Ruditapes philippinarum) stands as the second most important bivalve species in fisheries and aquaculture. Native to the Pacific coast of Asia, it is now well-established in North America and Europe, where its on-going management reflects local economic interests. The historic record of transfers spans the 20th century and suggests sequential movement from Japan to North America, as a hitch-hiker on oysters, and then intentional introduction in Europe, but global genetic data are missing. We have studied mitochondrial DNA and microsatellite markers in nine populations from Asia, North America and Europe. The results from the two types of markers indicated a good concordance of present-day genetic structure with the reported history of clam transfers across continents, and no evidence of relevant concealed introductions from continental Asia in Europe and North America. However, European populations showed a loss of genetic variability and significant genetic differentiation as compared to their American counterparts. Our study shows that in spite of the increasing ease for species to spread out of their native range, in the case of the Manila clam this has not resulted in new invasion waves in the two studied continents.Globally, the Manila clam ( One of the consequences of global change on marine ecosystems is the sudden introduction of species in new areas, which often show an invasive behavior and interact strongly with native species leading to changes in the ecosystem function1378910Ruditapes philippinarum) , which is one of the most appreciated shellfish species, is a good example of this type of situation. Manila clam culture represented 25% of global mollusk production in 2014. The natural distribution of the Manila clam extends over the western coasts of the Pacific Ocean ranging from the Philippines to Russiahttp://www.fao.org/fishery/statistics/global-aquaculture-production/query).The Manila clam  in 1936, and it is widely accepted that it came as an unnoticed hitchhiker with oysters imported from Japan317181921While the expansion of the Manila clam has been facilitated by its biological traits, such as high fecundity, a long larval phase (ca. 3 weeks), and broad salinity (15–50 PSU) and temperature tolerance (6–30 °C)24R. decussatus and subsequent introgression30In North America and Europe the Manila clam became naturalized immediately after its introduction and has shown a typical invasive character. The syndrome of ecological problems caused by invasive species is emerging in places where the Manila clam has established. This include an increase of clam numbers and the displacement of native species1623262728In contrast with the expansion experienced in North America and Europe, the situation of the Manila clam in its native range in Asia is characterized by stock reductions attributed to overexploitation and coastal pollution3334353637The economic importance reached by the Manila clam, and the problems related to its decline in Asia and its expansion and invasive behaviour in North America and Europe, have boosted scientific studies and integrated management plans394020343537384216452032333435363738COI have been studied in populations from China and Japan33Previous studies using genetic markers in native populations indicate that mitochondrial sequences and microsatellites can be used to test the introduction history of the Manila clam and to study the genetic population structure. DNA sequences of the mitochondrial gene COI sequences and microsatellites. Our goals were: 1) to test the reported Japanese origin of American and European populations; 2) to test whether introductions from continental Asia in North America and Europe have taken place; and 3) to test the predictions about the genetic variability of North American and European populations based on their differing colonization histories.In this paper we report a study of the genetic variability of Manila clam populations across continents by using mitochondrial We sampled 9 populations, two from China, one from Japan, two from North America and four from Europe . We obta33COI haplotypes and their frequencies by regions are represented in a phylogenetic network in We found a total of 113 haplotypes, from which 82 were unique . Sixty s33Hd) and low levels of nucleotide diversity (π) found previouslyHd ranged from 1.00 (in four Asian populations) to 0.69 (EUR-1) (Hd (0.80–1.00) and Europe the lowest (0.69–0.82), with American populations showing intermediate values (0.79 and 0.89). A similar trend was found in the case of π , taken from a previous studyOur analyses confirmed the high levels of haplotype diversity ( (EUR-1) . By regi clade A . The higD in only 1 population, indicating no significant departures from neutrality in the COI data set.Neutrality tests  renderedFST ranged between 0.041 and 0.246, and in most cases were significant after a sequential Bonferroni test  pair wise oni test . No signFST value of 0.109  and Japan , followed by Europe .We obtained a total of 0.109 . Within FST of 0.126, and interregional differentiation accounted for the majority of interpopulation variability (FCT = 0.081). A hierarchical model was also used to extract the among-population, within-regions component in genetic differentiation tests between pairs of regions. China and Europe were the most differentiated regions . No significant differentiation between Japan and America was found . America and Europe showed a high but non-significant interregional differentiation (FCT = 0.093).AMOVAFIS values ranging from −0.132 in EUR-4 to 0.183 in NAM-1  and expected heterozygosity (He) showed average values of 9.5 ± 0.3 and 0.7 ± 0.01, with little variation among populations, except slightly lower diversities in China (A) over loci ranged from 9.8 ± 4.1 in NAM-1 to 7.7 ± 3.2 in EUR-3, with the lowest values observed in European populations  was lowest in European populations and CHI-S   . In agreFCT) accounted for 5.4% of the total variation among populations. FCT values obtained with hierarchical analysis of F-statistics for two-region models indicated that the most differentiated regions were both Europe and America with respect to China, and the less differentiated were America and Europe, as expected from the reported history of clam introductions.The hierarchical analysis of variance based on a model of four regions  showed tet al. methodResults of Bayesian model-based clustering (BMBC) of genotype dataDLR statisticResults of assignment tests are given in COI haplotypes and in clams carrying COI haplotypes of other clades .This test could be carried out only in the JAP population, where mitochondrial clades A and C were in sufficient frequencies. We tested the difference in the estimated membership fraction of the genotype cluster 3, obtained from the BMBC analysis, in clams carrying clade A r clades . A StudePopulation genetics of Manila clams in their native range has been described elsewhere, but a specific discussion of the results obtained from our Asian samples is necessary before using them as a reference in the study of American and European populations. Previous studies33COI results. The absence of significant non-random association between nuclear alleles and mitochondrial haplotypes shows that the admixture between Chinese and Japanese genetic backgrounds in JAP occurred several generations ago, otherwise there would not have been time enough for the associations established when founding the population to disappearMicrosatellite data also support this view. We have found that most microsatellite alleles were present in the samples from both regions, and only a small proportion were exclusive of Japanese or Chinese samples, in agreement with previous studiesCOI data support the Japanese ancestry of North American populations. All the individual clams from North America analysed in this study, with only two exceptions, carried clade A haplotypes, as expected if they originated from Japan. In the case of the two individuals that carried haplotypes of other clades, the haplotype was C-4 in both cases. This was the most abundant haplotype of clade C, and has been documented in some localities from Japan in previous3315The The Bayesian model-based clustering (BMBC) analysis based on microsatellites also provided support to the Japanese origin of North American Manila clams. In this case the interesting observation is that cluster 3, which was the most common in the Japanese sample, but was rare in China, was also the most common in the American populations. Similarly, cluster 1, which was the most common in China, was almost absent from North America . The cluThe populations of Manila clam first recorded in America are supposed to have originated from nonintentional introductions, as a carry over with the Pacific oyster imports from Japan in the 1920’s to 1970’s44COI, the presence of haplotypes of clade A, which was typical of American populations, was almost exclusive in the European samples. The only exception, an individual from EUR-1, carried a clade C haplotype (C-4), which was also present in very low frequencies in America  the lowest values appeared in the two Chinese samples, but the European populations showed lower values than the two American and the Japanese samples 56FCT) between China and Europe than between Europe and North America, and a lack of genetic differentiation within Europe and North America. These results are congruent with the short time elapsed since the introduction of the Manila clam in these two regions, the long larval period that facilitates gene flow within the regions, and the aquaculture practices that have been developed after the introductions in N. America and Europe and favour the genetic mixing of populations. Mitochondrial data agree with this picture in general, although the values of population differentiation are higher for COI than for microsatellites as expected from its uniparental mode of inheritance58COI data contrast with microsatellites in showing higher differentiation between Europe and N. America than between N. America and Japan, which split earlier. Moreover, one haplotype (A-77) that was in relatively high frequency in European populations was absent from the American and the Japanese populations , Pacific North America and southern Europe (Nine populations of Manila clam n Europe . Twenty DNA extraction was carried out by boiling a piece of tissue in a 10% Chelex 100 preparation of 200–400 mesh (Biorad) during 20 minutes.The universal forward primer LCO1490Taq polymerase. The forward primer was fluorescently labeled with one of NED, VIC, PET or FAM fluorochromes. Each PCR started with a denaturation step of 3 minutes at 94 °C, followed by 35 cycles of 30 seconds each, consisting of denaturation at 94 °C, annealing at 58 °C and extension at 72 °C. A final step of 72 °C was carried out during 2 minutes. The PCR products were electrophoresed on an automated sequencer (ABI 3730 or ABI3730XL) at the genomics facilities of the SCSIE .After initial trials, seven microsatellites were selected for the present study on the basis of the absence or very low and manageable occurrence of artifacts such as allele dropout, stuttering or null alleles: Asari16, Asari24, Asari54, Asari62 and Asari64h), their frequencies, number of segregating sites (S), measures of haplotype diversity (Hd) and nucleotide diversity (π), and their standard deviations, were determined with the software package DnaSP v565The sequences obtained were edited with BioeditThe evolutionary relationships among COI sequences were represented with a phylogenetic network constructed with the program Network (fluxus-engineering.com), using a median-joining algorithmFST, hierarchical F-statisticsFST) was partitioned in among-regions (FCT) and among-populations, within-regions (FSC) components. The significance of the statistics was tested with a non-parametric permutation approach run for 30000 permutations.Pair-wise Genotyping was performed with the software GeneMapper v.4.1 (Applied Biosystems). Allele calling was achieved by adjusting the automated allele binning to a known internal size standard run alongside the PCR fragments. Low quality genotyping scores were revised manually. The program ALLELOGRAMFIS were obtained across loci and populationAllelic frequency estimation and Hardy Weinberg (HW) equilibrium tests were performed with the program Genepop'007Ap) across populations by means of a rarefaction procedure implemented in the program ADZEWe studied the private allele richness  method with the software STRUCTURE, version 2.3.451et al. formulaDLR statistic, a measure of the power of successful assignmentAssignment tests were performed on individual multilocus genotypes in order to estimate the probabilities of individual clams to be resident to a reference population. Individual assignation likelihoods were computed with the program GENECLASS2Accession codes: GenBank accessions of COI sequences are LT600424-LT600470.How to cite this article: Cordero, D. et al. Population genetics of the Manila clam (Ruditapes philippinarum) introduced in North America and Europe. Sci. Rep.7, 39745; doi: 10.1038/srep39745 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Xenopsylla cheopis (Siphonaptera: Pulicidae) is a vector of plague. Despite this insect’s medical importance, especially in Madagascar where plague is endemic, little is known about the organization of its natural populations. We undertook population genetic analyses (i) to determine the spatial genetic structure of X. cheopis in Madagascar and (ii) to determine the potential risk of plague introduction in the neighboring island of Mayotte.The flea X. cheopis differed, with the mean number of alleles per locus per population ranging from 1.78 to 4.44 and with moderate to high levels of genetic differentiation between populations. Three distinct genetic clusters were identified, with different geographical distributions but with some apparent gene flow between both islands and within Malagasy regions. The approximate Bayesian computation (ABC) used to test the predominant direction of flea dispersal implied a recent population introduction from Mayotte to Madagascar, which was estimated to have occurred between 1993 and 2012. The impact of this flea introduction in terms of plague transmission in Madagascar is unclear, but the low level of flea exchange between the two islands seems to keep Mayotte free of plague for now.We genotyped 205 fleas from 12 sites using nine microsatellite markers. Madagascan populations of X. cheopis, in Madagascar and suggests that a flea population from Mayotte has been introduced to Madagascar recently. As plague has not been reported in Mayotte, this introduction is unlikely to present a major concern for plague transmission. Nonetheless, evidence of connectivity among flea populations in the two islands indicates a possibility for dispersal by fleas in the opposite direction and thus a risk of plague introduction to Mayotte.This study highlights the occurrence of genetic structure among populations of the flea vector of plague, The online version of this article (doi:10.1186/s13071-017-2290-6) contains supplementary material, which is available to authorized users. Xenopsylla cheopis (Siphonaptera: Pulicidae) is a holometabolous insect ectoparasite and was first described in Egypt  was calculated for values of K ranging from 1 to 12, with five iterations for each K-value. The best estimate of K was taken to be the maximum value observed before the plateau of the curve Ln P(D) against K [STRUCTURE simultaneously identifies potential populations (clusters) and probabilistically assigns individuals to each of the gainst K . STRUCTUgainst K  was alsogainst K . CLUMPP gainst K  was usedgainst K .k-means clustering approach [adegenet package [find.clusters with the prior that the maximum number of clusters is equal to 12 (K = 12).DAPC is a multivariate statistical method which uses the approach . DAPC fi package  of the R package . The ideX. cheopis between Mayotte and Madagascar. DIYABC v.2.0 [An approximate Bayesian computation (ABC) analysis was conducted to infer the history of population introduction of BC v.2.0  was usedX. cheopis. The generation time of X. cheopis varies between 18 days to 20 months according to biotic and abiotic conditions [X. cheopis show seasonal dynamics in both the Central Highlands and Mahajanga [For all demographic parameters, prior distribution ranges were implemented according to current knowledge of nditions . Laboratahajanga . Larval ahajanga  and so, ahajanga , 55 afteahajanga . PrincipdivMigrate function from the R-package diveRsity v.1.9.89 [DivMigrate uses the method described in Sundqvist et al. [To determine directional relative migration between the three chosen populations, we used the v.1.9.89  using Jov.1.9.89  and witht et al. .IS values  (Table P < 0.05). Estimated frequencies of null alleles per locus per population ranged from 0.16 to 0.45   approached a plateau at K = 4  to 0.51 (Antananarivo vs Ambondromisotra), with most values quite high (> 0.25) and almost all values of FST significantly different from 0. The unbiased FSTENA values ranged from 0.01 (Port of Mahajanga vs Marolaka) to 0.45  .Division of populations into genetic groups was also reflected by the differentiation among these populations suggested by values of Fp) was obtained for scenario 6 (p = 0.50), with scenarios 7 and 5 having substantially lower probabilities  and with Scenario 5 favored over 7 . All other scenarios for both approaches had low (< 0.1) probabilities  providing confidence in the scenario choice. The favored Scenario 6 assumes that the population from Marolaka was a result of an admixture of a population from Longoni and from Amparafaravola  and Amparafaravola (Madagascar) migrated and constituted the sink population of Marolaka (Madagascar). High significant relative migration rates were obtained: 0.87 (Longoni to Marolaka) and 1 (Amparafaravola to Marolaka)  at an admixture rate of r2 = 55.8% (95% CI: 21–82%) , compared with a range of 0.01–0.21 for rats [Within Madagascar, although there was fairly high genetic differentiation between populations, there was evidence of some gene flow between populations. As predicted, for rats , and higfor rats . Althougfor rats , 32. MorX. cheopis with the results for R. rattus reveal some similarities and some interesting differences. It is notable that the R. rattus genetic structure appears to broadly follow a north/south divide [X. cheopis which showed shared membership of different clusters. Although our results therefore suggest some congruence with the phylogeographic structure of hosts, as suggested for another fur flea, Listropsylla agrippinae, in South Africa [X. cheopis did not appear to be strongly associated with geographical distance and R. rattus genetic structure. Specifically, some sites further south also showed shared membership of different clusters , whilst, unlike for R. rattus [vs Tsiroanomandidy and Ambondromisotra), indicating that in some cases little gene flow occurs between populations separated by relatively short distances. These apparently contradictory results could be explained by differences in the relative importance of human-mediated dispersal between R. rattus and X. cheopis and between sites.Thus, comparisons of our results for h divide . The norh Africa , in gene. rattus , differeR. rattus have largely been replaced by R. norvegicus . Flea enanarivo ). Thus, nanarivo , human-mhabitats , this wohabitats . In contX. cheopis in rural landscapes and the likely effects on dispersal rates and effective population sizes, the number of clusters detected in Madagascar (three) is perhaps surprisingly low. This is especially true when compared to the more significant, local clustering of Y. pestis [Y. pestis in the landscape (transmitted between rats in habitats other than houses by the endemic flea S. fonquerniei) and presumably increased opportunities for dispersal. Although our results do suggest significant levels of gene flow, likely via human-mediated dispersal, they may also reflect the restricted nature of our study as sampling too few individuals per site can lead to underestimation of the number of clusters [Whilst fleas did show more genetic structuring than rats, given the patchy distribution of . pestis , despiteclusters  and incoclusters . Howeverclusters . In our X. cheopis showed heterozygote deficit which is significant in almost all cases. Evolutionary processes such as genetic drift, natural selection, inbreeding, mutation, population bottleneck or gene flow may influence allele frequencies and cause heterozygote deficit. Several of these may have contributed to our results. In addition to the gene admixture and gene flow between populations discussed above, fleas obtained from individual rats or rat families may be related, whilst population bottlenecks could occur within the spatially restricted populations of X. cheopis or due to seasonal dynamics in highland populations [X. cheopis within Madagascar and elucidate the role of rat dispersal and human-mediated dispersal. However, our rather limited study already yields important insights, possibly due to the strong hierarchical structure inherent within parasite populations.Other factors may also influence the observed patterns of genetic variation within and between populations. Nine among twelve populations of ulations . IncreasdivMigrate analyses suggesting asymmetric gene flow from Mayotte to Madagascar. This exchange is likely to be linked to commerce and shipping routes in the Indian Ocean and reflects similar patterns in previous studies of other species. The mitochondrial haplotype group associated with the R. rattus introduction to north Madagascar [R. rattus introduction was found in Mayotte [R. rattus from Madagascar [X. cheopis from Mayotte, only one R. rattus individual in Madagascar has been shown to carry a mitochondrial haplotype related to European human colonization [Our results indicate that limited flea exchange does occur between Mayotte and north Madagascar, with both the ABC analysis and the dagascar  has prev Mayotte . This ledagascar . Interesnization , again pX. cheopis) and plague-competent mammal host species such as R. rattus and an insectivore found to be infected with Y. pestis in Mahajanga (Suncus murinus) [Y. pestis indicate that Mahajanga outbreaks were triggered by dispersal of infected rodents or fleas from the Central Highlands [Our findings are important for assessing the epidemiological risk of plague introduction in plague free areas such as Mayotte. Mayotte already supports populations of both a plague-competent vector species (murinus) . Althougmurinus) , the infmurinus)  and geneighlands , the risX. cheopis is not associated with morphological differences, genetic differences might affect vector competence or resistance to pathogens [Aedes albopictus (insect vector of dengue and yellow fever viruses) [X. cheopis differ in their vector competence.Even if plague did arrive in Mayotte due to the movement of infected fleas or hosts, many other factors would influence plague establishment and the risk of epidemics in the human population. One such factor is vector competence. Although the genetic differentiation among populations of athogens  and therviruses) –67. InteS. fonquerniei.Clearly, to further understand the risk of plague introduction and establishment in neighboring countries such as Mayotte as well as plague outbreaks in Madagascar outside the plague focus, there is a need for further, more extensive studies of flea and rat dynamics and dispersal, including for the endemic vector species, X. cheopis, from Madagascar and the nearby island of Mayotte. Gene flow occurred between Madagascar and Mayotte, but with evidence for a flea population having been introduced recently from Mayotte to Madagascar. As X. cheopis is the main vector of plague in Madagascar, the introduction of individuals to Mayotte may present a risk of plague introduction to this island.This study shows strong spatial structure among populations of the flea vector of plague, Additional file 1:Protocol describing microsatellite primers development . (DOCX 19 kb)Additional file 2: Table S1.Estimated frequencies of null alleles per locus per population using Van Oosterhout’s method. (XLSX 10 kb)Additional file 3: Figure S1.a) Posterior probability L(K) and (b) DeltaK obtained based on K numbers of genetic populations ranging from 1 to 10. (PDF 52 kb)Identification of the number of genetic clusters using the methods of Pritchard & Evanno , 46. (a)Additional file 4: Table S2.FST and values between all populations. Table S3. Pairwise FSTENA values among populations. (XLSX 12 kb)Pairwise Additional file 5: Table S4.Probability for each of the seven tested scenarios of population introduction using direct and logistic approaches. (XLSX 9 kb)Additional file 6: Figure S2.a) Posterior probabilities of scenarios obtained through a logistic regression computed every 10% (between 10 and 100%) of the number of selected datasets. (b) PCA plot allowing to visualize how close datasets simulated  under each scenario (different colors) are from the observed dataset (large yellow dot). The most relevant scenario chosen was scenario 6. The probabilities for each scenario using direct and logistic approaches are given. (PDF 786 kb)Raw results obtained for the seven scenarios tested using DIYABC software. . Pseudo-observed datasets (pods) were drawn from 500 simulated datasets closest to the observed dataset (s = 500). (DOCX 17 kb)Additional file 8: Table S6.divMigrate from the package diveRsity [Bidirectional estimate of relative migration rates. The data give relative migration values by pairwise comparisons of the three populations from Madagascar and Mayotte. Analysis was performed using the function iveRsity . Jost’s iveRsity  and the


Amorphophallus paeoniifolius, is a commercially important vegetable crop because of its high production potential. In this study, we generated a total of 166 Gb of genomic data from 16 wild and 20 cultivated A. paeoniifolius individuals in southwestern China using restriction site associated DNA sequencing (RAD-seq). We compared the genome-wide variations between the wild and cultivated populations. Wild populations exhibited higher genetic diversity than did cultivated populations based on private allele number, expected heterozygosity, observed heterozygosity and nucleotide diversity. STRUCTURE analysis, principal component analysis (PCA) and a maximum likelihood (ML) tree indicated that A. paeoniifolius populations could be divided into three groups (a cultivated group and two wild groups) with significant genetic differentiation. The low genetic diversity and shallow genetic differentiation found within cultivated populations are likely caused by continuous selection and the clonal propagation methods used during domestication. The significant differentiation between the wild populations may suggest strong genetic drift due to small populations and human disturbance. The genome-wide single nucleotide polymorphisms (SNPs) identified in our study will provide a valuable resource for further breeding improvement and effective use of the germplasm. Accessing genetic variation between and within wild and cultivated populations of crops could provide insight into the general mechanisms of plant domestication and diversification and could guide the genetic improvement of crops in future breeding programs4.Crop domestication not only modifies the economic and agronomic traits but also leaves a genetic signature that affects both the genetic diversity and population structure of domesticated plantsAmorphophallus paeoniifolius (Dennst.) Nicolson is a tropical tuber crop that originates from south-east Asia and belongs to the genus Amorphophallus. It is an important economic crop because of its high production potential (50–60 t/ha) and popularity as a vegetable5. Amorphophallus paeoniifolius is mainly cultivated in India, and serves as an important food resource for humans and as animal feed6. Although Amorphophallus species have been historically used as a food source and in traditional medicine, A. paeoniifolius has not been widely planted in China. However, a new cultivar of A. paeoniifolius, A. paeoniifolius ‘Yellow’ was discovered in some villages in the southern Yunnan provinces in China in 20127. This cultivar differs from wild A. paeoniifolius in several ways, such as its tufty habit, glossy petiole and peduncle7. Amorphophallus paeoniifolius ‘Yellow’ has been domesticated in these villages for a long time. This cultivar has great potential as a vegetable crop for its fine character, including low fibre content in the corm and good disease resistance7.9. Genetic information before domestication and artificial selection might have been reserved in wild populations, which are particular resources for studying the influence of human selection on genetic variation in the A. paeoniifolius genome. However, the natural populations of A. paeoniifolius in China are strongly influenced by human activities, such as harvesting and deforestation, and most remaining populations are restricted to home gardens and agroforestry systems10. Thus, conservation measures must be taken to prevent the further decline of A. paeoniifolius resources, and information about genetic diversity and population structure is essential for formulating management and conservation approaches. Amorphophallus paeoniifolius can outcross, but vegetative propagation is usually used during cultivation and bears significant genetic load. The reliance on clonal propagation and the limited diversity of A. paeoniifolius germplasm make it highly vulnerable to many bacterial diseases, such as bacterial soft rot disease11. Heredity improvement of A. paeoniifolius cultivars using wild germplasms urgently needs to be addressed. Developing genomic resources, increasing understanding of the A. paeoniifolius gene pool (including wild germplasms), and gaining information about genetic diversity and population structure should speed the progress of biological research and genetic improvement.There is evidence that domestication has led to a reduction in genetic diversity for several cultivated cropsA. paeoniifolius. Only a few studies have been carried out to gain information on the genetic diversity of A. paeoniifolius and its relationships with relative species using molecular approaches such as simple sequence repeats (SSRs)13, inter-simple sequence repeats (ISSRs)14 and chloroplast DNA loci16. However, the molecular markers cannot provide sufficient resolution for genetic diversity and genetic structure inferences. Rapid progress in high-throughput sequencing technologies has provided an opportunity to infer genome-wide information from organisms without reference genomes with affordable cost. Reduced-representation genome sequencing allows us to discover thousands of genetic markers from many samples for population genomics studies19. These methods which consisted of restriction site associated DNA sequencing (RAD-seq) and genotyping by sequencing (GBS) have been successfully applied to population genomics studies of mangy species22.Currently limited genomic information hinders genetic studies of A. paeoniifolius domestication and accelerate its agricultural application, we generated and analysed genome-wild SNPs for the wild and cultivated populations of A. paeoniifolius (2n = 2x = 28) in southwestern China by RAD-seq to provide a better understanding of the genetic diversity, genetic structure and divergence of this species. Our study will enhance the future genetic improvement of this important crop.To contribute to the understanding of For the 36 sequenced samples, 166.2 Gb of raw data with an average of 4.49 Gb per sample were generated, ranging from 3.68 to 5.50 Gb. With quality filtering of the sequence data, a total of 161.0 Gb of clean data  was kept, presenting an average effective rate of 99.56%. In brief, our sequencing data showed high phred quality , with a stable GC content ranging from 41.07% to 44.58% Table .A. paeoniifolius at the germplasm level (between wild and cultivated germplasms), the 36 samples were divided into two groups. When we required loci to be present in at least 80% of the samples of the two groups, 32,536 RAD loci were retained. When comparing genetic diversity among the seven populations, 19,575 loci were retained after requiring loci to be present in 80% individuals of no less than six populations. More than two thirds of the SNPs at the population level (with an average of 73.70%) were confirmed to be transitions, and the observed transition vs. transversion (ts/tv) ratio ranged from 2.63 to 3.10 for each population. The variation numbers (transitions and transversions) and ts/tv ratios of the SNPs were much higher for the two wild populations of A. paeoniifolius than for the populations of A. paeoniifolius ‘Yellow’ , observed heterozygosity (HO), expected heterozygosity (HE) and nucleotide diversity (π) of the wild germplasm were 25440, 0.2289, 0.3463 and 0.3592, respectively. For A. paeoniifolius ‘Yellow’, the AP, HO, HE and π values were 880, 0.1963, 0.1022 and 0.1053, respectively. When analysing all nucleotide positions, including the non-polymorphic sites, the observed heterozygosity, expected heterozygosity and nucleotide diversity of wild A. paeoniifolius dropped to 0.0009, 0.0013 and 0.0013, respectively. The three statistics , including non-polymorphic sites of A. paeoniifolius ‘Yellow’, were 0.0007, 0.0004 and 0.0004, respectively  to 0.2617 (MXXZ); the expected heterozygosity for each population ranged from 0.0644 (MBT and MLYQ) to 0.2682 (HHXJ); the nucleotide diversity for each population ranged from 0.0721 (MLTS) to 0.2854 (HHXJ); and the inbreeding coefficient in each population ranged from −0.1011 (JD) to 0.0634 (HHXJ). When considering all nucleotide positions comprising the non-polymorphic sites, the observed heterozygosity dropped to 0.0004  and to 0.0008 (MXXZ and HHXJ); the expected heterozygosity decreased to 0.0002  and to 0.0008 (MXXZ and HHXJ); the nucleotide diversity ranged from 0.0002  to 0.0009 (HHXJ); and the inbreeding coefficient within each population ranged from −0.0003  to 0.0002 (HHXJ). The private allele number in each population ranged from 0 (MLTS) to 8151 (MXXZ)  revealed similar patterns. Structure Harvester suggested that see Fig. . The sevter Fig. , Fig. 3.ers Fig. . The geners Fig. .Figure 2FST = 0.194) was found between wild A. paeoniifolius and A. paeoniifolius ‘Yellow’ at the germplasm level (P < 0.05). The pairwise FST values between populations varied from 0 to 0.2909, with 9 of the 21 population pairs detected with significant values (P < 0.05) (Table A. paeoniifolius ‘Yellow’ were significantly differentiated.A moderate level of genetic differentiation (5) Table . None ofA. paeoniifolius ‘Yellow’ were analysed separately, only the statistics for the wild germplasm were significant, with the variation among populations measured as 44.2%  divided the overall genetic variance as 32.4% between the wild and cultivated germplasms, 20.6% among populations within the germplasm and 47.0% within populations  of 372 bp  SNPs and non-genic SNPs. Genic SNPs, which represent potential function-related variants, are useful for realizing phenotype mutations, genetic drift and gene flow in cultivated and natural populations; they are especially important for describing genes associated with complex traits bp Fig. .Amorphophallus konjac, 107 assembled contigs of A. paeoniifolius (0.01%) were aligned to the unigenes of A. konjac. According to the annotation results against NCBI’s non-redundant database, of the 107 unigenes that showed sequence similarity with A. paeoniifolius sequences, 102 unigenes were significantly mapped to known genes with BLASTX. The annotated sequences were implemented using Blast2GO for GO classification. The top two richest subcategories of the biological processes are metabolic processes and cellular processes. The most highly represented genes under the cellular component category are cell and cell part. Binding and catalytic activity represent the majority of molecular function  for the cultivated group were much lower than the wild accessions across the entire genome when at both the germplasm and population level . Consistent with this expectation, the ts/tv ratio of the seven A. paeoniifolius ‘Yellow’ formed one cluster, and the two wild populations were split into two clusters. The hierarchical AMOVA also revealed a high level of genetic variation among the three clusters  and a significant (P < 0.01) level of variation between the wild germplasms and the cultivar (32.4%)  as comparatively small populations. Human activities in recent years have dramatically influenced the genetic patterns of A. paeoniifolius populations, and the disturbances and encroachments from humans are still increasing. Deforestation for construction, farming and grazing has caused continuous and serious damage to the natural populations of A. paeoniifolius10. The higher FST values between the two wild populations may suggest stronger genetic drift caused by these factors  is mainly the unavailability of the reference genome data. Although we used the transcriptome dataset from the relative species A. konjac33 as the reference database, the genome of A. paeoniifolius is the best choice as the reference database to find more comprehensive SNP loci which are related to important agronomic traits such as characteristic secondary metabolism and crop defense of diseases. However, the large genome of A. paeoniifolius (proximate 4.21 Gb)34 has hindered us to obtain genomic information. In the near future, when the A. paeoniifolius plant genome sequencing is complete; we believe that the reference genome data will boost population genetics and functional genetic research in A. paeoniifolius.We obtained usable information for 102 contigs containing at least one SNP associated with gene function, which might be useful for future studies of the genetic mechanism of the distinct characteristics among wild and cultivated A. paeoniifolius in China have severely declined because of human activities10. Although we tried to collect as many samples as possible during field investigation, only 16 wild individuals and 20 cultivated individuals were acquired. It has been shown that using thousands of SNP loci could be powerful for population genetic analysis36, and the genome-wide SNPs might partly offset limitations due to the small sample size. Nonetheless, the 36 individuals used in our study were not sufficient for assessing the genetic diversity of A. paeoniifolius at the whole species level. The cultivar A. paeoniifolius ‘Yellow’ is only found in small regions of southern Yunnan province in China7. The sample locations in our study represented the full geographical range of the cultivar A. paeoniifolius ‘Yellow’. It is believed that this cultivar was domesticated from wild plant materials collected from adjacent areas by farmers7. Our sample strategies, which focusing on this small area, should be comprehensive in accessing changes in genetic variation during the domestication of A. paeoniifolius ‘Yellow’. Different genetic patterns discovered between wild and cultivated populations in our study could serve as a hint for artificial modifications to the A. paeoniifolius genome during domestication in southwestern China. As A. paeoniifolius has a relatively wide distribution range, further studies with sufficient samples are needed to fully evaluate the genetic diversity of A. paeoniifolius.Populations of A. paeoniifolius populations by using RAD-seq. We believe this is the first study to report the exploration of such a large number of novel SNPs from A. paeoniifolius and that further increases the amount of genomic resources available for this species. The results provide new insights into the genetic consequences of crop domestication.In conclusion, we reported the exploration of tens of thousands of SNPs to inspect the genetic relationship and compare the genetic diversity of wild and cultivated A. paeoniifolius (16 samples) and 5 populations of the cultivar A. paeoniifolius ‘Yellow’ (20 samples) were collected in 2016. A map of the sampling locations was created using software GenGis 2.5.037  and free raster map data from Natural Earth   Fig. . Leaves EcoRI, random fragmentation with the Covaris S220 instrument , barcode ligation and DNA purification, gel fragment selection, adapter ligation and fragment amplification. Pair-end sequencing with a read length of 150 bp was used to produce approximately 4 Gb of raw data for each sample with the Illumina HiSeq. 2000 platform .RAD sequencing library preparation and sequencing was conducted by the Novogene Bioinformatics Technology CO. ltd, Beijing. Briefly, the libraries were prepared following DNA digestion with EcoRI cutting sites were also discarded.The raw data from 36 individuals was first quality-filtered. Adapter sequences and paired reads with alternative reads containing ≥50% low-quality bases  or ≥10% unidentified nucleotides were removed. The putative duplication reads and reads without intact 38 was utilized. The filtered data for each individual were grouped into loci by ustacks with a minimum stack depth (-m) of 5 and a distance allowed between stacks (-M) of 2. The loci for all samples were then merged into catalogues by cstacks with distances between catalogue loci (-n) of 2, and the loci of each individual were matched against the catalogue to obtain genotypes of the loci in each sample with sstacks.To identify SNP loci for population genetic studies, the Stacks tool set39 in all analyses. Because the sample size in our study was relatively small, SNP loci with a global minor allele frequency (MAF) < 0.05 were therefore discarded to limit false SNP identification. SNP loci were selected using the ‘populations’ program implemented in Stacks38. Molecular statistics for the SNPs for the seven populations were analysed using Arlequin 3.5.140.To analyse the genetic diversity at the germplasm level, the genetic diversity statistics in the two germplasm groups were estimated separately. At least 80% of the samples (r = 0.8) and in all two germplasm groups (p = 2) must contain a locus for it to be included in the analyses. When we analysed the genetic diversity and structure at the population level, a locus was required to be present in 80% of the individuals (r = 0.8) and in no less than six populations (p = 6). Only a single SNP was randomly selected per locus to remove tightly linked SNP lociAP), nucleotide diversity (π), heterozygosity (HO and HE) and inbreeding coefficient (FIS), were calculated using the ‘populations’ program in Stacks38. To analyse pairwise population differentiation and differentiation between wild and cultivated germplasms, FST values were also computed with the ‘populations’ program and tested based on 1000 permutations with Arlequin 3.5.140.Genetic diversity indices, including the private allele number . The ‘populations’ program in Stacks38 was employed to output SNPs into the structure-format file. In the STRUCTURE analysis, an admixture model with correlated allele frequencies between populations was used. Ten replicates for each K (K = 1–6) were computed, with 50,000 burn-ins followed by 150,000 Markov chain Monte Carlo steps. The optimal K was inferred based on the ΔK method implemented in STRUCTURE HARVESTER 0.6.9442. Admixture proportions from replicate simulations at the optimal K were averaged using CLUMPP 1.1.243. Summary outputs were displayed with the program Distruct 2.144. PCA analysis was conducted using the Adegenet package45 in R to further investigate the genetic structure between populations. A variant call format (VCF) file was generated using the ‘populations’ program in Stacks38. A maximum likelihood (ML) tree of 36 individuals was constructed with 1000 bootstraps using the SNPhylo software46.Genetic structure was investigated by STRUCTURE 2.3.440, and the significant level for the variance components was computed using 1000 permutation steps.AMOVA was conducted to quantify genetic variation at three different hierarchical levels: among germplasm groups, among populations within the germplasm group and within populations. Genetic variations were further tested by assigning populations to genetic clusters identified by population structure analyses . AMOVA was also conducted to assess intra-differentiations within wild or cultivated germplasms. The analyses were conducted in Arlequin 3.5.138. The collated sets of reads for each catalogue locus were then assembled into contigs by the command ‘exec_velvet.pl’, which executes the Velvet47 program. To estimate the homology of these contigs to coding regions, a transcriptome dataset of a related species (A. konjac) was downloaded from NCBI (SRR555564)33 and assembled into unigenes using the Trinity 2.4.0 software48. The SNP-associated RAD tag sequences were aligned against the assembled transcriptome of A. konjac using SOAP 2.2149 with the default settings. To investigate the gene function of loci, a BLASTX search was applied against NCBI’s non-redundant database by BLAST 2.2.2850 with an E-value of 1e−6. According to the annotation results, Blast2GO 2.5.051 was used to obtain functional classification of the sequences using GO terms with an E-value of 1e−6, which maps sequences to gene functions in term of molecular function, cellular components and biological processes52.To examine genic SNPs, paired-end sequences for each catalogue locus with at least one SNP were collated using the command line ‘sort_read_pairs.pl’ implemented in StacksAmorphophallus paeoniifolius individuals was deposited in the National Center for Biotechnology Information (NCBI) Sequence-Read Archive (SRA) database with the accession numbers SAMN07175567 - SAMN07175602.The raw RAD sequence data for the 36 wild and cultivated Supplementary Figures and Tables


Sedum album (Crassulaceae) is a common inhabitant of rocky sites in central European dry grasslands. We inferred the phylogeographic history of S. album over its distribution range in Europe. Genetic diversity within and differentiation between 34 S. album populations was examined using AFLP markers. Population isolation was indicated based on the rarity of the fragments and by isolation-by-distance effects. We sequenced the trnL-trnF region in 32 populations and used chloroplast microsatellites to analyze chloroplast haplotype distributions. Two distinct S. album lineages were detected. One lineage was comprised of populations from eastern and central parts of central Europe, and the Apennine Peninsula. A second lineage was comprised of populations from the Iberian Peninsula and western and northern parts of central Europe. Glacial refugia were identified based on the accumulation of ancient chloroplast haplotypes, high diversity of AFLP fragments within populations, and high levels of rare fragments in Liguria, Serbia, the Apennine and Iberian peninsulas. Cryptic refugia were detected in the Czech Republic and Slovakia. Isolation by distance was present all over the distribution range, and it was separately detected in southwestern and central Europe. In western Europe, where a contact zone between the two lineages can be expected, no isolation by distance was detected. Our results suggest migration routes of S. album northeastward from glacial refugia in southern Iberia, northward from the Apennine Peninsula, and northward and westward from the southeastern parts of central Europe. Therefore, central European grasslands were recently colonized by northern cryptic populations and source populations originating in the east and the Apennine Peninsula.Phylogeographic analyses of plants in Europe have revealed common glacial refugia and migration routes for several trees and herbs with arctic-alpine distributions. The postglacial histories of dry grassland species in central Europe have rarely been analyzed, even though the extremely species-rich habitat is threatened.  The geographical distribution of plant species has always been influenced by climatic and edaphic factors. Quaternary ice ages dramatically reduced the habitats of most species –3. LargeNevertheless, next to the general contradiction-expansion theories, the plants and animals could have survived in northern areas characterized by suitable microclimate . For manHelianthemum in southern France and near the Pyrenees, from where the species migrated northward and westward [Comparative phylogeographic studies identified patterns in the distribution of genetic diversity that could explain collective areas of glacial refugia and migration routes in Eurasian areas ,8. The Iwestward . Refugiawestward ,12,14–16westward ,17,18. Rwestward ,19.In addition to archeobotanical findings  genetic techniques are the methods of choice used to reveal the postglacial history of plant species . PossiblRegarding migrations during interglacial periods and after the LGM, mankind was an influential factor for most plant species in central Europe ,32. NatuTo date, the postglacial histories of several tree species trees ,11,14–18Sedum album L. (Crassulaceae) is a typical inhabitant of dry grasslands in alkaline and calcareous soils in central Europe. It can be found on rocks and shallow soils within the Festuco-Brometalia vegetation type and in pioneer vegetation on rocks within the Sedo-Scleranthetalia-group  [S. album can also be found in crevices on stony riverbanks and in forests with oak or olea in the Mediterranean. Further, the species immigrates to man-made habitats, including the stone walls of buildings and gardens in cities and villages [S. album is common, and it is distributed over wide regions in temperate Europe and the Mediterranean.The succulent illenii) –56. S. avillages ,57–59. NS. album in Europe using AFLP markers, chloroplast sequences (trnL-trnF), and chloroplast microsatellites to answer the following questions: 1) Can we infer the postglacial history of a common plant like S. album using standard methods (AFLPs and chloroplast markers)? 2) Was S. album introduced to central Europe after the LGM from glacial refugia in the southwest or southeast? 3) Can we detect cryptic refugia in central Europe? 4) What are the characteristics of the migration routes of this species to dry grasslands in central Europe?In the present study, we investigated 34 populations of Sedum album L. (Crassulaceae) is a perennial herb, with succulent woody stem and succulent, linear-cylindrical to ovoid leaves. Seeds are long-term persistent and dispersed by rain and water. Shoots and leaves are very resistant to drought and can develop adventitious roots when they encounter favorable conditions or habitats. The flowers have white to pink petals and are either pollinated by insects, or self-pollinated.S. album was used as ornamental, medicinal, and edible plant, and was proven to grow near human settlements [tlements ,59–64. Ttlements ,65. The tlements ,55. In tS. athoum, S. micranthum) that have been described based on leaves (size and shape), flowers , distribution, and habitat conditions.Chromosome numbers of 2n = 2x = 32, 34 and 38, as well as tetraploid individuals with 2n = 4x = 64, 68 have been described –68, whicS. album were sampled in dry grassland  and rock slopes  all over Europe  to 14 (S12) plants per population were sampled .AFLP analysis was conducted with 388 individuals in total following the protocol of Vos et al.  with minClear and well-defined fragments were scored manually in the program BioNumerics v. 3.0 (Applied Maths). The fragments with sizes of 60–420 bp were processed and scored across all individuals as either present or absent. Both individuals and fragment sizes that did not give clear, defined, and reproducible fragments were excluded from the analysis. The resulting binary matrix was used for further statistical analysis.To analyze the quality and reproducibility of the fragments, 55 individuals were replicated, which gave an error rate of 1.36% .Genetic diversity within populations was calculated based on all markers that produced polymorphic fragments, percentage of polymorphic fragments, and Shannon Index (SI = ∑ pi ln pi) for each population , using tRarity of fragments can indicate the level of isolation and differentiation . TherefoAmong population distances were estimated with the program AFLP-SURV  based onThe differentiation within populations, among populations, and among main groups revealed by neighbor-net graphs and Bayesian clustering was calculated in GenAlEx version 5 . Based oBased on pairwise PhiPT values from AMOVA and pairwise geographic population distances (km) we conducted a Mantel-Test  in GenAl5 iterations, with a burn-in-period of 104. For each predefined number of K, 10 iterations were run. From the resulting values of L(K) standard deviations and ΔK were calculated to affirm the most likely number of groups with STRUCTURE harvester [Genetically homogenous groups were inferred with Bayesian clustering in the program STRUCTURE version 2.2 for all individuals (K = 1–35) and two subgroups in separate runs  . Allele arvester ,85. The arvester , and thearvester .The plastid trnL intron and trnL-F spacer sequences were chosen for a preliminary test using primers Tab c and Tab f , because2 (50 mM), 0.08 μl Taq (PeqLab) and 2.12 μl water for molecular biology (Roth). The reactions were performed in a thermal cycler (Eppendorf) with 35 cycles of denaturing at 95°C (30 s), annealing at 52°C (90 s) and extension at 72°C (4 min), followed by a final extension step at 72°C (7 min), and hold at 4°C.Polymerase chain reactions (PCRs) were carried out in 10 μl reaction volumes containing: 3 μl DNA (7.8 ng/μl), 0.4 μl of each primer (10 mM), 1 μl BSA, 1 μl dNTPs (5 mM), 1 μl PCR Buffer (10X), 1 μl MgClThe PCR products were purified using 4 μl of a mixture of Exonuclease , SAP  and water (3.12 μl). Purification was conducted at 37°C (30 min) and concluded with a step at 95°C (5 min).2EDTA  ice-cold EtOH (96%) and washed with EtOH (70%). These products were subjected to capillary gel electrophoresis on an automated sequencer .Cycle sequencing was performed with 3 μl purified product, 0.6 μl Buffer , 0.6 μl primer (10 μM), 1.4 μl DTCS Master Mix (Beckman Coulter) and 4.4 μl water for molecular biology (Roth). The PCR products were precipitated with Glycogen (20 mg/ml), NaAc , NaTwo individuals per population were used for this analysis. All the samples were amplified in both directions (with Tab f and Tab c), but an overlap could not be achieved in any of the samples. To reassure the stability of the sequences, individuals were sequenced twice and consensus sequences were used for further analyses. Populations F5 from France and GB from Great Britain were excluded from further analyses because we failed to produce two appropriate sequences per population.We compared the resulting sequences with those in GenBank using Blast . AlignmeSedum dasyphyllum from Barcelona (BCN) [Concatenated cpDNA sequences were used to build a network under statistical parsimony  in TCS na (BCN) .Maximum parsimony (MP) heuristic searches were conducted in PAUP* 4.0a  with TBRUniversal conserved chloroplast microsatellite primers  were tested in an initial screening of four individuals . Ccmp2, For each individual, 1 μl of the PCR products of each primer was mixed and added to Sample Loading Solution, charged with an internal standard (CEQ Size Standard 400) and run on an automated capillary sequencer . Chloroplast haplotypes were defined by fragment lengths using CEQ 8000 software. A haplotype network was built under statistical parsimony in TCS v1.21 . GeograpAFLP analysis of 385 individuals out of 34 populations resulted in 361 fragments , of which 96.4% were polymorphic. Twenty-four fragments were private in single populations . GeneticIn the neighbor-net graph  the sepaDifferentiation was high between populations in general 72.3%, . We founTo reveal the influence of other regions on central European populations, we tested differentiations of all combinations of the regions against each other . The groWe found significant correlation of genetic and geographic distances with Mantel-Test over the whole dataset  indicating isolation by distance among populations. Isolation by distance was further present in two of the main network groups , but absent between the populations from Western Europe (data not shown).Bayesian analysis distinguished the most probable subdivision in two clusters . Forward strand  was 324 bases long and had 14 mutation sites  indels, two 2-nt indels, two 3-nt indels and one 8-nt indel). Reverse strand  resulted in 426 bases with 16 variable positions . Overall, we detected 19 single-nt polymorphisms and 11 indels resulting in 18 sequence haplotypes , Austria (A1), Czech Republic (CZ), Slovakia (SK) and Germany  shared haplotype H1 ; Table 1S. dayphyllum was manually set as an outgroup [Maximum parsimony analysis yielded 29947 equally parsimonious trees. For a 50% majority rule gene tree outgroup  Fig 6)..S. dayphChloroplast microsatellites revealed six haplotypes , Table 1S. album populations in Europe with AFLPs, chloroplast sequence analysis and chloroplast microsatellites. A clear east/west subdivision in the investigated area, with a south-northward contact zone in western Europe was detected. AFLPs supported the results of chloroplast microsatellites and sequences (single exceptions discussed below), consistent with the findings of other studies for plants and animals [We found high resolution and clear geographic structure in  animals ,98.S. album showed high differentiation and high rarity levels. Both values suggest that populations are more isolated than those from the other regions. The microsatellites revealed distinct haplotypes of populations E4 from northern Spain and PO from Portugal. The divergences of clades from the Iberian Peninsula and western Europe seem to be ancient compared to the clades from central Europe and Italy. The Iberian Peninsula has been suggested as one of the main glacial refugia for Alnus glutinosa [Helianthemum sp. [Rosa pendulina [The Iberian Peninsula populations of lutinosa , Heliantemum sp.  and Rosaendulina . In all S. album in the Pyrenees.Populations AND, E2, and F5 are situated in the Pyrenees. They were clearly assigned to the Iberian Peninsula group and belonged to a distinct cluster in the Bayesian analysis of the western group K = 7, . MoreoveS. album has survived the LGM in lowland central Europe refugia, as suggested for Helianthemum nummularium [S. album inhabits makes survival in northern cryptic refugia possible.Populations from western Europe  are closely related to populations from the Iberian Peninsula . This northward line in western Europe represents the genetic border with populations in central Europe. Based on high genetic diversity within populations, it is possible that mularium . Populatmularium ,6. This mularium ,100,101.Although population BE situated in north-central Europe also had a basic position in the cpDNA analysis , the rarCentral European and Italian populations share one microsatellite haplotype, except for I5 and I6 from Liguria. Additionally, nine populations from Central Europe and Italy shared one sequence haplotype; further haplotypes had a close relation (except for I5 and I6 from Liguria). This group forms one derived cluster in the MP tree. In the AFLP network, populations from Central Europe and Italy could be divided in three subgroups . Owing to poor differentiation, and low rarity and diversity, a young colonization history can be assumed for most populations from Switzerland  and Germany .Population D3 shares one microsatellite type with Serbian populations and is closely related to the sequence haplotype of Serbian populations. It showed high rarity, but low genetic diversity, which would be explained by a single dispersal event inducing a bottleneck and high isolation.S. album in the Czech Republic and Slovakia.High rarity was also found in populations from the Czech Republic (CZ) and Slovakia (SK), along with high diversity and the most ancient cpDNA haplotype (H1) that is distributed widely in Central Europe. All analyses point towards cryptic refugia for S. album along the river valley of the Danube can be assumed.Italian populations, which are situated north and east of the Apennine , showed close genetic relations northward to Germany and eastward to the Czech Republic and Slovakia . TherefoPopulations situated near the Alps  have a strong relation to populations from the middle of the Apennine peninsula. We suggest that at least these parts of the Alps are colonized by lowland southern Italian source populations after the LGM . FurtherAnthyllis montana [S. album.Mountain ranges act as contact zones for different animal and plant species –105. In  montana ,43. Notw montana ,30,106. Anthyllis montana [S. album in the nearby population I6 in Liguria. It has a strong connection to the south-western group in Spain/Portugal, but also has some similarities with the Serbian populations. A strong relation between populations along the Mediterranean coast, from Spain and France to the middle of the Apennine Peninsula, and further eastward to Serbia was detected; this potentially reflects the northern distribution limit of S. album that first expanded west- and eastward after the LGM, before the ice and steppe regions moved further north. Moreover, dispersal along with human migrations are important considerations due to the ethnobotanical use of S. album and the longevity of seeds and shoots. Human migrations, in particular with La Hoguette culture, were documented from south-eastern Europe along the middle of the Apennine Peninsula and the Mediterranean coast [S. album.Population I5 from north-eastern Italy (Liguria) had a strong connection to populations from Serbia. In AFLP analysis, it was also related to the group on the Iberian Peninsula. In  montana , a stron montana . A similan coast ,100, resFour populations  constitute the most ancestral group in the MP tree. High rarity but low genetic diversity in population D3 indicates a singular long-distance dispersal event from a source in south-eastern Europe. Both Serbian populations  show low rarity and differentiation among populations, as revealed by the AFLP analysis. In the AFLP analysis, Central European populations were more related to Serbian populations than to populations from Iberia and Western Europe. It is possible that Serbia was colonized from source populations farther south or east on the Balkan peninsula (e.g. Greece or Bulgaria) after the LGM, and populations migrated to Central Europe. The influence of the eastern lineage on Central Europe is observed in the strong relation to population I5 and the close relation to central and northern populations, as indicated in the AFLP analysis.Besides the clear east/west division, there was an admixture of the main AFLP lineages in populations from Germany (D4), Liguria , Italy (I1), and Serbia . Multiple colonization events would explain the observed pattern in D4 and I1. For the postulated glacial refugia in Liguria and Serbia, the combination of long-term isolation and recent frequent gene flow by pollination would explain the pattern of AFLPs and cpDNA . A clearS. album populations in Europe. S. album survived in glacial refugia on the Iberian and the Apennine Peninsula, and probably in eastern parts of Central Europe—as shown for several other species [A combined analysis of the conserved chloroplast regions and AFLP markers with high resolution made it possible to infer the historical processes of  species ,9,108. WS. album migrated to western and north-western parts of Europe from Spain/Portugal, but grasslands in Central Europe were primarily recolonized by cryptic source populations or source populations coming from the Apennine Peninsula and eastern Central or south-eastern Europe.Recently two studies on dry grassland species demonstrated the colonization of Central Europe from source populations on the Iberian Peninsula after the LGM ,101. In S1 FigMost probable subdivision of the western group was a) K = 3 and b) K = 7.(TIF)Click here for additional data file.S2 FigMost probable subdivision of the eastern group was K = 3.(TIF)Click here for additional data file.S1 TableRaw data of 385 individuals in 34 populations that are used for all further analyses; included are geographic coordinates for each population.(XLSX)Click here for additional data file.S2 TableS. album individuals from 32 populations that were used for all further analyses of chloroplast sequences.Concatenated sequences of (DOCX)Click here for additional data file.


The cost of Whole Genome Sequencing (WGS) has decreased tremendously in recent years due to advances in next-generation sequencing technologies. Nevertheless, the cost of carrying out large-scale cohort studies using WGS is still daunting. Past simulation studies with coverage at ~2x have shown promise for using low coverage WGS in studies focused on variant discovery, association study replications, and population genomics characterization. However, the performance of low coverage WGS in populations with a complex history and no reference panel remains to be determined.South Indian populations are known to have a complex population structure and are an example of a major population group that lacks adequate reference panels. To test the performance of extremely low-coverage WGS (EXL-WGS) in populations with a complex history and to provide a reference resource for South Indian populations, we performed EXL-WGS on 185 South Indian individuals from eight populations to ~1.6x coverage. Using two variant discovery pipelines, SNPTools and GATK, we generated a consensus call set that has ~90% sensitivity for identifying common variants . Imputation further improves the sensitivity of our call set. In addition, we obtained high-coverage for the whole mitochondrial genome to infer the maternal lineage evolutionary history of the Indian samples.Overall, we demonstrate that EXL-WGS with imputation can be a valuable study design for variant discovery with a dramatically lower cost than standard WGS, even in populations with a complex history and without available reference data. In addition, the South Indian EXL-WGS data generated in this study will provide a valuable resource for future Indian genomic studies.The online version of this article (doi:10.1186/s12864-017-3767-6) contains supplementary material, which is available to authorized users. The rapid development of next-generation sequencing technologies has resulted in a fruitful decade of genomic discoveries, many of which are becoming integrated into translational settings and promise to dramatically improve clinical outcomes . DespiteWe aim to continue these developments and hypothesize that a study design of sequencing at population scale  with each subject at 1–2x coverage  would capture sufficient information to understand population genomic attributes such as diversity, population substructure, and admixture. Such a study design would decrease the cost for a population genomics study to tens of thousands of dollars. This design has broad utility for both population genomics studies in various model species  and diseSouth Asian populations are an example of major populations that lack adequate reference panels. South Asian populations on the Indian subcontinent are known to have a complex demographic history with multiple socio-linguistic groups , 15. TheAs a proof-of-principle, we present the results from extremely low coverage whole genome sequencing (EXL-WGS) of eight South Asian populations from a wide spectrum of social and cultural strata living in the state of Andhra Pradesh. The population samples belong to four broad self-identified classifications: lower caste, middle caste, upper caste and tribe. Using EXL-WGS of 185 samples with coverages between 1x and 2x, we demonstrate that the EXL-WGS study design generates accurate genomic variant information and reliably recapitulates population substructure generated by previous methods. Moreover, sequencing approaches provide an advantage for population studies compared to genotyping array platforms, which are known to have substantial ascertainment bias , 22. FurWe sequenced 185 samples from the state of Andhra Pradesh to an average read depth of coverage of 1.6x (ranging from 0.84x to 3.39x)  is set at 2.8, SNPTools [s = 2.8 as determined in the simulation study  , for varThe final call set included 4,457,475 autosomal biallelic SNVs with a transition/transversion ratio of 2.09. Of these, 97,309 2.18%) are novel with respect to the South Asian dataset in the 1000 Genomes Project Phase 3 (1000GP3-SAS), and ~5700 SNVs are absent in dbSNP build 141. The vast majority of the SNV sites have an average coverage between 0.5x and 4x, close to our average sequencing depth of 1.6x  genotyping array genotype calls and Sanger sequencing results from previous studies , 26. ForNext we assessed if the EXL-WGS provides sufficient information for examining population structure in SAS-AP samples. First, simulation experiments were carried out by thinning the reads from the 1000 Genomes dataset to test the feasibility of performing principal component analysis (PCA) on common SNVs in an EXL-WGS cohort , East Asian (1000GP3-EAS) and South Asian (1000GP3-SAS) samples showed that our samples are most closely related to the 1000GP3-SAS samples, as expected . This value is higher than those of other populations sampled across the Indian subcontinent . PCA th from low-coverage sequencing for population genetics analyses, without genotype calling –7. For sST estimates between populations in SAS-AP and 1000GP3-SAS is maximum for tribal populations at approximately 0.02.The EXL-WGS study design can be a highly effective and affordable strategy to generate population-specific imputation reference panels, which can improve imputation accuracy in association studies that use SNP arrays as primary data sources. Using a simulation dataset, we showed EXL-WGS imputation reference panel has a comparable performance to the SNP array reference panel within the same population  value than the 1000GP3 panel for all population classifications  in the tribal population and least apparent for the lower caste (0.902 vas 0.892). All the missing SNVs were recovered using both the reference panels. Given the high genetic diversity in the Indian subcontinent, and the unique ancestry profiles of populations, using a custom reference panel will be better than using any of the existing populations, even for SNVs in the MAF range ≥ 10%.For the imputation experiment, approximately one-third of the samples from each of the main caste and tribal classifications from SAS-AP were chosen as a target set for imputation. The remaining samples from SAS-AP were used as a representative EXL-WGS population-specific reference panel, and 160 randomly selected 1000GP3-SAS samples were used as the generic reference panel. Approximately 5% of sites were removed from the target set see  and the ons Fig. . The R2 To determine if the better performance of the SAS-AP reference panel is due to the batch effect between the 1000 Genomes and the SAS-AP samples, or due to population composition, we further evaluated the performance of the reference panels for imputing the 1000 Genomes ITU samples as the target  and four single C base addition in KD7. All four additions in KD7 are within homopolymeric C regions. These differences are likely attributable to the well-known difficulties in sequencing homopolymeric regions on the Ion Torrent platform. Additionally, no differences were found between the EXL-WGS data and lineage-defining SNVs genotyped previously in a subset of the 185 samples using single-base extension genotyping [Next, we determined the mtDNA haplogroup distribution among SAS-AP samples using mitochondrial whole-genome sequences. Samples were grouped into populations based on their caste or tribe affiliation, and the proportion of each major mtDNA lineage was calculated for each population Fig. . MitochoIn the past, SNP genotyping arrays have been used to survey genomic diversity in previously unexplored populations , 26, 32.SNP genotyping arrays are usually designed using existing genetic information. Therefore, for populations that have not been studied extensively and do not have a good reference population, the SNP array is likely to miss population-specific variants and bias population structure analysis , 22. An ADMIXTURE analysis suggests South Asian samples can be predominantly divided into two clines, one aligned with populations having west Eurasian ancestry and one aligned with populations having East Asian ancestry. In our analysis, all castes are closer to the Eurasians than to the East Asians along these clines. The position of caste populations along the west Eurasian cline is consistent with previous results on higher ANI component in higher ranks [Here we demonstrate the benefit of EXL-WGS over SNP genotyping arrays by studying populations from South Asia. The Indian subcontinent has witnessed multiple waves of migration since the first migration of modern humans out of Africa –37, whicer ranks . The Khoer ranks . The IruST analyses are largely congruent between the two sets of analyses  and generated high-quality mitochondrial haplotypes for every SAS-AP sample. Using the haplotypes we were able to examine the material lineage diversity among the samples. Among tribal samples, all Irula people have the deep-rooted ancestral mitochondrial haplogroup M that is typical of South Asia. Thirteen percent of the Khonda Dora samples have the mitochondrial haplogroup U. Although haplogroup U is shared with western European populations, it has some deep  India-specific branches . The mitIn our project the average yield of SNVs per individual is approximately 2.5 million for MAF ≥ 10%, and a SNP genotyping array of comparable yield will cost ~ $170/sample. The cost of sequencing one gigabase has been estimated to be less than $30 on a HiSeq 2500 . AccountFor coverages less than 2x, there is a valid concern about genotyping accuracy, especially for heterozygotes. In a recent case-control study involving more than 10,000 samples with an average depth of coverage ~1.7 x, mean genotype concordance was better than 98% with respect to deep WGS gold standard datasets and SNP arrays . Indeed,The advances in sequencing technologies are making EXL-WGS a more cost-effective and advantageous strategy than SNP genotyping arrays for studying new populations. EXL-WGS allows for the discovery of population-specific variants that are not present on a SNP array, provides a population-specific reference panel for imputation, and generate a high-quality mitochondrial genome for each sample.A total of 235 samples were collected from the state of Andhra Pradesh in India. All samples belong to the Dravidian language family and were collected as unrelated individuals as described previously , 49. AllWhole genome sequencing using DNA samples from the blood was performed at the Human Genome Sequencing Center, Baylor College of Medicine using Illumina HiSeq following a standard protocol . The rawThe parameter fitting of the SNPtools pipeline was done on a simulated cohort generated using Protocol 1 from 208 AFR samples from the 1000 Genomes Phase 1 data  with covVariant discovery by the Genome Analysis Tool Kit GATK, v2.4-9) pipeline roughly followed the best practice recommendation for alignment processing and variant calling . Startin.4-9 pipeAmong the 235 samples, 50 exhibited a high number of SNVs. The dataset was tested for the confounding variables of sequencing depth and batch effect, and all 50 samples were in the batches sequenced on days 29-31 and days 41–43. These 50 samples were removed from further analysis, and SNVs were recalled using the SNPTools for a new consensus call set. The filtered dataset with 185 samples is presented in Table SNPTools and GATK call sets: SNVs with MAF <10% were filtered out from both call sets. A consensus site list was generated for sites that are present in both call sets, and the phased SNPtools calls for the consensus sites were used for further analysis and annotation.ST analysis, samples from the 1000 Genomes Phase 3 dataset were merged with SAS-AP samples. Twenty samples were randomly chosen from each population from the 1000GP3 dataset except the SAS populations, for a total of 140, 80, 100 and 100 samples in 1000GP3-AFR, 1000GP3-AMR, 1000GP3-EAS and 1000GP3-EUR groups, respectively. All 489 samples in the 1000GP3-SAS dataset were used for the population genetic analyses. CombineVariants in GATK  was useST between populations.The smartpca module of EIGENSTRAT (version 5.0.1)  was usedADMIXTURE (version 1.02) [2 > 0.2 within 50 SNV windows using PLINK [ADMIXTURE. Multiple ADMIXTURE runs were performed to cover the number of ancestral populations (K) values from 4 to 7.Genome-wide admixture estimates were obtained using a model-based algorithm implemented in on 1.02) . To elimng PLINK  as recomth site from this intersection was then removed from the consensus set, thereby deleting approximately 5% of the common sites from the target dataset for imputation. This strategy of removing SNVs ensures a genome-wide assessment of imputation accuracy where there is enough haplotype structure information remaining in the target dataset to effectively impute the missing SNVs. Beagle (ver 3.09) [For this experiment, 6, 23, 20 and 12 samples were randomly chosen from 16 upper caste, 69 middle caste, 62 lower caste, and 38 tribal samples, respectively. This leaves 179, 162, 165 and 173 samples remaining in the SAS-AP dataset as the reference panel for imputation experiment of upper caste, middle caste, lower caste, and tribal populations, respectively. One hundred and sixty 1000GP3-SAS samples were chosen randomly from the 489 1000GP3-SAS samples and SNVs with MAF <10% were filtered out to generate a generic reference panel. The target missing SNVs were selected using a 2-stage process. First a site level intersection of all three datasets used in an imputation experiment  was produced. Every 20er 3.09)  was usedAdditional file 1: Table S1.Sequencing and variant calling statistics for 185 SAS-AP samples. (XLS 50 kb)Additional file 2:Supplementary Information. (PDF 1370 kb)


Taxidea taxus), as a proxy for evaluating their evolutionary potential across the northern extent of the species’ range. We compared genetic structure of 20 microsatellites and the major histocompatibility complex (MHC DRB exon 2) to evaluate whether small, isolated populations show low adaptive polymorphism relative to large and well‐connected populations. Our results suggest that gene flow plays a prominent role in shaping MHC polymorphism across large spatial scales, while the interplay between gene flow and selection was stronger towards the northern peripheries. The similarity of MHC alleles within subspecies relative to their neutral genetic differentiation suggests that adaptive divergence among subspecies can be maintained despite ongoing gene flow along subspecies boundaries. Neutral genetic diversity was low in small relative to large populations, but MHC diversity within individuals was high in small populations. Despite reduced neutral genetic variation, small and isolated populations harbour functional variation that likely contribute to the species evolutionary potential at the northern range. Our findings suggest that conservation approaches should focus on managing adaptive variation across the species range rather than protecting subspecies per se.Small and isolated populations often exhibit low genetic diversity due to drift and inbreeding, but may simultaneously harbour adaptive variation. We investigate spatial distributions of immunogenetic variation in American badger subspecies ( American badgers are divided into four subspecies based on differences in skull size, pelage colour and geographical distribution , which are separated by mountain ranges , Saskatchewan (SK) and Manitoba (MB). These populations are connected to T. t. taxus in the Great Plains of the United States and the Upper Peninsula (UP) of Michigan. Finally, a small, endangered, isolated population of T. t. jacksoni persists in southern Ontario  of Michigan. The most peripheral western and eastern populations (TO and ON) are also the most genetically differentiated  and neutral genetic (20 microsatellites) variations to account for the effects of gene flow and genetic drift. Specifically, we sought to determine whether small, isolated badger populations show lower levels of MHC diversity relative to large and well‐connected nonperipheral populations, resulting from high rates of genetic drift or whether these isolated peripheral populations act as repositories of local immunogenetic adaptation. We also sought to determine whether functional immunogenetic markers reflect current subspecies and conservation designations for 22.1n = 236) from hair snares, harvested pelts, incidental deaths and radio‐tagged badgers. Samples in Canada and the north‐western USA included T. t. jeffersonii from BC ; T. t. taxus from AB (n = 39), SK (n = 25), MB (n = 48) and UP (n = 22); T. t. jacksoni in LP (n = 23) and ON (n = 19)  Fig.  and Ethi19) Fig. .We genotyped samples at 20 loci  to synonymous (dS) substitutions, where ω = dN/dS >1 indicates the effect of positive selection. We calculated the ratio of dN and dS per site, using the modified Nei–Gojobori method with the Jukes–Cantor correction for multiple substitutions in MEGA v6.6 . We checked for signatures of recombination using the genetic algorithm recombination detection method using the Datamonkey website.We tested for signatures of historical positive selection in MHC using the one‐tailed 2.3.2k) for each population in ARLEQUIN v3.11 . We tested for significant differences in MHC individual diversity among populations using a type II ANOVA followed by pairwise comparisons . We tested the correlation between microsatellite allelic richness and MHC individual diversity using Pearson product moment correlations in R  and expected heterozygosity (He) using GENALEX v.6.5  in FSTAT v.2.9.3.2  and private allelic richness (Par) adjusted for unequal sample sizes by rarefaction in HP‐RARE v.1.0  between small, peripheral populations (TO and ON) and nonperipheral populations using 1,000 permutations in FSTAT v.2.9.3.2  and linkage disequilibrium (LD) for each sampling location were examined using probability test in GENEPOP v.4.2 Rousset, . For eac Goudet,  and alle Goudet, . We esti2.5FST distances between all sampling regions pairs were calculated using the Jukes–Cantor distance model in ARLEQUIN by entering the nucleotide MHC sequences and the number of individuals per sequence and population as haplotype data. For microsatellites, FST was calculated using the number of different alleles. Statistical significance (p < .05) of FST values was estimated by 1,000 randomizations. We used partial Mantel correlations to test the effect of isolation by geographical distance (IBD) on MHC genetic distances, while controlling for the genetic differentiation at neutral loci. Significance of Mantel correlation coefficients was tested by permuting observations 1,000 times using the R library vegan , with 10 iterations at each value of k. We compared models with and without the LOCPRIOR function, which includes the sampling regions of origin in the analysis. The most likely number of k‐clusters was chosen by compiling runs using STRUCTURE HARVESTER v.0692    per individual. Using 27 duplicate samples, the degree of change sequencing modelling provided complete allele repeatability in 22 individuals (81.5%), which is a similar rate reported in other studies , followed by T. t. jacksoni (Ad = .62). Differences in values of MHC individual diversity among populations were statistically significant , and pairwise post hoc comparisons showed that significant differences were between TO versus AB, and TO versus MB (p < .05).We identified 26 MHC alleles from the eight sampled regions (GenBank KU059084–KU059109). Overall polymorphism showed 23 segregating sites with average Jukes–Cantor pairwise differences of 6.4% (SD = 1.4%). Individuals had one to four MHC alleles . One MHC allele (H16) predominated in all sampled regions, but the presence and frequency of the other 24 alleles varied clearly among subspecies and regions. Four MHC alleles  were detected only in k = 3 as the most likely scenario, with the clusters corresponding roughly to subspecies designations. One cluster included T. t. jeffersonii from TO; the second included T. t. taxus from AB, SK, and MB; and the third included T. t. jacksoni from LP and ON. Samples from EK and UP showed admixture between their geographically adjacent clusters . The genetic algorithm recombination detection method found no significant evidence (p > .05) of recombination in the 22 potential breakpoints explored. Table All observed MHC alleles differed by at least one amino acid (Table S2) and were presumed functional based on lack of stop codons, an absence of frame‐shift mutations, or extremely high amino acid sequence identity (90%–96%) with functional mammalian DRB alleles (GenBank). The one‐tailed 3.3Ar was statistically different (p < .05) between small, isolated populations relative to nonperipheral badgers. Taxidea t. taxus badgers showed lower inbreeding coefficients and larger estimates of effective population sizes relative to TO and ON populations (Table p = .03). We found no significant correlation between private microsatellite allelic richness and the number of private MHC alleles .We found <2% genotyping error rate, largely corresponding to ON samples that had low DNA template amounts from hairs . We detected significant departures from HWE for eight microsatellite loci , but with no consistent patterns across sampling regions. Most deviations from HWE were observed for TO and none in SK. Significant LD was detected for one pair of loci at two sampling regions (EK and AB: Tt15 × Tt27), but the overall data set did not show any significant LD. We retained all 20 microsatellites for subsequent analyses, as significant deviations of HWE and LD were not consistent across regions. Nineteen microsatellite loci were polymorphic in all sampling regions. The only exception was Tt‐1, which was monomorphic in ON badgers. Badgers from AB, SK and MB showed the highest values of genetic diversity  were assigned strongly to a second cluster containing the T. t. taxus samples. A third cluster included the ON samples (T. t. jacksoni), with UP (T. t. jacksoni) and LP (T. t. taxus) badgers showing high genetic admixture between their adjacent clusters  than microsatellites . AMOVA based on the three subspecies showed a similar trend, but explained a lower proportion of the genetic variance compared to the grouping by sampling region .AMOVAs showed that the proportion of genetic variance partitioned among sampling regions was higher for MHC , but the strength of this correlation varied among regions . The CoA plot shows the joint trend of the covariance between the MHC and microsatellites for each region . Mantel test showed a positive significant correlation of geographical and genetic distances for MHC  and microsatellites . Controlling for the effect of neutral genetic differentiation on MHC against geographical distances in the partial Mantel test did not change observed trends . MHC and microsatellite genetic distances were significantly correlated .Pairwise 4Our results show the importance of neutral processes in shaping the distribution of MHC polymorphism across the northern range of the American badger and highlight the stronger interactions between gene flow, genetic drift and selection towards the western and eastern peripheries of the badger range. The strong similarity of MHC alleles within designated subspecies relative to their neutral genetic differentiation indicates adaptive divergence among subspecies. This suggests that subspecies can be considered ecomorphs, which respond to different selective pressures across their range through local adaptation. These results can better inform conservation management of endangered badger populations, by shifting the focus of conservation efforts towards the conservation of adaptive genetic diversity across the species range.4.1Canis lupus, Niskanen et al., Microtus montanus, Winternitz & Wares, Meles meles, Sin, Dugdale, Newman, Macdonald, & Burke, Gulo gulo, Rico et al., Mustela lutreola, Becker, Nieberg, Jahreis, & Peters, Enhydra lutris, Aguilar, Jessup, Estes, & Garza, Procyon lotor, Kyle et al., Ursus arctos, Kuduk et al., Major histocompatibility complex DRB exon 2 diversity in the American badger was moderate relative to other species. Badger MHC diversity  was similar to the Finnish wolf  between TO and EK, and the Flathead Montana and north‐west Washington is also expected to limit population connectivity COSEWIC, . In the ion Fig. , and samT. t. jeffersonii and T. t. jacksoni populations compared to the larger correlation for the Prairie badgers . This result indicates a larger discrepancy in the degree of joint genetic structure between MHC and neutral loci towards the peripheries, suggesting ecological adaptation.The similarity of MHC alleles between populations within subspecies, despite their geographical isolation towards the range margins, might reflect high effective migration rates of beneficial MHC alleles , mice (Peromyscus sp.), woodchucks (Marmota monax) and eastern cottontail (Sylvilagus floridanus) , ground squirrels (Spermophilus sp.) and marmots . Our data support these divisions and can greatly inform conservation efforts. For example, if only microsatellite data is used, the designation of TO and ON as distinctive conservation units would be supported, but the indication of substantial gene flow between EK and T. t. taxus populations would not warrant their designation as different units. On the other hand, the MHC genetic differentiation of EK from T. t. taxus and its higher MHC similarity with TO likely suggest that EK badgers are under similar selective pressures to the badgers in TO. Therefore, translocating EK and T. t. taxus badgers into each other's environments might increase the probability of outbreeding depression resulting from the reproduction between adaptively diverged populations  or require a more direct approach to mitigation (i.e. human persecution). For example, badgers are poisoned either secondarily, due to consumption of prey that have consumed rodenticides, or directly in cases where landowners do not want badgers on their property (COSEWIC, Badgers face many threats across their range as habitat is becoming increasingly fragmented by land‐use changes. Areas of high urbanization and road density are expected to drastically limit badger movements and increase incidental deaths by road crossing COSEWIC, . At the COSEWIC, . DiseaseCOSEWIC, , with paHabitat loss and climate change are expected to promote the expansion of pathogens and their vectors and thus increase the incidence of diseases affecting wildlife in northern regions (Brooks & Hoberg, 10.5061/dryad.qb87r. MHC sequences can be accessed on GenBank KU059084‐KU059109.Microsatellite genotypes at 20 loci and binary‐encoded data of MHC DRB exon 2 for 236 samples of American badgers are available on Dryad: doi: Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.