Homo sapiens interbred with other hominin groups. By the late 1990s, published genetic work had largely concluded that archaic groups made no lasting genetic contribution to modern humans; less than a decade later, this conclusion was reversed following the successful DNA sequencing of an ancient Neanderthal. This reversal of consensus is noteworthy, but the reasoning behind it is not widely understood across all academic communities. There remains a communication gap between population geneticists and paleoanthropologists. In this review, we endeavor to bridge this gap by outlining how technological advancements, new statistical methods, and notable controversies ultimately led to the current consensus.Questions surrounding the timing, extent, and evolutionary consequences of archaic admixture into human populations have a long history in evolutionary anthropology. More recently, advances in human genetics, particularly in the field of ancient DNA, have shed new light on the question of whether or not  According to this view, H. sapiens originated over 1 million years ago and speciation between regional subpopulations was prevented by substantial gene flow.H. sapiens, with subsequent global dispersal and rapid replacement of other hominin taxa at around 50,000–60,000 years ago (ka).H. sapiens and other hominin taxa during dispersals.H. sapiens and other groups while acknowledging the central role of Africa as the primary birthplace of the species  models. The multiregional model proposed significant continuity between BOX 1Adaptive introgression: The movement of genetic variants from one population or species into another that provide an evolutionary advantage to the population or species that acquires them.Allele: One version of a genetic polymorphism. For example, consider a single position in the genome that is variable in a sample between adenine (A) and thymine (T) nucleotides. A and T are referred to as the variant's two alleles.Coverage: The number of times a specific genomic position has been independently sequenced, or a genome‐wide average of this value across all positions for a given sequencing experiment.Effective population size: The hypothetical number of individuals that a population would need to contain in order to exhibit certain characteristics under an idealized model. This can be estimated from the amount of genetic diversity in a sample, among other features. For example, a population can have a census size of 9,000 but exhibit a low level of genetic diversity expected of an idealized population of only 3,000 individuals. Thus, this hypothetical population's census population size is three times that of its effective size.Genetic drift: The random change in allele frequency over time in a population due to stochastic variation from one generation to the next. The power of genetic drift on a population's evolutionary trajectory is inversely correlated with its effective population size.Haplotype: A group of alleles that tend to be inherited together from one generation to the next due to their physical linkage on a chromosome.Linkage disequilibrium: The statistical association between alleles at different positions in the genome, generally due to physical proximity and genetic linkage between loci.Locus : A specific region of the genome.Nuclear genome: The genetic information contained within the nucleus of the cell. In humans, it is comprised of 22 autosomal chromosomes and two sex chromosomes (X and Y). Because of recombination, which occurs on all chromosomes except the Y, an individual's nuclear genome represents thousands of independent loci that are informative about historical demographic processes.Mapping: The process of computationally aligning sequencing reads to a reference genome.Mitochondrial genome: A small circular piece of non‐recombining DNA that is contained within the mitochondria of the cell. It is transmitted from a mother to all her offspring  acting over generations.Population split: The point in time when two populations, derived from one larger ancestral population, cease to be governed by the same evolutionary processes. Once populations split, they continue to diverge over time.Recombination: The process by which chromosome pairs exchange segments during the formation of gametes. When it occurs normally, no information is gained or lost from the full complement of chromosomes, but new configurations of genetic variants can arise. In the parent, the grandparental chromosome pairs can recombine with each other, resulting in a recombinant chromosome that is passed down to the parent's offspring.Sequence divergence: The process by which genetic lineages accumulate mutational differences from each other over time. Sequences can diverge independent of population divergence or splitting.Single nucleotide polymorphisms (SNPs): Genetic variants in the identity of a single base in the genome.mitochondrial genome of 147 people from extant modern human populations supported a recent African origin based on the limited genetic differences among individuals from different continents, with the basal lineages being carried by Africans.coalescence times among sequences were dated to 50–200 ka, indicating a very recent common ancestry for all extant humans.autosomal DNA further corroborated the RAO hypothesis.Results from human genetic data began to weigh in on these debates in 1987, when a survey of the D‐loop section of the BOX 2mitochondrial genome is a small  stretch of non‐recombining DNA that is passed from mother to child through the mother's egg cell. Over evolutionary time, mutations accumulate in different mitochondrial lineages, which makes it possible to reconstruct past relationships between different groups and trace the genetic history of females in the population. The pedigree figure above left, which depicts females as circles and males as squares, shows the transmission of mitochondrial genomes  through the generations. Without recombination, offspring carry the same sequence as their mother, except when novel mutations occur.The human nuclear genome, but up to thousands of mitochondria that each contain several copies of their genome. Furthermore, because the modern human mitochondrial sequence was well known, it was feasible to target a phylogenetically informative region in an ancient specimen for sequencing using the older Sanger sequencing technology. For these reasons, mitochondrial aDNA quickly became an important source of information for studies of archaic admixture.Early aDNA studies found that, in old, degraded specimens, mitochondrial sequences were the most readily recoverable DNA/genetic material. This is primarily due to their abundance; each cell in the body carries only two copies of the effective population size than the autosomal nuclear genome and is subject to a proportionately stronger degree of genetic drift. Therefore, while the absence of archaic mtDNA lineages in modern humans was interpreted by some to indicate no introgression, this observation is in fact compatible with a substantial level introgression. This situation is illustrated in the figure below left, where introgression occurs at generation t1 with a small number of yellow Neanderthal mitochondrial sequences migrating into the modern human gene pool (red arrow). Over the next few generations, the frequency of the yellow mitochondrial eventually drifts to zero even in the absence of negative selection.However, mtDNA has limited power to conclusively answer whether or not archaic and AMH interbred. One reason is that, because it is only transmitted through the generations by females, the mitochondrial genome always has a smaller m), and decreases with the age of the gene flow event. In order to determine how many independent loci  would be needed to make a determination on the occurrence of admixture between modern humans and Neanderthals, Wall conducted a power analysis assuming a specific demographic model, and estimated that information from 50 to 100 independent loci would be needed.It is important to note that this illustration depicts only one possible iteration of the highly stochastic process that leads to new generations. Under this model, it is also possible that the yellow type persists in the human gene pool until the present day. The likelihood of this scenario increases with higher levels of initial migration  occurrence, a consensus that held until the first archaic hominin nuclear DNA sequencing results were published in 2006.The analysis of mtDNA led most geneticists to initially conclude that archaic introgression did not occur.ture Box . Non‐neuol Table . These v3mapping  them to a reference genome. By contrast, the Sanger sequencing method used in earlier studies required researchers to specify a genomic target region. This can only be accomplished if the entire region plus its flanking sequences are intact in the ancient sample. While Sanger sequencing had the capability of producing longer reads , this benefit was not often realized in aDNA studies where input DNA is typically already in fragments of 10s to 100s of bp long. On the other hand, NGS was designed to produce large quantities of short reads in parallel, which had the additional effect of driving down the sequencing cost per base.It was not always obvious that the full nuclear genome of an archaic individual would ever be sequenced. aDNA, if it survives in any appreciable quantity, is highly damaged and fragmented, which makes piecing long sequences together a major technological and computational challenge. However, the development of “next‐generation sequencing” (NGS) technology in the 2000s significantly mitigated this problem. One benefit of NGS is that individual loci do not need to be specifically targeted to be sequenced; it is capable of sequencing a random selection of all the fragments in a DNA sample. The resulting short reads can later be assembled computationally by These technological advances re‐opened the possibility of ancient genome sequencing, and in 2006 two competing research groups, who produced articles authored by Green et al. (from the Max Planck Institute for Evolutionary Anthropology) and Noonan et al. (from the Joint Genome Institute), published analyses of large amounts of Neanderthal nuclear sequence.BOX 3In 2006, the first two studies of a nuclear Neanderthal genome published significant quantities of ancient sequence and also inferred population genetic parameters such as Neanderthal‐AMH divergence time and relatedness.Noonan et al. estimated a human‐Neanderthal DNA sequence divergence date of 706 ka, while Green et al. estimated a date of 516 ka, with very little overlap in their 95% confidence intervals. Additionally, Green et al. estimated a divergence time between modern human sequences that overlapped considerably with their estimate of the human–Neanderthal divergence time. This result in particular should have prompted skepticism from the research team, considering the hominin fossil record, as well as previous mtDNA studies, which estimated the human‐Neanderthal divergence time to be 3–4 times older than the divergence among modern human sequencessingle nucleotide polymorphisms (SNPs), Green et al. also claimed evidence for substantial levels of Neanderthal introgression.allele by looking at the homologous site in the chimpanzee genome. Green et al. found that Neanderthals shared the derived allele with some modern humans at far more loci than they would have expected under a simple demographic model.By surveying a set of population split time to have been extremely recent (35 ka), while from the Noonan et al. dataset they inferred a much earlier date (325 ka). Furthermore, they found that the degree of sequence similarity between the Green et al. Neanderthal and modern Europeans suggested an extremely high Neanderthal admixture proportion of 94%.In a reanalysis of both datasets and using a uniform set of methods, Wall and Kim confirmed large inconsistencies between both studies.Strikingly, Wall and Kim also found that their estimate of the human‐Neanderthal divergence time from the Green et al. dataset changed depending on the length of the sequenced DNA fragment considered; using only short sequencing reads, their estimate was 696 ka, but the medium and large read classes yielded significantly younger divergence times.This case study serves to highlight the difficulties of working with hominin aDNA.4coverage, Neanderthal genome.In 2010, following their initial attempt to sequence Neanderthal autosomal DNA, researchers at the Max Planck Institute for Evolutionary Anthropology produced a full, low single nucleotide polymorphisms (SNPs) where the archaic genome shared the derived allele with one human genome, while another human genome carried the ancestral allele .The most highly publicized result of this 2010 article was that individuals from certain extant human populations contain a substantial amount, between 1 and 4%, of Neanderthal‐derived ancestry in their genomes  and one of the modern human populations but not the other (H1/H2) at biallelic sites that exhibit either an “ABBA” or “BABA” pattern. These are determined through comparison to an outgroup, in this case the chimpanzee (Pan). The chimpanzee state is assumed to be ancestral, and is denoted as “A,” while the derived allele is denoted as “B.” While this assumption may not always hold, such as in the case of recurrent mutations on the chimpanzee lineage, the effects of this type of misspecification are not expected to systematically bias this statistic, as long as mutation rates across human groups are constant.loci are tested for “ABBA” and “BABA” patterns, which do not follow the population tree and are thus expected to be a result of either introgression, ILS, or recurrent mutation. As the latter two processes are expected to affect all human populations equally, they should generate as many ABBA single nucleotide polymorphisms (SNPs) as BABA SNPs. In the equation above, c is either 1 or 0 based on whether the pattern is seen or not. To calculate D, the number of sites that conform to the ABBA pattern is subtracted from the number that conform to the BABA pattern and divided by the total number of sites considered. Thus, values of D that significantly deviate from 0  can support the presence of introgressed archaic ancestry in one of the modern populations.The D statistic was first used by Green et al. (2010) to demonstrate that Neanderthals appeared to be more similar to non‐African modern humans than Africans.f), but is simply an observation that parameterized demographic models can be compared with. Another method of obtaining a point estimate of f uses the S‐statistic, which is simply the numerator of the D‐statistic. The equation above and diagram below show how, in theory, the ratio between S‐statistics can be used to estimate f directly, where HnAfr is a modern non‐African human population whoseImportantly, the D‐statistic does not directly yield an estimate of the archaic ancestry proportion  of this archaic group to modern Melanesians, but no contribution to Eurasians  conditions typical of extremely high altitude environments.EPAS1 gene was most similar to the Denisovan.EPAS1 alleles with the Denisovan.EPAS1 haplotype variants were likely polymorphic in the ancestral human‐Denisovan population and underwent incomplete lineage sorting (ILS)  gene, which is involved in regulating brain volume, showed signatures of introgression.MCPH1 haplotype bearing many derived substitutions was identified in 70% of individuals in a global panel but was at low frequency within Africans. However, no archaic specimen sequenced to date matches the candidate non‐African version of MCPH1. This observation does not exclude the possibility that this haplotype has an archaic origin, as the genomes available for comparison represent only two of an unknown number of archaic species. They do, however, leave the status of MCPH1 in question.An under‐emphasized result of studies of the Neanderthal and Denisovan genomes is the lack of corroboration of genomic regions that had been previously hypothesized in earlier studies to be of archaic origin. For example, researchers suggested that the microcephalin , this process represents a type of molecular clock that tracks the number of generations that have passed since an introgression event; longer Neanderthal tracts in modern human genomes imply a more recent introgression event, and vice versa  declined from 3–6% to approximately 2%, implying strong selection against archaic genetic elements.f was an artifact of the statistic used in the original article, which failed to account for recent gene flow between modern human populations.f across individuals to zero, diminishing the efficiency of selection against Neanderthal ancestry and leading to f becoming relatively stable over time.Taking a genome wide‐perspective, Fu et al. analyzed aDNA from an AMH dating from 45,000–47,000 years ago and found that the proportion of Neanderthal DNA in AMH  were shown to carry the same alleles as modern humans.9m from the same observed data  neutral demographic model is not so extreme under a more realistic model. In this section, we outline other possible drivers of genomic signals resembling those that arise under archaic introgression Figure .9.1In studies of archaic admixture, ancestral human populations are often modeled as panmictic; that is, all members of the population choose a mate at random from among anyone else in the population. In reality, a multitude of factors  structure populations such that certain pairings on individuals are much more likely than others. There is strong evidence from AMH morphology to suggest that the ancestral population was structured within Africa.The authors of an early Neanderthal genome study point out that they could not distinguish between ancestral population structure and archaic introgression.9.2ILS refers to a discrepancy in the relationship between populations (or species) and genetic lineages. ILS and ancestral population structure are distinct concepts that can create similar patterns in genomic data. Over evolutionary time, both populations and genetic lineages generate trees through splitting and divergence Figure . In case9.3Balancing selection is a type of natural selection that maintains more than one haplotype in a population at intermediate frequencies over long time scales. This form of selection can occur if population‐level variation improves fitness, as in the case of HLA genes related to immunity, if the environment is fluctuating, or if individual heterozygotes are more fit than either homozygote, as with sickle cell anemia in malarial environments.9.4Contamination remains a problem in aDNA studies. Small amounts of modern contamination in archaic sequencing experiments can “modernize” ancient individuals, leading to incorrect inferences of population history and archaic admixture9.5When using a modern human reference to assemble genomes of highly diverged individuals, reference bias (or “mapping bias”) can occur. Reads in the sequencing library that are more similar to the reference are more likely to map, and thus be included in subsequent analyses Figure .112 Addi9.6Recent evidence has highlighted the importance of ghost admixture, that is, introgression with populations for which there is neither descendant group nor even fossil evidence, in hominin evolutionary history. Certain features of the available genetic data of archaic and modern humans are best fit by population genetic models that include introgression events with as yet unidentified groups.f based on pairwise allele counts (such as the ratio of S‐statistics) are prone to biases when introgression from ghost populations has occurred.Rogers and Bohlender showed that estimators of 10The field of aDNA and archaic introgression continues to rapidly expand as new specimens are sequenced, and novel laboratory and analytical techniques are developed. However, in the midst of these exciting advances, the statistical methods employed across studies often remain difficult to understand and to evaluate by non‐specialists.f, the fraction of our genomes of archaic origin, have been constantly revised in light of new data (Table Given the sheer quantity of discoveries being made each year, it has not been possible cover all interesting facets of ancient introgression. Other recent reviews take complementary anthropological perspectives and dive deeper into many of the topics raised here.ta Table . Finally11


Keyacris scurra, which was used in classical evolutionary studies in the 1960s. It had a wide distribution across New South Wales (NSW) and Victoria in pre‐European times but has now become threatened because of land clearing for agriculture and other activities. We revisited remnant sites of K. scurra, with populations now restricted to only one area in Victoria and a few small patches in NSW and the Australian Capital Territory (ACT). Using DArtseq to generate SNP markers as well as mtDNA sequence data, we show that the remaining Victorian populations in an isolated valley are genetically distinct from the NSW populations and that all populations tend to be genetically unique, with large FST values up to 0.8 being detected for the SNP datasets. We also find that, with one notable exception, the NSW/ACT populations separate genetically into previously described chromosomal races (2n = 15 vs. 2n = 17). Isolation by distance was detected across both the SNP and mtDNA datasets, and there was substantial differentiation within chromosomal races. Genetic diversity as measured by heterozygosity was not correlated with the size of remaining habitat where the populations were found, with high variation present in some remnant cemetery sites. However, inbreeding correlated negatively with estimated habitat size at 25–500 m patch radius. These findings emphasize the importance of small habitat areas in conserving genetic variation in such species with low mobility, and they highlight populations suitable for future translocation efforts.Conservation research is dominated by vertebrate examples but the shorter generation times and high local population sizes of invertebrates may lead to very different management strategies, particularly for species with low movement rates. Here we investigate the genetic structure of an endangered flightless grasshopper,  Keyacris scurra was an abundant invertebrate in southeastern Australia whose distribution has declined drastically leading to its current threatened status. Here we use SNP markers to show that the populations are highly structured across its remnant range but also that remnant populations contain high levels of genetic variation. Inbreeding levels, but not genetic variation, appear to be correlated with the size of habitat patches. Morabines represent a unique group of Australian flightless grasshoppers, with a characteristic matchstick‐like appearance. The morabines consist of ~250 species and 41 genera found across Australia on a range of plant types including grasses, trees, and shrubs  or 2n = 17 (with one of the autosomes split into two acrocentric chromosomes)  White, . Populat) White, .K. scurra was already threatened when he indicated that they consist of “relatively minute ‘islands’ in the general area within which the species occurs.” Most of these "ecological islands" studied by White were places which had escaped agricultural intensification and regular grazing, such as small rural cemeteries, small reserves, and railway cuttings  as far north as Orange. White  noted thThemeda triandra, usually predominates. This once dominant grass is removed by cropping and is grazing sensitive, and it now only dominates relict areas, which are often also refuges for other similarly sensitive plant species .The species appears confined to habitats of a special type in which the tall perennial grass, d White, . SuitablK. scurra, establish patterns of genetic variation in remnant populations, and consider associations between genetic variation and the extent of remaining suitable habitat. We resample areas where the species was previously found as well as new areas that appear to have suitable vegetation. Our results show a high level of genetic differentiation across regions even when these are relatively close together, evidence for genetic isolation by distance in both nuclear and mtDNA markers, evidence of inbreeding in some populations, and some genetic differentiation patterns unrelated to the chromosomal constitution of populations. We show that genetic diversity varies among populations, and we test whether this variability as well as inbreeding is related to the extent of habitat available in the proximity of the sampling sites. We find that even very small habitat patches may support populations with valuable genetic diversity, although increased inbreeding seems to relate to smaller habitat size.Here we use genome‐wide SNP markers to assess the genetic structure of 22.1K. scurra were collected from 17 locations from NSW and Victoria in 2019 for molecular work following an extensive survey to map the current distribution of this species  and with the approval of the Department of the Environment, Land, Water and Planning in Victoria following the rediscovery of the species from Omeo. Only a few individuals were collected from the smaller populations   Table . Grassho2.2® 100 Resin  method on the upper half of a grasshopper hind limb. Tissue was crushed with 2 × 3 mm glass beads and 200 µl of 5% (w/v) Chelex® 100 suspension using a mixer mill. Extractions were incubated for 2 hr at 60°C with 5 µl proteinase K (20 mg/ml)  and heated at 90°C for 10 min. Prior to polymerase chain reaction (PCR) amplification, extractions were spun at 14,000 rpm for 2 min, and DNA in solution was removed from just above the Chelex® resin.A total of 59 individuals were screened from the ACT and NSW  as well as Victoria  with all regions in Table 2, 2 units of Taq polymerase (New England Biolabs), 0.20 µM forward and reverse primers, and 4 µl of 1:10 diluted template DNA.Polymerase chain reaction was performed to amplify approximately 700 base pairs (bp) of the mitochondrial cytochrome oxidase subunit 1 (COI) gene using the primer combination LCO1490: 5'‐ggtcaacaaatcataaagatattgg‐3' and HCO2198: 5'‐taaacttcagggtgaccaaaaaatca‐3' , 40 cycles of denaturation at 95°C for 45 s, annealing at 53°C for 45 s and extension at 72°C for 1 min, and then a final extension step at 72°C for 5 min (1 cycle). All PCRs were conducted in Eppendorf Mastercycler S Gradient machines. PCR amplicons were sequenced from both directions using Sanger sequencing (Macrogen Inc.), and the chromatograms were analyzed using Geneious version 11.1.4 . DArTSeq™ DNA extraction,sequencing and SNP genotyping methods are explained in detail elsewhere  was supplied to Diversity Arrays Pty Ltd  for high‐density  DArTSeq™ assay. Eight samples were first tested with multiple restriction enzyme combinations, and an “optimal” set was determined based on the fraction of the genome represented, while controlling average read depth and the number of polymorphic loci  and the same number between stacks between individuals (n = 4). Genotyped SNPs were outputted to the VCF file format for read filtering.Following adaptor and barcode sequence trimming, raw fastq files of DArTSeq™ samples (HiSeq processing) were processed with the STACKs denovo_map.pl pipeline  with VCFtools  (in the case of heterozygosity), whether all SNPs or one SNP per sequence were included in the analysis, and whether all nucleotides including monomorphic nucleotides were included in estimates of heterozygosity. MAC rather than minor allele frequency was used, as recently advocated for population structure analysis  locus randomly selected from the datasets, all SNPs across sequences, or all nucleotides sequenced including those that were monomorphic. In the first approach, there were 2060 SNPs retained from 13,518 SNPs identified at MAC = 1 for the heterozygosity estimate, whereas when all SNPs were retained, there were 10,618 SNPs that contributed.All datasets were passed to the R “adegenet” package as genind objects for further calculations of heterozygosity and other statistics. Sites with only one individual were excluded from population measures but were included in individual heterozygosity assessments. The “Hs” function from “adegenet” was used to calculate expected heterozygosity for populations.2.4.4K values between K = 1 and K = 10 were investigated, with ten runs per value of K and K = 10 set as the maximum based on available computing resources. Results were passed to the program CLUMPAK for collation and summarizing and evaluated according to various K‐inference procedures to determine optimal settings  was conducted on the SNP dataset using the “pegas” amova function implemented in “poppr”  to check for isolation by distance. Mantel tests comparing distance matrices and genetic distance were also undertaken in “adegenet.”Pairwise  Goudet, . These w2.5https://www.phylo.org/) . Four independent Monte Carlo runs each with four Markov chains (MCMC) were done for 20,000,000 generations using random starting trees and a temperature parameter value of 0.1. Trees were sampled every 500 generations, and the first 25% of generations were discarded as burn‐in. The MCMC trace files were visualized and analyzed in the program Tracer, version 1.7.1  for incorporation of branch length and support value (BS for ML and probability for BI) information. Resultant files were then visualized using the R packages ggtree, version 2.0.4  and confirmed sequence identity using BLASTn sequence homology searches against the National Center for Biotechnology Information (NCBI) nonredundant nucleotide database (https://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastn&PAGE_TYPE=BlastSearch&LINK_LOC=blasthome). A haplotype network was generated using PopART version 1.7 (http://popart.otago.ac.nz) and the minimum spanning network option. This program was considered appropriate because we had no sites with missing data.For all CO1 coding sequences, we first performed amino acid translations and searches for premature stop codons in Geneious version 11.1.4  determined from heterozygosity estimates where MAC = 1 and an original filtering step where an equal number of individuals per population were maintained.Given the low vagility of the t radius . The com33.1r > 0.92). We therefore ran all further analyses with one SNP retained per sequence with all individuals considered, which maximizes the retention of variation in populations where sample sizes are small, but nevertheless allows all individuals from a population to be used in computing heterozygosity  varied from expected heterozygosity (He) in some cases as reflected by FIS computed as ((He−Ho)/He), resulting in some FIS values that were substantial and positive  (Table r = 0.89).There was a significant difference in heterozygosity among populations when heterozygosity of individuals was compared , suggesting that populations in smaller habitat patches are more inbred  and 3.33.3.1n = 17 populations , as determined from the earlier cytological work, fall apart from most of the populations but the other 2n = 17 sites  are not separated from the 2n = 15 populations, while two other 2n = 15 populations  also show some separation.The network diagram of mtDNA variation Figure  indicate3.3.2K = 6, separating the northeast, southeast, west, and central regions as well as distinguishing the outlying Cooma and Omeo populations . Based on the nuclear markers, the 2n = 17 Gundagai samples also fall close to the other 2n = 17 populations, unlike for the mtDNA markers. Apart from the Omeo and Cooma populations, the other 2n = 15 populations fell into two groups, but most individuals could still be allocated to sites, highlighting substantial differentiation across the sample sites even when these were quite close together. However Kambah Pool and Burra fell close together, as well as Windellama, Bungonia, and Gundary,  was regressed against geographic distance . Comparisons with the Cooma population were notable for falling above the line established from the other population comparisons, which is consistent with the high FST values for comparisons with this population  consistent with the IBD regression analysis.For analyses of IBD, e Figure  with then Figure . A Manter = 0.876, p < 0.001) in agreement with the nuclear comparison. A Mantel test also indicated a positive association between the nuclear differences among populations and the mtDNA differences .We also ran an IBD analysis on the mtDNA data by comparing the number of nucleotide differences between populations. A Mantel test on the mtDNA data indicated a significant association between geographic distance and nucleotide differences  may need to be excluded to avoid overgrazing of Themeda. And cemetery management groups could be consulted to ensure that suitable habitat is fenced and not regularly mowed. Management of the Omeo populations will be particularly important since these appear to comprise the last remaining stronghold of the species in Victoria and are genetically quite distinct.The value of small reserves in preserving invertebrates ; Funding acquisition ; Investigation ; Methodology ; Resources (lead); Supervision (lead); Writing‐original draft (lead). Vanessa White: Formal analysis ; Investigation ; Writing‐review & editing (supporting). Moshe Jasper: Formal analysis . Hiromi Yagui: Investigation ; Methodology ; Writing‐review & editing . Steve J Sinclair: Methodology ; Writing‐review & editing . Michael Kearney: Funding acquisition ; Methodology ; Resources ; Supervision ; Writing‐review & editing .Supplementary MaterialClick here for additional data file.


Zymoseptoria tritici were collected from sites within the Euro‐Mediterranean region subject to a broad range of climatic conditions. We tested for local adaptation, by accounting for the diversity of responses at the individual and population levels on the basis of key thermal performance curve parameters and “thermotype”  composition. The characterization of phenotypic responses and genotypic structure revealed the following: (i) a high degree of individual plasticity and variation in sensitivity to temperature conditions across spatiotemporal scales and populations; and (ii) geographic variation in thermal response among populations, with major alterations due to seasonal patterns over the wheat‐growing season. The seasonal shifts in functional composition suggest that populations are locally structured by selection, contributing to adaptation patterns. Further studies combining selection experiments and modeling are required to determine how functional group selection drives population dynamics and adaptive potential in response to thermal heterogeneity.Plant pathogen populations inhabit patchy environments with contrasting, variable thermal conditions. We investigated the diversity of thermal responses in populations sampled over contrasting spatiotemporal scales, to improve our understanding of their dynamics of adaptation to local conditions. Samples of natural populations of the wheat pathogen  We investigated the diversity of thermal responses in fungal plant populations sampled within the Euro‐Mediterranean region. We highlighted (i) a high degree of individual plasticity and variation in sensitivity to temperature conditions across spatiotemporal scales and populations; and (ii) geographic variation in thermal response among populations, with major alterations due to seasonal patterns. The seasonal shifts in functional composition suggest that populations are locally structured by selection and thus reveal two‐tier adaptive dynamics. The analysis of the plasticity and variation of thermal sensitivity across individuals, populations, and scales was conducted in the case of 22.1Z. tritici populations for the exploration of spatial and temporal components of thermal adaptation   to 5  years. These conditions reduced the potential effects of previous environmental acclimation , although such effects cannot be completely excluded. The strains were later confirmed to be genetically unique strains based on neutral genetic markers. We chose to consider 25 or 30 strains  per population instead of the minimum level of 15 identified on the basis of a rarefaction analysis  over a 4‐day period at 12 constant temperatures ranging from 6.5 to 33.5°C  was calculated according to the standardized specific experimental framework developed by Boixel et al.  describing in vitro growth rate as a function of temperature were established by fitting a quadratic function to the temperature–growth rate (or performance P) estimates for each strain: P(T) = Pmax + Curv(T − Topt)2 where Curv is a shape parameter (see Table Pmax), which informs on TPC height ; second, thermal optimum (Topt), which informs on TPC position at the peak performance ; and third, thermal performance breadth , which informs on the sensitivity of the response to temperature change around Topt (“width shift” modes of variation). The estimates of the minimum and maximum temperatures (Tmin and Tmax), which define limits of growth, were not retained for further analysis as they fell outside the range of temperatures tested. Differences in thermal responses were assessed in two successive ways: (i) differences in the range and mean values of Pmax, Topt, and TPB80, assessed with parametric or nonparametric  statistical tests for comparing variances and means; and (ii) typological comparisons grouping together TPCs with similar thermal characteristics  based on a K‐means clustering procedure applied to the covariation of Pmax, Topt, and TPB80 for all TPCs (Methods +), “cold‐adapted” (CA), “intermediate” (‐), “warm‐adapted” (WA), and “highly warm‐adapted” (WA+) that perform better at lower, low, median, high, and higher temperatures, respectively. When in quotation marks here and hereafter, the term “adapted” refers to this higher performance at specific temperature ranges  and, at this point, not directly to an assumption about the adaptation to the local environment in which they have been collected. A comparison of the distribution patterns in thermotypes across populations and scales was conducted to detect phenotypic differentiation based on chi‐squared tests on the observed frequency distribution of thermotypes.Thermal responses were phenotyped by determining the l et al. , which h Methods . This fu2.3Z. tritici populations were genotyped for 12 neutral genetic markers on DNA extracted from 50 mg of fresh fungal material from 5‐day cultures, following SSR amplification and sequencing in one multiplex PCR sample, and allele size annotation  were evaluated with random allelic permutation procedures in GENETIX  monthly averaged values of 1961–1990 climate normals  and geographic populations (on Topt and TPB80), on the basis of sensitivity analyses assessing the robustness of the conclusions to variations in the approximation of QST by PST , 9.6–25.1°C for Topt, and 2.8–30.9°C for TPB80, across all 350 strains. Individual thermal phenotypes are summarized in Figure t test, p > .05): P(T)seasonal = 0.30 − 0.00077 × (T − 18.3)2 vs. P(T)geographic = 0.30 − 0.00088 × (T − 18.2)2. Interindividual variation around this average TPC was greater for the seasonal than for the geographic scale, as demonstrated by the standard shift in TPC position along the x‐ and y‐axes . Interindividual variation within populations was similar at both the geographic and the seasonal scales, with equivalent variances for Pmax (x¯ ± 0.06 h−1 [SD] on average), Topt (x¯ ± 2.59°C [SD] on average), and TPB80 (x¯ ± 5.72°C [SD] on average) within the 12 populations . The populations may therefore be considered similar in terms of their individual variances for thermal traits. By contrast, they were not similar in terms of the corresponding population means, as significant differences were detected for Topt and TPB80 (p < .05) but not for Pmax .We observed a very high level of interindividual variation for the three thermal traits chosen to describe TPCs, within a range of 0.17–0.46 hs Figure  and the 3.2Topt (“cold‐ vs. warm‐adapted”), TPB80 , and Pmax (“low‐ vs. high‐performer”) dimensions . Indeed, regression analysis revealed a significant negative correlation between Pmax and TPB80 across all individuals . About 10% of individuals did not follow this pattern, with high values of both Pmax and TPB80. These high‐performer generalists  may be considered as “jack‐of‐all‐temperatures” as they perform well over the whole range of temperature covered in the experiment . This heterogeneous distribution was particularly pronounced for high‐temperature generalists , TPB80 , and Pmax .TPCs were classified into thermotypes with similar thermal responses  and TPB80 , but not for Pmax , for which no population differentiation was detected . There was a two‐degree difference in Topt between the IS population and the 7 other populations  were particularly abundant in the Dfb populations (RU‐KZ‐LV), as shown by their long‐tailed distributions skewed toward lower temperatures . The IS population was characterized by a higher TPB80 for its average population response than the other populations, particularly DK  were less abundant in Cfb populations (DK‐FR‐IR), which were characterized by a higher proportion of more highly specialist individuals  than the average , with a horizontal shift of Topt toward higher temperature of the order of 5°C (SPR1) and 2.3°C (SPR2) on average (Table +). WA+ strains were significantly more abundant in SPR populations  had a higher thermal optimum than winter subpopulations , thermal optimum (Topt), and thermal performance breadth (TPB80). This detailed characterization was made possible by the large range of temperatures and the high resolution of this experimental study , the extensive sampling strategy (350 strains from 12 populations collected within the Euro‐Mediterranean region), and the use of a dedicated and previously validated experimental framework based on turbidity measurements  compared with growth in axenic culture  an increase in the mean thermal optimum of a given population with the annual mean temperature of its location of origin; (ii) a particularly marked adaptation to high temperatures of the population sampled in Israel, consistent with the results obtained for another Israeli population investigated by Zhan and McDonald  but was generally more marked over the seasonal scale . These findings are particularly striking because the choice of geographic populations made it possible to cover three contrasting Köppen–Geiger climatic zones Figure . Samplin4.4Z. tritici populations collected from local wheat fields  in each phenotyped population , despite the clear patterns of adaptation observed for Topt and the large differences in environmental temperatures. This maintenance of diversity suggests that Z. tritici is highly tolerant to thermal variations . One possible explanation for this finding is that the substantial adaptation of populations to their environments  is hindered by a balance between gene flow and local selection  exemplified the extremely high diversity of Z. tritici populations, even at a very local scale and whatever their putative admixture and/or local adaptation characteristics, in line with previous population genetic studies ; a mean value that hides substantial differences in dispersal abilities and/or effective population sizes between fungal pathogens with reported data from low (FST = 0.02) to very high (FST = 0.9) genetic differentiation ; data curation (lead); formal analysis (lead); methodology ; software (lead); visualization (lead); writing – original draft (lead); writing – review and editing . Michaël Chelle: Conceptualization ; funding acquisition ; investigation ; methodology ; project administration ; supervision ; writing – original draft (supporting); writing – review and editing . Frédéric Suffert: Conceptualization ; funding acquisition ; investigation ; methodology ; project administration ; supervision ; writing – original draft (supporting); writing – review and editing .Supplementary MaterialClick here for additional data file.


Anopheles hinesorum is a mosquito species with variable host preference. Throughout New Guinea and northern Australia, An. hinesorum feeds on humans  while in the south‐west Pacific's Solomon Archipelago, the species is abundant but has rarely been found biting humans (it is exclusively zoophagic in most populations). There are at least two divergent zoophagic (nonhuman biting) mitochondrial lineages of An. hinesorum in the Solomon Archipelago representing two independent dispersals. Since zoophagy is a derived  trait in this species, this leads to the question: has zoophagy evolved independently in these two populations? Or conversely: has nuclear gene flow or connectivity resulted in the transfer of zoophagy? Although we cannot conclusively answer this, we find close nuclear relationships between Solomon Archipelago populations indicating that recent nuclear gene flow has occurred between zoophagic populations from the divergent mitochondrial lineages. Recent work on isolated islands of the Western Province (Solomon Archipelago) has also revealed an anomalous, anthropophagic island population of An. hinesorum. We find a common shared mitochondrial haplotype between this Solomon Island population and another anthropophagic population from New Guinea. This finding suggests that there has been recent migration from New Guinea into the only known anthropophagic population from the Solomon Islands. Although currently localized to a few islands in the Western Province of the Solomon Archipelago, if anthropophagy presents a selective advantage, we may see An. hinesorum emerge as a new malaria vector in a region that is now working on malaria elimination. This meRitchie, . Both AnAnopheles hinesorum—previously An. farauti 2, belonging to the Anopheles farauti complex. Although phylogeographic, behavioural and ecological studies have been performed on many members of this species complex  being found in coastal and inland habitats up to of over 1000 m above sea level . These HLCs were performed near (within 50 m of) productive larval sites, no one has yet been able to collect blood fed adults from these populations, and their hosts remain unknown. A previous study also showed that exclusive zoophagy in An. hinesorum is a derived trait, finding two distinct zoophagic mitochondrial (mtDNA) lineages  of a new mitochondrial lineage. Finally, it is possible that the initial population on the islands  evolved or already exhibited zoophagy and contained multiple mitochondrial lineages which subsequently became dominant in the north and the south of the Archipelago.Ambrose et al.  hypothesAn. hinesorum in the Solomon Archipelago are exclusively zoophagic, including populations from Bougainville and Guadalcanal  on humans  published in Ambrose et al. (n = 61). We develop 14 novel microsatellite primers for the species and generate microsatellite data from throughout the species range (n = 456). We include mitochondrial and nuclear microsatellite data from samples collected in human landing catches by Burkot et al.  for 60 individuals in this study. We aligned this with previously published homologous sequence data , multivariate analyses, estimation of fixation indices, a neighbour‐joining tree based on pairwise G′ST and AMOVA. Initially, we assessed population structure using the Bayesian clustering program STRUCTURE v. 2.3.4 . Sites where mosquitoes were sampled were used to define location priors for populations from Australia and New Guinea. In the Solomon Archipelago, we used the islands that individuals were sampled from as location priors. We ran STRUCTURE output through the CLUMPAK server  and K = 10 (predicted by the ‘Estimated Ln Prob of Data’). Additional STRUCTURE plots for all K values run can be found in Data We performed a variety of analyses to assess population structure of adegenet package , discriminant analysis of principal components  to retain for each analysis. For the full data set, we retained 80 PCs and ten discriminant axes (DAs), and for the Solomon Archipelago data alone (n = 177), we retained 30 PCs and 4 DAs. We present two types of plots that were generated from the DAPC: a composition plot (a bar plot—similar to a STRUCTURE plot) and pairwise plots of the first two discriminant axes.We initially defined populations (as requested by DAPC) based on results by Ambrose et al.  as well GST, G′ST and Jost's D, between the populations identified by STRUCTURE and multivariate methods. We plotted results for one of these indices (G′ST) in tabular form, as well as building a neighbour‐joining tree based on pairwise G′ST using the R package ape  in the data compared with the null (random) expectation.We used the program GenAlEx v.6.5  and is shared with individuals from the Papuan peninsula. The other haplotype falling in this group was only sampled in one larva collected from Ghizo. Thirdly, apart from Western Province, all newly sampled Solomon Archipelago COI haplotypes belong to the northern island lineage.The mtDNA haplotype network Figure  expands 3.2K = 2, STRUCTURE separated individuals from the Solomon Islands from individuals sampled from Australia and New Guinea, which form a single group. At K = 10, STRUCTURE identified two groups in Australia (Northern Territory and Queensland), four in New Guinea  and four in the Solomon Archipelago . DAPC analysis revealed evidence of eleven distinct clusters, in agreement with those found by STRUCTURE but with additional genetic differentiation between Guadalcanal and Nggela , between populations within regions  and between regions  and significantly lower than expected variance within samples  compared with the null model  population is the most distantly related at the nuclear level based on consistently high pairwise fixation indices relative to the other populations Figure . Within K2 also clearly separates the Solomon Archipelago from populations from Australia and New Guinea  and Santa Isabel (Solomon Islands) appear as closest relatives in the DAPC  and at least once in An. hinesorum  in a widespread zoophagic population in the Solomon Archipelago. Despite the southern and northern Solomon Archipelago mtDNA lineages being highly divergent, all populations from the Archipelago form a closely related group at the nuclear DNA level. These close relationships suggest that recent nuclear gene flow has occurred between them or that they share a more recent common ancestor than their mtDNA genomes suggest. The northern mtDNA lineage dominates the islands extending from Bougainville in the north to Nggela in the south, although several individuals sampled from Santa Isabel possess a haplotype commonly found on Guadalcanal (southern lineage). This pattern suggests either past connectivity between these islands or long‐distance migration of females.Three distinct evolutionary scenarios may have generated the observed pattern of exclusive zoophagy in two divergent mtDNA lineages of compoplots show mixed assignment of individuals from different islands in the Solomon Archipelago. Comparatively low fixation indices also indicate that recent gene flow has occurred. This result makes sense given that most islands of the Solomon Archipelago were connected by land bridges and formed a larger island known as Greater Bukida, separated from Guadalcanal by only 2 km of ocean at times of lowest sea level  of samples from this population fell into three genetically distinct and geographically defined groups: one from New Guinea (Papuan Peninsula) and two from the Solomon Archipelago (northern and southern lineages). One Western Province haplotype sampled in eleven individuals is identical to a sequence sampled from an anthropophagic population in New Guinea—the only case of haplotype sharing observed between Solomon Archipelago and New Guinean populations. This raises the possibility that female An. hinesorum from New Guinea were able to arrive in the Western Province of the Solomon Islands, reproduce with local mosquitoes, and in the process transfer anthropophagy to this island population.Recent fieldwork in Solomon Islands Western Province identified An. hinesorum from New Guinea to the Western Province. During the World War II Pacific engagement, American airbases connected the Western Province to New Guinea via airstrips in Lae and Milne Bay (the eastern point of the Papuan peninsula—see Figure An. hinesorum were abundant at these New Guinean airbase sites (Beebe & Cooper, There are two obvious recent dispersal routes for Even though a commonly sampled mitochondrial haplotype in the Solomon Islands Western Province is identical to a haplotype sampled in a New Guinean population—the only case of haplotype sharing between New Guinean and Solomon Archipelago populations—the nuclear microsatellites suggest the genomes of the Western Province population appear to be mostly of native Solomon Archipelago origin. This is shown by the close relationships at microsatellite loci between individuals from Western Province and the rest of the Solomon Archipelago. In mosquitoes, olfaction is the primary sense that governs host preference Takken, , and it An. farauti (Beebe et al., An. hinesorum from the Solomon Archipelago has serious implications for the transmission of malaria, especially if this phenotype spreads through other populations in the Archipelago. Anopheles hinesorum is common and abundant through the Solomon Islands showing larval site plasticity, and existing both inland and at elevation (Beebe et al., An. hinesorum through the Solomon Islands.Today, the only common species known to transmit malaria in the Solomon Archipelago is the coastally restricted 5An. hinesorum in the Western Pacific, clarifying population subdivisions. This lays the groundwork necessary to use this species as a novel model system for studying human host preference in mosquitoes. Large mtDNA divergences likely do not indicate species boundaries, as nuclear gene flow is evident between some highly diverged lineages in the Solomon Archipelago. Although we cannot be certain that exclusive zoophagy in the Solomon Island populations was transmitted between these divergent lineages via gene flow, our results suggest that gene flow between islands of the Archipelago has occurred. Further work is necessary to disentangle the hypotheses regarding the origins of zoophagy in the Solomon Archipelago. We detected New Guinean mitotypes in a recently discovered anthropophagic population from the Solomon Islands indicating that human‐mediated transport of the species may have resulted in anthropophagy being introduced to the Archipelago. The emergence of this phenotype may have ramifications for the epidemiology and transmission of malaria on the Solomon Archipelago; specifically, it may result in increased malaria transmission in inland villages.In this study, we have achieved a more complete understanding of population genetic relationships of The authors declare no conflicts of interest.Fig S1‐S3Click here for additional data file.Table S1‐S4Click here for additional data file.Supplementary MaterialClick here for additional data file.


Lycorma delicatula (White), the spotted lanternfly (SLF) is known to be native to China, India, and Vietnam, but after the first detection in 2004 as invasive in Korea, it was also found in Japan in 2008 and the United States in 2014. As a polyphagous sap-sucking insect, the SLF seriously damages the host plant by sucking phloem sap and producing honeydew, which causes sooty mold disease on leaves and this damage eventually results in an economic loss by reducing the quality and yield of the fruits. After the emergence and spread of SLF in Korea, it has not been confirmed yet where they came from and how they invaded from the source region. To infer the most likely source population for the Korean invasive populations, we investigated the population structure of SLF including its native region (China) and invasive regions (Japan and Korea) using 15 microsatellite loci which were previously developed. Our study set out to solve the correlation between the source and invasive populations of SLF, especially with regards to identifying artificial transfer possibly reoccurring in other invasive regions.Lycorma delicatula (White) suddenly arrived in Korea where it rapidly spread out in the central region of Korea and caused serious damage to grape vineyards. To trace the source region of its invasiveness, population genetic structures were compared between the native region, China, and the introduced regions, Korea and Japan. We examined 762 individuals from 38 different population collections using 15 microsatellite loci. Both principal coordinate and structure analyses displayed that the Chinese populations were separated into three subgroups which were located significantly far apart from each other. Among them, the Shanghai population was located closest to most Korean populations. Based on the genetic relationships and structures, it was revealed that the multiple introductions into Korea occurred at least three times. In addition, the Shanghai population was strongly estimated to be a source of initial invasive populations of Korea. In addition, analysis of the approximate Bayesian computation suggested simultaneous spread from two distant locations early in the invasion by artificial transportation of the host plants bearing egg masses. Our population genetics study can provide a precedent case with regards to identifying spreads by anthropogenic outcomes in other invasive regions. The occurrence of invasive pests is considerably increasing due to a large degree of human-mediated trades around the world ,2,3. An Lycorma delicatula (White), the spotted lanternfly (SLF), is known to be native to China, India, and Vietnam  was obtained using the ad hoc quantity, which is calculated based on the second-order rate of change of the likelihood [K was calculated using the online resource STRUCTURE HARVESTER 0.6.94 [STRUCTURE 2.3.4 was used to analyze the genetic structure of 38 SLF populations using a Bayesian clustering approach . We set kelihood . To corrR 0.6.94  that expR 0.6.94 . In addiR 0.6.94 . For eacR 0.6.94  with MonR 0.6.94 .δn), which is finally used to estimate the posterior distribution of parameters [δn = 40,000 (1%) simulated datasets closest to the pseudo-observed dataset were selected for the logistic regression, which are similar to the δn = 400 (0.01%) ones for the direct approach [A), mean genetic diversity for each group and between groups, genetic differentiation between pairwise groups (STF), classification index, shared alleles distance (ASD), and Goldstein distance.To estimate the relative likelihood of alternative introduction scenarios of the SLF, an approximate Bayesian computation (ABC) was performed for microsatellite data as implemented in DIYABC 1.0.4 . DIYABC rameters . The DIYrameters . To idenapproach . The sumHo) and expected heterozygosity (HE) values in Korean populations ranged from 0.172 to 0.500 and from 0.171 to 0.513, respectively, whereas in Chinese populations, Ho and HE values ranged from 0.413 to 0.548 and from 0.423 to 0.608, respectively. There was no evidence of significant linkage disequilibrium or frequency of null alleles. In HWE, there were significant deviations in KR09-GW, CN10-LA by heterozygote deficit, which was likely due to retaining numerous unique genotypes with private alleles within a population related to their relatively high HE. Values related to genetic  diversity were shown as generally higher throughout the native region than in the invasive regions. Gene diversity (HS) and mean number of alleles (NA) in Korean populations averaged 0.45 and 3.69, respectively, which were lower than those of Chinese populations, 0.51 and 4.26, respectively. Similarly, allelic richness  in Korean populations was slightly lower than RS (2.87 ± 0.38) in Chinese populations. Inbreeding coefficients (ISF) showed a non-significant difference between observed and expected heterozygosity in most populations, but some initial populations such as KR07-SL, KR09-GB, KR09-GW, etc. had relatively high ISF values in the invasive area.We successfully genotyped 762 SLF individuals using 15 microsatellite loci, which were found as all non-clonal MLGs . ObserveK = 4)) suggests that there are relatively different regional structures in combination of variation over time.To confirm genetic variance between the preordained groups, four cases were analyzed using AMOVA implemented in ARLEQUIN  Table 3Table 3. FST) among 38 different geographical populations  were relatively low (averaging 0.012), which was lower than FST within Korean populations (0.069).We estimated pairwise genetic differentiation (ulations . PairwisA result of PCoA  estimatep < 0.05 for Wilcoxon signed-rank tests) was detected in 19 invasive populations . In addition, the mode shift revealed a recent bottleneck in six invasive populations . Only KR10-KJ was estimated to bottleneck in both the SMM and mode shift.Although the bottleneck test should be cautiously regarded because the sample size for some populations was less than 30 individuals , signifir (correlation coefficient) of the Y-axis indicates that the genetically related group inferred to be distributed in a geographic boundary as the first initial section with a positive value. First, for the Korean group, the Mantel test for IBD to examine the correlation between genetic and geographic distance of the samples showed significantly lower correlation, with r = 0.078 (p = 0.010), than for the Chinese group (see below). When GD and GGD were pairwise compared in each sample at 10 km class . When GD and GGD were pairwise compared in each sample at 20 km class  and ΔK. In the all STRUCTURE results  [δn. To propose the most likely scenario of an invasive route of the SLF when introduced to Korea, ABC tests were conducted with four scenarios . The datnδ) , which rδn = 4000) to 0.036  with a 95% CI of 0.006–0.036 and 0.028–0.043, which assumes NG recently diverged from MG and both previously diverged from SG. Scenario 2 (δn = 4000) to 0.035  with a 95% CI of 0.006–0.032 and 0.028–0.043. Scenario 3 (δn = 4000) to 0.047  with a 95% CI of 0.010–0.047 and 0.024–0.036. Scenario 4 (δn = 4000) to 0.900  with a 95% CI of 0.904–0.961 and 0.886–0.914.As derived from the results , scenarienario 2 B, which enario 3 C, which enario 4 D, which The ABC simulations based on the four alternative scenarios (1–4) for tracing the invasion route of the SLF gave strong support to the scenario 4 (mean posterior probability: 0.900–0.932) while the remaining other three scenarios (1–3) showed much lower posterior probabilities <0.036; . These sZhang et al.  found thThe Korean and Japanese populations showed relatively low genetic diversity, a typical low genetic diversity in the invasive populations ,52,53. ABased on the results of our population genetics , most ofBased on the results of the spatial autocorrelation  and IBD,Ailanthus altissima, so it seems likely that the settling and spread pattern will repeat advantageously around the zone where the host plants were densely cultivated [A. altissima, is commonly used for ornamental landscape trees, street trees, and embankments in China and Korea, so it is pointed out that its high density in the invasive range has been a major cause of the spread of SLF [A. alitissima is essential for lay eggs after mating [For the SLF to settle and re-spread, the host plant is most essentially limited to the overwintering host, especially ltivated ,54. Treed of SLF . Interesr mating . As the r mating . As withr mating , the spar mating  was relaOur results suggest that some populations of SLF in around 2009 have been introduced independently and intermittently into Korea, and afterwards, certain populations that appeared to dominate the genetic structure in 2010 had a large spread around that time. At the beginning of the invasion, the insignificant genetic differences and the significance of the bottleneck in the Korean populations support the rapid spread of a certain source population with high initial density. Most of the SLF populations dominantly found in Korea were due to the spread of individuals native to Shanghai, but apart from these, genetically similar individuals to Beijing and Tianjin were in Cheonan in 2006 (similar to the 2010 Japanese population), and those matching the Shandong region appear to have been found in Samcheok in 2011. Interestingly, considering that similar genotypes were occurring nationwide in Korea in 2010 and 2011, it is not possible to rule out continuous introductions from China, especially Shanghai, to Korea by the bridgehead effect  rather tA. alitissima, the main host plant of SLF, and it is very relevant to the initial spread that the seedlings possibly harboring SLF egg masses were imported in large quantities at that time [A. altissima seedlings were brought into Korea and divided into a nursery in one place . The seedlings were transported to geographically distant regions in Korea, and the spread of the SLF introduced in the form of the egg mass was a cause that could occur simultaneously [The situation of the SLF introduction in Korea was estimated as the import of the seedlings of hat time ,15. As ahat time ,58. Initaneously ,20. The Population genetics studies of this invasion propagation process may be necessary for regions where SLF has invaded, particularly in North America, because they can help identify unnatural spreads that are anthropogenic outcomes . Their e


Aedes albopictus, has spread around the world. The migration was mainly mediated by maritime transportations. This species is known as an efficient vector for arboviruses, and it was responsible for the recent dengue outbreak in Tokyo, Japan. As the vector competence varies among geographical populations, and insecticide resistant populations have emerged, it is important to reveal their movements. The present study uses molecular techniques to search for a sign of introduction of an exotic population in three major international seaports on Kyushu Island.The Asian tiger mosquito, Ae. albopictus were sampled around the international seaports of Fukuoka, Kitakyushu, and Nagasaki. Pairwise fixation indexes were estimated between the sampled populations based on 13 microsatellite markers. There was no clear genetic differentiation between distant and port populations in Kitakyushu and Nagasaki. However, the analysis found one distinct group near the container terminal in Fukuoka, which handles international freight containers mainly from adjacent countries. DNA samples were also obtained from Goto, Tsushima, Honshu, Ryukyu, Thailand, and the Philippines; and a cluster analysis and discriminant analysis revealed that the distinct group in Fukuoka did not belong to these groups. Combined with the results of phylogenetic analysis based on CO1, these results implied that this group originated from one Asian temperate region outside of Japan. Neutrality test and mismatch distribution analysis suggested that the establishment of this group was not recent.Adults of Ae. albopictus introduction from a temperate region of Asia through maritime freight container transportation. The genetically distinct group found in Fukuoka likely originated from a temperate region outside of Japan. Maritime container transportation may introduce to Japan mosquitoes with greater vector competence/insecticide resistance. This is the first study to describe the spatial population structure of Ae. albopictus in Japan using molecular techniques.The present study found a sign of  Aedes albopictus is an invasive species and an efficient disease vector. The bioecological traits of this species and human-mediated transportations have fueled its worldwide spread. Because the levels of vector competence and insecticide resistance vary among geographical strains, the worldwide migration of this species is a concern for public health and vector control. While numerous studies have been done in non-native areas, within its native areas in Asia movements have not been explored. This study used molecular techniques to search for signs of introduction of an exotic population through three major international seaports on Kyushu Island, Japan. The present study found a genetically distinct group of Ae. albopictus near the container terminal in Fukuoka. The study suggests that its origin was one temperate region of East Asia outside of Japan, and the establishment of this group was not recent. As vector competence varies among different populations and the knock down resistance gene has been reported from some populations outside Japan, the risk of introducing mosquitoes with greater vector competence/insecticide resistance needs to be considered. This is the first study to describe the spatial population structure of Ae. albopictus in Japan using molecular techniques. Aedes albopictus , is indigenous to East Asia [The Asian tiger mosquito, s Skuse, 894, is iast Asia . Becauses Skuse, 894, is iast Asia , this spast Asia ,7. The mast Asia . For insast Asia . The mosast Asia . The GloAedes albopictus is an efficient vector for arboviruses [Aedes aegypti [Ae. albopictus, Japan is not endemic for the arboviral diseases transmitted by this mosquito. However, occasional autochthonous transmissions of dengue viruses (DENVs) occurred in 1942–1944 [Aedes albopictus is able to pass DENVs to progeny transovarially [oviruses ,2, and ioviruses –12. In Ioviruses ,14, and  aegypti . Despite942–1944 , and mos942–1944 ,18. Althvarially , which mAe. albopictus varies among different geographical populations [Ae. albopictus had lower competence for dengue virus than populations from Malaysia and Hawaii [Aedes albopictus populations in Japan lack the knockdown resistance (kdr) mutation in the voltage-gated sodium channel (VGSC) [kdr has been reported recently from China, Singapore, and other locations [Ae. albopictus has been conducted, while invasions of Ae. aegypti in international airports in Japan are occasionally found by larval research and ovitraps [Ae. aegypti cannot overwinter in Japan [Ae. albopictus is greater because of its overwintering ability by diapause eggs. Thus, for risk management of arbovirus transmissions in Japan it is important to monitor Ae. albopictus introduction at international entry points. However, unlike the situation for Ae. aegypti [Ae. albopictus morphologically from local populations. To identify introduced individuals from local populations, genetic analysis using molecular markers such as microsatellites is a suitable method. High polymorphism has been observed in some determined microsatellite loci of Ae. albopictus [As the vector competence of ulations ,22, the d Hawaii . Aedes al (VGSC) . Howeverocations –29, and ovitraps . Considein Japan , the thr aegypti , it is ibopictus  and prevbopictus ,34, USA bopictus , and Eurbopictus . In Germbopictus .Ae. albopictus. Introduction of foreign mosquitoes would influence the genetic structure of the local Japan populations, and might lead to a transformation of vector competence and insecticide resistance, thus complicating arbovirus transmission and vector control. The present study hypothesized that maritime transportations facilitate the introduction of exotic Ae. albopictus individuals to Japan. To test this hypothesis, we used microsatellite and cytochrome c oxidase subunit 1 (CO1) molecular techniques to explore the possibility that exotic Ae. albopictus has entered the major international seaports on Kyushu Island. Specifically, this study determined if the genetic structures of Ae. albopictus populations in the seaports and their vicinities are distinct from those of other local populations. The study also inferred the origins of the seaport populations by comparing their genetic structures and phylogeographic relationship with those of other Japanese and oversea populations.Japan and adjacent countries have a lengthy trading history, with long-term and fixed traffic patterns. Cargo entering Japan by ships greatly exceeds that by airplanes, thus increasing the chance of the importation of exotic Ae. albopictus from abroad, we compared the genetic structure of adult mosquitoes collected in three cities on Kyushu Island, Fukuoka, Kitakyushu, and Nagasaki, the locations of the busiest international terminals. Accordingly, it was sought to observe genetic differences between ship terminals and distant areas due to a population introduced via maritime transportation. In each city, three areas were designated for sampling: two areas around the terminals and one distant area. Fukuoka has two large container terminals; Island City Terminal and Kashii Park Terminal. These terminals are located next to each other in the northern part of Hakata Port  collected in 2013 and from Ryukyu Islands (four islands) collected in 2017 and 2019, which deposited in the Institute of Tropical Medicine, Nagasaki University . Extracted DNA was genotyped based on 13 microsatellite primers according to Beebe et al. . A 10 μla), the number of effective alleles (Ne), and the observed (Ho) and expected  values of heterozygosity were calculated using GenAlEx  using Genepop (ver. 4.7) [st was conducted using stats package in R (ver. 4.0.2). The difference in genetic variation among three areas in each city was assessed using an analysis of molecular variance (AMOVA) (Arlequin ver. 3.5.2.2) [Fixation index (F), allelic richness (Ner. 4.7) ,41 with 3.5.2.2) . The ana3.5.2.2) ,44. The 3.5.2.2) . The bes3.5.2.2) . Members3.5.2.2) ,48.Mitochondrial DNA cytochrome c oxidase subunit 1 (CO1) sequences were determined to investigate the genetic structure in Japan and to estimate the origin of a distinct population. To examine the CO1 polymorphisms of samples, DNA was amplified with two set of primers developed by Zhong et al. : 1454F (Fs statistics [Hri) [A TCS haplotype network was constructed using PopArt1.7  with 1000 iterations ,52. Deviatistics  and Tajiatistics , which watistics  and DnaSatistics  under thcs [Hri)  and the cs [Hri) .Ae. albopictus. Only sequences that were hit with over 95% query coverage were used, by means of LC591859 as a query to conduct a blastn screen. A total of 524 sequences were retrieved. The analysis used only sequences that were found in the indigenous areas and after trimming had at least one identical sequence in other sources. The tree topology was visualized with FigTree (ver. 1.4.4) [To detect putative sources of introduced populations, a phylogenetic tree was constructed using Bayesian inference (BI) with the Markov Chain Monte Carlo (MCMC) algorithm on BEAST (ver. 1.10.4) . Ten mil. 1.4.4) .Ae. albopictus adults was collected from 55 sites  of Fst values were over 0.05. Low Fst values (<0.05) were observed among five populations in the container terminal area (FU1 –FU5) except that between FU2 and FU3 . Fst values among eight populations in the distant area (FU11 –FU18) were also low with 89% (25/28) of the values less than 0.05. Five populations in the Chuo terminal area showed a moderate genetic difference with four of ten Fst values more than 0.05. Fst values between populations of different areas were relatively high with 61% (64/105) of the values more than 0.05 (st<0.05) within and between the areas (st < 0.05) within and between different areas , while most genetic variation occurred within populations. Post-hoc pairwise comparisons indicated that genetic differentiation was greatest between the container terminal area and the distant area . The genetic differentiation was also significant between the container terminal area and the Chuo terminal area  and between the Chuo terminal area and the distant area . These results suggested that three areas were genetically structured respectively, and the container terminal area was more distinctive than the other two areas. In Kitakyushu, the percentage variation among different areas was small and not significant . Likewise, the percentage variation among the three areas in Nagasaki was small and not significant .When an AMOVA was run for 18 populations in three areas in Fukuoka, the percentage variation among the areas was 3.4% , but Fukuoka B was more genetically similar to other Japanese populations except for the Ryukyu Islands. The Fst values with the Philippines, Thailand, and the other groups in Japan were all over 0.05 (P < 0.01) for Fukuoka A populations . The most common haplotype in Fukuoka B (82/196) was H29, and it was less common in Fukuoka A (15/93) . However, unlike the results of the microsatellite analysis, the Fst analysis based on haplotype composition did not clearly divide the Fukuoka populations . Thailand (H1-12) and Philippines (H13-16) did not share haplotypes with each other or with the Japanese populations H17-92; . Among tulations  Tables.Fs suggested a demographic expansion of Fukuoka A (P < 0.01), but the analysis with Tajima’s D did not suggest the expansion (P > 0.05)  . The bimong time .The phylogenetic tree showed that the most common haplotype H52 in Fukuoka A belonged to haplogroup A1a2 which occurs mainly in the temperate regions of East Asia and some colonized areas such as Europe and North America. All other haplotypes found in Fukuoka A belonged to A1a1 or A1a2, which also occur among the populations in the temperate regions of East Asia and the colonized areas. None of the Japanese populations in the present study harbored haplotypes belonging to A1b, A2, or A3, which occur mainly in the tropical populations of this species .Ae. albopictus (Fukuoka A) in the vicinity of the international terminals in Fukuoka. The five populations near the container terminal (FU1-5) showed distinctness in Fst and Fct values based on microsatellite analysis. Another population near Chuo terminal (FU6) was similar to these five populations in cluster and discriminant analyses. As Fukuoka A and B are separated by less than 3 km without physical barriers such as a hill, it is plausible that Fukuoka A originated from outside of the study collection areas rather than being derived from Fukuoka B parapatrically. The establishment of Fukuoka A appears to have been too recent to mix genes homogeneously with the local population. However, the results of Fu’s Fs tests, Tajima’s D, and the atypical shape of mismatched distribution suggest that it was not a recent introduction event. The genetic feature of the introduced population endured rather than vanished, possibly because the population size of the founder was not small, the frequency of introduction was not low, or the introduced individuals could reproduce in suitable breeding sites without conspecific species.This study identified one genetically distinct group of st < 0.05, st showed that Fukuoka B was similar to Kitakyushu, a neighbor city (45 km apart) of Fukuoka. The genetic structure of the island populations (Goto and Tsushima) was similar to Nagasaki populations, possibly the result of historical human-mediated transportations. These results indicate a general intraregional-associated genetic pattern in Japanese Ae. albopictus such that close populations showed genetic similarity. However, the genetic profile of Fukuoka A did not fit that intraregional-associated pattern; and was genetically quite dissimilar from other Japanese populations regardless of geographical distance, as tested by Bayesian clustering, discriminant analysis, and Fst. Fukuoka B is the most genetically similar population to Fukuoka A, but this is presumed to be caused by some limited degree of gene flow between the two groups. Considering that Fukuoka A was distributed near the international terminal, it is likely that the origin of Fukuoka A was outside of Japan. We cannot deny the possibility of the introduction from other areas of Japan such as northern Honshu, Shikoku, and Ogasawara islands. However, it is difficult to propose that Fukuoka A populations were introduced from those areas; considering that the northern Honshu population has expanded recently from the Honshu population [Ae. albopictus in Japan and might yield more signs of possible introduction.It is of interest to determine the origin of Fukuoka A. Our results showed that Fukuoka A was genetically different from the other Japanese and tropical populations. Other Japanese populations except for Ryukyu Islands showed small genetic differences  and all other haplotypes of Fukuoka A were within clades of roughly temperate areas excepting several tropical areas containing colonized regions. Moreover, according to the definition of a haplogroup per Battaglia et al. , we assibopictus . Also nobopictus , and thebopictus , and theAe. albopictus. This notion is explained by the amount of container cargo handled by the Fukuoka container terminals. The Fukuoka terminals are located next to each other, and their combined cargo traffic is 6 to 7 times greater than each Kitakyushu terminal. The amount of cargo handled by the Nagasaki terminal was relatively small. Although the Fukuoka Chuo terminal and the Nagasaki terminals host the first and second largest numbers of cruise ships in Japan, respectively, the results suggest that mosquitoes are less likely to be introduced by cruise ships. Closed freight containers may provide more protected space for trapped mosquitoes, while cruise ships have better hygiene and open environment to the sea, which may reduce the chance of importing mosquitoes. The high volume of cargo shipping in Fukuoka might enhance the opportunity for introduction of exotic Ae. albopictus. Furthermore, if a population is introduced from a similar temperate environment, it might survive by repeated introductions in the seaport areas of Japan.A genetically distinct population were found in Fukuoka, but not in Kitakyushu or Nagasaki. This suggests that large introduction may be required to establish an exotic population. Frequent introduction may be related to transportation type and the nature and magnitude of cargo traffic might be better than passenger ships for facilitating international movement of kdr of Ae. albopictus in China [Most containers handled by the Fukuoka terminals originated from Asian countries, mainly China and South Korea. Those introduced individuals with greater vector competence/insecticide resistance should be given more attention. Specifically, there were several reports of in China ,28, and st values. The simulation by Hale et al. suggested that 25 to 30 individuals are needed to estimate allele frequencies with 5–9 microsatellite markers [Ae. albopictus, which will help to delineate a better picture of the worldwide movements of this mosquito species.The small sample sizes at some sites might have limited precise estimations of their F markers . Because markers  proposedAe. albopictus introduction through maritime freight container transportation. The populations found in the international container terminals in Fukuoka likely originated from a temperate region outside of Japan. However, the populations in the international terminals in Kitakyushu and Nagasaki were not genetically distinct from the other populations. As vector competence varies among different populations [Ae. albopictus in Japan using molecular techniques. Further study will give us more detailed information of population structure and ongoing introduction of this mosquito species in Japan.The present study found a sign of ulations , and theulations –29, the S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Tablea: mean number of alleles; Ne: number of effective alleles; Ho: observed heterozygosity; He: expected heterozygosity; uHe: unbiased expected heterozygosity; F: fixation index.Displayed are the mean values of each population and the standard error (SE). N: mean populations size; N(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.S1 FigOnly results supported by Evanno’s best K are shown. (A) indicates the cluster assignment with K = 2, red: cluster 1; and orange: cluster 2. (B) shows the cluster assignment with K = 8, red: cluster 1; orange: cluster 2; yellow: cluster 3; green: cluster 4; blue: cluster 5; purple: cluster 6; brown: cluster 7; and grey: cluster 8.(TIF)Click here for additional data file.S2 Fig1–18: FU1-FU18 colored by red; 19–25: KK1-KK7 colored by orange; 26–36: NG1-NG11 colored by yellow; 37–38: GT1-GT2 colored by green; 39–46: TS1-TS8 colored by light blue; 47–50: RK1-RK4 colored by navy blue; 51–53: HS1-HS3 colored by purple; 54: PHL colored by brown; and 55: THA colored by black.(TIF)Click here for additional data file.S3 Fignaturalearthdata.com and National Land Numerical Information (Administrative Area Data) @ Ministry of Land, Infrastructure, Transport and Tourism, Japan .Created by processing Free vector and raster map data @ (TIF)Click here for additional data file.