Pocillopora have been more intensively studied than those of any other reef-building taxon. However, recent investigations have revealed that the current morphological classification is inadequate to represent genetic lineages. In this study, we isolated and characterized novel microsatellite loci from morphological Pocillopora meandrina (Type 1) and Pocillopora acuta (Type 5). Furthermore, we characterized previously reported microsatellite loci. A total of 27 loci (13 novel loci) proved useful for population genetic analyses at two sites in the Ryukyu Archipelago, in the northwestern Pacific. Clonal diversity differed in each genetic lineage. Genetic structure suggested by microsatellites corresponded to clusters in a phylogenetic tree constructed from a mitochondrial open reading frame (mtORF). In addition, we found an unknown mitochondrial haplotype of this mtORF. These microsatellite loci will be useful for studies of connectivity and genetic diversity of Pocillopora populations, and will also support coral reef conservation.Population genetics of the coral genus  Pocillopora, especially Pocillopora damicornis, is the most studied reef-building coral in terms of population genetics9. This genus includes both broadcast-spawning and brooding species10 and it is distributed from the Indian Ocean to the East Pacific. In Pocillopora, 17 species are currently recognized in Veron11 and in Coral of the World , while 22 species are registered in the World Register of Marine Species (WoRMS) (http://www.marinespecies.org/), as of March 2017. However, based on gross morphology, the number of Pocillopora species may be overestimated12, because recent genetic studies have suggested that the traditional classification may not correspond to genetic species15. Nevertheless, 16 or more genetic lineages of Pocillopora have been considered as putative species based on haplotypes of a mitochondrial DNA region15 and genetic structure analyzed using microsatellite markers15.The genus 16, Japan. A recent phylogenetic approach confirmed six lineages of Pocillopora in the northwestern Pacific12. Pocillopora corals have been damaged by various global and local anthropogenic disturbances, and coral populations have not yet recovered from repeated mass bleaching events since 1998 at reefs in the Ryukyu Archipelago17. Population genetics studies using genetic markers make it possible to distinguish invisible inter- and intraspecific relationships among populations. These studies have estimated genetic diversity, differentiation among locations, reproductive characteristics, and species delimitations for various organisms, including corals. Microsatellites, composed of tandemly repeated regions of nucleotides are highly polymorphic among individuals and chromosomes. Next-generation sequencing technology has facilitated development of microsatellite loci, which have recently been developed for reef building corals19.Approximately 400 reef-building coral species inhabit the Ryukyu ArchipelagoPocillopora in the Ryukyu Archipelago. Although microsatellites have been already reported in Pocillopora, we developed additional markers to widen the choice of markers for population genetics analyses between and within lineages. We developed 13 additional microsatellite markers from morphological Pocillopora meandrina and Pocillopora acuta colonies. In addition, we validated and characterized microsatellites previously reported from Pocillopora for populations in the Ryukyu Archipelago. Those were developed by Magalon et al.20, Magalon et al. unpublished, and Starger et al.21 and recently, more loci have been isolated by Pinzón & LaJeunesse13 and Torda et al.8. Gorospe & Karl22 re-designed primers for two loci, PV7 from Magalon et al.20 and Pd3-010 from Starger et al.21 and designated them as Pd2-AB79 and Pd3-EF65, respectively. Using all of these validated microsatellite markers, we genetically characterized populations from multiple lineages of Pocillopora from Ueno and Yoshino, Miyako Island, in the Ryukyu Archipelago.In this study, using next-generation sequencing, we developed cross-lineage microsatellite loci in order to facilitate population genetic analyses for multiple lineages of P. meandrina and 7,021,083 reads comprising 2,056,539,596 bp for P. acuta) from sequence data derived from genomic DNA. These were used for microsatellite detection and primer design. MISA and Primer3 were employed to identify 1,597 reads with primer sequences, including repeats under the following conditions . After removing incomplete or extremely long repeats to facilitate fragment analysis, 752 reads remained . Of these reads, we selected 50 with homologous repeat sequences and flanking regions, from P. meandrina and P. acuta, to be employed as cross-lineage microsatellite loci. Based on the genetic delimitation and definition by Pinzón et al.10, these morphological colonies displayed Type 1 and Type 5 mitochondrial open reading frames (mtORF), respectively. The nuclear ribosomal internal transcribed spacer 2 (ITS2) sequence from the Type 1 colony was ITS2 type T (see below).We successfully merged single sequences , PV5, PV620, Pd3-002, Pd3-01021, or Pd138, which have been widely used in other population genetics studies. However, redesigned primer sequences targeting flanking regions identified in databases, such as Gorospe & Karl22 may have improved amplification of the loci, PV7 and Pd3-010. Actually, Pd3-010 was not useful, but Pd3-EF65 by virtue of nested primer sets, was useful even though it targeted the same locus as Pd3-010. Previously reported loci appear to be effective for populations in the Ryukyu Archipelago  are shown in Table PID ranged from 3.3e–26 to 1.5e–20 (Table p > 0.05) in any microsatellite locus pairs after removal of replicate loci (PV7 is the same locus as Pd2-AB79). Novel microsatellite loci developed here are derived from the nuclear region since it exhibits only moderate heterozygosity and one or two peaks in fragment analysis, excluding scoring errors. Also, polymorphism of zooxanthella loci was confirmed in the same multilocus lineage (MLL). These loci will facilitate combining multiple loci for effective multiplex PCR.We confirmed that 13 non-overlapping loci could produce sufficient PCR amplification in all genetic lineages, based on mitochondrial haplotypes derived from fragment analyses , which differed by 5 bp. A maximum likelihood phylogenetic tree based on mtORF haplotypes was constructed  at the Ueno site, and haplotype groups of mtORF  at the Yoshino site. Furthermore, Type 1 was separated into two haplotype groups based upon ITS2. At least six lineages of et al.10. Using the method of Evanno et al.24 to determine the most probable number of genetic populations (K), the largest peak of ΔK was K = 3 . Some MLLs in mtORF Type 5 were assigned to the cluster containing Type 4. However, there was only one mtORF Type 4 sample. Further studies with additional samples are needed to fully distinguish these two lineages. Also, when K ≥ 6 in STRUCTURE analysis, definite genetic structure was detected, even between sites within mtORF Type 5, despite the close geographic proximity of these populations, ~17 km along the coast. Thus, genetic structure even in the same genetic lineage at fine geographic scale could be confirmed in a brooding species25. In part, genetic differentiation within a given lineage may reflect differences of water depth (<~17 m) between sites.Genetic structure among genetic lineages separated on the basis of mtORF and based on 27 microsatellite loci  and may provide useful information about coral population genetics in general. By sampling a greater number of specimens across a larger geographic area, these microsatellite loci will be beneficial for population genetics within and between Pocillopora lineages in various localities. They will be helpful to understand genetic structure and population dynamics at contemporary and historical time scales, and for parentage analysis, identification of evolutionary lineages, and genetic diversity to understand maintenance of coral populations.In conjunction with primers developed previously, these new primer pairs also may be used for a variety of Pocillopora in the Ryukyu Archipelago. mtORF Type 5 obtained at two sites for validation of microsatellites indicated large number of clonal replicates, especially in Ueno. We detected distinct genetic structure among lineages, as estimated from mtORF haplotypes . Although Schmidt-Roach et al.12 reported that at least six lineages of Pocillopora inhabit the northwestern Pacific region, this study indicated that all six occur in the Ryukyu Archipelago, despite sampling only two sites. We confirmed one more lineage with an unknown haplotype in this region. Additional genetic diversity may be discovered in this region by extending the number and geographical distribution of sampling sites. More extensive analyses of genetic diversity and connectivity in within and between populations will be needed to better understand population maintenance and dynamics for conservation and management of coral reef organisms.This study suggested that 13 new and 14 previously reported loci are useful as cross-lineage microsatellites for population genetic analyses of P. meandrina and P. acuta, along the western coast of Okinawa Island in the Ryukyu Archipelago, a subtropical area located in the northwestern Pacific Ocean, Japan. These belonged to mitochondrial open reading frame (mtORF) Type 1 and Type 5 (see Results and Discussion). Specimens were preserved in ethanol and genomic DNA was extracted using a DNeasy Blood & Tissue Kit (Qiagen) following the standard protocol. We sequenced 250-bp paired-end reads using a MiSeq sequencer (Illumina) according to the manufacturer’s instructions. After merging single-end sequences using PEAR ver. 0.9.826, to isolate reads of 100 bp or more having repeat sequences of P. meandrina (Type 1), we used MISA (http://pgrc.ipk-gatersleben.de/misa/) to detect simple sequence repeats and to design PCR primers using Primer3 (http://pgrc.ipk-gatersleben.de/misa/primer3.html). We searched P. acuta (Type 5) using BLAST+ ver. 2.3.027. We confirmed that sequence regions, including microsatellites, were conserved between the two lineages.We collected branches from the morphological species, Pocillopora colonies were collected at Ueno  and Yoshino  at Miyako Island at the Ryukyu Archipelago, Japan. Genomic DNA was extracted from preserved coral branches as described above. Mitochondrial haplotypes were confirmed by sequencing the mtORF region28. PCR reaction mixtures consisted of: (10 μL) containing <30 ng/μL template DNA, AmpliTaq Gold 360 Master Mix (Thermo Fisher Scientific), and the primers  for mtORF: FATP6.1 (5ʹ-TTTGGGSATTCGTTTAGCAG-3ʹ) and RORF (5ʹ-SCCAATATGTTAAACASCATGTCA-3ʹ)29. The PCR protocol consisted of 94 °C for 1 min, followed by 40 cycles at 94 °C for 30 s, 53 °C for 30 s, and 72 °C for 75 s, with a final extension at 72 °C for 5 min. After reaction of Exonuclease I (Takara) and Shrimp Alkaline Phosphatase (Takara) to clean up PCR products, sequencing was conducted by Macrogen Japan.To confirm validation and polymorphism of microsatellite loci, branches from 90 29 including unpublished work of Mayfield et al., using MUSCLE in MEGA ver. 6.0630. The molecular evolution model was selected by MEGA, and the best model was determined to be the HKY (Hasegawa-Kishino-Yano) model with a gamma distribution of rate variation across sites (+G). Rapid bootstrap analysis employing the maximum likelihood method for phylogenetic analysis was carried out using MEGA with the model using 1000 bootstrap replicates. The phylogenetic tree was drawn in FigTree ver. 1.4.2 (http://tree.bio.ed.ac.uk/software/figtree/).mtORF sequences obtained were aligned with others from previous studies29. PCR reaction mixtures comprised: (10 μL) containing <30 ng/μL template DNA, AmpliTaq Gold 360 Master Mix, and primers  of ITS2: ITSc2-5 (5ʹ-AGCCAGCTGCGATAAGTAGTG-3ʹ) and R28S1 (5ʹ-GCTGCAATCCCAAACAACCC-3ʹ)29. Conditions for PCR and sequencing were the same as for mtORF.The nuclear ribosomal internal transcribed spacer 2 (ITS2) was used for identification of less differentiated genetic lineages within Type 1Pocillopora previously developed by Magalon et al.20, Magalon et al. (unpublished), Starger et al.21, Pinzón & LaJeunesse13, Torda et al.8, and two loci modified by Gorospe & Karl22. For scoring of microsatellite genotypes of each colony, the PCR reaction mixture (5 μL) contained template DNA (<30 ng/μL), AmpliTaq Gold 360 Master Mix, and three primers for each locus: a non-tailed reverse primer (0.5 μM), a forward primer with a sequence tail of U19 (5ʹ-GGTTTTCCCAGTCACGACG-3ʹ) (0.5 μM), and a U19 primer (0.5 μM) fluorescently labeled with FAM, VIC, NED, or PET31. The PCR protocol consisted of 95 °C for 9 min, followed by 35 cycles at 95 °C for 30 s, 56 °C for 30 s, and 72 °C for 1 min, with a final extension at 72 °C for 5 min. We furthermore conducted PCR using microsatellites for zooxanthellae, C1.0232, SymC_3-02, SymC_3-0333, and D1Sym1134 within the same MLL to confirm that the microsatellites were derived from nuclear loci, since different symbiont genotypes have been detected from the same MLL in Pocillopora35. PCR conditions were the same as for microsatellites from colonies, except for the annealing temperature (50 °C for 4 zooxanthellae microsatellites). PCR products were analyzed using an ABI 3730 capillary DNA sequencer (Thermo Fisher Scientific) with the GeneScan 600 LIZ size standard (Thermo Fisher Scientific) to identify genotypes by the length of the amplicon. Fragment size and intensity were confirmed using Geneious ver. 9.0.4 (Biomatters).Together with novel microsatellite loci developed here, we characterized loci for 36. If genotypes of ≤3 loci differed and all other loci coincided, a colony was considered to be clonal, derived by asexual reproduction. Either a scoring error or a somatic mutation was assumed to be responsible for the variable locus/loci. The number of different loci was calculated using GenAlEx ver. 6.50137. When different genotypes were determined to belong to the same MLL, the most common genotype was assigned38. However, if the most common genotype could not be determined , the genotype was set to zero39. We also calculated PSEX to estimate the possibility of coincidence of multilocus genotypes by sexual reproduction, using GenClone ver. 2.040. After removing clonal replicates from the data set, the number of alleles, values of observed and expected heterozygosity , and deviation index (FIS) from Hardy-Weinberg equilibrium were evaluated for each locus and lineage using GenAlEx. Lineages with few MLLs were not used for calculation of these genetic indices. The probability of identity (PID) was also calculated using GenAlEx to estimate the resolution of loci for each lineage/site. Linkage disequilibrium was estimated for each lineage using Genepop on the Web42.The concept of multilocus lineage (MLL) was employed to avoid underestimating clonality due to genotyping errors and somatic mutations43. A burn-in period of 100,000 followed by 1,000,000 Markov chain Monte Carlo (MCMC) replications was used for population clustering without LOCPRIOR (prior sampling location information) model under the admixture model and assuming independent allele frequencies44. After calculation of the mean log probability, Ln P(D), to estimate the most probable number of genetic clusters, the number of clusters was determined using the method of Evanno et al.24, as implemented in STRUCTURE HARVESTER45. Run data were merged using CLUMPAK46.Genetic structure based on Bayesian clustering was inferred using STRUCTURE ver. 2.3.4Supplementary Table S1


Coryphaenoides mediterraneus, with a focus on the Atlantic–Mediterranean transition. We used nine nuclear microsatellites and the mitochondrial cytochrome c oxidase I gene from 6 different sampling areas. No population genetic structure was found within Mediterranean with both marker types . However, within the Atlantic a contrasting pattern of genetic structure was found for the mtDNA and nuclear markers . When comparing samples from Atlantic and Mediterranean they exhibited high and significant levels of genetic divergence  regardless the genetic marker used. Furthermore, no shared haplotypes were found between Atlantic and Mediterranean populations. These results suggest very limited genetic exchange between Atlantic and Mediterranean populations of C. mediterraneus, likely due to the shallow bathymetry of the Strait of Gibraltar acting as a barrier to gene flow. This physical barrier not only prevents the direct interactions between the deep-living adults, but also must prevent interchange of pelagic early life stages between the two basins. According to Bayesian simulations it is likely that Atlantic and Mediterranean populations of C. mediterraneus were separated during the late Pleistocene, which is congruent with results for other deep-sea fish from the same region.Population genetic studies of species inhabiting the deepest parts of the oceans are still scarce and only until recently we started to understand how oceanographic processes and topography affect dispersal and gene flow patterns. The aim of this study was to investigate the spatial population genetic structure of the bathyal bony fish  Polyprion americanus [Rimicaris exoculata, [Aphanopus carbo, [Antimora rostrata, [Hoplostethus atlanticus, [Coryphaenoides rupestris, [Helicolenus dactylopterus, [Population genetic studies of species inhabiting the deepest parts of the oceans are still scarce compared to shallow or coastal water relatives. The deep-sea is historically described as a stable and homogeneous environment where the existence of barriers to dispersal and gene flow among populations are less evident . Some stericanus ), the hyoculata, ), the bls carbo, ), the blostrata, ) and theanticus, ). Nevertpestris, ) and theopterus, ) show a Although much work is still needed to understand the most important processes and mechanisms affecting dispersal and gene flow patterns in the deep sea, the number of studies relating oceanographic processes and topography with genetic patterns has been increasing in the last years i.e. , 10, 11), 1110, 1Within the Mediterranean Sea, the Straits of Sicily and Messina may function as barriers between the western and the eastern Mediterranean which may influence gene flow of several marine organisms –17. The Within the North Atlantic Ocean the most prominent topographical feature is the Mid-Atlantic Ridge (MAR) located between the Azores and Iceland, rising from abyssal depths to about 800 m below the sea surface. The MAR is interrupted by a major fracture zone, the Charlie–Gibbs Fracture Zone  which is the deepest connection between the north-eastern and north-western Atlantic and influences the pathway of the North Atlantic Current circulation . Due toCoryphaenoides mediterraneus , is a benthopelagic deep-sea macrourid fish that inhabits continental slopes, ocean ridges and seamounts usually at depths between 1000 m and 3000 m [C. mediterraneus, such as on the species early life stages, and the uncertainty of how bathymetry and oceanography affects dispersal potential, greatly limits the knowledge on population connectivity across the species’ range. Therefore, the aim of this study was to characterize the spatial population genetic structure of the bathyal bony fish C. mediterraneus, with special emphasis on the transition between Atlantic and Mediterranean Sea.The Mediterranean grenadier, d 3000 m , 26, altd 3000 m . Despited 3000 m , 29), bud 3000 m , as welld 3000 m . The sped 3000 m , and difd 3000 m , 35. Altd 3000 m . The sped 3000 m , 38) whid 3000 m . Not mucd 3000 m – 42) andC. mediterraneus is neither an endangered nor a protected species.No specific permits were required for the described field studies, since all the specimens used came from scientific cruises only. All specimens from this deep sea species were already dead when arrived on board, since they were fished from great depths. C. mediterraneus were collected from 3 main geographic areas  was collected from a total of 152 specimens in MAR, 90 in ROC and 121 from MED. The MED data includes a set of 28 specimens collected in 2013, which were not included in the genetic screening.® (EaZy Nucleic Acid Isolation) Mag-Bind Tissue DNA kit  with the KingFisher mL magnetic particle processor , according to the manufacturer’s instructions. The mitochondrial cytochrome c oxidase subunit I (COI) was partial amplified (613 bp) for 193 individuals by polymerase chain reaction (PCR) using the FishF2 and FishR2 primers [2O and were conducted under the following thermal cycle conditions: initial denaturation of 2 min at 94°C, followed by 35 cycles of denaturation for 30 s at 94°C, annealing for 60 s at 55°C, extension for 1 min 35 s at 72°C, with a final extension of 7 min at 72°C. No template controls were included to check for possible DNA contamination. Electrophoresis of PCR products was performed on a 1% agarose gel to assure the integrity of the products. Finally, all amplified products were purified using ExoSAP-IT  and sequenced commercially at BMR Genomics . All haplotypes were confirmed by sequencing both the forward and reverse strand for at least one individual per haplotype.Genomic DNA was extracted using the E.Z.N.A. primers . PCR amp® Tissue DNA Kit (OMEGA bio-tek) according to the manufacturer’s instructions. A total of 375 fish were genotyped for 9 nuclear microsatellite loci developed for other related species , 3 μL of dNTPs (1 mM), 1 μL of 10x PCR Buffer (Qiagen) and dH2O to reach the final volume. Thermal cycling conditions consisted in an initial denaturation of 4 min at 95°C, followed by 30–45 cycles of denaturation for 45 s at 95°C, 60 s at the corresponding annealing temperature (Table B in xl (Life Technologies). All genotypes were scored independently by two persons using GeneMapper software .Genomic DNA was extracted using the E.Z.N.A.C. mediterraneus (three from MAR and one from Greenland) were available from Barcode of Life Data Systems , and were used for comparison in the haplotype network. All sequences were aligned using SEAVIEW [Four mtDNA COI sequences of  SEAVIEW  and CLUS SEAVIEW ). A hapl SEAVIEW  and the  SEAVIEW , with NeHn), haplotype diversity (Hd) and nucleotide diversity (π), were calculated for each location. Genetic distance (ΦST) between localities was estimated based on the mean number of pairwise differences among sequences in Arlequin . The ne1.2.; [D  and Fu’s; [D [FS  were conch  in multFDR; [R2  was deteFDR; [R2 ).A Principal Component Analyses (PCA) was performed to visualise the genetic structure in the dataset using Primer software  based op-distances between Atlantic and Mediterranean haplo-groups with 10000 bootstrap replications. Such analyses was also performed between C. mediterraneus and four of its closest relatives  according to mtDNA COI phylogenetic reconstruction [In order to estimate the average evolutionary divergence over sequences, the MEGA software (version 6.0 ) was usetruction , for comHT [HO) and expected (HE) heterozygosity, observed number of alleles and allelic richness  was calculated using FSTAT , the stepwise- mutation model (SMM) and 50 000 simulations.Gene diversity in the total sample (HT ), observon 2.9.3 ) and divon 2.9.3 . Deviati9.3 [FIS , and tession 4.6 ). The FDP-values . Micro-CP-values ) was useP-values  and LosiP-values  were useFST estimator [FST tests was assessed by G-test for allele frequency differences in genepop using 10000 dememorizations and batches, and 10000 iterations per batch. FST was also estimated with Arlequin based on the pairwise differences using 10000 permutations of the data. P-values were evaluated for significance under the FDR approach in multiple tests situations [FST and tested for genetic divergence as described above, before pooling them together.Genetic differences among localities were quantified by stimator , over altuations . The genPCA-GEN  and sigBottleneck software (version 1.2.02 [The n 1.2.02 ) was appΦST and FST tests was estimated using POWSIM (version 4.1 [t) with an effective population size (Ne) of 3000 to yield the desired level of divergence. This Ne value, was chosen to be above the recommended minimum of 2000 , to minimize loss of alleles and its negative effect on power estimates. Both markers were tested independently. The percentage of significant outcomes (P < 0.05) is interpreted as the power of the data to detect the defined level of genetic divergence. A sampling scheme corresponding to the empirical data in each marker was used and the analyses were conducted using 1000 dememorizations, 100 batches and 1000 interactions per batch. Genetic isolation-by-distance (IBD) within the Atlantic was tested for both markers using ISOLDE as implemented in genepop, using 10000 permutations of the data for the Mantel tests. FST and ΦST semi matrices were calculated as specified above and geographic distances were calculated as the shortest possible oceanic path between sampled locations using Google Earth (Google Inc.).Statistical power of the obtained statistically significant results under different true levels of sion 4.1 ), adjustFST and ΦST for comparison purposes. Pairwise Dest values were estimated in GeneALEx [P-values in multiple tests situations were evaluated for significance using the FDR approach.Jost’s D statistics  was calcGeneALEx , using 9ΦST results. The optimal grouping was selected based on largest FCT (variance between groups/ regions) in relation to FSC (variance between populations within groups/regions) values.Population structure was characterized by the hierarchical analysis of molecular variance (AMOVA) using ARLEQUIN based on pairwise differences and 10000 permutations. Multiple groupings of samples were tested, based initially on geographical location (e.g. Atlantic and Mediterranean) and secondly based on PCA and pairwise FST values between the clusters, the study area was divided into 10000 rectangles .Spatial population genetic structure was also investigated by the Bayesian clustering algorithm implemented in Geneland (version 4.0.3 ) runningt) between Atlantic and Mediterranean and long-term effective population size (Ne) of both populations and for both types of markers. Because DIYABC requires the same number of end populations in all competing scenarios, it is not possible to compare directly scenarios that account for the different genetic structure found in the Atlantic with the different marker types  [−9 and 8.0 x 10−8 while all other parameters were left as default. The summary statistics used in the analyses , implemypes see  section.Fig A in : Scenarived data  and the , G = 0)  had the , G = 0) ) value ace table   was on average of 0.54% ± 0.20% (± SE), and the average p-distances between C. mediterraneus and other closely related Coryphaenoides species varied between 5.74% ± 0.95% (C. striaturus) and 11.29% ± 1.31% (C. brevibarbis).For the mtDNA, 193 COI sequences (613 bp) were amplified containing a total of 11 polymorphic sites . From the resulting 10 haplotypes, 3 were singletons. The estimated haplotype diversity was low for the three main geographic regions, varying between 0.119 and 0.409, whereas the nucleotide diversity ranged from 0.0002 to 0.0009, for ROC and MED, respectively . ConsideHO) and expected (HE) heterozygosity were generally low, varying between 0.35 (MAR2 and MED1) and 0.45 (ROC12) for the former, and between 0.37 (MED1) and 0.45 (MAR3) for the later. Allelic richness (Rs) displayed a similar pattern for the three main sampled regions, with no statistical difference in the levels found inside the MED (7.2) compared to ROC  and MAR  over the nine loci was low (0.422), however it varied among loci, from 0.021 (CaraA102) to 0.926 (Crup7). The total number of alleles per locus ranged from 2 (CaraA102) to 35 , after applying the FDR adjustment. Within the Atlantic Ocean, sampling sites exhibit a more complex genetic pattern with low levels of differentiation observed between MAR1 and ROC , and also between MAR2 and MAR3 . However, significant levels of genetic differentiation were found between the two northern (MAR1/ROC) and the two southern locations (MAR2/MAR3)  for the Atlantic samples.Very high and significant pairwise estimates of genetic differentiation between Atlantic and Mediterranean were found (mean The PCA results  show a sFCT), and minimizes the ‘within samples’ variation (FSC). Therefore the best population grouping suggests the separation of the Atlantic and Mediterranean populations. Within the Atlantic MAR1 and ROC are grouped together and are distinct of MAR2 and MAR3, which also are grouped together. In the same way, Geneland analyses revealed three clusters corresponding to MAR1/ROC, MAR2/MAR3 and MED populations  even when removing the two loci showing HW deviations and possible presence of null alleles , therefore the two samples were pooled together in one ROC sampling for further analyses.Regarding the temporal analysis for the ROC samples, no genetic heterogeneity was detected when comparing 2011 and 2012 samples . In contrast, for microsatellites we found no significant genetic structure within the Atlantic  nor within the Mediterranean . No significant separation along the PC2 was found . Also, no evidence of isolation-by-distance within the Atlantic was found . The best AMOVA grouping found was:  , and as the other analyses suggests the separation of the Atlantic and Mediterranean populations  suggesting population expansion. Small Rozas’s R2 values were found for MAR1/ROC and MED , whereas a higher R2 was resulted for MAR2/MAR3 (0.119).For mtDNA COI demographic histories were inferred for MAR1/ROC, MAR2/MAR3 and MED populations independently. No deviations from the neutrality was found using the Tajima’s P > 0.05). However the Wilcoxon tests for heterozygosity deficiency was significant for the two regions, suggesting population expansion  and MED (NMED) did not produce distinct modes regardless the large priors given. All other estimated parameters showed distinct modes  were large  was the best supported with higher posterior probability , with Mediterranean specimens attaining significantly smaller sizes than in Atlantic localities  were statistically different  with both nuclear and mitochondrial markers supporting the existence of significant genetic divergence, or a “genetic break”, between the two basins . Together with the apparent absence of shared mtDNA haplotypes, this suggests highly restricted or no connectivity between populations on either side of the Strait of Gibraltar. Direct exchange across the Strait of Gibraltar by the active dispersal of the movements of grown fish is improbable given the species’ deep vertical distribution [Centroscymnus coelolepis [C. mediterraenus, the roundnose grenadier . Although grenadiers seem to exhibit ontogenetic downward migration, few species have been properly studied and vertical migration distances and timing seem to vary among species [C. mediterraneus, however larvae from Coryphaenoides sp. were collected from epipelagic layers (<200 m) from the Aegean Sea (eastern Mediterranean [Coryphaenoides are reported (C. mediterraeus and C. guentheri), and both species share similar depth of occurrence and population genetic structure , the early life stages collected at Aegean Sea suggest that C. mediterraneus larvae may indeed reach the epipelagic layer. However oceanographic processes, such as upwelling or eddies may also have some role in the transportation of this early life stages to such shallow layers, since their abundance at collections sites was low [C. mediterraneus early life stages can reach layers shallow enough to cross the Strait of Gibraltar, those egg/ larvae have to be viable and adapt to the dramatic differences in the environmental conditions  between Mediterranean and Atlantic. The higher temperatures in the Mediterranean  and in  species –92. Mars species  suggeste species , 95 usinerranean , 97). Si was low , 97. Evean (e.g. ) may alsan .p-distance values between the two C. mediterraneus haplo-groups found (Atlantic and Mediterranean) are much lower (0.54% ± 0.20%) than those found between C. mediterraneus and other closely related Coryphaenoides species analysed (from 5.74% ± 0.95% to 11.29% ± 1.31%). According to the phylogenetic reconstruction using mtDNA COI region [C. mediterraneus is C. striaturus. The estimated p-distance values between these two species are about one order of magnitude higher than those reported herein between the Atlantic and Mediterranean populations of C. mediterraneus. This suggests that the Atlantic and Mediterranean populations of C. mediterraneus should be treated as belonging to the same species. However, the fact that the Mediterranean population appears isolated, together with the size differences , suggest that this population may be on its separated evolutionary path.The estimated I region  the closC. mediterraneus from the Western and Eastern Mediterranean (both types of markers after FDR correction). This finding may be due to the fact that the Strait of Sicily is about 100 meters deeper that the Strait of Gibraltar which may be enough for the C. mediterraneus early life stages easily overpasses this potential barrier. Furthermore, local strong and periodical upwelling processes, , bring s, , with a marked higher level of genetic variability at the southern areas . The resC. mediterraneus populations were found with the tests employed both for mtDNA and microsatellites. The best supported scenario chosen by DIYABC showed elevated modal values of Ne after the Atlantic—Mediterranean separation Click here for additional data file.S2 AppendixC. mediterraneus (Cmed). The file is in fasta format. Haplotypes frequencies: H1-15; H2-108; H3-4; H4-1: H5-2; H6-1; H7-14; H8-49; H9-1; H10-2.This file contains all 10 haplotypes found for mtDNA COI in the studied areas for (FST)Click here for additional data file.S3 AppendixC. mediterraneus (Cmed). The file is in genepop 3 digits format, which is widely used and can be easily converted in other types of files. It contains the genotypes for the 9 nuclear loci screened in the 8 localities studied: MAR1- Northern Mid-Atlantic Ridge; MAR2- Middle Mid-Atlantic Ridge; MAR3- Southern Mid-Atlantic Ridge; ROC- Rockall; MED1- Western Mediterranean; MED2- Eastern Mediterranean.This file contains the microsatellites genotypes for the 375 specimens of (TXT)Click here for additional data file.


Until now, little attention has been paid to the geographic distribution and evaluation of genetic diversity of durum wheat from the Central Fertile Crescent (modern-day Turkey and Syria). Turkey and Syria are considered as primary centers of wheat diversity, and thousands of locally adapted wheat landraces are still present in the farmers’ small fields. We planned this study to evaluate the genetic diversity of durum wheat landraces from the Central Fertile Crescent by genotyping based on DArTseq and SNP analysis. A total of 39,568 DArTseq and 20,661 SNP markers were used to characterize the genetic characteristic of 91 durum wheat land races. Clustering based on Neighbor joining analysis, principal coordinate as well as Bayesian model implemented in structure, clearly showed that the grouping pattern is not associated with the geographical distribution of the durum wheat due to the mixing of the Turkish and Syrian landraces. Significant correlation between DArTseq and SNP markers was observed in the Mantel test. However, we detected a non-significant relationship between geographical coordinates and DArTseq (r = -0.085) and SNP (r = -0.039) loci. These results showed that unconscious farmer selection and lack of the commercial varieties might have resulted in the exchange of genetic material and this was apparent in the genetic structure of durum wheat in Turkey and Syria. The genomic characterization presented here is an essential step towards a future exploitation of the available durum wheat genetic resources in genomic and breeding programs. The results of this study have also depicted a clear insight about the genetic diversity of wheat accessions from the Central Fertile Crescent. Triticum L., a member of the tribe Triticeae, which contains about 300 species [founder crop assemblage’ on which ‘Old World’ agriculture was built [T. dicoccum to take place as the major cultivated form of allotetraploid wheat based on the studies of restriction fragment length polymorphism data (RFLP) [Cultivated wheats and their close wild relatives belong to the genus  species . Durum was built ,3. Durumas built  and repla (RFLP) . Southeaa (RFLP) .Geographical expansion of durum wheat was intimately associated with human migrations. It is cultivated mainly in the marginal areas of Mediterranean region, Southern Europe, and North Africa, while more recently it has started to expand to Southern Asia. It played a critical role in the food of local people of Mediterranean Basin, where about 75% of the world’s durum wheat is produced . Here, dThe genetic diversity analysis of plants is a critical component of plant genetics, breeding, conservation and evolution . HoweverMore recently, a novel approach named genotyping-by-sequencing (GBS) has been developed to perform simultaneous SNP discovery and genotyping . The GBSThe Fertile Crescent, particularly the Eastern Mediterranean area, is considered to be the fundamental center of wheat domestication and diversity . Albeit A diversity panel was assembled comprising of DNAs of durum wheat landraces representing the various geographical regions of Turkey and Syria . The durum wheat landraces originated from a wide range of ecological conditions of soil, temperature and water availability, representing the natural distribution of durum wheat from Syria and Turkey. 91 durum wheat landraces including 32 landraces collected from various geographical areas of Syria and 59 landraces belonging to different climatic zones of Turkey were used as plant material. The collected set of durum wheat landraces used in this study represents the samples collected by the ICARDA plant genetic resources team, which are preserved at ICARDA gene bank, Aleppo, Syria. All the data about the origin, collection site, and passport information are shown in -1.Genomic DNA was obtained from each single selected plant of each landrace according to CTAB protocol  with som-1 was sent to Diversity Array Technology (http://www.diversityarrays.com/) for SNP and DArTseq analysis following the protocol as described by [Genotyping by sequencing analysis of the 91 durum wheat landraces was performed by using a whole genome profiling service for SNP and DArTseq markers. 100 μl of 50 ng μlribed by . Raw seqAll the images from DArTseq and SNP platforms were analyzed using DArTsoft v.7.4.7 . The DArTseq and SNP markers were scored using DArTsoft as binary data (1/0), indicating the presence or absence of a marker in the genomic representation of each sample as described by Akbari et al. . The DArDArTseq and SNP markers obtained for each landrace were used to calculate the genetic diversity using the statistical software ‘R’. Genetic distance among the durum wheat landraces was measured from the proportion of shared alleles obtained from DArTseq and SNP marker data set by using Jaccard similarity index and transformed into distance by using the vegdist function of vegan package in R. Correlation matrices between the both marker systems were determined by using the Mantel test as implemented in the ape package of statistical software program ‘R’ employing 10,000 random iterations in the non-parametric test calculator.Pair-wise genetic distances among durum wheat landraces was used to construct the Neighbor Joining trees using the ape package implemented in R. The computer software MEGA 6.0  was usedIn order to have a clear picture about the genetic structure of durum wheat landraces collected, we applied the Bayesian model-based clustering algorithm implemented in the STRUCTURE software. Admixture and shared allele frequencies model was used to determine the number of clusters (K) in the range from 1 to 12. For each run, the initial burn-in period was set to 500 with 500,000 MCMC (Markov chain Monte Carlo) iterations, with no prior information on the origin of individuals. The ΔK method was used to determine the most suitable value of K as implemented in Structure Harvester .ST values. Adonis function of the vegan package was used as an alternative to AMOVA  to estimate the variance between populations of both regions.Turkish and Syrian landraces were grouped in two populations (Turkey and Syria). Differentiation and significance levels were assessed by calculating the pair-wise FA total of 56,334 DArTseq markers were generated for the 91 landraces representing different ecological and geographical areas of Turkey and Syria. The chromosomal locations of some DArTseq markers  have been provided by the Diversity Array Technology, Pvt, Ltd, Australia. However, most of the DArTseq markers have been reported first time in these accessions and their chromosomal location have not been described yet. A total of DArT 39,568 markers showed polymorphism and were used for further analysis. The overall polymorphism information contents (PIC) of the DArTseq markers was 0.265 and the median 0.000. The distribution of DArTseq markers according to their PIC values is shown in The DArTseq marker data set was used to calculate the Jaccard genetic distance index values among the 91 durum landraces. The average genetic distance among all landraces was 0.494 and the highest genetic distance (0.687) was calculated between a Turkish landraces “Gumushane” and Syrian landrace ‘”Hama_2”, while the minimum genetic distance (0.0486) was found between the Turkish landrace “Konya_4” and a Syrian landrace “AlHasakah”. A dendrogram was constructed for all the landraces based on the Jaccard genetic distance. DArTseq based Neighbor joining analysis grouped all durum landraces into 3 clusters, A, B and C. Cluster A harbored 18 landraces (15 from Turkey and 3 from Syria), and cluster B consisted of 11 landraces with 7 from Turkey and 4 from Syria. Cluster C is a heterogeneous group with the rest of landraces . There wAfter we got an idea about the diversity among the landraces of each country, we estimated the genetic distances among the pairs of landraces between each country and we found that both countries have the same level of genetic diversity and there was no clear differentiation among the landraces of both countries. The average genetic distance between Turkish and Syrian landraces was 0.494. Mean Jaccard genetic distance among Turkish landraces was 0.492 and it was slightly higher for Syrian landraces (0.496). When we talk about the genetic distance among pairs of landraces within each country, the genetic distance ranged from 0.065 to 0.658, whereas in the case of Syria, it varied from 0.049 to 0. 687. To have more insight into the landraces grouping and the pattern of variation, principal coordinate analysis (PCoA) was utilized to measure the variation in durum wheat collection based on the DArTseq markers. In our study, first two principal coordinates explained 56% of the total variations . Using tTo have an idea about the population genetic structure of the Turkish and Syrian landraces, Bayesian clustering modeling was used as implemented in STRUCTURE using the DArTseq markers data set. The determination of suitable number of clusters in STRUCTURE analysis is bit tricky task, as there is no clear and repeatable value of K. In order to find the suitable value of K, the number of cluster (K) was plotted against ΔK according to Evanno et al. . The higA total of 20,661 SNP markers were generated by DArT sequencing and used for evaluation of genetic diversity of 91 durum wheat landraces representing the diversity present in Turkey and Syria. As with DArTseq markers, the SNP dataset used in this research was not previously used or mapped for wheat. 9,791 SNP markers were previously mapped and their chromosomal locations were provided by Diversity Array Technology, Pvt, Ltd, Australia. All of the SNP markers were polymorphic and were consistent. However, most of the SNPs (52.6%) reported here are new and their chromosomal locations are still unknown. Several quality parameters have been generated by the DArT software, including polymorphism information contents (PIC), call rate and reproducibility of each marker. PIC value of the SNP markers ranged from 0.011 to 0.5, with an average of 0.302. The frequency distribution of PIC values of the 20,661 SNP markers used in this study is shown in the histogram .Genetic distances (D) were calculated among all pairs of durum wheat landraces, based on the shared-allele distances. The highest genetic distance was detected between the Turkish landrace “Gumushane” and the Syrian landrace “Damascus_4”, with a value of 0.68, while the mean genetic distance was 0.51. We continued with the Neighbor Joining analysis based on the Jaccard genetic distance and all the landraces were grouped into three clusters A, B and C with 18, 11, and 62 landraces respectively . ClusterSNP marker data was also used for estimating the genetic structure of the landraces using the Bayesian clustering model implemented in the computer software STRUCTURE, and logarithm probability relative to standard deviation (ΔK) was used to estimate the optimal value of cluster (K). Population structure of durum wheat landraces from Central Fertile Crescent was explained at different K values ranging from 3 to 5 . Most ofAverage genetic distance among Turkish landraces was 0.516 and ranged from 0.029 to 0.698, whereas in case of Syria, it varied between 0.038 and 0.594. Genetic distance between both countries ranged from 0.025 to 0.680.Comparisons among the clusters derived from DArTseq and SNP markers depicted high association between both markers system  and SNP have proved to be a robust molecular markers used for analysis of genetic diversity and genetic mapping in many crops ,19,20. TDArTseq and SNP markers have not separated Turkish and Syrian durum wheat landraces according to their provenance and did not group them corresponding to their geographical origin. Landraces from Turkey and Syria were mixed in different clusters. In case of SNP analysis, all groups have shown patterns of clustering. Blend of the Turkish and Syrian landraces also explains nearby relationship of the durum wheat genetic resources from both countries. This close relationship among the durum wheat genetic resources of two countries is not surprising, as we clearly know that Karacadağ mountains in south eastern part of Turkey  and NortThe informativeness of the DArTseq and SNP markers was estimated by the Polymorphism information content (PIC). PIC provides the information about the diversity of a gene or DNA segment in a population which is used for indicating the evolutionary pressure on the allele and the mutations in a locus that might have happened over a time period. PIC value is calculated as a maximum of 0.5 when a marker is scored as 50% of 0 and 50% of 1. Average PIC values of the all DArTseq and SNP markers were 0.265 and 0.302 respectively. Overall, the distribution of PIC values was asymmetrical and skewed towards the lower values in both markers systems. We were not able to compare PIC values as there are only few reports on genetic diversity using DArT and SNPs and we could not trace any report using DArTseq markers in genetic diversity studies in durum wheat. Average PIC values obtained in our study by both markers systems were higher than the PIC value obtained by Ren et al.  studied In addition to the PIC value, some other quality parameters, such as call rate and reproducibility of the each marker within the panel of diverse landraces were also estimated. Call rate is the percentage of valid scores in all possible scores for a marker, where reproducibility is the measured in percentage of reproducibility of the scoring for replicated samples.We described here a whole genome analysis of population structure among single selected plants from each durum wheat landrace representing the diversity of Turkey and Syria. The grouping of the landraces based on the Bayesian model showed the same results as reflected in Neighbor Joining analysis and Principal coordinate analysis. Groups A and B of cluster analysis Figs  and 3B cIn order to see whether or not genetic distance or genetic diversity is correlated with eco-geographical coordinates, we have conducted mental test to have a clear picture about the pattern of variations among landraces . It was This is the first report of a DArTseq analysis results for durum wheat landraces from the Central Fertile Crescent. The results illustrated here present an advantageous starting point for future genomics studies in durum wheat for trait of interest. Genomic selection has an advanced breeding tool that holds great potential for plant breeding, but which depends on a large number of molecular markers and having a relatively well-balanced genome-wide coverage . The rapOne of the most promising approaches for trait improvement is the introduction of novel alleles. As a first step, allele mining approaches can be performed in various ways and in different germplasm collections. Therefore, we are conducting country-wide multi-location field experiments with diverse environments for phenotyping the germplasm and are trying to identify the linked markers for genetic dissection of complex traits. In addition, genetic relationships could be used for the selection of parents for inclusion in the breeding program, if no pedigree data available. Here we have randomly selected single plants from each landrace and have provided the genetic diversity in a panel of landraces collected from the area, known as the most genetically diversified area or center of domestication. The information generated here could be used to design breeding programs adapted to local needs. The huge number of available DArTseq and SNP markers, their cost-effectiveness and relatively high polymorphism content are excellent aspects for extensive genome-wide screening for genetic diversity purposes. The results obtained with the DArTseq markers were in good agreement with those obtained with SNP, which might be due the possibility of genotyping 1000s of loci without any previous sequence information. The genetic diversity of the durum wheat gene pool must be further elucidated to facilitate classification, proper maintenance, conservation and utilization of these valuable resources.S1 Table(XLSX)Click here for additional data file.


Cryptobranchus alleganiensis alleganiensis). Hellbenders are broadly distributed throughout river systems in the eastern United States, but are present in specific environmental locations throughout their range. The large range of the species and history of population fragmentation suggest that local and regional processes contribute to the distribution of cutaneous symbiont diversity. Therefore, we characterized the skin and environmental bacterial communities at eight rivers throughout the range of the species. We observed variation among hellbender populations in skin microbial community diversity and proportion of shared operational taxonomic units (OTUs) between animal and river water communities. Among populations sampled, we noted significant clumped OTU turnover  resulting in unique cutaneous communities. In addition, we observed a significant positive correlation between skin community divergence and hellbender population genetic divergence. Host-population skin community dissimilarity did not correlate strongly with distance between sampling locations, indicating a weak spatial effect on the distribution of symbionts. These results suggest that species sorting mechanisms  structure local skin microbial communities in hellbenders. The variation in skin community composition observed among host populations foreshadows a similar pattern in important functional characteristics . Future work should focus on investigating forces shaping microbiome structure in eastern hellbenders, examining functional variation among populations, and evaluating effectiveness of microbiome management recommendations.Multicellular hosts maintain complex associations with microbial communities. While microbial communities often serve important functional roles for their hosts, our understanding of the local and regional processes that structure these communities remains limited. Metacommunity analyses provide a promising tool for investigating mechanisms shaping microbiome heterogeneity, which is essential for predicting functional variation between hosts. Using a metacommunity framework, we examined heterogeneity in the skin microbiome of the eastern hellbender ( Actinobacteria serve as keystone taxa in the gut of humans due to their high degree of ecological connectedness with other members of the microbiota  and regional scales  serve as an ideal model to investigate community structure and distribution patterns of cutaneous microbes. This species has exhibited population declines and low levels of recruitment within the last 30 years . In addition, we assessed the influence of dispersal on local community structure. We predicted a positive correlation between geographic distance and community dissimilarity in response to limits to hellbender dispersal. Finally, we tested for differences in community composition between the two genetic demes and between hellbenders from each population . We expected to observe differentiation between both genetic demes and among each locality (species sorting paradigm) given that host dispersal and environmental heterogeneity can influence skin community assembly in amphibians.Figure 1; Indiana, West Virginia, North Carolina, Tennessee, and Georgia), making sure to include sites across the range for each of the two genetic demes described in We sampled eastern hellbenders between June 18 and July 31, 2014. Our sampling occurred throughout five states . We obtained land-use, latitudinal, and elevational data from publically available GIS databases. We chose to include these layers as they have been previously associated with stream microorganism biogeography  following the protocol described in de novo operational taxonomic units (OTUs) with UCLUST  we removed OTUs that were represented by fewer than 0.005% of the total read count . We alsoWe conducted a series of analyses to explore the skin microbiota of hellbenders. In brief, we evaluated differences in richness and diversity between the cutaneous microbial communities of hellbenders from different populations. In addition, we implemented metacommunity analysis to assess patterns in bacterial OTU distribution across the eastern hellbender metapopulation. Lastly, we assessed differences in community composition between the two genetic demes of eastern hellbenders and among the sampled populations. We performed all statistical analyses in R version 3.2.0 unless otherwise noted.We assessed differences in community richness/diversity between the two genetic demes and among populations, and compared the proportion of shared OTUs between skin and water samples at each population. We calculated richness (observed OTUs) and Shannon Diversity Index values within each sample from the abundance-based OTU table in QIIME. We used richness or Shannon Diversity Index values for each hellbender as dependent variables, genetic deme assignment as a fixed factor, and population as a random factor in negative binomial generalized linear mixed models (richness) or linear mixed models (Shannon Diversity Index). In addition, we assessed pairwise differences in richness and Shannon Diversity Index between all populations using Tukey’s honest significant difference (HSD) tests. We also calculated the proportion of OTUs shared between hellbenders and the corresponding river water samples. We used the proportion of shared OTUs as dependent variables, genetic deme assignment as fixed factor, and population as random factors in a generalized linear mixed model. Lastly, we tested pairwise differences in proportion of shared OTUs between all populations using Tukey’s HSD tests.Coherence is a measure of the number of embedded species absences (gaps within a species range) within an ordinated community matrix. Negative coherence (more embedded absences within the matrix than expected by random chance) indicates a “checkerboard” metacommunity structure. Positive coherence indicates the response of species to a gradient of environmental variation, and denotes the need to evaluate species turnover and boundary clumping to identify structure (Species turnover represents the number of times that one species replaces another between sites. Negative turnover (denoted as lower replacements than expected by chance) is associated with a nested structure while positive turnover (larger replacements than expected by chance) is associated with Gleasonian or Clementsian structures , a value less than one corresponds with an even spaced structure (hyperdisplaced range boundaries), and a value equal to 1 corresponds with a Gleasonian structure (randomly distributed boundaries). We implemented the default ‘r1’ fixed-proportional null model to calculate the significance of the EMS indices calculated. The fixed-proportional model maintains the OTU richness within each locality while filling OTU ranges based on their marginal probabilities. Because we were working with a very large dataset, we restricted permutations to 99 and allowed null matrices to have empty rows and columns as recommended by We assessed the metacommunity structure as described in tructure . Speciesructures . BoundarWe chose to include all OTUs in the analysis even though a high proportion of OTUs in our dataset were rare . While metacommunity analysis was developed for macro-communities with fewer species, it has been effectively implemented to characterize the metacommunity structure of bacterial communities before . As suchFor all community composition comparisons, we transferred the OTU tables and corresponding Newick phylogenetic tree to R, and the package GUniFrac was used to build UniFrac distance matrices  matrices. The derived correlations were compared to correlations originated from 10,000 random permutations.To evaluate the effect of population-level genetic differentiation we conducted correlations between microbial community distances and genetic/geographic distances (Fst). To evaluate population genetic distance, we obtained microsatellite genotype data from n = 5; Buffalo Creek, West Virginia-BuC, n = 5; and Little River, North Carolina-LR, n = 8) and five populations within the Tennessee River Drainage  for a total of 43 hellbender and eight water samples (Supplementary Table SRR5479798-?SRR5479789). A total of 1,656 OTUs were identified across all adult swabs and water samples after filtration and rarefication. Hellbender skin bacterial communities were dominated by a few abundant OTUs. The core microbiome of eastern hellbenders was dominated by nine OTUs belonging to the phyla Proteobacteria, Actinobacteria, Firmicutes, Cyanobacteria, and Verrucomicrobia . OTUs with the highest abundance on the skin of eastern hellbenders were assigned to the family Comanmonadaceae (mean relative abundance: 46.5%), order Stramenopiles (9.4%), and the genus Proprionibacterium (8.4%).We collected samples from three populations within the Ohio River Drainage . Shannon Diversity Index values did not differ between the two genetic demes . We found significant differences in skin community richness and diversity among sampling localities from post hoc multiple comparisons . With respect to the proportion of shared OTUs between individuals and river water, hellbenders from the Ohio River Drainage (mean ± SD: 0.29 ± 0.12) shared a higher proportion of OTUs with the river water compared to hellbenders from the Tennessee River Drainage . Finally, we found significant differences among sampling localities in the proportion of shared OTUs between river water and the skin from post hoc multiple comparisons .Hellbenders from the Ohio River Drainage possessed richer communities  than hellbenders from the Tennessee River Drainage  and positive turnover . In addition, we found significant positive boundary clumping in the distribution of OTUs . Together, these three values indicate a Clementisan pattern in skin microbial metacommunities throughout the eastern hellbender range. We noted significant correlations between hellbender sample ordination scores and elevation  and latitude . However, we did not note a significant correlation between sample ordination scores and HUC 12-level percent forest cover . There was a discernable clumping of OTU boundaries  that separated two major compartments of ordinated samples corresponding mostly to the Blue River, Buffalo Creek, and South Fork of the Holston River (compartment 1) and the Little River, Hiwassee River, Tumbling Creek, Fightingtown Creek, and Fires Creek (compartment 2). However, the boundary between these compartments did not align as expected between the two eastern hellbender genetic demes .The fixed-proportional null model in the EMS analysis revealed that the hellbender cutaneous bacterial metacommunities displayed positive coherence , positive turnover , and significant positive boundary clumping . Within compartment 1, sample grouping is noticeable between hellbenders from the Blue River/Buffalo Creek and the South Fork of the Holston River . Within compartment 2, grouping is noticeable between hellbenders from Fightingtown Creek/Little River and Hiwassee River/Fires Creek/Tumbling Creek . Samples from compartment 1 were collected from sites with higher latitudes , lower elevation (392.56 ± 54.88 vs. 595.33 ± 43.23 m), and lower HUC 12-level percent forest cover (62.94 ± 1.61 vs. 75.39 ± 3.75%) than samples form compartment 2.Within both compartments cutaneous bacterial metacommunities displayed Clementsian structure as evidenced by positive coherence . However, no variation was noted when abundance of OTUs was taken into account . In contrast, a strong difference among sampling localities was noted when comparing microbiome communities using unweighted  and weighted UniFrac distances . PCoA graphs display clear partitioning of points based on population over genetic sub-population for unweighted UniFrac distances  and weak grouping for weighted UniFrac distances . There were significant positive correlations between skin community dissimilarity and genetic distances . There was a weak, but significant, correlation between skin community dissimilarity and distance throughout the range of the species .Composition of the hellbender skin microbiome varied more strongly by population than by genetic deme. Community composition between the two genetic demes varied moderately when based on presence/absence of OTUs alone  between populations. Despite differences in richness, we did not observe significant variation in community diversity  between the two genetic demes or among populations. An absence of variation in community diversity likely resulted from similar patterns of OTU abundances (skewed toward a few abundant OTUs) throughout the range.Clostridium difficile infections . This structure indicates similarities among groups of OTUs in their adaptive trade-offs or tolerances to local environmental factors  and environmental variables may create a gradient of suitable habitat for cutaneous microbial symbionts. Among populations of hellbenders, we have characterized variation in symbiont dispersal and possible physiological constraints/adaptive trade-offs that result in varying patterns of taxonomic turnover . Hellbenders have experienced population reductions due to habitat loss, water quality degradation, harvesting, and disease . RecentlIt is important to evaluate whether captive eastern hellbenders maintain associations with the core microbes identified in this study . Similar microbes are also described as core members of the skin microbiome of wild hellbenders and other amphibians , indicatConservation management can benefit by incorporating microbial barriers into translocation planning as well. Currently, translocation design is performed following recommendations from population genetics studies . HoweverOH-G, JH, and RW contributed in the research design. OH-G performed sample collection, laboratory work, and bioinformatics analysis. Statistical analysis was performed by OH-G with input from JH. The manuscript was written by OH-G with input from JH and RW.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.


Canis lupus familiaris) exists today within hundreds of closed populations throughout the world, each with defined phenotypes. A singular geographic region with broad diversity in dog breeds presents an interesting opportunity to observe potential mechanisms of breed formation. Italy claims 14 internationally recognized dog breeds, with numerous additional local varieties. To determine the relationship among Italian dog populations, we integrated genetic data from 263 dogs representing 23 closed dog populations from Italy, seven Apennine gray wolves, and an established dataset of 161 globally recognized dog breeds, applying multiple genetic methods to characterize the modes by which breeds are formed within a single geographic region. Our consideration of each of five genetic analyses reveals a series of development events that mirror historical modes of breed formation, but with variations unique to the codevelopment of early dog and human populations. Using 142,840 genome‐wide SNPs and a dataset of 1,609 canines, representing 182 breeds and 16 wild canids, we identified breed development routes for the Italian breeds that included divergence from common populations for a specific purpose, admixture of regional stock with that from other regions, and isolated selection of local stock with specific attributes.Through thousands of years of breeding and strong human selection, the dog ( A genomic pattern for breed status classification based on values from 79 globally recognized purebreeds has recently been defined and includes threshold levels from four homozygosity measurements  was founded in 1882 with the registration of the Bracco Italiano pedigree (ENCI). Today, ENCI recognizes 16 different Italian breeds (ENCI), of which 13 are utilized in this study. Additionally, seven local landrace populations, defined as distinct dog varieties unique to a specific geographic region with historically limited breeding populations, are included in this study. The latter are not recognized by any purebred canine registry but, nonetheless, may display a genetic pattern consistent with other purebreeds  range from two to the number of breeds within each cladistic analysis. The optimal K value was determined by maximum likelihood of the subdivision . The breed‐specific F was determined by averaging individual F values for all dogs of a single breed. These values were compared to previously reported purebred genetic parameters  and homozygosity decay rates for each breed were calculated from the IlluminaHD SNP chip genotypes using Plink 1.9  that yielded the lowest residual standard error. Likewise, the ideal structural division (K) was that which resulted in the greatest likelihood. In the case of the New World clade, the Apennine wolf population was included due to the presumed hybridization history with the German Shepherd Dog to produce the Lupo Italiano.Admixture analysis with TREEMIX and structural analysis with fastSTRUCTURE were conducted on each breed group that contains an Italian breed as a separate test of breed relationships. The ideal breed relationship phylogeny was selected based on the number of admixture events .The patterns of relatedness shown in the neighbor‐joining phylogeny and haplotype sharing Figure  are closa Figure . A shareK = 10). Among the livestock flock guardian breeds, several have a unique genetic signature. However, only five of the 12 Mannara's Dogs and eight of the 14 Pastore della Silas express the breed‐specific signatures at a level of 50%. This implies that these breeds are comprised of dogs that vary from a central breed definition and that the long history of strong selection which defines many established breeds is lacking in these populations.Like the New World breed group, the Mediterranean breed group is similarly complex . An underlying genetic signature is present in dogs from several regions including the Saluki from the Middle East, the Central Asian Shepherd Dog, the Anatolian Shepherd from Turkey, and Italian dogs, and to a lesser extent, the Great Pyrenees from France, Caucasian Shepherd from Western Asia, and Pharaoh Hound from Malta  Figure . Early w4.2Herding behavior is suggested to have arisen from multiple geographic and genetic backgrounds (Arnott, et al. The German Shepherd Dog displays significant haplotype sharing with several Mediterranean and other European breeds dated between 1859 and 1867, well before the establishment of the German Shepherd Dog as a unique breed in 1899. These estimated dates likely reflect the influence of a pervasive common livestock dog in continental Europe from which the German Shepherd Dog was formed (Caius, The six Italian herding breeds now cluster paraphyletic to the German Shepherd Dog, along with the previously mentioned Berger Picard, Chinook, Xoloitzcuintli, and Peruvian Inca Orchid. This result is striking given the differences in morphology and behavior between the breeds. Yet, the results make genetic sense. There were eight predicted admixture events in the New World clade based on the TREEMIX analysis, with two of them occurring in the direction from the German Shepherd Dog or Lupo Italiano to the Central American hairless breeds, while five introgression events indicate admixture of the German Shepherd Dog and the European herding breeds. The recurring pattern of a common genetic link to the German Shepherd Dog suggests a breed history that centers around a broadly distributed European herding dog stock, one that has given rise to the German Shepherd Dog, the Italian herding breeds, and the French Berger Picard.4.3The flock guardian breeds of Italy present a surprisingly accurate reflection of human industry. Management of domestic sheep and goats has been a key need since early human occupation, with skeletal remains of domestic caprines and dogs found in the Neolithic settlements of Sicily (Debono Spiteri et al., The data presented in this study link the four flock guardian breeds from peninsular Italy for the first time. Interestingly, while the Maremma Sheepdog displays genetic evidence of breed relationship to the remaining mainland flock guardians, the Mannara's Dog, Mastino Abruzzese, and Pastore della Sila do not show substantial genetic ties to each other. This pattern is distinct from that observed in the German Shepherd Dog, where 12 of the 19 breeds with significant haplotype sharing to the German Shepherd Dog also share with at least one other related breed. This suggests that the Maremma Sheepdog is reflective of the original flock guardian of the region and that, perhaps through the process of transhumance, seeded the distal pastoral flock guardian populations Figure . In factWhile the previous comparison demonstrates genetic relationships between dogs involved in transhumance, the same is lacking in dogs of similar occupation and physical phenotypes for which there is no evidence of seasonal migration. Specifically, haplotype sharing for other European flock guardian breeds demonstrates shared genetic signatures between the Great Pyrenees of France and Spain and the Italian Maremma Shepherd, but no genetic connection between the Hungarian Komondor and Kuvasz breeds to the Italian flock guardian breeds. Similarly, the Fonni's Dog, a flock guardian from the island of Sardinia, does not show a genetic relationship to the mainland flock guardian breeds. Transhumance was therefore a key force for breed formation along the mainland Italian peninsula, Alps, and Pyrenees mountains of France and Spain. However, in Hungary and Sardinia, in the absence of transhumance Pounds, , breed f4.4Human‐driven selection has yielded hundreds of dog breed variants. Utilizing 23 closed dog populations from a distinct geographic location, in‐depth demographic analyses relative to a large cohort of established dog breed populations reveals three modes through which selection has been applied: divergence from a large collection of phenotypically similar individuals; independently through repeated selection for a particular purpose without influence of introgression from other similar breeds; and inclusion of foreign breeding stock with desired traits. The present sampling of Italian breeds allows for the analysis of populations passing throughout multiple breed development stages.The impact of human advancement on breed distribution and development is readily visible in relation to the agricultural practice of transhumance and the spread of livestock guardian breeds along the resultant routes. We have further elucidated a theory for a common agrarian shepherd dog type, regional to Central Europe, which likely existed prior to modern breed differentiation. The genetic signatures of this population can be recognized as having contributed to many regional breeds of European herding dogs, including the well‐known German Shepherd Dog, and the multiple Italian herding breeds adapted to working in the pastoral regions of Northern Italy. The analysis of additional regional dog breeds will expand our understanding of the impacts and routes of artificial selection, revealing ever more interplay between human and canine coevolution.The authors have no conflict of interests to declare.A.T. and D.L.D. contributed equally to this manuscript, through conceptualization, analyses, interpretation, and writing, and are to be considered co‐first authors. S.F., S.M., D.B., and R.C. provided resources and editing. M.P. and H.G.P. provided conceptualization and editing. L. L. and R. C. provided resources. G.P. provided departmental supervision. A.C.H. and A.N.H. provided sample management and processing. E.A.O. and P.C. provided conceptualization, funding acquisition, project administration and supervision, and editing. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Stramonita haemastoma has been examined in the Western Mediterranean and North‐Eastern Atlantic populations with mtDNA COI sequences and three newly developed microsatellite markers. We identified two cryptic lineages, differentially fixed for alternative mtDNA COI haplogroups and significantly differentiated at microsatellite loci. The mosaic distribution of the two lineages is unusual for a warm‐temperate marine invertebrate with a teleplanic larval stage. The Atlantic lineage was unexpectedly observed as a patch enclosed in the north of the Western Mediterranean Sea between eastern Spain and the French Riviera, and the Mediterranean lineage was found in Macronesian Islands. Although cyto‐nuclear disequilibrium is globally maintained, asymmetric introgression occurs in the Spanish region where the two lineages co‐occur in a hybrid zone. A first interpretation of our results is mito‐nuclear discordance in a stable postglacial hybrid zone. Under this hypothesis, though, the location of genetic discontinuities would be unusual among planktonic dispersers. An alternative interpretation is that the Atlantic lineage, also found in Senegal and Venezuela, has been introduced by human activities in the Mediterranean area and is introgressing Mediterranean genes during its propagation, as theoretically expected. This second hypothesis would add an additional example to the growing list of cryptic marine invasions revealed by molecular studies.Molecular approaches have proven efficient to identify cryptic lineages within single taxonomic entities. Sometimes these cryptic lineages maybe previously unreported or unknown invasive taxa. The genetic structure of the marine gastropod  Stramonita haemastoma is a rocky shore gastropod belonging to the family Muricidae usually found in warm‐temperate waters  of four forward and four reverse primers (Table VF1_t1: VF1d_t1: LepF1_t1: VF1i_t1 (1:1:1:3) or VR1_t1: VR1d_t1: LepRI_t1: VR1i_t1 (1:1:1:3) and sequenced with M13  was used to read the resulting chromatograms.In addition to mtDNA Bank see , data wers Table  in the f2.2Fst were obtained using Genetix software v4.0.5.2 . The null hypothesis of linkage equilibrium was never rejected with exact tests. Allele frequencies are presented in Table COI haplotype diversity in Figure The analysis of the mitochondrial diversity has revealed 167 haplotypes and a high haplotypic and nucleotide diversity (hd = 0.976 and π = 0.016), over the whole dataset. Two mitochondrial clusters of sequences, hereafter named haplogroups, were clearly distinguished in the Neighbor‐Joining tree Figure  and in t3.2The group of samples from the area around the Siculo‐Tunisian Strait (STS), including samples from Tabarca, Bizerte, Korbous, Kelibia and Houaria (Tunisia), Annaba (Algeria), and Palermo  were nearly exclusively composed of cluster B haplotypes at the mitochondrial locus, with the exception of two individuals found in Palermo. Samples from the area around the Almeria–Oran Front (AOF) including Torreveija and Almeria (Spain), and Oran (Algeria) were fixed for the B haplogroup. Finally, our sample from the French Riviera in Pramousquier (France) was also composed of cluster B haplotypes. In addition, data from Claremont et al.  showed t3.3K = 2, as supported by Evanno's Δk , while no significant nuclear genetic differentiation was found within these entities with the single exception of the Arcachon Bay sample (belonging to lineage A) that proved to be slightly differentiated to other lineage A populations . This genetic difference of Arcachon Bay sample with other samples from cluster A was also revealed by the STRUCTURE analyzes for K = 3  two cryptic mitochondrial lineages also differentiated at three nuclear microsatellite markers, (ii) an unexpected mosaic distribution of the two lineages with a surprising patch of the Atlantic lineage in the North‐Western part of the Occidental basin in the Mediterranean Sea and (iii) hybridization between the two lineages when found in sympatry. There is little need to discuss at length the discovery of cryptic lineages with molecular markers as this observation is pervasive in the sea  lineage distributed elsewhere in the Mediterranean Sea. Furthermore, in each of these other examples of discontinuous distribution, the geographical range of the distribution in the Atlantic Ocean is preponderantly north to the Cantabrian Sea, in accordance with a temperate water preferendum. On the contrary, the distribution of the A lineage of S. haemastoma is therefore at an unusual place. In addition, the genetic break between the Gulf of Lion and the French Riviera would also be an unusual result in a planktonic disperser. Genetic differentiation has often been reported within the Mediterranean occidental basin in restricted dispersers  , South America, or South‐West Africa. Small scale invasion from the Atlantic coasts has never been reported in another bentho‐pelagic marine species but as explained above is difficult to demonstrate as it is difficult to refute a natural postglacial redistribution of vicariant lineages. Claremont et al.  haplotypes, weaker genetic structure between introduced populations, and more importantly a lack of concordance between the phylogeny and the geographical distribution of the haplotypes  (Viard et al., 5S. haemastoma, with an unusual mosaic distribution. This mosaic distribution could result from human‐mediated introduction: The unexpected location of the sympatric area, the patchy, and restricted distribution of the lineage A and the asymmetric introgression pattern support the hypothesis that the A lineage is invading in the Mediterranean Sea. We were, however, not able to fully dismiss the alternative hypothesis that the mosaic distribution results from postglacial population displacement, the asymmetry of introgression in the hybrid zone being then a consequence of mito‐nuclear discordance in a stable hybrid zone. Our results clearly call for deeper investigation: A broader geographic and genomic sampling together with a monitoring of the distribution could allow disentangling of the two hypotheses. In any case, S. haemastoma proves an interesting model species to better understand the connectivity of planktonic dispersers in the Occidental basin of the Mediterranean Sea.We have discovered two cryptic lineages in North‐Eastern Atlantic and Mediterranean populations of the teleplanically dispersing marine snail None declared.S. haemastoma. T.E.A conducted the molecular laboratory work. T.E.A and N.B analyzed the data. T.E.A and N.B. wrote the manuscript. F.V revised and commented the article.N.B and T.E.A designed the study. T.E.A, N.T.E.M, C.S, and D.C sampled  Click here for additional data file.