Harpia harpyja) is a forest dwelling species that is considered near threatened and suffers from habitat loss in the forests of the Neotropical region. In this study, 72 historical and current samples were assessed using eight autosomal microsatellite markers to investigate the distribution of genetic diversity of the Harpy Eagle of the Amazonian and Atlantic forests in Brazil. The results showed that the genetic diversity of Harpy Eagle decreased in the regions where deforestation is intense in the southern Amazon and Atlantic Forest.Habitat loss and fragmentation intensify the effects of genetic drift and endogamy, reducing genetic variability of populations with serious consequences for wildlife conservation. The Harpy Eagle ( Habitat loss and fragmentation can lead to reduction in connectivity of populations with concomitant decrease in gene flow, thus increasing genetic differentiation and reducing genetic variability ,2. GenetHarpia harpyja, Accipitridae) is the largest eagle in the Neotropical region; it occurs in low densities within its tropical forest habitat [The Harpy Eagle .Deforestation effects on the genetic diversity of Harpy Eagle was evaluate using samples from historical specimens and samples from areas subject to elevated levels of deforestation in Brazil, corresponding to the southern Amazon (arc of deforestation) and the Atlantic Forest . AmazoniBlood, tissue and feather samples were used as source of DNA, with feathers being the most frequently used tissue type. DNA from all samples types was extracted using the Qiagen® DNA Extraction Kit. To degrade keratin of the feathers, 30μl of dithiothreitol (100 mg/ml) was added in the first step of the protocol following the method described by Horváth et al. .primers had the M13 primer added at their 5' end, enabling the incorporation of fluorescent dye using the method described by Schuelke [Eight autosomal microsatellite loci transferred to the Harpy Eagle from other species were used. These loci were previously tested, and were found to be polymorphic, in Hardy-Weinberg equilibrium and without linkage disequilibrium . The useSchuelke . The PolSchuelke . The proThe genotyping of museum samples was repeated from two to five times to avoid possible errors due to the small quantities and high levels of degradation of the DNA . HomozygThe program Micro-Checker v2.2  was usedK) was estimated using the Bayesian clustering algorithm implemented in Structure 2.3 [K = 1–5, with 106 MCMC interactions and a 105 burn-in period using the models of correlated allele frequencies and allowing mixture. For each value of K, the average log-likelihood was calculated. The analysis was carried out on the complete dataset.To test whether genetically distinct populations exist, the number of populations  Northern Amazon (NAM) (N = 11), (ii) Southern Amazon (SAM) (N = 30), (iii) Atlantic Forest (ATF) (N = 31), (iv) Historical Southern Amazon and Atlantic Forest (HSA) (N = 22), (v) Contemporary Southern Amazon and Atlantic Forest (CSA) (N = 39), (vi) Historical Atlantic Forest (HAT) (N = 18) and (vii) Contemporary Atlantic Forest (CAT) (N = 13). Using these groups, we compared several scenarios. Spatial scenarios: NAM, SAM and ATF. Temporal scenarios: HSA and CSA; and HAT and CAT. Spatial-temporal scenarios: NAM, HSA and CSA ; and NAMFST) [HO) and expected heterozygosity (HE) and the mean number of alleles per locus (A).We used the Arlequin 3.5 software package  to assesFST)  for the HE metric as this metric is less sensitive to differences in sample size [The Wilcoxon signed-ranks test was employed to test the significance of differences between the levels of genetic variability in the temporal scenarios using the ple size .HE) using the program BOTTLENECK 1.2.02 [HE values were significant, and thus if there is signal of a recent genetic bottleneck.To test for recent genetic bottleneck, we tested for heterozygosity excess  = -1140.30, σ = 19.00; LnP (D|K = 2) = -1151.51, σ = 131.35; LnP (D|K = 3) = -1262.18, σ = 426.86; LnP (D|K = 4) = -1255.54, σ = 418.06; LnP (D|K = 5) = -1309.77, σ = 522.97).Analysis in Structure showed no population structuring; the highest mean probability supported the existence of just one population , how, howFST,FST values observed in the comparison between NAM and CSA were greater than those observed between NAM and HSA , with FST of 0.12 between current fragmented populations and FST of 0.032 between historical and contemporary samples although historical and recent genetic diversity levels were indistinguishable. The Harpy Eagle, as well as other large eagles, has a long lifespan and generation time of 18.5 year [Haliaeetus albicilla) in Europe [Our results were quite different from those encountered in other eagle species. For example, Martínez-Cruz et al.  found th8.5 year , thus th8.5 year –68, as in Europe . In the n Europe . Contrarn Europe . As seenHaliaeetus albicilla (HE = 0.510–0.606) [Haliaeetus vocifer (HE = 0.413–0.554), Haliaeetus leucocephalus (HE = 0.349–0.464) [Aquila chrysaetos (HE = 0.48) [Aquila adalberti (HE = 0.549) and Aquila heliaca (HE = 0.627) [Haliaeetus vociferoides (HE = 0.101–0.163) whose reduced genetic diversity is the result of a historical setting of hundreds of thousands of years in which the species went through with a low population [Genetic diversity levels found in the Brazilian Harpy Eagle are comparable with those found in other eagle species that are not threatened, for example 0–0.606) ,69, Hali = 0.48) ; and som= 0.627) . The expLerner et al.  studied The consequences of the reduction in genetic diversity make the results of this study very preoccupying for the conservation of the Harpy Eagle in southern Amazon and Atlantic Forest. Reduced heterozygosity is a hallmark of populations with reduced fitness and elevated risk of extinction . A correThe use of samples derived from collections allowed us to evaluate the genetic variability of both historical and current samples of the Harpy Eagle in the context of the deforestation scenario of Brazilian tropical forests. The Harpy Eagle genetic diversity that was apparently homogeneous throughout its distribution in the forests of Brazil in the past has become reduced under the current deforestation scenario. However, we believe that conservation measures together with habitat preservation can be positive for the maintenance of the genetic diversity of the Harpy Eagle. Such actions might involve: (i) protection of nesting trees and breeding pairs; (ii) protection of the remaining areas of southern Amazon and Atlantic Forest; and (iii) restoration and protection of forest corridors between the Amazon and Atlantic Forest.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.


Health Education England (HEE) is responsible to the UK government for creating a lasting education legacy to support thousands of healthcare professionals as they upskill in response to this genomic revolution. The place of genetic counselors, genetic counseling, and ultimately “genomic counseling” within this mix forms the focus of this Commentary. This piece is written with the British context in mind, where genetic counseling is delivered predominantly within regional clinical genetics services by the government-funded National Health Service (NHS).Mainstream medical services, whether they are oncology, pediatrics, infectious diseases, cardiology, or dermatology are increasingly using genomic data in patient management Graham . Throughdoing genetic counseling means communicating genetic information in a meaningful way to patients. But it does not just mean having a conversation that happens to involve genetic information; it goes much further than that. Genetic counseling is a process of “helping people understand and adapt to the medical, psychological and familial implications of genetic contributions to disease” ”  has no family history of a particular condition who is then faced with a genome-based test and subsequent result (Middleton www.gcrb.org) and outcome measures to define success  may need to explain a genetic test result . In this situation they are unlikely to explore the implications of the result for family members nor be arranging cascade screening, however, they are likely to be using strong, empathic communication skills to help the patient understand and appreciate the significance of the genetic information . “Debate about what ‘genomic counseling’ will include and who will practice it has been fueled by the transition from single-gene focused genetic counseling and testing to a full genomic medicine approach” Ormond , p. 189.In terms of patient management, the breadth and scope of genomic data to be revealed from a sequenced assay, is potentially enormous. Metaphorically speaking, when searching a genomic sequence (library) for a particular gene(s) (book) we may: (1) search for one individual book or select books on one topic ; or (2) choose to browse all the shelves and pick out a collection of books across multiple topics .Each of these scenarios is described in more detail:If a whole-genome sequence is done to answer a specific clinical question, for example, why was my child born blind? The sequence is used as a resource of DNA, but a specific clinical question can be answered via a targeted bioinformatics analysis, for example, only looking at a panel of visual impairment genes. Here, the clinical question is specific and despite genomic technologies being used as part of the testing repertoire, as the results are targeted; it is almost insignificant that the mechanism to obtain the result uses sequencing technology. From the genetic counselor's perspective; the experience of delivering the results to the patient is the same. Here, there may be a strong emotional context, with the necessity to support multiple members of the family to communicate and evaluate risk of developing the same condition. Again genomic counseling  is really just the same as genetic counseling.What is pivotal in terms of education is that health professionals in mainstream medicine understand that not all genes are deterministic. In this interim period while genomic technologies are being introduced into mainstream services, but the training in interpretation has not yet caught up, the potential for inappropriate referrals into clinical genetics services is enormous. For example, anecdote from colleagues in clinical genetics suggest a significant increase in a new wave of referrals for common polymorphisms, such genomic results may not be significant in terms of health and do not require the involvement of a clinical geneticist or genetic counselor. As education about genomics filters into mainstream practice, such a result can be handled appropriately without specialist referral Fig..Depending on what question is being answered through the screening, a whole-genome/exome sequence would provide multiple options for output, ranging from a few results to potentially hundreds or even thousands. In making these choices, we need to be cognizant of the limitations in our ability to interpret much of the rare variation present in our genomes and the ascertainment bias  that confounds the use of much of our existing knowledge in a screening context.Given the limitations in interpretation, should a screening mechanism be chosen, it could be applied in several different ways. For example, screening could be done opportunistically each time a sequence is performed for specific clinical reasons, for example, when offering an exome sequence for a child with developmental disorders an opportunistic screen for 24 cancer and cardiac conditions could be performed at the same time  based on a genotype, when the phenotype does not exist yet . Communicating risk and possibly multiple risks containing multifactorial effects and helping the patient to adapt and incorporate this could constitute ‘genomic counseling’ in this scenario.If the screening is being used in a healthy adult as part of a public health agenda, let's assume the patient has no awareness of, or concerns about, any particular conditions in their family. Due to this there may be limited emotional triggers, pretest, to guide and inform the patient about the conditions being tested for , for genetic counselors to gate-keep genomic information delivery for mainstream medicine. They may, however, have a large role in supporting other healthcare practitioners to do so. There will be many conversations involving genomic data that have limited emotional context, for these, all that is required is a health professional who understands how to interpret the data and incorporate this into their usual practice. However, if ever the receipt of genomic data does result in a more complex reaction  then referral into a clinical genetics service is still recommended.Clinical geneticists and genetic counselors manage whole families rather than individuals, work with the emotional fallout from inherited disease and are experts in rare multisystem and inherited genetic conditions and so it could be argued that there will always be a need for this specialist domain of care.It is not clear whether genetic counselors internationally should lay claim to the title “genomic counselor.” However, what is clear is that genomic medicine is being mainstreamed on an enormous scale and that health professionals who have no connection to clinical genetics and who have no understanding of what genetic counselors do, will be delivering information gleaned from genomic technology. The HEE have recognized that there is an urgent need to address training within the NHS to upskill the workforce with respect to genomic knowledge. What is necessary to develop alongside this is an upskilling of knowledge in how this information can be communicated and the implications for families. Genetic counselors are in a strong position to inform this teaching.doing some level of genomic counseling; but, does that make them a “genomic counselor?” Decisions will have to be made about whether this remains the domain of genetic counselors. Our sense is that genetic counselors and clinical geneticists will become expert practitioners in genomic counseling and will specialize in the management of genomic information delivery when there is an emotional and familial context . “Genetic counselors have a long-standing history of working on the clinical forefront of implementing new genetic technology. Genomic sequencing is no exception”  then it is logical to conclude that through the upskilling of the workforce, most health professionals in the NHS will be In time a new hierarchy may be established, linked to qualifications and training and a distinct profession may emerge with protection over the title “genomic counselor.” In the meantime, genetic counselors need to engage with the debate about this, upskill their own knowledge with respect to bioinformatics, sequencing, data interpretation, and visualization and the ethical, legal, and social issues raised by genomics and in time, decide whether they will lead or be led with respect to genomic counseling.


Myotis lucifugus, at swarming sites in southeastern Canada using 9 nuclear microsatellites and a 292-bp region of the mitochondrial genome. Analyses of FST, ΦST, and Bayesian clustering (STRUCTURE) found weak levels of genetic structure among swarming sites for the nuclear and mitochondrial genome  suggesting high contemporary gene flow. Hierarchical AMOVA also suggests little structuring at a regional  level. Metrics of nuclear genetic structure were not found to differ between males and females suggesting weak asymmetries in gene flow between the sexes. However, a greater degree of mitochondrial structuring does support male-biased dispersal long term. Demographic analyses were consistent with past population growth and suggest a population expansion occurred from approximately 1250 to 12,500 BP, following Pleistocene deglaciation in the region. Our study suggests high gene flow and thus a high degree of connectivity among bats that visit swarming sites whereby mainland areas of the region may be best considered as one large gene pool for management and conservation.Characterizing movement dynamics and spatial aspects of gene flow within a species permits inference on population structuring. As patterns of structuring are products of historical and current demographics and gene flow, assessment of structure through time can yield an understanding of evolutionary dynamics acting on populations that are necessary to inform management. Recent dramatic population declines in hibernating bats in eastern North America from white-nose syndrome have prompted the need for information on movement dynamics for multiple bat species. We characterized population genetic structure of the little brown bat,  Understanding the structure and dynamics of populations has long been recognized as a foundation for informing management decisions for species at risk because it provides the essential evolutionary perspective to the conservation process Frankel . PopulatThe degree of connectivity within and among populations is influenced by environmental and biotic factors and traits specific to species such as dispersal. Dispersal is the movement of individuals from their natal group to a breeding group such that genetic exchange has occurred  have high vagility Fenton  with manTemperate dwelling bats exhibit an annual cycle consisting of a lengthy period of reduced activity during hibernation, followed by a shorter active period used for self-maintenance and reproduction. For most of the active season, the sexes are segregated with females forming maternity colonies and males apparently living independently or in small groups Safi , althougMyotis lucifugus) is a small (6–10 g) temperate swarming species, distributed widely across North America  which supports the contention that autumn swarming facilitates gene flow. Further, recent European studies showed higher genetic diversity at swarming sites compared to summering sites which supports the extra-colony hypothesis where multiple summering colonies fuse at swarming sites such that they act as mating centers . Methods for the capture and handling of bats were approved by the Saint Mary's Animal Care Committee under permit from each provincial jurisdiction. White-nose syndrome was detected in winter 2009/2010 in southern counties of Quebec close to the sampling sites, and no further sampling was conducted. Detection of WNS in the winter of 2010/2011 in New Brunswick at one of the sites restricted our sampling to one site that was in a different county and did not have WNS detected at the time of sampling. We also reduced our trapping efforts in Nova Scotia in autumn 2011 to only sample sites where sample sizes were exceptionally low to reduce the risk of spreading the disease via the capture and handling of bats as WNS was not detected at the sites that autumn.During the autumns of 2009–2011 (10 August to 06 October), bats were trapped in harp traps  or mist nets  set at 15 swarming sites in three Canadian provinces: Quebec (QC), New Brunswick (NB), and Nova Scotia  were collected from each of the wings of individuals , 0.1 mmol/L EDTA, pH 8).For all captures, sex was identified, and age was determined as young-of-the-year (YOY) or adult based on the degree of ossification and fusion in the epiphyseal growth plates of the fourth metacarpal Anthony . Two smaμL reaction volumes containing 1× PCR Buffer , 0.2 mmol/L of each dNTP (Invitrogen), 1.5 mmol/L MgCl2, 0.16 mg/mL Bovine Serum Albumin , 0.05 U/μL Taq DNA polymerase, and approximately 10 ng of template DNA. The PCR amplification conditions were as follows: an initial denaturing cycle of 95°C for 5 min; followed by 30 cycles of 95°C for 30 sec, an annealing temperature of 55°C for 1 min, 72°C for 1 min; with a final extension period of 64°C for 45 min. The PCR products were purified using the Antarctic Phosphatase/Exonuclease I protocol . Sanger sequencing was performed with primer KAHVII using the Macrogen INC., Seoul, Korea Sequencing Service. All base calls were verified manually through visual examination of electropherograms, and sequences were trimmed to a common 292-bp segment using 4Peaks (v1.7) DNA sequence editing software (Griekspoor and Groothuis An approximate 300-base-pair (bp) fragment of the mitochondrial control region, hypervariable II domain (HV II), was amplified in 356 individuals Table  using thh; Nei π; Tajima Mitochondrial DNA (mtDNA) sequences were aligned using Clustal W  was examined using a hierarchical analysis of molecular variance (AMOVA) on adult females, adult males, and all adults. To determine what substitution model was most appropriate for our mitochondrial data, we ran ModelGenerator  of 0.11 and estimated transition/transversion rate ratio of 11.91. The genealogical relationships between mtDNA haplotypes were explored using a median-joining network . Networks allow for alternative potential evolutionary relationships to be shown as internal cycles. Median-joining networks incorporate median vectors which represent unsampled sequences or ancestral sequences that can allow for greater inference of genealogical relationships despite “missing” intermediary haplotypes.To examine genetic differentiation among all swarming sites, ΦS , we analyzed the mtDNA HV II data as the full dataset from all 15 swarming sites. First, we examined the distribution of the number of pairwise differences, the mismatch distribution, of samples to infer whether a recent and sudden expansion occurred . Each forward primer was labeled with one of four fluorescent dyes . Amplification conditions for PCR were as follows: an initial denaturing cycle of 95°C for 5 min; followed by 30 cycles of 95°C for 30 sec, annealing temperature for 1 min, 72°C for 1 min; with a final extension period of 64°C for 45 min. Cycling was carried out on Applied Biosystems  96 Well Veriti Thermal Cyclers, and amplified products were size-separated and visualized on an ABI 3500xL capillary electrophoresis system. Alleles were scored using GeneMarker  by comparison with GeneScan 600 LIZ® internal lane size standard (Life Technologies). For each individual, all loci electropherograms were visually inspected for verification of allele peak size calling; allele peaks were binned for scoring after examination of frequency distributions of raw allele calls. A negative and positive sample control  was used on each 96-well plate run to ensure typing consistency among runs.All samples were genotyped at 10 microsatellite loci previously described for this species  and expected heterozygosities (HE), number of alleles observed (NA) per population, and null allele frequency per locus were assessed using CERVUS v3.0.3  and 2010 .Microsatellite loci were tested for departure from Hardy–Weinberg equilibrium (HWE) across each locus and within each swarming site using the Markov chain method in GENEPOP v4.1.3  with a burn-in of 500,000 steps and 2,000,000 recorded for the Markov chain Monte Carlo (MCMC) steps. We examined the ln probability, ln[P(X|K)], of the ten runs for each value of K . Pairwise FST values were converted to (FST / (1 − FST)) following Rousset  to test for correlation between geographic distance and genetic differentiation using a Mantel test implemented in the web-based IBDWS  where sex was randomly assigned to individuals within each subpopulation holding the number of each sex constant.Lastly, we tested for sex-biased dispersal by investigating Ft et al. . We consn = 69) followed by New Brunswick  and Nova Scotia . Four haplotypes were found in high frequency (n = 30 or greater), with one found at 13 swarming sites  and two found at 12 swarming sites . Both of these haplotypes were found in all three provinces. The remaining high-frequency haplotype  was found at 10 swarming sites, 9 of which were in Nova Scotia and at one site in New Brunswick where only one individual with this haplotype was found. Haplotype diversity (h) was relatively high averaging 0.8523 ± 0.0981 (SD) and ranging from 0.8552 ± 0.0804, 0.8857 ± 0.1731, and 0.9073 ± 0.0285 for Nova Scotia, New Brunswick, and Quebec, respectively. Nucleotide diversity (π) was generally low and similar across all swarming sites averaging 0.0150 ± 0.0028 (SD) with a range of 0.0094 to 0.0184, although by province it was highest in Quebec followed by Nova Scotia and New Brunswick at 0.0155 ± 0.0029, 0.0154 ± 0.0025, 0.0132 ± 0.038, respectively.Ninety-five haplotypes were obtained from 356 adult individuals sampled across the fifteen swarming sites. Fifty-three polymorphic sites defined the haplotypes arising from 45 transitions, eight transversions, and two insertion/deletion events. Many haplotypes were found in only single individuals (56.8%). After correcting for sample size, we found that at the regional level, Quebec had the highest proportion of unique haplotypes  although these differences do not appear to differ greatly in magnitude; we did not test for significant differences. The pattern of variation in ST were significant, after correction for multiple tests, and the global ΦST estimate for all adults was 0.045 (P < 0.001). Analyzed separately, males and females had similar global ΦST estimates of 0.045 and 0.052 (both P < 0.001), respectively. Hierarchical analysis by AMOVA found that the majority of mitochondrial genetic differences were found within swarming sites (91.4%) and only 3.05% (P < 0.0001) of the variation found among provinces suggesting low regional structuring. The median-joining network , but still indicative of low levels of population differentiation. Twenty-eight of the 105 pairwise comparisons (25.7%) of Φork Fig. .FS statistic was statistically significant at FS = −99.87 (P < 0.001), and (P = 0.11) and Fu and Li's F* and D* were not significant . The shape of the Bayesian skyline plot (BSP) suggests a similar population history to that of the mismatch distribution with an inferred population expansion  was removed from subsequent analysis because of significant deviations from Hardy–Weinberg equilibrium (HWE) across all swarming sites. Eight of remaining nine loci (without inclusion of comparisons of Mluc30) generally met the assumptions of HWE (Table S3) with Mluc5 showing deviations from HWE in six of the 15 sites and a null allele frequency estimation of 6.3%. Locus Mluc21 showed deviations from HWE in 13 of 15 sites and a null allele frequency estimate of 31.5%. We chose to retain this locus for analyses after an exploratory run with locus Mluc21 omitted produced similar results for pairwise FST estimates, FIS estimates, and the test for overall heterozygote deficiency. Although null alleles can reduce genetic diversity resulting in increased FST estimates , ranged from 0 to 3.3% per locus with a mean error rate of 1.6% although we did not perform a blind test of this. We retained 735 adults and 168 YOY for analyses that were successfully genotyped at ≥ seven of the nine loci. Mean observed heterozygosity was moderately high for adults . When analyzed separately, female and male adult bats also displayed a similar magnitude of global FST at 0.003 ± 0.002 SE (P = 0.003) and 0.001 ± 0.001 SE (P = 0.002), respectively. Despite the smaller sample sizes, the two cohort groups composed of YOY displayed a similar order of magnitude of global FST estimates to that found for the adult dataset . These low estimates suggest high contemporary gene flow among swarming sites or shared recent ancestry for each sex and age class. Estimates of FIS for all swarming sites were positive (Table FIS = 0.135 ± 0.049 (SE), and the global test for heterozygote deficiency was significant (P < 0.005). This suggests nonrandom mating may occur within sites although the presence of null alleles at some loci could also explain these positive FIS estimates.Metrics of population structure on nuclear markers indicate weak population differentiation. Of the 105 pairwise nt Table , and theE P = 0.0. When anK)] from the STRUCTURE analysis, across the replicates demonstrated convergence of the chains and indicated that K = 1 (mean ln[P(X|K)] = −24912.98 ± 0.175 (SD)), was the most likely number of genetic clusters represented in the data . No evidence of correlation between geographic distance and genetic differentiation (isolation by distance) was found . Hierarchical analysis by AMOVA of microsatellite data indicated that the majority of genetic variation was found within swarming sites at the individual level  and very low variation found among provinces . Analyzed separately, adult males and adult females showed similar patterns to all adults together with only 0.11 and 0.08% of the variation found among provincial regions for males and females, respectively, supporting the lack of isolation-by-distance pattern.Low variance in the ln[P(X|r of −0.015 (range: −0.061 to 0.033 per site) within all sites. The mean expected within swarming site pairwise relatedness in 1000 permutations was −0.015, and therefore, the observed mean was not significantly different from simulated values of random groupings of bats (P = 0.532). Relatedness was similarly low for males and females when analyzed separately where no observed mean within swarming sites estimates were significantly different from random expectations after Bonferroni correction . In testing for sex-biased dispersal in FSTAT, we found stronger differentiation for females compared to males  and higher relatedness for females compared to males . However, these differences were not significantly different .Average pairwise relatedness among individuals within swarming sites was low with a mean M. lucifugus in southeastern Canada consistent with high gene flow. We found low global and pairwise FST among swarming sites with only one significant pairwise comparison suggesting that some weak structuring does occur. The significant comparison occurred between site 8 and site 9 where aside from this comparison, most other comparisons involving site 8 had higher estimates of FST. This may reflect that this site was sampled more frequently than all other sites owing to other concurrent studies being conducted there which could have influenced the estimates of allele frequencies at the site. Higher sampling effort could result in the greater detection of rare alleles at this site relative to other sites such that it appears more differentiated. Regardless, the vast majority of pairwise comparisons were not significant suggesting high gene flow. Further support of high genetic connectivity comes from our STRUCTURE results which did not detect any genetic clusters within the data, and from the low estimates of pairwise relatedness among individuals that did not differ from expectations of free mixing of bats among swarming sites . Similar low estimates of relatedness at swarming sites were also found in three species of whiskered bats (genus Myotis) despite the presence of some pairs which may be full siblings . If bats on a given night represent a small proportion of those swarming over the season and these bats are from the same summering colony/area that share common ancestry, this could explain these results.The results from our mitochondrial DNA analyses also showed low levels of genetic structuring and further suggest a recent history of high gene flow in our sampled region. No structuring associated with geography at multiple spatial scales was detected from the hierarchical AMOVA. The median-joining network displayed little structuring of haplotypes by swarming site with many high-frequency haplotypes found at multiple sites and no clustering in any areas of the network by individual sites. In examining the network at the provincial level, there is still little evidence for strong structuring with 6 of the 7 haplogroups containing sequences found in ≥2 provinces with the exception of the singleton found in Nova Scotia. Site 7 stands out as having some of the highest ΦM. nattereri , mating takes place during migration  for M. lucifugus in our study area experienced a population expansion since the last glaciation. This interpretation is supported by several lines of evidence including the starlike topology of the median-joining network, neutrality tests, mismatch distribution, and Bayesian skyline plot analysis. A significant neutrality test can suggest multiple scenarios including a population expansion, genetic “hitchhiking” by an advantageous mutation, or background selection. However, some of these various explanations can potentially be differentiated from each other by comparing different neutrality tests. For example, Fu and Li's F* and D* statistics  in the HV II region was relatively high, and nucleotide diversity (π) was low, a pattern which is consistent with a population expansion. A similar pattern of exceptionally high h and low π was described in the tropical Brazilian free-tailed bat (T. brasiliensis) which is thought to have undergone an expansion within the past 3000 years  where the inferred expansion followed the Younger Dryas period  where large Ne reduces the role of genetic drift. Key factors that influence Ne include population size and patterns of reproductive success  based on large historical hibernating population estimates (Trombulak et al. T. brasiliensis (Russell et al. e, low levels of genetic structure are expected even with low genetic exchange and future work that characterizes this parameter would provide valuable insight into the genetic structuring of M. lucifugus, particularly in light of the large population declines from WNS.Our findings suggest a high degree of genetic connectivity in es Storz . AlthougP. destructans (Lindner et al. M. lucifugus which may reflect movement patterns of bats (Miller-Butterworth et al. The implications of high genetic connectivity in managing populations under the epizootic of WNS remain complicated and largely unknown. High genetic connectivity may imply dispersal, whether permanent or temporary, over extensive spatial scales. As recent work has shown bat-to-bat transmission in a laboratory setting (Lorch et al. M. lucifugus in southeastern Canada. We found no evidence to suggest a strong signature of structure but rather found evidence of a demographic expansion following deglaciation of the region. Although our study suggests dispersal over a large spatial scale in the recent past, predicting how the dynamics of dispersal will contribute to the trajectory of population persistence in the future is not a straightforward process. Since the emergence of WNS, many local hibernating populations have been dramatically reduced in the eastern portion of the range (Frick et al. In summary, our findings suggest high gene flow and therefore high genetic connectivity among swarming sites of


Litoria raniformis) is listed as vulnerable to extinction in Australia, and endangered in the state of Victoria. Remaining populations of this species in and around the city of Melbourne are threatened by habitat loss, degradation and fragmentation due to urban expansion. We used mitochondrial DNA (mtDNA) and microsatellites to study the genetic structure and diversity of L. raniformis across Melbourne's urban fringe, and also screened four nuclear gene regions . The mtDNA and nuclear DNA sequences revealed low levels of genetic diversity throughout remnant populations of L. raniformis. However, one of the four regions studied, Cardinia, exhibited relatively high genetic diversity and several unique haplotypes, suggesting this region should be recognized as a separate Management Unit. We discuss the implications of these results for the conservation of L. raniformis in urbanizing landscapes, particularly the potential risks and benefits of translocation, which remains a contentious management approach for this species.Two pervasive and fundamental impacts of urbanization are the loss and fragmentation of natural habitats. From a genetic perspective, these impacts manifest as reduced genetic diversity and ultimately reduced genetic viability. The growling grass frog ( The impacts of urbanization on biodiversity are numerous , but a pAssessing the genetic origins of populations and effectively managing genetic diversity are central to their persistence in both the short and long term ,10. Gene2 and has a population of approximately 4.25 million people [2 over the next 20 years [The proportion of the world's human population living in urban areas grew rapidly during the twentieth century, from an estimated 220 million to 2.8 billion . Austral20 years . Urban g20 years .Litoria raniformis) in the MMA. This species has declined markedly over the last three decades, yet significant remnant populations persist in the low-altitude, urban-fringe environments to the southwest (Wyndham), northwest (Melton), north (Hume–Whittlesea) and southeast (Cardinia) of Melbourne (L. raniformis across Melbourne. We predict that: (i) genetic diversity of L. raniformis across Melbourne's urban fringe is low due to past declines and more recent habitat loss and fragmentation from urbanization, (ii) a genetic bottleneck may have occurred as a result of these processes, and (iii) genetic structuring is present between remnant populations in Cardinia and the other three regions, due both to the fundamental geographical isolation of this region and to the more recent loss of connecting populations  in southeastern Australia and resulting epidemics of chytridiomycosis were almost certainly a major contributor [wetlands . This spwetlands ; howeverwetlands ,25. Althtributor . Populattributor , but lowtributor , allowintributor –31.L. raniformis around Melbourne are now threatened by the rapid pace of urban expansion. Urbanization has led to wetland loss, degradation and fragmentation in each of the four regions in which significant remnant populations of L. raniformis persist  were collected from remnant populations of L. raniformis in the Wyndham, Melton, Hume–Whittlesea and Cardinia regions (N=270) were collected during the current study between December 2010 and March 2011 across the other three regions. We divided each region into three geographical clusters of sites for the purposes of sampling  included slow-flowing pools along streams, as well as farm dams, swamps and water-treatment ponds. Between 1 and 10 individuals were sampled per site depending on population size and capture success.Tissue samples  between the second and third toes closest to the body on the left hind limb. Toe web samples were stored in 95% ethanol and kept at −18°C for approximately two weeks, then −80°C for up to 3.5 months. Further details on these samples may be found in electronic supplementary material, S1. Latex gloves were worn when taking samples and were changed between individuals. Tissue sampling equipment was also sterilized in 70% ethanol between frogs to prevent the spread of pathogens such as the chytrid fungus.L. raniformis in this region [Samples from Hume–Whittlesea were collected between October 2004 and February 2006 as part of a study on the metapopulation dynamics of s region  (figure s region  for addi2.3N=112) were sequenced for NADH dehydrogenase subunit 4 (ND4) encompassing all COI haplotypes and geographical regions. Each of these gene regions have been shown to be variable in previous studies of L. raniformis [We sequenced the mitochondrial gene COI for all 377 samples and a subset of samples , 1 μM forward primer, 1 μM reverse primer and 6 μl dH2O. We amplified a partial sequence of 495 bp of COI, using the primers Cox (5′-TGATTCTTTGGGCATCCTGAAG-3′) and Coy (5′-GGGGTAGTCAGAATAGCGTCG-3′) [et al. [We performed PCR amplification of the samples from Wyndham, Melton and Cardinia in a 20 μl total volume with 2 μl of DNA template, 10 μl GoTaq Hot Start Polymerase (Promega) (25 mM MgClGTCG-3′) . AmplifiGTCG-3′) ). For CO [et al. .We amplified a partial sequence of 665 bp of ND4 for the subset of 112 samples , using the primers ND4-3 (F) (5′-TTAGCAGGAACACTTCTAAAACTAG-3′) and ND4-1 (R) (5′-GAAAGTGTTTAGCTTTCATCTCTAG-3′) . Amplifi2O in all cases. We routinely included negative controls and checked for contamination. Following successful amplification, we purified PCR products using ExoSAP-IT (USB) following the manufacturer's instructions and sent the purified products to Macrogen (Korea) for sequencing using a 3730XL DNA sequencer (ABI). We BLAST searched all sequences to confirm identity and aligned them using Geneious Pro v. 5.6 [We diluted extracted DNA to a ratio of 1:10 with dHo v. 5.6 . We repe2.4et al. [L. raniformis around Melbourne [′ end of the reverse primer to reduce variation in stutter . See Hale et al. [2, GoTaq Hot Start Polymerase, 5× Colourless GoTaq Flexi Buffer, 5× Green GoTaq Flexi Buffer), 0.5 μM reverse primer, 0.15 μM forward primer, 0.25 μM fluorescently labelled 454A primer and 3.1 μl dH2O. Amplification involved 95°C 2 min, 42 cycles of 95°C 30 s, 50°C 45 s, 72°C 45 s, followed by 72°C 5 min  as described by Hale et al. , in two elbourne . Three me et al.  for methe et al. ). Fragme2.5etwork v. 4.610 [We estimated completeness of haplotype sampling of populations using the Stirling probability distribution and Bayes' theorem . Median-v. 4.610  for COI v. 4.610 .naSP v. 5.10.1 [D), where a large, positive value of D is consistent with a population that has experienced a recent bottleneck [FS), which assesses the number of rare alleles in the population and departures from conditions of neutrality [r), which quantifies the smoothness of the observed mismatch distribution and indicates whether populations are expanding or contracting. A substantial mismatch is characteristic of a population not at equilibrium [We used D. 5.10.1  to detecttleneck , (2) Fu'utrality , and (3)ilibrium . Values icro-Checker (v. 2.2.3) [HE and HO, respectively) were implemented in Genepop v. 4.2 [are v. 1.0, which accounts for differences in sample size [FST between populations was calculated using GenAlEx v. 6.5 [For the microsatellite data, we used M. 2.2.3)  to test p v. 4.2  with defp v. 4.2 . We calcple size . FST betx v. 6.5 .tructure v. 2.3.4 [K) was set to range from 1 to 12 (where 12 is the number of clusters within regions). Simulations were run 10 times for each proposed value of K. We are confident that the chains had converged, as several runs at each K with different run lengths gave consistent parameter values. To determine K, we used Structure Harvester v. 0.6.93 [e Pr(X|K), as well as the rate of change in the log probability of the data between successive K estimates. The value of K with the highest rate of change and the largest mean loge Pr(X|K) was selected [K and weak structure that did not seem biologically applicable .We estimated the number of distinct genetic populations using microsatellites for a subset of 117 samples in the Bayesian population clustering program Sv. 2.3.4 . We usedv. 2.3.4 . We used. 0.6.93 , which pselected ,61. The ottleneck v. 1.2.02 [M-ratio tests calculated in M_P_VAL and Critical_M [ottleneck, we tested for heterozygosity excess, indicative of population size reduction, using a Wilcoxon test applied to a two-phase model, with 78% single step mutations, as recommended by Peery et al. [M-ratio tests were calculated in M_P_VAL, using data formatted in FORMATOMATIC v. 0.8.1 [M-ratio tests are based on the ratio of the number of microsatellite alleles to the range in allele size. During a bottleneck, the number of alleles is expected to decline faster than the range in allele size, so the M-ratio is expected to be smaller in bottlenecked populations [To detect the signature of a past bottleneck from the microsatellite data, we used B. 1.2.02 ,63 and Mitical_M  for eachy et al.  and a vav. 0.8.1 . M-ratioulations .M-ratio method is likely to detect older events than tests based on heterozygosity, because more time is required for the M-statistic to reach equilibrium [θ=4Neμ, where Ne=effective population size and μ=per generation mutation rate), the average size of mutations that are not one-step and the proportion of multi-step mutations. We calculated θ for each population identified by the preceding Structure analysis using Migrate v. 3.6.6 [M were compared with the critical value (MC), calculated in Critical_M, estimated after 10 000 simulations. In all the analyses using microsatellite data, the low number of markers used could have limited the power of our methods to detect a bottleneck. However, methods based on examining mtDNA haplotypes can be more powerful for detecting bottlenecks than microsatellite methods based on genetic structure [The ilibrium . Three pv. 3.6.6 . We emplv. 3.6.6  and 0.22v. 3.6.6 . Values tructure .3.3.1n=x), were high for all regions (more than 0.99), indicating a high likelihood that all haplotypes from each region were sampled. At the finer scale, with regions separated into their component site clusters, there was at least 99% certainty of completeness of sampling for all clusters (Pr(n=x)≥0.99) except the southern-most cluster from the Cardinia region, at which Pr(n=x)=0.75. Overall, there was a high probability that all COI haplotypes were sampled.The posterior probabilities of completeness of haplotype sampling, Pr. In total, there were 26 distinct haplotypes. Seven haplotypes were present in the Wyndham region (three unique to the region), eight in Melton (three unique), seven in Hume–Whittlesea (five unique) and 11 from the Cardinia region (10 unique). The haplotype network derived from the concatenated COI and ND4 gene regions also revealed similar results to those derived from COI alone . In total, there were 33 distinct haplotypes. Eight haplotypes were present in the Wyndham region (three unique to the region), nine in Melton (three unique), 11 in Hume–Whittlesea (eight unique) and 13 from the Cardinia region .Additionally, three nuclear gene regions were aligned, using a subset of the 19 most variable COI samples. The fourth nuclear gene region, CRYBA1, failed to successfully amplify. Rhod and RAG-1 showed no variation between samples. POMC showed variation for eight individuals; however, this variation was not parsimoniously informative, as it occurred at heterozygous sites . Due to the lack of diversity, there was no scope for further population-level analyses with the nuclear DNA.3.2K=34.740 for K=2 and ΔK=0.024–1.145 for K=3–11). Population I contained all samples collected from the Wyndham, Melton and Hume–Whittlesea regions, while Population II contained all samples collected from the Cardinia region in the southeast (p=0.025–0.045 following FDR correction for multiple comparisons). Overall, each locus generally conformed to HWE across both populations (Ho=0.586 for Lr9 and Population II Ho=0.367 for Lr6). We observed significant homozygote excess, suggesting the presence of null alleles in Population II for Lr6; however, we chose to retain all loci for subsequent analyses, given there was no evidence of null alleles in Population I or when analysing the data as one population. Population I had 18 alleles, with an allelic richness of 2.33. Population II had 18 alleles, and an allelic richness of 2.43. Pairwise FST between the two genetic populations was low (0.004) and not statistically significant (p=0.176).The Structure analysis using geographical region as prior information revealed two clear genetic units . A one-tailed Wilcoxon's test for heterozygosity excess in Bottleneck found Population I displayed evidence of a recent genetic bottleneck (p=0.031); however, this did not remain statistically significant following FDR correction for multiple comparisons (p=0.063). Similarly, the M-ratio tests on microsatellite loci did not detect evidence of a bottleneck in either of the populations. Using θ=3.1 (Population I) and θ=0.967 (Population II), the average M-ratio values were 0.817–0.888 and were higher than the M-critical values, of 0.695–0.697.There was only weak evidence for a genetic bottleneck based on mtDNA data for COI . The rag4.L. raniformis around Melbourne, Australia's fastest growing city. We predicted that: (i) genetic diversity of these populations would be low due to past declines and more recent habitat loss and fragmentation, (ii) genetic bottlenecks would be evident, and (iii) genetic structuring would be present between remnant populations in Cardinia and the other three regions studied.This study sought to assess the genetic structure and diversity of remnant populations of 4.1L. raniformis around Melbourne, supporting our first hypothesis. Additionally, a large proportion of individuals included in our study shared one haplotype (haplotype 1), with few mutations between all the haplotypes present. In comparison, a study that looked at COI sequences across 34 amphibian species, from six families and 11 genera, reported an average nucleotide diversity of 0.203 which is considerably higher than the population-level diversity found in our study , the sister species to L. raniformis, that covered approximately 1000 km, expected heterozygosity levels were reported as high  when compared to other amphibian species [L. raniformis metapopulations in one of our study regions, Hume–Whittlesea. Using data from 11 microsatellite markers, the signature of a recent bottleneck was found at one site. This population was separated from nearby sites by a four-lane highway, which appeared to significantly reduce gene flow. Hale et al. [L. raniformis due to bottlenecks.Measures of genetic diversity within populations such as allelic richness, haplotype diversity, heterozygosity values and polymorphism have been found to be lower in amphibians in urban areas than in non-urban environments ,71–75. I species . A previ species  examinede et al.  suggesteL. raniformis studied here, due to both past population declines (resulting from chytridiomycosis in particular) and more recent habitat loss and fragmentation due to urbanization. However, the data did not support this hypothesis, with both mtDNA and nuclear microsatellite loci analyses failing to detect the signature of a bottleneck. For the microsatellite data, we assessed levels of heterozygosity excess, indicative of population size reduction. However, while commonly used, this method is strongly influenced by the more common alleles [We hypothesized that genetic bottlenecks would be evident in the populations of  alleles , which m alleles , statist alleles ,65 the m alleles . Indeed,L. aurea similarly found no signature of a bottleneck [L. raniformis around Melbourne is due to factors other than recent bottlenecks. In the first instance, it may be that remnant populations of this species around Melbourne may not have suffered the drastic reductions in abundance necessary to produce a bottleneck signature [L. raniformis displays metapopulation dynamics, with occupancy, mark–recapture and genetic data confirming that migration over distances of 1–2 km is crucial to the viability of population networks [L. raniformis around Melbourne, including more detailed microsatellite analyses.One or more of these factors may have influenced our ability to detect a population bottleneck in our study species. However, dramatic declines in the sister species ttleneck . It seemignature . Secondlignature . Previounetworks ,34,35. GGenetic structuring was present between remnant populations in Cardinia and the other three regions, due to both the historical and more recent isolation of this region, supporting our third hypothesis. This was demonstrated by both the mtDNA and microsatellite analyses. Of the four main regions in the study, Cardinia exhibited the highest level of genetic diversity and all haplotypes present there were unique to the region. Additionally, the microsatellite analyses revealed Cardinia should be considered a distinct genetic unit from the other regions.4.2L. raniformis from Cardinia in southeastern Melbourne are genetically distinct from the west and north of Melbourne, due to the presence of unique haplotypes and higher genetic diversity. Under Moritz's [Our study indicates populations of Moritz's  definitiMoritz's . Based oL. raniformis within the urban growth areas into two categories: (1) high-quality habitat that will be protected and managed for the species and (2) habitat of lower conservation significance that can be destroyed for urban development, but for which compensatory habitat is required [L. raniformis in Melbourne's urban growth areas [L. raniformis can be successfully relocated [L. aurea have failed or the focal populations are performing poorly [L. aurea being the subject of more translocation attempts than any other Australian frog [The Victorian Government has classified suitable habitat for required . Transloth areas . Individth areas . Under tth areas . There ielocated . Indeed,g poorly , despiteian frog .L. raniformis, it is important that the geographical location of specimens is considered. This will help to maintain the genetic integrity and evolutionary potential of the species around Melbourne, two key objectives of Victoria's Flora and Fauna Guarantee Act 1988. This appears most important in the southeast Cardinia region, to maintain the levels of genetic diversity and the unique haplotypes found in the region. We caution that we only analysed neutral genetic diversity here, when in fact levels of genetic variability inferred from neutral markers are often poor correlates of quantitative variation for adaptively important traits [L. raniformis across Melbourne's urban fringe, using mtDNA and microsatellite markers, we are able to forewarn managers of the low genetic diversity displayed by remnant populations, identify genetic MUs and regional centres of haplotype endemism.If future captive breeding programmes are required or translocations are attempted for t traits . Neverth


Otis tarda) living in Austria-Slovakia-West Hungary (West-Pannonian region), one of the few populations of this globally threatened species that survives across the Palaearctic, has been assessed for the first time in this study. Fourteen recently developed microsatellite loci identified one single population in the study area, with high values of genetic diversity and gene flow between two different genetic subunits. One of these subunits (Heideboden) was recognized as a priority for conservation, as it could be crucial to maintain connectivity with the central Hungarian population and thus contribute to keeping contemporary genetic diversity. Current conservation efforts have been successful in saving this threatened population from extinction two decades ago, and should continue to guarantee its future survival.The genetic diversity, population structure and gene flow of the Great Bustards ( Otis tarda, Linnaeus 1758) is a globally endangered species, classified as vulnerable in the Red List of Threatened Species . However, both populations survived and have even slightly increased in numbers, reaching nowadays 197 birds in Germany and 505 birds in the West-Pannonian population (February 2015 in both cases), thanks to continued and intensive conservation efforts, centered on habitat management programs in both countries plus captive breeding in Germany . Specifically for the study population in the West-Pannonian region, conservation efforts since 2001 have centered on implementing large-scale agri-environmental measures funded through Austrian and Hungarian Agri-environmental Scheme for Great Bustard and Austrian, Hungarian and Slovakian Great Bustard LIFE, LEADER, INTERREG and Rural Development projects to (1) improve the quality of the habitat, (2) increase the species’ reproductive success  population of Great Bustards, using fourteen recently developed microsatellite loci . The resDuring the 2012 and 2013 breeding seasons (between early April and early September), Great Bustard moulted feathers were searched as DNA source in all areas previously known to be used by the species in Austria. In Austria, the authors had verbal permission from hunters to collect feathers in their properties. No other official permit is needed in this country to collect feathers. As for Hungary, the authors had a permit to collect gene samples issued for the Hungarian LIFE project (LIFE04 NAT/HU/000109), in which the Hungarian Ministry of Environment and Water was a co-financier and the regional competent Fertő–Hanság National Park Directorate was a partner. Single or small groups of feathers were found at 80 sites, covering the three most important breeding areas in Austria: Weinviertel, Marchfeld and Heideboden . To minihttp://genepop.curtin.edu.au). Deviations from Hardy–Weinberg equilibrium after Bonferroni correction (HWE), the number of alleles per locus (Na), the expected and observed heterozygosities averaged across loci , the inbreeding coefficient (FIS) and the Fixation Indexes (FST) and their associated P-values, were calculated with GenoDive 2.0b25 .Microchecker was employed to search for null alleles, scoring errors and large allele dropout . Linkagee 2.0b25 . Allele e 2.0b25 . Allelice 2.0b25 . The pree 2.0b25 , with thK) from 1 to 3. Ten independent runs were performed for each K. We run two sets of STRUCTURE analyses: one without using sample location as prior, one using sample location as prior (LocPrior option). To determine the number of genetic clusters (K), we used the DK method of X|K) as implemented by the program Structure Harvester v.0.6.94 . Settings: admixture of individuals based on mixture clustering after clustering of groups of individuals; 1,000 iterations used to estimate the admixture coefficients for the individuals; 200 reference individuals from each population (as recommended by the software developers); 10 genetically diverged maximum groups used to estimate the admixture coefficients for the reference individuals. The third approach was a discriminant analysis of principal components (DAPC), a multivariate method implemented in the adegenet package (v. 1.3-1) for the R software ; after that, DAPC was employed to assign individuals into populations, retaining the n/3 number of principal components  with 80% of the cumulative deviance ; and (2) without searching and optimal K: each individual was a priori assigned to its location of origin, obtaining for each individual the probability of assignment to their populations of samplings. Lastly, Oncor (Ne) of the genetic estimated units were calculated with LDNe v.1.31 software  simulation implemented in STRUCTURE 2.3.4  were usev.0.6.94 . The secv.0.6.94 , which gsoftware  that idey, Oncor  Leave-Onsoftware  employinNm) among breeding areas were estimated by the mean frequency of private alleles with the above-mentioned Genepop software.Contemporary gene flow among populations was studied under the assignment test criterion of Two of the fourteen available microsatellite loci were discarded from analyses for different reasons: the Ot3 locus did not amplify (probably due to mutation(s) in the primer(s) area(s)) and the Ot6 locus was monomorphic in the dataset. Within the other twelve loci, amplification success was 87.4% and Microchecker discarded the presence of scoring errors, large allele dropout and null alleles in the dataset. The Identity Analysis showed two individuals with the same genotype in the Weinviertel breeding area, one of which was deleted in order to avoid resampling. The genetic variability ; Fig. 2 K = 1) in the whole dataset. Even forcing K = 2 or 3, results did not show differences among breeding areas, they only showed mixed genotypes across all the three sampling points. Despite this, BAPS analyses showed the presence of two genetic subunits  yielded higher assignment values: 95.8% of correct individual assignment for the genetic subunit composed by Weinviertel and Marchfeld, and 85.7% of correct individual assignment for the other genetic subunit (Heideboden). In addition to this, and in accordance with BAPS and Oncor results, FSTP-values were not significant between Weinviertel and Marchfeld and highly significant  between Heideboden and the other two breeding areas (Ne) were estimated for the two mentioned genetic subunits, resulting in 30.3 individuals (95% CI [18.4–58.1]) for the subunit composed by Weinviertel and Marchfeld and 57.1 individuals (95% CI [28.5–247.9]) for the other subunit (Heideboden).According to Structure Harvester, Structure results (with and without LocPrior option) did not reveal a clear population structure across the study area, showing a unique genetic unit . The number of migrants per generation , being higher between Heideboden and the other two breeding areas (Weinviertel and Marchfeld) than between the two latter. The Nm value between Heideboden and the genetic subunit including Weinviertel and Marchfeld individuals was 3.62, the highest of all estimated Nm values.According to the assignment tests on recent gene flow, 66.3% of the individuals were residents in the breeding area where they had been sampled when comparing the three sampling sites, and 81.6% when comparing the two genetic subunits  in spite of a strong decrease in numbers of individuals suffered in the past decades, with a slightly smaller number of alleles per locus but higher allelic richness than the world’s largest populations of this species  were also in accordance with those found for the species in other areas . These hypothesised movements could be confirmed through marking individuals. Therefore, within the conservation and management plan for the future, all extant breeding groups should be protected, but paying special attention to the Heideboden subunit, since due to its proximity to central Hungarian populations it could be crucial. This subunit should be therefore a priority for the conservation of other West-Pannonian Great Bustard breeding groups, and to guarantee their connection to the main Hungarian populations further east.In addition to this, the whole West Pannonian population is not far from other Hungarian breeding groups, from which considering again the dispersal capacity of the species , dispersSumming up, our study is the first description of the genetic diversity and gene flow of the West-Pannonian population of Great Bustards based on analysis of microsatellite loci. This is one of the few populations that survived the sharp decreases that decimated this globally endangered species during the last century in central Europe. Our results identified one population in the study area, formed by two genetic subunits with high migration rates among them. The current genetic variability is high. Conservation efforts should be directed not only to preserve all extant breeding groups, but also the connectivity among them and with central Hungarian populations, in order to keep the genetic diversity of West-Pannonian Great Bustards at a high level. Current management and protection actions should therefore be maintained in the study area in order to guarantee the survival of this Great Bustard population.10.7717/peerj.1759/supp-1Supplemental Information 1Bustards’ microsatellite genotypes in Genepop format.Click here for additional data file.


Cerotoma trifurcata(Forster) (Coleoptera: Chrysomelidae), is a common pest of soybean in the Midwest United States. However, there are currently no reports on the genetic variability ofC. trifurcata. This study examined 15–30 individuals from 25 sample locations to estimate genetic variability and gene flow within and amongC. trifurcatafrom across the Mid- west. Amplified fragment length polymorphism generated 175 markers for analyses. Results from analysis of molecular variance (AMOVA) indicated that the majority of genetic variation was from within samples; only a small amount of the total variation was attributed to the variation among the samples. The GST for the entireC. trifurcatapopulation indicated that the majority of genetic variation was found within the samples, further supporting the AMOVA results. The estimated average gene flow among theC. trifurcatasamples was 1.83. The Mantel test revealed no indication of correlation between geographical and genetic distance for all theC. trifurcatasamples. These findings show thatC. trifurcatain the Midwest are genetically heterogeneous and part of a large, interbreeding population.Bean leaf beetle, Cerotoma trifurcata(Forster) (Coleoptera: Chrysomelidae), is a pest of leguminous crops, especially soybean, in the United States.Cerotoma trifurcataadults directly damage the soybeans by feeding on the leaves, stems, and pods  is a widely used, powerful technique for DNA profiling mostly used in assessing diversity within and among organisms that have varying genomic structures. Although AFLP produces dominant markers, it can be used to detect molecular genetic variations in DNA of any source or complexity without prior sequence knowledge  along two transects in the Midwest United States. A totaep nets . Two peep nets . The Eaep nets . All otep nets . The nuC. trifurcataadults using a hexadecyltrimethylammoniumbromide  extraction protocol as modified byDNA was extracted from the thorax ofwww.thermoscientific.com). The Nanodrop spectrophotometer provides both the quality and quantity measurements based on the 280/260 ratio readings. However, this does not show fully the DNA quality, that is, if it is degraded or not. So, a 1% agarose gel with a λ DNA marker (22.2 ng/µL) was run at 60 volts for 20 min to further quantify the DNA. The agarose gels were visualized under the UV light using Genomic Solution software . After quantification, the DNA samples were diluted to 23 ng/µL concentration by adding 1 X TE buffer. These diluted DNA samples were then kept at -20°C until they were used, after which the samples were kept at -80°C as vouchers.Each DNA sample was quantified by using both a 1% agarose gel and Nanodrop spectrophotometer (ND 1000 V3.5.1)  DNA template preparation; 2) DNA template preamplification; and 3) selective amplification of the pre-amplified product. The DNA extracts were digested with EcoR1 and Mse1 restriction enzymes and ligated with specific adapters (www.licor.com) were used in this study to determine the genetic variability within and between theC. trifurcatasamples . The visibility, sharpness, and repeatability of the bands were guiding criteria in marker selection for scoring. Profiles from multiple individuals were aligned and scored based on the presence (1) or absence (0) of a band on the AFLP gel, producing a binary data matrix.C. trifurcata. Genetic differentiation between samples was assessed using Nei’s gene diversity index (GST) in POPGENE; gene flow was estimated from GST, expressed as (Nm) = 0.5 (1- GST)/GST , the Mantel test, and gene flow. Fall armyworm larvae,Spodoptera frugiperda(J.E. Smith) (Lepidoptera: Noctuidae) were used as the outlier group to test the robustness of the analytical tool in the POPGENE analysis.DBOOD  was useST)/GST . West  at a particular locus to the number of the replicated individuals . Loci wA total of 175 loci ranging in size from 50 to 400 bp were observed using the three primer combinations . About The number of loci that were polymorphic for all the samples examined ranged between 124 and 168, with an average of 143 loci. The average loci polymorphism was 82% and ranged from 70.86% to 96% for Ames (Iowa) and Concord (Nebraska), respectively .P= 0.181); the regression supported this finding . Similarly, results from the eastern Midwest (Illinois/Ohio) also showed no significant dependency of genetic distance on geographic distance . Therefore, these samples (2003 and 2008) were used as part of the overall analyses.The total genetic diversity (HT), when comparing the 2008 and 2010 Nebraska samples, was 0.400, 0.410, 0.440, and 0.296 for Lincoln, Mead, Concord, and Clay Center, respectively. The proportion of total diversity among these samples (GST) was 0.136, 0.124, 0.089, and 0.032 for Lincoln, Mead, Concord, and Clay Center, respectively. Gene flow (Nm) for Lincoln, Mead, Concord, and Clay Center were 3.189, 3.527, 5.109, and 5.250, respectively, which indicates a high gene flow between the 2008 and 2010 samples. The total genetic diversity of the East samples taken in 2003 and 2010 was 0.385. The proportion of total diversity among samples was 0.175, and gene flow was found to be 2.362 for East samples. Mantel tests revealed no correlation between genetic and geographic distance for the western Midwest (Nebraska) region samples  was high. This indicates that the overall heterozygosity of theC. trifurcatapopulation is higher than that seen in individual samples. Analysis of multiple locations in POPGENE  (The average heterozygosity (HS) for individual samples was 0.335; the highest HS (0.425) was recorded at Concord, NE, and the lowest (0.229) was recorded at Lewis, IA . The av (1.83) .P= 0.180) in theC. trifurcatasamples. This implied that there was no structure in the genetic variation among the samples in relation to either an increase or decrease in geographical distance. The majority of the dissimilarity matrixes had values between 0.1 and 0.25  from the total variation was from withinriation . The ges study . Moreovnalysis .The reproducibility of the results by the three primer pairs, tested on 24 samples randomly selected from various samples, indicated that the AFLP approach was accurate and reliable. The average error rate found in this study was 5.85% . The maC. trifurcata, is difficult to directly observe. The introduction of and advances in molecular biology provide a platform to explore this area by using genetic markers to provide the information needed to infer gene flow and migration tendencies of individuals among different sample locations. Analysis ofC. trifurcatagenetic structure is a key aspect to understand its population dynamics in agricultural scenarios. The development of effective pest management strategies relies on a multidisciplinary approach, and one component of this is knowledge of the population genetic structure of this pest. The formulation of pest management strategies depends on information such as population size, the factors affecting it, and even on the level of interaction among individuals from different locations, which all can influence the scale at which control practices should be implemented. This latter aspect can be addressed by an analysis and understanding of population genetic structure. The presence of geographic races or biotypes between or within geographic samples may indicate that different control approaches will be required  and East (Illinois/Ohio) relative to year of sampling. There was also high gene flow (Nm) between the 2008 and 2010 samples for Nebraska as well as for the 2003 and 2010 Illinois/OhioC. trifurcatasamples. This relatively low GST and high Nm strongly supports that the majority of genetic variation is found withinC. trifurcatasamples rather than between years, prompting our decision to analyze all data together. Temporal population variation analyses provide a way of measuring realtime migration regardless of population history and identifying individuals in a sample as probable immigrants  quality and availability (C. trifurcatafrom an early-planted soybean area until the first generation was produced. Therefore, the majority of migration by these beetles is likely to occur after the first generation. A proportion of the population is capable of having seasonal migratory flights that spread the population when their original location gets negatively affected by adverse environmental conditions (The understanding of molecular data and the genetic principles can enhance the knowledge about insect origin, their diversity, and determination of their capabilities to reproduce in particular environments and communities. The study of insect genetic composition can also define a species in terms of their distinctive- ness, their relatedness, and their phylogenetic position. The lack of genetic differentiation observed in this study can, at least in part, be due to the expansion of soybean acreage, which provides continuous habitat and food resources forability . The beability ; this iditions . By so C. trifurcatahaving short duration, unsustainable flights that only cover short distances (C. trifurcatasamples, especially their genetic structure. It is possible that this increase in food source may lead to the reduction in natural movements ofC. trifurcatasearching for soybean host plants, hence the increase in the residency time in a location and thus creating a possibility of higher genetic differentiation.There have been reports ofstances . HoweveC. trifurcatamolecular genetics. Based on these findings, it is concluded that there is no substantial genetic difference among theC. trifurcatasample locations in the Midwest, US. The findings of genetic variability ofC. trifurcatasupport the conclusion that in the Midwest, this insect is genetically heterogeneous and part of a large, interbreeding population. Future research should extend the geographic range of samples to include other states outside the Midwest and even include samples from Canada. This will create a better understanding of this insect, which is growing in importance as an agricultural pest.This is one of the first studies on the


Depiction of the genetic diversity, linkage disequilibrium (LD) and population structure is essential for the efficient organization and exploitation of genetic resources. The objectives of this study were to (i) to evaluate the genetic diversity and to detect the patterns of LD, (ii) to estimate the levels of population structure and (iii) to identify a ‘core collection’ suitable for association genetic studies in sweet cherry.Prunus species. A ‘core collection’ containing 156 accessions was selected using the maximum length sub tree method.A total of 210 genotypes including modern cultivars and landraces from 16 countries were genotyped using the RosBREED cherry 6 K SNP array v1. Two groups, mainly bred cultivars and landraces, respectively, were first detected using STRUCTURE software and confirmed by Principal Coordinate Analysis (PCoA). Further analyses identified nine subgroups using STRUCTURE and Discriminant Analysis of Principal Components (DAPC). Several sub-groups correspond to different eco-geographic regions of landraces distribution. Linkage disequilibrium was evaluated showing lower values than in peach, the reference The present study constitutes the first population genetics analysis in cultivated sweet cherry using a medium-density SNP (single nucleotide polymorphism) marker array. We provided estimations of linkage disequilibrium, genetic structure and the definition of a first INRA’s Sweet Cherry core collection useful for breeding programs, germplasm management and association genetics studies.The online version of this article (doi:10.1186/s12870-016-0712-9) contains supplementary material, which is available to authorized users. Prunus avium L. is an economically important temperate species exploited as timber, fruit or rootstock. In Europe, sweet cherry, the cultivated form of P. avium, is grown in large areas. Cherries are very appreciated not only for their taste and flavor but because they are the first stone fruits in the markets after the winter. In 2013, Western Europe sweet cherry production represented the 4th one in the world  according to FAO data (www.fao.org).Prunus avium originated likely in an area between the Black and the Caspian Seas [Prunus avium area of origin but the hypothesis of several different domestication events from different wild populations cannot be discarded [ian Seas , 2. Stonian Seas  suggesteian Seas . Sweet ciscarded . First ciscarded , sweet ciscarded , 7. As aiscarded . These fiscarded  before biscarded , 10.Prunus database). On the contrary, a narrow genetic bottleneck is found in modern cultivars [Although many landraces have been lost, a large diversity still exists in Europe (i.e.: 900 cherry landraces are reported in the European ultivars . Landracultivars –13. Moreultivars ).Drosophila suzukii). Hence, exploring cherry genetic diversity is crucial in order to create new cultivars well adapted to these challenges. Ex situ genetic resources collections remain valuable reservoirs of allelic variability for many traits not yet exploited in current breeding programs. Cherry collections characterization is therefore a major step to facilitate the increased utilization of cherry genetic resources and encourage the sharing of conservation responsibilities between countries in Europe. INRA is the leader of the Prunus genetic resources French national network and it manages large cherry collections including the French National Sweet Cherry collection. The preservation, evaluation and management of large ex situ germplasm collections are expensive and time consuming [In Europe, cherry producers face nowadays new challenges such as sustainable production of high quality fruits, climate change or invasion of new pathogens , near Bordeaux (France). A total of 210 accessions were studied, 50 % of them are of French origin, and belong for a large part to the French National Sweet Cherry Genetic Resources Collection. The rest of the accessions are of 15 other countries of America, Asia and Europe, with a total number of accessions per country ranging from one to twenty  and bred cultivars. Bred cultivars (n = 111) result from selections made quite early (n = 27) and from modern breeding (n = 84). This classification was mainly based either on information coming from literature or, for the French National Sweet Cherry collection, on information gathered in collaboration with the ‘Centre National de Pomologie’ at Alès  . Six Spanish landraces and one Hungarian modern variety, not included in the INRA’s Prunus Genetic Resources Center, were included in the study and were provided by PhD Angel Fernandez i Marti  according to the manufacturer’s instructions. Genomic DNA was quantified using spectrophotometry Nanoview  and fluorimetry Quant-iT™ Picogreen® (Invitrogen) according to the manufacturer’s instructions. Fifteen μl of DNA with a concentration between 50 ng/μl – 75 ng/μl were used for subsequent analyses.www.ncbi.nlm.nih.gov/projects/SNP [www.rosaceae.org [www.rosaceae.org [All accessions were genotyped using the RosBREED cherry 6 K Illumina Infinium II® SNP array v1 . Genotypects/SNP  and eachceae.org ). Physicceae.org were infeceae.org  and the ceae.org . SNP posceae.org ) , or MAF lower than 0.05, were discarded from further analysis.The Hardy Weinberg equilibrium (HWE) and the minor allele frequency (MAF) were calculated for each SNP using PLINK . The SNPo), the expected heterozygosity (He) and the inbreeding coefficient (FIS) were calculated on landraces and bred cultivars using adegenet 2.0 R package [The average number of alleles, the observed heterozygosity  using BOTTLENECK v1.2.02 program . A Sign 2 threshold was 0.5. Pairwise LD measures for multiple SNPs were calculated using PLINK [Because LD can affect both Principal Coordinate Analysis (PCoA) and STRUCTURE analysis, the marker set was pruned by excluding SNPs in strong LD using PLINK software . SNPs weng PLINK .2 as estimated from haplotype frequencies, although it will typically be very similar. Because it is faster to calculate, it provides a good way to screen for strong LD [2 data [2 summarizes both recombinational and mutational history [Correlations based on genotype allele counts, i.e. not phased genotypic data, were used to estimate the LD using PLINK . The squtrong LD . Total l [2 data  using R  [2 data . r2 summ history .PCoA , Bayesian-based (STRUCTURE software ) and DisPCoA is a distance-based model which uses jointly a dissimilarity matrix calculated with a simple-matching index, and a factorial analysis. PCoA was performed using DARwin 6.0.010 software  , 40. Thist [The model-based approach implemented in the software package STRUCTURE  was alsost  among thThe assumptions underlying the population genetics model in STRUCTURE may limit its use in crops. Unlike natural populations, crops are subjected to displacements, breeding, clonal propagation, absence of panmictic conditions. Thus, we complemented the STRUCTURE analysis with the DAPC. The absence of any assumption about the underlying population genetics model, in particular concerning Hardy-Weinberg equilibrium or linkage equilibrium, is one of the main assets of DAPC analysis . DAPC wast [The number of PCs retained can have a substantial impact on the results of the analysis. Indeed, retaining too many components with respect to the number of individuals can lead to over-fitting and instability . We usedst  among thCore collections are subsamples of larger genetic resources collections which are created in order to include a minimum number of accessions representing the maximum diversity of the original collection. DARwin 6.0.010’s function ‘maximum length sub tree’ has been used to select a reference set in chickpea , cowpea https://www.rosaceae.org/ and at INRA’s GnpIS repositories {Steinbach, 2013 #3425}.The genotyping data set supporting the results of this article are available at n = 40 SNPs) or Minor Allele Frequency (MAF) (n = 3269 SNPs) lower than 5 % were discarded for further analysis using PLINK [n = 2785 SNP) were deleted in the MAF step. A total of 1215 SNP markers were retained after these filtering steps (Table The genotyping of 210 landraces and cultivars with the RosBREED Cherry 6 K SNP array generated genotyping data points (Table ng PLINK . Homozygn = 27), as compared to the modern breeding sample (n = 84).The average number of alleles in both early and modern cultivars combined (bred cultivars) was the same than in landraces, whereas the number of alleles was lower in early selections than in modern breeding cultivars Table . This coGenetic diversity parameters showed higher diversity in landraces compared to bred cultivars. However, no significant differences in observed or expected heterozygosity were found between modern and early selected cultivars. Further, inbreeding was lower for landraces compared to bred cultivars (both early and modern), whereas no differences were found between early and modern cultivars Table .eq) under the two-phase mutation (TPM) model [P < 0.01) heterozygosity excess under the model as an indication of recent demographic contraction.To verify whether the landraces, early and modern bred cultivars have experienced a population reduction in size, we detected excess heterozygosity in a population at mutation-drift equilibrium (HM) model  by usingP. avium trees using 1215 non LD-pruned SNP markers  showed mixed ancestry . In the admixed cluster, landraces and early selected or modern bred accessions are equally represented. The majority (n = 12) of the 18 Italian accessions  of the INRA’s collection showed mixed ancestry, among them only ‘Adriana’ has a membership value lower than 50 % in the bred cluster. Nearly 53 % of the French bred cultivars are admixed, 62 % of them being selections from the INRA’s sweet cherry breeding program: ‘Ferbolus’, ‘Fernier’, ‘Fercer’, ‘Ferprime’ and ‘Folfer’, showing more than 50 % of membership in the bred cluster. Results obtained with STRUCTURE were confirmed by the representation of PCoA analysis based on genetic distance matrix using DARwin 6.0.010 software [st values among STRUCTURE clusters ranged from 0.022 (Admixed-Bred cultivars) to 0.058 (Landraces-Bred cultivars) n = 88, erity n = 2 of the As the Evanno ∆K preferentially detects the uppermost level of structure of the data , we analConcerning the landraces group, the Evanno criterion gives a strong signal for K = 2 and a weaker for K = 4  to 0.142 (Cluster 2-Cluster 9)  tree based on the dissimilarity matrix between 210 accessions of the INRA’s Sweet Cherry Collection was initially built to assess the genetic distribution of markers. Groups of NJ tree were, in general, in agreement with STRUCTURE (K = 2) Fig.  and DAPCDARwin 6.0.010 function maximum length sub tree method was iteratively used to eliminate the most redundant accessions until the percentage of sphericity index and pruned edge came to a flat line, corresponding to 156 accessions  between landraces and selected cultivars are in agreement with the loss of diversity associated to breeding. A higher impact of breeding compared to domestication was shown for sweet cherry [Significant differences for Ht cherry . HoweverThe excess of heterozygosity found for sweet cherry can also be related to a genetic bottleneck, as found by the BOTTLENECK software. These results are in agreement with previous bottleneck events suggested in sweet cherry , 11. WheWhen LD declines rapidly with distance, LD mapping is potentially very precise . LD decaLD decays rapidly in a gene by recombination after selection for a particular allele , the timr2 values > 0.8 was found  used to analyze the structure of the INRA’s Sweet Cherry collection appeared to provide complementary information. STRUCTURE performed well in detecting global clusters of diversity and results were confirmed by PCoA. Nevertheless, the two parameters used to choose the most likely number of clusters in STRUCTURE did not give the same value for K. Evanno ΔK method gave K = 2 in the whole analysis as well as in the investigation of cryptic structure. The Evanno method finds the uppermost level of structure in the data, as it focuses exclusively on the change in slope. According to some authors this may cause ΔK to be artificially maximal at K = 2 in some cases . NeverthThe DAPC method provides an interesting alternative to STRUCTURE software as it does not require that populations are in HW equilibrium and can handle large sets of data without using parallel processing software. However, as for other multivariate analyses, the reduction of genetic information to interindividual or interpopulation distances may represent a substantial loss of information . Neverthk-means, as k-means provides optimal groups for DAPC and therefore both classifications will be mostly consistent [Regarding membership to clusters, DAPC provides membership values that are different from admixture coefficients from STRUCTURE, but they can still be interpreted as proximities of individuals to the different clusters . Howevernsistent .st value found in our study among clusters four and six . This is especially clear for the INRA’s cultivars released in the last two decades, as most of them (more than 60 %) are included in cluster four. Hence, the use of landraces different from the clusters four, five or six, as founding clones, would increase the genetic diversity of new cultivars. Also, most North American cultivars (USA and Canada) are included in two close clusters (four and six). This is in agreement with the repeated use of five founding clones and one genetic source for self-compatibility in sweet cherry breeding in North America  and withCharacterization and maintenance of germplasm collections is a laborious task. Genetic and phenotypic knowledge is crucial for a better understanding and utilization of the available genetic resources by breeders . In thisSome putative synonymous cultivars were probably renamed when released in the same region but at different periods of time. For example, ‘Bigarreau Jaboulay’ and ‘Guigne Ramon Oliva’ were released in Southeastern France in 1822 in 1900, respectively. Other possibilities could be that those cultivars were released in different regions or countries, or even commercialized with different names. Thus, ‘Lazar’, described as “a seedling of unknown parentage probably a selection from ‘Burlat’”  was identified in this study as a putative synonym of ‘Burlat’.In other context, the cluster of putative synonyms identified in this study: ‘Badacsony’, ‘Belge’ ‘Ferrovia’, ‘Gégé’, ‘Noire de Meched’, and ‘Stark Lambert’; is in accordance with previous fingerprinting analysis using AFLP and SSR markers . HoweverThe diversity of INRA’s Sweet Cherry core collection could be maximized by introducing exotic plant material underrepresented so far, such as landraces and wild cherries. For example, the Spanish landraces ‘Punxeta’ and ‘Tarrega’ are two good candidates to be included in the INRA’s Sweet Cherry Collection. In additionINRA’s Sweet Cherry core collection represent a valuable tool for the development of genome-scale analysis aimed at deciphering the genetic determinism of traits for this species.In the present study, we show the first population-genetics analysis in cultivated sweet cherry using a medium-density SNP marker array. We provide estimations of linkage disequilibrium, genetic structure using different approaches and the definition of a first INRA’s Sweet Cherry core collection. This information will be useful for parent selection in breeding programs, germplasm management and association genetics studies. Thanks to the perennial nature of sweet cherry and the ease of vegetative propagation, this core collection could be easily disseminated worldwide for further analyses.