Achyrocline flaccida (Weinm.) DC. is a native plant from the grassy fields of South America with high value in folk medicine. In spite of its importance, no genetic and conservation studies are available for the species. In this work, microsatellite and ISSR (inter-simple sequence repeat) markers were used to estimate the genetic variability and structure of seven populations of A. flaccida from southern Brazil. The microsatellite markers were inefficient in A. flaccida owing to a high number of null alleles. After the evaluation of 42 ISSR primers on one population, 10 were selected for further analysis of seven A. flaccida populations. The results of ISSR showed that the high number of exclusive absence of loci might contribute to the inter-population differentiation. Genetic variability of the species was high (Nei’s diversity of 0.23 and Shannon diversity of 0.37). AMOVA indicated higher genetic variability within (64.7%) than among (33.96%) populations, and the variability was unevenly distributed (FST 0.33). Gene flow among populations ranged from 1.68 to 5.2 migrants per generation, with an average of 1.39. The results of PCoA and Bayesian analyses corroborated and indicated that the populations are structured. The observed genetic variability and population structure of A. flaccida are discussed in the context of the vegetation formation history in southern Brazil, as well as the possible anthropogenic effects. Additionally, we discuss the implications of the results in the conservation of the species.Better knowledge of medicinal plant species and their conservation is an urgent need worldwide. Decision making for conservation strategies can be based on the knowledge of the variability and population genetic structure of the species and on the events that may influence these genetic parameters.  To understand the genetic variability of domesticated or wild plants and animals by 2020 is one of the goals of the United Nations . The aimAmong the different types of vegetation that exist in the Atlantic Forest, the ancient grassy fields, known as "Campos de Altitude", form a forest–grassland mosaic in the southern portion of this biome, and are one of the less studied and most threatened vegetation in Brazil . RelativAchyrocline flaccida (Weinm) DC. (Asteraceae) is a medicinal plant species found in the original formation of grassy ecosystems, at forest edges, and in regions of vegetation regeneration in the southern portion of the Atlantic Forest. The species is herbaceous, popularly known as "Macela" and is the most common Achyrocline species in south and southeast Brazil. It is one of the most commonly used native plant species in folk medicine in South America [ America . The inf America .A. flaccida is closely linked with popular culture in Brazil. For example, every year on Good Friday, before sunrise, families go to the fields to harvest A. flaccida infructescence. It is believed that the plant is most effective in the treatment of diseases when the material is harvested in this manner. Achyrocline flaccida is mainly used in the treatment of digestive system disorders [A. flaccida is not available in the literature, which makes it difficult to reach conclusions about its real conservation status.The harvest of isorders –12 and fisorders . The plaisorders ,13,14. TA. flaccida populations can help in conservation and effective management of overexploited plant species [A. flaccida. The transferability of microsatellite markers between related species has been successfully achieved [A. flaccida. Additionally, when there is no previous knowledge of microsatellite regions for the genome of the species, ISSR (inter-simple sequence repeat) markers can also be used as an alternative [Information on the distribution of genetic variability within and between natural  species . DNA-bas species . Microsaachieved –19 and cernative –23. The ernative .Calibrachoa heterophylla populations differed because they were influenced by local geomorphological events along the coast of the state of Rio Grande do Sul and northern Uruguay, which could not be identified if only long distance models of isolation and/or other species were used.Furthermore, when data on genetic variability and population structure is aligned with the geological and paleoclimatic history of the habitat of a given species, the results can help define the patterns of distribution of a species throughout the historical and present timeline. For this understanding, the individual study of each species is necessary, because the extrapolation of data from one species to another can often lead to inaccurate conclusions owing to physical or biological barriers that influence one species but not the other. Mäder et al.  concludeA. flaccida, this work sought to answer the following questions: 1—The transferability of microsatellite markers is an efficient strategy for obtaining genetic data from A. flaccida?; 2—ISSR markers are efficient for obtaining population genetic data in A. flaccida?; 3—The populations of A. flaccida of the Atlantic Forest are structured? and 4—Can high utilization of this species in folk medicine to influence the patterns of genetic variability in the natural populations. The answers to these questions will help determine the real state of A. flaccida conservation in the grassy ecosystems of southern Brazil and, if necessary, contribute to the elaboration of conservation strategies and rational exploitation of the species. Additionally, the data obtained here may help us understand the patterns of maintenance and expansion of the plant populations of the grassy ecosystems in the Atlantic Forest of southern Brazil from a historical perspective.Aiming to contribute to the reduction of the scientific gap regarding the genetic data of A. flaccida were collected throughout their distribution in the grassy ecosystems of the Atlantic Forest biome in southern Brazil and were named according to the county of origin (Achyrocline (Less.) DC. in Brazil proposed by Deble [In this study, seven populations of f origin . For allby Deble . The numby Deble  and actuby Deble  are showby Deble . The conA. flaccida, a literature review was first carried out to identify primer transferability studies among Asteraceae species. Of the primer pairs identified, 15 were selected based on the phylogenetic proximity of A. flaccida to the species for which the primers were initially developed , 20 ng DNA, and ultrapure water (to complete the volume).For the transferability evaluation, the 15 primer pairs were first evaluated by PCR in 10 For each primer pair, the annealing temperature described in the literature was initially used . When no-1). To determine the size of the amplified fragments, a DNA ladder 100–bp marker was used.The amplified products were separated by electrophoresis in a 3% agarose gel at a constant 110 V current for 4 h and visualized under UV light by staining with ethidium bromide   . Step 2:entified  and usede primer  for 45 sA. flaccida in Step 1, each amplified locus was evaluated according to the presence (1) or absence (0) of the DNA fragments (band). Based on the binary matrix obtained, the discriminatory power of ISSR primers was evaluated using three parameters: (i) polymorphism information content (PIC), (ii) marker index (MI), and (iii) resolving power (RP).To select the best ISSR primers for i = 2ƒi (1 − fi); where PICi is the polymorphic information content of the marker ‘i,’ ƒi is the frequency of the amplified locus (band present), and 1—ƒi is the frequency of the null allele [The PIC for each ISSR loci was computed as PICl allele .E) and is defined as the product of the total number of loci per primer (n) and the fraction of polymorphic loci (β) (EMR = n. β).”MI was calculated as described in Varshney et al. : MI = PIIb, where, Ib represents how informative the locus is of the polymorphism. The Ib can be translated into a 0–1 scale using the formula: Ib = 1 − (2 × |0.5 –p|), where, p is the proportion of the genotypes showing the locus.The RP was calculated according Prevost and Wilkinson : RP = ∑IA. flaccida was performed as follows: first, the 10 primers that showed the highest values for each attribute  were identified separately. Then, 10 ISSR primers were identified according the following criteria in the following order: 1. primers that showed the highest values for PIC, MI, and RP, 2. primers that showed the highest values for PIC and PR, 3. primers that showed the highest values for MI and RP. Whenever a primer was selected, it was excluded before applying the next criteria.The selection of the 10 best ISSR primers for genetic studies in A. flaccida were evaluated by PCR in the seven populations. Each locus amplified in each population was evaluated according to the presence (1) or absence (0) of a product band.The 10 best ISSR primers identified for A. flaccida populations, the exclusive presence and exclusive absence of each locus in each population was determined. Then, the loci were grouped to construct a graphical distribution of the genetic variability with respect to population and sampling sites. For this, the loci were grouped according to the pattern of its presence or absence in the populations. After obtaining the loci groups for each population, the total of possible occurrences (possible bands) for all groups of loci and the number of occurrences observed in each group were computed. The number of occurrences observed for a group of loci was divided by the total possible occurrences in all groups of loci in a population to generate the frequency for that loci group within the population. The frequency values obtained for each group of loci were used to construct the graphs for the distribution and frequency of the loci groups in the populations.For the analysis of the distribution pattern of each locus in the st), and gene flow (Nm) among the populations were calculated using the POPGENE software version 1.32 [The percentage of polymorphism (P), the Shannon diversity index (I), the Nei's genetic diversity (h), the Nei’s genetic distance (D), the coefficient of genetic differentiation (Gion 1.32 . A dendrST) were performed using the Arlequin software version 3.11 [Analysis of molecular variance (AMOVA) and the genetic differentiation index  amplified fragments of expected sizes after optimizing the annealing temperatures. However, when these 10 loci were evaluated in the A. flaccida, 35 primers (83.3%) showed DNA amplification  were polymorphic in all populations. The degree of polymorphism did not show a high variation among populations, with the lowest and highest values of 55.2% and 63.8% in the Porto Barreiro and Campos Novos populations, respectively.The 10 ISSR primers identified in the first stage of this study amplified 221 loci when evaluated in the seven populations of Of the 190 loci evaluated, 99 formed 11 groups with at least four loci per group. The largest group comprised 44 loci present in all populations and the smallest group comprised four loci. The remaining 91 loci had no similar pattern of distribution in the sampled populations and are referred to here as “others”. The analysis of the loci pattern allowed us to graphically visualize the distribution of genetic variability in the populations . The higThe Nei’s genetic variability of the populations ranged from 0.14  to 0.20 (Panambi), with all populations average of 0.23. The Shannon genetic variability index (I) ranged from 0.23  to 0.31 (Panambi) and all populations average of 0.37 .ST, the index of the genetic differentiation that considers how the genetic diversity is distributed among the populations was 0.33. The correlation between the Nei’s genetic distances and the geographical distances (in km) between populations (The AMOVA showed that the greatest variation was within the populations (66.71%) compared to the variation among populations (33.29%). Gulations  was posiA. flaccida populations was 1.39. In pairwise comparisons, the populations showed variable Nm values  among all m values . The gret values .The PCoA allowed for the visualization of the spatial structure of the population distribution. Thus, the populations Coxilha, Panambi, and Campos Novos were isolated in quadrants two and three, although Panambi and Campos Novos contained individuals that were far from the center of the population cluster . The GuaIn the Bayesian simulations of the Structure program, the number K  was defined as six. The distribution of individuals in the six genetic groups obtained  showed tIn the dendrogram drawn from the Nei’s genetic distances , the GuaA. flaccida populations; however, although Asteraceae primers were selected from the literature based on phylogenetic proximity, reports of transferability, and numbers of amplified alleles, they were not transferrable to A. flaccida. It is interesting that when these microsatellite primers were tested in 10 samples, 66.66% amplified fragments of expected size; however, when they were evaluated in whole populations, these primers were monomorphic and/or had a high number of null alleles. Notably, in the majority of studies that developed microsatellite primers, the authors tested these primers on a small number of samples from other species, which may falsely confirm their transferability. As with A. flaccida, these primers may have an excess of null alleles and/or be monomorphic when evaluated in populations with higher numbers of individuals and therefore, are not useful in population genetic studies. The results obtained in this study reinforce the need for the development of microsatellite primers specific to A. flaccida. As the development of microsatellites is expensive, and our group has been developing works with ISSR markers, we used these markers to get faster and more economical population genetic data of A. flaccida.In Myrtaceae and Rosaceae species, the transferability of microsatellite markers has been extensively explored and proven effective ,50–53. TA. flaccida  indicates high genetic variability in the species.The percentage of polymorphisms has been used as a measure of variability. In Asteraceae, variable values of polymorphism were found: 98.78% in lifolius , 70.0% ictorious , and 65.insignis . Thus, tA. flaccida was variable, with the populations of Marialva PR and Porto Barreiro PR indicating higher deviations in the number of loci and consequently, lower variability  in the Marialva population . These results are in agreement with the proposed by Hamrick and Godt [The parameters that quantify the genetic diversity, Nei’s genetic diversity (h), and Shannon diversity index (I) were detected at high levels in and Godt , that geFST 0.33).The distribution of the genetic diversity obtained by AMOVA showed higher variation within populations (66.71%) than among populations (33.29%), following the pattern observed in the literature for allogamous and/or pioneer species –61. In aGst  and Marialva (700 m) are at similar altitude to Coxilha (750 m) and were still genetically distant. The analysis of the current ecosystems over the last 100 years and the history of these regions since the last glacial maximum led us to two complementary hypotheses for the diversity and genetic structure observed in A. flaccida populations.The diversity and genetic structure of natural populations are affected by several factors including migratory capacity, mating systems, ecological characteristics of their habitats, altitude, and recent and historical events ,63. In AA. flaccida populations were collected. The Guarapuava, Xanxerê, and Campos Novos populations are in a high altitude continuum separated from the Coxilha and Panambi populations by the Uruguay River valley  seems to influence the patterns of genetic variability in the natural populations of the species. The lack of previous genetic data of A. flaccida does not allow drawing any inferences about genetic drift on the species, but our results give support to the conclusion that the species is not at risk of extinction in the short term in the studied regions.In conclusion, the results provided in this work show that: 1—the transferability of microsatellite markers is not an efficient strategy on


Plethodon cinereus) has long-served as a model system in ecology, evolution, and behavior, and studies surveying molecular variation in this species have become increasingly common over the past decade. However, difficulties are commonly encountered when extending microsatellite markers to populations that are unstudied from a genetic perspective due to high levels of genetic differentiation across this species’ range. To ameliorate this issue, we used 454 pyrosequencing to identify hundreds of microsatellite loci. We then screened 40 of our top candidate loci in populations in Virginia, Pennsylvania, and Ohio—including an isolated island population ~ 4.5 km off the shore of Lake Erie (South Bass Island). We identified 25 loci that are polymorphic in a well-studied region of Virginia and 11 of these loci were polymorphic in populations located in the genetically unstudied regions of Ohio and Pennsylvania. Use of these loci to examine patterns of variation within populations revealed that South Bass Island has low diversity in comparison to other sites. However, neither South Bass Island nor isolated populations around Cleveland are inbred. Assessment of variation between populations revealed three well defined genetic clusters corresponding to Virginia, mainland Ohio/Pennsylvania, and South Bass Island. Comparisons of our results to those of others working in various parts of the range are consistent with the idea that differentiation is lower in regions that were once glaciated. However, these comparisons also suggest that well differentiated isolated populations in the formerly glaciated portion of the range are not uncommon. This work provides novel genetic resources that will facilitate population genetic studies in a part of the red-backed salamander’s range that has not previously been studied in this manner. Moreover, this work refines our understanding of how neutral variation is distributed in this ecologically important organism.The red-backed salamander ( The r studies ,4). In a studies –7. These studies ,9, the d studies ,11, phen studies ,13, fine studies ,15, and  studies ,17.At present, most of what is known about the molecular ecology of red-backed salamanders is based on populations in western Virginia –16,18–20P. cinereus [e.g., a well-studied region in western Virginia and a region around Cleveland, Ohio that is becoming increasingly well studied from an ecological perspective) that have not been surveyed for microsatellite diversity previously.Recently, several studies examining the evolutionary ecology of red-backed salamander populations in Ohio have been conducted –27. Howecinereus ,14,20, tcinereus –19,21–23cinereus . The moscinereus  have rescinereus ,16,17,23During November 2011 Salamander tail clippings were collected from the Washington and Lee University (WLU) campus in Rockbridge County, Virginia, USA  to facilet al. [DNA for sequencing was isolated according to the phenol/chloroform extraction method described by Taggart et al.  and isolet al. ,32) thatet al. . A libraTo identify 454 fragments that contained potentially amplifiable loci (PALs), we used MSATCOMMANDER 1.0.8  to scan i.e., we excluded compound and interrupted repeats) tri-pentanucleotide repeat motifs because they are frequently easier to score than dinucleotide repeats [Upon identifying microsatellite containing 454 fragments, we prioritized tandem -tagged primer, 0.8 μM of 6-FAM labeled M13(-21) primer, 0.2 μM of M13(-21)-tagged primer, and 0.625 units of GoTaq polymerase (Promega). Reaction conditions were: 94°C for 2 minutes followed by 25 cycles of (1) 94°C for 30 seconds, (2) 62°C for 30 seconds decreasing by 0.3°C per cycle and (3) 72°C for 40 seconds. These conditions were followed by 8 additional cycles of (1) 94°C for 30 seconds, (2) 53°C for 30 seconds, and (3) 72°C for 40 seconds and a final cleanup step of 72°C for 30 minutes. Genotyping reactions were run in 96 well plates that contained four duplicate reactions per locus in WLU, and on average ~ five duplicate reactions per locus per SBI and OH/PA locale. Reaction success was determined by 2% agarose gel electrophoresis and successful reactions were shipped to the Arizona State University DNA Lab where they were subjected to fragment analysis in an ABI 3730 (Life Technologies) using GENESCAN LIZ 600 as an internal sizing standard. Standard curve fitting, manual scoring, and binning were performed using GENEIOUS, Version R9 (Biomatters).DNA for PCR was isolated from tail clippings using the Blood and Tissue DNeasy kit (Qiagen) according to the manufacturer’s instructions. This procedure included an RNAse digestion and resulting isolates were quantified and qualified via UV spectrophotometry and agarose gel electrophoresis. The 40 PALs selected for screening  were inio), and Hardy-Weinberg expected heterozygosity (He). Given the uneven sample sizes among populations we additionally calculated allelic richness (AR) using POPGENKIT, where sample size was determined for each locus based on the smallest number of individuals sampled across all populations [IS for each locus in each population. MICROCHECKER, Version 2.2.3 [GENALEX, Version 6.5  was usedulations . GENEPOPulations  was usedulations  estimatoon 2.2.3  was usede with the level of heterozygosity expected at drift-mutation equilibrium (Heq)—a quantity that is more sensitive than He to the loss of genetic richness that occurs during population reductions. Deviations were assessed under the stepwise mutation model (SMM), infinite alleles model (IAM), and two-phase mutation model (TPM). Following the recommendations of Piry et al. [e and Heq using the Wilcoxon signed-rank test implemented in BOTTLENECK. In addition, the output from GENALEX was used to calculate mean M-ratios across polymorphic loci, which were assessed against the critical value of 0.68 recommended by Garza and Williams [e) estimates were generated using polymorphic loci for each respective locale via the linkage disequilibrium [We used the polymorphic loci from each locale to test for evidence of recent reductions in effective population size via the heterozygosity excess approach implemented in BOTTLENECK . This apy et al. , under tWilliams . Effectiilibrium  and the ilibrium  implemenilibrium .ST and Hedrick’s further standardized G"ST [We examined population differentiation using several approaches based upon a variety of conceptual and computational frameworks. First, we used GENALEX to calculate global and pairwise estimates of Gzed G"ST  that werzed G"ST  to inferzed G"ST  to compuzed G"ST . Replicazed G"ST  and DISTzed G"ST . We thenzed G"ST  in GENALBecause the algorithm implemented in STRUCTURE tends to recover the highest level of subdivision among hierarchically differentiated populations , we performed two additional analyses in STRUCTURE on the mainland OH/PA sites. When conducting these analyses, we examined K = 1–5 when considering SQ, DB, MBSC, and ANF and K = 1–4 when considering SQ, DB, and MBSC. Both of these analyses were based on the same model, number of replicate runs, and MCMC parameters detailed above for the large-scale STRUCTURE analysis.adegenet package [i.e., island, stepping stone, etc.). When performing DAPC, we used K-means clustering and the Bayesian information criterion (BIC) to assess the fit of K-means clustering solutions for K = 1–40. The cluster memberships determined via K-means were then used as prior group assignments when performing DAPC. Prior to performing DAPC we assessed the optimal number of principal components to retain using the cross-validation procedure described in Jombart and Collins [STRUCTURE generates clusters by maximizing conformity to Hardy-Weinberg equilibrium and tends to assign individuals to superficial clusters when sampling is conducted across an isolation-by-distance (IBD) cline ,55. Give package  for the  Collins .ST/(1 –FST) against the natural logarithm of geographic distance [2. Rather, we use the slope of this regression and the associated approximate bootstrap confidence interval to get a rough idea of the degree of correlation between genetic differentiation and geographic distance across a scale that spans ~ 10–200 km.Finally, we examined the relationship between genetic differentiation and geographic distance among mainland OH/PA locales in order to gain insight into the degree to which IBD influences substructure within the OH/PA cluster identified by our large-scale STRUCTURE analysis (see below). To do this, we used the GENEPOP  package distance ,60. BecaST into a population-specific component (β) common to all loci and a locus-specific component (α) common to all populations. This in turn enables comparisons between models containing α and β terms for a given locus (selection model) and models in which the α term for a given locus has been removed . When running BAYESCAN we used 20 pilot runs with a length of 5000 steps, a burn in period of 100,000 steps, a sample size (number of sampled steps) of 100,000 with a thinning interval of 10, and prior odds for the neutral model of 10. This analysis was performed across all locales . The scored and binned microsatellite genotypes used to perform all subsequent analyses are given in Of the 40 PALs selected for molecular screening see . The disPc5, Pc9, Pc10, Pc15, Pc23, Pc25, and Pc26). In addition to detecting evidence of null alleles at these loci, MICRO-CHECKER also detected evidence of null alleles at Pc27, and Pc34. There was no evidence of genotypic disequilibrium among any pair of loci in WLU after correcting for multiple testing [Sample sizes, diversity statistics, and inbreeding coefficients for the WLU population are given in  testing .Pc25 in DB). Evidence for null alleles was detected at Pc5 in DB and MBSC, and at Pc15 in MBSC. There was no statistical evidence for genotypic disequilibrium among pairs of loci within or across OH/PA locales upon correcting for multiple testing [Sample sizes, diversity statistics, and inbreeding coefficients are given for SBI and the OH/PA sites in  testing .i.e., heterozygosity excess tests and M-ratios) for recent population reductions at any of our sites  that reliably amplified in all populations. We excluded Pc12 and Pc25 due to complete failure within some OH/PA localities and Pc3 for failure in WLU. We opted to include Pc13 and Pc14 when comparing all six locales as these two loci were polymorphic in WLU. However, we removed Pc13 and Pc14 for our investigations of fine-scale population differentiation among OH/PA locales as these markers were monomorphic across all of these sites.Analyses that examined genetic differentiation between all sampled locales were based on the 11 loci . Locus-specific values of G"ST ranged from 0.524–0.883 and were also all highly statistically significant . Combining information across all loci, the global estimate of GST was 0.351  and the analogous estimate for G"ST was 0.669 . Pairwise comparisons revealed pronounced differentiation between WLU and all other sampled localities  against the natural logarithm of distance between sites in km. The equation estimated by this regression is y = -0.122 + 0.070x with approximate 95% confidence intervals of -0.376–0.069 for the intercept and 0.024–0.157 for the slope, suggesting the effects of isolation by distance within the OH/PA cluster are not negligible. Nevertheless, as can be seen in In order to examine the degree of IBD among sites within the OH/PA cluster, we also regressed FK-means clustering and BIC suggested that K = 4–7 all represented essentially equally valid summaries of our data . As suchIn this study, we used 454 pyrosequencing to identify hundreds of potentially amplifiable microsatellite loci from the red-backed salamander—an ecologically important species that has long-served as a model system in evolutionary ecology , 21–27. ST = -0.006). Similarly, DAPC results based on these markers recovered analogous clusters to those obtained from STRUCTURE and yielded similar albeit slightly weaker patterns of correct individual assignment. Collectively, these results show that the panel of markers we have identified are informative at relatively small spatial scales, even in comparisons involving populations that were founded as a result of post-glacial range expansion (see below). While our endeavors will not eliminate the need for researchers working in other parts of the range to conduct screens to verify amplification success and polymorphism in their study populations, they do provide meaningful guidance about which loci to try first. Indeed, ongoing work in one of our labs (RBP) has begun to extend a subset of these markers  to the Peaks of Otter Salamander, Plethodon hubrichti, and we recommend starting with this panel of 16 markers when transferring markers to unstudied red-backed salamander populations and cross-amplifying markers in closely related species.Attempts to utilize microsatellite markers developed from large, well-studied populations in western Virginia  in otherR for SBI was 1.974, whereas among OH/PA sites mean AR varied between 2.786–3.507 and mean AR at WLU was 3.940. These findings are likely a consequence of a founder’s effect followed by strong drift in the SBI population. However, we were unable to detect other genetic signatures of a recent bottleneck in SBI, and this population appears to be more-or-less in Hardy-Weinberg equilibrium. Given our fairly small sample size in SBI  and the tendency of bottleneck tests to be underpowered [The most striking pattern when comparing intra-population diversity and summary statistics across populations is how much lower diversity estimates from SBI are relative to the other five locales we sampled. For example, in SBI, 6 of 14 (42.9%) loci were monomorphic in comparison to values ranging from 2 of 27  to 3 of 13  at other sites . Moreover, mean Arpowered , it is pR (3.507), followed by ANF (3.071), DB (2.859), and SQ (2.786). However, other measures of diversity  did not follow this pattern. Thus, as reported by Jordan et al. [e for SQ and DB, we could not directly assess the relationship between patch size and effective population size. However, the sampling effort required to collect individuals at DB was substantially lower than SQ, which suggests a larger census population size within DB. Differences in salamander abundance between DB and SQ probably reflect the profusion of high-quality microhabitat (rocks) at DB. As was the case with SBI, we did not detect unequivocal genetic signatures of recent population reductions at any of the OH/PA sites. However, SQ and ANF both had mean M-ratios < 0.68, although these estimates were within one SE of this critical value. None of the OH/PA sites were markedly out of Hardy-Weinberg equilibrium, with DB, MBSC, and SQ having mild homozygote excess (on average ~ 5% to < 1% more homozygosity than expected) and ANF exhibiting mild heterozygote excess (on average 1.5% less homozygosity than expected). Collectively, these results suggest that these mainland OH/PA populations are not highly inbred even though some of them (SQ and DB) are restricted to small isolated patches of habitat.Among mainland OH/PA sites, ANF is within a large tract of continuous forest and MBSC is within a considerable, albeit occasionally interrupted, wooded area near the shores of a small manmade lake. On the other hand, SQ is within a somewhat isolated patch of woods that is surrounded by farmland and suburban residential areas, while DB is within a ~ 2 km strip of woods (< 200 m wide) that is surrounded on both sides by urban residential areas. MBSC had the highest mean An et al.  for site2 in total area that is boarded by the city of Lexington, Virginia to the south and east, pastureland to the west and northwest, and the Maury River to the north and northeast. AR at this site was somewhat higher than at the other sites in our study, and it is possible that this is related to the older age of Appalachian populations relative to sites that were glaciated during the Pleistocene [IS = 0.223, SE = 0.073), and while this may be attributable to null alleles, there is evidence that the WLU population has undergone a recent population reduction, as heterozygosity excess tests were significant under the IAM and TPM. Interestingly, surveys of dinucleotide loci from sites within large tracts of continuous forest near Mountain Lake Biological Station  resulted in considerably larger genetic richness estimates  than locale; , they suST 0.358–0.441) demonstrates that there are isolated populations within the formerly glaciated portion of the red-backed salamander’s range that are very different from populations at relatively nearby locales. Similarly, Noël et al. [The pattern of genetic structuring recovered by our analyses of between population variation is one in which there is isolation by distance at small to intermediate spatial scales (~ 10–200 km) and marked differentiation among geographic regions. In a general sense, this finding is consistent with the original geographic patterns of protein electrophoretic rates offered by Highton and Webster . Howeverl et al.  observed2 plots separated by distances of 2 km or less. While comparison of these studies is confounded with any differential effects that may exist between urban and rural landscapes, it suggests that the degree of differentiation among formerly glaciated sites in Ohio is more similar to formerly glaciated sites in Indiana than it is to un-glaciated sites in Virginia. Interestingly, in contrast to the results of Cabe et al. [In a survey of six dinucleotide microsatellite loci across 10 sites (maximum distance between sites of 70 km) within the fragmented, rural landscape of northeastern Indiana, Jordan et al.  observede et al. , Noël ete et al.  were unae et al. ,24 for ae et al. . Becausee et al. , it is pi.e., South Bass Island, Long Island, Ile-Bizar, Ile-Perrot, and Montreal Island) are particularly remote, these results strongly suggest that aquatic barriers as small as one km across, and perhaps even less, are capable of effectively isolating red-backed salamander populations [One of the more striking results of our study was that the degree of differentiation between SBI and Cleveland area populations ~ 100 km away , was greater than the degree of differentiation between these three sites and WLU. Indeed, the DAPC we performed ordinated OH/PA closer to WLU than SBI  despite ulations . This coulations .In this paper, we have presented genetic resources that will enable the scientific community to conduct population genetic studies in regions of the red-backed salamander’s range that have not previously been investigated in this manner. In addition, we have demonstrated the utility of these resources by using them to assess genetic variation within and between three well differentiated portions of this species range. In many respects, our findings are consistent with the original description of geographic patterns of protein variation for this species . HoweverS1 Fig(PDF)Click here for additional data file.S2 Fig(PDF)Click here for additional data file.S3 Fig(PDF)Click here for additional data file.S4 Fig(PDF)Click here for additional data file.S5 Fig(PDF)Click here for additional data file.S6 Fig(PDF)Click here for additional data file.S7 Fig(PDF)Click here for additional data file.S8 FigIndividuals are represented by a single bar. The number of clusters is K = 5 and colors correspond to those in (PDF)Click here for additional data file.S1 File(XLSX)Click here for additional data file.S2 File(FASTA)Click here for additional data file.S3 File(FASTA)Click here for additional data file.S4 File(FASTA)Click here for additional data file.S5 File(FASTA)Click here for additional data file.S6 File(XLSX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Tablee and/or associated confidence limits.Ninety-five percent confidence intervals are given in parentheses. The symbol ∞ indicates that NeESTIMATOR was unable to estimate N(DOCX)Click here for additional data file.


Rhododendron weyrichii, which is distributed in the southwestern parts of the Japanese archipelago and on an island of South Korea, using statistical phylogeographic approaches based on the DNA sequences of two chloroplast and eight nuclear loci in samples analyzed from 18 populations on eight continental islands, and palaeodistribution modeling. Time estimates for four island populations indicate that the durations of vicariance history are different between these populations, and these events have continued since the last glacial or may have predated the last glacial. The constancy or expansion of population sizes on the Japanese islands, and in contrast a bottleneck in population size on the Korean island Jeju, suggests that these islands may have provided different conditions for sustaining populations. The result of palaeodistribution modeling indicates that the longitudinal range of the species as a whole has not changed greatly since the last glacial maximum. These results indicate that exposed seafloors during the glacial period formed both effective and ineffective migration corridors. These findings may shed light on the effects of seafloor exposure on the migration of plants distributed across continental islands.Continental islands provide opportunities for testing the effects of isolation and migration on genetic variation in plant populations. In characteristic of continental islands is that the geographic connections between these islands, which are currently distinguished by seaways, have experienced fluctuations caused by sea‐level changes due to climate oscillations during the Quaternary. Plant populations on the islands have migrated between these islands via the exposed seafloors or been isolated. Here, we examined the demographic history of a temperate shrub,  Firstly, most studies to date have examined only a few DNA sequences , and stochastic variance between gene genealogies in such a limited number of genomic regions has made it difficult to obtain reliable estimates of population demographies. Secondly, if population genetic analyses are not conducted in the framework of an appropriate time scale, it is not possible to make any biogeographically meaningful inferences about the drivers of population divergence. This is particularly problematic in phylogeographic analyses of continental island species, because here population divergence can be triggered by interglacial geographic isolation and/or glacial habitat isolation. In the last decade, demographic modeling of natural populations based on the coalescent approach has become commonplace  is a deciduous shrub species, occurring mainly in temperate regions that experience high rainfall during summer in southwestern parts of the Japanese Archipelago including the Kii Peninsula of Honshu, Shikoku, and Kyushu islands and small islands surrounding them, and in Jeju Island in the southwest of the Korean Peninsula, disjunctly . Its pollinators are butterflies and bumblebees, and thus, exchange of pollen between island populations is infrequent under present‐day interglacial conditions. However, the dispersal barriers formed by seaways among neighboring islands disappeared during the LGM (ca. 21 kya) due to the shallow depth of the sea  sequences. We also examined the distribution of the species during the LGM using ecological niche modeling. The specific aims of the study were (1) to estimate population genetic divergence between continental islands and to address the isolation–migration histories of these populations; (2) to evaluate differences in genetic diversity and historical changes in population size among islands; and (3) to make inferences about population survival on each island during the LGM.The configuration of the landscape in these island regions is believed to have affected the distribution and demographic history of plant populations. In this study, we examined the demographic history of 22.1R. weyrichii individuals from 18 populations on eight continental islands .Leaf samples were collected from 142 2.2trnG intron and rpl36‐rps8) were PCR‐amplified from four individuals per population using universal primers  found in rpl36‐rps8 was counted, but these repeats were excluded from alignments when determining cpDNA haplotypes. Genealogical relationships for all cpDNA haplotypes were constructed as a parsimony network using TCS v. 1.06  and aligned using the Muscle algorithm implemented in MEGA v. 5 Edgar, . Mononuc2.42.4.1Arabidopsis thaliana  databases to identify a possible function for the product of each locus.The nDNA sequences acquired were also assembled using DNA Baser and aligned using Muscle in MEGA; indel polymorphisms in these sequences were omitted from subsequent analyses. The haplotype phases of the aligned sequences were determined using PHASE v. 2.1  and nucleotide diversity  at each locus was estimated based on the four‐gamete test  sequences, and significance was determined using 10,000 coalescent simulations. In addition, an HKA test . All of these analyses were performed using DnaSP, with the exception of the HKA test which was carried out using the HKA program (http://genfaculty.rutgers.edu/hey/software#HKA). Within‐population genetic diversity was evaluated for each population. Nucleotide diversity, Watterson's θ , with 3.0 × 104 iterations after a burn‐in period of 2.0 × 104. The optimal value of K was estimated by plotting the log likelihood of the data, Ln Pr(X|K)  , which is a product of the absolute time in years (T) and the mutation rate (μ), population size , migration rate per mutation event , and population migration rate (2NM = 0.5θm) were estimated using IMa2  model. To estimate the IM history among four major regional population groups , the population demographic parameters Figure  populatiThe approximate Bayesian computation (ABC) approach enables us to infer demographic history by estimating the values of parameters in a complex model without calculating its likelihood , specimens in two herbaria , and personal observations. In total, 172 presence records for R. weyrichii were obtained covering the entire range of the species, after removal of duplicate records from within each 2.5‐arc‐minutes cell. Current climate data at a resolution of 2.5 arc‐minutes were obtained from WorldClim . We prepared the LGM palaeoclimate layers at a resolution of 2.5 arc‐minutes following the methods of Sakaguchi et al. .The model calibrated with current climate conditions was projected onto the reconstructed climate during the LGM obtained from two climatic simulations, the Community Climate System Model  ranging from 9 to 25 and the nucleotide diversity for all sites (π) ranging from 0.0018 to 0.0060. Recombination events were recognized for seven loci, all except PHYE, and the number of minimum recombination events (RM) ranged from 0 to 9 (Table D test) and interspecific  variation (Fay and Wu's H test), neutral evolution of every locus was not rejected . The π, Watterson's θ (θW), and D values for each population ranged from 0.0024 to 0.0054, 0.0027 to 0.0057, and −0.571 to 0.656, respectively  between populations ranged from 0.0031 to 0.0069 (Table S2). Each nuclear locus had major haplotypes, and variable patterns of haplotype distribution were detected among loci . In the case of K = 2, the distribution of clusters showed a division between Kyushu and Shikoku , and cluster 4 predominated in Jeju and was also recognized in Fukue .The pairwise genetic divergence  between Jeju and Kyushu (tJJ+KY), between Shikoku and Kii (tSK+KI), and between Jeju–Kyushu and Shikoku–Kii (t1A+2A) estimated by the IM model were 0.043 (0.008–0.276), 0.006 (0.001–0.041), and 0.151 (0.051–0.384), and the corresponding estimates of the divergence time (T) between these islands were 69 kya (13–443), 9 kya (2–65), and 243 kya (81–616), respectively , were not rejected by likelihood ratio tests, with the exceptions of migration from Shikoku to Kyushu and from Kyushu to Jeju in the sense of time forward.The posterior modes and 95% highest posterior density (HPD) intervals for the split time (0 [95% HPD] = 0.136 [0.000–0.673]) than the other populations  was supported for Kii and Kyushu, whereas the exponential growth model (Model 2) was supported for Shikoku and the instantaneous size reduction model Model 3) was supported in the case of Jeju . The predicted distribution based on current climatic conditions was similar to the actual distribution of the species with high probability >0.50), although some areas along the Pacific Ocean side and on the western edge of Honshu were also predicted to be suitable  than those on Jeju according to ABC analysis; the pattern was similar for the result of IM analysis. Palynological studies have suggested that warm‐temperate forests may have retreated to southern refugia and been replaced by cold‐tolerant coniferous and broadleaf vegetation throughout most of the Japanese Archipelago during the LGM , which is distributed on the Pacific Ocean side of Honshu. An intraspecific taxon with a different flower color, which is recognized as R. weyrichii f. purpureum Hara, in the northern part of Kii is considered to have resulted from introgression events from the other species, as has also occurred in other closely related Rhododendron species  showed large population sizes (θCarpinus or Quercus whereas fossil pollen records suggest that the island has been dominated by grassland with patches of cool‐temperate deciduous broadleaved woodland and that conditions were dry during the LGM (Chung, R. weyrichii; however, Bayesian clustering and demographic analyses suggested that R. weyrichii may have survived in restricted and scattered habitats on or around the island during the LGM. The possibility of the invisible refugia is supported by the high genetic diversity of tree species on the island (Chung et al., In contrast to the populations in the Japanese Archipelago, the estimated value of effective population size on Jeju was low, and this is likely to have been caused not by a recent bottleneck event. In addition, the effective population size on Jeju has not expanded after the bottleneck event. Although the time estimates given by IM and ABC analyses exhibited different values, this difference may be the result of an estimation error due to difference in examined models and model simplification. At least the accepted model and the time estimate suggested that the Jeju population is not likely to have been formed by recent migration from the Japanese island. The Jeju population is currently restricted along rivers in warm temperate forests characterized by trees of M Chung, . In addi4.3When considering isolation and migration among islands, the LGM is an important period in history Hewitt, , 2004. U5R. weyrichii populations using model‐based approaches revealed that history of population isolation between islands is likely to have a considerable influence on population survival on each island, even if the islands were sometimes connected geographically during climatic oscillations (Qi et al., Statistical phylogeographic analyses of None declared. Click here for additional data file.


Glycine max), many “immortalized” genotypes of elite varieties spanning the last century have been preserved and characterized using ∼50,000 single nucleotide polymorphic (SNP) markers. Also due to autogamy, the history of North American soybean breeding can be roughly divided into pre- and posthybridization eras, allowing for direct interrogation of the role of recombination in improvement and selection. Here, we report on genome-wide characterization of the structure and history of North American soybean populations and the signature of selection in these populations. Supporting previous work, we find that maturity defines population structure. Though the diversity of North American ancestors is comparable to available landraces, prehybridization line selections resulted in a clonal structure that dominated early breeding and explains many of the reductions in diversity found in the initial generations of soybean hybridization. The rate of allele frequency change does not deviate sharply from neutral expectation, yet some regions bare hallmarks of strong selection, suggesting a highly variable range of selection strengths biased toward weak effects. We also discuss the importance of haplotypes as units of analysis when complex traits fall under novel selection regimes.Crop improvement represents a long-running experiment in artificial selection on a complex trait, namely yield. How such selection relates to natural populations is unclear, but the analysis of domesticated populations could offer insights into the relative role of selection, drift, and recombination in all species facing major shifts in selective regimes. Because of the extreme autogamy exhibited by soybean ( The study of crop domestication inspired many of the earliest insights in evolutionary biology , althougThe Huang-Huai Valley in China appears to be the center of origin of domestication for soybean . BecauseThe early phase of soybean development entailed the selection of lines that were optimal for particular growing regions. Desirable traits were likely to be quite similar in the prehybridization and posthybridization eras . Yet, gst values between US and Canadian varieties relative to four landrace subpopulations, noting that sharp distinctions in allele frequencies for known genes, such as E1, a maturity gene, and the T locus, which controls tawny vs. gray pubescence. Two recent studies have compared elite soybean cultivars from North America with a sample of globally distributed landraces  matrices were generated using the command-line implementation of TASSEL 4.0 (-distanceMatrix) (maturity ].Results), was assessed, and the number of markers traced to a particular ancestor was tallied for every ancestor and divided by the total markers. Markers for which the longest haplotype could not be determined or was ambiguous were not counted in the genome-wide average. Scripts used to perform key aspects of this analysis, among others associated with this study, are available as in File S3.Because of the very low heterozygosity levels in soybean, each marker was determined to be most closely related to one of 29 major North American ancestors based on the ancestor with which it had the longest match length to the left and right of each marker. These 29 ancestors were chosen based on their percent contribution as assessed previously using pedigree analysis  value was used to characterize changes in diversity. By normalizing by πa, this statistic allows comparison across loci of various starting diversity levels. The log2 transformation is an extension of that rationale in that when two separate loci start at the same diversity level, a reduction to 25% the original diversity, for example, should appear twice as substantial as a reduction to 50%.TASSEL 5.0 was used to calculate average pairwise difference, π, between haplotype windows for a given set of lines. A sliding window that was 50 markers wide was moved in 10 marker increments across the length of each chromosome. TASSEL options were as follows: -diversity, -diversitySlidingWin, -diversitySlidingWinStep 10, and -diversitySlidingWinSize 50. The units of π are the number of pairwise differences per marker averaged across the sliding window. The π measure for all 29 North American ancestors, πx), sample.interval=c, profile.likelihood=FALSE, and bound=c,” where x is the number of loci that had an initial allele frequency between 0.5 and 0.6. The generational intervals  were selected based on the effective number of generations we assumed to have occurred during each decade or combination of decades and the average midpoint of the years of release within each group.For each population, we grouped varieties released from the 1940s, 1950s, and 1960s and used these allele frequencies for generation 0. Only loci with major alleles that started at a frequency between 0.5 and 0.6 were used for the initial timepoints. This frequency filtering was done in order to avoid analyzing loci with alleles that commonly reappear after fixation as a result of statistical sampling. Varieties released in each additional decade  were grouped separately, and we assessed allele frequencies within these decades, treating them as sequential samples. The effective population size was estimated for each set of temporal data points using the R package NB  with theWe evaluated the statistical power of four possible measures of selection based on the set of simulations defined in st measures and linear regression, only the timepoints up to and including the first timepoint at which an allele reached fixation (<5% or >95%) were used. The slope of the linear regression was estimated using the Perl module Statistics::LineFit, reported as Δf. The logistic regression coefficient . Sequential timepoint samples were used as for Ne estimation above, except that all loci with an initial major allele frequency <0.95 were included, not just those between 0.5 and 0.6. The starting frequency distribution of simulated, neutral alleles was designed to reflect that of the actual markers in each population.We used the N2(πx / πa). See Thresholds for putatively selected regions were determined based on the shape and variance of total distributions of Δf and logAll possible haplotypes within a 50 marker window were identified and their frequencies assessed across each chromosome in 10 marker increments as done for the diversity analysis above. Each unique haplotype in the pre-1970s sample was assigned a color in order of highest to lowest frequency . HaplotyH) was assessed using H-scan (version 1.3) developed by Philip Messer (https://dl.dropboxusercontent.com/u/77898333/H-scan.cpp).For each window, the top three largest rates of change (|Δf|) for individual markers were averaged and reported along with the most rapid change for a haplotype within the same window. The use of three alleles was a heuristic approach to balance a) the excessive noise of using only the single highest marker in a window and b) the dramatic reduction in sensitivity associated with taking the average across the entire window. Average pairwise length of shared haplotypes . Each line was genotyped using the SoySNP50K Infinium Chip as part of USDA’s effort to characterize the entire Glycine germplasm bank. The data are publicly available. Historical analysis in maize indicates that modern breeding for heterotic groups strongly differentiated North American populations . Nearly every ancestor shows a significantly higher IBS with one or more populations over another . In As described above, it is known from pedigree analysis that Northern and Southern breeding lines are derived from distinct ancestry. Therefore, it is likely that populations 0-I, III-IV, and V+ each have very distinctive profiles of ancestry. To investigate this possibility, we calculated the average IBS of each population relative to each of the 29 major North American ancestors . To achieve a more refined measurement of the degree to which an ancestral line contributed to a population, we compared the haplotypes of elite lines within each population released prior to the 1970s to the haplotypes of all 29 major North American ancestors .The relationship of elite population structure to the North American soybean ancestors has implications for which genomic regions experienced reduced diversity in the earliest lines developed from hybridization breeding. Diversity within those early populations could be reduced because of selection or because there was reduced diversity among the lines that served as parents in the vast majority of crosses resulting in those lines , but they also clarify situations in which one ancestor shares substantial haplotype structure with another ancestor but did not contribute to the same population, as in the case of S-100 [Jackson (PI 548657) was excluded from this haplotype analysis because it was introduced in the 1950s and is 85% identical to Roanoke (PI 548485)  suggests a major cause for the early and stable distinction between these MG0-I and MGIII-IV populations  ]. In addulations . The anculations , it has ulations . This fiIn the remainder of the manuscript, we treat ancestors with a fraction contribution >0.03 as “founding ancestors” of a particular population. This distinction is in contrast to the group of all 29 major North American ancestors used above.2 ratio of genetic diversity (π) of the earliest stages of the posthybridization era (pre-1970s), πx, to that of all 29 North American ancestors, πa. Generally, this diversity measure varies between 2 and −2. Values were rarely >2, thus, diversity was rarely substantially increased (File S1).With regard to the biased contribution of different ancestors, we attempted to determine if a region of reduced diversity in a population resulted from the pool of founding ancestors being fixed at that locus or from a single ancestral haplotype that was rapidly fixed in early stages of regional breeding. For this analysis, genotyping information for each population was divided into windows that were 50 markers long. For each of these windows, we assessed the log2 diversity ratio. This result is due to there being little or no diversity among all 29 North American ancestors.Using chromosome 10 as an example , there aFile S1). In nearly all cases, a single haplotype appears in all or most of the founding ancestors at regions of reduced diversity. Because there is variation for these regions across the total set of ancestors (otherwise the log2 diversity ratio would be ∼0), these loci could possibly represent regions that are important to their specific regions of cultivation. The most obvious of these would be genomic intervals containing genes related to flowering time. Indeed, all four of the major effect maturity genes, e1–e4, are present at a threshold of <2.3 (File S1); therefore, the ancestors were segregating for haplotypes that were eventually fixed by 1970. In the MG 0-I population, the ancestral haplotype common to Lincoln and Capital was lost in favor of the more common alternative haplotype .It is rare for any population to completely lose diversity across a 50 bp window , although there does appear to be mild population differentiation when moving from pre-1970s populations to 2000s populations .Because populations are finite, evolution occurs due to genetic drift regardless of selection. The effective population size, Nedict Ne . Becausee for each population is given in e, followed by 0-I and then III-IV. Inbreeding reduces Ne because, in effect, it is structuring one population into several subpopulations due to the nonrandom mating of genotypes. The use of a single genotype as a parent within a population over time is one form of inbreeding. In turn, our Ne estimates correlate with the homogeneity of parentage within each population: MG V+ has three major ancestors, MG 0-I has two, and MG III-IV has only one (Lincoln) (NLincoln) .st statistic, as well as two simple statistics based on ether linear or logistic regression. We simulated the allele frequency trajectory based on the number of generations in our sample and a population size of 200, a value comparable to relevant Ne estimates , the variance in estimates resulted in poor power to differentiate selected loci at a 5% false positive rate  indicates that selected loci are likely of small effect and, after including the markers in high LD with selected loci, comparable in number to neutral loci. Given the difficulty in devising an appropriate null distribution (see Discussion), the loci with the strongest signatures of change are the best candidates for regions under strongest selection  and have been under intensive selective pressure. Indeed, we know that variation in allele frequencies is increased by selection in the populations used herein, although we cannot be sure of the magnitude. If selection has, in fact, driven many alleles to higher frequency, the observation that few values extend beyond the distribution under neutral expectation  were removed (data not shown) . This result indicates that a genomic region has become fixed without a substantial change in constituent allele frequencies. We refer to these windows as “haplotype sneaks” for the remainder of the manuscript . Across all populations, we found 15 examples of Type 2|3 regions, although 73% occurred in the MG 0-I population. As an example, a ∼500 marker-wide region from chromosome 11 of MG 0-I has three subregions, with haplotypes that changed more rapidly than any of the underlying markers  across the genome for each population . We trac markers . This re−6). The inclusion of neutral regions or regions selected for single alleles will reduce this ratio. Thus, the median value of 0.86 among haplotype sneaks, though higher than neutral, does not exceed 1. Moreover, haplotype change was assessed based on pre-1970s samples relative to 2000s samples, whereas Δf is only evaluated prior to fixation across all decades and, therefore, can have a higher value even if total change is the same. Still, composite graphs across all populations (File S2) rarely reveal examples, such as Across all populations and genomic windows, the ratio of greatest-haplotype-change to greatest-individual-allele-change for haplotype sneaks is 18% greater than neutral windows as defined in Using haplotype spectrum plots, we also interrogated soft sweeps, which were the most common mode of selection detected in our data . For exaFile S2) show that large genomic tracks can have increases in π and decreases in H relative to pre-1970s cultivars, as was suggested by 2 diversity ratios were slight: –0.05 and –0.01 in MG 0-I and V+ populations, respectively, likely reflecting a balance between increased diversity related to recombination and reduced diversity related to selection. In contrast, the MG III-IV population exhibited a genome-wide increase in H from 77 to 112 in pre-1970s populations relative to 2000s, and a sharper reduction in diversity with a median log2 ratio of –0.19.Haplotype spectra plots from MG V+ population (File S2), although in many cases selection has reduced the diversity locally . As described in the Results, it is likely inappropriate to assume that the majority of loci are behaving in a neutral fashion in crop populations under active selection for a complex trait. This is not only because of selection, but because of the high LD present in these populations. Therefore, establishing an appropriate null model remains extremely challenging. Even in an experimental population with known demographics, selection and other modes of nonrandom mating can result in a twofold reduction in Ne estimates calculated directly from demographic parameters .There are numerous statistics available for detecting selection. These different statistics are sensitive to different evolutionary time-scales and to how the data are structured (election . In modethan Fst  and boththan Fst . Though It has long been appreciated that simultaneous selection at multiple loci can dramatically affect selection efficacy . In the As made clear by this study and many others, it can be very difficult to define an appropriate null distribution for selection. As it eliminates the need to estimate a null distribution from the tested data, perhaps the most useful methodology for understanding selection in crop improvement will involve analyzing genome-wide marker data for hundreds of members of known breeding pedigrees in which resultant progeny were the product of selection (


Aedes aegypti is the main vector of dengue, Zika, chikungunya and yellow fever viruses. This major disease vector is thought to have arisen when the African subspecies Ae. aegypti formosus evolved from being zoophilic and living in forest habitats into a form that specialises on humans and resides near human population centres. The resulting domestic subspecies, Ae. aegypti aegypti, is found throughout the tropics and largely blood-feeds on humans.The mosquito Ae. aegypti specimens from an urban population in Senegal in West Africa were more closely related to populations in Mexico and Sri Lanka than they were to a nearby forest population. We estimate that the populations in Senegal and Mexico split just a few hundred years ago, and we found no evidence of Ae. aegypti aegypti mosquitoes migrating back to Africa from elsewhere in the tropics. The out-of-Africa migration was accompanied by a dramatic reduction in effective population size, resulting in a loss of genetic diversity and rare genetic variants.To understand this transition, we have sequenced the exomes of mosquitoes collected from five populations from around the world. We found that Ae. aegypti in Senegal and domestic populations on other continents are more closely related to each other than to other African populations. This suggests that an ancestral population of Ae. aegypti evolved to become a human specialist in Africa, giving rise to the subspecies Ae. aegypti aegypti. The descendants of this population are still found in West Africa today, and the rest of the world was colonised when mosquitoes from this population migrated out of Africa. This is the first report of an African population of Ae. aegypti aegypti mosquitoes that is closely related to Asian and American populations. As the two subspecies differ in their ability to vector disease, their existence side by side in West Africa may have important implications for disease transmission.We conclude that a domestic population of The online version of this article (doi:10.1186/s12915-017-0351-0) contains supplementary material, which is available to authorized users. Aedes aegypti, which transmits dengue, chikungunya, yellow fever and Zika viruses. A widespread epidemic of the Zika virus has recently occurred across South America, Central America and the Caribbean and has been linked to fetal brain abnormalities , ]: z = –29.6, p < < 0.0001; , ]: z = –27.2, p < < 0.0001). When we attempted to infer specific migrations between these populations using either f3 statistics or TreeMix, we found that the results were inconsistent. Importantly, however, allowing migration does not alter the topology of the tree in Fig. Despite finding no evidence using the three-population test for the Senegal Urban population being a mixture of African and non-African populations, we do find evidence for admixture among our five populations. We used the four-population test  to examiWe next fitted explicit demographic models to our genetic data, both to provide an additional test of how our populations are related to each other, and to understand when population splits occurred and how population sizes changed . We fittK = 2) suggested that there may have been migration back to Senegal Urban from non-African populations. Similar results have been reported in previous admixture analyses of populations from Senegal [In apparent contradiction of these conclusions, our admixture analysis Fig. ; K = 2 s Senegal . However Senegal . To exam6), suggesting that this ancestral population was still in Africa. Therefore, the two populations likely separated shortly before the out-of-Africa migration. Approximately 3000 generations ago, there was a strong reduction in the effective population size of the Mexican population, presumably reflecting a bottleneck associated with the out-of-Africa migration. Alongside this, the Senegal Urban population experienced a reduction in its effective population size ~4150 generations ago. The divergence of the Senegal Forest population from Senegal Urban and Mexico was considerably more ancient .The demographic model allows us to infer when populations split and how their population size has changed Fig. . FollowiAe. aegypti aegypti arose, it evolved a suite of characters that increased its capacity to vector dengue virus and yellow fever virus [FST = 1) in Senegal Forest versus Sri Lanka and 254 such sites when Senegal Forest was compared to Mexico  [PBSn1 and per-SNP FST in Additional files When the anthropophilic subspecies er virus , 14, 15.e PBSn1)  to identOr4; AAEL015147) plays a key role in Ae. aegypti aegypti’s preference for feeding on humans. Three windows in our dataset tag this gene, but they show little evidence for genetic differentiation in any of the three domesticated populations . We similarly found no individual SNPs in this gene that were strongly differentiated between the subspecies  of the gene we identified is associated with genetic variation in Drosophila olfaction [McBride et al.  found thlfaction . While tlfaction .Table 1GAe. aegypti aegypti populations is insecticides. An important mechanism involves changes to the target of DDT and pyrethroids that makes it insensitive to these insecticides  [VGSC, and we find only marginal evidence of differentiation . However, two amino acid variants known to be associated with insecticide resistance are at frequencies of 73% and 85% in Mexico but absent elsewhere ; cytochrome P450 is a family of proteins whose functions include breaking down insecticides in Aedes aegypti [A key selection pressure on many L006019) . The gen aegypti   [Ae. aegypti aegypti, while populations within Africa were Ae. aegypti formosus. Furthermore, anthropophilic populations in sub-Saharan Africa evolved independently from those outside Africa. Our data and analyses consistently reject this model.Our conclusions contradict the prevailing model of l Kenya) . Under tAe. aegypti aegypti from elsewhere in the world migrated back to Africa. It is clear that this population is not directly derived from non-African populations, as it has greater genetic diversity than the Mexican or Sri Lankan populations . Furthee Africa , inferene Africa  and compe Africa . TherefoAe. aegypti aegypti populations from Senegal Urban, Mexico and Sri Lanka than in the Ae. aegypti formosus populations. Furthermore, genetic diversity was lowest outside of Africa, intermediate in the Senegal Urban population of Ae. aegypti aegypti and highest in the African Ae. aegypti formosus populations. This was reflected in the rates of genetic drift in these populations  than Ae. aegypti formosus [Ae. aegypti aegypti’s importance as a disease vector results from it living alongside and biting humans [Ae. aegypti formosus in Senegal was from a forested area, our Ugandan population was from a human-disturbed region outside Kampala. Furthermore, previous studies in West Africa have found mosquitoes that morphologically resemble Ae. aegypti formosus breeding indoors [Ae. aegypti formosus lives alongside and feeds on humans in Africa is unclear.The finding that close relatives of American and Asian t Africa , and it formosus , and simformosus . Howeverformosus . In addig humans . It will indoors . TherefoAe. aegypti aegypti populations on the coast of Kenya which appear genetically distinct from other African populations [Another unanswered question is the distribution of the two forms across Africa. Further sampling and analysis will not only resolve this, but will also reveal the extent of gene flow between the two subspecies. This may help us understand why they have remained genetically distinct in Africa. In East Africa crosses have found no evidence of assortative mating or intrinsic reproductive incompatibilities . Howeverulations .Ae. aegypti. The subspecies were originally defined based on colouration [Ae. aegypti formosus . However, our results demonstrate that Ae. aegypti aegypti occurs in Senegal, and there is no conflict between genetic and morphological definitions of the subspecies in our dataset. Therefore, an important question is whether other African populations fall neatly into the two subspecies and whether they can be identified from morphological characteristics.Our results have important implications for the definition of the two subspecies of ouration , but genAe. aegypti in the past, most of which have used small numbers of genetic markers. Where datasets are small, there can be a lack of statistical power; for example, a previous study of 11 SNPs in Senegal found no significant genetic differentiation between the subspecies [Why do our conclusions differ from those of previous studies? There have been numerous population genetics studies of bspecies . Many stbspecies , but makbspecies –66. Othebspecies , 19, 21.Ae. aegypti populations in Africa arose separately from domestic populations elsewhere in the tropics [FST is not straightforward [Ae. aegypti aegypti from Senegal is not because these populations are unrelated, but is instead due to the population bottleneck associated with the out-of-Africa migration that caused large changes in allele frequencies that differentiate African from non-African populations. We confirmed this argument for our dataset by simulating data genomic data under our demographic model, and demonstrated that this led to distantly related African populations being incorrectly grouped together in an admixture analysis.In contrast to our results, previous studies of microsatellites and SNPs concluded that domestic  tropics , 16. Thi tropics . We see tforward . For exatforward . TherefoAe. aegypti aegypti evolved remains an important question. One approach to identify these changes is to look for regions of the genome that are strongly differentiated between the subspecies. This is greatly helped by comparing African populations of the two subspecies, as the shifts in allele frequencies that occurred during the out-of-Africa migration are likely to have obscured any effects of natural selection. We have catalogued the most strongly differentiated genes between subspecies in our dataset, and we hope that this list of candidate genes will be of interest to researchers interested in specific traits. However, to conclusively identify the genetic basis of adaptation, it will be necessary to include more populations, sequence the genome outside the exome to allow more powerful tests of selection and ultimately link these differences to phenotypic changes.The genetic basis of the changes in vector competence and behaviour that occurred when Ae. aegypti in Senegal and domestic populations on other continents share a different common ancestor from other African populations. The most parsimonious explanation of this observation is that an ancestral population of Ae. aegypti evolved to specialise on humans in Africa, giving rise to the subspecies Ae. aegypti aegypti. The descendants of this population are still found in Africa today. The rest of the world was colonised when mosquitoes from this population migrated out of Africa. Non-African populations are genetically distinct from African ones due to the population bottleneck that accompanied this migration.We conclude that a domestic population of


Drosophila nigrosparsa populations. The number of loci was gradually reduced from 11 to 1, using the Allelic Richness (AR) and Private Allelic Richness (PAR) as criteria for locus removal. The effect of each reduction step was evaluated by the number of genetic clusters detectable from the data and by the allocation of individuals to the clusters; in the latter, excluding ambiguous individuals was tested to reduce the rate of incorrect assignments. We demonstrate that more than 95% of the individuals can still be correctly assigned when using eight loci and that the major population structure is still visible when using two highly polymorphic loci. The differences between sorting the loci by AR and PAR were negligible. The method presented here will most efficiently reduce genotyping costs when small sets of loci (“core sets”) for long-time use in large-scale population screenings are compiled.Small, isolated populations are constantly threatened by loss of genetic diversity due to drift. Such situations are found, for instance, in laboratory culturing. In guarding against diversity loss, monitoring of potential changes in population structure is paramount; this monitoring is most often achieved using microsatellite markers, which can be costly in terms of time and money when many loci are scored in large numbers of individuals. Here, we present a case study reducing the number of microsatellites to the minimum necessary to correctly detect the population structure of two  Culturing organisms in the laboratory is a frequently used method in many biological fields such as ecology, conservation biology, and evolutionary biology.One method to rapidly identify changes in genetic diversity is monitoring using molecular markers like microsatellites,−6 to 10−2 events per locus and generationIn testing this method, we used microsatellite markers. Microsatellites were discovered in the early 1980s and are short and highly variable nucleotide tandem repeats in DNA sequences.Drosophila nigrosparsa Strobl, 1898.In detail, the purpose of this study was to evaluate a method determining how few loci are needed to still detect the short-term changes in genetic structure in a population threatened by loss of diversity. We used individuals of two populations of the cool-climate mountain fly Drosophila nigrosparsa Strobl, 1898 were sampled at Kaserstattalm  and at Pfitscherjoch  using fermented banana baits from July to August 2012.Individuals of two natural populations of a for 45 s, and 72°C for 1 min, followed by 72°C for 10 min. Locus-specific Ta was 48°C  and 55°C . Amplification success was checked by agarose gel electrophoresis. Capillary electrophoresis was performed by a commercial provider  using an ABI 3130 instrument . The resulting traces were visualized using PeakScanner software v1.0  and scored manually. In total, microsatellite profiles of 558 individuals were generated .DNA of individual flies was extracted using the Sigma GenElute Mammalian Genomic DNA Miniprep Kit  according to the manufacturer's instructions. Eleven species-specific microsatellite loci  were amplified via M13-tailed labelling.ST, and Analyses of Molecular Variance (AMOVA) were computed in GenAlEx v6.4140. In the AMOVA, the generations  and the populations  were used as hierarchy levels in multiple combinations. Linkage disequilibrium (LD) was calculated using Arlequin v3.5 with 10,000 iterations.Deviations from Hardy-Weinberg-Equilibrium (HWE), pairwise FTo detect the genetic variation of K and P and to asses a potential effect of husbandry (loss of genetic variation from Generation 0 to Generation 5), AR and PAR were calculated for each population and generation using HP-Rare v1.0 assuming 52 genes,STRUCTURE v2.3.3For further assessment of the minimum number of loci needed to distinguish between K and P flies, the individuals of Generation 5 were used. STRUCTURE analysis and search for best K were performed as described above with 496 individuals . The loci were then sorted by the mean AR value of the two populations; the locus with the lowest AR was removed and STRUCTURE analysis/best K search re-performed. Locus removal and data analysis were repeated until only the locus with the highest AR remained. The same procedure was applied on the dataset using PAR, resulting in each 10 reduced datasets for AR and PAR.Ap to belong to cluster A and a probability Bp = 1 – Ap to belong to cluster B. We considered an individual assigned to cluster A when its Ap was larger than 0.5 plus a variable exclusion threshold value x. Accordingly, an individual was assigned to cluster B when Bp > 0.5 + x. Individuals with Ap or Bp larger than 0.5 but smaller than or equal to 0.5 + x were considered as unassignable (U). Thresholds from x = 0.00 to x = 0.50 were used in 0.05-steps. As this algorithm for cluster assignment handles just K = 2, which is also the true number of clusters as discernible from the analysis using all data, also in the two reduced datasets where another value than two was suggested as best K (see Results), the STRUCTURE results for K = 2 were used for computation. On the individual level, this algorithm allowed three outcomes: (i) Correct assignment: An individual was assigned to the same cluster it had been assigned to when using all 11 loci. (ii) Incorrect assignment: An individual was assigned to the cluster opposite to the one it had been assigned to when using 11 loci. (iii) Exclusion: Due to an admixture value close to 0.5, no assignment was achieved. At x = 0.00, no exclusion occurred, while at x = 0.50 all individuals were excluded. Higher levels of x can be expected to reduce cases of incorrect assignment but also reduce the number of individuals assigned at all.STRUCTURE analysis with 11 loci resulted in a best K of 2 (see Results and Discussion). From the 10 repetitions of this K, the individual cluster assignment of the run with the highest LnP(D) was used as benchmark for comparison with the STRUCTURE assignments of the reduced datasets. In detail, at K = 2, STRUCTURE provides for each individual a probability The assignment of each individual to A, B, and U in all loci-reduced datasets was compared with its assignment when using all data, and incorrect assignment rate  and exclusion rate  were calculated in Excel 2013.Scoreable alleles were found in 89.6% (DN48) to 98.2% (DN40) of the individual amplicons (Table S2). The number of alleles per locus ranged from 12 to 25, with a mean of 19.36. AR per locus ranged from 7.63 (DN40 in K5) to 20.00 (DN39 in K0), PAR from 0.05 (DN40 in K5) to 3.95 (DN45 in P0). Over all loci, average AR was 13.38 for K0, 13.30 for P0, 11.77 for K5, and 11.18 for P5; average PAR was 0.99 for K0, 1.28 for P0, 0.45 for K5, and 0.51 for P5 . Thus, the number of loci significantly deviating from HWE had increased from K0 to K5 and from P0 to P5. A similar trend emerged in LD, where the number of significantly linked locus pairs increased from K0 to K5 (3 to 30) and from P0 to P5 (0 to 21) (Table S5). Significant deviations from HWE and significant LD in wild populations like K0 and P0, which were collected in the field to establish the laboratory stocks, would indicate that non-neutral evolutionary forces like inbreeding, non-random mating, and/or selection are acting on the populations.ST values ranging from 0.01 to 0.03 among the various combinations of populations and generations except between the two Generation 0 populations, for which the values were not significant (IS value ranged from 0.11 to 0.19 and was always significant in the various combinations. The percentage of variation between populations increased from 0.01% between K0 and P0 to 2.71% between K5 and P5. These results indicate a weak population differentiation, slightly increasing during five generations of laboratory culturing, and are in line with the loss of Allelic Richness observed between Generation 0 and 5.The AMOVA revealed significant but very low Fnificant . The FISSTRUCTURE analysis of K0, P0, K5, and P5 resulted in a best K = 2. In Generation 0, single individuals assigned mainly to one of the two clusters, or intermediate, existed in both populations K and P. After five generations, some sorting had occurred, with one cluster dominated by individuals from K and the other by individuals from P . This soThe sequence of locus removal is given in Screening for loss of genetic diversity is of high importance for laboratory culturing and will often require the screening of many individuals.


We describe how selection by industrial pollutants and other stressors has acted on multiple populations of killifish and posit that extreme nucleotide diversity uniquely positions this species for successful evolutionary adaptation. Mechanistic studies have identified some of the genetic underpinnings of adaptation to a well‐studied class of toxic pollutants; however, multiple genetic regions under selection in wild populations seem to reflect more complex responses to diverse native stressors and/or compensatory responses to primary adaptation. The discovery of these pollution‐adapted killifish populations suggests that the evolutionary influence of anthropogenic stressors as selective agents occurs widely. Yet adaptation to chemical pollution in terrestrial and aquatic vertebrate wildlife may rarely be a successful “solution to pollution” because potentially adaptive phenotypes may be complex and incur fitness costs, and therefore be unlikely to evolve quickly enough, especially in species with small population sizes.For most species, evolutionary adaptation is not expected to be sufficiently rapid to buffer the effects of human‐mediated environmental changes, including environmental pollution. Here we review how key features of populations, the characteristics of environmental pollution, and the genetic architecture underlying adaptive traits, may interact to shape the likelihood of evolutionary rescue from pollution. Large populations of Atlantic killifish  We focus on rapidly and repeatedly evolved pollution tolerance in populations of Atlantic killifish , and those species that we care about conserving tend to be larger bodied animals with relatively small population sizes and long generation times . Short generation times allow evolutionary change to closely track the pace of environmental change  may disrupt cardiovascular and craniofacial development in vertebrate embryos  determines organismal fitness, natural selection may act on genetic variation to alter that map and mitigate the effects of environmental perturbation. Those fitness‐restoring variants are of basic interest in evolutionary biology because their origin, the distribution of their fitness effects, and how the structure of the genotype–phenotype map shapes those factors are not yet well‐known. They are also of basic interest in molecular biology, the goal of which is to understand developmental and regulatory processes at a molecular level. Systems in which evolution has occurred in response to toxic exposure could be thought of as forward genetic screens in which the pool of mutations has been enriched for those that are functionally and environmentally significant—a potentially very different set than might be uncovered through genomewide association in populations not subject to natural selection, or through mutagenic approaches. A useful feature of evolutionary toxicology systems is that they tend to be replicated. Many environmentally damaging human activities  occur repeatedly in discrete locations, applying similar selection pressures across populations and species of organisms in ways that strengthen conclusions that can be drawn from studying them.22.1F. heteroclitus) present a compelling study system for revealing the mechanisms that may contribute to rapidly evolved adaptation to environmental pollution. This is because they are abundant in coastal marsh ecosystems  concentrations, where PCBs are used as a proxy for urban and industrialized global contamination  , biota sampled from NBH more than 20–30 years later continue to bioaccumulate PCBs . These sediments were highly polluted with PAHs, PCBs, and many other toxic contaminants , implicated the AHR pathway as likely being involved in the adaptive mechanism. The AHR is a ligand‐activated transcription factor that was initially identified because of its role in mediating dioxin  toxicity and in regulating the induction of xenobiotic‐metabolizing enzymes in response to TCDD and PAHs in mice , and association with the nuclear bHLH‐PAS protein AHR nuclear translocator (ARNT). The ligand‐bound AHR‐ARNT complex interacts with specific enhancer sequences (AHR response elements or AHREs) on target genes to regulate the expression of those genes. The transient activation of AHR and subsequent induction of xenobiotic‐metabolizing enzymes is considered an adaptive response, facilitating the biotransformation and excretion of toxic endogenous and exogenous compounds. However, sustained activation of AHR, such as occurs by exposure to poorly metabolizable DLCs or constant exposure to labile AHR agonists, leads to toxicity through sustained misregulation of genes involved in cellular homeostasis. The AHR is thus an integral component of the mechanism by which DLCs and some PAHs cause toxicity, and loss of AHR function protects against these effects  and paralogs of each of these (designated “a” and “b”), the result of a whole‐genome duplication at the base of the teleost lineage, after its divergence from the lineage leading to tetrapods  showed signals of selection in the NBH population  were conducted to characterize the genetic basis of tolerance in the NBH population using a QTL mapping approach. For this purpose, F1 progeny were produced by cross‐breeding mature killifish from NBH and Block Island, RI, one of the most sensitive populations ever tested . Variants near other AHR pathway genes also appeared correlated with the tolerance phenotype. For example, the most significant QTL identified, explaining up to 46% of the phenotypic variance within families analyzed  affecting the AHR‐ligand binding complex suggests both a mechanism for tolerance to DLCs, and an explanation for why variation in AHR alone only partially accounts for tolerance in killifish. Thus, the QTL approach identified genetic regions associated with DLC tolerance that included some genes known for their involvement in the AHR signal transduction pathway through which DLCs act, as well as other markers whose roles in DLC tolerance are not yet known.Seven main QTL intervals associated with NBH tolerance were identified on three linkage groups or putative chromosomes, as well as one additive and three epistatic interactions , and at ~82% frequency in the third (NBH). The second haplotype exists only in the ER population and is close to fixation. Both haplotypes have a core region of about 100 kb unbroken by recombination, which contains many variants showing high frequency differences between tolerant and sensitive populations. For these two haplotypes, however, we detected no variants  that are both shared among them and that distinguish them from all sensitive reference populations. This suggests that the causal variants in each haplotype are different, although because there are some small gaps in the reference assembly in this region, we cannot exclude the possibility that we did not detect the causal variant.CYP1A falls in another very highly ranked outlier region in all four populations. In this region, we again see divergence between variants likely under selection in the northern tolerant populations and the southern. In this case, the re‐sequencing data indicate a series of duplications of the region containing CYP1A in the three northern populations, but not in the southern population. Individuals from tolerant populations in the north have up to eight copies of CYP1A per diploid genotype (mean = 4) while individuals from the southern tolerant population and all sensitive populations have an average of 2 ; thus, there is no evidence of duplication in the southern tolerant population. In northern populations, there is evidence for three separate duplication events with different genomic spans. Short read data and the local signature of selection indicate that at least some of the extra copies are inserted in tandem.AHR1b/2b are within outlier regions in two tolerant populations. Five additional genes  are in outlier regions in only the southern tolerant population , adaptation to other stressors in these radically altered habitats , compensatory adaptations to the negative pleiotropic consequences of primary tolerance‐conferring adaptations, and perhaps adaptations that confer fitness advantage at specific life stages. In contrast, the QTL mapping approach is designed to identify population differences related to specific traits of experimental interest, for example, tolerance to a specific chemical structure like PCB126. Together, these complementary approaches offer great potential for revealing the genetic architecture that underpins adaptation.5.4AHR pathway genes are consistently differentially responsive in all tolerant populations compared to their sensitive counterparts, and AHR pathway genes harbor among the strongest signatures of selection in all tolerant populations  is within the top‐ranking selection signature region in NBH fish. Some environmental toxicants may be transported from cells by these proteins, whereas others can sensitize organisms to other xenobiotics by blocking MDR function and preventing their export. Contaminants that are common in urban estuaries, such as personal care products, pesticides, heavy metals, and PCBs, may interact with MDR proteins and disrupt their function  transport proteins are efflux pumps that often serve as the first line of cellular defense upon exposure to toxic chemicals by preventing their intracellular accumulation Bard, . A homolKCNB2, KCNC3) in cardiomyocytes and RYR3 that regulates intracellular calcium. What distinguishes the ER site from other polluted sites is extreme contamination with complex mixtures of PAHs  and hypoxia‐inducible factor (HIF‐2α) genes, may reflect possible compensatory changes  Sterna dougallii are exposed to PCBs primarily by ingestion of fish within their feeding range , killifish population genomic studies have also shown the complex pattern of genes under selection in the wild. While extrapolation of these observations confirms that adaptation in a rapidly changing, human‐altered habitats will not be simple or typically fast enough to provide rescue for most species, the killifish system will continue to serve as a valuable model to predict and test how the interaction of ecology and evolution contribute to the ability of species to respond to rapidly changing environmental conditions.