In the last decade, several studies aimed at dissecting the genetic architecture of local small ruminant breeds to discover which variations are involved in the process of adaptation to environmental conditions, a topic that has acquired priority due to climate change. Considering that traditional breeds are a reservoir of such important genetic variation, improving the current knowledge about their genetic diversity and origin is the first step forward in designing sound conservation guidelines. The genetic composition of North-Western European archetypical goat breeds is still poorly exploited. In this study we aimed to fill this gap investigating goat breeds across Ireland and Scandinavia, including also some other potential continental sources of introgression. The PCA and Admixture analyses suggest a well-defined cluster that includes Norwegian and Swedish breeds, while the crossbred Danish landrace is far apart, and there appears to be a close relationship between the Irish and Saanen goats. In addition, both graph representation of historical relationships among populations and f4-ratio statistics suggest a certain degree of gene flow between the Norse and Atlantic landraces. Furthermore, we identify signs of ancient admixture events of Scandinavian origin in the Irish and in the Icelandic goats. The time when these migrations, and consequently the introgression, of Scandinavian-like alleles occurred, can be traced back to the Viking colonisation of these two isles during the Viking Age (793-1066 CE). The demographic analysis indicates a complicated history of these traditional breeds with signatures of bottleneck, inbreeding and crossbreeding with the improved breeds. Despite these recent demographic changes and the historical genetic background shaped by centuries of human-mediated gene flow, most of them maintained their genetic identity, becoming an irreplaceable genetic resource as well as a cultural heritage. Capra hircus) have been subjected to long-distance transportation from different geographic areas over thousands of years1. In particular, the islands were often used as strategic hubs of economic activity along the maritime routes and lots of domestic animals were translocated to islands to assure food availability2. Their small size and their remarkable versatility, adaptability and a greater resilience with respect to other ruminants3 made goats an ideal commodity, easy to be carried along land, maritime and riverine routes, following human displacements. The wool was used for warriors’ clothing and sailcloth4, making goats suitable not only for feeding but also for supplying the complex trading networks that were expanding. Over the past two centuries there has been an extensive transportation and intensive selection pressure on some very productive breeds at the expense of some traditional local breeds, which became neglected. These phenomena led to a dramatic reduction in their levels of genetic diversity, and in some cases pushed them to the brink of extinction5. The value of traditional breeds is recognised as providing a basis for future studies on diversity, domestication and the evolution of genes and traits of interest because they retain adaptive, specific alleles to thrive in their own environment6. Therefore, preserving the genetic variability and the uniqueness of indigenous goat breeds must be a priority in managing conservation and sustainable breeding programs.Since their domestication beginning ca. 11,500 years ago in Southwest Asia, goats . Our second objective was to understand how gene flow and admixture events have shaped the genetic makeup of Scandinavian and Irish breeds, tracing back their origin. Nevertheless, our results can help to establish the “health status” of these local landrace goat breeds, identifying those which can be considered as the last modern archetypal ‘ancient’ type of goat. Indeed, these insights may be a starting point to discover the potential value of some breeds as a reservoir of historical genetic heritage. Finally, although with a certain caution, the goat genome could be considered a type of “bioproxy” – an organism that, through its close association with humans, shares a common colonisation history—such as the mouse genome, as proposed in previous studies13. The use of the goat genome as a tool to indirectly infer the human phylogeography can become a complementary approach for discovering new clues about historical human land and maritime routes that are still uncertain.The accessibility of cutting-edge genomic techniques, the large amount of genetic data available in public databases and the feasibility of fine-grained bioinformatic tools allowed researchers to move forward in the study of demography and evolution of several organisms and to dissect the complex process of domesticationIn this study, the analyses were performed on two datasets. The first one included 10 breeds belonging to Northern and Western Europe (our target area and hereafter indicated by the acronym NW-EU): Icelandic landrace (ICL), Norwegian landrace , Swedish landrace (SWE), Danish landrace (DNK), Finnish landrace (FIN), Irish landrace . In the second one, a wider dataset (indicated by the acronym WHOLE), we added breeds from several countries—The Netherlands (NLD), Normandy (Fosseé—FSS), Northern and Southern Spain  and the South of Italy , as well as Alpine (ALP), Saanen (SAA) and Toggenburg (TOG), with a total of 24 breeds (see “ST and the Reynolds’ distance matrices for the WHOLE dataset are shown in Supplementary Table 10. For NRW and the Irish breeds we might suspect an isolate-breaking effect (the mixing of two previously isolated populations). The highest levels of inbreeding calculated at the whole genome level (FROH) characterise the populations from the islands , indicating a limited gene flow with the populations from the mainland, while the Swedish landrace shows very low levels of inbreeding. The FROH estimates at individual level indicate that in DNK breed, some animals stand out for their greater values  such as ICL, ARR and SKO, display more homozygous stretches and a bigger proportion of the genome covered by ROH, in comparison with breeds of larger size. In addition, these breeds have very long stretches (> 16 Mb) and also a higher number of ROH falling in the 2–4 class of length. Moreover, the Irish breeds carry a greater number of ROH included in the medium-length class (> 4–8). FIN, SWE and SEL have a smaller proportion of the genome covered by homozygote stretches, in agreement with the FROH values . From the ancestor BEZ—or a breed very close to it—there are three migrations events, towards NRW, FIN and BLB; the last significant vector indicates gene flow from the Norwegian coastal SKO towards FIN .The case of the NW-EU dataset is different Fig. B, where lts Fig. B togethelts Fig. B highlig15, if all three permutations of f4-statistic for a certain set of four populations are (significantly) non-zero, then at least one of the populations must be admixed; this is one of the most common signals of admixture used in the literature. Thus, out of 37,950 possible tree topologies tested, we selected the most valuable results (following the criteria detailed in methods), summarising them in Supplementary Table To evaluate the presence of admixture and gene flow, we further computed the f3 and f4 statistics. We did not observe significant results for the f3 test in either of the two datasets. Interestingly, we obtained some significant results using the f4 statistic. Following the explanations of the authorsIn the second step of the screening process, we focused only on the NW-EU breeds, excluding all possible “Alpine-Saanen influx” that could mask or confuse the signal of past admixture that we are looking for. Thus, we selected only the triplets with highly significant  non-zero values, summarising them in Supplementary Table The admixture proportions estimated via f4-ratio support the past gene flow among the study target populations. As we can observe in Supplementary Table The weighted linkage disequilibrium decay curves method implemented in the program ALDER was used to test some scenarios suggested by f4 and f4-ratio and to infer the admixture time that led to the genesis of Icelandic goats, and the possible contribution of Norse breeds in shaping the genetic make-up of Irish goat breeds. The weighted LD decay curves depicted in Supplementary Fig. 16 and subsequently, the admixture proportions and the time of admixture were inferred with the f4-ratio and the exponential LD decays. The first two components of Principal Component Analysis clearly separate the “Scandinavian” group from the “Continental” and the “South-Western European” ones. The Swedish breed is clustering with the Norwegian coastal populations with a FST value of 0.069 and a common ancestry is supported by Neighbor-Net and ADMIXTURE results. The genetic background at the most significant value of inferred ancestries (K = 22) underlines again a well-defined and shared genetic component in SWE and SEL almost without any foreign contribution. In agreement with that, the demographic history of the Swedish population appears not to be characterised by bottleneck or recent inbreeding, and it confirms several aspects already detected by analysing the genetic distances, the heterozygosity and homozygosity level. Moreover, the SWE population looks like a possible reference population for the Icelandic goats when we explore the population history with overlaid migration events using TreeMix and the f4 statistic. The proportion of this introgression is about 13% (f4-ratio between SEL|SWE|ICL). We retrieved a signal of admixture from the donor SWE to the Irish OIG and another potential donor NRW towards both OIG and BLB, but not towards ARR. The reason why we did not find any sign of past introgression in ARR probably lies in the high level of isolation in comparison with the other two Irish populations10 that can erase signatures of other old demographic events. A small population size combined with a fragmented distribution probably also favoured the maintenance of high levels of inbreeding in the Icelandic, Skorpa and Aran populations, a point that emerges from our results. This is mirrored also by the very long Runs of Homozygosity (ROHs) that characterise these isolated breeds. However, all the Irish breeds also carry a greater number of ROH included in the medium-length class (> 4–8), that is related to populations that have undergone a population bottleneck17, as confirmed by previous data18. Focusing on the second PCA analysis that includes only the Northern-Western European group, the small genetic distance between the Danish and the Irish goats could be associated with both a common recent introgression with the Saanen breed (for improvement purposes) but also with an older relationship related to the Norse conquest of the Irish and British Isles5. This “Scandinavian-like” – mostly Norwegian – ancestry component was already detected using the ancient and modern mitochondrial DNA of feral and improved Irish goats5. These patterns of introgression are observed also in the Icelandic goats: in particular there are two migration edges in the Maximum Likelihood tree that link this breed to (i) the Irish Bilberry and (ii) the branch that includes all breeds of Nordic origin. TreeMix analysis also detects another migration event, congruent with f4 estimates, that indicates not only the Scandinavian breed but also the Spanish Bermeya as candidate reference populations for this gene flow event (BEY towards BLB). Bermeya is a small, endangered breed from Asturias, Northern Spain (census of ~ 200019), a region that has been conquered by the Vikings during the Viking Age. However, also two human genetic studies about the origin of Celtic people also argued on the Spanish introgression in different timeframes into the Irish genome together with a Norwegian-like genetic component21. The possible contribution of BEY as donor to the Irish breed is confirmed in the TreeMix analysis, f4-statistic, the f4-ratio and the LD-decay curve. In particular, the LD-decay rate (that corresponds to the time of admixture) is consistent with the Iron Age and the Celtic expansion during the Roman Empire (~ 366 BCE)22. The f4-ratio quantified the Spanish-BEY proportion between 42 and 48% (BEY to BLB) and 18% and 21% (BEY to OIG), which is also evident in the ADMIXTURE analysis. The SAA_FR introgression detected in a small proportion is probably recent and related to the introduction of the Saanen breed in improvement schemes5. The TreeMix reconstructions based on ancient and modern Icelandic horses22 revealed that the modern individuals were most closely related to a group of North European horses including pre-Viking Pictish horses from Britain (c.a. sixth-seventh century), Viking horses (c.a. ninth-tenth century) and with samples of the Gallo- Roman period. This is in line with the diaspora of Scandinavian seafaring warriors and traders, as well as with the expansion of the Roman Empire22. In addition, and in agreement with another human genetic study that investigates the genomic history of the Iberian Peninsula, the authors documented a consistent trend of increased ancestry related to Northern and Central European populations from the Iron Age onward. This genetic cline increases from 10–19% in individuals along the Mediterranean coast to 28–43% in the North of Spain where Indo-European Celtiberian languages were likely spoken23.We analysed patterns of genetic diversity between Scandinavian and Irish goat breeds using publicly available genotypes and new data generated for a Swedish landrace population. We aimed to dissect the genetic status of the Swedish landrace in comparison with other Northern-Western European breeds. We found signs of introgression of Norwegian alleles in the genome of Icelandic and Irish breeds and further investigated these patterns by inferring the gene flow and admixture events that occurred in the past. These putative events were tested by f4 statistics24 and25 that assign to Icelandic goats a North-European (most likely Norwegian) origin after being imported during the colonisation of Iceland. The first settlement in Iceland also included individuals with North-Atlantic-like ancestry as described in Ref.26, who analysed the whole genome sequences of 27 ancient Icelanders. They further showed that these individuals were markedly more similar to their source populations in Scandinavia and in the British-Irish Isles than to modern Icelanders, whose genomes have been shaped by 1100 years of extensive genetic drift26.Those discoveries again confirm a complex network between the target study area during the history and corroborate the two gene flow events from Irish and Norwegian breeds towards Icelandic goats. The migration events of TreeMix, involving the Norwegian breeds and the Southern European populations (including the FSS from the Normandy) in both directions are once again probably linked to the trading routes during the Viking Age. A significant exponential LD decay is also detected in the Icelandic goats when we use the two Norwegian NRW|SEL as proxy to reference populations, providing further evidence for admixture. In this case, the admixture midpoint was estimated by ALDER program to have occurred ~ 1100 years ago, according to Refs.28.Previous studies performed on Icelandic sheep data identified patterns of admixture between other Scandinavian countries, assuming a Norwegian origin (thus descendant from Old Norwegian Short Tail Landrace) that fits well with historical records29. The first two centuries of this period are characterised by Viking raids and the subsequent Norse settlements along the coast, with five ports established at Dublin, Wexford, Waterford, Cork and Limerick. A strong signature of ancestral Scandinavian influence in the Irish genomes is also recorded in Connacht29. This western province of Ireland (Connacht) includes the county of Mayo, where the Old Irish goats analysed in this study have been collected. The County of Waterford (in the southern province of Munster) is the county where Bilberry originates from. In addition, the Scandinavian ancestral component was discovered also in cattle, analysing mediaeval cattle remains from Dublin30.The last significant LD decay rates point to the Irish breeds BLB|OIG as receiving populations and the NRW and SWE as representative donors, and the admixture times range from ~ 1300 to 960 years ago. These dates indicate a slightly greater timeframe back to the past in agreement with the earlier invasions of Ireland in comparison to Iceland, covering a period of more of 300 years (ninth-twelfth century) from the first Viking raids to the Norman invasion31 indicates a surge of gene flow from the British-Irish Isles into Scandinavia during the Viking period. This is perhaps not surprising, given the extent of Norse activities in the British-Irish Isles as said above. Indeed, raid and trade were often overlapping activities: the travellers were not only warriors but also farmers. The main trading commodities were jewels, slaves, metals, and farm animals. Studies on the wool used for sails in Viking ships demonstrated that at least 80% of analysed wool fragments were imported from outside of Denmark32. In addition to the above references, in a very recent study33 isotopic analyses of dogs and horses’ remains from different burial sites in the United Kingdom shed light on the Norse origin of the two species.A recent human genetic study aimed to assess the impact of historical migrations on the Scandinavian gene pool5 and like it happened in humans34. For example, the Old Irish goats have been subjected to casual hunting, reduction of their grazing area for urban development and indiscriminate culling of feral herds, which has led this population to the brink of extinction5. Although these goat breeds already have been now genetically well characterised, many questions regarding their origin and breed development remain to be discovered. For this reason, it is worth further investigate them using a fine-grained approach, combining ancient DNA and modern samples, using a whole genome sequence approach and more specific bioinformatic tools, which will give a long-term view of the formation and evolution of these breeds.Altogether, our insights suggest that the genome of these modern landrace still retain some clues of past human migrations though this ancient footprint has been eroded by the introgression of improved breeds and demographic declines, as argued byIn light of these findings, we can argue that the Swedish goat gene pool is well characterised, with good genetic variability levels, almost purebred with a Nordic genetic background similar to the neighbouring Norwegian coastal goats. Our ancestry analyses are supported by patterns documented in human phylogeography studies, previous studies in sheep and horse and historical records, identifying traces of Scandinavian-related ancestries in the genome of Icelandic and Irish goat breeds compatible with maritime Viking migration routes. This journey in the footsteps of the Vikings brought us back to the past, following hidden clues in the genome of indigenous goats. Most of them are in a critical status of conservation, surviving in small herds threatened by the demands of intensive production or the loss of habitats. Irish and Scandinavian breeds constitute ideal candidates that deserve efforts for a specific conservation program. We highlight their importance as a historical genetic resource because they retain in their genome a weak but still detectable signal of an ancient gene flow related to the formation of large-scale trading and cultural networks that spread people, animals and commodities, and revealing the untold potential of some endangered, unutilised, traditional goat breeds.The scope of this study was to assess the genetic diversity and the demographic history of Northern-Western European goat breeds. In addition, we aimed to detect past migration events explaining the breed formation of modern autochthonous goats in this target region of Europe.37. In this study, two datasets were built: the first one constituted by 10 breeds and 206 goats belonging to Northern and Western Europe (hereafter indicated by the acronym NW-EU) which are our target populations. For the second dataset, indicated by the acronym WHOLE, we added breeds from The Netherlands, Normandy (Northern France), Northern and Southern Spain and the South of Italy, as well as Alpine, Saanen and Toggenburg, with a total of 24 breeds and 669 goats. Sampling location is detailed in the map . Another technical reason for including cosmopolitan breeds is to deal with the ascertainment bias of the SNP chip. We also took into consideration the results from Ref.38, in which the Old Irish Goat (OIG) breed is closely related to the Southern Italian breeds as highlighted by the Neighbour-Joining tree and historical data about the migration routes during the Viking Age (750–1050 CE)31. Thus, the wider dataset (WHOLE) includes goat breeds that belong to countries of the ancient Vikings’ routes, from the continental Europe (the Netherlands) and from Southern-Western Europe along the Atlantic coast and part of the Mediterranean .We included the transboundary breeds since in the last decades they have contributed in a small fraction to the genome of Irish and Danish landraces, as suggested by previous results39. In particular for the Swedish Landrace, the sample collection, DNA extraction and the genotyping methods have been previous described in Ref.40. After merging, the SNP data were remapped against ARS1.2 assembly and the quality control was performed using PLINK v1.941, following the FAO guidelines for the genomic characterisation of animal genetic resources42. We excluded the variants that were unmapped, mapped on the sex chromosomes and on the basis of missing call rate per SNP (–geno < 0.05), of the minor allele frequency (–maf > 0.01) and of the individual missingness (–mind < 0.05). In addition, we performed a LD-pruning (Linkage Disequilibrium) using –indep-paiwise 50 5 0.2, (i) to reduce the bias due to the ascertainment43 and (ii) to remove individuals with extreme observed heterozygosity. The command –king cat-off in PLINK v2.0 was used to remove closely related (and possible duplicate) animals. This procedure left 35,375 SNPs for the subsequent analyses. Finally, we used BITE44 for reducing the unbalance among populations and retaining individuals from 5 to 50 on the basis of population structure. To convert these data into a format suitable for different input files, we used PGDSpider v2.0.4.045 for PLINK to Arlequin46 and CONVERTF  and the LD decay curves were estimated with the SNeP software51 with default settings and a correction to adjust the LD for small sample sizes. The genomic inbreeding coefficient FROH, the Runs of Homozygosity distribution per chromosome and classes of length as well as the total amount of the genome covered by these segments, were used to assess the level of inbreeding of the NW-EU populations and to infer past demographic events. All the calculations were performed with the R package DetectRUNS 0.9.552 (R core v4.1) applying the consecutive function and with the following settings: minSNP = 20, maxGap = 10^6, minLengthBps = 1 Mb, maxOppRun = 1, maxMissRun = 1. The five classes of length are the following: 0–2, 2–4, 4–8, 8–16 and > 16 Mb.We used Arlequin v.3.553 v4.14.2. The program TreeMix v1.1314 was applied to infer the gene flow and admixture events that occurred in the past. By using allele frequencies of SNP, we calculated a Maximum Likelihood tree that represents the evolutionary relationships across the analysed populations. We ran the program until the residuals plot R2 reached at least 0.998, that is from 0 (no migration) to 11 for the NW-EU dataset and from 0 to 15 for the WHOLE dataset, using the bezoar outgroup. Finally, we plotted the results by means of the plotting_funcs.R script provided within the same program. We also applied the function “treemix.fit” in BITE44 to evaluate TreeMix results, reporting the first population encountered in the donor subgraph, the first population encountered in the receiving subgraph, the migration weight (i.e. the estimated fraction of ancestry) in the receiving subgraph derived from the donor portion, jackknife and standard error estimate, and the p-value associated to the weight. As the authors of the program specified14, a “significant” p-value simply indicates that the hypothesised migration event significantly improves the fit to the data; this does not exclude the possibility of errors or indicate that the particular migration event tested is the correct one. For this reason, we used additional methods like three- and four-population (f3 and f4) statistics14 to test the robustness of the inference. These statistics were inferred with ADMIXTOOLS v5.154 and standard errors (SE) were computed with the block-Jackknife procedure using default options and Z-scores calculated on the SE. We tested for all the possible combinations of trees from the WHOLE dataset, producing a total of 6,900 triplets for thef3 test and 37,950 possible tree topologies for the f4 test. Afterwards, we checked all the results and retained only the most significant ones (− 20 < Z-score >  + 20). Thus, we focused only on the NW-EU target breeds, screening the results that had a minimum of − 4 < Z-score >  + 4 .To assess reticulate relationships between the study breeds, the matrix of Reynolds’ unweighted distances previously calculated was used to infer and visualise the Neighbor-Net via the software SplitsTree54, which allows the inference of the admixture proportions without access to accurate surrogates for the ancestral populations. The proportion of ancestry was computed as:To confirm the signal of gene flow found with the above mentioned methods, we applied f4-ratio estimation α, in ADMIXTOOLS v5.155 using the default parameters with a minimum genetic distance pre-calculated by the program and the 'maxchrom' parameter (set to 22 by default) that enables to use more than 22 chromosomes (maxchrom = 29). ALDER uses genotype data from a test population C and two reference populations A and B and computes unbiased weighted linkage disequilibrium (LD) statistic for making inference about admixture events in the target population C. If population C is derived from an admixture between two source populations close to the reference populations A and B, the pairwise LD of the three curves computed with A-B, A-C, and B-C weights should all exhibit a statistically significant signal of exponential decay as a function of the genetic distance. Thus, ALDER compares the three weighted LD curves to test for admixture and infers the decay rates that correspond to age of admixture. The p-value is also provided in the output from standard errors estimated by jackknifing over chromosomes. We performed the analysis on the basis of the results of the statistics described above  and joining the historical information with the most recent human genetic studies about Scandinavian and Celtic people31.The time of admixture was estimated with ALDER v.1.05Supplementary Figures.Supplementary Figure 3.Supplementary Figure 4.Supplementary Figure 5.Supplementary Figure 5.Supplementary Figure 6.Supplementary Table S1.Supplementary Table S2.Supplementary Table S3.Supplementary Table S4.Supplementary Table S5.Supplementary Table S6.Supplementary Table S6.Supplementary Table S7.Supplementary Table S8.


Bufo japonicus, is distributed on the main islands of Japan. In the present study, we applied multiplexed inter-simple sequence repeat genotyping by sequencing to achieve the fine-scale resolution of the genetic cluster in B. j. japonicus and B. j. formosus. We also elucidated hybridization patterns and gene flow degrees across contact zones between the clusters identified. Using SNP data, we found four genetic clusters in B. j. japonicus and B. j. formosus and three contact zones of the cluster pairs among these four clusters. The two oldest diverged lineages, B. j. japonicus and B. j. formosus, formed a narrow contact zone consistent with species distinctiveness. Therefore, we recommend that these two subspecies be elevated to the species level. In contrast, the less diverged pairs of two clusters in B. j. japonicus and B. j. formosus, respectively, admixed over a hundred kilometers, suggesting that they have not yet developed strong reproductive isolation and need to be treated as conspecifics. These results will contribute to resolving taxonomic confusion in Japanese toads.Hybridization following secondary contact may produce different outcomes depending on the extent to which genetic diversity and reproductive barriers have accumulated during isolation. The Japanese toad,  Hybrid zones are natural laboratories that offer many insights into speciation processes, thereby contributing to a more detailed understanding of evolution . HybridiBombina bombina and B. variegata; e.g., Bufotes viridis subgroups; e.g., Bufo bufo and B. spinosus; e.g., Bufo japonicus subspecies; Hybridization is frequent and evolutionarily significant in amphibians . There aBufo japonicus Temminck and Schlegel, 1838 is widely distributed in the Japanese archipelago, Honshu, Shikoku, Kyushu, and some adjacent islands. This species is divided into two subspecies, B. j. japonicus from western Japan and B. j. formosusB. j. japonicus and B. j. formosus showed a climatic cline in their morphometric characteristics, which was insufficient to distinguish them as different species because of their identity in the fundamental patterns of modes of life. However, B. j. japonicus and B. j. formosus to the species level based on the Miocene split estimated by mtDNA markers. However, they refrained from taxonomic changes because mitochondrial distances may not reflect actual species distances. Other studies proposed the Kinki region as a hybrid zone of B. j. japonicus and B. j. formosus by a C-banding analysis of chromosomes  with the Qiagen DNeasy Blood and Tissue Kit following the manufacturer’s instructions.A total of 155 individuals of on range . The AniB. japonicus and 13 of B. torrenticola, while library 2 had 40 DNA samples of B. japonicus, with six of B. japonicus overlapping in both libraries .The raw sequence reads of MIG-seq data were deposited in the DNA Data Bank of Japan (DDBJ) Sequence Read Archive (DRA) under accession number de novo analysis of MIG-seq data . The assembly contained 11 chromosome-level contigs and unplaced scaffolds. We ultimately mapped the filtered reads to the indexed reference sequences by bwa-mem2 version 2.2.1 (samtools version 1.15 (Raw paired-end sequences (reads 1 and 2) were filtered by fastp version 0.23.2  to trim seq data . As the on 2.2.1  to make ion 1.15 .B. japonicus and B. torrenticola to examine the genetic structure of Japanese toads, and dataset II, data from samples of B. j. japonicus and B. j. formosus to investigate the degree of reproductive isolation between the two subspecies. We excluded the 11 samples from these two datasets that were considered to be from artificially introduced populations based on a previous study  to ensure that an allele was in at least two diploid samples  at the optimal number of clusters (K) = 2 in the Structure analysis (see below: r = 0.80) and those present in two populations for all datasets (-p = 2). In the following stacks program, the two parameters, -r and -p, varied, and the others were common for each analysis.The reference-based analysis pipeline with the ks v2.60  was appl samples . We then samples . Subsequ samples . In the B. japonicus and B. torrenticola, we performed three different methods using SNP genotyping information and compared grouping among these methods: a discriminate analysis of principal components  method. This de novo clustering method and initial DAPC using the dapc function were run. The optim.a.score was then used to assess the optimal number of principal components (PCs) to retain. Once the optimal number of PCs was selected, a second DAPC analysis was conducted using this value.DAPC was performed on dataset I in the R package et 2.1.8 . This meK from 1 to 8, with ten runs for each K value. Markov chain Monte Carlo . We ran SNAPP for 10,000,000 iterations with mutation rates u and v = 1.0, a gamma distribution with alpha = 2 and beta = 200 for the lambda prior, and alpha = 1, beta = 250, kappa = 1, and lambda = 10 for snapprior, sampling every 1,000 steps. Convergence was examined using Tracer 1.7.2  with -r = 0.80 and -p = 3, and conducted a Structure analysis. The q-values on K = 2 for each sub-dataset were used to perform hzar. In addition to the three sub-datasets, we prepared sub-dataset III-2, which is data excluding samples in Shikoku and Seto Inland Sea (see discussion) and performed a similar analysis to that for the other sub-datasets.We performed the stacks program on this subset, setting four populations based on the results of DAPC on dataset II, with -tess3r version 1.1  into a single-dimensional distance from the center line of the hybrid zone. The probable center line of the admixture was estimated using R package sion 1.1 , 2018 anThe shape of a cline is modeled by combining three equations , 1991 thMCMC was performed for each model with the default values of 100,000 generations, each with a randomly selected seed and 10% of steps discarded as a burn-in. After each run, we compared the model performance using the Akaike information criterion score corrected for a small sample size AICc; . The modq-values > 0.98 for K = 2 in the Structure analysis of sub-datasets I, II, and III as parental individuals for each cluster following FST for SNPs between pairs of parental clusters using the stacks program on the sub-datasets, setting three populations  and -r = 0.80 and -p = 3. The diagnostic loci, FST = 1, were selected as ancestry-informative markers segregating between each pair of parental clusters.We assigned individuals in each contact zone to hybrid classes to estimate whether gene flow is an ongoing or historic admixture. We temporarily designated individuals with FST =1 were used. First-generation hybrids (F1) have an expected hybrid index of 0.5 and heterozygosity of 1.0. We regarded individuals with intermediate hybrid indices (>0.25 and <0.75) and high heterozygosity (≥0.5) as recent-generation hybrids, those with intermediate hybrid indices (>0.25 and <0.75) and low heterozygosity (<0.5) as later-generation hybrids, and those with low hybrid indices (≤0.25 or ≥0.75) as backcrossed to one or the other parental type according to previous studies  for the initial DAPC on dataset I. After running the initial steps, the first 21 PCs were retained following the result of the function . The BIC 4 and 5 , and botclusters .K estimation, K = 2 and 5 , southern B. j. formosus (SF), eastern B. j. japonicus (EJ), western B. j. japonicus (WJ), and B. torrenticola. Cluster assignments for individuals by DAPC are shown in Therefore, the DAPC . The fivB. torrenticola has rare admixtures with B. japonicus, three samples of B. torrenticola had q-values from 0.85 to 0.9, and one sample .The Structure bar plot revealed that B. japonicus  recovered the splits of the main clades confirmed in Based on SNAPP (290 SNPs), nuclear phylogeny confirmed deep splits between the five main clades . MitochoB. japonicus, including the 11 samples from the artificially introduced populations in Hokkaido, Izu Islands, and the Kanto region. Two individuals in Hokkaido (Asahikawa and Hakodate) had an admixture, mainly two clusters of NF and SF, similar to those in Niijima and Kouzushima  did not significantly differ from that of Structure analyses by SNP data. The baselines across the three contact zones are shown in hzar with the lowest AICc was that in which scaling was fixed to the minimum value of 0 and maximum value of 1, and no exponential tails were desired. In sub-datasets NF–SF and EJ–WJ and the mtDNA data of SF–EJ and NF–SF, the model selected was that in which scaling was fixed to the minimum and maximum observed mean values, and no exponential tails were desired.Each sub-dataset consisted of cluster pairs, sub-dataset I (NF–SF) of 47 samples, sub-dataset II (SF–EJ) of 47 samples, sub-dataset III (EJ–WJ) of 59 samples, and sub-dataset III-2 (EJ–WJ excluding samples in Shikoku and Seto Inland Sea) of 48 samples. The geographic distribution of each cluster detected by Based on SNP data, the cline width decreased from NF–SF 170 (CI [82–362]) km to EJ–WJ 162 (CI [63–330]) km and SF–EJ 29 (CI [24–76]) km . The estBased on mtDNA data, the cline width decreased from NF–SF 86 (CI [35–223]) km to EJ–WJ 75 (CI [31–212]) km and SF–EJ 39 (CI [18–106]) km . The estIn addition, in the sub-dataset EJ–WJ excluding samples in Shikoku and Seto Inland Sea (48 samples), the model selected for SNP and mtDNA data was that in which scaling was fixed to the minimum and maximum observed mean values, and no exponential tails were desired. Based on SNP data, the width was 99 (CI [33–301]) km and the distance from the baseline was −1.2 (CI −38 to 53) km. Based on mtDNA data, the width was 79 (CI [32–245]) km and the distance from the baseline was −33 (CI [−76 to −2.0]) km .FST > 1.0 between parental SF and EJ, and six loci for the NF and SF pair and EJ and WJ pair. Comparisons of individual hybrid indices and average heterozygosity using these differentiated loci revealed that none of the pairs contained F1 individuals , allele frequencies (-a), and inbreeding coefficients (-f) were selected using BA3-SNPs-autotune for each sub-dataset: sub-dataset NF–SF, -m = 0.2125, -a = 0.55, -f = 0.1; sub-dataset SF–EJ, -m = 0.2125,-a = 0.55, -f = 0.1281; sub-dataset EJ–WJ, -m = 0.1563, -a = 0.325, -f = 0.1.The mixing parameters for migration rates . In contrast, migration rates into hybrid populations were high .In the sub-dataset EJ–WJ, the self-recruitment of both parental populations was high at >95%, while that of the hybrid population was intermediate at 80.1%. The estimations of migration rates from hybrids into both parental populations were low . In contrast, migration rates into hybrid populations were high . The migration rates among each parental population were estimated to be very low, ranging between 1.3 and 2.6%.B. j. japonicus and B. j. formosus, were recommended for elevation to the species level given their Miocene split. However, the findings of these studies were insufficient for the taxonomic conclusion because they were based solely on mitochondrial analyses  in the northwest of France even with the absence of barriers to dispersal . In addition, whether these samples were included in library 1 or 2 and included in each dataset and sub-dataset for analyses (×: sub-selected for dataset and sub-dataset).Origin of samples analyzed in this study, including information on vouchers , GenBank accession numbers for mtDNA, mtDNA clade/species, DDBJ accession number for SNPs, and cluster estimated by DAPC (Click here for additional data file.


Neolamarckia cadamba (Roxb.) Bosser is a fast-growing deciduous tree species and belongs to the Neolamarckia genus of the Rubiaceae family. This species has great economic and medical values in addition to being an important timber species for multiple industrial purposes. However, few studies have examined the genetic diversity and population structure in the natural distribution of this species in China. Here, we applied both the haploid nrDNA ITS  and mtDNA (2 polymorphic loci) markers to investigate 10 natural populations  that covered most of the distribution of the species in China. The results showed that the nucleotide diversity was  N. cadamba (2n = 44) is an evergreen deciduous and fast-growing tree species and belongs to the Neolamarckia genus of the Rubiaceae family [N. cadamba can grow to 40–45 m in height and 100–160 cm in diameter [e family ,2. This e family ,2. N. cadiameter ,4. It isdiameter , for necdiameter ,9. In addiameter ,12,13,14diameter ,16.N. cadamba covered wide aspects. Provenance trials in China were conducted to assess the genetic variation among provenances in height, DBH (the diameter at the breast height), and wood volume [Recent studies on genetic variation and breeding of d volume ,16,17. Ad volume  to estimd volume ,20, trand volume ,22, exprd volume , gene did volume , the evod volume , and pold volume . A previd volume . The resd volume  reportedd volume  reportedN. cadamba is an anemophilous plant, pollen grains may be dispersed to long distances. Seeds are potentially locally distributed around mother trees due to gravity effects or dispersal by animals [The ecological and evolutionary processes underlying the present population structure have not been examined as well. Although we could exclude the impacts of interspecific processes, such as incomplete lineage sorting and introgression/hybridization, other processes, such as seed/pollen flow and local adaptation, were likely involved in shaping population structure. Previous provenance trials showed that significant population differentiation occurred in growth traits , suggest animals . Thus, wN. cadamba in China. Gene flow between populations could be inferred from the genetic structure analysis using molecular markers. For the nuclear genomes, we used the nuclear ribosomal internal transcribed spacer (nrDNA ITS) markers, which were frequently applied to studying phylogeography and population structure of both plant and animal species. For the organelle genomes, we used mitochondrial DNA (mtDNA) markers based on our previous sequencing of mitochondrial genomes of a few individuals where polymorphic loci were observed in some samples [Using nuclear and organelle markers, we investigated population genetic structure and genetic diversity in the natural distribution of  samples . However samples . Therefo samples ,32. In aN. cadamba in China. All sampling sites except for Baoshan were located at elevations below 1000 m. Trees were separated at least 50 m away in natural forest stands. A total of 239 individuals were analyzed in this study, with the sample size ranging from 15 to 32 among populations. DNA samples were extracted from silica-gel-dried leaves by following the CTAB 2X protocol [w/v) agarose gel electrophoresis. All quantified DNA samples were stored at −20 °C for polymerase chain reaction (PCR) amplification.Leaf samples were collected from ten natural populations , includiprotocol . The quaN. cadamba [For the mitochondrial genomes, we tried 11 pairs of primers that were selected from the relevant literature , but the cadamba , which cFor the nrDNA ITS markers, the forward and reverse primers were TCCTCCGCTTA TTGATATGC and GGAAGGAGAAGT CGTAACAAGG, respectively.2O, and 12.5 μL of a mixed enzyme . The PCR amplification for nrDNA ITS and mtDNA primers is detailed below: (i) preheating at 95 °C for 4 min; (ii) annealing at a 50–65 °C temperature interval for 30 s ; (iii) extension at 72 °C for 1 min, and repetition of the cycle of denaturation–annealing–extension for 35 times; (iv) 72 °C final extension for 10 min to make PCR amplification products be fully extended; and, finally, 4 °C to stop the reaction program. Then, the PCR products were run on 2% agarose gel electrophoresis. The results of gel running were examined by a gel imager, and the amplification products with clear and single bands were sent to Shanghai Biotech Biological Co., Ltd.  for sequencing. The Sanger method was used for sequencing. We checked all sequence data obtained from the company using Chromatogram Explorer 3.2 software. The sequences with high quality and without mixed peak signals were used for downstream analyses.Each PCR amplification was conducted in a 25 μL reaction volume. The amplification volume included 1 μL of template DNA, 1.0 μL of each forward and reverse primer, 9.5 μL of ddHWe aligned the sequences of both nrDNA ITS and mtDNA markers from 10 populations with MEGA7  and remoDNAsp v5  was used markers ,37,38. Tide site . The para sample . TCS v1.a sample  was usedPopulation genetic structure was analyzed using DNAsp v5  and ArleGst , Fst [42Fst [Nst ,44, and Nst [ϕst . The thrthan Gst .Isolation by distance (IBD) was tested through the regression of istances ,(1)Fst1The geographical distance between two populations was calculated using their latitude and longitude coordinates . A signiPhylogenetic relationships among individuals of the ten populations were analyzed using MEGA 7 . The phyGene flow was assessed under the assumption of the classical island model . For matf pollen ,31. Fromf pollen , the relStandard deviation of the point estimate  as Xiao . The Jacand Fstn , which wD [F statistics [D was calculated as the normalized difference of D was not significant from zero. This was the same case in testing neutrality using Fu’s F statistics. Significant negative values of Tajima’s D and Fu’s F also implied that a population had expanded after bottleneck effects. To further infer population demographic changes, mismatch distribution was analyzed using the Arlequin v3.0 package [We tested the neutrality of the nrDNA ITS markers using Tajima’s D  and Fu’satistics . Tajima’ package . Under a package , respectThe segments produced by the two primer pairs were about 650 bp for the primer F1-R1 amplification and about 400 bp for the primer F2-R2 amplification. Sequence alignment analysis confirmed that both amplified segments were located on genome 2 (GenBank Access No. MT364442) of Wang et al. . We obtaFor the haploid nrDNA ITS markers, the PCR amplification size was about 750 bp. We obtained 239 samples of sequences for downstream analyses .For the mtDNA markers, a total of 4 haplotypes were identified among the 161 sequenced individuals . HaplotyFor the haploid nrDNA ITS markers, the nucleotide diversity ranged from ± 0.0242 . The effAnalysis of molecular variance (AMOVA) indicated significant genetic differentiation among populations for both mtDNA and nrDNA ITS markers . For theA comparison of p-value = 0.2934. For the haploid nrDNA ITS markers, analysis of the regression of p-value = 0.5232. This correlation was also tested by the Mantel test and was not significant . Mantel tests also showed insignificant correlations between p-value = 0.896), between p-value = 0.140), and between p-value = 0.336).K = 6, with the minimum cross-validation (CV) error  but positive in the remaining five populations   . All p-vp-value = 0.0000) and Harpending’s raggedness index (Rag) was 0.136 . Other estimates of parameters were p-value = 0.94), Rag = 0.027 , N. cadamba species potentially underwent a weak expansion in a few local regions but did not exhibit global expansion.Further analysis of mismatch distribution showed that a few local populations could expand after bottleneck effects. For instance, with population FS, the sum of squared deviation (SSD) was 0.093  [T. ciliata (1.3741 at the species level) [N. cadamba more heavily relies on pollen dispersal to shape population structure.The second explanation is related to the reproductive ecology of es range ,68. The = 13.67) , Dactylo4–12.01) , and T. s level) , N. cadaN. cadamba has been overharvested and, therefore, the natural population density is declining due to its narrow distribution in South China. Our results implicate that most local populations did not undergo demographic changes. Thus, on the evidence of small population differentiation, it would be appropriate to focus on a few populations in genetic conservation.Two implications could be gained from the findings of this study. One implication is concerned with genetic conservation since population structure provides fundamental information for managing genetic resources . AlthougThe second implication is concerned with breeding that is currently being conducted ,17. AlthN. cadamba is a fast-growing timber tree species in South China. The species, also known as a miraculous tree, is exploited as a medicinal plant in addition to its use for industrial purposes. Here, we used both the mtDNA and nrDNA ITS markers to investigate ten populations that covered most of the natural distribution of N. cadamba in South China. Genetic diversity for both types of markers was randomly distributed in space, without phylogeographic structure. The genetic diversity was high from the analysis of the nrDNA ITS markers but low from the analysis of the mtDNA markers. Population genetic variation was mainly distributed within populations for the nrDNA ITS markers but among populations for the mtDNA markers. Effects of isolation by distance were absent among populations. The phylogenetic analysis showed close genetic relationships among individuals of the ten populations or among populations. The relative rate of pollen to seed flow was much greater than one, implying that pollen flow played a dominant role in contributing to gene flow of N. cadamba. Populations had not experienced expansion events and the nrDNA ITS sequences were selectively neutral. The overall results provide fundamental information for genetic conservation and breeding of N. cadamba in South China.


Coreoperca herzi is a freshwater fish endemic to Korea. So far, studies on C. herzi have mainly focused on ecological studies, but studies on its genetic diversity are lacking. For the first time, we investigated genetic diversity and structure using mitochondrial DNA data in this study. The genetic diversity was found to be low. In addition, the translocated population, Yangyangnamdaecheon, was confirmed to have originated from the Han River water system population as a result of genetic similarity. This study provides information on the genetic diversity, genetic structure, and translocated populations of C. herzi, providing a basis for the conservation of the species.Coreoperca herzi, belongs to the family Centropomidae. Thus far, studies on C. herzi have focused on mitochondrial genomes, egg development, and early life history, while studies on their genetic diversity or genetic structure are lacking. We investigated these aspects in this study using mitochondrial DNA data. Haplotypes were divided into the Hangang River, Nakdonggang River, Geumgang River, and southwest region water system populations. A translocated population, the Yangyang Namdaechun Stream, was confirmed to have originated from the Hangang River water system population based on haplotype distribution and genetic structure results. The FST of the mitochondrial DNA indicated distinct genetic differentiation in the Hangang, Nakdonggang, Geumgang, and southwest regions. According to COI and analyses, the analysis of molecular variance revealed a higher variance in the four water system groups (98.41%) than in the southwest region water system versus the Hangang River water system (80.27%) groups. This study presents basic data for conservation by providing extensive information on the genetic diversity, genetic structure, and translocation population of C. herzi.The Korean endemic aucha perch,  Coreoperca herzi Herzenstein (1896), is endemic to Korea and belongs to the order Perciformes and the family Centropomidae [C. herzi is a crucial species for domestic aquaculture, and its seed production has also been studied [The Korean aucha perch, zenstein 896, is ezenstein 896, is e studied . However studied .C. herzi is a commercial fish of major value, and wild broodstock is used for aquaculture. However, the genetic diversity of the offspring is low due to the small number of mothers. This low genetic diversity in offspring can have negative effects during interbreeding with natural populations [C. herzi have been conducted on the mitochondrial genome, egg development, and early life history, but there have been no studies on genetic diversity or genetic structure [ulations ,4. Henceulations . These ptructure ,7,8,9.C. herzi are known to exhibit morphological differences in white spots between the Hangang River water system and other southwestern water systems, as well as variations in the morphological development of eggs [C. herzi have been manually translocated to the Yangyang Namdaecheon Stream (YYND) population, which belongs to the waters of Korea’s east coast [ of eggs . Further of eggs ,11. C. hst coast ,13. Detest coast .C. herzi populations, which are endemic to Korea, were investigated using mitochondrial DNA (COI) datasets. This study may help in understanding the genetics and evolution of C. herzi and provide a basis for C. herzi conservation.In this study, the genetic diversity and genetic structure of 19 C. herzi populations were sampled at 19 points in 2019 using fishing nets; detailed information is given in C. herzi is endemic to Korea, and research on it does not require permission for animal ethics. The pectoral fin tissues of the fish samples were preserved in 99% ethanol. Genomic DNA was extracted from the preserved tissue of all specimens using the DNeasy Blood & Tissue kit  according to the manufacturer’s instructions.® pro gene amplifier. For the PCR, AccuPower® PCR Premix Kit  was used, and 1 μL of genomic DNA, 1 μL of each 1.0 μM forward and reverse primer, and 17 μL of tertiary distilled water were added and mixed to a final volume of 20 μL. The PCR conditions were as follows: pre-denaturation at 95 °C for 2 min, denaturation at 94 °C for 30 s, annealing at 52 °C for 30 s, and extension at 72 °C 35 times, followed by a final extension at 72 °C for 10 min, and termination at 4 °C. The COI gene PCR products were sequenced using an ABI 3730xl DNA Analyzer .The primers for mtDNA  were selected from Ward et al. , and theThe mtDNA was examined via alignment using the ClustalW algorithm of the MEGA software ver. 11.0.1  based onThe mtDNA sets showed genetic diversity among the 19 populations . The numCOI gene region of the mtDNA. In total, 22 haplotypes and 84 polymorphic sites were identified. The H1 haplotype was found to be shared among the Hangang River watershed populations . H2–H12 haplotypes were shared only in the Hangang River water system population. H13–H15 were shared in the Nakdonggang River water system populations , whereas H16 was only present in the NYS. H17 was shared by the Geumgang River water system populations (GYN and GND), while H18 and H19 appeared only in the Geumgang River populations. H21 was shared by MJJ, SON, SSJ, and YJS, while H22 appeared only in the Seomjingang River population. The YYND population may have translocated from the Hangang River population by sharing the H1 haplotype with the Hangang River water system populations  showed low genetic differentiation, with YJS at 0.069–0.273 and MJJ at 0.026–0.725.The In the median-joining network, haplotypes were divided into four groups centered on H1, H14, H17, and H21 . The firWe constructed an mtDNA-based phylogenetic tree of the 19 populations using the maximum likelihood (ML) method with PhyML (Ver. 3.0 ) Figure. The phyC. herzi was performed based on the haplotype distribution (FcT = 0.803), and among populations within the groups, it was 18.72% (FSC = 0.949). In contrast, by dividing the groups based on haplotype distribution, the AMOVA showed a difference in variance, which among the groups was 98.41% (FcT = 0.984) and among the populations within groups was 0.42% (FSC = 0.264).The AMOVA of ribution . The mtDC. herzi mtDNA was lower than in that of Siniperca scherzeri  and Sin7–0.0031 ,24. C. hiversity ,26. The breeding .C. herzi and the origin of the translocated population were investigated. The mtDNA datasets showed significant genetic differences in the Hangang River water system populations  and the YYND vs. Geumgang River populations (GYD and GND) vs. MJJ, SON, SJJ, and YJS vs. the Nakdonggang River populations . The haplotype was divided into four groups, and since the translocation population (the YYND population) shared the H1 haplotype with the Hangang River populations, this implied that the YYND population originated from the Hangang River populations. AMOVA supported the genetic differentiation of the four groups based on haplotype distribution. The AMOVA outcome of the Hangang River and southwest region water system populations was 80.27% among the groups, but that of the four groups according to haplotype distribution was 98.41%, which was genetically distinct. In addition, the ML tree supported the genetic differentiation pattern divided into four groups, and it was identical to the AMOVA and haplotype distribution. C. herzi was described by Park et al. [C. herzi.In this study, the genetic structure of C. herzi translocation in the YYND region based on the results of the genetic differences and haplotype sharing. The Hangang River population is geographically close to YYND and is prone to translocation by humans. In addition, since it was released to reinforce fishery resources, the YYND population may have originated from the Hangang River populations of the releasing mother population. Hypotheses strongly suggest that the YYND population originated from the Hangang River water system.We describe the most likely scenario for C. herzi is not widely practiced, and wild populations are supplied primarily by fisheries. As a result, overfishing poses a threat to this species. They are currently released for the purpose of reinforcing fishery resources via aquaculture; however, owing to the lack of commercial systematic aquaculture technology, breeding, or genetic breeding systems, the individuals are obtained from wild individuals. Furthermore, threats such as human habitat destruction and overfishing are gradually reducing their population, which can lead to their extinction in the absence of active conservation efforts. In this study, the genetic diversity of C. herzi was lower than that of other freshwater fish and populations such as NNG and YYND. Given the genetic differences between populations, our analysis suggests that methods of population expansion via artificial breeding should be considered.The Korean aucha perch is a commercially important species and a potentially valuable fishery resource. However, the aquaculture of C. herzi.Conservation strategies should be planned according to the conservation management units. We found that in mtDNA, the Han River water population had a unique haplotype and genotype that was genetically distinct from that of the southwest water population. Hence, The Hangang River watershed population should be treated as a conservation unit separate from other southwestern watershed populations. However, the Geumgang River populations (GYD and GND) vs. MJJ, SON, SJJ, and YJS vs. the Nakdonggang River populations  should be managed by dividing the conservation units, because the southwestern water system is divided according to its unique genetic variation based on the mtDNA haplotype. Given that the translocated population (the YYND population) has been translocated to a previously uninhabited area, the negative ecological impact of the translocation should be assessed and considered for inclusion in a conservation management unit. Our results provide information on the genetic basis for the conservation of Coreoperca herzi, belongs to the family Centropomidae. Thus far, studies on C. herzi have focused on mitochondrial genomes, egg development, and early life history, while studies on their genetic diversity or genetic structure are lacking. We investigated these aspects in this study using mitochondrial DNA data. Haplotypes were divided into the Hangang River, Nakdonggang River, Geumgang River, and southwest region water system populations. A translocated population, the Yangyang Namdaechun Stream, was confirmed to have originated from the Hangang River water system population based on the haplotype distribution, genetic structure, and scenario results. According to the COI analyses, the analysis of molecular variance revealed a higher variance in the four water system groups (98.41%) than in the southwest region water system versus the Hangang River water system (80.27%) groups. This study presented basic data for conservation by providing extensive information on the genetic diversity, genetic structure, and translocation population of C. herzi.The Korean endemic aucha perch,


Stipa breviflora. In total, 135 individual plants were sequenced and 25,786 polymorphic loci were obtained. We found low genetic diversity (He = 0.1284) within populations of S. breviflora. Four genetic clusters were identified along its distribution range. The Mantel test, partial Mantel test, and multiple matrix regression with randomization (MMRR) indicate that population differentiation was caused by both geographic distance and environmental factors. Through the STF outlier test and environmental association analysis (EAA), 113 candidate loci were identified as putatively adaptive loci. RPK2 and CPRF1, which are associated with meristem maintenance and light responsiveness, respectively, were annotated. To explore the effects of climatic factors on genetic differentiation and local adaptation of S. breviflora, gradient forest (GF) analysis was applied to 25,786 single nucleotide polymorphisms (SNPs) and 113 candidate loci, respectively. The results showed that both temperature and precipitation affected the genetic differentiation of S. breviflora, and precipitation was strongly related to local adaptation. Our study provides a theoretical basis for understanding the local adaptation of S. breviflora.Investigating the genetic mechanisms of local adaptation is critical to understanding how species adapt to heterogeneous environments. In the present study, we analyzed restriction site-associated DNA sequencing (RADseq) data in order to explore genetic diversity, genetic structure, genetic differentiation, and local adaptation of  FST ouutrality . Howeverutrality . Therefoositives .Stipa species, form the main type of vegetation  to the relatively warm and wet Loess Plateau. However, how this species adapts to these highly heterogeneous habitats, both geographically and ecologically, is still unknown. To uncover the genomic basis of genetic variation and local adaptation of S. breviflora, we sampled 135 individual plants belonging to 27 populations from its distribution area. We generated two datasets: all-SNP dataset that derived from the original RADseq, and the outlier dataset that derived from the all-SNP dataset and represents the loci under selection. We generated two datasets: all-SNP dataset that derived from the original RADseq, and the outlier dataset that derived from the all-SNP dataset and represents the loci under selection. Our study will provide information on the inter-relationship existing between heterogeneous environments and genetic variability, which will deepen our understanding of the local adaptation of S. breviflora.The distribution of 22.1Stipa breviflora is a wind-pollinated and selfing facultatively perennial grass  in accordance with the manufacturer’s protocol. Extracted DNA was quantified by NanoDrop 2000 UV–Vis spectrophotometers . Restriction site-associated DNA (RAD) libraries were prepared and sequenced for each DNA sample by Beijing Genomics Institute  using the restriction enzyme de novo loci, and to call the SNPs using the “denovo_map.pl” module with the following settings: minimum number of reads to create a stack, m = 2; maximum distance allowed between stacks, M = 2; maximum number of mismatches allowed between loci, n = 3; minimum number of populations a locus must be present in, p = 20; minimum percentage of individuals in a population required to process a locus for that population, r = 0.8; minimum minor allele frequency, min-maf = 0.05. In addition, data analysis was restricted to the first SNP per RAD locus, to reduce the impact of linkage disequilibrium (-write_single_snp). The filtered dataset  of 25,786 SNPs was exported in vcf format using the “-vcf” option.Standard quality control (QC) pipelines  were used to process the raw sequencing data. Raw reads from the same library were demultiplexed according to index barcodes and reads containing adaptors were removed. Reads with more than 40% low-quality bases (phred scores < 20) and reads with more than 10% “Ns” were discarded using SOAPnuke v1.5.6 . STACKS 2.3Ho), expected heterozygosity (He), and inbreeding coefficient (Fis) were calculated using the “populations” module in STACKS v1.48 (K ranging from 1 to 27 and repeated the process 10 times for each K (number of clusters) with different random seeds. The most probable number of clusters was inferred by the lowest cross-validation error. We also conducted PCA in plink v2.0 (STF) was computed using the R package “hierfstat” (Nucleotide diversity (π), observed heterozygosity  (ST/F(1 – STF). Mantel and partial Mantel tests were performed using the “vegan” package  were downloaded from WorldClim (lim.org) . PCA waslim.org) . Genetic package . Multipl package .2.5STF outlier test and EAA to detect outliers. Firstly, Bayescan v2.1  using the program BLASTN  database and Gene Ontology  database were used for BLAST search and annotation.We used both the can v2.1  was usedcan v2.1  was run can v2.1 . We set m BLASTN  with an 2.6https://r-forge.r-project.org/R/?group_id=973). R packages “raster”  is a non-parametric, machine learning, regression tree approach that uses SNP allele frequencies (as response variables) and climatic data (as predictors) to identify environmental gradients that are associated with genetic variation and also to determine allele frequency turnover along that gradient. We applied gradient forest analysis to the all-SNP dataset and the outlier dataset, using gradientForest_0.1–18 . Population HN, located in the central part of the S. breviflora distribution region, showed the highest genetic diversity with the highest Ho (0.2180), He (0.1919), and π (0.1146). In contrast, the peripheral population, PL, exhibited the lowest level of genetic diversity, with an Ho of 0.0076 and He of 0.0068  were explained among individuals within populations. Variation between groups accounted for only 17.99% of the total variance (p < 0.001), and a higher percentage of variance  was attributed to the difference among populations within groups. We detected a large genetic differentiation between populations, with STF values ranging from 0.04 (BN vs. HG) to 0.36 (PL vs. HJ)  and isolation by environment (IBE)  in S. breviflora populations, which were also supported by a partial Mantel test  and MMRR  (S. breviflora populations. IBD explains slightly more of the variation in genetic differentiation than IBE.The Mantel test detected significant patterns in both isolation by distance (IBD) , which regulates plant growth , demonstrating the considerable heterogeneity of precipitation in the study region. However, temperature factors appeared to be more highly associated with genetic differentiation for the all-SNP dataset, with bio2 , bio3 , and bio1  ranking second, third, and fourth in R2 weighted importance, respectively  using RAD sequencing data (He = 0.34) and He = 0.52), which were based on simple-sequence repeat (SSR) markers. A similar phenomenon occurs in the study of maize germplasm   . This rectively) . SNP marctively) . In addis henryi , Eupteleiosperma , and Tax. mairei .S. breviflora  spikelet in other populations. We speculated that the distinctive purple spikelet is an adaptive trait that enables the species to survive in a harsh environment with strong solar radiation in the QTP. Both IBD and IBE played important roles in triggering genetic differentiation in S. breviflora , isothermality (bio3), and annual mean temperature (bio1) were also noticeable, as S. breviflora populations is consistent with the results of a previous study by Stipa breviflora is mainly distributed in temperate eastern Asia, where there are temporal and spatial variations in rainfall, confined mainly to summer  was detected as the most important climatic variable in the two datasets  gene expression, which is responsible for light responsiveness  of NGDC  repository, accession number CRA007694.JN contributed to the conception and design of the study. JN, DY, JL, YF, and ZL contributed to the investigation of the study. ZD, DY, and JL performed the statistical analysis. DY and JL performed the visualization of the study. DY wrote the original draft of the manuscript. JN revised and edited the manuscript. All authors contributed to the article and approved the submitted version.


The analysis of mitochondrial DNA (mtDNA) hypervariable region (HVR) sequence data from ancient human remains provides valuable insights into the genetic structure and population dynamics of ancient populations. mtDNA is particularly useful in studying ancient populations, because it is maternally inherited and has a higher mutation rate compared to nuclear DNA. To determine the genetic structure of three Colombian pre-Hispanic populations and compare them with current populations, we determined the haplotypes from human bone remains by sequencing several mitochondrial DNA segments. A wide variety of mitochondrial polymorphisms were obtained from 33 samples. Our results support a high population heterogeneity among pre-Hispanic populations in Colombia. The archaeological research conducted in Colombia has unveiled a history of habitation dating back to around 10,000 BP . This tiRecent archaeological discoveries propose three prehistoric periods in Colombia: the agro-potter period spanning from 500 to 900 BP ±100 years), the formative period from 1400 to 2800 BP (±200 years), and the Paleoamerican period extending from 5000 to 8000 BP (±2000 years) ,7,8,9,100 years, Ancient DNA extraction and analysis from remains recovered at indigenous archaeological sites have emerged as vital tools for comprehending the origins of Colombia’s population. These endeavors strive to unravel the genetic makeup of pre-Columbian communities and, based on this genetic structure, elucidate genetic connections between these populations  and the contemporary Colombian populace ,12. AddiThe unearthing of pre-Hispanic remnants within Colombia’s contemporary landscape unveils precious windows into the civilizations of antiquity that once thrived in the area. These archaeological revelations, encompassing not only human remains but also artifacts and architectural remnants, provide fascinating glimpses into the cultural traditions, societal structures, and pronounced genetic diversity of these ancient communities ,17,18,19This study’s primary objective rested upon delineating the genetic makeup of three distinct pre-Hispanic population clusters in Colombia: the Bolo Temprano, Lache, and Aburrae groups. The overarching aim was to foster a deeper comprehension of the intricate phylogenetic interrelationships among these individuals. This exploration, in turn, offers a repository of molecular insights with the potential to illuminate the genetic essence of the pre-Columbian societies that once inhabited modern Colombian territories. Furthermore, it aims to illuminate the intricate genetic ties between these historic Native American population cohorts and the contemporary populace.This study encompassed a total of 33 samples extracted from ancient remains associated with three distinct pre-Columbian indigenous groups [800–1600 AP]. Among these samples, six were sourced from the Lache community, recovered from sites within the Boyacá department’s Jericho region. Additionally, 10 samples originated from the Aburráe group, derived from individuals discovered in various locations within the Antioquia department, including Cerro del Volador (one sample), Cerro de la Colinita (one sample), Medellín, and the Alto de las Flores area . Lastly, 17 samples were linked to the Bolo Temprano population, originating from archaeological sites within the Valle del Cauca department .To facilitate the analysis of these specimens, a human genetics laboratory was established at the Center for Biomedical Research, Universidad de la Sabana, Chía, Colombia, strictly adhering to the guidelines proposed by Hummel  to preveThe sample decontamination and treatment followed the procedures outlined by Casas-Vargas et al. , utiliziThe determination of mitochondrial haplotypes centered on amplifying a 388 bp fragment from the hypervariable region I  of human mtDNA, referencing the Cambridge Reference Sequence (rCRS) . This am® MaxyGene™ THERM-1000 cycler, manufactured by Axygen , and housed at the Medical Research Science Center within the Faculty of Medicine at the University La Sabana in Chia, Colombia. The cycling conditions comprised an initial temperature of 95 °C for 8 min, followed by 40 cycles of 94 °C, 59.6 °C, and 72 °C for 1 min each. The amplified PCR products were validated through 2% agarose gel electrophoresis. Optimal bands were subjected to re-amplification in a final volume of 50 μL using the same conditions mentioned above. As part of the authenticity criteria, negative controls were included for DNA extraction and PCR  and T16362C], these particular variants were not present in the eight individuals examined in the current study. Instead, all individuals in this study share variation [C16290T], which has been previously associated with haplogroup A. Notably, haplotype A2 demonstrates a widespread distribution across North America and is linked with a Native American haplogroup that is particularly prevalent in the northern latitudes of the continent . This di2C, theseThis affirmation finds validation in a mitogenomic analysis conducted by Achilli et al. . Their sWithin the confines of haplogroup A2, distinct subhaplogroups have emerged, namely A2ab [C16291T], A2ad1 [A16175G], A2af1b1b [C16168T], A2ah [A16098G], and A2i [T16325C]. The A2ab subhaplogroup has been identified in contemporary Native American populations residing in the United States . SimilarRegarding haplogroup B2, its phylogenetic structure delineates six documented subhaplogroups: B2a, defined by [16111T] transitions ; B2s, chThe B2a haplotype has been observed among various population groups in Mexico, southwest Honolulu, and the United States, as well as the Nuxálk, Apache, Navajo, and Tsimshian peoples . AchilliLimited information exists regarding the population of the B2g1 subhaplogroup. According to the EMPOP database, this variant has been identified in 20 individuals typified in Mexico and San Diego. In contrast, the B4j subhaplogroup has not been documented in other populations. In Asia, the monophyletic nature of the B4 haplogroup has been consistently debated. The ancestral branch, B4a1c haplogroup, originated in East Asia 15,000 years ago , with thConfirming the presence of the B4c1a1a haplogroup presents a more intricate challenge. With no reports in the Americas and sparse occurrences in Asia and Japan, Tanaka et al.  were unaThe C1 haplogroup is widespread among current American populations , suggestLastly, the C1b5b haplogroup has been documented in seven individuals from the central region of South America, while C1C4 appears in 29 subjects from El Salvador. The D4h3a clade predominantly inhabits South America and, according to Perego et al. , it reprDrawing from the phylogeny proposed by Derenko et al. , D4h3a oThe analysis of the three studied population groups reveals a strikingly elevated level of genetic diversity compared to the contemporary populations residing in Colombia ,68. WhatThis wealth of genetic diversity is not just a matter of academic curiosity; it opens up intriguing avenues of inquiry into the complex history of human populations in this region. It prompts questions about migration patterns, interactions between different groups, and the dynamic interplay between human communities and their environment.It is important to delve deeper into the implications of this diversity. One plausible hypothesis is that Colombia, with its diverse landscapes, may have acted as a meeting point for various population groups over time. This could be attributed to its geographical location, which bridges different regions and environments within the Americas.The concept of Colombia as a hub for cultural interactions underscores the significance of this region as a melting pot of diverse traditions, languages, and lifestyles. It becomes evident that the rich tapestry of human experiences and interactions in Colombia has deep historical roots .From a biological perspective, the elevated genetic diversity observed suggests a long history of human presence in the area, marked by migrations, adaptations, and the mixing of distinct genetic lineages. This scenario paints a picture of a region where different groups have continuously crossed paths, leading to genetic intermingling and the emergence of unique genetic profiles .When we examine the mitochondrial DNA (mtDNA) haplotypes found in ancient remains from present-day Colombia, we are presented with invaluable evidence that can serve as a cornerstone for constructing hypotheses about the populations that once inhabited Colombian territories. One conceivable scenario is that Amerindians, the indigenous peoples of the Americas, trace their origins back to a relatively small group that embarked on a momentous migration from Northeast Asia into the Americas, as well as adjacent regions in Western Asia. This initial migration would have marked a pivotal moment in human history, as it laid the foundation for the peopling of the entire American continent. ,73,74However, the story does not end with this initial migration. It is likely that, over time, the descendants of these early migrants underwent a process of fragmentation into smaller, distinct entities. These smaller groups likely dispersed across the vast expanse of the American continent. This phenomenon of fragmentation and dispersion among these groups is a recognized genetic process known as “genetic drift”.Genetic drift can be likened to the branching of a tree, where each branch represents a separate population group. As these groups became geographically isolated from one another, they could have developed unique genetic characteristics. Over generations, these characteristics manifested as the variety of mtDNA haplotypes that we observe within each population.Following the arrival of European colonizers in the Americas, a tumultuous period unfolded, marked by a series of impactful events including wars, the enslavement of indigenous peoples, devastating epidemics, the mixing of different ethnic groups, and various other factors. This complex historical context likely had profound consequences on the indigenous communities in the Americas ,76.One of the key outcomes of this tumultuous era was the isolation and population decline experienced by many of these indigenous communities. The upheaval caused by European colonization disrupted established ways of life, led to the loss of traditional territories, and resulted in significant population losses due to violence, disease, and forced labor.Geographical distances and natural barriers, such as mountain ranges, dense forests, and vast rivers, further compounded the isolation of different American populations. These geographical features not only hindered physical movement but also limited gene flow between isolated groups. As a result, genetic drift, the process through which genetic characteristics change in isolated populations over time, became increasingly pronounced.The cumulative effects of these historical factors can help elucidate the remarkable inter-population diversity observed in the mtDNA haplotypes examined in this study. When we contrast this diversity with the relative genetic consistency found in the maternal line of modern-day Colombian inhabitants, it becomes evident that the genetic legacy of these historic events is still discernible today.The swift accumulation of molecular data gathered from various American populations has substantially expanded their utility in testing alternative theories related to the colonization of the Americas. This wealth of genetic information has become a valuable resource for researchers seeking to unravel the complex history of the first settlers in the Americas.Furthermore, the integration of genetic data into insights from other disciplines, such as archaeology and paleo-environmental studies, has yielded a more comprehensive and multi-dimensional understanding of the initial colonization of the Americas. These interdisciplinary assessment studies have played a pivotal role in corroborating and refining existing theories, while shedding light on the emergence of distinct Paleoamerican groups.Through aligning genetic data with archaeological findings, researchers have been able to construct more accurate narratives of the past. For example, the genetic evidence can complement archaeological discoveries by providing insights into the movements, interactions, and genetic relationships among ancient populations.Similarly, the incorporation of paleo-environmental data, such as climate records and vegetation patterns, can help contextualize genetic findings. Changes in the environment over time can influence human migration patterns and adaptation strategies, and genetic data can corroborate or challenge hypotheses regarding how these factors interplayed.Through these collaborative efforts across scientific disciplines, our comprehension of the peopling of the Americas has become richer and more nuanced. It has not only reaffirmed the significance of ancient American populations, but has also revealed the intricate tapestry of human history, showcasing the diverse groups and cultures that thrived across the continent millennia ago.In light of recent research, there is growing support for the hypothesis that these ancient populations might have followed a migration route along the Pacific coast as they entered the Americas ,77,78. TThe idea of a coastal migration is particularly intriguing because it has the potential to shed new light on the genetic profiles of American populations, specifically in terms of human leukocyte antigen (HLA) diversity. Coastal environments offer unique ecological niches and resources that may have influenced the genetic makeup of the populations inhabiting these regions. Consequently, the genetic diversity observed in contemporary American populations, including the diversity in HLA genes related to immune responses, could be partially attributed to the selective pressures and environmental adaptations associated with coastal living .Moreover, it is important to entertain the concept of reverse migration from America to Asia at various points in history. While the prevailing narrative often focuses on migrations from Asia to the Americas, genetic evidence should also prompt us to consider the possibility of human populations moving in the opposite direction. Such reverse migrations, if supported by further research, could have implications for our understanding of the complex interactions and exchanges that occurred between the two continents over millennia ,83,84,85Indeed, while the findings from studies in population genetics provide substantial support for the hypotheses discussed, reconstructing the history of these populations requires a multidisciplinary approach that spans various fields of study with a shared goal. To gain a more precise and comprehensive understanding of the complex history of these ancient populations, it is imperative to integrate data into insights from genetics, archaeology, anthropology, and other relevant disciplines.One crucial aspect of this interdisciplinary endeavor is the detailed examination of individual haplotypes. These genetic markers can yield nuanced information about the genetic diversity, migration patterns, and relationships within and between ancient populations. By scrutinizing individual haplotypes, researchers can discern specific genetic signatures, trace migration routes, and decipher the genetic impact of various historical events.Furthermore, establishing correlations between these haplotypes is equally vital. These correlations enable researchers to compare different hypotheses or models that have been proposed to explain the origins, migrations, and interactions of these ancient populations. By identifying consistent patterns or deviations across populations, researchers can refine their theories and construct more accurate historical narratives.However, it is essential to acknowledge that, before meaningful comparisons can be made, a critical reevaluation of previously reported South American variants is necessary. This process involves revisiting and reanalyzing existing genetic data, ensuring their accuracy, and considering how they align with the new findings. Such a comprehensive review of the existing genetic record is fundamental to building a more robust foundation for the interdisciplinary study of these ancient populations and their remarkable history.A potentially more accurate approach has been presented by Stoneking and Krause , who conFollowing the extraction and analysis of DNA from the 33 samples sourced from ancient remains dating back to 800–1600 AP and found in the departments of Boyacá, Antioquia, and Valle del Cauca, a remarkable genetic diversity and the identification of four distinct American population haplogroups were achieved. These discoveries are poised to significantly contribute to the discourse surrounding the origins of the earliest American peoples.The prevailing heterogeneity within the A, B, C, and D haplotypes, which has been observed across contemporary populations throughout the continent, underscores the presence of the C1 and D4h3a variants. These variants lend credence to the hypothesis proposing a rapid colonization of the Pacific coast.Haplotypes affiliated with haplogroup B4 suggest an ancestral maternal lineage linked to West Asia among ancient American populations. However, for a comprehensive understanding of haplotypes and haplogroups, it is essential to augment genetic relationship databases with more data and reassess polymorphisms identified in prior studies. This will facilitate the identification of more direct links between human groups from diverse regions based on their ancient DNA. This endeavor holds potential significance, particularly for groups that may belong to distinct cultures originating from various corners of the world.


Spodoptera frugiperda, is a significant pest of many crops in the world and it is native to the Americas, where the species has shown the ability to rapidly evolve resistance to insecticides and transgenic plants. Despite the importance of this species, there is a gap in the knowledge regarding the genetic structure of FAW in South America. Here, we examined the genetic diversity of FAW populations across a wide agricultural area of Brazil and Argentina using a Genotyping-by-Sequencing (GBS) approach. We also characterized samples by their host strain based on mitochondrial and Z-linked genetic markers. The GBS methodology enabled us to discover 3309 SNPs, including neutral and outlier markers. Data showed significant genetic structure between Brazil and Argentina populations, and also among the Argentinian ecoregions. Populations inside Brazil showed little genetic differentiation indicating high gene flow among locations and confirming that structure is related to the presence of corn and rice strains. Outlier analysis indicated 456 loci putatively under selection, including genes possibly related to resistance evolution. This study provides clarification of the population genetic structure of FAW in South America and highlights the importance of genomic research to understand the risks of spread of resistance genes.The fall armyworm (FAW),  Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), is a major agricultural pest that can feed on several different hosts [The fall armyworm (FAW), nt hosts . FAW havnt hosts . The sprIn North America, FAW populations from Texas and Florida make annual migrations northwards to recolonize areas in the north of USA and Canada . This beA complicating factor for FAW is that the species can be subdivided into two groups called host strains that differ in their distribution on plant hosts in the field, with the C-strain preferentially found in corn and the R-strain in pasture grasses and, to a lesser extent, rice , 8. The At this time, the most consistent evidence of population structure in South America is that indicative of the two host strains, although some level of genetic structure has been observed for populations within Paraguay and within Brazil –13. OverFall armyworm caterpillars were manually collected in fields from 12 locations in Brazil under the SISBIO license number 58435, and from 3 locations of Argentina, between June of 2018 and January of 2021 , Table 1https://qgis.org/en/site/. Accessed on February 26th, 2023). Publicly available shapefile of South American country boundaries was downloaded from IBGE-Mapas .Distribution map of the populations was drawn using the software QGIS v3.28.3-Firenze. . The COI sequences were used to confirm species identification as well. Sequences were aligned with Clustal W [For the 228 specimens whose reads were successfully retained after GBS processing, we did polymerase chain reaction (PCR) amplifications of the COI and TpiEI4 regions to characterize host strains based on diagnostic polymorphisms at mCOI1164, mCOI1287 and gTpi183 positions using the same primer sequences and procedures as described elsewhere [lustal W . The genNsiI-MseI . The barcoded NsiI adapters and a common MseI adapter were ligated to the digested DNA of each sample. Barcoded DNA fragments from all samples were pooled in a single tube and amplified by PCR. The libraries were single-end sequenced to 150 nucleotides on a single lane using the Illumina NextSeq500/550 sequencing kit v2  at the Genome Investigation and Analysis Laboratory of University of São Paulo.The steps of the GBS library preparation were done according to methodology described elsewhere  with theprocess-radtags in STACKS v.1.42 [Spodoptera frugiperda genome ZJU_Sfru_1.0, under Bioproject PRJNA590312 [http://broadinstitute.github.io/picard). We identified SNPs using freebayes 1.3.4 [2 threshold of 0.6. Results were stored in variant call format (VCF) after an additional filter to remove six samples with more than 25% of missing data, and SNPs identified at sexual chromosome W present only in females, mitochondrial genome or in unanchored contigs of the reference genome.Sequencing quality of GBS libraries was evaluated using FastQC . The 3’eS v.1.42 . Reads cNA590312 , using tNA590312 . AlignmeNA590312  and Picaes 1.3.4  with --ses 1.3.4  and BCFtes 1.3.4 . We retaO, expected heterozygosity HE, nucleotide diversity π, the inbreeding coefficients (FIS), and the pairwise Fixation Index (FST) using hierfstat package [IS using confidence intervals calculated based on 1000 bootstrap resamples. FST relations were illustrated by heatmaps generated by the RColorBrewer R package. Genetic structure was additionally explored through the principal component analysis (PCA) and the discriminant analysis of principal components (DAPC) using ade4 [adegenet [Genetic diversity was estimated by calculating the observed heterozygosity H package , 27. We ing ade4  and adegadegenet , 30 for adegenet . Specimeadegenet .Tpi marker as previously described [TpiH individuals were not included in this analysis. Outlier SNPs were identified using three methods. The fsthet package [ST–heterozygosity relationship from the empirical distribution, and outliers were selected with a 95% confidence level threshold. The pcadapt package [ST. We retained candidate markers identified by at least two methods and the remaining loci were considered as neutral. We compared the sequences containing outliers with the annotation files of the reference genome to identify loci present in encoding genes. We generated a fasta file containing the protein sequences to run Blast2GO [We searched for loci putatively under selection in the set of 15 populations and in the set of strains, where samples were identified as R- or C- strains using the escribed . TpiH in package  generate package  consider package  assumes Blast2GO  softwareBlast2GO .Tpi marker (95%) than COI (86%), consistent with other studies suggesting that Tpi is a better strain marker than COI [Tpi-hybrids (TpiH) were found only in Brazilian locations, mainly in MA02 population, which also had many R-strain samples . Estimates of genetic diversity were similar across locations and are summarized in ST calculations . Likewise, Brazilian R-strain populations MA02 and RS had pairwise FST = 0. Lower pairwise FST distances  and 306 of these were within predicted protein coding genes of FAW. After Blast2GO analysis, 220 proteins were successfully mapped, and 94 were annotated  in the sex chromosome Z, which concentrated over twice the number of outliers compared to the autosomal chromosomes . The locGBS has been used successfully in insect pests to reveal insights about gene flow and coancestry , spatialTpiR diagnostic markers, and the few specimens featuring discordant genotypes likely represent vestiges of interbreeding events that occurred in the past. Based solely on diagnostic polymorphisms in COI and Tpi regions, MA02 and AR03 populations showed increased levels of strain hybridization, and we were able to describe the level of gene flow of these locations based on GBS data set.By assessing a large number of samples in Brazil, we confirmed that FAW collected in corn fields were predominantly C-strain, with less than 4% of samples featuring both the COI-RS and ST distances and PCA plots confirmed that the Brazilian populations are structured by host strains, rather than by geographical ecoregions.GBS data revealed high levels of gene flow and low genetic differentiation between MA02 and RS population, which was composed by pure R-strain samples. Since these two populations were the most geographically distant locations sampled in Brazil, apart over 3200 km, we presumed that MA02 was composed by R-strain specimens with recent events of hybridization. Altogether, the genetic analysis based on pairwise FLong distance migration enables FAW populations to travel from Southern Texas and Florida up to Canada, a distance of nearly 2500 km, in less than three months , 43. TheSeveral studies comparing populations from Brazil and Argentina in the past showed strong similarities between the two countries , 44–46, ST analysis indicated significant genetic structure between countries and among provinces inside Argentina. This result is consistent with observations of mating incompatibility between populations collected in northern Argentina compared to those from the Pampas region, which indicated pre-reproductive isolating barriers between geographically separated populations [Nevertheless, Fulations . GBS datulations , 48. We In order to explain how selection pressures might be affecting FAW populations in South America, we examined the putative annotations of genes containing outlier SNPs. Host strain outliers were mostly concentrated on the sex chromosome Z, suggesting that the selection pressures are acting upon specific regions of the FAW genome. This result corroborates with previous study where the preponderance of strain specific SNPs were Z-linked , and is Bt toxins [Other functional annotations revealed proteins that were likely involved in binding activities and that were present in or related to the cell membrane. Mutations in Cry receptor genes have been reported in numerous lepidopteran species to be the most common mechanism of resistance against t toxins , and hert toxins , esterast toxins , JHAMT [t toxins , and alst toxins . Two nott toxins . UDP-glut toxins , a toxicST distances showed genetic structure between FAW populations of Brazil and Argentina, which has important IRM implications if resistant populations are reported in either country.From the Insect Resistance Management (IRM) perspective, resistance evolution is one of the most challenging problems in the sustainable control of FAW . TherefoIn conclusion, by combining classic molecular markers for FAW host strain identification, and genome-wide SNPs identified with GBS, we obtained more resolution of population structure than previously reported. The genetic structure and pattern of FAW in Argentina and Brazil reinforces the importance of phytosanitary barriers between countries for effective FAW management in each location. In agreement with this issue, outlier analysis suggested that positive selection is associated with field management and host strain divergences. Taking all this into consideration, current GBS data proved to be useful for population genomics research in South America and it may be applied to other geographies where the species has been introduced.S1 TableMost populations were not found at equilibrium. Brazilian populations featured lower observed heterozygosity than the expected at p < 0.05. The coefficient FIS also indicated that the Brazilian populations collected in corn fields had significant inbreeding. On the other hand, the fall armyworm populations from Argentina featured more outbreeding and private alleles.(DOCX)Click here for additional data file.S2 Table*associated with populations. **associated with host strains and populations. Loci with no mark are associated with host strains.(DOCX)Click here for additional data file.S3 Table*associated with populations. **associated with host strains and populations. Loci with no mark are associated with host strains.(DOCX)Click here for additional data file.S4 TableDarker orange indicates longer distances.(DOCX)Click here for additional data file.S1 Fig(A) FST calculated with all variant loci (3309 SNPs). (B) FST calculated using neutral markers (2853 SNPs). (C) FST was calculated using candidates putatively under positive selection (456 SNPs) obtained by three methods . Darker green color represents a higher degree of differentiation.(TIF)Click here for additional data file.S2 FigThe Venn diagrams shows the number of outlier SNPs associated to (A) FAW host strains and (B) populations.(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 FigGeographic locations are represented by different colors, and dots represent different individuals. The inset shows BIC values for different number of k clusters. Analysis performed with (A) All SNP loci, (B) 2,853 neutral SNPs, (C) 456 outliers. Plots generated using adegenet package for R software. Sampling locations were considered as priori groupings.(TIF)Click here for additional data file.S5 FigLocations were represented mostly by C-strain moths, except for MA02 and RS locations where most samples were identified as R-strain.(TIF)Click here for additional data file.