The present paper integrates phylogenetic and population genetics analyses based on mitochondrial and nuclear molecular markers in silversides, genus Odontesthes, from a non-sampled area in the SW Atlantic Ocean to address species discrimination and to define Managements Units for sustainable conservation. All phylogenetic analyses based on the COI mitochondrial gene were consistent to support the monophyly of the genus Odontesthes and to include O. argentinensis, O. perugiae-humensis and some O. bonariensis haplotypes in a basal polytomy conforming a major derivative clade. Microsatellites data revealed somewhat higher genetic variability values in the O. argentinensis-perugia populations than in O. bonariensis and O. perugia-humensis taxa. Contrasting population genetics structuring emerged from mitochondrial and microsatellites analyses in these taxa. Whereas mitochondrial data supported two major groups (O. argentinensis-perugia-humensis vs. O. bonariensis-perugiae-humensis populations), microsatellite data detected three major genetic entities represented by O. bonariensis, O. perugiae-humensis and an admixture of populations belonging to O. argentinensis-perugiae respectively. Therefore, the star COI polytomy in the tree topology involving these taxa could be interpreted by several hypothetic scenarios such as the existence of shared ancestral polymorphisms, incomplete lineage sorting in a radiating speciation process and/or reticulation events. Present findings support that promiscuous and recent contact between incipient species sharing asymmetric gene flow exchanges, blurs taxa boundaries yielding complicated taxonomy and Management Units delimitation in silverside genus Odontesthes from SW Atlantic Ocean basins.
Citation: García G, Ríos N, Gutiérrez V, Varela JG, Bouza Fernández C, et al. (2014) Promiscuous Speciation with Gene Flow in Silverside Fish Genus Odontesthes (Atheriniformes, Atherinopsidae) from South Western Atlantic Ocean Basins. PLoS ONE 9(8): e104659. doi:10.1371/journal.pone.0104659
Editor: Valerio Ketmaier, Institute of Biochemistry and Biology, Germany
Received: May 29, 2014; Accepted: July 11, 2014; Published: August 15, 2014
Copyright: © 2014 Garcia et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files.
Funding: This research received financial support from the project Fondo María Viñas_2009_1_2793 (FMV_2009_1_2793_Project) granted by the Agencia Nacional de Investigación e Inovación (ANII) of Uruguay. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
The New World presents multiple examples of atherinid species flocks or adaptive radiations arising from habitat transitions , , . Silverside fish from South America constitute a exciting model to understand the scenario of fish speciation driven by divergent natural selection , .
The silverside genus Odontesthes includes 20 nominal species  distributed in marine, estuarine and freshwater environments of tropical and temperate regions in South America . Most Odontesthes species co-occur in the same habitats and they are characterized by a great morphological homogeneity . The low morphological divergence between species and the high meristic plasticity within species together with the tendency of local populations to form micro-geographic habitat associations had led to complicated taxonomy among silverside taxa .
Among freshwater representative species, two of them O. bonariensis and O. hatcheri are endemic of rivers and lakes located east of the Andes in subtropical and temperate areas . The distribution of these species was originally allopatric: O. hatcheri occuring in the South (Patagonia), whereas O. bonariensis occupying Central and Northern Argentina, South Brazil and Paraguay. The occurrence of the spontaneous hybridization between both species in a communal laboratory tank has been reported .
On the other hand, marine silversides generally have similar life history strategies, occurring in large numbers in semi-isolated populations in estuaries and coastal lagoons , , , . Ten species of Odontesthes are endemic of a chain of small shallow lakes spread along the South Western Atlantic Ocean coastal plain , . Among them, in Patos Lagoon estuary and its adjacent marine coastal area occurs O. argentinensis and O. incisa, whereas in the freshwater habitats of Patos-Mirim lagoon system can be found O. bonariensis, O. humensis, O. retropinnis and O. aff. perugiae.
Most Odontesthes species represent economically important resources for artisanal and recreational fisheries in South America and particularly O. bonariensis shows a great potential for aquaculture development .
The identification of incipient ecological species represents an opportunity to investigate the current evolutionary process where adaptive divergence and reproductive isolation are associated . Beheregaray and Sunnucks  found that niche divergence due to estuarine colonization by marine silverside fish led to isolation by adaptation and speciation in the presence of high gene flow, one of the most convincing reports of parapatric speciation in aquatic organisms from the Southern Hemisphere. Beheregaray et al.  explored the role of adaptive diversification and recent sea-level changes as evolutionary drivers in the O. perugiae species complex which comprises several allopatric and sympatric morphotypes found in the lakes and rivers of southern Brazil, Uruguay and northern Argentina . Most morphotypes have uncertain taxonomic status and are endemic to the vast system of lakes of the Coastal Plain of Rio Grande do Sul State (CPRS), southern Brazil . Beheregaray et al.  performed a phylogeographic reconstruction of radiations in the South American coastal freshwater O. perugiae species complex, and also reported some of the most rapid speciation rates for a vertebrate group.
Gene flow among hybridizing species with incomplete reproductive barriers blurs species boundaries, while selection under heterogeneous local ecological conditions or along strong gradients may counteract this tendency . Thus, phylogeographic approach provides a valuable framework to identify signatures of divergent natural selection associated with ecological divergence and the possible occurrence of reticulation events among incomplete reproductively isolated taxa.
In this study we implement a phylogeographic analysis based on mtDNA coding sequences (cytochrome oxidase subunit I, COI) and ten microsatellite loci to access in the species boundaries and to test possible reticulation and introgression events among Odontesthes taxa from the SW Atlantic Ocean, the Río de la Plata estuary and in the Uruguay River basins. At the same time this information will contribute for a long-term success of Management Units for sustainable conservation of these taxa in fisheries and aquaculture.
Materials and Methods
Sample collection and DNA extraction
All sampling protocols for this scientific study were approved by CNEA (Comisión Nacional de Experimentación Animal) from Uruguay.
A total of 163 individuals of Odontesthes from 20 sampling sites through three major regions, the Río de la Plata (RP) estuary (N = 45), Lower Uruguay and Negro river (UNR) basins (N = 23) and Atlantic coast (AC) sites of SWA Ocean (N = 95) were included in the present study. All these samples were primarily ascribed to O. bonariensis (Ob), O. perugiae species complex (Op), O. humensis (Oh), O. argentinensis (Oa) and only two specimens from O. incisa (Oi) according to Dyer  morphological diagnosis. Tissue samples were obtained from artisanal gillnets fisheries operating in these areas during 2006–2012. The sampled areas are shown in Figure 1 and Appendix S1. Sample codes are as follows: collecting site name and the corresponding environments in lowercase (i.e.: S = stream, P = port, B = beach, L = lagoon or lake, D = dam, T = town). Tissues of the voucher specimens were deposited in the collection of the Evolutionary Genetics Section in the Faculty of Sciences, University of the Republic, Montevideo, Uruguay.
Figure 1. Distribution map of 20 sampling sites through three major areas, lower Uruguay and Negro river (UNR) basins, the Río de la Plata (RP) estuary, and associated coastal lagoons and sites from SWAtlantic Ocean (AC) in Odontesthes as follows: UNR- Las Cañas beach (CAB), Yaguarete stream (YAS), Pavón stream (PVS), Baygorria dam (BAD), Rincón del Bonete dam (RBD), Ansina town (ANT); RP- Buceo Port (BP), Hatchery and Carrasco lake (CAL), Pando stream (PAS), Pinar beach (PNB), Solis Chico stream (SCS); Solis Grande stream (SGS); Piriapolis beach (PRB), Sauce Lagoon (SL), Chascomus Lagoon (CHL), Argentina; AC-, Garzón Lagoon (GL), Rocha Lagoon (RL), Castillos Lagoon (CL), Valizas stream (VAS), National Institute for Fisheries Research and Development (INIDEP), Argentina.doi:10.1371/journal.pone.0104659.g001
Genomic DNA of sacrificed specimens was isolated from muscle tissue (fixed in ethanol 95%) using sodium chloride protein precipitation, followed by ethanol precipitation modified from Medrano et al. .
PCR amplifications and sequencing of the mitochondrial COI gene
A fragment of 650 bp from the COI gene was amplified using FishF2 and FishR1 primers . Reaction volume was 10 µL containing 10X supplied buffer, 0.25 mM MgCl2, 0.2 mM of each dNTP (10 mM), 0.25 µM of each primer (10 µM), 0.1 units of Taq DNA polymerase (Invitrogen) and approximately 100 ng/ul of template DNA. Cycling conditions consisted of one initial denaturation at 94°C for 5 min followed by 35 cycles of 94°C for 30 s, 52°C for 30 s, 72°C for 1 min and a final extension of 72°C for 10 min.
Amplified COI products were sequenced directly on both strands in a Perkin-Elmer ABI Prism 377 Automated Sequencer (MACROGEN, Seoul, Korea). Sequence alignments were performed using Clustal X 1.8 .
Statistical analyses of sequences from COI data set
Corrected estimates of pairwise sequence divergence were obtained using Kimura's  two-parameter algorithm (K2P) implemented in MEGA 5.0 . Within a population, DNA polymorphism was measured by calculating the proportion of segregating sites (S), the haplotype diversity (h) , and the nucleotide diversity (π)  with ARLEQUIN v3.11  and DnaSP version 4.50  programs. Tajima's  and Fu's  tests implemented in DnaSP 4.50  were performed to check the mutation/drift equilibrium and any departure from neutrality. Significance of Fu's Fs  and Tajima's D  values was evaluated using the coalescent algorithm comparing the observed value with a null distribution generated by 10,000 replicates, and giving an empirical population sample size and the observed number of segregating sites.
Phylogenetic analysis and divergence time estimates of the mitochondrial gene
The phylogeographic relationships among mitochondrial COI haplotypes in Odontesthes populations from the sampled area were assessed by using two different methodologies. A non-model based method (MP, maximum-parsimony) was implemented in PAUP* 4.0b10  following an equally weighted MP analysis using heuristic search (MULPARS option, stepwise addition, tree-bisection-reconnection [TBR] branch swapping, 100 replicates). A strict consensus between rival trees was computed to reconcile equally parsimonious topologies. The degree of confidence assigned to nodes in the trees was assessed by bootstrapping with 500 replicates.
In ML and BI analyses, the best-fitted nucleotide substitution model for each data set was determined in Modeltest v.3.7  based on the Akaike information criterion , which simultaneously compares multiple nested or non-nested models. In the COI data set among the 56 models of nucleotide substitution, the best fit was the HKY+Γ model  with gamma distribution (Γ). The gamma distribution shape parameter value was 0.18. The likelihood scores estimated for these models were used as the prior settings for the ML analysis in the data set (−lnL = −1602.50). Heuristic search (again with 100 replicates of stepwise addition and TBR branch swapping) in ML analyses was implemented in PAUP* 4.0b10 . The robustness of the nodes was determined after 1,000 bootstrapping replicates as implemented in PhyML 3.0 (http://atgc.lirmm.fr/phyml), according to the algorithm developed by Guindon et al. . In this case, the NNI (a fast nearest neighbour edge interchange search) swapping algorithm option was implemented. Nonparametric bootstrap values above 75% were considered to be robust support for clades .
All trees were rooted by means of an outgroup criterion using sequences of O. regia, O. incisa, O. smitti, O. hatchery and O. platensis and a more distantly taxon Atherina hepsetus retrieved from the GenBank.
For the data set, divergence time of nodes and the age of the most recent common ancestor (tMRCA) were estimated with the BEAST v.1.5.4 software . This program performs Bayesian statistical inferences of parameters by using MCMC (Monte Carlo Markov chain) as a framework. Input files were generated with Beauti v.1.5.4  assuming uncorrelated lognormal trees and a Yule speciation process as prior information. The nucleotide substitution model and its parameter values were selected according to the Modeltest v.3.7  results. An uncorrelated lognormal relaxed molecular clock, which allows rate variation among lineages, was implemented using an estimated rate for mitochondrial genome of 0.023 . We carried out two independent runs of 10 million generations. Trees and parameters were sampled every 1,000 iterations, with a burn in of 10%. Results of each run were visualized in the Tracer v.1.5 program  to ensure that stationarity has been achieved and that convergence has been reached. Each analysis was repeated many times to optimize the operators of parameters until no suggestion message appeared in the log file. The timing of clade divergence and the tMRCA were estimated in million years ago (Mya) with a mean and a 95% HPD (lower and upper). Posterior probabilities and the maximum credibility tree were calculated using the TreeAnnotator v.1.5.4 software .
AMOVA, isolation by distance and historical demography
To determine the genetic structure of Odontesthes samples the variance components among hierarchical partitions in the dataset were assessed by Analysis of Molecular Variance (AMOVA) . The Euclidean metric of Excoffier et al.  was used to construct the pairwise distances matrix. The genetic variation was partitioned into three components, i.e., among groups (ФCT), among populations within groups (ФSC), and among individuals within populations (ФST), after disregarding either their original populations or their groups. For both molecular markers, populations were ascribed to three major sampling areas such as Atlantic coast (AC), Rio de la Plata (RP) and Uruguay and Negro river basins (UNR), and different grouping hypotheses for the populations were tested. The significance of the observed Ф-statistics was tested using the null distribution generated from 3,000 non-parametric random permutations of the data matrix variables and P-values were adjusted with sequential Bonferroni corrections for multiple comparisons .
Relationships and geographical distribution of the haplotypes were analysed in the haplotype network constructed with NETWORK v. 188.8.131.52 (http://www.fluxus-engineering.com/sharenet.htm), which implements the median-joining method, in the absence of recombination . The network was optimized using maximum parsimony criterion.
Population subdivision and the level of genetic isolation among sampling sites were measured assuming an infinite sites model . Pairwise estimates Ф-statistics were calculated in ARLEQUIN v3.11 .
To determine to what extent the geographic distance could explain the genetic differentiation among locations, a test for isolation by distance was performed using the Mantel test . In this case, this test determines if there is a significant correlation between the geographic distance matrix (represented by the minimum coastline or river contour distance in kilometers) and the pairwise Fst matrix between collecting sites. The significance of the Z value (Mantel coefficient) was calculated using random permutation procedures implemented in the Mantel Non-parametric Test Calculator 2.0 . Statistical significance was accessed through 1,000 permutations.
To assess to the historical demography of Odontesthes we compared the observed frequency distribution of pairwise nucleotide differences among haplotypes (i.e., mismatch distribution) in relation to the expected under a sudden population expansion model  implemented in ARLEQUIN v3.11  and DnaSP version 4.50  programs. The significance of the assumed model was tested using the sum of squares deviations (SSD) between the observed and expected data by means a parametric bootstrapping approach (1,000 permutations) and considering the Harpending's raggedness index . The mismatch distribution will be multimodal in stable populations and unimodal in expanding ones. The time of a possible population expansion (τ) can be calculated as τ = 2ut , where τ is the mode of the mismatch distribution and u is the mutation rate of the sequence (such that u = µmT, where µ is the mutation rate/site/generation and mT is the number of nucleotide base pairs). If the sudden expansion model was not rejected, then τ was converted to time since expansion (t) in years before present as follows: [YBP (t = τ/2u)]. For Odontesthes silversides, the mtDNA substitution rate was estimated in 0.023 . Because time (t) is measured in generations and the age at sexual maturity for Odontesthes was calculated as minimum population doubling time 1.4–4.4 years (http://www.fishbase.org), to convert to time since expansion in years, we have multiply by the generation time of a mean 2.9 years.
Analysis of microsatellite markers
A total of 120 individuals from 13 populations were analyzed using these nuclear markers (Appendix S1). Ten polymorphic microsatellite loci developed for Odontesthes were amplified: Odon02, Odon09, Odon27, Odon38, Odon39 ; and Obo01, Obo26; Obo46; Obo54 and Obo77 . The forward primer of each pair was fluorescently labeled as follows: Odon02, Odon25, Odon39, Obo01, Obo54 with 5′-FAM; Odon27, Odon38, Obo26 and Obo77 with 5′-HEX; and finally Odon09 with 5′-NED.
PCR amplifications were carried out in a reaction volume of 10 µl (final concentrations in parenthesis) each containing DNA extract (400 ng/ul); dNTPs (0.1 mM each); primers (10 µM each); MgCl2 Invitrogen (0.8–2.5 mM); Taq DNA Polymerase Invitrogen (0.04 U/µl); and Invitrogen buffer (1X). Amplification conditions were those proposed by  and  respectively. The PCR reactions were carried out in a Verity 96-Well Thermal Cycler (Applied Biosystems) and the PCR products separated on an ABI 377 automated sequencer. The amplified fragments were genotyped using an ABI 3730 DNA Sequencer (Applied Biosystems) and visualization of the results was performed using the program GeneMapper 3.7 software (Applied Biosystems). Alleles were scored using a GeneScan 500 LIZ Size Standard and Genotyper software (Applied Biosystems, Inc.).
Statistical and population structure analyses based on nuclear markers
Among all populations, only 13 were analyzed with microsatellites. To implement the analysis of the Odontesthes data set, based on biogeographic criteria and to avoid statistical bias due to the low number of samples in some collecting sites, the populations were first ascribed to different taxa as follows: Oa including population from GL collecting site; Ob belonging to populations from CAL, SL and CL; Oph populations from CAB, BAD, RBD; finally Oap embracing populations from BP, PNB, PAS, SCS, SGS, PRB and RL. The number of alleles, the allelic richness, the expected heterozygosity corrected for sampling bias, the observed heterozygosity, the polymorphic information content and the estimated null allele frequency were calculated for each locus in the whole population per taxon using CERVUS version 3.0.3 . GENEPOP 4.0.10  was used to perform the exact test for Hardy-Weinberg (HW) equilibrium by microsatellite loci (test multi-population) and by population (test multi-locus) using the Markov chain method with 1,000 iterations. Linkage disequilibrium between loci and deviations from Hardy-Weinberg equilibrium for each locus were tested by a Markov chain method following the algorithm of Guo and Thompson  and using the Bonferroni  correction for multiple comparisons (α = 0.05). All the analyses outlined above were implemented in GENEPOP 4.0.10 . Wright's F-statistics (Fis, Fst, and Fit ) over populations and loci were calculated by FSTAT version 184.108.40.206 . To detect the presence of scoring errors or the possible presence of null alleles, we analyzed the genotypic matrices obtained with the Micro-Checker software .
An analysis of population subdivision and clustering of individual genotypes was implemented with STRUCTURE v. 2.2  by a MCMC method. We considered 1 to 13 different populations (K = 1 to K = 13). Ten independent runs employing an admixture model were implemented with a burn-in period length of 50,000 iterations, followed by 100,000 MCMC replicates. The average of these independent runs was calculated and the true value of “K” was accessed following the approach detailed in the manual of STRUCTUREv. 2.2 (http://pritch.bsd.uchicago.edu/structure.html).
Different groups of hypotheses and populations as sources of variation were assessed in the AMOVA considering all ten loci using ARLEQUIN 3.1 software package . Furthermore, FST values for pairwise comparisons of the 13 Odontesthes populations and their significance level for genetic differentiation (P = 0.05) and Rst were tested additionally with FSTAT .
Population divergence and migration rates from both molecular markers
To discriminate between the relative effects of divergence and gene flow on the speciation process, we analyzed our data set under the Isolation with Migration model . The “isolation with migration” model in IMa does not assume gene flow and genetic drift are in equilibrium, making it the most appropriate for recently diverged populations that share haplotypes and alleles due to both gene flow and ancestral polymorphism. The model assumes that an ancestral population splits into two descendant populations that may continue to exchange genes after separation. Following  we consider Ob as a freshwater sister taxon of Oa and Oph, sharing a common freshwater ancestor with these taxa.
The method estimates posterior probability distributions for both ancestral and actual population sizes, directional migration rates between the two populations, and the time elapsed since population splitting. An MCMC approach is used to draw a sample from the posterior distribution of genealogies and to estimate three types of population parameters: population size (θ = 4Nu), splitting time (t = Tu, where T is the time in generations since the common ancestry, and it is of the same order of 4N) and migration rates (2NM = 4Nu×m/2). The priors were finally set as follows: the upper bound of population sizes q = 10, splitting times t = 4 and migration rates m = 2, respectively. We run the MCMC simulations with 100,000 burn-in steps and 10,000.000 sampled genealogies. The posterior distributions of migration rates and population sizes are derived analytically from the sampled genealogies.
Genetic variation in the mitochondrial COI gene in Odontesthes species from SWA Ocean basins
This study includes a data set of 655 bp of mitochondrial COI gene from 156 individuals belonging to populations of O. argentinensis, O. perugia, O. humensis and O. bonariensis (GenBank accession numbers: KJ854753–KJ854894, see Appendix S1). Moreover, other sequences from Odontesthes species and one more distantly related genera (Atherina hepsetus) were retrieved from the GenBank and included for both the pairwise distance comparisons and the phylogenetic analyses.
Among 36 COI haplotypes initially assigned to O. argentinensis, 30% of them were shared with O. perugiae and 25% with O. humensis respectivelly. Among 7 COI haplotypes initially grouping O. bonariensis sequences, 58% of them were shared with O. perugiae and 8% with O. humensis. Therefore we partitioned the statistical analysis in two different data sets: O. argentinensis-perugiae-humensis (Oaph) and O. bonariensis-perugiae-humensis (Obph).
The Oaph populations showed higher haplotype diversity (h) and nucleotide diversity (π) than Obph (Table 1). Thirty six haplotypes were found in Oaph populations whereas only seven in Obph taxa. Except for the three most common haplotypes (H_1 and H_2 in Obph and H_6 in Oaph), most haplotypes represented rare variants that explained the observed haplotype diversity in each taxa (Appendix S1). A significant excess of low-frequency haplotypes and thereby negative and significant values of both Tajima's and Fu's neutrality tests were observed in Oaph indicating a departure from neutrality, whereas Obph presented only negative and significant values in Tajima's D test (Table 1). These values would be consistent with populations that experienced demographic expansion scenarios or alternatively selective sweeps.
Table 1. Estimates of DNA polymorphism in COI gene of Odontesthes populations from SW Atlantic Coast, Río de la Plata estuary and Uruguay-Negro River basins.doi:10.1371/journal.pone.0104659.t001
In Oaph populations the average of the corrected pairwise K2P sequence divergence between COI haplotypes was higher than in Obph (Table 1). The average pairwise distances between haplotypes of O. argentinensis-perugiae-bonariensis-humensis taxa and other Odontesthes species included in present study (O. regia, O. platensis, O. smitti and O. hatchery) was 0.047±0.011 (mean ± SE), whereas the divergence between the former and O. incisa was 0.075±0.018. The average divergence between the ingroup and the outgroup A. hepsetus was 0.611±0.153.
Present phylogenetic analyses included 43 haplotypes from Oaph and Obph populations. All performed phylogenetic analyses (ML and beast) conducted using the HKY+Г model of sequence evolution, clearly identified a major monophyletic and recently derivate clade with a high posterior probability of occurrence, including minor monophyletic clades which collapsed in a basal polytomy joining most of the 41 haplotypes of Oaph and a well supported clade of Obph (Fig. 2). Other minor clade integrated by two O. bonariensis haplotypes collapsed basal to the major clade. Other species from the genus Odontesthes (O. regia, O. smitti, O. hatchery and O. platensis) were reciprocally monophyletic in relation to the minor clade of O. bonariensis and the major derivate clade, whereas O. incisa was the most basal taxon of the genus Odontesthes. Simultaneously we used a reference calibration time for nodes by assuming a substitution rate of conventional rate for mitochondrial genome of 0.023 mutations/site/per million years  to capture a plausible time interval (lower and upper estimate) for clade divergence. All Odontesthes clades showed a high probability to have diverged between 0.1 and 2.5 Mya (Quaternary). The divergence between the genus Atherina and Odontesthes occurred in the Miocene.
Figure 2. Tree topology generated using the HKY+Γ model of molecular evolution based on 43 COI gene haplotypes (H) of Odontesthes from lower Uruguay and Negro river basins, the Río de la Plata estuary, SWA Ocean basins.
Bayesian phylogeographic inference framework implemented in beast 1.5.4 and the estimated divergence dates. Numbers above branches refer to the Bayesian posterior probability of occurrence for clades while bootstrap support values from ML bootstrap are shown below branches. The bottom bar summarizes the time-scale divergence dates in Mya.doi:10.1371/journal.pone.0104659.g002
Population genetic structure, isolation by distance and historical demography
Table 2 shows the pairwise FST values of the COI data set among the 15 collecting sites analyzed with this marker. Low population genetic structure was detected among localities ascribed to Oap from RP estuary and AC areas respectively. Nevertheless, these localities appeared divergent to those ascribed to Obph from some RP estuary sites, and UNR basins. Remarkably the CAL collecting site seems to be the most divergent from all the remaining ones. The most plausible population structuring based on COI data set among tested hypotheses in the AMOVA was addressed following two different grouping criteria: (a) assigning all populations to two-group of samples; (b) forming three groups of populations (Table 3). The two-group hypothesis (a) pointed out that most genetic variation was distributed among groups (ΦCT), suggesting a remarkably higher level of genetic structure when samples from marine and estuarine morphs ascribed to Oaph populations was considered as a separate group from the other including freshwater samples from Obph taxa.
Table 2. Pairwise FST values based on COI data set of Odontesthes populations from SW Atlantic Coast, Río de la Plata estuary and Uruguay-Negro River basins.doi:10.1371/journal.pone.0104659.t002
Table 3. Analysis of molecular variance (AMOVA) based on COI gene of Odontesthes populations from SW Atlantic Coast, Río de la Plata estuary and Uruguay-Negro River basins.doi:10.1371/journal.pone.0104659.t003
The haplotype network based on COI gene (Fig. 3) showed a strikingly star-shaped topology including the two most frequent haplotypes with a high proportion of singletons, typical of populations that have suffered a recent demographic expansion. One of the most frequent and central haplotypes (H_6) including samples of Oaph is present in 11 sampling sites and is shortly interconnected by one to three step-mutations to most haplotypes of the network, belonging to Oaph populations. A single step mutation separated H_6 from the other most frequent haplotype (H_2), which included samples belonging to Obph taxa from 6 sampling sites. Remarkably, the network topology showed some loops involving the central H_6 and H_2 haplotypes and their respective derivate ones. Therefore these alternative links may be representing equally good connections due to homoplasy or perhaps the existence of peripheral reticulation events among them.
Figure 3. Haplotype network (constructed with NETWORK v. 220.127.116.11 software) of Oaph and Obph taxa.
Black dots represent missing haplotypes and circle size is proportional to haplotype frequency. Different colours in each circle indicate the collecting sites as described in the Figure 1.doi:10.1371/journal.pone.0104659.g003
Taking into account all collecting sites, negative values in Mantel test were observed (r = −0.126, p = 0.050), showing a negative correlation between genetic and geographic distances and excluding the isolation by distance model of population differentiation in Odontesthes.
Figure 4 shows an unimodal mismatch distribution pattern in the COI data set which adjusted to the distribution predicted by the growth–decline population model  in the Oaph populations. The sum of squares deviations was SSD = 0.148 (P>0.06) and Harpending's Raggedness index was 0.486. The estimate parameter under the model was τ = 3.218. The time of expansion-decline in Oaph based on a substitution for this marker was estimated to have started around 227,000 YBP. In the Obph populations data set the sum of squares deviation value was SSD = 0.180 (P>0.05) and Harpending's Raggedness index was 0.492, therefore population growth-decline hypothesis was accepted for this taxon. The estimate parameter under the model was τ = 7.843 and the time of expansion-decline in Obph populations were estimated to have started around 497,000 YBP.
Figure 4. Mismatch distribution in Odontesthes species under the growth–decline population model using mtDNA COI data set.
(a). Oaph and (b). Obph populations.doi:10.1371/journal.pone.0104659.g004
Genetic variability in multi-locus nuclear data
The measures of microsatellite genetic variation including total number of alleles, allelic richness, heterozygosity and HWE deviation for each locus and the corresponding average across all loci per taxon are showed in Table 4. Significant departures from Hardy-Weinberg equilibrium were found at some loci of the following populations: Oap (Odon27 and Obo54); Oph (Obo26, Odon27, Odon39 and Odon02); Ob (Obo39, Obo54 and Odon02). This could be due to a Wahlund effect, with a reduction of heterozygosity caused by any subpopulation structure. The null hypothesis of equilibrium was accepted across all loci in Oa population and when a global test across loci and populations was performed (p<0.05, Table 4). Based on Fis estimates there was also no support for inbreeding at any locality, except from Ob populations (average across all loci 0.177).
Table 4. Estimates of DNA polymorphism based on ten microsatellite loci in Odontesthes populations from SW Atlantic Coast, Río de la Plata estuary and Uruguay-Negro River basins.doi:10.1371/journal.pone.0104659.t004
Micro-Checker analysis suggested heterozygote deficit at some loci, but not in all populations (p<0.05) and that the deficit of heterozygotes in these loci, were not due to stuttering or large allele dropout but it might be the result of null alleles, such as in the cases of Obo01 and Obo 54 in the Oap populations. The number of alleles per locus varied from 11 (Odon27) to 71 (Obo01) in the total sample. Average number of alleles ranged from 25 (Oap) to 5.8 (Oa) (Table 4). Allelic number was significantly lower in the locus Odon27 than the remaining in all populations. Allelic richness was significantly lower in the locus Odon27 for Ob populations than the remaining ones. The highest number of private alleles was detected in the Oap population using FSTAT package.
Exact test of genotypic linkage disequilibrium were not significant (p<0.05) after Bonferroni correction in the global approach, except for two pairs of loci (Odont 39-Odont27 and Obo01-Obo54).
Population genetics structure based on microsatellites
Pairwise Fst values among 13 populations showed little differentiation for Oap taxa, as well as among those belonging to Oph, whereas the populations from O. bonariensis presented little to moderate genetic differentiation (Table 5). Moderate differentiation was evident between Oap and Oph populations whereas large differentiation (FST>0.15) was evident between Oph and Ob taxa pairwise comparisons.
Table 5. Pairwise FST values based on ten microsatellite loci of Odontesthes populations from SW Atlantic Coast, Río de la Plata estuary and Uruguay-Negro River basins.doi:10.1371/journal.pone.0104659.t005
Among all grouping hypotheses tested, AMOVA results showed that three groups rendered the most plausible hypothesis with the largest percentage of variance within individuals, followed by among groups, whereas remaining components of variance value were very low (Table 6).
Table 6. Analysis of molecular variance (AMOVA) based on ten microsatellite loci in Odontesthes populations from Atlantic Coast, Río de la Plata estuary and Uruguay-Negro River basins.doi:10.1371/journal.pone.0104659.t006
Both STRUCTURE (Fig. 5) and Neighbour-Joining (Fig. 6) analyses detected similar population genetic structure with the microsatellite data set. Using STRUCTURE, the posterior probability for K = 2 or K = 3 was very similar, but we assume the three cluster assignments Ln Pr (X|K = 3) = −5102, 89 as the most plausible one for our data set, whereas the probabilities for the other K values assayed were negligible (Fig. 5). Considering three clusters (K = 3) the individuals from SL, CL and CAL ascribed to Ob were assigned mainly to one genetically homogeneous cluster, whereas those from eight localities ascribed to Oap populations were mostly assigned separately, and finally three other localities (CAB, RBD and BAD) were clustered as a separated and genetically homogeneous group belonging to Oph taxa (Figure 5).
Figure 5. Estimated population structure based on the STRUCTURE analysis (K = 3) of the 10 nuclear microsatellite loci.
Each bin or three colored vertical bar represents the estimated membership fraction of an individual into three major population clusters. Name of 13 collecting sites are above bars.doi:10.1371/journal.pone.0104659.g005
Figure 6. NJ tree based on a matrix of Nei's DA genetic distance based on ten microsatellites data between O. argentinensis, O.perugiae-humensis and O.bonariensis taxa (calculated the Populations, 1.2.30, Langella 1999).
Clusters indicate the distributions of individuals in relation to their corresponding taxon.doi:10.1371/journal.pone.0104659.g006
The NJ tree based on Nei's genetic distance matrix detected the same three separated clusters belonging to the same aforementioned taxa (Figure 6).
Isolation and Migration analyses
Because little to moderate genetic differentiation was detected in Oaph populations (based on both molecular markers) it was considered as single unit in the IMa2 under the two-population analyses (Fig. 7). Therefore, the performed analysis included the following two groups of populations: Oaph vs. Obph. The peaks of the six parameter estimate were confined to narrow ranges with the corresponding posterior distribution (Fig. 7). The estimate of population size for q0 (Oaph) under two markers was two-fold higher than that of the ancestral population (q2), indicating a possible population expansion events (Fig. 7a,b). Conversely, there seems not to be obvious change for the effective population size of q1 (Obph), whereas minor signals of bottleneck followed by population expansion appeared (Fig. 7a). Asymmetric migration rates were recovered from the IMa2 coalescent analysis (Fig. 7c,d) for both molecular markers. Microsatellite data (Fig. 7d) showed significant gene flow from Oaph to Obph whereas lower signal of gene flow was evident in the reverse direction. Conversely COI data (Fig. 7c) revealed higher posterior probability of retrospective gene flow from Obph to Oaph but not in the opposite direction.
Figure 7. Marginal posterior probability distribution for the Isolation-with-migration demographic parameters obtained in IMa2 for both molecular markers.
Curves are shown for estimates of effective population size in Oaph populations (q0), Obph bonariensis (q1) and ancestral population (q2) for COI data set (a) and for microsatellite data (b). Estimate migration rate in each pairwise comparison analyses of Oaph vs. Obph (m0>1) and Obph vs. Oaph (m1>0) for COI data set (c) and microsatellite data (d).doi:10.1371/journal.pone.0104659.g007
Phylogenetic analysis and Odontesthes species delimitation from SW Atlantic Ocean basins
All phylogenetic analyses based on the COI mitochondrial gene were consistent to support the monophyly of the genus Odontesthes and to include Oaph and some Obph haplotypes within a major derivate clade in an unresolved basal polytomy joining a minor clade integrated by other O. bonariensis sequences. The star polytomy included minor and poorly differentiated clades not geographically structured, with high posterior probability of occurrence and suggesting a recent radiation process. Furthermore, pairwise genetic distance values between these taxa were within the range of Odontesthes intraspecific levels. In contrast, phylogenetic analyses based on COI gene reported high posterior probability of occurrence in other cladogenetic events involving more distantly Odontesthes species. Therefore, O. smitti, O. regia and O. hatcheri integrated a monophyletic and sister group of the O. bonariensis-argentinensis-perugiae-humensis clade, whereas O. incisa split as a basal clade among the Atherinopsoidei.
Previous molecular phylogenetic analyses based on several mitochondrial genes proposed that O. bonariensis and O. argentinensis taxa comprise a common genetic lineage , . It was consistent with their shared morphological characters  and with no statistically significant morphometric differentiation between them .
Remarkably in the present work, Oph populations were included in the aforementioned star polytomy together with Oa samples and some Ob haplotypes. Beheregaray and Sunnuck , based on demographic and phylogeographic history analyses of coastal Odontesthes, had proposed that O. perugiae species complex originated from an ancestral marine-estuarine lineage currently represented by O. argentinensis. At the same time, O. argentinensis would have emerged as the most recently derived marine species of the genus, having a common freshwater ancestor species with O. bonariensis having diversified during the Pleistocene . Therefore, all these three taxa share common ancestry. Our results seem congruent with these findings, dating the aforementioned cladogenetic events about 0.1 and 2.5 Mya (since the Pleistocene-Post-Pleistocene).
Moreover, present analyses pointed out about the absence of phylogenetic signals to discriminate these four Odontesthes taxa which collapsed in the derivate basal polytomy. This could be interpreted as a hard polytomy and it would be explained by several hypothetic differentiation scenarios such as, the existence of shared ancestral polymorphisms, incomplete lineage sorting in radiating speciation process and/or reticulation events involving these taxa. Our results may be congruent with some recent events of hybridization since hybrid individuals tend to collapse in a basal polytomy when included in a cladistic analysis .
Ancestral polymorphism, lineage sorting or introgression scenarios in the Odontesthes differentiation from SWA ocean basins?
Microsatellites data set revealed relatively higher heterozigosity values in the Oaph and Oa from GL populations than in Ob taxon. These values were similar to those reported for Oa from southern Brazil , , but the heterozygosity values in the Oph species complex found by Behegaray et al.  were lower than in the present work.
Contrasting population genetics structuring emerged from mitochondrial and microsatellites analyses. AMOVA, Bayesian STRUCTURE inference and distance analyses based on microsatellite data yielded congruent assignment of each individual into three clusters (K = 3). Two of them including genetically homogeneous groups such as Ob from SL, CL and CAL, and on the other hand, samples of Oph from two RBD, BAD and CAB (Fig. 6). The nuclear homogeneity detected in Ob should be expected since following Dyer , this taxon has its origins in lakes and lagoons of the Province of Buenos Aires, Argentina, connected with the Rio de la Plata estuary, and in Rio Grande do Sul, Brazil. Nevertheless, there are no records of Ob being native to Uruguay, and multiple deliberated introduction events from Argentina lagoons to different freshwater and estuarine environments for extensive aquaculture purposes have been reported in the former country .
On the other hand, a second cluster of individuals belonging to the remaining collecting sites represent a highly heterogeneous group of mixed ancestry between the marine-estuarine taxon Oa and the freshwater Oph taxa. This group showed a gradual variation in its nuclear genomic structure from the hypothetical shared ancestors. The variation is yet evident in the same marine-estuarine environment (i.e. RL, PNB and BP) irrespective of its geographic distance and excluding the isolation by distance model of differentiation.
In contrast to microsatellite data, the AMOVA based on mitochondrial COI gene straightforward supports the existence of two groups: one including Obph populations and other integrated by Oaph samples. Consistent with genetic distances, haplotype network showed a strikingly star-shaped topology including two most frequent haplotypes shortly interconnected by branch lengths of one step mutation, one of them ascribed to Oaphs and the other one belonging to Obph taxa.
Taking into account all present data, the existence of hybridization events could have occurred among these four highly related taxa in sympatric estuarine areas. In particular introgression from Oaph taxa seems to have occurred toward O. bonariensis matrilineal genome. Contrasting IMa2 results from both molecular markers were consistent with a hypothetic hybridization and introgression scenarios between these taxa.
Previously, it has been reported  natural hybridization between both taxa (O. bonariensis vs. O. argentinensis) in the Salada Grande Lagoon from Argentina.
In the area under study, Pleistocene and Post-Pleistocene marine transgression produced habitat modifications and fragmentations in particular in coastal and shelf regions from South America . As a principal consequence of these events, several rivers and coastal lagoons system were periodically separated from the Atlantic Ocean by sand bars, generating associated estuarine environments along South America coast . Bamber and Henderson  supported that physically variable environments, such as estuaries and coastal brackish lagoons, pre-adapt silverside populations to invade, colonize and rapidly speciate into vacant freshwater niches. Incipient lakes may provide special conditions for radiations because of their remote access and low or absent competition from endemic lineages specialized in particular resources.
Nevertheless there is absence of absolute geographical and physiological barriers to gene flow that separate these Odontesthes populations in the study area. The Río de la Plata represents a continuous estuarine environment linking marine (SWA Ocean) to freshwater populations of Odontesthes inhabiting the Uruguay-Negro River basin.
Remarkably, the nuclear genomic heterogeneity detected in the Oaph group of populations would be explained by alternatively shared ancestral polymorphism, incomplete lineage sorting in radiating taxa and/or past recent process of reticulation events. In this sense, Beheregaray et al.  mentioned that O. argentinensis-perugiae populations share common mitochondrial haplotypes perhaps representing the matrilineal ancestor of them. These authors hypothesized that a fundamental issue is whether the O. perugiae morphotypes endemic to coastal lakes are the outcome of an evolutionary radiation or merely reflect phenotypic plasticity within a single species.
Historical demography and Managements Units in sustainable fisheries and conservation strategies
Mismatch distribution and neutrality tests based in the COI data set yielded to different historical demographic scenarios in which population expansion could be proposed for Oaph populations. We note that the inferred IMa2 parameter of the effective population size in Oaph is larger than the supposed common ancestor and the Obph. This scenario could be consistent with secondary contacts between incipient species showing different combinations of nearly interspecific hybridizations and recent mixing populations.
Nevertheless, historical demographic parameters in Obph suggest that these populations have undergone past recent of more or less dramatic bottlenecks and founder effect episodes of population reductions, perhaps associated to freshwater Pampean mainland lakes and lagoons environments changes since later Pleistocene.
Beheregaray and Sunnuck  proposed that ecological speciation and “divergence-with-gene-flow” adjust to Odontesthes model of speciation. Present findings pointed out that promiscuous and recent contact between incipient species sharing high level of asymmetric gene flow blurs species boundaries yielding to complicated taxonomy and species delimitation among silverside genus Odontesthes.
Based on present data we propose that Oaph populations from the SW Atlantic Ocean, RP and UNR basins could be considered a metapopulation system for fishery policies and conservation purposes.
Present nuclear and mitochondrial data alert us about the sustainability in native and captive populations of O. bonariensis, within the aquaculture programs, regarding the moderate to relatively low genetic diversity found in this taxon, despite potential past/present reticulation events among its highly related sister species.
Catalog number, collecting sites and areas, GenBank accession numbers and haplotype of Odontesthes individuals from lower Uruguay and Negro river (UNR) basins, the Río de la Plata (RP) estuary, and associated coastal lagoons and sites from SW Atlantic Ocean (AC). Samples included in the microsatellite population analyses are indicated with an X.
We thank S. Sanchez, L. Insua, V. Perez, M. López and M. Portela for technical support. We thank the research project granted by the Programa de Desarrollo Tecnológico 71_06 (PDT 71_06) of Uruguay for provide Odontesthes samples from Rocha Lagoon. We thank the following colleagues for kindly providing Odontesthes specimens: M. Loureiro F. Texeira, S. Serra, from different Negro river sites in Uruguay, A. Accuña from Solís Chico, Solís Grande and Pando streams and additionally S. Serra for O. perugia and O. humensis morphological diagnosis. The authors are also grateful to the Japanese government for the donation of equipment. The research of G.G. and V.G. was also supported by the Sistema Nacional de Investigadores (SNI).
Conceived and designed the experiments: GG CBF BGP PMP. Performed the experiments: NR VG JG. Analyzed the data: GG NR CBF. Contributed reagents/materials/analysis tools: GG CBF BGP PMP. Contributed to the writing of the manuscript: GG CBF BGP PMP.
- 1. Beheregaray L, Levy J (2000) Population genetics of the silverside Odontesthes argentinensis (Teleostei, Atherinopsidae), evidence for speciation in an estuary of southern Brazil. Copeia 2000: 441–447. doi: 10.1643/0045-8511(2000)000[0441:pgotso]2.0.co;2
- 2. Beheregaray L, Sunnucks P (2001) Fine-scale genetic structure, estuarine colonization and incipient speciation in the marine silverside Odontesthes argentinensis. Molecular Ecology 10: 2849–2866. doi: 10.1046/j.1365-294x.2001.t01-1-01406.x
- 3. Heras S, Roldán MI (2011) Phylogenetic inference in Odontesthes and Atherina (Teleostei: Atheriniformes) with insights into ecological adaptation. Comptes Rendus Biologies 334: 273–281. doi: 10.1016/j.crvi.2011.03.004
- 4. Froese R, Pauly D (2012) Species of Odontesthes in FishBase. June 2012 version.
- 5. Dyer BS (1998) Phylogenetic systematics and historical biogeography of the Neotropical silverside family Atherinopsidae (Teleostei, Atheriniformes). In: Malabarba LR, Reis RE, Vari RP, Lucena ZM, Lucena CAS, Phylogeny and Classification of Neotropical Fishes. Edipucrs, Brazil.
- 6. Bemvenuti MA (2006) Silversides in South Brazil: Morphological and ecological aspects. Biocell 30: 111–118.
- 7. Bamber RN, Henderson PA (1985) Morphological variation in British atherinids, and the status of Atherina presbyter Cuvier (Pisces: Atherinidae). Biological Journal of Linnean Society 25: 61–76. doi: 10.1111/j.1095-8312.1985.tb00386.x
- 8. Campos H (1984) Los géneros de atherinidos (Pisces: Atherinidae) del sur de Sudamerica Revista Argentina de Ciencias Naturales Bernardino Rivadavia (Buenos Aires), Serie Zoologia. 13: 71–84.
- 9. Strüssmann CA, Saito T, Usui M, Yamada H, Takashima F (1997) Thermal thresholds and critical period of thermolabile sex determination in two atherinid fishes Odontesthes bonariensis and Patagonina hatcheri. Journal of Experimental Zoology 278: 167–177. doi: 10.1002/(sici)1097-010x(19970615)278:3<167::aid-jez6>3.3.co;2-0
- 10. Potter IC, Ivantsoff W, Cameron R, Minard J (1986) Life cycles and distribution of atherinids in the marine and estuarine waters of southern Australia. Hydrobiologia 139: 23–40. doi: 10.1007/bf00770239
- 11. Bamber RN, Henderson PA (1988) Preadaptive plasticity in atherinids and the estuarine seat ofteleost evolution. Journal of Fish Biology 33: 17–23. doi: 10.1111/j.1095-8649.1988.tb05554.x
- 12. Creech S (1991) An electrophoretic investigation of populations of Atherina boyeri Risso, 1810 and Atherina presbyter Cuvier, 1829 (Teleostei: atherinidae): genetic evidence in support of the two species. Journal of Fish Biology 39: 807–816. doi: 10.1111/j.1095-8649.1991.tb04410.x
- 13. Bemvenuti MA (2002) Diferenciação morfológica das espécies de peixes-rei Odontesthes Evermann and Kendall (Osteichthyes, Atherinopsidae) no extremo sul do Brasil: morfometria multivariada. Revista Brasilera de Zoología, Curitiba 19: 239–249. doi: 10.1590/s0101-81752002000100024
- 14. Malabarba LR, Dyer B (2002) Description of three new species of the genus Odontesthes from the rio Tramandaí drainage, Brazil (Atheriniformes: Atherinopsidae). Ichthyological Exploration Freshwaters 13: 257–272.
- 15. Miranda LA, Cassará MC, Somoza GM (2005) Increase in milt production by hormonal treatment in the pejerrey fish Odontesthes bonariensis (Valenciennes 1835). Aquaculture Research 36: 1473–1479. doi: 10.1111/j.1365-2109.2005.01357.x
- 16. Beheregaray L, Sunnucks P, Briscoe D (2002) A rapid fish radiation associated with the last sea level changes in southern Brazil, the silverside Odontesthes perugiae complex. Proceedings of the Royal Society of London. Series B 269: 65–73. doi: 10.1098/rspb.2001.1838
- 17. Bemvenuti MA (1997) Relações morfológicas e osteológicas entre Odontesthes perugiae e O. mirinensis (Pisces: Atherinidae, Atherinopsinae). Atlântica, Rio Grande 19: 113–131.
- 18. Zardi GI, Nicastro KR, Canovas F, Ferreira Costa J, et al. (2011) Adaptive Traits Are Maintained on Steep Selective Gradients despite Gene Flow and Hybridization in the Intertidal Zone. PLoS ONE 6: e19402 doi:10.1371/journal.pone.0019402.
- 19. Dyer BS (2006) Systematic revision of the South American silversides (Teleostei, Atheriniformes). Biocell 30: 69–88.
- 20. Medrano JF, Aasen E, Sharrow L (1990) DNA extraction from nucleated red blood cells. Biotechniques 8: 43.
- 21. Ward RD, Zemlak TS, Innes BH, Last PR, Hebert PDN (2005) DNA barcoding Australia's fish species. Philosophical Transactions of the Royal Society B 360: 1847–1857. doi: 10.1098/rstb.2005.1716
- 22. Thompson JD, Gibson TJ, Plewniak FM, Jeanmougin F, Higgins DG (1997) The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Research 25: 4876. doi: 10.1093/nar/25.24.4876
- 23. Kimura M (1980) A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. Journal of Molecular Evolution 16: 111–120. doi: 10.1007/bf01731581
- 24. Tamura K, Peterson D, Peterson N, Stecher G, Nei M, et al. (2011) MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and MaximumParsimony Methods. Molecular Biology and Evolution 28: 2731–2739. doi: 10.1093/molbev/msr121
- 25. Nei M (1987) Molecular evolutionary genetics. Columbia University Press, New York.
- 26. Excoffier L, Laval G, Schneider S (2005) Arlequin version 3.0: an integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online 1: 47–50.
- 27. Rozas J, Sánchez-Del Barrio JC, Messeguer X, Rozas R (2003) DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics 19: 2496–2497. doi: 10.1093/bioinformatics/btg359
- 28. Tajima F (1989) Statiscal method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123: 585–595.
- 29. Fu YX (1997) Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics 147: 915–925.
- 30. Swofford DL (2002) PAUP*. Phylogenetic Analysis Using Parsimony (*and Other Methods) ver. 4.0b5. Sinauer Associates: MA.
- 31. Drummond AJ, Rambaut A (2007) BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology 7: 214. doi: 10.1186/1471-2148-7-214
- 32. Posada D, Crandall KA (1998) MODELTEST: testing the model of DNA substitution. Bioinformatics 14: 817–818. doi: 10.1093/bioinformatics/14.9.817
- 33. Akaike H (1974) A new look at the statistical model identification. IEEE Transactions on Automatic Control AC-19: 716–723. doi: 10.1109/tac.1974.1100705
- 34. Hasegawa M, Kishino K, Yano T (1985) Dating the human-ape splitting by a molecular clock of mitochondrial DNA. Journal of Molecular Evolution 22: 160–174. doi: 10.1007/bf02101694
- 35. Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, et al. (2010) New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Systematic Biology 59: 307–321. doi: 10.1093/sysbio/syq010
- 36. Hillis DM, Bull JJ (1993) An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analysis. Systematic Biology 42: 182–192. doi: 10.2307/2992540
- 37. Rambaut A, Drummond AJ (2009) Tracer v.1.5. http://beast.bio.ed.ac.uk/Tracer.
- 38. Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131: 479–491.
- 39. Rice WR (1989) Analyzing tables of statistical tests. Evolution 43: 223–225. doi: 10.2307/2409177
- 40. Bandelt HJ, Forster P, Rohl A (1999) Median-joining networks for inferring intraspecific phylogenies. Molecular Biology and Evolution 16: 37–48. doi: 10.1093/oxfordjournals.molbev.a026036
- 41. Kimura M, Crow JF (1964) The number of alleles that can be maintained in a finite population. Genetics 49: 725–738.
- 42. Mantel N (1967) The detection of disease clustering and generalized regression approach. Cancer Research 27: 209–220.
- 43. Liedloff A (1999) Mantel Nonparametric Test Calculator for Windows. Version 2.00. Distributed by the author, School of Natural Resource Sciences, Queensland University of Technology GPO Box 2434, Brisbane, 4001, Australia.
- 44. Rogers AR, Harpending H (1992) Population growth makes waves in the distribution of pairwise genetic differences. Molecular Biology and Evolution 9: 552–569.
- 45. Harpending HC (1994) Signature of ancient population growth in a low resolution mitochondrial DNA mismatch distribution. Human Biology 66: 591–600.
- 46. Koshimizu E, Strüssmann CA, Tejedor ED (2009) Development of polymorphic microsatellite loci for two Atherinopsid fishes, pejerrey (Odontesthes bonariensis) and Patagonian pejerrey (O. hatcheri). Molecular Ecology Resources 9: 1460–1466.
- 47. Kalinowski ST, Taper ML, Marshall TC (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Molecular Ecology 16: 1099–1106. doi: 10.1111/j.1365-294x.2007.03089.x
- 48. Rousset F (2008) GENEPOP'007: a complete re-implementation of the GENEPOP software for Windows and Linux. Molecular Ecology Resources 8: 103–106. doi: 10.1111/j.1471-8286.2007.01931.x
- 49. Guo S, Thompson E (1992) Performing the exact test for Hardy Weinberg Proportion for multiple alleles. Biometrics 48: 361–372. doi: 10.2307/2532296
- 50. Bonferroni C (1936) Teoria statistica delle classi e calcolo delle probabilit. Publicación del R. Istit Sup Sci Econ Commerc Firenze 8: 3–62.
- 51. Weir B, Cockerham C (1984) Estimating F statistics for the analysis of population structure. Evolution 38: 1358–1370. doi: 10.2307/2408641
- 52. Goudet J (2001) FSTAT, a program to estimate and test gene diversities and fixation indices (version 2.9.3). Available from http://www2.unil.ch/popgen/softwares/fstat.htm.
- 53. van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes 4: 535–538. doi: 10.1111/j.1471-8286.2004.00684.x
- 54. Nei M, Tajima F, Tateno Y (1983) Accuracy of estimated phylogenetic trees from molecular data. II. Gene frequency data. Journal of Molecular Evolution 19: 153–170. doi: 10.1007/bf02300753
- 55. Langella O (1999) Populations 1.2.28: a population genetic software. CNRS UPR9034. http://bioinformatics.org/~tryphon/populations/ [last accessed 24.06.2010].
- 56. Pritchard J, Stephens M, Donelly P (2000) Inference of population structure using multilocus data. Genetics 155: 945–959.
- 57. Hey J, Nielsen R (2007) Integration within the Felsenstein equation for improved Markov chain Monte Carlo methods in population genetics. Proceedings of the National Academy of Sciences of the United States of America 104: 2785–2790. doi: 10.1073/pnas.0611164104
- 58. Tombari AD, Volpedo AV, Echeverria DD (2005) Desarrollo de la sagitta en juveniles y adultos de Odontesthes argentinensis (Valenciennes 1835) y O. bonariensis (Valenciennes 1835) de la provincia de Buenos Aires, Argentina (Teleostei: Atheriniformes). Revista Chilena de Historia Natural 78: 623–633. doi: 10.4067/s0716-078x2005000400003
- 59. McDade LA (1992) Hybrids and phylogenetic systematics II. The impact of hybrids on cladistic analysis. Evolution 46: 1329–1346. doi: 10.2307/2409940
- 60. Carnevia D (2008) Plan nacional de desarrollo de la acuicultura, Uruguay. 2008. Estrategia general para el desarrollo de la acuicultura sostenible en la República Oriental del Uruguay. Montevideo, DINARA – FAO. 40 p.
- 61. Tejedor D (2001) El pejerrey como recurso genético. In: Grosman F, Fundamentos biológicos, económicos y sociales para una correcta gestión del recurso pejerrey. Editorial Astyanax, Azul, Buenos Aires, Argentina.
- 62. Sprechman P (1978) The paleoecology and paleogeography of the Uruguayan coastal area during the Neogene and Quaternary. Zitteliana 4: 3–72.
- 63. Montaña JR, Bossi J (1995) Geomorfología de los humedales de la cuenca de la Laguna Merín en el departamento de Rocha. Facultad de Agronomía_UDELAR_Uruguay 2: 1–32.