCA carried on mtDNA haplogroup frequencies  showed tST distances between the studied populations were calculated (ST = 0.055) and the Northern populations (Algiers and Oran1) , whereas, the geographically neighbors Reguibate and Zenata cluster together (FST = 0.018). The Mantel test shows no correlation between the mtDNA and Y-chromosome Fst vales .Pairwise based Flculated  and the lculated . The higThe AMOVA analysis based on mtDNA haplogroups and haplotypes data shows no differences between the Southern and Northern populations and between the Arabs and Berbers, even excluding the Reguibate sample from the Arab group . SignifiA genome-wide SNP array typed in a subset of individuals and samples was analyzed to complement our knowledge of the genetic structure in the Algerian population. The first two axes of the PCA show a differentiation of sub-Saharan (i.e. Yoruba), Middle Eastern , European (i.e. Basque), and Algerian individuals . All indIn order to establish putative ancestral components in the genotyped individuals, an ADMIXTURE analysis was performed for the same samples . At K = In order to test whether the heterogeneity detected in the Algerian population might be attributed to differential sexual admixture, an analysis of the autosomal versus the X-chromosome diversity was also performed. The results of the PCA and ADMIXTURE analyses carried out exclusively for X-chromosome markers  are simiOur results of uniparental and autosomal markers in Algeria agree with the presence of ancestral components previously described in North Africa, attesting the genome complexity of Algerians . ConcernThe genetic structure observed in the Algerian analyzed groups is neither fully correlated with ethnic affiliation (Berber-Arab) nor with geography (coast vs. inland). It is noteworthy, however, that when we removed the Reguibate population from the Arab group, a significant differentiation was observed between the paternal gene pool profiles of Arabs and Berbers. This absence of differentiation between Arabs and Berbers is in agreement with what has been already observed in several North African populations by the analysis of different genetic markers, such as autosomal classical markers  ,12,14; aThe genetic heterogeneity among Algerian populations highlights the complex relations between biological, social, cultural and geographical contexts. The distribution and frequencies of the North African, Eurasian and sub-Saharan components both in uniparental and autosomal markers is variable in each group, not only when comparing Berber and non-Berber, but also within linguistic groups. For example, some autochthonous North African haplogroups were not present in certain samples, such as the mtDNA U6 haplogroup that was absent in Algiers and present in only one individual in the analyzed Zenata group. In the same way, mtDNA haplogroup M1 is absent in the Zenata population. The absence of the maternal North African component in these groups, especially the Zenata Berbers, might be explained by extensive genetic drift and the remarkable high frequency of sub-Saharan lineages (~23% for the Y-chromosome E-M2 haplogroup and ~ 65% of mtDNA L lineages) in the Zenata sample. Our autosomal analysis also shows the close position of the Zenata group to the sub-Saharan populations, and the high variance in this sub-Saharan ancestry suggest that this group has experienced recent gene flow.The complex demography of the Algerian samples analyzed is also reflected in the sexual bias of gene flow and admixture. MtDNA sub-Saharan haplogroups are more frequent than the Y-chromosome lineages, suggesting higher sub-Saharan female gene flow in our Algerian samples. This is in agreement with autosomal and X- chromosome ancestral components, where there is also evidence of sexual bias in the sub-Saharan component. On the other hand, Y-chromosome results show higher frequency of North African than mtDNA haplogroups. This is in agreement with the results for autosomal and X-chromosome markers, which associate North African component to males, while the Middle Eastern and European ancestries seem to be derived from a female gene flow into Algeria. This difference can be explained by the historic and prehistoric role and status of women in the Algerian society: sometimes considered as an object of warlike conflict or as alliances between occupant's and occupied various clans, as denounced by some ethnologists and historians ,50.It has been shown that some Berber populations  are heterogeneous and outliers within the genetic North African landscape, and they seem to have experienced long periods of genetic isolation without subsequent admixture with other groups . This prIt has been observed that cultural isolation in rural communities promotes, by the effect of genetic drift, stronger loss of diversity and larger genetic differentiation levels than those observed in urban areas . In addiThe overall ancestral proportion of admixture components within populations considering mitochondrial and Y-chromosome haplogroups and autosomal markers reflects a similar history of gene flow at the population level. However, the comparison of the different genetic markers at individual level reflects differences as a result of the difference inheritance models of each marker. This discrepancy can be seen in present example of the Zenata sample where these markers were tested in each individual . It is cS1 Fig(TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.S7 Table(XLSX)Click here for additional data file.S8 Table(XLSX)Click here for additional data file.


Canis aureus) is one of the most common and widely distributed carnivores in India but phylogeographic studies on the species have been limited across its range. Recent studies have observed absence of mitochondrial (mt) DNA diversity in European populations while some North African populations of golden jackal were found to carry gray wolf (Canis lupus lupaster) mtDNA lineages. In the present study, we sequenced 440 basepairs (bp) of control region (CR) and 412 bp of cytochrome b (cyt b) gene of mtDNA from 62 golden jackals sampled from India (n = 55), Israel (n = 2) and Bulgaria (n = 5), to obtain a total of eighteen haplotypes, comprising sixteen from India and one each from Israel and Bulgaria. Except for three previously described haplotypes represented by one cyt b and one CR haplotype both from India, and one CR haplotype from Bulgaria, all haplotypes identified in this study are new. Genetic diversity was high in golden jackals compared to that reported for other canids in India. Unlike the paraphyletic status of African conspecifics with the gray wolf, the Indian (and other Eurasian) golden jackal clustered in a distinct but shallow monophyletic clade, displaying no evidence of admixture with sympatric and related gray wolf and domestic dog clades in the region. Phylogeographic analyses indicated no clear pattern of genetic structuring of the golden jackal haplotypes and the median joining network revealed a star-shaped polytomy indicative of recent expansion of the species from India. Indian haplotypes were observed to be interior and thus ancestral compared to haplotypes from Europe and Israel, which were peripheral and hence more derived. Molecular tests for demographic expansion confirmed a recent event of expansion of golden jackals in the Indian subcontinent, which can be traced back ~ 37,000 years ago during the late Pleistocene. Our results suggest that golden jackals have had a potentially longer evolutionary history in India than in other parts of the world, although further sampling from Africa, the Middle East and south-east Asia is needed to test this hypothesis.The golden jackal ( Canis aureus, Linneaus 1758) is a medium-sized canid with a wide range of distribution, occurring in northern and eastern Africa, southeastern Europe, the Middle East and extending eastwards into central, southern and southeast Asia as far south as Sri Lanka and Thailand [The golden jackal (Thailand ), which Thailand , 4.Canis lupus), the golden jackal is fairly common throughout its range. Due to their tolerance of dry habitats and omnivorous diet, they can live in a wide variety of habitats. Golden jackals are opportunistic and often venture into human habitations at night to feed at garbage dumps, or scavenge on livestock carcasses. In India, the golden jackal is found in most protected areas, semi-urban and rural landscapes of the country, except in the high elevation regions of the Himalaya. Certain pastoral areas in western and northern India, which have abundant livestock also support high jackal densities. This is mainly because many cattle carcasses are available for jackals and other carnivores to scavenge upon, as prevailing socio-religious beliefs among the people in this region taboo the consumption of beef [Unlike the closely related and much rarer sympatric species, the gray wolf ( of beef . Based o of beef . On the  of beef .Canis lupus lupaster). Although interpreted as a taxonomic misidentification, this entity could have resulted from the introgression of gray wolf mtDNA into golden jackal populations, as observed from the ‘intermediate’ or hybrid jackal-wolf morphotypes observed at a Senegalese study site by Gaubert et al. [Despite their wide range of distribution, limited population genetic studies on the golden jackal have been carried out , 8, 9. Pt et al. . Howevert et al. . Limitedt et al.  and posst et al. . HithertIn this paper, we present to our knowledge a first assessment on the genetic variability of the golden jackal populations in India. The Indian golden jackal populations are important for investigating phylogeography in the species as they encompass a major central portion of their global distribution. This study used mtDNA sequences to explore the following themes with regard to golden jackal systematics and phylogeography in India—(i) genetic diversity among golden jackal populations in India, (ii) signatures of population change, and (iii) relationships to wolves and other wolf-like canids in the region and across their range.Canis aureus is listed in schedule III of this Act, and as species of least concern by the IUCN red list. This research project was conceived and radio collaring of jackals was done prior to the formation of an animal ethics committee at the Wildlife Institute of India. The research was approved by the Training and Academic Council (TRAC) of the Wildlife Institute of India which is composed of experienced wildlife biologists, academicians, wildlife managers, the dean and director of the Wildlife Institute. The TRAC approves research proposals based on their scientific merit and value for conservation. Use of soft catch leg-hold traps, capture techniques and anesthesia for canids were approved by TRAC and the Chief Wildlife Warden. Smithsonian Institution scientists were not involved in the field ecology study and were subsequently involved in study design and training of two student co-authors in the genetics portion of the study. Furthermore, none of the samples were processed in the genetics lab at the Smithsonian Institution. All laboratory analysis was done at the Conservation Genetics laboratory of the Wildlife Institute of India. Samples from Bulgaria and Israel were provided by Ivan Nikolov  and Dr. Eli Geffen  respectively.Samples were collected from road-killed individuals and from golden jackals that were captured for a radio-telemetry study in Gujarat. Golden jackals were captured using a rubber padded "soft catch" foot hold trap and subsequently anesthetized using a gas powered dart delivery system with a combination of 8mg/kg ketamine and 2mg/kg xylazine . Blood sn = 7) were obtained opportunistically from road-killed individuals of golden jackal from across northern, western and peninsular India between the years 1994 to 2012 (n = 11) were obtained from golden jackals that were captured for a telemetry study in Gujarat in western India. Two samples from Israel and five samples from Bulgaria were also obtained for analyses. Samples were collected in 15 ml polypropylene screw cap tubes containing 70% ethanol in field and stored at -20°C upon arrival at the lab. Total DNA was extracted using the DNeasy extraction kit . We amplified approximately 440 bp region of the mtDNA CR locus using the primer pairs ThrL15926 and DL-H16340 [b gene using a canid specific light primer  and hair samples  and uniCanis sp., we performed a Bayesian Markov Chain Monte Carlo (MCMC) sampling scheme in MrBayes v3.2.2 [b (332 bp) and CR (277bp) sequences of golden jackals generated in this study, and including corresponding sequences of other wolf-like canids available in GenBank. Maned wolf (Chrysocyon brachyurus) sequence was used as outgroup to root the tree. The run length consisted of a total of 2 million MCMC replicates, of which the first 0.5 million runs comprised the burn-in, and chain convergence was assessed from the average standard deviation in split frequencies (<0.01). Gaps were treated as missing data and not used in analysis. Trees were analyzed using the Hasegawa-Kishino-Yano . Network calculations were carried out by assigning equal weights to all variable sites and with default values for the epsilon parameter (epsilon = 0) in order to minimize alternative median networks. Gaps were treated as missing data and nucleotide alignment blocks containing indels were removed before analysis.To understand evolutionary relationships of golden jackals with other s v3.2.2  by usingno , generano , Felsenno  and mixno  and CR 7bp sequeork tree  of mtDNAS), nucleotide (Π) and haplotype diversity (h). Nucleotide diversity is the average number of nucleotide differences per site and h is the probability that any two randomly sampled haplotypes are different [D [FS [S). Tajima’s D statistic is a measure of the observed variation seen in a population with respect to variation expected in a randomly evolving population at drift-mutation equilibrium. If the variation is selectively neutral and populations are at equilibrium, Tajima’s D will be indistinguishable from zero. On the other hand populations which experienced a contraction will have positive value of D (too few segregating sites/too many pairwise differences). D will be negative in populations which are undergoing demographic expansion or mutational selection (too many segregating sites/too few pairwise differences). The related Fu’s FS statistic measures the discrepancy between nucleotide differences observed in the sample, compared to the distribution expected in a randomly evolving selectively neutral sample at population equilibrium. A significantly negative value of Fu’s FS statistic indicates recent demographic expansion or departure from the null model hypothesis of selective neutrality and population equilibrium. The P-value is obtained from the proportion of random FS statistics to the observed FS value. Mismatch distribution tests detect patterns of variation of observed sequence differences to that expected in a randomly neutral population at drift-mutation-equilibrium. Populations that have experienced a recent expansion typically produce a right-skewed unimodal peak, whereas ragged and multimodal distributions are symptomatic of populations at demographic equilibrium [t), the parameter Tau (Τ)τ was estimated from mismatch distributions of pairwise differences among golden jackal haplotypes, and the formula Τ = 2μt was rearranged to calculate t, where μ is the mutation rate of the control region in units of per base pair per generation. We used a mutation rate (μ) of 7.30 x 10−5 bp-1 yr-1 as previously applied to CR sequences in the gray  and red vulpes, ). A gene vulpes, .b showed lower genetic diversity compared to CR sequences, with only nine haplotypes being obtained from a total of 40 cyt b sequences of golden jackal from India, Israel and Bulgaria. Seven cyt b haplotypes (six from this study and one from GenBank) were found in India  and CR (>10%) sequences , coyote , Himalayan wolf  and peninsular Indian wolf , based on cyt b and CR sequences respectively. Average cyt b and CR distances between golden jackal and the wolf-dog clade was slightly higher (8.2% and 15.1% respectively). Besides these relationships to previously recognized wolves from various parts of the globe, we also compared sequences of canids recently proposed to represent African wolves  which were previously classified as golden jackals [A total of eighteen CR haplotypes comprising sixteen from India, and one each from Israel and Bulgaria, were obtained from CR sequences of 58 golden jackals (56 from this study and two from GenBank) from India, the Middle East and Europe . In contin India . CR and sequence , 9, 38, al India . All theequences . The tax jackals .b haplotype network showed a shallow star-like radiation, and with individual haplotypes differing from each other by one to two nucleotide bases  of the CR haplotypes are completely peripheral with only one connection to the network  compared to golden jackals from other regions and related Indian canids  of ~37,083 years before present (YBP) for the Indian jackals , dhole  and maned wolf as outgroups, supports similar relationships of this group of Canis as previously reported by Lindblad-Toh et al. [b genetic distance >5%). The cyt b gene is commonly used as a genetic marker to distinguish among mammalian species, and >5% sequence divergence is typically observed between morphologically recognized species [C. mesomelas) and side-striped jackals (C. adustus) to golden jackals [b genetic distances). The paraphyletic origins of the jackal group have also been reported by previous studies on canid systematics [b genetic distance), golden jackals formed a sister clade with the Ethiopian wolf, albeit with low phylogenetic support (Bayesian posterior probability < 0.90). Phylogenetic support was similarly low (Bayesian posterior probability < 0.90) at the fork leading to the divergence of the archetypal wolf clades  from the neighbouring clade represented by the coyote, Ethiopian wolf and golden jackal. However, the evolutionary relationships among these group of Canis species have been well established [In this study, we sequenced a 440 bp fragment of the noncoding mtDNA CR locus and 412 bp of the coding mtDNA cyt h et al. , Ruenessh et al.  and Gaub species . Despite jackals , they artematics , 42. Altablished , 42 and Canis adustus) and not golden jackal. Unlike the noticeable incidences of hybridization between golden jackal and gray wolf observed in the African golden jackal/ wolf (Canis lupus (aureus) lupaster) in western and northern Africa [Canis species in India. The ranges of golden jackal and gray wolf overlap greatly not just in India, but also in southern Asia, the Middle East and the Balkans. Hybridization between jackals and wolves  may occur, especially in localities where population depletion has led to reduced mate availability in the wild. Extensive sampling of golden jackals, wolves and feral dogs, especially around areas of ecological overlap and contact zones from throughout the Indian subcontinent, is required to detect any incidence of potential admixture in this region. Furthermore, information from bi-parentally inherited nuclear markers is required as mtDNA sequencing can only reveal maternal genetic history. Further studies using autosomal nuclear markers (microsatellites and SNPs) and Y-chromosome linked markers are needed to evaluate the population structure, demographic history and potential hybridization with other canid species in the region.The phylogenetic analysis revealed a polytomy and no clear pattern of genetic structure between Indian, Israeli, Bulgarian and previously published haplotypes . We excln Africa , 12 and n Africa , there wn Africa  and anecn Africa , we deteb haplotypes and fifteen of sixteen CR haplotypes found in India were novel and have not yet been reported for other golden jackals published in GenBank. No clear phylogeographic pattern in India could be inferred from analysis of cyt b and CR haplotypes. Since cyt b had low resolution and revealed a polytomy as evidenced by the shallow star-like radiation in the median-joining network  mtDNA haplotype C lineage which is present in a wide-arc from Kashmir to eastern Nepal [Assuming that the ancestral haplotypes are internal while the derived haplotypes are peripheral, the CR haplotype CauInd11 with six connections to other haplotypes, and CauInd01, CauInd07, CauInd08 and CauInd15 with four connections, are relatively ancestral compared to the remaining haplotypes. These basal haplotypes were restricted to western and northern India and absent from other sampled regions. In contrast, CR haplotypes sampled from southern CauInd09) and central India  in our study were observed to be localized and more derived relative to northern and western Indian haplotypes. The most widespread Indian haplotype is CauInd01, represented by eight individuals from western  and northern (Uttar Pradesh) India. CauInd11 with six connections is the most ancestral haplotype sampled in our study. Due to low sampling intensity across India (except Gujarat state in western India) it is quite likely that more ancestral haplotypes may as yet be unsampled. The evidence of extensive branching, existence of alternative connections and shallow divergence seen in the golden jackal haplotype network is indicative of a population that has recently undergone demographic expansion. Indian CR haplotypes are not monophyletic with respect to other haplotypes found in GenBank  and sequ and centrn Nepal .D and Fu’s FS test statistics which are negative and in the mismatch distribution of pairwise differences which produced a right-skewed unimodal peak characteristic of demographic expansion. The non-significance of observed test statistics is likely due to the low sample sizes across many haplotypes. By using estimates of mutation rate previously applied in related species [~ 18 000 to 25,000 years ago [Signatures of demographic expansion or selection in the Indian golden jackal populations are evident from both Tajima’s  species , 36, to ears ago , 48. Theears ago . Howeverears ago , so our ears ago .Canis surveyed to date in India. Only four CR haplotypes were recovered for peninsular Indian wolf, five for Himalayan wolf and eleven for C. lupus familiaris [b haplotype was found when sequencing multiple individuals from different localities for each of these species [b sequences of Indian jackals revealed seven different but closely related haplotypes throughout the region, only differing by one or two base substitutions from one another . The post-Pleistocene expansion from refugial populations in the Indian-subcontinent to neighbouring regions seems likely as attested by the negative Tajima’s and Fu’s test statistics and right-skewed mismatch distribution peak. The star shaped polytomy of the haplotype network suggest that golden jackals may have undergone dramatic demographic changes in the recent past. Based on currently available data the Indian-subcontinent seems to be the center of radiation of golden jackals.Our study showed that haplotype diversity in the golden jackal was much higher than in any other member of the genus miliaris . In addi species . However another . This suS1 Fig(TIF)Click here for additional data file.S2 FigHaplotype circles are colour coded according to geographic locality, and circle size is proportional to haplotype frequency. Each node represents a one base pair change. Circle sizes are proportional to the number of individuals represented by each haplotype.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 TableEstimating the best model of molecular substitution inferred using Log Bayes Factors (LBF) from Bayesian posterior distributions in Mr Bayes. Rate variation for tested models—gamma distributed rate variation across sites (gamma); gamma distributed with proportion of invariable sites (invgamma); rate variation with proportion of invariable sites (propinv); equal rate variation across sites .(DOCX)Click here for additional data file.


The expression of lactase which digests lactose from milk in humans is generally lost after weaning, but selected mutations influencing the promoter of the lactase gene have spread into the human populations. This is considered a classical example of gene-culture co-evolution, and several studies suggested that the lactase gene has been under strong directional evolutionary selective pressure in the past 5000 to 10,000 years.In the present study we investigated the distribution of three gene variants leading to lactase persistence in 12 different East African populations as well as one European population. Our results show that with the exception of Copts and Nilotic populations who are fully lactose non-persistent, the majority of populations of East Africa show at least partly lactose persistence, with both ethnic and socio-economic aspects playing an important role in the distribution of genetic variants. In this study, the variants C/G-13907 and T/G-13915, which are the major variants among the nomadic Arabs in the Arabia and Beja of East Africa, showed remarkable frequencies in Sudanese populations, especially those of pastoralists, in line with the historical links and bidirectional migration of nomadic populations between Arabia and East Africa. The C/T-13910 variant, generally associated with European populations is uniquely present among the Fulani.These data indicate that a combination of socio-economic, ethnic and evolutionary factors converged to shape the genetic structure of lactase persistence in East African populations.The online version of this article (doi:10.1186/s13104-015-1833-1) contains supplementary material, which is available to authorized users. LCT gene [The milk sugar lactose requires hydrolysis in the intestinal tract into the monosaccharides glucose and galactose in order to facilitate their absorption by the enterocytes. The breakdown of lactose in the small intestine is catalyzed by the enzyme lactase, a glycoside hydrolase, which is encoded in humans by the LCT gene . LactaseLCT gene –4.LCT gene has been under strong directional evolutionary selective pressure resulting from shared cultural traits, animal domestication and adult milk consumption within the past 5000–10,000 years [MCM6 gene are known to regulate the LCT enhancer and are associated with lactase persistence in humans: the C/T-13910 SNP found mainly in Europeans, and C/G-13907, T/G-13915 and G/C-14010 SNPs found in African and Middle Eastern populations, while T/G-14009 is found in Ethiopia [The ability of adult humans to digest lactose sugar and the nutritional benefit conferred by this trait  is considered as a classical example of gene-culture co-evolution , 6. Many00 years –10. The Ethiopia , 10–13. The link between domestication of cattle and the inhabitants of the Nile Valley has a long history . ArcheolMCM6 variants modulating LCT. Variation in these SNPs lead to the tolerance to lactose in different populations from East Africa living along the Nile Valley in the current territory of the Sudan, South Sudan and Ethiopia. We correlated this information with the occupational characteristics of each of the populations, as well as with ethnic and historical aspects, to increase our understanding of population history in this ancient space of human civilizations.The aim of the present study was to assess the presence of three To investigate the genetic diversity of lactase persistence alleles among East African populations, a total of 488 saliva samples of unrelated individuals from 12 different East-African ethnic groups from the Sudan, South Sudan and Ethiopia were collected from different geographical area in the Sudan prior to separation.The samples used in the present study were collected and studied with ethical approval and informed consent (ref. SUM/2010/7). All protocols were approved by the IRB of the Sudan Medical and Scientific Research Institute (SUMASRI) at the University of Medical Sciences and Technology in Khartoum, and were carried out in accordance with the approved guidelines.Appropriate informed consent and questionnaires were obtained from all participants before sample collection; and samples were grouped according to their self-declared ethnic background of parents and grandparents, and languages. Sample sizes, geographic origin, and linguistic affiliation for each population are reported in Table All samples were genotyped for three SNPs in the MCM6 gene, which have previously been shown to regulate transcriptional activity of the LCT promoter and therefore confer tolerance to lactose (C/G-13907 (rs41525747), C/T-13910 (rs4988235) and T/G-13915 (rs41380347)) , 22. TheThe genotype and haplotype frequencies of the SNPs conferring lactase persistence among the selected populations are shown in Fig. P = 0.01). In addition, there was no significant pairwise disequilibrium between loci, with the only exception found between C/T-13910 and T/G-13915 (P = 0.01), and between C/G-13907 and T/G-13915 (P = 0.01) in Nuba.The SNPs in the various populations were tested for Hardy–Weinberg Equilibrium and pairwise disequilibrium using the three variants C/G-13907, C/T-13910 and T/G-13915. The Copts and Nilotes were excluded from the analysis due to the absence of any variants among the genotyped population. The values of observed and expected heterozygosity and fixation indices and their significance are shown in Table MCM6 genetic variants that influence expression of LCT gene were identified in selected East African ethnic groups living in the present territory of the Sudan, South Sudan and Ethiopia  .Nilotes are of unusually large stature, and live in the savannas of the Upper Nile region. They comprise Dinka, Nuer, Shilluk, Anyuak, Baria and a number of small ethnic groups. Nilotes speak languages within the Nilo-Saharan family. Farming and hunting are the major nutritional sources in Dinka and Nuer, populations that breed cattle and lead a semi-nomadic life, while Shilluk, Baria and Anyuak are agriculturalists , 28.LCT mutations, explain the absence/low frequencies of LP alleles among these ancient sedentary populations of the Nile Valley.The Copts (ancient Egyptians) descend from longstanding cultures of city-states and empires along the Nile, the socio-activities of this group being farming and trade. These different socio-cultural aspects of Copts, Nilotes and Nuba, most likely combined with the serendipitous lack of arising of novel The other residential groups of the Nile  are agriculturists. Despite the fact that their economy is mainly agricultural, they exhibit moderate allele frequencies of LP. This is intriguing in the sense that one would expect sedentary populations to be more able to admix and receive genes from their nomadic counterparts, as the area surrounding the Nile is economically attractive. This assumption is supported by the negative values of the fixation indices of these groups, which may indicate the increase of heterozygosity. Arabs, Nubians and Beja of the Sudan, and Ethiopians show high frequencies of the allele T/G-13915, which is the major LP variant among the nomadic Arabs in Arabian Peninsula . This suEthiopians genotyped in this study consist of three major groups, Oromo, Amhara and Tigray, they practice farming and animal breeding. Ethiopians display a genetic similarity with Beja of the Sudan; both of them have significant frequencies of lactase persistence haplotypes.Darfurians is a collective term for a number of residential agriculturalist groups living in arid areas in west of the Sudan (Darfur). Most of the groups in the area practice seasonal cultivation of crops during rainy seasons. They do not rely on fresh milk which is likely the reason why they have low proportion of lactase persistence alleles.Rob (sour yogurt) in the Sudan and South Sudan, white cheese, Mish and Gariss in the Sudan, and Ergo in Ethiopia. Rob and Ergo are naturally fermented cow’s or goat’s milk products [Mish are known in urban communities, and they were probably introduced into the Sudan from Egypt during the Turkish rule in the 19th Century. The major forms of milk fermentation give a good example of the integration of Arab and African cultures in the Sudan [Gariss is the special fermented milk of Arab camel herders in east and west of the Sudan. The camel herders spend sometimes months sustained on Gariss alone [Fresh milk is commonly used in pastoralist communities, and although agriculturalists of the Sudan, South Sudan and Ethiopia show lower frequencies of lactase persistence compared to pastoralists, the milk products are widely consumed by all socio-economic classes of East African agriculturalists. Both pastoralists and non-pastoralists exhibit different cultures of fermented milk products, including products , 30, 31.he Sudan . Gariss ss alone . Acetic ss alone .LCT gene variants that are associated with LP in twelve different East African populations. With the exception of Copts and Nilotes who are fully lactose intolerant, the majority of populations of East Africa have lactase persistence at moderate frequency. The genetic cause of lactose tolerance is however variable, with both ethnic and socio-economic aspects playing an important role in the distribution of genetic variants. The allele T/G 13915, the major LP variant among the nomadic Arabs in Arabian Peninsula, shows high frequencies in Sudanese populations, in line with the historical links and bidirectional migration of nomadic populations between Arabia and East Africa.In conclusion, in the present study we have investigated the distribution of These data tally with the previous data of the distribution of lactase persistence in East Africa, although future studies are warranted to investigate the distribution of more LP variants among the populations studied here. In conclusion, our study indicates that a combination of life style/culture with evolutionary pressure played a crucial role in shaping genetic structure of LP in African populations.


Ixodes scapularis, the tick vector of the Lyme disease spirochete, is distributed over most of the eastern United States, but >80% of all Lyme disease cases occur in the northeast. The role that genetic differences between northern and southern tick populations play in explaining this disparate distribution of Lyme disease cases is unclear. The present study was conducted with 1,155 SNP markers in eight nuclear genes; the 16S mitochondrial gene was examined for comparison with earlier studies. We examined 350 I. scapularis from 7 states covering a representative area of the species. A demographic analysis using Bayesian Extended Skyline Analysis suggested that I. scapularis populations in Mississippi and Georgia began expanding 500,000 years ago, those in Florida and North Carolina 200,000 years ago and those from Maryland and New Jersey only during the past 50,000 years with an accompanying bottleneck. Wisconsin populations only began expanding in the last 20,000 years. Analysis of current migration patterns suggests large amounts of gene flow in northern collections and equally high rates of gene flow among southern collections. In contrast there is restricted and unidirectional gene flow between northern and southern collections, mostly occurring from northern into southern populations. Northern populations are characterized by nymphs that quest above the leaf litter, are easy to collect by flagging, frequently feed on mammals such as rodents and shrews, commonly attach to people, and about 25% of which are infected with B. burgdorferi. If there is a genetic basis for these behaviors, then the patterns detected in this study are of concern because they suggest that northern I. scapularis populations with a greater ability to vector B. burgdorferi to humans are expanding south. Ixodes scapularis is the main vector of Borrelia burgdorferi, the bacterium that causes Lyme disease, the most prevalent vector borne disease in the United States. There are more than 30,000 new cases reported yearly, and possibly ten times that number of cases actually occur [Ixodes scapularis ticks have a wide distribution throughout eastern North America, with populations found along the Atlantic seaboard from Florida to Nova Scotia, and from the Atlantic coast west to the 100th meridian [I. scapularis differs dramatically between the northern and southern populations [I. scapularis quest above the leaf litter, are easy to collect by flagging, frequently feed on mammals such as rodents, commonly attach to people, and about 25% of questing nymphs are infected with B. burgdorferi. In the south, nymphal I. scapularis are difficult to collect by flagging, rarely attach to rodents or people, appear to be more common on reptiles than mammals, and B. burgdorferi infection is extremely rare in questing ticks [The black-legged tick, ly occur . The blaly occur , Powassoly occur . Ixodes meridian . But rismeridian , 7. Inteulations . In the ng ticks . CorrespI. dammini and I. scapularis, respectively [I. dammini was reduced to a junior synonym of I. scapularis [These and additional morphological differences were considered sufficient to classify northern and southern ticks as distinct species, ectively . Howeverapularis . Discretapularis –13. Lateapularis –17 and rapularis  or “All apularis  and anotapularis  or “Soutapularis  In additapularis –17.I. scapularis ticks has been investigated in several other studies. Some of them focus in specific areas, such as those in Virginia [I. scapularis ticks is described as highly structured on highly mobile hosts [I. scapularis using sequence information from the genome project (https://www.vectorbase.org/organisms/ixodes-scapularis) for primer design [I. scapularis [The migration pattern of Virginia  and New Virginia , while oVirginia , 21 for Virginia , the brele hosts , 24. Recr design  and to aapularis . This stapularis  supporteI. scapularis populations with a greater ability to vector B. burgdorferi to humans appear to be expanding south. To assess this possibility, we herein describe a study with sample sizes increased to fifty ticks/collection and the numbers of states sampled increased to seven to cover a more representative area of the distribution of I. scapularis. Larger samples sizes allowed us to perform a demographic analysis using Bayesian Extended Skyline plots [I. scapularis in the U.S and enabled us to perform a non-equilibrium analysis of gene flow [We were intrigued by the patterns indicated by these nuclear marker studies , 25 becane plots  to assesene flow . Three gI. scapularis. Ticks from New Jersey, Wisconsin and North Carolina were collected in 2009 by dragging sheets of cloth across vegetation (“flagging”). Flagging was also used in 2011 to collect from Maryland and in 2012 from Mississippi and Florida. Ticks in the 2012 Georgia collection were taken off of dead deer at a hunter check station. A minimum of 50 ticks were analyzed in each of the seven collections. For Virginia, New Jersey and Mississippi only 40 ticks were collected, since 10 were previously used in another study [Collection sites were selected in an opportunistic fashion throughout the natural range of er study . No specThe counties where collections occurred are mapped in www.genome.jp/tools/clustalw) and visually inspected to insure correct alignment along codons. The phase unknown sequences of each of the 9 genes were entered in “fas” format into DnaSP v5 [observed number of pairwise differences per nucleotide between all pairs of sequences. θ, calculated from η, is the average expected number of pairwise differences per nucleotide between all pairs of sequences. θ also estimates the approximate product of effective population size (Ne) and the neutral mutation rate per site per generation (μ) and therefore estimates the approximate maximum expected amount of genetic variation in a natural population. Tajima’s D [Nine genes were used for this study: Ixolaris 2A, Defensin, Heat shock protein 70 b2, Trospa, Ferredoxin-glutamate synthase, Dihydropyrimidine dehydrogenase, Serotonin 4 receptor, Acetylcholinesterase and 16S. Extensive details on gene selection, DNA isolation, primer design, PCR conditions, and sequencing protocols are published . SequencDnaSP v5 , where eDnaSP v5  into a pjima’s D  is the nAll aligned haplotypes were compared using RAxML v. 8  to identhttp://mrbayes.sourceforge.net/download.php). Results were visually compared to assess whether MrBayes and BEAST produce similar trees. The Bayesian Evolutionary Analysis Utility (BEAUti v1.8.1) in BEAST [http://beast.bio.ed.ac.uk/treeannotator in BEAST with 3% of trees used during burnin. FigTree v1.4.2 in BEAST was used to view the maximum clade credibility tree and to display the posterior probability (PP) for each branch.Maximum clade credibility trees were estimated for the 8 nuclear genes combined and for the 16S using the Bayesian Evolutionary Analysis Sampling Trees (BEAST v1.8.1) package  and by Min BEAST  generatein BEAST . The (HKin BEAST  was usedNe changes through time by directly inferring Ne as a function of time using sequence data. We used EBSP to assess the evolutionary history of I. scapularis.Extended Bayesian Skyline Plot (EBSP) analysis  was alsoθ and the effective migration rate 4Nem among collections using LAMARC 2.1.10 [M equals m (the immigration rate per generation) divided by μ. If M = 1, the rate that new alleles enter a population through immigration is equal to the rate new alleles arise by mutation. The effective migration rate 4Nem was calculated between a donor and recipient population as M multiplied by the recipient population θ. A 4Nem < 1 suggests that immigration is insufficient to offset the effects of genetic drift so that populations diverge in allele frequencies while a 4Nem > 1 suggests that there is sufficient immigration to offset the effects of genetic drift to maintain homogeneity among populations. 4Nem values are displayed as arrows on the collecting site map .The 8 nuclear gene sequences were next entered as a group for analysis of C 2.1.10 , 43. In site map  to indicobserved number of pairwise differences per nucleotide. θ, calculated from η, is the average expected number of pairwise differences per nucleotide. Tajima’s D is the normalized difference between π and θThe significance of D is indicated by *p<0.05, **p<0.01, ***p<0.001. The D ratio is only calculated for exons and is D for replacements substitutions divided by D for silent substitutions. Dhp and Hsp, average θ values and π values were greater in southern collections  [Ixodes ricinus sequences appear in green (clade A). Sequences collected exclusively in the south are colored red (e.g. clade C-E) while those only collected in the north are blue. Any high order branches that join both north and south sequences are black (clades B and F). The I. scapularis clade B has a PP = 0.95, the next three clades C-E are exclusively southern (red) in composition with PP = 0.99. Clade F (PP = 0.91) contains the remainder of all sequences and is a mixture of ticks collected in both the north and south. Note that this tree implies historical, but not necessarily current, unidirectional introgression of southern ticks into the north since no blue sequences appear in southern clades C-E. The topology of the maximum clade credibility tree and PP are extremely similar to those generated by MrBayes (tree not shown).Phylogenetic relationships among all of the 16S sequences generated in the present study and using ars (My) . The maxMaximum clade credibility coalescent trees were next derived for the combined nuclear genes but without outgroups since these genes have not been sequenced in other acari . This trhttp://beast-mcmc.googlecode. com/svn-history/r3615/trunk/doc/EBSP). The authors demonstrate the essential role of multiple loci in recovering population size dynamics. Multi-locus data recover past bottlenecks that cannot be characterized by analysis of a single locus.[Ixodes scapularis populations in Mississippi and Georgia began expanding 500,000 years ago, those in Florida and North Carolina 200,000 years ago and those from Maryland and New Jersey only during the past 50,000 years with an accompanying bottleneck. Wisconsin populations only began expanding in the last 20,000 years. This demographic analysis is consistent with a hypothesis that I. scapularis arose as a species in the southeastern U.S., expanded further south to Florida and North to the Carolinas and only within the last 50,000 years became established in the Northeast. Northern Midwest and Canadian populations only became established as the Laurentide Ice Sheet retreated.Extended Bayesian Skyline Plot (EBSP)  was perfle locus. EBSP aredo not appear in the north. On the other hand ticks from the red group occur exclusively in New Jersey and Mississippi. These results suggest historical unidirectional and bidirectional flow of mitochondrial genomes. Blue southern ticks appear in other southern states. Green ticks appear frequently in southern collections. Red ticks appear in both the northern and southern collections.The program STRUCTURE was used to estimate the numbers of genetic clusters (K) of ticks on the basis of their 16S haplotypes  and for A different pattern emerges from analysis of the combined nuclear genes which reflects current gene flow. The ΔK method again estimated three genetic groups. Green bars represent ticks primarily from Maryland, New Jersey, and Wisconsin while red bars represent ticks primarily from the four southern collections. The third blue genetic group consists primarily of ticks from Georgia, with some blue group ticks appearing in Florida, Mississippi and North Carolina. Two blue group ticks appear in Maryland and some northern ticks have genes from the red group. Conversely northern green cluster genes appear variously in southern collections. These analyses suggest, in agreement with 4Nem among northern collections , among southern collections , from north to south  and south to north . When analyzing all nuclear genes together, the average 4Nem among northern collections was 6.42 reproductive migrants per generation while there were 5.27 reproductive migrants per generation among southern collections. 4Nem was reduced between southern and northern collections with 1.51 migrants from the north to the south/generation and only 0.07 migrants from the south into the north/generation. Considering all nuclear markers together there was ~ 21 fold greater migration from north to south relative to the reverse direction.Rates and directions of gene flow were estimated for all nuclear genes combined using LAMARC. 4Nem values are also depicted as arrows in 4Nem <1 between pairs of collections are not connected with arrows. Green arrows among New Jersey, Maryland and Wisconsin indicate both directional and bidirectional gene flow among northern populations. Similarly, green arrows among North Carolina, Georgia, Mississippi and Florida indicate both directional and bidirectional gene flow among southern populations. There are no arrows that originate in the south and end in northern collections. Instead southern collections are all recipients of alleles from the north. North Carolina and Georgia receive immigrants from New Jersey, Florida receives immigrants from Maryland and Mississippi receives immigrants from Wisconsin.I. scapularis consistently reported greater genetic diversity in southern versus northern collections. This trend was noted earlier for the 16S mitochondrial genes [Earlier studies on the population genetics of al genes –16 and ial genes , and CO1al genes  mitochonal genes  and for al genes . The samI. scapularis collections [I. scapularis collections and detected a multimodal distribution with up to 17 mismatches in southern collections [I. scapularis populations appear to be at a demographic equilibrium while northern populations have gone through a recent demographic expansion. This trend is in agreement with the Tajima’s D analysis in the current and previous [Mismatch patterns were previously examined in northern and southern lections , 25. Thelections . The misThe maximum clade credibility coalescent 16S tree implies historical unidirectional introgression of southern ticks into the north and agrees in almost all respects with the published trees estimated by Maximum Parsimony, Distance/Neighbor Joining, Maximum Likelihood and Bayesian techniques in all previous studies –17, 25. I. scapularis arose as a species in the southeastern U.S. Populations in Mississippi and Georgia began expanding into Florida and North Carolina half a million years ago and into Maryland and New Jersey only 50,000 years ago and with an accompanying population bottleneck. Wisconsin populations only began expanding in the last 20,000 years as the Laurentide Ice Sheet retreated. During the northward expansion and accompanying population bottleneck, a barrier to gene flow arose such that very little bidirectional gene flow occurred between northern and southern ticks. This barrier must have existed over an extended period of time (and may still exist) in order to account for the small percentage of the alleles shared between northern and southern collections and for the patterns of isolation implied by the nuclear maximum clade credibility coalescent tree. During this time I. scapularis nymphs may have evolved away from an ancestral tendency to quest at ground level towards questing above the leaf litter. At the same time they may have switched from the ancestral tendency to seek and feed on reptiles towards locating and feeding primarily on mammals. Eventually the gene flow barrier seems to have partially broken down such that there is now gene flow albeit unidirectional from northern populations into the south.Taken as a whole these results suggest a scenario in which This scenario assumes that questing above the leaf litter and host preference are both genetic traits which are polymorphic in natural populations. In fact there is no data to support this idea. These behaviors may instead be plastic in response to different environmental conditions in northern and southern habitats.I. scapularis. By questing above the leaf litter, they frequently contact humans and rodents, thereby serving as an excellent bridge vectors passing Lyme disease spirochetes from their rodent and soricid reservoirs to people [While our study supports a model of current restricted, largely unidirectional gene flow, many biological questions remain unanswered. The principal vectors of Lyme disease spirochetes in the eastern US are nymphal o people . In conto people , 49, whiI. scapularis in the northeastern United States are favored by temperate environmental conditions and abundant rodent, bird, and large mammal hosts. Earlier studies [I. scapularis especially in Virginia, the Carolinas and Georgia will be needed to delineate the geographic regions where barriers and corridors for gene flow are occurring.Apparently, the highly successful populations of  studies , 21 and  studies –53, perhS1 TableColors correspond to those in (XLSX)Click here for additional data file.