Exocoetus volitans, a species of two-winged flyingfish, is a good model for understanding large-scale patterns of epipelagic fish population structure because it has a circumtropical geographic range and completes its entire life cycle in the epipelagic zone. Buoyant pelagic eggs should dictate high local dispersal capacity in this species, although a brief larval phase, small body size, and short lifespan may limit the dispersal of individuals over large spatial scales. Based on these biological features, we hypothesized that E. volitans would exhibit statistically and biologically significant population structure defined by recognized oceanographic barriers. We tested this hypothesis by analyzing cytochrome b mtDNA sequence data (1106 bps) from specimens collected in the Pacific, Atlantic and Indian oceans (n = 266). AMOVA, Bayesian, and coalescent analytical approaches were used to assess and interpret population-level genetic variability. A parsimony-based haplotype network did not reveal population subdivision among ocean basins, but AMOVA revealed limited, statistically significant population structure between the Pacific and Atlantic Oceans . A spatially-unbiased Bayesian approach identified two circumtropical population clusters north and south of the Equator , a previously unknown dispersal barrier for an epipelagic fish. Bayesian demographic modeling suggested the effective population size of this species increased by at least an order of magnitude ~150,000 years ago, to more than 1 billion individuals currently. Thus, high levels of genetic similarity observed in E. volitans can be explained by high rates of gene flow, a dramatic and recent population expansion, as well as extensive and consistent dispersal throughout the geographic range of the species.Delineating populations of pantropical marine fish is a difficult process, due to widespread geographic ranges and complex life history traits in most species.  Recent and rapid losses of global marine biodiversity make the genetic characterizations of marine organisms, and populations, a high priority . In gene2; ). This i2; .Exocoetus volitans, (family Exocoetidae), may be particularly useful for resolving these questions.Because epipelagic habitats (surface waters of the open ocean) are among the most vulnerable to increasing sea surface temperatures and global climate change, it is imperative that we understand the population-level genetic diversity of open ocean inhabitants. Spatial patterns of genetic variation have been reviewed for populations of epipelagic and circumtropical fishes . A numbeE. volitans can leap from the water and glide through the air using enlarged pectoral fins, allowing evasion of epipelagic predators. Despite an exceptional predator-evasion strategy, flyingfishes are important prey for larger fish, sharks, squids, seabirds and marine mammals. As an epipelagic specialist, E. volitans completes all life stages in the upper stratum of the water column, and can be abundant in warm surface waters [E. volitans at smaller spatial scales is likely due to extrinsic factors, such as primary productivity [Like other members of the Exocoetidae, e waters . The patuctivity .Exocoetus volitans spawns buoyant, pelagic eggs that should contribute to increased dispersal potential [E. volitans is small bodied , a relaE. volitans from throughout its entire circumtropical range, including far offshore epipelagic localities that are only accessible for research via dedicated long-range expeditions. Specifically, we addressed the following questions: (i) What is the worldwide genetic population structure of E. volitans? (ii) Are populations of E. volitans separated by previously described marine fish barriers? (iii) Is there evidence of a recent population expansion, or has the effective population size remained constant for a long period ? Using parsimony, AMOVA, Bayesian, and coalescent modelling methods, we measured and interpreted multiple population genetic parameters for this representative circumtropical epipelagic specialistIn this study, we tested for population subdivision using mtDNA sequences of Exocoetus volitans specimens were collected at night using flood lights and long-handled dip nets during 13 research cruises on the following research vessels from 1992 to 2010: Endeavor, Shoyo Maru, Gordon Gunter, McArthur II, David Starr Jordan, Kahana, and Oscar Elton Sette. The majority of specimens in the Pacific Ocean were collected during Stenella Abundance Research cruises, while Atlantic specimens were collected during the South Atlantic Black Carbon research cruise. Specimens were also donated by collaborators. In total, 266 E. volitans specimens were collected from 97 locations throughout the Atlantic, Pacific, and Indian Oceans (n Oceans . All speb (cytb) gene (1106 bps) was amplified using previously published protocols [Genomic DNA was extracted using DNeasy kits  and a portion of the mitochondrial cytochrome tb) gene 06 bps watb) gene 06 bps wah; nucleotide diversity, π; Θk (per sequence) and Θs (per site) were calculated using DNAsp v.5 [Population genetic summary statistics , Sunda Shelf Barrier , Benguela Barrier , and the Eastern Pacific Barrier: a deep water division between the Western and Eastern Pacific  within Arlequin v.3.5 [Because biogeographic barriers for epipelagic fishes are not well characterized, we postulated that barriers which have been demonstrated in other broadly distributed marine fishes could affect ine taxa . Four of Pacific . The Easin v.3.5  separatea priori into testable gene pools. To delineate populations more objectively, we used the Bayesian clustering model implemented by Geneland v.1 [MOVA requires that individuals are grouped land v.1 , 18. To μ) was 2% per base pair (bp) per million years, which has been previously used for marine teleosts [Exocoetus volitans lives for approximately one year [τ), which was converted to years based on τ = 2μkt . Goodness-of-fit between the observed and null MMD was calculated using Harpending raggedness indices (HRI) and sum of square deviations (SSD). Effective population sizes before and after population expansion were estimated as Θk, which was converted to Ne based on Θk = 2Nekμ. Finally, we used BEAST v.1.6.1 [Ne through time from the shape of the gene genealogy [The cytb genealogy was evaluated against the null model of neutral evolution in a single gene pool using three methods described below. Individuals were grouped in putative populations according to distribution , as well as based on Bayesian cluster analysis , with 242 singleton haplotypes and only 12 haplotypes shared among individuals. However, nucleotide diversity was low, with an average number of only 7.049 differences among pairs of sequences (π = 0.006 ± 0.0002). Global estimates of Θk, and Θs were 44.626 and 0.04125, respectively (We sequenced cytb fragments (1106 bps) from 266 an Ocean . There wectively . Indepenectively .The gene genealogy revealed a well-connected set of 242 unique, 12 shared, and 324 unsampled haplotypes . The ancST = 0.0352, p < 0.001), but not the other three putative barriers  revealed two gene pools: a “northern cluster” (n = 83: average posterior probability of assignment = 0.855 ± 0.136), and a “southern cluster” (n = 183: average posterior probability of assignment = 0.819 ± 0.156). Low posterior probabilities of assignment (0.50–0.55) were detected for only 13 individuals. ST = 0.027, p < 0.001).The individual clustering algorithm implemented in Geneland , Fu and Li's D  and Fu and Li's F  particularly during early life stages [E. volitans primarily occurs in epipelagic waters throughout all stages of life (holo-epipelagic) [H. affinis spawns in aggregations, attaching eggs to floating vegetation [E. volitans broadcasts buoyant eggs [E. volitans contributes to high levels of population connectivity is not fully understood because the reproductive biology of this species remains to be fully documented. Major distinctions in life history and population sizes likely confer species differences in population-level genetic variation.Despite two statistically significant barriers to global dispersal, p = 0.1, ). Howeve smaller . Additioe stages , while Egetation , 30 whilE. volitans can be compared with other genetic studies involving widespread marine fishes based on mitochondrial DNA data .Our finding of minimal global-scale population structure in DNA data . A numbe = 0.09; , bigeye  = 0.22; ) and blu = 0.22; ). Intere = 0.22; , large b 0.0001; ) and smaE. volitans, drive nonequilibrium conditions that can result in estimates of genetic divergence that are comparable to the effects of extensive contemporary gene flow [ST are consistent with high gene flow, they are also consistent with the persistent signature of a recent population expansion under almost any level of current gene flow [ST estimates. Thus, based on our data, we cannot dismiss the possibility that current gene flow across the range of E. volitans is lower than indicated by ΦST estimates [Extremely large effective population sizes, that are comparable to those we estimate for ene flow . Althougene flow . Our eststimates .E. volitans: the Isthmus of Panama barrier and a worldwide equatorial barrier  for the Isthmian and equatorial barriers  was also suggested by Chou and colleagues [H. oxycephalus. These authors suggested that range and/or demographic expansion may have been driven by the end of an era of maximum cooling sea surface temperatures (SST). Indeed, sea level changes  during the Pleistocene have been suggested as correlated for population bottlenecks and/or by post-glacial range expansions in many species [E. volitans for warmer tropical waters may have shaped its demographic history, and likely continues to influence the species' contemporary patterns of gene flow. However, given our study’s focus on a single genetic marker, we cannot discount other explanations for the mitochondrial gene genealogy. An alternative interpretation is that a selective sweep occurred within this species, leading to an abundance of distal branches, creating the "fireworks"-like appearance of this genealogy , the species-wide effective population size of lleagues  for demo species . The preogy (see ). MultilS1 TableMuseum voucher numbers (when available) and collection information are included for individuals used in genetic data analyses (n = 266). Assignments to southern or northern clusters resulting from analysis within Geneland v.1  are also(PDF)Click here for additional data file.


Sebastes mentella and investigate possible introgression within the genus by analyzing 13 microsatellites in 2,562 redfish specimens sampled throughout the North Atlantic. The data support an historical divergence between the “shallow” and “deep” groups, beyond the Irminger Sea where they were described previously. A third group, “slope,” has an extended distribution on the East Greenland Shelf, in addition to earlier findings on the Icelandic slope. Furthermore, S. mentella from the Northeast Arctic and Northwest Atlantic waters are genetically different populations. In both areas, interspecific introgression may influence allele frequency differences among populations. Evidence of introgression was found for almost all the identified Sebastes gene pools, but to a much lower extent than suggested earlier. Greenland waters appear to be a sympatric zone for many of the genetically independent Sebastes groups. This study illustrates that the identified groups maintain their genetic integrity in this region despite introgression.Genetic population structure is often used to identify management units in exploited species, but the extent of genetic differentiation may be inflated by geographic variation in the level of hybridization between species. We identify the genetic population structure of  Sebastes mentella is the most economically important species of the genus. It displays a high degree of genetic population diversity across its distributional range. In the Irminger Sea, two distinct groups, “shallow ” (50–550 m) and “deep (=deep pelagic)” (550–800 m), have been reported  to examine the genetic structure of S. mentella in Greenland, Iceland, and Irminger Sea waters, II) to investigate the extent of introgression among co‐occurring Sebastes species/gene pools, and III) to assess whether introgression may influence apparent species and population structure in the region.Despite the importance of Greenland waters as habitat and fisheries area for Sea ICES  although22.1S. mentella samples were collected during 2011 and 2012 from Greenland waters by commercial fishing vessels and research surveys. All the fish were caught by trawl. Samples were from different seasons  and life stages (juveniles and adults). Norwegian samples were collected from the shelf and pelagic waters in different seasons of the years  waters, and Irminger Sea from the EU REDFISH project (1998–2001). The Irminger Sea reference samples were characterized as “deep” and “shallow” S. mentella based on both morphological characters and sampling depths as described by Magnusson and Magnusson  as suggested by Barsukov et al.  cm].In total, 35 samples (collections of fish) consisting of 2,562 redfish specimens were included in the study Table . Nineteeagnusson . We inclv et al. . The aduv et al.  [for ins2.2m primer, and 15–25 ng DNA. The 5′ end on the forward primer was labeled with a fluorescent dye by the manufacturer . The GeneAmp 9700 (Applied Biosystems) thermal cycler was used for the amplification, with a PCR profile consisting of an initial denaturation step of 95°C for 15 min followed by 25 cycles of 95°C for 30 s, 56°C for 90 s, and 72°C for 60 s, ending with 60°C for 45 min. The PCR products were size‐separated and genotyped using an ABI 3130 XL automated sequencer (Applied Biosystems) and the GeneMapper 4.0 software (Applied Biosystems). Micro‐Checker . We analyzed a total of 13 microsatellite loci: Seb09, Seb25, Seb31, Seb33, Seb45, Smen05 . False discovery rate control  genotyped with 13 microsatellites to detect genetic structuring within the species. To estimate the magnitude of introgression, individual admixture analysis was performed for the total dataset consisting of all 35 samples  genotyped for ten loci . A Bayesian approach, as implemented in STRUCTURE  in STRUCTURE, an admixture model was used. Furthermore, a correlated allele frequency model was applied as the differentiation among the clusters was low  was compared with hybridization in the Northeast Arctic (Norwegian), and Northwest Atlantic waters (Flemish cap) following the approach of Nielsen et al. (Q) originated from other groups  were used as base population for generating in silico “pure” individuals using the program HYBRIDLAB , Norwegian S. norvegicus was used as baseline sample for identification of hybrids. Hence, hybrids were investigated only in S. mentella and S. fasciatus samples for the Northwest Atlantic. The same approach was used for identification of hybrids with S. viviparus in Greenland waters as the species has not been identified west of Iceland . A total of 45 fish within each cluster were randomly selected from the relevant samples. Rather than running all of the clusters together, pairwise cluster comparisons were chosen to reduce computational time. The IM model assumes random mating, free recombination among loci, and no recombination within loci. The MCMC‐based method of the program uses sampling of gene genealogies to estimate posterior probability densities of demographic parameters scaled by mutation rate per generation per year (μ). A stepwise mutation (SM) model was applied for the ten microsatellite loci.The isolation‐with‐migration (IM) model as implemented in IMa2 Hey,  was applt (time since divergence), swapping rates, autocorrelation value, trend‐line plots were evaluated. After a burn‐in of 500,000 steps, 2,000,000 more steps were run to save 20,000 genealogies for each pair of clusters. To ensure convergence for the estimation, 150 chains were used for all of runs with high heating schemes (“−ha0.975 −hb0.75”) so that the updates for the chains are accepted at higher rates. Introgression/bidirectional migration rates (m1 and m2) were estimated as effective number of migrants per generation , population size parameters , and time since divergence in generations (tμ) without converting for a given mutation rate, and generation time.A few preliminary analyses were performed with wider priors. The estimated effective sample size values of parameter 33.1N = 17) varied between 3.51 and 20.49. Gene diversities per locus within samples were between 0.14 and 0.969 (mean = 0.77). Significant heterozygote deficits were observed for all loci . Nineteen of 35 samples deviated significantly from Hardy–Weinberg expectation before FDR control, and 18 of them remained significant after FDR (Table S2). For the 35 Sebastes samples, 162 of 1,575 pairwise tests (10.29%) showed significant deviations from linkage equilibrium. LD was found for fish from all four species (between one and ten significant pairwise comparisons between loci). However, only 21 LD tests remained significant after FDR control. For the 27 S. mentella samples, 212 of 2106 tests for linkage equilibrium (approx. 10%) deviated significantly from expected values. After FDR, 57 of those tests remained significant without any spatial pattern. No evidence for null alleles or short allele dominance was detected by Micro‐Checker.The number of alleles per locus ranged from 13 to 69, and mean allelic richness , an initial investigation identified 138 redfish as S. norvegicus, which were removed from the subsequent analyses. As no differentiation was observed between temporal samples from two different S. mentella locations . The “deep” cluster consisted of 89% fish from the “deep” sampling group (depth = 830–850 m), fish from East and West Greenland waters (no depth record) in addition to individuals from the Icelandic Shelf , Northwest Atlantic , Irminger Sea “shallow” , and Northeast Arctic  waters. In the “slope” cluster, most individuals (89%) were from East Greenland waters sampled on the shelf (227–350 m). Approximately 29% (N = 17) of the “Icelandic Shelf” sample clustered with the “slope”  was considered, six clusters were identified by STRUCTURE . A much lower, but still significant proportion of the genetic variance could be ascribed to differentiation among samples within groups . The S. mentella “shallow” group from Northwest Atlantic (FC) and Northeast Arctic (Nor) were significantly differentiated from each other, and from the Irminger Sea “shallow” group plus “shallow” group samples (except two) from Greenland waters  of rs Table . Finallyrs Table .3.3Q > 10% from other genomes) individuals identified through the admixture analyses. Clusters were formed with comparable numbers of fish (Table S3) to obtain similar statistical power. The cluster of pure S. fasciatus (Table S3: Fasciatus) showed significant heterozygote deficiency, only before FDR control. All the admixed clusters except for S. mentella and S. fasciatus, and the “deep” and “shallow” groups of S. mentella were out of Hardy–Weinberg equilibrium. However, none of them remained significant except the admixed cluster of S. mentella and S. viviparus  after FDR. The admixed clusters had higher gene diversities than one or both of the parental clusters . A total of 59 (6.39%) tests for deviations from linkage equilibrium within clusters were significant, with more deviations observed in the admixed clusters .Genetic diversities, Hardy–Weinberg and linkage equilibria were estimated within the clusters with designated pure and hybrid . No significant simulation bias was observed . Interspecific hybridization appeared to be most prevalent in the Northeast Arctic waters. In these waters, admixed individuals were observed both for S. mentella–S. norvegicus and S. mentella–S. viviparus . No significant admixture between S. norvegicus and S. viviparus was detected . In the Northwest Atlantic, hybrid genotypes were observed for S. mentella–S. norvegicus, S. mentella–S. fasciatus, and S. norvegicus–S. fasciatus , but none of the cases conformed to a hybrid swarm scenario.STRUCTURE revealed admixed individuals for all geographically co‐occurring clusters. Within Greenland waters, we found the highest rate of hybridization among the three S. mentella. Hybridization between the “shallow–slope” pair was just higher than for the “deep–slope” pair. In contrast, symmetric patterns of introgression of much lower levels were estimated between Norvegicus‐A–”shallow” Mentella, Norvegicus‐B–”shallow” Mentella, and Norvegicus‐B–”deep” Mentella.In Greenland waters, evidence of significant introgression was observed in all cluster pairs studied using the IM model Figure . The higΘ) were comparable for the three S. mentella clusters  was higher than that estimated by Stefansson et al. (FST = 0.009) but almost identical to that of Shum et al. (FST = 0.031). Estimates of the demographic history by the IM model revealed that the divergence between these two groups was more ancient (tμ = 0.11) than that between “Giants” and “Norvegicus‐B” (tμ = 0.06), supporting a deep evolutionary divergence between “shallow” and “deep” groups as suggested by Stefánsson et al.  and of juveniles collected in autumn. The finding of juvenile fish is not surprising, because Greenland waters are suggested to be nursery grounds for all S. mentella on the Greenland and Iceland Shelf waters are assessed separately by ICES. In light of the results presented here, this should be reconsidered as stock dynamics appear to be linked across continental slopes, and the effect of fishing intensity on either shelf could affect the entire stock unit. A similar scenario has also been described for Atlantic cod where the East Greenland and Iceland slopes are inhabited by the same populations , there was evidence of statistically significant genetic variance among samples within groups. This result was also supported by the many significant pairwise up Table  suggestsup Table  and by Jup Table , but notup Table . An isols Tables  and 4 sus Tables . The higs Tables , 4, 5, is Tables  who hypoS. mentella complex  in the Northeast Arctic waters hybridize more frequently with both S. viviparus and S. norvegicus (“Norvegicus‐B”) than in other areas. One plausible reason for this might be the differential abundance of species. Recent surveys conducted in the Northeast Arctic waters have indicated a much greater abundance of S. mentella than S. norvegicus . The results imply that Heterozygote deficiencies were apparent in some loci for several samples, consistent with observations using some of these loci in other studies . This approach may limit the applicability of the IM method for providing realistic estimates of introgression and demographic parameters. However, no severe bias has been observed in other comparable studies (Chan et al., The SM model is only option for IM analyses of microsatellite data, but microsatellites probably do not follow this model. Strasburg and Rieseberg  analyzedS. mentella especially in the Irminger Sea have caused failure of an efficient management of the stocks for the latest decade. The poor knowledge of biological parameters for the species and of stock identity have resulted in uncertain advice over the past (ICES S. mentella, and catches have consequently exceeded biological advice by more than three times due to autonomous quota setting by each fishing nation (ICES S. mentella in the present study is anticipated to lead to a more robust advice which again likely will ensure a sustainable fishery by a common fishery management.Lack of knowledge on stock identity and scientific discrepancy in perception of stock entities of ast ICES . This laion ICES . The fur5S. mentella throughout its range, including Greenland waters. The identification of all three S. mentella groups in Greenland waters supports the interpretation of this region as a nursery area and population mixing zone. Fish from the “shallow” group were identified across the North Atlantic, but divided into three populations: Northeast Arctic, Irminger Sea/Greenland, and Northwest Atlantic. Therefore, we clarify the genetic stock identity of S. mentella from the Northeast Arctic, which was previously disputed. The “deep” group S. mentella were identified in the Irminger Sea and Greenland waters, but some were also found in the Northwest Atlantic. The “slope” fish from the Icelandic Shelf and Greenland waters were not genetically differentiated, which suggests genetic connectivity of “slope” fish in East Greenland–Iceland Shelves. In Greenland waters, the “slope” group was the main target for the commercial fleets in spring. Although genetic heterogeneity was evident, low‐to‐moderate extent of gene flow was observed across the North Atlantic, implying incomplete reproductive isolation for Sebastes clusters possibly due to their close evolutionary relationship. The genetic differentiation between S. mentella groups were less than that between the other Sebastes clusters. Our findings mostly support the existing management practice of S. mentella throughout the North Atlantic (Cadrin et al., We provide the first genetic investigation of http://dx.doi.org/10.5061/dryad.94d1s.Data available from the Dryad Digital Repository: No conflict of interest declared. Click here for additional data file.


Vigna radiata (L.) R. Wilczek var. radiata] is an important grain legume globally, providing a high-quality plant protein source largely produced and consumed in South and East Asia. This study aimed to characterize a mungbean diversity panel consisting of 466 cultivated accessions and demonstrate its utility by conducting a pilot genome-wide association study of seed coat color. In addition 16 wild accessions were genotyped for comparison and in total over 22,000 polymorphic genome-wide SNPs were identified and used to analyze the genetic diversity, population structure, linkage disequilibrium (LD) of mungbean. Polymorphism was lower in the cultivated accessions in comparison to the wild accessions, with average polymorphism information content values 0.174, versus 0.305 in wild mungbean. LD decayed in ∼100 kb in cultivated lines, a distance higher than the linkage decay of ∼60 kb estimated in wild mungbean. Four distinct subgroups were identified within the cultivated lines, which broadly corresponded to geographic origin and seed characteristics. In a pilot genome-wide association mapping study of seed coat color, five genomic regions associated were identified, two of which were close to seed coat color genes in other species. This mungbean diversity panel constitutes a valuable resource for genetic dissection of important agronomical traits to accelerate mungbean breeding.Mungbean [ Vigna radiata (L.) R. Wilczek var. radiata] is a grain legume originating from South Asia. It belongs to subgenus Ceratotropis of the Fabaceae family which comprises 23 species including the closely related wild mungbean [Vigna radiata var. sublobata (Roxb) Verdcourt]. As a summer legume species with a short growth duration (55–70 days from sowing to maturity) and the ability to fix atmospheric nitrogen, mungbean delivers economic, farming systems, and environmental benefits. The crop is vital to smallholder farmers in Asia with an annual production of 3.5–4.0 million tons where it represents an excellent cheap source of carbohydrates, high quality protein (dry seeds 27% protein), folate and iron (Mungbean , or black gram, produces sterile progeny when hybridized to mungbean  R. Wilczek var. radiata] germplasm held in Australia by the National Mungbean Improvement Program . The material originated from various sources worldwide and represents the widest range of phenotypic traits observed and characterized by the mungbean breeding team over the past 50 years. These included seed coat color, seed size and weight, days to flower, days to maturity, plant habit, plant height, and reaction to key foliar diseases. Sixteen wild accessions [Vigna radiata var. sublobata (Roxb Verdcourt)] originating from Australia were also included in the study as a comparison to the diversty panel of cultivated mungbeans.The mungbean diversity panel consists of 466 accessions representing the cultivated mungbean [1). The samples were genotyped following an integrated DArT and genotyping-by-sequencing (GBS) methodology involving complexity reduction of the genomic DNA to remove repetitive sequences using methylation sensitive restrictive enzymes prior to sequencing on next generation sequencing platforms (DArT2). The sequence data generated were then aligned to the mungbean reference genome sequence, Vradi_ver6 .All 482 mungbean accessions were planted at Hermitage Research Facility, Warwick, QLD, Australia , over the summer of 2015. The field trial design was unreplicated single field plots for each accession, 4.5 m2)/n where Pi is the frequency of the i th allele and n is the total number of genotypes (The polymorphism information content (PIC) of each DArTseq SNP marker was determined using the following formula: PIC = 1-Σ(Pienotypes .2r) using the TASSEL program (v5.1.0)  . Only r2K (K = 2:10), and choose the value of K for which the cross-entropy curve exhibits a plateau (K = 4).Population structure of the 466 cultivated accessions was analyzed using a Structure-like Population Genetic Analyses in R package LEA . The numST) among the four sub-populations was calculated using R package PopGenome  performed in the software package DARwin v6.0 .K was calculated using Scaled IBS method implemented in TASSEL 5.1.0. Bonferroni correction was applied to set thresholds for P-value significant (0.05/n); n represented the number of SNPs used in trait-marker association analysis. The Manhattan plot was generated using the R package qqman (Association mapping was conducted using mixed linear model (MLM) controlling for Q and kinship (K) as fixed and random effects respectively in TASSEL 5.1.0. Minor allele frequency (MAF) > 0.01 was used to filter SNPs prior to analysis. Q was extracted from results of previous population structure analysis, which detected four sub-populations. ge qqman .Table 1 and Figure 1). A total of 7,675 SNPs segregated within the cultivated population, with an average PIC value of 0.174. In contrast, 6,174 SNPs segregated within the wild population with an average PIC value of 0.305 . Additionally, individual chromosomes of the cultivated population were estimated, no substantial differences were observed . A range of sub-populations (K = 2:10) were tested and a K-value of 4 was determined to best capture the structure of the cultivated population based on minimal cross-entropy  or Australian breeding lines . Those accessions with passport data were mostly from Southern Asia, Taiwan, Thailand, Philippines, and Vietnam with uniformly green seed coats.Sub-population 2 was comprised of 40 accessions and had the widest range of passport data, with the accessions predominantly from Middle Eastern countries including Afghanistan, Uzbekistan, Tajikistan, Kyrgyzstan and Iran, with single accessions from China, India, Netherlands, and Turkey. This sub-population also had the widest range of seed coat colors, although largely green with a number of speckled, a single yellow accession and additionally this was the only sub-population to contain brown seed coats.Sub-population 3 contained the largest number of accessions (59) mainly derived from Southern Asian countries, Cambodia, Philippines and Thailand with single accessions from China, Hong Kong, India, Indonesia, and Vietnam. This sub-population also contained the highest number of accessions from Iran (6). Of the 59 accessions, 19 displayed yellow seed coats while the remaining accessions were green in color with two speckled seed coats.Sub-population 4 contained the lowest number of accessions (22), and the majority of the accessions did not have passport data; those that did were from India and Pakistan with a single line from Taiwan. Seed coat colors were primarily green with three accessions displaying speckled seed coats.Figure 4). The first two principal coordinates accounted for approximately 34.04% of the genotypic variance with coordinates one (x-axis) and two (y-axis) explaining 18.18 and 15.86%, respectively.Principal coordinate analysis was also used to visualize the relationships amongst the cultivated accessions in the panel. When the four sub-populations were plotted they clustered toward the extremities of the plot based on their genetic differences (ST) using PopGenome. Sub-populations 1 and 3 were the most closely related with an overall FST value of 0.42, while sub-populations 1 and 2 show the highest degree of differentiation, with an FST value of 0.57 (Table 2). Sub-population 1 had uniform green seed coats, in contrast to sub-population 2 which had a wide variation of seed coat colors. Sub-populations 1 and 3 however, shared similar characteristics with many accessions originating from Southern Asia and uniform seed color.The genome-wide genetic differentiation between the four contrasting mungbean sub-populations identified in structure were calculated using fixation index . These SNPs were located in five distinct genomic regions distributed across chromosomes 3, 4, 5, and 7  controlling seed coat color through flavonoid 3′-hydroxylase in soybean (TASSEL v5.1.0 was used to conduct a pilot genome-wide association mapping (GWAS) for seed coat color to demonstrate the effectiveness of the diversity panel for trait dissection. Seed coat color was chosen because it’s an oligogenic trait which does not change based on the environment the plant is grown and is economically important to the mungbean industry. Using the MLM model, nine SNPs were identified as significantly associated with seed color based on  soybean  associat soybean .The replacement of traditional and local crops with elite varieties harboring superior agronomic traits has led to increased yields but also the gradual erosion of genetic diversity of cultivated varieties. Globally, plant breeders are addressing the threat to cultivated crops with narrow genetic diversity by establishing large collections of genetically diverse germplasm. In this study, we investigated the application of genome-wide SNP markers to analyze the genetic diversity of a large, diverse mungbean germplasm panel. The markers generated from this germplasm panel provide a new resource to conduct high-resolution analysis of genetic diversity, population structure, LD and the capacity to identify genes controlling important agronomic traits. Additionally, this is the first high-resolution quantification of LD decay in mungbeans, defining the extent of LD within and between cultivated and wild mungbeans. The genetic diversity analysis, population structure and LD analysis provide the foundation that can be used to broaden the genetic base of mungbean breeding material. The genome-wide association study provides an example of how the data can be used to identify genomic regions responsible for phenotypic traits. SNP markers provide a level of resolution to breeding programs far beyond traditionally used methods which relied solely on passport data such as geographical origin and pedigrees  or genetThe domestication syndrome, resulting from restricting the number of elite varieties used in breeding under selection for key traits such as larger grain size, has come at the expense of diminishing overall genetic diversity . Low genHighly informative PIC values as defined by The clear differentiation between cultivated and wild mungbean gene pools, as demonstrated in the PCA analysis . Wild mungbean has retained a higher degree of allelic diversity providing an important source of material for increasing the genetic diversity of the cultivated gene pool.The number and density of markers required for an association mapping analysis is determined by the distance over which LD decays. The LD patterns of mungbean reflect its long history of domestication  and as aMedicago truncatula, a leguminous plant used in genomic studies the LD decayed rapidly, dropping too approximately half of its initial value within ∼3 kb  are identified through the establishment of association between genomic marker data and traits of interest. Previous studies revealed the genetic factors controlling important agronomic traits in mungbean using biparental populations such as, major QTLs for hard-seededness and seed weight ; powderysistance . Due to sistance , QTLs weFigure 5) is an example of how the features of this data set can provide high resolution mapping opportunities. A Nested Association Mapping (NAM) population in mungbean, currently being developed by the Queensland mungbean improvement team, will provide a powerful complementary population to the diversity panel described here. The structure of the mungbean NAM population encompasses 26 of the most genetically and phenotypically diverse accessions, backcrossed to one elite line adapted to the local production (Supplementary Figure The structure of our population, which captured vast historical recombination accumulated during mungbean cultivation, combined with the high density of markers genome-wide overcome barriers seen in previous studies. The GWAS performed in this study (CD, DJ, and EM conceived and designed the experiments. TN collected the data. TN, EM, and YT analyzed data. TN, EM, and YT wrote the manuscript. SM, BW, DJ, and EM revised the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Haliotis diversicolor) is a commercially valuable species for both fisheries and aquaculture. The production of annual farmed small abalone in Taiwan, once the highest in the world, has dramatically decreased in the past 15 years, and currently, the industry is close to collapse. Understanding the genetic diversity of small abalone and developing stock identification methods will be useful for genetic breeding, restoring collapsed stocks, managing stocks, and preventing illegal trade. We investigated 307 cultured and wild individuals from Taiwan, Japan, and Bali Island (Indonesia) by using the mitochondrial cytochrome c oxidase subunit I (COI) gene. Network analysis of mtDNA COI gene sequences revealed that the individuals collected from Taiwan, Japan, and Indonesia could be identified, and showed significant genetic divergence. In addition, the Indonesian population  was significantly different from the other populations and might need to be considered a separate species. We discovered a single nucleotide polymorphism marker in the mtDNA COI gene that can be used to distinguish the Taiwan population from the Japan population. We also developed a polymerase chain reaction-restriction fragment length polymorphism method for rapid detection. Furthermore, we could identify the cultured stocks, wild population, and hybrid stocks by using 6 microsatellites and amplified fragment length polymorphism. This study contributes useful tools for stock identification and the production of high-disease resistant small abalone strains (Japan × Taiwan or Taiwan × Japan). Efforts should be made to avoid unintentional random genetic mixing of the Taiwan population with the Japan population and subsequent breakdown of population differentiation, which impair local adaptation of the Taiwan wild population. Molecular markers revealed a split between the Taiwan and Japan populations, and the existence of a possible barrier to the free dispersal of small abalone is discussed.Small abalone ( Haliotis is the sole genus in the Haliotidae family, with approximately 56 species worldwide [The abalone genus orldwide –2. Theseorldwide . Approxiorldwide –5. Smallorldwide –2,6.H. discus hanni or a hybrid between H. discus hanni and H. discus discus accounted for nearly 95% of abalone production [In Taiwan, small abalone is commercially valuable for both fisheries and aquaculture because of its high price, rapid growth, and short life cycle –8. Aquacoduction .However, disease outbreaks and substantial mortality of small abalone have occurred at the postlarval and grow-out stages in both Taiwan and southern China since 2002 . In TaiwHatchery-reared stock has often been used as broodstock to produce the next generation for each year. Genetic degradation resulting from inbreeding may be the major reason for the mortality event, because high genetic diversity increases the population’s ability to withstand environmental perturbations and disease outbreaks ,20–21. SHaliotis diversicolor endemic to Taiwan. The taxonomic status of small abalone is also controversial and unclear. Only minor morphological differences exist among H. diversicolor, H. diversicolor aquatilis, H. diversicolor diversicolor, and H. diversicolor supertexta regarding the relative ridge height of the shell [Despite several decades of small abalone farming in Taiwan, the genetic structure of wild populations and cultured stocks of Taiwan small abalone remains unclear. In comparison with other abalone species, limited information is available on the genetic composition of he shell . UnderstH. diversicolor complex  across most of its distribution throughout the biogeographical region. Furthermore, we used AFLP, SSR, and the mtDNA COI gene to examine the population genetic structure of wild, cultured, and intraspecific hybrid small abalone, H. diversicolor, with an emphasis on intensive sampling in Taiwan and the Japanese archipelago. Microsatellite loci and AFLP have been successfully used to determine population genetics and identify the hybrids of closely related species or sympatric species with similar morphology. Microsatellites have been used to detect loss of genetic diversity in cultured populations. Finally, we identified an SNP site in the mtDNA COI gene and used it to develop a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method for identifying regional genetic differentiation between the Taiwan and Japan populations. In recent years, poaching, overfishing, climate warming and pollution have led to increasing concerns about the status of this abalone stock. Knowledge regarding the genetic diversity and the patterns of the stock structure is an essential for developing effective conservation approaches. However, no information is available on the genetic composition of wild and hatchery cultured small abalone in Taiwan. This information would be useful for the development of a more effective management for the small abalone industry and the conservation of small abalone, H. diversicolor, in Taiwanese waters.Molecular genetics contributes to our understanding of the population, and this is particularly true for species that lack morphological differences among the population . In thisThis study was conducted in accordance with all Taiwan and Japan laws. Neither specific permits were required for the described field studies nor were specific permissions required for the locations/activities described in this study. The location is not privately owned or protected in any way. The field studies did not involve endangered or protected species.H. diversicolor and hybrids, including 7 individuals of H. diversicolor squamata, were used in this study . Sequences were determined using the ABI 3770  and edited and aligned in the DNA Baser (www.dnabaser.com). All sequences obtained in this study have been posted on GenBank (KX853541-KX853847).The primer pair HdCOI, H. diversicolor complex, other Haliotis spp., and invertebrate taxa available from GenBank, were analyzed phylogenetically. The best-fitting nucleotide substitution model was tested by comparing the lowest Bayesian Information Criterion (BIC) scores by using MEGA v5  was used for species identification –30. A daNhp), average number of nucleotide differences (k), haplotype diversity (h), and nucleotide diversity (π) was calculated with DNASP v5.0 [p-distance and Kimura 2-parameter model) were calculated by using MEGA v5 [Polymorphic sites, transitions, and transversions, were obtained using Arlequin v3.5 . Number ASP v5.0 . Mean nu MEGA v5 .ΦST values. Both statistical significances of the estimates were assessed by 10,000 permutations using Arlequin v3.5 [The significance of the population structure was tested using analysis of molecular variance (AMOVA) and pairwise uin v3.5 . The rel5’-TGGCGACGACCAATTATACA-3’ and 5’-GGGGTAGACTGTCCATCCTG-3’, was designed and used to amplify the partial mitochondrial COI gene including the SNP site (COI-116), yielding a 247-bp fragment. Amplifications of the SNP site (COI-116) were performed using an initial denaturation of 94°C for 3 min, followed by 35 cycles of 94°C for 60 s, 58°C for 30 s, and 72°C for 30 s and a final extension at 72°C for 3 min. Subsequently, the amplified samples (5 μL) were subjected to endonuclease digestion by using the 4-base recognition enzymes MnlI . Digestion was directly performed in the 10× NEB buffer 4 at 37°C for 3 h. The DNA fragments were separated on a 2.0% agarose gel with a fluorescent dye .The primer pair Hd116, μL reaction volumes containing 5–10 ng template DNA; 1× PCR buffer ; 200 μM of each dNTP, 1.5 mM MgCl2, and 0.5 U Taq polymerase ; and 4 pmol of each primer. Thereafter, PCR cycling was performed on an Autorisierter Thermocycler  with initial denaturing at 95°C for 2 min, followed by 30 cycles of denaturing for 30 s at 95°C, annealing for 30 s at locus-specific temperatures, extension for 30 s at 72°C, and a final extension for 10 min at 72°C. The PCR products were denatured and visualized using denaturing polyacrylamide gels (6%), followed by silver staining [A total of 6 microsatellite primer sets were used, with 5 from Ren et al. : MS-1, Mstaining . AllelesHo), expected genetic diversity (He), FIS were calculated and the Chi-square Hardy–Weinberg equilibrium test were performed using GENALEX 6.41 [Procedures for microsatellite analysis were based on Hsu et al. . The obsLEX 6.41 . To elucLEX 6.41 . Three iLEX 6.41 . SummatiLEX 6.41 .E-ATA/M-CGCA, E-AGC/M-CGCT, E-ACT/M-CGCA, E-AGG/M-CCTG, E-ACT/M-CGCG, and E-ACC/M-CCG. The PCR products were denatured and visualized using denaturing polyacrylamide gels (6%), followed by silver staining [D) were calculated using the Dice similarity coefficient [He) was calculated according to the allelic frequencies (square root method) by using GenAlEx 6.41 [AFLP protocols were modified from Vos et al.  followinstaining . Band sifficient  and Excefficient . GeneticlEx 6.41 . PrinciplEx 6.41 .H. diversicolor complex, including samples collected from 3 locations in Japan, 7 locations in Taiwan, and one location in Indonesia  from GenBank , H. walallensis, H. kamtschatkana complex , H. tuberculata (H. tuberculata tuberculata and H. tuberculata coccinea), H. diversicolor complex , and H. diversicolor squamata  and represented monophyletic relationships. The lowest p-distance of 0.017 was detected between H. walallensis and the H. kamtschatkana complex, and the highest p-distance of 0.194 was detected between H. cracherodii and the H. diversicolor complex  from 307 individuals of small abalone, the ndonesia . In addi GenBank . Eight csquamata . The COI complex . The p-das 0.135 . The spe species .H. diversicolor complex, collected from 3 locations in Japan and 7 locations in Taiwan (Nhp) per location ranged between 6 in TK-C and 25 in JF-W. The number of private haplotypes per location ranged between 0 in TK-C and TP-C and 20 in JF-W (Nhp) and the highest number of private haplotypes. H_1 and H_10 were the most common haplotypes in the Japan stocks, and H_4 and H_30 were the most common haplotypes in the Taiwan stocks  were obtained from 300 individuals of small abalone, n Taiwan . Only onn Taiwan . The num in JF-W . Moreoveocks see .k), haplotype diversity (h), and nucleotide diversity (π) was high, indicating no inbreeding in the wild populations from Taiwan and Japan, and a slight inbreeding in cultured stocks from Taiwan (k = 3.442–4.273), haplotype diversity (h = 0.964–0.974), and nucleotide diversity (π = 0.426–0.529). By contrast, cultured stock from Taiwan (TP-C and TK-C) had a lower average number of nucleotide differences (k = 1.366–1.991), haplotype diversity (h = 0.703–0.838), and nucleotide diversity (π = 0.169–0.247) (The average number of nucleotide differences (m Taiwan . Wild po9–0.247) .Haliotis samples collected from Taiwan, Japan, and Bali Island (Indonesia). The first level, two distinct clades (H. diversicolor complex and H. diversicolor squamata) according to the Bayesian phylogenetic tree  between the Taiwan stocks and Japan wild populations  between the Taiwan cultured stocks and Taiwan wild populations, except for TE-W and TK-C  and the Japan wild populations . Limited differentiation or no significant differentiation was observed among the Taiwan cultured stocks   .Haliotis samples collected from Taiwan and Japan. The “G type” and “A type” were mainly found in the Taiwan and Japan populations, respectively , 2 Taiwan wild stocks (TE-W and TH-W), and 4 Taiwan cultured stocks . Hybrid identification was performed using 6 different AFLP primer combinations. The AFLP profiles proved to be highly reproducible. No difference was observed among the replicates, although different amounts of DNA were used. For the TE-H cross, the 6 AFLP primer combinations generated a total of 149 markers, of which 71 were polymorphic, with an average of 47.65 markers per primer set . All 6 pH. discus is also unclear, and discriminating these species according to morphological characteristics is difficult. Six microsatellite markers proved to be successful for evaluating the significant genetic differences between 2 subspecies, H. discus hannai and H. discus discus [H. diversicolor, H. diversicolor aquatilis, H. diversicolor diversicolor, and H. diversicolor supertexta, were clustered together. No divergence was detected among these haplotypes, suggesting that they are the same species. Hence, H. diversicolor, H. diversicolor aquatilis, H. diversicolor diversicolor, and H. diversicolor supertexta are not detectable for stock management. H. diversicolor squamata, an Indonesian small abalone, is significantly different from the other 4 small abalone species (p-distance = 0.135) and may need to be considered a separate species  is a small, worldwide commercial abalone and has a wide geographical distribution in the warm water regions of the northwest Pacific  [Haliotis diversicolor) is small and has a maximum shell length of approximately 10 cm; it mainly inhabits shallow subtidal areas in subtropical and temperate zones of the southern area of mainland Japan, except for Okinawa, where small abalone was introduced from Taiwan and Japan [−1 [Small abalone (n Japan) –2,6. Thend Japan . The smand Japan . The relapan [−1 , may plaPomacentrus coelestis) [Pagrus major) [Plecoglossus altivelis), red seabream, and neon damsel fish [P. coelestis between mainland Japan and Okinawa. Based on the disjunctive distribution of small abalone species coupled with the genetic differences between the Taiwan and Japan wild populations observed in this study, small abalone is likely formed by several small breeding units, implying high genetic variability. The biogeographic pattern of small abalone is analogous with that of marine reef fish P. coelestis, amphidromous fish ayu, and oceanodromous demersal fish red seabream. The Tokara Gap and the Kerama Gap might also act as barriers to the free dispersal of small abalone.During the Pleistocene, land bridges, lower sea levels, and current hydrodynamic regimes profoundly changed in the northwest Pacific –52. Thess major) . The strs major) . The Toksel fish . Liu et h), was found to be very high for both the Taiwan and Japan wild populations of small abalone  of all 4 Taiwan cultured stocks  was not significantly different from that of the Taiwan wild population (TH-W) (π) without an accompanying loss of mtDNA haplotype diversity (h) may be explained by the loss of low-frequency alleles, which usually occurs during a population bottleneck. Continued intensive breeding practices lead to reduced genetic diversity if the size of effective populations is limited. The slight reduction of genetic diversity in the Taiwan cultured stocks  compared with that in the Taiwan wild population (TE-W and TH-W) may be attributed to the small number of parent abalone used for reproduction, because the cultured stocks consistently underwent a population bottleneck and subsequent genetic drift. The hatchery cultured TK-C stock showed marked reduction in the number of haplotypes (Nhp = 6) and haplotype diversity (h = 0.703) in comparison with the Taiwan wild populations and other cultured stocks. This finding is consistent with the observation that the cultured stocks obtained without exchanging broodstocks are characterized by reduced genetic variation due to genetic drift in the aquaculture environment.It has been reported that aquaculture practices tend to reduce genetic variation in cultured stocks of abalone species –60. Geneing AFLP . An et aing AFLP  developen (TH-W) . By contn (TH-W)  and 3. Bn (TH-W) . In the n (TH-W) . Loss ofNhp) and the highest number of private haplotypes (Nhp) per location ranged between 6 in the Taiwan cultured stock (TK-C) and 25 in the Japan wild population (JF-W). The number of private haplotypes per location ranged between 0 in the Taiwan cultured stock (TK-C and TP-C) and 20 in the Japan wild population (JF-W)  exhibited the highest number of haplotypes (plotypes . The numn (JF-W) . The losΦST values, AMOVA, and AFLP all supported significant differentiation between cultured stocks and wild populations  aquaculture is in disarray. The precise origin and pedigree information of broodstocks are unknown, and the genetic management of small abalone is difficult.Pairwise ons Figs  and 3. SH. midae ,61–62. TH. midae . In TaiwH. midae ,22. BecaH. diversicolor) [The release of cultured seeds into natural habitats is one measure for restoring collapsed abalone stocks. Stocking hatchery-reared organisms in wild populations usually greatly affect the genetic integrity of native wild populations and can even dilute and/or replace native wild populations when seeds are released in numbers that exceed the carrying capacity of release regions . Hamasaksicolor) –66. In nsicolor) –69. Typhsicolor) . Farmed sicolor) . The “esIn conclusion, no information has previously been available on the genetic structure and variation between and within the cultured stocks and wild populations of small abalone in Taiwan, until now. This study showed no genetic differentiation between the 2 wild populations (TE-W and TH-W) and revealed significant differentiation among the cultured stocks . The genetic differences between geographical populations (Taiwan and Japan) can provide wide genetic diversity for selective breeding and hybridization for the sustainable use of this species. To avoid potentially harmful disease spread and the ecological and genetic consequences of escape through spawning, the pond water used for culturing small abalone in Taiwan according to the present coastal farming style should be treated properly before discharge. Efforts should also be made to avoid the unintentional genetic mixing of the Taiwan native wild population with the Japan population and subsequent breakdown of population differentiation, which impair local adaptation of the Taiwan native wild population. Continued monitoring of the genetic diversity among wild populations, cultured stocks, and intraspecies hybrids by using molecular markers is important for effective management of the small abalone industry and conservation of small abalone in Taiwanese waters.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 TableNumbers in bold are private haplotypes.(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S7 TableD: genetic distance (based on similarity coefficient); Shannon Information Index (I); He: expected heterozygosity ; UHe: unbiased expected heterozygosity.(DOCX)Click here for additional data file.S1 File(PDF)Click here for additional data file.


One of the ultimate aims of ex situ conservation is reintroduction of endangered animals into their natural habitats while maintaining 90 % of the founder genetic diversity. Advances in molecular genetics and microsatellite genotyping techniques make it possible to accurately estimate genetic diversity of captive animals of unknown ancestry. Here we assess genetic diversity of the red panda population in Padmaja Naidu Himalayan Zoological Park, Darjeeling, which plays a pivotal role in ex situ conservation of red panda in India. We generated microsatellite genotypes of fifteen red pandas with a set of fourteen loci. This population is genetically diverse with 68 % observed heterozygosity (HO) and mean inbreeding (FIS) coefficient of 0.05. However population viability analysis reveals that this population has a very low survival probability (<2 %) and will rapidly loose its genetic diversity to 37 % mainly due to small population size and skewed male-biased sex ratio. Regular supplementation with a pair of adult individuals every five years will increase survival probability and genetic diversity to 99 and 61 % respectively and will also support future harvesting of individuals for reintroduction into the wild and exchange with other zoos.Red panda  Ailurus fulgens), also known as the lesser panda, is one of earth’s living fossils and its ancestors can be traced back to more than ten million years ago across Eurasia , Darjeeling, and Himalayan Zoological Park (HZP), Gangtok. These animals are periodically exchanged with international zoos as part of the Species Survival Plan to maintain genetic diversity among captive bred individuals. The two Indian zoo populations of red panda have the distinctive priority of being located within the range states of its wild population distribution; and importantly being part of international captive breeding program, have the potential to provide a link between captive and wild populations Glatston . TherefoPadmaja Naidu Himalayan Zoological Park (PNHZP), Darjeeling plays a pivotal role in red panda captive breeding in India, and had fifteen individuals, including three founders  and twelve captive-born at the time of our study (2012–2013). Fresh faecal samples of all fifteen red pandas  were collected in sterile bottles with 90 % ethanol. Out of these animals, blood samples from four males and three females were also collected in EDTA-coated vacutainer tubes. Samples were acquired as per the Padmaja Naidu Himalayan Zoological Park and Central Zoo Authority, Govt. of India, ethical guidelines and procedures. No animal was injured as a result of this study. All samples were transported to the laboratory and stored at −20 °C until DNA isolation. Genomic DNA from blood was isolated by standard phenol–chloroform method  and sibling (PSIB) from a pair of genotypes was determined from allele frequencies, and minimum number of loci required to differentiate siblings was restricted to nine loci. Mismatched genotypes were re-examined manually for scoring errors, and in some cases the respective loci were genotyped again. All loci were scored manually for genotyping errors, amplification success and certainty of PCR repetitions in Microsoft EXCEL spreadsheets.Allele frequency and identity analyses were implemented as described by Reddy et al.  to matchE) and observed (HO) heterozygosities using allele frequency function in CERVUS 3.0. Polymorphism Information Content (PIC) of heterozygous loci was also obtained from allele frequencies. Alleles deviating from Hardy–Weinberg equilibrium (HWE) were tested with Genepop v4 (Rousset IS) in the population were determined using FSTAT  from a pair of unrelated individuals is 0.0001 with a minimum of six least variable loci and 9.7 × 10−13 with all fourteen loci, while probability of identifying siblings (PSIB) from pair of animals is 0.001 with nine least variable loci and 1.06 × 10−5 with all fourteen loci. Identity analysis in CERVUS 3.0 correctly matched genotypes obtained from faecal and blood DNA samples of each animal. Genotypes obtained with a minimum of eleven loci were sufficient to generate genetic diversity parameters effectively.We genotyped all fifteen red pandas at PNHZP at a minimum of eleven microsatellite loci, and got an average dropout rate of 9.8 % at fourteen loci and 89 % amplification success rate Table . We needE) and Observed (HO) heterozygosities were 0.714 and 0.681 respectively  of 0.64, and 3–7 alleles per locus Table . Expectely Table  analysisly Table  indicateAccording to baseline scenario simulations, the captive red panda population at PNHZP is a slow growing population. Deterministic growth rate  is 10.3 % , with a mean generation time of 4.27 years for both females and males, while retaining only 37 % gene diversity after 100 years. Survival probability of this population without any additional intervention is less than 2 %. Gene diversity can however be maintained at 61 %  by supplementing this population with one reproductively active female and male once every 5 years till 100th year. Supplementation also helps in increasing the population size to about 45 individuals in 25 years  and dropout 9.81 %) rates comparable with multiplex protocols described earlier , Darjeeling has the largest captive population of red panda in India and is principally responsible for conservation breeding of this species in India. Although supported by two other satellite zoos in Gangtok and Nainital, their respectively populations are presently too small to influence the breeding program. Being located in the species’ range states, Darjeeling and Gangtok’s captive red panda populations have tremendous potential to grow, maintain the genetic diversity of the international captive population and restock dwindling wild populations.


IIL1 locus in the Bur-0 accession of the model plant Arabidopsis thaliana. The IIL1 triplet expansion is an example of cryptic genetic variation as its phenotypic effects are seen only under genetic or environmental perturbation, with high temperatures resulting in a growth defect. Here we demonstrate that the IIL1 triplet expansion associated growth defect is not a general stress response and is specific to particular environmental perturbations. We also confirm and map genetic modifiers that suppress the effect of IIL1 triplet repeat expansion. By collecting and analyzing accessions from the island of Ireland, we recover the repeat expansion in wild populations suggesting that the repeat expansion has persisted at least 60 years in Ireland. Through genome-wide genotyping, we show that the repeat expansion is present in diverse Irish populations. Our findings indicate that even deleterious alleles can persist in populations if their effect is conditional. Our study demonstrates that analysis of groups of wild populations is a powerful tool for understanding the dynamics of cryptic genetic variation.Triplet repeat expansions underlie several human genetic diseases such as Huntington's disease and Friedreich's ataxia. Although such mutations are primarily known from humans, a triplet expansion associated genetic defect has also been reported at the  The trinucleotide repeat expansion, when present in a homozygous state, causes a temperature-dependent reduction in IIL1 transcript levels and severely impairs growth of this accession under short days at elevated temperatures  and not in standard growth conditions . Thus, the phenotypic impact of the repeat expansion could be seen only upon genetic or environmental perturbation, indicating that this repeat expansion represents a cryptic genetic variation  mapping for one of these modifiers. Furthermore, we collect and analyze A. thaliana accessions and demonstrate that the IIL1 triplet has persisted in multiple independent natural populations for over 50 years. Our results significantly expand our understanding of the persistence of cryptic genetic variation within plant species.In this paper, we demonstrate that the iil phenotyping, QTL analysis and temperature assays as described previously  have been described previously . This region was defined as the areas of north Co. Clare and adjacent parts of southeast Co. Galway associated with visible karstified limestone. Wild plants were sourced from all roadsides, field-sides, churchyards and graveyards, accessible open pastures, and other places suitable for the growth of weedy ruderals. Our second set of collections comprised additional accessions from other areas of the island of Ireland, chosen from recent records of A. thaliana obtained from the Botanical Society of Britain and Ireland . In each case, multiple individuals were collected from the same stand, with seed from 5 to 10 plants sampled from each wherever available. The entire Irish Arabidopsis thaliana collection, consisting of 529 samples that represent 150 locations is listed in Table Plants and seeds of Seeds were stratified for 4 days in the dark at 4°C then moved to different growth conditions depending on the experiment. For plate assays (hypocotyl elongation/root length), seeds were sterilized in 1.5 ml tubes in 70% ethanol with 0.1% Triton X-100 for 3–5 min and washed in 95% ethanol for 1–2 min. Seeds were then spotted onto 0.5 × MS media plates. Root length was measured 5 days post-germination and hypocotyl elongation measured 10 days post-germination from photographic images, using ImageJ64 software for Macintosh . Temperature sensitivities in root length and hypocotyl elongation among wild accessions were calculated from regression of hypocotyl/root length onto temperature means (23SD vs. 27SD). The impact of repeat expansion, soil type or the genotype on phenotypes as well as genotype × environment interactions were analyzed using JMP  through appropriate analysis of variance (ANOVA) models. For example, the effect of repeat expansion was assessed using a model with the repeat expansion as the factor and hypocotyl length or temperature sensitivity as a response. Degree of leaf serration was based on a relative scale generated from within the dataset ranging from 1 to 9 Figure . A singlGenotyping of 131 plants, which were bulked, was performed by Diversity Arrays Technology Pty Ltd  as described previously  with 4 independent runs for each K, each run starting with a burn-in period of 100,000 steps followed by 100,000 Markov Chain Monte Carlo iterations. The most probable value of K was selected according to the Evanno method  and assessed for the appearance of the iil phenotype. Among the tested conditions , we did not observe the iil phenotype in any stress condition except for the UV-B exposure  and light (UV-B) alterations.The e Figure . At 23°CC Figure . AnalysiC Figure . Therefoiil phenotype segregates in a Mendelian manner only in certain genetic crosses  but not in others , which suggested the presence of genetic modifiers that can mask the phenotypic impact of the GAA/TTC repeat expansion  from seven geographic locations that contained the s Figure . In somee Figure . Neverthn Figure . To ensun Figure . Thus, wTo determine whether the accessions that carry the repeat expansion are genetically similar to each other, we analyzed the genetic diversity among Irish accessions using DArT-seq , which was also reflected in temperature sensitivity (p < 0.01) , temperature sensitivity in root length  and hypocotyl elongation . In addition, we observed an impact of soil type on root length at both temperatures  and leaf serration  consistent with the observed geographic pattern . However, with the major groups of repeats (9 or 26 repeats) mapping to specific sub-clusters, this could also be explained by a strong effect of population structure. Thus, geographic differentiation and population structure accounts for most of the variation in leaf serration in the Irish accessions.Variation in triplet repeat length, even in their non-expanded ranges, has been shown to be associated with phenotypic differences in other species  and was correlated with an increase in the instability of the repeat expansion. UV-B exposure is known to have many effects on plant growth and development such as decreased plant height, decreased leaf area, reduced stomata number and curling of leaves, as well as an increase in axillary branching . This may simply be a reflection of the iil phenotype, which prevents the plants from reaching the flowering stage and not per se an effect of flowering. However, natural suppressors with reduced numbers of repeats in the Bur-0 background flowered earlier compared to Bur-0 in long day conditions  diversity, and the diversity within the phenotypic traits analyzed. This notion is further supported by the measured phenotypic traits of flowering time, hypocotyl elongation, degree of leaf serration and germination all of which span response ranges similar to those observed between populations from other geographical regions.Our study has generated a new collection of genotyped strains from an island population that is suitable for studying natural variation in ruderal plants. We have also provided evidence that the Irish population displays both genotypic and phenotypic diversity, as other regional populations . Analyzed Date . Computational analysis of the data . Wrote the manuscript . Designed and Supervised the study (CS and SB).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Sotalia guianensis is a small dolphin that is vulnerable to anthropogenic impacts. Along the Brazilian Atlantic coast, this species is threatened with extinction. A prioritized action plan for conservation strategies relies on increased knowledge of the population. The scarcity of studies about genetic diversity and assessments of population structure for this animal have precluded effective action in the region. Here, we assessed, for the first time, the genetic differentiation at 14 microsatellite loci in 90 S. guianensis specimens stranded on the southeastern Atlantic coast of the State of Espírito Santo, Brazil. We estimated population parameters and structure, measured the significance of global gametic disequilibrium and the intensity of non-random multiallelic interallelic associations and constructed a provisional synteny map using Bos taurus, the closest terrestrial mammal with a reference genome available. All microsatellite loci were polymorphic, with at least three and a maximum of ten alleles each. Allele frequencies ranged from 0.01 to 0.97. Observed heterozygosity ranged from 0.061 to 0.701. The mean inbreeding coefficient was 0.103. Three loci were in Hardy-Weinberg disequilibrium even when missing genotypes were inferred. Although 77 of the 91 possible two-locus associations were in global gametic equilibrium, we unveiled 13 statistically significant, sign-based, non-random multiallelic interallelic associations in 10 two-locus combinations with either coupling  or repulsion  forces. Most of the interallelic associations did not involve the major alleles. Thus, for either physically or non-physically linked loci, measuring the intensity of non-random interallelic associations is important for defining the evolutionary forces at equilibrium. We uncovered a small degree of genetic differentiation  with a hierarchical clustering into one segment containing members from the southern and northern coastal regions. The data thus support the scenario of little genetic structure in the population of S. guianensis in this geographic area. Sotalia guianensis, is a small dolphin of the Delphinidae family 24, the Sota-11 186 bp allele to [CA]16, the Sota-12 132 bp allele to [GT] 33, and the Sota-13 158 bp allele to [CA]20.We note that the Sota-10 through Sota-14 loci had not been genotyped previously in Sotalia spp. is available for chromosomal mapping of the genetic markers used in this study. There is, however, a genome draft for the common bottlenose dolphin Tursiops truncatus (Baylor Ttru_1.4/ turTru2) [T. truncatus is 42,XX or 42,XY [Tursiops truncatus and Bos taurus  to 42.2% (Sota-02)  . The dipor 42,XY . No chroor 58,XY ) reasonior 58,XY . The strSota-02) . ThirteeSignificant global gametic disequilibrium was limited to 14 out of the 91 possible two-locus combinations . The numD´ coefficients between all possible two-locus combinations to uncover coupling (D'(+)) or repulsion (D'(-)) non-random interallelic forces at disequilibrium. Twelve possible two-locus combinations exhibited at least one significant interallelic association  and 3 with repulsion  forces. Except for one allele pair in the Sota-05/Sota-13 two-locus combination, the interallelic associations did not involve the major alleles from both loci. The only syntenic two-locus non-random interallelic association observed was between Sota-02*208 bp and Sota-05*232 bp on chromosome 5, and the allele pair included the most frequent Sota-02 allele.Recombination events represent an important evolutionary process determining gametic equilibrium. Thus, we measured interallelic ociation . Thus, tST = 0.010; P-value = 0.463; 95%CI: -0.000–0.026, for 30,000 random replicates). Second, we employed Bayesian clustering analysis to reveal that all the genotypes clustered in one segment with no significant separation between southern and northern designations. One segment was observed by setting the possible number (K) of clusters from 1 to 10 (Posterior probabilities ranged from 1 to 0.1). Lastly, we estimated the Nei’s genetic distances at the 14 microsatellite loci, grouped the individual genotypes by similarity using hierarchical clustering, and displayed the similarity in a dendrogram  at ten microsatellites, five of which were also genotyped in our study.We show that a sampling of 90 Guiana dolphins stranded in the Atlantic coastal area of the State of Espírito Santo, Brazil, composes a population with little genetic structure. The evidence is three-fold: a low degree of genetic differentiation, low inbreeding coefficients, and clustering into one segment containing members from the southern and northern coastal regions. Our study is the first to assess the genetic diversity of , Brazil , also shS. guianensis that used the same primer sets [T. truncatus, the same locus exhibited eight alleles [S. guianensis.Decreased locus diversity is often seen when using heterologous primer sequences  . Here, wmer sets , 43, 45. alleles . Our datTursiops truncatus, Tursiops aduncus, Cephalorhynchus eutropia, and Stenella frontalis) have reported FST values ranging from 0.034 to 0.20 with varying sample sizes [Genetic studies in other dolphin genera  3-fold excess of male specimens in our samples. This imbalance may be due to anthropogenic actions, such as fishing activities. The majority of dolphins in fishing-net accidents are young and male [Other factors, however, may influence the structure of a cetacean population: the distribution of prey , 77, socand male , which iA second important aspect of our study addresses the prospective application of the syntenic map of the microsatellite loci for kinship analyses. It is evident in other biological systems , 82 thatS1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.


Current professional society guidelines recommend genetic carrier screening be offered on the basis of ethnicity, or when using expanded carrier screening panels, they recommend to compute residual risk based on ethnicity. We investigated the reliability of self-reported ethnicity in 9138 subjects referred to carrier screening. Self-reported ethnicity gathered from test requisition forms and during post-test genetic counseling, and genetic ancestry predicted by a statistical model, were compared for concordance.We identified several discrepancies between the two sources of self-reported ethnicity and genetic ancestry. Only 30.3% of individuals who indicated Mediterranean ancestry during consultation self-reported this on requisition forms. Additionally, the proportion of individuals who reported Southeast Asian but were estimated to have a different genetic ancestry was found to depend on the source of self-report. Finally, individuals who reported Latin American demonstrated a high degree of ancestral admixture. As a result, carrier rates and residual risks provided for patient decision-making are impacted if using self-reported ethnicity.Our analysis highlights the unreliability of ethnicity classification based on patient self-reports. We recommend the routine use of pan-ethnic carrier screening panels in reproductive medicine. Furthermore, the use of an ancestry model would allow better estimation of carrier rates and residual risks.The online version of this article (10.1186/s12863-017-0570-y) contains supplementary material, which is available to authorized users. High throughput technologies like microarrays and next generation sequencing permit the simultaneous interrogation of multiple disease-causing mutations in many genes, allowing expanded carrier screening for almost any disease to be routinely used in medical practice. In contrast, some professional guidelines still recommend carrier screening for certain mutations based on ethnicity –3 and phEthnicity is defined as the membership in a specific group sharing cultural, religious, or racial traits , while gThe incidence of several monogenic diseases varies widely across different populations: Asian Americans account for over 50% of thalassemia cases in the US , AfricanIn order to determine the reliability of self-reported ethnicity for clinical decision-making, we compared two sources of self-reported ethnicity, written and verbal, with genetic ancestry as estimated by a statistical model, from a cohort of 9138 patients undergoing genetic carrier screening. Additionally, the relationship between disease carrier status and genetic ancestry within self-reported ethnic groups was studied. Our results indicate that self-reported ethnicity is not a reliable source on which to base clinical decisions.Our study population included 9138 patients undergoing genetic carrier screening, who were referred from fertility specialists, obstetricians/gynecologists, and genetic counselors. Eighty-six percent of the samples were from US clinics, eighty-six percent from Spanish clinics and the remainder from other countries. Before undergoing in vitro fertilization, couples in fertility clinics were offered CarrierMap , a genetic test that determines carrier status for 311 autosomal recessive or X-linked genetic diseases. Informed consent to perform this research was obtained during sample requisition, and confirmed during the genetic counseling session that all patients are offered when CarrierMap results are reported to them. All data presented here is de-identified (HHS 45 CFR part 46.101(b)(4)).Participants’ ethnicities were self-reported at two separate points in the testing process. The initial report was gathered on the test requisition form, where patients were asked to select all ethnicities that apply from the following list of options (chosen by reviewing the literature): African; East Asian; European; French Canadian; Jewish; Latin American; Mediterranean; Middle Eastern; Native American; South Asian; Southeast Asian; Other  genotyping platform using standard protocols recommended by the manufacturer.In order to estimate the genetic ancestry of our samples, we modified the Expectation Maximization (EM) Algorithm used in FRAPPE , 19. We We obtained allele frequencies for all populations and SNPs in the ALFRED database . This da2 of 0.5 and a window size of 1000 to get a final list of SNPs that are in linkage equilibrium [Next, we filtered the list of markers to include only biallelic SNPs existing in Illumina’s Infinium CoreExome-24. We also removed any SNP with a call rate lower than 99.9%. Finally, since the EM algorithm assumes independence of each locus, we used Plink’s pairwise independence command with an Rilibrium . The finIn order to reduce the full list of SNPs to only those that are informative of ancestry , we used Wright’s Fst measure . InsteadI) and a set of six ancestral populations (K), a vector Qi =  is estimated for each individual (i). Each coordinate in the vector Qi is an estimate of the probability that a random allele from i originates from population k. Our dataset contains genotypes for all i at the 1142 AIMs we selected (M). Each individual’s genotype is captured in a column vector gi, where each entry gim holds the number of copies of “allele 1” at marker m for individual i. The choice of which allele is “allele 1” is arbitrary as long as it is consistent across samples. Departing from FRAPPE, we also have a computed matrix of allele frequencies across populations (F). In this matrix, element fkm holds the allele frequency of marker m in population k.The model was formalized in a similar manner to FRAPPE and ADMIXTURE , 19. ForQi is independent and equal toThe log-likelihood of each sample’s vector The Expectation Maximization algorithm updates the parameters via the maximization step:These steps are repeated until the estimation converges. Namely, once:ε = 0.01) and still retain an acceptable computation time.Since we are not estimating the population allele frequencies, we can choose strict stopping criteria . Similarly, there were significant discrepancies in the requisition form vs. consult for Native American, Jewish and European ethnicities. These differences suggest that the manner in which self-reported ethnicity is collected affects what is reported.Some of the groups had very consistent patterns of identification across both self-reported sources. For example, 92.7% of patients that selected African on the requisition form identified having African ancestry during the consult, while 95.5% of patients that identified having African ancestry during the consult also selected African on the requisition form. Other groups showed more complex patterns of self-identification. For example, 89.6% of patients that selected Mediterranean on the requisition form also identified it during the consult, while only 30.3% of patients that reported having some Mediterranean ancestry during the consult actually selected it on the requisition form . Similarly, the mean European ancestry of Latin American patients identified as carriers of cystic fibrosis is 59.4% while the mean European ancestry of non-carriers is 51.9% (P = 0.03). Finally, the mean European ancestry of African carriers of GJB2-related nonsyndromic hearing loss is 23.0%, while the mean European ancestry of non-carriers is 12.2% (P = 0.01).In order to better understand how genetic ancestry estimates within self-reported ethnic groups impact clinical estimates of risk, we investigated the relationship between carrier status of cystic fibrosis, sickle cell anemia, and GJB2-related nonsyndromic hearing loss and predicted ancestry among self-reported African and Latin American patients. These diseases were chosen because they are common and strongly associated with specific ancestral groups. We found significant differences in carrier risk based on genetic ancestry , and include all mutations described for a given disease, present in different populations. Additionally, targeted next generation sequencing can be used to detect novel or poorly described mutations in genes of interest. While, pan-ethnic panels have some disadvantages , 32, givA second conclusion from this study is that, since carrier rates, detection rates and residual risks vary based on ancestry, in order to accurately counsel patients about their reproductive risks, genetic ancestry should be determined in clinical practice. Prior reports also describe sets of Ancestry Informative Markers (AIMs) that could be used to determine genetic ancestry, although further work is needed to ensure that allele frequency estimates are representative of all populations and that the ancestry estimates are meaningful for all individuals –38.Limitations of the present study include that the data was studied retrospectively using the records of a clinical carrier screening company. Self-reported ethnicity from requisition forms was entered into the database during sample accessioning on a rolling basis. It is possible that some of the records were entered incorrectly or later modified by genetic counselors. To ensure accurate measurement, we manually reviewed several hundred scanned requisition forms: both randomly and in cases where discordance between self-reports and genetic ancestry was found. Reviewing records randomly showed that less than 1% of the self-reported labels were incorrect in the database. Another limitation is that our genetic ancestry model is based on allele frequency estimates from a limited sample size and assumes that grouping individuals by continent provides meaningful estimates of origin. A better way would be to account for subtle differences in genetic ancestry among local subpopulations, however, this would require expanded screening platforms and increased resources. Despite these limitations, we were able to correctly estimate the origin of validation samples from the 1000 Genomes Project and we found a strong relationship between carrier rates and ancestry proportion in admixed populations. This shows that the ancestry model provides meaningful information. Further work with larger cohorts is needed to refine the ancestry model and to measure the relationship between carrier rates and genetic ancestry for more diseases. Additionally, in diseases where environmental factors are known to play a part, further work is needed to understand how much impact ancestry has versus social and cultural influences of an individual’s self-identified group.Estimates of carrier rates and residual risks depend on whether self-reported ethnicity or genetic ancestry is used to account for population differences. Furthermore, self-reports are not reliable for clinical decision-making. In order to mitigate the risk of ordering the wrong testing panel, we recommend the use of expanded pan-ethnic carrier screening panels. Additionally, in order to accurately estimate carrier rates and residual risks, we recommend the use of a genetic ancestry model in clinical genetic testing.Additional file 1:Requisition form used in this study. (PDF 287 kb)Additional file 2:Supplementary tables. (XLSX 39181 kb)Additional file 3: Figure S1.Plot of the first and second principal components obtained by Principal Component Analysis on 44 geographic groups (described in Additional file