Callosobruchus chinensis (Linnaeus) is one of the most destructive pests of leguminous seeds. Genetic differentiation and diversity analysis of 345 C. chinensis individuals from 23 geographic populations using 20 polymorphic simple sequence repeats revealed a total of 149 alleles with an average of 7.45 alleles per locus. The average Shannon's information index was 1.015. The gene flow and genetic differentiation rate values at the 20 loci ranged from 0.201 to 1.841 and 11.0–47.2%, with averages of 0.849 and 24.4%, respectively. In the 23 geographic populations, the effective number of alleles and observed heterozygosity ranged from 1.441 to 2.218 and 0.191–0.410, respectively. Shannon's information index ranged from 0.357 to 0.949, with the highest value in Hohhot and the lowest in Rudong. In all comparisons, the fixation index (FST) values ranged from 0.049 to 0.441 with a total FST value of 0.254 among the 23 C. chinensis populations, indicating a moderate level of genetic differentiation and gene flow among these populations. Analysis of molecular variance revealed that the genetic variation within populations accounted for 76.7% of the total genetic variation. The genetic similarity values between populations varied from 0.617 to 0.969, whereas genetic distances varied from 0.032 to 0.483. Using unweighted pair-group method using arithmetical averages cluster analysis, the 23 geographic collections were classified into four distinct genetic groups but most of them were clustered into a single group. The pattern of the three concentrated groups from polymerase chain reactions analysis showed a somewhat different result with cluster. As a traditional human food resource, legumes are important crops for planting structure adjustment, international trade and increasing the income of mountain farmers in China. In recent years, human health consciousness has increased and the nutritive value of legumes has been recognized. Thus, legumes have increasingly become the focus of agricultural production. China ranks first in the world for food legume yield and number of types produced. Also, as the world's second-biggest exporter, China accounts for 12% of global food legume exports Liu, . TherefoCallosobruchus chinensis L. (Coleoptera: Bruchidae) is one of the most serious pests of leguminous stored seeds in Asia    , pea (Pisum sativum L.), soybean (Glycine max L. Merr.) , pigeon pea [Cajanus cajan (L.) Millspaugh] , peanut (Arachis hypogaea L.), and lotus seed (Nelumbo nucifera Gaertn.)           populations  or microsatellite DNA markers are extensively used in the construction of genetic linkage maps, the evaluation of genetic diversity, ecology and evolution studies, and many other types of studies. Microsatellites are popular genetic markers because of their co-dominance, high abundance and polymorphism rates, multi-allelic nature, and rapid detection of alleles by a wide variety of methods  gene was sequenced for genetic diversity analysis of eight populations of C. chinensis from Japan, Korea and Taiwan collected from different habitats, and six haplotypes were detected based on the COI sequence differences . The DNA concentration was measured using a Qubit® DNA Assay Kit in a Qubit® 2.0 Fluorometer . The DNA was stored at −20°C for subsequent analyses.The total genomic DNA of a single adult with its gut removed was extracted with the TIANamp Genomic DNA Kit according to the manufacturer's instructions . The quality of the extracted DNA was monitored on 1.5% agarose gels. DNA purity was checked using the NanoPhotometeret al.  and 30 ng of DNA template. Reactions were performed using a GeneAmp® PCR System 9700 thermal cycler  programmed for 94°C for 4 min, followed by 35 cycles of 94°C for 30 s, 50–60°C  for 30 s and 72°C for 60 s. A final extension was performed at 72°C for 10 min. The PCR products were analyzed by electrophoresis on 8.0% non-denaturing polyacrylamide gels and silver stained. The band sizes were determined roughly based on a 100 bp DNA ladder .Simple sequence repeat analysis was performed following the procedure of Duan et al. b. PCR weet al., Na), number of effective alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), Nei's expected heterozygosity (Nei), Shannon's information index (I), F-statistics , gene flow (Nm), Nei's genetic identity and genetic distance (D) between various geographical populations. Significance analysis was performed with SPSS10.0 software .The fragment lengths of the alleles from each individual were recorded from the banding patterns of SSR amplifications. In order to reduce genotyping errors of microsatellites, MICROCHECKER 2.2.3 soft was used to remove or adjust null alleles (van Oosterhout FST (θ) value  was determined using the equation Nm = 0.5(1 − FST)/FST  clustering trees using the MEGA 4 software .MICRO-CHECKER estimated 0.069 of frequency of null alleles, which coincided with the excellent amplification of these microsatellite loci among ulations . A totalulations . The effulations . In addiFIS, IT, FSTF) and measuring gene flow (Nm) at each locus. The F-statistics at each locus among the 23 populations are listed in Nm < 1). The other eight loci, including CCM139, CCM168, CCM2, CCM40, CCM49, CCM33, CCM162 and CCM4, showed 1 < Nm < 2; none of the loci had low genetic differentiation among populations (Nm > 4). This indicated that the loci CCM72, CCM118, CCM1, CCM83, CCM29, CCM56, CCM125, CCM143, CCM71, CCM46, CCM108 and CCM16 had relatively large genetic differentiation among populations while CCM139, CCM168, CCM2, CCM40, CCM49, CCM33, CCM162 and CCM4 had moderate genetic differentiation  and gene flow (Nm) were estimated from the 20 SSR loci between C. chinensis populations  and RD populations, followed by FST values of 0.440 and 0.430 between the Changde (CD) and TS, and CD and Guangan (GA) populations, respectively. Although the FST value between the TS and RD is greater than that between CD and TS and between CD and GA, there are no significant differences between them. The corresponding minimum Nm values were 0.633, 0.640 and 0.663, respectively, which suggested considerable genetic differentiation between these pairwise populations. In contrast, the FST values between the Urumuqi (UM) and Lingchuan (LC), and Enshi (ES) and Xinye (XY) populations were 0.049 and 0.050, with corresponding Nm values of 9.788 and 9.581, respectively, demonstrating very low genetic differentiation and sufficient gene flow between the two pairwise populations. AMOVA analysis indicated that 76.7% of the total molecular variance was due to differences within geographic regions and 23.3% of the variance was associated with differences among populations  representing important regional locations for legume production and storage in China. The present study is the first attempt at assessing the genetic diversity of C. chinensis using the SSR marker technique. It has demonstrated the validity and suitability of using SSR markers to detect genetic variation among C. chinensis populations.Microsatellite loci are powerful tools for population genetics studies because of the reproducibility and precision of these markers in detecting multiple alleles. Here, we used 20 microsatellite markers developed by Duan et al. b using iC. chinensis populations were 0.4901 and 0.3389, respectively, suggesting a moderate level of genetic diversity among the samples. From this, we demonstrated that the C. chinensis population in ES (Hubei) had the highest genetic diversity, whereas the RD (Jiangsu) population had the lowest genetic diversity. The fixation index (FST) reflects the degree of genetic differentiation among populations. FST is close to 0 when the genetic variation shows no sign of fixation between populations. However, FST is close to 1 when genetic differentiation is at a high level. Gene flow (Nm) is considered one of the major factors in the homogenization of population genetic structure. Because gene flow and genetic drift are mutually antagonistic, exchange of genes can increase the amount of genetic variation within populations while decreasing differentiation between populations  and RD (Jiangsu), and TS and Changde (Hunan), with distances of more than 1300 km from TS to RD and Changde. There are major differences in growth seasons, weather conditions, agricultural practices and legume varieties between these regions. In addition, based on our surveys, the Jilü series varieties and landraces were cultivated in TS, while Sulü and Tongcan series varieties and local breeds were mainly cultivated in RD. Moreover, mung bean and adzuki bean were main legumes in TS, whereas faba bean, pea and cowpea were cultivated widely in RD. Therefore, legume varieties varied greatly between the regions. In addition, the lack of legume seed exchange indeed existed between the regions due to different kinds of legumes, lack of communication and so on. In contrast, although the two areas are approximately 3000 km apart, the UM, Xinjiang and LC, Shanxi collections had the lowest genetic variation. This is understandable because frequent seed exchanges have occurred and the same varieties have been planted and stored in both areas for several years, furthermore, C. chinensis is apt to communicate and diffuse along with legume seeds by means of egg, larva, pupa or adult, which results in interaction of C. chinensis between the two areas and identical host selection pressures in both populations.Gene heterozygosity is an optimal parameter to measure genetic variation within populations. The average heterozygosity approximately reflects the level of genetic variation. The observed heterozygosity did not significantly deviate from expected heterozygosity at most of the loci, which confirmed validity of these loci among the collections in this study. The average expected and observed heterozygosity values for the 20 microsatellite loci and 23 C. chinensis populations from different regions, which enhances genetic variation among populations but decreases genetic differentiation within populations. However, frequent exchanges of legume seeds have taken place via trading and communication among some production areas for many years, which very likely includes C. chinensis eggs, nymphs, pupas, or adults. Therefore, the spread and diffusion of this pest increases the mating and gene flow among different collections and enhances heterogenization within populations.Based on AMOVA analysis, 23.3% of the total variation was found among regions, whereas 76.7% variance was attributable to population divergence within the regions. China is a large country with complex terrain and hence different levels of geographical isolation arise between As shown in the UPGMA clustering plot based on genetic distance between populations, the maximum genetic similarity was between the HF and RD collections, followed by the UM and LC, and ES and XY populations, whereas the WL and GA populations shared the minimum genetic similarity, followed by the WL and BB populations. The geographic distance between WL and GA is less than 300 km, but both of these regions are mountainous, and the food legume varieties planted in the two areas differ greatly; hence, the host selection pressures differ and there is limited communication, which has resulted in geographical isolation and limited exchange of genetic information between the two populations.C. chinensis from these regions and then leads to a decline in genetic differentiation therefore individuals from Cluster I and Cluster II comprised a principal component.The pattern of three groups from PCA analysis looked different from cluster result with four genetic groups. Compared with C. chinensis is apt to diffuse and spread by way of seed trade and communication, which results in frequent gene flow and decreases heterogeneity among collections from different regions in China. Therefore, our findings that there is high adaptability and moderate genetic diversity among C. chinensis populations are understandable and reasonable, and should help to develop a control strategy for C. chinensis.High adaptability to different environments or hosts is usually correlated with abundant genetic diversity. However,


Pinus koraiensis has a unique distribution in northeast Asia. The Changbai Mountains and the Korean peninsula (CM/KP) are usually considered to be the LGM refugia for P. koraiensis. However, the Xiaoxingan Range (XR), at the northern part of this species’ distribution, is another possible refugium. We used chloroplast sequencing and ten nuclear single-copy gene loci to calculate the genetic diversity pattern of P. koraiensis. The probabilities of a single LGM refugium and of multiple LGM refugia were calculated based on approximate Bayesian computation. The effect of the latitudinal gradient on genetic diversity was not significant. However, unique alleles occurred at low frequencies in CM/KP and XR. A conservative estimate of the coalescence time between CM/KP and XR is 0.4 million years ago, a time prior to the LGM. Gene flow between CM/KP and XR was estimated to be more than one in per generation, an amount that may be sufficient to limit genetic divergence between the regions. Our study strongly supports the hypothesis that XR was another LGM refugium in addition to CM/KP.The northern microrefugia that existed during the Last Glacial Maximum (LGM) are a key factor in the demographic history of species.  Historical climate change, especially during the last glacial maximum, has affected the demographic history of species and shaped modern distributions. Enlarged ice caps in North America and Europe during the LGM caused significant local extinctions of temperate flora in their northern ranges1457Pinus koraiensis Siebold & Zuccarini) is distributed in Northeast China and adjacent regions including the Korean peninsula and the Russian Far East  and scattered locations in the Japanese archipelago. Pollen records indicate that mixed forest in NEA was replaced by boreal forest, tundra or steppe during the LGM. Very low amounts of Pinus pollen have been found during this period49Korean pine . The Changbai Mountains (CM) can act as a barrier blocking cold air masses from Siberia. Therefore, the southern CM and the Korean peninsula (KP) are areas that potentially supported relict populations of Korean pine during the LGM. Existing phylogeographic studies on plants distributed in NEA have found relatively higher genetic diversity in CM and/or KP, suggesting possible LGM refugia in CM and/or KPet al.et al.et al.Pinus222324Kremenetski In this study, we utilized multiple nsc DNA markers and robust statistical phylogeographical approaches. Our goal was to assess the possibility of XR as another LGM refugium. The specific questions asked are as follows: (1) Do NEA populations have a genetic diversity gradient related to latitude? Does the XR population have unique alleles? (2) What were the coalescence times of the continental Asian Korean pine populations before and after the LGM? (3) What was the direction of migration between the CM and the XR populations? If only one LGM refugium existed, in CM/KP, the XR populations probably originated from postglaciation expansion from the south. Hence, we would expect a significant cline in genetic diversity from south to north, and no unique alleles would be expected in XR populations. Based on this hypothesis, the coalescence time of the continental populations would be after the LGM, and a northward migration would be expected. If LGM refugia existed in both CM/KP and XR, a cline in genetic diversity is less likely. Unique alleles might exist in both CM/KP and XR populations. In a multiple refugia hypothesis, we would expect a long coalescence time for the continental populations, at least before the LGM. Both northward and southward migrations are expected if both CM/KP and XR supported relict populations during the LGM.psbA-trnH was 597 bp. This fragment generated four haplotypes in the continental populations, with three polymorphic sites. The grey haplotype, CP1, was most dominant, occurring in all studied populations. The less frequent CP2 haplotype was found in both CM and XR. CP3 was only found in CM (populations LHS and XBH), while CP4 was only found in XR (population TWH)  .πt) was 0.00295, ranging from 0.00866 (a3ip2) to 0.00023 (CL180Contig1_03). The nucleotide diversity of silent sites (πs) was 0.00537 (0–0.00866), and that of nonsynonymous sites (πa) was 0.00062 (0–0.00285). Detailed information on the genetic diversity of each locus is presented in D, Fu and Li’s D* and F*, no nsc loci departed significantly from the neutral hypothesis , and KP also had unique alleles at five loci   .πX) ranged from 0.0014 to 0.0036. Two CM populations, RNZ and TU, had the lowest genetic diversity (0.0014), while a northern marginal population of CM (RH) had the highest genetic diversity (0.0036). Another two populations, BS (in CM) and YL (in XR), had relatively high genetic diversity  (AR) and private allelic richness (PAR), while CBS (in CM) had the lowest AR and PAR (The genetic diversity of each population (ctively) , Fig. 1. and PAR .πX , AR , or PAR (R = -0.475 P = 0.073). A Mantel test showed no significant pattern of isolation by distance .Pearson correlation analyses indicated no significant correlation between latitude and The genetic diversity pattern of continental Korean pine populations fit the MRM best, with the posterior probability equal to 1 . The BayS = 4.34 × 104 and NN = 0.09 × 104, Nem) was slightly larger than 1 individual , while the contrasting direction of migration was less than 1 individual . The coalescence time of the CM/KP and XR populations was 3.96 × 104 generations ago (95% HPD: 0.50 × 104–7.58 × 104). The ancestral population was slightly larger than the population of the CM/KP region (median NA = 5.39 × 104).The long-term effective population size of the CM/KP region was nearly 50 times larger than that of the XR region , P. sylvestris var. mongolica (six chlorotypes)Larix sibirica (one chlorotype)Juglans mandschurica (one chlorotype)Quercus mongolica (four chlorotypes)Acer mono (four chlorotypes)πt), 0.00062 (πa), and 0.00537(πs), which were consistent with levels of genetic diversity reviewed by Leffler et al.Pinus specieset al.P. sylvestris var. mongolica had the lowest diversity based on seven nsc loci , but this was greater than that of Korean pine. Populations of Korean pine from the CM/KP and XR regions had unique alleles in the chloroplast and nuclear genome, but the latitudinal gradient of population genetic diversity was not significant. ABC simulations strongly supported the theory that CM/KP and XR regions had an ancestral coalescence time long before the LGM. These findings suggest that the continental Korean pine probably had multiple refugia populations during the LGM.Based on ten nsc DNA loci and one chloroplast intergenic fragment, we found low genetic diversity within mainland populations of Korean pine. This result was consistent with another report using mitochondria and chloroplasts by Aizawa F. mandschuricaQ. mongolica , and J. mandshurica30Picea chihuahuana, naturally distributed in Northwestern Mexico, shows two spatially separated mitotypes, which disperse via seeds. In contrast, no phylogeographic structure was found from chloroplast markers, which are dispersed via pollen in conifer speciesWe found no significant gradients related to latitude and no pattern of isolation by distance (P > 0.05). Many populations located in CM/KP had high genetic variation and uniqueness   , Fig. 4.CL180Contig1_03 was unique to XR, and H4 of 0_1688_02 was unique to CM/KP (Nem) due to population expansion and the strong dispersal capability of pine pollen (discussed above). WrightAlthough CM/KP and XR probably had separate refugia during the glaciation period, the populations from the two mountain ranges shared almost all dominant haplotypes in both nuclear and chloroplast markers  and 2, wto CM/KP . From anto CM/KP , Fig. 4.Fraxinus mandschurica is found in XR , and this location has been considered a northern microrefugium. However, we again note that long-term average migration from XR to CM/KP is quite low, less than one individual per generation  and the Xiaoxingan Range had relict populations of Korean pine during the LGM. The coalescence time between the populations of the two mountain ranges was at least 5000 generations ago, i.e., an estimated 0.4 million years ago. Although the two mountain ranges shared most of the total genetic variation, unique alleles exist in both regions for all studied markers. In contrast to the macrorefugia in the Changbai Mts. and its adjacent area, the microrefugium in the Xiaoxingan Range, combined with strong gene flow between regions, may have prevented genetic differentiation and eliminated the pattern of genetic variation over the species’ range.Due to the limited samples from the Korean peninsula and the Sikhote-Alin Mts., we treated those two regions and the Changbai Mts. as a single unit. Although the samples from the Korean peninsula were limited, we found unique alleles occurring with low frequency there . Some stDuring 2009–2012, we collected leaf samples from 75 adult trees in 21 natural populations covering the entire range of Korean pine in the NEA. From each population, 2–9 individuals were sampled, and the sampled individuals were at least 30 m apart from each other . The neepsbA-trnH, trnS-trnG and trnL-trnFtrnS-trnG and trnL-trnF . Therefore, we only report the results from psbA-trnH, which was polymorphic. PCR products were directly sequenced using an ABI 3730 automated sequencer (Applied Biosystems)from BGI Tech Co., Ltd., Beijing, China. Each haplotype found was also verified by a cloning method. A pGEM–T Easy Vector  was used in the cloning procedure, and at least five clones were sequenced. All sequence data have been deposited in GenBank, with accession nos. KP182424-KP182921, KT993573-KT995096.Total DNA was extracted from needles using a Plant Genomic DNA Kit . We selected ten polymorphic nsc loci based on 44 loci initially developed for other pine species2324http://www.codoncode.com/aligner/) with the “Muscle” module. Each individual sequence was independently checked by two researchers, and heterozygous sites were marked by hand. Sequences of all 10 nsc loci were phased in DNAsp 5.10.01 using default settingsIFG8612 had two indels (3 bp and 55 bp). We replaced the two deletions of IFG8612 with almost the same sequence as the inserts, with only one base pair difference. Hence, each indel was treated as a nucleotide substitution and assumed to evolve by nucleotide substitution.Sequences were aligned using the CodonCode Aligner 3.6.1 Program (H), haplotype diversity (Hd), the number of segregating sites (S)θw), silent sites (θws), and the nucleotide diversity at total sites (πt), silent sites (πs), and nonsynonymous sites (πa)DD* and F*Population genetic variation was assessed by the following parameters: the observed number of haplotypes (Median-joining networks were reconstructed in Network 4.6.1.2 for haplotypes found in each of the 10 nsc loci and the cpDNAπXi) and between populations (πXYi) were calculated for each sampled population and each locus (i) using Alequin 3.5 softwareπX) and between populations (πXY) were calculated by the sum πXi or πXYi of each locus divided by the total sequence length of the ten nsc loci.Pairwise genetic differences within populations . Mantel tests of the correlation between genetic distance (πXY) and geographic distance (kilometers) were calculated using GenAIEx 6.1The Pearson correlation coefficient between latitude and the genetic diversity indices was calculated and tested using R 3.1.0  hypothesized that CM/KP populations and XR populations coalesced after the LGM, while the multiple LGM refugia (MRM) ABC model hypothesized that CM/KP and XR populations coalesced before the LGM. In both models, the migration direction and magnitude were unrestricted. We had limited samples for KP and the Sikhote-Alin Mts. , so we treated populations in CM, KP and the Sikhote-Alin Mts. as a single southern population (marked as CM/KP), while we treated populations in XR as a northern population (marked as XR). Populations FZ, QS and RH were located far from the center of CM and near the XR region . Hence, −9 according to a previous estimate for Pinus speciesNem: 0–1000). Details of the models and the msABC executable statements are shown in In the ABC models, we set the average mutation rate for the ten nsc loci as 1.31× 10SπFST) and shared allelic richness. The Bayes factor was used to determine the best supported model using the observed dataFor each model, we simulated one million steps. Model selection was conducted in the statistics package abc in R 3.1.0. The “mnlogistic” method was used for model selection, with a tolerance rate of 0.001. We used 16 summary statistics that were closely related to gene flow and effective population size, including the mean and variance of segregating sites within populations and between populations For the best supported model, an additional four million steps were simulated. With the five million simulations, we estimated parameters such as the coalescence time of the CM/KP and XR populations, effective population size, and the migration rate between the CM/KP and XR populations. To ensure that the estimated range was located in the prior range, a log transformation was applied during the procedure. Neuronet’s method with nnet = 50 was used in the parameter estimation.How to cite this article: Bao, L. et al. Contributions of multiple refugia during the last glacial period to current mainland populations of Korean pine (Pinus koraiensis). Sci. Rep.5, 18608; doi: 10.1038/srep18608 (2015).


Acropora cervicornis, a threatened, keystone reef-building coral has undergone severe declines (>90 %) throughout the Caribbean. These declines could reduce genetic variation and thus hamper the species’ ability to adapt. Active restoration strategies are a common conservation approach to mitigate species' declines and require genetic data on surviving populations to efficiently respond to declines while maintaining the genetic diversity needed to adapt to changing conditions. To evaluate active restoration strategies for the staghorn coral, the genetic diversity of A. cervicornis within and among populations was assessed in 77 individuals collected from 68 locations along the Florida Reef Tract (FRT) and in the Dominican Republic.ST values and significant divergence relative to distance. There are also significant differences in SNP allele frequencies over small spatial scales, exemplified by the large FST values among corals collected within Miami-Dade county.Genotyping by Sequencing (GBS) identified 4,764 single nucleotide polymorphisms (SNPs). Pairwise nucleotide differences (π) within a population are large (~37 %) and similar to π across all individuals. This high level of genetic diversity along the FRT is similar to the diversity within a small, isolated reef. Much of the genetic diversity (>90 %) exists within a population, yet GBS analysis shows significant variation along the FRT, including 300 SNPs with significant FLarge standing diversity was found within each population even after recent declines in abundance, including significant, potentially adaptive divergence over short distances. The data here inform conservation and management actions by uncovering population structure and high levels of diversity maintained within coral collections among sites previously shown to have little genetic divergence. More broadly, this approach demonstrates the power of GBS to resolve differences among individuals and identify subtle genetic structure, informing conservation goals with evolutionary implications. Acropora has experienced particularly large declines over the last 30 years, with losses exceeding 95 % in some areas [Acropora cervicornis is the fastest growing Caribbean coral [Caribbean coral reef communities have lost nearly 80 % of coral cover since the early 1980s , 3. Amonme areas  and up tme areas . The staan coral  and is tan coral –13. WithA. cervicornis can negatively impact this species’ genetic diversity. Reduced populations may lose uniquely adapted individuals and rare alleles, each important for adaptation and potential recovery. Reduced genetic diversity also can compromise successful sexual reproduction by decreasing the potential of cross-fertilization . Since ng event . To reporonments , evaluatA. cervicornis shows significant regional structure  for populations separated by more than 500 km in both nuclear and mitochondrial genes, suggesting restricted gene flow over large distances and potentially isolated populations [A. cervicornis using microsatellites showed little population differentiation and no significant population structure [A. palmata into A. cervicornis [Genetic variation in ulations . Yet, witructure ; these rtructure . Althougtructure . This ravicornis . The finA. cervicornis populations using individuals collected throughout the FRT) with individuals from the Dominican Republic used as an outgroup  [A total of 77 samples were collected and analyzed: 66 individuals along the Florida Reef Tract and 11 individuals from around the Dominican Republic  . SamplesCollections were made under the following permits: Convention on International Trade in Endangered Species of Wild Fauna and Flora Permits 11US835702/9, United States Department of the Interior National Park Service Scientific Research and Collecting Permits BISC-2013-SCI-0010, NOAA Florida Keys National Marine Sanctuary Research Permit FKNMS-2011-150, and Florida Fish and Wildlife Conservation Commission Special Activity License SAL-13-1086-SCRP.Genomic DNA was isolated using a silica column as described in . IsolateA. digitifera genome (the only published acroporid genome) to prevent the inclusion of Symbiodinium DNA, which would be present in background levels in any coral sample. Aligning to a genome also enhances the identification of allelic SNPs at a specific locus because sequence reads that match two or more locations in the genome are discarded [A. digitifera genome results in unique sequence tags, which are aligned, 64 bp sequence reads that have a unique genome location. The TASSEL pipeline with BWA and Bowtie was used to call SNPs with a minimum allele frequency of at least 5 % and a minimum of 5 reads per locus to reduce the impact of sequencing error . Only loci called by both alignment tools were used to produce a conservative selection of loci for analysis. Before downstream processing, SNPs were filtered using an iterative progression to select individuals with at least 70 % of the called loci and loci that were present in at least 90 % of samples for analyses. Arlequin v.3.11 [O), expected heterozygosity (HE) and fixation index (FST). Loci with significantly greater observed than expected heterozygosity (p < 0.01) were discarded from analysis, and loci with significant linkage-disequilibrium  were identified using Tassel [A. digitifera genome) and removed.Raw Illumina sequences were received from Elim Biopharmaceuticals and processed using the GBS analysis pipeline TASSEL 4.0 . The TASiscarded . This sen v.3.11  was usedg Tassel  with a 1ST outlier values , was calculated using the ‘ape’ package in R . SNP π ved data, ), the pred data,  was usedtructure  was usedtructure . RaXML wtructure  with 100tructure ) was seltructure . Discrimtructure , 33. Thetructure . DAPC waTable versus polymorphisms between alleles and, iii) eliminating SNPs in linkage-disequilibrium [Next-generation sequencing and identification of informative SNPs requires: i) filtering the data such that most SNPs occur in most individuals, ii) removing inappropriate SNPs that represent nucleotide differences between paralogs (different loci) ilibrium , 36–40. A. digitifera genome [A. digitifera genome was used to remove Symbiodinium sequences. In total, 868,023 unique sequence tags  aligned to the published reference genome [A. digitifera genome were not analyzed because of potential background symbiont or bacterial DNA contamination. After preliminary filtering, three individuals were discarded because they had less than 30 % of the sequence reads. It is possible that inefficiencies during library construction led to low numbers of reads in these individuals. The remaining 77 individuals had 400,000 to 2,300,000 reads per individual.Sequencing data returned a total of 159,634,510 sequences and 91,643,894 (57.4 %) were retained because they contained both the barcode and cut site. Then, these retained sequences were aligned to the a genome . Alignmee genome . Sequencp-value < 0.01, or an r2 > 0.20) [Short 64 bp sequences were aligned using two alignment tools, Bowtie  and BWA  > 0.20) . RemovinSymbiodinium may have conserved genes that could align to the A. digitifera genome. This would seem unlikely because if there were multiple types of Symbiodinium, these should have excessive observed heterozygosity and would be filtered out. Yet, to examine this possibility we used BLAST-N with all sequence tags that define the 4,764 SNP against the Symbiodinium minutum Mf 1.05b.01 (taxid:1280413) genome. Only one tag had an e-value < 10−5, and this sequence only matched 83 % of the genome for 49 of the 64 bp . Eight more tags had e-values < 1 %, but none of these matched more than half of the sequence tag. Thus, it seems unlikely that the alignments contain Symbiodinium sequences.There is an additional concern that A. cervicornis in Broward County is growing at the edge of its spatial range, so high diversity may be unexpected. Importantly, within each population π measurements are comparable to π across populations  between samples. The π within each FRT population  averages 37 % with a range of 23.9–44.0 % .The 57 individuals from the Florida nursery collections  a hierarchical AMOVA , 2) analT values , 3) a Map < 0.001) among groups, among populations within Florida and within populations , so they may be more reflective of the statistical power of using many loci [An AMOVA of all 4,764 loci for two groups (Florida and DR) with four populations within Florida  shows significant variation , suggesting that most SNPs are evolving independently and the differences among populations are not due to one or a few linked loci. The average distance to the next closest SNP is > 25 kb . These close, non-significant SNPs indicate lack of linkage or selective sweeps and high, long-term standing genetic variation. The individuals sampled from the Miami-Dade nursery should have captured much of the local genetic variation as they were initially collected from a large area (~35 km span), collections were separated by at least 500 m, and all represent unique genets [Among the three Florida transects , there are 300 SNPs with significant Fe genets .Fig. 3LoST values  correlation between genetic variation and spatial distribution; this trend explains approximately 38 % of the genetic variation (R2 = 0.378) and is driven mainly by the differences between Florida and the Dominican Republic, supporting the regional structure previously reported [2 = 0.104). Importantly, the genetic variation explained by geographic separation increases if either Broward or Monroe  is excluded, because these two most distant sub-regions of the FRT are more similar to each other than either is to the spatially intermediate Miami-Dade corals. The results of the Mantel test support the pairwise FST values, which indicate significant structure between Miami-Dade and Monroe/Broward, but little genetic divergence between Monroe and Broward.To further parse differences between sub-regions, a Mantel Test was used to calculate the correlation between genetic and geographic distance. Here, 377 SNPs with significant Freported . When exST value differences between the Miami-Dade nursery and Miami-Dade ‘Wild’ collections, π is similar in both collections , suggesting a change in allele frequencies associated with the local environment. These data suggest there are many genetic differences among populations and genetic diversity is high in each of the three Florida transects. These data also support the conclusion that the differences among collections are not a linear function of geographic distance within Florida; geographically close collections may have more differences that geographically dispersed collections.Using DAPC with 4,764 SNPs shows that the first discriminant function separates the Dominican Republic from the Florida corals, while the second discriminant function separates the four Florida populations Fig. . When onST values. Half or 150 of these SNPs were outliers. Outlier SNPs have FST values with changes in allele frequencies that are not found in 100,000 random permutations of the data and are thought to be due adaptive evolution [Corals from the three Florida transects had 300 loci with significant Fvolution , 59. Altvolution , a steppvolution . Thus weST values . Each of these SNPs has an average of 120 reads among the twenty individuals from Miami-Dade and Wild populations  and over 350 reads among all individuals. Two-hundred and thirty-four (89 %) of these SNPs with significant FST values are significant outliers [A. cervicornis – A. palmata hybrids. Unlike the other collections, which were identified based on morphology and microsatellite tags, the Wild collection was only identified by morphology. Although we have no reason to believe that the Wild samples were hybrids, the fine scale genetic divergence we found is similar to the rare, fine scale structure that was attributed to one-way introgression of A. palmata into A. cervicornis [It has not escaped our attention that the Wild collection of 10 individuals within a single reef within Miami-Dade is different from the Miami-Dade transect collected from the surrounding area. While these individuals from Miami-Dade and Wild are phylogenetically similar to the other samples , the comparison between these two populations shows 260 SNPs with significant Foutliers . The divvicornis . Thus alData presented here suggest that there is potentially much adaptive variation due to subtle environmental differences influencing coral distribution and growth, including temperature, water chemistry, light, nutrients, and sedimentation. This variation may occur over spatial scales as small as individual reefs. Due to the potential for high adaptive variation, introducing a broad range of genotypes along the FRT (such as those housed within nurseries) would enhance the frequency of adaptive genotypes and the subsequent rate of offspring survival. This is especially true if crossings during mass spawning events produce a larger range of genotypes able to take advantage of a large breadth of ecological niches. Thus, the best conservation and restoration strategy may be to increase genetic variation on all spatial scales  as much as possible to provide diversity to cope with changing conditions .This study found substantial genetic variation within existing staghorn populations being raised in coral nurseries. These nursery corals are presently used for coral propagation and outplanted to enhance population recovery of the threatened staghorn coral reefs. Greater than 90 % of the variation among all the samples is found within a nursery’s collection of corals, indicating that these nurseries have captured significant genetic diversity.These GBS data indicate both large variation within populations and adaptive divergence among populations, and should help form policies that guide conservation efforts to restore staghorn coral reefs. We suggest that the caution against moving corals long distances during restoration  should bA. cervicornis. Here, we show, for the first time, population structure across the FRT and high diversity within populations, including within a single reef evidenced as the genetic structure between and among FRT populations. Previous work on A. cervicornis using mtDNA, a few nuclear genes, and microsatellites found no difference among the FRT coral populations [The GBS approach produced genotype frequencies for 4,764 SNPs that allowed for the resolution of population differences unavailable using other techniques –17. Eachulations –17, 62.ST values indicative of adaptive difference. There are also significant differences over small spatial scales, exemplified by differences between Wild and Miami-Dade individuals that were all collected within the same area  is large (37 %) for all collections and similar to GBS measures of π in large outbred populations of 3-spine stickleback or natural populations of yeast [To further develop effective conservation and management plans for this species and other threatened corals considered as candidates for active propagation and restoration, it is essential to understand the extent of genetic variation within and among populations , 17. Usiof yeast , 52.The GBS methodology used here highlights the ability to discover subtle changes in populations by using thousands of loci and large numbers of individuals. Conservation genetics using these high throughput techniques provide a new lens for assessing management implications and population connectivity via important increases in resolution, but also in varied and specific genetic metrics such as population structure, nucleotide diversity, and loci that may be under selection. These data are particularly important to active restoration projects as they give a better understanding of population structure, how and where to relocate coral, and potential repercussions of active intervention. Furthermore, the ability to describe genetic diversity over local to regional distributions enables conservation practitioners to manage resources over appropriate scales, becoming more efficient and effective. GBS allows for increased restoration effectiveness through conservation genetics, while developing a more thorough understanding of threatened coral communities.Acropora cervicornis hapmap (DOI: 10.6070/H4FB50XX) and sequence tags (DOI: 10.6070/H49K4872) are available at LabArchives.com. Sequence files are available at NCBI's BioSample database, accessions SAMN03295587 - SAMN03295662.Raw sequences have been submitted to NCBI as a Sequence Read Archive (SRA). The


Guatemala is a multiethnic and multilingual country located in Central America. The main population groups separate ‘Ladinos’ (mixed Native American-African-Spanish), and Native indigenous people of Maya descent. Among the present-day Guatemalan Maya, there are more than 20 different ethnic groups separated by different languages and cultures. Genetic variation of these communities still remains largely unexplored. The principal aim of this study is to explore the genetic variability of the Maya and ‘Ladinos’ from Guatemala by means of uniparental and ancestry informative markers (AIMs).i) Native American ancestry: 92% for the Maya vs. 55% for the ‘Ladino’, and (ii) European ancestry: 8% for the Maya vs. 41% for the ‘Ladino’. In addition, the impact of the Trans-Atlantic slave trade on the present-day Guatemalan population is very low , in part mirroring the fact that Guatemala has a predominant orientation to the Pacific Ocean instead of a Caribbean one. Sequencing of entire Guatemalan mitogenomes has led to improved Native American phylogeny via the addition of new haplogroups that are mainly observed in Mesoamerica and/or the North of South America.Analyses of uniparental genetic markers indicate that Maya have a dominant Native American ancestry . ‘Ladino’, however, show a clear gender-bias as indicated by the large European ancestry observed in the Y-chromosome (75%) compared to the mtDNA (0%). Autosomal polymorphisms (AIMs) also mirror this marked gender-bias:  and the Classic (200–1000 AD) Eras of the Mesoamerican chronology, coinciding with development of the most distinctive and advanced Mesoamerican civilization, the Maya. Phylogenetic features of mtDNA data also suggest a demographic scenario that is compatible with moderate local endogamy and isolation in the Maya combined with episodes of gene exchange between ethnic groups, suggesting an ethno-genesis in the Guatemalan Maya that is recent and supported on a cultural rather than a biological basis.The online version of this article (doi:10.1186/s12864-015-1339-1) contains supplementary material, which is available to authorized users. Instituto Nacional de Estadística of Guatemala; INE; http://www.ine.gob.gt).The Republic of Guatemala is located in Central America, bordering the Pacific Ocean, between El Salvador and Mexico, and the Caribbean Sea between Honduras and Belize Figure . GuatemaMinisterio de Educación  as a heterogeneous population, which expresses itself in Spanish as a maternal language and possesses specific cultural traits of ‘Hispanic’ origin mixed with indigenous cultural elements. Already in 1690, the chronicler Francisco Antonio de Fuentes y Guzmán described the ‘Ladinos’ as ‘mestizos, mulatos and negros’. There is extensive historical documentation indicating trend in Guatemala to marriages between different ethnic groups  or Colombia [A2w] or in Peru [A2ar]). The data cannot disregard the possibility of migrations from South America to Central America and the Caribbean. There are previous evidences pointing to this possibility ,30,65 buThe phylogeographic characteristics of other mtDNA clades, however, point to demographic movements occurring to a more regional scale, almost exclusively within the Mesoamerican area. A number of these clades date back to the Pre-Classic and Classic Era Figure ; the devOther population movements occurring during the Post-Classic Era  could also contribute to the dispersal of these lineages into this region. In particular, the role of the Nahua people ,67, alsoThe large amount of shared variability observed between the different Maya ethnic groups (and with other Mesoamerican populations) analyzed in the present study and the lack of specific variability characterizing them is in agreement with a previous genetic study which obtained signs of genetic homogeneity among various Maya groupings by G-tests . In contThe complete genotype results for Y-chromosomal SNP variation are given in Additional file The individual described above (#GT24) bearing the mtDNA Sub-Saharan haplotype L3b1a carries a Y-chromosomal haplogroup R1* of European ancestry.PCA plot Figure A based oAdditional analysis carried out using Discriminant analysis of Principal Components (DAPC) underlines the outcomes of PCA and provides further assessment of between-population structures . There was only one Maya who shows a moderate percentage of African co-ancestry (4.4%). This subject  is of self-described Q’eqchi’ ancestry and carries a Native American mtDNA haplotype (B2t). This percentage of African ancestry in this Q’eqchi’ individual could simply mirror the variability of ancestry estimates using panels of AIMs containing a limited amount of SNPs , and notFinally, for the AIM-InDel marker rs34122827, we found a third allelic state in one Mayan sample (#Marco_03). This allele corresponds to a T deletion occurring in the long allele background . Interestingly, this variant was found to be specific to Europeans , whereasloci show that the Maya population samples are mainly composed of Native American haplogroups with a minor presence of sub-Saharan (only on the mtDNA) and/or European lineages (only on the Y chromosome). AIM-InDels also points to the predominant Native American nature of the Maya , and the European component in the male-specific genome (Y-chromosome: 75%). These results mirror the important demographic impact of the European colonizers in Guatemala (with a large effective population size) and their role in the extinction of the Native American population from the region. In particular, the patterns observed in ‘Ladinos’ indicate that the male population from Guatemala suffered more dramatically the consequences of the European conquest as mirrored by the differential ancestry components of the mtDNA and the Y-chromosome in the ‘Ladinos’. The Native American component of present-day Guatemalans was much better preserved in both male and female Maya, probably thanks to their geographic isolation in very inaccessible areas of the country.Although African slaves arrived in Guatemala in the period between the VI and XVII century to replace the indigenous population as a labor force , our datOverall, the data reveal the existence of a fluid gene flow in Mesoamerica and a predominant unidirectional flow towards South America. The main movements could have occurred during the Pre-Classic (1800 BC-200 AD) and the Classic (200–1000 AD) Eras of the Mesoamerican chronology. This period coincide with development of the Maya, which was the most distinctive and advanced Mesoamerican civilization. Phylogenetic features of control region mtDNA data and the mitogenomes analyzed also suggest a demographic scenario that is compatible with moderate local endogamy and isolation in the Maya combined with episodes of gene exchange between ethnic groups. This pattern of variability is in agreement with a recent ethno-genesis of the Maya, which seems more established in cultural rather than a biological basis.There is one main limitation in the present study. Thus, most of the demographic inferences carried out in this study are devoted to the analysis of the mtDNA variation . This is mainly due to the fact that the level of resolution provided by the mtDNA in our study is high compared to the resolution obtained for the other markers analyzed. Y-chromosomal and autosomal markers were genotyped in order to provide a more complete picture of the genetic patterns of Guatemalans. For instance, these markers have revealed the existence of an important gender-bias in this country , whiFundación de Antropología Forense de Guatemala (FAFG) in prosecuting crimes against humanity that took place during the 1960–1996 civil war [Lastly, the data generated in the present study represent one of the very few genetic studies carried out in Native Guatemalans, and the ethnic groups sampled are analyzed here for the first time with a particular combination of uniparental and AIMs. The results provide new insight into the admixture characteristics of the Guatemalan population, with a clear gender bias observed in the ‘Ladinos’ but virtually absent in the Maya. The data also show important insights into the demography and the ethno-history of the Guatemalans and the important role of Mesoamerica as a passageway between North and South America. Last but not least, the data are also of particular interest from a forensic genetics point of view, as the results of our study may also contribute to the on-going work of the ivil war .Instituto Nacional de Ciencias Forenses during the sample period; INACIF; http://www.inacif.gob.gt/). However, we ensured that every subject fully understood the aim of our study, which conforms to the Spanish Law for Biomedical Research (Law 14/2007-3 of July) and which was approved by the ethical commission of the Universidade de Santiago de Compostela. A document of informed consent was translated by a native Maya translator to the members of the villages and in particular to the donors. In case volunteers were analphabetic, fingerprints were used as signatures. The individual ethnic origin of participants was recorded by a detailed genealogy questionnaire. If self-reported family relationships were recognized during recruitment, just samples from one family member were considered for the analysis, independently from the degree of relationship. Distant relationships cannot be disregarded.‘Ladino’ individuals were mainly recruited in cities , while indigenous people were sampled directly in their communities in and around the highlands of Guatemala (Verapaz), the geographic heart of the country Figure . GuatemaRecruitment of samples was limited by two main factors: (i) Maya linguistic diversity and their reservation towards medical study participation, and (ii) logistical difficulties for DNA sampling in a partially rough terrain with very difficult access.DNA extraction was carried out from saliva samples on buccal swabs by organic standard procedures.http://www.phylotree.org; [HaploGrep [A total of 110 samples  where analyzed for the mtDNA . The seaploGrep  and manuaploGrep . PotentiaploGrep -83. In oaploGrep ,84. UnexBased on the information provided by the control region profiles  were genotyped for the Y-chromosome . Estimation of the coalescent times of the most recent common ancestor (TMRCA) was computed using two different procedures.TMRCA was initially calculated using a ML procedure Table . For thiρ) of the haplotypes of a clade to the respective root haplotype together with a heuristic estimate of the standard error (σ) calculated from an estimate of the genealogy  and 1 (perfect star phylogeny) [TMRCA was also computed from the averaged distance (ylogeny) ,93.Both methods show very similar divergence ages when applied to mitogenomes. However, the averaged distance to the root shows an anomalous behavior on A2w1 and its sub-clades, with ages that are about twice  larger than estimates based on ML (compare to a 1.2 of averaged discrepancy for the rest of the sub-clades). Estimates based on synonymous mutations show also large discrepancies with the ML method. In addition, A2w1 shows very low values of star-likeness  came from populations of three different continents: Africa , Europe , and America . Present-day East Asians were not taken into account as a reference population, assuming that these populations did not substantially contribute to the recent genetic heritage of the Guatemalan people, as is the case in other American locations [Admixture proportions from autosomal data were inferred by comparing genetic profiles from the present study with those publicly available from the Human Genome Diversity Cell Line Panel, HGCP-CEPH . These ocations ,71,95.Statistical analysis of AIMs included different tools aimed at disentangling the population structure of the Guatemalan study samples. Multivariate analyses were carried out using Principal Component Analysis (PCA). PCA condenses in a few principal components  an initial set of data that can contain quantitative variables, into a group of fewer variables resulting in a linear combination of the originals.http://www.r-project.org/), together with the SNPassoc package .To further estimate individual ancestry proportions we used ADMIXTURE . This sohttp://empop.org), Familytree (https://familysearch.org/), and the Sorenson (http://www.smgf.org/) databases. Note that frequencies obtained from these additional database searchers provide only approximate figures given that their web-interfaces were not conceived specifically for population genetic purposes (e.g. forensic casework in the case of EMPOP).Finally, phylogeographic searchers of mtDNA profiles were carried out on an in-house database containing >27,000 mitogenomes and >170,000 partial (mainly HVS-I) mtDNA sequences. Additional exploratory haplotype searchers were carried out on EMPOP (


STF values) of the genetic markers of the DMET Plus array between the relevant parental populations. Although the average levels of genetic differentiation are low, there is a long tail of markers showing large frequency differences, including markers located in genes belonging to the Cytochrome P450, Solute Carrier (SLC) and UDP-glucuronyltransferase (UGT) families as well as other genes of PGx relevance such as ABCC8, ADH1A, CHST3, PON1, PPARD, PPARG, and VKORC1. We show how differences in admixture history may have an important impact in the distribution of allele and genotype frequencies at the population level.Studies of pharmacogenomics-related traits are increasingly being performed to identify loci that affect either drug response or susceptibility to adverse drug reactions. However, the effect of the polymorphisms can differ in magnitude or be absent depending on the population being assessed. We used the Affymetrix Drug Metabolizing Enzymes and Transporters (DMET) Plus array to characterize the distribution of polymorphisms of pharmacogenetics and pharmacogenomics (PGx) relevance in two samples from the most populous Latin American countries, Brazil and Mexico. The sample from Brazil included 268 individuals from the southeastern state of Rio de Janeiro, and was stratified into census categories. The sample from Mexico comprised 45 Native American Zapotecas and 224 self-identified Mestizo individuals from 5 states located in geographically distant regions in Mexico. We evaluated the admixture proportions in the Brazilian and Mexican samples using a panel of Ancestry Informative Markers extracted from the DMET array, which was validated with genome-wide data. A substantial variation in ancestral proportions across census categories in Brazil, and geographic regions in Mexico was identified. We evaluated the extent of genetic differentiation (measured as  VKORC1 3673G>A transition, a major determinant of warfarin dose requirement for appropriate anticoagulation 3673A allele, associated with low warfarin dose, ranges from <10% in sub-Saharan Africans to>90% in Southeast Asian populations VKORC1 3673G>A SNP to predict warfarin dosage across populations worldwide The development of high-throughput and rapid genotyping technologies in parallel with the completion of the Human Genome Project led to a wealth of information on human genetic diversity and its impact on disease susceptibility and drug response. Pharmacogenetics and pharmacogenomics research explores the contribution of genetic individuality to variability in drug response, to provide relevant information for personalized drug therapy. A common finding in PGx studies is that the frequency of genetic variants associated with drug response differs across and within populations. One distinct example is the In this study, we used the Affymetrix Drug Metabolizing Enzymes and Transporters (DMET) Plus array to characterize the distribution of PGx polymorphisms in a combined cohort of Brazilians and Mexicans. The DMET array interrogates variants in 231 genes involved in drug pharmacokinetics The Brazilian cohort consisted of 268 healthy, unrelated adults recruited in the city of Rio de Janeiro in the Southeast region. The study protocol was approved by the Ethics Committee of the Instituto Nacional de Câncer, Rio de Janeiro. Each individual signed an informed consent to participate, and was asked to self-identify according to the “race/color” classification scheme adopted by the official Brazilian Census The Mexican cohort included 45 Native American Zapotecas (NAT) individuals and 224 self-identified Mestizo individuals (MEX) from 5 states located in geographically distant regions in Mexico. In our study, the Native American parental frequencies were estimated based on a Zapoteca sample recruited in the State of Oaxaca. Previous research has indicated that Zapotecas were the most useful population for building an admixture mapping map for Latino populations Samples were genotyped using the Affymetrix DMET Plus platform, using standard protocols. This platform interrogates 1,936 genetic variants across 231 genes of PGx relevance, including biallelic and triallelic SNPs, copy-number variants and insertion/deletions. Quality control tests were performed on data using PLINK In order to evaluate the ancestry proportions of the Brazilian and Mexican samples, we identified 71 unlinked Ancestry Informative Markers (AIMs) from the DMET Plus array. The selection of AIMs was based on frequency differences between the three main parental groups relevant for Latin American populations: European, African and Native American. We used as representatives of the parental groups 59 individuals from Europe (Hapmap CEU from northwestern Europe), 208 individuals from Africa  To validate the DMET Latin American AIMs panel, we used the program STRUCTURE v 2.3.4 CEU (EUR), Africans YRI+LWK (AFR) and Native Americans (NAT). The program EIGENSOFT was also used to obtain STF estimates for all the pairwise comparisons.A Principal Component Analysis (PCA) was carried out with the program EIGENSOFT STF to allele frequencies to characterize differentiation at specific SNPs as previously reported The program PHASE v 2.1.1 We assessed the relationship between allele frequencies and ancestry proportions by fitting non-linear piece-wise smooth logistic regression models We estimated ancestry proportions in the Brazilian and Mexican samples using a panel of 71 unlinked, highly informative AIMs included in the DMET Plus array. The panel was identified based on the frequency differences between the relevant parental populations . Detailed information about the panel of AIMs, including parental frequencies, is provided in 2R values for the major ancestral components of the Mexican Mestizo population . The 2R value observed for the African ancestral contribution was lower (Illumina 550K: 0.42 and Affymetrix 100K: 0.32), as expected given the relatively small average African ancestry observed in the Mexican Mestizo sample.In order to evaluate the discriminatory power of the AIMs panel, we estimated the correlation of the individual admixture estimates obtained with the panel of 71 DMET AIMs with estimates based on genome-wide data for Mexican Mestizo individuals for which data were available  was performed to describe the diversity of Mexican and Brazilian populations in relation to the three ancestral populations . The PCASTF statistic, which is a measure of the degree of genetic differentiation between populations, for all the markers included in the DMET Plus array. STF was calculated for all possible pairwise population combinations of the parental samples . STF values for all the pairwise comparisons. STF values for all the pairwise comparisons in a graphical format. The average STF values are low, indicating reduced genetic differentiation. However, it is important to note the broad distribution of STF values. While most of the genetic markers have low genetic differentiation, there are many outliers with high STF values. The highest average STF values are observed between the African and the Native American samples (STF = 0.085). The STF values observed for the African-European and European-Native American comparisons were 0.059 and 0.062, respectively. The average genetic differentiation between the Brazilian and Mexican samples with respect to the parental samples is lower than the genetic differentiation observed between the parental samples (STF = 0.012), as expected given the history of admixture in Brazil and Mexico.We calculated the We also explored haplotype diversity using the program PHASE. We used this program to estimate haplotype frequencies based on 1,647 biallelic SNPs located on 214 DMET genes. We restricted our analysis to common haplotypes with frequencies equal or higher than 5% in each sample. We identified slightly more than 1,000 different haplotypes with these characteristics. The African sample shows the highest haplotype diversity (more than 68% of the common haplotypes are found in the African sample) and the Native American sample shows the lowest haplotype diversity (only 46.5% of the common haplotypes are found in the Native American sample). In agreement with expectations based on population history, the Brazilian sample has intermediate haplotype diversity between the African and European samples, and the Mexican Mestizo sample has intermediate haplotype diversity between the European and Native American samples .CYP2D6, UGT1A1 and VKORC1 genes, which can be inferred based on the markers of the DMET Plus array. Although, unfortunately the array does not capture all the functional variants described for these genes, such as UGT1A1*28. The allele frequencies of several CYP2D6 variants of functional importance are known to vary amongst ethnic groups, and this explains variation in interindividual drug response CYP2D6*4 allele, and the decreased-activity allele CYP2D6*41 are considerably higher in Europeans than in Native American or West African populations. As expected, the relative frequencies for these alleles are intermediate in the admixed samples, and the variants are present in frequencies that are proportional to the relative admixture proportions. In the case of UGT1A1, the frequencies of variants that have been associated with irinotecan response (−3156G>A/−349C>T and UGT1A1*60) CYP2D6 and UGT1A1 alleles/haplotypes observed in Europeans vs. the other two populations are probably the result of ascertainment bias, because most of the studies exploring variants with potentially functional effects have been carried out in European populations. Finally, for VKORC1 there are also clear differences across populations in the distribution of haplotypes associated with low (H1 and H2) and high (H7/H8 and H9) warfarin dose requirements In STF values) between the parental populations that are most relevant for the Brazilian (European and African populations) and Mexican Mestizo (European and Native American) samples. www.pharmgkb.org), and their Bonferroni adjusted p-values are less than 1×10−20 in the European-African comparison and less than 1×10−6 in the European-Native American comparison. The SNPs listed in ABCC8, ADH1A, CHST3, PON1, PPARD, PPARG, and VKORC1. Of note, 6 of the SNPs identified in the African-European comparison are also present in the European-Native American comparison: rs2470890 at CYP1A2, rs2242480 at CYP3A4, rs1050152 at SLC22A4, rs2242046 at SLC28A1, rs1060896 at SLC28A2 and rs7867504 at SLC28A3. The list of markers with high genetic differentiaton for Brazilians and Mexicans is presented in We identified the genetic markers included in the DMET Plus array that show the most extreme genetic differentiation  to explore how individual ancestry proportions influence allele frequencies for www.pharmgkb.org/page/cpic). We selected these SNPs to examine the impact of admixture on the distribution of clinically-important PGx polymorphisms in Brazilians and Mexicans. Initially, we calculated the STF values for each locus in pair-wise comparisons of proxy parental populations, namely EUR versus AFR (most relevant for Brazilians) and EUR versus NAT (most relevant for Mexicans). The average STF for the 18 markers was 0.037 in EUR versus AFR and 0.044 in EUR versus NAT , whereas large genetic divergence (STF>0.15) was observed for rs1135840 in CYP2D6 between EUR and NAT, and for rs9923231 in VKORC1 between EUR and AFR. We show the three-dimensional plots for these two markers in CYP2D6, which shows moderate genetic divergence between EUR and both AFR and NAT.Eighteen SNPs in the DMET array are included in the published guidelines of the Clinical Pharmacogenetics Implementation Consortium . The estimates of genetic (haplotype) diversity based on the DMET Plus data are also consistent with evidence based on dense genome-wide data We evaluated the distribution of The admixture proportions of the individuals of Brazil and Mexico were estimated using a panel of highly informative AIMs included in the array. We selected 71 unlinked markers based on the degree of genetic differentiation between the relevant ancestral populations. The number of AIMs was limited due to the relatively low number of markers included in the DMET array  and the fact that many of the markers are in linkage disequilibrium and do not provide independent information. However, the ancestry information content of the panel is high and the individual admixture estimates obtained with the DMET AIMs panel are highly correlated with admixture estimates based on genome-wide data (Affy 100K and Illumina 550K) in a subset of the Mexican samples  and PharmGKB level 1A . The CYP2C19 allele rs12248560 T (CYP2C19*17) is an ultrarapid metabolizer of drugs such as amitriptyline and clopidogrel. The frequency of this allele is more than 4-fold higher in states with high European admixture proportions (e.g Sonora: 0.144 and GUA: 0.136) than in states with high Native American admixture proportions (e.g. GUE: 0.033)  .As stated above, although the overall genetic differentiation of the markers interrogated in the DMET Plus array is low, there are many loci that show high levels of genetic differentiation between the parental populations relevant for contemporary Brazilians and Mexicans. Given the broad range of admixture proportions observed in Brazil (both in terms of census categories and geographic regions) and Mexico (geographic regions), this has clear PGx implications. We displayed graphically in VKORC1 rs9923231 SNP, a major determinant of warfarin dose in CPIC guidelines, may be used as an example of the practical PGx implications of admixture history. The frequency of the rs9923231T allele, which associates with high warfarin sensitivity, varies 13-fold among proxy parental populations of Brazilians and Mexicans: 4.1% in sub-Saharan Africans (HapMap YRI and LWK), 38.1% in Europeans (HapMap CEU) and 52.2% in Native Americans (Zapotecas). Limdi et al VKORC1 rs9923231 SNP increases as the frequency of the A allele increased, such that VKORC1 explained greater variability in dose among Europeans compared to Africans and African Americans. Accordingly, warfarin-dosing algorithms including VKORC1 rs9923231 as a co-variate have considerably greater predictive power in Europeans compared to Africans The In summary, our study emphasizes the remarkable population complexity found in Brazil and Mexico: there is a broad range of admixture proportions within census categories and geographic regions, which is a reflection of differences in population history. It is important to consider that, although Brazil and Mexico are the largest countries in Latin America, they only represent a subset of the diversity observed in this vast geographic area. It is therefore critical to have this rich diversity in mind when considering the PGx impact of admixture Figure S1Population structure analysis using 71 AIMs. Individual ancestry proportions in Brazilians  and Mexican Mestizo (MEX).(TIF)Click here for additional data file.Figure S2Analysis of correlation of individual ancestry estimates for Mexican Mestizo individuals for which data are available for the DMET Plus array and genome-wide arrays. Data for 74 individuals were available for both the DMET Plus array and the Illumina 550K array. Data for 68 individuals were available for both the DMET Plus array and the Affymetrix 100K array. Individual ancestry estimates for the Illumina 550K array were obtained with the program ADMIXTURE. Individual ancestry estimates for the Affymetrix 100K array were obtained with the program STRUCTURE using 1814 AIMs (TIF)Click here for additional data file.Figure S3STF values. Pairwise comparisons were done for the three ancestral populations and for the admixed populations Mexico and Brazil, a) Europe vs Africa; b) Europe vs Native American; c) Africa vs Native American; and d) Mexico vs Brazil.Distribution of (TIF)Click here for additional data file.Figure S4Percentage of total common haplotypes observed per population. In order to prepare this plot, first we identified all the haplotypes present in each sample with a frequency equal or higher than 5%. The combined number of haplotypes observed was 1017. The Bar plots represent the percentage of haplotypes observed in each individual sample (e.g. 100% would correspond to the 1017 haplotypes observed in the combined sample). The data set presented includes all the Mexican admixed samples (MEX(MX)), all the Brazilian census groups , the Native American Zapoteca sample (NAT(ZAP)), and several HapMap samples , JPT.CHB).(TIF)Click here for additional data file.Figure S5Surface plots describing the predicted relationship between the frequency of rs16947 and parental ancestry, obtained by fitting piece-wise smooth logistic regression models to the 268 Brazilians and 224 Mexicans data. The relative proportions of Native American, African ancestry and European ancestry are presented as described in (TIF)Click here for additional data file.Table S1Allele Frequencies and FST values for 71 Ancestry Informative Markers (AIMs) in ancestral populations.(XLSX)Click here for additional data file.Table S2FST values for all pairwise comparisons among HapMap populations, Zapotecos (NAT), Brazilians  and Mexicans (MEX).(XLSX)Click here for additional data file.Table S3Polymorphisms showing the highest genetic differentiation between Native Americans and the Admixed populations.(XLSX)Click here for additional data file.Table S4Polymorphisms showing the highest genetic differentiation between Africans and the Admixed populations.(XLSX)Click here for additional data file.Table S5Minor Allele Frequencies (MAF) for 1,647 genetic markers. The markers are those included in the DMET Plus array and for all populations: Europeans (Hapmap CEU), Africans (Hapmap YRI and LWK), Native Americans (Zapotecas), Brazilians and Mexican mestizos (Guanajuato (GUA); Guerrero (GUE); Sonora (SON); Veracruz (VER) and Yucatan (YUC)).(XLSX)Click here for additional data file.Data S1Genotype data with 1,647 genetic markers from 537 individuals form Brazil and Mexico.(ZIP)Click here for additional data file.


Dothistroma septosporum is a haploid fungal pathogen that causes a serious needle blight disease of pines, particularly as an invasive alien species on Pinus radiata in the Southern Hemisphere. During the course of the last two decades, the pathogen has also incited unexpected epidemics on native and non-native pine hosts in the Northern Hemisphere. Although the biology and ecology of the pathogen has been well documented, there is a distinct lack of knowledge regarding its movement or genetic diversity in many of the countries where it is found. In this study we determined the global population diversity and structure of 458 isolates of D. septosporum from 14 countries on six continents using microsatellite markers. Populations of the pathogen in the Northern Hemisphere, where pines are native, displayed high genetic diversities and included both mating types. Most of the populations from Europe showed evidence for random mating, little population differentiation and gene flow between countries. Populations in North America (USA) and Asia (Bhutan) were genetically distinct but migration between these continents and Europe was evident. In the Southern Hemisphere, the population structure and diversity of D. septosporum reflected the anthropogenic history of the introduction and establishment of plantation forestry, particularly with Pinus radiata. Three introductory lineages in the Southern Hemisphere were observed. Countries in Africa, that have had the longest history of pine introductions, displayed the greatest diversity in the pathogen population, indicating multiple introductions. More recent introductions have occurred separately in South America and Australasia where the pathogen population is currently reproducing clonally due to the presence of only one mating type. Cryphonectria parasitica in North America and Europe , that causes Dothistroma needle blight (DNB), is by far the most important invasive pathogen of non-native pine species  trees in the Himalayas has, however, been confirmed  from six regions (=continents). These included Africa (South Africa and Kenya), Europe , Asia (Bhutan), North America (U.S.A.), South America (Chile and Ecuador), and Australasia   , 1× PCR buffer containing 2 mmol/L MgCl2, 0.25 mmol/L of each dNTP, 100 nmol/L of the forward and reverse primers, one of which was fluorescently labelled and 1 mmol/L additional MgCl2. The PCR conditions consisted of an initial denaturation step of 10 min followed by 10 cycles of 94°C for 30 s, specified annealing temperature for 45 s  were carried out in a total volume of 12.5 eneMapper™ software version 3.0 . Multilocus genotypes were obtained by combining the alleles present at all twelve loci for each isolate. All isolates having the same multilocus haplotype in a population were considered as clones.To facilitate multiplexing, PCR amplicons  were combined according to the approximate size of the amplicons and type of fluorescent label attached to the primer. Samples were subjected to electrophoresis on an ABI 3100 sequencer. Allele assignments were determined using ABI-Prism ®Gpopgene version 1.32   (Goudet N = 10) as described by El Mousadik and Petit (N = 4). The clonal fraction was calculated for each population by dividing the number of genotypes observed in the population by the total population size and subtracting this from one.In addition to calculating gene diversity, estimates of allelic richness were computed for each population and region in the program ) Goudet . Unequalnd Petit . Romaniaultilocus version 1.3 (http://www.agapow.net/software/multilocus) (Agapow and Burt n / n − 1)(1 − Σipi2) where pi is the frequency of the ith genotype and n is the number of individuals sampled. Here, the multilocus genotype of all possible pairs of individuals is compared and the proportion of pairs that are different is calculated. Completely clonal populations would score a value of 0 while those where all individuals have different multilocus genotypes would score 1.Measures of genotypic diversity (D) were quantified in Mgenalex version 6.1 . The distance matrix generated was used to construct a Neighbor-joining (NJ) tree in Mega version 5 , a statistic based on the rate of change in the log probability of data with respect to the number of clusters, was used to interpret the real number of clusters  and their applications to control for population stratification were performed using the methods described by Patterson et al. . This anigrate-n Version 3.4.4 (Beerli θ) and the mutation-scaled immigration rates (M) between populations. M is defined as m/μ, where m is the proportion of migrants in the population in each generation and μ the mutation rate per generation per microsatellite locus. M therefore measures the importance of immigration versus mutation in introducing new variants into a population. The number of alleles per locus was used as a measure of mutation rate (μ) for the microsatellite data. Theta (θ), is the product of the inheritance scaler (=2 for haploids), the effective population size (Ne), and the mutation rate (μ) per generation (θ = 2Neμ). Migrate uses a Bayesian approach based on the coalescent theory to estimate the population parameters. Microsatellite input data were converted to repeat numbers and a Brownian motion approximation to the stepwise mutation model was used. Starting values of θ and M were generated from FST assuming an inheritance scaler of 0.5 (for haploids). For the search strategy, the mutation rate was set to constant for all loci, the posterior distributions were generated using slice sampling and a static heating scheme with four chains of temperatures of 1,000,000, 3, 1.5, and 1 was used. Analyses were performed using one long chain, 100,000 steps recorded every 100 steps and a burn-in of 50,000. Three independent Migrate runs using different starting random seed numbers were performed on two datasets to ensure convergence of parameter estimates. The first dataset was used to compare migration between the six continents and the second between the 14 individual countries.An MPI version of M4 Beerli  implemenMAT1-1 and MAT1-2 were assayed using a set of primers developed by Groenewald et al. (D. septosporum. Degenerate primers (Dot Mat1r 5′- TTGCCTGACCGGCTGCTGGTG-3′ and Dot Mat2r 5′- CTGGTCGTGAAGTCCATCGTC-3′) and species-specific primers (D. septo Mat2f 5′- GTGAGTGAACGCCGCACATGG-3′ and D. septo Mat1f 5′- CGCAGTAAGTGATGCCCTGAC-3′) were multiplexed in a single reaction. PCR reactions were carried out in a total volume of 12.5 μL and consisted of: 10–20 ng DNA, 1× PCR buffer containing 2 mmol/L MgCl2, 0.5 mmol/L MgCl2, 0.12 mmol/L of each dNTP, 200 nmol/L of each of the four primers and 0.032 U FastStart Taq DNA Polymerase (5 U/μL) (Roche Diagnostics). Cycling conditions consisted of an initial denaturation of 5 min at 94°C followed by 40 cycles of 94°C for 20 s, 65°C for 20 s, 72°C for 40 s and a final elongation of 7 min at 72°C. The presence of the MAT1-1 idiomorph was indicated by an amplicon size of 823 bp and these isolates were designated MAT 1. Presence of the MAT1-2 idiomorph was determined by the amplification of a fragment of 480 bp and these isolates were designated MAT 2. An exact binomial test, using two-tailed P-values  was used to determine whether populations deviated from the null hypothesis of a 1:1 ratio of mating types.The mating types d et al. , to amplD. septosporum. Thirteen isolates from Hungary that produced an allele size of 109 bp were identified as Dothistroma pini  followed by the United States 6.2%). Only the Austrian and Hungarian populations showed 100% polymorphism for the 12 loci and contained the highest allelic richness . In the Southern Hemisphere, although two unique alleles were present in the Kenyan population, those from South Africa, Chile, Ecuador, and New Zealand contained no unique alleles , percentage of unique alleles 36.2%), gene diversity (0.57) and allelic richness (4.79). The North American, Asian, and African populations contained moderate levels of diversity, with values of 6.2/0.25/2.33 and 1.5/0.33/2.97 and 1.5/0.38/2.47, for the percentage of unique alleles, gene diversity and allelic richness, respectively. The South American and Australasian populations had the lowest levels of diversity with gene diversity and allelic richness values of 0.22/1.7 and 0.05/1.2, respectively. The populations from South America, however, contained the third highest number of unique alleles at 3.1%, after Europe and North America. Overall, the clonal fraction in the Northern Hemisphere populations was low (mean 17%), compared to those in the Southern Hemisphere (mean 65%) , it was still significant for population structure.AMOVA analyses showed that at a global scale, with the continents representing regions, most of the variation was distributed within populations (61%), but a significant proportion of the variation (32%) was also attributed to differences among regions Table . Eight ptructure analyses revealed the highest posterior probability for five clusters/populations  and Australasian (orange lineage) isolates  and last three  significant axes are presented for cluster/geographic location  and 196 parameters at a global scale (14 countries) in three independent runs. While there was adequate chain mixing, independent runs did not converge in estimates of the magnitude of migration among countries, or continents, for any of the runs. While absolute values did not match, in many cases similar migration directionality was observed between runs. Results of the migration parameters for the comparisons between continents for a single MMAT1-2 idiomorph being significantly more common in Poland while the MAT1-1 was more common in the United States  is due to the large numbers of unique alleles present in the individual country collections. These populations, mainly on planted P. nigra, were genetically very similar, despite their occurrence in different countries. This can be explained by the fact that these countries border on each other and thus have no barriers to gene flow. Migration or range expansion of D. septosporum during the last 50 years in Europe, due to effective dispersal of asexual spores (conidia) and extensive movement of pine material  between these countries. DNB has been known in Chile since 1957 .Direct movement of 7 Gibson , but was7 Gibson . Given tD. septosporum population in New Zealand is clonal. This is consistent with previous investigations  and evidently, additional introductions of D. septosporum have not occurred.Results of this study clearly show that the D. septosporum moved from New Zealand to Australia naturally across the Tasman Sea  of the alleles were common to the fungal populations from these areas. It was thus not possible to validate the hypothesis of Hirst et al.  that D. D. septosporum is an important example of human mediated, but unintentional movement of a plant pathogen. This movement has facilitated the establishment of D. septosporum in many areas of the world where pines are planted outside their natural ranges. Although available cultures from countries considered in this study varied in number, intriguing patterns of local range expansion and global spread emerged. There remains substantial opportunity to expand the knowledge gained in this study with larger numbers of isolates from areas that could not be sampled or where sampling was not optimal. In particular, it would be most interesting to consider the population genetics of isolates from North and Central America, which could provide intriguing insights into the possible area of origin of D. septosporum.The worldwide distribution of D. septosporum to infect new hosts, and to become established in new areas (Woods et al. In the future, optimal climatic conditions, influenced dramatically by climate change, and the planting of susceptible trees in monocultures are likely to increase the potential for Dothistroma septosporum provides an outstanding model organism to study biological invasions because it has become established both in the Northern and Southern Hemisphere, where it can be viewed alternatively as a native pathogen or an alien invasive, influenced by planting practices, other human activities and climate change. Whereas populations of the pathogen in the Northern Hemisphere are genetically heterogenous and sexually recombining, those in the Southern Hemisphere, with the exception of Africa, have low levels of diversity and contain a single mating type gene. It will thus be important to monitor and prevent the further spread of different, possibly more virulent genotypes and opposite mating type genes, into these predominantly monoculture plantations of susceptible hosts in the Southern Hemisphere.