Ovis canadensis). Based on a long‐term pedigree and individual monitoring, we documented the genetic decline, restoration and rescue of the population. Microsatellite analyses revealed that the demographic bottleneck reduced expected heterozygosity and allelic diversity by 6.2% and 11.3%, respectively, over two generations. Following supplementation, first‐generation admixed lambs were 6.4% heavier at weaning and had 28.3% higher survival to 1 year compared to lambs of endemic ancestry. Expected heterozygosity and allelic diversity increased by 4.6% and 14.3% after two generations through new alleles contributed by translocated individuals. We found no evidence for outbreeding depression and did not see immediate evidence of swamping of local genes. Rapid intervention following the demographic bottleneck allowed the genetic restoration and rescue of this bighorn sheep population, likely preventing further losses at both the genetic and demographic levels. Our results provide further empirical evidence that translocation can be used to reduce inbreeding depression in nature and has the potential to mitigate the effect of human‐driven environmental changes on wild populations.Isolation of small populations is expected to reduce fitness through inbreeding and loss of genetic variation, impeding population growth and compromising population persistence. Species with long generation time are the least likely to be rescued by evolution alone. Management interventions that maintain or restore genetic variation to assure population viability are consequently of significant importance. We investigated, over 27 years, the genetic and demographic consequences of a demographic bottleneck followed by artificial supplementation in an isolated population of bighorn sheep ( The population suffered a demographic bottleneck in 1992–2002 when a density‐dependent decline  , is 30 km east of the Canadian Rockies. Due to its geographic isolation, immigration is rare. Since 1972, individually marked bighorn sheep have been monitored and captured 2–5 times per year  and FSTAT . We compared the genetic parameters of the translocated sheep with the native population (sheep born on Ram Mountain) using these measures. We also contrasted the population of native residents to a sub‐group of nonadmixed native residents (Ram Mountain ancestry only), to evaluate how the population benefited from admixture over time.We obtained accurate measurements of the genetic decline and restoration of the Ram Mountain population following the demographic bottleneck and translocations, because nearly all individuals that survived to a few weeks of age were sampled. PCR amplification was performed at 26 ungulate‐derived microsatellite loci  residents. The first admixed lamb was born in 2003. Thus, we only considered 2003–2016 for analyses of genetic rescue. Maternities and paternities were known for all 173 lambs born in 2003–2016. Of these, seven were F3 offspring that were excluded from genetic rescue analyses due to low sample size. During this period, nonresident males sired 39 (22%) resident lambs. These sires arrived at Ram Mountain for the rut, as is typical of bighorn sheep . Movement of males between these two mountains has been documented, and both populations are considered the same genetic unit  and the interaction between sex and admixture  fixed effects  and linear mixed models (LMM) to analyse the effect of outbreeding on fitness‐related traits in juveniles from 2003 to 2016. Models were fitted using the Crawley, . Explain2.5popbio package , however, did not differ between 1990 and 2003 (Table FST) was 0.015 (95% CI: 0.006–0.027) between the pre‐ and postdecline Ram Mountain native resident population. An additional four alleles present in 1990–2003 were lost before 2016  between translocated individuals and the 2003 nonadmixed native residents was 0.127 (95% CI: 0.088–0.167), and both populations contained several private alleles  reproduced in the study population Table . For tra5% reprod3.3FST) was 0.022 (95% CI: 0.010–0.035) between the pre‐ and post‐translocation Ram Mountain native resident population. Genetic restoration began in 2006 and genetic diversity of the native resident group recovered to values measured in the predeclining (1990) population by 2016  or summer mass gain . The interaction between sex and admixture was not a significant predictor for any response variable for lambs or yearlings  differed by 1.3% in scenarios with  and without genetic rescue  . High predation following a density‐dependent decline led to a demographic bottleneck and population stagnation. The drastic decline of 83% in population size over two generations was followed by a significant decrease in genetic diversity as predicted by genetic drift (Nei et al., 1 lambs providing an opportunity for recovery. We suggest that the increase in population size observed in 2015–2017 was partly attributable to increased fitness of F1 juveniles. Our comparison of female‐based demographic scenarios with and without genetic rescue suggests that even a small input of outbred sheep favours population persistence. Those demographic scenarios, however, should be interpreted with caution because they used the same vital rates for adult females and simulated a fixed proportion of admixed individuals in the population over time (Supporting Information Appendix 3 generation and to remain at that level subsequently, unless the population becomes inbred again (Frankham, 1 lambs of both sexes had higher fitness compared with nonadmixed lambs regardless of the sex of the translocated parent. Contrary to our expectations, however, we did not find evidence for increased fitness in F2 juveniles. Smaller sample sizes for F2 and lack of statistical power may explain these different results. Further investigation will seek to identify the mechanisms behind the genetic rescue of Ram Mountain where significant increases in F1 fitness were observed despite modest decline in genetic diversity. Increased fitness following outbreeding may have occurred through a reduction in inbreeding or adaptive evolution (Whiteley et al., At Ram Mountain, prior to translocations, juvenile recruitment was the dominant demographic parameter in periods of population stagnation and increase (Coulson, Gaillard, & Festa‐Bianchet, The potential for outbreeding depression is a primary concern with translocations and is supported by theory Edmands, . Recent Translocations of bighorn sheep are frequently used for conservation of this species (Brewer et al., Given the current rate of habitat loss and human‐induced environmental changes, many populations may not be able to adapt or persist. Species with long generation times, such as bighorn sheep, are the least likely to be rescued by evolution (Vander Wal et al., The study was authorized by the Université de Sherbrooke Animal Care Committee, affiliated with the Canadian Council on Animal Care, protocols MFB2006‐01 and MFB2014‐01.The authors declare no conflict of interests.M.A.P. designed the study, conducted statistical analyses and wrote the first draft of the manuscript with input from M.F.B. and F.P.; D.C. performed molecular analyses and paternity assignments; M.A.P., M.F.B. and J.J. collected field data; and J.J. supervised sheep translocations. All authors contributed to the writing and revision of the manuscript. Click here for additional data file.


Rhodeus notatus collected from seven different rivers to obtain better understand historical gene flow of freshwater fish on the Korean Peninsula. Based on our phylogenetic analyses, this Korean species originated through the paleo-Yellow River from China and first colonized near the west coast. These genetic data also provided evidence of estuary coalescences among the rivers flowing to the west and southwest coast on well-developed continental shelf. In addition, the pattern of population structure revealed the biogeodispersal route from the west coast to the south coast. It could be inferred that massive migration was not involved in the formation of southern populations, since the signature of historical genetic drift was clearly observed. Our study is the first genetic attempt to confirm hypotheses describing the migration of freshwater species towards the end of East Asia, which have previously been developed using only geological reasoning.The modern-day distribution of freshwater fishes throughout multiple rivers is likely the result of past migration during times when currently separate drainages were once connected. Here, we used mitochondrial and microsatellite analyses for 248 individuals of  The high degree of interpopulation genetic differentiation normally found in freshwater fish species has often been attributed to the fragmented nature of freshwater environments7. However, the distribution of freshwater fish species throughout multiple drainage basins is likely the result of past migration during times when currently separate drainages were once connected8. Insight into historical changes in past drainage systems and gene flow in a given region can be obtained by characterizing the pattern of genetic diversity and structure among populations that are currently spatially separated10.Primary freshwater fish species living in separate river systems are not able to come into contact naturally. Even within a single river system, populations can be isolated by landscape structures13. This peninsula is a small but complex mountainous terrain that was created in the course of large-scale tectonic events from the early Triassic to early Miocene eras14. The sea between the western part of the Korean Peninsula and China is known to have been a lake into which the Yellow River once flowed; this lake was connected to the estuaries of many rivers flowing to the west coast on the Korean Peninsula15. Previous studies16 have claimed that many fish species found in these western-flowing rivers on the Korean Peninsula originated from the paleo-Yellow River system. Since the estuaries of these western-flowing rivers are connected or located in proximity on the huge continental shelf that is present around the west coast, it is presumed that freshwater fish species could move to other rivers whenever the sea levels became much lower than at present during the Pleistocene18. These rivers may have been isolated from the rivers that flow to the south coast where the continental shelf is not as well developed9. The coastal rivers on the east of the Korean Peninsula, which are surrounded by mountain ranges and are thought to have historically been influenced by the Amur River system from the north (east Russia), can also be regarded as an isolated region19. In this way, the freshwater system on the Korean Peninsula can be seen as having three independent historical subdistricts15.The geography of the Korean Peninsula provides an excellent opportunity to explore the connections among the historical formation of freshwater systems and the colonization of freshwater fishRhodeus notatus is a small freshwater bitterling species  native to China and the Korean Peninsula20. Before Kim revised the taxonomy of Rhodeus15, R. notatus of the Korean Peninsula was called R. atremius or R. suigensis in Japan or treated as a subspecies of R. atremius 21. In fact, R. notatus has often been recognized as a member of the species complex including these two Japanese (sub)species and R. fangi in China, because these species share both the same number of chromosomes , which is one pair less than other congeners, and other morphological features24. The Korean species was eventually synonymized with R. notatus after it was demonstrated that it had more morphological traits in common with Chinese R. notatus than other species within this species complex15. On the Korean Peninsula, R. notatus inhabits rivers flowing into the west and south coasts25. The distribution of this species preserves the historical imprints of migration through the paleo-Yellow River and the process of spreading to the freshwater system on the Korean Peninsula. The species could have migrated between rivers by sharing estuaries on the west coastal continental shelf11. Given that the continental shelf is not well-developed around the south coastal region, however, estuary coalescence might not be a major way to colonize the rivers flowing into the south coast, but instead it is more likely that gene flow occurred through the sharing of spatially proximal watersheds due to topographical erosion13. If so, large-scale population migration could not have been possible.R. notatus  the populations located in the rivers flowing into the west coast have genetic and phylogenetic signatures of estuary coalescence, iii) the populations of rivers flowing into the south coast where the continental shelf is not well-developed have signatures of history isolated from the western populations, and iv) the populations of the rivers flowing to the south coast, which probably formed through small-scale migration, have signatures of historical genetic drift.In this study, six mitochondrial and eight microsatellite loci were analyzed to estimate the level of intrapopulation genetic diversity, genetic structure among all major populations found on the Korean Peninsula and phylogenetic placement of tus Fig. . The resR. notatus. A total of 9, 15, 12, 8, 10 and 15 unique haplotypes were identified from the sequence alignments of COI (KY628232 – KY628240), NADH1 (KY628271 – KY628285), NADH2 (KY628259 – KY628270), 16 S (KY628241 – KY628248), 12 S (KY628249 – KY628258) and cyt b (KY628286 – KY628300), respectively (Supplementary Table h) varied between 0.200  and 0.844  and southern population groups  caused by the presence of null alleles, according to the results of Micro-Checker27. The overall level of interpopulation genetic differentiation was substantial with global FST = 0.361 and RST = 0.894  values with a few exceptions , suggesting the significant contribution of stepwise mutations to interpopulation genetic differentiation at the microsatellite loci. However, the average pairwise RST values were much lower than those of pairwise FST in the comparisons among populations of southern population group  approach was applied to identify historical pathway from western population group to population TJ using DIYABCata Fig. . These fata Fig. . Our DIYata Fig. , indicates Table .Figure 6Rhodeus notatus populations examined in this study is quite low, given that fewer than two haplotypes per mitochondrial locus were observed in a population. Although no direct comparison was attempted using the same loci, the average number of microsatellite alleles per locus in a population was much below the known freshwater fish average32. Tanakia somjinensis, also a member of Acheilognathidae, has a much higher microsatellite diversity than R. notatus29. Given that T. somjinensis is a highly restricted Korean endemic species and is protected by Korean authority33, careful monitoring and management strategies for R. notatus will likely be required.The average intrapopulation genetic diversity of the eight R. suigensis and R. atremius were the earliest branches from the clade of R. notatus species complex, suggesting that this complex originally evolved near Japan, or that peripheral speciation occurred around Japan from a widely distributed common ancestor. This prediction aligns with the previous claims that there have been widespread migrations of freshwater species between China and Japan via the Korean Peninsula36. In addition, the clear phylogenetic division of the Japanese species from others may be related to the geological process in which Japanese Archipelago has become completely separated from the continent by the sea. It can be assumed from our data that R. notatus on the Korean Peninsula originated through the paleo-Yellow River, based on the results of historical distribution estimation using our DEC model analysis and its phylogenetic affinity to the Chinese populations of R. notatus and R. fangi.The results of our phylogenetic analysis revealed that two Japanese species, R. notatus haplotypes are distinct from all Korean R. notatus haplotypes, it is difficult to determine the origin of R. notatus on the Korean Peninsula using only the degree of genetic affinity to Chinese haplotypes. The presence of strong genetic structure in the western population group demonstrates that there has been little active gene flow among the populations formed by paleo-yellow confluence. From the results of our haplotype network, DEC model and DIYABC analyses, we attempted to reconstruct the historical pathway to form southern population group from western population group. Solely based on our DEC model results, some individuals from population HG further migrated south to form a peri-Tamjin River population (TJ). It might be possible that populations GE and MG might have formed from the dispersal from population HG; both our haplotype network and microsatellite analyses indicate that the southern population group and population TJ had the closest genetic affinity with population MG. These results were also supported by DIYABC simulation and showed, at least indirectly, the historical trace of a dispersal over time from north to south on the west coastal continental shelf and to southern coastal rivers through population TJ.Given that Chinese 38; however, our data do not suggest that population TJ has even been particularly large throughout its history. This suggests that the region encompassing population TJ might have received migrants from several western coastal populations on the Korean Peninsula. Two slightly differentiated haplogroups were present in the monophyletic population TJ can be considered as evidence of gene flow from multiple isolated regions. Although the Korean Peninsula has never been covered with glaciers during Pleistocene glacial advances, cold and arid weather had persisted long even in the central region39 where the populations HG and GE are located. Under these historical circumstances, there may have been massive migration of freshwater species to more favorable regions, and large populations may have been formed in the southwestern corner.The genetic diversity of population TJ was high compared to other populations in both mitochondrial and microsatellite loci. Although the mitochondrial diversity of population HG was also high, its microsatellite diversity was substantially lower than others, with half of the loci being completely fixed to a single allele. Models of neutral evolution suggest that genetic diversity is roughly proportional to the size of a populationAlthough population YS is also located on the southwestern corner of the Korean Peninsula, no clear signature of historical gene flow was identified from the western population group. Our genetic analyses revealed that population YS showed some degree of genetic affinity with population TJ and with the southern populations, SJ, NA1 and NA2. This result suggested the presence of a biogeographic pathway from population TJ to YS and then to the southern populations. The biogeographic route of freshwater systems along the south coast has never been reported to date, and in this respect, our results are of great importance.40. Massive gene flow might not have been possible through watershed capture, as predicted in the introduction. The results of our various analyses help prove this assumption. First, our M-ratio data showed the signature of historical bottlenecks in populations SJ, NA1 and NA2. Second, at a regional level, the relative contribution of stepwise mutations to genetic differentiation among populations of southern population groups was much less pronounced; it is more likely that genetic drift was the cause of the differentiation among these populations. Finally, as evidenced by our EBSP, the populations of southern population group had likely undergone historical size decline.As noted above, unlike the west coast of the Korean Peninsula, the continental shelf is not well developed around the south coast, and opportunities for past rivers to share estuaries with sea level fluctuation may not have existed. Indeed, studies have reported on the signature of gene flow by watershed capture between southern-flowing riversPopulation NA2 contained rather unusual haplotypes that were genetically close to those of the western population group, especially population HG. It is not reasonable to suspect that such a genetic composition was caused by anthropogenic introduction of this species living in the Han River into the Nakdong River, because these two populations did not share the identical haplotypes. In addition, such a genetic pattern was not observed in our microsatellite analysis. Considering that the watershed locations of the Han and Nakdong Rivers are spatially proximal, it is possible that these haplotypes of population NA2 were naturally distributed; however, no direct evidence has yet been reported in support of this hypothesis.R. notatus. First, our study revealed that R. notatus on the Korean Peninsula originated through the paleo-Yellow River system from China. Second, our genetic data demonstrated that the rivers flowing into the west and southwest coasts had formed confluence with the paleo-Yellow River system. However, the presence of a strong and complicated genetic structure within the western population group implies that historical gene flow among populations was not highly active, probably because long-term perfect confluence has not been formed, and the topographical structure on the continental shelf has strongly influenced on the pattern of gene flows. Third, the rivers flowing to the south coast seem to have been completely isolated from the confluence on the west and southwest, considering the great genetic difference between the western and southern population groups. Our data demonstrate that populations on the southwest corner had served as a biogeodispersal passage from west to south on the peninsula. Finally, migration among the populations of southern population group might have been possible only by small-scaled watershed captures, which was supported by the signature of historical genetic drift found in populations SJ, NA1 and NA2 from our results. This study represents the first use of molecular genetics to characterize the process of shaping contemporary distribution of freshwater species in the southwestern part of the Korean Peninsula. The inferences about the various fine-scale biogeographic pathways obtained here can be verified by a comparative study in the future with taxa having similar geographical distribution, for example, R. sinensis of the same genus.We were able to address our major questions regarding the geographic origins of extant diversity among populations of Rhodeus notatus individuals used in our genetic studies were 248 specimens stored at the Department of Life Sciences, Yeungnam University. Those specimens were collected from eight populations on seven different river basins flowing into west coast  and south coast , NADH dehydrogenase subunit 1 (NADH1), NADH dehydrogenase subunit 2 (NADH2), 12 S rRNA (12 S) and 16 S rRNA (16 S), were sequenced for 10 selected R. notatus individuals per population. Information on the mitochondrial primer sets used in this study45 was provided in Supplementary Table Taq buffer (containing 2.5 mM MgCl2), 0.25 mM dNTPs, 1 μM of each primer and 0.25 units of Taq DNA polymerase . Thermal cycling was composed of an initial denaturation at 95 °C for 5 min, 35 cycles of a denaturation at 95 °C for 30 sec, an annealing at 54 or 56 °C , cytochrome 46. The coding loci, including COI, cyt b, NADH1 and NADH2, were examined against the inferred reading frame for the corresponding proteins using MEGA 6.0647. The intrapopulation genetic diversity was quantified by the number of haplotypes (hn), haplotype diversity (h)48 and nucleotide diversity (π)48 estimated using DnaSP 5.1049. The unrooted haplotype network was generated for the six mitochondrial loci and the concatenated sequences of all loci based on the connection limit above 0.95 in probability using TCS 1.26350 to analyze the distribution of haplotype diversity.All mitochondrial sequences were rechecked through BLAST searches and aligned using Geneious 9.1.851, and GTR + I + G was chosen as the best-fit substitution model by jModelTest 252 as the best-fitting nucleotide substitution model. BI analysis consisted of two parallel runs of 80 million Markov Chain Monte Carlo (MCMC) generations with sampling every 1,000 steps. The consensus tree for each data set was generated after removing the first 25% of sampled trees as burn-in. The Bayesian posterior probabilities (in percent) were presented as the node confidence in the tree. The ML tree analysis was conducted using IQ-Tree 1.3.10 with 10,000 ultrafast bootstrap replicates53. The best-fit substitution model was chosen to be GTR + I + G based on Bayesian Information Criterion (BIC) using ModelFinder54 implemented in IQ-Tree. Cyt b sequences were used in divergence time estimation using BEAST 2.3.026. This mitochondrial locus was used for this analysis because the cyt b sequence was most commonly reported in bitterling and cyprinid species that could be used as comparative materials from China and Japan and outgroups; see Supplementary Table th generations, using GTR + I + G selected by jModelTest 2 as the best-fitting nucleotide substitution model. A Yule tree prior and an uncorrelated lognormal relaxed-clock were implemented on this analysis. Calibration of the molecular clock was conducted by using the earliest fossil record data of Acheilognathidae56 for the basal node of this family . Tracer 1.65757 was used to examine the convergence of run parameters by determining whether ESSs (effective population sizes) exceeded 200. The maximum clade credibility tree with median heights was generated using TreeAnnotator 2.3.058, after discarding the first 25% of trees as burn-in. FigTree 1.4.259 was used to visualize the topology of the consensus tree generated with divergence times. The biogeographic history of R. notatus and the closely related species was explored under the dispersal-extinction-cladogenesis (DEC) model of geographic range evolution60 implemented in RASP 3.261. The DEC model was used to assess the likelihood of all possible ancestral distributions at a given node57. A biogeographic model was constructed by coding each species or population used in the BEAST analysis as occurring in one of the nine regions including the seven drainage basins in which Korean R. notatus individuals were collected, China and Japan. The tests of DEC were performed based on the parameters obtained from our BEAST analysis, and the results were visualized on the tree using Affinity Designer 1.6.1 .Phylogenetic trees were generated under two different algorithms, Bayesian inference (BI) and maximum likelihood (ML). All six mitochondrial loci were used in the reconstruction of phylogenetic trees. BI tree analysis was performed using MrBayes 3.2R. notatus population and genetic cluster based on three different methods. First, Tajima’s D62 and Fu’s Fs63 were calculated using DnaSP. Second, mismatch distribution analysis was carried out to show the observed distribution of pairwise differences between mitochondrial sequences under the model of population expansion64 using Arlequin 3.565 for each genetic cluster. Finally, extended Bayesian skyline plot (EBSP) was created using BEAST for each genetic cluster66 to evaluate historical demographic changes of effective population size over historical time under the HKY model and strict-clock model with mutation rates (1% per million years)67. The EBSP analysis was performed for 10 million generations with sampling every 1,000 steps and discarding the first 25% as burn-in. Tracer was used to assess the convergence between runs by examining whether ESSs exceeded 200 as an indicator.All six mitochondrial loci were used to find the best approximation regarding the historical demographic pattern for each 69. The 5′ end of each forward primer was fluorescently labelled with either FAM, HEX or NED . PCR was conducted using a 10 µl mixture containing 1 µl of extracted DNA, 1× Taq buffer (containing 2.5 mM MgCl2), 0.25 mM dNTPs, 1 µM of each primer and 0.15 units of Taq DNA polymerase (Solgent). Thermal cycling consisted of an initial denaturation at 95 °C for 5 min, 35 cycles of a denaturation at 95 °C for 30 sec, an annealing at 54–58 °C for 30 sec, an extension at 72 °C for 45 sec, and an final extension at 72 °C for 10 min. The fluorescently labeled PCR products were genotyped on an ABI 3730xl Genetic Analyzer by Biomedic Inc  and scored using GeneMapper 3.7 (Applied Biosystems). Allele size was determined using the Peak Scanner 1.0 (Applied Biosystems).All samples were genotyped using eight previously reported microsatellite primer sets (Supplementary Table FIS) estimated in Arlequin, Fstat 2.9.3.270 and Genepop 4.271. Genepop was used to detect whether the genotype frequencies were deviated from Hardy-Weinberg equilibrium for each locus–population combination using the Fisher’s exact test based on Markov chain parameters with 1000 batches and 10,000 iterations per batch72. Fisher’s exact test of linkage disequilibrium between pairs of loci was performed with the Markov chain algorithm under the null hypothesis of independence using Genepop. Microsatellite genotypes were checked using Micro-Checker 2.2.327.Genetic diversity for each locus and population was quantified with the mean or total number of alleles per locus, allelic richness, observed and expected heterozygosities and fixation index  were quantified for each population using Arlequin to test whether populations have historically experienced a significant reduction in size75. Mc was calculated with default values and θ (=4Neμ) = 1 and 10 under a TPM constraining the model by defining 80% of mutations as conforming to a stepwise mutation model and 20% as an infinite allele model. Critical significance values in all statistics were corrected for multiple comparisons based on the Bonferroni procedure76.The expected percentage of family  relatedness for each population was determined using ML-Relate. A significant excess of expected heterozygosity under the mutation-drift equilibrium relative to expected heterozygosity under Hardy-Weinberg equilibrium was checked based on the Wilcoxon sign-rank test under the TPM (two phase model) with a setting of 70% stepwise mutations model (SMM) and 30% infinite alleles model (IAM) using Bottleneck v1.2FST77 and RST78, as well as pairwise FST77 and RST79 estimated by Arlequin and Genepop. A randomization procedure of allele sizes was then conducted using SPAGeDi v1.180, whereby the different allele sizes found at a locus were subjected to 2,000 random permutations to examine whether the allele sizes from stepwise mutation contributed to population differentiation81. Bayesian clustering analysis with the software Structure v2.3.482 was used to estimate the degree of structuring among populations. Before analysis, the putative numbers of genetically distinguishable groups (K) were predicted by the delta K method83 implemented in Structure Harvester v0.6.9484. Ten independent MCMC runs were performed for each K with 4 × 105 iterations after a burn-in of 105 iterations. To visualize the relationship between individuals and populations based on the best linear combination of allele frequencies, principal component analysis (PCA) was implemented using GENETIX v4.0585. To test competing hypotheses about biogeographic pathways leading to population TJ from western population groups showing strong genetic structure, an Approximate Bayesian Computation (ABC) approach was taken, implemented in the software DIYABC v.2.1.029. A total of five scenarios with a null hypothesis were tested (Fig. Genetic distance among populations was quantified using global Supplementary Information.


Betula nana). In genome‐wide restriction site‐associated single nucleotide polymorphism (SNP) data, we found 267 significant associations between SNP loci and environmental variables. We ranked populations by maladaptation estimated using allele frequency deviation from the general trends at these loci; this gave a different prioritization for conservation action than the Shapely Index, which seeks to preserve rare neutral variation. Populations estimated to be maladapted in their allele frequencies at loci associated with annual mean temperature were found to have reduced catkin production. Using an environmental niche modelling (ENM) approach, we found annual mean temperature (35%), and mean diurnal range (15%), to be important predictors of the dwarf birch distribution. Intriguingly, there was a significant correlation between the number of loci associated with each environmental variable in the GEA and the importance of that variable in the ENM. Together, these results suggest that the same environmental variables determine both adaptive genetic variation and species range in Scottish dwarf birch. We suggest an assisted gene flow strategy that aims to maximize the local adaptation of dwarf birch populations under climate change by matching allele frequencies to current and future environments.When populations of a rare species are small, isolated and declining under climate change, some populations may become locally maladapted. Detecting this maladaptation may allow effective rapid conservation interventions, even if based on incomplete knowledge. Population maladaptation may be estimated by finding genome–environment associations (GEA) between allele frequencies and environmental variables across a local species range, and identifying populations whose allele frequencies do not fit with these trends. We can then design assisted gene flow strategies for maladapted populations, to adjust their allele frequencies, entailing lower levels of intervention than with undirected conservation action. Here, we investigate this strategy in Scottish populations of the montane plant dwarf birch ( In the UK, dwarf birch is a nationally scarce montane tree that has experienced an accelerated decline in recent decades, likely due to the combined impact of anthropogenic climate change and moorland management that permits over‐browsing and burning  have more genomic loci associated with them in GEA, perhaps as a result of stronger selection for adaptation . We provide preliminary evidence in support of this hypothesis in dwarf birch. Third, we evaluate our estimates of nonadaptedness (c‐RONA) of dwarf birch populations against the Shapley index, an existing conservation prioritization most often applied to neutral markers. Finally, we illustrate a strategy of AGF to maximize adaptive genetic diversity and hence sustain the adaptive potential of British dwarf birch populations. We discuss the advantages and limitations of this approach in the context of managing dwarf birch and other plants exposed to rapid environmental change.22.1http://www.worldclim.org) at 1km resolution  records from the period 1960 to present. Records were sourced from national databases, conservation partners and fieldwork observations  estimates for all populations under current and future conditions. Second, ENM performance was assessed using a generalized linear model with a quasipoisson error distribution to test for a relationship between present time HSI estimates and mean population catkin counts. We also tested for a relationship between HSI (explanatory variable) and mean germination rates (response variable) using a quasibinomial error distribution. Here, we are explicitly testing the hypothesis that plants displayed greater reproductive output in locations with a higher ENM‐derived HSI.2.3PstI. Raw reads were filtered using Stacks v1.35  to which the population would be best adapted. The residual deviation of the observed value from this expectation is a measure of the deviation from the optimum environment for that population (c‐RONA) and is proportional to the change in allele frequency that would be required to match the population to its local environment (weighted by β). This measure is therefore analogous to those employed by Rellstab et al. . We estimated the vector of effect sizes, Endelman . In thisb et al.  and Pinab et al. , which qb et al. .2.8We compared the magnitude of c‐RONA across dwarf birch populations with the Shapley index  square root transformed catkin counts and (b) germination rate across study populations. Finally, we tested for a correlation between the relative importance of environmental variables identified in our ENM and the number of GEA loci associated with each variable.33.1p < .001) at a logistic threshold of occurrence of 0.193. Four variables together contributed >85% to the predictive model performance including annual mean temperature (34.9%) and maximum temperature of the warmest month (22.1%) (Table The dwarf birch ENM was well parameterized with high mean test AUC (0.946 ± 0.008) and a low mean test omission rate  Table . Future st month 2.1% (Tab%) Table . Excludi%) Table .3.2F1,26 = 7.50, p = .011) as well as HSI and the proportion of seeds that germinated  = 0.84, p = .008) between methods, in the number of genotype–environment associations identified for each environmental variable  and 0.000–0.260 for putative adaptive markers . We found more significant pairwise FST values for adaptive markers (92 of 312 pairwise comparisons) than for neutral markers . If these populations are excluded, mean pairwise neutral FST is 0.069 and mean pairwise adaptive FST is 0.076.Pairwise 3.5X2 = 23.14, p < .001) and leaf  expressed sequences are significantly over‐represented among putatively adaptive loci.The 267 loci mapped to 185 unique scaffolds in our reference genome. Based on RNAseq data, 35 candidate regions showed evidence of gene expression in flower tissue (19%), 15 showed gene expression in leaf tissue (8%) and 13 showed gene expression in both (7%). In comparison to the overall SNP data set, we found that both flower (3.6r(24) = 0.44, p = .023), despite a number of outliers as shown by the low correlation coefficient, but no such pattern for putative adaptive genetic diversity (Pearson's r(24) = 0.004, p = .983; Figure Mean population c‐RONA based on environmentally associated SNPs under present climate was 0.22 (±0.10), ranging from 0.07 (SE ± 0.06) at Glen Cannich to 0.39 (±0.24) at Beinn Enaiglair on the Western periphery of the species range Tables . BLUP es3.7For each population across each environmental variable, we identified the geographically closest “donor” population with an allele frequency that would reduce c‐RONA (within confidence limits) at the “recipient” site Figures  and S7. 3.8F1,23 = 5.84, p = .025; Figure F11,14 = 8.07, p = .004). Finally, in a comparison of ENM and GEA methods, we found a significant correlation between the number of genotype–environment associations and the percentage contribution of environmental variables defining species range in our ENM (r(8) = 0.69, p = .027; Figure If c‐RONA values do indeed quantify the degree of maladaptation, they should be negatively correlated with independent measurements of population fitness. The c‐RONA values for annual mean temperature (AMTemp) were significantly negatively correlated with mean population catkin counts  across 24 environmental variables, which is consistent with the number of associations identified in similar studies  are particularly small or isolated, and those on the margins of the species’ distribution. This result is consistent with reconstruction of demographic history and genetic differentiation by Borrell et al. , where w Nichols  and evalBased on our inference that populations with low c‐RONA are more locally adapted, we then performed a comparison between c‐RONA and the Shapley index based on neutral diversity. We find that populations with the highest inferred conservation value  were also those with the greatest deviation from optimum allele frequencies (highest c‐RONA; Table To illustrate a possible application for this prioritization framework, we sought to identify putative dwarf birch donor populations that possess adaptive alleles at frequencies that would display reduced c‐RONA in a recipient population Figures  and S7. Our suggested approach has some limitations: RADseq only identifies variation in a subset of the genome (Lowry et al., 5Estimating the degree of maladaptation in populations as a criterion to inform selection of plant material for genetic rescue, composite provenancing or species reintroductions is currently the subject of considerable interest (Gibson, Espeland, Wagner, & Nelson, None declared. Click here for additional data file.


As in other Latin American populations, Argentinians are the result of the admixture amongst different continental groups, mainly from America and Europe, and to a lesser extent from Sub-Saharan Africa. However, it is known that the admixture processes did not occur homogeneously throughout the country. Therefore, considering the importance for anthropological, medical and forensic researches, this study aimed to investigate the population genetic structure of the Argentinian Patagonia, through the analysis of 46 ancestry informative markers, in 433 individuals from five different localities. Overall, in the Patagonian sample, the average individual ancestry was estimated as 35.8% Native American (95% CI: 32.2–39.4%), 62.1% European (58.5–65.7%) and 2.1% African (1.7–2.4%). Comparing the five localities studied, statistically significant differences were observed for the Native American and European contributions, but not for the African ancestry. The admixture results combined with the genealogical information revealed intra-regional variations that are consistent with the different geographic origin of the participants and their ancestors. As expected, a high European ancestry was observed for donors with four grandparents born in Europe (96.8%) or in the Central region of Argentina (85%). In contrast, the Native American ancestry increased when the four grandparents were born in the North (71%) or in the South (61.9%) regions of the country, or even in Chile (60.5%). In summary, our results showed that differences on continental ancestry contribution have different origins in each region in Patagonia, and even in each locality, highlighting the importance of knowing the origin of the participants and their ancestors for the correct interpretation and contextualization of the genetic information. Soon after the Spanish conquest in the beginning of the 16zambique . Accordizambique . On the zambique . This reUntil then, the Argentinian Patagonia had been inhabited mainly by hunter-gatherer native groups of low demographic density and high residential mobility. Although these groups had a long history of sporadic contacts with foreigners, only at the end of the 19th century there was a significant demographic change in the region, due to strong migratory flows coming from inland provinces and from bordering countries, mainly attracted by new labor opportunities .Our research group has previously investigated the genetic composition of urban Argentinian populations with focus on the Patagonia region by means of uniparental and autosomal markers. In five populations of Chubut and Río Negro provinces, the analysis of mitochondrial DNA and Y-chromosome markers revealed heterogeneity through autochthonous and allochthone contributions. In this sense, mitochondrial analysis showed a higher Native American maternal contribution in populations of Esquel, San Carlos de Bariloche, Comodoro Rivadavia, Puerto Madryn and Trelew ,6–9. ForRegarding autosomal markers, the studies carried out in urban populations of Argentinian Patagonia varied on the number of populations, the source populations and the number of samples, and the genetic markers analyzed. In this respect, Toscanini et al.  analyzedStudies carried out by our research team in Argentinian Patagonia comprised the analysis of blood systems ,6,7, autThe most comprehensive ancestry studies by Seldin et al. , Wang etThe present study aimed to analyze a panel of 46 ancestry informative insertion-deletion markers (AIM-Indels), described by Pereira et al. , in a reFor a more in-depth interpretation, with focus in the regional and local differences, the ancestry results were analyzed taking into account genealogical and historical data. This information allowed for investigating possible associations between genetic ancestries inferred by the 46 AIMs panel and the geographic origin of the participants.The knowledge of the genetic composition of Argentinian Patagonia, in terms of individual and population ancestry composition will provide important information for medical, forensic and anthropological studies in the region.This study was approved by the Ethics Committees of Puerto Madryn Zonal Hospital (Resol.009/2015) and San Carlos de Bariloche Zonal Hospital (Resol. 1510/2015). Moreover, it has been endorsed by Hospitals’ Teaching and Research Committees of Trelew, Comodoro Rivadavia and Esquel. Biological samples involved in the study were coded and anonymized, as per the Argentina National Law 25.326 of Protection of Personal Data. All samples were collected under written informed consent to participate in this study.A volume of 5 ml of blood was EDTA collected from 433 healthy non-related voluntary blood donors, randomly selected from hemotherapy services of public and private hospitals of five Argentinian Patagonia cities; two from the Andes region, namely San Carlos de Bariloche and Esquel, and three located in the coastal area: Puerto Madryn, Trelew, and Comodoro Rivadavia .Participants were thoroughly informed of the scopes of the study and answered a questionnaire to obtain information about their birthplace and that of the two preceding generations (parents and grandparents). This information allowed us to evaluate a possible association between genetic ancestry and geographic origin. DNA extraction was performed as described in Parolin et al. .A panel of 46 AIM-Indels, developed by Pereira et al.  was genoFST) between populations across 46 AIM-Indel markers were visualized in a multi-dimensional scaling (MDS) plot performed with the R v3.1.1 FactoMineR [ad-hoc scripts. Geographic representations of the birthplace and ancestry proportions of the donors were obtained by ordinary kriging using the Geostatistical Analyst module of ArcMap 9.3 (ESRI). The covariances of the studied parameters (percentage of ancestry) were modeled in terms of the distance between sampling units [http://qgis.osgeo.org) and ArcGis Desktop 10.6.1 software using spatial data obtained from GADM webpage (https://gadm.org/license.html), which are freely available for academic purpose.Allele frequency estimations, Hardy-Weinberg exact tests, and population differentiation tests were performed using the Arlequin software v.3.5.2 . PopulatctoMineR  statistictoMineR . In agrectoMineR . STRUCTUctoMineR . AveragectoMineR . This noctoMineR . A Chi-sctoMineR  was prefctoMineR  implemenng units . The mapp ≥ 0.0038; for a significant level of 0.001, when applying the Bonferroni’s correction for 46 tests performed) [The genotyping results obtained in the five urban populations from Argentinian Patagonia are shown in rformed) .The estimation of continental admixture in 433 Argentine Patagonian individuals varied from 0.4 to 99.4% Native American, 0.3 to 99.2% European, and 0.2 to 23.4% African. Individual genetic ancestry obtained was represented in a ternary plot .The ternary plot showed a linear distribution of the Patagonia samples between European and Native American parental populations, with a tendency of more density towards the European component.The average individual ancestry estimated in the total Patagonia sample was 35.8% (95% CI: 32.2–39.4%) Native American, 62.1% (95% CI: 58.5–65.7%) European, and 2.1% (95% CI: 1.7–2.4%) African. Comparing the five studied localities , a prevaThe Kruskal-Wallis test showed that the differences observed for the Native American and European ancestry distributions among the five samples are statistically significant , while no significant differences  were observed for the African ancestry. In all pairwise comparisons, significant differences (p<0.05) were observed for both for Native American and European ancestry proportions, except between Comodoro Rivadavia and Esquel  and between Trelew and San Carlos de Bariloche .The overall results showed three main groups among central Patagonian localities: i) Comodoro Rivadavia and Esquel, ii) Trelew and San Carlos de Bariloche, and iii) Puerto Madryn.Aiming to compare the ancestry distribution between the three main regions of the country (North/Center/South), our data was analyzed together with those obtained by Toscanini et al. , for theDifferences on the ancestry of Argentinian regions were also found in other studies, based on 24 AIMs  and 99 AAt regional level, the relatively high preservation of the Native American ancestry obtained in current urban Patagonia populations might be related to the late incorporation of this region to the National State Law 1584, 1884), which allowed the Native populations to keep their autonomy for longer. Also, it might be related to the high migratory flow that the Patagonia region received from the inland provinces and from bordering countries, mainly Chile, with high Native American genetic background 84, 1884,–40.Likewise, at the local level, the admixture results obtained seem to be related to the birthplace of the participants and their ancestors, since a high variation was observed among grandparents’ birthplaces, for the five Patagonian samples. Comparing to the remaining samples, Esquel showed the lowest immigration from other regions, allowing for a better preservation of the original genetic background . Indeed,2), registered 39.5% of Native American ancestry . Therefore, migrations have had an important impact in the growth of their populations.The five cities sampled here have less than 160 years of existence and relative low population densities  was compared with the proportions of Native American, European and African ancestries of the participants, to investigate a possible association between them. For this analysis, 85 individuals with the 4 grandparents born in the same geographic place were selected. These samples were grouped according to the grandparents’ origin in five major regions: Europe, Chile, North Argentina, Central Argentina, and South Argentina.Not surprisingly, the results showed that the number of individuals with grandparents from Europe was highly associated to the European ancestry in the population. The average of European ancestry among individuals with all grandparents from Europe was 96.8% . This isAlso, a clear association was observed between the Native American ancestry and the number of grandparents born in Chile. The average Native American ancestry among individuals with four grandparents from Chile was 60.5%. These findings are in accordance with the relatively high prevalence of the Native American ancestry (range 46.9%-49.5%) reported in Chilean Patagonia .Comparing the three main regions of Argentina, an association was also observed between the grandparents’ birthplace and the average European and Native American ancestries of the individuals. As expected, a high correlation between European ancestry and birthplaces in the Central region of Argentina was observed. The average European ancestry among individuals with all grandparents born in the Central region was 85% . As prevIn contrast, the Native American ancestry increased and the European decreased when the four grandparents were born in the North (NAM = 71%) or in the South NAM = 61.9%) regions of the country . These r1.9% regipost-hoc analysis showed no significant differences (p>0.05), for the Native American and European ancestries, between donors with four grandparents born in Europe and in Central Argentina , neither between donors with four grandparents born in Chile, North and South Argentina . These results are consistent with the high average European ancestry (≥ 85%) in the samples with four grandparents born in Central Argentina and in Europe. Also, similar average Native American ancestry (≥ 60%) was observed among participants with four grandparents born in Chile, North and South Argentina  were observed for the Native American and European ancestry distributions among participants with four grandparents born in the three main regions of Argentina, Europe or Chile. However, no significant differences  were detected for the African component. In accordance with the ancestry frequencies obtained for each region , the posrgentina .The results obtained showed a clear variation in ancestry proportions mainly associated to the geographical origin of the samples. In order to obtain a spatial representation of this variation, we performed a geostatistical modelling based on the geographic coordinates for the birthplaces of the participants and their individual ancestry. For this representation, 392 individuals born in North, Central and South Argentina, and in Chile were included (41 samples from other countries or with incomplete birthplace information were excluded). The distribution of the individual genetic ancestry among the samples included in this analysis varied from 0.4 to 99% Native American, 0.6 to 99.2% European, and 0.3 to 23.4% African contribution.In agreement with previous studies ,21,22,39FST genetic distances were calculated between the five Patagonian populations from this study, and samples from six Argentinian provinces [Using data from the 46 AIM-Indels, pairwise rovinces , six Sourovinces , Boliviarovinces  and Colorovinces ,28, as wrovinces   between the Argentinian populations and the parental and other South American populations except between Buenos Aires and South Brazil. Puerto Madryn showed low distances and no significant differences with Buenos Aires  and La Pampa . This is in agreement with the higher European ancestry registered in these populations, and with the birthplace of the grandparents of Puerto Madryn individuals, most born in the Central region of the country . This is consistent with the relatively high Native American ancestry present in these populations from the North and South regions Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 TableFST) between 17 South American populations, and 3 parental populations , and corresponding non-differentiation P-values Genetic distances (.(XLSX)Click here for additional data file.


Ceratitis capitata, as a member of the family Tephritidae, is one of the most studied invasive species feeding on many fruit crops in the tropics and subtropics worldwide. This study aims to determine the global macrogeographic population structure of Ceratitis capitata and reconstruct its potential migration routes.Invasive species are a growing threat to food biosecurity and cause significant economic losses in agricultural systems. Despite their damaging effect, they are attractive models for the study of evolution and adaptation in newly colonised environments. The Mediterranean fruit fly, A partial mitochondrial cytochrome oxidase I gene from >400 individual medflies and 14 populations from four continents was sequenced and subjected to Bayesian demographic modelling.The Afrotropical populations  harbour the majority of haplotypes detected, which also are highly divergent, in accordance with the presumed ancestral range of medflies in Sub-Saharan Africa. All other populations in the presumed non-native areas were dominated by a single haplotype also present in South Africa, in addition to a few, closely related haplotypes unique to a single local population or regional set, but missing from Africa. Bayesian coalescence methods revealed recent migration pathways from Africa to all continents, in addition to limited bidirectional migration among many local and intercontinental routes.The detailed investigation of the recent migration history highlights the interconnectedness of affected crop production regions worldwide and pinpoints the routes and potential source areas requiring more specific quarantine measures. Globalisation and international economic trade have increased the transportation of species outside their natural ranges. Thus, human activities assist the spread of exotic species and increase the rates at which pest species invade new areas . The arrCeratitis capitata, also known as medfly, poses a severe economic threat to agriculture, especially fruit production, due to its broad range of more than 260 different host plant species and worldwide distribution  are the predominant methods used. However, due to harmful effects of insecticides, the Sterile Insect Technique (SIT) using the release of males subjected to sublethal X-ray irradiation is becoming increasingly common . The sucPopulation genetic studies can be used to understand medfly invasion biology by focusing on the degree of subdivision within and among local regions. Additionally, information on demography and dispersal can be inferred from genetic data. However, the interpretation of these data in the medfly is challenging as repeated range expansions and invasions, as well as several cases of regional eradication, have impacted its distribution and genetic diversity. The medfly population genetic structure and invasion routes have been previously studied using various molecular approaches at local  as well C. capitata collected from different populations around the globe, and to reconstruct plausible migration routes using Bayesian coalescence approaches.In this study, a large-scale phylogeographic analysis was conducted using the cytochrome oxidase gene I (COI) for a pathway analysis of medfly populations across their distribution range. We aim to determine the current macrogeographic population structure of C. capitata were collected from 11 sites across all biogeographic regions where the species occurs    between Sequences representing populations at further sites  were obtained from GenBank, which was used to increase the sample size at the main collection sites (see c oxidase subunit I (COI) was amplified using the primers LCO1490 (5′-GGTCAACAAATCATAAAGATATTGG-3′) and HCO2198 (5′-TAAACTTCAGGGTGACCAAAAAATCA-3′) . A fragment of the mitochondrial gene cytochrome ATCA-3′) . PCRs weATCA-3′)  togetherk), number of segregating sites (S), haplotype diversity (h) and nucleotide diversity (π). The median-joining (MJ) network . Two independent simulations were run using the Hasegawa-Kishino-Yano (HKY) substitution model and uncorrelated lognormal relaxed molecular clock. Each independent run was performed for 5 ×107 Markov chain Monte Carlo (MCMC) iterations (sampled every 1000 iterations) and discarding 10% of the trees as burn-in implemented in BEAST v.2.4  studies . To avoiper year , and theneration . The latper year . Each ruper year . Finallyθ), population growth (g) and migration rates (M) . Migration rate was estimated as M = m∕µ, where m is the probability of immigrants per generation and µis the mutation rate per site per generation. The migration rate was multiplied by the θ value of the corresponding recipient population to obtain the migrants per generation value (Nm) (Connectivity was explored with the software LAMARC v.2.1.10 which estimates demographic parameters such as theta (ates (M) . Theta vlue (Nm) . The seaC. capitata collected in 14 sites distributed worldwide were included in the analysis. The final truncated alignment was 538 bp in length corresponding to 179 amino acids of the mitochondrial COI gene. The number of segregating sites (S) within populations ranged from 23 in Kenya and one in Greece (k) varied between 18 in Kenya and one and two in Tunisia and Greece, respectively. Tunisia was not included in the further analysis of intra-population diversity because of the lack of haplotype variation. Haplotype diversity (h) and nucleotide diversity (π) were much higher in the populations from Kenya and South Africa than anywhere else , Alanine to Threonine (Peru), Isoleucine to Threonine (Kenya), Proline to Serine (Spain), Valine to Isoleucine . All of these changes were mapped to the tips of the haplotype network .The median-joining haplotype network contained a total of 58 distinct haplotypes with a low number of ‘unsampled’  haplotypes . The netFst analysis performed on the 13 localities (Tunisia excluded) showed that the majority of the populations were significantly differentiated  were significant for Tajima’s  Fu’s Fs . From thD. melanogaster are shown). The time to the most recent common ancestor (tmrca) was estimated at around 11,600 years ago in the Afrotropical  to 0.003 . The Lamarc results also indicated asymmetric migration between the Afrotropical and the other populations, whereby the Palearctic received the lowest migrants per generation (Nm = 4.35) and the Australasian population the highest (Nm = 5.47), while migrant flow in the opposite direction was insignificant  remains too low to resolve the contradicting literature on the subject of population subdivision in Sub-Saharan Africa  among extremely distant populations suggests a recent connection of all non-native populations. This common haplotype is also present in South Africa, but only as a very small proportion, and it is peripheral to the haplotype network of African haplotypes. While the distribution of Cc_21 indicates a shared history of all non-native populations, the derivation of this haplotype from the South African population is not strongly supported. An individual carrying the Cc_21 haplotype could be the ancestor to all non-native populations, even if this haplotype was rare in the ancestral population, but conceivably the source population could be from elsewhere in Africa where the Cc_21 haplotype is more prevalent. Only more detailed surveys of native African populations will resolve this question.D and Fu’s values for Kenya and South Africa which are best interpreted as the result of purifying selection, as expected in mitochondrial protein-coding gene evolution , but characterised by residual levels of connectivity at regional scales despite considerable distance separating the populations, such as Egypt and Iran or Brazil and Peru. However, the COI marker used in this study has limitations due to comparatively low variation that may be insufficient to resolve events on the time scale of the medfly dispersal. Yet using an appropriate mutation rate, the demographic analysis produced plausible scenarios associated with the Holocene era, which is closely related to the agriculture and domestication process in the humanity. The inferred migration patterns among populations provide crucial information for the understanding of successful medfly invasions and thus pinpointing where countermeasures are required, in particular in a world connected via agricultural commodities trade. The case of successful containment in Guatemala and the dangers of fruit fly migration from elsewhere in the South and Central American regions illustrate these problems clearly. We used the most basic of molecular markers to study these phenomena, based on short fragment of a single locus, and studied pattern and process of medfly history at global levels based on just 14 local sites. The results are highly plausible and consistent with other studies using diverse approaches. However, the conclusions have to remain tentative, given the limited detail of sampling. Genomic approaches and much denser sampling at regional and global scales will be required to confirm the conclusions drawn here.10.7717/peerj.5340/supp-1Table S1N, number of individuals per haplotype; Haplotype code, corresponding to each unique haplotype nomenclature.Click here for additional data file.10.7717/peerj.5340/supp-2Supplemental Information 1Ceratitis capitata, and the number refers to the region where the specimens belong as found in Cc correspond to Click here for additional data file.


Sternopygus dariensis across the Isthmus of Panama. We found strong genetic divergence between eastern and western populations of S. dariensis. Over 77% of the UCE loci examined were differentially fixed between populations, and these loci appear to be distributed across the species’ genome. Population divergence occurred within the last 1.1 million years, perhaps due to global glaciation oscillations during the Pleistocene. Our results are consistent with a pattern of genetic differentiation under strict geographic isolation, and suggest the presence of incipient allopatric species within S. dariensis. Genetic divergence in S. dariensis likely occurred in situ, long after the closure of the Isthmus of Panama. Our study highlights the contribution of spatial isolation and vicariance to promoting rapid diversification in Neotropical freshwater fishes. The study of spatially-segregated populations within the Isthmus of Panama could reveal how genetic differences accumulate as allopatric speciation proceeds.Spatial isolation is one of the main drivers of allopatric speciation, but the extent to which spatially-segregated populations accumulate genetic differences relevant to speciation is not always clear. We used data from ultraconserved elements (UCEs) and whole mitochondrial genomes  to explore genetic variation among allopatric populations of the weakly electric fish  On the other, the exposure of the land bridge facilitated dispersal and colonization in both terrestrial5 and freshwater organisms7. In addition, global events such as the Pleistocene glaciations8 have facilitated the expansion and contraction of local populations via changes in sea level11. Together, these events have defined the current spatial structure of the Isthmian populations14, with implications for allopatric divergence across isolated populations.The closure of the Isthmus of Panama is one of the main drivers of Neotropical diversification. On the one hand, the rise of the Isthmus resulted in immediate reduction in gene flow between marine organisms on the two sides of the Isthmus19. However, the extent to which spatially segregated populations accumulate genetic differences relevant to allopatric divergence is not always clear. In addition, if divergence occurs, its historical context might be difficult to define, given the dynamic nature of the rise of the Isthmus of Panama. For instance, allopatric divergence might proceed randomly across the range of segregated populations, or it might be driven by multiple dispersal and colonization events21. Furthermore, divergence of seemingly isolated populations might be influenced by selective  and random processes  that are difficult to disentangle if relying on low numbers of molecular markers22. Here, we explore these issues by quantifying genetic variation at both nuclear loci linked to ultraconserved elements  is a geographically unique species within the Blue-green knifefish  species complex. Similar to other Neotropical electric fishes25, this Sternopygus complex originated in South America, but it has since colonized the Isthmus of Panama. Although it has not been resolved whether S. aequilabiatus and S. dariensis are allospecies or distinct species, here we consider S. dariensis as an independent species following Hulen et al.26 and Albert27. However, our inferences do not change if we consider S. dariensis as synonym of S. aequilabiatus as suggested by Maldonado et al.28. Sternopygus dariensis is narrowly distributed from the Pacific slope of Colombia to the Tabasará River in western Panama26, which represents the effective range limit of the species. As with other weakly electric fishes, S. dariensis has an elongate eel-shaped body and the ability to produce electric organ discharges (EOD) used for electrolocation and communication30. Interestingly, despite evidence for genetic variation in other species of the genus Sternopygus32 no population-level analysis has been performed within the Isthmus of Panama. Thus, quantifying genetic variation across Isthmian populations of S. dariensis will help inform the tempo and mode of allopatric divergence in Neotropical freshwater fishes.S. dariensis across the Isthmus of Panama.By integrating available data from mitogenomes as well as UCEs, we examine i) the historical factors driving allopatric divergence across spatially segregated populations, and ii) the genetic consequences of allopatric divergence in the weakly electric fish S. dariensis. The 118 variant loci contained 285 single nucleotide polymorphisms (SNPs), ranging from 1 to 8 SNPs per locus. The complete dataset including the outgroup Eigenmannia humboldtii had 98 enriched UCE loci with a total alignment length of 85 028 bp. UCE raw read data are available on NCBI SRA SRP071703  that had an average length of 861 bp shared across individuals of Similar results were obtained with the Bayesian clustering analyses (based on the 118 SNPs), which revealed high posterior probability for two well-defined independent clusters (K = 2), as identified by maximum ΔK value Fig. . These tElectrophorus electricus), and 83 loci (containing 129 fixed SNPs) were mapped to the channel catfish  genome . By contrast, the PCAdapt analysis identified 12 potential outlier loci associated with differences between the two lineages, at FDR of 0.05  UCE loci containing 150 fixed SNPs. All UCE loci were successfully mapped to the available genomic scaffolds of the electric eel  , but the greatest genetic distance  from the eastern population of the Chucunaque River   and one assembled previously  and represented up to 45% of all sampled individuals. The second-most common haplotype was unique to the eastern population  were identified within Sternopygus, the first one including S. arenatus and S. dariensis; the second clade included S. macrurus and S. xingu. The split within the first clade (S. arenatus and S. dariensis) occurred during the Pliocene period, approximately 3.4 Ma (95% HPD: 1.2–6.7 Ma), while divergence between western and eastern clades of S. dariensis took place in the Pleistocene, approximately 1.1 Ma (95% HPD: 0.5–2.6 Ma).Mitochondrial-based dating of TMRCA placed the first split within Sternopygidae around 13.6 Ma  and suggest that S. dariensis is composed of two genetic lineages, likely representing incipient allopatric species.Overall, our analysis of population structure based on UCEs revealed two divergent clusters (without evidence for admixture) that corresponded to eastern  and western populations  properties of the EODs in maintaining prezygotic isolation and speciation50. Cytogenetic analyses have also been used to test for genetic incompatibility Gymnotiformes52. Overall, however, our findings indicate that substantial genetic divergence has accumulated within the Isthmus of Panama. This also suggests that the diversity of Sternopygus species might have been underestimated, possibly due to the existence of cryptic species across the Isthmian range of the genus.The historical context of this divergence is consistent with a scenario of early divergence between populations from Tuira/Chucunaque and Tumaganti watersheds, followed by more recent dispersal from Tumaganti to the western watersheds (Santa María and San Pablo). This scenario could explain the low genetic variation across the three western populations , possibly due to a strong bottleneck (or founder effect) or a limited time for the accumulation of genetic differences54. However, allopatric divergence may also be affected by adaptive processes , which might lead to genomic islands of divergence58. Distinguishing between these possibilities requires a large number of genetic markers that can be mapped across the genome60. Although our analysis only included a few individuals per population and a reduced representation of the species’ genome (285 SNPs), the high number of fixed loci between populations, and the broad distribution of these loci across the majority of the species’ chromosomes, is consistent with a model of strict allopatric divergence53. In addition, the low number of loci under selection also points towards the role of non-adaptive processes as the predominant driver of divergence in S. dariensis. For instance, Picq et al.6 found sizeable evidence of the role of drift in EOD evolution. However, further work is needed to disentangle the contribution of both factors to in situ divergence in S. dariensis post-colonization of the Isthmus of Panama. This work could benefit from inclusion of additional sampling sites, and a larger number of individuals to examine genetic structure across the entire range of the species. In addition, future work should explore the geographic origins of S. dariensis in South America and its pattern of colonization of the Isthmus of Panama.An expected consequence of allopatric divergence is the accumulation of genetic differences across large portions of the species’ genome due to random driftS. dariensis progressed in situ post-colonization of the Isthmus of Panama, and that genetic divergence is likely to occur widely across the species’ genome. Thus, our findings support the pattern of genetic differentiation expected under the classical model of allopatric divergence. Although reproductive isolation between allopatric populations is difficult to determine in nature, we suggest that integrating UCEs and mitogenome data is a useful approach to assess the evolution of genetic incompatibilities between geographically isolated populations. Our findings also underscore the role of vicariance and spatial isolation in promoting diversification in weakly electric fishes. Although more work is needed to disentangle the demographic and phylogeographic history of S. dariensis across its range, the study of spatially segregated populations within the context of the Isthmus of Panama could provide further insights into the accumulation of genetic differences that drive allopatric diversification in freshwater fishes.In summary, our results suggest that allopatric divergence in 10H12O2) derived from clove oil. Twelve specimens of Sternopygus dariensis were collected from four sites in the Republic of Panama , and then collected using a dip-net. Fish were then euthanized with an overdose of eugenol  designed to target 500 highly conserved loci across fishes. We determined the size of enriched and purified pools with a Bioanalyzer , and quantified enriched libraries by qPCR (Kapa Biosystems) prior to sequencing. Genomic libraries were multiplexed before sequencing 300 bp from both ends on the Illumina MiSeq platform at Naos Molecular Laboratory of the Smithsonian Tropical Research Institute (STRI), in Panama City, Panama.We extracted DNA from frozen-preserved tissues following the Qiagen DNeasy Blood and Tissue Kit  protocol. We quantified all DNA extracts with a Qubit Fluorometer , assessed each extract for quality by electrophoresis, and then sheared extracts by sonication to a target size of 600 bp on a Covaris S220 instrument . Approximately, 500 ng of genomic DNA was used to prepare twelve 300 bp paired-end libraries, following the protocol Kapa Kit , and the UCE protocol described in Faircloth 62, which works with Trimmomatic63. We then followed the standard PHYLUCE64 pipeline (http://phyluce.readthedocs.io/en/latest) for processing target-enriched UCEs data. Trinity version r2013-02-2566 was used to assemble reads using the script assemblo_trinity.py. We then used the match_ contigs_to_probes.py script to map assembled contigs to the UCE probes, which allowed us to assemble contigs representing enriched UCE loci from each species. We created two FASTA datasets: the first containing both the ingroup and outgroup taxa, and the second with only the ingroup, to increase the number of shared loci. We then followed the PHYLUCE pipeline to produce MAFFT67 alignments across all loci from both datasets. We removed locus names from each alignment, and created a complete dataset, with each locus containing data for all the individuals. Alignments of the first dataset (containing both ingroup and outgroup) were concatenated in PHYLIP format for subsequent analyses of phylogenetic structure (see below).Raw sequence data were converted to FASTQ before demultiplexing, trimming and cleaning using Illumiprocessor68. We converted SAM files to Binary Alignment Map (BAM) files format using the SAMtools69, and Picard (http://broadinstitute.github.io/picard/) to identify and remove PCR duplicates. We added read groups for each individual using Picard, and merged the BAM files across individuals with the SAMtools. We used the Genome Analysis Toolkit . This included restricting data to high-quality SNPs (Q30), and read-back phasing in GATK. At the end of the pipeline we created a Variant Call File (VCF) with nuclear SNPs. Finally, we used Python scripts from the seqcap_pop pipeline to convert the phased VCF into an input file for subsequent population analyses.We chose the sample with the most UCE contigs recovered within the ingroup as reference sequence to call SNPs. We mapped reads  to this reference using the program BWA71. Support for the best ML topology was assessed by performing 1000 nonparametric bootstraps in CIPRES Science Gateway72. For this analysis we used the GTR GAMMA site-rate substitution model for the best ML tree obtained from CIPRES Science Gateway72, using JModelTest 273.To quantify phylogenetic structure across species , we performed unpartitioned concatenated maximum-likelihood (ML) analyses, using RAxML 8.0.19S. dariensis populations, we used a Bayesian clustering algorithm as implemented in STRUCTURE 2.3.474. One random SNP from each locus was selected using the script structure_from_vcf.py (github.com/mgharvey/seqcap_pop) to create STRUCTURE input file, to minimize linkage disequilibrium. The number of subpopulations (ΔK) was determined using the ad-hoc statistical method, based on the rate of change in the log probability of data between successive K values. Ten independent runs for K values ranging from 1 to 4 were performed with a burn-in length of 50,000, followed by 500,000 interactions. Best K results were analyzed on Structure Harvester75 and Clumpak76.To estimate population structure across S. dariensis populations, we quantified the proportion of SNPs that were differentially fixed (FST)77 between the two major clades recovered from the STRUCTURE analysis (see results). These analyses were performed in the R package adegenet version 3.2.279, and was performed on the 285 SNPs data set using the script adegent_from_vcf.py (github.com/mgharvey/seqcap_pop). To determine the genomic distribution of differentiated SNPs, we mapped each fixed SNP (UCE locus) to the available scaffolds of the electric eel, Electrophorus electricus80 genome using BLAST on SequenceServer (http://www.sequenceserver.com) implemented in EFISH genomics (https://efishgenomics.integrativebiology.msu.edu/blast_search/). We also mapped the fixed SNPs to the channel catfish, Ictalurus punctatus81 chromosomes, using the NCBI Genome Workbench version 2.12.8. In cases in which we obtained multiple hits, we retained the hits with >90% sequence identity and the highest query coverage. Finally, to examine the pattern of genetic divergence between clades, we estimated the frequency distribution, including skewness, of FST values across the entire SNP dataset.To further examine divergence across 33 and PCAdapt82. BayeScan uses differences in allele frequencies between populations, and estimates the probability that each locus is subject to selection using a Bayesian method. BayeScan was run under default settings. In PCAdapt, population structure is defined with PCA, and outliers are detected with respect to their contribution to population structure. Cattell’s graphical rule was used to choose the number of principal components (K) that identify potential SNPs under selection. Outliers were selected by performing the q-value procedure at a false discovery rate (FDR) of 0.05 using the R package qvalue83. PCAdapt was run assuming three genetic clusters after graphical evaluation of the eigenvalues according to Luu et al.82. To account for population structure, we retained the first two PC axes that explained most variation. For both analyses, the input file was created using the previously generated VCF file, and it was converted to other formats, as needed, using PGD Spider84 for BayeScan and Plink v1.985 for PCAdapt.We quantified outlier loci with two methods: BayeScan 2off-target reads by following the same methodology described in Aguilar et al.34. The complete sequences of mitogenomes were annotated in Geneious version 11.1.486 using the complete mitochondrial genome sequence of S. dariensis (GenBank accession no. MH399590) as a reference.We identified mitogenomes from UCEs nad6 and stop codons excluded). We aligned them using Multiple Alignment using Fast Fourier Transform (MAFFT)87 in Geneious version 11.1.486. Sternopygus arenatus88 and Eigenmannia sp. mitogenomes89 were used as outgroup . Maximum likelihood (ML) analyses were performed using RAxML. The resulting tree topology was evaluated by a rapid bootstrap analysis with 1000 replicates. Bayesian inference (BI) analyses were performed in MrBayes on XSEDE version 3.2.6 on CIPRES Science Gateway72. We ran two independent runs of 2,000,000 generations for each of the four chains. Each chain was sampled every 2000 generations with a burn-in of 25%. Trees inferred prior to stationarity were discarded as burn-in, and the remaining trees were constructed using a 50% majority-rule consensus tree with posterior probabilities.In order to compare mitochondrial gene sequences, we extracted the protein coding genes  using uncorrected p-distances among unique haplotypes with MEGA version 790. In addition, we calculated pairwise distance across Sternopygus species , using the cox1 gene. Standard error estimates were obtained by a 1000 bootstrap replicates under a maximum likelihood model91. Phylogenetic relationships between haplotypes were determined by constructing a Templeton, Crandall and Sing (TCS) haplotype network35 based on cox1 sequences in PopArt 1.7 . One previously published cox1 (645 bp) sequence6 from Tuira River from Eastern Panama, was aligned independently to the newly generated mitogenomes.We also assessed the evolutionary distance (uncorrected p-distance) among 93 on the CIPRES Science Gateway72 under a relaxed molecular clock with uncorrelated lognormal distribution of rates, to allow for lineage-specific rate variation, and using a Yule speciation model as tree prior. Sequences of cox1, cytb and 16S were concatenated on a 2217 bp alignment. Nucleotides were first grouped into four different partitions: the 1st, 2nd, and 3rd codon positions respectively for cox1 and cytb; and the 16S. Nucleotide substitution models were estimated for each partition using the Bayesian Information Criterion in Partition Finder94. The best-fit models for the three genes were TVM + I + G , and the TRN + G (for the 3rd codon position of the coding genes). Bayesian posterior distributions of evolutionary rates were estimated using Markov Chain Monte Carlo (MCMC) procedure. Four independent MCMC chains were run for 4 × 107 generations and were sampled every 1,000 generations, after discarding the first 20% as burn-in. We used TRACER version 1.695 to test for convergence of the chains to the stationary distribution, which was determined by an effective size (ESS) of over 20095. The four independent runs were combined using LogCombiner v1.8, and the dates of divergence along with their 95% confidence intervals (HPD) were estimated using Tracer v1.6. The resulting phylogeny and the 95% HPD for the dates of divergence for the major clades were visualized using FigTree v1.496.We estimated divergence time among populations and species using BEAST2 on XSEDE v2.4.8Humboldtichthys kirschbaumi dated to c. 10 Ma, which shares morphological characters  with extant Sternopygus species97. The fossil age was placed on the stem node of the genus Sternopygus, using an uniform prior distribution with a maximum age equal to the maximum tree root height, following Picq et al.6. We used the three sequences  to include all Sternopygus species available in Genbank and four genera of Gymnotiformes as outgroups . This research was approved by the Institutional Animal Care and Use Committee (IACUC) at the Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT AIP), and all methods were performed according to the guidelines and regulations of the approved protocol (IACUC-16-001).Supplementary information