Mytilus from six locations in southern Chile with 1240 SNPs obtained with RAD‐seq. Differentiation among locations with 891 neutral SNPs was low (FST = 0.005). Higher differentiation was obtained with a panel of 58 putative outlier SNPs (FST = 0.114) indicating the potential for local adaptation. This panel identified clusters of genetically related individuals and demonstrated that much of the differentiation (~92%) could be attributed to the three major regions and environments: extreme conditions in Patagonia, inner bay influenced by aquaculture (Reloncaví), and outer bay (Chiloé Island). Patagonia samples were most distinct, but additional analysis carried out excluding this collection also revealed adaptive divergence between inner and outer bay samples. The four locations within Reloncaví area were most similar with all panels of markers, likely due to similar environments, high gene flow by aquaculture practices, and low geographical distance. Our results and the SNP markers developed will be a powerful tool supporting management and programs of this harvested species.Chilean mussel populations have been thought to be panmictic with limited genetic structure. Genotyping‐by‐sequencing approaches have enabled investigation of genomewide variation that may better distinguish populations that have evolved in different environments. We investigated neutral and adaptive genetic variation in  Genetic data have been widely used in recent years to facilitate delineation of management units; however, this has been difficult for species with high gene flow and low differentiation Waples . Most maFST loci that are putative outliers have also been shown to be highly informative to determine the geographical origin of individuals  of reduced representation libraries like restriction‐site‐associated DNA  , and a subsequent study reported in a hybrid zone of M. chilensis, M. edulis, and M. trossulus in the Magellan Strait surrounding the international port of Punta Arenas  is an important commercial species in Chile, and it is distributed along approximately 1900 km of the Chilean coast from the Arauco Gulf (35°S) in the north to Cape Horn (55°S) in the south (Hernández and González M. chilensis has been explored using five RAPD primers (54 presumptive dominant loci), and with seven and 26 allozyme loci, in populations from Arauco (35°S) to Punta Arenas (53°S) , with the possible exception of an austral population from Punta Arenas (53°S). Studies with microsatellite markers have found similar results of limited genetic structure  was used to extract DNA using the phenol–chloroform method described by Larraín et al. (2012). Extracted DNA was quantified using the Quant‐iT dsDNA pico‐green assay kit  in 96‐well plates and a Perkin Elmer Victor 5 plate reader. Since some of the collected individuals were too small (15–25 mm) to identify phenotypic species, these samples were tested with diagnostic species markers as described by Larraín et al. (2012). In brief, primers Me15‐16 produce different sizes of amplicons by species: 180 pb for C‐value) published for M. galloprovincialis of 1.92 pg . Two libraries were constructed containing 96 individuals per library and 500 ng DNA per individual. In each library, pooled individuals were tagged by ligation of one of 96 unique 6‐bp barcode adapter (P1 adapter) to the SbfI site, and 4 μg was sheared by sonication using a Bioruptor UCD‐300 instrument . After sonication, each library was concentrated using the Qiagen MinElute PCR purification kit  and submitted to AMPure bead purification and size selection . Size selection was performed on each library by first binding DNA fragments larger than 700 bp with a 2:1 ratio of DNA to beads, followed by a 1:1 ratio of DNA to suspension buffer (binding DNA fragments larger than 200 bp) in order to yield final products with DNA fragments ranging from 200 to 700 bp. Prior to sequencing, RADtag libraries were quantified by quantitative PCR  on an ABI 7900HT Sequence Detection System . The libraries were then sequenced in a total of four lanes (two each) by single‐end 100 base reads using an Illumina® HiSeq 1500 sequencer . The total number of reads obtained was 822,488,647, of which 738,252,110 passed the quality filters and were retained for SNP identification (89.76%). The number of sequences obtained per individual ranged from 155,007 to 21,512,094 with an average of 4,236,976 reads. Two individuals from Pichicolo were excluded from subsequent analysis due to low number of quality reads .Restriction‐site‐associated DNA (RAD) libraries were prepared with the restriction enzyme s et al.  and sequSoftware package, version 1.08  less than 5% were removed, retaining 4305 SNPs for further steps. Second, 2140 SNPs were removed because they were not genotyped in all six populations. Third, only one bi‐allelic SNP per RADtag was permitted, removing another 865 SNPs. Fourth, to filter out potential paralogous markers, 60 SNPs were removed because they showed significant deviations from Hardy–Weinberg equilibrium .Two scenarios using LOSITAN  using the R package adegenet 3.1‐1 Jombart  was perfFST/(1−FST) and the logarithm of geographical distance estimated following the coastline among pairs of locations, with 10,000 permutations in program ISOLDE implemented in Genepop on the web (http://genepop.curtin.edu.au/index.html).Isolation‐by‐distance (IBD) gene flow analysis using a Mantel test Rousset  was perfMytilus individuals to their geographical origin  and with the double cross‐validation proposed by Anderson  using thThe number of RADtags predicted using SimRAD was 8530 close to the mean number of RADtags obtained per samples with STACKS . In these RADtags initially were included 16,888 presumptive SNPs in the catalog, in which 4305 SNPs were genotyped in the 70% or more samples. However, after subsequent filtering, a final panel of 1240 SNPs was retained with an average genotyping success of 90% in the remaining 190 samples.Average expected heterozygosities per location across all 1240 SNPs were similar, with values of 0.2321 for Caleta La Arena, 0.2322 for Quillaipe, 0.2330 for Canutillar, and 0.2333 for Pichicolo in the Reloncaví zone, 0.2328 for Canal Coldita in Chiloé Island zone, and 0.2244 for Isla Peel in Patagonia zone.FST CI 99.5%), with 17 shared SNPs between both scenarios. Outlier tests also identified 981 putatively neutral loci for scenario 1, which fell inside of a conservative CI of 10–90% of FST distribution.Outlier analyses run in LOSITAN identified 58 and 34 SNPs as candidates for positive selection among scenarios 1 and 2, respectively  but significant . Higher global genetic differentiation was observed in scenario 2 with a FST of 0.088  with the panel of 34 SNPs and for scenario 1 with a global FST of 0.114  for the 58 SNP panel.Global FST values for the neutral panel were not significantly different from zero for 10 of the 15 interlocation comparisons as shown by 95% confidence intervals, and significant values were only observed in comparisons where Isla Peel location (Patagonia zone) was involved  and the four populations from Reloncaví zone, but with a higher average pairwise FST than scenario 1 of 0.159.On the other hand, the location Canal Coldita from Chiloé Island zone shows moderate genetic differentiation with the other four populations from Reloncaví Gulf with an average pairwise FST values in both scenarios. However, there were two exceptions with the comparisons between Pichicolo and Caleta La Arena for scenario 1  were identified with DAPC with two discriminant functions extracted with 60 principal components retaining a 93.3% of conserved variance. For scenario 2, again three clusters (K = 3) were observed with 50 principal components retaining a 97.8% of conserved variance  on DAPC for the putatively neutral panel was obtained for ters K =  were ideThe three clusters observed in scenario 1 correspond to the three main geographical zones included in this study Fig. . All indIn scenario 2, DAPC classified 83.9% of samples from Canal Coldita (Chiloé Island zone) in one cluster. Assignment to this location with the panel of 34 SNPs was 87.1% (27 of 31 samples) for LOO method and 86.7% 13 of 15 samples) for STH method  and outlier SNPs in scenario 1  since they included the most distinct and geographically distant collection from Patagonia. However, for scenario 2 , the IBD Spearman correlation was nonsignificant (rS = 0.6485 right‐tailed P = 0.1491).The IBD analysis showed significant and positive Spearman correlations for the neutral SNP panel  but significant differentiation with the five northern locations, confirming the findings of Toro et al.  in Reloncaví zone, outer bay exposed to open sea influence in Chiloé Island, and extreme climatic conditions in Patagonia zone (scenario 1) with different contribution of freshwater and variable levels of salinity. Across these three zones, the 58 outlier SNP panel showed the highest levels of genetic differentiation ever reported among collections from these three different zones, and they consistently discriminate individuals collected from these three geographical areas using DAPC, LOO, and STH reallocation methods. This pattern of genetic differentiation was concordant with an effect of isolation by distance at a large geographical scale. Our analyses support strong genetic differentiation between the Patagonia location and northern locations (Reloncaví and Chiloé Island zones). This is consistent with previous studies using RAPD and allozyme markers  to 21.0 ppt in Quillaipe and similar average water temperature  were distinct from the other two zones, supporting the finding that the population of ch Stotz . Active ch Stotz  and seedch Stotz . This sich Stotz , suggestFST outlier detection method FDIST2 used here  have only achieved 50.7% correct re‐assignment to origin locations which is too low to be used effectively in traceability applications (Larraín et al. Traceability of aquaculture products is necessary in order to effectively regulate poaching and overharvest of natural populations, maintain genetic diversity of propagated stocks (e.g., Ogden M. chilensis with these FST outlier SNP panels is much improved but it is necessary in future research, to test the effectiveness of these panels in a wider zone and across years to evaluate the temporal stability of allele frequencies.In conclusion, our study demonstrates that species with high gene flow may require analyses at different geographical scales and multiple panels of putative adaptive loci to reveal hidden population structure. The SNP marker panels developed here increased assignment accuracy compared to previous microsatellite loci, probably due to the use of adaptive loci and the number of markers employed. Genetic traceability for None declared.Data S1. Name of SNP makers developed for Chilean mussel.Click here for additional data file.


Pachygrapsus marmoratus, common across the north-eastern Atlantic Ocean, Mediterranean and Black seas. Previous studies revealed no or weak genetic structuring at meso-geographic scale based on mtDNA, while genetic heterogeneity at local scale was recorded with microsatellites, even if without clear geographic patterns. Continuing the search for phylogeographic signal, we here enlarge the mtDNA dataset including 51 populations and covering most of the species’ distribution range.The extent of genetic structure of a species is determined by the amount of current gene flow and the impact of historical and demographic factors. Most marine invertebrates have planktonic larvae and consequently wide potential dispersal, so that genetic uniformity should be common. However, phylogeographic investigations reveal that panmixia is rare in the marine realm. Phylogeographic patterns commonly coincide with geographic transitions acting as barriers to gene flow. In the Mediterranean Sea and adjoining areas, the best known barriers are the Atlantic-Mediterranean transition, the Siculo-Tunisian Strait and the boundary between Aegean and Black seas. Here, we perform the so far broadest phylogeographic analysis of the crab This enlarged dataset provides new evidence of three genetically separable groups, corresponding to the Portuguese Atlantic Ocean, Mediterranean Sea plus Canary Islands, and Black Sea. Surprisingly, hierarchical AMOVA and Principal Coordinates Analysis agree that our Canary Islands population is closer to western Mediterranean populations than to mainland Portugal and Azores populations. Within the Mediterranean Sea, we record genetic homogeneity, suggesting that population connectivity is unaffected by the transition between the western and eastern Mediterranean. The Mediterranean metapopulation seems to have experienced a relatively recent expansion around 100,000 years ago.P. marmoratus is shaped by the geological history of Mediterranean and adjacent seas, restricted current gene flow among different marginal seas, and incomplete lineage sorting. However, they also caution from exclusively testing well-known biogeographic barriers, thereby neglecting other possible phylogeographic patterns. Mostly, this study provides evidence that a geographically exhaustive dataset is necessary to detect shallow phylogeographic structure within widespread marine species with larval dispersal, questioning all studies where species have been categorized as panmictic based on numerically and geographically limited datasets.Our results suggest that the phylogeographic pattern of The online version of this article (doi:10.1186/s12862-016-0720-2) contains supplementary material, which is available to authorized users. Terrestrial and marine biogeographic regions all over the world are defined based on the distribution of extant species. Boundaries separating adjacent regions may derive from historical breaks or from present-day environmental differences and may contribute to giving rise to genetic discontinuities within species and to allopatric speciation events.The Mediterranean Sea has a long and complex geological history that has contributed to its high biodiversity and high proportion of endemisms . This epBased on range distributions, community composition of marine fauna and differences in salinity and winter surface temperatures, the Mediterranean Sea can be subdivided in two main basins, a western and an eastern one, separated by the Strait of Sicily . MoreoveMeganyctiphanes norvegica corresponding to the north-eastern Atlantic, the western Atlantic, the Alboran Sea and the Mediterranean Sea. The swordfish Xiphias gladius is another example of genetic isolation among Atlantic and Mediterranean populations [Palinurus elephas notwithstanding its long larval phase, with the existence of separated gene pools in the Atlantic Ocean, the western and eastern Mediterranean Sea, respectively [Boundaries among basins and sub-basins can act as barriers to dispersal of marine organisms at different orders of magnitude, shaping intra- and inter-specific marine diversity (reviewed in ). Evidenulations  and geneulations . A similectively –10.Tursiops truncatus, for example, are genetically and morphologically differentiated from Mediterranean and Atlantic conspecifics [Phocoena phocoena is represented by an endemic subspecies, P. phocoena relicta, in the Black Sea [Calanus constitute another well-studied example of marine invertebrates whose Black Sea populations are genetically separated from those of the Atlantic, western Mediterranean, Adriatic and Aegean populations [Another relevant phylogeographic transition is the boundary between the eastern Mediterranean basin and the Black Sea through the Marmara Sea. The Black Sea is a relatively small semi-enclosed body of water differentiated from the adjacent Aegean Sea in terms of its chemo-physical conditions and biodiversity . Currentpecifics , while tlack Sea . Copepodulations .Pachygrapsus marmoratus  . This species occupies the upper and middle shore levels of the rocky coasts of the Mediterranean Sea, Black Sea and north-eastern Atlantic Ocean, from Brittany to Morocco, including the Canary Islands, the Azores, and Madeira [Most of these examples of intraspecific differentiation refer to pelagic species, while few ones report about the influence of seal level changes on benthic coastal species. Thus, the aim of this study is to investigate intraspecific differentiation in one of the most common, widely distributed and best known invertebrate species of the Mediterranean Sea, the marbled crab  Madeira , 17. Not Madeira , and thu Madeira  before t Madeira , 21. Con Madeira –24. OverP. marmoratus covering the Atlantic Ocean, the various basins and sub-basins of the Mediterranean Sea and the Black Sea  with the twofold aim of: 1) depicting the effect of currently recognised biogeographic breaks on the geographical distribution of intraspecific genetic variation; and 2) uncovering how historical events may have contributed to shape patterns of intra- and inter-population genetic diversities.In this study, we gathered a very large dataset to investigate regional population genetic structure and phylogeographic pattern of the marbled crab Sea Fig. . With rePachygrapsus marmoratus were included in the present phylogeographic study, of which 246 were specifically analysed de novo and the remaining 341 had been previously published: 238 sequences from western Mediterranean and Atlantic by Fratini et al. [A total of 587 samples of i et al. , 98 sequi et al.  and fivei et al. . SpecimeTotal genomic DNA extraction was performed from muscle tissue using the Puregene Kit (Gentra Systems) or the Salting Out extraction method . DNAs wehttp://www.bmr-genomics.it). Unpublished haplotypes were submitted to molecular databases (accession numbers KX529672-KX529696). The sequences were corrected manually with the program CHROMAS version 1.55  and aligned by eye with BioEdit ver. 7.2.5 [Selective amplification of 658 basepairs of the mtDNA CoxI was performed as reported in Fratini et al. , using ti2)n/n ‐ 1, where xi is the frequency of a haplotype and n is the sample size), and the nucleotide diversity  [The nucleotide composition as well as the number and type of mutations were calculated with MEGA6 . The numcentage)  were calcentage) .http://www.fluxus-engineering.com/sharenet.htm) to assess the intra-specific evolutionary relationships among the haplotypes of P. marmoratus. Genetic differentiation among populations was estimated by one-way AMOVA [Ф) [Фst values, under the null hypothesis of no differentiation, were computed by permutation tests from 10,000 random permutations of haplotypes between populations and, when appropriate, populations between groups. When needed, multitest corrections were performed following the B-H method [http://webs.uvigo.es/acraaj/SGoF.htm).A minimum spanning network was built with NETWORK version 4.5.0.1   were comMOVA [Ф) ). AdditiH method  using thH method ; http://Фst pairwise values). The analysis was run using the covariance-standardized method as implemented in GenAlex 6.5 [To visualize the occurrence of genetic structure and setting our biogeographic hypotheses, we performed a Principal Coordinates Analysis (PCoA), based on the genetic distances among all pairwise combinations of populations   to fit dr. 1.8.3 . BSP plor. 1.8.3 , 47, andr. 1.8.3  was usedr. 1.8.3  was usedr. 1.8.3 .Our mtDNA CoxI alignment was cropped to a length of 596 basepairs. It has an A-T rich nucleotide composition , as commonly found in the mitochondrial DNA of arthropods . The datMost haplotypes differ from each other by single or very few mutations Fig. . The netThe average haplotype and nucleotide diversities are 0.75 ± 0.02 and 0.27 ± 0.1, respectively . After correcting for multiple tests with the B-H method [Фst pairwise values. The Black Sea populations are genetically separated from all the Atlantic populations with very high Фst values (from a maximum of 0.92 recorded for AZ vs TH to a minimum of 0.38 for CK vs CA) and from most of the Mediterranean populations . Alternatively, we included the Alboran population within the Atlantic group, for testing the hypothesis that the Atlantic-Mediterranean transition could be located at the Almería-Oran Front in line with the break reported for other species by Patarnello et al. [Фct were slightly lower, being equal to 0.32 (P < 0.001). When the Atlantic population from Canary Islands (CA) was grouped with the Mediterranean populations, in line with the PCoA results, the Фct value increased to 0.36 (P < 0.001). Finally, a separation among the main Mediterranean basins was not underlined from a further 2-way AMOVA, splitting the Mediterranean group into three subgroups , as indicated from the lower Фct value respect to those associated to the previous biogeographic hypotheses .Based on the As Table . First, The neutrality tests provided evidence of departure from mutation-drift equilibrium, since all the tests  recorded significant values for the overall population and the three geographic groups . Among Xantho , 54 and Pilumnus , the her. alatus , and therocarpus  show lithic area , 21. HowP. marmoratus with more than 550 individuals from 51 populations distributed from the Atlantic Ocean to the Black Sea. Our results clearly reveal genetic differentiation of populations from the Black Sea from those of the Mediterranean Sea and Atlantic Ocean. The distribution of genetic variation in P. marmoratus is thus strongly determined by the biogeographic barrier between the Aegean and Black seas, known to restrict dispersal for many marine species at past and present times .Patella [P. marmoratus larvae, as reported for other marine species . Interestingly, the here included population from Canary Islands, which is situated southwest to the Gibraltar Strait, does not appear to belong to the Portuguese Atlantic lineage. A similar latitudinal phylogeographic break has been reported for two limpets of the genus Patella  and it wiewed in ). But a iewed in ). Sampliiewed in . HoweverP. marmoratus individuals. Previous population genetic studies based on the same mtDNA marker recorded no or only a subtle separation between Mediterranean and Atlantic populations [P. marmoratus is the result of the complex geological history of Mediterranean Sea and adjacent seas, past isolation due to Pleistocene glaciations, reduced current gene flow in association with the main geographic boundaries, and incomplete lineage sorting.In this study, we report for the first time sharp geographic breaks in the genetic composition of ulations , 21. TheAs clearly shown by the network and genetic diversity indices, Mediterranean populations present higher average levels of intraspecific genetic variation in comparison to Atlantic and Black Sea populations. This result could be partially produced by the overall larger Mediterranean sample size. However, possible differences in evolutionary history in the different basins may argue against the possibility that it is a simple sampling artefact. The low haplotype and nucleotide diversities observed in the Black Sea and Atlantic population can also be the likely result of a strong bottleneck and founder effect, due to past and current isolation.P. marmoratus followed this route and expanded within the entire Mediterranean Sea or if it survived the Messinian Salinity Crisis in local refugia within the Mediterranean Sea, as suggested for Carcinus aestuarii by Marino et al. [P. marmoratus has been affected in more recent times by the drastic paleoclimatic events occurring during the Quaternary period. In correspondence to the repeated glaciations and the associated sea level changes during this time, the contact between the Mediterranean Sea and adjoining epeiric seas was likely interrupted, while during interglacial periods it was plausibly re-established. Based on the geographic distribution of haplotypes, we suppose that the main direction of these fluxes was from the Mediterranean to the Atlantic Ocean and Black Sea, as two of the most common haplotypes of the Mediterranean Sea are represented in low percentages in Atlantic and Black Sea populations . The BSP results also support the effect of paleoclimatic events on P. marmoratus genetic composition, since a clear sign of demographic expansion was found for the Mediterranean metapopulation, dated around 60,000-180,000 years ago, i.e. long before the Last Glacial Maximum. In contrast, the Black Sea lineage showed evidence of demographic stability according to the BSP. The Black Sea was a freshwater lake during the Last Glacial Maximum [Following the opening of the Gibraltar Strait, 5.33 million years ago, most of the Mediterranean marine fauna and flora arrived from the Atlantic Ocean . It is co et al. , and sub Maximum  and thusP. marmoratus within the Mediterranean Sea, as already reported from previous studies based on the same mtDNA marker [P. marmoratus. Larvae of P. marmoratus spend approximately one month in the water column and appear to be able to maintain connectivity among populations, likely following a stepping-stone model, i.e. the most common model for marine species with wide distribution ranges [Our study recorded genetic homogeneity of A marker , 21. Then ranges , 62. Hown ranges , 60, 63)n ranges ).P. marmoratus at local scale, even if without clear association to geography. Fratini et al. [P. marmoratus population structure. Notwithstanding, mtDNA markers do not produce a priori higher estimates of gene flow than hypervariable nuclear markers, as recently stated in Karl et al. [High level of gene flow can be the reason for lack of substructure within the Mediterranean Sea. However, we have to keep in mind that genetic studies based on microsatellite polymorphisms –24 repori et al.  hypothesl et al. . FurtherPachygrapsus marmoratus across its distribution range and unravel the existence of three distinct phylogeographic lineages, corresponding to the Portuguese Atlantic Ocean, the Mediterranean Sea plus Canary Islands, and the Black Sea. Their genetic distinctiveness is likely the consequence of geological and paleoclimatic processes, historically affecting Mediterranean Sea and adjacent waters, and it may currently be maintained by present-day geographic breaks and species-specific biological traits. Local adaptations to climatic conditions and environmental parameters may contribute to increase the recorded genetic differences among lineages. Morphometric and eco-physiological studies on individuals from the three geographic clusters should be interesting for corroborating this hypothesis.This is the first study to provide clear evidence of genetic differentiation of


Microvelia horvathi (Hemiptera: Veliidae). Three hypotheses were developed using ecological niche models (ENM). We tested these hypotheses using mitochondrial (COI + COII) and nuclear data (ITS1 + 5.8S + ITS2). The phylogenic analysis revealed a shallow divergence in mitochondrial data. Clade I was mostly confined to the northern region and clade II was nearly restricted to the southern region. The historical process of Pleistocene climatic fluctuations during the LGM promoted divergence, along with such geographical barriers as the Wuyi, Nanling and Xuefeng mountains and ecological factors of temperature and vegetation type, contributed to these shallow genetic divergences and helped maintain them. The north-south population differentiation probably occurred during the transition from LIG to LGM, with post-LGM population expansion. The results of genetic data were mostly consistent with the spatial predictions from ENM. Our study emphasizes the multiple effects influencing genetic population differentiation, and also contributes to our knowledge of the phylogeography of other aquatic organisms in subtropical China.Subtropical China is a centre of speciation and well known for its high biological diversity and endemism. To understand the impact of historical, geographical and ecological factors on the intraspecific lineage divergence of invertebrates, we examined these processes in a semiaquatic bug,  Understanding the historical and environmental factors that influence the genetic structure of populations is important for studying the mechanisms of adaptive divergence and speciation. In the Northern Hemisphere, patterns of contemporary population genetic structure of extant species have been greatly affected by Pleistocene climatic fluctuations, such as range expansion or isolation in glacial refugiaCeratosolen sp.Castanopsis eyreiParus monticolusMicrovelia dougalsi douglasi14The Asian subtropics are a global biodiversity hotspot considered to be one of the most important areas of endemism for many organisms7Phylogeography has benefitted from recent developments in GIS technology, which now allows a more powerful investigation of the geographic components of genetic variationMicrovelia horvathi Lundblad 1933, which belongs to the familiy Veliidae (Insecta: Hemiptera), and is found in the subtropics of China, Japan and Korea. This species usually lives on the quiet water surfaces of nearshore areas, including rain pools, ditches, swampy ground, or paddy fieldsMany previous phylogeographical studies have focused on plant and vertebrate species in subtropical China10M. horvathi in the present, the LGM and the LIG. ENM projected that M. horvathi potential spaces contracted and were ultimately isolated in two mainly separated refugia (northern and southern refugia) where they underwent major divergence , indicating good predictive model performance. The current niche-predicted distribution of this species was generally similar to its actual distribution, with a potentially continuous range in subtropical China and a fragmentary range in southern Japan and Korea . When prnd Korea . When thnd Korea .For the mitochondrial data, 1405 bp of protein-coding regions of mitochondrial genome were obtained from 250 individuals, including sections of the COI (726 bp) and COII (679 bp) genes. Ninety unique haplotypes were derived among all individuals. The 96 polymorphic sites included 67 singleton variable and 29 parsimony informative sites. The nucleotide diversities and haplotype diversities ranged from 0.00057 to 0.00360 with an average of 0.00262, and 0.378 to 1.000 with an average of 0.845, respectively . NJ analM. horvathi was not apparent in the nuclear data  (P < 0.001), but not in nuclear DNA   . However < 0.05) . The Man 0.3120) .D, Fu and Li’s D*, and the significance of Fu’s Fs   .M. horvathi. Three of eight comparisons were significant  and precipitation in the driest month . The PCA-env results suggested the two different lineages might not occupy identical habitat, but the differences could simply be due to the differential availability of habitat in the different regions that they occupied , and all these populations also showed haplotype diversities both from clade I and clade II   . In concM. horvathi. This conclusion was based on the relatively strong coincidence between the northern and southern structural groups and zoogeographical fauna in subtropical ChinaM. horvathi inhabited temperate deciduous forest and evergreen broad-leaved forest. In contrast, in the Oriental Realm, it mostly inhabited monsoon rain forest, evergreen broad-leaved forest and island monsoon rain forest, which were warmer and had more precipitation during the year. Among many present-day ecological factors, SEEVA analysis . The PCR procedure for COI, COII and nuclear markers (ITS1 + 5.8S + ITS2) included an initial denaturation at 94 °C for 2 minutes, followed by 31–33 cycles of 30 seconds at 92 °C, 30 seconds at 48–52 °C and 1 minute at 72 °C, ending with a final extension at 72 °C for 8 minutes. The chromatograms of sequences were unimodal, which excluded pseudogene disturbance. Sequences were visually proofread and aligned in Bioedit 7.1 softwareWe selected 31 sampling sites for in China , Fig. S1http://www.worldclim.org/) that were thought to most likely restrict semi-aquatic bugs distributionA total of 47 occurrence records were obtained for niche modeling, including 33 records from the alcohol preserved specimens and 14 records from pinned specimens in Nankai University or the published literature. We chose the seven bioclimatic variables from the WorldClim database (S), haplotype distribution (Hap), number of haplotypes (Nhap), haplotype diversity (Hd), and nucleotide diversity (π), which were all calculated in DNASP 4.0p distances to reconstruct an unrooted NJ tree to elucidate the phylogenetic relationships among mitochondrial haplotypes of M. horvathi using PAUP* 4.0b10We estimated genetic diversities by the number of polymorphic sites . The other approach used a Bayesian coalescent-based method  in BEAST 1.8.2. A relaxed uncorrelated lognormal molecular clock was applied. We ran the chains for 100 million generations, and checked to make sure the ESS was more than 200, after which the first 10% were discarded as “burn-in”.Then two methods were used to estimate population expansion time. One approach used M. horvathi. First, we tested the correlations between the ecological divergences and the phylogenetic splits using spatial evolutionary and ecological vicariance analysis (SEEVAhttp://www.worldclim.org/). Quantitative variables  were scored as ordered continuous data, while the qualitative variables (vegetation type) were treated as non-ordered categorical data. We divided these variables into four states according to the default setting in SEEVA. We investigated the correlations between ecological shifts and the phylogenetic splits using Fisher’s exact tests and divergence indices (D). Second we used PCA-env function in the R scriptD, with values ranging from 0 to 1, or from more to less similar respectively.We used two approaches to test ecological divergences between two phylogenetic lineages of sis SEEVA. We extrHow to cite this article: Ye, Z. et al. Phylogeography of a semi-aquatic bug, Microvelia horvathi (Hemiptera: Veliidae): an evaluation of historical, geographical and ecological factors. Sci. Rep.6, 21932; doi: 10.1038/srep21932 (2016).


Sesame is an important oil crop widely cultivated in Africa and Asia. Understanding the genetic diversity of accessions from these continents is critical to designing breeding methods and for additional collection of sesame germplasm. To determine the genetic diversity in relation to geographical regions, 96 sesame accessions collected from 22 countries distributed over six geographic regions in Africa and Asia were genotyped using 33 polymorphic SSR markers. Large genetic variability was found within the germplasm collection. The total number of alleles was 137, averaging 4.15 alleles per locus. The accessions from Asia displayed more diversity than those from Africa. Accessions from Southern Asia (SAs), Eastern Asia (EAs), and Western Africa (WAf) were highly diversified, while those from Western Asia (WAs), Northern Africa (NAf), and Southeastern Africa (SAf) had the lowest diversity. The analysis of molecular variance revealed that more than 44% of the genetic variance was due to diversity among geographic regions. Five subpopulations, including three in Asia and two in Africa, were cross-identified through phylogenetic, PCA, and STRUCTURE analyses. Most accessions clustered in the same population based on their geographical origins. Our results provide technical guidance for efficient management of sesame genetic resources in breeding programs and further collection of sesame germplasm from these different regions. Sesamum indicum L.) has been described as one of the oldest oilseed plants used by humans [n = 2x = 26 chromosomes that belongs to the family of Pedaliaceae, Sesamum genus, and is the most commonly cultivated edible oil crop species out of over 30 species in this genus [Sesame  among major oilseeds . Beyond Africa and Asia account for more than 96% of the world sesame seed production, with India, Sudan, and China as leading producer countries . Sesame Sesamum malabaricum Burm [The origin of cultivated sesame and the process underlying its domestication have been controversial, though Africa and Asia were identified as probable origins ,18,19,20cum Burm ,21.Genetic diversity of crops plays an important role in sustainable development and food security , as it aKnowledge of the genetic diversity and population structure of germplasm collections is an important foundation for crop improvement and a key component of effective conservation and breeding strategies . It is tMolecular characterization is now the favorite way to quantify variation within germplasm samples. Many studies have dissected the genetic diversity of sesame accessions using different types of molecular markers (Random Amplified Polymorphic DNA (RAPD) ,26,27, IIn this study, we examined the genetic diversity of a representative set of sesame accessions from 22 countries of Africa and Asia. The overall goal is to provide a comprehensive insight into sesame diversity between and within these continents for a better management of the genetic resources used in breeding programs.Sesamum indicum L., 2n = 2x = 26), comprised of landraces and modern cultivars representing geographically and phenotypically wide variation, were used in this study. Among these accessions, 48 were collected in nine African countries and 48 in 13 Asian countries  method . Moreove2. All PCRs were conducted in 96-well plates in a S-1000 Thermal Cycler . The PCR cycles were 94 °C (5 min), 35 cycles of 94 °C (30 s), 55 °C (30 s), 72 °C (30 s), followed by the extension step for 5 min at 72 °C. The amplified products were separated in 6% denaturing polyacrylamide gel and visualized by silver staining as described by [SSR polymorphism screening was first performed using 4000 candidate markers and six accessions (three accessions from Africa and three from Asia). A total of 33 highly polymorphic SSR markers  were selribed by .For each locus across the genotypes, allele scoring was done manually based on the presence of a particular size allele in each of the germplasm samples. Presence was denoted as “1” and absence of an allele as “0.” For variability analysis within accessions, only two individuals from the same accession (K1712) displayed different alleles from the 10 others at one marker. Thus, further analyses focused on the bulked samples of the 96 accessions, which were grouped into six populations according to their geographical origins as indicated in k (1 to 10) representing the number of clusters considered. The burn-in number and iterations for each run were both set to 100,000 and the true k was determined according to the method described by [A Neighbor-Joining (NJ) tree based on Nei’s genetic distance  was alsoribed by . Sesame A pre-test for assessing the variability within 24 accessions from West Africa with a single plant DNA extraction approach was performed. Out of the 35 markers used, only the marker ZMM1522 was polymorphic (2.86%), with two individuals among the 12 from the accession K1712 exhibiting different alleles. This result suggests that the genotyped accessions were relatively homozygous. Two markers including the marker ZMM1522 from the 35 markers were excluded and the 33 marker-genotype combinations that displayed clear bands were retained to analyze the bulked samples of the 96 accessions.Thirty-three polymorphic SSRs were used to assess the genetic diversity in a sesame panel, with at least two markers per linkage group. A total of 137 alleles among the 96 sesame accessions were observed . Number vs. 4.8). Ne values ranged from 1.265 (West Asia) to 1.458 (South Asia). Values of He also varied among the different groups and ranged between 0.343 (North Africa) and 0.598 (South Asia). Asia showed relatively higher He values than Africa. The Shannon’s Information index (I) values ranged from 0.209 (West Asia) to 0.414 (South Asia).Diversity indices varied greatly between the six geographical regions. Among them, the highest MAF (0.7) was observed in North Africa (NAf), whereas quite similar MAFs were found in the five other groups . The anaOut of the 137 alleles, 49 (35.77%) were specific to geographical origin. West Africa and East Asia exhibited the highest private allele numbers , but no private alleles were found in West Asia, which might be due to the low sample number from this area. In general, the data showed that Africa harbored more private alleles (30) than Asia (21).South Asia showed the highest PIC value (0.5421), whereas North Africa showed the lowest PIC value (0.2828). Generally, accessions from Asia displayed relatively higher values for He, I, and PIC than those from Africa.The genetic distance matrix generated by GENALEX 6.4 was used for Principal Component Analysis of the 96 sesame accessions . The firThe AMOVA results indicate that 44.66% of the total molecular variation in sesame accessions used in the study was partitioned among geographical groups, and 55.34% was attributed to differentiation within geographical groups . In termk value corresponding to the genetic groups, the ad hoc quantity Δk was used. The highest value of Δk for the 96 sesame accessions was for k = 2  according to STRUCTURE with er k = 2 a. It waser k = 2 b. Subpopvs. individuals), and the number of SSR markers. In addition, the bulked sampling approach used in this study may have the tendency to influence the estimates of the diversity indices compared to the individual sampling approach, which is more informative. The genetic diversity observed in African accessions was lower than Asian accessions as shown by He, I PIC, and AMOVA results. These findings are in agreement with the low genetic diversity in African materials previously reported by [This study analyzed the genetic diversity and population structure of cultivated sesame accessions from Africa and Asia using 33 SSR markers. SSRs have widely been used in genetic diversity and evolutionary analysis in many crops because of their low cost, high polymorphism information content, reproducibility, co-dominant nature, and complete genome coverage ,46. The orted by . In anotorted by , sesame orted by ,48,49.The findings from our study are in agreement with the earlier reports of sesame domestication from India ,21 in thIt was observed in the study that accessions from three regions, namely East Asia, South Asia, and West Africa, had the highest diversity indices, suggesting that these regions contained more genetic diversity of sesame than the other geographical regions. Previous works ,26 have Earlier works in rice and sorghum where the researchers used 1794 worldwide accessions of rice and 3367 accessions of sorghum showed some level of correlation between geographical origins and SSR patterns ,54.We observed a close genetic relationship between accessions from East Africa, North Africa, and Guinea in West Africa to the accessions from Asia in the study. This close genetic relationship observed might be due to the introduction of sesame into many countries and material exchange from widely separated locations . For insAccording to , sesame Finally, contrary to the conclusions of , based oA few previous studies have compared sesame’s genetic diversity between Asia and Africa, but in those studies the authors did not include a representative set of African materials compared to the Asian samples included. Our results fine-tune the previous knowledge about sesame diversity in both continents using a set of representative accessions. Large sesame germplasm collections are available in the gene banks of many countries such as the United States, South Korea, China, and India ,34. Howe


BreedingSturgeons”). This information was used to plan a breeding scheme considering familiar groups as breeding units and identifying mating priorities. A two-step strategy is proposed: a short-term breeding program, relying on the 13 remaining F0 individuals of certain wild origin; and a long-term plan based on F1 families. Simulations to evaluate the loss of alleles in the F2 generation under different pairing strategies and assess the number of individuals to breed, costs and logistical aquaculture constraints were performed. The strategy proposed is transferable to the several other tetraploid sturgeon species on the brink of extinction.In species with long life cycles and discontinuous availability of individuals to reproduction, implementing a long-term captive breeding program can be difficult or impossible. In such cases, managing diversity among familiar groups instead of individuals could become a suitable approach to avoid inbreeding and increase the possibility to accomplish a breeding scheme. This is the case of several sturgeon species including the Adriatic sturgeon, whose recovery depends on the management of a few captive stocks directly descended from the same group of wild parents. In the present study, relatedness among 445 potential breeders was inferred with a novel software for pedigree reconstruction in tetraploids (“ The first one is the complete genetic characterization of all breeders available in captivity in order to quantify the amount of genetic variation and to assess the purity of the stocks. Typically, captive stocks contain only a fraction of the original genetic variability present in the larger wild population. A second goal aims at retaining and transmitting most of the residual genetic diversity to the future generations of captive breeders, thus securing the long-term future of the species i.e. the “breeders unit”, for the production of the future generations In this regard, pedigree-based management practices are used to identify candidate breeders, International Union for Conservation of Nature (IUCN) are the most threatened group of species in the world, with 85% of sturgeons being at risk of extinction (http://www.iucnredlist.org). The decline of sturgeon populations is mostly attributed to human activities, including overexploitation for the harvesting of caviar, habitat degradation, damming of rivers and poaching i.e. slow growth, late age at maturity, 2-years or more resting stage between reproductions) complicate breeding plans as selected individuals might not be available when needed for reproduction. Moreover, sturgeons show high juveniles mortality, which might translate into different number of retained fingerlings from each reproduction that reaches maturity. This can result in broodstocks composed by different familiar groups with unbalanced sizes. Consequently, in the absence of pedigree information, the risk of mating close relatives can be high, thus increasing relatedness and distorting founder diversity Among fishes, the need of establishing long-term captive programs is especially urgent for sturgeons, which according to the recent report (March 2010) of the Acipenser naccarii), an endemism of the Adriatic region. Given its tetraploid status With the aim of proposing adequate approaches for the management of broodstocks composed by familiar groups that differ in size and genetic composition, we focused on the Adriatic sturgeon . A breeding program was initiated in 1977 with the transfer of ca. 50 immature wild individuals (F0) to the private aquaculture plant Azienda Agricola V.I.P. . Since the late 1980s, following the first successful reproduction in captivity BreedingSturgeons”), candidate breeders were identified. A breeding plan was then designed based on family groups as breeding units. The rationale of using families rather than individuals is based on the fact that selected individuals might not be available for reproduction when needed due to the particular complex life history traits of sturgeons (i.e. they reproduce every other year), but related individuals might be available instead. Our breeding program was also supported by simulations in order to estimate the loss of genetic diversity under different scenarios as well as to evaluate the sustainability of the plan from an economic and logistic point of view. The present approach can also be applied to many other species of sturgeons whose recovery depends on the establishment of ex situ strategies based on captive broodstock.In the present study, we used a pedigree-based approach to conduct the characterization of the stocks available at the Azienda Agricola V.I.P. Plant, including (1) all remaining individuals of the parental F0 stock, and (2) a large number of F1 individuals retained from many breedings performed in the facilities during the last 30 years. After pedigree reconstruction using a new allocation program specific for tetraploid species  exempted this study from review because it was an extra moenia activity. Nevertheless, we tried to minimize the impact of sample collection on the animals. All samples were collected in aquaculture facilities by the owners. Fish were kept into the pond water to minimize stress and were released immediately after sample collection, which consisted of painless clippings from the caudal fin. No mortality, pain or stress was observed.We analyzed a total of 42 individuals from the parental stock F0, already genotyped at 24 microsatellite loci We also analyzed 445 F1 individuals. In July 2003, about half of the F1 individuals died due to a poisoning incident and only 233 animals survived. All analyses were conducted considering the full F1 data set  and considering those F1 alive at present .Our analysis also includes 133 individuals from the Ticino River Park in Italy for comparison. This individuals are part of a stock established from a very limited number of breeders Genomic DNA was extracted from fin-clip (10–100 mg) using the DNA Easy Tissue Extraction Mini Kit (Euroclone) and stored at −4°C.Prior to the analysis, species status of all individuals was assessed using mitochondrial DNA haplotypes plus species-specific SNPs at the S7 and Vimentin genes Finally, in order to detect the presence of other species or interspecific hybrids, the analyses of the mitochondrial control region was supplemented with the scoring of species-specific SNPs in two genes, the ribosomal Protein S7 and Vimentin, following the approach developed in R). The interpretation of microsatellite patterns in tetraploids is not straightforward due to the presence of multiple alleles at each locus that can be present in more than one copy, thus the true genotype cannot be accurately resolved. As an alternative, we used the classic band-sharing approach as proposed in All F1 individuals were genotyped at 7 microsatellite loci: LS-39 BreedingSturgeons”) was implemented to estimate an allocation compatibility index for each F1 individual to all possible parent pairs in the F0 stock, assuming a tetrasomic mode of inheritance with no dominance A new software (“ci(x), of an individual to a putative parent pair as: ci(x) = ∑[A(p1)+A(p2)]/4, where A(pi) is the number of alleles that could have been inherited from parent-i. A(pi) can vary between 0  and 2 . And ci(x) can vary between 0 and 1. Multi locus estimates of compatibility indexes were obtained as average across all microsatellites loci. In this procedure the following assumptions must be satisfied: a) all the offspring alleles should be shared with the parental pair, b) two of the offspring alleles must be shared with the mother and two with the father, c) a complete heterozygote can not transmit two copies of the same allele. The above conditions should be satisfied by at least one of the inferred genotypes in the two parents and in the offspring.For all possible pairs of putative males and females in the F0 stock and the F1 individuals, we inferred all possible tetraploid genotypes compatible with the observed microsatellite profiles at all loci. We defined a single locus compatibility index, Each F1 individual was allocated to the parent pairs associated with a compatibility index above a threshold  chosen to account for possible genotyping errors at one locus.Individuals that could not be assigned to any parent pairs  probably represent the progeny of wild F0 individuals died before the characterization of the F0 stock. All individuals allocated with a compatibility index higher than the threshold value were checked for mitochondrial concordance with the putative mother.We also used the program to test the power of the set of 7 microsatellite loci used for parental allocation. To do so, we generated 1,000 virtual F1 profiles from the F0 individuals. We identified the allocation power of our microsatellite panel as the fraction of virtual F1 profiles unequivocally allocated back to the correct parental pair.In order to identify closely related individuals  among not-allocated animals, distributions of pairwise genetic distances between full- and half-sibs were created and threshold values under which 99% of comparisons between animals with a given degree of relatedness were identified A “whole-family” approach (rather than a single-breeder approach) was used. The parent pair of each family was considered to be representative of the genetic diversity of the corresponding progeny. This allowed using a higher amount of genetic information since all the F0 individuals are genotyped at 24 loci In the case of families with unknown pedigree, estimation of genetic distances from the cumulative profile of parents was not possible. In these cases, parental profiles were inferred cumulating the phenotypes of their offspring using the 7 loci genotyped for parental allocation analysis. Genetic distances estimated on these partial profiles were included in the matrix after observing a significant positive correlation  between distances estimated at 24 and 7 loci by using the Mantel test implemented in PopTools priority families”) for reproduction was estimated based on how often the parents of each family were already represented in the F1 “breeders unit”. This value was estimated by averaging the number of progeny of the two parents across all the families in the “breeders unit”. In this way, the smallest families with under-represented parents were the first to be selected for reproduction. The above values were then converted into an ordinal scale (“priority”). Following the established order, each priority family was then paired with the more distant one (named “mating family”) selected from among all of the families available in the “breeders unit”.The strategy proposed for the breeding plan is based on the following three criteria: (a) prioritize families with higher genetic value, (b) exclude crosses between families with a shared parent and (c) avoid already-performed crosses. Priority of the different families . This choice was necessary to avoid that some families with a high genetic distance from many others were used in too many crosses. This process was implemented in the R software “BreedingPlanSturgeons” also used to compare the different pairing strategies described in the following paragraph.With the aim of excluding crosses between half-sibs families, starting from the F0 profiles at 24 loci, all the possible combinations of virtual families (cumulative profiles) sharing one parent were created and the pairwise genetic distances estimated. The highest distance observed (0.35) was used as threshold value to exclude all crosses involving a shared parent. In the selection of the mating families we imposed the constraint that each mating family” was manually identified and a single cross suggested.For the families whose parents were unknown, the information at 7 loci was used, which yielded a threshold value of 0.45. These families were excluded from the automated analyses and for each of them the more distant “CostsBreedingSturgeons” , was developed to infer the number of crosses that can be simultaneously performed in a given hatchery. It includes the estimate of costs and yields of a given breeding program based on the number of individuals generated and reared until release. It also considers that at the beginning of the third year , a fraction of the individuals are retained in the facilities in order to preserve the captive stock, while the rest of individuals can be released into the wild.A first R-script, “e.g. mortalities and growth rates at different life stages) and costs  in order to estimate the total financial cost of the project. Additional variables are reported in Table A in We took into consideration the following constraints: number of individuals that can be induced every year, availability of ponds for rearing families separately until tagging and maximum number of animals that can be hosted. We also considered biological features , was developed to estimate the expected fraction of alleles of the F1 stock that are successfully transmitted to the progeny under different breeding strategies. To this purpose, the program “BreedingSturgeons”  was applied to generate a virtual F2 progeny from the observed F1 microsatellite phenotypes. The minimum number of individuals to be crossed in order to ensure the transmission of all F1 alleles was estimated. Based on the order of the “priority families”, four different scenarios were simulated in which the “mating families” were chosen by “Maximum Distance”, selecting 1, 2, 3 or 4 individuals per family  or with “mating family” selected for having the higher genetic distance (Priority – Maximum distance). The process of random selection of the “mating family” was repeated 100 times for each “priority family” and for each resulting combination breeders were randomly extracted from the two families. Also the extraction of the breeders was repeated 100 times for each family to minimize possible effects of differences due to intra-family diversity. Finally, from each virtual cross, 20 fingerlings  vs. priority order of the first family with “breeders unit” was not considered since this information was not available. Moreover, all families for which less than 24 loci were genotyped were excluded from the simulations. For the above simulations RStudio was used.In all the above simulations, the sex of animals of the “Prior to the analysis, species status of all individuals was assessed using mitochondrial DNA haplotypes  plus speThe number of individuals showing each haplotype in the two stocks  were: 0/0; 118/53, 220/106, 0/0, 75/45, 4/0, 37/23 for haplotype 1 to 7 respectively. A total of 11 individuals  were heteroplasmic, presenting a double peak in the chromatogram sequence, and were counted as two different haplotypes for the analysis. When comparing genetic diversity across generations , the F1 Measures of genetic diversity at microsatellite loci are detailed in Prior to the parental allocation analysis, the power of the markers was assessed using 1,000 virtual F1 individuals. Using the 7 microsatellite set, a correct assignment of 92% was observed. Hence, we can consider the set of microsatellites to be informative enough for parental allocation procedures.Parental allocations at 7 microsatellite loci for all the F1_V.I.P. individuals (N = 445) are summarized in Table C in A short-term breeding plan including the 13 F0 individuals still alive at present  was designed after evaluation of the genetic relatedness of the individuals . We aimebreeders unit”: 30 reared at V.I.P.  plus two families from the Ticino River Park . Pairwise genetic distances among families are shown in The long-term plan was designed based on the F1 progeny, using a family-based approach. A total of 32 crosses was planned, one for each of the 32 families that composed the “In the case of 4 not-allocated and 2 allocated families, generated by a single F0 female . Induction of fish is not straightforward but assuming to induce 5 males and 5 females per cross, at least one successful reproduction is expected. Number of individuals at the 2ividuals  after asrd year, after tagging, the progeny is split into a fraction that is retained in a common tank with all other families to preserve the captive broodstock and a fraction that can be released into the wild. On the basis of a 10% yearly mortality, ca. 140 individuals are retained  can be released into the wild . At the start of the 3retained  in orderthe wild . FinallyBreedingPlanSturgeons” to estimate the optimal number of breeders are presented in Results from simulations using the script “Finally, results from simulations conducted to compare three alternative mating strategies are shown in ex situ captive breeding plan based on genetic and demographic information upon which to establish management decisions. The program here proposed meets the two principals generally required in captive breeding: (i) the complete genetic characterization of all the individuals and (ii) the planning of a breeding scheme that minimizes genetic relatedness in order to maximize genetic variability. One particular characteristic of our breeding plan is that is “family-based” in contrast with most breeding plans that are “individual-based”. One of the difficulties when working with sturgeons is that adults are only reproductively active every other year or more rarely. This represents a serious problem since a selected individual might not be available for reproduction when needed. However, this problem can be avoided by using a family rather than a single individual approach, so that related individuals might be available instead.We present the first breeding plan for the Adriatic sturgeon, a species which is believed to be possibly extinct in nature and whose future entirely relies on the implementation of an BreedingSturgeons”) and based on the inference of all possible genotypes compatible with observed band profiles, showed a higher allocation efficiency compared with the simple band sharing approach Pedigree reconstruction was applied to characterize the F1 stock retained at the V.I.P. plant and produced by crossing F0 individuals in the last 20 years. The approach implemented by the new software , compared to the 35% estimated for the stock reared by the Ticino River Park A. naccarii F0 gene pool but these are not the only new alleles detected. Additional alleles not present in the parental generation were also found among not-allocated F1 individuals. The presence of new alleles in the F1 might be explained by inheritance from F0 breeders that died several years ago and are not present in our sample. Alternatively, F1 individuals carrying new alleles might be hybrids produced in the hatchery and accidentally mixed into the stock. Accordingly, accepting the risk of losing rare variants we chose to exclude from the broodstock all the animals carrying extra alleles.Finally, our results also show how important is to test for the presence of hybrids or alien species. In many aquaculture facilities, different species or interspecific hybrids are reared, so that mixing of individuals can accidentally happen, and those can go unnoticed unless properly tested. In our case, two reciprocal hybrids between Adriatic and White sturgeon were found within the F1 progeny. As expected, hybrids showed microsatellite alleles not present in the In the case of the Adriatic sturgeon, recruitment of new breeders from the wild is not possible since the species is possibly extinct in nature, so a breeding plan using wild breeders can only be achieved using the original F0 brought to the V.I.P. facilities in 1977. However, the F0 stock at the V.I.P. plant has been greatly reduced in size in recent years, probably due to senescence. While only 13 individuals remain at present, we propose a priority short-term breeding program to be attempted with these remaining F0 individuals. The plan includes 6 females and 7 males for a total of 18 selected crosses on the basis of pairwise genetic distance . It shouWe present a complete long-term breeding plan based on familiar groups that aims at generating enough animals to ultimately allow for the re-introduction of the species back into its natural environment. Considering the low chances of successful reproduction of these animals and their limited number, most efforts were devoted to developing a long-term breeding strategy involving families of F1 generation, assuming that at least some of the individuals are reproducible every year.founder assumption”, in which wild founders of a captive population are assumed to be equally unrelated The program starts with the exclusion of combinations between families sharing one parent, together with families that do not share any parent but show low genetic distances, which might be indicative of relatives. This allows minimizing possible errors due to the “priority family” are not available, one possibility is to postpone the cross until the following reproductive season and to slightly modify the priority order. If the unavailable individuals belong to the “mating family”, one possibility is to save the priority order and to select an alternative “mating family”, choosing the second more distant family. As shown by simulations, selection of family combinations based on priority and genetic distance were more efficient in transmitting the higher possible number of alleles to the next generation relative to the random strategies (“Priority – Random” and “Random – Random”). This was particularly true when number of crosses was low, which suggests that random approaches are not recommended for short-term programs. In fact, the higher standard deviation of the two strategies in which at least one family is randomly selected may result in a significant loss of allele diversity after few generation of captive breeding. Accordingly, the breeding plan here proposed was based on the Priority – Maximum distance approach. On one side, the establishment of a priority score allows to first cross those families whose genetic traits have the higher risk to be lost, since they are shared by a lower number of individuals in the population. On the other side, the use of maximum distance minimizes inbreeding and tends to increase the number of crosses involving families that are genetically peculiar, and consequently, are more often selected as “mating families”.Our choice of keeping separated for two years the animals produced by different family combinations, until the moment of tagging, limits the number of crosses that can be simultaneously performed with a finite number of ponds. However, it allows tracking the pedigree of every single animal providing useful information for monitoring the release program or for managing the following generation of captive broodstock. Alternatively, instead of crossing one individual per family, it could be considered to cross more individuals of the same family that can be pooled and do not require additional ponds. This would also increase the efficiency of allele transmission and guarantee that all F0 alleles of each family are inherited by the F2 generation, as shown by simulations that suggest the use of at least 3 breeders from the same family when possible. However, these numbers might be not easy to reach given the small size of some families and the discontinuous availability of breeders for reproduction . Moreover, if breeders of the “ex situ conservation plans through the retention of part of the fingerlings as future breeders is the only way forward. In this context, the approach here developed based on the management of familiar groups instead of individuals can become of major interest. Moreover, for those species that share with the Adriatic sturgeon the tetraploid condition, such as the Russian sturgeon (A. gueldenstaedtii), the Persian sturgeon (A. persicus), the Chinese sturgeon (A. sinensis) and many others, the methods here optimized are directly transferable. This would allow a careful identification of familiar groups thus providing the basis for the establishment of breeding programs that takes into account the genetic composition of the available broodstock together with logistic and economic constraints.The present work represents the first breeding plan for the Adriatic sturgeon based on its detailed genetic characterization and can be considered as a reference guideline for all conservation actions based on controlled reproductions of this species. As in the case of Adriatic sturgeon, many other sturgeon species are critically endangered with greatly reduced wild populations and a consequent difficulty in collecting breeders from the wild. For such species the establishment of ex situ management for meeting conservation goals. The low cost of microsatellite markers facilitates the collection of genetic data that can inform breeding programs about the best pairing individuals so as to minimize mean relatedness. In our study, as few as 7 microsatellite markers were sufficient to unambiguously allocate all F1 individuals. In the event of higher number of putative parents, which might be the case in other sturgeon species, the number of microsatellites should be increased to ensure complete allocation.Our study also showcases the importance of genetic approaches to ex situ genetically heterogeneous broodstocks is the starting point for the rehabilitation of self-sustaining natural populations. However, in the short run, the survival rate of the released fingerlings depends on their capability do adapt to the target environment. In this sense, the establishment of adequate rearing protocols aimed to produce individuals with a high probability of survival is strongly encouraged. As clearly reported in FAO guidelines for sturgeon management and release Since genetic diversity is an essential prerequisite for the long-term adaptive potential, the availability of As important as it is to use genetic studies into conservation practices, those need to be coordinated and not be carried out separately and restrictively. In the case of the Adriatic sturgeon, at present several local administrations are active in the attempt of recovering the species in its historical natural range. Unfortunately, these actions are often represented by short-term programs and are completely isolated and uncoordinated. Therefore, providing a common program like the one presented in our study that can connect and integrate the different actions would represent the first step towards a responsible concerted management of the Adriatic sturgeon. Finally, in order to implement successful conservation strategies, important actions against habitat degradation are urgently needed including the restoration of natural spawning sites and the re-establishment of river connectivity (i.e. fish passages at dams). A relevant challenge for conservation genetics is to go beyond the scientific since reintroduction is not merely a biological issue but a social, cultural and political one as well. An important part of the framework required for the successful incorporation of genetic data into conservation decision-making of culturally-important species is involvement where possible of local people in the program, together with public education about the project.File S1Tables with additional details about the two R-scripts and samples analyzed are reported. Tables A and B include a brief description of variables used in the two R-scripts. Table C reports details about results of parental allocations.(DOCX)Click here for additional data file.File S2“CostsBreedingSturgeons” and “BreedingPlanSturgeons” scripts. The zip file includes all system and executive files to run programs. As example, input files used to run “BreedingPlanSturgeons” script are also included.(ZIP)Click here for additional data file.


Genetic diversity within species may promote resilience to environmental change, yet little is known about how such variation is distributed at broad geographic scales. Here we develop a novel Bayesian methodology to analyse multi-species genetic diversity data in order to identify regions of high or low genetic diversity. We apply this method to co-distributed taxa from Australian marine waters. We extracted published summary statistics of population genetic diversity from 118 studies of 101 species and > 1000 populations from the Australian marine economic zone. We analysed these data using two approaches: a linear mixed model for standardised data, and a mixed beta-regression for unstandardised data, within a Bayesian framework. Our beta-regression approach performed better than models using standardised data, based on posterior predictive tests. The best model included region  bioregions), latitude and latitude squared. Removing region as an explanatory variable greatly reduced model performance (delta DIC 23.4). Several bioregions were identified as possessing notably high genetic diversity. Genetic diversity increased towards the equator with a ‘hump’ in diversity across the range studied (−9.4 to −43.7°S). Our results suggest that factors correlated with both region and latitude play a role in shaping intra-specific genetic diversity, and that bioregion can be a useful management unit for intra-specific as well as species biodiversity. Our novel statistical model should prove useful for future analyses of within species genetic diversity at broad taxonomic and geographic scales. Genetic diversity can be considered the most basic level of biodiversity ,2. The nMany factors will influence genetic diversity within populations. Neutral population genetic diversity is expected to be proportional to long-term effective population size and mutation , which iConversely, recent work has demonstrated that marine community evenness  decreased towards the equator due to the presence of a greater number of rare species . We mighBioregions represent an attempt to delineate areas containing distinct species assemblages, common across a broad range of taxa. Such regions are likely to possess similarities in both evolutionary history and environmental characteristics, making them a useful unit for testing biogeographic hypotheses . Common In order to determine within species genetic diversity patterns at a broad geographic scale, large amounts of data are required. A synthetic analysis that makes use of existing data from previously published studies has many advantages. Most notably, information can be obtained for a large number of species across a broad geographic extent, for very little cost and low effort. Without such a comprehensive data set, the description of ecosystem scale patterns is compromised. Combining data across multiple studies involves substantial challenges that need to be recognised. These include: combining data from different genetic markers and measures of genetic diversity, uneven geographic sampling, and uneven taxonomic sampling. However, the benefit of being able to generalise across a broad range of species and geographic extent should outweigh these disadvantages, where care is taken in the analysis see –37)..37]).http://www.ala.org.au; )To allow a more direct comparison, both analysis methods 1) ‘standardised’ (Z) and 2) ‘unstandardised’ (H), were executed within a Bayesian framework using the software WinBUGS version 1.4.3 , called We tested the utility of all combinations of five explanatory variables for each analysis type. These variables were: sample size (n), marker (M), species (S), latitude (L), latitude squared (L2) and region (R). Sample size was included as an explanatory term for the dispersion of our measure of genetic diversity . GenThe model for standardized data  can be formally written as:Ri CAR prior) and S is the species effect . For further details please see The model for unstandardized data  can be written as:All models were assessed based on: 1) Deviance Information Criteria score  and 2) Once the best model was determined (based on DIC and PPP results), a final run of 500 000 iterations, with thinning every 100 iterations and a burnin of 50 000 was performed. We report the mean as a measure of central tendency and 95% central posterior density intervals for regional mean genetic diversity and latitude effects where appropriate. Models were run for data from coastal regions only, ensuring all data sets used had a minimum of 3 populations once outer regions were excluded. To assess variation in geographic patterns between different taxonomic groups, in addition to the coastal region data set containing all species , models were also run for a dataset comprised of Actinopterygii and Chondrichthyes (ray-finned and cartilaginous fish) , and Mollusca , separately.E or h from 101 species . From these we obtained 1154 population data points containing either H species . Coastalth of January 2015 detected 978 new publications, of which 57 matched our criteria. These included major taxonomic groups in similar proportions to those identified previously, with Molluscs (7/57) and Crustaceans (6/57) still under represented based on the number of known species around Australia. However, 25% of studies had sites located in either the Australian Bight or Joseph Bonaparte Gulf, suggesting that progress is being made towards a better understanding of these regions.From 100 papers identified through an ad hoc search by author, 76 were already captured in our database, suggesting we may have missed 24% of relevant literature in the time period we surveyed. Additional ad hoc searches of taxonomic groups that were under represented in our database (Platyhelminthes and Annelida) did not yield any new articles. Our search of articles from mid 2012 to the 20Sample sites for population genetic studies were not evenly distributed around Australia . The majThe region co-sampling cluster analysis indicated that neighbouring regions commonly shared surveyed species . An exceThe taxonomic spread of species targeted for population genetic studies was wide, however most ‘broad operational taxonomic units’ contained small sample sizes . The topNo model for standardised data passed the posterior predictive tests for fit . This inThe best overall model, based on both DIC and PPP scores, was the ‘unstandardised’ model that contained species, marker, latitude, latitude squared and regional effects  and 29  had notably high genetic diversity and region 39 (Southern Qld / N NSW) was notably low , Fig 2. 2 = 0.02, p = 0.26). However, when comparing regions where Molluscs were sampled with at least 10 populations there was no relationship between the entire dataset and Molluscs , S1 Fig.This study represents the largest synthesis to date of marine population genetic studies at an Australia wide scale. We have developed statistical methods to allow the regional analysis of population genetic data from multiple sources. This well parameterised Bayesian method appears to be an improvement over the more commonly used ‘standardisation’ approach, based on posterior predictive testing. Region was found to be a useful explanatory variable in describing the broad scale distribution of genetic diversity, in addition to latitude. Genetic diversity increased towards the equator, however the relationship between diversity and latitude was best described as ‘humped’, rather than linear. Our study has identified several regions as having either higher or lower genetic diversity than those around them (particularly high diversity in the Joseph Bonaparte Gulf (IMCRA 26) and low diversity in southern Queensland, northern NSW (IMCRA 39). Describing this regional variation represents a first step towards understanding the broad scale processes that might be driving them.The distribution of information on population genetic diversity was uneven around Australia. Sampling was primarily coastal and highest on the east coast of Australia, particularly the Great Barrier Reef. While well studied, the southern GBR has not often been co-sampled with other regions,. This lack of co-sampling of the GBR with other regions has previously been identified based on a dataset of tropical species spanning the Indo-Pacific . The ‘ToThere are over 32000 species recorded in major databases as occurring in the Australian marine economic zone, though, based on the rate of discovery of undescribed species, the actual number is far higher . While wGenetic information, in combination with other methods, is extremely useful for defining biological stocks ,64, an uGenetic diversity followed the expected negative relationship with latitude, increasing towards the equator. Species richness has a strong correlation with latitude , whiIMCRA region was a useful concept to explain the distribution of intra-specific genetic variation, both for standardised and unstandardised data. Regional patterns persisted after latitude had been accounted for, and so additional explanations for these differences are needed. Three regions were found to possess ‘high’ levels of genetic diversity (The Joseph Bonaparte Gulf (26), NW coast (27) and the Central West coast (29)), and one possessed ‘low’ diversity (Queensland/northern NSW (39), based on the best fitting unstandardised model.Areas of high diversity might represent regions of admixture, where distinct evolutionarily significant units overlap . High wIt was surprisingly difficult to limit a search to the marine environment in a specific geographic area, despite attempting to do so across five different databases. While we may have extracted data from approximately 75% of relevant publications, it is unlikely that there was a strong taxonomic bias in this missing data due to our search methodology. It is possible that there was some geographic bias, as some databases required the use of place names to restrict to location. However, as we included the terms ‘Joseph Bonaparte Gulf’ and ‘Australian Bight’ we believe our finding that these regions were under sampled remains valid. Our survey of recent literature suggests that while taxonomic biases remain, some progress is being made towards a better understanding of the Great Australian Bight and Joseph Bonaparte Gulf. We hope that this first attempt to summarise population genetic research in the Australian marine environment will provide a useful starting point for future researchers.The majority of population genetic analyses performed on wild species to date have utilised neutral genetic markers, due to their greater tractability for analyses. It may be that for conservation purposes, functional genetic diversity is of greater relevance, as this diversity will result in a change in an organism’s phenotype, however there generally appears to be weak correlation between functional and neutral genetic diversity ,77. FurtThe majority of studies considering broad patterns of population genetic diversity, by necessity, focus on common, widely distributed species (e.g. ). Rare sTaxonomic groups were not evenly represented across regions and, despite the inclusion of species as an explanatory variable, this taxonomic bias will have influenced our results. This is evidenced by the low regional mean obtained for molluscs from the highest diversity region in the entire and ‘fish’ only data sets , S1 Fig.Pelagic marine species richness was shown to peak in the mid latitudes (20–40 degrees), whereas coastal species peaked in the western Pacific, close to the equator . Our stuWe focus on regional means, and do find some significant results, yet the large standard deviations we obtained indicate extensive variation exists within regions , Fig 2. Posterior predictive testing provided greater support for the unstandardised Bayesian models, indicating that these models were better able to reproduce results comparable to the observed data. It is perhaps not surprising that there was little correspondence between estimates of regional means using the two methods. Using the standardised approach, we removed the effects of marker and species by giving each study the same mean. While this does allow studies to be compared directly, we lose information as to whether some species have higher ‘absolute’ levels of genetic diversity. It is possible that the Bayesian analysis has captured geographic variation in ‘absolute’ genetic diversity to some extent, allowing a broader exploration of geographic variation in intra-specific diversity.Additionally, to accurately standardise data requires a good understanding of the underlying mean and distribution for the species. For studies with few populations sampled, z-scored data will not be accurate, and this inaccuracy may detract from the underlying signal obtained from better sampled species. This may be the reason our standardised models failed all posterior predictive tests. If sufficient populations were available to calculate a reliable mean and standard deviation for a study, z-score transformed data may provide useful insight into whether areas possess unusually high or low genetic diversity relative to the species as a whole. However, if only smaller sample sizes are available, this may generate so much noise in the data that the results may be of limited use.While the unstandardised Bayesian approach represents an advance in statistical methods for combining summary statistics calculated from diverse genetic marker types and species, further improvements are possible. If more data were available, a larger number of genetic marker categories might improve model performance. McCusker and Bentzen  found suData collected for this analysis suggests that there are gaps in available information for some marine regions around Australia, particularly for most offshore regions, the Great Australian Bight and Gulf of Carpentaria (though this may be improving), and for taxonomic groups such as Crustacea and Mollusca. Analysis of co-sampling of species across regions indicated that species from the southern GBR (region 40) were often not sampled in other regions. Only 20% of Australia’s top 49 commercial marine species were included in this analysis. Expansion of this database would allow these gaps to be confirmed and prioritised for future research.ST. While careful statistical analysis would be required to take into account factors such as distance between populations, and population genetic diversity and its influence on estimates of FST, this wealth of information could allow a broad scale insight into connectivity among multiple species around Australia. We advocate public data archiving for marine genetic studies that make population datasets more visible and enable deeper connections between data, regions and study species–including analysis of connectivity [In addition to information on intraspecific genetic diversity, population genetic data on connectivity is often included in population genetic studies, in the form of summary statistics such as Fectivity . We encoInformation on average regional genetic diversity could be incorporated into the decision framework for the designation of marine park areas, with the potential for increased protection afforded to areas of consistently high diversity. For example, the area around Joseph Bonaparte Gulf, was identified as possessing high genetic variation, yet this region is under-represented in the existing Commonwealth reserve system .Genetic marker systems that assay a larger proportion of the genome are becoming increasingly cost-effective for non-model organisms. Increased use of such datasets, particularly if there was also geographic consistency in sampling locations across species, may provide a more direct avenue towards describing broad scale patterns of population genetic diversity and connectivity in the future by using estimates that are more directly comparable and accurate, and include both functional and neutral estimates of population genetic diversity e.g. .S1 Appendix(DOCX)Click here for additional data file.S2 Appendix(ZIP)Click here for additional data file.S3 AppendixSee associated readme.txt for a full explanation of column headings.(ZIP)Click here for additional data file.S1 Fig(EPS)Click here for additional data file.S2 Fig(TIFF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


Liocarcinus depurator we assessed the contribution of historical and contemporary processes on population connectivity patterns across three main oceanographic discontinuities along the Atlantic-Mediterranean transition: Gibraltar Strait, Almeria-Oran Front and Ibiza Channel. A partial fragment of the cytochrome oxidase I gene was sequenced in 366 individuals collected from localities at both sides of each discontinuity during three time periods. Although localities showed genetic fluctuations through time, a significant gradient was detected along the coast for all sampling periods. Significant inter-annual differences identified within the Alicante area, north of the Almeria-Oran Front, were associated with shifts in the relative contribution of Atlantic and Mediterranean water masses. The persistence of a clinal pattern in the Atlantic-Mediterranean transition area together with local fluctuations suggests a complex balance of dispersal and selection.Spatial genetic studies often require sampling broadly separated areas, difficult to access simultaneously. Although comparing localities surveyed at different time periods might result in spurious genetic differentiation, there is a general believe on the stability of genetic structure through time, particularly if sampled localities are isolated or very distant. By analysing spatial and temporal genetic differentiation of the portunid crab  Spatial genetic studies have increased in the last decades in many taxa while temporal genetic studies, despite being essential to understand biodiversity distribution, are still scarce. Landscape genetics and phylogeography are both concerned with understanding the distribution of genetic variation across natural environments1358The large population sizes of marine organisms generally result in little genetic differentiation despite restricted gene flow, and molecular markers show practical limitations in making inferences for recent timescales and single time point samples111314Three oceanographic discontinuities along the Atlantic-Mediterranean transition in the south and eastern Iberian Peninsula  have been shown to restrict gene flow in several marine species. The connection of the Mediterranean Sea and the Atlantic Ocean through the Gibraltar Strait is characterized by the inflow of surface Atlantic water and outflow of deeper Mediterranean water1791419121423182512Liocarcinus depurator showed that the Almeria-Oran front did not represent a significant barrier to gene flow, whereas Ibiza Channel acted as the main genetic barrierL. depurator across the three main oceanographic discontinuities along the Atlantic-Mediterranean transition. A partial region of the mitochondrial DNA cytochrome oxidase subunit I (COI) was analysed in 366 individuals from five areas situated at both sides of each discontinuity  and sampled during three time periods , and another including haplotypes mostly found in the Mediterranean (Ldep02 and related haplotypes) and were thus referred as the Atlantic (ATL) and the Mediterranean (MED) haplogroups, respectively  the present study evidences that contemporary processes impact local genetic diversity and modify connectivity between populations. Temporal variability of oceanographic discontinuities should not be overlooked when defining connectivity patterns because this could mislead conservation decisions (e.g. when designing networks of marine protected areas)28Liocarcinus depurator populations under strong influence from Atlantic waters and decaying diversity going into the Mediterranean, suggests an Atlantic origin of the species. Many phylogeographic studies identify genetically differentiated units that can be attributed to vicariance or selection reducing gene flowCOI haplotypes for L. depurator can be related to an abrupt decline of sea temperature in north Atlantic waters around 38–40 kya14L. depurator probably diverged due to vicariance events and posterior range expansions, as observed in other species influenced by climatic fluctuations during the Quaternary3435Changes in environmental conditions  and historical shifts of species distributions can shape genetic variation, as shown by spatially-explicit demographic modelling of genetic differentiationLiocarcinus depurator epipelagic larvae could drive genetic connectivity of this species by moving along with surface currents4et al.The greater diversity observed in samples under stronger Atlantic influence  using microsatellite loci suggesting genetic exchange from the west side of the Almeria-Oran front towards the east and northet al.The largest fluctuations in haplotype frequency across time were found in ALAC located between two main oceanographic discontinuities, the Almeria-Oran front in the south and the Ibiza Channel in the north. The ALAC07 sample showed a relatively high frequency of individuals from the Atlantic (ATL) haplogroup, whereas ALAC09 and ALAC13 were clearly dominated by haplotypes from the Mediterranean (MED) haplogroup. A strong genetic break between Almeria-Oran front and Ibiza Channel and higher proportion of Atlantic genotypes was also observed in the comber  pointed to the effect of variable reproductive success, and highlighted the unpredictable nature of connectivity in coral reef fishes43Clupea arenguset al.et al.Liocarcinus depurator as well as in other species with high dispersal capabilities  gene fragment was amplified using the universal primers LCO1490 and HCO2198et al.2 (25 mM), 0.5 μl dNTP’s (1 mM) and 0.4 μl (10 μM) of each primer. PCR products of 2013 samples were cleaned with ExoSAP (1.2 U Exonuclease and 1.2 U Shrimp Phosphatase per μl) at a proportion of 1:2 (ExoSAP:PCR product) and sequenced at the Scientific and Technical Services of the University of Barcelona (Spain) or at Macrogen Inc. .Muscle tissue from each individual was preserved in pure ethanol on board of the vessel. Total DNA extraction was performed for 2009 and 2010 samples using Chelex 10% as in Estoup ST values and their significance assessed performing 1000 permutations with Arlequin v. 3.5P-values were corrected for multiple comparisons using the false discovery rate (FDR) as in NarumST pairwise distances with GenAlEx v6.5et al.Sequences were visually inspected, aligned and trimmed, to obtain a final alignment of 527 bp, with BioEdit v7.2.5Liocarcinus depurator haplotypes were estimated by Bayesian Inference (BI) using MrBayes v 3.2L. depurator COI sequences was reconstructed using the median joining methodThe phylogenetic relationships between http://www.socib.eu/) and buoys located within the different sampling areas  salinity data as a proxy for identifying Atlantic and Mediterranean water masses .