The EUROFORGEN NAME panel is a regional ancestry panel designed to differentiate individuals from the Middle East, North Africa, and Europe. The first version of the panel was developed for the MassARRAY system and included 111 SNPs. Here, a custom AmpliSeq EUROFORGEN NAME panel with 102 of the original 111 loci was used to sequence 1098 individuals from 14 populations from Europe, the Middle East, North Africa, North-East Africa, and South-Central Asia. These samples were also sequenced with a global ancestry panel, the Precision ID Ancestry Panel. The GenoGeographer software was used to assign the AIM profiles to reference populations and calculate the weight of the evidence as likelihood ratios. The combination of the EUROFORGEN NAME and Precision ID Ancestry panels led to fewer ambiguous assignments, especially for individuals from the Middle East and South-Central Asia. The likelihood ratios showed that North African individuals could be separated from European and Middle Eastern individuals using the Precision ID Ancestry Panel. The separation improved with the addition of the EUROFORGEN NAME panel. The analyses also showed that the separation of Middle Eastern populations from European and South-Central Asian populations was challenging even when both panels were applied. Analysis of ancestry informative markers (AIMs) may be used to infer the biogeographic ancestry of the individual that left the trace sample at the crime scene3. Sets of AIMs can be combined to target different geographical regions on large or small geographical scales. The resolution of ancestry at the continental level, e.g. Africa, Europe, East Asia, and the Americas has been achieved using commercially available panels including the Precision ID Ancestry Panel and the ForenSeq DNA Signature Prep Kit9. However, such panels have limited success with population assignment of individuals with admixed ancestries and may not be able to differentiate individuals from regions that have experienced multiple population migration events.The identification of perpetrators of crimes by DNA investigations may be hindered by the absence of a reference sample from the offenders or database hits. In such cases, there is a need for additional DNA analyses that can lead the investigation in a specific direction10. Within the last 5000 years, many different powerful empires have dominated the region, fighting each other for political control and subsequently declining in power after relatively short periods of reign11. As a consequence, the borders in the Middle East changed and parts of the populations migrated each time a new empire gained power14. Migration of individuals to and from the surrounding regions further reduced the level of genetic divergence between the Middle Eastern, European, and South-Central Asian populations 15. The current political borders between the countries in the Middle East were agreed between the United Kingdom and France in 191616, and they do not reflect the genetics of the Middle East populations18. Furthermore, the Middle East is situated in the centre of an allele frequency gradient from North-Western Europe to East Asia19. This makes it particularly difficult to differentiate individuals from the Middle East, Europe, and South-Central Asia15.From a population genetic perspective, the Middle East is a particularly interesting region. The Middle East (covering Turkey in the West to Afghanistan in the East) connects Africa, South-Central Asia, and Europe and has a history of many human migration events20. It includes 111 AIMs and was designed to improve the population assignment of individuals from the Middle East, North Africa, and Europe. The AIMs were amplified with four PCR multiplexes and analysed using the MassARRAY System. Each multiplex required 2.5–10 ng DNA, which is more than what is recovered from the majority of crime scene samples. Therefore, a custom AmpliSeq assay was developed for the Ion S5 platform21. Of the 111 loci in the EUROFORGEN NAME panel, 102 loci were successfully amplified and sequenced with as little as 0.5–1 ng DNA.The EUROFORGEN North Africa and Middle East (NAME) panel is a regional ancestry panel for ancestry inference of individuals from the Middle East and North Africa6. We used the method developed for the GenoGeographer software22 to assess whether the use of the combination of the EUROFORGEN NAME and Precision ID Ancestry Panel markers would improve the correctness of the assignment of individuals to their population of origin. It was further investigated if the combination of the panels increased the weight of the evidence of the assignment of the population of origin.In this work, we typed 1098 individuals from 14 populations from the Middle East, North Africa, North-East Africa, South-Central Asia, and Europe for 265 AIMs using the AmpliSeq EUROFORGEN NAME panel and the Precision ID Ancestry Panel (Thermo Fisher Scientific)20, and 762 were typed with the custom AmpliSeq EUROFORGEN NAME panel21. Only the 102 loci that were included in both assays were used for the population genetic and ancestry analyses below. The information concerning the physical position and rs-numbers of the loci included in the AmpliSeq design is shown in Supplementary Table 21 and in this work. Two AIMs, rs12913832 and rs4833103, were present in both the EUROFORGEN NAME panel and the Precision ID Ancestry Panel. These two AIMs performed best in the EUROFORGEN NAME panel, and the results from the Precision ID Ancestry Panel were not used. Of the 1098 individuals, 28 individuals had no genotype calls in more than 10% of the loci. The data of these individuals were excluded from further analysis. Data for the remaining 1070 individuals were used for the downstream analyses.Of the 1098 individuals analysed, 336 were typed with the MassARRAY EUROFORGEN NAME assaycor = 4.9E-04). There was an excess of homozygotes of the T allele, which was caused by a deletion downstream of the locus that was associated with the C allele. Only samples typed with the MassARRAY assay were affected by the deletion; the locus was in HWE in the populations typed with the AmpliSeq EUROFORGEN NAME panel. The locus, which was also in linkage disequilibrium (LD) with another locus (see below), was excluded from further population genetic analysis.The data obtained with the EUROFORGEN NAME and Precision ID Ancestry panels were tested separately for Hardy–Weinberg equilibrium (HWE). For the EUROFORGEN NAME panel, the data of the AIM rs7873963 was in Hardy–Weinberg disequilibrium in five populations (Pcor = 3.07E−4). Among Portuguese individuals, 74 had the TT genotype, two had the CC genotype, while no heterozygote individual was observed. Among Pakistani individuals (N = 72), 43 individuals had the TT genotype, 13 the CC genotype, and 16 the CT genotype.The HWE was also assessed for the markers present in the Precision ID Ancestry panel. After Bonferroni correction, the AIM rs310644 was in Hardy–Weinberg disequilibrium in the Pakistani and Portuguese populations , one group on chromosome 7 (rs9649356—rs1227171), one group on chromosome 10 (rs2031581—rs2765650), and one group on chromosome 12 (rs10862511—rs10506882) seemed to form haplotype blocks. The loci rs1406045 (typed with the EUROFORGEN NAME panel) and rs4463276 (typed with the Precision ID Ancestry Panel) on chromosome 6 as well as rs621341, typed with the EUROFORGEN NAME panel, and rs6754311, typed with the Precision ID Ancestry Panel on chromosome 2 were in linkage disequilibrium (Supplementary Table Linkage disequilibrium (LD) analysis was performed on the combined dataset including 265 AIMs with 34,980 pairs of loci. Besides LD most likely due to physical linkage, LD between alleles at different chromosomes was also observed. Supplementary Tables The population variation of reference groups from Sub-Saharan Africa (N = 606), Europe (N = 604), the Middle East N = 134), South-Central Asia (N = 689), and East Asia (N = 504) was analysed. Figure 34, SouthTo evaluate the genetic structure of the populations, STRUCTURE analyses were performed using K = 3 to K = 7. Figure Based on the STRUCTURE and PCA results, the 14 populations typed in this work were grouped into five meta-populations: (1) a European meta-population including individuals from Albania, Denmark, Greece, Portugal, and Slovenia, (2) a Middle Eastern meta-population including individuals from Afghanistan, Iran, Iraq, Syria, and Turkey, (3) a North-East African meta-population including individuals from Eritrea and Somalia, (4) a North-African meta-population including individuals from Morocco, and (5) a South-Central Asian meta-population including individuals from Pakistan.23. This was done for the EUROFORGEN NAME panel (72 loci), the Precision ID Ancestry Panel (161 loci), and the combined dataset (233 loci). The AIM profiles were tested against both the individual’s meta-population of origin and the four other meta-populations. Table A z-score test was performed for each of the 1070 individuals using the GenoGeographer software and the cross-validation methodIrrespectively of the origin of the sample, the number of AIM profiles categorised as “Ambiguous” was lower with the combined set of markers than with the Precision ID Ancestry Panel. The reduction in the number of ambiguous profiles was most pronounced for individuals from the Middle East and South-Central Asia Table . In bothP < 0.05) with the combined panel.For the North African and the North-East African meta-populations, the number of profiles assigned to the ‘Rejected’ category increased when the combined panel was used. Regarding North African individuals, four profiles classified as ‘Accepted’ and two profiles classified as ‘Ambiguous’ with the Precision ID Ancestry panel were assigned as ‘Rejected’ with the combined panel. For the North-East African individuals, three profiles (one defined as ‘Accepted’ and two as ‘Ambiguous’) were classified as ‘Rejected’ when the combined panel was used. These AIM profiles were outliers in all reference populations  for their populations of origin. Overall, the combined panel  and the North-East African meta-population , 15 AIM profiles were “Rejected” from their true meta-populations of origin with the Precision ID Ancestry Panel, while 24 AIM profiles were “Rejected” with the combined panel. These individuals may belong to populations that were not included among the reference populations, or they may have mixed ancestries. In both cases, investigations of neighbouring populations, including Sub-Saharan populations, would have been relevant.For forensic genetic population assignment, sufficient population reference data and their geographical distribution play a major role37. In the assessment of ancestry, however, there is a logic challenge in situations in which both likelihoods in the LR are based on hypotheses that are nonsense. Methods based on the likelihood principle are—on their own—not well suited for the evaluation of the plausibility of the hypotheses of the ancestry of an individual with a particular AIM profile. To avoid calculating LRs based on two nonsense-hypotheses—which would make such an LR of no use—we introduced a prior-test of the probabilities of the hypotheses based on the z-score test. If both hypotheses are rejected, no further calculation of LR is performed. In practical forensic genetic work, this means that LRs are only calculated if the AIM profile of the individual is accepted in at least one of the reference populations and the LR will give meaningful information. If an AIM profile is accepted to belong to only one population, it is still relevant to calculate the LRs based on comparison with all other relevant populations to assess the strength of the evidence. If an AIM profile is accepted to belong to two or more populations, the various LRs based on comparisons between the relevant populations can be calculated. If any LR is statistically significantly higher than any other, this will be strong evidence in favour of the individual belonging to the population resulting in the highest likelihood. Again, the strength of the evidence is given by the LR. It must, however, be taken into consideration that the pure fact that an AIM profile based on a z-score value ≤ 1.64 (P > 0.05) is accepted to belong to one—and only one—tested population does not prove that the individual belongs to that particular population. The individual may instead belong to another population that is genetically close to the tested population, or the individual may be of admixed ancestry with sufficient contribution from the tested population to allow the admixed AIM profile to be accepted into that population. The individual could also belong to a population that is not present in the reference database. Thus, in a case with a question to which of two populations an individual belongs, the first step would be to perform a z-test. If the AIM profile can belong to any of the tested populations, the LR is calculated as the weight of the evidence. If the results of the z-test indicate that the AIM profile for practical purposes cannot belong to any of the tested populations, no further calculation is performed, and the conclusion is that the contributor of the AIM profile does not belong to any of the proposed populations.LRs were calculated for individuals that were assigned to their assumed population of origin (“Accepted” and “Ambiguous” categories) Fig. . The useThe analyses performed in this work demonstrated that the addition of the loci in the EUROFORGEN NAME panel to those of the Precision ID Ancestry Panel improved the efficiency of the population assignment of individuals from Europe, the Middle East, North Africa, North-East Africa, and South-Central Asia. However, when comparing the performance of the panels separately, the Precision ID Ancestry Panel had higher inclusion and rejection rates than the EUROFORGEN NAME panel, which was designed as a regional ancestry panel and not as a stand-alone panel.20. To reach a minimum of 75 individuals per population23, samples from 220 individuals from these populations were typed with the AmpliSeq EUROFORGEN NAME panel , either in this or previous works31.A total of 1098 samples were selected from the Biobank of the Department of Forensic Medicine, University of Copenhagen, Denmark . All samples were anonymized. According to the Danish Act on Research Ethics Review of Health Research Projects, the work did not require approval by the Ethics Committee. The authors confirm that all methods were performed in accordance with the relevant guidelines and regulations. A total of 336 individuals from Albania, Denmark, Greece, Iraq, Slovenia, Somalia, and Turkey were previously typed with the MassARRAY EUROFORGEN NAME assayDNA was extracted from either blood samples using the QIAamp DNA Blood Mini Kit  or from blood or buccal swabs on FTA cards  with the BioRobot EZ1 Workstation  and the QIAamp DNA Investigator Kit .DNA extracts were quantified with the Qubit dsDNA High Sensitivity (HS) Assay Kit (Thermo Fisher Scientific) and a Qubit 3.0 Fluorometer (Thermo Fisher Scientific).6 and preparing the libraries using half volume of reagents. The DNA input ranged from 0.3 to 1 ng. The DNA libraries were purified with Agencourt AMPure XP magnetic beads  with a Biomek 3000 Laboratory Automation Workstation 39. The barcoded libraries were quantified using a Qubit Fluorometer and the Qubit dsDNA HS Assay Kit (Thermo Fisher Scientific). The DNA libraries were subsequently pooled in equimolar concentrations (28–35 pM) using a Biomek 3000 Laboratory Automation Workstation 39. The template preparation  was performed on an Ion Chef instrument (Thermo Fisher Scientific) using the Ion S5 Precision ID Chef Kit (Thermo Fisher Scientific). Approximately 80 libraries were loaded per Ion 530 chip. A negative control was included per chip. Sequencing was performed with an Ion S5 (Thermo Fisher Scientific) using the Ion S5 Precision ID Sequencing Kit (Thermo Fisher Scientific).DNA libraries were built using the AmpliSeq EUROFORGEN NAME panel and the Precision ID Ancestry Panel (Thermo Fisher Scientific) and the Ion AmpliSeq Library Kit. 2.0 (Thermo Fisher Scientific) according to the manufacturers’ recommendations, except for using 25 PCR cyclesSequence analysis was performed with data from BAM-files using the HID-SNP Genotyper v.5.2.2 plug-in on a Torrent Suite server. Target and hotspot BED-files were provided to specify the loci of interest in the human hg19 reference genome. The following default settings were used for the data analysis: Minimum allele frequency = 0.1, minimum coverage = 6, minimum coverage of either strand = 0, and maximum strand bias = 1. The plug-in generated CSV-files that were used for the downstream analysis. The Precision ID Ancestry Panel and AmpliSeq EUROFORGEN NAME DNA libraries were analysed separately as the datasets required different target and hotspot BED-files. To evaluate the quality of the data, the heterozygote balance (Hb) and noise level were calculated. The Hb was calculated as the number of reads for one nucleotide divided by the number of reads for the other nucleotide in the called genotype in the order A, C, G, and T. Noise was calculated as the number of reads that were different from the called genotype divided by the total number of reads. Two sets of genotype acceptance criteria were applied: (1) a minimum read depth ≥ 45 reads and 0.3 ≤ heterozygote balance ≤ 3.0; and (2) for loci with a read depth of 20 to 44, 0.7 ≤ heterozygote balance ≤ 1.3 and no noise. Genotypes that did not fulfil these criteria were named NN, i.e. no data.40 using 1,000,000 Markov chain steps. Pairwise tests for linkage disequilibrium (LD) between alleles was tested with Arlequin v.3.5.2.2 using an exact test. Only individuals with full profiles (no missing data) were used for the LD analysis. Since multiple tests were performed, the P values of analyses of HWE and LD were adjusted with the method of Bonferroni41 and indicated as Pcor. Data from loci that showed statistically significant LD were further investigated using the HaploView v. 4.2 software to assess whether the loci were included in haplotype blocks using the default model42.Tests for Hardy–Weinberg equilibrium (HWE) of alleles were performed with the Arlequin v.3.5.2.2 software20  were explored. For each K, 10 iterations were performed for the EUROFORGEN NAME panel, and three for the combined panel. We used the admixed model with correlated allele frequencies. Population information was used for reference populations to help cluster formation (POPFLAG = 1). The optimal K was evaluated using STRUCTURE HARVESTER47. The membership proportions were plotted using CLUMPP v.1.1.22248 and Distruct v. 1.1.2349. Results from the PCA and the STRUCTURE analyses were used to group the 14 populations into meta-populations.The principal component analyses (PCA) were performed using a custom-designed script written in R v. 3.5.0 using the ‘23. Using the z-score test, GenoGeographer first tested if the investigated AIM profile could be grouped with any of the reference populations in the database. The test included an estimation of the variance of the allele frequencies in the reference populations50. If the P value of the AIM profile belonging to a reference population was < 0.05 (z-score > 1.64), GenoGeographer rejected the hypothesis that the AIM profile belonged to that particular reference population  accepted in only one meta-population  or (2) accepted in more than one meta-population  and the likelihood of the AIM profile belonging to the population was statistically significantly higher than those of all other likelihoods (P < 0.05). An AIM profile was included in the “Rejected” category if it was not accepted in any meta-population (z-score > 1.64). An AIM profile was included in the “Ambiguous” category if it was (1) accepted in more than one meta-population  and (2) the population likelihoods were not statistically significantly different from each other . The likelihood ratios (LR)  were compared to each other using the GenoGeographer software‘ggplot2’ v. 3.2.1 R package (https://ggplot2.tidyverse.org/index.html) were used to visualise the LRs.R v. 3.5.0 and the Supplementary Information.


Callipogon relictus is one of the largest longhorn beetle species and also the only remnant species of the genus Callipogon found in the Palearctic region. Knowledge of the phylogeographic history and current conservational status is essential to understand its unique distribution and to establish efficient conservation strategies. We studied the phylogeographical pattern and genetic diversity of C. relictus from almost its entire geographical range. The level of genetic diversity and divergence of C. relictus from the known distributions in four regions in Russia, China, North Korea, and South Korea using two mitochondrial markers (COI and COII) revealed that genetic diversity lies within the range of intraspecific levels. Relatively high genetic diversity with no distinct phylogeographic structures indicates that the wide range of current fragmented populations might be the remnant of genetically diverse populations in the past. The results of our phylogenetic and population genetic analyses suggest that C. relictus populations surveyed in the present study can be used as a “source” for a future restoration and conservation program. The findings of the genetic characteristics and phylogeographic history of C. relictus will help to establish effective conservation strategies for this endangered longhorn beetle species in Northeast Asia.The critically endangered Callipogon (Eoxenus) relictus Semenov, is the only remnant species found in the Palearctic region, while all other Callipogon species are distributed mainly in Central America and partly in South America. This species has been placed in the first category  of the Red Data Book in Russia and designated as one of the top-priority target species among all endangered invertebrate species for restoration in South Korea since 2006. Although its restricted distribution in Northeast Asia with a high conservational value has been highlighted, genetic features of C. relictus from different geographic regions remain unexplored. We first investigated the level of genetic diversity and phylogeographic patterns of C. relictus to evaluate the current conservational status and the feasibility of the implementation of a restoration program. The average genetic divergence of mitochondrial gene COI based on Kimura-2-parameter distance among the four regions in Russia, China, North Korea, and South Korea was 2.2%, which lies within the range of intraspecific levels. However, two separate clades with 3.8% divergence were identified, despite no geographical clustering of haplotypes. The linear pattern of the haplotype network with a high level of haplotype and nucleotide diversities suggests that the wide range of currently fragmented populations might be the remnant of genetically diverse populations in the past. This study will provide crucial information on the genetic characteristics and phylogeographic history of C. relictus, which will help to establish conservation strategies for this cherished insect species in Northeast Asia.The longhorn beetle,  Callipogon relictus is one of the largest, most charismatic longhorn beetle species and also the only remnant species of genus Callipogon Audinet-Serville, 1832, found in the Palearctic entomo-fauna , Quercus mongolica (Fagaceae), Quercusaliena, Quercus serrata, Carpinuslaxiflora (Betulaceae), etc. [C. relictus in South Korea; one in the Gwangneung Forest in Gyeonggi-do (province) and the other in Chuncheon in Gangwon-do, which is located 100 km to the east of the Gwangneung Forest, almost in the same latitude (37° N) [C. relictus in the Gwangneung forest and a new location in Yangyang have been reported in Korea during four consecutive years from 2007 to 2017 [e), etc. ,15,16,17 (37° N) . Unfortu to 2017 .C. relictus was found for almost 20 years in Gwangneung Forest during the period of 1986–2006 [C. relictus, therefore, has emerged as a critical need and it requires restoration of this species in Korea. Restoration practices, such as reintroduction, are becoming an effective and increasingly common strategy for conservation efforts, especially in the cases of dramatically decreasing populations in nature reserves [C. relictus, use of the current population in Gwangneung Forest is conceivable, given their continuous occurrences [While a single adult female was found every year from 2014 to 2017 , no fema986–2006 . These o986–2006 . Conservurrences . In someurrences . Neverthurrences ,22. The urrences . Reintrourrences ,35,36,37urrences . Howeverurrences ,42,43,44Genetic information, such as the genetic diversity level and phylogeographic history/structure of an endangered species, will assist in developing their effective conservation strategies ,46. It cUrsus thibetanus) in South Korea, which is one of the most successful cases for restoration of wild mammals, showed an originally low genetic diversity and the genetic admixture of two source populations, Russia and North Korea, in the restored population based on a combined analysis of mitochondrial and microsatellite markers [C. relictus from different distributions is not available and phylogeographic pattern has not been investigated, despite its unique distribution and conservation value.Furthermore, the level of intraspecific genetic variation has also been suggested to be the population’s capacity to adapt to novel environmental conditions ,50,51. I markers . Thus, t markers . HoweverC. relictus from the localities covering the whole distribution using two mitochondrial gene sequences, cytochrome oxidase I and II (COI and COII). We aimed to (1) test whether historical gene flow occurred among the current fragmented C. relictus populations in Northeast Asia and (2) to establish a knowledge base of the genetic diversity level and phylogeographic patterns amongst the geographic populations of C. relictus in Northeast Asia, in order to provide fundamental information on source populations for developing appropriate conservation strategies, including future restoration and reintroduction programs for this endangered insect species.Here, we first investigated the level of genetic diversity and divergence of C. relictus specimens from Russia , China , and North Korea  were collected between 2008 and 2015  of C. relictus of South Korean origin available on NCBI GenBank database [Callipogon species  from Mexico were used as outgroup species. The collection locations for the sampled specimens are shown in Thirty-two and 2015 , preservdatabase ,55 were COI (788 bp fragment) and COII (700 bp). PCR was performed with a total reaction volume of 20 μL using forward (C1-J-2183: 5′-CAACATTTATTTTGATTTTTTGG-3′) and reverse (TL2-N-3014: 5′-TCCAATGCACTAATCTGCCATATTA-3′) primers for COI and forward (TL2-J-3043: 5′-TGGCAGATTAGTGCAATGGATTTAA-3′) and reverse (TK-N-3768: 5′-ACTTGCTTTCAGTCATCTAATG-3′) primers for COII modified from published primers [COI and COII of C. relictus obtained in the current study were deposited in GenBank under accession numbers MW173845–MW173876 and MW160689–MW160705, respectively. Sequences of COI for Callipogonbarbatum, C. senex and C. lemoinei were also deposited under the accession numbers MW173877–MW173879, respectively.Total genomic DNA was isolated from the legs of specimens using DNeasy Blood and Tissue Kit , and PCR was performed to amplify fragments of mitochondrial  primers , using ACOI (788 bp) of C. relictus (n = 33) and the three outgroup species  were aligned using Clustal W implemented BioEdit v.7.0.1 [D and Fu’s Fs statistics estimated to test for neutrality using MEGA 4.0 [A total of 36 sequence reads of  v.7.0.1  and manuMEGA 4.0  and ARLEMEGA 4.0 .COII gene due to very low levels of overall intraspecific mean diversity (0.004) of C. relictus (n = 17).Bayesian inference (BI), maximum likelihood (ML), and neighbor-joining (NJ) analyses were conducted for phylogenetic reconstruction. BI and ML trees were inferred for all obtained sequences using MrBayes 3.2  and PhyMC. relictus were determined using NJ algorithms in DnaSP v5 [h) and nucleotide diversity (π) were estimated using ARLEQUIN v3.5. A haplotype network was inferred using HAPSTAR v0.7 [The haplotypes of the 33 individuals of DnaSP v5 . The genTAR v0.7 .C. relictus was accessed by a hierarchical analysis of molecular variance (AMOVA) analysis, implemented in ARLEQUIN v3.5. Each of the 12 populations  among the C. relictus specimens, but 0.049 (ranging from 0 to 0.219) among C. barbatum, C. lemoinei, and C. senex  and bootstrap (100) values  values . Two inte is low . Despitee is low . Furthere is low  and ChinCOII gene sequences (700 bp each) of C. relictus had only five parsimonious informative sites (0.7%), the genetic distance between pairwise comparisons of all the sequences based the Kimura-2-parameter model ranged from 0 to 0.012, and the overall average distance was 0.004  of 0.9375. The number of unique haplotypes (singletons) obtained from single individuals was 13 (39%), and the most common haplotype  was shared among North Korea (n = 5), China (n = 1), and South Korea (n = 1). A linear pattern of haplotype network was identified, and haplotypes, shared by more than two individuals, were located at both marginal ends of the network rather than being in the middle.A total of 19 haplotypes of calities  were obtφCT = −0.075) and −25.85% (φCT = −0.259), respectively. Most of the variances were observed among populations within groups and within populations in both biogeographical groupings  and 1.23247 (p = 0.707), respectively.AMOVA could not detect any significant genetic structures between two groups when the 12 populations were divided by the latitudinal degree of 40°00′ N (I) or 43°00′ N (II) . Moleculroupings . Non-sigCallipogon relictus remnant populations in Northeast Asia to provide baseline information for developing effective conservation or restoration strategies. Callipogon relictus specimens from the 12 different geographical locations, which cover almost the whole distribution of the species and extend across a distance of ~1400 km from the northern  to the southern limit (Gwangneung Forest in South Korea), did not show any distinct geographical structures   with 39% of singletons of C. relictus from 12 localities is much higher than other threatened saproxylic beetles. For examples, Rosalia alpina, an endangered and strictly protected saproxylic beetle, showed 0.541 of haplotype diversity from Central and South-East Europe [Monochamus sartor, which is one of the famous timber pests [Rhagium inquisitor, a ribbed-pine borer [Massicus raddei [C. relictus existed before and fragmented into its present distributions.We first document the phylogeographic patterns of ructures . We founructures . This geructures  might excapacity . In factcapacity . Therefoplotypes  might inthe past . Furthert Europe  and 0.68t Europe . On the er pests , Rhagiums raddei , a serios raddei , the higs raddei . This hiCOI phylogeny from 12 different localities could support the hypothesis that the current regional populations of C. relictus that we analyzed might represent the remnants of ancestral populations with genetic mosaics. Although average genetic distance was 2.2% among all 33 individuals from 12 different sites, a much greater distance was found between several individuals belonging to the two different clades  [C. relictus existed before and fragmented into its present distributions. However, we should note that the level of genetic diversity and phylogeographic pattern could be over- or underestimated due to the small sample size and geographical gaps of sampling sites in this study, since physical access to local populations and achieving large sample sizes for this endangered species are very challenging.Two distinct clades in the  gibber) . Thus, tCOI gene is known to be a good proxy for the evaluation of the conservation status of the species in the case of a lack of previous information and census data [COI) for this study, our data enable to uncover the levels of genetic diversity, divergence among populations, and also phylogeographic history of C. relictus. We are currently developing novel nuclear microsatellite markers, which can be further used for more detailed conservation study. The results of our phylogenetic and haplotype analyses could suggest that all the C. relictus sites surveyed in the present study could be used as a source population of C.relictus to the sites which are facing dramatic population decrease, as all the local populations constitute a monophyletic group with an intraspecific level of genetic divergence. For example, such reintroduction would likely improve the genetics of C. relictus in South Korea cases by increasing the genetic diversity of the local population via outbreeding. The present study indicates that the South Korean group exhibits the highest genetic similarity, compared to the North Korean , Chinese (North West), and Russian  groups, in this order (C. relictus populations covering major geographic distributions examined in the present study would be valuable for preserving current local populations and designing the successful development of a conservation program for this endangered longhorn beetle species.Genetic diversity in the sus data . Knowledsus data . Althougis order . Such geis order , the levC. relictus population is a consequence of fragmentation from the genetically fairly varied populations in the past, the reasons behind the severe reduction in populations in South Korea, in contrast to those in Russia, should be more thoroughly studied for a successful conservation program. Dramatic decreases in the Korean peninsula population have been suggested to stem from global climate change [C. relictus was found to have a limited distribution with a southernmost limit above 37° N, it may be hypothesized that the distributional range of C. relictus is associated with higher latitudes. The influence of temperature and global change on the abundance and distribution of terrestrial invertebrates are well-documented in most Lepidoptera [C. relictus were not northern or boreal species but rather adapted to the climate of Northeast Asia [C. relictus in South Korea is that the rapid reduction in population was caused by anthropogenic habitat destruction rather than climate change. It is also worth noting that the systematic logging of Caprinus laxiflora, C. laxiflora, Quercus aliena, and Q. serrata [C. relictus, in the Gwangneung Forest during the 1970s resulted in a temporal shortage of suitable host trees and dramatically reduced the Gwangneung population, which is located at the southern limit of the species distribution, in a region that may be a unique habitat in South Korea. It might be concluded that the massive logging of C. laxiflora colonies resulted in the simultaneous removal of multiple generations of juveniles developing in the timbers.If the pattern of the current e change . Indeed,idoptera ,78,79,80idoptera ,82, reduidoptera ,84, and idoptera ,85. Moreidoptera . It was ast Asia . An alte serrata , which iC. relictus populations, spanning almost its entire geographical range, analyzed in the present study will provide baseline, but valuable guidelines for maintaining current local populations and also for developing a successful conservation program for this endangered longhorn beetle species.The information on the genetic diversity and phylogeographic pattern/structure of


Equus hemionus ssp. in Israel, a breeding core was created from individuals of two different subspecies (E. h. onager & E. h. kulan). Today the population comprises approximately 300 individuals and displays no signs of outbreeding depression. The aim of this study was a population genomic evaluation of this conservation reintroduction protocol. We used maximum likelihood methods and genetic clustering analyses to investigate subspecies admixture and test for spatial autocorrelation based on subspecies ancestry. Further, we analysed heterozygosity and effective population sizes in the breeding core prior to release and the current wild population. We discovered high levels of subspecies admixture in the breeding core and wild population, consistent with a significant heterozygote excess in the breeding core. Furthermore, we found no signs of spatial autocorrelation associated with subspecies ancestry in the wild population. Inbreeding and variance effective population size estimates were low. Our results indicate no genetic or behavioural barriers to admixture between the subspecies and suggest that their hybridization has led to greater genetic diversity in the reintroduced population. The study provides rare empirical evidence of the successful application of subspecies hybridization in a reintroduction. It supports use of intraspecific hybridization as a tool to increase genetic diversity in conservation translocations.Reintroductions are a powerful tool for the recovery of endangered species. However, their long‐term success is strongly influenced by the genetic diversity of the reintroduced population. The chances of population persistence can be improved by enhancing the population's adaptive ability through the mixing of individuals from different sources. However, where source populations are too diverse the reintroduced population could also suffer from outbreeding depression or unsuccessful admixture due to behavioural or genetic barriers. For the reintroduction of Asiatic wild ass  The long‐term goal of a viable self‐sustaining population is strongly dependent on the genetic makeup  actively selected against males of a different color morph, thereby preventing hybridization of different genetic clusters within the same species  and the Turkmen kulan (E. h. kulan)  were collected opportunistically during veterinary treatments, fitting of radio collars and from animals killed in traffic accidents from across the population's range  and E. h. kulan (N = 15) subspecies from captive populations in European zoos, collected opportunistically during veterinary treatments or from dead individuals  and Sbfl1 . The ddRADseq library preparation followed a protocol adapted from Peterson et al.  to purify DNA, following the manufacturers protocol. Samples were digested with the high‐fidelity versions of the restriction enzymes n et al. . Librarin et al.  and a me2.3n = 9, onagers n = 5) to identify diagnostic SNPs, which are fixed for alternative alleles in the two subspecies and calculated hybrid indices as the proportion of alleles inherited from either subspecies . Out of the total of 4231 SNP positions, two were not detected in any of the onagers and were removed from the analysis. Of the remaining 4229 SNPs, only 13 (0.3%) were found to be fixed for different alleles in the two subspecies populations.To investigate levels of admixture in the Israeli populations, we calculated hybrid indices for each individual. First, we analysed the zoo samples  for other samples. We further investigated admixture levels using pairwise fixation indices (FST) and calculated for all pairs of populations in the hierfstat R package  as 2. We set the alternative ancestry prior (POPALPHAS = 1) which allows for distinct α‐values for each ancestral population, as recommended when sampling is unbalanced  chain preceded by 1 × 105 burn‐in iterations and 10 repetitions.We calculated individual hybrid indices both from diagnostic SNPs and using maximum likelihood (ML) methods implemented in the R package  Goudet, . We tested Wang, . Runs weadegenet R package  for this analysis. We calculated expected (He) and observed heterozygosity (Ho) and the mean inbreeding coefficient across loci for each population using the pegas R package  and inbreeding (Nef) effective population sizes using the program NeEstimator V2 , as recommend for larger numbers of markers . These values indicated a very even subspecies ancestry in the founder population which shifted after release to a slightly higher proportion of onager ancestry in the wild population. This was consistent with pairwise FST values, which were all significant at p < 0.05. The founder and wild population both displayed a stronger genetic differentiation from the kulans than from the onagers  and those obtained by maximum likelihood including all 4229 SNPs  and kulans . The founder population also displayed significantly greater variation in individual heterozygosity levels  than the wild population  (Bartlett's test: K‐squared(1) = 5.194, p < 0.05; Figure FIT was low in all populations, yet significantly smaller in the founder population than in the wild , while the linkage disequilibrium method estimated an inbreeding effective size of Nef = 27.6 (19.2–43.9). For the founder population, the estimated inbreeding effective size was even smaller at Nef = 7.1 (3.2–12.6).Effective population size estimates for the wild and the founder population were small. For the wild population, the temporal method estimated a variance effective population size (95% CIs) of 4E. h. onager and E. h. kulan. Our population genomic analysis demonstrated high levels of admixture between these subspecies in the breeding core (founder population), after three generations of unmanaged mating. Admixture levels remained high in the reintroduced wild population, yet with a slight bias towards increased onager ancestry. No spatial autocorrelation arising from subspecies ancestry was detected in the wild population. These results indicated that there were no genetic or behavioural barriers to subspecies hybridization and that no cryptic subpopulations have formed due to a lack of admixture. This may be due to weak genetic differentiation between the subspecies; we found that only 0.03% of the analysed SNPs were fixed for opposite alleles in the onager and kulan samples, which is consistent with previous findings demonstrating only low genetic divergence between onagers and kulans  succeeded in establishing large free‐ranging populations  exceeding those observed in other reintroduced populations of E. hemionus (Saltz & Rubenstein, E. hemionus ssp. in Israel, controlled experiments would be necessary to verify whether the hybridization was critical to this rare reintroduction success, and these are not currently feasible. Nevertheless, our results are in‐line with a growing body of literature which suggests that sourcing founder individuals from different subspecies, or genetically differentiated populations, can enhance the population genetic diversity.Our analysis has wider implications for conservation translocations in general. The reintroduction in Israel is a rare success in Despite increasing evidence that intraspecific hybridization holds enormous potential for species recovery programmes, deliberate admixture of individuals from different subspecies or even genetic lineages remains highly controversial. This is because of the associated risk of outbreeding depression if source populations are genetically too divergent (Frankham et al., Intentional admixture may be considered as a conservation tool for systems where the risk of outbreeding depression is low. While still much research is needed on how to accurately predict the risk of outbreeding depression, a cautious approach could include a first stage of careful assessment of the genetic differentiation between potential source populations (e.g. see Frankham et al., While there is increasing evidence for the potential benefits of mixed source reintroductions, long‐term genetic data of successfully admixed reintroduced populations are scarce. Yet such case studies are important for evaluating this strategy as a conservation tool and advancing general conservation translocation guidelines. Our study therefore represents an advance through provision of valuable empirical data on a successful and complete admixture between individuals from two different subspecies.None declared.Supplementary MaterialClick here for additional data file.


Triosteum pinnatifidum Maxim., an alpine plant, is traditionally used for several medicinal purposes. Here, both chloroplast DNA sequences and nuclear low copy sequence markers were used to investigate the genetic diversity and population structure of T. pinnatifidum. Materials were collected from thirteen localities in the northeast Qinghai–Tibet Plateau (QTP) and adjacent highlands and advanced analytical toolkits were used to access their origin and range shifts. The results revealed a higher level of population differentiation based on chloroplast DNA (cpDNA) concatenated sequences compared with the nuclear DNA sequences , indicating that pollen flow was still extensive in T. pinnatifidum. A decline in haplotype variation was observed from the plateau edge and adjoining highlands toward the platform of the QTP. The hypothesis “dispersal into the QTP,” proposing that T. pinnatifidum experienced migration from the plateau edge and adjacent highlands to the platform, was supported. These results were in line with the hypothesis that multiple refugia exist on the plateau edge and adjacent highlands rather than on the plateau platform. Our unimodal mismatch distribution, star-like network supported a recent expansion in T. pinnatifidum. Fluctuations in the environment and climate have a great effect on both genetic structure and species distribution . Quatern2   . Such coforests) . Thus, tforests) .Extreme environments, including glaciers, can threaten the survival of plants and cause a sharp reduction in plant distribution to refuge areas . HoweverAconitum gymnandrum .Glacier refugia are found on several mountains in China . Howevermnandrum  and PotePicea crassifolia  is a perennial species distributed in sunny places along the streamside and coniferous forests from 1,800 to 2,900 m  and one nuclear DNA low copy sequence (AT103) were generated for 13 localities and analyzed with advanced toolkits. For demographic history analysis, palaeodistributional modeling was used. To clarify our objectives, all localities were divided into two groups: the Edge group (P7–P13) and the Platform group (P1–P6).Our objectives were (i) to explore the molecular diversity and population structure using both maternally inherited chloroplast DNA and biparentally inherited nuclear DNA sequences, and (ii) to investigate distribution range shifts (to the plateau) of Different field expeditions were carried out during 2008 and 2017 to collect as many of the locality as possible in accordance with the specimen records in the herbaria. From the field, fresh leaves of 3–14 individuals were collected for each locality, separated by at least 20 m. The distance between localities was usually more than 50 km. A total of 86 individuals from 13 localities were collected in the Sichuan, Qinghai, Shaanxi, and Shanxi provinces. Among these localities, five were from the QTP, three localities were from the adjoining highlands region, and five localities were from the plateau edge . The leaGenomic DNA was extracted from the silica-gel dried leaves following a modified Cetyltrimethyl Ammonium Bromide (CTAB) protocol . The qua2+), 2.0 µL 10 mM dNTPs, 1 µL 5 pM of each primer, and 0.4 µL (1.5 units) Taq polymerase . The amplification conditions were 5 min at 95 °C, followed by 35 cycles of 50 s at 95 °C, 1 min at 58 °C, and 1 min at 72 °C, with a final extension of 6 min at 72 °C. PCR products were purified using the CASpure PCR Purification Kit  following the manufacturer’s protocols. Sequencing reactions and analysis were performed using an ABI 3730xl DNA sequencer .Polymerase chain reactions (PCR) were performed at a 50 µL volume containing 1.2 µL template DNA (∼20 ng), 5 µL 10 × PCR buffer (with Mghttp://www.technelysium.com.au). The DNA sequences were aligned in Clustal_X (T. pinnatifidum were submitted to GenBank (MH277369 –MH277382). The cpDNA fragments, rbcL-accD and rps15-ycf1, were concatenated for downstream analyses.The chromatograms of each sequence were checked visually using Chromas ver. 2.33  calculations as implemented in Network ver. 5.0.0.3 , total gene diversity (HT), GST , GST , and NSTGST . The significance of FST was tested using 1,023 permutations. Formula Nm = (1−FST)/(4*FST) was used to estimate the gene flow for overall localities  was used as a statistical test to accept or reject the hypothesis of sudden population expansion. Harpending’s raggedness index (HRI)  and its http://www.gbif.org/) and the occurrences were grouped. After this, the best ecological niches were fitted in the present and past  using different available algorithms: surface range envelope  within an R environment through different packages. Briefly, six bioclimatic variables ; isothermality; annual precipitation; precipitation of driest; and precipitation seasonality (coefficient of variation), All algorithms were employed in BIOMOD2 . The MCr years;  was usedHT) were much higher than those of gene diversity within localities (HS) for T. pinnatifidum in the overall localities based on the two datasets , the edge group , and the platform group  haplotypes (H1–H7) and five AT103 haplotypes  were retrieved based on polymorphic sites across the concatenated cpDNA sequences  and the Platform group (P1–P6). The grouping strategy was organized by the: (1) difference in the altitude of localities, with the Edge group under 2,900 m and the Platform group above 3,000 m (NST < GST). For both cpDNA and AT103 haplotypes, NST (number of substitution types) was smaller than GST  overall and in the two groups (except for AT103 in Edge group), and a nonsignificant phylogeographic structure was shown  loc 3,000 m ; Fig. 1.as shown .T. pinnatifidum Northwest China distribution. Other young haplotypes surrounded these two haplotypes as branches in the network. The unique cpDNA haplotype H3 and idiotypic AT103 haplotype S5 were only distributed in adjacent highlands (Shaanxi and Shanxi provinces). Another unique AT103 haplotype S4 only existed on the QTP platform. Additionally, the haplotype network was star-like, indicating the expansion of T. pinnatifidum localities.Our network analysis indicated that the cpDNA haplotype H2 and AT103 haplotype S2 could be the origin of other haplotypes because they remained at the center of the structure . They weD values based on chloroplast DNA and AT103 sequences overall and in the two groups were negative or zero but not significant . Fu’s Fs statistics for cpDNA also showed nonsignificant negative or positive values for the two datasets, which revealed the relative stability of the T. pinnatifidum localities , Edge, and Platform groups, respectively; Tajima’s calities . Howevercalities . Due to Paleodistribution modelling also supported the hypothesis of increased suitable habitat, mainly from the QTP to its periphery . The PalT. pinnatifidum experienced three large population increases between 5–7 Ma, followed by a small decline about 2 Ma, and remained relatively stable for the rest of the time.The result of bayesian skyline plot analyse indicated that FST = 0.654 vs. 0.5763 vs. 1.00 for cpDNA, FST = 0.398 vs. 0.2411 vs. 0.6606 for AT103 of the overall distribution, Edge group, and Platform group respectively). This may indicate that pollen gene flow has a widespread influence on the T. pinnatifidum population. A study by Nm < 1), indicating divergence between localities . This was regarded as evidence for extremely limited seed gene flow but extensive pollen gene flow  as revealed by chloroplast and nuclear markers; however, population differentiation was higher for ITS sequences (FST = 0.9627) than for cpDNA (FST = 0.6368) markers. Seed migration that occurred among localities that could homogenize maternally inherited genetic variation and inbreeding in localities of R. chrysanthemifolia were interpreted as the two causes.Similarly, the study of ene flow . Such a anations . Gao et T. pinnatifidum seed has limited germination rates and lower dispersal efficiency than pollen. In conclusion, the conflicting patterns of population differentiation in T. pinnatifidum could be due to matrilineal inheritance of cpDNA markers in the case of restricted seed migration. Our results demonstrated that different sources of genetic variation for DNA markers could provide divergent molecular information. Thus, the joint application of plastid and nuclear DNA markers could improve the research accuracy of genetic variation and population structure. Additionally, more low- or single-copy nuclear genes are needed to promote the dataset in future studies.As described above, HS) was detected for the two datasets  of cpDNA was higher than that of AT103 in this species  HT = 0.950, HS = 0.571,  and environmental factors  (T. pinnatifidum may result mainly from the high frequency of common haplotypes (H2 for cpDNA and S2 for AT103) throughout the distribution  . The genribution . Furtherribution , and difribution . Due to T. pinnatifidum from the plateau edge and adjoining highlands to the platform of the QTP suggested a marked founder effect in the relatively recent past  that were more widely distributed along the edge of the QTP platform. This is similar to the third hypothesis explaining species range shifts on the QTP, as described previously. For the founder effect, after glaciation or other conditions, the genetic diversity of localities in the glacier refugia would be more abundant than that in later or recently occupied areas.The dominant haplotypes H2 and S2 were contained in several localities from the plateau edge and adjacent highlands as well as in most plateau platform localities. Thus, our survey supports the “into the QTP” hypothesis that QTP platform localities were colonized from either a single refugium or from several refugia localities  distinct expansions occurred in the last interglacial maximum up to the last glacial maximum, (ii) a partial reduction occurred during the Mid-Holocene, and (iii) from the Mid-Holocene to the current period, the species has expanded, which is not significant as it has occurred on a small range. Range expansion in LGM or other cold periods has been reported for several alpine plant species distributed in the QTP and adjoining areas . This pacold LGM .T. pinnatifidum has experienced current demographic expansion. The mismatch distribution analysis with SSD and raggedness index values did not reject a sudden expansion model. Additionally, bayesian skyline plot analysis of T. pinnatifidum showed three large population increases between 5–7 Ma.Similarly, the star-like network together with the unimodal distribution of mismatches  based onIn certain plateau edge and adjacent highland localities, there was an absence of dominant haplotypes. In particular, locality P2  was fixed with no dominant haplotype for either the cpDNA or AT103 dataset. However, the star-like network of the cpDNA and AT103 haplotypes suggested that all branch haplotypes originated from the dominant haplotypes H2 and S2, respectively. The isolation created by the characteristic topography and environment generally leads to the reduction of genetic variation and conservation of private haplotypes. Thus, isolation could be the cause of the absence of dominant haplotypes in certain localities.T. pinnatifidum, was assessed for the first time. An integrated approach of paleodistribution reconstruction combined with genetic data was used. Disparate patterns of genetic diversity based on cpDNA and nuclear DNA markers were observed.The development and retreat of glaciers and the ecological environment have had a marked impact on the species distribution and genetic structure. Here, the genetic structure, diversity, and demography of an important medicinal herb species, T. pinnatifidum localities than that based on nuclear DNA. This idiosyncratic pattern might be due to a high level of pollen-mediated gene flow and limited gene flow through seeds in the T. pinnatifidum locality. Our results further revealed that there may have been one or several refugia for this species during glaciation. The dispersal of T. pinnatifidum from the plateau edge and adjoining highland to the plateau platform was also represented. We refrained from making strong conclusions; however, our work provides a basis to substantiate the alternative hypothesis regarding range shift on the QTP and adjacent highlands.There was higher genetic variation based on the cpDNA in 10.7717/peerj.12754/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.12754/supp-2Supplemental Information 2Bio1-annual mean temperature (°), bio2-mean diurnal range [mean of monthly max temp-min temp] (° ), bio3-isothermality (BIO2/BIO7)( ×100), bio12-annual precipitation (mm), bio14-precipitation of driest month (mm), bio15-precipitation seasonality (mm)Click here for additional data file.10.7717/peerj.12754/supp-3Supplemental Information 3Click here for additional data file.


Populus tremula) across Europe by means of whole-genome resequencing of a collection of 411 individual trees. We dissected admixture patterns between aspen lineages and observed a strong genomic mosaicism in Scandinavian trees, evidencing different colonization trajectories into the peninsula from Russia, Central and Western Europe. As a consequence of the secondary contacts between populations after the last glacial maximum, we detected an adaptive introgression event in a genome region of ∼500 kb in chromosome 10, harboring a large-effect locus that has previously been shown to contribute to adaptation to the short growing seasons characteristic of Northern Scandinavia. Demographic simulations and ancestry inference suggest an Eastern origin—probably Russian—of the adaptive Nordic allele which nowadays is present in a homozygous state at the north of Scandinavia. The strength of introgression and positive selection signatures in this region is a unique feature in the genome. Furthermore, we detected signals of balancing selection, shared across regional populations, that highlight the importance of standing variation as a primary source of alleles that facilitate local adaptation. Our results, therefore, emphasize the importance of migration–selection balance underlying the genetic architecture of key adaptive quantitative traits.Understanding local adaptation has become a key research area given the ongoing climate challenge and the concomitant requirement to conserve genetic resources. Perennial plants, such as forest trees, are good models to study local adaptation given their wide geographic distribution, largely outcrossing mating systems, and demographic histories. We evaluated signatures of local adaptation in European aspen ( FST and absolute divergence DXY  after several filtering steps . A deeper analysis of the composition of the species structure with NGSAdmix revealed five different ancestral populations and different levels of hybridization in particular geographic regions. Chinese and Russian samples, represented by solid colors in Due to the broad geographic coverage of Given these observations, we took a closer look at the genomic mosaicism of the Scandinavian population. We used EIGMIX, taking Russian, Scottish and Latvian populations as proxies of the ancestral Siberian, Western and Central European populations, respectively . These pFST estimations , or Latvia and Southern Scandinavia , whereas comparisons between populations without signs of admixture, such as China and Russia, reached values as high as 0.35, which approach FST values observed between closely related aspen species.These observations were also supported by imations , as we oP. tremula for potential introgression events that could have occurred given the admixed background we observed in Scandinavia. We followed a four-taxon approach for these scans, keeping the Chinese population as an outgroup in all our comparisons. We calculated the fdM introgression statistic , which combines both fd and distance estimations and that is less sensitive to the timing of gene flow. Both estimators give positive values when introgression occurs between P3 (donor population: Russia or Latvia) and P2 (Northern Scandinavia), and negative values if it occurred between P3 and P1 (Southern Scandinavia), on a scale from −1 to 1. When evaluating gene flow from Russia into Scandinavia, we obtained fdM and df mean genomic values of −0.008 and 0.014, respectively (fdM = 0.85 (FDR = 3.6e−3) and df = 0.89 (FDR = 1.33e−50). As expected, there were differences in DXY and FST patterns between subpopulations at this region: FST is remarkably high between Nordic subpopulations and any other geographic location, whereas DXY decreases when northern Norwegian, Swedish, and Russian subpopulations are contrasted  genes, are encoded in this introgressed genomic block: Potra2n10c20839  and Potra2n10c20842  and the region surrounding these two genes is known to have been subject to a selective sweep in the northern Swedish population  did not reach the accepted significance threshold to be confidently classified as regions targeted by positive selection or 2) were not geographically limited, that is, they are present in at least two distant subpopulations  online. FST values did not differ between BS-affected regions and genome-wide estimations, however , with an average value of 0.17 on the BS bins versus 0.11 at the genome-wide level B; averag however  online.  however C. The in[FDR] < 0.01 and ADD ≥ 0.5 (dosage form donor A(Latvia) = 0.76; dosage form donor B(Russia) = 0.24), where the predicted up/downstream gene models correspond to Potra2n15c28701/02, annotated as presenilin-like and exocyst subunit Exo70 family protein-coding genes, respectively. Similarly, in the Nordic populations of Scandinavia, we identified regions of Russian ancestry with SNPs displaying high β-scores on chromosome 4  = 0.29; dosage from donor B(Russia) = 0.71) only 3 kb downstream of the gene model Potra2n4c9007 annotated as a gibberellin 3-beta-dioxygenase coding gene, and on chromosome 19  = 0.29; dosage form donor B(Russia) = 0.71), upstream of gene model Potra2n19c34341, annotated as and autophagy-related protein 13 coding gene.We took a deeper look at gene models in close proximity to SNPs with high β-scores and high ADD in hybrid populations, as the bias in allele dosage from any of the donor population could give insights on the beneficial impact of those alleles  online. P. tremula across the Eurasian continent provides a good scenario to test for changes in population sizes across time. We evaluated population size changes through time using the stairway plot method, which is based on the composite likelihood of the site frequency spectrum (SFS) of the species and/or selected subpopulations. We used 50 random samples from our collection to generate the overall behavior of the species, as well as for specific collection sites (Russia and Northern Scandinavia). We observed the strongest reduction in Ne ∼700–800 ka and this sharp decrease in Ne was observed across all subpopulations, which means it was a bottleneck that affected the entire species and that predated its dispersal in the Eurasian continent. A second bottleneck occurred ∼150–170 ka in the populations from Central Europe and Scandinavia, and a third, mild bottleneck spanned from ∼10–35 ka, a period representing the last glacial era in the Northern hemisphere. These two bottlenecks were not present in the Russian subpopulation and instead, we only observed a second decrease of Ne around 60–80 ka in this population (The expansion of pulation .4), whereas the divergence of both lineages occurred 760 ka, consistent with the first bottleneck seen at the species level in the stairway plot analyses.Given the admixed nature of the Scandinavian individuals, we also evaluated 19 different demographic models including simple models of divergence with and without migration, models with instantaneous size changes, ancient migration or secondary contact, ancient migration plus instantaneous size change, and island models of vicariance and founder events. We used two levels of resolution for this analysis: We ran the 19 models at the chromosome level  online, P. tremula is not a novel idea, in fact, it has previously been documented between divergent lineages in Europe using data from microsatellite loci , Russia, Scandinavia (Sweden and Norway), Eastern European (Latvia) and what we suggest may correspond to Central and Western Europe (Scotland and Southern Norway + Iceland). Although Chinese and Russian individuals appear to be partly isolated from Western populations , the genomic mosaicism is evident particularly in Scandinavia, where the population can be divided into at least two different groups that follow the latitudinal gradient along the peninsula. Individuals from Northern Scandinavia have a strong Russian ancestral component, whereas those from Southern Scandinavia have strong influence from both Eastern and Central/Western European population. The observations of two independent routes of colonization of Scandinavia, one from the south and another one from the northeast along the ice-free Norwegian Atlantic coast, agree with findings in other organisms, such as brown bears , we observed that Russian and Northern Scandinavian populations have experienced symmetric migration following a secondary contact, making it possible for backcrossing to occur and thereby promoting introgression between the two populations. Second, using information only from the adaptively introgressed region on chromosome 10, we confirmed that, indeed, the secondary contact models are the most strongly supported (together with vicariance and late admixture) and that the migration in this region was stronger from Russia into Scandinavia than in the opposite direction  online. FT2 allele present in Northern Scandinavia displays partial dominance  in regions across multiple chromosomes shared by all the aspen lineages, indicated that BS has maintained ancestral polymorphisms in the species. Indeed, excess of diversity around selected loci may be due to the retention of ancestral polymorphisms or due to the accumulation of derived polymorphisms, which happens faster than expected under neutrality. The former is expected if the same allelic lineages have been evolving under BS for a long time, with drift and mutation determining polymorphism within each lineage. The latter would occur if new, more recent instances of BS appear, facilitating the establishment of new neutral polymorphisms ; given tArabidopsis thaliana  between individuals to minimize the risk of sampling identical genets. Leaf samples were stored in silica gel before shipping to Sweden. Geographical coordinates were recorded for the sampled trees. The individuals included in the study  and their geographic origins are listed . For the Icelandic samples, library preparation and sequencing were conducted by Génome Québec, Canada. Briefly, 1 µg of high-quality DNA was used for paired-end libraries construction. The 12 libraries were sequenced in three lanes of Illumina HiSeqv4 with read length of 125 bp. All other samples were subjected to paired-end sequencing using libraries with an average insert size of either 350 or 650 bp, and samples were sequenced by the National Genomics Infrastructure at Science for Life Laboratory, Stockholm, on an Illumina HiSeq 2000 or Illumina HiSeq X platform to a mean per-sample depth of approximately 17×.P. tremula v2.0  and found that they did not exceed 14% of the sequencing reads in individual libraries (ranging from 3% to 13.8%).Resequenced accessions were mapped against the reference genome of ula v2.0 , using Bula v2.0 ]—mem aliula v2.0 . Depth aula v2.0  online. P. tremula, available at ftp://plantgenie.org/Data/PopGenIE/Populus_tremula/v2.2/, using picard LiftoverVcf, which allowed for better resolution at the chromosome level. Further SNP pruning with vcf/bcftools removed positions with extreme depth values , absent in more than 30% of the samples, nonbiallelic or displaying an excess of heterozygosity .We used GATK v3.8 to call variants . First, We used plink .Next, we used vcftools to output the genotype likelihood information contained in the pruned VCF file; the resulting beagle-formatted file was input into NGSAdmix to estimate individual admixture proportions across a varying number of ancestral populations . We treated each chromosome independently; the corresponding vcf file was converted to .geno format using parseVCF.py. From these files, we calculated diversity and divergence values for each subpopulation  in nonoverlapping 10-kb windows, using the script genomics.py. Finally, we used the script ABBABABAwindows.py to compute the four-taxon D statistic and f estimators in nonoverlapping windows of 10 kb as well. For these calculations, we tested gene flow from the Russian  or Latvian  subpopulations into Northern Scandinavia  or Southern Scandinavian , setting the Chinese  samples as the outgroup. Since we were interested in estimating shared variation between Russian and Northern Scandinavian individuals, we focused on the fdM introgression statistic, described by fdM gives positive values when introgression occurred between P3 and P2, and negative values if it occurred between P3 and P1. In order to avoid stochastic errors that could produce meaningless values, we only considered windows with at least 100 biallelic SNPs.We combined several statistics developed to identify introgressed genomic regions. These included the classic ABBA–BABA test in its developed df  was 15, which we chose as the lower threshold to keep chromosome fragments considered to have BS signals. We then revised the gene content in such windows, allowing for sites to be within and up/downstream of the gene models. We used topGO v.2.36.0 (In addition, we ran betascan , to detev.2.36.0  to look A, supplementary fig. 11A, Finally, we combined iSAFE and β-scores with ELAI calculated ADD to assess the effect of hybridization in each scan of selection C and 5C.supplementary figure 11We chose StairwayPlot  to inferPopulus (In addition, we aimed to confirm the directionality of the gene flow events we detected on chromosome 10 between the Russian and Scandinavian individuals. For this, we explored alternative demographic models using the diffusion approximation method of dadi  to analyPopulus . We ran Populus  online fPopulus  online.In order to generate confidence intervals for the parameters estimated from the demographic models with the highest likelihood, we created 100 bootstrap replicates of the spectra and calculated the standard deviations of the best-fit parameters using the Godambe methods .Molecular Biology and Evolution online.msab229_Supplementary_DataClick here for additional data file.


Populus sect. Turanga (hereafter referred to as “Populus”), including Populus euphratica and Populus pruinosa, are the predominant tree species in desert riparian forests in northwestern China. These trees play key roles in maintaining ecosystem balance, curbing desertification, and protecting biodiversity. However, the distribution area of Populus forests has been severely diminished and degraded in recent years due to increased habitat destruction and human activity. Understanding the genetic diversity among Populus individuals and populations is essential for designing conservation strategies, but comprehensive studies of their genetic diversity in northwest China are lacking. Here, we assessed the population structures and genetic diversity of 1,620 samples from 85 natural populations of Populus (59 P. euphratica and 26 P. pruinosa populations) covering all of northwestern China using 120 single nucleotide polymorphism (SNP) markers. Analysis of population structure revealed significant differentiation between these two sister species and indicated that strong geographical distribution patterns, a geographical barrier, and environmental heterogeneity shaped the extant genetic patterns of Populus. Both P. euphratica and P. pruinosa populations in southern Xinjiang had higher genetic diversity than populations in other clades, perhaps contributing to local geographic structure and strong gene flow. Analysis of molecular variance (AMOVA) identified 15% variance among and 85% variance within subpopulations. Mantel tests suggested that the genetic variation among P. euphratica and P. pruinosa populations could be explained by both geographical and environmental distance. The genetic diversity of P. euphratica showed a significant negative correlation with latitude and longitude and a positive correlation with various environmental factors, such as precipitation of warmest quarter and driest month, temperature seasonality, and annual mean temperature. These findings provide insights into how the genetic differentiation of endangered Populus species was driven by geographical and environmental factors, which should be helpful for designing strategies to protect these genetic resources in the future. Populus euphratica Oliv. and Populus pruinosa Schrenk are sister species in the section Turanga . Both species are predominant trees in the extremely arid desert areas in northwestern China and play important roles in maintaining ecosystem balance and protecting biodiversity  indicated that this was lower in southern Xinjiang (SX) than in northern Xinjiang (NX)  and P. pruinosa  in northwest China. Based on our de novo assembled reference genome and published resequencing data, we developed 120 high-quality SNPs with MAF ≥ 0.4 for further genetic analysis. Our objectives were to (1) determine the optimal population structures of P. euphratica and P. pruinosa; (2) evaluate genetic diversity and genetic differentiation between and within the subpopulations; and (3) assess the relationships between population-level genetic diversity and geographical as well as environmental factors. Our findings provide new insights into the genetic differentiation of P. euphratica and P. pruinosa and lay a genetic foundation for the construction of priority conservation areas of Populus.In this study, we collected the leaves of 1,620 accessions from 85 natural populations throughout the natural distribution range of P. euphratica individuals from 59 natural populations in northwest China, including 27 populations from southern Xinjiang (SX), 23 from northern Xinjiang (NX), and 9 total from Gansu (GS), Qinghai (QH), Ningxia (NiX), and Inner Mongolia (NMG) provinces , 22 of which co-occurred with P. euphratica. To reduce the impact of clonal ramets, all sampled individuals from each population were located at least 100 m apart. The leaves were dried with silica gel in the field. Total DNA was extracted from the leaves and purified using a modified CTAB method  values ranged from 60°C to 64°C, with an optimal value of 62°C; (iii) product size was ≤500 bp; (iv) sequenced reads had to be able to cover target sites. Primers for each target site that could specifically amplify the target were obtained  SNPobtained . LibrariP. euphratica reference genome using the BWA-MEM algorithm (version 0.7.15-r1140). After alignment, GATK (version 3.7)  adaptor sequences of reads were removed using Cutadapt software (version 1.13); (ii) low-quality bases were removed using Trimmomatic software (Version 0.36); (iii) reads ≤50 bp long were excluded. The reliable clean reads were aligned to the K-value was used to evaluate the number of clusters based on the genotyping data; the number of genetic clades was predefined using 10,000 iterations for each run. The optimal K-value was determined using Structure Harvester  was calculated. Multiple indicators of genetic diversity from each population, such as Shannon's information index (I), observed heterozygosity (Ho), expected heterozygosity (He), and polymorphism information content (PIC), were obtained using GenAlEx v6.503.Analysis of Molecular Variance (AMOVA) was performed and Nei's genetic distance was calculated using GenAlEx 6.503 based on the number of subpopulations  were obtained  were retained (https://genepop.curtin.edu.au/) . Latitude and longitude were considered to be the main geographical factors affecting the P. euphratica and P. pruinosa populations. All seven retained bioclimatic variables were environmental factors. PCA was used to analyze the climate variables of the sample sites, and the absolute values from standardized PC1 scores were obtained based on correlation analyses using R version 3.5.0.To examine the relationships between genetic diversity at the population level and geographical factors, as well as environmental factors according to a previous study  and P. pruinosa , we sampled 1,620 individuals from 85 natural Populus populations covering the distribution regions throughout northwestern China . In addition, for P. euphratica, compared to previous studies, we collected samples from the easternmost population (SZWQ) of China for the first time and added samples from Ningxia Province (ZW). For P. pruinosa, compared to previous studies, samples from three populations of P. pruinosa  were collected for the first time in northern Xinjiang , implying the presence of recent gene flow in the two species. When K = 3, the P. euphratica populations were further divided into southern Xinjiang, northern Xinjiang, and mixed clusters . When K = 4, the P. euphratica populations were divided into four distinct clades that demonstrated strong geographical distribution patterns .We then carried out population structure analysis based on our genotypic data . When K P. pruinosa and P. euphratica, and intermediate individuals (SX1) were primarily from the mixed forests of P. pruinosa and P. euphratica in southern Xinjiang   of this region. The phylogenetic tree, which was constructed to represent the genetic distances between these populations, revealed distinctly different evolutionary relationships among the populations (P. euphratica and P. pruinosa) showed significant differentiation at the species level regardless of geographical distance.PCA and neighbor-joining phylogenetic analysis confirmed our findings about population structure. PC1 mainly explained the variation between and LPX) . The preulations . All thrP. euphratica and P. pruinosa  for each clade and population. The genetic diversity values revealed higher diversity for P. pruinosa (He = 0.256) than for the four clades of P. euphratica. For P. euphratica, the SX clade exhibited the highest genetic diversity (He = 0.216), followed by the GNM clade (He = 0.212) and the NX clade (He = 0.206), while the QH clade had the lowest genetic diversity (He = 0.112)  .P. euphratica and P. pruinosa  had the highest genetic diversity (He = 0.29) and the TLX population (from the TC region of northern Xinjiang) had the lowest genetic diversity (He = 0.11). On the whole, the populations of southern Xinjiang had relatively high genetic diversity , followed by one population from Inner Mongolia (EJN) and those from Ningxia (ZW) and Gansu (GZX and JTX), while the populations of northern Xinjiang  and QH (GEM), and the second population from Inner Mongolia (SZWQ), had relatively low genetic diversity  had the highest genetic diversity (He = 0.28), while the YLX population (BaZ region of southern Xinjiang) had the lowest (He = 0.12). The three P. pruinosa populations  found only in northern Xinjiang had relatively low genetic diversity  between P. euphratica and P. pruinosa was high , moderate differentiation between NX and SX (FST = 0.044) and between NX and QH (FST = 0.044), and lower genetic differentiation between SX and GNM (FST = 0.010).The genetic divergence  and ALE (8/11) samples were in SX1  was higher, especially for MLX, FYX, TLX, MQX, SZWQ, and GEM , which is associated with the isolated geographic location of this region  than among populations (15%) of P. euphratica, suggesting a high level of differentiation (FST = 0.147) accompanied by a high rate of gene flow between P. euphratica populations (Nm = 1.447).We further analyzed the genetic differentiation within e in SX1 , suggest and GEM . Howevers region . Overallntiation . Nei's gPopulus is significantly associated with isolation-by-distance and/or isolation-by-environment, we conducted Mantel tests between pairwise genetic differentiation [FST/(1 – FST)] and a geographical distance matrix, as well as a Euclidean bioclimatic distance matrix with the seven bioclimatic variables. Geographical distance  than the P. pruinosa populations (R2 = 0.05), while geographical distance contributed equally to the genetic differentiation of both the P. euphratica and P. pruinosa populations.To determine whether the genetic differentiation in distance  and envidistance  had signdistance  and envidistance  were alsHe) of P. euphratica and P. pruinosa at the population level, we performed correlation analysis between the genetic diversity of Populus and latitudinal, longitudinal, and environmental factors. He showed significant negative correlations with longitude and especially latitude for the P. euphratica populations , soil moisture around the root system, and the evapotranspiration of soil water . The names of the SNP repository and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/, PRJNA738601.The datasets presented in this study can be found in online repositories. The reference genome of Populus euphratica is available at our Populus genome database (ZL and ZW conceived and designed the study and provided suggestions and comments about the manuscript. ZG collected and analyzed the data and wrote the manuscript. JZ, XC, PJ, SZ, and JS collected the samples. RQ and HL provided constructive comments. ZW revised the manuscript. All authors read and approved 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.