Amomum villosum Lour. is the plant that produces the famous traditional Chinese medicine Amomi Fructus. Frequent habitat destruction seriously threatens A. villosum germplasm resources. Genetic diversity is very important to the optimization of germplasm resources and population protection, but the range of inherited traits within A. villosum is unclear. In this study, we analyzed the genetic diversity and genetic structures of A. villosum populations in Guangdong and constructed a local reference DNA barcode library as a resource for conservation efforts.A. villosum. Five universal DNA barcodes were amplified and used in the construction of a DNA barcode reference library. Parameters including percentage of polymorphic sites (PPB), number of alleles (Na), effective number of alleles (Ne), Nei’s gene diversity index (H), and Shannon’s polymorphism information index (I) were calculated for the assessment of genetic diversity. Genetic structure was revealed by measuring Nei’s gene differentiation coefficient (Gst), total population genetic diversity (Ht), intra-group genetic diversity (Hs), and gene flow (Nm). Analysis of molecular variance (AMOVA), Mantel tests, unweighted pair-group method with arithmetic mean (UPGMA) dendrogram, and principal co-ordinates (PCoA) analysis were used to elucidate the genetic differentiation and relationship among populations.DNA barcoding and Inter-Simple Sequence Repeat (ISSR) markers were used to investigate the population genetics of A. villosum populations using the selected six ISSR primers; 56 bands, 84.85% for all the seven A. villosum populations were polymorphic. The A. villosum populations showed high genetic diversity , whereas the gene flow was weak (Nm = 0.6143). Gst (0.4487) and AMOVA analysis indicated that there is obvious genetic differentiation amongA. villosum populations and more genetic variations existed within each population. The genetic relationship of each population was relatively close as the genetic distances were between 0.0844 and 0.3347.A total of 531 sequences were obtained from the five DNA barcodes with no variable sites from any of the barcode sequences. A total of 66 ISSR bands were generated from  Amomum villosum Lour. is a medicinal plant from Zingiberaceae family mainly grown in southern China that produces the famous traditional Chinese medicine (TCM), Amomi Fructus. The dried capsule of A. villosum is brown, ellipsoid, with branched or simple, soft spines that has the effect of dampening appetite, “warming” the spleen to stop diarrhea, regulating qi, and preventing miscarriage -based molecular markers are widely used in the analysis of plant genetic diversity. Among them, Inter-Simple Sequence Repeat (ISSR) markers are fast and efficient, do not require pre-determination of target sequence information, and have the characteristics of high polymorphism, high reliability, and low cost . DNA barpsbA-trnH, ITS, matK, and rbcL, were used to investigate the genetic diversity of seven populations of A. villosum in Guangdong Province, especially in Yangchun City, and provide insights into the identification, conservation, breeding, and cultivation of A. villosum.Mitochondrial cytochrome oxidase I (COI) gene is an efficient species identification tool frequently used in the genetic diversity analysis of animals . In planA. villosum populations were collected in Guangdong Province using random strategy (A. villosum plants coming from Guangdong (Jinhuakeng), Yunnan, and Guangxi provinces and the country Myanmar. The sampled plants were identified by Zhihai Huang, the chief Chinese pharmacist of the Second Clinical College of Guangzhou University of Chinese Medicine. Fresh and healthy leaves were removed from the plants, dried, and preserved in silica gel immediately upon collection in the field, then stored in an ultra-low temperature refrigerator  in the laboratory. For detailed information and the geographic locations of the samples collected see Sample collections were conducted with the permission of Research Department of the Second Clinical College, Guangzhou University of Chinese Medicine from August 2018 to November 2018. A total of 141 samples from seven strategy  that sam2O. The primer sequences and amplification conditions of different DNA barcodes are shown in The total DNA was extracted using a DP305 plant DNA kit . The NanoDrop2000 ultra-micro ultraviolet spectrophotometer  was used to determine the DNA concentration and purity. The extracted DNA was finally diluted to 10 ng/L as the template that be subsequently amplified. The PCR amplification reaction system of the experiment contained 2× Taq PCR Mix 12.5 L, forward primer (2.5 M) 1.0 L, reverse primer (2.5 M) 1.0 L, genomic DNA 2.0 L, and added up to 25 L with ddHA. villosum populations , 2 μL template DNA (20 ng), 1 μLISSR selected primer, and 7 μL ddH2O. The ISSR PCR amplification was programmed in the ProFlex thermocycler as follows: pre-denaturation at 94 °C for 5 min, 35 cycles of denaturation at 94 °C for 45s, annealing at the 46.83–56.60 °C according to the primers for 45s, extension at 72 °C for 2 min, with a final extension at 72 °C for 5 min and preservation at 4 °C. ISSR-PCR products were separated on a 2% agarose gel stained with Goldview by electrophoresis in 1 ×TAE buffer at 80 V. The gels were visualized under UV light and photographed with a ChemiDoc imaging system . The molecular weights of ISSR-PCR products were estimated using a 100 bp Plus DNA Ladder .100 ISSR universal primer sequences published by Columbia University were screened . Six priulations . The 20  and the QR code on the right could be scanned directly for the DNA sequence.The two-way sequenced peaks of DNA barcodes were evaluated and assembled using the CondonCode Aligner v8.0.1 software . Low-quaReproducible ISSR-PCR bands were determined with the help of the GelPro32 software and manual correction. These clear bands were scored as either present (1) or absent (0), thus generating an ISSR phenotype data matrix that was imported in Popgene32 software to analyze genetic diversity and genetic structure . GeneticA. villosum. The OD260/280 was 1.76−1.98 for all the DNA samples and the concentration was 73.70–1294.80 ng/L. Five DNA barcodes of all the samples were amplified and sequenced bi-directionally. Finally, 531 sequences were gained and submitted to the Genbank database (rbcL (100.00%) > ITS (98.58%) > ITS2 (95.04%) > psbA-trnH (53.90%) >matK (29.08%) (A. villosum in Guangdong Province.We extracted the genomic DNA from 141 samples of database . The PCR(29.08%) . The ranWe also analyzed the sequences of each barcode we obtained. The sequences of the five barcodes had no variation sites, showing a strong conservation. Among the five DNA barcodes, ITS2 had the shortest sequence length and the highest GC content. The sequences of each barcode are shown in A. villosum. The ISSR-PCR fragments of A. villosum populations ranged from 300 bp to 2000 bp. An example of amplified profiles is shown in 10.6084/m9.figshare.14622987). A total of 66 ISSR bands were generated from A. villosum populations using the selected six primers. Among them, 56 bands were polymorphic, thus the percentage of polymorphic bands was 84.85% for all seven A. villosum populations. For each primer, it amplified 6–14 bands with the polymorphic ratio of 64.29%–100.0%  while population TK had the lowest genetic diversity . At the species level, the values of Na, Ne, H, and I were 1.9394, 1.5662, 0.3281, and 0.4895, respectively.Genetic diversity information of A. villosum populations analyzed by Popgene 32 is shown in P = 0.001) genetic variation was within populations while 31.26% (P = 0.001) was between populations  (Genetic distance is the main indicator used to examine the degree of genetic differentiation and the relationship between groups. The genetic distances of the seven populations were between 0.0844 and 0.3347 . Among t 0.5504) .A. villosum populations were divided into three groups at the similarity coefficient of 0.84. Three populations, ZJD, TK, and ZY, formed one group. Three populations, GY, MM, and YC, formed another group. One population, XFC, formed a single group. The results of PCoA based on the unbiased matrix of Nei were consistent with UPGMA cluster analysis. The first two principal components accounted for 48.04% of the total variation of ISSR markers indicated from PCoA . Among the seven populations, population ZY had the highest genetic diversity; this is consistent with the fact that it had diverse germplasm resources. The Gst results (0.4487) indicated that there is obvious genetic differentiation among A. villosum populations (A. villosum populations is probably due to its pollination style and habitat fragmentation. The morphological structure of A. villosum flowers makes them extremely difficult to self-pollinate. Due to the lack of pollinating insects, such as bees and ants A. villosum in Guangdong mainly relies on artificial pollination. The gene flow is consequently restricted to a small population. The habitat fragmentation of A. villosum in Yangchun is also likely to reduce the exchange of pollens between populations. A. villosum including two populations from Yangchun city, Guangdong province and one population from Yunnan province. They found the high genetic diversity of A. villosum populations with the polymorphic percentage was 92.16%, which was consistent with our finding.We analyzed the genetic diversity and genetic structure of ulations  and moreulations . The weaA. villosum has been cultivated in Yangchun for approximately 200 years after being introduced into Guangxi, Yunnan, and Fujian provinces in southern China (Amomum villosum populations in Guangdong Province, especially in the Daodi producing area of Amomi Fructus, Yangchun City, have high genetic diversity inferred from our study. Yangchun has expanded the planting area of Amomum villosum in recent years. However, considering the small populations and the increasingly fragmented habitat as well as the lower gene flow of A. villosum, we need to take measures to protect the genetic resources of the species. On one side, we could conduct in-situ conservation in Tankui Village, because the population has the lowest genetic diversity indicating it was the most threatened. On the other side, we recommend collecting core germplasm resources based on this study and reconstructing the germplasm garden in Yangchun City to preserve genetic diversity of A. villosum.Amomi Fructus has been used in China for more than a thousand years and was mainly imported from abroad for much of that time. rn China . SpeciesA. villosum populations in Guangdong Province. The A. villosum populations have high genetic diversity, but ISSR markers revealed that their gene flow is weak. The genetic relationship of each population is relatively close. More measures are needed to protect the genetic resources of A. villosum in Guangdong province, especially in Amomi Fructus’s Daodi producing area, Yangchun City.In this study, a local DNA barcode reference library containing 531 sequences was constructed from 141 samples from seven 10.7717/peerj.12325/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.12325/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.12325/supp-3Supplemental Information 3Click here for additional data file.


Diplazium caudatum, a hypothesized species of the Tertiary Palaeotropical flora and currently with its populations restricted across Macaronesia and disjunctly in the Sierras de Algeciras . We analysed 12 populations across the species range using eight microsatellite loci, sequences of a region of plastid DNA, and carry out species-distribution modelling analyses. Our dating results confirm the Tertiary origin of this species. The Macaronesian archipelagos served as a refuge during at least the Quaternary glacial cycles, where populations of D. caudatum preserved higher levels of genetic variation than mainland populations. Our data suggest the disappearance of the species in the continent and the subsequent recolonization from Macaronesia. The results of the AMOVA analysis and the indices of clonal diversity and linkage disequilibrium suggest that D. caudatum is a species in which inter-gametophytic outcrossing predominates, and that in the Andalusian populations there was a shift in mating system toward increased inbreeding and/or clonality. The model that best explains the genetic diversity distribution pattern observed in Macaronesia is, the initial and recurrent colonization between islands and archipelagos and the relatively recent diversification of restricted area lineages, probably due to the decrease of favorable habitats and competition with lineages previously established. This study extends to ferns the concept of Macaronesia archipelagos as refugia for genetic variation.Macaronesia has been considered a refuge region of the formerly widespread subtropical lauroid flora that lived in Southern Europe during the Tertiary. The study of relict angiosperms has shown that Macaronesian relict taxa preserve genetic variation and revealed general patterns of colonization and dispersal. However, information on the conservation of genetic diversity and range dynamics rapidly diminishes when referring to pteridophytes, despite their dominance of the herbaceous stratum in the European tropical palaeoflora. Here we aim to elucidate the pattern of genetic diversity and phylogeography of  Macaronesia, which comprises the mid-Atlantic oceanic archipelagos of the Azores, Canaries, Cape Verde, Madeira and Selvagems, is considered an exceptional biogeographical and evolutionary model system . Ref. 22 proposeVandenboschia speciosa (Willd.) G. Kunkel and Culcita macrocarpa C. Presl  Ma coinciding with the end of the first interglacial period and beginning of the second Pleistocene glaciation . The predictions obtained by MAXENT for the present and the LIG show similar suitable areas for the habitat of ial area . Accordiial area .Among ferns, asexuality is considered a common phenomenon where it has been documented in approximately 10% of species . AsexualD. caudatum an outcrossing breeding system predominates  showed that in ominates . In Andaominates , and theominates , point tominates .D. caudatum, since intra-gametophytic selfing generates totally homozygous sporophytes (from the same haploid gametophyte). In order for these populations to increase their genetic diversity and viability sexual reproduction with immigrant genotypes is necessary  is probably due to the progressive retraction towards the south and subsequent disappearance of the lauroid-type palaeoflora, as a result of the strong climatic changes from the Middle Miocene onwards [D. caudatum could be one of the species that survived in Iberian and Macaronesian shelters, like other Tertiary species of ferns. Diplazium caudatum joins the list of ferns present in the Macaronesia and Iberian Peninsula for which a Tertiary origin is corroborated, and therefore its relictual nature , time w onwards ). Accord onwards  D. caudariensis, ; Culcitapeciosa, ). HoweveD. caudatum; [D. caudatum, could occur during the Pliocene, a period where fossils of trees of this palaeoflora, such as Laurophyllum, have been recorded and when the region presented available habitats for the persistence of these long-term forests, refugees from the newly established Mediterranean climate [Dating results showed that the first haplotype divergence event corresponds to the private haplotypes of Madeira 1.8 Ma; . In accoaudatum; ). Accordaudatum;  the arri climate .D. caudatum to the Macaronesia region could be from populations in the Iberian Peninsula. However, our data does not support currently existing populations as source populations of those in Macaronesia. Populations that have persisted for a long time in shelters are expected to harbour high levels of genetic diversity with respect to populations resulting from new colonization or recolonization processes . In islift; see . Contrardophytes ,112,113.D. caudatum disappeared from the continent at some point. This assumption would be consistent with the large temporal gap detected between the estimated date of origin of the lineage of D. caudatum (19.11 Ma) and that of initial divergence of haplotypes  and supports the homogenising effect of long-distance dispersal, decreasing diversity among populations and regions, as shown by the lack of existence of isolation by distance when Andalusian populations where removed from analysis, and that the differentiation between the Azores and the Canary Islands is less than the differentiation between the Canary Islands and Madeira, despite the fact that the latter two archipelagos are geographically closer . The higipelagos A,B. Thisipelagos A and froon range , the BSPon range . RecentlD. caudatum are widely dispersed between islands and archipelagos, the rest (and most recent haplotypes) are private to single islands , the di


BoLA-DRB3 genetic diversity was compared to that of taurine and zebuine breeds worldwide to estimate functional diversity. High allele richness was observed for Simmental and Simbrah cattle; nevertheless, high homozygosity was associated with individual low sequence variability in both the β1 domain and the peptide binding region (PBR), thereby implying reduced MHC-presented peptide repertoire size. There were strong signals of positive selection acting on BoLA-DRB3 in all populations, some of which were poorly structured and displayed common alleles accounting for their high genetic similarity. PBR sequence correlation analysis suggested that, except for a few populations exhibiting some divergence at PBR, global diversity regarding potential MHC-presented peptide repertoire could be similar for the cattle populations analyzed here, which points to the retention of functional diversity in spite of the selective pressures imposed by breeding.The major histocompatibility complex (MHC) exerts great influence on responses to infectious diseases and vaccination due to its fundamental role in the adaptive immune system. Knowledge about MHC polymorphism distribution among breeds can provide insights into cattle evolution and diversification as well as population-based immune response variability, thus guiding further studies. Colombian Simmental and Simbrah cattle’s  This paesponses . By contathogens .IIa subregion  and the genes encoding the expression of class II antigen presentation (DR and DQ)-related molecules are located in chromosome 23 ubregion . BoLA-DRnctional . Such po alleles . Such hi alleles . BoLA-DR spectra .BoLA-DRB3 alleles, and information regarding their frequency has thus been used for running infectious disease control programs  might bprograms , while oprograms . Such involution .Bos taurus) breed that was selected in North America and Europe, mainly for increasing meat production efficiency (Bos indicus) adaptability, maternal instinct, hardiness and disease resistance with Simmental fertility, milk production and beef quality  Animal Research Ethics Committee (minutes No.201901).Whole blood was collected from the coccygeal or jugular veins of 130 Simmental  and Simbrah cattle  (Supplementary Data S1), stored in EDTA-containing vacutainer tubes. Bovines were selected from extensive production systems from Colombia’s main breeding regions characterized by a reduced number of purebred animals per farm. The herds and purebred animals analyzed were randomly sampled avoiding related individuals. Genomic DNA (gDNA) was extracted using the PureLink Genomic DNA Mini Kit  and following the manufacturer’s instructions. Previous allelic richness data  of 14 taBoLA-DRB3 exon 2 was amplified with primers DRB3F (5′-TCCCGCATTGGTGGGTGT-3′) and DRB3R (5′-CTCCACACTGGCCGTCCAC-3′)  and 50 ng gDNA, in a 50 ml final volume. Two independent reactions were performed for each sample, following previous recommendations to avoid chimeric product formation (CAC-3′) . The PCRormation . The theBoLA-DRB3 allele sequences reported in the IPD-MHC database  was used for assembling and editing each sequence independently. Polymorphic positions were recognized for producing a final consensus sequence containing IUPAC ambiguity codes. HAPLOFINDER  was useddatabase , as prevdatabase .a) and allele frequencies were manually obtained by direct counting using the maximum likelihood method for estimating standard errors for allele frequencies according to Li (ho) and ARLEQUIN v.3.5 (he). The correlation between sample size and these estimators was used for assessing their dependence. Allele richness  was also used for comparing the number of alleles found in each population independently from sample size (FIS index (dS) and nonsynonymous (dN) substitutions per site by Nei-Gojobori’s method with Jukes-Cantor correction. The Z-test was used for assessing dN/dS ratio significance. Codons subject to positive selection were inferred using maximum likelihood  and Bayood (FEL ) methodsood    from all (DA)  for gene (DA)  was used) . No new alleles were detected. Three alleles  occurred with >5% frequency in both populations and seven  only in the Simmental breed. Four alleles  occurred with >5% frequency in Simbrah, accounting for 31.67% of cumulated frequency, whereas 10 alleles  with >5% frequency, accounting for 61.94% cumulative frequency, occurred in Simmental. Twenty alleles were shared by both cattle populations, accounting for 64.7% of their mean cumulative allele frequency   .Rs) showed that Simmental and Simbrah had a high genetic diversity, similar to what was observed for Colombian Normande and Philippine populations (ho (r = 0.36) and he (r = 0.06), highlighting these estimates as being good proxy of BoLA-DRB3 diversity in the populations analyzed here. Colombian Simmental, Colombian Normande, Spanish Morucha and Colombian Simbrah had the lowest ho and the highest he values, in contrast with the results for other breeds  to 88.95% (Colombian Normande), with Colombian Simmental (88.79%) and Simbrah (86.33%) displayed some of the highest values . BoliviadN was significantly higher than average dS for Colombian Simmental and Simbrah populations, similar to what was observed across all the other populations  or moderately occurring ones  were identified in populations that are not closely related  to 0.1185 (Peruvian Holstein with Bolivian Nellore) , while the second was formed by Philippine, Colombian Simmental, Colombian Simbrah, Bolivian Yacumeño and Colombian Normande populations . Differences between Colombian Simmental and Simbrah were also observed regarding Argentinian, Peruvian, Chilean and Paraguayan Holstein.Pairwise Nellore) . All comobserved ; the firColombian Simbrah was differentiated from native Philippine, Colombian Normande, Bolivian Yacumeño and Holstein populations to a greater extent than Colombian Simmental. On the contrary, Colombian Simmental was more differentiated from Philippine Native-Brahman, Philippine Brahman, Spanish Morucha, Peruvian Nellore-Brahman and Bolivian Nellore than Colombian Simbrah .DA clustering was similar to that based on pairwise FST among Holstein and the Philippine populations  had 28 alleles in common, accounting for 95.2% of their mean cumulative allele frequency. Ten of these common alleles  occurred with >5% frequency in at least one of these populations. The Philippine group (0.169 mean DA distance) had 65 common alleles accounting for 93.1% of their mean cumulative allele frequency, of which 8  were alleles with >5% frequency. The group formed by Colombian and Bolivian Yacumeño populations (0.387 mean DA distance) had 49 alleles in common, accounting for 69.1% of their mean cumulative allele frequency. Seventeen  of these shared alleles had >5% frequency.Genetic distance ulations . The latFST and DA distance analysis  due to high BoLA-DRB3*048:02, 003:01 and 005:01 frequency, whereas Nellore cattle had high BoLA-DRB3*028:01, 009:02 and 022:01 frequencies.Groups identified in the first two principal component (PC) plots were consistent with those identified in analysis . The firPBR logo representation showed that positions 70, 71, 74, 11, 13, 30, 67, 37, and 57 were highly variable and tended to accumulate non-conservative changes, while positions 82, 83, 14, 15, 40, 72, 73, 79, 29, 64, 47, 9, and 38 were invariable or only displayed conservative changes . Some hiPBR correlation analysis identified four major groups . The firin silico binding predictive algorithms that can be used for understanding and predicting immune response patterns  aimed at identifying MHC-associated peptides and developing patterns . MHC higpatterns . In this country .ho  associated with similar he values across populations  indicated a marked allele frequency distribution variation, while ho values were the lowest for Colombian cattle, with FIS indices being thereby the highest for these populations. Population sub-structuring may have reduced ho , thus mFIS indicated heterozygote deficiency for BoLA-DRB3, the persistence of identical or similar alleles  in spite of the overall genetic differentiation points to the action of balancing selection. Moreover, the highly significant dN/dS values and codons identified under positive selection suggest that aa variability preference has not been eroded in these cattle. Although drift and non-random mating are well-known factors leading to increased homozygosity  are factors affecting allele frequency distribution , which izygosity  as well  account ].BoLA-DRB3*011:01, are possibly present in all populations, or absent in a few of them, such as BoLA-DRB3*010:01, 012:01 and 014:01:01. Considering that taurine and zebuine cattle were domesticated in more than two independent events    . Anothersen ones . Despitectively) , they occtively)  (Supplemctively) . Neverthectively . AllelesBoLA-DRB3, others had a shallow structure due to the sharing of several alleles occurring with high or intermediate frequency. These populations clustered into five groups according to the measures of differentiation used. Low mean distance values indicated high genetic affinity for these populations and more detailed analysis showed that commonly occurring alleles accounted for a large percentage of their mean cumulative allele frequency. Several factors may result in weak structure. For instance, the limited genetic distance between Colombian Simmental and Normande might be due to sample origin, as geographical dispersal patterns in cattle reflects those of exportation and co-migration in humans , Colombian Simmental, Simbrah and other cattle populations may have a limited potential MHC-presented peptide repertoire diversity could be similar among all cattle populations analyzed and that breeding did not decrease functional diversity. Additional analyses directly addressing peptide repertoire diversity are needed to confirm these results.MHC PBR positions hosted the highest β1 domain variability associated with the peptides to which an allele could bind . The sim in pigs . The hig in pigs . This wo


Parus major) from nine European cities, each paired with an adjacent rural site, to address this major knowledge gap in our understanding of wildlife urban adaptation. We find that a combination of polygenic allele frequency shifts and recurrent selective sweeps are associated with the adaptation of great tits to urban environments. While haplotypes under selection are rarely shared across urban populations, selective sweeps occur within the same genes, mostly linked to neural function and development. Collectively, we show that urban adaptation in a widespread songbird occurs through unique and shared selective sweeps in a core-set of behaviour-linked genes.Urbanisation is increasing worldwide, and there is now ample evidence of phenotypic changes in wild organisms in response to this novel environment. Yet, the genetic changes and genomic architecture underlying these adaptations are poorly understood. Here, we genotype 192 great tits ( The genetic architecture underlying rapid adaptive responses to novel environments are poorly understood. A study of great tits from nine European cities finds that urban adaptation in a widespread songbird occurred through unique and shared selective sweeps in a core-set of behaviour-linked genes. Many species show phenotypic adaptations to the multiple urban challenges, such as higher levels of noise, artificial light at night, air pollution, altered food sources or habitat fragmentation6. These adaptations include changes in behaviour, e.g., refs. 9, morphology and locomotion, e.g., refs. 13 or toxin tolerance14. Indeed, there is now evidence that the phenotypic divergence between urban and rural populations may have a genetic basis in some species15, in line with the finding that micro-evolutionary adaptations in natural populations can occur within short timescales, particularly in response to human activities18. The study of the genetic signals of adaptation could provide important insights into the magnitude of the evolutionary change induced by urbanisation on wildlife. However, the short evolutionary timescale, the dependence of evolution on local factors, and the polygenic nature of many phenotypic traits, make detecting the genomic signals of adaptation difficult19.Urban development is rapidly expanding across the globe, and although urbanisation is regarded a major threat for wildlife20 or on a narrow geographical scale, e.g., refs. 22, thereby limiting the inferences that can be made on the consistency of genomic responses to urbanisation5. Conversely, the study of multiple populations on a broad geographical scale provides a powerful framework to identify the evolutionary forces shaping the genomic responses and to test the repeatability of urban adaptation24. In particular, comparing across populations enables the distinction between random demographic non-adaptive processes, such as genetic drift, and signatures of natural selection, as selection might be expected to affect the same genomic regions (nucleotides or genes) and/or functional pathways across cities25. The current evidence on the genomic basis of urban adaptations ranges from high parallelism, involving a single or few genes23, to polygenic, and to putative genetic redundancy, e.g., ref. 22. This discrepancy might be due to the variable and sometimes local urban selection pressures together with the polygenic nature of many adaptive phenotypic traits, which could lessen the likelihood for shared genetic changes at the nucleotide level26.The majority of studies on the genomic basis of urban adaptation have either focused on a limited number of markers and genesParus major), to identify the genetic basis of urban adaptation. The great tit is a widely distributed songbird and a model species in urban, evolutionary and ecological research, e.g., refs. 36, with demonstrated phenotypic changes in response to urban environments in several populations37. In addition, genomic resources are well developed for this species38 and it is known that across its European range, the species presents low genetic differentiation41. In order to examine genomic responses to urbanisation on a broad geographical scale, we analyse pairs of urban and rural great tit populations from nine localities across Europe .A total of 192 great tits from the nine paired urban–rural populations were genotyped at 517,603 filtered SNPs, with 10–16 individuals per sampling site  except for the urban populations in Munich and Paris  within population pairs , as well as between urban populations (urban vs urban), was on average higher than the differentiation between rural populations  across Europe  compared to rural populations  showed that urban birds likely independently colonised multiple times European cities from forest sources42. In our study, the finding of independent clusters for some urban populations also point towards a similar scenario, i.e., an independent and repeated colonisation of urban habitats from largely admixed rural populations. However, the overall weak genetic divergence and the detection of significant migration events across distant populations suggests a possible role of gene flow in the facilitation of urban adaptation, via the spread of adaptive alleles. Still, in our subsequent analyses we treated all our urban–rural population pairs as independent, including Munich and Paris, as selection pressures might differ across cities and result in idiosyncratic genomic responses to selection despite any ongoing gene flow.Overall, our results reveal weak population structuring across Europe, with slightly increased genetic differentiation between urban populations compared to the more admixed rural populations. Previous results in another European songbird, the blackbird  and those with more genes , based on all urban-associated SNPs detected by LFMM, clearly separated urban and rural populations along PC1GEA  approaches, LFMM (latent-factor mixed models) and an additional Bayesian approach (using BayPass). Testing for GEAs with LFMM  is higher compared to the effect size of a significant “habitat × locality” interaction term, which describes differences in the direction and magnitude of the allele frequency change between cities44. Applying these models to each urbanisation-associated SNP from the LFMM model (2758 SNPs), we detected large variation in allele frequency shifts across localities . In contrast to this, most of the “core urbanisation SNPs” showed similar allele frequency differences across localities, with 76% of them showing a main effect of the urban habitat  and the “core urbanisation SNPs” . In comparison, both the effect of “locality”, which corresponds to the distinct evolutionary history of the local populations , and the interaction of “habitat × locality” , explained much smaller proportions of the total variation  than the habitat term by itself. In contrast, genetic variation along PC2 and PC3 was mostly inconsistent across localities and likely specific for each city  on allele frequency shifts in the detected SNPs, we assessed using univariate linear models, the explanatory power of habitat, locality (city), and their interaction on the direction and strength of allele frequency shifts per-SNP across all paired populations. A significant “habitat” term indicates consistent allele frequency shifts across cities, particularly when the effect size  and white-footed mice (Peromyscus leucopus)45. Therefore, we further performed genome-wide scans of differentiation and selective sweep analyses in each of our studied populations to test if these contributed to the urban adaptation in great tits and, importantly, to explore if selective sweeps were population specific or widely shared across Europe.While GEA approaches are powerful tools for identifying even subtle allele frequency shifts associated with local adaptationXP-nSL)46. Using this approach, we found that between 436 and 700 genomic windows , which clustered into 127–173 wider genomic regions, showed signatures of selection in urban populations  or geographic distance , suggesting that shared adaptive genetic variation through introgression and gene flow between neighbouring urban populations likely did not facilitate urban adaptation. However, we cannot fully exclude the role of gene flow as migration was generally strong, even across large distances  between each adjacent urban and rural pair across the same windows  were largely population specific  and clustered genomic outlier regions  compared to XP-nSL. This result suggests that ongoing/recent sweeps outnumber older and completed selective sweeps in urban great tits. Similar to XP-nSL, the Rsb outlier windows were only shared across a maximum of five populations and in general widely distributed across the genome , were pervasive across the genomes of urban great tits, supporting our inference of a highly redundant polygenic adaptation to urban environments. The underpinning genomic changes associated with urban adaptation were largely population specific, likely the result of differential selective pressures, adaptation through complex multivariate phenotypic changes and/or selection on standing genetic variation50. Nonetheless, we still detected shared selective sweeps across urban populations, suggesting the presence of common genomic responses to the urban selective pressures, either through repeated selective sweeps or sharing of adaptive genetic variants.Overall, the selection analyses showed that selective sweeps, and in particular those that are recent and ongoing  and differentiation (FST) with two proxies of genomic recombination rate, i.e., LD and intronic GC-content (both in 200 kb non-sliding windows). LD is correlated with population-specific recombination rates and the strength of selection, while intronic GC-content is a surrogate for the long-term recombination rate variation across the great tit genome, i.e., a higher GC-content will indicate a higher recombination rate52. To confirm that both proxies provide similar pictures of the recombination landscape, we tested their correlation across all population pairs. Indeed, LD and GC-content, were (negatively) correlated in all populations , and 362–923 with completed selective sweeps (Rsb). Of these genes, 64–207, and 5–76, were detected in at least two urban populations . Such consistent genomic responses on the gene or functional level could explain the similarity in phenotypic responses to environmental variation despite a large variation on the haplotype levelχ21 = 77.95, P < 2.2 × 10−16), we conservatively focused our functional interpretation only on those genes that were associated with signatures of selection (XP-nSL or Rsb) in more than half of all urban populations (≥5 urban populations), as these likely play more important roles in urban adaptation. In total, we detected 42 genes associated with recent or ongoing selective sweeps in at least five populations (XP-nSL: max. six populations), and 15 genes associated with older completed selective sweeps  or genetic distance , which is in accordance with the results regarding shared outlier windows and further supports that many selective sweeps likely occurred independently in multiple urban populations. In addition, 12 of the 57 shared genes under selection were also associated with urbanisation in the LFMM analysis  in seven and six populations, respectively, but also previously shown to be differentially expressed in blood and/or liver between urban and rural birds from Malmö59. Moreover, following Malmö as an example, one gene found to be differentially expressed in Watson et al.59, VPS13A, was highly differentiated (ZFST) and associated with selective sweeps in that particular population, but importantly, also under selection in Madrid (Rsb) and Lisbon (XP-nSL) and in general, associated with urbanisation . This exemplifies that some genes show signatures of urban adaptation on a continental scale, making them strong candidates for adaptation in these urban centres.Although it is statistically unlikely to detect selective sweeps in the same gene in more than three urban populations by chance alone , the exact locations of these signatures were not consistent  codes for a receptor of the neurotransmitter serotonin, a pathway consistently identified as target of changes linked to urbanisation. Indeed, two previous studies in birds, one on European blackbirds using a candidate gene approach and another on burrowing owls (Athene cunicularia), using full-genome resequencing, also described changes in this pathway as the main difference between urban and rural populations22. Both species also show consistent urban–rural differences in two behaviours associated with serotonin: down-regulation of the stress axis and altered nocturnal behaviour under artificial light at night, respectively62. The same gene, HRT7, has also been directly linked to behavioural differences between migratory and resident rainbow trout (Onchorynchus mykiss)63, supporting its potential role in behavioural changes in urban great tits. The CDH18 gene (Chr 2), is part of a superfamily of membrane proteins involved in synaptic adhesion and revealed as a candidate gene in phonological alterations in humans64. The PTPRD and VPS13A genes (both in Chr Z), are suggested to be involved in hippocampal neural development65 and were previously linked to bird navigation, flight performance and migratory behaviour68. Moreover, two other genes under selection and associated with urbanisation are involved in the regulation of cognitive processes and behavioural disorders in vertebrates (DLG2 (ref. 69) and NRXN3 (ref. 70), Chr 1 and 5, respectively), and were also previously linked to urban divergence in burrowing owls22.Many of the genes associated with urbanisation have previously been linked to behavioural divergence, and cognitive and learning functions, suggesting adaptive phenotypic shifts related to behaviour. In particular, 72. These findings were furthermore supported by gene ontology (GO) analysis of the 2758 urbanisation-associated SNPs , linked to 984 genes (1501 SNPs in genic regions). Accordingly, most of the GO terms were related to neural functioning and development , cell adhesion  and sensory perception . Each of the paired sampling sites  was sampled within the same season. Barcelona and Munich were sampled during winter, however, in both cases only known birds (recaptures) were included in the study, thus, all birds can be considered resident. All urban populations were located within the city boundaries, the areas are characterised with significant proportion of human-built structures, such as houses and roads with managed parks as the only green space  were obtained either from the jugular or brachial vein and stored at 4 °C in ethanol or SET buffer and subsequently frozen at −20 °C. In each case, procedures were identical for the paired urban and rural populations. All procedures employed during field work were approved by national Ethical Committees and authorisations to collect samples were delivered by the Environment Department of the Generalitat de Catalunya (permit no. AECC/SF/0438), the Scottish Natural Heritage (permit no. 52463) and UK Home Office (license no. 70/7899), the Malmö-Lund animal Ethical Committee (permit no. M454 12:1), the CEMPA and Portuguese Ministry of Environment (permit nos. 40/2014 and 164/2014), the Ministry of the Environment, Housing and Territorial Planning of Madrid , the Institute for Environmental Protection and Research  and the Lombardy Region (permit no. 3462), the Tierschutzgesetz  and the Regierung von Oberbayern (permit nos. 55.2-1-54-2532.2-7-07 and 55.2-1-54-2532-140-11) and the Minister of Higher Education, Research and Innovation , the Prefect of Paris and the Prefect of Seine et Marne (permit nos. DRIEE-2012-31 and DRIEE-2012-32) and the CRBPO . DNA was extracted from ~5 µl samples of red blood cells in 195 µl of phosphate-buffered saline, using Macherey-Nagel NucleoSpin Blood Kits , and following the manufacturer’s instructions or manual salt extraction (ammonium acetate). The quantity and purity of the extracted genomic DNA was high as measured using a Nanodrop 2000 Spectrophotometer (Thermo Fisher Scientific) and Qubit 2.0 Fluorometer (Thermo Fisher Scientific).75, based on aerial images from Google Maps (Google Maps 2017), and following the methods described in different studies assessing the effect of urbanisation on wild bird populations76. Briefly, each sampling site was represented by a 1 × 1 km rectangular area around the capture locations. We opted to use this spatial resolution around the sampling sites to approximately cover individuals’ territory32, but also to ensure that we considered the heterogeneity within each selected site. The content in each rectangle was evaluated dividing the image in 100 × 100 m cells and considering three land-cover characteristics in each: proportion of buildings, vegetation (including cultivated fields) and paved surfaces  for each of the urban or rural populations per locality, see Table urb values were transformed to obtain negative values in the less urbanised and positive values in the more urbanised sites. We used the average of the urbanisation estimates if birds were captured in more than one location within each site . All quantifications were done in triplicates by the same person (P.S.) and the estimates were highly repeatable  = 0.997–0.987, P < 0.001).To quantify the degree of urbanisation at each site, we used the UrbanizationScore image analysis software38. Thus, this SNP chip allowed us to genotype a large number of individuals on a genome-wide basis at high SNP density without a strong ascertainment bias. SNP calling was done following the “Best Practices Workflow” in the software Axiom Analysis Suite 1.1.0.616 (Affymetrix©) and all the individuals passed the default quality control steps provided by the manufacturer  and previous studies using the same SNP chip77. A total of 544,610 SNPs were then exported to a variant-calling format (VCF) and Plink v. 1.9 (ref. 78), and further filtered and assigned to chromosomes using the P. major reference genome build 1.1 . A total of 155 SNPs were not found in the used assembly and 26,852 SNPs were not in chromosomic regions; thus, these SNPs were removed from further analysis leaving a total of 517,603 SNPs.All 192 individuals were successfully genotyped using a custom made Affymetrix© great tit 650 K SNP chip at Edinburgh Genomics . The Affymetrix SNP chip was developed based on whole-genome sequencing data from great tits sampled across multiple European populations, largely corresponding to our sample sitesHe) for each population using Plink v. 1.9 (ref. 78), and tested if genetic diversity significantly differed between urban–rural populations from the same location using t tests in R, and overall across urban–rural pairings using a Wilcoxon rank-sum test in R v.3.6.1 (ref. 79). Furthermore, we estimated pairwise FST between all population pairs , using VCFtools v. 0.1.15 (ref. 80). Mean average FST was computed across all comparisons after setting negative values to zero.We calculated the genome-wide genetic diversity as expected heterozygosity (78), using a variance inflation factor threshold of 2 (“-indep 50 5 2”), retaining 358,149 SNPs. Using this LD-pruned dataset, we performed a PCA using Plink. We performed two different PCAs, (i) only with autosomes and excluding all small linkage groups and the Z-chromosome, and (ii) including the Z-chromosome but excluding all small linkage groups. Subsequently, we performed additional dimensionality reduction for each PCA dataset using the first 20 principal components, using the UMAP v.0.2.7.0 R-package with default settings81. We also compared the results to the UMAP based on the first ten PCs. Genetic ancestry analysis was performed using the software package fastStructure v.1.0 (ref. 82), with K ranging from 2 to 9 and cross-validation. In addition, we inferred a population tree based on allele frequency co-variances using Treemix v.1.3 (ref. 83), with blocks of 100 SNPs. We fitted up to five migration edges and determined the optimal number of migration edges that lead to the best fitting population tree by (i) comparing the likelihoods of trees with different number of migration edges, (ii) estimating the total variance explained by each tree and (iii) by comparing the significance of the fitted migration edges.For analyses of population structure, we pruned the SNP dataset based on LD in Plink v.1.9  inferred with fastStructure v.1.0, we ran LFMM with two and four latent factors, respectively. Each model was run five times for 10,000 iterations with a 5000-iteration burn-in. We calculated the median z-score for each locus across all ten runs, and selected SNPs with a FDR < 1% to be associated with urbanisation. The results with two or four latent factors were highly concordant and the same candidate loci were recovered; thus, we only used the results obtained with four latent factors for further analyses. We also assessed the distribution of P values to check for the impact of confounding factors , we detected a far higher number of associated SNPs . We estimated the allele frequency–environment association for each SNP with the urbanisation score for each population accounting for population structure, using a covariance matrix. We estimated the covariance matrix using the LD-pruned SNP dataset in the core model using default parameters: 20 pilot runs of 1000 iterations, a run length of 50,000 iterations, sampling every 25th iteration, and a burn-in of 5000 iterations. The resulting covariance matrix was used as input for five replicated runs of the auxiliary covariate model using the above settings. The strength of association is given in the test by estimated Bayes factor . We calculated the median Bayes factor across all five replicated runs and considered all SNPs with a deciban unit (dB) > 20 as urbanisation associated. This is the strictest criterion and is considered as “decisive evidence” for the association87. Using a resampling-without-replacement-based permutation approach and a chi-square test, we determined if the overlap between the LFMM and BayPass candidate SNPs is higher than expected by chance.Second, we analysed associations with urbanisation using the auxiliary covariate model implemented in BayPass v.2.1 (ref. FST88) for each urban and rural pair for each SNP, using VCFtools v. 0.1.15 (ref. 80). We subsequently summarised and plotted FST values in 200 kb sliding windows with 50 kb steps, using the WindowScanR v.0.1 R-package (https://github.com/tavareshugo/WindowScanR), and standardised window-based FST estimates using a z-transformation (ZFST). Standardisation was performed separately for autosomes and the Z-chromosome.To identify genomic regions distinguishing adjacent urban and rural great tits, we estimated the genetic differentiation . For computational reasons, the analysis was performed on a thinned SNP dataset , for which we randomly selected one SNP every ~50 kb.To determine if the extent of genetic differentiation between all possible population pairs was significantly different from zero, we estimated Rsb score below) to identify genomic regions showing signs of older and completed selective sweeps. We used fastPHASE v.1.4 (ref. 90) to reconstruct haplotypes and impute missing data independently for each chromosome using the default parameters, except that each individual was classified by its population (“-u” option). We used ten random starts of the EM algorithm (“-T” option) and 100 haplotypes (“-H” option). The fastPHASE output files were analysed using rehh v.2.0 (ref. 91) to calculate Rsb statistics per focal SNP. The Rsb score is the standardised ratio of integrated EHHS  between two populations91. This statistic measures the extent of haplotype homozygosity between two populations and follows the rationale that if a SNP is under selection in one population compared to the other, the region around this locus will show an unusually high level of haplotype homozygosity compared to the neutral distribution. In accordance to Gautier and colleagues91, we considered significant SNPs putatively under selection in urban populations based on a threshold of Rsb ≥ 4. To identify genomic regions consistently showing strong signals of selection, we summarised Rsb scores in 200 kb sliding windows (50 kb steps) and selected windows under selection as those with (i) an average Rsb scores above the 95th percentile of the genome-wide distribution (separately for autosomes and the Z-chromosome) and (ii) a proportion of urban outlier SNPs (Rsb > 4) above the 95th percentile of the genome-wide distribution (separately for autosomes and the Z-chromosome). The proportion of outlier SNPs per window was the number of SNPs with Rsb values >4 compared to the total number of SNPs per window92. Because recombination rates can be assumed to be conserved between closely related urban and rural populations, the cross-population comparative nature of the Rsb statistic provides an internal control that cancels out the effect of heterogeneous recombination across the genome48.To identify genomic regions showing signs of selective sweeps in urban–rural population pairs, we used two haplotype-based selection scans. First, we scanned the genome for regions showing differences in extended haplotype homozygosity (EHHS) between urban and rural populations (see nSL93 statistic (XP-nSL) that tests for signatures of ongoing or recently completed selective sweeps and is implemented in selscan v.1.3.0 (ref. 46). XP-nSL contrasts nSL, the number of segregating sites by length, between two populations and thus tests for differential local adaptation. Analogous to Rsb, we conservatively detected genomic regions by a 200 kb sliding windows as those with (i) average XP-nSL scores above the 95th percentile of genome-wide distribution (separately for autosomes and the Z-chromosome) in each population and (ii) proportions of outlier SNPs (XP-nSL > 2) above the 95th percentile. We also plotted haplotype patterns around candidate genes using the haplostrips software v.1.3 (ref. 94).Second, we used a cross-population XP-nSL and Rsb) into outlier regions, if windows were not >200 kb apart, using csaw v.3.12 (ref. 95).To determine larger genomic regions associated with signals of selection, we merged adjacent outlier windows for each selection statistic (n genes (n = number of genes with signatures of selection in each urban population) for each population from the list of all SNP-linked genes using the “resample” function in R, assessed the amount of overlap between populations (from two to eight populations) and repeated the sampling 100,000 times for each comparison. We then calculated the mean and 95% CI for each comparison and compared the number of observed shared candidate genes to the expected number of candidate genes. The expected number of genes showing signs of selection in three or more populations was zero, thus we focused on genes showing signs of selection (Rsb and XP-nSL) in three or more populations.To determine the consistency of selection across urban centres, we implemented a resampling approach to assess the likelihood of genes showing signs of selection in two, three, four or more populations. We resampled with replacement Y ∼ habitat × locality × habitat × locality”) to quantify the effects of (i) “habitat” , (ii) “locality”  and (iii) “habitat × locality” interaction 96. We performed this analysis for all individual SNPs  and based on PC scores from the first three PC axes for all LFMM candidate SNPs (PCLFMM), and those overlapping between the LFMM and BayPass analyses . The PCA was estimated for each SNP dataset using SNPrelate v.3.12 (ref. 97). We used the “EtaSq” function implemented in BaylorEdPsych v.0.5 (ref. 98) to extract the effect sizes  for the model terms in each linear model.To determine the explanatory power of urbanisation-associated SNPs and consistency in allele frequency changes across populations, we used linear models .To estimate the impact of variation in recombination rate and linked selection in low-recombination regions on patterns of divergence , we estimated the correlations of LD and intronic GC-content in 200 kb windows with measures of selection/differentiation (r2) across the genome using Plink 1.9 (ref. 78) for pairs of SNPs located up to 200 kb apart for each urban population . LD estimates were averaged in 200 non-sliding windows using the WindowScanR v.0.1 R-package.First, we estimated patterns of LD (P. major) reference genome build 1.1 , as low intronic GC-content is a good proxy for long-term reduced recombination in that region52. Intron coordinates were extracted from the great tit reference genome using the plyranges v.3.12 (ref. 99) and GenomicRanges v.3.12 (ref. 100) R-packages, and the GC-content for each intron inferred using the “nuc” function in BEDtools v.2.28 (ref. 101). Intronic GC-content values were further averaged across 200 kb non-sliding windows using WindowScanR.Second, we estimated the GC-content for all introns across the great tit  across all 200 kb windows for each population, using the “cor.test” function in R.Lastly, we estimated the genome-wide Pearson correlations between LD, GC-content and all estimators of selection (P. major) reference genome build 1.1 . We used all genes containing SNPs associated with urbanisation . To analyse the enrichment of functional classes, we identified overrepresented GOs , using the WebGestalt software tool102. The gene background was set using annotated great tit genes (annotation release ID 101) containing SNPs from the SNP chip and with Homo sapiens orthologues. H. sapiens genes were used as a reference set as human genes are better annotated with GO terms than those of any avian system 39. We focused on non-redundant GO terms to account for correlations across the GO graph topology and GO terms as implemented in WebGestalt102. An FDR < 0.05 was used as a threshold for significantly enriched GO terms. Furthermore, we searched the public record for functions of individual candidate genes. We also used GOrilla103 to visualise the connections of GO terms associated with LFMM candidate genes and Cytoscape v.3.6.1 (ref. 104) to visualise the GO network and identify all enriched GO terms , including redundant terms.We obtained the gene annotations for all candidate SNPs from the great tit (XP-nSL or Rsb outlier windows. Overlaps between outlier windows and annotated genes were assessed using the plyranges R-package v.3.12.Candidate genes associated with signatures of selection were those that overlapped with significant Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Quercus liaotungensis Koidz. is an ecologically and economically important tree species widely distributed in Northern China. However, the effective assessment, utilization, and protection of Q. liaotungensis resources remain unexplored.Q. liaotungensis populations of Northern China were investigated for genetic diversity and structure using 19 simple sequence repeat (SSR) primer pairs.In total, 120 samples obtained from 12 Ne) was 6.084, the genetic differentiation coefficient (Fst) was 0.033, and the mean observed heterozygosity (Ho) and expected heterozygosity (He) were 0.690 and 0.801, respectively. Moreover, analysis of molecular variance (AMOVA) showed a 5.5% genetic variation among 12 Q. liaotungensis populations, indicating that a high level of genetic diversity and a low degree of genetic differentiation among Q. liaotungensis populations. STRUCTURE and cluster analysis divided the 12 Q. liaotungensis populations into the following three subpopulations: Bashang Plateau subpopulation (SH), Liaodong Peninsula subpopulation (NC), and Loess Plateau subpopulation (other 10 populations). The cluster analysis based on 19 climatic factors was consistent with the genetic structure. A positive correlation was found between genetic distance and geographical distance  by the Mantel test, and two boundaries were found among the 12 Q. liaotungensis populations by the Barrier analysis, indicating that Q. liaotungensis populations existed isolated by geographical distance and physical barrier.The total number of alleles detected was 293, the average number of effective allele (Q. liaotungensis.This study suggests that geographical isolation, physical barrier, climatic types, and natural hybridization promote the formation of genetic structures, which can contribute to future protection and genetic improvement of  Quercus liaotungensis Koidz. is a dominant species found in deciduous broad-leaved forests of Northern China  markers are highly polymorphic, stable, codominant, and hence regarded as effective means to study the genetic diversity and genetic structure of Quercus species . Zeng etongolica . Yang etQ. liaotungensis from different distribution zones in China. The objectives of this study are as follows: (1) how the genetic diversity and genetic differentiation among 12 Q. liaotungensis populations; (2) the genetic structure and the number of subpopulations were assessed; (3) whether the geographical distance, physical barrier, and climate factors influenced the genetic structure. These findings are advantageous for revealing genetic information and assisting the conservation and utilization of Q. liaotungensis germplasm resources.Here, we used 19 SSR primers to detect and estimate the genetic variation of Q. liaotungensis samples from 12 natural populations were collected from five provinces in China  of Northern China. Bashang Plateau (Hebei Province) and Liaodong Peninsula (Liaoning Provinces) are present in the distribution on an overlapping ecological niche of Q. liaotungensis and Q. mongolica species. The distance of each individual was above 50 m. Young leaves were collected and dried using silica gel for DNA extraction and stored at −80 °C until use.A total of 120 in China , Table 1The total genomic DNA was extracted from young leaves using the DNA secure Plant Kit . The quality and concentration of DNA were detected by agarose gel electrophoresis and NanoDrop 2000 spectrophotometer , respectively. High-quality DNA was used immediately or stored at −20 °C until use.Q. liaotungensis populations was studied using 19 SSR primers , and 0.5 µL of forward primer (1 µM) with a fluorescent label with FAM, HEX . The PCR program was as follows: pre-denaturation at 94 °C for 5 min, followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at 55 °C for 30 s, and extension at 72 °C for 30 s, with a final extension at 72 °C for 10 min. The PCR products were analyzed by capillary electrophoresis in an ABI 3730xl DNA Analyzer . The SSR allele size was determined by GeneMarker version 2.2 software .The genetic diversity of 12  primers  (Table 2Na), the effective number of alleles (Ne), observed heterozygosity (Ho), expected heterozygosity (He), and Shannon’s information index (I). Deviation from Hardy-Weinberg proportions (HWP) was investigated in each population at a single locus (PIC) at each locus was calculated according to the following formula Fst) of each locus and the matrix among 12 Q. liaotungensis populations were calculated using FSTAT version2.9.3 software ((Nm) was evaluated using the following formula: Nm = (1 − Fst)/4Fst. Analysis of molecular variance (AMOVA) was performed among and within populations using GenAlEx version 6.5 software  at 10 arc-min resolution using ArcGIS software version10.2. The clustering heat map of 19 climatic factors was drawn using Origin 2018 software. The correlation between genetic distance and climatic factors was detected by the Mantel test , and also for the length of the burn-in period and MCMC after setting the length to 100,000 and 200,000, respectively. The optimal K value was selected according to the deltaK criterion using the “STRUCTURE HARVESTER” online program with the method from Evanno  for each locus ranged from 2.989 (bcqm50) to 12.961 (ssrQrZAG96), with an average of 6.084. The observed heterozygosity (Ho) for each locus varied from 0.420 (bcqm76) to 0.900 (Qden05011), with an average of 0.690, whereas the expected heterozygosity (He) ranged from 0.666 (bcqm50) to 0.923 (ssrQrZAG96), with an average of 0.801. Shannon’s information index (I) ranged from 1.330 (bcqm50) to 2.750 (ssrQrZAG96), with an average of 2.013. The genetic differentiation coefficient (Fst) (0.008(bcqm96)–0.077(ssrQrZAG112)) and polymorphic information content (PIC) (0.893(bcqm50)–0.963(ssrQrZAG101)) were detected at all loci. Gene flow (Nm) varied from 2.997 in locus ssrQrZAG112 to 31.000 in locus bcqm96, with an average of 11.286. 19 loci were accorded with Hardy-Weinberg proportions(HWP).We used 19 pairs of SSR primers to generate 293 alleles from 120 individuals of 12 ulations . The resQ. liaotungensis populations was shown in Na) was 6.781, and it varied from 6.316 for the SH population to 7.474 for the NC population, whereas the average effective number of alleles (Ne) was 4.477, ranging from 3.819 for the SH population to 5.224 for the NC population. Shannon’s information index (I) varied from 1.498 for the SH population to 1.753 for the NC population, with a mean of 1.599. Mean value of observed heterozygosity (Ho = 0.688) were less than that of expected heterozygosity (He = 0.737). The mean value of fixation index (Fis) was 0.067, ranging from 0.062 for the DT population to 0.324 for the SH population, and Q. liaotungensis populations accorded with HWP, except for the SH population. Among them, the NC population had the highest genetic diversity parameters , whereas the SH population had the lowest. Thus, by comparison, the NC population showed the highest level of genetic diversity.The genetic diversity of 12 Fst value was between 0.00–0.05 and 0.05–0.15, respectively, and the Fst value more than 0.15 showed a high genetic differentiation , the average gene flow (Nm) was 11.286, which showed that the gene frequently changed among the 12 Q. liaotungensis populations. The relatively high level of gene flow was consistent with the low level of genetic differentiation. AMOVA showed that 94.5% of the genetic variation was found within 12 Q. liaotungensis populations, and only 5.5% of the variation occurred among 12 Q. liaotungensis populations  between KC and SH populations.The genetic differentiation was low and moderate among populations when the ntiation . The genulations . The resulations , and theQ. liaotungensis populations was generated based on Nei’s genetic distances using the Unweighted Pair Group Method with Arithmetic Mean (UPGMA) method (Q. liaotungensis populations under a coefficient of 0.2 can be divided into 3 clusters: SH population (cluster I), NC population (clusterI I), and other 10 populations (cluster I I I). The result of the Mantel test was significant for Nei’s genetic and geographical distances of 12 Q. liaotungensis populations . Analyses of the physical barrier between the 12 Q. liaotungensis populations supported the two boundaries shown in Q. liaotungensis populations. The boundary b separated NC and SH population.A dendrogram of 12 ) method . The Q. ulations , indicatQ. liaotungensis populations was constructed based on 19 climatic factors, as shown in Q. liaotungensis populations were divided into 3 clusters, and the outcome was highly similar to the cluster analysis based on genetic distance, indicating that the genetic structure of Q. liaotungensis may be affected by climatic conditions. However, the result of the Mantel test between Nei’s genetic distance and climatic factors of 12 Q. liaotungensis populations was not significant  (The cluster heat map of 12 = 0.120) .Q. liaotungensis was analyzed with a Bayesian model using STRUCTURE software. The result showed that ΔK reached a maximum value when K = 3, indicating that 12 Q. liaotungensis populations can be divided into 3 subpopulations  and Liaodong peninsula subpopulation (NC) was 0.054, and between Bashang plateau subpopulation and Loess plateau subpopulation (other 10 populations) was 0.068, indicating a moderate level of genetic differentiation among 3 subpopulations. Meanwhile, we have investigated gene flow (Nm) among 3 subpopulations. The pair-wise value of Nm among 3 subpopulations was 3.41 (Bashang Plateau vs. Loess Plateau), 7.44 (Liaodong Peninsula vs. Loess Plateau), and 4.38 (Liaodong Peninsula vs. Bashang Plateau), respectively.In addition, we independently investigated the genetic differentiation and gene flow among 3 subpopulations, and found that the higher values of Q. liaotungensis populations showed a high level of genetic diversity, especially concerning heterozygosity (He = 0.801), which was higher than that of other Quercus species, such as summer oak (Q. robur) (He = 0.764) (Q. acutissima) (He = 0.660) (Q. mongolica) (He = 0.630)  in this report was higher than that of previous report (He = 0.754)  , sawtoot= 0.660) , and Mon= 0.630) . On the ountains . The wid= 0.754) . The mai= 0.754) .Q. liaotungensis populations. The NC population is located in the Liaodong Peninsula of Northeast China, where the ecological niche overlap for Q. liaotungensis and Q. mongolica species. Therefore, the natural hybridization of the 2 species could lead to gene introgression and show a much larger genetic diversity than the other populations. The SH population had the lowest genetic diversity and significantly deviated from the HWP. Fewer individuals existed in secondary forests with a patchy distribution of Q. liaotungensis, thereby causing this phenomenon.At the population level, the NC population had the highest genetic diversity out of the 12 Q. liaotungensis populations and higher genetic variation within 12 Q. liaotungensis populations. This difference could be attributed to high outcrossing rates, reproduction, wind-pollination, and acorn transport (Q. liaotungensis population was low (Fst = 0.033), and the result was consistent with the recent research on Quercus species, such as holm oak (Q. ile x) (Fst = 0.018) (Q. suber) (Fst = 0.017)  may limit genetic drift and reduce genetic differentiation.Compared to the herbaceous plants, the woody plants have lower genetic differentiation among 12 ransport . The lev= 0.018)  and cork= 0.017) . Moreove= 0.017) . In the Q. liaotungensis is divided into 3 subpopulations with the Bayesian model, which is consistent with the results of the cluster analysis based on Nei’s genetic distance. Furthermore, the results of the Mantel test showed that the genetic distance had a significantly positive correlation with the geographic distance , indicating clear isolation by distance (IBD) among the investigated Q. liaotungensis populations. A larger distance from 35.89 km (between KC and DS population) to 1,642.82 km (between NC and SM population) based on the latitude and longitude may lead to a more significant genetic differentiation. In addition, two boundaries exist in 3 groups of 12 Q. liaotungensis populations. The boundary a, isolated the 10 Q. liaotungensis populations from Loess Plateau in China by Taihang Mountains. The boundary b, corresponding to the Liao River, and separated the NC population from the Liaodong Peninsula and SH population from Bashang Plateau. Therefore, the geographical distance and physical barriers jointly affected the genetic differentiation among Q. liaotungensis populations. Additionally, the genetic differentiation of marginal populations of the Q. liaotungensis was higher than that of the central populations in China  and have adapted to distinct ecological niches with unique temperature and precipitation seasonality, resulting in high genetic differentiation. Interestingly, the NC and SH population have higher precipitation  and temperature differences (bio4 and bio7) when compared to other populations, respectively, and these two populations had been separately divided into 2 distinguished clusters. Secondly, Q. liaotungensis populations showed a dynamic expansion decline trend during the Quaternary climatic oscillations and increased genetic differentiation between central and peripheral populations. Hence, we can conclude that climatic conditions exert an important influence on the genetic structure of Q. liaotungensis.The genetic structure formation not only depends on geographical isolation but also affected by the changes of distribution and size mediated by climatic conditions . Studiesulations . In thisQ. liaotungensis and Q. mongolica occurs in areas of ecological niche overlap. The hybrid traits, such as all of the differentiated leaf and reproductive traits, tend to those of Q. liaotungensis  of pie charts to be larger than the other groups. In addition, studies have shown that interspecific hybridization frequently occurs in the closely related species of Quercus  is required. Meanwhile, seeds and scions should be collected to establish germplasm pools for ex-situ protection. Because the genetic variation exists mainly within the populations, we need to collect as many families and individuals as possible at each population. In addition, active management, such as the establishment of seed forests and artificial promotion of natural regeneration, is necessary.The germplasm resources of Q. liaotungensis populations in China using 19 SSR primer pairs. The Q. liaotungensis population presents a relatively high genetic diversity and low genetic differentiation, with the majority of variations occurring mainly within the population. The STRUCTURE analysis shows that the genetic structure of Q. liaotungensis populations can be divided into three subpopulations. The Mantel test reveals a positive correlation between Nei’s genetic distance and geographic distance, and two boundaries were found among the 12 Q. liaotungensis populations by the Barrier analysis, indicating that Q. liaotungensis populations have been isolated by distance and physical barrier. In addition, climatic conditions and natural hybridization influence the genetic structure of Q. liaotungensis populations. All together, the findings of this study will play an essential role in the conservation and genetic improvement of Q. liaotungensis.In this study, we evaluated the genetic diversity and structure of 12 10.7717/peerj.10922/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.10922/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.10922/supp-3Supplemental Information 3Click here for additional data file.10.7717/peerj.10922/supp-4Supplemental Information 4Click here for additional data file.10.7717/peerj.10922/supp-5Supplemental Information 5Click here for additional data file.10.7717/peerj.10922/supp-6Supplemental Information 6Click here for additional data file.


Halyomorpha halys (Hemiptera: Pentatomidae) is native to East Asia but has invaded many countries in the world. BMSB is a polyphagous insect pest and causes significant economic losses to agriculture worldwide. Knowledge on the genetic diversity among BMSB populations is scarce but is essential to understand the patterns of colonization and invasion history of local populations. Efforts have been made to assess the genetic diversity of BMSB using partial mitochondrial DNA sequences but genetic divergence on mitochondria is not high enough to precisely accurately identify and distinguish various BMSB populations. Therefore, in this study, we applied a ddRAD (double digest restriction-site associated DNA) sequencing approach to ascertain the genetic diversity of BMSB populations collected from 12 countries (2 native and 10 invaded) across four continents with the ultimate aim to trace the origin of BMSBs intercepted during border inspections and post-border surveillance.Brown marmorated stink bug (BMSB), A total of 1775 high confidence single nucleotide polymorphisms (SNPs) were identified from ddRAD sequencing data collected from 389 adult BMSB individuals. Principal component analysis (PCA) of the identified SNPs indicated the existence of two main distinct genetic clusters representing individuals sampled from regions where BMSB is native to, China and Japan, respectively, and one broad cluster comprised individuals sampled from countries which have been invaded by BMSB. The population genetic structure analysis further discriminated the genetic diversity among the BMSB populations at a higher resolution and distinguished them into five potential genetic clusters.The study revealed hidden genetic diversity among the studied BMSB populations across the continents. The BMSB populations from Japan were genetically distant from the other studied populations. Similarly, the BMSB populations from China were also genetically differentiated from the Japanese and other populations. Further genetic structure analysis revealed the presence of at least three genetic clusters of BMSB in the invaded countries, possibly originating via multiple invasions. Furthermore, this study has produced novel set of SNP markers to enhance the knowledge of genetic diversity among BMSB populations and demonstrates the potential to trace the origin of BMSB individuals for future invasion events.The online version contains supplementary material available at 10.1186/s12864-021-07678-z. Halyomorpha halys  (Hemiptera: Pentatomidae) is a highly polyphagous pest with a wide host range [The brown marmorated stink bug (BMSB), ys Stål, 855 , such as the COI (Cytochrome c oxidase I) and/or COII (Cytochrome c oxidase II) genes , 22–24. The detection of different genetic markers is crucial for studying genetic diversity. Recently, a high-throughput sequencing-based method (HTS) has replaced traditional gel-based experiment to discover genetic markers . RADseq To select the most suitable restriction enzyme (RE) pairs for digesting BMSB genomes, in silico test using 15 combinations of REs against the BMSB genome scaffolds were conducted. The simulation revealed that more than 100 K fragments produced from most of the RE pairs selected except the pairs, MseI-MluCI, MspI-PstI and EcoRI-PstI  . On average, 9 million raw paired end reads were generated for each individual. The 3′ end adaptors of raw reads were trimmed and low quality reads were discarded. Using quality-trimming of the sequence data, 387,629 SNPs were estimated from 399 BMSB individuals. A highly stringent QC criterion was applied for filtering the SNPs, and only those loci that were shared by all the individuals were retained. This resulted with 1775 high confidence biallelic SNPs from 389 individuals. Further analysis showed that the 1775 SNPs were distributed in 484 scaffolds and 1–20 SNPs were detected in each of those scaffolds with average 3.7 SNPs per scaffold  were revealed by Principal Component Analysis (PCA) using the SNP data generated from 389 BMSB individuals Fig. . All BMSTo further emphasise the outcome of genetic clustering pattern via principal component analysis, minimum spanning networks (MSN) were constructed using the SNPs profile of each individual, and genetic variability was visualised among the population lineages Fig. . The MSNST revealed significant (p < 0.05) genetic differences (except for that between China and Serbia) among 12 geographical groups or countries, with FST value ranging from 0.0006 between BMSB populations from Hungary and Serbia, to 0.2084 between BMSB populations from Japan and Romania (Table ST = 0.0847) than that between the populations of China and many other BMSB-invaded countries, such as Slovenia (FST = 0.0379). Similarly, the genetic distance between the invaded populations in the USA and Chile was relatively low (FST = 0.0393) compared to the genetic distance between BMSB populations in Chile and the native regions, China (FST = 0.0984) and Japan (FST = 0.1765). Moreover, the FST value between the BMSB populations from the neighbouring countries was very small, for example, Turkey and Georgia (FST = 0.0165); Austria and Slovenia (FST = 0.0203); Hungary and Serbia (FST = 0.0006) . Therefore, the results indicate that the individuals from one country are more genetically different within them than that the difference they have with the other countries.Fst analysis of the five genetic clusters Table  showed to) and the Expected Heterozygosity (He) for all the countries are not very high, around 0.2 . Conversely the Ho is bigger than the He in the other countries, indicating that an isolate-breaking effect is happening, and interbreeding is occurring among those populations.The heterozygosity analysis was showed that the Observed Heterozygosity , phylogenetic analysis and population structure analysis to elucidate the population structure and genetic diversity among the BMSB populations. The present study unambiguously proved that the BMSB populations in the two native regions of China and Japan were genetically distinct. Many BMSB populations from the invaded countries were genetically closer to those of China. Conversely, the Japanese BMSB populations were isolated and showed genetically less similar to those from the invaded countries. Overall, this study has provided a remarkable resolution in unravelling the population structure and estimating the genetic relatedness among the BMSB populations from a set of native and invaded regions of the world.The PCA and MSN analyses showed that the Japanese BMSB populations were isolated from the other populations studied here. The fastSTRUCTURE analysis showed that population structures of the BMSB samples from China and Japan were derived predominantly from different genetic components Fig. . These rST < 0.25) between the BMSB populations in Japan and the invaded countries of Chile, Georgia, Italy, Romania, Turkey, and the USA , indicating that these established populations have been undergoing population expansion stage [Moreover, the PCA Fig.  and 4 inon stage .One individual BMSB sample from the Italy cohort was genetically closely related to the Chinese population Fig. , suggestThe population structure analysis of BMSB indicated that there were at least five genetic clusters identified among the BMSB populations studied here. Besides the genetic clusters of native BMSB populations from China and Japan, there were three genetic clusters in the BMSB-invaded countires. The analysis showed that the BMSB populations from the USA, Georgia, Turkey, Italy, Hungary, and Chile were more likely belong to one genetic cluster due to their similar genetic structure. Since first detected in the USA in 1996 , BMSB haAnother interesting phenomenon is that the genetic structures between BMSB populations originating from Slovenia, Austria, and Serbia and the Chinese populations were more genetically related than those between the Chinese and the other European populations Fig. . This suST values between the BMSB samples from Romania and the two native countries, China, and Japan, were 0.1333 and 0.2084, respectively, which were larger than the FST values from other invaded populations. The population structure analysis showed that Romanian BMSB samples had a unique genetic structure, which indicates that this group could have been invaded from a place of origin that was not sampled in this study. Therefore, this study further emphasised the importance of sampling. Overall, this study covered a wide range of areas including wide BMSB sampling from the native regions and the invaded countries, although we still missed samples from some countries, such as Korea, Greece, Canada and Switzerland. Therefore, further study of ddRADseq of BMSB samples from those countries will provide more insights into genetic diversity of the BMSB populations and facilitate in inferring a more in-depth invasion pathway.BMSB was first reported in Romania in 2015  and haveThis study also provided novel genetic information on the BMSB populations for some of the European countries, such as Austria, Serbia, Slovenia, and Georgia. Since BMSB was detected in Austria  and SerbIn comparison with the mitochondrial based (i.e. COI and COII) haplotypes analyses, here we show that ddRADseq can provide a higher resolution in identifying and characterising different BMSB genetic populations. As an alternative, analysis of genome-wide SNPs via whole genome sequencing can be applied for deeper understanding the BMSB genome and genetic diversity. However, it is still more expensive due to the large size of the BMSB genome (~ 1 Gbp) . TherefoThis study demonstrates that the restriction enzymes pair of EcoRI and MspI is suitable for generating restriction-associated DNA fragments for identifying SNPs within the BMSB genome through ddRAD sequencing. Via population genomic analyses using ddRADseq data, we detected remarkable genetic diversity among different BMSB populations studied in both the native and invaded countries. We believe that this study could also assist in studying the invasion history of BMSB populations and tracing the potential geographical origin of unknown BMSB intercepted at the border or in post-border scenarios in biosecurity settings using the population structure model. Thus, ddRAD sequencing going to be an invaluable emerging technology added into the biosecurity toolbox for tracing the geographic origin of insects at the border/post-border in the near future.BMSB samples were collected from 41 regions in 12 countries, namely Austria, Chile, China, Georgia, Hungary, Italy, Japan, Romania, Serbia, Slovenia, Turkey, and the USA Table . The fieThe selection of restriction enzyme (RE) is the crucial step for experimental ddRADseq analysis and discovery of the SNPs across the genome for genetic diversity study, thus initial in silico tests on the RE used for the library was conducted. To select the best RE, a simulation based on the BMSB reference genome  and 15 combinations of nine enzymes . A Python script  for digestion of BMSB genome via ddRADseq approach, 399 BMSB individuals were further subjected to double-digest restriction-associated DNA (ddRAD) sequencing. ddRAD libraries were prepared using 500 ng of genomic DNA from each sample following the protocol described by Peterson et al.  with somin vitro: RAD sequencing and bioinformatics analysis". To call SNPs from ddRADseq data, the raw fastq files were mapped to the scaffold of the reference genome, Hhal_2.0 (RefSeq assembly accession: GCF_000696795.2), to produce a mapping file (SAM format) using BWA v 0.7.17 [To pre-process the raw sequencing data generated via ddRAD, a similar pipeline and data quality filtering approach was applied as described in the section of "Selection of restriction enzymes v 0.7.17 . The SAMv 0.7.17 . SNPs wev 0.7.17 . The quav 0.7.17 . As a reUsing the SNPs identified from the 389 BMSB individuals, we conducted principal component analysis (PCA), neighbour-net tree and population structure analysis using fastSTRUCTURE to elucidate the population structure and genetic diversity among the BMSB populations. PCA was conducted based on 1775 high quality SNPs obtained from the 389 individuals using Plink 1.9   was determined as 5 using a python script, chooseK.py within the fastSTRUCTURE software.To provide additional insight into the genetic variation and population differences, population genetic structure analysis was conducted. The population genetic structure was inferred using the SNPs profile of individual samples. In this process, fastSTRUCTURE 1.0  was usedA roadmap of the BMSB invasive pathway was created using Tableau  by inputAdditional file 1. Sequence result of selection of restriction enzymes.Additional file 2. SNP distribution in Scaffold.Additional file 3. PCA plot using one SNP from each scaffold.Additional file 4. 3D PCA plot.Additional file 5. Sample collection information.Additional file 6. RE digest simulation script.Additional file 7. Heterozygosity analysis.