Bactrocera tryoni, is a major pest of Australian horticulture which has expanded its range in association with the spread of horticulture over the last ~ 150 years. Its distribution in northern Australia overlaps that of another fruit fly pest to which some authors accord full species status, Bactrocera aquilonis. We have used reduced representation genome-wide sequencing to genotype 359 individuals taken from 35 populations from across the current range of the two taxa, plus a further 73 individuals from six of those populations collected 15–22 years earlier. We find significant population differentiation along an east–west transect across northern Australia which likely reflects limited but bidirectional gene flow between the two taxa. The southward expansion of B. tryoni has led to relatively little genetic differentiation, and most of it is associated with a move into previously marginal inland habitats. Two disjunct populations elsewhere in Australia and three on Melanesian islands are each clearly differentiated from all others, with data strongly supporting establishment from relatively few founders and significant isolation subsequently. Resequencing of historical samples from one of the disjunct Australian populations shows that its genetic profile has changed little over a 15-year period, while the Melanesian data suggest a succession of ‘island hopping’ events with progressive reductions in genetic diversity. We discuss our results in relation to the control of B. tryoni and as a model for understanding the genetics of invasion and hybridisation processes.The Queensland fruit fly,  Bactrocera tryoni Froggatt, 1897; 'Qfly') is both a major pest of horticulture in Australia and some Pacific islands and a useful model for understanding genetic processes associated with range expansion and invasion1. Qfly was originally confined to the relatively wet tropical and sub-tropical east coast of Queensland (QLD) and the north eastern coast of New South Wales (NSW), with populations in the northern-most regions of the Northern Territory (NT) (nNT) and northern Western Australia (nWA) recognised by some authors as a distinct species, the Northern Territory fruit fly 4. Over the last ~ 150 years, however, B. tryoni has expanded southward in association with the development of horticultural industries5. No infestations of Qfly were reported in the Sydney area (latitude ~ 33°5′ South) before the twentieth century6, but by the 1960s Qfly were found in Gippsland in Victoria (latitude ~ 37°5′ South)7. Later expansions included incursions further inland in QLD, NT and southern Australia4, with opportunistic invasions into New Caledonia, French Polynesia, Pitcairn Island and Cook Island in the Pacific1. Given increasing trade and horticultural activities in Australia and the region, climate modelling suggests a high likelihood of further expansion, under both current and future climate scenarios9.The Queensland fruit fly  with some differentiation to the north and south. Moreover there was also a progressive divergence westward along the north coast into the northern parts of the Northern Territory and northern Western Australia (nNT/nWA). An apparently distinct and potentially isolated population in central Australia was also identified17. As noted, several authors have classified the nNT/nWA populations as B. aquilonis, which is mainly distinguished from B. tryoni by a slightly paler thorax and abdomen, and more pointed aculeus on the ovipositor20. However, Drew and Lambert19 noted that the differences in colouration ‘are so slight as to be of questionable value for species-level discrimination’, and Wang et al.21 reported a Nei’s genetic distance of just 0.014 between the two taxa based on microsatellites. Cameron et al.17 argued that the nNT/nWA populations are simply progressively extreme samples of an essentially continuous clinal pattern of genetic differences from the east coast populations. There is as yet no genetic data on the island populations in the South Pacific but a specific succession of ‘island hopping’ invasions has been proposed based on the dates of the first records on those islands; Qfly was first reported in New Caledonia and the Loyalty Islands around 1969, in French Polynesia a year later, and subsequently in Cook Islands 22.Broadly consistent with all the distributional and ecological data, early population genetic studies with microsatellite markers indicated significant genetic differences across the species range‘island hopping’ hypothesis and investigate the genetics of disjunct as opposed to continuous spatial range expansions. Finally, we discuss the relevance of our results to the ecotypic variation, future distribution and management of the Qfly.The present study explores Qfly/NTfly population structure from across the known geographic range using over two thousand single nucleotide polymorphisms (SNPs) generated from genome-wide reduced representation resequencing. We examine both the spatial and temporal dimensions of the invasion process within Australia by sampling expansions southwards and inland and sampling and resampling from the centre and margins of the earlier range over a 15–22-year interval. Additionally, we characterise extant Pacific island populations to test the 16. Some flies were collected as adults from lure traps  and then preserved in 100% ethanol. Others were collected as larvae from infested fruits, reared through to adults as part of the previous studies15 and then frozen at − 80 °C. Between four and 20 individuals were analysed per collection. Six B. neohumeralis (a closely related sister species in the tryoni complex) individuals which were used as an out-group in one analysis were collected from infested fruits from Cape Tribulation (16°08′ South), Brisbane (27°41′ South) and Mareeba (17°00′ South) and processed as per the Qfly and NTfly samples above. All flies were identified morphologically according to the species descriptions in Drew20, except that, like many of the previous authors, we could not consistently distinguish nNT/nWA flies from eastern states Qfly . Figure ggmap23 and ggplot224 in R version 3.6.1 (https://www.r-project.org/)25, with final edits in Inkscape 0.92.4, https://inkscape.org/).We sampled a total of 368 individuals from 35 localities between 2015 and 2018, and for six locations we also had a total of 83 samples from 1994 to 2003 courtesy of the earlier microsatellite-based studies26. PstI and SphI restriction enzyme digestion, ligation of < 200 bp fragments to a bar coding adapter, PCR amplification, and Illumina HiSeq2500 sequencing were completed following the DArTseq protocol of Georges et al.27. SNPs were called from the resulting sequence reads using the DArT analytical pipeline as described by Georges et al.27 and the resulting dataset was read into R, together with associated metadata, using the helper functions of the dartR R package28. Filtering of SNPs involved excluding those which were (a) not scored consistently in two replicate runs of the protocol , (b) had < 10 × or > 250 × read depth or c) a call rate < 90% . Filtering of individuals then involved excluding those with a call rate < 90% . Finally, we only retained one randomly chosen SNP from any sequenced tag containing multiple SNPs. After filtering, the data from nine individuals in the N + E + D dataset (see below) were excluded, as were 23 individuals from the temporal dataset (the nine above plus four more from the 2015–2018 samples and ten from the 1994–2013 samples).Individual flies were transferred from ethanol or − 80 °C storage into 96-well plates at − 20 °C and sent to Diversity Arrays Technology Pty Ltd  for DNA extraction as per Kilian et al.Native range (N) populations: the 20 2015–2018 collections in the Native Qfly/NTfly range.Expansion (E) populations: samples from 10 populations in the essentially contiguous expansion southward and inland.Disjunct (D) populations: samples from Broome, Alice Springs, and the Melanesian islands, andTemporal data: samples from six locations, collected 15–22 years earlier (1994–2003) for the previous microsatellite studies, plus the 2015–2018 collections from the same locations.The analyses below were structured around four sets of samples:Depending on the question, the analyses below were conducted on the three spatial datasets  or the temporal dataset.29, which was implemented in the R package “adegenet”30 and used the localities sampled as priors for populations. The optimal number of Principal Components (PCs) to be retained was selected using alpha score optimisation with the optim.a.score function in the “adegenet” package, retaining 83, 77, 51, and 12 PCs from the N, N + E, N + E + D and temporal datasets, respectively ely Fig. . The Bayely Fig. .31) to estimate individual fly admixture coefficients. This involves an algorithm which is similar to the Bayesian clustering program structure32 but uses non-negative matrix factorisation and least-square optimisation to facilitate working with large datasets. The R package LEA31 implements this algorithm in the snmf function. The SNP data were converted first into a Structure-like input format with the gl2faststructure function from the dartR package and then into the required format for the snmf function with the helper function struct2geno from the LEA package. The snmf algorithm was run with K values for all the datasets, with 100 repetitions per K value and other options set to default values in all cases. The value of K that best explained the results was selected using the cross-entropy criterion as detailed by the LEA package authors31  against the geographical distance . Secondly, we conducted a redundancy analysis (RDA) of allele frequencies against polynomial functions of latitude and longitude  in this dataset as per Meirmans35. The overall model and specific functions within it were tested for significance using the anova.cca function from the vegan package34 with 1,000 permutations for each test. We then multiplied the percentage of variance accounted for by the latitude and longitude of each population (i.e. the constrained variance of the RDA) by the overall Nei’s D for all populations to obtain the percentage of the total genetic variation that is explained by the spatial variables36.We conducted two analyses to test for any isolation by distance in the N + E dataset. First we ran a Mantel test of the linearised genetic distances between populations  populations. We created an input file of allele frequencies for every contemporary sample according to the TreeMix manual. We then built a maximum likelihood tree from the allele frequencies using the default 500 SNP block setting, rooting the trees with B. neohumeralis and visualising them with the R script provided with the software38.We investigated the origins of the contiguous expansion (E) and disjunct invasion (D) populations by inferring a population tree from the N + E + D dataset using TreeMixgl.collapse.recursive function in the dartR package28. This method sums the fixed differences between each pair of populations and combines the members of each pair which do not have a significant number of fixed differences, where the number of differences expected due to sampling error is estimated from a thousand bootstrapping runs with the gl.collapse.pval function. The process is repeated until no further non-significant pairs are found28. The resulting set of collapsed populations can be thought of as diagnostic operational taxonomic units (OTUs) between which there is strong support for an absence of recent gene flow.We tested for fixed differences between populations in the N + E + D dataset using the 39 implemented in the gl.diversity function in the dartR package28. Additionally we calculated Fst between all populations in the N + E + D dataset with the gl.fst.pop function from the dartR package and tested their significance using 1,000 bootstrap replications.We also estimated genetic diversity summary statistics  for all populations, using the formulae of Sherwin et al.17 and contemporary populations collected from the same localities (Table dist in R) using the poppr.amova function in the poppr package and simulations with 1,000 permutations generated with the randtest function40. We then screened for changes within each population pair over the 15–22 years by calculating Fst between the two temporal samples from each locality with the gl.fst.pop function from the dartR package and testing their significance using 1,000 bootstrap replications.The temporal dataset contained six pairs of samples from previous Qfly population genetic studiesAfter quality filtering, the data comprised 2,785 SNPs for 359 individuals for the 2015–2018 samples for the spatial analyses and 2,344 SNPs  from 138 individuals for the temporal analyses (i.e. the six populations scored on both the 2015–2018 and 1994–2003 datasets).We used a combination of clustering (DAPC) and admixture coefficients (sNMF) analyses to test for differentiation among the 20 populations we sampled from the Qfly/NTfly native range . DA1 in the DAPC analysis accounted for 31.5% of the variance and separated most of the nNT/nWA populations from the QLD populations, with Darwin (DA) and Borroloola (BO) as intermediates. DA2, accounting for 16% of the variance, separated Darwin populations from the others Fig. . The croThe sNMF analysis including the southerly and north-western QLD populations  found a K value of two yielded the lowest cross-entropy Fig.  and show7, 283 = 3.31, P = 0.001). Most of the spatial effect was related to longitude , which is consistent with the distinction between the QLD and nNT/nWA ancestry groups. However, the low overall explanatory value of distance indicates there is also significant gene flow unrelated to distance and probably facilitated by horticultural trade among the native range and contiguous expansion populations.Consistent with a genetic structure suggestive of isolation by distance, a Mantel test of genetic vs geographic distance between all pairs of populations in the N + E dataset yielded a significant positive correlation with geographic distance . However, the redundancy analysis  samples identified the five geographically disjunct populations as genetically distinct Fig. . The thrB. neohumeralis as the outgroup , found no populations or groups of populations were distinguished by a statistically significant number of fixed differences , so it remains possible that the populations further west than those in our analysis are ecologically distinct from B. tryoni. There are several examples in the literature whereby insect species have retained ecotypic distinction in the face of quite high levels of genetic introgression42. The east/west transect covered here crosses a number of biogeographical barriers which have led to differentiation between closely related species of amphibians43, birds46, other insects48, mammals49 and plants50 across different geological periods52.There is little genetic differentiation across the native and expanded Qfly range down the east coast of Australia, but larger differences are evident along an east/west transect across the north of Australia. These results concur with the pattern of differences obtained in earlier allozyme54 that these southerly coastal populations would have derived from the adjacent native Qfly range rather than the more distant nNT/nWA.Populations from the southerly Qfly expansion down the east coast show little genetic differentiation from the north coast populations, except for progressively less evidence of nNT/nWA genotypes. This fits with an expectation8, and are the closest in our sample to a region previously recognised as a Fruit Fly Exclusion Zone (FFEZ)55  control programmes now under way in what was the FFEZ58 may benefit from using the adjacent populations as source material for their mass release strains.Although the differences are not large, the three more interior southern expansion populations, Griffith, Ardlethan and Shepparton, are all somewhat displaced from their coastal counterparts and more distinct from the nNT/nWA genotypes in the DAPC plot. These populations are in regions previously classified as ecologically marginal for the Qfly)55 Fig. . The FFEisland-hopping model in which flies migrated from the east coast of Australia into New Caledonia and Loyalty Island , which in turn became the source of migrants to the more distant Tahiti 22. Thus our data show a progressive reduction of genetic diversity . Our data did not identify the source of the other disjunct Australian population, Alice Springs, in central Australia. Notwithstanding its isolation it is not deficient in genetic diversity. This is evident in our temporal analysis, which shows the genetic composition of the Alice Springs population has changed very little in the 15 years between samples, suggesting its founding population was large enough to avoid bottleneck issues and there has been little immigration since.Given that all five of the disjunct populations show a level of genetic differentiation  indicative of low gene flow with other populations, they could all be good candidates for local eradication programs based on SIT.15 for ecotypic differentiation in relation to abiotic stress resistance. They only studied 12 populations, mostly from the east coast of Australia but also including Darwin, Alice Springs and Griffith. Darwin and Alice Springs were found to be distinguished by relatively high heat resistance, and Griffith by relatively high desiccation resistance, all of which is consistent with the genetic differentiation from the east coast populations evident in the present study. Among their ten east coast populations, however, Cape Tribulation  and Sydney (SY) were found to have relatively high desiccation resistance, and Sydney relatively high heat resistance as well, which would not have been predicted from our data. Furthermore, a separate sample of the Sydney population was collected and tested two years later for desiccation resistance and again found to have relatively high resistance, suggesting it was a stable, inherited feature of the population15. While our spatial analysis is based on over 2,700 SNPs taken randomly from across the genome, it can clearly miss phenotypically important genetic differences whose distribution across the species range departs from those seen from the overall trends evident in the summary statistics from our data.We can compare our evidence for genetic differentiation across the Qfly/NTfly range with the data of Popa-Báez et al.15 with those of Qin et al.59 on B. dorsalis, another widely distributed tephritid pest. They screened for differences in four taxa previously recognised as different species from a wide range of locations in Africa, Asia and Hawaii, using microsatellite and morphometric (wing length) analysis. Their microsatellite work revealed differences between the African and Hawaiian samples on one hand and the east Asian populations on the other, with only minor differences in wing length among their samples. In contrast, the stronger evidence of genetic differentiation and ecotypic variation evident in the current study and Popa-Báez et al.15 might in part reflect a greater power of our DArT data and the multiple stress response traits measured by Popa-Báez et al.15, but it could also indicate a stronger tendency for local differentiation in Qfly.It is interesting to compare the results presented in this study and Popa-Báez et al.Supplementary Information.


Sardina pilchardus populations offshore the Iberian Peninsula. We performed a seascape genetics approach that consisted of the high throughput sequencing of mitochondria’s ATP6, COI, CYTB and ND5 and five microsatellite loci on 96 individuals coupled with environmental information on sea surface temperature and dissolved oxygen across five sampling locations. Results show that, despite sardines forming a nearly panmictic population around Iberian Peninsula, haplotype frequency distribution can be explained by gradients of minimum sea surface temperature and dissolved oxygen. We further identified that the frequencies of the most common CYTB and ATP6 haplotypes negatively correlate with minimum sea surface temperature across the sampled area, suggestive of a signature of selection. With signatures of selection superimposed on highly connected populations, sardines may be able to follow environmental optima and shift their distribution northwards as a response to the increasing sea surface temperatures. Ongoing climatic changes, with predictable impacts on marine environmental conditions, are expected to trigger organismal responses. Recent evidence shows that, in some marine species, variation in mitochondrial genes involved in the aerobic conversion of oxygen into ATP at the cellular level correlate with gradients of sea surface temperature and gradients of dissolved oxygen. Here, we investigated the adaptive potential of the European sardine  As biological responses fall in the spectrum of “adapt, move or go extinct”, the range shifts, biological invasions and re-shaping of entire ecosystems, are thus expected to increase in frequency . The marte zones  and hypote zones ,5. Investe zones . Advancete zones . Coupledte zones ,9.On top of the environmental pressures imposed by climate change, marine species of commercial relevance are also subject to overexploitation. Unsustainable harvesting compromises the viability of stocks in multiple ways. For example, underestimating stock sizes leads to a logical reduction in the critical mass of spawners necessary to maintain population dynamics ; capturiSardina pilchardus is a small epipelagic fish inhabiting the north eastern Atlantic coast, the Mediterranean, and the Black Sea. It is a key component of the Mediterranean blue economy, supported by centuries-old tradition of consumption, and more recently, production of canned products [The European sardine products . Both thproducts ,22,23. CIn this work, we aim to investigate the adaptive potential of sardine populations surrounding the temperate zone of the Iberia Peninsula to fluctuations on sea surface temperature and dissolved oxygen. We focused on genetic variation at the mitochondrial level, as the mitochondrial genome encodes for genes involved on the oxidative phosphorylation (OXPHOS) pathway ,25. The A total of 96 individuals from 5 locations, Bay of Biscay (Spain), Gulf of Lion (France), Sesimbra , Olhão  and Tarragona (Spain) were collected, spanning the Atlantic-Mediterranean region surrounding the Iberian Peninsula . DNA wasTo explore whether the mitochondrial regions identified as putative under selection on other small pelagic fishes would exhibit similar signatures on sardines, 4 mitochondrial genes, each encoding different subunits involved in specific complexes of the mitochondrial respiratory chain were used: ND5 (NADH: ubiquinone oxireductase core subunit 5) for respiratory complex I; CYTB (cytochrome b) for respiratory complex III; COI (cytochrome c oxidase I) for respiratory complex IV; ATP6 (ATP synthase membrane subunit 6) for respiratory complex V. To facilitate the identification which within-gene regions should target sardines, we collected sequences from NCBI of other small pelagic species on which signatures of selection have been reported on our target genes. Those were then aligned with BioEdit  against Extracted DNA was sent to CIBIO (Centro de Investigação em Biodiversidade e Recursos Genéticos) in Vairão, Portugal, to primer optimization, library preparation and amplicon sequencing. The primer-pairs specifically designed for this study are available on bwa-mem algorithm [Demultiplexing, barcode removal and QC control were performed in Illumina’s Basespace online platform. Only reads with Phred quality score (Q) > 30 were utilized in this study. Demultiplexed reads were aligned against a reference, i.e., sardine’s mitogenome (reference NCBI: NC_009592.1) with lgorithm . Only relgorithm  through ST calculation . The level of significance was set to α = 0.05 [ST pairwise values in the R package ecodist, with the level of significance set to α = 0.05 [Haplotype diversity (Hd), number of haplotypes (nH), nucleotide diversity (π) and segregation sites (S) were calculated both independently for each gene in DNAsp . In totaα = 0.05 . Isolatiα = 0.05 . The numα = 0.05 .All computations were performed in the R environment . A Redunvegan [p-value = 0.0125). The overall statistical significance of the RDA model was assessed using an ANOVA-like permutation function, anova.cca, implemented in the in the R package vegan . Signifivegan . Lastly,As we were interested in screening for signatures of selection on each specific respiratory complex, a phylogenetic inference of events of selection was performed independently for each gene-specific dataset. As such, we utilized methods included in Hyphy via the Datamonkey web interface, which are based on the inference of nonsynonymous and synonymous substitution rates across phylogenies . A singlNuclear genetic variation was investigated with five microsatellites previously described in other sardine studies–SAB07, SAR09, SR15, SAR112, SAR218, and SP17 ,46. AmplK) that most likely explains the observed distribution of nuclear diversity implemented in the R package adegenet [K through the inflection point of the Bayesian Inference Criteria (BIC) curve and subsequent calculation of discriminant components. Lastly, we plotted the 95% confidence interval ellipses of the identified K groups overlaid on the original distribution. For that, we utilized the two major linear discriminants (LD1 and LD2) extracted from the discriminant analysis as graphical coordinates. We further estimated the pairwise FST among locations, derived from allelic frequencies in Arlequin v3.5.2.2 . Isolation by distance was also inspected and analyses were performed similarly to those described in the previous We first assessed the likelihood of each locus to be in the Hardy-Weinberg equilibrium (HWE), as consistent deviations could compromise assessment of neutral differentiation. HWE was computed per loci and population in Arlequin v 3.5.2.2. The possibility of population structure was then investigated through multiple approaches. First, we utilized a Discriminant Analysis of Principal Components (DAPC) to explore the number of clusters  was reported to be the subject of clinal selection along the Mediterranean . In thisStacks was inspected visually and utilized to construct haplotypes from the reference mitogenome. As genes were analyzed as fully independently, fragments were trimmed to remove uninformative invariant sites at the edges of the DNA string prior to population genomic analysis. Sizes of the fragments utilized varied across genes, specifically ATP6 (381 bp), COI (291 bp), CYTB (201 bp) and ND5 (330 bp). The 96 individuals sequenced for the four targeted genes produced a total of 912,609 usable reads. On average, 2223.84 (SE ± 128.96) paired-end reads per individual were utilized for the ATP6, 2599.17 (SE ± 115.99) for the COI, 2693.29 (SE ± 140.73) for the CYTB and 1990.04 (SE ± 97.33) for the ND5. Average coverage per individual varied from 304.07 (SE ± 18.80) on ATP6 to 208.19 (SE ± 9.22) at CYTB. The position of variant sites identified with S = 3.6, SES = 0.219; µnHap = 4.6, SEnHap = 0.219; µHd = 0.717, SEHd = 0.02; µπ = 6 × 10−3, and SEπ = 3 × 10−4), while the COI showed a high conservation rate . Among the sampled locations, genetic diversity was only pronouncedly different for the ATP6, as Tarragona and the Gulf of Lions reported a single haplotype in contrast to the Bay of Biscay and Sesimbra, where we observed three different haplotypes  and ND5 between Tarragona and Olhão . Investigating the overall number of haplotypes shared among locations revealed that closer sampled locations shared more haplotypes, suggesting that geographic distance might play a role in connectivity, despite the absence of clearly structured populations , and with an adjust R2 = 0.48 (p = 0.050) and the marginal effect of each environmental variable showed minimum sea surface temperature (sst_min) to be significant   .We further identified haplotype 1 of ATP6 and haplotype 3 of CYTB to present a significant negative correlation with (minimum) sea surface temperature b. Modelsp < 0.1), while FUBAR detected sites 53, 49, 24, 36, and 52 . For ND5, FEL detected site 58 (p = 0.05), while FUBAR detected sites 58, 64, and 90 . The Bayesian approach further identified four sites on the COI, namely, 8, 44, 53, and 57   . All the1,4 = 6.02, p = 0.01)  values ranged between 0.65 (SD ± 0.27) in Sesimbra and 0.74 (SD ± 0.16) for the Gulf of Lion. Rarefied allelic richness over all loci varied between Sesimbra (12) and the Bay of Biscay (13.44). Private allelic richness, and indicator of population-specific alleles, was also similar from one location to another, being the extremes Tarragona (1.18) and the Bay of Biscay (2.24). Garza-Williams index, which estimates the effects of potential bottlenecks from observed heterozygosity, also indicated a striking similarity across populations . Observe = 0.01) .ST comparisons further reinforced such a scenario as all but one showed a significant result, for p = 0.02 (FBay of Biscay vs Gulf LionST  = 0.05). While those locations are at the maximum geographic distance possible within our sampled sites, correlating geographic and genetic distances obtained no significant value. Lastly, STRUCTURE analyses also revealed panmixia . However, we detected averaged pairwise FST among comparisons and this varied significantly across loci  . Exploring the structure and explaining each locus, we did not observe significant departures from what would be expected from panmixia: CIs of the 95% ellipses largely overlapped in every locus . Pairwis < 0.01) B. Post-hEnvironmental alterations driven by the ongoing rapid climatic shifts impose intense selective pressures on populations of marine organisms, and particularly on those that are currently exploited. Understanding the response repertoire of those species is crucial to develop effective and sustainable exploitation plans to accommodate potential shifts in the distribution range and overall impacts on the viability of populations. By screening the variation on genes directly involved in metabolic performance, we aimed to infer the adaptive potential of sardine populations to shifts in temperature and dissolved oxygen. We observed a high degree of connectivity among populations and further revealed a putative molecular basis of adaptation to cold temperatures. Under the predicted increase in sea surface temperature, our results indicate that sardines might be able to follow environmental optima and extend their distribution northwards. ST pairwise estimate associated with microsatellite data between the Bay of Biscay and the Gulf of Lion. As Mantel tests did not support a general pattern of isolation by distance, we consider having identified a signature of limited dispersal among sampled locations, possibly due to the natural barrier imposed by the Alboran Sea, as suggested by Ramon and Castro (1997) [Genetic diversity estimates across investigated markers suggested the Bay of Biscay harboring higher diversity among investigated populations. At the mitochondrial level, three out of four genes (CYTB being the exception) exhibited a higher number of haplotypes and/or nucleotide diversity, and microsatellite markers consistently showed a higher rarefied number of alleles and private alleles among sardines collected on the Bay of Biscay. The expected a positive correlation between genetic diversity and effective population size and may simply suggest that the Bay of Biscay assembles a larger number of reproducing individuals in comparison to all others . The reso (1997) .Generally, our observations are consensual within the existing studies dedicated to sardine population structure in the region, though the majority suggests a sardine panmictic stock ,51,56, aExploring the role of specific environmental factors on the distribution of sardine’s mitochondrial diversity revealed that only minimum values of temperature and dissolved oxygen across sampled locations significantly explained the gradients of genetic variation. By showing that the distribution of the more frequently observed haplotypes of two of the targeted genes—ATP and CYTB—negatively correlated with minimum surface temperature, we can infer that the sardine stock in the screened geographical area is selected to tolerate colder sea surface temperatures. These results agree with previous works on mitochondrial DNA selection on other marine fishes, particularly on anchovies  and on AUnder and intense fishing pressure, the capacity for the European sardines to positively respond to ongoing climatic shifts must be resolved before developing practices of sustainable exploitation. Here, we focused on the European sardine stocks around the Iberian Peninsula and provided additional evidence for the existence of an apparent near panmictic population with a high degree of connectivity. This connectivity might be important to maintain frequency distribution of key mitochondrial haplotypes across the species distribution range, ensuring not only the species adaptive potential, but also an overall capacity to migrate to follow environmental optima: eggs and larvae of European sardine have been reported as North as the Baltic Sea . Strong Shifts in thermal conditions are particularly stressful for ectotherms. Additionally, there are certainly other mechanisms involved in a putative adaptive response to thermal variation. For instances, adaptive and non-adaptive phenotypic plasticity are known to play a decisive role in assisting organisms to cope with shifting temperatures ,71. Epig


Zea mays ssp. mays) is one of the most important crops in the world, with a long and a relatively well-documented history of domestication. The current consensus points towards a single domestication event from teosinte Zea mays ssp. parviglumis from the Balsas Basin in Southwestern Mexico. However, the underlying diversity of teosintes from Z. mays ssp. parviglumis and Zea mays ssp. mexicana was not taken into account in early studies. We used 32 739 single nucleotide polymorphisms (SNPs) obtained from 29 teosinte populations and 43 maize landraces to explore the relationship between wild and cultivated members of Zea. We then inferred the levels of gene flow among teosinte populations and maize, the degree of population structure of Zea mays subspecies, and the potential domestication location of maize. We confirmed a strong geographic structure within Z. mays ssp. parviglumis and documented multiple gene flow events with other members of the genus, including an event between Z. mays ssp. mexicana and maize. Our results suggest that the likely ancestor of maize may have been domesticated in Jalisco or in the southern Pacific Coast and not in the Balsas Basin as previously thought. In this context, different populations of both teosinte subspecies have contributed to modern maize's gene pool. Our results point towards a long period of domestication marked by gene flow with wild relatives, confirming domestication as long and ongoing process.The widespread use of genomic tools has allowed for a deeper understanding of the genetics and the evolutionary dynamics of domestication. Recent studies have suggested that multiple domestications and introgression are more common than previously thought. However, the ability to correctly infer the many aspects of domestication process depends on having an adequate representation of wild relatives. Cultivated maize ( For example, multiple domestication events with gene flow have been inferred for pigs, rice, barley, chili pepper and common bean –4. As a a) . ,7. a) [6ronments .Figure Zea mays species complex consists of four subspecies: the domestic maize (Zea mays ssp. mays (Schrad. Iltis) and three wild relatives collectively called teosinte. One of the wild relatives, Zea mays ssp. mexicana (hereafter mexicana), grows predominantly at high elevations (1600–2700 m) in the relatively dry regions of Central Mexico. Another wild relative, Zea mays ssp. parviglumis  is adapiglumis; . On the uatemala . GeneticGuerrero ,16–18.parviglumis somewhere in the Balsas Basin of Southwestern Mexico (1), Alcholoa (2) and Huitzuco (8) [The current paradigm for the domestication of maize points to a single origin from zuco (8) ,19,20. Szuco (8) , as wellzuco (8) . Howevermexicana; this introgression probably occurred in the past [parviglumis, its genomic composition is also a product of mexicana, particularly in maize growing in the Mexican highlands [. The introgression has probably obscured some of the historical features of the initial domestication of maize [parviglumis in some analyses [There are at least two factors that have complicated inferences about the domestication and evolution of maize. Multiple lines of evidence indicate that the adaptation of maize from the lowlands to the highlands was aided by introgression from the past ,24 and mthe past . Hence, of maize , includianalyses ,20. In sanalyses ,27.parviglumis as the ancestor of maize was unable to differentiate whether parviglumis from the Balsas or Jalisco populations were more closely related to the Mexican landraces of maize [parviglumis samples were from the Balsas populations [parviglumis included 34 plants from throughout the geographic distribution of parviglumis, but only five plants (20%) were from Jalisco, one from Nayarit, another from Colima and the rest mainly from the Balsas region [parviglumis diversity and therefore may have had limited power to identify the most likely origin of domesticated maize.A second complication is the location of maize domestication. The foundational isozyme study that established of maize . Subsequof maize . It is wulations . Similars region . The limMore recent genome-based analyses provide hints that the Balsas origin may not be correct. For example, a SNP-based study investigated the origin of maize by inferring maize ancestral allele frequencies and comparing them with those of extant teosinte accessions, showing that maize landraces from the Jalisco region have allele frequencies that were closest to the inferred ancestral maize allelic frequencies . This saA more recent analysis of population genomic data placed the time of divergence between maize and four Balsas accessions at approximately 75 000 years BP , which gparviglumis merits additional attention based on two additional lines of reasoning. The first is that parts of the state of Jalisco, like the Balsas Basin, have been identified as a potential refugia during the warm period of the mid-Holocene [parviglumis was distributed across the Jalisco and Balsas regions dating back to the last glacial maximum, approximately 21 000 years BP [Phaseolus vulgaris and possibly P. acutifolius) [. Thus, both climatological and cultural data suggest the possibility of maize domestication in the Jalisco-southern Pacific Coast region.Given the limitations of current analyses, we believe that the western distribution of Holocene . Moreoveyears BP . The secyears BP ), just ayears BP . Third, ifolius) –34. Thusparviglumis from the Jalisco region has been understudied, but recent population genetic surveys have included more Jalisco populations. For example, Pyhäjärvi et al. [parviglumis populations are genetically structured and that Jalisco populations generally contain high levels of genetic diversity. More recently, our group used the MaizeSNP50 bead chip to genotype 28 teosinte populations including a broad sampling of Jalisco [parviglumis populations and a strong genetic differentiation among Jalisco populations [Historically, i et al.  genotype Jalisco –18. Thesulations –18.parviglumis and mexicana , five populations from the Balsas Basin and two from the Pacific Coast of Oaxaca and Guerrero, with 43 maize landraces  and 30 673 SNPs [mexicana, parviglumis and other members of Zea and to investigate the history of introgression among the subspecies of Zea mays to propose an alternative domestication centre for maize.In this study, we combined genotypic data from 29 teosinte populations, which represent the entire range of cal, see ) and incable S2; ,36). Alt673 SNPs . We used2.2.1.mexicana and 13 populations of parviglumis for a total of 403 individuals, which covers the entire range of geographical and environmental conditions of both subspecies  were removed using Plink 1.07 [Zea luxurians (n = 6), Z. diploperennis (n = 6) and Z. perennis (n = 6) were added to some of the analyses, in order to have a proper outgroup for the Zea mays complex. Data was obtained from Trtikova et al. [SNPs were detected with the Illumina Maize SNP50 Bead Chip as described for maize by Arteaga et al.  and for  [et al. . Automatink 1.07 , for a ta et al. . The shaa et al.  yielded et al. [To evaluate the effect of ascertainment bias in our data, parallel analyses were performed using the genotyping-by-sequencing (GBS) teosinte and maize dataset from Swarts et al. , by filtet al. . The dat2.3.Z. luxurians, Z. perennis and Z. diploperennis as outgroups [Z. luxurians, and the resulting relationships were displayed with a network with the NeighborNet algorithm implemented by SplitsTree [Genetic differentiation was explored with a principal component analysis (PCA) with all the 30 673 SNPs of maize, teosinte and outgroups, using the package TASSEL 5 . A genetutgroups . The samutgroups , using alitsTree .K values tested ranged from 1 to 10, with 10 iterations each. The optimal K values were evaluated with the Evanno method [Genetic clustering analyses were performed with fastStructure . The numo method .2.4.Z. perennis and Z. diploperennis as an outgroup [http://bar.utoronto.ca/webphylip/) and visualized with FigTree v.1.3.1 (https://github.com/rambaut/figtree/releases). The analysis was carried out with the 30 673 SNPs dataset including the Z. perennis and Z. diploperennis.In general, it is difficult to discern between shared ancestral polymorphism and gene flow . To exploutgroup . Bootstroutgroup . The conmexicana [mexicana populations. We included all 403 georeferenced samples of teosinte (both parviglumis and mexicana) and 44 georeferenced maize accessions belonging to the following landraces of the conico group: conico (n = 30), arrocillo (n = 4), chalqueño (n = 5) and cacahuacintle (n = 5). The analysis was performed with TESS3 [To better represent gene flow between populations on a geographic scale, we performed a geographically explicit ancestry analysis using all teosinte populations, and ‘conico’ maize accessions which showed admixture in the fastStructure analysis and have been reported to have introgressed with mexicana ,26. Onlyth TESS3 . Unlike 3.a). The first was that there is a clear differentiation between maize landraces and the teosintes. These two groups were separated by the first principal component, which described 10% of the variation. This observation is initially surprising, since maize is derived from parviglumis, so one might expect the differentiation between maize and the teosintes would be lower. Nevertheless, this observation has been made previously with both ascertained , with the Jalisco populations from Telpitita (13) and Villa Purificacion (27) on the Pacific Coast forming a distinct cluster from the other Jalisco and Pacific Coast populations despite being geographically close (figure 3a).We first analysed genetic structure within our dataset with a PCA; this revealed three interesting features a. The fiSNPchip; ) and nonSNPchip; ) data. TSNPchip; . In figuobserved –18, parvparviglumis from Jalisco more closely to maize than most populations of parviglumis from the Balsas region except populations Teloloapan (1) and Alcholoa (2). In the dendogram, the northern Jalisco highland Guachinango (12) population is closest to maize. The network also highlights the intermediate position of certain parviglumis populations, in particular Tepoztlan (9) from the Balsas region . These results are very similar to those obtained with GBS data, where maize is clearly divergent from teosinte, and with some Balsas populations more related to mexicana in the dendogram , and with a Jalisco parviglumis population closely clustering with maize .We also constructed a dendogram of individuals, based on IBS over all loci. The network shows individuals strongly clustered by population and those branches were collapsed . Our results also place populations of analyses a. These parviglumis from Jalisco (and particularly from Guachinango 12) is introgression. We examined our SNPchip data for potential evidence of introgression among taxa and populations by first examining genetic structure, based on the fastStructure algorithm. For these analyses, K = 6 was the optimal number of clusters (b), followed closely by K = 7 . For K = 6, the outgroups (pink) form a distinct group, whereas mexicana is split in two groups correlated to altitude (light and dark blue), with a single very admixed population (Tepoztlan 9) found in a potential contact zone between parviglumis and mexicana. In parviglumis, we detected differentiation into several groups: a homogeneous lowland Jalisco group including two populations (lime green), a group of six populations from Jalisco and the Pacific Coast (dark green), and a very admixed group of five populations from Balsas including genetic components of highland Jalisco and Pacific parviglumis, but also of lowland and highland mexicana. High admixture between parviglumis and mexicana can be due to geographical proximity and has been previously reported [A second potential explanation for the close relationship between maize and clusters b, followreported .K = 6, maize is mostly homogeneous, with some landraces showing more admixture with mexicana and parviglumis. These landraces are mostly from the conico group found in the highlands of Central Mexico (12) and Toliman (28), which are not geographically close nor environmentally similar to highland maize, show introgression with maize. The second best grouping was K = 7, which split maize into two groups, but with no obvious structure  [mexicana .For l Mexico , where agure S3) . Overalland Z. diploperennisZ. perennis  as outgroups to infer ancestral states of alleles and to distinguish gene flow from shared ancestral polymorphism [et al. [parviglumis group , and by the low support of the relationships of some Balsas populations with either parviglumis and mexicana . Similar studies show that equal admixture proportions can indicate recent hybridization rather than ancestral polymorphism [To further explore the relevance of introgression, we inferred migration events in a maximum-likelihood framework , using Zmorphism . As no s [et al. , we used [et al.  producesis group . Overallanalysis b, and bymexicana , and by morphism ,50.Figumexicana population  to maize and another from maize to another mexicana highland population , another from lowland Jalisco (Villa Purificacion 27) to Z. luxurians, and one from maize to parviglumis from Guachinango (12), in Jalisco. The later explains the admixture proportions and genetic similarity of that population with maize and shows that introgression events did not happen homogeneously , and another from an ancestral mexicana from Jalisco (Jesus Maria 32) to maize. The ancestral nature of the later event is indicated by the position of the migration arrow along the branch, instead of the tip of the modern populations. Such ancestral introgression has also been confirmed in different studies [mexicana from central Mexico . However, gene flow between maize and parviglumis was not previously reported [parviglumis. Altogether, we have presented a novel analysis of genetic diversity and divergence in Zea mays, including wild and domesticated samples. Our PCA results show a high degree of genetic structure and differentiation of parviglumis populations , particularly the Jalisco lowland populations of Telpitita (13) and Villa Purificacion (27) on the Pacific Coast that form a distinct cluster. This genetic heterogeneity highlights the importance of having a dense enough sampling in the mountains of Jalisco, neighbouring Michoacan state, and the Pacific Coast, which have not been considered in previous domestication studies, despite the area's high biological and cultural diversity [Once ancestral polymorphism was identified, four main potential admixture events were detected  are distributed there and at least one of them (beans) was domesticated in the region . Moreoveed beans ,34,51. Ued beans . Howeverparviglumis populations, as opposed to the admixed Balsas populations of Teloloapan (1), Alcholoa (2) and Chilpancingo (5) , but a complex scenario with ongoing introgression and contributions from different wild relatives . It has been proposed that the introgression with highland mexicana populations allowed maize to grow in high-altitude central Mexico [figure 1c).Altogether, our results reveal an ancient divergence between maize and teosinte and a close relationship with the Jalisco-Pacific Coast populations. These populations (dark green; figures pancingo  (light gulations , and in tleneck (,19 ; figl Mexico , which m4.mexicana and parviglumis. These results highlight the importance of having a broad representation of potential wild relatives in order to understand the domestication process of modern crops. In the present example, the remarkable genetic differentiation of parviglumis populations means that sampling is crucial to identify the closest relatives to maize, as only the Western and Pacific Coast populations seem to share a gene pool with maize. Given the complexities of the gene flow patterns and the high probability that domestication of maize was a protracted and complex process, we can conclude that pinpointing a single geographic region as centre of origin for maize is a mirage and may never be solved, but we also suggest that the Balsas Basin in not a probable area for it.In conclusion, our results showed more introgression events than previously reported, between maize and western populations of A broader sampling strategy of maize wild relatives showed that the domestication process was long and complex, incorporating genetic material from different sources, from Jalisco and Pacific Coast of Mexico. The ongoing gene flow between maize and wild relatives, as well as the continuous improvement of landraces highlights the need to protect their wild relatives from genetic erosion and/or extinction, so they can remain a source of genetic diversity for future generations.


SLA-DRB1 locus diversity to that of internationally reported populations. Twenty SLA-DRB1 alleles were identified in the six populations analysed here using sequence-based typing. The amount of alleles ranged from six (Manta and Casco Mula) to nine (San Pedreño). Only one allele (01:02) having > 5% frequency was shared by all three commercial line populations. Allele 02:01:01 was shared by five populations (around > 5% frequency). Global FST indicated that pig populations were clearly structured, as 20.6% of total allele frequency variation was explained by differences between populations (FST = 0.206). This study’s results confirmed that the greatest diversity occurred in wild boars, thereby contrasting with low diversity in domestic pig populations.Analysing pig class II mayor histocompatibility complex (MHC) molecules is mainly related to antigen presentation. Identifying frequently-occurring alleles in pig populations is an important aspect to be considered when developing peptide-based vaccines. Colombian creole pig populations have had to adapt to local conditions since entering Colombia; a recent census has shown low amounts of pigs which is why they are considered protected by the Colombian government. Commercial hybrids are more attractive regarding production. This research has been aimed at describing the allele distribution of Colombian pigs from diverse genetic backgrounds and comparing Colombian  This makes them a good model for biomedical research in areas such as immunology, therapeutics, production and xenotransplantation; characterising their immunological systems will lead to advances in such disciplines6. MHC antigen presentation has been widely studied in various species regarding functions associated with the immune system7. Genetic diversity has been comparatively analysed in the Suidae family concerning Sus scrofa (wild boars) and their congener Sus scrofa domesticus (domestic pig), along with independent analysis12.Pig species are of great interest as a source of protein for human beings and due to their close relationship to humans in terms of anatomy, physiology and geneticsSus scrofa species; it is located on chromosome 7 and is formed by class I and class III (position 7p1.1) and class II complex regions (position 7q1.1)10. Class I and class II complex genes are related to immunity and inflammation and are characterised by being highly polymorphic4. Interestingly, the class II complex expresses proteins on the surface of antigen presenting cells (e.g. macrophages and dendritic cells); forming a protein complex, peptides anchored to the peptide-binding region (PBR) and the T-lymphocyte receptor (TCR) promote a humoral immune response17. SLA-DRB1  and SLA-DQB1  have the greatest polymorphism (https://www.ebi.ac.uk/ipd/mhc/). These genes consist of six exons; exon 2 encodes the PBR and has the greatest polymorphism12, thereby providing it with greater diversity for presenting peptides18. This study did not consider analysing the SLA-DRA gene because it has poor genetic variability, as happens in humans19.The MHC is called the swine leukocyte antigen (SLA) in the 20, reproduction21 and/or genetic characterisation22. Several studies in the field of biomedical research have concluded that SLA-DRB1 is an xenoantigen5; some studies have even been aimed at determining which pig alleles have the greatest reactivity23 whilst others have dealt with xenotransplantation25. MHC gene variability could be affected by natural and/or artificial selection27; regarding diversity, allele determination in a target population is thus relevant when designing epitope-based vaccines where it is recommended that the most prevalent pig population alleles (super-types) are identified so that such vaccines are designed to serve the majority29.Studies have evaluated MHC-Class II haplotype relationship with such parameters as production30. The different breeds used in the modern pig industry have a greater impact on the rural economy because they are considered a low-cost protein source32. The appearance of the domestic pig in America arose from the introduction of Iberian or hairless pigs during the time of the Conquest; they have become adapted to local conditions over a period lasting more than 500 years, having some special phenotypical characteristics33. Three breeds are currently located in specific areas of Colombia. The nucleus of the Casco Mula breed is on Colombia’s Eastern Plains  and the foothills of the Eastern Plains region (Piedemonte Llanero), the San Pedreño breed is in the Antioquia and Viejo Caldas departments and the Zungo breed is found on the Atlantic coast (mainly in the Córdoba department). The latter region is considered the place where the first specimens arrived in Colombia35.Local pigs are used in various traditional production systems worldwide, including native pigs in Asia, Africa and the Mediterranean (Iberian pigs); they are called creole pigs in Latin American countries31.Phenotypically, the San Pedreño breed is black, has a small head, a short snout and straight/upright ears; the Casco Mula breed’s name arises from syndactyly, as the pigs are multi-coloured, have red and sometimes black hair, a medium-sized snout, concave head forward-sloping, large ears and strong, short legs. The Zungo breed is characterised by being black and hairless, large-sized and having floppy ears; it has been reported that pigs from the Caribbean region have been crossed with pigs from the Duroc, Poland China and Hampshire breeds35. According to previous reports these breeds are characterised by being able to produce meat and reproduce in difficult environmental situations32. Several studies have used genetic markers for better characterising breeds regarding their production potential36; a germplasm bank-based study of the San Pedreño breed recently characterised its genetic structure35.These breeds’ living nuclei are kept in germplasm banks in the Colombian Agricultural Research Corporation’s (AGROSAVIA) research centres because they have a nucleus consisting of less than 1000 individualswww.solla.com)37. This research was thus aimed at genotyping the SLA-DRB1 locus in pig populations from Colombian creole breeds and commercial hybrids and comparing the diversity amongst Colombian populations and to that of some previously reported international ones.The creole pig’s adaptation to varying environmental conditions has promoted the development of their productive and reproductive abilities. Production-related genetic improvement programmes in Colombia have enabled the development of commercial hybrids whose production-related qualities abilities have favoured their widespread distribution in Colombia  and another seven were unique for the commercial pig group .The study involved sampling 188 pigs from locations in Colombia; 91 pigs were creoles and 97 came from a commercial line  being found in all three breeds. The SLA-DRB1*02:01:01 allele was shared by five populations where it occurred with > 5% frequency; moreover, this allele had > 40% frequency in creole populations. The San Pedreño population had the greatest amount of alleles  were shared amongst the three populations. Four unique alleles  were observed in the Remanso population (U.D.C.A) , the highest being observed in the Manta population (74.2%), followed by Remanso (71.0%). The Casco Mula population had the greatest homozygosity in the creole pig group 73.3%)  and haplotypes (h: 9), whilst the Zungo breed had the greatest nucleotide π: 0.09214) and haplotype (Hd: 0.753) diversity  was slightly higher than that for the production animals (2 events). No recombination events were found regarding Casco Mula; the recombinant ons Fig. .DRB1*02:01:01, *10:01:01, *01:01, *09:01:01 and *01:02 alleles were found (often having very high frequencies) in several Colombian, European and Asian populations. Several alleles were unique to one population and often found to have low frequency, including the DRB1*10:04 (Remanso) and *02:05 (San Pedreño) alleles. Some alleles were not found in Colombian populations, being restricted to just some European  or both European and Asian populations  (Table 1) Table .IS were determined for these populations  breed having the greatest ho amongst all six populations, whereas Casco Mula (ho:0.267) had a ho comparable to that of Remanso (ho:0.290) and Manta (ho:0.258). Casco Mula (he:0.380) had the lowest he value, which was twice as low as those for the San Pedreño (he:0.728) and Zungo (he:0.743) breeds. Remanso (he:0.558) and Manta (he:0.563) had the lowest he values amongst commercial line populations, due to the extremely biased allele frequency distribution in these populations. All populations had higher expected than observed heterozygosity and had significant heterozygote deficiency, being almost twice as high in the Manta  than the Casco Mula breed . Both commercial line and creole pigs had the lowest observed heterozygosity (except for Duroc pigs) compared to that for other pig populations, although expected heterozygosity levels were more similar to those for other populations. Allele richness  had a clear sample size-related effect on the amount of alleles identified (Table ho nor he appeared to be affected by sample size (ho r = 0.13 and he r = 0.17), indicating that these estimates should be good representatives for SLA-DRB1 diversity in these pig populations. Colombian creole and commercial line pig populations had the highest Hardy–Weinberg variations .Observed and expected heterozygosity and Fns Table  to examiula ho:0.67 had a (Nd) and synonymous (Sd) polymorphisms was calculated to evaluate sequence diversity amongst populations. Considering the whole β1 domain, Sd ranged from 2.32 (Remanso) to 8.65 (Micromini) and Nd from 7.80 (Casco Mula) to 19.02 (KNP). Colombian populations had the lowest values for both Nd and Sd, despite the amount of alleles or sample size being the lowest amongst all populations. This indicated a less divergent gene pool for the Colombian populations. When only considering PBR codons, Sd ranged from 0.70 (Remanso) to 2.79 (Micromini) and Nd from 7.0 (Duroc) to 11.11 (KNP); Colombian populations, Yorkshire_E, SNU and Duroc also had low levels of diversity. As expected, a large percentage (54% to 82%) of Nd in the β1 domain was due to PBR positions, confirming these positions being the most variable ones  . Multidimensional scaling (MDS), using the DA genetic distance matrix, was explored to depict population relationships in two dimensions  Table . DA geneDA distance and the alleles shared by its members  accounted for 76% of its mean absolute allele frequency . The third cluster consisted of Landrace_C and Micromini, having a 0.432 DA distance and its common alleles  explained 63% of mean absolute allele frequency  . The first was a compact group consisting of Duroc, Zungo, Casco Mula and San Pedreño. This group had a 0.26 mean ΔK distribution, an inferred K value of 4 provided the best fit to the data and thus all individuals could be grouped in 4 populations  genetic diversity for the first time in two Colombian pig populations. It was seen that the amount of alleles was similar in each population; the Casco Mula breed had the least amount of alleles. Individuals from the San Pedreño breed had the most alleles and individuals from the Zungo breed the highest nucleotide variability . However, some populations having low Rs had high he (corrected for sample size), indicating a marked variation regarding allele frequency distribution.This study’s results confirmed greater diversity in wild boars, contrasting with low diversity in domestic pig populations. The clearest differences were observed regarding allele richness which was especially low in some populations  and its small effective population size35 could lead to intensive in-breeding which would then produce differences regarding allele frequency and could eventually lead to a loss of some alleles. This idea could also be supported by the high FIS values for some of these populations, indicating higher homozygote percentages than those to be expected in a population in equilibrium and could suggest higher endogamy levels.Considering that genetic drift and the structure of animal crosses are factors affecting allele frequency distribution DRB1*01:02 and *10:01 were previously considered ancestral due to their presence in populations having different origins26. It was seen in this study that alleles DRB1*01:01, *01:02, *02:01:01, *09:01:01 and *10:01:01 were broadly distributed, often having high frequency in various populations. As the pigs’ domestication seems to have been occurred during six independent events44, these alleles’ distribution could either indicate their presence in the founding populations in only some domestication events or their presence in the founding populations in all domestication events, accompanied by the subsequent loss of some alleles due to drift and/or natural selection. Allele DRB1*02:01:01 may thus have been present in pig populations originating the creole and commercial line populations but which could have disappeared due to genetic drift (or its frequency could have become reduced and not been sampled) in the Manta population. In fact, several studies have established that mutationally robust populations might have less mutational load; however, it is not clear whether small populations have less susceptibility to drift-related fitness reduction45.Alleles 35, confirmed by analysing pedigree data from information collected from 2008 to 2017 for estimating the generation interval, the level of pedigree integrity, consanguinity and evolution. It was particularly interesting that this group had 6.73% consanguinity35. There have been no reports concerning this for Casco Mula pigs to date.The creole pig group’s results particularly seem to have coincided with previously reported data regarding individuals from the San Pedreño breed46, it was decided to use bioinformatics methods, involving Haplofinder software, for assigning alleles in heterozygous individuals; this tool has been used regarding bovine species for DR48 and DQA49, thereby facilitating assigning a large amount of individuals, resorting to cloning in just 16% of the population. The data obtained from analysing variability between populations revealed a low level of heterozygotes, this being more evident in individuals from the Casco Mula breed and those from the Manta and Remanso groups.Considering the group’s experience50 and have been considered a molecular mechanism associated with MHC genetic diversity; such phenomenon has been observed in ungulate51 and passerine species52.The recombination events observed in this study coincided with that reported by other authors53. Detecting high levels of homozygosity in various regions of the genome of inbred Babraham pigs led to developing specific MHC-related analysis, revealing a high level of homozygosity, thereby making it a candidate for research group use as a biomodel54.Studies in Poland regarding commercial line pigs and native individuals have analysed runs of homozygosity (ROH), identifying genome regions having high ROH levels, for example, SSC4 (51.9–55.9 Mb) which is related to various functions, including immunological onesSLA-DRB1 locus. Interestingly, the low genetic differentiation in Colombian creole populations contrasted sharply with the great differentiation between commercial line populations. This could have arisen from crossing individuals for obtaining such lines. Commercial lines’ impact on Landrace pigs’ genetic diversity has been evaluated recently; the current breed provides evidence of the old lines’ formation, but that such fusion has reduced Landrace genetic diversity55. Various clusters were identified based on a small genetic distance and/or high bootstrap support values. This indicated that the populations forming these clusters have high genetic identity and detailed analysis has revealed that they share a large percentage of their mean absolute allele frequency and the alleles so involved. Such information could be used in infectious disease control programmes or when designing vaccines58. The SLA-DRB1*02:01:01 allele has 79% amino acid identity with HLA-DRB1*01:01 in pigs and has been used for making a bioinformatics predictor based on pocket profile methodology28, highlighting the need for characterising SLA diversity when designing vaccination and control programmes.The pig populations had a clear genetic structure based on the The study involved sampling 188 animals from six populations, thereby identifying a first group called the creole pig group consisting of individuals from the Zungo (n = 26), Casco de Mula (n = 30) and San Pedreño populations (n = 35). All blood samples from this group were provided by AGROSAVIA’s research centres. A second group called the commercial line consisted of Super Mom 52 and PIC commercial hybrid populations; blood samples were taken on three pig farms in the Cundinamarca department, identified as follows: Remanso U.D.C.A (n = 31), Manta (n = 31) and Ubaque (n = 35) . Genomic material was extracted following Wizard Genomic DNA Purification Kit recommendations. All samples’ DNA integrity was determined on 1.5% agarose gel; a µDrop microplate reader was used for determining DNA concentration. The samples were then stored at − 20 °C until PCR. The sample collection procedure was approved by the Universidad de Ciencias Aplicadas y Ambientales’ (U.D.C.A) bioethics committee (in minutes No.002/2019). All procedures followed the guidelines and regulations established in the Colombian code of bioethics (resolution 8430 of 1993) and Law 84/1989 regarding the protection of animals.8, Microminipig59, SNU , Yorkshire, Berkshire, Korean Native Pigs (KNP), Duroc and Landrace14, Landrace_C and Yorkshire_C26 and Pietrain pigs6.Genotypical data regarding the populations reported in the pertinent literature was included for carrying out the comparative analysis of diversity between Colombian and international populations, such as Wild boarSLA-DRB1 exon 2 sequences, using a pair of primers reported in the literature: forward 5′-GTCCACGCAGCGCATTTCTT-3′38 and reverse 3′-ACACACACTCTGCCCCCCG-5′26. Amplified fragment length was 328 bp; 2X high-fidelity Kodaq PCR MasterMix was used and reaction volume was 25 µL, distributed as follows: 7 µL nuclease-free water, 12.5 µL enzyme Master Mix, 1.25 µL for each primer [10 µM] and 3 µL genomic DNA (concentration ranged from 50–100 μg/µL). Amplification conditions were as follows: initial denaturing at 94 °C for 3 min, 35 cycles consisting of denaturing at 94 °C for 30 s., annealing at 68.2 °C for 30 s., extension at 72 °C for 1 min, followed by a final extension step at 72° for 5 min. All PCR products were amplified in 2 independent reactions, revealed on 2% agarose gel and then purified and sent to Macrogen Inc. (South Korea) to be sequenced in both senses.Polymerase chain reaction (PCR) was used for obtaining the https://digitalinsights.qiagen.com) was used for assembling and analysing the sequences. Heterozygotic individuals’ sequences were manually edited, IUPAC/IUBMB single-letter code was used for ambiguous pairs60 and Haplofinder Python script was used for assigning them49. This involved creating a library with the exon 2 sequences from the alleles reported for SLA-DRB1 in IPD-MHC (www.ebi.ac.uk/ipd/mhc). pGEM-T Easy vector (Promega) was used for ligating heterozygotic samples which could not be assigned by bioinformatics methods which were then transformed in competent E. coli JM109 cells to separate both alleles, following the protocol reported by FIDIC61. Selection involved blue/white colony screening; the amount of positive colonies was replicated and scaled for plasmid purification; 5–10 positive clones were obtained per sample, confirmed on 1.5% agarose gel and sent to Macrogen again to be sequenced in both senses. The complete genotyping results are shown in Table CLC Main Workbench v.3.6.5 software  was used for aligning the sequences; they were then evaluated for identifying indels (insertion and elimination events) which could have affected the length of any sequence to be analysed. Minor adjustments were then made to the alignments to eliminate gaps. DnaSP (v5) software (http://www.ub.edu/dnasp/) was used for evaluating each population’s genetic diversity, nucleotide diversity (π), theta (per site) from eta (Θ), the amount of segregating sites (S), the amount of haplotypes (h) and haplotype diversity (Hd) along with their standard deviations (SD).The MUSCLE sequence alignment tool (http://www.microbesonline.org/fasttree/) for phylogenetic reconstruction; node robustness was evaluated by bootstrap method with 1000 replicates62. The phylogenetic trees were visualised in the web tool Interactive Tree Of Life V3 (http://itol.embl.de)63; the Recombination Detection Program (version 4) (RDP4) was also used. In-depth statistical analysis included using RDP, GENECONV (for detecting gene conversion), BootScan , Maximum Chi-Squared test (MaxiChi) , Chimaera , Sister Scanning (SiScan) , 3Seq (for ascertaining whether any sequence in a data set is a recombinant or mosaic), VisRD  and BURT  methods64.Maximum likelihood trees with double precision, considering Jukes-Cantor as a substitution model were built based on the alignments using FastTree Version 2.1.9  and unbiased expected heterozygosity (he) according to Nei67 were estimated using Arlequin v.3.5 software for population genetic analysis68. Potential Hardy–Weinberg variation percentages were estimated by FIS statistic test69 included in Genepop v.4.7.0, using the exact test of significance70. Molecular Evolutionary Genetics Analysis (MEGA X)71 software was used for calculating the average amount of nonsynonymous (Nd) and synonymous (Sd) polymorphisms and their standard errors  for all sequence pairs within populations. Nd and Sd were not normalised for sequence length to attain the percentage of polymorphisms in the PBR regarding the whole β1 domain encoding sequence.The maximum likelihood method was used for obtaining the amount of alleles (Na) and allele frequencies by direct counting, along with their standard errors72 was used for assessing variation amongst populations. POPTREE2 software73 was used for estimating DA genetic distances between populations from allele frequencies74. R packages ape 75 and poppr76 were used to estimate Nei standard genetic distances between populations from amino acid sequences77. R packages ape, poppr and stats were used for inferring dendrograms with NJ and BIONJ algorithms. Confidence values for nodes in the dendrogram were obtained by bootstrapping alleles with 1,000 replicates and the trees were constructed using webserver Phylogeny.fr78. Multidimensional Scaling (MDS) analysis based on DA genetic distances involved using the R cmdscale function. R squared was used for evaluating the representation of the trees’ original distances and MDS and correlation analysis was used for evaluating sample size effects on he and ho. The Bayesian iterative algorithm in STRUCTURE multilocus genotype data for assigning individuals to a particular population79 was used for further evaluation of population structure, inferring genetic clusters in which individuals could be assigned. Structure harvester80 a programme for parsing Pritchard’s STRUCTURE output and performing the Evanno method81 was used for determining the most likely K by ΔK distribution. Ten replicates were run for each K using the admixture model with correlated allele frequencies and Markov Chain Monte Carlo 50,000 burn-in steps, followed by 100,000 iterations.Arlequin software v.3.5.2 analysis of molecular variance (AMOVA)Supplementary Information


Portunus pelagicus (Linnaeus 1758), inhabits coastal areas of Southeast and East Asia, and is one of high fisheries commodities with an export value for Indonesia and an increasing global market demand, annually. However, the data of genetic diversity and their spatial connectivity of populations in Indonesia are not yet known, even when it is important to inform stock unit management and sustainable use. This study aimed to determine the genetic diversity and differentiation of blue swimming crabs across Indonesian populations in different Fishery Management Area (FMA), and their spatial genetic connectivity, as well as to deliver implications for sustainable fishery. A total of 297 individuals were collected and amplified using cytochrome oxidase I mitochondrial DNA. This study has showed the highest values for haplotype and nucleotide diversity in the eastern part of Indonesia, where exploitation is relatively low. Significant genetic differentiation between populations  and the fisheries management areas  were revealed. Low spatial connectivity was observed between populations in a distance of at least more than 60 kilometers. This study suggests that BSC populations in Indonesia, likely have several stock units, and preferably different fisheries management plans and actions across the region thoroughly and simultaneously. This would be effective for management and their sustainable conservation.The blue swimming crab (BSC),  Portunus pelagicus Linnaeus, 1758) inhabits coastal waters of Southeast and East Asia , becausustralia .A total of 40 haplotypes were observed in all populations, where the highest was found in Pamekasan and the lowest in Pamandati. A diverse type of haplotype has an impact on the genetic diversity in a population. The more diverse types of composite haplotype population level of genetic diversity, genetic in the population will be higher and vice versa . GeneticPortunus pelagicus on this study showing distinct five clades, of each Fisheries Management Area (FMA), except in Sulawesi and Lombok (713–714). Sezmiş (2004) [P. armatus (previously known as P. pelagicus), each clade consisting of individual mixes of different populations in Australian waters. Phylogenetic interpreted as a model for representing approximately relationship ancestor organisms, molecular sequences or both [The reconstruction of phylogenetic trees for ş (2004)  produced or both . This sh or both .FST was indicating strong subdivision and low gene flow between populations. The current study is similar to some of previous studies, which have revealed sub structure on the P. pelagicus populations. In Australia, some studies showed Australian waters are divided into four subpopulations based on different markers . The study of Bryars and Adams [P. pelagicus was investigated from 16 different assemblages throughout the geographic range of this species in Australian waters [A high value of nd Adams  using aln waters . This inet al. [P. pelagicus who has an extended planktonic larval stages would potentially has high larval dispersal and might occur of extensive gene flow between conspecific samples within geographic mesoscale that is from ten to hundreds of kilometres. In contrast with the observed result in China, population genetic structure has a limited occurrence with a high level of gene flow along the distribution areas of this species in China [P. pelagicus populations [P. pelagicus are capable of moving substantial distances, with one recorded as traveling 20 km in one day in Moreton Bay, Queensland [P. pelagicus is also regarded as a potential species vagile since adults are able to travel in geographic mesoscale daily [The current study is contradictory as previously assumed by Yap et al.  that thein China . While iulations . This reeensland , 55. Othle daily , which sFST, suggest that each fisheries management area (FMA) in Indonesia should be treated differently by developing fishery management plan and strategic action at each management region. The biological characteristics of blue swimming crab, the coherent organized nature of the industry, and its reliance on sustainability conscious export markets makes the blue swimming crab fishery strategic for starting the process and inclusive collaborative management model for coastal fisheries [P. pelagicus in Indonesia, including conservation genetics, and utilization management of this species on a sustainable basis.The blue swimming crab has a high productivity and rapid growth rates , thus deisheries . Informa


Spartina alterniflora Loisel. (Poaceae), native to the eastern United States, was introduced unintentionally into Japan (Aichi and Kumamoto Prefectures) at around 2010. This invasive species could easily and rapidly spread to estuarine areas of Japan via vigorous trade and transport, making the prediction of its future invasion necessary. Here, the distribution and structure of the genetic variation of S. alterniflora in Japan were examined using chloroplast DNA (cpDNA) and microsatellite genotyping analyses for clarifying its invasion route and process. According to the cpDNA analysis, S. alterniflora populations in Japan had a single haplotype (haplotype C4) that is the most dominant genotype around the Florida Peninsula, the region of its origin, and is also widely found in the introduced populations in the East Asia. Microsatellite analysis also showed a loss of genetic diversity in Japanese S. alterniflora populations  = 1.20–1.39) compared with that in its native region (AR = 4.58–4.59), suggesting a founder effect on S. alterniflora that might have occurred after invasion of the species into Japan. The principal coordinate analysis and The STRUCTURE analysis indicated that no gene mixing among Japanese local populations  was observed, indicating that Spartina invasion occurred independently into these regions. Among the three regions, trading between the ports of northern Kumamoto and the U.S. was obviously lower than trading with China. We concluded that invasive S. alterniflora might have independently invaded Japan at different times through an East Asia route, particularly via China . Therefore, it is important to strengthen the quarantine control on the importation of commodities, especially of transport vehicles at potential donor spots , and to share information networks on invasive species between each region/port for minimizing further risks of biological species such as SpartinaAmong invasive species, aquatic plants pose serious threats to local biodiversity and ecosystem functions.  Invasive species are extremely harmful to native ecosystems and thus are regarded as one of the major threats of biodiversity loss . InternaInformation on the origin and invasion history of each invasive species is essential for preventing its further spread successfully . For exaSpartina alterniflora Loisel (smooth cordgrass), a plant native to the Atlantic coast of North America and the Gulf of Mexico, was first detected in 2008 in Aichi Prefecture and in 2009 in Kumamoto Prefecture, followed by identification in multiple rivers and tidal flats in both prefectures    . Howeverrdgrass)  greatly on e.g., . In addixclusion  and chanxclusion  were fouhe world , and all in 2014 . To achiS. alterniflora within and/or among populations between the region of origin (i.e. the Atlantic coast of the United States)   based on the extremely low-level of inter-population genetic diversity. On the other hand, populations of this species in the San Francisco Bay, California, and China, which were introduced intentionally, had a relatively high genetic diversity (There are some studies that compared the genetic variation of  States)  and the  States) . For exahe 1890s . This fa source) . Also, Biversity .S. alterniflora in Japan and its origin were assessed by analyzing the degree of genetic diversity and genetic mixing in Japanese populations, using chloroplast and nuclear molecular markers. Then, the genetic variance of S. alterniflora was compared between populations in the region of origin (the eastern U.S.) and those in several introduced regions (the Pacific coast of the U.S. and some East Asian countries). This study will elucidate whether actual invasion route of S. alterniflora into Japan was derived from the region of origin  or from a secondary introduction via introduced regions. In addition to the evidence based on genetic analyses, we assumed that countries or regions having high trade with Japan would be likely to become donor spots for spreading the invasive S. alterniflora irrespective of intentional/unintentional pathways. Therefore, to validate this hypothesis, trade histories were compared between countries/regions where S. alterniflora has grown naturally  and Japan (Aichi and Kumamoto Prefectures). In particular, we hypothesized that there was a high possibility of “secondary introduction” from China since many biological invaders such as Solenopsis invicta Buren (fire ant) and Limnoperna fortunei Dunker (golden mussel) invaded Japan associated with recent vigorous trade with China  were collected from the populations which were introduced into Aichi and Kumamoto Prefectures  facing the Ariake Sea (northern Kumamoto) and the Oono River  facing the Yatsushiro Sea (southern Kumamoto), respectively. In contrast, only three samples from three colonies were collected in the estuary of the Shirakawa River  facing the Ariake Sea (northern Kumamoto) because almost all the populations had been eradicated by 2012 to 2015 by drawing out and backhoe dredger  and Tab B (5′-TCT ACC GAT TTC GCC ATA TC-3′) targeting the trnT–trnL region; and Tab C (5′-CGA AAT CGG TAG ACG CTA CG-3′) and Tab F (5′-ATT TGA ACT GGT GAC ACG AG-3′) targeting the trnL–trnF region were used (4 reaction Buffer (2.0 μl), 10 mM dNTP mix (1.6 μl), 50 mM MgCl2 (1.6 μl), 0.2 μl of each 100 pM primer pair, and 5 U/µl of Biotaq™ DNA polymerase (0.1 μl)  were used. The temperature conditions of trnT–trnL region (54°C) and the trnL–trnF region (67.5°C). A TaKaRa PCR Thermal Cycler  was used for the PCR assay. PCR products were purified using NucleoSpin Extract II  and then were used as a template for the cycle sequencing reaction. The cycle sequencing reaction assay was conducted by Macrogen Japan Corporation  and analyzed using a 3730xl DNA analyzer . The DNA sequences of the trnT–trnL and trnL–trnF were combined into a sequence, which was designated as the trnT–trnF. The base sequence of the trnT–trnL obtained in this study was compared with the existing 42 haplotypes in S. alterniflora (accession numbers AY927278–AY927299 and DQ486839–DQ486858) (To compare the chloroplast DNA (cpDNA) haplotypes of d States  and Japaere used . The totQ486858)  in orderQ486858) , in statQ486858) . All namS. alterniflora populations in Japan were identified using 11 different microsatellite markers (n = 27), Shirakawa (n = 3), Tsuboi (n = 20), and Oono (n = 19) Rivers, but the sample of the Shirakawa was excluded from some of the subsequent analyses because of only one genet.Microsatellite analysis was conducted using 11 microsatellite markers , developed by S. alterniflora in Japan with that in the previous studies (P), genotype diversity (g), observed (HO) and expected (HE) values for heterozygosity, gene diversity (h), allelic richness (AR), and coefficient of inbreeding (FIS) were used as indicators. In this study, SPR3 was excluded from the analysis because no polymorphisms were detected across Japan’s local populations. The polymorphic locus rate (P) was calculated for each local population. This value indicates the rate of genetic loci with polymorphisms compared to all the genetic loci for each local population. Presence/absence of the multilocus genotype matches in among individual polymorphic gene loci was analyzed using Software GENALEX ver. 6.5 (g) for each S. alterniflora population was calculated, and then the duplicate clones were removed from the data set and excluded from the following analyses according to g indicates the rate of the individuals with duplicate clones removed in each local population. The observed (HO) and expected (HE) values for heterozygosity were calculated using GenAlEx ver. 6.5 (h), allelic richness (AR), and coefficient of inbreeding (FIS), and its confidence intervals were calculated using FSTAT ver. 2.9.3 , the Shirakawa River and Tsuboi River (northern Kumamoto), and Oono River (southern Kumamoto). The sequences of trnT–trnF region from Japanese populations revealed that all S. alterniflora populations in Japan had a single haplotype (accession number: LC565815): the haplotype C4 , Tsuboi River , and Oono River .Results of the genetic analysis of Japanese g) was extremely high at 0.93 ± 0.12 in samples from the Atlantic coast of the U.S. (native range), and similar tendencies were also found in other regions where S. alterniflora invaded  and the introduced in Willapa Bay (the Pacific coast of the U.S.) (g = 0.95). On the other hand, low g values were found in samples from the Shirakawa River (g = 0.33) and Guangdong province in China (g = 0.32), where almost all analyzed samples had the same genotype. The inbreeding coefficient (FIS) of each population in Japan indicated that estimated FIS values of samples from the Tsuboi (FIS = 0.29) and Oono (FIS = 0.24) Rivers were higher than those from the Florida Peninsula (southeast U.S.) (FIS = −0.02 ± 0.17) and China (FIS = −0.02 ± 0.16), suggesting the significantly excessive homozygosity (P<0.05). However, the FIS values of samples from the Umeda River (FIS = 0.01) did not deviate from the Hardy-Weinberg equilibrium , the stepwise mutation model (SMM), and the two-phased model of mutation (TPM) (P<0.05). In addition, the mode shift test suggested that a bottleneck  would have been formed in these populations in recent years  based on co-dominant genotypic distances revealed that genetic distances of g Axis 1 Figure 3S. alterniflora populations of Japan were classified into three groups: 1) Umeda River (Aichi), 2) Shirakawa and Tsuboi Rivers (northern Kumamoto), and 3) Oono River (southern Kumamoto)   and the Florida Peninsula (southeast U.S.) , the region of its origin   located in the Pacific coast of the U.S.  was expected by the mode shift test in S. alterniflora population in Japan. Therefore, these results reveal that the founder effect might have occurred in Japanese S. alterniflora population. Such low genetic diversities associated with a founder effect were also found in other Spartina species such as S. versicolor Fabre introduced in Europe  Table 1.s origin , and Chi ± 0.46)  and Willthe U.S.  that arey so far . Indeed,n Europe  and S. dthe U.S. . Since tS. alterniflora were intentionally introduced into China from multiple areas of the Atlantic coast of the U.S.  for eco-engineering purposes   in the southeast U.S., especially around the Florida Peninsula. Populations of S. alterniflora in the Grays Harbor, Washington (haplotype B) and Taiwan (haplotype C4), which had only a single haplotype as well as Japan  . The cov in 1985  and then in 1985  due to eas Japan Figure 2as Japan  and the as Japan , respectS. alterniflora irrespective of intentional/unintentional pathways as mentioned before. Undoubtedly, this can be generalized regardless of taxonomic groups. Thus, to validate this hypothesis, trade histories were compared between countries/regions where S. alterniflora has grown  (https://www.gtis.com/gta/). The findings revealed that when compared the amount of trade between the Yatsushiro Port (southern Kumamoto), which includes the Oono River and the U.S.  and the East Asian countries , differences in the trade value with both countries were similar and/or slightly higher in the East Asian countries. Similar trend on the amount of trade with U.S.  and the East Asian countries  was observed at Mikawa Port (Aichi) including the Umeda River. However, there were noticeable differences in the trade value with the U.S.  and the East Asian countries  at Kumamoto Port (northern Kumamoto) which includes the Shirakawa and Tsuboi Rivers, indicating that the value with the East Asian countries was markedly higher than that with the U.S. These data suggest that the route through which invasive S. alterniflora was introduced to Japan is likely to be from the East Asian countries, particularly from China all together considering the rate of its haplotype frequency  and Mikawa Bay (Aichi), when young Ruditapes philippinarum Adams and Reeve shellfish were imported   and the requency Figure 2requency , and thuimported . Similartivation . From thS. alterniflora local populations in Japan for estimating the route through which S. alterniflora invaded Japan revealed that genotypes of the populations were clearly different in each river  a deliberate release and/or an escape from planting, cultivation, revegetation sites, and so on; 2) unintentional arrival via a transport vehicle such as in ballast water, cargo, and airfreight; and 3) natural spread from a neighboring region where the species itself is alien  are found in estuaries in an enclosed bay  in the Tsuboi River (northern Kumamoto) had a heterozygous at only one locus, while two individuals growing sympatrically (St. 14 and 17) had a homozygous at all of the loci  , they may be considered as clones with exactly the same genotype due to the extreme homozygosity. The number of alleles per marker on each S. alterniflora population in Japan was less than and/or equal to 2   and asexl (seed) . It is sore 2008 . In othereported . NeverthS. alterniflora populations in Japan were as follows: 1) all S. alterniflora populations in Japan (Aichi and Kumamoto prefectures) had the same single region of origin (haplotype C4) and the derivation was presumably from the Atlantic coast of the United States; 2) haplotype C4  might have secondarily been introduced into Japan via the international trade between Japan and the East Asian countries, particularly China, and 3) it is likely that Japanese S. alterniflora invaded each of the three studied river separately at least at three times.From this discussion, we conclude that genetic characteristics, invasion process, and route of Spartina species /asexual (rhizome) propagations should be intensively mown and excavated when they are unintentionally introduced. Simultaneously, it is also important that S. alterniflora is detected and eliminated at an early invasion stage in order to minimize its invasion. In this study, we predicted the low frequency of S. alterniflora invasion. The reason was that the number of alleles per marker on each S. alterniflora population in Japan was less than and/or equal to 2 , accession number: LC565815.YM, MT, and DH designed and coordinated the research. YM, TH, AN, and DH collected samples. YM, MT, and YI analyzed the data. YM and DH drafted the paper with the input of NN. All authors contributed to the article and approved the submitted version.Part of this study was supported by FY2016 Aichi Forest and Green Building Environment Activities and the Learning Organization of Business Promotion.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.