Reticulitermes flavipes. It is invasive in France and is thought to have arrived from Louisiana during the 18th century. While the putative source of French populations has been identified, little is known about how the termite spread following its establishment. Here, we examined expansion patterns at different spatial scales in urban areas to clarify how R. flavipes spread in France. Based on our analyses of phylogeography and population genetics, results suggest a scenario of successive introductions into the Charente-Maritime region, on the Atlantic Coast. Two major expansion fronts formed: one that spread toward the northeast and the other toward the southeast. At the regional scale, different spatial and genetic distribution patterns were observed: there was heterogeneity in Île-de-France and aggregation in Centre-Val de Loire. At the local scale, we found that our three focal urban sites each formed a single large colony that contained several secondary reproductives. Our findings represent a second step in efforts to reconstruct termite’s invasion dynamics. They also highlight the role that may have been played by the French railway network in transporting termites over long distances.Termites are social insects that can also be major pests. A well-known problem species is the subterranean termite,  The invasion process can be divided into a series of stages during which there are barriers that must be overcome for a population to become invasive ,2. UnderReticulitermes flavipes is an invasive subterranean termite (Rhinotermitidae) that lives in forests and urban areas, where it can cause significant damage to wooden structures of human origin [R. santonensis) most likely came from an area in or around New Orleans, Louisiana [R. flavipes was accidentally introduced to France during the 18th century, when Louisiana was a French territory, arriving in shipments of agricultural products and/or timber [Reticulitermes flavipes is now well established in France: its range extends over the western half of the country, from Paris to Marseille. It is common in urban areas but also occurs in certain pine forests along the Atlantic coast. Rochefort and La Rochelle were the first two cities in which termite damage to anthropogenic structures was reported—they are two major ports along the Atlantic Coast that played an important role in international trade during the period mentioned above [Reticulitermes flavipes remains extremely widespread and abundant in urban and natural areas in and around these two cities. All of the evidence points to the following scenario: individuals of R. flavipes first arrived in one or several ports along the Atlantic Coast on ships coming from Louisiana. They reproduced and established themselves before spreading to other cities and expanding into local forests. If such is the case, the French populations of R. flavipes have been evolving independently for about 200 years [n origin . It is nn origin ,18. A reouisiana . It has r timber ,19. Retied above ,21. Reti00 years .Reticulitermes display a high degree of invasiveness and frequently infest anthropogenic structures [Reticulitermes species, which then affect termite population dynamics.In temperate habitats, termites of subterranean genera such as ructures ,23,24. Sructures , also knructures . This prructures ,28. It iR. flavipes populations has highlighted the relationship between invasion success and colony breeding structure [Interestingly, the ability of colonies to produce neotenics seems to be highly variable among species and populations . Researctructure . Whereastructure ,29,30,31tructure . More sptructure . The resR. flavipes in its French introduced range. More specifically, the aim was to identify and evaluate the genetic links among infestations to identify the invasion pathways that the termite may have followed at national and regional scales. We focused on two highly infested regions, Île-de-France (center = Paris) and Centre-Val de Loire (center = Tours), and estimated population variation, maternal lineages , and population genetic structure . We also characterized colony breeding system along the invasion front in Centre-Val de Loire, from west to northeast. This study contributes to our understanding of how R. flavipes spreads within new environments, and confirms that certain anthropogenic factors might strongly affect the termite’s population dynamics.The objective of this study was to characterize the post-establishment dynamics of R. flavipes, we used specimens from different parts of France (64 sampling locations) and the US (20 sampling locations) collected over the course of a previous study [To investigate invasive populations of us study  (Table SR. flavipes. A first one was sampled in Île-de-France (IDF), a region including the city of Paris, and a second one was sampled 150 km away from Paris, in Centre-Val de Loire (CVL), a region including the cities of Tours and Orléans. Samples were taken from wood fragments, damaged wooden structures, and/or pitfall traps using artificial feeding stations . Specimens were stored in 96% ethanol at 4 °C until DNA extraction. Forty-five locations were sampled in IDF (PP1 to PP45), and 62 locations were sampled in CVL (TC01 to TC62). In total, samples were obtained from 36 cities , Joué-les-Tours (11 points: TCJT01 to TCJT11), and La Riche (7 points: TCLR01 to TCLR07) . These 3Genoscreen  using BigDye v. 3.1 and a 96-capillary Applied Biosystems 3730xl DNA Analyzer . COII sequence alignment and performance were examined with Geneious v.9.4 (https://www.geneious.com) . New sequences were deposited in GenBank under the accession numbers provided in A 658-bp fragment of the mitochondrial cytochrome oxidase II (COII) gene was amplified and sequenced for 107 individuals (45 IDF + 62 CVL) using the modified primers A-tLeu (5’-CAGATAAGTGC-ATTG GATTT-3’)  and TK-N® Genomic Purification Kit . To investigate dispersal dynamics at national and regional scales, 100 termites  were genotyped at the eight highly polymorphic microsatellite loci targeted by the multiplex sets developed by Baudouin et al. 2017 [Rf1-3, Rf6-1, Rf15-2, Rf21-1, Rf11-1, RS1, RS15, and RS43, which were all previously described by Vargo [Rf6-1, RS1, Rf11-1, Rf-21-1, RS43, Rf24-2, RS15, Rf1-3, RS76, and Rf15-2. PCR amplification and genotyping were performed at Genoscreen platform (http://www.genoscreen.fr/fr/) . Alleles were scored using Geneious v. 9.4.DNA from individual specimens was extracted using the Wizardal. 2017 : Rf1-3, by Vargo , Dronnetby Vargo , and DeHby Vargo . At the http://cibio.up.pt/software/tcsBU/), which speeds up the production of publication-ready networks resulting from TCS analysis [Phylogenetic analyses were performed using four methods: maximum parsimony (MP), neighbor-joining (NJ), maximum-likelihood (ML), and Bayesian inference (BI). The MP and NJ methods were applied using SEAVIEW , and theanalysis .To look for evidence of spatial and genetic structure in populations, we analyzed the microsatellite and mitochondrial data  using BTo detect recent bottlenecks, we estimated the deviation between observed heterozygosity and expected heterozygosity under mutation-drift balance using BOTTLENECK v. 1.2.02 . Tests wHd) and nucleotide diversity (Nd) were calculated from the mitochondrial data using ARLEQUIN v. 3.0 [Na), allelic richness (Rs), and gene diversity (Hs); Fstat v. 2.9.3 was employed [Genepop on the Web [Haplotype diversity -based differentiation test from nificant ,30,51. Genepop on the Web, which allows colonies to be classified according to family type . To do this, the observed number and frequency of alleles and genotypes within colonies were compared to expected values for the three family types [p < 0.05) carried out across all loci. Colonies were classified as extended families when there were four or fewer alleles at all loci, and when worker genotypes were not consistent with those expected for a single pair of reproductives  or when genotype frequencies deviated significantly from those expected for simple families. Colonies were classified as mixed families when more than four alleles were found at one or more loci, a pattern that is consistent with offspring produced by more than two unrelated reproductives.The breeding structure of each colony was determined using ly types ,35,52. CSTF/(1-STF) and the natural-log-transformed geographical distances between sampling locations [Genepop on the Web.Isolation by distance  was calculated for all the sampling locations for each site . The correlation coefficient between ocations  was obtaThe alignment of the 191 COII sequences revealed 44 variable positions along the 658-bp sequence, which resulted in a total of 18 haplotypes. In France, there were twelve haplotypes, which were named A, B, C, D, E, F, G, H, I, J, K, and CE (newly identified).The phylogenetic trees constructed by the four methods  arrived at congruent topologies and confirmed that the samples fell into two main clades, as previously observed  Figure . One claParsimony network analysis revealed the relationship among the 18 COII haplotypes given a 90% confidence interval . HaplotyFocusing on the regional scale, we noted that the dominant haplotype in IDF was the predominant haplotype in France, haplotype A, whereas haplotype B was the most common haplotype in CVL. However, both haplotypes occurred in both IDF and CVL. The two study regions differed in the spatial distribution of mitochondrial variants—the pattern was heterogeneous in IDF, while single-haplotype clusters were seen in CVL. IDF and CVL haplotype numbers were 6 and 4, respectively, and the haplotype diversity indices were 0.561 and 0.531, respectively . In CharThe STRUCTURE analysis revealed that the 164 colonies in France  were grp > 0.05). One genotypic linkage disequilibrium was observed: between loci Rf11-1 and Rf15-2 in cluster S1. The STRUCTURE genetic analyses showed that allele number per locus (Na), allelic richness (Rs), and gene diversity (Hs) were significantly lower in S3 than in the other four clusters   . S4 and  < 0.05) .p-value = 0.027). In the case of S2, support came from both IAM  and TPM . For S4, support came from the SMM . No mode shifts in allele frequency distribution were observed in any of the clusters.Recent bottlenecks were evidenced in S1, S2, and S4 . For S1,S) and gene diversity (HS) among sites . Based on the number of genotypes, these three colonies were classified as extended families . Because colonies displayed a small number of alleles per locus, it was impossible to determine whether it was actually a mixed family as opposed to an extended family [2 = 0.001, p = 0.348 for Tours; n = 11, r2 = 0.003, p = 0.024 for Joué-les-Tours; and n = 7, r2 = 0.053, p = 0.261 for La Riche).At the local scale, in CVL, only six loci were included in the analyses because four loci were found to be monomorphic . For these six microsatellite loci, there were an average of 2.3 alleles per locus (range 2–3) . There wng sites . There wd family . There wR. flavipes was first introduced to one or several ports  along the French Atlantic Coast, arriving on ships coming from Louisiana during the XVIII century. According to this scenario, introduced populations would have dispersed to other cities and forests. This hypothesis is supported by the genetic results obtained in this study. The current haplotype distribution in France suggests that a limited number of propagules containing only two haplotypes, A and C, initially arrived in Charente-Maritime. In addition, several punctual introduction events could have occurred independently into Gironde, Paris, Maine et Loire, Loire Atlantic, Tarn et Garonne and Loiret counties which present four haplotypes H, K, E and CE also found in US.It has been hypothesized that R. flavipes appears to have spread toward Southeastern France, infesting the Saintonge region  and then the region of Bordeaux before reaching southern France (Toulouse and Martigues). In the case of the second front, R. flavipes seems to have headed toward Northeastern France, with a series of introductions taking place within the Poitevin region (city of Poitiers) and Touraine region (Tours), before the termite reached Paris and more distant northern cities (Rouen and Orléans). Along these expansion fronts, new variant haplotypes  could have diverged from the haplotypes of the initial invasive populations (A and C). As for haplotype CE, which is highly distinct from the other haplotypes found in France, it has only been observed in the Loiret region (next to city of Orléans). It is closely related to a variant found in North Carolina and Virginia in the US. With our data, the most parsimonious hypothesis to explain the presence of this divergent haplotype in France is an independent introduction event. Several haplotypes identified in France diverged by only a few mutations from haplotypes A and C. We found that the predominant haplotype in France (haplotype A) was present in Rochefort and La Rochelle, two major port cities that played an important role in international trades when Louisiana was a colonial territory belonging to the kingdom of France ,21. BaseR. flavipes into France is unclear. The partial support for such events in certain genetic clusters could be due to a deficit in heterozygosity, which is often seen in introduced populations of R. flavipes and can result from inbreeding among related neotenics [It is well known that populations of introduced species often experience genetic bottlenecks ,54. In teotenics . In addiR. flavipes in France have long been an open question. Numerous studies have underscored the role played by human-mediated transport, which has facilitated the insects’s long-distance dispersal and increased its rate of spread [The dynamics behind the expansion of f spread ,12,13,14f spread . Study hf spread ,55,56. IR. flavipes in France, which is thought to have occurred in the 18th century on the Atlantic Coast and in the Saintonge region; the train reached both rather early on  [Coptotermes species [Coptotermes formosanus in southern US [It may have been fully or nearly concomitant with the arrival of ore 1860 ). We may to 1922 . In CVL, (1980s) ,55. Some species . Severalthern US ,62. It hThe analyses looking at phylogeography and genetic structure revealed the presence of different distribution patterns within the two focal study regions. In CVL, the distribution of infestations seems rather aggregative. Except for the termites taken from near Orléans (which displayed the unique haplotype CE), all the other aggregates were characterized by a single haplotype and formed genetic clusters; this result suggests that there were three termite outbreaks that locally expanded over the years following the initial introduction events. In contrast, the distribution pattern was highly heterogenous in IDF. The genetic clusters identified by STRUCTURE were not continuous units, as would be expected if populations were structured. Eighty percent of the clusters identified in the French populations were present in IDF . The STRR. flavipes exhibit a particular colony breeding structure, in which hundreds of neotenics are present and colonies have a propensity to fuse, traits that occur in both forests  and urban populations  [R. flavipes to successfully invade new areas [2 for Tours; 7600 m2 for Joué-Les-Tours; and 2600 m2 for La Riche. In introduced populations of R. flavipes, colonies are often large in both forests and urban areas [R. flavipes populations [Previous research has shown that all introduced populations of , Paris) ,29,30,31ulations .R. flavipes, a termite species that is a major pest, invaded and spread throughout France after its introduction about two centuries ago. In a previous study, we identified the putative source population of French populations [This study provides an evidence-supported scenario for how ulations ; these n


Research on multiple taxa has shown the differential success of maintaining demographic versus genetic stability and viability in captive populations. In typical captive populations, usually founded by few or related individuals, genetic diversity can be lost and inbreeding can accumulate rapidly, calling into question their ultimate utility for release into the wild. Furthermore, domestication selection for survival in captive conditions is another concern. Therefore, it is crucial to understand the dynamics of population sizes, particularly the effective population size, and genetic diversity at non-neutral and adaptive loci in captive populations. In this study, we assessed effective population sizes and genetic variation at both neutral microsatellite markers, as well as SNP variants from the MHC-B locus of a captive Red Junglefowl population. This population represents a rare instance of a population with a well-documented history in captivity, following a realistic scenario of chain-of-custody, unlike many captive lab populations. Our analyses, which included 27 individuals comprising the entirety of one captive population show very low neutral and adaptive genetic variation, as well as low effective sizes, which correspond with the known demographic history. Finally, our study also shows the divergent impacts of small effective size and inbreeding in captive populations on microsatellite versus adaptive genetic variation in the MHC-B locus. Our study provides insights into the difficulties of maintaining adaptive genetic variation in small captive populations.Captive populations are considered a key component of  Ne). One issue in captive populations is the differential reproductive success of some breeding pairs that are better suited to captive conditions, leading to selection for survival in captive environments. This phenomenon can further reduce the Ne due to founder effects  to characterize the impacts of un-managed captive breeding over a period of 57 years (38–57 generations). The study population called the Richardson Strain (RRJF) has a well-documented history since its importation to the United States in 1961. The history of this population is illustrated as a flowchart in In this study, we used a captive population of the Red Junglefowl (The study population of Red Junglefowl (RJF) was initially imported from Northern India in 1961 as part of the US Fish and Wildlife’s Foreign Game Introduction Program (FGIP) and documented in USFWS Special Reports . More reThe research colony maintained at Texas A&M University (TAMU) is one of the two known remaining populations that trace their ancestry back to the survivors of Mr. Richardson’s flock. The TAMU colony was established with two males and three females and expanded to 27 individuals at the time of the study. All available individuals were included in this present study.Ne) can be defined as the size of an ideal population that experiences the same amount of genetic drift or inbreeding as the actual (census) population , and analyzed linkage disequilibrium using two types of markers—namely microsatellite markers and SNP markers. The SNP markers assayed genetic diversity along chromosome 16 (details in ‘Methods’), a microchromosome which contains both the MHC class I and class II genes, in addition to olfactory receptors and scavenger proteins  domestication selection . In thespulation . A numbeproaches . Due to proteins . The MHCproteins .A total of 27 birds bred in captivity at the Texas A&M Poultry Research Center were genotyped in this study. The population represents three generations. The parental cohort was comprised of two males and three females in January 2016 and had expanded to 27 individuals by the second half of 2017. At the time of sampling, the population included original parents (used to establish colony), in addition to two subsequent generations that were hatched in Texas. All individuals available were included in this study.m for each primer pair (and considering M13 sequence), and amplification was performed in a 25 µl reaction using NEB Taq Polymerase with reaction buffer  and NEB dNTPs (New England Biolabs). PCR amplification was performed on an Eppendorf Mastercycler Pro thermal cycler , running an initial denaturation at 95 °C for 5 min, followed by 35 cycles of denaturation , annealing , and extension , and a final extension for 10 min. Each microsatellite locus was amplified and then pooled for multiplex genotyping based on combinations of fluorescently labeled probes. Multiplex genotyping was performed on the ABI 3730 capillary analyzer at the DNA sequencing facility on Science Hill  for fragment analysis. For SNP analyses, equimolar DNA isolates were submitted to the molecular genetics lab at Hy-Line International for genotyping using a custom SNP panel , and measures of the inbreeding coefficient FIS were both calculated within GENALEX, based on 999 permutations of the data. These parameters were estimated for both the microsatellite and SNP data independently.The raw capillary electrophoresis data was downloaded into the software Geneious  and analyzed using the microsatellite plugin. Allele bins, based on peak data from across all samples, were created for each locus. Following this, every individual biological sample was processed through the peak calling step. Once the automatic peak calls were obtained, every allele call was manually verified to check for errors. The final allele calls were exported into the MS Excel-based tool, GENALEX v6.5 . The date estimates were generated using the software program NeEstimator, version 2 .Next, to estimate the effective population size of this captive-bred population, we used three different estimators that are known to estimate contemporary or recent effective population sizes—namely the heterozygosity excess (HE) method , the linersion 2 . These eon 2 , haplotype diversity, and estimate of Tajima’s D, using the R package PEGAS . For the SNP dataset, only 37.8% of the loci were polymorphic, which translated into heterozygosity estimates of 0.107, 0.096, and 0.098  values across all pairwise comparisons. D′ was estimated to have a value of 1, indicating little or no recombination between marker pairs . Such hiπ) was 0.009, whereas the haplotype diversity was 0.43. Finally, we found a significantly negative Tajima’s D based on the haplotype sequences −3.19 (P < 0.01), suggesting a genetic bottleneck . Comparison of nucleotide diversity and haplotypes at MHC loci from wild jungefowl and domestic chicken from other studies are shown in Analysis of haplotypes in the study population using the program PHASE revealed five unique haplotypes , and of Ne estimates were less than 10 for the microsatellite marker dataset, except for the heterozygote excess method . If these estimates are compared against the total number of individuals in the local population (Texas A&M), the Ne∕Nc ratios range from about 0.14–0.27 for microsatellite markers, whereas they range from 0.007–0.17 for the SNP based estimates.The s method . For theex situ conservation programs, and also has implications for endangered wild populations with small numbers of breeding individuals. One important suggestion is that estimates of functional genetic diversity and effective population sizes are overestimated by microsatellite loci.Our study generated valuable new understanding of genetic diversity and effective population sizes in populations that have persisted in captivity for a fairly small number of generations (<60). Additionally, our comparison of genome wide neutral microsatellite diversity, and high-density SNP survey of adaptive genetic loci revealed important differences in how these marker types respond to population bottlenecks, and how that is reflected in the estimates of effective population size; while microsatellite-based genetic diversity estimates were low, they were, nonetheless, higher than SNP-based estimates for the MHC-linked region. These differences were also reflected in the population histories revealed by these markers; effective size estimates were extremely low for the MHC-linked SNP loci. The disparity in estimates between the neutral and adaptive marker types is potentially concerning from the perspective of captive population based We found relatively low genetic diversity based on heterozygosity, among both marker types, but estimates of heterozygosity were higher based on microsatellite markers compared to MHC-linked SNP loci. This is not a surprising result, as microsatellites may not be highly correlated with underlying genomic diversity , for exaWhile it is difficult in our study to determine how the MHC-linked SNP loci may be representative of whole genome diversity, in this study population we expect that chromosome 16 would be experiencing selection or drift in ways that are consistent with the rest of the genome. The MHC is a set of important adaptive loci , and in ,as observed in the current study, it would be potentially concerning from the perspective of measuring the genetic viability of wild populations.The second conclusion of the comparison between microsatellite markers and SNP markers is the potential implications of such disparity for other endangered or threatened species of conservation interest. Several studies have used microsatellite markers to assess genetic variation following population contractions . Due to Ne estimates across all estimators. On the one hand this is consistent with the known demographic history of few breeding individuals at any given time, on the other hand, low estimates may arise from small sample size or other conditions. We expect Ne estimates to be biased downward due to the small number of individuals in this study, but these sample sizes are not unusual in endangered populations. Several of the Ne estimators expect biased estimates at sample sizes under N = 50. However, in this study, 100% of individuals were sampled. Another source of bias, especially for the LD method, as reported by Ne estimates using the LD, and perhaps the MC method.We found low (single digit) Ne estimates were not unexpected, but the differences between the microsatellite markers from across the genome, and the single chromosome SNP markers were notable, and reveal different population histories. Both the MC and the LD methods estimated Ne to be equal to or lower than one, based on the SNP dataset. Whether these differences are the result of different recombination frequencies for marker types or actual biological lineages for unique haplotypes is challenging to differentiate. Our finding of a low number of MHC haplotypes in this population suggests that fewer unique haplotypes to be driving the observed pattern. Due to our exact knowledge of the census size, the Ne∕Nc ratios are informative about both the processes of marker inheritance, as well as the performance of the estimators themselves. Secondly, all the three estimators used in this study are expected to represent the previous or recent parental generations. Therefore, for both the LD and MC methods, we believe that the estimates obtained here represent the founding event of the Texas population in 2016. On the other hand, as changes in heterozygosity occur more gradually over time, and the accumulation of inbreeding may take several generations, the HE estimator may be more representative of a founder event bounded by the initial founding of the US populations in 1961. However, as our analyses of haplotypes and recombination frequencies showed, all the MHC-linked SNP loci are in very high linkage disequilibrium. Such lack of independence among loci in the entire population will be indistinguishable from an effective size of one, which is what we observe here. Our results point to one of the limitations of LD methods in populations such as the study population, where the founders represent only five unique haplotypes. Secondly, the MHC region is inherited as haplotypes instead of segregating loci along the region , real world scenarios such as our study population (both the census and effective sizes are low) pose challenges for the application and interpretation of Ne estimates, and show the need for development of methods to assess and correct for bias in such situations.Finally, the number of microsatellite loci and the low diversity at these loci might be another source of bias in the estimates. Even though we chose microsatellite loci that were reported to be highly polymorphic, these loci had low diversity in the study population. While We observed only three major haplotypes in the population, and it will be valuable to understand how these haplotypes are maintained in subsequent generations. We believe that the low haplotype diversity is a consequence of the history of captive breeding among a small number of individuals, rather than a reflection of the source populations. Haplotype diversity in other wild junglefowl populations has been reported to be quite high. For example, ex situ conservation goals starting with captive populations. Finally, we showed how captive breeding populations, even in the absence of any intentional selection, can affect linkage structure across a set of adaptive genetic loci, and potentially reduce the fitness and adaptability of captive-born individuals upon release back into the wild.Our study showed low genetic diversity and small effective population sizes in a captive breeding bird population. Furthermore, our study was able to relate effective population sizes to the known demographic history of the captive population. Given this history, the low effective population size estimates we found are not surprising. Furthermore, the low genetic diversity, and haplotype diversity both indicate that these populations are indeed pure, and unmixed with domestic varieties, since their initial importation to the United States. Our study shows the rapid loss of genetic diversity in captive populations in only a few generations (50–57 generations since importation), which can be particularly concerning from the standpoint of 10.7717/peerj.5803/supp-1Table S1A table showing the microsatellite loci, known polymorphism, and relevant data such as expected annealing temperature, primer sequences, and notes on whether the locus was retained in final analyses.Click here for additional data file.10.7717/peerj.5803/supp-2Supplemental Information 1Data file which includes all the microsatellite genotyping data, as well as the SNP data for the study population. The SNP data is formatted in the GenAlex format, whereas the microsatellite data is presented in the Genepop format.Click here for additional data file.


Hb G‐Coushatta variant was reported from various populations’ parts of the world such as Thai, Korea, Algeria, Thailand, China, Japan and Turkey. In our study, we aimed to discuss the possible historical relationships of the Hb G‐Coushatta mutation with the possible migration routes of the world. For this purpose, associated haplotypes were determined using polymorphic loci in the beta globin gene cluster of hemoglobin G‐Coushatta and normal populations in Denizli, Turkey.F‐statistics, historical‐demographic analyses, mismatch distribution analysis of both populations and applied the test statistics in Arlequin ver. 3.5 software program.We performed statistical analysis such as haplotype analysis, Hardy–Weinberg equilibrium, measurement of genetic diversity and population differentiation parameters, analysis of molecular variance using The diversity of haplotypes has been shown to indicate different genetic origins for two populations. However, AMOVA results, molecular diversity parameters and population demographic expansion times showed that the Hb G‐Coushatta mutation develops on the normal population gene pool. Our estimated τ values showed the average time since the demographic expansion for normal and Hb G‐Coushatta populations ranged from approximately 42,000 to 38,000 ybp, respectively.Our data suggest that Hb G‐Coushatta population originate in normal population in Denizli, Turkey. These results support the hypothesis that the multiple origin of Hb G‐Coushatta and indicate that mutation may have been triggered the formation of new variants on beta globin haplotypes. The haplotypes obtained by testing seven polymorphic restriction sites in this region of the beta globin gene cluster provide important data on the structure of populations, their origins and their possible associations with mutations  Glu→Ala]  , which is based on three parameters: θ0, θ1 (θ before and after the population growth) and τ .In the first step of our study, PCR‐RFLP (Polymerase chain reaction‐restriction fragment length polymorphism) method was applied on seven polymorphic restriction sites  in the β‐globin gene cluster as previously reported  with Arlequin ver 3.5   Table , respect0 and θ1) also show a similar historical growth period for the populations (Table p > .05) for each of the seven polymorphic loci and the Hb G‐Coushatta population was in Hardy–Weinberg equilibrium except for fourth loci.In terms of the time estimations, parameter values of τ and historical population parameters θ  (Table p < .05) genetic differences showed that the two populations are not diversified by the effect of migration on the gene pool. The difference in haplotype diversity between the two populations may be the possible effect of mutation formation on polymorphic loci in the β‐globin gene cluster.Table h), low nucleotide diversity (π) and similar average number of pairwise nucleotide differences (k) between the two populations  for the two populations, suggesting that these populations are at neutral equilibrium , while the Hb G‐Coushatta population is departure from the unimodal distribution . The reason for this difference in distribution is that the Hb G‐Coushatta population presented in Table p > .05) means that there will be no change in allelic or genotypic frequencies from one generation to the next. However, with the possible effect of Hb G‐Coushatta mutation in the fourth locus may have occurred as the difference between the observed and expected pairwises. Mismatch distribution results were supported by the level of Harpending's raggedness index and p values of SSD in Table Table ions Li, . Additioum Table . These fum Table ,b, 1993.um Table . Accordint p > .0 for the 0, θ1 (θ before and after the population growth) and τ   and 38,000 ybp , respectively. Historic demographic expansions were investigated by the examination of frequency distributions of pairwise differences between sequences (mismatch distribution), which is based on three parameters: θe) Table . In our e) Table , 2017.Homo sapiens neanderthalensis (HN) constitute a group of hominids whose particular morphology developed in Europe during the last 350,000 years under the effect of selection and genetic drift reaching its final form approximately 130,000 ybp , the first modern humans  we had to observe the genetic drifts in our data but we did not observe genetic drifts during the time course of about 40,000 ybp up to the present time.In conclusion, these findings further suggest that the Hb G‐Coushatta population originated in the normal population in Denizli, Turkey. Although two populations share common genetic origin findings, they have different haplotype variations. We think that the reason for these variations is the departure from Hardy–Weinberg equilibrium of the fourth locus in the Table Authors Ozturk, Arikan, Atalay and O. Atalay declare that they have no conflicts of interest.SA, provided support in the data generation of the laboratory results, sample collection and preparation. AA and EOA supervised the study, support in the data interpretation and manuscript preparation.


Dociostaurus crassiusculus, an endangered species with limited dispersal capacity and narrow habitat requirements. Our analyses indicate the presence of two ancient lineages and three genetic clusters resulted from historical processes of population fragmentation (~18–126 ka) that predate the Anthropocene. Landscape genetic analyses indicate that the limits of major river basins are the main geographical feature explaining large-scale patterns of genomic differentiation, with no apparent effect of human-driven habitat fragmentation. Overall, our study highlights the importance of detailed phylogeographic, demographic and spatially-explicit landscape analyses to identify evolutionary significant units and determine the relative impact of historical vs. anthropogenic factors on processes of genetic fragmentation in taxa of great conservation concern.Inferring the demographic history of species is fundamental for understanding their responses to past climate/landscape alterations and improving our predictions about the future impacts of the different components of ongoing global change. Estimating the time-frame at which population fragmentation took place is also critical to determine whether such process was shaped by ancient events  or if, conversely, it was driven by recent human activities (e.g. habitat loss). We employed genomic data (ddRAD-Seq) to determine the factors shaping contemporary patterns of genetic variation in the Iberian cross-backed grasshopper  Many organisms show nowadays highly fragmented distributions due to a natural patchy distribution of their particular habitats7 or as consequence of their originally continuous populations became isolated due to habitat fragmentation driven by human activities9 or past climatic/geological events11. The genetic, ecological and evolutionary consequences of severe population fragmentation are numerous, including alteration of selective pressures, genetic erosion, inbreeding, accumulation of deleterious mutations, reduced evolutionary potential and, ultimately, increased risk of extinction13. For these reasons, the study of population fragmentation is a major area of research for conservation biologists and geneticists, and particular attention has been paid to taxa forming small populations and presenting narrow distributions, low dispersal capabilities, and specific habitat requirements15.Inferring the evolutionary and demographic history of species and populations is fundamental for understanding how they were impacted by past environmental and landscape alterations and anticipating their responses to different components of global change such as climatic variations17. This has important implications to inform on ground conservation practices18. If recent human-induced habitat fragmentation is identified as the main driver of population genetic structure and disruption of gene flow, then conservation practices should focus on restoring population connectivity either creating corridors to dispersal or assisting gene flow to avoid the long-term negative consequences of inbreeding and loss of genetic diversity20. If, instead, population genetic structure was driven by ancient processes, then the different clades, lineages or genetic clusters might represent evolutionary significant units (ESUs) with particular local adaptations that deserve to be managed independently to maximize the protection of both vicariant and adaptive diversity22. Beyond the temporal scale of population divergence, identifying the proximate factors shaping contemporary patterns of genetic structure is also fundamental to understand how organisms interact with the different components of the landscape23. Genetic and spatial information has been successfully integrated to infer dispersal routes across different habitat types20, identify natural barriers to dispersal  and determine the consequences of human activities on disrupting gene flow of natural populations . For this reason, testing alternative spatially-explicit scenarios of population connectivity under a landscape genetic framework can help to determine the relative role of human and natural barriers to gene flow on structuring present-day patterns of genetic variation30. This takes particular relevance in the case of specialist taxa with patchy distributions, as identifying contemporary barriers to gene flow and cryptic corridors to dispersal is crucial to establish management practices aimed to restore or enhance connectivity among remnant populations20.Estimating the time-frame at which population fragmentation took place is critical to determine whether such process was driven by historical processes that predate the Anthropocene or if, conversely, it is a direct consequence of human activities33. Explanations for the high diversity of the Iberian Peninsula include its historically high climatic stability34, the low impact of Pleistocene glaciations in comparison with northern temperate areas35, its current proximity and Miocene connection with North Africa and other Mediterranean regions36, and the presence of deep environmental gradients and a complex topography37. Despite its high biodiversity and conservation value, the Mediterranean region has been exposed to millennia of strong human intervention34 that have reduced the original extent of its primary vegetation by ~95%33. This region is also predicted to be impacted by intense effects of climate change and experience distributional shifts and remarkable range contractions in many taxa39. Both severe habitat loss and climate warming represent serious threats for many taxa with small and highly fragmented distributions that deal with important difficulties for maintaining viable populations and face risk of extinction41. Thus, understanding the evolutionary history, demographic trends, and interactions with landscape heterogeneity of these taxa is critical for establishing effective conservation policies and informed management practices that ensure their long-term persistence43.The Iberian Peninsula constitutes an important biodiversity hotspot, with high species richness, rates of endemism and levels of intra-specific genetic diversityDociostaurus crassiusculus , a species of great conservation concern that has been recently catalogued as “endangered” in the Red List of European Orthoptera44. The taxonomic position of this species was controversial and according to morphological criteria it has been considered for a long time a subspecies of the Asian Dociostaurus kraussi 47. A recent re-evaluation of the taxonomic status of the genus using genetic data has supported the presence of two well recognized species in concordance with their disjunct distributions: D. crassiusculus in the Iberian Peninsula and D. kraussi in Asia48. The full species status of D. crassiusculus makes it of higher conservation concern provided that the very few known populations of the species persist in highly isolated pockets of habitat embedded in an expansive matrix of unsuitable areas3. The species is currently distributed in central-southeast Iberia, mostly occupying pseudo-steppe habitats with halophytic plant communities linked to gypsum or hypersaline soils3. These narrow habitat requirements, together with the reduced flying capacity of the species and the progressive loss of its natural habitat by human activities, has led that all populations of D. crassiusculus are nowadays extremely fragmented and at high risk of extinction by stochastic phenomena49.In this study, we use genomic data to infer the processes structuring genetic variation in the Iberian cross-backed grasshopper D. crassiusculus. Specifically, we first used genomic data to analyse the spatial genetic structure of extant populations of the species, identify main lineages and establish their phylogenomic relationships, and define hierarchical units for conservation and management21. Second, we tested alternative coalescent-based demographic and migration models to infer spatial patterns and rates of inter-population gene flow, estimate the timing of population fragmentation at different spatial scales and, ultimately, determine whether the genetic structure of the species is a consequence of ancient events  or if, conversely, it is compatible with human-driven population fragmentation16. Finally, we generated alternative isolation-by-resistance (IBR) scenarios of population connectivity within a spatially-explicit framework to identify the specific landscape features shaping genetic differentiation in the species and unravel the relative importance of natural  vs. anthropogenic (habitat loss) processes of genetic fragmentation.Here, we employ restriction-site-associated DNA sequencing (ddRAD-seq), coalescent-based simulations and a landscape genetics framework to evaluate alternative demographic scenarios, estimate the timing of population fragmentation, and infer the processes shaping contemporary patterns of genetic structure across all known populations of D. crassiusculus. The number of reads per individual  before and after different quality filtering steps is shown in Supplementary Fig. Stacks for p = 2 and p = 4 contained 80,534 and 65,459 unlinked SNPs, respectively. The datasets obtained with PyRAD for Wclust = 90% and MinCov = 11 and 23 contained 32,424 and 18,442 unlinked SNPs, respectively; and for Wclust = 95% and MinCov = 11 and 23 contained 42,053 and 23,628 unlinked SNPs, respectively. Population genetic statistics  calculated with Stacks for all positions (polymorphic and non-polymorphic) and considering loci that were represented in at least two (p = 2) and four populations (p = 4) and the 50% of individuals within populations (r = 0.5) are presented in Supplementary Table FST values ranged from 0.063 to 0.237 and all were significantly different from zero based on 100 permutations , always identified K = 2 as the most likely clustering solution according with the ΔK criterion . The two clusters presented no signature of genetic admixture and split the southernmost population (ORCE) from the remainder of the populations  and Central populations (PHUE-SALI-BONI) in two different genetic clusters, but in this case the geographically closer populations (TAJU-BELI and PHUE-SALI) showed a considerable degree of genetic admixture (~25%) , in which PC1 split the Southern population (ORCE) from the remainder of the populations, and PC2 separated Northern (TAJU-BELI) from Central populations (PHUE-SALI-BONI)  Fig. . The resNI) Fig. .Figure 1Snapp were well-resolved and nodes presented high posterior probabilities , Snapp analyses supported an earlier split of ORCE from the remainder of the populations, which in turn divided into Northern (TAJU) and Central populations (PHUE and BONI)  and different population combinations for Central and Northern populations  yielded analogous results (data not shown)50. The best tree from SVDquartets yielded the same topology than Snapp, but the relationships among populations were not well resolved  probably as a result of inter-population gene flow or incomplete lineage sorting  Fig. . Analyseing Fig. .Figure 3Fastsimcoal2 analyses supported models A, B and D   occurred ~126 ka (95% CIs: 90–197 ka), probably during the Eemian Interglacial period (115–130 ka)  indicate that this event took place ~17 ka (95% CIs: 11–24 ka), around the last glacial maximum  (Table m) inferred between Central and Southern populations (mC-S) was nearly an order of magnitude lower than the migration rate between Northern and Central populations (mN-C) and between ancestral populations (mANC) after the first population split (TDIV2)  Fig. . AlthougNC) Fig. , they weNC) Fig. . Demograr2 = 0.830; P = 0.001) , indicate that vicariance with multiple contacts  is likely to have led to the current genetic structure of the species (i.e. isolation with gene flow). The best supported scenario (Model B) is the one considering gene flow between recently split populations across time, with higher contemporary migration rates among closer populations from Northern and Central genetic clusters  than those inferred between Northern and Central populations (Model A)  Table . Thus, dper se the degree of genetic differentiation among populations and revealed that the limits of major river basins are the main factor explaining large-scale patterns of genetic structure in D. crassiusculus  presenting highly fragmented populations and inhabiting a similar geographic area51 and in geckos (genus Rhynchoedura) from arid regions of Australia55. These results indicate the importance of this landscape feature on the evolutionary histories of terrestrial organisms from steppe and arid landscapes55. Rivers themselves do not seem to be an important barrier to dispersal in our study system, as populations located within the same basin but at different sides of main river stems or their tributaries (e.g. TAJU and BELI) show low levels of genetic differentiation in comparison with populations located in different basins56. Estimates of divergence time among contemporary populations of D. crassiusculus  indicate that the origin of the species and its different lineages is probably posterior to the formation of the main river basins from the central-south Iberia, which are thought to have acquired their current configuration during the Oligocene-Pliocene57. Thus, the different genetic clusters and lineages are not likely to have resulted from population isolation in different palaeodrainages or ancient geological surfaces26, but probably reflect the role of river drainages and lowlands as corridors of suitable habitat facilitating connectivity among populations located within the same basin51. Given that a predominantly flat landscape characterizes the distribution area of D. crassiusculus and the main drainages are not separated by an abrupt topography (i.e. mountain systems), our results suggest that populations of the species have probably remained linked to lowlands  from different river basins58 rather than physically separated by ridges representing the divides between drainages. Accordingly, our analyses indicate that other landscape features such as topographic roughness (slope) or the distribution of the typical habitats and lithological formations occupied by the species are not important factors explaining spatial patterns of genetic structure in D. crassiusculus  across the distribution range of the species could have reduced our ability to identify barriers to dispersal linked to unsuitable geological formations or, alternatively, might reflect the capacity of the species to cross them. In any case, we must point out that our landscape genetic analyses should be interpreted with extreme caution, given that the very few extant populations of the species (n = 6) strongly limit the power of our analyses and the scope of the obtained inferences.Our landscape genetic analyses indicate that geographical distance, the spatial distribution of suitable habitats, lithology or topography do not explain lus Fig. . These rsin Fig. . Apart fus Table . PreviouD. crassiusculus are a consequence of ancient processes of population fragmentation 61 or Conservation Significant Units (CSU)62. These entities are likely to be substantially reproductively isolated from each other, represent an important component in the evolutionary legacy of the species, and include all discrete genetic and geographic subunits below the species level for status assessment, establishing conservation priorities and setting on-ground management strategies63. Of particular concern is the highly divergent Southern lineage because, as far as we know, it is currently represented by a single small population (ORCE) within the Guadalquivir river basin and Andalucía region  have been extirpated in the last decades49. All remaining populations are extremely small and submitted to severe impacts of human intervention  and stochastic phenomena (e.g. flash flooding) that have been linked to sharp population declines49. The expected time-lag between population fragmentation/declines and the genetic consequences of such processes  might explain why recent human impacts have not been yet reflected in spatial patterns of genetic variation64. Unfortunately, the small number of extant populations at local/regional scales (1–2 populations/genetic cluster), makes difficult to perform detailed analyses to evaluate the role of current landscape structure  on the genetic connectivity of contemporary populations65. Future genomic analyses of specimens available in museum collections3 could help to determine temporal changes in genetic diversity and study past patterns of gene flow in relation with historical landscape composition52.Coalescent-based analyses support the fact that range-wide patterns of genetic structure in ion Fig. . The corion Fig. , we mustD. crassiusculus can be regarded as independent units that require adequate conservation and management strategies to preserve their idiosyncratic evolutionary histories. Conservation actions for D. crassiusculus should be focused on the preservation of areas with sensitive habitat occupied by the main lineages and units delineated by our genomic analyses. These should include the control of negative human interventions and the monitoring of local populations, actions that could also benefit other co-distributed and poorly-known species with similar ecological requirements and fragmented populations linked to gypsum and salt steppes of the Iberian Peninsula67. Given the extremely low number and size of extant populations of the species, ex-situ conservation plans and reintroduction/translocations programmes in restored habitats could help to reduce the chances of species/lineage extinction69. These conservation actions should always consider the genomic singularity of the different units identified in this study and be accompanied with long-term habitat management and population monitoring70. Future studies including detailed ecological information  and genome scans to detect potential loci under selection implicated in ecological adaptation73 would be of great help to get a better understanding of the processes underlying the evolutionary history of the different lineages and refine the conservation actions for this endangered species.Overall, our genomic data support that the different lineages and genetic clusters of Dociostaurus crassiusculus   Fig. . All theet al.74. In brief, DNA was doubly digested with the restriction enzymes MseI and EcoRI  and Illumina adaptors including unique 7-bp barcodes were ligated to the digested fragments. Ligation products were pooled, size-selected between 475–580 bp with a Pippin Prep  machine and amplified by PCR with 12 cycles using the iProofTM High-Fidelity DNA Polymerase . The library was sequenced in a single-read 150-bp lane on an Illumina HiSeq. 2500 platform at The Centre for Applied Genomics .We used NucleoSpin Tissue kits  to extract and purify genomic DNA from the hind femur of each individual. Genomic DNA was individually barcoded and processed into one genomic library using the double-digestion restriction-fragment-based procedure (ddRADSeq) described in Peterson, Stacks v. 1.3577 and PyRAD v. 3.0.6678 to assemble our sequences into de novo loci and call genotypes. This allowed us to examine the robustness of our analyses based on SNP datasets obtained using two of the most popular programs currently available to assemble RAD-seq data78. The choice of different filtering thresholds using either Stacks or PyRAD had little impact on the obtained inferences50. For this reason, unless otherwise indicated, all downstream analyses were performed using a SNP dataset obtained with Stacks including only those loci that were represented in at least four populations (p = 4). See Supplementary Methods for additional details on sequence assembling and data filtering.We used both P), nucleotide diversity (π), observed (HO) and expected (HE) heterozygosity, and the Wright’s inbreeding coefficient (FIS), were calculated using the program populations from Stacks75. For biallelic RADSeq loci, π is an estimate of expected heterozygosity and is therefore a useful measure of the genetic diversity of populations. Furthermore, FIS measures the reduction in observed heterozygosity as compared to expected heterozygosity for an allele in a population, with positive values indicating non-random mating or cryptic population structure82. Pair-wise FST values of genetic differentiation were calculated between all pairs of populations in Arlequin v.3.583. We used PGDSpider v. 2.1.0.384 to convert Variant Call Format (VCF) files provided by Stacks into the correct format needed for Arlequin.Population genetics statistics, including major allele frequency . For each dataset, we ran Structure assuming correlated allele frequencies and admixture and without using prior population information86. We conducted 15 independent runs for each value of K, where K ranged from 1 to n + 1 for the dataset of n populations, to estimate the “true” number of clusters with a burn-in step of 100,000 iterations followed by 200,000 MCMC cycles. We retained the ten runs having the highest likelihood for each value of K and defined the number of populations best fitting the dataset using log probabilities [Pr(X|K)]87 and the ΔK method88, as implemented in Structure Harvester89. We used Clumpp v. 1.1.2 and the Greedy algorithm to align multiple runs of Structure for the same K value90 and Distruct v. 1.191 to visualize as bar plots the individual’s probabilities of membership to each inferred genetic cluster. Complementary to Bayesian clustering analyses and in order to visualize the major axes of population genetic differentiation, we performed individual-based PCA using the R 3.3.3 (R Core Team 2017) package Adegenet92.We analysed population genetic structure and identified groups of individuals with similar ancestral gene pools using the Bayesian clustering method implemented in the program Snapp v.1.3.093 plug-in for Beast v.2.4.594. Due to the large computational demands of this program, Snapp analyses were conducted using a random subset of 2,500 SNPs and including four populations  representative of the main geographical areas  (see Results section). We ran these analyses using different theta priors to allow for different current and ancestral population sizes . The forward (u) and reverse (v) mutation rates were set to be calculated by Snapp and the remaining parameters were left at default values. We used the phrynomics R script written by Barb Banbury (https://github.com/bbanbury/phrynomics) to remove non-binary and invariant SNPs, code heterozygotes, and format input files for Snapp. We used different starting seed numbers to run two independent runs for each scenario, each with >5 million generations sampled every 1,000 steps. Each run was inspected in Tracer v.1.695 in order to check the convergence to stationary of the chains and confirm that Effective Sample Sizes (ESS) for all parameters were always much higher than 200. Afterwards, we combined the two replicate runs for each analysis using LogCombiner v.2.4.5, discarded 10% of trees as burn-in and used TreeAnnotator v.2.4.5 to obtain maximum credibility trees. Phylogenetic trees were displayed with DensiTree v.2.2.596. Complementary to Snapp, we also ran phylogenetic analyses using SVDquartets97 as implemented in Paup* v.4.0a15298. Analyses with SVDquartets included Dociostaurus maroccanus  as outgroup. Phylogenetic trees were constructed by exhaustively evaluating all possible quartets from the dataset and uncertainty in relationships was quantified using 1,000 bootstrapping replicates.We inferred the phylogenetic relationships among the studied populations using the coalescent model implemented in the Fastsimcoal2 and the site frequency spectrum (SFS)100 to compare six hypothetical models of gene flow , effective population sizes (θ), and migration rates per generation (m)100 under the best supported model/s. For Fastsimcoal2 analyses we considered the three genetic groups inferred by Structure and PCAs  and the topology yielded by phylogenomic analyses in Snapp (see Results section)101. For each of the three population groups considered in the simulations, we selected 11 individuals from the Northern cluster, 12 individuals from the Central cluster, and the 6 individuals from the Southern cluster. A folded joint SFS was calculated considering a single SNP per locus to avoid the effects of linkage disequilibrium102. Because we did not consider invariable sites in the SFS , we fixed the effective population size for one of the populations  to enable the estimation of other parameters in Fastsimcoal2102. The effective population size fixed in the models was calculated from the level of nucleotide diversity (π) and estimates of mutation rate per site per generation (μ), since Ne = (π/4μ). Nucleotide diversity (π) for the population ORCE was estimated from polymorphic and non-polymorphic loci using Stacks  using a custom Python script written by Qixin He and available on Dryad102. The final SFS contained information for 10,167 variable SNPs.We used see Fig. , calcula102. We used an information-theoretic model selection approach based on the Akaike’s information criterion (AIC) to determine the probability of each model given the observed data106. After the maximum likelihood was estimated for each model, we calculated the AIC scores106. AIC values for each model were rescaled (ΔAIC) calculating the difference between the AIC value of each model and the minimum AIC obtained among all competing models (i.e. the best model has ΔAIC = 0). Confidence intervals of parameter estimates for the best supported models were obtained from 100 parametric bootstrap replicates by simulating SFS from the maximum composite likelihood point estimates and re-estimating parameters each time81.Each of the six models was run 100 replicated times using the computing resources provided by CESGA  and considering 100,000–250,000 simulations for the calculation of the composite likelihood, 10–40 expectation-conditional maximization (ECM) cycles, and a stopping criterion of 0.001107. We applied circuit theory and used Circuitscape 4.0109 to calculate resistance distance matrices between all pairs of populations under five hypothetical scenarios of gene flow: (i) a “flat” landscape in which all cells have equal resistance (resistance = 1), which is analogous to geographical distance but more appropriate for comparison with others competing models also generated with Circuitscape25; (ii) topographic roughness (slope); (iii) resistance offered by the boundaries of the main river basins from the study area  and the final layer was transformed to 30 arc-sec (c. 1 km) resolution for subsequent analyses. Natural habitats occupied by the species, natural habitats not occupied by the species, and non-natural habitats were defined according to Corine Land Cover maps110. We considered as natural habitats occupied by the species the Corine Land Cover categories “Natural grassland” and “Sclerophyllous vegetation”, which represent the two habitat classes used by the species according to our own occurrence data3. Natural habitats not occupied by the species included all other habitats falling within the category “Forest and semi-natural areas” plus the category “Pastures”. Non-natural habitats not occupied by the species grouped all other land cover categories, including agricultural areas and artificial surfaces110. The lithological categories constituting the typical habitats occupied by the species  were identified according to our own occurrence data3 and mapped using the spatial dataset OneGeology-Europe (http://info.igme.es/cartografia/oneGeology.asp?mapa = oneGeology). In scenarios iii-v we assigned a range of resistance values  to the barrier (limit of main river basins) or the areas not occupied by the species (non-suitable habitats/lithologies), which allowed us to identify the resistance value for these landscape features that best fits our data of genetic differentiation (FST)111. Non-natural habitats  were assumed to offer twice the resistance than natural habitats not occupied by the species . In Circuitscape, we employed a four-neighbor cell connection scheme in order to make effective the resistance assigned to river basin boundaries, as linear landscape features become permeable through pixel corners under the eight-neighbor cell connection scheme108. Finally, we determined how well the different landscape resistance models fit observed data of genetic differentiation (FST) using multiple matrix regressions with randomization (MMRR) as implemented in R 3.3.3107. The final model was selected following a backward procedure, initially fitting all explanatory terms and progressively eliminating non-significant variables until all retained variables were significant. The significance of the variables excluded from the model was tested again until no additional variable reached significance67.We generated alternative spatially-explicit isolation-by-resistance (IBR) scenarios of population connectivity and tested which one is better supported by observed data of genetic differentiationSupplementary Information


Bactrocera minax (Enderlein) (Diptera: Tephritidae) is an important citrus pest in Asia with a non-uniform distribution. In some locations, it had been reported to occur but was either eradicated or disappeared itself. To understand species dispersal of B. minax, we collected and analyzed 359 individuals from 18 localities in China. One mitochondrial DNA gene fragment (nad4) was used to investigate the genetic diversity and population genetic structure of B. minax. The populations were divided by phylogenetic analyses and statistical parsimony haplotype networks into three branches: a Central China (CC) branch, a Western China (WC) branch, and a Southern China (SC) branch. A total of 93 variable sites  and 91 unique haplotypes were observed in the 359 individuals scored from the nad4 gene of the 18 B. minax populations. This indicated that B. minax had a high level of genetic diversity. These populations also showed a discrete distribution in both the scatter plots of genetic versus geographical distance for pairwise population comparisons and the median-joining network of haplotypes, which revealed the strong genetic structure of B. minax. Bactrocera minax (Enderlein) (Diptera: Tephritidae), is an important pest of citrus fruits in Asia [B. minax was first reported in Sikkim, India in 1920, and the first infestation in China was reported in Chongqing in 1940. This species was formally named the Chinese citrus fly in 1955 to distinguish it from the Japanese orange fly, B. (Tetradacus) tsuneonis (Miyake) [B. minax in 134 counties and cities of nine provinces in China so far, and the geographic distribution of the pest continues to expand.The Chinese citrus fly,  in Asia ,2,3. InfB. minax is considered unique among the members of family Tephritidae in being univoltine, i.e., one generation per year [B. minax live and feed inside host fruit, making effective pest control difficult. Most published research on B. minax has focused on the basic biology, ecology, and behavior [cox1; nad1, cytb, and nad5) were used to infer two main invasion routes and origin of the oriental fruit fly, B. dorsalis (Hendel) [B. minax is scarce despite the current and potential risk from this species.per year ,6. The lbehavior ,8. Popul(Hendel) ,10. Thernad4 is regarded as a very useful marker owing to its high rate of evolution and rich polymorphism [B. minax in Mainland China was investigated through analysis of molecular variations in a fragment of the mtDNA gene nad4, and we also studied genetic diversity among different geographic populations of B. minax in China.Animal mtDNA is a favorite molecule for evolutionary studies due to several special characteristics, such as simple sequence organization, maternal inheritance, and absence of recombination . Among tmorphism . In thisB. minax adults were trapped in citrus orchards through pheromone traps at 18 locations in China  was amplified as described by Zhang [nad4-F (5′-ACAAAACAAACCTGACGAAC-3′) and nad4-R (5′-TAGTAGAATGAATCTTTTTATA-3′). Each PCR was performed in a volume of 25 µL containing 80 ng of total genomic DNA, 0.25 µM of each primer, 1.5 mM MgCl2, 10 × PCR buffer, 0.2 mM dNTPs, and 1.25 U Taq DNA polymerase . The temperature profile included an initial denaturation at 95 °C for 5 min followed by 35 cycles of 94 °C for 45 s, 48 °C for 60 s, and 72 °C for 45 s, and a final extension step of 72 °C for 10 min. PCR products were subsequently purified and sequenced in both forward and reverse directions .Total DNA was extracted using DNeasy Blood and Tissue Kits  from the thorax of each individual. A fragment of the mtDNA gene by Zhang , using pD test [F statistic [Sequence alignment and identification of unique haplotypes were performed using ClustalX ver. 2.1 , and theD test , Fu’s F tatistic , and mistatistic ,18. Desctatistic , includiK) was the value that maximized CTF. ARLEQUIN ver. 3.11 was used to perform hierarchical analysis of molecular variance (AMOVA) based on the grouping results from SAMOVA, including comparisons among groups, among populations, and within populations.The 18 geographic populations were grouped using SAMOVA ver. 1.0 based on sequence information and coordinate data . The mosPairwise genetic distances between populations were estimated using MEGA ver. 5.05 , and thenad4 gene, 93 variable sites  and 91 unique haplotypes were observed (GenBank accession numbers KF310532-KF310890). The nad4 protein-coding region began at the first site of the sequence. Like the two mitochondrial genes 16S rDNA and COI (A+T biased) [nad4 was also biased toward A+T (65.5%). The populations showed a high level of haplotype diversity (h) which ranged from 0.386 at WZ to 0.928 at WL, nucleotide diversity (π) ranged from 0.001 at JZ to 0.009 at JY, and the average number of nucleotide differences (k) ranged from 0.837 at JZ to 5.584 at JY, except for the ZX population   , the bas< 0.001) . Only 15CTF values suggested an optimum of three groups for the 18 populations, as follows: (i) Central China ; (ii) Western China ; and (iii) Southern China . Results of AMOVA showed that the largest percentage of variation (46.15%) occurred among groups , indicating that there may be factors limiting the gene flow among regions.The g groups , while 1STF values among populations ranged from −0.018 (between the FC and LZ population) to 0.796 (between the WZ and ZX population), while the average values ranged from 0.277 (from the other populations to LL) to 0.612 (from the other populations to YC)  < 0.315 (between CC and SC) (Pairwise s to YC) . Pairwis and SC) .M ranged from 47.0 (WZ→ZG) to 838.3 (LL→JZ), and no asymmetrical gene flow was found. The gene flow values among populations ranged from 0.156 (WL→ZX) to 21.508 (TY→ZG), the immigration rates varied from 0.322 of ZX to 10.006 of TY, and the emigration rates from populations ranged from 1.561 of FC to 3.319 of SY. The immigration rates of ZG, TY, and LL populations  were significantly higher than the emigration rates of these three populations, and were also significantly higher than immigration rates of other populations.The migration rates were estimated using Bayesian inference in Migrate ver. 3.5.1, which revealed high effective immigration rates per generation between regions . Unidirenad4 sequences showed that the SC cluster had the lowest immigration rate (1.175) and the highest emigration rate (22.785), and the situation (the immigration rate < the emigration rate) was opposite to the CC and WC clusters  were located centrally, with rare haplotypes connected to them through few mutations. Six haplotypes  were shared by at least two groups but only two were shared by all three groups  .nad4 gene, neutrality test results showed that Tajima’s D values were significantly negative for all B. minax populations pooled together and the CC+WC clusters , but not for the SC cluster . Tajima’s D values ranged from −2.398 (p < 0.01) of WZ to 1.639 of HZ (p > 0.05). The values of Tajima’s D were significantly different among these populations  and also significantly negative in each population (ranging from −34.028 of JZ to −15.700 of WL), except for the ZX population  (Based on the ulations . Fu’s Fs > 0.05) .nad4 data from the 18 populations and each population group revealed a sudden demographic expansion (τ) ranged from 0.000 (ZX) to 10.309 (YC)  of 1.7 × 10−8 per year for mitochondrial genes [nad4 gene of B. minax was in the YC population with about 448,000 years, XX and JZ populations were approximately 10,000 (τ = 0.066) and 170 (τ = 0.004) years old. And the most special was the ZX population with no expansion history (τ = 0.000), which may be newly established.The unimodal mismatch distributions based on xpansion . The exp309 (YC) . To estial genes . The oldB. minax populations had moderately high levels of genetic diversity except the ZX population with only one haplotype, which may represent a newly-colonized site. Based on the pairwise STF values for nad4 sequences, the 18 B. minax populations were highly genetically differentiated. Meanwhile, the AMOVA results of the 18 populations showing 46.15% variation among groups, indicating a strong population genetic structure of B. minax in Mainland China. Moreover, the scatter plots of genetic versus geographical distances for pairwise population comparisons and the median-joining network of haplotypes also exhibit a discrete distribution and support the same conclusion. Combining the differences among SAMOVA with phylogeny analysis and pairwise STF values among populations, we hypothesize that B. minax may have invaded these areas on multiple separate occasions. The results of AMOVA and haplotypes phylogeny analyses, based on nad4 sequence data, showed limited gene flow among regions and suggested that the Yangtze River, Nanling Mountains, and Wushan Mountains may have acted as substantial barriers to gene flow.A species’ genetic resources exist at two fundamental levels, genetic differences among individuals within local populations and those among populations . All theSTF estimates will increase with geographical distance [B. minax in mainland China. In contrast, the immigration rate (21.591) was much higher than the emigration rate (3.199) in the WC cluster, while the immigration rate (8.696) was basically symmetrical with the emigration rate (5.447) in the CC cluster  indicated that there was still excess heterozygosity in some B. minax populations. Moreover, the unimodal mismatched distributions of the nad4 gene within the 18 B. minax populations meant a population expansion in agreement with the negative Tajima’s D, and reflected the main coalescence depth of the haplotypes which is ultimately traces to a single ancestor.Four main factors promote biological evolution: mutation, gene flow, random genetic drift, and natural selection . Levels distance . The val cluster . The genulations , the rea Fs test ,36. The  Fs test . Based oB. minax was first recorded in mainland China. Since then, B. minax has continued to spread. It was found in five provinces in 1957, six in 1966, eight in 1995, and nine in 2006. The centers of origin and the diffusion paths of B. minax are unknown. In this study, it was found that the oldest coalescence time for nad4 gene in B. minax was about 448,000 years ago, and the ZX population may be newly established with no expansion history. As to the demographic history the major dispersal routes of B. minax into Mainland China, we would need more loci and more samples.In 1940, B. minax individuals from 18 localities in China, and used a mitochondrial DNA gene fragment nad4 to investigate the genetic diversity and population genetic structure of this species. Eighteen B. minax populations were divided by phylogenetic analyses and statistical parsimony haplotype networks into three branches: a Central China (CC) branch, a Western China (WC) branch, and a Southern China (SC) branch. A total of 93 variable sites and 91 unique haplotypes were observed in the 359 nucleotides scored from the nad4 gene, which indicated that B. minax had a high level of genetic diversity. These populations also showed a discrete distribution in both the scatter plots of genetic versus geographical distance for pairwise population comparisons and the median-joining network of haplotypes, which revealed the strong genetic structure of B. minax.We collected 359


Populus davidiana, a widespread species distributed in Eurasia. Three groups in northeast, central, and southwest China were constructed according to the simulation results from SAMOVA, composition of chloroplast haplotypes and structure results. We revealed that the northeast China had endemic haplotypes, the haplotypes and nucleotide diversity in northern regions were not lower than that in southern China, and this species has not experienced population expansion base on the estimation of Bayesian skyline plots. Ecological niche modeling (ENM) indicated that the northeast China had a high suitability score during the last glacial maximum. The combined evidence clearly demonstrated that northeastern and southwestern refugia were maintained across the current distributional range of P. davidiana during the LGM. The genetic differentiation between these two refugia might be mainly caused by differences of climate among these areas. The phylogeographic analyses of a widely distributed P. davidiana provided robust evidence to clarify the issue of refugia in northeast China, and these results are of great importance for understanding the influence of Quaternary glaciations on the distribution and evolution of species in East Asia.Despite several phylogeographic studies had provided evidence to support the existence of glacial refugia of cool‐temperate deciduous trees in northeast China, the species used in these studies were limited by the species ranges, which could not exclude the possibility that northern populations were the colonists from southern refugial populations during the last glacial maximum (LGM). Here, we estimated the nucleotide variation in  DB (Dongbei)the northeast of ChinaHB (Huabei)the central ChinaNF (Nanfang)the southwest of China1Climatic oscillations have profoundly affected the current distributions and genetic structures of many plant and animal species in the Northern Hemisphere in the past three million years Hewitt, . In EuroCastanea, Castanopsis, Cyclobalanopsis, Fagus, Pterocarya) and eurythermal  broad‐leaved tree taxa in tropical or subtropical areas of China , a temperate deciduous tree distributed continuously in mainland China, Mongolia, Korea, and the Far East of Russia, which is a keystone species in boreal forest communities. P. davidiana is highly resistant to cold, drought, and barren soils. Natural populations mainly grow on slopes, ridges, and gullies, often forming a small area of pure or mixed forest with other tree species, so the influence of human activities on their distribution is relatively small. Therefore, P. davidiana is an excellent model to shed light on the phylogeographical history of Asian trees.P. davidiana. We specifically aimed to address: (a) whether or not glacial refugia existed across northeast China, and (b) reconstruct the Quaternary history of the species through evaluating the distribution patterns of chloroplast haplotypes and nuclear gene polymorphisms within and among populations of P. davidiana.To verify the two possible origins of cool‐temperate deciduous trees in northeastern China, it is necessary to obtain a widely distributed species’ population structure and genetic diversity distribution. In this research, we used both nuclear and cpDNA sequences and ecological niche models (ENMs) to identify the phylogeographic patterns of 22.1P. davidiana were sampled from 32 natural populations throughout its distribution range in mainland China  and six single‐copy nuclear loci  were used to amplify and sequence 8 to 30 P. davidiana trees of the 32 populations. Primers used are listed in Supporting information Table P. davidiana and Populus tremuloides  were downloaded from GenBank (accession numbers KP887111–KP887162). The new sequences were deposited in GenBank under accession numbers .Total genomic DNA was isolated from ~25 mg silica‐gel‐dried leaf from each individual of 32 natural populations using a modified CTAB method Doyle, . Based o2.32.3.1http://www.fluxus-engineering.com) following the median‐joining method, in which all indels were not considered.The assembled contigs of each individual were aligned using CLUSTALX  was performed for cpDNA sequence matrices to define the number of population groups using SAMOVA 2.0  and haplotypes (H), haplotype diversity (Hd), nucleotide diversity parameters (π), Watterson's θw , were estimated for the regions (the composition of these regions are listed in the Table FST) for each nuclear locus was also calculated in Arlequin 3.5.2.2  ranging from 1 to 10 and 20 replicate runs were carried out for each K. We used the admixture model and the correlated allele frequencies model to estimate the genetic structure of P. davidiana. All runs included a burn‐in period of 100,000 iterations, following 1,000,000 Markov Chain Monte Carlo repetitions with the aim of ensuring the reproducibility of the STRUCTURE results , Ln P (K), and the rate of change of Ln P (K) between successive K values , which were obtained from the STRUCTURE results, an analysis of molecular variance (AMOVA) was performed in Arlequin 3.5.2.2 , population divergence time . Markov chain simulation for 5 × 107 steps, where the first 5 × 106 were discarded as burn‐in; and uniform prior distributions from 0 to 5 for tpop. Convergence was determined by assessing the consistency of model values for each of the parameters across three runs. The modes of the posterior distribution for both T and θ were used to estimate divergence times between pairwise clades. We assumed a mutation rate of 2.5 × 10−9 per site per year and a generation time of 15 years in Populus , and the last glacial maximum (LGM) using MAXENT v.3.3.335 . Climate estimates for the LGM were provided by the Community Climate System Model (CCSM) and the Model for Interdisciplinary Research on Climate (MIROC) 3.2 (http://www.pmip2.cnrs-gif.fr) at 2.5 arc‐min resolution, as well as climate estimates for the current time (http://www.worldclim.com). In addition, we projected the model to the LIG  using the climate model of Otto‐Bliesner et al.  were contained in the cpDNA sequences of the P. davidiana. Haplotypes distributed in each population are presented in Figure P. davidiana, two (SYJY and BJ) were fixed by a single haplotype (H5 and H11), while the remaining 31 were polymorphic.Fifty‐one haplotypes were found in the combined cpDNA sequences of K = 2 to K = 5 and then reached a plateau at K > 5. However, if single‐population clusters were left out, as is usual in SAMOVA, we ended up with K = 3 as the optimal number of population groups ; and between northeast and southwest: NST » GST  ranged from 0.571 to 0.656 for the six nuclear loci. The mean diversity levels of nucleotides and haplotypes of the nuclear loci in the DB and HB were slightly higher than in the NF region (Table Rm) of the nuclear loci ranged from 1 to 12 in the species, implying high levels of outcrossing. As expected, the sequence variation of cpDNA was lower than the nuclear loci, which was reflected by the lower mutation rate in the chloroplast genome of plants and the lower effective population size of the cpDNA.The nucleotide diversity of each locus is shown in Table on Table . For sinThe average haplotype diversity ranged from 0.375 to 0.406 and nucleotide diversity varied between 0.0002 and 0.0005. The mean diversity levels in the DB and HB were slightly higher than those in the NF region  and ranged from 0.0069 to 0.5820 for the five nuclear loci (Table The 3.3K), increased linearly from K = 1 to K = 2, and then increased slowly up to K = 8, while the highest ΔK occurred at K = 2  and ranged from 14.75% at DSH 7% to 24.51% at DSH12 (Table p < 0.001). Approximately 12.63% of the total variation was attributed to the variation among populations within group (7.99%–12.67%). Within each group, the average variation components among populations (4.35%–20.87%) were much lower than that within populations (79.13%–95.65%). The pairwise FST values showed strong genetic differentiation among groups (0.251–0.362), and all values were significant (Table AMOVA indicated that variations among groups were significant (3.4Bayesian skyline plots (BSP) revealed effective population size of the three groups Figure . It show3.5P. davidiana had a high predictive power, with an area under the receiving operator curve of 0.987 (p < 0.001). The distributional prediction under current climate conditions was a good representation of the extant species distribution between 25°N and 55°N . Analysis of the differences in genetic diversity between the extent geographic distributions is the major method for reconstructing species histories during the Quaternary  was not lower than other regions, and this was supported by the mean higher level of haplotype and nucleotide diversity of the cpDNA locus  only existed in the NF region and the ancient haplotype H5 mainly appeared in southwest China Figure . The div only exia Figure . Based o4.3et al. . These results together with the AMOVA analysis indicated high genetic differentiation between pairwise groupsThree main phylogeographical groups  were uncovered in the distribution of P. davidiana is a wind‐pollinated species and there were several mixed zones of populations in DB, HB, and NF groups according to our study. It was surprise that genetic variation still significantly existed between these regions, indicating that geographic isolation might not be the main reason to produce genetic differentiation among the three groups. On the other hand, the populations of P. davidiana in SOUTH (excluding GBJD population) group mainly distributed in south of Sichuan Province, west of Guizhou Province and Yunnan Province .The new sequences were deposited in GenBank under accession numbers ( Click here for additional data file.