Miscanthus has great potential as a biofuel feedstock because of its high biomass, good burning quality, environmental tolerance, and good adaptability to marginal land. In this study, the genetic diversity and the relationship of 24 different natural Miscanthus sinensis populations collected from Southwestern China were analyzed by using 33 pairs of Sequence Related Amplified Polymorphism (SRAP) primers. A total of 688 bands were detected with 646 polymorphic bands, an average of 19.58 polymorphic bands per primer pair. The average percentage of polymorphic loci (P), gene diversity (H), and Shannon’s diversity index (I) among the 24 populations are 70.59%, 0.2589, and 0.3836, respectively. The mean value of total gene diversity (TH) was 0.3373 ± 0.0221, while the allelic diversity within populations (SH) was 0.2589 ± 0.0136 and the allelic diversity among populations (STD) was 0.0784. The mean genetic differentiation coefficient (Gst = 0.2326) estimated from the detected 688 loci indicated that there was 76.74% genetic differentiation within the populations, which is consistent with the results from Analysis of Molecular Variance (AMOVA) analysis. Based upon population structure and phylogenetic analysis, five groups were formed and a special population with mixed ancestry was inferred indicating that human-mediated dispersal may have had a significant effect on population structure of M. sinensis. Evaluating the genetic structure and genetic diversity at morphological and molecular levels of the wild M. sinensis in Southwest China is critical to further utilize the wild M. sinensis germplasm in the breeding program. The results in this study will facilitate the biofuel feedstock breeding program and germplasm conservation.The genus  Miscanthus is comprised of C4 perennial rhizomatous grasses, originated from Eastern Asia. Owing to high biomass productivity [Miscanthus have attracted considerable attention as one of the most promising non-food bioenergy crops. There are about 10-15 Miscanthus species distributed worldwide, of which seven are native to China [M. × giganteus, has been intensively studied in Europe as a biomass feedstock [M. × giganteus is propagated by plant rhizomes or tissue culture and does not produce fertile flowers or seeds, and its production is heavily limited by its natural sterility and a narrow genetic base [M. × giganteus, M. sinensis is propagated by seeds which is a favorable trait for crop adoption and provides a comparable yield in some places and could be a valuable genetic resource for biofuel crop domestication and improvement [M. sinensis in Europe, a much broader range of adaptation than M. × giganteus was found in this diploid species [M. sinensis it is considered possible to breed varieties with similar or better yield but higher tolerance for frost and drought than M. × giganteus. Besides, it can be used in crosses to create new cultivars of M. × giganteus.The genus uctivity , low-nutuctivity ,3, and hto China ,7,8. Sineedstock ,10. Howetic base . As a prrovement ,12. Base species . So withCarthamus tinctorius, Cucurbita pepo, buchloe dactyloides, and Solanum lycopersicon [Gossypium hirsutum and Triticum aestivum [Molecular markers are essential tools for germplasm evaluation, genetic analysis, and marker-assisted breeding for crop improvement. Employing molecular markers, such as Sequence Related Amplified Polymorphism (SRAP), Amplified Fragment Length Polymorphism (AFLP), Inter-Simple Sequence Repeats (ISSR) and Simple Sequence Repeats (SSR) ,17,18,19persicon ,22,23,24aestivum ,26.Miscanthus were published showing the abundant resources distributed in China [et al. and Clark et al. revealed the population structure of M. sinensis native to China using SSR and SNP makers respectively. Xu et al. used 20 pairs of EST-SSR makers of sorghum to analyze 26 populations of M. sinensis from Southwest China, indicating a high genetic diversity and the existence of a gene flow in M. sinensis populations in this area. However, the SSR markers used in that study were mainly derived from the non-coding regions, which may not be able to provide sufficient evidence to reveal the diversity and differentiation of M. sinensis in Southwest China; therefore, SRAP markers, derived from the coding region, were used in this study. Southwest China, as one of the 34 biodiversity hot spots around the World, has abundant wildlife resources [M. sinensis germplasm, which is widely distributed in Southwest China and to eventually utilize this valuable germplasm for crop improvement. However, there are no thorough studies on the genetic diversity and population structure of the germplasm distributed in Southwest China. Therefore, in this study, we evaluated the genetic diversity and population structure of 24 M. sinensis natural populations collected in Southwest China using SRAP markers to facilitate the conservation of the Miscanthus germplasm and breeding in the near future.In recent years, many reports on in China ,27,28,29esources . It is cM. sinensis, which have significant differences among the morphological characterization and geographic location, were selected to screen 100 pairs of SRAP primers. In total, 33 of them generated robust discernible bands , Nei’s  gene divT) was 0.3373 ± 0.0221, while the gene diversity within populations (HS) was 0.2589 ± 0.0136 and the gene diversity among populations (DST) were 0.0784. The mean genetic differentiation coefficient (GST = 0.2326) estimated from the 688 bands indicated that there were 76.74% genetic variation within populations. These results demonstrated that the accessions had a higher level of genetic variation within populations than among them. The AMOVA analysis (M. sinensis wild populations showed similar results that both the genetic variations within (86.0%) and among (14.0) populations were significant. In addition, there was a high frequency of gene flow (Nm = 1.6493) between populations, indicating there were more than one effective immigrants from one population into another at each generation.The total gene diversity  and introgression among populations, so it is reasonable that the genetic variation within populations is greater than that among populations [in China ,32. Knowlization . In this markers ,12,18. M markers ,36,37,38R makers . The genR makers . In planulations ,42.The population structure of the 260 individuals was estimated under the Hardy-Weinberg Equilibrium by using STRUCTURE V2.3.3 software. Based on maximum likelihood and delta K (∆K) values, the number of optimum subgroups was five . By usinThe genetic similarities (GS) of 260 individuals ranged from 0.565 to 0.972 with an average of 0.659 which showed a high level of genetic variation range among the accessions. The Un-weighted Pair-group Method with Arithmetic mean (UPGMA) dendrogram based on GS data obviously revealed that when at the genetic similarity coefficient value of 0.659, five major clusters were formed and group 1 accessions were mainly collected from the Yuxi area of Yunnan. The genotypes of group 2 were primarily collected from Zigong and Jian’ge in Sichuan. Group 3 contained mostly accessions from Jiangyou and Guangyuan. Group 4 accessions were mainly collected from Yaan, Daying, Banan and Zunyi . The resM. sinensis in Southwestern China.The genetic distances (GD) among the 24 populations were estimated by Nei’s  unbiasedM. sinensis plants were found within a range of 5 km around it. Therefore, a habitat fragmentation was formed as influenced by founder effect.Apparently, Pop12 and Pop24 were differentiated from the other populations in both Structure and UPGMA analysis. The main reason could be the distinct geographic isolation between this two and the rest populations. In addition, Pop12 has the lowest genetic diversity parameters which are P (21.22%), H (0.0787), and I (0.1162), and a low gene flow exists between Pop12 and other populations. Furthermore, Pop12 has a narrow distribution range in this area and almost no other Through the structure analysis, 14 out of 260 individuals with mixed ancestry were all from Pop16. In principle, all of the genetic material of the sampled individuals comes from one or more of K unobserved populations with each population characterized by a set of allele frequencies at each locus. When individuals have mixed ancestry, this means that each genotyped allele comes from one or more populations. We synthesized geographic information to analysis the accessions from Pop16 and found that they all collected along with the G42 highway in China which is the only entrance to the Dead Sea of China located in Da Ying County. The Dead Sea of China is a famous scenic spot where the total number of tourists is approximately 3 million per year. The huge traffic flow and the complex environment could help the seed spread widely. Hence a high gene flow occurred in this area and the plants there had a mixed ancestry. Although some researchers think these man-made factors contribute to the long term survival of populations, this is controversial , as seveM. sinensis from southwest China assessed using SSR makers [M. sinensis accessions. In total, as widely used PCR-based markers, SRAP has advantages over SSR markers, since no prior knowledge of target sequences is required which make it to be widely utilized.The previous clustering result of R makers  was diffR makers ,50. SSRsR makers . In diffR makers . AlthougR makers  were mucM. sinensis collected from 24 natural populations in Sichuan, Chongqing, Guizhou, and Yunnan provinces in 2010  according to the manufacturer’s protocol. The quality and concentration of the DNA were determined by comparing the sample with known standards of lambda DNA on 0.8% (w/v) agarose gels. The isolated genomic DNA was diluted to 20 ng/μL and stored at −20 °C for PCR amplification.Fresh young leaves from each sampled individual were collected and dried by desiccant (silicagel self indicator). Genomic DNA was extracted from the dried leaves using the Plant Genomic DNA kit , 0.8 μL primers (10 pmol/μL), 0.4 μL Golden DNA Polymerase  and 5 μL of ddH2O. Amplification was performed on a Peltier Thermal Cycler  under the following conditions: 5 min at 94 °C, followed by 5 cycles at 94 °C for 1 min, 35 °C for 1 min, and 72 °C for 1 min, and then 35 cycles at 94 °C for 1 min, 50 °C for 1 min, and 72 °C for 1 min, extended at 72 °C for 10 min, then stored at 4 °C. The SRAP fragments were separated on 6% denatured polyacrylamide gels  and electrophoresis, later the gel were stained by AgNO3 solution and photographed by the Gel Doc XR system (Bio-Rad).SRAP primer sequences (Li and Qurios)  used in T) which was divided into gene diversity within populations (HS) and the gene diversity among populations (DST). These parameters were related according to the equation HT = HS + DST. The genetic differentiation coefficient (GST) was calculated as a ratio of DST/HT, which was used to measure the population differentiation. The genetic distance (GD) among 24 populations were also computed using the same program [ST)/GST to estimate the level of gene drift among the populations [M. sinensis individuals was performed using STRUCTRE v2.3.4 software [M. sinensis populations were estimated using the Unweighted Pair-group Method with Arithmetic mean (UPGMA) cluster analysis based on the GD matrix. Analysis of molecular variance (AMOVA) was used to calculate variation among and within population using GenAlEx ver.6.41 [For the statistical analysis, the SRAP banding patterns which could be unambiguously scored across all the sampled populations were recorded manually for band presence (1) or absence (0), each of them was treated as an independent character regardless of its intensity. The discriminatory power of different SRAP primers was evaluated by means of polymorphic information content (PIC) . The res program . Gene flulations . Populatsoftware  with thesoftware ,57. For software . Geneticver.6.41 .M. sinensis is a cross-pollination plant, having complex genetic background and high heterozygosities. Hence, the genetic diversity and population structure analysis in the work reported here will facilitate genetic improvement and cultivar development with desired traits in further M. sinensis breeding programs.SRAP markers were proved as useful tools in genetic diversity detection and population structure analysis. The 33 SRAP markers generated 688 bands with 646 as polymorphic bands. The average percentage of polymorphic bands (P), gene diversity (H), and Shannon’s diversity index (I) are 93.90%, 0.3377 and 0.5032 at species level respectively, indicating high level of genetic diversity. The mean genetic differentiation coefficient (Gst = 0.2326) estimated from 688 bands indicated that the larger genetic variation was found within populations which is consistent with the results calculated by the AMOVA analysis. In addition, there was a high frequency of gene flow (Nm = 1.6493) between populations, indicating there were more than one effective immigrant from one population into another at each generation. The population structure and phylogenetic analysis revealed five groups. Southwest China is located in one of the biodiversity hotspots of the world and the climate is variable. Additionally,


The medieval history of several populations often suffers from scarcity of contemporary records resulting in contradictory and sometimes biased interpretations by historians. This is the situation with the population of the island of Crete, which remained relatively undisturbed until the Middle Ages when multiple wars, invasions, and occupations by foreigners took place. Historians have considered the effects of the occupation of Crete by the Arabs (in the 9th and 10th centuries C.E.) and the Venetians (in the 13th to the 17th centuries C.E.) to the local population. To obtain insights on such effects from a genetic perspective, we studied representative samples from 17 Cretan districts using the Illumina 1 million or 2.5 million arrays and compared the Cretans to the populations of origin of the medieval conquerors and settlers. Highlights of our findings include (1) small genetic contributions from the Arab occupation to the extant Cretan population, (2) low genetic contribution of the Venetians to the extant Cretan population, and (3) evidence of a genetic relationship among the Cretans and Central, Northern, and Eastern Europeans, which could be explained by the settlement in the island of northern origin tribes during the medieval period. Our results show how the interaction between genetics and the historical record can help shed light on the historical record. Ancient written sources are typically concise and noncontemporary, hence theories and interpretations of historians are sometimes based on extrapolations or on a (perhaps subjective) synthesis of inadequate information. Population genetics analysis can complement historical approaches by detecting and quantifying changes in population structure as a result of migrations and population admixture, but, to the best of our knowledge, no Cretan genetic analyses based on whole‐genome autosomal markers have appeared in prior work. A number of studies have been conducted using Y DNA  who had paternal and maternal grandparents originating from villages located in the same district of Crete. With this approach, we reconstructed the rural population of Crete at the time of birth of the grandparents of the participants . According to the 1881 census, the Greek population of Crete consisted of 205,000 individuals , the 1000 Genomes Project (http://www.1000genomes.org), and other sources.To explore relationships beyond the regions of the Cretan populations, we analyzed samples from published datasets from populations from around the world Figure . Samples2.3To merge datasets from the different sources described in Table 2.4Despite the fact that the missing genotype rates in any of the datasets that we analyzed in our work were quite low (invariably below 1%), we chose to perform an additional quality control check and remove any SNP that had a missing rate exceeding 20% in any of the populations under study when merging datasets. Our objective was to remove SNPs that might cause spurious artifacts in our analyses simply because they had many missing genotypes in one of the studied populations.2.5We used Eigenstrat  ranged between two and eight in all our analyses. Prior to running ADMIXTURE, we pruned the SNPs to remove SNPs in high linkage disequilibrium (LD). Toward that end, we used the PLINK software and pruned SNPs using a windowed approach and a value of r2 equal to 0.8. We used DISTRUCT v.1.1 and CLUMPP v.1.1.2 to visualize the output of ADMIXTURE , with 619,756 SNPs in common prior to processing. The second dataset included 1,882 samples with 275,180 SNPs in common. A map of the origins of the samples in this second dataset is shown in Figure http://faculty.washington.edu/browning/conform-gt.html) prior to running Beagle. 566 and 590 markers, respectively, were excluded because of an inability to confirm the strand orientation. Of the remaining markers, any with minor allele frequency less than 1%, Hardy–Weinberg P‐values less than 10−6, or containing more than 2% missing data were excluded. Thus 560,891 SNPs were included for the dataset with 759 individuals, and 257,945 SNPs were included for the dataset with 1,882 individuals.Allele strand, reference, and alternate alleles were aligned with the 1000 Genomes European populations , using the conform‐gt Beagle Utility  was used to generate plots and summarize IBD distributions. The heat maps summarize average pairwise IBD between chromosomes from different individuals in the populations being compared. Specifically, we calculated the sum of the lengths of IBD segments shared between a pair of individuals in the two populations (or within a population), then divided by the number of unique pairs of individuals in the two populations (or within a population) and by four times the genome length (for the four ways to pair chromosomes between two people). We excluded pairs of individuals with more than 40% IBD sharing. This threshold excludes half siblings, full siblings, and avuncular pairs.R Core Team  and in the IBD sharing heat‐plot of Figure Another feature of the Cretan genetic diversity is an east‐to‐west gradient in gene frequencies shown in the PCA plot of Figure The east‐to‐west gradient could represent ancient population settlement patterns. It is known that the Minoan settlements concentrated in central and eastern Crete  shared between individuals in two populations Tables  and S4. Within Europe, Crete is most closely related to Central and Eastern Europe Figure  and S4. In contrast to the IBD data, PCA comparisons of Crete with the European populations distinguish the Cretans from Central, Northern, and Eastern Europeans Figures . PCA ploThe differences in the results of PCA and IBD analysis probably reflect differences in time frames. The genome‐average coalescent time for pairs of samples determines the locations of samples in PCA space McVean, . Coaleschttp://groups.csail.mit.edu/cb/alder), a method that uses the decay of admixture LD to estimate the time of a single pulse of admixture and quantify its proportion, using the Cretan population as the mixed population and varying the source population. In Table To determine the time frame when the IBD relationships between Crete and Eastern and Central Europe were developed, we applied ALDER ._ Overall, the PCA and ADMIXTURE analyses did not provide evidence that the Arab occupation of Crete resulted in the levels of admixture that would have been recognized by our techniques.PCA Figures  clearly 3.2.2The 134 years of the Arab rule ended when the army of the Byzantine general Nicephorus Phokas conquered Crete after a year‐long hard‐fought campaign . We attempted to provide such insights regarding the effects of various historical events on the genetics of the population of Crete.Historians have attempted to analyze the population effects of the Arab occupation of Crete on the basis of a relatively inadequate written record. Except for the campaign of the Byzantine general Nicephorus Phocas to Crete (which has been recorded in detail), little written record exists on the 134 years of Arab occupation. It has been suggested that the Arab occupation had a dramatic effect on the composition of the Cretan population Sefakas, . During A similar controversy exists on the impact of the 435 years of the Venetian rule. The Venetians were accomplished bureaucrats and left a good record of their administration of the colony. According to those sources, approximately 2,000 feudalists initially colonized Crete in the 13th century. However, many other Venetian and Italian merchants, soldiers, and artisans settled in the urban centers McKee,  later. EOur genetic analysis provides further evidence to address such historical controversies. Our statistical analyses included PCA, ADMIXTURE, IBD, ALDER, and the ChromoPainter/FineSTRUCTURE pipeline. All results from those statistical tools seem to be (broadly) in agreement. That being said, overinterpretation of statistical analyses is a common pitfall  and further analyses using larger sample sizes, more sophisticated statistical tools, and ancient DNA might shed further light on the historical controversies surrounding Crete.The genetic impact of the Andalusian and the Near Eastern Arabs seems minimal; similarly, the genetic contribution of the Venetians to Cretans is low Tables An unexpected insight in the history of Crete was provided by the IBD analysis. The results showed that the Cretans share high IBD with Western (CEU), Central , Northern , and Eastern  European populations. Indeed, in previous studies, there has been an excess of IBD sharing reported between Eastern Europe and the Greeks, while an admixture event has been inferred using Poland as a representative population of the eastern component in the Greek population  and in areas of Asia Minor, attacked the islands including Crete and Cyprus, devastated Greece under Alaric, and eventually attained considerable Germanic influence on the affairs of the 5th and 6th century Byzantine Empire  ADMIXTURE analysis results for the 17 Cretan subpopulations. (b) Dendrogram resulting from the FineSTRUCTURE/ChromoPainter analysis of the Cretan samples, following a chromatic ordering of the Cretan subpopulations based on latitudeFIGURE S4 Correlation between geographic coordinates (latitude) and the second principal componentFIGURE S5 Relationships between Crete and neighboring populationsFIGURE S6 Bootstrap results for Europe, Caucasus, and the Near EastFIGURE S7 Bootstrap confidence intervals for regions of EuropeFIGURE S8 Heat map comparing relationships between Crete and Southern European populationsFIGURE S9 Bootstrap confidence intervals around mean pairwise identity by descent for populations in Table S4FIGURE S10 Bootstrap confidence intervals around mean pairwise identity by descent for populations in Table S5FIGURE S11 Principal component analysis plots for the Cretans and several European populationsFIGURE S12 ADMIXTURE analysis results for the Cretans and European populationsFIGURE S13 ADMIXTURE analysis results for the Cretans and Slavic populationsFIGURE S14 A network analysis and visualization of the connections between the populations of Main Figure 6(a) as revealed by the top three (panel a) and top five (panel b) principal componentsFIGURE S15 ADMIXTURE analysis results for the Cretans and the Sicilian populationsFIGURE S16 (a) Dendrogram resulting from the FineSTRUCTURE and ChromoPainter analysis of the Southern European populations, following a chromatic ordering of the populations. (b) Pairwise coincidence matrix generated by the FineSTRUCTURE and ChromoPainter analysis using Southern European populationsFIGURE S17 Principal component analysis plots for the Cretans and Near Eastern Semitic populationsFIGURE S18 ADMIXTURE analysis results for the Cretans and the Near Eastern Semitic populationsFIGURE S19 Principal component analysis results for the Cretans and populations of medieval conquerors and settlers in the islandFIGURE S20 ADMIXTURE analysis results for the Cretans, the Andalusians, the French, and the BasqueFIGURE S21 ADMIXTURE analysis results for the Cretans and North African populationsFIGURE S22 ADMIXTURE analysis results for the Cretans and Near Eastern populationsFIGURE S23 Principal component analysis plots comparing the Cretan populations with the population of ArmeniaFIGURE S24 ADMIXTURE plot of Cretans and ArmeniansFIGURE S25 ADMIXTURE analysis results for the Cretans, Venetians, and two Italian populationsTABLE S1 The 17 Cretan subpopulations included in the studyTABLE S2 Populations used in this studyTABLE S3 Populations sharing identity by descent with west CreteTABLE S4 Populations sharing identity by descent with East CreteTABLE S5 Linkage disequilibrium–based inference of admixture times and proportions for the Cretan population using ALDERTABLE S6 Amount of Cretan ancestry captured by the Andalusians, the Basques and the FrenchTABLE S7 Amount of Cretan ancestry captured by Near Eastern populationsTABLE S8 Amount of Cretan ancestry captured by the population of VenetoTABLE S9 Populations sharing identity by descent with SicilyTABLE S10 IBD shared with Cyprus (n = 30); populations are sorted alphabeticallyClick here for additional data file.


Colossoma macropomum which in recent years has been suffering from severe exploitation. Our aim was to investigate the existence or not of genetic differentiation across the wide area of its distribution and to investigate changes in its effective population size throughout its evolutionary history. We sampled individuals from 21 locations distributed throughout the Amazon basin. We analyzed 539 individuals for mitochondrial genes (control region and ATPase gene 6/8), generating 1,561 base pairs, and genotyped 604 individuals for 13 microsatellite loci obtaining, on average, 21.4 alleles per locus. Mean HE was 0.78 suggesting moderate levels of genetic variability. AMOVA and other tests used to detect the population structure based on both markers indicate that C. macropomum comprises a single and large panmitic population in the main channel of the Solimões-Amazonas River basin, on the other hand localities in the headwaters of the tributaries Juruá, Purus, Madeira, Tapajós, and localities of black water, showed genetic structure. The greatest genetic differentiation was observed between the Brazilian Amazon basin and the Bolivian sub-basin with restricted genetic flow between the two basins. Demographic analyzes of mitochondrial genes indicated population expansion in the Brazilian and Bolivian Amazon basins during the Pleistocene, and microsatellite data indicated a population reduction during the Holocene. This shows that the historical demography of C. macropomum is highly dynamic. Conservation and management strategies should be designed to respect the existing population structure and minimize the effects of overfishing by limiting fisheries C. macropomum populations.We studied the natural populations of a flagship fish species of the Amazon,  Colossoma macropomum (tambaqui) is on the top of the list of most important commercial species. This species also has an important ecological role, as it is an important disperser of seeds of trees and shrubs of the Amazonian floodplain  samples of the mainstream of the Amazon River, as well as eight of its main tributaries; (ii) samples of all three major water types of the Amazon  based on the classifications of Sioli  sColossoma macropomum were collected directly from artisanal fishers at 21 localities within the Brazilian Amazon basin and one locality in the Bolivian sub-basin  were as follows: denaturation at 94°C for 60 s, primer annealing at 50°C for 30 s, primer extension at 68°C for 90 s, followed by a final extension at 68°C for 5 min. The first three steps were repeated 35 times.Total genomic DNA was extracted using Proteinase K/Phenol-chloroform/isoamyl alcohol protocol and precipitated with 70% ethanol , each sample was sequenced in two steps, using the CMF2 (forward) and CMR2 (reverse) internal primers . The samples were sequenced using the BigDye terminator v3 kit (ThermoFisher), following the manufacturer's protocol. Due to the size of the control region of C. macropomum. The amplification conditions for each multiplex were: For three pairs of primers: 1.5 μl MgCl2 (25 mM), 1.5 μl dNTPs (10 mM), 1.5 μl 10x buffer , 1.0 μL of each forward primer containing one of the two M13 tails (2 μM), 1.5 μL of each reverse primer, 1.5 μL of fluorescence-labeled M13f (FAM) primer, 0.7 μL of primer fluorescence-labeled M13r (HEX), 0.8 μl Taq DNA Polymerase (5 U/μl) and 1 μl DNA (50–100 ng), with a final volume of 14.5 μl. For two pairs of primers: 3.0 μl ultra pure water, 1.5 μl MgCl2 (25 mM), 1.5 μl dNTPs (10 mM), 1.5 μl 10x buffer , 1.0 μL of each forward primer containing one of the M13 tails (2 μM), 1.5 μL of each reverse primer, 1.5 μL of the fluorescently labeled M13f primer (FAM), or 0.7 μL of fluorescently labeled M13r primer (HEX), 0.6 μl of Taq DNA Polymerase (5 U/μl), and 1 μl of the DNA (50–100 ng), with a final volume of 14 μl.Microsatellite genotypes were generated using a multiplex design  for 20 s, and extension at 68°C for 30 s, repeated for 30 times, followed by another cycle for annealing the M13 primers with the following conditions: denaturation at 94°C for 20 s, annealing of the M13 fluorescence-labeled primer at 50°C for 20 s, and extension at 68°C for 30 s, repeated for 20 times, with final extension of 30 min at 68°C.GeneMapper™ software version 4.0 . Matrix of genotypes is available at https://github.com/legalLab/datasets.For the genotyping reaction the PCR products were diluted to between 10–50 μL with ultra-pure water depending on the intensity of PCR products on an agarose gel. For each 1 μl of diluted product, 8.0 μL of Hi-Di formamide , and 1.0 μL 6-carboxy-X-rhodamine (ROX) size standard from DeWoody et al.  were addMH514288–MH514827 for control region and MH520124–MH520663 for ATPase genes.The sequences of the control region and subunits 6 and 8 of the ATPase gene were verified, edited and aligned in the program BIOEDIT v7.0.5 Hall, . The ATPST were also estimated, and statistical significance was corrected for multiple comparisons  implemented in the program ARLEQUIN v3.5  using the median-joining algorithm.In order to investigate patterns of change in −8 mutations per site and per year   and expected (HE) heterozygosities, gene diversity (h), nucleotide diversity (π), linkage disequilibrium (LD) between pairs of loci and the Hardy-Weinberg equilibrium (HWE) were calculated. All these parameters were estimated using ARLEQUIN v3.5  for each sample. The effective population size (Ne) for each population was estimated using the LD method . The analysis was run with 1,000,000 MCMC step, discarding the first 100,000 steps. The Isolation by Distance (IBD) was tested via a correlation between genetic and geographical distance using the Mantel test implemented in the Software Arlequin , m (migration rates), and theta (θ) where θ = 2 Neμ. We sampled 20,000,000 Monte Carlo Chain Markov Chain Monte Carlo (MCMC) generations after discarding the first 1,000,000 generations as burn-in. Two independent runs were carried out with different starting points, in order to verify convergence. The two independent runs converged and thus were combined and the parameters θ, m, and t were estimated. Then, these were converted into demographic parameters: contemporary effective population size, number of migrants per generation, and time of divergence of the populations in generations. The analyses using IMa2 were performed with pairs of sampling sites located at the geographic extremes along the main channel of the Amazon River and between upstream and downstream localities of principal tributaries. We also estimated geneflow using the program MIGRATE 3.1.6  between the localities and the relative number of migrants per generation Nm = Mθ/2. To convert the results into biological information, we assumed a 3-year generation time for C. macropomum (previously justified with mtDNA data), and a mutation rate μ = 5 × 10−4  or bottleneck effect, we tested for heterozygosity excess in the program BOTTLENECK , where a bottleneck depletes the number of alleles faster than reducing allelic size range of the microsatellite  ranged from 0.714 in Guajará-Mirim to 0.797 in Eirunepé (Juruá River). Mean heterozygosity was 0.777 ± 0.395 for all loci and all locations (Supplementary Table FIS) ranged from 0.023 to 0.144 and was significant for all localities.A total of 604 individuals were genotyped for 13 microsatellite loci. The data revealed no evidence of allelic stutters or large allele dropouts (genotyping errors) and neither linkage disequilibrium (LD). However, deviation from the Hardy-Weinberg equilibrium (EHW) was observed at the Cm1E3 locus in 17 of the 21 sampled localities and the locus was therefore removed from the population analyses. Genetic variability parameters were quite homogeneous among the individuals from different localities , demonstrating no correlation between the genetic distances of the sampling sites and their respective geographic distances.AMOVA of the mtDNA data demonstrated that more than 90% of genetic variance was within sampling sites. When AMOVA was performed without Guajará-Mirim (Bolivian sub-basin), ΦFST = 0.0111, P = 0.00124). Based in this result, additional AMOVA tests were implemented assuming two main groups: Amazon basin vs. Bolivia basin and, within the Amazon basin, tributaries vs. main channel. The AMOVA results were significant for both analyses , respectively.Global AMOVA of microsatellite data resulted in partitioning more than 98% variance within sites  only when the Bolivian sub-basin was included in the analysis.The matrix of pairwise T Figure  and FST K = 2 , FCT was maximized for both the mtDNA and microsatellite datasets, but with significant support only for the mtDNA data. Bayesian analyses implemented in STRUCTURE v2.3.4 identified three biological groups. The highest posterior probability was LnP (K = 3) = −31766.0000. The three populations comprised individuals from the Bolivian sub-basin and the Brazilian Amazon basin. Individuals from the three localities in the Madeira River showed a linear gradient of admixture between these two populations, and a contribution of an additional biological group principally within the Humaitá locality  considering all samples as well as when considering the two basins separately  , which fits a pattern expected under stable population size, although this was not supported by Harpending's raggedness index. The sum of squared deviations  as well as the inference performed for the two basins separately . Thus, these values neither support nor reject the null hypothesis of a demographic population expansion for C. macropomum  Table  for all C. macropomum has undergone a pronounced population decline in both the Amazon and Bolivian basins  and occurred with 0.9992 probability. Population decline started at approximately 10,000 (Amazon) and 2,500 (Bolivia) years ago. Signs of population reduction in the Bottleneck program were significant for 18 locations under the SMM model, however Mvalue showed no signal of population reduction, with exception of individuals from Tefé (Table Ne) were low for majority of the localities. However, the confidence intervals were also “infinite” for all but the Madeira River, Parintins, Eirunepe and Tabatinga localities.Results based in MSVar analyses show that historically s Figure . The meaColossoma macropomum is not panmictic throughout its distribution area. Considering the entire sample, AMOVA, SAMOVA, STRUCTURE, ΦST (DNAmt), and FST/GST (microsatellites) analyses, suggested genetic differentiation of the Bolivian sub-basin and Brazilian Amazon basin localities.The use of more variable genetic markers, such as microsatellites, has confirmed some of our earlier findings. Nm) for DNAmt and microsatellite data evidenced restricted gene flow between the two basins, but enough to maintain the exchange of genes, thereby minimizing effects of genetic drift. The microsatellite data demonstrate that migration between the two basins is bidirectional. The results of both the IMa and MIGRATE analyses show that gene flow is greater from Bolivia to the Brazilian Amazon, which is in agreement with the results described by Farias et al. , which gradually isolated the Bolivian basin, resulting in considerable changes in the drainage pattern, in which the main rivers north of Bolivia drain into the Amazon River through the Madeira River  is associated with the upper Madeira River rapids, which serve as a natural barrier that restricts, but does not prevent, geneflow between the populations of Batista, . The TeoC. macropomum in the main channel of Amazonas River in the Brazilian Amazon basin was supported by all population structure analyses based on mitochondrial genes and microsatellites loci. These findings confirm the pattern reported by Santos et al. (ST)), and worked at much smaller geographic scales. However, ΦST comparisons involving the tributaries were significant even after Bonferroni corrections. Fisher's exact test and Hedrick's GST analysis with microsatellites markers show a weak population differentiation between localities, and stronger differentiation involving comparisons with tributaries, and also black water sites. Geneflow between the main stream localities and tributary headwaters and black water sites generally is smaller than one effective migrant per generation which also confirms the migration patterns observed in IMa and MIGRATE analyses. Contrary to this pattern, STRUCTURE analysis shows population differentiation only for upper Madeira . STRUCTURE program uses a Bayesian approach to investigate the number of biological groups in the dataset. The discordance, between these analyses, could be due to the fact that GST analyses are based on variance in allelic frequencies between/among groups and Fisher's exact test uses contingency tables to test null hypothesis that the alleles are drawn from the same distribution in all populations. These two analyses are more sensitive to detecting smaller and finer levels of genetic differentiation, while STRUCTURE tests for shared system of mating among individuals of the same group. The algorithm of STRUCTURE will not necessarily detect weak structure  to Tabatinga (20) there seem to be not even a signal of isolation-by-distance between the two localities separated by approximately 2,500 Km. The observed lack of genetic structuring of um Junk,  and thisHO suffers from sampling effects, we used HE as a minimally biased estimate of diversity  is not in agreement with DeWoody and Avise  which have higher HE as would be expected by their much larger census sizes. Colossoma macropomum has an intermediate HE, again a reflection of its frugivorous lifestyle combined with large body size, and thus smaller census size than the other migratory characids but larger census size than the predatory catfishes.In this respect, when compared to freshwater fishes of Europe and North America, the heterozygosities of Amazonian fishes may appear to be high, but this is an illusion. The expected heterozygosities are C. macropomum suggested population expansion in the Amazon basin, which is the same scenario suggested by Farias et al. , probably due to climate change related to Last Glacial Maximum and during the mid-Holocene epoch  and occurred with 0.9992 probability.Corroborating the observation for the Holocene, analyses of microsatellite data in MSVar indicate that The demographic decrease was from approximately 100,000 effective individuals to approximately 5,000 individuals, an approximate 1.5 orders of magnitude decrease. Similar values for current effective population size were inferred using IMa2 , Resolution 301 .IF and TH conceived the experiment and obtained funding. MS, IF, and TH conducted fieldwork, collected specimens, analyzed the results, and wrote the manuscript. MS collected molecular data. All authors contributed to and reviewed the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Malaria remains endemic in several countries of South America with low to moderate transmission intensity. Regional human migration through underserved endemic areas may be responsible for significant parasite dispersion making the disease resilient to interventions. Thus, the genetic characterization of malarial parasites is an important tool to assess how endemic areas may connect via the movement of infected individuals. Here, four sites in geographically separated areas reporting 80% of the malaria morbidity in Colombia were studied. The sites are located on an imaginary transect line of 1,500 km from the northwest to the south Pacific Coast of Colombia with a minimal distance of 500 km between populations that display noticeable ethnic, economic, epidemiological, and ecological differences.Plasmodium vivax samples from the four populations were genotyped by using eight microsatellite loci. Although a strong geographic structure was expected between these populations, only moderate evidence of genetic differentiation was observed using a suite of population genetic analyses. High genetic diversity, shared alleles, and low linkage disequilibrium were also found in these P. vivax populations providing no evidence for a bottleneck or clonal expansions as expected from recent reductions in the transmission that could have been the result of scaling up interventions or environmental changes. These patterns are consistent with a disease that is not only endemic in each site but also imply that there is gene flow among these populations across 1,500 km.A total of 624 P. vivax are consistent with a “corridor” where connected endemic areas can sustain a high level of genetic diversity locally and can restore parasite-subdivided populations via migration of infected individuals even after local interventions achieved a substantial reduction of clinical cases. The consequences of these findings in terms of control and elimination are discussed.The observed patterns in  Plasmodium vivax populations were characterized to assess whether the most endemic areas in Colombia were connected. Samples were collected from passive surveillance studies in four locations across an imaginary transect line of 1,500 km from the northwest to the south Pacific Coast of Colombia (South America). Considering the distance, and contrary to expectations, we found weak levels of genetic differentiation between these parasite populations with no evidence indicating that their genetic diversity has been eroded as expected whenever the prevalence of the disease is successfully reduced, e.g., through control programs or environmental changes. Although the sampling lacks the geographic and temporal detail to describe how the dispersion of parasite lineages occurred, the observed patterns are consistent with a series of infected populations that are connected in space by human movements allowing the parasite to diffuse across this 1,500 km transect. This malaria corridor needs to be characterized to achieve elimination.The regional movements of infected individuals that connect suitable transmission areas make malaria resilient to control efforts. Those movements are expected to leave genetic signatures in the parasite populations that can be detected using analytical tools. In this study, the genetic makeups of  Plasmodium vivax, a resilient parasite that requires a demanding treatment to eliminate dormant liver parasite forms [Malaria elimination is a public health priority. Yet, regardless of a notable reduction in the global malaria burden, more than 40% of the world’s population remains at risk of infection . Althougte forms –8. Moreote forms ,10. ConsPlasmodium vivax populations are studied. The sampling sites are located along an imaginary transect line of approximately 1,500 km from the northwest to the south Pacific Coast of Colombia. Those four human populations showed different levels of P. vivax prevalence [Parasite genetic studies have focused on detecting deviation from random mating (population structure), a pattern that results from several processes including inbreeding, population expansions, and geographic differentiation due to limited migration –15. Beyoevalence , and theevalence –8, parasP. vivax has shown to be a resilient parasite. These localities are: (i) Tierralta from the Department of Córdoba in the northern area (API ~10.7); (ii) Quibdó , (iii) Buenaventura , and (iv) Tumaco  in the southeast area of the Pacific Coast. In Tierralta  and Buenaventura , the predominant malaria parasite species is P. vivax (~85% and 75% respectively) while in Quibdó  and Tumaco  most of the malaria cases are caused by Plasmodium falciparum with P. vivax having a clearly lower prevalence (~30% and 21% respectively). The samples were collected between 2012–2013 in all areas with Buenaventura having an extended sampling (from 2011 to 2015). A complete description of these areas can be found elsewhere [We selected four localities with high malaria prevalence but different average annual parasite incidence (API) ,16. In aP. vivax were included in this study, and the parasites were genotyped as described below.A total of 1,328 symptomatic volunteers were passively recruited when visiting the health posts for malaria diagnosis ,17. PatiP. vivax DNA positive and negative controls were included in each batch of tests. Genomic parasite DNAs were genotyped by using fluorescently labeled PCR primers that target microsatellite loci (STRs). A set of eight standardized STRs for P. vivax was used; these loci were selected out of the pool that has been previously explored [2; Promega, USA). A negative control (nuclease-free dH2O) and positive control (a P. vivax infected blood sample confirmed to be positive by thick blood smear examination) were used. Amplification conditions for PCRs were reported elsewhere depending on the set of primers [Total DNA was extracted from the whole blood samples using the PureLink Genomic DNA kit . Parasite species was confirmed by a Real-time PCR (RT-qPCR) as described elsewhere . Standarexplored . In partexplored  and 14.1explored . All PCR primers ,20. Fluo primers –15,19,20One of the approaches typically used to compare populations with different transmission intensities is to estimate the average multiplicity of infection (MOI) . MOI is p-values were obtained by using a bootstrap method [To compare the MOI estimates of Tumaco with the other locations a two-sided bootstrap test with the null hypothesis of equality of MOI was performed as follows. For B = 10000 bootstrap samples (consisting of subsamples from Tumaco and the other location of corresponding sample size) the difference in the MOI estimates of Tumaco and the other location were calculated, and p method . Holm’s p method ,22.P. vivax within each population and the differentiation of the parasite populations among the four localities. The genetic diversity within each sampled population was estimated using a series of summary statistics implemented in the Haplotype Analysis software v1.05 [He) were estimated [He was defined asn is obtained by taking the sum of identifiable genotypes (phased) over all samples, and pi is the relative frequency of the i-th haplotype  in all sampled haplotypes. He gives the average probability that a pair of alleles randomly selected from the population is different. For this analysis, complex infections with differences at more than two loci were not included because the haploid genotypes could not be inferred. However, He was also calculated per locus. In this case, pi is the frequency of allele i, and He is the average probability that a pair of alleles randomly selected from the population is different. For the allele frequencies, the ML estimates [Under the assumption that patterns in the parasite genetic variation are driven, at least in part, by the regional movement of infected individuals and the local epidemiology –13,15, are v1.05  where thstimated  on all tstimates  were usestimates .Fst) were also estimated and their significance assessed using a randomization test. A limitation in this kind of analysis is that samples with multiple alleles at more than two loci were not included because the haploid genotypes could not be inferred. Then, an analysis of molecular variance (AMOVA) [Fst). Probabilities for the AMOVA statistics were calculated based on individual randomizations.To assess the parasite population differentiation between localities, normalized fixation index ( (AMOVA) ,27 was p (AMOVA) . The AMOIn order to test that changes in malaria incidence, particularly after deploying interventions, were driven by the introduction or residual presence of a few parasite lineages, pairwise measurements of linkage disequilibrium (LD) were estimated to detect potential clonal expansions. Since many pairs of loci have a different number of alleles, standard measurements of LD will be essentially biased and cannot be adequately compared across loci and populations , this isK populations or clusters characterized by a set of allele frequencies at each locus. The observed genetic diversity was evaluated under different K values (K = 2 to 15), and each K value was run independently 15 times with a burn-in period of 100,000 iterations followed by 100,000 iterations. The admixture model that allows for the presence of individuals with ancestry in two or more of the K populations was used in all the analyses [K values from Structure [K) was computed, and the K-value that better explains the genetic data was an estimate of the number of circulating clusters or populations. Complex infections with differences at more than two loci were not included in this analysis.To identify clusters of parasites that could separate the four localities, two methods were used, (i) a Bayesian model-based clustering algorithm that considers admixture as implemented in the Structure v2.3.4 software  and (ii)analyses . Structutructure . CLUMPP tructure , and thetructure . The posThen, PCA was estimated using R on all the samples, but also eliminating alleles that appear less or equal than 5 and 10 times in the whole sample  to explore if there was an effect driven by alleles in low frequency. For the PCA, alleles at each locus were coded by 0–1 variables, indicating the absence and presence of alleles, where the number 0–1 variables for each locus coincides with the number of alleles at that locus. This allowed including samples with missing data and samples with multiple infections. Concerning of alleles at low frequencies, alleles that occurred less or equal than 5 or 10 times, were not considered in some of the PCA analyses from the data set by deleting the respective 0–1 variables. This allowed exploring the effect of potential amplification errors without eliminating samples completely. For the PCA only data from Buenaventura collected before April 2013 was included as only this time range of collection is comparable with that of the other regions. Given that, alleles in low frequency could affect MOI, heterozygosity, linkage disequilibrium, and PCA analyses; those calculations were repeated eliminating those alleles that were in low frequency (less than 2%). Although no differences were observed, those results were provided.Haplotype genealogies found in malaria cases for each locality were inferred for eight microsatellites by using the Global Optimal eBURST algorithm , as implThe number of isolates genotyped from each population varied between locations: 258 from Tierralta, 65 from Quibdó, 235 from Buenaventura, and 66 from Tumaco. A description of the samples in terms of single and multiclonal infections, samples with incomplete data, and how they were used on different analyses is reported in The estimated MOI parameter was relatively low and consistent across all populations sampled . Since sA qualitative inspection of the allele-frequency spectra, as estimated from the maximum likelihood approach , can proP. vivax mean genetic diversity and the relative heterozygosity (per locus and genotype-based) are high in all the sampled populations   . This ob studies ,36–40. Tery high  with onlery high  within pery high  where thery high .Fst values were significant and relatively high, between 0.10 and 0.23 with Buenaventura and Tierralta being the two populations less differentiated and Tumaco showing the highest Fst values when compared to the others . However, part of the observed differentiation could be a sampling effect of alleles in low frequency. Indeed, the AMOVA indicated that most of the variation was explained within populations. This is a similar pattern detected in a substantially smaller geographic area in Peru [ in Peru . Neverth in Peru . Thus, fFst values, and it differs from the other three parasite populations in terms of average LD and genetic diversity. All these observations are consistent with the fact that Tumaco is the most geographically isolated population with the lowest P. vivax prevalence. However, regardless of these differences, Tumaco shared parasites with the others as indicated by the clustering methods and the haplotype networks , the data available did not support strong geographic isolation between these parasite populations. The temporal changes in the genetic structure in Buenaventura may indicate the introduction of new parasites at the time. However, the low level of LD also indicates that this replacement of parasites was not driven by a few lineages that expanded locally but by the influx of a diverse group of parasites. In the case of Tumaco, it showed the highest rks Figs –4.P. vivax malaria corridor that likely facilitates the persistence of these parasite populations across the sampled imaginary transect line of 1,500 km. In this context, a malaria corridor is defined as spatially connected endemic areas that sustain a high level of genetic diversity regionally and can restore parasite-subdivided populations (“rescue effect”) even after interventions succeeded in reducing transmission locally [The results presented here are consistent with the existence of a  locally . Indeed,P. vivax genotypes were shared between the sampled populations. This suggests a multi-generation gene flow where genotypes are broken by recombination (as detected by microsatellite loci) rather than recently introduced parasite lineages expanding locally. This pattern indicates that regionally coordinated control efforts could increase the fragmentation of the P. vivax populations making them more susceptible to local extinction (elimination). Furthermore, if it is identified, deploying interventions in such contact zones could be a cost-effective strategy for achieving the elimination goal. A possibility to explore is assessing the effect of mining communities since those may act as catching areas for individuals moving from distant places [P. falciparum, particularly in the Pacific Coast of Colombia and Peru [P. vivax, P. falciparum shows a strong LD across populations indicating that such connectivity allows for stable inbreed clones to expand [The lack of a suitable temporal and spatial sampling across this transect did not allow describing the dynamic of the parasite dispersion and the identification of the contact zones in the context of the proposed malaria corridor model. However, on the positive side, almost no linked multilocus t places . It couland Peru ,50. Unlio expand . NeverthP. vivax infections across settings that indicate a comparable low to moderate transmission in all sites, regardless of differences in malaria morbidity [The samples included in this study were mostly from symptomatic patients. However, the importance of asymptomatic carriers in these dynamics can be anticipated ,51. Evenorbidity . It is worbidity . In addiP. vivax endemic region. Although important in terms of providing a partial description of how parasites disperse in space, studies as the one reported here (as many others) lack the spatial and epidemiological detail required for accurately describing such spatiotemporal dynamics. Nevertheless, this study highlights the need for carefully planned epidemiological investigations that, together with population genetic tools, can accurately model these complex dynamics at an actionable time scale, such as; make inferences from one transmission season to the next.Here we provide a static but valuable picture of a complex process critical for malaria control and elimination in a S1 FigTop: alleles with absolute frequency ≤ 5 among all populations were removed. Bottom: alleles with absolute frequency ≤ 10 among all populations were removed.(PDF)Click here for additional data file.S2 Fig(PDF)Click here for additional data file.S3 FigTop: alleles with absolute frequency ≤ 5 among all populations were removed. Bottom: alleles with absolute frequency ≤ 10 among all populations were removed.(PDF)Click here for additional data file.S4 Fig(PDF)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S4 Table(PDF)Click here for additional data file.


Atlantic salmon is characterized by a high degree of population genetic structure throughout its native range. However, while populations inhabiting rivers in Norway and Russia make up a significant proportion of salmon in the Atlantic, thus far, genetic studies in this region have only encompassed low to modest numbers of populations. Here, we provide the first “in‐depth” investigation of population genetic structuring in the species in this region. Analysis of 18 microsatellites on >9,000 fish from 115 rivers revealed highly significant population genetic structure throughout, following a hierarchical pattern. The highest and clearest level of division separated populations north and south of the Lofoten region in northern Norway. In this region, only a few populations displayed intermediate genetic profiles, strongly indicating a geographically limited transition zone. This was further supported by a dedicated cline analysis. Population genetic structure was also characterized by a pattern of isolation by distance. A decline in overall genetic diversity was observed from the south to the north, and two of the microsatellites showed a clear decrease in number of alleles across the observed transition zone. Together, these analyses support results from previous studies, that salmon in Norway originate from two main genetic lineages, one from the Barents–White Sea refugium that recolonized northern Norwegian and adjacent Russian rivers, and one from the eastern Atlantic that recolonized the rest of Norway. Furthermore, our results indicate that local conditions in the limited geographic transition zone between the two observed lineages, characterized by open coastline with no obvious barriers to gene flow, are strong enough to maintain the genetic differentiation between them. Yet, despite the significance of this region for Atlantic salmon, a detailed picture of population genetic structure in Norway is lacking, with the literature on Norwegian rivers confined largely to scattered population samples within broader scale assessments , SSsp2210, SSspG7, SSsp2201, SSsp1605, SSsp2216 : SSsp3016   to avoid high overestimation of the percentage of outliers . Due to the impossibility of handling data sets exceeding 100 populations, LOSITAN was conducted separately for each of the regional divisions obtained from STRUCTURE.Screening for outlier loci was performed using two methods. First, with the approach implemented in ARLEQUIN v.3.5.1.2  were calculated with MSA  and unbiased expected heterozygosity (uHe) were computed with GenAlEx  was conducted using the program GenoDive, version 2.0b , we conducted a cline analysis to estimate the shape, center, and width of the cline generated by our molecular data  in the full data set, whereas LOSITAN suggested that MHC2 was the only locus under directional selection in the two main clusters resulting after the first hierarchical division of the 115 samples. Thus, using a combined approach, MHC2 remained the only candidate for directional selection. The influence of this locus was tested by conducting STRUCTURE with and without it Appendix . As inclHardy–Weinberg deviations were reported in ~10% of the tests performed across populations for every locus, but they were reduced to 2.9% after sequential Bonferroni correction. Likewise, the percentage of deviations from LD decreased from 16.5% to 5% after correction. In both cases, the departures from expectations were distributed across populations and loci, therefore, no loci were dropped from the data set based on the results from these analyses.Over the 18 microsatellites, a total of 413 alleles were observed, ranging from 5 to 7 alleles in SsaD486 and Ssa14, respectively, to 41 in SsaD144 and SsaD157. The total number of alleles per population ranged from 78 to 259, with a mean of 217 Table . The Kovτ = −0.177, p = 0.005), Ho , uHe  or overall allelic richness   whereas for locus Sp1605, the trend was reverse .The level of genetic variation showed a significantly increasing latitudinal N‐S trend following the coastline from Russia to southern Norway when measured either as: average number of alleles per locus within population , but not with Ho  nor with Ar . After performing Bonferroni correction for multiple comparisons, the Wilcoxon test did not reveal any population displaying evidence of having experienced recent bottlenecks. Likewise, no mode shift in allele frequencies was detected in any of them, all showing L‐shaped allele frequency distributions; that is, the number of alleles in the low‐frequency classes (<0.1) exceeded the number of alleles in the higher frequency ones.In Norway, the conservation limits expressed as kg of female fish per river were significantly correlated with Ne (3.2K test of STRUCTURE results showed two clusters (ΔK = 176.5) that divided the data set in a northernmost group ranging from the rivers Unya(1) to Reisa(51) , and a southern cluster from the rivers Laukhelle(53) to Enningdalselva(115) (63 rivers)  appears as a transitional river. This genetic division also corresponds to a change in life history as the eastern populations and the White Sea populations are mainly “autumn‐run” salmon, which ascend the river the more than a year before spawning, while the Barents Sea rivers are dominated by “summer‐run” salmon spawning in the same year they return to the river. On the northern coast of the Kola Peninsula, there seems to be a genetic shift between the rivers east (10–20) and west 26–36 of the Kola Bay , Alvsvågvassdraget(55), and Gårdselva(56) appear different from the rivers on the mainland. This was revealed more clearly at structure runs at higher values of K , ranging between 0.012 (SsaD486) and 0.079 (Ssa289), with the global estimate over the 18 loci being 0.037 (p < 0.0001). The highest pairwise FST (0.202) was identified between the two Russian rivers Unya(1) and Kovda(3)  were recorded between five pairs of rivers within a range of 19 to 430 km of distance from each other. Almost all the pairwise comparisons except for 14 (0.2%) were significantly different from zero (p < 0.05). The nonsignificant values ranged from 0.0007 to 0.0041 in a range of geographic distances of 19–534 km.All global single‐locus estimates for FST and geographic distance, demonstrating an overall pattern of genetic isolation by distance (IBD) among the 115 populations . The removal of the aberrant Kodva(3) sample increased the strength of the IBD pattern  and with a width of 296 km Figure . Both th4This study, based on the analysis of >9,000 individuals sampled in 115 rivers, represents the first extensive investigation of genetic structure within and among Norwegian and northwest Russian Atlantic salmon populations. Our most important results are summarized as follows. We observed (a) highly significant population genetic structuring in all regions, following a hierarchical geographic pattern, (b) a clear genetic division in the north of Norway with a geographically limited transition zone Figures  and 6,  restricted straying and/or gene flow, (b) divergent selective forces.There are still many unknowns regarding straying rates among salmon populations, though they clearly vary in time and space , and potentially life history or other adaptive characteristics, appear linked with some of the patterns of genetic structure observed here. For example, in the relatively isolated Trondheimsfjord in mid‐Norway, the ten rivers sampled show a clear pattern of genetic divergence between the rivers with demographically small populations  and those with demographically large or very large populations  Figure , once agLandscape features are known to influence population genetic structure in Atlantic salmon  were obtained from juvenile fish caught by electrofishing, or in some cases, scale samples collected in rod fisheries. Juvenile fish captured by electrofishing were euthanized before samples were collected. The permits required to obtain samples were issued by the Federal Agency for Fisheries (Russian Federation), and different County Governors of Norway. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Canis lupus) range. We studied the persistent, the expanding and a small, isolated group within the Iberian wolf population, using 3 MHC class II genes , which diversity was compared with 39 microsatellite loci.Different population trajectories are expected to impact the signature of neutral and adaptive processes at multiple levels, challenging the assessment of the relative roles of different microevolutionary forces. Here, we integrate adaptive and neutral variability patterns to disentangle how adaptive diversity is driven under different demographic scenarios within the Iberian wolf  contains supplementary material, which is available to authorized users. Genetic drift and natural selection are often seen as two counteracting evolutionary forces across populations . In largIn vertebrates, the major histocompatibility complex (MHC) is the prime candidate for pathogen resistance genes and contains some of the most polymorphic functional loci , 12. TheCanis lupus), which erstwhile ranged over most of the Iberian Peninsula, but after decades of severe human persecution became confined to small and fragmented populations, representing about 1/5 of the former population range ) lme4  and lmerlmerTest  implemenp-value), following [adegenet and ade4 R packages [Expectations that functional diversity exceeds neutral diversity were tested by a one-tailed t-test  in the three assigned demographic groups and whole Iberian wolf range. (PDF 19 kb)Additional file 2:Table S2. Number of three-locus (DLA-DRB1/DQA1/DQB1) haplotypes (N) and their frequency (f) in the three assigned demographic groups and whole Iberian wolf range. (PDF 14 kb)Additional file 3:Table S3. Comparison of the DLA-DRB1, DQA1, DQB1 alleles and three-locus haplotypes (DRB1/DQA1/DQB1) in the Iberian (this study), Croatian [¥alleles found in the North American wolf population [Croatian , ItalianCroatian , FinnishCroatian  wolf popCroatian , 38 ¥allpulation , 48; # hpulation . NI: no Additional file 4:Table S4. Genetic diversity values for the three MHC loci in the Iberian wolf range. Sample size (n), mean number of alleles (Na), mean number of effective alleles (Ne), mean observed and expected heterozygosities (Ho and He), mean inbreeding coefficient (FIS), number of segregating sites (S), nucleotide diversity (π), number of mutations (η) Watterson’s mutation parameter (θW), neutrality tests of Tajima’s D and Fu &Li D*, and estimates of average nucleotide and aminoacid distances. Statistical significance: *P < 0.05, **P < 0.02. Standard error estimates shown in brackets. (PDF 139 kb)Additional file 5:Table S5. Positively selected codons in each Iberian wolf demographic group according to OmegaMap analysis and codons putatively belonging to the peptide-binding regions (PBR) suggested by [ested by  for DLA-Additional file 6:Table S6. Model selection information, including Akaike Information Criterion (AICc), delta AICc (ΔAICc) and weight of selected model for number of alleles (Na), allelic richness (AR), observed (Ho) and expected (He) heterozygosities. (PDF 128 kb)Additional file 7:Table S7. Estimates of combined diversity measures of each demographic group, standard errors (S.E.) and probability inferred from t-value, according to the selected model. (PDF 11 kb)Additional file 8:Table S8. Mean number of alleles (Na), mean number of effective alleles (Ne), mean allelic richness (AR), observed (Ho) and expected (He) heterozygosities, and mean inbreeding coefficient (FIS) at the microsatellite and MHC loci, in three demographic groups , including standard deviation (s.d). The probability of the values to differ between microsatellite and MHC loci was tested by a one-tailed t-test . Values with statistical significance are in bold (p < 0.05). (PDF 28 kb)Additional file 9:Table S9. Thermocycling profile for PCR amplification of the three MHC fragments used in this work. Annealing temperature (AT) was set initially at 64 °C (DRB1), 54 °C (DQA1) and 76 °C (DQB1). (PDF 97 kb)


Bettongia lesueur) in a translocation to mainland Australia over three generations. Using 18 microsatellite loci and the mitochondrial D-loop region, we monitored the released animals and their offspring between 2010 and 2013. Despite high levels of divergence between the two source populations (FST = 0.42 and ϕST = 0.72), there was clear evidence of interbreeding between animals from different populations. However, interbreeding was non-random, with a significant bias towards crosses between the genetically smaller-sized Barrow Island males and the larger-sized Dorre Island females. This pattern of introgression was opposite to the expectation that male–male competition or female mate choice would favour larger males. This study shows how mixing diverged populations can bolster genetic variation in newly established mammal populations, but the ultimate outcome can be difficult to predict, highlighting the need for continued genetic monitoring to assess the long-term impacts of admixture.The use of multiple source populations provides a way to maximise genetic variation and reduce the impacts of inbreeding depression in newly established translocated populations. However, there is a risk that individuals from different source populations will not interbreed, leading to population structure and smaller effective population sizes than expected. Here, we investigate the genetic consequences of mixing two isolated, morphologically distinct island populations of boodies ( Species used in conservation translocations are often threatened or rare. Many have isolated populations that are subjected to loss of genetic variation, high levels of inbreeding, and elevated risks of extinction ,2,3. WhiPuma concolor coryi). The introduction of Texas panthers (Puma concolor stanleyana) from a geographically nearby population increased genetic diversity, reduced inbreeding, improved survival and fitness, and tripled the number of panthers [Mixing individuals from different source populations is one way to bolster genetic variation and avoid inbreeding in threatened species ,8,9. Hybpanthers ,12,13. Fpanthers . Interbrpanthers ,16. Conspanthers ,19,20,21Thamnophis ordinoides) produced a mismatch in body pattern and behaviour in hybrid snakes that had a higher mortality from predation in comparison to purebred snakes [While mixing differentiated populations can have favourable outcomes, it can also lead to fitness reductions in the progeny  due to post-zygotic isolation between source populations ,23,24. Cd snakes . Progenyd snakes  or fitned snakes . Common d snakes , low surd snakes , slow grd snakes , and decd snakes . In addid snakes ,32,33. Td snakes . Predicting whether outbreeding depression will occur is difficult. Generally, the risk of outbreeding depression becomes higher as the genetic distance between the parents becomes greater, but the amount of divergence required for it to occur varies from species to species ,36. The Bettongia lesueur) is a medium-sized, burrow-living marsupial endemic to Western Australia. B. lesueur is characterised by a short blunt head, with small rounded and erect ears. They are yellowy grey with a light grey underside, while the legs, feet, and tail are more yellow in colour [The boodie or burrowing bettong  Red List of Threatened Species  and as Tferences  and a loferences . Severalferences . Howeverferences .B. lesueur at Matuwa. Our specific aims were to first measure the genetic variation within and between source populations used in the Matuwa translocation with mitochondrial and nuclear markers. Second, we investigated the extent of genetic mixing between the two source populations, especially whether the body size difference has influenced the symmetry of introgression. Third, we measured levels of genetic variation to assess whether it was higher in the translocated population relative to the source populations, and whether levels of genetic variation have changed over time. Lastly, we investigated the genetic basis of phenotypic variation in body size between source populations and outcome of interbreeding on hybrid offspring body size. According to the framework of Frankham et al. , the likIn 2010, 56 females and 53 males from Dryandra Field Breeding Facility  and 27 females and 40 males from Barrow Island were reintroduced to Matuwa . All 67 Barrow Island founders were released in February, while Dryandra founders were released incrementally as follows: 20 in January, 80 in August , and 9 in October.N = 67 and Dryandra, N = 109) and four collected from the population at the translocation site once a year from 2010 to 2013 . All animals caught during trapping sessions had a tissue biopsy sample taken from their ear (stored in 70% ethanol) and were microchip implanted, weighed, sexed, aged, and measured for head length and long pes length. DNA was extracted using a ‘salting-out’ method [N = 49), Dorre Island (N = 5), and Bernier Island (N = 5) populations collected between 1999 and 2001  and were included in haplotype network analyses. We collected samples during the establishment of the translocated population at Matuwa in 2010 and during follow-up population monitoring between 2010 and 2013. Six cohorts were sampled in total, two collected from individuals translocated to Matuwa , edited using SEQUENCHER , and aligned with CLUSTAL W using default parameters [The mitochondrial (mtDNA) D-loop region was amplified using primers L15999M and H16498M . PCR wasrameters .Petrogale assimilis [P. xanthopus [Potorous longies [We genotyped each individual at 18 microsatellite loci that were developed for other macropod species, including 12 loci described in Donaldson and Vercoe , 3 loci ssimilis , 1 from anthopus ,56, and  longies   in ARLEQUIN version 3.0 [Mitochondrial DNA diversity was quantified by calculating the number of haplotypes, gene diversity and nucleotide diversity using DNASP version 5 . Pairwission 3.0 . Represesion 3.0 . For sitsion 3.0 .FIS), pairwise genetic divergence (FST), tests for differentiation among population samples, and genotypic disequilibrium were calculated using FSTAT version 2.9.3.2 [FIS values from Hardy–Weinberg Equilibrium was determined by randomization tests. Genetic divergences between pairs of population samples were quantified using Weir and Cockerham’s [FST (θ). Genotypic disequilibrium between each pair of loci within each population sample was assessed by testing the significance of association between genotypes. For these tests, a sequential Bonferroni correction [We assessed microsatellite genotyping quality by calculating the allele- and locus-specific genotypic error rates by re-genotyping randomly selected 10% of the total sample . We test 2.9.3.2 . The sigkerham’s  FST (θ).rrection  was applrrection .K = 2) because this was the number of source populations. To confirm the number of genetic clusters, we compared the likelihood values for different K values (1–10) and used the ΔK method of Evanno et al. [K . Four distinctive clades were apparent, corresponding to each of the remnant populations. Two clades were found within the Barrow Island population and one unique clade was detected in each of the Dorre and Bernier Island populations a. The AMEach of the source populations used to establish the Matuwa translocated population had both shared and unique haplotypes. Three haplotypes  were found in both the Dryandra and Barrow Island population samples. Individuals originating from Barrow Island also carried unique haplotypes , while individuals originating from Dryandra had only one unique haplotype (I) in addition to shared haplotypes b. HaplotLevels of mtDNA variation in the translocated population at Matuwa were comparable to the levels found in the Barrow Island source population but were higher than the Dryandra source population . SignifiP < 0.05 in all cases). However, there were no significant differences between samples from the translocation site and the Barrow Island source population or between samples taken from the translocation site in different years.Across the microsatellite data set, the amplification success rate was 0.973 per locus. The allele- and locus-specific genotypic error rates were 0.030 and 0.039, respectively. Six loci  showed evidence of null alleles in the source population samples, but none were consistently found in both populations. The data were analysed with and without loci with null alleles. Both showed similar results, but the presence of null alleles lowered the posterior probability of some samples in NEWHYBRIDS. Therefore, only results without null alleles were presented. Overall, estimates of genetic diversity were typically higher in the translocated population at Matuwa than the source populations . PairwisFIS values . Multilocus FIS values of the source populations were not significantly different from zero , 38.5% were designated as pure-bred Barrow Island, 28.4% pure-bred Dryandra, 18.3% F1 hybrid, and 14.7% post F1 generation. The classification in the NEWHYBRIDS analysis was consistent with STRUCTURE. All pure-bred individuals identified with NEWHYBRIDS had Q-values greater than 80% and all hybrid individuals had Q-values between 42% and 65%. Of the 20 F1 hybrids identified, 18 (90%) had a candidate mother from the Dryandra source population or was an adult female born at the translocation site with pure-bred Dryandra ancestry  and head length in females . Matuwa-born F1 hybrids were significantly larger than Matuwa-born Barrow Island pure-bred individuals and were similar in size to the Matuwa-born pure-bred Dryandra individuals, except for Matuwa-born F1 females, which had shorter pes length than pure-bred Dryandra born females , although other traits where trait values in the F1 hybrid were comparable to individuals with a pure-bred Dryandra ancestry  suggest that dominance or maternal effects are also important. The body size differences between populations also appear to have a genetic basis, as pure-bred offspring born at the translocation site maintained the body size differences observed between source populations, despite being raised in the same environment. Furthermore, intermediate trait values in FB. lesueur translocated to a new site on the mainland were able to interbreed and produced viable offspring. Admixed individuals were evident in the 2011 collection year after all of the founders were released. The lack of genetic mixing prior to 2011 likely reflected the different release times of founding animals, with the majority of Barrow Island founders being released in February 2010 and most Dryandra founders released mid-August 2010. After three years, more than half of the offspring born at the translocation site were of hybrid or backcrossed origin. Nevertheless, significantly positive FIS values were evident in each yearly collection taken from the translocated site, suggesting that while interbreeding was taking place, mating between individuals with different ancestries was non-random. By contrast, no deviations from random mating were observed in the source population samples.Despite high levels of genetic differentiation between remnant island populations, B. lesueur, suggested that maternal weight may play a role in developmental variations of B. lesueur pouch young of the same age due to larger females producing more milk, resulting in larger pouch young. On Dorre and Bernier Islands, B. lesueur females with a weight range of 1000–1600 g produced pouch young more frequently (from signs of lactation or trapped with pouch young) [Non-random mating was also evident from the asymmetrical introgression between source populations; crosses between smaller-sized Barrow Island males and larger-sized Dryandra females were significantly more common than expected. It is unlikely that the asymmetry was caused by different breeding cycles because our trapping records indicated no obvious differences in the frequency of pouch young carried by females originating from Barrow Island and Dryandra. Another possibility is that intrinsic, cyto-nuclear incompatibilities may have selected against hybrids resulting from crosses between Dryandra males and Barrow Island females during gestation ,73. The h young) . SmallerCapra ibex [Sphenodon guntheri [Jacana spinosa and J. jacana, female–female competition is a major determinant of reproductive success [J. spinosa females disproportionally produce hybrid offspring, which subsequently shifts average female body mass to be more similar to larger-sized species [In translocations, there are factors other than genetics that can influence the observed extent and direction of introgression, such as the pattern of mortality, release time and the relative proportions of different founder sources, variance in reproductive success, and selection. Some mortality is expected in translocations ,76. In fpra ibex  and Spheguntheri ) with thguntheri ,80,81,82 success . Larger  species . Dominan species . Lastly, species .Cottus cognatus) exhibited increased levels of genetic diversity, but the increases were only slightly higher than the single most genetically diverse source population. While we found no evidence of differences in genetic diversity among collection years, previous studies have shown that translocated populations often lose genetic diversity as a result of the founder effect [As found in previous studies on translocated populations involving multiple source populations, we found evidence of higher levels of genetic variation in the translocated population than in one or more of the source populations ,18,84,85r effect , mating r effect ,87, or sr effect ,77,88. Ir effect  in this There is little information on managing unexpected negative outcomes of introgression in wild populations, for example, outbreeding depression, genetic swamping, maladaptation, and unexpected loss of genetic diversity. In the case of outbreeding depression, two management strategies have been proposed to mitigate its deleterious effects: the selective removal of admixed individuals and the introduction of one parental stock to encourage backcrossing . While t


Tilia cordata in Denmark based on tests of 91 trees selected from 12 isolated populations. We used quantitative analysis of spring phenology and population genetic analysis based on SSR markers to infer the likely historical genetic processes within and among populations. High genetic variation within and among populations was observed in spring phenology, which correlated with spring temperatures at the origin of the tested T. cordata trees. The population genetic analysis revealed significant differentiation among the populations, but with no clear sign of isolation by distance. We infer the findings as indications of ongoing fine scale selection in favor of local growth conditions made possible by limited gene flow among the small and fragmented populations. This hypothesis fits well with reports of limited fruiting in the investigated Danish T. cordata populations, while the species is known for its ability to propagate vegetatively by root suckers. Our results suggest that both divergent selection and genetic drift may have played important roles in forming the genetic patterns of T. cordata at its northern distribution limit. However, we also speculate that epigenetic mechanism arising from the original population environment could have created similar patterns in regulating the spring phenology.We assessed the level of geographic differentiation of  Being close to its Northern limits, native Danish T. cordata mostly occur in small isolated populations in ancient forests  combined with very low level of gene flow among the presently very fragmented populations has led to adaptation at a very local scale in Denmark. Also, we study the level of genetic diversity based on the expectation that the life‐history characteristics of the species such as pollination mechanism determine the genetic differentiation happening within and among populations.QST value) with population differentiation based on putative neutral SSR markers . The presence of divergent natural selection will be indicated by QST > FST and uniform or stabilizing selection by QST < FST, while QST = FST suggests that genetic drift is the major driver behind differentiation among populations in the studied traits  selected for the Danish genetic resource conservation program  is the random effect of clones within population, and εijkl is the residual. The broad sense heritability (H2) was calculated according to Falconer and Mackay  variance in the clonal trial. We estimated the expected response to selection (R) for bud burst using breeder's equation following Falconer and Mackay  to fully unfolded leaves (score 6). From these bud burst data, population values  and variance components between populations and between clones within populations were estimated using model d Mackay  as VG/d Mackay  as folloR = iH2√V,P where i is the selection intensity, H2 is the broad sense heritability, and VP is the phenotypic variance.We used a scenario based on selection of the 5% and 10% most extreme phenotypes. We compared this measure of expected response from one round of strong selection with the present differences among populations in order to illustrate the magnitude of the present levels of population differentiation in timing of budburst.QST = VPOP/(VPOP + 2VG), where VPOP is the variance between populations and VG is the estimated genetic variance of the clones. QST values are downwards biased as we use the total genetic  variance as proxy for the additive genetic variance , using approximately 40 mg of leaf material and following the manufactures instructions. The samples were genotyped for nine nuclear microsatellites developed by Phuekvilai and Wolff , expected heterozygosity (He), number of observed alleles (Na), effective number of alleles (Ne), and allelic richness calculated via rarefaction (Na[rar]). The first measures were calculated in GenAlEx ver. 6.5  was correlated against the minimum May temperatures at site of origin in order to test whether the observed patterns indicate climate adaptation to the risk of early spring frost. Population bud burst scores were weighted by the inverse of their variance for increased precision in the procedure REG in SAS , and the broad sense heritability for bud burst was 0.44 and 0.53 for the two assessments, respectively  at the 12 original population sites belonging to the four climatically distinct eco‐geographic regions in Denmark   was <1°C. The average bud burst score ranged between 1.34 and 2.93 when assessed in April 2004 and between 2.14 and 3.28 when assessed in May 2006  was found between the southwest and north eco‐geographic regions. However, population Fst values and their corresponding geographic distance were not correlated   run on GenAlEx revealed no patterns among the 12 populations studied Figure . Hence, nt Table . Largest) Figure .4T. cordata distribution in Denmark  even though there is little differentiation among populations at the molecular level . The populations grouped within each eco‐geographic region showed a clear pattern in their correlation between phenology and temperature in spring. This suggests that these populations are isolated by environment rather than distance  suggest that in at least some species the mechanism may be very efficient . Click here for additional data file. Click here for additional data file.


Apodemus agrarius, is the most common mammal in Korea. Although microsatellite loci for the species have been identified from populations in southwestern China, amplification of those markers for Korean populations have been unsuccessful. The complicated taxonomy of Korean striped field mouse including populations on Jeju Island (A. a chejuensis) necessitates identification of additional molecular markers.The striped field mouse, A. a. chejuensis and tested these new markers against samples of both A. a chejuensis and A. a coreae, the mainland taxon. All 17 loci were amplified successfully for both taxa. Of the total 17 loci, one locus failed to amplify for a population on Heuksan Island. The cross-species transferability was also tested with the allied taxon, A. peninsulae and confirmed successful for 12 loci.We applied 454 pyrosequencing systems to develop a suite of microsatellite markers. Muscle tissue was harvested and sequenced from 30 Jeju striped field mouse specimens which yielded 12,165 reads with a mean length per read of 287 bp. From these reads, we identified 17 microsatellite loci for These newly developed markers will benefit studies of genetic structure, evolution, and resolving taxonomic problems of striped field mice and allied taxa in Korea. Apodemus agrarius  is widely distributed throughout Eurasia [A. a mantchuricus, A. a. chejuensis, A. a. pallenscens, and A. a. coreae) have been reported, but only A. a. chejuensis on Jeju Island has a definitive geographic barrier from the other subspecies [A. a. chejuensis has changed frequently in rank between species and subspecies. The striped field mouse is the first known vector of Hanta virus, which killed roughly 3000 United Nations soldiers per year during the Korean War, which has attracted great attention by epidemiologists [With 24 subspecies, the striped field mouse,  Pallas, 771 is wibspecies . Based obspecies , and mitbspecies –11, the ologists . Becauseologists .Simple Sequence Repeats  are one of the most common and efficient nuclear DNA markers for population genetics and phylogenetic studies of recently diverged taxa because they are multiallelic, highly polymorphic, abundant and show a codominant mode of inheritance , 14. HowA. a. chejuensis and its relationship to mainland species should be examined using both haplotypic  and genotypic molecular markers (nuclear DNA markers). Wu et al. [A. a chejuensis will be applicable for the mainland taxon, A. a coreae assuming their taxonomic status is different. Therefore, we developed 17 microsatellite loci from A. a. chejuensis for future investigation of genetic properties of the striped field mouse and then tested cross transferability for the markers against A. a coreae samples from the mainland.To address ongoing taxonomic debates, the status of u et al.  developeu et al. . Thus, nu et al. . Given tA. a. chejuensis collected on Jeju Island to develop microsatellites loci. We collected 15 individuals each at Yongdu-dong (YD), Jeju-si (N33°31′08.72″ E126°29′47.77″) and 15 individuals at Beophwan-dong (BH), Seogwipo-si, Korea (N33°24′42.97″ E126°51′52.74″). We captured mice in Sherman traps following guidelines of the American Society of Mammalogists [We used muscle tissues of alogists . SpecimeGenomic DNA was extracted using DNeasy Blood & Tissue Kit . The isolated DNA was visualized on 1% agarose gel and quantified in NanoDrop 2000 . We used a total amount of over 2 μg with concentration of 50 ng/μL or higher for 454 pyrosequencing library preparation. Library preparation, amplification, and sequencing were conducted at Macrogen Inc. . Briefly, after DNA quality control steps, isolated genomic DNAs were fragmented using restriction enzymes and tagged them with two multiplex identifiers. After amplification of DNA fragments, the prepared libraries were pooled and sequenced in 454 GS FLX platform (Roche).2, 0.5 μl of primers each, and 0.3 U of Taq polymerase . PCR conditions were follows: initial denaturation at 95 °C for 5 min followed by 35 cycles of denaturation at 94 °C for 60 s, annealing at 45–60 °C for 60 s, elongation at 72 °C for 90 s, and a final extension at 72 °C for 10 min. PCR products were selected and sequenced to confirm whether they contained microsatellite sequences.Candidate loci for microsatellites were selected using QDD3 software . A totalA M13-tail  was added to the 5′ end of each forward primers while a pig tail (GTTTCTT) was added to the 5′ end of each reverse primers. For multiplex PCR, we performed PCR amplifications in a total reaction volume of 16 μl containing 5 μl of 2× QIAGEN Multiplex PCR master mix (QIAGEN), 0.08 μl of M13-tailed forward primer, 0.8 μl of pig tailed reverse primer, 0.3 μl of templated DNA and 0.16 μl of each of fluorescence primer (FAM/VIC/PET/NED). Multiplex PCR cycling conditions were as follows: initial denaturation at 95 °C for 15 min followed by denaturation at 95 °C for 30 s, annealing  for 90 s and 72 °C for 30 s, with a final elongation at 72 °C for 20 min.).A. a chejuensis) from two populations (YD and BH) with the newly designed microsatellites. The amplified fragments were separated in ABI 3730xl DNA analyzer  and GeneMapper software v3.7 (Applied Biosystems) was used for manual scoring.We genotyped 30 Jeju striped field mice (Agrarius peninsulae) and one subspecies (A. a. coreae) using the 17 developed markers with the same PCR conditions. Additionally, we added an A. agrarius sample collected from Heuksan Island in the cross-species transferability run because Jo et al. [A. agrarius population in Heuksan Island might be a newly diverged subspecies from the mainland populations (A. a. coreae) in Korea.To test for cross-species transferability, we amplified one congener , observed heterozygosity (HO), expected heterozygosity (HE) and population divergence (FST) between the two populations (BH and YD). Polymorphic information contents (PIC) were also estimated in CENES software . We tested whether significant deviation from Hardy-Weinberg equilibrium (HWE) within each population across all amplified loci in ARLEQUIN 3.5. Linkage disequilibrium (LD) between pairs of loci within each population was tested using GENEPOP 4.2.1 [ST for all 30 individuals to examine clustering pattern among the individual genotypes in GENALEX v. 6.5 [The following genetic diversity parameters were calculated using ARLEQUIN 3.5 : the numOP 4.2.1 , 22. AllOP 4.2.1 . We perfOP 4.2.1 . We alsoX v. 6.5 .Four hundred and fifty-four pyrosequencing produced 12,165 reads with a mean length of 287 bp. We selected 335 candidate microsatellite loci from the produced reads and confirmed that 17 loci were polymorphic . No linkage disequilibrium was detected at any pair of loci.The number of alleles per locus in the two populations of ST (0.05) estimated between the two Jeju striped field mouse populations was not significantly different from zero (P > 0.99). The AMOVA results revealed that in the two populations most of genetic variation (88%) was harbored within each population, whereas among population genetic variation was proportionally minor  in most of the literature despite its high genetic divergence from mainland populations as revealed in a microsatellite analysis [A. a chejuensis might be more closely related to the mainland populations of A. a. coreae than the populations on Heuksan Island. Intensive population level studies with these developed markers might elucidate the true phylogenetic relationships among these three taxa.Cross-species amplification examined for a subspecies, ae Table . Except in Korea . In contanalysis . Our croA. agrarius is the deficiency of genetic markers [A. agrarius in not only the Korean Peninsula but the entire distribution for the species. The genetic markers might also be used to establish a management strategy for A. a. chejuensis, the most common endemic rodent on Jeju Island.Although this species is the main vector of Hanta virus and the most common mammal in the Korean Peninsula, few studies have addressed populations of the striped field mouse in Korea. One of the limitations in the study of  markers . The mic