Carcharhinus limbatus, Carcharhinus sorrah, Rhizoprionodon acutus, and Sphyrna lewini) between the Red Sea and all other water bodies surrounding the Arabian Peninsula. To assess intraspecific patterns of connectivity, we constructed statistical parsimony networks among haplotypes and estimated (1) population structure; and (2) time of most recent population expansion, based on mitochondrial control region DNA and a total of 20 microsatellites. Our analysis indicates that, even in smaller, less vagile shark species, there are no contemporary barriers to gene flow across the study region, while historical events, for example, Pleistocene glacial cycles, may have affected connectivity in C. sorrah and R. acutus. A parsimony network analysis provided evidence that Arabian S. lewini may represent a population segment that is distinct from other known stocks in the Indian Ocean, raising a new layer of conservation concern. Our results call for urgent regional cooperation to ensure the sustainable exploitation of sharks in the Arabian region.The northwestern Indian Ocean harbors a number of larger marine vertebrate taxa that warrant the investigation of genetic population structure given remarkable spatial heterogeneity in biological characteristics such as distribution, behavior, and morphology. Here, we investigate the genetic population structure of four commercially exploited shark species with different biological characteristics ( Understanding the spatio-temporal patterns of gene flow among geographically separated populations has long been a major focus in ecology. Limited genetic differentiation over broad spatial scales is often associated with the high dispersal capacities of marine organisms, resulting from either a highly dispersive larval phase affected by ocean currents or the active movements of juvenile and adult specimens in animals lacking a planktonic larval stage. Yet, there are numerous well-known examples of barriers to gene flow within and among populations that result in higher than expected genetic structure, even in species with presumed high levels of vagility  Fig.. First, C. leiodon: Moore et al. H. bentuviai: Baranes and Randall H. randalli: Last et al. Second, existing studies suggest variation in distributional and morphological patterns within Arabian elasmobranch species. Several elasmobranch species in the Arabian region have highly localized known distributions ; (2) the spot-tail shark, Carcharhinus sorrah ; (3) the milk shark, Rhizoprionodon acutus ; and (4) the scalloped hammerhead shark, Sphyrna lewini .Patterns of dispersal and population structure can vary significantly even among closely related species in shared habitats  of 98 cm in the study region while C. sorrah, C. limbatus, and S. lewini can reach 196 cm, 287 cm, and 303 cm TL, respectively (R. W. Jabado unpubl. data). Carcharhinids and Sphyrnids are placental livebearers with typically low intrinsic rates of increase. Although S. lewini exhibits the highest fecundity of all four study species, ) and nuclear (microsatellites) markers. Congruence between both types of markers has been shown to yield a high degree of intraspecific resolution, providing a useful tool for the delineation of marine lineages and populations , Oman, the United Arab Emirates (UAE), and Bahrain; C. limbatus and S. lewini were collected from all locations except Bahrain , but landings at this site originated from fishing grounds spanning the country's entire Red Sea coast  following the manufacturer's instructions and subsequently stored at −80°C until further analysis.C. limbatus, 12 loci; C. sorrah, 9 loci; R. acutus, 8 loci; S. lewini, 12 loci). Microsatellite loci were adopted from Feldheim et al. . Thermal profiles consisted of a denaturation step at 95°C for 15 min, followed by 30 cycles of 30 sec at 94°C, annealing for 90 sec at loci-specific temperatures between 55°C and 60°C (Table S2), and an extension of 60 sec at 72°C, with a final extension of 30 min at 60°C. Fragment analysis was conducted in an Applied Biosystems 3730 XL genetic analyzer, and microsatellite alleles were scored using GENEMAPPER software . The null hypothesis of Hardy–Weinberg equilibrium (HWE) was tested using GENEPOP on the Web (v4.2 Rousset E), observed (HO) and unbiased (UHE) heterozygosity, allelic richness, and mean number of alleles.Shark samples were genotyped at 8 to 12 microsatellite loci  using S Hedrick  to compeC. limbatus, C. sorrah, and R. acutus using the forward primer ProL2 and the reverse primer PheCacaH2  was used to assemble, check, manually edit, and subsequently align sequences using the MUSCLE algorithm. Aligned sequences were exported to FaBox (Villesen http://blast.ncbi.nlm.nih.gov/Blast.cgi). In the case of R. acutus, no reference sequences were available prior to this study. Therefore, to validate initial species identification, all R. acutus samples were amplified for the COI gene using the primer combination Fish F1 and Fish R1  for species recognition. If sequence data did not match the original identification, respective specimens  were excluded from the data set.For each species, we examined genetic subdivision based on sequence variation in the mtDNA CR. Approximately 1120 base pairs (bp) of the 5′end of the mtDNA CR was amplified for  Berumen . For S. Villesen  and collC. limbatus, C. sorrah, and S. lewini, haplotype networks were constructed to explore the relationships among intraspecific haplotypes. Published haplotypes were sourced from Keeney et al. , and subsequently assessed using a statistical parsimony network constructed in TCS .An AMOVA under the Tamura–Nei (TN) model of sequence evolution, which was individually selected as the most appropriate model for all four species in jModelTest  Fs values. The time since the most recent population expansion was estimated by fitting the population parameter τ  reported for other shark species , observed (HO), and unbiased (UHE) heterozygosities, allelic richness, and mean number for each locus and species within each sample region are provided in Table S2. No signs of linkage disequilibrium were detected among any pairs of loci after correction for multiple comparisons.Microsatellite indices of genetic diversity, that is expected . To ensure that the pattern of microsatellite structure (or lack thereof) was not being driven by a single locus, we conducted locus-by-locus AMOVA analyses (data not shown), which gave consistent results across all except one locus . This locus was solely responsible for the observed pattern of significant population structure and was subsequently removed from the analysis.In all species, several microsatellite loci showed deviations from HWE in one or both of the putative populations and signs of null alleles (Table S2). To test whether significant differences between expected vs. observed heterozygosities at some loci could confound population level analyses, we removed all those loci and re-ran AMOVA analyses. A comparison of h) and nucleotide (π) diversities were found for C. limbatus and S. lewini, while C. sorrah and R. acutus showed slightly higher h and π values  and for R. acutus for the OAB region only  , R. acutus , and S. lewini   were defined, characterized by five polymorphic sites composed of five transitions (Table S3A). Except for three singletons, all haplotypes were found in both putative populations and matched known Indian Ocean and Indo-Pacific mtCR haplotypes from the global data set of Keeney and Heist . Two singletons were unique to the Red Sea and one was unique to the OAB. Novel haplotypes were very closely related to Indian Ocean and Indo-Pacific haplotypes reported in Keeney and Heist , characterized by 12 polymorphic sites composed of 10 transitions, one transversion, and one deletion (Table S3B). All common haplotypes were observed in both putative populations. One haplotype clearly dominated the sample set (CS1). Seven haplotypes matched haplotypes from the range-wide data set of Giles et al. . All novR. acutus specimens defined 25 haplotypes (GenBank Accession Numbers: KR232957-KR232981) characterized by 22 polymorphic sites composed of 18 transitions, five transversions, and two deletions (Table S3B). All common haplotypes were separated by two mutational steps at most. Three singletons and one haplotype, recorded from two individuals only, were separated from the cluster of common haplotypes by up to 10 mutational steps. Except for one (RA7) that was unique to the OAB, all common haplotypes were shared in both sampling regions. Haplotype RA17 dominated the sample set and was found in more than half of all OAB samples , characterized by four polymorphic sites composed of two transitions and two transversions (Table S3) that differed by no more than one mutational step from each other. Two haplotypes clearly dominated the sample set  of four different shark species, from collection locations spanning across over 5000 km of coastline genotyped at two types of genetic markers (mtDNA and nuclear DNA). Contrary to previous findings of significant population genetic structure across the region in different taxa, our results indicate that dispersal of sharks around the Arabian Peninsula is not limited by any obvious barriers to gene flow. Furthermore, ecological, morphological, and life-history differences among the investigated species do not appear to significantly influence their patterns of population structure. Divergent haplotypes in one of our study species (S. lewini), however, are suggestive of an Arabian population that is genetically distinct from others in the Indian Ocean.This study is the first to assess the population structure of large mobile marine vertebrates between the Red Sea and all other Arabian Ocean Basins. Our analyses were based on a comparatively large number of samples  and not consistent among different statistical tests. These inconsistencies might stem from the high number of null alleles in our data set, which might have been caused by (1) cross-species rather than species-specific loci used in this study due to the limited availability of microsatellite loci for all investigated species and/or (2) species-specific loci, which were developed for specimens sampled in other ocean regions. For future studies on elasmobranch species from regions that have not previously been included in samples used for the design of microsatellite markers, we hence recommend designing species-specific markers based on samples originating from the targeted study region.Several previous studies have shown the existence of historical, oceanographical, and ecological barriers to gene flow resulting in genetic subdivision in a range of marine organisms among ocean basins surrounding the Arabian Peninsula. Our analyses did not provide compelling evidence for more than one Arabian Sea genetic stock for C. limbatus, C. sorrah, and S. lewini demonstrated restricted dispersal across deep ocean habitats, genetic structure along continental margins was shown to be relatively minor  for C. sorrah and R. acutus, indicating recent population expansion events between approximately 178,000 and 214,000 years ago (TableThe homogenous population structure observed here was not unexpected, given the contiguous shelf habitat around the Arabian Peninsula and the high potential mobility of our study organisms. While previous regional and range-wide studies on ago Table. The decago Table. Anotherago Table.C. limbatus and S. lewini based on contrasting mitochondrial and nuclear data (Keeney et al. Additionally to the apparent homogenous population structure, we also found no indication of differences between male and female dispersal in any of the study species. This finding stands in contrast to previous studies describing marked philopatric behavior (Feldheim et al. C. limbatus and S. lewini was relatively low, with only seven and five haplotypes, respectively. Yet, this pattern appears to be typical for both species throughout their global range (Duncan et al. C. limbatus and C. sorrah matched previously published Indian Ocean and Indo-Pacific mtDNA haplotypes, all haplotypes discovered for S. lewini were novel.Genetic diversity for S. lewini specimens sampled around the Arabian Peninsula and specimens sampled in other, nearby Indian Ocean regions (e.g., the Seychelles and Madagascar, Duncan et al. S. lewini may have evolved to breed differently from conspecifics outside this area. Estuaries have repeatedly been reported as an important nursery habitat for S. lewini elsewhere in the world (e.g., Clarke S. lewini, however, exist near Djibouti City (Bonfil S. lewini may thus have evolved to no longer require estuaries as breeding/nursery grounds, eliminating the need for reproductive migrations and thereby reducing gene flow with other populations. Such scenarios may also explain why C. limbatus and C. sorrah, which are not reported as being strongly dependent on estuary nurseries, are genetically well connected to other Indian Ocean populations. Second, regional oceanography and upwelling zones may form temporary barriers between Arabian and other Indian Ocean populations. The Somali Current, for instance, which only operates between June and September (Schott S. lewini, but not with those of C. limbatus and C. sorrah. In this case, mixing with south Indian Ocean populations might be inhibited for S. lewini, but not for the other two species. Additional data on migration routes, migration times and breeding cycles, however, are needed to confirm either of these hypotheses.There are two possible explanations for the observed genetic separation between y Bonfil  and in hr Schott , may coiS. lewini, which comprise a large amount of the commercial harvest in the Arabian region (Jabado et al. The fact that Arabian R. acutus.Existing contemporary barriers such as regional upwelling systems and ocean currents are likely not influencing long-shore or stepping-stone connectivity even in smaller, less vagile shark species like S. lewini haplotypes with published western Indian Ocean haplotypes revealed the possibility of a S. lewini population in the Arabian region that is distinct from other Indian Ocean populations.A comparison of novel Similar dispersal patterns in sharks with contrasting ecological, morphological, life-history, and distributional patterns indicate that populations of other shark species are likely to also function as common stocks across all ocean basins surrounding the Arabian Peninsula.Molecular studies on a diverse range of elasmobranch species have done much to illuminate issues that complicate fisheries management and conservation (see Dudgeon et al. Overall, our results call for urgent regional cooperation on the management of shark stocks in all countries surrounding the Arabian Peninsula to ensure a sustainable future for this vital component of the marine biodiversity in the western Indian Ocean. Regulations on the exploitation of only one part of the stock will not suffice and management arrangements need to be implemented, enforced, and coordinated among all responsible authorities. Given current harvesting levels and the apparent connectedness of stocks, unregulated exploitation in one or several countries is likely to cause uniform depletion across the entire stock.


Gopherus. These lineages offer a powerful system to study speciation, because different biogeographic patterns  are observed at opposing ends of their distributions. We use 82 samples collected from 38 sites, representing the entire species' distribution and generate sequence data for mtDNA and four nuclear loci. A multilocus phylogenetic analysis in *BEAST estimates the species tree. RNA‐seq data yield 20,126 synonymous variants from 7665 contigs from two individuals of each of the three lineages. Analyses of these data using the demographic inference package ∂a∂i serve to test the null hypothesis of no gene flow during divergence. The best‐fit demographic model for the three taxa is concordant with the *BEAST species tree, and the ∂a∂i analysis does not indicate gene flow among any of the three lineages during their divergence. These analyses suggest that divergence among the lineages occurred in the absence of gene flow and in this scenario the genetic signature of ecological isolation (parapatric model) cannot be differentiated from geographic isolation .Evolutionary biology often seeks to decipher the drivers of speciation, and much debate persists over the relative importance of isolation and gene flow in the formation of new species. Genetic studies of closely related species can assess if gene flow was present during speciation, because signatures of past introgression often persist in the genome. We test hypotheses on which mechanisms of speciation drove diversity among three distinct lineages of desert tortoise in the genus  Geography, gene flow, and time strongly influence speciation, but the relative importance of these mechanisms can be difficult to quantify Via . CompetiIt is difficult to test empirically for signatures of past introgression in natural systems due to pervasive genetic drift, genetic draft and variation in coalescence times  lend themselves well to testing for the drivers of speciation and the roles played by ecology because they are recently diverged and wide‐ranging in multiple biomes  and G. morafkai (Morafka's desert tortoise) are a classic example of allopatric speciation resulting from geographic isolation by the Colorado River  and the G. morafkai Sonoran and Sinaloan lineages, gene flow is geographically extensive and there is genetic structure with isolation by distance , nuclear loci (nDNA), and RNA‐seq data.i (Mojave/Sonoran isolation) assumes that the Mojave and Sonoran lineages experienced divergence in isolation. Alternatively, H‐MSgf (Mojave/Sonoran gene flow) involves divergence with gene flow. Hypothesis H‐SSgf  assumes that the Sonoran and Sinaloan lineages experienced parapatric speciation without isolation and in the presence of gene flow. Alternatively, H‐SSgf would also apply if these lineages diverged with cycling periods of isolation in refugia followed by secondary contact and with repeated periods of introgression. Hypothesis H‐SSi  assumes that these lineages diverged without introgression during a single event of isolation  followed by secondary contact .We test hypotheses that the three lineages of desert tortoises experienced different mechanisms of speciation. Hypothesis H‐MSThe University of Arizona Institutional Care and Use Committee (IACUC) approved all handling protocols (IACUC Control no. 09‐138).G. berlandieri from a private collection and two samples of G. flavomarginatus collected in Durango, Mexico ; a captive individual of Sonoran G. morafkai from Arizona; and a wild‐caught Sinaloan G. morafkai obtained from just outside of Alamos, Sonora Mexico . Raw data were used to assemble reference transcriptomes. The third flowcell lane was used to generate low‐coverage RNA‐seq reads from six samples that were then mapped to the reference assemblies to assess diversity within and among the three lineages. For these six samples, we hand‐captured and collected samples from wild desert tortoises from the following three sites in 2013: two Sinaloan G. morafkai from the Reserva La Sierrita, Sierra de Alamos, Sonora, Mexico .The RNA‐seq data gathering used nine individuals in three flowcell lanes on the Illumina HiSeq platform. We dedicated two lanes to high‐coverage sequencing of three individuals, one for each of the following lineages: a captive individual of ts USFWS , Clark CFor RNA sample collection, we obtained <1 mL whole blood via brachial or subcarapacial venipuncture and mixed it with a greater than 50% volume RNA lysis/binding buffer from the Ambion RNAqueous kit . Samples were immediately put on ice and then transferred to liquid nitrogen for storage within 4 h of collection. All RNA samples were verified as being of the assumed lineage (and not hybrids) with subsequent DNA analyses using 25 microsatellite loci and mtDNA  following Edwards  to design primers with OLIGO PRIMER ANALYSIS 6.68  as follows: R35EX1_GOPH CACATACTGAATTTCCAGG, and R35EX2_GOPH GGACCTTTAAGTCATACAC.We sequenced a 1109 base pair (bp) portion of mitochondrial DNA , 0.2 mmol/L of each dNTP, 0.4 units of Platinum Taq , 5.0 mmol/L KCl, 10 ng of genomic DNA, and locus‐specific amounts of MgCl2 , by lineages within G. morafkai  and by geographic regions where mtDNA differentiation had been previously observed  for the mtDNA locus only, we set the prior for our Bayesian analysis in BEAST for divergence time between G. agassizii and G. morafkai (Sonoran) lineages to 5.9 ± 0.5 Ma based on Edwards . We quantified recovered RNA using a RiboGreen TBS‐380 Flourometer  and assessed sample quality with an Advanced Analytics Fragment Analyzer using the High Sensitivity RNA Kit . We used the Illumina TruSeq RNA kit  to build the cDNA library from total RNA. The kit targeted polyadenylated mRNA for second strand cDNA synthesis and size‐selected via enzyme‐mediated fragmentation. While building the cDNA library, we applied unique tags to each individual sample. We quantified each cDNA library using a Kapa Biosystems qPCR Kit  specific to the Illumina Adapter sequence. Next, we pooled samples in equimolar concentrations for the final cDNA library. We ran the three high coverage individuals representing each of the three tortoise lineages on two flowcell lanes using an Illumina HiSeq 2000 and we ran the six lower‐coverage individuals on a single flowcell lane using the Illumina HiSeq 2500 platform. All next‐generation sequencing protocols were performed at the University of Arizona Genetics Core following standard protocols.Haas et al. For each library, we processed raw reads to remove sequencing adaptors, trimmed for quality score (Q > 28) and length‐filtered (>37 bp) using TRIMMOMATIC 0.32 . Parameter confidence intervals were estimated by 100 conventional bootstraps over contigs and calculated as θ¯±1.96×σ(θ), where θ was the parameter of interest and σ was the standard deviation of the bootstrap results. To convert parameters from population genetics units  to physical units, we assumed a divergence time between G. agassizii and Sonoran G. morafkai lineages of 5.9 Ma . Both examples represented the same ambiguity in the same SNP and each of the four haplotypes among the ambiguous pairs was represented in the other 51 samples. For this locus we choose the pair with the highest P value to use for downstream analyses.We obtained usable sequences for the mtDNA and four of the six nuclear loci .Among the nuclear loci, haplotypes were both lineage‐specific and found globally across species of The matrilineal genealogy (mtDNA tree) had strong support across analyses for distinct Mojave/Sonoran/Sinaloan matrilines. Notwithstanding, the geographically distant Mojavian and Sinaloan matrilines were resolved as sister taxa, and together they were the sister group to the intervening Sonoran matriline Fig. A. The muω employed different models for branches of the tree . This result suggested that this gene was under overall strong purifying selection. Next, we applied a model in which every branch had its own ω. This model was significantly more effective than one‐ratio model  was estimated to be larger than one (1.1), indicating that positive selection may have affected this lineage ‐based inference tool ∂a∂i  into the models, either as continuous flow, such as through parapatric speciation with continuous contact, or delayed flow, such as resulting from cycling periods in refugia followed by introgression during secondary contact, the maximum composite‐likelihood estimates for the gene flow parameter converged to zero (Table S1). Thus, we found no evidence of gene flow between any pair of the three populations and, thus, rejected hypotheses H‐MSgf and H‐SSgf.To guide development of three‐population models, we first considered simpler two‐population models. Initial two‐population models without gene flow  consistently yielded a larger effective population size for the Sonoran population than the others and a more recent divergence between the Sinaloan and Sonoran populations than between either of those populations and the Mojave (Table S1). Consistent with this result, the best‐fitting three population models involved recently diverged Sinaloan and Sonoran populations (Table S2). This result provided independent support for the *BEAST species tree. When we added gene flow . To estimate parameter uncertainty while accounting for linkage among variants, we used conventional bootstrapping. Table Based on our two‐population analyses, we considered three‐population models in which the Sinaloan and Sonoran populations were sisters and there was no gene flow between them. Figure G. agassizii and G. morafkai. This inundation now forms the Colorado River boundary between the species  does not differ from that obtained for the allopatric divergence of Sonoran/Mojave. Thus we cannot reject hypothesis H‐SSi that Sonoran and Sinaloan lineages diverged without significant introgression and that isolation  is responsible for the divergence. Secondary contact followed the isolation, as is currently observed.The ∂a∂i analysis also finds no evidence of gene flow during divergence of the Sonoran/Sinaloan lineages. Despite strong biogeographic evidence that the current contact zone between the Sonoran and Sinaloan lineages is a result of secondary contact after periods of isolation in Pleistocene refugia  processes of speciation. Either geography  or selection through ecological niche segregation should drive divergence via a reduction in gene flow, and both drivers may occur simultaneously Endler . GopheruGeographic isolation may also explain speciation of the Sonoran and Sinaloan lineages and an allopatric ‘speciation pump’ . These results suggest that if substantial gene flow had occurred between lineages during the evolution of desert tortoises, we would detect it.Inferences based on large numbers of gene sequences and few individuals have been shown to be robust for inference of population history (Wang and Hey Carduelis chloris), another nonmodel organism ; BioProject ID 281763.10.5061/dryad.g0m5s.Transcriptome assembly.fasta file, SNP data.vcf, and shared genotype.txt file used for this publication have been archived in Dryad. Provisional DOI: doi:Table S1. Models evaluated during demographic inference using ∂a∂i 1.6.3 (Gutenkunst et al. Table S2. Inference of species tree topology among the three tortoise populations.Table S3. Haplotype summary of mtDNA and 4 nDNA loci.Table S4. Overview of DNA polymorphism for mtDNA and 4 nDNA loci estimated for tortoises in the genus Gopherus.Click here for additional data file.


The amount and structure of genetic diversity in dessert apple germplasm conserved at a European level is mostly unknown, since all diversity studies conducted in Europe until now have been performed on regional or national collections. Here, we applied a common set of 16 SSR markers to genotype more than 2,400 accessions across 14 collections representing three broad European geographic regions  with the aim to analyze the extent, distribution and structure of variation in the apple genetic resources in Europe.ST = 0.031). A nested Bayesian clustering approach allowed identification of subgroups which revealed internal patterns of substructure within the groups, allowing a finer delineation of the variation into eight subgroups (FST = 0.044). The first level of stratification revealed an asymmetric division of the germplasm among the three groups, and a clear association was found with the geographical regions of origin of the cultivars. The substructure revealed clear partitioning of genetic groups among countries, but also interesting associations between subgroups and breeding purposes of recent cultivars or particular usage such as cider production. Additional parentage analyses allowed us to identify both putative parents of more than 40 old and/or local cultivars giving interesting insights in the pedigree of some emblematic cultivars.A Bayesian model-based clustering approach showed that diversity was organized in three groups, although these were only moderately differentiated  contains supplementary material, which is available to authorized users. Malus x domestica Borkh.) is one of the most important fruit crops grown in temperate zones and the most important in the Rosaceae family [Cultivated apple , eco-geography and/or passport information . The effUntil now, the studies of diversity and genetic structure conducted in European apple have been based on the analyses of material from limited geographic areas  , 22–26. ID) was extremely low: PID = 1.3 x 10−22, thus highlighting the low risk of erroneous attribution of accessions to duplicate groups. Redundancies were found both within and between collections, leading to the confirmation of numerous previously documented synonyms  and allowing the putative identification of numerous unknown synonyms or mutant groups . Redundancy groups also supported the notion of several national/local name translations such as the English cultivar ‘Cornish Gilliflower’ translated into ‘Cornwallské hřebíčkové’ , or ‘White Transparent’ and ‘Skleněné žluté’  in Czech and ‘Transparente Blanca’ in Spanish, the Russian cultivar ‘Korichnoe polosatoe’ translated into ‘Kaneläpple’ in Swedish , or the cultivar ‘La Paix’ translated into ‘Matčino’  in Czech. Several cases of homonymy  were also found, e.g., three different SSR profiles for the same accession names ‘Pomme Citron’ or ‘Charles Ross’. Data allowed identifying some obvious labeling errors, e.g., X2698 ‘Court Pendu Plat’ which was shown to be the rootstock ‘MM106’, or CRAW-0362 ‘Transparente de Croncels’ which was found likely to actually be ‘Filippa’  and for the germplasm from each of the three geographical groups  were found between all the geographic groups for all markers except for the CH-Vf1 locus when comparing Southern and Western germplasm (data not shown).The 16 SSR markers amplified a total of 369 alleles across the 1,859 apple accessions used for diversity analysis, ranging from 17 (CH02c09 and CH05f06) to 35 (CH02c06) alleles per locus. The average number of alleles per locus was 23.06, whereas the mean effective number of alleles per locus was 6.59  were identified as strongly associated to a group. This partitioning level corresponded to an asymmetric division of the material into three groups: K1 composed of 506 genotypes, K2 containing 401 genotypes, and K3, the largest group, comprising 952 genotypes. Diversity estimates revealed high levels of allelic variation within each group, with allelic richness ranging between 16.0 (K3) and 18.6 (K1) . The largest differentiation between pairs of groups was found between Northern + Eastern and Southern germplasm , whereas much lower FST values were found between the Western and each of the Northern + Eastern  and Southern  materials.The genetic differentiation between the three designated geographic regions of origin was low  was less evident (63 %), but still visible by comparison Fig. . AlthougqI < 0.8) for which the geographical regions of origin  was known, we defined a membership coefficient threshold (qI < 0.55) with the aim of identifying genotypes unambiguously in admixis, in order to examine whether a supplemental relationship could be found between geographical region and grouping by Structure for the admixed material. For the unambiguously admixed material  of Southern European origin, the average proportion of ancestry (qI) was 0.45 to K1 , followed by 0.42 to K3 and 0.13 to K2, the groups mostly composed by material from Western and Northern + Eastern European origins, respectively (data not shown); a slightly less pronounced, but complementary, pattern was observed for the unambiguously admixed germplasm  of Northern + Eastern Europe with average proportions of ancestry of 0.43, 0.35 and 0.22 to K2, K3 and K1, respectively. For the unambiguously admixed material  of Western origin the average proportion of ancestry to each of these three groups was almost identical (approximately 1/3). This result was in line with the lower FST values found between the groups K1/K3  in comparison with the slightly higher differentiation between the groups K1/K2  and K2/K3 . The dispersion of the three groups in the PCoA plot was also in agreement with these results, showing the highest overlap between K1 and K3 followed by K2 and K3.Within the admixed accessions .In order to investigate the substructuring of the diversity within each of the three groups identified in the initial analysis we used a nested application of the Structure software. To do this, the three groups were analyzed independently. To evaluate the strength of the hypothetical subdivisions  within each group, simulations for each K and ΔK for K1 suggested a probable subdivision of this material into three subgroups and the assignment of genotypes was well correlated between runs. The average proportion of ancestry for the accessions clustered in the three subgroups of K1 was 0.75, with 44 % of the accessions showing strong assignments. Two subgroups for K2 and three for K3 were similarly established. In both cases, the assignment of genotypes was well correlated between runs, and almost identical average proportions of ancestry to those for the subgroups of K1 were obtained with slightly higher proportions of strongly assigned accessions (47 % and 50 % respectively). Secondary peaks at other K values were also explored but these subdivisions had less statistical support (data not shown). Therefore, we adopted eight subgroups as the most suitable partitioning degree of substructuring  to 0.84 (K1.1), indicating a high level of heterozygosity contained in all the subgroups, the percentage of alleles represented in each one of the eight subgroups was very variable, ranging from 46 % (K3.2) to 76 % (K3.1). Some private alleles were identified in all subgroups except for K3.2. They were most abundant in K1.1, but a considerable number of them were found also in K3.3 and K2.1. Most of the private alleles (approx. 72 %) were also unique as they were identified in only one accession. To properly evaluate the allelic diversity between the eight subgroups, we applied a rarefaction approach to compensate for the differences in subgroup size. The allelic richness obtained for the eight subgroups supported the previous results, confirming the highest diversity in K1.1 and the lowest diversity in K3.2.Genetic diversity estimates were calculated for all the subgroups obtained by the nested Bayesian model-based clustering Table . While HST pairwise tests between subgroups , followed by K1.3/K2.1 , and the lowest to the pairs K1.1/K3.3  and K3.1/K3.3 .Estimates of genetic differentiation showed that only 3.7 % (K1) and 3.4 % (K2) accounted for variation among subgroups within groups  were identified with high (95 %) confidence level. These consisted of two already documented trios, , as welThe exchange of genotyping data between research units has increased considerably in recent years, with the aim to investigate the extent and distribution of diversity for specific crops at a wide geographic scale. In this study, the application of a common set of 16 SSR markers on a wide set of dessert apple cultivars distributed across three broad European regions allowed the detection of redundant accessions and duplicated genotypes between and within collections, and the description of the structuration of a significant part of the European apple diversity. Cross-comparison of SSR data in attempts to combine datasets from multiple sources has often been problematic due to challenges in harmonizing the allelic sizes between different laboratories , 29, 30.Interestingly, duplicate groups involving accessions from different collections underlined some putative drift in the cultivar denomination. Some good examples were ‘Pott’s seedling’ and ‘Pottovo’ (FBUNQ14), or ‘Signe Tillish’ and ‘Signatillis’ (FBUNQ34). In addition, ‘sports’ are often given derivative names  but the current analysis was not set up to distinguish between clones and ‘sports’ of cultivars with potential morphological differences. Many likely errors in denomination of genotypes were also detected when multiple representatives of a given cultivar were detected within a group, but a single supposed representative was obviously outside of the group and was often associated with representatives of a different cultivar. For example, ‘Drap d’Or’ and ‘Chailleux’ (FBUNQ92) are known to be synonyms used in France for the same cultivar, and accession DCA_D35 ‘Drap Dore’, which was found to belong to the group FBUNQ50, was most likely a denomination error since almost all other members of this group were ‘Winter Banana’. In other cases, accessions with uncertain denomination could be resolved, such as CRAW-1858 ‘Reinette Baumann?’ (FBUNQ21) and accession CRAW-1108 ‘Peasgood Nonsuch?’ (FBUNQ51) for which the molecular analyses confirmed that they were most likely ‘true-to-type’ cultivars. The question of ‘trueness-to-type’ is a major issue in apple germplasm management where extensive budwood exchange between regions and countries has occurred for centuries. Indeed, an erroneously denominated accession can be transmitted from collection to collection for years, such that a large number of representatives within a duplicate group (as per the present study) should not always be considered definitive proof of the trueness-to-type of accessions but this objective evidence is extremely valuable in highlighting issues to resolve. Since genebank curators have often collected material of old cultivars from private gardens or from tree pasture orchards, unidentified or misidentified material can later be detected either by classical phenotypic characters and/or by using genetic markers. As an example, this study showed that an old so called local cultivar ‘Madame Colard’ (CRAW-0365 – FBUNQ72), described to have been raised in 1910 by the nurseryman Joseph Colart at Bastogne (Belgium), exhibited the same SSR profile as the old English apple cultivar called ‘Royal Jubilee’ (UK-NFC 2000085) raised already in 1888. Further comparison with historical descriptions could conclude that they are the same cultivar. Additional insights from the passport data of accessions would be needed to help in tracing the transmission of the material from collection to collection and pomological characterization will be required to compare accessions to published descriptions of the variety. This will remain a task for the curators of collections, in order to improve curation of germplasm in a coordinated way.It is important to note that the criteria used to select the accessions at the country-level were not always the same. For instance, the INRA and UNIBO material corresponded to former “core collections” built to encompass a large variability not restricted to the national/local accessions , 24. ConMalus × domestica [The high level of diversity and heterozygosity in apple germplasm at a European level agreed with previous results obtained at collection-scale in several European countries, e.g., Italy , Spain , France omestica , iii) muomestica , 37 and,omestica , 42. Intomestica , 37, 42.This large-scale analysis in apple germplasm constitutes a good example of the efficiency and value of coordinated international actions to enhance the knowledge of diversity conserved at a European level. The results obtained offer a valuable step to undertake actions to coordinate European resources towards optimizing the management of apple germplasm across Europe in line with the aspirations of the European Cooperative program on Plant Genetic Resources (ECPGR). The results also offer a potential starting point that may open new opportunities for apple breeding in the near future. All breeding advances are built upon the diversity available, and a key role of the germplasm collections is to help safeguard natural forms of genetic variation and to make them accessible to plant biologists, breeders, and other key users . The extThe attribution of country of origin to traditional cultivars can be a matter of endless debate, especially for those dating back two-three centuries or more. Initial descriptions in pomologies and booklets can be subject to errors in denomination confused by historical distribution and renaming, resulting in synonymy, as well as the re-use of old names for more recent findings or misidentifications. This is less problematic for the better known old cultivars as many of them have been widely documented and monitored over years in several countries. However, for local cultivars and/or landraces where less information is available, the correct attribution can be complicated, especially between neighboring countries. It is also worthy of note that the ‘country of origin’ relies on a political construct, which can be prone to significant change within the potential lifetime of many varieties of apple . Therefore, we first used a conservative approach and discussed our findings in terms of three broad European regions of origin. Then, we analyzed the structuration at a country-scale, but noting that the exact attribution of a given country to a genotype was not always unanimously agreed so that this finer level of analysis should be considered with an element of caution.Using a Bayesian model-based clustering method we were able to initially discern the existence of three robust groups reflecting major divisions of the germplasm. These groups were linked with the three geographical regions of origin, although differentiated only to a low degree. This would reflect a situation whereby the cultivars from a given region were more frequently derived from crosses between parental cultivars from the same region than from cultivars from elsewhere. Nevertheless, the migration of the plant material associated to human movement together with hundreds of years of empirical selection may have caused a significant gene flow across Europe. This is clearly indicated by the low genetic differentiation between groups and has shaped the overall pattern of genetic diversity. A spatially and temporally dynamic process where seeds and mainly graftwood were exchanged between geographically distinct populations has contributed to the increase of the genetic diversity in each area through unintentional gene flow or human-mediated intentional crosses , 36, 44.Although there may have been some mistakes in attributing cultivars to country of origin, the genetic makeup of the cultivars at the European level clearly appeared to show a North-East to South gradient. Interestingly, some countries exhibit intermediate marker data patterns in consistency with their intermediate geographic positions. This was clearly manifested at the national scale for the German and Czech cultivars which were shared between K2 and K3 groups. Similarly, the French and Swiss cultivars were shared between K1 and K3 groups. By contrast, cultivars from Southern Europe , from Northwestern Europe , and from North + Eastern Europe (Sweden and Finland) and Russia were mostly assigned to a single group . For the admixed germplasm from Southern and Northern + Eastern European geographical regions of origin, a certain degree of introgression with the Western germplasm was also indicated in contrast to the low contribution of the Northern + Eastern germplasm into the Southern germplasm and viceversa. Thus, in agreement with the correspondence between clustering and regions or countries of origin of the germplasm, the geographical proximity appears to align with the patterning observed in the admixed accessions.nested (or two-steps) Structure” clustering method has been shown to be an efficient tool to delineate further levels of substructure in both apple and other plant species [fine-delineation” of the intra-variation within each main geographical region of origin. This is most probably the case for the K1.1 subgroup which mainly consists of Spanish cultivars and could reflect a process of both local adaption and isolation by distance related to the Pyrenean barrier. For the K1.3 subgroup, local adaptation to the Southern region could be inferred together with a potential for more intense commercial exchange between Italy and Southern France. For other subgroups, the relationship with particular countries or small regions was not obvious, but some interesting associations between subgroups of group K3 and recent cultivars and some of their founders or particular usage (cider apple cultivars) could be noticed.In cases demonstrating the presence of a significant hierarchical population structure as this study suggests, this method preferentially detects the uppermost level of structure , 48–50.  species , 49–52. The previously reported parentage of 10 recent cultivars was correctly inferred in all cases. These results served as a control and validated the parentage assignment obtained with the CERVUS software  indicatiThe parentage of some old cultivars was either confirmed, in the case of ‘Ernst Bosch’ = ‘Ananas Reinette’ x ‘Mank's Codlin’ (synonym: ‘Evino’) or augmented, in the case of ‘Ben’s Red’ = ‘Devonshire Quarrenden’ x ‘Box Apple’ Table  where thSome traditional folklore about the origination of old apple cultivars could be either substantiated or refuted by the SSR-based parentage information. As one example, the old Swedish cultivar ‘Förlovningsäpple’ is said to derive from a locally acquired seed in Northern Sweden where only a few cold-hardy apples can be grown. The two unknown parents were here inferred to be the Swiss cultivar ‘Heuapfel’ and the wide-spread cultivar ‘Saint Germain’ (X1646) also known as ‘Vitgylling’ in Sweden, a name used for a group of more or less similar, white-fruited, early-ripening and winter-hardy cultivars. Interestingly, the ‘Vitgylling’ accession included in the present study (BAL072) did not have the same SSR profile as ‘Saint Germain’, but they share one allele for all 16 SSR loci and may therefore be related. In two other cases, traditional Swedish folklore indicated that a sailor brought an exotic seed to the island of Gotland and to Kramfors in Northern Sweden, respectively, resulting in ‘Stenkyrke’ and ‘Kramforsäpple’. For ‘Stenkyrke’, one parent is the Swedish ‘Fullerö’ and the second is the German cultivar ‘Danziger Kantapfel’ which has been much grown in Sweden. The origin of ‘Stenkyrke’ is thus probably much more local than anticipated. Similarly, the surmised American sailor origin of the seed giving rise to ‘Kramforsäpple’ is refuted by the fact that the parents of this cultivar are the Swedish ‘Sävstaholm’ and ‘Åkerö’.It is important to keep in mind that trueness-to-type of the accessions is not guaranteed, thus the labeling of the offspring or the parents can be erroneous in some cases. Conversely, the inferred parentages are robustly established so that the genetic relationships between the accessions are valid independently of their names. Crosses between the two inferred parents could be performed to reproduce the cross which gave birth to the offspring cultivar, especially if genetic analysis of some particular traits of the latter genotype indicates an interesting application in plant breeding.Malus x domestica genotypes indicated that apple germplasm diversity reflects its origination within three main geographic regions of Europe, and that a weak genetic structure exists at the European level. This structuring of genetic variation in European dessert apple is caused by evolutionary processes relevant to the domestication of perennial fruit species with factors such as gene flow created by, e.g., ancient roads of commerce across the continent, other human activities like intentional selection and later breeding, and genetic drift. The remarkable differences in the allelic variation found at group and subgroup levels of germplasm stratification constitute a strong indication of that the diversity is hierarchically organized into three genepools, with consistent evidence of a pattern of internal substructure. The potential value for modern fruit production is mostly unknown since a majority of the accessions are poorly evaluated from an agronomic point of view. Thus, phenotypic data obtained with standardized methods is required to determine the commercial potential of the preserved material and to enable its use in new crosses to increase the genetic basis of the cultivated apple.The analysis of a large and representative set of The integration of data for collections from different European geographic regions using standardized methods will undoubtedly form an important step in developing the European strategy for conservation of apple germplasm and constitute the starting point to define a European “apple core collection”. This will constitute a decisive step in the field of conservation genetics, and may also have direct implications on the improvement of our understanding of the species, including i) the identification of genomic regions associated with commercially important horticultural traits, ii) the discovery of new germplasm features that may be taken advantage of for efficient breeding and iii) the analysis of genotype x environmental interactions for studying the stability of the most economically important traits for this species.Apple germplasm collections from nine European countries, plus Western part of Russia and Kyrgyzstan, were available for this study  in order to be combined into four different multiplexed reactions , the number of alleles with a frequency below 5 % (NB), the number of effective alleles (NE), and the observed (Ho) and expected (He) heterozygosity. The probability of identity (PID) was calculated as follows [pi and pj are the frequencies of the ith and jth alleles and i ≠ j. The cumulative PID over the 16 SSR was computed as the product of the PID of each individual marker.The multilocus SSR profiles were compared pairwise in order to establish the genetic uniqueness of each accession. Accessions were considered as duplicates if they had identical SSR fingerprints, or if they had one allelic difference for a maximum of two SSR loci thus making room for some genotyping errors and/or spontaneous SSR mutations. On this basis, redundant profiles were removed from the dataset to avoid bias in genetic analyses and duplicate groups were labeled with unique group ID codes (FBUNQ codes). An accession was declared as a putative triploid when at least three of the 16 SSR loci exhibited three distinct alleles. Analyses of descriptive diversity statistics were conducted at locus level. For each SSR marker, SPAGeDi v.1.3 software  was used follows :\documenUsing passport data along with reviewing published records with a focus on old literature  and specialized websites we were able to discern the geographical regions of origin for a large part of the unique genotypes analyzed. This was further helped by the resolution of identified duplicates and comparison of accessions against additional SSR data of the whole UK-NFC apple collection kindly made available from the UK-NFC database  and of tK) and to quantify the proportion of ancestry of each genotype to the inferred subpopulations. No prior information about the geographical origin of the accessions was considered in the analysis. Ten independent runs were carried out for K values ranging from two to 10 using 500,000 Markov Chain Monte Carlo (MCMC) iterations after a burn-in of 200,000 steps assuming an admixture model and allelic frequencies correlated. In order to assess the best K value supported for our dataset, the ΔK method [K values. When the results described above suggested additional substructuring of the diversity in subgroups, a second-level (nested) application of the Structure clustering method was carried out analyzing separately each of the K major groups previously obtained [qI) was ≥0.80 [The software Structure v.2.3.4  was usedK method  was usedK method  to examiobtained , 50, 51.as ≥0.80 –72; otheas ≥0.80 , which eas ≥0.80  in orderTo validate the genetic structure revealed by the Bayesian model-based clustering two complementary approaches using the Darwin software package v6.0.10  were conST estimates for the different partitioning levels considered in each case were also obtained using Genodive [Ho and He, number of total alleles, number of private alleles, i.e., those only found in one (sub)division level, and number of unique alleles, i.e., those only detected in one unique accession. The software FSTAT v.2.9.3.2 [Population differentiation was estimated by analyses of molecular variance (AMOVA) through Genodive  under twGenodive . Descrip.2.9.3.2  was applOn the basis of the SSR profiles of the unique genotypes, accessions were analyzed to infer possible parent-offspring relationships using Cervus v.3.0 software . In ordeST, fixation index ‘F-statistics’; LOD, logarithm of odds ratio; PCR, polymerase Chain reaction; SSR, simple sequence repeat.ECPGR, European cooperative programme for plant genetic resources; F


Hippocampus guttulatus on the Atlantic coast of NW Iberian Peninsula. Information about spatial structure and temporal stability of wild populations was obtained based on microsatellite markers, and used for monitoring a captive breeding program firstly initiated in this zone at the facilities of the Institute of Marine Research . No significant major genetic structure was observed regarding the biogeographical barrier of Cape Finisterre. However, two management units under continuous gene flow are proposed based on the allelic differentiation between South-Atlantic and Cantabrian subpopulations, with small to moderate contemporary effective size based on single-sample methods. Temporal stability was observed in South-Atlantic population samples of H. guttulatus for the six-year period studied, suggesting large enough effective population size to buffer the effects of genetic drift within the time frame of three generations. Genetic analysis of wild breeders and offspring in captivity since 2009 allowed us to monitor the breeding program founded in 2006 in NW Spain for this species. Similar genetic diversity in the renewed and founder broodstock, regarding the wild population of origin, supports suitable renewal and rearing processes to maintain genetic variation in captivity. Genetic parentage proved single-brood monogamy in the wild and in captivity, but flexible short- and long-term mating system under captive conditions, from strict monogamy to polygamy within and/or among breeding seasons. Family analysis showed high reproductive success in captivity under genetic management assisted by molecular relatedness estimates to avoid inbreeding. This study provides genetic information about H. guttulatus in the wild and captivity within an uncovered geographical range for this data deficient species, to be taken into account for management and conservation purposes.This study was focused on conservation genetics of threatened  Hippocampus spp.) are endangered species due to population decline of many wild populations by means of direct overexploitation, incidental captures, habitat destruction and other anthropogenic perturbations /(8μ); μ: mutation rate [Signatures of genetic bottlenecks were investigated using the M-value method implemented in M_P_Val . Mean M-ion rate ) [50, 51ion rate , 52, 53.Population structureAST between pairs of population samples was estimated using Metapop v2.0.a1 [DEST and the standardized Hedrick’s [G”ST were estimated using GenAlEx v6.5 [G”ST is further corrected for bias when number of populations is small [Arlequin v3.11 [a priori grouping of samples according to their estuarine location  was perin v3.11  to assesG”ST against the logarithm of the geographical distances among the four estuaries of origin. Mantel test  was conducted to assess the relationship between genetic and geographical distances, using the software IBDWS [Isolation-by-distance over the studied distribution area was evaluated using the correlation of Rousset’s distance measure  based onre IBDWS .K) was inferred using the Bayesian MCMC approach implemented in Structure v2.3.1 [Ks tested (1 to 13) and the mean of Ln probabilities of data (Ln Pr(X|K)) across runs were calculated. Posterior probability of each K was computed from Bayes’ Rule [K was also estimated according to the Evanno’s ΔK statistic using Structure Harvester v0.6.94 [Structure output for the best ΔK was summarized to correct the variance across runs using Clumpp v1.1.2 [Distruct v1.1 [Number of population units , supplemented with captured Mysidacea (Leptomysis sp. and Siriella sp.).The conditions for the maintenance of the individuals in captivity were reported by Planas et al. , 12. BriGenepop, applying Bonferroni correction for multiple tests. Genetic diversity estimators , together with theoretical probabilities for exclusion  and for sibling identity (SI) were estimated using Cervus. DEST and G”ST between Stock09 and South-Atlantic wild population samples, as well as between Stock09 and Stock06 were estimated using GenAlEx .Genetic diversity in the renewed broodstock since 2009 (Stock09) was compared with the Galician wild population based on the complete set of 13 loci, and with the stock founded in 2006  between all pairs of breeders in the renewed Stock09 was computed using Wang estimator [SPAGeDi v1.2; [r-values for unrelated , half-sibs  and full-sibs  kinships were used as thresholds to classify individuals . The mi.375≤FS; , 71).Parentage analysis of wild and captive progenygerud 2.0 [Cervus.The renewed broodstock  was distributed in five aquaria (A to E) under unbiased sex-ratio treatment (5–7 M:5–7 F) to improve reproductive success based on previous data , 35. Temerud 2.0 , and theSpatial variation on either side of Cape Finisterre discontinuityH. guttulatus collected in 2006 from Cantabrian Sea (CS06) and South-Atlantic coasts . It was not associated to genotyping errors using Micro-Checker, which only showed signs of null alleles at Hgut6 at low frequency (0.03) in CS06. There was no evidence of linkage disequilibrium between all pairs of loci tested. There was no indication of spatial change in genetic diversity between CS06 and SA06, with no significant differences in number of alleles, allelic richness and expected heterozygosity . The spatial samples showed M-ratios around 0.7 which is a diagnostic value of genetic bottlenecks [M = 0.679 and 0.697 in CS06 and SA06, respectively). The M-ratio obtained in the whole dataset  was also lower than the cutoff value of 0.82 reported for stable natural populations [M-values reached statistical significance or were marginally significant  based on single spatial samples were 862 in CS06  and 200 in SA06 .Samples of ts SA06; ; Fig. 1 tlenecks   and standardized G”ST  values were obtained between CS06 and SA06. Allelic differentiation between both population samples was significantly different from zero at 0.05 level , with 26 private alleles although mostly rare at the most variable loci (only three with a frequency above 0.05). Similar results were observed when the only locus deviating from HW (Hgu-USC2) was excluded (Hgut4 (P = 0.0003) with two alternative alleles in CS06  and SA06 .Small and non-significantly different from zero excluded . HeterogSpatial and temporal variation along northwestern Iberian coastsStructure analyses for the global dataset (≈0). These same posterior probabilities of K were observed in the spatial analyses from the same year (CS06 and SA06). The highest ΔK was observed for K = 6 and K = 2 in the global and spatial analyses, respectively, using Structure Harvester, but none of them was consistent with a temporal or spatial clustering. Thus, the proportion of the sample assigned to each cluster was roughly symmetric (1/K in each population) and most individuals were fairly admixed  and Hgut6  were excluded from the global and spatial analysis . Only 0.47% was assigned to differences among temporal replicates within estuary  and no differences were found among estuaries . Correlation between genetic and geographical distances among estuaries was not significant . These data support geographical and temporal genetic stability (i.e. one panmictic unit) of H. guttulatus in the area under study.Results from  admixed ., indicaif K = 1 . SimilarHgu-USC7 in SA09 and Hgu-USC5 in SA11  were found using Micro-Checker. No significant deviations from HW expectations were detected after Bonferroni correction within each of the four temporal samples. Concordance to HW was observed when they were pooled. There were no indications of linkage disequilibrium between all pair of loci tested within temporal samples. No significant differences in genetic diversity were observed for allelic richness and heterozygosity estimators among the four temporal SA samples (P>0.05). Neither significant differences in genetic diversity by sex nor heterogeneity of allele frequencies between sexes within temporal samples have been detected. The temporal moment-based estimate of Ne was 1,602  in the South-Atlantic population sample of H. guttulatus (SA06 vs. SA11).Accordingly, South-Atlantic estuarine samples were grouped in four temporal samples for population monitoring along six-year period . The highest ΔK was observed for K = 2 using Structure Harvester, but with signs of genetic homogeneity  and between pairs of samples .According to the global structure analysis, a single population cluster including all temporal samples was also the most probable alternative using the Bayesian analysis (H. guttulatus (Stock09). No significant differences in genetic diversity were observed between the Stock09  . Similar genetic diversity was detected in the renewed Stock09  or known (Excl2: 0.9999), and for sibling identity (SI: 0.9988). Small and non-significantly different from zero estimates of genetic differentiation were observed between the renewed Stock09 and the founder Stock06 , as well as between the renewed Stock09 and the four temporal South-Atlantic wild population samples . These r) among breeders within the renewed broodstock of H. guttulatus ranged from -0.269 to 0.550 (mean r: 0.001). Relatedness estimates were low for most pairwise dyads , and high for only a few comparisons between breeders . Two of these latter corresponded to specimens of similar size collected from the same estuary and sampling date, thus suggesting real cases of highly-related individuals, beyond inherent error on individual pairwise r estimations [Pairwise relatedness coefficients  six The parentage analysis of the 39 batches revealed 30 full-sib families (FS), since some captive batches were assigned to the same mating pair ; Fig. 2.Variable mating behavior was observed from wild to captive conditions ; Fig. 2.Relatedness between effective mating pairs showed similar ranges in captive (-0.157 for FS30 to 0.315 for FS17) than wild (-0.144 for FS9 to 0.312 for FS6) reproductive events, with lower average in captivity  than in nature . Global relatedness between all pairs of reproductively successful breeders was 0.055 (SD: 0.152), in accordance with the management under low relatedness aquaria and natural mating system.A: 10.8; He: 0.59) and South-Atlantic  population samples of H. guttulatus in NW Spain was not significantly different to that described over five loci in other European populations of the species [P>0.05). These values were within the range reported for other seahorse species, such as the endangered H. capensis  or H. he: 0.53; ), but lo = 0.79; ).H. guttulatus in this study could be related with population demography, based on the decline reported in some coastal areas of Galicia [H. guttulatus does not suffer fishing pressure for international trade, and its major threat is related with the vulnerability of its habitat, often degraded by anthropogenic actions, such as coastal development, effect of fishing gear and pollution [M-ratio tests [Genetic diversity in  Galicia . In Spaiollution , 6, 76. io tests . Althougio tests .Ne) can aid to understand the population status of threatened seahorse species, such as H. guttulatus. Despite the necessity of being cautious of the accuracy of Ne estimation [Ne was observed in South-Atlantic and Cantabrian subpopulations of H. guttulatus. A larger but less precise Ne estimate was observed in the South-Atlantic subpopulation, with an infinite upper confidence limit. The lower limit that could be an indicator of the lowest possible level of Ne [Ne in such sample. Discrepancy between temporal and single-sample estimates suggests accuracy dependence on the sampling design, and this uncertainty should be taken into account for further management actions [Ne estimates would be closer to the metapopulation size of contemporary generations [Ne estimates than local census observed in the field surveys [Ne value, cautions about the population persistence on South-Atlantic and Cantabrian coasts should be considered from a conservation perspective in vulnerable habitats, to insure maintenance of genetic variation at the long-term [The estimation of contemporary effective population size . Other biogeographical barriers have been suggested eastern  or sout Biscay; , 89). Thnisterre , althougH. guttulatus throughout Cantabrian and South-Atlantic Galician coasts. However, two management units under continuous gene flow would be proposed based on the allelic distinctiveness (AST) detected between Cantabrian and South-Atlantic subpopulations. This parameter could be a key point in conservation programs because it gives idea of the potentiality for evolution among subpopulations, since allelic diversity variables are better predictors of long-term adaptation than gene frequency variables [This study supports the existence of a single panmictic population of ariables .H. guttulatus for the six-year period studied (2006–2012). It suggests that effective population size (Ne) could be large enough to buffer the effects of genetic drift, within the time frame of 2–3 generations, although the confidence intervals also alert about the smallest possible Ne in such population (see above). Continuous gene flow could lead homogenization avoiding the loss of genetic variation in the metapopulation of H. guttulatus. It was associated with low exposure coastal habitats in the underwater surveys, including bays, estuaries and harbors, as other seahorse species [Genetic diversity was temporary stable in the South-Atlantic population of  species . Seahors species , 91. Not species –94.ex situ maintenance for species that are prone to effects of human activities or are likely to become endangered in a very short time [H. guttulatus in NW Spain with conservation and research purposes [H. guttulatus in captivity, a key point to guarantee the long-term adaptive potential in conservation programs [The International Union for Conservation of Nature (IUCN) recognizes the importance of the ort time . Captiveort time . Since 2purposes . The genpurposes . It suggprograms .The high exclusion and sibling identity probabilities (>0.99) for the most polymorphic loci in the renewed Stock09 allowed the assignment to a single parent pair for all wild and captive batches of newborn seahorses. Each wild batch was compatible with a unique maternal genotype, suggesting different wild female parents  when further reproduced under captive conditions. Mate swapping was observed among different breeding seasons in this study (8%), mostly of females , as reported in this species . Howeveraptivity . Geograpaptivity , 101. InNaud et al.  have poiNe). Multiple mating and temporal polygamy can have similar effects on increasing Ne and improving the maintainance of genetic diverstity in a conservation context [Ne [H. guttulatus in captivity, that should be taken into account for management practices with conservation purposes.The mating systems may have large effects on effective population size  will maintain short-term genetic diversity (approximately 98% in one generation), but suggests caution about population management in captivity with the aim of ensuring its long-term adaptive potential [Family data showed higher breeder contribution in the renewed (72%) than in the founder  broodstotential , 95.Hippocampus guttulatus in the wild and under captive conditions, within an uncovered geographical range for this data deficient species [This study adds new genetic information about the conservation status of northwestern Iberian population of  species . Genetic species , 107 cou species ) for thrS1 FigStructure’s runs. A) Global analysis based on the set of 13 loci. B) Global analysis excluding Hgu-USC2; C) Spatial analysis based on the set of 13 loci. D) Spatial analysis excluding Hgu-USC2 and Hgut6. E) Temporal analysis based on the set of 13 loci.Consensus plots across ten (TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.


Paramuricea clavata is a habitat forming species, characterized by short larval dispersal and high reproductive output, but low recruitment. In the recent past, the species was impacted by mass mortality events caused by increased water temperatures in summer. In the present study, we used 9 microsatellites to investigate the genetic structure and connectivity in the highly threatened populations from the Ligurian Sea (NW Mediterranean). No evidence for a recent bottleneck neither decreased genetic diversity in sites impacted by mass mortality events were found. Significant IBD pattern and high global FST confirmed low larval dispersal capability in the red gorgonian. The maximum dispersal distance was estimated at 20–60 km. Larval exchange between sites separated by hundreds of meters and between different depths was detected at each site, supporting the hypothesis that deeper subpopulations unaffected by surface warming peaks may provide larvae for shallower ones, enabling recovery after climatically induced mortality events.Estimating the patterns of connectivity in marine taxa with planktonic dispersive stages is a challenging but crucial task because of its conservation implications. The red gorgonian  Extreme weather events, including floods, heat waves and droughts, are currently emerging as one of the most important facets of climate change, and a growing body of literature is focused on extreme events . AnomaloIf natural populations consist of reduced numbers of individuals, loss of genetic variability may dramatically influence the populations themselves, since genetically depauperate populations might fail to adapt to future environmental changes, eventually causing their disappearance. Due to the predicted intensification of weather extremes, many species may not have sufficient genetic potential for the evolution of strategies able to mitigate their impact. Nevertheless, genetic diversity reduction after mass mortality events is not a rule in the marine realm ; 6. TherConnectivity patterns and gene exchange among populations are major research topics in marine ecology and are essential for the planning of marine reserves , to funcParamuricea clavata  is a key species of sublittoral rocky habitats  and spatial distance [km] was tested using a Mantel test (n = 2000).The isolation by distance pattern was tested in GENEPOP. The shortest possible distance over sea between each reef pair was measured using Google Earth 7.1.2.2041. The relationship between genetic distance . Our research supports the hypothesis of ; 28 thatty event . In the ty event . Our finP. clavata populations affected by mass mortality events. This may be due to the lack of test power and other confounding factors, including recent expansion or Wahlund effects. Our research confirmed low larval dispersal capability in the red gorgonian, since the maximum dispersal distance inferred from our data was between 20 and 60 km. However, this reduced ability for dispersal during the larval phase may still be ecologically significant for population replenishment and persistence, enabling migration between local populations. Population recovery after mortality events may be dependent on the possibility of propagule immigration from external sources, such as Protected Areas. Additionally, migration between reefs located at different depths implies that deeper refugia may provide larvae for shallow subpopulation recovery after climatically-induced mortality events affecting mostly shallow sites.Our study failed to detect any genetic diversity loss in the S1 Fig(PDF)Click here for additional data file.S2 Fig(PDF)Click here for additional data file.S1 TableP. clavata populations in the Ligurian Sea.The allele sizes in 10 loci studied in 6 (XLSX)Click here for additional data file.


Intraoperative Cell Salvage (ICS), hereby referred to ‘mechanical red cell salvage’, has been widely used in adult elective major surgeries to reduce requirement for homologous red blood cell transfusion and its associated complications. However, amount of free haemoglobin (fHb) from ICS has been shown related to incidence of renal failure. fHb is the most important indicator of quality control of cell salvaged blood, thus monitoring the fHb concentration is imperative to minimise renal injury. However, currently there has been lacking quick biochemical markers to monitor the levels of fHb during ICS. The aim of this study was to screen quick biochemical markers for evaluating the amount of fHb during use of intraoperative cell salvage.Twenty patients undergoing elective cardiovascular surgery were enrolled. Blood was collected and processed using a Fresenius continuous auto-transfusion system device. The concentration of fHb, albumin (Alb), and calcium (Ca) in three washing modes were measured, and their clearance rates were calculated. The correlations among the clearances and concentrations of fHb, albumin, and calcium were analysed.fHb = 0.310CRALB + 0.686, R = 0.753, p = 0.000, CRfHb = 0.073 CR Ca + 0.913, R = 0.497, p = 0.000.In three washing modes, concentrations of albumin and calcium are significantly associated with amount of fHb:fHb(g/L) = 0.111Alb(g/L) –0.108, R = 0.638, p = 0.000; fHb(g/L) = 1.721Ca(mmol/L) +0.091, R = 0.514, p = 0.000. Furthermore, the clearance rates of albumin and calcium significantly predict clearance of fHb, CRIn clinic practice, clearance rates of albumin, or calcium can be used to evaluate the quality of salvaged blood, fHb. Bed-side measurement of calcium could offer a more feasible means for clinicians to undertake a real-time assessment of fHb. In the surgeries involving major blood loss, allogeneic red blood cell transfusion is often life-saving. However, allogeneic red blood cell transfusion has been shown to be associated with short-term and long-term complications of infectious diseases, non-infectious serious hazards of transfusion (NISHOTs) , or incrICS has now been widely used, as a substitution for allogeneic red blood cell transfusion, in adult elective major surgeries -12. OverThe institutional Ethics Committee of the Beijing Friendship Hospital approved the study proposal. Written informed consent was obtained from all participants. Adult patients undergoing elective cardiovascular surgeries with an estimated intraoperative blood loss of more than 800 ml were enrolled in this study. Exclusion criteria included the patients with haematopathy, malignancy, a contaminated operative field, or requirement for allogeneic red blood cell transfusion during current surgery.As we previously reported , FreseniThree phases are involved in the cell salvage. During phase 1, blood is collected from the operating field to the reservoir using heparinised physical saline as the anticoagulant. During phase 2, three modes: big flux mode, standard mode and high quality mode, were used to separate, wash and concentrate the cells to reinfusion bags. In phase 3, concentrated washed red cells are then reinfused into the patient.The blood samples were collected from the following time points and sites. The first time blood samples (3 ml) were obtained from venous blood. The second blood samples (10 ml) obtained from the reservoir following the blood in the reservoir was well mixed during phase 1. The third blood samples (5 ml ×3) were collected from the reinfusion bag after each mode was completed during phase 2. The volume of shed blood and the volume of reinfusion bag of each washing mode were recorded for calculating clearance rate. All blood samples were analysed within 20 min after collection.Free haemoglobin concentrations were measured using a HemoCue Plasma Low/Hb Photometer . Haemoglobin (Hb) concentrations were measured using a HemoCueHb 201+ Analyser . Albumin concentrations were measured using HITACHI 7600 automatic biochemical analyser (Japan), and the concentration of calcium and haematocrit (Hct) were measured using GEM Premier 3000 blood gas machine (USA). The internal quality control of HITACHI 7600 automatic biochemical analyser was done with the standard samples from Wako Pure Chemical Industries every morning, and external quality control was done with the samples provided by National Centre for Clinical Laboratories every four months. The quality control of GEM Premier 3000 blood gas machine was done with the standard samples from Instrumentation Laboratory.For the calculation of clearance rate, the concentrations of fHb, albumin and calcium in the reservoir and reinfusion bag, the volumes of shed blood in the reservoir for different washing modes, the corresponding volumes of washed blood in the reinfusion bag, the concentrations of Hb in the reinfusion bags of different washing modes were measured and recorded.The efficacy of collection, centrifugation, and washing was assessed by the clearance rate (CR) of fHb, albumin and calcium, which were calculated using the following equationsafter was the concentration of fHb, albumin or calcium of the washed blood in the reinfusion bag, volumeafter was the volume of washed blood in the reinfusion bag, solutebefore was the concentration of fHb, abumin or calcium of blood collected in the reservoir, and volumebefore was the volume of blood collected in the reservoir.Where soluteThe percentage of haemolysis was calculated using the following formula :Where fHb, Hb and Hct were the concentrations of fHb, Hb and haematocrit (Hct) in the reinfusion bag.All statistical analyses were performed using SPSS 13.0 software . Descriptive statistics were calculated on all measures to determine the characteristics of the sample, to check normality assumptions and to ensure adequate variability. All results are presented as mean ± standard deviation (SD) or incidence . Univariate linear regression analysis was applied to quantify the association of the clearance rates of fHb, albumin and calcium. A P-value of 0.05 was considered to be statistically significant.From March to November 2012, 20 patients  undergoing off-pump Coronary Artery Bypass Grafting surgeries (n = 13) and vascular surgeries with an American Society of Anaesthesiology physical status II-IIIwere enrolled to the study. The mean age of the patients was 60.0 ± 14.0 years old (49–81 years old). The mean preoperative concentration of albumin was 38.3 ± 3.1 g/L (31.0-42.4 g/L), and the mean of calcium was 2.20 ± 0.09 mmol/L (2.09-2.44 mmol/L), which were in the normal range. The concentration of albumin and calcium were 18.4 ± 5.1 g/L (9.8-31.4 g/L) and 0.61 ± 0.17 mmol/L (0.33-0.99 mmol/L) in the reserviors, 4.6 ± 1.6 g/L (1.2-8.4 g/L) and 0.19 ± 0.08 mmol/L (0.10-0.37 mmol/L) in the reinfusion bags. After the procedure of cell salvage, the concentration of fHb, clearance rate of fHb and the percentage of haemolysis see Table In each of these three modes,  there existed positive correlation between the concentration of albumin and that of fHb in the reinfusion bag. In the mode of big flow, fHb(g/L) = 0.118ALB(g/L) –0.166, r = 0.780, p = 0.000; in the standard mode, fHb(g/L) = 0.068ALB(g/L)-0.082, r = 0.659, p = 0.002; in the high quality mode, fHb(g/L) = 0.175ALB(g/L) –0.366, r = 0.663, p = 0.001. In combined three washing modes, the correlation between fHb and albumin in the reinfusing bag was fHb (g/L) = 0.111ALB(g/L) –0.108, r = 0.638, p = 0.000  = 1.608Ca(mmol/L) + 0.122, r = 0.564, p = 0.010; in the standard mode, fHb(g/L) =0.967Ca(mmol/L) + 0.211, r = 0.469, p = 0.037; in the high quality mode, fHb(g/L) = 2.676Ca(mmol/L) –0.075, r = 0.571, p = 0.011. In combined three washing modes, the correlation between fHb and calcium in the reinfusing bag was fHb(g/L) =1.721Ca(mmol/L) + 0.091, r = 0.514, p = 0.000 (see Table fHb ) and that of albumin(CRALB). In the mode of big flow, CRfHb = 0.295CRALB + 0.699, r = 0.638, p = 0.008; In the standard mode, CRfHb = 0.324CRALB + 0.675, r = 0.896, p = 0.000;In the high quality mode, CRfHb = 0.275CRALB + 0.719, r = 0.540, p = 0.017. In combined three washing modes, the regression relationship of clearance of fHb and clearance of albumin in the reinfusing bag was CRfHb = 0.310CRALB + 0.686, r = 0.753, p = 0.000 . In the mode of big flow, CRfHb = 0.261 CRCa + 0.734, r = 0.746, p = 0.000;In the standard mode, CRfHb = 0.111CRCa + 0.894, r = 0.760, p = 0.000; In the high quality mode, CRfHb = -0.100CRCa + 0.997, r = 0.592, p = 0.008. In combined three washing modes, the regression relationship between clearance of fHb and clearance of calcium was CRfHb = 0.073 CR Ca + 0.913, r = 0.497, p = 0.000  may be destroyed by the suction with negative pressure and centrifugation. These destroyed RBC will increase fHb. When the fHb level in plasma is > 1 g/L, the metabolic load may exceed the tolerance in adults, and methaemoglobin may form to cause organ injury. In particular, circulating fHb may precipitate within renal tubules, which leads to haemoglobinuria nephropathy and tubular dysfunction . HoweverHowever, in clinical settings, measurements of concentrations of fHb have to be undertaken in a specialised haematological laboratory, which usually takes more than two hours before the results become available. This is useless for clinicians to be able to manipulate the process of cell salvage to improve the quality of cell salvaged blood before reinfusion.Bed-side fHb analyser is currently available to be able to assay the concentration of fHb accurately in 60 seconds. But the instrument is too expensive to be applied widely.r 0.638, 0.896 and 0.540 for three washing modes  respectively. This association again has offered clinicians a feasible mean to learn the clearance rate of fHb from the clearance rate of albumin. However, like lactate dehydrogenase that was strongly correlated to fHb [The basic mechanism of autotransfusion system device is to eliminate the components that the molecular weight lighter than that of erythrocyte through the centrifuging. The molecular weight of albumin and fHb are 66000 Dalton and 67000 Dalton respectively, lighter than erythrocyte. Molecules of Alb and fHb should stay at the same layer and be eliminated together during the procedure of centrifuging, so the clearance rates of these two should be expected to be similar. Our study suggests there is a linear relationship between the concentrations of fHb and albumin. Therefore, the regression equation will allow us to calculate the concentration of fHb from the concentrations of albumin. Also, clearance rate of fHb is positively correlated with clearance of albumin and their correlation coefficient d to fHb , assays Potassium assay was suggested as a biochemical marker for evaluating the clearance of fHb, but the elimination of fHb during the washing process was not correlated with the residual concentration of potassium ,18. ThisEither heparin or citrate can be used for anticoagulation during red blood cell salvage. There existed controversy about which anticoagulant is best. Also heparin anticoagulation increased the fHb level compared to citrate, but the haemolysis rate was still in normal range . BecauseOur study has limitations, firstly, the fHb concentrations of patients’ blood were not tested before and after the transfusion of cell salvaged red blood cells; secondly, the study has a small sample size in cardiovascular surgery only. These findings are promising and further studies with larger sample size in a number of types of surgeries are needed to confirm these outcomes and to establish whether these clinical biochemical markers will offer utility in this regard.In summary, during the use of Continuous Auto Transfusion System device for cardiac and vascular surgeries, the concentration and clearance rate of albumin, and calcium can be employed as useful biochemical markers to evaluate the quality control of cell salvaged blood, fHb, in the washing modes of big flux, standard and high quality. Because the concentration of calcium can be assayed quickly using a blood gas machine in the operation room, bed-side measurement of calcium could offer a more feasible means for clinicians to undertake a real-time assessment of fHb.The authors declare that they have no competing interests.MT had the concept, PD designed and set up the study with supervision from MT and FGS. PD, JC and XL obtained the consents, collected all the samples and undertook the measurements. PD completed analysing the data with statistical support from a statistician and drafted the manuscript. FGS was chiefly responsible for the acquisition and interpretation of data and for finalising the manuscript. MT, FGS and PD also were involved in critical review of the manuscript. PD completed revision after submission. All authors read and approved the final manuscript.