Spodoptera frugiperda is thought to have undergone a rapid ‘west-to-east’ spread since 2016 when it was first identified in western Africa. Between 2018 and 2020, it was recorded from South Asia (SA), Southeast Asia (SEA), East Asia (EA), and Pacific/Australia (PA). Population genomic analyses enabled the understanding of pathways, population sources, and gene flow in this notorious agricultural pest species. Using neutral single nucleotide polymorphic (SNP) DNA markers, we detected genome introgression that suggested most populations in this study were overwhelmingly C- and R-strain hybrids (n = 252/262). SNP and mitochondrial DNA markers identified multiple introductions that were most parsimoniously explained by anthropogenic-assisted spread, i.e., associated with international trade of live/fresh plants and plant products, and involved ‘bridgehead populations’ in countries to enable successful pest establishment in neighbouring countries. Distinct population genomic signatures between Myanmar and China do not support the ‘African origin spread’ nor the ‘Myanmar source population to China’ hypotheses. Significant genetic differentiation between populations from different Australian states supported multiple pathways involving distinct SEA populations. Our study identified Asia as a biosecurity hotspot and a FAW genetic melting pot, and demonstrated the use of genome analysis to disentangle preventable human-assisted pest introductions from unpreventable natural pest spread.The fall armyworm (FAW)  These exotic arthropods can have significant negative impact on agricultural production13, and the environments . Good phytosanitary practice together with robust biosecurity preparedness can lower the risk and help mitigate the effects of these invasive species. Invasive arthropods, especially species of agricultural importance, may also introduce novel genotypes  into related native populations through introgression and hybridisation, or into established populations of invasive species, thereby increasing their genomic diversity and further complicating pest management .Movements of exotic arthropods are increasingly being linked with global agricultural and horticultural tradeSpodoptera frugiperda), a highly polyphagous noctuid moth native to the tropical and subtropical regions of the Americas, was officially reported in Western Africa in early 201619, followed by rapid detections across sub-Saharan Africa  by February 2018. In Asia, its occurrence was first reported in South Asia (SA) in India in May 2018, and by December 2018, it had been reported in Bangladesh, Sri Lanka, and in Myanmar , and in China  by January 2019. In SEA, throughout 2019, detection of FAW was reported from Indonesia23, Laos, Malaysia, Vietnam24, the Philippines25, Cambodia (S Khay pers. ob.), and in EA from the Republic of Korea27 and Japan (FAO 2021) in July 2019. The moth's strong flight ability  and potential to contaminate certain agricultural trade commodities  leads to its success as a pest and its detection in increasing number of countries.The fall armyworm .In the native range, FAW is conventionally divided into the C-strain and the R-strain36 and in Australia, FAW was first detected in the Erub and Saibai Islands in the Torres Strait in January 2020, and by early February it was confirmed from maize fields in Queensland (QLD), followed by detection in Western Australia (WA), Northern Territory (NT), New South Wales (NSW), Victoria (VIC), and as of April 2021, it was also reported from Tasmania, as well as Norfolk Island in the Pacific, and most recently (March 2022) also in New Zealand. The FAW is now established across northern Australia and has been reported in a number of crops including sorghum and sugarcane. Since reported by Goergen et al.19, the rapid detections of FAW across the sub-Saharan African nations followed by Asian  detections, has led to the general acceptance in the scientific and agricultural sectors that the pest spread eastward from an initial incursion into Africa37. This perception fits the reported patterns of detection, but does it really fit the actual movement of this species across the Old World?In early 2020, FAW was detected in Pacific/Australia (PA) in Papua New Guinea38) and Asian  invasive populations identified gene flow patterns and signatures that suggested the FAW’s recent spread was due to multiple introductions, with invasive populations likely to have moved from the east  to Africa . Genomic analyses of Chinese and African FAW populations by Gui et al.40 also detected signatures that were best explained by independent introduction events in EA, and a likely east-to-west movement of the FAW. The authors’ conclusion however, nevertheless maintained the prevailing axiom that FAW arrived in China from western African, with its most recent origin to the Yunnan Province being from the neighbouring country of Myanmar43.Studies based on nuclear DNA markers involving African  and frequencies of introduction  of the current invasive FAW populations in Africa, Asia, and Pacific/Australia will have significant implications for the future management of this pest, especially with respect to the delimitation between human-assisted introductions  vs. climatic factor-assisted natural migration , insecticide resistance management49, and climate  adaptation and tolerance (e.g.53), highlighting most likely agents of spread. It also highlights that evaluating possible future incursion routes makes it necessary to identify weak points in the phytosanitary risk assessments, to enable future targeted monitoring at the right places, and to critically assess official reporting and announcement dates. The implications are significant, such as in reverse simulation studies (e.g.55) that relied on reported detections dates to identify potential wind patterns for explaining pest dispersal patterns, but have not incorporated appropriate genomic/genetic data to ensure consistency between multiple datasets. This could result in significant biosecurity concerns relating to anthropogenic-assisted introductions not being addressed due to the perceived difficulty of preventing pest spread via natural migration.Understanding the spread patterns  loci to: (1) determine the genomic diversity of invasive populations of FAW and the likelihood of multiple introduction events, and (2) determine the area of origin and introduction pathways of FAW populations in Australia. This information can then be used to delineate between human-assisted vs. climate-assisted migration patterns of FAW in SEA and PA regions and inform risk assessments for future incursions of both natural and anthropogenic spread.56 who detected only two  C-strain mtCOI haplotype individuals from a much larger  Northern Territory sample size. Proportions of C-strain to R-strain also varied significantly across the different SEA populations (Table 57). All Australian populations analysed for their corn or rice mitochondrial haplotypes via mitogenome assemblies of whole genome sequencing data therefore contrasted with the invasive populations from SEA where in some countries  FAW with the C-strain mtCOI haplotypes made up approximately 50% of the populations examined  from Australian samples. Our results, particularly that from Northern Territory, are not dissimilar to the finding of Piggott et al.ns Table  in contrTpi) gene used to differentiate the C- and R-strains suggested that virtually all individuals from the SEA, PA, and South Korean  carried the C-strain genotype at the Tpi gene. Of all SEA and PA individuals assessed, none was homozygous for the rice allele at this locus, while a number of samples (n = 10) were heterozygous C-/R-strains, primarily from the Philippines as well as one sample each from Malaysia and South Korea. Similar to the conclusions of Zhang et al.34, at least in the invasive range, our finding suggested that the Tpi is not a useful marker: not only are the majority of samples of ‘corn’ preference, with limited evidence of hybrids and therefore contrasting greatly with whole genome analysis, but both the Tpi and the mitochondrial markers frequently contradicted each other, and do not provide accurate genealogy in, e.g., hybrid females or their offspring, especially if the female also mated with a hybrid male31.Mutations in the Triosephosphate isomerase  differed from the one present in the Yunnan CY and Indian populations, although the four haplotypes clustered with high 87–100%) bootstrap support. One other C-strain mitogenome was detected in one individual from China00% bootsS. frugiperda populations based on 870 neutral single nucleotide polymorphic (SNP) markers provided evidence of complex genetic relationship especially between individuals representing the invasive populations  formed two closely related sister clades with long branch lengths, suggesting these likely represented separate introduction events. Based on analyses of nuclear SNP data, the main Australian FAW population clade consisted of multiple sister clades and were clustered with varying degree of bootstrap support values. Some of these Australian populations appeared to share close relationship with the FE  population , while others had largely unknown invasive origin(s).Maximum Likelihood (ML) phylogenetic analysis of the global ons Fig. . While tSoutheast Asian countries  and Pacific/Australia  have populations that were mixed, and interestingly were ancestral to East African populations , while some Australian populations  were shown to be closely related to these SE Asian populations with strong bootstrap support . Myanmar and China appeared to not share FAW populations with similar SNP profiles despite being neighbours. Multiple introductions of FAW with diverse genetic profiles and potentially similarly diverse origins were therefore likely the main reason for their wide spread detection across the Old World.Clear evidence of multiple introductions can therefore be seen from the phylogenetic analysis, with unique introduction events likely underpinning the establishment of FAW populations in EA.  and SEA . In Australia, while the NT/NSW populations shared closer evolutionary relationships with SE Asian populations, the population origin for most of Qld and WA populations was unclear, and could be due to a sampling effect . Some Burdekin and South Korean individuals appeared to share closer evolutionary lineage, although the factor leading to this detected pattern remained as yet unknown.33; π = 0.279–0.329) in native and invasive populations based on the same set of 870 SNP loci. The high nucleotide diversity estimates from the SEA, Australia and South Korean populations likely reflected effects of limited  highly polymorphic SNPs from non-coding genomic regions being used, and are comparable to the findings from Tay et al.33 that used the same sets of SNP loci. We did not detect significant overall differences between the various invasive populations, and for the SE Asian and Australian populations the nucleotide diversity estimates were generally between 0.258 and 0.291. All invasive populations from Africa , SA/EA , South Korea), SEA , Laos, Vietnam, Myanmar, Philippines), and Pacific (PNG)/Australia (WA (Kununurra), NT, QLD , NSW (Wee Waa)) showed higher average observed heterozygosity (Hetobs) than the average expected heterozygosity (Hetexp), with the highest Hetobs seen in the Malawian population as also reported previously33. Within the Australian populations, highest average observed heterozygosity was seen in the Strathmore population, while in populations in SEA  and the EA  all showed similar average Hetobs. Negative average FIS values for all populations were consistent with Hetobs being higher than Hetexp, and suggested populations were out-breeding . Similar to the previous findings33, the lower Hetexp  could likewise indicate recent mixing of distinct populations from SEA that suggest multiple introductions .The basic population diversity statistics for each population are listed in Table ca. 30%) were also shown to not be in Hardy–Weinberg equilibrium (HWE) especially for the Malaysian , but also Australian , Chinese , South Korean, and Malawian populations. Taken as a whole, genetic diversity results from this study therefore suggested that the invasive Asian  FAW populations exhibited signatures of recent mixing of previously separated populations. Simulated patterns of moth migration of various invasive FAW populations such as between Myanmar and China  and to Australia54 are incompatible with the population genomic data, which suggests these were likely discrete and non-panmictic FAW populations with the most probable explanation being due to multiple origins of founding populations.The observed heterozygosity excess detected in all invasive range populations could be further explained as due to population sub-structure and isolation breaking through periodic migration. Significant numbers of loci (FST) between populations varied significantly , while across Asia  since 2016 but also potentially pre-2014 .Estimates of pairwise genetic differentiation  and SEA .Interestingly, significant genetic differentiation was observed between populations from Yunnan province in China and populations from Myanmar, Laos, and Vietnam. Penang and Johor  populations were not significantly differentiated from other SE Asian populations, nor with Ugandan and Malawian populations from east Africa. Individuals from Benin and Mackay  showed non-significant genetic differentiation with all populations except with Kedah, and for Mackay also surprisingly with the Wee Waa population from New South Wales. The South Korean population exhibited significant genetic differentiation with SE Asian population except with Mackay, India and the Yuanjiang (YJ) population in Yunnan Province. Finally, the Kedah population, being one of the earliest collected samples from Malaysia and having been maintained as a laboratory population, showed strong differentiation with all populations , Northern Territory (NT), Queensland , and Wee Waa (NSW) populations suggests these populations likely derived from separate establishment events. The WA Kununurra population was not significantly differentiated from the Johor State , India and the Cangyuan (CY) China populations, suggesting a potential south-eastern route from SA/SEA into north-western Australia. Contrasting this, Walkamin and Mackay populations showed non-significant genetic differentiation with the Madang (PNG) population, suggesting a potential second pathway for SEA individuals to arrive at the north-eastern region of Australia. Significant genetic differentiation between WA, NT, and Qld populations suggested that at least during the early stage of pest establishment in northern Australia, there was limited gene flow to homogenise the unique genetic background carried by these distinct individuals, some of which exhibited also distinct insecticide resistance profilesWe selected specific populations to compare using Principal Component Analysis (PCA) as examples to support evidence of independent introductions, as seen from Fig. PCA also showed that differences existed between FAW populations from the Madang Province in PNG and with the Strathmore population from Qld Fig. e. The SEPCA further enabled visualisation of genetic diversity amongst Australia FAW populations, suggesting that arrival and establishment of FAW likely involved separate introduction events that followed closely after each other and over a short timeframe. While it had been anticipated that the southward spread of FAW from SEA would necessarily lead to Australia FAW and PNG FAW to share similar genetic backgrounds, the Madang Province FAW population appeared to be different from the Strathmore (Qld) population, with the Madang population being more similar to Lao PDR/Vietnam populations, and the Strathmore population more similar to FAW from South Korea.Directionality of gene flow between African, South Asia (Indian), East Asia (China) and SE Asian populations were predominantly from China to east African and SE Asian populations , India, and Chinacf. WA/Qld), likely involved individuals from diverse genetic background . At K = 4, the majority of Australian populations appeared to contain genetic clusters similar to China  and to SEA .Admixture analysis that excluded New World, African and Indian populations identified four genetic clusters  to best describe these invasive populations from SEA, and EA , and Pacific/Australia Fig. a. At K =Overall admixture patterns at best K = 4 in China and SEA remained unchanged when analysed together with African and Indian individuals Fig.  that ide34. While the current invasive populations in Africa and Asia likely arrived already as hybrids as suggested by Yainna et al.68, the Malaysia Kedah State population was potentially established by offspring of a non-admixed female. Distinct admixture patterns in Malaysian FAW populations between Kedah and Johor/Penang states therefore suggested that establishment of these populations was likely as separate introduction events. As reported also in Tay et al.33, the Chinese YJ population appeared to have admixed signature that differed from XP and CY populations, and suggested that the YJ population could have a different introduction history than the XP and CY populations. Similar multiple genetic signatures based on lesser nuclear markers by Jiang et al.39 also supported likely multiple introductions of China Yunnan populations.Genome-wide SNP loci demonstrated that invasive FAW populations from SEA and Australia exhibited admixed genomic signatures similar to that observed in other invasive populationsS. frugiperda in Asia , the detection of distinct population sub-structures between what had been widely assumed  as genetically linked populations between Myanmar and China, of multiple introduction pathways into north western and north eastern Australia, and the identification of potential SEA origins of eastern African  FAW populations. The findings highlight the need to infer population movements through genome-wide analyses; while critical assessments are needed of conclusions based on movement studies such as reverse trajectory analyses55, and inference of population genetics relying solely on detection reports and limited  DNA markers. Importantly, the study demonstrated the unexpected complexity of FAW populations across its current sub-Saharan, South Asia, Southeast Asia, East Asia, and Pacific/Australia invasive ranges since the species’ initial 2016 confirmation in western Africa. Results from this study further supported that human (anthropogenic)-assisted activities were likely major contributing factors, as also cautioned by Early et al.7 based on the prevailing opposite wind direction  in the African continent.In this study, we demonstrated through genomic analysis of genome-wide SNP markers signatures of multiple independent introductions of 69 has generally been regarded as a result of its long distance migration ability  following a single introduction into west Africa62 and subsequent wind-assisted dispersal37. In contrast, genomic  evidence has begun to emerge that the current widespread establishments of FAW populations in Asia were the result of multiple introductions, and likely associated with international agricultural trade. While pre-border interception data from SEA are generally lacking, regular interceptions of FAW in agricultural commodities by Europhyte  provided evidence to demonstrate the regular interceptions of FAW from its native countries  were associated with international trade activities. These ‘bridgehead invasive populations’44 established across Asia and Africa enabled subsequent establishments of localised secondary invasive populations via multiple factors including agricultural trade activities and natural migration .The rapid spread rate of this pest since 2016 to over 70 countries33 with distinct signatures, Jiang et al.39 identified six separate genetic signatures in populations from southern and northern China, and Schlum et al.38 and Tay et al.33 identified a total of at least four separate introductions in African populations . Population genetic analyses based on limited partial gene markers have also identified low frequencies of unusual polymorphism patterns in the Tpi and mtDNA gene markers in some African and an Indian FAW . Similarly, Gui et al.40 also detected signatures suggestive of independent introductions based on genome wide SNP analyses but have nevertheless maintained the African origin theory. While the conclusions by these authors have reinforced the hypothesis of the west–east movement of FAW, increasing whole genome evidence makes it more reasonable to conclude that these earlier single gene findings were also evidence of multiple unrecognised independent introductions.From the analyses presented here, we suggest that the number of independent introductions of FAW is likely underestimated. For example, while our genomic analyses have identified populations in Malaysia, South Korea, and China32 enabled integration of the published dataset  with the current SE Asia, East Asia, and Pacific/Australia FAW populations to reveal a complex picture of the pest’s invasive history. While multiple introductions especially in the Asian continent  have played an important role leading to the perception of rapid spread, introductions from elsewhere have also contributed to the African establishment and expansion. Further to genomics evidence, resistance allele characterisation and bioassay experiments have also identified invasive populations with non-overlapping unique insecticide resistance profiles in China , Indonesia74, Australia49, India75, and Africa77.Our investigation based on previously described genome-wide neutral SNP markersBemisia tabaci MED and MEAM1 species , and for the related noctuid pest Helicoverpa armigera , and underpinned the perceived rapid spread  of these pests in their introduced habitats. Early confirmation of invasive pests in novel habitats is also often challenging especially if initial population sizes were small. For example, while the initial detections of H. armigera in Brazil was during the cropping seasons of 2012/201380, its presence in Brazil was only subsequently confirmed to be at least as early as in 200881 and potentially earlier elsewhere  in the South American continent82. Similarly for the FAW, its presence in Vietnam was reported since 200883, and pre-border interceptions of FAW from non-native ranges  back to its native range by the USDA Identification Technology Program (ITP) were pre-201467, and pre-dated the 2016 first reported cases of FAW in east Africa19. In Uganda, farmer surveys85 showed that FAW damage symptoms on maize crops were first identified in the Namutumba (since 2013) and the Kamuli (since 2014) districts, while Otim et al.86 reported farmers observed FAW damage symptoms in eastern and northern Uganda since 2014, although farmers at the time were unaware of this highly invasive exotic armyworm species. Findings of field surveys86 were in agreement with anecdotal observations and with single-gene response on Bt maize in South and East Africa, that the FAW could have been present in Africa several years prior to its confirmation in West Africa70.Multiple independent introductions of invasive agricultural pests are well-documented such as for the cryptic whitefly 66 of outbreaks around Hanoi remained to be answered. Malaysian populations from Penang and Johor States were also shown to be linked to, and potentially source populations for, Ugandan and Malawian FAW populations  in China. While reverse trajectory studies by, e.g., Wu et al.55 that suggested Yunnan province FAW to have originated from Myanmar, results from the present study showed that there was very little genetic connectivity between them  have been reported88. Similarly, arrival and subsequent detection of S. frugiperda populations across the northern region of Australia also likely represented separate establishments based on nuclear SNP analysis but did not support the reverse trajectory simulation findings of Qi et al.54. Populations between WA, NT, and Qld were shown to be genetically differentiated, suggesting limited gene flow between these populations at the early stage of invasions. The Kununurra population was found to be less genetically differentiated with the Johor  population , suggesting a route moving south-east from South Asia/SE Asia into Western Australia, potentially via Indonesia. The PNG population was shown to be not significantly differentiated from the Walkamin (Qld) population, while gene flow directionality analysis linked Yunnan populations , significant differences in resistance to indoxacarb was nevertheless detected between WA (Kununurra) and Qld (Strathmore) populations49, and could be due to the different source populations for the WA and the Qld populations. On-going studies to monitor for potential arrivals of novel resistance alleles and those already reported in Indonesia and China to Australia will therefore be needed to inform and impact future FAW management strategies.Boaventura et al.ca. > 7000 km). Regardless, it highlights the challenge faced by biosecurity agencies globally in preventing accidental introductions of alien species.Phylogenetic analyses using both mitochondrial genomes and nuclear SNP loci supported multiple introductions at different scales. At least 12 C-strain mitochondrial genomes based on concatenated PCGs were identified, with some mitochondrial DNA genomes being detected only in SEA populations . In the R-strain, at least 19 unique mitochondrial DNA genomes were detected , though unknown, is potentially as early as pre-2014  and populations from SEA and China remained largely separate at least as recently as 2019/2020, based on analysis of our 870 SNP loci , contradicting the hypothesis of a Myanmar origin for the Yunnan S. frugiperda population55. Taken as a whole and incorporating population substructure  analysis, directional migration analysis of invasive S. frugiperda populations identified East Asia  and SEA as biosecurity hotspots, while multiple introductions involving genetically distinct S. frugiperda likely occurred in north-western  and north-eastern  Australia.An important finding from this study has been that the SE Asian populations were largely clustered away from other Asian  populations, supporting separate establishment histories of 58), and to provide practical information to regulators and to some extent producers on how best to manage new invasive populations. The use of genome-wide SNP loci obtained via whole genome sequencing has enabled the elucidation of pathways to disentangle origins and establishment histories. This, bolsters risk assessment efforts, and provide information to biosecurity agencies and to international inter-governmental agencies to differentiate between natural and human-assisted spread. While it would be unlikely to stop natural migration of pests, accidental introductions via human-assisted spread are preventable. Findings from this study set the precedent that aims to inform biosecurity agencies and policy makers to effect behavioural change in the case where pest establishment and spread were underpinned by poor phytosanitary practices.Population genomic studies via whole genome sequencing have enabled the spread patterns of this invasive pest to be re-evaluated to reveal highly complex scenarios that were likely associated with, or at least initiated by, trade activities. Whole genome sequencing is therefore proposed herein as essential for future biosecurity monitoring, in order to allow population genomics to directly impact on development of management policies and strategies , Southeast Asia , and Pacific/Australia ) were surveyed for whole genome sequencing (Table 49 prior to being stored at -20˚C (once laboratory colonies were established) for DNA extraction purpose. Individuals from these two locations used therefore represent the original field-collected populations from northern Australia.ng Table ; Fig. 6.DNA of individual FAW samples Table  was extrhttps://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) and aligned to the S. frugiperda rice genome (v1.0)89 using bwa_mem2 (v2)90. Duplicate alignments were removed using SAMBLASTER (v 0.1.26)91 and sorting completed using SAMtools (v1.9)92). Variants were then predicted using BBMap (v38.90)93 and normalised using bcftools (1.9)92. These variants were then subsampled using 870 SNP’s from Tay et al.33 for further analyses.Genome sequencing data for each individual were trimmed to remove adapter sequences using Trim Galore!  and invasive  FAW populations that were reported in33 to infer the overall Maximum Likelihood (ML) phylogeny by IQ-Tree94. Based on the phylogenetic analysis, we undertook separate admixture analyses95 by: (1) excluding New World, African, and Indian populations  + Southeast Asia + Pacific/Australia), and (2) excluding New World and Australian populations  + East Asia  + Southeast Asia + Papua New Guinea).For population and evolutionary genomic analyses of the SEA, South Korean, and Pacific/Australian FAW populations, we used the same set of the previously reported 870 neutral genome-wide SNPs38) meant that inclusion of our limited native populations  vs. the higher number of invasive FAW populations  were unlikely to provide greater certainty to detect potential origins of invasive populations. The study therefore uses 452 samples with an average sequencing depth of 19.24  for evolutionary genomic interpretations relating to the gene flow patterns of the global FAW populations. Detailed description of the methods has been provided33. Admixture was run using multiple K values (3–9), and the cross-validation error (CV) was quantified for each K. The K value with the least CV error (K = 4 in this case) was selected for further interpretation. The 870 SNPs for this present study have been deposited in CSIRO public Data Access Portal96.In the population genomic analysis, native FAW populations were excluded as the implication of multiple introductions that resulted in the establishment of Old World invasive FAW populations  and expected (Hetexp) heterozygosities for each population. The number of loci in the global population and individual populations departing significantly from Hardy–Weinberg equilibrium (HWE) was assessed using PLINK 2.098. The populations program in Stacks was used to calculate nucleotide diversity (π) and FIS (99 inbreeding coefficient) and used only variant loci with no window size specified. We used Genepop (v4.7.5)100 to calculate pairwise comparisons of weighted FST values between populations, with significance of differentiation between populations tested using the exact G test.We used the populations program in Stacks33. Briefly, we used Geneious 11.1.5 to map raw sequences for each FAW individual against a reference genome (GenBank accession number MT897262 (for mtCOI C-strain)/MT897275 (for mtCOI R-strain);33), followed by fine-tuning to resolve regions of poor assembly and ambiguity. Fully assembled mitogenomes were then annotated using MITOS101 by selecting invertebrate mitochondrial genetic code 5. Bed files from MITOS annotations were imported into Geneious 11.1.5 to fine-tune the predicted annotations of gene and protein coding genes (PCGs).The mitogenomes of all individuals from SEA (n = 94), East Asia , and Pacific/Australia (n = 164) were individually assembled following the approach as described in Tay et al.33 were combined and aligned using MAFFT Alignment v7.450103 within Geneious 11.1.5, using the default Auto option for Algorithm, 1.53 for Gap open penalty 0.123 for offset value, and 200 PAM/K = 2 for Scoring matrix. Once aligned, we trimmed and removed all intergenic regions including the A-T rich replication origin, all tRNAs, and the two rRNA genes, leaving 11,303 bp of the 13 concatenated PCGs. We identified unique concatenated PCG mitogenomes within individual countries using the DNAcollapser in FaBox (1.5)104, and partitioned these unique concatenated PCG mitogenomes prior to inferring ML phylogenies without outgroups using IQ-tree implementing UFBoot94 with 1000 replications to ascertain node confidence. Visualisation and presentation of the phylogeny : GenBank MF197867; corn (C-strain): GenBank MF197868; see22). We note that classification of the FAW host-strain  is contentious depending on the markers used  and may have limited applications in hybrid populations33, we nevertheless provided this information based on both the partial mtCOI gene identity and the TPI exon 5 gene region as previously described , to differentiate between the C-strain and R-strain S. frugiperda, whole genome sequence data were mapped to the SFRU_RICE_002481 contig89 at location 12939.With the non-recombinant nature of the mitogenomes, we analysed the mitogenomes of the FAW according to their strain classification  and the R-strain (rice strain)) separately to identify the conservative number of maternal founders for both strains across the invasive ranges, based on concatenation of the 13 PCG regions only, excluding the tRNA and rRNA genes, and the variable intergenic and AT-rich regions. We follow the naming suggestion of Tay et al.109 and visualised using ggplot2110. To enable visualisation of evidence of independent introductions we compared (1) China  populations vs. Myanmar, (2) within Malaysian populations between those collected from Penang and Johor States vs. Kedah State; (3) between China and East Africa , and (4) between China, Malaysia (Kedah State), and Australia ).Principal Component Analysis (PCA) was also carried out to increase interpretability of the large and complex FAW genomic dataset through maximising variance by creating new uncorrelated variables and to aid in visualisation. PCA based on the 870 SNPs was performed using PLINK v1.9111 was carried out using the complete set of 870 SNP loci for all invasive populations from Africa, Asia, and SEA, with the exception of the Kedah State  population that showed unique genomic background (and represented a population from the on-going lab-maintained culture first collected from maize field in 2019). Australia populations representing the ‘final arrival’ populations, were also excluded in the DivMigrate analysis to increase interpretability relating to East Africa, South Asia, East Asia and SEA populations. Relative migration was assessed using the GST statistics with 100 bootstrap replications and filter threshold  was set at 0.453 and plotted using the graph visualisation and manipulation software Gephi 0.9.2 < www.gephi.org > and countries were separately drawn using Microsoft PowerPoint for Mac v16.54.DivMigrate analysisSupplementary Figures.Supplementary Table S1.Supplementary Table S2.


Testudo graeca (T. g. buxtoni and T. g. zarudnyi) across their contact zone in Central Iran. Our results showed high levels of phylogeographic and phenotypic variation in the contact zone. Two monophyletic clades including, clade 1 (T. g. zarudnyi) and clade 2 (T. g. buxtoni) were identified. Furthermore, four distinct subclades were found in T. g. buxtoni, across a wide geographic range. Divergence time analysis suggests that the two subspecies diverged from one another after the uplifting of the Zagros Mountains during the early Pliocene. Using neutrality tests and mismatch distribution analysis, we found no evidence of recent population expansion. Morphological associations among geographical populations in the contact zone found more distinctions, with some significant adaptive and non-adaptive morphological variations in these populations. These distinctive morphological populations can be considered as management units (MUs) to conserve the evolutionary potential of this species. Finer scale evolutionary studies are required to address the southern part of the Zagros mountain range, where the overlapping of mitochondrial clades and subclades has occurred. Such information is essential for effective conservation of T. graeca populations, preventing translocation or mixing of individuals without comprehensive genetic and morphological assessment.Contact zones are considered as windows into the evolutionary process, allowing identification of factors influencing the evolutionary forces. Here, we combined phylogenetic and morphometric analyses to explore the evolutionary process affecting the taxonomic pattern of two subspecies of  Therefore, evolutionary biologists are interested in contact zones of distinct taxa because they can provide natural laboratories for assessing hybridization and isolation mechanisms2. Moreover, molecular and morphological data of taxa in contact zones elucidate the taxonomic status of a species1.Contact zones can serve as windows into the evolutionary process that enable us to identify factors influencing the evolutionary forces. The extent and nature of barriers are best understood where divergent taxa are in contactTestudo graeca, Testudinidae) is a widely distributed species with pronounced genetic and morphological differentiation between geographically vicariant populations6. Molecular studies using mtDNA markers have detected several divergent clades, corresponding to the currently recognized subspecies, with admixed populations along contact zones4. Five more divergent T. graeca subspecies exist in the Near and Middle East and southeastern Europe: T. g. ibera, T. g. terrestris, T. g. buxtoni, T. g. zarudnyi, T. g. armenaica, and T. g. anamurensis. Additional monophyletic groups of subspecies have been recognized in the western Mediterranean: T. g. graeca, T. g. cyrenaica, T. g. marokkensis, T. g. nabeulensis, T. g. soussensis, and one undescribed lineage. Although several studies have been conducted to evaluate the genetic diversity and population structure within the eastern subspecies9, phylogenetic relationships of these subspecies are not fully resolved10. Compared to genetic investigations12, morphological studies found much more differentiation, suggesting up to 20 distinct taxa within the T. graeca complex. More taxa were recognized in the Near and Middle East and southeastern Europe, which were regarded by some authors as distinct species16. Previous morphological studies focused on traditional morphometrics18, whereas geometric morphometrics has not been used for shell morphology before.The spur-thighed tortoise ; on the IUCN Red List, the species is assigned to Vulnerable category26: (1) T. g. buxtoni, distributed from north-western to the center of Iran, (2) T. g. armeniaca from north-western Iran, and (3) T. g. zarudnyi occurring in the central and eastern parts of the country. The contact zone of T. g. buxtoni and T. g. zarudnyi is along the Zagros and Irano-Turanian ecoregion in Central Iran27. Despite the extensive morphological variability of T. graeca, the phylogenetic relationships of Iranian subspecies have remained unknown. This is especially true for the two eastern subspecies, T. g. buxtoni and T. g. zarudnyi. The current study aimed to (1) fill the phylogeographic gaps of the eastern subspecies, in the extent of T. graeca complex, and determine the divergence time of mitochondrial lineages (2) assess the recent population expansion of T. g. buxtoni and T. g. zarudnyi; (3) clarify morphological and mitochondrial breaks in Central Iran, which is considered to be the contact zone of the two subspecies.In Iran, three subspecies are currently recognizedT. g. buxtoni and T. g. zarudnyi was evaluated, relative to other subspecies of the species’ global range  and Bayesian inference (BI) yielded identical tree topologies in which 10 lineages from the species’ worldwide range , and clade 2 (subspecies T. g. buxtoni) were identified. Clade 1 is predominantly distributed throughout the eastern part of the contact zone, whereas clade 2 is mainly distributed in the western part of the contact zone with an overlap across the central part of the contact zone , H3 and H5 were the most common haplotypes that were shared by 12 and 9 individuals, respectively .A median joining (MJ) network, illustrating the relationship between spur-thighed tortoise haplotypes, is depicted in Fig. ST was obtained among populations, with 92% of the variation was partitioned among populations and 8% within populations. The significant genetic structure was proved by high fixation index (Fst = 0.92) , significant FT. graeca in Iran was averaged at about 6.7 Mya with 95% highest posterior density (HPD) intervals of 5–8.4. The divergence time of T. g. zarudnyi was estimated at about 3.9 Mya (95% HPD: 2.3–5.5), while the value for T. g. buxtoni was about 4 Mya (95% HPD: 2.7–6.9).Divergence times of all supported nodes (> 0.5/50) in the phylogenetic tree are given in Table Mismatch distribution analyses and neutrality tests suggested no evidence for unimodal distribution and didn’t reveal significant population expansion Fig. .Figure 4The cluster analysis revealed the presence of four distinct morphological clusters across the study area Fig. . When thP < 0.0001)  Fig. . Results01) Fig. . Further01) Fig. . Based oP values (P < 0.0001) from permutation tests  indicated significant Mahalanobis distances among studied populations  in Central Iran to fill phylogeographic and phenotypic gaps in this area. Moreover, the results provide essential information to develop effective conservation plans. The main results are elaborated in the sections below.The phylogeography, morphological diversity, and population structure of the most widely distributed tortoise, 10. Incorporating sufficient samples of eastern subspecies into our analyses has led to some achievements in the phylogenetic structure of the species. In our analysis, 10 divergent clades were identified, associating with the current known subspecies of T. graeca.Our finding confirmed the general topology suggested by previous studiesT. g. zarudnyi, and T. g. buxtoni formed two monophyletic clades. Four subclades were further identified within T. g. buxtoni, three of which  were found in Iran, whereas subclade B was only identified in sequences from Turkey. The subclade C was the most geographically wide-spread group in the contact zone. However, the other two subclades (A and D) were restricted to small geographic areas. Subclades A and B could probably adapt to their local environment, while subclades C and D  were widely distributed throughout T. g. buxtoni geographic range. Subclade D was mainly distributed outside the contact zone, with a high level of genetic diversity. Subclade C was the most diverse and widely distributed haplotype in the contact zone. It shares one haplotype (H94) in the northern and southern parts of T. g. zarudnyi distribution range. We found T. g. buxtoni, the only subspecies, with distinct subclades in a wide geographic range. Therefore, it is recommended to introduce new subspecies, particularly in western part of the region, which has been pronounced in a considerable genetic diversity and differentiation through a long evolutionary history9.The two subspecies, T. g. zarudnyi) had a smaller distribution range in the contact zone, having three haplotypes. Haplotype H5 is distributed further from the two subspecies border and confined to the previously recognized distribution range7, while haplotype H3 is the most frequent haplotype in the contact zone. This haplotype was also recorded in some localities in the distribution range of T. g. buxtoni, close to the border of the two subspecies.The second subspecies , Southern part of Zagros Eco-Region (SZ), Plain areas of Irano-Turanian Eco-Region (P.I-T) and Mountainous areas of Irano-Turanian Eco-Region (M.I-T). These regions are different based on the most significant climatic factors, including annual precipitation and temperature seasonality  and Irano- Turanian (mainly T. g. zarudnyi) populations. In geometric morphometric analyses, the differentiation among morphological populations was completely clear for CZ in carapace and P.I-T in plastron. Although Copernic coefficients represented the distinctiveness of morphological populations, based on the existing overlaps, some similarities between CZ and M.I-T populations (in plastron) and between SZ and M.I-T (in carapace) were observed. Moreover, SZ was located at the center of the traditional CVA scatter plot  and plastral lobes were narrower in P. I-T populations to provide wider openings for head and limbs and facilitate mobility. By contrast, the height of the carapace, width of vertebral scales and plastral lobes are greater in the populations of CZ and M. I-T and they have longer coastal scales. This can be attributed to the different environmental conditions in CZ and M. I-T compared to P. I-T , which can stimulate more plant growth, and the availability of more shelters in mountainous landscapes.As it can be inferred from our results, environmental conditions act effectively on costal scales; carapace height, and width of plastron lobes41 have also recommended the supracaudal and nuchal scales as reliable diagnostic characters for distinguishing the populations of Testudo species. Furthermore, some morphological variables such as MGSL, AbSL, FSL, GSL, PSL and IHASO can be used for discriminating the populations. Among these variables, IHASO is visually more obvious. The decrease in inner height of the anterior shell in P.I-T and M.I-T is evidently due to the inclination of the gular scales inward.Our results illustrated the importance of supracaudal and nuchal carapace scales for distinguishing populations. Previous studies42. These key phylogeographic and phenotypic achievements remind the importance of contact zones as suitable sites for studying evolutionary processes. However, finer scale evolutionary studies are required to address the southern part of the Zagros mountain range, where the overlapping of mitochondrial clades and subclades as well as the morphological populations are happening. Consequently, translocation or mixing of individuals, even for conservational purposes, cannot be acceptable without comprehensive genetic and morphological assessment.The separation of the two subspecies is remarkably proved by mitochondrial clades as well as traditional and carapace geometric morphometrics. It seems that the Zagros Mountains act as ecological barriers, separating the geographic ranges of the two subspecies, though geographical overlap between mitochondrial clades and morphological populations in the southern part of Zagros implies the possibilities of gene flow in this part of the contact zone. For example, similar environmental conditions of M. I-T and CZ may have resulted in similar morphological features in the populations of these two subspecies (see above). Based on the current study, we recommend that these distinctive morphological populations can be considered as management units (MUs) to conserve the evolutionary potential causing adaptive and non-adaptive morphological variations, more effectively43. Biopsy sampling technique as a non-destructive, quick and safe method was carried out to reduce the possibility of bleeding and infection44. However, alcohol was used before and after the sampling.Samples and data were collected in accordance with the guidelines and regulations of the Iranian Department of Environment (DOE) under permission No. 97/6549. All individuals were sampled, photographed, morphologically measured and released at the point of capture with no harm. Sample collection followed the ethical recommendations in the ARRIVE guidelinesT. g. buxtoni and T. g. zarudnyi in Central Iran  were used to obtain 0.5 mm deep tissues from the scales under feet close to the spurs. The tissue was immediately stored in pure 99% ethanol.The sampling was conducted in two consecutive years (2018 and 2019) during the species activity period in the contact zone of b gene, using CytbG (5′ AACCATCGTTGTWATCAACTAC 3′) and mt-f-na (5′AGGGTGGAGTCTTCAGTTTTTGGTTTACAAGACCAATG 3′) primers47. Amplifications were performed in 25 µl volumes, containing 10 µl of the Ampliqon PCR master mix, 1 µl of each primer, 9 µl H2O and 4 µl of DNA. The thermocycling was performed using an initial denaturation at 95° for 5 min followed by 35 cycles of 30 s at 94°, 50 s at 55°, and 1 min at 72° and a final extension at 72° for 7 min. Purified PCR products were sequenced on an ABI PRISM 3730xl using the BigDye Terminator Cycle Sequencing kit v.3.1 (Applied BioSystems).Genomic DNA was extracted from tissue samples using WizPrep™ gDNA Mini Kit (Cell/Tissue) following the manufacturers’ instructions. Polymerase chain reaction was performed for amplification of a 948 bp fragment of the mitochondrial cyt 48 and checked visually. In addition to T. g. buxtoni and T. g. zarudnyi sequences, all other subspecies sequences were retrieved from GenBank and included in the final dataset. Sequences of T. hermanni (AJ888362), T. marginata (AJ888333), and T. kleinmanni (AJ888371) were used as outgroup representatives.Sequences were edited with SeqScape v.2.6 software (Applied Biosystems) and aligned with 229 previously published mtDNA sequences from GenBank using the ClustalW algorithm implemented in Mega v.749. The substitution saturation was checked in DAMBE v.650.The number of polymorphic sites (S), nucleotide diversity (π), number of haplotypes (H), haplotype diversity (h), and the average number of pairwise differences (K) were calculated using DnaSP 5.10.151 was used to reveal the optimal partitioning scheme and nucleotide substitution model, using the Bayesian Information Criterion (BIC). Nucleotide substitution models include K80 + G for the first, HKY + G for the second, and GTR + G for the third codon position. Maximum likelihood (ML) and Bayesian inference (BI) approaches were employed to assess the phylogenetic relationships. Bayesian phylogenetic tree was constructed in MrBayes v.3.2.7a52 using two independent runs of four Markov Chain Monte Carlo (MCMC), ran simultaneously for 10 million generations and sampling every 1,000 generations. The first 25% of the sampled trees and estimated parameters were discarded as burn- in. The effective sample size (ESS) value was checked to be above 200 in Tracer v.1.7.153. The consensus phylogenetic tree was then edited in FigTree v.1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/).PartitionFinder v.2.1.154 for 10,000 bootstrap steps. Two methods for species delimitation were then used to identify the specific boundaries in the species. These approaches were implemented on online servers: the Poisson Tree Process model  and the General Mixed Yule Coalescent method .Additionally, maximum likelihood analysis was performed in IQ-TREE v.1.6.1255 to clarify the phylogenetic relationships among haplotypes. Pairwise Fst and an analysis of molecular variance (AMOVA) were performed in Arlequin v.3.5.2.256 with 10,000 permutations to estimate the level of genetic structure among clades and subclades in the contact zone.A Median-Joining (MJ) network analysis was implemented in PopArt v.1.73557. Two calibration dates of 7.6 and 9 Mya were respectively applied for inferring the minimum ages of the lineages. The first one consisted of T. kleinmanni plus T. marginata and the second was located between T. hermanni and the first calibration node10  on different scales of carapace and plastron were performed, using calipers with an accuracy of 0.02 mm. Measured carapace scales consisted of nuchal, five vertebral, and supracaudal scales in the middle, and eight pleural scales on both sides of the vertebral. In plastrons, each scale is divided into two parts by a suture, and the scutes of the plastron include gular, humeral, pectoral, abdominal, femoral and anal.18: straight carapace length (SCL), from the outermost projection of the cervical scale to the outermost projection of the posteriors marginal; plastron length (PL), from the outermost projection of the gulars to the posterior end of the anal; median carapace width (CW), at the center of the carapace; maximum carapace width (MCW), at posterior marginal 7–9; carapace height (CH), the vertical measurement between the most dorsal point of carapace and the most ventral point of plastron; length of bridge (LB), between axillary and inguinal scales; maximum (not midline) gular scale length (MGSL); maximum (combined left plus right) gular scale width (MGSW); maximum humeral scale width (CHSW); maximum pectoral scale width (CPSW); maximum abdominal scale width (CAbSW); maximum femoral scale suture length width (CFSW); maximum anal scale width (CSAW); gular suture length (GSL), humeral suture length (HSL); pectoral suture length (PSL); abdominal suture length (AbSL); femoral suture length (FSL); anal suture length (ASL); nuchal length (NL), straight-line measurement from the anterior edge of cervical scale to posterior end; nuchal width (NW), the width of cervical at the posterior end; maximum width of first vertebral scale (VW1); maximum width of second vertebral scale (VW2); maximum width of third vertebral scale (VW3); maximum width of fourth vertebral scale (VW4); maximum width of fifth vertebral scale (VW5); maximum median length of first vertebral scale (VL1); maximum median length of second vertebral scale (VL2); maximum median length of third vertebral scale (VL3); maximum median length of fourth vertebral scale (VL4); maximum median length of fifth vertebral scale (VL5); maximum dorsal width of supracaudal scale (DSW); maximum ventral width of supracaudal (VSW); maximum median length of supracaudal length (SL); first costal scale along length, as the minimum straight line distance between the anteriormost and posteriormost contact points with adjacent  marginal scales (CL1); length of second costal scale along the marginal (CL2); length of third costal scale along the marginal (CL3); length of fourth costal scale along the marginal (CL4); and maximum inner height of anterior shell opening parallel to median axis (IHASO).Traditional morphometric measurements were performed following the protocol of Türkozan et al.61. In order to eliminate the effect of size, morphometric data were standardized prior to performing analyses, using the following formula.Since the morphological features may change with increasing body size, the effect of dimensions must be reduced and differences between the groups should be due to the differences in body shape and not the relative size. Thus, standardizing morphometric data is required to reduce the changes caused by allometric growth62 to assess the differences, using one-way analysis of variance (ANOVA) , including Central part of Zagros Eco-Region (CZ), Southern part of Zagros Eco-Region (SZ), Plain areas of Irano-Turanian Eco-Region (P.I-T) and Mountainous areas of Irano-Turanian Eco-Region (M.I-T). We also recorded the most significant factors shaping the distribution pattern of the individuals, i.e., annual precipitation and temperature seasonality of each areaA) Table . Inter-gTortoises were labeled and photographed alive without anesthesia, using a Canon 350 D digital camera (8 MP). Photographic conditions such as camera settings, magnification, focus, lens size, camera distance from the sample surface and backlight were consistent for all individuals and images were taken from ventral and dorsal views. The camera was placed parallel to the ground plane, as such that the focal axis of the camera was parallel to the horizontal plane of reference and centered on the plastron and carapace.65. In total, 31 and 25 two-dimensional (2D) landmarks were digitized on carapace and plastron, respectively  was performed to group the studied populations. All analyses were conducted using PAST63 and MorphoJ68.On each image, 2D coordinates of fixed landmarks were digitized by the same person, using TPS DIG v. 2.31ely Fig. . LandmarSupplementary Information.


Monochasma savatieri Franch. ex Maxim is a medicinally valuable herb. However, the collection and protection of the wild germplasm resources of M. savatieri are still insufficient, and their genetic diversity and population structure have been poorly studied.M. savatieri individuals from Fujian, Hunan, Jiangxi, and Zhejiang provinces for genetic diversity and population structure, using 33 newly developed expressed sequence tag-simple sequence repeat (EST-SSR) markers. Applying these markers, we detected a total of 208 alleles, with an average of 6.303 alleles per locus. The polymorphic information content varied from 0.138 to 0.884 (average: 0.668), indicating a high level of polymorphism. At the population level, there was a low degree of genetic diversity among populations , with Zhejiang individuals showing the highest genetic diversity among the four populations (Fst = 0.497), which indicated little gene flow within the M. savatieri populations (Nm = 0.253). Mantel test analysis revealed a significant positive correlation between geographical and genetic distance among populations , and structure and principal coordinate analyses supported classification of populations into three clusters, which was consistent with the findings of cluster analysis.We collected and examined 46 M. savatieri does not look optimistic, and accordingly, protective efforts should be beefed up on the natural wild populations. This study provided novel tools and insights for designing effective collection and conservation strategies for M. savatieri.As a rare medicinal plants, the protection of The online version contains supplementary material available at 10.1186/s12864-022-08832-x. Monochasma savatieri Franch. ex Maxim, a perennial medicinal plant in the Scrophulariaceae family, is endemic to China and Japan, where it grows preferentially on sandy hillsides and in grassy clusters. In China, it is mainly distributed in southeastern regions, including the provinces of Jiangxi, Fujian, Hunan, and Zhejiang [M. savatieri can be used for medicinal purposes, including the treatment of colds, cough, pneumonia, fever, toothache, and irregular menstruation [Zhejiang , 2. The truation –5. Prepatruation , 7.M. savatieri has a long history of medicinal use and is one of the essential component of Yanning granules, which has been designated a “national protected traditional Chinese medicine variety” [M. savatieri has been unsuccessful. In recent years, there has been an increase in the market demand for M. savatieri, which has often led to limitations in the supply of its wild resources. Such scarcities among wild populations can be attributed to the fact that M. savatieri is a root hemiparasite that has stringent habitat requirements and a naturally weak reproductive capacity [M. savatieri are characterized by a short period of dormancy, and germination rates decline sharply with a prolongation of storage time. Consequently, if, on reaching maturity, the seeds lack suitable germination conditions, they will rapidly lose vitality [M. savatieri have sharply deteriorated and reduced in size. Their number of individuals and size of natural population have markedly declined in recent years owing to the short seed dormancy and inherently poor regeneration. This has resulted in substantial losses of genetic resources, as indicated by a survey conducted in China by Chen et al. [M. savatieri in almost all investigated regions showed sharp declines. Moreover, in Japan, M. savatieri has long been listed as an endangered species [M. savatieri is considered a matter of particular urgency. Currently, however, there is a notable lack of information regarding the genetic variation of M. savatieri, which thereby hinders evaluations of the genetic status of this species and makes it difficult to formulate appropriate scientifically based resource conservation strategies.variety” , 9. Howecapacity . Moreovevitality . Owing tn et al. , who fou species . ConsequM. savatieri are still limited, and one of the most important reasons is the lack of effective molecular markers for the species.Analyses of species genetic diversity and population structure play key roles in genetic resource conservation and plant breeding , 15. In M. savatieri from the major distribution provinces of China. Meanwhile, we detected an abundance of EST-SSRs in the assembled transcripts of the full-length transcriptome data of M. savatieri, and from among these, we developed reproducible polymorphic EST-SSR markers to assess the level of genetic diversity and genetic structure for the collected wild germplasm resources of M. savatieri. The collected wild germplasm resources and genetic information will provide novel insights for the conservation, utilization and breeding strategies development of M. savatieri.In this study, great efforts have been made to collect and preserve the wild germplasm resources of https://github.com/AWan222/LRCyc). The frequency of SSR distribution  was 87.40%, with an average of one locus per 2.76 kb. In addition, we found that 9078 sequences contained more than one SSR loci, and that there were 6363 (17.77%) compound SSRs. The SSR types were abundant, ranging from mononucleotide to hexanucleotide repeats, and the number of each type varied. Among these, mononucleotide  and dinucleotide  EST-SSRs were the most abundant repeat types, followed by trinucleotide loci , with less than 1.00% of the total being represented by tetra-, penta-, and hexa-nucleotides   was obtained for a K value of 3   and 0.481 to 0.583 (average: 0.535) respectively, which are lower than the values previously obtained for Paeonia decomposita [Magnolia sinostellata [Camellia nitidissima [M. savatieri is lower than that of these three species. For plants, reproductive patterns, genetic drift, natural selection, anthropogenic activities, and habitat fragmentation are among the main factors contributing to changes in genetic diversity [M. savatieri populations is attributable to its narrow range of distribution, along with the large spatial distance between populations, which limits inter-population gene exchange. Moreover, excessive harvesting of natural populations, habitat destruction, and declining population sizes may contribute to inbreeding and genetic drift within the M. savatieri population, thereby reducing its genetic diversity. Nevertheless, among the four regional populations examined in this study, we identified the Zhejiang population as being the genetically most diverse. Generally, a higher genetic diversity is indicative of a higher complexity of plant diversity, and consequently a greater potential for environmental adaptation [M. savatieri will predictably provide a theoretical basis for its protection and breeding.Analysis of stellata , and Camidissima , thus iniversity . It can aptation . AccordiM. savatieri would tend to indicate a significant genetic differentiation among populations. This assumption was supported by our AMOVA results (P < 0.001), indicating a higher molecular variation among populations (49.74%) than within populations (48.36%). Gene flow is one of the main factors contributing to the maintenance of a homogeneous population genetic structure. Theoretically, at Nm values > 1, there is a lower likelihood of genetic drift, thereby limiting the genetic differentiation among populations, whereas conversely, when Nm < 1, gene flow is insufficient to counteract the effects of genetic drift, thereby favoring an increase in the genetic differentiation among populations [M. savatieri populations, indicating that low levels of gene exchange would not weaken the differentiation among populations caused by genetic drift, which we suspect could be the primary factor influencing the genetic structure of M. savatieri. It can be reasoned that these findings reflect the characteristics of M. savatieri, such as its semi-parasitism, low reproductive capacity, and low seed viability. Moreover, the viability of M. savatieri populations is increasingly being threatened by habitat fragmentation and destruction, and consequently, declining numbers and hindered gene exchange may lead to a gradual increase in genetic differentiation.The degree of differentiation between natural populations can be described in terms of gene flow (Nm) and the genetic differentiation coefficient (Fst), which are negatively correlated, with a higher differentiation coefficient between populations being taken to be indicative of a lower extent of gene flow . Geneticulations . In the M. savatieri. PCoA and UPGMA clustering analyses were performed to classify the assessed materials based on their genetic similarity coefficients and genetic distance, which can clarify the intuitive relationship between populations [The genetic structure of species reflects the mutation, recombination, genetic drift, and selection effects experienced by populations during the course of evolution , and thuulations . Howeverulations . ConsequR2 = 0.3304, P < 0.05). Collectively, these results tend to imply that geographical isolation, which would hinder gene exchange between different populations and isolate different gene pools, could be the primary factor contributing to the apparent genetic differentiation among M. savatieri populations.UPGMA clustering analysis divided the 46 individuals collected from 10 different wild regions into two clusters, thereby indicating the presence of two discrete genetic populations among these regions. Using STRUCTURE analysis, these individuals were clearly divided into three different clusters, with a few examples of admixed individuals. These results indicate the relatively homogeneous genetic structure of most samples, and the similar composition of samples collected from the same regions. The results of PCoA analysis were found to be identical to those obtained using STRUCTURE and were in general consistent with the UPGMA clustering tree. In addition, we found that the genetic relationships among populations reflected the natural geographical locations of these populations, which was supported by the Mantel test results, which revealed a significant positive correlation between the geographical and genetic distances among populations , 11 from Hunan Province (HN), eight from Jiangxi Province (JX), and 18 from Zhejiang Province (ZJ)  Fig. . The forM. savatieri by Biomarker Technologies . The MISA  software was used to identify SSR loci from the transcript sequences (length ≥ 1000 bp) as previous described [https://db.cngb.org/search/project/CNP0003034/).Full-length transcriptome sequencing data was obtained for the leaves and stems of escribed . SSR sea2O. The amplification reaction program was as follows: pre-denaturation at 95 °C for 5 min; followed by 30 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 45 s, and extension at 72 °C for 30 s; and a final extension at 72 °C for 10 min. The PCR products were detected using 8% denaturing polyacrylamide gels with 0.5× TBE buffer [For PCR amplification, we used 10 μL reaction mixtures, containing 1 μL (100 ng/μL) of genomic DNA, 5 μL of 2× FastTaq Premix , 1 μL (0.01 nmol/μL) of the primers, and 3 μL of ddHE buffer , run at E buffer . The patE buffer  to compuE buffer . PopulatE buffer . The lenE buffer , and cluE buffer .Additional file 1: Supplemental Table 1. Details and sources of the 46 Monochasma savatieri samples analyzed in this study. Supplemental Fig. 1. The representative gel pictures with scoring by the EST-SSR markers. The patterns of bands were analyzed by a gel imaging analysis system (version Tocan 240). Supplemental Fig. 2. The photos of some representative samples in this study.


Aspidodera raillieti infects different marsupial and rodent hosts in the Nearctic and Neotropical regions, implying a gene flow among populations. However, niche diversification of the main hosts of A. raillieti in superimposed areas may provide conditions for population genetic structuring within this parasite species. We examined the genetic structuring of A. raillieti infecting three marsupial species co-occurring along the South and Southeast Brazilian Atlantic Forest, a hotspot of biodiversity.The population genetics of parasites may be influenced by host specificity, life cycle, host geographical range, evolutionary history, and host population structure. The nematode We employed morphometric analyses and partial mitochondrial cytochrome c oxidase I gene sequences (MT-CO1) to characterize populations via phylogenetic and phylogeographic analyses.A. raillieti specimens recovered from the marsupial hosts Didelphis aurita, D. albiventris, and Philander quica, we identified 99 MT-CO1 haplotypes forming four haplogroups and four clades in networks and phylogenetic trees, respectively. Clades I and II encompassed parasites of D. albiventris from the South region, clade III comprised parasites of D. aurita from the South and Southeast regions, and clade IV encompassed parasites of D. aurita and D. albiventris from the South and Southeast regions and parasites of P. quica from the South region. High genetic differentiation between clades, with a high fixation index and greater genetic variation in the analysis of molecular variance (AMOVA), indicated low gene flow between clades. Haplotypes shared among host species revealed a lack of host specificity. A significant correlation in the Mantel test suggested parasite isolation by distance, while there was no evidence of geographical structure between populations. Negative neutrality test values for clades III and IV suggested recent population expansion. Morphometric differentiation between A. raillieti specimens recovered from different host species, as well as from different localities, was more evident in males. Among 175 A. raillieti populations in the South and Southeast Atlantic Forest resulted from historical events rather than from current geographical distribution or host specificity. We also demonstrate morphometric variation associated with host species and localities, suggesting phenotypic plasticity to host attributes and to spatial variables.The genetic structure of The online version contains supplementary material available at 10.1186/s13071-022-05288-6. Aspidodera Railliet & Henry, 1912; Paraspidodera Travassos, 1914; Lauroia Proença, 1938; and Nematomystes Sutton, Durette-Desset & Chabaud, 1980 [Aspidodera is morphologically characterized by cuticular expansion forming a cephalic hood with cordons arranged in six longitudinal loops at the anterior end, three lips, an oesophagus with a terminal bulb, a ventral sucker on males, a pair of spicules and a gubernaculum, and a posterior region ending in a digitiform projection [Aspidodera spp. are distributed along the southern Nearctic and the entire Neotropical region, parasitizing the cecum and the large intestines of mammals of the orders Didelphimorphia, Cingulata, Pilosa, and Rodentia [The nematodes of the family Aspidoderidae Freitas, 1956, superfamily Heterakoidea Railliet & Henry, 1912, comprise Aspidodera raillieti Travassos, 1913 [Aspidodera were considered junior synonyms of A. raillieti because the morphological and morphometric differences used to propose these new species are not diagnostic characters and thus do not allow distinguishing them from A. raillieti. Among them are A. harwoodi Chandler, 1932 described from D. virginiana Kerr, 1792 in the USA; A. diazungriai Masf-Pallares and Vergara, 1971, parasitizing Didelphis pernigra J. A. Allen, 1900 in Paraguay; and A. vicentei Kohn, Fernandes and Mello, 1982, described from Nectomys squamipes Brants, 1827 in Brazil [A. raillieti might be associated with its geographical distribution and its hosts.os, 1913  is widelos, 1913 , 4, 5, 8Aspidodera raillieti has been found in all Brazilian biomes in areas of Amazonia, Atlantic Forest, Caatinga, Cerrado, Pampa, and Pantanal. This nematode was found parasitizing different species of marsupials, including Didelphis aurita Wied-Neuwied, 1826; Didelphis albiventris Lund, 1840; Didelphis marsupialis Linnaeus, 1758; Philander quica ; Philander opossum ; Chironectes minimus ; Metachirus myosurus ; Caluromys lanatus ; Marmosops incanus ; and a single rodent species, Nectomys squamipes  [A. raillieti in areas of the Brazilian Atlantic Forest: D. aurita, D. albiventris, P. quica, and C. minimus [s, 1827) –11. Four minimus . The Atl minimus –16.A. raillieti presupposes significant gene flow between populations of different host species, despite this nematode having a monoxenous life cycle [A. raillieti population structure is expected to depend on host movements [Parasite populations may have their genetic structure influenced by several factors, such as the degree of host specificity, effective population size, geographical distance between populations, host dispersal ability, evolutionary history, host population structures, and life cycle complexity –19. The fe cycle . Therefoovements , 20–22, ovements .D. aurita and D. albiventris, based on climatic niches throughout their geographical distributions, showed that these marsupials might explore different niches in areas where they co-occur, mostly in areas of forest-grassland mosaics [D. aurita may act as a biotic barrier for D. albiventris, where this habitat mosaic is not available for their coexistence [A study on the ecological modelling of  mosaics . In addixistence . These dP. quica overlaps with that of D. aurita and partially overlaps with that of D. albiventris [Philander quica and D. aurita have niche overlap and compete with each other [P. quica by D. aurita occurs [However, the distribution of iventris , 25. Phich other , 27; bota occurs , which mD. albiventris exhibit patterns of isolation by distance when comparing disjunction distributions between South and Southeast Brazil [D. aurita at a regional scale in Southeast Brazil [Nevertheless, another study demonstrated that populations of t Brazil . The samt Brazil , 31. LikA. raillieti, a parasite of the marsupials D. aurita, D. albiventris, and P. quica in South and Southeast Atlantic Forest localities. We hypothesized that A. raillieti populations are genetically structured as a function of their host species and/or geographical distances.In this context, we aimed to examine the population genetic structure of the nematode This study was conducted in eight localities in the Brazilian Atlantic Forest, from the state of Rio Grande do Sul in Brazil’s South Region to the state of Espírito Santo in the Southeast Region Fig.  and 2. TMarsupials were captured using Tomahawk Live Trap  model 201 traps (16″ × 5″ × 5″) baited with a mixture of peanut butter, banana, oats, and bacon.A. raillieti. Organs were placed separately in Petri dishes, washed twice in physiological saline solution (NaCl 0.85%) to remove tissue debris, and stored in 70% ethanol solution. For examination, nematodes were clarified in 25% glycerin alcohol. Measurements and drawings were produced with the aid of a camera lucida attached to a Nikon Eclipse E200 MV R microscope. Specimens were randomly selected for measurements. The number of specimens used for morphometric analyses was based on the parasite burden   to compaA. raillieti specimens correctly classified within their original group. Thus, we used DAPC to evaluate the results from the genetic analyses. DAPC was performed using the package ‘adegenet’ [DAPC is a robust method for describing variations between defined groups, selecting principal components (PCs) that explain the greatest variation between groups while minimizing the variation within each group. We used the cross-validation optimization procedure to identify the ideal number of PCs to be retained by DAPC and selected the components associated with the lowest root mean squared error . Finallydegenet’  in the Rdegenet’ .A. raillieti using the QIAamp DNA Mini Kit  according to the manufacturer’s instructions. Before DNA isolation, each specimen was morphologically characterized and subsequently washed in distilled water. Amplifications of the mitochondrial cytochrome c oxidase subunit I gene (MT-CO1) by polymerase chain reaction (PCR) were performed individually for each A. raillieti specimen using the primer cocktail described by Prosser et al. [Taq DNA polymerase, 400 μM dATP, 400 μM dGTP, 400 μM dCTP, 400 μM dTTP, 3 mM MgCl2), 0.5 μl of each primer cocktail (10 μM of a three-forward primer mix and 10 μM of a three-reverse primer mix), 1 μl of genomic DNA, and ultrapure water in a total volume of 25 μl. Thermal cycling conditions were 94 °C for 1 min; five cycles at 94 °C for 40 s, 45 °C for 40 s, and 72 °C for 1 min; 35 cycles at 94 °C for 40 s, 51 °C for 40 s, and 72 °C for 1 min; and a final extension at 72 °C for 5 min [https://plataformas.fiocruz.br/). Sequencing was performed using the 96-capillary 3730xl DNA Analyzer (Applied Biosystems).We isolated genomic DNA from mid-section fragments of each adult specimen of r et al. . Each reor 5 min . SuccessFor each specimen, DNA sequencing reads were assembled into contigs and edited for ambiguities using the Geneious version 9.1.8 bioinformatics software platform , resultiLauroia trinidadensis (Aspidoderidae). Since Nematomystes and A. raillieti formed a monophyletic group in previous studies [Nematomystes spp. to the ingroup in our phylogenetic analyses. The second dataset, used for phylogeographic analyses, included only our 175 sequences of A. raillieti.All sequences obtained in this study were deposited in GenBank (accession numbers OL676808–OL676982)  as optimality criteria were generated using the PhyML, version 3.0 online web server . EvolutiBayesian inference (BI) analyses were performed using MrBayes, version 3.2.6 , executeA. raillieti sequences into groups according to (1) the clades recovered in the ML and BI phylogenetic trees, (2) the host species, and (3) the geographical localities. Additionally, using DNAsp, the genetic diversity of each group was calculated by the numbers of haplotypes (H), polymorphic sites (S), haplotype diversity (Hd), and nucleotide diversity (π).Haplotype networks were inferred using the program PopART, version 1.7 , under tFst) [Fst to measure levels of genetic differentiation between groups. We also used the program Arlequin to assess deviation from neutrality using Tajima’s D [Analysis of molecular variance (AMOVA)  and fixaFst)  were calFst) . We usedjima’s D  and Fu’sjima’s D  tests foA. raillieti specimens, as well as the correlation between genetic distances and elevation differences from all geographical localities studied. The genetic distance matrix was calculated in the package ‘ape’ [The Mantel test  was usedge ‘ape’  using thge ‘ape’ , under Age ‘ape’ . The elege ‘ape’ . All proge ‘ape’ . All staA. raillieti, respectively. For the comparison between host species, eight and 14 PCs were retained for female and male A. raillieti, respectively. The proportion of male specimens correctly classified to their original group was approximately 83% for locality and 75% for host species. The proportion of female specimens correctly classified was 75% for localities and 67% for host species.The number of PCs retained in the DAPC varied according to the investigated group. For the comparison between localities, 11 and 14 PCs were retained for female and male A. raillieti, revealing three clusters, each cluster formed by specimens with high morphometric proximity. One of these clusters was formed by the locality of Porto Alegre, Rio Grande do Sul (POA-RS); the second was formed by the localities of São Gonçalo do Sapucaí, Minas Gerais (SGS-MG), Santo Amaro da Imperatriz, Santa Catarina (SAI-SC), Curitiba, Paraná (CUR-PR), and Petrópolis, Rio de Janeiro (PET-RJ); and the third was formed by Rio de Janeiro, Rio de Janeiro (RIO-RJ) and Paraty, Rio de Janeiro (PTY-RJ)  Fig. a.Fig. 2aAmong the variables that best discriminated among locality groups for males were length and width of the sucker, length and width of the hood, length of the cordon, and length of the caudal spine Fig. a. For feD. aurita, nine D. albiventris, and four P. quica hosts collected in eight different localities. We obtained 489 bp MT-CO1 gene consensus sequences from 175 A. raillieti specimens. The first matrix, used for phylogenetic inferences, resulted in 183 taxa and 480 sites. The second matrix, used for phylogeographic analyses, included only our 175 sequences of A. raillieti with 489 sites. No long branch was observed in the PhyPA method, indicating the absence of pseudogenes. Xia’s test provided no evidence for substitution saturation in any data matrix.We successfully sequenced adult worms recovered from 17 The ML best-fit model chosen by SMS in PhyML under AIC was GTR + G, with four substitution rate categories and gamma shape parameter α = 0.095, resulting in a tree with lnL = −3030.323236 score. The BI sampling, after 25% ‘burn-in’, resulted in a mean estimated marginal likelihood of –3129.3479 . The ESSs were robust for all parameters.Aspidodera raillieti specimens formed a monophyletic group in both phylogenies . Within A. raillieti, four main monophyletic groups were recovered and identified as clades I, II, III, and IV  comprised In the BI topology Fig. a, clade A. raillieti, we identified 99 haplotypes with 114 polymorphic sites. These 99 haplotypes were grouped into four haplogroups, corresponding to the clades recovered in the phylogenies, separated by genetic distances of 20 to 30 mutational steps  of The localities RIO-RJ and PTY-RJ included clades III and IV haplotypes. The locality POA-RS included clades I, II, and IV haplotypes. The locality CUR-PR had only one clade III haplotype, while all others had clade IV haplotypes. Haplotypes from the localities CAR-ES (clade III), PET-RJ (clade IV), SGS-MG (clade IV) and SAI-SC (clade IV) clustered in only one haplogroup per locality Fig. c. Some hD. aurita (PET-RJ) and D. albiventris (SGS-MG). Haplotype 64 was shared between D. aurita (CUR-PR) and P. quica (SAI-SC). Haplotype 53 was shared between D. albiventris (POA-RS) and P. quica (SAI-SC)  Fig. .Fig. 7MeThe AMOVA result for clade groups revealed higher variation among clades, which represented 80.64% of the total variation, while the variation within clades represented 19.36%. The genetic variation for the host species groups revealed less variation among host species, which represented 28.50% of the variation, while the variation within host species represented 71.50%. The genetic variation for locality groups revealed higher variation among localities, which represented 57.52% of the variation, while the variation within localities represented 42.48% , host species (P < 0.01) (Table P < 0.05). No difference was observed between RIO-RJ and CAR-ES or between PTY-RJ and CAR-ES    Table , and locES Table . The Man01) Fig. a and a s01) Fig. b.Table 7P = 0.005), while Fs values were significant for both clade III (−15.09) and clade IV (−24.39) (P = 0.000). For the host species groups, the D and Fs values were significant only for the group of A. raillieti parasites of P. quica . For the locality groups, D values were significant only for the localities PTY-RJ , PET-RJ  and CUR-PR , whereas Fs values were significant for the localities CUR-PR , SGS-MG , and SAI-SC .In Tajima’s D and Fu’s Fs neutrality tests, calculated for the clades, D values (−2.02) were significant only for clade III  indicated morphometric differentiation for both females and males, however, with partial overlapping of some specimens from different host species.The DAPC for A. raillieti specimens associated with host species and localities, our results identified the cephalic hood width for male and female specimens, the sucker length and width for females, and the bulb length and width for females. This morphometric variability may be a consequence of adaptations to environmental conditions, as observed in the trematode Echinostoma paraensei Lie & Basch, 1967 [Among the variables that best discriminated ch, 1967 .A. raillieti specimen groups associated with different localities, female nematodes had greater overlap between localities, while males were differentiated into three groups. The first group was composed of male specimens from the localities RIO-RJ and PTY-RJ, the second was composed of specimens from POA-RS, and the third was composed of specimens from PET-RJ, SGS-MG, CUR-PR, and SAI-SC.When analysing DAPC morphometric differentiation between A. raillieti, thus suggesting phenotypic plasticity regarding host attributes and spatial variables [Our findings indicated the influence of host species, as well as locality, on the morphometry of ariables .Aspidodera raillieti is a parasite with a monoxenous life cycle [Population structure can be influenced by different evolutionary forces. Among them, gene flow is considered of fundamental importance, as it allows the exchange of genetic information between populations, homogenizing the variation among them . Populatfe cycle , dependiA. raillieti. These results provide evidence that these lineages experienced past events that contributed to the genetic divergence observed between clades, since the genetic structuring observed in these helminths was not related to geographical distance, as evidenced by the presence of divergent clades in the same locality.Our phylogenetic trees and networks recovered four clades of Fst values, indicating high genetic differentiation between clades [A. raillieti.The genetic structure observed using AMOVA indicated a greater genetic variation among clades (interpopulation) than within clades (intrapopulation). The highly significant n clades , concurrFst, with high values both between geographically distant localities and between closer localities. Nevertheless, the Mantel test showed a significant and positive correlation between genetic and geographical distances, indicating isolation by distance (IBD). The disagreement between the population structure analyses and the Mantel test may be a consequence of the co-occurrence of haplotypes from different clades in the same locality, possibly due to historical processes. The phylogeographic patterns of species can be affected by different factors, such as dispersal or vicariant events, which can promote differentiation between populations [No geographical structuring was observed, since the AMOVA results had similar percentages of genetic variation among and within localities . This was congruent with ulations . In addiulations , 69. Howulations .A. raillieti has also been identified in populations of the nematode Heligmosomoides polygyrus , a parasite of the forest rodent Apodemus sylvaticus . To understand the phylogeographic pattern of H. polygyrus from different localities in Europe, Nieberding et al. [A. raillieti clades , with some haplotypes co-occurring in some localities.The high genetic diversity observed in g et al.  studied H. polygyrus and A. raillieti have no specialized structures for dispersal; thus, gene flow between populations depends mainly on host movements and social behaviour. However, H. polygurus is a host specialist and has a wide distribution congruent with its host, partially reflecting the phylogeographic history of its host [A. raillieti is a host-generalist parasite that is able to infect several marsupials and one rodent species, which makes its phylogeographic patterns potentially more complex, requiring studies with broader geographical ranges and other host species to better understand its genetic population structure.Similarly, the infective free-living stages of its host , 71. In A. raillieti by host species, the phylogenetic and phylogeographic results showed no evidence of population specificity for host species, unlike the morphometric analyses, since nematode haplotypes from different marsupial species were in the same clade. Additionally, some haplotypes were shared between different host species. Corroborating this pattern, no structuring was observed in A. raillieti associated with host species, as AMOVA indicated low genetic variation between the specimens recovered from each host species (interhost). The significant Fst values between host species indicated moderate genetic differentiation. Moreover, this genetic differentiation may result partially from geographical distances among localities and from divergent clades.Analysing Didelphis aurita and D. albiventris are omnivorous frugivores, while P. quica is an omnivorous insectivore, and all have overlapping diets [D. albiventris is a habitat generalist, while the other two species mostly occur in forested regions [D. aurita and D. albiventris occur in abundance in degraded areas [P. quica [D. aurita and D. albiventris explore different niches, this barrier may not have been sufficient to prevent gene flow between populations of A. raillieti in these hosts. We also observed a significant correlation between genetic divergence and elevation differences. The geographical distribution of D. albiventris is larger than that of D. aurita, as the former is a more habitat generalist and has greater climatic tolerance than the latter, which is also reflected in the elevation.Some ecological characteristics of the host species studied promote unfavourable conditions for the emergence of parasite population genetic structuring patterns. ng diets . They alng diets , 74. How regions , 76. In ed areas , unlike P. quica . AlthougP. quica  have shoP. quica and D. albiventris than between parasites recovered from P. quica and D. aurita, as the distribution of P. quica overlaps that of D. aurita but not completely that of D. albiventris [D. aurita and P. quica have niche overlap, compete [A. raillieti specimens recovered from P. quica and D. albiventris than between A. raillieti specimens recovered from P. quica and D. aurita. This may be because A. raillieti samples of P. quica were collected from a single locality, closer to D. albiventris than to D. aurita localities.Moreover, we expected to find greater genetic differentiation between parasites recovered from iventris , 29. As  compete , 28, and compete , all theA. raillieti populations, the nematode Trichostrongylus axei , a host-generalist parasite that infects multiple sympatric wild ungulates, showed no evidence of genetic structure associated with host species [T. axei populations would be structured due to the degree of spatial niche partitioning between hosts.As observed in  species . The autOligacanthorhynchus microcephalus  parasitizing three definitive hosts of the tribes Didelphini, Didelphis marsupialis, D. virginiana, and Philander opossum from different localities in Mexico. Phylogenetic analyses demonstrated a similar pattern to that found for A. raillieti, in which the specimens of O. microcephalus were grouped into three main clades, which were not correlated either with definitive host species or with geographical distributions. The lack of population structuring was attributed to several aspects, including host natural histories, dispersal abilities, sympatries, overlapping diets, and the fact that the arthropod intermediate hosts of O. microcephalus are distributed throughout the entire geographical range of this parasite.López-Caballero et al.  performeClimate changes, such as Pleistocene glaciations, promoted the retraction of tropical forests, forming refuges and the subsequent expansion of these forests due to climate amelioration. Populations from refuge areas that undergo postglacial demographic expansion have consequent genetic signatures , 80. TheIn our neutrality tests, parasitic specimens from the PTY-RJ, PET-RJ, CUR-PR, SGS-MG, and SAI-SC localities had significant negative values, some of which were negative for Tajima’s D or Fu’s Fs. This expansion signature was congruent with the genetic diversity indices, showing high haplotype diversity and low nucleotide diversity for the MT-CO1 gene for all groups studied . These results also showed that although there were many haplotypes, they differed from each other by only a few nucleotide substitutions. This pattern is consistent with a rapidly expanding population from a small effective population size .A. raillieti has a Neotropical and partially Nearctic distribution, future studies should include specimens from other biomes, encompassing its entire distribution range, to better understand the evolutionary history of this parasite. It would also be necessary to include nuclear genetic markers from independent loci to verify whether the phylogeographic pattern observed for the MT-CO1 gene is corroborated. Additionally, the inclusion of a time scale to estimate divergence times between clades would make it possible to verify congruence between cladogenesis and palaeogeographical and climatic events [Since c events , 82.A. raillieti populations in the South and Southeast Atlantic Forest was likely associated with historical events, such as past climate changes, and not with the host species D. aurita, D. albiventris, and P. quica or with the current geographical distribution of this parasitic nematode. We also observed greater morphometric variation than molecular structuring associated with host species and localities, suggesting phenotypic plasticity related to host functional traits, as well as to spatial variables.Based on our results, we concluded that the genetic structure of Additional file 1: Table S1. Municipality and state of origin, hosts, and GenBank accession number of MT-CO1 gene sequences of 175 A. raillieti specimens from this study.Additional file 2: Figure S1. Bayesian phylogenetic trees of partial MT-CO1 sequences of A. raillieti from this study and of aspidoderid species from GenBank. The sequence of Lauroia trinidadensis was added as an out-group. Clade I of A. raillieti is not collapsed.Additional file 3: Figure S2. Bayesian phylogenetic trees of partial MT-CO1 sequences of A. raillieti from this study and of aspidoderid species from GenBank. The sequence of Lauroia trinidadensis was added as an out-group. Clade II of A. raillieti is not collapsed.Additional file 4: Figure S3. Bayesian phylogenetic trees of partial MT-CO1 sequences of A. raillieti from this study and of aspidoderid species from GenBank. The sequence of Lauroia trinidadensis was added as an out-group. Clade III of A. raillieti is not collapsed.Additional file 5: Figure S4. Bayesian phylogenetic trees of partial MT-CO1 sequences of A. raillieti from this study and of aspidoderid species from GenBank. The sequence of Lauroia trinidadensis was added as an out-group. Clade IV of A. raillieti is not collapsed.